Issues [Year wise]

Secret Data Embedding using Texture Synthesis
Authors : Suphiya P. Inamdar,, Suhas B. Bhagate,
Affiliations : Dept. of Computer Science and Engineering, D.K.T.E. Society’s Textile and Engineering Institute, Ichalkaranji, India.
Abstract :

af

A steganography is an art of hiding confidential data into digital media such as image, audio, video etc. The proposed the system using steganography using reversible texture synthesis. Texture synthesis uses the concept of the patch which represents an image block of source texture where its size is user specified. A texture synthesis process resamples a smaller texture image and provides a new image with arbitrary size and shape. Instead of using an existing cover image to hide messages, the algorithm conceals the source texture image and embeds secret messages using the process of texture synthesis. This allows extracting the hidden messages and source texture from a stego synthetic texture. The approach offers some advantages. First, the scheme provides the embedding capacity that is proportional to the size of the stego texture image. Second, the reversible capability inherited from this scheme includes functionality, which allows recovery of the source texture. And third, there will be no image distortion since the size of the new texture image is user-specified
Citation :

af

Suphiya P. Inamdar,Suhas B. Bhagate (2018). Secret Data Embedding using Texture Synthesis. International Journal of Computer Engineering In Research Trends, 5(7), 207-211. Retrieved from http://ijcert.org/ems/ijcert_papers/V5I703.pdf
Keywords : Steganography, Data embedding, Texture synthesis, Cover medium, Index table.
References :

af

[1]	N. Provos and P. Honeyman, ―Hide and seek: An introduction to steganography,‖ IEEE Security Privacy, vol. 1, no. 3, pp. 32–44, May/Jun. 1999.
[2]	F. A. P. Petitcolas, R. J. Anderson, and M. G. Kuhn, ―Information hiding survey,‖ Proc. IEEE, vol. 87, no. 7, pp. 1062–1078, Jul. 1999. 
[3]	A. Efros and T. K. Leung, “Texture synthesis by non-parametric sampling,” in Proc. of the Seventh IEEE International Conference on Computer Vision, 1999, pp. 1033-1038.
[4]	L.-Y. Wei and M. Levoy, “Fast texture synthesis using tree-structured vector quantization,” in Proc. of the 27th Annual Conference on Computer Graphics and Interactive Techniques, 2000, pp. 479-488.
[5]	L. Liang, C. Liu, Y.-Q. Xu, B. Guo, and H.-Y. Shum, “Real-time texture synthesis by patch-based sampling,” ACM Trans. Graph., vol. 20, no. 3, pp. 127-150, 2001.
[6]	A. Efros and W. T. Freeman, “Image quilting for texture synthesis and transfer,” in Proc. of the 28th Annual Conference on Computer Graphics and Interactive Techniques, 2001, pp. 341-346.
[7]	Renjie Chen, Ligang Liu, Guangchang Dong, ― Local resampling for patch-based texture synthesis in vector fields‖, Int. J. of Computer Applications in Technology ,2004.
[8]	Z. Ni, Y.-Q. Shi, N. Ansari, and W. Su, “Reversible data hiding,” IEEE Trans. Circuits Syst. Video Technol., vol. 16, no. 3, pp. 354-362, 2006.
[9]	H. Otori and S. Kuriyama,―Data-embeddable texture synthesis,‖ in Proc. 8th Int. Symp. Smart Graph., Kyoto, Japan, 2007, pp. 146–157. 
[10]	X. Li, B. Li, B. Yang, and T. Zeng, “General framework to histogram-shifting-based reversible data hiding,” IEEE Trans. Image Process., vol. 22, no. 6, pp. 2181-2191, 2013.
[11]	Kuo- Chen Wu and Chung-Ming Wang, “Steganography Using Reversible Texture Synthesis”, IEEE Transaction On Image Processing ,vol.24,no.1,pp.2015
:10.22362/ijcert/2018/v5/i7/v5i703
DOI Link : https://doi.org/10.22362/ijcert/2018/v5/i7/v5i703
Download :
  V5I703.pdf
Refbacks : Currently there are no refbacks
Piracy Detection of Video Contents by Signature Matching Method
Authors : Aishwarya. M. Chavan, ,
Affiliations : Dept. of Computer Science and Engineering, DKTE‘s TEI (An Autonomous Institute), Ichalkaranji, India
Abstract :

af

Security has become the primary concern to protect the critical and sensitive information such as multimedia. A problem faced by nowadays is that multimedia contents are getting pirated on a large scale. These contents need to be protected from getting duplicated. The primary goal is to detect the duplication of both 2D and 3D video contents. Essential components in identifying the piracy are the generation of unique signatures and a matching engine to match them. The system detects pirated multimedia contents.
Citation :

af

Aishwarya. M. Chavan (2018). Piracy Detection of Video Contents by Signature Matching Method. International Journal of Computer Engineering In Research Trends, 5(7), 202-206. Retrieved from http://ijcert.org/ems/ijcert_papers/V5I701.pdf
Keywords : 3D SBS, SUFR, video signatures, KD Tree.
References :

af

[1]	J. Lu. Video signatures for copy identification: From research to industry applications. In IS&T/SPIE Electronic Imaging, volume 7254 of SPIE Proceedings, pages 725402–725402. International Society for Optics and Photonics, SPIE, 2009.
[2]	S. Ioffe. Full-length video signature. Google Inc., July 24 2012. US Patent 8229219.
[3]	E. Metois, M. Shull, and J. Wolosewicz.  Detecting online abuse in images. Markmonitor Inc., Apr. 12 2011. US Patent7925044.       
[4]	J. Law-To, O. Buisson, V. Gouet-Brunet, and N. Boujemaa. Robust voting algorithm based on labels of behaviour for video copy detection. In ACM Multimedia, 2006.
[5]	W. L. Zhao, C.-W. Ngo, H.-K. Tan, and X. Wu. Near-duplicate keyframe identification with interest point matching and pattern learning. Multimedia, IEEE Trans. on, 2007.
[6]	A. Joly, O. Buisson, and C. Frelicot. Content-based copy retrieval using distortion-based probabilistic similarity search. Multimedia, IEEE Transactions on, 2007.
[7]	E. Maani, S. Tsaftaris, and A. Katsaggelos. Local feature extraction for video copy detection in a database. In ICIP, 2008.
[8]	M. Douze, H. Jegou, and C. Schmid. An image-based approach to video copy detection with spatio-temporal postfiltering. Multimedia, IEEE Transactions on, 2010.
[9]	J. Song, Y. Yang, Z. Huang, H. T. Shen, and R. Hong. Multiple feature hashing for real-time large scale near-duplicate video retrieval. In ACM Multimedia, 2011.
[10]	J. M. Barrios, B. Bustos, and X. Anguera. Combining features at search time: Prisma at video copy detection task. In Proc. TRECVID, 2011.
[11]	M. Jiang, S. Fang, Y. Tian, T. Huang, and W. Gao. Pkuidm @ trecvid 2011 cbcd: Content-based copy detection with cascade of multimodal features and temporal pyramid matching. In Proc. TRECVID, 2011.
[12]	Mohamed Hefeeda, Senior Member, IEEE, Tarek ElGamal, Kiana Calagari, and Ahmed Abdelsadek Cloud-based Multimedia Content Protection System IEEE Transactions on   Multimedia,2015.
:10.22362/ijcert/2018/v5/i7/v5i701
DOI Link : https://doi.org/10.22362/ijcert/2018/v5/i7/v5i701
Download :
  V5I701.pdf
Refbacks : Currently there are no refbacks

 

Mining Frequent Patterns Using Multiprocessor Architecture for Improving Efficiency
Authors : Ms.Priyanka D. Patil, Prof. Dinesh D. Patil ,
Affiliations : 1. PG Scholar Student 2. HOD of Computer Science and Engineering
Abstract :

af

Numerous analysts have developed plans to create the frequent item sets. The time required for producing persistent itemises plays a vital role. A few calculations are planned, concerning as it was the time factor. Our examination incorporates profundity investigation of calculations what's more, talks about a few issues of producing incessant itemsets from the calculation. We propose a productive parallel approach called Parallel Dynamic Bit Vector Frequent Closed Sequential Patterns (pDBV-FCSP) merging with Apriori and FP growth utilizing multi-core processor for mining FCSPs from huge databases. The pDBV-FCSP isolates the interest space to diminish the required storage space and performs conclusion checking of prefix groupings appropriate on time to reduce execution time for mining customary example of progressive cases. This approach conquers the issues of parallel mining, for example, overhead of correspondence, synchronization and information replication. It likewise comprehends the heap adjust issues of the workload between processors with a dynamic component that re-appropriates the work when a few procedures are out of work to limit the site without moving CPU time.
Citation :

af

Ms.Priyanka D. Patil,Prof. Dinesh D. Patil (2018). Mining Frequent Patterns Using Multiprocessor Architecture for Improving Efficiency. International Journal of Computer Engineering In Research Trends, 5(6), 192-201. Retrieved from http://ijcert.org/ems/ijcert_papers/V5I605.pdf
Keywords : data mining, dynamic bit vectors, dynamic load balancing, multi-core processors, closed sequential patterns.
References :

af

[1] R. Agrawal and R. Srikant, "Fast algorithms for mining association rules," The International Conference on Very Large Databases , pp. 487499, 1994

[2] R. Agrawal, and R. Srikant,"Mining sequential patterns," The International Conference on Data Engineering , pp. 314, 1995.

[3] R. Srikant and R. Agrawal, "Mining Sequential Patterns : Generalizations and performance improvements," Proceedings of the Fifth International Conference on Extending Database Technology,( Avignon, France, 1996), Springer-Verlag, vol. 1057, 3-17

[4] Masseglia, F., Cathala, F., and Poncelet, P., PSP: Prefix tree for sequential patterns. In Proc. of the 2nd  European Symposium on Principles of Data Mining and Knowledge Discovery PKDD98). 176184, France, LNAI, 1998.

[5] Nanopoulos, A. and Manolopoulos, Y., Mining patterns from graph traversals. Data and Knowledge Engineering, 2001

[6] Nanopoulos, A. and Manolopoulos, Y. 2000. Finding generalized path patterns for Web log data mining. Data and Knowledge Engineering, 37(3):243---266

[7] Spiliopoulou, M, The Laboriuos, Way from data mining to Web mining, Journal of Computer Systems & Engg ,Special Issue on Semantics of the Web, 14 :( 113 -126), 1999

[8] J. Pei, J. Han, B. Mortazavi-Asl, and H. Zhu. 2000. Mining access patterns efficiently from web logs. In Proceedings of the Paci_c-Asia Conference on Knowledge Discovery and Data Mining (PAKDD00). Kyoto,Japan, pp. 396-399,
400-402, 2000

[9] Tzung-Pei, Hong,Ching-Yao Wang and Shian-Shyong Tseng, "An Incremental Mining Algorithm for Maintaining Sequential Patterns  Using Pre-large Sequences," Journal Expert Systems with  Applications, Vol. 38, Issue 6,p p.7051-7058, 2011.

[10] Jen-Wei Huang, Chi-Yao Tseng, Jian-Chih Ou, Ming- Syan Chen,  "A General Model for Sequential Pattern Mining with a Progressive Database,"IEEE Transactions on Knowledge and Data Engineering,

[11] Jiaxin Liu, "The design of storage structure for a sequence in incremental sequential patterns mining," Networked Computing and  Advanced Information Management (NCM), pp. 330 - 334, 2010.

[12] Philippe Fournier,Viger,Roger Nkambou and Vincent Shin-Mu Tseng, "RuleGrowth: Mining Sequential Rules Common to Several  Sequences by Pattern-Growth, Symposium on Applied Computing,  pp . 951-960, 2011. 

[13]Pratima O. Fegade,etal,"Mining Frequent Itemsets for Improving the Effectiveness of Marketing and Sales"International Journal of Computer Science and Information Technologies, Vol. 5 (3) , 2014

[14] Margaret Rouse (March 27, 2007). "Definition: multi-core processor". TechTarget. Archived from the original on August 5, 2010. Retrieved March 6, 2013. 

[15] Bryan Schauer. "Multicore Processors - A Necessity" (PDF). Archived from the original (PDF) on 2011-11-25. 
:10.22362/ijcert/2018/v5/i6/v5i605
DOI Link : https://doi.org/10.22362/ijcert/2018/v5/i6/v5i605
Download :
  V5I605.pdf
Refbacks : Currently there are no refbacks
A Review on Cryptography Techniques using DNA Computing
Authors : Pritesh Bhimani, ,
Affiliations : Computer Engineering, Diwaliba Polytechnic
Abstract :

af

Cryptography and steganography are one of the most critical and needed areas of computer and data security. A mixer of both can make more secure the data. Cryptography is the way to secure the transfer data from sender to receiver. Steganography is a way to ensure the data by the hiding it. One new term is added with the Cryptography for making data more secure is DNA. DNA cryptography is a new hopeful way in cryptography research. DNA can be used to store and transmit the information with the more secure method and most used to perform the computation. Combination of DNA and Cryptography make sure for the security in this world. Nowadays DNA cryptography is in the development phase, and it requires lots of work, efforts and research to reach a fully developed stage. This paper describes different DNA based cryptography techniques that increase the security of cryptography techniques.
Citation :

af

Pritesh Bhimani (2018). A Review on Cryptography Techniques using DNA Computing . International Journal of Computer Engineering In Research Trends, 5(6), 187-191. Retrieved from http://ijcert.org/ems/ijcert_papers/V5I604.pdf
Keywords : DNA structure, Polymer Chain Reaction (PCR), Central Dogma of Molecular biology, DNA digital coding, DNA Cryptography, RSA, OTP, IDEA.
References :

af

[1]	M Borda, T. Olga, DNA Secret Writing Techniques, Communications (COMM), 2010 8th International Conference. Pp. 451-456, IEEE 2010. 
[2]	C. Guangzhao, Q. Limin, W. Yanfeng, Z. Xuncai, An Encryption Scheme Using DNA Technology , Bio-Inspired Computing: Theories and Applications, 2008. BICTA 2008. 3rd International Conference. Pp. 37-42, IEEE-2008. 
[3]	Crick Francis, "Molecular Structure of Nucleic acid: A Structure of Deoxyribose Nucleic Acid", April 25, 1953. Nature 171(April 25,1953): 737-738
[4]	Dhawan Sanjeev, Saini Alisha, Secure Data Transmission Techniques Based on DNA Cryptography, International Journal of Emerging Technologies in Computational and Applied Sciences, 2012.
[5]	Wang Xing, Zhang Qiang, DNA computing-based cryptography", Bio-Inspired Computing, 2009. BIC-TA '09. Fourth International Conference. PP. 1-3, IEEE 2009
[6]	P. Rakheja, Integrating DNA Computing in International Data Encryption Algorithm (IDEA), International Journal of Computer Applications, 2011, Volume 26  no.-3, July 2011.
:10.22362/ijcert/2018/v5/i6/v5i604
DOI Link : https://doi.org/10.22362/ijcert/2018/v5/i6/v5i604
Download :
  V5I604.pdf
Refbacks : Currently there are no refbacks
Inventory Management Techniques: Optimizing Plant Operation in a Manufacturing Industry
Authors : Shivaji Sagar, ,
Affiliations : Mechanical & Automation Engineering Department, Amity School of Engineering & Technology, Amity University, Mumbai, India
Abstract :

af

The main objective of this paper was to study the inventory management techniques and analyze the pros and cons of the existing technique and if needed, suggest a better-suited technique. The paper also sketches a background on the various costs involved and general inventory management techniques followed. The study uses a descriptive research design. The area of the study was a mechanical industry which produces valves, located in Chennai which is located in the Ambattur Industrial Estate. The inputs from the respondents were collected using a questionnaire and an interview guide. Secondary information was collected from different sources like; textbooks, internet, newspapers, magazines, and journals. The researchers obtained information from the staff and some clients who order directly from its premises. The sample size consisted of 50 respondents. The gender and age compositions of the respondents were established to eliminate any bias, in case of any. The results from the questionnaires and personal interviews were tabulated and analyzed and a relationship between the inventory management technique employed and performance was established based on the opinions of the respondents. A majority of the respondents agreed to positive relationship between the technique and performance of the company. A few respondents indicated inventory management as having a negative relationship on the performance. These same respondents believed that, inventory management involves a lot of costs, inconsistency as there is overcharging of customers, use of highly skilled workers in charge of managing inventories, theft, obsolescence among others all of which increase on the costs hence reducing much of the on the performance of the organization in question especially in the production department.
Citation :

af

Shivaji Sagar(2018). Inventory Management Techniques: Optimizing Plant Operation in a Manufacturing Industry. International Journal of Computer Engineering In Research Trends, 5(6), 167-175. Retrieved from http://ijcert.org/ems/ijcert_papers/V5I602.pdf
Keywords : Inventory Management, EOQ, Management, Optimization, Plant Operation
References :

af

[1]. Alvesson, M. (2001); The Structuring of Organizations: Prentice-Hall, Englewood Cliffs, N.J.
[2]. Leenders/ Fearon (1997); Purchasing and Supply Management 11th Edition.
[3]. Malcom Saundrers (2005); Strategic purchasing and supply chain management 2nd edition, Pittman Publishing, 128, Long Acre London.
[4]. Gary J. Zenz (1997); Purchasing and the Management of Materials Florida State University, 7th edition, simultaneously, Canada, USA.
[5]. Ronald H. Ballow (1997); Business Logistics Management International Edition, Prentice Hall International  Inc., USA.
[6]. Michael, E. Porter, (1994); Competitive Advantages of Nations, Mc Millan.
[7]. Peter, D. (1983); The Practice Management Heinemann, Professional Publication.
[8]. Peter J. And Waterman. R. (1988); In Search of Excellence; Lessons from American Best-Run Companies,Harper andRow. 
[9]. Hellen C. (1993); Human Resources Management Personnel Policies and Procedures.
[10]. Lau A., &Snell R. (2006); Structure and Growth in Small Hong Kong Enterprises. International Journal of Entrepreneurial Behaviour& Research, 2 (3), 29-47.
[11]. Lei, D, Slocum, J.W., &Pitts, R.A. (1999); Designing Organizations for Competitive Advantage: The Power of unlearning and Learning. Organizational Dynamics, winter, 24-38.
[12]. Likert R. (2003); The New Patterns of Management: Mc Graw-Hill, New York.
[13]. Colvin, J. G &Slevin, D.P (2007); The Structures in Fives: Designing Effective Organizations, Prentice-Hall, Englewood Cliffs, N.J.
[14]. Halachmi, A., & Bouckart G. (2005); Performance Measurement, Organizational Technology and Organizational Technology and Organizational Design. Work Study, 43 (3), 19-25.
[15]. Dervitsiotis KN 1981. Operations Management. USA: Mcgraw-Hill Series in Industrial Engineering and Management Science.
[16]. Drury C 1996. Management and Cost Accounting. London: International Housan Business Press.
[17]. Keth L, A Muhlemen, J Oakland 1994. Production and Operations Management. London: Pitman Publisher. 
[18]. Kotler P 2002: Marketing Management. 2nd Edition. The Millennium Edition. New Delhi: Prentice Hall Of India
[19]. Lucey T 199: Quantitative Techniques. 4th Edition. London: Ashford Colour Press. 
[20]. Lucey T 1996. Costing. 5th Edition. London: Ashford Colour Press.
[21]. Monks JG 1996: Operations Management. 
[22]. Schaum’s Outline of Theory and Problems. 2nd Edition. USA: McGrawHill Companies Inc. 
[23]. Morris C 1995. Quantitative Approach in Business Studies: London: Pitman Publisher. 
[24]. Rosenblatt BS 1977. Modern Business- A Systems Approach. 2nd Edition, Boston:  Houghton Mifflin Co.
[25]. Schroeder RG 2000. Operations Management- Contemporary Concepts and Cases. USA: International Edition. 
[26]. Thomas CK, Kenneth LB 1990. Principles of Marketing. 3rd Edition, USA: Scott Foresman And Co
:10.22362/ijcert/2018/v5/i6/v5i602
DOI Link : https://doi.org/10.22362/ijcert/2018/v5/i6/v5i602
Download :
  V5I602.pdf
Refbacks : Currently there are no refbacks
Enhancement of Cloud Workflow Scheduling Algorithm on Workflow Scheduling for Cloud
Authors : Ms.Ashvini L.Khandekar, Prof. Dinesh D. Patil, Prof. Aniket D. Pathak
Affiliations : 1PG Scholar Student, Shri Sant Gadge Baba College of Engineering & Technology, Bhusawal, Maharashtra. 2Prof. Dinesh D. Patil. Associate Professor & HOD of Computer Science and Engineering, Shri Sant Gadge Baba College of Engineering & Technology, Bhusawal, Maharashtra. 3 Prof. Aniket D. Pathak. Assistant Professor, Shri Sant Gadge Baba College of Engineering & Technology, Bhusawal, Maharashtra.
Abstract :

af

The distributed computing is an Internet-based registering to rise as another engineering which means to give stable, adaptable and QoS ensured dynamic condition for end-clients. As multi-occupancy is one of the key highlights of distributed computing where specialist organizations and clients have versatile and financial advantages for same cloud stages. In distributed computing condition the execution procedure requires asset administration because of the preparing ability is high to the asset proportion. The point of the framework is to deal with asset administration by executing logical workflows. The Assignment of errands is finished by the Cloud-based Workflow Scheduling Algorithm (CWSA). The booking calculation enhances the execution of Traditional workflows and aides in minimisation of workflow consummation time, lateness, execution cost and utilization of sitting out of gear assets of cloud utilizing test system Workflow sim.
Citation :

af

Ms.Ashvini L.Khandekar, Prof. Dinesh D. Patil, Prof. Aniket D. Pathak (2018). Enhancement of Cloud Workflow Scheduling Algorithm on Workflow Scheduling for Cloud. International Journal of Computer Engineering In Research Trends, 5(6), 155-166. Retrieved from http://ijcert.org/ems/ijcert_papers/V5I601.pdf
Keywords : Cloud computing, direct acyclic graph, multi-tenancy, resource management, scientific workflow applications.
References :

af

[1] J. Yu and R. Buyya, " A Taxonomy of Workflow Management Systems for Grid Computing," Journal of Grid Computing, Springer, pp. 171-200, 2005
[2] Yash P. Dave,Avani S. Shelat,Dhara S. Patel ”Various Job Scheduling Algorithms in Cloud Computing: A Survey” S.A.Engineering College,2014
[3] FairouzFakhfakh ,HatemHadjKacem, Ahmed HadjKacem ”Workflow Scheduling in Cloud Computing: A survey” IEEE 18th International Enterprise Distributed Object Computing Conference Workshops and Demonstration,2014
[4] F. S. Hsieh and J. B. Lin, “A dynamic scheme for scheduling complex tasks in manufacturing systems based on collaboration of agents,” Applied Intelligence, vol. 41, no. 2, pp. 366–382, 2014.
[5] H. Topcuoglu, S. Hariri, and M. Y. Wu, “Performance-effective and low-complexity task scheduling for heterogeneous computing,” IEEE Trans. Parallel and Distributed.Sys.,vol. 13, no. 3, pp. 260–274, 2002.
[6] A. R adulescu and A. J. C. van Gemund, “On the complexity of list scheduling algorithms for distributed-memory systems,” in Proc., ACM Supercomputer. June 1999, pp. 68–75.
[7] H. M. Fard, R. Prodan, J. J. D. Barrionuevo, and T. Fahringer, “A multi-objective approach for workflow scheduling in heterogeneous environments,” in Proc., IEEE/ACM CCGrid, pp. 300–309,2012.
[8] S. Darbha and D. P. Agrawal, “Optimal scheduling algorithm for distributed-memory machines,” IEEE Trans. Parallel Distributed.System., vol. 9, no. 1, pp. 87–95, 1998
[9] R. Bajaj and D. P. Agrawal, “Improving scheduling of tasks in a heterogeneous environment,” IEEE Trans. Parallel and Distrib.Sys., vol. 15, no. 2, pp. 107–118, 2004.
[10] A. Gerasoulis and T. Yang, “A comparison of clustering heuristics for scheduling directed acyclic graphs on multiprocessors,” J. Parallel and Distrib.Comput., vol. 16, no. 4, pp. 276 – 291,1992.
[11] J.-C. Liou and M. A. Palis, “An efficient task clustering heuristic for scheduling DAGs on multiprocessors,” in Proc., Resource Man-agement, Symp.of Parallel and Distrib. Processing, pp. 152–156,1996.
[12] K. Bessai, S. Youcef, A. Oulamara, C. Godart, and S. Nurcan, “Bi-criteria workflow tasks allocation and scheduling in cloud computing environments,” in Proc., IEEE CLOUD, 2012, pp. 638–64,2012
[13] T. He, S. Chen, H. Kim, L. Tong, and K.-W. Lee, “Scheduling parallel tasks onto opportunistically available cloud resources,” in Proc., IEEE CLOUD,pp. 180–187,2012.
[14] Z. Xiao, W. Song, and Q. Chen, “Dynamic resource allocation using virtual machines for cloud computing environment,” IEEE Trans. Parallel and Distrib. Sys., vol. 24, no. 6, pp. 1107–1117, 2013.
[15] S. T. Maguluri, R. Srikant, and L. Ying, “Stochastic models of load balancing and scheduling in cloud computing clusters,” in Proc., IEEE INFOCOM,pp. 702–710,2012,.
[16] T. R. Browning and A. A. Yassine, “Resource-constrained multi-project scheduling: Priority rule performance revisited,” Int. Journal of Production Economics, vol. 126, no. 2, pp. 212–228, 2010.
[17] D. Shue, M. J. Freedman, and A. Shaikh, “Performance isolation and fairness for multi-tenant cloud storage,” in Proc., USENIX OSDI, pp. 349–362,2012
[18] S. Pandey, L. Wu, S. Guru, and R. Buyya, “A particle swarm optimization-based heuristic for scheduling workflow applications in cloud computing environments,” in Proc., IEEE Advanced Information Networking and Applications, pp. 400–407,2010
[19] M. A. Rodriguez and R. Buyya, “Deadline based resource pro-visioning and scheduling algorithm for scientific workflows on clouds,” IEEE Trans. Cloud Comput., vol. 2, no. 2, pp. 222–235, 2014
[20 ] Z. Wu, X. Liu, Z. Ni, D. Yuan, and Y. Yang, “A market-oriented hierarchical scheduling strategy in cloud workflow systems,” J. Supercomputing, vol. 63, no. 1, pp. 256–293, 2013.
[21] H. M. Fard, R. Prodan, and T. Fahringer, “A truthful dynamic workflow scheduling mechanism for commercial multicloud environments,” IEEE Trans Parallel and Distrib.Syst., vol. 24, no. 6, pp. 1203–1212, 2013.
[22] J. Yu, R. Buyya, and K. Ramamohanarao, “Workflow scheduling algorithms for grid computing,” in Metaheuristics for Scheduling in Distrib.Comput. Environments, vol. 146, pp. 173–214,2008
[23] G. Juve, E. Deelman, K. Vahi, G. Mehta, B. Berriman, B. Berman, and P. Maechling, “Scientific workflow applications on amazon ec2,” in Proc., IEEE E-Science Wksp,pp. 59–66, 2009
[24] J. Jin, J. Luo, A. Song, F. Dong, and R. Xiong, “Bar: An efficient data locality driven task scheduling algorithm for cloud computing,” in Proc., IEEE/ACM CCGrid, pp. 295–304,2011
[25] D. Yuan, Y. Yang, X. Liu, and J. Chen, “A data placement strategy in scientific cloud workflows,” Future Gener. Comput.Syst., vol. 26, no. 8, pp. 1200–1214, 2010.
[26] Q. Zhu and G. Agrawal, “Resource provisioning with budget constraints for adaptive applications in cloud environments,” IEEE Trans. Services Comput., vol. 5, no. 4, pp. 497–511, 2012
[27] W. Tsai, X. Sun, Q. Shao, and G. Qi, “Two-tier multi-tenancy scaling and load balancing,” in Proc., IEEE ICEBE, Nov. 2010, pp. 484–489.
[28] Q. Zhu and G. Agrawal, “Resource provisioning with budget constraints for adaptive applications in cloud environments,” IEEE Trans. Services Comput., vol. 5, no. 4, pp. 497–511, 2012
[29] Z. Wu, X. Liu, Z. Ni, D. Yuan, and Y. Yang, “A market-orientedhierarchical scheduling strategy in cloud workflow systems,” J.Supercomputing, vol. 63, no. 1, pp. 256–293, 2013.
[30] L. Ramakrishnan, C. Koelbel, Y. sukKee, R. Wolski, D. Nurmi,D. Gannon, G. Obertelli, A. YarKhan, A. Mandal, T. Huang,K. Thyagaraja, and D. Zagorodnov, “Vgrads: enabling e-scienceworkflows on grids and clouds with fault tolerance,” in Proc.,IEEE High Performance Comput. Networking, Storage and Analysis, pp. 1–12,2012.
[31] K. Plankensteiner and R. Prodan, “Meeting soft deadlines in sci-entific workflows using resubmission impact,” IEEE Trans. ParallelandDistrib. Sys., vol. 23, no. 5, pp. 890–901, May 2012.
[32] S. Abrishami, M. Naghibzadeh, and D. H. J. Epema, “Deadline-constrained workflow scheduling algorithms for infrastructure asa service clouds,” Future Gener. Comput.Syst., vol. 29, no. 1, pp.
158–169, Jan. 2013.
[33] E. Deelman, J. Blythe, Y. Gil, C. Kesselman, G. Mehta, K. VahK. Blackburn, A. Lazzarini, A. Arbree, R. Cavanaugh, and S. Koranda, “Mapping abstract complex workflows onto grid environments,” J. Grid Comput., vol. 1, no. 1, pp. 25–39, 2003.
[34]Ms. Ashvini L. Khandekar et.al,”Implementation of Cost Optimization Approaches for Workflow Scheduling in Distributed Data Mining Architecture”,IJCEA, Volume XII, Issue II, 2018
[35] Bhaskar Prasad Rimal,” Workflow Scheduling in Multi-Tenant Cloud Computing Environments”, IEEE TRANSACTIONS,2016
:10.22362/ijcert/2018/v5/i6/v5i601
DOI Link : https://doi.org/10.22362/ijcert/2018/v5/i6/v5i601
Download :
  V5I601.pdf
Refbacks : Currently there are no refbacks
A Study on Current Frauds Trends in the Indian Banking Industry and Its Detection Using Data Mining Algorithms
Authors : Mandeep Kaur , ,
Affiliations : Department of Computer Engineering,Modern Group of Colleges.
Abstract :

af

In the globalized and changed business state of the latest couple of years, we confront an unquestionably growing volume of frauds especially in the financial fragments in India. The Indian cash related organizations division has seen exponential advancement in the latest decadean improvement that has not been without its snares, as events of distortion have moreover been on the rising. Extortion achieves colossal incidents to the overall public exchequer, as needs are negatively impacting organization transport. Budgetary extortion is a considerable business, adding to a normal 20 billion USD in organize mishaps yearly. Industry authorities assume that this figure is actually extensively higher, as firms can't unequivocally recognize and measure incidents on account of distortion. The most exceedingly horrendous effect of budgetary frauds is on FDI inflows into India. Changes in advancement, cheats have taken shape and modalities of dealing with bad behaviour, passing on logically current procedures for execution. As money related exchanges turn out to be progressively innovation-driven, they appear to have turned into the weapon of decision with regards to fraudsters. In this paper, we share our point of view on the patterns in frauds in the money related part, the changing administrative scene and the courses for misrepresentation aversion and control. This paper thus tends to current misrepresentation inclines in cash pertaining area and instrument of cheats recognition through the localisation of information mining endless supply of the examples; including a more massive amount of check/verification to managing an account procedure can be included.
Citation :

af

Mandeep Kaur (2018). A Study on Current Frauds Trends in the Indian Banking Industry and Its Detection Using Data Mining Algorithms. International Journal of Computer Engineering In Research Trends, 5(6), 177-186. Retrieved from http://ijcert.org/ems/ijcert_papers/V5I603.pdf
Keywords : Financial Frauds, Technology, data mining.
References :

af

[1].Carney, M. (2014), Inclusive Capitalism: creating a sense of the systemic, Speech given by Mark Carney, Governor of the Bank of England at the Conference on Inclusive Capitalism, London 27 May 2014.

[2].CBI (2014), Corporate Frauds-Risk & Prevention under Changing Paradigm, address by Ranjit Sinha, Director, Central Bureau of Investigation on May 13, 2014.

[3].Chakrabarty, K.C (2013), Frauds in the banking sector: Causes, Cures and Concerns, Inaugural address by Dr. K. C. Chakrabarty , Deputy Governor, Reserve Bank of India on July 26, 2013 during the National Conference on Financial Fraud organized by ASSOCHAM at New Delhi.

[4].Deloitte (2014), India Fraud Survey, Edition 1.

[5].Deloitte (2015), Deloitte India Banking Fraud Survey.

[6].Gandhi, R. (2014), Growing NPAs in Banks: Efficacy of Ratings Accountability & Transparency of Credit Rating Agencies, Conference conducted by ASSOCHAM on May 31, 2014.

[7].Gandhi, R. (2015), Financial Frauds-Prevention: A Question of Knowing Somebody, 2nd National Conference on Financial Frauds Risks & Preventions organized by ASSOCHAM on June 26, 2015 at New Delhi.

[8].IMF (2014), Financial Sector Assessment Program Review: Further adaptation to the postcrisisera, IMF Policy Papers.

[9].IMF (2014), IMF Response to the Financial and Economic crisis, Independent Evaluation Office, IMF.

[10].Kohler, H. (2002), Working for a better globalization, Remarks by Horst Kohler at the Conference on Humanizing the Global Economy Laeven, L. and Valencia, F. (2012), Systemic Banking Crises Database: An Update, IMFWorking Paper No. 12/163.

[11] Hand Tracking in HCI Framework Intended  For Wireless Interface IJCERT VOL2 2015
:10.22362/ijcert/2018/v5/i6/v5i603
DOI Link : https://doi.org/10.22362/ijcert/2018/v5/i6/v5i603
Download :
  V5I603.pdf
Refbacks : Currently there are no ref backs

 

Consistency as Indicator of Usability for Social Softwares
Authors : Nelson Bogomba Masese, Simon Maina Karume ,
Affiliations : * Department of Computer Science, Kabarak University, Kenya, Department of Information Technology, Kibabii University, Kenya 2 Department of Computer Science, Laikipia University, Kenya email: mcanelson @gmail.com
Abstract :

af

Background/ Objectives: Consistency is recognition of the fact that it is easier to do things in a familiar context. Consistency makes software applications more comfortable to use the objective of the paper is to evaluate software consistency as an indicator of usability for social software's. Methods/Statistical analysis: A sample of 345 respondents was selected. The data was collected through the use of questionnaires and interview targeting mobile social users in 11 constituencies of former Rift valley province of Kenya. The researcher purposively sampled WhatsApp, Facebook and Twitter as softwares used in this study. Descriptive statistics were used to analyze the data. Findings: This finding indicated that that 30.1% of the respondents agreed that the interface is consistent in the whole application in Facebook, followed by 15.4% in WhatsApp while 4.3% agreed in Twitter. Regarding whether icons and images are consistent in the whole application, it was reported by 36.8% of the respondents to be consistent in WhatsApp while Facebook users confirmed 16.5% while Twitter users were 6.7%. The findings further indicate that the social software becomes more consistent its usability increases, the consistency of shortcut keys with the operations, consistency of color, type and fonts displays influence usability of the social software. The paper has provided insights that consistency is vital, software designers should consider it in the software development process. Improvements: there is need to conduct further studies on other social software to confirm if these results are in line with all social software.
Citation :

af

Nelson Bogomba Masese, Simon Maina Karume (2018). Consistency as Indicator of Usability for Social Softwares. International Journal of Computer Engineering In Research Trends, 5(5), 148-154. Retrieved from http://ijcert.org/ems/ijcert_papers/V5I503.pdf
Keywords : Consistency, Usability, Social Software
References :

af

[1] Tovi Grossman, George Fitzmaurice, Ramtin Attar (2009). A Survey of Software Learnability: Metrics, Methodologies and Guidelines,CHI 2009 2009 Boston, MA, USA conference  university. Issues in Science and Technology, 22(1),pp 113.
[2] Auden, W. H. (2013). Menu Selection, Form Fill-In, and Dialog Boxes. Designing the User Interface: 
Pearson New International Edition: Strategies for Effective Human-Computer Interaction, pp223.
[3] Savery, C. (2014).Consistency maintenance in networked games (Doctoral dissertation).pp-60-62
[4] Tidwell, J. (2010).Designing Interfaces: Patterns for effective interaction design. "O'Reilly Media, Inc.".pp-50-54
[5] Goecks, J., Nekrutenko, A., & Taylor, J. (2010). Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences.Genome biology,11(8), pp 86.
[6] Swartout, B., Patil, R., Knight, K., & Russ, T. (1996, November). Toward distributed use of large-scale ontologies. In Proc. of the Tenth Workshop on Knowledge Acquisition for Knowledge-Based Systems (pp. 138-148). 
[7] Matejka, J., Grossman, T., & Fitzmaurice, G. (2013, April). Patina: Dynamic heatmaps for visualizing application usage. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems ACM  (pp. 3227-3236). 
[8] Hashim, A. S., Ahmad, W. F. W., Nordin, S. M., & Jaafar, A. (2014). Usability study of free schools system for secondary schools in Malaysia. rIn User Science and Engineering (i-USEr), 2014 3rd International Conference on IEEE (pp. 198-203).
[9] Bollini, L. (2017). Beautiful interfaces. From user experience to user interface design. The Design Journal, 20(sup1), pp 89-S101.
[10] Bevan, N., Carter, J., & Harker, S. (2015,). ISO 9241-11 revised: What have we learnt about usability since 1998?. In International Conference on Human-Computer Interaction(pp. 143-151). 
[11] Nielsen, J. (1999). Designing web usability: The practice of simplicity. New Riders Publishing. 
[12] Issa, T., & Isaias, P. (2015). Usability and Human-Computer Interaction (HCI). In Sustainable Design  Springer, London (pp. 19-36)..
[13] Gu, X., Gu, F., & Laffey, J. M. (2011). Designing a mobile system for lifelong learning on the move. Journal of Computer Assisted Learning, 27(3), pp204-215.
[14] Buxton, B. (2010).Sketching user experiences: getting the design right and the right design. Morgan Kaufmann publication.pp 89-90
[15] Shneiderman, B. (2010). Designing the user interface: strategies for effective human-computer interaction. Pearson Education India  pp 100-102.
[16] Kelders, S. M., Pots, W. T., Oskam, M. J., Bohlmeijer, E. T., & van Gemert-Pijnen, J. E. (2013). Development of a web-based intervention for the indicated prevention of depression. BMC medical informatics and decision making,13(1),pp 26.
[17] Johnson, J. (2013).Designing with the mind in mind: simple guide to understanding user interface design guidelines. Elsevier.pp-45
[18] Abuali, A. N., & Abu-Addose, H. Y. (2011). A Comparative Study Of Techniques Used For Evaluating Web Page Quality Of The Public Organizations In Jordan - Amman.  International Journal Of Academic Research,3(2).pp 56
[19] Wilson, C. (2013).User interface inspection methods: a user-centered design method. Newnes.pp 80-84
[20] Fu, K. K., Yang, M. C., & Wood, K. L. (2015). Design principles: The foundation of design. In ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference (pp. V007T06A034-V007T06A034). American Society of Mechanical Engineers pp 77 -80
[21] Gartenberg, D., Thornton, R., Masood, M., Pfannenstiel, D., Taylor, D., & Parasuraman, R. (2013). Collecting health-related data on the smartphone: mental models, cost of collection, and perceived benefit of feedback. Personal and ubiquitous computing,17(3), 561-570.
[22] Shafiq, M., Ahmad, M., & Choi, J. G. (2017). Public System Usability Analysis for the Valuation of Cognitive Burden and Interface Standardization: A Case Study of Cross-ATM Design.Journal of Organizational Computing and Electronic Commerce pp 54-67
[23] O'Neil Jr, H. F., Ni, Y., Jacoby, A., & Swigger, K. M. (2013). Human  benchmarking for the evaluation of expert systems. Technology Assessment in Software Applications, pp13.
[24] Ritter, F. E., Baxter, G. D., & Churchill, E. F. (2014). Methodology III: Empirical Evaluation. In Foundations for Designing User-Centered Systems Springer, London.
 (pp. 353-380). 
[25] Klckner, A., Pinto, N.,  Lee, Y., Catanzaro, B., Ivanov, P., & Fasih, A. (2012). PyCUDA and PyOpenCL: A scripting-based approach to GPU run-time code generation. Parallel Computing, 38(3),  pp 157-174.
[26] Beatty, K. (2013). Teaching & Researching: Computer-assisted language learning. Routledge  pp 124-129.
[27] Jalon, J., Robert, J., & Paterson, T. (2012). U.S. Patent No. 8,185,839. Washington, DC: U.S. Patent and Trademark Office pp 67-78
[28] Shneiderman, B. (2010). Designing the user interface: strategies for effective human-computer interaction. Pearson Education India.
[29] Sandip Sharad Shirgave, Prof. S. V. Pingale, Prof. A. A. Rajguru, Prof. N. M. Sawant," Access Control Methodology for Online Social Network" International Journal Of Computer Engineering In Research Trends Volume 2, Issue 5, May 2015, PP 293-295 , ISSN (Online):  pp 2349-7084
[30] Neil, T. (2014).Mobile design pattern gallery: UI patterns for smartphone apps. " O'Reilly Media, Inc."pp 45-49
[31] Krejcie, R.V., & Morgan, D.W.(1970). Determining Sample Size for Research Activities. Educational and Psychological Measurement, 30, pp 607-610
[32] Masese  Nelson, Samwuel Mbugua,  Geoffrey Muchiri (2016). Research data for PhD thesis.
:10.22362/ijcert/2018/v5/i5/v5i503
DOI Link : https://doi.org/10.22362/ijcert/2018/v5/i5/v5i503
Download :
  V5I503.pdf
Refbacks : Currently there are no refbacks
Experimental Study of the Effects of Machining Parameters on the Surface Roughness in the Turning Process
Authors : Vikas B. Magdum , Dr. Vinayak R. Naik ,
Affiliations : 1* Assistant Professor, Department of Mechanical Engineering, D. K. T. E. Society’s Textile and Engineering Institute, Ichalkaranji, Maharashtra, India, 416115 2 Professor and Head, Department of Mechanical Engineering, D. K. T. E. Society’s Textile and Engineering Institute, Ichalkaranji, Maharashtra, India, 416115
Abstract :

af

In this work, experiments are carried out to study the effect of cutting parameters cutting speed, feed rate, and depth of cut on surface roughness during dry turning of 40C8. The objective of this study is to build multiple regression models for a better understanding of the effects of spindle speed, feed and depth of cut on the surface roughness. Full factorial design of experiments corresponding to trials was followed for the experimental design. Analysis of variance determines the contribution of each factor on the output. It is found that feed rate is the most influencing parameter affecting the surface roughness (44.13%) and is followed by cutting speed and depth of cut. The developed predicted model, which includes the effect of spindle speed, feed rate an extent h decrease t and any two-variable interactions, gives an accuracy of about 91.91 %. This study is helpful for understanding and controlling effect of cutting parameters on the surface finish of machined surfaces in dry turning operation.
Citation :

af

Vikas B. Magdum , Dr. Vinayak R. Naik (2018). Experimental Study of the Effects of Machining Parameters on the Surface Roughness in the Turning Process. International Journal of Computer Engineering In Research Trends, 5(5), 141-147. Retrieved from http://ijcert.org/ems/ijcert_papers/V5I502.pdf
Keywords : Surface Finish; ANOVA; Regression, Surface Roughness; Turning, SN ratio.
References :

af

[1] C. Natarajan, S. Muthu and P. KaruPPuswamy, “Investigation of cutting parameters of surface roughness for a non-ferrous material using the artificial neural network in CNC turning”, Journal of Mechanical Engineering Research, ISSN 2141 – 2383 ©2011 Academic Journals, Vol. 3(1), PP. 1-14, January 2011.
[2] Ilhan asilturk, Harun Akkus, “Determining the effect of cutting parameters on surface roughness in hard turning using the Taguchi method”, Measurement, Elsevier Ltd, PP 1-8, 2011.
[3] Jithin babu.r, a Ramesh Babu, “Correlation among the cutting parameters, surface roughness and cutting forces in turning process by experimental studies”, 5th International & 26th All India Manufacturing Technology, Design and Research Conference (AIMTDR 2014), IIT Guwahati, Assam, India, PP 459.1-459.6, December 12th –14th , 2014.
[4] Ilhan Asilturk, “On-line surface roughness recognition system by vibration monitoring in CNC turning using adaptive neuro-fuzzy inference system (ANFIS)”, International Journal of the Physical Sciences, ISSN 1992 - 1950 ©2011 Academic Journals Vol. 6(22), 2011, PP. 5353-5360, 2 October.
[5] K. Adarsh Kumar, Ch. Ratnam, BSN Murthy, B. Satish Ben, K. Raghu Ram Mohan Reddy, “Optimization of surface roughness in face turning operation in machining of EN-8”, International Journal of Engineering Science & Advanced Technology, ISSN: 2250–3676, Volume-2, Issue-4, PP 807 – 812, July-Aug 2012.
[6] Suleyman Neseli, Suleyman Yaldız, Erol Turkes, “Optimization of tool geometry parameters for turning operations based on the response surface methodology”, Measurement, Elsevier, 44,  PP 580–587, 2011.
[7] H. M. Somashekara, Dr. N. Lakshmana Swamy, “Optimizing surface roughness in turning operation using Taguchi technique and ANOVA”, International Journal of Engineering Science and Technology (IJEST), ISSN: 0975-5462, Vol. 4, No.05, PP 1967-1973, May 2012.
[8] Jignesh G. Parmar, Prof. Alpesh Makwana, “Prediction of surface roughness for end milling process using Artificial Neural Network”, International Journal of Modern Engineering Research (IJMER), ISSN: 2249-6645, Vol.2, Issue.3, PP-1006-1013, May-June 2012. 
[9] M.F.F. Ab. Rashid and M.R. Abdul Lani, “Surface Roughness Prediction for CNC Milling Process using Artificial Neural Network”, Proceedings of the World Congress on Engineering 2010 Vol III, WCE 2010, London, U.K., PP 1-6, June 30 - July 2, 2010.
[10] M. Nalbant, H. Gokkaya, G. Sur, “Application of Taguchi method in the optimization of cutting parameters for surface roughness in turning”, Materials and Design, Elsevier, 28, PP 1379–1385, 2007.
[11] G. Akhyar, C. H. Che Haron, J. A. Ghani, “Application of Taguchi method in the optimization of tuning parameters for surface roughness”, International Journal of Science Engineering and Technology, ISSN: 1985-3785, Vol. 1, No. 3, PP 60-66, 2008.
[12] Dr. S. S. Mahapatra, Amar Patnaik, Prabina Ku. Patnaik, “Parametric Analysis and Optimization of Cutting Parameters for Turning Operations based on Taguchi Method”, Proceedings of the International Conference on Global Manufacturing and Innovation, PP 1-9, July 27-29, 2006. 
:10.22362/ijcert/2018/v5/i5/v5i502
DOI Link : https://doi.org/10.22362/ijcert/2018/v5/i5/v5i502
Download :
  V5I502.pdf
Refbacks : Currently there are no refbacks
Finite Element Analysis of Helical Gear Pair for Bending and Contact Stresses
Authors : Vishal Singh, ,
Affiliations : Mechanical Engineering Department, MMMUT Gorakhpur (INDIA)
Abstract :

af

In gear design, excessive tooth contact stresses and bending stresses are one of the prime gear failure factors; therefore, its analysis is critical to shortening the possibility of gear tooth failure. In the present work, the tooth bending stresses and contact stresses in a helical gear pair is calculated using AGMA theory and finite element analysis (FEA). The modelling of the helical gear pair is carried out in CREO and ANSYS is used for FEA. It is observed that the bending stresses and contact stresses, both decreases with an increase in the helix angle if pressure angle remains constant. However, the error in the calculation by AGMA and FEA is higher for the bending stresses than the contact stresses and bending stresses.
Citation :

af

Vishal Singh (2018). Finite Element Analysis of Contact and Bending Stresses in Helical Gear Pair. International Journal of Computer Engineering In Research Trends, 5(5), 600-604. Retrieved from http://ijcert.org/ems/ijcert_papers/V5I501.pdf
Keywords : Helical gear pair, bending stresses, Contact stresses
References :

af

[1] 	S. S. Rattan, Theory of Machines, 4th ed., New Delhi: McGraw Hill Education (India) Pvt. Ltd., 2015. 
[2] 	V. B. Bhandari, Design of Machine Element, 3, Ed., 2013. 
[3] 	R. G. Budynas and J. K. Nisbett, Shigley Mechanical Engineering Design, McGraw-Hill, 2011.
[4] 	N. Ganeshan and S. Vijayarangan, "A Static Analysis Of Composite Helical Gear Using A Three-Dimensional Finite Element Method," Elsevier Science Ltd., vol. 49, pp. 253-268, 1993. 
[5] 	P. B. Pawar and A. A. Utpat, "Development of Aluminium Based Silicon Carbide Particulate Metal Matrix Composite for Spur Gear," Procedia Materials Science, vol. 6, pp. 1150-1156, 2014. 
[6] 	J. Venkatesh and P. B. G. S. N. Murthy, "Design and Structural Analysis of High Speed Helical Gear Using," International Journal of Engineering Research and Applications, vol. 4, no. 3, pp. 01-05, 2014. 
[7] 	S. Jyothirmaia, R. Ramesh, T. Swarnalathac and D. Renuka, "A Finite Element Approach to Bending, Contact and Fatigue Stress Distribution in Helical Gear Systems," International Conference on Materials Processing and Characterisation, p. 907 – 918, 2014. 
[8] 	S.-C. Hwang, J.-H. Lee, D.-H. Lee, S.-H. Han and K.-H. Lee, "Contact stress analysis for a pair of mating gears," Mathematical and Computer Modelling, p. 40–49, 2013. 
[9] 	S. S. Patil, S. Karuppanan, I. Atanasovska and A. A. Wahab, "Contact Stress Analysis of Helical Gear Pairs, Including," International Journal of Mechanical Sciences, 2014. 
[10] 	P. R. P. M. M. S.Sai Anusha, "Contact Stress Analysis of Helical Gear by Using AGMA and ANSYS," International Journal of Science Engineering and Advanced Technology, vol. 2, no. 12, pp. 1012-1016, 2014. 
[11] 	M. G. Khosroshahi and A. M. Fattahi, "Three Dimensional Stress Analysis of a Helical Gear Drive with Finite Element Method," MECHANIKA, vol. 23, no. 5, pp. 630-638, 2017. 
[12] 	R. Devraj, "Contact Stress Analysis of a Helical Gear," Applied Mechanics and Materials, Vols. Vols. 766-767,, no. ISSN: 1662-7482, pp. 1070-1075, 2015. 
[13] 	B. Venkatesh, S. V. Prabhakar, S. D. Prasad, V. Kamala and A. Prasad, "Parametric investigation of the combined effect of Gear parameters on Tangential Force and Dynamic Tooth Load of 40 Ni2 Cr1 Mo 28 Steel Helical," International Journal of Current Engineering and Technology, no. 2, pp. 687-691, 2014. 
[14] 	A. S. Achar, R. P. Chaitanya and S. Prabhu, "A Comparison of Bending Stress and Contact Stress of a Helical Gear as Calculated by AGMA Standards and FEA," International Journal of Emerging Technology and Advanced Engineering, vol. 4, no. 5, pp. 38-43, 2014. 
[15] 	H. H. Htet San, H. H. Win and M. Thein, "Design and Contact Stress Analysi of Helical Gear for Light-Weight Car," International Journal of Mechanical And Production Engineering, vol. 5, no. 8, pp. 7-12, 2017. 
[16] 	J. Hedlund and A. Lethovaara, "Modeling of helical gear contact with tooth deflection," Tribology International 40, p. 613–619, 2007. 
[17] 	I. Atanasovaska, V. N. Stanojlovic, D. Dimitrijevic and D. Momcilovic, "Finite Element Model For Stress Analysis And Nonlinear Contact Analysis Of Helical Gears," Scientific Technical Review, pp. 61-69, 2009. 
[18] 	C. R. Mohana Rao and G. Muthuveerappan, "Finite Element Modelling And Stress Analysis of Helical Gear teeth," Elsevier Science Ltd, vol. Vol 49, pp. 1095-1116, 1993. 
[19] 	F. L. Litvin, A. Fuentes, I. Pere, L. Carvel, K. Kawasaki and R. F. Handschuh, "Modified involute helical gears: computerized design, simulation of meshing and stress analysis," Comput. Methods Appl. Mech. Engrg, pp. 3619-3655, 2003. 
[20] 	P. Pawara and A. A. Utpat, "Analysis of Composite Material Spur Gear Under Static Loading Condition," Materials today Proceeding, vol. 2, no. 4-5, p. P.B.PawaraAbhay A.Utpat, 2015. 
[21] 	T. R. Katona, "The effects of load location and misalignment on," American Journal of Orthodontics and Dentofacial Orthopedics, pp. 394-402, 1994. 
[22] 	M. Barbieri, A. Zippo and F. Pellicano, "Adaptive Grid-Size Finite Element Modeling of Helical Gear Pairs," Mechanism and Machine Theory, vol. 80, pp. 17-32, 2014. 
[23] 	C. Wanga, M. C. Wua, , F. Xua,, . M.-C. Hsua, and Y. Ba, "Modeling of a Hydraulic Arresting Gear Using Fluid–StructureInteraction and Isogeometric Analysis," International Jurnal Computers and Fluids, 2015. 
[24] 	S. Keshari and S. K. Srivastava, "Design of Helical Gear: A Review of Non-Conventional Optimization Techniques," International Conference on Innovations and Developments in Mechanical Engineering, pp. 18-22, 2017. 
[25] 	K. Mao, "Gear tooth contact analysis and its application," Wear 262, p. 1281–1288, 25 July 2006. 
[26] 	O. Asi, "Fatigue failure of a helical gear in a gearbox," Engineering Failure Analysis, p. 1116–1125, 2006. 
[27] 	A. Flodin and S. Andersson, "A simplified model for wear prediction in helical gears," Elsevier Science, p. 285–292, 2001. 
[28] 	N. Li, W. Li, N. Liu and H. Liu, "Analytical Method on Contact Stress of Helical Gear with Asymmetric Involutes," Advanced Materials Research, vol. 321, pp. 157-160, 2011. 
[29] 	C. B. Tsay and Z. H. Fong, "Tooth Contact Analysis for Helical Gear with Pinion Circular Arc Teeth and Gear Involute Shaped Teeth," Journal of Mechanisms, Transmissions, and Automation in Design, vol. 111, pp. 278-284, 1989. 
[30] 	F. L. Litvin, J. S. Chen and J. Lu, "Load Share and Finite Element Stress Analysis for Double Circular-Arc Helical Gear," Mathl. Comput. Modelling, vol. 21, pp. 13-30,, 1995. 
[31] 	Y. Zhang and Z. Fang, "Analysis of Transmission Errors Under Load of Helical Gears With Modified Tooth Surfaces," JOURNAL OF MECHANICAL DESIGN, vol. 119, pp. 120-126, 1997. 
[32] 	B. Venkatesh, V. Kamala and A. Prasad, "Design, Modelling and Manufacturing of Helical Gear," INTERNATIONAL JOURNAL OF APPLIED ENGINEERING RESEARCH, vol. 1, no. ISSN 0976-4259, pp. 103-114, 2010. 
[33] 	Y.-J. Wu, J.-J. Wang and Q.-K. Han, "Static/dynamic contact FEA and experimental study for tooth profile modification of helical gears," Journal of Mechanical Science and Technology, vol. 5, no. 26, p. 1409~1417, 2012. 
[34] 	S. Neptu and P. Srichandr, "Failure of a helical gear in a power plant," Engineering Failure Analysis, pp. 81-90, 2013. 
[35] 	P. P. Jadhav and S. V. Bhasakar, "Design and Analysis of Helical Gear Made of Stainless Steel and Nylon Under Different Loading Condition," IJERT, vol. 5, no. Issue 10, pp. 546-552, 2016. 
[36] 	S. A. Quadri and D. R. Dolas, "Contact Stress Analysis of Involute Spur gear under Static loading," International Journal of Scientific Research Engineering & Technology, vol. 4, no. 5, pp. 593-596, 2015. 
[37] 	K. Naresh and C. Chandrudhu, "Design And Analysis Of Helical Gear," International Journal Of Professional Engineering Studies, vol. 6, no. 4, pp. 194-203, 2016. 
[38] 	R. Sahu, S. Singh, V. and A. Bhoi, "Parametric Stress Analysis of Spur And Helical Gear Using Fea With Aspect Ratio," International Journal of Mechanical And Production Engineering, Vols. 5,, no. 11, pp. 63-69, 2017. 
[39] 	P. Shivaji and S. B. Zope, "Review on- Design And Analysis of Spur Gear To Overcome Gear Stucking And Scuffing," International Journal of Advance Research and Innovative Ideas in Education, vol. 1, no. 3, pp. 298--303, 2015. 
[40] 	T. Yeh, D. C. Yang and S.-H. Tong, "Design of New Tooth Profile for High Load Capacity Gear," Machanism of Machine Theory, pp. 1105-1120, 2001. 
[41] 	D. Liu, T. Ren and X. Jin, "Geometrical Model and Tooth Analysis of Undulating Face Gear," Mechanism and Machine Theory, vol. 56, pp. 140-155, 2015. 
:10.22362/ijcert/2018/v5/i5/v5i501
DOI Link : https://doi.org/10.22362/ijcert/2018/v5/i5/v5i501
Download :
  V5I501.pdf
Refbacks : Currently there are no refbacks

 

Speed Enhancement of QFT Bound Generation using GPU
Authors : Pallavi d Pawar, Mukesh D Patil, Vishwesh A. Vyawahare
Affiliations : Dept. of Electronics & Telecom, Electronics Ramrao Adik Institute of Technology, Nerul
Abstract :

af

In control theory, Quantitative Feedback Theory (QFT) developed by Issac Horowitz, has gained a lot of popularity. Many researchers have proposed a method to generate the bounds that from the literature it is observed that generation of bound takes a lot of time for online design of the controller. It is necessary to speed up the computation of bound generation. This paper exhibits the parallel computing power of the GPU (Graphics Processing Unit) in the area of QFT. In this paper, GPU based approach is proposed to speed up the computation of stability bound. By using MATLAB parallel computing toolboxes, GPU computational power can be easily accessed with the minimum knowledge of GPU architecture, MATLAB code can be executed on the GPU. In order to achieve faster execution of QFT bound generation, NVIDIA GPU with the support of MATLAB parallel computing toolbox is used in this work. Performance comparison of the algorithm for sequential implementation on CPU and parallel implementation on GPU is carried out. This work analyzes the relative performance of GPU vs CPU. In this paper, GPU based approach proposed for significant speedup in the computation of bound using QFT and it is observed that GPU provides speedup two to three times as compared to the CPU.
Citation :

af

Pallavi d Pawar, Mukesh D Patil, Vishwesh A. Vyawahare (2018). Speed Enhancement of QFT Bound Generation using GPU. International Journal of Computer Engineering In Research Trends, 5(4), 129-135. Retrieved from http://ijcert.org/ems/ijcert_papers/V5I406.pdf
Keywords : Quantitative Feedback Theory, QFT bounds, QFT Toolbox, Parallel computing toolbox (PCT), Graphics Processing Unit
References :

af

[1] Chait, Yossi and Yaniv, Oded, ``Multi-input/single-output computer-aided control design using the quantitative feedback theory,' International Journal of Robust and Non-linear Control,vol. 3,pp. 47-54,1993. R. M. Osgood, Jr., Ed. Berlin, Germany: Springer-Verlag, 1998. 
[2] Houpis, Constantine H., Steven J. Rasmussen, and Mario GarciaSanz. Quantitative feedback theory: fundamentals and applications. CRC press, 2005. 
[3] Patil, Mukesh D., and Kausar R. Kothawale``Design of robust PID controller for flexible transmission system using quantitative feedback theory (QFT),' Advances in Computing, Communication and Control (2011): 479-485. 
[4] Brown, Matthew, and I. R. Petersen,``Exact computation of the Horowitz bound for interval plants,'Decision and Control, 1991., Proceedings of the 30th IEEE Conference on. IEEE, 1991. 
[5] Fialho IJ, Pande V, Nataraj PSV, ``Design of feedback system using kharitonov’s segment in Quantitative Feedback Theory,' Proceeding of thr 1st QFT syposium,Dayton,OH,1992;457-470. 
[6] Zhao, Yongdong, and Suhada Jayasuriya ``On the generation of QFT bounds for general interval plants,' Transactions-American Society Of Mechanical Engineers Journal Of Dynamic Systems Measurement And Control 116 (1994): 618-618. 
[7] East, D. J, ``A new approach to optimum loop synthesis,' International Journal of Control 34.4 (1981): 731-748. 
[8] Longdon, L., and D. J. East, ``A simple geometrical technique for determining loop frequency response bounds which achieve prescribed sensitivity specifications,' International Journal of Control 30.1 (1979): 153-158. 
[9] Yang, Shih‐Feng, ``Generation of QFT bounds for robust tracking specifications for plants with affinely dependent uncertainties,'International Journal of Robust and Nonlinear Control 21.3 (2011): 237-247. 
[10] Chait, Yossi, Craig Borghesani, and Yuan Zheng. "Single-loop QFT design for robust performance in the presence of nonparametric uncertainties." Journal of dynamic systems, measurement, and control 117.3 (1995): 420-425.
 [11] Rodrigues, J. M., Y. Chait, and C. V. Hollot. "An efficient algorithm for computing QFT bounds." transactions-american society of mechanical engineers journal of dynamic systems measurement and control 119 (1997): 548-552. 
[12] Yang, Shih-Feng. "Efficient algorithm for computing QFT bounds." International Journal of Control 83.4 (2010): 716-723. 
[13] Nataraj, P. S. V., and Gautam Sardar. "Computation of QFT bounds for robust sensitivity and gain-phase margin specifications." transactions-american society of mechanical engineers journal of dynamic systems measurement and control 122.3 (2000): 528-534. 
[14] Nataraj, Palur SV. "Computation of QFT bounds for robust tracking specifications." Automatica 38.2 (2002): 327-334. 
[15] Nataraj, P. S. V., and Gautam Sardar. "Template generation for continuous transfer functions using interval analysis." Automatica 36.1 (2000): 111-119.
 [16] Gutman, Per‐Olof, Mattias Nordin, and Bnayahu Cohen. "Recursive grid methods to compute value sets and Horowitz–Sidi bounds." International Journal of Robust and Nonlinear Control 17.2‐3 (2007): 155-171.
 [17] Yang, Shih‐Feng. "Generation of QFT bounds for robust tracking specifications for plants with affinely dependent uncertainties." International Journal of Robust and Nonlinear Control 21.3 (2011): 237-247.
 [18] Bailey, F. N., and C-H. Hui. "A fast algorithm for computing parametric rational functions." IEEE transactions on automatic control 34.11 (1989): 1209-1212. 
[19] Ballance, D. J., and G. Hughes, ``A survey of template generation methods for Quantitative Feedback Theory,' (1996): 172-174. 
[20] Fu, Minyue. "Computing the frequency response of linear systems with parametric perturbation." Systems & Control Letters 15.1 (1990): 45-52. 
[21] BARTLETT, ANDREW C. "Computation of the frequency response of systems with uncertain parameters: a simplification." International Journal of Control 57.6 (1993): 1293-1309. 
[22] Patil, Mukesh D., P. S. V. Nataraj, and Vishwesh A. Vyawahare,'Automated design of fractional PI QFT controller using interval constraint satisfaction technique (ICST),' Nonlinear Dynamics69.3 (2012): 1405-1422. [23] Purohit, Harsh, and P. S. V. Nataraj, ``Optimized and automated synthesis of robust PID controller with quantitative feedback theory,' ." Industrial Instrumentation and Control (ICIC), 2015 International Conference on. IEEE, 2015. 
[24] Baida Zhang, Shuai Xu, Feng Zhang, Yuan Bi and Linqi Huang,``Accelerating MatLab Code using GPU: A Review of Tools and Strategies,'in Magnetism, vol. III, G. T. Rado and H. Suhl, Eds. New York: Academic, 1963, pp. 271–350. 
[25] https://www.researchgate.net/figure/270222593_fig1_Fig-1-CPUvs-GPU-Architecture 
[26] Chandrima Roy, Kalyankumar Datta and Devmalya Banerjee, ``Quantitative Feedback Theory based Controller Design of an Unstable System,'IJCA Proceedings on International Conference on Communication, Circuits and Systems 2012 iC3S(5):11-15, June 2013.
 [27] Amin, Shraddha. "Review On Quantitative feedback Theory (QFT) To Maintain Power System Stabilty." (2014).
 [28] Altman, Yair M ``Accelerating MATLAB Performance: 1001 tips to speed up MAT- LAB programs,' 2014.
:10.22362/ijcert/2018/v5/i4/v5i406
DOI Link : https://doi.org/10.22362/ijcert/2018/v5/i4/v5i406
Download :
  V5I406.pdf
Refbacks : Currently there are no refbacks
Performance Analysis of Various Encryption and Multilevel Encryption Techniques for Cloud Computing Security
Authors : Prof. (Ms.) Kimaya Ambekar, Prof. (Dr.) R. Kamatchi ,
Affiliations : 1. Asst. Professor, Somaiya Institute of Management Studies & Research ,2.Professor, Amity University
Abstract :

af

Cloud computing has been seen as a revolutionary transformation from buy-as-you-need to pay-as-you-use of IT resources. Many organizations have adopted this huge paradigm shift but still, the cloud industry is seeing a little hesitation in adopting Cloud technology. Security is the prominent barrier. Encryption algorithms that can be used in the cloud computing for confidentiality purpose. Here in this paper, a complete analysis of various crypto-graphical algorithms has done. If the application demands quicker response time then one should use Blowfish Algorithm. If the application demands lesser memory space then one should opt Blowfish / AES algorithm. If an application requires more security AES and Blowfish are major considerations. If Applications need more security then for 2nd level of encryption RSA if the best algorithm.
Citation :

af

Prof. (Ms.) Kimaya Ambekar, Prof. (Dr.) R. Kamatchi (2018). Performance Analysis of Various Encryption and Multilevel Encryption Techniques for Cloud Computing Security. International Journal of Computer Engineering In Research Trends, 5(4), 122-128. Retrieved from http://ijcert.org/ems/ijcert_papers/V5I405.pdf
Keywords :
References :

af

[1] Cloud Computing Trends: 2017 State of the Cloud Survey, Kim Weins, https://www.rightscale.com/blog/cloud-industry-insights/cloud-computing-trends-2017-state-cloud-survey accessed on 09/12/17 at 6:00 pm
[2] Prof. (Ms.) Kimaya Ambekar, Prof. (Dr.) Kamatchi R.Enhanced User Authentication Model in Cloud Computing Security, Springer International Publishing AG 2016, DOI 10.1007/978-3-319-47952-1_26, pg 327-338
[3] Infotechno- Technology is a life, http://www.infotechno.net/cryptography, Accessed on 09/12/17 at 6:00 pm
[4] What is symmetric key encryption?, https://www.quora.com/What-is-symmetric-key-encryption, Accessed on 09/12/17 at 6:00 pm
[5] Giuseppe, Asymmetric RSA encryption in Java, http://www.giuseppeurso.eu/en/asymmetric-rsa-encryption-in-java/, Accessed on 09/12/17 at 6:00 pm
[6]Symmetric-key algorithm, https://en.wikipedia.org/wiki/Symmetric-key_algorithm
[7] Advantages and Disadvantages of Asymmetric and Symmetric Cryptosystems,  http://www.uobabylon.edu.iq/eprints/paper_1_2264_649.pdf, Accessed on 09/12/17 at 7:00 pm
[8] Data Encryption Standard, https://www.tutorialspoint.com/cryptography/data_encryption_standard.htm
[9] Ritu Tripathi, Sanjay Agrawal, Comparative Study of Symmetric and Asymmetric Cryptography Techniques, International Journal of Advance Foundation and Research in Computer (IJAFRC), Volume 1, Issue 6, June 2014, ISSN 2348 - 4853
[10] Data Encryption Standard (DES), http://searchsecurity.techtarget.com/definition/Data-Encryption-Standard
[11] Triple DES, https://www.tutorialspoint.com/cryptography/triple_des.htm
[12] Advanced Encryption Standard, https://www.tutorialspoint.com/cryptography/advanced_encryption_standard.htm
[13] Al Jeeva et all, Comparative analysis of performance efficiency and security measures of some encryption algorithms, International Journal of Engineering Research and Applications (IJERA) ISSN: 2248 - 9622 www.ijera.com, Vol. 2, Issue 3, May-Jun 2012, pp.3033-3037
[14] Advanced Encryption Standard (AES),http://searchsecurity.techtarget.com/definition/Advanced-Encryption-Standard,Accessed on 11/12/17 at 3:00 pm
[15] Diffie–Hellman key exchange, https://en.wikipedia.org/wiki/Diffie%E2%80%93Hellman_key_exchange, Accessed on 12/12/17 at 3:00 pm
[16] RSA (cryptosystem), https://en.wikipedia.org/wiki/RSA_(cryptosystem),Accessed on 12/12/17 at 5:00 pm
[17] RSA Public Key Encryption System, https://globlib4u.wordpress.com/2013/10/16/rsa-public-key-encryption-system/, http://www.lsi-contest.com/2008/spec2_e.html#intro, Accessed on 15/12/17 at 2.00pm
:10.22362/ijcert/2018/v5/i4/v5i405
DOI Link : https://doi.org/10.22362/ijcert/2018/v5/i4/v5i405
Download :
  V5I405.pdf
Refbacks : Currently there are no refbacks
Selection of Gamete Donor Profiles Using Priority Method
Authors : Rajendra B. Patil, Ajay S. Patil , Hiren Dand
Affiliations : 1.S. K . Somaiya College, Mumbai ,2.School of Computer Sciences, NMU, Jalgaon,3.3Mulund College of Commerce, Mumbai
Abstract :

af

Gamete donation is a part of assisted reproductive technology (ART) with third party reproduction used to conceive. Using donor gamete sample provides medically infertile woman to increase her chance of conceiving and delivering a child. In couple seeking IVF treatment, especially female partner is distressed with pressure from the family, relatives and society. And hence the couples expect to have the gamete donor who may have physical resemblance with the women partner. The gamete bank collects the recipient attributes and matches with the donor profiles that closely resemble recipient partner, including ethnicity, height, body-build, complexion, eye color, hair color and texture. Once a possible match is found, the recipient is given information about the gamete donor and decides whether to proceed or wait for another donor. The practice followed by ART specialist for selecting the gamete donor demands that the profiles are very popularly selected based on attribute priority. The couple expects that the gamete donor should have certain physical resemblance with couple partners. Many a times couple gives preferences for certain attribute for resemblance. By understanding this problem we have designed an attribute priority algorithm that selects the donor profile based on the attributes set with priority. We have selected total 543 records collected from gamete banks. This technique is useful when the couples prioritize the attributes while selecting the gamete donor profiles.
Citation :

af

Rajendra B. Patil,Ajay S. Patil ,Hiren Dand (2018). Selection of Gamete Donor Profiles Using Priority Method. International Journal of Computer Engineering In Research Trends, 5(4), 114-121. Retrieved from http://ijcert.org/ems/ijcert_papers/V5I404.pdf
Keywords : Gamete Donor Profiles Assisted Reproductive Technology.
References :

af

[1]	Jennifer Burr, “Fear, fascination and the sperm donor as ‘abjection’ in interviews with heterosexual recipients of donor insemination”, Sociology of Health & Illness Vol. 31 No. 5, 2009, pp. 705–718, 2009, ISSN 0141–9889
[2]	Baum,Kenneth, (2001), "Golden Eggs: Towards the Rational Regulation of Oocyte Donation", Brigham Young University Law Review, 1, pp 1-33.
[3]	Guidelines for ART Clinics in India ICMR/NAMS, (2011), “Chapter 1: Introduction, Brief History of ART and Requirements of ART Clinics”, pp. 12-17.
[4]	Benno Torgler and Stephen Whyte, (2013), “Selection Criteria in the search for a sperm donor: Internal versus External attributes”, CREMA (Center for Research in Economics, Management and the Arts), paper no. 22,pp.34-41.
[5]	Rajendra B. Patil, B.V Pawar, Ajay S. Patil (Nov 2015),"Sperm Donor Selection Using Nominal and Binary Variable Methods", IJCA, Vol. 130 (14)
[6]	Shen S., A. Khabani, Klein N., D. Battaglia  (February 2003). Statistical analysis of factors affecting fertilization rates and clinical outcome associated with intracytoplasmic sperm injection, American society for Reproductive Medicine, Vol. 79(2),pp.355-360.
[7]	S.Golombok, C.Murray, V.Jadva, E.Lycett, F.MacCallum and J.Rust, (2006), “Non-genetic and non-gestational parenthood: consequences for parent–child relationships and the psychological well-being of mothers, fathers and children at age 3”, Human Reproduction Vol.21(7), pp. 1918–1924.
[8]	Lourenco F, Lobo V, Bacao F, (2004), “Binary-based similarity measures for categorical data and their application in Self Organizing Maps”, Joclad, Vol.6(4),pp. 1-18
[9]	The Practice committee of the American Society for Reproductive Medicine and the Practice Committee of the society for Assisted Reproductive Technology, (2013), “Recommendations for gamete and embryo donation: a committee opinion”, Fertility and Sterility, Vol. 99(1),pp. 47-62.
[10]	Trevor G. Cooper and Ching-Hei Yeung, (January 2006), “Computer-aided evaluation of assessment of “grade a” spermatozoa by experienced technicians”, American Society for Reproductive Medicine, Published by Elsevier Inc., Vol. 85(1), pp. 220 – 224
[11]	 Rosely Gomes Costa, (Mar 2007), "Racial Classification Regarding Semen Donor Selection In Brazil", Developing World BioEthics, Vol. 7(2), pp. 104-111
:10.22362/ijcert/2018/v5/i4/v5i404
DOI Link : https://doi.org/10.22362/ijcert/2018/v5/i4/v5i404
Download :
  V5I404.pdf
Refbacks : Currently there are no refbacks
BIG DATA ANALYSIS ON YOUTUBE USING HADOOP and MAPREDUCE
Authors : Soma Hota, ,
Affiliations : Amity School of Engineering and Technology - Computer Science Engineering, Amity University, Mumbai - Pune
Abstract :

af

We live in a digitalized world today. An enormous amount of data is generated from every digital service we use. This enormous amount of generated data is called Big Data. According to Wikipedia, Big data is a term for data sets that are so large or complex that traditional data processing application software is inadequate to deal with them .Big data challenges include capturing data, data storage, data analysis, search, sharing, transfer, visualization, querying, updating and information privacy. Google‘s video streaming services, YouTube, is one of the best examples of services which produces a huge quantity of data in a very short period. Data mining of such an enormous quantity of data is performed using Hadoop and MapReduce to measure performance. Hadoop is a system which provides a reliable shared storage of such huge datasets on the cloud and also provides an analysis system. The storage is provided by HDFS (Hadoop Distributed File System) and analysis by MapReduce. MapReduce is a programming model and an associated implementation for processing large data sets. This paper presents the algorithmic work on big data problem and its optimal solution using Hadoop cluster and HDFS for YouTube dataset storage and using parallel processing to process large data sets using Map Reduce programming framework. In this paper, we solve two problem statements using the YouTube dataset – top 5 video categories (genres) with the maximum number of videos uploaded and top 5 video uploaders on YouTube. A particularly distinguishing feature of this paper is its focus on analytics performed in unstructured data, which constitute 95% of big data.
Citation :

af

Soma Hota (2018). BIG DATA ANALYSIS ON YOUTUBE USING HADOOP and MAPREDUCE. International Journal of Computer Engineering In Research Trends, 5(4), 98-104. Retrieved from http://ijcert.org/ems/ijcert_papers/V5I403.pdf
Keywords : Big Data definition, Data mining, YouTube data analysis, Hadoop, HDFS, MapReduce, unstructured dataset analysis.
References :

af

1.	Webster, John. "MapReduce: Simplified Data Processing on Large Clusters", "Search Storage", 2004. Retrieved on 25 March 2013. https://static.googleusercontent.com/media/research.g oogle.com/en//archive/mapreduce-osdi04.pdf

2.	Bibliography: Big Data Analytics: Methods and Applications by Saumyadipta Pyne, B.L.S. Prakasa Rao, S.B. Rao

3.	YOUTUBE COMPANY STATISTICS. https://www.statisticbrain.com/youtube-statistics/

4.	Youtube.com @2017. YouTube for media. https://www.youtube.com/yt/about/press/

5.	Big data;Wikipedia https://en.wikipedia.org/wiki/Big_data

6.	Kallerhoff, Phillip. ―Big Data and Credit Unions: Machine Learning in Member Transactions https://filene.org/assets/pdfreports/301_Kallerhoff_M achine_Learning.pdf

7.	Marr,Barnard.―Why only one of the 5 Vs of big data really matters http://www.ibmbigdatahub.com/blog/why-only-one-5-vs- big-data-really-matters
8.	Resources Management Association (IRMA). 2016. Information. "Chapter 1 - Big Data Overview". Big Data: Concepts, Methodologies, Tools, and Applications, Volume I. IGI Global. http://common.books24x7.com/toc.aspx?bookid=114 046
9.	Apache Hadoop
10.	http://hadoop.apache.org/
11.	How To Analyze Big Data With Hadoop Technologies; 3pillarglobal.com. 2017  https://www.3pillarglobal.com/insights/analyze-big-data-hadoop-technologies Dean, S. Ghemawat, MapReduce: Simplified Data Processing on Large Clusters, in:

12.	OSDI‘04, 6th Symposium on Operating Systems

13.	Design and Implementation, Sponsored by USENIX, in cooperation with ACM SIGOPS, 2004, pp. 137– 150

14.	Big Data Tutorial1:MapReduce https://wikis.nyu.edu/display/NYUHPC/Big+Data+T utorial+1%3A+MapReduce

15.	MacLean,Diana.‖A Very Brief Introduction to MapReduce http://hci.stanford.edu/courses/cs448g/a2/files/map_r educe_tutorial.pdf

16.	Edureka.‘Install Hadoo p:Setting up a single node cluster‘. https://www.edureka.co/blog/install-hadoop-single-node-hadoop-cluster
:10.22362/ijcert/2018/v5/i4/v5i403
DOI Link : https://doi.org/10.22362/ijcert/2018/v5/i4/v5i403
Download :
  V5I403.pdf
Refbacks : Currently there are no refbacks
Activation Functions and Training Algorithms for Deep Neural Network
Authors : Gayatri Khanvilkar, Deepali Vora,
Affiliations : Department of Information Technology Vidyalankar Institute of Technology Mumbai, India
Abstract :

af

Machine Learning is a Field of computer science that gives the computer the ability to learn without being explicitly programmed. It is core subpart of artificial intelligence. Whenever new data exposed, computer programs, are enabled to learn, grow, change, and develop by themselves. Machine learning is study and construction of algorithms that learn and do the prediction based on data. Deep learning is nothing but subfield of machine learning. Structure and function of human brain inspire deep learning. Deep learning' name is used for stack neural network. The deep neural network is an Artificial Neural Network with number of hidden layers and hence different from the normal artificial neural network. Supervised and unsupervised manner can train it. Training of such Deep neural network is difficult also it mainly faces two challenges, i.e. over fitting and computation time. Deep neural network train with the help of training algorithms and activation function. So, in this paper mostly used Activation Function (Sigmoid, Tanh and ReLu) and Training Algorithms (Greedy layer-wise Training and Dropout) are analysed and according to this analysis comparison of activation functions and training algorithms are given
Citation :

af

Gayatri Khanvilkar, Deepali Vora (2018). Activation Functions and Training Algorithms for Deep Neural Network. International Journal of Computer Engineering In Research Trends, 5(4), 98-104. Retrieved from http://ijcert.org/ems/ijcert_papers/V5I402.pdf
Keywords : Deep Neural network, Activation Functions, Vanishing gradient, Greedy Algorithm, Dropout Algorithm
References :

af

[1]	Wikipedia contributors. "Machine learning." Wikipedia, The Free Encyclopedia. Wikipedia, The Free Encyclopedia, 24 Oct. 2017. Web. 29 Oct. 2017
[2]	Wikipedia contributors. "Deep learning." Wikipedia, The Free Encyclopedia. Wikipedia, The Free Encyclopedia, 23 Oct. 2017. Web.
[3]	Schmidhuber, Jrgen. "Deep learning in neural networks: An overview." Neural networks 61 (2015): 85-117. 


[4]	Deeplearning4j Development Team. Deeplearning4j: Opensource distributed deep learning for the JVM, Apache Software Foundation License 2.0. http://deeplearning4j.org 
[5]	Aleksander, Igor, and Helen Morton. An introduction to neural computing. Vol. 3. London: Chapman & Hall, 1990. 
[6]	"opening up deep learning for everyone", http://www.jtoy.net/2016/02/14/op ending-up-deep-learning-foreveryone.html, October 2017.
[7]	Lau, Mian Mian, and King Hann Lim. "Investigation of activation functions in the deep belief network." Control and Robotics Engineering (ICCRE), 2017 2nd International Conference on. IEEE, 2017. 
[8]	Understanding Activation Functions in Neural Networks, https://medium.com/the-theory-ofeverything/understanding-activationfunctions-in-neural-networks9491262884e0, September 2017. 
[9]	Activation functions and its type which is better?, https://medium.com/towards-datascience/activation-functions-and-itstypes-which-is-better-a9a5310cc8f, September 2017. 
[10]	The Vanishing Gradient Problem, https://medium.com/@anishsingh20/ the-vanishing-gradient-problem48ae7f501257, September 2017. 
[11]	Qian, Sheng, et al. "Adaptive activation functions in convolutional neural networks." Neurocomputing (2017).
[12]	Gay, M. "IBM ILOG CPLEX Optimization Studio CPLEX Users Manual." International Business Machines Corporation 12 (2012).
[13]	Liu, Jun, Chuan-Cheng Zhao, and Zhi-Guo Ren. "The Application of Greedy Algorithm in Real Life." DEStech Transactions on Engineering and Technology Research mcee (2016). 
[14]	Wikipedia contributors. "Greedy algorithm." Wikipedia, The Free Encyclopedia. Wikipedia, The Free Encyclopedia, 19 Apr. 2017. Web. 28 Oct. 2017. 
[15]	Wang, Jian-Guo, et al. "A mothed of improving identification accuracy via deep learning algorithm under the condition of deficient labelled data." Control Conference (CCC), 2017 36th Chinese. IEEE, 2017. 
[16]	Tong, Li, et al. "Predicting heart rejection using histopathological whole-slide imaging and deep neural network with dropout." Biomedical & Health Informatics (BHI), 2017 IEEE EMBS International Conference on. IEEE, 2017. 
[17]	Wang, Long, et al. "Wind turbine gearbox failure identification with deep neural networks." IEEE Transactions on Industrial Informatics 13.3 (2017): 13601368. 
[18]	Ko, Byung-soo, et al. "Controlled dropout: A different approach to using dropout on deep neural network." Big Data and Smart Computing (BigComp), 2017 IEEE International Conference on. IEEE, 2017. 
[19]	McMahan, H. Brendan, et al. "Ad click prediction: a view from the trenches." Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining. ACM, 2013.
:10.22362/ijcert/2018/v5/i4/v5i402
DOI Link : https://doi.org/10.22362/ijcert/2018/v5/i4/v5i402
Download :
  V5I402.pdf
Refbacks : Currently there are no refbacks
Impact of shifting load centers on the stability of the forklift
Authors : Pratyush Deshmukh, Gunchita Kaur Wadhwa,
Affiliations : Department of Mechanical and Automation Engineering, Amity School of Engineering and Technology, Amity University Mumbai, Mumbai, India
Abstract :

af

This study discusses how to design a system to establish the stability of a forklift fork working with different weights using designing and simulation software. The stresses which appear in the lifting installation of a fork-lift truck at loading-unloading operations are investigated for given input data like load carrying capacity of the fork, the effects of various loads on different positions of the fork regarding stresses and then compare calculated Stresses with allowable material stresses (yield stress/F.O.S). This paper focuses on the significance of Load Centre when subjected to loading at different positions.
Citation :

af

Pratyush Deshmukh, Gunchita Kaur Wadhwa (2018). Impact of shifting load centers on the stability of the forklift. International Journal of Computer Engineering In Research Trends, 5(4), 92-97. Retrieved from http://ijcert.org/ems/ijcert_papers/V5I401.pdf
Keywords : Forklift, load centre, load carrying capacity, fork, design
References :

af

1.	I.I. Boyko, S.P. Cherednichenko «Transport-freight systems and warehouses: educational manual»/. Rostov -Don/ Phoenix, 2007 р.155-161.
2.	 Carina Rislund, HilleviHemphälä, Gert-Åke Hansson c, IstvanBalogh (2013), “Evaluation of three principles for forklift steering Effects on physical Workload”, International Journal of Industrial Ergonomics, Vol. 43.
3.	Ehlanda A, Williams M S and Blakeborough A (2010), “Dynamic load model for fork-lift trucks”, Engineering Structures, Vol. 32, pp. 2693–2701.
4.	George Pantazopoulos, Athanasios Vazdirvanidis, Andreas Rikos and AnagnostisToulfatzis (2014), “Analysis of abnormal fatigue failure of forklift forks”, Case Studies in Engineering Failure Analysis, Vol. 2, pp. 9–14.
5.	Jan-Florian Hoenghoff, Andreas Jungk, Werner Knop, and LudgerOvermeyer (2011), “Using 3D Field Simulation for Evaluating UHF RFID Systems on Forklift Trucks”, IEEE Transactions On Antennas And Propagation, Vol. 59, No. 2, February 2011.
6.	 Juan M Massone and Roberto E Boeri (2010), “Failure of forklift forks”, Engineering Failure Analysis, Vol. 17, pp. 1062–1068.
7.	NolimoSolman K (2002), "Analysis of interaction quality in human-machine systems applications for forklifts", Applied Ergonomics, Vol. 33, pp. 155–166.
8.	Souvik Das, GoutamMukhopadhyay and Sandip Bhattacharyya (2015), "Failure analysis of axle shaft of a forklift", Case Studies in Engineering Failure Analysis, Vol. 3.
9.	Timothy R, Driscoll N, James E Harrison, Clare Bradley, Rachel S Newson (2008), “The Role of Design Issues in Work-Related Fatal Injury in Australia”, Journal of Safety Research, Vol. 39, pp. 209 – 214.
10.	Tim Horberrya Ã, Tore J Larssona, Ian Johnstona and John Lambert (2004), "Forklift safety traffic engineering and intelligent transport systems a case study", Applied Ergonomics, Vol. 35, pp. 575–581.
:10.22362/ijcert/2018/v5/i4/v5i401
DOI Link : https://doi.org/10.22362/ijcert/2018/v5/i4/v5i401
Download :
  V5I401.pdf
Refbacks : There are no refbacks

 

Review on Augmented Reality Applications in Education
Authors : Priya Porwal, Dr. Kamatchi Iyyer,
Affiliations : CSE Department, Amity University Mumbai, Mumbai Pune Expressway,Panvel 41020, India
Abstract :

af

In todays modern age technology has reached every aspect of our lives. It is imperative to consciously use technology to make teaching and learning effective in our education system. Augmented Reality (AR) allows us to see real world with virtual elements. It is a new 3D technology that merges physical and digital world in real time. This paper illustrating the previous studies and research conducted in different subjects in education system including Inorganic Chemistry, Geosciences, Astronomy and soft teaching through children storytelling etc., using Augmented Reality. In all the studies and research conducted on education system, it was common finding that understanding of students about particular topic or subject has improved using AR technology as compared to traditional methods. Its just a beginning and lot yet to be done to introduce technology in education system for the betterment of our society and nation. The previous research and studies has covered many topics and provides guidance to us to take forward the research into other related fields to achieve the common objective of Betterment of education system. I have identified and chosen to propel the research into Engineering Education. Engineering is complex subject and includes many diverse areas like Computers, Civil and Mechanical to name few. I feel there is a huge possibility to create applications using AR which can help stakeholders (teachers and students both) understand and make understand complex subject easily by showcasing results/outcomes in virtual environment. AR applications should be created in such a way that it is worldwide accepted and can be implemented in engineering colleges at reasonable cost and should not be privy to few colleagues, after all Shiksha pe Sabka Haq Hai.
Citation :

af

Priya Porwal, Dr. Kamatchi Iyyer (2018). Review on Augmented Reality Applications in Education. International Journal of Computer Engineering In Research Trends, 5(3), 87-91. Retrieved from http://ijcert.org/ems/ijcert_papers/V5I304.pdf
Keywords : AR, Augmented Reality, Education, Engineering Education.
References :

af

[1] Shelton BE. Augmented reality and education: Current projects and the potential for classroom learning. New Horizons for Learning. 2002;9.

[2] Kerawalla L, Luckin R, Seljeflot S, Woolard A. Making it real: exploring the potential of augmented reality for teaching primary school science. Virtual Reality. 2006 Dec 1;10(3-4):163-74.

[3] Pasarti O, Hajdin H, Matusaka T, Jambori A, Molnar I, Tucsnyi-Szab M. Augmented Reality in education. INFODIDACT 2011 InformatikaSzakmdszertaniKonferencia. 2011.

[4] Asai K, Kobayashi H, Kondo T. Augmented instructions-a fusion of augmented reality and printed learning materials. In Advanced Learning Technologies, 2005. ICALT 2005. Fifth IEEE International Conference on 2005 Jul 5 (pp. 213-215). IEEE.

[5] Kaufmann H. Construct3D: an augmented reality application for mathematics and geometry education. InProceedings of the tenth ACM international conference on Multimedia 2002 Dec 1 (pp. 656-657). ACM.

[6] Liarokapis F, Petridis P, Lister PF, White M. Multimedia augmented reality interface for e-learning (MARIE). World Transactions on Engineering and Technology Education. 2002 Jan 1;1(2):173-6.

 [7] Azuma R, Baillot Y, Behringer R, Feiner S, Julier S, MacIntyre B. Recent advances in augmented reality. IEEE computer graphics and applications. 2001 Nov;21(6):34-47.

[8] Freitas R, Campos P. SMART: a SysteM of Augmented Reality for Teaching 2 nd grade students. InProceedings of the 22nd British HCI Group Annual Conference on People and Computers: Culture, Creativity, Interaction-Volume 2 2008 Sep 1 (pp. 27-30). BCS Learning & Development Ltd.

[9]Lee J, Luchini K, Michael B, Norris C, Soloway E. More than just fun and games: Assessing the value of educational video games in the classroom. InCHI'04 extended abstracts on Human factors in computing systems 2004 Apr 24 (pp. 1375-1378). ACM.

[10] Billinghurst M, Duenser A. Augmented reality in the classroom. Computer. 2012 Jul;45(7):56-63.

[11] Liarokapis F, Mourkoussis N, White M, Darcy J, Sifniotis M, Petridis P, Basu A, Lister PF. Web3D and augmented reality to support engineering education. World Transactions on Engineering and Technology Education. 2004 Jan 1;3(1):11-4.

[12] White M, Jay E, Liarokapis F, Kostakis C, Lister P. A virtual interactive teaching environment using XML and augmented reality. International Journal of Electrical Engineering Education. 2001 Oct;38(4):316-29. 

[13] Andujar JM, Mejas A, Marquez MA. Augmented reality for the improvement of remote laboratories: an augmented remote laboratory. IEEE transactions on education. 2011 Aug;54(3):492-500. 

[14] Shardul Gurjar, Hinal Somani, "A Survey on Use of Augmented Reality in Education"2016 IJEDR | Volume 4, Issue 4 | ISSN: 2321-9939

[15] Salvador-Herranz G, Prez-Lpez D, Ortega M, Soto E, Alcaiz M, Contero M. Manipulating Virtual Objects with your hands: A case study on applying Desktop Augmented Reality at the Primary School. InSystem Sciences (HICSS), 2013 46th Hawaii International Conference on 2013 Jan 7 (pp. 31-39). IEEE.

[16] Maier P, Klinker G. Augmented chemical reactions: An augmented reality tool to support chemistry teaching. InExperiment@ International Conference (exp. at'13), 2013 2nd 2013 Sep 18 (pp. 164-165). IEEE. 

[17] Martn-Gutirrez J, Saorn JL, Contero M, Alcaiz M, Prez-Lpez DC, Ortega M. Design and validation of an augmented book for spatial abilities development in engineering students. Computers & Graphics. 2010 Feb 28;34(1):77-91. 

[18] Martn-Gutirrez J, Fabiani P, Benesova W, Meneses MD, Mora CE. Augmented reality to promote collaborative and autonomous learning in higher education. Computers in Human Behavior. 2015 Oct 31;51:752-61.

[19] Oh YJ, Suh YS, Kim EK. Picture puzzle augmented reality system for Infants creativity. In Ubiquitous and Future Networks (ICUFN), 2016 Eighth International Conference on 2016 Jul 5 	 (pp. 343-346). IEEE 
:10.22362/ijcert/2018/v5/i3/v5i304
DOI Link : https://doi.org/10.22362/ijcert/2018/v5/i3/v5i304
Download :
  V5I304.pdf
Refbacks : Currently there are no refbacks
Design & Fabrication of Multi-level Screening Machine
Authors : D P Jadhav, Harishchandra Ekal, Karan Jambhale, Mahadev Garad
Affiliations : Department of Mechanical Engineering D. Y. Patil College of Engineering and Technology, Kolhapur, India
Abstract :

af

Different type of material in powder form or solid form is separated by using two-level screening machines. This machine can be used in different industries like mining, chemical, food & in metallurgical industries to separate component in different sizes. The work can be done by very few people. It requires very less time for completing work. This screening machine is made up of solid material like steel having high strength. It has two opening sides, from which different types of sand are obtained. In that screening machine two screens are placed to separate different size of components. The screens are made up of the wire mesh and come in various grid sizes
Citation :

af

D P Jadhav,Harishchandra Ekal,Karan Jambhale, Mahadev Garad (2018). Design & Fabrication of Multi-level Screening Machine. International Journal of Computer Engineering In Research Trends, 5(3), 82-86. Retrieved from http://ijcert.org/ems/ijcert_papers/V5I303.pdf
Keywords : Sieve, Screen, Machine, Design.
References :

af

[1] M. Majumder & P. Ghosh, “Finite element analysis of vibration screening techniques using EPS”, 2015.
[2] Dr Patel Bhavesh, "Design of Vibratory Screen used in Coal Mining Industry to Prevent Failure". February- 2013.
[3] Zhao Yue -mina, Zhang Cheng-Yong, renting, "Dynamic design theory and application of large vibrating screen", 2009
[4] Song Yan, Jiang Xiao-hong, Song Juan & Zhang Jian-xun, “Dynamic analysis of a chaotic vibrating screen”.
[5] Design of machine element by  V B Bhandari Book
[6]OLADEJI AKANNI OGUNWOLE of “Construction and Testing of a Dry Sand Sieving Machine  Design,”
[7] Salunkhe Prashant of “study the design of multilevel vibration screening machine.” 
[8] Design standards - Mechanical engineering and Installations, M. Mottier 
[9] Workshop Technology,Volume-1.2, Hajara Chaudhari. 
[10] Joseph E. Shigley, Mechanical engineering design.
:10.22362/ijcert/2018/v5/i3/v5i303
DOI Link : https://doi.org/10.22362/ijcert/2018/v5/i3/v5i303
Download :
  V5I303.pdf
Refbacks : Currently there are no refbacks
Designing and Fabricating a Variable Magnetic Damper for Semi Active Suspension System
Authors : D. Vamsi Krishna, J. Prasanth Babu, K. Ashok
Affiliations : Dept. Mechanical, SRM Institute of Science and Technology, SRM University, Chennai, India
Abstract :

af

Background/Objectives: The purpose of the project is to formulate MR fluid and fabricate MR damper.MR damper is modelled to provide semi-active suspension system in vehicles. Methods/Statistical analysis: The stiffness of suspension system can be varied by using MR fluid. The project aims at fabrication of MR damper and preparation of magneto-rheological fluid, which can vary its viscosity inside the damper in the presence of magnetic field. MR fluid varies its stiffness under the magnetic field; this principle is used to control the damping action of the shock absorber. Findings: The iron particles in the MR fluid opposes the carrier fluid passing through piston head holes. This resistance builds strong opposition for shock absorber oscillation. As With increasing the current provided the number of cycles the damper can sustain is rising which can result in more lifetime of damper. Improvements/Applications: This Technology can be further implemented in Brake System. These MR Dampers are used in certain automobile industries and vehicles. Some automobile industries are working on it to implement in the near future.
Citation :

af

D. Vamsi Krishna,J. Prasanth Babu and K. Ashok (2018). Designing and Fabricating a Variable Magnetic Damper for Semi-Active Suspension System. International Journal of Computer Engineering In Research Trends, 5(3), 77-81. Retrieved from http://ijcert.org/ems/ijcert_papers/V5I302.pdf
Keywords : MR Fluid, Damper, Suspension, Carrier Fluid
References :

af

[1] Bhau K.Kumbhar, Satyajit R.Patil(2014) “A Study on Properties and Selection Criteria for Magneto-Rheological (MR) Fluid Components” March 10-12, India.
[2] M. Kciuk, R. Turczyn “Properties and application of magnetorheological fluids”. JAMME, September – October 2006.
[3] Bhau K. Kumbhar, Satyajit R. Patil, Suresh M. Sawant “Synthesis and characterization of magneto-rheological fluids for MR brake application”. Engineering Science and Technology, an International Journal, 2015.
[4] Fengchen Tu, Quan Yang, Caichun He, Lida Wang” Experimental Study and Design on Automobile Suspension Made of Magneto-Rheological Damper”, International Conference on Future Energy, Environment, and Materials, China, 2012.
[5] T.Imthiyaz Ahameda, R.Sundarrajan, G.T.Prasaatha, V.Raviraja “Implementation of Magneto-rheological dampers in bumpers of Automobiles for reducing impacts during accidents”.
12th Global Congress on Manufacturing And Management, GCMM 2014.
[6] Raju Ahamed, Md Meftahul Ferdaus, Yancheng Li “Advancement in energy harvesting magneto-rheological damper”. Korea-Australia rheology journal – November 2016.
[7] Zekeriya Parlak, Tahsin Engin, Ismail Calli (2012) “Optimal design of MR damper via finite element analyses of fluid dynamic and magnetic field”, 2012.
[8] Weng W. Chooi, S. Olutunde Oyadiji “Design, modelling and testing of magnetorheological (MR) dampers using analytical flow solutions”, 2007.
[9] vamsi Krishna D, N. Sai Prabhu “Variable magnetic damper for semi-active suspension system”, JCPS Volume 9 Issue 4, October - December 2016.
:10.22362/ijcert/2018/v5/i3/v5i302
DOI Link : https://doi.org/10.22362/ijcert/2018/v5/i3/v5i302
Download :
  V5I302.pdf
Refbacks : Currently there are no refbacks
OUTLET SUPERVISOR: LEADERSHIP AND OVERSIGHT FOR CUSTOMERS
Authors : B. Lakshmi, M. Kavya,
Affiliations : Department of Computer Applications, V.R.S.E.C, Vijayawada -7, Andhra Pradesh, India
Abstract :

af

The Shopping Mall Management System will allow more than one shop owner to set up different shops, to sell various products under one roof, i.e. mall. The mall performs the creation of a set of different shops, such as a bookstore, a shoe store, clothes store, jewellery store etc. In the existing mechanism, customers need to search for the shop’s manually in a mall. Shop owners also directly contact the mall administrator for their new shop setup. Even mall administrator also maintains the shop’s data manually. It is like storing information in records. It will create the burden for the management to keep all the records. It is a very much time-consuming process. The article is going to develop a web-based application which is shopping mall management system. This application can be applied to any shop. The Mall owner is the super user and has complete control over all the activities that can be performed. The app notifies the administrator of all shop creation requests, and the administrator can then approve or reject them. The administrator maintains whole mall database. That means updating, deletion, reset tasks are managed.
Citation :

af

B. Lakshmi,M. Kavya (2018). OUTLET SUPERVISOR: LEADERSHIP AND OVERSIGHT FOR CUSTOMERS. International Journal of Computer Engineering In Research Trends, 5(3), 72-76. Retrieved from http://ijcert.org/ems/ijcert_papers/V5I301.pdf
Keywords : outlet, oversight, supervision, opportunistic, architecturally
References :

af

[1] Arentze, T. A., Oppewal, H., & Timmermans, H. J. (2005). “A Multipurpose Shopping Trip Model to Assess Retail Agglomeration Effects”. Journal of Marketing Research, 42(1), 109-115. 

[2] Arnold, M. J., & Reynolds, K. E. (2003). “Hedonic shopping motivations”. Journal of Retailing, 79(2), 77-95.

[3] Aronson, E., & Aronson, J. (2012). “The social animal”, (11th ed). New York: Worth.

[4] Bachi Reddy Sarath Kumar Reddy, G.Viswanath, “Authorized Deduplication: An Approach for Secure Cloud Environment”. International Journal of Computer Engineering In Research Trends, Volume 4, Issue 8, August -2017, pp. 341-345, ISSN: 2349-7084.
 
[5]   http://www.w3schools.com/html/default.asp.

[6]   http://www.w3schools.com/css/default.asp.
:10.22362/ijcert/2018/v5/i3/v5i301
DOI Link : https://doi.org/10.22362/ijcert/2018/v5/i3/v5i301
Download :
  V5I301.pdf
Refbacks : Currently there are no refbacks

 

A Microcontroller Based Smart Helmet Using GSM &GPS Technology in Construction Sites
Authors : Sherif Kamel Hussein, ,
Affiliations : Associate Professor- Department of Communications and Computer Engineering, October University for Modern Sciences and Arts, Giza, Egypt
Abstract :

af

Nowadays due to the regular increase in population number that leads to building a new city to accommodate the extra number of people so, there will be more sites that contain a lot of workers, and to save workers life we have to make a tool with smart actions to keep workers life safe. Many techniques were offered before based on different technologies like Zigbee, Radio Frequency identifications (RFIDs). The smart helmet is the proposed solution that will keep track the worker health conditions, environmental conditions, and locate his place in the site by using ARM microcontroller, GPS, GSM modules and a group of sensors.
Citation :

af

Sherif Kamel Hussein (2018). A Microcontroller Based Smart Helmet Using GSM &GPS Technology in Construction Sites. International Journal of Computer Engineering In Research Trends, 5(2), 65-71. Retrieved from http://ijcert.org/ems/ijcert_papers/V5I209.pdf
Keywords : Global system for mobile (GSM), Global Positioning System (GPS), Low Drop-Out Advanced Risk Machine(ARM), ATtention (AT), Digital Cellular systems( DCS), Printed Circuit Board (PCB)
References :

af

[1]	Mohd Khairul Afiq Mohd Rasli, Nina Korlina Madzhi, Juliana Johari.),“Smart Helmet with Sensors for Accident Prevention”, Faculty of Electrical Engineering, University Teknologi Mara, Malaysia.,2013.
[2]	Shabina.S. “Smart Helmet usingRFand WSN Technology for underground mines safety”, Faculty of Communication Engineering, University k_Ramakrishman, Tricky,2014.
[3]	STMicroelectronics.STM32F072x8STM32F072xB,[Online]. Available: http://www.st.com ,2016.
[4]	“SIM300 Hardware Interface Description”. Available:[online],http://probots.co.in/Manuals/SIM300.pdf2016 
[5]	SKYLAB.GPSModuleDatasheet [ online ]Available,
http://www.nooelec.com/files/SKM53_Datasheet.pdf,2016
[6]	“Texas Instruments.HDC1000 Low Power, High Accuracy Digital Humidity Sensor with TemperatureSensor”,[online].Available:http://www.ti.com/lit/ds/symlink/hdc1000.pdf,2016.
[7]	“Maximintegrated.MAX30100,Pulse Oximeter and Heart-Rate Sensor IC for Wearable Health.”,[online],Available:http://datasheets.maximintegrated.com,2017
[8]	“NXP. Accelerometer Datasheet “,( online].Available: https://lancaster-university.github.io/microbit-docs/resources/datasheets/MMA8653.pdf , 2015
:10.22362/ijcert/2018/v5/i2/v5i210
DOI Link : https://doi.org/10.22362/ijcert/2018/v5/i2/v5i210
Download :
  V5I210.pdf
Refbacks : Currently there are no refbacks
AN EDA &PLOTTING TOOLS INTRODUCTION ON IRIS DATA SET
Authors : R. Anil Kumar, N. Ravi Kiran, D. Nehemiah
Affiliations : Assistant Professor, Department of Computer Science and Engineering G.Pullaiah College of Engineering and Technology, Kurnool.
Abstract :

af

Exploratory data analysis is a task of analyzing data from tools such as statistics, linear algebra, and some plotting techniques it is a very important task for a data set for analyzing data before building an actual machine learning models. It is called exploratory because we understand the data by being Sherlock Holmes. In this paper, we understand some basic plotting tools by using a real-world toy dataset (iris dataset)
Citation :

af

R. Anil Kumar, N. Ravi Kiran, D. Nehemiah (2018). AN EDA &PLOTTING TOOLS INTRODUCTION ON IRIS DATA SET. International Journal of Computer Engineering In Research Trends, 5(2), 62-64. Retrieved from http://ijcert.org/ems/ijcert_papers/V5I209.pdf
Keywords : IRIS, 2-D Scatterplot, Pair plots, Histogram, PDF, CDF.
References :

af

[1]	http://www.lac.inpe.br/~rafael.santos/Doc /s R/CAP386/IntroEDA-Iris.html 
[2]	https://www.kaggle.com/lalitharajesh/irisdataset-exploratory-data-analysis 
[3]	https://www.datacamp.com/community/t utorials/exploratory-data-analysis-python 
[4]	https://en.wikipedia.org/wiki/Exploratory_ data_analysis 
[5]	https://en.wikipedia.org/wiki/Box_plot 
[6]	https://en.wikipedia.org/wiki/Violin_plot 
[7]	https://en.wikipedia.org/wiki/Pair
[8]	https://en.wikipedia.org/wiki/Histogram
:10.22362/ijcert/2018/v5/i2/v5i209
DOI Link : https://doi.org/10.22362/ijcert/2018/v5/i2/v5i209
Download :
  V5I209.pdf
Refbacks : Currently there are no refbacks
Machine Learning for Depression Diagnosis using Twitter data
Authors : Krishna Shrestha, ,
Affiliations : CSE Department, Amity University Mumbai, India
Abstract :

af

World Health Organisation reports that Depression is the most prevalent mental illness and major causes of disability in the world. Though effective treatment for Depression is known, it does not reach the majority of the sufferers in both rich as well as poor countries. In an attempt to address this issue, numerous scientists and researchers are working upon the development of Machine Learning models that shall identify the stage of depression of Twitter user from the users' public tweets and other activities on Twitter. This paper: (1) provides background on depression, use of Twitter for predictions and machine learning; (2) reviews previous studies that employed machine learning for identifying depression; and (3) attempts to guide to future work on the topic.
Citation :

af

Krishna Shrestha (2018). Machine Learning for Depression Diagnosis using Twitter data. International Journal of Computer Engineering In Research Trends, 5(2), 56-61. Retrieved from http://ijcert.org/ems/ijcert_papers/V5I208.pdf
Keywords : Machine Learning, Artificial Intelligence, Twitter data, Depression detection, Public Health
References :

af

[1]	World Health Organization (WHO), 10 Facts on Mental Health, World Health Organisation, 2015. [Online]. Available: http://www.who.int/features/factfiles/mental_health/mental_health_facts/en/. [Accessed: 31-Dec-2017].
[2]	World Health Organization, Depression and other common mental disorders: global health estimates, 2017.
[3]	R. Detels and C. C. Tan, The Scope and Concerns of Public Health, Oxford Textb. Glob. Public Heal., vol. 1, pp. 318, 2015.
[4]	World Health Organization (WHO), Depression (Fact Sheet), World Health Organisation, 2017. [Online]. Available: http://www.who.int/mediacentre/factsheets/fs369/en/. [Accessed: 31-Dec-2017].
[5]    S. W. H. Assembly, "The global burden of mental disorders and the need for a comprehensive, coordinated response from health and social sectors at the country level," Sixty-fifth World Health Assembly, no. May, pp. 25, 2012.
[6] G. Winokur, "Duration of Illness before Hospitalization (Onset) in the Affective Disorders," Neuropsychobiology, vol. 2, no. 23, pp. 8793, 2008.
[7]	T. E. Oxman, S. D. Rosenberg, and G. J. Tucker, The language of paranoia, Am. J. Psychol., 1982.
[8]	G. W. Brown, B. Andrews, T. Harris, Z. Adler, and L. Bridge, Social support, self-esteem and depression., Psychol. Med., vol. 16, no. 4, pp. 81331, 1986.
[9] S. S. Rude, C. R. Valdez, S. Odom, and A. Ebrahimi, "Negative Cognitive Biases Predict Subsequent Depression," Cognit. Ther. Res., vol. 27, no. 4, pp. 415429, 2003.
[10]	M. S. Robinson and L. B. Alloy, Negative cognitive styles and stress-reactive rumination interact to predict depression: A prospective study, Cognit. Ther. Res., vol. 27, no. 3, pp. 275291, 2003.
[11]	C. R. Cloninger, D. M. Svrakic, and T. R. Przybeck, Can personality assessment predict future depression? A twelve-month follow-up of 631 subjects, J. Affect. Disord., vol. 92, no. 1, pp. 3544, 2006.
[12]	S. Vazire and S. D. Gosling, e-Perceptions: Personality impressions based on personal websites, J. Pers. Soc. Psychol., vol. 87, no. 1, pp. 123132, 2004.
[13]	J. W. Pennebaker, M. R. Mehl, and K. G. Niederhoffer, Psychological Aspects of Natural Language Use: Our Words, Our Selves, Annu. Rev. Psychol., vol. 54, no. 1, pp. 547577, 2003.
[14]	P. Resnik, A. Garron, and R. Resnik, Using Topic Modeling to Improve Prediction of Neuroticism and Depression in College Students, Proc. 2013 Conf. Empir. Methods Nat. Lang. Process., no. October, pp. 13481353, 2013.
[15]	M. A. Moreno et al., "Feeling bad on Facebook: Depression disclosures by college students on a social networking site," Depress. Anxiety, vol. 28, no. 6, pp. 447455, 2011.
[16]	H. A. Schwartz et al., Towards Assessing Changes in Degree of Depression through Facebook, Proc. Work. Comput. Linguist. Clin. Psychol. From Linguist. Signal to Clin. Real., pp. 118125, 2014.
[17]	Shannon Greenwood, Andrew Perrin, and Maeve Duggan, Demographics of Social Media Users in 2016 | Pew Research Center, Pew Research, 2016. [Online]. Available: http://www.pewinternet.org/2016/11/11/social-media-update-2016/. [Accessed: 01-Jan-2018].
[18]	J. Mikal, S. Hurst, and M. Conway, Ethical issues in using Twitter for population-level depression monitoring: A qualitative study, BMC Med. Ethics, vol. 17, no. 1, 2016.
[19] R. Kotikalapudi, S. Chellappan, F. Montgomery, D. Wunsch, and K. Lutzen, "Associating internet usage with depressive behaviour among college students," IEEE Technol. Soc. Mag., vol. 31, no. 4, pp. 7380, 2012.
[20]	M. De Choudhury, M. Gamon, S. Counts, and E. Horvitz, Predicting Depression via Social Media, Proc. 7th Int. AAAI Conf. Weblogs Soc. Media, vol. 2, pp. 128138, 2013.
[21]	A. G. Reece, A. J. Reagan, K. L. M. Lix, P. S. Dodds, C. M. Danforth, and E. J. Langer, Forecasting the onset and course of mental illness with Twitter data, Sci. Rep., vol. 7, no. 1, pp. 111, 2017.
[22]	T. K. Houston, L. A. Cooper, H. T. Vu, J. Kahn, J. Toser, and D. E. Ford, Screening the Public for Depression Through the Internet, Psychiatr. Serv., vol. 52, no. 3, pp. 362367, 2001.
[23]	B. A. Husaini, J. A. Neff, J. B. Harrington, M. D. Hughes, and R. H. Stone, Depression in rural communities: Validating the CES?D scale, J. Community Psychol., vol. 8, no. 1, pp. 2027, 1980.
[24]	Park Minsu, Chiyoung Cha, and Meeyoung Cha, Depressive Moods of Users Portrayed in Twitter, ACM SIGKDD Work. Healthc. Informatics, pp. 18, 2012.
[25]	S. Tsugawa et al., On estimating depressive tendencies of Twitter users utilizing their tweet data, Proc. - IEEE Virtual Real., 2013.
[26]	M. Nadeem, M. Horn, and G. Coppersmith, Identifying Depression on Twitter, CoRR, pp. 19, 2016.
[27]	A. Ritter, S. Clark, Mausam, and O. Etzioni, Named Entity Recognition in Tweets: An Experimental Study, Proc. 2011 EMNLP (EMNLP 2011), pp. 15241534, 2011.

:10.22362/ijcert/2018/v5/i2/v5i208
DOI Link : https://doi.org/10.22362/ijcert/2018/v5/i2/v5i208
Download :
  V5I208.pdf
Refbacks : Currently there are no refbacks
Evaluation of Industrial Based Object Detection Method Using Artificial Neural Network
Authors : F. S. Ishaq, I. A. Alhaji, Halis Altun,Y. Atomsa, M. L. Jibrin, S. A. Sani
Affiliations : Dept. of Mathematics and Computer Science, Faculty of Science, Federal University, Kashere, Gombe, Nigeria
Abstract :

af

The essence of the study is to analyse an algorithm which will provide a robust and computationally light method, which might be suitable to implement in the real-time industrial application such as object detection and recognition. For industrial applications, the primary step in automatic detection and classification of an object is to find the object automatically from an image using features related to its shape. This chore is a very complex one. Therefore, to hit the target Histogram of oriented gradient (HOG) algorithm is selected to extract the image features. Average Magnitude Difference Function AMDF is employed to correct the alignment defect. Finally, Artificial Neural Network (ANN) was employed to detect the type of object in the image efficiently. None the less, a database was generated. The database consists of images of real industrial products which are of different shapes and sizes, captured under different lightning conditions. The outcome of the experiment conducted on the database recorded 98.10% success.
Citation :

af

F. S. Ishaq, I. A. Alhaji,Halis Altun,Y. Atomsa, M. L. Jibrin, S. A. Sani(2018). Evaluation of Industrial Based Object Detection Method Using Artificial Neural Network. International Journal of Computer Engineering In Research Trends, 5(2), 50-55. Retrieved from http://ijcert.org/ems/ijcert_papers/V5I207.pdf
Keywords : 1-D mask, HOG algorithm, AMDF algorithm, k-nearest Neighbours algorithm, Cross-correlation Functions algorithms and MLP algorithm
References :

af

[1]	Demirci, B., Arslan, O., Tunaboylu, N. S., & Altun, H. (2013, May). Implementing HOG & AMDF based shape detection algorithm for computer vision & robotics education using LEGO Mindstorms NXT. In Technological Advances in Electrical, Electronics and Computer Engineering (TAEECE), 2013 International Conference on (pp. 288-293). IEEE.
[2]	Ahsan, A. M., & Mohamad, D. B. (2013). Features Extraction for Object Detection Based on Interest Point. TELKOMNIKA Indonesian Journal of Electrical Engineering, (Vol. 11, No. 5, pp. 2716-2722).
[3]	Yilmaz, A., Javed, O., & Shah, M. (2006). Object tracking: A survey. Acm computing surveys (CSUR), (Vol. 38, No. 4, pp. 13).
[4]	Comaniciu, D., & Meer, P. (1999). Mean shift analysis and applications. In Computer Vision, 1999. The Proceedings of the Seventh IEEE International Conference on (Vol. 2, pp. 1197-1203). IEEE.
[5]	Shi, J., & Malik, J. (2000). Normalized cuts and image segmentation. Pattern Analysis and Machine Intelligence, IEEE Transactions on, (Vol. 22, No. 8, pp. 888-905).
[6]	Caselles, V., Kimmel, R., & Sapiro, G. (1997). Geodesic active contours. International journal of computer vision, (Vol. 22, No. 1, pp. 61-79).
[7]	Stauffer, C., & Grimson, W. E. L. (2000). Learning patterns of activity using real-time tracking. Pattern Analysis and Machine Intelligence, IEEE Transactions on, (Vol. 22, No. 8, pp. 747-757).
[8]	Oliver, N. M., Rosario, B., & Pentland, A. P. (2000). A Bayesian computer vision system for modelling human interactions. Pattern Analysis and Machine Intelligence, IEEE Transactions on, (Vol. 22, No. 8, pp. 831-843).
[9]	Monnet, A., Mittal, A., Paragios, N., & Ramesh, V. (2003, October). Background modelling and subtraction of dynamic scenes. In Computer Vision, 2003. Proceedings. Ninth IEEE International Conference on (pp. 1305-1312). IEEE.
[10]	Harris, C., & Stephens, M. (1988, August). A combined corner and edge detector. In Alvey vision conference (Vol. 15, p. 50).
[11]	Lowe, D. G. (2004). Distinctive image features from scale-invariant keypoints. International journal of computer vision, (Vol. 60, No. 2, pp. 91-110).
[12]	Bay, H., Ess, A., Tuytelaars, T., & Van Gool, L. (2008). Speeded-up robust features (SURF). Computer vision and image understanding, (Vol. 110, No. 3, pp. 346-359).
[13]	Shashua, A., Gdalyahu, Y., & Hayun, G. (2004, June). Pedestrian detection for driving assistance systems: Single-frame classification and system level performance. In Intelligent Vehicles Symposium, 2004 IEEE (pp. 1-6). IEEE.
[14]	Dadal, N. and Triggs, B.: Finding People in Images and Videos, PhD thesis, French National Institute for Research in Computer Science and Control (INRIA), July 2006.
[15]	Peker, M., Altun, H., & Karakaya, F. (2012, October). Hardware emulation of HOG and AMDF based scale and rotation invariant robust shape detection. In Engineering and Technology (ICET), 2012 International Conference on (pp. 1-5). IEEE.
[16]	[16]	 Arslan, O., Demirci, B., Altun, H., & Tunaboylu, N. S. (2013, April). A novel rotation- invariant template matching based on HOG and AMDF for industrial laser cutting applications. In Mechatronics and its Applications (ISMA), 2013 9th International Symposium on (pp. 1-5). IEEE.
[17]	Papageorgiou, C. P., Oren, M., & Poggio, T. (1998, January). A general framework for object detection. In Computer vision, 1998. Sixth international conference on (pp. 555-562). IEEE.
[18]	Rowley, H. A., Baluja, S., & Kanade, T. (1998). Neural network-based face detection. Pattern Analysis and Machine Intelligence, IEEE Transactions on, (Vol. 20, No. 1, pp. 23-38.
[19]	Viola, P., Jones, M. J., & Snow, D. (2003, October). Detecting pedestrians using patterns of motion and appearance. In Computer Vision, 2003. Proceedings. Ninth IEEE International Conference on (pp. 734-741). IEEE.
:10.22362/ijcert/2018/v5/i2/v5i207
DOI Link : https://doi.org/10.22362/ijcert/2018/v5/i2/v5i207
Download :
  V5I707.pdf
Refbacks : Currently there are no refbacks
Current Issues on Single Image Dehazing Method
Authors : Falah Ibrahim , MSM Rahim,
Affiliations : Dept. of Computer Science, Zakho Technical Institute, Duhok Polytechnic University, Zakho, Iraq
Abstract :

af

Nowadays the role of computer vision and graphic have seen in wide application fields, so haze and fog fetch trouble to many computer vision and often effect on graphics applications as it diminishes the scene’s clarity. Haze forms when climate conditions stay slack for a time-frame. Building on the bearing of view as for the sun it might be brownish or bluish. Haze reduces the contrast and saturation degraded the quality of preview and captured the image. So it attenuates the mild pondered from the scenes and similarly blends it with some additive light inside the atmosphere. Here comes the role of the dehazing method though is very important in computer vision applications, it can take off haze from the pictures, increment the scene vision. From earlier up to now there are many methods have been proposed for improving images, single image dehazing method is one of them, and recently the researchers are more interesting with this method. The goal of this study firstly gives a brief introduction to image enhancement and restoration algorithms and suggested a variety of dehazing algorithm. Secondly, explore the different techniques of single image dehazing to remove the haze professionally from the digital images. Finally, summarized the comparison among these methods based on image quality assessment.
Citation :

af

Falah Ibrahim.MSM Rahim (2018). Current Issues on Single Image Dehazing Method. International Journal of Computer Engineering In Research Trends, 5(2), 37-49. Retrieved from http://ijcert.org/ems/ijcert_papers/V5I205.pdf
Keywords : Dehazing Method, Single image, Outdoor image, Image restoration, Image Enhancement, Dark Channel.
References :

af

1.  Sharma R, Chopra V. A review of different image dehazing methods.  
2. Patel SP, Nakrani M. A Review on Methods of Image Dehazing. 
3. Ding M, Wei L. Single-image haze removal using the mean vector L2-norm of RGB image sample window. Opt-Int J Light Electron Opt. 2015;126(23):3522–8. 
4.  Lee S, Yun S, Nam J-H, Won CS, Jung S-W. A review of dark channel prior based image dehazing algorithms. EURASIP J Image Video Process. 2016;2016(1):4.  
5.  Lu H, Li Y, Nakashima S, Serikawa S. Single image dehazing through improved atmospheric light estimation. Multimedia Tools Appl. 2016;75(24):17081–96.  
6. Chengtao C, Qiuyu Z, Yanhua L. A survey of image dehazing approaches. In IEEE; 2015. p. 3964–9. 
7. Liang J, Ren L, Ju H, Zhang W, Qu E. Polarimetric dehazing method for dense haze removal based on distribution analysis of angle of polarization. Opt Express. 2015;23(20):26146–57. 
8.  Kaufman Y, Tanré D, Gordon H, Nakajima T, Lenoble J, Frouin R, et al. Passive remote sensing of tropospheric aerosol and atmospheric correction for the aerosol effect. J Geophys Res-Atmospheres. 1997;102(D14):16815–30.  
9. Singh D, Kumar V. Comprehensive survey on haze removal techniques. Multimedia Tools Appl. 2017;1–26.  
10. Badhe MV, Prabhakar LR. A Survey on Haze removal using Image visibility Restoration Technique. Int J Comput Sci Mob Comput. 2016;5(2):96–101. 
11. Minnaert M, Singer S. The Nature of Light and Colour in the Open Air. Phys Today. 1954;7:16. 
12. Unsworth MH. Daylight and its spectrum (second edition). By S. T. Henderson. Adam Hilger Ltd. (Bristol), 1977. Pp. 349 + x, 87 figs., 8 plates, 9 tables. Q J R Meteorol Soc. 1979 Jan 1;105(443):320–320. 
13. McCartney EJ. Optics of the atmosphere: scattering by molecules and particles. N Y John Wiley Sons Inc 1976 421 P. 1976; 
14. Narasimhan SG, Nayar SK. Vision and the atmosphere. Int J Comput Vis. 2002;48(3):233–54. 
15. Narasimhan SG, Nayar SK. Contrast restoration of weather degraded images. IEEE Trans Pattern Anal Mach Intell. 2003;25(6):713–24. 
16. Nayar SK, Narasimhan SG. Vision in bad weather. In IEEE; 1999. p. 820–7. 
17. Long J, Shi Z, Tang W, Zhang C. Single remote sensing image dehazing. IEEE Geosci Remote Sens Lett. 2014;11(1):59–63. 
18. Ge G, Wei Z, Zhao J. Fast single-image dehazing using linear transformation. Opt-Int J Light Electron Opt. 2015;126(21):3245–52. 
19. Pan X, Xie F, Jiang Z, Yin J. Haze removal for a single remote sensing image based on deformed haze imaging model. IEEE Signal Process Lett. 2015;22(10):1806–10. 
20. He K, Sun J, Tang X. X.: Single image haze removal using dark channel prior. 2009; 
21. Alharbi EM, Ge P, Wang H. A Research on Single Image Dehazing Algorithms Based on Dark Channel Prior. J Comput Commun. 2016;4(02):47. 
22.  Das D, Chaudhuri SS, Roy S. Dehazing technique based on the dark channel prior model with sky masking and its quantitative analysis. In IEEE; 2016. p. 207–10.  
23. Kil TH, Lee SH, Cho NI. A dehazing algorithm using dark channel prior and contrast enhancement. In IEEE; 2013. p. 2484–7. 
24. Ullah E, Nawaz R, Iqbal J. Single image haze removal using improved dark channel prior. In IEEE; 2013. p. 245–8. 
25. Zhang T, Chen Y. Single image dehazing based on improved dark channel prior. In Springer; 2015. p. 205–12. 
26. Chengtao C, Qiuyu Z, Yanhua L. Improved dark channel prior dehazing approach using adaptive factor. In IEEE; 2015. p. 1703–7. 
27. Yu H, Cai C. An adaptive factor-based method for improving dark channel prior dehazing. In IEEE; 2016. p. 417–20. 
28. Lu X, Lv G, Lei T. Single image dehazing based on multiple scattering model. In IEEE; 2014. p. 239–44. 
29. Wang R, Li R, Sun H. Haze removal based on multiple scattering model with superpixel algorithm. Signal Process. 2016;127:24–36. 
30. Wang W, Yuan X, Wu X, Liu Y, Ghanbarzadeh S. An efficient method for image dehazing. In IEEE; 2016. p. 2241–5. 
31. Tan RT. Visibility in bad weather from a single image. In IEEE; 2008. p. 1–8. 
32. Fattal R. Single image dehazing. ACM Trans Graph TOG. 2008;27(3):72. 
33. Tarel J-P, Hautiere N. Fast visibility restoration from a single color or gray level image. In IEEE; 2009. p. 2201–8. 
34. Fattal R. Dehazing using color-lines. ACM Trans Graph TOG. 2014;34(1):13. 
35. Tang K, Yang J, Wang J. Investigating haze-relevant features in a learning framework for image dehazing. In 2014. p. 2995–3000. 
36. Zhu Q, Mai J, Shao L. A fast single image haze removal algorithm using color attenuation prior. IEEE Trans Image Process. 2015;24(11):3522–33. 
37. Cai B, Xu X, Jia K, Qing C, Tao D. Dehazenet: An end-to-end system for single image haze removal. IEEE Trans Image Process. 2016;25(11):5187–98. 
38. Berman D, Avidan S. Non-local image dehazing. In 2016. p. 1674–82. 

:10.22362/ijcert/2018/v5/i2/v5i205
DOI Link : https://doi.org/10.22362/ijcert/2018/v5/i2/v5i205
Download :
  V5I205.pdf
Refbacks : Currently there are no refbacks
SURVEY ON REAL-TIME ANALYSIS OF ECG TELEMETRY SYSTEM
Authors : Shantha Priya.E, Sudha.V, Balakrishnan.C
Affiliations : Student Computer Science and Engineering, S.A.Engineering College, Chennai
Abstract :

af

A novel flag quality-mindful Internet of Things empowered electro cardiogram (ECG) telemetry framework for ceaseless cardiovascular wellbeing checking applications. The proposed quality-mindful ECG checking framework comprises of three modules the fundamental goals of this paper are outline and improvement of a light-weight ECG for naturally arranging the procured ECG motion into worthy or inadmissible class and continuous usage of proposed IOT-empowered ECG observing structure utilizing ECG sensors, controller, and cloud server. The proposed framework will give the promising outcome and the battery lifetimes will build due to the nature of flag from an adequate transmission.
Citation :

af

Shantha Priya.E,Sudha.V,Sujitha.T, Balakrishnan.C.(2018). SURVEY ON REAL-TIME ANALYSIS OF ECG TELEMETRY SYSTEM. International Journal of Computer Engineering In Research Trends, 5(2), 34-36. Retrieved from http://ijcert.org/ems/ijcert_papers/V5I204.pdf
Keywords : RASP, KNN, range query, threat model, ECG sensor, Controller, Cloud Server
References :

af

[1] D. He, and S. Zeadally, "An analysis of RFID authentication schemes for the internet of things in healthcare environment using elliptic curve cryptography,"  IEEE Internet Things J., vol. 2, no. 1, pp. 72-83, 2015.

[2] Abhishek Srivastava, Nithin Sankar k., Bio-WiTel: A Low Power Integrated Wireless Telemetry System For Healthcare 
Application in 401-406 MHz of Med Radio Spectrum. IEEE Internet Things J., vol. 2, no. 6, pp. 515-526, 2016.

[3] Joannis Chatzigiannakis, Emil Stoyanov Valchinov., Advanced observation and Telemetry heart System Utilizing Wearable ECG device and a Cloud Platform.  IEEE Internet Things J., vol. 3, no. 1, pp. 72-83, 2015.

[4] Nemati, Ebrahim, M. Jamal Deen, and Tapas Mondal. "A wireless wearable ECG sensor for long-term applications." Communications Magazine, IEEE 50.1 (2014).

[5] S. Thomas, R. R. Harrison, A. Leonardo, and M. S. Reynolds, "A battery-free multichannel digital neural/EMG telemetry system for flying insects," IEEE  Transactions on Biomedical Circuits and Systems, vol. 6, no. 5, pp. 424–436,  October 2013.

[6] S. Mandal, L. Turicchia, and R. Sarpeshkar, "A low-power, battery-free tag for body sensor networks," IEEE Pervasive Computing, vol. 9, no. 1, pp. 71–77, Jan.- March 2012.

[7] S. Popa, K. Fricke, J. Dubois, A. Kottam, and R. Sobot, “Murine heart volume: Numerical comparison and calibration of conductance catheter models,” Biomedical Engineering, IEEE Transactions on, vol. PP, no. 99, pp.2014. 
:10.22362/ijcert/2018/v5/i2/v5i204
DOI Link : https://doi.org/10.22362/ijcert/2018/v5/i2/v5i204
Download :
  V5I204.pdf
Refbacks : Currently there are no refbacks
A Survey on Data Perturbation with Encrypted Data Transfer
Authors : Swathi.C, Sharmila.K, Sujitha.T, K.B.Aruna
Affiliations : Computer Science and Engineering, S.A. Engineering college, Chennai -600077
Abstract :

af

An application that is utilized to recover information from the vast database is troublesome in numerous divisions like IT and furthermore in government parts and associations. In this way, the reaction time will be low. For this reason, we propose a technique called RASP information irritation to give secure and efficient range question and KNN inquiry administrations. By utilizing this strategy, we can recover information rapidly. The KNN-R calculation is intended to work with the RASP go inquiry calculation to process the KNN questions. In this way, the recovery of data from the vast database is snappy and straightforward and furthermore, the reaction time will be high the principle favourable position of utilizing this calculation is reaction time. The analysis of data on threats and queries under precisely defined threat model was done to improve the security. So, the recoup of data from an extensive database is very easy and quick and also the response time will be very high. The main advantage of using this algorithm is response time
Citation :

af

Swathi.C,Sharmila.K,Sujitha.T, K.B.Aruna.(2018). A Survey on Data Perturbation with Encrypted Data Transfer. International Journal of Computer Engineering In Research Trends, 5(2), 30-33. Retrieved from http://ijcert.org/ems/ijcert_papers/V5I203.pdf
Keywords : RASP, KNN, range query, threat model, security, response time.
References :

af

[1] R. Agrawal, J. Kiernan, R. Srikant, and Y. Xu, "Order-preserving encryption for numeric data," in Proceedings of ACM SIGMOD Conference, 2004.

[2] M. Armbrust, A. Fox, R. Griffith, A. D. Joseph, R. K. and Andy Konwinski, G. Lee, D. Patterson, A. Rabkin,I. Stoica, and M. Zaharia, "Above the clouds: A Berkeley view of cloud computing," Technical  Report, University of Berkeley, 2009.

[3] J. Bau and J. C. Mitchell, "Security modelling and analysis," IEEE Security and Privacy, vol. 9, no. 3, pp. 18–25,2011.	

[4] S. Boyd and L. Vandenberghe, Convex Optimization. Cambridge University Press, 2004.
[5] N. Cao, C. Wang, M. Li, K. Ren, and W. Lou, “Privacy-preserving multi-keyword ranked search over encrypted cloud data,” in INFOCOMM, 2011.

[6] K. Chen, R. Kavuluru, and S. Guo, “Investigation on Privacy and Secure content of location based Queries,” in ACM Conference on Data and Application Security and Privacy, 2011, pp. 249–260.

[7]  B.Kundan, N.Poorna Chandra Rao,Dr S.Prem Kumar, “Geometric data perturbation for outsourced data mining,” International Journal of Computer Engineering in Research Trends,vol.2,no.9, pp. 543-546,2015. 

[8] K. Chen, L. Liu, and G. Sun, “Towards attack-resilient geometric data perturbation,” in SIAM Data Mining Conference, 2007.

[9] B. Chor, E. Kushilevitz, O. Goldreich, and M. Sudan, “Private information retrieval,” ACM Computer Survey, vol. 45, no. 6, pp. 965–981, 1998.

[10] R. Curtmola, J. Garay, S. Kamara, and R. Ostrovsky, “Searchable symmetric encryption: improved definitions and efficient constructions,” in Proceedings of the 13th ACM conference on Computer and communications security. New York, NY, USA: ACM, 2006, pp. 79–88.

[11] N. R. Draper and H. Smith, Applied Regression Analysis. Wiley, 1998.

[12] H. Hacigumus, B. Iyer, C. Li, and S. Mehrotra, "Executing SQL over encrypted data in the database-service-provider model," in Proceedings of ACM SIGMOD Conference, 2002.

[13] T. Hastie, R. Tibshirani, and J. Friedman, The Elements of Statistical Learning. Springer-Verlag, 2001.

[14] Prof. R. Poorvadevi, S.Keerthana, V.S. Ghethalaxmipriya, K. Venkatasailokesh,,” An Enforcement of Guaranteed Client Level Defensive Mechanism in Public Cloud Services”. International Journal of Computer Engineering in Research Trends,vol.4,no.2, pp. 20-24,2017.

[15] K.Samunnisa, Maloth Bhavsingh, “Privacy-Preserving Scalar Product Computation over Personal Health Records International Journal of Computer Engineering in Research Trends,vol.3,no.12, pp. 42-47,2016.
[16] A. Hyvarinen, J. Karhunen, and E. Oja, Independent Component Analysis. Wiley, 2001.

[17] I. T. Jolliffe, Principal Component Analysis. Springer, 1986.

[18] F. Li, M. Hadjieleftheriou, G. Kollios, and L. Reyzin, “Dynamic authenticated index structures for outsourced databases,” in Proceedings of ACM SIGMOD Conference, 2006.

[19] K. Liu, C. Giannella, and H. Kargupta, “An attacker’s view of distance preserving maps for privacy preserving data mining,” in Proceedings of PKDD, Berlin, Germany, September 2006.

[20] M. L. Liu, G. Ghinita, C. S.Jensen, and P. Kalnis, “Enabling search services on outsourced private spatial data,” The International Journal of on Very Large Data Base, vol. 19, no. 3, 2010.

[21] Y. Manolopoulos, A. Nanopoulos, A. Papadopoulos, and Y. Theodoridis, R-trees: Theory and Applications. Springer-Verlag, 2005.

[22] R. Marimont and M. Shapiro, “Nearest neighbour searches and the curse of dimensionality,” Journal of the Institute of Mathematics and its Applications, vol. 24, pp. 59–70, 1979.

[23] M. F. Mokbel, C. yin Chow, and W. G. Aref, “The new casper: Query processing for location services without compromising privacy,” in Proceedings of Very Large Databases Conference (VLDB), 2006, pp. 763–774.

[24] P. Paillier, “Public-key cryptosystems based on composite degree residuosity classes,” in EUROCRYPT. Springer-Verlag, 1999, pp. 223–238.

[25] S. Papadopoulos, S. Bakiras, and D. Papadias, “Nearest neighbor search with strong location privacy,” in Proceedings of Very Large Databases Conference (VLDB), 2010.

[26] F. P. Preparata and M. I. Shamos, Computational Geometry: An Introduction. Springer-Verlag, 1985.

[27] M. Rudelson and R. Vershynin, “Smallest singular value of a random rectangular matrix,’’Communications on Pure and Applied Mathematics, vol. 62, pp. 1707–1739, 2009.

[28] E. Shi, J. Bethencourt, T.-H. H. Chan, D. Song, and A. Perrig, “Multi-dimensional range query over encrypted data,” in IEEE Symposium on Security and Privacy, 2007.

[29] R. Sion, “Query execution assurance for outsourced databases,” in Proceedings of Very Large Databases Conference (VLDB), 2005.

[30] C. Wang, N. Cao, J. Li, K. Ren, and W. Lou, “Secure ranked keyword search over encrypted cloud data,” in Proceedings of IEEE International Conference on Distributed Computing Systems (ICDCS), 2010.

[31] P. Williams, R. Sion, and B. Carbunar, “Building castles out of mud: Practical access pattern privacy and correctness on untrusted storage,” in ACM Conference on Computer and Communications Security, 2008.

[32] W. K. Wong, D. W.-l. Cheung, B. Kao, and N. Mamoulis, “Secure knn computation on encrypted databases,” in Proceedings of ACM SIGMOD Conference. New York, NY, USA: ACM, 2009, pp. 139–152.

[33] M. Xie, H. Wang, J. Yin, and X. Meng, “Integrity auditing of outsourced data,” in Proceedings of Very Large Databases Conference (VLDB), 2007, pp. 782–793.

[34] H. Xu, S. Guo, and K. Chen, “Building confidential and efficient query services in the cloud with rasp data perturbation,” Wright State Technical Report, http://arxiv.org/abs/1212.0610,
 
[35] M. L. Yiu, C. S. Jensen, X. Huang, and H. Lu, “Spacetwist: Managing the trade-offs among location privacy, query performance, and query accuracy in mobile services,” in Proceedings of IEEE International Conference on Data. 
:10.22362/ijcert/2018/v5/i2/v5i203
DOI Link : https://doi.org/10.22362/ijcert/2018/v5/i2/v5i203
Download :
  V5I203.pdf
Refbacks : Currently there are no refbacks
POWER SAVING SYSTEM USING SENSOR OVER IoT
Authors : Vani Sri.S, Sneha.S, Dr.G.Umarani Srikanth
Affiliations : 1Computer science and engineering department, S.A.Engineering College, Chennai
Abstract :

af

The objective of this paper is to save electric power to detect human using a PIR sensor. We often leave the place without switching off lights, fans and Air Conditioner etc. Therefore electricity is getting wasted. Here we have done a power saving in which electricity cost will be saved by sensing the movement of people entering or by leaving out the room. If the sensor identifies that there are no persons present inside the room, then electrical appliances will be turned OFF automatically. If any person enters the room, automatically devices will be turned ON. Here we are separately controlling every electrical appliance by specifying the area. We can also vary the speed of the fan by sensing the room temperature. If the temperature is more the speed of the fan will even more. If there is no user in the room, it switches off the lights, fans, or AC with the help of interface which is in between the switchboard of appliances and PIR sensor. DC relay is also used for the turn ON and turn OFF of the electrical devices according to the output which is in the PIC controller circuit. How many appliances are turned on can also be checked through online? If anyone wants to see who are present inside the room can also be seen with their images on the cloud.
Citation :

af

Vani Sri.S,Sneha.S,Dr.G.Umarani Srikanth.(2018). POWER SAVING SYSTEM USING SENSOR OVER IoT. International Journal of Computer Engineering In Research Trends, 5(2), 25-29. Retrieved from http://ijcert.org/ems/ijcert_papers/V5I202.pdf
Keywords : Internet of thing, Cloud, PIR Sensor, Relay, Appliances, ESP8266, Arduino
References :

af

[1] Young-Sung Son, Topi Pulkkinen, Kyeong-Deok   Moon and Chaekyu Kim, “Home Energy Management System”, IEEE, Vol. 56, No.3, August 2010.

[2] Khusvinder Gill, Shuang-Hua Yang, Fang Yao, and     Xin Lu, “A ZigBee-Based Home Automation”, IEEE, Vol .55, No.2, May 2009.

[3] Chia-Hung Lien, Ying-Wen Bai, and Ming-Bo Lin, Member, “Using Remote- Controller for Home Power Management”, IEEE,  Vol.53, No.4,  November 2007.

 [4] Masahiro Inoue, Senior Member, Toshiyasu Higuma, Yoshiaki Ito, Noriyuki Kushiro, and Hitoshi Kubota, “Architecture for Home Energy Management System”, IEEE, Vol.49, No.3, August 2003. 

 [5] Jinsung Byun, Boungju Jeon, Junyoung Noh, Youngil Kim, and Sehyun Park, Member, “An Adjusting Sensor for Smart Home Services based on ZigBee", IEEE, Vol.58, No.3, August 2012.

 [6] Nagender Kumar Suryadevara, Student Member,Subhas Chandra Mukhopadhyay, Fellow, Sean Dieter Tebje Kelly, and Satinder Pal Singh Gill, “Using WSN Smart Sensors and Actuator for Power Management in Buildings”, IEEE, Vol.20, N0.2, April 2015.

 [7] Joon Heo, Student Member, Choong Seon Hong, Member, Seok Bong Kang and Sang Soo Jeon, “Design & Implementation of Control system  for Power  Consumption”,IEEE, Vol.54, No.1, February 2008.

 [8] Jinsoo Han, Haeryong Lee, and Kwang-Roh Park,       “Controlling through remote and Energy-Saving  Architecture based on ZigBee ", IEEE, Vol.55, No.1,   February 2009.

 [9] Jinsoo Han, Chang-Sic Choi, Wan-Ki Park, Ilwoo Lee, and Sang-Ha Kim, “Smart Home Management System Including Renewable Energy done on ZigBee and PLC”, IEEE, Vol.60, N0.2, May 2014.

 [10] Jinsung Byun, Insung Hong, and Sehyun Park,          Member, “Intelligent Cloud Home Energy Management          System Using Household Appliance”, IEEE, Vol.58,           No.4, November 2012.

[11] Ying-Wen Bai and Yi-Te Ku, “Room Light           Intensity Detection & control Using Microprocessor           and Light Sensors”, IEEE, Vol.54, No.3, August 2008.

 [12] Minsoo Lee, Member, Yoonsik Uhm, Yong Kim,         Gwanyeon Kim and Sehyun Park, Member, “Intelligent       Power Management Device with Middleware based             Living Pattern Learning for Power Reduction”, IEEE,            Vol.55, No.4,  November 2009.

[13] Bojan Mrazovac, Milan Z. Bjelica, Dragan Kukolj,         Senior Member,  Branislav M. Todorović, Member, and            Dragan Samardžija, Member, “Human Detection for     Residential Smart Energy Systems by ZigBee RSSI          Changes”, IEEE, Vol.58, No.3, August 2012

[14] Jinsung Byun, Sunghoi Park, Byeongkwan Kang, Insung Hong, and Sehyun Park, Member, “Design  &Implementation of an  Energy Saving System for Power Reduction”, IEEE, Vol.59, No.3, August 2013.

[15] Hyung-Bong Lee, Lee-Jeong Park, Sung-Wook Park, Tae-Yun Chung, and Jung-Ho Moon, “ Remote  Control for Home Appliances through a  Wired Sensor Network”, IEEE, Vol.56, No.4, November 2010.

[16] Cheng-Hung Tsai, Ying-Wen Bai, Chun-An Chu,      Chih-Yu Chung and Ming-Bo Lin, Member, “PIR-Sensor        based Lighting Device with Ultra-low Standby Power          Consumption”, IEEE, Vol.57, No.3, August 2011.

[17] Dae-Man Han and Jae-Hyun Lim, Member,       ”Implementing smart home energy management using         zigbee”, IEEE, Vol. 56, No. 3, August 2010.

[18] Suk Lee, Member, IEEE, Kyoung Nam Ha, Kyung      Chang Lee, Member, “pyroelectric infrared sensor for Awareness of smart home", IEEE, Vol.52, No.4,       November 2006.

[19] MariagraziaDotoli, “Guest Editorial Special Issue on      Automation and Optimization for  Energy Systems”,     IEEE, Vol.14, No.2,  April 2017.

 [20] F.Erden, S. Bingol and A.E Cetin, “Hand Gesture on      Remote Control System Using Infrared Sensors and         Camera”, IEEE, Vol.60, N0.4, November 2014. 
:10.22362/ijcert/2018/v5/i2/v5i202
DOI Link : https://doi.org/10.22362/ijcert/2018/v5/i2/v5i202
Download :
  V5I202.pdf
Refbacks : Currently there are no refbacks
SURVEY ON WOMEN SAFETY USING IOT
Authors : B.Sindhu Bala, M.Swetha, M.Tamilarasi and D.Vinodha
Affiliations : Computer Science and Engineering, S.A.Engineering College, Chennai
Abstract :

af

Nowadays women are facing many security problems in the society. In such cases, they feel handicap and need help to protect them. Even though many technologies have been introduced for women still kidnapping, eve teasing and sexual harassment are taking place in our country. When the women face into unsecured situations, to ensure the safety, automatic detection system needs to establish which send an alert message which includes the location of the police department. This can be done by sensing various factors such as abnormal sounds, body reaction like trembling, dreading and heartbeat which can be sensed using sensor and to provide the alert message.In this paper, we surveyed the existing mechanism for detecting locations, for sending communications and collecting physical parameters of the human body using sensors.
Citation :

af

B.Sindhu Bala,M.Swetha,M.Tamilarasi and D.Vinodha.(2018). SURVEY ON WOMEN SAFETY USING IOT. International Journal of Computer Engineering In Research Trends, 5(2), 16-24. Retrieved from http://ijcert.org/ems/ijcert_papers/V5I201.pdf
Keywords : Automatic detection, alert message, abnormal sound, heartbeat, trembling, sensor.
References :

af

[1] B.Vijaylashmi1, Renuka.S2, Pooja Chennur3, Sharangowda.Patil4, "Self defence system for women safety with location tracking and SMS alerting through Gsm network.IJRET: International Journal of Research in Engineering and Technology ISSN: 2319-1163 ISSN: 2321-7308.
[2] Ramesh Kumar P a,*, Srikanth b, KL Sailaja c," Location Identification of the Individual based on Image Metadata”, Procedia Computer Science 8 ( 2016 ) 451 – 454.
[3] Chaoran Zhou, Hongwei Jia, Zhicai Juan, Xuemei Fu, and Guangnian Xiao, "A Data-Drive Method for Trip Ends IdentificationUsing Large-Scale Smartphone-based GPS Tracking Data", Ieee Transactions On Intelligent Transportation Systems, Vol. 18, No. 8, August 2017
[4] TAKUYA MAEKAWA1, NAOMI YAMASHITA2, AND YASUSHI SAKURAI3,” How Well Can a User’s Location Privacy Preferences be Determined Without Using GPS Location Data?”, Received 2 December 2013; revised 25 March 2014; accepted 18 June 2014. Date of publication 8 July 2014; date of current version 6 December 2017.Digital Object Identifier 10.1109/TETC.2014.2335537
[5] Hung Nguyen, Karina Lebel, Sarah Bogard, Etienne Goubault, Patrick Boissy, and Christian Duval,” Using Inertial Sensors to Automatically Detect and Segment Activities of Daily Living in People With Parkinson’s Disease”, TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, VOL. 26, NO. 1, JANUARY 2018 197
[6] Igor R. de Almeida, Vinicius J. Castle, Norman I. Badler, SoraiaRauppMusse,
andCláudioRosito Jung, “Detection of Global and Local Motion Changes in Human Crowds”, Ieee Transactions On Circuits And Systems For Video Technology, Vol. 27, No. 3, March 2017.
[7] Dawei Fan, Luis Lopez Ruiz, Jiaqi Gong, “An Energy Harvesting Modeling and Profiling Platform for Body Sensor Networks”,IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, VOL. 22, NO. 1, JANUARY 2018.
[8]  JG Lourens,”Detection and Logging Advertisements using its Sound,”IEEE TRANSACTIONS ON BROADCASTING, VOL. 36, NO. 3, SEPTEMBER 1990
[9] HasmahMansor, Muhammad Helmy Abdul Shukor, Siti Sarah Meskam, NurQuraisyiaAqilahMohdRusli,N.SakinahZamery, “Body Temperature Measurement for Remote Health Monitoring System” ,26-27 November 2013, Kuala Lumpur.
:10.22362/ijcert/2018/v5/i2/v5i201
DOI Link : https://doi.org/10.22362/ijcert/2018/v5/i2/v5i201
Download :
  V5I201.pdf
Refbacks : Currently there are no refbacks

 

Investigation of Mining Association Rules on XML Document
Authors : P.M. Gavali, ,
Affiliations : Computer Science and Engineering, D.K.T.E. Society's Textile and Engineering Institute, Ichalkranji, India
Abstract :

af

XML is globally accepted format for sending the data on internet and between different applications which are running on different platforms and architectures. Due to this, the huge amount of data on the internet is in XML. Thus researchers are attracted toward XML to identify interesting findings and patterns from these documents. Many data mining algorithms have been applied to XML including clustering, classification and association rules. In this paper association, rule mining on XML document is studied. This can be used to identify what work is done in the stated field and how we can extend it further in future.
Citation :

af

P.M. Gavali(2018). Investigation of Mining Association Rules on XML Document. International Journal of Computer Engineering In Research Trends, 5(1), 12-15. Retrieved from http://ijcert.org/ems/ijcert_papers/V5I103.pdf
Keywords : XML, Data Mining, Association rules.
References :

af

1.	Chit Nilar Win, Khin Haymar Saw Hla, Mining frequent patterns from XML Data. 
2.	Jun Shin, Juryon Paik, and Ungaro Kim," Mining Association Rules from a Collection of XML Documents using Cross Filtering Algorithm", International Conference on Hybrid Information Technology, 0-7695-2674-8/06,2006
3.	Wu Gongxing, A Study on the Mining Algorithm of Fast Association Rules for the XML Data, Proceedings of the Third International Conference on Web Information Systems Engineering (Workshops)
0-7695-1754-3/02,2002
4.	S. Devi Mahalakshmi, Dr K. Vijayalakshmi, Dr K. Muneeswaran, G.Priyanka," Mining Intensional Information for answering XML-Queries using Tree-based Association Rules Approach",
5.	S.Thangarasu, D.Sasikala, Extracting Knowledge from XML Document Using Tree-based Association Rules, 2014 International Conference on Intelligent Computing Applications, 978-1-4799-3966-4/14,2014
6.	Carlo Combi, Barbara Oliboni, Rosalba Rossato, Querying XML documents by using association rules, Proceedings of the 16th International Workshop on Database and Expert Systems Applications (DEXA05) 1529-4188/05,2005
7.	Laura Irina Rusu, Wenny Rahayu, David Taniar, Extracting Variable Knowledge from Multiversioned XML Documents, Sixth IEEE International Conference on Data Mining - Workshops (ICDMW'06)
0-7695-2702-7/06
8.	Myint Myint Khaing, Nilar Thein, An Efficient Association Rule Mining For XML Data, SICE-ICASE International Joint Conference 2006,5782-5786, Oct. 18-21, 2006 in Bexco, Busan, Korea
9.	Xin-Ye Li, Jin-Sha Yuan, Ying-Hui Kong, Mining Association Rules from XML Data with Index Table, Proceedings of the Sixth International Conference on Machine Learning and Cybernetics, pg.no.3905-3910, Hong Kong, 19-22 August 2007
10.	D. Sasikala, K. Premalatha, Mining association rule from XML Document using modified index table, 2013 International Conference on Computer Communication and Informatics (ICCCI -2013), Jan. 04  06, 2013, Coimbatore, INDIA
11.	Xinwei Wang and Chunjing Cao," Mining Association Rules from Complex and Irregular XML Documents using XSLT and XQuery", International Conference on Advanced Language Processing and Web Information Technology, 978-0-7695-3273-8/08,2008
12.	R.Porkodi, V.Bhuvaneswari, R.Rajesh, T.Amudha," An Improved Association Rule Mining Technique for XML Data Using XQuery and Apriori Algorithm", 2009 IEEE International Advance Computing Conference (IACC 2009),pgno.1510-1514 Patiala, India, 6-7 March 2009
13.	Miss. Ujwal Arjun Bodke, Santosh Kumar, 2015 International Conference on Computing Communication Control and Automation, 978-1-4799-6892-3/15,2015
14.	Ashraf Abazeed, Ali Mamat, Md Nasir Sulaiman, Hamidah Ibrahim, Scalable Approach for Mining Association Rules from Structured XML Data 2009 2nd Conference on Data Mining and Optimization
27-28 October 2009, Selangor, Malaysia.
15.	Md. Sumon Shahriar, Sarawat Anam," Quality Data for Data Mining and Data Mining for Quality Data: A Constraint-Based Approach in XML", 2008 Second International Conference on Future Generation Communication and Networking Symposia, pg.no.47-49.
16.	Sheetal Rathi, C.A Dhote, Vivek Bangera," Speeding up Frequent Itemset Mining Process on XML Data using Graphic Processor", IEEE, 978-1-4799-4236-7/14
17.	Yijun Bei, Gang Chen, Lihua Yu, Feng Shao, Jinxiang Dong, XML Query Recommendation Based On Association Rules, Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, 0-7695-2909-7/07, 2007.
18.	Khalid Iqbal, Sohail Asghar, Simon Fong, A PPDM Model Using Bayesian Network for Hiding Sensitive XML Association Rules, IEEE, 978-1-4577-1539-6/11, 2011.
19.	I.Suganya, N.Velmurugan, Dr.P.Ganeshkumar,XML Query-Answering Support System using Association Mining Technique. 
:10.22362/ijcert/2018/v5/i1/v5i103
DOI Link : https://doi.org/10.22362/ijcert/2018/v5/i1/v5i103
Download :
  V5I103.pdf
Refbacks : Currently there are no ref backs
Review of Rule Quality Measurement: Metrics and Rule Evaluation Models
Authors : Munirah Muslim, E. Winarko,
Affiliations : Computer Science Department, Gadjah Mada University of Yogyakarta, Indonesia
Abstract :

af

A rule-based system is a system based on the set of rules used to make inference knowledge. The system gathers knowledge into the representation of knowledge in the form of a rule. However, the knowledge in the form of the rule is inductive, meaning that the algorithm can construct the rule by studying a limited number of cases and then the induced rule of a limited number of cases and then generalize it to the general reality from time to time. This, of course, has the degree of inaccuracy in expressing reality into knowledge, or an experienced expert builds it but it is not absolute that the knowledge it possesses is 100% accurate or always consistently true from one time-space location to another time-space location. Therefore, the need for a formula that can measure the quality of the resulting rule and assess the consistency of the rule. In this study, we did a review of the ideas of people trying to measure knowledge built inductively by either the algorithm or the experts. These measurements are based on several parameters defined by them according to the underlying assumptions. This review seeks to partially present how ideas to measure the rule as knowledge representation from a varied viewpoint and how people construct evaluation models to assess the resulting regulations either from the experts or human experts as well as those resulting from the induction rule algorithm much developed.
Citation :

af

Munirah Muslim,E. Winarko(2018). Review of Rule Quality Measurement: Metrics and Rule Evaluation Models. International Journal of Computer Engineering In Research Trends, 5(1), 4-11. Retrieved from http://ijcert.org/ems/ijcert_papers/V5I102.pdf
Keywords : Review, Quality, Measurement, Metric, Rule, Evaluation, Model.
References :

af

[1] P. Smyth and R. M. Goodman, “An Information Theoretic Approach to Rule Induction from Databases,” vol. 4, no. 4, pp. 301–316, 1992.
[2] R. Shinghal, “Evaluating the Interestingness of Characteristic Rules,” pp. 263–266, 1996.
[3] S. Dreiseitl, M. Oil, C. Baumgartner, and S. Viterbo, "An evaluation of heuristics for rule ranking," Artif. Intell. Med., vol. 50, no. 3, pp. 175–180, 2010.
[4] J. F. Roddick and M. Spiliopoulou, “A survey of temporal knowledge discovery paradigms and methods,” IEEE Trans. Knowl. Data Eng., vol. 14, no. 4, pp. 750–767, 2002.
[5] F. Provost, “A Survey of Methods for Scaling Up Inductive Algorithms,” vol. 169, pp. 131–169, 1999.
[6] I. Inza, P. Larrañaga, R. Etxeberria, and B. Sierra, “Feature Subset Selection by Bayesian network-based optimization,” vol. 123, pp. 157–184, 2000.
[7] F. Provost, “Tree Induction for Probability-Based Ranking,” vol. 5, pp. 199–215, 2003.
[8] J. Sulzmann and F. Johannes, “An Empirical Comparison of Probability Estimation Techniques for Probabilistic Rules,” no. 2003, pp. 317–331, 2009.
[9] A. A. Freitas, “On rule interestingness measures,” Knowledge-Based Syst., vol. 12, no. March, pp. 309–315, 1999.
[10] K. E. N. Mcgarry, “A survey of interestingness measures for knowledge discovery,” pp. 39–61, 2005.
[11] X. Huynh, F. Guillet, J. Blanchard, and P. Kuntz, “A Graph-based Clustering Approach to Evaluate Interestingness Measures : A Tool and a Comparative Study,” vol. 50, pp. 25–50, 2007.
[12] B. Vaillant, S. Lallich, and P. Lenca, “On the behavior of the generalizations of the intensity of implication : A data-driven comparative study,” vol. 447, pp. 421–447, 2008.
[13] J. Hills, L. M. Davis, and A. Bagnall, “Interestingness Measures for Fixed Consequent Rules,” pp. 68–75, 2012.
[14] P. Flach, N. Lavrac, and B. Zupan, “Rule Evaluation Measures: A Unifying View,” Proc. 9th Int. Work. Inductive Log. Program., pp. 174–185, 1999.
[15] F. Johannes and P. A. Flach, “An Analysis of Rule Evaluation Metrics,” 2003.
[16] D. Christensen, “David Christensen - Measuring Confirmation.pdf.” pp. 437–461, 1999.
[17] S. Greco, R. Słowi, and I. Szcz, “Measures of rule interestingness in various perspectives of confirmation,” vol. 347, pp. 216–235, 2016.
[18] M. Michalak, M. Sikora, and Ł. Wróbel, “Rule Quality Measures Settings in a Sequential Covering Rule Induction Algorithm - an Empirical Approach,” vol. 5, pp. 109–118, 2015.
[19] P. F. Nada Lavrac, Bojan Cestnik, Dragan Gamberger, “Decision Support Through Subgroup Discovery : Three Case Studies and the Lessons Learned,” no. 1994, pp. 115–143, 2004.
[20] D. M. W. Powers, “ROC-ConCert,” pp. 12–15, 2012.
[21] P. Salgado, “Relevance as a new measure of relative importance: of sets of rules,” no. 3, pp. 3770–3777, 2000.
[22] [22] F. Coenen and P. Leng, “An Evaluation of Approaches to Classification Rule Selection,” IEEE Int. Conf. Data Min., pp. 2–5, 2004.
[23] Y. Yao and B. Zhou, “Micro and Macro Evaluation of Classification Rules,” Proc. Seventh IEEE Int. Conf. Cogn. Informatics, ICCI 2008, Stanford Univ. California, USA, 2008.
[24] D. M. W. Powers, “Evaluation: From Precision, Recall And F-Measure To Roc, Informedness, Markedness & Correlation,” vol. 2, no. 1, pp. 37–63, 2011.
[25] H. Abe, S. Tsumoto, M. Ohsaki, and T. Yamaguchi, “Evaluating Learning Algorithms to Construct Rule Evaluation Models Based on Objective Rule Evaluation Indices,” 2007.
[26] H. Abe, S. Tsumoto, M. Ohsaki, and T. Yamaguchi, “Evaluating Learning Algorithms to Support Human Rule Evaluation with
Predicting Interestingness Based on Objective Rule Evaluation Indices,” vol. 282, no. 2008, pp. 269–282, 2008.
[27] H. Abe and S. Tsumoto, “Comparing Accuracies of Rule Evaluation Models to Determine Human Criteria on Evaluated Rule Sets,” pp. 1–7, 2008.
[28] H. Abe and S. Tsumoto, “Rule Evaluation Model as Behavioral Modeling,” pp. 8–15, 2009.
[29] A. Gruca and M. Sikora, "Rule-based functional description of genes – Estimation of the multicriteria rule interestingness measure by the UTA method," Integr. Med. Res., vol. 33, no. 4, pp. 222–234, 2013.
[30] A. Gruca and M. Sikora, “Data- and expert-driven rule induction and filtering framework for functional interpretation and description of gene sets,” pp. 1–14, 2017.
[31] U. Stanczyk, “Weighting and Pruning of Decision Rules,” pp. 106–114, 2016.
[32] K. K. Sethi, D. K. Mishra, and B. Mishra, “Novel Algorithm to Measure Consistency between Extracted Models from Big Dataset and Predicting Applicability of Rule Extraction,” IEEE Trans. Knowl. Data Eng., 2014.
[33] H. Mutluri and P. Sujatha, “Challenges in Big Data using Data Mining Techniques,” Int. J. Comput. Eng. Res. Trends, vol. 2, no. 12, pp. 924–930, 2015.

:10.22362/ijcert/2018/v5/i1/v5i102
DOI Link : http://dx.doi.org/10.22362/ijcert/2018/v5/i1/v5i102
Download :
  V5I102.pdf
Refbacks : Currently there are no refbacks
The quest for the fulfillment of Destiny: A study on Santiago in Paulo Coelho's "Alchemist."
Authors : M. Laxmi Manogna, Dr. G. Mohana Charyulu, Dr. G. Kiran Kumar
Affiliations : K L ( Deemed to be University), Vaddeswaram, Guntur Dist. AP
Abstract :

af

This paper examines the quest for fulfillment of Destiny as it is presented in the book Alchemist written by Paulo Coelho. The modern thinkers explain the concept of human Destiny as self-transcendence. The paper focuses on a theological endeavor within the tradition which Santiago, the protagonist of the book follows. The ethnocentric understanding of human nature is the belief that man was created as of the image of God. Therefore, human life will also be followed and reached to the Destiny in the fruitful relationship. The life of Santiago itself reveals how Paulo Coelho imagines the quest of the human being for achieving the fortune of his expectation.
Citation :

af

M. Laxmi Manogna,Dr. G. Mohana Charyulu and Dr. G. Kiran Kumar(2017). The quest for the fulfillment of Destiny: A study on Santiago in Paulo Coelho's 'Alchemist.'. International Journal of Computer Engineering In Research Trends, 5(1), 1-3. Retrieved from http://ijcert.org/ems/ijcert_papers/V5I101.pdf
Keywords : quest, destiny, human life, God, fortune.
References :

af

1.Coelho, Paulo, The Alchemist Published by HarperCollins, 1998.
2.	Coelho, Paulo. Warrior of the Light: A    Manual, translated from the Portuguese by Margaret Jull Costa. New York, NY: HarperCollins, 2003.
:10.22362/ijcert/2018/v5/i1/v5i101
DOI Link : https://doi.org/10.22362/ijcert/2018/v5/i1/v5i101
Download :
  V5I101.pdf
Refbacks : Currently there are no refbacks

 

Comparative Performance Analysis of Different Data Mining Techniques and Tools Using in Diabetic Disease
Authors : Sarangam Kodati, Dr. R P. Singh,
Affiliations : Department of Computer Science and Engineering, Sri Satya Sai University of Technology and Medical Science, Sehore, Bhopal, Madhya Pradesh, India
Abstract :

af

Data mining means to the process of collecting, searching through, and analyzing a significant amount of data in a database. The most essential and popular data mining methods are classification, association, clustering, prediction or sequential patterns. In health concern businesses, data mining plays a vital role in the early prediction of diseases toughness. This paper explores the early prediction diabetic diabetes using various data mining methods and data mining tools. The dataset has taken 768 instances from PIMA Indian Dataset by determining the accuracy of the data mining techniques in prediction. The analysis proves that Modified J48 Classifier provides the highest comparative durability accuracy than other techniques.
Citation :

af

Sarangam Kodati,Dr. R P. Singh(2017). Comparative Performance Analysis of Different Data Mining Techniques and Tools Using in Diabetic Disease. International Journal of Computer Engineering In Research Trends, 4(12), 556-561. Retrieved from http://ijcert.org/ems/ijcert_papers/V4I1204.pdf
Keywords : Data mining Techniques, Data mining Tools, Diabetic disease, Performance Accuracy
References :

af

1. Han, j. And M. Kamber, Data Mining Concepts, and Techniques. 2006: Morgan Kaufmann Publishers. 2. Lee, I.-N., S.-C. Liao, and M. Embrechts, Data mining techniques applied to medical information. Med. inform, 2000.

2. Obenshain, M.K., Application of Data Mining Techniques to Healthcare Data. Infection Control and Hospital Epidemiology, 2004.

3. Sandhya, J., et al., Classification of Neurodegenerative Disorders Based on Major Risk Factors Employing Machine Learning Techniques. International Journal of Engineering and Technology, 2010. Vol.2, No.4.

4. Gaganjot Kaur, Amit Chhabra, “Improved J48 Classification Algorithm for the prediction of Diabetes”, International Journal of Computer Applications(0975-8887) vol.98 No.22, July 2014. 

5 P. Radha, Dr. B. Srinivasan, “ Predicting Diabetes by consequencing the various Data mining Classification Techniques”, International Journal of Innovative Science, Engineering & Technology, vol. 1 Issue 6, August 2014, pp. 334-339 

6. Mohtaram Mohammadi, Mitra Hosseini, Hamid Tabatabaee, “Using Bayesian Network for the prediction and Diagnosis of Diabetes” , MAGNT Research Report, vol.2(5), pp.892-902. 

7. Sudesh Rao, V. Arun Kumar, “Applying Data mining Technique to predict the diabetes of our future generations”, ISRASE eXplore digital library, 2014. 

8. Veena vijayan, Aswathy Ravikumar, “ Study of Data mining algorithms for prediction and diagnosis of Diabetes Mellitus”, International Journal of Computer Applications (0975-8887) vol. 95-No.17, June 2014 
9. Arwa Al-Rofiyee, Maram Al-Nowiser, Nasebih Al-Mufad, Dr. Mohammed Abdullah AL-Hagery, “Using Prediction Methods in Data mining for Diabetes Diagnosis'http://www.psu.edu

10. K.R Lakshmi, S.Premkumar, “ Utilization of Data mining Techniques for prediction of Diabetes Disease survivability”, International Journal of Scientific & Engineering Research, vol.4 Issue 6, June 2013. 

11. Murat Koklu and Yauz Unal, “ Analysis of a International population of Diabetic patients Databases with Classifiers”, International Journal of Medical,Health,Pharmaceutical and Biomedical Engineering”, vol.7 No.8, 2013. 

12. Rupa Bagdi, Prof. Pramod Patil,” Diagnosis of Diabetes Using OLAP and Data Mining Integration”, International Journal of Computer Science & Communication Networks,Vol 2(3), pp. 314-322. 

13. Ashwinkumar.U.M and Dr. Anandakumar K.R, “Predicting Early Detection of cardiac and Diabetes symptoms using Data mining techniques”, International conference on computer Design and Engineering, vol.49, 2012. 

14. S. Sapna, Dr. A. Tamilarasi and M. Pravin Kumar, “Implementation of Genetic Algorithm in predicting Diabetes”, International Journal of computer science, vol.9 Issue 1, No.3, January 2012. 

15. Manaswini pradhan, Dr. Ranjit kumar sahu, “ predict the onset of diabetes disease using Artificial Neural Network”, “ International Journal of Computer Science & Emerging Technologies, vol.2 Issue 2, April 2011. 

16. Muhammad Waqar Aslam and Asoke Kumar Nandi, “Detection of Diabetes using Genetic Programming”, European Signal Processing Conference (EUSIPCO-2010), ISSN 2076-1465. 

17. Huy Nguyen Anh Pham and Evangelos Triantaphyllou, “ Prediction of Diabetes by Employing New Data 
mining approach which balances Fitting and Generalization Springer 2008. 
:10.22362/ijcert/2017/v4/i12/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I1204.pdf
Refbacks : Currently there are no refbacks
Cancer Detection in Mammograms by Extracting Geometry and Texture Features
Authors : Pallavi P. Jadhav, , Prof. U. A. Nuli,
Affiliations : D.K.T.E. Society’s Textile And Engineering Institute, Ichalkaranji.
Abstract :

af

Breast cancer is one of the most frequently occurring diseases which cause death among women. Masses present in mammogram of breast, primarily indicates breast cancer and it is important to classify them as benign or malignant. Benign and malignant masses differ in geometry and texture characteristics. However, not every geometry and texture feature that is extracted contributes to the improvement of classification accuracy; thus, to select the best features from a set is important. Proposed new system will examine the feature selection methods for mass classification.
Citation :

af

Pallavi P. Jadhav,Prof. U. A. Nuli (2017). Cancer Detection in Mammograms by Extracting Geometry and Texture Features. International Journal of Computer Engineering In Research Trends, 4(12), 552-555. Retrieved from http://ijcert.org/ems/ijcert_papers/V4I1203.pdf
Keywords : Breast cancer, mammograms, Region of Interest (ROI), Feature Extraction
References :

af

[1]	R. Rangayyan, N. Mudigonda, and J. Desautels, “Boundary modeling and shape analysis methods for classification of mam-mographic masses,”  Med. Biol. Eng. Comput., vol. 38, no. 5, pp. 487–496, 2000.R. Nicole, "The Last Word on Decision Theory," J. Computer Vision, submitted for publication. (Pending publication)
[2]	N. Mudigonda, R. Rangayyan, and J. Desautels, “Gradient and texture analysis for the classification of mammographic masses,” IEEE Trans.Med. Imag., vol. 19, no. 10, pp. 1032–1043, Oct. 2000.
[3]	J. Kilday, F. Palmieri, and M. Fox, “Classifying mammographic lesionsusing computerized image analysis,” IEEE Trans. Med. Imag., vol. 12,no. 4, pp. 664–669, Dec. 1993.S.P. Bingulac, “On the Compatibility of Adaptive Controllers,” Proc. Fourth Ann. Allerton Conf. Circuits and Systems Theory, pp. 8-16, 1994. (Conference proceedings)
[4]	S. Pohlman, K. Powell, N. Obuchowski, W. Chilcote, andS. Grundfest-Broniatowski, “Quantitative classification of breast tumors in digitized mammograms,” Med. Phys., vol. 23, no. 8, pp. 1337–1345,Aug. 1996.
[5]	A. Rojas Dominguez and A. Nandi, “Toward breast cancer diagnosis based on automated segmentation of masses in mammograms,”Pattern Recog., vol. 42, no. 6, pp. 1138–1148, Jun. 2009
[6]	B. Sahiner, H. Chan, N. Petrick, M. Helvie, and M. Goodsitt, “Computerized characterization of masses on mammograms: The rubber bandstraightening transform and texture analysis,” Med. Phys., vol. 25, no. 4,pp. 516–526, Apr. 1998.
[7]	M .MeselhyEltoukhy, I. Faye, and B. Belhaouari Samir, “A comparison of wavelet and curvelet for breast cancer diagnosis in digital mammogram,”Comput. Biol. Med., vol. 40, no. 4, pp. 384–391, Apr. 2010.
[8]	]  R. Kohavi and G. H. John, “Wrappers for feature subset selection,” Artif.Intell., vol. 97, no. 1/2, pp. 273–324, Dec. 1997.
[9]	I. Guyon, J. Weston, S. Barnhill, and V. Vapnik, “Gene selection for cancer classification using support vector machines,” Mach. Learn., vol. 46,no. 1, pp. 389–422, 2002.
[10]	P. A. Estévez, M. Tesmer, C. A. Perez, and J. M. Zurada, “Normalized mutual information feature selection,” IEEE Trans. Neural Netw., vol. 20,no. 2, pp. 189–201, Feb. 2009.
[11]	P. A. Mundra and J. C. Rajapakse, “SVM-RFE with MRMR filter for gene selection,” IEEE Trans. NanoBiosci., vol. 9, no. 1, pp. 31–37,Mar. 2010
[12]	H. Peng, F. Long, and C. Ding, “Feature selection based on mutual information criteria of max-dependency, max-relevance, and min-redundancy, ”IEEE Trans. Pattern Anal. Mach. Intell., vol. 27, no. 8, pp. 1226–1238,Aug. 2005.
:10.22362/ijcert/2017/v4/i12/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I1203.pdf
Refbacks : Currently there are no refbacks
NHSKCA: A NEW HEURISTIC FOR SYMMETRIC KEY CRYPTOGRAPHIC ALGORITHM
Authors : Ira Nath, Deepashree Bhattacharyya, Agnisuddha Mandal, Nandini Kundu and Oindrila De
Affiliations : JIS College of Engineering, Kalyani, Nadia, West Bengal, 741235
Abstract :

af

A plain text or clear text is basically any communicating language that human being speaks. A message or plain text can be understood by anybody who knows the language and as long as the message is not codified in any manner. So now we have to use coding scheme to ensure the information is hidden from anyone for whom it is not intended even those who can see the coded data. Cryptography is a method of storing and transmitting data in a particular form so that only those for whom it is intended can read and process it. Cryptography is the practice and study of hiding information. In modern times cryptography is considered as a branch of both mathematics and computer science and is affiliated closely with information theory, computer science and engineering. There are two basic types of cryptography-Symmetric key and asymmetric key cryptography. There are few well known symmetric key algorithms i.e, DES, RSA, MD5, etc. This paper describes cryptography, various symmetric key algorithms in detail and then proposes a new symmetric key algorithm. Algorithms for both encryption and decryption are also provided here. The advantages of this new algorithm are also explained properly.
Citation :

af

Ira Nath,Deepashree Bhattacharyya Agnisuddha Mandal, Nandini Kundu and Oindrila De (2017). NHSKCA: A NEW HEURISTIC FOR SYMMETRIC KEY CRYPTOGRAPHIC ALGORITHM. International Journal of Computer Engineering In Research Trends, 4(12), 547-553. Retrieved from http://ijcert.org/ems/ijcert_papers/V4I1202.pdf
Keywords : Cryptography, Symmetric Key, Plain Text, Security, Asymmetric Key.
References :

af

1.	Debasis Das, U.A. Lanjewar and S.J. Sharma,“The Art of Cryptology: From Ancient Number System to Strange Number System”, IJAIEM, Volume 2, Issue 4, April 2013, ISSN 2319-4847.
2.	David Naccache, “Cryptography and Security: From Theory to Applications”, Springer, 2012.
3.	H.B. Pethe, Dr. S. R. Pande, “An overview of Cryptographic Hash Function M-5 and SHA”, IOSR-JCE, 2016.
4.	Ius Mentis: Law and technology explained, “The MD5 cryptographic hash function”, Oct 1, 2005.
5.	Alok Kumar Kasgar, Mukesh Kumar Dhariwal, NeerajnTantubay, Hina Malviya, “A Review Paper of Message Digest 5 (MD5)”, IJMEMR, Volume1, Issue 4, December 2013, ISSN: 2320-9984 (Online).
6.	Evgeny Milanov, “The RSA Algorithm”, June, 2009.
7.	Avi Kak, “Public-Key Cryptography and the RSA Algorithm”, Lecture Notes on “Computer and Network Security”, February 16, 2017.
8.	William Stallings, “Cryptography and Network Security: Principles and Practices”, Publisher: Prentice Hall, November 16, 2005, Pages-592.
:10.22362/ijcert/2017/v4/i12/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I1202.pdf
Refbacks : Currently there are no refbacks
LDA Based Tea Leaf Classification on the Basis of Shape, Color and Texture
Authors : ANAMIKA SHARMA, PARUL MALHOTRA,
Affiliations : CSE, Sri Sai University ,Palampur, H.P, India
Abstract :

af

Background/Objectives: The presented paper shows a model of leaf segmentation for tea leaf, its seem to be a promising and feasible approach to perform the task of detecting arbitrary shapes in a tea leaf image with a minimum prior. The performance for given image samples was satisfying. Methods/Statistical analysis: Traditional models were very easy to use in but they did not detect boundaries very accurately. On the other hand proposed algorithm was able to detect boundaries well and will be enhanced with image blending to prove the effectiveness of the technique in real applications. Findings: The results have been displayed in the result section with comparison to previous system in terms of area, time and efficiency. Improvements/Applications: In the proposed LDA system accuracy has been improved.
Citation :

af

ANAMIKA SHARMA and PARUL MALHOTRA (2017). LDA Based Tea Leaf Classification on the Basis of Shape, Color and Texture. International Journal of Computer Engineering In Research Trends, 4(12), 543-546. Retrieved from http://ijcert.org/ems/ijcert_papers/V4I1201.pdf
Keywords : Segmentation, LDA, PDE, SVM, RGB
References :

af

1.N. Krishnan, C. Nelson Kennedy Babu, V.V. Joseph Raja pandi anand N. Richard Devaraj, A Fuzzy Image Segmentation using Feed forward Neural Networks with Supervised Learning. Proceedings of the International Conference on Cognition and Recognition.
2.	R. J. Zawadzki, A. R. Fuller, D. F. Wiley, B. Hamann,S. S. Choi, and J. S. Werner, Adaptation of a support vector machine algorithm for segmentation and visualization of retinal structures in volumetric optical coherence tomography data sets.Journal of Biomedical Optics, vol. 12, no. 4, pp. 041 206, 1–8, 2007.
3.	A.R. Fuller, R. J. Zawadzki, S. Choi, D. F. Wiley, J. S. Werner, and B. Hamann, Segmentation of three-dimensional retinal image data. . IEEE Transactions on, vol. 13, no. 6, pp. 1719–1726, 2007	
4.	Jayamala K. Patil, Raj Kumar, “Advances In Image Processing For Detection of Plant Diseases” JABAR,vol. 2(2), pp. 135-141, June-2011.
5.	Mr. Pramod and S. landge , Automatic Detection and Classification of Plant Disease through Image Processing. International Journal of Advanced Research in Computer Science and Software Engineering, Volume 3, Issue 7, ISSN: 2277 128X, 2013.
6.	S. Arivazhagan, R. Newlin Shebiah, S. Ananthi, S. Vishnu Varthini, Detection of unhealthy region ofplant leaves and classification of plant leaf diseases using texture features. CIGR, vol. 15(1), pp. 211-217, March 2013.
7.	Dodla. Likhith Reddy, Dr. D Prathyusha Reddy.” Texture Image Segmentation Based on threshold Techniques. “International Journal of Computer Engineering in Research Trends., vol.4, no.3, pp. 69-75, 2017.
8.	Venkata Srinivasu Veesam, Bandaru Satish Babu.” A Relative Study on the Segmentation Techniques of Image Processing.“International Journal of Computer Engineering in Research Trends., vol.4, no.5, pp. 155-160, 2017.
:10.22362/ijcert/2017/v4/i12/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I1201.pdf
Refbacks : Currently there are no refbacks

 

A Survey on Taxonomy learning using Graph-based Approach
Authors : Diksha R. Kamble, Krishna S. Kadam ,
Affiliations : Dept. of Computer Science and Engineering, DKTE’s TEI, Ichalkaranji (An Autonomous Institute), 416115, India.
Abstract :

af

Taxonomy learning is an important task for developing successful applications as well as knowledge obtaining, sharing and classification. The manual construction of the domain taxonomies is a time-consuming task. To reduce the time and human effort will build a new taxonomy learning approach named as TaxoFinder. TaxoFinder takes three steps to automatically build the taxonomy. First, it identifies the concepts from a domain corpus. Second, it builds CGraphs where a node represents each of such concepts and an edge represents an association between nodes. Each edge has a weight indicating the associative strength between two nodes. Lastly TaxoFinder derives the taxonomy from the graph using analytic graph algorithm. The main aim of TaxoFinder is to develop the taxonomy in such a way that it covers the overall maximum associative strengths among the concepts in the graph to build the taxonomy. In this evaluation, compare TaxoFinder with existing subsumption method and show that TaxoFinder is an effective approach and give a better result than subsumption method.
Citation :

af

Diksha R. Kamble and Krishna S. Kadam (2017). A Survey on Taxonomy learning using Graph-based Approach. International Journal of Computer Engineering In Research Trends, 4(11), 539-542. Retrieved from http://ijcert.org/ems/ijcert_papers/V4I1113.pdf
Keywords : Taxonomy learning, ontology learning, TaxoFinder, concept taxonomy, concept graphs, similarity, associative strength
References :

af

[1]	M.A.Hearst, “Automatic acquisition of hyponyms from large text corpora,” in Proc.14th Conf. Comput. Linguistics, 1992, vol. 2,pp. 539–545
[2]	F.M.Suchanek, G.Ifrim, and G.Weikum, “Combining linguistic and statisticalanalysis to extract relations from web documents,”in Proc. 12th ACM SIGKDD Int. Conf. Knowl. Discovery Data Mining, 2006, pp. 712–717.
[3]	E.-A. Dietz, D. Vandic, and F. Frasincar, “TaxoLearn: A semantic approach to domain taxonomy learning,” in Proc. IEEE/WIC/ACM Int. Joint Conf. Web Intell. Intell. Agent Technol., 2012, pp. 58–65.
[4]	W. Wang, P. Mamaani Barnaghi, and A. Bargiela,“Probabilistic topic models for learning terminological ontologies,” IEEE Trans.Knowl. Data Eng., vol. 22, no. 7, pp. 1028–1040, Jul. 2010.
[5]	Z. Kozareva and E. Hovy, “A semi-supervised method to learn and construct taxonomies using the web,” in Proc. Conf. Empirical Methods Natural Language Process., 2010, pp. 1110–1118.
[6]	P. Velardi, S. Faralli, and R. Navigli, “OntoLearn Reloaded: A graph-based algorithm for taxonomy induction,” Comput. Linguistics,vol. 39, no. 3, pp. 665–707, 2013.
[7]	K. Meijer, F. Frasincar, and F. Hogenboom, “A semantic approachfor extracting domain taxonomies from text,” Decision SupportSyst., vol. 62, pp. 78–93, 2014.
[8]	Y.-B. Kang, P. D. Haghighi, and F. Burstein, “CFinder: An Intelligent Key Concept Finder from Text for Ontology Development,”Expert Syst. Appl., vol. 41, no. 9, pp. 4494–4504, 2014.
[9]	Yong-Bin Kang, Pari Delir Haghigh, and Frada Burstein,”TaxoFinder: A graph-based approach for taxonomy learning.” Vol.28, no 2,2016.
[10]	Satish Kumar, Sujan Babu Vadde, ” Typicality Based Content-Boosted Collaborative Filtering  Recommendation Framework. “International Journal of Computer Engineering in Research Trends., vol.2, no.11, pp. 809-813, 2015.
[11]	Y.Usha Sree,P.Ragha Vardhani.” Pattern Finding in Large Datasets with Big Data Analytics Mechanism. “International Journal of Computer Engineering in Research Trends., vol.2, no.5, pp. 359-364, 2015.
:10.22362/ijcert/2017/v4/i11/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I1113.pdf
Refbacks : Currently there are no ref backs
Various Mechanisms for understanding Short Text
Authors : Pournima G. Kamble, S. B. Bhagate ,
Affiliations : Dept. of Computer Science and Engineering, DKTE’s TEI, Ichalkaranji (An Autonomous Institute), 416115, India.
Abstract :

af

Now a day’s all people use short text in real life for communication and chatting purpose. Short texts are also uses in news titles, social posts, tweets, conversations, keywords, search queries. Short text understanding is an ambiguous process in opinions, deals, events and private messages. The short text is produce that contain social posts, conversations, keywords and news titles which are limited context and represent the insufficient information or meaning of the text. As short text has more than one meaning, they are difficult to understand as they are ambiguous and noisy. The term can be either single or multi-word. Short texts do not contain sufficient data. Some short texts have unique characteristics. So these short texts are difficult to handle. It required better understand the short text. Semantic analysis is essential to understand the short text accurately. Tasks such as segmentation, part-of-speech tagging, and concept labeling are used for semantic analysis. Conduct short text uses in real life data. The prototype system is built and used to understand the short text. These systems provide the semantic knowledge from knowledge base and collection of written words that are automatically harvest. Creating construction of co-occurrence network showing to better understand for short text.
Citation :

af

Pournima G. Kamble and S. B. Bhagate (2017). Various Mechanisms for understanding Short Text. International Journal of Computer Engineering In Research Trends, 4(11), 519-523. Retrieved from http://ijcert.org/ems/ijcert_papers/V4I1109.pdf
Keywords : Short Text, Part of speech tagger, Semantics, text segmentation, Term Extraction
References :

af

[1] Xiaojiang Lei, Xueming Qian, Member, IEEE, and Guoshuai Zhao, “Rating Prediction based on Social Sentiment from Textual Review”, IEEE Trans. VOL. 18, NO. 9, 2016.
[2] K. H. L. Tso-Sutter, L. B. Marinho, L. Schmidt-Thieme, “Tag-aware recommender systems by fusion of collaborative filtering algorithms”, in Proceedings of the 2008 ACM symposium on Applied computing, 2008, pp. 1995-1999.
[3] X. Qian, H. Feng, G. Zhao, and T. Mei, “Personalized recommendation combining user interest and social circle”, IEEE Trans. Knowledge and data engineering. 2014, pp. 1763-1777.
[4] X. Yang, H. Steck, and Y. Liu, “Circle-based recommendation in online social networks”, in Proc. 18th ACM
SIGKDD Int. Conf. KDD, New York, NY, USA, Aug. 2012, pp. 1267–1275.
[5] M. Jiang, P. Cui, R. Liu, Q. Yang, F. Wang, W. Zhu, and S. Yang, “Social contextual recommendation”, in proc. 21st ACM Int. CIKM, 2012, pp. 45-54.
[6] H. Feng, and X. Qian, “Recommendation via user‟s personality and social contextual”, in Proc. 22nd ACM international conference on information & knowledge management. 2013, pp. 1521-1524.
[7] F. Li, N. Liu, H. Jin, K. Zhao, Q. Yang, X. Zhu, “Incorporating reviewer and product information for review rating prediction,” in Proceedings of the Twenty-Second international joint conference on Artificial Intelligence, 2011, pp. 1820-1825.
[8] G. Ganu, N. Elhadad, A Marian, “Beyond the stars: Improving rating predictions using Review text content”, in 12th International Workshop on the Web and Databases (WebDB 2009). pp. 1-6.
[9] Y. Ren, J. Shen, J. Wang, J. Han, and S. Lee, “Mutual Verifiable Provable Data Auditing in Public Cloud Storage”, Journal of Internet Technology, vol. 16, no. 2, 2015, pp. 317-323.
[10] Y. Zhang, G. Lai, M. Zhang, Y. Zhang, Y. Liu, S. Ma, “Explicit factor models for explainable recommendation based on phrase-level sentiment analysis”, in proceedings of the 37th international ACM SIGIR conference on Research & development in information retrieval, 2014.
[11] X. Lei, and X. Qian, “Rating prediction via exploring service reputation”, 2015 IEEE 17th International Workshop on Multimedia Signal Processing (MMSP), Oct 19-21, 2015, Xiamen, China. pp.1-6.
[12] B. Sarwar, G. Karypis, J. Konstan, and J. Reidl, “Item-based collaborative filtering recommendation algorithms”, in Proc. 10th International Conference on World Wide Web, 2001, pp. 285-295.
[13] K. H. L. Tso-Sutter, L. B.Marinho, L. Schmidt-Thieme, “Tag-aware recommender systems by fusion of collaborative filtering algorithms”, in Proceedings of the 2008 ACM symposium on Applied computing, 2008, pp. 1995-1999.
[14] R. Salakhutdinov, and A. Mnih, “Probabilistic matrix factorization”, in NIPS, 2008.
[15] X. Qian, H. Feng, G. Zhao, and T. Mei, “Personalized recommendation combining user interest and social circle”, IEEE Trans. Knowledge and data engineering. 2014, pp. 1763-1777.
[16] L. Qu, G. Ifrim, G. Weikum, “The bag-of-opinions method for review rating prediction from sparse text patterns”, in Proc. 23rd International Conference on Computational Linguistics, 2010, pp. 913–921.
[17] K. Zhang, Y. Cheng, W. Liao, A. Choudhary, “Mining millions of reviews: a technique to rank products based on importance of reviews”, in Proceedings of the 13th International Conference on Electronic Commerce, Aug. 2011, pp. 1-8.
[18] B. Pang, Bo, L. Lee, and S. Vaithyanathan, “Thumbs up? Sentiment classification using machine learning techniques”, in Proc. EMNLP, 2002, pp. 79-86.
[19] D. Tang, Q. Bing, T. Liu, “Learning semantic representations of users and products for document level sentiment classification”, in Proc. 53th Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing, Beijing, China, July 26-31, 2015, pp. 1014–1023.
[20] T. Nakagawa, K. Inui, and S. Kurohashi, “Dependency tree-based sentiment classification using CRFs with
Hidden Variables”, NAACL, 2010, pp.786-794.
[21] Sunil B. Mane, Kruti Assar, Priyanka Sawant, & Monika Shinde,” Product Rating using Opinion Mining” International Journal of Computer Engineering In Research Trends., vol.4, no.5, pp. 161-168, 2017.
[22] K.Arun A.Srinagesh and M.Ramesh, ”Twitter Sentiment Analysis on Demonetization tweets in India Using R language. “International Journal of Computer Engineering in Research Trends., vol.4, no.6, pp. 252- 258, 2017.
[23] TekurVijetha, M.SriLakshmi and Dr.S.PremKumar,” Survey on Collaborative Filtering and content-Based Recommending. “International Journal of Computer Engineering in Research Trends., vol.2, no.9, pp. 594- 599, 2015.
[24] N.Satish Kumar, Sujan Babu Vadde, ” Typicality Based Content-Boosted Collaborative Filtering Recommendation Framework. “International Journal of Computer Engineering in Research Trends., vol.2, no.11, pp. 809-813, 2015.
[25] D.Ramanjaneyulu,U.Usha Rani,”In Service Oriented MSN Providing Trustworthy Service Evaluation. “International Journal of Computer Engineering in Research Trends., vol.2, no.12, pp. 1192-1197, 2015.
:10.22362/ijcert/2017/v4/i11/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I1109.pdf
Refbacks : Currently there are no refbacks
Survey on: Prediction of Rating based on Social Sentiment
Authors : Milind M. Sutar, Tanveer I. Bagban,
Affiliations : Dept. of Computer Science and Engineering, DKTE’s TEI, Ichalkaranji (An Autonomous Institute), 416115, India.
Abstract :

af

Nowadays e-commerce services have made the lifestyle very easy and fast, and now it has also become more popular. E-commerce market has grown very large. A large number of venders and products are available on e-commerce. Many questions and confusion arise when we buy e-commerce services/products. People read a product review, when they need to decide whether to purchase a product or not, then the poll of others become important. The opinion of others review makes an effect on user decision. Factors like purchase records, geographical location and their categories are taken into account in the traditional recommended system (RS). The prediction accuracy can be improved in a recommended system by systems Sentiment-based rating prediction method (RPS) approach. In textual reviews, each user’s sentiment is calculated on items and user sentimental approach is proposed. Interpersonal sentimental influence is considered along with users own sentimental attributes. Then items reputation is concluded by customer’s comprehensive evaluation. To make accurate rating prediction three factors are fused together such as user sentiment similarity, interpersonal sentimental influence, and item’s reputation similarity. Performance evaluation is measure based on these three sentimental factors on the dataset collected from Yelp. Experimental results show that user preference can be characterized by the sentiment from text review and it can improve the performance of recommendation system.
Citation :

af

Milind M. Sutar and Tanveer I. Bagban (2017). Survey on: Prediction of Rating based on Social Sentiment. International Journal of Computer Engineering In Research Trends, 4(11), 533-538. Retrieved from http://ijcert.org/ems/ijcert_papers/V4I1112.pdf
Keywords : Item reputation, Reviews, Rating prediction, Recommender system, Sentiment influence, User sentiment, Sentiment analysis.
References :

af

[1] Xiaojiang Lei, Xueming Qian, Member, IEEE, and Guoshuai Zhao, “Rating Prediction based on Social Sentiment from Textual Review”, IEEE Trans. VOL. 18, NO. 9, 2016.
[2] K. H. L. Tso-Sutter, L. B. Marinho, L. Schmidt-Thieme, “Tag-aware recommender systems by fusion of collaborative filtering algorithms”, in Proceedings of the 2008 ACM symposium on Applied computing, 2008, pp. 1995-1999.
[3] X. Qian, H. Feng, G. Zhao, and T. Mei, “Personalized recommendation combining user interest and social circle”, IEEE Trans. Knowledge and data engineering. 2014, pp. 1763-1777.
[4] X. Yang, H. Steck, and Y. Liu, “Circle-based recommendation in online social networks”, in Proc. 18th ACM
SIGKDD Int. Conf. KDD, New York, NY, USA, Aug. 2012, pp. 1267–1275.
[5] M. Jiang, P. Cui, R. Liu, Q. Yang, F. Wang, W. Zhu, and S. Yang, “Social contextual recommendation”, in proc. 21st ACM Int. CIKM, 2012, pp. 45-54.
[6] H. Feng, and X. Qian, “Recommendation via user‟s personality and social contextual”, in Proc. 22nd ACM international conference on information & knowledge management. 2013, pp. 1521-1524.
[7] F. Li, N. Liu, H. Jin, K. Zhao, Q. Yang, X. Zhu, “Incorporating reviewer and product information for review rating prediction,” in Proceedings of the Twenty-Second international joint conference on Artificial Intelligence, 2011, pp. 1820-1825.
[8] G. Ganu, N. Elhadad, A Marian, “Beyond the stars: Improving rating predictions using Review text content”, in 12th International Workshop on the Web and Databases (WebDB 2009). pp. 1-6.
[9] Y. Ren, J. Shen, J. Wang, J. Han, and S. Lee, “Mutual Verifiable Provable Data Auditing in Public Cloud Storage”, Journal of Internet Technology, vol. 16, no. 2, 2015, pp. 317-323.
[10] Y. Zhang, G. Lai, M. Zhang, Y. Zhang, Y. Liu, S. Ma, “Explicit factor models for explainable recommendation based on phrase-level sentiment analysis”, in proceedings of the 37th international ACM SIGIR conference on Research & development in information retrieval, 2014.
[11] X. Lei, and X. Qian, “Rating prediction via exploring service reputation”, 2015 IEEE 17th International Workshop on Multimedia Signal Processing (MMSP), Oct 19-21, 2015, Xiamen, China. pp.1-6.
[12] B. Sarwar, G. Karypis, J. Konstan, and J. Reidl, “Item-based collaborative filtering recommendation algorithms”, in Proc. 10th International Conference on World Wide Web, 2001, pp. 285-295.
[13] K. H. L. Tso-Sutter, L. B.Marinho, L. Schmidt-Thieme, “Tag-aware recommender systems by fusion of collaborative filtering algorithms”, in Proceedings of the 2008 ACM symposium on Applied computing, 2008, pp. 1995-1999.
[14] R. Salakhutdinov, and A. Mnih, “Probabilistic matrix factorization”, in NIPS, 2008.
[15] X. Qian, H. Feng, G. Zhao, and T. Mei, “Personalized recommendation combining user interest and social circle”, IEEE Trans. Knowledge and data engineering. 2014, pp. 1763-1777.
[16] L. Qu, G. Ifrim, G. Weikum, “The bag-of-opinions method for review rating prediction from sparse text patterns”, in Proc. 23rd International Conference on Computational Linguistics, 2010, pp. 913–921.
[17] K. Zhang, Y. Cheng, W. Liao, A. Choudhary, “Mining millions of reviews: a technique to rank products based on importance of reviews”, in Proceedings of the 13th International Conference on Electronic Commerce, Aug. 2011, pp. 1-8.
[18] B. Pang, Bo, L. Lee, and S. Vaithyanathan, “Thumbs up? Sentiment classification using machine learning techniques”, in Proc. EMNLP, 2002, pp. 79-86.
[19] D. Tang, Q. Bing, T. Liu, “Learning semantic representations of users and products for document level sentiment classification”, in Proc. 53th Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing, Beijing, China, July 26-31, 2015, pp. 1014–1023.
[20] T. Nakagawa, K. Inui, and S. Kurohashi, “Dependency tree-based sentiment classification using CRFs with
Hidden Variables”, NAACL, 2010, pp.786-794.
[21] Sunil B. Mane, Kruti Assar, Priyanka Sawant, & Monika Shinde,” Product Rating using Opinion Mining” International Journal of Computer Engineering In Research Trends., vol.4, no.5, pp. 161-168, 2017.
[22] K.Arun A.Srinagesh and M.Ramesh, ”Twitter Sentiment Analysis on Demonetization tweets in India Using R language. “International Journal of Computer Engineering in Research Trends., vol.4, no.6, pp. 252- 258, 2017.
[23] TekurVijetha, M.SriLakshmi and Dr.S.PremKumar,” Survey on Collaborative Filtering and content-Based Recommending. “International Journal of Computer Engineering in Research Trends., vol.2, no.9, pp. 594- 599, 2015.
[24] N.Satish Kumar, Sujan Babu Vadde, ” Typicality Based Content-Boosted Collaborative Filtering Recommendation Framework. “International Journal of Computer Engineering in Research Trends., vol.2, no.11, pp. 809-813, 2015.
[25] D.Ramanjaneyulu,U.Usha Rani,”In Service Oriented MSN Providing Trustworthy Service Evaluation. “International Journal of Computer Engineering in Research Trends., vol.2, no.12, pp. 1192-1197, 2015.
:10.22362/ijcert/2017/v4/i11/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I1112.pdf
Refbacks : Currently there are no refbacks
Survey on Tag Based Image Search
Authors : Snehal N. Paraj, Suresh K. Shirgave,
Affiliations : Dept. of Computer Science and Engineering, DKTE’s TEI, Ichalkaranji (An Autonomous Institute), 416115, India.
Abstract :

af

Now a day’s Flicker, Facebook is the popular social media websites. These sites are useful to the user to uploading their photos with free tags. There is need to develop a tag-based image search engine to find out the user-oriented images which are spread over the internet. The social re-ranking method is used for tag-based image search. The main goal is sorting the images according to their semantic information, social views and visual information. Each user uploads many images with different tags. The initial results are based on photos or images uploaded by different users. So first sort these images using the inter-user re-ranking method. Users that have higher uploaded images concerning the given query rank higher. Intra user re-ranking sorts these images based on ranked user set and find out related images from each user’s image set. The system gives better results using inverted index structure, visual feature, social views and semantic feature.
Citation :

af

Snehal N. Paraj and Suresh K. Shirgave (2017). Survey on Tag Based Image Search. International Journal of Computer Engineering In Research Trends, 4(11), 529-532. Retrieved from http://ijcert.org/ems/ijcert_papers/V4I1111.pdf
Keywords : Social media, Tag based Image Search, Social views, Image Search, Re-ranking, Retrieval
References :

af

[1] D. Liu, X. Hua, L. Yang, M. Wang, and H. Zhang. Tag ranking. Proceedings of the IEEE International Conference on World Wide Web, 2009: 351-360.
[2] M. Wang, K. Yang, X. Hua, and H. Zhang. Towards relevant and diverse search of social images. IEEE Transactions on Multimedia, 12(8):829-842, 2010.
[3] G. Agrawal, R. Chaudhary. Relevancy tag ranking. In Computer and Communication Technology, pp. 169-173, IEEE, 2011.
[4] L. Chen, D. Xu, I. Tsang. Tag-based image retrieval improved by augmented features and group-based refinement. Multimedia, IEEE
Transactions on, 14(4), 1057-1067, 2012.
[5] L. Wu, R. Jin. Tag completion for image retrieval. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 35(3), 716-727, 2013.
[6] L. Chen, S. Zhu, Z. Li. Image retrieval via improved relevance ranking. In Control Conference, pp. 4620-4625, IEEE, 2014.
[7] X. Qian, D. Hua, Y. Tang, and T. Mei, “social image tagging with diverse semantics”, IEEE Trans. Cybernetics, vol.44, no. 12, 2014, pp. 2493-2508.
[8] XuemingQian, Yisi Zhao, Junwei Han: Image Location Estimation by Salient Region Matching. IEEE Transactions on Image Processing 24(11): 4348-4358 (2015)
[9] X.Qian, D. Lu, X. Liu, “Tag based image retrieval by user-oriented ranking”. Proceedings of International Conference on Multimedia Retrieval.ACM, 2015.
[10] 10. X. Qian, y. Xue, Y. Tang, X. Hou.”Landmark Summarization with Diverse Viewpoints”, IEEE Trans. Circuits and Systems for Video Technology, 2015
[11] 11. Xueming Qian, Dan Lu, Xiaoxiao Liu. Tag Based Image Search by Social Re-ranking. IEEE Transactions on, Multimedia 2016.
[12] Ajin P Thomas, Sruthi P.S, Jerry Rachel Jacob, Vandana V Nair, Reeba R,‖ Survey on Different Applications of Image Processing.‖ International Journal of Computer Engineering In Research Trends.,vol.4,no.2,pp. 13-19,2017.
[13] Trisha Chakraborty, Nikita Nalawade, Abhishri Manjre, Akanksha Sarawgi, Pranali P Chaudhari,‖ Review of Various Image Processing Techniques for Currency Note Authentication.‖ International Journal of Computer Engineering In Research Trends.,vol.3,no.3,pp. 119-122,2016.
[14] Gunjan, Er. Madan Lal,‖ Investigation of Various Image Steganography Techniques in Spatial Domain.‖ International Journal of Computer Engineering In Research Trends., vol.3,no.6,pp. 347-351,2016.
[15] G.Prasanthi, A.Somasekhar,‖ Anti-Theft Tracking and Controlling Of Vehicle According Us.‖ International Journal of Computer Engineering In Research Trends., vol.2, no.12, pp. 898-903, 2015.
:10.22362/ijcert/2017/v4/i11/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I1111.pdf
Refbacks : Currently There are no refbacks
Relevance Feature Search for Text Mining: A Survey
Authors : Rekha R. Kamble, Dattatraya V. Kodavade,
Affiliations : Dept. of Computer Science and Engineering, DKTE’s TEI, Ichalkaranji (An Autonomous Institute), 416115, India.
Abstract :

af

To determine the quality of user searched documents is a huge challenge in discovering relevance feature. To search the text, document, image, etc. approximately user want relevant features. The techniques earlier used where term based and pattern based. These days clustering methods like partition based, density based and hierarchical is used along with different feature selection method. Extracting terms from the training set for describing relevant features is known as the term-based approach. Low-level support problem is solved by partition based text mining, but it suffers from a large number of noise patterns. Information content in documents is identified by frequent sequential patterns and sequential patterns in the text documents and the useful features for text mining are extracted from this. Extracted terms are classified into three type’s positive terms, general terms and negative terms. To deploy high-level features over low level features positive and negative patterns in text documents are discovered in the present paper.
Citation :

af

Rekha R. Kamble and Dattatraya V. Kodavade (2017). Relevance Feature Search for Text Mining: A Survey. International Journal of Computer Engineering In Research Trends, 4(11), 524-528. Retrieved from http://ijcert.org/ems/ijcert_papers/V4I1110.pdf
Keywords : Text mining, text feature extraction, text classification
References :

af

[1]	Y. Li, A. Algarni, and N. Zhong, “Mining positive and negative patterns for relevance feature discovery,” in Proc. ACM SIGKDD Knowl. Discovery Data Mining, 2010, pp. 753–762.
[2]	N. Zhong, Y. Li, and S.-T. Wu, “Effective pattern discovery for text mining,” in IEEE Trans. Knowl. Data Eng., vol. 24, no. 1, pp. 30–44, Jan. 2012.
[3]	Z. Zhao, L. Wang, H. Liu, and J. Ye, “On similarity preserving feature selection,” in IEEE Trans. Knowl. Data Eng., vol. 25, no. 3, pp. 619–632, Mar. 2013.
[4]	YueLi,, Arif ”Relevance feature discovery for text mining” IEEE transaction on knowledge and data engineering,vol.27,no.6,  pp.1656-1669, june2015.
[5]	N. Azam and J. Yao, “Comparison of term frequency and document frequency based feature selection metrics in text categorization,”Expert Syst. Appl., vol. 39, no. 5, pp. 4760–4768,2012.
[6]	X. Li and B. Liu, “Learning to classify texts using positive andunlabeled data,” in Proc. 18th Int. Joint Conf. Artif. Intell., 2003,pp. 587–592.
[7]	Y. Li, A. Algarni, S.-T. Wu, and Y. Xue, “Mining negative relevancefeedback for information filtering,” in Proc. Web Intell. Intell.Agent Technol., 2009, pp. 606–613.
[8]	G. Salton and C. Buckley, “Term-weighting approaches in automatictext retrieval,” in Inf. Process. Manage., vol. 24, no. 5,pp. 513–523, Aug. 1988.
[9]	The Porter Stemmer home page (with the original paper and code): http://www.tartarus.org/~martin/PorterStemmer/ 988.
[10]	K.Arun  .SrinageshandM.Ramesh,”Twitter Sentiment Analysis on Demonetization tweets in India Using R language.”International Journal of Computer Engineering in Research Trends., vol.4, no.6, pp. 252- 258, 2017.
[11]	TekurVijetha, M.SriLakshmi andDr.S.PremKumar,”Survey on Collaborative Filtering and content-Based Recommending.”International Journal of Computer Engineering in Research Trends., vol.2, no.9, pp. 594- 599, 2015.
[12]	N.Satish Kumar, SujanBabuVadde,”Typicality Based Content-BoostedCollaborative Filtering RecommendationFramework.”International Journal of Computer Engineering in Research Trends., vol.2, no.11, pp. 809-813, 2015
[13]	B.Kundan,N.Poorna Chandra Rao and DrS.PremKumar,”Investigation on Privacy and Secure content of location based Queries.”International Journal of Computer Engineering in Research Trends., vol.2, no.9, pp. 543-546, 2015.
:10.22362/ijcert/2017/v4/i11/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I1110.pdf
Refbacks : Currently there are no refbacks
A Survey on Keyword Interrogation Implication on Document Vicinity Based on Location
Authors : Akshay A. Bhujugade, Dattatraya V. Kodavade ,
Affiliations : A Survey on Keyword Interrogation Implication on Document Vicinity Based on Location
Abstract :

af

Keyword suggestions are the basic feature of the search engine and it accesses relevant information. The naive user doesn’t know how to express their queries; keyword suggestion in web search assists users to access relevant information without any prior knowledge of how to express in queries. The keyword suggestion module can use the current location of a user and retrieve documents which are near to user location. The Euclidean distance is measured for user location and the documents locations. Accordingly the edge weight adjustment is done referring initial K-D graph. The keyword-document graph is used to map the keyword queries and the spatial distance between the resulting documents and the user location. The graph is browsed in random walk with restart, for calculating the highest score for better keyword query suggestion. The paper discusses techniques for the keyword suggestions and also about location-aware keyword query suggestion framework and improved partition based algorithm.
Citation :

af

Akshay A. Bhujugade and Dattatraya V. Kodavade (2017). A Survey on Keyword Interrogation Implication on Document Vicinity Based on Location. International Journal of Computer Engineering In Research Trends, 4(11), 514-518. Retrieved from http://ijcert.org/ems/ijcert_papers/V4I1108.pdf
Keywords : Query suggestion, Document proximity, spatial databases.
References :

af

[1]	Shuyao Qi, Dingming Wu, and Nikos Mamoulis “Location Aware Keyword Query Suggestion Based on Document Proximity,” IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, VOL. 28, NO. 1, JANUARY 2016.
[2]	D. Wu, M. L. Yiu, and C. S. Jensen, “Moving spatial keyword queries: Formulation, methods, and analysis,” ACM Trans. Database Syst., vol. 38, no. 1, pp. 7:1–7:47, 2013. 
[3]	Y. Lu, J. Lu, G. Cong, W. Wu, and C. Shahabi, “Efficient algorithms and cost models for reverse spatial-keyword k-nearest neighbor search,” ACM Trans. Database Syst., vol. 39, no. 2, pp. 13:1–13:46, 2014. 
[4]	R. Baeza-Yates, C. Hurtado, and M. Mendoza, “Query recommendation using query logs in search engines”, in Extending Database Technology, pp.588–596, 2004. 
[5]	P. Berkhin, “Bookmark-coloring algorithm for personalized pagerank computing,” Internet Math., vol. 3, pp. 41–62, 2006. 
[6]	 N. Craswell and M. Szummer, “Random walks on the click graph,” in Proc. 30th Annu. Int. ACM SIGIR Conf. Res. Develop. Inf. Retrieval , pp. 239–246, 2007. 
[7]	 H. Cao, D. Jiang, J. Pei, Q. He, Z. Liao, E. Chen, and H. Li, “Context-aware query suggestion by mining click-through and session data,” in Proc. 14th ACM SIGKDD Int. Conf. Knowl. Discovery Data Mining, pp. 875–883,2008.
[8]	M. P. Kato, T. Sakai, and K. Tanaka, “When do people use query suggestion Inf. Retr., vol. 16, no. 6, pp. 725–746, 2013.
[9]	H. Tong, C. Faloutsos, and J.-Y. Pan, “Fast random walk with restart and its applications,” in Proc. 6th Int. Conf. Data Mining, pp. 613–622, 2006.
[10]	N. Craswell and M. Szummer, “Random walks on the click graph,” in Proc. 30th Annu. Int. ACM SIGIR Conf. Res. Develop. Inf. Retrieval, pp. 239–246, 2007.
[11]	Y. Fujiwara, M. Nakatsuji, M. Onizuka, and M. Kitsuregawa, “Fast and exact top-k search for random walk with restart,” Proc. VLDB Endowment, vol. 5, no. 5, pp. 442–453, Jan. 2012. 
[12]	V. Swathi ,D. Saidulu , B. Chandrakala,” Enabling Secure and Effective Spatial Query Processing on the Cloud using Forward Spatial Transformation,” International Journal of Computer Engineering In Research Trends.,vol.4,no.7,pp.301-307, July2017.
:10.22362/ijcert/2017/v4/i11/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I1108.pdf
Refbacks : Currently There are no refbacks
APPLICATION OF FACTS TECHNOLOGY TO POWER SYSTEM PROTECTION IN THE NIGERIAN 330kV NETWORK USING GENETIC ALGORITHM
Authors : J. M ALOH, U. C OGBUEFI, V. C MADUEME
Affiliations : ELECTRICAL/ELECTRONIC ENGINEERING DEPARTMENT, FACULTY OF ENGINEERING AND TECHNOLOGY, FEDERAL UNIVERSITY, NDUFU ALIKE IKWO, EBONYI STATE, NIGERIA
Abstract :

af

This paper focused on Fault current limitation in the Nigerian 330kV Power Network. The strategy adopted is the use of a genetic algorithm to optimize the proportional integral (PI) control parameters of the Unified Power Flow Controllers (UPFC). Also, the SIMULINK model of the Nigerian 330kV system was developed. Then, the result from the simulation carried out proved the versatility of UPFC on fault current limitation in the power system when the PI parameter is optimized using genetic algorithm. This indicates that the UPFC achieved an effective average of 59.23% fault current limitation. The result is shown to have high impact for protection of critical assets within the power system such as circuit breakers. At a fault impedance of 0.0001Ω, the UPFC provided a 45.81% protection margin for the type of high voltage circuit breakers used in the 330kV system.
Citation :

af

J. M ALOH,U. C OGBUEFI and V. C MADUEME (2017). APPLICATION OF FACTS TECHNOLOGY TO POWER SYSTEM PROTECTION IN THE NIGERIAN 330kV NETWORK USING GENETIC ALGORITHM. International Journal of Computer Engineering In Research Trends, 4(11), 500-513. Retrieved from http://ijcert.org/ems/ijcert_papers/V4I1107.pdf
Keywords : Fault Current Limitation, Genetic Algorithm, Protection, Unified Power Flow Controller and Proportional Integral.
References :

af

[1] Heresh Seyedi and Barzan Tabe: “Appropriate placement of fault current limiting reactors in different HV substation arrangement” Circuits and systems, Vol. 3, pp. 252 -262, 2012.
[2] A.D Filomena, M. Reswner, R.H. Salim and A.S. Bretas “Distribution systems fault Analysis considering fault resistance estimation” International Journal of Electrical Power and Energy Systems, Vol. 33  No. 2, pp. 1326-1335, 2011.
[3] J. Schabbach, “Short-Circuit Currents” second edition, published by the Institution of Engineering and Technology (IET). London, UK.Vol. 3, pp. 230-236, June 2008.
[4] T. Roininen, C.E solver, H. Nordi, A. Bosma, P. Jonsson and A. Alfredsson, “ ABB Live Tank Circuit Breakers Application Guide” www.abb.com, pp. 1-4, 2006.
[5] Song HAN, Xhe-yan MAO and Young Chang “A Study on modeling of High-voltage short circuit current limiter in Electromechanical Transient Simulation”. International conference on power system technology, pp. 1-10, 2010. 
[6] B.W. Lee, J. Sim, K. B. Park and I.S Oh. “Practical Application issues of super conducting salt current limiters for Electric power systems”. IEEE Transactions on Applier super conducting, Vol. 18, No.2, pp. 620-623, 2008.
[7] D. Fedasynk, P. Serdyuk, Y. Semchyshyn and Lnv Polytechnic National University, “Resistance Super Conducting fault current limiter simulation and design,” 15th International Conference, Pocnam, 19-21, pp. 349-353, June 2008.
[8] K.H Hartong, “Is-limiter, the solution for high short circuit current application”, ABB calor Emarg, www.abb.com. 2002.
[9] J.F Arum, P.C Fernandez, E.H Rose, A.D Ajuz and A. Castanheira. “Brazillian successful experience in the usage of current limiting reactors for short circuit limitation”, International Conference on Power Systems Transients (IPSTOS) Montreal, Ia No.2, pp. 215 -220, June 2005.
[10] Z-X, Geng, X.Lin, J.-Y Xu and C. Tian “Effects of series reactor on short-circuit current and transient recovery voltage,” 2008 International Conference on high Voltage Engineering and Application, Changing Vol. 9, No. 3, pp.254-526, November 2008.
[11] J.J. Paserba. “How FACTS controllers benefit AC transmission systems,” IEEE, Vol, 2, No. 4, pp. 1-10, 2003.
[12] R.K Verma, R.M. Mathur, “Thyristor-based FACTS controllers for electrical transmission systems”, IEEE , Vol. 4, No. 3, pp. 277-288, 2002.
[13] B.K. Johnson, Benchmark Systems for Simulation of TCSC and SVC “IEEE transaction, Vol. 3, No. 3, pp. 234-255, 2002.
[14] S.S Rao, “Engineering optimization theory and practice” 4th Edition, John Wiley & Sons Inc, pp. 93, 2009.
[15] P. Suman Pramod Kumar, N. Vijaysimha and C.B Saravanan “Static synchronous series compensator for series compensation of BHV transmission line”, IJAREEVE Vol 2. Issue 7, pp 3183, July 2013.
[16] S. H. Kermanshachi and N. Sadati “Genetic Multivariable PID controller-Base on IMC, Annual Meeting of the North American Fussy Information Processing Society NAFIPS, Vol. 107, No. 3, pp. 174 -177, 2007.
[17] G. B. Tan, L. Jiang,  and Yang “A Novel Immune Genetic Algorithm-Base PID Controller. Leg. IEEE computer society. 3rd International Conference on National Computation, ICNC, Vol.  207, No. 4, pp. 282 -286, 2007.
[18] A. O’Dwyer, “Handbook of PI and PID controller Tuning Rules, 3rd editions, Imperial College Press, pp. 34, 2009.
[19] N. S. Nise, “Control System Engineering 3rd edition, (ECSA), pp. 67, 2006. 
:10.22362/ijcert/2017/v4/i11/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I1107.pdf
Refbacks : Currently there are no refbacks
Comparative Study of Surface Irrigation and Drip Irrigation for Tomato crop
Authors : Manoj Kumar Semil, M.K. Choudhary, Gaurav Kumar Patel
Affiliations : Civil Engineering Department, Maulana Azad National Institute of Technology Bhopal
Abstract :

af

Estimating irrigation water requirements accurately is important for water project planning and management also maximum yield per unit water applied should be more efficient use of irrigation water that mean the provision of additional quantities of water to increase the irrigated area with optimum crop production. A comparative study has been made at Etkhedi and Dhamaniya village, near Bhopal, India which is at Latitude of 23°15ˈ00ˈN and Longitude of 77°25ˈ00ˈE for tomato crop considering four irrigation systems. The first is a surface irrigation system (Furrow irrigation) adopted by farmer, the second one is also a surface irrigation but consider irrigation scheduling, third one is drip irrigation system adopted by farmer and fourth one is a drip irrigation system, designed for the same field. The result concluded that water might have been used efficiently under drip irrigation system. When compared with traditional surface irrigation method adopted by farmer and considering irrigation scheduling for tomato crop. Drip irrigation system demands least quantity of water as well as minimum cost of water as compared to other system. Water saved in designed drip irrigation system in 37.33%, 65.32% and 68.22% with respect to furrow irrigation (farmer’s method), irrigation scheduling and drip adopted by farmer respectively.
Citation :

af

Manoj Kumar Semil,M.K. Choudhary and Gaurav Kumar Patel (2017). Comparative Study of Surface Irrigation and Drip Irrigation for Tomato crop. International Journal of Computer Engineering In Research Trends, 4(11), 493-499. Retrieved from http://ijcert.org/ems/ijcert_papers/V4I1106.pdf
Keywords : Drip irrigation system, irrigation scheduling, yield, root zone depth, furrow irrigation, application efficiency
References :

af

[1]	Mateos, L., Berengena, J., Orgaz, F., Diz, J., & Fereres, E.,” A comparison between drip and furrow irrigation in cotton at two levels of water supply”, Agricultural Water Management, 19(4), 313e324, 1991.
[2]	Choudhary M.K, Shete D.T and Modi P.M, “A case study of micro and surface irrigation system for banana crop”, WAP/INCID/WS-MIW/93, 1993.
[3]	Chartzoulakis, K., Drosos, N.,” Water requirements of greenhouse grown pepper under drip irrigation”, Acta Hort. (ISHS) 449, pp. 175–180, 1997.
[4]	ASCE EWRI (Environmental and Water Resources Institute), “The ASCE standardized reference evapotranspiration equation.” Rep. of the Task Committee on Standardization of Reference Evapotranspiration, Reston. ASCE EWRI (Environmental and Water Resources Institute), “The ASCE standardized reference evapotranspiration equation.” Rep. of the Task Committee on Standardization of Reference Evapotranspiration, Reston, 2005.
[5]	Kumar D. Suresh and K. Palanisamib,” Impact of Drip Irrigation on Farming System: Evidence from Southern India”, Agricultural Economics Research Review, Vol. 23, pp 265-272, July-December 2010.
[6]	 Bahirat, J.B. and Jadav, H.G, “To study the cost, returns and profitability of rose production in Satara district, Maharashtra”, The Asian journal of horticulture, Vol. 6, Issue 2, pp. 313-315, December, 2011.
[7]	Martínez, J., & Reca, J., “Water use efficiency of surface drip irrigation versus an alternative subsurface drip irrigation method”, Journal of Irrigation and Drainage Engineering, 140(10), 04014030,2014.
:10.22362/ijcert/2017/v4/i11/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I1106.pdf
Refbacks : Currently there are no Refbacks
LIFE APP
Authors : B. Kumara Swamy, ,
Affiliations : Sree Dattha Institute of Engineering and Science, Hyderabad, India
Abstract :

af

Many people are losing their lives due to lack of treatments doctors may not be available all the time. The doctor may not be aware of the patient’s condition, so that they may not be available to attend emergencies. The patient’s condition is examined before reaching the hospital i.e., checking B.P, body temperature, pulse etc..,. If the patient’s condition is critical then the patient’s condition is intimated to the hospital reception and makes the particular doctor available. By using the GPS the location and time by which the patient reaches hospital’s will be updated to the hospitals reception. As soon as the patient’s condition is intimated to hospital reception the return notification will be provided by the doctor to the people in the ambulance about the first aid to be given. Effective and immediate treatment can be provided. Prior knowledge about the patient’s condition is informed to the doctor. The GPS helps the doctor to be available by letting them know the location and time taken by the patient to reach the hospital.
Citation :

af

B. Kumara Swamy (2017). LIFE APP. International Journal of Computer Engineering In Research Trends, 4(11), 487-492. Retrieved from http://ijcert.org/ems/ijcert_papers/V4I1105.pdf
Keywords : GPS,Mobile App. Android,Doctors.
References :

af

[1] http://www.tomcat.apache.org/download-55.cgi
[2] http://www.oracle.com/pls/db102/homepage
[3] http://www.java.sun.com/j2ee/tutorial/1_3-fcs/doc/Servlets.html
[4] http://www.eclipse.org/documentation/
[5] http://download.oracle.com/javase/tutorial/jdbc/
:10.22362/ijcert/2017/v4/i11/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I1105.pdf
Refbacks : Currently There are no refbacks
Improving Service Accessibility (CSSR) In GSM Network using an Intelligent Agent-Based Approach
Authors : Eli-Chukwu, Ngozi Clara, Onoh, Greg Nwachukwu,
Affiliations : Department of Electrical / Electronics & Computer Engineering Federal University Ndufu Alike, Ikwo, Ebonyi State, Nigeria. (FUNAI)
Abstract :

af

The ability to access cellular network serves as the basis of any Key Performance Indicator to be measured. Accessing it allows subscribers to other features or value-added services rendered by the telecommunications operator. The inability to access telecommunication services continues to plunge the performance of the Global System for Mobile Communication network in Nigeria. Most often, when subscribers are denied access, it reduces the overall Call Success Rate (CSR). To this end, network samples were collected during drive test in Enugu State Nigeria, and GSM parameters that prompt blocked calls were extracted from the log-files using TEMS Discovery. The various causes of blocked calls that are software related and their respective solutions were embedded in an Artificial Intelligent system using a Case-Based Reasoning approach to avoid such blocked calls. The log-file was run with the AI system; the result shows that the system accessibility was improved by 5.23%
Citation :

af

Eli-Chukwu, Ngozi Clara and Onoh, Greg Nwachukwu (2017). Improving Service Accessibility (CSSR) In GSM Network using an Intelligent Agent-Based Approach. International Journal of Computer Engineering In Research Trends, 4(11), 478-486. Retrieved from http://ijcert.org/ems/ijcert_papers/V4I1104.pdf
Keywords : GSM, Network Accessibility, Network Quality, Artificial Intelligence, Case-Based Reasoning, Blocked call.
References :

af

[1]. Rappaport, T.S. (2001) Wireless Communications: Principles and Practice, Prentice Hall, USA.
[2]. Mkheimer, Baha and Jamoos, Ali (2012),‟ Evaluation and optimisation of GSM network in Jensen City, Palestine‟ International Journal Mobile Network Design and Innovation, Vol.4, No. 4, pp. 201–213
[3]. Halonen T., Romero J., Melero J.: GSM, GPRS, and EDGE Performance. John Wiley & Sons Ltd, 2003.
[4]. Dahlman, E., Parkvall, S. and Skold, J. (2011) 4G: LTE/LTE-Advanced for Mobile Broadband, Academic Press, UK.
[5]. Mishra, A.R. (2004) Fundamentals of Cellular Network Planning and Optimization 2G/2.5G/3G... Evolution to 4G, Wiley & Sons, Ltd., England.
[6].Mishra, A.R. (2007) Advanced Cellular Networks Planning and Optimization2G/2.5G/3G & Evolution to 4G, Wiley & Sons, Ltd., England.
[7]. Guowang M., Jens Z., Ki Won Sung; Ben S, (2016). Fundamentals of Mobile Data Networks. Cambridge University Press.
[8]. Quality of Service Indicators: GSM Mobile Networks - Quality of Service Survey. Portugal: Autoridade Nacional de Comunicações. October 2002
[9]. Mohamamd R.T, Ali A (2013) Root cause analysis and new practical schemes for improving of SDCCH accessing in cellular networks, International Conference on Information Communication and Embedded Systems (ICICES).
[10]. Na Yao, (2007) A CBR Approach for Radiation Pattern Control in WCDMA Networks,
[11]. Chantaraskul S, (2007) An intelligent-agent approach for congestion management in 3G networks, Elsevier Ltd.
:10.22362/ijcert/2017/v4/i11/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I1104.pdf
Refbacks : Currently there are no refbacks
User Assignment Algorithm for Energy Efficient Multiple Access Scheme of MIMO-OFDMA Systems
Authors : Shivkanya. D. Jadhav , V. M. Harnal ,
Affiliations : M. B. E. Society’s College Of Engineering Ambajogai ,Ambajogai, India
Abstract :

af

Energy Efficiency (EE) is the important issue for multi-user Multiple-Input Multiple-Output - Orthogonal Frequency-Division Multiple Access (MIMO - OFDMA) system. In this paper, the Energy-efficient Multiple Access (EMA) schemes are proposed to improve EE by selecting either Time-Division Multiple Access (TDMA) or Space-Division Multiple Access (SDMA) for each subband, based on the number of users and power consumption. The polynomial-complex and greedy-based user assignment algorithms for the EMA system are adapted to Maximize energy efficiency. System complexity and energy efficiency are compared. Simulation Results verified that the EE of Greedy (GUSA) algorithms could significantly improve energy efficiency with practically compare to Fine EMA algorithm with increasing complexity.
Citation :

af

Shivkanya. D. Jadhav and V. M. Harnal (2017). User Assignment Algorithm for Energy Efficient Multiple Access Scheme of MIMO-OFDMA Systems. International Journal of Computer Engineering In Research Trends, 4(11), 469-477. Retrieved from http://ijcert.org/ems/ijcert_papers/V4I1103.pdf
Keywords : Energy efficiency (EE), channel access method, multiple access methods, time-division multiple access (TDMA), space-division multiple access (SDMA), orthogonal frequency-division multiple access (OFDMA), EMA, user assignment, greedy algorithm
References :

af

[1]  Jingon Joung, and Sumei Sun, Senior Member IEEE, “EMA : Energy-Efficiency-Aware Multiple Access”, IEEE Communications Letters, Vol. 18, No. 6, June 2014.

[2]   Jingon Joung, and Sumei Sun, Senior Member IEEE, “User Assignment Algorithms for Energy-Efficiency-Aware Multiple Access (EMA) Systems” IEEE Communications Letters, Vol. 20, No. 8, August  2016.
       
[3]  C. Xiong, G. Y. Li, S. Zhang, Y. Chen, and S. Xu, “Energy efficient resource allocation in OFDMA networks,” in Proc. 2011 IEEE Global Communications Conference

[4]     S. Cui, A. J. Goldsmith and A. Bahai, “Energy constrained modulation optimization,” IEEE Trans. Wireless Commun, vol. 4, no. 5, pp. 2349–2360, Sept. 2005. 

[5] Y. Huang, C. Tan, and B. Rao, “Joint beamforming and power control in coordinated multicell: max-min duality, effective network and largesystem transition,” IEEE Trans. Wireless Commun, vol. 12, no. 6, pp.2730–2742, Jun. 2013. 

[6]   M. C. Gursoy, “On the capacity and energy efficiency of training-base transmissions over fading channels,” IEEE Trans. Inf. Theory, vol.55,no. 10, pp. 4543–4567, Oct. 2009. 

[7] D. W. K. Ng, E. S. Lo, and R. Schober,“Energy-   Efficient Resource Allocation in OFDMA Systems With Large Numbers of Base Station Antennas,” IEEE Trans Wireless Commun,vol.11, no.9, pp.3292– 3304,Sep.2012 .     

[8] S. He, Y. Huang, S. Jin, and L. Yang, “Coordinated beamforming for energy efficient transmission in multicell multiuser systems,” IEEE Trans.Commun, vol. 61, no. 12, pp. 4961–4971, Dec. 2013.
 
[9]   J. Joung, C. K. Ho, and S. Sun, “Power amplifier switching (PAS) forenergy efficient systems,” IEEE Wireless Commun. Lett., vol. 2, no. 1,pp. 14–17, Feb. 2013.

[10]   D. Liu et al., “User association in 5G networks: A survey  and an outlook,” IEEE Commun. Surveys ,  vol. 18,  no.2, pp. 1018–1044, 2nd Quart., 2016.

[11]  Dukka Venkataramana, Chiranjeevulu Bagathi, ” Energy Efficient Multiple Access Scheme for Multi-User System with Improved Gain ”,  International Journal of Computer Engineering In Research Trends, Volume 2, Issue 11, November-2015, pp. 739-743
:10.22362/ijcert/2017/v4/i11/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I1103.pdf
Refbacks : Currently there are no refbacks
An Active Cache-Supported Path Planning on Roads
Authors : Chimme.Mahendranath, V.Leena Parimala,
Affiliations : Department of CSE, Dr.K.V.Subba Reddy Institute of Technology.Kurnool, Andhra Pradesh
Abstract :

af

In mobile navigation positions, on-road path planning is an essential dimension that finds a sequence between a source area and the destination point. While on streets, the away organizing question might be scattered because of portion considers different circumstances, for the case, a sudden change in driving path, startling activity conditions, or loss of GPS signals. In these situations, path planning needs to be directed promptly. The requirement of timeliness is even more confusing when a vast number of path planning queries acquiesces to the server, e.g., during peak hours. As the response time is unjustified to user approval with personal navigation services, it is a mandate for the server to handle the massive workload of path planning requests efficiently. To handle issues with the presented system, we recommend a scheme, namely, Path Planning by Caching (PPC), that objectives to response a different path planning query efficiently by caching and reprocessing queried paths (queried-paths in short). Distinct conventional cache-based path planning systems where a cached query degenerates just once it matches entirely with an original query, PPC leverages partially matched queried-paths in the cache to response part(s) of the different query. As a consequence, the server only needs to figure the unmatched path segments, thus significantly reducing the overall system workload.
Citation :

af

Chimme.Mahendranath and V.Leena Parimala (2017). An Active Cache-Supported Path Planning on Roads. International Journal of Computer Engineering In Research Trends, 4(11), 461-468. Retrieved from http://ijcert.org/ems/ijcert_papers/V4I1102.pdf
Keywords : Path Planning by Caching (PPC), GPS, Cache Management, PPattern Detection.
References :

af

[1] N. Mondal, M. Bag, M. Mukherjee, S. Chatterjee, N. Pervin, G. C. Banerjee,” Characteristics and Nature of Routing Protocols Used in VANET: A Comprehensive Study. “International Journal of Computer Engineering in Research Trends., vol.2, no.5, pp.284-287, 2015.
[2] Ramesh S Gawali, Prof. Mrunali G. Vaidya,” Selection and Maintenance of Materialized Views using Genetic Algorithm. “International Journal of Computer Engineering in Research Trends., vol.3, no.12, pp. 629-631, 2016.
[3] M.SHIRISHA, M.RADHA,” AMES-Cloud: A Framework of AMOV & ESOL using Clouds. “International Journal of Computer Engineering in Research Trends., vol.2, no.5, pp. 305-309, 2015.
[4] Shital M Kuwarkar, Prof. U.A.Nul,” Energy Consumption on Smartphone Web Browsing in 3G Network. “International Journal of Computer Engineering in Research Trends., vol.4, no.7, pp. 290-295, 2017.
[5] Dr. Subhi R. M. Zeebaree, Karwan Jacksi,” Effects of Processes Forcing on CPU and Total Execution-Time Using Multiprocessor Shared Memory Systemd. “International Journal of Computer Engineering in Research Trends., vol.2, no.4, pp. 275-279, 2015.
[6] Mr .BETKAR AKSHAY SURESH, Mrs. N.SUJATHA,” PROGRESSIVE DUPLICATE DETECTION. “International Journal of Computer Engineering in Research Trends., vol.3, no.6, pp. 284-288, 2016.
[7] H. Mahmud, A. M. Amin, M. E. Ali, and T. Hashem, “Shared Execution of Path Queries on Road Networks,” Clinical Orthopaedics and Related Research, vol. abs/1210.6746, 2012.
[8] L. Zammit, M. Attard, and K. Scerri, “Bayesian Hierarchical Modelling of Traffic Flow - With Application to Malta’s Road Network,” in International IEEE Conference on Intelligent Transportation Systems, 2013, pp. 1376–1381.
[9] S. Jung and S. Pramanik, “An Efficient Path Computation Model for Hierarchically Structured Topographical Road Maps,” IEEE Transactions on Knowledge and Data Engineering, vol. 14, no. 5, pp. 1029–1046, 2002.
[10] E. W. Dijkstra, “A Note on Two Problems in Connexion with Graphs,” Numerische Mathematik, vol. 1, no. 1, pp. 269–271, 1959.
[11] U. Zwick, “Exact and approximate distances in graphs – a survey,” in Algorithms – ESA 2001, 2001, vol. 2161, pp. 33–48.
[12] A. V. Goldberg and C. Silverstein, “Implementations of Dijkstra’s  Algorithm Based on Multi-Level Buckets,” in Network Optimization,
 [13] P. Hart, N. Nilsson, and B. Raphael, “A Formal Basis for the Heuristic Determination of Minimum Cost Paths,” IEEE Transactions on Systems Science and Cybernetics, vol. 4, no. 2, pp. 100–107, 1967.
[14] A. V. Goldberg and C. Harrelson, “Computing the Shortest Path: A Search Meets Graph Theory,” in ACM Symposium on Discrete Algorithms, 2005.
[15] R. Gutman, “Reach-Based Routing: A New Approach to Shortest Path Algorithms Optimized for Road Networks,” in Workshop on Algorithm Engineering and Experiments, 2004.
[16] A. V. Goldberg, H. Kaplan, and R. F. Werneck, “Reach for A*: Efficient Point-to-Point Shortest Path Algorithms,” in Workshop on Algorithm Engineering and Experiments, 2006, pp. 129–143.
[17] S. Jung and S. Pramanik, “An Efficient Path Computation Model for Hierarchically Structured Topographical Road Maps,” IEEE Transactions on Knowledge and Data Engineering, vol. 14, no. 5, pp. 1029–1046, 2002.
[18] R. Goldman, N. Shivakumar, S. Venkatasubramanian, and H. Garcia-Molina, “Proximity Search in Databases,” in International Conference on Very Large Data Bases, 1998, pp. 26–37.
[19] N. Jing, Y.-W. Huang, and E. A. Rundensteiner, “Hierarchical Optimization of Optimal Path Finding for Transportation Applications,” in ACM Conference on Information and Knowledge Management, 1996.
[20] N. Jing, Y. wu Huang, and E. A. Rundensteiner, “Hierarchical Encoded Path Views for Path Query Processing: An Optimal Model and its Performance Evaluation,” IEEE Transactions on Knowledge and Data Engineering, vol. 10, pp. 409–432, 1998.
[21] U. Demiryurek, F. Banaei-Kashani, C. Shahabi, and A. Ranganathan, “Online Computation of Fastest Path in Time-Dependent Spatial Networks,” in International Conference on Advances in Spatial and Temporal Databases, 2011.
[22] H. Gonzalez, J. Han, X. Li, M. Myslinski, and J. P. Sondag, “Adaptive Fastest Path Computation on a Road Network: a Traffic Mining Approach,” in International Conference on Very Large Data Bases, 2007.
[23] J. R. Thomsen, M. L. Yiu, and C. S. Jensen, “Effective caching of shortest paths for location-based services,” in ACM International Conference on Management of Data, 2012. 
:10.22362/ijcert/2017/v4/i11/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I1102.pdf
Refbacks : Currently there are no refbacks
Improving Public Safety in Everyday's Life Using Mobile Computing Applications
Authors : Arwa AlKhunine, Mohammed Imran,
Affiliations : Computer Science Department, College of Computer Science & Information Technology, Dammam, Imam Abdulrahman Bin Faisal University ,34212, Saudi Arabia
Abstract :

af

Keeping the public safe has always been the most important task of the country. Different kinds of incidents happen almost every day and usually, they are not reported correctly to the intended department. The main departments in the country are (1) law enforcement, (2) fire department, and (3) emergency medical services. This paper presents several improvements for selected research studies in order to make the three departments well-connected and suitable for public areas. Indoor GPS helps in locating specific incidents' area inside buildings, this helps in saving the time and effort to assist any incident. Saving lives is an important aspect to maintain a healthy and safe environment where an immediate health care is provided to the injured which increases their chances to heal faster. Also, improved fire detection and controlling system helps in eliminating the danger and damage to other's property. Further, we should engage the citizens in the incident reporting process via providing user-friendly applications, arranging awareness campaigns, and adopting new technologies to make devices intelligent enough so they won't need a human controller.
Citation :

af

Arwa AlKhuninei and Mohammed Imran (2017). Improving Public Safety in Everyday's Life Using Mobile Computing Applications. International Journal of Computer Engineering In Research Trends, 4(11), 456-460. Retrieved from http://ijcert.org/ems/ijcert_papers/V4I1101.pdf
Keywords : Safety, Public, GPS, Emergency, Incident
References :

af

1)	O. Bayrak, C. Temizyurek, M. Barut, O. Turkyilmaz and G. Gur, "A Novel Mobile Positioning Algorithm Based on Environment Estimation," 2007 4th Workshop on Positioning, Navigation, and Communication, Hannover, 2007, pp. 211-215.
2)	P. Erickson et al., "Designing public safety mobile applications for disconnected, interrupted, and low bandwidth communication environments," 2013 IEEE International Conference on Technologies for Homeland Security (HST), Waltham, MA, 2013, pp. 790-796.
3)	A. Muyanja, P. I. Musasizi, C. Nassimbwa, S. S. Tickodri-Togboa, E. K. Kayihura and A. Ngabirano, "Requirements engineering for the Uganda police force crime records management system," 2013 21st IEEE International Requirements Engineering Conference (RE), Rio de Janeiro, 2013, pp. 30-307.
4)	M. S. A. Azmil, N. Ya'acob, K. N. Tahar and S. S. Sarnin, "Wireless fire detection monitoring system for fire and rescue application," 2015 IEEE 11th International Colloquium on Signal Processing & Its Applications (CSPA), Kuala Lumpur, 2015, pp. 84-89.
5)	R. Sowah, K. O. Ampadu, A. Ofoli, K. Koumadi, G. A. Mills and J. Nortey, "Design and implementation of a fire detection and control system for automobiles using fuzzy logic," 2016 IEEE Industry Applications Society Annual Meeting, Portland, OR, USA, 2016, pp. 1-8.
6)	Y. Okumura, E. Ohmori, T. Kawano, and K. Fukuda, 'Field strength and its variability in VHF und UHF land-mobile radio service,' Rev. Electr. Commun. Lab., vol. 16, no. 9, pp. 825, Sept. /Oct. 1968.
7)	A. Medeisis and A. Kajackas, "On the use of the universal Okumura-Hata propagation prediction model in rural areas," VTC2000-Spring. 2000 IEEE 51st Vehicular Technology Conference Proceedings (Cat. No.00CH37026), Tokyo, 2000, pp. 1815-1818 vol.3.
8)	F. V. Diggelen, C. Abraham, "Indoor GPS Technology", CTIA Wireless-Agenda, Dallas, 2001, pp.1-10.
9)	R. A. Malaney, "NETp1-06: A Secure and Energy Efficient Scheme for Wireless VoIP Emergency Service," IEEE Globecom 2006, San Francisco, CA, 2006, pp. 1-6.
10)	H. Kimm and S. Y. Shin, "Efficient use of java MIDP record management system in wireless devices," IEEE/Sarnoff Symposium on Advances in Wired and Wireless Communication, 2005., Princeton, NJ, 2005, pp. 113-116. 
11)	Y. H. Ho and S. Abdullah, "Reduced global positioning system (GPS) positioning error by mitigating ionospheric scintillation," 2014 IEEE Symposium on Wireless Technology and Applications (ISWTA), Kota Kinabalu, 2014, pp. 110-115.
12)	Shahil TP, Sharon Tom, Deepak Joseph, Jobin Francis, "Low Cost Multipurpose Camera. International Journal of Computer Engineering in Research Trends. Vol. 2, Issue 12, December 2015, pp 1170-1172 ISSN (Online): 2349-7084.
:10.22362/ijcert/2017/v4/i11/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I1101.pdf
Refbacks : Currently there are no refbacks

 

Loss Minimization and Voltage Profile Improvement with Network Reconfiguration and Distributed Generation
Authors : V Usha Rani, J Sridevi ,
Affiliations : EEE Dept., Gokaraju Rangaraju Institute of Engineering & Technology, Hyderabad,500090, India
Abstract :

af

A new method of reducing active power losses and voltage profile improvement in distribution networks by simultaneous placement of optimally sized Distributed Generation (DGs) is proposed in this paper. A loss sensitivity factor is mainly considered for DG placement in the distribution network for loss reduction and voltage profile improvement. This Loss Sensitivity Index method is tested in different cases with the combination of network reconfiguration and DGs. All cases are compared to identify the superiority of the proposed method. This method is tested to demonstrate the performance and effectiveness of the IEEE 33 Bus Radial Distributed System in ETAP software.
Citation :

af

V Usha Rani and J Sridevi (2017). Loss Minimization and Voltage Profile Improvement with Network Reconfiguration and Distributed Generation. International Journal of Computer Engineering In Research Trends, 4(10), 449-455. Retrieved from http://ijcert.org/ems/ijcert_papers/V4I1013.pdf
Keywords : Radial distribution System, Distributed Generation, Loss Sensitivity Factor, Network Reconfiguration, Loss Minimization, Voltage profile
References :

af

[1]	 Z. W. Geem, “Novel derivative of harmony search algorithm for discrete design variables,” Appl. Math. Computat., vol. 199, no. 1, pp. 223–230, May 2008.
[2]	S. Ghosh and K. S. Sherpa, “An efficient method for load-flow solution of radial distribution networks,” World Academy of Science, Engineering and Technology International Journal of Electrical and Computer Engineering Vol:2, No:9, 2008 
[3]	R. Srinivasa Rao, K. Ravindra, K. Satish, and S. V. L. Narasimham “Power loss minimization in distribution system using network reconfiguration in the presence of distributed generation,” IEEE Trans. on power systems, vol. 28, no. 1, Feb 2013.
[4]	M. E. Baran and F. Wu, "Network reconfiguration in the distribution system for loss reduction and load balancing," IEEE Trans. Power Del., vol. 4, no. 2, pp. 1401–1407, Apr. 1989. 
[5]	J. S. Savier and D. Das, “Impact of network reconfiguration on loss allocation of radial distribution systems,” IEEE Trans. Power Del., vol. 2, no. 4, pp. 2473–2480, Oct. 2007. 
[6]	S. Kalambe and G. Agnihotri, “Loss minimization techniques used in distribution network: bibliographical survey,” Renewable and Sustainable Energy Reviews, vol. 29, pp. 184 – 200, Jan.2014. 
[7]	T. T. Nguyen and A. V. Truong, “Distribution network reconfiguration for power loss minimization and voltage profile improvement using cuckoo search algorithm,” International Journal of Electrical Power & Energy Systems, vol. 68, pp. 233 – 242, June 2015.
[8]	R. Rajaram, K. S. Kumar, and N. Rajasekar, “Power system reconfiguration in a radial distribution network for reducing losses and to improve voltage profile using modified plant growth simulation algorithm with distributed generation (dg),” Energy Reports, vol. 1, pp. 116 – 122,Nov. 2015.
[9]	D. Q. Hung and N. Mithulananthan, “Multiple distributed generator placement in primary distribution networks for loss reduction,” Industrial Electronics, IEEE Transactions on, vol. 60, no. 4, pp. 1700–1708, Apr. 2013.
[10]	A. M. Imran and M. Kowsalya, “Optimal size and siting of multiple distributed generators in distribution system using bacterial foraging optimization,” Swarm and Evolutionary Computation, vol. 15, pp. 58 – 65, Apr. 2014.
:10.22362/ijcert/2017/v4/i10/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I1013.pdf
Refbacks : Currently There are no refbacks
Gasoline Fraud Buster
Authors : Shubham Patil, Harshad Jagtap, Sambhaji Ippar, Vaibhav Vidhate, Sheetal More, Puspendu Biswas
Affiliations : Department of Computer Engineering, Sanghavi college of Engineering, Nashik,
Abstract :

af

In today's world, the actual record of fuel filled and fuel consumption in vehicles is not maintained. It results in a financial loss. To quantify the actual amount of fuel into the tank we implement the system using the Internet of things. The system uses the flow sensor which calculates the amount of fuel runtime while filling the tank. The ultrasonic sensor continuously monitors the level of fuel in the tank. If suddenly the level fuel goes low then the system rings the beep and notifies the owner of car or bike. The system also provides the reporting function in which the fraud is directly reported to the higher authority or government officials. The system also stores the historical data for future use.
Citation :

af

Shubham Patil ,Harshad Jagtap, Sambhaji Ippar, Vaibhav Vidhate, Sheetal More and Puspendu Biswas (2017). Gasoline Fraud Buster. International Journal of Computer Engineering In Research Trends, 4(10), 444-448. Retrieved from http://ijcert.org/ems/ijcert_papers/V4I1012.pdf
Keywords : Flow Sensor, Ultrasonic Sensor, Raspberry Pi Introduction.
References :

af

[1] Fuel Management System,Areeg Abubakr Ibrahim Ahmed, Siddig Ali Elamin Mohammed, Mohamed Almudather Mahmoud Hassan Satte,2017 IEEE
[2] IOT BASED FUEL MONITORING FOR FUTURE VEHICLES, Prof.J.N.Nandimath,Varsha Alekar, Sayali Joshi, Sonal Bhite, Pradnya Chaudhari, Feb2017, IRJET
[3] DIGITAL FUEL INDICATOR Rishabh Neogi, Graphic Era Hill University, Dehradun, India, 2016, IJAME.
[4] www.howstu works.com
[5] http://www.speedyjim.net
[6]http://www.wisegeek.com/what-is-a-fuel gauge.htm
[7]http://www.en.wikipedia.org/wiki/PIC-microcontroller
[8] T.Lakshman,A.Naga Lavanya, Pure and Impurity Water Monitoring In All Accepts.International Journal of Computer Engineering in Research Trends., vol.2, no.12, pp. 880-884, 2015. 
[9] Albarbar, A., Fengshou Gu, and A. D. Ball. "Diesel engine fuelinjection monitoring using acoustic measurements and independent component analysis." Measurement 43.10 (2010): 1376-1386.
[10] Kum, Dongsuk, Huei Peng, and Norman K Bucknor. "Optimal energy and catalyst temperature management of plug-in hybrid electric vehicles for minimum fuel consumption and tail-pipe emissions." IEEE Transactions on Control Systems Technology 21.1
[11] Tie, Siang Fui, and Chee Wei Tan. "A review of energy sources and energy management system in electric vehicles." Renewable and Sustainable Energy Reviews 20 (2013): 82-102.
[12] Basu, Debraj, et al. "Wireless sensor network based smart home: Sensor selection, deployment and monitoring." Sensors Applications Symposium (SAS), 2013 IEEE. IEEE, 2013.48 (SAS), 2013 sIEEE. IEEE, 2013.
:10.22362/ijcert/2017/v4/i10/xxxx [UNDER PROCESS]
DOI Link : Not yet Updated
Download :
  V4I1012.pdf
Refbacks : Currently There are no refbacks
A Framework of Adaptive Video Publishing and sharing in Cloud Network
Authors : P.Oshin, A. Emmanuel Raju,
Affiliations : Department of CSE, Dr. K. V. Subba Reddy Institute of Technology, Kurnool, A.P,India.
Abstract :

af

The video traffic demands are raising over a mobile network through wireless link capacity cannot meet with the demand of video traffic. The increasing traffic demand is considered by video streaming and downloading. As a result, there is a gap between link capacity and traffic demands together with the time varying condition which results in the poor quality of video streaming service over a mobile network such as sending long buffering time and intermittent disruptions due to limited bandwidth and wireless link condition. Cloud computing provides various advanced services, AMES cloud network framework built to provide video services to user, it has two main parts: Efficient social video sharing and Adaptive mobile video streaming which built a private agent, which provides video streaming service for each user in the network efficiently. Thus, it provides efficient storage over cloud network.
Citation :

af

P.Oshin ,A. Emmanuel Raju (2017). A Framework of Adaptive Video Publishing and sharing in Cloud Network. International Journal of Computer Engineering In Research Trends, 4(10), 441-443. Retrieved from http://ijcert.org/ems/ijcert_papers/V4I1011.pdf
Keywords : Adaptive Video Streaming, Scalable Video Coding (SVC), Efficient Video Sharing, HTTP Live Streaming (HLS).
References :

af

1)	Y.  Li,  Y.  Zhang,  and  R.  Yuan,  “Measurement  and Analysis of a Large Scale Commercial Mobile Internet TV System,” in ACM IMC, pp. 209–224, 2011.

2)	Y. Fu, R. Hu, G. Tian, and Z. Wang, “TCP-Friendly Rate Control for Streaming Service Over 3G network,” in WiCOM, 2006.

3)	M. Wien, R. Cazoulat, A. Graffunder, A. Hutter, and P. Amon, “Real-Time System for Adaptive Video Streaming Based on SVC,” in IEEE Transactions on Circuits and Systems for Video Technology, vol. 17, no. 9, pp. 1227–1237, Sep. 2007.

4)	D. Niu, H. Xu, B. Li, and S. Zhao, “Quality-Assured Cloud Bandwidth Auto-Scaling for Video-on-Demand Applications,” in IEEE INFOCOM, 2012.

5)	S. Chetan, G. Kumar, K. Dinesh, K. Mathew, and M. A. Abhimanyu,  “Cloud  Computing  for  Mobile  World,” Tech. Rep., 2010.

6)	Q.   Zhang,   L.   Cheng,   and   R.   Boutaba,   “Cloud Computing: State-of-the-art and Research Challenges,” in Journal of Internet Services and Applications, vol. 1, no. 1, pp. 7–18, Apr. 2010.

7)	Y.  Li,  Y.  Zhang,  and  R.  Yuan,  “Measurement  and Analysis of a Large Scale Commercial Mobile Internet TV    System,” in ACM IMC, pp. 209–224, 2011.

8)	P. McDonagh, C. Vallati, A. Pande, and P. Mohapatra, “Quality-Oriented Scalable Video Delivery Using H. 264 SVC on An LTE Network,” in WPMC, 2011.

9)	Kamarthi Rekha, R. Vara Prasad and Dr.S.Prem Kumar,” User Adaptive Mobile Video Streaming and Resourceful Video Sharing in Cloud. “International Journal of Computer Engineering in Research Trends., vol.1, no.1, pp. 1-7, 2014. 

10)	Gattu Uma Maheswari, E Ramya,” A Structure of Adaptive Mobile Video Streaming and Methodical Social Video Sharing In the Cloud. “International Journal of Computer Engineering in Research Trends., vol.2, no.12, pp. 837-841, 2015. 

11)	M.SHIRISHA, M.RADHA,” AMES-Cloud: A Framework of AMOV & ESOV using Clouds. “International Journal of Computer Engineering in Research Trends., vol.2, no.5, pp. 305-309, 2015. 
:10.22362/ijcert/2017/v4/i10/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I1011.pdf
Refbacks : Currently There are no refbacks
Two Step Factor Based Authentication Control to Access Cloud Services
Authors : Mr. Mohammed Shuja Ur Rahman, Mr. Mohammed Khaleel Ahmed, Dr. G.S.S Rao
Affiliations : Nawab Shah Alam khan College of Engineering and Technology,Hyd
Abstract :

af

The innumerable points of interest of distributed computing have conveyed an enormous change to the way of life and the best approach to adapt to the world today, yet the cloud needs to achieve development. Be that as it may, the primary boundary to it's across the board appropriation is the security and protection issues. So as to make and keep up common trust among the clients and the cloud specialist co-ops, a well-characterized trust establishment ought to be executed. The information put away in the cloud remotely by the singular client or an association, so they lost control over the information, in this way making a security issue. The most difficult and hot research region in distributed computing now daily is the information security and access control. A powerful measure to ensure distributed computing assets and administrations in the begin is to execute an entrance control system. In this paper, the highlights of different access control systems are examined, and a novel structure of access control is proposed for distributed computing, which gives a multi-step and multifaceted confirmation of a client. The model proposed is an efficient and provably secure arrangement of access control for remotely facilitated applications.
Citation :

af

Mr. Mohammed Shuja Ur Rahman ,Mr. Mohammed Khaleel Ahmed and Dr. G.S.S Rao (2017). Two Step Factor Based Authentication Control to Access Cloud Services. International Journal of Computer Engineering In Research Trends, 4(10), 431-440. Retrieved from http://ijcert.org/ems/ijcert_papers/V4I1010.pdf
Keywords : Cloud Security, Access Control, Cloud Trust, Data Control, Multi-Factor Authentication
References :

af

[1] L. M. Vaquero, L. Rodero-Merino, J. Caceres and M. Lindner, "A break in the clouds: towards a cloud definition," ACM SIGCOMM Computer Communication Review, vol. 39, no. 1, (2008), pp. 50-55.
[2] S. Ullah and Z. Xuefeng, "Cloud Computing Research Challenges," In Proceedings of 5th IEEE International Conference on Biomedical Engineering and Informatics, (2012), pp. 1397-1401.
[3] S. Yu, C. Wang, K. Ren and W. Lou, "Achieving secure, scalable, and fine-grained data access control in cloud computing," In INFOCOM, 2010 Proceedings IEEE, IEEE, (2010), pp. 1-9.
[4] L. Yousef, M. Butrico and D. Da Silva, "Toward a Unified Ontology of Cloud Computing," Grid Computing Environments Workshop, GCE '08, (2008), pp. 1-10.  
[5] Z. Shen and Q. Tong, "The Security of Cloud Computing System enabled by Trusted Computing Technology," In Proceedings of 2nd International Conference on Signal Processing Systems, (2010), pp. 11- 15.
[6] R. L. Grossman, "The Case for Cloud Computing," IT Professional, vol. 11, no. 2, (2009), pp. 23-27.
[7] S. Ullah, Z. Xuefeng and Z. Feng, "TCloud: Challenges and Best Practices for Cloud Computing," International Journal of Engineering Research and Technology, vol. 1, no. 9, (2012), pp. 01-05.
[8] S. Subashini and V. Kavitha, "A survey on security issues in service delivery models of cloud computing", Journal of Network and Computer Applications, vol. 34, no. 1, (2011), pp. 1-11. 
[9] Di Vimercati, S. De Capitani, S. Foresti, S. Jajodia, S. Paraboschi and P. Samarati, "A data outsourcing architecture combining cryptography and access control", In Proceedings of the 2007 ACM workshop on Computer security architecture, ACM, (2007), pp. 63-69. 
[10]W. Wang, L. Zhiwei, R. Owens and B. Bhargava, "Secure and efficient access to outsourced data", In Proceedings of the 2009 ACM workshop on Cloud computing security, ACM, (2009), pp. 55-66. 
[11] S. Kamara and K. Lauter, "Cryptographic cloud storage", Financial Cryptography and Data Security, (2010), pp. 136-149. 
[12]J. Dai and Q. Zhou, "A PKI-based mechanism for secure and efficient access to outsourced data", In Networking and Digital Society (ICNDS), 2010 2nd International Conference on, vol. 1, (2010), pp. 640- 643, IEEE. 
[13]G. Zhao, X. Hu, Y. Li and L. Du, "Implementation and testing of an identity-based authentication system", In Computing, Communication, Control, and Management, 2009, CCCM 2009, ISECS International Colloquium on, vol. 4, IEEE, (2009), pp. 424-427. 
[14]E. -J. Yoon and K. -Y. Yoo, "Robust id-based remote mutual authentication with key agreement scheme for mobile devices on ecc", InComputational Science and Engineering, 2009, CSE'09, International Conference on, vol. 2, IEEE, (2009), pp. 633-640. 
[15]J. Wiebelitz, S. Piger, C. Kunz and C. Grimm, "Transparent identity-based firewall transition for eScience", In E-Science Workshops, 2009 5th IEEE International Conference on, IEEE, (2009), pp. 3-10. 
[16]D. Zissis and D. Lekkas, "Addressing cloud computing security issues", Future Generation Computer Systems, vol. 28, no. 3, (2012), pp. 583-592. 
[17]L. Rodero-Merino, L. M. Vaquero, E. Caron, A. Muresan and F. Desprez, "Building safe PaaS clouds: A survey on security in multitenant software platforms", Computers & Security, (2011). 
[18]H. Li, Y. Dai, L. Tian and H. Yang, "Identity-based authentication for cloud computing", Cloud Computing, (2009), pp. 157-166. 
[19]G. Miklau and D. Suciu, "Controlling access to published data using cryptography", In Proceedings of the 29th international conference on Very large data bases, vol. 29, VLDB Endowment, (2003), pp. 898-909.
[20]D. Naor, A. Shenhav and A. Wool, "Toward securing untrusted storage without public-key operations", In Proceedings of the 2005 ACM workshop on Storage security and survivability, ACM, (2005), pp. 51-56. 
[21]E. -J. Goh, H. Shacham, N. Modadugu and D. Boneh, "SiRiUS: Securing remote untrusted storage", NDSS, (2003). 
[22]H. Ahn, H. Chang, C. Jang and E. Choi, "User Authentication Platform using Provisioning in Cloud Computing Environment", Advanced Communication and Networking, (2011), pp. 132-138. 
[23]G. Ateniese, K. Fu, M. Green and S. Hohenberger, "Improved proxy re-encryption schemes with applications to secure distributed storage", NDSS, (2005). 
[24]R. Blom, "An optimal class of symmetric key generation systems", In Advances in Cryptology, Springer Berlin/Heidelberg, (1985), pp. 335-338.
[25] FARZANA, A.HARSHAVARDHAN,Integrity Auditing for Outsourced Dynamic Cloud Data with Group User Revocation. International Journal of Computer Engineering in Research Trends., vol.2, no.11, pp. 877-881, 2015. 
[26] N. Meghasree,U.Veeresh and Dr.S.Prem Kumar,Multi Cloud Architecture to Provide Data Privacy and Integrity. International Journal of Computer Engineering in Research Trends., vol.2, no.9, pp. 558-564, 2015. 
[27]A.Shekinah prema sunaina,Decentralized Fine-grained Access Control scheme for Secure Cloud Storage data. International Journal of Computer Engineering in Research Trends., vol.2, no.7, pp. 421-424, 2015. 
[28]P.Rizwanakhatoon and Dr.C.MohammedGulzar,SecCloudPro:A Novel Secure Cloud Storage System for Auditing and Deduplication. International Journal of Computer Engineering in Research Trends., vol.3, no.5, pp. 210-215, 2016. 
[29]B.SameenaBegum,.RaghaVardhini,Augmented Privacy-Preserving Authentication Protocol by Trusted Third Party in Cloud. International Journal of Computer Engineering in Research Trends., vol.2, no.5, pp. 378-382, 2015.

:10.22362/ijcert/2017/v4/i10/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I1010.pdf
Refbacks : Currently there are no refbacks
An Anti-Collusion Method for Secure Sharing Of Cloud Data for Dynamic Systems
Authors : Ms. Syeda Tahira Khalid, Dr. G.S.S Rao,
Affiliations : Nawab Shah Alam khan College of Engineering and Technology,Hyd
Abstract :

af

The distributed computing is related degree embryonic processing standard inside which assets of the registering outline region unit gave as administrations over the web. Sharing group asset among cloud clients could be a noteworthy drawback, consequently distributed computing gives a financially savvy and prudent answer. Mona, secure information sharing amid a multi-proprietor way for dynamic groups jelly learning, character protection from the partner degree clear cloud and allows visit revision of the enrollment. Amid this venture, we tend to propose protected multi-proprietor information sharing a subject, for dynamic groups inside the cloud. By use bunch signature and dynamic communicate mystery composing methods; any cloud client will namelessly impart learning to others. Proposing a trade show for Sharing Secure learning inside the Cloud for the Dynamic Cluster.
Citation :

af

Ms. Syeda Tahira Khalid and Dr. G.S.S Rao (2017). An Anti-Collusion Method for Secure Sharing Of Cloud Data for Dynamic Systems. International Journal of Computer Engineering In Research Trends, 4(10), 424-430. Retrieved from http://ijcert.org/ems/ijcert_papers/V4I1009.pdf
Keywords : Cloud computing, data sharing, privacy-preserving, access control, dynamic groups.
References :

af

[1] M. Armbrust, A. Fox, R. Griffith, A.D. Joseph, R.H. Katz, A.Konwinski, G. Lee, D.A. Patterson, A. Rabkin, I. Stoica, and M.Zaharia, “A View of Cloud Computing,” Comm. ACM, vol. 53,no. 4, pp. 50-58, Apr. 2010.
[2] S. Kamara and K. Lauter, “Cryptographic Cloud Storage,” Proc.Int’l Conf. Financial Cryptography and Data Security (FC), pp. 136-149, Jan. 2010. 
[3] S. Yu, C. Wang, K. Ren, and W. Lou, Achieving Secure, Scalable, and Fine-Grained Data Access Control in Cloud Computing,”Proc. IEEE INFOCOM, pp. 534- 542, 2010. 
[4] M. Kallahalla, E. Riedel, R. Swaminathan, Q. Wang, and K. Fu,“Plutus: Scalable Secure File Sharing on Untrusted Storage,” Proc. USENIX Conf. File and Storage Technologies, pp. 29-42, 2003. 
[5] E. Goh, H. Shacham, N. Modadugu, and D. Boneh, “Sirius: Securing Remote Untrusted Storage,” Proc. Network and Distributed Systems Security Symp. (NDSS), pp. 131-145, 2003. 

[6] G. Ateniese, K. Fu, M. Green, and S. Hohenberger, “Improved Proxy Re-Encryption Schemes with Applications to Secure Distributed Storage,” Proc. Network and Distributed Systems Security Symp. (NDSS), pp. 29-43, 2005. 
[7] R. Lu, X. Lin, X. Liang, and X. Shen, “Secure Provenance: The Essential of Bread and Butter of Data Forensics in Cloud Computing,” Proc. ACM Symp. Information, Computer, and Comm. Security, pp. 282- 292, 2010.
[8] B. Waters, “Ciphertext-Policy Attribute-Based Encryption: An Expressive, Efficient, and Provably Secure Realization,” Proc. Int’l Conf. Practice and Theory in Public Key Cryptography Conf. Public Key Cryptography, http://eprint.iacr.org/2008/290.pdf, 2008. 
[9] V. Goyal, O. Pandey, A. Sahai, and B. Waters, “Attribute-Based Encryption for Fine-Grained Access Control of Encrypted Data,” Proc. ACM Conf. Computer and Comm. Security (CCS),pp. 89-98, 2006. 
[10] D. Naor, M. Naor, and J.B. Lotspiech, “Revocation and Tracing Schemes for Stateless Receivers,” Proc. Ann. Int’l Cryptology Conf.Advances in Cryptology (CRYPTO), pp. 41-62, 2001. 
[11] D. Boneh and M. Franklin, “Identity-Based Encryption from the Weil Pairing,” Proc. Int’l Cryptology Conf. Advances in Cryptology (CRYPTO), pp. 213-229, 2001. 
[12] D. Boneh, X. Boyen, and H. Shacham, “Short Group Signature,” Proc. Int’l Cryptology Conf. Advances in Cryptology (CRYPTO), pp. 41-55, 2004. 
[13] D. Boneh, X. Boyen, and E. Goh, “Hierarchical Identity Based Encryption with Constant Size Ciphertext,” Proc. Ann. Int’l Conf.Theory and Applications of Cryptographic Techniques (EUROCRYPT), pp. 440-456, 2005. 

[14] C. Delerablee, P. Paillier, and D. Pointcheval, “Fully Collusion Secure Dynamic Broadcast Encryption with Constant-Size Ciphertexts or Decryption Keys,” Proc. First Int’l Conf. Pairing-Based Cryptography, pp. 39-59, 2007. 

[15] D. Chaum and E. van Heyst, “Group Signatures,” Proc. Int’l Conf.Theory and Applications of cryptographic Techniques (EUROCRYPT), pp. 257-265, 1991. 

[16] A. Fiat and M. Naor, “Broadcast Encryption,” Proc. Int’l Cryptology Conf. Advances in Cryptology (CRYPTO), pp. 480-491, 1993. 

[17] B. Wang, B. Li, and H. Li, “Knox: Privacy Preserving Auditing for Shared Data with Large Groups in the Cloud,” Proc. 10th Int’l Conf. Applied Cryptography and Network Security, pp. 507-525, 2012. 
[18] FARZANA, A.HARSHAVARDHAN,”Integrity Auditing for Outsourced Dynamic Cloud Data with Group User Revocation. “International Journal of Computer Engineering in Research Trends., vol.2, no.11, pp. 877-881, 2015. 
[19] N. Meghasree,U.Veeresh and Dr.S.Prem Kumar,”Multi Cloud Architecture to Provide Data Privacy and Integrity. “International Journal of Computer Engineering in Research Trends., vol.2, no.9, pp. 558-564, 2015. 
[20]A.Shekinah prema sunaina,”Decentralized Fine-grained Access Control scheme for Secure Cloud Storage data. “International Journal of Computer Engineering in Research Trends., vol.2, no.7, pp. 421-424, 2015. 
[21]P.Rizwanakhatoon and Dr.C.MohammedGulzar,”SecCloudPro:A Novel Secure Cloud Storage System for Auditing and Deduplication. ”International Journal of Computer Engineering in Research Trends., vol.3, no.5, pp. 210-215, 2016. 
[22]B.SameenaBegum,.RaghaVardhini,”Augmented Privacy-Preserving Authentication Protocol by Trusted Third Party in Cloud. “International Journal of Computer Engineering in Research Trends., vol.2, no.5, pp. 378-382, 2015.

:10.22362/ijcert/2017/v4/i10/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I1009.pdf
Refbacks : Currently there are no refbacks
Dual Server Public Key Encryption With Keyword Search for Secure Cloud Storage
Authors : Anjum Saba Afsheen, Dr.G.S.S Rao,
Affiliations : Nawab ShahAlam khan College of Engineering and Technology, Hyd
Abstract :

af

Accessible cryptography is of accelerating enthusiasm for fending the data protection in secure, accessible distributed storage. During this paper, we tend to examine the safety of Associate in Nursing all-round kenned cryptological primitive, above all, open key cryptography with shibboleth ask for (PEKS) that is extraordinarily auxiliary in varied uses of distributed storage. Haplessly, it's been incontestable that the customary PEKS system experiences Associate in Nursing essential instability referred to as within watchword approximation assault (KGA) propelled by the threatening server. To deal with this security weakness, we tend to propose an aborning PEKS system named double server PEKS (DS-PEKS). As another principle commitment, we tend to characterize a starting variation of the graceful projective hash capacities (SPHFs) alluded to as direct and Homomorphic SPHF (LH-SPHF). We tend to at that time demonstrate a bland development of secure DS-PEKS from LH-SPHF. To stipulate the chance of our early system, we tend to offer a good representation of the final structure from a selection DiffieHellman-predicated LH-SPHF and demonstrate that it will accomplish the energetic security against within the KGA.
Citation :

af

Ms. Tamreen Fatima and Dr. G.S.S Rao (2017). Cross Stage Identification of Unknown Clients in Numerous Online Networking Systems . International Journal of Computer Engineering In Research Trends, 4(10), 400-406. Retrieved from http://ijcert.org/ems/ijcert_papers/V4I10008.pdf
Keywords : Keyword Search, Secure Cloud Storage, Encryption, Inside Keyword Guessing Attack, Smooth Projective Hash Function, Diffie-Hellman language.
References :

af

[1] R. Chen, Y. Mu, G. Yang, F. Guo, and X. Wang, A new general framework for secure public key encryption with keyword search, in Proc. 20th Australasian Conf. Inf. Secure. Privacy (ACISP), 2015, pp. 5976.
[2] P. Xu, H. Jin, Q. Wu, and W. Wang, Public-key encryption with a fuzzy keyword search: A provably secure scheme under keyword guessing attack, IEEE Trans. Comput., vol. 62, no. 11, pp. 22662277, Nov. 2013.
[3] D. Khader, Public key encryption with keyword search based on K-resilient IBE, in Proc. Int. Conf. Comput. Sci. Appl. (ICCSA), 2006, pp. 298308.
[4] R. Curtmola, J. Garay, S. Kamara, and R. Ostrovsky, Searchable symmetric encryption: Improved definitions and efficient constructions, in Proc. 13th ACM Conf. Comput. Commun.Secur. (CCS), 2006, pp. 7988.\
[5] M. Abdalla et al., Searchable encryption revisited: Consistency properties, relation to anonymous IBE, and extensions, in Proc. 25th Annu. Int. Conf. CRYPTO, 2005, pp. 205222.
[6] B. R. Waters, D. Balfanz, G. Durfee, and D. K. Smetters, Building an encrypted and searchable audit log, in Proc. NDSS, 2004, pp. 111.
[7] D. Boneh, G. Di Crescenzo, R. Ostrovsky, and G. Persiano, Public key encryption with keyword search, in Proc. Int. Conf. EUROCRYPT, 2004, pp. 506522.
[8] R. Agrawal, J. Kiernan, R. Srikant, and Y. Xu, Order preserving encryption for numeric data, in Proc. ACM SIGMOD Int. Conf. Manage. Data, 2004, pp. 563574.
[9] R. Gennaro and Y. Lindell, A framework for password-based authenticated key exchange, in Proc. Int. Conf. EUROCRYPT, 2003, pp. 524543.
[10] D. X. Song, D. Wagner, and A. Perrig, Practical techniques for searches on encrypted data, in Proc. IEEE Symp. Secure. Privacy, May 2000, pp. 4455.
[11] A.Raghavendra Praveen Kumar, K.Tarakesh, and U.Veeresh , A Secure and Dynamic Multi Keyword Ranked Search Scheme over encrypted. International Journal of Computer Engineering in Research Trends., vol.2, no.12, pp. 1137-1141, 2015.
[12] Mr. Rahul Hon, and Mrs. N.Sujatha, A Novel Framework to Measure the Degree of Difficulty on Keyword Query Routing. International Journal of Computer Engineering in Research Trends., vol.3, no.6, pp. 314-320, 2016.
[13] Kallem Rajender Reddy, and Y.Sunitha, A Novel Framework to Measure the Degree of Difficulty on Keyword Query Routing. International Journal of Computer Engineering in Research Trends., vol.2, no.9, pp. 640-645, 2015.
[14] Vadla Jhansi Rani, and K.Samson Paul, Secure Multi Keyword Dynamic Search Scheme Supporting Dynamic Update.. International Journal of Computer Engineering in Research Trends., vol.4, no.8, pp. 356-360, 2017.
[15] Mr. M. Veerabrahma Chary and Mrs.N.Sujatha, A Novel Additive Multi-Keyword Search for Multiple Data Owners in Cloud Computing. International Journal of Computer Engineering in Research Trends., vol.3, no.6, pp. 308-313, 2016.
[16] Mr. M. VEERABRAHMA CHARY, Mrs.N.SUJATHA, A Novel Additive Multi-Keyword Search for Multiple Data Owners in Cloud Computing . International Journal of Computer Engineering In Research Trends., vol.3, no.6, pp. 308-313, 2016.
[17] G.Lucy, D.Jaya Narayana Reddy, R.Sandeep Kumar, Enabling Fine-grained Multi-keyword Search Supporting Classified Sub-dictionaries over Encrypted Cloud Data. International Journal of Computer Engineering In Research Trends., vol.2, no.12, pp. 919-923, 2015.
[18] G.Dileep Kumar, A.Sreenivasa Rao, Privacy-Preserving Public Auditing using TPA for Secure Searchable Cloud Storage data. International Journal of Computer Engineering In Research Trends., vol.2, no.11, pp. 767-770, 2015.
:10.22362/ijcert/2017/v4/i10/xxxx [UNDER PROCESS]
DOI Link : Not Yet Assigned
Download :
  V4I10008.pdf
Refbacks : Currently there no refbacks
Cross Stage Identification of Unknown Clients in Numerous Online Networking Systems
Authors : Ms. Tamreen Fatima, Dr. G.S.S Rao,
Affiliations : Nawab Shah Alam Khan College of Engineering and Technology, Hyd
Abstract :

af

A previous couple of years have witnessed the emergence and evolution of a vivacious analysis stream on an oversized sort of online Social Media Network (SMN) platforms. Recognizing anonymous, nonetheless, same users among multiple SMNs continues to be AN intractable downside. Cross-platform exploration could facilitate solve several issues in social computing in each theory and applications. Since public profiles are often duplicated and impersonated merely by users with entirely different functions, most current user identification resolutions, which principally specialize in text mining of users public profiles, are fragile. Some studies have tried to match users supported the placement and temporal order of user content also as a genre. However, the locations are distributed within the majority of SMNs, and genre is tough to pick out from the short sentences of leading SMNs like Sina Microblog and Twitter. Moreover, since on-line SMNs are quite regular, existing user identification schemes supported network structure don't seem to be effective. The real-world friend cycle is extremely individual, and just about no 2 users share a congruent friend cycle. Therefore, it's additional correct to use a relationship structure to investigate cross-platform SMNs. Since same users tend to line up partial similar relationship structures in many SMNs, we tend to project the Friend Relationship-Based User Identification (FRUI) algorithmic rule. FRUI calculates an equal degree for all candidate User Matched Pairs (UMPs), and solely UMPs with high ranks are thought of as equal users. We tend to conjointly develop 2 propositions to enhance the potency of the algorithmic rule. Results of intensive experiments demonstrate that FRUI performs far better than current network structure-based algorithms.
Citation :

af

Ms. Tamreen Fatima and Dr. G.S.S Rao (2017). Cross Stage Identification of Unknown Clients in Numerous Online Networking Systems . International Journal of Computer Engineering In Research Trends, 4(10), 400-406. Retrieved from http://ijcert.org/ems/ijcert_papers/V4I1005.pdf
Keywords : Cross-Platform, Social Media Network, Anonymous Identical Users, Friend Relationship, User Identification
References :

af

[1]Wikipedia,"Twitter, "
http://en.wikipedia.org/wiki/Twitter. 2014.
[2] Xinhuanet, "Sina Microblog Achieves over 500
MillionUsers,"
http://news.xinhuanet.com/tech/2012-
02/29/c_122769084.htm. 2014.
[3] J. Liu, F. Zhang, X. Song, Y.I. Song, C.Y. Lin, and
H.W. Hon, "What's in a name?: an unsupervised
approach to link users across communities," Proc. of
the 6th ACM international conference on Web search
and data mining(WDM13), pp. 495-504, 2013.
[4] O. Goga, D. Perito, H. Lei, R. Teixeira, and R.
Sommer, "Large-scale Correlation of Accounts across
Social Networks," Tech- nical report, 2013.
[5] K. Cortis, S. Scerri, I. Rivera, and S. Handschuh,
"An ontology-based technique for online profile
resolution," Social Informatics, Berlin: Springer, pp.
284-298, 2013.
[6] F. Abel, E. Herder, G.J. Houben, N. Henze, and D.
Krause, "Cross-system user modeling and
personalization on the social web," User Modeling and
User-Adapted Interaction, vol. 23, pp. 169-209, 2013.
[7] N. Korula and S. Lattanzi, "An efficient
reconciliation algorithm for social networks," arXiv
preprint arXiv:1307.1690, 2013.
[8] P. Jain, P. Kumaraguru, and A. Joshi, "@ i seek 'fb.
me': identify- ing users across multiple online social
networks," Proc. of the 22nd International Conference
on World Wide Web Companion, pp. 1259-1268,
2013.
[9] X. Kong, J. Zhang, and P.S. Yu, "inferring anchor
links across multiple heterogeneous social networks,"
Proc. of the 22nd ACM International Conf. on
Information and Knowledge Management (CIKM13),
pp. 179-188, 2013.
[10] O. Goga, H. Lei, S.H.K. Parthasarathi, G.
Friedland, R. Sommer, and R. Teixeira, "Exploiting
innocuous activity for correlating us- ers across sites,"
Proc. 22nd international conference on World Wide
Web (WWW13),pp. 447-458, 2013.
[11] R. Zafarani and H. Liu, "Connecting users across
social media sites: a behavioral-modeling approach, "
Proc. of the 19th ACM SIGKDD International
Conference on Knowledge Discovery and Data Mining
(KDD13), pp.41-49, 2013.
[12] S. Bartunov, A. Korshunov, S. Park, W. Ryu, and
H. Lee, "Joint link-attribute user identity resolution in
online social net- works," The 6th SNA-KDD
Workshop 12, 2012.
[13] P. Jain and P. Kumaraguru, "Finding Nemo:
searching and re-solving identities of users acrossonline social networks," arXiv preprint
arXiv:1212.6147, 2012.
[14] M. Almishari and G. Tsudik, "Exploring
linkability of user re- views," Computer Security
ESORICS 2012 (ESORICS12), pp. 307- 324, 2012.
[15] D. Perito, C. Castelluccia, M.A. Kaafar, and P.
Manils, "How unique and traceable are usernames?,"
Privacy Enhancing Technol- ogies (PETS11), pp. 1-
17, 2011.
[16] A. Acquisti, R. Gross and F. Stutzman, "Privacy
in the age of aug- mented reality," Proc. National
Academy of Sciences, 2011.
[17] T. Iofciu, P. Fankhauser, F. Abel, and K. Bischoff,
"Identifying users across social tagging systems, Proc.
of the 5th International AAAI Conference on Weblogs
and Social Media, pp. 522-525, 2011.
[18] B. Zhou and J. Pei, "The k-anonymity and ldiversity
approaches for privacy preservation in social
networks against neighborhood attacks," Knowl. Inf.
Syst, vol. 28, no. 1,pp. 47-77, 2011.
[19] E. Raad, R. Chbeir, and A. Dipanda, "User profile
matching in social networks," Proc. Of the 13th
International Conference on Network-Based
Information Systems (NBiS10), pp.297-304, 2010.
[20] P. Erd?s and A. Rnyi, "On random graphs I,"
Publ. Math. De- brecen, vol. 6, pp. 290-297, 2010.
[21] R. Zafarani and H. Liu, "Connecting
corresponding identities across communities," Proc. of
the 3rd International ICWSM Con- ference, pp. 354-
357, 2009.
[22] M. Motoyama and G. Varghese, "I seek you:
searching and matching individuals in social
networks," Proc. of the 11th inter- national workshop
on Web Information and Data Management
(WIDM09), pp. 67-75, 2009.
[23] J. Vosecky, D. Hong, and V.Y. Shen, "User
identification across multiple social networks," Proc.
Of the 1st International Confer- ence on Networked
Digital Technologies, pp.360-365, 2009.
[24] A. Narayanan and V. Shmatikov, "Deanonymizing
social net- works," Proc. Of the 30th
IEEE Symposium on Security and Privacy (SSP09),
pp. 173-187, 2009.
[25] B. Zhou and J. Pei, "Preserving privacy in social
networks against neighborhood attacks," Proc. Of the
24th IEEE International Conference on Data
Engineering (ICDE08), pp. 506515, 2008.
[26] L. Backstrom, C. Dwork, and J. Kleinberg,
"Wherefore art thou r3579x?: anonymized social
networks, hidden patterns, and structural
steganography," Proc. of the 16th international conference
on World Wide Web(WWW07), pp. 181-190,
2007.
[27] R. Zheng, J. Li, H. Chen, and Z. Huang, "A
framework for au- thorship identification of online
messages: writing? style fea? tures and classification
techniques," J. of the American Society for
Information Science and Technology, vol. 57, no. 3,
pp. 378-393, 2006.
[28] O. De Vel, A. Anderson, M. Corney, and G.
Mohay, "Mining e-mail content for author
identification forensics, ACM Sigmod Record, vol.
30, no. 4, pp. 55-64, 2001.
[29] A. L. Barabasi and R. Albert, "Emergence of
scaling in random networks," Science, vol. 286, no.
5439, pp. 509-512, 1999.
[30] D.J. Watts, and S.H. Strogatz, "Collective
dynamics of small-world networks," Nature, vol.393,
no.6684, pp. 440-442, 1998.
[31].K.Arun ,A.SrinageshandM.Ramesh,Twitter
Sentiment Analysis on Demonetization tweets in India
Using R language.International Journal of Computer
Engineering in Research Trends., vol.4, no.6, pp. 252-
258, 2017.
[32]TekurVijetha, M.SriLakshmi
andDr.S.PremKumar,Survey on Collaborative
Filtering and content-Based
Recommending.International Journal of Computer
Engineering in Research Trends., vol.2, no.9, pp. 594-
599, 2015.
[33]N.Satish Kumar, SujanBabuVadde,Typicality
Based Content-BoostedCollaborative Filtering
RecommendationFramework.International Journal of
Computer Engineering in Research Trends., vol.2,
no.11, pp. 809-813, 2015.
[34]D.Ramanjaneyulu,U.Usha Rani,In Service-
Oriented MSN ProvidingTrustworthy Service
Evaluation.International Journal of Computer
Engineering in Research Trends., vol.2, no.12, pp.
1192-1197, 2015.
[35]B.Kundan,N.Poorna Chandra Rao and
DrS.PremKumar,Investigation on Privacy and Secure
content of location based Queries.International
Journal of Computer Engineering in Research Trends.,
vol.2, no.9, pp. 543-546, 2015.
:10.22362/ijcert/2017/v4/i10/xxxx [UNDER PROCESS]
DOI Link : Not Yet Assigned
Download :
  V4I1005.pdf
Refbacks : Currently There are no refbacks
Energy and Memory Clone Detection in Wireless Sensor Network
Authors : Mr. Amatul Mateen Shamsiya, Dr. G.S.S Rao,
Affiliations : Nawab ShahAlam khan College of Engineering and Technology, Hyd
Abstract :

af

An associate degree energy-efficient location-aware clone detection protocol is planned in densely deployed WSNs, which may guarantee productive clone attack detection and maintain satisfactory network life. Specifically, the situation info of sensors is employed and every which way choose witnesses situated in an exceedingly ring space to verify the legitimacy of sensors and to report detected clone attacks. The ring structure facilitates energy-efficient information forwarding on the trail towards the witnesses and also the sink. Planned protocol are able to do one hundred clone detection likelihood with unsuspicious witnesses. Moreover, in most existing clone detection protocols with random witness choice theme, the desired buffer of sensors is typically keen about the node density, whereas, in the planned protocol, the desired buffer of sensors is freelance of hop length of the network radius. Planned protocol are able to do long network life by effectively distributing the traffic load across the network.
Citation :

af

Amatul Mateen Shamsiya and Dr. G.S.S Rao (2017). Energy and Memory Clone Detection in Wireless Sensor Network . International Journal of Computer Engineering In Research Trends, 4(10), 413-418. Retrieved from http://ijcert.org/ems/ijcert_papers/V4I1007.pdf
Keywords : wireless sensor networks, clone detection protocol, energy efficiency, and network lifetime
References :

af

[1] Z. Zheng, A. Liu, L. X. Cai, Z. Chen, and X. Shen, “ERCD: An energy-efficient clone detection protocol in wasns,” in Proc. IEEE INFOCOM, Turin, IT, Apr. 14-19 2015, pp. 2436–2444. 
[2] R. Lu, X. Li, X. Liang, X. Shen, and X. Lin, “GRS: The green, reliability, and security of emerging machine to machine communications,” IEEE Communications Magazine, vol. 49, no. 4, pp. 28–35, Apr. 2013. 
[3] Christo Ananth, A.NasrinBanu, M.Manju, S.Nilofer, S.Mageshwari, A.PeratchiSelvi, “Efficient Energy Management Routing in WSN”, International Journal of Advanced Research in Management, Architecture, Technology and Engineering (IJARMATE), Volume 1, Issue 1, August 2012,pp:16-19 
[4] Liu, J. Ren, X. Li, Z. Chen, and X. Shen, “Design principles and improvement of cost function based energy aware routing algorithms for wireless sensor networks,” Computer Networks, vol. 56, no. 7, pp. 1951–1967, May. 2011. 
[5] T. Shu, M. Krunz, and S. Liu, “Secure data collection in wireless sen-sor networks using randomized dispersive routes,” IEEE Transactions on Mobile Computing, vol. 9, no. 7, pp. 941–954, Jul. 2010.
[6] Uma Vasala and Dr. G. R. Sakthidharan,” Effective Key Management In Dynamic Wireless Sensor Networks”..”International Journal of Computer Engineering in Research Trends., vol.4, no.7, pp. 308-312, 2017.
[7] K.MANIMALA and .RANJITH,” Mobile Transmission Using Rigorous Data for Wireless Sensor Networks”..”International Journal of Computer Engineering in Research Trends., vol.1, no.6, pp. 436-446, 2014.

[8] P. G. V. SURESH KUMAR1 , SEELAM SOWJANYA,” Developing An Enterprise Environment by Using Wireless Sensor Network System Architecture”..”International Journal of Computer Engineering in Research Trends., vol.2, no.10, pp. 902-908, 2015.

[9]  JALAGAM NAGAMANI, K.SUMALATHA,” EAACK: Secure IDS for Wireless Sensor Networks”..”International Journal of Computer Engineering in Research Trends., vol.1, no.6, pp. 461-469, 2014.

[10] G V N LAKSHMI PRIYANKA, TELUGU KAVITHA, B SWATHI and  P.SUMAN PRAKASH,” Significance of DSSD towards Cut Detection in Wireless Sensor Network”..”International Journal of Computer Engineering in Research Trends., vol.2, no.1, pp. 8-12, 2015.

[11] Kumara Swamy,E Ramya,” A Contemplate on Vampire Attacks in Wireless Ad-Hoc Sensor Networks”..”International Journal of Computer Engineering in Research Trends., vol.2, no.12, pp. 834-836, 2015.

[12] Shital Patil , Vishaka Patil , Rupali Warke , Priyanka Patil,” Prevention of Packet Hiding Methods In Selective Jamming Attack”..”International Journal of Computer Engineering in Research Trends., vol.3, no.4, pp. 194-196, 2016.
:10.22362/ijcert/2017/v4/i10/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I1007.pdf
Refbacks : Currently there are no refbacks
Integrated Keyword Quest With Designated Scrutinizer and Time Permit Locum Re-Encryption Method for E-Healthcare Cloud Systems
Authors : Mr. Mohammed Salman Khan, Ms. Syeda Farhath Begum, Dr. G.S.S Rao
Affiliations : Nawab ShahAlam khan College of Engineering and Technology, Hyd
Abstract :

af

The electronic health (e-health) document framework could be a new usage that provides a lot of comfort in health care. The protection protects and safe the sensitive non-public document that is necessary for the users, these factors portrays major issues for any evolution of the framework. The searchable encoding (SE) plan is associate degree invented to merge, protect and kindly perform the operation works that is very important partof the e-health document design. In our current system, a replacement science rudimentary name is integrated keyword quest with designated scrutinizer and time permit locum re-encryption method is performed (RedtPECK), this theme is predicated on time and tester–dependent classifiable encoding strategy. Such strategy delegate patients protocols to access the document in restricted time countwhich is found within the native space and remote space. The time span period for delegate to look the E-health document and decipher the delegators E-health document is often known. Once the time span for accessing record is outlined or set, the delegate or patient or user provided the authority will directly access the info. Our scheme supports for forwarding keyword attack, thence solely authority tester is in a position to ascertain the doable keywords.
Citation :

af

Mr. Mohammed Salman Khan,Ms. Syeda Farhath Begum and Dr. G.S.S Rao (2017). Integrated Keyword Quest With Designated Scrutinizer and Time Permit Locum Re-Encryption Method for E-Healthcare Cloud Systems . International Journal of Computer Engineering In Research Trends, 4(10), 407-412. Retrieved from http://ijcert.org/ems/ijcert_papers/V4I1006.pdf
Keywords : Searchable Encryption; Time Control;Integrated keywords Indices; Designated Tester; E-health,Offline Assume Keyword Attack.
References :

af

[1] Yang Yang, Maode Ma. “Conjunctive Keyword Search with Designated Tester” Journal of IEEE Transactions on Information Forensics and Security, Vol. 11, No. 4, April 2016
[2] J. Leventhal, J. Cummins, P. Schwartz, D. Martin, W. Tierney. “Designing a system for patients controlling providers’ access to their electronic health records: organizational and technical challenges,” Journal of General Internal Medicine, vol. 30, no. 1, pp. 17-24, 2015. 
[3] Google Inc. Google health vault. https://www.google.com/health. 
[4] P. Liu, J. Wang, H. Ma, H. Nie, “Efficient Verifiable Public Key Encryption with Keyword Search Based on KPABE,” In Proc. 2014 Ninth International Conference on Broadband and Wireless Computing, Communication, and Applications (BWCCA), IEEE, pp.584-589, 2014.
[5] L. Fang, W. Susilo, C. Ge, J. Wang, “Public key encryption with keyword search secure against keyword guessing attacks without random oracle,” Information Sciences, vol. 238, pp. 221-241, 2013. 
[6] Q. Tang, “Public key encryption schemes supporting equality test with authorization of different granularity,” International Journal of Applied Cryptography, vol. 2, no. 4, pp. 304-321, 2012. 
[7]C. Hu, P. Liu, “An enhanced searchable public key encryption scheme with a designated tester and its extensions,” Journal of Computers, vol. 7, no. 3, pp. 716-723, 2012. 
[8] H. Rhee, J. Park, D. Lee, “Generic construction of designated tester public-key encryption with keyword search,” Information Sciences, vol. 205, pp. 93-109, 2012. 
[9] W. Yau, R. Phan, S. Heng, B. Goi, “Security models for delegated keyword searching within encrypted contents,” Journal of Internet Services and Applications, vol. 3, no. 2, pp. 233-241, 2012. 
[10] K. Emura, A. Miyaji, K. Omote, “A timed-release proxy re-encryption scheme,” IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences, vol. 94, no. 8, pp. 1682-1695, 2011.
[11] J. Shao, Z. Cao, X. Liang, H. Lin, “Proxy re-encryption with keyword search,” Information Sciences, vol. 180, no. 13, pp. 2576-2587, 2010. 
[12] W. Yau, R. Phan, S. Heng, B. Goi, “Proxy Re-encryption with Keyword Search: New Definitions and Algorithms,” in Proc. International Conferences on Security Technology, Disaster Recovery and Business Continuity, Jeju Island, Korea, Dec. 13-15, 2010, vol.122, pp. 149-160, Springer. 
[13] J. Byun, H. Rhee, H. Park, D. Lee, “Off-line key-word guessing attacks on recent keyword search schemes over encrypted data,” in Proc. Third VLDB Workshop on Secure Data Management (SDM), Seoul, Korea, September 10-11, 2006, vol. 4165, pp. 75-83, Springer. 
[14] D. Boneh, G. Di Crescenzo, R. Ostrovsky, G. Persiano, “Public key encryption with keyword search,” in Proc. EUROCRYPT, Interlaken, Switzerland, May 2-6, 2004, vol. 3027, pp. 506–522, Springer. 
[15]R. Canetti, O. Goldreich, S. Halevi, “The Random Oracle Methodology,” Journal of the ACM, vol. 51, pp. 557- 594, 2004. 
[16] Sree Sai Rajesh C  , Syed Mohammed Nadeem  , Vajjala Revanth Kumar  and R.Varaprasad,” Cloud Supported Personal Health Records with Security and Audit ability.”International Journal of Computer Engineering in Research Trends., vol.1, no.4, pp. 230-234, 2014. 
[17] G.Lucy, D.Jaya Narayana Reddy and R.Sandeep Kumar,” Enabling Fine-grained Multi-keyword Search Supporting Classified Sub-dictionaries over Encrypted Cloud Data.”International Journal of Computer Engineering in Research Trends., vol.2, no.12, pp. 919-923, 2015. 
[18] Meghana A , Gaddam Gowthami , Mahendrakar Kavitha Bai  and  M.Srilakshmi,” Securing Personal Health Records in Cloud Utilizing Multi Authority Attribute Based Encryption.”International Journal of Computer Engineering in Research Trends., vol.1, no.4, pp. 214-219, 2014.
[19] PRAVEEN KUMAR and S.NAGA LAKSHMI,” Efficient Data Access Control for Multi-Authority Cloud Storage using CP-ABE..”International Journal of Computer Engineering in Research Trends., vol.2, no.12, pp. 1182-1187, 2015.
[20] Moulika Devi Vankala and G.P.S Prasanthi,” Analog and Digital PLL with Single Ended Ring VCO for “Full Swing Symmetrical Even Phase Outputs”..”International Journal of Computer Engineering in Research Trends., vol.3, no.8, pp. 441-446, 2016.
:10.22362/ijcert/2017/v4/i10/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I1006.pdf
Refbacks : Currently there are no refbacks
Proxy Cryptography Based on Data Uploading and Data Integrity in Cloud
Authors : Hafsa Fatima Amreen, Ms. FirdousRehana, Dr. G.S.S Rao
Affiliations : Nawab ShahAlam khan College of Engineering and Technology, Hyd
Abstract :

af

Many consumers wish to reserved their knowledge publicly cloud server (pcs). Along with the immersive evolution of cloud computing. There is a drawback within the security thus this security problem needs to be resolved to help purchasers to endeavor their knowledge in pcs. When pcs approach is incommodious for the consumer to the method the info the consumer can become envoy its proxy and so transfer them. There’s Associate in nursing another responsibility drawback referred to as remote knowledge integrity checking cloud storage publicly. It permits the consumer to examine whether or not their outsourced knowledge is unbroken flawless while not downloading the fundamental experience. From this security drawback, we tend to propose unique remote knowledge integrity. Checking and proxy originated knowledge uploading on identity-based publicly cloud employing a linear pairingripu-IDC protocol is represented. Supported the hardness of Diffie dramatist drawback the ripper-IDC protocol is assured. The particular ripe-IDC protocol is additionally coherent and pliant. Depends on the initial consumer authorization. The planned ripu-IDC will notice confidential remote knowledge integrity checking, emisory remote knowledge integrity checking and public remote knowledge integrity checking.
Citation :

af

Hafsa Fatima Amreen and Dr. G.S.S Rao (2017). Proxy Cryptography Based on Data Uploading and Data Integrity in Cloud . International Journal of Computer Engineering In Research Trends, 4(10), 392-399. Retrieved from http://ijcert.org/ems/ijcert_papers/V4I1004.pdf
Keywords : Public Cloud Server, Integrity Checking, BilinearPairing, Coherent, And Pliant.
References :

af

[1] V. Saiharitha, S. J. Saritha, “A privacy and dynamic multi-keyword ranked search scheme over cloud data encrypted” ,” IEICE Trans. Commun.,  pp. 190–200, 2016. 
[2] Y. Ren, J. Shen, J. Wang, J. Han, and S. Lee, “Mutual verifiable provable data auditing in public cloud storage,” J. Internet Technol., vol. 16, no. 2, pp. 317–323, 2015. 
[3] M. Mambo, K. Usuda, and E. Okamoto, “Proxy signatures for delegating signing operation,” in Proc. CCS, 1996, pp. 48– 57.
[4] E.-J. Yoon, Y. Choi, and C. Kim, “New ID-based proxy signature scheme with message recovery,” in Grid and Pervasive Computing (Lecture Notes in Computer Science), vol. 7861. Berlin, Germany: SpringerVerlag, 2013, pp. 945– 951. 
[5] B.-C. Chen and H.-T.Yeh, “Secure proxy signature schemes from the weil pairing,” J. Supercomput., vol. 65, no. 2, pp. 496–506, 2013.
[6] X. Liu, J. Ma, J. Xiong, T. Zhang, and Q. Li, “Personal health records integrity verification using attribute based proxy signature in cloud computing,” in Internet and Distributed Computing Systems (Lecture Notes in Computer Science), vol. 8223. Berlin, Germany: SpringerVerlag, 2013, pp. 238– 251. 
[7] H. Guo, Z. Zhang, and J. Zhang, “Proxy re-encryption with unforgeable re-encryption keys,” in Cryptology and Network Security (Lecture Notes in Computer Science), vol. 8813. Berlin, Germany: Springer-Verlag, 2014, pp. 20–33. 
[8] E. Kirshanova, “Proxy re-encryption from lattices,” in Public-Key Cryptography (Lecture Notes in Computer Science), vol. 8383. Berlin, Germany: Springer-Verlag, 2014, pp. 77–94. 
[9] P. Xu, H. Chen, D. Zou, and H. Jin, “Fine-grained and heterogeneous proxy re-encryption for secure cloud storage,” Chin. Sci. Bull., vol. 59, no. 32, pp. 4201–4209, 2014.
[10] S. Ohata, Y. Kawai, T. Matsuda, G. Hanaoka, and K. Matsuura, “Re-encryption verifiability: How to detect malicious activities of a proxy in proxy re-encryption,” in Proc. CT-RSA Conf., vol. 9048. 2015, pp. 410–428. 
[11] G. Ateniese et al., “Provable data possession at untrusted stores,” in Proc. CCS, 2007, pp. 598–609. 
[12] G. Ateniese, R. Di Pietro, L. V. Mancini, and G. Tsudik, “Scalable and efficient provable data possession,” in Proc. SecureComm, 2008, Art. ID 9. 
[13] C. C. Erway, A. Küpçü, C. Papamanthou, and R. Tamassia, “Dynamic provable data possession,” in Proc. CCS, 2009, pp. 213–222. 
[14] E. Esiner, A. Küpçü, and Ö. Özkasap, “Analysis and optimization on FlexDPDP: A practical solution for dynamic provable data possession,” Intelligent Cloud Computing (Lecture Notes in Computer Science), vol. 8993. Berlin, Germany: Springer-Verlag, 2014, pp. 65–83. 
[15] E. Zhou and Z. Li, “An improved remote data possession checking protocol in cloud storage,” in Algorithms and Architectures for Parallel Processing (Lecture Notes in Computer Science), vol. 8631. Berlin, Germany: SpringerVerlag, 2014, pp. 611–617. 
[16] H. Wang, “Proxy provable data possession in public clouds,” IEEE Trans. Services Comput., vol. 6, no. 4, pp. 551– 559, Oct./Dec. 2013. 
[17] H. Wang, “Identity-based distributed provable data possession in multicloud storage,” IEEE Trans. Services Comput., vol. 8, no. 2, pp. 328–340, Mar./Apr. 2015. 
[18] H. Wang, Q. Wu, B. Qin, and J. Domingo-Ferrer, “FRR: Fair remote retrieval of outsourced private medical records in electronic health networks,” J. Biomed. Inform., vol. 50, pp. 226–233, Aug. 2014. 
[19] H. Wang, “Anonymous multi-receiver remote data retrieval for pay-TV in public clouds,” IET Inf. Secur., vol. 9, no. 2, pp. 108–118, Mar. 2015.
[20] H. Shacham and B. Waters, “Compact proofs of retrievability,” in Proc. ASIACRYPT, vol. 5350.2008, pp. 90– 107.
[21] Q. Zheng and S. Xu, “Fair and dynamic proofs of retrievability,” in Proc. CODASPY, 2011, pp. 237–248.
[22] D. Cash, A. Küpçü, and D. Wichs, “Dynamic proofs of retrievability via oblivious RAM,” in Proc. EUROCRYPT, vol. 7881. 2013, pp. 279–295. 
[23] J. Zhang, W. Tang, and J. Mao, “Efficient public verification proof of retrievability scheme in cloud,” Cluster Comput., vol. 17, no. 4, pp. 1401–1411, 2014.
[24] J. Shen, H. Tan, J. Wang, J. Wang, and S. Lee, “A novel routing protocol providing good transmission reliability in underwater sensor networks,” J. Internet Technol., vol. 16, no. 1, pp. 171–178, 2015. 
[25] T. Ma et al., “Social network and tag sources based augmenting collaborative recommender system,” IEICE Trans. Inf. Syst., vol. E98-D, no. 4, pp. 902–910, 2015. //crypto.stanford.edu/pbc/thesis.pdf
[26] P.FARZANA, A.HARSHAVARDHAN,”Integrity Auditing for Outsourced DynamicCloud Data with Group User Revocation.”International Journal of Computer Engineering in Research Trends., vol.2, no.11, pp. 877-881, 2015.
[27] N. Meghasree,U.Veeresh and Dr.S.Prem Kumar,”Multi Cloud Architecture to Provide DataPrivacy and Integrity.”International Journal of Computer Engineering in Research Trends., vol.2, no.9, pp. 558-564, 2015.
[28] A.Shekinahpremasunaina,”Decentralized Fine-grained Access Controlscheme for Secure Cloud Storage data.”International Journal of Computer Engineering in Research Trends., vol.2, no.7, pp. 421-424, 2015.
[29] P. Rizwanakhatoon andDr.C.MohammedGulzar ,”SecCloudPro:A Novel Secure CloudStorage System for Auditing andDeduplication.”International Journal of Computer Engineering in Research Trends., vol.3, no.5, pp. 210-215, 2016.
[30] B.Sameena Begum, P.RaghaVardhini,”Augmented Privacy-Preserving AuthenticationProtocol by Trusted Third Party in Cloud.”International Journal of Computer Engineering in Research Trends., vol.2, no.5, pp. 378-382, 2015.
:10.22362/ijcert/2017/v4/i10/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I1004.pdf
Refbacks : Currently there are no refbacks
Hierarchical Clustering Over Rank Keyword Search with Secure and Competent Outlook
Authors : Ms. Shumaila Tajreen, Dr. G.S.S Rao,
Affiliations : Nawab ShahAlam khan College of Engineering and Technology, Hyd
Abstract :

af

As the volume of data in the data center is experiencing a tremendous growth, so vendor of data prefers to outsource sensitive and important documents for the purpose of privacy conserving. The documents are stored in encrypted format so it is essential to develop efficient search cipher text technique. In the process of encryption relationship between document is concealed which leads to perform deterioration. In this paper, a quality hierarchical clustering (QHC) method is proposed to support searching mechanism and to meet fast searching within cloud environment. In this paper multi-keyword ranked search, hierarchical clustering index (MRSE-HCI) architecture is used. For search result verification, least hash subtree is used. The proposed method has several advantages over traditional method in document’s retrieval and rank privacy.
Citation :

af

Ms. Shumaila Tajreen and Dr. G.S.S Rao (2017). Hierarchical Clustering Over Rank Keyword Search with Secure and Competent Outlook . International Journal of Computer Engineering In Research Trends, 4(10), 388-391. Retrieved from http://ijcert.org/ems/ijcert_papers/V4I1003.pdf
Keywords : Cloud Computing, Hierarchical Clustering, Security, Ciphertext search, multi keyword search, ranked search.
References :

af

[1].  Dynamic Multi-Keyword Ranked Searchable Security Algorithm Using CRSA and B-Tree Prasanna B T#1, C B Akki*2 #Department of ISE, EPCET Associate Professor, Bengaluru, INDIA-560049 *Department of ISE, SJBIT Professor, Bengaluru, INDIA-560060 
[2].  Reusability of Search Index over Encrypted Cloud Data on Dynamic update Kavitha R1, R J Poovaraghan2 Student, M.Tech, SRM University, Chennai, India1 Assistant Professor (OG), Department of Computer Science, SRM University, Chennai, India2.
[3]. Dynamic Multi-keyword Top-k Ranked Search over Encrypted Cloud Data Xingming Sun, Xinhui Wang, Zhihua Xia, Zhangjie Fu and Tao Li Jiangsu Engineering Center of Network Monitoring, Nanjing University of Information Science & Technology, Nanjing, 210044.
[4]. R. Ostrovsky, D. Boneh, G. Di Crescenzo, and G. Persiano, “Public key encryption with keyword search,” in Advances in Cryptology-Eurocrypt 2004, 2004, pp. 506–522.
[5]. R. Curtmola, J. Garay, S. Kamara and R. Ostrovsky “Searchable symmetric encryption: Improved definitions and efficient construc-tions”Proc. 13th ACM Conf. Comput. Commun. Secur., pp. 79-88, 2006.
[6]. G. Craig “Fully homomorphic encryption using ideal lattices”Proc. 41st Annu. ACM Symp. Theory Comput., vol. 9, pp. 169-178, 2009.
[7]. H. Pang, J. Shen and R. Krishnan ‘Privacy-preserving similarity-based text retrieval’ , ACM Trans. Internet Technol., vol. 10, no. 1, p. 39, Feb., 2010. 
[8]. Q.Wang et al, K. Ren, C.Wang, “Security challenges for the public cloud,” IEEE Internet Computing, 2012, vol. 16, no. 1, pp. 69–73.
[9]. S. Kamara, C. Papamanthou and T. Roeder “Dynamic searchable symmetric encryption”Proc. Conf. Comput. Commun. Secur., pp. 965-976, 2012.
[10]. S. Jarecki, C. Jutla, H. Krawczyk, M. Rosu and M. Steiner “Outsourced symmetric private information retrieval”Proc. ACM SIGSAC Conf. Comput. Commun. Secur., pp. 875-888, Nov., 2013.
[11]. D. Cash, S. Jarecki, C. Jutla, H. Krawczyk, M. Rosu and M. Steiner “Highly-scalable searchable symmetric encryption with support for Boolean que-ries”Proc. Adv. Cryptol,., pp. 353-373, 2013.
[12].  K. Ren, C. Wang, N. Cao, and W. Lou, “Enabling secure and efficient ranked keyword search over outsourced cloud data,” Parallel and Distributed Systems, IEEE Transactions on, 2012, vol. 23, no. 8, pp. 1467–1479.
[13]. S. Jarecki, D. Cash, J.Jaeger, C. Jutla, M. C. Rosu, and M.  Steiner, “Dynamic searchable encryption in very large databases: Data structures and implementation”, vol. 14, 2014,
[14]. R. X. Li, Z. Y. Xu, W. S. Kang, K. C. Yow and C. Z. Xu “Efficient Multi-keyword ranked query over encrypted data in cloud computing”Futur. Gener. Comp. Syst., vol. 30, pp. 179-190, Jan., 2014.
[15]. Chi Chen, Xiaojie Zhu, Peisong Shen “An Efficient Privacy-Preserving Ranked Keyword Search Method”, IEEE Transactions on Parallel and Distributed Systems, Vol. 27, No. 4, April 2016.  
[16] A.Raghavendra Praveen Kumar, K.Tarakesh, and U.Veeresh  ,” A Secure and Dynamic Multi Keyword Ranked Search Scheme over encrypted.” International Journal of Computer Engineering in Research Trends., vol.2, no.12, pp. 1137-1141, 2015.
[17] Mr. Rahul Hon, and Mrs. N.Sujatha,” A Novel Framework to Measure the Degree of Difficulty on Keyword Query Routing.” International Journal of Computer Engineering in Research Trends., vol.3, no.6, pp. 314-320, 2016.
[18] Kallem Rajender Reddy, and Y.Sunitha,” A Novel Framework to Measure the Degree of Difficulty on Keyword Query Routing.” International Journal of Computer Engineering in Research Trends., vol.2, no.9, pp. 640-645, 2015.
[19] Vadla Jhansi Rani, and K.Samson Paul,” Secure Multi Keyword Dynamic Search Scheme Supporting Dynamic Update..” International Journal of Computer Engineering in Research Trends., vol.4, no.8, pp. 356-360, 2017.
[20] Mr. M. Veerabrahma Chary  and Mrs.N.Sujatha,” A Novel Additive Multi-Keyword Search for Multiple Data Owners in Cloud Computing.” International Journal of Computer Engineering in Research Trends., vol.3, no.6, pp. 308-313, 2016.
:10.22362/ijcert/2017/v4/i10/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I1003.pdf
Refbacks : Currently there are no refbacks
An Encryption Scheme Based on Peculiarity For an Ordered File Hierarchy in Cloud Computing
Authors : Ms.Faiqa Mateen, Mr. Mohammed Khaleel Ahmed, 3 Dr. G.S.S Rao
Affiliations : Nawab ShahAlam khan College of Engineering and Technology, Hyd
Abstract :

af

There are several issues that always occur throughout the sharing of knowledge within the cloud. To unravel this,we use a technology of encoding known as the ciphertext attribute-based encoding which is employed in cloud computing. The files that are being shared on the cloud have the structure hierarchy feature. During this project, we propose the encoding policy supported peculiarity for associate ordered file hierarchy in cloud computing. The files that are present in an exceedingly graded format are encoded in an integrated access structure. The files that are in a serial layer format are combined into one structure that is accessible. This method saves plenty of time and price for the encoding. Below the quality assumption, this projected policy is verified to be secure and safe. Within the encoding and decipherment processes, the expected theme is established to be extremely economical. With the number of files increasing within the cloud because the users keep uploading them, the benefits of the projected theme become additional evident.
Citation :

af

Ms.Faiqa Mateen,Mr. Mohammed Khaleel Ahmed and Dr. G.S.S Rao (2017). An Encryption Scheme Based on Peculiarity For an Ordered File Hierarchy in Cloud Computing. International Journal of Computer Engineering In Research Trends, 4(10), 383-387. Retrieved from http://ijcert.org/ems/ijcert_papers/V4I1002.pdf
Keywords : Cloud computing, data sharing, file hierarchy, cipher text-policy, attribute-based.
References :

af

[1] C.-K. Chu, W.-T.Zhu, J. Han, J.-K. Liu, J. Xu, and J. Zhou, “Security concerns in popular cloud storage services,” IEEE Pervasive Comput., vol. 12, no. 4, pp. 50–57, Oct./Dec. 2013.
[2] T. Jiang, X. Chen, J. Li, D. S. Wong, J. Ma, and J. Liu, “TIMER: Secure and reliable cloud storage against data re-outsourcing,” in Proc. 10th Int. Conf. Inf. Secure. Pract.Exper., vol. 8434. May 2014, pp. 346–358.
[3] K. Liang, J. K. Liu, D. S. Wong, and W. Susilo, “An efficient cloud-based revocable identity-based proxy re-encryption scheme for public clouds data sharing,” in Proc. 19th Eur. Symp. Res. Comput. Secur., vol. 8712. Sep. 2014, pp. 257–272. 
[4] T. H. Yuen, Y. Zhang, S. M. Yiu, and J. K. Liu, “Identity-based encryption with post-challenge auxiliary inputs for secure cloud applications and sensor networks,” in Proc. 19th Eur. Symp. Res. Comput. Secur., vol. 8712. Sep. 2014, pp. 130–147.
[5] K. Liang et al., “A DFA-based functional proxy re-encryption scheme for secure public cloud data sharing,” IEEE Trans. Inf. Forensics Security, vol. 9, no. 10, pp. 1667–1680, Oct. 2014.
[6] T. H. Yuen, J. K. Liu, M. H. Au, X. Huang, W. Susilo, and J. Zhou, “k-times attribute-based anonymous access control for cloud computing,” IEEE Trans. Comput., vol. 64, no. 9, pp. 2595–2608, Sep. 2015.
[7] J. K. Liu, M. H. Au, X. Huang, R. Lu, and J. Li, “Fine-grained two factor access control for Web-based cloud computing services,” IEEE Trans. Inf. Forensics Security, vol. 11, no. 3, pp. 484–497, Mar. 2016.
[8] A. Sahai and B. Waters, “Fuzzy identity-based encryption,” in Advances in Cryptology. Berlin, Germany: Springer, May 2005, pp. 457–473. [9] V. Goyal, O. Pandey, A. Sahai, and B. Waters, “Attribute-based encryption for fine-grained access control of encrypted data,” in Proc. 13th ACM Conf. Comput. Commun.Secur., Oct. 2006, pp. 89–98.
[10] W. Zhu, J. Yu, T. Wang, P. Zhang, and W. Xie, “Efficient attribute-based encryption from R-LWE,” Chin. J. Electron., vol. 23, no. 4, pp. 778–782, Oct. 2014.
[11] J. Bethencourt, A. Sahai, and B. Waters, “Cipher text-policy attribute based encryption,” in Proc. IEEE Symp.Secur. Privacy, May 2007, pp. 321–334.
[12] L. Cheung and C. Newport, “Provably secure ciphertext policy ABE,” in Proc. 14th ACM Conf. Comput. Commun.Secur., Oct. 2007, pp. 456–465.
[13] L. Ibraimi, M. Petkovic, S. Nikova, P. Hartel, and W. Jonker, “Mediated ciphertext-policy attribute-based encryption and its application,” in Proc. 10th Int. Workshop Inf. Secur. Appl., Aug. 2009, pp. 309–323. 
[14] X. Xie, H. Ma, J. Li, and X. Chen, “An efficient ciphertext-policy attribute-based access control towards revocation in cloud computing,” J. Universal Comput. Sci., vol. 19, no. 16, pp. 2349–2367, Oct. 2013. 
[15] F. Guo, Y. Mu, W. Susilo, D. S. Wong, and V. Varadharajan, “CP-ABE with constant-size keys for lightweight devices,” IEEE Trans. Inf. Forensics Security, vol. 9, no. 5, pp. 763–771, May 2014.
[16] A. Balu and K. Kuppusamy, “An expressive and provably secure ciphertext-policy attribute-based encryption,” Inf. Sci., vol. 276, pp. 354–362, Aug. 2014.
[17] X. Liu, J. Ma, J. Xiong, and G. Liu, “Ciphertext-policy hierarchical attribute-based encryption for fine-grained access control of encryption data,” Int. J. Netw.Secur., vol. 16, no. 6, pp. 437–443, Nov. 2014.
[18] Y. Chen, Z. L. Jiang, S. M. Yiu, J. K. Liu, M. H. Au, and X. Wang, “Fully secure ciphertext-policy attribute based encryption with security mediator,” in Proc. 16th Int. Conf. Inf. Commun. Secur., vol. 8958. Dec. 2014, pp. 274–289.
[19] Y. Yang, J. K. Liu, K. Liang, K.-K. R. Choo, and J. Zhou, “Extended proxy-assisted approach: Achieving revocable fine-grained encryption of cloud data,” in Proc. 20th Eur. Symp. Res. Comput. Secur.(ESORICS), vol. 9327. Sep. 2015, pp. 146–166.
[20] J. Liu, X. Huang, and J. K. Liu, “Secure sharing of personal health records in cloud computing: Ciphertext-policy attribute-based signcryption,” Future Generat. Comput. Syst., vol. 52, pp. 67–76, Nov. 2015.
[21] K. Liang et al., “A secure and efficient ciphertext-policy attribute-based proxy re-encryption for cloud data sharing,” Future Generat. Comput. Syst., vol. 52, pp. 95–108, Nov. 2015.
[22] C.-I. Fan, V. S.-M.Huang, and H.-M. Ruan, “Arbitrary-state attributebased encryption with dynamic membership,” IEEE Trans. Comput., vol. 63, no. 8, pp. 1951–1961, Aug. 2014.
[23] H. Zheng, Q. Yuan, and J. Chen, “A framework for protecting personal information and privacy,” Secur.Commun.Netw., vol. 8, no. 16, pp. 2867–2874, Nov. 2015. 
[24] F. Xhafa, J. Wang, X. Chen, J. K. Liu, J. Li, and P. Krause, “An efficient PHR service system supporting fuzzy keyword search and fine-grained access control,” Soft Comput., vol. 18, no. 9, pp. 1795–1802, Sep. 2014.
[25] S. Wang, J. Yu, P. Zhang, and P. Wang, “A novel file hierarchy access control scheme using attribute-based encryption,” Appl. Mech. Mater., vols. 701–702, pp. 911–918, Jan. 2015.
[26] A.Shekinah Prema Sunaina,” Study on Competent and Revocable Data Access Control Scheme for Multi-Authority Cloud Storage Systems.” International Journal of Computer Engineering in Research Trends., vol.2, no.5, pp. 365-368, 2015.
[27] R.Srinivas and Ajay Kumar,” Attribute-Based Encryption for Reliable and Secure Sharing of PHR in Cloud Computing.” International Journal of Computer Engineering in Research Trends., vol.2, no.10, pp. 679-682, 2015.
[28] NUTAKKI PRASAD and K.KIRAN KUMAR,” A Dynamic Secure Multi Owner Data Sharing Scheme Over Cloud Computing.” International Journal of Computer Engineering in Research Trends., vol.2, no.10, pp. 889-895, 2015.
[29] S.L.SOWJANYA, D.RAVIKIRAN,” Secure Data Sharing for Dynamic Groups in the Public Cloud.” International Journal of Computer Engineering in Research Trends., vol.1, no.6, pp. 428-435, 2014.
[30] Allam Jyothi,G.Somasekhar and Dr S.Prem Kumar,” A Secure Multi-Owner Data Sharing Scheme for Dynamic Group in Public Cloud.” International Journal of Computer Engineering in Research Trends., vol.2, no.8, pp. 475-480, 2015.
 

:10.22362/ijcert/2017/v4/i10/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I1002.pdf
Refbacks : Currently There are no refbacks
Associating Social Media to e-Merchandise - A Cold Start Commodity Recommendation
Authors : Ms. Habeebunissa Begum, Dr. G.S.S Rao,
Affiliations : Nawab ShahAlam khan College of Engineering and Technology, Hyd
Abstract :

af

In recent years, the boundaries between e-commerce and social networking became increasingly blurred. Many e-commerce websites support the mechanism of social login where users can sign up the websites victimization their social network identities like their Facebook or Twitter accounts. Users can also post their contemporary purchased product on microblogs with links to the e-commerce product websites. Throughout this paper, we incline to propose a novel declare a cross-site cold-start product recommendation that aims to advocate product from e-commerce websites to users at social networking sites in “cold start” things, a retardant that has rarely been explored before. A massive challenge may be thanks to leverage knowledge extracted from social networking sites for a cross-site cold-start product recommendation. We tend to propose to use the coupled users across social networking sites and e-commerce websites (user’s global organization agency have social networking accounts and have created purchases on e-commerce websites) as a bridge to map users’ social networking choices to a clear feature illustration for a product recommendation. In specific, we incline to propose learning every users’ and merchandises’ feature representations (called user embedding and merchandise embedding, respectively) from info collected from e-commerce websites victimization continual neural networks, therefore, apply a modified gradient boosting trees methodology to rework users’ social networking choices into user embedding. We incline to develop a feature-based matrix then resolving approach which could leverage the learned user embedding for a cold-start product recommendation. Experimental results on associate degree outsized dataset made of the most important Chinese microblogging service SINA WEIBO and conjointly the biggest Chinese B2C e-commerce website JINGDONG have shown the effectiveness of our planned framework.
Citation :

af

Ms. Habeebunissa Begum.Dr. G.S.S Rao (2017). Associating Social Media to e-Merchandise - A Cold Start Commodity Recommendation: Study for Vehicular Ledger. International Journal of Computer Engineering In Research Trends, 4(10), 378-382. Retrieved from http://ijcert.org/ems/ijcert_papers/V4I1001.pdf
Keywords : e-commerce, product recommender, product demographic, microblogs, recurrent neural networks.
References :

af

1] F. Cheng, C. Liu, J. Jiang, W. Lu, W. Li, G. Liu, W. Zhou, J. Huang, and Y. Tang. Prediction of drug-target interactions and drug repositioning via network-based inference.PLoS Computational Biology, 8:e1002503, 2012. 
2] E. Constantinides. Influencing the online consumer’s behavior: the web experience.Internet research, 14:111–126, 2011.
3] J. L. Herlocker, J. A. Konstan, and J. Riedl.Explaining collaborative filtering recommendations. In Proceedings of the 2011 ACM conference on Computer supported cooperative work, pages 241–250. ACM,2011. 
4] C. Jayawardhena, L. T. Wright, and C. Dennis. Consumers online: intentions, orientations and segmentation. International Journal of Retail &Distribution Management, 35:515–526, 2011. 
5] A. Karatzoglou. Collaborative temporal order modeling. In Proceedings of the _fth ACM conferenceon Recommender systems, pages 313–316, 2009. 
6] I. Konstas, V. Stathopoulos, and J. Jose. On social networks and collaborative recommendation.InProceedings of the 32nd International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 195–202. ACM, 2007.
7] A. Liaw and M. Wiener.Classification and regression by randomforest.R news, 2:18–22, 2003. 
8] C.-H. Park and Y.-G. Kim. Identifying key factors affecting consumer purchase behavior in an online shopping context.International Journal of Retail & Distribution Management, 31:16–29, 2002.
9] P. Resnick, N. Iacovou, M. Suchak, P. Bergstrom, and J. Riedl. Grouplens: an open architecture for collaborative filtering of netnews. In Proceedings of the 1994 ACM Conference on Computer Supported Cooperative Work, pages 175–186. ACM, 2001.
10] B. Sarwar, G. Karypis, J. Konstan, and J. Reidl.Item-based collaborative filtering recommendation algorithms. In Proceedings of the 10th InternationalConference on World Wide Web, pages 285–295. ACM, 2001.
11] J. B. Schafer, J. A. Konstan, and J. Riedl.E-commerce recommendation applications. In Applications of Data Mining to Electronic Commerce, pages 115–153. Springer, 2001.
12] E. Shen, H. Lieberman, and F. Lam. What am I gonna wear?: scenario-oriented recommendation. In Proceedings of the 12th international conference on intelligent user interfaces, pages 365–368. ACM, 2000.
13] K. H. Tso-Sutter, L. B. Marinho, and L. Schmidt-Thieme.Tag-aware recommender systems by fusion of collaborative filtering algorithms. In Proceedings of the 2008 ACM symposium on Applied computing, pages 1995–1999. ACM, 2008.
14] R. Verheijden. Predicting purchasing behavior throughout the clickstream.Master’s thesis, Eindhoven University of Technology, May 1994.
15] F. Wu and B. A. Huberman.Novelty and collective attention.Proceedings of the National Academy of Sciences, USA, 104:17599–17601.
16].K.Arun ,A.SrinageshandM.Ramesh,”Twitter Sentiment Analysis on Demonetization tweets in India Using R language.”International Journal of Computer Engineering in Research Trends., vol.4, no.6, pp. 252-258, 2017.
17] TekurVijetha, M.SriLakshmi and Dr.S.PremKumar,” Survey on Collaborative Filtering and content-Based Recommending.” International Journal of Computer Engineering in Research Trends., vol.2, no.9, pp. 594-599, 2015.
18] N.Satish Kumar, SujanBabuVadde,” Typicality Based Content-BoostedCollaborative Filtering Recommendation Framework.” International Journal of Computer Engineering in Research Trends., vol.2, no.11, pp. 809-813, 2015.
19] D.Ramanjaneyulu, U.Usha Rani,” In Service-Oriented MSN ProvidingTrustworthy Service Evaluation.”International Journal of Computer Engineering in Research Trends., vol.2, no.12, pp. 1192-1197, 2015.
20]B.Kundan,N.Poorna Chandra Rao and DrS.PremKumar,” Investigation on Privacy and Secure content of location based Queries.” International Journal of Computer Engineering in Research Trends., vol.2, no.9, pp. 543-546, 2015.
:10.22362/ijcert/2017/v4/i10/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I1001.pdf
Refbacks : Currently There are no refbacks

 

Mechanization and Computerization in Road Transport Industry: Study for Vehicular Ledger
Authors : Dr.Porag Kalita, ,
Affiliations : Head: Automobile Engineering Department, Govt. of Assam,M R S Higher Secondary School, Titabor, Assam.
Abstract :

af

Efficient road transport is a complex subject and needs critical examination in order to have a fair idea of the subject. However, the important role of cargo transport by road plays in the development of the economy of a nation. Developing nation like India, raid transport is like to arteries of the giant body of industrial, agricultural and trading complex. Economic of transportation system is consisting by speedy movement, lesser loss or damage in transit. Lesser transit insurance cost of end transportation, deterioration in transit, detention at check post, costly finance, fuel price and heavy taxation. In terms of, mechanization and computerization, at present handling of cargo is done manually and all records and accounts are also maintained by man power. This indirectly increases the cost of transportation to a considerable extent. Resorting to mechanization for handling of cargo and computerization for records and accounts will go away in contributing to the economics of road transport.
Citation :

af

Dr.Porag Kalita. (2017). Mechanization and Computerization in Road Transport Industry: Study for Vehicular Ledger. International Journal of Computer Engineering In Research Trends, 4(9), 373-377. Retrieved from http://ijcert.org/ems/ijcert_papers/V4I9002.pdf
Keywords : Efficient transport, Loading Sheet, Movement of Goods, Vehicular ledger etc.
References :

af

[1] Article by BP Agarwal, in Journal of IRTDA, February.1983, Kolkata, India. 
[2] Course materials of IRTDA, Kolkatta, 1992.
[3] Dr.Porag Kalita,” Computer Application in Road Transport Industry in India: Study on Truck History Card..” International Journal of Computer Engineering in Research Trends., vol.2, no.9, pp. 600-608, 2015.
[4] Dr.Porag Kalita,”Experimental Study on Automobile Clutch Plate Juddering.” International Journal of Computer Engineering in Research Trends., vol.2, no.11, pp. 705-710, 2015.

:10.22362/ijcert/2017/v4/i9/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I9002.pdf
Refbacks : Currently There are no refbacks
A Study on Development of Multilingual Dictionary Software
Authors : Dr.J.VijiPriya , Dr.S.Suppiah , Ms. Adeela Ashraf
Affiliations : College of Computer Science and Engineering, University of Hail, Hail, Saudi Arabia
Abstract :

af

Machine Translation is global. Recently there is no global business without translation. Clients buy and sell everything online. Although there are various researchers to build translators, several research papers deal with design and implementation of Online Website Electronics Dictionaries, not Multilingual Dictionary software in any one of programming languages. As a result, there are many challenges to developers and researchers such as selection of programming language to develop machine translation software. This study presents the design and implementation of Multilingual Dictionary Software in Python. It motivates developers to build many more machine translators. This Multilingual Dictionary is tremendously useful to people who want a fast translation.
Citation :

af

Dr.J.VijiPriya ,Dr.S.Suppiah & Ms. Adeela Ashraf . (2017). A Study on Development of Multilingual Dictionary Software. International Journal of Computer Engineering In Research Trends, 4(9), 367-372. Retrieved from http://ijcert.org/ems/ijcert_papers/V4I9001.pdf
Keywords : Machine translation, Python, Multilingual, Dictionary, Text to Speech.
References :

af

1.	https://pypi.python.org/pypi/PyDictionary/1.3.4
2.	https://pythonhosted.org/goslate/
3.	http://pyttsx.readthedocs.io/en/latest/engine.html
4.	https://www.tutorialspoint.com/python/python_gui_programming.htm
5.	https://jkvsrg-english-to-multilingual dictionary.en.softonic.com/
6.	https://sourceforge.net/projects/jkvsrg-eng-multilingual-dict/
7.	https://www.altalang.com/beyond-words/2010/01/19/evaluating-machine-translationthe-present-and-future-of-multilingual-search/
8.	https://www.quora.com/Why-do-people-speak-different-languages-around-the-world-Why-dont-we-speak-the-same-language
9.	https://www.daytranslations.com/blog/2015/01/human-translation-important-5885
10.	https://www.cse.iitb.ac.in/~pb/papers/icon15-indowordnet-dictionary
11.	 Hutchins, W.J. 1995. Machine Translation: A Brief History. In Koerner, E.F.K.; Asher, R. E. (Eds.) A concise history of the language sciences: from the Sumerians to the cognitivists, Oxford: Pergamon Press, 431-445.
:10.22362/ijcert/2017/v4/i9/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I9001.pdf
Refbacks : Currently There are no refbacks

 

Novel Privacy Aware Public Auditing Scheme for Shared Cloud Data with Dynamic Groups
Authors : Mahendrakar Kavitha Bai, V.Leena Parimala ,
Affiliations : M.Tech(CSE),Dr.K.V.Subba Reddy Institute of Technology.Kurnool, Andhra Pradesh
Abstract :

af

Nowadays, cloud storage area turns out to be one of the critical services, for the reason that users can certainly modify and share data with others in the cloud. However, the integrity of distributed cloud data is susceptible to certain hardware errors, software failures or individual mistakes.
Citation :

af

Mahendrakar Kavitha Bai, & V.Leena Parimala . (2017). Novel Privacy-Aware Public Auditing Scheme for Shared Cloud Data with Dynamic Groups. International Journal of Computer Engineering In Research Trends, 4(8), 361-366. Retrieved from http://ijcert.org/ems/ijcert_papers/V4I8009.pdf
Keywords : Data Integrity; Homomorphic Verifiable; Nonframeability; Provable Security.
References :

af

[1] A. Fu, S. Yu, Y. Zhang, H. Wang and C. Huang, "NPP: A New Privacy-Aware Public Auditing Scheme for Cloud Data Sharing with Group Users," in IEEE Transactions on Big Data, vol. PP, no. 99, pp. 1-1.
doi: 10.1109/TBDATA.2017.2701347
[1] D. Fernandes, L. Soares, J. Gomes, et al, “Security issues in cloud environments: a survey,” International Journal of Information Security, vol. 12, no. 2, pp. 113-170, 2014. 
[2] W. Hsien, C. Yang, and M. Hwang, “A survey of public auditing for secure data storage in cloud computing,” International Journal of Network Security, vol.18, no.1, pp. 133-142, 2016. 
[3] J. Yu, K. Ren, C. Wang, et al, “Enabling Cloud Storage Auditing with Key-Exposure Resistance,” IEEE Transactions on Information Forensics and Security, vol.10, no.6, pp. 1167-1179, 2015.
 [4] Q. Wang, C. Wang, K. Ren, et al, “Enabling public auditability and data dynamics for storage security in cloud computing,” IEEE Transactions on Parallel and Distributed Systems, vol. 22, no. 5, pp. 847-859, 2011.
 [5] S. Yu, “Big privacy: challenges and opportunities of privacy study in the age of big data,” IEEE Access, vol. 4, no. 6, pp. 2751-2763, 2016. 
[6] C. Wang, Q. Wang, K. Ren, et al, “Privacy-preserving public auditing for data storage security in cloud computing,” Proceedings of IEEE INFOCOM, pp. 1-9, 2010. 
[7] B. Wang, B. Li, and H. Li, “Oruta: privacy-preserving public auditing for shared data in the cloud,” IEEE Transactions on Cloud Computing, vol.2, no.1, pp.43-56, 2014. 
[8] B. Wang, B. Li, and H. Li, “Knox: privacy-preserving auditing for shared data with large groups in the cloud,” Applied Cryptography and Network Security. Springer Berlin Heidelberg, pp. 507-525, 2012. 
[9] B. Wang, H. Li, and M. Li, “Privacy-preserving public auditing for shared cloud data supporting group dynamics,” Proceedings of IEEE ICC, pp. 1946-1950, 2013.
 [10] B. Wang, B. Li, and H. Li, “Public auditing for shared data with efficient user revocation in the cloud,” Proceedings of IEEE INFOCOM, pp. 2904- 2912, 2013. 
[11] B. Wang, B. Li, and H. Li, “Panda: Public auditing for shared data with efficient user revocation in the cloud,” IEEE Transactions on Services Computing, vol.8, no.1, pp. 92-106, 2015.
[12] C. Liu, J. Chen, L. Yang, et al, “Authorized public auditing of dynamic big data storage on cloud with efficient verifiable fine-grained updates,” IEEE Transactions on Parallel and Distributed Systems, vol.25, no.9, pp. 2234-2244, 2014.
 [13] H. Wang, and Y. Zhang, “On the Knowledge Soundness of a Cooperative Provable Data Possession Scheme in Multicloud Storage,” IEEE Transactions on Parallel and Distributed Systems, vol.25, no.1, pp. 264-267, 2014.
 [14] L. Huang, G. Zhang, and A. Fu, “Privacy-preserving public auditing for dynamic group based on hierarchical tree,” Journal of Computer Research and Development, vol.53, no.10, pp. 2334-2342, 2016. [15] Y. Yu, J. Ni, M. Au, et al, “Comments on a public auditing mechanism for shared cloud data service,” IEEE Transactions on Services Computing,vol.8, no.6, pp. 998-999 2015. 
[16] G. Ateniese, R. Burns, R. Curtmola, et al, “Provable data possession at untrusted stores,” Proceedings of ACM CCS, pp. 598-609, 2007.
 [17] A. Juels, and B. Kaliski, “PORs: Proofs of retrievability for large files,” Proceedings of ACM CCS, pp. 584-597, 2007.
 [18] Y. Yu, M. H. Au, and Y. Mu, “Enhanced privacy of a remote data integrity-checking protocol,” International Journal of Information Security, vol. 14, no. 4, pp. 307-318, 2015.
 [19] J. Yuan, and S. Yu, “Efficient public integrity checking for cloud data sharing with multi-user modification,” Proceedings of IEEE INFOCOM, pp. 2121-2129, 2014.
 [20] H. Wang, “Identity-based distributed provable data possession in multicolored storage,” IEEE Transactions on Services Computing, vol.8, no.2, pp.328-340, 2015.
 [21] L. Huang, G. Zhang, A. Fu, “Certificateless Public Verification Scheme with Privacy-preserving and Message Recovery for Dynamic Group,” Proceedings of ACSW, 2017. 
[22] T. Jiang, X. Chen, and J. Ma, “Public integrity auditing for shared dynamic cloud data with group user revocation,” IEEE Transactions on Computers, vol.65, no.8, pp.2363-2373, 2016. 
[23] H. Wang, “Proxy Provable Data Possession in Public Clouds,” IEEE Transactions on Services Computing, vol.6, no.4, pp.551-559, 2013. 
[24] Y. Yu, Y. L, J. N, et al., “Comments on public integrity auditing for dynamic data sharing with multiuser modification,” IEEE Transactions on Information Forensics and Security, vol.11, no.3, pp.658-659, 2016.
 [25] H. Jin, D. Wong, and Y. Xu, “Efficient group signature with forward secure revocation,” Security Technology. Springer Berlin Heidelberg, pp. 124-131, 2009.
[26] Mr. M. VEERABRAHMA CHARY, Mrs.N.SUJATHA,” A Novel Additive Multi-Keyword Search for Multiple Data Owners in Cloud Computing .” International Journal of Computer Engineering In Research Trends., vol.3, no.6, pp. 308-313, 2016.
[27] G.Lucy, D.Jaya Narayana Reddy, R.Sandeep Kumar,” Enabling Fine-grained Multi-keyword Search Supporting Classified Sub-dictionaries over Encrypted Cloud Data.” International Journal of Computer Engineering In Research Trends., vol.2, no.12, pp. 919-923, 2015.
 [28] G.Dileep Kumar, A.Sreenivasa Rao,” Privacy-Preserving Public Auditing using TPA for Secure Searchable Cloud Storage data.” International Journal of Computer Engineering In Research Trends., vol.2, no.11, pp. 767-770, 2015. 
[29] N. Meghasree,  U.Veeresh, Dr.S.Prem Kumar,” Multi Cloud Architecture to Provide Data Privacy and Integrity.” International Journal of Computer Engineering In Research Trends., vol.2, no.9, pp. 558-564, 2015. 
[30] P.FARZANA, A.HARSHAVARDHAN,” Integrity Auditing for Outsourced Dynamic Cloud Data with Group User Revocation.” International Journal of Computer Engineering In Research Trends., vol.2, no.11, pp. 877-881, 2015. 

:10.22362/ijcert/2017/v4/i8/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I8009.pdf
Refbacks : Currently There are no refbacks
Secure Multi Keyword Dynamic Search Scheme Supporting Dynamic Update.
Authors : Vadla Jhansi Rani, K.Samson Paul,
Affiliations : M.Tech(CSE),Dr.K.V.Subba Reddy Institute of Technology.Kurnool,Andhra Pradesh
Abstract :

af

Cloud computing is becoming predominant; data owners are motivated to delegate complex data managements to the commercial cloud for economic savings. Sensitive data is usually encrypted before being uploaded to the cloud, which unfortunately makes the frequently-used search function a challenging problem. In this paper, we present a new multi-keyword dynamic search scheme with result ranking to search encrypted data more secure and practical. In the scheme, we employ a powerful function-hiding inner product encryption to enhance the security by preventing the leakage of the search pattern. For the concern of efficiency, we adopt a tree-based index structure to facilitate the searching process and updating operations. A comprehensive security analysis is provided, and experiments over the real world data show that our scheme is efficient.
Citation :

af

Vadla Jhansi Rani, & K.Samson Paul. (2017). Secure Multi Keyword Dynamic Search Scheme Supporting Dynamic Update. International Journal of Computer Engineering In Research Trends, 4(8), 356-360. Retrieved from http://ijcert.org/ems/ijcert_papers/V4I8007.pdf
Keywords : secure search; ranked search; dynamic update; cloud computing.
References :

af

[1]Jingbo Yan, Yuqing Zhang, Xuefeng Liu,” Secure multi-keyword search supporting dynamic update and ranked retrieval,” Communication Technology (ICT)., Volume: 13, Issue: 10.
 [2] SONG D, WAGNER D, PERRIG A. Practical techniques for searches on encrypted data[C]// Proceedings of IEEE Symposium on Security and Privacy, 2000: 44-45.
[3] BOSCH C, HARTEL P, JONKER W, et al. A Survey of Provably Secure Searchable Encryption [J].ACM Computing Surveys, 2015, 47(2): 1-51.
[4] GOLLE P, STADDON J, and WATERS B. Secure Conjunctive Keyword Search over Encrypted Data[C]// Proceedings of Applied Cryptography and Network Security (ACNS), June 8-11, 2004:31-45.
[5] SUN Wenhai, WANG Bing, CAO Ning, et al. Verifiable Privacy-preserving Multi-keyword Text Search in the Cloud Supporting Similarity-based Ranking [J]. IEEE Transactions on Parallel and Distributed Systems, 2013, 25(11):71-82.
[6] CAO Ning, WANG Cong, LI Ming, et al. Privacy-Preserving Multi-Keyword Ranked Search over Encrypted Cloud Data [J]. IEEE Transactions on Parallel and Distributed Systems, 2014, 25(1): 222-233.
[7] XIA Zhihua, WANG Xinhui, SUN Xingming, et al.A Secure and Dynamic Multi-Keyword Ranked Search Scheme over Encrypted Cloud Data [J].IEEE Transactions on Parallel and Distributed Systems, 2016, 27(2): 340-352.
[8] KAMARA S, PAPAMANTHOU C, ROEDER T. Dynamic searchable symmetric encryption[C]//Proceedings of the 2012 ACM conference on Computer and communications security (CCS),2012: 965-976.
[9] CASH D, JAEGER J, JARECKI S. Dynamic Searchable Encryption in Very-Large Databases: Date Structures and Implementation[C]// Network & Distributed System Security Symposium (NDSS),February 23-26, 2014.
[10] KAMARA S, PAPAMANTHOU C. Parallel and dynamic, searchable symmetric encryption[C]//Proceedings of Financial Cryptography and Data Security (FC), April 1-5, 2013: 258-274.
[11] BISHOP A, JAIN A, KOWALCZYK L. Function-Hiding Inner Product Encryption[C]//Proceedings of Advances in Cryptology—ASIAic
[12] A.Raghavendra Praveen Kumar, K.Tarakesh,U.Veeresh,” A Secure and Dynamic Multi Keyword Ranked Search Scheme over encrypted.” International Journal of Computer Engineering In Research Trends., vol.2, no.12, pp. 1137-1141, 2015.
[13] Mr. M. VEERABRAHMA CHARY, Mrs.N.SUJATHA,” A Novel Additive Multi-Keyword Search for Multiple Data Owners in Cloud Computing .” International Journal of Computer Engineering In Research Trends., vol.3, no.6, pp. 308-313, 2016.
[14] G.Lucy, D.Jaya Narayana Reddy, R.Sandeep Kumar,” Enabling Fine-grained Multi-keyword Search Supporting Classified Sub-dictionaries over Encrypted Cloud Data.” International Journal of Computer Engineering In Research Trends., vol.2, no.12, pp. 919-923, 2015.
[15] G.Dileep Kumar, A.Sreenivasa Rao,” Privacy-Preserving Public Auditing using TPA for Secure Searchable Cloud Storage data.” International Journal of Computer Engineering In Research Trends., vol.2, no.11, pp. 767-770, 2015. 

:10.22362/ijcert/2017/v4/i8/xxxx [UNDER PROCESS]
DOI Link : not yet assigned
Download :
  V4I8007.pdf
Refbacks : Currently There are no refbacks
Utility Person Detection and Multi-View Video Tracking Annotation Model
Authors : M.Senbagapriya, Dr. P.Sumitra,
Affiliations : PG and Research Department of Computer Science Vivekananda College of Arts and Sciences for Women (Autonomous) Elayamapalayam.
Abstract :

af

In this thesis a generic methodology for the semi-automatic generation of reliable position annotations for evaluating multi-camera people-trackers on large video data sets. Most of the annotation data are automatically computed, by estimating a consensus tracking result from multiple existing trackers and people detectors and classifying it as either reliable or not. A small subset of the data, composed of tracks with insufficient reliability, is verified by a human using a simple binary decision task, a process faster than marking the correct person position. The proposed framework is generic and can handle additional trackers. In this thesis studied the most commonly used face edge detection techniques of Enhanced Sobel Edge Annotation Algorithm (ESEAA). Higher-level edge detection techniques and appropriate programming tools only facilitate the process but do not make it a simple task.
Citation :

af

M.Senbagapriya, & Dr. P.Sumitra. (2017). Utility Person Detection and Multi-View Video Tracking Annotation Model. International Journal of Computer Engineering In Research Trends, 4(8), 346-355. Retrieved from http://ijcert.org/ems/ijcert_papers/V4I8006.pdf
Keywords : Image processing, Digital Image Processing, Analog Image Processing Two dimensional signals
References :

af

[1]	M. Liem and D. Gavrila, “A comparative study on multi-person tracking using overlapping cameras,” in-proc. 9th Int. Comput. Vis. Syst., 2013, pp. 203–212.
[2]	C. Vondrick, D. Patterson, and D. Ramanan, “Efficiently scaling up crowdsourced video annotation,” Int. J. Comput. Vis., vol. 101, no. 1, pp. 184–204, Jan. 2013, doi: 10.1007/s11263-012-0564-1.
[3]	A. Utasi and C. Benedek, “A multi-view annotation tool for people detection evaluation,” in-proc. VIGTA, 2012, pp. 1–6.
[4]	L.ˇ Cehovin, M. Kristan, and A. Leonardis, “Is my new tracker better than yours?” in proc. WACV, Mar. 2014, pp. 540–547.
[5]	L. Marcenaro, P. Morerio, and C. S. Regazzoni, “Performance evaluation of multi-camera visual tracking,” in Proc. AVSS, Sep. 2012, pp. 464–469.
[6]	A. Milan, K. Schindler, and S. Roth, “Challenges of ground truth evaluation of multi-target tracking,” in Proc. CVPRW, Jun. 2013, pp. 735–742.
[7]	M. Kristan et al., “The visual object tracking VOT2013 challenge results,” in Proc. ICCVW, Dec. 2013, pp. 98–111.
[8]	S. Vijayanarasimhan and K. Grauman, “Active frame selection for label propagation in videos,” in-proc. ECCV, 2012, pp. 496–509.
[9]	I. Kavasidis, S. Palazzo, R. Di Salvo, D. Giordano, and C. Spampinato, “A semi-automatic tool for detection and tracking ground truth generation in videos,” in Proc. VIGTA, 2012, pp. 1–5.
[10]	I. Kavasidis, S. Palazzo, R. D. Salvo, D. Giordano, and C. Spampinato, “An innovative Web-based collaborative platform for video annotation,” Multimedia Tools Appl., vol. 70, no. 1, pp. 413–432, May 2013.
[11]	 Ajin P Thomas, Sruthi P.S, Jerry Rachel Jacob, Vandana V Nair, Reeba R,” Survey on Different Applications of Image Processing.” International Journal of Computer Engineering In Research Trends.,vol.4,no.2,pp. 13-19,2017. 
[12]	Trisha Chakraborty, Nikita Nalawade, Abhishri Manjre, Akanksha Sarawgi, Pranali P Chaudhari,” Review of Various Image Processing Techniques for Currency Note Authentication.” International Journal of Computer Engineering In Research Trends.,vol.3,no.3,pp. 119-122,2016. 
[13]	Gunjan, Er. Madan Lal,” Investigation of Various Image Steganography Techniques in Spatial Domain.” International Journal of Computer Engineering In Research Trends., vol.3,no.6,pp. 347-351,2016. 
[14]	 G.Prasanthi, A.Somasekhar,” Anti-Theft Tracking and Controlling Of Vehicle According Us.” International Journal of Computer Engineering In Research Trends., vol.2, no.12, pp. 898-903, 2015. 
:10.22362/ijcert/2017/v4/i8/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I8006.pdf
Refbacks : Currently There are no refbacks
Authorized Deduplication: An Approach for Secure Cloud Environment
Authors : Bachi Reddy Sarath Kumar Reddy, G.Viswanath,
Affiliations : ST. Johns College of Engineering & Technology, Yemmiganur, Kurnool (Dist)-Andhra Pradesh India.
Abstract :

af

nowadays a huge volume of data generated and stored into cloud data base from four corners of the universe, Data deduplication turns out to be more need for Cloud storage providers. By putting away a distinct duplicate copy of data, cloud Data extraordinarily diminishes their capacity and Data exchange costs. The benefits of data deduplication accompany a high cost regarding new security and protection contests. We propose secure data deduplication mechanism, a safe and efficient Storage service which guarantees bit level secure data deduplication and Data classified ness in the meantime. To perform secure access scheming user may satisfy access privileges issued by data owner at cloud level towards access restricting from unauthorized users or adversaries.
Citation :

af

Bachi Reddy Sarath Kumar Reddy, &G.Viswanath. (2017). Authorized Deduplication: An Approach for Secure Cloud Environment. International Journal of Computer Engineering In Research Trends, 4(8), 341-345. Retrieved from http://ijcert.org/ems/ijcert_papers/V4I8005.pdf
Keywords : Deduplication, authorized duplicate check, confidentiality, File level Check, Block Level Check, Convergent key, Metadata Supervisor.
References :

af

[1] P. Anderson and L. Zhang. “Fast and secure laptop backups with encrypted de-duplication”. In Proc. of USENIX LISA, 2010.
[2] M. Bellare, S. Keelveedhi, and T. Ristenpart. “Dupless: Server aided encryption for deduplicated storage”. In USENIX Security Symposium, 2013. 
[3] Pasqualo Puzio, Refik Molva ,MelekOnen,”CloudDedup: Secure Deduplication with Encrypted Data for Cloud Storage”, SecludIT and EURECOM, France. 
[4] Iuon –Chang Lin, Po-ching Chien ,”Data Deduplication Scheme for Cloud Storage” International Journal of Computer and Control(IJ3C),Vol1,No.2(2012) 
[5] Shai Halevi, Danny Harnik, Benny Pinkas,”Proof of Ownership in Remote Storage System”, IBM T.J.Watson Research Center, IBM Haifa Research Lab, Bar IIan University,2011.
 [6] M. Shyamala Devi, V.Vimal Khanna,Naveen Balaji ”Enhanced Dynamic Whole File De-Duplication(DWFD) for Space Optimization in Private Cloud Storage Backup”,IACSIT, August,2014.
 [7] Weak Leakage-Resilient Client –Side deduplication of Encrypted Data in Cloud Storage” Institute for Info Comm Research,Singapore,2013
 [8] Tanupriya Chaudhari , Himanshu shrivastav, Vasudha Vashisht, ”A Secure Decentralized Cloud Computing Environment over Peer to Peer”,IJCSMC,April,2013 
[9] Mihir Bellare, Sriram keelveedhi,Thomas Ristenart ,”DupLESS: Server Aided Encryption for Deduplicated storage” University of California, San Diego2013.
[10] Luna SA HSM. http://bit.ly/17CDPm1.
 [11] Opendedup. http://opendedup.org/. 
[12] Atul Adya, William J Bolosky, Miguel Castro, Gerald Cermak, Ronnie Chaiken, John R Douceur, Jon Howell, Jacob R Lorch, Marvin Theimer, and Roger P Wattenhofer. Farsite: Federated, available, and reliable storage for an incompletely trusted environment. ACM SIGOPS Operating Systems Review, 36(SI):1–14, 2002.
 [13] Mihir Bellare, Alexandra Boldyreva, and Adam ONeill. Deterministic and efficiently searchable encryption. In Advances in Cryptology-CRYPTO 2007, pages 535–552. Springer, 2007.
 [14] Mihir Bellare, Sriram Keelveedhi, and Thomas Ristenpart. Dupless: Server-aided encryption for deduplicated storage. 2013. 
[15] Mihir Bellare, Sriram Keelveedhi, and Thomas Ristenpart. Message-locked encryption and secure deduplication. In Advances in Cryptology–EUROCRYPT 2013, pages 296–312. Springer, 2013.
 [16] Kevin D. Bowers, Ari Juels, and Alina Oprea. Hail: a high-availability and integrity layer for cloud storage. In Proceedings of the 16th ACM conference on Computer and communications security, CCS ’09, pages 187–198, New York, NY, USA, 2009. ACM.
 [17] Landon P Cox, Christopher D Murray, and Brian D Noble. Pastiche: Making backup cheap and easy. ACM SIGOPS Operating Systems Review, 36(SI):285–298, 2002.
 [18] John R Douceur, Atul Adya, William J Bolosky, P Simon, and Marvin Theimer. Reclaiming space from duplicate files in a serverless distributed file system. In Distributed Computing Systems, 2002. Proceedings. 22nd International Conference on, pages 617–624. IEEE, 2002.
 [19] Danny Harnik, Benny Pinkas, and Alexandra Shulman-Peleg. Side channels in cloud services: Deduplication in cloud storage. Security & Privacy, IEEE, 8(6):40–47, 2010.
[20] Jollu Jayachandrudu,M.Sri lakshmi,Dr.S.Prem Kumar,” Enhanced Independent Access to Encrypted Cloud Databases ,”International Journal of Computer Engineering In Research Trends.,vol.2,no.9,pp. 589-593,2015.
[21] K.Naga Maha Lakshmi ,A.Shiva Kumar ,” Secure Data Deduplication and Data accessing among Multi-cloud Framework ,”International Journal of Computer Engineering In Research Trends.,vol.2,no.10,pp. 687-693,2015.
[22] D.Jayanarayana Reddy,M.Janardhan ,U.Veeresh,” Secure Data Deduplication over Distributed Cloud Server Framework with Effective User Revocation and Load Balancing.” International Journal of Computer Engineering In Research Trends.,vol.4,no.2,pp. 57-62,2017.
[23] Aradhyula Venkata Ramu, D.Ravi Kiran,” Novel Approach for Secure Data deduplication System .” International Journal of Computer Engineering In Research Trends.,vol.2,no.10,pp. 896-901,2015.
[24] K.Sudhamani,P.Rama Rao,R.Vara Prasad,” Secure Auditing and Deduplicating Data in Cloud,”International Journal of Computer Engineering In Research Trends.,vol.3,no.1,pp. 1-5,2016.
:10.22362/ijcert/2017/v4/i8/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I8005.pdf
Refbacks : Currently there are no refbacks
Protecting Data in Relational Database Management System using Purpose and Role-Based Access Control
Authors : Suraj Krishna Patil, Suhas B. Bhagate,
Affiliations : Computer Science & Engineering, TEI, Ichalkaranji, 416115, India
Abstract :

af

Background/Objectives: Privacy is a key requirement in handling personal and sensitive data. The Database Management System (DBMS) stores such kind of data and also provides tools to access and analyze this data. Methods/Statistical analysis: The Role-Based Access Control (RBAC) regulates the access to resources based on the roles of individual users. Purpose Based Access Control (PuBAC) regulates the access based on the purpose for which data can be accessed. It regulates the execution of queries based on purpose. Findings: From the result, it is observed that some records accessed by considering the purpose and role-based access control are less than some records accessed by original and purpose based access control query result. The system is more secure than the previous one. Improvements/Applications: This work can be used in the organizations, government, and private offices academic institutes. It can be extended to support big data and conditional purpose based access control.
Citation :

af

Suraj Krishna Patil, &Suhas B. Bhagate. (2017). Protecting Data in Relational Database Management System using Purpose and Role-Based Access Control. International Journal of Computer Engineering In Research Trends, 4(8), 336-340. Retrieved from http://ijcert.org/ems/ijcert_papers/V4I8004.pdf
Keywords : Privacy, Access Control, Query Rewriting
References :

af

1.	J.Byun and N.Li, “Purpose based access control for privacy protection in a relational database system,” VLDB J., vol.17, no.4, pp. 603–619, 2008.
2.	M.E.Kabir and H.Wang, “Conditional purpose based access control model for privacy protection,” in Proc. 20th Australian Conference Australian Database, 2009, vol.92, pp. 135–142.
3.	P.Colombo and E.Ferrari, “Enforcement of purpose based access control within relational database management systems,” IEEE Transactions Knowledge Data Engineering, vol.26, no.11, pp.2703-2716, Nov 2014.
4.	P.Colombo and E.Ferrari, “Enforcing obligations within relational database management systems”, IEEE Transactions Dependable secure computing, vol.11, no.4, pp.318-331, Jul/Aug 2014.
5.	M. Jafari, P. W. Fong, R. Safavi-Naini, K. Barker, and N. P. Sheppard, “Towards defining Semantic foundations for purpose-based privacy policies,” in Proc. 1st ACM Conf. Data Appl. Security Privacy, 2011, pp. 213-224.
6.	P.Colombo and E.Ferrari, “Efficient enforcement of action-aware purpose-based access control within relational database management systems,” IEEE Transaction Knowledge Data Engineering, vol. 27, no.08, pp. 2134-2147, Aug 2015.
7.	M. Kabir, H. Wang, and E. Bertino, “A role-involved conditional purpose-based access control model,” in E-Government, E-Services and Global Processes, series IFIP Advances in Information and Communication Technology, vol. 334, M. Janssen, W. Lamersdorf, J. Pries-Heje, and M. Rosemann, Eds. Springer, 2010. 
8.	V.Nikitha, P.Jhansi , K.Neelima and D.Anusha ,” Data sets preparing for Data mining analysis by SQL Horizontal Aggregation,” International Journal of Computer Engineering In Research Trends.,vol.3,no.9,pp. 225-229,2014.
9.	Neelima Kuderu, Dr. Vijaya Kumari,” Relational Database to NoSQL Conversion by Schema Migration and Mapping ,”International Journal of Computer Engineering In Research Trends.,vol.3,no.9,pp. 506-513,2016.
10.	Jollu Jayachandrudu,M.Sri lakshmi,Dr.S.Prem Kumar,” Enhanced Independent Access to Encrypted Cloud Databases ,”International Journal of Computer Engineering In Research Trends.,vol.2,no.9,pp. 589-593,2015. 
:10.22362/ijcert/2017/v4/i8/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I8004.pdf
Refbacks : There are currently no refbacks
A Novel Security Protocol for VANET
Authors : B. Divya, Dr. Ch. Mallikarjuna Rao,
Affiliations : Department of Computer Science and Engineering Gokaraju Rangaraju Institute of Engineering and Technology, Hyderabad, India
Abstract :

af

Vehicular ad-hoc network (VANET) has recently received signi?cant considerations to enhance traf?c security and ef?ciency. Notwithstanding, correspondence trust, and client protection still present useful worries to the sending of VANET, either suffer from the substantial workload of downloading the latest denial list from a remote authority or can't enable drivers made a beeline to choose the dependability of a message when the verification on messages is unknown. In this paper, to cope with these challenging concerns, we propose a new verification convention for VANET in a decentralized group model by using a new group signature scheme. In the assistance of the new group signature scheme, the proposed verification convention is featured with threshold authentication, ef?cient revocation, unforgeability, anonymity, and traceability. Also, the assisting group signature scheme may also be of independent interest, as it is characterized by ef?cient traceability and message-linkability at the same time. Broad investigations show that our proposed edge mysterious validation convention is secure, and the veri?cation of messages among vehicles can be quickened by utilizing batch message preparing methods.
Citation :

af

B. Divya, & Dr. Ch. Mallikarjuna Rao. (2017). A Novel Security Protocol for VANET. International Journal of Computer Engineering In Research Trends, 4(8), 330-335. Retrieved from http://ijcert.org/ems/ijcert_papers/V4I8003.pdf
Keywords : Vehicular ad-hoc networks (VANETs), conditional privacy, threshold authentication, group signature
References :

af

[1] Jun Shao, Xiaodong Lin, A threshold anonymous authentication protocol for valet
[2] S. Dietzel, E. Schoch, B. Konings, M. Weber, and F. Kargl, Resilient, secure aggregation for vehicular networks, IEEE Network, vol. 24, no. 1, pp. 2631, 2010. [Online]. Available: http://dx.doi.org/10.1109/ MNET.2010.5395780
 [3] The car two car communication consortium, http://www.car-to-car.org/.
[4] P. Papadimitratos, L. Buttyan, T. Holczer, E. Schoch, J. Freudiger, M. Raya, Z. Ma, F. Kargl, A. Kung, and J. Hubaux, Secure vehicular communication systems: Design and architecture, CoRR, vol. abs/0912.5391, 2009. [Online]. Available: http://arxiv.org/abs/0912.5391
 [5] G. Ateniese, J. Camenisch, M. Joye, and G. Tsudik, A practical and provably secure coalition-resistant group signature scheme, in Advances in Cryptology - CRYPTO 2000, 20th Annual International Cryptology Conference, Santa Barbara, California, USA, August 20-24, 2000, Proceedings, 2000, pp. 255270. [Online]. Available: http://dx.doi.org/10.1007/3-540-44598-6 16
 [6] J. Hubaux, S. Capkun, and J. Luo, The security and privacy of smart vehicles, IEEE Security & Privacy, vol. 2, no. 3, pp. 4955, 2004. [Online]. Available: http://doi.ieeecomputersociety.org/10.1109/ MSP.2004.26
 [7] M. Raya and J. Hubaux, Securing vehicular ad hoc networks, Journal of Computer Security, vol. 15, no. 1, pp. 3968, 2007. [Online]. Available: http://iospress.metapress.com/openurl.asp?genre= article&issn=0926-227X&volume=15&issue=1&spage=39
 [8] Y. Sun, R. Lu, X. Lin, X. Shen, and J. Su, An ef?cient pseudonymous authentication scheme with strong privacy preservation for vehicular communications, IEEE T. Vehicular Technology, vol. 59, no. 7, pp. 35893603, 2010. [Online]. Available: http: //dx.doi.org/10.1109/TVT.2010.2051468
 [9] X. Lin and X. Li, Achieving ef?cient cooperative message authentication in vehicular ad hoc networks, IEEE T. Vehicular Technology, vol. 62, no. 7, pp. 33393348, 2013. [Online]. Available: http://dx.doi.org/10.1109/TVT.2013.2257188 
[10] L. Wischhof, A. Ebner, and H. Rohling, Information dissemination in self-organizing intervehicle networks, IEEE Transactions on Intelligent Transportation Systems, vol. 6, no. 1, pp. 90101, 2005. [Online]. Available: http://dx.doi.org/10.1109/TITS.2004.842407
 [11] P. Golle, D. H. Greene, and J. Staddon, Detecting and correcting malicious data in vanets, in Proceedings of the First International Workshop on Vehicular Ad Hoc Networks, 2004, Philadelphia, PA, USA, October 1, 2004, 2004, pp. 2937. [Online]. Available: http://doi.acm.org/10.1145/1023875.1023881
 [12] L. Zhang, Q. Wu, A. Solanas, and J. Domingo-Ferrer, A scalable robust authentication protocol for secure vehicular communications, IEEE T. Vehicular Technology, vol. 59, no. 4, pp. 16061617, 2010. [Online]. Available: http://dx.doi.org/10.1109/TVT.2009.2038222
[13] L. Chen, S. Ng, and G. Wang, Threshold anonymous announcement in vanets, IEEE Journal on Selected Areas in Communications, vol. 29, no. 3, pp. 605615, 2011. [Online]. Available: http: //dx.doi.org/10.1109/JSAC.2011.110310
[14] U. S. D. of Transportation, Dedicated short range communications, http://www.its.dot.gov/DSRC/.
[15] D. Chaum and E. van Heyst, Group signatures, in Advances in Cryptology - EUROCRYPT 91, Workshop on the Theory and Application of of Cryptographic Techniques, Brighton, UK, April 8-11, 1991, Proceedings, 1991, pp. 257265. [Online]. Available: http://dx.doi.org/10.1007/3-540-46416-6 22
[16] D. Boneh, X. Boyen, and H. Shacham, Short group signatures, in Advances in Cryptology - CRYPTO 2004, 24th Annual International CryptologyConference, Santa Barbara, California, USA, August 1519, 2004, Proceedings, 2004, pp. 4155. [Online]. Available: http://dx.doi.org/10.1007/978-3-540-28628-8 3
[17] Anusha.V,K.Sumalatha, Mobile Social Networks for Flattering Unsigned Profile Matching , International Journal of Computer Engineering In Research Trends.,vol.1,no.6,pp. 384-390,2014.
[18] D.Ramanjaneyulu ,U.Usha Rani, In Service-Oriented MSN Providing Trustworthy Service Evaluation, International Journal of Computer Engineering In Research Trends.,vol.2,no.12,pp. 1192-1197,2015.
[19] Komal Patil, Geeta Mahajan, Disha Patil and Chitra Mahajan, Implementation of Motion Model Using Vanet, International Journal of Computer Engineering In Research Trends.,vol.3,no.4,pp. 179-182,2016.
[20] Pocha Nageswara Reddy, I.S.Raghuram, Dr.S.Prem Kumar, Advance EMAP for Vehicular Ad Hoc Networks. International Journal of Computer Engineering In Research Trends.,vol.1,no.4,pp. 253-258,2016. 
:10.22362/ijcert/2017/v4/i8/xxxx [UNDER PROCESS]
DOI Link : Not Yet Assigned
Download :
  V4I8003.pdf
Refbacks : There are currently no refbacks
File Sharing System between P2P
Authors : Ashayyagari Geyasri, Dr. S. Govinda Rao,
Affiliations : 1,2Department of Computer Science and Engineering Gokaraju Rangaraju Institute of Engineering and Technology Hyderabad, India
Abstract :

af

In this paper, making a framework which will share the record from one hub to another hub with high recurrence. Record sharing applications in portable impromptu systems (MANETs) have pulled in more consideration lately. The effectiveness of document questioning experiences the properties of systems including hub portability and restricted correspondence range and asset. An instinctive technique to reduce this issue is to make document reproductions in the system, however, despite the endeavors on record replication, no exploration has concentrated on the worldwide ideal copy creation with least normal questioning deferral. To begin with, do not have a run to designate limited assets to various documents to limit the normal questioning postponement. Second, they consider capacity as available assets for copies, however, disregard the way that the record holders' recurrence of meeting different hubs likewise assumes a critical part in deciding document accessibility. Hypothetically examine the impact of asset assignment on the regular questioning postponement and infer an asset allotment administer to limit the normal questioning deferral. In this paper present another idea of an asset for record replication, which considers both hubs are stockpiling and meeting recurrence. In this paper additionally, propose an appropriated record replication convention to understand the proposed run the show. Broad follow driven examinations with blended follows and genuine follows demonstrate that our convention can accomplish shorter normal questioning postponement at a lower cost than current replication agreements.
Citation :

af

Ashayyagari Geyasri, & Dr. S. Govinda Rao. (2017). File Sharing System between P2P. International Journal of Computer Engineering In Research Trends, 4(8), 325-329. Retrieved from http://ijcert.org/ems/ijcert_papers/V4I8002.pdf
Keywords : MANETs, querying delay, sparsely distributed MANETs.
References :

af

[1]   Qik, http://qik.com/, 2014. 
[2]    Flixwagon, http://www.flixwagon.com/, 2014. 
[3]	C. Palazzi and A. Bujari, A Delay/Disruption Tolerant Solution for Mobile to Mobile File Sharing, Proc. IFIP/IEEE Wireless Days, 2010. 
[4]    Y. Tseng, S. Ni, and E. Shih, Adaptive Approaches to Relieving Broadcast Storms in a Wireless Multihop Mobile Ad Hoc Network, Proc. 21st Intl Conf. Distributed Computing Systems (ICDCS), pp. 481-488, 2001. 
[5]	B. Chiara et al., HiBOp: A History Based Routing Protocol for Opportunistic Networks, Proc. IEEE Intl Symp. World of Wireless, Mobile and Multimedia Networks (WoWMoM), 2007. 
[6]	A. Lindgren, A. Doria, and O. Schelen, Probabilistic Routing in Intermittently Connected Networks, ACM SIGMOBILE Mobile Computing and Comm. Rev., vol. 7, no. 3, pp. 19-20, 2003. 
[7]	F. Li and J. Wu, MOPS: Providing Content-Based Service in Disruption-Tolerant Networks, Proc. IEEE 29th Intl Conf. Distributed Computing Systems (ICDCS), 2009. 
[8]	      S. Moussaoui, M. Guerroumi, and N. Badache, Data Replication in Mobile Ad Hoc Networks, Proc. Second Intl Conf. Mobile Ad-hoc and Sensor Networks (MSN), pp. 685-697, 2006. 
[9]	L. Yin and G. Cao, Supporting Cooperative Caching in Ad Hoc Networks, IEEE Trans. Mobile Computing, vol. 5, no. 1, pp. 77-89, Jan. 2006. 
[10]		C.V.Anchugam,Dr.K.Thangadurai, Link quality based Ant based Routing Algorithm (LARA) in MANETs, International Journal of Computer Engineering In Research Trends.,vol.4,no.1,pp.52-60,2017.
[11]  Nilima N. Patil, Kuldeep K. Vartha, Ashwini W. Wankhade, Sagar A. Patil, Secure Routing for MANET in Adversarial Environment, International Journal of Computer Engineering In Research Trends.,vol.3,no.4,pp.199-203,2016.
[12]   Priya Manwani, Deepty Dubey, Hybrid Protocol for Security Peril Black Hole Attack in MANET, International Journal of Computer Engineering In Research Trends.,vol.3,no.3,pp. 92-97,2016.
[13]   N.Asha Jyothi, G.Ramya, G.Mounika, R.Sandeep Kumar, Enhance the QoS capability of Hybrid Networks using QoS-Oriented Distributed Routing Protocol, International Journal of Computer Engineering In Research Trends.,vol.1,no.4,pp. 178-82,2014.
[14]   Jalagam Nagamani,K.Sumalatha, EAACK: Secure IDS for Wireless Sensor Networks, International Journal of Computer Engineering In Research Trends.,vol.1,no.6,pp. 461-469,2014.
[15]   Komal Patil, Geeta Mahajan, Disha Patil, Chitra Mahajan, Implementation of Motion Model Using Vanet, International Journal of Computer Engineering In Research Trends.,vol.3,no.4,pp. 179-1,2014.
:10.22362/ijcert/2017/v4/i8/xxxx [UNDER PROCESS]
DOI Link : Not Yet Assigned
Download :
  V4I8002.pdf
Refbacks : There are currently no refbacks
A Honeypot for a Small Network using Raspberry pi
Authors : Rodney Anthony Raj, Chayapathi A R ,
Affiliations : Information science and engineering, Acharya Institute of Technology, Doctor Sarvepalli Radhakrishnan Rd, Bengaluru, Karnataka 560107, India.
Abstract :

af

The security is the biggest worry around the world let it be in any field or life. It is nothing different in cyber or network where the security is the biggest concern thinking about attacks which could happen anytime. So, this project is upon security, cyber security. Where a forensic device is built to monitor the network, and find the details of attackers1. This device does not act as an antivirus rather pulls the attacker to run some exploits and make them fall into the trap, a honeypot device which will perform all this when connected to a network. This device can also be used in forensics during crime scene to identify if any attacker is trying to steal any data. This device will not completely screen off the attacker or the attack but rather will notify and keep us on the tab by telling us there’s attack which may happen or happening. Attacks will never be stopped if we are connected to the internet. Hence, the solution provided here is to find out the attackers.
Citation :

af

Rodney Anthony Raj, Chayapathi A R . (2017).A Honeypot for a Small Network using Raspberry pi. International Journal of Computer Engineering In Research Trends, 4(8), 319-324. Retrieved from http://ijcert.org/ems/ijcert_papers/V4I8001.pdf
Keywords : Malware, Raspberry pi, Honeypot, Cybercrime, Rootkits, Attacker, network, PUTTY, Nmap and Hacker.
References :

af

1.	2016: Current State of Cybercrime, RSA    whitepaper.
2.	Basic survey on Malware Analysis, Tools, and Techniques. Dolly Uppall, Vishaka Mehra, and Vinod Verma, 2013.
3.	A survey of cybercrime. Zhicheng Yang., 2012.
4.	Detecting and Classifying Morphed Malware: A Survey Sanjam Singla, 2012.
5.	Evolution, Detection, and Analysis of Malware for Smart Devices Guillermo Suarez-Tangil, Juan E. Tapiador, Pedro Peris-Lopez, and Arturo Ribagorda, 2012.
6.	A Survey on Techniques in Detection and Analyzing Malware Executables Kirti Mathur, 2012.
7.	Malware Analysis and Classification: A Survey Ekta Gandotra, Divya Bansal, Sanjeev Sofat, 2012.
8.	Malware and cyber crime. House of Commons, Science and Technology Committee. 2012.
9.	Malware and Malware Detection Techniques: A Survey. Jyoti Landage, 2011.
10.	A Survey on Malware Attacks on Smartphones Kireet, Dr.Meda, and Sreenivasa Rao, 2011.
11.	Cybercrime and it’s types, analysis, and prevention techniques, Alpna, Sona Malhotra 2016.
12.	Web based Forensic Systems, srivathsa rao, vinaya hegde, jyothi Prasad, ijsrt, 2011.
13.	Y. Li and A. Nosratinia, “Security in cyber forensics,” Wireless Communications, IEEE Transactions on, vol. 11, no. 1, pp. 328–337, 2011.
14.	Cyber Black Box: Network intrusion forensics system for collecting and preserving evidence of attack, Jong Hyun Kim, Australian Fornsics, 2015
15.	Cybersecurity:risks, vulnerabilities and countermeasures to prevent social engineering attacks Conteh, Schmick, 2016
:10.22362/ijcert/2017/v4/i8/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I8001.pdf
Refbacks : Currently there are no refbacks

 

Non-Stationary Signal Analysis A Modified Time Frequency Approach
Authors : Devika, Monalisa Nayak, Kodanda Dhar Sa, Dillip Dash
Affiliations : Department of Electronics and Tele Communication, Indira Gandhi Institute of Technology, Odisha, India
Abstract :

af

Fourier investigation becomes invaluable when the signal contains non-stationary characteristics or transitory characteristics like transients and patterns that vary with time. As time domain and frequency domain representations are inadequate to give all the information possessed by the non-stationary signal. Therefore time-Frequency methods (TFMs) are used to analyze a signal in time and frequency domains simultaneously. This paper deals with the analysis of non-stationary signals by using short time Fourier transform; fractional Fourier transform to analyze the time frequency behavior of the non-stationary signal. A combination method is known as Short time fractional Fourier transform (STFRFT) also proposed here, which provides unique properties of the non-stationary signal. By using different windows like the rectangular window, Hamming window, Hanning window and Blackman window, the fractional Fourier transform of the chirp signal has been plotted. The MATLAB simulations were made to show the STFRFT of the signal.
Citation :

af

Devika, Monalisa Nayak,Kodanda Dhar Sa, Dillip Dash. (2017).Non-Stationary Signal Analysis A Modified Time Frequency Approach. International Journal of Computer Engineering In Research Trends, 4(7), 313-318. Retrieved from http://ijcert.org/ems/ijcert_papers/V4I7006.pdf
Keywords : Fourier Transform, FRFT, Non-Stationary signals, STFT, Window function
References :

af

[1] Qi L, Tao R, Zhou S, Wang Y., Detection and parameter estimation of multicomponent LFM signal based on the fractional Fourier transform. Science in China series F: information sciences, 2004, 47(2), pp. 184-98.
[2] Claasen T, Mecklenbräuker W., TIME-FREQUENCY SIGNAL ANALYSIS. Philips Journal of Research. 1980, 35(4/5), pp. 276-300.
[3] Rao P, Taylor F. Estimation of instantaneous frequency using the discrete Wigner distribution. Electronics letters, 1990,126 (4), pp. 246-8.
[4] Choi H, Williams W., Improved time-frequency representation of multicomponent signals using exponential kernels. IEEE Transactions on Acoustics, Speech, and Signal  Processing, 1989, 37(6), pp. 862-71.
[5] Hossen AN, Heute U, Shentov OV, Mitra SK. Subband DFT—part II: accuracy, complexity and applications. Signal Processing, 1995,41(3), pp. 279-94.
[6] Hammond JK, White PR., The analysis of non-stationary signals using time-frequency methods. Journal of Sound and Vibration. 1996, 190(3), pp. 419-47.
[7] Chen VC, Ling H., Time-frequency transforms for radar imaging and signal analysis.  Artech House, 2002.
[8] Narayanan VA, Prabhu KM.,  The fractional Fourier transform: theory, implementation and error analysis. Microprocessors and Microsystems, 2003, 27(10), pp. 511-21.
[9] Qu H, Wang R, Qu W, Zhao P.,  Research on DOA Estimation of Multi-Component LFM Signals Based on the FRFT. Wireless Sensor Network, 2009, 1(3), pp. 171-81.
[10] Sun HB, Liu GS, Gu H, Su WM, Application of the fractional Fourier transform to  moving target detection in airborne SAR, IEEE Transactions on Aerospace and  Electronic Systems, 2002, 38(4), pp. 1416-24.
[11] Tao R, Zhang F, Wang Y., Fractional power spectrum. IEEE Transactions on Signal Processing. 2008, 56(9), pp. 4199-206.
[12] Podder P, Khan TZ, Khan MH, Rahman MM. Comparative performance analysis of hamming, hanning and blackman window. International Journal of Computer  Applications, 2014,96(18), pp. 2001-2006.
:10.22362/ijcert/2017/v4/i7/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I7006.pdf
Refbacks : There are currently no refbacks
Enabling Secure and Effective Spatial Query Processing on the Cloud using Forward Spatial Transformation
Authors : V. Swathi, D. Saidulu, B. Chandrakala
Affiliations : Assistant Professor, Department of Computer Science and Engineering, Guru Nanak Institutions Technical Campus-Hyderabad, India.
Abstract :

af

Data outsourcing is a common cloud computing model that allows data owners to takings advantage of its on-demand storage and computational resources. The main challenge is maintaining data confidentiality regarding intruders. Presented methodologies either conciliation the undisclosed of the data or undergo from high communication cost between the server and the user. To overcome this problem, we suggest a dual transformation and encryption scheme for spatial data, where encrypted queries are executed entirely by the service provider on the encrypted database, and encrypted results are returned to the user.The user issues encrypted spatial range queries to the service provider and then use the encryption key to decrypt the query response returned which establishments a balance between the security of data and efficient query response as the queries be processed on encrypted data at the cloud server finally our proposed method moderates the unique query communication cost between the authorized user and service provider.
Citation :

af

V. Swathi, D. Saidulu, B. Chandrakala. (2017).Enabling Secure and Effective Spatial Query Processing on the Cloud using Forward Spatial Transformation. International Journal of Computer Engineering In Research Trends, 4(7), 301-307. Retrieved from http://ijcert.org/ems/ijcert_papers/V4I7004.pdf
Keywords : Data Encryption, Forward Spatial Transformation, Security, Query Processing, Database Outsourcing, Spatial Databases.
References :

af

[1] Z. Xiao and Y. Xiao, “Security and privacy in cloud computing,” IEEE Communications Surveys & Tutorials,, vol. 15, no. 2, pp. 843–859, 2013.
[2] M. L. Yiu, G. Ghinita, C. S. Jensen, and P. Kalnis, “Enabling search services on outsourced private spatial data,” The VLDB Journal, vol. 19, no. 3, pp. 363–384, 2010.
 [3] P. Wang and C. V. Ravishankar, “Secure and efficient range queries on outsourced databases using r-trees,” in 2013 IEEE 29th International Conference on Data Engineering (ICDE). IEEE, 2013, pp. 314–325.
 [4] A. M. Talha, I. Kamel, and Z. A. Aghbari, “Enhancing confidentiality and privacy of outsourced spatial data,” in 2015 IEEE 2nd International Conference on Cyber Security and Cloud Computing (CSCloud). IEEE, 2015, pp. 13–18. 
 [5] S. Yu, C. Wang, K. Ren, and W. Lou, “Achieving secure, scalable, and fine-grained data access control in cloud computing,” in IEEE Infocom, 2010 proceedings. IEEE, 2010, pp. 1–9. 
[6] H. Xu, S. Guo, and K. Chen, “Building confidential and efficient query services in the cloud with rasp data perturbation,” IEEE transactions on knowledge and data engineering, vol. 26, no. 2, pp. 322–335, 2014. 
[7] H. Hu, J. Xu, C. Ren, and B. Choi, “Processing private queries over untrusted data cloud through privacy homomorphism,” in IEEE 27th International Conference on Data Engineering. IEEE, 2011, pp. 601– 612.
 [8] G. Zhao, C. Rong, J. Li, F. Zhang, and Y. Tang, “Trusted data sharing over untrusted cloud storage providers,” in IEEE Second International Conference on Cloud Computing Technology and Science (CloudCom). IEEE, 2010, pp. 97–103.
[9] H. Hacigum¨ us, B. Iyer, and S. Mehrotra, “Providing database as a ¨ service,” in 18th International Conference on Data Engineering, 2002. Proceedings. IEEE, 2002, pp. 29–38. [10] E. Damiani, S. Vimercati, S. Jajodia, S. Paraboschi, and P. Samarati, “Balancing confidentiality and efficiency in untrusted relational dbmss,” in Proceedings of the 10th ACM conference on Computer and Communications Security. ACM, 2003, pp. 93–102. 
 [11] W.-S. Ku, L. Hu, C. Shahabi, and H. Wang, “Query integrity assurance of location-based services accessing outsourced spatial databases,” in Advances in Spatial and Temporal Databases. Springer, 2009, pp. 80– 97.
 [12] A. Khoshgozaran and C. Shahabi, “Private buddy search: Enabling private spatial queries in social networks,” in International Conference on Computational Science and Engineering, 2009 (CSE’09)., vol. 4. IEEE, 2009, pp. 166–173.
[13] Anil Kumar Uppula , Srinivasulu Tadisetty ,” Achieving better Authentication and Copyright protection Using DWT and SVD Based Watermarking Scheme,”International Journal of Computer Engineering In Research Trends.,vol.3,no.9,pp.487-491,September 2016.
[14] Venkata Srinivasu Veesam, Bandaru Satish Babu,” Evaluation of Captcha Technologies towards Graphical Password Scheme,” International Journal of Computer Engineering In Research Trends.,vol.2,no.1,pp.98-106,February 2015.
[15] D.J. Ashpin Pabi, N.Puviarasan, P.Aruna,” Fast Singular value decomposition based image compression using butterfly particle swarm optimization technique (SVD-BPSO),” International Journal of Computer Engineering In Research Trends.,vol.4,no.4,pp.128-135,April 2017.
:10.22362/ijcert/2017/v4/i7/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I7004.pdf
Refbacks : There are currently no refbacks
Effective Key Management In Dynamic Wireless Sensor Networks
Authors : Uma Vasala , Dr. G. R. Sakthidharan ,
Affiliations : M.Tech [CSE],Gokaraju Rangaraju Institute of Engineering and Technology
Abstract :

af

Recently, wireless detector networks (WSNs) have been deployed for a good form of applications, including military sensing, and pursuit, patient standing watching, traffic flow watching, wherever sensory devices typically move between different locations. Securing knowledge and communications need suitable encoding key protocols. In this paper, we tend to propose a certificate less efficient key management (CL-EKM) protocol for secure communication in dynamic WSNs characterized by node mobility. The CL-EKM supports economic key updates once a node leaves or joins a cluster and ensures forward and backward key secrecy. The protocol conjointly supports economic key revocation for compromised nodes and minimizes the impact of a node compromise on the protection of alternative communication links. A security analysis of our theme shows that our protocol is effective in defensive against separate attacks. We implement CL-EKMin Contiki OS and simulate it mistreatment Cooja machine to assess its time, energy, communication, and memory performance.
Citation :

af

Uma Vasala , Dr. G. R. Sakthidharan . (2017).Effective Key Management In Dynamic Wireless Sensor Networks . International Journal of Computer Engineering In Research Trends , 4(7), 308-312. Retrieved from http://ijcert.org/ems/ijcert_papers/V4I7005.pdf
Keywords : Wireless sensor networks, certificate less public key cryptography, key management scheme.
References :

af

[1] H. Chan, A. Perrig, and D. Song, “Random key predistribution schemes for sensor networks,” in Proc. IEEE Symp. SP, May 2003, pp. 197–213.
[2] W. Du, J. Deng, Y. S. Han, and P. K. Varshney, “A key predistribution scheme for sensor networks using deployment knowledge,” IEEE Trans. Dependable Secure Comput., vol. 3, no. 1, pp. 62–77, Jan./Mar. 2006.
[3] W. Du, J. Deng, Y. S. Han, P. Varshney, J. Katz, and A. Khalili, “A pairwise key predistribution scheme for wireless sensor networks,” ACM Trans. Inf. Syst. Secur., vol. 8, no. 2, pp. 228–258, 2005.
[4] M. Rahman and K. El-Khatib, “Private key agreement and secure communication for heterogeneous sensor networks,” J. Parallel Distrib. Comput., vol. 70, no. 8, pp. 858–870, 2010.
[5] M. R. Alagheband and M. R. Aref, “Dynamic and secure key management model for hierarchical heterogeneous sensor networks,” IET Inf. Secur., vol. 6, no. 4, pp. 271–280, Dec. 2012.
[6] D. S. Sanchez and H. Baldus, “A deterministic pairwise key predistribution scheme for mobile sensor networks,” in Proc. 1st Int. Conf. SecureComm, Sep. 2005, pp. 277–288.
[7] I.-H. Chuang, W.-T. Su, C.-Y. Wu, J.-P. Hsu, and Y.-H. Kuo, “Two-layered dynamic key management in mobile and long-lived cluster-based wireless sensor networks,” in Proc. IEEE WCNC, Mar. 2007, pp. 4145–4150.
[8] S. Agrawal, R. Roman, M. L. Das, A. Mathuria, and J. Lopez, “A novel key update protocol in mobile sensor networks,” in Proc. 8th Int. Conf. ICISS, vol. 7671. 2012, pp. 194–207.
[9] S. U. Khan, C. Pastrone, L. Lavagno, and M. A. Spirito, “An energy and memory-efficient key management scheme for mobile heterogeneous sensor networks,” in Proc. 6th Int. Conf. CRiSIS, Sep. 2011, pp. 1–8.
[10] X. Zhang, J. He, and Q. Wei, “EDDK: Energy-efficient distributed deterministic key management for wireless sensor networks,” EURASIP J. Wireless Commun. Netw., vol. 2011, pp. 1–11, Jan. 2011.
[11] N. Gura, A. Patel, A. Wander, H. Eberle, and S. C. Shantz, “Comparing elliptic curve cryptography and RSA on 8-bit CPUs,” in Proc. 6th Int. Workshop Cryptograph. Hardw. Embedded Syst., 2004, pp. 119–132.
[12] S. S. Al-Riyami and K. G. Paterson, “Certificateless public key cryptography,” in Proc. 9th Int. Conf. ASIACRYPT, vol. 2894. 2013, pp. 452–473.
[13] S. Seo and E. Bertino, “Elliptic curve cryptography based certificateless hybrid signcryption scheme without pairing,” CERIAS, West Lafayette, IN, USA, Tech. Rep. CERIAS TR 2013-10, 2013. [Online]. Available: https://www.cerias.purdue.edu/apps/reports_and_papers/.Seung-Hyun
[14] S. H. Seo, J. Won, and E. Bertino, “POSTER: A pairing-free certificateless hybrid sign cryption scheme for advanced metering infrastructures,” in Proc. 4th ACM CODASPY, 2014, pp. 143–146.
[15] Q. Huang, J. Cukier, H. Kobayashi, B. Liu, and J. Zhang, “Fast authenticated key establishment protocols for self-organizing sensor networks,” in Proc. 2nd ACM Int. Conf. WSNA, 2003, pp. 141–150.
[16] J.David Sukeerthi Kumar,” Investigation on Secondary Memory Management in Wireless Sensor Network,” International Journal of Computer Engineering In Research Trends.,vol .2,no.6,pp.387-391,June 2015.
[17] Kuruva Laxmanna, N.Poorna Chandra Rao, Dr.S.Prem Kumar,” Moderating vampire attacks in Wireless Sensor Network,” International Journal of Computer Engineering In Research Trends.,vol.1,no.3,pp.143-151,September 2014.
[18].P.G.V.SureshKumar,Seelam Sowjanya,”Developing an Enterpriseenvironment By Using Wireless Sensor Network System Architecture,” International Journal of Computer Engineering In Research Trends.,vol .2,no.10,pp.902-908,October 2015.
[19] Dr. C. Gulzar,AmeenaYasmeen," Maximum network lifetime with load balance and connectivity by clustering process for wireless sensor networks,”International Journal of Computer Engineering In Research Trends.,vol.3,no.7,pp.375-383,July 2016.
[20] A.Yogananda ,Chepuri Sai Teja ," A Multi-level Self-Controllable Authentication in Distributed m-Healthcare Cloud Environments, ” International Journal of Computer Engineering In Research Trends.,vol.3,no.8,pp.436-440,August 2016. 

:10.22362/ijcert/2017/v4/i7/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I7005.pdf
Refbacks : There are currently no refbacks
Searching of Web Data Using Ontological Matching
Authors : Shweta Shrivastava, Dr. Sanjay Agrawal,
Affiliations : AISECT University , Bhopal Ph.D. scholar Computer Sc. Department,
Abstract :

af

While phenomenally successful regarding size and number of users, today's World Wide Web is fundamentally a relatively straightforward artifact. Web content consists mainly of distributed hypertext and hypermedia and is accessed via a combination of keyword based search and link navigation. The explosion in both the range and quantity of web content has, however, highlighted some serious shortcomings in the hypertext paradigm. Every year, the number of documents on the Internet is increasing, presenting the correct information at the right time in the most appropriate form is important, and it results in better browsing experience for users. To deal with this issue, ontologys are proposed for knowledge representation, which is nowadays the backbone of semantic web applications. This is a challenging task as it requires complex queries to be answered with only a few keywords. Furthermore, it should allow the inferred knowledge to be retrieved easily and provide a ranking mechanism to reflect semantics and ontological importance. Proposed paper gives. A technique to improve the efficiency of matching web data with background knowledge.It finds correspondences between semantically related entities of ontology.
Citation :

af

Shweta Shrivastava , Dr. Sanjay Agrawal. (2017). Searching of Web Data Using Ontological Matching. International Journal of Computer Engineering In Research Trends , 4(7), 296-300. Retrieved from http://ijcert.org/ems/ijcert_papers/V4I7003.pdf
Keywords : Semantic Web, Ontology, Information Retrieval, inferred knowledge, ranking mechanism, Web Search.
References :

af

[1]  P Shvaiko, J Euzenat Ontology Matching: State of the Art and Future Challenges IEEE Transaction on Knowledge and Data Engineering, Vol. 25, No1. January 2013 Page(s): 158-176
[2]  Farrag, Tamer Ahmed, Saleh, Ahmed Ibrahim; Ali, Hesham Arafat Toward SWSs Discovery: Mapping from WSDL to OWL-S Based on Ontology Search and Standardization Engine IEEE Transaction on Knowledge and Data Engineering, Vol. 25, No5.  May 2013pages 1135-1147.
[3] A Telang, C Li, S Chakravarthy One Size Does Not Fit All: Toward User- and Query-Dependent Ranking for Web Databases IEEE transaction on knowledge and data engineering, vol 24, no9, September 2012 pages 1671 - 1685.
[4]  P Kremen, Z Kouba Ontology-Driven Information System Design IEEE Transaction on System, Man and Cybernetics-PartC: Applications and Reviewes, Vol. 42, No. 3, May 2012 pages 334  344.
[5] V Milea, F Frasincar, U Kaymak town: A Temporal Web Ontology Language IEEE Transaction on System, Man, and Cybernetics-PartB: Cybernetics, Vol. 42, No. 1, February 2012 pages 268 - 281.
[6] P Panov, S Dzeroski, L Soldatova OntoDM: An Ontology of Data Mining 2008 IEEE International Conference on Data Mining Workshops Page(s): 752 - 760.
  [7]  Wong, W Liu, M Bennamoun Ontology Learning from Text: A Look-Back and into the Future ACM Computing Surveys, Vol. 44, No. 4, Article 20, Publication date: August 2012.
[8]  Dimitrios A. Koutsomitropoulos, Ricardo Borillo Domenech, Georgia D. SolomouA Structured Semantic Query Interface for Reasoning Based Search and Retrieval The Semantic Web: Research and Applications Lecture Notes in Computer Sc. Volume 6643,2011,pp17-31.
[9]  J Zhai, K Zhou - Information Science and Management Semantic Retrieval for Sports Information Based on Ontology and SPARQL Published in:Information Science and Management Engineering (ISME), 2010 International Conference of  (Volume:1 )Date of Conference:7-8 Aug. 2010 Page(s): 395 - 398 .
[10]  Z Li, YL Zheng, SN Li, WW Liang  A Knowledge Sharing Convergence Platform Based on OWL-S and Semantic         Relations Published in Software Engineering (WCSE), 2010 Second World Congress on  (Volume:1 ) 19-20 Dec.  2010 Page(s): 65 - 68 .
[11]G. Shiva Prasad , N.V. Subba Reddy, U,Dinesh Acharya Knowledge Discovery from Web Usage Data: A Survey of Web Usage Pre processing Techniques  Information Processing and Management Communications in Computer and Information Science Volume 70, 2010, pp 505-507. 
[12]J. Euzenat and P. Shvaiko, Ontology Matching. Springer, 2007.
[13]F. Giunchiglia, M. Yatskevich, and P. Shvaiko, Semantic Matching: Algorithms and Implementation, J. on Data Semantics, vol. 9, pp. 1-38, 2007.
[14] J. Cardoso, Semantic Web Services: Theory, Tools, and Applications Idea Group, Inc., 2007.Web Services Description Language (WSDL), W3C Note, HTTP:// www.w3.org/TR/wsdl, 2001.
[15]Web Ontology Language for Services (OWL-S), W3C Member Submission, http://www.w3.org/Submission/OWL-S/, 2004.
[16]D. Martin, M. Burstein, D. Mcdermott, S.Mcilraith, M. Paolucci, K.Sycara, D.L. Mcguinness, E. Sirin, and N. Srinivasan, Bringing Semantics to Web Services with OWL-S World Wide Web, vol. 10, no. 3, pp. 243-277, Sept. 2007.
[17] T.A. Farrag and H.A. Ali, A Cluster-Based Semantic Web Services Discovery and Classification, Proc. ACME Second Intl Conf. Advanced Computer Theory and Eng., pp. 1825-1834, 2009.
[18]B. Di Martino, Semantic Web Services Discovery Based on Structural Ontology Matching, Intl J. Web and Grid Services, vol. 5, no. 1, pp. 46-65, 2009.
[19]OWL, http://www.w3.org/2004/OWL/, 2004.
[20]S Bhattacharjee, A Dwivedi, RR Prasad Ontology based spatial clustering framework for implicit knowledge discovery India Conference (INDICON), 2012 Annual IEEE 9 Dec. 2012 Page(s): 561 - 566 
[21]S. Chaudhuri, G. Das, V. Hristidis, and G. Weikum, Probabilistic Ranking of Database Query Results, Proc. 30th Intl Conf. Very Large Data Bases (VLDB), pp. 888-899, 2004.
[22[C. Dwork, R. Kumar, M. Naor, and D. Sivakumar, Rank Aggregation Methods for the Web, Proc. Intl Conf. World Wide Web (WWW), pp. 613-622, 2001.
[23]Yiyao Lu, Hai He, Hongkun Zhao, Weiyi Meng, Member, IEEE, and Clement Yu, Senior Member, IEEE Annotating Search Results from Web Databases IEEE Transaction on Knowledge and Data Engineering , Vol 25, No 3, March 2013.
[24] G Singh, V Jain, M Singh Ontology development using Hozo and Semantic analysis for information retrieval in Semantic Web  Image Information Processing (ICIIP), 2013 IEEE Second International Conference on 9-11 Dec. 2013 Page(s): 113 - 118 .
[25] Z Yun, S Huayou, Q Hengnian A Semantic Web Services discovery mechanism design and implementation based on OWL Ontology  Educational and Network Technology (ICENT), 2010 International Conference on 25-27 June 2010 Page(s): 139 - 143.
[26] Myint Myint Thein , Soe Lai Phyue , Mie Mie Su Thw, Semantic Web Information Retrieval in XML by mapping to RDF schema  Published in Networking and Information Technology (ICNIT), 2010 International Conference on 11-12 June 2010 Page(s): 500 - 503.
[27]T Bhatia  IJCST  Link Analysis Algorithms For Web Mining IJCT  vol 2 issue 2 June 2011
 [28]G Kumar, N Duhan, AK Sharma  Page ranking based on a number of visits of links of Web page  Computer and Communication Technology (ICCCT), 2011 2nd International Conference on 15-17 Sept. 2011 Page(s): 11 - 14 .
[29]J.R.G. Pulido a, M.A.G. Ruiz b, R. Herrera c, E. Cabello d, S. Legrand e, D. Elliman Ontology languages for the semantic web: A never completely updated review 0950-7051/$ - see front matter  2006 Elsevier B.V.
[30]. B.ASWINI, B.RANJITH, Robust Model-Based Data Management, International Journal of Computer Engineering in Research Trends, Volume 1, December 2014, pp 453-460. 
:10.22362/ijcert/2017/v4/i7/xxxx [UNDER PROCESS]
DOI Link : not yet updated
Download :
  V4I7003.pdf
Refbacks : There are currently no refbacks
Energy Consumption on Smartphone Web Browsing in 3G Network
Authors : Shital M Kuwarkar , Prof. U.A.Nuli,
Affiliations : Department of Computer Science and Engineering, D.K.T.E. Society’s Textile and Engineering Institute, Ichalkaranji, Shivaji University, Kolhapur, Maharashtra, India.
Abstract :

af

Nowadays usage of smartphone application has been reached great height. Web browsing on a smartphone takes a significant amount of power as it uses the features of 3G radio interface for downloading web pages. In this paper, two techniques are used to resolve this power consumption issue. In leading technologies, process computation sequence while loading a web page. Web browser first runs the computation that will generate new data transmission and put radio interface into low power state and release radio resource. Remaining computation is executed later. In the second technique, prediction of user reading time is performed using data mining techniques.
Citation :

af

Shital M Kuwarkar , Prof. U.A.Nuli. (2017). Energy Consumption on Smartphone Web Browsing in 3G Network. International Journal of Computer Engineering In Research Trends , 4(7), 290-295. Retrieved from http://ijcert.org/ems/ijcert_papers/V4I7001.pdf
Keywords : Radio Resource Control (RRC) protocol, DOM tree, Gradient Boosted Regression Tree (GBRT)
References :

af

[1] J. Flinn and M. Satyanarayanan, “Managing battery lifetime with energy-aware adaptation,” ACM Trans. Comput. Syst., pp. 137–179, May 2004.
[2] Virendrakumar Dhotre , Namdev Sawant , Pallavi Pawar, Rajshree Salgar  , Gitanjalee Hulwan,” Automatic Bus Enquiry System using Android”,International Journal of Computer Engineering In Research Trends, pp. 123-127, April-2017.
[3] J. Sorber, N. Banerjee, M. D. Corner, and S. Rollins, “Turducken: Hierarchical power management for mobile devices,” in Proc.ACM 3rd Int. Conf. Mobile Syst., Appl., Serv., 2005, pp. 261–274.
[4] M. Dong and L. Zhong, “Chameleon: A color-adaptive web browser for mobile OLED displays,” in Proc. ACM 9th Int. Conf. Mobile Syst., Appl., Serv., 2011, pp. 85–98.
[5] E. Shih, P. Bahl, and M. J. Sinclair, “Wake on Wireless: An event-driven energy saving strategy for battery operated devices,” in Proc. ACM 8th Annu. Int. Conf. Mobile Comput. Netw., 2002,pp. 160–171.
[6] F. R. Dogar, P. Steenkiste, and K. Papagiannaki, “Catnap: Exploiting high bandwidth wireless interfaces to save energy for mobile devices,” in Proc. ACM 8th Int. Conf. Mobile Syst., Appl., Serv., 2010, pp. 107–122.
[7] E. Rozner, V. Navda, R. Ramjee, and S. Rayanchu, “NAPman: network-assisted power management for wifi devices,” in Proc. ACM 8th Int. Conf. Mobile Syst., Appl., Serv., 2010, pp. 91–106.
[8] H. Zhu and G. Cao, “On supporting power-efficient streaming applications in wireless environments,” IEEE Trans. Mobile Comput., vol. 4, no. 4, pp. 391–403, Jul. 2005.
 [9] W. Hu, G. Cao, S. V. Krishanamurthy, and P. Mohapatra, “Mobility-assisted energy-aware user contact detection in mobile social networks,” in Proc. IEEE 33rd Int. Conf. Distrib. Comput Syst., 2013, pp. 155–164.
[10] A. Schulman, V. Navda, R. Ramjee, N. Spring, P. Deshpande, C. Grunewald, K. Jain, and V. N. Padmanabhan, “Bartendr: a practical approach to energy-aware cellular data scheduling,” in Proc. ACM 16th Annu. Int. Conf. Mobile Comput. Netw., 2010, pp. 85–96.
[11] A. J. Pyles, Z. Ren, G. Zhou, and X. Liu, “SiFii: Exploiting VoIP silence for WiFi energy savings insmart phones,” in Proc. ACM 13th Int. Conf. Ubiquitous Comput., 2011, pp. 325–334.
 [12] F. Qian, K. S. Quah, J. Huang, J. Erman, A. Gerber, Z. Mao, S. Sen, and O. Spatscheck, “Web caching on smartphones: Ideal vs. reality,” in Proc. ACM 10th Int. Conf. Mobile Syst., Appl., Services, 2012, pp. 127–140.
[13] B. Zhao, B. C. Tak, and G. Cao, “Reducing the delay and power consumption of web browsing on smartphones in 3G networks,” in Proc. IEEE 31st Int. Conf. Distrib. Comput. Syst., 2011, pp. 413– 422.
[14] N. Balasubramanian, A. Balasubramanian, and A. Venkataramani, “Energy consumption in mobile phones: A measurement study and implications for network applications,” in Proc. ACM 9th SIGCOMM Conf. Internet Meas. Conf., 2009, pp. 280–293.
[15] Configuration of Fast Dormancy, Std., Rev. Rel. 8, 2010. [Online]. Available: http://www.3gpp.org
[16] (2011) webkit’s speculative parsing, [Online]. Available: http://gent.ilcore.com/2011/01/webkitr.html
[17] (2012) Google SPDY, [Online]. Available: http://en.wikipedia.org/wiki/SPDY
[18] K. Zhang, L. Wang, A. Pan, and B. B. Zhu, “Smart caching for web browsers,” in Proc. 19th Int. World-Wide Web Conf., 2010, pp. 491–500.
[19] W. Hu and G. Cao, “Energy optimization through traffic aggregation in wireless networks,” in Proc. IEEE 33rd Annu. Int. Conf. Comput. Comm., 2014, pp. 916–924.

:10.22362/ijcert/2017/v4/i7/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I7001.pdf
Refbacks : There are currently no refbacks
Design a Fuzzy Logic Controller for Controlling Position of D.C. Motor
Authors : Zain-Aldeen S. A.Rahman, ,
Affiliations : Dept. of Electrical Techniques, Technical Institute / Qurna, Southern Technical University, Basra, Iraq
Abstract :

af

Fuzzy logic provides an accurate controller for controlling the systems when compared to the classical controllers such as a PID controller. In this work, a fuzzy logic controller (FLC) designed to control the position of a D.C. motor. The motor model is developed and transformed in subsystem by using the Matlab/ Simulink and its parameters taken from a datasheet for a real motor. The control signal adjusted in real time using proper fuzzy membership functions depending upon the armature voltage applied to the D.C. motor. Here tow inputs and one output are used. The fuzzy input variable (error) has seven membership functions, the fuzzy input variable (change of error) has five membership functions, and the fuzzy output variable represented by applied voltage has five membership functions. Important study parameters include input voltage of DC motor and its response for achieving accurate position and high efficiency of the motor. The results of the control achieved a suitable response for applications.
Citation :

af

Zain-Aldeen S. A.Rahman. (2017). Design a Fuzzy Logic Controller for Controlling Position of D.C. Motor. International Journal of Computer Engineering In Research Trends , 4(7), 285-289. Retrieved from http://ijcert.org/ems/ijcert_papers/V4I7002.pdf
Keywords : D.C. motor, Control, Position, System, Fuzzy, FLC
References :

af

1	Aisha Jilani et. al., “Controlling Speed of DC Motor with Fuzzy Controller in Comparison with ANFIS Controller”, Intelligent Control and Automation, 6, February 2015, pp. 64-47.

2	Rekha kushwah & Sulochana Wadhwani, “ Speed Control of Separately Excited Dc Motor Using Fuzzy Logic Controller”, International Journal of Engineering Trends and Technology (IJETT), Vol. 4, Issue 6, June 2013, pp. 2518-2523.

3	Md Akram Ahmad, et. al., “Speed control of a DC motor using Controllers”, Automation, Control and Intelligent Systems, 20, November, 2014; 2(6-1), pp. 1-9.

4	 AA Bature, et. al., “Design And Real Time Implementation Of Fuzzy Controller For DC Motor Position Control”, INTERNATIONAL JOURNAL OF SCIENTIFIC & TECHNOLOGY RESEARCH Vol.2, Issue 11, November, 2013, pp. 254-256.

5	Ravinder Kumar $ Vineet Girdhar, “ High Performance Fuzzy Adaptive Control for D.C. Motor”,  International Archive of Applied Sciences and Technology
IAAST; Vol 3 [3], Society of Education, India, September 2012, pp. 1- 10.

6	Ahmed El-Bakly, et. al., “ A Proposed DC Motor Sliding Mode Position Controller Design using Fuzzy Logic and PID Techniques” , 13th International Conference on AEROSPACE SCIENCES & AVIATION TECHNOLOGY, Military Technical College, Kobry Elkobbah, Cairo, Egypt, May 26 – 28, 2009, pp. 1-9.

7	Nirmala Ashok Dange & Ashwini Pawar, “ Position Control of Servo Motor Using Fuzzy Logic Controller”, International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, Vol. 5, Issue 6, June, 2016, pp. 5541- 5552.

8	SALIM, JYOTI OHRI, “FUZZY Based PID Controller for Speed Control of D.C. Motor Using LabVIEW” Vol. 10, 2015, pp. 154-159.

9	Umesh Kumar Bansal $ Rakesh Narvey, “Speed Control of DC Motor Using Fuzzy PID Controller”, Advance in Electronic and Electric Engineering, Vol. 3, No. 9,  Research India Publications, 2013, pp. 1209-1220.

10	 Miss. Vaishali Munde  & Prof. Mrs. V. S. Jape, “ Fuzzy Logic For Controlling Speed Of DC Motor”, The International Journal Of Engineering And Science (IJES), Vol. 2, Issue 5, 2013, pp. 33-39.
:10.22362/ijcert/2017/v4/i7/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I7002.pdf
Refbacks : There are currently no refbacks

 

Enhancing Load Balancing in Cloud Computing by Ant Colony Optimization Method
Authors : Prachi Verma, Sonika Shrivastava, R.K. Pateriya
Affiliations : Department of Computer Science & Engineering, MANIT, Bhopal, 462003, India
Abstract :

af

Cloud computing is an evolving technology which provides users “pay as you go” services on demand. Nowadays there is a tremendous increase in the use of the cloud by the clients due to its attractive features which results in a rapid growth of load on servers. Hence, load balancing has become a matter of concern in the domain of cloud computing. Load balancing is required to distribute the workload equally amongst all nodes in a network so that none of a node is overloaded or underloaded and each node does a similar amount of work in equal time. It minimizes the cost and time involved in the major computational models and helps to improve proper utilization of resources and system performance. Many approaches and algorithms are recommended by various researchers from all over the world to solve the problem of load balancing. In this paper, we present a technique built on Ant Colony optimization to address the issue of load balancing in a cloud environment.
Citation :

af

Prachi Verma, Sonika Shrivastava, & R.K. Pateriya. (2017). Enhancing Load Balancing in Cloud Computing by Ant Colony Optimization Method. International Journal of Computer Engineering In Research Trends, 4(6), 269-276. Retrieved from http://ijcert.org/ems/ijcert_papers/V4I6012.pdf
Keywords : Cloud Computing; Ant colony optimization, Swarm intelligence; Load Balancing;
References :

af

1 D. Saranya et.al, "Load Balancing Algorithms in Cloud Computing: A Review," International Journal of Advanced Research in Computer Science and Software Engineering, vol. 5, Issue 7, July 2015.
2 S. Sethi et.al, "Efficient Load Balancing in Cloud Computing using Fuzzy Logic," IOSR Journal of Engineering (IOSRJEN) ISSN: 2250-3021 vol. 2, pp. 65-71, July 2012.
3 T. Desai et.al, "A Survey of Various Load Balancing Techniques and Challenges in Cloud Computing," International Journal of Scientific & Technology Research, vol. 2, Issue 11, November 2013.
4 S. Rajoriya et.al, "Load Balancing Techniques in Cloud Computing: An Overview," International Journal of Science and Research (IJSR), vol. 3, Issue 7, July 2014
5 Sharma S. et.al, “Performance Analysis of Load Balancing Algorithms,” World Academy of Science, Engineering and Technology, 38, 2008.
6 Gross D. et.al, “Noncooperative load balancing in distributed systems”, Elsevier, Journal of Parallel and Distributed Computing, No. 65, pp. 1022-1034, 2005.
7 Nikravan M. et.al, “A Genetic Algorithm for Process Scheduling in Distributed Operating Systems Considering Load Balancing”, Proceedings 21st European Conference on Modelling and Simulation (ECMS), 2007.
8 M. Amar et.al, “SLA Driven Load Balancing for Web Applications in Cloud Computing Environment”, Information and Knowledge Management, 1(1), pp. 5-13, 2011.
9 Ekta Gupta et.al, “A Technique Based on Ant Colony Optimization for Load Balancing in Cloud Data Center”, 13th International Conference on Information Technology, 2014 IEEE.
10 M. Katyal et.al, “A Comparative Study of Load Balancing Algorithms in Cloud Computing Environment”, International Journal of Distributed and Cloud Computing Volume 1 Issue 2 December 2013 
11 S. Khan et.al, “Effective Scheduling Algorithm for Load Balancing using Ant Colony Optimization in Cloud Computing”, International Journal of Advanced Research in Computer Science and Software Engineering, Volume 4, Issue 2, February 2014..
12 Kun Li et.al, “Cloud Task scheduling based on Load Balancing Ant Colony Optimization”, 2011 Sixth Annual ChinaGrid Conference, 2011 IEEE.
13 D. Kashyap et.al, “A Survey Of Various Load BalancingAlgorithms In Cloud Computing”, INTERNATIONAL JOURNAL OF SCIENTIFIC & TECHNOLOGY RESEARCH VOLUME 3, ISSUE 11, NOVEMBER 2014. 
14 Book: Ant colony optimization by Macro Dorigo and Thomas Stutzle.
15 R. Rastogi et.al, "Load Balancing of Nodes in Cloud Using Ant Colony Optimization." Proceedings of the 14th International Conference on Computer Modelling and Simulation (UKSim), March 2012, IEEE, pp: 3-8.
16 Calheiros, R.N.; Ranjan, R.; Beloglazov, A.; de Rose, C.A.F.; Buyya, R. CloudSim: A toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms. Software 2011, 41, 23–50.
17. T.Deepa, & S Sharon Amulya Joshi. (2016). A Survey on Load Balancing Algorithms in Cloud.
International Journal of Computer Engineering In Research Trends, 3(7), 371-374. Retrieved from http://ijcert.org/ems/ijcert_papers/3703.pdf
:10.22362/ijcert/2017/v4/i6/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I6012.pdf
Refbacks : Currently There are no refbacks
CloudSim Framework for Federation of identity management in Cloud Computing
Authors : Rohit Shere, Sonika Shrivastava, R.K. Pateriya
Affiliations : Department of Computer Science & Engineering, MANIT, Bhopal, 462003, India
Abstract :

af

Cloud computing is built on several components for managing and making provision of abundant resources to business, on demand. Identity management is the essential element in cloud computing, and it is an inevitable standard security module that keeps away unauthorized users with unintentional interference to the system. The majority of work is being done to enhance this identity management component to overcome current limitations in authentication mechanisms. Federation among different clouds can be helpful in minimizing overhead and cost in overall identity management. Many cloud service providers are present in the industry with their independent identity management, but very few of them supports the federation among themselves to tackle the whole business collapse situation due to any disaster caused by nature. The Federation among these vendors can bring healthy competition in business markets that will lead to boost the confidence of cloud user in cloud computing. In this paper, our research work addresses a framework for researchers in identity management in cloud computing. The framework takes minimal effort and time for creating and simulating test environment for the generalized cloud environment.
Citation :

af

Rohit Shere, Sonika Shrivastava, & R.K. Pateriya. (2017). CloudSim Framework for Federation of identity management in Cloud Computing. International Journal of Computer Engineering In Research Trends, 4(6), 269-276. Retrieved from http://ijcert.org/ems/ijcert_papers/V4I6011.pdf
Keywords : FID, ECC algorithm, Hashing technique, CloudSim, Sign up Authentication.
References :

af

1.	Hong Liu, Student Member, IEEE, Huansheng Ning, Senior Member, IEEE, Qingxu Xiong, Member,IEEE, and Laurence T. Yang, Member, IEEE2014, “Shared Authority Based Privacy-preserving Authentication Protocol in Cloud Computing.”
2.	Adleman, L., “A subexponential algorithm for the discrete logarithm problem with application to cryptography”, Proc. 20th IEEE Found. Comp. Sci. Symp., 1979, 55-60. 
3.	Ganeshan R. et.al, “Performance analysis of Hyper-Elliptic Curve Cryptosystems over Finite Fields Fp for Genus 2 & 4”, IJCSNS Vol. 8 No. 12, Dec 2008
4.	“The Notorious Nine - Cloud Computing Top Threats in 2013,” https://downloads.cloudsecurityalliance.org/initiatives/top_threats“Panda: Public Auditing for Shared Data with Efficient User Revocation in the Cloud,” IEEE Transactions on Services Computing, VOL. X, NO. X, XXXX 2014, accepted.
5.	Jin Li, Yan Kit Li, Xiaofeng Chen, Patrick P. C. Lee, Wenjing Lou, “A Hybrid Cloud Approach for Secure Authorized Deduplication”, IEEE Transactions on Parallel and Distributed Systems, 2014.
6.	Lluis Pamies-Juarez, Pedro Garcia-Lopez, Marc Sanchez-Artigas, Blas Herrera, “Towards the Design of Optimal Data Redundancy Schemes for Heterogeneous Cloud Storage Infrastructures” ,” Computer Networks, Vol.55, 1100-1113, 2011.
7.	Deyan Chen, Hong Zhao, “Data Security and Privacy Protection Issues in Cloud Computing”, International Conference on Computer Science and Electronics Engineering 2012.
8.	K. Ren, C. Wang, and Q. Wang, “Security Challenges for the Public Cloud,” IEEE Internet Computing, vol. 16, no. 1, pp. 69–73,2012.
9.	Qian Wang, Cong Wang, Kui Ren, Wenjing Lou, Jin Li, ”Enabling Public Auditability and Data Dynamics for Storage Security in Cloud Computing”, Proc. IEEE transactions on parallel and distributed systems, vol. 22, no. 5, may 2011 .
10.	OASIS: Assertions and Protocol for the OASIS Security Assertion Markup Language (SAML) V2.0. OASIS Standard (2005) 
11.	Benjain Ertl, "Identity Harmonization for Federated HPC, Grid and Cloud Services", IEEE, pp. 621-627, 2016.
12.	Jaweher Zouari, "An Identity as a service framework for the cloud", IEEE, pp. 1-5, 2016.
13.	Yong Yu, "Identity based Remote Data Integrity hacking with perfect data privacy preserving for cloud storage", IEEE, pp. 1-11, 2016.
:10.22362/ijcert/2017/v4/i6/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I6011.pdf
Refbacks : There are currently no refbacks
Optimization of the 3rd Stage Rocket Trajectory Using Genetic Algorithm
Authors : K GOPINATH, P VIKRAM, N PRASHANTH
Affiliations : AERONAUTICAL DEPARTMENT,VEL TECH Dr.RR & Dr.SR UNIVERSITY
Abstract :

af

To optimize the third stage of a space launch vehicle, powered by Liquid Rocket Engine (LRE) and also to optimize the fuel efficiency by varying injection pressure and gravity turn. The space launch vehicle trajectory is designed analytically by using the general governing equations of the rocket. These trajectories are solved with the implementation of the genetic algorithm. The trajectories are designed and simulated with the commercial software MATLAB, furthermore the relation between parameters and generate MATLAB Coding to simulate the trajectory of the vehicle at 3rd stage. The governing equations are solved using Chebyshev polynomials subroutine and Lagrange polynomial equation available in MATLAB software. The variation of velocity, specific impulse, time is plotted for different parameter (injection pressure) values of the spacecraft
Citation :

af

K GOPINATH. (2017). Optimization of the 3rd Stage Rocket Trajectory Using Genetic Algorithm. International Journal of Computer Engineering In Research Trends, 4(6), 263-268. Retrieved from http://ijcert.org/ems/ijcert_papers/V4I6010.pdf
Keywords : 3rd Stage Rocket Trajectory Using Genetic Algorithm
References :

af

and space craft propulsion by
Martin J.L.Turner, states the information
about the above parameters1.
Trajectory Optimization for Target
Localization,Sameera S. Ponda
A simplified ascent trajectory optimization
procedure has been developed with
application of Ares I launch vehicle2.
Direct Trajectory Optimization by a
ChebyshevPseudospectral Method, journal
ofguidance, control, and dynamics Vol. 25,
No. 1, January–February 20023.
Fahroo, F., and Ross, I. M., “Costate
Estimation by a Legendre Pseudospectral
Method,” Journal of Guidance, Control, and
Dynamics, Vol. 24,No. 2, 2001, pp. 270–277.
Survey of Numerical Methods for
Trajectory Optimizationby John T. Betts
journal of guidance, control, and dynamics,
Vol. 21, No. 2, March–April 1998.
A chebyshev polynomial method for
optimal control with state
constraints,jacquesvlassenbroeckt,automatic
a, vol. 24, no. 4, pp. 499-506, 19884.
Space trajectory optimization and l1-
optimalcontrol problems, michael ross,
modern astrodynamics, pp. 155-
188,elsevierastrodynamics series, 20065.
A genetic algorithm approach to solving
optimal control problems with linearly
appearingcontrolsh. Seywaldr.r.kumarts.m.
deshpande,aiaa
:10.22362/ijcert/2017/v4/i6/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I6010.pdf
Refbacks : There are currently no refbacks
Biometrics based Cryptographic Key Generation using Finger Print
Authors : Mrs. A. Ruba, Dr. G. Rajkumar, Dr. K. Parimala
Affiliations : N.M.S.S.Vellaichamy Nadar College, Madurai – 625019, Tamilnadu, India.
Abstract :

af

Accurate and automatic identification and verification of users are essential in all system. Shared secrets like Personal Identification Numbers or Passwords and key devices such as Smart Cards are not presently adequate in few situations. What is necessary is a system that could authenticate that the person is the person. The biometrics is improving the capability to recognize the persons. The usage of biometrics system permits the identification of a living person according to the physiological or behavioral features to be accepted without human involvement. The construction of cryptographic key from biometrics is used to make safe our system. To implement this concept, sender’s recent fingerprint would be used to construct key by combining it with the information. For key decryption, the sender’s Database fingerprint images, which are previously kept by receiver’s end, would be used.
Citation :

af

Mrs. A. Ruba, Dr. G. Rajkumar, & Dr. K. Parimala. (2017). Biometrics based Cryptographic Key Generation using Finger Print. International Journal of Computer Engineering In Research Trends, 4(6), 259-262. Retrieved from http://ijcert.org/ems/ijcert_papers/V4I6009.pdf
Keywords : Information Security, Biometrics, Cryptography, Encryption, Decryption, Cryptographic Key Generation
References :

af

[1]	B. Raja Rao, Dr. E.V.V. Krishna Rao et al., “Finger Print Parameter based Cryptographic Key Generation”, International Journal of Engineering Research and Applications (IJERA), Vol. 2, Issue 6, Nov – Dec, 2012, pp. 1598 – 1604.
[2]	Dr. G. Rajkumar, Dr. K. Parimala and Mrs. A. Ruba, “An Innovative Approach to Genetic Algorithm based Cryptography”, International Jouranl of Computer Science, Vol. 5, Issue 1, No 9, 2017,  Page No. 1199 – 1202.
[3]	N. Ratha and J. Connell et al. Cancelable biometrics: A case study in fingerprints. Intl. Conf. on Pattern Recognition, page 370C373, 2006 
[4]	N. Ratha, J. Connell, and R. Bolle. Enhancing security and privacy in biometrics-based authentication systems. IBM Systems Journal, 40(3):614C634, 2001. 
[5]	Nanavati, S. Thieme, M. and Nanavati, R. Biometrics: Identity Verification in a Networked World. Wiley Computer Publishing, New York, 2002 
[6]	Saad Abuguba, Milan M. Milosavljevic, and Nemanja Macek, “An Efficient Approach to Generating Cryptographic keys from the face and Iris Biometrics fused at the feature level,” International Journal of Computer Science and Network Security, Vol. 15, No. 6, June 2015.
[7]	Sanjukta Pal, Sucharita Pal, Dr. Pranam Paul “Fingerprint Geometry matching by Divide and Conquer Strategy” accepted and published in International Journal of Advanced Research in Computer Science(IJARCS), ISSN No. 0976-5697, Volume 4, No. 4, March-April 2013.
[8]	T. Connie, A. Teoh, M. Goh, and D. Ngo, “ Palm hashing: A novel approach for cancellable biometrics," Information processing letters, vol. 93, no. 1, pp. 1-5, 2005
[9]	Cryptography and Network Security Principles and Practices by William Stalling, Prentice Hall, 2005.
[10]	M.Sathya, & Dr.K.Thangadurai. (2017). Implementation of Optimization Using Eclat and PSO for Efficient Association Rule Mining. International Journal of Computer Engineering In Research Trends, 4(1), 4-8. Retrieved from http://ijcert.org/ems/ijcert_papers/V4I0102.pdf.

:10.22362/ijcert/2017/v4/i6/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I6009.pdf
Refbacks : There are currently no refbacks
Twitter Sentiment Analysis on Demonetization tweets in India Using R language
Authors : K.Arun , A.Srinagesh , M.Ramesh
Affiliations : Department of Computer Science, Acharya Nagarjuna University, Guntur, India,Dept of CSE, RVR & JC College of Engineering, Guntur , India
Abstract :

af

In this global village social media is in the front row to interact with people, Twitter is the ninth largest social networking website in the world, only because of microblogging people can share information by way of the short message up to 140 characters called tweets, It allows the registered users to search for the latest news on the topics they have an interest, Lakhs of tweets shared daily on a real-time basis by the members, it has more than 328 million active users per month , Twitter is the best source for the sentiment and opinion analysis on product reviews, movie reviews, and current issues in the world. In this paper, we present the sentiment analysis on the current twitters like Demonetization, Indians and all over the world people are sharing their opinions on Twitter about current news in the country. The sentiment analysis extracts positive and negative opinions from the twitter data set, R Studio provides the best environment for this Twitter sentiment analysis. Access Twitter data from Twitter API, data is written into txt files as the input dataset. Sentiment analysis is performed on the input dataset that initially performs data cleaning by removing the stop words, followed by classifying the tweets as positive and negative by polarity of the words. Generate the word cloud. Finally, that generates positive and negative word cloud, comparison of positive and negative scores to get the current public pulse and opinion
Citation :

af

K.Arun, A.Srinagesh, & M.Ramesh. (2017). Twitter Sentiment Analysis on Demonetization tweets in India Using R language. International Journal of Computer Engineering In Research Trends, 4(6), 252-258. Retrieved from http://ijcert.org/ems/ijcert_papers/V4I6008.pdf
Keywords : Twitter Data, Text Mining, Sentiment Analysis, NLP, R-Studio.
References :

af

1)	 Efthymios Kouloumpis. Theresa Wilson, Johanna Moore “Twitter Sentiment Analysis: The Good the Bad and the OMG!” In the Proceedings of Fifth International AAAI Conference on Weblogs and Social Media ,2011.
2)	Thelwall, M., Buckley, K., Paltoglou, G., Cai, D., & Kappas, “A Sentiment strength detection in short text”, Journal of the American Society for Information Science and Technology, 61(12), 2544–2558, 2010
3)	https://apps.twitter.com/app/13647643, Date accessed:12/04/2017
4)	https://about.twitter.com/company,Date  accessed:12/04/2017
5)	http://blog.revolutionanalytics.com/2017/01/cran-10000.html
6)	Yu.H and Hatzivassiloglou.V “Towards answering opinion questions: separating facts from opinions and identifying the polarity of opinion sentences” In the Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP-03),NOV 2003.
7)	M De Choudhury, YR Lin, H Sundaram, KS Candan, L Xie, A Kelliher  “Authoritative Sources in a Hyperlinked Environment” International AAAI Conference on Weblogs and Social Media 2010, ed. Conference Program Committee, AAAI Press, New York., MAY 2010, pp-34-41.
8)	 Hu, M., & Liu, B. (2004). Mining opinion features in customer reviews. National Conference on Artificial Intelligence.
9)	https://lagunita.stanford.edu/c4x/Engineering/CS-224N/asset/slp4.pdf, Date accessed:21/04/2017
10)	Jockers, M. L. (2017). Syuzhet: Extract sentiment and plot arcs from text. Retrieved from  https://github.com/mjockers/syuzhet.
11)	Sunil B. Mane, Kruti Assar, Priyanka Sawant, & Monika Shinde. (2017). Product Rating using Opinion Mining. International Journal of Computer Engineering in Research Trends, 4(5), 161-168. Retrieved from http://ijcert.org/ems/ijcert_papers/V4I503.pdf. 
:10.22362/ijcert/2017/v4/i6/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I6008.pdf
Refbacks : There are currently no refbacks
RULE OF LAW-AN OVERVIEW
Authors : Deepti Monga, ,
Affiliations : Panjab University, Chandigarh, India
Abstract :

af

Background/Objectives: The concept of rule of law opposed to arbitrary use of discretionary power of administrative authorities. It says that rule should be according to law and not according to man. It is the basic structure of our Constitution. Equality before law is corollary of rule of law. Methods/Statistical analysis: The methodology which is going to be adopted for the present research work will mainly be based on doctrinal analysis, i.e., the theoretical sources. The theoretical work will relate to administrative action of public body; their policies; Constitutional, Legislative, Executive and judicial control of administrative action through doctrine of legitimate expectation. It is proposed to collect material from various discipline of administrative and Constitutional law. It is also pertinent to mention that research will heavily reply on various journals, reviews and national & international judicial pronouncements. Findings: the modern concept of rule of law implies that the function of government in the free society should be executed in such a way so that civil and political rights of individual are recognized. Rule of law opposed to arbitrary power. It is corollary to Article 14 as it requires fairness in administrative actions. To enable or to compete with each other on equal planes it is necessary to take positive steps to equip the disadvantaged to bring to the level of fortunate advantage.
Citation :

af

Deepti Monga .(2017).RULE OF LAW-AN OVERVIEW.International Journal of Computer Engineering In Research Trends,4(6),248-251.Retrieved from http://ijcert.org/ems/ijcert_papers/V4I6006.pdf
Keywords : Rule of law, right to equality, judicial review.
References :

af

  J.J.R. Upadhyaya, Administrative Law, 27 (2004).  
  I.P.Massy, Administrative Law, 20 (1998). 
  Upadhyaya, Supra note 1 at 27.
  Available at www.lexisnexis.co.uk accessed on October 27, 2016.
  Ram Prasaed Narayan Sahi v. State of Bihar, AIR 1953 SC 215 at 217.
  Available at plato.stanford.edu accessed on October 27, 2016.
  Upadhyaya, Supra note 1 at 27.
 Quoted in Jagdish Swarup, L. M. Singhvi, Constitution of India-II, 236-237(2006).
  Massy, Supra note 2 at 20.
  Jagdish Swarup, L. M. Singhvi, Supra note 8 at 236.
  Upadhyaya, Supra note 1 at 27.
  U.P.D. Kesari, Lectures on Administrative Law, 24 (14th Ed).
  M.P.Jain, Indian Constitutional Law, 6 (2006). 
  Upadhyaya, supra note 1 at 29-30.
  I.P.Massy, Administrative Law, 2 (1999). 
  (1976) 2 SCC 521.
  A.I.R. 1970 SC 150
  H.W.R. Wade, Administrative Law, 25-26 (1977).
  Upadhyaya, Supra note 1 at 30.
  (1990) 2 SCC 653 at 658-59.
  AIR 1988 SC 1768 at 1769.
  AIR 1982 SC 1325.
  AIR 1987 SC 579.
  1999 SCC (cri) 577.
  AIR 1975 SC 2299.
:10.22362/ijcert/2017/v4/i6/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I6006.pdf
Refbacks : There are Currently no refbacks
ESTOPPEL AND LEGITIMATE EXPECTATION
Authors : Deepti Monga, ,
Affiliations : Panjab University, Chandigarh, India
Abstract :

af

Background/Objectives: Estoppels is a rule of evidence which prevents a party from denying the fact which he has already been asserted. The doctrine of legitimate expectation is closely related to the principle of estoppel as both the doctrines are based upon a clear and unambiguous promise. Methods/Statistical Analysis: The methodology which is going to be adopted for the present research work will mainly be based on doctrinal analysis, i.e., the theoretical sources. The theoretical work will relate to the administrative action of the public body; their policies; Constitutional, Legislative, Executive and judicial control of administrative action through the doctrine of legitimate expectation. It is proposed to collect material from the various discipline of Administrative and Constitutional law. It is also pertinent to mention that research will heavily rely on different journals, reviews, and national & international judicial pronouncements. Findings: Legitimate expectation has an important place in the realm of administrative law. It is an integral component of the principle of the rule of law that power should not be exercised arbitrarily. One of the safeguards is provided through judicial interpretation in a long list of cases that this administration discretion is subject to legitimate expectation vested in the people. It cannot be expected that there can be judicial intervention in the policy framing by the executive as it is an essential function belonging to the executive.
Citation :

af

Deepti Monga .(2017).ESTOPPEL AND LEGITIMATE EXPECTATION.International Journal of Computer Engineering In Research Trends,4(6),242-247.Retrieved from http://ijcert.org/ems/ijcert_papers/V4I6005.pdf
Keywords : Legitimate expectation, estoppels, judicial review, natural justice, the rule of law.
References :

af

  	H.K. Saharay (Ed.), M. Monir’s Law of Evidence, volume 2, 1863 (2006).
  	C.D. Field’s (Revised by Gopats Chaturvedi), C.D. Field’s Law of Evidence in India, Pakistan, Bangladesh, Burma, Ceylon, Malaysia and Singapore, vol. 5 at 4249 (12th Edition, 2007).
  	Batuk Lal, The Law Of Evidence, 375 (2004).
  	(1851) 1 SIM (N.3.) 205 at 207 quoted in Denis Browne, Ashburner’s Principles of Equity, 445 (1933).
  	H.W.R. Wade, Administrative law, 64 (1988). 
  	Cited from Sharma Transport v. Govt. of A.P., (2002) 2 SCC 188 at 201.
  	Available at: http://www.cili.in/article/viewFile/1544/1130 accessed on February 16, 2009.

  	1880 ILR 5 Cal 669.
  	1905 ILR 29 Bom 580; (1904) 29 Bom 580.
  	Available at: https://indiankanoon.org/doc/1880129/ accessed on May 2, 2016.
  	AIR 1968 SC 718. 
  	Id. at 718.
  	AIR 1954 Cal 151.
  	Id. at 156.
  	Hira Industries Ltd. v. State of C.G. and Ors., AIR 2007 Chh 7 at 17.
  	(1969) 1 All ER 904.
  	Available at: http://www.supremeCourtofindia.nic.in/speeches/speeches_2009/Jud cial_Review_of_Administrative_Action at 8 accessed on August 24, 2009. 
  	C.F. Forsyth, “The Provenance and Protection of Legitimate Expectations”, The Cambridge Law Journal, vol. 47, No. 2, 238-260 at 238 (July, 1988). 
  	Bugalo Maripe, “Legitimate Expectations and the Right to a Hearing: Lessons from the George Arbi Case”, Journal of African Law, vol. 42, No. 1 94-100 at 97 (1998).
  	Civil Appeal No. 15/93 (unreported). 
  	Bugalo Maripe, supra note 80 at 96-97.
  	(1985) AC 375: (1985) AC 374 (408-409).
  	(1990) 170 CLR 1.
  	M.A. Ikhariale, “The Doctrine of Legitimate Expectations: Prospects and Problems in Constitutional Litigation in South Africa”, Journal of African Law, vol. 45, No. 1, 1-12 at 4 (2001).
.
  	Available at: https://www.quora.com/What-are-the-similarities-and-differences between-the-doctrine-of-legitimate-expectation-and-the-doctrine-of estoppel accessed on November 18, 2015.
  	R (Bibi) v. Newham, LBC (2002) 1 WLR 237 at 55 available at supra note 4 at 6.
  	Councils of Civil Service Unions v. Minister for Civil Services, (1984) 3 All ER 935 cited from   Navjyoti Co-Group Housing Society v. Union of India, AIR 1993 SC 155 at 165.
  	AIR 1993 SC 155. 
  	Id. at 155.
  	Haoucher v. Min., (1991) L.R.C. (Const.) 819 (836’) – Australia quoted in Durga Das Basu, Constitutional Remedies and Writs, 367 (1994).
  	Official Liquidator v. Dayanand, (2008) 10 SCC 1 at 66.
  	MANU/SC/0392/2003.
  	MANU /SC/0219/1994.
  	Supra note 31.
  	Id. at 223. 
  	AIR 1999 SC 1801.
  	Id. at 1801-1802.
  	(1979) 2 SCC 409.
  	Id. at 452.
  	(1998) 2 SCC 502.
  	Id. at 509.
:10.22362/ijcert/2017/v4/i6/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I6005.pdf
Refbacks : There are currently no refbacks
GST- Present and Future
Authors : Ms. BHAWNA MUKARIA , ,
Affiliations : Former Assistant Professor Hindu College (Commerce Department), Sonipat -131001, Haryana, India
Abstract :

af

This paper is an analysis of the impact of GST (Goods and Services Tax) on Indian Taxation System. Here, we will study with a brief description of the historical scenario of Indian Taxation and its tax structure. Here, we are going to study about the present tax system and the impact of implementing GST in Indian Economy. The changed indirect tax system GST- Goods and Service Tax is planned to execute in India. Govt does not yet declare the GST implementation. And the implementation of GST law is under process. It is going to be implemented on 1st July 2017. The objective will be to maintain a common point between the basic structure and design of CGST, SGST, and SGST between states. In this article, I have started with the history of taxation in India after that I have included various opportunities and challenges, proposed work and various impacts of GST on Economy that GST brings before us to strengthen our free market economy.
Citation :

af

BHAWNA MUKARIA .(2017).GST- Present and Future.International Journal of Computer Engineering In Research Trends,4(6),236-242.Retrieved from http://ijcert.org/ems/ijcert_papers/V4I6004.pdf
Keywords : GST (Goods ad Service Tax), VAT (Value Added Tax), CGST (Central Goods and Service Tax), SGST (State Goods and Service Tax), I-GST (Integrated Goods and Service Tax)
References :

af

1)	GST to hit consumers, unorganized jobs. The Tribune, 2016.
2)	M. Economics.com
3)	Indian Express.com>business>Economy
4)	www.relakhs.com
5)	www.mapsofindia.com
6)	http://en.m.wikipedia.org
:10.22362/ijcert/2017/v4/i6/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I6004.pdf
Refbacks : Currently there are no refbacks
Content-Based Image Retrieval in Cloud Using Watermark Protocol and Searchable Encryption
Authors : R.Santhi , Dr.D.Yuvaraj,
Affiliations : Computer Science and Engineering, M.I.E.T Engineering College, Trichy
Abstract :

af

With the development of the imaging devices, such as digital cameras, smartphones, and medical imaging equipments, our world has been witnessing a tremendous growth in quantity, availability, and importance of images. The needs of efficient image storage and retrieval services are reinforced by the increase of large-scale image databases among all kinds of areas. Compared with text documents, images consume much more storage space. Hence, its maintenance is considered to be a typical example for cloud storage outsourcing. For privacy-preserving purposes, sensitive images, such as medical and personal images, need to be encrypted before outsourcing, which makes the CBIR technologies in plaintext domain to be unusable. In order to secure the data in cloud, the proposed system supports CBIR over encrypted images without leaking the sensitive information to the cloud server. Firstly, feature vectors are extracted to represent the corresponding images. After that, the pre-filter tables are constructed by locality-sensitive hashing to increase search efficiency. Moreover, the feature vectors are protected by the secure kNN algorithm, and image pixels are encrypted by a standard stream cipher. In addition, considering the case that the authorized query users may illegally copy and distribute the retrieved images to someone unauthorized, a watermark-based protocol is used to deter such illegal distributions. In watermark-based protocol, a unique watermark is directly embedded into the encrypted images by the cloud server before images are sent to the query user. Hence, when an illegal image copy is found, the unlawful query user who distributed the image can be traced by the watermark extraction.
Citation :

af

R.Santhi,Dr.D.Yuvaraj.(2017).Content-Based Image Retrieval in Cloud Using Watermark Protocol and Searchable Encryption.International Journal of Computer Engineering In Research Trends,4(6),231-235.Retrieved from http://ijcert.org/ems/ijcert_papers/V4I6003.pdf
Keywords : CBIR (Content-Based Image Retrieval), kNN algorithm, watermark, encrypted image.
References :

af

1.	Zhihua Xia, Xinhui Wang, Liangao Zhang, Zhan Qin, Xingming Sun, Kui Ren, “A Privacy-preserving and Copy-deterrence Content-based Image Retrieval Scheme in Cloud Computing” IEEE TRANSCATION ON INFORMATION FORENSIC AND SECURITY, VOL.11, NO. 11, NOVEMBER 2016.

2.	B. Ferreira, J. Rodrigues, J. Leit˜ao, and H. Domingos, “Privacypreserving content-based image retrieval in the cloud,” arXiv preprint arXiv:1411.4862, 2014.

3.	A. Rial, M. Deng, T. Bianchi, A. Piva, and B. Preneel, “A provably secure anonymous buyer–seller watermarking protocol,” Information Forensics and Security, IEEE Transactions on, vol. 5, no. 4, pp. 920– 931, 2010.

4.	Carson, C., Thomas, M., Belongie, S.,   Hellerstein, J. M. and Malik, J. 1999. Blobworld: A system for region-based image indexing and retrieval. In Proceedings of the Third International Conference on Visual Information and Information Systems, Springer-Verlag, London, UK. 509-516. 
5.	C. Wang, K. Ren, S. Yu, and K. M. R. Urs, “Achieving usable and privacy-assured similarity search over outsourced cloud data,” in Proc. of INFOCOM. IEEE, 2012, pp. 451–459.

6.	D. Boneh, G. Di Crescenzo, R. Ostrovsky, and G. Persiano, “Public key encryption with keyword search,” in Advances in Cryptology-Eurocrypt. Springer, 2004, pp. 506–522.

7.	S. Anto, S. Chandramathi,” An Expert System based on SVM and Hybrid GA-SA Optimization for Hepatitis Diagnosis,”, International Journal of Computer Engineering In Research Trends, 2(7):437-443, 2015.

8.	F. Long, H. J. Zhang, and D. D. Feng, "Fundamentals of Content-based Image Retrieval," in Multimedia Information Retrieval and Management, D. Feng Eds,Springer, 2003.

9.	Shivangi Jindal, Harkiran Kaur, “Intensification of Resolution in the Realm of
Digital Imaging,” International Journal of Computer Engineering In Research Trends, 3(6):343-346,2016.
10.	J. C. Bezdek, “Pattern Recognition with Fuzzy Objective Function Algorithms”, New York: Plenum Press, 1981. 

11.	Ma, W. and Manjunath, B.S. (1999) NeTra: a toolbox for navigating large image databases. Multimedia Systems, Springer-Verlag, Berlin, Germany. 7(3), 184-198. 

12.	Nbhan D. Salih , David Chek Ling Ngo, “ A novel method for shape representation,”  GVIP 05 Conference, 19-21 December 2005.

13.	Ravichandran K. and Ananthi B., “Color Skin Segmentation Using K-Means Cluster,  ” International Journal of Computational and Applied Mathematics, vol.4, no.2, pp. 153-157 , 2009.

14.	Rui, Y., Huang, T. S. and Mehrotra, S. 1997. Content-based image retrieval with relevance feedback in MARS. In Proceedings of International Conference on Image Processing. 2, 815-818. 

15.	S. Lian, Z. Liu, R. Zhen, and H. Wang, “Commutative watermarking and encryption for media data,” Optical Engineering, vol. 45, no. 8, pp. 080 510–080 510, 2006.

16.	W. Sun, B. Wang, N. Cao, M. Li, W. Lou, Y. T. Hou, and H. Li, “Privacypreserving multi-keyword text search in the cloud supporting similaritybased ranking,” in Proc. of 8th ACM SIGSAC symposium on Information, computer and communications security.
17.	Y. Ren, J. Shen, J. Wang, J. Han, and S. Lee, “Mutual verifiable provable   data auditing in public cloud storage,” Journal of Internet Technology, vol. 16, no. 2, pp. 317–323, 2015.

18.	Z. Fu, K. Ren, J. Shu, X. Sun, and F. Huang, “Enabling personalized search over encrypted outsourced data with efficiency improvement,” IEEE Transactions on Parallel & Distributed Systems, vol. PP, no. Online, pp. 1–1, 2015.
:10.22362/ijcert/2017/v4/i6/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I6003.pdf
Refbacks : Currently There are no refbacks
Enhancement in Crawling and Searching (Using Extended Weighted Page Rank Algorithm based on VOL)
Authors : Ms.Isha Mahajan, Ms. Harjinder Kaur, Dr. Darshan Kumar
Affiliations : Department of Computer Science & Engineering SSIET, Dinanagar - 143531, Distt. Gurdaspur, Punjab (India)
Abstract :

af

As the World Wide Web is becoming gigantic day by day, the number of web pages is increasing into billions around the world. To make searching much easier for users, search engines came into existence. Search engines are used to find specific information on the WWW. Without search engines, it would be almost impossible for us to locate anything on the Web unless or until we know a specific URL address. Every search engine maintains a central repository or databases of HTML documents in indexed form. Whenever a user query comes, searching is performed within that database of indexed web pages. The size of a repository of every search engine cannot keep each page available on the WWW. So it is desired that only the most relevant and important pages be stored in the database to increase the efficiency of search engines. This search engine database is maintained by special software called “Crawler.” A Crawler is a software that traverses the web and downloads web pages. Web Crawlers are also known as “Web Spiders,” “Robots,” “Internet Bots,” “Agents” and automatic Indexers” etc. Broad search engines, as well as many more specialized search tools, rely on web crawlers to acquire large collections of pages for indexing and analysis. Since the Web is a distributed, dynamic and rapidly growing information resource, a crawler cannot download all pages. It is almost impossible for crawlers to crawl the whole web pages from World Wide Web. Crawlers crawl the only fraction of web pages from World Wide Web. So a crawler should observe that the fraction of pages crawled must be most relevant and the most important ones, not just random pages. The crawler is an important module of a search engine. The quality of a crawler directly affects the searching quality of search engines. In our Work, we propose to improve the crawling of a web crawler, to crawl only relevant and important pages from WWW, which will lead to reduced server overheads. With our proposed architecture we will also be optimizing the crawled data by removing least used or never browsed pages. The crawler needs a huge memory space or database for storing page content etc, by not storing irrelevant and unimportant pages and never removing accessed pages, we will be saving a lot of memory space that will eventually speed up the queries to the database. In our approach, we propose to use Extended Weighted page rank based on visits of links algorithm to sort the search results, which will reduce the search space for users, by providing mostly visited pages and most time devoted pages by the user on the top of search results list. Hence reducing search space for the user.
Citation :

af

Isha Mahajan et.al, “Enhancement in Crawling and Searching(Using Extended Weighted Page Rank Algorithm based on VOL)”, International Journal of Computer Engineering In Research Trends, 4(6):pp:202-230,June-2017.
Keywords : Web Crawler, Extended Weighted Page Rank based on Visits of links, Weighted Page Rank, Page Rank, Page Rank based on visit of links, Search Engine, Crawling, bot, Information Retrieval Engine, Page Reading Time, User Attention Time, World Wide Web, Inlinks, Outlines, Web informational retrieval, online search.
References :

af

[1]	Internet World Stats survey  report available at - << http://www.internetworldstats.com/stats.htm >>.
[2]	Pew Research center’s Internet and American Life Project Survey  report available at  - << http://www.pewinternet.org/2012/03/09/main-findings-11/ >>.
[3]	Average Traffic a website receives from a Search Engine is << http://moz.com/community/q/what-is-the-average-percentage-of-traffic-from-search-engines-that-a-website-receives >>
[4]	Size of World Wide Web is available at  << http://www.worldwidewebsize.com/ >>
[5]	Carlos Castillo, Mauricio Marin, Andrea Rodrigue and Ricardo Baeza-Yates, “Scheduling Algorithms for Web Crawling” Proceedings of the Web Media & LA-Web 2004, 0-7695-2237-8 ©2004 IEEE, Pages 10-17.
[6]	S. Lawrence and C. L. Giles. Searching the World Wide Web. Science, 280 (5360) : 98–100, 1998.
[7]	Introduction to Web Crawler is available at - << http://en.wikipedia.org/wiki/Web_crawler >>
[8]	Introduction to Web Crawler is available at - << http://searchsoa.techtarget.com/definition/crawler >>
[9]	Amit Chawla and Rupali Ahuja, “Crawling the Web : Discovery and Maintenance of Large-Scale Web Data”, International Journal of Advances in Engineering Science (IJAES), ISSN: 2231- 0347, Volume-3, Pages 62-66, July 2013.
[10]	Sachin Gupta, Sashi Tarun and Pankaj Sharma, “Controlling access of Bots and Spamming Bots”, International Journal of Computer and Electronics Research (IJCER), ISSN: 2278-5795, vol. 3,issue 2, April 2014.
[11]	Sonal Tuteja, “Enhancement in Weighted PageRank Algorithm Using VOL”, IOSR Journal of Computer Engineering (IOSR-JCE), ISSN: 2278-0661, vol. 2, issue 6, pp. 135-141, Sept-Oct 2013.
[12]	Shweta Agarwal and Bharat Bhushan Agarwal, “An Improvement on Page Ranking Based on Visits of Links”, International Journal of Science and Research (IJSR), ISSN: 2319-7064, vol. 2, issue 6, pp. 265-268, June 2013.
[13]	S. Brin, and Page L., “The Anatomy of a Large Scale Hypertextual Web Search Engine”, Computer Network and ISDN Systems, vol. 30, issue 1-7, pp. 107-117, 1998. 
[14]	Wenpu Xing and Ali Ghorbani, “Weighted PageRank Algorithm”, Proceedings of the Second Annual Conference on Communication Networks and Services Research (CNSR ’04), IEEE, 2004.
[15]	Gyanendra Kumar, Neelam Duahn, and Sharma A. K., “Page Ranking Based on Number of Visits of Web Pages”, International Conference on Computer & Communication Technology (ICCCT)-2011, 978-1-4577-1385-9. 
[16]	Neelam Tyagi and Simple Sharma, “Weighted Page Rank Algorithm Based on Number of Visits of Links of Web Page”, International Journal of Soft Computing and Engineering (IJSCE), ISSN: 2231-2307, vol. 2, issue 3, pp. 441–446, July 2012.
[17]	Animesh Tripathy and Prashanta K Patra, “A Web Mining Architectural Model of Distributed Crawler for Internet Searches Using PageRank Algorithm”, Asia-Pacific Services Computing Conference, 978-0-7695-3473-2/08 © 2008 IEEE, Pages 513-518.
[18]	Lay-Ki Soon, Yee-Ern Ku  and Sang Ho Lee, “Web Crawler with URL Signature – A Performance Study”, 4th Conference on Data Mining and Optimization (DMO) 978-1-4673-2718-3/12 ©2012 IEEE,  Pages 127-130.
[19]	Farha R. Qureshi and Amer Ahmed Khan, “URL Signature with body text normalization in a web crawler”, International Journal of Societal Applications of Computer Science (IJSACS), ISSN 2319 – 8443, vol. 2, issue 3, Pages 309-312, March 2013.
[20]	Saurabh Pakhidde , Jaya Rajurkar and Prashant Dahiwale,  “Content Relevance Prediction Algorithm in Web Crawlers to Enhance Web Search”, International Journal of Advanced Research in Computer Engineering & Technology (IJARCET), ISSN: 2278 – 1323, vol 3, issue 3, March 2014.
[21]	Prashant Dahiwale, Pritam Bhowmik, Tejaswini Bhorkar and Shraddha Shahare, “Rank Crawler : A Web Crawler with Relevance Prediction Mechanism for True Web Analysis”, International Journal of Advance Foundation and Research in Computer (IJAFRC), ISSN: 2348-4853, vol. 1,issue 4, April 2014.
[22]	Information on HTTP_Referer is available at - << http://en.wikipedia.org/wiki/HTTP_referer >>.
[23]	Information on Url Normalization is available at - << http://en.wikipedia.org/wiki/Url_normalization >>.
[24]	Information on MD5 Hashing Algorithm is available at - << http://en.wikipedia.org/wiki/MD5 >>.
[25]	Introduction to WHOIS is available at - << http://en.wikipedia.org/wiki/Whois >>.
[26]	Sachin Gupta and Pallvi Mahajan, “Improvement in Weighted Page Rank based on Visits of Links (VOL) Algorithm”, International Journal of Computer and Communications Engineering Research (IJCCER), ISSN: 2321-4198, Vol. 2, Issue 3, Pages 119-124, May 2014.
[27]	Sachin Gupta and Sashi Tarun, “Extended Architecture of Web Crawler”, International Journal Of Computer & Electronics Research (IJCER), ISSN: 2278-5795, Vol. 3, Issue 3, Pages 147-169, June 2014.
[28]	Isha Mahajan, Harjinder Kaur and Dr. Darshan Kumar, “Extended Weighted Page Rank based on VOL by finding User Activities Time and Page Reading Time”, International Journal of Engineering Works (IJEW), ISSN: 2409-2770, Vol. 7, Issue 2, Pages 41-48, Feb 2017.
[29]	Introduction to Code Minification is available at - << https://developers.google.com/speed/docs/insights/MinifyResources >>.
[30]	Javascript Code Minification Api is available at - << https://javascript-minifier.com/ >>.
[31]	Introduction to Cron Jobs is available at - << https://code.tutsplus.com/tutorials/scheduling-tasks-with-cron-jobs--net-8800 >>.
[32]	Domain age calculating Api is available at - << https://github.com/99webtools/PHP-Domain-Age >>.
[33]	Mubasheera Tazeen, Shasikala.Ch, Dr.S.Prem Kumar,” Ontology Based PMSE with Manifold Preference”, International Journal of Computer Engineering In Research Trends (IJCERT),ISSN:2349-7084,Vol 1,Issue 1,Pages 15-21,July 2014.
[34]	Sachin Desale, Akhtar Rasool, Sushil Andhale, Priti Rane,” Heuristic and Meta-Heuristic Algorithms and Their Relevance to the Real World: A Survey”, International Journal of Computer Engineering In Research Trends (IJCERT),ISSN:2349-7084,Vol  2,Issue  5,Pages 296-304,May  2015.
:10.22362/ijcert/2017/v4/i6/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I6002.pdf
Refbacks : There are currently no refbacks
Survey on Big Data using Apache Hadoop and Spark
Authors : Priya Dahiya , Chaitra.B , Usha Kumari
Affiliations : Information Science Dept. , Acharya Doctor Sarvepalli Radhakrishnan Rd, Bengaluru, Karnataka 560107, India.
Abstract :

af

Big data is growing rapidly regarding volume, variability, and velocity which make it difficult to process, capture and analyze the data. Hadoop uses MapReduce which has two parts Map and Reduce whereas Spark uses Resilient Distributed Datasets (RDD) and Directed Acyclic Graph (DAG) for processing of large datasets. To store data both of them uses Hadoop Distributed File System (HDFS).This paper shows the architecture and working of Hadoop and Spark and brings out the differences between them and the challenges faced by MapReduce during processing of large datasets and how Spark works on Hadoop YARN.
Citation :

af

Priya Dahiya et.al, “Survey on Big Data using Apache Hadoop and Spark”, International Journal of Computer Engineering In Research Trends, 4(6):pp:195-201,June -2017.
Keywords : Big data, Spark, Hadoop, HDFS, MapReduce, YARN
References :

af

1. Varsha B.Bobade, “Survey Paper on Big Data and Hadoop”, International Research Journal of Engineering and Technology (IRJET) , Volume: 03 Issue: 01 | Jan-2016, e-ISSN: 2395-0056  p-ISSN: 2395-0072.

2. S. Justin Samuel, Koundinya RVP, Kotha Sashidhar and C.R. Bharathi,  “A SURVEY ON BIG DATA AND ITS RESEARCH CHALLENGES”, VOL. 10, NO. 8, MAY 2015 ISSN 1819-6608, ARPN Journal of Engineering and Applied Sciences.

3.Ms. Vibhavari Chavan, Prof. Rajesh. N. Pursue “Survey Paper On Big Data”, Vibhavari 
Chavan et al, / (IJCSIT) International Journal of Computer Science and Information Technologies, Vol. 5 (6) , 2014, 7932-7939.

4. Ankush Verma ,Ashik Hussain Mansuri ,Dr. Neelesh Jain “Big Data Management Processing with Hadoop MapReduce and Spark Technology: A Comparison” 2016 Symposium on Colossal Data Analysis and Networking (CDAN) , 978-1- 5090-0669-4/16/$31.00 © 2016 IEEE. 

5. Wei Huang, Lingkui Meng, Dongying Zhang, and Wen Zhang, “In-Memory Parallel Processing of Massive Remotely Sensed Data Using an Apache Spark on Hadoop YARN Model” , IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, VOL. 10, NO. 1, DECEMBER 2016.

6. Katarina Grolinger, Michael Hayes, Wilson A. Higashino, Alexandra L'Heureux1 David S.Allison ,Miriam A.M. Capretz, “Challenges for MapReduce in Big Data ”, 978-1- 4799-5069-0/14 $31.00©2014IEEEDOI10.1109/SERVICES.2014.4.

7. Xiuqin LIN, Peng WANG, Bin WU, “LOG ANALYSIS IN CLOUD COMPUTING ENVIRONMENT WITH HADOOP AND SPARK”, 978-1-4799-0094-7/13/$31.00©2013

8. K..Naga Maha Lakshmi et al., International Journal of Computer Engineering In Research Trends ,Volume 3, Issue 3, March-2016, pp. 134-142.

9. Sunil B. Mane et.al, “Product Rating using Opinion Mining”, International Journal of Computer Engineering In Research Trends, 4(5):161-168 ,May -2017.
:10.22362/ijcert/2017/v4/i6/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I6001.pdf
Refbacks : There are Currently no refbacks

 

DESIGN OF AN UNMANNED HOVERCRAFT
Authors : A.M Anushree Kirthika , Jagan Raj,
Affiliations : Aeronautical Department, Vel Tech Dr. RR& Dr.SR Technical University, Chennai, 600 062 India
Abstract :

af

This paper deals with the design of hovercraft where the hovercraft can travel on land as well as on water which is an unmanned aerial vehicle with a maximum take-off weight are 0.8 kg. The design of this hovercraft which is capable of hovering and forward motion. The hovercraft design criteria involve the stability and power to weight ratio. The air intake in a hovercraft plays a major role in the flow of air into the skirt. This design involves a multi-propeller hovercraft. There are holes designed for optimizing the design. The hover height is 15 cm. An open plenum type of hovercraft with a bag skirt configuration opts. The design of hovercraft is done via CATIA.
Citation :

af

A.M Anushree Kirthika et.al, “DESIGN OF AN UNMANNED HOVERCRAFT”, International Journal of Computer Engineering In Research Trends, 4(5):pp:190-194 ,May -2017.
Keywords : Hovercraft, hover, Open Plenum, Multipropeller hovercraft
References :

af

1)	A.K. Amiruddin, S.M. Sapuan and A.A. Jaafar “Development of a hovercraft prototype with an aluminum hull base”, International Journal of the Physics Sciences vol.6(17), pp.4185-4194, 2 September 2011
2)	Grant Wagner, Michael Butler, Derek Smith, Kyle Palmer, “Design and fabrication of a model hovercraft”, Final Report, Rose – Hulman Institute of Technology, Terre Haute, Indiana, 2 July 2008.
3)	C. Fitzergerald and R. Wilson, “Light Hovercraft Design”, 3rd Hoverclub of America Inc, 1995, 37-38.
4)	Grant Wagner “Universal Hovercraft, The World Leader in Hovercraft
5)	Introduction to RC Modeling -Module 4 Make a Hovercraft
6)	Kofi Anguah, Nick Szapiro “Design and construction of a Passenger Hovercraft”, E90 Final Report, 05/08/2009
7)	S.V. Uma Maheswara Rao, V.S. Surya Prakash (Professor, M.E Student, Department of Marine Engineering, AUCE (A), Visakhapatnam-5300003) Development of An Integrated Air Cushioned Vehicle (Hovercraft), International Journal of Modern Engineering Research (IJMER), 4(5),2014, 21.
8)	Edwin Chan Hanjiang, “Design of a working Model Hovercraft”, University Malaysia Pahang.
9)	S.H. Mohamed Noor, K.Syam, A.A Jaafar, M.F.Mohamad Sharif, IOP Publishing, Proceedings of i-MEC-APCOMS 2015.
:10.22362/ijcert/2017/v4/i5/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I509.pdf
Refbacks : There are no currently ref backs
An Ultra Wideband Bandpass Filter using Stepped Impedance Resonators and DGS Structures
Authors : Intekhab Hussain, M.G.Tiary,
Affiliations : Assistant Professor, AEIE Department, Asansol Engg. College, Asansol, WB, India.
Abstract :

af

In this paper, a compact ultra wideband (UWB) bandpass filter (BPF) with a passband covering 4.73 GHz to 10.43GHz with a bandwidth of 5.7 GHz and a fractional bandwidth of 75.2% is proposed. The filter has three transmission poles in the passband and has a wide stop band. The design and the performance of the proposed UWB BPF are characterized by using full-wave electromagnetic simulator IE3D.
Citation :

af

Intekhab Hussain et.al, “An Ultra Wideband Bandpass Filter using Stepped Impedance Resonators and DGS Structures”, International Journal of Computer Engineering In Research Trends, 4(5):185-189 ,May -2017.
Keywords : Bandpass filter, Stepped Impedance Resonator, Ultra-wideband, Defected Ground Structure.
References :

af

[1]  Federal Communications Commission (FCC), Revision of Part 15 of the Commission’s Rules Regarding Ultra-Wideband Transmission Systems, First Report and Order, FCC 02-48, 2002.
[2]   L.H. Hsieh, K. Chang, “Compact, low insertion-loss sharp-rejection, and wide-band microstrip bandpass filters,” IEEE Trans. Microwave Theory Tech., vol. 51, no. 4, pp. 1241-1246, 2003.
[3] H. Ishida, and K. Araki, “Design and analysis of UWB bandpass filter with ring filter,” IEEE Trans. MTT-S Int. Dig., vol.3, pp.1307-1310, 2004.
[4]  L. Zhu, H. Bu and K. Wu, “Broadband and compact multi-pole microstrip bandpass filters using ground plane aperture technique,” IEEE Trans. Microwave Theory Tech., vol.49, no.1, pp.71-77, Feb. 2002.
[5] L. Zhu, S. Sun and W. Menzel, “Ultra-wideband (UWB) bandpass filters using multiple-mode resonator,” IEEE Microw. Wireless Compon. Lett., vol.15, no.11, pp. 796-798, Nov. 2005.
[6]  P. Cai, Z. Ma, X. Guan, Y. Kobayashi, T. Anada and Gen Hagiwara,“A Novel compact ultra-wideband bandpass filter using a microstrip stepped-impedance four-modes resonator,” 2007 IEEE MTT-S International Microwave Symposium Digest, pp.751-754.
[7] Zhewang Ma, Wenqing He, Chun-Ping Chen, Yoshio Kobayashi, and Tetsuo Anada, “A Novel Compact Ultra-Wideband Bandpass Filter Using Microstrip Stub-Loaded Dual-Mode Resonator oublets,” 978-1-4244-1780-3/08 © 2008 IEEE
[8]  He, Z. N., X. L. Wang, S. H. Han, T. Lin, and Z. Liu, “The synthesis and design for new classic dual-band waveguide band-stop filters," Journal of Electromagnetic Waves and Applications, Vol. 22, No. 1, 119-130, 2008.
[9]  Dai, X.-W., C.-H. Liang, B.Wu, and J.-W. Fan, “Novel dual-band bandpass ¯lter design using microstrip open-loop resonators," Journal of Electromagnetic Waves and Applications, Vol. 22, No. 2/3, 219-225, 2008.
[10] Li, G., B. Wu, X.-W. Dai, and C.-H. Liang, “Design techniques for asymmetric dual-passband filters," Journal of Electromagnetic Waves and Applications, Vol. 22, No. 2/3, 375-383, 2008.
[11] Wang, J. P., B. Z. Wang, Y. X. Wang, and Y. X. Guo, “Dual-band microstrip stepped-impedance bandpass filter with defected ground structure," Journal of Electromagnetic Waves and Applications, Vol. 22, No. 4, 463-470, 2008.
[12] Dai, X.-W., C.-H. Liang, G. Li, and Z.-X. Chen, “Novel dual-mode dual-band bandpass ¯lter using microstrip meander-loop resonators," Journal of Electromagnetic Waves and Applications, Vol. 22, No. 4, 573-580, 2008.
[13] Hsu, C.Y., H.-R. Chuang, and C.-Y. Chen, “Compact microstrip UWB dual-band bandpass with tunable rejection band," Journal of Electromagnetic Waves and Applications, Vol. 23, No. 5/6, 617-626, 2009.
[14] Abu-Hudrouss, A. M. and M. J. Lancaster, “Design of multiple-band microwave filters using cascaded ¯lter elements," Journal of Electromagnetic Waves and Applications, Vol. 23, No. 10, 2109-2118, 2009.
[15] Weng, R. M. and P. Y. Hsiao, “Double-layered quad-band bandpass filter for multi-band wireless systems," Journal of Electromagnetic Waves and Applications, Vol. 23, No. 3, 2153-2161, No. 16, 2009.
[16] Alkanhal, M. A. S., “Dual-band bandpass filters using inverted stepped-impedance resonators," Journal of Electromagnetic Waves and Applications, Vol. 23, No. 8/9, 1211-1220, 2009.
[17] Progress In Electromagnetics Research, PIER 102, 2010 123 Myyake, H., S. Kitazawa, T. Ishizaki, T. Yamada, and Y. Nagatomi, “A miniaturized monolithic dual band filter using ceramic lamination technique for dual mode portable telephones," IEEE-MTT-S International Microw. Symp. Dig, Vol. 2, 789-792, 1997.
[18] Tsai, L. C. and C. W. Huse, “Dual-band bandpass filters using equal length coupled-serial-shunted lines and Z-transform techniques," IEEE Trans. on Microwave Theory and Tech., Vol. 52, No. 4, 1111-1117, Apr. 2004.
[19] Chen, C. Y. and C. Y. Hsu, “A simple and e®ective method for microstrip dual band design," IEEE Microw. Wireless Compon. Lett., Vol. 16, No. 3, 246-258, May 2006.
[20] Garca-Lamperez, A. and M. Salazar-Palma, “Dual band filter with split-ring resonators," IEEE MTT-S International Microw. Symp. Dig., 519-522, 2006.
[21] Quendo, C., E. Rius, and C. Person, “An original topology of dual-band filter with transmission zeros," IEEE-MTT-S International Microw. Symp. Dig., Vol. 2, 1093-1096, 2003.
[22] Tsai, C. M., H. M. Lee, and C. C. Tsai, “Planar filter design with fully controllable second passband," IEEE Trans. on Microwave Theory and Tech., Vol. 53, No. 11, 3429-3439, Nov. 2005.
[23] Chin, K. S., J. H. Yeh, and S. H. Chao, “Compact dual-Band bandstop filters using stepped-impedance resonators," IEEE Microw. Wireless Compon. Lett., Vol. 17, No. 12, 849-851, Dec. 2007.
[24] Kuo, J. T. and H. S. Cheng, “Design of quasi-elliptic function filters with a dual-passband response," IEEE Microw. Wireless Compon. Lett., Vol. 14, No. 10, 472-475, Oct. 2004.
[25] Kuo, J. T., T. H. Yeh, and C. C. Yeh, “Design of microstrip bandpass filters with a dual-passband responds," IEEE Trans. on Microwave Theory and Tech., Vol. 53, No. 4, 1331-1337, Apr. 2005.
[26] Sun, S. and L. Zhu, “Compact dualband microstrip bandpass filter without external feed," IEEE Microw. Wireless Compon. Lett., Vol. 15, No. 10, 644-646, Oct. 2005.
[27] Zhang, Y. P. and M. Sun, “Dual-band microstrip passband filter using stepped-impedance resonators with new coupling scheme,"IEEE Trans. on Microwave Theory and Tech., Vol. 54, No. 10, 3779-3785, Oct. 2006.
[28] Weng, M. H., H. W. Wu, and Y. K. Su, “Compact and low loss dual-band bandpass filter using pseudo-interdigital stepped lazquez-Ahumada et al. impedance resonators for WLANs," IEEE Microw. Wireless Compon. Lett., Vol. 17, No. 3, 187-189, Mar. 2007.
[29] Velazquez-Ahumada, M. C., J. Martel, F. Medina, and F. Mesa, “Design of a dual band-pass filter using modified folded stepped-impedance resonators," IEEE-MTT-S International Microw. Symp. Dig., 857-860, 2009.
[30] Hong, J.-S. and W. Tang, “Dual-band filter based on non-degenerate dual-mode slow-wave open-loop resonators," IEEE-MTT-S International Microw. Symp. Dig., 861-864, 2009.
:10.22362/ijcert/2017/v4/i5/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I508.pdf
Refbacks : There are currently no refbacks
Survey on current Digital forensic practices
Authors : Divith Devaiah M.M , Prakash B Metre ,
Affiliations : Acharya Doctor Sarvepalli Radhakrishnan Rd, Bengaluru, Karnataka 560107,
Abstract :

af

Cyber-crimes are taking over the world like a breeze. For every crimes committed around the globe, one or the other form of computer or any electronic device is used. So every crime can be linked as cyber-crime. To investigate these crimes, a cost friendly and easily available forensic device is required, which helps in collecting, analyzing and preserving data from which results can be extracted. This paper illuminates all the practices that are currently in place and also clarifies the effects of vulnerabilities.
Citation :

af

Divith Devaiah M.M et.al, “Survey on current Digital forensic practices”, International Journal of Computer Engineering In Research Trends, 4(5):180-184 ,May -2017
Keywords : : Cyber Crimes, Cyber Criminal, Forensic, Forensic tools, Vulnerability, Criminology, agile tool.
References :

af

1.	Malek Harbawi and Asaf Varol, “The Role of Digital Forensics in Combating Cybercrimes”.
2.	M. Al Fahdi, N.L. Clarke and S.M. Furnell, “Challenges to Digital Forensics: A survey of researchers & practitioners attitudes and opinions.
3.	B.Skaggs, B. Blackburn, G. Manes, S. Shenoi, “Network Vulnerability Analysis”.
4.	Prashant S. Shinde and Prof. Shrikant B. Ardhapurkar, “Cyber Security Analysis using Vulnerability Assessment and penetration Testing”.
5.	Abirami Sivaprasad and Smita Jangale, “A Complete study on Tools and Techniques for digital Forensic Analysis”.
6.	Andrw Jones and Stilianos Vidalis and Nasser Abouzakhar, “Information Security and digital forensics in the world of cyber physical systems”.
7.	Arun V. Sathanur and David J. Haglin, “A novel centrality Measure for network-wide cyber vulnerability assessment”.
8.	Arni Ariani, John Lewis and Pradeep K. Ray, “The vulnerability assessment for Emergency response Plans”.
9.	C.Balan, Dija S, Divya S, VIdyadharan, “The need to adopt agile methodology in the development of cyber forensic tools”.
10.	S.Al Sharif, F.Iqbal,T.Baker and A. Marrington, “Magec:An image searching tool for detecting forged images in forensic investigation”.
11.	Noble Kumari and A.K Mohapatra, “An insight into digital forensics branches and tools”.
12.	Simson L Garfinkel and Nicole Beebe, Lishu liu, “Detecting Threatening insiders with lightweight media forensics”.
:10.22362/ijcert/2017/v4/i5/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I507.pdf
Refbacks : There are currently no refbacks
Malware as a Component in Cybercrime: A Survey
Authors : Rodney Anthony Raj, Chayapathi A R ,
Affiliations : Information science and engineering, Acharya institute of technolgy, Doctor Sarvepalli Radhakrishnan Rd, Bengaluru, Karnataka 560107, India.
Abstract :

af

In today’s world we face lot of trouble by cybercrimes where every individual by some mean is a victim towards cybercrime knowingly or unknowingly. One of the main components in the cybercrime is malware and it really comes handy to wage an attack. This paper is a survey on what kind of malwares are used and how effectively they use malware to exploit the world through cybercrime.
Citation :

af

Rodney Anthony Raj et.al, “Malware as a component in cybercrime: A survey”, International Journal of Computer Engineering In Research Trends, 4(5):176-179 ,May -2017.
Keywords : Malware, Ransomware, Virus, Cybercrime, Rootkits, Attacker, and Hacker
References :

af

1.	2016: Current State of Cybercrime, RSA whitepaper.

2.	Basic survey on Malware Analysis, Tools, and Techniques. Dolly Uppall, Vishaka Mehra, and Vinod Verma.

3.	A survey of cybercrime. Zhicheng Yang.

4.	Detecting and Classifying Morphed Malwares: A Survey, Sanjam Singla.

5.	Evolution, Detection and Analysis of Malware for Smart Devices Guillermo Suarez-Tangil, Juan E. Tapiador, Pedro Peris-Lopez, and Arturo Ribagorda.

6.	A Survey on Techniques in Detection and Analyzing Malware Executables, Kirti Mathur.

7.	Malware Analysis and Classification: A Survey Ekta Gandotra, Divya Bansal, Sanjeev Sofat.

8.	Malware and cyber crime. House of Commons, Science and Technology Committee.

9.	Malware and Malware Detection Techniques: A Survey. Jyoti Landage.

10.	A Survey on Malware Attacks on Smartphones Kireet, Dr.Meda, and Sreenivasa Rao

11.	https://www.theguardian.com/technology/2016/oct/22/cyber-attack-hackers-weaponised-everyday-devices-with-malware-to-mount-assault

12.	https://securelist.com/analysis/quarterly-malware-reports/75640/it-threat-evolution-in-q2-2016-statistics/

13.	https://www.av-test.org/en/statistics/malware/

14.	https://blog.barkly.com/cyber-security-statistics-2017.

:10.22362/ijcert/2017/v4/i5/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I506.pdf
Refbacks : there are currently no refbacks
Secret Data Transmission Using Combination of Cryptography &Steganography
Authors : Ajin P Thomas, Sruthi P.S, Jerry Rachel Jacob, Vandana V Nair , Reeba R
Affiliations : Sreebuddha College Of Engineering, Alappuzha , India
Abstract :

af

Secure communication is when two entities are communicating and do not want a third party to listen in. For that, they need to communicate in a way not susceptible to eavesdropping or interception. Two varieties of security mechanism, cryptography and steganography are being applied. At the preceding stage, encryption is being provided to secret plain text using Vernam cipher (One-Time Pad) transposition technique. At the later stage, it transforms ciphertext into bytes and divides each byte into pairs of bits and assigns the decimal values to each pair, which is known as a master variable. Master variable value range will vary between 0 to 3. Depending upon the master patchy value, add that cipher text in the career image at Least Significant Bit (LSB) 6 th and 7 th bit location or 7 th and 8 th bit location or 7 th and 6 th or 8 th and 7 th bit location. Vernam cipher show good performance metrics regarding less CPU running time, fIle size same after Encryption and strong avalanche effect compare with all transposition cipher. After completion of embedding and sending the stego image to the receiver side, retrieving process of the cipher text from the said locations will be done. Moreover, then decryption process to get the secret plain text back will be performed using the Vernam cipher transposition algorithms.
Citation :

af

Ajin P Thomas et.al, “Secret Data Transmission Using Combination of Cryptography &Steganography”, International Journal of Computer Engineering In Research Trends, 4(5):171-175 ,May -2017.
Keywords : Cryptography &Steganography
References :

af

[I] R. J. Anderson and F. A.P. Petitcolas, "On The Limits of Steganography", IEEE Journal of selected Areas in communication, 16(4), pp. 474-481,Special Issue on Copyright & Privacy protection. ISSN 0733-8716, May 1998.
 [2] M. A. B. Younes and A. Jantan, "A New Steganography Approach for Image Encryption Exchange by using the LSB insertion", IJCSNS International Journal of Computer Science & Network Security, Vol 8, No 6 , pp. 247-254, June 2008.
 [3] G. Swain and S .. K .. Lenka, "Steganography-Using a Double Substitution Cipher", International Journal of Wireless Communications and Networking, Volume 2, Number I, pp.35-39. ISSN: 0975-7163, June 2010. 
[4] G. Swain and S. K. Lenka, " A Technique for Secure Communication using Message Dependent Steganography",Special issue of IJCCT, Vol. 2,No. 12,2010.
 [5] G. Swain and S. K. Lenka, "Steganography using the Twelve Square Substitution Cipher and Index Variable" ,IEEE transactions on Image Processing, pp. 84-88, 2011.
 [6] A. Nag, J. P. Singh, S. Khan and S. Ghosh," A Weighted Location Based LSB Image Steganography Technique", Springer ACC 2011, Part II, CCIS 191, pp. 620-627, 20 II.
 [7] C. Maiti, D. Baksi, I. Zamider, P. Gorai and D. R. Kisku," Data Hiding in Images Using Some Efficient Steganography Techniques",Springer SIP 2011, CCIS 260, pp. 195-203, 20 II. 
[8] B. Li,.,et al. "A survey on image steganography and steganalysis", Journal of Information Hiding and Multimedia Signal Processing, Vol. 2, No. 2, pp. 142172, 2011. 
[9]G. Swain and S . .K .. Lenka, "A Dynamic Approach to Image Steganography Using the Three Least Significant Bits and Extended Hill Cipher" Advanced Materials Research, voI.403-408, pp.842-849,2012. 
[10] S. Padmapriya, S. Saravanapriya and D. Jayachitra," Performance Analysis of Various Encryption Algorithms for Data Communication", International Journal of Computer 
:10.22362/ijcert/2017/v4/i5/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I505.pdf
Refbacks : There are Currently No refback
Survey on Mining Partially Ordered Sequential Rules
Authors : Mr. Sandipkumar Sagare, Prof. Suresh Shirgave,
Affiliations : M.E.C.S.E Student, C.S.E Department, D.K.T.E. Society’s Textile and Engineering Institute,Ichalkaranji, 416115
Abstract :

af

Nowadays in various applications such as stock market analysis, e-commerce sequential rule mining is used to extract important data. It majorly includes identification of common multiple sequential rules from given sequence database. One of the general forms of sequential rule mining is Partially Ordered Sequential rules in which listed items in left and right side of rule does not need to be ordered. These partially ordered sequential rules are identified using RuleGrowth Algorithm, TRuleGrowth Algorithm. These algorithms identify partially ordered sequential rules for more generalized decision making. In this paper we are focusing on such algorithms.
Citation :

af

Sandipkumar Sagare et.al, “Survey on Mining Partially Ordered Sequential Rules”, International Journal of Computer Engineering In Research Trends, 4(5):169-170 ,May -2017.
Keywords : Sequential rules, sequential patterns, temporal patterns, pattern mining, sequence, data mining.
References :

af

1. J. Pei, J. Han, B. Mortazavi-Asl, H. Pinto, Q.
Chen, U. Dayal, and M. Hsu, ―Mining sequential
patterns by pattern-growth: The pre-fixspan
approach,‖ IEEE Trans. Knowl. Data Eng., vol. 16,
no. 10, pp. 1–17, Oct. 2004.
2. R. Agrawal and R. Srikant, ―Mining sequential
patterns,‖ in Proc. 11th Int. Conf. Data Eng., 1995,
pp. 3–14.
3. J. Pei, J. Han, B. Mortazavi-Asl, H. Pinto, Q.
Chen, U. Dayal, and M. Hsu, ―Mining sequential
patterns by pattern-growth: The pre-fixspan
approach,‖ IEEE Trans. Knowl. Data Eng., vol. 16,
no. 10, pp. 1–17, Oct. 2004.
4. M. J. Zaki, ―SPADE: An efficient algorithm for
mining frequent sequences,‖ Mach. Learning, vol. 42,
no. 1–2, pp. 31–60, 2001.pp. 1–17, Oct. 2004.
5. D. Lo, S.-.C. Khoo, and L. Wong, ―Non-redundant
sequential rules—Theory and algorithm,‖ Inf. Syst.,
vol. 34, no. 4/ 5, pp. 438–453, 2009.
6. Y. Zhao, H. Zhang, L. Cao, C. Zhang, and H.
Bohlscheid, ―Mining both positive and negative
impact-oriented sequential rules from transactional
data,‖ in Proc. 13th Pacific-Asia Conf.
:10.22362/ijcert/2017/v4/i5/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I504.pdf
Refbacks : Currently there are no ref backs
Product Rating using Opinion Mining
Authors : Sunil B. Mane, Kruti Assar, Priyanka Sawant and Monika Shinde
Affiliations : Assistant Professor, Department of Computer Engineering and Information Technology, College of Engineering Pune Pune - 411005, Maharashtra, India.
Abstract :

af

Amazon.com is one of the largest electronic commerce website in the world which allows users to purchase different products and submit reviews on each one of them. The reviews allow the first-time buyers to understand the quality of the products and decide whether to make a purchase or not. The reviews result in unstructured big data which can be analyzed and used for recommendation of a product on the website. However, it is possible that some customers write fake reviews to promote or defame a particular brand. So it is important to detect and remove the fake reviews for providing the correct rating to the product. Also, it is necessary to create a fast and efficient system for analyzing big data. The present systems used for big data analysis are quite slow. So here, we use the Apache Spark framework for increasing the speed of processing the Amazon reviews. This paper provides a new implementation for analyzing Amazon reviews which involve detection of fake reviews, processing the genuine reviews using Apache Spark and finally rating the products.
Citation :

af

Sunil B. Mane et.al, “Product Rating using Opinion Mining”, International Journal of Computer Engineering In Research Trends, 4(5):161-168 ,May -2017.
Keywords : Opinion Mining, Apache Spark, Product Rating, Fake Review Detection, Natural Language Processing, Sentiment Analysis.
References :

af

[1] N. Nodarakis, S. Sioutas, A. Tsakalidis, and G. Tzimas. Large-Scale Sentiment Analysis On Twitter with Spark. Mar 15, 2016.
[2] Enock Kanyesigye , Sumitra Menerea," Sentiment Analysis Of Reviews Using Hadoop". 2016.
[3] J. McAuley, R. Pandey, J. Leskovec Knowledge Discovery and Data Mining, 2015.
[4] J. McAuley, C. Targett, J. Shi, A. van den Hengel SIGIR, 2015
[5] Eman M.G. Younis, Faculty of Computer and Information Minia University, Egypt, "Sentiment Analysis and Text Mining for Social Media Microblogs using Open Source Tools: An Empirical Study".February 2015
[6] Poobana S, Sashi Rekha k, "Opinion Mining From Text Reviews Using Machine Learning Algorithm ".3, March 2015
[7] Mrs. Uma Gurav, Prof. Dr. Nandini sidnal, "Opinion mining for reputation evaluation on unstructured Big Data " . 4, April 2015
[8] Spark. The apache software foundation: Spark homepage. http://spark.apache.org/, 2015. [Online; accessed 27-December-2015]
[9] Sunil B. Mane, Y. Sawant, S. Kazi, and V. ShindeReal.Time Sentiment Analysis of Twitter Data Using Hadoop,College of Engineering, Pune. 2014
[10] Anju Gahlawat. Big Data Analysis using R and Hadoop. September 2014
[11] Pravesh Kumar Singh, Mohd Shahid Husain, "METHODOLOGICALSTUDY OFOPINION MINING AND SENTIMENT ANALYSIS TECHNIQUES".  February 2014
[12] Kalyankumar B Waddar, K Srinivasa, "OPINION MINING IN PRODUCT REVIEW SYSTEM USING BIG DATA TECHNOLOGY HADOOP".Jul 5,2014
[13] Julia Kreutzer And Neele Witte, Opinion Mining Using SentiWordNet, Semantic Analysis, Uppsala University. 2013/14
[14] Arjun Mukherjee, Vivek Venkataraman, Bing Liu, Natalie Glance, "Fake Review Detection: Classification and Analysis of Real and Pseudo Reviews" .2013
[15] Nitin Jindal and Bing.Opinion Spam and Analysis.Department of Computer Science, University of Illinois at Chicago.Feb 12, 2008
[16] Bo Pang, Lillian Lee, “Opinion Mining and Sentiment Analysis” . 2008
[17] Bing Liu, Minquing hu, “Mining and summarizing Customer Reviews”. 2004
[18] K. Waddar and K. Srinivasa. OPINION MINING IN PRODUCT REVIEW SYSTEM USING BIG DATA TECHNOLOGY HADOOP
[19] B. Pang, L. Lee, and S. Vaithyanathan. Sentiment classification using machine learning techniques.
[20] Maria Soledad Elli, Yi-Fan Wang, Amazon Reviews, business analytics with sentiment analysis

:10.22362/ijcert/2017/v4/i5/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I503.pdf
Refbacks : There are no refback
A Relative Study on the Segmentation Techniques of Image Processing
Authors : Venkata Srinivasu Veesam, Bandaru Satish Babu,
Affiliations : Assistant Professor, R.V.R & JC College of Engineering. Andhra Pradesh, India.
Abstract :

af

Citation :

af

Venkata Srinivasu Veesam et.al, “A Relative Study on the Segmentation Techniques of Image Processing”, International Journal of Computer Engineering In Research Trends, 4(5):155-160,May -2017.
Keywords : Image Segmentation, Thresholding, Feature-based clustering, Region based segmentation, Model-based Segmentation, Graph-based Segmentation.
References :

af

[1] Waseem Khan, ”Image Segmentation Techniques: A Survey,” Journal of Image and Graphics, Vol. 1, No. 4, December 2013, available at, http://www.joig.org/uploadfile/2013/1226/20131226051740869.pdf  
[2] Sujata Saini and Komal Arora, ” A Study Analysis on the Different Image Segmentation Techniques,” International Journal of Information & Computation Technology. ISSN 0974-2239 Volume 4, pp. 1445-1452, 2014, available at, http://www.ripublication.com/irph/ijict_spl/ijictv4n14spl_13.pdf
[3] Rajeshwar Dass, Priyanka, and Swapna Devi,” Image Segmentation Techniques,” EJECT Vol. 3, Issue 1, ISSN: 2230-7109 (Online) |  ISSN: 2230-9543 (Print), Jan-March 2012.
[4] Rafael C. Gonzalez and Richard E. Woods, “Digital Image Processing,” 2nd ed., Beijing: Publishing House of Electronics Industry, 2007, 
[5] H. G. Kagami and Z. Beige, “Region-Based Detection versus Edge Detection,” IEEE Transactions on Intelligent information hiding and multimedia signal processing, pp. 1217-1221, 2009.
[6] K. K. Singh and A. Singh, “A Study of Image Segmentation Algorithms for Different Types of Images,” International Journal of Computer Science Issues, Vol. 7, Issue 5, 2010.
[7] Hassan Grema Kagami and Zou Beijing, “Region-Based Segmentation versus Edge Detection,” Intelligent Information Hiding and Multimedia Signal Processing, 2009. IIH-MSP '09. Fifth International Conference, pp. 1217 – 1221, DOI: 10.1109/IIH-MSP.2009.13, 2009.
[8] Nikita Sharma, Mahendra Mishra and Manish Shrivastava, “ Colour Image Segmentation Techniques and Issues: An Approach,” International, W. X. Kang, Q. Q. Yang, R. R. Liang, “The Comparative Research on Image Segmentation Algorithms,” IEEE Conference on ETCS, pp. 703-707, 2009.
[9] Muthukrishnan and Radha, “Edge Detection Techniques For Image Segmentation”, International Journal of Computer Science & Information Technology (IJCSIT), Vol 3, No 6, Dec 2011, available at  http://airccse.org/journal/jcsit/1211csit20.pdf
[10]http://homepages.inf.ed.ac.uk/rbf/CVonline/LOCAL_COPIES/MORSE/threshold.pdf
[11]http://www.ancient-asia-journal.com/articles/10.5334/aa.06113/
[12] Salem Saleh Al-Amri, N.V. Kalyankar and Khamitkar, ” Image Segmentation by Using Threshold Techniques,” Journal Of Computing, Volume 2, Issue 5, ISSN 2151-9617, May 2010, available at https://arxiv.org/ftp/arxiv/papers/1005/1005.4020.pdf 
[13] Santanu Bhowmik and Viki Datta,” A Survey on Clustering Based Image Segmentation,” International Journal of Advanced Research in Computer Engineering & Technology, Volume 1, ISSN: 2278 – 1323, Issue 5, July 2012, available at, http://ijarcet.org/wp-content/uploads/IJARCET-VOL-1-ISSUE-5-280-284.pdf
[14]Sriparna Saha and Sanghamitra Bandyopadhyay”, A new symmetry-based multiobjective clustering technique for the automatic evolution of clusters,” Journal Pattern Recognition, Volume 43, Issue 3, pp 738-751, March 2010.
[15] Lehmann,”Turbo segmentation of textured images,” on Pattern Analysis and Machine Intelligence, Vol: 33, pp: 16 – 29, 2011.
[16] J. Luo, R. T. Cray and Lee, “Incorporation of derivative priors in adaptive Bayesian color image segmentation’’, Proc. ICIP’97, Vol. 3, pp. 58-61, Oct 26-29, 1997.
[17] J. Gao and J. Zhang M. G. Fleming, ”A Novel Multiresolution Color Image Segmentation Technique and its application to Dermatoscopic Image Segmentation,” Image Processing, vol.3, pp.408-411, 2000.  
[18] Tamas Sziranyi, Josiane Zerubia, Laszlo Czuni, David Goldreich and Zoltan Kato, “Image Segmentation Using Markov Random Field Model in Fully Parallel Cellular Network Architectures”, Real-Time Imaging 6, DOI:10.1006/rtim.1998.0159, pp. 195-211 (2000), available at, https://www.inf.u-szeged.hu/~kato/papers/rti2000.pdf
[19] Pedro F. Felzenszwalb and Daniel P. Huttenlocher, “Efficient Graph-Based Image Segmentation,” International Journal of Computer Vision 59(2), pp. 167–181, 2004.
:10.22362/ijcert/2017/v4/i5/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I502.pdf
Refbacks : There are currently no refbacks
ACCELEROMETER–BASED HUMAN FALL DETECTION AND RESPONSE USING SMARTPHONES
Authors : Monisha Mohan, Arun P.S ,
Affiliations : Computer Science and Engineering, Sree Buddha College of Engineering, Pattoor P.O., Alappuzha Dist., Kerala, Pin code:690529, India,
Abstract :

af

Unobserved human falls can be dangerous and can badly affect health. Falls can cause loss of independence and fear among the older people. In most fall events external support is essential to avoid major consequences. Thus, the ability to automatically detect these fall events could help minimising the response time and therefore prevents the victim from having serious injuries. This paper presents a smartphone based fall detection and response sending application which is based on the built-in accelerometer sensor and GPS module in the smartphones. The data from the accelerometer is continuously screened when the phone is in the user’s belt or pocket. When a fall event is detected, the user’s location is tracked and SMS and email notifications are sent to a set of contacts.
Citation :

af

Monisha Mohan et.al, “Accelerometer–Based Human Fall Detection And Response Using Smartphones”, International Journal of Computer Engineering In Research Trends, 4(5):150-154, May -2017.
Keywords : Fall Detection, Smartphone, ADL, Accelerometer Sensor.
References :

af

[1] WHO, “Who global report on falls prevention in older age,” tech. rep., 2007.

[2] R. JM, B. DW, and L. LL, “Preventable medical injuries in older patients,” Archives of                                     Internal Medicine, vol. 160, no. 18, pp. 2717–2728, 2000.

[3] T. Masud and R. O. Morris, “Epidemiology of falls,” Age and Ageing, vol. 30, no. suppl 4, pp. 3–7, 2001.

[4] Friedman, S.M., Munoz, B., West, S.K., BandeenRoche, K. and Fried, L.P., 1997, September. Falls and fear of falling: Which comes first?. In JOURNAL OF THE AMERICAN GERIATRICS SOCIETY (Vol. 45, No. 9, pp. P186-P186). 351 WEST CAMDEN ST, BALTIMORE, MD 21201-2436: WILLIAMS & WILKINS.

[5] Brownsell, S. and Hawley, M.S., 2004. Automatic fall detectors and the fear of falling. Journal of telemedicine and telecare, 10(5), pp.262-266.

[6] Rubenstein, L.Z. and Josephson, K.R., 2002. The epidemiology of falls and syncope. Clinics in geriatric medicine, 18(2), pp.141-158.

[7] Tinetti, M.E., Liu, W.L. and Claus, E.B., 1993. Predictors and prognosis of inability to get up after falls among elderly persons. Jama, 269(1), pp.65-70.

[8] Fu Z, Delbruck T, Lichtsteiner P, Culurciello E: An address-event fall detector for assisted living applications. IEEE Trans Biomed Circuits Syst 2008, 2:88–96.

[9] Zhang C, Tian Y, Capezuti E: Privacy preserving automatic fall detection for elderly using RGBD cameras. In Proceedings of the 13th International Conference on Computers Helping People with Special Needs. Edited by Miesenberger K, Karshmer A, Penaz P, Zagler W. Linz: Springer-Verlag Berlin;2012:625–633. doi:10.1109/ICSSE.2010.5551751.http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=5551751&url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D5551751.

[10] Bourke A, O’Brien J, Lyons G: Evaluation of a threshold-based triaxial accelerometer fall detection algorithm. Gait Posture 2007, 26:194–199.

[11] Li Q, Stankovic JA, Hanson M, Barth A, Lach J: Accurate, fast fall detection using gyroscopes and accelerometer derived posture information. In Proceedings of the 6th International Workshop on Wearable and Implantable Body Sensor Networks. Edited by Lo B, Mitcheson P. Berkeley; 2009:138–143. doi:10.1109/BSN.2009.46.

[12] Shan S, Yuan T: A wearable pre-impact fall detector using feature selection and support vector machine. In Proceedings of the IEEE 10th International Conference on Signal Processing. Beijing: Institute of Electrical and Electronics Engineers; 2010:1686–1689. doi:10.1109/ICOSP.2010.5656840. 

[13] Lee RYW, Carlisle AJ: Detection of falls using accelerometers and mobile phone technology. Age Ageing 2011, 0:1–7.
:10.22362/ijcert/2017/v4/i5/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I501.pdf
Refbacks : There are currently no refbacks

 

Performance Analysis of Existing Beam forming Methods for Various Antenna Elements and Interference Sources
Authors : Yashoda B.S , Dr. K.R. Nataraj,
Affiliations : Ph.D. Research Scholar, Jain University, Bangalore, India.
Abstract :

af

Antenna Arrays make use of techniques like Maximal Ratio Combining or Diversity is combining to achieve high Signal to Noise Ratio (SNR). The two kinds of the major algorithms used are Direction of Arrival (DOA) and Beam forming. This paper studies and performs the performance analysis of existing beam forming algorithms, namely Least Mean Square (LMS), Recursive Least Mean Square (RLS), Griffiths and Variable Step Size Griffiths (VSSG). The algorithms are simulated for various cases Low RF Sources and Single Interference, Large RF Source and Single Interference, Low RF Sources and Multiple Interference angles and finally in the case of Large RF sources and multiple interference angles.
Citation :

af

Yashoda B.S et.al, “Performance Analysis of Existing Beam forming Methods for Various Antenna Elements and Interference Sources”, International Journal Of Computer Engineering In Research Trends, 4(4):142-149, April-2017.
Keywords : DOA, SNR, LMS, RLS
References :

af

[1]” Robust adaptive beamforming based on the Kalman filter”, A. El-Keyi ;  T. Kirubarajan ; A.B. Gershman,  IEEE Transactions on Signal Processing ( Volume: 53, Issue: 8, Aug. 2005.
[2] “Different adaptive beamforming algorithms for performance investigation of smart antenna system”, Ashraf A. M. Khalaf ;  Abdel-Rahman B. M. El-Daly ;  Hesham F. A. Hamed, Software, Telecommunications and Computer Networks (SoftCOM), 2016 24th International Conference .
[3] Comparative analysis of adaptive beamforming algorithm LMS, SMI and RLS for ULA smart antenna”, Dhaval N. Patel ;  B. J. Makwana ;  P. B. Parmar,  Communication and Signal Processing (ICCSP), 2016 International Conference on
[4] Griffiths L.J.: A simple adaptive algorithm for real time processing of in antenna arrays. Proc. IEEE 57, 1696–1704. 
[5] S. V. Narasimhan, S. Veena, H. Lokesha Variable step-size Griffiths’ algorithm for improved performance of feedforward/feedback active noise control, Signal, Image and Video Processing, 2010, Volume 4, Number 3, Page 309.
 [6] Kim, I.-S., Na, H.-S., Kim, K.-J., Park, Y.: Constraint filtered-X and filtered-U LMS algorithms for the active control of noise in ducts. J. Acoust. Soc. Am. 95(6) (1994)
[7]Kuo S.M., Morgan D.R.: Active noise control systems, algorithms and dsp implementations. Wiley, New York (1996)Google Scholar
[8] Kuo, S.M., Vijayan, D.: A secondary path modeling technique for active noise control. IEEE Trans. Speech Audio 5(4) (1997).
[9]Kwong R.H., Johnston E.W.: A variable step-size LMS algorithm. IEEE Trans. Signal Process. 40(7), 1633–1642 (1992).
:10.22362/ijcert/2017/v4/i4/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I404.pdf
Refbacks : There are currently no refbacks
Dynamic and Public Auditing with Fair Arbitration for Cloud Data
Authors : SAJJA SUNEEL, MANDAVILLI KAVYA ,
Affiliations : Asst.Professor, KG Reddy Engineering College, Hyderabad, Telangana
Abstract :

af

Storage outsourcing turned into a rising trend with the advent of the cloud computing, advancing the secure remote data auditing to be the future research area. Other than this research considers the problem of data dynamics support, public verifiability and dispute arbitration simultaneously. The data dynamics problem in auditing is solved by presenting an index switcher to preserve a mapping between block indices and tag indices and eradicate the passive outcome of block indices in the tag computation without incurring much overhead. We provide fairness guarantee and dispute arbitration in our scheme, which ensures that both the data owner and the cloud cannot misbehave in the auditing process or else it is easy for a third-party arbitrator to find out the cheating party. The framework is reaching out by executing the data dynamically and reasonable discretion on gatherings in the future.
Citation :

af

Sajja Suneel et.al, “Dynamic and Public Auditing with Fair Arbitration for Cloud Data”, International Journal Of Computer Engineering In Research Trends, 4(4):136-141, April-2017.
Keywords : Third Party Auditor (TPA), CSP, Proof Of Retrievability (POR).
References :

af

1. Y. Deswarte, J. J. Quisquater, and A. Saïdane, “Remote integrity checking,” In Integrity and internal control in information systems VI, Springer US, 1-11 (2004).
2. D. L. Gazzoni Filho, and P. S. L. M. Barreto, “Demonstrating data possession and uncheatable data transfer,” IACR Cryptology ePrint Archive 2006, 150 (2006).
3. A. Juels, and B. S. Kaliski Jr, “PORs: Proofs of retrievability for large files,” In Proceedings of the 14th ACM conference on Computer and communications security, Acm, 584-597 (2007).
4. G. Ateniese, R. Burns, R. Curtmola, J. Herring, L. Kissner, Z. Peterson, and D. Song, “Provable data possession at untrusted stores,” In Proceedings of the 14th ACM conference on Computer and communications security, Acm, 598-609 (2007).
5. H. Shacham, and B. Waters, “Compact proofs of retrievability,” In International Conference on the Theory and Application of Cryptology and Information Security, Springer Berlin Heidelberg, 90-107 (2008).
6. Q. Wang, C. Wang, J. Li, K. Ren, and W. Lou, “Enabling public verifiability and data dynamics for storage security in cloud computing,” In European symposium on research in computer security, Springer Berlin Heidelberg, 355-370 (2009).
7. M. A. Shah, R. Swaminathan, and M. Baker, “Privacy-Preserving Audit and Extraction of Digital Contents,” IACR Cryptology EPrint Archive 186 (2008).
8. C. Wang, K. Ren, W. Lou, and J. Li, “Toward publicly auditable secure cloud data storage services,” IEEE network 24, (2010).
9. C. C.  Erway, A. Küpçü, C. Papamanthou, and R. Tamassia, “Dynamic provable data possession,” ACM Transactions on Information and System Security (TISSEC) 17, (2015).
10. Y. Zhu, H. Wang, Z. Hu, G. J. Ahn, H. Hu, and S. S. Yau, “Dynamic audit services for integrity verification of outsourced storages in clouds,” In Proceedings of the 2011 ACM Symposium on Applied Computing, ACM, 1550-1557 (2011).
11. Q. Zheng, and S. Xu, “Fair and dynamic proofs of retrievability,” In Proceedings of the first ACM conference on Data and application security and privacy, ACM, 237-248 (2011).
12. A. Küpçü, “Official arbitration with secure cloud storage application,” The Computer Journal 58, 831-852 (2015).
13. N. Asokan, V. Shoup, and M. Waidner, “Optimistic fair exchange of digital signatures,” IEEE Journal on Selected Areas in communications 18, 593-610 (2000).
14. C. Wang, Q. Wang, K. Ren, and W. Lou, “Privacy-preserving public auditing for data storage security in cloud computing,” In Infocom, 2010 proceedings ieee, 1-9 (2010).
15. C. Wang, S. S. M Chow, Q. Wang, K. Ren, and W. Lou, “Privacy-preserving public auditing for secure cloud storage,” IEEE transactions on computers 62, 362-375 (2013).
16. B. Wang, B. Li, and H. Li, “Oruta: Privacy-preserving public auditing for shared data in the cloud,” In Cloud Computing (CLOUD), 2012 IEEE 5th International Conference on, 295-302 (2012).
17. J. Yuan, and S. Yu, “Proofs of retrievability with public verifiability and constant communication cost in cloud,” In Proceedings of the 2013 international workshop on Security in cloud computing, ACM, 19-26 (2013).
18. A. F. Barsoum, and M. A. Hasan, “Provable multicopy dynamic data possession in cloud computing systems,” IEEE Transactions on Information Forensics and Security 10, 485-497 (2015).
:NA
DOI Link : NA
Download :
  V4I43.pdf
Refbacks : There are currently no refbacks
Fast Singular value decomposition based image compression using butterfly particle swarm optimization technique (SVD-BPSO)
Authors : D.J. Ashpin Pabi, N.Puviarasan, P.Aruna
Affiliations : Research Scholar, Department of Computer Science and Engineering, Annamalai University, 608 002, India
Abstract :

af

Image compression is an important research area in an image processing system. Due to the compression of data rates, this finds crucial in applications of information security for the fast transmission. Singular Value Decomposition (SVD) is a compression technique which performs compression by using a smaller rank to approximate the original matrix of an image. SVD offers good PSNR values with low compression ratios. Compression using SVD for different singular values (Sv) with an acceptable PSNR increases the encoding time (ET). To minimize the encoding time, in this paper a fast compression technique SVD-BPSO is proposed using singular value decomposition and butterfly particle swarm optimization (BPSO). Application of the concept of BPSO towards singular value decomposition reduces the encoding time and improves the transmission speed. The performance of the proposed SVD-BPSO compression method is compared with SVD without optimization technique. The simulation results showed that the method achieves good PSNR with the minimum encoding time.
Citation :

af

D.J. Ashpin Pabi et.al, “Fast Singular value decomposition based image compression using butterfly particle swarm optimization technique (SVD-BPSO)”, International Journal Of Computer Engineering In Research Trends, 4(4):128-135, April-2017.
Keywords : Image Compression, Singular Value Decomposition (SVD), Butterfly Particle Swarm Optimization (BPSO), Encoding.
References :

af

1.	Moonen M et.al,” Singular value decomposition updating algorithm for subspace tracking”, SIAM Journal on Matrix Analysis and Applications, 13(4):1015-38,October-1992. 

2.	Konda  et.al, ”A new algorithm for singular value decomposition and its parallelization”, Parallel Comput., 35(6):331-344,June-2009.

3.	Julie Kamm L, SVD-Based Methods for Signal and Image Restoration, PhD Thesis, 1998.

4.	Yang J F et.al, “Combined Techniques of Singular Value Decomposition and Vector Quantization for Image Coding”, IEEE Trans. Image Processing, 4(8):1141 – 1146,August-1995.

5.	Awwal Mohammed Rufai et.al, “Lossy Image Compression using singular value decomposition and wavelet difference reduction”, Digital signal Processing, 24:117- 123,January-2014.

6.	Manoj Kumar, Ankita Vaish, An efficient encryption-then-compression technique for encrypted images using SVD, Digital Signal Processing, 60:81-89,January-2017.

7.	Jin Wang, Zhensen Wu et.al, “An efficient spatial deblocking of images with DCT compression”, Digital Signal Processing, 42:80-88,July-2015.

8.	Saiprasad Ravishankar, “Learning Sparsifying Transforms", IEEE Transactions on Signal Processing, 61(5):1072-1086,March-2013.

9.	K.M.M. Prabhu et.al, “3-D warped discrete cosine transform for MRI image compression”, Biomedical Signal Processing and Control, 8(1):50-58,January-2013.

10.	Kaveh Ahmadi et.al, “An efficient compression scheme based on adaptive thresholding in wavelet domain using particle swarm optimization”, Signal Processing: Image Communication, 32:33-39,March-2015.

11.	Fouzi Douak et.al, “Color image compression algorithm based on the DCT transform combined to an adaptive block scanning”, Int. J. Electron. Commun. (AEU), 65(1):16-26,January-2011.

12.	Lige Wang et.al, “Interpretation of Particle Breakage under Compression using X-ray”, Computed Tomography and Digital Image Correlation, Procedia Engineering, 102:240 – 248, 2015.

13.	Milan S. Savic et.al, “Coding algorithm for grayscale images based on Linear Prediction and dual mode quantization”, Expert Systems with Applications, 42(21):7285–7291,November-2015.

:10.22362/ijcert/2017/v4/i4/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I402.pdf
Refbacks : There are currently no refbacks
Automatic Bus Enquiry System using Android
Authors : Virendrakumar Dhotre, Namdev Sawant , Pallavi Pawar, Rajshree Salgar , Gitanjalee Hulwan
Affiliations : Assistant Professor, Computer Science & Engineering, SKN Sinhgad College of Engineering, 413304, India
Abstract :

af

Now people are not interested to carry systems along with them so we introduced mobile application “ABES” (Automatic bus enquiry system). Previously if we want to know any information about bus we should make a call to the enquiry system or by searching through internet. But now we can get all information about bus through this “ABES” app. In this application we are providing the all services related to the bus stand. We also provide the information about the bus time table and possible paths the all buses can travel. In this application user wants to find out the bus time from one place to another place. User needs to give the details of source and destination. Accordingly it will display the details of the bus going in that route .It is a time saving application to user. We are also providing the information about the source in which user are aware about the all the things related to that place. Number of time what happened passengers are going to the bus stand at that time bus may be late or passengers are late so that they are miss that bus they going to wait for next bus and time is also wasted , so to saving the time we will make this application. Most important benefit of this application is that, this application is not location restricted. User can use this application at any place. Because of that user can access all information related to bus at any time anywhere. This is an android based application
Citation :

af

Virendrakumar Dhotre et.al, “Automatic Bus Enquiry System using Android”, International Journal Of Computer Engineering In Research Trends, 4(4):123-127, April-2017.
Keywords : Automatic Bus Enquiry System using Android
References :

af

[1] Unity3D, Unity - Game Engine, http://unity3d.com/, downloaded: May 5th 2014. (Witte, 2008) Witte, C.; Armbruster, W.; Jäger, K. Au-tomatic generation of 3D models from real multisensor data. In Proceedings of the 11th International Conference on Information Fusion, pages 1823-1828, Cologne, Germany, 2008.
[2]VirtualWorldReview,http://www.virtualworldsreview.com/info/whatis.shtml
[3]. “A Comparison of Three Virtual World Platforms for the Purposes of Learning Support in Virtual Life”.
[4] “Network collaborative environment for human tissues 3D modeling”
[5] Virendrakumar Dhotre, “Personalized Web Search Using Browsing History and Domain Knowledge”, International Journal of Recent and Innovations Trends in Computing and Communication, ISSN: 2321-8169, Volume 3, Issue 3, March 2015. 
 [6]https://docs.unity3d.com/Manual/HOWTO-importObject.html
[7] Virendra A. Dhotre, “Image Authentication Using Stochastic Diffusino”, International Journal of Engineering Research and Technology, ISSN: 2278-0181, Volume 4, Issue 4, April-2015.
 [8] “he design and research of the somatosensory interaction system based on kinect and unity 3D”, Yanke Ci; Jinli Yao 2015 10th International Conference on Computer Science & Education (ICCSE) Year: 2015 Pages: 983 - 986, DOI: 10.1109/ICCSE.2015.7250394
[9] “The simulation of building escape system based on Unity3D” Qiyun Sun; Wanggen Wan; Xiaoqing Yu 2016 International Conference on Audio, Language and Image Processing (ICALIP) Year: 2016 Pages: 156 - 160, DOI: 10.1109/ICALIP.2016.7846656
[10] “Immersive VR for natural interaction with a haptic interface for Shape Rendering” Mario Covarrubias; Monica Bordegoni 2015 IEEE 1st International Forum on Research and Technologies for Society and Industry Leveraging a better tomorrow (RTSI) Year: 2015 Pages: 82 - 89, DOI: 10.1109/RTSI.2015.7325075
[11] A 3D Simulation System for Emergency Evacuation in Offshore Platforms Guilherme Bezerra Zampronio; Alberto Barbosa Raposo; Marcelo Gattass 2015 XVII Symposium on Virtual and Augmented Reality Year: 2015, Pages: 99 - 106, DOI: 10.1109/SVR.2015.21
[12] Virendrakumar Dhotre, Dr. K. j. karande “Refinement of Data Streams using Minimum  variance principle”, 978-1-4799-6629-5/14/$31.00_c 2014 IEEE.
[13] Virendrakumar Dhotre “Fog Computing: Mitigating Insider Data Theft Attacks in the Cloud”, International Journal of Trend in Research and Development, ISSN: 2394-9333, Volume 2, Issue 2, March-April, 2015.
 [14] ”3D Virtual Client Center and its Service Oriented Modeling”
.[15] Dhotre V. A. “Meet you – Social Networking on Android”, International Journal of Innovations and Advancement in Computer Science, ISSN: 2347-8616, Volume 4, Issue 4, April 2015.
[16] http://tf3dm.com/3d-models/electronics
[17] Virendrakumar A. Dhotre, “Integrity and Confidentiality for the Files in Cloud Storage”, International Journal of Trend in Research and Development, ISSN: 2394-9333, Volume 2, Issue 2, March-April 2015.
[18] Dhotre Virendrakumar, “A New Method of Image Compression and Decompression Using Huffman Coding Technic” International Engineering Research Journal, ISSN: 2395-1621, Volume 1, Issue 4, April 2015.
[19] Virendrakumar Dhotre, “Secure Data Transmission Using Wireless Data Transmission and Face Detection”, International Journal of Recent and Innovations Trends in Computing and Communication, ISSN: 2321-8169, Volume 2, Issue 4, April 2014.
:10.22362/ijcert/2017/v4/i4/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I401.pdf
Refbacks : There are currently no refbacks

 

To Increase Endurance and Durability of Battery Powered RC Hovercraft
Authors : Ajay Kumar Yadav, Dinesh M, Surendar Ganesan
Affiliations : Department of Aeronautical Engineering, Vel Tech Dr. RR & Dr. SR Technical University, Chennai
Abstract :

af

Yogendra P Jahagirdar, M Parvez Alam
Citation :

af

Ajay Kumar Yadav et.al, “To Increase Endurance and Durability of Battery Powered RC Hovercraft”, International Journal Of Computer Engineering In Research Trends, 4(3):119-122, March-2017.
Keywords : HOVERCRAFT,Battery Powered RC Hovercraft
References :

af

1.	http://www.antonine-education.co.uk/Pages/Physics_2/Mechanics/MEC_09/Mechanics_Page_9.htm
2.	http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1516-14392006000300002
3.	http://chinafrp.en.made-in-china.com/product/ySpQrwdAfchW/China-Supply-High-Strength-Carbon-Fiber-Tube.html
4.	Akshay Balachandran, Divyesh Karelia, Dr. Jayaramulu Challa, “Material selection for unmanned aerial vehicle”, In: International Journal of Mechanical Engineering and Technology.
5.	Aumkar Rane and Raghav Kabra, “Fabrication of Carbon Fiber Fuselage for Unmanned Aerial Vehicle”, In: International Journal of Research – Granthalayah
6.	Amit tiwari, “To study and fabrication of air cushion vehicle”, In: International Journal of Research – Granthalayah
7.	Okafor, B.E., “Development of Hovercraft prototype”, In: International Journal of Engineering and Technology (March 2013).
8.	Prof. P. S. Shirsath, Prof. M. S. Hajare, Prof. G. D. Sonawane, Mr. Atul Kumar, Mr. S. U. Gunjal, “A review on design and analysis of amphibious vehicle”, In: International journal of Science, Technology and Management (January 2015).
9.	Rakesh Chandmal Sharma, Manish Dhingra, Rajeev Kumar Pathak, Manish Kumar, “Air Cushion Vehicles: Configuration, Resistance and Control”, In: Journal of Science (2014).
10.	Anandhakumar, S. Ganeshan, S. Goutham, K. Pasupathi, “Design and fabrication of Hovercraft”, In: International Journal of Innovative Research in Science, Engineering and Technology (2015).
:10.22362/ijcert/2017/v4/i3/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I309.pdf
Refbacks : There are currently no refbacks
Spoken Keyword Spotting System Design Using Various Wavelet Transformation Techniques with BPNN Classifier
Authors : Senthil Devi K. A., Dr. B. Srinivasan ,
Affiliations : Assistant Professor, Gobi Arts & Science College, Tamil Nadu, India. 2 Associate Professor, Gobi Arts & Science College, Tamil Nadu, India.
Abstract :

af

SpokenKeyword spotting is a speech data mining task which is used to search audio signals for finding occurrences of a specified spoken word in the given speech file.It is essential to identify the occurrences of specified keywords expertly from lots of hours of speech contents such as meetings, lectures, etc. In this paper, keyword spotting system designed with various wavelet transformation techniques and BackpropagationNeural Network (BPNN). Back Propagation Neural Network (BPNN) is trained with two predefined spoken keywords based on known features, and finally, input speech features are compared with keyword features in the trained BPNN for spotting the occurrences of the specified keyword.The method of this paper tested with ten speech content often different speakers. Various statistical features extraction techniques with wavelet transformation are used. Performance comparison is done among these methods with Haar, Daubechies2 and Simlet 4 wavelets.
Citation :

af

Senthil Devi K. A et.al, “Spoken Keyword Spotting System Design Using Various Wavelet Transformation Techniques with BPNN Classifier”, International Journal Of Computer Engineering In Research Trends, 4(3):111-118, March-2017.
Keywords : Spoken keyword spotting, Speech data mining, MFCC, Wavelet Packet Decomposition, Discrete Wavelet Transformation, BPN neural network, wavelet families.
References :

af

1. Bahi, H., and Benati, N., [2009], “A new keyword
spotting approach”, IEEE International
Conference on Multimedia Computing and
Systems, pp. 77-80.
2. Chui CK, [1992], “An introduction to wavelets”.
Academic, New York.
3. P. Flandrin. Representation temps-fréquence.
Hermes, 1993
4. Fourier J, [1822], “The analytical theory of heat.
(trans: Freeman A)”, Cambridge University Press,
London, pp. 1878
5. Heerman P.D. and N.Khazenie, “Classification of
multispedtral remote sensing data using a bach
propagation neural network,” IEEE Trans, Geosci.
Remote Sensing, vol.GE_30,no.1,1992, pp.81-88.
6. Jo Yew Tham, Lixin Shen, Seng Luan Lee and
Hwee Huat Tan (2000) “A General Approach for
analysis and application of Discrete Multiwavelet
Transforms”, IEEE Transaction on Signal
Processing ,48(2), 457- 464.
7. Jothilakshmi, S., Spoken keyword detection using
autoassociative neural networks, International
Journal Speech Technology, Springer, 2013, pp.
83-89.
8. Khan, W. and Holton, R., Word spotting in
continuous speech using wavelet transform, IEEE
International Conference on Electro/Information
Technology, 2014, pp.275-279
9. Mallat S., [1999], “A wavelet Tour of Signal
Processing”, Academic Press, New York, 1999.
10. Qian S, [2002], “Time-frequency and wavelet
transforms”, Prentice Hall PTR, Upper Saddle,
River, NJ.
11. Rama Kishore, Taranjit Kaur, “Backpropagation
Algorithm: An Artificial Neural Network
Approach for Pattern Recognition”, International
Journal of Scientific & Engineering Research,
Volume 3, Issue 6, June-2012 1 ISSN 2229-5518.
12. Sangeetha, J. and Jothilakshmi, S., “A novel
spoken keyword spotting system using support
vector machine”, Engineering Applications of
Artificial Intelligence, Springer, 2014, pp. 287–
293.
13. Senthil devi K.A., Dr.Srinivasan B., “A novel
Keyword Spotting Algorithm in speech mining
using wavelet”, International Journal of Current
Research Vol. 8, Issue, 08, pp.36943-36946,
August, 2016.
14. Senthil devi K A., Dr.Srinivasan B., “Wavelet –
Neural Network Approach for keyword spotting in
Speech Mining”, International Journal of Trends
and Technologies”, Vol 43, Issue 3, pp 160-165,
2017.
15. Tao Li, Sheng Ma, Mitsunori Ogihara, ” Wavelet
methods in data mining”, Chapter 27 Data Mining
and Knowledge Discovery Handbook ,Springer,
2005, pp 603-626.
:10.22362/ijcert/2017/v4/i3/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I308.pdf
Refbacks : There are currently no refbacks
A Survey on RFID Based Vehicle Authentication Using A Smart Card
Authors : Ms.LITTY RAJAN , Ms.ALPANA GOPI , Ms. DIVYA P R ,Mr. SURYA RAJAN
Affiliations :
Abstract :

af

Now a day's every system is automated in order to face new challenges. In the present days Automated systems have less manual operations, flexibility, reliability and accuracy. Due to this demand for less manual controlling, every one prefers automated control systems. Especially in the home and industries of electronics, automated systems are giving good performance and flexibility to get controlling without your involvement. We are conducting a survey in this paper based on RFID applications. In this paper, we discussed about the vehicle authentication with RFID.RFID used for the automatic tracking and detection of tagged objects through radio waves. It requires RFID tag stores digital information when it comes in the visibility of reader and reader reads the digital information and send to the server.
Citation :

af

LITTY RAJAN et.al, “A Survey on RFID Based Vehicle Authentication Using A Smart Card”, International Journal Of Computer Engineering In Research Trends, 4(3):106-110, March-2017.
Keywords : RFID, tag , reader, rfid card, identification
References :

af

[1] RFID Technology Application in Container Transportation Wei Wang, Shidong Fan lShanghai Maritime Academy, China and Schoot of Energy and Power Engineering, Wuhan University of Technology, China.
[2] Automatic Vehicle Identification with Sensor-Integrated RFID System 1 J. Wisanmongkol, T.Sanpechuda and U.Ketprom Proceedings of ECTI-CON 2008.
[3] The Research and Application of RFID Technologies in Highway’s Electronic Toll Collection System Xu Guangxian Department of Electronic Information Engineering, Liaoning Technical University  HuLuDao, China.
[4] Aware and Smart Member Card: RFID and License Plate Recognition Systems Integrated Applications at Parking Guidance in Shopping Mall Cheng-kung Chung and Yu-kuang Hsieh, Yung-hau Wang   and Ching-ter Chang 8th International Conference on Advanced Computational Intelligence Chiang Mai, Thailand; February 14-16, 2016.
[5] RFID-BASED INFORMATION SHARING PLATFORM Ning Li, Zhongliang Deng, Feng Wan, Shibo Zhu, Xiao Liu Proceedings of ICCTA2009.
 [6] Design of an RFID Vehicle Authentication System: A Case Study for Al-Nahrain University Campus Fawzi M. Al-Naima, Haider S. Hatem International Journal of Scientific and Technological Research www.iiste.org ISSN 2422-8702 (Online) Vol 1, No.7, 2015.
[7] Security System for Vehicle using Number Plate Detection and RFID Paras Goyal, Iqbal Singh International Journal of Computer Applications (0975 – 8887) Volume 97– No.8, July 2014.
[8] Vehicle Tracking Using RFID Jayalakshmi J, Ambily O A International Journal of Engineering Research and General Science Volume 4, Issue 2, March-April, 2016 ISSN 2091-2730
[9] Vehicle Fitted Driving License Based Security and Road Safety System M. Rajesh , K. Vignesh Ramanathan , R. Jagadish  , S. Dhayalan International Journal of Innovative Research in Science, Engineering and Technology An ISO 3297: 2007 Certified Organization, Volume 4, Special Issue 4, April 2015.
[10] Embedded Based Conveyance Authentication and Notification System S. Dharanya , A. Umamakeswari  International Journal of Engineering and Technology (IJET) ISSN : 0975-4024 Vol 5 No 1 Feb-Mar 2013.
:10.22362/ijcert/2017/v4/i3/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I307.pdf
Refbacks : There are currently no refbacks
Internet level Traceback System for Identifying the Locations of IP Spoofers from Path Backscatter
Authors : Sharada K. Shiaragudikar, Nagaraj M. Benakanahalli, Pavana Baligar , Arunakumar Joshii, JagadeeshMeti
Affiliations : Asst.Prof,Department of Computer/Information Science and Engineering, S. K. S. V. M. Agadi College of Engineering and Technology, Laxmeshwar582116,India
Abstract :

af

It is normal that the attackers over the network may use the fake source IP address to conceal their actual locations. This paper proposes a framework that bypasses the deployment challenges of IP Traceback techniques [1]. This system researches Internet Control Message Protocol error messages (named path backscatter) activated by spoofing traffic, and tracks the Spoofers based on the information available by the public(e.g., topology). Along these, the proposed framework can discover the Spoofers with no deployment prerequisite. Despite the fact that the proposed framework can't work in all the spoofing attacks, it might be the most helpful mechanism to trace Spoofers before an Internet-level traceback framework has been deployed in real. The results are got by implementing in the form of simulation using Java platform for understanding the system over the networks.
Citation :

af

Sharada K. Shiaragudikar et.al, “Internet level Traceback System for Identifying the Locations of IP Spoofers from Path Backscatter”, International Journal Of Computer Engineering In Research Trends, 4(3):98-105, March-2017.
Keywords : Internet, IPaddress ,traceback mechanism,Spoofer,protocol.
References :

af

[1].Passive IP Traceback: Disclosing the Locations of IP Spoofers From Path Backscatter Guang Yao, Jun Bi, Senior Member, IEEE, and Athanasios V. Vasilakos, Senior Member.

[2] S. M. Bellovin, “Security problems in the TCP/IP protocol suite,”ACM SIGCOMM Comput.Commun. Rev., vol. 19, no. 2, pp. 32–48,Apr. 1989.

[3] ICANN Security and Stability Advisory Committee, “Distributed denial of service (DDOS) attacks,” SSAC, Tech. Rep. SSAC Advisory SAC008,Mar. 2006.

[4] C. Labovitz, “Bots, DDoS and ground truth,” presented at the 50thNANOG, Oct. 2010.

[5] The UCSD Network Telescope. [Online]. Available: http://www.caida.org/projects/network_telescope/

[6] S. Savage, D. Wetherall, A. Karlin, and T. Anderson, “Practical network support for IP traceback,” in Proc. Conf. Appl., Technol., Archit., Protocols Comput. Commun. (SIGCOMM), 2000, pp. 295–306.

[7] S. Bellovin. ICMP Traceback Messages.[Online]. Available: http://tools.ietf.org/html/draft-ietf-itrace-04, accessed Feb. 2003.

[8] A. C. Snoeren et al., “Hash-based IP traceback,” SIGCOMM Comput. Commun. Rev., vol. 31, no. 4, pp. 3–14, Aug. 2001. [8] D. Moore, C. Shannon, D. J. Brown, G. M. Voelker, and S. Savage,“Inferring internet denial-of-service activity,” ACM Trans. Comput. Syst., vol. 24, no. 2, pp. 115–139, May 2006. [Online]. Available: http://doi.acm.org/10.1145/1132026.1132027

[9] M. T. Goodrich, “Efficient packet marking for large-scale IP traceback,”in Proc. 9th ACM Conf. Comput. Commun.Secur. (CCS), 2002,pp. 117–126.

[10] D. X. Song and A. Perrig, “Advanced and authenticated marking schemes for IP traceback,” in Proc. IEEE 20th Annu. Joint Conf. IEEE Comput.Commun.Soc. (INFOCOM), vol. 2. Apr. 2001, pp. 878–886.

[11] A. Yaar, A. Perrig, and D. Song, “FIT: Fast internet traceback,” in Proc. IEEE 24th Annu. Joint Conf. IEEE Comput.Commun.Soc. (INFOCOM), vol. 2. Mar. 2005, pp. 1395–1406.

[12] J. Liu, Z.-J.Lee, and Y.-C. Chung, “Dynamic probabilistic packet marking for efficient IP traceback,” Comput.Netw., vol. 51, no. 3, pp. 866–882, 2007.

[13] K. Park and H. Lee, “On the effectiveness of probabilistic packet marking for IP traceback under denial of service attack,” in Proc. IEEE 20th Annu. Joint Conf. IEEE Comput.Commun.Soc. (INFOCOM), vol. 1. Apr. 2001, pp. 338–347
:10.22362/ijcert/2017/v4/i3/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I306.pdf
Refbacks : There are currently no refbacks
Various Obstruction Removal Techniques from a Sequence of Images
Authors : Miss Ashwini Gat, Mr. Uday Nuli, Mr. Sandip Murchite
Affiliations : Computer Science & Engineering, TEI’s DKTE, Ichakaranji, 416115/416115, India
Abstract :

af

Reflection or obstruction from images is a major reason for quality degradation of images in image processing. Camera Flash is frequently used to capture a good photograph of a scene under low light conditions. However, flash images have many problems: The flash can often be blinding and too strong, leading to blown out images. This report presents separate algorithms described in the literature that attempts to remove obstructions computationally. The strengths and weaknesses of each algorithm outlined.
Citation :

af

Ashwini Gat et.al, “Various Obstruction Removal Techniques from a Sequence of Images”, International Journal Of Computer Engineering In Research Trends, 4(3):86-88, March-2017.
Keywords : flash, reflection removal, obstruction, SPBSM, SID, GPSR.
References :

af

[1]	K. Gai, Z. Shi, and C. Zhang. Blind separation of superimposed moving images using image statistics. IEEE Transactions on Pattern Analysis and Machine Intelligence, 34(1):19–32, Jan 2012.

[2]	X. Guo, X. Cao, and Y. Ma. Robust separation of reflection from multiple images. In Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on, pages 2195–2202, June 2014.

[3]	Levin, A. Zomet, and Y.Weiss. Separating reflections from a single image using local features. In Computer Vision and Pattern Recognition, 2004. CVPR 2004. Proceedings of the 2004 IEEE Computer Society Conference on, Volume 1, pages I–306–I–313 Vol.1, June 2004

[4]	Y. Shih, D. Krishnan, F. Durand, and W. Freeman. Reflection removal using ghosting cues. In Computer Vision and Pattern Recognition (CVPR), 2015 IEEE Conference on, pages 3193– 3201, June 2015.

[5]	S. N. Sinha, J. Kopf, M. Goesele, D. Scharstein, and R. Szeliski. Image-based rendering for scenes with reflections. In ACM Trans. Graph. (August 2012). ACM SIGGRAPH, August 2012.

[6]	A. K. Jain, “Fundamentals of Digital Image Processing” Prentice-Hall, 1986, p 384.

[7]	Amit Agrawal Ramesh Raskar Shree K. Nayar† Yuanzhen Li Mitsubishi “Removing Photography Artifacts using Gradient Projection and Flash-Exposure Sampling” Electric Research Labs (MERL), Cambridge, MA_ †Columbia University

[8]	Li Michael S. Brown “Exploiting Reflection Change for Automatic Reflection Removal” Yu School of Computing, National University of Singapore liyu@nus.edu.sg | brown@comp.nus.edu.sg

[9]	B.himabindu (Asst. professor, Department of E.C.E, Chalapathi Institute of Technology, Guntur, A.P, India). “Removal of Shadows and Reflections in the Images By Using Cross-Projection Tensors” IOSR Journal of Engineering (IOSRJEN) ISSN: 2250-3021 Volume 2, Issue 8 (August 2012), PP 34-40 www.iosrjen.org www.iosrjen.org 34|Page 

[10]	 Mário A. T. Figueiredo, Senior Member IEEE, Robert D. Nowak, Senior Member, IEEE, and Stephen J. Wright “Gradient Projection for Sparse Reconstruction: Application to Compressed Sensing and Other Inverse Problems” IEEE journal of selected topics in signal processing, vol. 1, no. 4, december 2007.
[11]	A. Levin, A. Zomet, and Y. Weiss. “Separating reflections from a single image using local features”. In CVPR, 2004. [7]Song,Bo; Gong,shenwen; Ren,chunjian “Removing artifacts using gradient projection from a single image”. MIPPR 2011: Pattern Recognition and Computer Vision. Edited by Roberts, Jonathan; Ma, Jie. Proceedings of the SPIE, Volume 8004, article id. 80041C, 6 pp. (2011). (SPIE homepage). 
:10.22362/ijcert/2017/v4/i3/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I304.pdf
Refbacks : There are currently no refbacks
Youth Involvement in the Social Media for Discussing Social Problems
Authors : Dr.Basayya M Hosurmath, ,
Affiliations : Lecturer, Department of Journalism and Mass Communication Davangere University, Davangere
Abstract :

af

We can’t assume the society without the communication. As we know presently we all are very near, we are not alone, we all can share our thoughts, experience, ideas, information from anywhere, anytime and with anyone. That is all only possible from the inventions of new communication technologies. In every field we are using different tools for the communication as per the requirements.Hence, the impact of new technology is much in day to day life. As we know man is a Social Animal. He can not live without the society.To live in the society he defended on the society one or the other reason. Hence, to have good relation with the society he needs to communication to express his needs. In the beginning from the body language and verbal symbols man was expressing his feelings and needs. Later, after the invention of the language, communication became very easy. The later invention given extra feather to the communication. Invention of Print, Radio, TV. and New Media made it possible to communicate with mass people at the same time. In the latest technology the invention of computer and internet have given more opportunities for the communication.And it converged all media in one network. Internet technology has became the platform for the Social Network. The introduction of www(World Wide Web) concept by Tim Burners Lee in 1989 Social Network has became the place where society is involved in one network for sharing thoughts, ideas, expressions, information etc. about political, economical, social issues or subjects as per their requirements. In 1990 classmates.com has made to get in touch with the similar kind of people. With these Asian Avenue Black, Planet and Gente Profile also have started its service. The recent and most used social networks are Facebook and twitter. Facebook is on of the social network which has highest number of user in the world. And Twitter is in the second place.These social networks not only remained as the tool of sharing pictures, videos, text or a personal information. It is also used as the tool for creating social awareness in the society. Social awareness subjects like corruption, food wastage, new plans, social behaviour, good governance etc. are discussed in these networks and attracting many people towards this type of subjects.
Citation :

af

Dr.Basayya M Hosurmath et.al, “Youth Involvement in the Social Media for Discussing Social Problems”, International Journal Of Computer Engineering In Research Trends, 4(3):81-85, March-2017.
Keywords : Scoial Media , Facebook and twitter, Questionnaire and analyse.
References :

af

[1]	Donna L. Hoffman, Thomas P. Novak, April 1999/Vol. 42, No. 4 COMMUNICATIONS OF THEACM( Google scholar) 
[2]	www.nielsen.com
[3]	http://en.wikipedia.org/wiki/Social Media 
[4]	Kipp Bodnar – “Social Media Book” - Wiley Publication – 2012
[5]	Dave Awl – “Facebook Me” – Peachpit Press - 2009 
[6]	Joel Comm – “Twitter Power” – Wiley Publication – 2009.
:10.22362/ijcert/2017/v4/i3/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I303.pdf
Refbacks : There are currently no refbacks
Wide Band 3-D Novel flange Microstrip Patch Antenna Design employing Flexible Teflon Substrate
Authors : Avneet Kaur , Ekambir Sidhu,
Affiliations : Department of Electronics and Communication Engineering, Punjabi University Patiala, India
Abstract :

af

This paper encapsulates a novel microstrip patch antenna design over flexible Teflon substrate having dielectric constant εr= 2.1. The designed antenna exploits a rectangular patch (0.05mm thick) on the radiating patch along with microstrip feed line and defected ground plane on the other side of the substrate. The radiating element of the flexible flanged antenna design has a finite ground plane to accomplish an excellent impedance matching for maximum power transfer. The proposed antenna has an operating bandwidth of 2.9226 GHz which ranges from 15.197GHz-18.12GHz with a resonant frequency of 15.72GHz. This flexible flanged microstrip patch antenna design covers various applications including Radio Astronomy (15.35GHz-15.4GHz), Radiolocation/Airborne Doppler navigation aids (15.4GHz-15.43Hz), Radiolocation(civil)/Airborne Doppler navigation (15.43GHz-15.63GHz), Radiolocation(military) (15.7GHz-17.7GHz), FSS Earth Stations (17.7GHz-20.2GHz), Weather Satellite(18.1GHz-18.3GHz), Broadcasting(Satellite) (21.4GHz-22GHz). The proposed antenna operates for acceptable voltage standing wave ratio (VSWR) less than two. The characteristics of the proposed antenna fabricated on a flexible PVC and analyzed its performance at different antenna parameters like Return loss (dB), Impedance Bandwidth, Gain(dB), Directivity(dBi), VSWR and antenna impedance. The antenna has been designed in CST Microwave Studio 2014. The proposed antenna has been fabricated and tested using an E5071C Network analyser and an anechoic chamber. It has been observed that the simulated results, legitimately match with the experimental results.
Citation :

af

Avneet Kaur et.al, “Wide Band 3-D Novel flange Microstrip Patch Antenna Design employing Flexible Teflon Substrate”, International Journal Of Computer Engineering In Research Trends, 4(3):76-80, March-2017.
Keywords : Defected ground plane, Flexible antenna, PVC, Reduced shaped patch, Teflon
References :

af

[1]	B. D. Patel, Tanisha Narang1, Shubhangi Jain,”Microstrip Patch Antenna- A Historical Perspective of the Development,” Conference on Advances in Communication and Control Systems 2013 (CAC2S 2013) 
[2]	Indrasen Singh, Dr. V.S. Tripathi, “Micro strip Patch Antenna and its Applications: a Survey,” International Journal of Circuit Theory and Applications, vol. 2, no. 5, ISSN:2229-6093, Sept-Oct 2011.
[3]	Pavan Kumar Sharma, Veerendra Singh Jadaun,” Multi-Band Rectangular Microstrip Patch Antenna with Defected Ground Structure and a Metallic Stripe” International Journal of Technological Exploration and Learning (IJTEL) vol. 1, Issue 1, ISSN: 2319-2135, August 2012.
[4]	Stephyjohn, Manoj k c,” Microstrip Patch Antennas for Uwb Applications: A Review,” IOSR Journal of Electronics and Communication Engineering (IOSR-JECE), vol. 9, Issue 2, pp- 34-37, Mar - Apr. 2014.
[5]	M. T. Islam, M. Habib Ullah, J.S. Mandeep, N. Misran, and M.B.I Reaz,” A Low Profile High Gain Dual Band Patch Antenna for Satellite Application,”International Conference on Electrical, Electronics and Instrumentation Engineering (EEIE'2013), Nov. 27-28, 2013, Johannesburg (South Africa)
[6]	Jobin Kurian, UpamaRajan M.N, Shinoj K. Sukumaran, “Flexible Microstrip Patch Antenna using Rubber Substrate for WBAN Applications,” International Conference on Contemporary Computing and Informatics (IC3I), 2014.
[7]	C. Balanis, Antenna Theory Analysis and Design. New York: Wiley Interscience, 2005.
[8]	RameezShamalik, SushamaShelke, “Design and Simulation of Flexible Antenna for ISM band,” International Journal of Engineering Research and Applications (IJERA), ISSN: 2248-9622, Vol. 2, Issue 3, pp.2168-2170, 2012.
[9]	Shailesh Kumar, GajanandJagrawal and Deepak Billore,” E–Shaped Coaxial Feed Microstrip Patch Antenna for WLAN and WIMAX Applications,” International Journal of Current Engineering and Technology,vol.5, No.2, April 2015.
[10]	Hirohide Serizawa and KoheiHongo,”Radiation from a Flanged Rectangular Waveguide,” IEEE Transactions on Antennas and Propagation, vol. 53, no. 12, December 2005.
[11]	A. Zvyagintsev, A. Ivanov,”Radiation pattern calculation of Flanged Reflector antennas,” 12th International Conference on Mathematical Methods in Electromagnetic Theory, June 29 – July 02, 2008, Odesa, Ukraine.
[12]	Avneet Kaur, Gurnoor Singh, Ekambir Sidhu,”Novel Microstrip Patch Antenna Design employing Flexible PVC Substrate suitable for defence and Radio-determination Applications,” Progress in theproceedings of International conference on automatic control and dynamic optimization techniques, 9 september 2016, Pune, India.
[13]	T. Durga Prasad, K. V. Satya Kumar, MD KhwajaMuinuddin, ChistiB.Kanthamma, V.SantoshKumar,” Comparisons of Circular and Rectangular Microstrip Patch Antennas,” International Journal of Communication Engineering Applications-IJCEA, vol. 02, Issue 04; July 2011.
:10.22362/ijcert/2017/v4/i3/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I302.pdf
Refbacks : There are currently no refbacks
Texture Image Segmentation Based on threshold Techniques
Authors : Dodla. Likhith Reddy, Dr. D Prathyusha Reddi,
Affiliations : Professor, Dept.of ECE, PBR VITS, KAVALI
Abstract :

af

Image segmentation is the process of partitioning a digital image into multiple segments. The goal of segmentation is to simplify change the representation of an image into something that is more meaningful and easier to analyze. Image segmentation is used to give the values of objects and boundaries of a selected image like lines, curves. The image segmentation plays a critical role in a variety of pattern recognition applications such as robot vision, cartography, criminal investigation, remote sensing, object identification and recognition, military surveillance, quality assurance in industries, facial recognition and medical imaging, etc. The main aim of this paper is to propose methods are improving image segmentation and give the clear object about the image by using different techniques. This article presents a brief outline of some of the most commonly used segmentation techniques like Thresholding, Region based and Edge detection methods. The proposed methods implemented in MATLAB.
Citation :

af

Dodla. Likhith Reddy et.al, “Texture Image Segmentation Based on threshold Techniques”, International Journal Of Computer Engineering In Research Trends, 4(3):69-75, March-2017.
Keywords : Segmentation, Edge Detection, Region Based, threshold-based segmentation techniques.
References :

af

[1]	A. Bovik, M. Clark, W.S. Geisler, Multichannel texture analysis using localized spatial filters, IEEE Trans. Pattern Anal. and Machine Intelligence 12 (1990), 55-73
[2]	A. Khotanzad, A. Bouarfa, A parallel non-parametric clustering algorithm with application to image segmentation, Proc. 22nd Asilomar Conf. on Signals, Systems, and Computers, Pacific Grove, CA,( 1988)305-309
[3]	A. Laine, J. Fan, Frame representations for texture segmentation, IEEE Trans. Image Processing,  5 (1996) 771-780
[4]	A.K. Jain, F. Farrokhnia, Unsupervised texture segmentation using Gabor filters, Pattern Recognition, 24 (1991) 1167-1186
[5]	A.K. Jain, K. Karu, Learning texture discrimination masks, IEEE Trans. Pattern Anal. Machine Intelligence 18 (1996) 195-205.
[6]	Ahmed R. Khalifa et al.,Evaluating The Effectiveness Of Region Growing And Edge Detection Segmentation Algorithms,. Journal of American Science,6(10), (2010) , 580-587
[7]	Arbelaez, P., Maire, M., Fowlkes, C., Malik, J.: ‘Contour detection and hierarchical image segmentation’, IEEE Trans. Patt. Anal. Mach. Intell., 33, (5), (2010) 898–916
[8]	Arifin, A.Z., Asano, A.: ‘Image segmentation by histogram thresholding using hierarchical cluster analysis’, Patt. Recogn.Lett., 27, (13), (2006)1515–1521
[9]	AshwiniKunte, Anjali Bhalchandra, Efficient DIS Based Region Growing Segmentation Technique for VHR Satellite Images , ICGST-GVIP Journal, Volume 10, Issue 3, (2010)
[10]	B.B. Chaudhuri, N. Sarkar, Texture segmentation using fractal dimension, IEEE Trans. Pattern Anal. Machine Intelligence, 17 (1995) 72-77
[11]	B.S. Manjunath, R. Chellappa, Unsupervised texture segmentation using Markov random field models, IEEE Trans. on Pattern Anal. Machine Intelligence 13 (1991) 478-482
[12]	C. Bouman, B. Liu, Multiple resolution segmentation of textured images, IEEE Trans. Pattern Anal. Machine Intelligence 13 (1991) 99-113
[13]	Canny, J.: ‘A computational approach to edge detection’, IEEE Trans. Patt. Anal. Mach. Intell., 8, (6), (1986) 679–698
[14]	Carreira-Perpinan, M.A.: Acceleration strategies for Gaussian mean-shift image segmentation. Proc. IEEE Conf. on Computer Vision Pattern Recognition,  vol. 1, (2006)1160–1167
[15]	Carreira-Perpinan, M.A.: Acceleration strategies for Gaussian mean-shift image segmentation. Proc. IEEE Conf. on Computer Vision Pattern Recognition,  vol. 1, (2006) 1160–1167
[16]	Chen, T.W., Chen, Y.L., Chien, S.Y.: Fast image segmentation based on K-means clustering with histograms in HSV color space. Proc. IEEE Int. Workshop on Multimedia Signal Processing, October (2008) 322–325
[17]	Cheng, Y.: ‘Mean shift, mode seeking, and clustering’, IEEE Trans.Patt. Anal. Mach. Intell., 1995, 17, (8),  (1995) 790–799
[18]	Comaniciu, D., Meer, P.: ‘Mean shift: a robust approach toward feature space analysis’, IEEE Trans. Patt. Anal. Mach. Intell., 24, (5),  (2002) 603–619
[19]	Cour, T., Benezit, F., Shi, J.: ‘‘Spectral segmentation with Multiscale graph decomposition’‘. Proc. IEEE Conf. on Computer Vision Pattern Recognition, vol. 2, (2005) 1124–1131
[20]	Cui.Y, Dong.H, Zhou.E.Z, “An Early Fire Detection Method Based on Smoke Texture Analysis and Discrimination”, Journal Congress on Image and Sig. Proc., (2008), 95–99.
[21]	Cula.O.G and Dana.K.J, 3D texture recognition using bidirectional feature histograms, in Int. Journal Comp. Vis., vol.59, (2004 )33–60
[22]	D.K. Panjwani, G. Healey, “Markov random field models for unsupervised segmentation of textured color images”, IEEE Trans. Pattern Anal. Machine Intelligence, 17 (1995), 939-954
[23]	Delon, J., Desolneux, A., Lisani, J.L., Petro, A.B.: ‘A nonparametric approach for histogram segmentation’, IEEE Trans. Image Process., 16, (1),  (2007) 253–261.
[24]	Donald.A, Adjeroh and UmasankarKandaswamy, “Texton-based segmentation of retinal vessels”, Journal of Optical Society of America , vol. 24, no. 5,(2007)  1384–1393
[25]	Duda, R.O., Hart, P.E.: ‘Pattern classification and scene analysis’, (Wiley, 1973).
[26]	F.S. Cohen, Z. Fan, Maximum likelihood unsupervised textured image segmentation, CVGIP: Graphical Models and Image Processing 54 (1992) 239-251
[27]	Ghamisi, P., Couceiro, M.S., Benediktsson, J.A., Ferreira, N.M.: ‘‘An efficient method for segmentation of images based on fractional calculus and natural selection’‘, Expert Syst. 39, (16), (2012)12407–12417.
[28]	Glasbey, C.A.: ‘An analysis of histogram-based thresholding algorithms’, Comput. Vis. Graph. Image Process., 55, (6),  (1993) 532–537
[29]	H. D. Cheng and Y. Sun, “A hierarchical approach to color image segmentation using homogeneity”, IEEE Transaction on Image Processing, vol. 9, no. 12, 2000 (2071- 2082)
[30]	H. Greenspan, R. Goodman, R. Chellappa, C.H. Anderson, “Learning texture discrimination rules in a multiresolution system”, IEEE Trans. Pattern Anal. Machine Intelligence 16 (1994) 894-901
[31]	H. Seddik and E. Ben Braiek “Color Medical Images Watermarking, Based Neural Network Segmentation “GVIP Journal Special Special Issue on (Medical Image Processing), (2006) 81-86
[32]	http://wang.ist.psu.edu/docs/related/
[33]	http://www.imageprocessingplace.com/root_files_V3/image_databases.html.
[34]	http://www.ux.uis.no/~tranden/brodatz.html
[35]	Huang, S.H., Chu, Y.H., Lai, S.H., Novak, C.L.: ‘‘Learning-based vertebra detection and iterative normalized-cut segmentation for spinal MRI’‘, IEEE Trans. Med. Imag., 28, (8), (2009) 1595–1605
[36]	Idrissisidiyassine, Samir belfkih, "Texture image segmentation using a new descriptor and mathematical morphology”, in Int. Arab Journal of Information Technology, Vol.10, No.2, (2013)  204-208
[37]	J. Mao, A.K. Jain, “Texture classification and segmentation using multi resolution simultaneous autoregressive models”, Pattern Recognition 25 (1992) 173-188
[38]	. Serra, Image Analysis and Mathematical Morphology. London, U.K.: Academic, 1982
[39]	J.F. Silverman, D.B. Cooper, Bayesian clustering for un-supervised estimation of surface and texture models, IEEE Trans. Pattern Anal. Machine Intelligence 10 (1988) 482-495
[40]	J.H.Jaseema Yasmin1, D. Muhammad Noorul Mubarak2 , M.MohamedSathik 3, Border Detection of Noisy Skin Lesions by Improved Iterative Se]gmentation Algorithm using LOG Edge Detector ,  ICGST-GVIP Journal, Vol. 12 ( 2),  (2012) 56-64
[41]	J.L. Chen, A. Kundu, Unsupervised texture segmentation using multichannel decomposition and hidden Markov models, IEEE Trans. Image Processing, 4 (1995), 603-619
[42]	.Y. Hsiao, A.A. Sawchuk, “Unsupervised texture image segmentation using feature smoothing and probabilistic relaxation techniques”, Computer Vision Graphics Image Processing 48 (1989) 1-21
[43]	Jähne, B.: ‘Practical handbook on image processing for scientific and technical applications’ (CRC Press, 2004, 2nd Ed.), Ch. 15
[44]	Kekre.H.B,  SayleeGharge, "Texture Based Segmentation using Statistical Properties for Mammographic Images”, Int. Journal of Advanced Computer Science and Applications(IJACSA),  Vol. 1, No. 5, (2010) 102-107
[45]	Otsu, N.: ‘A threshold selection method from gray-level histograms’, IEEE Trans. Syst., Man, Cybern., 9, (1), (1979) 62–66. 
:10.22362/ijcert/2017/v4/i3/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I301.pdf
Refbacks : There are currently no refbacks

 

Secure Data Deduplication over Distributed Cloud Server Framework with Effective User Revocation and Load Balancing
Authors : D.Jayanarayana Reddy, M.Janardhan , U.Veeresh
Affiliations : Assistant Professor, Department of CSE, GPCET, Kurnool.
Abstract :

af

Nowadays Cloud Computing is an emerging Technology which leads various primitive services like SaaS, IaaS, and PaaS. Data deduplication mechanism is widely used to improve the bandwidth and storage space by removing duplicate copies of data from distributed cloud server.In Multi-owner manner data is stored and shared on distributed cloud server architecture, we have noticed some of the challenging issues, i.e., Users Privacy, Data Integrity, Load Balancing and Dynamic Ownership changes in attributes I,e User revocation Issues. To address the above challenges, we suggested a novel framework for Secure Data Deduplication over Distributed Cloud Server Framework with Effective User Revocation and Load Balancing Management. In our proposed framework, Block level hashing is pragmatic for every outsourced data and distributed into chunks and stored on distributed cloud servers, PoW protocol trappings Secured data deduplication and also provide an optimized solution for user revocation and load balancing issues , our projected approach is effective as the previous schemes while the added computational in the clouds is negligible.
Citation :

af

D.Jayanarayana Reddy et.al, “Secure Data Deduplication over Distributed Cloud Server Framework with Effective User Revocation and Load Balancing.”, International Journal Of Computer Engineering In Research Trends, 4(2):57-62, February-2017.
Keywords : Cloud Computing, Secure DataDeduplication, Load balancing, distributed cloud server, PoW Protocol.
References :

af

[1] M. Mulazzani, S. Schrittwieser, M. Leithner, and M. Huber, “Dark clouds on the horizon: using cloud storage as an attack vector and online slack space,” Proc. USENIX Conference on Security, 2011.
[2] Meister, D., Brinkmann, A.: Multi-level comparison of data deduplication in a backup scenario. In: SYSTOR ’09, New York, NY, USA, ACM (2009) 8:1–8:12 
[3] Mandagere, N., Zhou, P., Smith, M.A., Uttamchandani, S.: Demystifying data deduplication. In: Middleware ’08, New York, NY, USA, ACM (2008) 12–17 
[4] Aronovich, L., Asher, R., Bachmat, E., Bitner, H., Hirsch, M., Klein, S.T.: The design of a similarity based deduplication system. In: SYSTOR ’09. (2009) 6:1–6:14 
[5] Dutch, M., Freeman, L.: Understanding data de-duplication ratios. SNIA forum (2008) http://www.snia.org/sites/default/files/Understanding_Data_ Deduplication_Ratios-20080718.pdf. 
[6] Harnik, D., Margalit, O., Naor, D., Sotnikov, D., Vernik, G.: Estimation of deduplication ratios in large data sets. In: IEEE MSST ’12. (april 2012) 1 –11 
[7] Harnik, D., Pinkas, B., Shulman-Peleg, A.: Side channels in cloud services: Deduplication in cloud storage. Security Privacy, IEEE 8(6) (nov.-dec. 2010) 40 –47 
[8] Halevi, S., Harnik, D., Pinkas, B., Shulman-Peleg, A.: Proofs of ownership in remote storage systems. In: CCS ’11, New York, NY, USA, ACM (2011) 491–500 
[9] Di Pietro, R., Sorniotti, A.: Boosting efficiency and security in proof of ownership for deduplication. In: ASIACCS ’12, New York, NY, USA, ACM (2012) 81–82 
[10] Douceur, J.R., Adya, A., Bolosky, W.J., Simon, D., Theimer, M.: Reclaiming space from duplicate files in a serverless distributed file system. In: ICDCS ’02, Washington, DC, USA, IEEE Computer Society (2002) 617–632 
[11] Storer, M.W., Greenan, K., Long, D.D., Miller, E.L.: Secure data deduplication. In: StorageSS ’08, New York, NY, USA, ACM (2008) 1–10 
[12] Bellare, M., Keelveedhi, S., Ristenpart, T.: Message-locked encryption and secure deduplication. In: Advances in Cryptology–EUROCRYPT 2013. Springer 296–312 
[13]  Xu, J., Chang, E.C., Zhou, J.: Weak leakage-resilient client-side deduplication of encrypted data in cloud storage. In: 8th ACM SIGSAC symposium. 195–206 14. Bellare, M., Keelveedhi, S., Ristenpart, T.: DupLESS: server-aided encryption for deduplicated storage. In: 22nd USENIX conference on Security. (2013) 179–194
:10.22362/ijcert/2017/v4/i2/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I209.pdf
Refbacks : There are currently no refbacks
Analysis of Computational Time on DREAD Model
Authors : Didit Suprihanto, Retantyo Wardoyo,
Affiliations : Department of Electrical Engineering,Universitas Mulawarman, Kalimantan Timur, Indonesia, 75123
Abstract :

af

In identifying the risks, there are several factors needed to consider, such as the extent to which these risks are exploited and how much damage will occur. Considerations for choosing the most appropriate risk reduction that is fast and safe to perform a good calculation. Calculation complexity is one thing that should be considered in selecting an algorithm to be applied to the decision support system. This paper uses DREAD model by discussing the complexity testing and implement DREAD model into a program. Complexity is used to find out the computation time and its ratio completed with the result that the computation time of the final data is affected by the data addition. Therefore, the addition of data greatly affects to the computation time which is required the ratio of computing time, even though it has a bunch of similar data computation time and in fact these have different results that the ratio of computation time does not give any effect (stable). Computation ratio changes from the initial data group until the end of data group are not significantly compared with the value of computing time for each additional 100 tested data.
Citation :

af

Didit Suprihanto et.al, “Analysis of Computational Time on DREAD Model”, International Journal Of Computer Engineering In Research Trends, 4(2):53-56, February-2017.
Keywords : Complexity, Computing, DREAD
References :

af

[1] McEvoy, N., Whitcombe, A.,. Structured Risk Analysis. International conference on infrastructure security, vol. 2437, Bristol , October 1-3, 88-103. 2002
[2] Elky, S., An Introduction to Information System Risk Management. SANS Institute InfoSec Reading Room.copyright©SANS Institute. 2006.
[3] Hamdani., Wardoyo, R., The Complexity Calculation for Group Decision Making Using TOPSIS Algorithm. Advances of Science and Technology for Society AIP Conf. Proc. 1755, 070007-1–070007-7; doi: 10.1063/1.4958502 Published by AIP Publishing. 978-0-7354-1413-6: 2016.
[4] M. Ölmez and U. Lindemann, Procedia Comput. Sci. 28, 130 :2014.
[5] I. Wegener, Complexity Theory (Exploring the Limits of Efficient Algorithms) (Springer-Verlag, Dortmund), pp. 1–380: 2005
[6] Sipser, Michael, Introduction to the Theory of Computation – Second Edition, Thomson Course Technology, Massachusetts : 2006.
[7] Meier, J.D., Mackman, A., Vasireddy, S., Dunner,M., Escamilla, S., Murukan, A.,. Improving web application security: Threats and Countermeasures. Microsoft Corporation.2003..
:10.22362/ijcert/2017/v4/i2/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I208.pdf
Refbacks : There are currently no refbacks
K-Anonymous Privacy Preserving Technique for Participatory Sensing With Multimedia Data Over Cloud Computing
Authors : K.Lakshmi, J.Hemalatha, Farooq Basha
Affiliations : Asst.Prof, G.Pullaiah College of Engineering and Technology, Kurnool.
Abstract :

af

Nowadays distinctions of sensing facilities equipped with mobile wireless devices. Likewise, different service provider named participatory sensing system made available which gives outstanding life experience to users. Nevertheless, there are many challenges like privacy and multimedia data quality. There is no any earlier system that can resolve problems of confidentiality and quality, preserving participatory sensing system with multimedia data. Slicer is a K-anonymous privacy preservation scheme for participatory sensing with multimedia data over cloud framework. It combines data coding methods and message transfer strategies. To get the secure protection of user’s high data quality and also maintains privacy. Minimal Cost Transfer and Transfer On Meet-up, these are two data transfer strategies. For Minimal Cost Transfer, two parallel algorithms used. i.e., approximation algorithm and Heuristic algorithm. Slicer provides data quality with low communication.
Citation :

af

K.Lakshmi et.al, “K-Anonymous Privacy Preserving Technique for Participatory Sensing With Multimedia Data Over Cloud Computing”, International Journal Of Computer Engineering In Research Trends, 4(2):48-52, February-2017.
Keywords : Cloud mobile sensing, privacy preservation, anonymity, data aggregation
References :

af

1.	J. Burke, D. Estrin, M. Hansen, A. Parker, N.Ramanathan, S. Reddy, and M. B. Srivastava,“Participatory sensing,” presented at the First Workshop World-Sensor-Web 4th ACM Conf.Embedded Netw. Sen. Syst., Boulder, CO, USA, Oct.2006.
2.	”The world in 2013: ICT Facts and Figures,” International Telecommunication Union. [Online]. Available: http://www.itu.int,2013. 
3.	 R. K. Ganti, N. Pham, H. Ahmadi, S. Nangia, and T. F.Abdelzaher, “GreenGPS: A participatory sensing fuelefficient maps application,” presented at the 8th Int.Conf. Mobile Syst., Appl. Serv., San Francisco, CA,USA, Jun. 2010.  
4.	 X. O. Wang, W. Cheng, P. Mohapatra, and T. Abdelzaher,”Adsense: Anonymous reputation and trust in participatory sensing,” presented at the 32nd IEEE Int. Conf. Comput. Commun., Turin, Italy, Apr. 2013.
5.	E. D. Cristofaro and C. Soriente,”Participatory privacy: Enabling privacy in participatory sensing,” IEEE Netw., vol. 27, no. 1, pp. 3236, Jan./Feb. 2013.
6.	R. Chen, I. E. Akkus, and P. Francis, ”SplitX: High-performance private analytics,” presented at the ACM Special Interest Group Data Commun., Hong Kong, China, Aug. 2013.
7.	 N. Xia, H. H. Song, Y. Liao, M. Iliofotou, A. Nucci, Z.-L. Zhang, and A. Kuzmanovic,”Mosaic: Quantifying privacy leakage in mobile networks,” presented at the ACM Special Interest Group on Data Commun., Hong Kong, China, Aug. 2013.
8.	S. Han, V. Liu, Q. Pu, S. Peter, T. Anderson, A. Krishnamurthy,and D. Wetherall, ”Expressive privacy control with pseudonyms”presented at the ACM Special Interest Group Data Commun., Hong Kong, China, Aug. 2013.
9.	N. Kumar, N. Chilamkurti, and J. J. Rodrigues,”Learning automatabasedopportunistic data aggregation and forwarding scheme for alert generation in vehicular ad hoc networks,”Comput. Commun., vol. 39, pp. 2232, 2014.
10.	N. Kumar, N. Chilamkurti, and J. J. Rodrigues,”Privacy-aware message exchanges for HumaNets,”Comput. Commun., vol. 39, pp. 2232, 2014.

11.	Participatory Sensing: Applications and Architecture Deborah Estrin University of California, Los Angeles  : http://www.cs.cornell.edu/~destrin/resources/conferences/2010-Estrin-participatory-sensing-mobisys.pdf

:10.22362/ijcert/2017/v4/i2/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I207.pdf
Refbacks : There are currently no refbacks
Music Genre Classification Using MFCC, K-NN and SVM Classifier
Authors : Nilesh M. Patil, Dr. Milind U. Nemade,
Affiliations : Ph.D Research Scholar1, Pacific Academy of Higher Education and Research University, Udaipur, India.
Abstract :

af

The audio corpus available today on Internet and Digital Libraries is increasing rapidly in huge volume. We need to properly index them if we want to have access to these audio data. The search engines available in market also find it challenging to classify and retrieve the audio files relevant to the user’s interest. In this paper, we describe an automated classification system model for music genres. We firstly found good feature for each music genre. To obtain feature vectors for the classifiers from the GTZAN genre dataset, features like MFCC vector, chroma frequencies, spectral roll-off, spectral centroid, zero-crossing rate were used. Different classifiers were trained and used to classify, each yielding varying degrees of accuracy in prediction.
Citation :

af

Nilesh M. Patil et.al, “Music Genre Classification Using MFCC, K-NN and SVM Classifier”, International Journal Of Computer Engineering In Research Trends, 4(2):43-47, February-2017.
Keywords : Music, MFCC, K-NN, SVM, GTZAN dataset.
References :

af

[1]	G. Tzanetakis, P. Cook, “Musical genre classification of audio signals”, IEEE Transactions on Speech and Audio Processing, Vol. 10, Issue 5, July 2002.
[2]	Chandsheng Xu, Mc Maddage, Xi Shao, Fang Cao, and Qi Tan, “Musical genre classification using support vector machines”, IEEE Proceedings of International Conference of Acoustics, Speech, and Signal Processing, Vol. 5, pp. V-429-32, 2003.
[3]	N. Scaringella, G. Zoia, and D. Mlynek, “Automatic genre classification of music content: a survey”, IEEE Signal Processing Magazine, Vol. 23, Issue 2, pp. 133–141, 2006.
[4]	Jan Wülfing and Martin Riedmiller, “Unsupervised learning of local features for music classification” ISMIR, pp. 139–144, 2012.
[5]	Sox.sourceforge.net. Sox - sound exchange— homepage, 2015.
[6]	http://marsyas.info/downloads/datasets.html
:10.22362/ijcert/2017/v4/i2/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I206.pdf
Refbacks : There are currently no refbacks
Application of Computer in Production Planning and Control for SME’s
Authors : Dr Porag Kalita, ,
Affiliations : Head: Automobile Engineering Department, Govt. of Assam,Vocational Education (+2), M R S Higher Secondary School, Titabor, Assam.
Abstract :

af

The success of any enterprise largely depends upon its planning. Without planning become random and results are meaningless and no enterprises can avail success to its maximum satisfaction. Therefore, computerized planning for SME’s, paper work the clerks in the department must bring out every day on regular basis to bring interrelationship and ensure coordination between different work centers. There is again an important necessity that these documents are prepared in time and the communication is fast enough to reach the receiver before it becomes state with change of situation and directly or indirectly , it will be help for zero defect programme for SME’s in terms of re-engineering process.
Citation :

af

Dr Porag Kalita, “Application of Computer in Production Planning and Control for SME’s”, International Journal Of Computer Engineering In Research Trends, 4(2):38-42, February-2017.
Keywords : Computerized planning, Re-Engineering Process, Zero Defect programme
References :

af

[1] Course materials in Post graduate Diploma in Business Management, New Delhi, 1993.
[2] Course materials, Executive Development programme, IIM Bangalore, 1995, course director Prof L Prasad.
[3] Course materials Management Development programme, XLRI, Jamshedpur and course director Prof Madan. 
[4] Course materials in Fellow Management Research Programme in Business Administration, MSPI, New Delhi, 1999.  
[5] Paper by Dr. Porag Kalita, UGC sponsored National in Nalbari commerce College Assam,
[6] Course material by National Council of Labours Management, Chennai.1993.
[7] Paper by Dr. Porag Kalita, NAAC sponsored national seminar, J B College, Assam, India
[8] Course materials in IIPM, Kolkata in workshop on Total Productive Maintenance, 1997.                                                        
:10.22362/ijcert/2016/v3/i12/xxxx [Under Process]
DOI Link : Not yet assigned
Download :
  V4I205.pdf
Refbacks : There are currently no refbacks
Performance Analysis of Existing Direction of Arrival Algorithms for Various Mobile Sources and Antenna Elements
Authors : Yashoda B.S, Dr. K.R. Nataraj,
Affiliations : Ph.D Research Scholar1 Jain University, Bangalore, India.
Abstract :

af

In today’s world the number of mobile users is increasing day by day with the limited capacity there is a need for intelligent techniques that can provide same QOS (Quality of Service) across mobile users. In this paper existing methods namely Bartlett Method, Maximum Likelihood and MUSIC (Multiple Signal Classification) Method are described and simulated for various combinations of antenna elements and mobile separation configurations.
Citation :

af

Yashoda B.S et.al, “Performance Analysis of Existing Direction of Arrival Algorithms for Various Mobile Sources and Antenna Elements”, International Journal Of Computer Engineering In Research Trends, 4(2):33-37, February-2017.
Keywords : MUSIC, QOS, DOA
References :

af

[1] P. Laxmikanth, Mr. L. Surendra, Dr. D. Venkata Ratnam, S. Susrutha babu, Suparshya babu “ Enhancing the performance of AOA  estimation  in wireless communication using the MUSIC algorithm” SPACES-2015, Dept of ECE, K L UNIVERSITY.

[2] AndyVesa,Arpad lozsa “Direction of Arrival estimation for uniform sensor arrays” Electronics and Telecommunications(ISETC),  9th International Symposium on Electronics and Telecommunications 2010.

[3] Wing-KinMa, Tsung-HanHseih, Chong-Yung Chi “DOA estimation of quasi-stationary signals via Khatri-Rao subspace”, 2009, IEEE International Conference on Accoustics,speech and signal processing.

 [4] Yue Ivan Wu, Gerald Pacaba Arada, Kainam Thomas Wong “Electromagnetic coupling matrix modeling and ESPRIT-based direction finding –A case study using a uniform linear array of identical dipoles” 2009, IEEE International Conference on Acoustics, speech and signal processing.

 [5] H. L. Van Trees, Optimum Array Processing – Part IV of Detection, Estimation and Modulation Theory. Wiley-Interscience, 2002.

[6] D. T. Vu, A. Renaux, R. Boyer, and S. Marcos, “Some results on the weiss–weinstein bound for conditional and unconditional signal models in array processing,” Elsevier Signal Processing, vol. 95, no. 0, pp. 126 – 148, 2014.

[7] A. Renaux, P. Forster, P. Larzabal, C. D. Richmond, and A. Nehorai,“A fresh look at the bayesian bounds of the weiss-weinstein family,”Signal Processing, IEEE Transactions on, vol. 56, no. 11, pp. 5334 – 5352, November 2008.


[8] P. Stoica and B. Ng, “On the cramer-rao bound under parametric constraints,” IEEE Signal Processing Letters, vol. 5, no. 7, pp. 177 – 179, July 1998.

[9] T. J. Moore Jr., “A theory of cram´er-rao bounds for constrained parametric model,” Ph.D. dissertation, University of Maryland, College Park,Department of Mathematics, College Park, Maryland, USA, 2010.

[10] Y.-H. Li and P.-C. Yeh, “An interpretation of the moore-penrose generalized inverse of a singular fisher information matrix,” IEEE Transactions on Signal Processing, vol. 60, no. 10, pp. 5532 – 5536, October 2012.

[11] F. R¨omer and M. Haardt, “Deterministic cram´er-rao bounds for strict sense non-circular sources,” in International ITG/IEEE Workshop on Smart Antennas (WSA), February 2007.

[12] D. Schulz and R. S. Thom¨a, “Search-based MUSIC techniques for2D DoA estimation using EADF and real antenna arrays,” in 17th International ITG Workshop on Smart Antennas 2013 (WSA 2013), Stuttgart, Germany, 03 2013.

[13] M. Landmann, “Limitations of experimental channel characterisation,”Ph.D. dissertation, Ilmenau University of Technology, Electronic Measurement Research Laboratory, Ilmenau, Germany, 2007.

[14] M. Landmann, M. K¨aske, and R. Thom¨a, “Impact of incomplete and inaccurate data models on high resolution parameter estimation in multidimensional channel sounding,” IEEE Transactions on Antennas and Propagation, vol. 60, no. 2, pp. 557 – 573, February 2012.

[15] M. Landmann, A. Richter, and R. Thom¨a, “DoA resolution limits in MIMO channel sounding,” in IEEE Antennas and Propagation Society International Symposium, vol. 2, June 2004, pp. 1708 – 1711.

[16] Y. Tian and Y. Takane, “More on generalized inverses of partitioned matrices with banachiewicz–schur forms,” Linear Algebra and its Applications,vol. 7430, no. 5–6, pp. 1641 – 1655, 2009.

[17] Foutz, Jeffrey, Andreas Spanias, and Mahesh K. Banavar. ”Narrowbanddirection of arrival estimation for antenna arrays.” Synthesis Lectures on Antennas 3.1 (2008): 1-76.

 [18] Lau, C.K.E.; Adve, R.S.; Sarkar, T.K., ”Combined CDMA and matrix pencil direction of arrival estimation,” Vehicular Technology Conference, 2002. Proceedings. VTC 2002-Fall. 2002 IEEE 56th , vol.1, no.,pp.496,499 vol.1, 2002.

[19] Marot, J.; Fossati, C.; Bourennane, S., ”Fast subspace-based source localization methods,” Sensor Array and Multichannel Signal Processing Workshop, 2008. SAM 2008. 5th IEEE , vol., no., pp.203,206, 21-23 July 2008.
[20] Khmou, Y.; Safi, S., ”DOA estimation with fourth order propagator,”Multimedia Computing and Systems (ICMCS), 2014 International Conference on , vol., no., pp.1295,1300, 14-16 April 2014.

:10.22362/ijcert/2016/v3/i12/xxxx [Under Process]
DOI Link : Not yet assigned
Download :
  V4I204.pdf
Refbacks : There are currently no refbacks
Designing siRNA for Silencing Polo-Like Kinase 1 (Plk1) Gene of Prostate Cancer
Authors : JAYAPRAKASH. P, SIVAKUMARI. K, ASHOK. K AND RAJESH. S
Affiliations : PG AND RESEARCH DEPARTMENT OF ZOOLOGY, PRESIDENCY COLLEGE, CHENNAI- 600 005, TAMIL NADU, INDIA
Abstract :

af

Prostate cancer is the most commonly occurring cancer in American men, next to skin cancer. Existing treatment options and surgical intervention are unable to manage this cancer effectively. Therefore, continuing efforts are ongoing to establish a novel mechanism based targets and strategies for its management. PLK1 plays a key role in the mitotic entry of proliferating cells and regulates many aspects of mitosis which are necessary for successful cytokinesis. PLK1 is overexpressed in many tumour types with aberrant elevation frequently constituting a prognostic indicator of poor disease outcome and our study indicate that PLK1 could be an excellent target for the treatment as well as chemoprevention of prostate cancer.
Citation :

af

Jayaprakash. P et.al, “Designing siRNA for Silencing Polo-Like Kinase 1 (Plk1) Gene of Prostate Cancer”, International Journal Of Computer Engineering In Research Trends, 4(2):25-32, February-2017.
Keywords : Prostate cancer, PLK1 gene and siRNA
References :

af

1)	Landis, SH., Murray, T., Bolden, S. and Wing, P.A., (1998). Cancer statistics, 1998. CA. Cancer J. Clin. 48: 6-29.
2)	Jemal, A., Tiwari, R.C., Murray, T., Ghafoor, A., Samuels, A., Ward, E., Feuer, E. J. and Thun, M. J. (2004). Cancer statistics. CA. Cancer J. Clin. 54: 8-29.
3)	Reagan-Shaw, S. and Ahmad, N., (2005). Silencing of polo-like kinase (Plk) 1 via siRNA causes induction of apoptosis and impairment of mitosis machinery in human prostate cancer cells: implications for the treatment of prostate cancer. FASEB. J. 19: 611-613.
4)	Talcott, J.A., Rieker, P., Clark, J.A., Propert, K.J., Weeks, J.C., Beard, C.J., Wishnow, K.I., Kaplan, I., Loughlin, K.R., Richie, J.P. and Kantoff, P.W. (1998). Patient-reported symptoms after primary therapy for early prostate cancer: Results of a prospective cohort study. J. Clin. Oncol. 16: 275-283.
5)	Quinn, M. and Babb, P. (2002). Patterns and trends in prostate cancer incidence, survival, prevalence and mortality. Part I: International comparisons. BJU. Int. 90: 162-164.
6)	Herbert, J.R., Ghumare, S.S. and Gupta, P.C. (2006). Stage at diagnosis and relative differences in breast and prostrate cancer incidence in India: Comparison with the United States. Asian. Pac. J. Cancer. Prev. 7: 547-555.
7)	Daskivich, T.J. and Oh, W.K. (2006). Failure of gonadotropin-releasing hormone agonists with and without sterile abscess formation at depot sites: insight into mechanisms? Urology 67: 15-17.
8)	Gallagher, E. and Gapstur, R. (2006). Hormone-refractory prostrate cancer : A shifting paradigm in treatment. Clin. J. Oncol. Nurs. 10: 233-240.
9)	Golsteyn, R.M., Schultz, S.J., Bartek, J., Ziemiecki, A., Ried, T. and Nigg, E.A. (1994). Cell cycle analysis and chromosomal localization of human Plk1, a putative homologue of the mitotic kinases Drosophila polo and Saccharomyces cerevisiae Cdc5. J. Cell Sci. 107: 1509-1517.
10)	Glover, D.M., Hagan, I.M. and Tavares, A.A. (1998). Polo-like kinases: A team that plays throughout mitosis. Genes Dev. 12: 3777-3787.
11)	Donaldson, M.M., Tavares, A.A., Ohkura, H., Deak, P. and Glover, D.M., (2001b). Metaphase arrest with centromere separation in polo mutants of Drosophila. J. Cell Biol. 153: 663-676.
12)	Lane, H.A. and Nigg, E.A. (1996). Antibody microinjection reveals an essential role for human polo-like kinase 1 (Plk1) in the functional maturation of mitotic centrosomes. J. Cell Biol. 135(6 Pt 2): 1701-1713.
13)	Alexandru, G., Uhlmann, F., Mechtler, K., Poupart, M. A. and Nasmyth, K. (2001). Phosphorylation of the cohesin subunit Scc1 by Polo/Cdc5 kinase regulates sister chromatid separation in yeast. Cell. 105:  459-472.
14)	Sumara, I., Vorlaufer, E., Stukenberg, P.T., Kelm, O., Redemann, N., Nigg, E.A. and Peters, J.M. (2002). The dissociation of cohesin from chromosomes in prophase is regulated by polo-like kinase. Mol. Cell 9: 515-525.
15)	Lansing,T.J., McConnell, R.T., Duckett, D.R., Spehar, G.M., Knick, V.B., Hassler, D.F., Noro, N., Furuta, M., Emmitte, K.A. and Gilmer, T.M. (2007). In vitro biological activity of a novel small-molecule inhibitor of polo-like kinase 1. Mol. Cancer Ther.  6: 450-459.
16)	van Vugt, M.A., Bras, A. and Medema, R.H. (2004a). Polo-like kinase-1 controls recovery from a G2 DNA damage-induced arrest in mammalian cells. Mol. Cell. 15: 799-811.
17)	van Vugt, M.A., van de Weerdt, B.C., Vader, G., Janssen, H., Calafat, J., Klompmaker, R., Wolthuis, R.M. and Medema, R.H. (2004b). Polo-like kinase-1 is required for bipolar spindle formation but is dispensable for anaphase promoting complex/Cdc20 activation and initiation of cytokinesis. J. Biol. Chem. 279: 36841-36854.
18)	McInnes, C., Mezna, M. and Fischer, P.M. (2005). Progress in the discoveryof polo-like kinase inhibitors. Curr. Top. Med. Chem. 5: 181-197. 
19)	McInnes, C., Mazumdar, A., Mezna, M., Meades, C., Midgley, C., Scaerou, F., Carpenter, L., Mackenzie, M., Taylor, P. and Walkinshaw, M. (2006). Inhibitors of Polo-like kinase reveal roles in spindle-pole maintenance. Nat. Chem. Biol. 2(11): 608-617.
20)	Seong, Y.S., Kamijo, K., Lee, J.S., Fernandez, E., Kuriyama, R., Miki, T. and Lee, K.S. (2002). A spindle checkpoint arrest and a cytokinesis failure by the dominant-negative polo-box domain of Plk1 in U-2 OS cells. J. Biol. Chem. 277(35): 32282-32293.
21)	Leung, G.C., Hudson, J.W., Kozarova, A., Davidson, A., Dennis, J.W. and Sicheri, F. (2002). The Sak polo-box comprises a structural domain sufficient for mitotic subcellular localization. Nat. Struct. Biol. 9: 719-724.
22)	Golsteyn, R.M., Mundt, K.E., Fry, A.M. and Nigg, E.A. (1995). Cell cycle regulation of the activity and subcellular localization of Plk1, a human protein kinase implicated in mitotic spindle function. J. Cell Biol. 129(6): 1617-1628.
23)	Hamanaka, R., Smith, M.R., O'Connor, P.M., Maloid, S., Mihalic, K., Spivak, J.L., Longo, D.L. and Ferris, D.K. (1995). Polo-like kinase is a cell cycle-regulated kinase activated during mitosis. J. Biol. Chem. 270(36): 21086-21091.
24)	Hamanaka, R., Maloid, S., Smith, M.R., O'Connell, C.D., Longo, D.L. Ferris, D.K. (1994). Cloning and characterization of human and murine homologues of the Drosophila polo serine-threonine kinase. Cell. Growth. Differ. 5(3): 249-257.
25)	Holtrich, U., Wolf, G., Brauninger, A., Karn, T., Bohme, B., Rubsamen-Waigmann, H. and Strebhardt, K. (1994). Induction and down-regulation of PLK, a human serine/threonine kinase expressed in proliferating cells and tumors. Proc. Natl. Acad. Sci. USA. 91: 1736- 1740.
26)	Smith, M.R., Wilson, M.L. and Hamanaka, R. (1997). Malignant transformation of mammalian cells initiated by constitutive expression of the polo-like kinase. Biochem. Biophys. Res. Commun. 234: 397-405.
27)	Zhang, C., Pei, J., Kumar, D., Sakabe, I., Boudreau, H.E., Gokhale, P.C. and Kasid, U.N. (2007). Antisense oligonucleotides: target validation and development of systemically delivered therapeutic nanoparticles. Methods. Mol. Biol. 361:163-185.
28)	Spänkuch, B., Steinhauser, I., Wartlick, H., Kurunci-Csacsko, E., Strebhardt, K.I., Langer, K. (2008). Downregulation of Plk1 expression by receptor mediated uptake of antisense oligonucleotide-loaded nanoparticles. Neoplasia 10(3): 223-234.
29)	Sui, G., Soohoo, C., Affar, B., Gay, F., Shi, Y. and Forrester, W.C. (2002). A DNA vector-based RNAi technology to suppress gene expression in mammalian cells. Proc. Natl. Acad. Sci. USA. 99: 5515-5520. 
:10.22362/ijcert/2017/v4/i2/xxxx [UNDER PROCESS]
DOI Link : Not yet assigned
Download :
  V4I203.pdf
Refbacks : There are currently no refbacks
An Enforcement of Guaranteed Client Level Defensive Mechanism in Public Cloud Services
Authors : Prof. R. Poorvadevi, S.Keerthana, V.S. Ghethalaxmipriya, K. Venkatasailokesh
Affiliations : Assistant Professor1, Department of computer science and engineering, SCSVMV University, Kanchipuram, India
Abstract :

af

In the current era of cloud computing, the distinct enterprise information technology (IT) and business decision makers analyze the security implications of cloud computing to their business for the benefit of improving the business agility. Cloud has been playing a major role in the various multidisciplinary domains. Recent survey stated that 70% research issues are focusing on cloud security domain. Although, cloud is providing the huge amount of services to the users, still the client end level security problem is not completely eradicated. So, there is a major focus on improving and finding the solution for cloud security to know the various potential risks in the customer end. Several large cloud vendors have signaled practical implementations of the security mechanism, primarily to protect the cloud infrastructure from insider threats and advanced persistent threats. So, the proposed model brings the solution for giving the guaranteed type of cloud services in an attack free manner to the web clients. This could be achieved through the technique of client level guaranteed security system defensive approach. This mechanism will majorly operates on how to protect the user authentication procedures, security,policies, security layered approach from the client level transactions. The proposed work will be simulated on the cloud sim tool, through which end-users will obtain the better security solution in the public cloud environment.
Citation :

af

Prof. R. Poorvadevi et.al, “An Enforcement of Guaranteed Client Level Defensive Mechanism in Public Cloud Services”, International Journal Of Computer Engineering In Research Trends, 4(1):20-24, February-2017.
Keywords : Cloud vendor, public cloud security, cloud service provider, cloud customer, defensive model, cloud sim, data centre, and virtual machine
References :

af

1)	Miyoung jang; Min Yoon; Jae-Woo chang, paper entitled as “A Privacy-aware query authentication index for database outsourcing” IEEE conference publications 2014. 

2)	Wenjun Lu ; Google, Mountain View, CA, USA; Varna, A.L. ; Min Wu,”Confidentiality-Preserving Image Search: A Comparative Study between Homomorphic Encryption and Distance-Preserving Randomization”, IEEE transactions on volume 2 – 2014.

3)	Velciu, M.-A. ; Comput. Sci. Dept, Mil. Tech. Acad., Bucharest, Romania; Patrascu, A. ; Patriciu, V.-V, “Bio-cryptographic authentication in cloud storage sharing”, Applied Computational Intelligence and Informatics (SACI), 2014 IEEE 9th International Symposium on – 2014.

4)	Poornima, B. ; Rajendran, T, “Improving Cloud Security by Enhanced HASBE Using Hybrid Encryption Scheme”, Computing and Communication Technologies (WCCCT), 2014 World Congress on march-14.

5)	Durrani, A, “Analysis and prevention of vulnerabilities in cloud applications”, Information Assurance and Cyber Security (CIACS), 2014 IEEE Conference on 2014.

6)	Chang Liu ; Fac. of Eng. & IT, Univ. of Tech., Sydney, NSW, Australia and  more authors “Authorized Public Auditing of Dynamic Big Data Storage on Cloud with Efficient Verifiable Fine-Grained Updates Parallel and Distributed Systems”, IEEE Transactions on  cloud computing - 2014.

7)	Hussain, M. ; Dept. of Interdiscipl. Studies, Zayed Univ. Dubai, “Effective Third Party Auditing in Cloud Computing”, Advanced Information Networking and Applications Workshops (WAINA), 28th International Conference on  13-16 May 2014.

8)	Vikas Saxena, et al “Implementation of a secure genome sequence search platform on public cloud-leveraging open source solutions”, Journal of Cloud Computing: Advances, Systems and Applications 2014.
:10.22362/ijcert/2017/v4/i2/xxxx
DOI Link : Not yet assigned
Download :
  V4I202.pdf
Refbacks : There are currently no refbacks
Survey on Different Applications of Image Processing
Authors : Ajin P Thomas, Sruthi P.S, Jerry Rachel Jacob ,Vandana V Nair, Reeba R
Affiliations : Sree Buddha College Of Engineering, Alappuzha ,India
Abstract :

af

In Imaging Science, Image processing is processing of images using mathematical operations by using any form of signal processing for which the input is an image, a series of images, or a video, such as a photograph or video frame; the output of image processing may be either an image or a set of characteristics or parameters related to the image. These image processing techniques can be used to perform applications in real-world. This image processing technique helps to improve various aspects related in the real- world. Some of these applications are in the field of health science, security assurance and augmented reality and also this can be applied in real-time applications. All these applications are performed by using image processing as its basic platform.
Citation :

af

Ajin P Thomas et.al, “Survey on Different Applications of Image Processing”, International Journal Of Computer Engineering In Research Trends, 4(1):13-19, February-2017.
Keywords : Image Processing
References :

af

[1] Dalton, John, ―Extraordinary Facts Relating to the Vision of Colour‖, London: Cadel and Davins,. 1798, pp. 28–45. 
[2] G. M. Machodo, ―A Physiologically-based Model for Simulation of Color Vision Deficiency‖ IEEE Transaction on Visual and Computer Graphics Vol. 15. No 6. 2009, pp. 1291-1298 
 [3] G. M. Machodo, Manuel. M. Oliveira.―A Model for Simulation of Color Vision Deficiency and A Color Contrast Enhancement Technique for Dichromats‖, pp. 74, 2010
[4] V.Kanhangad, A.Kumar,and D.Zhang, "Contactless and pose invariant biometric identification using hand surface,"IEEE Trans, Image Process,, vol. 6, no. 3, pp. 1415-1424, May 2011
[5] The Hong Kong Polytechnic University (2015), Implementation Codes for 3D Palmprint Matching.
[6] W.L Li, L. Zhang, and D. Zhang, "Three dimensional palmprint recognition,"in Proc, IEEE Int.Conf.Syst., Main Cybern..,  Oct 2009, pp. 4847-4852.
[7] P. Rajavel, “Image Dependent Brightness Preserving Histogram Equalization”, IEEE Transactions on Consumer Electronics, Vol. 56, No. 2, May 2010
[8]. Yeong-Taeg Kim, “Contrast enhancement using brightness preserving bi-histogram equalization,” IEEE Transactions on Consumer Electronics, vol. 43, no. 1, pp. 1-8, Feb. 1997.
[9]. Soong-Der Chen and Abd. Rahman Ramli, “Contrast enhancement using recursive mean-separate histogram equalization for scalable brightness preservation,” IEEE Transactions on Consumer Electronics, vol. 49, no. 4, pp. 1301- 1309, Nov. 2003.
[10] Ronald Azuma, Yohan Baillot, Reinhold Behringer, "Recent Advances in Augmented Reality" , Computers & Graphics, November 2001.
 [11] Avery, B., Thomas, B., and Piekarski, W, "User Evaluation of See-Through Vision for Mobile Outdoor Augmented Reality.", In 7th Int'l Symposium on Mixed and Augmented Reality. pp 69-72. Cambridge, UK. Sep 2008. 
[12] Feng Zhou ; Duh,H.B.-L. ; Billinghurst, M. "Trends in augmented reality tracking, interaction and display" A review of ten years of ISMAR  Mixed and Augmented  Reality 2008. ISMAR 2008. 7th IEEE/ACM International. 
:10.22362/ijcert/2017/v4/i2/xxxx
DOI Link : Not yet assigned
Download :
  V4I201.pdf
Refbacks : There are currently no refbacks

 

Optimized control of Induction Heating System
Authors : Mrs. Asawari Dudwadkar , Dr. (Mrs.) Sayle Gha,
Affiliations : JJT University, Rajasthan, Asst. Prof., VESIT,Mumbai, India
Abstract :

af

In this paper a simple power and frequency control scheme is proposed for high power/high frequency Induction heating for Typical Heavy Industrial Applications like Induction Welding & Annealing which require operating on 100 kW / 100 kHz. The Proposed PI controller controls the load parameter values of R and L and thereby controls the resonance frequency of the whole model. The control scheme has the advantages of not only wide power regulation range but also ease of control output power. Also, it can achieve the stable and efficient Zero-Voltage-Switching in whole load range. The proposed method is described in detail and its validity is verified through simulink model. The model achieves proper power control for load ranging from 80 kW to 100kw.
Citation :

af

Mrs. Asawari Dudwadkar , Dr. (Mrs.) Sayle Gharge, “Optimized control of Induction Heating System”, International Journal Of Computer Engineering In Research Trends, 4(1):67-71, January-2017. [InnoSpace-2017:Special Edition]
Keywords : Induction heating, power control, PI controller
References :

af

[1] N. Mohan, T.M.Undeland, W.P.Robbins, “Power Electronic-Converters, Applications and Design", Second edition, John Wiley & Sons Inc., 1995.

[2]   O. Lucía, O. Jiménez, L. A. Barragán, I. Urriza, J. M
Burdío and D. Navarro, "System-on-programmable-           chip-based versatile modulation architecture applied to domestic induction heating," Industrial electronics, 2009. IECON '09. 35th Annual Conference of IEEE, Porto, 2009, pp. 2880-2885

[3] N. S. Bayindir, O. Kukrer and M. Yakup, "DSP-based PLL-controlled 50-100 kHz 20 kW high-frequency induction heating system for surface hardening and  welding applications," in IEE Proceedings – Electric Power Applications, vol. 150, no. 3, pp. 365-371,May 2003.

[4] J. Martis and P. Vorel, "Apparatus for induction heating 2.5 kW using a series resonant circuit," Mechatronics - Mechatronika (ME), 2014 16th International Conference on, Brno, 2014, pp. 130-135.

[5] T. Mishima, C. Takami and M. Nakaoka, "A New          Current Phasor-Controlled ZVS Twin Half-Bridge High-Frequency Resonant Inverter for Induction  Heating," in IEEE Transactions on Industrial Electronics, vol. 61, no. 5, pp. 2531-2545,May2014.

[6]   A. Amrhein and J. S. J. Lai, "A transformer-coupled,          Series-resonant topology for the induction heating of          aluminum cookware," 2015 9th International          Conference on Power Electronics and ECCE Asia          (ICPE-ECCE Asia), Seoul, 2015, pp. 1234-1239.

[7]   B. Saha and R. Y. Kim, "High Power Density Series          Resonant Inverter Using an Auxiliary Switched           Capacitor Cell for Induction Heating Applications,” In IEEE Transactions on Power Electronics, vol. 29   No. 4, pp. 1909-1918,April2014.

 [8] V. Esteveet al., "Improving the Reliability of             Series Resonant Inverters for Induction Heating             Applications," in IEEE Transactions on Industrial             Electronics, vol. 61, no. 5, pp. 2564-2572, May 2014. 
:-NA-
DOI Link : NA
Download :
  20170122.pdf
Refbacks : There are currently no refbacks
Bike Rider’s Safety Measures Using Helmet as a Key
Authors : Sanjeev Sahu, Lokesh Yadav, K Diwakar, Vibhor William
Affiliations : Mechatronics Engineering Department Chhatrapati Shivaji Institute of Technology Durg-491001, Chhattisgarh, India
Abstract :

af

Background/Objectives: The basic idea of the project is to make the helmet so smart that without wearing it the driver won’t be able to start the bike, so that it can ensure the safety of the riders. The main purpose of the project is to encourage wearing helmet. Method: The system design will be such that without wearing the helmet the rider cannot start two wheelers. The helmet will be connected to vehicle key ignition systems which will be electronically controlled. The smart helmet will be having micro switches fitted inside it, which will act as our switch for on/off ignition. It consist of a RF transmitter and an RF receiver system, the bike will not get started without wearing helmet by the driver, as the rider wear helmet an RF signals radiate from the transmitter and once these RF signals get sensed by the receiver placed in the ignition switch on the bike, bike will get started. Findings: People prefer motorcycles over the car as it is much cheaper to run, easier to repair, easier to park and flexible in traffic. In India more than 37 million people are using two wheelers. Since usage is high accident percentage of two wheelers are also high compared to four wheelers. Motorcycles have a higher rate of fatal accidents than trucks and buses. According to Ministry of Road Transport and Highways, Government of India there are around 1,44,391 bike accidents occurred in 2015 due to which 1,35,343 were injured and 36,803 were killed. Fatal injuries to the brain are an important reason behind deaths due to the road accidents. Therefore, a person riding a two wheeler must wear a helmet in order to protect his skull. Studies show that usage of helmet can save accident death by 30 to 40 percent. The risk of death is 2.5 times more among riders not wearing a helmet compared with those wearing a helmet. Riders wearing a helmet have a greater probability of survival during an accident. This project aims for accident avoidance, safety and security of bike riders. Applications: This can be used to minimize the accidents and casualties during riding can be used in broadcasting a message among the youth about the road safety and also a number of cases of violating traffic rules can be reduced.
Citation :

af

Sanjeev Sahu, Lokesh Yadav, K Diwakar, Vibhor William, “Bike Rider’s Safety Measures Using Helmet as a Key”, International Journal Of Computer Engineering In Research Trends, 4(1):61-66, January-2017. [InnoSpace-2017:Special Edition]
Keywords : Smart Helmet, RF Module, Encoder/Decoder IC, Bike Authentication, Micro Switches, Keyless Bike, Relay Operation, Motor Driver IC, Bike Theft Prevention.
References :

af

1.	Annual Report on ‘Road Accidents in India – 2015’, Transport Research Wing, Ministry of Road Transport and Highways, Government of India, New Delhi.

2.	Status Report on ‘Road Safety in India – 2015’, Transportation Research & Injury Prevention Programme (TRIPP), Indian Institute of Technology, New Delhi.

3.	Nitin Agarwal, Anshul Kumar Singh, Pushpendra Pratap Singh, Rajesh Sahani, Smart Helmet, International Journal of Engg. & Technology (IRJET) Vol. 2 Issue 2 ISSN (Online): 2395‐0056 (Print): 2395-0072 (May 2015).

4.	Manjesh N, Prof. 	Sudarshan Raju C H, Safety measures for two wheelers by Smart Helmet, International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 National Conference on Developments, Advances & Trends in Engineering Sciences (NCDATES), 09th & 10th January 2015.

5.	Amitava Das, Priti Das, Soumitra Goswami, Smart Helmet For Indian Bike Riders, Eleventh IRF International Conference, ISBN: 978-93-84209-47-6, 17th August 2014, Chennai, India.

6.	Ravi Nandu and Kuldeep Singh, Smart Helmet For Two-Wheelers, Advances in Automobile Engineering, ISSN: 2167-7670, Vol. 3 Issue 2, Department of Automobile Engineering, SRM University, Kattankulathur, Chennai, India.

7.	Manasi Penta, Monali Jadhav and Priyanka Girme, Bike Rider’s Safety Using Helmet, International Journal of Electrical Electronic Engineering and Telecommunications (IJEETC) ISSN: 2319-2518, Vol. 4, No. 2, Department of Electronics and Telecommunication, Dr. D Y Patil Technical Campus, Charoli (BK), Pune, India. 
:-NA-
DOI Link : NA
Download :
  20170114.pdf
Refbacks : There are currently no refbacks
Link quality based Ant based Routing Algorithm (LARA) in MANETs
Authors : C.V.Anchugam, Dr.K.Thangadurai,
Affiliations : Link quality based Ant based Routing Algorithm (LARA) in MANETs
Abstract :

af

Recently a new method is developed to handle the problem of routing in ad hoc network and overcomes the shortcomings of the classical methods; these methods are based on swarm intelligence inspired from biological swarms, such as ants in order to solve some complex problems such as finding food or optimizing route to food in real insect swarms. One of the most known routing algorithms for MANETs, as described Ant based Routing Algorithm (ARA) suffers from some limitations within the pheromone computing since it has not taken the necessary consideration to the characteristics of MANETs such as mobility and the medium constraint. Therefore, in our proposed enhancement to ARA called Link quality based ARA (LARA), it can be included the link quality in route selection and probability computing which have considerably improved the network performance and the system lifetime.
Citation :

af

C.V.Anchugam, Dr.K.Thangadurai, “Link quality based Ant based Routing Algorithm (LARA) in MANETs”, International Journal Of Computer Engineering In Research Trends, 4(1):52-60, January-2017. [InnoSpace-2017:Special Edition]
Keywords : MANETs, LARA, Routing, Link quality, Swarm Intelligence, Cross-layer.
References :

af

[1].	Al Agha K., Pujolle G., Vivier G., “Reseaux de mobiles et reseaux sans fil“, 2nd edition, Eyrolles, 2005. 
[2].	Basagni S., Chlamtac I., Syrotiuk V. R., Woodward B. A., “A Distance Routing Effect Algorithm for Mobility (DREAM)”, In Proceedings ACM/IEEE Mobicom, pages 76-84, October 1998.   
[3].	Camp, T., Boleng, J., Williams, B., Wilcox, L., Navidi, W.,  “Performance comparison of two location based routing protocols for ad hoc networks”, INFOCOM 2002, Twenty-First Annual joint conference of the IEEE Computer and Communications Societies, Proceedings, IEEE, Volume. 3, 2002,  pp. 1678 –168. 
[4].	Clausen T., Jacquet P., Viennot L., “Comparative Study of Routing Protocols for Mobile Ad hoc Networks”, Med-Hoc-Net’02, Sardegna, Italy, September 2002. 

[5].	Daniel Camara, Antonio Alfredo F. Loureiro, “A Novel Routing Algorithm for Hoc Networks”, Baltzer Journal of Telecommunications Systems, 18:1-3, Kluwer Academic Publishers, 2001, pp. 85-100.    
[6].	DiCaro G., Dorigo M., “Ant Colonies for Adaptive Routing in Packet-Switched Communications Networks”, Proceedings PPSN V - Fifth International Conference on Parallel Problem Solving from Nature, Amsterdam, Holland, September 27-30, 1998, pp. 673-682.    
[7].	Gerharz M.L, De Waal C., Frank M., Martini P., “Link Stability in Mobile Wireless Ad Hoc Networks”, Proceedings of the 27th Annual IEEE Conference on Local Computer Networks (LCN), Tampa, Florida, November 2002.  
[8].	Gunes M., Sorges U., Bouazisi I., “ARA - the Ant Colony Based routing Algorithm for MANETs”, Proceedings ICPP Workshop on Ad hoc Networks, Vancouver, Canada, 2002, pp. 7985.  
[9].	Heusse M., Snyers D., Guérin S., Kuntz P., "Adaptive agent-driven routing and load balancing in communication network", Proceedings ANTS'98,First International Workshop on Ant Colony Optimization, Brussels, Belgium, October 15-16, 1998.   
[10].	Iwata A., Chiang C.-C., Pei G., Gerla M., Chen T.-W., "Scalable Routing Strategies for Ad Hoc Wireless Networks", IEEE Journal on Selected Areas in Communications, Special Issue on Ad-Hoc Networks, Aug. 1999, pp.1369-1379.   
[11].	Jacquet, Paul Muhlethaler, Amir Qayyum, Anis Laouiti, Laurent Viennot, Thomas Clausen, “Optimized Link State Routing Protocol”, Internet Draft, draft-ietf-manet-olsr-04.txt, work in progress, June 2001.   
[12].	Jagannathan Sarangapani, “Wireless Ad Hoc and Sensor Networks Protocols”, Performance, and Control”, Taylor & Francis Group, LLC, 2007. 
[13].	Jiang M., Li J., Tay Y. C., “Cluster Based Routing Protocol (CBRP)”, Functional Specification Internet Draft, draft-ietf-manet-cbrp.txt, work in progress, June 1999. 
[14].	Jinyang Li, John Janotti, Douglas S. J. De Coutu, David R. Karger, Robert Morris. “A Scalable Location Service for Geographic Ad Hoc Routing”, M.I.T. Laboratory for Computer Science.   
[15].	Johnson D., Maltz D., Y-C. Hu, Jetcheva J., “The Dynamic Source Routing Protocol for Mobile Ad Hoc Networks”, Internet Draft, draft-ietf-manet-dsr-09.txt, work in progress, April 2003. 
[16].	Ko Y.-B., V. N. H. “Location-Aided Routing in mobile Ad hoc networks”, In Proceeding ACM/IEEE Mobicom, October 1998, pp. 66-75. 
[17].	Mesut Gunes et. al, “ARA - the ant-colony based routing algorithm for MANETs”, In Stephan Olariu, Proceedings of the 2002 ICPP Workshop on Ad Hoc Networks (IWAHN 2002), IEEE Computer Society Press, August 2002, pp. 79-85. 
[18].	Navid Nikaein, Christian Bonnet, Neda Nikaein. “Hybrid Ad Hoc Routing Protocol – HARP”, proceeding of IST 2001: International Symposium on Telecommunications.  
[19].	Park V., Corson S., ”TORA (Temporally-Ordered Routing Algorithm routing protocol)”,  Internet Draft, draft-IETF-MANET-TORA-spec- 03.txt, work in progress, June 2001. 
[20].	Perkins C., Royer E., Das S., “Ad hoc On-demand Distance Vector (AODV) Routing”, Internet Draft, draft-ietf-manet-aodv-11.txt, work in progress, Aug 2002. 
[21].	Perkins C. E., Bhagwat P., “Highly Dynamic Destination-Sequenced Distance Vector (DSDV) for Mobile Computers”, Proceedings of the SIGCOMM 1994 Conference on Communications Architectures, Protocols and Applications, Aug 1994, pp 234-244.  
[22].	Siva Ram Nurthy C.,  Manoj B.S., “Ad hoc wireless networks Architectures and Protocols”, le Prentice Hall, 2004. 
[23].	Sridhar K. N., Lillykutty J., Rajeev S., “Performance Evaluation and Enhancement of Link Stability Based Routing for MANETs”, lst International Workshop on Mobile and Wireless Networking (MWN 2004), Montreal, Quebec, Canada, August 15, 2004.    
[24].	Tsu-Wei Chen, Mario Gerla, "Global State Routing: A New Routing Scheme for Ad hoc Wireless Networks", Proceedings IEEE ICC'98.   
[25].	White T., "Swarm intelligence and problem solving in telecommunications", Canadian Artificial Intelligence Magazine, Spring, 1997.    
[26].	White T., "Routing with swarm intelligence", Technical Report SCE-97-15, Systems and Computer Engineering Department, Carleton University, September, 1997.    
[27].	Zygmunt J. Haas, Marc R. Pearlman, Prince Samar, “The Bordercast Resolution Protocol (BRP)”, Internet Draft, draft- ietf-manet-zone-zrp-04.txt, work in progress, July 2002. 
:-NA-
DOI Link : NA
Download :
  20170108.pdf
Refbacks : There are currently no refbacks
A Comparative Study of Discovering Frequent Subgraphs – Approaches and Techniques
Authors : B.Senthilkumaran, Dr.K.Thangadurai,
Affiliations : P.G. and Research,Department of Computer Science, Government Arts College (Autonomous), Karur-05.
Abstract :

af

Graph mining is an important research vertical and recently the usage of graphs has become increasingly imperative in modeling problematic complex structures such as electrical circuits, chemical compounds, protein structures, bioinformatics, social networks, workflow diagrams, and XML documents. Plethora of graph mining algorithms has been developed and the primary objective of this paper is to present a detailed survey regarding the approaches and techniques employed to find the issues and complexities involved.
Citation :

af

B.Senthilkumaran, Dr.K.Thangadurai, “A Comparative Study of Discovering Frequent Subgraphs – Approaches and Techniques”, International Journal Of Computer Engineering In Research Trends, 4(1):41-45, January-2017. [InnoSpace-2017:Special Edition]
Keywords : Graph, Mining, complex structure, techniques, modelling
References :

af

1] Chen, M.S., Han,J.and Yu,P.S. 1996 Data mining – An overview from database perspective, IEEE Transaction on knowledge and data engineering 8 , 866-883
[2] Alm, E. and Arkin, A.P. 2003. Biological Networks, Current Opinion in Structural Biology 13(2), 193– 202.
[3] Nijssen, S. and Kok, J., Faster association rules for multiple relations. In IJCAI’01:  Seventeenth International Joint Conference on Artificial Intelligence, 2001, vol. 2, pp. 891–896.
[4] Chuntao Jiang, Frans Coenen and Michele Zito, A Survey of Frequent Sub-graph Mining Algorithms:The Knowledge Engineering Review, Vol. 00:0, 1–31.c 2004.
[5] A. Inokuchi, T.Washio, and H. Motoda. An apriori-based algorithm for mining frequent substructures from graph data. In PKDD’00.
[6] J. Huan, W.Wang, and J. Prins. Efficient mining of frequent subgraph in the presence of isomorphism. UNC computer science technique report TR03-021, 2003.  
[7] J. Huan, W. Wang, J. Prins, and J. Yang. Spin: Mining maximal frequent sub-graphs from graph databases. UNC Technical Report TR04-018, 2004.  
[8] M. Kuramochi and G. Karypis. Grew-a scalable frequent subgraph discovery algorithm. In ICDM, pages 439–442,2004.
[9] ZhaonianZou, Jianzhong Li, Hong Gao, and Shuo Zhang : Frequent Subgraph Patterns from Uncertain Graph Data. IEEE Transactions On Knowledge And Data Engineering, Vol. 22, No. 9, September 2010.
[10] L. T. Thomas, S. R. Valluri, and K. Karlapalem. Margin:Maximal frequent subgraph mining. Proc. 6th IEEE Int’l Conf. Data mining (ICDM ’06), pp. 1097-1101, 2006.
[11] Inokuchi, A., Washio, T., Nishimura, K. and Motoda, H. 2002. A Fast Algorithm for Mining Frequent Connected Subgraphs, Technical Report RT0448, IBM Research, Tokyo Research Laboratory, Japan.
[12] Huan, J., Wang, W. and Prins, J. 2003. Efficient Mining of Frequent Subgraph in the Presence of Isomorphism, In Proceedings of the 2003 International Conference on Data Mining, 549-552.

:-NA-
DOI Link : NA
Download :
  20170109.pdf
Refbacks : There are currently no refbacks
Detection and area calculation of brain tumour from MRI images using MATLAB
Authors : Suman Das, Nashra Nazim Siddiqui, Nehal Kriti and Surya Prakash Tamang
Affiliations : Sikkim Manipal Institute of Technology, Sikkim-737132, India
Abstract :

af

The main objective of our task is to recognize a tumour and its quantifications from a particular MRI scan of a brain image using digital image processing techniques. The motivation of our work is to provide an efficient algorithm for detecting the brain tumour and calculating its growth. This research describes the proposed strategy to detect & extraction of brain tumour from patient’s MRI scan images of the brain. This method incorporates with some noise removal functions, segmentation and morphological operations which are the basic concepts of image processing. Detection and extraction of tumour from MRI scan images of the brain is done by using MATLAB software.
Citation :

af

Suman Das, Nashra Nazim Siddiqui, Nehal Kriti, Surya Prakash Tamang, “Detection and area calculation of brain tumour from MRI images using MATLAB”, International Journal Of Computer Engineering In Research Trends, 4(1):37-40, January-2017. [InnoSpace-2017:Special Edition]
Keywords : MRI, Brain Tumour, digital image processing, segmentation, morphology, MATLAB.
References :

af

[1]	 Dou, W., Ruan, S., Chen, Y., Bloyet, D., and Constans, J. M. (2007), “A framework of fuzzy information fusion for segmentation of brain tumor tissues on MR images”, Image and Vision Computing, 25:164–171. 
[2]	 T.Logeswari and M.Karnan, “An Improved Implementation of Brain Tumor Detection Using Segmentation Based on Hierarchical Self Organizing Map”, International Journal of Computer Theory and Engineering, Vol. 2, No. 4, August, 2010,pp.1793-8201. 
[3]	 R. Rajeswari and P. Anandhakumar, “Segmentation and Identification of Brain Tumor MRI Image with Radix4 FFT Techniques”, European Journal of Scientific Research, Vol.52 No.1 (2011), pp.100-109.
[4]	 S.Murugavalli, V.Rajamani, “A high speed parallel fuzzy c-mean algorithm for brain tumor segmentation”, ”BIME Journal”, Vol no: 06, Issue(1), Dec.,2006.
[5]	 Oelze, M.L,Zachary, J.F. , O'Brien, W.D., Jr., Differentiation of tumor types in vivo by scatterer property estimates and parametric images using ultrasound backscatter , on page(s) :1014 - 1017 Vol.1, 5-8 Oct. 2003. 
[6]	 T. Logeswari and M. Karnan, An improved implementation of brain tumor detection using segmentation based on soft computing, Second International Conference on Communication Software and Networks, 2010. ICCSN‟10.Page(s): 147-151. 
[7]	Devos, A, Lukas, L.,Does the combination of magnetic resonance imaging and spectroscopic imaging improve the classification of brain tumours?? On Page(s): 407 – 410, Engineering in Medicine and Biology Society, 2004. IEMBS '04. 26th Annual International Conference of the IEEE, 1-5 Sept. 2004.
[8]	Mohammad Shajib Khadem, “MRI Brain image segmentation using graph cuts”, Master of Science Thesis in Communication Engineering, Department of Signals and Systems, Chalmers University Of Technology, Goteborg, Sweden, 2010. 

:-NA-
DOI Link : NA
Download :
  20170111.pdf
Refbacks : There are currently no refbacks
Design of a System to Import Common Information of an Applicant from a Centralized Database While Filling Online Recruitment Application Form
Authors : Govind Prasad Arya, Devendra Prasad,
Affiliations : Uttarakhand Technical University, Dehradun, Assistant Professor in Computer Science & Engineering Department, Shivalik College of Engineering, Dehradun, India
Abstract :

af

In the past recruitment application forms were filled on papers by the candidates and then the filled forms were sent to the recruitment organization through postal services. But in current scenario most of the recruitment organizations are providing the facility of filling application forms online to the candidates. The candidate fills various application forms on regular basis due to higher degree of unemployment. It takes quite long to fill an application form as so many information like name, father’s name, mother’s name, date of birth, gender, addresses, qualification details, work experience has to be filled by candidate every time while filling the application forms of each recruitment organization. Sometimes the candidate has to fill the same information multiple times due to improper internet connectivity. It is also difficult to fill an application form using mobile because of the complex application interface. The applicants who have good computer knowledge may be comfortable with the filling of such complex forms online but it is very tedious task for a candidate having little knowledge of computer. In this research paper we propose a system that will import the common information of an applicant from a centralized database while filling recruitment application forms of various organizations. It will minimize the overheads of filling online application form. The applicants will be able to fill application form by a single click on import button available on the GUI interface of an online application form. The applicants who have basic knowledge of computer system will also be able to fill their recruitment application forms using proposed system. Methods/Statistical analysis: We feel the problem personally while filling online recruitment application forms. Every time the candidates have to fill the same set of information which is time consuming. Findings: The common information of the candidates can be stored in a centralized database from which the candidate can import his/her data while filling online application forms. Improvements/Applications: We have proposed a system for filling of common information of candidates in online application form using a centralized database which contains common information of candidates. Using the system we can save our time by importing of common information from the centralized database
Citation :

af

Govind Prasad Arya, Devendra Prasad, “Design of a System to Import Common Information of an Applicant from a Centralized Database While Filling Online Recruitment Application Form ”, International Journal Of Computer Engineering In Research Trends, 4(1):30-32, January-2017. [InnoSpace-2017:Special Edition]
Keywords : Online Services, IT Professionals, Software Engineering, Online Application Form, Import Information, Centralized Database, Online Application form from centralized database.
References :

af

-NA-
:-NA-
DOI Link : NA
Download :
  20170103.pdf
Refbacks : There are currently no refbacks
Felicitation of cloths for poor & needy people of villages in India
Authors : Govind Prasad Arya, Deepa Arya, Devendra Prasad
Affiliations : Uttarakhand Technical University, Dehradun, Assistant Professor in Computer Science & Engineering Department, Shivalik College of Engineering, Dehradun, India
Abstract :

af

The food, cloths & houses are the basic needs of pupils. There are a number of people in the world were those living below poverty lines. They have not proper food to eat, clothes to cover their bodies and homes to live. The government is felicitating the poor and needy peoples in a number of ways. Indian government provides different types of RASHAN CARDS to the Indian families on the basis of various annual incomes i.e BPL, APL, KhadyaSuraksha cards to avail them basic foods. There are so many schemes to provide economic help to construct their homes like Indira AawasYogana. Besides these there are various schemes to provide employments to the poor people for their survival. In this research paper, we proposed a scheme/system that felicitates the need of cloth, shoes to the poor & needy peoples of any age of uttarakhand in initial stage & for the other states in further stages. Using the proposed system we collect unused/old cloth, shoes from capable (rich) peoples as a donation and after processing (tailoring, washing & packaging) distribute them to the needy peoples on a regular basis. The system will specially concentrate on children, woman of villages & be free from caste, region, religion. Methods/Statistical analysis: We collect the data from the villages of uttarakhand. A lot of poor people are not capable to buy sufficient cloths for them or for their children. We find the same situation in the rural area of Uttar Pradesh (U.P) also. Findings: Although the government is facilitating food, houses to the poor & needy peoples still there is a need of cloths to the poor peoples of the India, especially in the rural area. The proposed scheme will contribute to the betterment of society. Improvements/Applications: We have proposed a scheme for felicitation of cloth. The model is shown in below mentioned figure.
Citation :

af

Govind Prasad Arya, Deepa Arya, Devendra Prasad, “Felicitation of cloths for poor & needy people of villages in India”, International Journal Of Computer Engineering In Research Trends, 4(1):33-36, January-2017. [InnoSpace-2017:Special Edition]
Keywords : Felicitation of cloth, Poor & needy people, Problems in rural areas, Donation of cloth, Help for poor children, Social work.
References :

af

[1]https://en.wikipedia.org/wiki/List_of_government_schemes_in_India, Wikipedia Portal.
[2]http://india.gov.in/my-government/schemes, A government of India Portal.
[3]http://blogs.reuters.com/india/2013/07/23/a-look-at-some-of-indias-cheap-food-schemes/
byAdityaKalra, July, 2013.
:-NA-
DOI Link : NA
Download :
  20170102.pdf
Refbacks : There are currently no refbacks
New Method for Automatic Detection of Brain Tumor in Multimodal Brain Magnetic Resonance Images
Authors : Bhima K, Jagan A,
Affiliations : BVRIT Narsapur, Telangana, India.
Abstract :

af

Brain tumor is a one of the severe life altering disease and analysis of brain imaging is a most important task of visualizing the brain inner anatomical structures, analyzing brain tumor and surgical planning. Magnetic Resonance Imaging is used to diagnose a variety of diseases in the brain and it is found to be much superior to other techniques especially for brain tissues. The main advantage is that the soft tissue differentiation is extremely high for MRI. Image processing plays vital role in medical image analysis and Image segmentation is a most conman technique for analysis of MR imaging in many clinical applications. The parallel segmentation methods and techniques are expressed for the automatic detection of tumor in multimodal brain MR Image by existing state-of-art methods. However the specific results are not being projected and established in the similar researches. Hence, this proposed work tackles about automatic segmentation and detection of tumor in multimodal brain MR images. The main aim of the proposed work to achieve high segmentation accuracy and detection of tumor in the multimodal brain MR images and it was demonstrated in multimodal brain MR Images, viz. FLAIR MRI, T1 MRI, MRI and T2 MRI. The relative performance of the Proposed Method is demonstrated over existing methods using real brain MRI and open brain MRI data sets.
Citation :

af

Bhima K, Jagan A, “New Method for Automatic Detection of Brain Tumor in Multimodal Brain Magnetic Resonance Images ”, International Journal Of Computer Engineering In Research Trends, 4(1):26-29, January-2017. [InnoSpace-2017:Special Edition]
Keywords : Brain Tumor, Watershed Method, FCMC method, Proposed Method, Bilateral Filter, Brain MR Image.
References :

af

1)	N Van . Porz, "Multi-modalodal glioblastoma segmentation: Man versus machine", PLOS ONE, vol. 9, pp. e96873, 2014.
2)	S. Bauer, R. Wiest, L.-P. Nolte and M. Reyes, "A survey of MRI-based medical image analysis for brain tumor studies", Phys. Med. Biol., vol. 58, no. 13, pp. R97-R129, 2013.
3)	L. Weizman, "Automatic segmentation, internal classification, and follow-up of optic pathway gliomas in MRI", Med. Image Anal., vol. 16, no. 1, pp. 177-188, 2012.
4)	S. Ahmed, K. M. Iftekharuddin and A. Vossough, "Efficacy of texture, shape, and intensity feature fusion for posterior-fossa tumor segmentation in MRI", IEEE Trans. Inf. Technol. Biomed., vol. 15, no. 2, pp. 206-213, 2011.
5)	Jin Liu, Min Li, Jianxin Wang, Fangxiang Wu, Tianming Liu, and Yi Pan,A Survey of MRI-Based Brain Tumor Segmentation Methods, TSINGHUA SCIENCE AND TECHNOLOGY, Volume 19, Number 6, December 2014.
6)	J. B. T. M. Roerdink and A. Meijster, “The watershed transform: Definitions, lgorithms and parallelization strategies,” Fundamenta Informaticae,vol. 41, pp. 187–228, 2000.
7)	Gang Li , Improved watershed segmentation with optimal scale based on ordered dither halftone and mutual information, Page(s) 296 - 300, Computer Science and Information Technology (ICCSIT), 2010, 3rd IEEE International Conference, 9-11 July 2011.
8)	Benson. C. C, Deepa V, Lajish V. L and Kumar Rajamani, "Brain Tumor Segmentation from MR Brain Images using Improved Fuzzy c-Means Clustering and Watershed Algorithm",  Intl. Conference on Advances in Computing, Communications and Informatics (ICACCI), Sept. 21-24, 2016, Jaipur, India.
9)	L´aszl´o Szil´agyi,L´aszl´o Lefkovits and Bal´azs Beny´o, "Automatic Brain Tumor Segmentation in Multispectral MRI Volumes Using a Fuzzy c-Means Cascade Algorithm",  12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD),2015.
10)	G.-C. Lin, W.-J. Wang, C.-C. Kang and C.-M. Wang, Multispectral mr images segmentation based on fuzzy knowledge and modified seeded region growing, Magnetic Resonance Imaging, vol. 30, no. 2, pp. 230-246, 2012.
11)	NageswaraReddy P, C.P.V.N.J.Mohan Rao, Ch.Satyanarayana, Optimal Segmentation Framework for Detection of Brain Anomalies, I.J. Engineering and Manufacturing, 2016, 6, 26-37.
:-NA-
DOI Link : NA
Download :
  20170115.pdf
Refbacks : There are currently no refbacks
A Study on Online Chatting and Blogging among Teens Age in Southwest Part of Nigeria and Its Impact: A Digital Dividend
Authors : Oyebola Blessed Olalekan, Ajayi Adeola,
Affiliations : Department of Computer Engineering Technology, Gateway (ICT) Polytechnic Saapade, Nigeria, 2Institute for Entrepreneurship and Development Studies Obafemi Awolowo University, Nigeria
Abstract :

af

The study surveyed the use of the Internet and social networking media as digital dividend among undergraduate students in Nigerian Polytechnic. A total of 700 questionnaires were distributed using a frequency count and percentage to select the respondents. A total of 527 questionnaires was retrieved were used for the survey. The findings revealed a high percentage use Internet and social networking media. The access point for them is mobile phones. The institution, though linked to the Internet is yet to provide access to students. Respondents subscribed for the access time through their pocket money. The use of the Internet among the students has affected the use of the school library because they claimed they got everything they needed to get in the library from the internet. Some problems they face in their use of the Internet include slowness of the server, electricity for charging their mobile phones and payment for the access time. The study recommends that the polytechnic should provide good access points for students and make it available in the library too.
Citation :

af

Oyebola Blessed Olalekan, Ajayi Adeola, “A Study on Online Chatting and Blogging among Teens Age in Southwest Part of Nigeria and Its Impact: A Digital Dividend”, International Journal Of Computer Engineering In Research Trends, 4(1):21-25, January-2017. [InnoSpace-2017:Special Edition]
Keywords : Access, Internet, Networking;, Social, Student, Telecommunication.
References :

af

 [1]  L. A. Ogunsola Hezekiah, (2005) Information and Communication Technologies and the Effects of lobalization: Twenty-First Century "Digital Slavery" for Developing Countries--Myth or Reality? Electronic Journal of Academic and Special Librarianship, v.6 no.1-2 (Summer 2005).
 [2] Social networking service. https://en.wikipedia.org/wiki/Social_networking_service
[3]  Audu C, Internet availability and use by postgraduate students of University of Nigeria, Nsukka, Global Review of Library & Information Science 2: 3443. 2003
[4] Oketunji, L., Computer application to libraries. Compendium of papers. presented at the 39th National Annual Conference and AGM of Nigerian Library Association held at Concord Hotel, Owerri from 17th 22nd June: 812,. 2001.
:-NA-
DOI Link : NA
Download :
  20170106.pdf
Refbacks : There are currently no refbacks
Development of a Sim800l Based Reprogrammable Household Smart Security System with Recipient Phone Call Alert
Authors : Oyebola Blessed Olalekan, ,
Affiliations : Department of Computer Engineering Technology, Gateway (ICT) Polytechnic Saapade, Nigeria
Abstract :

af

Security has become a major issue everywhere. Home security is becoming necessary nowadays as the possibilities of intrusion are increasing day by day. A traditional home security system gives the signals regarding alarm or text alert through GSM. However, this paper proffers, also, a reprogrammable system that puts forward phone call straightway to the recipient anywhere in the world with GSM network coverage SIM800L (GSM Module) with PIC12F1840 Microcontroller and a motion sensor or detector.
Citation :

af

Oyebola Blessed Olalekan, “Development of a Sim800l Based Reprogrammable Household Smart Security System with Recipient Phone Call Alert”, International Journal Of Computer Engineering In Research Trends, 4(1):15-20, January-2017. [InnoSpace-2017:Special Edition]
Keywords : Microcontroller, SMS, Call, Security
References :

af

1.	T.K Hareedran (2015) GSM home security system  with Arduino using GSM technology – An theft system http://www.electroschematics.com
2.	Ahmed, B.I, Yakubu, F.G Bagiwa, M.H and Abdullahi,U.I ( 2011), Remote Home management: An alternative for working cut home while way. World of computer science and information Technology Journal (WCSIT); 14144.147
3.	Jawarkar, N.P, M Ahmed, V Ladhake, S.A and Thakare, R.D (2008). Microcontroller based Remote monitoring using mobile through spoken commands. Journal of networks,3,2,58.63. Retrieved from http:// www. Academic publisher.com/ jnm/vol031/n002/jnw03025863.pdf
4.	Gwenael, L.Bodic (2005). Mobile messaging:SMS, EMS AND MMS
5.	Marie and Albert (1996) invention patent for a closed cicuit television security system.
6.	Sabudin, E.N., Zarina, M., Mohd, M.M., Abd Wahab, H., Johari, A. and Ghani, N.B. (2008). GSM based Notification speed Detection for Monitoring purposes. Proceeding of IEEE International Symposium of Information Technology. 
:-NA-
DOI Link : NA
Download :
  20170105.pdf
Refbacks : There are currently no refbacks
Distant Mission UAV capability with on-path charging to Increase Endurance, On-board Obstacle Avoidance and Route Re-planning facility
Authors : Pandya Garvit Kalpesh , ,
Affiliations : Department of Aeronautical Engg, Veltech Dr. RR & Dr. SR University, Chennai-600 062, India.
Abstract :

af

UAVs (Unmanned Aerial Vehicles), especially Quad copters is facing challenges in their mission due to its lower endurance. As such, the missions having long distances are not achievable through Quad copters. The performance of any vehicle, while testing, is one of the most important factors. This performance is based on range, endurance, altitude, attitude control, VTOL (Vertical Take-Off and Landing), battery life, and other autonomous functionalities. The major problem we are facing in the field of UAVs is battery life. The use of higher mAh battery is not a perfect solution as the weight also increases with the size of the battery and that will then require once level higher mAh battery and this may not end soon. Several different techniques can be applied to eliminate or reduce the above drawback. One can be, in the mission path itself, take the drone down to the ground, change its battery and continue the mission, which is a kind of out of logic things. The other solution which we can find is the use of a charging dock. In this case, no need to follow the vehicle, everything can be automatic with the help of a sensor and communication system. The above solution ends the endurance problem but, if the endurance is higher and mission is longer, it necessary to put on necessary sensors for the safety of the vehicle.
Citation :

af

Pandya Garvit Kalpesh, “Distant Mission UAV capability with on-path charging to Increase Endurance, On-board Obstacle Avoidance and Route Re-planning facility”, International Journal Of Computer Engineering In Research Trends, 4(1):10-14, January-2017. [InnoSpace-2017:Special Edition]
Keywords : UAV, charging facility, endurance, collision avoidance, route re-plan.
References :

af

1.	Skysense Company - Charging Pad Datasheet 201601 
2.	Victor H. L. Cheng: Concept Development of Automatic Guidance for Rotorcraft Obstacle Avoidance. In: IEEE transactions on Robotics and Automation 6(2):252-257, (1990)
3.	George Vachtsevanos, Ben Ludington, Johan Reimann, Panos Antsaklis, Kimon Valavanis: Modeling and Control of Unmanned Aerial Vehicles– Current Status and Future Directions. In: Workshop on Modeling and Control of Complex Systems (MCCS), Ayia Napa, Cyprus, (2005)
4.	Ryan W. Proud, Jeremy J. Hart, Richard B. Mrozinski: Methods for Determining the Level of Autonomy to Design into a Human Spaceflight Vehicle: A Function Specific Approach. In: NASA Johnson Space Center. (2013)
5.	Pulkit Goyal, Ewoud Smeur and Guido de Croon: Mission Planning for Sensor Network Deployment using a Fleet of Drones. In: Delft University of Technology, Delft, Zuid-Holland, 2629 HS, The Netherlands. (2016)
6.	www.erlerobotics.com
7.	Erick Camacho, Marco Robaina, Alessandro Tasca, Pedre Cuberos, Ibrahim Tansel, Sabri Tosungolu: Collision Avoidance Protocol for package Delivering Quadcopters. In: Florida Conference on Recent Advances in Robotics (2015).
8.	https://oscarliang.com/how-to-choose-battery-for-quadcopter-multicopter/
9.	Video – drone wireless charging system (Youtube.com)
10.	Video – World's first home w_ drone charging station (Youtube.com).   
:-NA-
DOI Link : NA
Download :
  20170107.pdf
Refbacks : There are currently no refbacks
A Review on Different Techniques of Solar Food Cooking
Authors : Usha.C.Pawar, S. J. Shankargouda, Dr. Pravin V.Honguntiker, ,
Affiliations : Department of Mechanical Engineering, DattaMeghe College of Engineering, Navi Mumbai, MS, India
Abstract :

af

Energy consumption for cooking is unavoidable, though there is continuously increasing the fuel price as well as scarcity of exhausting fossil fuels. Because cooking is the prime priority of human life all over the world. Cooking contributes a major part in sharing of total primary energy consumption in India. Hence it needs an alternative energy source for this purpose. Solar cookers are the best substitute for, heating, cooking and pasteurizing applications. In this paper a review has been made to study the existing literature in the field of solar cookers with the latent heat storage system using PCM.
Citation :

af

Usha.C.Pawar, S. J. Shankargouda, Dr. Pravin V.Honguntiker, “A Review on Different Techniques of Solar Food Cooking”, International Journal Of Computer Engineering In Research Trends, 4(1):5-9, January-2017. [InnoSpace-2017:Special Edition]
Keywords : Solar Energy, Thermal Energy Store, Phase Change Material.
References :

af

1.	Klemens Schwarzera , Maria Eugenia Vieira da Silva, ―Solar cooking system with or without heat storage for families and institutions, Solar energy 75 2003, 35–41
2.	Kassem, Talal K. and Youssef, M. S. Solar 
Cookers And Its Application For Food cooking In Remote Areas: Review
3.	Sharma, C. R. Chen, V. V. S. Murty, and A. Shukla― Solar cooker with Latent heat storage systems: a review, Renewable and Sustainable Reviews,Vol. 9, pp. 1599-1605, 2009. 
4.	Mohammadreza Sedighi1, Mostafa Zakariapour, ―A Review of Direct and Indirect Solar Cookers, Sustainable Energy, 2014, Vol. 2, No. 2, 44-51,2014.
5.	Lof GOG. Recent investigation in the use of solar energy for cooking. Solar Energy 1963;7:125–33
6.	R.M. Muthusivagami, R. Velraj , R. Sethumadhavan,―Solar cookers with And without thermal storage—A reviews , Renewable and Sustainable Energy Reviews 14, 691–701, 2010  
7.	Domanski R, El-Sebaii AA, Jaworski M. Cooking during off-sunshine hours using PCMs as storage media. Energy 1995;20:607–16
8.	Buddhi D, Sahoo LK. Solar cooker with latent heat storage: design and experimental testing. Energy Conversion and Management 1997;38:493–8 
9.	Sharma, S.D., Buddhi, D., Sawhney, R.L., Sharma, A., 2000. Design development and evaluation of a Latent heat unit for evening cooking in a solar cooker. Energy Conversion and Management 41, 1497– 1508.
10.	Sharma SD, Iwata T, Kitano H, Sagara K. Thermal performance of solar cooker based on an evacuated tube solar collector with a PCM storage unit. Solar Energy 2005;78:416–26
11.	Hussein HMS, El-Ghetany HH, Nada SA. Experimental investigation of novel indirect solar cooker with indoor PCM thermal storage and cooking unit. Energy Conversion and Management 2008; 49:2237– 46.
12.	R.M. Muthusivagami, R. Velraj and R. Sethumadhavan.“Solar cookers with and without thermal storage—A Review”, Renewable and Sustainable Energy Reviews, Vol. 14, pp. 691-701, 2009.
13.	Kedare et al. Solar Cooking through ARUN Solar Boiler and Solar Thermal. Ministry of New & Renewable Energy Government of India. ARUN®100 November 2014.
14.	Rane M V, Rane M M, Meena P M, Shankargouda S J, Bhave D P, Rane A M, Akshay P, 2014, Solar Collector with Absorber Integrated Heat Storage, Patent Application Number-2088-MUM-2014, 2014
15.	Rane M V, Rane M M, Meena P M, Shankargouda S J, Bhave D P, Rane A M, Akshay P, 2015, Solar Collector with Absorber Integrated Heat Storage, PCT Application Number-PCT-IN2015-0000269, PCT Filing Date: 29-06-2015, 2015a
:-NA-
DOI Link : NA
Download :
  20170113.pdf
Refbacks : There are currently no refbacks
Study of the effects of orientation and deformation of Sn on fusion cross sections using proximity potentials
Authors : Nabendu Kumar Deb , ,
Affiliations : Department of Physics, Gauhati University, Guwahati-781014, India
Abstract :

af

Background: The deformed targets and its orientation with collision axis of the projectile and the target in the nuclear fusion reaction influence the fusion cross-section. Statistical Analysis: The effects of static quadrupole and hexadecapole deformation of target are studied using various proximity potentials in the literature. Accordingly, the height and the position of the Coulomb interaction barrier for 18O+118Sn (deformed target) system is studied in this paper. Findings: The nucleus-nucleus potential was found to depend strongly on the deformation parameters as well as the orientation of the deformed target. The fusion cross section of the mentioned system was found out by applying parameters of the various proximity potential on the Wong’s formula. Also the result of a multi dimensional barrier penetration model (BPM) was assessed using CCFULL code. The fusion cross sections of approx 00, Prox 00DP, pro 77, Prox 88, modProx 88, Prox 10 over estimates the results obtained using BPM and the rest of the potentials under-estimates the result obtained using BPM technique.
Citation :

af

Nabendu Kumar Deb, “Study of the effects of orientation and deformation of Sn on fusion cross sections using proximity potentials”, International Journal Of Computer Engineering In Research Trends, 4(1):1-4, January-2017. [InnoSpace-2017:Special Edition]
Keywords : fusion cross-section, effects of deformation, effects of orientation, proximity potentials.
References :

af

1)	M. Dasgupta, D. J. Hinde, N. Rowley, A. M. Stefanini, Annu. Rev. Nucl. Part. Sci. 48, 401 (1998).
2)	P. D. Shildling et al., Physics Letter B 670, 99 (2008).
3)	E. Prasad et al., Physics Review C 81, 054608 (2010).
4)	J. O. Fernandez Niello et al., Physics Review C 43, 2303 (1991).
5)	M. J. Rhoades Brown, V. E. Oberacker, Physics Review Letter 50, 1435 (1983)
6)	I. Dutt, R. K. Puri, Physics Review C 81, 064608 (2010)
7)	I. Dutt, R. K. Puri, Physics Review C 81, 044615 (2010)
8)	I. Dutt, R. K. Puri, Physics Review C 81, 064609 (2010)
9)	C. J. Lin, J. C. Xu, H. Q. Zhang, Z. H. Liu, F. Yang, L.X. Lu, Physics Review C 63, 064606 (2001)
10)	P. Moller et al., Atomic Data and Nuclear Data Tables 59, 185 – 381 (1995)
11)	C. Y. Wong, Physics Review Letter 31, 766 (1973)
12)	N. Takigawa, T. Rumin, N. Ihara, Physics Review C 61, 044607 (2000)
13)	K. Hagino, N. Rowley, A. T. Kruppa, Comp. Physics Comm. 123, 143 (1999).

:-NA-
DOI Link : not applicable
Download :
  20170121.pdf
Refbacks : There are currently no refbacks

 

Dynamic and Public Auditing with Fair Arbitration for Cloud Data
Authors : SAJJA SUNEEL, MANDAVILLI KAVYA ,
Affiliations : Asst.Professor, KG Reddy Engineering College, Hyderabad, Telangana
Abstract :

af

Storage outsourcing turned into a rising trend with the advent of the cloud computing, advancing the secure remote data auditing to be the future research area. Other than this research considers the problem of data dynamics support, public verifiability and dispute arbitration simultaneously. The data dynamics problem in auditing is solved by presenting an index switcher to preserve a mapping between block indices and tag indices and eradicate the passive outcome of block indices in the tag computation without incurring much overhead. We provide fairness guarantee and dispute arbitration in our scheme, which ensures that both the data owner and the cloud cannot misbehave in the auditing process or else it is easy for a third-party arbitrator to find out the cheating party. The framework is reaching out by executing the data dynamically and reasonable discretion on gatherings in the future.
Citation :

af

Sajja Suneel et.al, “Dynamic and Public Auditing with Fair Arbitration for Cloud Data”, International Journal Of Computer Engineering In Research Trends, 4(4):136-141, April-2017.
Keywords : Third Party Auditor (TPA), CSP, Proof Of Retrievability (POR).
References :

af

1. Y. Deswarte, J. J. Quisquater, and A. Saïdane, “Remote integrity checking,” In Integrity and internal control in information systems VI, Springer US, 1-11 (2004).
2. D. L. Gazzoni Filho, and P. S. L. M. Barreto, “Demonstrating data possession and uncheatable data transfer,” IACR Cryptology ePrint Archive 2006, 150 (2006).
3. A. Juels, and B. S. Kaliski Jr, “PORs: Proofs of retrievability for large files,” In Proceedings of the 14th ACM conference on Computer and communications security, Acm, 584-597 (2007).
4. G. Ateniese, R. Burns, R. Curtmola, J. Herring, L. Kissner, Z. Peterson, and D. Song, “Provable data possession at untrusted stores,” In Proceedings of the 14th ACM conference on Computer and communications security, Acm, 598-609 (2007).
5. H. Shacham, and B. Waters, “Compact proofs of retrievability,” In International Conference on the Theory and Application of Cryptology and Information Security, Springer Berlin Heidelberg, 90-107 (2008).
6. Q. Wang, C. Wang, J. Li, K. Ren, and W. Lou, “Enabling public verifiability and data dynamics for storage security in cloud computing,” In European symposium on research in computer security, Springer Berlin Heidelberg, 355-370 (2009).
7. M. A. Shah, R. Swaminathan, and M. Baker, “Privacy-Preserving Audit and Extraction of Digital Contents,” IACR Cryptology EPrint Archive 186 (2008).
8. C. Wang, K. Ren, W. Lou, and J. Li, “Toward publicly auditable secure cloud data storage services,” IEEE network 24, (2010).
9. C. C.  Erway, A. Küpçü, C. Papamanthou, and R. Tamassia, “Dynamic provable data possession,” ACM Transactions on Information and System Security (TISSEC) 17, (2015).
10. Y. Zhu, H. Wang, Z. Hu, G. J. Ahn, H. Hu, and S. S. Yau, “Dynamic audit services for integrity verification of outsourced storages in clouds,” In Proceedings of the 2011 ACM Symposium on Applied Computing, ACM, 1550-1557 (2011).
11. Q. Zheng, and S. Xu, “Fair and dynamic proofs of retrievability,” In Proceedings of the first ACM conference on Data and application security and privacy, ACM, 237-248 (2011).
:NA
DOI Link : NA
Download :
  V4I403.pdf
Refbacks : There are currently no refbacks

 

IoT Based Smart Parking System Using RFID
Authors : Prof.S.S.Thorat, Ashwini M , Akanksha Kelshikar , Sneha Londhe , Mamta Choudhary
Affiliations : Assistant Professor, Information Technology, JSPM’S Jayawantrao Sawant College Of Engineering Hadapsar Pune,411028,India
Abstract :

af

With the exponential increase in the number of vehicles and world population day by day, vehicle availability and usage on the road in recent years, finding a space for parking the bike is becoming more and more difficult with resulting in the number of conflicts such as traffic problems. This is about creating a reliable system that takes over the task of identifying free slots in a parking area and keeping the record of vehicles parked very systematic manner.This project lessens human effort at the parking area to a great extent such as in case of searching of free slots by the driver and calculating the payment for each vehicle using parking area. The various steps involved in this operation are vehicle identification using RFID tags, free slot detection using IR sensors and payment calculation is done on the basis of period of parking and this is done with the help of real time clock.
Citation :

af

Prof.S.S.Thorat et.al, “IoT Based Smart Parking System Using RFID”, International Journal Of Computer Engineering In Research Trends, 4(1):9-12, January-2017.
Keywords : IoT, RFID, IR sensors.
References :

af

1. Thanh Nam Pham1, Ming-Fong Tsai1, Duc Bing Nguyen1, Chyi-Ren Dow1 and Der- Jiunn Deng2. “A Cloud Based Smart-Parking System Based on Internet-of-Things Technologies”. IEEE Access, volume 3,pp. 1581 1591, september 2015.

2. Renuka R. and S. Dhanalakshmi. “Android Based Smart Parking System Using slot Allocation reservations”. ARPN Journal of Engineering and Applied Sciences. VOL. 10, NO. 7, APRIL 2015.

3. ElMouatezbillah Karbab,Djamel Djenouri, Sahar Boulkaboul, Antoine Bagula, CERIST Research Center, Algiers, Algeria University of the Western Cape, Cape town, South Africa ,”Car Park Management with Networked WirelessSensors and Active RFID” ‘,978-1-4799-8802-0/15
©2015 IEEE

4. Harmeet Singh, Chetan Anand, Vinay Kumar, Ankit Sharma, “Automated Parking System With Bluetooth
Access”, International Journal Of Engineering And Computer Science ISSN:2319-7242,Volume 3 Issue 5, May 2014, Page No. 5773-5775

5. ThanhNamPham1,Ming-FongTsai1,Duc Bing Nguyen1, Chyi-Ren Dow1 and Der- Jiunn Deng2. “A Cloud-Based Smart-Parking System Based on Internet-of-Things Technologies”. IEEE Access, volume 3,
pp. 1581 1591, september2015.

6. Renuka R .and S.Dhanalakshmi.“ Android Based Smart Parking System Using slot Allocation reservations”.ARPN Journal of Engineering and Applied Sciences.VOL.10, NO. 7,APRIL2015.
7. SushilPalande, Surekha Gangurde, AkshayPote. “Automatic Pay And Park System”. International Journal
of Scientific and Research Publications, Volume5, Issue5, May

8. GGYU Gunasekara, ADAI Gunasekara and RPS Kathriarachchi General Sir John Kotelawala Defence University, Ratmalana ,SriLanka. “ A Smart Vehicle Parking Management Solution”. Proceedings of 8th International ResearchConference, KDU, Published November2015.

9. Baratam MKumar Gandhi and M.Kameswara Rao. .“A Prototype for IoT based Car Parking Management
System for  martCities”.IndianJournalofScienceandTechnology,Vol9(17),DOI:10.17485/ijst/2016/v9i17/92973,May201

10. Pooja Sanjay Pagar, Tabassum Jalal Khan, P. R. Ghodekar , M. R. Bhadange, V. Salve . “Smart Car Management System Using Raspberry Pi ”.International Journal Of Advanced Research in Engineering Management (IJAREM).

11. Zeyd in Pala , Nihat Inanc. “Utilizing Rfid For Smart Parking Applications”.FactaUniversitatisSeries:Mechanical EngineeringVol.7,No1, 2009, pp. 101118.


12. RakhiKalantri, AnandParekar, Akshay Mohite, Rohan Kankapurkar. “RFID Based Toll Collection System ” Rakhi Kalantri et al,/(IJCSIT)International Journal ofComputer Science and Information Technologies, Vol. 5 (2) , 2014,2582-2585.

13. VishwanathY, AishwaryaDKuchalli, DebarupaRakshit. “Survey paperonSmartParking System based on
Internet of Things”.Information Science, New HorizonCollegeof Engineering, Bengaluru, India.

14. Ahmed Yaseen Mjhool, Ali Abbas Al-Sabbagh, Ruaa A. Saeed Alsabah. “Smart Parking Techniques Based on Internet of things”.Journal of Networks and Telecommunication Systems, Vol.1 (1), 1-10, August, 2015.
:10.22362/ijcert/2017/v4/i1/xxxx
DOI Link : Not yet assigned
Download :
  V4I0103.pdf
Refbacks : There are currently no refbacks
Implementation of Optimization Using Eclat and PSO for Efficient Association Rule Mining
Authors : M.Sathya, Dr.K.Thangadurai,
Affiliations : PG and Research Department of Computer Science, Government Arts College (Autonomous), Karur, India,
Abstract :

af

In this paper, the IEPSO-ARM technique used Eclat algorithm for generating the association rules. With help of Eclat algorithm, IEPSO-ARM technique initially estimates the support value to find the frequent items in the dataset and then determines correlation value to generate the association rules. Finally, the IEPSO-ARM technique designed an Eclat based Particle Swarm Optimization (E-PSO) algorithm for generating the optimized association rule to analyze the frequently buying products by customer in supermarkets and to improve sales growth maintenance of supermarkets. The performance of IEPSO-ARM technique is tested with the metrics such as running time for frequent itemset generation, memory for association rule generation and number of rules generated.
Citation :

af

M.Sathya, Dr.K.Thangadurai, “Implementation of Optimization Using Eclat and PSO for Efficient Association Rule Mining”, International Journal Of Computer Engineering In Research Trends, 4(1):4-8, January-2017.
Keywords : frequent item set, Eclat, PSO, association rule mining, supermarkets
References :

af

[1] Zhi-Hong Deng, Sheng-Long Lv, “Fast mining frequent itemsets using Nodesets”, Expert Systems with Applications, Elsevier, Expert Systems with Applications, Elsevier, Volume 41, Pages 4505–4512, 2014

[2] Zhi-Hong Deng, Sheng-Long Lv, “PrePost+: An efficient N-lists-based algorithm for mining frequent itemsets via Children–Parent Equivalence pruning”, Expert Systems with Applications, Elsevier, Volume 42, Pages 5424–5432, 2015
[3] Meera Narvekara, Shafaque Fatma Syed, “An optimized algorithm for association rule mining using FP tree”, Procedia Computer Science, Elsevier, Volume 45, Pages 101 – 110,  2015 

[4] Anil Vasoya, Dr. Nitin Koli, “Mining of association rules on large database using distributed and parallel computing”, Procedia Computer Science, Elsevier, Volume 79, Pages 221 – 230, 2016 

[5] Ish Nath Jha, Samarjeet Borah, “Efficient Association Rule Mining Using Improved Apriori Algorithm”, International Journal of Scientific & Engineering Research, Volume 3, Issue 11, Pages 1-4, November-2012

[6] Manali Rajeev Raut, Hemlata Dakhore, “An Approach to Mining Association Rules in Horizontally Distributed Databases with Anonymous ID Assignment”, IEEE 2015 Global Conference on Communication Technologies (GCCT), Pages 23-24, April 2015

[7] M. Krishnamurthy, E. Rajalakshmi, R. Baskaran, A. Kannan, “Prediction of customer buying nature from frequent itemsets generation using Quine-McCluskey method”, IET Chennai Fourth International Conference on Sustainable Energy and Intelligent Systems (SEISCON 2013), Pages 12-14, 2013

[8] Jesmin Nahar, Tasadduq Imama, Kevin S. Tickle, Yi-Ping Phoebe Chen, “Association rule mining to detect factors which contribute to heart disease in males and females”, Expert Systems with Applications, Elsevier, Volume 40, Pages 1086–1093, 2013

[9] Bay VO, Frans Coenen, Bac Le, “new method for mining Frequent Weighted Itemsets based on WIT-trees”, Expert Systems with Applications, Elsevier, Expert Systems with Applications, Elsevier, Volume 40, Pages 1256–1264, 2013

[10] D. Magdalene Delighta Angeline, “Association Rule Generation for Student Performance Analysis using Apriori Algorithm”, The SIJ Transactions on Computer Science Engineering & its Applications (CSEA), Volume 1, Issue 1, Pages 12-16, March-April 2013

[11] Dr. S. Vijayarani and Ms. R. Prasannalakshmi, “Comparative Analysis of Association Rule Generation Algorithms in Data Streams”, International Journal on Cybernetics & Informatics (IJCI), Volume 4, Issue 1, Pages 15-25, February 2015  
[12] J.Suresh, P.Rushyanth,Ch.Trinath, “Generating associations rule mining using Apriori and FPGrowth Algorithms”, International Journal of Computer Trends and Technology (IJCTT), volume4, Issue4, Pages 887-892, April 2013 
[13] Ruchi Bhargava, Prof. Shrikant Lade, “Effective Positive Negative Association Rule Mining Using Improved Frequent Pattern”, International Journal of Modern Engineering Research (IJMER), Volume 3, Issue 2, Pages 1256-1262, March-April. 2013 
[14] Sample Dataset for Market Basket Analysis:http://recsyswiki.com/wiki/Grocery_shoppi  
:10.22362/ijcert/2017/v4/i1/xxxx
DOI Link : Not yet assigned
Download :
  V4I0102.pdf
Refbacks : There are currently no refbacks
A Survey on Virtual Classroom System for Online Training
Authors : Maram Adil Ali Alaziz, ,
Affiliations : Osmania University. India
Abstract :

af

Developing a virtual classroom system to promote a more preponderant count of students to splurge into the field of inculcation. It integrates the benefits of a physical classroom with the accommodation of a ‘no-physical-bar’ virtual learning environment, minus the commuting hazards and expenses. It will usher in the immense flexibility and sophistication in the subsisting learning platform structures, with the impeccable coalescence of synchronous and asynchronous interaction. It provides an expedient of collaborative learning for the students.
Citation :

af

Maram Adil Ali Alaziz, “A Survey on Virtual Classroom System for Online Training”, International Journal Of Computer Engineering In Research Trends, 4(1):1-3, January-2017.
Keywords : Head of the Department (H.O.D), Faculties, Students, Shared learning environment.
References :

af

[1] M. Armbrust et al., “Above the clouds: A Berkeley view of cloud computing,” University of California, Berkeley, Tech. Rep., Feb 2009.
[2]L. Siegel, “Let it rise: A special report on corporate IT,” in TheEconomist, Oct. 2008.
[3]  P. Barham, B. Dragovic, K. Fraser, S. Hand, T. Harris, A. Ho, R. Neugebauer, I. Pratt, and A. Warfield, “Xen and the art of virtualization,” in Proc. of the ACM Symposium on Operating Systems Principles (SOSP’03), Oct. 2003.
[4] “Amazon elastic compute cloud (Amazon EC2),http://aws.amazon.com/ec2/.”
[5] C. Clark, K. Fraser, S. Hand, J. G. Hansen, E. Jul, C. Limpach, I. Pratt, and A. Warfield, “Live Migration of virtual machines,” in Proc. of the Symposium on Networked Systems Design and Implementation (NSDI’05), May 2005.
[6] M. Nelson, B.-H. Lim, and G. Hutchins, “Fast, transparent migration for virtual machines,” in Proc. of the USENIX Annual Technical Conference, 2005.
[7] M. McNett, D. Gupta, A. Vahdat, and G. M. Voelker, “Usher: An extensible framework for managing clusters of virtual machines,” in Proc. of the Large Installation System Administration Conference (LISA’07), Nov. 2007. 
[8] T. Wood, P. Shenoy, A. Venkataramani, and M. Yousif, “Black-box and Gray-box strategies for virtual machine migration,” in Proc. Of the Symposium on Networked Systems Design and Implementation (NSDI’07), Apr. 2007.
[9] C. A. Waldspurger, “Memory Resource Management in VMware ESX Server,” in Proc. of the symposium on Operating systems design and implementation (OSDI’02), Aug. 2002.
[10] G. Chen, H. Wenbo, J. Liu, S. Nath, L. Rigas, L. Xiao, and F. Zhao, “Energy-aware server provisioning and load dispatching for connection-intensive Internet services,” in Proc. of the USENIX Symposium on Networked Systems Design and Implementation (NSDI’08), Apr. 2008.

:10.22362/ijcert/2016/v4/i1/xxxx
DOI Link : Not yet assigned
Download :
  V4I101.pdf
Refbacks : There are currently no Ref backs

 

An Effective algorithm for Spam Filtering and Cluster Formation
Authors : Kavitha Guda, ,
Affiliations : Associate Professor, Department of Computer Science and Engineering.
Abstract :

af

K-means clustering algorithm is one of the most widely used partitioning algorithms used for grouping the elements over spatiotemporal data. It is the fast, simple and can work with large datasets. It has some of the pitfalls regarding Number of iterations are more due to clusters details not known at an initial stage. It can detect only spherical clusters. Here we will propose a Hybrid K-Means clustering algorithm which will mostly work on the concept of splitting dataset and reducing the number of iterations. It will inherit the some of the features from two revised K-means algorithms. The advantage of separating more massive datasets is that handle easy, and the benefit of reducing iterations leads the easy cluster formation in this way the efficiency of the traditional K-means clustering algorithm is increased. Furthermore, we also proposed Naïve Bayes Algorithm for Email Spam Filtering on SPAMBASE Dataset.
Citation :

af

Kavitha Guda, “An Effective algorithm for Spam Filtering and Cluster Formation”, International Journal Of Computer Engineering In Research Trends, 3(12):659-666, December-2016.
Keywords : Data Mining, KDD, E-Mail, Spam, Naïve Bayes Algorithm, Spam Filter, K-Means Algorithm, Hybrid K-means Algorithm, SPAMBASE dataset.
References :

af

[1] Marek Rychly, Pavlina Ticha, “A tool for clustering in data mining”, International Federation for Information Processing, 2007.
[2]P.Verma, D.Kumar, “Association Rule Mining Algorithm’s Variant Analysis”, International Journal of Computer Application (IJCA), vol. 78, no. 14, September 2013, pp. 26–34.
[3]L.Firte, C.Lemnaru, R.Potolea, “Spam Detection Filter using KNN Algorithm and Resampling”, 6th International Conference on Intelligent Computer Communication and Processing- IEEE, 2010, pp.27-33. [4] G.Kaur, R.K.Gurm, “A Survey on Classification Techniques in Internet Environment”, International Journal of Advance Research in Computer and Communication Engineering, vol. 5, no. 3, March 2016, pp. 589–593.
[5] Rushdi, S. and Robet, M, “Classification spam emails using text and readability features”, IEEE 13th International Conference on Data Mining, 2013.
 [6] Androutsopoulos, I., Paliouras, G., and Michelakis, “E. Learning to filter unsolicited commercial e-mail”, Technical report NCSR Demokritos, 2011.
[7]Na shi, “Research on k-means clustering algorithm”, 3rd international symposium on intelligent information technology and security informatics, 2011. 
[8] Shah Sourabh, Singh Manmohan, “comparison of a time efficient modified k-mean algorithm with k-mean and kmedoid algorithm” international conference on communication systems and network technologies, 2012.
 [9] Boomjia M.D, “Comparison of partitioning based clustering algorithms”. 
[10] Han kwai, “Approximate distributed k-means clustering over a peer-to-peer network”, IEEE transactions on knowledge and data engineering, 2009.
[11]Tariq, M., B., Jameel A. Tariq, Q., Jan, R. Nisar, A. S., “Detecting Threat E-mails using Bayesian Approach”, IJSDIA International Journal of Secure Digital Information Age, Vol. 1. No. 2, December 2009.
[12]ML & KD- Machine Learning & Knowledge Discovery Group. http://mlkd.csd.auth.gr/concept drift.html.
[13] Rizky, W. M., Ristu, S., Afrizal, D. “The Effect of Best First and Spreadsubsample on Selection of a Feature Wrapper With Naïve Bayes Classifier for The Classification of the Ratio of Inpatients”. Scientific Journal of Informatics, Vol. 3(2), p. 41-50, Nov. 2016.
[14]Feng, W., Sun, J., Zhang, L., Cao, C. and Yang,Q., “A support vector machine based naive Bayes algorithm for spam filtering,” 2016 IEEE 35th International Performance Computing and Communications Conference (IPCCC), Las Vegas, NV, 2016, pp. 1-8.
[15] Lalchand G. Titare1, Prof. Riya Qureshi,” Cloud Centric loT Based Farmer’s Virtual Market place” International Journal of Computer Engineering In Research Trends., vol.3, no.12, pp. 654-658, 2016.
:10.22362/ijcert/2016/v3/i12/4321
DOI Link : 10.22362/ijcert/2016/v3/i12/4321
Download :
  V3I1210.pdf
Refbacks : Currently There are norefbacks
Cloud Centric loT Based Farmer’s Virtual Market place
Authors : Lalchand G. Titare, Prof. Riya Qureshi,
Affiliations : Department of Computer Science and Engg, BIT, Ballarpur, India
Abstract :

af

Cloud computing is aimed at providing IT as a service to the cloud users on-demand basis with greater flexibility, scalability, reliability and availability with utility computing model. This new ideal model of computing has a tremendous potential in it to be utilized as a part of the agriculture furthermore in rural improvement viewpoint in creating nations like India. The fragmented supply chain and inadequate health, safety and quality mechanisms (means the quantity and quality of fruits and vegetables) often do not meet the demands of high-end or international markets. Moreover, Indian farmers receive less than a fifth of the end price for the fruits and vegetables they produce, while a long line of middlemen, transporters, wholesalers and retailers get the rest. So, the aim behind developing this app is to give India’s huge farming community a fair and consistent price for their produce. Using this android based app “Cloud centric IoT based platform for Farmer’s virtual marketplace”, this paper concentrates on how Cloud Computing idea improves virtualization of supply chains in agribusiness segment which will help some of the farmers to overcome this problem. Using these app farmers can directly connect with the end users and supply the product directly to them. Farmers can get most advance grade cultivating and virtualization of supply chains systems, additionally track and check the entire methodology from production, distribution to consumption
Citation :

af

Lalchand G. Titare, Prof. Riya Qureshi, “Cloud Centric loT Based Farmer’s Virtual Market place”, International Journal Of Computer Engineering In Research Trends, 3(12):654-658,December-2016.
Keywords : Android, Cloud of things, Internet of Things, Virtual Commerce, Agriculture.
References :

af

1)	Reto Meier, “Professional android 4 application        development”. John Wiley & Sons, Inc. 10475 Cross point Boulevard Indianapolis, 2012
2)	K.B.Priya Iyer. Intelligent Path Finder for Goal Directed Queries in Spatial Networks. International Conference on Advances in Mobile Network, Communication and Its Application 2012 
3)	Kerry Taylor, Colin Griffith, David Lamb, Greg Falzon, and Mark Trotter, “Farming the Web of Things”, IEEE INTELLIGENT SYSTEMS Published by the IEEE Computer Society. 
4)	C.N. Verdouw, A.J.M. Beulens, J.G.A.J. van der Vorst, ‘’ Virtualisation of floricultural supply chains: A review from an Internet of Things perspective”, Computers and Electronics in Agriculture 99 ,Elsevier (2013) 160–175 
5)	Acharya, S.S. (2005), “Agriculture marketing and rural credit: Status, Issues and Reform agenda, Area, Production and Yield of Principal Crops in India”, Directorate of Economics and Statistics, Ministry of Agriculture.
6)	Global Positioning System Open Courseware from MIT, 2012
7)	van der Lans, Rick F. (September 7, 2009). The SQL Guide to SQLite (!st ed.)
8)	Newman, Chris (November 9, 2004), SQLite (Developer’s Library)(1st ed.).
9)	G. Suciu et al., “Smart cities built on resilient cloud computing and secure Internet of Things,” in Proc. 19th Int. Conf. Control Syst. Comput. Sci. (CSCS), May 2013, pp. 513–518.
10)	X. Yu, F. Sun, and X. Cheng, “Intelligent urban traffic management system based on cloud computing and Internet of Things,” in Proc. Int. Conf. Comput. Sci. Service Syst. (CSSS), Aug. 2012, pp. 2169–2172. 
11)	Mentzer, John T., William DeWitt, James S. Keebler, Soonhoong Min, Nancy W. Nix, Carlo D. Smith, & Zach G. Zacharia (2001): “Defining Supply Chain Management”, Journal of Business Logistics, Vol. 22, No. 2, pp. 1–25. 
12)	C. Perera, P. Jayaraman, A. Zaslavsky, P. Christen, and D. Georgakopoulos, “Dynamic configuration of sensors using mobile sensor hub in Internet of Things paradigm,” in Proc. IEEE Int. Conf. Intell. Sensors, Sensor Netw. Inf. Process., Apr. 2013, pp. 473–478.
13)	A. E. Al-Fagih, F. M. Al-Turjman, W. M. Alsalih, and H. S. Hassanein, “A priced public sensing framework for heterogeneous IoT architectures,” IEEE Trans. Emerging Topics Comput., vol. 1, no. 1, pp. 133–147, Jun. 2013.
:10.22362/ijcert/2016/v3/i12/xxxx
DOI Link : Not yet assigned
Download :
  V3I1209.pdf
Refbacks : There are currently no refbacks
Employee Rewards and Employee Work Motivation: An Indispensable Linkage
Authors : Dr. H S. ABZAL BASHA, ,
Affiliations : Assistant Professor, Department of Management Studies, G. Pullaiah College of Engineering & Technology, Pasupala (V), Kurnool -518452, A.P.
Abstract :

af

“People work for money, But go an extra mile for recognition, praise and rewards” - Dale Carnegie Today Indian banking sector is being considered as one of the most glorious, innovative service industry that has witnessed constant growth over the past three decades. Indian banking industry has a vital role in promoting public lending and public savings, and is widely recognized as a significant factor for the economic development of the country. The Indian banking industry is expected to be among the top 10 global markets in terms of value by 2025, strengthen by increasing domestic demand. Now-a-days managing talent in the banking sector is the most crucial Human Resource challenge all over the world, and it becomes as the main agenda of top management in every aspect in the predictable future. Employees who are pleased with rewards are more motivated to contribute and can do more effectively. This also converts into better customer experience and in turn, leads to stronger financial performance by the firm and overall economic growth. The present paper aims to decisively study and understand the role of Employee Reward System in SBI and ICICI bank and its impact on Employee Motivation and Organizational Performance.
Citation :

af

Dr. H S.ABZAL BASHA, “Employee Rewards and Employee Work Motivation: An Indispensable Linkage”, International Journal Of Computer Engineering In Research Trends, 3(12):645-653,December-2016.
Keywords : Employee Reward, Economic Development, Organizational Performance.
References :

af

1.	Broad, M., “Rewarding staff is simply good manners”, Personnel Today, 26 October, 2001. 
2.	Edward E Lawler, “Treat people right”. San Francisco: Jossey-Bass Inc., 2003. 
3.	Deeprose Donna, “How to recognise and reward employees”. Broadway,      New York: American Management Association, 1994. 
4.	Aniruddha Limaye and Ralsi Sharma; “Rewards and Recognition: Make a difference to the talent in your organization”, 2013.
5.	Maslow Abraham., “Motivation and Personality”, Harper and Row Publications: New York, First Edition, 1954.
6.	Report of the National Commission on Labour: Government of India Ministry of Labour and Employment and Rehabilitation, 1969. 
7.	Gurvinder Kaur;“A Thesis on Employee Empowerment and Organizational Effectiveness: A Comparative Study of Public, Private and Foreign banks in Some North Indian States, submitted to Thapar University, Punjab, November, 2013.
8.	Chandra Mohan Patnaik& Ashok Kumar Sahoo; “Empowerment of award staff in regional rural banks through training system: an analysis” Asian Journal of Multidimensional Research Vol.2 Issue 1, January 2013, ISSN 2278-4853.
9.	Zorah Abu Kassim et al., “Job Empowerment and Customer Orientation of Bank Employees in Kuching, Malaysia”, Contemporary Mgt Research, 131-140, Vol. 8, 2012.
10.	Quratul-AinManzoor; Impact of Employees Motivation on Organizational Effectiveness, ISSN 2157-60682012, Vol. 3, No-1.
11.	PreetiS.Rawat; Effect of Psychological Empowerment on Commitment of Employees: An Empirical Study, IPEDR vol.17 (2011), IACSIT Press, Singapore.
12.	Angwenyi Callen Nyanchama; Employee Empowerment Practices in Commercial Banks in Kenya, School Of Business, University Of Nairobi, 2009.
13.	Peters Silvia Chigozirim and ElhamMazdarani; The impact of employee empowerment on service quality and customer satisfaction in service organizations-A Case study of Lansforsakringar Bank AB, 2008,Malardalen University, Vasteras.
14.	David E Bowen and Edward Lawler; The Employment Approach to Service, Center for Effective Organizations, January, 1994. 
15.	GbalahamGbadmosi: “Employee Commitment An overview”, Management Review, 1995, vol. 12. pp. 87- 93 
16.	Decotics and summers; “A Path Analysis of a Model of the Antecodents and Consequences of Organisational Commitment”, Human Relations, 1987, pp. 445-470.
17.	O.R Krishnaswami and M. Ranganatham: Methodology of Research in Social Sciences, 2005, ISBN 81-8318-454-5. 
****

:10.22362/ijcert/2016/v3/i12/xxxx
DOI Link : Not yet assigned
Download :
  V3I1207.pdf
Refbacks : There are currently no refbacks
Intellectual Property Rights Issues and Challenges of Academic Libraries in Digital Environment
Authors : Firdous Maqbool Mir, ,
Affiliations : Library Assistant, Govt Degree College, Baramulla, Jammu & Kashmir ,India ,193101
Abstract :

af

Intellectual property (IP) has emerged as a key driver in knowledge economy. In the present scenario, IPR awareness is the key to technological innovations and in the emerging knowledge-based economy; the awareness among the creators of information and knowledge about IPR has become essential in the digital environment because in the digital environment it is becoming difficult to prove rights violation whenever they occur. This paper gives an overview of intellectual property rights (IPR) issues & challenges in digital environment and the paper deals with the copyright law as well as the role of librarians in the protection of copyright literature. Study also focused on patrons need towards understanding IPR laws in using library services without infringement. With the advancement of technology, Intellectual Property Rights have added new dimensions and there is a strong need for awareness and understanding on Intellectual Property Rights for library patrons.
Citation :

af

Firdous Maqbool Mir, “Intellectual Property Rights Issues and Challenges of Academic Libraries in Digital Environment”, International Journal Of Computer Engineering In Research Trends, 3(12):639-644-,December-2016.
Keywords : : Intellectual Property Rights, IPR, Digital Technology, Copyright.
References :

af

1.	Copyright Office. (2016). About Copyright Government of India. Retrieved November 17th,2016 from
 http://copyright.gov.in/Default.aspx
2.	Dolli, Manoj. (2012). Intellectual property rights: Regulations and trends in India. International Journal of Engineering Research, 3(12), 15-27 Retrieved November 15th , 2016 from
http://www.ijeronline.com/documents/volumes/Vol%203%20issue%202/ijer20120301MA(2).pdf      
3.	Malwad,N.M &Anjanappa,M.(1994). IPR in digital environment: Issues of concern to library community. Retrieved  November 20th , 2016 from
http://ir.inflibnet.ac.in/bitstream/1944/130/1/cali_37.pdf   
4.	Kannan, N. (2010). Importance of Intellectual property rights. International Journal of Intellectual Property Rights, 1(1), 1-5 Retrieved November 16th ,2016 from
http://iaeme.com/MasterAdmin/UploadFolder/IJIPR%20%20Importance%20of%20Intellectual%20Property%20Rights.pdf
5.	Kore, Sayali. C, Jadhav, Shital.T, Kadam, Amruta. S & Chavan, S. ushila. D. (2015). Introduction to Intellectual Property Right. Asian Journal of Pharmacy and Technology,5(4), 222-230.Retrieved November 16th,2016 from
http://www.asianpharmaonline.org/pdf.php?j=2231-5713&vol=5&issue=4&ab=ab176
6.	Sinha, Abhijeet & Bhardwaj, R.K. (2010). Digital Libraries and Intellectual Property Rights. International Conference on Digital Libraries. Retrieved November 15th , 2016 from
https://rajkbhardwaj.files.wordpress.com/2014/02/art-9.pdf    
7.	Rachchh, Manish.A.(2013). Module I- Basics of IPR; Gujarat Technological University. Retrieved November 15th ,2016 from
http://www.gtu.ac.in/circulars/13Aug/Module-1-BasicsofIPR_3rdAug2013.pdf
8.	Sinha, Abhijeet & Bhardwaj, R.K. (2010). Digital Libraries and Intellectual Property Rights. International Conference on Digital Libraries. Retrieved November 15th , 2016 from https://rajkbhardwaj.files.wordpress.com/2014/02/art-9.pdf    
:10.22362/ijcert/2016/v3/i12/xxxx
DOI Link : Not yet assigned
Download :
  V3I1206.pdf
Refbacks : There are currently no refbacks
A Survey of Big Data Analytics in Banking and Health Care today
Authors : P.Siva Kumar, B.Murthujavali, Surya Pogu Jayanna
Affiliations : Asst.Professor,Department of Computer Science and Engineering.,G.Pullaiah College of Engineering & Technology (GPCET), Kurnool
Abstract :

af

This paper gives an perception of how we can disclose added value from the data generated by healthcare and banking sector where Health care Organizations and Financial institutions are making use of Big Data in big ways, from boosting cyber security to reducing customer or Patient churn, cultivating customer or Patient loyalty, and more through innovative and personalized offerings that make effective services. Large amount of heterogeneous data is generated by these organizations. But without proper data analytics methods these data became useless. Big Data Analytics using Hadoop plays an effective role in performing meaningful real-time analysis on the huge volume of data and able to predict the emergency situations before it happens. It describes about the big data use cases in healthcare and banking sectors.
Citation :

af

P.Siva Kumar,B.Murthujavali,Surya Pogu Jayanna”, A Survey of Big Data Analytics in Banking and Health Care today”, International Journal Of Computer Engineering In Research Trends, 3(12):632-638,December-2016.
Keywords : Big Data, Hadoop, Healthcare,Banking, Map-Reduce.
References :

af

1. Yanglin Ren, Monitoring patients via a secure and mobile healthcare system, IEEE Symposium on wireless communication,2011
2. Dai Yuefa, Wu Bo, GuYaqiang ,Data Security Model for Cloud Computing, International Workshop on Information Security and Application,2009
3. Jeffrey Dean and Sanjay Ghemawat,MapReduce: Simplified Data Processing on Large Clusters,ACM,2008
4.Kayyali B, Knott D, Van Kuiken S. The big-data revolution in US health care: accelerating value and innovation. McKinsey & Company. 2013 Apr.   URL: https://digitalstrategy.nl/wp-content/uploads/E2-2013.04-The-big-data-revolution-in-US-health-care-Accelerating-value-and-innovation.pdf [accessed 2016-11-11] [WebCite Cache]
5. Cong Wang, Privacy-Preserving Public Auditing for Secure Cloud Storage,IEEE,2010
6. Konstantin Shvachko, HairongKuang, Sanjay Radia, Robert Chansler ,The Hadoop Distributed File System,IEEE,2010
7. Bill Hamilton, Big Data Is the Future of Healthcare, Cognizant white paper, 2010.
8. White Paper by SAS, How Government are using the Power of High Performance Analytics, 2013.
9. Michael Cooper &Peter Mell, Tackling Big Data Problems, NSIT Computer Security Workshop
10. Jean Yean, Big Data Bigger Opportunities, White Paper, U.S.General Services Administration.
11. Kruse CS, Goswamy R, Raval YJ, Marawi S Challenges and Opportunities of Big Data in Health Care: A Systematic Review JMIR Med Inform 2016;4(4):e38 URL: https://medinform.jmir.org/2016/4/e38 DOI: 10.2196/medinform.5359,   PMID: 27872036  ,PMCID: 5138448.
:10.22362/ijcert/2016/v3/i12/xxxx
DOI Link : Not Yet Assigned
Download :
  V3I1205.pdf
Refbacks : There are currently no refbacks
Selection and Maintenance of Materialized View using Genetic Algorithm
Authors : Ramesh S Gawali, Prof. Mrunali G. Vaidya,
Affiliations : BIT Ballarpur Gondwana University ,India
Abstract :

af

Data warehouse is a repository of large amount of data collected from multiple heterogeneous and distributed data sources. Quick response time and accuracy are the key points for success of any database. Performance of query can be improved by different approaches like query optimization, use of proper data structure etc. But leaving all these alternatives we are planning to use materialized view approach
Citation :

af

Ramesh S Gawali, ,Prof. Mrunali G. Vaidya," Selection and Maintenance of Materialized View using Genetic Algorithm”, International Journal Of Computer Engineering In Research Trends, 3(12):629-631,December-2016.
Keywords : data ware house, materialized view, optimization Query.
References :

af

 [1]Dr.T.Nalini, Dr.A.Kumaravel , Dr.K.Rangarajan,”A Novel Algorithm with IM-LSI Index For Incremental Maintenance of Materialized View” JCS&T Vol. 12 No. 1 April 2012 
[2] B.Ashadevi, R.Balasubramanian,” Cost Effective Approach for Materialized Views Selection in Data Warehousing Environment”, IJCSNS International Journal of Computer Science and Network Security, VOL.8 No.10, October 2008 
[3] Gupta, H. & Mumick, I., Selection of Views to Ma-terialize in a Data Warehouse. IEEE Transactions on Knowledge and Data Engineering, 17(1), 24-43, 2005. 
[4] Yang, J., Karlapalem. K., and Li. Q. (1997). A framework for designing materialized views in a data warehousing environment. Proceedings of the Seven-tieth IEEE International Conference on Distributed Computing systems, USA, pp:458
[5] V.Harinarayan, A. Rajaraman, and J. Ullman.“Implementing data cubes efficiently”. Pro-ceedings of ACM SIGMOD 1996 International Confer-ence on Management of Data, Montreal, Canada, pages 205--216, 1996. 
[6] A. Shukla, P. Deshpande, and J. F. Naughton, “Ma-terialized view selection for the multidimensional da-tasets,” in Proc. 24th Int. Conf. Very Large Data Bases, 1998, pp. 488–499. 
[7] Y.D. Choudhari and Dr. S. K. Shrivastava, “Cluster Based Approach for Selection of Materialized Views”, International Journal of Advanced Research in Com-puter Science and Software Engineering ,Volume 2, Issue 7, July 2012 

:10.22362/ijcert/2016/v3/i12/xxxx
DOI Link : Not yet assigned
Download :
  V3I1204.pdf
Refbacks : There are currently no refbacks
Secure Data Communication Using IDEA for Decentralized Disruption-Tolerant Military Networks
Authors : Atish D.  Buddhe , Prof. Hirendra R. Hajare,
Affiliations : BIT Ballarpur Gondwana University ,India
Abstract :

af

Nowadays Disruption tolerant network technologies are getting to be distinctly well known that permit wireless devices supported by soldiers to communicate with each other and access the confidential information or command consistently by abusing external storage nodes. The absolute most challenging issues in this scenario are the enforcement of authorization policies and the policies update for secure data retrieval. Ciphertext-policy attribute-based encryption is a promising cryptographic solution to the access control issues. However, the problem of applying CP-ABE in decentralized DTNs introduces several security and privacy challenges with regard to the attribute revocation, key escrow, and coordination of attributes issued from different authorities. We propose a secure data retrieval scheme using IDEA for decentralized DTNs where multiple key authorities manage their attributes independently. We demonstrate how to apply the proposed mechanism to productively deal with the classified information conveyed in the distributed in the disruption-tolerant military network.
Citation :

af

Atish Budhhe, Prof. Hirendra R. Hajare ," Secure Data Communication Using IDEA for Decentralized Disruption-Tolerant MilitaryNetworks”, International Journal Of Computer Engineering In Research Trends, 3(12):625-628,December-2016.
Keywords : — CP-ABE, Access control, attribute-based encryption (ABE), Dsruption-tolerant network (DTN), IDEA, multiauthority, secure data retrieval.
References :

af

[1] J. Burgess, B. Gallagher, D. Jensen, and B. N. Levine, “Maxprop: outing for vehicle-based disruption tolerant networks,” in Proc.IEEE INFOCOM, 2006, pp. 1–11.
[2] M. Chuah and P. Yang, “Node density-based adap-tive routing scheme for disruption tolerant networks,” in Proc. IEEE MILCOM, 2006, pp.1,6.
[3] M. M. B. Tariq, M. Ammar, and E. Zequra, “Mesage ferry route design for sparse ad hoc networks with mobile nodes,” in Proc. ACM MobiHoc, 2006, pp. 37–48.
[4] S. Roy andM. Chuah, “Secure data retrieval based on ciphertext policy attribute-based encryption () system for the DTNs,” Lehigh CSE Tech. Rep., 2009.
[5] M. Chuah and P. Yang, “Performance evaluation of content-based information retrieval schemes for DTNs,” in Proc. IEEE MILCOM,2007, pp. 1–7.
[6] M. Kallahalla, E. Riedel, R. Swaminathan, Q. Wang, and K. Fu, “Plutus: Scalable secure file sharing on un-trusted storage,” in Proc. Conf. File Storage Technol., 2003, pp. 29–42.
:DOI:10.22362/ijcert/2016/v3/i12/xxxx
DOI Link : Not Yet Assigned
Download :
  V3I1203.pdf
Refbacks : There are currently no refbacks
Intelligent XML Query-Answering Support with Efficiently Updating XML Data in Data Mining
Authors : Parag Zaware, Prabhudev.I,
Affiliations : Vishwabharati Academy College of Engineering, Ahmednagar
Abstract :

af

Data is present in various unstructured format. Extracting information from non structured documents is a very difficult task and it is become more and more critical when the amount of digital information available over the internet increases. This paper is based on design of Branch Organization Rule (BOR) results in approximate answer of queries for mining. XML is popular portable language best suitable for many web technologies hence we prefer XML. While implementing XML Query Answering we are going to implement Naïve Bayes as Machine learning algorithm which we will use specially for Query Classification. We are also implementing same concept for rules classifications by using which the trees are generated after applying queries. Due to creating classification of queries our accuracy of results will increase.
Citation :

af

Parag Zaware,Prabhudev.I," Intelligent XML Query-Answering Support with Efficiently Updating XML Data in Data Mining”, International Journal Of Computer Engineering In Research Trends, 3(12):613-619,December-2016.
Keywords : XML, Mining, query answer, Machine Learning.
References :

af

[1] Mirjana Mazuran, Elisa Quintarelli, and Letizia Tanca “Data Mining for XML Query-Answering Support”, IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, VOL. 24, NO. 8, AUGUST 2012


[2]A. Evfimievski, R. Srikant, R. Agrawal, and J. Gehrke, 
“Privacy Preserving Mining of Association Rules,” Proc. Eighth ACM Int’l Conf. Knowledge Discovery and Data Mining, pp. 217-228, 2002.
 
[3]C. Combi, B. Oliboni, and R. Rossato, “Querying XML 

Documents by Using Association Rules,” Proc. 16th Int’l Conf. Database and Expert Systems Applications, pp. 1020-1024, 2005

[4]D. Braga, A. Campi, S. Ceri, M. Klemettinen, and P. Lanzi, “Discovering Interesting Information in XML Data with Asso-ciation Rules,” Proc. ACM Symp. Applied Computing, pp. 450-454, 2003. 


[5]D. Barbosa, L. Mignet, and P. Veltri, “Studying the XML 
Web: Gathering Statistics from an XML Sample,” World Wide Web, vol. 8, no. 4, pp. 413-438, 2005.



[6]E. Baralis, P. Garza, E. Quintarelli, and L. Tanca, “Answer-ingXMLQueries	by Means of Data Summaries,” ACM Trans.InformationSystems, vol. 25, no. 3, p. 10, 2007.


[7]L. Feng, T.S. Dillon, H. Weigand, and E. Chang, “An 
XMLEnabled Association Rule Framework,” Proc. 14th Int’l Conf. Database and Expert Systems Applications, pp. 88-97, 2003. 

[8] World Wide Web Consortium, XML Schema, http://
www.w3C.org/TR/xmlschema-1/, 2001.

[9]Chai, K.; H. T. Hn, H. L. Chieu; “Bayesian Online Classifiers for Text Classification and Filtering”, Proceedings of the 25th annual international ACM SIGIR conference on Research and Development in Information Retrieval, August 2002.

[10] DATA MINING Concepts and Techniques, Jiawei Han, Micheline Kamber Morgan Kaufman Publishers, 2003
:10.22362/ijcert/2016/v3/i12/xxxx
DOI Link : Not Yet Assigned
Download :
  V3I1202.pdf
Refbacks : There are currently no refbacks
Indoor Environment Navigation for Blind with Voice Feedback
Authors : Parimal A. Itankar, Prof. Hirendra R. Hajare ,
Affiliations : BIT Ballarpur Gondwana University ,India
Abstract :

af

this paper presents assistive system for visually impaired with voice feedback which focuses on independent movement of blind people who suffer in an unknown environment with no assistance. This system has Radio Frequency Identification (RFID) for the path guidance identifying certain paths for the navigation which give features such as location identification. This proposed system on the user side include a RFID reader module with an integrated microcontroller, zigbee transceiver for transmitting the tag’s information and for playing information to the blind person were on the server side zigbee transceiver for communication. For the direction identification technique, RFID passive tag is employed on the path and for location recognition required tools and r building will be embedded with passive RFID tags. A data unique to each object and path location is on the server. The RFID reader reads the RFID tags and transmits the data by Zigbee to the server PC which in turn locates for the received Tag ID in the database and gives respond to the user with its identification data which is played at the blind person side by converting it from text to speech with the help of SAPI module.
Citation :

af

Parimal A. Itankar, Prof. Hirendra R. Hajare ," Indoor Environment Navigation for Blind with Voice Feedback”, International Journal Of Computer Engineering In Research Trends, 3(12):609-612,December-2016.
Keywords : Radio frequency identification (RFID), zigbee, Tag ID, server PC, wireless, database, SAPI module. .
References :

af

[1]. Abdullah Rehman, MohsinMurad, Arif Ali Shah, Sal-imUllah, Muhammad Fahad, Khawaja M. Yahya , ''RFAIDE--An RFID Based Navigation and Object Recogni-tion Assistant for Visually Impaired People'', University of Engineering and Technology, Peshawar, Pakistan, 978-1-4577-0768-1/11/2011 IEEE. 
[2]. Andreas Hub, Joachim Diepstraten, Thomas Ertl, ''De-sign and Development of an Indoor Navigation and Object Identification System for the Blind'', Visualization and Interactive Systems Institute University of Stuttgart. 
[3]. Abdelsalam (Sumi) Helal, Steven Edwin Moore, Balaji Ramachandran, ''Drishti: An Integrated Navigation System for Visually Impaired and Disabled'', University of Florida,Gainesville, FL-32611. 
[4]. Guth, D.A.; Rieser, J.J. ''Perception and the control of locomotion by blind and visually impaired pedestrians''. Foundations of Orientation and Mobility, (Second Edition), AFB Press, pp. 9-38, 1997. 
[5]. H. Mori, S. Totani, ''Robotic Travel Aid for the Blind: HARUNOBU-6''. In Proceedings of the Second European Conference On Disability, Virtual Reality, and Assistive Technology, Sövde, Sweden, 1998. 
[6]. Jenny Crave, Research Fellow, ''Access to electronic resources by visually impaired people'', CERLIM, Manchester Metropolitan University, UK, Information Research, Vol. 8 No. 4, July 2003. 
[7]. Jinying Chen, Xuben Wang, Zhi Li, Min Dong, ''Blind Path Identification System Design Base on RFID'', 2010 International Conference on Electrical and Control Engineering. 
[8]. L. W. Alonzi, D. C. Smith, G. J. Burlak, M. Mirowski, (1992). ''Radio frequency message apparatus for aiding ambulatory travel of visually impaired persons'', U.S. Patent 5,144,294 issued Sept. 1, 1992. 
[9]. M.B. Hancock, ''Electronic auto routing navigation system for visually impaired persons''. U.S. Patent 5,806,017 issued September 8, 1998. 
[10]. P.Bahl andV.Padmanabhan, “Radar: An In-Building RF–Based User Location andTracking system”, InProceed-ingsofthe IEEE INFOCOM 2000, MARCH 2000, PP775-784.
:DOI:10.22362/ijcert/2016/v3/i12/xxxx
DOI Link : Not yet assigned
Download :
  V3I1201.pdf
Refbacks : There are currently no refbacks

 

A Multilevel Scoring Mechanism to Compute Top - K Routing Plans for a Keyword Query
Authors : Mr Bharath Reddy, Mr. Manas Kumar Yogi, Grandhi Satya Suneetha
Affiliations : Dept of CSE, Pragati Engineering College, Kakinada. Andhra Pradesh, India
Abstract :

af

In recent years Keyword search over database is explored. For information retrieval keyword query used, but due to ambiguity of multiple queries over database should be explored. while getting multiple result to keyword query we need effective crawlers, if search engine might be give multiple result to the single query then computation of all the these results and suggesting best one among all result defined as problem statement. In this paper, the label ranking system over unpredictable is presented. The Keyword directing strategy is utilized to course the catchphrases to significant source. In this methodology two techniques are incorporated. If user gives a keyword query to the search engine then the search engine should process the query and returns the appropriate result based rank. The result construction done based on R-Tree and it allows NN queries should be computed and based on I-Index we will construct the score for each NN query result.
Citation :

af

Bharath Reddy et.al," A Multilevel Scoring Mechanism to Compute Top - K Routing Plans for a Keyword Query”, International Journal of Computer Engineering In Research Trends, 3(11):602-608,November-2016.
Keywords : Keyword searching, Uncertain graph, algorithm, Keyword routing, graph data, Keyword query
References :

af

[1] Wangchao Le, Feifei Li, Anastasios Kementsietsidis, Songyun Duan, Scalable Keyword Search on Large RDF Data", IEEE2013.
 [2] George Kollios, Michalis Potamias, and EvimariaTerzi, Clustering Large Probabilistic Graphs, IEEE vol. 25, NO. 2, February 2013
 [3] Ye Yuan, Guoren Wang, Lei Chen, and HaixunWang, Efficient Keyword Search on Uncertain Graph Data, IEEE vol. 25, no. 12, December 2013.
 [4] Jun Gao, Jiashuai Zhou, Jeffrey Xu Yu, and TengjiaoWang, Shortest Path Computing in Relational DBMSs, IEEE vol. 26, no. 4, April 2014.
 [5] ZhaonianZou, Jianzhong Li, Member, IEEE, Hong Gao, and Shuo Zhang, Mining Frequent Subgraph Patterns from Uncertain Graph Data‖, IEEE vol. 22, no. 9, September 2010.
 [6] Lifang Qiao, Yu Wang, A Keyword Query Method for Uncertain Database‖, 2nd International Conference on Computer Science and Network Technology, IEEE, 2012.
 [7] Bolin Ding, Jeffrey Xu Yu, Shan Wang, Lu Qin, Xiao Zhang, Xuemin Lin,‖ Finding Top-k Min-Cost Connected Trees in Databases‖, IEEE 1- 4244-0803-2/07/2007.
 [8] Thanh Tran and Lei Zhang, ‖ Keyword Query Routing‖, IEEE vol. 26, no. 2, February2014.
 [9] Ye Yuan, Guoren Wang, Haixun Wang, Lei Chen,‖ Efficient Subgraph Search over Large Uncertain Graphs‖. In Proceedings of the VLDB Endowment, Vol. 4,pp. 876-886, 2011.
 [10] Hao He, Haixun Wang, Jun Yang, Philip S. Yu,‖ BLINKS: Ranked Keyword Searches on Graphs‖, SIGMOD'07, June 2007. 
[11]Haoliang Jiang, HaixunWang, Philip S. Yu, and Shuigeng Zhou GString: A novel approach for efficient search in graph databases. In ICDE, 2007.
 [12] DennisShasha, Jason T.L.Wang, and RosalbaGiugno. Algorithmics and applications of tree and graph searching. In PODS, pages 39–52, 2002.
[13] Xifeng Yan, Philip S. Yu, and Jiawei Han. Substructure similarity search in graph databases. In SIGMOD, pages 766–777, 2005.
 [14] Branimir T. Todorovic, Svetozar R. Rancic, Ivica M. Markovic, Eden H. Mulalic, Velimir M. Ilic, ―Named Entity Recognition and Classification using Context Hidden Markov Model,‖ 9th Symposium on Neural Network Application in Electrical Engineering, NEUREL, pp. 43-46, 2008.
 [15] Dekai Wu, Weifeng Su and Marine Carpuat, ―A Kernel PCA Method for Superior Word Sense Disambiguation,‖ Proceedings of the 42nd Meeting of the Association for Computational Linguistics, pp. 637-644, 2004.
 [16]AbdelazizZitouni, AsmaDamankesh, ForooghBarakati, Maha Atari, Mohamed Watfa, FarhadOroumchian, ―Corpus-based Arabic Stemming Using N-grams,‖ Asia Information Retrieval Symposium - AIRS, vol. 6458, pp. 280-289, 2010.
 [17] Hassan Mohamed, Nazlia Omar, MohdJuzaidinAb Aziz, ―Statistical Malay Part-of-Speech (POS) Tagger using Hidden Markov Approach,‖ International Conference on Semantic Technology and Information Retrieval, pp. 231-236, June 2011.
:10.22362/ijcert/2016/v3/i11/1212
DOI Link : NA
Download :
  V3I1107.pdf
Refbacks : There are currently no refbacks
Parametric Optimization of Rectangular Beam Type Load Cell Using Taguchi Method
Authors : D.M. Kalai, V.A.Kamble, A.M.Rathod and B. K. Khot
Affiliations : Department. Of Mechanical Engineering DKTE’s TEI, Ichalkaranji, Maharashtra, India
Abstract :

af

In this work, Rectangular beam type load cell is considered for stress and strain analysis by using finite element method. The stress analysis is carried out to minimize the weight of Rectangular beam- type load cell without exceeding allowable stress. The intention of the work is to create the geometry of Rectangular beam-type load cell to find out the optimum solution. FEM software HyperWorks11.0.0.39 is using for parametric optimization of Rectangular beam type load cell. If the stress value is within the permissible range, then certain dimensions will be modified to reduce the amount of material needed. The procedure will be repeated until design changes satisfying all the criteria. Experimental verification will be carried out by photo-elasticity technique with the help of suitable instrumentation like Polariscope. Using Photo-elasticity technique, results are crosschecked which gives results very close to FEM technique. Experimental results will be compared with FEM results. With the aid of these tools the designer can develop and modify the design parameters from initial design stage to finalize basic geometry of load cell.
Citation :

af

D.M. Kalai et.al," Parametric Optimization of Rectangular Beam Type Load Cell Using Taguchi Method”, International Journal of Computer Engineering In Research Trends, 3(11):596-601,November-2016.
Keywords : Strain gauge, Load cell, Sensitivity, optimization, Volume, Taguchi, FEM.
References :

af

[1]	“Use of FEM and Photo elasticity for shape optimization of ‘S’ type load cell”; Mr. V. A. Kamble, Mr. P. N. Gore; International Journal of Science and Technology, Volume 5, Issue 3; March 2012.
[2]	“Shape Optimization of ‘S’ Type Load Cell Using Finite Element Method”; Mr. S. M Ghanvat, Prof. S. G. Patil; International Journal of Engineering Innovation & Research Volume 1, Issue 3; 2012.
[3]	“Stress Analysis of Crane Hook and Validation by Photo-Elasticity”; Rashmi Uddanwadiker; Scientific Research Engineering; Sept.2011.
[4]	“Finite Element Analysis and Optimization of a Beam Type Load Cell for an External Balance Design”; Ankit Soni, Pankaj Priyadarshi; Indian Institute of Space Science and Technology, Trivandrum; 2010.
[5]	“Performance Evaluation of Strain Gauge Based Load Cell to Improve Weighing Accuracy”; Prof. Kamlesh H. Thakkar, Prof. Vipul. M. Prajapati, Prof. Bipin D. Patel; International Journal of Latest Trends in Engineering and Technology (IJLTET), vol. 2; 2013.
[6]	“Measurement Systems, Application and Design”; Earnest Doebelin; Tata McGraw Hill, Page 438-446; 2009.

B.  BOOKS
[1]	“Experimental Stress Analysis”; James W. Dally, William F. Riley; Tata McGraw Hill; 1991.
[2]	“Experimental Stress Analysis”; Dr. Sadhu Singh; Khanna Publications; Fourth edition; 2009.

C. MANUALS
[1]	ADI ARTECH Transducers Pvt. Ltd.
 

:under process
DOI Link : Not yet assigned
Download :
  V3I1106.pdf
Refbacks : There are currently no refbacks
Robust Resource Allocation in Relay Node Networks for Optimization Process
Authors : G.Lalitha, Lakshmi Viveka K, Leelavathy Narkedamilly
Affiliations : Dept of CSE, Pragati Engineering College, Kakinada
Abstract :

af

Overlay steering has risen as a promising way to deal with enhances unwavering quality and effectiveness of the Internet. For one-jump overlay source steering, when a given essential way experiences the connection disappointment or execution debasement, the source can reroute the movement to the destination by means of a deliberately set transfer hub. Be that as it may, the over-substantial activity going through the same transfer hub may bring about incessant bundle misfortune and postponement jitter, which can corrupt the throughput and usage of the system. To defeat this issue, we propose a Load-Balanced One-jump Overlay Multipath Routing calculation (LB-OOMR), in which the activity is first part at the source edge hubs and afterward transmitted along numerous one-bounce overlay ways. So as to decide an ideal split proportion for the activity, we plan the issue as a direct programming (LP) definition, whose objective is to minimize the more regrettable case system blockage proportion. Since it is hard to take care of this LP issue in commonsense time, a heuristic calculation is acquainted with select the transfer hubs for building the disjoint one-jump overlay ways, which enormously lessens the computational multifaceted nature of the LP calculation. Reproductions in light of a genuine ISP system and an engineered Internet topology demonstrate that our proposed calculation can diminish the system clog proportion significantly, and accomplish top notch overlay directing administration.
Citation :

af

G.Lalitha et.al," Robust Resource Allocation in Relay Node Networks for Optimization Process”, International Journal of Computer Engineering In Research Trends, 3(11):589-595,November-2016.
Keywords : Relay Node Networks ,One-jump Overlay Multipath Routing ,OVERLAY ROUTING
References :

af

[1] D. G. Andersen, H. Balakrishnan, M. F. Kaashoek, and R. Morris, “Resilient overlay networks,” Proceedings of SOSP 2001, Oct. 2001.
 [2] S. Banerjee, C. Kommareddy, K. Kar, B. Bhattacharjee, and S. Khuller, “Construction of an efficient overlay multicast infrastructure for real-time applications,” Proceedings of INFOCOM 2003, April 2003.
 [3] D. G. Andersen, A. C. Snoeren, and H. Balakrishnan, “Best-path vs. multi-path overlay routing,” Proceedings of IMC 2003, Oct. 2003.
 [4] C.L.T. Man, G. Hasegawa, and M. Murata, “Monitoring overlay path bandwidth using an inline measurement technique,” IARIA International Journal on Advances in Systems and Measurements, vol.1, no.1, pp.50–60, Feb. 2008. 
[5] P. Rodriguez, S.M. Tan, and C. Gkantsidis, “On the feasibility of commercial, legal P2P content distribution,” SIGCOMM Computer Communication Review, vol.36, no.1, pp.75–78, Jan. 2006.
[6] S. Seetharaman and M. Ammar, “Characterizing and mitigating inter-domain policy violations in overlay routes,” Proceedings of ICNP 2006, pp.259–268, Nov. 2006.
 [7] T. Karagiannis, P. Rodriguez, and K. Papagiannaki, “Should Internet service providers fear peer-assisted content distribution?,” Proceedings of IMC 2005, pp.6–6, Oct. 2005. 
[8] IETF ALTO Working Group web site. available at http:// datatracker.ietf.org/wg/alto/.
 [9] H. Xie, Y. R. Yang, A. Krishnamurthy, Y. G. Liu, and A. Silberschatz, “P4P: Provider portal for applications,” SIGCOMM Computer Communication Review, vol.38, no.4, pp.351–362, Oct. 2008. 
[10] Planet Lab web site. available at http://www.planet-lab.org/. 
[11] G. Hasegawa, Y. Hiraoka, and M. Murata, “Effectiveness of overlay routing based on delay and bandwidth information,”  
[12] S. J. Lee, S. Banerjee, P. Sharma, P. Yalagandula, and S. Basu, “Bandwidth-aware routing in overlay networks,” Proceedings of INFOCOM 2008, pp.1732–1740, April 2008. 
[13] G. Smaragdakis, V. Lekakis, N. Laoutaris, A. Bestavros, J.W. Byers, and M. Roussopoulos, “EGOIST: overlay routing using selfish neighbor selection,” Proceedings of CoNEXT 2008, pp.1–12, Dec. 2008.
 [14] Z. Li and P. Mohapatra, “QRON: QoS-aware routing in overlay networks,” IEEE Journal on Selected Areas in Communications, vol.22, no.1, pp.29–40, Jan. 2004.
[15] M. Kamel, C. Scoglio, and T. Easton, “Optimal topology design for overlay networks,” Proceedings of NETWORKING 2007, pp.714– 725, May 2007.
[16] R. Cohen and D. Raz, “Cost effective resource allocation of overlay routing relay nodes,” Proceedings of INFOCOM 2011, 2011.
:under process
DOI Link : Not yet assigned
Download :
  V3I1105.pdf
Refbacks :
A Survey on: Sound Source Separation Methods
Authors : Ms. Monali R. Pimpale, Prof. Shanthi Therese , Prof. Vinayak Shinde,
Affiliations : Department of Computer Engineering, Mumbai University, Shree L.R. Tiwari College of Engineering and Technology,Mira Road, India.
Abstract :

af

now a day’s multimedia databases are growing rapidly on large scale. For the effective management and exploration of large amount of music data the technology of singer identification is developed. With the help of this technology songs performed by particular singer can be clustered automatically. To improve the Performance of singer identification the technologies are emerged that can separate the singing voice from music accompaniment. One of the methods used for separating the singing voice from music accompaniment is non-negative matrix partial co factorization. This paper studies the different techniques for separation of singing voice from music accompaniment.
Citation :

af

Monali R. Pimpale," A Survey on: Sound Source Separation Methods”, International Journal of Computer Engineering In Research Trends, 3(11):580-584,November-2016
Keywords : singer identification, non-negative matrix partial co factorization
References :

af

[1] Tuomas Virtanen ,”Unsupervised Learning Methods for Source Separation in Monaural Music Signals” Tuomas Virtanen

[2] T. Virtanen, “Monaural sound source separation by nonnegative matrix factorization with temporal continuity and sparseness criteria,” IEEE Trans. Audio, Speech, Lang. Process., vol. 15, no. 3, pp. 1066–1074,Mar. 2007.

[3] J. Yoo et al., “Nonnegative matrix partial co-factorization for drum source separation,” in Proc. IEEE Int. Conf. Acoust. Speech, Signal Process., 2010, pp. 1942 1945.

[4] M. Kim et al., “Nonnegative matrix partial co-factorization for spectral and temporal drum source separation,” IEEE J. Sel. Topics Signal Process., vol. 5, no. 6, pp. 1192–1204, Dec. 2011.

[5] Y. Hu and G. Z. Liu, “Singer identification based on computational auditory scene analysis and missing feature methods,” J. Intell. Inf. Syst., pp. 1–20, 2013.

[6] McAulay, Robert J., and Thomas F. Quatieri. "Pitch estimation and voicing detection based on a sinusoidal speech model." Acoustics, Speech, and Signal Processing, 1990. ICASSP-90., 1990 International Conference on. IEEE, 1990.

 [7] T. Virtanen, A. Mesaros, and M. Ryynanen, “Combining pitch-based inferenceandnon-negative spectrogram factorization in separating vocals from polyphonic music,” in Proc. ISCA Tutorial Res. Workshop Statist. Percept. Audit. (SAPA), 2008

[8] Zafar Rafii and Bryan Pardo, “REpeating Pattern Extraction Technique (REPET): A Simple Method for Music/Voice Separation”, IEEE Transactions on Audio, Speech, and Language Processing, vol. 21, no. 1, pp. 71 – 82, January 2013.

[9] Ying Hu and Guizhong Liu, “Separation of Singing Voice Using Nonnegative Matrix Partial CoFactorization for Singer Identification”, IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 23, no. 4, pp. 643 – 653, April 2015.   
[10] Yipeng Li, DeLiang Wang, Separation of Singing Voice from Music Accompaniment for Monaural Recordings, IEEE Transactions on Audio, Speech, and Language Processing,v.15 n.4, p.1475-1487, May 2007.

 [11] Virtanen, Tuomas. "Sound source separation using sparse coding with temporal continuity objective." Proc. ICMC. Vol. 3. 2003.

 [12] ICASSP 2007 Tutorial - Audio Source Separation based on Independent Component Analysis Shoji Makino and Hiroshi Sawada (NTT Communication Science Laboratories, NTT Corporation)

[13] Makino, Shoji, et al. "Audio source separation based on independent component analysis." Circuits and Systems, 2004. ISCAS'04. Proceedings of the 2004 International Symposium on. Vol. 5. IEEE, 2004.

[14] Virtanen, Tuomas. "Separation of sound sources by convolutive sparse coding." ISCA Tutorial and Researc Workshop (ITRW) on Statistical and Perceptual Audio Processing. 2004.

[15] Non-negative matrix factorization based compensation of music for automatic speech recognition, Bhiksha Raj, T. Virtanen, Sourish Chaudhure, Rita Singh, 2010.

[16] Reynolds, Douglas A., Thomas F. Quatieri, and Robert B. Dunn. "Speaker verification using adapted Gaussian mixture models." Digital signal processing 10.1 (2000): 19-41.

[17] Hochreiter, Sepp, and Michael C. Mozer. "Monaural separation and classification of mixed signals: A support-vector regression perspective." 3rd International Conference on Independent Component Analysis and Blind Signal Separation, San Diego, CA. 2001.
:under process
DOI Link : Not yet assigned
Download :
  V3I1103.pdf
Refbacks : There are currently no refbacks
Software Engineering Domain Knowledge to Identify Duplicate Bug Reports
Authors : Dr.J.KEZIYA RANI, ,
Affiliations : ASST.PROFESSOR, DEPT.OF.CS&T, S.K.UNIVERSITY, ANANTHAPURAMU.
Abstract :

af

Earlier, many methodologies was proposed for detecting duplicate bug reports by comparing the textual content of bug reports to subject-specific contextual material, namely lists of software-engineering terms, such as non-functional requirements and architecture keywords. When a bug report includes a word in these word-list contexts, the bug report is measured to be linked with that context and this information is likely to improve bug-deduplication methods. Here, we recommend a technique to partially automate the extraction of contextual word lists from software-engineering literature. Evaluating this software-literature context technique on real-world bug reports creates useful consequences that indicate this semi-automated method has the potential to significantly decrease the manual attempt used in contextual bug deduplication while suffering only a minor loss in accuracy.
Citation :

af

Dr.J.KEZIYA RANI," Software Engineering Domain Knowledge to Identify Duplicate Bug Reports”, International Journal of Computer Engineering In Research Trends, 3(11):585-588,November-2016.
Keywords : software literature; duplicate bug reports; information retrieval; machine learning; documentation.
References :

af

[1]	P. Runeson, M. Alexandersson, and O. Nyholm, “Detection of duplicate defect reports using natural language processing,” in Software Engineer-ing, 2007. ICSE 2007. 29th International Conference on. IEEE, 2007, pp. 499–510.

[2]	C. Sun, D. Lo, X. Wang, J. Jiang, and S.-C. Khoo, “A discriminative model approach for accurate duplicate bug report retrieval,” in Pro-ceedings of the 32nd ACM/IEEE International Conference on Software Engineering-Volume 1. ACM, 2010, pp. 45–54.

[3]	C. Sun, D. Lo, S.-C. Khoo, and J. Jiang, “Towards more accurate retrieval of duplicate bug reports,” in Proceedings of the 2011 26th IEEE/ACM International Conference on Automated Software Engineering. IEEE Computer Society, 2011, pp. 253–262.

[4]	A. Alipour, A. Hindle, and E. Stroulia, “A contextual approach towards more accurate duplicate bug report detection,” in Proceedings of the Tenth International Workshop on Mining Software Repositories. IEEE Press, 2013, pp. 183–192.

[5]	A. Alipour, “A contextual approach towards more accurate duplicate bug report detection,” Master’s thesis, University of Alberta, Fall 2013.

[6]	D. Han, C. Zhang, X. Fan, A. Hindle, K. Wong, and E. Stroulia, “Understanding android fragmentation with topic analysis of vendor-specific bugs,” in Reverse Engineering (WCRE), 2012 19th Working Conference on. IEEE, 2012, pp. 83–92.

[7]	R. S. Pressman and W. S. Jawadekar, “Software engineering,” New York 1992, 1987.

[8]	M. L. Murphy, The Busy Coder’s Guide to Advanced Android Develop-ment. CommonsWare, LLC, 2009.

[9]	N. Klein, C. S. Corley, and N. A. Kraft, “New features for duplicate bug detection.” in MSR, 2014, pp. 324–327.

[10]	N. Bettenburg, R. Premraj, T. Zimmermann, and S. Kim, “Duplicate bug reports considered harmful. . . really?” in Software Maintenance, 2008. ICSM 2008. IEEE International Conference on. IEEE, 2008, pp. 337–345.

[11]	N. Jalbert and W. Weimer, “Automated duplicate detection for bug tracking systems,” in Dependable Systems and Networks With FTCS and DCC, 2008. DSN 2008. IEEE International Conference on. IEEE, 2008, pp. 52–61.

[12]	Y. Dang, R. Wu, H. Zhang, D. Zhang, and P. Nobel, “Rebucket: A method for clustering duplicate crash reports based on call stack similarity,” in Proceedings of the 2012 International Conference on Software Engineering. IEEE Press, 2012, pp. 1084–1093.

[13]	A. Sureka and P. Jalote, “Detecting duplicate bug report using character n-gram-based features,” in Software Engineering Conference (APSEC), 2010 17th Asia Pacific. IEEE, 2010, pp. 366–374.

[14]	A. Lazar, S. Ritchey, and B. Sharif, “Improving the accuracy of duplicate bug report detection using textual similarity measures,” in Proceedings of the 11th Working Conference on Mining Software Repositories. ACM, 2014, pp. 308–311.

[15] A. Kiezun. Basic tutorial eclipse 3.1. [On-line]. Available: http://archive.eclipse.org/eclipse/downloads/drops/R-3. 1-200506271435/org.eclipse.jdt.doc.user.3.1.pdf.zip
[16] Sun Microsystems. (2008) Openoffice.org 3.0 developer’s guide. [Online]. Available:        https://wiki.openoffice.org/w/images/3/34/DevelopersGuide_ OOo3.0.0.odt 
[17]	Mozilla Developer Network and individual contributors. Mozilla developer guide. [Online]. Available: https://developer.mozilla.org/enUS/docs/Mozilla/Developer_guide
:under process
DOI Link : Not yet assigned
Download :
  V3I1104.pdf
Refbacks : There are currently no refbacks
An Image representation using Compressive Sensing and Arithmetic Coding
Authors : Dr. Renuka Devi S M , ,
Affiliations : ECE Dept, GNITS, Hyderbad-500008
Abstract :

af

The demand for graphics and multimedia communication over intenet is growing day by day. Generally the coding efficiency achieved by CS measurements is below the widely used wavelet coding schemes (e.g., JPEG 2000). In the existing wavelet-based CS schemes, DWT is mainly applied for sparse representation and the correlation of DWT coefficients has not been fully exploited yet. To improve the coding efficiency, the statistics of DWT coefficients has been investigated. A novel CS-based image representation scheme has been proposed by considering the intra- and inter-similarity among DWT coefficients. Multi-scale DWT is first applied. The low- and high-frequency subbands of Multi-scale DWT are coded separately due to the fact that scaling coefficients capture most of the image energy. At the decoder side, two different recovery algorithms have been presented to exploit the correlation of scaling and wavelet coefficients well. In essence, the proposed CS-based coding method can be viewed as a hybrid compressed sensing schemes which gives better coding efficiency compared to other CS based coding methods.
Citation :

af

Dr. Renuka Devi S M ," An Image representation using Compressive Sensing and Arithmetic Coding”, International Journal of Computer Engineering In Research Trends, 3(11):573-579,November-2016.
Keywords : Compressive sensing, Discrete wavelet tansform, Tree Structured wavelet CS, Basis Pursuit
References :

af

[1]	Donoho D.L., “Compressed sensing,” IEEE Transac-tions on Information Theory, vol. 52, pp. 1289–1306, 2006.
[2]	Cand`es E. J.  and Wakin M. B. , “An introduction to compressive sampling,” IEEE Signal Processing Magazine, vol. 25, pp. 21–30, 2008.
[3]	Tropp, Joel A., and Stephen J. Wright. "Computational methods for sparse solution of linear inverse problems." Proceedings of the IEEE 98.6 (2010): 948-958. 
[4]	Candès E., Romberg J. and Tao T., “Robust uncertainty principles: Exact signal   reconstruction from highly incomplete frequency information,” IEEE Trans. Inform. Theory, vol. 52,no. 2, pp. 489–509, Feb. 2006.
[5]	J. A. Tropp and A. C. Gilbert, “Signal recovery from random measurements via orthogonal matching pur-suit,” IEEE Transactions on Information Theory, vol. 53, pp. 4655–4666, 2007.
[6]	D. L. Donoho, Y. Tsaig, I. Drori, and J.-L. Starck, “Sparse solution of underdetermined linear equations by stagewise orthogonal matching pursuit,” March 2006, preprint.
[7]	B. Efron, T. Hastie, I. Johnstone, and R. Tibshirani, “Least angle regression,” Annals of Statistics (with discussion), vol. 32,pp. 407–499, 2004.
[8]	[Online]. Available: http://www.cs.ubc.ca/~mpf/spgl1/
[9]	Deng C.W., Lin W. S., Lee B. S. and Lau C. T., “Robust image compression based upon compressive sensing,” in Proc. IEEE Int. Conf. Multimedia and Expo. (IC-ME’10), Jul. 2010, pp. 462–467.
[10]	Ji S. , Xue Y. , and  Carin L., “Bayesian compressive sensing,” IEEE Transactions on Signal Processing, vol. 56, 2008,  pp. 2346–2356.
[11]	Said A. and Pearlman W. A., “A new, fast, and efficient image codec based on set partitioning in hierarchical trees,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 6, 1996,  pp. 243–250.
[12]	Pavithra V, Renuka Devi SMand Ganapathy Reddy Ch , "A survey of robust image coding techniques", IJCA (0975-8887),Volume No 71, No 5,May 2013,pp. 41-51
[13]	Pavithra V, Renuka Devi SM ‘An image representa-tion scheme by hybrid compressive sensing’ IEEE Asia Pacific Conference on Postgraduate Research in Microelectronics and Electronics (PrimeAsia),   19-21 December 2013
:10.22362/ijcert/2016/v3/i11/48908
DOI Link : http://www.dx.doi.org/10.22362/ijcert/2016/v3/i11/48908
Download :
  V3I1102.pdf
Refbacks : There are currently no refbacks
Multiple Encryption using ECC and Its Time Complexity Analysis
Authors : Vishal Kumar, Ratnesh Kumar, Mashud A. Barbhuiya and Monjul Saikia
Affiliations : Department of Computer Science and Engineering North Eastern Regional Institute of Science and Technology Arunachal Pradesh, INDIA
Abstract :

af

Rapid growth of information technology in present era, secure communication, strong data encryption technique and trusted third party are considered to be major topics of study. Robust encryption algorithm development to secure sensitive data is of great significance among researchers at present. The conventional methods of encryption used as of today may not sufficient and therefore new ideas for the purpose are to be design, analyze and need to be fit into the existing system of security to provide protection of our data from unauthorized access. An effective encryption/ decryption algorithm design to enhance data security is a challenging task while computation, complexity, robustness etc. are concerned. The multiple encryption technique is a process of applying encryption over a single encryption process in a number of iteration. Elliptic Curve Cryptography (ECC) is well known and well accepted cryptographic algorithm and used in many application as of today. In this paper, we discuss multiple encryptions and analyze the computation overhead in the process and study the feasibility of practical application. In the process we use ECC as a multiple-ECC algorithm and try to analyze degree of security, encryption/decryption computation time and complexity of the algorithm. Performance measure of the algorithm is evaluated by analyzing encryption time as well as decryption time in single ECC as well as multiple-ECC are compared with the help of various examples.
Citation :

af

Vishal Kumar et al. ," Multiple Encryption using ECC and Its Time Complexity Analysis”, International Journal of Computer Engineering In Research Trends, 3(11):568-572,November-2016.
Keywords : ECC, Koblitz Method, Multiple Encryption, Message Encoding, Decryption etc
References :

af

[1]	Anoop MS “Elliptic Curve Cryptography-An Implementation Guide” anoopms@tataelxsi.co.in.
[2]	Himanshu Gupta and Vinod Kumar Sharma "Multiphase Encryption: A New Concept in Modern Cryptography" IJCTE 2013 Vol.5(4): 638-640 ISSN: 1793-8201 DOI: 10.7763/IJCTE.2013.V5.765 is referred. 
[3]	William Stalling “Cryptography and Network Security” book (fourth edition).
[4]	N. Koblitz. “A Course in Number Theory and Cryptography”, Springer-Verlag, second edition, 1994.
[5]	W. Diffie and M. Hellman, “Exhaustive Cryptanalysis of the NBS Data Encryption Standard”, June 1977, pp. 74-84.
[6]	NIST Special Publication 800-78-2, “Cryptographic Algorithms and Key Sizes for Personal Identity Verification”, February 2010. 
[7]	Darrel Hankerson, Julio Lopez Hernandez, Alfred Menezes, “Software Implementation of Elliptic Curve Cryptography over Binary Fields”, 2000 
[8]	M. Brown, D. Hankerson, J. Lopez, A. Menezes, “Software Implementation of the NIST Elliptic Curves Over Prime Fields”, 2001
[9]	Certicom, “Standards for Efficient Cryptography, SEC 1: Elliptic Curve Cryptography”, Version 1.0, September 2000
[10]	Certicom, “Standards for Efficient Cryptography, SEC 2: Recommended Elliptic Curve Domain Parameters”, Version 1.0, September 2000, 
[11]	Alfred J. Menezes, Paul C. van Oorschot and Scott A. Vanstone, “Handbook of Applied Cryptography”, CRC Press, 1996
[12]	Data Security for e-Transaction. Retrieved on April 12th 2008, from Weblink: http://www.comp.nus.edu.sg/~jervis /cs3235/set.html
[13]	Ralph C. Merkle, Martin E. Hellman, “On the Security of Multiple Encryption, A technical note on Programming Technique & Data Structure” published in ACM, 1981, Volume 24, Number 7.
[14]	M. Saikia, S.J. Bora, Md. A. Hussain “A Review on Applications of Multimedia Encryption” in ISBN: 987-81-8487-088-6 in national conference on Network Security- issues 2010, Tezpur University
[15]	Vandana Thakur, Monjul Saikia "Comprehensive Survey of Multimedia Encryption Techniques" 26th National Conv. of Comp. Eng. held at the IEI (India), Assam February 4, 2012
[16]	Boruah, Debabrat; Saikia, Monjul, "Implementation of ElGamal Elliptic Curve Cryptography over prime field using C," International Conference on Information Communication and Embedded Systems (ICICES), 2014, vol., no., pp.1,7, 27-28 Feb. 2014
[17]	Kapoor, Vivek, Vivek Sonny Abraham, and Ramesh Singh. "Elliptic curve cryptography." Ubiquity 2008.May (2008): 7.
[18]	Merkle, Ralph C., and Martin E. Hellman. "On the security of multiple encryption." Communications of the ACM 24.7 (1981): 465-467.
[19]	Dahl, Ulf. "Data security system for a database having multiple encryption levels applicable on a data element value level." U.S. Patent No. 6,321,201. 20 Nov. 2001.
[20]	Zhang, Linhua. "Cryptanalysis of the public key encryption based on multiple chaotic systems." Chaos, Solitons & Fractals 37.3 (2008): 669-674.
[21]	Raju, G. V. S., and Rehan Akbani. "Elliptic curve cryptosystem and its applications." Systems, Man and Cybernetics, 2003. IEEE International Conference on. Vol. 2. IEEE, 2003.
[22]	Önen, Melek, and Refik Molva. "Secure data aggregation with multiple encryption." European Conference on Wireless Sensor Networks. Springer Berlin Heidelberg, 2007.
[23]	Bhati, Sunita, Anita Bhati, and S. K. Sharma. "A New Approach towards Encryption Schemes: Byte–Rotation Encryption Algorithm." Proceedings of the World Congress on Engineering and Computer Science. Vol. 2. 2012.
:10.22362/ijcert/2016/v3/i11/48907
DOI Link : http://www.dx.doi.org/10.22362/ijcert/2016/v3/i11/48907
Download :
  V3I1101.pdf
Refbacks : There are currently no refbacks

 

Locating Common Styles Based Totally On Quantitative Binary Attributes Using FP-Growth Algorithm
Authors : RAVULA KARTHEEK, B. SAMPATH BABU, CH. HARI KRISHNA
Affiliations : Assistant professor, Rise Krishna Sai Gandhi Group of Institutions: Ongole,
Abstract :

af

Discovery of frequent patterns from outsized information is taken into account as a crucial facet of data mining. There is always associate degree ever increasing demand to search out the frequent patterns. This paper introduces a technique to handle the categorical attributes associate degree numerical attributes in an economical means. Within the planned methodology, the ordinary database is reborn into quantitative information and thus it's reborn into binary values reckoning on the condition of the coed information. From the binary patterns of all attributes bestowed within the student information, the frequent patterns are known exploitation FP-growth; the conversion reveals all the frequent patterns within the student database.
Citation :

af

RAVULA KARTHEEK et al. ," Locating Common Styles Based Totally On Quantitative Binary Attributes Using FP-Growth Algorithm”, International Journal of Computer Engineering In Research Trends, 3(10):561-567,October-2016.
Keywords : Quantitative attributes, Data mining, FP-growth algorithm, frequent patterns.
References :

af

[1] Bo Wu, Defu Zhang, Qihua Lan, Jiemin Zheng ,An Efficient Frequent Patterns Mining Algorithm based on Apriori Algorithm and the FP-tree Structure Department of Computer Science, Xiamen University, Xiamen 
[2] Lei Want, Xing-Juan Fan2, Xing-Long Lot, Huan Zha Mining data association based on a revised FP-growth Algorithm Proceedings of the 2012 International Conference on Machine Learning and Cybernetics, Xian, 15- 17 July,
[3] R. Agrawal and R. Srikant. Fast algorithms for mining association rules. In VLDBY94, pp. 487-499.
[4] R. Agrawal, T. Imielinski, and A. Swami. Mining association rules between sets of items in large databases. In Proc.1993 ACM-SIGMOD Int. Conf. Management of Data, Washington, D.C., May 1993, pp 207216
[5] A. Savasere, E. Omiecinski, and S. Navathe. An efficient algorithm for mining association rules in large databases. Proceedings of the 21st International Conference on Very large Database,1995.
[6] J.S .Park ,M.S.Chen and P.S.Yu.An effective hash-based algorithm for mining association rules. In SIGMOD1995, pp 175-186.
[7] J. Han, J. Pei, and Y. Yin. Mining Frequent Patterns without Candidate Generation(PDF), (Slides), Proc. 2000 ACM-SIGMOD Int. May 2000.
[8] A.B.M.Rezbaul Islam, Tae-Sun Chung An Improved Frequent Pattern Tree Based Association Rule Mining Techniques Department of Computer Engineering Ajou University Suwon, Republic of Korea
[9] Agarwal R,Aggarwal C,Prasad V V V.A tree projection algorithm for generation of frequent item sets. In Journal of Parallel and Distributed Computing (Special Issue on High-Performance Data Mining),2000
[10] E. Ramaraj and N. Venkatesan, ― Bit Stream Mask Search Algorithm in Frequent Itemset Mining,‖ European Journal of Scientific Research,‖ Vol. 27 No.2 (2009).
[11] Qihua Lan, Defu Zhang, Bo Wu ,A New Algorithm For Frequent Itemsets Mining Based On Apriori And FP-Tree,Department of Computer Science, Xiamen University, Xiamen China 2009 IEEE
:under process
DOI Link : Not yet assigned
Download :</
  V3I1005.pdf