Impact Factor:6.549
 Scopus Suggested Journal: Tracking ID for this title suggestion is: 55EC484EE39417F0

International Journal
of Computer Engineering in Research Trends (IJCERT)

Scholarly, Peer-Reviewed, Open Access and Multidisciplinary




Welcome to IJCERT

International Journal of Computer Engineering in Research Trends. Scholarly, Peer-Reviewed, Open Access and Multidisciplinary

ISSN(Online):2349-7084                 Submit Paper    Check Paper Status    Conference Proposal

Back to Current Issues

Study on PASS: A Parallel Activity-Search System

MADIPADIGA VENKATESH, V .RAMESH, , ,
Affiliations
M.Tech (CS), Department of Computer Science & Engineering
Assistant Professor, Department of Computer Science & Engineering, Sri Indu Institute of Engineering and Technology, R.R Dist Telengana, India
:NOT ASSIGNED


Abstract
In this paper we investigate on set of activities presented via temporal stochastic automata, partitions of activities based on level based events, in this connection our investigation on issues with activity creations on temporal multi-activity graph in order to address this issues as our proposed system how system used PASS architecture with various implementation parts with that coordinates computations across nodes in the cluster and also shown that this algorithms enables to handle both large numbers of observations per second as well as large merged graphs. And also shown Partitioning times vs. TMAG size for different partitioning schemes and TMAG densities (sparseS, dense-D), averaged over number of compute nodes.


Citation
MADIPADIGA VENKATESH,V .RAMESH."Study on PASS: A Parallel Activity-Search System". International Journal of Computer Engineering In Research Trends (IJCERT) ,ISSN:2349-7084 ,Vol.2, Issue 11,pp.785-790, November- 2015, URL :https://ijcert.org/ems/ijcert_papers/V2I1118.pdf,


Keywords : Activity detection, temporal stochastic automata, parallel computation.

References
[1] M. Albanese, V. Moscato, A. Picariello, V. S. Subrahmanian, and O. Udrea, “Detecting stochastically scheduled activities in video,” in Proc. IJCAI, M. M. Veloso, Ed. San Francisco, CA, USA, 2007, pp. 1802– 1807. 
[2] S. Lühr, H. H. Bui, S. Venkatesh, and G. A. W. West, “Recognition of human activity through hierarchical stochastic learning,” in Proc. PerCom., Fort Worth, TX, USA, Mar. 2003, pp. 416–422. 
[3] T. Duong, H. Bui, D. Phung, and S. Venkatesh, “Activity recognition and abnormality detection with the switching hidden semi-Markov model,” in Proc. IEEE CVPR, Washington, DC, USA, 2005. 
[4] T. V. Duong, D. Q. Phung, H. H. Bui, and S. Venkatesh, “Efficient duration and hierarchical modeling for human activity recognition,” Artif. Intell., vol. 173, no. 7–8, pp. 830–856, May 2009. 
[5] R. Hamid, Y. Huang, and I. Essa, “ARGMode activity recognition using graphical models,” in Proc. IEEE CVPR, Madison, WI, USA, 2003.
[6] M. Albanese, S. Jajodia, A. Pugliese, and V. S. Subrahmanian, “Scalable analysis of attack scenarios,” in Proc. ESORICS, Leuven, Belgium, 2011, pp. 416–433.
 [7] M. L. Fredman and R. E. Tarjan, “Fibonacci heaps and their uses in improved network optimization algorithms,” in Proc. FOCS, 1984, pp. 338–346. 
[8] G. Palshikar and M. Apte, “Collusion set detection using graph clustering,” Data Knowl. Eng., vol. 16, no. 1, pp. 135–164, 2008. 
[9] M. Albanese, A. Pugliese, and V. S. Subrahmanian, “Fast activity detection: Indexing for temporal stochastic automaton-based activity models,” IEEE Trans. Knowl. Data Eng., vol. 25, no. 2, pp. 360–373, Feb. 2013.


DOI Link : NOT ASSIGNED

Download :
  V2I1118.pdf


Refbacks : Currently there are no Refbacks

Quick Links



DOI:10.22362/ijcert


Science Central

Score: 13.30





Submit your paper to [email protected]