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Scholarly, Peer-Reviewed, Open Access and Multidisciplinary
International Journal
of Computer Engineering in Research Trends (IJCERT)
Scholarly, Peer-Reviewed, Open Access and Multidisciplinary
International Journal of Computer Engineering in Research Trends. Scholarly, Peer-Reviewed,Open Access and Multidisciplinary
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| Paper Title | : | Ensemble based Model for Diabetes Prediction and COVID-19 Mortality Risk Assessment in Diabetic Patients |
| Authors | : | Dr. Sushma Jaiswal, Ms. Priyanka Gupta, , , |
| Affiliations | : | Guru ghasidas University Koni, Bilaspur (C.G.) |
| Abstract | : | Millions of individuals worldwide suffer from the chronic ailment known as diabetes, which can harm several organs including the kidneys, eyes, and heart arteries. Diabetes patients are those who are most impacted by COVID 19. This study explores the use of machine learning techniques for predicting diabetes and assessing COVID-19 mortality risks for diabetic patients. The study was conducted on a diabetes and covid 19 datasets containing demographic and clinical features of patients. On both the datasets, the machine learning techniques Support Vector Machine, Random Forest, Multilayer perceptron, naïve bayes and Logistic Regression are used. additionally, their combination is employed to improve the performances of the models. The accuracy, precision, recall, and F1-score of these algorithms were evaluated to determine their performance in predicting diabetes and covid 19. By making this enhancement, healthcare services could use less time, labour, and resources while also making decisions with more reliability. The results of the study showed that the ensemble model had the highest accuracy in predicting diabetes and covid 19. The study also found that older age, higher HbA1c levels, and the presence of comorbidities were significant predictors of mortality risk in diabetic patients with COVID-19. The study concludes that machine learning techniques can be useful in predicting diabetes and assessing COVID-19 mortality risks in diabetic patients, and these findings could aid in developing effective preventive and treatment strategies for diabetes and COVID-19. |
 | : | 10.22362/ijcert/2023/v10/i03/v10i0302 |
| DOI Link | : | https://doi.org/10.22362/ijcert/2023/v10/i03/v10i0302 |
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| Paper Title | : | Deep Artificial Neural Network based Blind Color Image Watermarking in YCbCr Color Domain using statistical features |
| Authors | : | Dr. Sushma Jaiswal, Mr. Manoj Kumar Pandey, , , |
| Affiliations | : | CSIT Department, Guru Ghasidas Central University, Bilaspur, CG |
| Abstract | : | A blind color image watermarking using deep artificial neural network (DANN) in YCbCr color model has been proposed aiming at achieving fair trade-off between imperceptibility and robustness. In the proposed watermarking a random generated watermark of length 512 bit is used for the training purpose and original watermark of length 512 bits is used for the testing. Principal component analysis (PCA) is applied to select the best 10 features out of 18 statistical features. Binary classification is used for watermark extraction. It shows the average imperceptibility of 33.34 dB and average SSIM of 0.9860 for four images Lena, Peppers, Mandril and Jet. It performs well in terms of balancing the imperceptibility and robustness, for the threshold value 32. The proposed scheme takes 7.56 seconds for watermark embedding and extraction. It also shows good robustness against common image attacks including the combination of image attacks except the gaussian noise with intensity 0.06 and cropping 20% attacks. The experiment result shows that the proposed watermarking technique performs well against other technique. |
| : | 10.22362/ijcert/2023/v10/i03/v10i0301 |
| DOI Link | : | https://doi.org/10.22362/ijcert/2023/v10/i03/v10i0301 |
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| Paper Title | : | Future of Communication-LIFI (Light Fidelity): A Review |
| Authors | : | Mr. Hilal Ahmad Shah, Mr. Inzimam Ul Hassan, Mr. Inam ul Haq, , |
| Affiliations | : | Chandigarh University |
| Abstract | : | As on date internet has made the revolution in the world. Whether you are using internet in a coffee shop, offices or at home. Speed of the internet is major issue. with the advent of technology, communication became the backbone of ICT. ICT had made our globe like a town. Today everyone (Business, institutions, organizations, entrepreneurs is thrust for getting right information at the right time and right place. Which, requires fast internet connectivity, Technology and large spectrum of channels. Present paper reflects the Future of Communication (LI-FI) which may affect all lives. It a technology that may be as fast as 500MBPS (30GBPS per minute) an alternative, cost effective and more robust and useful than Wi-Fi. The Visible light communication which may be the future of Internet |
| : | 10.22362/ijcert/2023/v10/i02/v10i0202 |
| DOI Link | : | https://doi.org/10.22362/ijcert/2023/v10/i02/v10i0202 |
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| Paper Title | : | A Review on the Innovation of Renewable Energy System |
| Authors | : | Ms. Avril Anne S. Bernal, Mr. Joemark D. Ablian, , , |
| Affiliations | : | Polytechnic College of Botolan |
| Abstract | : | Background/Objectives: The world is at a crucial crossroads, with the choice between continued reliance on non-renewable energy sources and embracing a cleaner, greener future powered by renewable energy. Renewable energy sources such as solar and wind power have been prioritized as the best options for future investment due to their unlimited potential. The research highlights the importance of transitioning towards renewable energy and the need for a comprehensive approach to integrate these sources into energy systems. Methods: This literature review examines and analyse existing research on the innovation of renewable energy system. Findings: This transition is crucial for a sustainable future and a sustainable power system. It has an opportunity to emerge as a leader in sustainable energy solutions by optimizing the integration of solar and wind energy through a cutting-edge scheduling model, dedicating a ministry to renewable energy, phasing out harmful subsidies, and mandating solar energy in housing. To make this transition, it should take a proactive approach, including incentives for private investment in renewable energy projects, promoting research and innovation, developing a comprehensive grid system, partnering with the private sector, and providing training and education programs. The study emphasizes the importance of immediate action and a concerted effort to ensure a sustainable future. The impact of policies and initiatives aimed at optimizing renewable energy integration, phasing out subsidies, and improving building efficiency can be studied to inform future efforts towards a more sustainable energy future. In conclusion, the transition towards renewable energy sources is a critical step towards a sustainable future and plays a significant role in achieving this through a holistic approach. |
| : | 10.22362/ijcert/2023/v10/i02/v10i0201 |
| DOI Link | : | https://doi.org/10.22362/ijcert/2023/v10/i02/v10i0201 |
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| Paper Title | : | Assessing the Performance of Python Data Visualization Libraries: A Review |
| Authors | : | Addepalli Lavanya, Lokhande Gaurav, Sakinam Sindhuja, Hussain Seam, Mookerjee Joydeep, Vamsi Uppalapati, Waqas Ali, Vidya Sagar S.D |
| Affiliations | : | Universidad Politécnica De Valencia, Valencia, Spain |
| Abstract | : | Python is one of the most widely used programming languages for data analysis, visualization, and machine learning. One of Python's key strengths is its rich library ecosystem that provides powerful data visualization tools. Several Python data visualization libraries have emerged in recent years, making it challenging for data analysts and scientists to choose the right library for their visualization needs. Therefore, this research paper aims to assess the performance of Python data visualization libraries and comprehensively review their strengths and limitations. The research paper begins by providing an overview of the most popular Python data visualization libraries, including Matplotlib, Seaborn, Plotly, Bokeh, Altair, and ggplot. We then evaluate each library's performance in terms of its functionality, ease of use, flexibility, and speed.. Additionally, we assess the visual quality of the plots produced by each library and compare them to industry standards. We evaluate the performance of each library by testing them on various datasets and use cases, including large and small datasets, static and interactive visualizations, and different plot types, such as scatter plots, line plots, bar charts, and heatmaps. Our findings suggest that each library has unique strengths and limitations, making choosing one library that fits all visualization needs difficult. However, Matplotlib, Seaborn, and Plotly are the most popular and widely used Python data visualization libraries, each with unique strengths. Matplotlib is a powerful and flexible library that offers a broad range of plotting options, making it ideal for creating complex and customized plots. Seaborn is a high-level library that simplifies the plotting process by providing a consistent interface and easy-to-use functions. Plotly is an interactive visualization library offering rich features for creating web-based visualizations and dashboards. We also find that Bokeh, Altair, and ggplot are less popular but offer unique features and functionality. Bokeh is a library for creating interactive visualizations and dashboards, while Altair is a declarative visualization library that simplifies the plotting process by enabling users to create plots using a simple and intuitive syntax. ggplot is a library that offers a grammar of graphics approach to plotting, making it ideal for users familiar with the R programming language. Overall, this research paper provides a comprehensive review of the most popular Python data visualization libraries and their performance in terms of functionality, ease of use, flexibility, and speed. The findings of this research can help data analysts and scientists choose the a good library for their visualization needs to be based on their specific requirements. Additionally, this research paper can provide a starting point for future research on improving the performance and functionality of Python data visualization libraries. |
| : | 10.22362/ijcert/2023/v10/i01/v10i0104 |
| DOI Link | : | https://doi.org/10.22362/ijcert/2023/v10/i01/v10i0104 |
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| Paper Title | : | Design And Simulation For 8-Shape 2x4 Slotted Array Antenna Using Ultra Wideband Applications |
| Authors | : | G. Shankara Bhaskara Rao, P.V.V Mahesh Kumar, R.P. Trinadh Babu, P. Saranya, Naveen, S.Bhanu Prakash |
| Affiliations | : | 1 Associate Professor 2,3,4,5,6UG Students, Department of Electronics and Communication Engineering .Sri Vasavi Engineering College(Autonomous), Tadepalligudem, Andhra Pradesh, India |
| Abstract | : | This paper presents a detailed study of the design, simulation, and characterization of a 2x4 slotted microstrip patch antenna array. The antenna array is fed by a microstrip transmission line and is designed on an FR4 substrate with dimensions of 130mm×150mm×1.60mm. The antenna is optimized to operate in two different frequency bands, S and C, respectively. The design process of the antenna array involved four iterations, which allowed for an optimal antenna design to be achieved. The proposed antenna exhibits excellent performance, as indicated by its S11 parameter, gain, and VSWR. The S11 parameter, which is a measure of how much power is reflected back from the antenna, is -22.77dB, indicating low levels of reflection and good impedance matching. The gain of the proposed antenna is 8.19dB, which represents the amount of power that is radiated in a specific direction relative to an isotropic radiator. This is a relatively high value and indicates that the proposed antenna has a high efficiency. The VSWR of the proposed antenna is 1.11, indicating good impedance matching and low levels of signal loss. To evaluate the performance of the antenna, S11 parameter, gain plots, and VSWR plots are provided in the paper. These plots demonstrate the antenna's excellent performance in both the S and C frequency bands, making it suitable for a wide range of applications that require high-performance antenna arrays. Overall, the results presented in this paper provide valuable insights into the design and performance of slotted microstrip patch antenna arrays, which could be useful for future research and development in this field. |
| : | 10.22362/ijcert/2023/v10/i01/v10i0103 |
| DOI Link | : | https://doi.org/110.22362/ijcert/2023/v10/i01/v10i0103 |
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| Paper Title | : | A Comprehensive Review of Data Visualization Tools: Features, Strengths, and Weaknesses |
| Authors | : | Addepalli Lavanya, Sakinam Sindhuja, Lokhande Gaurav, Waqas Ali , |
| Affiliations | : | Universidad Politécnica De Valencia, Valencia, Spain |
| Abstract | : | Data visualization tools have revolutionized processing, analysing, and communicating data. With the increasing amount of data available, it has become increasingly important to present data in an easily understandable and visually appealing way. As such, data visualization tools have become essential to data analysis and decisionmaking processes in various fields, including business, healthcare, social sciences, and engineering. This review paper aims to provide an overview of the various data visualization tools available and their features, strengths, and weaknesses. We begin by introducing the concept of data visualization and its importance in the data analysis process. We then provide a brief history of data visualization, highlighting its evolution over time from static charts to interactive and dynamic visualizations. We then discuss the available data visualization tools, including bar charts, line graphs, scatter plots, heat maps, tree maps, and network diagrams. For each type of visualization, we provide examples of when and how they can be used to present and analyse data effectively. Next, we examine the features and functionalities of popular data visualization tools, such as Tableau, Power BI, Google Data Studio, D3.js, and Python libraries like Matplotlib, Seaborn, and Plotly. We discuss the strengths and weaknesses of each tool and provide examples of realworld applications. In addition, we highlight the importance of choosing the right visualization tool based on the data type, audience, and purpose. We also discuss best practices for creating effective data visualizations, such as choosing the right colour scheme, designing for accessibility, and avoiding common pitfalls. Finally, we discuss future trends and developments in data visualization, such as using augmented and virtual reality for data visualization and incorporating machine learning and artificial intelligence in data visualization tools. In conclusion, data visualization tools have become an essential part of the data analysis process. This review paper overviews the available data visualization tools and their features, strengths, and weaknesses. By understanding the strengths and limitations of different visualization tools, researchers and analysts can effectively present and analyse data, leading to better decision-making and insights. |
| : | 10.22362/ijcert/2023/v10/i01/v10i0102 |
| DOI Link | : | https://doi.org/10.22362/ijcert/2023/v10/i01/v10i0102 |
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| Paper Title | : | Vision-based Hand Gesture Recognition for Indian Sign Language Using Convolution Neural Network |
| Authors | : | Boinpally Ashwanth, Sri Bhargav Ventrapragada , Shradha Reddy Prodduturi, Jeshwanth Reddy Depa, K. Venkatesh Sharma |
| Affiliations | : | CVR College of Engineering, R.R Dist, Telanagana. |
| Abstract | : | Hand gesture recognition is an important field of study for providing an alternative means of communication for individuals who are unable to speak. The Indian Sign Language (ISL) is one such language used by the deaf and mute community in India. In this paper, we propose a vision-based hand gesture recognition system for ISL using Convolutional Neural Network (CNN). The system captures hand gestures using a webcam and processes the images using a CNN trained on a dataset of ISL gestures. The system achieved a recognition accuracy of 93.5% on the test dataset, demonstrating its effectiveness in recognizing hand gestures in the ISL language. The proposed system provides a promising solution for helping the deaf and mute community in India to communicate more effectively and efficiently.To determine the shape of the sign, the first segmentation step is done based on skin color. After that, the discovered region is converted to a binary image. The binary image is then transformed using the Euclidean distance transformation. On the distance-modified picture, row and column projections are used. Central moments, as well as HU’s moments, are done to extract features. SVM and CNN are used for classification. |
| : | 10.22362/ijcert/2023/v10/i01/v10i0101 |
| DOI Link | : | https://doi.org/10.22362/ijcert/2023/v10/i01/v10i0101 |
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Latest issue :Volume 10 Issue 1 Articles In press
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| ☞ LAST DATE OF SUBMISSION : 31st March 2023 |
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| Citations Indices | All |
| Citations | 1026 |
| h-index | 14 |
| i10-index | 20 |
| Source: Google Scholar | |
| Acceptance Rate (By Year) | |
| Year | Rate |
| 2021 | 10.8% |
| 2020 | 13.6% |
| 2019 | 15.9% |
| 2018 | 14.5% |
| 2017 | 16.6% |
| 2016 | 15.8% |
| 2015 | 18.2% |
| 2014 | 20.6% |
