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ProctorXam - Online Exam Proctoring Tool 1

ProctorXam - Online Exam Proctoring Tool

引用

1st IEEE International Conference on Electronics, Computing, Communication and Control Technology, ICECCC 2024

作者： Ashwini, S. Bhuvan Kumar, M.S. Chandra Sai, D. Sathya, V. Atria Institute of Technology Dept. of Computer Science & Engineering Bangalore India

ISBN: (数字)9798350371802

ISBN: (纸本)9798350371802

Robust exam monitoring solutions are now essential in light of the most notable Covid-19 outbreak and the increasing inclination towards virtual learning. The automated method for supervising online exams that is suggested in this paper is intended to lessen the difficulties associated with exam cheating. With the assistance of our system's clever face detection algorithms, instructors may efficiently identify suspicious conduct by monitoring students' web activity and camera feed in real-time. Unlike earlier systems, ours provides improved accuracy and functionality, guaranteeing the authenticity of online tests. In light of the difficulties presented by the epidemic, this research attempts to offer a workable option for academic institutions and people wishing to administer fair and secure online exams. © 2024 IEEE.

关键词： Face recognition

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A Framework for Personality Prediction for E-Recruitment Using Machine Learning Algorithms 14

A Framework for Personality Prediction for E-Recruitment Usi...

引用

14th International Conference on Cloud Computing, Data Science and engineering, Confluence 2024

作者： Thapa, Lakshyajit Pandey, Aniket Gupta, Deepanshu Deep, Ayush Garg, Rakesh Amity University Dept. of Computer Science and Engineering Uttar Pradesh India

ISBN: (纸本)9798350344837

With rapid advancements in technology, the process of recruitment has evolved from traditional methods to online and automated methods known as e-recruitment. While e-recruitment streamlines the initial screening process, assessing the personality and suitability of candidates continues to remain a challenge. In this paper, we propose a framework for online personality prediction to aid the e-recruitment process. The framework utilizes machine learning algorithms to analyze user data from multiple online sources like resumes, social media profiles, and responses to psychometric tests, and predict their personality type based on established psychological theories. Four popular personality prediction models - Big Five, Myers Briggs, HEXACO, and Enneagram are discussed. State-of-the-art natural language processing and deep learning techniques like BERT are explored for feature extraction from text data. Popular supervised machine learning algorithms like logistic regression, Naive Bayes, k-nearest neighbors, support vector machines, random forest, XGBoost, and LSTM are compared to build predictive models. The proposed framework can help recruiters shortlist candidates better matched to job requirements, leading to increased hiring satisfaction and productivity. © 2024 IEEE.

关键词： Forecasting

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'RNN-Driven Prognosis of Heart Disease Based on Health Parameters' 2

'RNN-Driven Prognosis of Heart Disease Based on Health Param...

引用

2nd International Conference on Advanced Computing and Communication Technologies, ICACCTech 2024

作者： Rahi, Parvez Singh, Inderjeet Singh, Ajay Pal Kumar, Alok Chandigarh University Dept. of Computer Science & Engineering Punjab Mohali India

ISBN: (纸本)9798331519056

Cardiovascular diseases (CVD) are the leading cause of death globally and are estimated to affect 17. 9 million deaths annually. Early diagnosis is very important if one is to prevent adverse consequences. However, traditional diagnostic methods can take time to complete and miss subtle trends in patient information. This research presents an innovative approach utilizing a Recurrent Neural Network (RNN) model, optimized through Stochastic Gradient Descent (SGD), for the prediction of seven distinct types of heart disease: CAD, Heart Failure, AFib, Hypertensive Heart Disease, Congenital Heart Disease, Cardiomyopathy, and PAD. Their architecture is specifically suited for direct modeling of sequential patterns of the health related data that in turn helps to detect temporal patterns and changes in them. This model use ReLU activation function in their hidden layers, dropout in preventing overfitting and batch normalization for stable learning. Moreover, the feature augmentation is used in the model making it use various psychological and physiological parameters that help in making comprehensive predictions on the risks of heart disease. After training the RNN with a Kaggle dataset and properly tuning it, the model obtained an accuracy level of 91%, which means that is highly useful in identifying risk factors of cardiovascular diseases and could be used for early diagnosis and risk factors identification. © 2024 IEEE.

关键词： Recurrent neural networks

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Real-Time Stress Detection Using Facial Images and Convolutional Neural Networks

Real-Time Stress Detection Using Facial Images and Convoluti...

引用

2024 IEEE International Women in engineering (WIE) Conference on Electrical and computer engineering, WIECON-ECE 2024

作者： Sindu, M. Ashwin, T. Shyam Sunder, V. Shivasankaran, S. Poongothai, P. Ponnusamy, R. Chennai Institute of Technology Dept. of Computer Science and Engineering Tamil Nadu India Chennai Institute of Technology Dept. of Computer Mathematics Tamil Nadu India

ISBN: (纸本)9798331535476

Stress is one of the prevailing issues in today's world, deeply impacting the actual well-being of individuals. In this paper, we introduce an innovative method to detect stress that deviates from the mainstream approaches, which rely solely on physiologic signals and self-reporting. Our non-invasive, efficient, and scalable real-time system, built on the facial image data processed by CNNs, makes real-time human stress detection possible. The system captures facial expressions through video or static images, which it then processes within a CNN model to identify stress-related features. CNNs are particularly innovative in that they are adept.at automatically extracting and learning hierarchical features from extremely complex, unstructured data like facial images. Facial expression datasets were used to train and test the proposed model in different stress conditions. The model achieved a very good accuracy level in differentiating stressed from non-stressed states, thus putting it on par with professionals. Real-time testing of the system's performance was done on edge devices such as smartphones to prove its potential for use in real-life applications related to mobile health. As facial image data is utilised by the system, thereby killing the need for wearable sensors or invasive physiological monitoring, the approach would be more accessible for detecting stress levels. This research showed that CNN models developed based on facial images can transform stress monitoring. Its implications are wide, applicable in health care, workplace settings, and even self-manageable personal stress. In future work, the model should be generalised for diverse populations, the system's real-time capabilities enhanced, and multimodal data further integrated to increase detection accuracy and reliability. © 2024 IEEE.

关键词： Convolutional neural networks

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Medlet-Block: Secured Health-Based Cloudlet Platform Using Blockchain 16

Medlet-Block: Secured Health-Based Cloudlet Platform Using B...

引用

16th International Conference on COMmunication systems and NETworkS, COMSNETS 2024

作者： Gupta, Atrayee Agarwal, Varun Techno Main Saltlake Dept. of Computer Science and Engineering Kolkata India

ISBN: (纸本)9798350383119

Medical information cannot be easily shared and exchanged between various healthcare systems and providers due to a lack of interoperability, delays, inefficiencies, and above all lack of security. This paper provides a design of an edge-based blockchain for a secured health-care system which takes care of confidentiality, integrity, non-repudiation and other security challenges. © 2024 IEEE.

关键词： Block Health-care Symmetric key Transaction

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Model-Based Web Service Development Using Discrete Event systems

Model-Based Web Service Development Using Discrete Event Sys...

引用

2024 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2024

作者： Lee, Sunmin Lee, Minji Kim, Taehoon Jang, Sooyoung Choi, Changbeom Hanbat National University Dept. of Computer Engineering Daejeon Korea Republic of

ISBN: (纸本)9798331530839

A modern web service consists of two key components: a front-end and a back-end system. The front-end handles user interactions and forwards requests to the back-end. The back-end processes these requests, generates the necessary data or responses, and sends them back to the user through the front-end. Therefore, developing effective web services requires careful design of both the front-end and back-end systems, as well as the interface between them. This study focuses on the front-end and proposes a notation to represent it as discrete event systems, addressing challenges related to HTML syntax complexity and link modification. © 2024 IEEE.

关键词： Web services

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Impact of Novel Pre-Processing Techniques on Retinal Images 2

Impact of Novel Pre-Processing Techniques on Retinal Images

引用

2nd International Conference on Disruptive Technologies, ICDT 2024

作者： Sahu, Deepti Kaur, Mandeep Sharda University Dept. of Computer Science & Engineering Greater Noida India

ISBN: (纸本)9798350371055

Glaucoma, a gradually developing eye condition that can damage the optic nerve, is one of the leading causes of irreversible blindness worldwide. The detection of glaucoma is required in its initial phases for the prevention of the disease. Several machine learning and deep learning models have been developed to detect the disease. These models require a preprocessed structured data set for better efficiency and accuracy of detection. The image datasets used for this purpose have been found with several issues of outliers and noise that limit the accuracy of the results. Hence, proper handling of the dataset in terms of pre-processing is vital. This paper presents a novel pre-processing technique for better glaucoma detection as it is necessary to remove outliers from the retinal images. The proposed 'EMF' model for pre-processing comprises Enhancement, Morphology, and Filtering of the images to get better results on the Retina. Drishti dataset has been used to evaluate the efficiency of the proposed technique. This dataset has several outliers that limit the accuracy, making it difficult to diagnose glaucoma. However, with the usage of the proposed technique, the dataset could be efficiently utilized for glaucoma detection. Compared to current state-of-the-art techniques, the findings from the proposed approach were shown to be better in terms of MSE, PSNR, and entropy. © 2024 IEEE.

关键词： Frequency domain Glaucoma Pre-processing Region of interest Retinal image Spatial domain

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A New Half-Bridge/Dual-Stacked-Switches Structured Electrolytic Capacitor-less AC/DC Bi-Directional On-Boad Charger for High-Voltage EV Battery

A New Half-Bridge/Dual-Stacked-Switches Structured Electroly...

引用

2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Derakhshan, Siamak Lam, John York University Dept. Electrical Engineering and Computer Science Toronto Canada

ISBN: (纸本)9798350376067

This paper introduces a novel half-bridge (HB)/dual-stacked-switches based electrolytic capacitor-less bidirectional AC/DC converter for high voltage (HV) electric vehicle (EV) systems. The proposed two-stage AC/DC converter incorporates a closed-loop Power Factor Correction (PFC) mechanism based on the dq model of the input LCL filter, ensuring high-quality input current with minimized Total Harmonic Distortion (THD) during both conversion and inversion operations of the converter. Moreover, the front-end HB PFC circuit operates in Continuous Conduction Mode (CCM) that results in the elimination of the high peak current in the switches. Additionally, a dedicated closed-loop control system is deployed in the dual-stacked-switches resonant converter to significantly reduce the output voltage ripple, thus eliminating the use of bulky electrolytic-type storage capacitors. Output voltage regulation is realized by using Variable Frequency Modulation (VFM). Soft-switching operation is guaranteed for all the switches and diodes using CLLC resonant circuit for both conversion and inversion modes of operation. The proposed circuit's performance is verified through a 1kW, 120Vrms/800Vdc proof-of-concept prototype. © 2024 IEEE.

关键词： Electrolytic capacitors

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Efficient Parametric Model Order Reduction for Large-Scale Circuit Models using Extended Krylov Subspace 20

Efficient Parametric Model Order Reduction for Large-Scale C...

引用

20th International Conference on Synthesis, Modeling, Analysis and Simulation Methods and Applications to Circuit Design, SMACD 2024

作者： Chatzigeorgiou, Chrysostomos Floros, George Chatzigeorgiou, Dimitrios Evmorfopoulos, Nestor Stamoulis, George University of Thessaly Dept. of Electrical & Computer Engineering Volos38334 Greece

ISBN: (纸本)9798350351927

The arising packing density of Very Large-Scale Integrated (VLSI) circuit models is subject to parameter variations due to temperature, geometry, process, and operating conditions. As a result, parameter Model Order Reduction (MOR) is motivated by such practical problems to compute the reduced-order model once and then re-simulate the low-order model with just updating the parameters. In this paper, we present a parametric Moment Matching (MM) MOR method, which employs the Extended Krylov Subspace (EKS) to efficiently extract accurate reduced-order models. The proposed method can handle large scale (linear) circuits and generate the corresponding reduced order models in parametric format. Experimental results on the industrial IBM power grid benchmarks prove the effectiveness of the proposed methods. © 2024 IEEE.

关键词： VLSI circuits

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ImportChainBD: Blockchain Solutions for Transparent and Accountable Imported Cosmetic Products 3

ImportChainBD: Blockchain Solutions for Transparent and Acco...

引用

3rd IEEE International Conference on Blockchain and Distributed systems Security, ICBDS 2024

作者： Khan, Md. Adib Karmoker, Sagar Rumpa, Ummay Khadiza Rahman, Habibur Hossain, Md. Sabbir Anik, Nur Adnan Chowdhury Hasan, Mahamudul East West University Dept. of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9798350354348

To improve the supply-chain management system of Bangladesh for imported cosmetic products this paper proposes a blockchain-based solution. One of the major goals of this project is to increase the tax compliance of the government by stopping counterfeit and illegally imported cosmetic products. Which will enhance the trust of consumers and the brand's reputation. Using this system is quite easy and convenient, as All the information will be stored in the blockchain, so it will become a secure and immutable product tracking system for importers, distributors, and retailers to maintain their ledgers just by printing and scanning a QR code through an IoT device, and consumers can check the authenticity of these cosmetic products just by scanning them. If the product is verified to be suspicious, The Mobile Court Management System has the power to check its origin. Finally, we can say that it will avoid the sale of counterfeit items in the market and increase government revenue on tax. © 2024 IEEE.

关键词： Cosmetics

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