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8th IEEE International Conference on Computing, Communication, Control and Automation, ICCUBEA 2024

作者： Dixit, Rashmi Kothari, Aditi Jain, Shantala Walchand Institute of Technology Solapur Department of Computer Science & Engineering Maharastra Solapur India

ISBN: (纸本)9798350391770

Electronic communication is expanding quickly right now, and many new applications are following suit. This aided numerous enterprises in turning a profit in their corresponding industries. Online item bidding has become a popular method for buying and selling goods in the digital age. Online item bidding traces its roots back to the early days of the internet when platforms like eBay revolutionized the way people buy and sell goods. Over the years, online item bidding has evolved to include various platforms and technologies, making it a convenient and accessible way for individuals and businesses to engage in commerce. E-Auction System is one of the numerous electronic communication applications that is now receiving a lot of positive feedback from users. An efficient E-Commerce system that enables online communication between a party offering to buy an asset and a party who sells through E-Auction System. The many restrictions of traditional auctions, such as physical location, timing and travel, a finite number of participants, etc., have been greatly reduced by this online format. BlockChain and smart contracts can be used as a ground-breaking technology in our auction system that has caught the interest of numerous sectors. The security of payment gateways is very strong. Our model's objective is to enable everyone to organise their own auctions or participate in the auction from any location on Earth. We must adapt ourselves in accordance with the changes in technology. © 2024 IEEE.

关键词： Smart contract

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Image Segmentation for MRI Brain Tumor Detection Using Advance AI algorithm 2

Image Segmentation for MRI Brain Tumor Detection Using Advan...

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2nd International Conference on Networking, Embedded and Wireless Systems, ICNEWS 2024

作者： Roselinmary, S. Devadharshini, Y. Anand Institute of Higher Technology Department of Computer Science And Engineering Tamilnadu Chennai India

ISBN: (数字)9798350367461

ISBN: (纸本)9798350367461

The existence of a brain tumor indicates an unusual growth of cells in the brain, manifesting as either benign (non-cancerous) or malignant (cancerous). Artificial Intelligence (AI) plays a crucial role in detecting and diagnosing brain tumors, primarily utilizing medical imaging techniques such as Magnetic Resonance Imaging (MRI). This initiative aims to employ Roboflow for data annotation and model training, utilizing the YOLOv8 algorithm to precisely handle the detection of brain tumors in MRI scans through image segmentation. The dataset utilized in this project encompasses annotated MRI scans illustrating tumor regions, meticulously prepared and enhanced through the application of Roboflow. YOLOv8, renowned for its expeditious and accurate object detection capabilities, is implemented and fine-tuned utilizing the annotated dataset. Model evaluation incorporates metrics such as Mean Average Precision (MAP), Recall, and Precision. Although YOLOv8 is inherently designed for object detection, this study explores adaptations for image segmentation, treating tumors as distinct classes. The iterative refinement process encompasses fine-tuning and optimization to elevate model performance and ensure robust generalization to novel data. The focus is on the advancement of MRI-based brain tumor detection through the utilization of cutting-edge deep learning techniques. This study highlights the potential of customizing YOLOv8 for the precise task of detecting brain tumors in MRI scans, establishing a foundation for future progress in the field of medical imaging. © 2024 IEEE.

关键词： Magnetic resonance imaging

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Decentralized Energy Consumption Analysis Framework for Coordinated EVs Charging 14

Decentralized Energy Consumption Analysis Framework for Coor...

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

作者： Kakkar, Riya Agrawal, Smita Tanwar, Sudeep Institute of Technology Nirma University Department of Computer Science and Engineering Gujarat 382481 India

ISBN: (纸本)9798350344837

With the modernization of the transportation system, EVs penetration has been promoted significantly and holds great potential by maintaining energy sustainability for the greener environment. Nevertheless, owing to the vast number of EVs arriving at the CS, there is a high possibility of imbalanced energy exchange between EV and CS, which also disrupts the working of the smart grid. Moreover, security and privacy issues during EV energy transactions are not handled by the researchers to that extent. Thus, we propose a blockchain-based EV energy consumption analysis framework for predicting Evs' SoC in the smart grid environment. We have applied a sequential model to predict EVs SoC based on the various effecting parameters using optimizers such as Adam, Adadelta, and RMSprop. The incorporated IPFS protocol is combined with the blockchain to ensure the reliability and availability of the proposed framework during the EV energy consumption prediction. Finally, the proposed framework is analyzed and evaluated considering various standard performance metrics such as loss using MSE, MAE, and SoC error prediction in which the sequential model with Adam outperforms other optimizers in terms of minimum error and loss. © 2024 IEEE.

关键词： Blockchain

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Cheating Detection in Online Exam: A Comprehensive Survey 1

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8th International Conference on Information and Communication technology for Competitive Strategies, ICTCS 2023

作者： Bhowmik, Pratya Das, Smita National Institute of Technology Agartala Department of Computer Science and Engineering Tripura Agartala India

ISBN: (数字)9789819702107

ISBN: (纸本)9789819702091

Due to COVID-19, many educational institutes throughout the world shifted their means of teaching from offline to online. Online examination became more challenging while testing the academic skills or depth of knowledge of a student. The alarming situation ascends when a student practices unfair means during an online exam. In this paper, a survey is carried out based on recent research works where initially the reason behind cheating in exams is analyzed. Subsequently, detection measures for cheating during and after exams have also been discussed. Finally, various prevention measures for cheating have been studied to identify new research challenges in this field. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Students

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Analysis of Edge Detection Technique over Parallel Environment 2

Analysis of Edge Detection Technique over Parallel Environme...

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2nd IEEE International Conference on Advances in Information technology, ICAIT 2024

作者： Raghuramegowda, S.M. Raj, Rakesh S. Department of Computer Science & Engineering Adichunchanagiri Institute of Technology Chikkamagalur Karnataka577102 India

ISBN: (纸本)9798350383867

Image processing over parallel computing involves leveraging multiple processors or computing cores to perform various tasks on images simultaneously, significantly improving the efficiency and speed of image processing operations. Message Passing Interface (MPI), Parallel Virtual Machine (PVM), and other message passing libraries can be used to build a parallel computing environment. This paper aims at demonstrating how parallelism is possible for operations used in image processing using MPI. Morphological processes like dilation and erosion are the kinds of image processing methods we are contemplating about. © 2024 IEEE.

关键词： Virtual machine

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SSRFace: a face recognition framework against shallow data

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Multimedia Tools and Applications 2023年第12期82卷 18617-18633页

作者： Zhou, Yun-Ting Dy, Jilyan Bianca Hsu, Shang-Che Hsu, Yu-Ling Yang, Chao-Lung Hua, Kai-Lung Department of Computer Science and Information Engineering National Taiwan University of Science and Technology Keelung Rd Taipei106 Taiwan

Most existing deep-learning-based approaches rely on high-resolution large-scale datasets to improve their performance. However, obtaining such datasets is challenging for tasks such as face recognition. The best way to address this is first to address the issue deep-learning-based approaches experience when trained on limited samples or shallow datasets (i.e., lack of diversity). We propose SSRFace, a framework for face recognition on shallow datasets. In detail, SSRFace leverages two novel components: Segregate-Representation (SR) and SimInstance. SR utilizes unlabeled data and angular-margin-based loss to increase inter-class distance, improving class discrimination. SimInstance, on the other hand, has a straightforward approach to improving intra-class diversity. Our proposed SimInstance starts by learning the unique class distribution from the few samples before randomly sampling a feature representation to serve as new intra-class samples. We train our model on TinyFace, a shallow dataset, to show its capabilities. We show SSRFace performed better than other existing approaches with Rank-1 accuracy and mean average precision (mAP) when trained on shallow datasets. © 2022, The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature.

关键词： Face recognition

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A Weighted Privacy Mechanism under Differential Privacy 4

A Weighted Privacy Mechanism under Differential Privacy

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4th International Conference on Intelligent Technologies, CONIT 2024

作者： Hemkumar, D. Prashanth, Pvn Visvesvaraya National Institute of Technology Department of Computer Science and Engineering Maharhastra Nagpur India

ISBN: (纸本)9798350349900

As digital technology advances, electronic databases are amassing an ever-growing volume of personal data. Even with the removal of explicit identifiers, such as names and addresses, the remaining data fields can still be leveraged to create distinct individual profiles, posing a significant threat to privacy. Therefore, safeguarding the privacy of individuals within datasets is of utmost importance. One highly effective technique for preserving privacy is differential privacy. Existing literature has employed various methods, such as Laplace and output perturbation, to achieve differential privacy. However, the accuracy of these mechanisms varies depending on the specific queries and the chosen value of є. Consequently, there exists a necessity for a differential privacy mechanism that can maintain accuracy across a wide range of queries. In this paper, we propose a method within the differential privacy framework known as the 'weighted mechanism'', which integrates elements from both Laplace and perturbation mechanisms. This approach involves releasing outputs with the addition of random noise from a defined distribution. To evaluate its effectiveness, we conduct a series of experiments comparing the accuracy of established differential privacy methods with the proposed weighted mechanism across various types of queries. © 2024 IEEE.

关键词： Differential privacy

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Power Density Limits of Propulsion Motor for Electric Aircraft: A Study on Insulation Thickness

Power Density Limits of Propulsion Motor for Electric Aircra...

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2024 International Conference on Electrical Machines, ICEM 2024

作者： Wang, Jundong Dong, Jianning Niasar, Mohamad Ghaffarian Zhu, Gangwei Bauer, Pavol Delft University of Technology Department of Electrical Engineering Mathematics and Computer Science Delft Netherlands

ISBN: (纸本)9798350370607

This paper studies the power density limits of propulsion motor for electric aircraft considering thermal aspects and breakdown voltage reduction of insulation. The study em-ploys multi-objective optimization (MOO) to explore various mo-tor cooling options and filter configurations. The results show that motors with direct winding heat exchanger (DWHE) can reach higher specific power, while those equipped with water jacket cooling (WJC) offer a moderate design with simpler structure. Furthermore, the impact of sine wave and dv/dt filters on electric motors design is studied. The findings demonstrate that dv/dt filters enable designs with higher overall specific power compared to sine wave filters. Through simulations, this study identify the challenge faced by aviation motor design in significantly increased insulation thickness, necessitating advanced insulation materials with a minimum thermal conductivity of 5 W/(m.K) to facilitate a high specific power design. Based on this assumption, a preliminary design of 9.6 kW/kg with an efficiency of 98% is presented. © 2024 IEEE.

关键词： Thermal insulation

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A Comprehensive Review of Recent Artificial Intelligence Techniques and IOT Applications in Dairy Farms 10

A Comprehensive Review of Recent Artificial Intelligence Tec...

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10th International Conference on Advanced Computing and Communication Systems, ICACCS 2024

作者： Anusree, K. Rajeswari, M. Priyadharshini, C. Karunya Institute of Technology and Science Department of Computer Science and Engineering Tamil Nadu Coimbatore India Sahrdaya College of Engineering and Technology Kerala Kodakara India

ISBN: (纸本)9798350384369

Each and every aspect of daily life has undergone a change thanks to the Internet of Things technology that renders everything intelligent. The wide range of IoT applications has captivated numerous researchers, and IoT enabled dairy farming is being leveraged to undertake innovative studies integrating IoT and Artificial Intelligence (AI) technology. More prospects for intelligent dairy farming are being created by the IoT and data-driven methods. Since the global population is increasing, there is a constant appetite for milk. Developed countries use a greater amount of dairy products than developing nations do. Enhanced technological approaches are required to elevate milk production and meet the escalating demand for dairy products. It is anticipated that a farmer would be able to significantly increase milk output and conquer several traditional farming obstacles with the help of IoT and various AI solutions. This study discusses various difficulties that dairy farmers deal with on every day of their lives. The primary objective of this paper is to undertake a comprehensive review on various Io'T, machine learning(ML) and deep learning(DL) technologies used in the field of smart dairy farming. It also looks into the difficulties and issues that traditional methods encounter as well as their results. Furthermore, the development of an IoT -enabled automated system for dairy farming may benefit further from this evaluation of research. © 2024 IEEE.

关键词： Smart agriculture

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Monitoring, Tracking and Fighting Pandemics using Drone-based Artificial Intelligence in IoT 9

Monitoring, Tracking and Fighting Pandemics using Drone-base...

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9th International Conference on Advanced Computing and Communication Systems, ICACCS 2023

作者： Kumar, K. Praveen Sangeetha, S. Kumar, T Rajesh Bhuvaneswari, R. Rasi, D. Mahaveerakannan, R. Kakatiya Institute of Technology and Science Department of Information Technology Warangal India SIMATS Saveetha School of Engineering Department of Computer Science and Engineering Tamil Nadu Chennai India Computer Science and Applications Vellore India Sri Krishna College of Engineering and Technology Department of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350397376

The world has altered since the World Health Organization (WHO) designated (COVID-19) a worldwide epidemic. Everything in society, from professions to routines, has shifted to accommodate the new reality. The World Health Organization warns that future pandemics of infectious diseases are likely and that people should be ready for the worst. Therefore, this study presents a framework for tracking and monitoring COVID-19 using a Deep Learning (DL) perfect. The suggested framework utilises UAVs (such as a quadcopter or drone) equipped with artificial intelligence (AI) and the Internet of Things (IoT) to keep an eye on and combat the spread of COVID-19. AI/IoT for COVID-19 nursing and a drone-based IoT scheme for sterilisation make up the bulk of the infrastructure. The proposed solution is based on the use of a current camera installed in a face-shield or helmet for use in emergency situations like pandemics. The developed AI algorithm processes the thermal images that have been detected using multi-scale similar convolution blocks (MPCs) and Res blocks that are trained using residual learning. When infected cases are detected, the helmet's embedded Internet of Things system can trigger the drone system to intervene. The infected population is eradicated with the help of the drone's sterilisation process. The developed system undergoes experimental evaluation, and the findings are presented. The developed outline delivers a novel and well-organized arrangement for monitoring and combating COVID-19 and additional future epidemics, as evidenced by the results. © 2023 IEEE.

关键词： Coronavirus

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