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Security Analysis and Implementation Strategy for (E-Rupi) Digital Mobile Wallet Development 27

Security Analysis and Implementation Strategy for (E-Rupi) D...

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27th International Symposium on Wireless Personal Multimedia Communications, WPMC 2024

作者： Apraj, Siddhi Rohokale, Vandana Prasad, Ramjee Indian Institute of Technology Ropar Mathematics and Computing Punjab India Sinhgad Institute of Technology and Science Narhe Pune India Emeritus Aarhus University Herning Denmark

ISBN: (纸本)9798350392319

This paper discusses security analysis and implementation strategy for the E-Rupi Digital Wallet application. The platform DigiRupi requires to be easy, safe and secure as it keeps the details of the beneficiaries completely confidential. This seamless one-time payment mechanism enables users to redeem the voucher without a card, by means of a digital payments app. It needs to be secured from all aspects of Security threats like Access Control, Confidentiality, Authentication, Reputation, Integrity, Accuracy and Availability. We looked at regulatory compliances, trends. © 2024 IEEE.

关键词： Electronic money

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Revolutionizing Brain Tumour Prediction: A Pioneering GAN-based Framework for Synthetic Data Generation 7

Revolutionizing Brain Tumour Prediction: A Pioneering GAN-ba...

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7th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2023

作者： Kumpatla, Gautam Veresi, Hemanth Bala Subrahmanyam, P. Abhishek, S. Anjali, T. Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science and Engineering Amritapuri India Sathyabama Institute of Science and Technology Chennai India

ISBN: (纸本)9798350341485

Medical analysis is a key component of contemporary healthcare since it helps doctors diagnose patients accurately to plan and track their treatments. Accurate identification of brain tumors is essential for doctors to treat patients swiftly and efficiently. This research investigates a novel approach to overcome the constraints imposed by scarce and sensitive medical data, generating synthetic images of brain tumors using Generative Adversarial Networks (GANs). The proposed method has the potential to enhance activities involving medical processing, which will aid in making diagnoses and formulating treatment plans. The preliminary findings demonstrate its potential relevance to a wider variety of medical processing tasks, demonstrating that this augmentation method yields significant benefits. © 2023 IEEE.

关键词： Generative adversarial networks

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Enhanced Clustering and Channel Allocation in Wireless Mesh Networks

Enhanced Clustering and Channel Allocation in Wireless Mes...

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International Conference on Smart Systems and Wireless Communication, SSWC 2024

作者： Sushma Reddy, Ch. V. Harshini, V. Rayala, Abhyuday Chandavarkar, B.R. Department of Computer Science and Engineering National Institute of Technology Karnataka Mangaluru Surathkal India

ISBN: (纸本)9789819613472

Wireless mesh networks (WMNs) are crucial for establishing adaptable and scalable communication infrastructures among interconnected devices. Effective clustering and channel allocation are vital for enhancing WMN performance by addressing energy efficiency, latency, throughput, and interference challenges. Proper clustering facilitates the organization of network nodes into cohesive groups, enhancing communication efficiency and resource utilization. Additionally, channel allocation strategies ensure minimized collisions and improved overall network throughput, enhancing network stability and reliability. Existing approaches, such as clique-based channel assignment (CCCA) and two-hop neighbor clustering, present complexity, and interference level limitations. The significant contribution of this paper is to introduce a novel approach focused on clustering and channel assignment, referred to as enhanced clustering and channel allocation (ECCA), to optimize WMN performance—the clustering technique groups nodes based on maximal cliques in one-hop neighbors. Furthermore, channel assignment strategies are employed to minimize collisions and improve overall network throughput. The performance of ECCA is compared with state-of-the-art clique-based channel assignment (CCCA) in terms of the modularity, average number of nodes per cluster, average node degree, and coefficient of variance. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Wireless mesh networks (WMN)

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Secured and Optimized Hardware Accelerators using Key-Controlled Encoded Hash Slices and Firefly Algorithm based Exploration

Secured and Optimized Hardware Accelerators using Key-Contro...

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2023 International Conference on Microelectronics, ICM 2023

作者： Sengupta, Anirban Anshul, Aditya Kothari, Chirag Thakur, Sumer Indian Institute of Technology Indore Indian Statistical Institute Kolkata Computer Science and Engg India Indian Institute of Technology Indore Computer Science and Engg India Indian Institute of Technology Indore India

ISBN: (纸本)9798350380828

The design process of application-specific integrated circuits (ASICs) as hardware accelerators or reusable hardware intellectual property (IP) cores require considering various design goals like area, latency, and security against attacks such as IP piracy and false claims of IP ownership during architectural synthesis. The problem of IP piracy and false IP ownership claim poses a significant threat to hardware IP cores, jeopardizing innovation, fair competition, and economic growth. The proposed work introduces a novel security framework to design secured and optimized hardware accelerators using key-controlled encoded hash slices integrated with firefly algorithm (FF) based design space exploration (DSE) during high level synthesis (HLS). The proposed methodology also demonstrates the embedding of covert security constraints into an optimal 8-point DCT hardware IP design, obtained by performing a tradeoff between area and latency through the FF-based DSE. The proposed methodology achieves stronger tamper tolerance and entropy than recent approaches. The experimental results also provide design cost assessment and optimality analysis. © 2023 IEEE.

关键词： High level synthesis

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Cluster Based Concurrent Data Collection with Fault Tolerance for Shared IoT Applications 16

Cluster Based Concurrent Data Collection with Fault Toleranc...

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

作者： Kumar, Arvind Matam, Rakesh Swain, Srinibas Mukherjee, Mithun Indian Institute of Information Technology Guwahati Department of Computer Science and Engineering India Nanjing University of Information Science and Technology Nanjing China

ISBN: (纸本)9798350383119

Sharing IoT device infrastructure by multiple entities or applications for their respective sensing and monitoring needs is an effective way to reduce the upfront setup cost, ownership costs, and also to prevent over provisioning. Concurrent data collection in such a shared environment is a major challenge, given the number of devices and multiple processes relying on that data. Most of the existing works in this direction typically consider network scenarios where devices can reach the base station(s) directly. As this assumption is not always valid, few other works focused on concurrent data collection over multiple-hops. In such a shared multi-hop environment, the chances of device failures are high, especially considering the power constraints of devices. To address the issue of reliability in data collection, this paper presents a cluster-based fault tolerant network structure for concurrent data collection. The proposed work aims to minimize the delay and handles the topology changes in case of faults, and also lowers the transmission count. The validity of the proposed work is shown via analytical and simulation results. © 2024 IEEE.

关键词： Concurrent Data collection in IoT Network topology Shared IoT device infrastructure

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AlertPilot: Video-Based Driver Fatigue Detection with Enhanced Face Tracking 5th

AlertPilot: Video-Based Driver Fatigue Detection with Enhanc...

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5th Doctoral Symposium on Computational Intelligence, DoSCI 2024

作者： Tiwari, Amit Kumar Maurya, Deepanshu Pandey, Kartikeya Tiwari, Sanjeev Yadav, Shubham Department of Computer Science and Engineering United Institute of Technology Uttar Pradesh Prayagraj India

ISBN: (纸本)9789819771776

The human face serves as a crucial communicator of various states and conditions. When a driver experiences fatigue, subtle changes in facial expressions, such as increased blinking and yawning, become apparent. This article introduces a novel system known as AlertPilot, designed to detect signs of driver fatigue using video analysis, thus eliminating the need for additional driver equipment. To overcome the limitations of existing algorithms, a new face detection algorithm is proposed to enhance tracking precision. Furthermore, a novel face detection approach utilizing 69 key facial landmarks has been developed. These landmarks are instrumental in assessing the driver’s condition. By analyzing facial cues, AlertPilot can issue fatigue alerts to the driver, primarily focusing on eye and mouth movements. Rigorous testing has demonstrated AlertPilot’s remarkable accuracy, achieving approximately 95% precision. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Face recognition

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Improving Safety on the Internet: A New Multimodal Framework for Hateful Meme Classification 3

Improving Safety on the Internet: A New Multimodal Framework...

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3rd International Conference on Disruptive Technologies, ICDT 2025

作者： Duggal, Anusha Singh, Anjali Garg, Devesh Raj Kumar Goel Institute of Technology Department of Computer Science and Engineering Ghaziabad India

ISBN: (纸本)9798331519582

In the fast-changing social media world, a significant mode of communication carrying complex concepts and feelings has materialized: the manufacture of memes. It welcomes bad memes such as hatred, stereotypes, and misinformation, but many memes also have positive values for discussion. This paper directly addresses the challenge of detecting hateful memes. It leverages the 'Facebook hateful meme dataset', Kaggle, 2020 by Facebook AI, a hand-curated dataset, for conducting innovative model training to detect and mitigate the spread of hateful content. Our dataset analyzes multimodal representations of hate speech in memes, integrating both text and images for classification. The results are encouraging with the implementation of advanced neural network architectures, such as convolutional networks for image annotation and recurrent networks called text-data modelling. The implications of this paper extend beyond detection. This is a significant step in combating the spread of hateful content and ensuring a safer online space. Ultimately, this work benefits the larger natural language processing and computer vision community, making an argument necessary for interdisciplinary computational treatment of the intricacies of online hate. © 2025 IEEE.

关键词： Tweets

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Advancements in Hand Gesture Recognition Through Convolutional Neural Networks: A Comprehensive Study 8th

Advancements in Hand Gesture Recognition Through Convolution...

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8th International Conference on Internet of Things and Connected Technologies, ICIoTCT 2023

作者： Kumar, M. Dharani Bhargavi, K. Rekha, C. Rammohan, M. Department of Computer Science and Engineering PVKK Institute of Technology Andhra Pradesh Ananatapur India

ISBN: (纸本)9789819757855

Real-Time Hand Gesture Recognition Using Convolutional Neural Networks: A Robust Approach for Diverse Applications. Hand gestures are fundamental to human communication and find extensive utility across various domains. However, the real-time recognition of hand gestures using computer vision algorithms poses significant challenges. While several algorithms have incorporated color and depth cameras to facilitate gesture recognition, achieving robust classification across diverse individuals remains a notable hurdle. In this paper, we present a novel algorithm that leverages Convolutional Neural Networks (CNNs) for real-time hand gesture recognition. Our CNN model is trained on a comprehensive dataset consisting of nine distinct hand gestures, each comprising 500 images. Through rigorous evaluation, our proposed algorithm achieves an impressive average accuracy of 98.76%, underscoring its potential to establish secure and user-friendly interfaces for a wide range of applications. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Convolutional neural networks

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Statistical Modeling of Air Pollutants for Predicting AQI Levels

Statistical Modeling of Air Pollutants for Predicting AQI Le...

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2024 IEEE International Conference on Big Data, BigData 2024

作者： Kumar, Sudhir Mehra, Sourabh Jha, Harsh Kour, Vaneet Misra, Rajiv Indian Institute of Technology Computer Science and Engg. Patna801106 India

ISBN: (纸本)9798350362480

Air quality is a critical factor influencing public health, with pollutants such as particulate matter (PM10, PM2.5), ground-level ozone (O3), carbon monoxide (CO), sulfur dioxide (SO2), and nitrogen dioxide (NO2) posing significant health risks. Understanding the relationship between these pollutants is essential for effective air quality management. In this study, we apply a comprehensive range of statistical models, including Multivariate Analysis of Variance (MANOVA), Canonical Correlation Analysis (CCA), Factor Analysis, post-hoc tests, linear regression, and other techniques to evaluate the correlation between PM2.5 and key air pollutants. By employing these methods, we aim to identify the most significant contributors to PM2.5 levels and provide insights to inform air quality control strategies. Our findings offer a robust statistical framework for predicting PM2.5 concentrations, enhancing the ability of policymakers and environmental agencies to mitigate pollution-related health risks. © 2024 IEEE.

关键词： Nitrogen oxides

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AI-Driven Space Solar Power: Pioneering the Next Frontier in Global Energy 2

AI-Driven Space Solar Power: Pioneering the Next Frontier in...

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2nd International Conference on Computational Intelligence and Network Systems, CINS 2024

作者： Varrshini, G.M. Vignesh, U. Parvathi, R. School of Computer Science Engineering Vellore Institute of Technology Chennai600127 India

ISBN: (纸本)9798331504106

This review provides a close insight into recent and significant technological developments that have emerged in this ever-changing field of Space Based Solar Power, which has enormous potential to alter the global energy supply landscape by harnessing solar energy from outer space through technical advances such as Energy Harvesting from Space and Wireless Power Transmission along with novel engineering solutions being developed to overcome emerging challenges. It also focuses on how AI came into play in optimizing various features of the generation, transmission, and distribution processes. In the context of SBSP, standing for Solar Power Satellite, the energy from the sun is generally collected by using either solar collectors or the advanced light framework of the solar arrays. This captured sun energy is then converted to another type of energy with the help of different electronic devices, such as microwave or laser energy, for transmission back to Earth to be useful in practical ways. To offer a different perspective on SBSP’s ability to meet future energy needs while staying eco-friendly, the review covers environmental, economic, & geopolitical issues related to space-based solar power. It dives into how artificial intelligence (AI) can change the game for SBSP systems by making them more efficient and reliable and helps enormously in growing SBSP technologies. ©2024 IEEE.

关键词： Space power generation

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