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3rd international conference on Machine Vision and Augmented Intelligence, MAI 2023

作者： Shantilal, Sankhala Bhavik Singh, Amaresh Chandra Gupta, Nidhi Research and Development Isnartech PVT. LTD. Saharanpur India Department of Computer Applications National Institute of Technology Kurukshetra Kurukshetra India

ISBN: (纸本)9789819743582

An attendance management system allows us to track the attendance of students, teachers, employees, and other staff. It assists us in saving time and effort. Digital attendance systems have been used by some schools and companies in the past, but their accuracy and chances of locating an unidentified face aren’t all that significant. This attendance system is particularly effective for preventing errors while doing manual data entry and it comprises three main stages named Face Detection, Recognition, and Verification. Behavior analysis is combined with the attendance system. Although face detection and recognition have several applications in security, biometrics, and medicine, their best implementation in companies or schools is still in the early stages of research. The proposed approach is the most efficient alternative after comparing its accuracy and computational cost to those of preceding algorithms. This paper describes how an attendance management system integrates various facial recognition algorithms and object recognition techniques. The proposed model’s experimental results, which integrate detection, two-stage recognition, and analysis, are likely to be effective in modern schools and businesses. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Attendance management system Behavior analysis Face detection Face recognition Face recognition pipeline FaceNet model

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The 3rd Workshop on Quantum in Consumer Technology at IEEE Quantum Week 2024

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IEEE CONSUMER ELECTRONICS MAGAZINE 2025年第2期14卷 4-5页

作者： Sotelo, Rafael Giusto, Edoardo Nakamura, Yuichi Wang, Jingbo Rajan, Sreeraman Thapliyal, Himanshu Univ Montevideo Montevideo Uruguay Quantum South Montevideo Uruguay Univ Napoli Federico II Naples Italy NEC Corp Ltd Tokyo Japan Univ Western Australia Crawley WA Australia Carleton Univ Ottawa ON Canada Univ Tennessee Knoxville TN USA

The Workshop on Quantum in Consumer Technology at IEEE Quantum Week 2024 was an inspiring event that united experts from diverse fields to explore the present advancements and future possibilities of quantum technology in consumer applications. Organized by the Quantum in Consumer Technology Technical Committee of the IEEE Consumer Technology Society (CTSoc), this workshop focused on the integration and application of quantum technologies in consumer electronics, exploring current innovations and future directions;see CTSoc representatives in Figure 1(a). This workshop was part of the IEEE Quantum Week 2024, officially known as the IEEE international conference on Quantum Computing and Engineering (QCE24), which was held in the Palais des Congr & egrave;s in Montr & eacute;al, Qu & eacute;bec, Canada, from 15 to 20 September, 2024.

关键词： Quantum computing Consumer electronics conferences Australia Quantum sensing Resilience Quantum algorithm Optimization Logistics Approximation algorithms

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Hyperspectral Images for Crop Prediction using Machine and Deep Learning Models 3

Hyperspectral Images for Crop Prediction using Machine and D...

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3rd international conference on Electronics and Renewable systems, ICEARS 2025

作者： Mahalakshmi, R. Kumutha, K. Sakthivanitha, M. Lakshmi, R. Bagavathi Sirajudeen, Mohamed Padmanabhan, Sankar Vels Institute of Science Technology & Advanced Studies Department of Computer Applications-PG Tamil Nadu Chennai India Vels Institute of Science Technology Advanced Studies Department of Computer Applications-PG Tamil Nadu Chennai India Vels Institute of Science Technology & Advanced Studies Department of Computer Application Tamil Nadu Chennai India Vels Institute of Science Technology & Advanced Studies Department of Information Technology Tamil Nadu Chennai India Nilgiri College of Arts and Science Pg and Research Department of Computer Science Tami Nadu The Nilgiris India Hindustan Institute of Technology and Science Department of Electronics and Communication Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798331509675

Crop classification is essential for local and national governments to make informed agricultural decisions. Remote sensing technology has made it possible to employ high-resolution hyperspectral images (HSIs) for land cover classification for decades. Machine Learning (ML) and Deep Learning (DL) are becoming more popular for HSI categorization due to advances in processing capacity and technology. HSIs can accurately identify crop types due to their narrow and continuous spectral band reflection. This study compares traditional machine learning (ML) models like Support Vector Machines (SVM) and Random Forest (RF) to deep learning (DL) models like Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN) for hyperspectral image classification (HSI). The HSI categorization was evaluated using performance criteria such as accuracy, precision, recall, and the F1-Score. CNN achieved the highest accuracy of 96%, demonstrating that it is the most reliable solution for complex HSI classification tasks because it successfully captures spatial and spectral data. © 2025 IEEE.

关键词： Classification Deep Learning(DL) Hyperspectral Images(HSI) Machine Learning(ML)

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A Design Pattern-Based Approach for Analyzing MapReduce applications 3rd

A Design Pattern-Based Approach for Analyzing MapReduce Appl...

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3rd international conference on Language Processing and Knowledge Management, LPKM 2024

作者： Bessifi, Mayssa Younes, Ahlem Ben Ayed, Leila Ben FSEGS University of Sfax Sfax Tunisia ENSIT University of Tunis Tunis Tunisia ENSI University of la Manouba Manouba Tunisia

ISBN: (纸本)9783031850660

MapReduce is a widespread programming paradigm used to develop scalable parallel applications in various fields. Despite the simplicity of the MapReduce model, using it to effectively solve real-life problems can be challenging for developers and designers. Furthermore, ensuring the reliability and correct requirements of any system is fundamental at the early stage of development, as late corrections are estimated to be more than 200 times greater than corrections during requirement engineering. Therefore, a systematic approach is required to assist designers in developing reliable MapReduce applications. In this paper, we present a design pattern-based approach to the specification and formal verification of MapReduce applications using the BPMN notation and the Event B method. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Requirements engineering

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Pattern Diversity mm-Wave Rectangular Ring Shaped MIMO Antenna for 5G Communication and Internet of Things applications 3rd

Pattern Diversity mm-Wave Rectangular Ring Shaped MIMO Anten...

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3rd international conference on Computational Electronics for wireless Communications, ICCWC 2023

作者： Nahar, Tapan Das, Vishal Rawat, Sanyog Anguera, Jaume Department of Information & Communication Technology Marwadi University Rajkot India Department of Electronics & Communication Engineering Manipal University Jaipur Jaipur India Department of Electronics & Communication Engineering Central University of Rajasthan Ajmer Kishangarh India Ignion Barcelona Spain Smart Society Research Group Universitat Ramon Llull Barcelona Spain

ISBN: (纸本)9789819719457

The paper describes a rectangular ring-shaped two-element pattern diversity mm-wave MIMO antenna for 5G and IoT applications. The Roggers RT duroid substrate, having a dielectric constant of 2.2 and a height of 0.254 mm is used to design the proposed antenna. Its frequency range of operation is 12.6–35.1 GHz, and its gain is 4.5 dB with fluctuations of fewer than three decibels across the working range. Mutual coupling is less than −17 dB throughout the whole bandwidth, and efficiency is greater than 93%. All MIMO parameters have been computed and verified to fall under permissible bounds. Its small dimension of 1.4 × 1.5 × 0.0254 cm3 makes it economical and suitable for portable devices, 5G base stations, 5G mobiles, IoT terminals, healthcare devices, and a wide range of other mm-wave applications. Performances of the proposed antenna are better when compared to those of reported MIMO antennas. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Microstrip antennas

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A Comprehensive Survey and Implementation of Health Kiosk Innovations: AI Integration, IoT applications, and Predictive Healthcare Solutions 3

A Comprehensive Survey and Implementation of Health Kiosk In...

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3rd international conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics, IITCEE 2025

作者： Amrutesh, Aniverthy Bharadwaj, Shreelakshmi Darshan Kumar, T. Asha Rani, K.P. Gowrishankar, S. Dr. Ambedkar Institute of Technology Department of Computer Science and Engineering Karnataka Bengaluru560056 India

ISBN: (纸本)9798331515911

Kiosks, initially designed for administrative purposes, have rapidly evolved into vital tools in healthcare, offering a range of services such as diagnostics, telemedicine, and health data management. This paper presents a comprehensive survey of health kiosks, emphasizing their application in healthcare environments, particularly with the integration of AI, IoT, and predictive analytics. Key technologies, including advanced biometric sensors and AI-driven health insights, have significantly enhanced their functionality. The economic impact of deploying health kiosks, their integration with existing healthcare systems, and the importance of adhering to international medical standards are thoroughly examined. A review of academic research, patents, and industry innovations sheds light on the latest advancements, while case studies of real-world implementations demonstrate their growing adoption across different sectors. The paper also provides a comparative analysis of kiosk models globally, addressing challenges in deployment. Future trends such as AI and wearable technology integration, blockchain for secure health data management, and personalized healthcare services are explored, highlighting the potential for health kiosks to further revolutionize healthcare delivery. Considering the Literature available a practically feasible Health Kiosk is implemented with a custom ML model deployed with an accuracy of 95.3% is achieved. © 2025 IEEE.

关键词： Electronic health record

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A Hybrid Blockchain Framework for Secure, Scalable, and Energy-Efficient Digital Identity Management with Token-based Selective Disclosure 3

A Hybrid Blockchain Framework for Secure, Scalable, and Ener...

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3rd international conference on Electronics and Renewable systems, ICEARS 2025

作者： Velmurugan, M. Shinzeer, C.K. Maya, G. Ramya, R. Kanimozhi, R. Lathif, Syed Ismail Abdul Vel Tech Rangarajan Dr Sagunthala R&d Institute of Science And Technology Department Of Computer Science & Engineering Chennai600 062 India Lovely Professional University Department of School of Computer Applications Punjab Phagwara144411 India Srm Institute of Science and Technology Faculty of Management Kattankulathur603 203 India K.Ramakrishnan College of Engineering Department of Electronics and Communication Engineering Samayapuram621112 India Muthayammal Engineering College Computer Science and Engineering Rasipuram637408 India Srm Institute of Science and Technology Department of Data Science and Business Systems Chennai603203 India

ISBN: (纸本)9798331509675

Data breaches, identity theft, and the lack of user control within traditional digital identity management systems, it begs a more secure and decentralized alternative. In this study we propose a blockchain based digital identity management framework that implements privacy, security and transparency by employing distributed ledger technology. To provide tamper proof identity storage and automated verification, the proposed model uses cryptographic hashing and smart contracts. The use of a novel token-based access mechanism enables users to safely share their identity data with third parties, while keeping sensitive information out of sight. Security metrics are enhanced by 30% for data integrity with 45% reduction in unauthorized access attempts all through simulations. The framework also achieves improved efficiency reducing identity verification time by 40 percent compared to traditional systems. It offers a promising approach to address important vulnerabilities in centralized identity management in line with the development of marketable and user-friendly digital identity solutions. © 2025 IEEE.

关键词： Data integrity

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The Insight of Clustering algorithms for Emerging Networking Paradigms 12th

The Insight of Clustering Algorithms for Emerging Networking...

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12th international conference on Recent Trends in Computing, ICRTC 2024

作者： Yashoda, M.B. Shivashetty, Vrinda Gopinath, D. Santhosh, Y.N. Bengaluru India Department of Information Science and Engineering Sai Vidya Institute of Technology Bengaluru India

ISBN: (纸本)9789819788354

The evolution of networking paradigms has presented novel challenges and opportunities in network topology management. Clustering algorithms have been proposed for wireless Sensor Networks (WSN), but they could also be used to tackle similar difficulties in the Internet of Things (IoT) domain. The use of clustering would allow for more efficient routing and management of network topology by offloading a significant amount of communication overhead to the cluster head. The primary objective of clustering is to optimize energy consumption. By grouping nodes into clusters, energy management can be effective, extending network lifetime and enhancing overall efficiency. Load balancing is another crucial objective where clustering algorithms strive to distribute network load evenly across nodes, ensuring optimal resource utilization and preventing congestion. We aim to discuss the importance of clustering algorithms in the context of future networking directions, highlighting their applications and benefits. It explores various clustering techniques and analyses their performance and scalability. By understanding the significance of clustering algorithms, researchers and practitioners can develop novel approaches to address data analysis and management challenges, enabling efficient and intelligent networking systems. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： wireless sensor networks

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3rd international conference on Machine Learning, Cloud Computing and Intelligent Mining, MLCCIM 2024

3rd International Conference on Machine Learning, Cloud Comp...

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3rd international conference on Machine Learning, Cloud Computing and Intelligent Mining, MLCCIM 2024

ISBN: (纸本)9789819616930

The proceedings contain 27 papers. The special focus in this conference is on Machine Learning, Cloud Computing and Intelligent Mining. The topics include: Decentralized Optimal Tracking Control of MRMs Under Health Indicator-Based Event-Triggered Mechanism;iterative Learning Control for Nonlinear Switched Continuous-Time systems with Time-Varying Delay;Model Migration and Joint Communication and Computing Resource Allocation in Native AI wireless Networks;FTB-RRP Control for 2-D Continuous-Discrete systems in Roesser Model;Optimal UAVs Placement for TDOA Localization Method Based On An Improved Grey Wolf Optimization Algorithm;A Bat-BP Optimization Algorithm Based System of Dry Ice Decontamination for UAV;Optimal Resource Allocation Algorithm for Multi-user AI Tasks in Native AI Networks;study on Non-intrusive Load Monitoring Method Based on K-means Clustering and Dual Convolutional Neural Networks;research and Application of Computer Vision and Predictive Maintenance in Health Management of Conveying Equipment;attitude Stabilization Control for Unmanned Aerial Vehicle with Robotic Arm Based on Fixed-Time Observer Active Disturbance Rejection Control;state Estimation and Control of Switched Neural Networks with Mode-Dependent Hybrid Dwell Time;Distributed Consensus Control Research of Unmanned Aerial Vehicle (UAV) Swarms Based on Lennard-Jones Potential;lifetime Prediction of Fuel Cell Composite Operating Conditions Based on Genetic Algorithm Optimized Elman Neural Network;a Tiered Native Digital Twin for Telco Networks;defender: The Possibility of Repairing Jailbreak Defects;research on Special Vision Recognition and Fault Alarm System for Vertical Roller;malicious Traffic Classification Algorithm Based on Multimodal Fusion;Enhanced Affine Formation Control in Multi-agent systems with Disturbance Rejection Using RISE Controller;model Predictive Control for Contour Control in Biaxial System.

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3rd international conference on Machine Learning, Cloud Computing and Intelligent Mining, MLCCIM 2024

3rd International Conference on Machine Learning, Cloud Comp...

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3rd international conference on Machine Learning, Cloud Computing and Intelligent Mining, MLCCIM 2024

ISBN: (纸本)9789819616978

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