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2024 International Conference on Intelligent Computing and Sustainable Innovations in technology, IC-SIT 2024

作者： Mathias, Ajisha Pradeepthi, Gubba Vivek, Ongole Kishore, Kummara R&D Institute of Science and Technology Vel Tech Rangarajan Dr.Sagunthala Department of ECE Chennai India

ISBN: (纸本)9798350369175

Ship wake identification is crucial for analyzing ocean surface synthetic aperture radar (SAr) pictures because ship wakes typically include important vessel information. A significant proportion of detection algorithms make use of the linear traits of ship wakes by converting the lines in the spatial domain into either dark or light points in a transform domain, using techniques like the Hough or radon transforms. This study presents a novel approach for detecting ship wakes using a Gaussian Mixture Model (GMM). The method involves obtaining the radon transform of the SAr image, which enhances the visibility of linear features. In comparison to the state of art methodologies, the findings show that the method is successful in achieving greater wake detection accuracies. © 2024 IEEE.

关键词： Synthetic aperture radar

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design and development of Efficient Feeding Network Structure for Patch Antenna Array Modules in UAV Communication Applications

Design and Development of Efficient Feeding Network Structur...

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International Conference on VLSI, Signal Processing, Power Electronics, IoT, Communication and Embedded Systems, VSPICE-2022

作者： Bharati, Chandravijay Prasanna, r. Balasubramanian, E. Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Avadi Chennai India Department of Mechanical Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Avadi Chennai India

ISBN: (纸本)9789819944439

This article focused on the development of microstrip patch antenna with linear and planar array distribution structures. Ansoft HFSS electromagnetic simulation software was used to analyze the radiation and reflection parameter of the designed element. Initially, single element antenna was realized and further 1 × 2, 2 × 2, and 1 × 4 array structures were analyzed with a due consideration of two different substrate materials such as duroid-5880 and Fr-4. 1 × 4 array antenna with duroid-5880 offers highest gain of 14.12 dB. To validate the design concept, 1 × 2 array antenna was fabricated. S11 parameter was measured using a vector network analyzer and it has downward frequency shift by 54.5 MHz as compared to simulated results. The radiation characteristic of the antenna was measured on anechoic chamber, and the E/H plot reveals that antenna is unidirectional. Measured gain is enhanced by 7.82 dB as compared to simulated results. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Unmanned aerial vehicles (UAV)

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Machine Learning in Human resources Management for Higher Education institutes 1

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7th International Conference on Intelligent Computing and Optimization, ICO 2023

作者： Karthikeyan, M. Mariyappan, M.S.r. Sridevi, J. Kumar, S. Vishnu School of Management Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Avadi600062 India Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Avadi600062 India

ISBN: (数字)9783031733185

ISBN: (纸本)9783031733178

This research article explores the intersection of Machine Learning (ML) and the Internet within the domain of Human resource Management (HrM) in Higher Education institutes (HEIs). It investigates how these technologies can reshape Human resource (Hr) practices, specifically focusing of faculty retention. The ML model is designed to act upon the collected data to provide immediate support in aiding Hr professionals in predicting and managing employee retention. The research also highlights the importance of data collection using Internet, ensuring speeding and ethical data handling practices. The article encompasses a comprehensive review of existing literature, detailed methodology, practical implementation, and rigorous assessment of the proposed model, aiming to provide a holistic view of this transformative landscape in HrM. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Adversarial machine learning

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detection of Tongue-Based Myeloid Sarcoma Using Novel Cat Swarm Optimization and Comparison with Particle Swarm Optimization Algorithm 7

Detection of Tongue-Based Myeloid Sarcoma Using Novel Cat Sw...

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7th International Conference on Circuit Power and Computing technologies, ICCPCT 2024

作者： Nalini, N. deva Shahila, d Ferlin Ashwini, A. Vaishnavi, T. rosi, A. Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Electronics and Communication Engineering India

ISBN: (纸本)9798350372816

the exact scope of this research work is to compare novel cat swarm optimisation to particle swarm optimisation for tongue-based Myeloid Sarcoma detection. To perform the detection of tumor and leukemia, ten sample tongue datasets were subjected to novel Cat Swarm Optimisation and Particle Swarm Optimisation (PSO) methods, and the fiducial interval remaining at 95%. According to the simulation's performance metrics, Novel Cat Swarm Optimisation outperforms PSO (79%) in terms of accuracy, with a significant level of p = 0.001 (p0.05) in SPSS statistical analysis. From this study, the accuracy of detection of tumor and leukemia using Novel Cat Swarm Optimization showed better results than the PSO algorithm for the considered sample images. © 2024 IEEE.

关键词： Particle swarm optimization (PSO)

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Post-Quantum Cryptography Security with CSPM for Secure data Transmission in Cloud Environments 4

Post-Quantum Cryptography Security with CSPM for Secure Data...

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4th International Conference on Ubiquitous Computing and Intelligent Information Systems, ICUIS 2024

作者： rajkumar, N. Kumar, K. Kishore Gokul, M. durai, S. Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Cse Department Chennai India

ISBN: (纸本)9798331529635

Quantum computing poses a significant threat to traditional cryptographic systems, necessitating the exploration of robust alternatives to secure data transmission in the cloud. This abstract delves into the integration of Post-Quantum Cryptography (PQC) and Cloud Security Posture Management (CSPM) as a comprehensive solution. The proposed framework advocates for the adoption of a variant of the McEliece cryptosystem within the cloud infrastructure, providing resistance against potential quantum attacks. Encryption, fortified by Post-Quantum Cryptography, emerges as the dominant method for ensuring the security of cloud-stored data. In parallel, Cloud Security Posture Management (CSPM) is introduced as a set of security protocols designed to identify and remediate cloud misconfigurations, enhancing the overall security posture. This research highlights the synergy between PQC and CSPM, showcasing their collective effectiveness in mitigating emerging threats in cloud computing. The integration of Quantum Key distribution (QKd) further enhances data security, ensuring the confidentiality and integrity of transmitted information. The proposed model not only addresses current data breach challenges but also anticipates the evolving landscape of quantum computing, providing a forward-looking solution for secure data transmission in cloud environments. © 2024 IEEE.

关键词： Cloud security

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Intelligent Poka Yoke System for Secure and Efficient Industrial Equipment Monitoring and Control 3

Intelligent Poka Yoke System for Secure and Efficient Indust...

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3rd International Conference on Artificial Intelligence For Internet of Things, AIIoT 2024

作者： Arun, C.A. Manohar, relangi Sanjay Kirupa Krishan, G. Khan, Menaz Sharma, Aditya raj, Tanya Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Dept of ECE Chennai India

ISBN: (纸本)9798350372120

Ensuring the safety and efficiency of manufacturing processes is required in Industry 4.0. To address this, an intelligent Poka Yoke system is proposed, specifically designed for monitoring and controlling Industry Programmable Logic Controller machines. This system prioritizes security by requiring strict staff authorization, providing timely alerts, and granting access privileges based on predetermined criteria. It efficiently prevents unauthorized access and minimizes potential industrial dangers by leveraging modern technology such as employee access keys and NFC authentication. NFC is used to authenticate employee credentials, allowing access to only approved jobs by using raspberry Pi Pico as a controller. The technology detects anomalies and safety threats in real time while continuously monitoring equipment operations. The generated data is virtualized in a user-friendly web application, conveniently stored in Mongo dB cloud, allowing for instant notifications and automated equipment shutdown when necessary. This system improves workplace security, safety, and efficiency by streamlining operations and increasing productivity. © 2024 IEEE.

关键词： Industry 4.0

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IoT based Smart Voice and Gesture Controlled Wheelchair 5

IoT based Smart Voice and Gesture Controlled Wheelchair

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5th International Conference on Electronics and Sustainable Communication Systems, ICESC 2024

作者： Pappa, C. Kanmani Kumar, d. rajesh Preethi, d. Boopathy, M. Manimara Javeed, S. Imran Vel Tech Rangarajan Dr Sagunthala R&d Institute of Science and Technology Department of Ece Chennai Avadi India

ISBN: (纸本)9798350379945

The voice and gesture-controlled wheelchair introduces a new solution for the mobility of physically challenge ones. With the help of both voice command control and gesture control the wheelchair helps the person to navigate easily trough their life with ease and precision. By combining the three modes of control that are manual, gesture and voice control, the user can easily interact with the wheelchair without any difficulty. All the three modes of commands will be given through the app with the help of mobile. The wheelchair can be connected through Bluetooth with the mobile and the inputs will be given from the mobile phone through the application that is already installed in the mobile phone. The commands will be given through the mobile phone and the command will be transferred with the help of Bluetooth module connected to microcontroller. The required command will be executed with the help of microcontroller which has a set of command codes uploaded in it. © 2024 IEEE.

关键词： Wheelchairs

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Enhancing Early diabetes detection using Ensemble Machine Learning Models for Improved Prediction and Patient Care 5

Enhancing Early Diabetes Detection using Ensemble Machine Le...

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5th International Conference on Sustainable Communication Networks and Application, ICSCNA 2024

作者： Shanthini Watson Benjamin, Minu Inba Syed, Arshad Vamsi, Tamma raja Kumar, P.S.d.Sai Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Department of Computer Science & Engineering Chennai India

ISBN: (纸本)9798331530013

Millions of individuals worldwide suffer from diabetes, a chronic condition that must be detected early to avoid major health issues like kidney failure, nerve damage, and heart disease. By using ensemble technique which combines machine learning (ML) approaches and evaluate the outputs and generates final prediction, then diabetes can be predicted more precisely. random Forest, Support Vector Machine (SVM), and Logistic regression, were the machine learning techniques and Voting Classifier is the ensemble classification model which were examined in this study. The study evaluated these model's ability to predict diabetes using datasets such as the Pima Indian diabetes dataset. Through the integration of Support Vector Machine (SVM), random Forest, and Logistic regression algorithms using a Voting Classifier, proposed model achieves an accuracy of 79%. This ensemble approach demonstrates superior performance compared to individual algorithms, with improved precision (0.81) and recall (0.78). It is identified that Predictive accuracy is found to be highly dependent on key parameters including glucose, BMI, and age with correlation coefficients of 0.47, 0.29, and 0.24 respectively. This method showed that combining multiple ML algorithms can significantly enhance diabetes diagnosis and care in addition to improving prediction capabilities. In the end, the study emphasizes how machine learning can completely change the way diabetes is treated and stresses how crucial it is to keep developing and using these technologies in order to improve patient outcomes. © 2024 IEEE.

关键词： Adversarial machine learning

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MOEAGAC:an energy aware model with genetic algorithm for efficient scheduling in cloud computing

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International Journal of Intelligent Computing and Cybernetics 2022年第2期15卷 318-329页

作者： Nageswara Prasadhu Marri N.r.rajalakshmi CSE Vel Tech Rangarajan Dr Sagunthala R&D Institute of Science and TechnologyChennaiIndia

Purpose-Majority of the research work either concentrated on the optimization of scheduling length and execution cost or energy optimization *** research aims to propose the optimization of makespan,energy consumption and data transfer time(dTT)by considering the priority *** research work is concentrated on the multi-objective approach based on the genetic algorithm(GA)and energy aware model to increase the efficiency of the task ***/methodology/approach-Cloud computing is the recent advancement of the distributed and cluster *** computing offers different services to the clients based on their requirements,and it works on the environment of *** environment contains the number of data centers which are distributed *** challenges faced by the cloud environment are energy consumption of the data *** scheduling mechanism is needed to allocate the tasks to the virtual machines which help in reducing the *** paper concentrated on the minimizing the consumption of energy as well as makespan value by introducing the hybrid algorithm called as multi-objective energy aware genetic *** algorithm employs the scheduling mechanism by considering the energy consumption of the CPU in the virtual *** energy model is developed for picking the task based on the fitness *** simulation results show the performance of the multi-objective model with respect to makespan,dTT and energy ***-The energy aware model computes the energy based on the voltage and frequency distribution to the CPUs in the virtual *** directed acyclic graph is used to represent the task *** proposed model recorded 5% less makespan compared against the MOdPSO and 0.7% less compared against the HEFT *** proposed model recorded 125 joules energy consumption for 50 VMs when all are in active ***/value-This paper proposed the multi-

关键词： Cloud computing Priority roulette wheel selection Genetic algorithm Population

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Power efficient module in single chip for the energy optimized dynamic IoT communication

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Multimedia Tools and Applications 2025年第10期84卷 8107-8126页

作者： Gaikwad, Nitesh Shiyamala, S. Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr. Sagunthala R &D Institute of Science and Technology Tamil Nadu600062 India

The design of a power-efficient Internet of Things (IoT) dynamic communication system is the most required task for digital applications. However, allocating the optimal power based on the user requests is not an easy task. So, the current research article has planned to design a novel Firefly-based Power Estimation and Allocation (FbPEA) strategy for the communication microarchitecture. Here, the presented model is processed on the power chip of the microarchitecture module. Consequently, the data has been transmitted, and parameters were estimated in the LabView environment. Moreover, designing the microarchitecture of the LabView platform is new in the IoT communication fields. Compared to other tools, LabView has better power optimization and execution time results. Hence, using the LabView tool for the microarchitecture design has reduced the computation cost and complexity score of the designed FbPEA dynamic communication microarchitecture. The designed microarchitecture's efficiency has been verified with some critical parameters like power usage, execution time, and energy consumption. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Internet of things

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