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2022 IEEE IFEES World engineering Education Forum - Global engineering Deans Council, WEEF-GEDC 2022

作者： Kandakatla, Rohit Penta, Samyuktha Lingam, B. Sinha, Shiwani Chandraprakash, D. Udaya Sri, K. Kg Reddy College of Engineering and Technology Department of Electronics and Communication Hyderabad India Kg Reddy College of Engineering and Technology Department of Computer Science and Engineering Hyderabad India Kg Reddy College of Engineering and Technology Department of Civil Engineering Hyderabad India Kg Reddy College of Engineering and Technology Department of Mechanical Engineering Hyderabad India

ISBN: (纸本)9781665475280

Service learning in India is witnessing a large-scale adoption in higher education through the Unnat Bharat Abhiyan (UBA) program, a national-level service-learning program launched by India's Ministry of Education to promote community engagement and foster social responsibility among undergraduate students. The mission of UBA is to enable higher education institutions to partner with communities who live in rural India and engage in service-learning activities. The program advocates to build long-term engagement between academic institutions and nearby communities so that they could collaborate toward sustainable reciprocal partnerships. One of the goals of UBA is to establish linkages between academia and the community so that the knowledge created in the institutions could be targeted to solve complex societal problems. Higher education institutions that are part of this service-learning initiative were encouraged to do field studies through household surveys and informal interaction with the community members with a goal to identify unmet needs in the community. However, it was observed through prior research that the members of the community are only comfortable sharing their problems after faculty and students gain their trust. The paper presents a case study of a rural immersion experience that was introduced as part of the Unnat Bharat Abhiyan program at a private engineering institution in India. The 2-day rural immersion experience was designed to facilitate discussions among faculty and students with the community's various stakeholders, build trustworthy relationships, and empathize with their problems. The study employed a qualitative approach to investigate how students who were part of the rural immersion exercise described their experiences in the villages. Seven focus group discussions were conducted with 28 students who shared their highlights from visiting the villages and the process taken by them to identify unmet needs in the community. Themati

关键词： Rural areas

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Modeling and Simulation of Electric Vehicle using MATLAB

Modeling and Simulation of Electric Vehicle using MATLAB

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2024 OPJU International technology Conference on Smart Computing for Innovation and Advancement in Industry 4.0, OTCON 2024

作者： Bahuguna, Neeraj Kumar Sati, Govind Gusain, Raj Vidyarthi, Anurag Prakash, Rishi Gowri, R. Gb Pant University of Agriculture and Technology Department of Electrical Engineering Pantnagar India Vaaman Engineers India Ltd. Hindustan Zinc Pmp Department of Instrumentation Engineering Pantnagar India Propagation Research Lab Department of Electronics & Communication Engineering Dehradun India Graphic Era Hill University Department of Computer Science Engineering Dehradun India

ISBN: (纸本)9798350373783

With the progression of technology, the automobile industry has experienced a significant transformation due to the emergence of Electric Vehicles (EVs). EVs offer a sustainable means of transportation that doesn't harm the environment. The decline of global oil reserves and the detrimental effects of air pollution caused by conventional motor vehicles have motivated numerous researchers to explore alternative energy sources for vehicle propulsion. This study aims to investigate power flow calculations to ensure that the amount of electrical energy aligns with the requirements of the electric vehicle. Using MATLAB/Simulink software, a model of a small electric vehicle is designed to achieve optimal power flow response within the EV energy system and this article outlines the process of modeling an Electric Vehicle using MATLAB and Simulink, elucidating different components such as the Motor Model, Battery Model, Power Model, and Regenerative System. By employing Simulink, the designed Electric Vehicle is simulated, and important metrics such as Motor Torque, Vehicle Speed, and State of Charge of the Battery are calculated using a given Driving Cycle. The collected data is then analyzed to enhance the model's performance. © 2024 IEEE.

关键词： MATLAB

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Ai Machine Learning: Transformer Models For Enhanced Natural Language Processing - Techniques And Applications 12

Ai Machine Learning: Transformer Models For Enhanced Natural...

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12th International Conference on Internet of Everything, Microwave, Embedded, Communication and Networks, IEMECON 2024

作者： Pragith, S. Karthik, G.M. Sripriya, T. Rajasekaran, E. Periannasamy, S. Manthandi Aslam, Mohamed Zubair M.A. Department of Computer Science Engineering Vellore Institute of Technology Tamil Nadu Vellore India Vellore Institute of Technology Tamil Nadu Vellore India Department of ECE Jeppiaar Institute of Technology Tamil Nadu Chennai India Department of Science and Humanities V.S.B Engineering College Tamil Nadu Karur India Department of Electronics and Communication Engineering Mallareddy Engineering College for Women Maisammaguda Hyderabad India Department of AI &DS Dhanalakshmi College of Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350387315

Modern technologies are needed to strengthen network security defenses because of the increase in cyber attacks in recent years. Because deep learning in particular allows for real-time threat identification and thorough performance evaluation, artificial intelligence (AI) has become a powerful tool for improving cybersecurity measures. This study examines how deep learning methods can be used in AI cybersecurity frameworks, with an emphasis on how well they can detect and counteract changing cyberthreats. The use of convolutional neural networks (CNNs) and deep neural networks (DNNs) for anomaly detection and pattern identification in network traffic is specifically discussed. The study also investigates the integration of AI-driven analytics to assess the performance and efficacy of security protocols, offering insights into optimizing defensive strategies against sophisticated cyber attacks. By leveraging AI capabilities, organizations can achieve proactive threat management, enhance incident response times, and fortify their networks against emerging cyber threats. This abstract sets the stage for a comprehensive exploration of AI's role in cybersecurity, highlighting its transformative impact on network security operations. © 2024 IEEE.

关键词： Cyber attacks

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Grid-Interactive Novel Resilient Control of Solar PVWind-Battery Storage Microgrid Under Distorted and Unbalanced Grid Voltages

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IEEE Transactions on Consumer electronics 2025年

作者： Gali, Vijayakumar Jamwal, Prashant Kumar Gupta, Nitin Babu, B. Chitti Ahmadi, Mohammad Jawid Morey, Meghraj Sudhakar University of Hertfordshire School of Physics Engineering and Computer Science Department of Electrical and Electronics Engineering HatfieldAL109AB United Kingdom Nazarbayev University Department of Electrical and Computer Engineering Astana Kazakhstan Malaviya National Institute of Technology Department of Electrical Engineering Jaipur India Indian Institute of Information Technology Design and Manufacturing Department of Electronics and Communication Kancheepuram India

Integrating solar photovoltaic (PV), wind, and battery storage (BS) systems into the grid introduces significant power quality (PQ) challenges. In particular, the intermittent nature of solar PV and wind energy systems (WES), combined with nonlinear loads, can lead to grid instability. As a result, maintaining a reliable and high-quality power supply to consumers becomes a substantial challenge. This article presents two novel solutions to address these challenges: the anti-windup mixed-order generalized integrator (AWMOGI) and the adaptive delay operation period filter (ADOPF). The AWMOGI effectively extracts fundamental components from distorted utility grid voltages, minimizing DC offset and reducing steady-state oscillations. Meanwhile, the ADOPF swiftly captures positive sequence voltage components by introducing a two-sampling-interval delay in the d-q coordinate system. The hierarchical-loop controller parameters are optimized using a customized Harris Hawks Optimization (HHO) algorithm, which enhances error reduction and facilitates rapid establishment of reference values for DC-link voltage loop control. An adaptive dynamic power management scheme also enables the microgrid (MG) to manage surplus power from MG sources, reducing stress on the BS and ensuring DC-link voltage stability. The experimental results demonstrate significant improvements in handling utility grid abnormalities, dynamic loads, and intermittent microgrid source operation. The experimental results show a zero DC-off set and steady-state errors, a fast computational time of 35e-5s, and the THD of grid currents of 3.16%, which complies with the IEEE 519 standards. © 1975-2011 IEEE.

关键词： Adaptive filters

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Enhancing Hybrid Electric Vehicle Speed Controller based on Fractional Order PID using Jaya Optimization Algorithm 4

Enhancing Hybrid Electric Vehicle Speed Controller based on ...

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4th IEEE International Conference in Power engineering Applications, ICPEA 2024

作者： Naidu, Kanendra Rajendran, Gowthamraj Mohamad, Hasmaini Awalin, Lilik Jamilatul Kaliannan, Jagatheesan Embrandiri, Manoj School of Electrical Engineering College of Engineering Selangor Malaysia University of Catania Department of Electrical Electronics Engineering and Computer Science Catania Italy Univeritas Airlangga Faculty of Advanced Technology and Multidicipline Surabaya Indonesia Paavai Engineering College Department of EEE Pachal Namakkal India Barium Selat Sdn. Bhd Sungai Besi Kuala Lumpur Malaysia

ISBN: (纸本)9798350344578

The drive for sustainability has pushed forward various avenues in meeting the zero-carbon target. Electrification of vehicles has seen rapid growth, especially in replacing current internal combustion engine vehicles which relies on fossil fuel. The hybrid electrical vehicles (HEVs) that catalyze complete vehicle electrification provide a transition platform for vehicle users. The losses experienced by the HEVs which is contributed by the motor, generator, and battery have to be minimized to ensure efficient hybrid EV performance. The motor controller in the simulation model of the power-split hybrid transmission architecture is optimized using Jaya Optimization Algorithm (JOA). Two objective functions, which are speed regulation error and total electrical power loss are evaluated. Three different analyses for the Fractional order PID controller (FOPID) are carried out. The investigation comprises of comparative analysis with PID controller for first objective function, an analysis on FOPID controller based on second objective function, and an analysis of three different driving patterns. Overall improvement is observed in the integration of FOPID for HEV to enhance the performance of speed regulation and total electrical losses. © 2024 IEEE.

关键词： Optimization

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Data Fusion and Analysis Techniques for Enhanced Decision-Making in IoT Environments 7

Data Fusion and Analysis Techniques for Enhanced Decision-Ma...

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7th International Conference on electronics, Communication and Aerospace technology, ICECA 2023

作者： Deepa, S. Radhika, M. Diwakar, Meenakshi Rufina, Princy Nithya, A. Mohanapriya, M. Panimalar Engineering College Department of Electronics and Communication Engineering Tamilnadu Chennai India R.M.D. Engineering College Department of Information Technology Tamilnadu Chennai India S.A Engineering College Department of AI & DS Tamilnadu Chennai India Prince Shri Venkateswara Padmavathy Engineering College Department of Computer Science and Engineering Tamilnadu Chennai India R.M.K.College of Engineering and Technology Department of Computer Science and Engineering Tamilnadu Chennai India Jeppiar Institute of Technology Department of AI & DS Tamilnadu Chennai India

ISBN: (纸本)9798350340600

The proliferation of Internet of Things (IoT) devices has resulted in an inundation of diverse data sets that have the potential to considerably improve decision-making across many domains. This research work investigates the potential for modern data integration and analysis techniques to improve the decision-making abilities of IoT networks. Using regulated data acquisition, data integration, and cutting-edge analytic methods, the proposed work develops a solution to improve the accuracy of judgments. Using examples from smart manufacturing and healthcare monitoring, the proposed work demonstrates how the new methodology increases productivity and yields actionable data. Comparative analyses indicate that new methodologies markedly outperform those of the competition. This study identifies areas for future research on how integrating disparate IoT data with advanced analytics could lead to improved decision-making in a variety of contexts. © 2023 IEEE.

关键词： Internet of things

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Studying the Fundamentals of Internet of Things (IoT) in the Healthcare Applications 1

Studying the Fundamentals of Internet of Things (IoT) in the...

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1st International Conference on Healthcare Innovations, Software and engineering Technologies, HISET 2024

作者： Abu Eid, Aws Ismail Kadam Rangrao, Shrikant Patil Abhijit, Seema Sharma, Lakshay Rani, D Shobha Ukirade, Chaitali Arab Open University Faculty of Computing Studies Amman Jordan Jaywant College of Engineering and Polytechnic Department of Computer Science Engineering Karad India Jaywant College of Management Karad India Indraprastha Institute of Information Technology Delhi India Institute of Aeronautical Engineering Department of Electrical and Electronics Engineering Hyderabad India Department of Obstetrics and Gynecology Karad India

ISBN: (纸本)9798350360707

The Internet of Things (IoT) has brought smart healthcare systems to the medical industry. These systems are typically made up of a network, a remote server, and sensors with smart capabilities. The primary goals of this system are to offer multidimensional feature monitoring and fundamental therapy recommendations. The primary goals of Internet of Things (IoT)-based healthcare services are to enhance quality of life and offer a great user experience at an affordable price. The primary purpose of IoT is to give elderly patients with chronic illnesses access to trustworthy, efficient, and intelligent healthcare services as well as connectivity to the medical resources that are readily available. Thus, many studies are developed on the different applications which worked on the IoT for the healthcare which includes wearable as well as non-wearable devices or machines. Thus, it makes the users to obtain the data from anywhere and wherever required for the study or analysis of the patients. In the meantime, the Internet of Things is expanding to include even the tiniest sensors and the fundamentals of automation and machine-to-machine communication. © 2024 IEEE.

关键词： healthcare internet of things (IoT) network service

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A Novel Design SDNS Framework for High end Level Communication (5G) Network 4

A Novel Design SDNS Framework for High end Level Communicati...

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4th IEEE International Conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2024

作者： Deora, Mahipal Singh Saravanan, M. Sunitharekha, G. Pinkeyroshan, K.P.V. Mohammed, Safaa Hallol Abdtawfeeq, Tareq Hafdhi Bhupal Nobles University Computer Science & Engineering Udaipur India Ifet College of Engineering Department of Ece College Tamilnadu Villupuram India Hyderabad India Meenakshi College of Engineering Department of Electronics and Communication Engineering India National University of Science and Technology Collage of Pharmacy dhi qar64001 Iraq Al-farahidi University baghdad Iraq

ISBN: (纸本)9798350360165

Adding flexibility to 5G networks through circuit spinning an adaptable is a viable approach. Key components such as Network slicing, software-defined networking (SDN), and network service virtualization (NFV) are utilized in various innovative ways to enable end-to-end (E2E) isolation services. These methods facilitate the production of desired outputs, ensuring that each network slice is maintained and provisioned as necessary. The project's goal is to develop a website with planned and efficient content distribution using machine learning, incorporating dynamic slices with updated scheduling.A list of primary Key Performance Indicators (KPIs) including CPU power, bandwidth, latency, and connectivity, are used with a substrate manufacturing device that comes equipped with a protective layer to ensure that performance is optimal and safety is not compromised. In addition, the optimization approach, namely ADAM, with an MLP, is used to create network slices. Network slices for any service that is demanded are classified as massive device-type communication (mMTC), ultra-reliable low-latency communication (uRLLC), and enhanced mobile broadband (eMBB. This classification ensures that not just network slices are provided but that the resources are provided in an optimal manner. The Dijkstra algorithm is used to allocate the resources, such that the shortest path amongst the nodes of the substrate network is determined to maximize both user accessibility and the efficiency of resource utilization. These approaches, in a comprehensive manner, are sought to be introduced to improve the efficiency of the overall system in catering to the needs of modern 5 G networks. © 2024 IEEE.

关键词： 5G mobile communication systems

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Enhancing Lymph Node Classification in Rectal Cancer MRI Images Through a Multi-Model Approach

Enhancing Lymph Node Classification in Rectal Cancer MRI Ima...

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2024 IEEE International Conferences of AI, Science, engineering, and technology, AIxSET 2024

作者： Gupta, Rishit Iwahori, Yuji Funahashi, Kenji Bhuyan, M.K. Bhatt, Manish Kijsirikul, Boonserm Wang, Aili Ouchi, Akira Shimizu, Yasuhiro Indian Institute of Technology Guwahati Dept. of Electronics & Electrical Eng. Assam Guwahati India Chubu University Dept. of Computer Science Kasugai Japan Nagoya Institute of Technology Dept. of Computer Science Nagoya Japan Chulalongkorn University Dept. of Computer Engineering Bangkok Thailand Harbin University of Science and Technology Higher Educational Key Laboratory Harbin China Aichi Cancer Center Hospital Dept. of Gastroenterological Surgery Nagoya Japan

ISBN: (纸本)9798350390995

Rectal cancer remains to be a major issue worldwide, necessitating accurate and precise methods for proper classification of lymph nodes in MRI scan images to guide treatment decisions. The use of deep learning based techniques can help with the task of classification. This research focuses on enhancing the process of lymph node classification in rectal cancer MRI images by using a multi-model approach. Firstly, we explore the use of diffusion models in data augmentation, to produce synthetic lymph node images to counter the issue of limited dataset size. Secondly, Real-ESRGAN and Swin2SR super-resolution techniques are examined for their ability to improve image quality and hence enhance the accuracy of lymph node classifications. Lastly, ConvNeXt is employed as an advanced technique used to improve overall performance at classifying lymph nodes for rectal cancer. Through a series of detailed experiments on the dataset consisting of T2-Weighted Axial MRI scans from 54 patients, we demonstrate the effectiveness of our approach in classification of lymph nodes. The metrics like accuracy and precision exhibit significant improvements, highlighting the superiority of our multi-model approach. © 2024 IEEE.

关键词： Magnetic resonance imaging

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IoT Enabled Driver Compatible Cost-Effective System for Drowsiness Detection with Optimized Response Time 3rd

IoT Enabled Driver Compatible Cost-Effective System for Drow...

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3rd EAI International Conference on Cognitive Computing and Cyber Physical Systems, IC4S 2022

作者： Sarkar, Argha Kundu, Mayuri Pareek, Prakash Gupta, Nishu Reis, Manuel J. Cabral S. School of Computer Science and Engineering REVA University Karnataka Bangalore560064 India Department of Electronics and Communication Engineering Vishnu Institute of Technology Andhra Pradesh Bhimavaram534202 India Department of Electronic Systems Faculty of Information Technology and Electrical Engineering Norwegian University of Science and Technology Gjøvik2815 Norway Engineering Department UTAD/IEETA Vila Real5001-801 Portugal

ISBN: (纸本)9783031289743

The present work researches driver drowsiness, which constitutes a huge problem, and can turn into fatal incidents potentially involving the losing of lives, being it while driving in a highway (car, bus, truck, etc.), in the railway, or any other transportation mean (ship, airplane, etc.). Recent technology has been involved in the study of the fatigue behaviour. The purpose of this work is to identify the in-driver’s drowsiness, contributing to get rid of the accidents, mainly during the night, and to ensure better safety in train and on the highways. A camera is used to capture images from the driver, and face detection is executed in real-time to find out the exact position of driver’s face. Here, the blinking of the driver’s eye is under consideration. The fundamental concept lies in the closing of the driver’s eye for a specific duration of time. If the closing time exceeds that certain duration, drowsiness is detected and an alarm is sounded for awareness. Python and OpenCV (using Haarcascade library) are the fundamental programming platforms for sensing the facial attributes. In this work, a cost-effective system for the driver’s drowsiness detection is aimed. Further, the result also indicates the reduction of response and processing time, which is ideal for real time detection. © 2023, ICST Institute for computer Sciences, Social Informatics and Telecommunications engineering.

关键词： Python

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