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3rd IEEE international conference on Electrical Power and Energy systems. ICEPES 2024

作者： Bihari, Saket Singh, Anand LNCTU Electrical & Electronics Department Bhopal India

ISBN: (纸本)9798350390728

As global warming continues to accelerate, distributed generators based on renewable energy sources play an important role in power generation. Wind, solar, diesel generators, genets and battery storage systems.will provide large amounts of electricity in the near future. Powered by a variety of renewable and unconventional micro power sources, these distributed power sources offer benefits such as environmental friendliness, scalability, and adaptability, making them an attractive option for modern power system designs. A micro grid is a system of consistent loads and DG that operate as a single manageable unit. This setup reduces inefficiencies caused by multiple reverse power conversions in conventional alternating current or direct current grids. It also helps integrate variable renewable energy sources and loads, whether alternating current or direct current, into power systems. Regulars can modify the micro grid to meet specific needs, such as improving local reliability, reducing feeder losses, providing local voltage support, improving efficiency through waste heat utilization, reducing voltage sag or Providing uninterrupted power. Solar panels, wind turbines, generators and batteries provide electricity in these micro grids. The control system of the inverter has been updated to allow correct conversion from alternating current to direct current and direct current to Alternating current. Furthermore, the performance of the optimal fuzzy controller is equivalent to that of the proportional-integral controller. © 2024 IEEE.

关键词： Waste heat utilization

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proceedings - 2023 3rd international conference on Pervasive computing and Social Networking, ICPCSN 2023

Proceedings - 2023 3rd International Conference on Pervasive...

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3rd international conference on Pervasive computing and Social Networking, ICPCSN 2023

ISBN: (纸本)9798350322842

The proceedings contain 293 papers. The topics discussed include: battery energy management systems.in active distribution network;FMCG market analysis for wholesalers and retailers using machine learning;detection of insider threats using deep learning;bio-inspired optimization with transfer learning based crowd density detection on sparse environment;an overview on breast cancer detection and classification methods using machine learning techniques;disease prediction using random forest classifier by machine learning application;a study on working and applications of sequential deep learning models;Internet of Things towards the implementation of a smart city;enhancing supply chain traceability with blockchain technology: a study on dairy, agriculture, and seafood supply chains;and customer segmentation and market analysis for portfolio generation.

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2024 3rd international conference on Sustainable Mobility Applications, Renewables and Technology, SMART 2024

2024 3rd International Conference on Sustainable Mobility Ap...

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3rd international conference on Sustainable Mobility Applications, Renewables and Technology, SMART 2024

ISBN: (纸本)9798331532925

The proceedings contain 77 papers. The topics discussed include: a novel asymmetric split-spoke-type variable flux memory machine;a novel asymmetric variable flux memory machine with hybrid-layer permanent magnets;a novel stator surface-mounted permanent magnet machine with asymmetric stator pole configuration;achieving sustainable software systems.by reducing bloat and by promoting green practices in software engineering education;an efficient design optimization method for consequent-pole asymmetric rotor hybrid interior permanent magnet synchronous machine;design of gravity energy storage switched reluctance linear motor;newton-Raphson method using HHL algorithm for power flow quantum computing;and a new non-recursive analytical calibration approach for Li-ion ECMs based on voltage gradient and sigmoid function.

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3rd international Mobile, Intelligent, and Ubiquitous computing conference, MIUCC 2023

3rd International Mobile, Intelligent, and Ubiquitous Comput...

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3rd international Mobile, Intelligent, and Ubiquitous computing conference, MIUCC 2023

ISBN: (纸本)9798350306231

The proceedings contain 64 papers. The topics discussed include: enhancing counter synchronization in a secure communication scheme for can-based automotive embedded systems.implementation, fabrication and unit testing of phased antenna arrays for Wi-Fi indoor positioning;hybrid approach for COVID-19 severity identification;multimodal Arabic retrieval and recommendation system;key lessons from microservices for data mesh adoption;a comprehensive review on transformers models for text classification;and a run-length and discrete cosine transform based technique for image splicing detection.

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Efficient Signal Processing: Harnessing distributed Arithmetic for High-Speed FFT Operations 3

Efficient Signal Processing: Harnessing Distributed Arithmet...

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

作者： Bharathi, M. Mohanarangam, Krithikaa Shirur, Yasha Jyothi M. Andhra Pradesh Tirupati India Symbiosis Institute of Technology Pune India Bnm Institute of Technology Electronics and Communication Engineering Bangalore India

ISBN: (纸本)9798331515911

The present article introduces a novel approach to significantly enhance the computational efficiency of modern Digital Signal Processing (DSP) processors. The algorithm enhances the efficiency of Sum of Products (SOP) operations, which are essential for real-time signal processing applications, by utilizing distributed Arithmetic (DA) techniques for the Fast Fourier Transform (FFT) and its inverse (Inverse FFT) (IDFT) computations. The present study undertakes an exhaustive quantitative analysis to assess the computational delays of the proposed 2, 4, and 8-point Fast Fourier Transform (FFT) and Inverse Discrete Fourier Transform (IDFT) across various bit representations (4, 8, and 16-bit). For example, when using 4-bit representations, the computational delays for a 2-point Fast Fourier Transform (FFT) are measured to be 13.318ns, 30.629ns for a 4-point FFT, and 27.779ns for an 8-point FFT. Similarly, the delays for the 2-point Fast Fourier Transform (FFT) in an 8-bit representation are 13.727ns, the 4-point FFT in 22.276ns, and the 8-point FFT in 30.592ns. The study further includes the addition of appropriate delays for IDFT operations, which enhances the understanding of the effectiveness of the approach suggested in various scenarios. Furthermore, the research presents and evaluates three distinct categories of transforms, namely 2-point, 4-point, and 8-point FFT and IDFT structures. These structures utilize different quantities of Look-Up Tables (LUTs) for computational purposes. The research showcases the exceptional computing efficiency of the suggested design through detailed quantitative analysis, emphasizing its potential advantages in improving DSP implementations in practical situations. © 2025 IEEE.

关键词： Inverse problems

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Multi-Terminal Collaborative distributed Garden Planning System Integrating CG Technology 3

Multi-Terminal Collaborative Distributed Garden Planning Sys...

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3rd international conference on Pervasive computing and Social Networking, ICPCSN 2023

作者： Wang, Ye Liu, Qi School of Art Design and Media Sanda University Shanghai201209 China

ISBN: (纸本)9798350322842

The fast distributed garden planning system in colleges and universities is one of the mainstream applications of contemporary computers. The latest traditional methods usually use the GPU full virtualization technology as an entry point to improve the problem of a single user and a single computer, so that a physical computer can shared by multiple users without interfering with each other. With this basis, this research study designs the novel multi-terminal collaborative distributed garden planning system integrating CG technology. Key innovations are: (1) The parallel SSOR-AI preconditioning combined with the CG algorithm is proposed to improve the traditional CG model. (2) The designed multi-terminal collaboration model considers the heterogeneous structure that will be more robust for the complex data. (3) The virtual image model is designed to finish the whole work flow. In the experiment part, the data is collected from Baidu search engine with the size of more than 1000000, the various tests are conducted to validate the performance. © 2023 IEEE.

关键词： Search engines

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Intelligent Image Captioning with InceptionV3, LSTM, and PySpark Integration 3

Intelligent Image Captioning with InceptionV3, LSTM, and PyS...

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

作者： Kurian, Thanu Mathew, Jimsha K. Syam Dev, R.S. Anand, P.K. Vignesh, A. Rakshith, B.S. New Horizon College of Engineering Dept of Artificial Intelligence and Machine Learning Bengaluru India

ISBN: (纸本)9798331515911

Image captioning is a challenging task in artificial intelligence that involves generating descriptive captions for images automatically. In this project, we propose a novel approach leveraging advanced technologies such as PySpark, LSTM, and InceptionV3 to develop an effective image captioning system. We harness the power of PySpark, a distributed computing framework, to efficiently process large-scale image datasets and extract high-level features from images using the InceptionV3 convolutional neural network (CNN) model. These features capture the semantic information present in the images and serve as input to the caption generation model. The caption generation model utilizes LSTM neural network as the decoder component. LSTM is well-suited for sequential data processing and is capable of generating coherent and contextually relevant captions based on the extracted image features. The InceptionV3 model acts as the encoder, extracting meaningful visual features from input images, while the LSTM decoder generates captions by decoding these features into natural language descriptions. This multimodal approach enables the model to understand and describe the content of images accurately. Through experimentation and evaluation on diverse image datasets, our proposed system demonstrates promising results in generating accurate and human-like captions for a wide range of images. By integrating PySpark, LSTM, and InceptionV3, our image captioning system achieves state-of-the-art performance, highlighting the effectiveness of leveraging advanced technologies in solving complex AI tasks. © 2025 IEEE.

关键词： Convolutional neural networks

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Multi-Agent systems.for Autonomous IoT Network Management Using distributed Reinforcement Learning 3

Multi-Agent Systems for Autonomous IoT Network Management Us...

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3rd international conference on Intelligent systems. Advanced computing, and Communication, ISACC 2025

作者： Neelamegam, G. Venkatesan, Rajaram Ramya, S.R. Ramya, R.S. Akshya, J. Sundarrajan, M. Choudhry, Mani Deepak VSB College of Engineering and Technology Department of Computer Science and Engineering Tamil Nadu Coimbatore India Builders Engineering College Department of Artificial Intelligence and Data Science Tamil Nadu Tirupur India Dr NGP Institute of Technology Department of Computer Science and Engineering Tamil Nadu Coimbatore India Sri Ramakrishna Engineering College Department of Computer Science and Engineering Tamil Nadu Coimbatore India SRM Institute of Science and Technology Department of Computational Intelligence Tamil Nadu Chennai India SRM Institute of Science and Technology Department of Networking and Communications Tamil Nadu Chennai India SRM Institute of Science and Technology Department of Computing Technologies Tamil Nadu Chennai India

ISBN: (纸本)9798331523893

The ever-growing complexity of IoT networks ignited by their wide scale adoption in applications such as smart cities, the industrial automation, and health care, compelled to develop sophisticated yet resource efficient and scalable network management solution. Centralized systems.are traditional in architecture, which leads to higher latency and bottlenecks, while decentralized systems.can distribute workloads however the lack of adaptability to real time, along with the difficulty of extracting maximum resource usage, are limitations. In recent years, reinforcement learning (RL) based approaches have taken shape as a promising alternative to facilitate the automated learning and optimisation of task management. However, there are two challenges for existing RL based methods: slow convergence, inefficient priority assignment of tasks, and poor coordination amongst agents in the case of dynamic, large scale IoT environment. To solve these challenges, in this research we propose a distributed reinforcement learning based multi agent framework for managing IoT network. The framework also integrates a task prioritization mechanism to dynamically choose an optimal task allocation solution. Further validation was performed in a simulated IoT environment where real world inspired datasets were used. The proposed framework demonstrated 30% more task throughput than centralized, 25% less latency than decentralized, and 40% more energy efficiency than current RL based systems. The system was further validated using advanced visualizations such as anomaly detection maps and resource allocation efficiency graphs, demonstrating its capacity to manage dynamic load of tasks and resource allocation. The proposed framework addresses the critical limitations of current methods, through scalable, adaptive, and energy efficient framework for managing IoT network, and accordingly helps advancing the intelligent and autonomous IoT systems. © 2025 IEEE.

关键词： Resource allocation

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Optimizing Line Losses In distributed Electrical systems.Featuring V2G Integration 3

Optimizing Line Losses In Distributed Electrical Systems Fea...

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3rd IEEE international conference on Power Electronics, Intelligent Control and Energy systems. ICPEICES 2024

作者： Goud, B.Poojith Sreekar, M. Jain, Hari S. Vardhaman College Of Engineering Electrical and Electronics Engineering Shamshabad Hyderabad India

ISBN: (纸本)9798350387193

The growing demand for electric vehicles (EVs) has opened a new avenue for distributed energy systems.based on battery energy storage systems.(BESS). EVs, if integrated can provide a large BESS. Together with solar energy-based charging, the system can support energy affordability. The integration of vehicle-to-grid (V2G) technology is investigated in this study as an approach of reducing distribution line losses, thereby making a distribution even more efficient. This study focuses on the central part of the V2G systems.in exploring the bidirectional energy flow between electric vehicles and the power grid. This same bidirectional charging technology also allows power utilities to coordinate charging periods to minimise impact on the larger grid. This paper addresses the potential of a V2G system to optimize grid operations and reduce losses in distribution lines by using connected electric vehicle batteries as distributed energy storage units. This design evaluates the impact of his V2G integration on distribution system and details the economics of line loss, conductor cost and reliability of the system. The paper also discusses the technical challenges and suggests regulatory considerations associated with V2G integration within an existing power grid. Furthermore, this research quantifies the effective earnings and financial benefits brought by implementing V2G technology. © 2024 IEEE.

关键词： Vehicle-to-grid

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DDoS: distributed denial of service attack in communication standard vulnerabilities in smart grid applications and cyber security with recent developments

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ENERGY REPORTS 2023年 9卷 1318-1326页

作者： Hasan, Mohammad Kamrul Habib, A. K. M. Ahasan Islam, Shayla Safie, Nurhizam Abdullah, Siti Norul Huda Sheikh Pandey, Bishwajeet Univ Kebangsaan Malaysia Fac Informat Sci & Technol Ctr Cyber Secur Bangi 43600 Selangor Malaysia UCSI Univ Inst Comp Sci & Digital Innovat Kuala Lumpur Malaysia Jain Univ Bangalore India

Smart grid system is evident with control technologies and digital communications systems. The cyber-physical system is a critical infrastructure connected with complex drives and devices. The modern smart grid's prominent communication standard adopts high scalability, supports numerous communication devices' input/outputs, and has multi-vendor interoperability. Cyber-attack leads to an unstable power grid system and enormous economic loss. Throughout different cyber-attack, distributed denial of service attack is mostly destructive to smart grid infrastructure. This paper investigates smart grid cyber security systems.and the communication vulnerabilities of other communication protocols. A comprehensive study on distributed denial of service attack techniques and detection approaches is present. Finally, examine a new hybrid machine learning-based distributed denial of service attack detection technique for a sustainable smart grid system. & COPY;2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://***/licenses/by/4.0/).

关键词： DDoS attack Smart grid Communication standard Cyber security Machine learning

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