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Review of Present Status and Recent Development in Active Cell Balancing Technique 3

Review of Present Status and Recent Development in Active Ce...

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3rd international Conference on Power, Control and computing Technologies, ICPC2T 2024

作者： Karmakar, Shukla Yadav, Ankur Bohre, Aashish Kumar Bera, Tushar Kanti NIT Durgapur Dept. of Electrical Engg. West Bengal India

ISBN: (纸本)9798350349207

Electric Vehicles (EVs) prove to be a sustainable mode of transportation concerning environment friendliness and the limited reserve of petrol and diesel. Notably, a crucial constituent of an EV is the battery. So, it becomes significant to safeguard the battery and prolong its operational life. Battery Management systems (BMS) is a smart technique employed in EVs that manages and controls the charging and discharging operations of batteries. Cell Balancing (CB) is an imperative function of the BMS that maximizes battery efficiency by balancing the State Of Charge (SOC) levels and consequently the voltages of the cells in a battery pack. CB phenomenon is broadly classified into the Passive Cell Balancing (PCB) and Active Cell Balancing (ACB) strategies. PCB strategy involves the expulsion of charge from higher SOC cells to the connected dissipative resistors for balancing its SOC as per the lower SOC cells. This technique is usually preferred for low-power applications involving low cost. However, for high-power applications, it necessitates the use of the ACB strategy where charge from higher SOC cells is disseminated among the lower SOC cells so that the SOC of all the cells balances to an average SOC value. As a result, the battery run time can be augmented and that would extend the driving range of an EV. This work focuses on reviewing the different ACB strategies of BMS that can be successfully used for EV s. © 2024 IEEE.

关键词： Battery management systems

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Classification of Coordinators' Limitations in Cyber-Physical Production System Management 1

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3rd international Conference on Digital Technologies and applications

作者： Ouazzani-Chahidi, Abdelaziz Jimenez, Jose-Fernando Berrah, Lamia Loukili, Abdellatif Univ Savoie Mt Blanc LISTIC Lab Annecy France Univ Savoie Mt Blanc SYMME Lab Annecy France Sidi Mohamed Ben Abdallah Univ Ind Technol & Serv Lab Fes Morocco

ISBN: (数字)9783031298608

ISBN: (纸本)9783031298592;9783031298608

A Cyber-Physical Production System (CPPS) is represented by the interconnection between two kinds of systems: the first is virtual, which has increased computational capacities, and the second is physical, represented by a production workshop. In particular, this interconnection is intended to guarantee real-time monitoring of the execution of production operations, providing coordinators with relevant information to enable them to control the system and achieve the planned performance. However, the distributed architecture of the system and the massive data from each physical entity create certain limitations for the coordinators. This is a limitation in terms of medium and long-term perspective, mainly linked to the local decision-making action taken by the coordinator, which affects the performance of the CPPS. To help the coordinator in his decisions, it is first necessary to understand his limitations and incapacities vis-a-vis the CPPS system. The objective of this paper is to classify the limitations in terms of understanding the situation and the behaviors needed by the coordinators to deal with a dysfunctional situation that requires intervention.

关键词： Coordinators limitations Cyber-physical systems industrial performance performance management systems

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3rd international Conference on Intelligent computing Techniques for Smart Energy systems, ICTSES 2023

3rd International Conference on Intelligent Computing Techni...

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3rd international Conference on Intelligent computing Techniques for Smart Energy systems, ICTSES 2023

ISBN: (纸本)9789819784639

The proceedings contain 50 papers. The special focus in this conference is on Intelligent computing Techniques For Smart Energy systems. The topics include: Analysis of Fault and Current-Limiting Methods in the Power System;UDS for Data Communication in Temperature Monitoring;approximation in the Weighted Lipschitz Class by (C,α,θ)(E,q) Mean of Its Fourier Series;demand Response and Load Profile Analysis in Modern Electricity systems;First-Principles Study of the Structural, Optical and Electronic Properties of Zinc Blende GaN Through PBEsol and TB-mBJ Functionals;optimization-Based Cost Analysis for Energy Management System in Microgrids;classification and Prediction of Knee Osteoarthritis by Deep Learning Approach;Predicting Stock Price and Market Direction Using Statistical and LSTM Models;Comprehensive Evaluation of time Management with Balancing Resistors in Passive Cell Balancing Using the 1RC Model;PAWnnect: Pioneering IoT-ML Driven Pet Monitoring;transactive Energy Management for Microgrids: Peer-To-Peer Trading Using Stackelberg Game Approach;Unravelling the Mind's Emotions: A Review of EEG-Based Emotion Detection Using Machine Learning and Deep Learning;unlocking IoT Security: Enabling the Future with Lightweight Cryptographic Ciphers;Optimal Design of Nano Scale Voltage Amplifier Using Evolutionary Techniques for DG-MOSFET;flower Patterned with Elliptical Petals Multiband Microstrip Fractal Patch Antenna for Wireless applications;Optimal Scheduling of Solar PV Generators and Network Assets in Distribution Network;revolutionizing Biomedical Engineering with Microcontroller applications: A Comprehensive Review;investigation of Battery Temperature Impact on High Voltage Cable of Electric Vehicles;deep Learning Technique for Computer Vision-Based Pose Estimation for Augmented reality;Rectangular Shape Patch Antenna with Defected Ground Plane for 5G Sub 6 GHz Wireless Communication systems.

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Incremental Perception on real time 3D Data 22

Incremental Perception on Real Time 3D Data

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23rd Annual international workshop on Mobile computing systems and applications (HotMobile)

作者： Sarker, Arup Kumar Lin, Felix Xiaozhu Univ Virginia Charlottesville VA 22904 USA

ISBN: (纸本)9781450392181

Perception based on 3D data in autonomous vehicles (AV) pursues high accuracy at a high computational cost. It delays the downstream modules in an AV pipeline - planning, prediction, and control. This prolongs the AV's time-to-decision and ultimately hurts the vehicle's maneuver and safety. Towards efficient perception, our insight is that the perception module should attend to 3D pixels that are more relevant to the downstream modules. Accordingly, we propose incremental perception: each 3D frame is processed in progressive iterations;early iterations emit inexact perception results to the downstream modules;later iterations incorporate feedback from the downstream modules and accordingly refine a 3D frame's most relevant portions. Our early results show reduction in AV's time-to-decision and therefore safety improvement.

关键词： computer vision autonomous vehicles point cloud

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real-time Control applications Using Rapid Modeling Based on Surface Electromyography 3

Real-Time Control Applications Using Rapid Modeling Based on...

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3rd international Conference on Mechatronics and Automation Technology, ICMAT 2024

作者： Gong, Fenghao Bai, Dianchun Liu, Zhuo Li, Ruiji Lin, Zhongpeng Shenyang University of Technology China University of Electro-Communications Japan

ISBN: (纸本)9781643685649

Surface electromyography (sEMG) directly reflects muscle activity and has been widely applied in areas such as prosthetics, rehabilitation, exoskeletons, and human-computer interaction. However, traditional sEMG modeling methods are often constrained by the complexity of data and computation time, making it difficult to meet real-time control requirements. This paper proposes a rapid modeling method based on sEMG, exploring its application in hand assistive devices and medical rehabilitation. By designing sEMG datasets, extracting transient features, and using deep learning algorithms (Vision Transformer and ConvNext), the method effectively reduces modeling time and improves classification accuracy. Experimental results demonstrate that this method is both efficient and accurate in real-time control applications, making it suitable for various real-time interactive systems. © 2024 The Authors.

关键词： Deep learning

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3rd international Conference on Intelligent computing Techniques for Smart Energy systems, ICTSES 2023

3rd International Conference on Intelligent Computing Techni...

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3rd international Conference on Intelligent computing Techniques for Smart Energy systems, ICTSES 2023

ISBN: (纸本)9789819784288

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Construction and Operation of a Generative Artificial Intelligence-Assisted Language Learning System 3

Construction and Operation of a Generative Artificial Intell...

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3rd IEEE international Conference on Distributed computing and Electrical Circuits and Electronics, ICDCECE 2024

作者： Cao, Yilu Lu, Haoyu Zhou, Yingping Gao, Jiahui Wang, Han Jiao, Yabei College Of Foreign Languages Chongqing University Of Technology Chongqing China College Of Computer Science And Engineering Chongqing University Of Technology Chongqing China School Of Accountancy Chongqing University Of Technology Chongqing China Liangjiang International College Chongqing University Of Technology Chongqing China

ISBN: (纸本)9798350318609

The generative artificial intelligence-assisted language learning system is a system that utilizes artificial intelligence technology. It provides users with more personalized and efficient language learning services through core modules such as generative pre-trained models and personalized learning engines, It is currently one of the significant applications of artificial intelligence technology in the field of language learning. This paper aims to introduce the design, construction, and operation of a generative artificial intelligence-assisted language learning system. In this system, the generative pre-trained model GPT -3.5 is employed, incorporating core modules such as natural language processing, generative adversarial networks, and Transformer models. This paper also conducts detailed research and analysis on aspects such as text generation quality in the system, response time testing of the model within the system, and feedback on system application scenarios. Through the research presented in this paper, valuable reference and guidance can be provided for the development and application of generative artificial intelligence-assisted language learning systems. © 2024 IEEE.

关键词： Engines

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Development of a sleep monitoring system using cloud computing and big data techniques 3

Development of a sleep monitoring system using cloud computi...

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3rd international Conference on Advance computing and Innovative Technologies in Engineering, ICACITE 2023

作者： Duggal, Sonia Sood, Sanjay Singh, Mahipal Kumar, Komuravelly Sudheer Tiwari, Mohit Kumar, S. Veeresh Mriirs Faridabad Department of Computer Applications Haryana India Lovely Professional University Punjab Phagwara India Uttaranchal University Uttaranchal Institute of Technology Dehradun India Sr University School of Computer Science and Artificial Intelligence Telangana Warangal India Bharati Vidyapeeth's College of Engineering Department of Computer Science and Engineering Delhi India St. Martin's Engineering College Department of It Telangana Secunderabad India

ISBN: (纸本)9798350399264

Among the most significant sleep concerns is obstructive apnea syndrome in sleep (OASS) which harms the quality of life. A few effects of OASS include cognitive decline, impaired psychiatric function, behavior problems, and personality ailments. real-time monitoring of this condition is thus essential for clinical services. There seem to be numerous OASS-detecting techniques. Hence, the present experiment provides a new system both for detecting and assisting therapies of OASS in elderly individuals. This design was developed for tracking a variety of variables including the surroundings where a person goes to sleep, their sleeping quality, physical activity levels, and physiological variables by utilizing open data from smarter city systems. 2 sorts of processing are performed by the suggested method. In the instance of a crisis, real-time notices can be sent to those in charge of caring for the old aged owing to the rule-relied pre-processing technique. This method fundamentally relies on a fog computing strategy applied in a smarter device functioning at networking edges which also provides enhanced interoperable ability services, including technological, semantic, and syntactic capabilities. Big data devices on cloud computing are utilized in this process. The effectiveness of the system has also been assessed given latencies. The outcomes obtained indisputably show that pre-processing of data at networking edges increases system effectiveness. © 2023 IEEE.

关键词： Semantics

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Over-the-Air Automotive Radars Hardware-in-Loop Test for Development and Validation of Active Safety systems and Autonomous Cars 3

Over-the-Air Automotive Radars Hardware-in-Loop Test for Dev...

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3rd IEEE international workshop on Metrology for Automotive (IEEE MetroAutomotive)

作者： Hadj-Bachir, Mokrane Bagheri, Toktam Toss, Henrik de Souza, Philippe Sanfridson, Martin ESI Grp Rungis France UniqueSec AB Gothenburg Sweden RISE Res Inst Sweden Boras Sweden

ISBN: (纸本)9798350321876

Due to the development of new radar technology for advanced driver-assistance systems (ADAS) and automated driving (AD) applications, testing radars for real world conditions is highly desirable. However, testing autonomous driving functions on public roads can be dangerous and the tests results are not always reproducible. In this paper, we present a novel Over-the-Air (OTA) Hardware-In-the-Loop (HIL) radar target simulator for testing radar systems. The complete simulation setup including hardware and software implementations will be presented in this article. We illustrate a test procedure by creating Euro NCAP scenarios, and explain the benefits and importance of realtime HIL testing of automotive radars.

关键词： Automotive radar radar target simulator HIL environment simulator Euro NCAP ADAS ADS autonomous vehicle validation over-the-air

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Cognitive Congestion Alleviation Framework in IoT-Enabled WSN for Next-Gen Intelligent Transport systems via Optimized Capsule Attention Network 3

Cognitive Congestion Alleviation Framework in IoT-Enabled WS...

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3rd international Conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Mohandas, R. Sudha, Y. Narmatha, P. Venkata Prasad, P. Manikandan, N. Department of Electronics & Communication Engineering Chennai Institute of Technology Tamil Nadu Chennai India Department of Computer Science and Engineering Presidency University Karnataka Bangalore India Department of Computer Science and Engineering Sri Sairam College of Engineering Karnataka Bangalore India Department of Electrical and Electronics Engineering Chaitanya Bharathi Institute of Technology Telangana Hyderabad India Department of Business Administration Kalasalingam Business School Kalasalingam Academy of Research and Education Viruthunagar Krishnankoil India

ISBN: (纸本)9798331527549

The rapid advancement of Intelligent Transportation systems (ITS) has heightened the importance of reliable, real-time data transmission in Wireless Sensor Networks (WSNs). However, congestion in data-heavy Internet of Things (IoT)-enabled networks remains a critical challenge, impacting communication efficiency and decision-making in ITS. In high-density IoT-ITS applications, traditional congestion control methods are insufficient to address the complexity and dynamics of data flows. Existing solutions often fail to adapt in real time to varying traffic loads, leading to delays and data loss. There is a strong need for a congestion alleviation framework capable of intelligently prioritizing data while dynamically managing network resources to ensure seamless information exchange in large-scale deployments. This study presents a Cognitive Congestion Alleviation Framework in IoT-Enabled WSN for Next-Gen Intelligent Transport systems via Optimized Capsule Attention Network (V-CapMiAN-Parr), which combines the Vectorized Adaptive Capsule Neural Network (V-AdCapNet) and Multi-instance Attention Network (MAN), fine-tuned by the Parrot Optimizer (ParrOpt). This integration aims to effectively detect, mitigate, and prevent congestion through an advanced capsule-based attention mechanism with adaptive optimization. The suggested V-CapMiAN-Parr framework demonstrated significant improvements in congestion control, achieving data throughput efficiencies above 99.7%, packet delivery rates above 99.5%, and network reliability reaching 99.2% under high traffic loads. The model’s adaptive weighting mechanism ensures real-time responsiveness and reliability, crucial for next-gen ITS applications. The V-CapMiAN-Parr framework effectively addresses congestion issues in IoT-enabled WSNs, providing a robust, scalable solution for ITS applications. This cognitive framework’s advanced data prioritization and adaptive optimization capabilities are well-suited for enhancing the performanc

关键词： Traffic congestion

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