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Fault Detection and Fault-Tolerant Control of Single Phasing on Three-Phase System

IEEE Transactions on Instrumentation and Measurement 2025年 74卷

作者： Abdo, Ali Siam, Jamal Abdou, Ahmed Birzeit University Faculty of Engineering and Technology Department of Electrical and Computer Engineering Birzeit9730000 Palestine Palestine Ahliya University Department of Engineering BethlehemP1520468 Palestine

This article introduces a new and cost-effective solution to the long-standing problem of single phasing in electrical systems. It addresses the challenges caused by the failure of one phase in three-phase systems, improving reliability and performance for industrial and residential applications. The proposed method uses boost converter circuits to create a fault-tolerant approach. We describe a technique that converts the three-phase signal into direct current (dc) to compensate for the missing phase. Then, it reconstructs a balanced three-phase output using an inverter. This method ensures stable and efficient power generation, providing a versatile solution suitable for various load requirements. We conducted extensive analysis to assess power output, boost converter efficiency, and the impact of inverter integration. We also examined critical issues such as power delivery to loads, transient responses, and harmonic distortions under faulty conditions. In addition, we investigated the system’s performance when multiple phases may be lost. Our findings offer valuable insights into the feasibility and practicality of implementing this method in real-world electrical systems. Specifically, this approach demonstrates significant potential to enhance safety and operational reliability in power generation. Moreover, it shows considerable promise in improving the performance and dependability of three-phase loads. A practical test is added to verify the effectiveness of the proposed approach. © 1963-2012 IEEE.

关键词： Fault tolerance

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Unveiling Deception: Different Strategies for Combatting Arabic Fake News 25

Unveiling Deception: Different Strategies for Combatting Ara...

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25th International Arab Conference on Information technology, ACIT 2024

作者： Khattab, Nada Al-Qerem, Ahmad Nashwan, Shadi Jebreen, Issam Rajab, Mohammed Alauthman, Mohammad Jeadi, Mohammad Elrashidi, Ali Zarqa University Faculty of Information Technology Computer Science Department Zarqa13110 Jordan Middle East University Faculty of Information Technology Cybersecurity Department Amman11831 Jordan University Headquarter University of Anbar Ramadi Iraq University of Petra Department of Information Security Amman11196 Jordan University of Business and Technology Department of Electrical Engineering Jeddah21432 Saudi Arabia

ISBN: (纸本)9798331540012

the proliferation of fake news has become a widespread problem in the contemporary era of information, posing possible harm to public discussions, political stability, and community confidence. To tackle this difficulty, it is necessary to develop strong and effective detection methods that can accurately recognize misinformation in several languages, including Arabic. The aim of this study is to create and assess different models specifically designed for the identification of fake news in Arabic *** of deep Learning models like Recurrent Neural Networks (RNN), Long short-term memory (LSTM), Bidirectional long short term memory (Bi-LSTM) and convolutional neural network (CNN) are used in this study. On the other hand, some of the traditional machine learning models like k-nearest neighbors (KNN), Random Forests (RF), Extreme Gradient Boosting (XGBoost), decision tree (DT) and multi-layer perceptron (MLP) are also used. Also, transformers, like Generative pre-trained Transformer 3 (Gpt-3) and Bidirectional Encoder Representations from Transformers (BERT), are used as a feature extraction to convert text into numerical representation and assign different number to each token. All of these models were used in evaluation which of them is the best model in the process of fake news detection for the Arabic Language *** findings demonstrate strong performance across deep learning models, with CNN-LSTM, Bi-LSTM and CNN-Bi-LSTM exhibiting the best accuracy rates of 93.2% ,92.6%, 93.6% respectively. The LSTM model achieves a moderate accuracy of 87.4%, whilst the RNN model demonstrates a more modest accuracy of 56.8%. The results emphasize the capability of deep learning methods in reducing the dissemination of fake information in Arabic-language datasets. © 2024 IEEE.

关键词： Long short-term memory

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A Dual Broadband Antenna for V2X, LTE, and 5G Vehicular Communication Systems 7

A Dual Broadband Antenna for V2X, LTE, and 5G Vehicular Comm...

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7th IEEE International Conference on Electronic Information and Communication technology, ICEICT 2024

作者： Hu, Yiting Feng, Botao Chung, Kwok L. Ding, Xiao Gu, Wenzhe Deng, Li Shenzhen University College of Electronics and Information Engineering Shenzhen518060 China Huizhou University School of Computer Science and Engineering Huizhou China Macau University of Science and Technology Faculty of Humanities and Arts Macau999078 China Beijing University of Posts and Telecommunications College of Information and Communication Engineering Beijing China

In this paper, we present a novel dual broadband antenna tailored for vehicular applications. The antenna design incorporates circular and square patches, metal cylinders, and conductive vias. Our simulated results de... 详细信息

ISBN: (纸本)9798350384437

关键词： Advanced driver assistance systems

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FERI: Feature Enhancement and Relational Interaction for Image-text Matching 30

FERI: Feature Enhancement and Relational Interaction for Ima...

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30th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2024

作者： Zhang, Yu Zhang, Jianqiang Song, Gongpeng Lu, Qin Zhao, Shuo Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Jinan China Shandong Engineering Research Center of Big Data Applied Technology Faculty of Computer Science and Technology Jinan China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Computer Networks Jinan China Shandong Branch of China Mobile Communication Group Design Institute Co. Jinan China

ISBN: (纸本)9798331515966

Image-text matching is an important problem at the intersection of computer vision and natural language processing. It aims to establish the semantic link between image and text to achieve high-quality semantic alignment between the two modalities. However, the existing methods have the problem that the meaning expressed in the image or the complex narrative in the text cannot be fully understood due to insufficient feature extraction. Moreover, due to the essential modal differences between images and texts, how to effectively and accurately align the semantic contents in images and texts has become the key of research. In order to solve the above problems, this paper proposes a method based on feature enhancement and relationship interaction. When processing images, the proposed method fuses labeled features, region features and location features to represent images. When processing text, a combination of Bi-GRU and self-attention mechanism is used to represent the text. In order to further align the semantic content in images and texts accurately, this paper improves two relational interaction mechanisms by identifying connection relationships and learning association relationships. Thus, the relation enhanced embedding is obtained. Finally, it calculated the similarity of the enhanced embedding to judge the matching degree of the image and text. Extensive experiments on the public datasets Flickr30K and MSCOCO demonstrate the effectiveness of our method. © 2024 IEEE.

关键词： cross-modal retrieval feature enhancement image-text matching relationship interaction

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A Low-Profile Interdigital Diplexer for LEO Satellites Applications 31

A Low-Profile Interdigital Diplexer for LEO Satellites Appli...

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31st International Conference on Electrical engineering, ICEE 2023

作者： Fallahzadeh, Mojtaba Ahmadi, Behzad Kheirdoost, Ali K. N. Toosi University of Technology Electrical and Computer Engineering Department Tehran Iran Sattellite Research Institute Iranian Space Research Center Tehran Iran Communication Technology Faculty Tehran Iran

ISBN: (纸本)9798350312560

A low-profile diplexer is proposed for satellite telemetry, tracking and command (TT&C) applications in S-band frequency within 2.025-2.110/2.200-2.290 GHz. The diplexer consists of two interdigital band-pass filters and a coaxial power divider. The proposed diplexer has high potential for mass production because there is no need to tune the frequency response after fabrication. Also, the structure is lightweight and low-profile so it could be easily integrated into payload transceivers or antennas in small satellites specially CubeSats. A prototype of the proposed diplexer is fabricated and measured. The measured results are in good agreements with simulations. The measured return loss is lower than -15 dB in all ports, insertion loss is less than 0.7 dB and isolation between output ports is better than 55 dB. © 2023 IEEE.

关键词： Frequency response

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Design of optimal hybrid power system to provide reliable supply to rural areas of Ethiopia using MATLAB and Homer

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Renewables: Wind, Water, and Solar 2021年第1期8卷 1-7页

作者： Nebey, Abraham Hizkiel Faculty of Electrical and Computer Engineering Bahir Dar University Institute of Technology Bahir Dar Ethiopia

Integrating different energy resources, like solar PV, wind, and hydro is used to ensure reliable power to the rural community loads. Hybrid power system offers sufficient power supply for the rural villages by providing alternative supply for intermittent nature of renewable energy resource. Hence, intermittency of renewable energy resources is a challenge to electrify the rural community in a sustainable manner with the above sources. Thus, efficient resources management is a reasonable choice for intermittent renewable energy resources. The majority of rural villages in Ethiopia are suffering from lack of electricity. This causes deforestation, travel for long distance to fetch water, and no good social services, like clinic and schools, sufficiently. Therefore, the objective of this study was to maximize reliability of power supply by renewable energy sources. Data on wind speed and solar radiation are obtained from the NASA surface meteorological agency. While hydro data are obtained from physical measurements. Different configuration options are considered by Homer software to find the optimal configuration of hybrid system. The optimal configuration system is selected and hybrid components are sized. The optimal hybrid system consists of solar PV, wind, and hydro to supply a community load with a share of 13%, 52%, and 35% respectively. The fuzzy logic controller is designed to manage the intermittent nature of energies. Hence, the demand and energy sources are unpredictable;intelligent control system is important to manage the system accordingly. The control system is designed in MATALAB software. The result obtained from resource combination shows demand and supply are balanced. From the Twelve probabilistic combinations of demand and energy sources, one of the combinations shows that when 7.5 kW is demanded, the power generated/output from hybrid system is 10 kW which is greater than demand. To satisfy 7.5 kW demand control system takes 4.25 kW, 2.75 kW, a

关键词： Hybrid systems

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Application of Evolutionary Computing for Optimal Design of Base Station Antenna 7

Application of Evolutionary Computing for Optimal Design of ...

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7th IEEE International Conference on Electronic Information and Communication technology, ICEICT 2024

作者： Khan, Naveed Hamid Nawaz Feng, Botao Ding, Xiao Deng, Li Gu, Wenzhe Chung, Kwok L. Shenzhen University College of Physics and Optoelectronic Engineering Shenzhen518060 China Shenzhen University College of Electronics and Information Engineering Shenzhen518060 China Macau University of Science and Technology Faculty of Humanities and Arts Macau999078 China Beijing University of Posts and Telecommunications College of Information and Communication Engineering Beijing China Huizhou University School of Computer Science and Engineering Huizhou China Huizhou University School of Computer Science and Engineering Huizhou516007 China

ISBN: (纸本)9798350384437

This study outlines the development and refinement of an innovative base station antenna for contemporary wireless communication systems, which operates within the frequency range of 1.9 to 4.9 GHz. The antenna is made of copper and has a radiating patch thickness of 0.2 mm. The ground patch measures 38×38 mm and the total height of the antenna is 16 mm. The performance of the system relies on four reflecting walls that have been carefully carved to reduce out-of-band radiations and minimize interference. The antenna attains a peak gain of 6 dBi throughout the operational range, while keeping the |S11| parameters below -10 dBi, ensuring effective signal transmission. The process of optimization involves the utilization of evolutionary computers, more specifically a Genetic Algorithm, to meticulously adjust the design parameters. This approach guarantees that the antenna fulfills the demanding criteria of high gain and wide bandwidth, offering a strong and reliable solution for modern communication requirements. © 2024 IEEE.

关键词： Antenna grounds

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Enhancing MANETs Security Against Black Hole Attacks through Time-Based Node Analysis in AOMDV Protocol

Enhancing MANETs Security Against Black Hole Attacks through...

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Emerging Smart Technologies and Applications (eSmarTA), International Conference on

作者： Abdullah A. Naji Mogeeb A. Saeed Ammar H. Almagashi Alaa M. Ahmed Hashem S. Al-Atefi Mohammed N. Khaled Olayan M. Rashed Computer Network & Distributed Systems Department Al-Saeed Faculty Of Engineering &IT Taiz University Computer Networks & Distributed Systems Al-Saeed Faculty Of Engineering &IT Taiz University Computer Center & Information Technology Taiz University

ISBN: (数字)9798350354133

ISBN: (纸本)9798350354140

Mobile ad-hoc networks (MANETs) rely solely on direct node communication and function without a fixed infrastructure. Due to their decentralized design, they are susceptible to numerous security risks, with black hole attacks posing significant threats to routing integrity and confidentiality. This paper proposes a technique to enhance the Ad hoc On-Demand Multi-path Distance Vector (AOMDV) routing protocol's security against black hole attacks. The method involves a time-based reply message analysis to identify and mitigate malicious nodes. This algorithm improves the protocol's ability to detect and prevent black hole attacks by closely analyzing response time differences between malicious and normal nodes. The results of the simulation show that the suggested solution greatly enhances network performance by lowering the Routing Overhead Ratio from 1388.04% to 0.73% and the Packet Loss Rate from 74% to 11% while keeping a high Packet Delivery Ratio—up to 93% in different scenarios. These enhancements sustain strong data transmission in dynamic MANET environments, supporting network integrity and reliability.

关键词： Protocols Packet loss Routing Ad hoc networks Vectors Security Time factors

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Sharding:A Scalability Solutions for Blockchain Networks 3

Sharding:A Scalability Solutions for Blockchain Networks

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3rd IEEE International Conference on Blockchain and Distributed Systems Security, ICBDS 2024

作者： Kale, Dattatray Raghunath Jadhav, Amolkumar N. Kruishna Prasad, K. Salunkhe, Somanath Janardan Hirve, Sumit Goswami, Chandrashekhar Mit Art Design and Technology University Mit School of Computing Department of Computer Science & Engg Pune India Annasaheb Dange College of Engineering and Technology Department of Computer Science & Engg Ashta India Shrinivas University Department of Computer Science & Engg Mangalore India D Y Patil Agriculture and Technical University Department of Computer Science & Engg Talsande India Sir Padampat Singhania University Faculty of Computing and Informatics Rajasthan Udaipur India

ISBN: (纸本)9798350354348

Blockchain technology's decentralized and immutable data storage has changed a number of sectors. But typical blockchain networks scalability issues prevent them from being widely used for large-scale applications. By dividing the blockchain network into smaller, more controllable sections known as shards, sharding has become a viable remedy for scalability issues. This paper offers a thorough introduction to sharding as a blockchain network scalability solution. We explore the basic ideas of sharding as well as its advantages, drawbacks, and several sharding strategies. We also analyze experimental results and real-world implementations to assess how well sharding contributes to increased blockchain scalability. Lastly, we talk about possible developments in sharding approaches and future research paths to further improve the scalability of blockchain networks. © 2024 IEEE.

关键词： Distributed ledger

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GAF-GAN: Gated Attention Feature Fusion Image Inpainting Network Based on Generative Adversarial Network 29

GAF-GAN: Gated Attention Feature Fusion Image Inpainting Net...

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29th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2023

作者： Qiu, Ran Liang, Hu Liu, Yuchen Zhao, Shengrong Qilu University of Technology Shandong Academy of Sciences Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Jinan China Qilu University of Technology Shandong Academy of Sciences Shandong Engineering Research Center of Big Data Applied Technology Faculty of Computer Science and Technology Jinan China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Computer Networks Jinan China

ISBN: (纸本)9798350330717

Image inpainting, which aims to reconstruct reasonably clear and realistic images from known pixel information, is one of the core problems in computer vision. However, due to the complexity and variability of the underwater environment, the inability to extract valid pixel points and insufficient correlation between feature information in existing image inpainting techniques lead to blurring in the generated images. Therefore, a novel gated attention feature fusion image inpainting network based on generative adversarial networks (GAF-GAN) is proposed. The accuracy of feature similarity matching depends heavily on the validity of the information contained in the features. On the one hand, gating values are dynamically generated by gated convolution to reduce the interference of invalid information. On the other hand, semantic information at distant locations in an image is accurately acquired by the attention mechanism. For these reasons, we designed an improved gated attention mechanism. Gated attention mechanism make the network focus on effective information such as high-frequency texture and color fidelity of restored images. In addition, the dense feature fusion module is added to expand the overall receptive field of the network to fully learn the image features. Experimental results show that the proposed method can effectively repair defective images with complex texture structures and improve the reality and integrity of image details and structures. © 2023 IEEE.

关键词： Dense feature fusion module Gated attention mechanism Image inpainting Underwater environment

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