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3rd IEEE International Conference on electrical Power and Energy systems, ICEPES 2024

作者： Latha, Adharapurapu Hema Bhimasingu, Ravikumar Power Systems Wing APTRANSCO Vijayawada India IIT Hyderabad Department of Electrical Engineering India

ISBN: (纸本)9798350390728

This paper presents a new impedance based fault location identification method on two terminal transmission lines without using transmission line parameters. The voltage and current phasors from both the terminals of the transmission line are used for calculating fault distance on the transmission line. The value of the zero sequence compensation factor is also calculated using the during fault values of voltages and currents without using the known values. The impedances calculated from the pre-fault and during-fault values of the voltages and current phasors are compared for fault location identification. Further, the fault point voltage, thereby fault resistance is also obtained accurately. The proposed method is independent of transmission line parameters accuracy and the efficiency is tested for different fault types and fault distance on the transmission line. A 10 bus system is considered for simulation studies which is modelled in PSCAD software and the algorithm is implemented in MATLAB. © 2024 IEEE.

关键词： MATLAB

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A learning artificial visual system for motion direction detection

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Neural Computing and Applications 2024年第27期36卷 17181-17197页

作者： Chen, Tianqi Kobayashi, Yuki Todo, Yuki Tang, Zheng Faculty of Electrical and Computer Engineering Kanazawa University Kakuma Ishikawa Kanazawa9201162 Japan Department of Intelligence Information Systems University of Toyama Toyama9308555 Japan

Research on the visual system and its development is not only crucial for understanding how we see and interpret the environment from basic visual processing to complex perception but also aids in the development of technologies like virtual reality, augmented reality, and computer vision. In our previous paper, we have proposed a novel biological motion direction detection mechanism. Based on this mechanism, the authors of this paper proposed a learning artificial visual system (AVS) and use it to achieve motion direction detection. The learning AVS consists of two layers: the local visual feature detective neuron layer and the global feature detective neuron layer. For local motion direction detection, we use dendritic neurons to implement local motion direction-detective neurons and use them to extract local motion direction information. Global feature detective neurons are simply implemented by summing the local motion direction-detective neurons in each direction of possible motion. We trained the learning AVS by eliminating unnecessary branches or synapses and keeping only those that are strongly connected to the function of motion direction detection. Computer simulations demonstrate that AVS can learn the correct motion direction of objects with different shapes, size and positions. We compare the performance of AVS with support vector machine (SVM) and traditional convolutional neural networks (CNNs)—LeNet-5 and EfficientNet-B0 (EfN)—in motion direction detection and find that our learning AVS has better recognition accuracy, noise immunity and less demands on size of dataset and learning costs. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Neurons

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Lung tumor detection using modified EfficientNet-B1 15

Lung tumor detection using modified EfficientNet-B1

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Manojsenthil, K. Meeradevi, T. Samikannu, Ravi Anand, N. Dharanimukhi, V.S. Dhivya, S. Kongu Engineering College Department of Electronics and Communication Engineering Erode India Botswana International University of Science and Technology Department of Electrical and Communications Systems Engineering Palapye Botswana Kongu Engineering College Bachelor of Engineering Department of Electronics and Communication Engineering Erode India

ISBN: (纸本)9798350370249

Lung cancer has the greatest death rate and is the foremost predominant sort of cancer. CT scans are utilized to diagnose lung cancer because it produces detailed pictures of tumors within the body and track their development. CT scans of the lungs were handled using Computer-Aided Diagnosis (CAD) to identify any sign of harm. The tests are carried out on the 'IQOTH/NCCD' dataset for persons with lung cancer who have been classified as benign, malignant, or normal depending on whether or not they have lung cancer. The EfficientNet-B1 network takes the input image of size 240 × 240 pixels. The data augmentation techniques were used to address the class imbalance issue. The input image is passed through the seven blocks of the Modified EfficientNet-B1 architecture that consists of Convolutional layers, Mobile Inverted Bottleneck layers, Global average pooling 2D, Dropout and Dense layer. The Global average pooling 2D is used instead of max pooling and average pooling. The purpose of the Global average pooling layer is to diminish the dimensionality of an image by compressing the pixel values. The addition of layers to the block and modification of the hyperparameters lead to the increased accuracy. The Modified EfficientNet-B1 model achieved an accuracy of 99.4%. The proposed modified EfficientNet-B1 is compared with other pre-trained CNN models like VGG19, EfficientNet-B0 and EfficientNet-B1. The Modified EfficientNet-B1 performs better than other CNNs in terms of accuracy. The suggested approach is employed for widespread clinical setting deployment because it is fast and requires less parameters than other CNN-based models. © 2024 IEEE.

关键词： Lung cancer

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The Impact of Needle Electrode Curvature Radius on Space Charge Distribution Evolution: A Combined Experiment and Simulation Study 5

The Impact of Needle Electrode Curvature Radius on Space Cha...

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5th IEEE International Conference on Dielectrics, ICD 2024

作者： Liu, Yuxin He, Penglong Zhang, Bo He, Jinliang Tsinghua University State Key Laboratory of Power Systems Department of Electrical Engineering Beijing China

ISBN: (纸本)9798350308976

The insulation of electric power equipment inevitably generates non-uniform electric fields due to internal impurities and irregular electrodes. However, the measurement of space charge distribution under non-uniform electric fields remains insufficient. In this study, based on the previous research of space charge measurement under uneven electric fields, a comprehensive investigation on the space charge distribution in epoxy resin under the influence of varying needle electrode curvature radii was conducted. A dynamic combination of experiment and simulation was employed to measure and reconstruct the space charge distribution, and the impact of needle electrode curvature radius on space charge evolution was analyzed. The results show that the distribution of space charge has similar characteristics under different needle electrode curvature radius, and the peak value of charge density all appears inside the sample and gradually moves to the depth of the sample with time. As the curvature radius decreases, the initial electric field intensity and charge injection increase. The electric field of space charge weakens the electric field of the needle surface, especially with a smaller curvature radius, resulting in a greater decrease in the peak of space charge density over time. © 2024 IEEE.

关键词： Needles

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Silk-Aloe Vera Composite Piezoelectric Film: A New Paradigm in Eco- Friendly Piezoelectrics

IEEE Journal on Flexible Electronics

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IEEE Journal on Flexible Electronics 2024年第7期3卷 292-299页

作者： Bhagavathi, K. Aditya Bonam, Satish Joseph, Jose Rao, Karri Trinadha Singh, Shiv Govind Vanjari, Siva Rama Krishna Indian Institute of Technology Hyderabad Department of Electrical Engineering Hyderabad502285 India Digital University Kerala School of Electronic Systems and Automation Trivandrum695317 India

Piezoelectric materials derived from biological sources are given greater consideration in the present era due to their advantages, such as biocompatibility, sustainability, and potential for tailoring properties through chemical modification and genetic engineering. Silk, a bio-piezopolymer, derived from the silk glands of various species of silkworms, is extensively studied for its piezoelectric properties and applications thereof. This article presents the development of a composite bio-piezopolymer, amalgamating the material properties of silk and the extracts taken from a tropical desert plant, aloe vera. A comprehensive material characterization protocol is embraced to assess the performance of the thin film formed from the silk-aloe vera (SAV) composite solution. In addition to an improvement in the piezoelectric characteristics, the composite film exhibited excellent surface uniformity and crystallinity, proving its potential for real-time applications. Pressure sensors were fabricated with SAV composite films and characterized using a custom-built test setup. The characterization results surpassed the performance achieved by pressure sensors fabricated using only silk thin film. © 2022 IEEE.

关键词： Pressure sensors

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Enhancing stability and safety:A novel multi-constraint model predictive control approach for forklift trajectory

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IET Cyber-systems and Robotics 2024年第4期6卷 32-47页

作者： Yizhen Sun Junyou Yang Donghui Zhao Moses Chukwuka Okonkwo Jianmin Zhang Shuoyu Wang Yang Liu School of Electrical Engineering Shenyang University of TechnologyShenyangChina Intelligent Robot Laboratory Shenyang Open UniversityShenyangChina School of Information Engineering Shenyang UniversityShenyangChina Department of Intelligent Mechanical Systems Engineering Kochi University of TechnologyKochiJapan

The advancements in intelligent manufacturing have made high-precision trajectory tracking technology crucial for improving the efficiency and safety of in-factory cargo *** study addresses the limitations of current forklift navigation systems in trajectory control accuracy and stability by proposing the Enhanced Stability and Safety Model Predictive Control(ESS-MPC)*** approach includes a multi-constraint strategy for improved stability and *** kinematic model for a single front steeringwheel forklift vehicle is constructed with all known state quantities,including the steering angle,resulting in a more accurate model description and trajectory *** ensure vehicle safety,the spatial safety boundary obtained from the trajectory planning module is established as a hard constraint for ESS-MPC *** optimisation constraints are also updated with the key kinematic and dynamic parameters of the *** ESSMPC method improved the position and pose accuracy and stability by 57.93%,37.83%,and 57.51%,respectively,as demonstrated through experimental validation using simulation and real-world *** study provides significant support for the development of autonomous navigation systems for industrial forklifts.

关键词： automatic guided vehicles mobile robots robot manipulator tracking control

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Use of Plat-Bar Electrode Media to Detect Partial Discharge in Epoxy Resin Materials on PCB Surfaces 1

Use of Plat-Bar Electrode Media to Detect Partial Discharge ...

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1st International Conference on Electronic and Computer engineering, ECE 2023

作者： Mulyana, Elih Somantri, Maman Ardiansyah, Neris P. Yusri, Chafidz D. Electrical Engineering Education Department Universitas Pendidikan Indonesia Bandung Indonesia Electrical Engineering Study Program Faculty of Engineering Universitas Widyatama Bandung Indonesia

The electric power system must have a protection system with reliable electric power isolation, so that the supply of electrical energy works properly and optimally. There are several kinds of disturbances in the electric power distribution system, one of which is a partial discharge. This study aims to investigate the effect of plate-rod electrodes on partial discharge, partial discharge voltage limits in solid insulation, and the characteristics of partial discharge in electrode media, and waveforms in partial discharge detection sensors. After conducting research, it was found that in the plate-rod type electrode media, the PDIV voltage appeared earlier than the plate-plate electrode media due to the cross-sectional area of the electrode media. And the limit of the pre-discharge voltage of PCB type solid insulation on the plate-bar electrodes is at a voltage of 1.3 kV. Several indicators to determine the characteristics of the partial discharge are background noise off (BGN off), background noise on (BGN on), partial discharge inception voltage (PDIV), and partial discharge voltage. After being examined, the value of each partial discharge detection voltage was obtained at negative and positive polarity voltages on the electrode plates and plate needles respectively 2.85 kV, 2.95 kV and 1.32 kV, 1.57 kV. © 2023 Institute of Physics Publishing. All rights reserved.

关键词： Partial discharges

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MWRS: A MAB-based Worker Recruitment Scheme with Tripartite Stackelberg Game for Reliable Mobile Crowdsensing

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IEEE Transactions on Mobile Computing 2025年第7期24卷 5665-5680页

作者： Ouyang, Yan Zeng, Feng Xiong, Neal N. Liu, Anfeng Pedrycz, Witold School of Computer Science and Engineering Central South University Changsha410083 China Department of Computer Science and Mathematics Sul Ross State University AlpineTX79830 United States Department of Electrical and Computer Engineering University of Alberta EdmontonABT6G 2R3 Canada Systems Research Institute Polish Academy of Sciences Warsaw00-901 Poland Faculty of Engineering and Natural Sciences Department of Computer Engineering Istinye University Istanbul Turkey Department of Electrical and Computer Engineering Faculty of Engineering King Abdulaziz University Jeddah21589 Saudi Arabia

Mobile Crowdsensing (MCS) has emerged as a compelling paradigm for data sensing and collection, leveraging the widespread adoption of mobile devices and the active participation of numerous users. Despite its potential, MCS faces critical challenges, particularly in recruiting reliable workers and acquiring high-quality sensing data. Most existing approaches assume prior information on worker quality and are vulnerable to collusion attacks, especially having not comprehensively considered workers' reliability and stability. To address these problems, we propose a Multi-Armed Bandit (MAB) based Worker Recruitment Scheme (MWRS) integrated with the Tripartite Stackelberg Game (TSG) for MCS. Specifically, a trust evaluation and truth inference mechanism is introduced to assess the trustworthiness of workers through active truth detection. To enhance recruitment quality, we employ a trust-aware worker selection mechanism that utilizes a modified Upper Confidence Bound (UCB) algorithm, achieving an optimal balance between exploration and exploitation. Furthermore, the interactions among participants are modeled using a TSG framework, which formulates their respective payoffs to determine optimal decision-making strategies, thus achieving mutually beneficial outcomes. Extensive evaluations on real-world datasets demonstrate that our proposed scheme improves total quality by up to 30.8% and reduces regret by up to 80.3% compared to existing methods. © 2025 IEEE.

关键词： Decision making

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Distributed Optimization and Scaling Design for Solving Sylvester Equations

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Journal of systems Science & Complexity 2024年第6期37卷 2487-2510页

作者： CHENG Songsong YU Xin ZENG Xianlin LIANG Shu HONG Yiguang Anhui Engineering Laboratory of Human-Robot Integration System and Intelligent Equipment School of Electrical Engineering and AutomationAnhui UniversityHefei 230601China Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of TechnologyBeijing 100081China Department of Control Science and Engineering Tongji UniversityShanghai 201804China Shanghai Research Institute for Intelligent Autonomous Systems Tongji UniversityShanghai 201210China

This paper develops distributed algorithms for solving Sylvester *** authors transform solving Sylvester equations into a distributed optimization problem,unifying all eight standard distributed matrix *** the authors propose a distributed algorithm to find the least squares solution and achieve an explicit linear convergence *** results are obtained by carefully choosing the step-size of the algorithm,which requires particular information of data and Laplacian *** avoid these centralized quantities,the authors further develop a distributed scaling technique by using local information *** a result,the proposed distributed algorithm along with the distributed scaling design yields a universal method for solving Sylvester equations over a multi-agent network with the constant step-size freely chosen from configurable ***,the authors provide three examples to illustrate the effectiveness of the proposed algorithms.

关键词： Distributed optimization least squares solution linear convergence rate step-size interval Sylvester equation

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Leveraging Deep Learning Algorithms and Open-Source Spatial Datasets for Analysis of Flood and its relationship with land cover change, population growth in the Nam Ngum River Basin (NNRB), Lao PDR 57

Leveraging Deep Learning Algorithms and Open-Source Spatial ...

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57th IAA Symposium on Safety, Quality and Knowledge Management in Space Activities at the 75th International Astronautical Congress, IAC 2024

作者： Mangkhaseum, Sackdavong Hanazawa, Akitoshi Department of Electrical and Space Systems Engineering Kyushu Institute of Technology Fukuoka Kitakyushu City Japan

ISBN: (纸本)9798331312275

Monitoring transformations in land use and land cover (LULC) has significant effects on various aspects of the environment, including water resources, climate change, and biodiversity loss on a global scale. Exponential human population growth and the expansion of human land use have led to numerous changes and problems in ecosystems, natural disasters, and increased pressure on natural resource management at all scales. Remote sensing and earth observation have been employed for this purpose for decades, providing the capability to detect changes over extensive geographical areas. This study combines point-based data from publicly available open-source earth system datasets, historical flood observation datasets, Google’s cloud computing platform, and advanced remote sensing and deep learning techniques to create detailed flood susceptibility maps. Key datasets include digital elevation model (DEM), satellite-observed rainfall data, land use/land cover, and remote sensing image-derived indices such as NDVI and Sentinel-1 SAR imagery. The assessment employs various deep learning models, including Artificial Neural Networks (ANN), Long Short-Term Memory (LSTM), and Deep Neural Networks (DNN), to analyze hydro-meteorological and geomorphological parameters. These models were trained and tested using eleven flood conditioning variables and samples divided into training and testing datasets in a 70:30 ratio. Performance metrics such as accuracy, precision, and the area under the curve of Receiver Operating Characteristics (AUROC) were used to evaluate the models. The resulting flood susceptibility maps identify critical zones within the Nam Ngum River Basin at high risk of flooding, revealing that 36-53% of the basin area is highly susceptible, especially in low-elevation and low-slope regions. Additionally, 85-93% of the population is highly vulnerable to flooding within 261 to 296 km2 of built-up area. The results of this study show the alarming situation of flood ris

关键词： Risk management

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