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2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Afroz, Syed Sohail Feroz Syed Abukhousa, Emad Qwbaiban, Abdulaziz Alsaeed, Fahad Meliopoulos, A.P. Sakis Georgia Institute of Technology School of Electrical and Computer Engineering United States

ISBN: (纸本)9798350376067

Inverter-based resources (IBRs) such as solar and wind introduce significant challenges in fault management within power systems, particularly affecting the reliability of traditional distance relays in transmission lines. These relays, critical for detecting and isolating faults based on specific fault characteristics, increasingly misoperate due to the unique control strategies of IBRs that often suppress fault current levels. This study conducts a comprehensive evaluation of traditional distance protection versus dynamic state estimation-based protection (EBP) on a transmission line within a high IBR penetration environment. Through detailed simulations on an A-G fault along the transmission line, the analysis reveals that traditional relays struggle to accurately detect and respond to faults due to the altered electrical characteristics introduced by IBRs. Conversely, EBP demonstrates superior performance by utilizing real-time state estimations to adapt effectively to dynamic grid conditions, ensuring reliable fault detection and isolation. This paper highlights the necessity for advanced protection mechanisms in transmission systems to manage the complexities introduced by the growing integration of renewable energy sources. © 2024 IEEE.

关键词： Power transmission lines

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Modeling and Simulation of Grid-Connected PV System Faults Using MATLAB/Simulink 22

Modeling and Simulation of Grid-Connected PV System Faults U...

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22nd International Learning and technology Conference, L and T 2025

作者： Alkhawaja, Mayar Miguel, Sandy Shabab, Moutaz Abu Eddin Za'ter, Muhy Batarseh, Majd Ghazi Princess Sumaya University for Technology Electrical Engineering Department Amman Jordan King Abdullah University of Science and Technology Now With the Electrical and Computer Engineering Saudi Arabia University of Central Florida Now With the College of Engineering and Computer Science Orlando United States University of Colorado Boulder Electrical and Computer Engineering Boulder United States

ISBN: (纸本)9798331532215

Grid-connected photovoltaic (PV) systems are crucial to modern renewable energy strategies, but various types of faults can significantly impact their performance. Understanding the behavior of these faults is essential for improving system reliability and reducing maintenance costs. This paper investigates the impact of common faults, including open-circuit, short-circuit, partial shading, and grid faults, by simulating them using MATLAB/Simulink. The focus is on modeling faults that lead to power output reduction. The simulation results demonstrate how different fault types affect critical system parameters, such as grid voltage and active power output. The study highlights the value of simulation as a flexible approach for exploring fault scenarios, providing insights into fault detection and mitigation strategies that can help optimize PV system performance and support the development of robust fault data collection, detection, and classification techniques. © 2025 IEEE.

关键词： Power distribution faults

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Classification of ASD Based on fMRI Data Using Two Hybrid Learning Approaches 19

Classification of ASD Based on fMRI Data Using Two Hybrid Le...

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19th Iranian Conference on Intelligent Systems, ICIS 2024

作者： Gerdefaramarzi, Sara Soltani Hakimdavoodi, Hamidreza Isfahan University of Technology Department of Electrical and Computer Engineering Isfahan Iran

ISBN: (纸本)9798331507565

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition marked by challenges in communication, heightened sensitivity to sensory input, difficulties in adapting to change, and atypical patterns of play. Since traditional methods of diagnosing this disorder rely heavily on behavioral assessments, they are highly prone to errors. Consequently, it is necessary to provide a reliable method for diagnosing this mental disorder by leveraging advanced machine-learning techniques. In this paper, two hybrid learning approaches that only use fMRI data have been designed and implemented. The first method is the simultaneous training of a deep autoencoder and a single-layer perceptron (SLP) to extract beneficial features and properly tune the model's hyperparameters for classification. The second method combines a support vector machine model with a data augmentation strategy using simultaneous training of a generative adversarial network and a deep autoencoder to prevent model overfitting. It is worth mentioning that in the two proposed methods, the Extra-Trees algorithm is initially used for dimensionality reduction and feature selection. These two methods have been implemented on the entire publicly available dataset released by the Autism Brain Imaging Data Exchange, and both results have been compared. Our study in this paper achieved a maximum accuracy of 70.8%, sensitivity of 67.4%, and specificity of 75.3%. These results indicate that our proposed approaches have performed significantly better than many recent studies in this field. © 2024 IEEE.

关键词： Generative adversarial networks

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Novel Double-Damped Tuned AC Filters in HVDC Systems

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computers, Materials & Continua 2023年第4期75卷 1467-1482页

作者： Rana Shaheer Mehmood Asif Hussain Usman Ali Muhammad Tariq Mahmood Department of Electrical Engineering University of Management and TechnologyLahore54782Pakistan Department of Electrical and Computer Engineering Sungkyunkwan University2066Seobu-roJangan-guSuwon-si16419Gyeonggi-doKorea School of Computer Science and Engineering Korea University of Technology and Education1600ChungjeolnoByeogchunmyunCheonan31253Korea

This paper presents a performance analysis of novel doubledampedtuned alternating current (AC) filters in high voltage direct current(HVDC) systems. The proposed double-damped tuned AC filters offer theadvantages of improved performance of HVDC systems in terms of betterpower quality, high power factor, and lower total harmonic distortion (THD).The system under analysis consists of an 878 km long HVDC transmissionline connecting converter stations at Matiari and Lahore, two major cities inPakistan. The main focus of this research is to design a novel AC filter usingthe equivalent impedance method of two single-tuned and double-dampedtuned AC filters. Additionally, the impact of the damping resistor on the ACchannel is examined. TheTHDof theHVDCsystem with and without currentAC filters was also compared in this research and a double-damped tuned ACfilter was proposed. The results of the simulation represent that the proposeddouble-damped tuned AC filter is far smaller in size, offers better powerquality, and has a much lower THD compared to the AC filters currently inplace in the converter station. The simulation analysis was carried out utilizingpower systems computer-aided design (PSCAD) software.

关键词： Double-damped tuned AC filters harmonics high voltage DC systems long distance transmission power quality total harmonic distortion

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Statistical curriculum learning: An elimination algorithm achieving an oracle risk 37

Statistical curriculum learning: An elimination algorithm ac...

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37th Annual Conference on Learning Theory, COLT 2024

作者： Cohen, Omer Meir, Ron Weinberger, Nir Department of Electrical and Computer Engineering Technion - Israel Institute of Technology Israel

We consider a statistical version of curriculum learning (CL) in a parametric prediction setting. The learner is required to estimate a target parameter vector, and can adaptively collect samples from either the target model, or other source models that are similar to the target model, but less noisy. We consider three types of learners, depending on the level of side-information they receive. The first two, referred to as strong/weak-oracle learners, receive high/low degrees of information about the models, and use these to learn. The third, a fully adaptive learner, estimates the target parameter vector without any prior information. In the single source case, we propose an elimination learning method, whose risk matches that of a strong-oracle learner. In the multiple source case, we advocate that the risk of the weak-oracle learner is a realistic benchmark for the risk of adaptive learners. We develop an adaptive multiple elimination-rounds CL algorithm, and characterize instance-dependent conditions for its risk to match that of the weak-oracle learner. We consider instance-dependent minimax lower bounds, and discuss the challenges associated with defining the class of instances for the bound. We derive two minimax lower bounds, and determine the conditions under which the performance weak-oracle learner is minimax optimal. © 2024 O. Cohen, R. Meir & N. Weinberger.

关键词： Contrastive Learning

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Vehicle and pedestrian detection method based on improved YOLOv4-tiny

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Optoelectronics Letters 2023年第10期19卷 623-628页

作者： LI Jing XU Zhengjun XU Liang School of Computer Science and Engineering Tianjin University of TechnologyTianjin300384China School of Electrical Engineering and Automation Tianjin University of TechnologyTianjin300384China

Aiming at the problem of low detection accuracy of vehicle and pedestrian detection models,this paper proposes an improved you only look once v4(YOLOv4)-tiny vehicle and pedestrian target detection *** block attention module(CBAM)is introduced into cross stage partial Darknet-53(CSPDarknet53)-tiny module to enhance feature extraction *** addition,the cross stage partial dense block layer(CSP-DBL)module is used to replace the original simple convolutional module superposition,which compensates for the high-resolution characteristic information and further improves the detection accuracy of the ***,the test results on the BDD100K traffic dataset show that the mean average precision(mAP)value of the final network of the proposed method is 88.74%,and the detection speed reaches 63 frames per second(FPS),which improves the detection accuracy of the network and meets the real-time detection speed.

关键词： replace network method

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Finite Element Method of the System for Measuring the Magnetization Characteristics of MR Fluids 15

Finite Element Method of the System for Measuring the Magnet...

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15th International Conference Elektro, ELEKTRO 2024

作者： Mielnik, Zuzanna Cracow University of Technology Faculty Electrical an Computer Engineering Cracow Poland

ISBN: (纸本)9798350372359

In the automation and robotics industry, there is an increasing interest in the magnetization properties of intelligent materials, such as magnetorheological fluids (MR fluids). The article discusses the method of obtaining the magnetization characteristics of MR fluids and compares them with the results of finite element analysis. The use of MR fluids was also discussed. © 2024 IEEE.

关键词： Magnetorheological fluids

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Abnormal Activity Detection and Classification of Bus Passengers with In-Vehicle Image Sensing

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IEEE Access 2024年 12卷 23057-23065页

作者： Lin, Huei-Yung Tseng, Chun-Han National Taipei University of Technology Department of Computer Science and Information Engineering Taipei106 Taiwan National Chung Cheng University Department of Electrical Engineering Chiayi621 Taiwan

As the self-driving technology is getting mature for public transportation applications, the safety concern of onboard passengers has become an important issue. It is essential to identify inappropriate or hazardous behaviors of passengers for the vehicles without human operators. In this work, we propose a technique to detect and classify the abnormal activities of passengers in a bus environment. Different from the existing human activity classification algorithms, our approach reduces the occlusion and increases the recognition rate by acquiring images from an overhead vision system. To overcome the increased complexity on feature extraction and classification, an action recognition network for top-view images are proposed by incorporating both spatial and temporal information. An image dataset, BUS-HAR, is generated for practical application scenarios with bus passengers. Experiments using real-world scene images have demonstrated the feasibility of our technique compared to existing approaches. The codes and image dataset are made available publicly at https://***/richardkuo1999/passenger-action-recognition. © 2013 IEEE.

关键词： Extraction

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Photonic Crystal Microring Resonator on a Hybrid Silicon nitride-on-lithium niobate Platform

Photonic Crystal Microring Resonator on a Hybrid Silicon nit...

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CLEO: Applications and technology in CLEO 2024, CLEO: A and T 2024 - Part of Conference on Lasers and Electro-Optics

作者： Peng, Zhongdi Krishna, Rakesh Wu, Xi Hosseinnia, Amir H. Fan, Tianren Adibi, Ali School of Electrical and Computer Engineering Georgia Institute of Technology United States

We demonstrate a photonic crystal resonator on hybrid silicon nitride-on-lithium niobate (SiN-on-LN) platform, designed for microwave-assisted optical-frequency conversion applications. We measure a large intrinsic quality factor (Qint) of 1.47×105 with mode-splitting bandwidth of 14.6 GHz. © Optica Publishing Group 2024, © 2024 The Author(s)

关键词： Photonic crystals

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Bluetooth Low Energy-Based Novel Power Efficient Buffalo Calving Detection Solution

IEEE Networking Letters

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IEEE Networking Letters 2025年第1期7卷 6-10页

作者： Raina, Radhika Jeet Singh, Kamal Kumar, Suman Jain, Sarthak Indian Institute of Technology Ropar Department of Electrical Engineering Rupnagar140001 India Guru Gobind Singh Indraprastha University Computer Science and Engineering New Delhi110078 India

This letter focuses on tackling the challenge of accurately determining the timing of buffalo calving while prioritizing power efficiency. To achieve this, a novel, compact, lightweight and power efficient device is designed for buffalo comfort and can be conveniently attached to the tail. The device wirelessly transmits data to a gateway using Bluetooth Low Energy (BLE). This functionality becomes particularly crucial when the tail movement increases in the last 12 hrs before calving and is regarded as a key behavioral indicator for predicting the onset of labor. Moreover, when an accelerometer is tied to the buffalo's tail, the Z axis, which represents the vertical axis perpendicular to ground is anticipated to show the most notable deflections during this period as discussed in the literature. Thus, to conserve power, data is only transmitted when significant tail movement is detected, typically 12 hrs before calving, i.e., when Mean Z >-3 m/s2. This approach reduces the device's power consumption, extending its battery life to more than 6.08 years (approx.) using 620 mAh / 3V battery. © 2019 IEEE.

关键词： Accelerometers

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