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A State-Migration Particle Swarm Optimizer for Adaptive Latent Factor Analysis of High-Dimensional and Incomplete Data

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IEEE/CAA Journal of Automatica Sinica 2024年第11期11卷 2220-2235页

作者： Jiufang Chen Kechen Liu Xin Luo Ye Yuan Khaled Sedraoui Yusuf Al-Turki MengChu Zhou IEEE the College of Computer Science and Technology Chongqing University of Posts and Telecommunications the Department of Computer Science Columbia University the College of Computer and Information Science Southwest University the Department of Electrical and Computer Engineering Faculty of Engineeringand also with K.A.CARE Energy Research and Innovation CenterKing Abdulaziz University the Center of Research Excellence in Renewable Energy and Power Systems the Department of Electrical and Computer EngineeringFaculty of Engineeringand also with K.A.CARE Energy Research and Innovation CenterKing Abdulaziz University the Department of Electrical and Computer Engineering New Jersey Institute of Technology

High-dimensional and incomplete(HDI) matrices are primarily generated in all kinds of big-data-related practical applications. A latent factor analysis(LFA) model is capable of conducting efficient representation learning to an HDI matrix,whose hyper-parameter adaptation can be implemented through a particle swarm optimizer(PSO) to meet scalable ***, conventional PSO is limited by its premature issues,which leads to the accuracy loss of a resultant LFA model. To address this thorny issue, this study merges the information of each particle's state migration into its evolution process following the principle of a generalized momentum method for improving its search ability, thereby building a state-migration particle swarm optimizer(SPSO), whose theoretical convergence is rigorously proved in this study. It is then incorporated into an LFA model for implementing efficient hyper-parameter adaptation without accuracy loss. Experiments on six HDI matrices indicate that an SPSO-incorporated LFA model outperforms state-of-the-art LFA models in terms of prediction accuracy for missing data of an HDI matrix with competitive computational ***, SPSO's use ensures efficient and reliable hyper-parameter adaptation in an LFA model, thus ensuring practicality and accurate representation learning for HDI matrices.

关键词： Data science generalized momentum high-dimensional and incomplete(HDI)data hyper-parameter adaptation latent factor analysis(LFA) particle swarm optimization(PSO)

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RUL Estimation for Power Electronic Devices Using RNNs

RUL Estimation for Power Electronic Devices Using RNNs

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2024 Prognostics and System Health Management Conference, PHM 2024

作者： Cai, Congrui Lu, Zhonghai School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Embedded Systems Master Program Sweden School of Electrical Engineering and Computer Science Department of Electrical Engineering KTH Royal Institute of Technology Sweden

ISBN: (纸本)9798350360585

Recurrent Neural Networks (RNNs) are commonly used in data-driven approaches to estimate the Remaining Useful Lifetime (RUL) of power electronic devices. RNNs are preferred because their intrinsic feedback mechanisms are better suited to model time-series data. However, the impact of RNN complexity on estimation accuracy is rarely discussed in the literature. This issue is important because choosing a lower-complexity model that delivers the same or similar performance as a higher-complexity model can increase implementation efficiency. In the paper, we use three RNN models, namely, the vanilla version, LSTM (Long Short Term Memory) and GRU (Gated Recurrent Unit) to conduct RUL estimation for power electronic devices. We use two accelerated aging datasets, one dataset targeting the package failure of MOSFETs, and the other dataset targeting package failure of power diodes. Our study shows that a lower-complexity RNN does not necessarily deliver a lower performance. Similarly, a higher-complexity model does not assure a higher performance. As such, our work highlights the importance of selecting a proper neural network for RUL estimation not biased towards complex models. This is especially useful and important for implementing such RUL estimation techniques in embedded resource-constrained and speed-limited computins platforms. © 2024 IEEE.

关键词： Long short-term memory

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A Fault Diagnosis Method for Smart Meters via Two-layer Stacking Ensemble Optimization and Data Augmentation

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Journal of Modern Power systems and Clean Energy 2024年第4期12卷 1272-1284页

作者： Leijiao Ge Tianshuo Du Zhengyang Xu Luyang Hou Jun Yan Yuanliang Li School of Electrical and Information Engineering Tianjin UniversityTianjin 300072China School of Computer Science(National Pilot Software Engineering School) Beijing University of Posts and TelecommunicationsBeijing 100876China Concordia Institute for Information Systems Engineering Concordia UniversityMontrealQC H3G 1M8Canada

The accurate identification of smart meter(SM)fault types is crucial for enhancing the efficiency of operationand maintenance(O&M)and the reliability of power ***,the intelligent classification of SM fault typesfaces significant challenges owing to the complexity of featuresand the imbalance between fault *** address these issues,this study presents a fault diagnosis method for SM incorporatingthree distinct *** first module employs acombination of standardization,data imputation,and featureextraction to enhance the data quality,thereby facilitating improvedtraining and learning by the *** enhance theclassification performance,the data imputation method considersfeature correlation measurement and sequential imputation,and the feature extractor utilizes the discriminative enhancedsparse *** tackle the interclass imbalance of datawith discrete and continuous features,the second module introducesan assisted classifier generative adversarial network,which includes a discrete feature generation ***,anovel Stacking ensemble classifier for SM fault diagnosis is *** contrast to previous studies,we construct a two-layerheuristic optimization framework to address the synchronousdynamic optimization problem of the combinations and hyperparametersof the Stacking ensemble classifier,enabling betterhandling of complex classification tasks using SM *** proposedfault diagnosis method for SM via two-layer stacking ensembleoptimization and data augmentation is trained and validatedusing SM fault data collected from 2010 to 2018 in Zhejiang Province,*** results demonstrate the effectivenessof the proposed method in improving the accuracyof SM fault diagnosis,particularly for minority classes.

关键词： Data augmentation fault diagnosis feature extraction smart meter Stacking ensemble optimization

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Arabic text sentiment analysis and emotion classification using transformers 11

Arabic text sentiment analysis and emotion classification us...

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11th International Japan-Africa Conference on Electronics, Communications, and Computations, JAC-ECC 2023

作者： Mossad, Nada Mohamed, Youssef Fares, A. Zaky, Ahmed B. Alexandria21934 Egypt Benha University The Computer Systems Engineering Program Faculty of Engineering at Shoubra The Department of Electrical Engineering Egypt

ISBN: (纸本)9798350369328

Sentiment analysis and emotion classification are two crucial components of natural language processing (NLP), which have been widely explored in recent years due to their broad applications. Sentiment analysis aims to identify the polarity of written texts, ranging from positive to negative. Meanwhile, emotion classification is focused on recognizing and categorizing the emotional states expressed in the text. To achieve a deeper understanding of sentiments and emotions, it's essential to utilize models like BERT transformers that can effectively interpret the context. The process begins with data preprocessing, including tokenization and noise removal, followed by fine-tuning techniques to adapt the BERT model to the proposed tasks. We employed the BERT model on four datasets obtained from various sources, including Twitter, news websites, and restaurant reviews, where each dataset represents a distinct Arabic dialect. Our proposed model outperforms commonly used techniques like LSTM and CNN, yielding superior results. Despite the progress made, there are still challenges to overcome, such as dealing with Arabic diacritics, the new Arabic Arabizi, which uses Latin characters, and handling Arabic idioms. Further research is required to address these challenges adequately. © 2023 IEEE.

关键词： Sentiment analysis

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Adaptive Droop Control in VSC-Based MT-MVDC Distribution systems Considering ESS Participation

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IEEE Transactions on Energy Conversion 2024年第2期40卷 761-772页

作者： Sun, Pingyang Pinthurat, Watcharakorn Li, Gen Khalid, Muhammad Town, Graham Konstantinou, Georgios UNSW Sydney School of Electrical Engineering and Telecommunications NSW2052 Australia Rajamangala University of Technology Tawan-Ok Department of Electrical Engineering Chanthaburi Thailand Energy Technology and Computer Science Section Department of Engineering Technology Ballerup2750 Denmark King Fahd University of Petroleum and Minerals Electrical Engineering Department Interdisciplinary Research Center for Sustainable Energy Systems Dhahran31261 Saudi Arabia Macquarie University School of Engineering NSW2019 Australia

This paper proposes a novel adaptive droop (ADC) control for voltage source converter (VSC)-based multiterminal medium-voltage direct current (MT-MVDC) distribution systems with heterogeneous energy storage system (ESS) participation. The proposed ADC scheme can achieve MVDC bus voltage management and power sharing between VSCs with overloading operation, solving the issue that all VSCs on the rectifier/inverter side reach their power limits concurrently after a large system disturbance. This is accomplished by factoring in the real-time power/voltage values at VSC stations along with an extended power component. This component is contingent on the actual operational state of the ESSs and inversely correlated with the power delivered/absorbed by the ESSs. Moreover, the controllers of the battery and ultracapacitor systems incorporate two additional control loops, a novel VSC excess power reduction (VEPR) loop as well as inner expanded excess power reduction (EEPR) loop, to obtain the power reference values. The two loops ensure all VSCs operate within individual power limits after the engagement of the ESS. The effectiveness of proposed ADC strategy is confirmed through real-time simulations in a hybrid AC/MT-MVDC system. © 1986-2012 IEEE.

关键词： Charge storage

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Metasurfaces for next-generation wireless communication systems

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National Science Review 2023年第8期10卷 17-19页

作者： Younes Ra'di Nikita Nefedkin Petar Popovski Andrea Alù Department of Electrical Engineering and Computer Science Syracuse University Photonics Initiative Advanced Science Research Center City University of New York Department of Electronic Systems Aalborg University Physics Program Graduate Center City University of New York

The pace of development in the world of 5G communication systems has proven to be much more demanding than previous generations, with 5G-Advanced seemingly around the corner [1]. Extensive research is already underway to structure the next generation of wireless systems(i.e. 6G), which may potentially enable an unprecedented level of human–machine interaction [2].

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Analyzing Closed-loop Control Methods in Domino Resonant Inductive Wireless Power Transfer System

Analyzing Closed-loop Control Methods in Domino Resonant Ind...

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2023 IEEE International Conference on Environment and electrical engineering and 2023 IEEE Industrial and Commercial Power systems Europe, EEEIC / I and CPS Europe 2023

作者： Sarsembayev, Bayandy Heidari Yazdi, Seyed Saeid Shafiei, Sadjad Kermani, Mostafa Saukhimov, Almaz Bagheri, Mehdi Nazarbayev University Dept. of Electrical and Computer Engineering Astana Kazakhstan Sapienza University of Rome Dept. of Electrical Engineering Rome Italy University of Power Engineering and Telecommunications Dept. of Electrical Systems and Networks Almaty Almaty Kazakhstan

ISBN: (纸本)9798350347432

This study analyzes the closed-loop control strategy for the domino resonant inductive power transfer (DR-IPT) system (modulation of DC-link voltage, phase shift, and switching frequency) for wireless battery charging. A high-voltage AC line (HVAC) is supposed to provide the initial AC voltage for the power converter. Three closed-loop control scenarios are used and the performance of the DR-IPT is examined. The frequency and phase shift controls are applied directly to the full-bridge inverter via the PWM technique, and the DC-link voltage control is employed with the buck-boost converter. This study shows that PI controllers are appropriate to achieve the desired system performance to charge a LiPo battery. Also, the simulation results reveal that the charging process can be effectively regulated using controllers;however, among different approaches, the phase shift control method might be considered the most suitable approach for charging the LiPo battery and avoiding bifurcation and increasing the cost of the RD-IPT system. © 2023 IEEE.

关键词： Energy transfer

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Overview of Versatile Video Coding (H.266/VVC) and Its Coding Performance Analysis

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IEIE Transactions on Smart Processing and Computing 2023年第2期12卷 122-154页

作者： Lee, Minhun Song, HyeonJu Park, Jeeyoon Jeon, Byeungwoo Kang, Jungwon Kim, Jae-Gon Lee, Yung-Lyul Kang, Je-Won Sim, Donggyu Department of Computer Engineering Kwangwoon University Seoul Korea Republic of Department of Computer Engineering Sejong University Seoul Korea Republic of Department of Electrical and Computer Engineering Sungkyunkwan University Kyunggi-do Korea Republic of Communication and Media Research Laboratory Electronics and Telecommunications Research Institute Deajeon Korea Republic of School of Electronics and Information Engineering Korea Aerospace University Kyunggi-do Korea Republic of Department of Electronic and Electrical Engineering Graduate Program in Smart Factory Ewha Womans University Seoul Korea Republic of

Versatile Video Coding (H.266/VVC) is the newest video coding standard jointly developed by the Joint Video Experts Team (JVET), which is organized by the ITU-T Video Coding Experts Group (VCEG) and the ISO/IEC Moving Picture Experts Group (MPEG). H.266/VVC provides about 40% bitrate reduction compared with High Efficiency Video Coding (H.265/HEVC) for the same visual quality. This paper introduces in detail the core structure of H.266/VVC by highlighting its features within block partitioning structure, intra/inter prediction, transform, quantization, and in-loop filtering, compared to its predecessor (H.265/HEVC). H.266/VVC yields significantly improved the coding performance, but it increased the computational complexity, particularly for the encoder side, which remains a problem to be tackled for successful commercialization in the future. This paper examined the statistical performance of H.266/VVC coding tools from the bitstreams encoded by the VVC test model (VTM12.0) encoder through rate-distortion optimization under the JVET common test conditions. In addition, the complexity and performance analyses are conducted on the block partitioning structure and group of picture structure. It is expected that an optimized H.266/VVC encoder can be designed and developed by minimizing the coding loss based on the analysis data. © 2023 Institute of Electronics and Information Engineers. All rights reserved.

关键词： Image compression

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Switching Performance Evaluation of two State-of-the-Art SiC MOSFETs

Switching Performance Evaluation of two State-of-the-Art SiC...

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Australasian Universities Power engineering Conference, AUPEC

作者： Fredrick Nkado John Fletcher Hang Zhou Scott Tyo Fatemeh Babaeian School of Electrical Engineering and Telecommunications UNSW Sydney Department of Electrical and Computer Systems Engineering Monash University Melbourne

ISBN: (数字)9798350377941

ISBN: (纸本)9798350377958

This paper compares the switching performance of two state-of-the-art Silicon Carbide (SiC) Metal-Oxide-Semiconductor Field-Effect Transistors (MOSFETs) utilising the Double Pulse Test method. The evaluation focuses on assessing the impact of key parameters such as total gate charge $\left(Q_{g}\right)$ and on-resistance $\left(R_{O N}\right)$ on the switching characteristics of the MOSFETs. Through experimental investigation, the switching behaviours, including turn-on and turn-off times, switching losses, and body-diode reverse recovery characteristics ($Q_{r r}$), are analysed and compared between the two devices. The results demonstrate that a SiC MOSFET with a lower total gate charge and higher on-resistance exhibits superior switching performance compared to a SiC MOSFET with a higher total gate charge and lower on-resistance. The study concludes that prioritising low total gate charge for faster switching for pulsed power applications is more critical than minimising conduction losses through a lower $R_{O N}$.

关键词： Performance evaluation MOSFET Power engineering Silicon carbide Switching loss Switches Logic gates Transistors Switching circuits

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Capacity Development Through Intensive Training of Higher Education Teachers for Implementation of PLC Curricula in South-East Asia 21

Capacity Development Through Intensive Training of Higher Ed...

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21st International Conference on Information Technology Based Higher Education and Training, ITHET 2024

作者： Bencheva, Nina Zahariev, Plamen Hristov, Georgi Banjerdpongchai, David Kostadinov, Nikolay University of Ruse 'Angel Kanchev' Telecommunications Department Ruse Bulgaria Chulalongkorn University Department of Electrical Engineering Bangkok Thailand University of Ruse 'Angel Kanchev' Computer Systems and Technology Department Ruse Bulgaria

ISBN: (纸本)9798331516635

The ASEAN Factori 4.0 project seeks to contribute to the enhancement of education in industrial automation at six Asian universities in Thailand, Laos, and Cambodia. The paper outlines the steps of teacher-intensive training and evaluates the results, including an analysis of the methodology employed. The training was divided into two parts, each lasting two weeks. Its objective was to prepare teachers and equip them with practical skills to train students in programmable Logic Controllers (PLCs) and their applications in industrial automation. During the first part (Training 1), Asian teachers underwent training at three EU universities: Claude Bernard University Lyon 1, University of Ruse, and Grenoble Alpes University. The second part (Training 2) took place at the Centres of Excellence established in the six Asian universities: Chulalongkorn University, Mae Fah Luang University, Royal University of Phnom Penh, Institute of Technology of Cambodia, National University of Laos, and Savannakhet University. Pre- and Post-surveys were conducted after each training session to assess the participants' knowledge and gather feedback. The Pre-test aimed to evaluate the trainees' level of PLC knowledge, while the Post-test questionnaires collected feedback and assessed the courses' effectiveness. Two Post-tests were designed: one completed after each lab session to adjust training sessions and teaching materials based on the feedback, and another one assessing overall trainee satisfaction. The paper presents an analysis of the results of all surveys and conclusions with regard to the results and the effectiveness of the training are drawn. © 2024 IEEE.

关键词： Teaching

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