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Orbiting Optimization Model for Tracking Voltage Security Region Boundary in Bulk Power Grids

CSEE Journal of Power and Energy systems 2022年第2期8卷 476-487页

作者： Xue Li Tao Jiang Linquan Bai Xiao Kou Fangxing Li Houhe Chen Guoqing Li the Department of Electrical Engineering Northeast Electric Power UniversityJilin 132012China the Department of Systems Engineering and Engineering Management University of North Carolina at CharlotteCharlotteNC28223 USA the Department of Electrical Engineering and Computer Science University of TennesseeKnoxvilleTN37996 USA

A voltage security region(VSR)is a powerful tool for monitoring the voltage security in bulk power grids with high penetration of *** can prevent cascading failures in wind power integration areas caused by serious over or low voltage *** bottlenecks of a VSR for practical applications are computational efficiency and *** bridge these gaps,a general optimization model for tracking a voltage security region boundary(VSRB)in bulk power grids is developed in this paper in accordance with the topological characteristics of the ***,the initial VSRB point on the VSRB is examined with the traditional OPF by using the base case parameters as initial ***,the rest of the VSRB points on the VSRB are tracked one after another,with the proposed optimization model,by using the parameters of the tracked VSRB point as the initial value to explore its adjacent VSRB *** proposed approach can significantly improve the computational efficiency of the VSRB tracking over the existing algorithms,and case studies,in the WECC 9-bus and the Polish 2736-bus test systems,demonstrate the high accuracy and efficiency of the proposed approach on exploring the VSRB.

关键词： Optimal power flow(OPF) stress direction voltage security critical point voltage security region voltage security region boundary

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TCIP: Transformed Colour Intensity Profiles analysis for fault detection in power line insulators

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Multimedia Tools and Applications 2025年第8期84卷 4503-4534页

作者： Tomaszewski, Michal Gasz, Rafal Kasana, Singara Singh Osuchowski, Jakub Singh, Simranjit Zator, Slawomir Department of Computer Science Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Prószkowska 76 Opole45-758 Poland Department of Computer Science and Information Technology Central University of Haryana Haryana Mahendergarh123031 India Department of Information Technology Dr B. R. Ambedkar National Institute of Technology Punjab Jalandhar India Department of Safety Engineering and Technical Systems Faculty of Production Engineering and Logistics Opole University of Technology Prószkowska 76 Opole45-758 Poland

In response to the escalating demand for electricity, the aging process and inherent failures in power lines have become unavoidable challenges in their operational integrity. This research addresses the imperative need for a robust method to detect damage in power insulator disc images, introducing a novel feature extraction technique grounded in color intensity profile transformation and ensemble learning. For the purposes of the research, a specific dataset was developed based on publicly available images of power insulators. The collection consists of 9232 images of insulator discs which included 2184 images of damaged discs. The discernible damages include breakages and burnouts. Two distinct analysis variants were employed. In the first variant (V1), two classification groups were selected: disc with damages and disc without damages. In the second variant (V2), three classification groups were selected: discs without damage, broken discs, and burnout discs. The described research was divided into two successive stages. In the first of them (S1), the transformed color intensity profiles for the prepared data set were built and various machine learning models for their classification were trained and evaluated. In the next stage (S2), previously developed, highest efficient machine learning models, were used to make the detection of various damaged types of overhead line insulator discs. For the first stage of research high-performance results and a high value of the F1 score parameters were obtained (F1 score = 0.999 for the first variant (S1V1) and F1 score = 0.992 for the second variant (S1V2). In the second stage of research and the first variant (S2V1), the highest result of the F1 score was 0.932 and for the second variant (S2V2) F1 score was 0.930. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Feature extraction

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STARS Assisted Semi-Grant-Free NOMA Communications

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IEEE Transactions on Wireless Communications 2025年第6期24卷 4904-4919页

作者： Xie, Jin Yue, Xinwei Zhao, Jingjing Zou, Yixuan Liu, Yuanwei Liu, Rongke Ding, Zhiguo Key Laboratory of Information and Communication Systems China Beijing Information Science and Technology University Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing100101 China Beihang University School of Electronic and Information Engineering Beijing100191 China Queen Mary University of London School of Electronic Engineering and Computer Science LondonE1 4NS United Kingdom The University of Hong Kong Department of Electrical and Electronic Engineering Hong Kong Hong Kong Kyung Hee University Department of Electronic Engineering Gyeonggi-do Yongin-si17104 Korea Republic of Khalifa University Department of Computer and Information Engineering Abu Dhabi United Arab Emirates

This paper investigates the performance of simultaneously transmitting and reflecting surface (STARS) assisted semi-grant-free non-orthogonal multiple access network with randomly distributed users. By deploying STARS, the transmit signals of grant-based user (GBU) and grant-free users (GFUs) can be exquisitely adjusted to reduce interference. We propose a maximum channel scheduling (MCS) protocol that allows a GFU to access GBU’s channel with the assistance of STARS. In particular, the impacts of perfect/imperfect successive interference cancellation (pSIC/ipSIC) on MCS protocol are taken into account. To characterize the performance of STARS aided MCS (STARS-MCS) network, we derive the expressions of outage probability for GBU and GFU with pSIC/ipSIC. By applying convolution theorem and Laplace transform, the asymptotic expressions of outage probability and diversity orders for GBU and GFU are attained. We further design a STARS-based power control (SPC) strategy to eliminate the outage probability error floor and improve the outage performance. Numerical results show that: 1) The performance of STARS-MCS outperforms the existing benchmarks in terms of outage probability and system throughput;2) The SPC strategy can effectively improve the performance of the STARS-MCS network and eliminate the outage probability error floor at high signal-to-noise ratios;and 3) By adjusting reflection and transmission coefficients of STARS, the outage performance of GBU and GFU can be greatly enhanced. © 2025 IEEE. All rights reserved.

关键词： Laplace transforms

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Enhancing Object Detection Accuracy Through RGB and Event Fusion in Motion Blurred Images

Enhancing Object Detection Accuracy Through RGB and Event Fu...

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2024 International Conference on Electronics, information, and Communication, ICEIC 2024

作者： Son, Hyeok Jin Park, Kyung Dae Rhee, Chae Eun Inha University Department of Information and Communication Engineering Incheon Korea Republic of Inha University Department of Electrical and Computer Engineering Incheon Korea Republic of

ISBN: (纸本)9798350371888

Deep learning-based object detection exhibits impressive levels of accuracy. However, its performance significantly degrades when motion blur occurs in images captured with an RGB camera. In contrast, an event camera is a sensor that detects brightness changes for each pixel, offering advantages such as high temporal resolution and low latency. It has been recently applied to various computer vision tasks. In this paper, we propose a fused image that combines RGB and event data, leveraging the advantages of the event camera to enhance detection accuracy in motion-blurred images. No additional operations are required for deblurring. Thus, it incurs minimal computational overhead and can be used without modifying the existing object detection model structure. © 2024 IEEE.

关键词： Object detection

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Germanium microring avalanche photodetector for 2 μm wavelengths

Germanium microring avalanche photodetector for 2 μm wavele...

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2025 IEEE Silicon Photonics Conference, SiPhotonics 2025

作者： Zhang, Chao Zhao, Ziqiang Tang, Rui Toprasertpong, Kasidit Takagi, Shinichi Takenaka, Mitsuru The University of Tokyo Department of Electrical Engineering and Information Systems Tokyo Japan

Waveguide-coupled Ge avalanche photodetector operating at 2 μm wavelength was demonstrated on GeOI platform. Thanks to microring resonator and avalanche gain, we achieved 2.18 A/W responsivity at -11 V and clear eye ... 详细信息

ISBN: (纸本)9798331506186

关键词： Photodetectors

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Automated analysis of fundus images for the diagnosis of retinal diseases: a review

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Research on Biomedical engineering 2024年第1期40卷 225-251页

作者： Berto, Alexa Scarpa, Fabio Tsiknakis, Nikos Manikis, Georgios Fotiadis, Dimitrios I. Marias, Kostas Scarpa, Alberto D-Eye s.r.l. Padua Italy Department of Information Engineering University of Padova Padua35131 Italy Heraklion70013 Greece Department of Biomedical Research Institute of Molecular Biology and Biotechnology FORTH Ioannina45115 Greece Department of Materials Science and Engineering Unit of Medical Technology and Intelligent Information Systems University of Ioannina Ioannina45110 Greece Department of Electrical and Computer Engineering Hellenic Mediterranean University Heraklion71004 Greece

Purpose: Colour fundus images are widely used in diagnosis treatment decision of several retinal diseases such as diabetic retinopathy (DR), glaucoma and age-related macular degeneration (AMD). These very common conditions must be detected early and monitored to prevent progression and avoid permanent damage. Fundus images revealed to be useful also for the diagnosis of cataracts. In recent years, various automatic diagnostic support methods have been proposed in the literature, with the aim of facilitating widespread screening and obtaining quantitative, objective, and reproducible information. Methods: In this review paper, an overview of traditional, machine learning and modern deep learning techniques for ophthalmic disease diagnosis (i.e. glaucoma, DR, AMD, and cataract) using retinal fundus images is presented. In addition, various publicly available image datasets used for such purposes are described. Results: The current main challenges and findings are identified, as well as common aspects and discrepancies between the various methods developed for the various diseases. Conclusion: The overview of what has been done about all pathologies, rather than only on a specific one, could favour a migration of the best solutions and, hopefully, the development of a more precise and clinically useful automatic analysis of all pathologies. Important critical insights and research trends are also discussed. Graphical abstract: (Figure presented.) © The Author(s), under exclusive licence to The Brazilian Society of Biomedical engineering 2023.

关键词： Pathology

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Distributed Robust Indirect Adaptive Control for Manipulation of a Passive Object by a Group of Robotic Agents 63

Distributed Robust Indirect Adaptive Control for Manipulatio...

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Giordano, Jacopo Cenedese, Angelo Serrani, Andrea University of Padua Department of Information Engineering Italy The Ohio State University Department of Electrical & Computer Engineering ColumbusOH43210 United States

ISBN: (纸本)9798350316339

In this work, a distributed indirect adaptive controller is designed for a group of robotic agents cooperatively manipulating a common payload. Uncertainty on the model of the manipulated object and limited actuation capabilities of the single agents can significantly impact the overall behavior of the control system. An indirect adaptive control scheme is proposed in this paper to address these shortcomings. In particular, model uncertainty and loss of effectiveness of the actuators are handled in a unifying fashion by an adaptive control architecture that preserves physical consistency of the estimated inertial parameters of the manipulated object, while simultaneously providing an anti-windup mechanism for the estimated inertial parameters against actuator saturation. The stability of the closed loop system is proven theoretically and the performance and robustness of the control system are validated by means of comparative simulations with respect to a baseline state-of-the-art controller. © 2024 IEEE.

关键词： Adaptive control systems

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Assessing Biological Responses of Saccharomyces Cerevisiae to Low-Frequency Electromagnetic Fields: Insights and Implications 15

Assessing Biological Responses of Saccharomyces Cerevisiae t...

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15th International Conference Elektro, ELEKTRO 2024

作者： Bajtos, Marek Radil, Roman Janousek, Ladislav Dang, Nhat University of Zilina Faculty of Electrical Engineering and Information Technology Department of Electromagnetic and Biomedical Engineering Zilina Slovakia University of Colorado Boulder Department of Electrical Computer and Energy Engineering BoulderCO United States

ISBN: (纸本)9798350372359

This study investigates the biological effects of Low-Frequency Electromagnetic Fields (LF-EMF) on Saccharomyces cerevisiae yeast cells, an essential model organism in biological research. To achieve controlled exposure, the exposure system ensuring uniform exposition while maintaining identical cultivation conditions for both exposed and control samples is used. To evaluate the impact of LF-EMF, yeast cell growth and proliferation were quantified using a Bürker chamber before and after exposure. Our findings reveal statistically significant differences between the exposed and control samples, suggesting a potential biological response to LF-EMF. The present research offers valuable insights into the effects of LF-EMF on biological cells, contributing to the broader understanding of electromagnetic field's impact on living organisms. Furthermore, the proposed exposure system provides a reliable platform for future bioelectromagnetic research, facilitating health risk assessments and investigations into the therapeutic potential of LF-EMF exposure. © 2024 IEEE.

关键词： Electromagnetic fields

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OFDM with Generalized Cascade Index Modulation for Secure Communications

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China Communications 2024年第10期21卷 210-225页

作者： Hu Zeng Jin Xiaopin Yao Yudong Chen Fangjiong Wan Dehuan Liu Yun College of Information Science and Technology Zhongkai University of Agriculture and EngineeringGuangzhou 510225China College of Information Engineering China Jiliang UniversityHangzhou 310018China Department Electrical and Computer Engineering Stevens Institute of Technology HobokenNJ 07030USA School of Electronic and Information Engineering South China University of TechnologyGuangzhou 510641China Center for Data Science and Artificial Intelligence Guangdong University of FinanceGuangzhou 510521China

Cascade index modulation(CIM) is a recently proposed improvement of orthogonal frequency division multiplexing with index modulation(OFDM-IM) and achieves better error *** CIM, at least two different IM operations construct a super IM operation or achieve new functionality. First, we propose a OFDM with generalized CIM(OFDM-GCIM) scheme to achieve a joint IM of subcarrier selection and multiple-mode(MM)permutations by using a multilevel digital ***, two schemes, called double CIM(D-CIM) and multiple-layer CIM(M-CIM), are proposed for secure communication, which combine new IM operation for disrupting the original order of bits and symbols with conventional OFDM-IM, to protect the legitimate users from eavesdropping in the wireless communications. A subcarrier-wise maximum likelihood(ML) detector and a low complexity log-likelihood ratio(LLR) detector are proposed for the legitimate users. A tight upper bound on the bit error rate(BER) of the proposed OFDM-GCIM, D-CIM and MCIM at the legitimate users are derived in closed form by employing the ML criteria detection. computer simulations and numerical results show that the proposed OFDM-GCIM achieves superior error performance than OFDM-IM, and the error performance at the eavesdroppers demonstrates the security of D-CIM and M-CIM.

关键词： cascade index modulation low-complexity detector maximum likelihood OFDM physical layer security

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DeepCNN:Spectro-temporal feature representation for speech emotion recognition

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CAAI Transactions on Intelligence Technology 2023年第2期8卷 401-417页

作者： Nasir Saleem Jiechao Gao Rizwana Irfan Ahmad Almadhor Hafiz Tayyab Rauf Yudong Zhang Seifedine Kadry Department of Electrical Engineering Faculty of Engineering and TechnologyGomal UniversityD.I.KhanPakistan Department of Computer Science University of VirginiaCharlottesvilleVirginiaUSA Department of Information Technology College of Computing and Information Technology at KhulaisUniversity of JeddahJeddahSaudi Arabia Department of Computer Engineering and Networks College of Computer and Information SciencesJouf UniversitySkaka AljoufSaudi Arabia Centre for Smart Systems AI and CybersecurityStaffordshire UniversityStoke‐on‐TrentUK School of Computing and Mathematical Sciences University of LeicesterLeicesterUK Department of Applied Data Science Noroff University CollegeKristiansandNorway Artificial Intelligence Research Center(AIRC) Ajman UniversityAjmanUnited Arab Emirates Department of Electrical and Computer Engineering Lebanese American UniversityByblosLebanon

Speech emotion recognition(SER)is an important research problem in human-computer interaction *** representation and extraction of features are significant challenges in SER *** the promising results of recent studies,they generally do not leverage progressive fusion techniques for effective feature representation and increasing receptive *** mitigate this problem,this article proposes DeepCNN,which is a fusion of spectral and temporal features of emotional speech by parallelising convolutional neural networks(CNNs)and a convolution layer-based *** parallel CNNs are applied to extract the spectral features(2D-CNN)and temporal features(1D-CNN)representations.A 2D-convolution layer-based transformer module extracts spectro-temporal features and concatenates them with features from parallel *** learnt low-level concatenated features are then applied to a deep framework of convolutional blocks,which retrieves high-level feature representation and subsequently categorises the emotional states using an attention gated recurrent unit and classification *** fusion technique results in a deeper hierarchical feature representation at a lower computational cost while simultaneously expanding the filter depth and reducing the feature *** Berlin Database of Emotional Speech(EMO-BD)and Interactive Emotional Dyadic Motion Capture(IEMOCAP)datasets are used in experiments to recognise distinct speech *** efficient spectral and temporal feature representation,the proposed SER model achieves 94.2%accuracy for different emotions on the EMO-BD and 81.1%accuracy on the IEMOCAP dataset *** proposed SER system,DeepCNN,outperforms the baseline SER systems in terms of emotion recognition accuracy on the EMO-BD and IEMOCAP datasets.

关键词： decision making deep learning

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