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2023 IEEE International Conference on Robotics and Biomimetics, ROBIO 2023

作者： Wang, Wen Lin, Zheyuan Ji, Shanshan Li, Te Gu, Jason Wan, Minhong Zhang, Chunlong Research Center for Intelligent Robotics Zhejiang Lab Zhejiang Engineering Research Center for Intelligent Robotics Hangzhou311100 China Dalhousie University Department of Electrical and Computer Engineering Canada

ISBN: (纸本)9798350325706

Transformer-based visual technologies have witnessed remarkable progress in recent years, and person re-identification (ReID) is one of the active research areas that adopts transformers to improve the performance. However, a major challenge of applying transformers to ReID is the high computational cost, which hinders the real-time deployment of such methods. To address this issue, this paper proposes two simple yet effective techniques to reduce the computation of transformers for ReID. The first technique is to eliminate the invalid patches that do not contain any person information, thereby reducing the number of tokens fed into the transformer. Considering that computational complexity is quadratic with respect to input tokens, the second technique partitions the image into multiple windows, applies separate transformers to each window, and merges class tokens from each window, which can reduce the complexity of the self-attention mechanism. By combining these two techniques, our proposed method reduces the SOTA baseline model by 12.2% FLOPs, while slightly improving the rank-1 accuracy and only sacrificing 1.1% mAP on DukeMTMC-ReID dataset. © 2023 IEEE.

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Dynamic Evolutionary Game-based Modeling,Analysis and Performance Enhancement of Blockchain Channels

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IEEE/CAA Journal of Automatica Sinica 2023年第1期10卷 188-202页

作者： PeiYun Zhang MengChu Zhou ChenXi Li Abdullah Abusorrah IEEE the School of Computer Science Nanjing University of Information Science&TechnologyNanjing 210044China the Helen and John C.Hartmann Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewarkNJ 07102 USA the School of Computer and Information Anhui Normal UniversityWuhu 241003China the Department of Electrical and Computer Engineering Faculty of Engineeringand Center of Research Excellence in Renewable Energy and Power SystemsKing Abdulaziz UniversityJeddah 21481Saudi Arabia

The recent development of channel technology has promised to reduce the transaction verification time in blockchain *** transactions are transmitted through the channels created by nodes,the nodes need to cooperate with each *** one party refuses to do so,the channel is unstable.A stable channel is thus *** nodes may show uncooperative behavior,they may have a negative impact on the stability of such *** order to address this issue,this work proposes a dynamic evolutionary game model based on node *** model considers various defense strategies'cost and attack success ratio under *** can dynamically adjust their strategies according to the behavior of attackers to achieve their effective *** equilibrium stability of the proposed model can be *** proposed model can be applied to general channel *** is compared with two state-of-the-art blockchain channels:Lightning network and Spirit *** experimental results show that the proposed model can be used to improve a channel's stability and keep it in a good cooperative stable *** its use enables a blockchain to enjoy higher transaction success ratio and lower transaction transmission delay than the use of its two peers.

关键词： Blockchain channel network evolutionary game malicious behavior secure computing stability analysis

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Employing Feature engineering for River Stage Forecasting to Improve Hybrid Model Performance 32

Employing Feature Engineering for River Stage Forecasting to...

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32nd International Conference on Software, Telecommunications and computer Networks, SoftCOM 2024

作者： Mihel, Anna Maria Pecnik, Spela Vrbancic, Grega Lerga, Jonatan Krvavica, Nino University of Rijeka Faculty of Engineering Department of Computer Engineering Rijeka Croatia University of Maribor Intelligent Systems Laboratory Faculty of Electrical Engineering and Computer Science Maribor Slovenia University of Rijeka Faculty of Civil Engineering Department of Hydrotechnics and Geotechnics Rijeka Croatia

ISBN: (纸本)9789532901382

Establishing early warning systems and efficient management of water resources in tidal reaches is crucial for achieving adequate flood protection. In tidal reaches, the river stage interacts non-linearly with tides (downstream) and discharge (upstream), making the modeling of river processes extremely complex. Data-driven methods have proven helpful for predicting the river stage parameter. This contrasts with existing numerical approaches, which suffer from several limitations. The aim of this study was to predict the river stage of the upstream part of the tidal river, where the influence of salinity is present during the summer months. Using the CNN-LSTM model trained on historical records of the discharge (station of the variable to be predicted), the river stage of three downstream stations, and the point of interest, the prediction was carried out up to 24 hours in advance. By incorporating feature engineering, we achieved an improvement in model results for the longest horizon, confirmed by standard performance metrics, and considered it efficient and effective for risk mitigation. Introducing feature engineering into the data preprocessing resulted in a predictive performance improvement of 0.98% for the Nash-Sutcliffe Efficiency (NSE) metric, 7.0% for the root mean squared error (RMSE) metric, and 7.25% for the mean absolute error (MAE) metric over the second and third-best scenarios using a spectrogram and time-series data. © 2024 University of Split, FESB.

关键词： Mean square error

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Multi-Scale Time Series Segmentation Network Based on Eddy Current Testing for Detecting Surface Metal Defects

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IEEE/CAA Journal of Automatica Sinica 2025年第3期12卷 528-538页

作者： Xiaorui Li Xiaojuan Ban Haoran Qiao Zhaolin Yuan Hong-Ning Dai Chao Yao Yu Guo Mohammad S.Obaidat George Q.Huang the School of Intelligence Science and Technology University of Science and Technology Beijing the Beijing Advanced Innovation Center for Materials Genome Engineering the Key Laboratory of Intelligent Bionic Unmanned Systems and the Institute of Materials Intelligent Technology Liaoning Academy of Materials IEEE the Department of Computer Science Hong Kong Baptist University the School of Computer and Communication Engineering Key Laboratory of Advanced Materials and Devices for Post-Moore Chips Ministry of Education University of Science and Technology Beijing the Beijing Advanced Innovation Center for Materials Genome Engineering University of Science and Technology Beijing the School of Computer and Communication Engineering University of Science and Technology Beijing the King Abdullah Ⅱ School of Information Technology The University of Jordan the Department of Computational Intelligence the School of Computing SRM University the School of Engineering The Amity University The Hong Kong Polytechnic University

In high-risk industrial environments like nuclear power plants, precise defect identification and localization are essential for maintaining production stability and safety. However, the complexity of such a harsh environment leads to significant variations in the shape and size of the defects. To address this challenge, we propose the multivariate time series segmentation network(MSSN), which adopts a multiscale convolutional network with multi-stage and depth-separable convolutions for efficient feature extraction through variable-length templates. To tackle the classification difficulty caused by structural signal variance, MSSN employs logarithmic normalization to adjust instance distributions. Furthermore, it integrates classification with smoothing loss functions to accurately identify defect segments amid similar structural and defect signal subsequences. Our algorithm evaluated on both the Mackey-Glass dataset and industrial dataset achieves over 95% localization and demonstrates the capture capability on the synthetic dataset. In a nuclear plant's heat transfer tube dataset, it captures 90% of defect instances with75% middle localization F1 score.

关键词： Eddy current testing nondestructive testing semantic segmentation time series analysis

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Enhancing Human-Robot Cohesion through HAT Methods: A Crowd-Avoidance Model for Safety Aware Navigation 4

Enhancing Human-Robot Cohesion through HAT Methods: A Crowd-...

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4th IEEE International Conference on Human-Machine systems, ICHMS 2024

作者： Sellers, Timothy Lei, Tingjun Luo, Chaomin Liu, Lantao Carruth, Daniel W. Mississippi State University Department Of Electrical And Computer Engineering Mississippi StateMS39762 United States Indiana University Department Of Intelligent Systems Engineering BloomingtonIN47408 United States Mississippi State University Center For Advanced Vehicular Systems MS39759 United States

ISBN: (纸本)9798350315790

In the world of autonomous robots, achieving complete accuracy remains a challenge, underscoring the importance of human intervention, especially regarding safety. In Human-Autonomy Teaming (HAT), ensuring safe and effective human-robot cooperation in dynamic indoor settings is crucial. This paper introduces a framework designed to address this accuracy shortfall, enhancing safety and robotic interactions in these environments. Central to our approach is a hybrid graph system that melds the Generalized Voronoi Diagram (GVD) with spatio-temporal graphs, harmonizing human feedback, environmental elements, and key waypoints. An essential component is the improved Node Selection Algorithm (iNSA), which utilizes the revised Grey Wolf Optimization (rGWO) for enhanced adaptability and performance. Human insights are instrumental, from supplying initial environmental data and determining key waypoints to stepping in during unexpected challenges or dynamic changes in the environment. Extensive simulation and comparison tests confirm the reliability and effectiveness of our model, highlighting its unique advantages in the realm of HAT. © 2024 IEEE.

关键词： Motion planning

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Enhanced Reactive Power Transfer Capability and ZVS Range Analysis for a Single-Stage DAB based Electronic Transformer Using Bidirectional Switches

Enhanced Reactive Power Transfer Capability and ZVS Range An...

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2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Rawat, Shubham Narwal, Ramandeep Bhattacharya, Subhashish Baliga, B. Jayant Hopkins, Douglas C. North Carolina State University Freedm Systems Center Department of Electrical and Computer Engineering RaleighNC27695 United States

ISBN: (纸本)9798350376067

A single-stage single-phase dual active bridge (DAB) based solid-state transformer (SST) offers various advantages over its multi-stage counterparts, including higher efficiency and reliability due to fewer components and the absence of bulky electrolytic capacitors. However, the lack of a DC link limits its reactive power transfer capability from the supply to the load, a capability even conventional transformers possess. To address this, external compensation elements are required across the load terminals to meet the desired reactive power, diminishing its primary advantage. This paper introduces a technique for a single phase AC-AC DAB-based SST to enhance the transformer's reactive power transfer capacity. It also presents a detailed analysis of the zero voltage switching range of the converter bridges under various operating conditions while supplying reactive power. The proposed schemes and analysis are further validated by experimental results on a 120/164 Vrms and 450 VA hardware prototype, demonstrating a correlation with the experimental results and highlighting the practical benefits of the proposed scheme. © 2024 IEEE.

关键词： Zero voltage switching

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Parasitic Capacitance Analysis of Integrated Transformers with Parallel Windings

Parasitic Capacitance Analysis of Integrated Transformers wi...

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2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Yuan, Tianlong Jin, Feng Li, Qiang Virginia Polytechnic and State University Center for Power Electronics Systems Bradley Department of Electrical and Computer Engineering Blacksburg United States

ISBN: (纸本)9798350376067

The electric transportation market has experienced rapid growth in recent years, driven by increasing environmental concerns. Resonant converters play a crucial role in this sector due to their ability to provide isolation and regulation functions with high efficiency. A resonant inductance embedded transformer is a critical component of the LLC resonant converter, significantly influencing the power density of the entire system, particularly in high-power applications. To achieve higher power density, the operating frequency often exceeds hundreds of kilohertz. At such high frequencies, parasitic capacitance cannot be ignored, as it may cause electromagnetic interference (EMI) issues. In high-power applications, integrated transformers with parallel windings are commonly used, adding complexity to the system. Measuring the parasitic capacitance of these transformers becomes increasingly challenging. This paper presents various measurement methods for an integrated transformer with parallel windings in a 30 kW LLC resonant converter. The results obtained from different measurement techniques were consistent with each other and with simulation results, validating the accuracy of the methods employed. © 2024 IEEE.

关键词： Resonant converters

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Analysis and Comparison of Integrated Planar Transformers for CLLC Resonant Converters

Analysis and Comparison of Integrated Planar Transformers fo...

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2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Yuan, Tianlong Jin, Feng Yu, Gibum Li, Qiang Virginia Polytechnic and State University Center for Power Electronics Systems Bradley Department of Electrical and Computer Engineering Blacksburg United States

ISBN: (纸本)9798350376067

The advancement of electric vehicles and green energy technologies necessitates on-board chargers (OBCs) with higher power density and reduced costs. Integrated planar magnetics emerge as a highly competitive option due to their superior power density and ease of manufacturing compared to traditional magnetic designs. However, detailed flux analysis, particularly the distribution on the plate, remains essential for evaluating various transformer structures. This paper presents a comprehensive comparison of different core structures for integrated transformers, validated through an 11-kW CLLC resonant converter prototype with a 98.4% peak efficiency and 420 W/inch3 power density. © 2024 IEEE.

关键词： Resonant converters

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Modeling and Analysis of The Balance Network for Common Mode EMI Noise Suppression

Modeling and Analysis of The Balance Network for Common Mode...

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2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Yang, Qiuzhe Wang, Shuo Li, Qiang Virginia Tech Center for Power Electronics Systems Bradley Department of Electrical and Computer Engineering BlacksburgVA24061 United States

ISBN: (纸本)9798350376067

This paper presents the model of the balance technique for common mode noise suppression. Considering the resonance due to the self-parasitic capacitance of the inductor in the balance network, coupling between the inductors is essential to compensate for the impact of self resonance. The derived model illustrates how the coupling coefficient affects the balance condition. To verify the model, three coupled inductors with different coupling coefficients are designed. A voltage-gain based method is proposed to simulate the real noise source in the balance network. And the voltage ratio between the balance bridges can be experimentally measured. The result matches the prediction very well and verifies the balance model. © 2024 IEEE.

关键词： Interference suppression

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Grid-Forming Inverters for Enhancing Stability and Resilience in Distribution Networks under Transients and Restoration

Grid-Forming Inverters for Enhancing Stability and Resilienc...

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2024 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2024

作者： Selim, Alaa Zhao, Junbo Seo, Gab-Su Ding, Fei Cui, Bai University of Connecticut Department of Electrical and Computer Engineering United States National Renewable Energy Laboratory Power Systems Engineering Center GoldenCO80401 United States Iowa State University Department of Electrical and Computer Engineering United States

ISBN: (纸本)9798350313604

The increasing integration of distributed energy resources in distribution networks has significantly reduced system inertia, posing challenges to grid stability during transient events, such as Cold Load Pickup (CLPU). This paper proposes the implementation of grid-forming inverters (GFMs) to enhance the stability of low-inertia distribution systems. The paper also investigates the performance of the GFM-based approach in maintaining voltage profiles along the distribution feeder, especially during CLPU scenarios without synchronous machines. A comparison is made between the GFM-based system and the conventional synchronous machine setup. The synchronous machine is chosen as a reference point for evaluating the effectiveness of the GFM-based approach. The GFM-based system's performance is assessed under various challenging scenarios, including short-circuit faults, islanding, and a combination of these through extensive simulations. The results demonstrate the potential of GFMs to stabilize a distribution system and outperform the traditional rigid synchronous machine during transient events. © 2024 IEEE.

关键词： Electric power distribution

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