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48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Zhong, Yun Zhang, Fan Demiris, Yiannis Imperial College Personal Robotics Laboratory Department of Electrical and Electronic Engineering London United Kingdom

ISBN: (纸本)9781728163277

A fundamental challenge of analyzing human motion is to effectively represent human movements both spatially and temporally. We propose a contrastive self-supervised strategy to tackle this challenge. Particularly, we focus on dancing, which involves a high level of physical and intellectual abilities. Firstly, we deploy Graph and Residual Neural Networks with Siamese architecture to represent the dance motion and music features respectively. Secondly, we apply the InfoNCE loss to contrastively embed the high-dimensional multimedia signals onto the latent space without label supervision. Finally, our proposed framework is evaluated on a multi-modal Dance- Music-Level dataset composed of various dance motions, music, genres and choreographies with dancers of different expertise levels. Experimental results demonstrate the robustness and improvements of our proposed method over 3 baselines and 6 ablation studies across tasks of dance genres, choreographies classification and dancer expertise level assessment. © 2023 IEEE.

关键词： Motion analysis

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Solution to Coordination of Transmission and Distribution for Renewable Energy Integration into Power Grids:An Integrated Flexibility Market

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CSEE Journal of Power and Energy Systems 2023年第2期9卷 444-458页

作者： Tao Jiang Zhongwei Shen Xiaolong Jin Rufeng Zhang Alessandra Parisio Xue Li Xiao Kou Department of Electrical Engineering Northeast Electric Power UniversityJilin 132012China Key Laboratory of Smart Grid of Ministry of Education Key Laboratory of Smart Energy&Information Technology of Tianjin MunicipalityTianjin UniversityTianjin 300072China Department of Electrical and Electronic Engineering The University of ManchesterManchesterUK Department of Electrical Engineering and Computer Science University of TennesseeKnoxvilleTN37996USA.

Nowadays,transmission system operators(TSOs)encounter the challenges of securely operating power grids with high penetration of *** this context,more flexibility is needed than ever to maintain system *** rapid development of coordinated transmission and distribution technology recently,active distribution networks(ADNs)which have abundant flexible resources,have the potential to provide flexibility to the ***,an integrated transmission-distribution flexibility market is proposed in this *** the proposed framework,the energy market is first cleared to obtain baseline generation *** the baseline generation schedules are treated as inputs to the flexibility ***,the integrated flexibility market is cleared to facilitate flexibility trading between transmission and distribution *** preserve the data privacy of different market participants,an alternating direction method of multipliers(ADMM)based method is utilized to clear the markets in a distributed *** the energy market and flexibility market-clearing model,transmission network market clearing models are linear programming(LP)models,and distribution network market clearing models are second order cone programming(SOCP)*** the proposed method,only limited information is exchanged between TSO and *** studies are conducted on a revised IEEE 30-bus transmission network with two 33-node *** results demonstrate the proposed flexibility market framework can enhance competitiveness of generation companies in the transmission network and distributed generators(DGs)in the ***,flexibility purchasing cost is reduced by 17.7%compared to traditional flexibility supplied by generators according to the case study results,and ADNs can gain additional flexibility profit by providing flexibility.

关键词： ADMM ADN energy market flexibility market TSO-DSO coordination

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Improving Power Response of Single-Controllable VSG-Based Active Distribution Network

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CSEE Journal of Power and Energy Systems 2025年第1期11卷 102-114页

作者： Shah Fahad Arman Goudarzi Pierluigi Siano Ji Xiang Department of Electrical and Computer Engineering Missouri University of Science and TechnologyUSA University of Victoria Canada Department of Management&Innovation Systems University of SalernoItaly Department of Electrical and Electronic Engineering Science University of JohannesburgJohannesburg2006South Africa National Laboratory of Industrial Control Technology College of Electrical EngineeringZhejiang UniversityHangzhou310058China

Controlling an active distribution network(ADN)from a single PCC has been advantageous for improving the performance of coordinated Intermittent RESs(IRESs).Recent studies have proposed a constant PQ regulation approach at the PCC of ADNs using coordination of non-MPPT based ***,due to the intermittent nature of DGs coupled with PCC through uni-directional broadcast communication,the PCC becomes vulnerable to transient *** address this challenge,this study first presents a detailed mathematical model of an ADN from the perspective of PCC regulation to realize rigidness of PCC against ***,an H_(∞)controller is formulated and employed to achieve optimal performance against disturbances,consequently,ensuring the least oscillations during transients at ***,an eigenvalue analysis is presented to analyze convergence speed limitations of the newly derived system ***,simulation results show the proposed method offers superior performance as compared to the state-of-the-art methods.

关键词： Cooperative control of DGs hierarchical control system high penetration of intermittent RESs H_(∞)control optimal control in power systems single-controllable active distribution networks

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Data Augmentation via Face Morphing for Recognizing Intensities of Facial Emotions

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IEEE Transactions on Affective Computing 2023年第2期14卷 1228-1235页

作者： Huang, Tsung-Ren Hsu, Shin-Min Fu, Li-Chen National Taiwan University Department of Psychology Center for Artificial Intelligence & Advanced Robotics Taipei106319 Taiwan National Taiwan University Center for Artificial Intelligence & Advanced Robotics Department of Electrical Engineering Department of Computer Science and Information Engineering Taipei106319 Taiwan

Being able to recognize emotional intensity is a desirable feature for a facial emotional recognition (FER) system. However, the development of such a feature is hindered by the paucity of intensity-labeled data for model training. To ameliorate the situation, the present study proposes using face morphing as a novel way of data augmentation to synthesize faces that express different degrees of a designated emotion. Such an approach has been successfully validated on humans and machines. Specifically, humans indeed perceived different levels of intensified emotions in these parametrically synthesized faces, and FER systems based on neural networks indeed showed improved sensitivities to intensities of different emotions when additionally trained on the synthesized faces. Overall, the proposed data augmentation method is not only simple and effective but also useful for building FER systems that recognize facial expressions of mixed emotions. © 2010-2012 IEEE.

关键词： Face recognition

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Balancing Memorization and Generalization in RNNs for High Performance Brain-Machine Interfaces 37

Balancing Memorization and Generalization in RNNs for High P...

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37th Conference on Neural Information Processing Systems, NeurIPS 2023

作者： Costello, Joseph T. Temmar, Hisham Cubillos, Luis H. Mender, Matthew J. Wallace, Dylan M. Willsey, Matthew S. Patil, Parag G. Chestek, Cynthia A. Department of Electrical and Computer Engineering Biomedical Engineering Robotics and Neurosurgery University of Michigan Ann ArborMI United States

ISBN: (纸本)9781713899921

Brain-machine interfaces (BMIs) can restore motor function to people with paralysis but are currently limited by the accuracy of real-time decoding algorithms. Recurrent neural networks (RNNs) using modern training techniques have shown promise in accurately predicting movements from neural signals but have yet to be rigorously evaluated against other decoding algorithms in a closed-loop setting. Here we compared RNNs to other neural network architectures in real-time, continuous decoding of finger movements using intracortical signals from nonhuman primates. Across one and two finger online tasks, LSTMs (a type of RNN) outperformed convolutional and transformer-based neural networks, averaging 18% higher throughput than the convolution network. On simplified tasks with a reduced movement set, RNN decoders were allowed to memorize movement patterns and matched able-bodied control. Performance gradually dropped as the number of distinct movements increased but did not go below fully continuous decoder performance. Finally, in a two-finger task where one degree-of-freedom had poor input signals, we recovered functional control using RNNs trained to act both like a movement classifier and continuous decoder. Our results suggest that RNNs can enable functional real-time BMI control by learning and generating accurate movement patterns. © 2023 Neural information processing systems foundation. All rights reserved.

关键词： Mammals

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Understanding URDF: A Survey Based on User Experience 19

Understanding URDF: A Survey Based on User Experience

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19th IEEE International Conference on Automation Science and engineering, CASE 2023

作者： Tola, Daniella Corke, Peter Aarhus University Department of Electrical and Computer Engineering Aarhus Denmark Centre for Robotics Qut Brisbane Australia

ISBN: (纸本)9798350320695

With the increasing complexity of robot systems, it is necessary to simulate them before deployment. To do this, a model of the robot's kinematics or dynamics is required. One of the most commonly used formats for modeling robots is the Unified Robot Description Format (URDF). The goal of this article is to understand how URDF is currently used, what challenges people face when working with it, and how the community sees the future of URDF. The outcome can potentially be used to guide future research. This article presents the results from a survey based on 510 anonymous responses from robotic developers of different backgrounds and levels of experience. We find that 96.8% of the participants have simulated robots before, and of them 95.5% have used URDF. We identify a number of challenges that complicate the use of URDF, such as the inability to model parallel linkages and closed-chain systems, no real standard, lack of documentation, and a limited number of dynamic parameters to model the robot. Future perspectives for URDF are also determined, where 53.5% believe URDF will be more commonly used in the future, 12.2% believe other standards or tools will make URDF obsolete, and 34.4% are not sure what the future of URDF will be. Most participants agree there is a need for better tools to ensure URDF's future use. © 2023 IEEE.

关键词： Robots

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Area-Oriented Resubstitution For Networks of Look-Up Tables

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IEEE Transactions on computer-Aided Design of Integrated Circuits and Systems 2025年第7期44卷 2571-2584页

作者： Costamagna, Andrea Calvino, Alessandro Tempia Mishchenko, Alan Micheli, Giovanni De Swiss Federal Institute of Technology Lausanne Integrated Systems Laboratory Lausanne1015 Switzerland University of California Department of Electrical Engineering and Computer Sciences Berkeley United States

This paper addresses the challenge of reducing the number of nodes in Look-Up Table (LUT) networks with two significant applications. First, Field-Programmable Gate Arrays (FPGAs) can be modelled as networks of LUTs, and minimizing the node count is imperative to meet resource constraints. Second, in area-oriented design space exploration for standard-cell designs, collapsing a circuit into a LUT network, restructuring it, and later remapping to the original representation helps escape local minima. Thus, the development of algorithms for optimizing and restructuring LUT networks holds considerable promise for area-oriented optimization. Substitution (also called resubstitution) is a powerful logic minimization method that can identify non-local logic dependencies and exploit them for logic minimization. State-of-the-art substitution algorithms for LUT networks rely heavily on SAT solving, limiting the number of optimization attempts and the size of the substitution sub-networks to one node mishchenko2011scalable. Conversely, our method relies on circuit simulation to increase the number of substitution candidates and enables substitutions with more than one node. The experimental results show that the proposed method identifies optimization opportunities overlooked by other methods, improving 11 out of 23 best-known results in the EPFL synthesis competition and yielding a 3.46% area reduction compared to the state-of-the-art. © 1982-2012 IEEE.

关键词： Field programmable gate arrays (FPGA)

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Multifaceted progress in high-field superconducting magnet mechanics

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Acta Mechanica Sinica 2024年第4期40卷 1-3页

作者： Xingzhe Wang Seungyong Hahn Key Laboratory of Mechanics on Western Disaster and Environment Ministry of EducationCollege of Civil Engineering and MechanicsLanzhou UniversityLanzhou 730000China Department of Electrical and Computer Engineering Seoul National UniversitySeoul 08826Republic of Korea

High-field superconducting magnets are poised to revolutionize technologies,including particle accelerators,magnetic resonance imaging(MRI)machines,and fusion *** stand at the frontier of superconductor ***_(3)Sn wires,which operate at cold temperatures,along with rare-earth barium copper oxide(REBCO)coated conductors that include rare earth elements like Y,Gd,and Dy,are gaining *** high electrical efficiency in strong magnetic fields makes them particularly attractive for such advanced applications.

关键词： Nb_(3)Sn field earth

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Quantitative Analysis of Ankle Spasticity Through Electromyography Signal

Quantitative Analysis of Ankle Spasticity Through Electromyo...

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2024 Medical Technologies Congress, TIPTEKNO 2024

作者： Gurluk, Ayse Bilal, Hafiz Muhammad Hocaoglu, Elif Living Robotics Laboratory Graduate School of Health Sciences Physiotherapy and Rehabilitation Program Istanbul Medipol University Istanbul Turkey Living Robotics Laboratory Graduate School of Engineering and Natural Sciences Electrical-Electronics Engineering and Cyber-Systems Program Istanbul Medipol University Istanbul Turkey Living Robotics Laboratory Department of Electrical and Electronics Engineering Istanbul Medipol University Istanbul Turkey

ISBN: (纸本)9798331529819

This study presents a more accurate evaluation method for assessing ankle spasticity compared to conventional goniometric techniques by utilizing measurements obtained from Inertial Measurement Units (IMU) and surface electromyography (sEMG) devices. Integrating IMU and EMG sensors provides substantial benefits for accurately determining the range of motion (ROM) associated with spasticity during targeted movements. In this study, the proposed method provides precise measurement and an objective evaluation of onset time detection of antagonistic muscle co-contraction, and accordingly the ROM of the actuated joint. Moreover, the implementation of cost-effective wearable sensors enables the monitoring of muscle spasticity in clinical environments and can be particularly valuable in regions with limited access to experienced therapists, providing a more efficient approach to tracking spasticity levels. © 2024 IEEE.

关键词： Electromyography

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A Class Alignment Multi-Source Domain Adaptation for Partial Discharge Condition Assessment With Unknown Faults in GIS

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IEEE Internet of Things Journal 2025年第12期12卷 19955-19971页

作者： Wang, Yanxin Yan, Jing Yang, Zhou Zhang, Wenjie Wang, Jianhua Geng, Yingsan Srinivasan, Dipti Xi'an Jiaotong University State Key Laboratory of Electrical Insulation and Power Equipment Department of Electrical Engineering Xi'an710049 China National University of Singapore Energy Management and Microgrid Laboratory Singapore117581 Singapore Xi'an Jiaotong University Department of Computer Science Xi'an710049 China

Recently, domain adaptation has emerged as a powerful technique for on-site partial discharge (PD) condition assessment in gas-insulated switchgear (GIS). However, most existing methods face three major challenges: 1) Relying on a single source domain for model development poses difficulties in effectively utilizing source domain samples with distribution differences. 2) Limited condition assessment for unknown fault samples on-site, which faces distributional differences between multiple source domains. 3) Handling only a single task, which makes it challenging to generalize to multiple tasks simultaneously. To address these concerns, we propose a class alignment multi-source domain adaptation network (CLMSDAN) for GIS PD condition assessment with unknown faults. First, a diversity feature extractor is developed to extract diverse features while addressing the negative transfer issue caused by knowledge differences by mining both inter-domain and intra-domain features, thus enabling the transfer of rich knowledge at multiple levels. Second, a novel multi-source domain adaptation approach is employed from multiple perspectives to align distribution and distinguish between shared and unknown classes. Finally, a multi-classifier complementary strategy is introduced to recognize unknown faults, which automatically filters out source domain irrelevant class samples while distinguishing the contributions of different source domains to the target task. Experimental results show that CLMSDAN achieves 94.86% accuracy in diagnosis and 93.38% in severity assessment, outperforming baseline methods by over 10% in both tasks. This highlights its superior generalization and robustness across varying conditions and noise levels. © 2014 IEEE.

关键词： Electric switchgear

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