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5th IEEE International Conference on Advanced Information and Communication Technologies, AICT 2023

作者： Pariy, Vladislav Lipianina-Honcharenko, Khrystyna Brukhanskyi, Ruslan Sachenko, Anatoliy Tkachyk, Fedir Lendiuk, Dmytro West Ukrainian National University Department for Information Computer Systems and Control Ternopil Ukraine West Ukrainian National University Department of Business Analytics and Innovative Engineering Ternopil Ukraine Research Institute for Intelligent Computer Systems West Ukrainian National University Ternopil Ukraine Kazimierz Pulaski University of Technology and Humanities in Radom Department of Informatics and Teleinformatics Radom Poland West Ukrainian National University Department of Taxes and Fiscal Policy Ternopil Ukraine

ISBN: (纸本)9798350372571

This article is devoted to the development of Intelligent Verbal Interaction Methods with Non-Player Characters in Metaverse Applications. The creation of a character model using MetaHuman Creator and the implementation of dialogue animation are considered. The construction of answers based on text analysis and their submission to the chat window is described. The system has been tested and found to be stable and have a satisfactory response time of approximately 2 seconds. The results show the successful implementation of methods of verbal interaction with non-game characters in metaverse, which can be useful for further research and development in this area. © 2023 IEEE.

关键词： Animation

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Toward Dexterous Hand Functional Movement: Wearable Hybrid Soft Exoglove-FES Study

Toward Dexterous Hand Functional Movement: Wearable Hybrid S...

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IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob)

作者： Hossein Kavianirad Francesco Missiroli Satoshi Endo Lorenzo Masia Sandra Hirche Chair of Information-oriented Control School of Computation Information and Technology Technical University of Munich Munich Germany Assistive Robotics and Interactive ExoSuits (ARIES) Lab Institute for Computer Engineering (ZITI) Heidelberg University Heidelberg Germany

ISBN: (数字)9798350386523

ISBN: (纸本)9798350386530

Functional electrical stimulation (FES), a lightweight wearable technology leveraging active muscle recruitment, can assist functional movement for rehabilitation and various activities of daily living. However, the intricate and user-specific nature of the neuromuscular response to FES, such as the induction of muscular fatigue and discomfort, can lead to incomplete or imprecise functional movements. On the other hand, soft exoskeleton gloves, another form of lightweight wearable technology for hand movement assistance, guide movement externally with higher precision. In this research, therefore, we present a novel hybrid system that combines a soft exoskeleton glove and FES technology. Such an augmented hybrid system could reinforce the advantages of active muscle recruitment as a primary source of actuation with external actuation of the exoskeleton compensating for the limitations of FES in torque generation. Our objective is to investigate the performance of this hybrid system compared to the standalone FES system through experimental evaluation.

关键词： Torque Neuromuscular Exoskeletons Biomechatronics Fatigue Iron Hybrid power systems Neuromuscular stimulation Robots Recruitment

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A Self-Organization Reconstruction Method of Esn Reservoir Structure Based on Reinforcement Learning

SSRN

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SSRN 2023年

作者： Guo, Wei Yao, Huan Zhu, YingQin Zhang, ZhaoZhao Institute of Communication and Information Engineering Xi’an University of Science and Technology Xi’an710054 China Departmento de Automatico Control CINVESTAV-IPN Mexico CityD.F.07360 Mexico Institute of Computer Science and Technology Xi’an University of Science and Technology Xi’an710054 China

The dynamic reservoir of the randomly generated Echo State Network (ESN) contains numerous redundant neurons, resulting in collinearity in the highdimensional state space matrix. This collinearity impacts the prediction performance of the network. In order to address this issue, this paper introduces a self-organizing ESN structure optimization model that is based on reinforcement learning, called SR-ESN. The SR-ESN model employs pruning methods to reconstruct the reservoir using contribution and decision mechanisms. To mitigate potential instability caused by high coupling among neurons in a single reservoir, the concept of ensemble learning is applied to create multiple initial reservoir pools, thereby enhancing screening diversity. Simultaneously, the model utilizes reinforcement learning’s decision mechanism to identify effective neurons. Neurons with low contribution are pruned, while those with high contribution are retained for self-organizing reconstruction. This optimization of the network structure enhances its prediction performance. Based on both artificial and real datasets, the proposed SR-ESN model demonstrates superior prediction performance with minimal structural complexity compared to other prediction models. © 2023, The Authors. All rights reserved.

关键词： Reinforcement learning

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Broadband usage for rural communities in the North Island of Aotearoa New Zealand

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Intelligent and Converged Networks 2022年第3期3卷 244-259页

作者： Ming Xiang William Liu Edmund Lai Jairo Gutierrez Luca Chiaraviglio Jinsong Wu Control Science and Engineering South China University of TechnologyGuangzhou 510300Chinaand also with the South China Sea Institute of Planning and Environmental ResearchMinistry of Natural ResourcesGuangzhou 510300China Department of Computer Science and Software Engineering School of EngineeringComputer and Mathematical SciencesAuckland University of TechnologyAuckland 1010New Zealand Department of Electronic Engineering University of Rome“Tor Vergata”Rome 00133Italy Consorzio Nazionale Interuniversitario per le Telecomunicazioni(CNIT) Parma 43124Italy Department of Electrical Engineering Universidad de ChileSantiago 92101Chile

New Zealand government’s Rural Broadband Initiative(RBI)aims to invest 400 million New Zealand dollar to provide 99%of New Zealanders with access to 50 Mbps peak broadband speed,with the remaining 1%at 10 Mbps by *** 2017,stage 1 of the RBI has been completed,and research is needed to find out the level of usage,proficiency,and productivity achieved by ***,a survey was carried out to learn whether the rural residents and their communities are making good use of the new fast broadband *** survey collected data from 217 rural residents from North Island,and the results indicate that about half of the interview respondents are satisfied with the new broadband speed and the reliability which is offered by RBI stage ***,there is about 28%of the respondents disagreed with *** majority of the Internet uses for rural residents are information searching,reading news,online entertainment,and online *** that,only a small proportion of respondents know how to utilize the Internet in their work/business and benefit/profit from it,e.g.,using cloud technology capabilities and online marketing campaigns,*** ***,we argue that information and communications technologies(ICT)adoption is not only the availability of the infrastructure but also the beneficial outcomes of Internet *** other words,Internet skills in-depth training and education need to catch up with the infrastructure deployment,which is useful to fuel the digital productivity and inclusion for booming rural *** survey data-driven findings presented in this paper could serve as a reference to inform government policymakers and those who wish to create,invest,and take actions to speed up the economic and social growth of rural communities in Aotearoa New Zealand through the Internet while shifting from the Internet speed and traffic volume-driven to a more effective Internet connectivity and value-added driven rural economy.

关键词： data driven approach data-supported decision and policy making digital exclusion information and communications technologies(ICT)adoption effective connectivity rural broadband usage rural economic development

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Learning Communities from Equilibria of Nonlinear Opinion Dynamics

Learning Communities from Equilibria of Nonlinear Opinion Dy...

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IEEE Conference on Decision and control

作者： Yu Xing Anastasia Bizyaeva Karl H. Johansson Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology and with Digital Futures Stockholm Sweden Sibley School of Mechanical and Aerospace Engineering Cornell University Ithaca NY USA

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

This paper studies community detection for a nonlinear opinion dynamics model from its equilibria. It is assumed that the underlying network is generated from a stochastic block model with two communities, where agents are assigned with community labels and edges are added independently based on these labels. Agents update their opinions following a nonlinear rule that incorporates saturation effects on interactions. It is shown that clustering based on a single equilibrium can detect most community labels (i.e., achieving almost exact recovery), if the two communities differ in size and link probabilities. When the two communities are identical in size and link probabilities, and the intercommunity connections are denser than intra-community ones, the algorithm can achieve almost exact recovery under negative influence weights but fails under positive influence weights. Utilizing fixed point equations and spectral methods, we also propose a detection algorithm based on multiple equilibria, which can detect communities with positive influence weights. Numerical experiments demonstrate the performance of the proposed algorithms.

关键词： Accuracy Heuristic algorithms Image edge detection Stochastic processes Clustering algorithms Mathematical models Numerical models Detection algorithms

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Locate n' Rotate: Two-stage Openable Part Detection with Foundation Model Priors

arXiv

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arXiv 2024年

作者： Li, Siqi Chen, Xiaoxue Cheng, Haoyu Zhou, Guyue Zhao, Hao Tian, Guanzhong Ningbo innovation Center Zhejiang University China College of Control Science and Engineering Zhejiang University China Institute for AI Industry Research Tsinghua University China Department of Computer Science and Technology Tsinghua University China

Detecting the openable parts of articulated objects is crucial for downstream applications in intelligent robotics, such as pulling a drawer. This task poses a multitasking challenge due to the necessity of understanding object categories and motion. Most existing methods are either category-specific or trained on specific datasets, lacking generalization to unseen environments and objects. In this paper, we propose a Transformer-based Openable Part Detection (OPD) framework named Multi-feature Openable Part Detection (MOPD) that incorporates perceptual grouping and geometric priors, outperforming previous methods in performance. In the first stage of the framework, we introduce a perceptual grouping feature model that provides perceptual grouping feature priors for openable part detection, enhancing detection results through a cross-attention mechanism. In the second stage, a geometric understanding feature model offers geometric feature priors for predicting motion parameters. Compared to existing methods, our proposed approach shows better performance in both detection and motion parameter prediction. Codes and models are publicly available at https://***/lisiqizju/MOPD. © 2024, CC BY.

关键词： Intelligent robots

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A Real-time Cutting Model Based on Finite Element and Order Reduction

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computer Systems Science & Engineering 2022年第10期43卷 1-15页

作者： Xiaorui Zhang Wenzheng Zhang Wei Sun Hailun Wu Aiguo Song Sunil Kumar Jha Wuxi Research Institute Nanjing University of Information Science&TechnologyWuxi214100China Engineering Research Center of Digital Forensics Ministry of EducationJiangsu Engineering Center of Network MonitoringSchool of Computer and SoftwareNanjing University of Information Science&TechnologyNanjing210044China School of Automation Nanjing University of Information Science&TechnologyNanjing210044China State Key Laboratory of Bioelectronics Jiangsu Key Lab of Remote Measurement and ControlSchool of Instrument Science and EngineeringSoutheast UniversityNanjing210096China IT Fundamentals and Education Technologies Applications University of Information Technology and Management in RzeszowRzeszow Voivodeship100031Poland

Telemedicine plays an important role in Corona Virus Disease 2019(COVID-19).The virtual surgery simulation system,as a key component in telemedicine,requires to compute in ***,this paper proposes a realtime cutting model based on finite element and order reduction method,which improves the computational speed and ensure the real-time *** proposed model uses the finite element model to construct a deformation model of the virtual ***,a model order reduction method combining proper orthogonal decomposition and Galerkin projection is employed to reduce the amount of deformation *** addition,the cutting path is formed according to the collision intersection position of the surgical instrument and the lesion area of the virtual ***,the Bezier curve is adopted to draw the incision outline after the virtual lung has been ***,the simulation system is set up on the PHANTOM OMNI force haptic feedback device to realize the cutting simulation of the virtual *** results show that the proposed model can enhance the real-time performance of telemedicine,reduce the complexity of the cutting simulation and make the incision smoother and more natural.

关键词： Virtual surgery cutting model finite element model model order reduction Bezier curve

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A Unified Planning Model for Microgrids Considering Typical Scenarios and Operational Simulations

A Unified Planning Model for Microgrids Considering Typical ...

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Power and Electrical technology Conference (APET), Asia

作者： Mengmeng Su Jun Peng Yong Zhang Min Li Zhenwei Li Mingfei Ban North China Branch of State GRID Corporation of China Beijing China School of Electrical Engineering and Automation Harbin Institute of Technology Harbin China College of Computer and Control Engineering Northeast Forestry University Harbin China

ISBN: (数字)9798350367690

ISBN: (纸本)9798350367706

The structure of microgrids and the models considered have a significant impact on the planning and operational outcomes of micro grids. Additionally, micro grids encompass various models of primary equipment, including wind, solar, diesel, and storage, while the demand-side response mechanisms are continually being refined. This necessitates the construction of diverse load types, thereby increasing the complexity of micro grid planning and highlighting the need for further research into microgrid planning models. This paper presents various typical mathematical models for microgrids, employs spectral clustering algorithms to obtain representative scenarios, and constructs a unified planning model for microgrids. Furthermore, it elucidates the model adjustment methods under different planning objectives and conducts case analyses of microgrid planning issues.

关键词： Analytical models Costs Asia Clustering algorithms Microgrids Mathematical models Planning Complexity theory Optimization Load modeling

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Distributionally Robust control for Chance-Constrained Signal Temporal Logic Specifications

arXiv

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arXiv 2024年

作者： Kordabad, Arash Bahari Vlahakis, Eleftherios E. Lindemann, Lars Dimarogonas, Dimos V. Soudjani, Sadegh Max Planck Institute for Software Systems Kaiserslautern Germany Division of Decision and Control Systems KTH Royal Institute of Technology Stockholm Sweden Thomas Lord Department of Computer Science Viterbi School of Engineering University of Southern California Los Angeles United States

We consider distributionally robust optimal control of stochastic linear systems under signal temporal logic (STL) chance constraints when the disturbance distribution is unknown. By assuming that the underlying predicate functions are Lipschitz continuous and the noise realizations are drawn from a distribution having a concentration of measure property, we first formulate the underlying chance-constrained control problem as stochastic programming with constraints on expectations and propose a solution using a distributionally robust approach based on the Wasserstein metric. We show that by choosing a proper Wasserstein radius, the original chance-constrained optimization can be satisfied with a user-defined confidence level. A numerical example illustrates the efficacy of the method. © 2024, CC BY-NC-ND.

关键词： Stochastic systems

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Improved analysis of randomized SVD for top-eigenvector approximation

arXiv

引用

arXiv 2022年

作者： Tzeng, Ruo-Chun Wang, Po-An Adriaens, Florian Gionis, Aristides Lu, Chi-Jen Division of Theoretical Computer Science KTH Royal Institute of Technology Sweden Division of Decision and Control Systems KTH Royal Institute of Technology Sweden Institute of Information Science Academia Sinica Taiwan

Computing the top eigenvectors of a matrix is a problem of fundamental interest to various fields. While the majority of the literature has focused on analyzing the reconstruction error of low-rank matrices associated with the retrieved eigenvectors, in many applications one is interested in finding one vector with high Rayleigh quotient. In this paper we study the problem of approximating the top-eigenvector. Given a symmetric matrix A with largest eigenvalue λ1, our goal is to find a vector û that approximates the leading eigenvector u1 with high accuracy, as measured by the ratio R(û) = λ−11ûTAû/ûTû. We present a novel analysis of the randomized SVD algorithm of Halko et al. (2011b) and derive tight bounds in many cases of interest. Notably, this is the first work that provides non-trivial bounds for approximating the ratio R(û) using randomized SVD with any number of iterations. Our theoretical analysis is complemented with a thorough experimental study that confirms the efficiency and accuracy of the method. © 2022, CC BY.

关键词： Eigenvalues and eigenfunctions

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