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A population randomization-based multi-objective genetic algorithm for gesture adaptation in human-robot interaction

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Science China(Information Sciences) 2021年第1期64卷 188-200页

作者： Luefeng CHEN Wanjuan SU Min LI Min WU Witold PEDRYCZ Kaoru HIROTA School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Department of Electrical and Computer Engineering University of Alberta Tokyo Institute of Technology

In recent years, vision-based gesture adaptation has attracted great attention from many experts in the field of human-robot interaction, and many methods have been proposed and successfully applied, such as particle swarm optimization and genetic algorithm. However, the reduction of the error and energy consumption of a robot while paying attention to more subtle attitude changes is very important and *** view of these problems, we propose a population randomization-based multi-objective genetic *** gesture signal is processed with a slight change by imitating the biological evolution mechanisms. In the proposed algorithm, a random out-of-order matrix is added in the process of population evolution synthesis to prevent the premature grouping convergence of the new population. The weights of the objective function and the elite retention strategy are adopted, and the most adaptable individuals in each generation are inherited directly in the next generation without any recombination or mutation. To verify the effectiveness of the algorithm, preliminary application experiments are performed on the gesture adaptation of a robotic arm. The results are compared with the original signal, and the comparison shows that by using the proposed method, the energy consumption is reduced, and the end error is decreased to less than 3 mm while ensuring the tracking effect of the robotic arm. These obtained results meet the communication requirements for human-robot interactions such as handshakes. Moreover, the proposed method has better performance, uses less energy, and has a smaller tracking error than the particle swarm optimization, the single-objective genetic algorithm, and the traditional multi-objective genetic algorithm. A preliminary application experiment indicates that the robotic arm can adapt to human gestures in real time.

关键词： multi-objective genetic algorithm gesture adaptation human-robot interaction

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GrabDAE: An Innovative Framework for Unsupervised Domain Adaptation Utilizing Grab-Mask and Denoise Auto-Encoder

arXiv

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arXiv 2024年

作者： Chen, Junzhou Wen, Xuan Zhang, Ronghui Ren, Bingtao Wu, Di Xu, Zhigang Wang, Danwei The Guangdong Provincial Key Laboratory of Intelligent Transport System School of Intelligent Systems Engineering Sun Yat-sen University Guangzhou510275 China The School of Transportation Science and Engineering Beihang University State Key Lab of Intelligent Transportation System Beijing100191 China The School of Computer Science and Engineering Sun Yat-sen University Guangzhou510006 China The Guangdong Key Laboratory of Big Data Analysis and Processing Guangdong510006 China The School of Information Engineering Chang’an University Shaanxi Xi’an710064 China The School of Electrical and Electronic Engineering Nanyang Technological University Singapore639798 Singapore

Unsupervised Domain Adaptation (UDA) aims to adapt a model trained on a labeled source domain to an unlabeled target domain by addressing the domain shift. Existing Unsupervised Domain Adaptation (UDA) methods often fall short in fully leveraging contextual information from the target domain, leading to suboptimal decision boundary separation during source and target domain alignment. To address this, we introduce GrabDAE, an innovative UDA framework designed to tackle domain shift in visual classification tasks. GrabDAE incorporates two key innovations: the Grab-Mask module, which blurs background information in target domain images, enabling the model to focus on essential, domain-relevant features through contrastive learning;and the Denoising Auto-Encoder (DAE), which enhances feature alignment by reconstructing features and filtering noise, ensuring a more robust adaptation to the target domain. These components empower GrabDAE to effectively handle unlabeled target domain data, significantly improving both classification accuracy and robustness. Extensive experiments on benchmark datasets, including VisDA-2017, OfficeHome, and Office31, demonstrate that GrabDAE consistently surpasses state-of-the-art UDA methods, setting new performance benchmarks. By tackling UDA’s critical challenges with its novel feature masking and denoising approach, GrabDAE offers both significant theoretical and practical advancements in domain adaptation. © 2024, CC BY-NC-SA.

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Performance Analysis of MIMO-HARQ Assisted V2V Communications With Keyhole Effect

arXiv

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arXiv 2022年

作者： Zhang, Huan Liao, Zhengtao Shi, Zheng Yang, Guanghua Dou, Qingping Ma, Shaodan The State Key Laboratory of Internet of Things for Smart City The Department of Electrical and Computer Engineering University of Macau 999078 China The School of Intelligent Systems Science and Engineering Jinan University Zhuhai519070 China

Vehicle-to-vehicle (V2V) communications under dense urban environments usually experience severe keyhole fading effect especially for multi-input multi-output (MIMO) channels, which degrades the capacity and outage performance due to the rank deficiency. To avoid these, the integration of MIMO and hybrid automatic repeat request (HARQ) is proposed to assist V2V communications in this paper. By using the methods of integral transforms, the outage probabilities are derived in closed-form for different HARQ-assisted schemes, including Type I-HARQ, HARQ with chase combining (HARQ-CC), and HARQ with incremental redundancy (HARQ-IR). With the results, meaningful insights are gained by conducting the asymptotic outage analysis. Specifically, it is revealed that full time diversity order can be achieved, while full spatial diversity order is unreachable as compared to MIMO-HARQ systems without keyhole effect. Moreover, we prove that the asymptotic outage probability is a monotonically increasing and convex function of the transmission rate. More importantly, although HARQ-IR performs better than HARQ-CC owing to its higher coding complexity, this advantage becomes negligible in the large-scale array regime. Finally, the numerical results are verified by Monte-Carlo simulations along with some in-depth discussions. © 2022, CC BY.

关键词： Functions

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Effective Two-Stage Double Auction for Dynamic Resource Trading in Edge Networks via Overbooking

arXiv

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arXiv 2025年

作者： Wu, Sicheng Liwang, Minghui Wang, Deqing Wang, Xianbin Wu, Chao Tang, Junyi Li, Li Jiao, Zhenzhen The School of Informatics Xiamen University Fujian China The Department of Control Science and Engineering The National Key Laboratory of Autonomous Intelligent Unmanned Systems Tongji University Shanghai China Frontiers Science Center for Intelligent Autonomous Systems Ministry of Education Tongji University Shanghai China The Department of Electrical and Computer Engineering Western University ON Canada The School of Public Affairs Zhejiang University Hangzhou310027 China School of Information Science and Engineering Lanzhou University Lanzhou China The iF-Labs Beijing Teleinfo Technology Co. Ltd. CAICT China

To facilitate responsive and cost-effective computing resource scheduling and service delivery over edge-assisted mobile networks, this paper investigates a novel two-stage double auction methodology via utilizing an interesting idea of resource overbooking to overcome dynamic and uncertain nature from edge servers (sellers) and demand from mobile devices (as buyers). The proposed auction integrates multiple essential factors such as social welfare maximization and decision-making latency (e.g., the time for determining winning seller-buyer pairs) reduction, by introducing a stagewise strategy: an overbooking-driven pre-double auction (OPDAuction) for determining long-term cooperations between sellers and buyers before practical resource transactions as Stage I, and a real-time backup double auction (RBDAuction) for handling residual resource demands during actual transactions. In particular, by applying a proper overbooking rate, OPDAuction helps with facilitating trading contracts between appropriate sellers and buyers as guidance for future transactions, by allowing the booked resources to exceed supply. Then, since pre-auctions may cause risks, our RBDAuction adjusts to real-time market changes, further enhancing the overall social welfare. More importantly, we offer an interesting view to show that our proposed two-stage auction can support significant design properties such as truthfulness, individual rationality, and budget balance. Through extensive experiments, we demonstrate good performance in social welfare, time efficiency, and computational scalability, outstripping conventional methods in dynamic edge computing settings. Copyright © 2025, The Authors. All rights reserved.

关键词： Budget control

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Short - Term Prediction of Coke Pushing Current Peak Based on Improved ARIMA Model

Short - Term Prediction of Coke Pushing Current Peak Based o...

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Industrial Cyber-Physical systems (ICPS)

作者： Haiyang Wei Luefeng Chen Jie Hu Yi Ren Min Wu Witold Pedrycz Kaoru Hirota School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China Department of Electrical and Computer Engineering University of Alberta Edmonton Canada Tokyo Institute of Technology Yokohama Japan

Coke pushing current is an indicator to evaluate the difficulty of coke pushing operation. The higher coke pushing current is, the greater coke pushing resistance is, and the more difficult coke is to push out. Accurate prediction of current peak during future coke pushing operation can provide more time for production personnel to adjust production status and avoid difficult coke pushing in carbonization chamber. In this paper, a combination prediction model based on VMD (Variational Mode Decomposition) and improved ARIMA (Autoregressive Integrated Moving Average) models is proposed. Firstly, VMD algorithm is used to decompose time series of coke pushing current peak, de-noising data, and extracting main information of time series. Then, ARIMA model is used to predict mean change of linear elasticity and GARCH (Generalized Autore-gressive Conditional Heteroskedasticity) model is introduced to predict ARIMA model residual and improve heteroscedasticity of nonlinear part of time series, and then ARIMA-GARCH model is established. Finally, predicted value is obtained by the sum of each component prediction. The experimental results show that the proposed prediction model has a high prediction accuracy in the short-term prediction of coke pushing current peak. The scheme is applied to actual coking production to guide production of coke.

关键词： Resistance Ovens Time series analysis Noise reduction Production Predictive models Prediction algorithms

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IRS Channel Estimation in Cell-free MIMO Network: A Coalition Formation Guided Federated Learning Approach

IRS Channel Estimation in Cell-free MIMO Network: A Coalitio...

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2025 IEEE Wireless Communications and Networking Conference, WCNC 2025

作者： Liu, Haoxuan Qi, Nan Li, Xiaojie Boulogeorgos, Alexandros A. A. Tsiftsis, Theodoros A. Xiao, Ming Röning, Juha Nanjing University of Aeronautics and Astronautics Nanjing China Southeast University National Mobile Communications Research Laboratory Nanjing210096 China University of Western Macedonia Department of Electrical and Computer Engineering Kozani50100 Greece University of Thessaly Department of Informatics and Telecommunications Lamia35100 Greece University of Nottingham Ningbo China Department of Electrical and Electronic Engineering Ningbo315100 China School of Electrical Engineering KTH Royal Institute of Technology Stockholm Sweden University of Oulu Biomimetics and Intelligent Systems Group Finland

ISBN: (纸本)9798350368369

The downlink channel estimation is currently a critical bottleneck for IRS-assisted cell-free multiple input multiple output communication. Conventionally, most studies have employed deep learning methods to estimate the high-dimensional, complex cascaded channels generated by IRS, necessitating data collection from all users for centralized model training, which results in excessively large overheads, and data privacy problems. To tackle this challenge, a federated learning (FL)-based channel estimation framework incorporates coalition formation to guide the formation of FL user groups. We propose a coalition formation-enabled federated learning framework for channel estimation, utilizing a deep reinforcement learning (DRL) approach to intelligently group users into multiple coalitions, thereby improving channel estimation accuracy. Moreover, considering that nodes with similar distances to the base station and similar received signal power have a strong likelihood that they experience similar channel fading, we designed a transfer learning method that incorporates both received reference signal power and distance similarity metrics. The transfer learning technique is designed to accelerate the convergence of DRL-federated learning process. Simulations reveal that the proposed algorithms significantly reduce communication overhead for local users and improve data privacy while maintaining commendable channel estimation accuracy. © 2025 IEEE.

关键词： Deep reinforcement learning

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Recent progress on structural coloration

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Photonics Insights 2024年第2期3卷 1-30页

作者： Yingjie Li Jingtian Hu Yixuan Zeng Qinghai Song Cheng-Wei Qiu Shumin Xiao Ministry of Industry and Information Technology Key Lab of Micro-Nano Optoelectronic Information System Guangdong Provincial Key Laboratory of Semiconductor Optoelectronic Materials and Intelligent Photonic SystemsHarbin Institute of TechnologyShenzhenChina Pengcheng Laboratory ShenzhenChina Department of Electrical and Computer Engineering National University of SingaporeSingaporeSingapore Collaborative Innovation Center of Extreme Optics Shanxi UniversityTaiyuanChina

Structural coloration generates colors by the interaction between incident light and micro-or nanoscale *** has received tremendous interest for decades,due to advantages including robustness against bleaching and environmentally friendly properties(compared with conventional pigments and dyes).As a versatile coloration strategy,the tuning of structural colors based on micro-and nanoscale photonic structures has been extensively explored and can enable a broad range of applications including displays,anti-counterfeiting,and ***,scholarly research on structural colors has had limited impact on commercial products because of their disadvantages in cost,scalability,and *** this review,we analyze the key challenges and opportunities in the development of structural *** first summarize the fundamental mechanisms and design strategies for structural colors while reviewing the recent progress in realizing dynamic structural *** promising potential applications including optical information processing and displays are also discussed while elucidating the most prominent challenges that prevent them from translating into technologies on the ***,we address the new opportunities that are underexplored by the structural coloration community but can be achieved through multidisciplinary research within the emerging research areas.

关键词： structural coloration metasurfaces nanophotonics

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Outage Performance and Optimal Design of MIMO-NOMA Enhanced Small Cell Networks with Imperfect Channel-State Information

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China Communications 2021年第10期18卷 107-128页

作者： Zheng Shi Hong Wang Yaru Fu Guanghua Yang Shaodan Ma Xinrong Ye School of Intelligent Systems Science and Engineering Jinan UniversityZhuhai 519070China State Key Laboratory of Internet of Things for Smart City and the Department of Electrical and Computer Engineering University of MacaoMacao 999078China School of Communication and Information Engineering Nanjing University of Posts and TelecommunicationsNanjing 210003China School of Science and Technology Hong Kong Metropolitan UniversityHong Kong SARChina School of Physics and Electronic Information Anhui Normal UniversityWuhu 241002China

This paper focuses on boosting the performance of small cell networks(SCNs)by integrating multiple-input multiple-output(MIMO)and nonorthogonal multiple access(NOMA)in consideration of imperfect channel-state information(CSI).The estimation error and the spatial randomness of base stations(BSs)are characterized by using Kronecker model and Poisson point process(PPP),*** outage probabilities of MIMO-NOMA enhanced SCNs are first derived in closed-form by taking into account two grouping policies,including random grouping and distance-based *** is revealed that the average outage probabilities are irrelevant to the intensity of BSs in the interference-limited regime,while the outage performance deteriorates if the intensity is sufficiently ***,as the channel uncertainty lessens,the asymptotic analyses manifest that the target rates must be restricted up to a bound to achieve an arbitrarily low outage probability in the absence of the inter-cell ***,highly correlated estimation error ameliorates the outage performance under a low quality of CSI,otherwise it behaves ***,the goodput is maximized by choosing appropriate precoding matrix,receiver filters and transmission *** the end,the numerical results verify our analysis and corroborate the superiority of our proposed algorithm.

关键词： imperfect channel-state information(CSI) multiple-input multiple-output(MIMO) non-orthogonal multiple access(NOMA) small cell networks(SCNs)

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Energy Minimization for Wireless Powered Data Offloading in IRS-assisted MEC for Vehicular Networks

Energy Minimization for Wireless Powered Data Offloading in ...

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International Wireless Communications and Mobile Computing Conference, IWCMC

作者： Yuanzheng Tan Yusi Long Songhan Zhao Shimin Gong Dinh Thai Hoang Dusit Niyato School of Intelligent Systems Engineering Sun Yat-sen University China School of Electrical Engineering Yanshan University China Guangdong Provincial Key Laboratory of Fire Science and Intelligent Emergency Technology China School of Electrical and Data Engineering University of Technology Sydney Australia School of Computer Science and Engineering Nanyang Technological University Singapore

In this paper, we consider an IRS-assisted and wireless-powered mobile edge computing (MEC) system that allows both edge users and the IRS to harvest energy from the hybrid access point (HAP), co-located with the MEC server. Each edge user uses the harvested energy to offload its data to the MEC server. The IRS not only assists downlink energy transfer to the edge users, but also improves the users' uplink offloading rates. To minimize the overall energy consumption, we jointly optimize the users' offloading decisions, the HAP's active beamforming, as well as the IRS's energy harvesting and passive beamforming strategies. The energy minimization problem is intractable due to complicated couplings in both the objective function and constraints. We decompose this problem into the downlink energy transfer and the uplink data offloading phases. The uplink phase can be efficiently optimized by the conventional semi-definite relaxation (SDR) method, while the downlink phase depends on the alternating optimization between the users' offloading decisions and the joint active and passive beamforming strategies. Numerical results demonstrate that the proposed offloading scheme can significantly reduce the HAP's energy consumption compared with typical benchmarks.

关键词： Wireless communication Energy consumption Array signal processing Energy exchange Minimization Downlink Servers

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Arbitrage equilibria in active matter systems

arXiv

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arXiv 2024年

作者： Venkatasubramanian, Venkat Sivaram, Abhishek Sanjeevrajan, N. Sankar, Arun Complex Resilient Intelligent Systems Laboratory Department of Chemical Engineering Columbia University New YorkNY10027 United States Department of Chemical and Biochemical Engineering Technical University of Denmark Kongens Lyngby2800 Denmark Department of Materials Engineering Indian Institute of Technology-Madras Chennai600036 India School of Electrical Computer and Energy Engineering Arizona State University TempeAZ United States

The motility-induced phase separation (MIPS) phenomenon in active matter has been of great interest for the past decade or so. A central conceptual puzzle is that this behavior, which is generally characterized as a nonequilibrium phenomenon, can yet be explained using simple equilibrium models of thermodynamics. Here, we address this problem using a new theory, statistical teleodynamics, which is a conceptual synthesis of game theory and statistical mechanics. In this framework, active agents compete in their pursuit of maximum effective utility, and this self-organizing dynamics results in an arbitrage equilibrium in which all agents have the same effective utility. We show that MIPS is an example of arbitrage equilibrium and that it is mathematically equivalent to other phase-separation phenomena in entirely different domains, such as sociology and economics. As examples, we present the behavior of Janus particles in a potential trap and the effect of chemotaxis on MIPS. © 2024, CC BY.

关键词： Phase separation

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