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arXiv 2021年

作者： Yi, Xinlei Li, Xiuxian Yang, Tao Xie, Lihua Chai, Tianyou Johansson, Karl H. The Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm10044 Sweden The Digital Futures Stockholm10044 Sweden The Department of Control Science and Engineering College of Electronics and Information Engineering The Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai China The State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China School of Electrical and Electronic Engineering Nanyang Technological University 50 Nanyang Avenue Singapore639798 Singapore

This paper considers the distributed online convex optimization problem with time-varying constraints over a network of agents. This is a sequential decision making problem with two sequences of arbitrarily varying convex loss and constraint functions. At each round, each agent selects a decision from the decision set, and then only a portion of the loss function and a coordinate block of the constraint function at this round are privately revealed to this agent. The goal of the network is to minimize the network-wide loss accumulated over time. Two distributed online algorithms with full-information and bandit feedback are proposed. Both dynamic and static network regret bounds are analyzed for the proposed algorithms, and network cumulative constraint violation is used to measure constraint violation, which excludes the situation that strictly feasible constraints can compensate the effects of violated constraints. In particular, we show that the proposed algorithms achieve O(T max{κ,1-κ}) static network regret and O(T 1-κ/2) network cumulative constraint violation, where T is the time horizon and κ ∈ (0, 1) is a user-defined trade-off parameter. Moreover, if the loss functions are strongly convex, then the static network regret bound can be reduced to O(T κ). Finally, numerical simulations are provided to illustrate the effectiveness of the theoretical results. Copyright © 2021, The Authors. All rights reserved.

关键词： Economic and social effects

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Reachable set boundedness and fuzzy sliding mode control of MPPT for nonlinear photovoltaic systems

Reachable set boundedness and fuzzy sliding mode control of ...

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IEEE International Conference on Fuzzy systems (FUZZ-IEEE)

作者： Zhixiong Zhong Xingyi Wang Rathinasamy Sakthivel Chih-Min Lin Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou China Department of Applied Mathematics Bharathiar University Coimbatore India Department of Electrical Engineering Yuan Ze University Taoyuan Taiwan

ISBN: (数字)9781728169323

ISBN: (纸本)9781728169330

This paper develops a novel maximum power point tracking (MPPT) control strategy for nonlinear photovoltaic (PV) systems. The MPPT control problem of the considered PV systems is first formulated in the framework of fuzzy descriptor systems. Then, based on the new formulation, a fuzzy sliding mode control (FSMC) law is constructed to drive the state trajectories into a desired sliding surface within the finite-time T* with T*

关键词： Maximum power point trackers Trajectory Switches Fuzzy logic Sliding mode control DC-DC power converters

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Observation of quantum strong Mpemba effect

arXiv

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arXiv 2024年

作者： Zhang, Jie Xia, Gang Wu, Chun-Wang Chen, Ting Zhang, Qian Xie, Yi Su, Wen-Bo Wu, Wei Qiu, Cheng-Wei Chen, Ping-Xing Li, Weibin Jing, Hui Zhou, Yan-Li Institute for Quantum Science and Technology College of Science National University of Defense Technology Changsha410073 China Hunan Key Laboratory of Mechanism and technology of Quantum Information Changsha410073 China Hefei National Laboratory Anhui Hefei230088 China Key Laboratory of Low-Dimensional Quantum Structures and Quantum Control of Ministry of Education Hunan Normal University Changsha410081 China Department of Electrical and Computer Engineering National University of Singapore Singapore Singapore School of Physics and Astronomy University of Nottingham NottinghamNG7 2RD United Kingdom Centre for the Mathematics and Theoretical Physics of Quantum Non-equilibrium Systems University of Nottingham NottinghamNG7 2RD United Kingdom College of Science National University of Defense Technology Changsha410073 China

An ancient and counterintuitive phenomenon known as the Mpemba effect showcases the critical role of initial conditions in relaxation processes. How to realize and utilize this effect for speeding up relaxation is an important but challenging task in purely quantum system till now. Here, we experimentally study the strong Mpemba effect in a single trapped ion system in which an exponentially accelerated relaxation in time is observed by preparing an optimal quantum initial state with no excitation of the slowest decaying mode. Also, we demonstrate that the condition of realizing such effect coincides with the Liouvillian exceptional point, featuring the coalescence of both the eigenvalues and the eigenmodes of the systems. Our work provides an efficient strategy to engineer the dynamics of open quantum system, and suggests a link unexplored yet between the Mpemba effect and the non-Hermitian physics. Copyright © 2024, The Authors. All rights reserved.

关键词： Trapped ions

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The Performance Evaluation and Resilience Analysis of Supply Chain Based on Logistics Network

The Performance Evaluation and Resilience Analysis of Supply...

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第三十九届中国控制会议

作者： Weiqi Sun Yuanlong Li Liangren Shi Department of Automation Shanghai Jiao Tong Universityand Key Laboratory of System Control and Information Processing of the Ministry of Education Shanghai Key Laboratory of Navigation and Location-based Services and Academy of Information Technology and Electrical Engineering Shanghai Jiao Tong University

With the development of globalization, more and more enterprises are involved in the supply chain network with increasingly complex structure. In this paper, enterprises and relations in the logistics network are abstracted as nodes and edges of the complex network. A graph model for a supply chain network to specified industry is constructed, and the Neo4 j graph database is employed to store the graph data. This paper uses the theoretical research tool of complex network to model and analyze the supply chain, and designs a supply chain network evaluation system which include static and dynamic measurement indexes according to the statistical characteristics of complex network. In this paper both the static and dynamic resilience characteristics of the the constructed supply chain network are evaluated from the perspective of complex network. The numeric experimental simulations are conducted for validation. This research has practical and theoretical significance for enterprises to make strategies to improve the anti-risk capability of supply chain network based on logistics network information.

关键词： Complex network Supply chain network Graph database Neo4j Resilience evaluation

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Sparse common feature representation for undersampled face recognition

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IEEE Internet of Things Journal 2021年第7期8卷 5607-5618页

作者： Yang, Shicheng Wen, Ying He, Lianghua Zhou, MengChu Department of Computer Science and Technology Tongji University Shanghai200092 China Shanghai Key Laboratory of Multidimensional Information Processing Department of Computer Science and Technology East China Normal University Shanghai200241 China Department of Electrical and Computer Engineering New Jersey Institute of Technology NewarkNJ07102 United States Center of Research Excellence in Renewable Energy and Power Systems King Abdulaziz University Jeddah21589 Saudi Arabia

This work investigates the problem of undersampled face recognition (i.e., insufficient training data) encountered in practical Internet-of-Things (IoT) applications. Insufficient and uncertain samples captured by IoT devices may include background and facial disguise that makes face recognition more challenging than that with sufficient and reliable images. Many models work well in face recognition on a big data set, but when training data are insufficient, they achieve unsatisfactory performance. This work proposes a novel method named sparse common feature-based representation (SCFR) that provides a unique and stable result and completely avoids very time-consuming training required by a deep learning model. Specially, it constructs a common feature dictionary using both training and test images. Thereinto, a common feature is based on a discriminative common vector and learned by a Gaussian mixture model for both training and test images in a semisupervised learninig manner, which would reduce the difference among samples in each class. In the optimization, the latent indicator of test data is initialized by the estimated label. This can avoid learning invalid information and lead to good prototype images. A new variation dictionary characterizes variables that can be shared by different classes. Finally, this work adopts minimum reconstruction residuals to recognize test images, thus bringing about a substantial improvement in SCFR's performance. Extensive results on benchmark face databases demonstrate that the proposed method is better than the state-of-the-art methods handling undersampled face recognition. © 2014 IEEE.

关键词： Face recognition

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Pioneering the future of dentistry: AI-driven 3D bioprinting for next-generation clinical applications

Translational Dental Research

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Translational Dental Research 2025年第1期1卷

作者： Zihui Liang Xiaohong Liao Huiyi Zong Xinyao Zeng Hong Liu Congcong Wu Kavya Keremane Bed Poudel Jun Yin Kai Wang Jin Qian Huanjiang Laboratory Zhejiang University Zhuji 311800 China National Local Joint Laboratory for Advanced Textile Processing and Clean Production Wuhan Textile University Wuhan 430073 China School of New Energy and Electrical Engineering Hubei University Wuhan 430073 China Department of Materials Science and Engineering The Pennsylvania State University University Park PA 16802 USA The State Key Laboratory of Fluid Power Transmission and Control Systems School of Mechanical Engineering Zhejiang University Hangzhou 310027 China

Artificial intelligence (AI) is revolutionizing dentistry by enhancing the analysis of complex medical imaging data, automating the identification of anatomical landmarks, and improving diagnostic accuracy and treatment planning, etc. When combined with three-dimensional (3D) bioprinting, AI significantly optimizes the design and manufacturing processes, leading to highly precise and functional 3D-printed dental devices. AI-driven 3D bioprinting represents a transformative leap beyond traditional prosthetics, with the potential to create living tissues capable of regenerating oral structures. This technology pushes the boundaries of dental care by facilitating the development of biocompatible materials and complex tissue constructs that seamlessly integrate with interdisciplinary research, spanning advanced materials, future manufacturing techniques, and innovative clinical methodologies. This review examines the cutting-edge advancements in AI-assisted 3D bioprinting, focusing on its roles in tissue engineering, regenerative dentistry, and personalized treatment planning. Although many of these innovations remain in the research phase, they signify the dawn of a new era in dental medicine, where AI-driven bioprinting is poised to make the regeneration of teeth, gums, and bone structures a clinical reality. This paper provides a concise overview of these developments, emphasizing their potential to revolutionize dental practice.

关键词： Artificial intelligence 3D bioprinting Regenerative dentistry AI-driven manufacturing in prosthetics Advanced materials for dental regeneration

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A Mixed Gaussian Membership Function Fuzzy CMAC for a Three-Link Robot

A Mixed Gaussian Membership Function Fuzzy CMAC for a Three-...

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IEEE International Conference on Fuzzy systems (FUZZ-IEEE)

作者： Tuan-Tu Huynh Chih-Min Lin Tien-Loc Le Zhixiong Zhong Department of Electrical Engineering Yuan Ze University Taoyuan Taiwan R.O.C. Department of Electrical Electronic and Mechanical Engineering Lac Hong University Bien Hoa Vietnam Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou China

ISBN: (数字)9781728169323

ISBN: (纸本)9781728169330

This research produces a mixed Gaussian membership function (GMF) fuzzy cerebellar model articulation controller (CMAC) for a three-link robot. A mixed GMF is created using the current and the previous GMFs on each layer of CMAC to detect errors efficiently, so a mixed GMF fuzzy CMAC (MGMFFC) is able to train parameters efficiently and constructs the MGMFFC structure automatically. A Lyapunov cost function and the gradient descent techniques are utilized to get the adaptive with guaranteed system's stable. Simulation studies for a three-link robot show that the MGMFFC attains favorable tracking performance.

关键词： Two dimensional displays Robots Hypercubes Robustness Fuzzy logic Nonlinear systems Electronic mail

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Low-latency federated learning over wireless channels with differential privacy

arXiv

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arXiv 2021年

作者： Wei, Kang Li, Jun Ma, Chuan Ding, Ming Chen, Cailian Jin, Shi Han, Zhu Poor, H. Vincent School of Electrical and Optical Engineering Nanjing University of Science and Technology Nanjing210094 China Data61 CSIRO SydneyNSW2015 Australia The Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China The National Mobile Communications Research Laboratory Southeast University Nanjing210096 China The Department of Electrical and Computer Engineering The University of Houston HoustonTX77004 United States The Department of Computer Science and Engineering Kyung Hee University Seoul Korea Republic of The Department of Electrical and Computer Engineering Princeton University PrincetonNJ08544 United States

In federated learning (FL), model training is distributed over clients and local models are aggregated by a central server. The performance of uploaded models in such situations can vary widely due to imbalanced data distributions, potential demands on privacy protections, and quality of transmissions. In this paper, we aim to minimize FL training delay over wireless channels, constrained by overall training performance as well as each client's differential privacy (DP) requirement. We solve this problem in the framework of multi-agent multiarmed bandit (MAMAB) to deal with the situation where there are multiple clients confornting different unknown transmission environments, e.g., channel fading and interferences. Specifically, we first transform the long-term constraints on both training performance and each client's DP into a virtual queue based on the Lyapunov drift technique. Then, we convert the MAMAB to a max-min bipartite matching problem at each communication round, by estimating rewards with the upper confidence bound (UCB) approach. More importantly, we propose two efficient solutions to this matching problem, i.e., modified Hungarian algorithm and greedy matching with a better alternative (GMBA), in which the first one can achieve the optimal solution with a high complexity while the second one approaches a better tradeoff by enabling a verified low-complexity with little performance loss. In addition, we develop an upper bound on the expected regret of this MAMAB based FL framework, which shows a linear growth over the logarithm of communication rounds, justifying its theoretical feasibility. Extensive experimental results are conducted to validate the effectiveness of our proposed algorithms, and the impacts of various parameters on the FL performance over wireless edge networks are also discussed. Copyright © 2021, The Authors. All rights reserved.

关键词： Multi agent systems

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Regret and cumulative constraint violation analysis for online convex optimization with long term constraints

arXiv

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arXiv 2021年

作者： Yi, Xinlei Li, Xiuxian Yang, Tao Xie, Lihua Chai, Tianyou Johansson, Karl H. School of Electrical Engineering and Computer Science and Digital Futures KTH Royal Institute of Technology Stockholm Sweden Department of Control Science and Engineering College of Electronics and Information Engineering Shanghai Research Institute for Intelligent Autonomous Systems Institute for Advanced Study Tongji University Shanghai China State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang China School of Electrical and Electronic Engineering Nanyang Technological University Singapore Singapore

This paper considers online convex optimization with long term constraints, where constraints can be violated in intermediate rounds, but need to be satisfied in the long run. The cumulative constraint violation is used as the metric to measure constraint violations, which excludes the situation that strictly feasible constraints can compensate the effects of violated constraints. A novel algorithm is first proposed and it achieves an O(Tmax{c,1-c}) bound for static regret and an O(T (1-c)/2) bound for cumulative constraint violation, where c ϵ (0, 1) is a user-defined trade-off parameter, and thus has improved performance compared with existing results. Both static regret and cumulative constraint violation bounds are reduced to O(log(T )) when the loss functions are strongly convex, which also improves existing results. In order to achieve the optimal regret with respect to any comparator sequence, another algorithm is then proposed and it achieves the optimal O( p T (1 + PT )) regret and an O(√T) cumulative constraint violation, where PT is the path-length of the comparator sequence. Finally, numerical simulations are provided to illustrate the effectiveness of the theoretical results. Copyright © 2021, The Authors. All rights reserved.

关键词： Comparators (optical)

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Investigation on Insulating Properties of Epoxy Resin Impregnated Paper Affected by Curing Agents and Accelerator Contents

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IEEE Transactions on Dielectrics and electrical Insulation 2025年

作者： Teng, Chenyuan Ding, Yichao Zhou, Yuanxiang Zhao, Lei Zhang, Yunxiao Chen, Haoran Zhang, Youbing Zhejiang University of Technology College of Information Engineering Hangzhou310023 China Nankai University China and College of Electronic Information and Optical Engineering Tianjin300350 China Zhejiang Testing & Inspection Institute for Mechanical and Electrical Products Quality Co. Ltd Hangzhou310051 China Tsinghua University State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Department of Electrical Engineering Beijing100084 China State Grid Xinxiang Electric Power Supply Company Xinxiang453002 China

The curing formula is vital to the performance of epoxy resin impregnated paper (RIP) material. This work explored the effect of curing agents and accelerator contents on the thermal and electrical properties of RIP material. It was found that the RIP material cured with 1phr accelerator has the optimal glass transition temperature, electrical conductivity, dielectric loss and DC breakdown strength compared with RIP material cured by 0.5phr, 2phr, and 3phr accelerator. The RIP material cured with MEHHPA has better thermal and insulating properties compared with the RIP material cured with METHPA. The existence of the crepe paper amplifies the influence of accelerator and curing agent for the hydroxyl groups affect the curing process as well as the chain segment arrangement. This study provides the research support for the design of the curing formula for RIP insulation used in DC bushing. © 1994-2012 IEEE.

关键词： Dielectric losses

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