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arXiv 2021年

作者： Jiang, Xia Zeng, Xianlin Sun, Jian Chen, Jie Xie, Lihua Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China Beijing Institute of Technology Chongqing Innovation Center Chongqing401120 China School of Electronic and Information Engineering Tongji University Shanghai200082 China Ministry of Education Beijing100081 China School of Electrical and Electronic Engineering Nanyang Technological University Singapore639798 Singapore

The non-smooth finite-sum minimization is a fundamental problem in machine learning. This paper develops a distributed stochastic proximal-gradient algorithm with random reshuffling to solve the finite-sum minimization over time-varying multi-agent networks. The objective function is a sum of differentiable convex functions and non-smooth regularization. Each agent in the network updates local variables by local information exchange and cooperates to seek an optimal solution. We prove that local variable estimates generated by the proposed algorithm achieve consensus and are attracted to a neighborhood of the optimal solution with an (formula presented) convergence rate, where T is the total number of iterations. Finally, some comparative simulations are provided to verify the convergence performance of the proposed algorithm. © 2021, CC BY.

关键词： Optimal systems

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Public Service Management System of Urban Placenames for Sanya Case

Public Service Management System of Urban Placenames for San...

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2016年IEEE/INFORMS服务运筹、物流与信息化国际会议

作者： Wei Liu Fenghua Zhu Xisong Dong Gang Xiong Yongqiang Zhu Huazhou Wu Taozhong Liu Yuexiang Hu The State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences College of Information Science and Technology Beijing University of Chemical Technology Beijing Engineering Research Center of Intelligent Systems and Technology Institute of AutomationChinese Academy of Sciences Dongguan Research Institute of CASIA Cloud Computing CenterChinese Academy of Sciences Instituteof Smart Education Systems Qingdao Academy of Intelligent Industries Xiamen Kingtopinfo Technology Co.Ltd

The rapidly growing amount of social interaction makes geographical names an important and indispensable medium for people in social and economic exchanges. Especially in today's information age, the frequency of usage of name information has increased greatly. In this paper, a method for the construction of a cities' names database is proposed. This will include the processing of the outcome data from the names pilot survey, the consolidation into the database, the development of the cloud service and management system based on the geographical names and zoning database, and the construction of a relatively complete set of the public service system of geographical names based on a website and touch screen interface. The method has been applied in San Ya, China successfully, and very good results have been obtained. The platform can provide not only accurate and convenient services of geographical names, but also promote its economic development and social progress.

关键词： Public service system geographical names geographical names database cloud service platform

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Stability analysis of switched nonlinear delay systems with sampled-data inputs

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International Journal of Robust and Nonlinear control 2019年第14期29卷

作者： Zhichuang Wang Jian Sun Guoliang Chen Jie Chen School of Automation Beijing Institute of Technology Beijing China Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing China

This study addresses the uniformly globally asymptotically stability (UGAS) problem of switched nonlinear delay systems (SNDSs) with sampled-data inputs (SDIs). By using multiple Lyapunov functionals (MLFs) method, mode-dependent average dwell times, and the total activating time length of MLFs, some stability criteria are explicitly obtained for SNDSs with SDIs. Meanwhile, the UGAS property for SNDSs with some or all unstable modes is investigated. For unstable modes and stable modes, we adopt different switching signals. Besides, we establish some sufficient stability conditions in the form of an upper bound on the sum of dwell times and sampling intervals. Simulation examples are adopted to illustrate and verify the effectiveness of our proposed methods.

关键词： multiple Lyapunov functionals sampled-data inputs stability switched nonlinear delay systems

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Social Manufacturing Development with Sino-Finnish Innovation Cooperation

Social Manufacturing Development with Sino-Finnish Innovatio...

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2016年IEEE/INFORMS服务运筹、物流与信息化国际会议

作者： Jian Liu Gang Xiong Xiuqin Shang Timo R.Nyberg Yiming Wang Tongkai Ji The State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences College of Information Science and Technology Beijing University of Chemical Technology Cloud Computing Center Chinese Academy of Sciences Department of Industrial Engineering and Management School of ScienceAalto University Beijing Engineering Research Center of Intelligent Systems and Technology Institute of AutomationChinese Academy of Sciences

Innovation is changing the world every day by offering new technical solutions for the society, and the technology development powered by innovation has been changing the operation and structure of traditional manufacturing. Social manufacturing is the new trend of manufacturing development, especially in the field of apparel industry. Social manufacturing can create opportunities for customers to participate in the produce process of tailoring, and to make more personalizing clothes, which will also benefit for the related companies' brand making process. With the assistance of internet technology and industry globalization, we can establish several modes about the trend of social manufacturing and new related technology, social manufacturing can also prompt the international division of labor by reducing the producing costs and enlarging the market capacity, we will analyze the advance of Sino-Finland cooperation in the field of innovation and apparel industry, the international cooperation in manufacturing industry will benefit both customers and industry revolution with the assistance of social manufacturing.

关键词： social manufacturing innovation apparel industry international cooperation

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PSSE Redux: Convex relaxation, decentralized, robust, and dynamic approaches

arXiv

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arXiv 2017年

作者： Kekatos, Vassilis Wang, Gang Zhu, Hao Giannakis, Georgios B. Bradley Department of Electrical and Computer Engineering Virginia Tech BlacksburgVA24061 United States Department of Electrical and Computer Engineering University of Minnesota MinneapolisMN55455 United States State Key Lab of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing100081 China Department of Electrical and Computer Engineering University of Illinois UrbanaIL61801 United States

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Acoustic Source Tracking in Reverberant Environment Using A Novel PSO Particle Filter Framework

Acoustic Source Tracking in Reverberant Environment Using A ...

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Chinese Automation Congress (CAC)

作者： Jing Yang Xiuqin Shang Bin Hu Zhen Shen Gang Xiong Hui Wang College of Information Sciences and Technology Beijing University of Chemical Technology Beijing China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China The Cloud Computing Center Chinese Academy of Sciences Dongguan China

In this paper, several methods are combined together and applied to a Particle Filter based on Particle Swarm Optimization acoustic source tracking framework in order to solve some problems of sound source tracking. The Time Difference of Arrival (TDOA), which is extracted from the audio signal received by the microphone pair, makes observations. The Langevin Model is used to describe the speaker's motion characteristics. The pseudo-likelihood function is constructed by using the Global Coherence Field (GCF) function to update the particle weight, in order to solve problem of the phenomenon of spurious source due to noise and reverberation. According to the iterative process and particle flight conditions, the inertial weights of the particles are adjusted nonlinearly and dynamically. The concepts of superior flight speed and inferior flight speed are introduced to Particle Swarm Optimization, which helps jump out of local optimum and solves the problem of lack of particle diversity. Thus, the faster tracking of sound source is realized. In the framework, with fewer particles, the robustness of tracking is enhanced and accuracy of tracking is improved. Finally, the effectiveness of this framework for acoustic source tracking is verified through several Monte Carlo simulation experiments.

关键词： Microphones Particle filters Particle swarm optimization Tracking Coherence Reverberation

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Blockchain-based Social Manufacturing for Customization Production

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IFAC-PapersOnLine 2020年第5期53卷 53-58页

作者： Xiuqin Shang Xi Chen Lulu Niu Gang Xiong Zhen Shen Xisong Dong Zhengchao Shen Chao Liu Bangwen Xi the Research Center of Precision Sensing and Control the state key laboratory for management and control of complex systems & Beijing engineering research center of intelligent systems and technology institute of automation Chinese Academy of Sciences Beijing 100190 China Beijing University of Posts and Telecommunications Beijing 100876 China Alstom Beizhong Power (Beijing) Co. Ltd. Beijing 100040 China the System Integration Electronics (Hangzhou)Co. LTD No. 58 No. 11 Road Foxconn Qiantang Tech-Industrial Area HETZ Hangzhou 310018 China

This paper proposes the social manufacturing based on Blockchain, which realizes precise and efficient customization through smart contract and distributed accounting. It is a new manufacturing mode of service-oriented, distributed and collaborative customization. This paper proposes the definition of SM based on Blockchain. In the process of using to Blockchain, it can form a strong trust relationship, so that multiple nodes / roles in SM can save the complete copy of the whole database, rather than a centralized permission / role. Secondly, the Blockchain-based SM system is developed for customized manufacturing. Finally, its application case and the optimization results are given. In SM, it is the key that how to transform customized manufacturing actions into socialized actions of manufacturing resources through internet communities and interconnect Socialized Manufacturing Resources (SMRs) in upstream and downstream. In this paper, the smart contract relationship is established based on Blockchain between SMRs to build credit mechanism in SM, Which can ensure the effective circulation and association of SMRs.

关键词： Social Manufacturing Blockchain Optimization SM Resources

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Fitting a Functional Structural Plant Model based on Global Sensitivity Analysis

Fitting a Functional Structural Plant Model based on Global ...

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IEEE International Conference on Automation Science and Engineering

作者： Yubin LIN Mengzhen KANG Jing HUA National Key Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences State Key Laboratory of Management and Control for Complex Systems Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences

ISBN: (纸本)9781467304290

Calibration of a functional structural plant model is a challenging task because of the complexity of model structure. Parameter estimation through gradient-based optimization technique was highly dependent on initial parameter values. This motivated the use of global sensitivity analysis technique to choose parameter subset in fitting the data sequence. Global sensitivity indices were computed using the source sink ratio as the output of interest, which regulates all organ growth. By fitting on chrysanthemum data from nine sampling dates, it is shown that sensitivity analysts method helps to identify the influential parameters for a given sampling date. As a result, fitting process is less dependent on the initial parameter values. Current work provides a new method of calibrating a plant growth model with multiple outputs.

关键词： Sensitivity analysis plant models organ growth MACHINE SHOP PRACTICE

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An Interpretability Analysis of Travel decision Learning in Cyber-Physical-Social-systems

An Interpretability Analysis of Travel Decision Learning in ...

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Digital Twins and Parallel Intelligence (DTPI), IEEE International Conference on

作者： Miao Guo Peijun Ye Xudong Liu Sheng Liu Gang Xiong Liguo Zhang The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Faculty of Information and Technology Beijing University of Technology Beijing China The Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China The Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing The Cloud Computing Center Chinese Academy of Sciences Beijing China

In the few decades, the rise of Internet and social media has fundamentally changed the management, control, and operation modes of modern engineering and social systems like defense, energy, critical health care and ... 详细信息

关键词： Deep learning Social networking (online) Scalability Perturbation methods Neurons Transportation Transforms

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Joint Face Alignment and 3D Face Reconstruction with Efficient Convolution Neural Networks

Joint Face Alignment and 3D Face Reconstruction with Efficie...

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International Conference on Pattern Recognition

作者： Keqiang Li Huaiyu Wu Xiuqin Shang Zhen Shen Gang Xiong Xisong Dong Bin Hu Fei-Yue Wang School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China The Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China The Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences Dongguan China

3D face reconstruction from a single 2D facial image is a challenging and concerned problem. Recent methods based on CNN typically aim to learn parameters of 3D Morphable Model (3DMM) from 2D images to render face alignment and 3D face reconstruction. Most algorithms are designed for faces with small, medium yaw angles, which is extremely challenging to align faces in large poses. At the same time, they are not efficient usually. The main challenge is that it takes time to determine the parameters accurately. In order to address this challenge with the goal of improving performance, this paper proposes a novel and efficient end-to-end framework. We design an efficient and lightweight network model combined with Depthwise Separable Convolution and Muti-scale Representation, Lightweight Attention Mechanism, named Mobile-FRNet. Simultaneously, different loss functions are used to constrain and optimize 3DMM parameters and 3D vertices during training to improve the performance of the network. Meanwhile, extensive experiments on the challenging datasets show that our method significantly improves the accuracy of face alignment and 3D face reconstruction. Model parameters and complexity of our method are also improved greatly.

关键词： Training Solid modeling Three-dimensional displays Convolution Face recognition Neural networks complexity theory

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