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Semi-asynchronous personalized federated learning for short-term photovoltaic power forecasting

Digital Communications and Networks 2023年第5期9卷 1221-1229页

作者： Weishan Zhang Xiao Chen Ke He Leiming Chen Liang Xu Xiao Wang Su Yang College of Computer Science and Technology China University of Petroleum(East China)China Sichuan Energy Internet Research Institute Tsinghua UniversityChina School of Computer and Communication Engineering Beijing University of Science and TechnologyChina State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijingChina School of Computer Science Fudan UniversityChina

Accurate forecasting for photovoltaic power generation is one of the key enablers for the integration of solar photovoltaic systems into power *** deep-learning-based methods can perform well if there are sufficient training data and enough computational ***,there are challenges in building models through centralized shared data due to data privacy concerns and industry *** learning is a new distributed machine learning approach which enables training models across edge devices while data reside *** this paper,we propose an efficient semi-asynchronous federated learning framework for short-term solar power forecasting and evaluate the framework performance using a CNN-LSTM *** design a personalization technique and a semi-asynchronous aggregation strategy to improve the efficiency of the proposed federated forecasting *** evaluations using a real-world dataset demonstrate that the federated models can achieve significantly higher forecasting performance than fully local models while protecting data privacy,and the proposed semi-asynchronous aggregation and the personalization technique can make the forecasting framework more robust in real-world scenarios.

关键词： Photovoltaic power forecasting Federated learning Edge computing CNN-LSTM

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The ChatGPT After: Building Knowledge Factories for Knowledge Workers with Knowledge Automation

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IEEE/CAA Journal of Automatica Sinica 2023年第11期10卷 2041-2044页

作者： Yutong Wang Xiao Wang Xingxia Wang Jing Yang Oliver Kwan Lingxi Li Fei-Yue Wang State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190China School of Artificial Intelligence Anhui UniversityHefei 230039China Motion G Inc068898Singapore Department of Electrical and Computer Engineering Purdue School of Engineering and TechnologyIndiana University-Purdue University IndianapolisIndiana 46202-5132 USA IEEE

Briefing: This perspective introduces the concept and framework of knowledge factories with knowledge machines for knowledge workers to achieve knowledge automation for Industry 5.0 and intelligent *** The big hit of Chat GPT makes it imperative to contemplate the practical applications of big or foundation models [1]-[5]. However, as compared to conventional models, there is now an increasingly urgent need for foundation intelligence of foundation models for real-world industrial applications.

关键词： Automation template Chat GPT

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Integrated Inspection of QoM, QoP, and QoS for AOI Industries in Metaverses

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IEEE/CAA Journal of Automatica Sinica 2022年第12期9卷 2071-2078页

作者： Yutong Wang Yonglin Tian Jiangong Wang Yansong Cao Shixing Li Bin Tian IEEE The State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190China Department of Engineering Science Faculty of Innovation EngineeringMacao University of Science and TechnologyMacao 999078China North Automatic Control Technology Institute in Taiyuan ShanxiChina Qingdao Academy of Intelligent Industries Shandong 266109China

With the rapid development of information technologies such as digital twin, extended reality, and blockchain,the hype around "metaverse" is increasing at astronomical speed. However, much attention has been paid to its entertainment and social functions. Considering the openness and interoperability of metaverses, the market of quality inspection promises explosive growth. In this paper, taking advantage of metaverses, we first propose the concept of Automated Quality Inspection(Auto QI), which performs integrated inspection covering the entire manufacturing process, including Quality of Materials, Quality of Manufacturing(Qo M), Quality of Products, Quality of Processes(Qo P), Quality of systems, and Quality of Services(Qo S). Based on the scenarios engineering theory, we discuss how to perform interactions between metaverses and the physical world for virtual design instruction and physical validation feedback. Then we introduce a bottomup inspection device development workflow with productivity tools offered by metaverses, making development more effective and efficient than ever. As the core of quality inspection,we propose Quality Transformers to complete detection task,while federated learning is integrated to regulate data *** summary, we point out the development directions of quality inspection under metaverse tide.

关键词： Automated Optical Inspection Metaverses Quality Inspection Transformers

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A Deep Learning Based Personal Authentication Method Using sEMG Signal 41

A Deep Learning Based Personal Authentication Method Using s...

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第41届中国控制会议

作者： Lina Tong Mingjia Zhang Daisong Liu Hanghang Ma Yuxiang Zhang Liang Peng School of Mechanical Electronic & Information Engineering Chinese University of Mining and Technology-Beijing State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChina Academy of Science

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Personal authentication means that the relevant system confirms whether the identity of the user is real,legal and unique.A safe and convenient personal authentication method is a core for guarantee the security of our information and *** Electromyography(sEMG),which exists on the surface of the skin,is a good signal to achieve personal authentication,for it is difficult to be extracted and *** this paper,a new personal authentication method using forearm sEMG is ***,8-channel sEMG signals are recorded by Myo armband that is placed on right forearm of 14 subjects who perform the same hand open ***,two different deep learning models are presented to classify the *** multi-layers Convolution Neural Network(ML-CNN) and two stages Long Short Term Memory(2 s-LSTM) Network can achieve accuracy of 97.50% and 93.60% respectively,shows it is feasible to achieve the goal of personal *** the time cost of ML-CNN is higher than the 2 s-LSTM,both are lower than human reaction *** the architecture of ML-CNN is more suitable to achieving the goal of personal authentication.

关键词： Personal Authentication Surface Electromyography(sEMG) Myo multi-layers Convolution Neural Network(CNN) LSTM Network

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Parallel Sensing in Metaverses: Virtual-Real Interactive Smart systems for “6S” Sensing

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IEEE/CAA Journal of Automatica Sinica 2022年第12期9卷 2047-2054页

作者： Yu Shen Yuhang Liu Yonglin Tian Xiaoxiang Na School of Artificial Intelligence University of Chinese Academy of ScienceBeijing 100190China IEEE The State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190China Department of Engineering University of CambridgeTrumpington StreetCB21PZUnited Kingdom

In the construction of Metaverses,sensors that are referred to as the“bridge of information transmission”,play a key *** functionality and efficiency of today’s sensors,which operate in a manner similar to physical sensing,are frequently constrained by their hardware and *** this research,we proposed the Parallel Sensing framework,which includes background,concept,basic methods and typical application of parallel *** our formulation,sensors are redefined as the integration of real physical sensors and virtual software-defined sensors based on parallel intelligence,in order to boost the performance of the *** sensor will have a parallel counterpart in the virtual world within the framework of parallel *** sensors serve as the brain of sensors and maintain the same properties as physical *** sensing allows physical sensors to operate in discrete time periods to conserve energy,while cloud-based descriptive,predictive,and prescriptive sensors operate continuously to offer compensation data and serve as *** better illustrate parallel sensing concept,we show some example applications of parallel sensing such as parallel vision,parallel point cloud and parallel light fields,both of which are designed by construct virtual sensors to extend small real data to virtual big data and then boost the performance of perception *** results demonstrate the effective of parallel sensing *** interaction between the real and virtual worlds enables sensors to operate actively,allowing them to intelligently adapt to various scenarios and ultimately attain the goal of“Cognitive,Parallel,Crypto,Federated,Social and Ecologic”6S sensing.

关键词： Parallel Sensing Parallel Intelligence CPSS Metaverses Virtual and Real Interaction “6S”Sensing.

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Framework and key Technologies for High-speed Railway Comprehensive Transport Hub 3

Framework and Key Technologies for High-speed Railway Compre...

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3rd IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2023

作者： Xiong, Gang Zhang, Wei Liu, Xiaoming Yuan, Zhiming Zhu, Fenghua Zhang, Zundong Chinese Academy of Sciences State Key Laboratory for Multimodal Artificial Intelligence Systems Beijing China North China University of Technology School of Electrical and Control Engineering Beijing China China Academy of Railway Science Communication Signal Research Institute Beijing China Chinese Academy of Sciences State Key Laboratory for Management and Control of Complex Systems Beijing China

ISBN: (纸本)9798350318470

The surge in urban population density in China has underscored the vital role of high-speed rail and subway systems in urban transit. Comprehensive transportation hubs, notably high-speed rail passenger terminals, have emerged as linchpins for seamless multimodal transit both within and beyond urban centers. China's railway sector vigorously champions the innovative concept of "station-city integration"and has articulated a forward-looking "16-word policy"for modern railway stations: "Seamless integration, environmental friendliness, economic viability, and intelligent accessibility". The judicious allocation of resources and the augmentation of coordination and control capabilities within comprehensive transportation hubs are imperative for the harmonious evolution of urban transit. The implementation of intelligent control systems for transportation hubs has emerged as a pivotal area of research. This study delves into the framework and critical technologies for high-speed railway comprehensive transport hubs, encompassing various components and their intricate interplay, including transport modalities, infrastructure, travelers, environmental factors, and information systems, thus forming a prototypical cyber-physical-social system. Addressing the prevalent and pressing imperative for the advancement of "station-city integration"high-speed railway comprehensive transport hubs, this research endeavor aims to surmount bottleneck challenges and refine the oversight of passenger flows at high-speed rail terminals. The findings hold noteworthy theoretical import and portend promising practical applications. © 2023 IEEE.

关键词： Integration

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Single Camera Based Gait Analysis Method with Scaled and Image Coordinate key-points

Single Camera Based Gait Analysis Method with Scaled and Ima...

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2022 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2022

作者： Xiang, Tian-Yu Zhou, Xiao-Hu Xie, Xiao-Liang Liu, Shi-Qi Wang, Chen Gui, Mei-Jiang Li, Hao Hou, Zeng-Guang University of Chinese Academy of Sciences State Key Laboratory of Management and Control for Complex Systems Institute of Automation School of Artificial Intelligence Beijing100049 China

ISBN: (数字)9781665469838

ISBN: (纸本)9781665469838

Clinical experiments and scientific evidence show the relations between gait and cognition. Neurological diseases (like stroke and cerebral palsy) distract patients' attention and restrict their executive functions. Furthermore, these diseases impair patients' movement and limit their social participation. Quantitative motion assessment is significant to medical decision-making for neurological disorders but is possible only with expensive motion capture systems and professional medical workers. Here, an end-To-end video-based quantitative gait analysis algorithm is proposed. Unlike previous works, which only focus on image coordinate key-points, our algorithm also utilizes scaled key-points that can depict the size of patients. These two groups of features are sent to other neural networks to extract temporal and spatial characteristics, and then the deep features are fused by the attention mechanism. Finally, a statistic model is used to process the proposed outputs to get a final result. Experiments on the public patients' dataset show the effectiveness and accuracy of our model. Furthermore, the ablation study proves that every step of the proposed method contributes to the whole system's performance. © 2022 IEEE.

关键词： Gait analysis

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Modeling the dynamic impacts of maritime network blockage on global supply chains

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The Innovation 2024年第4期5卷 103-109,102页

作者： Shen Qu Yunlei She Qi Zhou Jasper Verschuur Lu-Tao Zhao Huan Liu Ming Xu Yi-Ming Wei Center for Energy and Environmental Policy Research Beijing Institute of TechnologyBeijing 100081China School of Management Beijing Institute of TechnologyBeijing 100081China Beijing Key Lab of Energy Economics and Environmental Management Beijing 100081China Oxford Programme for Sustainable Infrastructure Systems(OPSIS) Environmental Change InstituteUniversity of OxfordOX12JD OxfordUK State Key Joint Laboratory of Environment Simulation and Pollution Control School of EnvironmentTsinghua UniversityBeijing 100084China State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex Beijing 100084China School of Environment Tsinghua UniversityBeijing 100084China

Recent phenomena such as pandemics,geopolitical tensions,and climate change-induced extreme weather events have caused transportation network interruptions,revealing vulnerabilities in the global supply chain.A salient example is the March 2021 Suez Canal blockage,which delayed 432 vessels carrying cargo valued at$92.7 billion,triggering widespread supply chain *** ability to model the spatiotemporal ramifications of such incidents remains *** fill this gap,we develop an agent-based complex network model integrated with frequently updated maritime *** Suez Canal blockage is taken as a case *** results indicate that the effects of such blockages go beyond the directly affected countries and *** Suez Canal blockage led to global losses of about$136.9($127.5–$147.3)billion,with India suffering 75%of these *** losses show a nonlinear relationship with the duration of blockage and exhibit intricate trends post *** proposed model can be applied to diverse blockage scenarios,potentially acting as an earlyalert system for the ensuing supply chain ***,high-resolution daily data post blockage offer valuable insights that can help nations and industries enhance their resilience against similar future events.

关键词： chains valued extreme

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Multi-Blockchain Based Data Trading Markets With Novel Pricing Mechanisms

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IEEE/CAA Journal of Automatica Sinica 2023年第12期10卷 2222-2232页

作者： Juanjuan Li Junqing Li Xiao Wang Rui Qin Yong Yuan Fei-Yue Wang IEEE the State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China the College of Computer Science and Engineering Shandong University of Science and TechnologyQingdao 266590China the School of Artificial Intelligence Anhui UniversityHefei 266114 the Qingdao Academy of Intelligent Industries Qingdao 230031China the School of Mathematics Renmin University of ChinaBeijing 100872China the State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190 the Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China

In the era of big data,there is an urgent need to establish data trading markets for effectively releasing the tremendous value of the drastically explosive *** security and data pricing,however,are still widely regarded as major challenges in this respect,which motivate this research on the novel multi-blockchain based framework for data trading markets and their associated pricing *** this context,data recording and trading are conducted separately within two separate blockchains:the data blockchain(DChain) and the value blockchain(VChain).This enables the establishment of two-layer data trading markets to manage initial data trading in the primary market and subsequent data resales in the secondary ***,pricing mechanisms are then proposed to protect these markets against strategic trading behaviors and balance the payoffs of both suppliers and ***,in regular data trading on VChain-S2D,two auction models are employed according to the demand scale,for dealing with users’ strategic *** incentive-compatible Vickrey-Clarke-Groves(VCG)model is deployed to the low-demand trading scenario,while the nearly incentive-compatible monopolistic price(MP) model is utilized for the high-demand trading *** temporary data trading on VChain-D2S,a reverse auction mechanism namely two-stage obscure selection(TSOS) is designed to regulate both suppliers’ quoting and users’ valuation ***,experiments are carried out to demonstrate the strength of this research in enhancing data security and trading efficiency.

关键词： Auction data trading markets multi-blockchain pricing mechanisms

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Automated Silicon-Substrate Ultra-Microtome for Automating the Collection of Brain Sections in Array Tomography

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IEEE/CAA Journal of Automatica Sinica 2021年第2期8卷 389-401页

作者： Long Cheng Weizhou Liu Chao Zhou Yongxiang Zou Zeng-Guang Hou the State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 the School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China

Understanding the structure and working principle of brain neural networks requires three-dimensional reconstruction of brain tissue samples using array tomography *** order to improve the reconstruction performance,the sequence of brain sections should be collected with silicon wafers for subsequent electron microscopic ***,the current collection of brain sections based on silicon substrate involve mainly manual collection,which requires the involvement of automation techniques to increase collection *** paper presents the design of an automatic collection device for brain ***,a novel mechanism based on circular silicon substrates is proposed for collection of brain sections;second,an automatic collection system based on microscopic object detection and feedback control strategy is *** results verify the function of the proposed collection *** objects(brain section,left baffle,right baffle)can be detected from microscopic images by the proposed detection *** efficiency can be further improved with position feedback of brain sections *** has been experimentally verified that the proposed device can well fulfill the task of automatic collection of brain *** the help of the proposed automatic collection device,human operators can be partially liberated from the tedious manual collection process and collection efficiency can be improved.

关键词： Array tomography automatic collection system brain sections microscopic object detection serial section

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