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arXiv 2020年

作者： Jiao, Qing Li, Yushan He, Jianping Shi, Ling Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong

Topology inference is a crucial problem for cooperative control in multi-agent systems. Different from most prior works, this paper is dedicated to inferring the directed network topology from the observations that consist of a single, noisy and finite time-series system trajectory, where the cooperation dynamics is stimulated with the initial network state and the unmeasurable latent input. The unmeasurable latent input refers to intrinsic system signal and extrinsic environment interference. Considering the time-invariant/varying nature of the input, we propose two-layer optimization-based and iterative estimation-based topology inference algorithms (TO-TIA and IE-TIA), respectively. TO-TIA allows us to capture the separability of global agent state and eliminates the unknown influence of time-invariant input on system dynamics. IE-TIA further exploits the identifiability and estimability of more general time-varying input and provides an asymptotic solution with desired convergence properties, with higher computation cost compared with TO-TIA. Our novel algorithms relax the dependence of observation scale and leverage the empirical risk reformulation to improve the inference accuracy in terms of the topology structure and edge weight. Comprehensive theoretical analysis and simulations for various topologies are provided to illustrate the inference feasibility and the performance of the proposed algorithms. Copyright © 2020, The Authors. All rights reserved.

关键词： Multi agent systems

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Inter-area coordination approach for metro train regulation under localized bi-directional power supply shortage during peak periods

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computers & Industrial Engineering 2025年 207卷

作者： Xuekai Wang Andrea D’Ariano Shuai Su Tao Tang Boyi Su Maode Yan School of Electronics and Control Engineering Chang’an University Xi’an 700054 China State Key Laboratory of Advanced Rail Autonomous Operation Beijing Jiaotong University Beijing 100044 China Frontiers Science Center for Smart High-speed Railway System Beijing Jiaotong University Beijing 100044 China Department of Civil Computer Science and Aeronautical Technologies Engineering Roma Tre University Rome 00154 Italy

Faults in the traction power supply system of metro lines frequently cause Localized Bi-directional Power Supply Shortage (LBPSS) during peak periods, significantly restricting the traction power available to trains in the under-supplied area, and have knock-on impacts on train operations in other regions. To mitigate the impacts of LBPSS on the entire line, this paper proposes an inter-area coordination approach for the train regulation problem, dividing the global problem into three sequential sub-problems. In the first stage, a cooperative control approach optimizes the control strategies in the under-supplied area, restoring the balance between power supply and demand within the power supply capacity constraints. Building on these results, the second stage reschedules the train timetable in the well-supplied areas using multiple dispatching measures. Since synchronization of entry and exit times between different regions may not be fully achieved in the first two stages, the third stage fine tures hard-to-synchronize entry/exit times, and adjusts control strategies in the under-supplied area via feedback adjustment. To address the unique challenges of each sub-problem, this paper adopts the specific algorithms: Independent Deep Q-Networks (IDQN) for cooperative control, the GUROBI solver for timetable rescheduling, and Adaptive Large-scale Neighborhood Search (ALNS) for fine-tuning synchronization. Notably, for complex constraints associated with the feedback adjustment problem, an improved ALNS algorithm is introduced, which incorporating a constraint operator to enhance convergence speed and solution quality through heuristic rules. Finally, numerical experiments based on the Beijing Metro Yizhuang Line validate the effectiveness of the proposed approach. Results indicate that the solution quality improves by up to 20.0% and 2.8% compared to two previous train regulation approaches: the conservative approach based on maximum traction power and the two-stage ap

关键词： Adaptive large-scale neighborhood search Distributed train dispatching Localized bi-directional power supply shortage Metro system Train regulation

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NiuEM: A Nested-iterative Unsupervised Learning Model for Single-particle Cryo-EM Image Processing

NiuEM: A Nested-iterative Unsupervised Learning Model for Si...

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2020 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2020

作者： Hu, Rui Cai, Jiaming Zheng, Wangjie Yang, Yang Shen, Hong-Bin Shanghai Jiao Tong University Key Lab. of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Department of Computer Science and Engineering Shanghai200240 China Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Jiao Tong University Department of Bioinformatics and Biostatistics Shanghai200240 China

ISBN: (纸本)9781728162157

Cryo-electron microscopy (cryo-EM) has become a mainstream technology for solving spatial structures of biomacromolecules, while the processing of cryo-EM images is a very challenging task. One of the great challenges is the high noise in the images. A common method is to cluster the images with close projecting angles to get mean images, which are used for 3D reconstruction. However, due to the extremely low signal-to-noise-ratio, common clustering methods often fail to obtain high-quality mean images, leading to poorly reconstructed structures. In this study, we present a new unsupervised learning framework, called NiuEM, to discriminate images captured from different angles and yield cluster-mean images. NiuEM first generates pseudo-labels and then exploits both contrastive loss and cross-entropy loss for training convolutional layers to learn feature representations. Moreover, the pseudo-labels are updated iteratively to enhance the reliability of labels. We assess the performance of NiuEM on four data sets via both visualized and quantitative experiments. Especially, two kinds of metrics are adopted to measure the performance, regarding the clustering quality and the resolution of reconstructed 3D models, respectively. The experimental results show that NiuEM achieves very competitive clustering accuracy in the comparison with the state-of-the-art image clustering methods. Moreover, the cluster mean images yielded by NiuEM lead to better initial 3D models compared with the mainstream reconstruction tools. © 2020 IEEE.

关键词： Image reconstruction

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End-to-End AI-Based Point-of-Care Diagnosis system for Classifying Respiratory Illnesses and Early Detection of COVID-19

arXiv

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arXiv 2020年

作者： Belkacem, Abdelkader Nasreddine Ouhbi, Sofia Lakas, Abderrahmane Benkhelifa, Elhadj Chen, Chao Department of Computer and Network Engineering CIT UAEU UAE Department of Computer Science and Software Engineering CIT UAEU UAE Cloud Computing and Applications Reseach Lab Staffordshire University United Kingdom Key Laboratory of Complex System Control Theory and Application Tianjin University of Technology China

Respiratory symptoms can be a caused by different underlying conditions, and are often caused by viral infections, such as Influenza-like illnesses or other emerging viruses like the Coronavirus. These respiratory viruses, often, have common symptoms, including coughing, high temperature, congested nose, and difficulty breathing. However, early diagnosis of the type of the virus, can be crucial, especially in cases such as the recent COVID-19 pandemic. One of the factors that contributed to the spread of the pandemic, was the late diagnosis or confusing it with regular flu-like symptoms. Science has proved that one of the possible differentiators of the underlying causes of these different respiratory diseases is coughing, which comes in different types and forms. Therefore, a reliable lab-free tool for early and more accurate diagnosis that can differentiate between different respiratory diseases is very much needed. This paper proposes an end-to-end portable system that can record data from patients with symptom, including coughs (voluntary or involuntary) and translate them into health data for diagnosis, and with the aid of machine learning, classify them into different respiratory illnesses, including COVID-19. With the ongoing efforts to stop the spread of the COVID-19 disease everywhere today, and against similar diseases in the future, our proposed low cost and user-friendly solution can play an important part in the early diagnosis. Copyright © 2020, The Authors. All rights reserved.

关键词： Diagnosis

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Secure-by-construction optimal path planning for linear temporal logic tasks

arXiv

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arXiv 2020年

作者： Yang, Shuo Yin, Xiang Li, Shaoyuan Zamani, Majid Department of Automation and Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Shanghai200240 China Computer Science Department University of Colorado BoulderCO80309 United States Computer Science Department Ludwig Maximilian University of Munich Munich80539 Germany

In this paper, we investigate the problem of planning an optimal infinite path for a single robot to achieve a linear temporal logic (LTL) task with security guarantee. We assume that the external behavior of the robot, specified by an output function, can be accessed by a passive intruder (eavesdropper). The security constraint requires that the intruder should never infer that the robot was started from a secret location. We provide a sound and complete algorithmic procedure to solve this problem. Our approach is based on the construction of the twin weighted transition systems (twin-WTS) that tracks a pair of paths having the same observation. We show that the security-aware path planning problem can be effectively solved based on graph search techniques in the product of the twin-WTS and the Büchi automaton representing the LTL formula. The complexity of the proposed planning algorithm is polynomial in the size of the system model. Finally, we illustrate our algorithm by a simple robot planning example. Copyright © 2020, The Authors. All rights reserved.

关键词： computer circuits

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State Estimation for Integrated Energy systems: Motivations, Advances, and Future Work

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IEEE Transactions on Power systems 2024年

作者： Zhao, Junbo Srivastava, Ankur Guo, Ye Cetenovic, Dragan Lin, Yuzhang Levi, Victor Yin, Guanxiong Huang, Manyun Zhang, Tingting Li, Zhigang Chen, Yanbo Exposito, Antonio G. Zhang, Wen Zheng, Weiye Chakrabarti, Saikat Li, Yang Sharma, Ankush Kamwa, Innocent Guo, Qinglai Terzija, Vladimir Mili, Lamine University of Connecticut Department of Electrical and Computer Engineering StorrsCT06269 United States Tsinghua University Tsinghua-Berkeley Shenzhen Institute Shenzhen518055 China The University of Manchester Department of Eee ManchesterM13 9PL United Kingdom University of Kragujevac Faculty of Technical Sciences Čačak Čačak32000 Serbia New York University Department of Electrical and Computer Engineering NY11201 United States Tsinghua University Department of Electrical Engineering Beijing100084 China Hohai University College of Energy and Electrical Engineering Nanjing210098 China Shandong University Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Jinan250061 China The Chinese University of Hong Kong-Shenzhen School of Science and Engineering Shenzhen518172 China North China Electric Power University School of Electrical and Electronic Engineering Beijing102206 China University of Sevilla Spain Sevilla41092 Spain South China University of Technology School of Electrical Power Engineering Guangzhou510641 China Indian Institute of Technology Kanpur Department of Electrical Engineering Kanpur208016 India Northeast Electric Power University School of Electrical Engineering Jilin132012 China Laval University Department of Electrical and Computer Engineering QuebecQCG1V 0A6 Canada Tsinghua University State Key Laboratory of Power Systems Department of Electrical Engineering Beijing100084 China Newcastle University School of Engineering Newcastle upon TyneNE1 7RU United Kingdom Virginia Polytechnic Institute and State University Bradley Department of Electrical and Computer Engineering Falls ChurchVA22043 United States

This paper summarizes the technical activities of a three-year-long IEEE Task Force (TF) on State Estimation (SE) for Integrated Energy systems (IES). It presents the formal definition and characteristics of IES, along with the comprehensive discussion on Electric Power systems (EPS) model, and static and dynamic models associated with heating and natural gas systems. The paper also identifies the barriers of SE for IES, such as estimation modeling, observability analysis, and measurement requirements, together with addressing multi-scale dynamics. An extensive comparative analysis between Integrated Energy systems-State Estimation (IES-SE) and more established Electric Power system-State Estimation (EPS-SE) is presented. The paper also provides future research needs and directions related to IES-SE. © 1969-2012 IEEE.

关键词： Power system analysis

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A distributed strategy-updating rule with event-triggered communication for noncooperative games

A distributed strategy-updating rule with event-triggered co...

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第三十九届中国控制会议

作者： Xin Cai Feng Xiao Bo Wei State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University School of Control and Computer Engineering North China Electric Power University School of Electrical Engineering Xinjiang University

This paper focuses on a noncooperative game among a network of agents with double-integrator dynamics. A gradientbased and consensus-based strategy-updating rule is proposed for each agent to attain the Nash equilibrium outcome of the ***, we analyze the implementation of the designed rule with discrete-time communication. An asynchronous eventtriggered communication scheme is presented to ensure the asymptotical convergence to the Nash equilibrium and the network is free of Zeno behavior. Simulations are performed on the double-integrator agents to illustrate the effectiveness of the proposed methods.

关键词： Nash equilibrium double-integrator dynamics event-triggered communication noncooperative games

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Learning Latent Semantic Attributes for Zero-Shot Object Detection

Learning Latent Semantic Attributes for Zero-Shot Object Det...

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International Conference on Tools for Artificial Intelligence (ICTAI)

作者： Kang Wang Lu Zhang Yifan Tan Jiajia Zhao Shuigeng Zhou Shanghai Key Lab of Intelligent Information Processing and School of Computer Science Fudan University Shanghai China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing Electro-Mechanical Engineer Institute Beijing China

ISBN: (数字)9781728192284

ISBN: (纸本)9781728185361

Zero-shot Object Detection (ZSD) aims to locate and classify instances of unseen categories. Existing methods focus on learning the mapping from visual space to semantic space, while the learning of discriminative representations for ZSD has not gained enough attention. In this paper, we demonstrate the necessity to learn discriminative semantic representations for ZSD, and propose a new end-to-end framework for this task. Our framework is able to learn discriminative semantic representations in an augmented space introduced for both user-defined and latent attributes, and refine the user-defined attributes with the help of unseen and external classes. The proposed method is extensively evaluated on two challenging ZSD datasets, and the experimental results show that our method significantly outperforms several existing methods.

关键词： Visualization Conferences Semantics Object detection Tools Boosting Task analysis

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Variable Selection Method Based on Partial Mutual Information and Its Application to NOx Emission Prediction

Variable Selection Method Based on Partial Mutual Informatio...

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第三十九届中国控制会议

作者： QIN Tianmu ZHANG Jinzhe YOU Mo YANG Tingting North China Electric Power Research Institute Co. Ltd. State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources School of Control and Computer EngineeringNorth China Electric Power University

Data-driven modeling methods are widely used in industrial processes as the foundation of control and *** selection of optimal variable set plays an important role in model *** order to enhance the model prediction accuracy,a partial mutual information(PMI) method was proposed to select the optimal variable *** were used to validate the effectiveness of PMI ***,PMI method was applied to select main influencing factors of NOx emission of coal-fired boiler and the selection results were used as inputs of three different data-driven *** comparison between the models with or without variable selection was *** results showed that the PMI method enhanced the model prediction accuracy and avoided the over-fitting problem.

关键词： NOx emission coal-fired boiler partial mutual information(PMI) data-driven modeling

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Automated IoT based Smart Water Quality Assessment system

Automated IoT based Smart Water Quality Assessment System

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International Conference on system Modeling & Advancement in Research Trends (SMART)

作者： Durgesh Pant Ashutosh Bhatt Muneer Khan O.P. Nautiyal Pankaj Adhikari USERC Dehradun Birla Institute of Applied Sciences Bhimtal Computer Control System Design Laboratory Russia

ISBN: (数字)9781728132457

ISBN: (纸本)9781728132464

The aim of this paper is to develop automated Internet of Things (IoT) based Water Quality monitoring system. The different sensors are used to monitor the different parameters of water. The whole system having Arduino to interface the sensors and GSM module for remotely monitoring the data. This complete system is solar powered. The device is useful for accessing the quality of water. It can monitor the different water bodies in real time. We are presenting a design and development of a cost effective system for real time water monitoring. Also the device can measure other physical and chemical properties of the water. The Apparatus consist of modules Turbidity Sensor, pH sensor, Temperature & TDS Sensor. All sensors are connected with Ardurino. Ardurino converts the signal form into system readable form and send it to GSM module. The GSM Module will send the sensed data to Smart devices/ cloud through IOT platform. The result can be accessed daily/weekly or monthly.

关键词： Internet of Things Total Dissolved Solid Power of Hydrogen (Ph) Global system for Mobile Liquid Crystal Display Internet of things TOTAL DISSOLVED SOLIDS Water Quality LIQUID CRYSTAL DISPLAY Sensors Global mobile communication-systems wireless phone water bodies

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