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2016年IEEE/INFORMS服务运筹、物流与信息化国际会议

作者： Sifeng.Jing Xiwei.Liu Chuanzhong.Xu Institute of Smart Education Systems Qingdao Academy of Intelligent Industries The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Refinery No.2 Petro China Fushun Petrochemical Company

past chemical industry accident cases include volume valuable information like precursor, equipment involved, relevant causes and experiences of emergence response. In-depth analysis and fully utilization of these information play an important decision-making role in controlling risk and enhancing safety performance in chemical industry. In this work, a survey of use of accident data is conducted around the world and the result shows that the detailed use of these information play an important role in preventing accidents. However, in china there much more needs to be done in the application of accident data. According to the needs of safety management of chemical plants, a simple and effective method of the use of chemical accident cases is proposed based on collecting and analyzing of a large number of chemical accident cases. And finally, a utilization system of chemical industry accident cases is implemented through Microsoft access 2010. The result shows that the system can realize the effective management and use of past chemical accident information.

关键词： chemical accident cases use of information database fuzzy query chemical safety performance

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Two Intersections Traffic Signal Control Method Based on ADHDP

Two Intersections Traffic Signal Control Method Based on ADH...

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2016年IEEE汽车电子与安全国际会议

作者： Lin Cao Bin Hu Xisong Dong Gang Xiong Fenghua Zhu Zhen Shen Dong Shen Yuliang Liu 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 Institute of Smart Education Systems Qingdao Academy of Intelligent Industries Dongguan Research Institute of CASIA Cloud Computing CenterChinese Academy of Sciences Beijing Engineering Research Center of Intelligent Systems and Technology Institute of AutomationChinese Academy of Sciences

With the rapid development of Chinese economy and automotive industry,urban traffic congestion has become increasingly ***,how to effectively alleviate the traffic congestion and improve the efficiency of vehicles has become the main *** signal control is one of the effective ways to solve urban traffic *** this paper,a traffic signal control method based on Action-Dependent Heuristic Dynamic Programming(ADHDP) is *** control algorithm is simulated on two intersections,both of which have two phases with four entrance *** computer simulation results show that the control method has the better ability of on-line learning compared with traditional Fix-Time Control,and can effectively improve the average speed of vehicles,and reduce travel time and alleviate the traffic pressure.

关键词： ADHDP Traffic Signal Control Adaptive Control intelligent Transportation systems

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An overview of recent progress in high-order nonholonomic chained system control and distributed coordination

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Journal of Control and Decision 2015年第1期2卷 64-85页

作者： Jie Huang Jie Chen Hao Fang Lihua Dou School of Automation Beijing Institute of TechnologyBeijingChina State Key Laboratory of Intelligent Control and Decision of Complex Systems BeijingChina Fujian Institute of Education FuzhouChina

This paper reviews some main results and progress concerning with nonholonomic system control,especially focusing on the networked chained system *** controllability of nonholonomic system,the control method of nonholonomic system,the chained form transformation,the basic graph theory for multi-agent systems are recalled,*** important definitions,lemmas,theorems and dynamics are *** the consensus and formation control problems for networked nonholonomic chained systems are ***,some open questions are proposed.

关键词： distributed coordination multi-agent system nonholonomic system chained system high-order

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A process simulation-based quantitative HAZOP analysis method

A process simulation-based quantitative HAZOP analysis metho...

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IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI

作者： Jianlong Chen Xiwei Liu Sifeng Jing Gang Xiong Xiuqin Shang Changjian Cheng The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Chemical Engineering and the Environment Beijing Institute of Technology Beijing China Institute of Smart Education Systems Qingdao Academy of Intelligent Industries Qingdao China Cloud Computing Center Chinese Academy of Sciences Dongguan China Beijing Engineering Research Center for Intelligent Systems and Technology Chinese Academy of Science Beijing China

ISBN: (纸本)9781509029280

Hazard and operability (HAZOP) methodology is an important Process Hazard Analysis (PHA) technique for ensuring safety production in chemical industry. Due to the lacks of accuracy and reliability in manual HAZOP analysis, the quantitative HAZOP analysis has gained more and more attention. In this work, a process simulation-based HAZOP analysis method and its flow chart are proposed. And the proposed method is applied to a steam generation subsystem in an ethylene pyrolysis unit on a dynamic process simulation platform. All deviation parameters of system can be calculated and described quantitatively. The case study shows the proposed method is useful for the effective risk prevention and control measures in a chemical process.

关键词： Analytical models Hazards Manuals Process control Boilers

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Suspicious face detection based on key frame recognition under surveillance video

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2016年 9712 LNCS卷 645-652页

作者： Zheng, Xiaohui Ning, Yi Chen, Xianjun Zhan, Yongsong Guangxi Colleges and Universities Key Laboratory of Intelligent Processing of Computer Image and Graphics Guilin University of Electronic Technology GuilinGuangxi541004 China Guangxi Experiment Center of Information Science Guilin University of Electronic Technology GuilinGuangxi541004 China Guangxi Colleges and Universities Key Laboratory of Cloud Computing and Complex Systems Guilin University of Electronic Technology GuilinGuangxi541004 China Guangxi Key Laboratory of Trusted Software Guilin University of Electronic Technology GuilinGuangxi541004 China

ISBN: (纸本)9783319409993

Surveillance video is characterized by large amount of data and redundancy, which makes the suspicious face detection to be a problem. To solve the problem above we proposed suspicious face detection based on key frame. Surveillance video has the type of fixed background, so this paper used the frame difference method with low computational complexity and small computation to extract the key frame. We proposed a new method combined DPM with skin color detection to detect the suspicious face in the key frames. To solve the speed bottleneck of the traditional DPM, we proposed to use the fast HOG LUT feature extraction and the near optimal cost sensitive decision making improving the traditional method. Meanwhile we used YCrCb + otsu skin color segmentation. Since the otsu is easily affected by the illumination, we proposed an improved skin color detection. Experiment results show that the proposed algorithms are robust and accurate for real-time. © Springer International Publishing Switzerland 2016.

关键词： Face recognition

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Author Correction: BigNeuron: a resource to benchmark and predict performance of algorithms for automated tracing of neurons in light microscopy datasets

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Nature methods 2024年第10期21卷 1959页

作者： Linus Manubens-Gil Zhi Zhou Hanbo Chen Arvind Ramanathan Xiaoxiao Liu Yufeng Liu Alessandro Bria Todd Gillette Zongcai Ruan Jian Yang Miroslav Radojević Ting Zhao Li Cheng Lei Qu Siqi Liu Kristofer E Bouchard Lin Gu Weidong Cai Shuiwang Ji Badrinath Roysam Ching-Wei Wang Hongchuan Yu Amos Sironi Daniel Maxim Iascone Jie Zhou Erhan Bas Eduardo Conde-Sousa Paulo Aguiar Xiang Li Yujie Li Sumit Nanda Yuan Wang Leila Muresan Pascal Fua Bing Ye Hai-Yan He Jochen F Staiger Manuel Peter Daniel N Cox Michel Simonneau Marcel Oberlaender Gregory Jefferis Kei Ito Paloma Gonzalez-Bellido Jinhyun Kim Edwin Rubel Hollis T Cline Hongkui Zeng Aljoscha Nern Ann-Shyn Chiang Jianhua Yao Jane Roskams Rick Livesey Janine Stevens Tianming Liu Chinh Dang Yike Guo Ning Zhong Georgia Tourassi Sean Hill Michael Hawrylycz Christof Koch Erik Meijering Giorgio A Ascoli Hanchuan Peng Institute for Brain and Intelligence Southeast University Nanjing China. Microsoft Corporation Redmond WA USA. Tencent AI Lab Bellevue WA USA. Computing Environment and Life Sciences Directorate Argonne National Laboratory Lemont IL USA. Kaya Medical Seattle WA USA. University of Cassino and Southern Lazio Cassino Italy. Center for Neural Informatics Structures and Plasticity Krasnow Institute for Advanced Study George Mason University Fairfax VA USA. Faculty of Information Technology Beijing University of Technology Beijing China. Beijing International Collaboration Base on Brain Informatics and Wisdom Services Beijing China. Nuctech Netherlands Rotterdam the Netherlands. Janelia Research Campus Howard Hughes Medical Institute Ashburn VA USA. Department of Electrical and Computer Engineering University of Alberta Edmonton Alberta Canada. Ministry of Education Key Laboratory of Intelligent Computation and Signal Processing Anhui University Hefei China. Paige AI New York NY USA. Scientific Data Division and Biological Systems and Engineering Division Lawrence Berkeley National Lab Berkeley CA USA. Helen Wills Neuroscience Institute and Redwood Center for Theoretical Neuroscience UC Berkeley Berkeley CA USA. RIKEN AIP Tokyo Japan. Research Center for Advanced Science and Technology (RCAST) The University of Tokyo Tokyo Japan. School of Computer Science University of Sydney Sydney New South Wales Australia. Texas A&M University College Station TX USA. Cullen College of Engineering University of Houston Houston TX USA. Graduate Institute of Biomedical Engineering National Taiwan University of Science and Technology Taipei Taiwan. National Centre for Computer Animation Bournemouth University Poole UK. PROPHESEE Paris France. Department of Neuroscience Columbia University New York NY USA. Mortimer B. Zuckerman Mind Brain Behavior Institute Columbia University New York NY USA. Department of Computer Science Northern Illinois Universit

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Security-aware Signal Packing Algorithm for CAN-based Automotive Cyber-physical systems

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IEEE/CAA Journal of Automatica Sinica 2015年第4期2卷 422-430页

作者： Yong Xie Liangjiao Liu Renfa Li Jianqiang Hu Yong Han Xin Peng Key Laboratory for Application Technology of Internet of Things of Fujian Educational Bureau Xiamen University of Technology Key Laboratory of Embedded and Networking Computing of Hunan Province Hunan University Key Laboratory on Complex Systems Optimization & Controlling of Hunan High Education Institutions Hunan Institute of Science and Technology

Network and software integration pose severe challenges in cyber-security for controller area network (CAN)-based automotive cyber-physical system (ACPS), therefore we employ message authentication code (MAC) to defend CAN against masquerade attack, but the consequent bandwidth overhead makes it a necessity to find the tradeoff among security, real-time and bandwidth utilization for signal packing problem (SPP) of CAN. A mixed-security signal model is firstly proposed to formally describe the properties and requirements on security and real-time for signals, and then a mixed-integer linear programming (MILP) formulation of SPP security-aware signal packing (SASP) is implemented to solve the tradeoff problem, where the bandwidth utilization is improved and the requirements in both security and real-time are met. Experiments based on both society of automotive engineers (SAE) standard signal set and simulated signal set showed the effectiveness of SASP by comparing with the state-of-the-art algorithm. © 2014 Chinese Association of Automation.

关键词： Algorithms Bandwidth Communication channels (information theory) Control system synthesis Embedded systems Integer programming

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Event-based state estimation of discrete-state hidden Markov models

Event-based state estimation of discrete-state hidden Markov...

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作者： Shi, Dawei Elliott, Robert J. Chen, Tongwen State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China School of Mathematical Sciences University of Adelaide SA5005 Australia Haskayne School of Business University of Calgary CalgaryAB Canada Department of Electrical and Computer Engineering University of Alberta EdmontonABT6G 1H9 Canada

The state estimation problem for hidden Markov models subject to event-based sensor measurement updates is considered in this work, using the change of probability approach. We assume the measurement updates are transmitted through wired or wireless communication networks. For the scenarios with reliable and unreliable communication channels, analytical expressions for the probability distributions of the states conditioned on all the past point- and set-valued measurement information are obtained. Also, we show that the scenario with a lossy channel, but without the event-trigger, can be treated as a special case of the reliable channel results. Based on these results, closed-form expressions for the estimated communication rates under the original probability measure are presented, which are shown to be the ratio between a weighted 1-norm and the 1-norm of the unnormalized conditional probability distributions of the states under the new probability measures constructed. Implementation issues are discussed, and the effectiveness of the results is illustrated by numerical examples and comparative simulations. © 2015 Elsevier Ltd. All rights reserved.

关键词： Hidden Markov models

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A kind of adaptive dynamic transit signal priority control method

A kind of adaptive dynamic transit signal priority control m...

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World Congress on intelligent Control and Automation (WCICA)

作者： Xisong Dong Gang Xiong Wenwen Kang Fenghua Zhu State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing CO China Cloud Computing Center Chinese Academy of Sciences Dongguan CO China Qingdao Academy of Intelligent Industries Qingdao CO China Chinese Academy of Sciences Institute of Automation Beijing CO China

ISBN: (纸本)9781467384155

Transit signal priority (TSP) is the most effective method to improve the operational efficiency of public transports. This paper presents an adaptive dynamic TSP control method of public traffic, by adjusting the signal time to give buses passing priority at intersections, which can take into account not only the dynamic time of bus's reaching the intersections according to the actual road conditions, but also the benefit balance of priority and non-priority vehicles. This control method has been successfully piloted in BRT Line 1 in Guangzhou, China. The average BRT vehicles' travel time under each signal priority operation is reduced by about 34 seconds, and the average delay time is decreased about 10% while it causes only acceptable negative impact on non-priority social vehicles. These pilot results demonstrate the validity and effectiveness of the control algorithm.

关键词： Vehicles Vehicle dynamics Roads Automation Delays Green products Detectors

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Exploiting structural similarity of log files in fault diagnosis for Web service composition

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CAAI Transactions on Intelligence Technology 2016年第1期1卷 61-71页

作者： Xu Han Binyang Li Kam-Fai Wong Zhongzhi Shi Beijing Key Laboratory of Electronic System Reliability Technology Capital Normal University Beijing China University of International Relations Beijing China Department of Systems Engineering & Engineering Management The Chinese University of Hong Kong Hong Kong China The Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China

With increasing deployment of Web services, the research on the dependability and availability of Web service composition becomes more and more active. Since unexpected faults of Web service composition may occur in different levels at runtime, log analysis as a typical data- driven approach for fault diagnosis is more applicable and scalable in various architectures. Considering the trend that more and more service logs are represented using XML or JSON format which has good flexibility and interoperability, fault classification problem of semi-structured logs is considered as a challenging issue in this area. However, most existing approaches focus on the log content analysis but ignore the structural information and lead to poor performance. To improve the accuracy of fault classification, we exploit structural similarity of log files and propose a similarity based Bayesian learning approach for semi-structured logs in this paper. Our solution estimates degrees of similarity among structural elements from heterogeneous log data, constructs combined Bayesian network （CBN）, uses similarity based learning algorithm to compute probabilities in CBN, and classifies test log data into most probable fault categories based on the generated CBN. Experimental results show that our approach outperforms other learning approaches on structural log datasets.

关键词： Web services composition Fault diagnosis Combined Bayesian network （CBN） Similarity Probability

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