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IEEE Conference on computer Vision and Pattern Recognition

作者： Lyndsey C. Pickup Zheng Pan Donglai Wei YiChang Shih Changshui Zhang Andrew Zisserman Bernhard Scholkopf William T. Freeman Visual Geometry Group Department of Engineering Science University of Oxford Department of Automation Tsinghua University State Key Lab of Intelligent Technologies and Systems Tsinghua National Laboratory for Information Science and Technology (TNList) Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology Max Planck Institute for Intelligent Systems

ISBN: (纸本)9781479951192

We explore whether we can observe Time's Arrow in a temporal sequence-is it possible to tell whether a video is running forwards or backwards? We investigate this some-what philosophical question using computer vision and machine learning techniques. We explore three methods by which we might detect Time's Arrow in video sequences, based on distinct ways in which motion in video sequences might be asymmetric in time. We demonstrate good video forwards/backwards classification results on a selection of YouTube video clips, and on natively-captured sequences (with no temporally-dependent video compression), and examine what motions the models have learned that help discriminate forwards from backwards time.

关键词： YouTube Training Support vector machines Physics Testing Histograms Visualization

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Network design for distributed consensus estimation over heterogeneous sensor networks

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IFAC Proceedings Volumes 2014年第3期47卷 5550-5555页

作者： Wen Yang Ling Shi Ye Yuan Xiaofan Wang Hongbo Shi Key Laboratory of Advanced Control and Optimization for Chemical Processes (East China University of Science and Technology) Ministry of Education Shanghai 200237 Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong P. R. China Department of Engineering University of Cambridge UK Department of Automation Shanghai Jiaotong University Shanghai 200240

This paper considers distributed estimation over heterogeneous sensor networks. We propose a distributed estimation strategy based on PageRank algorithm, where the link weight depends on the edge estimation covariances. We prove that the proposed estimator obtains better estimates than one typical estimator under identical initial conditions. Motivated by the advantage of the sensors with high accuracy locating at important positions, we propose an optimal sensor deployment strategy to arrange locations for sensors in a given physical network. Numerical examples are provided to demonstrate the effectiveness of the proposed estimator, showing a better performance under the optimal sensor deployment.

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Robust Perturbed Output Regulation and Its Application to Synchronization of Nonlinear Heterogeneous Multi-Agents

Robust Perturbed Output Regulation and Its Application to Sy...

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IEEE Annual Conference on Decision and Control

作者： Xi Chen Zhiyong Chen Hai-Tao Zhang School of Electrical Engineering and Computer Science The University of Newcastle Callaghan NSW 2308 Australia Key Laboratory of Image Processing and Intelligent Control School of Automation and the State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and Technology Wuhan 430074 P.R. China

ISBN: (纸本)9781467360890

The conventional output regulation problem aims to achieve reference tracking and disturbance rejection while references and disturbances are generated by an autonomous exosystem. When the exosystem is perturbed by an external event, a novel robust perturbed output regulation problem is formulated and solved in this paper. The formulation arises from a kind of synchronization problem of multiple agents. Hence, the proposed solution leads to a decentralized control algorithm for synchronization of multiple agents with nonlinear heterogeneous dynamics.

关键词： Output Regulation decentralized control algorithm Disturbance rejection external events computer algorithms

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A unified framework for optimality analysis of model predictive control

A unified framework for optimality analysis of model predict...

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World Congress on Intelligent Control and automation (WCICA)

作者： Xin Cai Shaoyuan Li Ning Li Kang Li Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Shanghai P.R. China Electrical Engineering and Computer Science Queen's University Belfast Belfast UK

As well-known, model predictive control is closely related to optimal control. This paper studies relationships between them and provides a unified framework for optimality analysis of model predictive controllers (MPC). The optimality is evaluated by comparing total performance of MPC with finite and infinite horizon optimal cost. Based on relaxed value iteration method, upper and lower bounds of optimality evaluation functions are expressed explicitly in terms of optimization horizon. These results reveal detailed characteristics on performance of closed-loop MPC systems due to using “receding horizon optimization” implementation style.

关键词： Optimal control Nonlinear systems Cost function Predictive control Predictive models

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A traffic congestion control method in the cyber physical systems

A traffic congestion control method in the cyber physical sy...

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17th International IEEE Conference on Intelligent Transportation Systems & The Asia-Pacific Council on Systems engineering Conference 2014

作者： Di-Hua Sun Tong Zhou Min Zhao Wei-Ning Liu Zhiyong Yang Geng Zhang Hui Liu the Key Laboratory of Dependable Service Computing in Cyber Physical Society of Ministry of Education and College of Automation Chongqing University the College of Information Engineering Chongqing Vocational Institute of Engineering the Key Laboratory of Dependable Service Computing in Cyber Physical Society of Ministry of Education and College of Computer Science Chongqing University

Congestion control is a process to achieve optimal decision-making and effective control of vehicles through the interaction of vehicular perception and control,and it shows the typical characteristic of cyber physical *** on the physical-world model of Konishi et al.,a new control method to suppress the traffic jam is proposed in the feedback cyber physical systems under the open boundary,which considers the effect of safe headway on the traffic system from the perspective of tight conjoining between the transportation cyber system and the transportation physical *** using the Hurwitz stability criteria and the H∞ norm theory,the condition under which the traffic jam can be well suppressed is *** between our method and the previous methods is carried *** simulation results show that the temporal behavior obtained by our method is better than those of the previous control methods,and our control method could be well applied to traffic congestion control in cyber physical *** simulation results are consistent with the theoretical analysis.

关键词： A traffic congestion control method in the cyber physical systems

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Evaluating dataflow vulnerabilities of scientific workflow based on data dependency patterns

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Journal of Computational Information Systems 2013年第12期9卷 4861-4868页

作者： Fu, Xiaodong Liu, Li Feng, Yong Liu, Xiaoyan Zhang, Jing Yunnan Provincial Key Laboratory of Computer Technology Application Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming 650500 China

If potential contributors leading to system failure can be identified when a scientific workflow is modelled, a lot of system vulnerabilities may thus be revealed and improved. In this paper, we first use data dependency patterns to describe dataflow in a scientific workflow. Then, the state function that describes the causal relations leading to incorrect state of an output is presented. We use a series of fault tree symbols to illustrate the state functions. Thus, fault tree analysis method is used to identify critical elements and elements combinations that lead to the incorrect state of any output item and calculate the probability of the incorrect state based on the probabilities of the basic events in the analysed workflow. Finally, an importance measure is designed to prioritize the contributors of system failure. The feasibility and effectiveness of the proposed methods are proved by example and experiments. © 2013 by Binary Information Press.

关键词： Fault tree analysis

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A Feasible Control Strategy for LQG Control Problem with Parameter and Structure Uncertainties

A Feasible Control Strategy for LQG Control Problem with Par...

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International Conference on Computational Intelligence and Security

作者： Guo Xie Dan Zhang Xinhong Hei Fucai Qian School of Automation and Information Engineering Xi'an University of Technology Xi'an China State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University China Beijing China School of Computer Science and Engineering Xi'an University of Technology Xi'an China

ISBN: (纸本)9781479974351

Previous efforts have mainly been made on Linear Quadratic Gaussian (LQG) control problem with parameter uncertainties. However, in practice the change of system environment and parameters usually leads to the change of system structure. On the basis of a receding horizon strategy forth LQG control problem with unknown parameters, this paper provides a solution to LQG control problems which involve both parameter and structure uncertainties. When system parameters are estimated and updated gradually, this method considers the impact of the change of system structure on the performance index. It realizes parameters estimation based on posterior probability by Bayesian theorem, eliminates the correlation between system structures by changing the weighted symmetric matrices, obtains control gain minimizing the performance index and learns the future information at the same time. Finally, simulation results illustrate the effectiveness and accuracy of the proposed method.

关键词： Uncertainty Filtering Performance analysis Optimal control Mathematical model Symmetric matrices Process control

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Automated Sunspot Detection Using Morphological Reconstruction and Adaptive Region Growing Techniques

Automated Sunspot Detection Using Morphological Reconstructi...

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第三十三届中国控制会议

作者： Lan Yu Linhua Deng Song Feng Department of Information Engineering Yunnan Land and Resources Vocational College National Astronomical Observatories/ Yunnan Astronomical Observatory Chinese Academy of Sciences Yunnan Key Laboratory of Computer Technology Application / Faculty of Information Engineering and Automation Kunming University of Science and Technology

ISBN: (纸本)9781479947249

Sunspots are dark areas with respect to their surrounding area because the temperature of sunspot areas is lower than the average temperature of the solar surface. It provides essential information for many aspects of solar physics. A sunspot is composed of umbra and penumbra. It is a prerequisite for studying solar physics and spatial atmosphere to accurately segment and extract sunspot structures. Consequently, we propose an automated detection technique for segmenting and extracting them. The detection procedure is composed of two steps:(1) segmenting and extracting sunspot umbra with morphological reconstruction;(2) detecting and segmenting sunspot penumbra with region growing. For evaluating the accuracy of the detection procedure,we used a high-resolution observation obtained by Solar Optical Telescope onboard Hinode, and other obtained with the Dutch Open Telescope to illustrate the performance. The results demonstrate that our proposed technique is significant effective and accurate, and is suitable for studying the sunspot evolution and their physical phenomena.

关键词： Automated detection,Sunspot umbrae,Sunspot penumbrae,Morphological reconstruction,Adaptive region growing

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Verification of relationship between heart rate and body movement for fatigue estimation

Verification of relationship between heart rate and body mov...

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IEEE International Conference on Industrial Informatics (INDIN)

作者： Jinhua She Hitoshi Nakamura Junya Imani Yasuhiro Ohyama Hiroshi Hashimoto Min Wu School of Information Science and Engineering Hunan Engineering Laboratory for Advanced Control and Intelligent Automation Changsha China School of Computer Science Tokyo University of Technology Hachioji Japan Graduate School of Bionics Tokyo University of Technology Hachioji Japan Master Program of Innovation for Design and Engineering Advanced Institute of Industrial Technology Japan

It is an urgent need to find an objective way to estimate the degree of fatigue of employees. In this study, we designed a monitoring and estimation system for the degree of fatigue. This paper explains a long-term pedaling experiment that we use it to explore the possibility to use only the time sequence data of head movement during pedaling to estimate the fatigue. While we show the possibility for this through experimental data, it is clear that we need to collect more data to establish an estimation method.

关键词： Fatigue Heart rate Estimation Educational institutions Monitoring Correlation Electronic mail

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Unmanned Aerial Vehicles (UAV) Heading Optimal Tracking Control Using Online Kernel-based HDP Algorithm

Unmanned Aerial Vehicles (UAV) Heading Optimal Tracking Cont...

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International Joint Conference on Neural Networks

作者： Fuxiao Tan Derong Liu Xinping Guan Bin Luo School of Computer and Information Fuyang Teachers College State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University School of Computer Science and Technology Anhui University

ISBN: (纸本)9781479914821

UAV can work in places that are dangerous, or not easy to reach for humans. However, due to active control and operating difficulties, it is still a challenge to develop fully autonomous flight in complex environments. This paper applies a novel heuristic dynamic programming for the UAV heading optimal tracking controller design, using kernel-based heuristic dynamic programming (KHDP). Kernel-based HDP is developed by integrating kernel methods and approximately linear dependence (ALD) analysis with the critic learning of HDP algorithm. Compared with conventional HDP where neural networks are widely used and their features were manually designed, the proposed algorithm can obtain better generalization capability and learning efficiency through applying the sparse kernel machine into the critic learning process of HDP algorithm. Simulation and experimental results of UAV heading optimal tracking control problems demonstrate the effectiveness of the proposed kernel-based HDP algorithm.

关键词： Kernel Algorithm design and analysis Heuristic algorithms Equations Vectors Approximation algorithms Mathematical model

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