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Chinese Control Conference (CCC)

作者： Yunji Zhao Hailong Pei Baoluo Liu School of Electrical Engineering and Automation Henan Polytechnic University Jiaozuo 454000 China Key Laboratory of Autonomous Systems and Networked Control (South China University of Technology) Ministry of Education Guangzhou 510640 China Department of Computer and Information Engineering Luoyang Institute of Science and Technology Henan 471023 China

Object tracking algorithm based on Meanshift algorithm with fixed kernel bandwidth does not realize object tracking correctly with the scale of object changed. According to this, a scheme of kernel bandwidth adaptive adjustment and predictions of object cancroids based on Kalman filter is proposed in this paper. In this algorithm, Object location predicted based on Kalman filter is used to initialize the Meanshift algorithm. The variation tendency of the kernel bandwidth is also determined based on Kalman filter. Experiment results demonstrate that this algorithm can realize the kernel bandwidth adaptive adjustment and object location prediction. The robustness of the tracking algorithm is also enhanced.

关键词： Prediction algorithms Kalman filters Electronic mail Kernel Bandwidth Robustness Conferences

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Ontology-based support for security requirements specification process

Ontology-based support for security requirements specificati...

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Confederated International Workshops on On the Move to Meaningful Internet systems, OTM 2012: OTM Academy, Industry Case Studies Program, EI2N 2012, INBAST 2012, META4eS 2012, OnToContent 2012, ORM 2012, SeDeS 2012, SINCOM 2012, and SOMOCO 2012

作者： Daramola, Olawande Sindre, Guttorm Moser, Thomas Department of Computer and Information Sciences Covenant University Ota Nigeria Norway Christian Doppler Laboratory for Software Engineering Integration for Flexible Automation Systems Vienna University of Technology Austria

ISBN: (纸本)9783642336171

The security requirements specification (SRS) is an integral aspect of the development of secured information systems and entails the formal documentation of the security needs of a system in a correct and consistent way. However, in many cases there is lack of sufficiently experienced security experts or security requirements (SR) engineer within an organization, which limits the quality of SR that are specified. This paper presents an approach that leverages ontologies and requirements boilerplates in order to alleviate the effect of lack of highly experienced personnel for SRS. It also offers a credible starting point for the SRS process. A preliminary evaluation of the tool prototype - ReqSec tool - was used to demonstrate the approach and to confirm its usability to support the SRS process. The tool helps to reduce the amount of effort required, stimulate discovery of latent security threats, and enables the specification of good quality SR. © 2012 Springer-Verlag.

关键词： Ontology

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Managing implicit requirements using semantic case-based reasoning research preview

Managing implicit requirements using semantic case-based rea...

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18th Working Conference on Requirements Engineering: Foundation for Software Quality, REFSQ 2012

作者： Daramola, Olawande Moser, Thomas Sindre, Guttorm Biffl, Stefan Department of Computer and Information Science Norwegian University of Science and Technology Trondheim Norway Christian Doppler Laboratory for Software Engineering Integration for Flexible Automation Systems Vienna University of Technology Austria

ISBN: (纸本)9783642287138

[Context and motivation] Implicit requirements (ImRs) are defined as requirements of a system which are not explicitly expressed during requirements elicitation, often because they are considered so basic that developers should already know them. Many products have been rejected or users made unhappy because implicit requirements were not sufficiently addressed. [Question/Problem] Requirement management tools have not addressed the issue of managing ImRs, also despite the challenges of managing ImRs that exist in practice the issue has not received sufficient attention in the literature. [Principal Idea/results] This planned research will investigate how automated support can be provided for managing ImRs within an organizational context, which is currently lacking in practice. This work proposed an approach that is based on semantic case-based reasoning for managing ImRs. [Contribution] We present the concept of a tool which enables managing of ImRs through the analogy-based requirements reuse of previously known ImRs. This ensures the discovery, structured documentation, proper prioritization, and evolution of ImRs, which improves the overall success of software development processes. © 2012 Springer-Verlag.

关键词： Case based reasoning

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Sketch-based interface for creation and visual representation of hyper videos

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Ruan Jian Xue Bao/Journal of Software 2013年第SUPPL.2期24卷 32-41页

作者： Du, Yi Lü, Fei Tian, Feng Hou, Wen-Jun Ma, Cui-Xia Dai, Guo-Zhong Scientific Data Center Computer Network Information Center The Chinese Academy of Sciences Beijing 100190 China Beijing Key Laboratory of Human-Computer Interaction Institute of Software Chinese Academy of Sciences Beijing 100190 China Beijing Key Laboratory of Network Systems and Network Culture Beijing University of Posts and Telecommunications Beijing 100876 China Automation School Beijing University of Posts and Telecommunications Beijing 100876 China

Due to its nonlinear potential, hyper video offers improvement in users' browsing efficiency and visual information's representation ability compared with that of traditional video. Based on the advantages of sketch and sketch based interface, this paper provides an intuitive sketch based interface for supporting hyper video creation to describe users' intention and improve user experiences. Furthermore, a force-directed graph layout algorithm for representing video semantics is discussed. This algorithm constructs a model for video semantics. It brings attributions such as temporal or spatial information, video structure and constraints between video clips into mass of nodes and attractive forces or repulsive force of edges in the force-directed graph. Result shows that it is an intuitive method to represent the dynamitic process of creation and modification for hyper videos. © Institute of Software Chinese Academy of Sciences.

关键词： Directed graphs

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Multi-stage multi-task feature learning

The Journal of Machine Learning Research

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The Journal of Machine Learning Research 2013年第1期14卷

作者： Kevin Murphy Bernhard Schölkopf Pinghua Gong Jieping Ye Changshui Zhang Google MPI for Intelligent Systems State Key Laboratory on Intelligent Technology and Systems Tsinghua National Laboratory for Information Science and Technology Department of Automation Tsinghua University Beijing China Computer Science and Engineering Center for Evolutionary Medicine and Informatics The Biodesign Institute Arizona State University Tempe AZ

Multi-task sparse feature learning aims to improve the generalization performance by exploiting the shared features among tasks. It has been successfully applied to many applications including computer vision and biomedical informatics. Most of the existing multi-task sparse feature learning algorithms are formulated as a convex sparse regularization problem, which is usually suboptimal, due to its looseness for approximating an l0-type regularizer. In this paper, we propose a non-convex formulation for multi-task sparse feature learning based on a novel nonconvex regularizer. To solve the non-convex optimization problem, we propose a Multi-Stage Multi-Task Feature Learning (MSMTFL) algorithm; we also provide intuitive interpretations, detailed convergence and reproducibility analysis for the proposed algorithm. Moreover, we present a detailed theoretical analysis showing that MSMTFL achieves a better parameter estimation error bound than the convex formulation. Empirical studies on both synthetic and real-world data sets demonstrate the effectiveness of MSMTFL in comparison with the state of the art multi-task sparse feature learning algorithms.

关键词： multi-stage multi-task learning non-convex sparse learning

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Modified Iterative-Learning-Control-Based Ramp Metering Strategies for Freeway Traffic Control With Iteration-Dependent Factors

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IEEE Transactions on Intelligent Transportation systems 2012年第2期13卷 606-618页

作者： Zhongsheng Hou Jingwen Yan Jian-Xin Xu Zhenjiang Li Advanced Control Systems Laboratory of School of Electronic and Information Engineering Beijing Jiaotong University Beijing China Department of Electrical and Computer Engineering National University of Singapore Singapore Key Laboratory of Complex Systems and Intelligence Science Institute of Automation Chinese Academy of Sciences Beijing China

For a freeway traffic system with strict repeatable pattern, iterative learning control (ILC) has been successfully applied to local ramp metering for a macroscopic freeway environment by formulating the original ramp metering problem as an output tracking, disturbance rejection, and error compensation problem. In this paper, we address the freeway traffic ramp-metering system under a nonstrict repeatable pattern. ILC-based ramp metering and ILC add-on to ALINEA strategies are modified to deal with the presence of iteration-dependent parameters, iteration-dependent desired trajectory, and input constraints. Theoretical analysis and extensive simulations are used to verify the effectiveness of the proposed approaches.

关键词： Traffic control Trajectory Mathematical model Vehicles Equations Feedback control

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Human Behavior Imitation for a Robot to Play Table Tennis

Human Behavior Imitation for a Robot to Play Table Tennis

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The 24th Chinese Control and Decision Conference (第24届中国控制与决策学术年会 2012 CCDC)

作者： Qizhi Wang Xianqiang Zhang De Xu School of Computer and Information Technology Beijing Jiaotong University Beijing 100044 PR Chin State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese

The main purpose of this paper is to make table tennis robots complete the hit table tennis ball action by imitating human’s behavior. The main strategy is to record a video of action which people played the table tennis, then analysis the video of the racket trajectory. The racket in the image is extracted by image processing when the each frame is captured in the video. Then three-dimensional coordinates of the center of the racket and racket posture are obtained via PnP positioning approach based on the intrinsic parameters of the camera. The table tennis robot will off-line learn to complete the imitation of basic actions of the racket trajectory and postures. A large number of experimental data is used to establish basic actions of table tennis robot.

关键词： Imitation off-line learning the trajectory of the racket table tennis robot PnP positioning method

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Shared control teleoperation for targets acquisition

Shared control teleoperation for targets acquisition

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Chinese Control and Decision Conference, CCDC

作者： Dongli Wang Huaping Liu Fuchun Sun Yonggui Du Automation college of information engineering Taiyuan university of technology 030024 china Tsinghua national laboratory for information science and technology state key laboratory of intelligent technology and systems department of computer science and technology tsinghua university Beijing 100084 china

It is very difficult to capture the target in the microgravity environment, simply by relying on ground operators. Based on shared control theory, this paper effectively combines the decision-making ability of ground operators and the independent ability of space robot, through making full use of independent control ability of the space robot, and reducing operators' workload and working time, to achieve more valid capture for targets. Shared control is more accurate capture of the target compared with teleoperation in experimental.

关键词： Aerospace electronics Robot kinematics Grippers Control systems Solid modeling Heuristic algorithms

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Doubly selective channel estimation for amplify-and-forward relay networks

Doubly selective channel estimation for amplify-and-forward ...

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IEEE Conference on Wireless Communications and Networking

作者： Gongpu Wang Feifei Gao Jiaru Lin Chintha Tellambura School of Computer and Information Technology Beijing Jiaotong University China National Mobile Communications Research Laboratory South East University Nanjing China State Key Laboratory of Intelligent Technology and Systems Tsinghua National Laboratory for Information Science and Technology Department of Automation Tsinghua University Beijing China Key Laboratory of Universal Wireless Communications Ministry of Education China Department of Electrical and Computer Engineering University of Alberta Edmonton Canada

In this paper, the estimation of doubly selective channel is considered for amplify-and-forward (AF) relay networks. The complex exponential basis expansion model (CE-BEM) is chosen to describe the time-varying channel, from which the infinite channel parameters are mapped onto finite ones. Since direct estimation of these coefficients encounters high computational complexity and large spectral cost, we develop an efficient estimator targeting at some specially defined channel parameters. The training sequence design that can minimize the channel estimation mean-square error is also proposed.

关键词： Training Channel estimation Relays Wireless communication Educational institutions Estimation Vectors

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Multi-Stage Multi-Task Feature Learning* 12

Multi-Stage Multi-Task Feature Learning*

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Annual Conference on Neural information Processing systems

作者： Pinghua Gong Jieping Ye Changshui Zhang State Key Laboratory on Intelligent Technology and Systems Tsinghua National Laboratory for Information Science and Technology (TNList) Department of Automation Tsinghua University Beijing 100084 China Computer Science and Engineering Center for Evolutionary Medicine and Informatics The Biodesign Institute Arizona State University Tempe AZ 85287 USA

ISBN: (纸本)9781627480031

Multi-task sparse feature learning aims to improve the generalization performance by exploiting the shared features among tasks. It has been successfully applied to many applications including computer vision and biomedical informatics. Most of the existing multi-task sparse feature learning algorithms are formulated as a convex sparse regularization problem, which is usually suboptimal, due to its looseness for approximating an ?_0o-type regularizer. In this paper, we propose a non-convex formulation for multi-task sparse feature learning based on a novel regularizer. To solve the non-convex optimization problem, we propose a Multistage Multi-Task Feature Learning (MSMTFL) algorithm. Moreover, we present a detailed theoretical analysis showing that MSMTFL achieves a better parameter estimation error bound than the convex formulation. Empirical studies on both synthetic and real-world data sets demonstrate the effectiveness of MSMTFL in comparison with the state of the art multi-task sparse feature learning algorithms.

关键词： Learning learning algorithms Non-Convex Biomedical informatics Theoretical analysis Parameter estimation images computer vision state of the art Dataset Convexity Religious Missions SYNTHETICS

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