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American Control Conference

作者： Bin Zhang Yingmin Jia Junping Du Jun Zhang Seventh Research Division and the Department of Systems and Control Beihang University (BUAA) Beijing 100191 China Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia School of Computer Science and Technology Beijing University of Posts and Telecommunications Beijing 100876 China School of Electronic and Information Engineering Beihang University (BUAA) Beijing 100191 China

ISBN: (纸本)9781479901777

This paper is devoted to the finite-time control problem for multiple manipulators, where unmodeled dynamics is taken into consideration. An effective coordinated control strategy is introduced, under which distributed protocols with continuous feedbacks are proposed. By applying the homogeneous theory for stability analysis, it is proven that the multi-robot system can be globally finite-time stabilized through our protocols. Numerical simulations on four manipulators with two degrees of freedom are presented to validate the effectiveness of the control strategy.

关键词： unmodeled dynamics control strategy Manipulators two degrees of freedom multi-robot systems Stability analysis distributed protocol

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State estimation for jump Markov linear systems with uncompensated biases

State estimation for jump Markov linear systems with uncompe...

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American Control Conference

作者： Wenling Li Yingmin Jia Junping Du Jun Zhang Deyuan Meng Seventh Research Division and the Department of Systems and Control Beihang University (BUAA) Beijing 100191 China. Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia School of Computer Science and Technology Beijing University of Posts and Telecommunications Beijing 100876 China School of Electronic and Information Engineering Beihang University (BUAA) Beijing 100191 China

ISBN: (纸本)9781479901777

This paper studies the problem of state estimation for jump Markov linear systems with uncompensated biases. By describing the state and the measurement biases as additive random variables, a suboptimal filter has been developed by applying the basic interacting multiple model (IMM) approach. To derive a precise representation of the biases contributions to the state estimation, three auxiliary matrices are introduced with respect to the correlation between the state estimation errors and the biases, which helps to derive mode-conditioned estimates in the framework of the IMM. A numerical example involving tracking a maneuvering target is provided to compare the performance of the proposed filter with that of the augmented state filter.

关键词： Jump Markov linear system Interacting multiple model Uncompensated bias State estimation Bias uncompensated maneuvering target Linear system interacting boson model Markov jump IMM

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Innovative instruction, assessment & evaluation in programming language concepts 2012

Innovative instruction, assessment & evaluation in programmi...

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2012 IEEE International Conference on Information science and Technology, ICIST 2012

作者： Powers, David M. W. Department of Computer Science School of Computer Science Engineering and Mathematics Flinders University Australia Beijing Municipal Key Laboratory for Multimedia and Intelligent Software Technology Beijing University of Technology China

ISBN: (纸本)9781457703454

This paper describes the development of a course in Programming Concepts over a period of a decade. Initially we present educational principles that underlie the approach, as well as specific and generic aims for this course. We then proceed to show how an integrated program of assessment and instruction has allowed teaching and comparison of multiple programming paradigms and concepts within a common framework. The specifiation of specific and generic skills and the extents to which they are expected to be covered has been closely validated with surveys framed around them. We also address some general issues in modern education. © 2012 IEEE.

关键词： Teaching

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Formation learning algorithms for mobile agents subject to 2-D dynamically changing topologies

Formation learning algorithms for mobile agents subject to 2...

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American Control Conference

作者： Deyuan Meng Yingmin Jia Junping Du Jun Zhang Wenling Li Seventh Research Division and the Department of Systems and Control Beihang University (BUAA) Beijing 100191 P. R. China Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia School of Computer Science and Technology Beijing University of Posts and Telecommunications Beijing 100876 P. R. China School of Electronic and Information Engineering Beihang University (BUAA) Beijing 100191 P. R. China

ISBN: (纸本)9781479901777

In this paper, we consider a two-dimensional (2-D) formation problem for multi-agent systems subject to switching topologies that dynamically change along both a finite time axis and an infinite iteration axis. We present a distributed iterative learning control (ILC) algorithm via the nearest neighbor rules. By employing the 2-D approach, we develop both the asymptotic and exponentially fast convergence of our formation ILC, which can be guaranteed by conditions in terms of the spectral radius and the matrix norms, respectively.

关键词： Multi-agent systems ILC switching topologies formation learning algorithms learning algorithms Multi-agent systems International Labour Conference Mobile agents spectral radius

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Convex and scalable weakly labeled SVMs

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 Yu-Feng Li Ivor W. Tsang James T. Kwok Zhi-Hua Zhou Google MPI for Intelligent Systems National Key Laboratory for Novel Software Technology Nanjing University Nanjing China School of Computer Engineering Nanyang Technological University Singapore Department of Computer Science and Engineering Hong Kong University of Science & Technology Hong Kong

In this paper, we study the problem of learning from weakly labeled data, where labels of the training examples are incomplete. This includes, for example, (i) semi-supervised learning where labels are partially known; (ii) multi-instance learning where labels are implicitly known; and (iii) clustering where labels are completely unknown. Unlike supervised learning, learning with weak labels involves a difficult Mixed-Integer Programming (MIP) problem. Therefore, it can suffer from poor scalability and may also get stuck in local minimum. In this paper, we focus on SVMs and propose the WELLSVM via a novel label generation strategy. This leads to a convex relaxation of the original MIP, which is at least as tight as existing convex Semi-Definite Programming (SDP) relaxations. Moreover, the WELLSVM can be solved via a sequence of SVM subproblems that are much more scalable than previous convex SDP relaxations. Experiments on three weakly labeled learning tasks, namely, (i) semi-supervised learning; (ii) multi-instance learning for locating regions of interest in content-based information retrieval; and (iii) clustering, clearly demonstrate improved performance, and WELLSVM is also readily applicable on large data sets.

关键词： clustering convex relaxation cutting plane multi-instance learning semi-supervised learning weakly labeled data

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Ant colony optimization with multi-agent evolution for detecting functional modules in protein-protein interaction networks

Ant colony optimization with multi-agent evolution for detec...

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3rd International Conference on Information Computing and Applications, ICICA 2012

作者： Ji, Junzhong Liu, Zhijun Zhang, Aidong Jiao, Lang Liu, Chunnian College of Computer Science and Technology Beijing University of Technology Beijing Municipal Key Laboratory of Multimedia and Intelligent Software Technology Beijing 100124 China Department of Computer Science and Engineering University at Buffalo State University of New York Buffalo NY 14260 United States

ISBN: (纸本)9783642340611

Functional module identification in a Protein-Protein Interaction (PPI) network is one of the most important and challenging tasks in computational biology. For detecting functional modules, it is difficult to solve the problem directly and always results in a low accuracy and a large discard rate. In this paper, we present a novel algorithm of ant colony optimization with multi-agent evolution for detecting functional modules. The proposed ACO-MAE algorithm enhances the performance of ant colony optimization (ACO) by incorporating multi-agent evolution (MAE). First, the ant colony optimization for solving Traveling Salesman Problems (TSP) is conducted to construct primary clustering results. Then, the multi-agent evolutionary process is performed to move out of local optima. From simulation results, it is shown that the proposed ACO-MAE algorithm has superior performance when compared to other existing algorithms. © 2012 Springer-Verlag.

关键词： Ant colony optimization

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Reports of the AAAI 2011 fall symposia

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AI Magazine 2012年第1期33卷 71-78页

作者： Blisard, Sam Carmichael, Ted Ding, Li Finin, Tim Frost, Wende Graesser, Arthur Hadzikadic, Mirsad Kagal, Lalana Kruijff, Geert-Jan M. Langley, Pat Lester, James McGuinness, Deborah L. Mostow, Jack Papadakis, Panagiotis Pirri, Fiora Prasad, Rashmi Stoyanchev, Svetlana Varakantham, Pradeep Interactive Systems Section Naval Research Laboratory Washington DC United States Department of Software and Information Systems University of North Carolina Charlotte United States Qualcomm Inc. United States Department of Computer Science and Electrical Engineering University of Maryland Baltimore County United States Department of Psychology Institute of Intelligent Systems University of Memphis United States Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology United States Germany Department of Computer Science and Engineering Arizona State University Tempe AZ United States Department of Computer Science North Carolina State University United States Department of Computer Science and Cognitive Science Rensselaer Polytechnic Institute United States School of Computer Science Carnegie Mellon University United States Department of Informatics and Systems University of Sapienza Rome Italy Department of Informatics and Systems ALCOR Lab University of Sapienza Rome Italy Department of Health Informatics and Administration University of Wisconsin-Milwaukee United States Columbia University United States School of Information Systems Singapore Management University Singapore Singapore

The Association for the Advancement of Artificial Intelligence was pleased to present the 2011 Fall Symposium Series, held Friday through Sunday, November 4-6, at the Westin Arlington Gateway in Arlington, Virginia. The titles of the seven symposia are as follows: (1) Advances in Cognitive Systems;(2) Building Representations of Common Ground with intelligent agents;(3) Complex Adaptive Systems: Energy, Information, and Intelligence;(4) Multiagent Coordination under Uncertainty;(5) Open Government Knowledge: AI Opportunities and Challenges;(6) Question Generation;and (7) Robot-Human Teamwork in Dynamic Adverse Environments. The highlights of each symposium are presented in this report. Copyright © 2012, Association for the Advancement of Artificial Intelligence. All rights reserved.

关键词： intelligent agents

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Spatio-Temporal Adaptive Super-Resolution Reconstruction Model Based on Zemike Moment for Spatial Video Sequences

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China Communications 2012年第12期9卷 93-107页

作者： Liang Meiyu Du Junping JangMyung Lee Liu Honggang Zhang Yun Beijing Key Laboratory of Intelligent Telecommunication Software and Multimedia School of Computer Science Beijing University of Posts and Telecommunications Beijing 100876 P. R. China Department of Electronics Engineering Pusan Nation University Busan Korea

Video Super-Resolution （SR） reconstruction produces video sequences with High Resolution （HR） via the fusion of several Low-Resolution （LR） video frames. Traditional methods rely on the accurate estimation of subpixel motion, which constrains their applicability to video sequences with relatively simple motions such as global translation. We propose an efficient iterative spatio-temporal adaptive SR reconstruction model based on Zemike Moment （ZM）, which is effective for spatial video sequences with arbitrary motion. The model uses region correlation judgment and self-adaptive threshold strategies to improve the effect and time efficiency of the ZM-based SR method. This leads to better mining of non-local self-similarity and local structural regularity, and is robust to noise and rotation. An efficient iterative curvature-based interpolation scheme is introduced to obtain the initial HR estimation of each LR video frame. Experimental results both on spatial and standard video sequences demonstrate that the proposed method outperforms existing methods in terms of both subjective visual and objective quantitative evaluations, and greatly improves the time efficiency.

关键词： video super-resolution fuzzy registration scheme Zemike moment non-local self-similarity self-adaptive threshold

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A novel segmentation method for convex lesions based on dynamic programming with local intra-class variance 12

A novel segmentation method for convex lesions based on dyna...

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27th Annual ACM Symposium on Applied Computing, SAC 2012

作者： Yu, Mali Huang, Qiliang Jin, Renchao Song, Enmin Liu, Hong Hung, Chih-Cheng School of Computer Science Huazhong University of Science and Technology Wuhan China Key Laboratory of Education Ministry for Image Processing and Intelligent Control Wuhan Hubei China Radiology Department Second People's Hospital of Nanning Nanning China School of Computing and Software Engineering Southern Polytechnic State University GA United States

ISBN: (纸本)9781450308571

Lesion segmentation plays an important role in medical image processing and analysis. There exist several successful dynamic programming (DP) based segmentation methods for general images. In those methods, the gradient is used as an important factor in the cost function to attract the contours to the boundaries. Since medical images have their characteristics such as low contrast, blurred edges and high noises, the gradient operator cannot work well enough to achieve a satisfactory performance for boundary detection. We define the local intra-class variance and combine it with the dynamic programming method to replace the traditional gradient operation. Experiments on synthetic and X-ray images are carried out and the results are compared with Canny and fast multilevel fuzzy edge detection (FMFED) algorithms. It is demonstrated that the proposed method performs better on medical images with low contrast, blurred edges and high noises. In addition, 483 regions of interest of mammograms randomly extracted from DDSM of the University of South Florida are used to compare our proposed method with the plane-fitting and dynamic programming method (PFDP), and the normalized cut segmentation method (Ncut). The results demonstrate that our method is more accurate and robust than PFDP and Ncut. © 2012 ACM.

关键词： Dynamic programming

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Scaling Laws of Multicast Capacity for Power-Constrained Wireless Networks under Gaussian Channel Model

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IEEE Transactions on computers 2012年第5期61卷 713-725页

作者： Cheng Wang Changjun Jiang Xiang-Yang Li Shaojie Tang Yuan He Xufei Mao Yunhao Liu Key Laboratory of Embedded System and Service Computing Ministry of Education Shanghai China Department of Computer Science and Engineering Building of Electronics and Information Engineering University of Tongji Shanghai China Department of Computer Science Illinois Institute of Technology Chicago IL USA Tsinghua National Laboratory for Information Science and Technology (TNLIST) Tsinghua University Beijing China Department of Computer Science and Engineering University of Tongji China Department of Computer Science Hong Kong University of Science and Technology Kowloon Hong Kong China Tsinghua National Laboratory for Information Science and Technology (TNLIST) School of Software Tsinghua University Beijing China Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia Beijing University of Posts and Telecommunications Beijing China

We study the asymptotic networking-theoretic multicast capacity bounds for random extended networks (REN) under Gaussian channel model, in which all wireless nodes are individually power-constrained. During the transmission, the power decays along path with attenuation exponent α >; 2. In REN, n nodes are randomly distributed in the square region of side length √n. There are n s randomly and independently chosen multicast sessions. Each multicast session has n d + 1 randomly chosen terminals, including one source and n d destinations. By effectively combining two types of routing and scheduling strategies, we analyze the asymptotic achievable throughput for all n s = ω(1) and nd. As a special case of our results, we show that for n s = Θ(n), the per-session multicast capacity for REN is of order Θ(1/√n d n) when nd = O(n/(log n) a+1 ) and is of order Θ(1/n d · (log n) -n/2 ) when n d = Ω(n/log n).

关键词： Lattices Throughput Upper bound Road transportation Receivers Interference Routing

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