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International Conference on Software engineering (ICSE)

作者： Xiangyu Zhang Mengxiang Lin Kai Yu School of Computer Science and Engineering State Key Laboratory of Software Development Environment Beihang University Beijing China School of Mechanical Engineering and Automation State Key Laboratory of Software Development Environment Beihang University Beijing China

ISBN: (纸本)9781467310673

Software debugging starts with bug reports. Test engineers confirm bugs and determine the corresponding developers to fix them. However, the analysis of bug reports is time-consuming and manual inspection is difficult and tedious. To improve the efficiency of the whole process, we propose a bug processing framework that integrates bug report analysis and fault localization. An instance of the framework is implemented for regression faults. Preliminary results on a large open source application demonstrate both efficiency and effectiveness.

关键词： Debugging Data mining Educational institutions Software computer bugs Isolators Google

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{\cal U}Boost: Boosting with the Universum

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IEEE Transactions on Pattern Analysis and Machine Intelligence 2012年第4期34卷 825-832页

作者： Chunhua Shen Peng Wang Fumin Shen Hanzi Wang Australian Center for Visual Technologies and School of Computer Science University of Adelaide North Terrace SA Australia School of Automation Science and Electrical Engineering Beihang University Beijing China School of Computer Science and Technology Nanjing University of Science and Technology of PLA Nanjing China Cognitive Science Department School of Information Science and Technology and Fujian Key Laboratory of the Brain-like Intelligent Systems Xiamen University Xiamen Fujian China School of Computer Science University of Adelaide SA Australia

It has been shown that the Universum data, which do not belong to either class of the classification problem of interest, may contain useful prior domain knowledge for training a classifier [1], [2]. In this work, we design a novel boosting algorithm that takes advantage of the available Universum data, hence the name UBoost. UBoost is a boosting implementation of Vapnik's alternative capacity concept to the large margin approach. In addition to the standard regularization term, UBoost also controls the learned model's capacity by maximizing the number of observed contradictions. Our experiments demonstrate that UBoost can deliver improved classification accuracy over standard boosting algorithms that use labeled data alone.

关键词： Boosting Training Educational institutions Optimization Algorithm design and analysis Histograms Accuracy

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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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ZHENG classification in Traditional Chinese Medicine based on modified specular-free tongue images

ZHENG classification in Traditional Chinese Medicine based o...

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IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW)

作者： Ratchadaporn Kanawong Tayo Obafemi-Ajayi Jun Yu Dong Xu Shao Li Ye Duan Computer Science Department and Informatics Institute University of Missouri Columbia MO USA College of Automation Engineering Qingdao University China MOE Key Laboratory of Bioinformatics and Bioinformatics Division TNLIST and Department of Automation Tsinghua University Beijing China

ISBN: (纸本)9781467327466

Traditional Chinese Medicine practitioners usually observe the color and coating of a patient's tongue to determine ZHENG (such as Cold or Hot ZHENG) and to diagnose different stomach disorders including gastritis. In our previous work, we explored new modalities for clinical characterization of ZHENG in gastritis patients via tongue image analysis using various supervised machine-learning algorithms. We proposed a system that learns from the clinical practitioner's subjective data how to classify a patients health status by extracting meaningful features from tongue images based on color-space models. In this paper, we propose an enhancement to the ZHENG classification system: a coating separation technique using the MSF images such that feature extraction is applied only to the coated region on the tongue surface. The results obtained over a set of 263 gastritis patients (most of whom are either Cold Zheng or Hot ZHENG), and a control group of 48 healthy volunteers demonstrate an improved performance for most of the classification types considered.

关键词： Tongue Image color analysis Feature extraction Standards Coatings Reflection Biomedical imaging

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Task-based Grasp Adaptation on a Humanoid Robot

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IFAC Proceedings Volumes 2012年第22期45卷 779-786页

作者： Jeannette Bohg Kai Welke Beatriz León Martin Do Dan Song Walter Wohlkinger Marianna Madry Aitor Aldóma Markus Przybylski Tamim Asfour Higinio Martí Danica Kragic Antonio Morales Markus Vincze Humanoids and Intelligence Systems Lab Institute for Anthropomatics KIT DE Autonomous Motion Lab MPI for Intelligent Systems DE Robotic Intelligence Laboratory Department of Computer Science and Engineering UJI ES Computer Vision and Active Perception lab KTH SE Automation and Control Institute TUW AT

In this paper, we present an approach towards autonomous grasping of objects according to their category and a given task. Recent advances in the field of object segmentation and categorization as well as task-based grasp inference have been leveraged by integrating them into one pipeline. This allows us to transfer task-specific grasp experience between objects of the same category. The effectiveness of the approach is demonstrated on the humanoid robot ARMAR-IIIa.

关键词： Robotic Grasping and Manipulation Task-based Grasp Synthesis Visual Servoing Attention Segmentation Object categorization System Integration

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An Embedded Co-AdaBoost and Its Application in Classification of Software Document Relation

An Embedded Co-AdaBoost and Its Application in Classificatio...

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International Conference on Semantics, Knowledge and Grid (SKG)

作者： Jin Liu Juan Li Yuan Xie Jeff Lei Qiping Hu State Key Laboratory of Software Engineering Computer School Wuhan University China State Key Laboratory of Intelligent Control and Management of Complex Systems Institute of Automation CAS China Department of Computer Science and Engineering University of Texas Arlington USA International School of Software Wuhan University China

To enhance classification performance by making use of easily available unlabelled data to overcome the scarcity of labelled data, this paper proposes an Embedded Co-Adaboost algorithm that integrates multi-view learning into the Adaboost learning framework and at the same time leverages the advantages of Co-training algorithm for performance enhancement. Experimental results demonstrate the effectiveness of the proposed algorithm in terms of the convergence rate, the accuracy, and the steady performance as compared to the original AdaBoost algorithm, without relying on redundant and sufficient feature sets. As a algorithm application in software engineering, the Embedded Co-AdaBoost has been applied to the classification of software document relations to improve the quality of the architecture design documents and the reusability of design knowledge.

关键词： Classification algorithms Training Software Accuracy Partitioning algorithms Software algorithms Convergence

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Design of multiple anti-windup loops for multiple activations

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science China(Information sciences) 2012年第9期55卷 1925-1934页

作者： WU XiongJun 1,2 & LIN Zongli 3,1 1 Department of automation,Shanghai Jiao Tong University,and Key laboratory of System Control and Information Processing,Ministry of Education of China,Shanghai 200240,China 2 No.802 Institute of Shanghai Academy of Space Flight Technology,the Eighth Academy of China Aerospace science and Technology Corporation,Shanghai 200090,China 3 Charles L.Brown Department of Electrical and computer engineering,University of Virginia,P.O.Box 400743,Charlottesville,VA 22904-4743,USA 1. Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 China2. No. 802 Institute of Shanghai Academy of Space Flight Technology the Eighth Academy of China Aerospace Science and Technology Corporation Shanghai 200090 China3. Charles L. Brown Department of Electrical and Computer Engineering University of Virginia P.O. Box 400743 Charlottesville VA 22904-4743 USA

This paper considers anti-windup design for linear systems subject to actuator *** anti-windup gains are designed for activations immediately at the occurrence actuator saturation,after the saturation has reached a certain level and in anticipation of the occurrence of saturation,*** design is based on the minimization of L 2 gain from the disturbance to the controlled output of the resulting closed-loop *** anti-windup scheme involves a single anti-windup loop for immediate activation.A recent innovation is to design a single anti-windup loop for delayed or anticipatory activation,as well as to design two anti-windup gains,one for immediate activation and one for delayed *** design of three anti-windup gains for three different activations is shown through simulation to lead to significant further performance improvement over the previous activation schemes.

关键词： actuator saturation anti-windup anticipatory activation delayed activation L 2 gain nonlinear control

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Development of Prosthesis Grasp Control Systems on a Robotic Testbed

Development of Prosthesis Grasp Control Systems on a Robotic...

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IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics

作者： Bart Peerdeman Ugo Fabrizi Gianluca Palli Claudio Melchiorri Stefano Stramigioli Sarthak Misra MIRA - Institute for Biomedical Technology and Technical Medicine (Control Engineering Group) University of Twente LAR DEIS - Laboratory of Automation and Robotics Department of Electronics Computer Science and Systems University of Bologna

ISBN: (纸本)9781457711992

Modern myoelectric hand prostheses continue to increase in functionality, while their control is constrained by the limits of myoelectric input. This paper covers the development and testing of grasp control systems for multifunctional myoelectric prosthetic hands. The functionality of modern hand prostheses is often focused on the task of grasping, which can be divided into high-level grasp planning and low-level finger control. Initially, models can used to test these control systems, but for proper evaluation actual implementation on a physical system is required. The University of Bologna (UB) Hand IV prototype is an anthropomorphic, tendon-driven robotic hand, which makes it well-suited to represent the structure of modern prostheses. One of the main control systems tested in this paper is based on the intrinsically passive controller (IPC), the structure of which offers guaranteed passivity and stability. After several grasping tests, the systems are evaluated on compliant behavior, grasping ability, and dynamic appearance. IPC proves to be a powerful approach to interaction control, without the associated sensor requirements which could be difficult to meet in modern hand prostheses.

关键词： Grasp control systems Prosthetic hand Prosthesis robotic hand

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Improved genetic algorithm for magnetic material two-stage multi-product production scheduling: A case study

Improved genetic algorithm for magnetic material two-stage m...

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IEEE Conference on Decision and Control

作者： Yefeng Liu Tianyou Chai S. Joe Qin Quanke Pan Shengxiang Yang State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang China School of Engineering University of Southern California USA Department of Computer Science University of Leicester Leicester UK

ISBN: (纸本)9781467320658

In this paper an improved genetic algorithm (GA) was present for magnetic material two-stage, multi-product, production scheduling problem (TMPS) with parallel machines. TMPS was changed into molding-stage's multi-product production scheduling problem (MMPS) and the scheduling model was set up for the first time. A set of random solutions were explored first, better feasible solutions were obtained by GA. To shorten the solving time and improve solution accuracy, an improved GA was proposed. We improved GA's crossover operator, adopted heuristic greedy 3PM crossover operator (HG3PMCO) to reduce GA's computational time. Through contrast of computational results of MILP, general GA and improved GA, the improved GA has demonstrated its effectiveness and reliability in solving the molding sintering production scheduling problems and the MILP model set up for the first time is reasonable. At last, the improved genetic algorithm was used in molding stage and sintering stage TMPS of magnetic material.

关键词： Genetic algorithms Job shop scheduling Magnetic materials Biological cells Sociology

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Almost optimal accessing of nonstochastic channels in cognitive radio networks

Almost optimal accessing of nonstochastic channels in cognit...

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IEEE Annual Joint Conference: INFOCOM, IEEE computer and Communications Societies

作者： Xiang-Yang Li PanLong Yang Yubo Yan LiZhao You Shaojie Tang QiuYuan Huang Department of Computer Science Illinois Institute of Technology Chicago IL USA Institute of Communications Engineering People's Liberation Army University of Science and Technology China Institute of Command Automation PLA University of Science and Technology USA State Key Laboratory for Novel Software Technology NanJing University China Department of Electrical and Computer Engineering University of Florida USA

ISBN: (纸本)9781467307734;9781467307758

We propose joint channel sensing, probing, and accessing schemes for secondary users in cognitive radio networks. Our method has time and space complexity O(N·k) for a network with N channels and k secondary users, while applying classic methods requires exponential time complexity. We prove that, even when channel states are selected by adversary (thus non-stochastic), it results in a total regret uniformly upper bounded by Θ(√TN log N), w.h.p, for communication lasts for T timeslots. Our protocol can be implemented in a distributed manner due to the nonstochastic channel assumption. Our experiments show that our schemes achieve almost optimal throughput compared with an optimal static strategy, and perform significantly better than previous methods in many settings.

关键词： Throughput Sensors Probes Protocols Cognitive radio Complexity theory Channel estimation

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