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International Journal of Digital Content Technology and its Applications 2012年第20期6卷 268-276页

作者： Liu, Jin Wu, Yangping Zhuo, Dan Hu, Qiping Wang, Yan Zhang, Wensheng State Key Lab of Software Engineering Computer School Wuhan University China International School of Software Wuhan University China State Key Lab of Management and Control for Complex Systems Institute of Automation Chinese Academy of Science China

One of challenges in GIS Web service is mass GIS data storage and processing. There are at least three obstacles that oppose dealing with this challenge: the mismatch between the frequent requirement of concurrent tasks for accessing data in GIS Web service and the poor performance of conventional storage mechanism such as relational databases;the insufficiency of relational databases to manage complex data types in GIS Web service;the horizontal scalability of storage for non-stop GIS Web service evolution. This paper proposes a distributed cached storage solution, as the mixture of MongoDB storage and Memcached cache, for GIS Web service. Both techniques are closely related to NoSQL that is a class of database management system identified by its non-adherence to the widely used relational database management system (RDBMS) model. A concise case that facilitates a better understanding of this work indicates its feasibility.

关键词： Websites

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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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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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Overhead Power Line Detection from UAV Video Images

Overhead Power Line Detection from UAV Video Images

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International Conference on Mechatronics and Machine Vision in Practice

作者： Tang Wen YANG Hang YIN Qiu Qi RUAN Jian Da HAN Jun Tong QI Qing YONG Zi Tong WANG Zeng Qi SUN Beijing Key Laboratory of Advanced Information Science and Network Technology Institute of Information Science Beijing Jiaotong University Beijing 100044 China Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing 100044 China State Key Laboratory of Robotics Shenyang Institute of Automation CAS Shenyang 110016 China Department of Computer Science and Technology Tsinghua University Beijing 100084 China

ISBN: (纸本)9781467316439

Currently, unmanned aerial vehicles (UAVs) are applied to routine inspection tasks of electric distribution networks. As an important information source, machine vision attracts much attention in the area of the UAV's autonomous control. To this end, real-time algorithms are studied-in this paper to detect the power lines in the UAV video images. First, video images are converted into binary images through an adaptive thresholding approach. Then, Hough Transform is used to detect line candidates in the binary images. Finally, a fuzzy C- means (FCM) clustering algorithm is used to discriminate the power lines from the detected line candidates. The properties of power lines are used to remove the spurious lines, and the length and slope of the detected lines are used as features to establish the clustering data set. Experimental results show that the algorithms proposed are effective and able to tolerate noises from complicated terrain background and various illuminations.

关键词： Hough transforms autonomous aerial vehicles computer vision fuzzy set theory pattern clustering power overhead lines power system control video signal processing

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Multi-sensor sequential fusion estimation for systems with random one-step delay

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Nanjing Li Gong Daxue Xuebao/Journal of Nanjing University of science and Technology 2012年第SUPPL.2期36卷 255-262页

作者： Chai, Zhong Wen, Cheng-Lin Feng, Xiao-Liang Institute of Systems Science and Control Engineering School of Automation Hangzhou Dianzi University Hangzhou 310018 China College of Computer and Information Engineering Hohai University Nanjing 211100 China

In networked control systems, when sensor data are transmitted through network, time delay is almost inevitable. This paper is concerned with multiple-sensor system with random one-step delay. By introducing random variables and augmenting the state vector, the initial system with random one-step delay can be transformed into a new system with random parameters. The fusion estimator is designed based on the new system in the sense of minimizing the estimation error covariance. The sequential fusion algorithm is proposed. Linear unbiased state estimation under one-step random delay for single sensor performs well in the study, while this paper mainly considers multiple-sensor fusion to get better estimation result. The simulation is presented to illustrate the efficiency of the proposed algorithm.

关键词： Networked control systems

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Composition of united multiple diseases evolution topological model

Composition of united multiple diseases evolution topologica...

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9th International Symposium on Intelligent Systems and Informatics, SISY 2011

作者： Karpičs, I. Markovičs, Z. Markoviča, I. Institute of Computer Control Automation and Computer Engineering Faculty of Computer Science and Information Technology Riga Technical University Riga Latvia

ISBN: (纸本)9781457719745

Mathematical models are constructed and used as a methodology of various functioning systems structure investigation and performance analysis. The main goal of mathematical model usage is to perform wholesome diagnostics and correct work resumption of investigated system. In the article topological modeling method has been investigated by giving fundamental basics and application spheres by examples. Authors propose model construction method with an example from medicine by creating multiple diseases (arterial hypertension, atherosclerosis and diabetes mellitus) evolution topological model with formal aspects. Developed modeling method and united diseases model can be used to prognosticate evolution of diseases, perform inspection of used therapies and provide information for optimal therapy complex selection. © 2011 IEEE.

关键词： Topology

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Monitoring and control of liquid nitrogen level of the 13C separation column using NI PXI-1031

Monitoring and control of liquid nitrogen level of the 13C s...

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6th IEEE International Symposium on Applied Computational Intelligence and Informatics, SACI 2011

作者： Neaga, A.O. Festila, C. Dulf, E.H. Both, R. Szelitzky, T. Gligan, M. Technical University of Cluj Napoca Department of Automatic Control Faculty of Automation and Computer Science Cluj Napoca Romania National Institute for Research and Development of Isotopic and Molecular Technologies Cluj Napoca Romania

ISBN: (纸本)9781424491094

This paper is a step forward by making real time control system design to monitor and control process variables to ensure its smooth operation and desired reliability. Liquid nitrogen level in the condenser is a core component of isotopic separation process to obtain (13C), so is needed a special focus on monitoring and control. The goal of the work is to design a controller for the liquid nitrogen in the condenser of (13C) isotope separation column using NI-PXI 1031 (PCI eXtensions for Instrumentation) from National Instruments. The designed ON-OFF controller is implemented in LabVIEW and are discussed the advantages and disadvantages. © 2011 IEEE.

关键词： controllers

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Composition of united multiple diseases evolution topological model

Composition of united multiple diseases evolution topologica...

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International Symposium on Intelligent Systems and Informatics (SISY)

作者： I. Karpičs Z. Markovičs I. Markoviča Institute of computer control automation and computer engineering Faculty of computer science and information technology Riga Technical University Riga Latvia

关键词： Mathematical model Medical treatment Diseases Organisms Medical diagnostic imaging Predictive models Numerical models

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Development and evaluation of normal performance recovery method of a functional system

Development and evaluation of normal performance recovery me...

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International Symposium on Applied Machine Intelligence and Informatics (SAMI)

作者： I. Karpics Z. Markovics Faculty of Computer Science and Information Technology Institute of Computer Control Automation and Computer Engineering Riga Technical University Riga Latvia

Different type dynamic systems in functional work phase lose performance and it's necessary to establish normal operation level by using external influence. External influence can be defined as recovery method. In practice exists different possibilities how to resume performance of system and the main objective is to select the most efficient solution. In the article new approach for normal operation recovery selection is defined, including each recovery and recoveries complex assessment for optimal solution selection. For optimal solution choice benefit and disadvantage criteria are proposed. For practical implementation in case of medicine, arterial hypertension evaluation and pathogenesis therapy selection is described.

关键词： Medical treatment Mathematical model Organisms Medical diagnostic imaging Hypertension Optimization Decision making

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Predicting the unobservable Visual 3D tracking with a probabilistic motion model

Predicting the unobservable Visual 3D tracking with a probab...

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IEEE International Conference on Robotics and automation (ICRA)

作者： Thomas Mörwald Marek Kopicki Rustam Stolkin Jeremy Wyatt Sebastian Zurek Michael Zillich Markus Vincze Automation and Control Institute University of Technology Vienna Austria School of Computer Science University of Binningham UK

Visual tracking of an object can provide a powerful source of feedback information during complex robotic manipulation operations, especially those in which there may be uncertainty about which new object pose may result from a planned manipulative action. At the same time, robotic manipulation can provide a challenging environment for visual tracking, with occlusions of the object by other objects or by the robot itself, and sudden changes in object pose that may be accompanied by motion blur. Recursive filtering techniques use motion models for predictor-corrector tracking, but the simple models typically used often fail to adequately predict the complex motions of manipulated objects. We show how statistical machine learning techniques can be used to train sophisticated motion predictors, which incorporate additional information by being conditioned on the planned manipulative action being executed. We then show how these learned predictors can be used to propagate the particles of a particle filter from one predictor-corrector step to the next, enabling a visual tracking algorithm to maintain plausible hypotheses about the location of an object, even during severe occlusion and other difficult conditions. We demonstrate the approach in the context of robotic push manipulation, where a 5-axis robot arm equipped with a rigid finger applies a series of pushes to an object, while it is tracked by a vision algorithm using a single camera.

关键词： Tracking Robots Visualization Computational modeling Image edge detection Three dimensional displays Physics

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