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International Conference on Intelligent Agent & Multi-Agent Systems (IAMA)

作者： M. Mohamed Sathik A. Abdul Rasheed Reader in Computer Science Sathakathullah Appa College Tirunelveli Tamilnadu. India Assistant Professor in Computer Applications Valliammai Engineering College Kattankulathur Chennai Tamilnadu India

Social network is the group of individuals who have common interest. Data mining has the greatest attention of research over the past decade. The machine learning field evolved from the broad field of artificial intelligence, in which the machine (computers) can be enabled to think or act as intelligent as humans. Classification is the machine learning problem in which the given dataset can be classified upon known classes. Social network has great impact in product marketing. In this paper we consider the classification as a social network problem. To prove this, we have taken a dataset and classify it using ID3 implementation. The dataset contains multivariate and multi - classes. The results obtained by classification are considered as social networks.

关键词： Social network services Data mining Machine learning Educational institutions IP networks Supervised learning computer science Artificial intelligence Learning systems MySpace

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A Study On Iterative Learning Control With Adjustment Of Learning Interval For Monotone Convergence In The Sense Of Sup-Norm

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Asian Journal of Control 2008年第1期4卷

作者： Kwang-Hyun Park Zeungnam Bien Division of EE Department of EECS Korea Advanced Institute of Science and Technology 373–1 Kusong-dong Yusong-gu Taejon 305–701 Korea. Zeungname Bien:received the B.S. degree in electronics engineering from Seoul National University Seoul Korea in 1969 and the M.S. and Ph.D. degrees in electrical engineering from the University of Iowa Iowa City Iowa U.S.A. in 1972 and 1975 respectively. During 1976–1977 academic years he taught as assistant professor at the Department of Electrical Engineering University of Iowa. Then Dr. Bien joined Korea Advanced Institute of Science and Technology summer 1977 and is now Professor of Control Engineering at the Department of Electrical Engineering and Computer Science KAIST. Dr. Bien was the president of the Korea Fuzzy Logic and Intelligent Systems Society during 1990–1995 and also the general chair of IFSA World Congress 1993 and for FUZZ-IEEE99 respectively. He is currently co-Editor-in-Chief for International Journal of Fuzzy Systems (IJFS) Associate Editor for IEEE Transactions on Fuzzy Systems and a regional editor for the International Journal of Intelligent Automation and Soft Computing. He has been serving as Vice President for IFSA since 1997 and is now Chief Chairman of Institute of Electronics Engineers of Korea and Director of Humanfriendly Welfare Robot System Research Center. His current research interests include intelligent control methods with emphasis on fuzzy logic systems service robotics and rehabilitation engineering and large-scale industrial control systems. Kwang-Hyun Park:received the B.S. M.S. and Ph.D. degrees in electrical engineering and computer science from KAIST Korea in 1994 19997 and 2001 respectively. He is now a researcher at Human-friendly Welfare Robot System Research Center. His research interests include learning control machine learning human-friendly interfaces and service robotics.

It has been found that some huge overshoot in the sense of sup-norm may be observed when typical iterative learning control (ILC) algorithms are applied to LTI systems, even though monotone convergence in the sense of λ-norm is guaranteed. In this paper, a new ILC algorithm with adjustment of learning interval is proposed to resolve such an undesirable phenomenon, and it is shown that the output error can be monotonically converged to zero in the sense of sup-norm when the proposed ILC algorithm is applied. A numerical example is given to show the effectiveness of the proposed algorithm.

关键词： Iterative learning control monotone convergence learning interval sup-norm

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TRACKING CONTROL IN THE PRESENCE OF NONLINEAR DYNAMIC FRICTIONAL EFFECTS: ROBOT EXTENSION

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Asian Journal of Control 2008年第3期1卷

作者： M. Feemster D.M. Dawson A. Behal W. Dixon Matthew Feemster received the B.S degree in Electrical Engineering from Clemson University Clemson South Carolina in December 1994. Upon graduation he remained at Clemson University and received the M.S. degree in Electrical Engineering in 1997. During this time he also served as a research/teaching assistant. His research work focused on the design and implementation of various nonlinear control algorithms with emphasis on the induction motor and mechanical systems with friction present. He is currently working toward his Ph.D. degree in Electrical Engineering at Clemson University. Darren M. Dawson was born in 1962 in Macon Georgia. He received an Associate Degree in Mathematics from Macon Junior College in 1982 and a B.S. Degree in Electrical Engineering from the Georgia Institute of Technology in 1984. He then worked for Westinghouse as a control engineer from 1985 to 1987. In 1987 he returned to the Georgia Institute of Technology where he received the Ph.D. Degree in Electrical Engineering in March 1990. During this time he also served as a research/teaching assistant. In July 1990 he joined the Electrical and Computer Engineering Department and the Center for Advanced Manufacturing (CAM) at Clemson University where he currently holds the position of Professor. Under the CAM director's supervision he currently leads the Robotics and Manufacturing Automation Laboratory which is jointly operated by the Electrical and Mechanical Engineering departments. His main research interests are in the fields of nonlinear based robust adaptive and learning control with application to electro-mechanical systems including robot manipulators motor drives magnetic bearings flexible cables flexible beams and high-speed transport systems. Aman Behal was born in India in 1973. He received his Masters Degree in Electrical Engineering from Indian Institute of Technology Bombay in 1996. He is currently working towards a Ph.D in Controls and Robotics at Clemson University. His research focuses on the control of no

In this paper, we extend the observer/control strategies previously published in [25] to an n -link, serially connected, direct drive, rigid link, revolute robot operating in the presence of nonlinear friction effects modeled by the Lu-Gre model. In addition, we also present a new adaptive control technique for compensating for the nonlinear parameterizable Stribeck effects. Specifically, an adaptive observer/controller scheme is developed which contains a feedforward approximation of the Stribeck effects. This feedforward approximation is used in a composite controller/observer strategy which forces the average square integral of the position tracking error to an arbitrarily small value. Experimental results are included to illustrate the performance of the proposed controllers.

关键词： Friction compensation nonlinear control

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Exploring the Synergism of a Multiple Auction-Based Task Allocation Scheme for Power-Aware Intrusion Detection in Wireless Ad-Hoc Networks

Exploring the Synergism of a Multiple Auction-Based Task All...

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International Conference on Communication Systems

作者： T. Srinivasan R. Chandrasekar Vivek Vijaykumar V. Mahadevan A. Meyyappan M. Nivedita Department of Computer Science and Engineering Assistant Professor Department of Information Technology Department of Information Technology Sri Venkateswara College of Engineering Sriperumbudur India Department of Computer Science and Engineering Sri Venkateswara College of Engineering Sriperumbudur

In this paper we propose a multiple auction-based task allocation scheme for identifying and distributing network-monitoring and decision-making tasks amongst the various nodes in a wireless ad-hoc network for performing power-aware intrusion detection. By iteratively performing this scheme we show that a power-optimal solution can be reached in a bandwidth constrained and energy-preserving network with only the nodes capable of supporting the various tasks chosen. We also demonstrate that simultaneous localized auctions have a lesser overhead than a single auction based scheme that was a subject of our previous work. Our scheme also serves to distribute the intrusion detection tasks according to the needs and constraints of a large and dynamic network. We have compared the performance of our scheme with the existing power-aware intrusion detection approaches in terms of various performance metrics and have demonstrated its associated low overhead

关键词： Intrusion detection Ad hoc networks Peer to peer computing Monitoring Bandwidth Batteries Power engineering and energy Power system modeling computer science Wireless application protocol

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Design of a Navigator for the Optimized Path-Tracking of Underwater ROVs using a Nero-Genetic Fuzzy Controller

Design of a Navigator for the Optimized Path-Tracking of Und...

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Proceedings of the Biannual World Automation Congress

作者： Hamed Kashani Mohammad Hossein Saghafi Mahmood Fathy Mohsen Soriani Computer Engineering Iran University of Science and Technology Iran MSc. Student of Computer Eng. at Iran University of Science and Technology(IUST) Iran MSc. Student of Mechanical Eng. at Sharif University of Technology Iran Computer Engineering IUST University Iran Professor of Computer Eng. at IUST Iran Mohsen Soriani Assistant Professor of Computer Eng. at IUST Iran

This paper proposes a sub-time-optimum soft-computing based controller to follow a desired path with a desired velocity by mobile robots with identified dynamical behavior. This method consists of a fuzzy controller where a trained neural network sets its membership functions values in on-line mode. Training of the network is done by a genetic algorithm for various vehicle initial positions and different path convexities in off-line. After the training of the network, during vehicle motion, it retrieves sub-optimized fuzziness values and sends them to the fuzzy control algorithm according to the vehicle position. Meanwhile, the influential of the path convexity is considered in fuzziness of membership functions. This method leads us to make almost the best decision for the mobile robot at each moment. This method is applied to an underwater remotely operated vehicle (ROV) to develop an autopilot for its control system. Simulation results show good performance of the method in this specifics problem.

关键词： Navigation Design optimization Remotely operated vehicles Fuzzy control Mobile robots Velocity control Fuzzy neural networks Fuzzy sets Neural networks Genetic algorithms

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Adaptive robust attitude tracking control of spacecraft

Adaptive robust attitude tracking control of spacecraft

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IEEE Conference on Control Technology and Applications (CCTA)

作者： R.B. Motlagh M.R.J. Motlagh Electrical Engineering Department Iran University of Science and Technology Iran Assistant Professor of controls in Computer Engineering Department Iran University of Science and Technology Tehran Iran

A nonlinear adaptive-robust scheme is presented to control a class of nonlinear systems. It effectively combines the design techniques of adaptive and robust control to improve performance by retaining the advantages of both techniques. It enhances transient performance and eliminates robustness problems compared to a parameter adaptive control. It also improves tracking performance by reducing modeling uncertainty and optimizes control effort by estimating bound uncertainty compared to a deterministic robust control. The controller is applied to a spacecraft making the body frame track a reference orientation, when there are parametric uncertainty, modeling errors, and external disturbances

关键词： Programmable control Adaptive control Robust control Attitude control Space vehicles Uncertainty Nonlinear control systems Control systems Nonlinear systems Error correction

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A High Performance IP Lookup for IPv6 using Parallel Computation Models

A High Performance IP Lookup for IPv6 using Parallel Computa...

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The 19th International Teletraffic Congress-ITC19

作者： D.Diwakar Srinivasan.T Department of Computer Science and Engineering Sri Venkateswara College of Engineering Sriperumbudur India.M.E.Final Year Department of Computer Science and Engineering Sri Venkateswara College of Engineering Sriperumbudur India.Assistant Professor

One of the key design issues for the next generation routers is the IP Lookup mechanism. IP address lookup is the challenging because it requires a longest matching prefix lookup. It is compounded by increasing routing table size, increased traffic and migration to IPv6 addresses. Existing solutions like BSD radix Tries, scale poorly when traffic in router increases or when employed for the IPv6 addresses. In our paper we describe a parallel computation models based lookup for the routing table. This mechanism provides lookup for a maximum of n*16 IPv6 addresses simultaneously, where n represents the number of processors. We propose a parallel binary trie search technique for the lookup to facilitate concurrent insertions and searching on the routing table. Using the proposed technique a router can achieve a much higher packet forwarding rate and throughput.

关键词： IPv6, Parallel Computation, IP Lookup

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AFOPT algorithm for multilevel databases

AFOPT algorithm for multilevel databases

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International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)

作者： R. Gyorodi C. Gyorodi M. Pater O. Boc Z. David Assistant professor Phd. Engineering Department of Computer Science Faculty of Electrotehnics and Informatics University of Oradea Oradea Romania Lecturer Engineering Phd. Student Department of Computer Science Faculty of Electrotehnics and Informatics University of Oradea Oradea Romania MSc student Department of Computer Science Faculty of Electrotehnics and Informatics University of Oradea Oradea Romania

With the widespread computerization in business, government, and science, the efficient and effective discovery of interesting information from large databases becomes essential. Previous studies on data mining have been focused on the discovery of knowledge at single conceptual level, either at the primitive level or at a rather high conceptual level. This paper presents an algorithm based on the AFOPT algorithm for multilevel databases that uses the benefits of multileveled databases, by using the information gained by studying items from one concept level for the study of the items from the following concept levels.

关键词： Itemsets Data mining Transaction databases computer science Informatics Government Machine learning Association rules Performance gain Pattern matching

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Damage Detection and Correlation-Based Localization Using Wireless Mote Sensors

Damage Detection and Correlation-Based Localization Using Wi...

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IEEE International Symposium on Intelligent Control (ISIC)

作者： E.H. Clayton Bong-Hwan Koh Guoliang Xing Chien-Liang Fok S.J. Dyke Chenyang Lu Graduate Research Assistant in the Department of Civil Engineering Washington University of Saint Louis Saint Louis MO USA Postdoctoral Research Associate in the Department of Civil Engineering Washington University of Saint Louis Saint Louis MO USA Edward C. Dicke Professor of Civil Engineering Washington University of Saint Louis Saint Louis MO USA Computer Science and Engineering Washington University of Saint Louis Saint Louis MO USA

This study focuses on an experimental damage detection and correlation-based localization demonstration using wireless sensors. A simple cantilever beam has been constructed in the laboratory to serve as a test bed for measuring acceleration responses with these devices. The goal of this preliminary investigation is to test the feasibility and functionality of a wireless sensor network (WSN) to detect and localize damage utilizing current wireless mote technology

关键词： Wireless sensor networks Testing Civil engineering Accelerometers Sensor arrays Sensor systems computer science Micromechanical devices Power engineering computing Power engineering and energy

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CLUSTERING ANALYSIS OF DEBRIS-FLOW STREAMS

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International Journal of Sediment Research 2004年第1期19卷 37-46页

作者： Yuan-Fan TSAI,Huai-Kuang TSAI,Cheng-Yan KAO Professor of Computer Science and Information Engineering National Taiwan University Taipei Taiwan Assistant Professor of Dept. of Social Studies Education National Taipei Teachers College Taipei 106 Taiwan Post doctoral fellow of Computer Science and Information Engineering National Taiwan University Taipei Taiwan

The Chi-Chi earthquake in 1999 caused disastrous landslides, which triggered numerous debris flows and killed hundreds of people. A critical rainfall intensity line for each debris-flow stream is studied to prevent such a disaster. However, setting rainfall lines from incomplete data is difficult, so this study considered eight critical factors to group streams, such that streams within a cluster have similar rainfall lines. A genetic algorithm is applied to group 377 debris-flow streams selected from the center of an area affected by the Chi-Chi earthquake. These streams are grouped into seven clusters with different characteristics. The results reveal that the proposed method effectively groups debris-flow streams.

关键词： Debris flow Genetic algorithm hierarchical clustering The Chi-Chi earthquake

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