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IEEE international conference on Systems, Man and Cybernetics

作者： E. Sobiesk J.A. Hamilton J.A. Marin D.E. Brown M. Gini Department of Electrical Engineering & Computer Science United States Military Academy West Point NY USA Department of Systems Engineering University of Virginia Charlottesville VA USA Department of Computer Science University of Minnesota Minneapolis MN USA

The digitized battlefield of the 21st Century will revolutionize the methods used to maintain military command and control. The tremendous amount of data available will necessitate the use of intelligent automated systems that augment, and in some cases replace, the human structures currently in place. One aspect of such systems is terrain-based tracking. We discuss an intelligent terrain-based system for tracking multiple vehicles moving across terrain. Specifically, our system extracts and utilizes knowledge about groups to improve the performance of a discrete state-space motion model. Parallel programming techniques are utilized to compute probability densities for the vehicles. A learning component allows for real-time adjustment based on performance.

关键词： Land vehicles Military computing intelligent systems Air traffic control Sensor phenomena and characterization Target tracking Computer science Command and control systems data mining Working environment noise

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A virtual test-bench for analog circuit testability analysis and fault diagnosis

A virtual test-bench for analog circuit testability analysis...

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international Automatic Testing conference, AUTOTEstCON

作者： S. Chakrabarty V. Rajan J. Ying M. Mansjur K. Pattipati S. Deb Department of Electrical and System Engineering University of Connecticut Storrs CT USA University of Connecticut Storrs CT US

Are fault simulation techniques feasible and effective for fault diagnosis of analog circuits? In this paper, we investigate these issues via a software tool which can generate testability metrics and diagnostic information for analog circuits represented by SPICE descriptions. This tool, termed the virtual test bench (VTB), incorporates three different simulation-based techniques for fault detection and isolation. The first method is based on the creation of fault-test dependency models, while the other two techniques employ machine learning principles based on the concepts of: (1) Restricted Coloumb Energy (RCE) Neural Networks, and (2) learning Vector Quantization (LVQ). Whereas the output of the first method can be used for the traditional off-line diagnosis, the RCE and LVQ models render themselves more naturally to on-line monitoring, where measurement data from various sensors is continuously available. Since it is well known that analog faults and test measurements are affected by component parameter variations, we have also addressed the issues of robustness of our fault diagnosis schemes. Specifically, we have attempted to answer the questions regarding fixing of test measurement thresholds, obtaining the minimum number of Monte-Carlo runs required to stabilize the measurements and their deviations, and the effect of different thresholding schemes on the robustness of fault models. Although fault-simulation is a powerful technique for analog circuit testability analysis, its main shortcomings are the long simulation time, large volume of data and the fidelity of simulators in accurately modeling faults. We have plotted the simulation time and volume of data required for a range of circuit sizes to provide guidance on the feasibility and efficacy of this approach.

关键词： Circuit testing Analog circuits Circuit analysis Circuit faults Circuit simulation Fault diagnosis Machine learning Robustness Analytical models Software tools

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A data mining tool for learning from manufacturing systems

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COMPUTERS & INDUstRIAL engineering 1997年第1-2期33卷 27-30页

作者： Koonce, DA Fang, CH Tsai, SC MICROSOFT CORP ISSAQUAHWA

This paper describes a software tool DBMine, developed to assist industrial engineers in data mining. This tool implements three common data mining methodologies: Bacon's algorithm, Decision Trees and DB-Learn. Implemented in Microsoft Visual Basic 3.0(C), DBMine, can utilize data in Microsoft Access 2.0(C) and in Watcom SQL(C) databases. This paper will also present an example session in which job shop sequences produced by a Genetic Algorithm are explored for regularity. (C) 1997 Elsevier Science Ltd.

关键词： Computer aided software engineering

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Improving test strategies and fault isolation with expert systems

Improving test strategies and fault isolation with expert sy...

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international Automatic Testing conference, AUTOTEstCON

作者： M. Ben-Bassat I. Beniaminy D. Joseph IET Intelligent Electronics Limited Anaheim CA USA

This paper focuses on the use of commercial off-the-shelf (COTS) expert systems in integrated diagnostics (1D) for military applications. Expert systems have developed and matured over the past several years to become a viable tool capable of functioning as a procedural tool for identifying diagnostic requirements, analyzing test system capabilities, and providing seamless diagnostic data transfer from requirement to analysis to operations. The most important differentiating characteristics of expert systems are their modeling methods, and their architecture. The modeling method drastically affects the time required to build a model, and the architecture must be open enough to integrate with the many tools used in engineering, deployment, and maintenance of the supported equipment throughout its life cycle. In this article, we present the Fault Modeling method, which has been field-proven over the past decade as flexible enough to meet the challenges of different lifecycle tasks, as well as lending itself to learning-self-improvement over time, even when starting with no knowledge. Expert systems using this model feature rapid deployment, and are able to cover the entire ID process including: capture of existing data, analysis of fault detection and isolation capabilities of the unit under test, and a means to assess diagnostic system designs early in the development phase. The systems integrate easily with simulators, automatic test equipment (ATE), and portable maintenance aid (PMA) equipment.

关键词： System testing Expert systems Diagnostic expert systems Costs Design engineering Automatic test equipment Automatic testing Maintenance Power system modeling Design automation

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Policing function in ATM network using multi-layer neural network

Policing function in ATM network using multi-layer neural ne...

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conference on Local Computer Networks (LCN)

作者： Kuang Klark Fan A.P. Jayasumana Department of Electrical Engineering Colorado State University Fort Collins CO USA

Artificial neural networks provide an attractive alternative in performing the policing function at the user network interface (UNI) of an asynchronous transfer mode (ATM) network. In order to guarantee quality of service (QOS) for the established connections in ATM networks, one of the policing functions at the UNI is to ensure that all data streams entering the ATM network conform to the allocated bandwidth, or otherwise the cell loss priority (CLP) bit in the ATM cell header must be set to reflect the situation that the output of the UNI has exceeded the permissible bandwidth. Feed-forward neural networks with back-propagation learning algorithms are chosen to perform the policing function at the UNI. Numerical results are presented to illustrate that the neural network is capable of performing the policing function.

关键词： intelligent networks Multi-layer neural network Neural networks Asynchronous transfer mode Bandwidth Communication system traffic control Feedforward neural networks Quality of service Feedforward systems B-ISDN

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On the integration of neural networks and fuzzy logic systems

On the integration of neural networks and fuzzy logic system...

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1995 IEEE international conference on Systems, Man and Cybernetics - intelligent Systems for the 21st-Century

作者： YUAN, Y SUARGA, S MCMASTER UNIV MICHAEL G DEGROOTE SCH BUSINESSHAMILTONON L8S 4M4CANADA

ISBN: (纸本)0780325605

Both neural networks (NN) and fuzzy logic systems (FLS) deal with important aspects of knowledge representation, inferencing, and learning process but they use different approaches and have their own strengths and weaknesses. NN can learn from sample data automatically, but lack of explanation ability. FLS are capable to perform approximate reasoning, but usually are not self-adaptive. The real power of artificial intelligence lies in the integration of NN and FLS. The existing methods of integration can be classified into three broad categories: 1) building FLS with NN, 2) converting NN into FLS, and 3) combining FLS and NN into a hybrid system. A variety of applications have been developed with the integration of NN and FLS. The direction of further research in this area is suggested.

关键词： Neural networks Fuzzy logic Neurons Function approximation Knowledge representation learning Artificial intelligence Adaptive systems Pattern recognition Medical control systems

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Trajectory learning for a friendly interactive robot for service tasks

Trajectory learning for a friendly interactive robot for ser...

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1995 IEEE international conference on Systems, Man and Cybernetics - intelligent Systems for the 21st-Century

作者： RAFFLIN, C FOURNIER, A UNIV MONTPELLIER 2 CNRSLIRMMLAB INFORMAT ROBOT & MICROELECTR MONTPELLIERF-34392 MONTPELLIER 5FRANCE

ISBN: (纸本)0780325605

To perform missions, indoor mobile robots must be able to follow collision-free trajectories. We have designed a learning system to teach the robot trajectories so that the feasibility of the paths can be ensured. During the execution, the robot follows the learned trajectory but on-line localization and obstacle avoidance are also performed so that the robot can always achieve the requested mission even in indoor dynamic environments. The learning process is made of three phases. The first one is a structuring phase in which we classify all trajectories to be learned. The next phases are the teleoperation phase for data acquisition and the checking phase to test the learned trajectory. We present all the phases and some experiments.

关键词： Robot learning

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Knowledge modeling in integrated symbolic-connectionist systems

Knowledge modeling in integrated symbolic-connectionist syst...

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1995 IEEE international conference on Systems, Man and Cybernetics - intelligent Systems for the 21st-Century

作者： KHOSLA, R DILLON, T LA TROBE UNIV APPL COMP RES INSTEXPERT & INTELLIGENT SYST LABMELBOURNEVICAUSTRALIA

ISBN: (纸本)0780325605

Knowledge Based Systems (Expert Systems), Fuzzy Systems, and Artificial Neural Networks (ANN) are the three most widely used computational paradigms for emulating different aspects of human cognition like information processing, knowledge representation, and learning. A proper integration of these three paradigms can help to realize powerful problem solving strategies especially for large data intensive domains. In this direction we have developed a generic architecture for integration of symbolic(knowledge based and fuzzy) and connectionist (Artificial Neural Networks) systems for large, data intensive domains at the task structure level, computational (symbol) level, and the program level. In this paper we outline the knowledge modeling aspects of the integrated symbolic (knowledge based and fuzzy)-connectionist architecture. The knowledge content of the architecture can facilitate a problem solver in modeling the knowledge required for using as well as integrating the three intelligent paradigms.

关键词： Computer simulation

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Skill representation and acquisition

Skill representation and acquisition

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1995 IEEE international conference on Systems, Man and Cybernetics - intelligent Systems for the 21st-Century

作者： LEE, S CHEN, J UNIV SO CALIF DEPT COMP SCILOS ANGELESCA 90089

ISBN: (纸本)0780325605

This paper presents a new approach for representing and acquiring skill by a robot based on experimental data. Skill is represented by describing a feasible state transition region embedded in experimental data as an union of hyper-ellipsoidal subregions of various sizes and shapes. Multi-resolution Radial Basis Competitive and Cooperative Network (MRCCN) is formulated for self-organizing hyper-ellipsoidal subregions and for providing accurate forward and backward state transitions through interpolation. Skill acquisition is performed by finding an optimal path from the current to the goal state in the feasible state transition region. The search for an optimal path is based on Bidirectional Dynamic Path Planning (BDPP) algorithm proposed in this paper.

关键词： Robot learning

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Development of an object-oriented intelligent clinical information management system

Development of an object-oriented intelligent clinical infor...

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Proceedings of the 1995 IEEE engineering in Medicine and Biology 17th Annual conference and 21st Canadian Medical and Biological engineering conference. Part 2 (of 2)

作者： Kalogeropoulos, D. Carson, E.R. Collinson, P.O. Cramp, D.G. Cent for Measurement and Information in Medicine London United Kingdom

An intelligent Clinical Information Management System (CIMS) to assist in the effective use of information derived from clinical laboratory data in the intensive care unit, has been designed and implemented and is undergoing evaluation. The key intelligent instrument of CIMS is described in the context of the clinical interpretation of acid-base balance and electrolyte data as part of the measurement process of blood-gas analysis. CIMS helps to illustrate the concepts and technological issues involved in the production of intelligent clinical instrumentation systems and provides evidence as to the level of machine intelligence required to achieve such objectives.

关键词： database systems

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