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IEEE International Conference on Automated Software engineering (ASE)

作者： K.S. Barber T. Graser J. Holt Laboratory for Intelligent Processes and Systems Electrical and Computer Engineering University of Technology Austin TX USA

The structure of a software architecture strongly influences the architecture's ability to prescribe systems satisfying functional requirements, non functional requirements, and overall qualities such as maintainability, reusability, and performance. Achieving an acceptable architecture requires an iterative derivation and evaluation process that allows refinement based on a series of tradeoffs. Researchers at the University of Texas at Austin are developing a suite of processes and supporting tools to guide architecture derivation from requirements acquisition through system design. The various types of decisions needed for concurrent derivation and evaluation demand a synthesis of evaluation techniques, because no single technique is suitable for all concerns of interest. Two tools in this suite, RARE and ARCADE, cooperate to enable iterative architecture derivation and architecture property evaluation. RARE guides derivation by employing a heuristics knowledge base, and evaluates the resulting architecture by applying static property evaluation based on structural metrics. ARCADE provides dynamic property evaluation leveraging simulation and model-checking. This paper presents a study whereby RARE and ARCADE were employed in the early stages of an industrial project to derive a Domain Reference Architecture (DRA), a high-level architecture capturing domain functionality, data, and timing. The discussion emphasizes early evaluation of performance qualities, and illustrates how ARCADE and RARE cooperate to enable iterative derivation and evaluation. These evaluations influenced DRA refinement as well as subsequent design decisions involving application implementation and computing platform selection.

关键词： Software architecture computer architecture Yarn Application software Connectors Laboratories intelligent systems intelligent structures Maintenance engineering Timing

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Facial feature extraction using genetic algorithm

Facial feature extraction using genetic algorithm

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2002 Congress on Evolutionary Computation, CEC 2002

作者： Yen, Gary G. Nithianandan, Nethrie Intelligent Systems and Control Laboratory School of Electrical and Computer Engineering Oklahoma State University Stillwater OK 74074-5032 United States

ISBN: (纸本)0780372824

An automatic facial feature extraction method is presented in this paper. The method is based on the edge density distribution of the image. In the preprocessing stage a face is approximated to an ellipse, and a genetic algorithm is applied to search for the best ellipse region match. In the feature extraction stage, the genetic algorithm is applied to extract the facial features, such as the eyes, nose and mouth, in the predefined sub regions. The simulation results validates that the proposed method is capable of automatically extracting features from various video images effectively under natural lighting environments and in the presence of certain amount of artificial noise and of multi-face oriented with angles. © 2002 IEEE.

关键词： Genetic algorithms

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Image Processing-Based Mine Detection Techniques: A Review

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Subsurface Sensing Technologies and Applications 2002年第3期3卷 153-202页

作者： Paik, Joonki Lee, Cheolha P. Abidi, Mongi A. Imaging Robotics and Intelligent Systems Laboratory Department of Electrical and Computer Engineering The University of Tennessee Knoxville

Various mine detection techniques are reviewed with particular emphasis on signal and image processing methods. Based on the target, mines are classified into two types; anti-tank mine (ATM) and anti-personnel mine (APM). Because of the variety of mine types, current mine detection techniques are diversified. The assumption is made that most mine detection techniques consist of sensor, signal processing, and decision processes. For the sensor part, ground penetration radar (GPR), infrared (IR), and ultrasound (US) sensors are reviewed and their characteristics are summarized for the corresponding output signals. For the signal processing and decision parts, a set of image processing techniques including filtering, enhancement, feature extraction, and segmentation are surveyed. Segmentation is used to extract mine signal from various competing signals. For most image processing techniques covered by this paper, mine detection related experimental results are included or reproduced from existing works.

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Quantitative measures of the accuracy, comprehensibility, and completeness of a fuzzy expert system

Quantitative measures of the accuracy, comprehensibility, an...

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IEEE International Conference on Fuzzy systems (FUZZ-IEEE)

作者： Phayung Meesad G.G. Yen Intelligent Systems and Control Laboratory Electrical and Computer Engineering Oklahoma State University USA

Using optimization tools such as genetic algorithms to construct a fuzzy expert system (FES), focusing only on its accuracy without considering comprehensibility may result in a system that is not easy to understand or the so called a black box model. To exploit the transparency features of FESs for explanation in higher-level knowledge representation, a FES should provide high comprehensibility while preserving its accuracy. The completeness of fuzzy sets and rule structures should also be considered to guarantee that every data point has a response output. This paper proposes some quantitative measures to determine the degree of the accuracy, comprehensibility, and completeness of FESs. These quantitative measures are then used as a fitness function for a genetic algorithm in an optimally built FES.

关键词： Hybrid intelligent systems Knowledge representation Genetic algorithms Fuzzy systems Predictive models intelligent systems intelligent control Control system synthesis Laboratories Genetic engineering

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Image segmentation and classification using color features

Image segmentation and classification using color features

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IEEE Region 8 International Symposium on Video/Image Processing and Multimedia Communications (EURASIP)

作者： M.S. Stachowicz D. Lemke Laboratory for Intelligent Systems Department of Electrical and Computer Engineering University of Minnesota Duluth USA

Color provides a wealth of information for interpretation of image content. The increased availability of affordable digital color cameras has created the opportunity to explore the degree to which color is useful in computer vision. This paper shows that a system for image segmentation and classification can be created using color as the primary feature. This system is comprised of two phases: segmentation and classification. In the first step, an image is searched with a blob detection algorithm to determine the location of any possible foreground elements. These areas are extracted from the image to be used in the next step. Classification is done using a set of eight color features that are optimally selected for each database. The appropriate feature vector is created for each foreground area removed from the original image. The vector is then compared to a preconstructed database to be identified. For this paper USA postage stamps on envelopes were used as the test cases.

关键词： Image segmentation Image databases computer vision Spatial databases Laboratories intelligent systems System testing Digital cameras Detection algorithms Image recognition

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Triangle mesh-based edge detection and its application to surface segmentation and adaptive surface smoothing

Triangle mesh-based edge detection and its application to su...

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IEEE International Conference on Image Processing

作者： Y. Sun D.L. Page J.K. Paik A. Koschan M.A. Abidi Imaging Robotics and Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Tennessee Knoxville USA

Triangle meshes are widely used in representing surfaces in computer vision and computer graphics. Although 2D image processing-based edge detection techniques have been popular in many application areas, they are not well developed for surfaces represented by triangle meshes. This paper proposes a robust edge detection algorithm for triangle meshes and its applications to surface segmentation and adaptive surface smoothing. The proposed edge detection technique is based on eigen analysis of the surface normal vector field in a geodesic window. To compute the edge strength of a certain vertex, the neighboring vertices in a specified geodesic distance are involved. Edge information are used further to segment the surfaces with the watershed algorithm and to achieve edge-preserved, adaptive surface smoothing. The proposed algorithm is novel in robustly detecting edges on triangle meshes against noise. The 3D watershed algorithm is an extension from previous work. Experimental results on surfaces reconstructed from multi-view real range images are presented.

关键词： Image edge detection Smoothing methods Application software Image segmentation Surface reconstruction computer vision computer graphics Geophysics computing Noise robustness Image reconstruction

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Adaptive critic fault tolerant control using dual heuristic programming

Adaptive critic fault tolerant control using dual heuristic ...

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International Joint Conference on Neural Networks (IJCNN)

作者： G.G. Yen P.G. Lima Intelligent Systems and Control Laboratory School of Electrical and Computer Engineering Oklahoma State University Stillwater OK USA

In this paper a hierarchical architecture that combines a high degree of reconfigurability and long-term memory is proposed as a fault tolerant control algorithm for complex nonlinear systems. Dual heuristic programming (DHP) is used for adapting to faults as they occur for the first time in an effort to prevent the build up of a general failure and also as tuning device after switching to a known scenario. A dynamical database, initialized with as much information of the plant as available, oversees the DHP controller. The decisions of which environments to record, when to intervene and where to switch are autonomously taken based on specifically designed quality indexes. The results of the application of the complete algorithm to a proof-of-the-concept numerical example help to illustrate the fine interrelations between each of its subsystems.

关键词： Programmable control Adaptive control Fault tolerance Control systems Nonlinear control systems Nonlinear systems Stability Databases Switches Algorithm design and analysis

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Real-time reconfigurable control system design using on-line neural estimator

Real-time reconfigurable control system design using on-line...

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International Joint Conference on Neural Networks (IJCNN)

作者： Liang-Wei Ho G.G. Yen Intelligent Systems and Control Laboratory School of Electrical and Computer Engineering Oklahoma State University Stillwater OK USA

The growing demand in system reliability and survivability under failures has urged ever-increasing research effort on the development of fault diagnosis and accommodation. In this paper, the on-line fault tolerant control problem for dynamic systems under unanticipated failures is investigated from a realistic point of view without any specific assumption on type of system dynamical structure or failure scenarios. The sufficient condition for system on-line stability under catastrophic failures has been derived using the discrete-time Lyapunov stability theory. Based upon the existing control theory and the modern intelligent techniques, an on-line fault accommodation control strategy is proposed to deal with the desired trajectory-tracking problems for systems suffering from various unknown and unanticipated catastrophic failures. To investigate the feasibility of the developed technique for unanticipated fault accommodation in real hardware under the real-time environment, an on-line fault tolerant control test bed has been constructed to validate the proposed technology. Both on-line simulations and the real-time experiment show encouraging results and promising futures of on-line real-time fault tolerant control based solely upon insufficient information of the system dynamics and the failure modes.

关键词： Real time systems Control systems Fault tolerant systems Reliability Fault diagnosis Sufficient conditions Stability Lyapunov method Control theory Hardware

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On the local interpretation of Takagi-Sugeno fuzzy models from a dynamical systems view

On the local interpretation of Takagi-Sugeno fuzzy models fr...

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IEEE International Conference on Fuzzy systems (FUZZ-IEEE)

作者： Seok-beom Lee G.G. Yen Intelligent Systems and Control Laboratory School of Electrical and Computer Engineering Oklahoma State University Stillwater OK USA

Takagi-Sugeno (TS) fuzzy models have been the popular choice for multi-model based nonlinear system identification for controller design. However, the interpretation of the model from a dynamical systems point of view is still unclear. We investigate the interpretation of the TS fuzzy models in terms of local dynamics of nonlinear systems in state space. The investigation is based on the comparison between the constant-affine recursive i/o equation and constant-affine state space representations. We show that the true local dynamics is not identifiable by TS fuzzy models by analysis and example. For the identification of constant-affine state space models, a subspace identification algorithm is proposed to identify the true local dynamics with zero initial conditions.

关键词： Takagi-Sugeno model Fuzzy systems Least squares approximation Fuzzy control Control system synthesis Nonlinear systems State-space methods Equations Function approximation Nonlinear control systems

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Dynamic database approach for fault tolerant control using dual heuristic programming

Dynamic database approach for fault tolerant control using d...

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American Control Conference (ACC)

作者： G.G. Yen P.G. de Lima Intelligent Systems and Control Laboratory School of Electrical and Computer Engineering Oklahoma State University Stillwater OK USA

In this paper a hierarchical architecture that combines a high degree of reconfigurability and long-term memory is presented as a fault tolerant control algorithm for complex nonlinear systems. Dual heuristic programming (DHP) is used for adapting to faults as they happen for the first time in an effort to prevent the build up of a general failure and also as tuning device after switching to a known scenario. A dynamical database, initialized with as much information of the plant as available, oversees the DHP controller. The decisions of which environments to record, when to intervene and where to switch are autonomously made based on the specifically designed quality indexes. Results of the application of the complete algorithm to a proof-of-the-concept numerical example help to illustrate the fine interrelations between each of its subsystems.

关键词： Dynamic programming Databases Fault tolerance Control systems Programmable control Adaptive control Nonlinear control systems Nonlinear systems Stability Switches

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