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Highly Compressed Zernike Moments by Smoothing

Highly Compressed Zernike Moments by Smoothing

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International Conference on systems, Signals and Image Processing, IWSSIP

作者： G. A. Papakostas Y. S. Boutalis D. A. Karras B. G. Mertzios Department of Electrical and Computer Engineering Democritus University of Thrace Xanthi Greece Department of Automation Chalkis Institute of Technology Chalkida Greece Department of Automation Laboratory of Control Systems. and Computer Intell. Thessaloniki Institute of Technology Thessaloniki Greece

A novel methodology that improves the discrimination capabilities of the compressed feature vectors, used in pattern recognition tasks, is presented in this paper. The Zernike moment signals of some patterns are extracted and are compressed by using a typical wavelet compression technique. In order to increase the compression ratio without loosing a great amount of significant information, the moment signals are smoothed appropriately before the compression. As a result, highly compressed feature vectors that include enough classification information are derived. The resulted improved features are studied for their discriminative power through appropriate experiments.

关键词： Smoothing methods Image coding Polynomials Automation Feature extraction Pattern classification Digital images Image reconstruction Laboratories Automatic control

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A multidiscipline and multi-rate modeling framework for planar solid-oxide fuel cell based power-conditioning system for vehicular APU

A multidiscipline and multi-rate modeling framework for plan...

引用

Summer computer Simulation Conference 2007, SCSC 2007, Part of the 2007 Summer Simulation Multiconference, SummerSim 2007

作者： Mazumder, Sudip K. Pradhan, Sanjaya Hartvigsen, Joseph Rancruel, Diego Von Spakovsky, Michael R. Khaleel, Moe Department of Electrical and Computer Eng Lab for Energy and Switching-electronics Systems University of Illinois Chicago United States Philips United States SOFC and Hydrogen Technologies Ceramatec United States New Product Introduction GE Power Generation Technology United States Department of Mechanical Engineering Center for Energy Systems Research Virginia Polytechnic Institute and State University United States Computational Sciences and Mathematics Division Pacific Northwest National Laboratory United States

ISBN: (纸本)9781622763580

We develop a numerical modeling framework for planar solid-oxide fuel cell (PSOFC) based vehicular auxiliary power unit (APU). The power-conditioning system (PCS) model comprises the comprehensive transient models of PSOFC, balance-of-plant and power-electronics subsystems (i.e., BOPS and PES, respectively), and application load (AL). It can be used for resolving the interactions among PSOFC, BOPS, PES, and AL, control design and system optimization, and fuel-cell durability studies. The PCS model has several key properties including the following: i) it can predict simultaneously predict spatial as well as temporal dynamics;ii) it has two levels of abstraction: comprehensive (for detailed dynamics) and reduced-order (for fast simulation);and iii) the fastsimulation model can be implemented completely in Simulink/Matlab environment, thereby significantly reducing the cost as well as time and provides the avenue for real-time simulation and integration with vehicular power-train models using the widely used ADVISOR. We compared the computational overhead and accuracy of the fast-simulation and comprehensive models and the show significant savings in time obtained using the former without compromising accuracy.

关键词： Simulink

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AUTOMATED 3-D QUANTIFICATION OF BRAIN TISSUE AT THE CELLULAR SCALE FROM MULTI-PARAMETER CONFOCAL MICROSCOPY IMAGES

AUTOMATED 3-D QUANTIFICATION OF BRAIN TISSUE AT THE CELLULAR...

引用

IEEE International Symposium on Biomedical Imaging

作者： Gang Lin Yousef Al Kofahi James A. Tyrrell Christopher Bjornsson William Shain Badrinath Roysam Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute Troy NY USA Laboratory of Nervous System Disorders New York State Department of Health Wadsworth Center Albany NY USA

ISBN: (纸本)9781424406715;1424406714

Brain tissue is the most complex tissue in the mammalian anatomy. It is structurally complex, containing diverse cell types and vasculature with complex spatial relationships. It is also complex in terms of molecular constituents, and their relationship to the structural constituents. There is a need for technologies to map normal and injured brain tissue and compute appropriate quantitative measurements in support of a large number of investigations. We present a systematic methodology named FARSIGHT (fluorescence association rules for image-based insight), combining multi-parameter immuno-histochemical labeling, three-dimensional confocal microscopy, linear unmixing, segmentation, and associative morphometry to map and quantify diverse aspects of brain tissue. In addition to morphometric measurements of individual structures from individual imaging channels, we propose the use of distance maps, distance-weighted integrals, and distributions as an efficient basis for computing a versatile set of such associative measurements. These features enable classification of all the major cell types, and computation of their inter-relationships.

关键词： Brain Microscopy Anatomy Appropriate technology Fluorescence Association rules Diversity reception Labeling Image segmentation Distributed computing

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Management of an intelligent argumentation network for a web-based collaborative engineering design environment

Management of an intelligent argumentation network for a web...

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International Symposium on Collaborative Technologies and systems

作者： Xiaoqing Liu Man Zheng Ganesh K. Venayagamoorthy Ming Leu Department of Computer Science University of Missouri Rolla Rolla MO USA Real-Time Power and Intelligent Systems Laboratory Department of Electrical & Computer Engineering University of Missouri Rolla Rolla MO USA Department of Mechanical and Aerospace Engineering University of Missouri Rolla Rolla MO USA

ISBN: (纸本)9781424433896;0978569911

Conflict resolution is one of the most challenging tasks in collaborative engineering design. In our previous research, a web-based intelligent collaborative system was developed to address this challenge based on intelligent computational argumentation. However, two important issues were not resolved in that system: priority of participants and self-conflicting arguments. In this paper, we develop two methods for incorporating priorities of participants into the computational argumentation network: 1) weighted summation and 2) re-assessment of strengths of arguments based on priority of owners of the argument using fuzzy logic inference. In addition, we develop a method for detection of self-conflicting arguments. Incorporation of priority of participants and detection of self-conflicting arguments have strengthen the capability of managing intelligent argumentation network for the web-based collaborative engineering design system developed in our previous research.

关键词： Collaboration Artificial intelligence Fuzzy sets Engines Input variables Robustness USA Councils

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Particle Swarn Optimized Adaptive Dynamic Programming

Particle Swarn Optimized Adaptive Dynamic Programming

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IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning, (ADPRL)

作者： Dongbin Zhao Jianqiang Yi Derong Liu Key Laboratory of Complex Systems and Intelligence Science Institute of Automation Chinese Academy and Sciences Beijing China Department of Electrical and Computer Engineering University of Illinois Chicago Chicago IL USA

Particle swarm optimization is used for the training of the action network and critic network of the adaptive dynamic programming approach. The typical structures of the adaptive dynamic programming and particle swarm optimization are adopted for comparison to other learning algorithms such as gradient descent method. Besides simulation on the balancing of a cart pole plant, a more complex plant pendulum robot (pendubot) is tested for the learning performance. Compared to traditional adaptive dynamic programming approaches, the proposed evolutionary learning strategy is verified as faster convergence and higher efficiency. Furthermore, the structure becomes simple because the plant model does not need to be identified beforehand

关键词： Dynamic programming Particle swarm optimization Neural networks Robots Backpropagation Adaptive systems Evolutionary computation Learning Cost function Testing

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Intelligent Local and Hierarchical Control of FACTS Devices

Intelligent Local and Hierarchical Control of FACTS Devices

引用

2007 IEEE Power engineering Society Conference and Exposition in Africa (IEEE PES PowerAfrica 2007), part 1

作者： Salman Mohagheghi Ganesh K. Venayagamoorthy Ronald G. Harley Intelligent Power Infrastructure Consortium Georgia Institute of Technology Atlanta GA USA Real-Time Power and Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Missouri MO USA Department of Electrical and Computer Engineering University of Missouri-Rolla MO USA Emeritus University of Kwazulu-Natal South Africa

This paper presents an overview of the applications of intelligent control techniques on local and hierarchical control of FACTS devices. These control techniques are superior to the conventional linear/nonlinear control schemes in the sense that they are independent of any mathematical model of the power system to be controlled. In addition, they do not depend on the operating conditions and the configuration of the system to which the FACTS device is connected. A Static Compensator (STATCOM) is used as the example in order to compare the performances of the proposed intelligent controllers with those of their linear counterparts. Nevertheless, the ideas put forth in this paper are applicable to other shunt or series FACTS devices as well. Two different control schemes are evaluated: a fuzzy logic based local controller and a neuro-fuzzy hierarchical controller for a STATCOM in a multimachine power system.

关键词： Nonlinear control systems Control systems Power system control Power systems Automatic voltage control Intelligent control Mathematical model Power system modeling Control system synthesis STATCOM

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Sensor Enabled Rule Based Alarm System for the Agricultural Industry

Sensor Enabled Rule Based Alarm System for the Agricultural ...

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12th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA 2007), vol.2

作者： Christos Gogos Panayiotis Alefragis Efthymios Housos Computer Systems Laboratory Department of Electrical & Computer Engineering University of Patras Patras Greece

This paper describes a system that generates intelligent alarms using sensor data located at various geographical locations. Users are informed using a rule enabled engine whenever certain conditions demanding attention occur, through an SMS messaging system. The user can easily define, through a graphical user interface, new rules or update existing ones. An agricultural case study of the system is presented.

关键词： Sensors SMS Alarms Rule engine XML Microclimate

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A Hidden Markov Models Tool for Estimating the Deterioration Level of a Power Transformer

A Hidden Markov Models Tool for Estimating the Deterioration...

引用

12th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA 2007), vol.2

作者： F. Sotiropoulos P. Alefragis E. Housos Computer Systems Laboratory Department of Electrical & Computer Engineering University of Patras Patras Greece

In electrical power systems, asset management procedures have developed into a central element of network operations and planning. Hidden Markov Models (HMM) can be used to transform various data collected from substation equipment into failure probabilities. Based on these failure probabilities a mathematical decision tool can be created which could be used in system-level simulation and experimentation. In particular, collected data utilizing the dissolved gas analysis-in-oil (DGA) field methodology for transformers are analyzed with HMM for the prediction of their deterioration level.

关键词： Asset Management Hidden Markov Models Maintenance Substation Component Reliability HMM

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Conjugate Gradient Projection Approach for MIMO Gaussian Broadcast Channels

Conjugate Gradient Projection Approach for MIMO Gaussian Bro...

引用

IEEE International Symposium on Information Theory

作者： Jia Liu Y. Thomas Hou Sastry Kompella Hanif D. Sherali Department of Electrical and Computer Engineering Virginia Tech Blacksburg VA USA Information Technology Division U.S. Naval Research Laboratory Washington DC USA Department of Industrial and Systems Engineering Virginia Tech Blacksburg VA

ISBN: (纸本)9781424413973

Researchers have recently shown that the dirty-paper coding (DPC) is the optimal transmission strategy for multiple-input multiple-output Gaussian broadcast channels (MIMO BC). Moreover, by the channel duality, the nonconvex MIMO BC sum rate problem can be transformed to the convex dual MIMO multiple-access channel (MIMO MAC) problem with a sum power constraint. In this paper, we design an efficient algorithm based on conjugate gradient projection (CGP) to solve the MIMO BC maximum sum rate problem. Our proposed CGP algorithm solves the dual sum power MAC problem by utilizing the powerful concept of Hessian conjugate. We also develop a rigorous algorithm to solve the projection problem. We show that CGP enjoys provable convergence, scalability, and efficiency for large MIMO BC systems.

关键词： MIMO Broadcasting Algorithm design and analysis Convergence Scalability Iterative algorithms Switches Broadcast technology Information technology Laboratories

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Dynamic Modeling of Wind Farms with Fixed-Speed Wind Turbine Generators

Dynamic Modeling of Wind Farms with Fixed-Speed Wind Turbine...

引用

2007 IEEE Power engineering Society General Meeting (PES 2007), vol.10

作者： Wei Qiao Ronald G. Harley Ganesh K. Venayagamoorthy Intelligent Power Infrastructure Consortium (IPIC) School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA University of KwaZulu-Natal Durban South Africa Real-Time Power and Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Missouri Rolla Rolla MO USA

A wind farm typically consists of a large number of individual wind turbine generators (WTGs) connected by an internal electrical network. To study the impact of wind farms on the dynamics of the power system, an important issue is to develop appropriate wind farm models to represent the dynamics of many individual WTGs. This paper presents various dynamic models, including a detailed model and three reduced-order equivalent models, of wind farms with fixed-speed WTGs. These models are developed and compared by simulation studies in the PSCAD/EMTDC environment under different wind velocity and fluctuation conditions as well as gird fault conditions. Concluding remarks are provided on how to choose an appropriate wind farm model for power system dynamic and transient studies.

关键词： Detailed model Equivalent model Fixed-speed wind turbine Squirrel-cage induction generator Wind farm

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