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2011 18th IEEE International Conference on Electronics, Circuits and Systems, ICECS 2011

作者： Qiu, Ji Gao, Xiang Jiang, Yifei Xiao, Xu Key Laboratory of Computer System and Architecture Institute of Computing Technology Graduate University of Chinese Academy of Science Beijing 100190 China Department of Electrical and Computer Engineering University of Illinois at Urbana-Champaign Urbana IL United States

ISBN: (纸本)9781457718458

ISS (Instruction Set Simulator) plays an important role in pre-silicon software development for ASIP. However, the speed of traditional simulation is too slow to effectively support full-scale software development. In this paper, we propose a hybrid simulation framework which further improves the previous simulation methods by aggressively utilizing the host machine resources. The utilization is achieved by categorizing instructions of ASIP application into two types, namely custom and basic instructions, via binary instrumentation. Then in a way of hybrid simulation, only custom instructions are simulated on the ISS and basic instructions are executed fast and natively on the host machine. We implement this framework for an industrial ASIP to validate our approach. Experimental results show that when the implemented ISS, namely GS-Sim, is applied to practical multimedia decoders, an average simulation speed up to 1058.5MIPS can be achieved, which is 34.7 times of the state-of-art dynamic binary translation simulator and is the fastest to the best of our knowledge. © 2011 IEEE.

关键词： Software design

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Computational Intelligence for Control of Wind Turbine Generators

Computational Intelligence for Control of Wind Turbine Gener...

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IEEE Power and Energy Society General Meeting

作者： Wei Qiao Jiaqi Liang Ganesh K. Venayagamoorthy Ronald Harley Department of Electrical Engineering University of Nebraska-Lincoln School of Electrical and Computer Engineering Georgia Institute of Technology Real-Time Power and Intelligent Systems Laboratory Missouri University of Science and Technology

ISBN: (纸本)9781457710001

This paper summarizes past and ongoing research in the area of the application of computational intelligence (CI) for control of wind turbine generators (WTGs). Several intelligent design approaches and control strategies, including optimal design of WTG controllers using particle swarm optimization (PSO) and mean-variance optimization (MVO) algorithms and adaptive critic design-based coordinated optimal adaptive control for wind plants and shunt FACTS devices, are presented for dynamic performance and fault ride-through enhancement of WTGs and the associated power grid. The effectiveness of these intelligent design approaches and control strategies are demonstrated by nonreal- and real-time simulations in PSCAD/EMTDC and RSCAD/RTDS, respectively.

关键词： Computational intelligence (CI) Doubly fed induction generator (DFIG) Dual heuristic programming (DHP) FACTS device Heuristic dynamic programming (HDP) Particle swarm optimization (PSO) Radial basis function neural network (RBFNN) Wind turbine Wind Generators Artificial Intelligence Computational intelligence Wind Energy Conversion Systems Standing Orders Intelligent Design design approach dynamic characteristics shunt Optimal design

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Automatic Web service composition based on Horn clauses and Petri nets

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Expert Systems with Applications 2011年第10期38卷 13024-13031页

作者： Tang, Xianfei Jiang, Changjun Zhou, Mengchu Department of Computer Science and Technology Tongji University Shanghai 201804 China Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai 201804 China Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ 07102 United States

This paper introduces an automatic Web service composition method based on logical inference of Horn clauses and Petri nets. The Web service composition problem is transformed into the logical inference problem of Horn clauses by exploring the dependency relations among services. An algorithm is presented, to determine whether the composite service exists in time that is linear in the size of the knowledge base. It can also return the rule set necessary for the composition. Petri nets are chosen to model the rule set and its structural analysis techniques are used to obtain the composite service. © 2010 Elsevier Ltd. All rights reserved.

关键词： Automatic reasoning Knowledge base Petri nets Service composition Web service

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Trusted Framework for Health Information Exchange

Trusted Framework for Health Information Exchange

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Frontiers of Information Technology (FIT)

作者： Muhammad Afzal Maqbool Hussain Mahmood Ahmad Zahid Anwar School of Electrical Engineering and Computer Science Semantic Systems Research Laboratory Pakistan Department of Computing School of Electrical Engineering and Computer Science Pakistan

Healthcare Interchange Exchange (HIE) is set of healthcare entities that link regions and nations around the world to share healthcare information about patients. HIE provides a unified interface to various stakeholders to access patient data. For example, individuals want to access personal data, practitioners want to import their patient data from Personal Health Records (PHR) and researchers want to access anonymized patient data for research purposes with ensured individual privacy. Keeping in view requirements of various stakeholders it is challenging to design an HIE system that ensures the security and privacy of patient information, such that the health records remain interoperable and scalable. This paper proposes, an HIE framework that will provide secure access to patient data and adhere to the interoperability rules. Implementation of l-diversity algorithm ensures individual privacy especially when the data is made available publicly for statistical analysis.

关键词： Medical services Authentication Data privacy Joining processes Encryption Standards organizations

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Support for the evolution of C++ generic functions

Support for the evolution of C++ generic functions

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Lecture Notes in computer science

作者： Pirkelbauer, Peter Dechev, Damian Stroustrup, Bjarne Lawrence Livermore National Laboratory Center for Applied Scientific Computing Livermore CA 94550-9698 United States University of Central Florida Department of Electrical Engineering and Computer Science Orlando FL 32816-2362 United States Texas AandM University Department of Computer Science and Engineering College Station TX 77843-3112 United States

ISBN: (纸本)9783642194399

The choice of requirements for an argument of a generic type or algorithm is a central design issue in generic programming. In the context of C++, a specification of requirements for a template argument or a set of template arguments is called a concept. In this paper, we present a novel tool, TACE (template analysis and concept extraction), designed to help programmers understand the requirements that their code de facto imposes on arguments and help simplify and generalize those through comparisons with libraries of well-defined and precisely-specified concepts. TACE automatically extracts requirements from the body of function templates. These requirements are expressed using the notation and semantics developed by the ISO C++ standards committee. TACE converts implied requirements into concept definitions and compares them against concepts from a repository. Components of a well-defined library exhibit commonalities that allow us to detect problems by comparing requirements from many components: Design and implementation problems manifest themselves as minor variations in requirements. TACE points to source code that cannot be constrained by concepts and to code where small modifications would allow the use of less constraining concepts. For people who use a version of C++ with concept support, TACE can serve as a core engine for automated source code rejuvenation. © 2011 Springer-Verlag Berlin Heidelberg.

关键词： Semantics

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A domain partition model approach to the online fault recovery of FPGA-based reconfigurable systems

A domain partition model approach to the online fault recove...

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作者： Shang, Lihong Zhou, Mi Hu, Yu Yang, Erfu School of Computer Science and Engineering Beihang University Beijing 100191 China Key Laboratory of Computer System and Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Department of Electronic and Electrical Engineering University of Strathclyde Glasgow Gl 1XW United Kingdom

Field programmable gate arrays (FPGAs) are widely used in reliability-critical systems due to their reconfiguration ability. However, with the shrinking device feature size and increasing die area, nowadays FPGAs can be deeply affected by the errors induced by electromigration and radiation. To improve the reliability of FPGA-based reconfigurable systems, a permanent fault recovery approach using a domain partition model is proposed in this paper. In the proposed approach, the fault-tolerant FPGA recovery from faults is realized by reloading a proper configuration from a pool of multiple alternative configurations with overlaps. The overlaps are presented as a set of vectors in the domain partition model. To enhance the reliability, a technical procedure is also presented in which the set of vectors are heuristically filtered so that the corresponding small overlaps can be merged into big ones. Experimental results are provided to demonstrate the effectiveness of the proposed approach through applying it to several benchmark circuits. Compared with previous approaches, the proposed approach increased MTTF by up to 18.87%. Copyright © 2011 The Institute of Electronics, Information and Communication Engineers.

关键词： Fault tolerance

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Comparison of TDNN and RNN performances for neuro-identification on small to medium-sized power systems

Comparison of TDNN and RNN performances for neuro-identifica...

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IEEE Symposium on Computational Intelligence Applications In Smart Grid (CIASG)

作者： Diogenes Molina Jiaqi Liang Ron Harley Ganesh K. Venayagamoorthy Department of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA Real-Time Power and Intelligent System Laboratory Missouri University of Science and Technology Rolla MO USA

For Artificial Neural Networks (ANN) to become more widely used in power systems and the future smart grids, ANN based algorithms must be capable of scaling up as they try to identify and control larger and larger parts of a power system. This paper goes through the process of scaling up an ANN based identifier as it is driven to identify increasingly larger portions of a power system. Distributed and centralized approaches for scaling up are taken and the pros and cons of each are presented. The New England/New York 68-bus power network is used as the test bed for the studies. It is shown that while a fully-connected (centralized) ANNs is capable of identification of the system with appropriate accuracy, the increase in the training times required to obtain an acceptable set of weights becomes prohibitive as the system size is increased.

关键词： Artificial neural networks Power system dynamics Recurrent neural networks Training Generators Testing

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Discriminant component analysis and self-organized manifold mapping for exploring and understanding image face spaces

Discriminant component analysis and self-organized manifold ...

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24th SIBGRAPI Conference on Graphics, Patterns, and Images Tutorials, SIBGRAPI-T 2011

作者： Giraldi, Gilson A. Kitani, Edson C. Del-Moral-Hernandez, Emilio Thomaz, Carlos E. Department of Computer Science National Laboratory for Scientific Computing Petropolis Brazil Polytechnic School University of São Paulo São Paulo Brazil Department of Electrical Engineering Centro Universitario Da FEI São Bernardo do Campo Brazil

ISBN: (纸本)9780769545493

Face recognition is a multidisciplinary field that involves subjects in neuroscience, computer science and statistical learning. Some recent research in neuroscience has indicated that the ability of our memory relies on the capability of orthogonalizing (pattern separation) and completing (pattern prototyping) partial patterns in order to encode, store and recall information. From a computational viewpoint, pattern separation can be cast in the subspace learning area while pattern prototyping is closer to manifold learning methods. So, subspace (or manifold) learning techniques have a close biological inspiration and reasonability in terms of computational methods to possibly exploring and understanding the human behavior of recognizing faces. Therefore, the aim of this paper is threefold. Firstly, we review some theoretical aspects about perceptual and cognitive processes related to the mechanisms of pattern separation and pattern prototyping. Then, the paper presents the basic idea of manifold learning and its relationship with subspace learning with focus on the dimensionality reduction problem. Finally, we present the Discriminant Principal Component Analysis (DPCA) and the Self-Organized Manifold Mapping (SOMM) algorithm to exemplify respectively pattern separation and completion techniques. We show experimental results to demonstrate the effectiveness of DPCA and SOMM algorithms on well-framed face image analysis. © 2011 IEEE.

关键词： Separation

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Adaptive critic design based dynamic optimal power flow controller for a smart grid

Adaptive critic design based dynamic optimal power flow cont...

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IEEE Symposium on Computational Intelligence Applications In Smart Grid (CIASG)

作者： Jiaqi Liang Ronald G. Harley Ganesh K. Venayagamoorthy School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA Real-Time Power and Intelligent Systems Laboratory Missouri University of Science and Technology Rolla MO USA

An adaptive critic design (ACD) based dynamic optimal power flow control (DOPFC) is proposed in this paper as a solution to the smart grid operation in a high short-term uncertainty and variability environment. With the increasing penetration of intermittent renewable generation, power system stability and security need to be ensured dynamically as the system operating condition continuously changes. The proposed DOPFC dynamically tracks the power system optimal operating point by continuously adjusting the steady-state set points from the traditional OPF algorithms. The ACD technique, specifically the dual heuristic dynamic programming (DHP), is used to provide nonlinear optimal control, where the control objective is formulated explicitly to incorporate system operation economy, stability and security considerations. A 12 bus test power system is used to demonstrate the development and effectiveness of the proposed ACD-based DOPFC using recurrent neural networks.

关键词： Power system dynamics Recurrent neural networks Generators Power system stability Automatic generation control Training

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SOLARE: Self-Organizing Latency-Aware Resource Ensemble

SOLARE: Self-Organizing Latency-Aware Resource Ensemble

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IEEE International Conference on High Performance computing and Communications (HPCC)

作者： Heungsik Eom David Isaac Wolinsky Renato J. Figueiredo Advanced Computing and Information Systems Laboratory Department of Electrical and Computer Engineering University of Florida Gainesville USA Department of Computer Science Yale University New Haven USA

This paper proposes and evaluates Self-Organizing Latency-Aware Resource Ensemble (SOLARE), a peer-to-peer self-organizing and self-managing cluster system based upon network coordinates and utility functions. In contrast to previous works, SOLARE is a fully decentralized clustering algorithm without any central units such as servers, super peers, cluster heads or landmarks. Furthermore, SOLARE allows for adaptability to dynamic network changes by monitoring the utility of a cluster and migrating nodes to other higher-utility clusters when the utility of an existing cluster is low. Quantitative, simulation-driven evaluations show that SOLARE is able to satisfy user demands expressed by utility functions that integrate system parameters in terms of intra cluster latencies and the number of cluster members. Also, we verify the ability of SOLARE to adapt to dynamic network changes through simulation based experiments that consider the number of nodes which migrate into another cluster and average utility value as nodes join SOLARE.

关键词： Peer to peer computing Clustering algorithms Monitoring computer architecture Servers Performance evaluation Heuristic algorithms

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