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Computing the singular solution of power flow system

5th International Conference on Mechanical and Electrical Technology, ICMET 2013

作者： Ji, Zhen Yi Wu, Wen Yuan Li, Yi Feng, Yong Automated Reasoning and Cognition Key Lab Chongqing Institute of Green and Intelligent Technology Chinese Academy of Science Chongqing 401120 China Lab. of Computer Reasoning and Trustworthy Comput School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu 611731 China

ISBN: (纸本)9783037858349

The purpose of this paper is to compute the singular solution of the nonlinear equations arising in power flow system. Based on the approximate null space of the Jacobian matrix, more equations are introduced to the origin system. Meanwhile, the Jacobian matrix of augmented equations at initial value is full rank, then the algorithm recovers quadratic convergence of Newton's iteration. The algorithm in this paper leads to higher accuracy of the singular solution and less iteration steps. In addition, two power flow systems are studied in this paper and the results show this new method has high accuracy and efficiency compared with traditional Newton iteration © (2013) Trans Tech Publications, Switzerland.

关键词： Newton-Raphson method

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Error control schemes in solar energy harvesting wireless sensor networks

Error control schemes in solar energy harvesting wireless se...

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2012 International Symposium on Communications and Information Technologies, ISCIT 2012

作者： Jalali, Fatemeh Khodadoustan, Safieh Ejlali, Alireza School of Science and Engineering Sharif University of Technology International Campus Iran Department of Computer Engineering Embedded System Research Lab. Sharif University of Technology Iran

ISBN: (纸本)9781467311571

To scavenge the energy from the environment and extend the network lifetime, some wireless sensor networks (WSNs) have been equipped with energy harvesters recently. However, the variable amount of environmental energy can affect the reliability of energy harvesting wireless sensor networks (EH-WSNs). In addition, data transmission over a wireless media is vulnerable. Hence, utilizing suitable error control schemes are necessary to improve the reliability. Regarding this point, Automatic Repeat Request (ARQ) and Cooperative ARQ (C-ARQ) schemes are applied in this generation of WSNs. Conventional ARQ as well as C-ARQ scheme are considered and examined through simulation. A comparative analysis of these two schemes in terms of energy consumption, energy efficiency and reliability is provided. This analysis shows that C-ARQ is the more appropriate error control scheme in EH-WSNs to manage the variable environmental energy and improve the reliability and energy efficiency. © 2012 IEEE.

关键词： Wireless sensor networks

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Poster abstracts

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Sleep and Biological Rhythms 2016年第1期5卷 A1-A189页

作者： J. Ferrie M. Shipley F. Cappuccio E. Brunner M. Miller M. Kumari M. Marmot A. Coenen J. L. Castillo F. Araya G. Bustamante L. Montecino C. Torres S. Oporto J. Gronli E. Fiske R. Murison B. Bjorvatn E. Sorensen R. Ursin C. M. Portas S. Rajaraman A. Gribok N. Wesensten T. Balkin J. Reifman N. Dursunoglu S. Ozkurt S. Baser O. Delen S. Sarikaya P. Sadler P. Mitchell D. Françon M. Decobert B. Herve A. Richard G. Griebel P. Avenet B. Scatton G. L. Fur D. Eckert A. Jordan A. Wellman S. Smith A. Malhotra D. White D. Bruck I. Thomas A. Kritikos W. Oertel K. Stiasny-Kolster D. Garcia-Borreguero W. Poewe B. Hoegl R. Kohnen E. Schollmayer J. Keffel C. Trenkwalder A. Valle S. Roizenblatt F. Fregni P. Boggio S. Tufik K. Ward L. Robertson L. Palmer P. Eastwood D. Hillman J. Lee S. Mukherjee V. de Padova G. Barbato G. Ficca I. Zilli P. Salzarulo M. Veldi T. Hion V. Vasar M. Kull L. Nowak J. Davis Y. Latzer O. Tzischinsky S. Crowley M. Carskadon M. Anca-Herschkovitsch D. Frey J. Ortega C. Wiseman C. Farley K. Wright A. Campbell A. Neill K. Spiegel R. Leproult E. Tasali N. Scherberg E. van Cauter A. T. Noradina N. A. Karim I. Norlinah A. A. Raymond R. Sahathevan B. Hamidon E. Werth R. Poryazova R. Khatami C. Bassetti R. G. Beran L. Ainley G. Holand J. Duncan H. Kinney B. Davis B. Hood S. Frey C. Schmidt M. Hofstetter P. Peigneux C. Cajochen W.-P. Hu J.-D. Li C. Zhang L. Boehmer J. Siegel Q.-Y. Zhou Y. Sagawa H. Kondo T. Takemura H. Kanayama Y. Kaneko M. Sato T. Kanbayashi Y. Hishikawa T. Shimizu A. Viola L. James L. Schlangen D.-J. Dijk R. Andretic Y.-C. Kim K.-A. Han F. Jones R. Greenspan L. Sanford L. Yang X. Tang K. Dieter E. Uta H. Sven M. Richard N. Oyane S. Pallesen F. Holsten Y. Inoue M. Fujita N. Emura K. Kuroda N. Uchimura A. Johnston J. Astbury G. Kennedy K. Hoedlmoser M. Schabus T. Pecherstorfer S. Moser G. Gruber P. Anderer W. Klimesch N. Naidoo M. Ferber A. Pack D. Neu O. Mairesse G. Hoffmann A. Dris L. Lambrecht P. Linkowski P. Verbanck O. Le Bon N. Matsuura M. Yamao N. Adachi R. Aritomi Y. Komada H. Tanaka S. Shirak University College London London UK University College London London USA Warwick Medical School London UK Warwick Medical School Coventry USA Radboud University Nijmegen Nijmegen Netherlands Department of Neurology University of Chile Santiago Chile Neurology Service Hospital del Salvador Santiago Chile Family Health Center Juan Pablo II Santiago Chile Department of Biomedicine Section on Physiology Univeristy of Bergen Bergen Norway Department of Public Health and Primary Health Care Univeristy of Bergen Bergen Norway Department of Public Health and Primary Health Care University of Bergen Bergen Norway Norwegian Competence Center for Sleep Disorders Haukeland University Hospital Bergen Norway Department of Child and Adolescent Psychiatry Haukeland University Hospital Univeristy of Bergen Bergen Norway Department of Biomedicine University of Bergen Bergen Norway US Army Medical Research and Materiel Command Fort Detrick Frederick USA Walter Reed Army Institute of Research Silver Spring USA Department of Behavioral Biology Walter Reed Army Institute of Research Silver Spring USA Faculty Department of Pulmonology Pamukkale University Medical Denizli Turkey University of Ballarat Ballarat Australia Sanofi-Aventis Recherche et Developpement Paris France Brigham and Women’s Hospital Harvard Medical School Boston USA The University of Queensland Adelaide Australia School of Psychology University of Queensland Brisbane Australia The University of Queensland Brisbane Australia Victoria University Melbourne Australia Department of Psychology Victoria University Melbourne Australia School of Psychology Victoria University Melbourne Australia Philips-Universität Marburg Germany Philips-Universitaet-Marburg Marburg Germany Instituto de Investigaciones del Sueno Madrid Spain Universitätsklinik für Neurologie Innsbruck Austria Universitaetsklinik fuer Neurologie Innsbruck Austria IMEREM GmbH Nuernberg Germany Schwarz Pharma AG Monheim Germany

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Memetic three-dimensional gabor feature extraction for hyperspectral imagery classification

Memetic three-dimensional gabor feature extraction for hyper...

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3rd International Conference on Swarm Intelligence, ICSI 2012

作者： Zhu, Zexuan Shen, Linlin Sun, Yiwen He, Shan Ji, Zhen City Key Laboratory of Embedded System Design College of Computer Science and Software Engineering Shenzhen University Shenzhen 518060 China Shenzhen Key Lab. of Biomedical Engineering School of Medicine Shenzhen University 518060 China School of Computer Science University of Birmingham Edgbaston Birmingham B15 2TT United Kingdom

ISBN: (纸本)9783642309755

This paper proposes a three-dimensional Gabor feature extraction for pixel-based hyperspectral imagery classification using a memetic algorithm. The proposed algorithm named MGFE combines 3-D Gabor wavelet feature generation and feature selection together to capture the signal variances of hyperspectral imagery, thereby extracting the discriminative 3-D Gabor features for accurate classification. MGFE is characterized with a novel fitness evaluation function based on independent feature relevance and a pruning local search for eliminating redundant features. The experimental results on two real-world hyperspectral imagery datasets show that MGFE succeeds in obtaining significantly improved classification accuracy with parsimonious feature selection. © 2012 Springer-Verlag.

关键词： Feature Selection

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A multiple feature fusion model for image segmentation based on hierarchical visual pathway

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Advances in Information sciences and Service sciences 2012年第8期4卷 274-282页

作者： Hu, Dekun Li, Jianping Yang, Simon X. Gregori, Stefano School of Computer Science and Engineering University of Electronic Science and Technology of China China Advanced Robotics and Intelligent Systems Lab School of Engineering University of Guelph Canada

To segment an object from its background in an image for advanced vision processing, this paper presents a novel bio-inspired general framework for image segmentation in complex nature scenes, which is a hierarchical system that mimics the organization of layered early visual area in primate visual cortex. The proposed methodology consists of two typical stages: the first stage is a parallel modular structure including three segmenting operators based on color feature, form feature and texture feature, each of which solves the segmentation problem independently for the same input. Then, a fusion operation, multiple feature fusion segmentation (MFFS), integrates these three feature segmentations together through the backpropagation neuron network (BPNN) in the last stage, which simulates the operation of area following the lateral geniculate nucleus in primary visual cortex. The proposed approach is applied to several segmentation experiments of many single objects in clustering conditions, the result shows that the approach is capable of competing with state-of-the-art systems.

关键词： Neural networks

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MOEA/D with iterative thresholding algorithm for sparse optimization problems

MOEA/D with iterative thresholding algorithm for sparse opti...

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12th International Conference on Parallel Problem Solving from Nature, PPSN 2012

作者： Li, Hui Su, Xiaolei Xu, Zongben Zhang, Qingfu Institute for Information and System Sciences Key Lab. for Intelligent Networks and Network Security Xi'an Jiaotong University Xi'an Shaanxi 710049 China School of Computer Science and Electronic Engineering University of Essex Wivenhoe Park Colchester CO4 3SQ United Kingdom

ISBN: (纸本)9783642329630

Currently, a majority of existing algorithms for sparse optimization problems are based on regularization framework. The main goal of these algorithms is to recover a sparse solution with k non-zero components(called k-sparse). In fact, the sparse optimization problem can also be regarded as a multi-objective optimization problem, which considers the minimization of two objectives (i.e., loss term and penalty term). In this paper, we proposed a revised version of MOEA/D based on iterative thresholding algorithm for sparse optimization. It only aims at finding a local part of trade-off solutions, which should include the k-sparse solution. Some experiments were conducted to verify the effectiveness of MOEA/D for sparse signal recovery in compressive sensing. Our experimental results showed that MOEA/D is capable of identifying the sparsity degree without prior sparsity information. © 2012 Springer-Verlag.

关键词： Multiobjective optimization

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Model checking cooperative multi-agent systems in BDI logic

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Journal of Information and Computational science 2012年第5期9卷 1185-1194页

作者： Chen, Qingliang Su, Kaile Wu, Lijun Xu, Zhaocheng School of Electronics Engineering and Computer Science Peking University Beijing 100871 China Department of Computer Science Jinan University Guangzhou 510632 China Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai China Institute for Integrated and Intelligent Systems Griffith University Brisbane Australia School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China

Traditional temporal logics such as LTL (Linear Temporal Logic) and CTL (Computation Tree Logic) have shown tremendous success in specifying and verifying hardware and software systems. However, this kind of logic can only model the dynamic behaviors for a single system, and fall short in capturing the joint and concurrent aspects in the composition of systems, such as the interactions and coordinations of agents in Multi-agent systems. Although ATL (Alternating-time Temporal Logic) can solve the problem to a certain extent, by preceding the temporal operators with a selective path quantifier, to specify that the interactions between entities inside the system can make sure that there is a strategy to reach a certain state, it can not formalize the rational mental attitudes of the agents such as the Belief, Desire and Intention (BDI) which plays an essential role in decision making during cooperation with other agents. This paper will investigate this problem by proposing a logic of ATLBDI (Alternating-time Temporal Logic of Belief Desire and Intention) and discuss the algorithmic issues such as model checking algorithms and the computational complexity, along with examples to show its effectiveness. We conclude that model checking for ATLBDI is completely tractable and is in PTIME-Complete, which is quite an optimistic and promising result for further applications. © 2012 by Binary Information Press.

关键词： Multi agent systems

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Skull-closed autonomous development: Object-wise incremental learning

Skull-closed autonomous development: Object-wise incremental...

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9th International Symposium on Neural Networks, ISNN 2012

作者： Wang, Yuekai Wu, Xiaofeng Weng, Juyang State Key Lab. of ASIC and System Fudan University Shanghai 200433 China Department of Electronic Engineering Fudan University Shanghai 200433 China School of Computer Science Fudan University Shanghai 200433 China Dept. of Computer Sci. and Eng. Michigan State University East Lansing MI 48824 United States

ISBN: (纸本)9783642313455

The series of Where-What Networks (WWNs) is a brain-inspired developmental model that simulates the dorsal (where) stream and the ventral (what) stream that converge to the motor area in the frontal cortex. Since developmental learning is always incremental, the order of different stimuli should affect the outcome of learning. In contrast to the uniform distribution of stimuli across image frames used in prior WWN experiments, this work studies non-uniform distribution in the sense that during training one object is presented at all the image locations before another object is presented. A new mechanism called cell regenesis is introduced to enable a less-often used cell to recommit its neuronal resource to new stimuli. The experimental results shown in this paper indicate that WWN-6 can deal with object-wise incremental learning. © 2012 Springer-Verlag.

关键词： computer vision

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A biologically-inspired network for generic object recognition using CUDA

A biologically-inspired network for generic object recogniti...

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2009 11th IEEE International Conference on e-Health Networking, Applications and Services, Healthcom 2009

作者： Wang, Yuekai Wu, Xiaofeng Song, Xiaoying Zhang, Wenqiang Weng, Juyang State Key Lab. of ASIC and System Fudan University Shanghai 200433 China Department of Electronic Engineering Fudan University Shanghai 200433 China School of Computer Science Fudan University Shanghai 200433 China Dept. of Computer Sci. and Eng. Michigan State University East Lansing MI 48824 United States

Generic object recognition is one of the most important fields in the artificial intelligence. Some cortex-like networks for generic object recognition are proposed these years. But most of them concentrated on the discussion about the recognition performance (such as recognition rate, number of objects to be recognized), not the practicability, i.e., implementation with ubiquitous devices and application in real time. This paper reports a try on implementation of a biologically-inspired where-what network (WWN), which integrates object recognition and attention in a single network, via parallelizing the various stages of the network training with CUDA on GPU to shorten the training time. The experiment on HAIBAO Robot exhibited in 2010 Shanghai Expo shows that this optimization can achieve a speedup of almost 16 times compared to the C-based program on an Intel Core 2 DUO 3.00 GHZ CPU in real environments. © 2012 Springer-Verlag GmbH.

关键词： Object recognition

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Error Control Schemes in Solar Energy Harvesting Wireless Sensor Networks

Error Control Schemes in Solar Energy Harvesting Wireless Se...

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International Symposium on Communications and Informaiton Technologies

作者： Fatemeh Jalali Safieh Khodadoustan Alireza Ejlali School of Science & Engineering Sharif University of Technology Department of Computer Engineering Embedded System Research Lab. Sharif University of Technology

ISBN: (纸本)9781467311564

关键词： Automatic repeat request ERROR CONTROL Wireless sensor networks Scheme Energy sources Energy efficiency Solar Energy

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