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Congress on Evolutionary Computation

作者： Gang Chen Wenjian Luo Tao Zhu Anhui Province key Laboratory of Software Engineering in Computing and Communication University of Science and Technology of China Hefei Anhui China

ISBN: (纸本)9781479914869

Evolutionary clustering is a hot research topic that clusters the time-stamped data and it is essential to some important applications such as data streams clustering and social network analysis. An evolutionary clustering should accurately reflect the current data at any time step while simultaneously not deviate too drastically from the recent past. In this paper, the differential evolution (DE) is applied to deal with the evolutionary clustering problem. Comparing with the typical k-means, evolutionary clustering based on DE (deEC) could perform a global search in the solution space. Experimental results over synthetic and real-world data sets demonstrate that the deEC provides robust and adaptive solutions.

关键词： Clustering algorithms History Vectors Evolutionary computation Equations Sociology Statistics

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An improved genetic algorithm for dynamic shortest path problems

An improved genetic algorithm for dynamic shortest path prob...

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Congress on Evolutionary Computation

作者： Xuezhi Zhu Wenjian Luo Tao Zhu Anhui Province key Laboratory of Software Engineering in Computing and Communication University of Science and Technology of China Hefei Anhui China

The Shortest Path (SP) problems are conventional combinatorial optimization problems. There are many deterministic algorithms for solving the shortest path problems in static topologies. However, in dynamic topologies, these deterministic algorithms are not efficient due to the necessity of restart. In this paper, an improved Genetic Algorithm (GA) with four local search operators for Dynamic Shortest Path (DSP) problems is proposed. The local search operators are inspired by Dijkstra's Algorithm and carried out when the topology changes to generate local shortest path trees, which are used to promote the performance of the individuals in the population. The experimental results show that the proposed algorithm could obtain the solutions which adapt to new environments rapidly and produce high-quality solutions after environmental changes.

关键词： Sociology Statistics Heuristic algorithms Topology Algorithm design and analysis Digital signal processing Biological cells

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Combining multipopulation evolutionary algorithms with memory for dynamic optimization problems

Combining multipopulation evolutionary algorithms with memor...

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Congress on Evolutionary Computation

作者： Tao Zhu Wenjian Luo Lihua Yue Anhui Province Key Laboratory of Software Engineering in Computing and Communication Hefei Anhui China School of Computer Science and Technology University of Science and Technology of China Hefei Anhui China

ISBN: (纸本)9781479914869

Both multipopulation and memory are widely used approaches in the field of evolutionary dynamic optimization. It would be interesting to examine the effect of the combinations of multipopulation algorithms (MPAs) and memory schemes. However, since most of the existing memory schemes are proposed with single population algorithms, straightforwardly applying them to MPAs may cause problems. By addressing the possible problems, a new memory scheme is proposed for MPAs in this paper. In the experiments, several existing memory schemes and the newly proposed scheme are combined with a MPA, i.e. the Species-based Particle Swarm Optimizer (SPSO), and these combinations are tested on cyclic and acyclic problems. The experimental results indicate that 1) straightforwardly using the existing memory schemes sometimes degrades the performance of SPSO even on cyclic problems; 2) the newly proposed memory scheme is very competitive.

关键词： Sociology Statistics Memory management Optimization Heuristic algorithms Benchmark testing Particle swarm optimization

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26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 Antwerp, Belgium. 15-20 July 2017 Abstracts

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 95-176页

作者： [Anonymous] Department of Neuroscience Yale University New Haven CT 06520 USA Department Physiology & Pharmacology SUNY Downstate Brooklyn NY 11203 USA NYU School of Engineering 6 MetroTech Center Brooklyn NY 11201 USA Departament de Matemàtica Aplicada Universitat Politècnica de Catalunya Barcelona 08028 Spain Institut de Neurobiologie de la Méditerrannée (INMED) INSERM UMR901 Aix-Marseille Univ Marseille France Center of Neural Science New York University New York NY USA Aix-Marseille Univ INSERM INS Inst Neurosci Syst Marseille France Laboratoire de Physique Théorique et Modélisation CNRS UMR 8089 Université de Cergy-Pontoise 95300 Cergy-Pontoise Cedex France Department of Mathematics and Computer Science ENSAT Abdelmalek Essaadi’s University Tangier Morocco Laboratory of Natural Computation Department of Information and Electrical Engineering and Applied Mathematics University of Salerno 84084 Fisciano SA Italy Department of Medicine University of Salerno 84083 Lancusi SA Italy Dipartimento di Fisica Università degli Studi Aldo Moro Bari and INFN Sezione Di Bari Italy Data Analysis Department Ghent University Ghent Belgium Coma Science Group University of Liège Liège Belgium Cruces Hospital and Ikerbasque Research Center Bilbao Spain BIOtech Department of Industrial Engineering University of Trento and IRCS-PAT FBK 38010 Trento Italy Department of Data Analysis Ghent University Ghent 9000 Belgium The Wellcome Trust Centre for Neuroimaging University College London London WC1N 3BG UK Department of Electronic Engineering NED University of Engineering and Technology Karachi Pakistan Blue Brain Project École Polytechnique Fédérale de Lausanne Lausanne Switzerland Departement of Mathematics Swansea University Swansea Wales UK Laboratory for Topology and Neuroscience at the Brain Mind Institute École polytechnique fédérale de Lausanne Lausanne Switzerland Institute of Mathematics University of Aberdeen Aberdeen Scotland UK Department of Integrativ

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FACIAL ACTION UNIT RECOGNITION BY RELATION MODELING FROM BOTH QUALITATIVE KNOWLEDGE AND QUANTITATIVE DATA

FACIAL ACTION UNIT RECOGNITION BY RELATION MODELING FROM BOT...

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IEEE International Conference on Multimedia and Expo Workshops

作者： Zhen Gao Shangfei Wang Chongliang Wu Jun Wang Qiang Ji Key Lab of Computing and Communication Software of Anhui Province School of Computer Science and Technology University of Science and Technology of China Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute

ISBN: (纸本)9781479947164

In this paper, we propose to capture Action Unit (AU) relations existing in both qualitative knowledge and quantitative data through Credal Networks (CN). Each node of the CN represents an AU label, and the links and probability intervals capture the probabilistic dependencies among multiple AUs. The structure of CN is designed based on prior knowledge. The parameters of CN are learned from both knowledge and ground-truth AU labels. The AU preliminary estimations are obtained by an existing image-driven recognition method. With the learned credal network, we infer the true AU labels by combining the relationships among labels with the previous obtained estimations. Experimental results on the CK+ database and MMI database demonstrate that with complete AU labels, our CN model is slightly better than the Bayesian Network (BN) model, demonstrating that credal sets learned from data can capture uncertainty more reliably;With incomplete and error-prone AU annotations, our CN model outperforms the BN model, indicating that credal sets can successfully capture qualitative knowledge.

关键词： Prior knowledge Credal network AU recognition

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Classifying and clustering in negative databases

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Frontiers of Computer Science 2013年第6期7卷 864-874页

作者： Ran LIU Wenjian LUO Lihua YUE School of Computer Science and Technology University of Science and Technology of China Hefei 230027 China Anhui Province Key Laboratory of Software Engineering in Computing and Communication University of Science and Technology of China Hefei 230027 China

Recently, negative databases （NDBs） are proposed for privacy protection. Similar to the traditional databases, some basic operations could be conducted over the NDBs, such as select, intersection, update, delete and so on. However, both classifying and clustering in negative databases have not yet been studied. Therefore, two algorithms, i.e., a k nearest neighbor （kNN） classification algorithm and a k-means clustering algorithm in NDBs, are proposed in this paper, respectively. The core of these two algorithms is a novel method for estimating the Hamming distance between a binary string and an NDB. Experimental results demonstrate that classifying and clustering in NDBs are promising.

关键词： negative databases classification clustering k nearest neighbor k-means hamming distance

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Simultaneous measurement of refractive index, temperature and strain based on core diameter mismatch and polarization-maintaining FBG

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Optoelectronics Letters 2013年第3期9卷 238-240页

作者：童峥嵘王洁玉张卫华曹晔 Key Laboratory of Film Electronics and Communication Devices and Key Laboratory of Intelligent Computing and Novel Software Technology School of Computer and Communication Engineering Tianjin University of Technology

A kind of fiber-optic sensor for simultaneous measurement of refractive index of surrounding medium, temperature and strain is described. Based on core diameter mismatch, a multimode-single mode-multimode (MSM) structure is presented. It is demonstrated that the three parameters can be measured respectively by the interference of the core mode and cladding modes excited in the single mode fiber (SMF). Then combined with a polarization-maintaining fiber Bragg grating (PMFBG) which has different sensing properties from MSM structure, three parameters are measured simultaneously. The experimental results show that PMFBG is insensitive to the refractive index and the refractive index sensitivity of the MSM structure is 96.04 nm·RIU^(-1); the temperature sensitivities of the characteristic wavelength for MSM structure and the center wavelengths of fast and slow axes for PMFBG are 0.0911 nm °C^(-1), 0.00976 nm °C^(-1) and 0.0105 nm °C^(-1), respectively; the strain sensitivities of those are -0.013 nm με^(-1), 0.012 nm με^(-1) and 0.012 nm με^(-1), respectively.

关键词：温度敏感性应变灵敏度同时测量折射率不匹配光纤光栅直径 MSM结构

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Highly birefringent photonic crystal fibers with flattened dispersion and low confinement loss

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Optoelectronics Letters 2013年第1期9卷 45-48页

作者：曹晔李荣敏童峥嵘 Key Laboratory of Film Electronics and Communication Devices Key Laboratory of Intelligent Computing and Novel Software Technology School of Computer and Communication Engineering Tianjin University of Technology

A highly birefringent index-guiding photonic crystal fiber (PCF) with flattened dispersion and low confinement loss is proposed by introducing two small air holes with the same diameter in the core area. The fundamental mode field, birefringence, confinement loss, effective mode area and dispersion characteristic of the fibers are studied by the full-vector finite element method (FEM). Simulation results show that a high birefringence with the order of 10 -3 and a low confinement loss of 0.001 dB/km are obtained at 1550 nm. Furthermore, flattened chromatic dispersion from 1450 nm to 1590 nm is obtained.

关键词：光子晶体光纤平坦色散高双折射损耗矢量有限元法气孔直径折射指数色散特性

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IPRAR: A DFG-based approach to instruction clustering for multicluster VLIW DSP processor with SIMD structure

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Journal of Computational Information Systems 2014年第3期10卷 1257-1269页

作者： Yang, Yangzhao Gu, Naijie Zhao, Zeng Ren, Kaixin School of Computer Science and Technology University of Science and Technology of China Hefei 230027 China Anhui Province Key Laboratory of Computing and Communication Software Hefei 230027 China USTC and Loongson Technology Associated Laboratory Institute of Advanced Technology University of Science and Technology of China Hefei 230027 China

Modern Very Long Instruction (VLIW) DSP can improve performance by using instruction-level parallelism (ILP) and obtain better parallelism through instruction clustering. The essence of clustering is resource allocation. Traditional clustering method assumes that one instruction can only be assigned to a certain cluster, which is inapplicable to the architecture with SIMD structure. To address this issue, this paper presents IPRAR, a novel instruction clustering algorithm for the features of SIMD structure based on DFG. Due to considering the features of SIMD structure, IPRAR can be implemented on BWDSP100 with satisfactory. Besides, IPRAR can make the load of cluster more balanced and minimize the intercluster communication overload. Finally, numerous experiment results show that the IPRAR has an average of 7-10% performance improvement compared to the traditional methods. © 2014 Binary Information Press.

关键词： Clustering algorithms

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Optimizing BLAS2 for a decoupled access/execute architecture processor

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Journal of Computational Information Systems 2014年第3期10卷 1231-1241页

作者： Zhao, Zeng Gu, Naijie Yang, Yangzhao Ren, Kaixin School of Computer Science and Technology University of Science and Technology of China Hefei 230027 China USTC and Loongson Technology Associated Laboratory Institute of Advanced Technology University of Science and Technology of China Hefei 230027 China Anhui Province Key Laboratory of Computing and Communication Software Hefei 230027 China

Basic Linear Algebra Subroutines (BLAS) is a widely used basic mathematical library for high-performance computing. It has a great impact on the performance of supercomputers. This paper focuses on memory accessing optimization for the level-2 library of BLAS (BLAS2) based on Godson-3B chips. The key contribution of this work is proposing several methods to make full use of the Godson-3B's hardware features, as well as to improve the performance of memory access. GEMV, the kernel function of BLAS2, is selected to demonstrate the optimization methods for Godson-3B. Using Single Instruction Multiple Data (SIMD) instructions, Direct Register Access (DRA) and Direct Cache Access (DCA) of Godson-3B, two optimization algorithms for GEMV are introduced in this paper. Experiments show that the best computing performance of the optimized GEMVs on Godson-3B is more than 1.8Gops, which is far superior to that of other versions. While the test scale of GEMVs is greater than the size of L2-cache, its average performance exceeds UBLAS and OpenBlas, the two most famous optimized BLAS libraries for GODSON, by more than 60% and 20% respectively. © 2014 Binary Information Press.

关键词： Supercomputers

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