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A parallel NURBS-based isogeometric analysis framework on multi-core CPUs

Journal of Computational Information Systems 2012年第16期8卷 6589-6600页

作者： Guo, Licai Huang, Zhangjin Gu, Naijie School of Computer Science and Technology University of Science and Technology of China China Key Laboratory of Software in Computing and Communication Anhui China USTC-SICT Joint Laboratory on Network and Communication China

A parallel framework for NURBS-based isogeometric analysis on multi-core cpus is presented in this paper. The framework is composed of two parts: (1) construction of the stiffness matrix and right hand side vector;(2) a parallel sparse solver. We analyze the properties of NURBS basis, use the ELLPACK format to store the stiffness matrix. The parallel strategy is dividing the matrix and vectors into disjoint parts. Each core computes one part in parallel. We test the effectiveness and efficiency of the framework on an 8-core machine and a 48-core machine. The framework solves the 2-d poisson equation and can solve 1.05 million degrees of freedom in about 22 seconds using 32 cores. The speed-up of the construction reaches 28.3 using 32 cores. © 2012 Binary Information Press.

关键词： Stiffness matrix

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Clustering time-evolving data using an efficient differential evolution 6th

Clustering time-evolving data using an efficient differentia...

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6th International Conference on Swarm Intelligence, ICSI 2015 held in conjunction with the 2nd BRICS Congress on Computational Intelligence, CCI 2015

作者： Chen, Gang Luo, Wenjian Anhui Province key Laboratory of Software Engineering in Computing and Communication School of Computer Science and Technology University of Science and Technology of China HefeiAnhui China

ISBN: (纸本)9783319204659

The previous evolutionary clustering methods for time-evolving data usually adopt the temporal smoothness framework, which controls the balance between temporal noise and true concept drift of clusters. They, however, have two major drawbacks: (1) assuming a fixed number of clusters over time;(2) the penalty term may reduce the accuracy of the clustering. In this paper, a Multimodal Evolutionary Clustering (MEC) based on Differential Evolution (DE) is presented to cope with these problems. With an existing chromosome representation of the ACDE, the MEC automatically determines the cluster number at each time step. Moreover, instead of adopting the temporal smoothness framework, we try to deal with the problem from view of the multimodal optimization. That is, the species-based DE (SDE) for multimodal optimization is adopted in the MEC. Thus the MEC is a hybrid of the ACDE and the SDE, and designed for time-evolving data clustering. Experimental evaluation demonstrates the MEC achieves good results. © Springer International Publishing Switzerland 2015.

关键词： Cluster analysis

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A clustering system for gene expression data based upon genetic programming and the HS-model

A clustering system for gene expression data based upon gene...

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3rd International Joint Conference on Computational Sciences and Optimization, CSO 2010: Theoretical Development and Engineering Practice

作者： Liu, Guiquan Jiang, Xiufang Wen, Lingyun Key Laboratory of Software in Computing and Communication Anhui Province School of Computer Science and Technology University of Science and Technology of China Hefei Anhui 230027 China

ISBN: (纸本)9780769540306

Cluster analysis is a major method to study gene function and gene regulation information for there is a lack of prior knowledge for gene data. Many clustering methods existed at present usually need manual operations or predetermined parameters, which are difficult for gene data. Besides, gene data possess their own characteristics, such as large scale, high-dimension, and noise. Therefore, a systematic clustering algorithm should be proposed to effectively deal with gene data. In this paper, a novel genetic programming (GP) clustering system for gene data based on hierarchical statistical model (HS-model) is proposed. And an appropriate fitness function is also proposed in this system. This clustering system can largely eliminate the infection of data scale and dimension. The proposed GP clustering system is applied to cluster the whole intact yeast gene data without dimensionality reduction. The experimental results indicate that the algorithm is highly efficient and can effectively deal with missing values in gene dataset. © 2010 IEEE.

关键词： Cluster analysis

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A fast algorithm for finding community structure based on community closeness

A fast algorithm for finding community structure based on co...

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3rd International Joint Conference on Computational Sciences and Optimization, CSO 2010: Theoretical Development and Engineering Practice

作者： Jiang, Xiufang Liu, Guiquan Lin, Zhiting Key Laboratory of Software in Computing and Communication Anhui Province School of Computer Science and Technology University of Science and Technology of China Hefei Anhui 230027 China

ISBN: (纸本)9780769540306

Recently, the characterization of community structures in complex networks has received a considerable amount of attentions. Effective identification of these communities or clusters is a general problem in the field of data mining. In this paper we present a fast hierarchical agglomerative algorithm based on community closeness (FHACC) algorithm, for detecting community structure which is very efficient and faster than many other competing algorithms. FHACC tends to agglomerate such communities that share the most common vertices into larger ones. Its running time on a sparse network with n vertices and m edges is O(mk¯+mt), where k¯ denotes the mean vertex degree, and t is the iteration times of community agglomeration in FHACC algorithm. The algorithm was tested on several real-world networks and proved to be high efficient and effective in community finding. © 2010 IEEE.

关键词： Complex networks

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Chaos-based estimation method for software reliability

Chaos-based estimation method for software reliability

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2nd International Conference on Networks Security, Wireless communications and Trusted computing, NSWCTC 2010

作者： Shao, Chenxi Huang, Chao MOE-Microsoft Key Laboratory of Multimedia Computing and Communication University of Science and Technology of China Hefei Anhui China Computer Science Department University of Science and Technology of China Hefei Anhui China Anhui Province Key Laboratory of Software in Computing and Communication Hefei Anhui China

ISBN: (纸本)9780769540115

Reliability is one of the essential attributes of the dependable software, and an important factor for quantitatively characterizing software quality. Conventional methodology is software Reliability Growth Model (SRGM), which specifies the form of a random process that describes the behavior of software failures with respect to time. In this paper, we propose that the behavior of software failures possesses determinacy as well as randomness. So we apply chaos theory to software reliability assessment. Based on chaos theory, we can estimate software reliability according to the objective law hidden in the data, unlike the SRGM which usually makes a number of assumptions. This approach avoids the subjectivity in the SRGM. Also, we analyze the actual software failures data sets with the add-weighted one-rank localregion method (AOLM) based on chaos theory and compare the results with the conventional stochastic SRGM JM (Jelinsky-Moranda) model and NHPP (nonhomogeneous poisson process) mode. Comparison results show that the proposed method fits better than the stochastic ones. © 2010 IEEE.

关键词： software reliability

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A self-organized algorithm based on digital hormone

A self-organized algorithm based on digital hormone

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International Conference on Advanced Computer Theory and Engineering

作者： Xia, Li Xufa, Wang Yang, Lei Haifeng, You Key Laboratory of Software in Computing and Communication Anhui Province School of Computer Science and Technology University of Science and Technology of China Hefei China

ISBN: (纸本)9781424465408

In this paper, a self-organized algorithm for task allocation, based on the hormone reaction-diffusion mechanism, is proposed for a multi-robot system. Hormone messages are used to coordinate the movement of robots. By the regulation of hormones, agents could adjust their behaviors in time and improve the ability of self-organization. A simulation of task allocation in the multi-robot system is performed, experimental results demonstrate that our method can accomplish the task effectively and reduce the total cost. © 2010 IEEE.

关键词： Multipurpose robots

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A hormone-based clustering algorithm in wireless sensor networks

A hormone-based clustering algorithm in wireless sensor netw...

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2010 2nd International Conference on Computer Engineering and Technology, ICCET 2010

作者： Dong, Dayuan You, Haifeng Zhang, Yipeng Wang, Xufa Key Laboratory of Software in Computing and Communication Anhui Province School of Computer Science and Technology University of Science and Technology of China Hefei China

ISBN: (纸本)9781424463503

Clustering problem is one of the hottest issues in wireless sensor networks (WSNs). The strategy for selection of cluster head has not been sufficiently investigated. In this paper, we propose a hormone-based clustering algorithm (HCA) inspired by the communication mechanism of bio-endocrine system to prolong the lifetime of the sensor nodes. Two kinds of hormones, cluster hormone and member hormone, are used in the algorithm. Hormone message can promote a node to become a cluster head or a member node. Comparative experiment shows that the proposed algorithm has effectively prolong the lifetime of WSN compared with LEACH[1] and HEED[2]. © 2010 IEEE.

关键词： Clustering algorithms

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A hybrid particle swarm optimization for high-dimensional dynamic optimization 11th

A hybrid particle swarm optimization for high-dimensional dy...

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11th International Conference on Simulated Evolution and Learning, SEAL 2017

作者： Luo, Wenjian Yang, Bin Bu, Chenyang Lin, Xin Anhui Province Key Laboratory of Software Engineering in Computing and Communication School of Computer Science and Technology University of Science and Technology of China HefeiAnhui230027 China

ISBN: (纸本)9783319687582

High-Dimensional Dynamic Optimization Problems (HDDOPs) commonly exist in real-world applications. In evolutionary computation field, most of existing benchmark problems, which could simulate HDDOPs, are non-separable. Thus, we give a novel benchmark problem, called high-dimensional moving peaks benchmark to simulate separable, partially separable, and non-separable problems. Moreover, a hybrid Particle Swarm Optimization algorithm based on Grouping, Clustering and Memory strategies, i.e. GCM-PSO, is proposed to solve HDDOPs. In GCM-PSO, a differential grouping method is used to decompose a HDDOP into a number of sub-problems based on variable interactions firstly. Then each sub-problem is solved by a species-based particle swarm optimization, where the nearest better clustering is adopted as the clustering method. In addition, a memory strategy is also adopted in GCM-PSO. Experimental results show that GCM-PSO performs better than the compared algorithms in most cases. © Springer International Publishing AG 2017.

关键词： Particle swarm optimization (PSO)

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Multi-question negative surveys 3rd

Multi-question negative surveys

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3rd International Conference on Data Mining and Big Data, DMBD 2018 held in conjunction with the 9th International Conference on Swarm Intelligence, ICSI 2018

作者： Jiang, Hao Luo, Wenjiang Anhui Province Key Laboratory of Software Engineering in Computing and Communication School of Computer Science and Technology University of Science and Technology of China HefeiAnhui230027 China

ISBN: (纸本)9783319938028

The negative survey is an emerging method of collecting sensitive information. It could obtain the distribution of sensitive information while preserving the personal privacy. When collecting sensitive information, several questions are often provided together to the respondents. However, when reconstructing positive survey results of multiple questions, previous reconstruction methods have some shortcomings. In this paper, we propose a new reconstruction method for multi-question negative surveys. Experimental results show that our method could obtain more reasonable results. © Springer International Publishing AG, part of Springer Nature 2018.

关键词： Surveys

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An efficient synchronisation protocol for wireless sensor network

An efficient synchronisation protocol for wireless sensor ne...

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作者： Huang, Liusheng Xu, Hongli Wan, Yingyu Wu, Junmin Li, Hong Department of Computer Science and Technology University of Science and Technology of China Anhui Province Key Laboratory of Software in Computing and Communication Hefei 230027 China

Time synchronisation is a critical topic in wireless sensor networks for its wide applications, such as data fusion, TDMA scheduling and cooperated sleeping, etc. In this paper, we present an Accurate Time Synchronisation (ATS) protocol based on linear least square for sensor networks. Unlike the previous protocols, all nodes aren't synchronised to some reference nodes or sink node, but to a virtual clock. Moreover, each pair of the nodes is synchronised to each other. The main advantages of ATS are simplicity and accuracy. Especially, the variance of the synchronised drift error is less than Dsδ/ 2β 2, where Ds, δ and β are the depth of the network, the maximal variance of the link delay and the sampling interval, respectively. The experiments show that ATS protocol has achieved at least 37% performance enhancement than the previous pairwise algorithm. Copyright © 2007 Inderscience Enterprises Ltd.

关键词： Synchronization

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