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A NEW CASCADING FAILURE MODEL WITH DELAY TIME IN CONGESTED COMPLEX NETWORKS

Journal of Systems Science and Systems engineering 2009年第3期18卷 369-381页

作者： Jian WANG Yanheng LIU Yu JIAO College of Computer Science and Technology Jilin University Changchun 130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun 130012 China

Cascading failures often occur in congested complex networks. Cascading failures can be expressed as a three-phase process： generation, diffusion, and dissipation of congestion. Different from the betweenness centrality, a congestion function is proposed to represent the extent of congestion on a given node. Inspired by the restart process of a node, we introduce the concept of ＂delay time,＂ during which the overloaded node Cannot receive or forward any traffic, so an intergradation between permanent removal and nonremoval is built and the flexibility of the presented model is demonstrated. Considering the connectivity of a network before and after cascading failures is not cracked because the overloaded node are not removed from network permanently in our model, a new evaluation function of network efficiency is also proposed to measure the damage caused by cascading failures. Finally, we investigate the effects of network structure and size, delay time, processing ability, and traffic generation speed on congestion propagation. Cascading processes composed of three phases and some factors affecting cascade propagation are uncovered as well.

关键词： Complex networks cascading failures congestion effects propagation model

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Genetic algorithm with affinity propagation

Genetic algorithm with affinity propagation

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International Conference on Information and Automation (ICIA)

作者： Chunguo Wu Hao Gao Lianjiang Yu Yanchun Liang Rongwu Xiang College of Computer Science and Technology Key Laboratory for Symbol Computation and Knowledge Engineering of National Education Ministry Jilin University Changchun China School of Basic Courses Shenyang Pharmaceutical University Shenyang China

ISBN: (纸本)9781424457014

Classical genetic algorithm suffers heavy pressure of fitness evaluation for time-consuming optimization problems, e.g., aerodynamic design optimization, qualitative model learning in bioinformatics. To address this problem, we present a combination between genetic algorithms and clustering methods. Specifically, the clustering method used in this paper is affinity propagation. The numerical experiments demonstrate that the proposed method performs promisingly for well-known benchmark problems in the term of optimization accuracy.

关键词： Genetic algorithms Clustering methods Evolutionary computation Design optimization Optimization methods Design automation Computer science Educational technology Pharmaceutical technology knowledge engineering

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A hybrid algorithm of minimum spanning tree and nearest neighbor for classifying human cancers

A hybrid algorithm of minimum spanning tree and nearest neig...

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International Conference on Advanced Computer Theory and engineering, ICACTE

作者： Chunbao Zhou Liming Wan Yanchun Liang College of Computer Science and Technology Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Jilin University Changchun China Research Institute on General Development and Evaluation of Equipment EAAF of PLA Beijing China

ISBN: (纸本)9781424465392

Classification and prediction of different cancers based on gene expression profiles are important for cancer diagnosis, cancer treatment and medication discovery. The k nearest neighbor algorithm (k-NN) is one easy and efficient machine learning method for cancer classification and the parameter k is crucial. In this paper, we integrate minimum spanning tree (MST) and k nearest neighbor algorithm (k-NN) for cancer classification. The MST is designed for the selection of parameter k and the nearest neighbors for k-NN. Firstly we build a minimum spanning tree (MST) based on Euclidean distance between each two samples for gene expression data only including one unknown class sample. Secondly for unknown class sample in the gene expression data, we find the connected samples and then apply majority vote principle. Thirdly if there are tied votes then we expend the connected samples with the nearest neighbors for unknown class sample until all the samples are expended or the class for unknown sample is obtained. This hybrid algorithm is referred to as MSTNN. The hybrid algorithm MSTNN is compared with k-NN and other 3 existing classification algorithms on CNS dataset, Colon dataset and Lung dataset, 3 binary class gene expression datasets and 3 multi-class gene expression datasets: Leukemia1, Leukemia2, and Leukemia3 involving human cancers. The MSTNN algorithm improves 5.65% better than k-NN on average LOOCV accuracy and 13.80% better than k-NN on testing datasets classification average accuracy, and achieves the best performance in all the 5 algorithms. The results demonstrate that the proposed MSTNN algorithm is feasible to classify human cancers.

关键词： Classification algorithms Artificial neural networks Niobium Lungs Colon Support vector machines Cancer

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Deriving all minimal consistency-based diagnosis sets using SAT solvers

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Progress in Natural Science:Materials International 2009年第4期19卷 489-494页

作者： Xiangfu Zhao a,b, Liming Zhang a,b, Dantong Ouyang a,b, Yu Jiao a,b a key laboratory of symbolic computation and knowledge engineering of Ministry of Education, jilin university, Changchun 130012, China b School of Computer Science and Technology, jilin university, Changchun 130012, China [a]Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun 130012 China [b]School of Computer Science and Technology Jilin University Changchun 130012 China

In this paper, a novel method is proposed for judging whether a component set is a consistency-based diagnostic set, using SAT solv- ers. Firstly, the model of the system to be diagnosed and all the observations are described with conjunctive normal forms (CNF). Then, all the related clauses in the CNF files to the components other than the considered ones are extracted, to be used for satisfiability checking by SAT solvers. Next, all the minimal consistency-based diagnostic sets are derived by the CSSE-tree or by other similar algorithms. We have implemented four related algorithms, by calling the gold medal SAT solver in SAT07 competition – RSAT. Experimental results show that all the minimal consistency-based diagnostic sets can be quickly computed. Especially our CSSE-tree has the best effciency for the singleor double-fault diagnosis.

关键词： Conjunctive normal form Consistency-based diagnosis Model-based diagnosis SAT solver

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Ontology based automatic attributes extracting and queries translating for deep web

Journal of Software

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Journal of Software 2010年第7期5卷 713-720页

作者： Liang, Hao Ren, Fei Zuo, Wanli He, Fengling College of Computer Science and Technology Jilin University Changchun 130012 China Department of Information Changchun Taxation College Changchun 130117 China China Development Bank Center of Operations Beijing 100037 China Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Changchun 130012 China

Search engines and web crawlers can not access the Deep Web directly. The workable way to access the hidden database is through query interfaces. Automatic extracting attributes from query interfaces and translating queries is a solvable way for addressing the current limitations in accessing Deep Web. However, the query interface provides semantic constraints, some attributes are co-occurred and the others are exclusive sometimes. To generate a valid query, we have to reconcile the key attributes and semantic relation between them. We design a framework to automatically extract attributes from query interfaces taking full advantage of instances information and enrich the attribute sets embedded in the semantic query interface by Ontology technique. Each attribute is extended into a candidate attribute expressed by a hierarchy tree and describes the semantic relation of the attributes. We carry out our experiments in the real-world domain and results showed the validation of query translation framework. © 2010 ACADEMY PUBLISHER.

关键词： Ontology

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Computing minimal diagnosis with binary decision diagrams algorithm

Computing minimal diagnosis with binary decision diagrams al...

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6th International Conference on Fuzzy Systems and knowledge Discovery, FSKD 2009

作者： Wang, Kun Li, Zhan-Shan Ai, Yang Zhang, Yong-Gang Key Laboratory of Symbolic Computation Knowledge Engineering for Ministry of Education Jilin University Jilin Changchun China

ISBN: (纸本)9780769537351

In this paper we propose an algorithm of computing minimal diagnosis based on BDD (Binary Decision Diagram). First we give the concept of disjunction equations, and map the collection of conflict sets into disjunction equations, then we compile the system into a BDD, further we compute the minimal hitting sets by solving the BDD and minimizing hitting sets. The reliability and completeness of the algorithm are proved. Variable ordering and construct controlling of BDD are used to further reduce the size of final BDD and the number of non-minimal hitting sets to be generated. The efficiency of computing minimal hitting sets is highly improved. Experimental results show that the algorithm isn't restricted by the structure of system and conflict sets, compared with three algorithms in the references, it can generate all the minimal hitting sets, and it works well in random circumstances. © 2009 IEEE.

关键词： Binary decision diagrams

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An Efficient Method for Calculating Qualitative Spatial Relations

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电子学报(英文版) 2009年第1期18卷 42-46页

作者： WANG Shengsheng LIU Dayou College of Computer Science and Technology Key Laboratory of Symbolic Computing and Knowledge Engineering of Ministry of Education Jilin University Changchun 130012 China

Qualitative spatial relations are widely used in geospatial ontologies, geospatial (semantic) web services, spatial description logics etc. Methodology to obtain qualitative spatial relations (especially complex spatial relations) from Geographical information system (GIS) has not been studied in previous literatures. An efficient method for calculating complex qualitative spatial relations is discussed here. First, the multi-granularities approximate representation of spatial objects is proposed, it is designed for GIS object types (such as polygon), and requires less process time. Then some algorithms for calculating complex spatial relations based on the multi-granularities approximate representation are given. Finally, this method is implemented and used to obtain topology and direction relations from world map. The analysis and test results show that this method supports complex and integrated spatial relations and requires less process time than traditional method. This method is suitable for obtaining spatial relations for geospatial ontologies and other applications.

关键词：空间关系计算地理信息系统地理本体信息系统设计网络服务描述逻辑空间对象

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An approach to accelerate diagnosis by isomorphic determining

An approach to accelerate diagnosis by isomorphic determinin...

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2009 International Conference on Information engineering and Computer Science, ICIECS 2009

作者： Wang, Xiaoyu Ouyang, Dantong Feng, Yuxuan Zhao, Jian College of Computer Science and Technology Jilin University Key Laboratory Symbolic Computation and Knowledge Engineering Ministry of Educaion Changchun China

ISBN: (纸本)9781424449941

When diagnosing dynamic system represented as discrete-event systems, it needs to find what happened to the systems from observations. The behavior of system could be represented by automaton model. The diagnostic task consists in determining the models compatible with the observations, but the global computation which is needed in synchronization costs exponential time. In this paper we propose a new method to simplify the automaton by isomorphic determining. The cost of computation will be significantly cut down by merging the automatons with the same structure, and the time-complexity of the diagnosis process could be reduced by the method. ©2009 IEEE.

关键词： Discrete event simulation

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A model for representing topological relations between regions with holes

A model for representing topological relations between regio...

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1st International Conference on Information Science and engineering, ICISE2009

作者： Huo, Linlin Ouyang, Jihong Liu, Dayou College of Computer Science and Technology Jilin University China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun China

ISBN: (纸本)9780769538877

This paper proposes a unified model - D9-intersection model to represent topological relations between regions with holes. D9-intersection model can describe simple regional relations as accurately as 9-intersection model. When holes are allowed, D9-intersection model can distinguish relations that 9 - intersection could not and then be more expressive than 9-intersection model. In addition, we present the reasoning method based on D9-intersection model restricting to regions with at most one hole. ©2009 IEEE.

关键词： Topology

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K-means on commodity GPUs with CUDA

K-means on commodity GPUs with CUDA

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2009 WRI World Congress on Computer Science and Information engineering, CSIE 2009

作者： Bai, Hong-Tao He, Li-Li Ouyang, Dan-Tong Li, Zhan-Shan Li, He College of Computer Science and Technology Jilin University 130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Jilin University 130012 China

ISBN: (纸本)9780769535074

K-means algorithm is one of the most famous unsupervised clustering algorithms. Many theoretical improvements for the performance of original algorithms have been put forward, while almost all of them are based on Single Instruction Single Data (SISD) architecture processors (CPUs), which partly ignored the inherent paralleled characteristic of the algorithms. In this paper, a novel Single Instruction Multiple Data (SIMD) architecture processors (GPUs) based k-means algorithm is proposed. In this algorithm, in order to accelerate compute-intensive portions of traditional k-means, both data objects assignment and k centroids recalculation are off-loaded to the GPU in parallel. We have implemented this GPU-based k-means on the newest generation GPU with Compute Unified Device Architecture (CUDA). The numerical experiments demonstrated that the speed of GPU-based k-means could reach as high as 40 times of the CPU-based k-means. © 2008 IEEE.

关键词： Graphics processing unit

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