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A novel approach to identify influential functions in complex software network based on complex network

ICIC Express Letters 2016年第2期10卷 485-492页

作者： Huang, Guoyan Chen, Xiaojuan Wu, Hongfei Zhang, Peng Ren, Jiadong College of Information Science and Engineering No. 438 West Hebei Ave Qinhuangdao China Computer Virtual Technology and System Integration Laboratory of Hebei Province Yanshan University No. 438 West Hebei Ave Qinhuangdao China

Identifying influential nodes is an important issue in understanding the process of information diffusion in complex software networks. Researchers generally define functions as nodes, and relationship of function calls as edges to map software into complex network. This paper proposes a novel approach to identify the influential nodes in complex software network based on complex network. Firstly, we map the function and relationship of function calling or dependency to a directed weighted call network (DWCN). Secondly, we define NodeScore (NS) to evaluate the importance of nodes in network. It has higher influence when the node has lager value of NS. The NS of each node is calculated by two parts in our opinion, Direct Dependency Nodes (DDN) and Indirect Dependency Nodes (IDN). Thirdly, algorithm ComputeNodeScore is proposed to calculate NS of each node. Finally, we mine top-k nodes based on the NS. Experimental results of various versions about software Tar and cflow show the approach is effective for identifying the influential nodes. © 2016, ICIC Express Letters ICIC International.

关键词： Complex networks

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Mining critical nodes in software execution network based on complex network

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ICIC Express Letters, Part B: Applications 2016年第9期7卷 1879-1884页

作者： Wang, Lei Dong, Jun Ren, Jiadong College of Information Science and Engineering Yanshan University No. 360 Hebei Ave Qinhuangdao066004 China E & A College Hebei Normal University of Science and Technology No. 360 Hebei Ave Qinhuangdao066004 China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province No. 438 Hebei Ave Qinhuangdao066004 China

It is significant for measuring the importance of nodes accurately to improve software stability and robustness in software network. A software execution directed network takes function as a node and relationship of function as an edge in this paper. To nd the critical nodes in the network, a novel method is proposed to measure the nodes' importance by means of depth search mining in software execution. According to the principle of cascading failure, a novel critical nodes metrics FID is dened for nodes measuring and sorting. Critical nodes mining (CNM) algorithm is put forward for calculating FID value of each node and sorting. We choose top-ranking nodes as critical nodes which play an important role in software execution process. Experimental results show that CNM algorithm can measure the critical nodes accurately in software network. © 2016 ICIC International.

关键词： Complex networks

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Critical node measuring method improved based on pagerank and betweenness

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ICIC Express Letters, Part B: Applications 2016年第11期7卷 2381-2387页

作者： Wang, Lei Dong, Jun Ren, Jiadong College of Information Science and Engineering Yanshan University No. 438 Hebei Ave. Qinhuangdao066004 China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province No. 438 Hebei Ave. Qinhuangdao066004 China E&A College Hebei Normal University of Science and Technology No. 360 Hebei Ave. Qinhuangdao066004 China

In software execution network, PageRank and betweenness methods are used to determine the importance of nodes. The experiment results show that the differences between nodes are not strong and cannot reflect the software nodes’ importance degree. In order to solve this problem, this paper adds the entropy weight method to the calculation of node weights, and puts the weights of nodes into the computing of two measuring methods above. Finally, we get the ranking result of nodes’ importance which means we can find out the critical nodes from top ones. Experimental results indicate that the method is efficient for critical node measuring. © 2016 ICIC International.

关键词： Surveying

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Skin panel design for a morphing mechanism

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ICIC Express Letters, Part B: Applications 2016年第10期7卷 2161-2167页

作者： Zhao, Qiang Guo, Xliuan Xi, Fengfeng Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province College of Information Science and Engineering Yanshan University No. 438 Hebei Avenue Qinhuangdao066004 China Department of Aerospace Engineering Ryerson University TorontoONM5B 2K3 Canada

A segmentation method is proposed to aid rigid skin panel design for an existing modular morphing wing mechanism. The method divides the surface of the modular morphing mechanism into panels through geometry discretization, and then the skin which is made up of these rigid panels will have better rigidity and it will morph more free without any gap. The method comprises three basic morphing types based on the motion of upper platform. Wherein, the mechanism side is firstly divided into a plurality of panels and each of them is approximated to flat, and then shape changes of one panel before and after morphing are analyzed. Therefore, panels can be designed as moveable and fixed patches to achieve seamless morphing. At last, computer simulation is set up to further verify the correctness of the method. © 2016 ICIC International.

关键词： Morphing mechanism Seamless morphing Skin panel Surface segmentation

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Point cloud coarse matching method for similar objects

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ICIC Express Letters 2016年第9期10卷 2283-2289页

作者： Zhao, Qiang Guo, Xijuan Zhang, Buying Bai, Xinyu Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Yanshan University No. 438 Hebei Ave. Qinhuangdao066004 China College of Information Science and Engineering Yanshan University No. 438 Hebei Ave. Qinhuangdao066004 China Technical Center Shenyang Aircraft Corporation Shenyang110850 China

Point cloud matching is much more difficult when an initial estimate of the relative pose is not known. In order to reduce the effect of relative pose on matching operation and improve the computing speed, this article presents a method to fast match the pose of two similar objects through the covariance of their point cloud coordinates. This paper contains three parts. In the first part, a matrix is constructed through the values of point coordinates of one object and then a set of orthogonal vectors will be obtained through eigenvector of the matrix. Rotation matrix will be obtained by comparing the vectors of two similar objects. In the second part, a description of procedures is given and the complexity of the algorithm is analyzed. In the last part, the experiment shows the proposed method has high computing efficiency and the matching results are acceptable. © 2016 ICIC International.

关键词： Covariance matrix

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An improved community discovery algorithm in weighted social networks

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ICIC Express Letters 2016年第1期10卷 35-41页

作者： Guo, Jingfeng Liu, Miaomiao Liu, Linlin Chen, Xiao College of Information Science and Engineering Yanshan University No. 438 West Hebei Ave Qinhuangdao China College of Information Science and Engineering Northeast Petroleum University No. 199 Fazhan Road Daqing China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province No. 438 West Hebei Ave Qinhuangdao China

The algorithm AGMA (Automatic Graph Mining Algorithm) is improved and a novel community discovery algorithm, namely CRMA (Clustering Re-clustering Merging Algorithm) is proposed which can realize more reasonable community division for weighted social networks. Firstly, in the re-clustering stage, AGMA neglected the clustering situation of neighbors of current node and it did not take the weights of edges connecting the current node and its unclustered neighbors into account, which led to that some nodes cannot be clustered or their clustering was unreasonable. Aiming to this, the concept of the connection compactness between the node and the community is introduced, and then through clustering and re-clustering each node would be divided into the community that has the largest connection compactness with the node according to the node weight, the edge weight and the friend coecient between the node and the community. Secondly, for community division in some unweighted networks and signed networks, if there are many nodes whose clustered neighbors are less than its unclustered neighbors, the division results of AGMA tend to result in the lower modularity. In view of this problem, the concepts of positive edge weight density, the cluster density and the connection coecient between clusters are proposed. Lastly, communities are merged based on the above three concepts after re-clustering and the modularity is eectively enhanced. The higher correctness and better generality of the improved algorithm are veried through experiments. © 2016 ICIC International.

关键词： Clustering algorithms

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Semantic analysis and retrieval of spatial data based on the uncertain ontology model in Digital Earth

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International Journal of Digital Earth 2015年第1期8卷 3-16页

作者： Shengtao Sun Lizhe Wang Rajiv Ranjan Aizhi Wu The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province School of Information Science and EngineeringYanshan UniversityQinhuangdaoChina Institute of Remote Sensing and Digital Earth Chinese Academy of SciencesBeijingChina Computational Informatics CSIROCanberraACTAustralia College of Vehicles and Energy Yanshan UniversityQinhuangdaoChina

Metadata are the information about and description of *** Digital Earth,metadata become variant and heterogeneous with many *** paper studies uncertain features in the generation and application of metadata,and two types of uncertainties(incomplete and imprecise)are described based on semantic quantitative measurement method semantic relationship quantitative measurement based on possibilistic logic and probability statistic(SRQ-PP).Moreover,in the case study,we apply two types of quantitative measurements based on SRQ-PP to describe incomplete(uncertain)knowledge and imprecise(vague)information separately in spatial data service retrieval,which in turn is helpful to identify additional potential data resources and provide a quantitative analysis of the results.

关键词： metadata semantic ontology uncertainty measurement spatial data digital earth

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A novel collaborative recommendation algorithm integrating probabilistic matrix factorization and neighbor model

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Journal of Information and Computational Science 2015年第5期12卷 2011-2019页

作者： Yu, Hongtao Dou, Lisha Zhang, Fuzhi The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province School of Information Science and Engineering Yanshan University Qinhuangdao China

The existing collaborative recommendation algorithms suffer from lower recommendation precision due to the problem of data sparsity. To solve this problem, we propose a novel collaborative recommendation algorithm which integrates the probabilistic matrix factorization and neighbor models. We first propose a method to calculate the similarity between users or items based on the probabilistic matrix factorization model and construct a natural exponential function to compute the weighted similarity. Then we devise a collaborative recommendation algorithm to make recommendations for the target user, which dynamically adjusts the recommendation results for user-and item-based models by the balance adjustment factor. The experimental results on the MovieLens dataset show that the proposed algorithm outperforms the existing algorithms in terms of prediction accuracy. Copyright © 2015 Binary Information Press.

关键词： Exponential functions

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Research on community detection in social network based on Pairwise Merging

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Journal of Computational Information systems 2015年第19期11卷 7079-7086页

作者： Chen, Jing Wan, Yun Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Qinhuangdao China College of Information Science and Engineering Yanshan University Qinhuangdao China

Community detection has become an important challenge during the past decade. Network is divided into some groups or communities that are densely connected to each other inside while less connected to the nodes outside. Community detection in social networks using hybrid merging of sub-communities is proposed. It is based on the idea of bottom to up. But the initial phase of algorithm resulted in many sub- communities and hybrid merging generated some weak communities. In order to resolve these problems, the algorithm CDPM (Community Detection based on Pairwise Merging of sub-communities) is proposed in this paper. The main idea of the algorithm starts with some small communities. Then, these small communities are extended by using similarity in order to decrease the number of sub-communities. Finally, these sub-communities are merged by pairwise merging which is mainly based on maximization modularity. Meanwhile, checking structure of every community is to avoid the appearance of weak community. The CDPM is proved on two real networks, and the results show that the performance of CDPM is close to real network and the quality of community detection is improved. © 2015 by Binary Information Press.

关键词： Merging

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Community detection algorithm in signed social networks based on statistics and merger

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Journal of Information and Computational Science 2015年第15期12卷 5589-5599页

作者： Guo, Jingfeng Zhao, Yue Hu, Xinzhuan Liu, Yuanying College of Information Science and Engineering Yanshan University Qinhuangdao China Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Qinhuangdao China

Researches on community detection in signed social networks focus on the assignment of positive and negative edges. However, the community detection approaches that positive and negative edges are handled separately in two phases cannot make full use of negative edges, which seriously affects the accuracy of community detection. To solve the problem, a new algorithm called CDA SM (Community Detection Algorithm Based on Statistics and Merger) is proposed: merge into the two phases as an unified process;in the process of community detection, the node shall be added to the community in which the node has the maximum contribution as well as the minimum interference degree. The accuracy and time efficiency of CDA SM have been demonstrated through a set of experiments including both un-weighted common networks and un-weighted signed social networks. © 2015 by Binary Information Press

关键词： Signal detection

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