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Corrigendum to “Fast and scalable lock methods for video coding on many-core architecture” [J. Vis. Commun. 25 (7) (2014) 1758–1762]

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Journal of Visual Communication and Image Representation 2015年 26卷 350-350页

作者： Weizhi Xu Hui Yu Dianjie Lu Fenglong Song Da Wang Xiaochun Ye Songwei Pei Dongrui Fan Hongtao Xie Institute of Microelectronics Tsinghua University Beijing China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing China Key Lab. of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China School of Information Science and Engineering Shandong Normal University Jinan China Department of Computer Science and Technology Beijing University of Chemical Technology Beijing China Institute of Information Engineering Chinese Academy of Sciences National Engineering Laboratory for Information Security Technologies Beijing China

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Corrigendum to “Fast and scalable lock methods for video coding on many-core architecture” [J. Vis. Commun. Image R. 25(7) (2014) 1758–1762]

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Journal of Visual Communication and Image Representation 2015年 27卷 57-57页

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Laplacian normalization and random walk on heterogeneous networks for disease-gene prioritization

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Computational biology and chemistry 2015年 57卷 21-8页

作者： Zhi-Qin Zhao Guo-Sheng Han Zu-Guo Yu Jinyan Li Hunan Key Laboratory for Computation and Simulation in Science and Engineering and Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University Xiangtan Hunan 411105 China. Hunan Key Laboratory for Computation and Simulation in Science and Engineering and Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University Xiangtan Hunan 411105 China School of Mathematical Sciences Queensland University of Technology GPO Box 2434 Brisbane Q4001 Australia. Electronic address: yuzg1970@***. Advanced Analytics Institute & Centre for Health Technologies University of Technology Sydney Broadway NSW 2007 Australia. Electronic address: jinyan.li@uts.edu.au.

Random walk on heterogeneous networks is a recently emerging approach to effective disease gene prioritization. Laplacian normalization is a technique capable of normalizing the weight of edges in a network. We use this technique to normalize the gene matrix and the phenotype matrix before the construction of the heterogeneous network, and also use this idea to define the transition matrices of the heterogeneous network. Our method has remarkably better performance than the existing methods for recovering known gene-phenotype relationships. The Shannon information entropy of the distribution of the transition probabilities in our networks is found to be smaller than the networks constructed by the existing methods, implying that a higher number of top-ranked genes can be verified as disease genes. In fact, the most probable gene-phenotype relationships ranked within top 3 or top 5 in our gene lists can be confirmed by the OMIM database for many cases. Our algorithms have shown remarkably superior performance over the state-of-the-art algorithms for recovering gene-phenotype relationships. All Matlab codes can be available upon email request.

关键词： Disease genes and phenotypes Heterogeneous network Laplacian normalization Leave-one-out cross-validation Random walk with restart Shannon information entropy

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Coordinated obstacle avoidance with reduced interaction

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Neurocomputing 2014年 139卷 233-245页

作者： Jiaojie Li Wei Zhang Housheng Su Yupu Yang Hongtao Zhou Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 China Department of Measurement and Control Technology Shanghai Dian Ji University Shanghai 200240 China School of Automation Key Laboratory of Education Ministry for Image Processing and Intelligent Control Huazhong University of Science and Technology Luoyu Road 1037 Wuhan 430074 China

In this paper, we study the coordinated obstacle avoidance algorithm of multi-agent systems when only a subset of agents has obstacle dynamic information, or every agent has local interaction. Each agent can get partial measuring states information from its neighboring agent and obstacle. Coordinated obstacle avoidance here represents not only the agents moving without collision with an obstacle, but also the agents bypassing and assembling at the opposite side of the obstacle collectively, where the opposite side is defined according to the initial relative position of the agents to the obstacle. We focus on the collective obstacle avoidance algorithms for both agents with first-order kinematics and agents with second-order dynamics. In the situation where only a fixed fraction of agents can sense obstacle information for agents with first-order kinematics, we propose a collective obstacle avoidance algorithm without velocity measurements. And then we extend the algorithm to the case in switched topology. We show that all agents can bypass an obstacle and converge together, and then assemble at the opposite side of the obstacle in finite time, if the agents׳ topology graph is connected and at least one agent can sense the obstacle. In the case where obstacle information is available to only a fixed fraction of agents with second-order kinematics, we propose two collective obstacle avoidance algorithms without measuring acceleration when the obstacle has varying velocity and constant velocity. The switched topology is considered and extended next. We show that agents can bypass the obstacle with their positions and velocities approaching consensus in finite time if the connectivity of switched topology is continuously maintained. Several simulation examples demonstrate the proposed algorithms.

关键词： Obstacle avoidance Consensus Reduced interaction Circular motion Multi-agents

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Multifractal analysis of weighted networks by a modified sandbox algorithm

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Scientific reports 2015年第1期5卷 17628页

作者： Yu-Qin Song Jin-Long Liu Zu-Guo Yu Bao-Gen Li Hunan Key Laboratory for Computation and Simulation in Science and Engineering and Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University Xiangtan Hunan 411105 China. College of Science Hunan University of technology Zhuzhou Hunan 412007 China. School of Mathematical Sciences Queensland University of Technology Brisbane Q4001 Australia.

Complex networks have attracted growing attention in many fields. As a generalization of fractal analysis, multifractal analysis (MFA) is a useful way to systematically describe the spatial heterogeneity of both theoretical and experimental fractal patterns. Some algorithms for MFA of unweighted complex networks have been proposed in the past a few years, including the sandbox (SB) algorithm recently employed by our group. In this paper, a modified SB algorithm (we call it SBw algorithm) is proposed for MFA of weighted networks. First, we use the SBw algorithm to study the multifractal property of two families of weighted fractal networks (WFNs): "Sierpinski" WFNs and "Cantor dust" WFNs. We also discuss how the fractal dimension and generalized fractal dimensions change with the edge-weights of the WFN. From the comparison between the theoretical and numerical fractal dimensions of these networks, we can find that the proposed SBw algorithm is efficient and feasible for MFA of weighted networks. Then, we apply the SBw algorithm to study multifractal properties of some real weighted networks - collaboration networks. It is found that the multifractality exists in these weighted networks, and is affected by their edge-weights.

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MULTI-TRACKING OF FIRST ORDER MULTI-AGENT NETWORKS VIA SELF-TRIGGERED CONTROL

MULTI-TRACKING OF FIRST ORDER MULTI-AGENT NETWORKS VIA SELF-...

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西南大学2014年全国博士生学术论坛(电子技术与信息科学领域)

作者： Guang-Song Han Zhi-Hong Guan Jie Chen Ding-Xin He Ming Chi College of Automation Huazhong University of Science and Technology Wuhan 430074 China and the Key Laboratory of Image Information Processing and Intelligent Control (Huazhong University of Science and Technology) Ministry of Education Wuhan 430074 China

A multi-tracking problem of multi-agent networks is investigated in this paper where multi-tracking refers to that the states of multiple agents in each subnetwork asymptotically converge to the same desired trajectory in the presence of information exchanges among *** multi-tracking of first order multi-agent networks with directed topologies was ***-triggered protocols were proposed along with triggering functions to solve the stationary multi-tracking and bounded dynamic *** self-triggered scheduling is obtained, and the system does not exhibit Zeno *** examples are provided to illustrate the effectiveness of the obtained criteria.

关键词： Multi-agent networks stationary multi-tracking bounded dynamic multi-tracking self-triggered control

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Protein folding structure optimization based on GAPSO algorithm in the off-lattice model

Protein folding structure optimization based on GAPSO algori...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Xiaoli Lin Xiaolong Zhang Department of City College Wuhan University of Science and Technology Wuhan China Hubei Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Wuhan China

ISBN: (纸本)9781479956708

Predicting the spacial folding structure of a protein, given its sequence of amino acids, is one of the central problems in computational biology field. This paper studies the AB off-lattice model with two species of monomers, called hydrophobic (A) and hydrophilic (B). Based on this simplified model, the low energy configurations are searched by using the GAPSO. A kind of optimization about the mutation mechanism and the Euclidean interference mechanism are presented, where a novel local adjustment strategy is also used to enhance the searching ability of the global minimum within the AB off-lattice model. Starting from random conformations, the GAPSO method can find the low-energy conformation of the Fibonacci sequences and the real protein sequences. Compared with other optimization methods, the proposed novel method could converge to the lower energy folds. It appears that the proposed method can used for solving protein folding problem, which is based on the thermodynamic hypothesis.

关键词： Proteins Amino acids Interference Particle swarm optimization Optimization Sociology Statistics

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A Survey of Commonsense Knowledge Acquisition

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Journal of Computer Science & technology 2013年第4期28卷 689-719页

作者：臧良俊曹聪曹亚男吴昱明曹存根 Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences University of the Chinese Academy of Sciences The Second Lab Institute of Information Engineering Chinese Academy of Sciences

Collecting massive commonsense knowledge （CSK） for commonsense reasoning has been a long time standing challenge within artificial intelligence research. Numerous methods and systems for acquiring CSK have been developed to overcome the knowledge acquisition bottleneck. Although some specific commonsense reasoning tasks have been presented to allow researchers to measure and compare the performance of their CSK systems, we compare them at a higher level from the following aspects： CSK acquisition task （what CSK is acquired from where）, technique used （how can CSK be acquired）, and CSK evaluation methods （how to evaluate the acquired CSK）. In this survey, we first present a categorization of CSK acquisition systems and the great challenges in the field. Then, we review and compare the CSK acquisition systems in detail. Finally, we conclude the current progress in this field and explore some promising future research issues.

关键词： commonsense knowledge knowledge acquisition knowledge representation and reasoning

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Block-Based Salient Region Detection Using a New Spatial-Spectral-Domain Contrast Measure

Block-Based Salient Region Detection Using a New Spatial-Spe...

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IEEE International Symposium on Multimedia

作者： Nan Mu Xin Xu Li Chen Jing Tian Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Wuhan China School of Computer Science and Technology Wuhan University of Science and Technology Wuhan China

ISBN: (纸本)9781479943104

Visual saliency is an important cue in human visual system, it can identify salient region in image. Image contrast has been utilized as an effective feature to detect the salient region. The conventional contrast measures utilize both spectral and spatial properties of image in many salient region detection methods. However, they only consider the local characteristics of image region, consequently, the global characteristics are neglected. This paper presented a new contrast measure by exploiting both local and global characteristics of image regions. Furthermore, the proposed measure is utilized to perform salient region detection in image. Experiments are conducted on the MSRA test database to compare the performance of the proposed approach with the state-of-the-art salient region detection algorithms.

关键词： Spectral analysis Computer vision Visualization Computational modeling Pattern recognition Databases Image color analysis

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An energy efficient cluster-based routing protocol for intelligent environmental monitoring system

An energy efficient cluster-based routing protocol for intel...

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International Conference on Systems and Informatics (ICSAI)

作者： Dapeng Cheng Yingjie Song Yanyan Mao Xiangrong Wang School of Computer Science and Technology Shandong Institute of Business and Technology Yantai China College of Information Science and Engineering Shandong University of Science and Technology Qingdao China Key Laboratory of Intelligent Information Processing in Universities of Shandong (Shandong Institute of Business and Technology) Yantai china

ISBN: (纸本)9781479954599

Routing is a basic service for intelligent environmental monitoring system. However, traditional routing protocols cause unnecessary energy consumption due to the high communication overhead. In this paper, we proposed RERP, an energy efficient cluster-based routing protocol for intelligent environmental monitoring system. RERP improves LEACH protocol by limiting the selection range of cluster head. RERP also achieves reasonable cluster head election by considering residual energy, relative density and centroid distance. Simulation results show that RERP can save 54 th percentile energy more than LEACH after 2000 clustering rounds. When the network size is 500, RERP can still guarantee 99.6% nodes alive after 2000 clustering rounds.

关键词： Wireless sensor networks Artificial intelligence Clustering algorithms Nominations and elections Routing protocols Environmental monitoring

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