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Locally Linear Embedding for the Construction of the Purkinje System

Locally Linear Embedding for the Construction of the Purkinj...

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International Conference on Biomedical Engineering and computer science (ICBECS)

作者： Jie Li Kuanquan Wang Wangmeng Zuo Yongfeng Yuan Bio-computing Research Center School of Computer Science and Technology Harbin Institute of Science and Technology Harbin China

Locally linear embedding (LLE), recently proposed unsupervised procedure for mapping high-dimensional data nonlinearly to a lower-dimensional space, is shown to yield remarkable good results in exploratory analysis and visualization. LLE is able to learn the global structure of nonlinear manifolds, and it maps its inputs into a single global coordinate system of lower dimensionality, which takes good advantage of remaining points close to each other in the computed low-dimensional space when they are close to each other in the high-dimensional space. However, the application to the closed geometry is consequently limited. The purkinje system is a very important conduction system in the endocardial surface of the ventricle that is a semi-closed organ. Traditional construction of the purkinje system is mostly relevant to the fractal tree or something similar, which is based of supposed theory and is an approximation to the actuality. In this paper, a novel method for the construction of the purkinje system in the canine left ventricle by applying LLE algorithm is proposed. The results show that the construction of the purkinje system approaches the one in real structure of the left ventricle better than ever reconstructed.

关键词： Geometry Space technology Data visualization Image reconstruction computer science Fractals Biomedical imaging Magnetic resonance imaging Computed tomography Reconstruction algorithms

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On dynamic weighting of data in clustering with K-alpha means

On dynamic weighting of data in clustering with K-alpha mean...

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2010 20th International Conference on Pattern Recognition, ICPR 2010

作者： Chen, Si-Bao Wang, Hai-Xian Luo, Bin Key Lab. of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei Anhui 230039 China Key Lab. of Child Development and Learning Science Research Center for Learning Science Southeast University Nanjing Jiangsu 210096 China

ISBN: (纸本)9780769541099

Although many methods of refining initialization have appeared, the sensitivity of K-Means to initial centers is still an obstacle in applications. In this paper, we investigate a new class of clustering algorithm, K-Alpha Means (KAM), which is insensitive to the initial centers. With K-Harmonic Means as a special case, KAM dynamically weights data points during iteratively updating centers, which deemphasizes data points that are close to centers while emphasizes data points that are not close to any centers. Through replacing minimum operator in K-Means by alpha-mean operator, KAM significantly improves the clustering performances. © 2010 IEEE.

关键词： Clustering algorithms

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Subspace selection using semi-supervised harmonic mean of Kullback-Leibler divergences

Subspace selection using semi-supervised harmonic mean of Ku...

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2010 7th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2010

作者： Chen, Si-Bao Wang, Hai-Xian Luo, Bin Key Lab of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei Anhui 230039 China Key Lab of Child Development and Learning Science of Ministry of Education Research Center for Learning Science Southeast University Nanjing Jiangsu 210096 China

ISBN: (纸本)9781424459346

In many areas of pattern recognition and machine learning, subspace selection is an essential step. Fisher's linear discriminant analysis (LDA) is one of the most well-known linear subspace selection methods. However, LDA suffers from the class separation problem. The projection to a subspace tends to merge close class pairs. A recent result, named maximizing the geometric mean of Kullback-Leibler (KL) divergences of class pairs (MGMD), can significantly reduce the class separation problem. Furthermore, maximizing the harmonic mean of Kullback-Leibler (KL) divergences of class pairs (MHMD) emphasizes smaller divergences more than MGMD, and deals with the class separation problem more effectively. However, in many applications, labeled data are very limited while unlabeled data can be easily obtained. The estimation of divergences of class pairs is unstable using inadequate labeled data. To take advantage of unlabeled data for subspace selection, semi-supervised MHMD (SSMHMD) is proposed using graph Laplacian as normalization. Quasi-Newton method is adopted to solve the optimization problem. Experiments on synthetic data and real image data show the validity of SSMHMD. ©2010 IEEE.

关键词： Discriminant analysis

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An Approach for Evaluating Availability and Performability of Data Processing center in the Internet of Things Environment

An Approach for Evaluating Availability and Performability o...

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International Conference on Pervasive computing Signal Processing and Applications (PCSPA)

作者： Yi Feng Zhan Zhang Hao Liu De-Cheng Zuo Xiao-Zong Yang Dependable and Mobile Computing Center School of Computer Science & Technology Harbin Institute of Technology Harbin China

With the developing of pervasive computing technology especially the appearance of the internet of things, there will generate more tremendous real-time or OLTP information that requires the data center with high availability and performability. This paper proposes a hierarchical approach to model and evaluate the availability and performability of the transaction processing data center using throughout under fault-injection as reward rate. An example is given out to illustrate the use of the approach.

关键词： Availability Computational modeling Internet computers Fault tolerance Fault tolerant systems Maintenance engineering

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Manifold alignment via corresponding projections

Manifold alignment via corresponding projections

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2010 21st British Machine Vision Conference, BMVC 2010

作者： Zhai, Deming Li, Bo Chang, Hong Shan, Shiguang Chen, Xilin Gao, Wen School of Computer Science and Technology Harbin Institute of Technology China Digital Media Research Center Institute of Computing Technology CAS China Key Laboratory of Intelligent Information Processing Chinese Academy of Sciences China Institute of Digital Media Peking University China

ISBN: (纸本)1901725405

In this paper, we propose a novel manifold alignment method by learning the underlying common manifold with supervision of corresponding data pairs from different observation sets. Different from the previous algorithms of semi-supervised manifold alignment, our method learns the explicit corresponding projections from each original observation space to the common embedding space everywhere. Benefiting from this property, our method could process new test data directly rather than re-alignment. Furthermore, our approach doesn't have any assumption on the data structures, thus it could handle more complex cases and get better results compared with previous work. In the proposed algorithm, manifold alignment is formulated as a minimization problem with proper constraints, which could be solved in an analytical manner with closed-form solution. Experimental results on pose manifold alignment of different objects and faces demonstrate the effectiveness of our proposed method. © 2010. The copyright of this document resides with its authors.

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Digesting online multimedia presentation archives based on visual effects

Digesting online multimedia presentation archives based on v...

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5th International Conference on P2P, Parallel, Grid, Cloud and Internet computing, 3PGCIC 2010

作者： Watanabe, Yousuke Wu, Yi Yokota, Haruo Global Scientific Information and Computing Center Tokyo Institute of Technology 2-12-1 Ookayama Meguro-ku Tokyo 152-8552 Japan Department of Computer Science Graduate School of Information Science Tokyo Institute of Technology 2-12-1 Ookayama Meguro-ku Tokyo 152-8552 Japan

ISBN: (纸本)9780769542379

Online video archives provide a large amount of multimedia presentation contents through the Internet. But, it takes a long time to find what they really want to watch from a lot of presentation videos. We have been developing a system to summarize multiple presentation contents that match given keywords. In this paper, we intends to obtain a interesting digest including visually attractive scenes instead of generating a sketch of presentation contents. We propose methods to calculate the importance of scenes by considering color distribution and animation occurrence. Finally, we evaluate the effectiveness of the proposed methods. © 2010 IEEE.

关键词： Multimedia services

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News filtering and summarization on the Web

News filtering and summarization on the Web

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作者： Wu, Xindong Wu, Gong-Qing Xie, Fei Zhu, Zhu Hu, Xue-Gang Lu, Hao Li, Huiqian School of Computer Science and Information Engineering Hefei University of Technology China Zhejiang Taobao Network China Key Laboratory of Complex Systems and Intelligence Science Institute of Automation Chinese Academy of Sciences China Center for Social Computing and Parallel Systems Institute of Automation Chinese Academy of Sciences China

The news filtering and summarization (NFAS) system can automatically recognize Web news pages, retrieve each news page's title and news content, and extract key phrases. This extraction method substantially outper...

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Comprehensive Practice on Service Engineering: An Experimental Solution

Comprehensive Practice on Service Engineering: An Experiment...

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International Conference on Service sciences (ICSS)

作者： Zhongjie Wang Xiaofei Xu Dianhui Chu Lanshun Nie Tianyi Zang Xiaofeng Liu Research Center of Intelligent Computing for Enterprises and Services (ICES) School of Computer Science and Technology Harbin Institute of Technology Harbin China

ISBN: (纸本)9781424466030;9780769540177

To develop a well-designed curriculum of service engineering is a prerequisite for training students get new skills and ability to design and develop globally effective solutions in a service business environment. As service engineering is an application-oriented discipline, sufficient practice is extremely important. In this paper, we show an experimental solution of a course "comprehensive practice on service engineering", which has been explored for three years in Harbin Institute of technology. Its objective, process, execution program, and detailed design of each phase, are elaborately presented. Lessons learned from the explorations and future improvement on this solution, are briefly discussed.

关键词： Design engineering Knowledge engineering Engineering management Educational institutions Ice computer science Electronic mail Continuous improvement Systems engineering and theory Technological innovation

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Value Network Based Service Choreography Design and Evolution

Value Network Based Service Choreography Design and Evolutio...

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IEEE International Conference on e-Business Engineering (ICEBE)

作者： Zhongjie Wang Dianhui Chu Xiaofei Xu Research Center of Intelligent Computing for Enterprises and Services (ICES) School of Computer Science and Technology Harbin Institute of Technology Harbin China

We present a pattern-oriented service design and evolution approach by transforming the high-level service value network into service choreography scenario. In this approach, “value” is considered the ultimate goal of a service, and designing an executable SOA-based service system starts from the acquisition of business-level value exchange relationships between participants in the service. Such value information is modeled as Service Value Network (SVN). Following a four-step process, SVN is gradually mapped to software-level service choreography and the corresponding interface design, thereby keeping the consistency between both levels. Especially, we present five typical service value exchange patterns to facilitate the construction and transformation of SVN with higher efficiency. A case study from ocean transportation service is shown for demonstration.

关键词： Software Outsourcing Object oriented modeling Companies Copper Transportation

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The Bundling of Multiple Requirements for Maximizing the Utilization of Service Resources

The Bundling of Multiple Requirements for Maximizing the Uti...

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IEEE International Conference on e-Business Engineering (ICEBE)

作者： Zhongjie Wang Xiaofei Xu Dianhui Chu Xianzhi Wang Research Center of Intelligent Computing for Enterprises and Services (ICES) School of Computer Science and Technology Harbin Institute of Technology Harbin China

We present a service resource selection and scheduling approach capable of maximizing the resource utilization rate (RUT) and the requirement satisfaction degree (RSD) by bundling multiple customer requirements (CRs). In traditional approaches, each CR is optimally satisfied by independently selecting a set of candidate service resources. This possibly leads to a low RUT and low RSD. In our approach, multiple CRs raised within a certain time period are bundled and a virtual service resource (VSR) is constructed to satisfy these requirements simultaneously by making full use of the sharing nature of resources. Specifically, each CR is first decomposed into a set of atomic requirements, which are then re-aggregated according to their requested resources. For four types of service-resource sharing patterns, we present the corresponding greedy algorithms that construct the VSR and its scheduling. The goals of our methods are (1) maximizing the satisfaction degree of CRs and (2) maximizing the RUT of service resources. The effectiveness of our approach is demonstrated in an experiment for a typical scenario of ocean transportation service.

关键词： Strontium Concrete Job shop scheduling Resource management Quality of service Containers

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