检索结果-内蒙古大学图书馆

Explicit determination of mean first-passage time for random walks on deterministic uniform recursive trees

Physical Review E 2010年第1期81卷 016114-016114页

作者： Zhongzhi Zhang Yi Qi Shuigeng Zhou Shuyang Gao Jihong Guan School of Computer Science Fudan University Shanghai 200433 China Shanghai Key Lab of Intelligent Information Processing Fudan University Shanghai 200433 China Department of Computer Science and Technology Tongji University 4800 Cao’an Road Shanghai 201804 China

The determination of mean first-passage time (MFPT) for random walks in networks is a theoretical challenge, and is a topic of considerable recent interest within the physics community. In this paper, according to the known connections between MFPT, effective resistance, and the eigenvalues of graph Laplacian, we first study analytically the MFPT between all node pairs of a class of growing treelike networks, which we term deterministic uniform recursive trees (DURTs), since one of its particular cases is a deterministic version of the famous uniform recursive tree. The interesting quantity is determined exactly through the recursive relation of the Laplacian spectra obtained from the special construction of DURTs. The analytical result shows that the MFPT between all couples of nodes in DURTs varies as N ln N for large networks with node number N. Second, we study trapping on a particular network of DURTs, focusing on a special case with the immobile trap positioned at a node having largest degree. We determine exactly the average trapping time (ATT) that is defined as the average of FPT from all nodes to the trap. In contrast to the scaling of the MFPT, the leading behavior of ATT is a linear function of N. Interestingly, we show that the behavior for ATT of the trapping problem is related to the trapping location, which is in comparison with the phenomenon of trapping on fractal T-graph although both networks exhibit tree structure. Finally, we believe that the methods could open the way to exactly calculate the MFPT and ATT in a wide range of deterministic media.

关键词： Eigenvalues and eigenfunctions

来源：评论

学校读者我要写书评

暂无评论

A Robust Method for License Plate Detection

A Robust Method for License Plate Detection

引用

Pacific-Rim Symposium on Image and Video technology (PSIVT)

作者： Jian Luo Su Yang Ruimin Guan Haijun Niu School of Computer Science and Technology & Shanghai Key Laboratory of Intelligent Information Processing Fudan University Shanghai China

License plate detection plays an important role in vehicle license plate recognition for intelligent transport systems. This paper presents a robust method for license plate detection. As we observed, license plate area contains rich corner points' information. The whole procedure is as follows: (1) Extract the interesting points using Harris corner detector in enhanced car image. (2) Cluster the corner points and apply outlier detection to every cluster. (3) Merge the clusters close to each other and use the gradient information to find the proper block in which the license plate area is enclosed. (4) Train a simple cascade classifier to classify the blocks into two categories: The area possibly containing license plate and those not. (5) Detect the plate region by the rectangle window. Experimental results demonstrate the robustness and the generality of our method.

关键词： Licenses Image edge detection Clustering algorithms Image color analysis Feature extraction Classification algorithms Robustness

来源：评论

学校读者我要写书评

暂无评论

Protein backbone dihedral angle prediction based on probabilistic models

Protein backbone dihedral angle prediction based on probabil...

引用

The 4th International Conference on Bioinformatics and Biomedical Engineering(第四届IEEE生物信息与生物医学工程国际会议 iCBBE 2010)

作者： Xin Geng Jihong Guan Shuigeng Zhou Qiwen Dong Dept.of Computer Science and Technology Tongji University Shanghai China Shanghai Key Lab of Intelligent Information Processing School of Computer Science Fudan University

Protein backbone dihedral angles are important descriptors of local conformation for amino acids. Protein backbone dihedral angle prediction lays the foundation for prediction of higher-order protein structure. Existing prediction methods of protein backbone angles mainly exploit traditional machine learning techniques. In this paper, we propose to use two well-known types of probabilistic models ---maximum entropy Markov models (MEMMs) and conditional random fields (CRFs) to predict the backbone dihedral angles of amino acid sequences. Experiments conducted on dataset PDB25 show that these two probabilistic models are effective in dihedral angle prediction, and CRFs outperform MEMMs.

关键词： Proteins Spine Predictive models Amino acids Sequences Hidden Markov models Entropy Support vector machines Support vector machine classification computer science

来源：评论

学校读者我要写书评

暂无评论

A novel theory of business process virtualiztion on E-commerce

引用

ICIC Express Letters 2010年第2期4卷 381-387页

作者： Hong, Daocheng Ling, Hong Li, Yangmei School of Management Key Lab of Intelligent Information Processing Fudan University Shanghai 200433 China School of Computer Science and Shanghai Key Lab of Intelligent Information Processing Fudan University Shanghai 200433 China Research Center for Marketing Shanghai China Express Co. Ltd Shanghai 200433 China

In practice, many commercial activities that have traditionally beenconducted via physical mechanisms are being conducted virtually by means ofinformation technology (IT). Visualization of business process has beenreceiving more and more attention in the management literatures. However, fewdocuments research IT-enabled business process of e-commerce from theperspective of media interactivity and richness. This paper focuses oncommercial activities and proposes a novel theory of business processvirtualization (BPV) with theory construction methodology. BPV theory provides anew lens for researching e-commerce and process management which are playing acritical role in contemporary research field. With BPV theory, the unique case -development of mobile-banking in China is interpreted properly as a case ofapplication. Additionally, the conceptual framework also has superiorinstructional and explanatory power for both research and practice. ICIC International © 2010.

关键词： Electronic commerce

来源：评论

学校读者我要写书评

暂无评论

Homology based Multi-instance Kernel combination for Gram-negative protein subcelluar localization

Homology based Multi-instance Kernel combination for Gram-ne...

引用

International Conference on Bioinformatics and Biomedical technology (ICBBT)

作者： Suyu Mei Wang Fei Shanghai Key Laboratory of Intelligent Information Processing School of Computer Science Fudan University Shanghai China

ISBN: (纸本)9781424467754;9781424467761

Previous computational models generally exclude homology out of the training set to reduce potential predictive bias. This paper proposes a hierarchical kernel to incorporate homology for more accurate similarity definition between two protein sequences. Metaphorized as the scenario of multi-instance learning, a homologous sequence is viewed as one evolutionary instance of the target sequence and all the homologous sequences constitute one homology bag. The bottom-level kernel is defined as k-mer spectrum kernel to define the similarity between any two instances; the middle-level multi-instance kernel is defined as the sum of all the spectrum kernels, actually the similarity definition between two homology bags, called Homology-based Multi-instance Kernel (HoMIKernel). By varying k-mer size and compressing 20 amino acids, we can derive multiple HoMIKernels, which are further combined into the top-level kernel called HoMIKernel+ to capture more contextual information and cover size-varying motifs. We evaluate HoMIKernel+ on Gram-negative benchmark dataset. The experiments show that HoMIKernel+ achieves better predictive performance than the baseline models and the incorporation of homologous sequences does increase the predictive performance.

关键词： Kernel Amino acids Protein sequence Predictive models Feature extraction laboratories information processing computer science Computational modeling Computational intelligence

来源：评论

学校读者我要写书评

暂无评论

Nonparametric regression for the short-term traffic flow forecasting

Nonparametric regression for the short-term traffic flow for...

引用

International Conference on Mechanic Automation and Control Engineering (MACE)

作者： Tao Zhang Lifang Hu Zhixin Liu Yuejie Zhang School of information Management and Engineering Shanghai University of Finance and Economics Shanghai China School of Computer Science Shanghai Key Laboratory of Intelligent Information Processing Fudan University Shanghai China

ISBN: (纸本)9781424477371

This paper uses the K-NN based nonparametric regression to forecast the short term traffic flow, applies the prediction interval calculated by K to forecast during unconventional road condition, and improves the forecasting results. Finally, nonparametric regression's advantages of high accuracy and strong transplant ability are showed while being compared with neural network.

关键词： Telecommunication traffic Economic forecasting Traffic control Predictive models Nearest neighbor searches Databases Runtime technology forecasting Weather forecasting Finance

来源：评论

学校读者我要写书评

暂无评论

Determining global mean-first-passage time of random walks on Vicsek fractals using eigenvalues of Laplacian matrices

引用

Physical Review E 2010年第3期81卷 031118-031118页

作者： Zhongzhi Zhang Bin Wu Hongjuan Zhang Shuigeng Zhou Jihong Guan Zhigang Wang School of Computer Science Fudan University Shanghai 200433 China Shanghai Key Lab of Intelligent Information Processing Fudan University Shanghai 200433 China Department of Mathematics College of Science Shanghai University Shanghai 200444 China Department of Computer Science and Technology Tongji University 4800 Cao’an Road Shanghai 201804 China Mahle Technologies Holding (China) Co. Ltd. Shanghai 201400 China

The family of Vicsek fractals is one of the most important and frequently studied regular fractal classes, and it is of considerable interest to understand the dynamical processes on this treelike fractal family. In this paper, we investigate discrete random walks on the Vicsek fractals, with the aim to obtain the exact solutions to the global mean-first-passage time (GMFPT), defined as the average of first-passage time (FPT) between two nodes over the whole family of fractals. Based on the known connections between FPTs, effective resistance, and the eigenvalues of graph Laplacian, we determine implicitly the GMFPT of the Vicsek fractals, which is corroborated by numerical results. The obtained closed-form solution shows that the GMFPT approximately grows as a power-law function with system size (number of all nodes), with the exponent lies between 1 and 2. We then provide both the upper bound and lower bound for GMFPT of general trees, and show that the leading behavior of the upper bound is the square of system size and the dominating scaling of the lower bound varies linearly with system size. We also show that the upper bound can be achieved in linear chains and the lower bound can be reached in star graphs. This study provides a comprehensive understanding of random walks on the Vicsek fractals and general treelike networks.

关键词： Fractals

来源：评论

学校读者我要写书评

暂无评论

Risk analysis of system security based on evidence theory

Risk analysis of system security based on evidence theory

引用

2010 International Conference on computer Design and Applications, ICCDA 2010

作者： Xu, Peida Xu, Jianling Deng, Yong Su, Xiaoyan Key Laboratory of Digital Agricultural Early-warning Technology Ministry of Agriculture of China Beijing China Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University China School of Electronics and Information Technology Shanghai Jiao Tong University Shanghai China Grain Economics Institute Nanjing University of Finance and Economics Nanjing China Hangzhou Key Lab. of E-Business and Information Security Hangzhou Normal University Hanzhou Zhejiang China Hangzhou Key Lab. of E-Business and Information Security Hangzhou Normal University Shanghai China

ISBN: (纸本)9781424471638

Risk evaluation is very important to the design and improvement of physical protection systems. In this paper, an evaluation method of multi-source information fusion is proposed based on the D-S evidence theory. In the proposed method, each individual component of the protection system in the simulated plane is modeled. Then, the threat report of each component according to the specific tactics is determined based on its real environment. Finally, the comprehensive threat distribution is obtained based on through the D-S evidence theory to combine multi-sources information. The proposed method can easily applied to the evaluation of the effectiveness of the protection system. We make the total threat of the protection system lowest through changes of the protection resources allocation. A numerical example is used to illustrate the efficiency of the proposed method. © 2010 IEEE.

关键词： information fusion

来源：评论

学校读者我要写书评

暂无评论

Risk analysis of physical protection system based on evidence theory

引用

Journal of information and Computational science 2010年第13期7卷 2871-2878页

作者： Xu, Peida Su, Xiaoyan Wu, Jiyi Sun, Xiaohong Zhang, Yajuan Deng, Yong College of Computer and Information Sciences Southwest University Chongqing 400715 China Hangzhou Key Lab of E-Business and Information Security Hangzhou Normal University Zhejiang 310036 China College of Food Science and Technology Shanghai Ocean University Shanghai 201306 China Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University Hunan 411105 China Key Subject Laboratory of National defense for Radioactive Waste and Environmental Security Southwest University of Science and Technology Mianyang 621010 China School of Electronics and Information Technology Shanghai Jiao Tong University Shanghai 200240 China

关键词： information fusion

来源：评论

学校读者我要写书评

暂无评论

Complex networks and computing

引用

中国高等学校学术文摘·计算机科学 2009年第3期3卷 322-323页

作者： Shuigeng ZHOU Zhongzhi ZHANG Shanghai Key Lab of Intelligent Information Processing School of Computer Science Fudan University Shanghai 200433 China

Nowadays complex networks are pervasive in various areas of science and technology. Popular examples of complex networks include the Internet, social networks of collaboration, citations and co-authoring, as well as biological networks such as gene and protein interactions and others. Complex networks research spans across mathematics, computer science, engineering, biology and the social sciences. Even in computer science area, increasing problems are either found to be related to complex networks or studied from the perspective of complex networks, such as searching on Web and P2P networks, routing in sensor networks, language processing, software engineering etc. The interaction and mergence of complex networks and computing is inspiring new chances and challenges in computer science.

关键词： complex networks computer science protein interactions collaboration social perspective software research problems language Internet related found area Web P2P new

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：