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The 6th International Conference on Computer Research and Development

作者： Yubao Liu Guihe Qin College of Computer Science and Technology Jilin UniversityChangchunChina College of Computer Science and TechnologyChangchun University College of Computer Science and Technology Jilin UniversityChangchunChina Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of EducationJilin University

In this paper, a hybrid TS-DE algorithm based on Tabu search and differential evolution algorithm is proposed to solve the reliability redundancy optimization problem. A differential evolution algorithm is embedded in Tabu search algorithm. TS is applied for searching solutions space, and DE is used for generating neighborhood solutions. The advantages of both algorithms are considered simultaneously. And an adaptive hybrid TS-DE approach is developed to solve three benchmark reliability redundancy allocation problems. By comparing with other algorithms reported in previous literatures, experimental results show that the proposed method is effective and efficient for solving the reliability redundancy optimization problem.

关键词： nonlinear programming Tabu search differential evolution reliability optimization redundancy allocation

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Modeling and Mining Spatiotemporal Social Contact of Metapopulation from Heterogeneous Data

Modeling and Mining Spatiotemporal Social Contact of Metapop...

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IEEE International Conference on Data Mining (ICDM)

作者： Bo Yang Hongbin Pei Hechang Chen Jiming Liu Shang Xia School of Computer Science and Technology Jilin University Changchun China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education China Department of Computer Science Hong Kong Baptist University Hong Kong National Institute of Parasitic Diseases Chinese CDC Shanghai China

ISBN: (纸本)9781479943012

During an epidemic, the spatial, temporal and demographical patterns of disease transmission are determined by multiple factors. Besides the physiological properties of pathogenes and hosts, the social contacts of host population, which characterize individuals' reciprocal exposures of infection in view of demographical structures and various social activities, are also pivotal to understand and further predict the prevalence of infectious diseases. The means of measuring social contacts will dominate the extent how precisely we can forecast the dynamics of infections in the real world. Most current works focus their efforts on modeling the spatial patterns of static social contacts. In this work, we address the problem on how to characterize and measure dynamical social contacts during an epidemic from a novel perspective. We propose an epidemic-model-based tensor deconvolution framework to address this issue, in which the spatiotemporal patterns of social contacts are represented by the factors of tensors, which can be discovered by a tensor deconvolution procedure with an integration of epidemic models from rich types of data, mainly including heterogeneous outbreak surveillance, social-demographic census and physiological data from medical reports. Taking SIR model as a case study, the efficacy of the proposed method is theoretically analyzed and empirically validated through a set of rigorous experiments on both synthetic and real-world data.

关键词： Educational institutions Diseases Sociology Statistics Tensile stress Surveillance Data models

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Research and implementation of improved real-time crawler modeling

Research and implementation of improved real-time crawler mo...

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International Conference on Electrical Information and Mechatronics, ICEIM 2012

作者： Zuo, Xianglin Wang, Wenbo Wang, Ying Zuo, Wanli College of Computer Science and Technology Jilin University Changchun China Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education China

ISBN: (纸本)9783037856901

The past decade has witnessed the rapid development of search engines, which has become an indispensable part of everyday life. However, people are no longer satisfied with accessing to ordinary information, and they may instead pay more attention to fresh information. This demand poses challenges to traditional search engines, which concern more about relevance and importance of web pages. A search engine compresses three modules: crawler, indexer and searcher. Changes are needed for all these three parts to improve search engine's freshness. This paper investigates the first part of search engine - crawler, we analyze the requirements for real-time crawler, and propose a novel real-time crawler based on more accurate estimation of refresh time. Experimental results demonstrate that the proposed real-time crawler can help search engine improve its freshness. © (2013) Trans Tech Publications, Switzerland.

关键词： Search engines

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Superpixels Based Interactive Image Segmentation Algorithm

Superpixels Based Interactive Image Segmentation Algorithm

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2013 International Conference on Information,Business and Education Technology(ICIBET 2013)

作者： LONG Jian-wu SHEN Xuan-jing ZANG Hui CHEN Hai-peng College of Computer Science and Technology Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University

ISBN: (纸本)9781629932101

A superpixels based interactive image segmentation algorithm is proposed in this paper. Firstly the initial segmentation is obtained by MeanShift algorithm, and then a graph is built using pre-segmented regions as nodes, finally min-cut/maxflow algorithm is implemented for global solution. In this process, each region is represented by a color histogram and Bhattacharyya coefficient is chosen to calculate the similarity between any two regions. Extensive experiments are performed and the results show that the presented algorithm obtains much more satisfactory segmentation results with less user interaction and less comsuming time than MSRM algorithm.

关键词： interactive image segmentation graph cut mean shift

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Adaptive Image Thresholding by Background Subtraction

Adaptive Image Thresholding by Background Subtraction

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2013 International Conference on Information,Business and Education Technology(ICIBET 2013)

ISBN: (纸本)9781629932101

In this paper, an adaptive image thresholding algorithm is proposed for thresholding images with uneven illumination. Firstly, a Gaussian scale space, which is produced from the convolution of a two-dimensional Gaussian function with an input image, is used to estimate the background image. Followed by background subtraction, the objective image can be easily obtained to eliminate interference of uneven illumination. Thirdly, to highlight those darker objects, gamma correction is employed to enhance the objective image. Finally, the thresholding result is extracted easily using the global valley-emphasis Otsu method. The experimental results show that the introduced method yields satisfactory visual quality.

关键词： thresholding background estimation background subtraction

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An adaptive and fast valley emphasis multilevel otsu thresholding algorithm

An adaptive and fast valley emphasis multilevel otsu thresho...

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2013 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2013, at WORLDCOMP 2013

作者： Long, Jianwu Shen, Xuanjing Chen, Haipeng Zhang, He College of Computer Science and Technology Jilin University Changchun Jilin China Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Jilin University Changchun Jilin China

ISBN: (纸本)1601322534

The multilevel thresholding problem is a challenge task due to the fact that the computation is usually very time-consuming for obtaining the optimal multilevel thresholds. Though the state-of-the-art multilevel thresholding algorithms applied various meta-heuristic techniques or acceleration strategies, they still directly searched the optimal thresholds in the whole histogram only for the fixed thresholds number given by the user. Considering that the optimal thresholds usually locate at the valleys of the histogram, we propose an adaptive and fast valley emphasis multilevel Otsu thresholding algorithm (AFVEO). We constrain the searching space in locations of all valleys of the histogram, and it can greatly reduce the iterations required for computing the between-class variance due to the fact that the number of valleys is much fewer than the size of the histogram. And most important we can obtain the optimal multilevel thresholds for different thresholds number without fixed one given by the user. The experimental results indicate that the proposed method is more efficient than traditional Otsu method, recursive Otsu method, valley emphasis Otsu method and neighborhood valley emphasis Otsu method. © 2013 CSREA Press. All rights reserved.

关键词： Image segmentation

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Visual saliency and extended hidden markov model based approach for image splicing detection

Visual saliency and extended hidden markov model based appro...

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2013 International Conference on Mechanical and Electronics engineering, ICMEE 2013

作者： Li, Xiang Shen, Xuan Jing Lv, Ying Da Chen, Hai Peng College of Computer Science and Technology Jilin University Changchun Jilin China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun Jilin China

ISBN: (纸本)9783037858103

In order to improve the detection accuracy of spliced images, a new blind detection based on visual saliency was proposed in this paper. Firstly, create the edge conspicuous map by an improved OSF-based method, and extract fixations by visual attention model. Then locate those fixations on conspicuous edges by conspicuous edge positioning method. Accordingly, key feature fragments can be captured. Secondly, extract Extended Hidden Markov Model features, and reduce their dimension by SVM-RFE. Finally, support vector machine was exploited to classify the authentic and spliced images. The experimental results showed that, when testing on the Columbia image splicing detection dataset, the detection accuracy of the proposed method was 96.68%. © (2013) Trans Tech Publications, Switzerland.

关键词： Hidden Markov models

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Improve the quality of XML clustering by boosting theory

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Journal of computational Information Systems 2013年第11期9卷 4247-4254页

作者： Liu, Zhaojun Li, Xiongfei Li, Wei Key Laboratory of Symbolic Computation and Knowledge Engineering for Ministry of Education Jilin University Changchun 130012 China

XML documents cluster analysis is a hot research topic. Researchers proposed a number of methods to cluster XML document collections. Boosting is successful well-known methods for improving the quality of clustering. This paper proposed a method named ICBQ which improve the clustering quality by boosting theory. The experiment runs on the both real dataset and synthetic dataset, we choose the Nierman's method, Dalamagas's method and Flesca's method to evaluate the ability of ICBQ. The experimental result shows that our approach is more precise than no boosting methods. © 2013 by Binary Information Press.

关键词： XML

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Applying functional dependencies to improve the performance and robustness of hidden naive bayes

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Journal of computational Information Systems 2013年第19期9卷 7967-7974页

作者： Qin, Shidong Wang, Limin Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun 130012 China

Hidden Naive Bayes (HNB) has demonstrated remarkable progress in classification accuracy, accurate class probability estimation and ranking. Since HNB is based on one-dependence estimators to get the approximate value of conditional probability, in this paper we try to get more accurate approximations of Bayesian classifier by applying the data dependence theory of relational database. Originally HNB uses a hidden parent of an attribute to represent the influences of all other attributes, while the influence is directed in the Bayesian network. In this paper, we proposed to use the chain rule to estimate the influence among attributes. Compared to HNB, experimental results show that our algorithm has both advantages in classification accuracy and ranking performance which is measured by the area under the ROC curve (AUC). © 2013 Binary Information Press.

关键词： Bayesian networks

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A New Mobile Visual Search System Based on the Human Visual System

A New Mobile Visual Search System Based on the Human Visual ...

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第四届国际仿生工程学术会议

作者： Bo Zhao Hongwei Zhao Pingping Liu Guihe Qin School of Computer Science and Technology Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education

We describe a novel mobile visual search system based on the saliency mechanism and sparse coding principle of the human visual system (HVS). In the feature extraction step, we first divide an image into different regions using the saliency extraction algorithm. Then scale-invariant feature transform (SIFT) descriptors in all regions are extracted while regional identities are preserved based on their various saliency levels. According to the sparse coding principle in the HVS, we adopt a local neighbor preserving Hash function to establish the binary sparse expression of the SIFT features. In the searching step,

关键词： mobile vision search, human vision system, saliency, sparse coding, Hash, SIFT descriptor.

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