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IEEE International Conference on Cognitive Informatics

作者： Fang, Fang Miao, Jun Qing, Laiyun Gao, Wen School of Computer Science and Technology Harbin Institute of Technology Harbin 150001 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China School of Information Science and Engineering Graduate University of the Chinese Academy of Sciences Beijing 100049 China Institute for Digital Media Peking University Beijing 100871 China

ISBN: (纸本)9781424480401

Gaze movement plays an important role in human visual search system. How to simulate such a system to efficiently encode and decode gaze movement for target searching is a meaningful issue. There are two key points that should be addressed for this issue. First, eye movement is affected by the visual context that includes more than one object in images. It is important to study how to encode the spatial relationship between the target and the other objects, and decode the spatial relationship to drive the gaze moving to the target. Second, the human retina has a non-uniform distribution of light sensing neurons, which can be viewed as a composition of neuron arrays in different spatial resolutions. When a system searches a target, how many scales of visual fields should be involved to sense the image stimulus? In this paper, we propose a visual search system using the population cell coding mechanism and the multi-scale visual field as sensing input. As an example, the system is applied to human eye center searching. An experimental comparison of a Full-scale visual field coding system and a Gradual-scale coding system is carried out. The experiment results show the Gradual-scale coding system performs better than Full-scale coding system for target searching. © 2010 IEEE.

关键词： Eye movements

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Risk analysis of system security based on evidence theory

Risk analysis of system security based on evidence theory

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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

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Hybrid Particle Swarm Optimized Wavelet Network for Video OCR

Hybrid Particle Swarm Optimized Wavelet Network for Video OC...

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International Symposiums on information processing (ISIP)

作者： Tongcheng Huang Liping Yin Institute of Laser and Information Technology Shaoyang University Shaoyang China Key Laboratory of Intelligent Information Processing Chinese Academy and Sciences Beijing China

A hybrid particle swarm optimization (PSO)-based wavelet neural network (WNN) for Video OCR is presented in this paper. Video OCR is an important task towards enabling automatic content-based retrieval of digital video databases. However, since text is often displayed against a complex background, its detection and extraction is a challenging problem. In this paper, wavelet transformation is done on the different current and the wavelet coefficients are obtained. The wavelet coefficients are given as inputs to the wavelet neural network trained by particle swarm optimization (PSO-WNN). The final network output of real text regions is different from those non-text regions. The experimental results demonstrate the effectiveness of the proposed method.

关键词： Artificial neural networks Optical character recognition software Particle swarm optimization Training Discrete wavelet transforms Algorithm design and analysis

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Schedulability analysis for real-time messages over switched Ethernet with EDF scheduling

Schedulability analysis for real-time messages over switched...

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International Conference on information Science and Engineering (ICISE)

作者： Ming Tan Zhen Wei Key Laboratory of Network and Intelligent Information Processing Hefei University Hefei China School of Computer and Information Hefei University of Technology Hefei China

To overcome the drawback that switched Ethernet can not meet the real-time requirements in industrial communications, an improved message transmission model in which switch and the end-nodes control the real-time traffic with Earliest Deadline First (EDF) scheduling was proposed. In addition, a distributed admission control method for periodic messages which is performed by the source and the destination nodes without the modification of the operational features of Ethernet switch was presented. Moreover, a more general schedulability condition for real-time periodic message over switched Ethernet was given and proved by using real-time scheduling theory.

关键词： Switches Real time systems Ethernet networks Scheduling algorithm Job shop scheduling Admission control Synchronization

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Research and progress of cluster algorithms based on granular computing

International Journal of Digital Content Technology and its ...

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International Journal of Digital Content technology and its Applications 2010年第5期4卷 96-104页

作者： Shifei, Ding Li, Xu Hong, Zhu Liwen, Zhang School of Computer Science and Technology China University of Mining and Technology Xuzhou China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Science Beijing China

Granular Computing (GrC), a knowledge-oriented computing which covers the theory of fuzzy information granularity, rough set theory, the theory of quotient space and interval computing etc, is a way of dealing with incomplete, unreliable, uncertain fuzzy knowledge. In recent years, it is becoming one of the main study streams in Artificial Intelligence (AI). With selecting the size structure flexibly, eliminating the incompatibility between clustering results and priori knowledge, completing the clustering task effectively, cluster analysis based on GrC attracts great interest from domestic and foreign scholars. In this paper, starting from the development of GrC, firstly, the main newly achievements about clustering and GrC are researched and summarized. Secondly, principle of granularity in clustering, the effective clustering algorithms with the idea of granularity as well as their merits and faults are analyzed and evaluated from the point view of rough set, fuzzy sets and quotient space theories. Finally, the feasibility and effectiveness of handling high-dimensional complex massive data with combination of these theories is outlooked.

关键词： Clustering algorithms

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Entity answer extraction and homepage recognition

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Journal of information and Computational Science 2010年第1期7卷 277-283页

作者： Xian, Yantuan Yu, Zhengtao Xu, Yangbo Li, Lina Zou, Junjie Guo, Jianyi School of Information Engineering and Automation Kunming University of Science and Technology Kunming 650051 China Institute of Intelligent Information Processing Computer Technology Application Key Laboratory of Yunnan Province Kunming 650051 China

This paper proposed a method for entity answer extraction, which examined three levels of relevance, including document, passage and entity. The entity answer extraction system and homepage recognition are also described in detail. The results on TRECT 2009 test topics show the effectiveness of our approaches. Accuracy of entity answer extraction reaches 88.93% and accuracy of entity homepage recognition is 91.15%. Copyright © 2010 Binary information Press.

关键词： Extraction

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Frequent term based peer-to-peer text clustering

Frequent term based peer-to-peer text clustering

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International Symposium on Knowledge Acquisition and Modeling, KAM

作者： Qing He Tingting Li Fuzhen Zhuang Zhongzhi Shi Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences China Chinese Academy of Sciences China

Text clustering is an important technology for automatically structuring large document collections. It is much more valuable in peer-to-peer networks. The high dimensionality of documents means much more communication could be saved if each node could get the approximate clustering result by distributed algorithm instead of transferring them into a center and do the clustering. Most of the existing text clustering algorithms in unstructured peer-to-peer networks are based on K-means algorithm. A problem of those algorithms is that the clustering quality may decreased with the increase of the network size. In this paper, we propose a text clustering algorithm based on frequent term sets for peer-to-peer networks. It requires relatively lower communication volume while achieving a clustering result whose quality will not be affected by the size of the network. Moreover, it gives a term set describing each cluster, which makes it possible for people to have a clear comprehension for the clustering result, and facilitates the users to find resource in the network or manage the local documents in accordance with the whole network.

关键词： Copper

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Collaborative dual-PLSA: Mining distinction and commonality across multiple domains for text classification

Collaborative dual-PLSA: Mining distinction and commonality ...

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作者： Zhuang, Fuzhen Luo, Ping Shen, Zhiyong He, Qing Xiong, Yuhong Shi, Zhongzhi Xiong, Hui Key Laboratory of Intelligent Information Processing Institute of Computing Technology CAS China Graduate University of Chinese Academy of Sciences China Hewlett Packard Labs China China Innovation Work Australia MSIS Department Rutgers University United States

The distribution difference among multiple data domains has been considered for the cross-domain text classification problem. In this study, we show two new observations along this line. First, the data distribution difference may come from the fact that different domains use different key words to express the same concept. Second, the association be-tween this conceptual feature and the document class may be stable across domains. These two issues are actually the distinction and commonality across data domains. Inspired by the above observations, we propose a gen- erative statistical model, named Collaborative Dual-PLSA (CD-PLSA), to simultaneously capture both the domain dis-tinction and commonality among multiple domains. Dif-ferent from Probabilistic Latent Semantic Analysis (PLSA) with only one latent variable, the proposed model has two latent factors y and z, corresponding to word concept and document class respectively. The shared commonality in-tertwines with the distinctions over multiple domains, and is also used as the bridge for knowledge transformation. We exploit an Expectation Maximization (EM) algorithm to learn this model, and also propose its distributed ver-sion to handle the situation where the data domains are geographically separated from each other. Finally, we con-duct extensive experiments over hundreds of classification tasks with multiple source domains and multiple target do-mains to validate the superiority of the proposed CD-PLSA model over existing state-of-the-art methods of supervised and transfer learning. In particular, we show that CD-PLSA is more tolerant of distribution differences. ©Copyright The Ninth IEEE International Conference on Data Mining, 2009.

关键词： Semantics

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A fixed-point decoding approach for statistical machine translation on mobile terminals

A fixed-point decoding approach for statistical machine tran...

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International Symposium on Universal Communication, ISUC

作者： Xiang Li Jin'an Xu Wenbin Jiang Qun Liu Yajuan Lü School of Computer and Information Technology Beijing Jiaotong University Beijing China Key Laboratory of Intelligent Information Processing Chinese Academy and Sciences Beijing China

The demand for statistical machine translation on mobile terminals is increasing rapidly, but translation speed is restricted by the embedded processors without a floating-point unit. This paper proposes an approach to convert floating-point numbers into fixed-point numbers for SMT decoding on mobile terminals in order to reduce the impact of the processors without a floating-point unit on translation speed. The experiments based on PC and mobile terminal show that this approach ensures the quality of translation and the speed of fixed-point arithmetic operations is 135.6% faster than that of floating-point arithmetic operations. Therefore, this approach can efficiently improve translation speed of SMT systems on mobile terminals with weak ability in floating-point arithmetic operations.

关键词： Decoding Mobile communication Speech Floating-point arithmetic Program processors Computers Speech recognition

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Distinguishing Patients with Gastritis and Cholecystitis from the Healthy by Analyzing Wrist Radial Arterial Doppler Blood Flow Signals

Distinguishing Patients with Gastritis and Cholecystitis fro...

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International Conference on Pattern Recognition

作者： Xiaorui Jiang Dongyu Zhang Kuanquan Wang Wangmeng Zuo Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences China Department of Computer Science and Technology Harbin Institute of Technology China

ISBN: (纸本)9781424475421

This paper tries to fill the gap between Traditional Chinese Pulse Diagnosis (TCPD) and Doppler diagnosis by applying digital signal analysis and pattern classification techniques to wrist radial arterial Doppler blood flow signals. Doppler blood flows signals (DBFS) of patients with cholecystitis, gastritis and healthy people are classified by L2-soft margin SVM and 5 linear classifiers using the proposed feature - piecewise axially integrated bispectra (PAIB). A 5-fold cross validation is used for performance evaluation. The classification accuracies between either two groups of subjects are greater than 93%. Gastritis can be recognized with higher accuracy than cholecystitis. Cholecystitis can be recognized with higher accuracy on left hand data than right. The findings in this paper partly conform to the theory of TCPD. Though the sample size is relatively small, we could still argue that the methods proposed here are effective and could serve as an assistive tool for TCPD.

关键词： Support vector machines Doppler effect Feature extraction Diseases Wrist Pathology Accuracy

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