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6th International Conference on Semantics, Knowledge and Grid, SKG 2010

作者： Sun, Xiaoping Zhuge, Hai Jiang, Xiaorui Key Lab of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences 100190 Beijing China

ISBN: (纸本)9780769541891

With the permeation of information technology into the physical world and human society, we are on the way to a Cyber Physical Society (CPSocio). A CPSocio inter-connects the nature, the cyber space, and the society, so as to provide human beings with a better living and working environment. Researches on CPSocio will lead to a new revolution of information science and technology. In realizing CPSocio, semantics is the most fundamental problem. It is the foundation of all the intelligent activities such as communication, interaction, and cooperation in CPSocio. We are facing various scientific challenges to understand and clarify principles and models of the computing in CPSocio. In this paper we focus on the interactive computing model of Cyber Physical Society, discussing a possible architecture and computing model that enable future intelligent distributed services in CPSocio. The proposed model focuses on the interactive computation emerged from self-interpretation, self-organization and interactions of individual objects. Selfinterpretation enables objects to actively express their own semantic information to others. Interaction among objects will help achieving computing solutions in open, dynamic, limited and heterogeneous environments with partial available information and services. The model aims at providing a feasible framework for systematically tackling key problems and building intelligent services in CPSocio. © 2010 IEEE.

关键词： Semantics

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Dense Sigma set representation for pedestrian detection

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ICIC Express Letters 2011年第3期5卷 835-840页

作者： Hong, Xiaopeng Chang, Hong Shan, Shiguang Chen, Xilin Gao, Wen School of Computer Science and Technology Harbin Institute of Technology No. 92 West Da-Zhi Street Harbin 150001 China Key Lab of Intelligent Information Processing Chinese Academy of Sciences Institute of Computing Technology No. 6 Kexueyuan South Road Zhongguancun Haidian District Beijing 100190 China Institute of Digital Media Peking University No. 5 Yiheyuan Road Haidian District Beijing 100871 China

This paper proposes an effective and efficient pedestrian detection method which is based on 2nd order statistics image representation and linear Support Vector Machine classifiers (SVMs). After arranging a sample image into a dense structure of regions, the key issue is how to represent each image region. Exploiting the traditional covariance matrix region descriptor is a feasible way. However, it requires the usage of computationally demanding non linear classifiers, such as the radial basis function kernel SVMs, because the distance metric between covariance matrices is not in Euclidean space. Instead, we propose Sigma set as the region descriptor to represent each image region. As a result, this representation, which is named dense Sigma set, together with the efficient linear classifier achieves high accuracy. Experimental results on the INRIA pedestrian detection dataset show that dense Sigma set is a powerful and discriminative image representation method for pedestrian detection. © 2011 ISSN 1881-803X.

关键词： Support vector machines

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Cyber physical society

Cyber physical society

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6th International Conference on Semantics, Knowledge and Grid, SKG 2010

作者： Zhuge, Hai Key Lab of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences 100190 Beijing China

ISBN: (纸本)9780769541891

Natural physical space provides material basis for the birth and evolution of human beings and civilization. The progress of human society has created the cyber space. With the rapid development of information technology, the cyber space is connecting physical space, social space and mental space to form a new world - Cyber Physical Society. The way to explore the cyber physical society is different from the way to explore the natural physical space and society. This paper describes the ideal of the Cyber Physical Society, and presents its distinguished characteristics and scientific issues. Research on the Cyber Physical Society could lead to the revolution of society, science and technology. © 2010 IEEE.

关键词： Cyber Physical System

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C*-tree: A multi-dimensional index structure for resource space model

C*-tree: A multi-dimensional index structure for resource sp...

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6th International Conference on Semantics, Knowledge and Grid, SKG 2010

作者： Zeng, Qiang Zhuge, Hai Key Lab of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China

ISBN: (纸本)9780769541891

Resource Space Model (RSM) is a semantic data model for specifying, organizing, and retrieving resources based on classification of resources. An efficient index mechanism is critical for its implementation. However, traditional index mechanisms are not well suitable to resource spaces because the spaces are discrete and hierarchical. This paper proposes a new multidimensional index structure C*-tree. It employs boxes to represent resources so that the containment of boxes can reflect the hierarchical structure of resources. The metric function defined in the C*-tree is able to gather close resources in the index structure. To avoid overlap between bounding boxes, a new restricted bounding box is further introduced. Moreover, the insertion algorithms based on the data partition approach can fully utilize characteristics of RSM. The C*-tree is scalable and efficient on both the number of dimension and the amount of data for different distributions. © 2010 IEEE.

关键词： Semantics

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A resource space model for dataspace

A resource space model for dataspace

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6th International Conference on Semantics, Knowledge and Grid, SKG 2010

作者： Jiang, Xiaorui Sun, Xiaoping Zhuge, Hai Knowledge Grid Research Group Key Lab of Intelligent Information Processing Institute of Computing Technology CAS Beijing China

ISBN: (纸本)9780769541891

Data space is a semi-structural data model for the management of large-scale heterogeneous data objects. In a data space, each data object consists of a set of attribute-value pairs to describe the internal properties of the object and their relationships to other objects. The data space model provides a flexible query language that supports attribute queries and semantic link queries. In this paper we introduce a Resource Space Model that extends the concepts of data space to make it more flexible by incorporating classification semantics. We model a data space as a set of Resource Spaces (RS) with each RS representing a kind of resources that share common attributes and can be put into the same category, either according to a user's knowledge of the world or his query preferences. Our model is suitable for designing a user-tailored semantic view of a data space while at the same time without losing the schema-later data-centric nature. A practical query language is introduced to implement flexible query operations on the resource spaces of the data space. Examples show how the proposed model and language support both the schema query and the data query. © 2010 IEEE.

关键词： Query languages

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An epipolar resticted inter-mode selection for stereoscopic video encoding

An epipolar resticted inter-mode selection for stereoscopic ...

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28th Picture Coding Symposium, PCS 2010

作者： Yang, Guolei Liang, Luhong Gao, Wen Peking University China Key Lab. of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences China

ISBN: (纸本)9781424471348

Fast stereoscopic video encoding becomes a highly desired technique because the stereoscopic video has been realizable for applications like TV broadcasting and consumer electronics. The stereoscopic video has high inter-view dependency subject to epipolar restriction, which can be used to reduce the encoding complexity. In this paper, we propose a fast inter-prediction mode selection algorithm for stereoscopic video encoding. Different from methods using disparity estimation, candidate modes are generated by sliding a window along the macro-block line restricted by the epipolar. Then the motion information is utilized to rectify the candidate modes. A selection failure handling algorithm is also proposed to preserve coding quality. The proposed algorithm is evaluated using independent H.264/AVC encoders for left and right views and can be extended to MVC. Experimental results show that encoding times of one view are reduced by 41.4% and 24.4% for HD and VGA videos respectively with little quality loss. © 2010 IEEE.

关键词： Encoding (symbols)

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

ISBN: (纸本)9780769541099

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. © 2010 IEEE.

关键词： Blood

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Conditional random fields for machine translation system combination

Conditional random fields for machine translation system com...

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International Conference on Asian Language processing

作者： Xia, Tian Zhe, Shandian Liu, Qun Key Lab. of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences P.O. Box 2704 Beijing 100190 China

ISBN: (纸本)9780769542881

Minimum Error Rate Training (MERT) as an effective parameters learning algorithm is widely applied in machine translation and system combination area. However, there exists an ambiguity problem in respect to the training goal and it is hard for MERT to tackle, that is different parameters may lead to the same minimum error rate in training but greatly different performances in testing. We propose a novel training objective as the unique goal for training towards, namely partial references, and by use of conditional random fields (CRF) to cast the decoding procedure in system combination as a sequence labeling problem. Experiments on Chinese-English translation test sets show that our approach significantly outperforms the MERT-based baselines with less training time. © 2010 IEEE.

关键词： Errors

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Using global statistics to rank retrieval systems without relevance judgments

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作者： Shi, Zhiwei Wang, Bin Li, Peng Shi, Zhongzhi Information Retrieval Group Center for Advanced Computing Research Institute of Computing Technology Beijing 100190 China Key Lab. of Intelligent Information Processing Institute of Computing Technology CAS Beijing 100190 China

ISBN: (纸本)3642163262

How to reduce the amount of relevance judgments is an important issue in retrieval evaluation. In this paper, we propose a novel method using global statistics to rank retrieval systems without relevance judgments. In our method, a series of global statistics of a system, which indicate the percentage of its documents found by k out of all the N systems (k = 1, 2, ..., N), are selected, then a linear combination of the series of global statistics is utilized to fit the mean average precision (MAP) of the retrieval system. Optimal coefficients are obtained by linear regression. No human relevance judgments are required in the entire process. Compared with existing evaluation methods without relevance judgments, our method has two advantages. Firstly, it outperforms all early attempts. Secondly, it is adjustable for different effectiveness measurements, e.g. MAP, precision at n, and so forth. © 2010 IFIP.

关键词： information retrieval

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Machine translation with lattices and forests

Machine translation with lattices and forests

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23rd International Conference on Computational Linguistics, Coling 2010

作者： Mi, Haitao Huang, Liang Liu, Qun Key Lab. of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences China Information Sciences Institute Viterbi School of Engineering University of Southern California United States

Traditional 1-best translation pipelines suffer a major drawback: the errors of 1- best outputs, inevitably introduced by each module, will propagate and accumulate along the pipeline. In order to alleviate this problem, we use compact structures, lattice and forest, in each module instead of 1-best results. We integrate both lattice and forest into a single tree-to-string system, and explore the algorithms of lattice parsing, lattice-forest-based rule extraction and decoding. More importantly, our model takes into account all the probabilities of different steps, such as segmentation, parsing, and translation. The main advantage of our model is that we can make global decision to search for the best segmentation, parse-tree and translation in one step. Medium-scale experiments show an improvement of +0.9 BLEU points over a state-of-the-art forest-based baseline.

关键词： Pipelines

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