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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...

引用

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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Assignment reduct and its calculation method in inconsistent incomplete decision system

Assignment reduct and its calculation method in inconsistent...

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IEEE International Conference on Granular computing (GRC)

作者： Zuqiang, Meng Zhongzhi, Shi Hua, Qin College of Computer Electronics and Information Guangxi University Nanning 530004 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China

ISBN: (纸本)9780769541617

Attribute reduction is a basic issue in rough set theory. But related researches on reduction in inconsistent incomplete decision system (IIDS) are currently rarely reported. In this paper, the concept of assignment reduct is extended from inconsistent complete decision system (ICDS) to IIDS and then the property of assignment-core attribute is analysed, and finally a method to calculate assignment reduct is put forward by using the heritable trait of assignment reduct. Example analysis shows that the proposed method is effective. This work provides an effective solution for attribute reduction in IIDS. © 2010 IEEE.

关键词： Rough set theory

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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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Accurate Braille-Chinese translation towards efficient Chinese input method for blind people

Accurate Braille-Chinese translation towards efficient Chine...

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5th International Conference on Pervasive computing and Applications, ICPCA10

作者： Wang, Chao Wang, Xiangdong Qian, Yueliang Lin, Shouxun Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Graduate University of Chinese Academy of Sciences Beijing 100080 China

ISBN: (纸本)9781424491421

People with visual disabilities have difficulties in inputting Chinese into computer via conventional methods. Although some specialized devices and software can help Chinese blind users input Mandarin Braille into computers, translation of Mandarin Braille into Chinese is still a problem. In this paper, a new approach for translation of prevailing Mandarin Braille to Chinese character is proposed. By using characteristics of prevailing Mandarin Braille such as word segmentation-concatenation rule and tone information in the N-gram decoding process, the translating approach is able to achieve higher performance than current methods. Furthermore, under a paragraph and article translation scheme, language model adaptation is adopted by using combination of N-gram language model and cache-based language mode to improve translation performance. Experimental results show that the overall precision for the translation is 94.3%. If proper nouns are not considered, the precision can reach 95.1%. ©2010 IEEE.

关键词： Computational linguistics

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Nonparametric curve extraction based on ant colony system

Nonparametric curve extraction based on ant colony system

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作者： Tan, Qing He, Qing Shi, Zhongzhi Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences China Graduate University Chinese Academy of Sciences China

ISBN: (纸本)9781577354642

Curve extraction is an important and basic technique in image processing and computer vision. Due to the complexity of the images and the limitation of segmentation algorithms, there are always a large number of noisy pixels in the segmented binary images. In this paper, we present an approach based on ant colony system (ACS) to detect nonparametric curves from a binary image containing discontinuous curves and noisy points. Compared with the well-known Hough transform (HT) method, the ACS-based curve extraction approach can deal with both regular and irregular curves without knowing their shapes in advance. The proposed approach has many characteristics such as faster convergence, implicit parallelism and strong ability to deal with highly-noised images. Moreover, our approach can extract multiple curves from an image, which is impossible for the previous genetic algorithm based approach. Experimental results show that the proposed ACS-based approach is effective and efficient. Copyright © 2010, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Binary images

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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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Research of neural network algorithm based on FA and RBF

Research of neural network algorithm based on FA and RBF

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2010 2nd International Conference on Computer Engineering and technology, ICCET 2010

作者： Ding, Shifei Jia, Weikuan Su, Chunyang Chen, Jinrong School of Computer Science and Technology China University of Mining and Technology Xuzhou 221008 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Science Beijing 100080 China

ISBN: (纸本)9781424463503

This paper proposes a radial basis function (RBF) neural network algorithm based on factor analysis (FA-RBF) with the architecture feature of RBF network when the data are high-dimensional and complex. By reducing the feature dimension of the original data, FA-RBF algorithm regards the data after dimension reduction as the inputs of the RBF network, and then trains and simulates the network. The algorithm obviously simplifies the network architecture. By analyzing an example, the results show when the algorithm's predicted precision is not reduced, the convergence velocity is improved, the running time is saved and the error of the predicted value is reduced. In order to test and verify the validity of the new algorithm, we compare it with the RBF neural network algorithm based on principal component analysis (PCA-RBF), the predicted results of FA-RBF algorithm are better than the results of RBF and PCA-RBF algorithm. © 2010 IEEE.

关键词： Radial basis function networks

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Sorted label classifier chains for learning images with multi-label

Sorted label classifier chains for learning images with mult...

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18th ACM International Conference on Multimedia ACM Multimedia 2010, MM'10

作者： Liu, Xi Shi, Zhiping Li, Zhixin Wang, Xishun Shi, Zhongzhi Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Graduate University of Chinese Academy of Sciences Beijing 100049 China

ISBN: (纸本)9781605589336

In the real world, images always have several visual objects instead of only one, which makes it difficult for conventional object recognition methods to deal with them. In this paper, we present a topologically sorted classifier chain method for learning images with multi-label. We first provide a means of generating a topo-logically sorted label chain ordering by employing a topological sort algorithm and then apply the chain ordering to the classifier chain model proposed by [1] to classify multi-label images. Our method can capture the correlations between labels very effectively due to the sorted label chain ordering and the advantages brought by classifier chain method. We evaluate the proposed method on Corel dataset and demonstrate the micro and macro F1 measures superior to the state-of-the-art methods. © 2010 ACM.

关键词： Object recognition

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2010 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2010

作者： Han, Xu Shi, Zhongzhi Niu, Wenjia Chen, Kunrong Yang, Xinghua Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences 100190 Beijing China Graduate University of Chinese Academy of Sciences 100049 Beijing China

ISBN: (纸本)9780769541914

With the rapid development of XML language which has good flexibility and interoperability, more and more log files of software running information are represented in XML format, especially for Web services. Fault diagnosis by analyzing semi-structured and XML like log files is becoming an important issue in this area. For most related learning methods, there is a basic assumption that training data should be in identical structure, which does not hold in many situations in practice. In order to learn from training data in different structures, we propose a similarity-based Bayesian learning approach for fault diagnosis in this paper. Our method is to first estimate similarity degrees of structural elements from different log files. Then the basic structure of combined Bayesian network (CBN) is constructed, and the similarity-based learning algorithm is used to compute probabilities in CBN. Finally, test log data can be classified into possible fault categories based on the generated CBN. Experimental results show our approach outperforms other learning approaches on those training datasets which have different structures. © 2010 IEEE.

关键词： Bayesian networks

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Web service composition on the environment level

Web service composition on the environment level

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

作者： Cai, Guangjun Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Graduate University Chinese Academy of Sciences Beijing 100049 China

ISBN: (纸本)9780769541891

Service-oriented computing (SOC) promises a world of cooperating services loosely connected, creating dynamic business processes and agile applications. Service composition plays a very important role in it. One important problem related to service composition is about what the content of service description is. Most approaches focus on the description about web services themselves, and fail to consider the behaviour of the services in composition. This paper introduces a composition approach on the environment level. The basic idea of it is to develop a model-based approach by using the stability character of environment to encapsulate the changing of the service and the request. Our approach both facilitate to improve the composition efficiency and is more appropriate for compositing complex services or behaviour services based on its' behaviour. A running travel example is used to illustrate our approach. © 2010 IEEE.

关键词： Web services

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