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Doppler blood flow signal analysis meets traditional Chinese pulse diagnosis

Doppler blood flow signal analysis meets traditional Chinese...

引用

International Conference on BioMedical Engineering and Informatics (BMEI)

作者： Xiaorui Jiang Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China

In traditional Chinese pulse diagnosis (TCPD), diseases of internal organs can be detected by recognizing pulse waveform patterns of wrist radial arterial. However pulse waveform analysis, for which Doppler diagnosis is a powerful tool, is limited to cardiovascular diseases. This paper tries to fill the gap between TCPD and Doppler diagnosis by applying signal analysis and pattern recognition technologies to Doppler blood flow signals (DBFS's) of wrist radial arterial, which are recorded from both hands of healthy people, gastritis and cholecystitis patients. DBFS's are classified using the features proposed by an L2-soft margin support vector machine (L2-SVM): five clinical Doppler parameters (DP), wavelet energies (WE), wavelet packet energies (WPE), and piecewise axially integrated bispectra (PAIB). 5-fold cross validation is used for performance evaluation. The sick are differentiated from the healthy with an accuracy of about 80% using DP, WE and WPE, while the classification rate between gastritis and cholecystitis reaches 100%. Using PAIB, ether two groups of subjects are classified with accuracy greater than 93%. Gastritis is more accurately recognized than cholecystitis, while the latter is recognized with a higher accuracy on data from the left hand than right. Though the sample size is relatively small, we still argue that the methods proposed here are effective and could serve as an assisstive tool for TCPD.

关键词： Doppler effect Wavelet packets Feature extraction Diseases Wrist Pathology Accuracy

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A visual search system based on multi-scale population cell coding

A visual search system based on multi-scale population cell ...

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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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Collaborative dual-PLSA: Mining distinction and commonality across multiple domains for text classification 10

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

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Proceedings of the 19th ACM international conference on information and knowledge management

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 Works China MSIS Department Rutgers University United States

ISBN: (纸本)9781450300995

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 between 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 generative statistical model, named Collaborative Dual-PLSA (CD-PLSA), to simultaneously capture both the domain distinction and commonality among multiple domains. Different 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 intertwines 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 version to handle the situation where the data domains are geographically separated from each other. Finally, we conduct extensive experiments over hundreds of classification tasks with multiple source domains and multiple target domains 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. © 2010 ACM.

关键词： Classification (of information)

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2010 IEEE 5th International Conference on Bio-Inspired computing: Theories and Applications, BIC-TA 2010

作者： Zhang, Zhujin Wang, Shuo Zhang, Xingyi Zhang, Zheng Department of Control Science and Engineering Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China School of Computer and Information Science University of South Australia Adelaide SA 5095 Australia Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei 230039 China

ISBN: (纸本)9781424464388

Randí et al. proposed a significant graphical representation for DNA sequences, which is very compact and avoids loss of information. In this paper, we build a fast algorithm for this graphical representation with time complexity O(n2), and find another important advantage in the representation: no degeneracy. Moreover, we propose a new method to do similarity analysis of DNA sequences based on the representation. The approach adopts four elements of covariance matrix as a descriptor, and is illustrated on the first exon of beta-globin genes from 11 different species. © 2010 IEEE.

关键词： DNA sequences

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AUTOMATIC IMAGE ANNOTATION WITH CONTINUOUS PLSA

AUTOMATIC IMAGE ANNOTATION WITH CONTINUOUS PLSA

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IEEE International Conference on Acoustics, Speech, and Signal processing

作者： Zhixin Li Zhiping Shi Xi Liu Zhongzhi Shi The Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China

ISBN: (纸本)9781424442959

Automatic image annotation has become an important and challenging problem due to the existence of semantic gap. In this paper, we firstly extend probabilistic latent semantic analysis (PLSA) to model continuous quantity. In addition, corresponding Expectation-Maximization (EM) algorithm is derived to determine the model parameters. Furthermore, in order to deal with the data of different modalities in terms of their characteristics, we present a semantic annotation model which employs continuous PLSA and standard PLSA to model visual features and textual words respectively. The model learns the correlation between these two modalities by an asymmetric learning approach and then it can predict semantic annotation for unseen images. We compare our approach with several state-of-the-art approaches on a standard Corel dataset. The experiment results show that our approach performs more effectively and accurately.

关键词： automatic image annotation continuous PLSA latent aspect model image retrieval image retrieval auto-marking images ANNOTATIONS AUTOMATIC Semantics model parameters

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A NOVEL SPARSE CODING MODEL BASED ON STRUCTURAL SIMILARITY

A NOVEL SPARSE CODING MODEL BASED ON STRUCTURAL SIMILARITY

引用

IEEE International Conference on Acoustics, Speech, and Signal processing

作者： Zhiqing Li Zhiping Shi Xi Liu Zhongzhi Shi Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China

ISBN: (纸本)9781424442959

Understanding and modeling the function of the neurons and neural systems are primary goal of systems neuroscience. Sparse coding theory demonstrates that the neurons in primary visual cortex form a sparse representation of natural scenes in the viewpoint of statistics. In this paper, we propose a novel sparse coding model based on structural similarity (SS_SC) for natural image feature extraction. The advantage for our model is to be able to preserve structural information from a scene, which human visual perception is highly adapted for. Using the proposed sparse coding model, the validity of image feature extraction is testified. Furthermore, compared with standard sparse coding (SC) model, the experimental results show that the quality of reconstructed images obtained by our method outperforms the SC method.

关键词： Natural image sparse coding structural similarity computational model biological visual system Sparse coding Computational modeling Visual System image feature natural scenes Feature extraction Neurons sparse representation Visual Perception Striate Cortex

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Preservative translations between logical systems

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作者： Shen, Yuming Ma, Yue Cao, Cungen Sui, Yuefei Wang, Ju Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences 100190 China Graduate University of Chinese Academy of Sciences 100049 China School of Computer Science and Information Engineering Guangxi Normal University 541004 China

ISBN: (纸本)3642163262

This paper investigates a subclass of translations between logical systems, called the preservative translations, which preserve the satisfiability and the unsatisfiability of formulas. The definition of preservative translation is given and connections between the preservative translation and other definitions of translations in the literature are discussed. Some properties of logical systems, such as the compactness and the decidability, which are characterized by the existence of preservative translations between logical systems are also studied. © 2010 IFIP.

关键词： Artificial intelligence

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Non-rigid object reconstruction based on multi-view images: A survey

Non-rigid object reconstruction based on multi-view images: ...

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2010 3rd International Congress on Image and Signal processing, CISP 2010

作者： Liu, Zhi Wang, Hongjun Li, Qingli Jun, Shi School of Information Science and Engineering Shandong University Jinan China Key Laboratory of Intelligent Computing and Information Processing Ministry of Education China School of Information Science East China Normal University Shanghai China Shandong Institute of Light Industry Jinan China

ISBN: (纸本)9781424465149

In this paper we review the major approaches to non-rigid object reconstruction based on multi-view images. It tries to reflect the profile of this area by focusing more on those subjects that have been given more importance in the literature. In this context most of the paper is devoted to present all kinds of approaches for non-rigid object reconstruction based on multi-view images. A number of references are provided that describe applications of non-rigid object reconstruction based on multi-view images The paper ends by addressing some important issues and open questions that can be subject of future research. ©2010 IEEE.

关键词： Image reconstruction

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An intelligent call center platform for mobile communication enterprises

An intelligent call center platform for mobile communication...

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2010 International Conference on Communications and Mobile computing, CMC 2010

作者： Wang, Weimin Liu, Liangliang Wang, Dongsheng Cao, Yanan Wu, Yuming Qi, Baoyuan Qiao, Dongchun Guo, Jingyang Zheng, Yufei Cao, Cungen Li, Jianghua Shi, Yuan Li, Ruilin Sang, Changqin Shen, Nan Key Lab of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Customer Service Center Guangdong Communication Group China Mobile Guangzhou 510100 China

ISBN: (纸本)9780769539898

In this paper, we introduced an intelligent call center platform (ICCP) for communication enterprises. The platform is based on two broad suites of technologies: Knowledge management and natural language processing. First, we designed an enterprise knowledge modeling technology, and provided a knowledge management system for managing customer service knowledge. Then mobile customers are allowed to send Chinese queries, through either Internet tools (e.g. MSN, QQ, BBS and Fetion) or Wireless SM devices (e.g. mobile phones), to a multi-tier natural language understanding engine, and the engine retrieves the knowledge bases to find correct answers after understanding the queries. The ICCP has been successfully used in a domestic communication group since March 2009, and achieved a satisfactory performance. © 2010 IEEE.

关键词： Knowledge management

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Efficient SLCA computing service for XML filtering in IaaS

Efficient SLCA computing service for XML filtering in IaaS

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12th International Asia Pacific Web Conference, APWeb 2010

作者： Zhang, Chenjing Wang, Xiaoling Zhou, Aoying Shanghai Key Laboratory of Intelligent Information Fudan University China College of Information Technology Shanghai Ocean University China Shanghai Key Laboratory of Trustworthy Computing Software Engineering Institute East China Normal University China

ISBN: (纸本)9780769540122

Cloud provides dynamically computing services for large scales of data over the Internet. IaaS(information as a service) is one of utilities to provide information service in Cloud computing. Large scales of XML data are produced continually in Internet. Efficient information filtering services are needed. Previous XML filter approaches aim at XPath queries. However, many users tend to use keywords to describe requirements. SLCA (Smallest Lowest Common Ancestor)-based XML keyword search is one of the most important information retrieval approaches. Former approaches focus on building centralized index for a large scale of XML document collection and can't process continuous XML streams. This paper addresses SLCA computing service for continuous XML document. A novel SLCA computing service is designed, where SLCAs are obtained in one scan of XML stream. We demonstrate the efficiency of our algorithms analytically and experimentally. © 2010 IEEE.

关键词： XML

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