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International Symposium on Communications and Information Technologies

作者： Ravi Uttamatanin Peerapol Yuvapoositanon Apichart Intarapanich Saowaluck Kaewkamnerd Sissades Tongsima The Electrical Engineering Graduate Program Faculty of Engineering Mahanakorn University of Technology Bangkok Thailand Electronic Engineering Department Mahanakorn University of Technology Bangkok Thailand National Electronics and Computer Technology Center Pathumtani Thailand National Center for Genetic Engineering and Biotechnology Pathumtani Thailand

ISBN: (纸本)9781467355797

Identification of good metaphase spread is an important step in chromosome analysis for genetic disorder detection. In this paper, we propose a rule for chromosome classification to identify good metaphase spreads. The chromosome shapes were classified into four main classes. The first and the second classes refer to individual chromosomes with straight and bended shapes, respectively. The third class is characterized as those chromosomes with overlapping bodies and the forth class is for the non-chromosomal artifacts. Good metaphase spreads should largely contain the first and the second classes while the number of the third class should be kept minimal. Several image parameters were examined and used for creating rule-based classification. The threshold value for each parameter is determined using statistical model. We observed that the empirical probability density function of the parameters can be represented by Gaussian model and, hence, the threshold value can be easily determined. The proposed rules can efficiently and accurately classify the individual chromosome with > 90% accuracy.

关键词： Chromosome Metaphase selection Metaphase spread Rule base classification Gaussian model

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Poster abstracts

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Sleep and Biological Rhythms 2016年第1期5卷 A1-A189页

作者： J. Ferrie M. Shipley F. Cappuccio E. Brunner M. Miller M. Kumari M. Marmot A. Coenen J. L. Castillo F. Araya G. Bustamante L. Montecino C. Torres S. Oporto J. Gronli E. Fiske R. Murison B. Bjorvatn E. Sorensen R. Ursin C. M. Portas S. Rajaraman A. Gribok N. Wesensten T. Balkin J. Reifman N. Dursunoglu S. Ozkurt S. Baser O. Delen S. Sarikaya P. Sadler P. Mitchell D. Françon M. Decobert B. Herve A. Richard G. Griebel P. Avenet B. Scatton G. L. Fur D. Eckert A. Jordan A. Wellman S. Smith A. Malhotra D. White D. Bruck I. Thomas A. Kritikos W. Oertel K. Stiasny-Kolster D. Garcia-Borreguero W. Poewe B. Hoegl R. Kohnen E. Schollmayer J. Keffel C. Trenkwalder A. Valle S. Roizenblatt F. Fregni P. Boggio S. Tufik K. Ward L. Robertson L. Palmer P. Eastwood D. Hillman J. Lee S. Mukherjee V. de Padova G. Barbato G. Ficca I. Zilli P. Salzarulo M. Veldi T. Hion V. Vasar M. Kull L. Nowak J. Davis Y. Latzer O. Tzischinsky S. Crowley M. Carskadon M. Anca-Herschkovitsch D. Frey J. Ortega C. Wiseman C. Farley K. Wright A. Campbell A. Neill K. Spiegel R. Leproult E. Tasali N. Scherberg E. van Cauter A. T. Noradina N. A. Karim I. Norlinah A. A. Raymond R. Sahathevan B. Hamidon E. Werth R. Poryazova R. Khatami C. Bassetti R. G. Beran L. Ainley G. Holand J. Duncan H. Kinney B. Davis B. Hood S. Frey C. Schmidt M. Hofstetter P. Peigneux C. Cajochen W.-P. Hu J.-D. Li C. Zhang L. Boehmer J. Siegel Q.-Y. Zhou Y. Sagawa H. Kondo T. Takemura H. Kanayama Y. Kaneko M. Sato T. Kanbayashi Y. Hishikawa T. Shimizu A. Viola L. James L. Schlangen D.-J. Dijk R. Andretic Y.-C. Kim K.-A. Han F. Jones R. Greenspan L. Sanford L. Yang X. Tang K. Dieter E. Uta H. Sven M. Richard N. Oyane S. Pallesen F. Holsten Y. Inoue M. Fujita N. Emura K. Kuroda N. Uchimura A. Johnston J. Astbury G. Kennedy K. Hoedlmoser M. Schabus T. Pecherstorfer S. Moser G. Gruber P. Anderer W. Klimesch N. Naidoo M. Ferber A. Pack D. Neu O. Mairesse G. Hoffmann A. Dris L. Lambrecht P. Linkowski P. Verbanck O. Le Bon N. Matsuura M. Yamao N. Adachi R. Aritomi Y. Komada H. Tanaka S. Shirak University College London London UK University College London London USA Warwick Medical School London UK Warwick Medical School Coventry USA Radboud University Nijmegen Nijmegen Netherlands Department of Neurology University of Chile Santiago Chile Neurology Service Hospital del Salvador Santiago Chile Family Health Center Juan Pablo II Santiago Chile Department of Biomedicine Section on Physiology Univeristy of Bergen Bergen Norway Department of Public Health and Primary Health Care Univeristy of Bergen Bergen Norway Department of Public Health and Primary Health Care University of Bergen Bergen Norway Norwegian Competence Center for Sleep Disorders Haukeland University Hospital Bergen Norway Department of Child and Adolescent Psychiatry Haukeland University Hospital Univeristy of Bergen Bergen Norway Department of Biomedicine University of Bergen Bergen Norway US Army Medical Research and Materiel Command Fort Detrick Frederick USA Walter Reed Army Institute of Research Silver Spring USA Department of Behavioral Biology Walter Reed Army Institute of Research Silver Spring USA Faculty Department of Pulmonology Pamukkale University Medical Denizli Turkey University of Ballarat Ballarat Australia Sanofi-Aventis Recherche et Developpement Paris France Brigham and Women’s Hospital Harvard Medical School Boston USA The University of Queensland Adelaide Australia School of Psychology University of Queensland Brisbane Australia The University of Queensland Brisbane Australia Victoria University Melbourne Australia Department of Psychology Victoria University Melbourne Australia School of Psychology Victoria University Melbourne Australia Philips-Universität Marburg Germany Philips-Universitaet-Marburg Marburg Germany Instituto de Investigaciones del Sueno Madrid Spain Universitätsklinik für Neurologie Innsbruck Austria Universitaetsklinik fuer Neurologie Innsbruck Austria IMEREM GmbH Nuernberg Germany Schwarz Pharma AG Monheim Germany

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Partial response maximum likelihood sequence detector for a nonlinear magnetic recording channel

Partial response maximum likelihood sequence detector for a ...

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2010 International Conference on System Science and engineering, ICSSE 2010

作者： Kao, Tsai-Sheng Chen, Chiu-Hsiung Chen, Sheng-Chih Hou, Sheng-Yun Chang, Yuan-Chang Chou, Xsing-Bang Department of Electronic Engineering Hwa-Hsia Institute of Technology Taipei Taiwan Department of Computer Science and Information Engineering China University of Technology Hsinchu Taiwan Graduate Program of Digital Contens and Technologies ChengChi University Taipei Taiwan

ISBN: (纸本)9781424464746

The nonlinear effects of partial erasure and transition shift, however, often limit the performance attained by the partial response maximum likelihood (PRML) detector because of model mismatch. Conventionally, the nonlinear effects are either ignored or approximated by linearization technique. In the article, a PRML detector for the PR4 model including the nonlinear effects has been developed to improve the detector performance. The new representation is more accurate and the corresponding PRML detector has better performance without increasing the realization complexity. computer simulation results show that the new representation outperforms the conventional ones due to the enhanced modeling capability. The method is also expected to be applied in the high order partial response channel. © 2010 IEEE.

关键词： Magnetic recording

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Correlation functions for storage data and nonreturn-to-zero-inverted modulated data of a high-density magnetic recording channel with partial erasure effect

Correlation functions for storage data and nonreturn-to-zero...

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2010 International Conference on computer Modeling and Simulation, ICCMS 2010

作者： Kao, Tsai-Sheng Chen, Chiu-Hsiung Chen, Sheng-Chih Chang, Yuan-Chang Wang, Shun-Te Department of Electronic Engineering Hwa-Hsia Institute of Technology Taipei Taiwan Department of Computer Science and Information Engineering China University of Technology Hsinchu Taiwan Graduate Program of Digital Contens and Technologies ChengChi University Taipei Taiwan

ISBN: (纸本)9780769539416

As magnetic recording densities grow, the nonlinear distortions, known as transition shift and partial erasure, arise and limit the performance of the detector. Despite that the transition shift can be compensated by a write current technique, the effect of partial erasure complicates the evaluation of the correlation functions for the storage data and the nonreturn-to-zero- inverted modulated data. In this article, we observe the dependence between the partial erasure effect and storage data, and derive the correlation functions for storage data and nonreturn-to-zero-inverted modulated data in a high density magnetic recording channel. The closed-form of the correlation functions are obtained, these results are applied to verify the timing function of the Muller & Mueller's phase detector in a partial response class IV channel via computer simulations. © 2010 IEEE.

关键词： Signal detection

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The keyword-based and semantic-driven data matching approach for assisting structuralizing the textual clinical documents

The keyword-based and semantic-driven data matching approach...

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International Conference on Biomedical engineering and Informatics

作者： Chen, Chi-Huang Ping, Xiao-Ou Wang, Zi-Jun Hsieh, Sheau-Ling Chen, Li-Chin Tseng, Yi-Ju Hsu, Ching-Wei Lai, Feipei Department of Electrical Engineering National Taiwan University Taipei Taiwan Graduate Institute of Computer Science and Information Engineering National Taiwan University Taipei Taiwan Graduate Institute of Biomedical Electronic and Bioinformatics National Taiwan University Taipei Taiwan EECS International Graduate Program Institute/IT Center National Chiao Tung University Hsinchu Taiwan

ISBN: (纸本)9781424464968

The clinical data stored in the health information system can be categorized as two types including structuralized data and non-structuralized ones. In the paper, a data extraction system is developed to assist data retrieval from the non-structuralized textual clinical documents such as radiology reports, pathology reports, etc. The system provides keyword-based and semantic-driven data matching methodology to extract the specific information from the textual clinical documents. The matching methodology provides the capabilities to recognize the selected keywords and the related semantics in the documents. Through the extraction verification interface, clinicians can extract and verify the matched information semi-automatically. The extracted data can be filled into predefined case-oriented templates. The structuralized data can be stored back into the clinical data warehouse for further analyzing. Moreover, the case-oriented templates can support collecting corresponding extracted data for various researches. ©2010 IEEE.

关键词： Semantics

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Partial response maximum likelihood sequence detector for a nonlinear magnetic recording channel

Partial response maximum likelihood sequence detector for a ...

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International Conference on System Science and engineering (ICSSE)

作者： Tsai-Sheng Kao Chiu-Hsiung Chen Sheng-Chih Chen Sheng-Yun Hou Yuan-Chang Chang Xsing-Bang Chou Department of Electronic Engineering Hwa-Hsia College of Technology and Commerce Taipei Taiwan Department of Computer Science and Information Engineering China University of Technology Hsinchu Taiwan Graduate Program of Digital Content and Technologies Chengchi University Taiwan

关键词：

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The keyword-based and semantic-driven data matching approach for assisting structuralizing the textual clinical documents

The keyword-based and semantic-driven data matching approach...

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International Conference on BioMedical engineering and Informatics (BMEI)

作者： Chi-Huang Chen Xiao-Ou Ping Zi-Jun Wang Sheau-Ling Hsieh Li-Chin Chen Yi-Ju Tseng Ching-Wei Hsu Feipei Lai Department of Electrical Engineering National Taiwan University Taipei Taiwan Graduate Institute of Computer Science and Information Engineering National Taiwan University Taipei Taiwan Graduate Institute of Biomedical Electronic and Bioinformatics National Taiwan University Taipei Taiwan EECS International Graduate Program Institute IT Center National Chiao Tung University Hsinchu Taiwan

关键词： Data mining Semantics Pattern matching Tumors Radiology Pathology Cancer

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Time series mining approach for noninvasive intracranial pressure assessment: An investigation of different regularization techniques

Time series mining approach for noninvasive intracranial pre...

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2009 WRI World Congress on computer Science and Information engineering, CSIE 2009

作者： Wu, Shaozhi Xu, Peng Asgari, Shadnaz Bergsneider, Marvin Hu, Xiao Department of Neurosurgery David Geffen School of Medicine University of California Los Angeles CA United States Biomedical Engineering Graduate Program Henry Samueli School of Engineering and Applied Science University of California Los Angeles CA United States School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu 610054 China

ISBN: (纸本)9780769535074

A data mining framework has been proposed to estimate intracranial pressure (ICP) non-invasively in our previous work. In the corresponding approach, the feature vector extracted from arterial blood pressure (ABP) and flow velocity (FV) is translated to the estimated errors by the mapping function for each entry in the database. In this paper, three different mapping function solutions, linear least squares (LLS), truncated singular value decomposition (TSVD) and standard Tikhonov regularization (STR) are systemically tested to compare the possible effects of different solutions on the non-invasive ICP estimation. The conducted comparison demonstrated that the selection of mapping function solution actually influences the estimation. Among the tested three solutions for mapping function, TSVD and STR show better ICP estimation performance with smaller ICP errors than LLS. © 2008 IEEE.

关键词： Flow velocity

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Time Series Mining Approach for Noninvasive Intracranial Pressure Assessment: An Investigation of Different Regularization Techniques

Time Series Mining Approach for Noninvasive Intracranial Pre...

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computer Science and Information engineering, CSIE, WRI World Congress on FLAGGED

作者： Shaozhi Wu Peng Xu Shadnaz Asgari Marvin Bergsneider Xiao Hu Biomedical Engineering Graduate Program Henry Samueli School of Engineering and Applied Science University of California Los Angeles USA Neural Systems and Dynamics Laboratory Department of Neurosurgery the David Geffen School of Medicine University of California Los Angeles USA School of Computer Science and Engineering University of Electronic Science and Technology Chengdu China

关键词： Cranial pressure Data mining Biomedical engineering Data engineering Spatial databases computer science Feature extraction Arterial blood pressure Biomedical measurements Laboratories

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Comparison of Different Approaches to ICP Dominated Pulse Extraction

Comparison of Different Approaches to ICP Dominated Pulse Ex...

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International Conference on Bioinformatics and Biomedical engineering (ICBBE)

作者： Peng Xu Shaozhi Wu Shadnaz Asgari Magdalena Kasprowicz Marvin Bergsneider Xiao Hu Center of Neuroinformatics School of Life Science and Technology University of Electronic Science and Technology Chengdu China Neural Systems and Dynamics Laboratory Department of Neurosurgery the David Geffen School of Medicine University of California Los Angeles USA School of Computer Science and Engineering University of Electronic Science and Technology Chengdu China Biomedical Engineering Graduate Program Henry Samueli School of Engineering and Applied Science University of California Los Angeles USA University of California Los Angeles Los Angeles CA US

Changes of ICP waveform morphology are characterized with different patients' states like hypertension, hydrocephalus and traumatic brain injury etc. Morphological clustering and analysis of ICP pulse (MOCAIP) approach is recently developed to extract ICP morphology feature, in which hierarchical clustering is used to extract the dominated pulse. In this paper, we evaluate the feasibility of using principle component analysis (PCA) and independent component analysis (ICA) to extract dominated pulse. The comparative study among clustering, PCA and ICP based approaches shows that PCA approach may be an alternative of clustering approach to extract dominated pulse in a faster fashion when dataset is of large size.

关键词： Independent component analysis Morphology Principal component analysis Biomedical engineering Feature extraction Electrocardiography Tellurium Hypertension Data mining Laboratories

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