检索结果-内蒙古大学图书馆

mathematics and Visualization 2014年 37卷 221-245页

作者： Pfister, Hanspeter Kaynig, Verena Botha, Charl P. Bruckner, Stefan Dercksen, Vincent J. Hege, Hans-Christian Roerdink, Jos B.T.M. School of Engineering and Applied Sciences Harvard University 33 Oxford St CambridgeMA02138 United States Vxlabs Somerset West South Africa Institute of Computer Graphics and Algorithms Vienna University of Technology Favoritenstraße 9-11/E186 Wien1040 Austria Department of Visualization and Data Analysis Zuse Institute Berlin Takustraße 7 Berlin14195 Germany Johann Bernoulli Institute for Mathematics and Computer Science University of Groningen P.O. Box 407 AK Groningen9700 Netherlands

Connectomics is a branch of neuroscience that attempts to create a connectome, i.e., a completemap of the neuronal system and all connections between neuronal structures. This representation can be used to understand how functional brain states emerge from their underlying anatomical structures and how dysfunction and neuronal diseases arise. We review the current state-of-the-art of visualization and image processing techniques in the field of connectomics and describe a number of challenges. After a brief summary of the biological background and an overview of relevant imaging modalities, we review current techniques to extract connectivity information from image data at macro-, meso- and *** also discuss data integration and neural network modeling, as well as the visualization, analysis and comparison of brain networks. © 2014, Springer-Verlag London.

关键词： Visualization

来源：评论

学校读者我要写书评

暂无评论

Detect the Rail Track Flaw by Estimating the Camera Shaking

Detect the Rail Track Flaw by Estimating the Camera Shaking

引用

IEEE International Conference on Intelligent Transportation Systems

作者： Liang Wang Xiaoyue Luo Berthold K. P. Horn Shengchun Wang Siwei Luo Beijing Key Lab of Traffic Data Analysis and Mining Beijing Jiaotong University Beijing China Department of Mathematics Linfield College OR USA Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Boston MA USA

In this paper, we present a method of detecting the rail track bends and flaws. Different from the traditional machine-vision based methods which analyze the images of the rail surface, we estimate the shake of the camera - which is caused by the flaw or bend of the rail track - from the video used for railway environment surveillance. We provide both theoretical analysis - based on the theory of optical flow and passive navigation - and the corresponding fast algorithms, i.e. the brightness-pattern-matching code (BPMC) and shaking-type code (STC). Our method uses the surveillance video of the railway environment directly, thus, we do not need extra expensive instruments.

关键词： Rails Cameras Brightness Optical imaging Algorithm design and analysis Turning Navigation

来源：评论

学校读者我要写书评

暂无评论

Detect the Rail Track Flaw by Estimating the Camera Shaking

Detect the Rail Track Flaw by Estimating the Camera Shaking

引用

17th International IEEE Conference on Intelligent Transportation Systems & The Asia-Pacific Council on Systems Engineering Conference 2014

作者： Liang Wang Xiaoyue Luo Berthold K.P.Horn Shengchun Wang Siwei Luo Beijing Key Lab of Traffic Data Analysis and Mining Beijing Jiaotong University Department of Mathematics Linfield CollegeOR 97128USA CSAIL Department of Electrical Engineering and Computer ScienceMassachusetts Institute of TechnologyBostonMA02139 USA

In this paper,we present a method of detecting the rail track bends and *** from the traditional machine-vision based methods which analyze the images of the rail surface,we estimate the shake of the camera — which is caused by the flaw or bend of the rail track — from the video used for railway environment *** provide both theoretical analysis — based on the theory of optical flow and passive navigation — and the corresponding fast algorithms,*** brightness-pattern-matching code(BPMC) and shaking-type code(STC).Our method uses the surveillance video of the railway environment directly,thus,we do not need extra expensive instruments.

关键词： image Detect the Rail Track Flaw by Estimating the Camera Shaking Track

来源：评论

学校读者我要写书评

暂无评论

Highlights from the 11th ISCB Student Council Symposium 2015. Dublin, Ireland. 10 July 2015

引用

BMC bioinformatics 2016年第3期17 Suppl 3卷 95页

作者： Katie Wilkins Mehedi Hassan Margherita Francescatto Jakob Jespersen R. Gonzalo Parra Bart Cuypers Dan DeBlasio Alexander Junge Anupama Jigisha Farzana Rahman Griet Laenen Sander Willems Lieven Thorrez Yves Moreau Nagarajan Raju Sonia Pankaj Chothani C. Ramakrishnan Masakazu Sekijima M. Michael Gromiha Paddy J Slator Nigel J Burroughs Przemysław Szałaj Zhonghui Tang Paul Michalski Oskar Luo Xingwang Li Yijun Ruan Dariusz Plewczynski Giulia Fiscon Emanuel Weitschek Massimo Ciccozzi Paola Bertolazzi Giovanni Felici Pieter Meysman Manu Vanaerschot Maya Berg Hideo Imamura Jean-Claude Dujardin Kris Laukens Westa Domanova James R. Krycer Rima Chaudhuri Pengyi Yang Fatemeh Vafaee Daniel J. Fazakerley Sean J. Humphrey David E. James Zdenka Kuncic Plant Pathology and Plant-Microbe Biology Section School of Integrative Plant Science Cornell University Ithaca USA Graduate Field of Computational Biology Cornell University Ithaca USA School of Computing & Mathematics University of South Wales Cardiff UK Department of Genome Biology for Neurodegenerative Diseases German Center for Neurodegenerative Diseases (DZNE) within the Helmholtz Association ᅟ Germany Department of Surgery Massachusetts General Hospital The Broad Institute of MIT and Harvard Boston USA Department of Systems Biology Technical University of Denmark Kemitorvet Denmark Protein Physiology Lab Facultad de Ciencias Exactas y Naturales Universidad de Buenos Aires Buenos Aires Argentina Molecular Parasitology Unit (MPU) Institute of Tropical Medicine Antwerp Belgium Advanced Database Research and Modeling (ADReM) research group University of Antwerp Antwerpen Belgium Department of Computer Science University of Arizona Tucson USA Department of Veterinary Clinical and Animal Sciences Center for non-coding RNA in Technology and Health University of Copenhagen Copenhagen Denmark University College Dublin Dublin Ireland Department of Electrical Engineering (ESAT) STADIUS Center for Dynamical Systems Signal Processing and Data Analytics KU Leuven Leuven Belgium Minds Medical IT Department Leuven Belgium Scientific Institute of Public Health (WIV-ISP) Platform of Biotechnology and Molecular Biology (PBB) Brussels Belgium Department of Development and Regeneration @ Kulak KU Leuven Kortrijk Belgium Department of Biotechnology Bhupat and Jyoti Metha School of Biosciences Indian Institute of Technology Madras Chennai India Philips Research North America Briarcliff Manor USA Global Scientific Information and Computing Center (GSIC) Tokyo Institute of Technology Tokyo Japan Systems Biology Centre University of Warwick Senate House Coventry UK Systems Biology Doctoral Training Centre University of Warwick Senate House Coventry UK Center for B

A1 Highlights from the eleventh ISCB Student Council Symposium 2015 Katie Wilkins, Mehedi Hassan, Margherita Francescatto, Jakob Jespersen, R. Gonzalo Parra, Bart Cuypers, Dan DeBlasio, Alexander Junge, Anupama Jigisha, Farzana Rahman O1 Prioritizing a drug’s targets using both gene expression and structural similarity Griet Laenen, Sander Willems, Lieven Thorrez, Yves Moreau O2 Organism specific protein-RNA recognition: A computational analysis of protein-RNA complex structures from different organisms Nagarajan Raju, Sonia Pankaj Chothani, C. Ramakrishnan, Masakazu Sekijima; M. Michael Gromiha O3 Detection of Heterogeneity in Single Particle Tracking Trajectories Paddy J Slator, Nigel J Burroughs O4 3D-NOME: 3D NucleOme Multiscale Engine for data-driven modeling of three-dimensional genome architecture Przemysław Szałaj, Zhonghui Tang, Paul Michalski, Oskar Luo, Xingwang Li, Yijun Ruan, Dariusz Plewczynski O5 A novel feature selection method to extract multiple adjacent solutions for viral genomic sequences classification Giulia Fiscon, Emanuel Weitschek, Massimo Ciccozzi, Paola Bertolazzi, Giovanni Felici O6 A Systems Biology Compendium for Leishmania donovani Bart Cuypers, Pieter Meysman, Manu Vanaerschot, Maya Berg, Hideo Imamura, Jean-Claude Dujardin, Kris Laukens O7 Unravelling signal coordination from large scale phosphorylation kinetic data Westa Domanova, James R. Krycer, Rima Chaudhuri, Pengyi Yang, Fatemeh Vafaee, Daniel J. Fazakerley, Sean J. Humphrey, David E. James, Zdenka Kuncic

关键词： Visceral Leishmaniasis Feature Selection Method Frequent Itemset Mining Leishmania Donovani Student Council

来源：评论

学校读者我要写书评

暂无评论

11th German Conference on Chemoinformatics (GCC 2015) Abstracts

引用

JOURNAL OF CHEMINFORMATICS 2016年第SUPPL 1期8卷 1-27页

作者： [Anonymous] GDCh-CIC Division Associated Board Member Beilstein-Institut zur Förderung der Chemischen Wissenschaften Trakehner Str. 7-9 60487 Frankfurt Germany. ufechner@beilstein-institut.de. Division Medicinal Chemistry Amsterdam Institute for Molecules Medicines and Systems (AIMMS) VU University Amsterdam The Netherlands. Centre for Bioinformatics Uni Hamburg Bundesstr. 43 20146 Hamburg Germany. Sanofi-Aventis Deutschland GmbH 65926 Frankfurt am Main Germany. stefan.guessregen@***. Sanofi-Aventis Deutschland GmbH 65926 Frankfurt am Main Germany. GlaxoSmithKline Stevenage SG1 2NY UK. nicola.j.richmond@***. Discngine Paris 75011 France. Organisch-Chemisches Institut Westfälische Wilhelms-Universität Münster Germany. marwin.segler@wwu.de. Organisch-Chemisches Institut Westfälische Wilhelms-Universität Münster Germany. Bundeskriminalamt Wiesbaden Central Analytics II 65173 Wiesbaden Germany. Department of Chemistry and Biochemistry University of California Santa Barbara CA 93111 USA. shea@chem.ucsb.edu. Department of Chemistry and Biochemistry University of California Santa Barbara CA 93111 USA. Chemistry Department Ludwig-Maximilians-Universität München Butenandtstr. 7 81377 Munich Germany. Inorganic Chemistry and Center for Nanointegration University of Duisburg-Essen Essen Germany. CAM-D Technologies Essen Germany. Institute for Bioinformatics and Chemoinformatics Westphalian University of Applied Sciences Recklinghausen Germany. Institute for Bioinformatics and Chemoinformatics Westphalian University of Applied Sciences Recklinghausen Germany. achim.zielesny@w-hs.de. Leiden University Leiden Netherlands. j.fraaije@chem.leidenuniv.nl. Culgi BV Berlin Germany. Physikalische Chemie III TU Dortmund 44227 Dortmund Germany. stefan.kast@tu-dortmund.de. Centre for Molecular Informatics Department of Chemistry University of Cambridge Lensfield Road Cambridge CB2 1EW United Kingdom. kcb27@cam.ac.uk. Centre for Molecular Informatics Department of Chemistry

来源：评论

学校读者我要写书评

暂无评论

Joint analysis of BICEP2/Keck Array and Planck data

引用

Physical Review Letters 2015年第10期114卷 101301-101301页

作者： P. A. R. Ade N. Aghanim Z. Ahmed R. W. Aikin K. D. Alexander M. Arnaud J. Aumont C. Baccigalupi A. J. Banday D. Barkats R. B. Barreiro J. G. Bartlett N. Bartolo E. Battaner K. Benabed A. Benoît A. Benoit-Lévy S. J. Benton J.-P. Bernard M. Bersanelli P. Bielewicz C. A. Bischoff J. J. Bock A. Bonaldi L. Bonavera J. R. Bond J. Borrill F. R. Bouchet F. Boulanger J. A. Brevik M. Bucher I. Buder E. Bullock C. Burigana R. C. Butler V. Buza E. Calabrese J.-F. Cardoso A. Catalano A. Challinor R.-R. Chary H. C. Chiang P. R. Christensen L. P. L. Colombo C. Combet J. Connors F. Couchot A. Coulais B. P. Crill A. Curto F. Cuttaia L. Danese R. D. Davies R. J. Davis P. de Bernardis A. de Rosa G. de Zotti J. Delabrouille J.-M. Delouis F.-X. Désert C. Dickinson J. M. Diego H. Dole S. Donzelli O. Doré M. Douspis C. D. Dowell L. Duband A. Ducout J. Dunkley X. Dupac C. Dvorkin G. Efstathiou F. Elsner T. A. Enßlin H. K. Eriksen E. Falgarone J. P. Filippini F. Finelli S. Fliescher O. Forni M. Frailis A. A. Fraisse E. Franceschi A. Frejsel S. Galeotta S. Galli K. Ganga T. Ghosh M. Giard E. Gjerløw S. R. Golwala J. González-Nuevo K. M. Górski S. Gratton A. Gregorio A. Gruppuso J. E. Gudmundsson M. Halpern F. K. Hansen D. Hanson D. L. Harrison M. Hasselfield G. Helou S. Henrot-Versillé D. Herranz S. R. Hildebrandt G. C. Hilton E. Hivon M. Hobson W. A. Holmes W. Hovest V. V. Hristov K. M. Huffenberger H. Hui G. Hurier K. D. Irwin A. H. Jaffe T. R. Jaffe J. Jewell W. C. Jones M. Juvela A. Karakci K. S. Karkare J. P. Kaufman B. G. Keating S. Kefeli E. Keihänen S. A. Kernasovskiy R. Keskitalo T. S. Kisner R. Kneissl J. Knoche L. Knox J. M. Kovac N. Krachmalnicoff M. Kunz C. L. Kuo H. Kurki-Suonio G. Lagache A. Lähteenmäki J.-M. Lamarre A. Lasenby M. Lattanzi C. R. Lawrence E. M. Leitch R. Leonardi F. Levrier A. Lewis M. Liguori P. B. Lilje M. Linden-Vørnle M. López-Caniego P. M. Lubin M. Lueker J. F. Macías-Pérez B. Maffei D. Maino N. Mandolesi A. Mangilli M. Maris P. G. Martin E. Martínez-González S. Masi P. Mason S. Matarrese K. G. Megerian School of Physics and Astronomy Cardiff University Queens Buildings The Parade Cardiff CF24 3AA United Kingdom Institut d’Astrophysique Spatiale CNRS (UMR8617) Université Paris-Sud 11 Bâtiment 121 Orsay France Department of Physics Stanford University Stanford California 94305 USA California Institute of Technology Pasadena California USA Harvard-Smithsonian Center for Astrophysics 60 Garden Street MS 42 Cambridge Massachusetts 02138 USA Laboratoire AIM IRFU/Service d’Astrophysique–CEA/DSM–CNRS–Université Paris Diderot Bâtiment 709 CEA-Saclay F-91191 Gif-sur-Yvette Cedex France SISSA Astrophysics Sector via Bonomea 265 34136 Trieste Italy Université de Toulouse UPS-OMP IRAP F-31028 Toulouse cedex 4 France CNRS IRAP 9 Avenue colonel Roche BP 44346 F-31028 Toulouse cedex 4 France Joint ALMA Observatory Vitacura Santiago Chile Instituto de Física de Cantabria (CSIC-Universidad de Cantabria) Avenida de los Castros s/n Santander Spain APC AstroParticule et Cosmologie Université Paris Diderot CNRS/IN2P3 CEA/lrfu Observatoire de Paris Sorbonne Paris Cité 10 rue Alice Domon et Léonie Duquet 75205 Paris Cedex 13 France Jet Propulsion Laboratory California Institute of Technology 4800 Oak Grove Drive Pasadena California USA Dipartimento di Fisica e Astronomia G. Galilei Università degli Studi di Padova via Marzolo 8 35131 Padova Italy Istituto Nazionale di Fisica Nucleare Sezione di Padova via Marzolo 8 I-35131 Padova Italy University of Granada Departamento de Física Teórica y del Cosmos Facultad de Ciencias Granada Spain University of Granada Instituto Carlos I de Física Teórica y Computacional Granada Spain Institut d’Astrophysique de Paris CNRS (UMR7095) 98 bis Boulevard Arago F-75014 Paris France UPMC Université de Paris 06 UMR7095 98 bis Boulevard Arago F-75014 Paris France Institut Néel CNRS Université Joseph Fourier Grenoble I 25 rue des Martyrs Grenoble France Department of Physics and Astronomy University College London L

We report the results of a joint analysis of data from BICEP2/Keck Array and Planck. BICEP2 and Keck Array have observed the same approximately 400 deg2 patch of sky centered on RA 0 h, Dec. −57.5°. The combined maps reach a depth of 57 nK deg in Stokes Q and U in a band centered at 150 GHz. Planck has observed the full sky in polarization at seven frequencies from 30 to 353 GHz, but much less deeply in any given region (1.2 μK deg in Q and U at 143 GHz). We detect 150×353 cross-correlation in B modes at high significance. We fit the single- and cross-frequency power spectra at frequencies ≥150 GHz to a lensed-ΛCDM model that includes dust and a possible contribution from inflationary gravitational waves (as parametrized by the tensor-to-scalar ratio r), using a prior on the frequency spectral behavior of polarized dust emission from previous Planck analysis of other regions of the sky. We find strong evidence for dust and no statistically significant evidence for tensor modes. We probe various model variations and extensions, including adding a synchrotron component in combination with lower frequency data, and find that these make little difference to the r constraint. Finally, we present an alternative analysis which is similar to a map-based cleaning of the dust contribution, and show that this gives similar constraints. The final result is expressed as a likelihood curve for r, and yields an upper limit r0.05<0.12 at 95% confidence. Marginalizing over dust and r, lensing B modes are detected at 7.0σ significance.

关键词： STOKES equations FREQUENCIES of oscillating systems POWER spectra GRAVITATIONAL waves

来源：评论

学校读者我要写书评

暂无评论

Automated error detection using association rules

Automated error detection using association rules

引用

作者： Malik, Waqas Ahmed Unwin, Antony Department of Computer Oriented Statistics and Data Analysis Institute of Mathematics University of Augsburg Universittsstrasse 14 D-86159 Augsburg Germany

High data quality is important for every application. Inaccurate or inadequate data can lead to inappropriate assumptions, misleading results, bias and ultimately poor policy and decision making. Finding errors and cleaning data is a time consuming process. This paper presents a framework for automatically detecting unusual and erroneous data values in datasets. The main idea is to generate association rules with very high confidence and to identify the cases that are exceptions to these rules. Experimental results show that the proposed framework is able to successfully identify erroneous values in large datasets. © 2011-IOS Press and the authors. All rights reserved.

关键词： Error detection

来源：评论

学校读者我要写书评

暂无评论

A complete gradient clustering algorithm

A complete gradient clustering algorithm

引用

3rd International Conference on Artificial Intelligence and Computational Intelligence, AICI 2011

作者： Kulczycki, Piotr Charytanowicz, Malgorzata Systems Research Institute Polish Academy of Sciences Center for Stochastic Data Analysis Methods Newelska 6 PL-01-447 Warsaw Poland Cracow University of Technology Department of Automatic Control and Information Technology Cracow Poland Catholic University of Lublin Institute of Mathematics and Computer Science Lublin Poland

ISBN: (纸本)9783642238956

A gradient clustering algorithm, based on the nonparametric methodology of statistical kernel estimators, expanded to its complete form, enabling implementation without particular knowledge of the theoretical aspects or laborious research, is presented here. The possibilities of calculating tentative optimal parameter values, and then - based on illustrative interpretation - their potential changes, result in the proposed Complete Gradient Clustering Algorithm possessing many original and valuable, from an applicational point of view, properties. Above all the number of clusters is not arbitrarily imposed but fitted to a real data structure. It is also possible to increase the scale of the number (still avoiding arbitrary assumptions), as well as the proportion of clusters in areas of dense and sparse situation of data elements. The method is universal in character and can be applied to a wide range of practical problems, in particular from the bioinformatics, management and engineering fields. © 2011 Springer-Verlag.

关键词： Clustering algorithms

来源：评论

学校读者我要写书评

暂无评论

An interactive graphical system for visualizing data quality-Tableplot graphics

引用

11th Biennial Conference of the International Federation of Classification Societies, IFCS 2009 and with the 33rd Annual Conf of the German Classification Society (Gesellschaft fur Klassifikation) on Classification as a Tool fo Research, GfKl 2009

作者： Malik, Waqas Ahmed Unwin, Antony Gribov, Alexander Department of Computer Oriented Statistics and Data Analysis Institute of Mathematics University of Augsburg Germany

ISBN: (纸本)9783642107443

Poor quality, inaccurate or inadequate data can lead to inappropriate assumptions, misleading results, bias and ultimately poor policy and decision making. Finding errors and cleaning data is a time consuming process and requires domain knowledge. This work presents a modified technique - called Interactive Tableplot - for visualizing data and supporting the incorporation of user's domain knowledge so that erroneous cases are easily revealed. Tableplot is implemented in the software Gauguin (Gribov et al. 2006) that provides techniques for the interactive visual exploration of multivariate datasets. © 2010 Springer-Verlag Berlin Heidelberg.

关键词： Decision making

来源：评论

学校读者我要写书评

暂无评论

T.N. Herzog, F.J. Scheuren, & W.E. Winkler (2007). data quality and record linkage techniques. New York: Springer Science+Business Media. 234 pp. US$44.95. ISBN: 978-0-387-69502-0.

引用

Psychometrika 2007年第1期73卷 165-166页

作者： Malik, Waqas Ahmed Unwin, Antony Department of Computer-Oriented Statistics and Data Analysis Institute of Mathematics University of Augsburg Augsburg Germany

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：