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9th International Conference on Computer Graphics Theory and Applications, GRAPP 2014

作者： Ostkamp, Morin Luzar, Sven Bauer, Gernot Software Engineering Lab Münster University of Applied Sciences Soester Straße 13 D-48155-Münster Germany

ISBN: (纸本)9789897580024

Media facades and other public displays are a common sight in our everyday life. They can be found at various places, such as shopping malls or traffic hubs, e.g., the Times Square in New York City or Shibuya Crossing in Tokyo. Thanks to advances in technology, media facades are not bound to plane, rectangular shapes. Thus, many media facades are curved to increase their visual appearance or to better harmonize with the building behind. One example of such a curved media facade is the "Medienfassade" in the city ofMünster. The shown content, however, is visually distorted due to the facade's concave shape. That visual distortion may cause problems for certain types of content, i.e., QR codes, that may thus not be scanned with mobile apps. Since QR codes became popular in recent years, it appears desirable to display these codes on curved media facades, too. Thus, we propose two preprocessing approaches to compensate for the visual distortions of the curved media facade. An in-situ evaluation showed that both approaches can be used to "rectify" the distorted QR codes and let them be scanned successfully.

关键词： Inverse problems

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26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 Antwerp, Belgium. 15-20 July 2017 Abstracts

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 95-176页

作者： [Anonymous] Department of Neuroscience Yale University New Haven CT 06520 USA Department Physiology & Pharmacology SUNY Downstate Brooklyn NY 11203 USA NYU School of Engineering 6 MetroTech Center Brooklyn NY 11201 USA Departament de Matemàtica Aplicada Universitat Politècnica de Catalunya Barcelona 08028 Spain Institut de Neurobiologie de la Méditerrannée (INMED) INSERM UMR901 Aix-Marseille Univ Marseille France Center of Neural Science New York University New York NY USA Aix-Marseille Univ INSERM INS Inst Neurosci Syst Marseille France Laboratoire de Physique Théorique et Modélisation CNRS UMR 8089 Université de Cergy-Pontoise 95300 Cergy-Pontoise Cedex France Department of Mathematics and Computer Science ENSAT Abdelmalek Essaadi’s University Tangier Morocco Laboratory of Natural Computation Department of Information and Electrical Engineering and Applied Mathematics University of Salerno 84084 Fisciano SA Italy Department of Medicine University of Salerno 84083 Lancusi SA Italy Dipartimento di Fisica Università degli Studi Aldo Moro Bari and INFN Sezione Di Bari Italy Data Analysis Department Ghent University Ghent Belgium Coma Science Group University of Liège Liège Belgium Cruces Hospital and Ikerbasque Research Center Bilbao Spain BIOtech Department of Industrial Engineering University of Trento and IRCS-PAT FBK 38010 Trento Italy Department of Data Analysis Ghent University Ghent 9000 Belgium The Wellcome Trust Centre for Neuroimaging University College London London WC1N 3BG UK Department of Electronic Engineering NED University of Engineering and Technology Karachi Pakistan Blue Brain Project École Polytechnique Fédérale de Lausanne Lausanne Switzerland Departement of Mathematics Swansea University Swansea Wales UK Laboratory for Topology and Neuroscience at the Brain Mind Institute École polytechnique fédérale de Lausanne Lausanne Switzerland Institute of Mathematics University of Aberdeen Aberdeen Scotland UK Department of Integrativ

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25th Annual Computational Neuroscience Meeting CNS-2016, Seogwipo City, South Korea, July 2-7, 2016 Abstracts

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BMC NEUROSCIENCE 2016年第1期17卷 1-112页

作者： [Anonymous] Computational Neurobiology Laboratory The Salk Institute for Biological Studies San Diego USA UNIC CNRS Gif sur Yvette France The European Institute for Theoretical Neuroscience (EITN) Paris France ATR Computational Neuroscience Laboratories Kyoto Japan Krembil Research Institute University Health Network Toronto Canada Department of Physiology University of Toronto Toronto Canada Department of Medicine (Neurology) University of Toronto Toronto Canada Department of Physics University of New Hampshire Durham USA Department of Neurophysiology Nencki Institute of Experimental Biology Warsaw Poland Department of Theory Wigner Research Centre for Physics of the Hungarian Academy of Sciences Budapest Hungary Department of Mathematical Sciences KAIST Daejoen Republic of Korea Department of Mathematics University of Houston Houston USA Department of Biochemistry & Cell Biology and Institute of Biosciences and Bioengineering Rice University Houston USA Department of Biology and Biochemistry University of Houston Houston USA Grupo de Neurocomputación Biológica Dpto. de Ingeniería Informática Escuela Politécnica Superior Universidad Autónoma de Madrid Madrid Spain Department of Biological Sciences University of Southern California Los Angeles USA Center for Neuroscience Korea Institute of Science and Technology Seoul South Korea Department of Neurology Albert Einstein College of Medicine Bronx USA Center for Neuroscience KIST Seoul South Korea Department of Neuroscience University of Science and Technology Daejon South Korea Systems Neuroscience Group QIMR Berghofer Medical Research Institute Herston Australia Department of Psychology Yonsei University Seoul South Korea Department of Psychiatry Kyung Hee University Hospital at Gangdong Seoul South Korea Department of Psychiatry Veterans Administration Boston Healthcare System and Harvard Medical School Brockton USA Department of Electrical and Electronic Engineering The University of Melbourne Parkvil

A1 Functional advantages of cell-type heterogeneity in neural circuits Tatyana O. Sharpee A2 Mesoscopic modeling of propagating waves in visual cortex Alain Destexhe A3 Dynamics and biomarkers of mental disorders Mitsuo Kawato F1 Precise recruitment of spiking output at theta frequencies requires dendritic h-channels in multi-compartment models of oriens-lacunosum/moleculare hippocampal interneurons Vladislav Sekulić, Frances K. Skinner F2 Kernel methods in reconstruction of current sources from extracellular potentials for single cells and the whole brains Daniel K. Wójcik, Chaitanya Chintaluri, Dorottya Cserpán, Zoltán Somogyvári F3 The synchronized periods depend on intracellular transcriptional repression mechanisms in circadian clocks. Jae Kyoung Kim, Zachary P. Kilpatrick, Matthew R. Bennett, Kresimir Josić O1 Assessing irregularity and coordination of spiking-bursting rhythms in central pattern generators Irene Elices, David Arroyo, Rafael Levi, Francisco B. Rodriguez, Pablo Varona O2 Regulation of top-down processing by cortically-projecting parvalbumin positive neurons in basal forebrain Eunjin Hwang, Bowon Kim, Hio-Been Han, Tae Kim, James T. McKenna, Ritchie E. Brown, Robert W. McCarley, Jee Hyun Choi O3 Modeling auditory stream segregation, build-up and bistability James Rankin, Pamela Osborn Popp, John Rinzel O4 Strong competition between tonotopic neural ensembles explains pitch-related dynamics of auditory cortex evoked fields Alejandro Tabas, André Rupp, Emili Balaguer-Ballester O5 A simple model of retinal response to multi-electrode stimulation Matias I. Maturana, David B. Grayden, Shaun L. Cloherty, Tatiana Kameneva, Michael R. Ibbotson, Hamish Meffin O6 Noise correlations in V4 area correlate with behavioral performance in visual discrimination task Veronika Koren, Timm Lochmann, Valentin Dragoi, Klaus Obermayer O7 Input-location dependent gain modulation in cerebellar nucleus neurons Maria Psarrou, Maria Schilstra, Neil Davey, Benjamin Torben-Ni

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The biometric menagerie-A fuzzy and inconsistent concept

The biometric menagerie-A fuzzy and inconsistent concept

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5th International Workshop on Soft Computing Applications, SOFA 2012

作者： Popescu-Bodorin, Nicolaie Balas, Valentina Emilia Motoc, Iulia Maria Artificial Intelligence and Computational Logic Lab. Mathematics and Computer Science Department Spiru Haret University Bucharest Romania Automatics and Applied Software Department Faculty of Engineering Aurel Vlaicu University Arad Romania

ISBN: (纸本)9783642339400

This paper proves that in iris recognition, the concepts of sheep, goats, lambs and wolves-as proposed by Doddington and Yager in the so-called Biometric Menagerie, are at most fuzzy and at least not quite well defined. They depend not only on the users or on their biometric templates, but also on the parameters that calibrate the iris recognition system. This paper shows that, in the case of iris recognition, the extensions of these concepts have very unsharp and unstable (non-stationary) boundaries. The membership of a user to these categories is more often expressed as a degree (as a fuzzy value) rather than as a crisp value. Moreover, they are defined by fuzzy Sugeno rules instead of classical (crisp) definitions. For these reasons, we said that the Biometric Menagerie proposed by Doddington and Yager could be at most a fuzzy concept of biometry, but even this status is conditioned by improving its definition. All of these facts are confirmed experimentally in a series of 12 exhaustive iris recognition tests undertaken for University of Bath Iris Image Database while using three different iris code dimensions (256x16, 128x8 and 64x4), two different iris texture encoders (Log Gabor and Haar Hilbert) and two different types of safety models. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Biometrics

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An approach to develop location-based efficiency systems without real test drives

An approach to develop location-based efficiency systems wit...

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2012 IEEE International Electric Vehicle Conference, IEVC 2012

作者： Ganslmeier, Thomas Kellner, Martin Bruegge, Bernd Audi Electronics Venture GmbH Sachsstrasse 18 85080 Gaimersheim Germany VW Electronic Research Lab. Belmont CA 94002 United States Department of Applied Software Engineering TU Munich Germany

ISBN: (纸本)9781467315623

The development of intelligent vehicle systems based on non-deterministic input signals of the environment, have a dramatically increased complexity. Real test drives are no longer adequate to cover all test-cases, due to costs and complexity. One way to meet this challenge is a simulated test drive. In this case the driver, the environment and the vehicle are described within simulation models. Scenarios can be reproduced exactly. Tests can be executed automatically. Based on realistic road networks, realistic positioning data can be simulated. This allows development and testing of location-based systems. Especially for electric vehicles location-based systems are of great importance. We developed a simulation framework which represents the three domains (vehicle, driver and environment) within a closed-loop simulation. Using the framework we are able to execute simulated test-drives. In order to confirm the significance of the simulated test drive for the development, we validate the quality of the simulation results with data recorded on an electric vehicle fleet test. The architecture enables to reproduce a real test drive within a closed loop simulation. © 2012 IEEE.

关键词： Digital storage

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Research on virtual reality sound effects for high-speed train simulation system

Journal of Software

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Journal of software 2012年第8期7卷 1919-1922页

作者： Su, Ruidan Zhang, Kunlin Yan, Weiwei Zhao, Zhandong Xu, Huaiyu Wen, Tao College of Information Science and Engineering Northeastern University Shenyang China Integrated Circuit Applied Software Lab Software College Northeastern University Shenyang China Service Science Research Center Shanghai Advanced Research Institute Chinese Academy of Sciences China

In this paper, virtual reality sound effects for high-speed train simulation system using wavelet denoising algorithm is studied. As one important part of the high speed train operation system, virtual reality system visualizes most parameter in train operation process. Sound effect system provides sound information to the whole simulation system. It is greatly significance to the whole effect and reality of the simulation. Here we will introduce high-speed train virtual reality sound analysis and acquisition method. Based on wavelet denoising algorithm, we analyze the filtering mechanism and realization of highspeed train virtual reality sound effect. Combining audio files and the type of virtual reality scene, we present a new virtual reality sound model and realization mode;eventually offer a new ideal and flexible solution to high-speed train virtual reality sound effect system. © 2012 ACADEMY PUBLISHER.

关键词： Virtual reality

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FECG extraction using wavelet denoising and neural networks approach

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ICIC Express Letters 2011年第3期5卷 667-673页

作者： Yin, Ying Ye, Mao Zhu, Yuanxiang Ren, Dongxiao School of Applied Mathematics School of Computer Science and Engineering University of Electronic Science and Technology of China No. 4 Sec. 2 Jianshe North Road Chengdu 610054 China State Key Lab. for Novel Software Technology Nanjing University 22 Hankou Road Nanjing 210093 China

Neural networks have received much attention in the extraction of fetal electrocardiogram signal in recent years. This paper provides a new method to extract the fetal electrocardiogram signal which uses wavelet denoising and backpropagation algorithm. We suppose there are two signals obtained from thoracic region and abdominal region of a pregnant woman. By denoising the abdominal signal using wavelet, and then subtracting the distorted thoracic signal from the denoised abdominal signal, the fetal electrocardiogram signal is achieved. The distorted thoracic signal is received by backpropagation algorithm because neural networks can uniformly approximate every continuous function if there is sufficient number of neurons in the hidden layer. © 2011 ISSN 1881-803X.

关键词： Extraction

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Assessment of NER solutions against the first and second CALBC Silver Standard Corpus

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Journal of Biomedical Semantics 2011年第5期2卷 1-12页

作者： Rebholz-Schuhmann, Dietrich Yepes, Antonio Jimeno Li, Chen Kafkas, Senay Lewin, Ian Kang, Ning Corbett, Peter Milward, David Buyko, Ekaterina Beisswanger, Elena Hornbostel, Kerstin Kouznetsov, Alexandre Witte, René Laurila, Jonas B Baker, Christopher JO Kuo, Cheng-Ju Clematide, Simone Rinaldi, Fabio Farkas, Richárd Móra, György Hara, Kazuo Furlong, Laura I Rautschka, Michael Neves, Mariana Lara Pascual-Montano, Alberto Wei, Qi Collier, Nigel Chowdhury, Md Faisal Mahbub Lavelli, Alberto Berlanga, Rafael Morante, Roser Van Asch, Vincent Daelemans, Walter Marina, José Luís van Mulligen, Erik Kors, Jan Hahn, Udo European Bioinformatics Institute EMBL Outstation Hinxton Cambridge CB10 1SD United Kingdom Erasmus University Medical Center Dept. of Medical Informatics Rotterdam Netherlands St. John's Innovation Centre Linguamatics Ltd Cambridge United Kingdom Friedrich-Schiller-Universität Language and Information Engineering (JULIE) Lab Jena Germany University of New Brunswick Dept. of Computer Science and Applied Statistics Canada Concordia University Dept. of Computer Science and Software Engineering Montreal Canada Academia Sinica Institute of Information Science Taipei 115 Taiwan University of Zürich Switzerland Hungarian Academy of Sciences Research Group on Artificial Intelligence Hungary Nara Institute of Science and Technology Nara Japan IMIM (Hospital del Mar Research Institute) Universitat Pompeu Fabra Research Programme on Biomedical Informatics (GRIB) Barcelona Spain National Center for Biotechnology-CSIC Madrid Spain National Institute of Informatics Tokyo Japan Fondazione Bruno Kessler Trento Italy Universitat Jaume I Spain University of Antwerp CLiPS Belgium Complutense University of Madrid Spain

Background: Competitions in text mining have been used to measure the performance of automatic text processing solutions against a manually annotated gold standard corpus (GSC). The preparation of the GSC is time-consuming and costly and the final corpus consists at the most of a few thousand documents annotated with a limited set of semantic groups. To overcome these shortcomings, the CALBC project partners (PPs) have produced a large-scale annotated biomedical corpus with four different semantic groups through the harmonisation of annotations from automatic text mining solutions, the first version of the Silver Standard Corpus (SSC-I). The four semantic groups are chemical entities and drugs (CHED), genes and proteins (PRGE), diseases and disorders (DISO) and species (SPE). This corpus has been used for the First CALBC Challenge asking the participants to annotate the corpus with their text processing solutions. Results: All four PPs from the CALBC project and in addition, 12 challenge participants (CPs) contributed annotated data sets for an evaluation against the SSC-I. CPs could ignore the training data and deliver the annotations from their genuine annotation system, or could train a machine-learning approach on the provided pre-annotated data. In general, the performances of the annotation solutions were lower for entities from the categories CHED and PRGE in comparison to the identification of entities categorized as DISO and SPE. The best performance over all semantic groups were achieved from two annotation solutions that have been trained on the SSC-I. The data sets from participants were used to generate the harmonised Silver Standard Corpus II (SSC-II), if the participant did not make use of the annotated data set from the SSC-I for training purposes. The performances of the participants' solutions were again measured against the SSC-II. The performances of the annotation solutions showed again better results for DISO and SPE in comparison to CHED and P

关键词： Chemical Entity Cosine Similarity Semantic Type Semantic Group Annotate Corpus

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Reports of the AAAI 2010 fall symposia

Reports of the AAAI 2010 fall symposia

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作者： Azevedo, Roger Biswas, Gautam Bohus, Dan Carmichael, Ted Finlayson, Mark A. Hadzikadic, Mirsad Havasi, Catherine Horvitz, Eric Kanda, Takayuki Koyejo, Oluwasanmi Lawless, William F. Lenat, Doug Meneguzzi, Felipe Mutlu, Bilge Oh, Jean Pirrone, Roberto Raux, Antoine Sofge, Donald A. Sukthankar, Gita Van Durme, Benjamin Yorke-Smith, Neil Department of Educational and Counseling Psychology McGill University Canada Center for Intelligent Systems Vanderbilt University United States Microsoft Research Redmond United States Department of Software and Information Systems University of North Carolina Charlotte United States Complex Systems Institute United States Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology United States Media Lab. Massachusetts Institute of Technology United States ATR Intelligent Robotics and Communication Laboratories Kyoto Japan Department of Electrical and Computer Engineering University of Texas Austin United States Department of Mathematics Paine College Augusta GA United States Cycorp Austin TX United States Robotics Institute Carnegie Mellon University United States Department of Computer Sciences University of Wisconsin Madison United States University of Palermo Italy Honda Research Institute United States Navy Center for Applied Research in Artificial Intelligence Naval Research Laboratory Washington DC United States Department of Electrical Engineering and Computer Science University of Central Florida United States Department of Computer Science Johns Hopkins University United States American University of Beirut Lebanon SRI International's Artificial Intelligence Center United States

The Association for the Advancement of Artificial Intelligence (AAAI) presented the 2010 Fall Symposium Series on November 11-13, 2010. The eight symposia included Cognitive and Metacognitive Educational Systems, Commonsense Knowledge, Complex Adaptive Systems: Resilience, Robustness, and Evolvability, Computational Models of Narrative, Dialog with Robots, Manifold Learning and Its Applications, Proactive Assistant Agents and Quantum Informatics for Cognitive, Social, and Semantic Processes. Cognitive and Metacognitive Educational Systems aimed to provide a comprehensive definition of metacognitive educational systems that is inclusive of the theoretical, architectural, and educational aspects of this field. The AAAI Commonsense Knowledge Fall Symposium had the goal of bringing together the diverse elements of this community whose work benefits from or contributes to the representation of general knowledge about the world. One of the specific goals of Proactive symposium was to gather the researchers from various projects in assistant agents to share their wisdom in retrospect.

关键词： Semantics

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FECG extraction using Bayesian inference and neural networks approximation

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Journal of Computational Information Systems 2010年第6期6卷 1769-1778页

作者： Yin, Ying Ye, Mao Ren, Dongxiao Zhu, Yuanxiang Yang, Chenxue School of Applied Mathematics University of Electronic Science and Technology of China Chengdu 611731 China School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu 611731 China State Key Lab. for Novel Software Technology Nanjing University Nanjing China

Neural networks have received much attention in the extraction of fetal electrocardiogram signal in recent years. This paper provides a new method to extract the fetal electrocardiogram signal which uses Bayesian inference and neural networks approximation. We suppose there are two signals obtained from thoracic region and abdominal region of a pregnant woman. Due to the characteristics of Bayesian statistics, electrocardiogram signal can be modeled by generalized Gaussian distribution. Neural networks is used to approximate nonlinear function. The distorted thoracic signal is obtained by backpropagation algorithm because neural networks can uniformly approximate any continuous function if there is sufficient number of neurons in the hidden layer. Iterative technique is also used to update the fetal electrocardiogram signal. By using Bayesian inference and neural networks approximation, the fetal electrocardiogram signal is achieved. Simulations demonstrate that the effectiveness of our method. Copyright © 2010 Binary Information Press.

关键词： Extraction

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