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ACM Special Interest Group on computer Graphics and Interactive Techniques Conference, SIGGRAPH 2014

作者： McNamara, Ann Mania, Katerina Koulieris, George Itti, Laurent Department of Visualization Texas A and M University United States Dept. of Electronic and Computer Engineering Technical University of Crete Greece Department of Computer Science Psychology and Neuroscience University of Southern California United States

ISBN: (纸本)9781450329620

Rendering and design efficiency become critical when deploying computer graphics to mobile devices and games. This course addresses novel approaches to leverage models of visual attention, based on low and high level scene features, to propel attention-aware rendering computation. The result: perceptually-optimized scalable algorithms for mobile platforms and game design. Recent research on low-level attention algorithms whose architecture and function is closely inspired from biological brains will be reviewed (Baldi & Itti, 2010). High level saliency instigated by cognitive information such as scene context and topology will also be discussed (Zotos, Mania, & Mourkoussis, 2009;?, ?). Prediction of attention can significantly improve many aspects of computer graphics and games. Image synthesis can be accelerated by reducing computation on non-attended scene regions. Subtle gaze manipulation (Bailey, McNamara, Sudarsanam, & Grimm, 2009a) improves mammography training and spatial recall as well as dynamically inuence interactive neuroscientific protocols in fMRI. The course will showcase through interactive content how employing a visual attention model leads to efficient game design. Many games rely on search or target detection tasks to solve riddles or find game objects. Adjusting the difficulty of a level could be facilitated by relocating objects estimated to attract attention. By incorporating visual attention estimation, perceptually optimized renderers for mobile platforms can dynamically ignore perceptually non-important details. Modern video games and interactive applications are simultaneously deployed for computers, consoles and mobile devices of diverse computational power. Complex effects including but not limited to complex refraction and subsurface scattering that are standard in desktop computers, could also scale efficiently in portable devices if attention-aware. Examples such as the integration of a high level saliency model in a LOD manager, enab

关键词： computer games

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PAPR reduction in an OFDM system using recursive clipping and filtering technique

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WSEAS Transactions on Communications 2014年第1期13卷 291-297页

作者： Islam, Anamul Ahmed, N. Ahamed, Nizam Uddin Rahman, Matiur Aljunid, S.A. Dept. of Applied Physics and Electronic Engineering University of Rajshahi Bangladesh School of Computer and Communication Engineering University Malaysia Perlis Malaysia Biomedical Engineering Program Mechatronic Engineering University Malaysia Perlis Malaysia College of Computer Science and Information System Najran University Saudi Arabia

An Orthogonal Frequency Division Multiplexing (OFDM) scheme is expected as an efficient technique for next generation wireless communications. However, high Peak to Average Power Ration (PAPR) of OFDM system is the main drawback which degrades the transmitter power efficiency causes poor performance of the system. To reduce PAPR of OFDM signal, several works on clipping technique have been proposed. This paper is incorporated the improvement of the PAPR and Bit Error Rate (BER) performance using clipping method. It has been shown from the result that by employing the recursive clipping and filtering, 11.45 dB of PAPR of original OFDM signal is reduced down to 4.77 dB. Hence, BER is also increased significantly. This research is carried out through MATLAB simulation and gradually measured the effect of PAPR on BER under AWGN channel for 16QAM scheme with 256 points OFDM. Moreover, it is studied the effect of OFDM signal while passing through High Power Amplifier (HPA). Finally, the PAPR reduction technique such as recursive clipping and filtering (RCF) is implemented.

关键词： Orthogonal frequency division multiplexing

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Feature extraction for identification of sugarcane rust disease

Feature extraction for identification of sugarcane rust dise...

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2014 International Conference on Information, Communication Technology and System, ICTS 2014

作者： Dewi, Ratih Kartika Ginardi, R. V. Hari Information Technology and Computer Science Program Brawijaya University Malang Indonesia Dept. of Informatics Faculty of Information Technology Institut Teknologi Sepuluh Nopember Surabaya Indonesia

ISBN: (纸本)9781479968572

This research propose an image pattern classification to identify rust disease in sugarcane leaf with a combination of texture and color feature extraction. The purpose of this research is to find appropriate features that can identify sugarcane rust disease. Firstly, normal and diseased images are collected and pre-processed. Then, features of shape, color and texture are extracted from these images. After that, these images are classified by support vector machine classifier. A combination of several features are used to evaluate the appropriate features to find distinctive features for identification of rust disease. When a single feature is used, shape feature has the lowest accuracy of 51% and texture feature has the highest accuracy of 96.5%. A combination of texture and color feature extraction results a highest classification accuracy of 97.5%. A combination of texture and color feature extraction with polynomial kernel results in 98.5 % classification accuracy. © 2014 IEEE.

关键词： Feature extraction

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Dark Energy Survey Year 1 results: Methodology and projections for joint analysis of galaxy clustering, galaxy lensing, and CMB lensing two-point functions

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Physical Review D 2019年第2期99卷 023508-023508页

作者： E. J. Baxter Y. Omori C. Chang T. Giannantonio D. Kirk E. Krause J. Blazek L. Bleem A. Choi T. M. Crawford S. Dodelson T. F. Eifler O. Friedrich D. Gruen G. P. Holder B. Jain M. Jarvis N. MacCrann A. Nicola S. Pandey J. Prat C. L. Reichardt S. Samuroff C. Sánchez L. F. Secco E. Sheldon M. A. Troxel J. Zuntz T. M. C. Abbott F. B. Abdalla J. Annis S. Avila K. Bechtol B. A. Benson E. Bertin D. Brooks E. Buckley-Geer D. L. Burke A. Carnero Rosell M. Carrasco Kind J. Carretero F. J. Castander R. Cawthon C. E. Cunha C. B. D’Andrea L. N. da Costa C. Davis J. De Vicente D. L. DePoy H. T. Diehl P. Doel J. Estrada A. E. Evrard B. Flaugher P. Fosalba J. Frieman J. García-Bellido E. Gaztanaga D. W. Gerdes R. A. Gruendl J. Gschwend G. Gutierrez W. G. Hartley D. Hollowood B. Hoyle D. J. James S. Kent K. Kuehn N. Kuropatkin O. Lahav M. Lima M. A. G. Maia M. March J. L. Marshall P. Melchior F. Menanteau R. Miquel A. A. Plazas A. Roodman E. S. Rykoff E. Sanchez R. Schindler M. Schubnell I. Sevilla-Noarbe M. Smith R. C. Smith M. Soares-Santos F. Sobreira E. Suchyta M. E. C. Swanson G. Tarle A. R. Walker W. L. K. Wu J. Weller Department of Physics and Astronomy University of Pennsylvania Philadelphia Pennsylvania 19104 USA Kavli Institute for Particle Astrophysics and Cosmology Stanford University 452 Lomita Mall Stanford California 94305 Dept. of Physics Stanford University 382 Via Pueblo Mall Stanford California 94305 Department of Physics and McGill Space Institute McGill University Montreal Quebec H3A 2T8 Canada Kavli Institute for Cosmological Physics University of Chicago Chicago Illinois 60637 USA Institute of Astronomy University of Cambridge Madingley Road Cambridge CB3 0HA United Kingdom Kavli Institute for Cosmology University of Cambridge Madingley Road Cambridge CB3 0HA United Kingdom Universitäts-Sternwarte Fakultät für Physik Ludwig-Maximilians Universität München Scheinerstr. 1 81679 München Germany Department of Physics & Astronomy University College London Gower Street London WC1E 6BT United Kingdom Department of Astronomy/Steward Observatory 933 North Cherry Avenue Tucson Arizona 85721-0065 USA Jet Propulsion Laboratory California Institute of Technology 4800 Oak Grove Dr. Pasadena California 91109 USA Center for Cosmology and Astro-Particle Physics The Ohio State University Columbus Ohio 43210 USA Institute of Physics Laboratory of Astrophysics École Polytechnique Fédérale de Lausanne (EPFL) Observatoire de Sauverny 1290 Versoix Switzerland Department of Physics University of Chicago 5640 South Ellis Avenue Chicago Illinois 60637 USA Argonne National Laboratory 9700 South Cass Avenue Lemont Illinois 60439 USA Scottish Universities Physics Alliance Institute for Astronomy University of Edinburgh Royal Observatory Blackford Hill Edinburgh EH9 3HJ United Kingdom Center for Cosmology and AstroParticle Physics The Ohio State University 191 West Woodruff Avenue Columbus Ohio 43210 USA Department of Astronomy and Astrophysics University of Chicago Chicago Illinois 60637 USA Observatories of the Carnegie Institution of Washington 813 Santa Ba

Optical imaging surveys measure both the galaxy density and the gravitational lensing-induced shear fields across the sky. Recently, the Dark Energy Survey (DES) Collaboration used a joint fit to two-point correlations between these observables to place tight constraints on cosmology (T. M. C. Abbott et al. (Dark Energy Survey Collaboration), Phys. Rev. D 98, 043526 (2018)). In this work, we develop the methodology to extend the DES Year 1 joint probes analysis to include cross-correlations of the optical survey observables with gravitational lensing of the cosmic microwave background as measured by the South Pole Telescope (SPT) and Planck. Using simulated analyses, we show how the resulting set of five two-point functions increases the robustness of the cosmological constraints to systematic errors in galaxy lensing shear calibration. Additionally, we show that contamination of the SPT+Planck cosmic microwave background lensing map by the thermal Sunyaev-Zel’dovich effect is a potentially large source of systematic error for two-point function analyses but show that it can be reduced to acceptable levels in our analysis by masking clusters of galaxies and imposing angular scale cuts on the two-point functions. The methodology developed here will be applied to the analysis of data from the DES, the SPT, and Planck in a companion work.

关键词： Cosmic microwave background Cosmological parameters Dark energy Evolution of the Universe Large scale structure of the Universe

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Corrigendum to “Biocorrosion behavior of biodegradable nanocomposite fibers coated layer-by-layer on AM50 magnesium implant” [Mater. Sci. Eng. C 58 (2016) 1232–1241]

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Materials science and Engineering: C 2016年 61卷 1029-1029页

作者： Abdalla Abdal-hay Anwarul Hasan Yu-Kyoung Kim Min-Ho Lee Abdel Salam Hamdy Khalil Abdelrazek Khalil Dept. of Engineering Materials and Mechanical Design Faculty of Engineering South Valley University Qena Egypt Dept. of Mechanical and Biomedical Engineering American University of Beirut Beirut Lebanon Dept of Mechanical and Industrial Engineering College of Engineering Qatar University P.O. Box 2713 Doha Qatar Dept of Dental Biomaterials and Institute of Biodegradable Materials Institute of Oral Bioscience and School of Dentistry (plus BK21 program) Chonbuk National University Jeon Ju 561-756 South Korea Dept. of Manufacturing and Industrial Engineering College of Engineering and Computer Science University of Texas Rio Grande Valley 1201West University Dr. Edinburg TX 78541-2999 USA Dept. of Mechanical Engineering College of Engineering King Saud University P.O. Box 800 Riyadh 11421 Saudi Arabia Dept. of Mechanical Engineering Faculty of Energy Engineering Aswan University Aswan Egypt

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Peak Misdetection In Heart-Beat-Based Security: Characterization and Tolerance

Peak Misdetection In Heart-Beat-Based Security: Characteriza...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society

作者： Robert M. Seepers Christos Strydis Pedro Peris-Lopez Ioannis Sourdis Chris I. De Zeeuw Dept. of Neuroscience Erasmus Medical Center Dept. of Computer Science Universidad Carlos III de Madrid Dept. of Computer Science & Engineering Chalmers University of Technology

ISBN: (纸本)9781424479276

The Inter-Pulse-Interval (IPI) of heart beats has previously been suggested for security in mobile health (mHealth) applications. In IPI-based security, secure communication is facilitated through a security key derived from the time difference between heart beats. However, there currently exists no work which considers the effect on security of imperfect heart-beat (peak) detection. This is a crucial aspect of IPI-based security and likely to happen in a real system. In this paper, we evaluate the effects of peak misdetection on the security performance of IPI-based security. It is shown that even with a high peak detection rate between 99.9% and 99.0%, a significant drop in security performance may be observed (between -70% and -303%) compared to having perfect peak detection. We show that authenticating using smaller keys yields both stronger keys as well as potentially faster authentication in case of imperfect heart beat detection. Finally, we present an algorithm which tolerates the effect of a single misdetected peak and increases the security performance by up to 155%.

关键词： Authentication Entropy Wireless communication Heart beat Wireless sensor networks Communication system security

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A Detection of CMB-Cluster Lensing using Polarization Data from SPTpol

arXiv

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arXiv 2019年

作者： Raghunathan, S. Patil, S. Baxter, E. Benson, B.A. Bleem, L.E. Crawford, T.M. Holder, G.P. McClintock, T. Reichardt, C.L. Varga, T.N. Whitehorn, N. Ade, P.A.R. Allam, S. Anderson, A.J. Austermann, J.E. Avila, S. Avva, J.S. Bacon, D. Beall, J.A. Bender, A.N. Bianchini, F. Bocquet, S. Brooks, D. Burke, D.L. Carlstrom, J.E. Carretero, J. Castander, F.J. Chang, C.L. Chiang, H.C. Citron, R. Costanzi, M. Crites, A.T. Costa, L.N. da Desai, S. Diehl, H.T. Dietrich, J.P. Dobbs, M.A. Doel, P. Everett, S. Evrard, A.E. Feng, C. Flaugher, B. Fosalba, P. Frieman, J. Gallicchio, J. García-Bellido, J. Gaztanaga, E. George, E.M. Giannantonio, T. Gilbert, A. Gruendl, R.A. Gschwend, J. Gupta, N. Gutierrez, G. Haan, T. de Halverson, N.W. Harrington, N. Henning, J.W. Hilton, G.C. Hollowood, D.L. Holzapfel, W.L. Honscheid, K. Hrubes, J.D. Huang, N. Hubmayr, J. Irwin, K.D. Jeltema, T. Kind, M. Carrasco Knox, L. Kuropatkin, N. Lahav, O. Lee, A.T. Li, D. Lima, M. Lowitz, A. Maia, M.A.G. Marshall, J.L. McMahon, J.J. Melchior, P. Menanteau, F. Meyer, S.S. Miquel, R. Mocanu, L.M. Mohr, J.J. Montgomery, J. Moran, C. Corbett Nadolski, A. Natoli, T. Nibarger, J.P. Noble, G. Novosad, V. Ogando, R.L.C. Padin, S. Plazas, A.A. Pryke, C. Rapetti, D. Romer, A.K. Roodman, A. Rosell, A. Carnero Rozo, E. Ruhl, J.E. Rykoff, E.S. Saliwanchik, B.R. Sanchez, E. Sayre, J.T. Scarpine, V. Schaffer, K.K. Schubnell, M. Serrano, S. Sevilla-Noarbe, I. Sievers, C. Smecher, G. Smith, M. Soares-Santos, M. Stark, A.A. Story, K.T. Suchyta, E. Swanson, M.E.C. Tarle, G. Tucker, C. Vanderlinde, K. Veach, T. de Vicente, J. Vieira, J.D. Vikram, V. Wang, G. Wu, W.L.K. Yefremenko, V. Zhang, Y. Department of Physics and Astronomy University of California Los AngelesCA90095 United States School of Physics University of Melbourne ParkvilleVIC3010 Australia Department of Physics and Astronomy University of Pennsylvania PhiladelphiaPA19104 United States Fermi National Accelerator Laboratory MS209 P.O. Box 500 BataviaIL60510 United States Kavli Institute for Cosmological Physics University of Chicago 5640 South Ellis Avenue ChicagoIL60637 United States Department of Astronomy and Astrophysics University of Chicago 5640 South Ellis Avenue ChicagoIL60637 United States High Energy Physics Division Argonne National Laboratory 9700 S. Cass Avenue ArgonneIL60439 United States Astronomy Department University of Illinois at Urbana-Champaign 1002 W. Green Street UrbanaIL61801 United States Department of Physics University of Illinois Urbana-Champaign 1110 W. Green Street UrbanaIL61801 United States Canadian Institute for Advanced Research CIFAR Program in Gravity and Extreme Universe TorontoONM5G 1Z8 Canada Department of Physics University of Arizona TucsonAZ85721 United States Max Planck Institute for Extraterrestrial Physics Giessenbachstrasse Garching85748 Germany Universitäts-Sternwarte Fakultät für Physik LudwigMaximilians Universität München Scheinerstr. 1 München81679 Germany Cardiff University CardiffCF10 3XQ United Kingdom Fermi National Accelerator Laboratory P. O. Box 500 BataviaIL60510 United States NIST Quantum Devices Group 325 Broadway Mailcode 817.03 BoulderCO80305 United States Instituto de Fisica Teorica UAM/CSIC Universidad Autonoma de Madrid Madrid28049 Spain Department of Physics University of California BerkeleyCA94720 United States Institute of Cosmology & Gravitation University of Portsmouth Dennis Sciama Building Burnaby Road PortsmouthPO1 3FX United Kingdom Faculty of Physics Ludwig-Maximilians-Universität Scheinerstr. 1 Munich81679 Germany Department of Physics & Astronomy University Co

We report the first detection of gravitational lensing due to galaxy clusters using only the polarization of the cosmic microwave background (CMB). The lensing signal is obtained using a new estimator that extracts the lensing dipole signature from stacked images formed by rotating the cluster-centered Stokes Q/U map cutouts along the direction of the locally measured background CMB polarization gradient. Using data from the SPTpol 500 deg2 survey at the locations of roughly 18,000 clusters with richness λ ≥ 10 from the Dark Energy Survey (DES) Year-3 full galaxy cluster catalog, we detect lensing at 4.8σ. The mean stacked mass of the selected sample is found to be (1.43 ± 0.40) × 1014 M☉which is in good agreement with optical weak lensing based estimates using DES data and CMB-lensing based estimates using SPTpol temperature data. This measurement is a key first step for cluster cosmology with future low-noise CMB surveys, like CMB-S4, for which CMB polarization will be the primary channel for cluster lensing measurements. Copyright © 2019, The Authors. All rights reserved.

关键词： Surveys

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Amb-EM: A SNP-based prediction of HLA alleles using ambiguous HLA Data 14

Amb-EM: A SNP-based prediction of HLA alleles using ambiguou...

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5th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics, ACM BCB 2014

作者： Paunić, Vanja Steinbach, Michael Madbouly, Abeer Kumar, Vipin Dept. of Computer Science University of Minnesota MinneapolisMN55455 United States National Marrow Donor Program Bioinformatics Research MinneapolisMN55413 United States

ISBN: (纸本)9781450328944

The Human Leukocyte Antigen (HLA) genes are some of the most studied genes on the genome. This is due to their importance in bone marrow and solid organ transplantation, as well as their strong associations with many autoimmune, infectious, and inammatory diseases. As such, they can be a highly valuable asset to clinicians and researchers for elucidating biological mechanism that may drive those diseases. The extraordinary genetic polymorphism that exists in this region makes it very challenging to type. Therefore, several approaches were proposed for prediction of HLA genes from widely available genome-wide single nucleotide polymorphism (SNP) data sets in the attempt to reduce cost and utilize existing data. These methods use SNPs and highresolution training HLA data to build models for prediction of HLA genes in new samples. However, most of the existing HLA data sets are not available in high-resolution (exact allele assignment) but contain allelic ambiguities (inexact allele assignments). This is a result of existing typing methodologies not always being able to distinguish between several possible alleles at a given gene and produce ambiguous allele as a result. Current approaches for prediction of HLA genes from SNP data do not accommodate learning from ambiguous HLA data and, as such, miss the potential for an increased sample size and consequently improvements in prediction performance. In this paper, we propose Amb-EM, a novel algorithm for SNP-based prediction of HLA genes that utilizes ambiguities in the HLA data and predicts highresolution alleles using ambiguous HLA alleles for building the model. Additionally, we measure the impact that the uncertainty in the training data has on the prediction accuracy, and evaluate it on a real world data set. Our results show that the prediction from ambiguous HLA data outperforms the alternative approach which first imputes the ambiguous data into high-resolution HLA alleles and uses it to build the model. Copyrig

关键词： Forecasting

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A problem-action relation extraction based on causality patterns of clinical events in discharge summaries 14

A problem-action relation extraction based on causality patt...

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23rd ACM International Conference on Information and Knowledge Management, CIKM 2014

作者： Seol, Jae-Wook Jo, Seung-Hyeon Yi, Wangjin Choi, Jinwook Lee, Kyung-Soon Dept. of Computer Science and Engineering CAIIT Chonbuk National University Korea Republic of Interdisciplinary Program of Bioengineering College of Engineering Seoul National University Korea Republic of Dept. of Biomedical Engineering College of Medicine Seoul National University Korea Republic of

ISBN: (纸本)9781450325981

Medical knowledge extraction has great potential to improve the treatment quality of hospitals. In this paper, we propose a clinical problem-action relation extraction method. It is based on clinical semantic units and event causality patterns in order to present a chronological view of a patient's problem and a physician's action. Based on our observation, a clinical semantic unit is defined as a conceptual medical knowledge for a problem and/or action. Since a clinical event is a basic concept of the problem-action relation, events are detected from clinical texts based on conditional random fields. A clinical semantic unit is segmented from a sentence based on time expressions and inherent structure of events. Then, a clinical semantic unit is classified into a problem and/or action relation based on event causality features in support vector machines. The experimental result on Korean medical collection shows 78.8% in F-measure when given the answer of clinical events. This result shows that the proposed method is effective for extracting clinical problem-action relations.

关键词： Semantics

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Abstracts and Workshops 7th National Spinal Cord Injury Conference November 9-11, 2017 Fallsview Casino Resort Niagara Falls, Ontario, Canada Abstracts

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JOURNAL OF SPINAL CORD MEDICINE 2017年第6期40卷 813-869页

作者： [Anonymous] a NET Team Toronto Rehabilitation Institute - University Health Network Toronto ON Canada. fo Neural Engineering and Therapeutic Team Lyndhurst Centre Toronto Rehabilitation Institute - University Health Network Toronto ON Canada. c Rick Hansen Institute Vancouver BC Canada. ev Rick Hansen Institute Vancouver BC Canada. fc Stan Cassidy Hospital University of New Brunswick Fredericton NB Canada. fd Dalhousie University Halifax NS Canada. e University of Saskatchewan Saskatoon SK Canada. aa University of Calgary Calgary AB Canada. y Dalhousie University Halifax NS Canada. fa Health Sciences Centre Winnipeg MB Canada. fb University of Manitoba Winnipeg MB Canada. h University of Alberta Edmonton AB Canada. i Universite Laval Quebe c City QC Canada. bd Rick Hansen Institute Vancouver BC Canada. fz Clinician Investigator Lyndhurst Centre Toronto Rehabilitation Institute University Health Network and Assistant Professor Department of Medicine Division of Physical Medicine and Rehabilitation University of Toronto. v University of Toront o Toronto ON Canada. n Institute of Biomaterials and Biomedical Engineering University of Toronto Toronto ON Canada. o Toronto Rehabilitation Institute - University Health Network Toronto ON Canada. ga Clinical Scientist Lyndhurst Centre Toronto Rehabilitation Institute University Health Network and Assistant Professor Department of Physical Therapy University of Toronto. dx Department of Electrical and Computer Engineering University of Toronto Toronto ON Canada. fm Lawson Health Research Institute London ON Canada. r Parkwood Institute London ON Canada. bi Parkwood Institute London ON Canada. s University of British Columbia Vancouver BC Canada. t Simon Fraser University Burnaby BC Canada. u DeltaQuest Foundation Concord MA USA. z Institut national d'excellence en santé et en services sociaux (INESSS) Quebec City QC Ca

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