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arXiv 2018年

作者： Shajib, A.J. Birrer, S. Treu, T. Auger, M.W. Agnello, A. Anguita, T. Buckley-Geer, E.J. Chan, J.H.H. Collett, T.E. Courbin, F. Fassnacht, C.D. Frieman, J. Kayo, I. Lemon, C. Lin, H. Marshall, P.J. McMahon, R. More, A. Morgan, N.D. Motta, V. Oguri, M. Ostrovski, F. Rusu, C.E. Schechter, P.L. Shanks, T. Suyu, S.H. Meylan, G. Abbott, T.M.C. Allam, S. Annis, J. Avila, S. Bertin, E. Brooks, D. Rosell, A. Carnero Kind, M. Carrasco Carretero, J. Cunha, C.E. da Costa, L.N. de Vicente, J. Desai, S. Doel, P. Flaugher, B. Fosalba, P. García-Bellido, J. Gerdes, D.W. Gruen, D. Gruendl, R.A. Gutierrez, G. Hartley, W.G. Hollowood, D.L. Hoyle, B. James, D.J. Kuehn, K. Kuropatkin, N. Lahav, O. Lima, M. Maia, M.A.G. March, M. Marshall, J.L. Melchior, P. Menanteau, F. Miquel, R. Plazas, A.A. Sanchez, E. Scarpine, V. Sevilla-Noarbe, I. Smith, M. Soares-Santos, M. Sobreira, F. Suchyta, E. Swanson, M.E.C. Tarle, G. Walker, A.R. Department of Physics and Astronomy University of California Los AngelesCA90095-1547 United States Institute of Astronomy Madingley Road CambridgeCB3 0HA United Kingdom European Southern Observatory Karl-Schwarzschild-Strasse 2 Garching bei Muenchen85748 Germany Departamento de Ciencias Fisicas Universidad Andres Bello Fernandez Concha 700 Las Condes Santiago Chile Millennium Institute of Astrophysics Chile Fermi National Accelerator Laboratory P. O. Box 500 BataviaIL60510 United States Observatoire de Sauverny VersoixCH-1290 Switzerland Institute of Cosmology and Gravitation University of Portsmouth PortsmouthPO1 3FX United Kingdom Physics Dept. University of California Davis 1 Shields Ave. DavisCA95161 United States Kavli Institute for Cosmological Physics University of Chicago ChicagoIL60637 United States Department of Liberal Arts Tokyo University of Technology Ota-kuTokyo144-8650 Japan Kavli Institute for Particle Astrophysics and Cosmology P.O. Box 20450 MS29 StanfordCA94309 United States UTIAS University of Tokyo KashiwaChiba277-8583 Japan Staples High School WestportCT06880 United States Instituto de Física y Astronomía Universidad de Valparaíso Avda. Gran Bretaña 1111 Playa Ancha Valparaíso2360102 Chile Research Center for the Early Universe University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-0033 Japan Department of Physics University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-0033 Japan University of Tokyo 5-1-5 Kashiwanoha Kashiwa Chiba277-8583 Japan Subaru telescope National Astronomical Observatory of Japan 650 North Aohoku Place HiloHI96720 United States MIT Kavli Institute for Astrophysics and Space Research CambridgeMA02139 United States Dept. of Physics Durham University South Road DurhamDH1 3LE United Kingdom Max-Planck-Institut für Astrophysik Karl-Schwarzschild-Str. 1 Garching85748 Germany Physik-Department Technische Universität München James-Franck-Straße 1 Garching85748 Germany In

Strong-gravitational lens systems with quadruply-imaged quasars (quads) are unique probes to address several fundamental problems in cosmology and astrophysics. Although they are intrinsically very rare, ongoing and planned wide-field deep-sky surveys are set to discover thousands of such systems in the next decade. It is thus paramount to devise a general framework to model strong-lens systems to cope with this large influx without being limited by expert investigator time. We propose such a general modelling framework (implemented with the publicly available software Lenstronomy) and apply it to uniformly model three-band Hubble Space Telescope Wide Field Camera 3 images of 13 quads. This is the largest uniformly modelled sample of quads to date and paves the way for a variety of studies. To illustrate the scientific content of the sample, we investigate the alignment between the mass and light distribution in the deflectors. The position angles of these distributions are well-aligned, except when there is strong external shear. However, we find no correlation between the ellipticity of the light and mass distributions. We also show that the observed flux-ratios between the images depart significantly from the predictions of simple smooth models. The departures are strongest in the bluest band, consistent with microlensing being the dominant cause in addition to millilensing. Future papers will exploit this rich dataset in combination with ground based spectroscopy and time delays to determine quantities such as the Hubble constant, the free streaming length of dark matter, and the normalization of the initial stellar mass function. Copyright © 2018, The Authors. All rights reserved.

关键词： Galaxies

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Shape Representation and Classification through Pattern Spectrum and Local Binary Pattern -- A Decision Level Fusion Approach

Shape Representation and Classification through Pattern Spec...

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International Conference on Signal and Image Processing (ICSIP)

作者： B.H. Shekar Bharathi Pilar Department of Computer Science Mangalore University Mangalore Karnataka India Dept. of Master of Computer Applications St. Aloysius College Mangalore Karnataka India

In this paper, we present a decision level fused local Morphological Pattern Spectrum (PS) and Local Binary Pattern (LBP) approach for an efficient shape representation and classification. This method makes use of Earth Movers Distance (EMD) as the measure in feature matching and shape retrieval process. The proposed approach has three major phases: Feature Extraction, Construction of hybrid spectrum knowledge base and Classification. In the first phase, feature extraction of the shape is done using pattern spectrum and local binary pattern method. In the second phase, the histograms of both pattern spectrum and local binary pattern are fused and stored in the knowledge base. In the third phase, the comparison and matching of the features, which are represented in the form of histograms, is done using Earth Movers Distance (EMD) as metric. The top-n shapes are retrieved for each query shape. The accuracy is tested by means of standard Bulls eye score method. The experiments are conducted on publicly available shape datasets like Kimia-99, Kimia-216 and MPEG-7. The comparative study is also provided with the well known approaches to exhibit the retrieval accuracy of the proposed approach.

关键词： Shape Skeleton Histograms Feature extraction Earth Transform coding Electric shock

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Big data Processing for Prediction of Traffic Time Based on Vertical data Arrangement

Big Data Processing for Prediction of Traffic Time Based on ...

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IEEE International Conference on Cloud Computing Technology and science (CloudCom)

作者： Seungwoo Jeon Bonghee Hong Byungsoo Kim Dept. of Electrical and Computer Engineering Pusan National University Busan South Korea Dept. of Data Science Inje University Busan South Korea

ISBN: (纸本)9781479940929

To predict future traffic conditions in each road with unique spatiotemporal pattern, it is necessary to analyze the conditions based on historical traffic data and select time series forecasting methods which can be predicting next pattern for each road according to the analyzed results. Our goal is to create a new statistical model and a new system for predictive graphs of traffic times based on big data processing tools. First, we suggest a vertical data arrangement, gathering past traffic times in the same time slot for long-term prediction. Second, we analyze each traffic pattern to select time-series variables because a time-series forecasting method for a location and a time will be selected according to the variables that are available. Third, we suggest a spatiotemporal prediction map, which is a two-dimensional map with time and location. Each element in the map represents a time-series forecasting method and an R-squared value as indicator of prediction accuracy. Finally, we introduce a new system including RHive as a middle point between R and Hadoop clusters for generating predicted data efficiently from big historical data.

关键词： Roads Forecasting Spatiotemporal phenomena Market research Accuracy Analytical models Predictive models

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A Two Stage Approach for Handwritten Malayalam Character Recognition

A Two Stage Approach for Handwritten Malayalam Character Rec...

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International Workshop on Frontiers in Handwriting Recognition

作者： Jomy John K.V. Pramod Kannan Balakrishnan Bidyut B. Chaudhuri Dept. of Computer Applications Cochin University of Science and Technology Kochi India Computer Vision & Pattern Recognition Unit Indian Statistical Institute Kolkata India

Handwritten character recognition is still a research challenge in OCR discipline, especially for Indian scripts. This paper deals with handwritten Malayalam, a major Indian script, where past work considered a small subset of characters only. In this paper we deal with complete set of basic characters, vowel and consonant signs and compound characters that may be present in the script. Here the recognition task is more difficult because of large numbers of classes and high interclass similarity. To tackle the problem, we proposed a two-stage approach. The first stage is a group classifier, where a group consists of similar characters and those that misclassify among themselves. In the second stage, a character assigned to a group in the first stage is classified to a particular character class. The proposed scheme is more accurate and efficient than a single stage scheme.

关键词： Compounds Character recognition Support vector machines Shape Handwriting recognition Feature extraction databases

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An Evaluation of Popular Edge Detection Techniques in Digital Image Processing

An Evaluation of Popular Edge Detection Techniques in Digita...

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International Conference on Intelligent Computing applications (ICICA)

作者： N. Anandakrishnan S. Santhosh Baboo Research Scholar Department of Computer Science Bharathiar University Coimbatore PG & Research Dept. of Computer Applications D.G. Vaishnav College Chennai

Edge is a sudden change that occurs in an image. Edge Detection is the approach used most frequently for segmenting images based on abrupt changes in intensity. It is a concept that covers a number of fields in today's environment. In this paper the survey of different Edge Detection techniques like classical, augmented or may be a derived algorithm in different bases such as Fuzzy Logic, Genetic Algorithm, or Neural Networks and others which are used as Soft Computing Approaches today, are comparatively studied.

关键词： Image edge detection Detectors Image color analysis Noise Image segmentation Neural networks Laplace equations

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An Architecture for data Security in Cloud Computing

An Architecture for Data Security in Cloud Computing

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World Congress on Computing and Communication Technologies (WCCCT)

作者： M. Sugumaran B. Bala Murugan D. Kamalraj Dept. of Computer Science & Engineering Pondicherry Engineering College Puducherry India Dept. of Comput. Sci. & Applic. Rajiv Gandhi Arts & Sci. Coll. Puducherry India Dept. of Computer Science & Applications Rajiv Gandhi Arts & Science College Puducherry India

Cloud computing is a more flexible, cost effective and proven delivery platform for providing business or consumer services over the Internet. Cloud computing supports distributed service oriented architecture, multi-user and multi-domain administrative infrastructure. So, it is more prone to security threats and vulnerabilities. At present, a major concern in cloud adoption is towards its security and privacy. Security and privacy issues are of great concern to cloud service providers who are actually hosting the services. In most cases, the provider must guarantee that their infrastructure is secure and clients' data and applications are safe, by implementing security policies and mechanisms. The security issues are organized into several general categories: trust, identity management, software isolation, data protection, availability reliability, ownership, data backup, data portability and conversion, multi platform support and intellectual property. In this paper, it is discuss about some of the techniques that were implemented to protect data and propose architecture to protect data in cloud. This architecture was developed to store data in cloud in encrypted data format using cryptography technique which is based on block cipher.

关键词： Cloud computing computer architecture Encryption Ciphers

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Discriminative DCT: An Efficient and Accurate Approach for Off-Line Signature Verification

Discriminative DCT: An Efficient and Accurate Approach for O...

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International Conference on Signal and Image Processing (ICSIP)

作者： R.K. Bharathi B.H. Shekar Dept. of Master of Computer Applications S.J. College of Engineering Mysore Karnataka India Department of Computer Science Mangalore University Mangalore Karnataka India

In this paper, we proposed to combine the transform based approach with dimensionality reduction technique for off-line signature verification. The proposed approach has four major phases: Preprocessing, Feature extraction, Feature reduction and Classification. In the feature extraction phase, Discrete Cosine Transform (DCT) is employed on the signature image to obtain the upper-left corner block of size mX n as a representative feature vector. These features are subjected to Linear Discriminant Analysis (LDA) for further reduction and representing the signature with optimal set of features. Thus obtained features from all the samples in the dataset form the knowledge base. The Support Vector Machine (SVM), a bilinear classifier is used for classification and the performance is measured through FAR/FRR metric. Experiments have been conducted on standard signature datasets namely CEDAR and GPDS-160, and MUKOS, a regional language (Kannada) dataset. The comparative study is also provided with the well known approaches to exhibit the performance of the proposed approach.

关键词： Support vector machines Discrete cosine transforms Training Feature extraction Forgery Knowledge based systems Vectors

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A Random Sampling Algorithm for SVP Challenge Based on y-Sparse Representations of Short Lattice Vectors

A Random Sampling Algorithm for SVP Challenge Based on y-Spa...

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International Conference on Computational Intelligence and Security

作者： Dan Ding Guizhen Zhu Dept. of Computer Sciences Tsinghua University Beijing ChinaPR Data Communication Science and Technology Research Institute Beijing ChinaPR

ISBN: (纸本)9781479974351

In this paper, we propose a novel random sampling algorithm for the shortest vector problem (SVP) based on the y-sparse representations of the short lattice vectors. The experimental results show that the random sampling algorithm outperforms the other two SVP algorithms under the benchmarks of SVP challenge[1]. Therefore, the random sampling algorithm is an efficient SVP solver for the shortest vector problem.

关键词： Vectors Lattices Cryptography Complexity theory Polynomials Algorithms

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Dark Energy Survey year 1 results: 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100卷 023541-023541页

作者： T. M. C. Abbott F. B. Abdalla A. Alarcon S. Allam J. Annis S. Avila K. Aylor M. Banerji N. Banik E. J. Baxter K. Bechtol M. R. Becker B. A. Benson G. M. Bernstein E. Bertin F. Bianchini J. Blazek L. E. Bleem S. L. Bridle D. Brooks E. Buckley-Geer D. L. Burke J. E. Carlstrom A. Carnero Rosell M. Carrasco Kind J. Carretero F. J. Castander R. Cawthon C. Chang C. L. Chang H-M. Cho A. Choi R. Chown T. M. Crawford A. T. Crites M. Crocce C. E. Cunha C. B. D’Andrea L. N. da Costa C. Davis T. de Haan J. DeRose S. Desai J. De Vicente H. T. Diehl J. P. Dietrich M. A. Dobbs S. Dodelson P. Doel A. Drlica-Wagner T. F. Eifler J. Elvin-Poole W. B. Everett B. Flaugher P. Fosalba O. Friedrich J. Frieman J. García-Bellido M. Gatti E. Gaztanaga E. M. George D. W. Gerdes T. Giannantonio D. Gruen R. A. Gruendl J. Gschwend G. Gutierrez N. W. Halverson N. L. Harrington W. G. Hartley G. P. Holder D. L. Hollowood W. L. Holzapfel K. Honscheid Z. Hou B. Hoyle J. D. Hrubes D. Huterer B. Jain D. J. James M. Jarvis T. Jeltema M. W. G. Johnson M. D. Johnson S. Kent D. Kirk L. Knox N. Kokron E. Krause K. Kuehn O. Lahav A. T. Lee E. M. Leitch T. S. Li M. Lima H. Lin D. Luong-Van N. MacCrann M. A. G. Maia A. Manzotti D. P. Marrone J. L. Marshall P. Martini J. J. McMahon F. Menanteau S. S. Meyer R. Miquel L. M. Mocanu J. J. Mohr J. Muir T. Natoli A. Nicola B. Nord Y. Omori S. Padin S. Pandey A. A. Plazas A. Porredon J. Prat C. Pryke M. M. Rau C. L. Reichardt R. P. Rollins A. K. Romer A. Roodman A. J. Ross E. Rozo J. E. Ruhl E. S. Rykoff S. Samuroff C. Sánchez E. Sanchez J. T. Sayre V. Scarpine K. K. Schaffer L. F. Secco S. Serrano I. Sevilla-Noarbe E. Sheldon E. Shirokoff G. Simard M. Smith M. Soares-Santos F. Sobreira Z. Staniszewski A. A. Stark K. T. Story E. Suchyta M. E. C. Swanson G. Tarle D. Thomas M. A. Troxel D. L. Tucker K. Vanderlinde J. D. Vieira P. Vielzeuf V. Vikram A. R. Walker R. H. Wechsler J. Weller R. Williamson W. L. K. Wu B. Yanny O. Zahn Y. Zhang J. Zuntz Cerro Tololo Inter-American Observatory National Optical Astronomy Observatory Casilla 603 La Serena Chile Department of Physics & Astronomy University College London Gower Street London WC1E 6BT United Kingdom Department of Physics and Electronics Rhodes University P.O. Box 94 Grahamstown 6140 South Africa Institut d’Estudis Espacials de Catalunya (IEEC) 08193 Barcelona Spain Institute of Space Sciences (ICE CSIC) Campus UAB Carrer de Can Magrans s/n 08193 Barcelona Spain Fermi National Accelerator Laboratory P.O. Box 500 Batavia Illinois 60510 USA Institute of Cosmology & Gravitation University of Portsmouth Portsmouth PO1 3FX United Kingdom Department of Physics University of California Davis California 95616 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 Department of Physics and Astronomy University of Pennsylvania Philadelphia Pennsylvania 19104 USA LSST 933 North Cherry Avenue Tucson Arizona 85721 USA Argonne National Laboratory 9700 South Cass Avenue Lemont Illinois 60439 USA Kavli Institute for Cosmological Physics University of Chicago Chicago Illinois 60637 USA Department of Astronomy and Astrophysics University of Chicago Chicago Illinois 60637 USA CNRS UMR 7095 Institut d’Astrophysique de Paris F-75014 Paris France Sorbonne Universités UPMC Univ Paris 06 UMR 7095 Institut d’Astrophysique de Paris F-75014 Paris France School of Physics University of Melbourne Parkville VIC 3010 Australia 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 High Energy Physics Division Argonne National Laboratory Argonne Illinois 60439 USA Jodrell Bank Center for Astrophysics School of Physic

We perform a joint analysis of the auto and cross-correlations between three cosmic fields: the galaxy density field, the galaxy weak lensing shear field, and the cosmic microwave background (CMB) weak lensing convergence field. These three fields are measured using roughly 1300 sq. deg. of overlapping optical imaging data from first year observations of the Dark Energy Survey (DES) and millimeter-wave observations of the CMB from both the South Pole Telescope Sunyaev-Zel’dovich survey and Planck. We present cosmological constraints from the joint analysis of the two-point correlation functions between galaxy density and galaxy shear with CMB lensing. We test for consistency between these measurements and the DES-only two-point function measurements, finding no evidence for inconsistency in the context of flat ΛCDM cosmological models. Performing a joint analysis of five of the possible correlation functions between these fields (excluding only the CMB lensing autospectrum) yields S8≡σ8Ωm/0.3=0.782−0.025+0.019 and Ωm=0.260−0.019+0.029. We test for consistency between these five correlation function measurements and the Planck-only measurement of the CMB lensing autospectrum, again finding no evidence for inconsistency in the context of flat ΛCDM models. Combining constraints from all six two-point functions yields S8=0.776−0.021+0.014 and Ωm=0.271−0.016+0.022. These results provide a powerful test and confirmation of the results from the first year DES joint-probes analysis.

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

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Fast 3D Object Alignment from dept. Image with 3D Fourier Moment Matching on GPU

Fast 3D Object Alignment from Depth Image with 3D Fourier Mo...

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International Conference on 3D Imaging, Modeling, Processing, Visualization and Transmission (3DIMPVT)

作者： Hong-Ren Su Hao-Yuan Kuo Shang-Hong Lai Chin-Chia Wu Institute of Information Systems and Applications National Tsing Hua University Hsinchu Taiwan Dept. of Computer Science National Tsing Hua University Hsinchu Taiwan

In this paper, we develop a fast and accurate 3D object alignment system which can be applied to detect objects and estimate their 3D pose from a dept. image containing cluttered background. The proposed 3D alignment system consists of two main algorithms: the first is the 3D detection algorithm to detect the top-level object from a dept. map of the cluttered 3D objects, and the second is the 3D Fourier based point-set alignment algorithm to estimate the 3D object pose from an input dept. image. We also implement the proposed 3D alignment algorithm on a GPU computing platform to speed up the computation of the object detection and Fourier-based image alignment algorithms in order to align the 3D object in real time.

关键词： Three-dimensional displays Graphics processing units Image segmentation Object detection Fourier transforms Parallel processing

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