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On the implementation of the Opus coordination language

Concurrency and Computation: Practice and Experience 2000年第4期12卷

作者： Erwin Laure Matthew Haines Piyush Mehrotra Hans Zima Institute for Software Technology and Parallel Systems University of Vienna Liechtensteinstrasse 22 A-1090 Vienna Austria Department of Computer Science University of Wyoming Laramie WY 82071-3682 U.S.A. Institute for Computer Applications in Science and Engineering NASA Langley Research Center Mail Stop 132C Hampton VA 23681-0001 U.S.A.

Opus is a new programming language designed to assist in coordinating the execution of multiple, independent program modules. With the help of Opus, coarse grained task parallelism between data parallel modules can be expressed in a clean and structured way. In this paper we address the problems of how to build a compilation and runtime support system that can efficiently implement the Opus constructs. Our design considers the often-conflicting goals of efficiency and modular construction through software re-use. In particular, we present the system requirements for an efficient Opus implementation, the Opus runtime system, and describe how they work together to provide the underlying services that the Opus compiler needs for a broad class of machines. Copyright © 2000 John Wiley & Sons, Ltd.

关键词： Opus task parallelism data parallelism coordination

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Interactive video lessons for electromagnetic education

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computer applications in engineering Education 1993年第2期1卷 147-147页

作者： Iskander, M.F. Reed, T. Breen, J. III. Electrical Engineering Department University of Utah Salt Lake City Utah 84112 Dr. Iskander edited two special issues of theJournal of Microwave Power one on “Electromagnetics and Energy Applications” March 1983 and the other on “Electromagnetic Techniques in Medical Diagnosis and Imaging” September 1983. He authored one book onElectromagnetic Fields and Waves published by Prentice Hall 1992 he edited theCAEME Software Book Vol. I 1991 and coedited two books onMicrowave Processing of Materials one published by the Materials Research Society in 1991 and the second to be published in 1992. The holder of seven patents he has contributed 16 chapters to eight research books published more than 100 papers in technical journals and made numerous presentations in technical conferences. In 1983 he received the College of Engineering Outstanding Teaching Award and the College Patent Award for creative innovative and practical invention. In 1984 he was selected by the Utah Section of the IEEE as the Engineer of the Year. In 1984 he received the Outstanding Paper Award from the International Microwave Power Institute and in 1985 he received the Curtis W. McGraw ASEE National Research Award for outstanding early achievements by a university faculty member. In 1991 he received the ASEE George Westinghouse National Award for innovation in Engineering Education. He also received the 1992 Richard R. Stoddard Award from the IEEE EMC Society. In 1986 Dr. Iskander established the Engineering Clinic Program in the College of Engineering at the University of Utah. Since then the program has attracted more than 45 research projects from 18 different companies throughout the United States. He is also the director of the NSF/IEEE Center for Computer Applications in Electromagnetics Education (CAEME). He coorganized symposia on “Microwave Processing of Materials” held in conjunction with Materials Research Society meetings Springs of 1990 and 1992 in San Francisco. He also organized several workshops and special

With the availability of a large number of software packages for electromagnetic (EM) education through the national computer applications in Electromagnetic Education (CAEME) Center [1] and other individual efforts, there have been some concerns regarding the ability to integrate this software effectively in routine classroom teaching. Basically, congested EM curricula do not provide instructors with sufficient time to include software demonstrations and simulations during class periods. It is also not clear whether students will be able, adequately and independently, to understand basic underlying concepts and physical phenomena from visualization of colorful graphics and from the output of performed simulations. To help integrate available EM software in classroom teaching for both instructor use and student independent study, CAEME developed three interactive video lessons for student instruction. Interactive media lessons integrate and allow individuals to interactively manipulate information from multimedia such as video, software, and animated graphics, and also include instructional information such as quizzes and tutorials. In this article, we present the features of three interactive video lessons in EM developed by CAEME. These lessons include tutorials, simulations from CAEME software and videos, and quizzes to evaluate student understanding. The lessons use animated graphics illustrating specific dynamic phenomena and specific measurement procedures. They also keep a record of student quiz scores for instructor use. These, as well as other features of the three developed interactive video lessons, and the software and hardware requirements for developing such lessons, will be described.

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NSF/IEEE CAEME center. An exciting opportunity to align electromagnetic education with the nineties

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computer applications in engineering Education 1992年第1期1卷 33-33页

作者： Iskander, M.F. CAEME Director Electrical Engineering Department University of Utah Salt Lake City Utah 84112 Dr. Iskander edited two special issues of theJournal of Microwave Power one on “Electromagnetics and Energy Applications” March 1983 and the other on “Electromagnetic Techniques in Medical Diagnosis and Imaging” September 1983. He authored one book onElectromagnetic Fields and Waves published by Prentice Hall in 1992 he edited theCAEME Software Book Vol. I 1991 and he coedited a third book onMicrowave Processing of Materials published by the Materials Research Society in 1991. The holder of seven patents he has contributed 16 chapters to eight research books published more than 90 papers in technical journals and made numerous presentations in technical conferences. In 1983 he received the College of Engineering Outstanding Teaching Award and the College Patent Award for creative innovative and practical invention. In 1984 he was selected by the Utah Section of the IEEE as Engineer of the Year. In 1984 he received the Outstanding Paper Award from the International Microwave Power Institute and in 1985 he received the Curtis W. McGraw ASEE National Research Award for outstanding early achievements by a university faculty member. In 1991 he received the ASEE George Westinghouse National Award for innovation in engineering education. In 1986 Dr. Iskander established the Engineering Clinic Program in the College of Engineering at the University of Utah. Since then the program has attracted more than 45 research projects from 18 companies throughout the United States. He is also the director of the NSF/IEEE Center for Computer Applications in Electromagnetics Education (CAEME). He co-organized symposia on “Microwave Processing of Materials” held in conjunction with Materials Research Society meetings in the Springs of 1990 and 1992 in San Francisco. He also organized several workshops and special sessions in conjunction with IEEE symposia. Dr. Iskander is the editor of the journalComputer Applications i

The National Science Foundation/Institute of Electrical and Electronic Engineers (NSF/IEEE) Center for computer applications in Electromagnetic (EM) Education (CAEME) was funded in early 1990 by the National Science Foundation to stimulate and accelerate the use of computers and software tools in EM education. The Center is managed by the Executive Office of IEEE on behalf of the Antennas and Propagation Society. This organizational structure provided avenues for broad participation by universities, professional societies, and corporations in the Center's activities. In two years of operation, CAEME has organized several workshops and special sessions in international meetings, published its first software book, prepared a lesson on “Electromagnetic Waves” using interactive video, and raised over $ 130,000 from university membership, participating societies, and corporate sponsors. This article summarizes CAEME activities, outlines its organizational structure, and briefly describes the contents of its first software book. Future developments are discussed and avenues for participation are outlined.

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NTIRE 2022 Challenge on Efficient Super-Resolution: Methods and Results

arXiv

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arXiv 2022年

作者： Li, Yawei Zhang, Kai Timofte, Radu Van Gool, Luc Kong, Fangyuan Li, Mingxi Liu, Songwei Du, Zongcai Liu, Ding Zhou, Chenhui Chen, Jingyi Han, Qingrui Li, Zheyuan Liu, Yingqi Chen, Xiangyu Cai, Haoming Qiao, Yu Dong, Chao Sun, Long Pan, Jinshan Zhu, Yi Zong, Zhikai Liu, Xiaoxiao Hui, Zheng Yang, Tao Ren, Peiran Xie, Xuansong Hua, Xian-Sheng Wang, Yanbo Ji, Xiaozhong Lin, Chuming Luo, Donghao Tai, Ying Wang, Chengjie Zhang, Zhizhong Xie, Yuan Cheng, Shen Luo, Ziwei Yu, Lei Wen, Zhihong Wu, Qi Li, Youwei Fan, Haoqiang Sun, Jian Liu, Shuaicheng Huang, Yuanfei Jin, Meiguang Huang, Hua Liu, Jing Zhang, Xinjian Wang, Yan Long, Lingshun Li, Gen Zhang, Yuanfan Cao, Zuowei Sun, Lei Alexander, Panaetov Wang, Yucong Cai, Minjie Wang, Li Tian, Lu Wang, Zheyuan Ma, Hongbing Liu, Jie Chen, Chao Cai, Yidong Tang, Jie Wu, Gangshan Wang, Weiran Huang, Shirui Lu, Honglei Liu, Huan Wang, Keyan Chen, Jun Chen, Shi Miao, Yuchun Huang, Zimo Zhang, Lefei Ayazoglu, Mustafa Xiong, Wei Xiong, Chengyi Wang, Fei Li, Hao Wen, Ruimian Yang, Zhijing Zou, Wenbin Zheng, Weixin Ye, Tian Zhang, Yuncheng Kong, Xiangzhen Arora, Aditya Zamir, Syed Waqas Khan, Salman Hayat, Munawar Khan, Fahad Shahbaz Gao, Dandan Zhou, Dengwen Ning, Qian Tang, Jingzhu Huang, Han Wang, Yufei Peng, Zhangheng Li, Haobo Guan, Wenxue Gong, Shenghua Li, Xin Liu, Jun Wang, Wanjun Zeng, Kun Lin, Hanjiang Chen, Xinyu Fang, Jinsheng Zhang, Shuhao Zhang, Yuhao Sinha, Abhishek Kumar Moorthi, S. Manthira Dhar, Debajyoti Yang, Hao-Hsiang Huang, Zhi-Kai Chen, Wei-Ting Chang, Hua-En Kuo, Sy-Yen Tan, Wei Chen, Hao Xu, Qian Narang, Pratik Singh, Usneek Sameen, Syed Khaitan, Harsh Yinghua, Liu Tianlin, Zhang Xiaoming, Zhang Meng, Dingxuan Tian, Chunwei Morshed, Mashrur M. Ahsan, Ahmad Omar Computer Vision Lab ETH Zurich Switzerland University of Würzburg Germany ByteDance Shenzhen China State Key Laboratory for Novel Software Technology Nanjing University China ByteDance Inc China NetEase Inc. China Shenzhen Institutes of Advanced Technology CAS China University of Macau China Shanghai AI Lab Shanghai China Nanjing University of Science and Technology China Amazon Web Services United States China Alibaba DAMO Academy EFC Yuhang District Zhejiang Hangzhou China East China Normal University China Youtu Lab Tencent China Megvii Technology China University of Electronic Science and Technology of China China School of Artificial Intelligence Beijing Normal University China Alibaba Group China Bilibili AI China Nankai-Baidu Joint Lab Nankai University Tianjin China Platform Technologies Tencent Online Video China Higher School of Economics Russia Huawei Moscow Research Center Russia Hunan University China Xidian University China Xilinx Technology Beijing Limited China College of Information Science and Engineering Xinjiang University Urumqi China Department of Electronic Engineering Tsinghua University Beijing China Nanjing University China McMaster University Canada School of Telecommunication Engineering Xidian University Xi’an China School of Computer Science Wuhan University Wuhan China School of Mathematical Science University of Electronic Science and Technology of China Chengdu China School of Computer Science The University of Sydney Sydney Australia Aselsan Research Ankara Turkey School of Electronic and Information Engineering South-Central University for Nationalities Wuhan China Guangdong University of Technology China Fujian Normal University Fuzhou University Jimei University China Design Group China Abu Dhabi United Arab Emirates Monash University Melbourne Australia Mohamed bin Zayed University of AI United Arab Emirates North China Electric Power University Changping District Beijing China The School of Art

This paper reviews the NTIRE 2022 challenge on efficient single image super-resolution with focus on the proposed solutions and results. The task of the challenge was to super-resolve an input image with a magnification factor of ×4 based on pairs of low and corresponding high resolution images. The aim was to design a network for single image super-resolution that achieved improvement of efficiency measured according to several metrics including runtime, parameters, FLOPs, activations, and memory consumption while at least maintaining the PSNR of 29.00dB on DIV2K validation set. IMDN is set as the baseline for efficiency measurement. The challenge had 3 tracks including the main track (runtime), sub-track one (model complexity), and sub-track two (overall performance). In the main track, the practical runtime performance of the submissions was evaluated. The rank of the teams were determined directly by the absolute value of the average runtime on the validation set and test set. In sub-track one, the number of parameters and FLOPs were considered. And the individual rankings of the two metrics were summed up to determine a final ranking in this track. In sub-track two, all of the five metrics mentioned in the description of the challenge including runtime, parameter count, FLOPs, activations, and memory consumption were considered. Similar to sub-track one, the rankings of five metrics were summed up to determine a final ranking. The challenge had 303 registered participants, and 43 teams made valid submissions. They gauge the state-of-the-art in efficient single image super-resolution. © 2022, CC BY.

关键词： Chemical activation

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Arrays. A software package for analysis of antenna arrays

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computer applications in engineering Education 1992年第1期1卷 109-109页

作者： Elsherbeni, A.Z. Ginn, P.H. Electrical Engineering Department University of Mississippi University Mississippi 38677 Dr. Atef Z. Elsherbeni:received an honorary BSc in Electronics and Communications an honorary BSc in Applied Physics and an MEng in Electrical Engineering all from Cairo University Cairo Egypt in 1976 1979 and 1982 respectively. He also received a PhD in Electrical Engineering from Manitoba University Winnipeg Manitoba Canada in 1987. He was a research assistant with the faculty of Engineering at Cairo University from 1976 to 1982 and at the Electrical Engineering Department Manitoba University from 1983 to 1986 and a Postdoctoral fellow in the same department from January to August 1987. He joined the faculty at the University of Mississippi in August 1987 where he is currently an Associate Professor of Electrical Engineering. During the last few years he was involved in developing software for undergraduate education related to electromagnetic waves and antenna design courses. His professional interests include microstrip antennas scattering and diffraction of electromagnetic waves numerical techniques and computer applications for electromagnetics education. He has authored or coauthored over 80 technical papers and reports on applied electromagnetics antenna design and microwave subjects. Dr. Elsherbeni is a senior member of the Institute of Electrical and Electronics Engineers (IEEE) belonging to the Antennas and Propagation Microwave Theory and Techniques and Magnetics Societies. His honorary memberships include the Electromagnetics Academy and the Scientific Sigma Xi Society. Patrick Ginn:was born in Corinth Mississippi on June 30 1969. Mr. Ginn attended Kossuth High School where he was awarded the STAR student award. He attended Northeast Mississippi Junior College from 1987 to 1989. In 1989 he began attending the University of Mississippi. He is currently enrolled as an undergraduate in the Electrical Engineering Department. Mr. Ginn expects to receive his BSEE in August 1992. He has r

This article describes a software package useful for the instruction of antenna array theory. The program provides the radiation pattern of different types of antennas, the array factor of linear, two-dimensional and three-dimensional arrays, and the total radiation pattern. The elements of the array are isotropic source, Hertzian dipole, straight thin wire dipole, and finite line source with uniform current distribution. The user has the freedom to choose one of the supported element types or to provide the pattern of an antenna element based on experimental or calculated data. This article serves as a tutorial for selected examples as well as a quick guide for the use of this software.

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Reading Retardation or Linguistic Deficit? III: a Further Examination of Response Strategies in a Reading Test Completed by Hearing‐impaired Children

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Journal of Research in Reading 1983年第1期6卷 19-28页

作者： Beggs, W.D.A. Breslaw, P.I. W.D. Alan Beggs is a Research Fellow now working in the Blind Mobility Research Unit within the Department of Psychology at Nottingham. He obtained his first degree in Psychology from Queens University Belfast and holds a PhD from the University of Nottingham. His interests and publications have covered perceptual illusions the control of voluntary movement information processing in reading eye movements in reading clumsiness and auditory spatial knowledge in the deaf. Dr Beggs' address is Blind Mobility Research Unit Department of Psychology University of Nottingham University Park Nottingham NG7 2RD UK. W.D.A. BEGGS Blind Mobility Research Unit Department of Psychology University of Nottingham University Park Nottingham NG7 2RD UK. P.I. BRESLAW Department of Psychology University of Nottingham University Park Nottingham NG7 2RD UK. Paul I. Breslaw was a Research Assistant in the Department of Psychology at the University of Nottingham for a number of years until 1981. During that period he contributed to research projects in the automatic generation of variables in computer controlled experiments the study of on-line techniques for eye-movement recording during reading problem solving and paced aiming and the development of communicative competence in deaf children. He holds a BSc from the University of Sussex and an MPhil from Nottingham. He has recently turned his attention exclusively to computer science and runs his own software consultancy for real time and robot applications in psychology and engineering. He may be contacted at the Department of Psychology University of Nottingham University Park Nottingham NG7 2RD UK.

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CLEER - AN AI-SYSTEM DEVELOPED TO ASSIST EQUIPMENT ARRANGEMENTS ON WARSHIPS

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NAVAL ENGINEERS JOURNAL 1989年第3期101卷 127-137页

作者： ZHOU, HH SILVERMAN, BG SIMKOL, J Dr. H. Harry Zhou:is a research professor at the Institute for Artificial Intelligence of The George Washington University. Dr. Zhou received his master's degree and Ph.D. in computer science from Vanderbilt University in 1984 and 1987 respectively. He did his dissertation in the fields of artificial intelligence analogical reasoning and machine learning. His research interests include: classifier systems genetic algorithms learning by analogy inductive learning adaptive expert systems automated knowledge acquisition and adaption. He is also interested in data base design programming languages mental modeling and software engineering. Dr. Barry G. Silverman:is director of the Institute for Artificial Intelligence and a professor at the Engineering Administration Department of The George Washington University. He is also president of IntelliTek Inc. an AI consulting firm. Dr. Silverman received the B.S.E. M.S.E. and Ph.D. degrees from the University of Pennsylvania. He has been a principal developer of four generic AI products as well as eight AI applications. Since 1979 he has written over 100 papers and reports on these AI efforts. Joel Simkol:is a research scientist currently engaged in designing expert system architectures to support electronic warfare vulnerability analyses threat assessments shipboard topside antenna arrangements and C3countermeasures employment. Mr. Simkol's work in applying expert systems technology to electromagnetic interference and to spectrum management has generated increased interest and participation from all branches of government agencies.

This paper describes a modularized AI system being built to help improve electromagnetic compatibility (EMC) among shipboard topside equipment and their associated systems. CLEER is intended to act as an easy to use integrator of existing expert knowledge and pre-existing data bases and large scale analytical models. Due to these interfaces; to the need for portability of the software; and to artificial intelligence related design requirements (such as the need for spatial reasoning, expert data base management, model base management, track-based reasoning, and analogical (similar ship) reasoning) it was realized that traditional expert system shells would be inappropriate, although relatively off-the-shelf AI technology could be incorporated. In the same vein, the rapid prototyping approach to expert system design and knowledge engineering was not pursued in favor of a rigorous systems engineering methodology. The critical design decisions affecting CLEER's development are summarized in this paper along with lessons learned to date all in terms of “how,” “why,” and “when” specific features are being developed.

关键词： Artificial Intelligence

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Finding high-redshift strong lenses in DES using convolutional neural networks

arXiv

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arXiv 2018年

作者： Jacobs, C. Collett, T. Glazebrook, K. McCarthy, C. Qin, A.K. Abbott, T.M.C. Abdalla, F.B. Annis, J. Avila, S. Bechtol, K. Bertin, E. Brooks, D. Buckley-Geer, E. Burke, D.L. Carnero Rosell, A. Carrasco Kind, M. Carretero, J. da Costa, L.N. Davis, C. de Vicente, J. Desai, S. Diehl, H.T. Doel, P. Eifler, T.F. Flaugher, B. Frieman, J. García-Bellido, J. Gaztanaga, E. Gerdes, D.W. Goldstein, D.A. Gruen, D. Gruendl, R.A. Gschwend, J. Gutierrez, G. Hartley, W.G. Hollowood, D.L. Honscheid, K. Hoyle, B. James, D.J. Kuehn, K. Kuropatkin, N. Lahav, O. Li, T.S. Lima, M. Lin, H. Maia, M.A.G. Martini, P. Miller, C.J. Miquel, R. Nord, B. Plazas, A.A. Sanchez, E. Scarpine, V. Schubnell, M. Serrano, S. Sevilla-Noarbe, I. Smith, M. Soares-Santos, M. Sobreira, F. Suchyta, E. Swanson, M.E.C. Tarle, G. Vikram, V. Walker, A.R. Zhang, Y. Zuntz, J. Centre for Astrophysics & Supercomputing Swinburne University of Technology Victoria3122 Australia Institute of Cosmology & Gravitation University of Portsmouth PortsmouthPO1 3FX United Kingdom School of Software and Electrical Engineering Swinburne University of Technology P.O. Box 218 HawthornVIC3122 Australia Cerro Tololo Inter-American Observatory National Optical Astronomy Observatory Casilla 603 La Serena Chile Department of Physics & Astronomy University College London Gower Street LondonWC1E 6BT United Kingdom Department of Physics and Electronics Rhodes University PO Box 94 Grahamstown6140 South Africa Fermi National Accelerator Laboratory P. O. Box 500 BataviaIL60510 United States LSST 933 North Cherry Avenue TucsonAZ85721 United States CNRS UMR 7095 Institut d’Astrophysique de Paris ParisF-75014 France Sorbonne Universités UPMC Univ Paris 06 UMR 7095 Institut d’Astrophysique de Paris ParisF-75014 France Kavli Institute for Particle Astrophysics & Cosmology Stanford University P. O. Box 2450 StanfordCA94305 United States SLAC National Accelerator Laboratory Menlo ParkCA94025 United States Laboratório Interinstitucional de e-Astronomia - LIneA Rua Gal. José Cristino 77 Rio de Janeiro RJ20921-400 Brazil Observatório Nacional Rua Gal. José Cristino 77 Rio de Janeiro RJ20921-400 Brazil Department of Astronomy University of Illinois at Urbana-Champaign 1002 W. Green Street UrbanaIL61801 United States National Center for Supercomputing Applications 1205 West Clark St. UrbanaIL61801 United States Barcelona Institute of Science and Technology Campus UAB Bellaterra [Barcelona08193 Spain Madrid Spain Department of Physics IIT Hyderabad KandiTelangana502285 India Department of Astronomy/Steward Observatory 933 North Cherry Avenue TucsonAZ85721-0065 United States Jet Propulsion Laboratory California Institute of Technology 4800 Oak Grove Dr. PasadenaCA91109 United States Kavli Institute for Cosmological Physics

We search Dark Energy Survey (DES) Year 3 imaging data for galaxy-galaxy strong gravitational lenses using convolutional neural networks. We generate 250,000 simulated lenses at redshifts > 0.8 from which we create a data set for training the neural networks with realistic seeing, sky and shot noise. Using the simulations as a guide, we build a catalogue of 1.1 million DES sources with 1.8 19, g_mag > 20 and i_mag > 18.2. We train two ensembles of neural networks on training sets consisting of simulated lenses, simulated non-lenses, and real sources. We use the neural networks to score images of each of the sources in our catalogue with a value from 0 to 1, and select those with scores greater than a chosen threshold for visual inspection, resulting in a candidate set of 7,301 galaxies. During visual inspection we rate 84 as "probably" or "definitely" lenses. Four of these are previously known lenses or lens candidates. We inspect a further 9,428 candidates with a different score threshold, and identify four new candidates. We present 84 new strong lens candidates, selected after a few hours of visual inspection by astronomers. This catalogue contains a comparable number of high-redshift lenses to that predicted by simulations. Based on simulations we estimate our sample to contain most discoverable lenses in this imaging and at this redshift range. Copyright © 2018, The Authors. All rights reserved.

关键词： Lenses

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An extended catalog of galaxy-galaxy strong gravitational lenses discovered in DES using convolutional neural networks

arXiv

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arXiv 2019年

作者： Jacobs, C. Collett, T. Glazebrook, K. Buckley-Geer, E. Diehl, H.T. Lin, H. McCarthy, C. Qin, A.K. Odden, C. Caso Escudero, M. Dial, P. Yung, V.J. Gaitsch, S. Pellico, A. Lindgren, K.A. Abbott, T.M.C. Annis, J. Avila, S. Brooks, D. Burke, D.L. Carnero Rosell, A. Carrasco Kind, M. Carretero, J. da Costa, L.N. de Vicente, J. Fosalba, P. Frieman, J. García-Bellido, J. Gaztanaga, E. Goldstein, D.A. Gruen, D. Gruendl, R.A. Gschwend, J. Hollowood, D.L. Honscheid, K. Hoyle, B. James, D.J. Krause, E. Kuropatkin, N. Lahav, O. Lima, M. Maia, M.A.G. Marshall, J.L. Miquel, R. Plazas, A.A. Roodman, A. Sanchez, E. Scarpine, V. Serrano, S. Sevilla-Noarbe, I. Smith, M. Sobreira, F. Suchyta, E. Swanson, M.E.C. Tarle, G. Vikram, V. Walker, A.R. Zhang, Y. Centre for Astrophysics and Supercomputing Swinburne University of Technology P.O. Box 218 HawthornVIC3122 Australia Swinburne University of Technology HawthornVIC3122 Australia Institute of Cosmology & Gravitation University of Portsmouth Portsmouthpo1 3fx United Kingdom Fermi National Accelerator Laboratory P. O. Box 500 BataviaIL60510 United States School of Software and Electrical Engineering Swinburne University of Technology P.O. Box 218 HawthornVIC3122 Australia Phillips Academy AndoverMA01810 United States Cerro Tololo Inter-American Observatory National Optical Astronomy Observatory Casilla 603 La Serena Chile Fermi National Accelerator Laboratory P. O. Box 500 BataviaIL60510 United States Instituto de Fisica Teorica UAM/CSIC Universidad Autonoma de Madrid Madrid28049 Spain Department of Physics & Astronomy University College London Gower Street LondonWC1E 6BT United Kingdom Kavli Institute for Particle Astrophysics & Cosmology Stanford University P. O. Box 2450 StanfordCA94305 United States SLAC National Accelerator Laboratory Menlo ParkCA94025 United States Madrid Spain Laboratório Interinstitucional de e-Astronomia - LIneA Rua Gal. José Cristino 77 Rio de Janeiro RJ20921-400 Brazil Department of Astronomy University of Illinois at Urbana-Champaign 1002 W. Green Street UrbanaIL61801 United States National Center for Supercomputing Applications 1205 West Clark St. UrbanaIL61801 United States Barcelona Institute of Science and Technology Campus UAB Bellaterra [Barcelona08193 Spain Observatório Nacional Rua Gal. José Cristino 77 Rio de Janeiro RJ20921-400 Brazil Barcelona08034 Spain Campus UAB Carrer de Can Magrans s/n Barcelona08193 Spain Kavli Institute for Cosmological Physics University of Chicago ChicagoIL60637 United States California Institute of Technology 1200 East California Blvd MC 249-17 PasadenaCA91125 United States Department of Physics Stanford University 382 Via Pueblo Mall Sta

We search Dark Energy Survey (DES) Year 3 imaging for galaxy-galaxy strong gravitational lenses using convolutional neural networks, extending previous work with new training sets and covering a wider range of redshifts and colors. We train two neural networks using images of simulated lenses, then use them to score postage stamp images of 7.9 million sources from the Dark Energy Survey chosen to have plausible lens colors based on simulations. We examine 1175 of the highest-scored candidates and identify 152 probable or definite lenses. Examining an additional 20,000 images with lower scores, we identify a further 247 probable or definite candidates. After including 86 candidates discovered in earlier searches using neural networks and 26 candidates discovered through visual inspection of blue-near-red objects in the DES catalog, we present a catalog of 511 lens candidates. Copyright © 2019, The Authors. All rights reserved.

关键词： Surveys

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Human genome meeting 2016 : Houston, TX, USA. 28 February - 2 March 2016

引用

Human genomics 2016年第1期10 Suppl 1卷 12页

作者： A. K. Srivastava Y. Wang R. Huang C. Skinner T. Thompson L. Pollard T. Wood F. Luo R. Stevenson R. Polimanti J. Gelernter X. Lin I. Y. Lim Y. Wu A. L. Teh L. Chen I. M. Aris S. E. Soh M. T. Tint J. L. MacIsaac F. Yap K. Kwek S. M. Saw M. S. Kobor M. J. Meaney K. M. Godfrey Y. S. Chong J. D. Holbrook Y. S. Lee P. D. Gluckman N. Karnani A. Kapoor D. Lee A. Chakravarti C. Maercker F. Graf M. Boutros G. Stamoulis F. Santoni P. Makrythanasis A. Letourneau M. Guipponi N. Panousis M. Garieri P. Ribaux E. Falconnet C. Borel S. E. Antonarakis S. Kumar J. Curran J. Blangero S. Chatterjee J. Akiyama D. Auer C. Berrios L. Pennacchio T. R. Donti G. Cappuccio M. Miller P. Atwal A. Kennedy A. Cardon C. Bacino L. Emrick J. Hertecant F. Baumer B. Porter M. Bainbridge P. Bonnen B. Graham R. Sutton Q. Sun S. Elsea Z. Hu P. Wang Y. Zhu J. Zhao M. Xiong David A. Bennett A. Hidalgo-Miranda S. Romero-Cordoba S. Rodriguez-Cuevas R. Rebollar-Vega E. Tagliabue M. Iorio E. D’Ippolito S. Baroni B. Kaczkowski Y. Tanaka H. Kawaji A. Sandelin R. Andersson M. Itoh T. Lassmann Y. Hayashizaki P. Carninci A. R. R. Forrest C. A. Semple E. A. Rosenthal B. Shirts L. Amendola C. Gallego M. Horike-Pyne A. Burt P. Robertson P. Beyers C. Nefcy D. Veenstra F. Hisama R. Bennett M. Dorschner D. Nickerson J. Smith K. Patterson D. Crosslin R. Nassir N. Zubair T. Harrison U. Peters G. Jarvik F. Menghi K. Inaki X. Woo P. Kumar K. Grzeda A. Malhotra H. Kim D. Ucar P. Shreckengast K. Karuturi J. Keck J. Chuang E. T. Liu B. Ji A. Tyler G. Ananda G. Carter H. Nikbakht M. Montagne M. Zeinieh A. Harutyunyan M. Mcconechy N. Jabado P. Lavigne J. Majewski J. B. Goldstein M. Overman G. Varadhachary R. Shroff R. Wolff M. Javle A. Futreal D. Fogelman L. Bravo W. Fajardo H. Gomez C. Castaneda C. Rolfo J. A. Pinto K. C. Akdemir L. Chin S. Patterson C. Statz S. Mockus S. N. Nikolaev X. I. Bonilla L. Parmentier B. King F. Bezrukov G. Kaya V. Zoete V. Seplyarskiy H. Sharpe T. McKee K. Popadin N. Basset-Seguin R. Ben Chaabene M. Andrianova C. Verdan K. Grosdemange O. Sumara M. E JCSRI Greenwood Genetic Center Greenwood USA School of Computing Clemson University Clemson USA Biochemical Genetics Laboratory Greenwood Genetic Center Greenwood USA Department Psychiatry Yale Sch Med and VA CT Healthcare Center West Haven USA Department Genetics Yale Sch Med and VA CT Healthcare Center West Haven USA Department Neurobiology Yale Sch Med and VA CT Healthcare Center West Haven USA Singapore Institute for Clinical Sciences Singapore Singapore National University of Singapore Singapore Singapore University of British Columbia Vancouver Canada KK Women’s and Children’s Hospital Singapore Singapore University of Southampton and University Hospital Southampton NHS Foundation Trust Southampton UK University of Auckland Auckland New Zealand McKusick-Nathans Institute of Genetic Medicine Johns Hopkins University School of Medicine Baltimore USA Esslingen University of Applied Sciences Esslingen Germany German Cancer Research Center Heidelberg Germany Department of Genetic Medicine and Development University of Geneva Medical School Geneva Switzerland Geneva University Hospitals-HUG Service of Genetic Medicine Geneva Switzerland GE3 Institute of Genetics and Genomics of Geneva University of Geneva Medical School Geneva Switzerland South Texas Diabetes and Obesity Institute School of Medicine University of Texas Rio-Grande Valley Edinburg USA South Texas Diabetes and Obesity Institute School of Medicine University of Texas Rio-Grande Valley Brownsville USA Institute of Genetic Medicine Johns Hopkins University Baltimore USA Genomics Division Lawrence Berkeley National Laboratory Berkeley USA Molecular and Human Genetics Baylor College of Medicine Houston USA Department of Translational Medical Sciences Federico II University Naples Italy Metabolon Inc Durham USA Section of Pediatric Neurology and Neuroscience Baylor College of Medicine Houston USA Tawam Hospital Abu Dhabi United Arab Emirates Stanford Medical School Stanford USA Sch

O1 The metabolomics approach to autism: identification of biomarkers for early detection of autism spectrum disorder A. K. Srivastava, Y. Wang, R. Huang, C. Skinner, T. Thompson, L. Pollard, T. Wood, F. Luo, R. Stevenson O2 Phenome-wide association study for smoking- and drinking-associated genes in 26,394 American women with African, Asian, European, and Hispanic descents R. Polimanti, J. Gelernter O3 Effects of prenatal environment, genotype and DNA methylation on birth weight and subsequent postnatal outcomes: findings from GUSTO, an Asian birth cohort X. Lin, I. Y. Lim, Y. Wu, A. L. Teh, L. Chen, I. M. Aris, S. E. Soh, M. T. Tint, J. L. MacIsaac, F. Yap, K. Kwek, S. M. Saw, M. S. Kobor, M. J. Meaney, K. M. Godfrey, Y. S. Chong, J. D. Holbrook, Y. S. Lee, P. D. Gluckman, N. Karnani, GUSTO study group O4 High-throughput identification of specific qt interval modulating enhancers at the SCN5A locus A. Kapoor, D. Lee, A. Chakravarti O5 Identification of extracellular matrix components inducing cancer cell migration in the supernatant of cultivated mesenchymal stem cells C. Maercker, F. Graf, M. Boutros O6 Single cell allele specific expression (ASE) IN T21 and common trisomies: a novel approach to understand DOWN syndrome and other aneuploidies G. Stamoulis, F. Santoni, P. Makrythanasis, A. Letourneau, M. Guipponi, N. Panousis, M. Garieri, P. Ribaux, E. Falconnet, C. Borel, S. E. Antonarakis O7 Role of microRNA in LCL to IPSC reprogramming S. Kumar, J. Curran, J. Blangero O8 Multiple enhancer variants disrupt gene regulatory network in Hirschsprung disease S. Chatterjee, A. Kapoor, J. Akiyama, D. Auer, C. Berrios, L. Pennacchio, A. Chakravarti O9 Metabolomic profiling for the diagnosis of neurometabolic disorders T. R. Donti, G. Cappuccio, M. Miller, P. Atwal, A. Kennedy, A. Cardon, C. Bacino, L. Emrick, J. Hertecant, F. Baumer, B. Porter, M. Bainbridge, P. Bonnen, B. Graham, R. Sutton, Q. Sun, S. Elsea O10 A novel causal methylation network approach to Alzheimer’s

关键词： Pulmonary Arterial Hypertension Oral Squamous Cell Carcinoma Deep Neural Network Autosomal Recessive Polycystic Kidney Disease Whole Genome Bisulfite Sequencing

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