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arXiv 2021年

作者： Akhazhanov, A. More, A. Amini, A. Hazlett, C. Treu, Tommaso Birrer, S. Shajib, A. Schechter, P. Lemon, C. Nord, B. Aguena, M. Allam, S. Andrade-Oliveira, F. Annis, J. Brooks, D. Buckley-Geer, E. Burke, D.L. Rosell, A. Carnero Kind, M. Carrasco Carretero, J. Choi, A. Conselice, C. Costanzi, M. Da Costa, L.N. Pereira, M.E.S. De Vicente, J. Desai, S. Dietrich, J.P. Doel, P. Everett, S. Ferrero, I. Finley, D.A. Flaugher, B. Frieman, J. García-Bellido, J. Gerdes, D.W. Gruen, D. Gruendl, R.A. Gschwend, J. Gutierrez, G. Hinton, S.R. Hollowood, D.L. Honscheid, K. James, D.J. Kim, A.G. Kuehn, K. Kuropatkin, N. Lahav, O. Lima, M. Lin, H. Maia, M.A.G. March, M. Menanteau, F. Miquel, R. Morgan, R. Palmese, A. Paz-Chinchón, F. Pieres, A. Malagón, A. A. Plazas Sanchez, E. Scarpine, V. Serrano, S. Sevilla-Noarbe, I. Smith, M. Soares-Santos, M. Suchyta, E. Swanson, M.E.C. Tarle, G. To, C. Varga, T.N. Weller, J. Department of Electrical and Computer Engineering University of California Los AngelesCA90095 United States Department of Electrical and Computer Engineering Nazarbayev University Nur-Sultan Kazakhstan Post Bag 4 Ganeshkhind Pune411007 India UTIAS The University of Tokyo Kashiwa Chiba277-8583 Japan Department of Statistics University of California Los AngelesCA90095 United States Department of Political Science University of California Los AngelesCA90095 United States Department of Physics and Astronomy PAB 430 Portola Plaza Box 951547 Los AngelesCA90095-1547 United States Graduate School of Education Stanford University 160 450 Serra Mall StanfordCA94305 United States Department of Astronomy & Astrophysics University of Chicago ChicagoIL60637 United States MIT Kavli Institute for Astrophysics and Space Research 37-664G 77 Massachusetts Avenue CambridgeMA02139 United States Observatoire de Sauverny VersoixCH-1290 Switzerland Fermi National Accelerator Laboratory P. O. Box 500 BataviaIL60510 United States Kavli Institute for Cosmological Physics University of Chicago ChicagoIL60637 United States Laboratório Interinstitucional de e-Astronomia - LIneA Rua Gal. José Cristino 77 RJ Rio de Janeiro20921-400 Brazil Instituto de Física Teórica Universidade Estadual Paulista São Paulo Brazil 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 Center for Astrophysical Surveys National Center for Supercomputing Applications 1205 West Clark St. UrbanaIL61801 United States Department of Astronomy University of Illinois at Urbana-Champaign 1002 W. Green Street UrbanaIL61801 United States The Barcelona Institute of Science and Technology Campus UAB Barcelona08193 Spain Center for Cos

Strongly lensed quadruply imaged quasars (quads) are extraordinary objects. They are very rare in the sky - only a few tens are known to date - and yet they provide unique information about a wide range of topics, including the expansion history and the composition of the Universe, the distribution of stars and dark matter in galaxies, the host galaxies of quasars, and the stellar initial mass function. Finding them in astronomical images is a classic "needle in a haystack" problem, as they are outnumbered by other (contaminant) sources by many orders of magnitude. To solve this problem, we develop state-of-the-art deep learning methods and train them on realistic simulated quads based on real images of galaxies taken from the Dark Energy Survey, with realistic source and deflector models, including the chromatic effects of microlensing. The performance of the best methods on a mixture of simulated and real objects is excellent, yielding area under the receiver operating curve in the range 0.86 to 0.89. Recall is close to 100% down to total magnitude i ∼ 21 indicating high completeness, while precision declines from 85% to 70% in the range i ∼ 17 - 21. The methods are extremely fast: training on 2 million samples takes 20 hours on a GPU machine, and 108 multi-band cutouts can be evaluated per GPU-hour. The speed and performance of the method pave the way to apply it to large samples of astronomical sources, bypassing the need for photometric pre-selection that is likely to be a major cause of incompleteness in current samples of known quads. © 2021, CC BY.

关键词： Galaxies

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Security issues in cloud computing for healthcare

Security issues in cloud computing for healthcare

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International Conference on Computing for Sustainable Global Development (INDIACom)

作者： Repu Daman Manish M. Tripathi Saroj K. Mishra School of Telemedicine & Biomedical Informatics Sanjay Gandhi Post Graduate Institute of Medical Sciences Lucknow UP INDIA Dept. of Computer Science & Engineering Integral University Lucknow UP India

ISBN: (纸本)9781467394178

ICT infrastructure in healthcare domain is improved with the advancement of technology. Health data consist multi-format data as it has text reports, MRI, CT-SCAN images, & pathological slides. Healthcare domain has a large volume of data which is archived as Electronic Health Record (EHR) and it has to be updated frequently. The data of the patients has to be available whenever and wherever necessary in the future course of treatment as patient history. Such a huge archival of data in the hospital needs Skilled manpower, Information and Communication Technology (ICT) and Civil infrastructure and its recurring maintenance cost. Cloud technology thus provides the necessary infrastructure as pay per usage model and when used in healthcare sector lowers the cost of storage, processing and updating infrastructure with minimum cost. Data of patients which are confidential and private in nature can be stored in cloud by selecting appropriate deployment models as different models have different levels of security.

关键词： Handheld computers Decision support systems Conferences

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Performance Analysis of Agent Based Framework

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Procedia computer science 2015年 47卷 37-44页

作者： K. Sindhuja A.V. Monisha S. Padmavathi Post Graduate Student Computer Science and Engineering Thiagarajar College of Engineering Madurai and 625015 India Under Graduate Student Computer Science and Engineering Thiagarajar College of Engineering Madurai and 625015 India Associate Professor Computer Science and Engineering Thiagarajar College of Engineering Madurai and 625015 India

Cloud computing is the delivery of on-demand computing resources – everything from applications to datacenters over the internet on pay per use basis. Service composition in cloud is an important mechanism usually done through several scheduling policies or by dynamic resource allocation techniques. Services delivered to the users lack Quality of Service during this composition phase. Hence, an Agent-based cloud computing paradigm for resource allocation is proposed that consist of designing and developing software agents for cloud service discovery, finding appropriate service and service composition. Here, two types of agents are created – consumer agent that process the user requirements and service provider agent that clusters the output from consumer agent. Finally, each user is mapped to each producer. Experimental results shows efficient execution of user requests using agent with 100% success execution rate in a parallel manner than that of using Hadoop.

关键词： Agent Hadoop Service discovery Service composition Consumer Agent Service Provider Agent

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Implementation Method CUSUM To Determine The Accident Prone Areas in Web Based

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Journal of Physics: Conference Series 2018年第1期1114卷

作者： Rozzi Kesuma Dinata Dahlan Abdullah H Hartono Cut Ita Erliana Berliana Kusuma Riasti Akbar Iskandar Ifit Novita Sari Nurmawati Ricardo Freedom Nanuru Lusi Dwi Putri Rosida Tiurma Manurung S. Sriadhi A A Saleh T Astari Muammar Khaddafi Department of Informatics Universitas Malikussaleh Aceh Indonesia Department of Computer Science STMIK IBBI Medan Indonesia Department of Industrial Engineering Universitas Malikussaleh Aceh Indonesia Department of Informatics Universitas Sebelas Maret Surakarta. Indonesia Department of Informatics STMIK AKBA Makassar Indonesia Departement of: Social Science Education Program Post Graduate Program Universitas Kanjuruhan Malang Malang Indonesia Faculty of industry Technique University of 45 Surabaya Indonesia Universitas Kristen Indonesia Maluku Ambon Indonesia Department of Civil Engineering Universitas Lancang Kuning Pekanbaru Indonesia Graduate Program in Scientific Psychology Universitas Kristen Maranatha Indonesia Department of Electrical Engineering Universitas Negeri Medan Indonesia Statistics Financial & Social Sciences Research Group Indonesia Department of Elementary School Teacher Education STKIP Citra Bangsa Aceh Utara Aceh Indonesia Department of Accounting Universitas Malikussaleh Aceh Indonesia

At the Unit Laka Lantas Polres Lhokseumawe determining accident-prone areas on roads in Lhokseumawe still using manual systems. Determination of accident-prone areas are less effective because the police Unit Laka Lantas Polres Lhokseumawe just using the data of the last year and had to repeatedly calculate manually accident-prone areas based on the number of human casualties. In this study the system implementation CUSUM method (Cummulative Summary) to determine the accident-prone areas designed using the web-based programming language PHP. In this system there are three processes to determine areas prone to accidents, the accident rate calculations based on the weighted severity, blacksite calculations using the Z-Score method for determining areas prone to accident blackspots and calculations using the CUSUM method to determine the critical points of an accident. The data used are secondary data obtained from the Police Unit Laka Lantas Polres Lhokseumawe years 2009-2013.

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Retraction: Implementation Method CUSUM To Determine The Accident Prone Areas in Web Based (J. Phys.: Conf. Ser. 1114 012093)

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Journal of Physics: Conference Series 2018年第1期1114卷

This paper was retracted by IOP Publishing on 12 December 2018. This paper was published due to a technical error and was not intended to be included in this journal. Retraction published: 8 February 2019

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The optical band gap of LiTaO3 and Nb2O5-doped LiTaO3 thin films based on Tauc Plot method to be applied on satellite

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IOP Conference Series: Earth and Environmental science 2017年第1期54卷

作者： R Estrada N Djohan D Pasole M Dahrul A Kurniawan J Iskandar H Hardhienata Irzaman Department of Electrical Engineering Faculty of Engineering and Computer Science Krida Wacana Christian University Jl. Tj. Duren Raya No. 4 Jakarta 11470 Indonesia. Student of Electrical Engineering Faculty of Engineering and Computer Science Krida Wacana Christian University Jl. Tj. Duren Raya No. 4 Jakarta 11470 Indonesia. Post Graduate of Biophysics Faculty of Mathematics and Natural Sciences Bogor Agricultural University Jl. Raya Dramaga Bogor 16680 Indonesia. Department of Physics Faculty of Mathematics and Natural Sciences Bogor Agricultural University Jl. Raya Dramaga Bogor 16680 Indonesia.

This research observed the optical band gap of thin films made from LiTaO3 undoped (0%) and doped (5% and 10%) with Nb2O5 in the 1 M-solubility deposited on n-type Si (111) substrates. The thin films are manufactured with coating process of substrates by Chemical Solution Deposition (CSD) method using a spin coater device at a rotation speed of 3000 rpm for 30 seconds and annealed in furnace (Nabertherm B180) at a temperature of 850°C for 15 hours. The optical absorption data of thin films are obtained by using an Ocean Optics USB2000 device in the wavelength of visible light. The band gap curve is determined from optical absorption data processing using Tauc Plot method. The Tauc Plot with indirect transition shows that LiTaO3 doped with Nb2O5 provides increased optical band gap value in a range less than 3.5 eV. Based on the results of this research, it can be concluded that LiTaO3 and Nb2O5-doped LiTaO3 thin films on n-type Si (111) substrate are semiconductor materials and has the potential to be applied on satellite.

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The effect of annealing temperature variation on the optical properties test of LiTaO3 thin films based on Tauc Plot method for satellite technology

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IOP Conference Series: Earth and Environmental science 2017年第1期54卷

作者： N Djohan R Estrada D Sari M Dahrul A Kurniawan J Iskandar H Hardhienata Irzaman Department of Electrical Engineering Faculty of Engineering and Computer Science Krida Wacana Christian University Jl. Tj. Duren Raya No. 4 Jakarta 11470 Indonesia. Student of Electrical Engineering Faculty of Engineering and Computer Science Krida Wacana Christian University Jl. Tj. Duren Raya No. 4 Jakarta 11470 Indonesia. Post Graduate of Biophysics Faculty of Mathematics and Natural Sciences Bogor Agricultural University Jl. Raya Dramaga Bogor 16680 Indonesia. Department of Physics Faculty of Mathematics and Natural Sciences Bogor Agricultural University Jl. Raya Dramaga Bogor 16680 Indonesia.

The purpose of the present research is to observe the energy gap of thin films made from LiTaO3 in 1 M-solubility deposited on n-type Si (111) substrates with annealing temperature variation. The manufacture of thin films has been formed by Chemical Solution Deposition (CSD) method using spin coater on 3000 rpm speed for 30 seconds and performed annealing process using furnace (Nabertherm type B180) at a temperature of 750°C, 800°C and 850°C for 15 hours. The absorbance of thin films is measured by using an Ocean Optics USB2000 device and processed into the energy gap curve using Tauc Plot method. The result shows that the energy gap of thin films associated with indirect transitions are increased from 2.78 eV to 2.93 eV with the rise of annealing temperature. The research shows that the thin films on n-type Si (111) substrates made of LiTaO3 produces sensitivity to violet light spectrum and have the potential to be developed as a sensor on satellite technology.

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Estimates, trends, and drivers of the global burden of type 2 diabetes attributable to PM_2·5 air pollution, 1990–2019: an analysis of data from the Global Burden of Disease Study 2019

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The Lancet Planetary Health 2022年第7期6卷 e586-e600页

作者： Burkart, Katrin Causey, Kate Cohen, Aaron J Wozniak, Sarah S Salvi, Devashri Digvijay Abbafati, Cristiana Adekanmbi, Victor Adsuar, Jose C Ahmadi, Keivan Alahdab, Fares Al-Aly, Ziyad Alipour, Vahid Alvis-Guzman, Nelson Amegah, Adeladza Kofi Andrei, Catalina Liliana Andrei, Tudorel Ansari, Fereshteh Arabloo, Jalal Aremu, Olatunde Aripov, Timur Babaee, Ebrahim Banach, MacIej Barnett, Anthony Bärnighausen, Till Winfried Bedi, Neeraj Behzadifar, Masoud Béjot, Yannick Bennett, Derrick A Bensenor, Isabela M Bernstein, Robert S Bhattacharyya, Krittika Bijani, Ali Biondi, Antonio Bohlouli, Somayeh Breitner, Susanne Brenner, Hermann Butt, Zahid A Cámera, Luis Alberto Cantu-Brito, Carlos Carvalho, Felix Cerin, Ester Chattu, Vijay Kumar Chauhan, Bal Govind Choi, Jee-Young Jasmine Chu, Dinh-Toi Dai, Xiaochen Dandona, Lalit Dandona, Rakhi Daryani, Ahmad Davletov, Kairat De Courten, Barbora Demeke, Feleke Mekonnen Denova-Gutiérrez, Edgar Dharmaratne, Samath Dhamminda Dhimal, Meghnath Diaz, Daniel Djalalinia, Shirin Duncan, Bruce B El Sayed Zaki, Maysaa Eskandarieh, Sharareh Fareed, Mohammad Farzadfar, Farshad Fattahi, Nazir Fazlzadeh, Mehdi Fernandes, Eduarda Filip, Irina Fischer, Florian Foigt, Nataliya A Freitas, Marisa Ghashghaee, Ahmad Gill, Paramjit Singh Ginawi, Ibrahim Abdelmageed Gopalani, Sameer Vali Guo, Yuming Gupta, Rajat Das Habtewold, Tesfa Dejenie Hamadeh, Randah R Hamidi, Samer Hankey, Graeme J Hasanpoor, Edris Hassen, Hamid Yimam Hay, Simon I Heibati, Behzad Hole, Michael K Hossain, Naznin Househ, Mowafa Irvani, Seyed Sina Naghibi Jaafari, Jalil Jakovljevic, Mihajlo Jha, Ravi Prakash Jonas, Jost B Jozwiak, Jacek Jerzy Kasaeian, Amir Kaydi, Neda Khader, Yousef Saleh Khafaie, Morteza Abdullatif Khan, Ejaz Ahmad Khan, Junaid Khan, Md Nuruzzaman Khatab, Khaled Khater, Amir M Kim, Yun Jin Kimokoti, Ruth W Kisa, Adnan Kivimäki, Mika Knibbs, Luke D Kosen, Soewarta Koul, Parvaiz A Koyanagi, Ai Defo, Barthelemy Kuate Kugbey, Nuworza Lauriola, Paolo Lee, Paul H Leili, Mostafa Lewycka, Sonia Li, Shanshan Lim, Lee-Ling Li Institute for Health Metrics and Evaluation University of Washington Seattle WA United States Department of Health Metrics Sciences School of Medicine University of Washington Seattle WA United States Division of Plastic and Reconstructive Surgery University of Washington Seattle WA United States Research Insights and Innovation Seattle WA United States Health Effects Institute Boston MA United States School of Public Health Boston University Boston MA United States Department of Juridical and Economic Studies La Sapienza University Rome Italy Department of Population Medicine Cardiff University Cardiff United Kingdom Sport Science Department University of Extremadura Badajoz Spain School of Public Health Imperial College London London United Kingdom Department of Primary Care and Public Health Imperial College London London United Kingdom Mayo Evidence-based Practice Center Mayo Clinic Foundation for Medical Education and Research Rochester MN United States John T. Milliken Department of Internal Medicine Washington University in St. Louis St. Louis MO United States Clinical Epidemiology Center US Department of Veterans Affairs (VA) St Louis MO United States Health Management and Economics Research Center Iran University of Medical Sciences Tehran Iran Department of Health Economics Iran University of Medical Sciences Tehran Iran Preventive Medicine and Public Health Research Center Iran University of Medical Sciences Tehran Iran Pars Advanced and Minimally Invasive Medical Manners Research Center Iran University of Medical Sciences Tehran Iran Department of Community and Family Medicine Iran University of Medical Sciences Tehran Iran Research Group in Hospital Management and Health Policies Universidad de la Costa (University of the Coast) Barranquilla Colombia Research Group in Health Economics University of Cartagena Cartagena Colombia Department of Biomedical Science University of Cape Coast Cape Coast Ghana Cardiology Department Ca

Background: Experimental and epidemiological studies indicate an association between exposure to particulate matter (PM) air pollution and increased risk of type 2 diabetes. In view of the high and increasing prevalence of diabetes, we aimed to quantify the burden of type 2 diabetes attributable to PM_2·5 originating from ambient and household air pollution. Methods: We systematically compiled all relevant cohort and case-control studies assessing the effect of exposure to household and ambient fine particulate matter (PM_2·5) air pollution on type 2 diabetes incidence and mortality. We derived an exposure–response curve from the extracted relative risk estimates using the MR-BRT (meta-regression—Bayesian, regularised, trimmed) tool. The estimated curve was linked to ambient and household PM_2·5 exposures from the Global Burden of Diseases, Injuries, and Risk Factors Study 2019, and estimates of the attributable burden (population attributable fractions and rates per 100 000 population of deaths and disability-adjusted life-years) for 204 countries from 1990 to 2019 were calculated. We also assessed the role of changes in exposure, population size, age, and type 2 diabetes incidence in the observed trend in PM_2·5-attributable type 2 diabetes burden. All estimates are presented with 95% uncertainty intervals. Findings: In 2019, approximately a fifth of the global burden of type 2 diabetes was attributable to PM_2·5 exposure, with an estimated 3·78 (95% uncertainty interval 2·68–4·83) deaths per 100 000 population and 167 (117–223) disability-adjusted life-years (DALYs) per 100 000 population. Approximately 13·4% (9·49–17·5) of deaths and 13·6% (9·73–17·9) of DALYs due to type 2 diabetes were contributed by ambient PM2·5, and 6·50% (4·22–9·53) of deaths and 5·92% (3·81–8·64) of DALYs by household air pollution. High burdens, in terms of numbers as well as rates, were estimated in Asia, sub-Saharan Africa, and South Am

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Cloud Computing – A Unified Approach for Surveillance Issues

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IOP Conference Series: Materials science and engineering 2017年第1期225卷

作者： C R Rachana Dr. Reshma Banu Dr. G F Ali Ahammed Dr. B D Parameshachari Associate Professor & Head DoS in Computer Science Pooja Bhagavat Memorial Mahajana Education Centre K.R.S. Road Metagalli Mysuru-16. Professor & Head Department of I S E GSSSIETW Mysore Karnataka India. Associate Professor Department of Computer Science Engineering VTU Post Graduate Centre Mysuru. Professor & Head TCE Dept. GSSSIETW Mysore Karnataka India.

Cloud computing describes highly scalable resources provided as an external service via the Internet on a basis of pay-per-use. From the economic point of view, the main attractiveness of cloud computing is that users only use what they need, and only pay for what they actually use. Resources are available for access from the cloud at any time, and from any location through networks. Cloud computing is gradually replacing the traditional Information Technology Infrastructure. Securing data is one of the leading concerns and biggest issue for cloud computing. Privacy of information is always a crucial pointespecially when an individual's personalinformation or sensitive information is beingstored in the organization. It is indeed true that today; cloud authorization systems are notrobust enough. This paper presents a unified approach for analyzing the various security issues and techniques to overcome the challenges in the cloud environment.

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A comparative analysis of R Tree and R+ Tree based image segmentation and reconstruction

A comparative analysis of R Tree and R+ Tree based image seg...

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International Conference on Computing for Sustainable Global Development (INDIACom)

作者： Priyasmita Chatterjee Rajesh Siddavatam Pradeep Kandula Debolina Ghosh Rishabh Roy Graduate Student Computer Science Engineering KIIT University Bhubaneswar INDIA Dean and Professor Department of Computer Science KIIT University Bhubaneswar INDIA Professor Computer Science Engineering KIIT University Bhubaneswar INDIA Under Graduate Student Computer Science Engineering KIIT University Bhubaneswar INDIA

ISBN: (纸本)9781479968329

In this paper we represent a comparative analysis of R-Tree and R+ Tree based image segmentation & reconstruction. Here this algorithm is to select the significant pixel[4] is used to select the physically powerful edges. These are store in R tree and R+ tree for better image reconstruction. The bounding boxes are created by these edges using edge detection technique and the pixels of image sets are encapsulated in the bounding box. By Delaunay triangulation image reconstruction is done.

关键词： Erbium Hafnium

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