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32nd International Conference on Computers and Their Applications, CATA 2017

作者： Dos Lima, Aline F. Costa, Thiago S.A. Oliveira, Sandro R.B. Melo, Pamella B. Rodrigues, Juan P. P. Graduate Program in Computer Science Federal University of Pará Belém Pará Brazil Graduate Program in Information Technology Management Ideal College - Devry Belém Pará Brazil

ISBN: (纸本)9781943436064

The importance of adopting the evolutionary maintenance is becoming increasingly long life of a software without it losing its quality and its functionalities, however performing evolutionary maintenance of legacy systems is not always an easy task, considering that these systems often have incomplete and inconsistent documentation or even that was lost over time. We want to understand what software process assets can help in the implementation of requirements development practices in evolutionary maintenance in adherence to CMMI-DEV model, how these assets can be used by requirements team and how this team evaluate this application. This paper aims to present an implementation approach of the RD (Requirements Development) process area of CMMI-DEV (Capability Maturity Model Integration for Development) in the Brazilian company, called Vibe Desenvolvimento, for evolutionary maintenance projects with data collection from reverse engineering, and perform the adherence analysis of the model implemented in relation to the process area studied, through the application of questionnaires to Requirements Analyst team of this company, and the analysis of the work products generated in each specific practice of RD process area. © ISCA, CATA 2017.

关键词： Legacy systems

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Retraction notice to "A deep learning approach based on graphs to detect plantation lines" [Heliyon Volume 10, Issue 11, 15 June 2024, e31730]

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Heliyon 2024年第23期10卷 e40689页

作者： Diogo Nunes Gonçalves José Marcato Junior Mauro Dos Santos de Arruda Vanessa Jordão Marcato Fernandes Ana Paula Marques Ramos Danielle Elis Garcia Furuya Lucas Prado Osco Hongjie He Lucio André de Castro Jorge Jonathan Li Farid Melgani Hemerson Pistori Wesley Nunes Gonçalves Faculty of Computer Science Federal University of Mato Grosso do Sul Av. Costa e Silva Campo Grande 79070-900 MS Brazil. Faculty of Engineering Architecture and Urbanism and Geography Federal University of Mato Grosso do Sul Av. Costa e Silva Campo Grande 79070-900 MS Brazil. Faculty of Agricultural Sciences Federal University of Grande Dourados Av. Costa e Silva Dourados 79070-900 MS Brazil. Faculty of Science and Technology São Paulo State University (UNESP) R. Roberto Simonsen 305 Presidente Prudente 19060-900 SP Brazil. Program of Environment and Regional Developement University of Western São Paulo Raposo Tavares km 572 Presidente Prudente 19067-175 SP Brazil. Department of Geography and Environmental Management University of Waterloo Waterloo ON N2L 3G1 Canada. National Research Center of Development of Agricultural Instrumentation Brazilian Agricultural Research Agency (EMBRAPA) 13560-970 R. XV de Novembro 1452 São Carlos SP Brazil. Department of Information Engineering and Computer Science University of Trento Trento 38122 Italy. INOVISAO Dom Bosco Catholic University Avenida Tamandaré 6000 Campo Grande 79117-900 MS Brazil.

[This retracts the article DOI: 10.1016/***.2024.e31730.].

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A deep learning approach based on graphs to detect plantation lines

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Heliyon 2024年第11期10卷 e31730页

Identifying plantation lines in aerial images of agricultural landscapes is re-quired for many automatic farming processes. Deep learning-based networks are among the most prominent methods to learn such patterns and extract this type of information from diverse imagery conditions. However, even state-of-the-art methods may stumble in complex plantation patterns. Here, we propose a deep learning approach based on graphs to detect plantation lines in UAV-based RGB imagery, presenting a challenging scenario containing spaced plants. The first module of our method extracts a feature map throughout the backbone, which consists of the initial layers of the VGG16. This feature map is used as an input to the Knowledge Estimation Module (KEM), organized in three concatenated branches for detecting 1) the plant positions, 2) the plantation lines, and 3) the displacement vectors between the plants. A graph modeling is applied considering each plant position on the image as vertices, and edges are formed between two vertices (i.e. plants). Finally, the edge is classified as pertaining to a certain plantation line based on three probabilities (higher than 0.5): i) in visual features obtained from the backbone; ii) a chance that the edge pixels belong to a line, from the KEM step; and iii) an alignment of the displacement vectors with the edge, also from the KEM step. Experiments were conducted initially in corn plantations with different growth stages and patterns with aerial RGB imagery to present the advantages of adopting each module. We assessed the generalization capability in the other two cultures (orange and eucalyptus) datasets. The proposed method was compared against state-of-the-art deep learning methods and achieved superior performance with a significant margin considering all three datasets. This approach is useful in extracting lines with spaced plantation patterns and could be implemented in scenarios where plantation gaps occur, generating lines with few-to-no

关键词： Aerial imagery Convolutional neural networks Object detection Remote sensing UAV

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Population of Merging Compact Binaries Inferred Using Gravitational Waves through GWTC-3

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Physical Review X 2023年第1期13卷 011048-011048页

作者： R. Abbott T. D. Abbott F. Acernese K. Ackley C. Adams N. Adhikari R. X. Adhikari V. B. Adya C. Affeldt D. Agarwal M. Agathos K. Agatsuma N. Aggarwal O. D. Aguiar L. Aiello A. Ain P. Ajith T. Akutsu P. F. de Alarcón S. Akcay S. Albanesi A. Allocca P. A. Altin A. Amato C. Anand S. Anand A. Ananyeva S. B. Anderson W. G. Anderson M. Ando T. Andrade N. Andres T. Andrić S. V. Angelova S. Ansoldi J. M. Antelis S. Antier F. Antonini S. Appert Koji Arai Koya Arai Y. Arai S. Araki A. Araya M. C. Araya J. S. Areeda M. Arène N. Aritomi N. Arnaud M. Arogeti S. M. Aronson K. G. Arun H. Asada Y. Asali G. Ashton Y. Aso M. Assiduo S. M. Aston P. Astone F. Aubin C. Austin S. Babak F. Badaracco M. K. M. Bader C. Badger S. Bae Y. Bae A. M. Baer S. Bagnasco Y. Bai L. Baiotti J. Baird R. Bajpai M. Ball G. Ballardin S. W. Ballmer A. Balsamo G. Baltus S. Banagiri D. Bankar J. C. Barayoga C. Barbieri B. C. Barish D. Barker P. Barneo F. Barone B. Barr L. Barsotti M. Barsuglia D. Barta J. Bartlett M. A. Barton I. Bartos R. Bassiri A. Basti M. Bawaj J. C. Bayley A. C. Baylor M. Bazzan B. Bécsy V. M. Bedakihale M. Bejger I. Belahcene V. Benedetto D. Beniwal T. F. Bennett J. D. Bentley M. BenYaala F. Bergamin B. K. Berger S. Bernuzzi C. P. L. Berry D. Bersanetti A. Bertolini J. Betzwieser D. Beveridge R. Bhandare U. Bhardwaj D. Bhattacharjee S. Bhaumik I. A. Bilenko G. Billingsley S. Bini R. Birney O. Birnholtz S. Biscans M. Bischi S. Biscoveanu A. Bisht B. Biswas M. Bitossi M.-A. Bizouard J. K. Blackburn C. D. Blair D. G. Blair R. M. Blair F. Bobba N. Bode M. Boer G. Bogaert M. Boldrini L. D. Bonavena F. Bondu E. Bonilla R. Bonnand P. Booker B. A. Boom R. Bork V. Boschi N. Bose S. Bose V. Bossilkov V. Boudart Y. Bouffanais A. Bozzi C. Bradaschia P. R. Brady A. Bramley A. Branch M. Branchesi J. Brandt J. E. Brau M. Breschi T. Briant J. H. Briggs A. Brillet M. Brinkmann P. Brockill A. F. Brooks J. Brooks D. D. Brown S. Brunett G. Bruno R. Bruntz J. Bryant T. Bulik H. J. Bulten A. Buonanno R. Buscicchio D. Buskulic C. Buy R. L. Byer L. Cadonati LIGO Laboratory California Institute of Technology Pasadena California 91125 USA Louisiana State University Baton Rouge Louisiana 70803 USA Dipartimento di Farmacia Università di Salerno I-84084 Fisciano Salerno Italy INFN Sezione di Napoli Complesso Universitario di Monte S. Angelo I-80126 Napoli Italy OzGrav School of Physics & Astronomy Monash University Clayton 3800 Victoria Australia LIGO Livingston Observatory Livingston Louisiana 70754 USA University of Wisconsin-Milwaukee Milwaukee Wisconsin 53201 USA OzGrav Australian National University Canberra Australian Capital Territory 0200 Australia Max Planck Institute for Gravitational Physics (Albert Einstein Institute) D-30167 Hannover Germany Leibniz Universität Hannover D-30167 Hannover Germany Inter-University Centre for Astronomy and Astrophysics Pune 411007 India University of Cambridge Cambridge CB2 1TN United Kingdom Theoretisch-Physikalisches Institut Friedrich-Schiller-Universität Jena D-07743 Jena Germany University of Birmingham Birmingham B15 2TT United Kingdom Center for Interdisciplinary Exploration & Research in Astrophysics (CIERA) Northwestern University Evanston Illinois 60208 USA Instituto Nacional de Pesquisas Espaciais 12227-010 São José dos Campos São Paulo Brazil Gravity Exploration Institute Cardiff University Cardiff CF24 3AA United Kingdom INFN Sezione di Pisa I-56127 Pisa Italy International Centre for Theoretical Sciences Tata Institute of Fundamental Research Bengaluru 560089 India Gravitational Wave Science Project National Astronomical Observatory of Japan (NAOJ) Mitaka City Tokyo 181-8588 Japan Advanced Technology Center National Astronomical Observatory of Japan (NAOJ) Mitaka City Tokyo 181-8588 Japan Universitat de les Illes Balears IAC3–IEEC E-07122 Palma de Mallorca Spain University College Dublin Dublin 4 Ireland INFN Sezione di Torino I-10125 Torino Italy Università di Napoli “Federico II” Complesso Universitario di Monte S. Angelo I-80126 Napoli

We report on the population properties of compact binary mergers inferred from gravitational-wave observations of these systems during the first three LIGO-Virgo observing runs. The Gravitational-Wave Transient Catalog 3 (GWTC-3) contains signals consistent with three classes of binary mergers: binary black hole, binary neutron star, and neutron star–black hole mergers. We infer the binary neutron star merger rate to be between 10 and 1700 Gpc−3 yr−1 and the neutron star–black hole merger rate to be between 7.8 and 140 Gpc−3 yr−1, assuming a constant rate density in the comoving frame and taking the union of 90% credible intervals for methods used in this work. We infer the binary black hole merger rate, allowing for evolution with redshift, to be between 17.9 and 44 Gpc−3 yr−1 at a fiducial redshift (z=0.2). The rate of binary black hole mergers is observed to increase with redshift at a rate proportional to (1+z)κ with κ=2.9−1.8+1.7 for z≲1. Using both binary neutron star and neutron star–black hole binaries, we obtain a broad, relatively flat neutron star mass distribution extending from 1.2−0.2+0.1 to 2.0−0.3+0.3M⊙. We confidently determine that the merger rate as a function of mass sharply declines after the expected maximum neutron star mass, but cannot yet confirm or rule out the existence of a lower mass gap between neutron stars and black holes. We also find the binary black hole mass distribution has localized over- and underdensities relative to a power-law distribution, with peaks emerging at chirp masses of 8.3−0.5+0.3 and 27.9−1.8+1.9M⊙. While we continue to find that the mass distribution of a binary’s more massive component strongly decreases as a function of primary mass, we observe no evidence of a strongly suppressed merger rate above approximately 60M⊙, which would indicate the presence of a upper mass gap. Observed black hole spins are small, with half of spin magnitudes below χi≈0.25. While the majority of spins are preferentially aligned wi

关键词： Gravitational wave sources Gravitational waves Gravitational wave detection

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Designing the Application of Security Text Messages into Audio Files Using Data Encryption Standard (DES) Algorithms Using the End of File (EOF) Method 1

Designing the Application of Security Text Messages into Aud...

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1st Workshop on Environmental science, Society, and technology, WESTECH 2018

作者： Pardede, A.M.H. Pramana, Anggi Zarlis, Muhammad Iskandar, Akbar Manurung, Rosida Tiurma Sriadhi, S. Kurniawan, Citra Hasibuan, Abdurrozzaq Siregar, Nurintan Asyiah Sari, Ayu Esteka Mulyaningsih, Indrya Iskandar Alam, Teguh Hidayat Ibrahim Listyorini, Tri Winarno, Edy Tulus STMIK Kaputama Binjai Sumatera Utara Indonesia Department of Computer Science Universitas Sumatera Utara Medan Indonesia Department of Informatics STMIK AKBA Makassar Indonesia Graduate Program in Scientific Psychology Universitas Kristen Maranatha Indonesia Department of Electrical Engineering Universitas Negeri Medan Indonesia Department of Electrical Engineering Sekolah Tinggi Teknik Malang Indonesia Faculty of Engineering Universitas Islam Sumatera Utara Medan Indonesia Department of Management STIE Labuhanbatu Sumatera Utara Indonesia Department of Management STIE Sakti Alam Kerinci Jambi Indonesia Department of Indonesian Language Teaching Institut Agama Islam Negeri Syekh Nurjati Cirebon Indonesia Department of Informatics Engineering Universitas Muhammadiyah Sorong Sorong Indonesia Department of English Education Universitas Muhammadiyah Sorong Sorong Indonesia Department of Informatics Universitas Muria Kudus Indonesia Faculty of Information Technology Universitas Stikubank Semarang Indonesia Department of Mathematics Universitas Sumatera Utara Medan Indonesia

There are several ways to deal with security issues of confidential data sent via the internet, including using cryptographic techniques and steganography. Steganography is the science and art of concealing information / messages in a media in such a way that its existence is not detected by other parties who are not entitled to the information. Instead, cryptography disguises the meaning of a message, but does not hide that there is a message because the file looks suspicious. The Steganography technique used here was End Of File (EOF). The EOF technique described how to add data or files at the end of the image file. For this technique, the size of data or files that will be hidden could be larger than the size of the image file. The hidden data will be inserted at the end of the file so that it will not affect the image. This steganography application is also equipped with a cryptographic function Data Encryption Standard (DES) at the time of insertion of data that functions as a generator code and encrypts data, so that the security of a data in the file is more protected and protected from those who are not entitled to know the data. © Published under licence by IOP Publishing Ltd.

关键词： Steganography

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Classifying Attitudes of Thai Business Organizations Toward the Perceived Benefit of Customer Predictive Analytics

Classifying Attitudes of Thai Business Organizations Toward ...

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International Symposium on Soft Computing and Intelligent Systems (SCIS)

作者： Santisook Limpeeticharoenchot Nagul Cooharojananone Thira Chavarnakul Kanokwan Atchariyachanvanich Technopreneurship and Innovation Management Program Graduate School Chulalongkorn University Bangkok Thailand Department of Mathematics and Computer Science Faculty of Science Chulalongkorn University Bangkok Thailand Department of Commerce Chulalongkorn University Bangkok Thailand Faculty of Information Technology King Mongkut’s Institute of Technology Ladkrabang Bangkok Thailand

ISBN: (纸本)9781538626344;9781538626337

In this paper, we applied K-means++, Agglomerative and Decision Tree techniques to classify characteristics of Thai business organizations toward the perceived benefit of predictive analytics. We believe that different characteristics of business organizations require different solution approaches to overcome challenges and gain business value. In the exploratory survey, we collected 84 respondents, who are data analysts, business analysts, business owners, management, and IT managers. The respondents' size of organization varies from small firms to large firms. The result from three techniques of classification shows that Thai business organizations perceiving the benefit of predictive analytics could be divided into two groups. We further confirmed that with the analysis of variance technique to identify the difference of means in each parameter. We also found that the most important descriptive profile is led by customer-related factors such as a change in the percentage of customers, the number of direct customers, and number of sales and marketing staff. These are followed by technology factors, which are the number of external and internal data sources and number of analytics and technologies currently used for data analytics.

关键词： Organizations Data analysis Clustering algorithms Big Data Organizational aspects Decision trees

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BTEX exposure and its body burden pose differential risks for asthma and its phenotypic clusters

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Allergy 2023年第7期78卷 2036-2040页

作者： Yuan-Ting Hsu Chao-Chien Wu Chin-Chou Wang Wen-Yu Chung Chau-Chyun Sheu Yi-Hsin Yang Ming-Yen Cheng Ruay-Sheng Lai Sum-Yee Leung Chi-Cheng Lin Yu-Feng Wei Ching-Hsiung Lin Sheng-Hao Lin Jeng-Yuan Hsu Wei-Chang Huang Chia-Cheng Tseng Yung-Fa Lai Meng-Hsuan Cheng Huang-Chi Chen Chih-Jen Yang Chian-Heng Su Chien-Jen Wang Shih-Chang Hsu Chih-Hsing Hung Chon-Lin Lee Ming-Shyan Huang Shau-Ku Huang National Institute of Environmental Health Sciences National Health Research Institutes Miaoli Taiwan. Department of Internal Medicine Division of Pulmonary and Critical Care Medicine Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine Kaohsiung Taiwan. Department of Public Health Kaohsiung Medical University Kaohsiung Taiwan. Department of Computer Science and Information Engineering National Kaohsiung University of Science and Technology Kaohsiung Taiwan. Department of Internal Medicine Division of Pulmonary and Critical Care Medicine Kaohsiung Medical University Hospital Kaohsiung Medical University Kaohsiung Taiwan. Department of Internal Medicine School of Medicine College of Medicine Kaohsiung Medical University Kaohsiung Taiwan. National Institute of Cancer Research National Health Research Institutes Tainan Taiwan. Department of Mathematics Hong Kong Baptist University Hong Kong China. Division of Chest Medicine Kaohsiung Veterans General Hospital Kaohsiung Taiwan. Department of Internal Medicine Chest Division Antai Medical Care Cooperation Antai Tian-Sheng Memorial Hospital Pingtung Taiwan. Department of Internal Medicine E-Da Cancer Hospital I-Shou University Kaohsiung Taiwan. Department of Internal Medicine Division of Chest Medicine Changhua Christian Hospital Changhua Taiwan. Institute of Genomics and Bioinformatics National Chung Hsing University Taichung Taiwan. Department of Recreation and Holistic Wellness MingDao University Changhua Taiwan. Department of Medical Research Division of Clinical Research Taichung Veterans General Hospital Taichung Taiwan. Department of Internal Medicine Division of Chest Medicine Taichung Veterans General Hospital Taichung Taiwan. Department of Medical Technology Jen-Teh Junior College of Medicine Nursing and Management Miaoli Taiwan. School of Medicine Chung Shan Medical University Taichung Taiwan. Ph.D. Program in Translational Medicine National Chung Hsing Universi

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European first-year university students accept evolution but lack substantial knowledge about it: a standardized European cross-country assessment

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Evolution: Education and Outreach 2021年第1期14卷 1-22页

作者： Kuschmierz, Paul Beniermann, Anna Bergmann, Alexander Pinxten, Rianne Aivelo, Tuomas Berniak-Woźny, Justyna Bohlin, Gustav Bugallo-Rodriguez, Anxela Cardia, Pedro Cavadas, Bento Filipe Barreiras Pinto Cebesoy, Umran Betul Cvetković, Dragana D. Demarsy, Emilie Đorđević, Mirko S. Drobniak, Szymon M. Dubchak, Liudmyla Dvořáková, Radka M. Fančovičová, Jana Fortin, Corinne Futo, Momir Geamănă, Nicoleta Adriana Gericke, Niklas Grasso, Donato A. Lendvai, Ádám Z. Mavrikaki, Evangelia Meneganzin, Andra Mogias, Athanasios Möller, Andrea Mota, Paulo G. Naciri, Yamama Németh, Zoltán Ożańska-Ponikwia, Katarzyna Paolucci, Silvia Pap, Péter László Petersson, Maria Pietrzak, Barbara Pievani, Telmo Pobric, Alma Porozovs, Juris Realdon, Giulia Sá-Pinto, Xana Savković, Uroš B. Sicard, Mathieu Sofonea, Mircea T. Sorgo, Andrej Stermin, Alexandru N. Tăușan, Ioan Torkar, Gregor Türkmen, Lütfullah Tutnjević, Slavica Uitto, Anna E. Varga, Mirna Vazquez-Ben, Lucia Venetis, Constantinos Viguera, Enrique Virtbauer, Lisa Christine Vutsova, Albena Yruela, Inmaculada Zandveld, Jelle Graf, Dittmar Institute for Didactics of Biology Justus-Liebig-University Giessen Giessen Germany Institute for Biology Teaching and Learning Research in Biology Education Humboldt-Universität Zu Berlin Berlin Germany Faculty of Life Science Department of Biology University of Leipzig Leipzig Germany Didactica Research Unit Faculty of Social Sciences & Behavioural Ecology & Ecophysiology Group Department of Biology University of Antwerp Antwerp Belgium Organismal and Evolutionary Biology Research Program University of Helsinki Helsinki Finland University of Information Technology and Management in Rzeszów Rzeszów Poland Public & Science (VA) Stockholm Sweden Department of Pedagogy and Didactics University of A Coruña A Coruña Spain Escola Superior de Educação Politécnico do Porto Porto Portugal Department of Science and Mathematics Polytechnic Institute of Santarém/School of Education Santarém Portugal Faculty of Education/Department of Mathematics and Science Education Usak University Uşak Turkey Chair of Genetics and Evolution Faculty of Biology University of Belgrade Belgrade Serbia Department of Botany and Plant Biology University of Geneva Geneva Switzerland Department of Evolutionary Biology Institute for Biological Research “Siniša Stanković” - National Institute of Republic of Serbia University of Belgrade Belgrade Serbia Institute of Environmental Sciences Jagiellonian University Kraków Poland Department of Parliamentarism and Political Management National Academy for Public Administration Under the President of Ukraine Kyiv Ukraine Department of Teaching and Didactics of Biology Charles University Praha Czech Republic Department of Biology Faculty of Education Trnava University Trnava Slovakia Laboratory of Didactic André Revuz University of Paris Paris France Institut Ruđer Bošković/Division of Molecular Biology Zagreb Croatia Department/Research Center in Systems Ecology and Sustainability University of Bucharest Bucharest Romania Department of Envir

Background: Investigations of evolution knowledge and acceptance and their relation are central to evolution education research. Ambiguous results in this field of study demonstrate a variety of measuring issues, for instance differently theorized constructs, or a lack of standardized methods, especially for cross-country comparisons. In particular, meaningful comparisons across European countries, with their varying cultural backgrounds and education systems, are rare, often include only few countries, and lack standardization. To address these deficits, we conducted a standardized European survey, on 9200 first-year university students in 26 European countries utilizing a validated, comprehensive questionnaire, the “Evolution Education Questionnaire”, to assess evolution acceptance and knowledge, as well as influencing factors on evolution acceptance. Results: We found that, despite European countries’ different cultural backgrounds and education systems, European first-year university students generally accept evolution. At the same time, they lack substantial knowledge about it, even if they are enrolled in a biology-related study program. Additionally, we developed a multilevel-model that determines religious faith as the main influencing factor in accepting evolution. According to our model, knowledge about evolution and interest in biological topics also increase acceptance of evolution, but to a much lesser extent than religious faith. The effect of age and sex, as well as the country’s affiliation, students’ denomination, and whether or not a student is enrolled in a biology-related university program, is negligible. Conclusions: Our findings indicate that, despite all their differences, most of the European education systems for upper secondary education lead to acceptance of evolution at least in university students. It appears that, at least in this sample, the differences in knowledge between countries reflect neither the extent to which school curricul

关键词： Acceptance Assessment Attitude Europe Evolution Higher education Knowledge Multilevel modeling Religious faith Socioscientific issues

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GWTC-3: Compact Binary Coalescences Observed by LIGO and Virgo during the Second Part of the Third Observing Run

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Physical Review X 2023年第4期13卷 041039-041039页

作者： R. Abbott T. D. Abbott F. Acernese K. Ackley C. Adams N. Adhikari R. X. Adhikari V. B. Adya C. Affeldt D. Agarwal M. Agathos K. Agatsuma N. Aggarwal O. D. Aguiar L. Aiello A. Ain P. Ajith S. Akcay T. Akutsu S. Albanesi A. Allocca P. A. Altin A. Amato C. Anand S. Anand A. Ananyeva S. B. Anderson W. G. Anderson M. Ando T. Andrade N. Andres T. Andrić S. V. Angelova S. Ansoldi J. M. Antelis S. Antier S. Appert Koji Arai Koya Arai Y. Arai S. Araki A. Araya M. C. Araya J. S. Areeda M. Arène N. Aritomi N. Arnaud M. Arogeti S. M. Aronson K. G. Arun H. Asada Y. Asali G. Ashton Y. Aso M. Assiduo S. M. Aston P. Astone F. Aubin C. Austin S. Babak F. Badaracco M. K. M. Bader C. Badger S. Bae Y. Bae A. M. Baer S. Bagnasco Y. Bai L. Baiotti J. Baird R. Bajpai M. Ball G. Ballardin S. W. Ballmer A. Balsamo G. Baltus S. Banagiri D. Bankar J. C. Barayoga C. Barbieri B. C. Barish D. Barker P. Barneo F. Barone B. Barr L. Barsotti M. Barsuglia D. Barta J. Bartlett M. A. Barton I. Bartos R. Bassiri A. Basti M. Bawaj J. C. Bayley A. C. Baylor M. Bazzan B. Bécsy V. M. Bedakihale M. Bejger I. Belahcene V. Benedetto D. Beniwal T. F. Bennett J. D. Bentley M. BenYaala F. Bergamin B. K. Berger S. Bernuzzi C. P. L. Berry D. Bersanetti A. Bertolini J. Betzwieser D. Beveridge R. Bhandare U. Bhardwaj D. Bhattacharjee S. Bhaumik I. A. Bilenko G. Billingsley S. Bini R. Birney O. Birnholtz S. Biscans M. Bischi S. Biscoveanu A. Bisht B. Biswas M. Bitossi M.-A. Bizouard J. K. Blackburn C. D. Blair D. G. Blair R. M. Blair F. Bobba N. Bode M. Boer G. Bogaert M. Boldrini L. D. Bonavena F. Bondu E. Bonilla R. Bonnand P. Booker B. A. Boom R. Bork V. Boschi N. Bose S. Bose V. Bossilkov V. Boudart Y. Bouffanais A. Bozzi C. Bradaschia P. R. Brady A. Bramley A. Branch M. Branchesi J. Brandt J. E. Brau M. Breschi T. Briant J. H. Briggs A. Brillet M. Brinkmann P. Brockill A. F. Brooks J. Brooks D. D. Brown S. Brunett G. Bruno R. Bruntz J. Bryant T. Bulik H. J. Bulten A. Buonanno R. Buscicchio D. Buskulic C. Buy R. L. Byer G. S. Cabourn Davies L. Cadonati G. Cagn LIGO Laboratory California Institute of Technology Pasadena California 91125 USA Louisiana State University Baton Rouge Louisiana 70803 USA Dipartimento di Farmacia Università di Salerno I-84084 Fisciano Salerno Italy INFN Sezione di Napoli Complesso Universitario di Monte S. Angelo I-80126 Napoli Italy OzGrav School of Physics & Astronomy Monash University Clayton 3800 Victoria Australia LIGO Livingston Observatory Livingston Louisiana 70754 USA University of Wisconsin-Milwaukee Milwaukee Wisconsin 53201 USA OzGrav Australian National University Canberra Australian Capital Territory 0200 Australia Max Planck Institute for Gravitational Physics (Albert Einstein Institute) D-30167 Hannover Germany Leibniz Universität Hannover D-30167 Hannover Germany Inter-University Centre for Astronomy and Astrophysics Pune 411007 India University of Cambridge Cambridge CB2 1TN United Kingdom Theoretisch-Physikalisches Institut Friedrich-Schiller-Universität Jena D-07743 Jena Germany University of Birmingham Birmingham B15 2TT United Kingdom Center for Interdisciplinary Exploration and Research in Astrophysics (CIERA) Northwestern University Evanston Illinois 60208 USA Instituto Nacional de Pesquisas Espaciais 12227-010 São José dos Campos São Paulo Brazil Gravity Exploration Institute Cardiff University Cardiff CF24 3AA United Kingdom INFN Sezione di Pisa I-56127 Pisa Italy International Centre for Theoretical Sciences Tata Institute of Fundamental Research Bengaluru 560089 India University College Dublin Dublin 4 Ireland Gravitational Wave Science Project National Astronomical Observatory of Japan (NAOJ) Mitaka City Tokyo 181-8588 Japan Advanced Technology Center National Astronomical Observatory of Japan (NAOJ) Mitaka City Tokyo 181-8588 Japan INFN Sezione di Torino I-10125 Torino Italy Università di Napoli “Federico II” Complesso Universitario di Monte S. Angelo I-80126 Napoli Italy Université de Lyon Université Claude Bernard Lyon 1 CNRS Institut L

The third Gravitational-Wave Transient Catalog (GWTC-3) describes signals detected with Advanced LIGO and Advanced Virgo up to the end of their third observing run. Updating the previous GWTC-2.1, we present candidate gravitational waves from compact binary coalescences during the second half of the third observing run (O3b) between 1 November 2019, 15∶00 Coordinated Universal Time (UTC) and 27 March 2020, 17∶00 UTC. There are 35 compact binary coalescence candidates identified by at least one of our search algorithms with a probability of astrophysical origin pastro>0.5. Of these, 18 were previously reported as low-latency public alerts, and 17 are reported here for the first time. Based upon estimates for the component masses, our O3b candidates with pastro>0.5 are consistent with gravitational-wave signals from binary black holes or neutron-star–black-hole binaries, and we identify none from binary neutron stars. However, from the gravitational-wave data alone, we are not able to measure matter effects that distinguish whether the binary components are neutron stars or black holes. The range of inferred component masses is similar to that found with previous catalogs, but the O3b candidates include the first confident observations of neutron-star–black-hole binaries. Including the 35 candidates from O3b in addition to those from GWTC-2.1, GWTC-3 contains 90 candidates found by our analysis with pastro>0.5 across the first three observing runs. These observations of compact binary coalescences present an unprecedented view of the properties of black holes and neutron stars.

关键词： Gravitational waves

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Middle East and North African Health Informatics Association (MENAHIA): A New Opportunity for the Region

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Yearbook of Medical Informatics 2019年第1期28卷 292-296页

作者： Riyad Alshammari Najeeb Al-Shorbaji Zakiuddin Ahmed Zaid Al-Hamadan Abdulwahhab Alshammari Osama El Hassan Dari Alhuwail Salim Al Salmi Eiman Al-Jafar Hassan Ghazal College of Public Health and Health Informatics King Saud bin Abdulaziz University for Health Sciences Riyadh Saudi Arabia King Abdullah International Medical Research Center Riyadh Saudi Arabia Ministry of the National Guard- Health Affairs Riyadh Saudi Arabia President of the Saudi Health Informatics Association President of the eHealth Development Association of Jordan Program Director RAHAH King Saud University Project Director Riphah Institute of Health Improvement & Safety CEO Digital Care Pakistan Associate Professor Jordan University of Science and Technology College of Applied Medical Sciences King Saud bin Abdulaziz University for Health Sciences Riyadh Saudi Arabia Vice-Chair of Emirates Health Informatics Society Head of eHealth section at Dubai Health Authority Dubai United Arab Emirates Department of Information Science College of Computing Sciences and Engineering Kuwait University Kuwait Health Informatics Unit Dasman Diabetes Institute Kuwait Associate Deanship for Health Information Management Program Oman College of Health Sciences Muscat Sultanate of Oman Department of Health Informatics and Information Management Faculty of Allied Health Sciences Kuwait University Kuwait. National Center for Scientific and Technological Research Rabat and President of the Moroccan Society for Telemedicine and eHealth Rabat Morocco

During the 2018 IMIA General Assembly (GA) held on Oct 2018 in Sri Lanka, a new organization, the Middle East and North African Health Informatics Association (MENAHIA) was established as a regional non-governmental organization to promote Health Informatics in the region. Health Informatics activities in applications, education, and research have been growing in the Middle East and North African region for many years. Over the past year, health informatics initiatives within the region focused on the education sector and the workforce. The need to enhance the education delivery and methods is essential in promoting Health Informatics in the region as well as establishing master programs in many countries within the region. This paper provides an overview of the variety of initiatives that are occurring in the region and are endorsed by MENAHIA.

关键词： Saudi Arabia Pakistan Jordan United Arab Emirates Morocco Kuwait Oman Bahrain Health Informatics the Middle East

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