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Publisher Correction: Global estimates on the number of people blind or visually impaired by cataract: a meta-analysis from 2000 to 2020

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Eye (London, England) 2024年第11期38卷 2229-2231页

作者： Konrad Pesudovs Hugh R. Taylor Tabassom Sedighi Rupert R. A. Bourne Shahina Pardhan Van Charles Lansingh John H. Kempen Ian Tapply Arthur G. Fernandes Maria Vittoria Cicinelli Alessandro Arrigo Nicolas Leveziel Serge Resnikoff Seth Flaxman Mukkharram M. Bikbov Tasanee Braithwaite Alain Bron Ching-Yu Cheng Monte A. Del Monte Joshua R. Ehrlich Leon B. Ellwein David Friedman João M. Furtado Gus Gazzard Ronnie George M. Elizabeth Hartnett Jost B. Jonas Rim Kahloun Moncef Khairallah Rohit C. Khanna Janet Leasher Julie-Anne Little Vinay Nangia Michal Nowak Tunde Peto Pradeep Ramulu Fotis Topouzis Mitiadis Tsilimbaris Ya Xing Wang Ningli Wang Paul Svitil Briant Theo Vos Katrin Burkart Kaleb Coberly Xiaochen Dai Stephen S. Lim Tomislav Mestrovic Ali H. Mokdad Christopher J. L. Murray Jaimie D. Steinmetz Awoke Misganaw Yohannes Habtegiorgis Abate Mohammad Abdollahi Mozhan Abdollahi Ayele Mamo Abebe Olumide Abiodun Richard Gyan Aboagye Woldu Aberhe Abrha Hasan Abualruz Hiwa Abubaker Ali Eman Abu-Gharbieh Salahdein Aburuz Tadele Girum Girum Adal Mesafint Molla Adane Isaac Yeboah Addo Qorinah Estiningtyas Sakilah Adnani Muhammad Sohail Afzal Muhammad Umair Shahin Aghamiri Bright Opoku Ahinkorah Aqeel Ahmad Sajjad Ahmad Ali Ahmadi Siamak Sabour Ayman Ahmed Haroon Ahmed Ahmad Samir Alfaar Abid Ali Syed Shujait Shujait Ali Awais Altaf Hubert Amu Emmanuel Manu Sofia Androudi Rodrigo Anguita Abhishek Anil Rimple Jeet Kaur Muhammad Aaqib Shamim Saeid Anvari Anayochukwu Edward Anyasodor Francis Appiah Jalal Arabloo Haleh Ayatollahi Mosab Arafat Damelash Areda Reza Arefnezhad Brhane Berhe Aregawi Akeza Awealom Asgedom Tahira Ashraf Seyyed Shamsadin Athari Bantalem Tilaye Tilaye Atinafu Birhan Tsegaw Taye Maha Moh’d Wahbi Atout Alok Atreya Ahmed Y. Azzam Hassan Babamohamadi Sara Bagherieh Yogesh Bahurupi Atif Amin Baig Shumaila Nargus Biswajit Banik Mainak Bardhan Saurav Basu Kavita Batra Nebiyou Simegnew Bayileyegn Fatemeh Bazvand Addisu Shunu Beyene Awoke Masrie Asrat Derese Devidas S. Bhagat Akshaya Srikanth Bhagavathula Pankaj Bh Medicine & Health University of New South Wales Sydney NSW Australia School of Optometry and Vision Science University of New South Wales Sydney NSW Australia School of Population and Global Health University of Melbourne Carlton VIC Australia Vision and Eye Research Institute Anglia Ruskin University Cambridge UK HelpMeSee Instituto Mexicano de Oftalmologia Santiago de Querétaro Mexico University of Miami Gables FL USA University of Utah Salt Lake City UT USA Chief Medical Office HelpMeSee New York NY USA Mexican Institute of Ophthalmology Queretaro Mexico Department of Ophthalmology Massachusetts Eye and Ear/Shepens Eye Research Institute/Harvard Medical School Boston MA USA Eye Unit MyungSung Christian Medical Center (MCM) Comprehensive Specialized Hospital and MyungSun Medical College Addis Ababa Ethiopia Department of Ophthalmology Addis Ababa University Addis Ababa Ethiopia Sight for Souls Bellevue WA USA Department of Ophthalmology Harvard University Boston MA USA Eye Unit MyungSung Medical College Addis Ababa Ethiopia Addenbrooke’s Hospital Cambridge UK Department of Ophthalmology Cambridge University Hospitals Cambridge UK Federal University of Sao Paolo Sao Paolo SP Brazil University of Calgary Calgary AB Canada Department of Ophthalmology and Visual Sciences Federal University of São Paulo Sao Paulo Brazil School of Medicine Vita-Salute San Raffaele University Milan Italy Department of Ophthalmology IRCCS San Raffaele Scientific Institute Milan Italy Department of Ophthalmology San Raffaele Scientific Institute Milano Italy IRCCS San Raffaele Scientific Institute Vita-Salute University Milan Italy Scientific Institute San Raffaele Hospital Vita-Salute University Milan Italy University of Poitiers Poitiers France CHU de Poitiers Poitiers France Ophthalmology Department CHU de Poitiers (Poitiers University Hospital) Poitiers France Unité 1084 National Institute of Health and Medical Research (INSERM) Poitiers France

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Recent progress and trends in predictive visual analytics

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Frontiers of computer Science 2017年第2期11卷 192-207页

作者： Junhua LU Wei CHEN Yuxin MA Junming KE Zongzhuang LI Fan ZHANG Ross MACIEJEWSKI State Key Lab of Computer Aided Design and Computer Graphics Zhejiang University Hangzhou 310058 China College of Science Zhejiang University of Technology Hangzhou 310023 China College of Computer Science and Technology Zhejiang University of Technology Hangzhou 310023 China School of Computing Informatics and Decision Systems Engineering Arizona State University Tempe AZ 85287-8809 USA

A wide variety of predictive analytics techniques have been developed in statistics, machine learning and data mining; however, many of these algorithms take a black-box approach in which data is input and future predictions are output with no insight into what goes on during the process. Unfortunately, such a closed system approach often leaves little room for injecting domain expertise and can result in frustration from analysts when results seem snurious or confusing. In order to allow for more human-centric approaches, the visualization community has begun developing methods to enable users to incorporate expert knowledge into the pre- diction process at all stages, including data cleaning, feature selection, model building and model validation. This paper surveys current progress and trends in predictive visual ana- lytics, identifies the common framework in which predictive visual analytics systems operate, and develops a summariza- tion of the predictive analytics workfiow.

关键词： predictive visual analytics visualization visual analytics data mining predictive analysis

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TOI-2458 b: A mini-Neptune consistent with in situ hot Jupiter formation

arXiv

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arXiv 2024年

作者： Šubjak, Jan Gandolfi, Davide Goffo, Elisa Rapetti, David Jankowski, Dawid Mizuki, Toshiyuki Dai, Fei Serrano, Luisa M. Wilson, Thomas G. Goździewski, Krzysztof Nowak, Grzegorz Jenkins, Jon M. Twicken, Joseph D. Winn, Joshua N. Bieryla, Allyson Ciardi, David R. Cochran, William D. Collins, Karen A. Deeg, Hans J. Garcia, Rafael A. Guenther, Eike W. Hatzes, Artie P. Kabath, Petr Korth, Judith Latham, David W. Livingston, John H. Lund, Michael B. Mathur, Savita Narita, Norio Orell-Miquel, Jaume Palle, Enric Persson, Carina M. Redfield, Seth Schwarz, Richard P. Watanabe, David Ziegler, Carl Astronomical Institute Czech Academy of Sciences Fričova 298 Ondřejov251 65 Czech Republic Center for Astrophysics | Harvard & Smithsonian 60 Garden Street CambridgeMA02138 United States Dipartimento di Fisica Universita degli Studi di Torino via Pietro Giuria 1 TorinoI-10125 Italy Thuringer Landessternwarte Tautenburg Sternwarte 5 Tautenburg07778 Germany NASA Ames Research Center Moffett FieldCA94035 United States Research Institute for Advanced Computer Science Universities Space Research Association WashingtonDC20024 United States Institute of Astronomy Faculty of Physics Astronomy and Informatics Nicolaus Copernicus University Grudziadzka 5 Toruń87-100 Poland Astrobiology Center of NINS 2-21-1 Osawa Mitaka Tokyo181-8588 Japan National Astronomical Observatory of Japan 2-21-2 Osawa Mitaka Tokyo181-8588 Japan Institute for Astronomy University of Hawai'i 2680 Woodlawn Drive HonoluluHI96822 United States Department of Physics University of Warwick Gibbet Hill Road CoventryCV4 7AL United Kingdom SETI Institute Mountain ViewCA94043 United States Department of Astrophysical Sciences Princeton University PrincetonNJ08544 United States NASA Exoplanet Science Institute-Caltech/IPAC PasadenaCA91125 United States McDonald Observatory The University of Texas AustinTX United States Center for Planetary Systems Habitability The University of Texas AustinTX United States C. Via Lactea S/N Tenerife La LagunaE-38205 Spain Dept. de Astrofisica Tenerife La LagunaE-38206 Spain Universite Paris-Saclay Universite Paris Cite CEA CNRS AIM Gif-sur-Yvette91191 France Lund Observatory Division of Astrophysics Department of Physics Lund University Box 118 Lund22100 Sweden Astronomical Science Program Graduate University for Advanced Studies SOKENDAI 2-21-1 Osawa Mitaka Tokyo181-8588 Japan Komaba Institute for Science The University of Tokyo 3-8-1 Komaba Meguro Tokyo153-8902 Japan Chalmers University of Technology Departmen

We report on the discovery and spectroscopic confirmation of TOI-2458 b, a transiting mini-Neptune around an F-type star leaving the mainsequence with a mass of M*= 1.05 ± 0.03Mo, a radius of R*= 1.31 ± 0.03 Ro, an effective temperature of Teff = 6005 ± 50 K, and a metallicity of -0.10 ± 0.05 dex. By combining TESS photometry with high-resolution spectra acquired with the HARPS spectrograph, we found that the transiting planet has an orbital period of ∼3.74 days, a mass of Mp = 13.31±0.99M⊕ and a radius of Rp = 2.83±0.20 R⊕. The host star TOI-2458 shows a short activity cycle of ∼54 days revealed in the HARPS S-index and Hα times series. We took the opportunity to investigate other F stars showing activity cycle periods comparable to that of TOI-2458 and found that they have shorter rotation periods than would be expected based on the gyrochronology predictions. In addition, we determined TOI-2458's stellar inclination angle to be i*= 10.6+13.3 -10.6 degrees. We discuss that both phenomena (fast stellar rotation and planet orbit inclination) could be explained by in situ formation of a hot Jupiter interior to TOI-2458 b. It is plausible that this hot Jupiter was recently engulfed by the star. Analysis of HARPS spectra has identified the presence of another planet with a period of P = 16.55 ± 0.06 days and a minimum mass of Mp sin i = 10.22 ± 1.90M⊕. Using dynamical stability analysis, we constrained the mass of this planet to the range Mc (10, 25)M⊕. © 2024, CC BY.

关键词： Stars

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Fitbeat: COVID-19 estimation based on wristband heart rate

arXiv

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arXiv 2021年

作者： Liu, Shuo Han, Jing Puyal, Estela Laporta Kontaxis, Spyridon Sun, Shaoxiong Locatelli, Patrick Dineley, Judith Pokorny, Florian B. Costa, Gloria Dalla Leocani, Letizia Guerrero, Ana Isabel Nos, Carlos Zabalza, Ana Sørensen, Per Soelberg Buron, Mathias Magyari, Melinda Ranjan, Yatharth Rashid, Zulqarnain Conde, Pauline Stewart, Callum Folarin, Amos A. Dobson, Richard J.B. Bailón, Raquel Vairavan, Srinivasan Cummins, Nicholas Narayan, Vaibhav A. Hotopf, Matthew Comi, Giancarlo Schuller, Björn Eihw - Embedded Intelligence for Health Care and Wellbeing University of Augsburg Augsburg Germany Department of Computer Science and Technology University of Cambridge Cambridge United Kingdom Iis Aragón University of Zaragoza Zaragoza Spain Madrid Spain Department of Biostatistics and Health Informatics Institute of Psychiatry Psychology and Neuroscience King's College London London United Kingdom Department of Engineering and Applied Science University of Bergamo Bergamo Italy Division of Phoniatrics Medical University of Graz Graz Austria Neurorehabilitation Unit Institute of Experimental Neurology University Vita Salute San Raffaele Istituto di Ricovero e Cura A Carattere Scientifico Ospedale San Raffaele Milan Italy Department of NeurologyNeuroimmunology Hospital Universitari Vall DHebron Universitat Autònoma de Barcelona Barcelona Spain Danish Multiple Sclerosis Centre Department of Neurology Copenhagen University Hospital Rigshospitalet Copenhagen Denmark Institute of Health Informatics University College London London United Kingdom Janssen Research and Development Llc TitusvilleNJ United States Department of Psychological Medicine Institute of Psychiatry Psychology and Neuroscience King's College London London United Kingdom South London and Maudsley National Health Service Foundation Trust London United Kingdom Institute of Experimental Neurology Istituto di Ricovero e Cura A Carattere Scientifico Ospedale San Raffaele Milan Italy Glam - Group on Language Audio and Music Imperial College London London United Kingdom

This study investigates the potential of deep learning methods to identify individuals with suspected COVID-19 infection using remotely collected heart-rate data. The study utilises data from the ongoing EU IMI RADAR-CNS research project that is investigating the feasibility of wearable devices and smartphones to monitor individuals with multiple sclerosis (MS), depression or epilepsy. As part of the project protocol, heart-rate data was collected from participants using a Fitbit wristband. The presence of COVID-19 in the cohort in this work was either confirmed through a positive swab test, or inferred through the selfreporting of a combination of symptoms including fever, respiratory symptoms, loss of smell or taste, tiredness and gastrointestinal symptoms. Experimental results indicate that our proposed contrastive convolutional auto-encoder (contrastive CAE), i. e., a combined architecture of an auto-encoder and contrastive loss, outperforms a conventional convolutional neural network (CNN), as well as a convolutional auto-encoder (CAE) without using contrastive loss. Our final contrastive CAE achieves 95:3% unweighted average recall, 86:4% precision, an F1 measure of 88:2%, a sensitivity of 100% and a specificity of 90:6% on a test set of 19 participants with MS who reported symptoms of COVID-19. Each of these participants was paired with a participant with MS with no COVID-19 symptoms. Copyright © 2021, The Authors. All rights reserved.

关键词： Convolution

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Measurements of azimuthal anisotropy of nonprompt D0 mesons in PbPb collisions at √sNN = 5.02 TeV

arXiv

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arXiv 2022年

作者： Tumasyan, A. Adam, W. Andrejkovic, J.W. Bergauer, T. Chatterjee, S. Damanakis, K. Dragicevic, M. Del Valle, A. Escalante Hussain, P.S. Jeitler, M. Krammer, N. Lechner, L. Liko, D. Mikulec, I. Paulitsch, P. Pitters, F.M. Schieck, J. Schöfbeck, R. Schwarz, D. Sonawane, M. Templ, S. Waltenberger, W. Wulz, C.-E. Darwish, M.R. Janssen, T. Kello, T. Sfar, H. Rejeb Van Mechelen, P. Bols, E.S. D’Hondt, J. De Moor, A. Delcourt, M. El Faham, H. Lowette, S. Moortgat, S. Morton, A. Müller, D. Sahasransu, A.R. Tavernier, S. Van Doninck, W. Vannerom, D. Clerbaux, B. De Lentdecker, G. Favart, L. Hohov, D. Jaramillo, J. Lee, K. Mahdavikhorrami, M. Makarenko, I. Malara, A. Paredes, S. Pétré, L. Postiau, N. Thomas, L. Bemden, M. Vanden Velde, C. Vander Vanlaer, P. Dobur, D. Knolle, J. Lambrecht, L. Mestdach, G. Rendón, C. Samalan, A. Skovpen, K. Tytgat, M. Van Den Bossche, N. Vermassen, B. Wezenbeek, L. Benecke, A. Bruno, G. Bury, F. Caputo, C. David, P. Delaere, C. Donertas, I.S. Giammanco, A. Jaffel, K. Jain, Sa. Lemaitre, V. Mondal, K. Taliercio, A. Tran, T.T. Vischia, P. Wertz, S. Alves, G.A. Coelho, E. Hensel, C. Moraes, A. Teles, P. Rebello Júnior, W.L. Aldá Pereira, M. Alves Gallo Filho, M. Barroso Ferreira Malbouisson, H. Brandao Carvalho, W. Chinellato, J. Da Costa, E.M. Da Silveira, G.G. De Jesus Damiao, D. Sousa, V. Dos Santos De Souza, S. Fonseca Martins, J. Herrera, C. Mora Amarilo, K. Mota Mundim, L. Nogima, H. Santoro, A. Do Amaral, S.M. Silva Sznajder, A. Thiel, M. Silva, F. Torres Da Araujo, De Pereira, A. Vilela Bernardes, C.A. Calligaris, L. Tomei, T.R. Fernandez Perez Gregores, E.M. Mercadante, P.G. Novaes, S.F. Orzari, B. Padula, Sandra S. Aleksandrov, A. Antchev, G. Hadjiiska, R. Iaydjiev, P. Misheva, M. Shopova, M. Sultanov, G. Dimitrov, A. Litov, L. Pavlov, B. Petkov, P. Petrov, A. Shumka, E. Keshri, S. Thakur, S. Cheng, T. Javaid, T. Yuan, L. Hu, Z. Liu, J. Yi, K. Chen, G.M. Chen, H.S. Chen, M. Iemmi, F. Jiang, C.H. Kapoor, A. Liao, H. Liu, Z.-A. Sharma, R. Song, J.N. Tao, J. Yerevan Physics Institute Yerevan Armenia Institut für Hochenergiephysik Vienna Austria Universiteit Antwerpen Antwerpen Belgium Vrije Universiteit Brussel Brussel Belgium Université Libre de Bruxelles Bruxelles Belgium Ghent University Ghent Belgium Université Catholique de Louvain Louvain-la-Neuve Belgium Centro Brasileiro de Pesquisas Fisicas Rio de Janeiro Brazil Universidade do Estado do Rio de Janeiro Rio de Janeiro Brazil Universidade Estadual Paulista Universidade Federal do ABC São Paulo Brazil Institute for Nuclear Research and Nuclear Energy Bulgarian Academy of Sciences Sofia Bulgaria University of Sofia Sofia Bulgaria Instituto De Alta Investigación Universidad de Tarapacá Casilla 7 D Arica Chile Beihang University Beijing China Department of Physics Tsinghua University Beijing China Institute of High Energy Physics Beijing China State Key Laboratory of Nuclear Physics and Technology Peking University Beijing China Sun Yat-Sen University Guangzhou China University of Science and Technology of China Hefei China Nanjing Normal University Nanjing China Fudan University Shanghai China Zhejiang University Zhejiang Hangzhou China Universidad de Los Andes Bogota Colombia Universidad de Antioquia Medellin Colombia University of Split Faculty of Electrical Engineering Mechanical Engineering and Naval Architecture Split Croatia University of Split Faculty of Science Split Croatia Institute Rudjer Boskovic Zagreb Croatia University of Cyprus Nicosia Cyprus Charles University Prague Czech Republic Escuela Politecnica Nacional Quito Ecuador Universidad San Francisco de Quito Quito Ecuador Academy of Scientific Research and Technology of the Arab Republic of Egypt Egyptian Network of High Energy Physics Cairo Egypt Fayoum University El-Fayoum Egypt National Institute of Chemical Physics and Biophysics Tallinn Estonia Department of Physics University of Helsinki Helsinki Finland Helsinki Institute of Physics Helsinki Finland Lap

Measurements of the elliptic (v2) and triangular (v3) azimuthal anisotropy coefficients are presented for D0 mesons produced in b hadron decays (nonprompt D0 mesons) in lead-lead collisions at √sNN = 5.02 TeV. The results are compared with previously published charm meson anisotropies measured using prompt D0 mesons. The data were collected with the CMS detector in 2018 with an integrated luminosity of 0.58 nb−1. Azimuthal anisotropy is sensitive to the interactions of quarks with the hot and dense medium created in heavy ion collisions. Comparing results for prompt and nonprompt D0 mesons can assist in understanding the mass dependence of these interactions. The nonprompt results show lower magnitudes of v2 and v3 and weaker dependences on the meson transverse momentum and collision centrality than those found for prompt D0 mesons. The results are in agreement with theoretical predictions that include a mass dependence in the interactions of quarks with the medium. © 2022, CC BY.

关键词： Anisotropy

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Intelligent offloading of reports processing in aging mobile devices

Intelligent offloading of reports processing in aging mobile...

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2017 IEEE SmartWorld Ubiquitous Intelligence and Computing, Advanced and Trusted Computed, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovation, SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI 2017

作者： Al-Mousa, Amjed Alzoubi, Ahmad Computer Engineering Department Princess Sumaya University for Technology Amman Jordan Computer Science and Engineering Department Frederick University Nicosia Cyprus

ISBN: (纸本)9781538604342

In the era of mobile computing, mobile devices are required to collect and process a lot of data about the users' actions and preferences. However, with a large number of older devices in the market, not all devices are able to keep up with the increasing reporting requirements. Offloading computations to the cloud is typically suggested to allow the processing of users' data without severely impacting the user experience on these older devices. This paper is focused on collecting reporting data in older devices. It discusses the factors that impact the decision making process of whether to collect raw files from the client and offload computations to the cloud or proceed with local processing of raw files and transmit summarized data to the cloud. In addition, the paper proposes an algorithm to deal with expected hard imitations arising from the aforementioned factors. It also proposes the use of fuzzy logic as a means to optimize the decision making process between these different factors. © 2017 IEEE.

关键词： Decision making

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Combination of 3des with dct algorithm in message security

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IOP Conference Series: Materials Science and engineering 2020年第1期725卷

作者： S. Guntur MKM Nasution RW Nasution Master Program (S2) of Informatics Engineering Faculty of Computer Science and Information Technology University of Sumatera Utara Medan Indonesia Department of Mathematics Faculty of Mathematics and Natural Sciences University of Sumatera Utara Medan Indonesia

In the digital era, communication through computer networks plays an important role. Through electronic communication, a person can make transactions or communication very quickly and practically. Sending data / messages from one place to another is much constrained by the issue of confidentiality. There are many ways you can hide data / messages that will be sent. First, using cryptographic techniques, namely by encoding data / messages using certain algorithms. Another technique is to insert a message that will be sent to other media, so that the message will be hidden and what will appear is other media used to insert *** will be performed a Performance Analysis of the Combination of 3DES and DCT Algorithms in Securing Message Files into the Image.

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Federated machine learning with Anonymous Random Hybridization (FeARH) on medical records

arXiv

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arXiv 2019年

作者： Cui, Jianfei Liu, Dianbo Viterbi School of Engineering University of Southern California Los AngelesCA90007 United States Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology CambridgeMA02139 United States Department of Biomedical Informatics Medical School Harvard University BostonMA02115 United States Computational Health Informatics Boston Children's Hospital BostonMA02115 United States

Sometimes electrical medical records are restricted and difficult to centralize for machine learning, which could only be trained in distributed manner that involved many institutions in the process. However, sometimes some institutions are likely to figure out the private data used for training certain models based on the parameters they obtained, which is a violation of privacy and certain regulations. Under those circumstances, we develop an algorithm, called "federated machine learning with anonymous random hybridization" (abbreviated as 'FeARH'), using mainly hybridization algorithm to eliminate connections between medical record data and models' parameters, which avoid untrustworthy institutions from stealing patients' private medical records. Based on our experiment, our new algorithm has similar AUCROC and AUCPR result compared with machine learning in centralized manner and original federated machine learning, at the same time, our algorithm can greatly reduce data transfer size in comparison with original federated machine learning. Copyright © 2019, The Authors. All rights reserved.

关键词： Data transfer

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Hybrid cryptosystem multi-power RSA with N=PmQ and VMPC

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IOP Conference Series: Materials Science and engineering 2020年第1期725卷

作者： U Erdiansyah MKM Nasution Sawaluddin Master Program (S2) of Informatics Engineering Faculty of Computer Science and Information Technology University of Sumatera Utara Medan Indonesia Department of Mathematics Faculty of Mathematics and Natural Sciences University of Sumatera Utara Medan Indonesia

In digital world, data and information is very valuable and much targeted by unauthorized parties. One way to secure messages is cryptography. Cryptography itself is a branch of science in concealing messages. In further development a hybrid cryptosystem was formed which combines symmetrical and asymmetric cryptography, which in this paper uses VMPC and Multi-Power.. The RSA Multi-Power algorithm is an asymmetric algorithm that is excellent at message encryption but requires a long process time because it uses very complicated calculations. While VMPC has advantages in the process with fast time and relatively small size of ciphertext. Here we have analyzed the performance of various variants of RSA that have been hybridized with VMPC and given the results.

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Evidence for X(3872) in Pb-Pb Collisions and Studies of its Prompt Production at sNN=5.02 TeV

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Physical Review Letters 2022年第3期128卷 032001-032001页

作者： A. M. Sirunyan A. Tumasyan W. Adam F. Ambrogi T. Bergauer M. Dragicevic J. Erö A. Escalante Del Valle M. Flechl R. Frühwirth M. Jeitler N. Krammer I. Krätschmer D. Liko T. Madlener I. Mikulec N. Rad J. Schieck R. Schöfbeck M. Spanring W. Waltenberger C.-E. Wulz M. Zarucki V. Drugakov V. Mossolov J. Suarez Gonzalez M. R. Darwish E. A. De Wolf D. Di Croce X. Janssen T. Kello A. Lelek M. Pieters H. Rejeb Sfar H. Van Haevermaet P. Van Mechelen S. Van Putte N. Van Remortel F. Blekman E. S. Bols S. S. Chhibra J. D’Hondt J. De Clercq D. Lontkovskyi S. Lowette I. Marchesini S. Moortgat Q. Python S. Tavernier W. Van Doninck P. Van Mulders D. Beghin B. Bilin B. Clerbaux G. De Lentdecker H. Delannoy B. Dorney L. Favart A. Grebenyuk A. K. Kalsi L. Moureaux A. Popov N. Postiau E. Starling L. Thomas C. Vander Velde P. Vanlaer D. Vannerom T. Cornelis D. Dobur I. Khvastunov M. Niedziela C. Roskas K. Skovpen M. Tytgat W. Verbeke B. Vermassen M. Vit G. Bruno C. Caputo P. David C. Delaere M. Delcourt A. Giammanco V. Lemaitre J. Prisciandaro A. Saggio P. Vischia J. Zobec G. A. Alves G. Correia Silva C. Hensel A. Moraes E. Belchior Batista Das Chagas W. Carvalho J. Chinellato E. Coelho E. M. Da Costa G. G. Da Silveira D. De Jesus Damiao C. De Oliveira Martins S. Fonseca De Souza H. Malbouisson J. Martins D. Matos Figueiredo M. Medina Jaime M. Melo De Almeida C. Mora Herrera L. Mundim H. Nogima W. L. Prado Da Silva P. Rebello Teles L. J. Sanchez Rosas A. Santoro A. Sznajder M. Thiel E. J. Tonelli Manganote F. Torres Da Silva De Araujo A. Vilela Pereira C. A. Bernardes L. Calligaris T. R. Fernandez Perez Tomei E. M. Gregores D. S. Lemos P. G. Mercadante S. F. Novaes Sandra S. Padula A. Aleksandrov G. Antchev R. Hadjiiska P. Iaydjiev M. Misheva M. Rodozov M. Shopova G. Sultanov M. Bonchev A. Dimitrov T. Ivanov L. Litov B. Pavlov P. Petkov A. Petrov W. Fang X. Gao L. Yuan M. Ahmad Z. Hu Y. Wang G. M. Chen H. S. Chen M. Chen C. H. Jiang D. Leggat H. Liao Z. Liu A. Spiezia J. Tao E. Yazgan H. Zhang S. Zhang J. Zhao A. Agapitos Y. Ban G. Ch Yerevan Physics Institute Yerevan Armenia Institut für Hochenergiephysik Wien Austria Institute for Nuclear Problems Minsk Belarus Universiteit Antwerpen Antwerpen Belgium Vrije Universiteit Brussel Brussel Belgium Université Libre de Bruxelles Bruxelles Belgium Ghent University Ghent Belgium Université Catholique de Louvain Louvain-la-Neuve Belgium Centro Brasileiro de Pesquisas Fisicas Rio de Janeiro Brazil Universidade do Estado do Rio de Janeiro Rio de Janeiro Brazil Universidade Estadual Paulista São Paulo Brazil Universidade Federal do ABC São Paulo Brazil Institute for Nuclear Research and Nuclear Energy Bulgarian Academy of Sciences Sofia Bulgaria University of Sofia Sofia Bulgaria Beihang University Beijing China National Centre for Physics Quaid-I-Azam University Islamabad Pakistan Department of Physics Tsinghua University Beijing China University of Virginia Charlottesville Virginia USA Institute of High Energy Physics Beijing China State Key Laboratory of Nuclear Physics and Technology Peking University Beijing China The University of Kansas Lawrence Kansas USA Zhejiang University Hangzhou China Universidad de Los Andes Bogota Colombia Universidad de Antioquia Medellin Colombia University of Split Faculty of Electrical Engineering Mechanical Engineering and Naval Architecture Split Croatia University of Split Faculty of Science Split Croatia Institute Rudjer Boskovic Zagreb Croatia University of Cyprus Nicosia Cyprus Charles University Prague Czech Republic Escuela Politecnica Nacional Quito Ecuador Universidad San Francisco de Quito Quito Ecuador Academy of Scientific Research and Technology of the Arab Republic of Egypt Egyptian Network of High Energy Physics Cairo Egypt National Institute of Chemical Physics and Biophysics Tallinn Estonia Department of Physics University of Helsinki Helsinki Finland Helsinki Institute of Physics Helsinki Finland Lappeenranta University of Technology Lappeenranta Finland IRFU CEA Un

The first evidence for X(3872) production in relativistic heavy ion collisions is reported. The X(3872) production is studied in lead-lead (Pb-Pb) collisions at a center-of-mass energy of sNN=5.02 TeV per nucleon pair, using the decay chain X(3872)→J/ψπ+π−→μ+μ−π+π−. The data were recorded with the CMS detector in 2018 and correspond to an integrated luminosity of 1.7 nb−1. The measurement is performed in the rapidity and transverse momentum ranges |y|<1.6 and 15

关键词： Particle & resonance production Quark-gluon plasma Relativistic heavy-ion collisions Hadron colliders

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