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arXiv 2020年

作者： Förster, Francisco Cabrera-Vives, G. Castillo-Navarrete, E. Estévez, P.A. Sánchez-Sáez, P. Arredondo, J. Bauer, F.E. Carrasco-Davis, R. Catelan, M. Elorrieta, F. Eyheramendy, S. Huijse, P. Pignata, G. Reyes, E. Reyes, I. Rodríguez-Mancini, D. Ruz-Mieres, D. Valenzuela, C. Álvarez-Maldonado, I. Astorga, N. Borissova, J. Clocchiatti, A. de Cicco, D. Donoso-Oliva, C. Graham, M.J. Kurtev, R. Mahabal, A. Maureira, J.C. Molina-Ferreiro, R. Moya, A. Palma, W. Prez-Carrasco, M. Protopapas, P. Romero, M. Sabatini-Gacitua, L. Snchez, A. San Martín, J. Sepúlveda-Cobo, C. Vera, E. Vergara, J.R. Center for Mathematical Modeling University of Chile AFB170001 Chile Millennium Institute of Astrophysics Nuncio Monseñor Sótero Sanz 100 Providencia Santiago Chile Departamento de Astronomía Universidad de Chile Casilla 36D Santiago Chile Department of Computer Science University of Concepcin Chile Department of Electrical Engineering Universidad de Chile Av. Tupper 2007 Santiago8320000 Chile Instituto de Astrofísica Facultad de Física Pontificia Universidad Católica de Chile Av. Vicuña Mackenna 4860 Macul Santiago7820436 Chile Department of Engineering and Science Universidad Adolfo Ibaez Av. Diagonal Las Torres 2700 Santiago Chile Centro de Astroingeniería Pontificia Universidad Católica de Chile Av. Vicuña Mackenna 4860 Macul Santiago7820436 Chile Space Science Institute 4750 Walnut Street Suite 205 BoulderCO80301 United States Department of Mathematics and Computer Science Universidad de Santiago de Chile Av. Libertador Bernardo OHiggins 3663 Estación Central Santiago Chile Instituto de Informática Universidad Austral de Chile General Lagos 2086 Valdivia Chile Departamento de Ciencias Físicas Universidad Andres Bello Avda. Republica 252 Santiago Chile Institute of Astronomy University of Cambridge Madingley Road CambridgeCB3 0HA United Kingdom Instituto de Física y Astronomía Universidad de Valparaíso Av. Gran Bretaña 1111 Playa Ancha Casilla5030 Chile Division of Physics Mathematics and Astronomy California Institute of Technology PasadenaCA91125 United States Center for Data Driven Discovery California Institute of Technology PasadenaCA91125 United States Institute for Applied Computational Science Harvard University CambridgeMA United States Departmento de Informática y Computación Universidad Tecnológica Metropolitana Santiago Chile

We introduce the Automatic Learning for the Rapid Classification of Events (ALeRCE) broker, an astronomical alert broker designed to provide a rapid and self–consistent classification of large etendue telescope alert streams, such as that provided by the Zwicky Transient Facility (ZTF) and, in the future, the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). ALeRCE is a Chilean–led broker run by an interdisciplinary team of astronomers and engineers, working to become intermediaries between survey and follow–up facilities. ALeRCE uses a pipeline which includes the real–time ingestion, aggregation, cross–matching, machine learning (ML) classification, and visualization of the ZTF alert stream. We use two classifiers: a stamp–based classifier, designed for rapid classification, and a light–curve–based classifier, which uses the multi–band flux evolution to achieve a more refined classification. We describe in detail our pipeline, data products, tools and services, which are made public for the community (see https://***). Since we began operating our real–time ML classification of the ZTF alert stream in early 2019, we have grown a large community of active users around the globe. We describe our results to date, including the real–time processing of 9.7×107 alerts, the stamp classification of 1.9 × 107 objects, the light curve classification of 8.5 × 105 objects, the report of 3088 supernova candidates, and different experiments using LSST-like alert streams. Finally, we discuss the challenges ahead to go from a single-stream of alerts such as ZTF to a multi–stream ecosystem dominated by LSST. Copyright © 2020, The Authors. All rights reserved.

关键词： Surveys

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Spectral Structure of Elastic Neumann–Poincaré Operators

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Journal of Physics: Conference Series 2018年第1期965卷

作者： Yoshihisa Miyanishi Kazunori Ando Hyeonbae Kang Center for Mathematical Modeling and Data Science Osaka University Osaka 560-8631 Japan Department of Electrical and Electronic Engineering and Computer Science Ehime University Ehime 790-8577 Japan Department of Mathematics and Institute of Applied Mathematics Inha University Incheon 22212 S. Korea

In [1, 2], it is proved that the elastic Neumann–Poincaré operator defined on the smooth boundary of a bounded domain, which is known to be non-compact, is in fact polynomially compact. As a consequence, it is shown that the spectrum of the elastic Neumann-Poincaré operator consists of non-empty sets of eigenvalues accumulating to certain numbers determined by Lamé parameters. The purpose of this paper is to review these results and their proofs, and to discuss about some questions related to these results.

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Correction: CEPC Technical Design Report: Accelerator

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Radiation Detection Technology and Methods 2024年第1期9卷 184-192页

作者： Abdallah, Waleed de Freitas, Tiago CarlosAdorno Afanaciev, Konstantin Ahmad, Shakeel Ahmed, Ijaz Ai, Xiaocong Aleem, Abid Altmannshofer, Wolfgang Alves, Fabio An, Weiming An, Rui Anderle, Daniele Paolo Antusch, Stefan Arai, Yasuo Arbuzov, Andrej Arhrib, Abdesslam Ashry, Mustafa Bai, Sha Bai, Yu Bai, Yang Bairathi, Vipul Balazs, Csaba Bambade, Philip Ban, Yong Bandyopadhyay, Triparno Bao, Shou-Shan Barber, Desmond P. Bat, Ays¸e Batozskaya, Varvara Behera, Subash Chandra Belyaev, Alexander Bertucci, Michele Bi, Xiao-Jun Bi, Yuanjie Bian, Tianjian Bianchi, Fabrizio Bieko¨tter, Thomas Biglietti, Michela Bilanishvili, Shalva Binglin, Deng Bodrov, Denis Bogomyagkov, Anton Bondarenko, Serge Boogert, Stewart Boonekamp, Maarten Borri, Marcello Bosotti, Angelo Boudry, Vincent Boukidi, Mohammed Boyko, Igor Bozovic, Ivanka Bozzi, Giuseppe Brient, Jean-Claude Budzinskaya, Anastasiia Bukhari, Masroor Bytev, Vladimir Cacciapaglia, Giacomo Cai, Hua Cai, Wenyong Cai, Wujun Cai, Yijian Cai, Yizhou Cai, Yuchen Cai, Haiying Cai, Huacheng Calibbi, Lorenzo Cang, Junsong Cao, Guofu Cao, Jianshe Chance, Antoine Chang, Xuejun Chang, Yue Chang, Zhe Chang, Xinyuan Chao, Wei Chatrabhuti, Auttakit Che, Yimin Che, Yuzhi Chen, Bin Chen, Danping Chen, Fuqing Chen, Fusan Chen, Gang Chen, Guoming Chen, Hua-Xing Chen, Huirun Chen, Jinhui Chen, Ji-Yuan Chen, Kai Chen, Mali Chen, Mingjun Chen, Mingshui Chen, Ning Chen, Shanhong Chen, Shanzhen Chen, Shao-Long Chen, Shaomin Chen, Shiqiang Chen, Tianlu Chen, Wei Chen, Xiang Chen, Xiaoyu Chen, Xin Chen, Xun Chen, Xurong Chen, Ye Chen, Ying Chen, Yukai Chen, Zelin Chen, Zilin Chen, Boping Chen, Chunhui Cheng, Hok Chuen Cheng, Huajie Cheng, Shan Cheng, Tongguang Chi, Yunlong Chimenti, Pietro Chiu, Wen Han Cho, Guk Chu, Ming-Chung Chu, Xiaotong Chu, Ziliang Coloretti, Guglielmo Crivellin, Andreas Cui, Hanhua Cui, Xiaohao Cui, Zhaoyuan D’Anzi, Brunella Dai, Ling-Yun Dai, Xinchen Dai, Xuwen De Maria, Antonio De Filippis, Nicola De La Taille, Christophe De Mori, Francesca De Sio, Chiara Del Core, Elisa Deng, Cairo University Giza Egypt Xi’an Jiaotong-Liverpool University Suzhou China Institute of Power Engineering of National Academy of Sciences of Belarus Minsk Belarus Pakistan Institute of Nuclear Science and Technology (PINSTECH) Islamabad Pakistan Applied Physics Department Science and Technology Federal Urdu University of Arts Islamabad Pakistan Zhengzhou University Zhengzhou China Institute of High Energy Physics Chinese Academy of Sciences Beijing China University of California Santa Cruz Santa Cruz USA Nanjing University Nanjing China Beijing Normal University Beijing China Harvard University Cambridge USA South China Normal University Guangzhou China University of Basel Basel Switzerland High Energy Accelerator Research Organization (KEK) Tsukuba Japan Joint Institute for Nuclear Research Dubna Russia Faculty of Sciences and Techniques Université Abdelmalek Essaadi Tangier Morocco Southeast University Nanjing China Department of Physics University of Wisconsin–Madison Madison USA Instituto de Alta Investigación Universidad de Tarapacá Arica Chile Monash University Melbourne Australia Laboratoire de Physique des 2 infinis Irène Joliot-Curie – IJCLab Orsay France Peking University Beijing China Department of Physics and Nanotechnology SRM Institute of Science and Technology Kattankulathur India Shandong University Jinan China University of New Mexico Albuquerque USA Bandirma Onyedi Eylul University Bandırma Turkey National Centre for Nuclear Research Warsaw Poland Indian Institute of Technology Madras (IN) Chennai India University of Southampton Southampton UK INFN Milano - LASA Segrate Italy Sun Yat-Sen University Guangzhou China China Institute of Atomic Energy Beijing China INFN-University of Torino Turin Italy Karlsruhe Institute of Technology Institute for Theoretical Physics Karlsruhe Germany INFN-Sezione di Roma Tre Rome Italy Kutaisi International University Kutaisi Georgia Soochow University Suzhou China Budker Institute

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Lower bounds on the robustness to adversarial perturbations 17

Lower bounds on the robustness to adversarial perturbations

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Proceedings of the 31st International Conference on Neural Information Processing Systems

作者： Jonathan Peck Joris Roels Bart Goossens Yvan Saeys Department of Applied Mathematics Computer Science and Statistics Ghent University Ghent Belgium and Data Mining and Modeling for Biomedicine VIB Inflammation Research Center Ghent Belgium Data Mining and Modeling for Biomedicine VIB Inflammation Research Center Ghent Belgium and Department of Telecommunications and Information Processing Ghent University Ghent Belgium Department of Telecommunications and Information Processing Ghent University Ghent Belgium

ISBN: (纸本)9781510860964

The input-output mappings learned by state-of-the-art neural networks are significantly discontinuous. It is possible to cause a neural network used for image recognition to misclassify its input by applying very specific, hardly perceptible perturbations to the input, called adversarial perturbations. Many hypotheses have been proposed to explain the existence of these peculiar samples as well as several methods to mitigate them, but a proven explanation remains elusive. In this work, we take steps towards a formal characterization of adversarial perturbations by deriving lower bounds on the magnitudes of perturbations necessary to change the classification of neural networks. The proposed bounds can be computed efficiently, requiring time at most linear in the number of parameters and hyperparameters of the model for any given sample. This makes them suitable for use in model selection, when one wishes to find out which of several proposed classifiers is most robust to adversarial perturbations. They may also be used as a basis for developing techniques to increase the robustness of classifiers, since they enjoy the theoretical guarantee that no adversarial perturbation could possibly be any smaller than the quantities provided by the bounds. We experimentally verify the bounds on the MNIST and CIFAR-10 data sets and find no violations. Additionally, the experimental results suggest that very small adversarial perturbations may occur with non-zero probability on natural samples.

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The development of secure mobile computing network based on secret sharing schemes

The development of secure mobile computing network based on ...

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IEEE NW Russia Young Researchers in Electrical and Electronic Engineering Conference (EIConRusNW)

作者： Nikolay Ivanovich Chervyakov Mikhail Grigorievich Babenko Maxim Anatolievich Deryabin Maria Nikolaevna Shabalina B A Alassane Department of Applied Mathematics and Mathematical modeling North Caucasian federal University Stavropol Russia Department Mathematics and Computer Cheikh Anta Diop University of Dakar Dakar Senegal

In the article the problem of construction of mobile networks for solving computationally complex problems is researched. It is proposed to use the modified secret sharing scheme (SSS) Asmuth-Bloom for distributed computing in the mobile network. The SSS constructed on the basis of residue number system (RNS) allows to parallelize arithmetic operations of addition and multiplication of numbers, but make it difficult to perform a division operation. The proposed method allows the efficient implementation of arithmetic operations of addition, multiplication and division in the RNS. To evaluate the performance of a mobile computing network the problem of solving systems of linear equations was used. It is shown that the use of the proposed approach makes it possible to parallelize computations and to ensure their safety.

关键词： Cryptography Mobile computing Mobile communication Fault tolerance Fault tolerant systems Interpolation Peer-to-peer computing

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A Novel Detection Intrusion Approach for Ubiquitous and Pervasive Environments

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Procedia computer Science 2016年 94卷 429-434页

作者： Lynda Sellami Djilali Idoughi Abderrahman Baadache Pierre Tiako Department of Computer Science A/Mira University of Bejaiaa Algeria Applied Mathematics Laboratory A/Mira University of Bejaia Algeria Modeling and Optimization Systems Laboratory University of Bejaia Algeria CITDR Tiako University Oklahoma USA

Ubiquitous system returns to making pervasive computing in everyday life, the objects of our environments become intelligent and communicate without anyone being aware of their communication processes Ubiquitous computing adds the concept of mobility to the notion of omnipresence; therefore, it makes reference to moving intelligent objects (from mobile computing) that can communicate with other ubiquitous objects in our daily lives These advantages expose the network to malicious and unauthorized activities The security of these networks, targeted by attackers, is an important issue For this, Intrusion Detection Systems (IDSs) have been widely discussed for solving networks intrusions problems Several solutions have been adopted to overcome these kinds of intrusion These IDS solutions are insufficient and/or incomplete because they are based on centralized devises, and did not consider the heterogeneity and mobility nature of these devices, which is the case for ubiquitous environments We developed a new IDS approach to support security problems in ubiquitous network The approach proposed is based on nodes authentication abilities for preventing inside and outside ubiquitous network intrusion.

关键词： Ubiquitous computing Intrusion detection system (IDS) Security Trust

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Jitter calculation in Core IMS

Jitter calculation in Core IMS

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IEEE NW Russia Young Researchers in Electrical and Electronic Engineering Conference (EIConRusNW)

作者： B A Alassane Konate Karim Nikolay Ivanovich Chervyakov Maxim Anatolievich Deryabin Mikhail Grigorievich Babenko Maria Nikolaevna Shabalina Laboratory of Computer Network and Telecommunications Cheikh Anta Diop University of Dakar Dakar Senegal Department Mathematics and Computer Cheikh Anta Diop University of Dakar Dakar Senegal Department of Applied Mathematics and Mathematical modeling North Caucasian federal University Stavropol Russia

The IP Multimedia Subsystem (IMS) enables the convergence of voice, data, and multimedia services. IMS is well integrated with existing voice and data networks, while adopting many of their key characteristics. SIP (Session Initiation Protocol) provides a pathway to build a single unified network, bridging the gap that previously existed between the once-separated Telecom and Internet networks. The Call Session Control Functions (CSCFs) servers are the key part of the IMS structure. They are the main components responsible for processing and routing signalling messages. For users and enterprise needs, network outages or significant degradations of the quality of service (QoS) become less and less tolerable. Our research works on improvement of the QoS in IMS networks. It is base in jitter calculation and proposal of reducing jitter for improving traffic.

关键词： Jitter Delays Quality of service IP networks Servers Multimedia communication Streaming media

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Intelligent model for measuring learners' satisfaction towards new contents 15

Intelligent model for measuring learners' satisfaction towar...

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15th International Conference on Information Technology Based Higher Education and Training, ITHET 2016

作者： Elghibari, Fatiha Elouahbi, Rachid El Khoukhi, Fatima Ezzahri, Layla Macs, Labo Amali, Said Department of Mathematics and Computer Science Moulay Ismail University Faculty of Sciences Meknes Morocco Team Modeling Applied Informatics in Humanities MIASH Moulay Ismail University Faculty of Humanities Meknes Morocco Team Théorie des Systèmes et Informatique TSI Moulay Ismail University Faculty of Sciences Meknes Morocco Team Outils Mathématiques en Economie Gestion et Actuariat OMEGA Moulay Ismail University Faculty of Juridical Economic and Social Sciences Meknes Morocco

ISBN: (纸本)9781509007783

Learner satisfaction is an important factor for a successful e-Learning. It allows learners to continue learning and provide their conveniences to facilitate the knowledge. That is why, the main purpose of this study is to enhance learning services in online environments, in order to keep learners' motivation and track their cognition' evolution. Namely, identify their satisfaction toward new inserted contents. In this paper, we present a learning model that detects satisfaction' degree of learners at two levels;during and after completing the course. During learning by using satisfaction agent (SA) that collects data and calculates satisfaction level towards each content' unit. This process allows to integrate improvement if we have a low levels of satisfaction. And after completing course in order to evaluate the evolution of learners' knowledge, and test the effectiveness of the methods and tools used in. © 2016 IEEE.

关键词： Motivation

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Intelligent model for measuring learners' satisfaction towards new contents

Intelligent model for measuring learners' satisfaction towar...

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International Conference on Information Technology Based Higher Education and Training, ITHET

作者： Fatiha Elghibari Rachid Elouahbi Fatima El Khoukhi Layla Ezzahri Said Amali Department of mathematics and computer Science Moulay Ismail University Meknes Morocco Team Modeling Applied Informatics in Humanities MIASH Moulay Ismail University Meknes Morocco Faculty of Sciences Moulay Ismail University Meknes Morocco Team Outils Mathématiques en Economie Moulay Ismail University Meknes Morocco

ISBN: (纸本)9781509007790

Learner satisfaction is an important factor for a successful e-Learning. It allows learners to continue learning and provide their conveniences to facilitate the knowledge. That is why, the main purpose of this study is to enhance learning services in online environments, in order to keep learners' motivation and track their cognition' evolution. Namely, identify their satisfaction toward new inserted contents. In this paper, we present a learning model that detects satisfaction' degree of learners at two levels; during and after completing the course. During learning by using satisfaction agent (SA) that collects data and calculates satisfaction level towards each content' unit. This process allows to integrate improvement if we have a low levels of satisfaction. And after completing course in order to evaluate the evolution of learners' knowledge, and test the effectiveness of the methods and tools used in.

关键词： Electronic learning Training Computational modeling Mathematical model computer science

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Author Correction: A human immune dysregulation syndrome characterized by severe hyperinflammation with a homozygous nonsense Roquin-1 mutation

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Nature communications 2019年第1期10卷 5337页

作者： S J Tavernier V Athanasopoulos P Verloo G Behrens J Staal D J Bogaert L Naesens M De Bruyne S Van Gassen E Parthoens J Ellyard J Cappello L X Morris H Van Gorp G Van Isterdael Y Saeys M Lamkanfi P Schelstraete J Dehoorne V Bordon R Van Coster B N Lambrecht B Menten R Beyaert C G Vinuesa V Heissmeyer M Dullaers F Haerynck Primary Immune Deficiency Research Lab Department of Internal Medicine and Pediatrics Centre for Primary Immunodeficiency Ghent Jeffrey Modell Diagnosis and Research Centre Ghent University Hospital Ghent Belgium. VIB Center for Inflammation Research Unit of Molecular Signal Transduction in Inflammation Ghent Belgium. Department of Biomedical Molecular Biology Ghent University Ghent Belgium. Department of Immunology and Infectious Disease and Center for Personalised Immunology (NHMRC Centre for Research Excellence) John Curtin School of Medical Research Australian National University Canberra Australia. Centre for Personalised Immunology (CACPI) Shanghai Renji Hospital Shanghai Jiao Tong University Shanghai China. Department of Internal Medicine and Pediatrics Division of Pediatric Neurology and Metabolism Ghent University Hospital Ghent Belgium. Institute for Immunology Biomedical Center Ludwig-Maximilians-Universität München Planegg-Martinsried Germany. Research Unit Molecular Immune Regulation Helmholtz Zentrum München Munich Germany. Department of Internal Medicine and Pediatrics Division of Pediatric Immunology and Pulmonology Ghent University Hospital Ghent Belgium. Department of Internal Medicine and Pediatrics Ghent University Hospital Ghent Belgium. Center for Medical Genetics Ghent University Hospital Ghent Belgium. VIB Center for Inflammation Research Unit of Data Mining and Modeling for Biomedicine Ghent Belgium. Department of Applied Mathematics Computer Science and Statistics Ghent University Gent Belgium. VIB Bioimaging Core VIB Center for Inflammation Research Ghent Belgium. The Australian Phenomics Facility John Curtin School of Medical Research Australian National University Canberra Australia. VIB Center for Inflammation Research Ghent Belgium. VIB Flow Core VIB Center for Inflammation Research Ghent Belgium. Department of Internal Medicine and Pediatrics Division of Pediatric Rheumatology Ghent University Hospital Ghent Belgium. D

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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