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ASYMPTOTIC BEHAVIOR OF GLOBAL SMOOTH SOLUTIONS FOR BIPOLAR COMPRESSIBLE NAVIER-STOKES-MAXWELL SYSTEM FROM PLASMAS

Acta mathematica Scientia 2015年第5期35卷 955-969页

作者：冯跃红王术李新 College of Applied Sciences Beijing University of Technology Laboratoire de Mathématiques Université Blaise Pascal Department of Mathematics and Computer Science Xinyang Vocational and Technical College

This paper is concerned with the bipolar compressible Navier-Stokes-Maxwell system for plasmas. We investigated, by means of the techniques of symmetrizer and elaborate energy method, the Cauchy problem in R^3. Under the assumption that the initial values are close to a equilibrium solutions, we prove that the smooth solutions of this problem converge to a steady state as the time goes to the infinity. It is shown that the difference of densities of two carriers converge to the equilibrium states with the norm ｜｜·｜｜H^s-1, while the velocities and the electromagnetic fields converge to the equilibrium states with weaker norms than ｜｜·｜｜H^s-1. This phenomenon on the charge transport shows the essential difference between the unipolar Navier-Stokes-Maxwell and the bipolar Navier-Stokes-Maxwell system.

关键词： bipolar compressible Navier-Stokes-Maxwell system plasmas global smooth solutions energy estimates large-time behavior

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DOT-K: A distributed online top-K elements algorithm using extreme value statistics

DOT-K: A distributed online top-K elements algorithm using e...

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IEEE International Conference on e-science and Grid Computing

作者： Nicholas Carey Tamás Budavári Yanif Ahmad Alexander Szalay Department of Computer Science Johns Hopkins University Baltimore Maryland Department of Applied Math and Statistics Johns Hopkins University Baltimore Maryland Department of Physics and Astronomy Johns Hopkins University Baltimore Maryland

Extremely large (peta-scale) data collections are generally partitioned into millions of containers (disks/volumes/files) which are essentially unmovable due to their aggregate size. They are stored over a large distributed cloud of machines, with computing co-located with the data. Given this data layout, even simple tasks are difficult to perform and naive algorithms can easily become quite expensive. We present a one pass, communications-efficient technique useful for both estimating upper order quantiles and selecting the largest k elements across a highly distributed dataset or stream. Our novel approach draws its foundations from Extreme Value Statistics (EVS) to reason about the statistical relationships between the tail distributions of dataset partitions. The tail of each partition is fitted by the Generalized Pareto Distribution, which captures threshold exceedances. The obtained parameters are communicated to a central coordinator and used to estimate quantiles, or solve for a threshold above which there are approximately k elements. We discuss the computational and bandwidth costs of the algorithm, and demonstrate the accuracy of the method on both a variety of synthetic datasets and a PageRank dataset.

关键词： Partitioning algorithms Distributed databases Estimation mathematical model Parameter estimation Random variables computer science

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Inducing approximately optimal flow using truthful mediators 15

Inducing approximately optimal flow using truthful mediators

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16th ACM Conference on Economics and Computation, EC 2015

作者： Rogers, Ryan Roth, Aaron Ullman, Jonathan Wu, Zhiwei Steven Applied Math and Computational Science Department University of Pennsylvania United States Department of Computer Science Columbia University United States

ISBN: (纸本)9781450334105

We revisit a classic coordination problem from the perspective of mechanism design: how can we coordinate a social welfare maximizing flow in a network congestion game with selfish players? The classical approach, which computes tolls as a function of known demands, fails when the demands are unknown to the mechanism designer, and naively eliciting them does not necessarily yield a truthful mechanism. Instead, we introduce a weak mediator that can provide suggested routes to players and set tolls as a function of reported demands. However, players can choose to ignore or misreport their type to this mediator. Using techniques from differential privacy, we show how to design a weak mediator such that it is an asymptotic ex-post Nash equilibrium for all players to truthfully report their types to the mediator and faithfully follow its suggestion, and that when they do, they end up playing a nearly optimal flow. Notably, our solution works in settings of incomplete information even in the absence of a prior distribution on player types. Along the way, we develop new techniques for privately solving convex programs which may be of independent interest.

关键词： algorithms differential privacy mechanism design

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Private pareto optimal exchange 15

Private pareto optimal exchange

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16th ACM Conference on Economics and Computation, EC 2015

作者： Kannan, Sampath Morgenstern, Jamie Rogers, Ryan Roth, Aaron Applied Math and Computational Sciences Department University of Pennsylvania United States Carnegie Mellon University Computer Science Department United States

ISBN: (纸本)9781450334105

We consider the problem of implementing an individually rational, asymptotically Pareto optimal allocation in a barter-exchange economy where agents are endowed with goods and preferences over the goods of others, but may not use money as a medium of exchange. Because one of the most important instantiations of such economies is kidney exchange - where the "input" to the problem consists of sensitive patient medical records - we ask to what extent such exchanges can be carried out while providing formal privacy guarantees to the participants. We show that individually rational allocations cannot achieve any non-trivial approximation to Pareto optimality if carried out under the constraint of differential privacy - or even the relaxation of joint-differential privacy, under which it is known that asymptotically optimal allocations can be computed in two sided markets [Hsu et al. STOC 2014]. We therefore consider a further relaxation that we call marginal-differential privacy - which promises, informally, that the privacy of every agent i is protected from every other agent j 6 ≡ i so long as j does not collude or share allocation information with other agents. We show that under marginal differential privacy, it is possible to compute an individually rational and asymptotically Pareto optimal allocation in such exchange economies.

关键词： algorithms differential privacy mechanism design

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Shortest Path to a Segment and Quickest Visibility Queries 31

Shortest Path to a Segment and Quickest Visibility Queries

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31st International Symposium on Computational Geometry, SoCG 2015

作者： Arkin, Esther M. Efrat, Alon Knauer, Christian Mitchell, Joseph S.B. Polishchuk, Valentin Rote, Günter Schlipf, Lena Talvitie, Topi Department of Applied Math and Statistics Stony Brook University United States Department of Computer Science University of Arizona United States Institute of Computer Science Universität Bayreuth Germany Communications and Transport Systems ITN Linköping University Sweden Institute of Computer Science Freie Universität Berlin Germany Department of Computer Science University of Helsinki Finland

ISBN: (纸本)9783939897835

We show how to preprocess a polygonal domain with a fixed starting point s in order to answer efficiently the following queries: Given a point q, how should one move from s in order to see q as soon as possible? This query resembles the well-known shortest-path-to-a-point query, except that the latter asks for the fastest way to reach q, instead of seeing it. Our solution methods include a data structure for a different generalization of shortest-path-to-a-point queries, which may be of independent interest: to report efficiently a shortest path from s to a query segment in the domain.

关键词： Visibility

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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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On the consistency of the likelihood maximization vertex nomination scheme: bridging the gap between maximum likelihood estimation and graph matching

The Journal of Machine Learning Research

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The Journal of Machine Learning Research 2016年第1期17卷

作者： Kevin Murphy Bernhard Schölkopf Vince Lyzinski Keith Levin Donniell E. Fishkind Carey E. Priebe Google MPI for Intelligent Systems Department of Applied Math and Statistics Johns Hopkins University Baltimore MD Department of Computer Science Johns Hopkins University Baltimore MD

Given a graph in which a few vertices are deemed interesting a priori, the vertex nomination task is to order the remaining vertices into a nomination list such that there is a concentration of interesting vertices at the top of the list. Previous work has yielded several approaches to this problem, with theoretical results in the setting where the graph is drawn from a stochastic block model (SBM), including a vertex nomination analogue of the Bayes optimal classifier. In this paper, we prove that maximum likelihood (ML)-based vertex nomination is consistent, in the sense that the performance of the ML-based scheme asymptotically matches that of the Bayes optimal scheme. We prove theorems of this form both when model parameters are known and unknown. Additionally, we introduce and prove consistency of a related, more scalable restricted-focus ML vertex nomination scheme. Finally, we incorporate vertex and edge features into ML-based vertex nomination and briey explore the empirical effectiveness of this approach.

关键词： graph inference graph matching graph mining stochastic block model vertex nomination

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Microwave spectro-polarimetry of matter and radiation across space and time

arXiv

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arXiv 2019年

作者： Delabrouille, Jacques Abitbol, Maximilian H. Aghanim, Nabila Ali-Haïmoud, Yacine Alonso, David Alvarez, Marcelo Banday, Anthony J. Bartlett, James G. Baselmans, Jochem Basu, Kaustuv Battaglia, Nicholas Climent, José Ramón Bermejo Bernal, José L. Béthermin, Matthieu Bolliet, Boris Bonato, Matteo Bouchet, François R. Breysse, Patrick C. Burigana, Carlo Cai, Zhen-Yi Chluba, Jens Churazov, Eugene Dannerbauer, Helmut de Bernardis, Paolo de Zotti, Gianfranco Valentino, Eleonora Di Dimastrogiovanni, Emanuela Endo, Akira Erler, Jens Ferraro, Simone Finelli, Fabio Fixsen, Dale Hanany, Shaul Hart, Luke Hernández-Monteagudo, Carlos Hill, J. Colin Hotinli, Selim C. Karatsu, Kenichi Karkare, Kirit Keating, Garrett K. Khabibullin, Ildar Kogut, Alan Kohri, Kazunori Kovetz, Ely D. Lagache, Guilaine Lesgourgues, Julien Madhavacheril, mathew Maffei, Bruno Mandolesi, Nazzareno Martins, Carlos Masi, Silvia mather, John Melin, Jean-Baptiste Dizgah, Azadeh Moradinezhad Mroczkowski, Tony Mukherjee, Suvodip Nagai, Daisuke Negrello, Mattia Palanque-Delabrouille, Nathalie Paoletti, Daniela Patil, Subodh P. Piacentini, Francesco Raghunathan, Srinivasan Ravenni, Andrea Remazeilles, mathieu Revéret, Vincent Rodriguez, Louis Rotti, Aditya Martin, Jose-Alberto Rubiño Sayers, Jack Scott, Douglas Silk, Joseph Silva, Marta Souradeep, Tarun Sugiyama, Naonori Sunyaev, Rashid Switzer, Eric R. Tartari, Andrea Trombetti, Tiziana Zubeldia, Íñigo CNRS/IN2P3 Université Paris Diderot Paris Cedex 1375205 France IRFU CEA Université Paris Saclay Gif-sur-Yvette91191 France University of Oxford Denys Wilkinson Building Keble Road OxfordOX1 3RH United Kingdom Université Paris-Sud Bâtiment 121 Orsay91405 France Center for Cosmology and Particle Physics Department of Physics New York University New YorkNY10003 United States School of Physics and Astronomy Cardiff University The Parade CardiffCF24 3AA United Kingdom Berkeley Center for Cosmological Physics University of California BerkeleyCA94720 United States Lawrence Berkeley National Laboratory One Cyclotron Road BerkeleyCA94720 United States Institut de Recherche en Astrophysique et Planétologie 9 av du Colonel Roche BP 44346 Toulouse Cedex 431028 France Jet Propulsion Laboratory California Institute of Technology 4800 Oak Grove Drive PasadenaCA91109 United States Faculty of Electrical Eng. Math. and Computer Sc. Delft Univ. of Technology Mekelweg 4 Delft2628 CD Netherlands SRON Netherlands Institute for Space Research Sorbonnelaan 2 Utrecht3584 CA Netherlands Argelander-Institut für Astronomie Universität Bonn Auf dem Hügel 71 BonnD-53121 Germany Department of Astronomy Cornell University IthacaNY14853 United States INAF - Osservatorio di Astrofisica e Scienza dello Spazio Via Gobetti 101 BolognaI-40129 Italy ICC University of Barcelona IEEC-UB Martí i Franques 1 BarcelonaE08028 Spain Aix Marseille Université CNRS CNES LAM Marseille France Jodrell Bank Centre for Astrophysics Dept. of Physics & Astronomy University of Manchester ManchesterM13 9PL United Kingdom INAF - Istituto di Radioastronomia Via Piero Gobetti 101 BolognaI-40129 Italy INAF - Osservatorio Astronomico di Padova Vicolo Osservatorio 5 PadovaI-35122 Italy Institut d’Astrophysique de Paris 98 bis Boulevard Arago Paris75014 France Canadian Institute for Theoretical Astrophysics University of Toronto ONM5S 3H8 Canada CAS Key Laboratory for

In the past few decades, a standard model of cosmology, ΛCDM, has emerged. According to our understanding, our Universe is about 13.8 billion years old, and expanded from an initial hot and dense state. Baryonic matter accounts for 5% of its present matter-energy content, non-baryonic dark matter for about 25%, and some unknown form of energy with negative pressure, dubbed dark energy, for the remaining 70%. The galaxies and clusters of galaxies that we observe today form by the gravitational collapse of tiny primordial fluctuations of the spacetime metric, thought to originate from an early stage of fast accelerated expansion, known as cosmic inflation. But very fundamental questions remain unanswered: we do not know what the dark matter and dark energy are, whether dark matter interacts, or if extra light particles exist. We are unsure whether inflation did indeed take place and exactly what physics was at work in the very early Universe. We still have to reconcile the laws of gravitation with the standard model of particle interactions – both of which are known to be incomplete and require extensions to explain existing observations. We do not know the topology of the Universe, or whether it is finite or infinite. We do not fully understand how structure forms, or why some structures on small scales appear to be incompatible with ΛCDM predictions. We do not have a convincing explanation for anomalies in the large-scale statistics of cosmic microwave background (CMB) anisotropies, except invoking chance multipole alignments and excursions in tails of the realization of a Gaussian random field. The distribution of matter and energy in the Universe, by virtue of being the product of physical laws and their effect on the Universe’s constituents, encodes answers to these questions. We thus propose to conduct an unprecedented full census of this distribution, over scales from one arcminute to the entire sky, and over 99% of cosmic history. The census will be carried ou

关键词： Galaxies

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Foreword

Proceedings of the 2016 International Conference on Image Pr...

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Proceedings of the 2016 International Conference on Image Processing, computer Vision, and Pattern Recognition, IPCV 2016 2016年

作者： Abd-Wahab, Mohd Helmy Al-Bakry, Abbas Al-Holou, Nizar Arabnia, Hamid R. Bhattacharya, Mahua Martinez Castillo, Juan Jose Daimi, Kevin Deligiannidis, Leonidas Djoudi, Lamia Atma Duong, Trung Eshaghian-Wilner, Mary Mehrnoosh Gravvanis, George A. Huang, Ruizhu Jandieri, George Kim, Byung-Gyu Kim, Tai-hoon Korovin, Iakov Lai, Guoming Lee, Hyo Jong Bin Mansor, Muhammad Naufal Marsh, Andrew Mostafaeipour, Ali Park, James J. Patil, Shashikant Ponalagusamy, R. Schaefer, Gerald Singh, Akash Solo, Ashu M.G. Swee, Sim Kok Thomas, Jaya Tinetti, Fernando G. Vladimir, Hahanov Wang, Shiuh-Jeng Yang, Mary Yoe, Hyun You, Jane Zhao, Wenbing Department of Computer Engineering University Tun Hussein Onn Malaysia Malaysia University of IT and Communications Baghdad Iraq Electrical and Computer Engineering Department IEEE/SEM-Computer Chapter University of Detroit Mercy DetroitMI United States University of Georgia United States ABV Indian Institute of Information Technology and Management MHRD Government of India India Acantelys Alan Turing Nikola Tesla Research Group and GIPEB Universidad Nacional Abierta Venezuela Computer Science and Software Engineering Programs Department of Mathematics Computer Science and Software Engineering University of Detroit Mercy DetroitMI United States Department of Computer Information Systems Wentworth Institute of Technology BostonMA United States Synchrone Technologies France Rutgers University State University of New Jersey New Jersey United States University of Southern California California United States Electrical Engineering University of California Los Angeles Los Angeles [UCLA CA United States Advanced Scientific Computing Applied Math and Applications Research Group Applied Mathematics and Numerical Computing and Department of ECE School of Engineering Democritus University of Thrace Xanthi Greece Texas Advanced Computing Center University of Texas AustinTX United States Georgian Technical University Tbilisi Georgia Institute of Cybernetics Georgian Academy of Science Georgia Multimedia Processing CommunicationsLab.[MPCL Department of Computer Science and Engineering College of Engineering SunMoon University Korea Republic of School of Information and Computing Science University of Tasmania Australia Southern Federal University Russia Computer Science and Technology Sun Yat-Sen University Guangzhou China Center for Advanced Image and Information Technology Division of Computer Science and Engineering Chonbuk National University Korea Republic of Faculty of Engineering Technology Kampus Uniciti Alam Universiti Malaysia Perlis UniMAP Malaysi

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