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IEEE International Conference on Big Data

作者： Saman Biookaghazadeh Yiqi Xu Shujia Zhou Ming Zhao Informatics and Decision Systems Engineering Arizona State University School of Computing and Information Sciences Florida International University Northrop Grumman Information Technology

Big-data systems are increasingly important for solving the data-driven problems in many science domains including geosciences. However, existing big-data systems cannot support the self-describing data formats such as NetCDF which are commonly used by scientific communities for data distribution and sharing. This limitation presents a serious hurdle to the further adoption of big-data systems by science domains and prevents scientific users from leveraging these systems to improve their productivity. This paper presents a solution to this problem by enabling big-data systems to directly store and process scientific data. Specifically, it enables Hadoop to efficiently store NetCDF data on HDFS and process them in MapReduce using convenient APIs. It also enables Hive to support standard queries on NetCDF data, transparently to users. The paper also presents an evaluation of the proposed solution using several representative queries on a typical geoscientific dataset. The results show that the proposed approach achieves substantial speedup (up to 20 times) and space saving (83% reduction), compared to the traditional approach which has to convert NetCDF data to CSV format for Hadoop and Hive to use them.

关键词： Meteorology Geology File systems Big data Computational modeling Data models Distributed databases

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A dynamic modularity based community detection algorithm for large-scale networks: DSLM

A dynamic modularity based community detection algorithm for...

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International Conference on Advances in Social Network Analysis and Mining, ASONAM

作者： Riza Aktunc Ismail Hakki Toroslu Mert Ozer Hasan Davulcu Computer Engineering Department Middle East Technical University Ankara Turkey School of Computing Informatics Decision Systems Engineering Arizona State University Tempe USA

ISBN: (纸本)9781509020942

In this work, a new fast dynamic community detection algorithm for large scale networks is presented. Most of the previous community detection algorithms are designed for static networks. However, large scale social networks are dynamic and evolve frequently over time. To quickly detect communities in dynamic large scale networks, we proposed dynamic modularity optimizer framework (DMO) that is constructed by modifying well-known static modularity based community detection algorithm. The proposed framework is tested using several different datasets. According to our results, community detection algorithms in the proposed framework perform better than static algorithms when large scale dynamic networks are considered.

关键词： Heuristic algorithms Mathematical model Social network services Detection algorithms Electronic mail GSM Image edge detection

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Crowdsourcing change

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Progress in informatics 2014年第11期11卷 3-7页

作者： Sundaram, Hari School of Computing Informatics and Decision Systems Engineering School of Arts Media and Engineering Arizona State University United States

This paper discusses the role of computing in engendering cooperation in social dilemmas such as sustainability and public health. These cooperative dilemmas exist at a large scale, within heterogeneous populations. Motivated by analysis of cooperation from empirical field studies, we argue that an integrative computational framework that analyzes social signals and verifies behaviors through smartphone sensors can shape and mold individual decisions to cooperate. We discuss four interconnected technical challenges and example solutions. The challenges include community discovery algorithms for construction of small homogenous groups, persuasion of individuals in resource constrained networks, activity monitoring in the wild and detection of large scale social coordination. We briefly discuss new applications that arise from a computational infrastructure for cooperation, including fighting childhood obesity, cybersecurity and improving public safety. © 2014 National Institute of informatics.

关键词： crowds networks multi-sensor integration society large-scale

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Web-Based Visualization of the Global Change Assessment Model 3

Web-Based Visualization of the Global Change Assessment Mode...

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3rd Workshop on Visualisation in Environmental Sciences, EnvirVis 2015 at EuroVis 2015

作者： Luo, W. Chang, Z. Kong, L. Link, R. Hejazi, M. Clarke, L. Maciejewski, R. School of Computing Informatics and Decision Systems Engineering Arizona State University TempeAZ United States Center for Science and the Imagination Arizona State University TempeAZ United States Joint Global Change Research Institute Pacific Northwest National Laboratory College ParkMD United States

ISBN: (纸本)9783905674859

The Global Change Assessment Model (GCAM) is an integrated assessment tool for exploring consequences and responses to global change. However, the current iteration of GCAM relies on NetCDF file outputs which need to be output from the model and then exported for visualization and analysis purposes. Such a requirement limits the uptake of this modeling platform for analysts that may wish to explore future scenarios. In this work, we present a web-based geovisual analytics interface for GCAM. Challenges of this work include enabling both domain expert and model experts to be able to functionally explore the model. We explore the use of various aggregation layers, coordinated views and how choices of icons can enhance the understanding of the underlying data. Our primary focus is on understanding the simulated impact of climate change on sectors of the global economy. To demonstrate our work, we present a case study which explores the potential impact that the China south-north water transportation project in the Yangtze River basin will have on projected water demands. © The Eurographics Association 2015.

关键词： Climate change

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Story detection using generalized concepts and relations

Story detection using generalized concepts and relations

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International Conference on Advances in Social Network Analysis and Mining, ASONAM

作者： Betul Ceran Nitesh Kedia Steven R. Corman Hasan Davulcu School of Computing Informatics and Decision Systems Engineering Arizona State University Tempe AZ Hugh Downs School of Human Communication Arizona State University Tempe AZ

ISBN: (纸本)9781509020942

A major challenge in automated text analysis is that different words are used for related concepts. Analyzing text at the surface level would treat related concepts (i.e. actors, actions, targets, and victims) as different objects, potentially missing common narrative patterns. Shallow parsers reveal semantic roles of words leading to subject-verb-object triplets. We developed a novel algorithm to extract information from triplets by clustering them into generalized concepts by utilizing syntactic criteria based on common contexts and semantic corpus-based statistical criteria based on "contextual synonyms". We show that generalized concepts representation of text (1) overcomes surface level differences (which arise when different keywords are used for related concepts) without drift, (2) leads to a higher-level semantic network representation of related stories, and (3) when used as features, they yield a significant 36% boost in performance for the story detection task.

关键词： Semantics Feature extraction Context Syntactics Social network services Clustering algorithms Merging

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Robot as a Service in computing Curriculum

Robot as a Service in Computing Curriculum

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International Symposium on Autonomous Decentralized systems (ISADAS)

作者： Yinong Chen Zhizheng Zhou School of Computing Informatics and Decision Systems Engineering Arizona State University Tempe AZ U.S.A. School of Finance Qilu University of Technology Shandong China

ISBN: (纸本)9781479982622

This paper reports the newly designed first computer science and first programming course CSE101 developed and taught at Arizona State University, and disseminated to many other universities, to address the enrollment crisis as reported by ACM CS Curriculum Committee Review Task Force in 2008. The course teaches the basic computer science and engineering concepts and gives the students the first programming experience through robotics programming. The initial curriculum and the ongoing improvement of the course are presented. The course started with its experiment environment using Microsoft Robotics Developer Studio, Visual Programming Language, and Lego Mind storms robots. The environment is extended to a Web-based programming environment and Intel architecture-based robots.

关键词： Robot sensing systems Robot programming Programming profession Springs Software

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Publisher Correction: The tuatara genome reveals ancient features of amniote evolution

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Nature 2020年第7823期585卷 E3页

作者： Neil J Gemmell Kim Rutherford Stefan Prost Marc Tollis David Winter J Robert Macey David L Adelson Alexander Suh Terry Bertozzi José H Grau Chris Organ Paul P Gardner Matthieu Muffato Mateus Patricio Konstantinos Billis Fergal J Martin Paul Flicek Bent Petersen Lin Kang Pawel Michalak Thomas R Buckley Melissa Wilson Yuanyuan Cheng Hilary Miller Ryan K Schott Melissa D Jordan Richard D Newcomb José Ignacio Arroyo Nicole Valenzuela Tim A Hore Jaime Renart Valentina Peona Claire R Peart Vera M Warmuth Lu Zeng R Daniel Kortschak Joy M Raison Valeria Velásquez Zapata Zhiqiang Wu Didac Santesmasses Marco Mariotti Roderic Guigó Shawn M Rupp Victoria G Twort Nicolas Dussex Helen Taylor Hideaki Abe Donna M Bond James M Paterson Daniel G Mulcahy Vanessa L Gonzalez Charles G Barbieri Dustin P DeMeo Stephan Pabinger Tracey Van Stijn Shannon Clarke Oliver Ryder Scott V Edwards Steven L Salzberg Lindsay Anderson Nicola Nelson Clive Stone Department of Anatomy University of Otago Dunedin New Zealand. neil.gemmell@otago.ac.nz. Department of Anatomy University of Otago Dunedin New Zealand. LOEWE-Center for Translational Biodiversity Genomics Senckenberg Museum Frankfurt Germany. South African National Biodiversity Institute National Zoological Garden Pretoria South Africa. School of Life Sciences Arizona State University Tempe AZ USA. School of Informatics Computing and Cyber Systems Northern Arizona University Flagstaff AZ USA. School of Fundamental Sciences Massey University Palmerston North New Zealand. Peralta Genomics Institute Oakland CA USA. School of Biological Sciences The University of Adelaide Adelaide South Australia Australia. Department of Ecology and Genetics - Evolutionary Biology Evolutionary Biology Centre (EBC) Uppsala University Uppsala Sweden. Department of Organismal Biology - Systematic Biology Evolutionary Biology Centre (EBC) Uppsala University Uppsala Sweden. Evolutionary Biology Unit South Australian Museum Adelaide South Australia Australia. Amedes Genetics Amedes Medizinische Dienstleistungen Berlin Germany. Museum für Naturkunde Berlin Leibniz-Institut für Evolutions- und Biodiversitätsforschung an der Humboldt-Universität zu Berlin Berlin Germany. Department of Earth Sciences Montana State University Bozeman MT USA. Department of Biochemistry University of Otago Dunedin New Zealand. European Molecular Biology Laboratory European Bioinformatics Institute Hinxton UK. Section for Evolutionary Genomics The GLOBE Institute Faculty of Health and Medical Sciences University of Copenhagen Copenhagen Denmark. Edward Via College of Osteopathic Medicine Blacksburg VA USA. Center for One Health Research Virginia-Maryland College of Veterinary Medicine Blacksburg VA USA. Institute of Evolution University of Haifa Haifa Israel. Manaaki Whenua - Landcare Research Auckland New Zealand. School of Biological Sciences The University of Auckland Auckland New Z

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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Erratum to: Theories in Business and Information systems engineering

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Business & Information systems engineering 2016年第5期58卷 327-328页

作者： Martin Bichler Ulrich Frank David Avison Julien Malaurent Peter Fettke Dirk Hovorka Jan Krämer Daniel Schnurr Benjamin Müller Leena Suhl Bernhard Thalheim Department of Informatics Technical University of Munich Garching/Munich Germany Chair of Information Systems and Enterprise Modelling Institute for Computer Science and Business Information Systems University of Duisburg-Essen Essen Germany Department of Information Systems Decision Sciences and Statistics ESSEC Business School Cergy Pontoise Cedex France German Research Center for Artificial Intelligence (DFKI GmbH) and Saarland University Saarbrücken Germany Business Information Systems The University of Sydney Business School The University of Sydney Sydney Australia Chair of Internet and Telecommunications Business Faculty of Business Administration and Economics University of Passau Passau Germany Innovation Management and Strategy Faculty of Economics and Business University of Groningen Groningen The Netherlands Decision Support and Operations Research Lab Department Business Information Systems Universität Paderborn Paderborn Germany Information Systems Engineering (ISE) Institut für Informatik Christian-Albrechts-Universität zu Kiel Kiel Germany

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Upper and Lower Bounds of Choice Number for Successful Channel Assignment in Cellular Networks

Upper and Lower Bounds of Choice Number for Successful Chann...

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IEEE International Conference on Communications

作者： Ran Wang Chenyang Zhou Anisha Mazumder Arun Das H. A. Kierstead Arunabha Sen School of Mathematical Sciences and Statistics Arizona State University School of Computing Informatics and Decision System Engineering Arizona State University

ISBN: (纸本)9781467364300

A cellular network is often modeled as a graph and the channel assignment problem is formulated as a coloring problem of the graph. Cellular graphs are used to model hexagonal cell structure of a cellular network. Assuming a 2-band buffering system where the interference does not extend beyond two cells away from the call originating cell, we study a version of the channel assignment problem in cellular graphs that been studied only minimally. In this version, each node has a fixed set of frequency channels where only a subset of which may be available at a given time for communication (as other channels may be busy). Assuming that only a subset of frequency channels are available for communication at each node, we try to determine the size of the smallest set of free channels in a node that will guarantee that each node of the cellular graph can be assigned a channel (from its own set of free channels) that will be interference free in a two band buffering system. The mathematical abstraction of this problem is known as the Choice Number computation problem and is closely related to the List Coloring problem in Graph Theory. In this paper we establish a lower and an upper bound of the distance-2 Choice Number of cellular graphs. In addition we also conduct extensive experimentation to study the impact of the availability of the number of free channels in a node to the percentage of the total number of nodes in the network that can be assigned an interference free channel in a two band buffering system.

关键词： Color Channel allocation Interference Mobile communication Mobile computing Wireless communication Upper bound

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On the smallest pseudo target set identification problem for targeted attack on interdependent power-communication networks

On the smallest pseudo target set identification problem for...

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MILCOM, Military Communications Conference

作者： Arun Das Chenyang Zhou Joydeep Banerjee Arunabha Sen Lloyd Greenwald School of Computing Informatics and Decision System Engineering Arizona State University Internet and Cybersecurity Research Department LGS Innovations

ISBN: (纸本)9781509000746

Recognizing the need for a deeper understanding of the interdependence between critical infrastructures, such as the power grid and the communication network, a number of models have been proposed and analyzed in the last few years. However, most of these proposed models are over simplified and fail to capture complex interdependencies that may exist between these critical infrastructures. The recently proposed Implicative Interdependency Model is able to capture these complex interdependencies involving conjunctive and disjunctive relationships to overcome most of these limitations. Due to the existing interdependencies between the power and communication networks, a failure involving a small set of power and/or communication network entities can trigger a cascading event, resulting in the failure of a much larger set of entities through the cascading failure process. This implies that an adversary with an intent of destroying a specific set of entities E' (real targets), no longer needs to make an effort to destroy E' directly, but instead identify a set of smaller entities E" (pseudo targets), whose destruction eventually leads to the destruction of the real target set E' due to the cascading failure process. A clever adversary will thus try to identify the smallest set of pseudo target entities E00, whose destruction eventually destroys E'. We refer to this problem as the Smallest Pseudo Target Set Identification Problem (SPTSIP). We divide the problem into four classes, and show that it is solvable in polynomial time for one class, and is NP-complete for others. We provide an approximation algorithm for the second class, and for the most general class, we provide an optimal solution using ILP, and a heuristic solution. We evaluate the efficacy of our heuristic using power and communication network data of Maricopa County, Arizona. The experiments show that our heuristic almost always produces near optimal results.

关键词： Communication networks Power system faults Power system protection Power grids Biological system modeling Complexity theory Target tracking

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