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Computing in Science & Engineering

Issue 5 • Sept.-Oct. 2016

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Displaying Results 1 - 20 of 20
  • Front Cover 
  • Front Cover

    Publication Year: 2016, Page(s): c1
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  • Rock Stars of Big Data [Advertisement]

    Publication Year: 2016, Page(s): c2
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  • Masthead 
  • Masthead

    Publication Year: 2016, Page(s): 1
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  • Table of Contents 
  • Table of Contents

    Publication Year: 2016, Page(s):2 - 3
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  • From the Editors 
  • The Future of NSF Advanced Computing Infrastructure Revisited

    Publication Year: 2016, Page(s):4 - 7
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  • Guest Editors' Introduction 
  • Science as a Service [Guest editors' introduction]

    Publication Year: 2016, Page(s):8 - 9
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  • Science as a Service 
  • A Case for Data Commons: Toward Data Science as a Service

    Publication Year: 2016, Page(s):10 - 20
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1707 KB) | HTML iconHTML

    Data commons collocate data, storage, and computing infrastructure with core services and commonly used tools and applications for managing, analyzing, and sharing data to create an interoperable resource for the research community. An architecture for data commons is described, as well as some lessons learned from operating several large-scale data commons. View full abstract»

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  • MRICloud: Delivering High-Throughput MRI Neuroinformatics as Cloud-Based Software as a Service

    Publication Year: 2016, Page(s):21 - 35
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (4194 KB) | HTML iconHTML

    Image analysis tools for brain magnetic resonance imaging (MRI) have become increasingly important for computer-aided diagnosis that involves large amounts of medical image data. The authors of this article have endeavored to develop software tools to serve the clinical research community, starting with a stand-alone executable, hybrid local computation model for today's modern architecture of clo... View full abstract»

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  • WaveformECG: A Platform for Visualizing, Annotating, and Analyzing ECG Data

    Publication Year: 2016, Page(s):36 - 46
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (3752 KB) | HTML iconHTML

    The electrocardiogram (ECG) is the most commonly collected data in cardiovascular research because of the ease with which it can be measured and the fact that changes in ECG waveforms reflect underlying aspects of heart disease. Despite its ubiquity, there are no open, noncommercial platforms for interactive management, sharing, and analysis of these data. WaveformECG addresses this unmet need. Ac... View full abstract»

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    Publication Year: 2016, Page(s): 47
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  • Computational Chemistry 
  • Chemical Kinetics: A CS Perspective

    Publication Year: 2016, Page(s):48 - 55
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (458 KB) | HTML iconHTML

    Chemical kinetics has played a critical role in understanding phenomena such as global climate change and photochemical smog, and researchers use it to analyze chemical reactors and alternative fuels. When computing is applied to the development of detailed chemical kinetic models, it allows scientists to predict the behavior of these complex chemical systems. This overview discusses algorithmic t... View full abstract»

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  • Cloud Computing 
  • A Cloud-Based Seizure Alert System for Epileptic Patients That Uses Higher-Order Statistics

    Publication Year: 2016, Page(s):56 - 67
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1356 KB) | HTML iconHTML

    Epilepsy is a chronic disease that causes seizures. Automatic detection of a seizure before its occurrence could protect patients from accidents and potentially save their lives. This article proposes a framework that automatically predicts seizures by analyzing EEG signals. The wireless sensor technology captures brain signals, and cloud-based services are used to collect and analyze EEG data fro... View full abstract»

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  • Hybrid Systems 
  • The Feasibility of Amazon's Cloud Computing Platform for Parallel, GPU-Accelerated, Multiphase-Flow Simulations

    Publication Year: 2016, Page(s):68 - 77
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (532 KB) | HTML iconHTML

    The feasibility of running MPI-parallel, GPU-accelerated, multiphase flow simulations on Amazon's Elastic Compute Cloud (EC2) service is evaluated as an alternative computational resource. A cloud cluster on Amazon EC2 is compared to a conventional local high-performance computing cluster in terms of performance and cost. The steps necessary to set up a cloud cluster and acquire the appropriate ha... View full abstract»

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  • Computer Simulations 
  • Massive Computation for Understanding Core-Collapse Supernova Explosions

    Publication Year: 2016, Page(s):78 - 92
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (6872 KB) | HTML iconHTML

    How do massive stars explode? Progress toward the answer is driven by increases in compute power. Petascale supercomputers are enabling detailed 3D simulations of core-collapse supernovae that are elucidating the role of fluid instabilities, turbulence, and magnetic field amplification in supernova engines. View full abstract»

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  • IEEE Computer Society 2016 Call for Major Award Nominations

    Publication Year: 2016, Page(s): 93
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  • Leadership Computing 
  • Multiyear Simulation Study Provides Breakthrough in Membrane Protein Research

    Publication Year: 2016, Page(s):94 - 97
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  • Visualization Corner 
  • Beyond the Third Dimension: Visualizing High-Dimensional Data with Projections

    Publication Year: 2016, Page(s):98 - 107
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  • The Last Word 
  • Computers in Cars

    Publication Year: 2016, Page(s): 108
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  • Back Covers 
  • Call for Nominees: Education Awards Nominations

    Publication Year: 2016, Page(s): c3
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  • Rock Stars of Pervasive, Predictive Analytics [Advertisement]

    Publication Year: 2016, Page(s): c4
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Aims & Scope

CS&E magazine emphasizes articles that help define the field as the interface among the applications (in science and engineering), algorithms (numerical and symbolic), system software, and computer architecture.

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
George K. Thiruvathukal
Loyola University