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Articles 61 - 90 of 141
Full-Text Articles in Numerical Analysis and Scientific Computing
Cooperation In Delay-Tolerant Networks With Wireless Energy Transfer: Performance Analysis And Optimization, Dusit Niyato, Ping Wang, Hwee-Pink Tan, Walid Saad, Dong In Kim
Cooperation In Delay-Tolerant Networks With Wireless Energy Transfer: Performance Analysis And Optimization, Dusit Niyato, Ping Wang, Hwee-Pink Tan, Walid Saad, Dong In Kim
Research Collection School Of Computing and Information Systems
We consider a delay-tolerant network (DTN) whose mobile nodes are assigned to collect packets from data sources and deliver them to a sink (i.e., a gateway). Each mobile node operates by using energy transferred wirelessly from the gateway. For such a network, two main issues are studied. First, when a mobile node is at the data source, this node must decide on whether to accept the packet received from the data source or not. In contrast, whenever a mobile node is at the gateway, it has to decide on whether to transmit the packets collected from the data sources or …
Deep Learning For Just-In-Time Defect Prediction, Xinli Yang, David Lo, Xin Xia, Yun Zhang, Jianling Sun
Deep Learning For Just-In-Time Defect Prediction, Xinli Yang, David Lo, Xin Xia, Yun Zhang, Jianling Sun
Research Collection School Of Computing and Information Systems
Defect prediction is a very meaningful topic, particularly at change-level. Change-level defect prediction, which is also referred as just-in-time defect prediction, could not only ensure software quality in the development process, but also make the developers check and fix the defects in time. Nowadays, deep learning is a hot topic in the machine learning literature. Whether deep learning can be used to improve the performance of just-in-time defect prediction is still uninvestigated. In this paper, to bridge this research gap, we propose an approach Deeper which leverages deep learning techniques to predict defect-prone changes. We first build a set of …
Distributed Caching Using The Htcondor Cached, Derek J. Weitzel, Brian Bockelman, David Swanson
Distributed Caching Using The Htcondor Cached, Derek J. Weitzel, Brian Bockelman, David Swanson
Holland Computing Center: Faculty Publications
A batch processing job in a distributed system has three clear steps, stage-in, execution, and stage-out. As data sizes have increased, the stage-in time has also increased. In order to optimize stage-in time for shared inputs, we propose the CacheD, a caching mechanism for high throughput computing. Along with caching on worker nodes for rapid transfers, we also introduce a novel transfer method to distribute shared caches to multiple worker nodes utilizing BitTorrent. We show that our caching method significantly improves workflow completion times by minimizing stage-in time while being non-intrusive to the computational resources, allowing for opportunistic resources to …
Automatic Video Self Modeling For Voice Disorder, Ju Shen, Changpeng Ti, Anusha Raghunathan, Sen-Ching S. Cheung, Rita Patel
Automatic Video Self Modeling For Voice Disorder, Ju Shen, Changpeng Ti, Anusha Raghunathan, Sen-Ching S. Cheung, Rita Patel
Computer Science Faculty Publications
Video self modeling (VSM) is a behavioral intervention technique in which a learner models a target behavior by watching a video of him- or herself. In the field of speech language pathology, the approach of VSM has been successfully used for treatment of language in children with Autism and in individuals with fluency disorder of stuttering. Technical challenges remain in creating VSM contents that depict previously unseen behaviors. In this paper, we propose a novel system that synthesizes new video sequences for VSM treatment of patients with voice disorders. Starting with a video recording of a voice-disorder patient, the proposed …
No Thermal Anomalies In The Mantle Transition Zone Beneath An Incipient Continental Rift: Evidence From The First Receiver Function Study Across The Okavango Rift Zone, Botswana, Youqiang Yu, Kelly H. Liu, M. Moidaki, Cory A. Reed, Stephen S. Gao
No Thermal Anomalies In The Mantle Transition Zone Beneath An Incipient Continental Rift: Evidence From The First Receiver Function Study Across The Okavango Rift Zone, Botswana, Youqiang Yu, Kelly H. Liu, M. Moidaki, Cory A. Reed, Stephen S. Gao
Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works
Mechanisms leading to the initiation and early-stage development of continental rifts remain enigmatic, in spite of numerous studies. Among the various rifting models, which were developed mostly based on studies of mature rifts, far-field stresses originating from plate interactions (passive rifting) and nearby active mantle upwelling (active rifting) are commonly used to explain rift dynamics. Situated atop of the hypothesized African Superplume, the incipient Okavango Rift Zone (ORZ) of northern Botswana is ideal to investigate the role of mantle plumes in rift initiation and development, as well as the interaction between the upper and lower mantle. The ORZ developed within …
Interference Effects For Intermediate Energy Electron-Impact Ionization Of H₂ And N₂ Molecules, Zehra Nur Ozer, Hari Chaluvadi, Don H. Madison, Mevlut Dogan
Interference Effects For Intermediate Energy Electron-Impact Ionization Of H₂ And N₂ Molecules, Zehra Nur Ozer, Hari Chaluvadi, Don H. Madison, Mevlut Dogan
Physics Faculty Research & Creative Works
We have studied electron impact ionization of H2 and N2 molecules at intermediate energies to look for possible two center interference effects experimentally and theoretically. Here we report a study of the interference factor I for 250 eV electron-impact ionization. The experimental measurements are performed using a crossed-beam-type electron-electron coincidence spectrometer and theoretical calculations are obtained using the Molecular Three Body Distorted Wave Approximation (M3DW). We found that the I-factor demonstrated strong evidence for two-center interference effects for both H2 and N2. We also found that the I-factor is more sensitive to projectile angular scans …
Improving Patient Flow With Data-Driven Patient Prioritization Method In The Emergency Department, Kar Way Tan, Sean Shao Wei Lam
Improving Patient Flow With Data-Driven Patient Prioritization Method In The Emergency Department, Kar Way Tan, Sean Shao Wei Lam
Research Collection School Of Computing and Information Systems
We aim to improve the length-of-stay (LOS) of patients in the Emergency Department (ED) ambulatory care area. We propose the use of real-time computerized physician order entry data and ED patient flow management system to estimate the consultation time of patients re-entering the queue to consult a doctor again after receiving treatment or results of tests. The estimation allows decision-makers to apply dynamic prioritization strategies that help the ED to identify patients who can complete their ED treatment process quickly, freeing up resources in the ED and lowering overall LOS.
Structured Learning From Heterogeneous Behavior For Social Identity Linkage, Siyuan Liu, Shuhui Wang, Feida Zhu
Structured Learning From Heterogeneous Behavior For Social Identity Linkage, Siyuan Liu, Shuhui Wang, Feida Zhu
Research Collection School Of Computing and Information Systems
Social identity linkage across different social media platforms is of critical importance to business intelligence by gaining from social data a deeper understanding and more accurate profiling of users. In this paper, we propose a solution framework, HYDRA, which consists of three key steps: (I) we model heterogeneous behavior by long-term topical distribution analysis and multi-resolution temporal behavior matching against high noise and information missing, and the behavior similarity are described by multi-dimensional similarity vector for each user pair; (II) we build structure consistency models to maximize the structure and behavior consistency on users' core social structure across different platforms, …
Message Passing For Collective Graphical Models, Tao Sun, Daniel Sheldon, Akshat Kumar
Message Passing For Collective Graphical Models, Tao Sun, Daniel Sheldon, Akshat Kumar
Research Collection School Of Computing and Information Systems
Collective graphical models (CGMs) are a formalism for inference and learning about a population of independent and identically distributed individuals when only noisy aggregate data are available. We highlight a close connection between approximate MAP inference in CGMs and marginal inference in standard graphical models. The connection leads us to derive a novel Belief Propagation (BP) style algorithm for collective graphical models. Mathematically, the algorithm is a strict generalization of BP—it can be viewed as an extension to minimize the Bethe free energy plus additional energy terms that are non-linear functions of the marginals. For CGMs, the algorithm is much …
Real Time Mission Planning, Emad William Saad, Stefan Richard Bieniawski, Paul Edward Riley Pigg, John Lyle Vian, Paul Michael Robinette, Donald C. Wunsch
Real Time Mission Planning, Emad William Saad, Stefan Richard Bieniawski, Paul Edward Riley Pigg, John Lyle Vian, Paul Michael Robinette, Donald C. Wunsch
Electrical and Computer Engineering Faculty Research & Creative Works
The different advantageous embodiments provide a system comprising a number of computers, a graphical user interface, first program code stored on the computer, and second program code stored on the computer. The graphical user interface is executed by a computer in the number of computers. The computer is configured to run the first program code to define a mission using a number of mission elements. The computer is configured to run the second program code to generate instructions for a number of assets to execute the mission and monitor the number of assets during execution of the mission.
Preface, Gennady Fridman, Jeremy Levesley, Ivan Tyukin, Donald C. Wunsch
Preface, Gennady Fridman, Jeremy Levesley, Ivan Tyukin, Donald C. Wunsch
Electrical and Computer Engineering Faculty Research & Creative Works
In August 2014 a conference on “Model reduction across disciplines” was held in Leicester, UK. As a scientific field, model reduction is an important part of mathematical modelling and data analysis with very wide areas of applications. The main scientific goal of the conference was to facilitate interdisciplinary discussion of model reduction and coarse-graining methodologies in order to reveal their general mathematical nature. This time, however, the conference had an additional personal and more profound mission – it was dedicated to the 60th birthday of Professor Alexander Gorban (albeit with some delay) whose fantastic achievements in applying model reduction techniques …
Changes In R, R Core Team
Changes In R, R Core Team
The R Journal
CHANGES IN R 3.2.1
CHANGES IN R 3.2.0
CHANGES IN R 3.1.3
Changes On Cran, Kurt Hornik, Achim Zeileis
Changes On Cran, Kurt Hornik, Achim Zeileis
The R Journal
New packages in CRAN task views
New contributed packages
Other changes
R Foundation News, Kurt Hornik
R Foundation News, Kurt Hornik
The R Journal
Donations
New Supporting Institutions
New Supporting Members
Identifying Complex Causal Dependencies In Configurational Data With Coincidence Analysis, Michael Baumgartner, Alrik Thiem
Identifying Complex Causal Dependencies In Configurational Data With Coincidence Analysis, Michael Baumgartner, Alrik Thiem
The R Journal
We present cna, a package for performing Coincidence Analysis (CNA). CNA is a configurational comparative method for the identification of complex causal dependencies—in particular, causal chains and common cause structures—in configurational data. After a brief introduction to the method’s theoretical background and main algorithmic ideas, we demonstrate the use of the package by means of an artificial and a real-life data set. Moreover, we outline planned enhancements of the package that will further increase its applicability.
Fslr: Connecting The Fsl Software With R, John Muschelli, Elizabeth Sweeney, Martin Lindquist, Ciprian Crainiceanu
Fslr: Connecting The Fsl Software With R, John Muschelli, Elizabeth Sweeney, Martin Lindquist, Ciprian Crainiceanu
The R Journal
We present the package fslr, a set of R functions that interface with FSL (FMRIB Software Library), a commonly-used open-source software package for processing and analyzing neuroimaging data. The fslr package performs operations on ‘nifti’ image objects in R using command-line functions from FSL, and returns R objects back to the user. fslr allows users to develop image processing and analysis pipelines based on FSL functionality while interfacing with the functionality provided by R. We present an example of the analysis of structural magnetic resonance images, which demonstrates how R users can leverage the functionality of FSL without switching …
The R Journal (June 2015) 7(1): Complete Issue, The R Foundation
The R Journal (June 2015) 7(1): Complete Issue, The R Foundation
The R Journal
Editorial, Bettina Grün
Contributed Research Articles
Peptides: A Package for Data Mining of Antimicrobial Peptides, Daniel Osorio, Paola Rondón-Villarreal, and Rodrigo Torres
fanplot: An R Package for Visualising Sequential Distributions, Guy J. Abel
sparkTable: Generating Graphical Tables for Websites and Documents with R, Alexander Kowarik, Bernhard Meindl, and Matthias Templ
rdrobust: An R Package for Robust Nonparametric Inference in Regression-Discontinuity Designs, Sebastian Calonico, Matias D. Cattaneo, and Rocío Titiunik
Frames2: A Package for Estimation in Dual Frame Surveys, Antonio Arcos, David Molina, Maria Giovanna Ranalli, and María del Mar Rueda
The Complex Multivariate Gaussian Distribution, Robin K. S. Hankin
sae: …
R As An Environment For Reproducible Analysis Of Dna Amplification Experiments, Stefan Rödiger, Michał Burdukiewicz, Konstantin Blagodatskikh, Michael Jahn, Peter Schierack
R As An Environment For Reproducible Analysis Of Dna Amplification Experiments, Stefan Rödiger, Michał Burdukiewicz, Konstantin Blagodatskikh, Michael Jahn, Peter Schierack
The R Journal
There is an ever-increasing number of applications, which use quantitative PCR (qPCR) or digital PCR (dPCR) to elicit fundamentals of biological processes. Moreover, quantitative isothermal amplification (qIA) methods have become more prominent in life sciences and point-of-care diagnostics. Additionally, the analysis of melting data is essential during many experiments. Several software packages have been developed for the analysis of such datasets. In most cases, the software is either distributed as closed source software or as monolithic block with little freedom to perform highly customized analysis procedures. We argue, among others, that R is an excellent foundation for reproducible and transparent …
Sae: An R Package For Small Area Estimation, Isabel Molina, Yolanda Marhuenda
Sae: An R Package For Small Area Estimation, Isabel Molina, Yolanda Marhuenda
The R Journal
We describe the R package sae for small area estimation. This package can be used to obtain model-based estimates for small areas based on a variety of models at the area and unit levels, along with basic direct and indirect estimates. Mean squared errors are estimated by analytical approximations in simple models and applying bootstrap procedures in more complex models. We describe the package functions and show how to use them through examples.
Frames2: A Package For Estimation In Dual Frame Surveys, Antonio Arcos, David Molina, Maria Giovanna Ranalli, Maria Del Mar Rueda
Frames2: A Package For Estimation In Dual Frame Surveys, Antonio Arcos, David Molina, Maria Giovanna Ranalli, Maria Del Mar Rueda
The R Journal
Data from complex survey designs require special consideration with regard to estimation of finite population parameters and corresponding variance estimation procedures, as a consequence of significant departures from the simple random sampling assumption. In the past decade a number of statistical software packages have been developed to facilitate the analysis of complex survey data. All these statistical software packages are able to treat samples selected from one sampling frame containing all population units. Dual frame surveys are very useful when it is not possible to guarantee a complete coverage of the target population and may result in considerable cost savings …
Sparktable: Generating Graphical Tables For Websites And Documents With R, Alexander Kowarik, Bernhard Meindl, Matthias Templ
Sparktable: Generating Graphical Tables For Websites And Documents With R, Alexander Kowarik, Bernhard Meindl, Matthias Templ
The R Journal
Visual analysis of data is important to understand the main characteristics, main trends and relationships in data sets and it can be used to assess the data quality. Using the R package sparkTable, statistical tables holding quantitative information can be enhanced by including spark-type graphs such as sparklines [] and sparkbars [].
These kind of graphics are well-known in literature and are considered as simple, intense and illustrative graphs that are small enough to fit in a single line. Thus, they can easily enrich tables and texts with additional information in a comprehensive visual way.
The R package sparkTable …
Fanplot: An R Package For Visualising Sequential Distributions, Guy J. Abel
Fanplot: An R Package For Visualising Sequential Distributions, Guy J. Abel
The R Journal
Fan charts, first developed by the Bank of England in 1996, have become a standard method for visualising forecasts with uncertainty. Using shading fan charts focus the attention towards the whole distribution away from a single central measure. This article describes the basics of plotting fan charts using an R add-on package alongside some additional methods for displaying sequential distributions. Examples are based on distributions of both estimated parameters from a time series model and future values with uncertainty.
The Gridgraphics Package, Paul Murrell
The Gridgraphics Package, Paul Murrell
The R Journal
The gridGraphics package provides a function, grid.echo(), that can be used to convert a plot drawn with the graphics package to a visually identical plot drawn using grid. This conversion provides access to a variety of grid tools for making customisations and additions to the plot that are not possible with the graphics package/
Peptides: A Package For Data Mining Of Antimicrobial Peptides, Daniel Osorio, Paola Rondón-Villarreal, Rodrigo Torres
Peptides: A Package For Data Mining Of Antimicrobial Peptides, Daniel Osorio, Paola Rondón-Villarreal, Rodrigo Torres
The R Journal
Antimicrobial peptides (AMP) are a promising source of antibiotics with a broad spectrum activity against bacteria and low incidence of developing resistance. The mechanism by which an AMPexecutes its function depends on a set of computable physicochemical properties from the amino acid sequence. The Peptides package was designed to allow the quick and easy computation of ten structural characteristics own of the antimicrobial peptides, with the aim of generating data to increase the accuracy in classification and design of new amino acid sequences. Moreover, the options to read and plot XVG output files from GROMACS molecular dynamics package are included.
Correspondence Analysis On Generalised Aggregated Lexical Tables (Ca-Galt) In The Factominer Package, Belchin Kostov, Mónica Bécue-Bertaut, François Husson
Correspondence Analysis On Generalised Aggregated Lexical Tables (Ca-Galt) In The Factominer Package, Belchin Kostov, Mónica Bécue-Bertaut, François Husson
The R Journal
Correspondence analysis on generalised aggregated lexical tables (CA-GALT) is a method that generalizes classical CA-ALT to the case of several quantitative, categorical and mixed variables. It aims to establish a typology of the external variables and a typology of the events from their mutual relationships. In order to do so, the influence of external variables on the lexical choices is untangled cancelling the associations among them, and to avoid the instability issued from multicollinearity, they are substituted by their principal components. The CaGalt function, implemented in the FactoMineR package, provides numerous numerical and graphical outputs. Confidence ellipses are also provided …
Rdrobust: An R Package For Robust Nonparametric Inference In Regression-Discontinuity Designs, Sebastian Calonico, Matias D. Cattaneo, Rocío Titiunik
Rdrobust: An R Package For Robust Nonparametric Inference In Regression-Discontinuity Designs, Sebastian Calonico, Matias D. Cattaneo, Rocío Titiunik
The R Journal
This article describes the R package rdrobust, which provides data-driven graphical and in ference procedures for RD designs. The package includes three main functions: rdrobust, rdbwselect and rdplot. The first function (rdrobust) implements conventional local-polynomial RD treatment effect point estimators and confidence intervals, as well as robust bias-corrected confidence intervals, for average treatment effects at the cutoff. This function covers sharp RD, sharp kink RD, fuzzy RD and fuzzy kink RD designs, among other possibilities. The second function (rdbwselect) implements several bandwidth selectors proposed in the RD literature. The third function (rdplot) provides data-driven optimal choices of evenly-spaced and …
News From The Bioconductor Project, Bioconductor Team
News From The Bioconductor Project, Bioconductor Team
The R Journal
The Bioconductor project provides tools for the analysis and comprehension of high throughput genomic data. The 1024 software packages available in Bioconductor can be viewed at http://bioconductor.org/packages/. Navigate packages using ‘biocViews’ terms and title search. Each package has an html page with a description, links to vignettes, reference manuals, and usage statistics. Start using Bioconductor version 3.1 by installing R 3.2.1 and evaluating the commandS
Implementing Persistent O(1) Stacks And Queues In R, Shawn T. O'Neil
Implementing Persistent O(1) Stacks And Queues In R, Shawn T. O'Neil
The R Journal
True to their functional roots, most R functions are side-effect-free, and users expect datatypes to be persistent. However, these semantics complicate the creation of efficient and dynamic data structures. Here, we describe the implementation of stack and queue data structures satisfying these conditions in R, available in the CRAN package rstackdeque. Guided by important work in purely functional languages, we look at both partially- and fully-persistent versions of queues, comparing their performance characteristics. Finally, we illustrate the usefulness of such dynamic structures with examples of generating and solving mazes.
Showtext: Using System Fonts In R Graphics, Yixuan Qiu
Showtext: Using System Fonts In R Graphics, Yixuan Qiu
The R Journal
This article introduces the showtext package that makes it easy to use system fonts in R graphics. Unlike other methods to embedfonts into graphics, showtext converts text into raster images or polygons, and then adds them to the plot canvas. This method produces platform-independent image files that do not rely on the fonts that create them. It supports a large number of font formats and Rgraphics devices, and meanwhile provides convenient features such as using web fonts and integrating with knitr. This article provides an elaborate introduction to the showtext package, including its design, usage, and examples.
Editorial, Bettina Grün
Editorial, Bettina Grün
The R Journal
On behalf of the editorial board, I am pleased to publish Volume 7, Issue 1 of the R Journal. This issue contains 16 contributed research articles. Each of them either presents an R package, a specific extension of an R package or applications using R packages available from the Comprehensive R Archive Network (CRAN, http:://CRAN.R-project.org). It thus provides a small insight into the wide variety of functionality covered currently by the more than 6800 packages available from CRAN.