Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Numerical Analysis and Scientific Computing (747)
- Programming Languages and Compilers (716)
- Engineering (274)
- Computer Engineering (243)
- Life Sciences (87)
-
- Artificial Intelligence and Robotics (78)
- Social and Behavioral Sciences (69)
- Other Computer Sciences (67)
- Electrical and Computer Engineering (63)
- Databases and Information Systems (60)
- Graphics and Human Computer Interfaces (51)
- Education (44)
- Biochemistry, Biophysics, and Structural Biology (40)
- Library and Information Science (36)
- Software Engineering (35)
- Structural Biology (30)
- Arts and Humanities (29)
- Theory and Algorithms (28)
- Higher Education (25)
- Data Science (23)
- Environmental Sciences (21)
- Scholarly Communication (20)
- Bioinformatics (19)
- Digital Humanities (17)
- Digital Communications and Networking (16)
- Medicine and Health Sciences (16)
- Law (15)
- Plant Sciences (15)
- Keyword
-
- Machine learning (29)
- Artificial intelligence (15)
- Image analysis (12)
- Machine Learning (12)
- Digital libraries (11)
-
- Software engineering (11)
- Algorithms (10)
- Image processing (10)
- Software Engineering (10)
- Classification (9)
- Computer vision (9)
- Support vector machine (9)
- Higher education (8)
- Honors programs and colleges (8)
- Neural networks (8)
- Security (8)
- Simulation (8)
- Data mining (7)
- Deep learning (7)
- Eye tracking (7)
- Android (6)
- Artificial Intelligence (6)
- Computer science education (6)
- Evolution (6)
- Generative artificial intelligence (6)
- Interpolation (6)
- UAV (6)
- Wireless sensor networks (6)
- Computer Science (5)
- Deep Learning (5)
- Publication
-
- The R Journal (708)
- School of Computing: Conference and Workshop Papers (274)
- School of Computing: Faculty Publications (203)
- School of Computing: Dissertations, Theses, and Student Research (201)
- School of Computing: Technical Reports (129)
-
- 3-D Printed Model Structural Files (29)
- Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023– (29)
- Honors Program: Senior Projects (Public) (21)
- Copyright, Fair Use, Scholarly Communication, etc. (15)
- Holland Computing Center: Faculty Publications (10)
- Journal of the National Collegiate Honors Council Online Archive (9)
- University of Nebraska-Lincoln Libraries: Faculty Publications (7)
- Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research (6)
- University of Nebraska-Lincoln Libraries: Presentations (6)
- UCARE: Research Products (5)
- CDRH Grant Reports (4)
- Department of Agricultural Economics: Dissertations, Theses, and Student Research (4)
- Department of Agricultural and Biological Systems Engineering: Dissertations, Theses, and Student Research (4)
- Department of Earth and Atmospheric Sciences: Dissertations, Theses, and Student Research (4)
- Department of Agricultural and Biological Systems Engineering: Faculty Publications (3)
- Department of Construction Engineering and Management: Faculty Publications (3)
- Department of Electrical and Computer Engineering: Faculty Publications (3)
- Department of Mathematics: Dissertations, Theses, and Student Research (3)
- Department of Special Education and Communication Disorders: Faculty Publications (3)
- School of Natural Resources: Faculty Publications (3)
- Department of Computer Electronics and Engineering: Dissertations, Theses, and Student Research (2)
- Department of Mechanical and Materials Engineering: Dissertations, Theses, and Student Research (2)
- Department of Teaching, Learning, and Teacher Education: Faculty Publications (2)
- Department of Teaching, Learning, and Teacher Education: Theses and Other Student Research (2)
- E-JASL: Electronic Journal of Academic and Special Librarianship (1999-2009, Volumes 1-10) (2)
- Publication Type
Articles 841 - 870 of 1739
Full-Text Articles in Computer Sciences
Towards Building A Review Recommendation System That Trains Novices By Leveraging The Actions Of Experts, Shilpa Khanal
Towards Building A Review Recommendation System That Trains Novices By Leveraging The Actions Of Experts, Shilpa Khanal
School of Computing: Dissertations, Theses, and Student Research
Online reviews increase consumer visits, increase the time spent on the website, and create a sense of community among the frequent shoppers. Because of the importance of online reviews, online retailers such as Amazon.com and eOpinions provide detailed guidelines for writing reviews. However, though these guidelines provide instructions on how to write reviews, reviewers are not provided instructions for writing product-specific reviews. As a result, poorly-written reviews are abound and a customer may need to scroll through a large number of reviews, which could be up to 6000 pixels down from the top of the page, in order to find …
Connecting Program Synthesis And Reachability: Automatic Program Repair Using Test-Input Generation, Thanhvu Nguyen, Westley Weimer, Deepak Kapur, Stephanie Forrest
Connecting Program Synthesis And Reachability: Automatic Program Repair Using Test-Input Generation, Thanhvu Nguyen, Westley Weimer, Deepak Kapur, Stephanie Forrest
School of Computing: Technical Reports
We prove that certain formulations of program synthesis and reachability are equivalent. Specifically, our constructive proof shows the reductions between the template-based synthesis problem, which generates a program in a pre-specified form, and the reachability problem, which decides the reachability of a program location. This establishes a link between the two research fields and allows for the transfer of techniques and results between them.
To demonstrate the equivalence, we develop a program repair prototype using reachability tools. We transform a buggy program and its required specification into a specific program containing a location reachable only when the original program can …
Recognizing And Combating Cybercrime, Marcia L. Dority Baker
Recognizing And Combating Cybercrime, Marcia L. Dority Baker
Information Technology Services: Publications
Can You Spot the Scam?
Scams make great stories. Tales of Internet crime or other fraud make up some of Hollywood's most exciting thrillers. While cybercrime blockbusters are fun to watch on the big screen, cybercrime is a serious problem on campuses globally.
How many people do you know who are the victim of a scam (Internet or phone)? According to the FBI, cybercrime is a growing threat that affects individuals and businesses around the world. A recent Washington Post article reported that cybercrime cost the global economy $445 billion in 2014.
White Paper, Hd-51897-14, Image Analysis For Archival Discovery (Aida), October 2016, Elizabeth M. Lorang, Leen-Kiat Soh
White Paper, Hd-51897-14, Image Analysis For Archival Discovery (Aida), October 2016, Elizabeth M. Lorang, Leen-Kiat Soh
CDRH Grant Reports
With its Office of Digital Humanities Start-up Grant, the Image Analysis for Archival Discovery (Aida) team set out to further develop image analysis as a methodology for the identification and retrieval of items of relevance within digitized collections of historic materials.1 Specifically, we sought to identify poetic content within historic newspapers, using Chronicling America's newspapers (http://chroniclingamerica.loc.gov/) as our test case. The project activities we undertook—both those completed and those in process—support this goal and align well with the activities proposed in our original funding application and as approved by NEH. To achieve our goal of creating an image processing-based system …
Final Report, Hd-51897-14, Image Analysis For Archival Discovery (Aida), October 2016, Elizabeth M. Lorang, Leen-Kiat Soh
Final Report, Hd-51897-14, Image Analysis For Archival Discovery (Aida), October 2016, Elizabeth M. Lorang, Leen-Kiat Soh
CDRH Grant Reports
With its Office of Digital Humanities Start-up Grant, the Image Analysis for Archival Discovery (Aida) team set out to further develop image analysis as a methodology for the identification and retrieval of items of relevance within digitized collections of historic materials. Specifically, we sought to identify poetic content within historic newspapers, using Chronicling America's newspapers (http://chroniclingamerica.loc.gov/) as our test case. The project activities we undertook—both those completed and those in process—support this goal and align well with the activities proposed in our original funding application and as approved by NEH. To achieve our goal of creating an image processing-based system …
Changes In R, R Core Team
Changes In R, R Core Team
The R Journal
CHANGES IN R 3.3.1 patched
CHANGES IN R 3.3.1
CHANGES IN R 3.3.0
Changes On Cran, Kurt Hornik, Achim Zeileis
Changes On Cran, Kurt Hornik, Achim Zeileis
The R Journal
In the past 8 months,1322 new packages were added to the CRAN package repository. 43 packages were unarchived,48 archived,1 package had to be removed.The following shows the growth of the number of active packages in the CRAN package repository:
Nonparametric Tests For The Interaction In Two-Way Factorial Designs Using R, Jos Feys
Nonparametric Tests For The Interaction In Two-Way Factorial Designs Using R, Jos Feys
The R Journal
An increasing number of R packages include nonparametric tests for the interaction in two-way factorial designs. This paper briefly describes the different methods of testing and reports the resulting p-values of such tests on datasets for four types of designs: between, within, mixed, and pretest-posttest designs. Potential users are advised only to apply tests they are quite familiar with and not be guided by p-values for selecting packages and tests.
Using Decipher V2.0 To Analyze Big Biological Sequence Data In R, Erik S. Wright
Using Decipher V2.0 To Analyze Big Biological Sequence Data In R, Erik S. Wright
The R Journal
In recent years, the cost of DNA sequencing has decreased at a rate that has outpaced improvements in memory capacity. It is now common to collect or have access to many gigabytes of biological sequences. This has created an urgent need for approaches that analyze sequences in subsets without requiring all of the sequences to be loaded into memory at one time. It has also opened opportunities to improve the organization and accessibility of information acquired in sequencing projects. The DECIPHER package offers solutions to these problems by assisting in the curation of large sets of biological sequences stored in …
Scmamp: Statistical Comparison Of Multiple Algorithms In Multiple Problems, Borja Calvo, Guzmán Santafé
Scmamp: Statistical Comparison Of Multiple Algorithms In Multiple Problems, Borja Calvo, Guzmán Santafé
The R Journal
Comparing the results obtained by two or more algorithms in a set of problems is a central task in areas such as machine learning or optimization. Drawing conclusions from these comparisons may require the use of statistical tools such as hypothesis testing. There are some interesting papers that cover this topic. In this manuscript we present scmamp, an R package aimed at being a tool that simplifies the whole process of analyzing the results obtained when comparing algorithms, from loading the data to the production of plots and tables.
Comparing the performance of different algorithms is an essential step …
Swmpr: An R Package For Retrieving, Organizing, And Analyzing Environmental Data For Estuaries, Marcus W. Beck
Swmpr: An R Package For Retrieving, Organizing, And Analyzing Environmental Data For Estuaries, Marcus W. Beck
The R Journal
The System-Wide Monitoring Program (SWMP)was implemented in 1995 by the US National Estuarine Research Reserve System. This program has provided two decades of continuous monitoring data at over 140 fixed stations in 28 estuaries. However, the increasing quantity of data provided by the monitoring network has complicated broad-scale comparisons between systems and, in some cases, prevented simple trend analysis of water quality parameters at individual sites. This article describes the SWMPr package that provides several functions that facilitate data retrieval, organization, and analysis of time series data in the reserve estuaries. Previously unavailable functions for estuaries are also provided to …
Spatio-Temporal Interpolation Using Gstat, Benedikt Gräler, Edzer Pebesma, Gerard Heuvelink
Spatio-Temporal Interpolation Using Gstat, Benedikt Gräler, Edzer Pebesma, Gerard Heuvelink
The R Journal
We present new spatio-temporal geostatistical modelling and interpolation capabilities of the R package gstat. Various spatio-temporal covariance models have been implemented, such as the separable, product-sum, metric and sum-metric models. Inareal-world application we comparespatio temporal interpolations using these models with a purely spatial kriging approach. The target variable of the application is the daily mean PM10 concentration measured at rural air quality monitoring stations across Germany in 2005. R code for variogram fitting and interpolation is presented in this paper to illustrate the workflow of spatio-temporal interpolation using gstat. We conclude that the system works properly and that the …
Model Builder For Item Factor Analysis With Openmx, Joshua N. Pritikin, Karen M. Schmidt
Model Builder For Item Factor Analysis With Openmx, Joshua N. Pritikin, Karen M. Schmidt
The R Journal
We introduce a shiny web application to facilitate the construction of Item Factor Analysis (a.k.a. Item Response Theory) models using the OpenMx package. The web application assists with importing data, outcome recoding, and model specification. However, the app does not conduct any analysis but, rather, generates an analysis script. Generated Rmarkdown output serves dual purposes: to analyze a data set and demonstrate good programming practices. The app can be used as a teaching tool or as a starting point for custom analysis scripts.
Quickpsy: An R Package To Fit Psychometric Functions For Multiple Groups, Daniel Linares, Joan López-Moliner
Quickpsy: An R Package To Fit Psychometric Functions For Multiple Groups, Daniel Linares, Joan López-Moliner
The R Journal
quickpsy is a package to parametrically fit psychometric functions. In comparison with previous R packages, quickpsy was built to easily fit and plot data for multiple groups. Here, we describe the standard parametric model used to fit psychometric functions and the standard estimation of its parameters using maximum likelihood. We also provide examples of usage of quickpsy, including how allowing the lapse rate to vary can sometimes eliminate the bias in parameter estimation, but not in general. Finally, we describe some implementation details, such as how to avoid the problems associated to round-off errors in the maximisation of the …
Variable Clustering In High-Dimensional Linear Regression: The R Package Clere, Loïc Yengo, Julien Jacques, Christophe Biernacki, Mickael Canouil
Variable Clustering In High-Dimensional Linear Regression: The R Package Clere, Loïc Yengo, Julien Jacques, Christophe Biernacki, Mickael Canouil
The R Journal
Dimension reduction is one of the biggest challenges in high-dimensional regression models. We recently introduced a new methodology based on variable clustering as a means to reduce dimensionality. We present here the R package clere that implements some refinements of this methodology. An overview of the package functionalities as well as examples to run an analysis are described. Numerical experiments on real data were performed to illustrate the good predictive performance of our parsimonious method compared to standard dimension reduction approaches.
Maps, Coordinate Reference Systems And Visualising Geographic Data With Mapmisc, Patrick E. Brown
Maps, Coordinate Reference Systems And Visualising Geographic Data With Mapmisc, Patrick E. Brown
The R Journal
The mapmisc package provides functions for visualising geospatial data, including fetching background map layers, producing colour scales and legends, and adding scale bars and orientation arrows to plots. Background maps are returned in the coordinate reference system of the dataset supplied, and inset maps and direction arrows reflect the map projection being plotted. This is a “light weight” package having an emphasis on simplicity and ease of use
Editorial, Michael Lawrence
Editorial, Michael Lawrence
The R Journal
On behalf of the editorial board, I am pleased to publish Volume 8, Issue 1 of the R Journal. This issue contains 27 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 but current cross-section of the burgeoning R ecosystem.
Metaplus: An R Package For The Analysis Of Robust Meta-Analysis And Meta-Regression, Ken J. Beath
Metaplus: An R Package For The Analysis Of Robust Meta-Analysis And Meta-Regression, Ken J. Beath
The R Journal
The metaplus package is described with examples of its use for fitting meta-analysis and meta-regression. For either meta-analysis or meta-regression it is possible to fit one of three models: standard normal random effect, t-distribution random effect or mixture of normal random effects. The latter two models allow for robustness by allowing for a random effect distribution with heavier tails than the normal distribution, and for both robust models the presence of outliers may be tested using the parametric bootstrap. For the mixture of normal random effects model the outlier studies may be identified through their posterior probability of membership in …
Conditional Fractional Gaussian Fields With The Package Fieldsim, Alexandre Brouste, Jacques Istas, Sophie Lambert-Lacroix
Conditional Fractional Gaussian Fields With The Package Fieldsim, Alexandre Brouste, Jacques Istas, Sophie Lambert-Lacroix
The R Journal
We propose an effective and fast method to simulate multidimensional conditional fractional Gaussian fields with the package FieldSim. Our method is valid not only for conditional simulations associated to fractional Brownian fields, but to any Gaussian field and on any (non regular) grid of points.
Progenyclust: An R Package For Progeny Clustering, Chenyue W. Hu, Amina A. Qutub
Progenyclust: An R Package For Progeny Clustering, Chenyue W. Hu, Amina A. Qutub
The R Journal
Identifying the optimal number of clusters is a common problem faced by data scientists in various research fields and industry applications. Though many clustering evaluation techniques have been developed to solve this problem, the recently developed algorithm Progeny Clustering is a much faster alternative and one that is relevant to biomedical applications. In this paper, we introduce an R package progenyClust that implements and extends the original Progeny Clustering algorithm for evaluating clustering stability and identifying the optimal cluster number. We illustrate its applicability using two examples: a simulated test dataset for proof-of-concept, and a cell imaging dataset for demonstrating …
Statmod: Probability Calculations For The Inverse Gaussian Distribution, Göknur Giner, Gordon K. Smyth
Statmod: Probability Calculations For The Inverse Gaussian Distribution, Göknur Giner, Gordon K. Smyth
The R Journal
The inverse Gaussian distribution (IGD) is a well known and often used probability distribution for which fully reliable numerical algorithms have not been available. We develop fast, reliable basic probability functions (dinvgauss, pinvgauss, qinvgauss and rinvgauss) for the IGD that work for all possible parameter values and which achieve close to full machine accuracy. The most challenging task is to compute quantiles for given cumulative probabilities and we develop a simple but elegant mathematical solution to this problem. We show that Newton’s method for finding the quantiles of a IGD always converges monotonically when started from the mode of the …
Heteroscedastic Censored And Truncated Regression With Crch, Jakob W. Messner, Georg J. Mayr, Achim Zeileis
Heteroscedastic Censored And Truncated Regression With Crch, Jakob W. Messner, Georg J. Mayr, Achim Zeileis
The R Journal
The crch package provides functions for maximum likelihood estimation of censored or truncated regression models with conditional heteroscedasticity along with suitable standard methods to summarize the fitted models and compute predictions, residuals, etc. The supported distributions include left- or right-censored or truncated Gaussian, logistic, or student-t distributions with potentially different sets of regressors for modeling the conditional location and scale. The models and their R implementation are introduced and illustrated by numerical weather prediction tasks using precipitation data for Innsbruck (Austria).
Stylometry With R: A Package For Computational Text Analysis, Maciej Eder, Jan Rybicki, Mike Kestemont
Stylometry With R: A Package For Computational Text Analysis, Maciej Eder, Jan Rybicki, Mike Kestemont
The R Journal
This software paper describes ‘Stylometry with R’ (stylo), a flexible R package for the high level analysis of writing style in stylometry. Stylometry (computational stylistics) is concerned with the quantitative study of writing style, e.g. authorship verification, an application which has considerable potential in forensic contexts, as well as historical research. In this paper we introduce the possibilities of stylo for computational text analysis, via a number of dummy case studies from English and French literature. We demonstrate how the package is particularly useful in the exploratory statistical analysis of texts, e.g. with respect to authorial writing style. …
Sbtools: A Package Connecting R To Cloud-Based Data For Collaborative Online Research, Luke A. Winslow, Scott Chamberlain, Alison P. Appling, Jordan S. Read
Sbtools: A Package Connecting R To Cloud-Based Data For Collaborative Online Research, Luke A. Winslow, Scott Chamberlain, Alison P. Appling, Jordan S. Read
The R Journal
The adoption of high-quality tools for collaboration and reproducibile research such as R and Github is becoming more common in many research fields. While Github and other version management systems are excellent resources, they were originally designed to handle code and scale poorly to large text-based or binary datasets. A number of scientific data repositories are coming online and are often focused on dataset archival and publication. To handle collaborative workflows using large scientific datasets, there is increasing need to connect cloud-based online data storage to R. In this article, we describe how the new R package sbtools enables direct …
Mclust 5: Clustering, Classification And Density Estimation Using Gaussian Finite Mixture Models, Luca Scrucca, Michael Fop, T Brendan Murphy, Adrian E. Raftery
Mclust 5: Clustering, Classification And Density Estimation Using Gaussian Finite Mixture Models, Luca Scrucca, Michael Fop, T Brendan Murphy, Adrian E. Raftery
The R Journal
Finite mixture models are being used increasingly to model a wide variety of random phenomena for clustering, classification and density estimation. mclust is a powerful and popular package which allows modelling of data as a Gaussian finite mixture with different covariance structures and different numbers of mixture components, for a variety of purposes of analysis. Recently, version 5 of the package has been made available on CRAN.This updated version adds new covariance structures, dimension reduction capabilities for visualisation, model selection criteria, initialisation strategies for the EM algorithm, and bootstrap-based inference, making it a full-featured R package for data analysis via …
Gender Prediction Methods Based On First Names With Genderizer, Kamil Wais
Gender Prediction Methods Based On First Names With Genderizer, Kamil Wais
The R Journal
In recent years, there has been increased interest in methods for gender prediction based on f irst names that employ various open data sources. These methods have applications from bibliometric studies to customizing commercial offers for web users. Analysis of gender disparities in science based on such methods are published in the most prestigious journals, although they could be improved by choosing the most suited prediction method with optimal parameters and performing validation studies using the best data source for a given purpose. There is also a need to monitor and report how well a given prediction method works in …
Cryptrndtest: An R Package For Testing The Cryptographic Randomness, Haydar Demirhan, Nihan Bitirim
Cryptrndtest: An R Package For Testing The Cryptographic Randomness, Haydar Demirhan, Nihan Bitirim
The R Journal
n this article, we introduce the R package CryptRndTest that performs eight statistical randomness tests on cryptographic random number sequences. The purpose of the package is to provide software implementing recently proposed cryptographic randomness tests utilizing goodness of-fit tests superior to the usual chi-square test in terms of statistical performance. Most of the tests included in package CryptRndTest are not available in other software packages such as the R package RDieHarder or the C library TestU01. Chi-square, Anderson-Darling, Kolmogorov-Smirnov, and Jarque-Bera goodness-of-fit procedures are provided along with cryptographic randomness tests. CryptRndTest utilizes multiple precision floating numbers for sequences longer than …
Clustering.Sc.Dp: Optimal Clustering With Sequential Constraint By Using Dynamic Programming, Tibor Szkaliczki
Clustering.Sc.Dp: Optimal Clustering With Sequential Constraint By Using Dynamic Programming, Tibor Szkaliczki
The R Journal
The general clustering algorithms do not guarantee optimality because of the hardness of the problem. Polynomial-time methods can find the clustering corresponding to the exact optimum only in special cases. For example, the dynamic programming algorithm can solve the one-dimensional clustering problem, i.e., when the items to be clustered can be characterised by only one scalar number. Optimal one-dimensional clustering is provided by package Ckmeans.1d.dp in R. The paper shows a possible generalisation of the method implemented in this package to multidimensional data: the dynamic programming method can be applied to find the optimum clustering of vectors when only subsequent …
Fwdselect: An R Package For Variable Selection In Regression Models, Marta Sestelo, Nora M. Villanueva, Luis Meira-Machado, Javier Roca-Pardiñas
Fwdselect: An R Package For Variable Selection In Regression Models, Marta Sestelo, Nora M. Villanueva, Luis Meira-Machado, Javier Roca-Pardiñas
The R Journal
In multiple regression models, when there are a large number (p) of explanatory variables which may o rmay not be relevant for predicting the response, it is useful to be able to reduce the model. To this end, it is necessary to determine the best subset of q (q p) predictors which will establish the model with the best prediction capacity. FWDselect package introduces a new forward stepwise based selection procedure to select the best model in different regression frameworks (parametric or nonparametric). The developed methodology, which can be equally applied to linear models, generalized linear models or generalized additive …
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 1211 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 3.3 by installing R 3.3.1 and evaluating the commands