Computer Sciences Commons^™

Rssampling: A Pioneering Package For Ranked Set Sampling, Busra Sevinc, Bekir Cetintav, Melek Esemen, Selma Gurler

The R Journal

Ranked set sampling (RSS) is an advanced data collection method when the exact measurement of an observation is difficult and/or expensive used in a number of research areas, e.g., environment, bioinformatics, ecology, etc. In this method, random sets are drawn from a population and the units in sets are ranked with a ranking mechanism which is based on a visual inspection or a concomitant variable. Because of the importance of working with a good design and easy analysis, there is a need for a software tool which provides sampling designs and statistical inferences based on RSS and its modifications. This …

Title: Ipwerrory: An R Package For Estimation Of Average Treatment Effect With Misclassified Binary Outcome, Di Shu, Grace Y. Yi

The R Journal

It has been well documented that ignoring measurement error may result in severely biased inference results. In recent years, there has been limited but increasing research on causal inference with measurement error. In the presence of misclassified binary outcome variable, Shu and Yi (2017) considered the inverse probability weighted estimation of the average treatment effect and proposed valid estimation methods to correct for misclassification effects for various settings. To expedite the application of those methods for situations where misclassification in the binary outcome variable is a real concern, we implement correction methods proposed by Shu and Yi (2017) and develop …

Semicomprisks: An R Package For The Analysis Of Independent And Cluster-Correlated Semi-Competing Risks Data, Danilo Alvares, Sebastien Haneuse, Catherine Lee, Kyu Ha Lee

The R Journal

Semi-competing risks refer to the setting where primary scientific interest lies in estimation and inference with respect to a non-terminal event, the occurrence of which is subject to a terminal event. In this paper, we present the R package SemiCompRisks that provides functions to perform the analysis of independent/clustered semi-competing risks data under the illness-death multi-state model. The package allows the user to choose the specification for model components from a range of options giving users substantial flexibility, including: accelerated failure time or proportional hazards regression models; parametric or non-parametric specifications for baseline survival functions; parametric or non-parametric specifications for …

R News, R Core Team

The R Journal

CHANGES IN R 3.6.1

Fixed Point Acceleration In R, Stuart Baumann, Margaryta Klymak

The R Journal

t A fixed point problem is one where we seek a vector, X, for a function, f, such that f(X) = X. The solution of many such problems can be accelerated by using a fixed point acceleration algorithm. With the release of the FixedPoint package there is now a number of algorithms available in R that can be used for accelerating the finding of a fixed point of a function. These algorithms include Newton acceleration, Aitken acceleration and Anderson acceleration as well as epsilon extrapolation methods and minimal polynomial methods. This paper demonstrates the use of fixed point accelerators in …

Nowcasting: An R Package For Predicting Economic Variables Using Dynamic Factor Models, Serge De Valk, Daiane De Mattos, Pedro Ferreira

The R Journal

The nowcasting package provides the tools to make forecasts of monthly or quarterly economic variables using dynamic factor models. The objective is to help the user at each step of the forecasting process, starting with the construction of a database, all the way to the interpretation of the forecasts. The dynamic factor model adopted in this package is based on the articles from Giannone et al. (2008) and Banbura et al. (2011). Although there exist several other dynamic factor model packages available for R, ours provides an environment to easily forecast economic variables and interpret results.

Unival: An Fa-Based R Package For Assessing Essential Unidimensionality Using External Validity Information, Pere J. Ferrando, Urbano Lorenzo-Seva, David Navarro-Gonzalez

The R Journal

The unival package is designed to help researchers decide between unidimensional and correlated-factors solutions in the factor analysis of psychometric measures. The novelty of the approach is its use of external information, in which multiple factor scores and general factor scores are related to relevant external variables or criteria. The unival package’s implementation comes from a series of procedures put forward by Ferrando and Lorenzo-Seva (2019) and new methodological developments proposed in this article. We assess models fitted using unival by means of a simulation study extending the results obtained in the original proposal. Its usefulness is also assessed through …

Optimparallel: An R Package Providing A Parallel Version Of The L-Bfgs-B Optimization Method, Florian Gerber, Reinhard Furrer

The R Journal

The R package optimParallel provides a parallel version of the L-BFGS-B optimization method of optim(). The main function of the package is optimParallel(), which has the same usage and output as optim(). Using optimParallel() can significantly reduce the optimization time, especially when the evaluation time of the objective function is large and no analytical gradient is available. We introduce the R package and illustrate its implementation, which takes advantage of the lexical scoping mechanism of R.

Integration Of Networks And Pathways With Starbiotrek Package, Claudia Cava, Isabella Castiglioni

The R Journal

High-throughput genomic technologies bring to light a comprehensive hallmark of molecular changes of a disease. It is increasingly evident that genes are not isolated from each other and the identification of a gene signature can only partially elucidate the de-regulated biological functions in a disease. The comprehension of how groups of genes (pathways) are related to each other (pathway-cross talk) could explain biological mechanisms causing diseases. Biological pathways are important tools to identify gene interactions and decrease the large number of genes to be studied by partitioning them into smaller groups. Furthermore, recent scientific studies have demonstrated that an integration …

Whats For Dynr: A Package For Linear And Nonlinear Dynamic Modeling In R, Lu Ou, Michael D. Hunter, Sy-Miin Chow

The R Journal

Intensive longitudinal data in the behavioral sciences are often noisy, multivariate in nature, and may involve multiple units undergoing regime switches by showing discontinuities interspersed with continuous dynamics. Despite increasing interest in using linear and nonlinear differential/difference equation models with regime switches, there has been a scarcity of software packages that are fast and freely accessible. We have created an R package called dynr that can handle a broad class of linear and nonlinear discrete- and continuous-time models, with regime-switching properties and linear Gaussian measurement functions, in C, while maintaining simple and easy-to-learn model specification functions in R. We present …

Swgee: An R Package For Analyzing Longitudinal Data With Response Missingness And Covariate Measurement Error, Juan Xiong, Grace Y. Yi

The R Journal

Though longitudinal data often contain missing responses and error-prone covariates, relatively little work has been available to simultaneously correct for the effects of response missingness and covariate measurement error on analysis of longitudinal data. Yi (2008) proposed a simulation based marginal method to adjust for the bias induced by measurement error in covariates as well as by missingness in response. The proposed method focuses on modeling the marginal mean and variance structures, and the missing at random mechanism is assumed. Furthermore, the distribution of covariates are left unspecified. These features make the proposed method applicable to a broad settings. In …

Simcorrmix: Simulation Of Correlated Data With Multiple Variable Types Including Continuous And Count Mixture Distributions, Allison Fialkowski, Hemant Tiwari

The R Journal

The SimCorrMix package generates correlated continuous (normal, non-normal, and mixture), binary, ordinal, and count (regular and zero-inflated, Poisson and Negative Binomial) variables that mimic real-world data sets. Continuous variables are simulated using either Fleishman’s third-order or Headrick’s fifth-order power method transformation. Simulation occurs at the component level for continuous mixture distributions, and the target correlation matrix is specified in terms of correlations with components. However, the package contains functions to approximate expected correlations with continuous mixture variables. There are two simulation pathways which calculate intermediate correlations involving count variables differently, increasing accuracy under a wide range of parameters. The package …

The R Journal (June 2019) 11(1): Complete Issue, The R Foundation

The R Journal

Editorial, Michael J. Kane

Contributed Research Articles

atable: Create Tables for Clinical Trial Reports, Armin Ströbel

Connecting R with D3 for Dynamic Graphics, to Explore Multivariate Data with Tours, Michael Kipp, Ursula Laa, and Dianne Cook

Optimization Routines for Enforcing One-to-One Matches in Record Linkage Problems, Diego Moretti, Luca Valentino, and Tiziana Tuoto

mixedsde: A Package to Fit Mixed Stochastic Differential Equations, Charlotte Dion, Simone Hermann, and Adeline Samson

Indoor Positioning and Fingerprinting: The R Package ipft, Emilio Sansano, Raúl Montoliu, Óscar Belmonte, and Joaquín Torres-Sospedra

RobustGaSP: Robust Gaussian Stochastic Process Emulation in R, Mengyang Gu, Jesus Palomo, and James …

A Data Driven Approach To Identify Journalistic 5ws From Text Documents, Venkata Krishna Mohan Sunkara

School of Computing: Dissertations, Theses, and Student Research

Textual understanding is the process of automatically extracting accurate high-quality information from text. The amount of textual data available from different sources such as news, blogs and social media is growing exponentially. These data encode significant latent information which if extracted accurately can be valuable in a variety of applications such as medical report analyses, news understanding and societal studies. Natural language processing techniques are often employed to develop customized algorithms to extract such latent information from text.

Journalistic 5Ws refer to the basic information in news articles that describes an event and include where, when, who, what and why …

Image Processing Algorithms For Elastin Lamellae Inside Cardiovascular Arteries, Mahmoud Habibnezhad

School of Computing: Dissertations, Theses, and Student Research

Automated image processing methods are greatly needed to replace the tedious, manual histology analysis still performed by many physicians. This thesis focuses on pathological studies that express the essential role of elastin lamella in the resilience and elastic properties of the arterial blood vessels. Due to the stochastic nature of the shape and distribution of the elastin layers, their morphological features appear as the best candidates to develop a mathematical formulation for the resistance behavior of elastic tissues. However, even for trained physicians and their assistants, the current measurement procedures are highly error-prone and prolonged. This thesis successfully integrates such …

A Data-Driven Approach For Detecting Stress In Plants Using Hyperspectral Imagery, Suraj Gampa

School of Computing: Dissertations, Theses, and Student Research

A phenotype is an observable characteristic of an individual and is a function of its genotype and its growth environment. Individuals with different genotypes are impacted differently by exposure to the same environment. Therefore, phenotypes are often used to understand morphological and physiological changes in plants as a function of genotype and biotic and abiotic stress conditions. Phenotypes that measure the level of stress can help mitigate the adverse impacts on the growth cycle of the plant. Image-based plant phenotyping has the potential for early stress detection by means of computing responsive phenotypes in a non-intrusive manner. A large number …

Cyanotech: A Strategic Audit, Trent Hoppe

Honors Program: Senior Projects (Public)

Microalgae is a fascinating group of organisms that possess a diverse array of interesting traits and benefits relevant to food, medicine, and biofuel. Extensive research behind the viability of microalgae to disrupt the market has sparked an emergent microalgae industry. Founded in 1983, one of the top microalgae companies in the world today is Cyanotech. With a 90-acre algae farm in Kailua-Kona, Hawaii and two flagship microalgae products that are world leaders in their categories, Cyanotech is well- positioned be setting the course for the industry and revolutionizing the use microalgae commercially. Despite these favorable attributes, Cyanotech has been trapped …

Gaindroid: General Automated Incompatibility Notifier For Android Applications, Bruno Vieira Resende E Silva

School of Computing: Dissertations, Theses, and Student Research

With the ever-increasing popularity of mobile devices over the last decade, mobile apps and the frameworks upon which they are built frequently change. This rapid evolution leads to a confusing jumble of devices and applications utilizing differing features even within the same framework. For Android apps and devices, representing over 80% of the market share, mismatches between the version of the Android operating system installed on a device and the version of the app installed, can lead to several run-time crashes, providing a poor user experience.

This thesis presents GAINDroid, an analysis approach, backed with a classloader based program analyzer, …

Feasibility And Security Analysis Of Wideband Ultrasonic Radio For Smart Home Applications, Qi Xia

School of Computing: Dissertations, Theses, and Student Research

Smart home Internet-of-Things (IoT) accompanied by smart home apps has witnessed tremendous growth in the past few years. Yet, the security and privacy of the smart home IoT devices and apps have raised serious concerns, as they are getting increasingly complicated each day, expected to store and exchange extremely sensitive personal data, always on and connected, and commonly exposed to any users in a sensitive environment. Nowadays wireless smart home IoT devices rely on electromagnetic wave-based radio-frequency (RF) technology to establish fast and reliable quality network connections. However, RF has its limitations that can negatively affect the smart home user …

Modeling And Economic Analysis Of A Crop–Livestock Production System Incorporating Cereal Rye As A Forage, Eric R. Coufal

Department of Agricultural Economics: Dissertations, Theses, and Student Research

This thesis consists of two chapters using agent-based modeling for a crop-livestock production system incorporating human labor. The first chapter examines the principles used to develop a fundamental simulation pertaining to grazing cereal rye (Secale cereal L.) with calves. Within the software guidelines, the base model has the ability to capture diverse system interactions between livestock/plants and land management with human labor efficiency. AnyLogic incorporates agent-based modeling while combining with discrete event modeling and system dynamics. The purpose of the model was to find the economic returns of grazing cover crops relative to the area of Mead, Nebraska. In …

Analysis And Comparison Of Multiple Approaches For Software Development Management As Applied To A Design Studio Project, Bethany Hage

Honors Program: Senior Projects (Public)

This research analyzes multiple approaches to software development management through the lens of my experience in the Raikes Design Studio capstone program. The Design Studio project I participated in was a project for the company Hudl, and throughout its course we used techniques from the Agile framework of Scrum. I compared the Scrum principles to my team’s own application over the course of the project, and I researched other software development methodologies such as Extreme Programming and Lean in order to determine whether they could improve the effectiveness of the current Design Studio experience. The proposed solution to this question …

Pascal's Triangle Modulo N And Its Applications To Efficient Computation Of Binomial Coefficients, Zachary Warneke

Honors Program: Senior Projects (Public)

In this thesis, Pascal's Triangle modulo n will be explored for n prime and n a prime power. Using the results from the case when n is prime, a novel proof of Lucas' Theorem is given. Additionally, using both the results from the exploration of Pascal's Triangle here, as well as previous results, an efficient algorithm for computation of binomial coefficients modulo n (a choose b mod n) is described, and its time complexity is analyzed and compared to naive methods. In particular, the efficient algorithm runs in O(n log(a)) time (as opposed to …

Interim Performance Report, Lg‐71‐16‐0152‐16, Extending Intelligent Computational Image Analysis For Archival Discovery, March 2019, Elizabeth Lorang, Leen-Kiat Soh, John O'Brien

CDRH Grant Reports

The primary goal of "Extending Intelligent Computational Image Analysis for Archival Discovery" is to investigate the use of image analysis as a methodology for content identification, description, and information retrieval in digital libraries and other digitized collections. Building on work started under a National Endowment for the Humanities' Office of Digital Humanities Start-up Grant, our IMLS project seeks to 1) analyze and verify our previously developed image analysis approach and extend it so that it is newspaper agnostic, type agnostic, and language agnostic; 2) scale and revise the intelligent image analysis approach and determine the ideal balance between precision and …

Work-In-Progress Reports Submitted To The Library Of Congress As Part Of Digital Libraries, Intelligent Data Analytics, And Augmented Description, Chulwoo Pack, Yi Liu, Leen-Kiat Soh, Elizabeth Lorang

School of Computing: Technical Reports

This document includes work-in-progress reports submitted to the Library of Congress as part of the Aida digital libraries research team's work on Digital Libraries, Intelligent Data Analytics, and Augmented Description: A Demonstration Project. These work-in-progress reports provide a snapshot glimpse, as well as underlying rationale and decision-making, at various points in the development of the project and its machine learning explorations. Reports cover explorations on historic newspapers, minimally-processed manuscript collections, materials digitized from physical originals and those digitized from microform surrogates, and investigate challenges related to image segmentation and document zoning, classification, document image quality analysis, metadata generation, and more.

Regulation Of Artificial Intelligence In Selected Jurisdictions, Jenny Gesley, Tariq Ahmad, Edouardo Soares, Ruth Levush, Gustavo Guerra, James Martin, Kelly Buchanan, Laney Zhang, Sayuri Umeda, Astghik Grigoryan, Nicolas Boring, Elin Hofverberg, Clare Feikhert-Ahalt, Graciela Rodriguez-Ferrand, George Sadek, Hanibal Goitom

Copyright, Fair Use, Scholarly Communication, etc.

Comparative Summary

This report examines the emerging regulatory and policy landscape surrounding artificial intelligence (AI) in jurisdictions around the world and in the European Union (EU). In addition, a survey of international organizations describes the approach that United Nations (UN) agencies and regional organizations have taken towards AI. As the regulation of AI is still in its infancy, guidelines, ethics codes, and actions by and statements from governments and their agencies on AI are also addressed. While the country surveys look at various legal issues, including data protection and privacy, transparency, human oversight, surveillance, public administration and services, autonomous vehicles, …

Big Data Investment And Knowledge Integration In Academic Libraries, Saher Manaseer, Afnan R. Alawneh, Dua Asoudi

Copyright, Fair Use, Scholarly Communication, etc.

Recently, big data investment has become important for organizations, especially with the fast growth of data following the huge expansion in the usage of social media applications, and websites. Many organizations depend on extracting and reaching the needed reports and statistics. As the investments on big data and its storage have become major challenges for organizations, many technologies and methods have been developed to tackle those challenges.

One of such technologies is Hadoop, a framework that is used to divide big data into packages and distribute those packages through nodes to be processed, consuming less cost than the traditional storage …

The Global Disinformation Order: 2019 Global Inventory Of Organised Social Media Manipulation, Samantha Bradshaw, Philip N. Howard

Copyright, Fair Use, Scholarly Communication, etc.

Executive Summary

Over the past three years, we have monitored the global organization of social media manipulation by governments and political parties. Our 2019 report analyses the trends of computational propaganda and the evolving tools, capacities, strategies, and resources.

1. Evidence of organized social media manipulation campaigns which have taken place in 70 countries, up from 48 countries in 2018 and 28 countries in 2017. In each country, there is at least one political party or government agency using social media to shape public attitudes domestically.

2.Social media has become co-opted by many authoritarian regimes. In 26 countries, computational propaganda …

Gmaim: An Analytical Pipeline For Microrna Splicing Profiling Using Generative Model, Kan Liu

School of Computing: Dissertations, Theses, and Student Research

MicroRNAs (miRNAs) are a class of short (~22 nt) single strand RNA molecules predominantly found in eukaryotes. Being involved in many major biological processes, miRNAs can regulate gene expression by targeting mRNAs to facilitate their degradation or translational inhibition. The imprecise splicing of miRNA splicing which introduces severe variability in terms of sequences of miRNA products and their corresponding downstream gene expression regulation. For example, to study biogenesis of miRNAs, usually, biologists can deplete a gene in the miRNA biogenesis pathway and study the change of miRNA sequences, which can cause impression of miRNAs. Although high-throughput sequencing technologies such as …

The R Journal (December 2018) 10(2): Complete Issue, The R Foundation

The R Journal

Editorial, John Verzani

Contributed Research Articles

stplanr: A Package for Transport Planning, Robin Lovelace and Richard Ellison

The utiml Package: Multi-label Classification in R, Adriano Rivolli and Andre C. P. L. F. de Carvalho

rcss: R Package for Optimal Convex Stochastic Switching, Juri Hinz and Jeremy Yee

nsROC: An R package for Non-Standard ROC Curve Analysis, Sonia Pérez-Fernández, Pablo Martínez-Camblor, Peter Filzmoser, and Norberto Corral

addhaz: Contribution of Chronic Diseases to the Disability Burden Using R, Renata Tiene de Carvalho Yokota, Caspar WN Looman, Wilma Johanna Nusselder, Herman Van Oyen, and Geert Molenberghs

Snowboot: Bootstrap Methods for Network Inference, Yuzhou …

Testfordep: An R Package For Modern Distribution-Free Tests And Visualization Tools For Independence, Jeffrey C. Miecznikowski, En-Shuo Hsu, Yanhua Chen, Albert Vexler

The R Journal

This article introduces testforDEP, a portmanteau R package implementing for the first time several modern tests and visualization tools for independence between two variables. While classical tests for independence are in the base R packages, there have been several recently developed tests for independence that are not available in R. This new package combines the classical tests including Pearson’s product moment correlation coefficient method, Kendall’s τ rank correlation coefficient method and Spearman’s ρ rank correlation coefficient method with modern tests consisting of an empirical likelihood based test, a density-based empirical likelihood ratio test, Kallenberg data-driven test, maximal information coefficient …