Programming Languages and Compilers Commons^™

Android Game, Ryan Weston

Williams Honors College, Honors Research Projects

The purpose of this project was to create an endless runner game for Android coded in Java and XML and developed in Android Studio. In the game, the player controls a frog that jumps from lily pad to lily pad to avoid logs moving toward the player. The player must also maneuver the lily pads as they can randomly disappear. There are three difficulties in the game that vary the disappearance rate of lily pads as well as the frequency and acceleration rate of the log obstacles. The game also has a scoring system and saves the high score locally …

V-Slam And Sensor Fusion For Ground Robots, Ejup Hoxha

Dissertations and Theses

In underground, underwater and indoor environments, a robot has to rely solely on its on-board sensors to sense and understand its surroundings. This is the main reason why SLAM gained the popularity it has today. In recent years, we have seen excellent improvement on accuracy of localization using cameras and combinations of different sensors, especially camera-IMU (VIO) fusion. Incorporating more sensors leads to improvement of accuracy,but also robustness of SLAM. However, while testing SLAM in our ground robots, we have seen a decrease in performance quality when using the same algorithms on flying vehicles.We have an additional sensor for ground …

Memory And Resource Leak Defects And Their Repairs In Java Projects, Mohammadreza Ghanavati, Diego Costa, Janos Seboek, David Lo, Artur Andrzejak

Research Collection School Of Computing and Information Systems

Despite huge software engineering efforts and programming language support, resource and memory leaks are still a troublesome issue, even in memory-managed languages such as Java. Understanding the properties of leak-inducing defects, how the leaks manifest, and how they are repaired is an essential prerequisite for designing better approaches for avoidance, diagnosis, and repair of leak-related bugs. We conduct a detailed empirical study on 452 issues from 10 large opensource Java projects. The study proposes taxonomies for the leak types, for the defects causing them, and for the repair actions. We investigate, under several aspects, the distributions within each taxonomy and …

Interaction, Collaboration And Content Creation In Informal Online Learning Environments: Multidimensional Analyses Of Longitudinal Data From The Scratch Coding Community, Seung B. Lee

Theses and Dissertations

Despite rising levels of participation by children and adolescents in large, informal online learning communities, there has been limited research examining the role that social dynamics play on the online behavior of young users. In this context, this mixed-methods longitudinal study aimed to investigate the relationship between interaction, collaboration and content creation through the analysis of user-generated comments and log-data from the Scratch platform. The research focused on more than 45,000 comments associated with the online activity of 200 randomly selected participants over a period of three months in early 2012. A combination of methodological techniques was applied in the …

Learning Personally Identifiable Information Transmission In Android Applications By Using Data From Fast Static Code Analysis, Nattanon Wongwiwatchai

Chulalongkorn University Theses and Dissertations (Chula ETD)

The ease of use of mobile devices has resulted in a significant increase in the everyday use of mobile applications as well as the amount of personal information stored on devices. Users are becoming more aware of applications' access to their personal information, as well as the risk that these applications may unwittingly transmit Personally Identifiable Information (PII) to third-party servers. There is no simple way to determine whether or not an application transmits PII. If this information could be made available to users before installing new applications, they could weigh the pros and cons of having the risk of …

Elucidating The Properties And Mechanism For Cellulose Dissolution In Tetrabutylphosphonium-Based Ionic Liquids Using High Concentrations Of Water, Brad Crawford

Graduate Theses, Dissertations, and Problem Reports (ETD)

The structural, transport, and thermodynamic properties related to cellulose dissolution by tetrabutylphosphonium chloride (TBPCl) and tetrabutylphosphonium hydroxide (TBPH)-water mixtures have been calculated via molecular dynamics simulations. For both ionic liquid (IL)-water solutions, water veins begin to form between the TBPs interlocking arms at 80 mol % water, opening a pathway for the diffusion of the anions, cations, and water. The water veins allow for a diffusion regime shift in the concentration region from 80 to 92.5 mol % water, providing a higher probability of solvent interaction with the dissolving cellulose strand. The hydrogen bonding was compared between small and large …

A Domain Specific Language For Digital Forensics And Incident Response Analysis, Christopher D. Stelly

LSU New Orleans Theses and Dissertations

One of the longstanding conceptual problems in digital forensics is the dichotomy between the need for verifiable and reproducible forensic investigations, and the lack of practical mechanisms to accomplish them. With nearly four decades of professional digital forensic practice, investigator notes are still the primary source of reproducibility information, and much of it is tied to the functions of specific, often proprietary, tools.

The lack of a formal means of specification for digital forensic operations results in three major problems. Specifically, there is a critical lack of:

a) standardized and automated means to scientifically verify accuracy of digital forensic tools; …

The R Journal (December 2019) 11(2): Complete Issue, The R Foundation

The R Journal

Editorial, Michael J. Kane

Contributed Research Articles

Using Web Services to Work with Geodata in R, Jan-Philipp Kolb

orthoDr: Semiparametric Dimension Reduction via Orthogonality Constrained Optimization, Ruoqing Zhu, Jiyang Zhang, Ruilin Zhao, Peng Xu, Wenzhuo Zhou, and Xin Zhang

coxed: An R Package for Computing Duration-Based Quantities from the Cox Proportional Hazards Model, Jonathan Kropko and Jeffrey J. Harden

Modeling Regimes with Extremes: The Bayesdfa Package for Identifying and Forecasting Common Trends and Anomalies in Multivariate Time-Series Data, Eric J. Ward, Sean C. Anderson, Luis A. Damiano, Mary E. Hunsicker, and Michael A. Litzow

Fitting Tails by the Empirical Residual …

Multimodal Mobile Sensing Systems For Physiological And Psychological Assessment, Nguyen Phan Sinh Huynh

Dissertations and Theses Collection (Open Access)

Sensing systems for monitoring physiological and psychological states have been studied extensively in both academic and industry research for different applications across various domains. However, most of the studies have been done in the lab environment with controlled and complicated sensor setup, which is only suitable for serious healthcare applications in which the obtrusiveness and immobility can be compromised in a trade-off for accurate clinical screening or diagnosing. The recent substantial development of mobile devices with embedded miniaturized sensors are now allowing new opportunities to adapt and develop such sensing systems in the mobile context. The ability to sense physiological …

R Foundation News, Torsten Hothorn

The R Journal

Membership fees and donations received between 2019-09-05 and 2020-02-24.

Conference: Report Conectar 2019, Marcela Alfaro Córdoba, Frans Van Dunné, Agustín Gómez Meléndez, Jacob Van Etten

The R Journal

ConectaR 2019: Encuentro de Usuarios R en Latinoamérica, took place during January 24-26, 2019 at the University of Costa Rica, in San José, Costa Rica. It was the first event in Central America endorsed by The R Foundation, and it was held completely in Spanish. The majority of the attendants were from Costa Rica (85%), but we had participants from 12 countries: Costa Rica, Guatemala, Peru, Colombia, Mexico, Argentina, Uruguay, Chile, Spain, the Netherlands, France and the USA. The three-day event consisted of talks, workshops, and poster sessions.

Lpirfs: An R Package To Estimate Impulse Response Functions By Local Projections, Philipp Adämmer

The R Journal

Impulse response analysis is a cornerstone in applied (macro-)econometrics. Estimating impulse response functions using local projections (LPs) has become an appealing alternative to the traditional structural vector autoregressive (SVAR) approach. Despite its growing popularity and applications, however, no R package yet exists that makes this method available. In this paper, I introduce lpirfs, a fast and flexible R package that provides a broad framework to compute and visualize impulse response functions using LPs for a variety of data sets.

Resampling-Based Analysis Of Multivariate Data And Repeated Measures Designs With The R Package Manova.Rm, Sarah Friedrich, Frank Konietschke, Markus Pauly

The R Journal

Nonparametric statistical inference methods for a modern and robust analysis of longitudinal and multivariate data in factorial experiments are essential for research. While existing approaches that rely on specific distributional assumptions of the data (multivariate normality and/or equal covariance matrices) are implemented in statistical software packages, there is a need for user-friendly software that can be used for the analysis of data that do not fulfill the aforementioned assumptions and provide accurate p value and confidence interval estimates. Therefore, newly developed nonparametric statistical methods based on bootstrap- and permutation-approaches, which neither assume multivariate normality nor specific covariance matrices, have been …

The Landscape Of R Packages For Automated Exploratory Data Analysis, Mateusz Staniak, Przemysław Biecek

The R Journal

The increasing availability of large but noisy data sets with a large number of heterogeneous variables leads to the increasing interest in the automation of common tasks for data analysis. The most time-consuming part of this process is the Exploratory Data Analysis, crucial for better domain understanding, data cleaning, data validation, and feature engineering

There is a growing number of libraries that attempt to automate some of the typical Exploratory Data Analysis tasks to make the search for new insights easier and faster. In this paper, we present a systematic review of existing tools for Automated Exploratory Data Analysis (autoEDA). …

Roahd Package: Robust Analysis Of High Dimensional Data, Francesca Ieva, Anna Maria Paganoni, Juan Romo, Nicholas Tarabelloni

The R Journal

The focus of this paper is on the open-source R package roahd (RObust Analysis of High dimensional Data), see Tarabelloni et al. (2017). roahd has been developed to gather recently proposed statistical methods that deal with the robust inferential analysis of univariate and multivariate functional data. In particular, efficient methods for outlier detection and related graphical tools, methods to represent and simulate functional data, as well as inferential tools for testing differences and dependency among families of curves will be discussed, and the associated functions of the package will be described in details.

Jomo: A Flexible Package For Two-Level Joint Modelling Multiple Imputation, Matteo Quartagno, Simon Grund, James Carpenter

The R Journal

Multiple imputation is a tool for parameter estimation and inference with partially observed data, which is used increasingly widely in medical and social research. When the data to be imputed are correlated or have a multilevel structure — repeated observations on patients, school children nested in classes within schools within educational districts — the imputation model needs to include this structure. Here we introduce our joint modelling package for multiple imputation of multilevel data, jomo, which uses a multivariate normal model fitted by Markov Chain Monte Carlo (MCMC). Compared to previous packages for multilevel imputation, e.g. pan, jomo adds the …

Cvcrand: A Package For Covariate-Constrained Randomization And The Clustered Permutation Test For Cluster Randomized Trials, Hengshi Yu, Fan Li, John A. Gallis, Elizabeth L. Turner

The R Journal

The cluster randomized trial (CRT) is a randomized controlled trial in which randomization is conducted at the cluster level (e.g., school or hospital) and outcomes are measured for each individual within a cluster. Often, the number of clusters available to randomize is small (≤ 20), which increases the chance of baseline covariate imbalance between comparison arms. Such imbalance is particularly problematic when the covariates are predictive of the outcome because it can threaten the internal validity of the CRT. Pair-matching and stratification are two restricted randomization approaches that are frequently used to ensure balance at the design stage. An alternative, …

Biclustermd: An R Package For Biclustering With Missing Values, John Reisner, Hieu Pham, Sigurdur Olafsson, Stephen Vardeman, Jing Li

The R Journal

Biclustering is a statistical learning technique that attempts to find homogeneous partitions of rows and columns of a data matrix. For example, movie ratings might be biclustered to group both raters and movies. biclust is a current R package allowing users to implement a variety of biclustering algorithms. However, its algorithms do not allow the data matrix to have missing values. We provide a new R package, biclustermd, which allows users to perform biclustering on numeric data even in the presence of missing values.

Modeling Regimes With Extremes: The Bayesdfa Package For Identifying And Forecasting Common Trends And Anomalies In Multivariate Time-Series Data, Eric J. Ward, Sean C. Anderson, Luis A. Damiano, Mary E. Hunsicker, Michael A. Litzow

The R Journal

The bayesdfa package provides a flexible Bayesian modeling framework for applying dynamic factor analysis (DFA) to multivariate time-series data as a dimension reduction tool. The core estimation is done with the Stan probabilistic programming language. In addition to being one of the few Bayesian implementations of DFA, novel features of this model include (1) optionally modeling latent process deviations as drawn from a Student-t distribution to better model extremes, and (2) optionally including autoregressive and moving-average components in the latent trends. Besides estimation, we provide a series of plotting functions to visualize trends, loadings, and model predicted values. A secondary …

Ppci: An R Package For Cluster Identification Using Projection Pursuit, David P. Hofmeyr, Nicos G. Pavlidis

The R Journal

This paper presents the R package PPCI which implements three recently proposed projection pursuit methods for clustering. The methods are unified by the approach of defining an optimal hyperplane to separate clusters, and deriving a projection index whose optimiser is the vector normal to this separating hyperplane. Divisive hierarchical clustering algorithms that can detect clusters defined in different subspaces are readily obtained by recursively bi-partitioning the data through such hyperplanes. Projecting onto the vector normal to the optimal hyperplane enables visualisations of the data that can be used to validate the partition at each level of the cluster hierarchy. Clustering …