Computer Sciences Commons^™

The R Journal (December 2015) 7(2): Complete Issue, The R Foundation

The R Journal

Editorial, Bettina Grün

Contributed Research Articles

Fitting Conditional and Simultaneous Autoregressive Spatial Models in hglm, Moudud Alam, Lars Rönnegård, and Xia Shen

VSURF: An R Package for Variable Selection Using Random Forests, Robin Genuer, Jean-Michel Poggi, and Christine Tuleau-Malot

zoib: An R Package for Bayesian Inference for Beta Regression and Zero/One Inflated Beta Regression, Fang Liu, and Yunchuan Kong

apc: An R Package for Age-Period-Cohort Analysis, Bent Nielsen

QuantifQuantile: An R Package for Performing Quantile Regression Through Optimal Quantization, Isabelle Charlier, Davy Paindaveine, and Jérôme Saracco

Numerical Evaluation of the Gauss Hypergeometric Function with the hypergeo Package, Robin K. S. …

An R Package For The Panel Approach Method For Program Evaluation: Pampe, Ainhoa Vega-Bayo

The R Journal

The pampe package for R implements the panel data approach method for program evaluation designed to estimate the causal effects of political interventions or treatments. This procedure exploits the dependence among cross-sectional units to construct a counterfactual of the treated unit(s), and it is an appropriate method for research events that occur at an aggregate level like countries or regions and that affect only one or a small number of units. The implementation of the pampe package is illustrated using data from Hong Kong and 24 other units, by examining the economic impact of the political and economic integration of …

Capstone Revival, Mary Mesele, Ruochen Lu, Quilin Jiang

School of Professional Studies

The capstone project is a culminating experience whereby students choose to research a topic that is relevant in their field of study and have been highly regarded as important learning activities. The capstone allows students to use research, analytical, problem solving and evaluation skills they have learned in the course of the graduate program. McGill indicates the benefit of the completion of a capstone project not only in gaining knowledge in capstone but also in learning how to apply the knowledge gained in other courses in the major (McGill, 2012). Currently, COPACE (College of Professional and Continuing Education) has three …

Battle Bot Ai – Patriot Bot, James Johnston

Computer Engineering

An entry in the the 'Battle Block AI' competition hosted by 'The AI Games'.

Energy Forecasting For Event Venues: Big Data And Prediction Accuracy, Katarina Grolinger, Alexandra L'Heureux, Miriam Am Capretz, Luke Seewald

Electrical and Computer Engineering Publications

Advances in sensor technologies and the proliferation of smart meters have resulted in an explosion of energy-related data sets. These Big Data have created opportunities for development of new energy services and a promise of better energy management and conservation. Sensor-based energy forecasting has been researched in the context of office buildings, schools, and residential buildings. This paper investigates sensor-based forecasting in the context of event-organizing venues, which present an especially difficult scenario due to large variations in consumption caused by the hosted events. Moreover, the significance of the data set size, specifically the impact of temporal granularity, on energy …

Students' Perspectives Of Mobile Learning Platforms: An Empirical Study, Muasaad Alrasheedi, Luiz Fernando Capretz, Arif Raza

Electrical and Computer Engineering Publications

Educational institutions are becoming involved in adopting technological innovations like th e mobile learning (m-Learning) platform for education. Mobile technologies are the next frontier as infrast ructure for m-Learning because they can provide high-quality learning capab ilities to satisfy the rising student demand for mobility and flexibility due to the ubiquitous nature of mobile tec hnology (smartphones) and the va st opportunities it offers, there ar e indications that smartphones could lead the next generation for learning platforms. Researchers have examin ed the idea from several angles and produced a copious amount of literature devoted to explaining the interrelationships of …

Management's Perspective On Critical Success Factors Affecting Mobile Learning In Higher Education Institutions - An Empirical Study, Muasaad Alrasheedi, Luiz Fernando Capretz, Arif Raza

Electrical and Computer Engineering Publications

Mobile learning (m-Learning) is considered to be one of the fastest growing learning platforms. The immense interest in m-Learning is attributed to the incredible rate of growth of mobile technology and its proliferation into every aspect of modern life. Despite this, m-Learning has not experienced a similar adoption rate in the education sector, chiefly higher education. Researchers have attempted to explain this anomaly by conducting several studies in the area. However, mostly the research in m-Learning is examined from the perspective of the students and educators. In this research, it is contended that there is a third important stakeholder group …

Positive Influence Dominating Set Generation In Social Networks, Akshaye Dhawan, Matthew Rink

Mathematics, Computer Science & Statistics Faculty Publications

Current algorithms in the Positive Influence Dominating Set (PIDS) problem domain are focused on a specific type of PIDS, the Total Positive Influence Dominating Set (TPIDS). We have developed an algorithm specifically targeted towards the non-total type of PIDS. In addition to our new algorithm, we adapted two existing TPIDS algorithms to generate PIDS. We ran simulations for all three algorithms, and our new algorithm consistently generates smaller PIDS than both existing algorithms, with our algorithm generating PIDS approximately 5% smaller than the better of the two existing algorithms.

Randomized Algorithms For Approximating A Connected Dominating Set In Wireless Sensor Networks, Akshaye Dhawan, Michelle Tanco, Aaron Yeiser

Mathematics, Computer Science & Statistics Faculty Publications

A Connected Dominating Set (CDS) of a graph representing a Wireless Sensor Network can be used as a virtual backbone for routing through the network. Since the sensors in the network are constrained by limited battery life, we desire a minimal CDS for the network, a known NP-hard problem. In this paper we present three randomized algorithms for constructing a CDS. We evaluate our algorithms using simulations and compare them to the two-hop K2 algorithm and two other greedy algorithms from the literature. After pruning, the randomized algorithms construct a CDS that are generally equivalent in size to those constructed …

On The Discovery Of Social Roles In Large Scale Social Systems, Derek Doran

Computer Science and Engineering Faculty Publications

The social role of a participant in a social system is a label conceptualizing the circumstances under which she interacts within it. They may be used as a theoretical tool that explains why and how users participate in an online social system. Social role analysis also serves practical purposes, such as reducing the structure of complex systems to relationships among roles rather than alters, and enabling a comparison of social systems that emerge in similar contexts. This article presents a data-driven approach for the discovery of social roles in large scale social systems. Motivated by an analysis of the present …

Mixed-Criticality Job Models: A Comparison, Sanjoy K. Baruah, Zhishan Guo

Computer Science Faculty Research & Creative Works

The Vestal model in widely used in the real-time scheduling community for representing mixed-criticality real-time workloads. This model requires that multiple WCET estimates -- one for each criticality level in a system -- be obtained for each task. Burns suggests that being required to obtain too many WCET estimates may place an undue burden on system developers, and proposes a simplification to the Vestal model that makes do with just two WCET estimates per task. Burns makes a convincing case in favor of adopting this simplified model; here, we report on our attempts at comparing the two models -- Vestal’s …

Toward Unification Of Explicit And Implicit Invocation-Style Programming, Yoonsik Cheon

Departmental Technical Reports (CS)

Subprograms like procedures and methods can be invoked explicitly or implicitly; in implicit invocation, an event implicitly causes the invocation of subprograms that are registered an interest in the event. Mixing these two styles is common in programming and often unavoidable in developing such software as GUI applications and event-based control systems. However, it isn't also uncommon for the mixed use to complicate programming logic and thus produce unclean code, code that is hard to read and understand. We show, through a small but realistic example, that the problem is not much on mixing two different styles itself but more …

A Systematic Derivation Of Loop Specifications Using Patterns, Aditi Barua, Yoonsik Cheon

Departmental Technical Reports (CS)

Any non-trivial program contains loop control structures such as while, for and do statements. A formal correctness proof of code containing loop control structures is typically performed using an induction-based technique, and oftentimes the most challenging step of an inductive proof is formulating a correct induction hypothesis. An incorrectly-formulated induction hypothesis will surely lead to a failure of the proof. In this paper we propose a systematic approach for formulating and driving specifications of loop control structures for formal analysis and verification of programs. We explain our approach using while loops and a functional program verification technique in which a …

Detecting Real-Time Check-Worthy Factual Claims In Tweets Related To U.S. Politics, Fatma Dogan

Computer Science and Engineering Theses - Archive

In increasing democracy and improving political discourse, political fact-checking has come to be a necessity. While politicians make claims about facts all the time, journalists and fact-checkers oftentimes reveal them as false, exaggerated, or misleading. Use of technology and social media tools such as Facebook and Twitter has rapidly increased the spread of misinformation. Thus, human fact-checkers face difficulty in keeping up with a massive amount of claims, and falsehoods frequently outpace truths. All U.S. politicians have successively adopted Twitter, and they make use of Twitter for a wide variety of purposes, a great example being making claims to enhance …

Qp-Subdue: Processing Queries Over Graph Databases, Ankur Goyal

Computer Science and Engineering Theses - Archive

Graphs have become one of the preferred ways to store structured data for various applications such as social network graphs, complex molecular structure, etc. Proliferation of graph databases has resulted in a growing need for effective querying methods to retrieve desired information. Querying has been widely studied in relational databases where the query optimizer finds a sequence of query execution steps (or plans) for efficient execution of the given query. Until now, most of the work on graph databases has concentrated on mining. For querying graph databases, users have to either learn a graph query language for posing their queries …

Lung Cancer Subtype Classification From Whole Slide Histopathological Images, Dheeraj Ganti

Computer Science and Engineering Theses - Archive

Lung Cancer is one of the most serious diseases causing death for human be- ings. The progression of the disease and response to treatment di ers widely among patients. Thus it is very important to classify the type of tumor and also able to predict the clinical outcomes of patients. Majority of lung cancers is Non-Small Cell Lung Cancer (NSCLC) which constitutes of 84 % of all the type of lung cancers. The two major subtypes of NSCLC are Adenocarcinoma (ADC) and Squamous Cell Car- cinoma (SCC). Accurate classi cation of the lung cancer as NSCLC and its subtype classi …

Quantitative Analysis Of Scalable Nosql Databases, Surya Narayanan Swaminathan

Computer Science and Engineering Theses - Archive

NoSQL databases are rapidly becoming the customary data platform for big data applications. These databases are emerging as a gateway for more alternative approaches outside traditional relational databases and are characterized by efficient horizontal scalability, schema-less approach to data modeling, high performance data access, and limited querying capabilities. The lack of transactional semantics among NoSQL databases has made the application determine the choice of a particular con- sistency model. Therefore, it is essential to examine methodically, and in detail, the performance of different databases under different workload conditions. In this work, three of the most commonly used NoSQL databases: MongoDB, …

Speaker Identification In Live Events Using Twitter, Minumol Joseph

Computer Science and Engineering Theses - Archive

The prevalence of social media has given rise to a new research area. Data from social media is now being used in research to gather deeper insights into many different fields. Twitter is one of the most popular microblogging websites. Users express themselves on a variety of different topics in 140 characters or less. Oftentimes, users “tweet” about issues and subjects that are gaining in popularity, a great example being politics. Any development in politics frequently results in a tweet of some form. The research which follows focuses on identifying a speaker’s name at a live event by collecting and …

Interactive Dashboard For User Activity Using Network Flow Data, Lalit Kumar Naidu

Computer Science and Engineering Theses - Archive

Data visualization is critical in analytical systems containing multi-dimensional dataset and problems associated with increasing data size. It facilitates the data explanation process of reasoning data and discovering trends with visual perception that are otherwise not evident within the data in its raw form. The challenge involved in visualization is presenting data in such a way that helps end users in the process of information discovery with simple visuals. Interactive visualizations have increasingly become popular in recent years with prominent research in the field of information visualization. These techniques are heavily used in web-based applications to present myriad forms of …

Real Time Analytics On Digital Distraction, Kristian Welch

Computer Science and Software Engineering

Hypothesis: empirically measuring the users productivity has the potential to significantly increase their productivity. This paper is the documentation of the process of building software capable of verifying this hypothesis. Starting with the research which gives enough evidence to warrant the hypothesis, also included is commentary on the prototyping, design decisions, and iteration based on user feedback of the software.

Co-Rotational Finite Element Solid Simulation With Collisions, Patrick Riordan

Computer Science and Software Engineering

This paper is a tutorial on how to implement a deformable solid simulation with collisions based off of Matthias Mueller's Real Time Physics Course Notes. It covers the topics continuum mechanics, finite element analysis, implicit Euler integration, and handling collision.

Changes On Cran, Kurt Hornik, Achim Zeileis

The R Journal

New packages in CRAN task views

New contributed packages

Other changes

Conference Report: User! 2015, Torben Tvedebrink

The R Journal

The11thinternational R user conference, useR! 2015, took place in Aalborg, Denmark, 1–3 July 2015. The Department of Mathematical Sciences, Aalborg University, hosted the conference, which took place in Aalborg Congress and Culture Centre.

Open-Channel Computation With R, Michael C. Koohafkan, Bassam A. Younis

The R Journal

The rivr package provides a computational toolset for simulating steady and unsteady one dimensional flows in open channels. It is designed primarily for use by instructors of undergraduate and graduate-level open-channel hydrodynamics courses in such diverse fields as river engineering, physical geography and geophysics. The governing equations used to describe open-channel flows are briefly presented, followed by example applications. These include the computation of gradually varied flows and two examples of unsteady flows in channels—namely, the tracking of the evolution of a flood wave in a channel and the prediction of extreme variation in the water-surface profile that results when …

Mmpp: A Package For Calculating Similarity And Distance Metrics For Simple And Marked Temporal Point Processes, Hideitsu Hino, Ken Takano, Noboru Murata

The R Journal

A simple temporal point process (SPP) is an important class of time series, where the sample realization of the process is solely composed of the times at which events occur. Particular examples of point process data are neuronal spike patterns or spike trains, and a large number of distance and similarity metrics for those data have been proposed. A marked point process (MPP) is an extension of a simple temporal point process, in which a certain vector valued mark is associated with each of the temporal points in the SPP. Analyses of MPPs are of practical importance because instances of …

Mtk: A General-Purpose And Extensible R Environment For Uncertainty And Sensitivity Analyses Of Numerical Experiments, Juhui Wang, Robert Faivre, Hervé Richard, Hervé Monod

The R Journal

Along with increased complexity of the models used for scientific activities and engineering come diverse and greater uncertainties. Today, effectively quantifying the uncertainties contained in a model appears to be more important than ever. Scientific fellows know how serious it is to calibrate their model in a robust way, and decision-makers describe how critical it is to keep the best effort to reduce the uncertainties about the model. Effectively accessing the uncertainties about the model requires mastering all the tasks involved in the numerical experiments, from optimizing the experimental design to managing the very time consuming aspect of model simulation …

Abctools: An R Package For Tuning Approximate Bayesian Computation Analyses, Matthew A. Nunes, Dennis Prangle

The R Journal

Approximate Bayesian computation (ABC) is a popular family of algorithms which perform approximate parameter inference when numerical evaluation of the likelihood function is not possible but data can be simulated from the model. They return a sample of parameter values which produce simulations close to the observed dataset. A standard approach is to reduce the simulated and observed datasets to vectors of summary statistics and accept when the difference between these is below a specified threshold. ABC can also be adapted to perform model choice.

In this article, we present a new software package for R, abctools which provides methods …

Altopt: An R Package For Optimal Experimental Design Of Accelerated Life Testing, Kangwon Seo, Rong Pan

The R Journal

The R package ALTopt has been developed with the aim of creating and evaluating optimal experimental designs of censored accelerated life tests (ALTs). This package takes the generalized linear model approach to ALT planning, because this approach can easily handle censoring plans and derive information matrices for evaluating designs. Three types of optimality criteria are considered: D-optimality for model parameter estimation, U-optimality for reliability prediction at a single use condition, and I-optimality for reliability prediction over a region of use conditions. The Weibull distribution is assumed for failure time data and more than one stress factor can …

Practools: Computations For Design Of Finite Population Samples, Richard Valliant, Jill A. Dever, Frauke Kreuter

The R Journal

PracTools is an R package with functions that compute sample sizes for various types of finite population sampling designs when totals or means are estimated. One-, two-, and three-stage designs are covered as well as allocations for stratified sampling and probability proportional to size sampling. Sample allocations can be computed that minimize the variance of an estimator subject to a budget constraint or that minimize cost subject to a precision constraint. The package also contains some specialized functions for estimating variance components and design effects. Several finite populations are included that are useful for classroom instruction.

Clustvarlv: An R Package For The Clustering Of Variables Around Latent Variables, Evelyne Vigneau, Mingkun Chen, El Mostafa Qannari

The R Journal

The clustering of variables is a strategy for deciphering the underlying structure of a data set. Adopting an exploratory data analysis point of view, the Clustering of Variables around Latent Variables (CLV) approach has been proposed by Vigneau and Qannari (2003). Based on a family of optimization criteria, the CLV approach is adaptable to many situations. In particular, constraints may be introduced in order to take account of additional information about the observations and/or the variables. In this paper, the CLV method is depicted and the R package ClustVarLV including a set of functions developed so far within this framework …