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An Interactive User Interface Improves Data Visualization In R, Nathan Sweem 2015 California State University - Sacramento

An Interactive User Interface Improves Data Visualization In R, Nathan Sweem

STAR Program Research Presentations

An interactive user interface application was created using the R statistical computing environment and the Shiny package to visualize historical data on the performance of mutual funds and exchange-traded funds (ETFs). Historical data for these funds is scraped from the Yahoo! Finance webpage. The application allows the user to analyze this historical data by category and fund family, which are also scraped from Yahoo! Finance. The application generates interactive plots to compare the performance of selected mutual funds and ETFs given the baseline and center determined by the user. The application has been modified to attentively match the data with …


Memes As Building Blocks: A Case Study On Evolutionary Optimization + Transfer Learning For Routing Problems, Liang FENG, Yew-Soon ONG, Ah-hwee TAN, Ivor W. TSANG 2015 Singapore Management University

Memes As Building Blocks: A Case Study On Evolutionary Optimization + Transfer Learning For Routing Problems, Liang Feng, Yew-Soon Ong, Ah-Hwee Tan, Ivor W. Tsang

Research Collection School Of Computing and Information Systems

A significantly under-explored area of evolutionary optimization in the literature is the study of optimization methodologies that can evolve along with the problems solved. Particularly, present evolutionary optimization approaches generally start their search from scratch or the ground-zero state of knowledge, independent of how similar the given new problem of interest is to those optimized previously. There has thus been the apparent lack of automated knowledge transfers and reuse across problems. Taking this cue, this paper presents a Memetic Computational Paradigm based on Evolutionary Optimization + Transfer Learning for search, one that models how human solves problems, and embarks on …


Neural Modeling Of Sequential Inferences And Learning Over Episodic Memory, Budhitama SUBAGDJA, Ah-hwee TAN 2015 Singapore Management University

Neural Modeling Of Sequential Inferences And Learning Over Episodic Memory, Budhitama Subagdja, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Episodic memory is a significant part of cognition for reasoning and decision making. Retrieval in episodic memory depends on the order relationships of memory items which provides flexibility in reasoning and inferences regarding sequential relations for spatio-temporal domain. However, it is still unclear how they are encoded and how they differ from representations in other types of memory like semantic or procedural memory. This paper presents a neural model of sequential representation and inferences on episodic memory. It contrasts with the common views on sequential representation in neural networks that instead of maintaining transitions between events to represent sequences, they …


New Product Development Flexibility In A Competitive Environment, Janne KETTUNEN, Yael GRUKSHA-COCKAYNE, Zeger DEGRAEVE, Bert DE REYCK 2015 Singapore Management University

New Product Development Flexibility In A Competitive Environment, Janne Kettunen, Yael Gruksha-Cockayne, Zeger Degraeve, Bert De Reyck

Research Collection Lee Kong Chian School Of Business

Managerial flexibility can have a significant impact on the value of new product development projects. We investigate how the market environment in which a firm operates influences the value and use of development flexibility. We characterize the market environment according to two dimensions, namely (i) its intensity, and (ii) its degree of innovation. We show that these two market characteristics can have a different effect on the value of flexibility. In particular, we show that more intense or innovative environments may increase or decrease the value of flexibility. For instance, we demonstrate that the option to defer a product launch …


Detection And Classification Of Malicious Javascript Via Attack Behavior Modelling, Yinxing XUE, Junjie WANG, Yang LIU, Hao XIAO, Jun SUN, Mahinthan CHANDRAMOHAN 2015 Singapore Management University

Detection And Classification Of Malicious Javascript Via Attack Behavior Modelling, Yinxing Xue, Junjie Wang, Yang Liu, Hao Xiao, Jun Sun, Mahinthan Chandramohan

Research Collection School Of Computing and Information Systems

Existing malicious JavaScript (JS) detection tools and commercial anti-virus tools mostly use feature-based or signature-based approaches to detect JS malware. These tools are weak in resistance to obfuscation and JS malware variants, not mentioning about providing detailed information of attack behaviors. Such limitations root in the incapability of capturing attack behaviors in these approches. In this paper, we propose to use Deterministic Finite Automaton (DFA) to abstract and summarize common behaviors of malicious JS of the same attack type. We propose an automatic behavior learning framework, named JS∗ , to learn DFA from dynamic execution traces of JS malware, where …


Automatic Video Self Modeling For Voice Disorder, Ju Shen, Changpeng Ti, Anusha Raghunathan, Sen-ching S. Cheung, Rita Patel 2015 University of Dayton

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 …


Meta-Raps Hybridization With Machine Learning Algorithms, Fatemah Al-Duoli 2015 Old Dominion University

Meta-Raps Hybridization With Machine Learning Algorithms, Fatemah Al-Duoli

Engineering Management & Systems Engineering Theses & Dissertations

This dissertation focuses on advancing the Metaheuristic for Randomized Priority Search algorithm, known as Meta-RaPS, by integrating it with machine learning algorithms. Introducing a new metaheuristic algorithm starts with demonstrating its performance. This is accomplished by using the new algorithm to solve various combinatorial optimization problems in their basic form. The next stage focuses on advancing the new algorithm by strengthening its relatively weaker characteristics. In the third traditional stage, the algorithms are exercised in solving more complex optimization problems. In the case of effective algorithms, the second and third stages can occur in parallel as researchers are eager to …


Simple Macro: Addon For World Of Warcraft, Yemane Gebreyesus 2015 California Polytechnic State University - San Luis Obispo

Simple Macro: Addon For World Of Warcraft, Yemane Gebreyesus

Computer Engineering

This senior project was started to try and solve a problem within World of Warcraft. That particular problem is the underdeveloped default macro interface, which Simple Macro aims to remedy by creating a more user-friendly interface that is accessible by a wider audience. It employs a click through method of accessing and editing data to reduce the amount of typing necessary. The addon also has a feature to specifically help players that want to change a target in certain groups of macros all at once. The project was developed in both Lua and XML.


The Gridgraphics Package, Paul Murrell 2015 The University of Auckland

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/


Correspondence Analysis On Generalised Aggregated Lexical Tables (Ca-Galt) In The Factominer Package, Belchin Kostov, Mónica Bécue-Bertaut, François Husson 2015 Transverse group for research in primary care

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 …


Changes In R, R Core Team 2015 University of Nebraska - Lincoln

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


R Foundation News, Kurt Hornik 2015 WU Wirtschaftsuniversität Wien

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 2015 University of Geneva

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.


Implementing Persistent O(1) Stacks And Queues In R, Shawn T. O'Neil 2015 Oregon State University

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.


R As An Environment For Reproducible Analysis Of Dna Amplification Experiments, Stefan Rödiger, Michał Burdukiewicz, Konstantin Blagodatskikh, Michael Jahn, Peter Schierack 2015 Brandenburg University of Technology Cottbus–Senftenberg

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 …


Showtext: Using System Fonts In R Graphics, Yixuan Qiu 2015 Purdue University

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.


Sae: An R Package For Small Area Estimation, Isabel Molina, Yolanda Marhuenda 2015 Universidad Carlos III de Madrid

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 2015 University of Granada

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 …


Fanplot: An R Package For Visualising Sequential Distributions, Guy J. Abel 2015 Vienna Institute of Demography, Austrian Academy of Sciences

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.


Editorial, Bettina Grün 2015 R Project

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.


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