Computer Sciences Commons^™

Implementation And Testing Of A Book Lookup System For The Robert E. Kennedy Library, Casey C. Sheehan

Computer Science and Software Engineering

The goal of this senior project centered around improving the quality of student and teacher experiences when visiting the library. The task of finding a book amongst the shelves is an arduous one, which I felt could be improved upon through implementation and testing of a Book Lookup system for the Cal Poly Robert E. Kennedy Library. Development for this project was done using a Python framework. Testing and earlier designs were also created using JavaScript and PHP. Repeated tests were conducted on the accuracy of the software and its ability to decrease user search-time when compared to conventional methods.

Review Classification, Balraj Aujla

Computer Science and Software Engineering

The goal of this project is to find a way to analyze reviews and determine the sentiment of a review. It uses various machine learning techniques in order to achieve its goals such as SVMs and Naive Bayes. Overall the purpose is to learn many different machine learning techniques, determine which ones would be useful for the project, then compare the results. Research is the foremost goal of the project, and it is able to determine the better algorithm for review classification, naive bayes or an SVM. In addition, an SVM which actually gave review’s scores rather than just classifying …

Security Techniques For Sensor Systems And The Internet Of Things, Daniele Midi

Open Access Dissertations

Sensor systems are becoming pervasive in many domains, and are recently being generalized by the Internet of Things (IoT). This wide deployment, however, presents significant security issues.

We develop security techniques for sensor systems and IoT, addressing all security management phases. Prior to deployment, the nodes need to be hardened. We develop nesCheck, a novel approach that combines static analysis and dynamic checking to efficiently enforce memory safety on TinyOS applications. As security guarantees come at a cost, determining which resources to protect becomes important. Our solution, OptAll, leverages game-theoretic techniques to determine the optimal allocation of security resources in …

Computational Fluid Dynamics Is Key To Better Flying Aircraft, Nihad E. Daidzic

Aviation Department Publications

No abstract provided.

Fault Detection And Localization Techniques For Concurrent Programs, Jing Xu

Computer Science and Engineering Dissertations - Archive

Concurrency faults are hard to detect and localize due to the nondeterministic behavior of concurrent programs. In this dissertation, we present three approaches to detecting and localizing faults in concurrent programs. The first approach identifies erroneous event patterns in a failed concurrent program execution. Given a failed execution, we characterize the execution as a sequence of context-switch points and then use controlled execution to distinguish erroneous context-switch points from benign context-switch points. Erroneous context-switch points are used to derive erroneous event patterns, which allow the user to quickly localize the actual fault. Our experiments were conducted on thirteen programs. Seven …

Exploratory Data Analysis Over Online Community Networks, Azade Nazi

Computer Science and Engineering Dissertations - Archive

An online community network links entities (e.g., users, products) with various relationships (e.g., friendship, co-purchase) and make such information available for access through a web interface. There are numerous such networks on the web, ranging from Twitter, Instagram, which links users as ``followers-followees'', to amazon.com, ebay.com, which links products with relationships such as ``also buy''. Online community networks often feature a web interface that only allows local-neighborhood queries - i.e., given a entity (e.g., users, products) of the community network as input, the system only returns the immediate neighbors of the entity. Further, the rate limit constraint restricts the number …

Integrative Approaches For Large-Scale Biomedical Data Analysis, Ashis Kumer Biswas

Computer Science and Engineering Dissertations - Archive

Advancement of the Next Generation Sequencing (NGS), also known as the High Throughput Sequencing (HTS) technologies allow researchers investigate genome, transcriptome, or epigenome of any organism from any perspective, thereby contributing to the enrichment of the biomedical data repositories for many of the lesser known phenomena. The regulatory activities inside genome by the non-coding RNAs (ncRNAs), the transcribed product of the long-neglected "junk DNA" molecules is one such phenomenon. While large-scale data about the ncRNAs are becoming publicly available, the computational challenges are being imposed to the bioinformaticians for efficient mining to get reliable answers to few subtle questions. Given …

Incremental And Decremental Svm For Regression, Honorius Gâlmeanu, Lucian Mircea Sasu, Rǎzvan Andonie

All Faculty Scholarship for the College of the Sciences

Training a support vector machine (SVM) for regression (function approximation) in an incremental/decremental way consists essentially in migrating the input vectors in and out of the support vector set with specific modification of the associated thresholds. We introduce with full details such a method, which allows for defining the exact increments or decrements associated with the thresholds before vector migrations take place. Two delicate issues are especially addressed: the variation of the regularization parameter (for tuning the model performance) and the extreme situations where the support vector set becomes empty. We experimentally compare our method with several regression methods: the …

Changes In R, R Core Team

The R Journal

CHANGES IN R 3.3.2 patched

News From The Bioconductor Project, Bioconductor Core Team

The R Journal

The Bioconductor project provides tools for the analysis and comprehension of high throughput genomic data. Bioconductor 3.4 was released on 18 October, 2016. It is com patible with R 3.3 and consists of 1296 software packages, 309 experiment data packages, and 933 up-to-date annotation packages. The release announcement includes descriptions of 101 new packages, and updated NEWS files for many additional packages. Start using Bioconductor by installing the most recent version of R and evaluating the commands

Mctest: An R Package For Detection Of Collinearity Among Regressors, Muhammad Imdadullah, Muhammad Aslam, Saima Altaf

The R Journal

It is common for linear regression models to be plagued with the problem of multicollinearity when two or more regressors are highly correlated. This problem results in unstable estimates of regression coefficients and causes some serious problems in validation and interpretation of the model. Different diagnostic measures are used to detect multicollinearity among regressors. Many statistical software and R packages provide few diagnostic measures for the judgment of multicollinearity. Most widely used diagnostic measures in these software are: coefficient of determination (R2), variance inflation factor/tolerance limit (VIF/TOL), eigenvalues, condition number (CN) and condition index (CI) etc. In this manuscript, we …

Weighted Distance Based Discriminant Analysis: The R Package Wedibadis, Itziar Irigoien, Francesc Mestres, Concepcion Arenas

The R Journal

The WeDiBaDis package provides a user friendly environment to perform discriminant analysis (supervised classification). WeDiBaDis is an easy to use package addressed to the biological and medical communities, and in general, to researchers interested in applied studies. It can be suitable when the user is interested in the problem of constructing a discriminant rule on the basis of distances between a relatively small number of instances or units of known unbalanced-class membership measured on many (possibly thousands) features of any type. This is a current situation when analyzing genetic biomedical data. This discriminant rule can then be used both, as …

Computing Pareto Frontiers And Database Preferences With The Rpref Package, Patrick Roocks

The R Journal

The concept of Pareto frontiers is well-known in economics. Within the database community there exist many different solutions for the specification and calculation of Pareto frontiers, also called Skyline queries in the database context. Slight generalizations like the combination of the Pareto operator with the lexicographical order have been established under the term database preferences. In this paper we present the rPref package which allows to efficiently deal with these concepts within R. With its help, database preferences can be specified in a very similar way as in a state-of-the-art database management system. Our package provides algorithms for an …

Dcovts: Distance Covariance/Correlation For Time Series, Maria Pitsillou, Konstantinos Fokianos

The R Journal

The distance covariance function is a new measure of dependence between random vectors. We drop the assumption of iid data to introduce distance covariance for time series. The R package dCovTS provides functions that compute and plot distance covariance and correlation functions for both univariate and multivariate time series. Additionally it includes functions for testing serial independence based on distance covariance. This paper describes the theoretical background of distance covariance methodology in time series and discusses in detail the implementation of these methods with the R package dCovTS.

Subgroup Discovery With Evolutionary Fuzzy Systems In R: The Sdefsr Package, Ángel M. García, Francisco Charte, Pedro González, Cristóbal J. Carmona, María J. Del Jesus

The R Journal

Subgroup discovery is a data mining task halfway between descriptive and predictive data mining. Nowadays it is very relevant for researchers due to the fact that the knowledge extracted is simple and interesting. For this task, evolutionary fuzzy systems are well suited algorithms because they can find a good trade-off between multiple objectives in large search spaces. In fact, this paper presents the SDEFSR package, which contains all the evolutionary fuzzy systems for subgroup discovery presented throughout the literature. It is a package without dependencies on other software, providing functions with recommended default parameters. In addition, it brings a graphical …

Variants Of Simple Correspondence Analysis, Rosaria Lombardo, Eric J. Beh

The R Journal

This paper presents the R package CAvariants (Lombardo and Beh, 2017). The package performs six variants of correspondence analysis on a two-way contingency table. The main function that shares the same name as the package– CAvariants– allows the user to choose (via a series of input parameters) from six different correspondence analysis procedures. These include the classical approach to (symmetrical) correspondence analysis, singly ordered correspondence analysis, doubly ordered correspondence analysis, non symmetrical correspondence analysis, singly ordered non symmetrical correspondence analysis and doubly ordered non symmetrical correspondence analysis. The code provides the flexibility for constructing either a classical correspondence plot or …

Diverse: An R Package To Analyze Diversity In Complex Systems, Miguel R. Guevara, Dominik Hartmann, Marcelo Mendoza

The R Journal

The package diverse provides an easy-to-use interface to calculate and visualize different aspects of diversity in complex systems. In recent years, an increasing number of research projects in social and interdisciplinary sciences, including fields like innovation studies, scientometrics, economics, and network science have emphasized the role of diversification and sophistication of socioeconomic systems. However, so far no dedicated package exists that covers the needs of these emerging fields and interdisciplinary teams. Most packages about diversity tend to be created according to the demands and terminology of particular areas of natural and biological sciences. The package diverse uses interdisciplinary concepts of …

Design Of The Tronco Bioconductor Package For Translational Oncology, Marco Antoniotti, Giulio Caravagna, Luca De Sano, Alex Graudenzi, Giancarlo Mauri, Bud Mishra, Daniele Ramazzotti

The R Journal

Models of cancer progression provide insights on the order of accumulation of genetic alterations during cancer development. Algorithms to infer such models from the currently available mutational profiles collected from different cancer patients (cross-sectional data) have been defined in the literature since late the 90s. These algorithms differ in the way they extract a graphical model of the events modelling the progression, e.g., somatic mutations or copy-number alterations.

TRONCO is an R package for TRanslational ONcology which provides a series of functions to assist the user in the analysis of cross-sectional genomic data and, in particular, it implements …

Qpot: An R Package For Stochastic Differential Equation Quasi-Potential Analysis, Christopher M. Moore, Christopher R. Stieha, Ben C. Nolting, Maria K. Cameron, Karen C. Abbott

The R Journal

QPot (pronounced ky oo + p¨ at) is an R package for analyzing two-dimensional systems of stochastic differential equations. It provides users with a wide range of tools to simulate, analyze, and visualize the dynamics of these systems. One of QPot’s key features is the computation of the quasi-potential, an important tool for studying stochastic systems. Quasi-potentials are particularly useful for comparing the relative stabilities of equilibria in systems with alternative stable states. This paper describes QPot’s primary functions, and explains how quasi-potentials can yield insights about the dynamics of stochastic systems. Three worked examples guide users through the application …

Multiplencc: Inverse Probability Weighting Of Nested Case-Control Data, Nathalie C. Støer, Sven Ove Samuelsen

The R Journal

Reuse of controls from nested case-control designs can increase efficiency in many situations, for instance with competing risks or in other multiple endpoints situations. The matching between cases and controls must be broken when controls are to be used for other endpoints. A weighted analysis can then be performed to take care of the biased sampling from the cohort. We present the R package multipleNCC for reuse of controls in nested case-control studies by inverse probability weighting of the partial likelihood. The package handles right-censored, left-truncated and additionally matched data, and varying numbers of sampled controls and the whole analysis …

Editorial, Michael Lawrence

The R Journal

On behalf of the editorial board, I am pleased to publish Volume 8, Issue 2 of the R Journal. This issue contains 33 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). This issue highlights the breadth and depth of the R package ecosystem, covering advances in statistical computing and visualization, as well as novel applications of R in specific domains. The authors have described a small but representative sample of the now more than 11000 packages …

Normal Tolerance Interval Procedures In The Tolerance Package, Derek S. Young

The R Journal

Statistical tolerance intervals are used for a broad range of applications, such as quality control, engineering design tests, environmental monitoring, and bioequivalence testing. tolerance is the only R package devoted to procedures for tolerance intervals and regions. Perhaps the most commonly-employed functions of the package involve normal tolerance intervals. A number of new procedures for this setting have been included in recent versions of tolerance. In this paper, we discuss and illustrate the functions that implement these normal tolerance interval procedures, one of which is a new, novel type of operating characteristic curve.

Micompr: An R Package For Multivariate Independent Comparison Of Observations, Nuno Fachada, João Rodrigues, Vitor V. Lopes, Rui C. Martins, Agostinho C. Rosa

The R Journal

The R package micompr implements a procedure for assessing if two or more multivariate samples are drawn from the same distribution. The procedure uses principal component analysis to convert multivariate observations into a set of linearly uncorrelated statistical measures, which are then compared using a number of statistical methods. This technique is independent of the distributional properties of samples and automatically selects features that best explain their differences. The procedure is appropriate for comparing samples of time series, images, spectrometric measures or similar high-dimension multivariate observations

Rnrfa: An R Package To Retrieve, Filter And Visualize Data From The Uk National River Flow Archive, Claudia Vitolo, Matthew Fry, Wouter Buytaert

The R Journal

The UK National River Flow Archive (NRFA) stores several types of hydrological data and metadata: daily river flow and catchment rainfall time series, gauging station and catchment information. Data are served through the NRFA webservices via experimental RESTful APIs. Obtaining NRFA data can be unwieldy due to complexities in handling HTTP GET requests and parsing responses in JSON and XML formats. The rnrfa package provides a set of functions to programmatically access, filter, and visualize NRFA data using simple R syntax. This paper describes the structure of the rnrfa package, including examples using the main functions gdf() and cmr() for …

Simulating Correlated Binary And Multinomial Responses Under Marginal Model Specification: The Simcormultres Package, Anestis Touloumis

The R Journal

We developed the R package SimCorMultRes to facilitate simulation of correlated categorical (binary and multinomial) responses under a desired marginal model specification. The simulated correlated categorical responses are obtained by applying threshold approaches to correlated continuous responses of underlying regression models and the dependence structure is parametrized in terms of the correlation matrix of the latent continuous responses. This article provides an elaborate introduction to the SimCorMultRes package demonstrating its design and usage via three examples. The package can be obtained via CRAN.

Nmfgpu4r: Gpu-Accelerated Computation Of The Non-Negative Matrix Factorization (Nmf) Using Cuda Capable Hardware, Sven Koitka, Christoph M. Friedrich

The R Journal

In this work, a novel package called nmfgpu4R is presented, which offers the computation of Non-negative Matrix Factorization (NMF) on Compute Unified Device Architecture (CUDA) platforms within the R environment. Benchmarks show a remarkable speed-up in terms of time per iteration by utilizing the parallelization capabilities of modern graphics cards. Therefore the application of NMFgets more attractive for real-world sized problems because the time to compute a factorization is reduced by an order of magnitude.

Comf: An R Package For Thermal Comfort Studies, Marcel Schweiker

The R Journal

The field of thermal comfort generated a number of thermal comfort indices. Their code implementation needs to be done by individual researchers. This paper presents the R package, comf, which includes functions for common and new thermal comfort indices. Additional functions allow comparisons between the predictive performance of these indices. This paper reviews existing thermal comfort indices and available code implementations. This is followed by the description of the R package and an example how to use the R package for the comparison of different thermal comfort indices on data from a thermal comfort study.

An Introduction To Principal Surrogate Evaluation With The Pseval Package, Michael C. Sachs, Erin E. Gabriel

The R Journal

We describe a new package called pseval that implements the core methods for the evaluation of principal surrogates in a single clinical trial. It provides a flexible interface for defining models for the risk given treatment and the surrogate, the models for integration over the missing counterfactual surrogate responses, and the estimation methods. Estimated maximum likelihood and pseudo-score can be used for estimation, and the bootstrap for inference. A variety of post-estimation methods are provided, including print, summary, plot, and testing. We summarize the main statistical methods that are implemented in the package and illustrate its use from the perspective …

Quantreg.Nonpar: An R Package For Performing Nonparametric Series Quantile Regression, Michael Lipsitz, Alexandre Belloni, Victor Chernozhukov, Iván Fernández-Val

The R Journal

The R package quantreg.nonpar implements nonparametric quantile regression methods to estimate and make inference on partially linear quantile models. quantreg.nonpar obtains point estimates of the conditional quantile function and its derivatives based on series approximations to the nonparametric part of the model. It also provides point-wise and uniform confidence intervals over a region of covariate values and/or quantile indices for the same functions using analytical and resampling methods. This paper serves as an introduction to the package and displays basic functionality of the functions contained within.

Two-Tier Latent Class Irt Models In R, Silvia Bacci, Francesco Bartolucci

The R Journal

In analyzing data deriving from the administration of a questionnaire to a group of individuals, Item Response Theory (IRT) models provide a flexible framework to account for several aspects involved in the response process, such as the existence of multiple latent traits. In this paper, we focus on a class of semi-parametric multidimensional IRT models, in which these traits are represented through one or more discrete latent variables; these models allow us to cluster individuals into homogeneous latent classes and, at the same time, to properly study item characteristics. In particular, we follow a within-item multidimensional formulation similar to that …