Introductory R For Water Resources - Fall 2019 - University Of North Carolina At Chapel Hill,
2019
University of North Carolina at Chapel Hill
Introductory R For Water Resources - Fall 2019 - University Of North Carolina At Chapel Hill, David Gorelick, Gregory Characklis
All ECSTATIC Materials
This is all course material for R for Researchers, a one-credit course taught at UNC Chapel Hill in Fall 2019 to introduce upperclassmen and graduate students to the R programming language and apply learned skills in basic water resources applications, as well as other (semi-related) topics of interest to students.
Lecture notes were distributed before (as a subset of full lecture notes) and after lectures, and lectures involved collaborative coding exercises with students in class without any powerpoint material. Course material here includes:
Syllabus: rough schedule and description of lectures
Lectures: pdf lecture notes with embedded code, including …
Towards Secure And Fair Iiot-Enabled Supply Chain Management Via Blockchain-Based Smart Contracts,
2019
Wilfrid Laurier University
Towards Secure And Fair Iiot-Enabled Supply Chain Management Via Blockchain-Based Smart Contracts, Amal Eid Alahmadi
Theses and Dissertations (Comprehensive)
Integrating the Industrial Internet of Things (IIoT) into supply chain management enables flexible and efficient on-demand exchange of goods between merchants and suppliers. However, realizing a fair and transparent supply chain system remains a very challenging issue due to the lack of mutual trust among the suppliers and merchants. Furthermore, the current system often lacks the ability to transmit trade information to all participants in a timely manner, which is the most important element in supply chain management for the effective supply of goods between suppliers and the merchants. This thesis presents a blockchain-based supply chain management system in the …
A Compiler Target Model For Line Associative Registers,
2019
University of Kentucky
A Compiler Target Model For Line Associative Registers, Paul S. Eberhart
Theses and Dissertations--Electrical and Computer Engineering
LARs (Line Associative Registers) are very wide tagged registers, used for both register-wide SWAR (SIMD Within a Register )operations and scalar operations on arbitrary fields. LARs include a large data field, type tags, source addresses, and a dirty bit, which allow them to not only replace both caches and registers in the conventional memory hierarchy, but improve on both their functions. This thesis details a LAR-based architecture, and describes the design of a compiler which can generate code for a LAR-based design. In particular, type conversion, alignment, and register allocation are discussed in detail.
Automatic Query Reformulation For Code Search Using Crowdsourced Knowledge,
2019
Singapore Management University
Automatic Query Reformulation For Code Search Using Crowdsourced Knowledge, Mohammad M. Rahman, Chanchal K. Roy, David Lo
Research Collection School Of Computing and Information Systems
Traditional code search engines (e.g., Krugle) often do not perform well with natural language queries. They mostly apply keyword matching between query and source code. Hence, they need carefully designed queries containing references to relevant APIs for the code search. Unfortunately, preparing an effective search query is not only challenging but also time-consuming for the developers according to existing studies. In this article, we propose a novel query reformulation technique–RACK–that suggests a list of relevant API classes for a natural language query intended for code search. Our technique offers such suggestions by exploiting keyword-API associations from the questions and answers …
Automatic Query Reformulation For Code Search Using Crowdsourced Knowledge,
2019
Singapore Management University
Automatic Query Reformulation For Code Search Using Crowdsourced Knowledge, Mohammad M. Rahman, Chanchal K. Roy, David Lo
Research Collection School Of Computing and Information Systems
Traditional code search engines (e.g., Krugle) often do not perform well with natural language queries. They mostly apply keyword matching between query and source code. Hence, they need carefully designed queries containing references to relevant APIs for the code search. Unfortunately, preparing an effective search query is not only challenging but also time-consuming for the developers according to existing studies. In this article, we propose a novel query reformulation technique–RACK–that suggests a list of relevant API classes for a natural language query intended for code search. Our technique offers such suggestions by exploiting keyword-API associations from the questions and answers …
Deep Code Comment Generation With Hybrid Lexical And Syntactical Information,
2019
Peking University
Deep Code Comment Generation With Hybrid Lexical And Syntactical Information, Xing Hu, Ge Li, Xin Xia, David Lo, Zhi Jin
Research Collection School Of Computing and Information Systems
During software maintenance, developers spend a lot of time understanding the source code. Existing studies show that code comments help developers comprehend programs and reduce additional time spent on reading and navigating source code. Unfortunately, these comments are often mismatched, missing or outdated in software projects. Developers have to infer the functionality from the source code. This paper proposes a new approach named Hybrid-DeepCom to automatically generate code comments for the functional units of Java language, namely, Java methods. The generated comments aim to help developers understand the functionality of Java methods. Hybrid-DeepCom applies Natural Language Processing (NLP) techniques to …
Code Readability: A Proposal On The Effects Of Psychology And Comprehension In Software Development And Maintenance,
2019
University of Northern Iowa
Code Readability: A Proposal On The Effects Of Psychology And Comprehension In Software Development And Maintenance, Ethan Brian Sankey
Honors Program Theses
Because of the diversity and complexity of the hundreds of coding languages out there, code readability has become more and more of an issue as the years have passed and as the popularity of technology that required built-in computers has increased. With so many different formats, styles, and restrictions on each language, even a developer with experience in only a few common languages may have trouble remembering which language allows for certain indentation, which language requires variable instantiation, which language requires return statements at the end of functions. While I can appreciate the diversity and efficiency that having many different …
Pantry: A Macro Library For Python,
2018
San Jose State University
Pantry: A Macro Library For Python, Derek Pang
Master's Projects
Python lacks a simple way to create custom syntax and constructs that goes outside of its own syntax rules. A paradigm that allows for these possibilities to exist within languages is macros. Macros allow for a shorter set of syntax to expand into a longer set of instructions at compile-time. This gives the capability to evolve the language to fit personal needs.
Pantry, implements a hygienic text-substitution macro system for Python. Pantry achieves this through the introduction of an additional preparsing step that utilizes parsing and lexing of the source code. Pantry proposes a way to simply declare a pattern …
The R Journal (December 2018) 10(2): Complete Issue,
2018
University of Nebraska - Lincoln
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,
2018
University at Buffalo
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 …
Smm: An R Package For Estimation And Simulation Of Discrete-Time Semi-Markov Models,
2018
Université de Rouen-Normandie
Smm: An R Package For Estimation And Simulation Of Discrete-Time Semi-Markov Models, Vlad Stefan Barbu, Caroline Bérard, Dominique Cellier, Mathilde Sautreuil, Nicolas Vergne
The R Journal
Semi-Markov models, independently introduced by Lévy (1954), Smith (1955) and Takacs (1954), are a generalization of the well-known Markov models. For semi-Markov models, sojourn times can be arbitrarily distributed, while sojourn times of Markov models are constrained to be exponentially distributed (in continuous time) or geometrically distributed (in discrete time). The aim of this paper is to present the R package SMM, devoted to the simulation and estimation of discrete-time multi-state semi-Markov and Markov models. For the semi-Markov case we have considered: parametric and non-parametric estimation; with and without censoring at the beginning and/or at the end of sample …
Fica: Fastica Algorithms And Their Improved Variants,
2018
Aalto University
Fica: Fastica Algorithms And Their Improved Variants, Jari Miettinen, Klaus Nordhausen, Sara Taskinen
The R Journal
In independent component analysis (ICA) one searches for mutually independent nongaussian latent variables when the components of the multivariate data are assumed to be linear combinations of them. Arguably, the most popular method to perform ICA is FastICA. There are two classical versions, the deflation-based FastICA where the components are found one by one, and the symmetric FastICA where the components are found simultaneously. These methods have been implemented previously in two R packages, fastICA and ica. We present the R package fICA and compare it to the other packages. Additional features in fICA include optimization of the extraction order …
Snowboot: Bootstrap Methods For Network Inference,
2018
Southern Methodist University
Snowboot: Bootstrap Methods For Network Inference, Yuzhou Chen, Yulia R. Gel, Vyacheslav Lyubchich, Kusha Nezafati
The R Journal
Complex networks are used to describe a broad range of disparate social systems and natural phenomena, from power grids to customer segmentation to human brain connectome. Challenges of parametric model specification and validation inspire a search for more data-driven and flexible nonparametric approaches for inference of complex networks. In this paper we discuss methodology and R implementation of two bootstrap procedures on random networks, that is, patchwork bootstrap of Thompson et al. (2016) and Gel et al. (2017) and vertex bootstrap of Snijders and Borgatti (1999). To our knowledge, the new R package snowboot is the first implementation of the …
Addhaz: Contribution Of Chronic Diseases To The Disability Burden Using R,
2018
Vrije Universiteit Brussel
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, Geert Molenberghs
The R Journal
The increase in life expectancy followed by the burden of chronic diseases contributes to disability at older ages. The estimation of how much chronic conditions contribute to disability can be useful to develop public health strategies to reduce the burden. This paper introduces the R package addhaz, which is based on the attribution method (Nusselder and Looman, 2004) to partition disability into the additive contributions of diseases using cross-sectional data. The R package includes tools to fit the additive hazard model, the core of the attribution method, to binary and multinomial outcomes. The models are fitted by maximizing the …
Stplanr: A Package For Transport Planning,
2018
University of Leeds
Stplanr: A Package For Transport Planning, Robin Lovelace, Richard Ellison
The R Journal
Tools for transport planning should be flexible, scalable, and transparent. The stplanr package demonstrates and provides a home for such tools, with an emphasis on spatial transport data and non-motorized modes. The stplanr package facilitates common transport planning tasks including: downloading and cleaning transport datasets; creating geographic “desire lines” from origin-destination (OD) data; route assignment, locally and interfaces to routing services such as CycleStreets.net; calculation of route segment attributes such as bearing and aggregate flow; and ‘travel watershed’ analysis. This paper demonstrates this functionality using reproducible examples on real transport datasets. More broadly, the experience of developing and using R …
Changes In R,
2018
University of Nebraska - Lincoln
Conference Report: Why R? 2018,
2018
Warsaw University of Technology
Conference Report: Why R? 2018, Michał Burdukiewicz, Marta Karas, Leon Eyrich Jessen, Marcin KosińSki, Bernd Bischl, Stefan Rödiger
The R Journal
The primary purpose of the Why R? 2018 conference was to provide R programming language enthusiasts with an opportunity to meet and discuss experiences in R software development and analysis applications, for both academia and industry professionals. The event was held 2-5 August, 2018 in a city of Wroclaw, a strong academic and business center of Poland. The total of approximately 250 people from 6 countries attended the main conference event. Additionally, approximately 540 R users attended the pre-meetings in eleven cities across Europe (Figure 2).
Conference Report: Latinr 2018,
2018
Fundación Sadosky
Conference Report: Latinr 2018, Laura Acion, Natalia Da Silva, Riva Quiroga
The R Journal
LatinR <- Latin American Conference about the Use of R in Research + Development (LatinR) was an international conference whose goal was bringing together the Latin Ameri can R community. The inagural LatinR took place at the Universidad de Palermo in Buenos Aires, Argentina, on September 3 to 5, 2018. About 100 participants from more than 10 differ ent countries (e.g., Argentina, Uruguay, Chile, Peru, Ecuador, Brazil, Costa Rica, Venezuela, Spain, United States, Canada) attended LatinR.
LatinR will be an annual meeting that will rotate among different countries in Latin America. LatinR 2019 will be hosted by the Universidad Católica de Chile in Santiago de Chile on September 25 to 27
Shinyitemanalysis For Teaching Psychometrics And To Enforce Routine Analysis Of Educational Tests,
2018
Czech Academy of Sciences
Shinyitemanalysis For Teaching Psychometrics And To Enforce Routine Analysis Of Educational Tests, Patrícia Martinková, Adéla Drabinová
The R Journal
This work introduces ShinyItemAnalysis, an R package and an online shiny application for psychometric analysis of educational tests and items. ShinyItemAnalysis covers a broad range of psychometric methods and offers data examples, model equations, parameter estimates, interpretation of results, together with a selected R code, and is therefore suitable for teaching psychometric concepts with R. Furthermore, the application aspires to be an easy-to-use tool for analysis of educational tests by allowing the users to upload and analyze their own data and to automatically generate analysis reports in PDF or HTML. We argue that psychometric analysis should be a routine …
Bnclassify: Learning Bayesian Network Classifiers,
2018
Universidad Politécnica de Madrid
Bnclassify: Learning Bayesian Network Classifiers, Bojan Mihaljević, Concha Bielza, Pedro Larrañaga
The R Journal
The bnclassify package provides state-of-the art algorithms for learning Bayesian network classifiers from data. For structure learning it provides variants of the greedy hill-climbing search, a well-known adaptation of the Chow-Liu algorithm and averaged one-dependence estimators. It provides Bayesian and maximum likelihood parameter estimation, as well as three naive-Bayes specific methods based on discriminative score optimization and Bayesian model averaging. The implementation is efficient enough to allow for time-consuming discriminative scores on medium sized data sets. The bnclassify package provides utilities for model evaluation, such as cross-validated accuracy and penalized log-likelihood scores, and analysis of the underlying networks, including network …
