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1,034 results for “Empirical”
Experimental material of the article "An Empirical Experiment of a Usability Requirements Elicitation Method based on Interviews"
<p>Questionnaires, problems description and solution, and raw data of the paper "An Empirical Experiment of a Usability Requirements Elicitation Method based on Interviews"</p>
Experimental materials for "Reanalysis of Empirical Data on Java Local Variables with Narrow and Broad Scope"
<p>Data, scripts, and graphs for the paper "Reanalysis of Empirical Data on Java Local Variables with Narrow and Broad Scope", published in ICPC 2023.</p><p>See README file for details on directories and usage.</p>
An Empirical Study to Evaluate the Impact of Mindfulness at a Software Company (Laboratory Package)
<p>For the empirical study carried out in an Andalusian software company to evaluate the effects of the practise of mindfulness, this laboratory package contains the experimental material used during its execution, the data sets (both "csv" and "sav" files) derived from the experimental tasks, and the results of the statistical analysis (both scripts and plots).</p>
Supplemental Materials for "Convective boundary mixing in main-sequence stars: theory and empirical constraints"
<p>MESA inlists and data products used for generating the figures of the review paper: "Convective boundary mixing in main-sequence stars: theory and empirical constraints".</p>
WP5.1 Stochastic and Empirical Multi-Hazard Event Sets for Europe: Earthquake Stochastic Event Set for Europe (ISO3166 code)
<p>Stochastic event set of earthquake ground motion sets, and respective event catalogue. The whole event set covers 10.000 years.<br> Ground motion provided as PGA and spectral components for [0.2s, 0.5s, 1.0s, 2.0s]. <br> csv files follow xyz-structure. Each column (except 1 and 2) represent an earthquake.<br> longitude/latitude/{Magnitude}_PGA{PGAmax}/...</p> <p>For spectral component, the final results were filtered removing events with maximum groundmotions <0.001g. </p>
Empirical research in software architecture - perceptions of the community (supplementary material)
<p>This repository contains supplementary material for the manuscript "Empirical research in software architecture - perceptions of the community" published in the Journal of Systems and Software (<a href="https://doi.org/10.1016/j.jss.2023.111684">https://doi.org/10.1016/j.jss.2023.111684</a>):</p> <ul> <li>ICSA_papers.xlsx: This file contains the papers published at ICSA 2017-2021.</li> <li>invited_PC_members.xlsx: This file contains all names of PC members of ECSA, ICSA, QoSA, CBSE and WICSA for all instances of these conferences. This information was collected in June 2017 from the publicly available websites of these conferences as well as the publicly available online profiles of PC members.</li> <li>protocol.pdf: This files contains a summary of the survey protocol.</li> <li>responses.xls: This file contains all the responses of the survey from all respondents for all questions.</li> </ul>
Supporting material for PyESDv1.0.1 An open-source Python framework for empirical-statistical downscaling of climate information
<p>The nature and severity of climate change impacts varies significantly from region to region. Consequently, high-resolution climate information is needed for meaningful impact assessments and the design of mitigation strategies. This demand has led to an increase in the coupling of Empirical Statistical Downscaling (ESD) models to General Circulation Model (GCM) simulations of future climate. Here, we present a new open-source Python package (<em>pyESD; </em>github.com/Dan-Boat/PyESD) that implements several Perfect Prognosis ESD (PP-ESD) methods and the whole downscaling cycle. The latter includes routines for data preparation, predictor selection and construction, model selection and training, evaluation, utility tools for relevant statistical tests, visualization, and more. The package includes a collection of well-established Machine Learning algorithms and allows the user to choose a variety of estimators, cross-validation schemes, objective function measures, hyperparameter optimization, etc., in relatively few lines of code. The package is highly modular and flexible and allows quick and reproducible downscaling of any climate information, such as precipitation, temperature, wind speed, or even glacial retreat. The dataset presented here serves as supporting material for the package description and evaluation manuscript</p>
An Empirical Study of Vulnerabilities in Edge Frameworks to Support Security Testing Improvement
<p>This package contains the material collected to perform the empirical study described in our paper entitled ‘An Empirical Study of Vulnerabilities in Edge Frameworks to Support Security Testing Improvement’ authored by Jahanzaib MALIK (<a href="mailto:jahanzaib.malik@uni.lu">jahanzaib.malik@uni.lu</a>) and Fabrizio PASTORE (fabrizio.pastore@uni.lu).</p> <p> </p>
Supplementary materials for: Exploring the impact of read clustering thresholds on RADseq-based systematics: an empirical example from European amphibians
<p><span>Restriction site-Associated DNA sequencing (RADseq) has great potential for genome-wide systematics studies of non-model organisms. However, accurately assembling RADseq reads into orthologous loci remains a major challenge in the absence of a reference genome. Traditional assembly pipelines cluster putative orthologous sequences based on a user-defined clustering threshold. Because improper clustering of orthologs is expected to affect results in downstream analyses, it is crucial to design pipelines for empirically optimizing the clustering threshold. While this issue has been largely discussed from a population genomics perspective, it remains understudied in the context of phylogenomics and coalescent species delimitation. To address this issue, we generated RADseq assemblies of representatives of the amphibian genera <em>Discoglossus</em>, <em>Rana</em>, <em>Lissotriton</em> and <em>Triturus</em> using a wide range of clustering thresholds. Particularly, we studied the effects of the intra-sample Clustering Threshold (iCT) and between-sample Clustering Threshold (bCT) separately, as both are expected to differ in multi-species data sets. The obtained assemblies were used for downstream inference of concatenation-based phylogenies, and multi-species coalescent species trees and species delimitation. The results were evaluated in the light of a reference genome-wide phylogeny calculated from newly generated Hybrid-Enrichment markers, as well as extensive background knowledge on the species' systematics. Overall, our analyses show that the inferred topologies and their resolution are resilient to changes of the iCT and bCT, regardless of the analytical method employed. Except for some extreme clustering thresholds, all assemblies yielded identical, well-supported inter-species relationships that were mostly congruent with those inferred from the reference Hybrid-Enrichment data set. Similarly, coalescent species delimitation was consistent among similarity threshold values. However, we identified a strong effect of the bCT on the branch lengths of concatenation and species trees, with higher bCTs yielding trees with shorter branches, which might be a pitfall for downstream inferences of evolutionary rates. Our results suggest that the choice of assembly parameters for RADseq data in the context of shallow phylogenomics might be less challenging than previously thought. Finally, we propose a pipeline for empirical optimization of the iCT and bCT, implemented in optiRADCT, a series of scripts readily usable for future RADseq studies.</span></p>
Dataset for the paper "The Relationship Between Different Python Argument-Passing Mechanisms and Fixes: An Empirical Study"
<p>This is the replication package of the article</p> <p>The Relationship Between Different Python Argument-Passing Mechanisms and Fixes: An Empirical Study</p> <p> </p> <p>Abstract:</p> <p>Modern programming languages (such as Python, but not only) have introduced a variety of constructs and syntactical elements to make software development more efficient and concise. Examples include lambda functions, comprehension collections, of mechanisms to facilitate the passing of arguments to a function. While many of such constructs may, in principle, be beneficial for developers, recent studies have shown that certain programming constructs introduce atoms of confusion, and may therefore affect program understanding. Moreover, recent work has shown that changes to some constructs, namely functional constructs of Python, induce more fixes than other changes. This paper studies the effect of different Python argument-passing mechanisms to investigate their relationship with code proneness to be fixed. Specifically, we study the fix-proneness for what concerns the function definition, as well as its invocation. This is done by analyzing the evolutionary history of 200 Python projects, for a total of about 3M functions and 12M call sites. While there are varying effects for what concerns parameter declaration mechanisms, we found evidence that keyword-based argument passing is less defect prone than positional argument passing, and this is not affected by size-related confounding factors.</p>
Data from: Behavioral thermoregulation of caterpillars is altered by temperature, but not parasitism: an empirical field study
<p>Laboratory assays show that parasites often have lower heat tolerance than their hosts. But how physiological tolerances and behavioral responses of hosts and parasites combine to affect their ecological interactions in heterogeneous field environments is largely unknown. We addressed this challenge using the model insect system of the braconid wasp parasitoid, <em>Cotesia congregata</em>, and its caterpillar host, <em>Manduca sexta</em>. We used experimental manipulations of microclimate in the field to determine how elevated daytime temperatures altered the behavior, performance, and survival of the host and parasite. Our experimental manipulation increased daily maximum temperatures on host plants, but had negligible effects on overall mean temperature. These increased maximum temperatures resulted in subtle, biologically relevant, changes in physiology and behavior of the host and parasitoid. We found that parasitism by the wasp did not significantly alter caterpillar thermoregulatory behavior, while experimentally increased daily maximum temperatures resulted in both parasitized and unparasitized caterpillars being found more frequently in cooler microhabitats. Overall, we did not observe the complete parasitoid mortality seen at extreme temperatures in laboratory studies, but gained insight into sublethal effects of increased daily maximum temperatures on host and parasitoid behavior and physiology. Climate change will alter both the biotic and abiotic environments that organisms face, and we show here that empirical experiments in the field are important for understanding organismal response to these new environments. </p>
Data and Code for "A Ray-Based Input Distance Function to Model Zero-Valued Output Quantities: Derivation and an Empirical Application"
<p>This data and code archive provides all the data and code for replicating the empirical analysis that is presented in the journal article "A Ray-Based Input Distance Function to Model Zero-Valued Output Quantities: Derivation and an Empirical Application" authored by Juan José Price and Arne Henningsen and published in the Journal of Productivity Analysis (DOI: <a href="https://doi.org/10.1007/s11123-023-00684-1">10.1007/s11123-023-00684-1</a>).</p> <p>We conducted the empirical analysis with the "R" statistical software (version 4.3.0) using the add-on packages "combinat" (version 0.0.8), "miscTools" (version 0.6.28), "quadprog" (version 1.5.8), sfaR (version 1.0.0), stargazer (version 5.2.3), and "xtable" (version 1.8.4) that are available at CRAN. We created the R package "micEconDistRay" that provides the functions for empirical analyses with ray-based input distance functions that we developed for the above-mentioned paper. Also this R package is available at CRAN (https://cran.r-project.org/package=micEconDistRay).</p> <p>This replication package contains the following files and folders:</p> <ul> <li><strong>README</strong><br> This file</li> <li><strong>MuseumsDk.csv</strong><br> The original data obtained from the Danish Ministry of Culture and from Statistics Denmark. It includes the following variables: <ul> <li><em>museum</em>: Name of the museum. </li> <li><em>type</em>: Type of museum (Kulturhistorisk museum = cultural history museum; Kunstmuseer = arts museum; Naturhistorisk museum = natural history museum; Blandet museum = mixed museum).</li> <li><em>munic</em>: Municipality, in which the museum is located.</li> <li><em>yr</em>: Year of the observation.</li> <li><em>units</em>: Number of visit sites.</li> <li><em>resp</em>: Whether or not the museum has special responsibilities (0 = no special responsibilities; 1 = at least one special responsibility).</li> <li><em>vis</em>: Number of (physical) visitors.</li> <li><em>aarc</em>: Number of articles published (archeology).</li> <li><em>ach</em>: Number of articles published (cultural history).</li> <li><em>aah</em>: Number of articles published (art history).</li> <li><em>anh</em>: Number of articles published (natural history).</li> <li><em>exh</em>: Number of temporary exhibitions.</li> <li><em>edu</em>: Number of primary school classes on educational visits to the museum.</li> <li><em>ev</em>: Number of events other than exhibitions.</li> <li><em>ftesc</em>: Scientific labor (full-time equivalents).</li> <li><em>ftensc</em>: Non-scientific labor (full-time equivalents).</li> <li><em>expProperty</em>: Running and maintenance costs [1,000 DKK].</li> <li><em>expCons</em>: Conservation expenditure [1,000 DKK]. </li> <li><em>ipc</em>: Consumer Price Index in Denmark (the value for year 2014 is set to 1).</li> </ul> </li> <li><strong>prepare_data.R</strong><br> This R script imports the data set MuseumsDk.csv, prepares it for the empirical analysis (e.g., removing unsuitable observations, preparing variables), and saves the resulting data set as DataPrepared.csv.</li> <li><strong>DataPrepared.csv</strong><br> This data set is prepared and saved by the R script prepare_data.R. It is used for the empirical analysis.</li> <li><strong>make_table_descriptive.R</strong><br> This R script imports the data set DataPrepared.csv and creates the LaTeX table /tables/table_descriptive.tex, which provides summary statistics of the variables that are used in the empirical analysis.</li> <li><strong>IO_Ray.R</strong><br> This R script imports the data set DataPrepared.csv, estimates a ray-based Translog input distance functions with the 'optimal' ordering of outputs, imposes monotonicity on this distance function, creates the LaTeX table /tables/idfRes.tex that presents the estimated parameters of this function, and creates several figures in the folder /figures/ that illustrate the results.</li> <li><strong>IO_Ray_ordering_outputs.R</strong><br> This R script imports the data set DataPrepared.csv, estimates a ray-based Translog input distance functions, imposes monotonicity for each of the 720 possible orderings of the outputs, and saves all the estimation results as (a huge) R object allOrderings.rds.</li> <li><strong>allOrderings.rds</strong> (not included in the ZIP file, uploaded separately)<br> This is a saved R object created by the R script IO_Ray_ordering_outputs.R that contains the estimated ray-based Translog input distance functions (with and without monotonicity imposed) for each of the 720 possible orderings.</li> <li><strong>IO_Ray_model_averaging.R</strong><br> This R script loads the R object allOrderings.rds that contains the estimated ray-based Translog input distance functions for each of the 720 possible orderings, does model averaging, and creates several figures in the folder /figures/ that illustrate the results.</li> <li><strong>/tables/</strong><br> This folder contains the two LaTeX tables table_descriptive.tex and idfRes.tex (created by R scripts make_table_descriptive.R and IO_Ray.R, respectively) that provide summary statistics of the data set and the estimated parameters (without and with monotonicity imposed) for the 'optimal' ordering of outputs.</li> <li><strong>/figures/</strong><br> This folder contains 48 figures (created by the R scripts IO_Ray.R and IO_Ray_model_averaging.R) that illustrate the results obtained with the 'optimal' ordering of outputs and the model-averaged results and that compare these two sets of results.</li> </ul>
Data from: Relational values of nature in empirical research: A systematic review
<p>In the past five years, scholarly and policy attention to relational values, a concept that articulates plural values of nature, has grown steadily. To date, there are no published syntheses of empirical research that explicitly address relational values. We perform a systematic literature review of n = 72 empirical studies of relational values to summarize the state of current research and to identify opportunities for future research and conceptual development. In our analysis, we categorize what authors identify as relational values and summarize study characteristics (e.g., study location, methods approach.) Authors collectively report n = 312 unique relational values. Categories of <em>identity, social cohesion, livelihoods, connection to place/human-nature connection</em>, and <em>religion</em> are most common. Scholarship that explicitly addresses relational values has increased since 2017 and exhibits substantial diversity: in how relational values are conceptualized (or not); in disciplinary associations; in geographical location; and in data collection methods. We find that most empirical research on relational values does not justify how its results reflect characteristics that establish the relational values concept as unique from other environmental values concepts. As a result, diverse interpretations of the relational values concept pose the risk of the relational values concept being so broad and inclusive that it becomes meaningless, or at least meaning-light.</p>
Dataset: What can be concluded from User Feedback? - An Empirical Study
<p>In 2022, we conducted a study on the awareness of users concerning existing software in order to compare users' description and their feedback.</p> <p>This data set contain 100 participants' description and feedback about the Komoot hiking app. The aspects were manually coded in the data set.</p>
Data for study "Digital tools for innovative higher education teaching - a Scoping Review of Empirical Studies".
<p>The goal of this research is to point out, by a scoping review of the papers published between 2020 and 2023, the digital tools used in the teaching process at the higher education level. The dataset was collected using Web of Science and Scopus databases.</p> <p>The dataset contains the following elements:</p> <ol> <li>paper details (Authors, Publication Year, Article Title, DOI),</li> <li>OECD classification,</li> <li>teaching tool assigned to paper.</li> </ol>
Reproduction package for "Revisiting the reproducibility of empirical software engineering studies based on data retrieved from development repositories"
<p>Reproduction package for "Revisiting the reproducibility of empirical software engineering studies based on data retrieved from development repositories", published in Information and Software Technology, Volume 164, December 2023. DOI: <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.infsof.2023.107318" target="_blank" rel="noreferrer noopener"><span><span>https://doi.org/10.1016/j.infsof.2023.107318</span></span></a></p>
Evaluating the Impact of Third-Party Library Reuse in Java Projects: An Empirical Study
<p>Update, we have added the following:<br> - `dataset.ipynb`: Computes all the dataset used for this study. The user needs to use a call graph generator like OPAL/WALA.</p> <p>- `loc.ipynb`: Computes a dataset for LOC information given a call graph dataset</p> <p>- `called-reuse.ipynb`: Computing a dataset for all called functions and LOC in third-party libraries</p> <p>- `megamorphic.ipynb`: Empirically decide the megamorphic call sites. <br> <br> This part of the submission related to the paper "Evaluating the Impact of Third-Party Library Reuse in Java Projects: An Empirical Study". Here is a table of contents:</p> <ul> <li>`census.csv`: extracted data from the Census-II</li> <li>`releases_all.csv`: all releases available from Maven Coordinates in Census-II</li> <li>`releases_jar.csv`: dataset of all releases with a POM and JAR file</li> <li>`releases_jar_6_months.csv`: releases selected when studiying the 6-month interval</li> <li>`releases_jar_6_months.csv`: releases selected when comparing consecutive versions per artefactid and groupid</li> <li>`loc_composition.csv`: data on the ratio of insourced and outsourced code in project releases</li> <li>`loc_desc_without_lambdas.csv`: mined data on LOC information and class information.</li> <li>`loc_reuse_lower_bound.csv`: data on the ratio of reused LOC and functions of outsourced code, lower-bound</li> <li>`loc_reuse_upper_bound.csv`: data on the ratio of reused LOC and functions of outsourced code, upper-bound</li> </ul>
Empirical primary studies where gamification is used to study energy behavior
<p>The data set is used to conduct a literature review on primary studies where gamification is used to study energy behavior; it contains original search results and after-filter results. The data set also includes a Bib file for all reviewed studies.</p>
The Moderating Effect of Employee Agility on the Link between Employee Vitality, Digital Literacy and Transformational Leadership with Job Performance: An Empirical Study of HR Practitioners in the Manufacturing Sector of Northern Malaysia.
<p>This is a dataset for a study that examines the effects of employee vitality, digital literacy, and transformational leadership on job performance. Additionally, it investigates the moderating role of employee agility in these relationships. Data were collected from HR practitioners in manufacturing companies in the northern region of Malaysia for analysis. The results indicate that the job performance of HR practitioners is positively influenced by employee vitality, digital literacy and transformational leadership. </p>
Results from the EMPIRE model in the openENTRANCE project
<p>This dataset contains scenario results from the EMPIRE model as part of Case Study 1 in the openENTRANCE project.</p> <p>The data file follows the IAMC data format and the conventions established by the openENTRANCE project. See <a href="https://github.com/openENTRANCE/openentrance">https://github.com/openENTRANCE/openentrance</a> for details.</p> <p>Visit the openENTRANCE Scenario Explorer at <a href="https://data.ene.iiasa.ac.at/openentrance">https://data.ece.iiasa.ac.at/openentrance</a> for more information about the openENTRANCE project and other datasets.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.