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3,947 results for “Requirements”
Ethical Requirements Stack for Fitness App
<p>An image of the Ethical Requirements Stack for the Fitness App</p>
Dataset of "Knowledge-based Sense Disambiguation of Multiword Expressions in Requirements Documents"
<p>This is the dataset used in the paper "Knowledge-based Sense Disambiguation of Multiword Expressions in Requirements Documents" at AIRE'21</p> <p> </p> <p>In this paper, we explore the use of a multiword expression detection in combination with a knowledge-based word sense disambiguation to disambiguate expressions in requirements documents.</p> <p>The dataset comprises a gold standard for multiword expression detection and sense disambiguation for Wikipedia and WordNet 3.1.</p> <p>It covers 18 projects: CM1, EBT and GANTT as well as the 15 projects of the NFR dataset.</p> <p> </p> <p><strong>File format</strong></p> <p>We use a tab-separated version of the DiMSUM file format and extended it with sense information.</p> <p>The nine original DiMSUM tab-separated columns:</p> <p>1. token offset</p> <p>2. word</p> <p>3. lowercase lemma</p> <p>4. POS</p> <p>5. MWE tag</p> <p>6. offset of parent token (i.e. previous token in the same MWE), if applicable</p> <p>7. strength level encoded in the tag, if applicable. Currently not used</p> <p>8. supersense label, Currently not used</p> <p>9. sentence ID</p> <p> </p> <p>and the two further columns for sense information:</p> <p>10. Wikipedia article name</p> <p>11. WordNet 3.1 synset</p> <p> </p> <p>The last two columns might end with .1 or .0 indicating that the sense is a fully applicable or partial sense of a multiword expression.</p> <p><strong>Attribution (of datasets used)</strong></p> <p>The NFR Dataset can be attributed to Jane Cleland-Huang.<br> Jane Cleland-Huang, Sepideh Mazrouee, Huang Liguo, & Dan Port. (2007). nfr [Data set]. Zenodo. Available: <a href="http://doi.org/10.5281/zenodo.268542">http://doi.org/10.5281/zenodo.268542</a><br> </p> <p>The CM1, EBT and GANTT datasets were retrieved from the Center of Excellence for Software & Systems Traceability (CoEST) <a href="https://doi.org/10.5281/zenodo.3309669">http://coest.org/</a></p>
Supplement to Creating Mobile Self-Triage Applications: Requirements and Usability Perspectives
<p>This is a supplement to our paper "Creating Mobile Self-Triage Applications: Requirements and Usability Perspectives", presented at the <strong>Second International Workshop on Requirements Engineering for Well-Being, Aging, and Health</strong> (REWBAH 2021, https://sites.google.com/view/rewbah2021) and published by IEEE CS.</p> <p>This zip file contains the email template used to invite participants, the consent letter, the pre-test interview, the protocol for the evaluator, the participant tasks, a questionnaire, and a description of three scenarios.</p> <p>Note that the Symptoms Pal application discussed in the paper was named <em>Symptom Checker Mobile</em> (SCM) at the time we performed the usability study.</p>
Evaluation of the shucking of certain species of scallops contaminated with domoic acid with a view to the production of edible parts meeting the safety requirements foreseen in the Union legislation - Summary statistics on occurrence and consumption data and exposure assessment results
<p>DomoicAcid_Raw_Occurrence_Data.CSV contains the raw occurrence dataset on Domoic Acid contaminant in scallops as extracted from EFSA DWH on the 9 June 2020, 16,369 samples presented in the opinion as described in its section 1.3.2. Occurrence data submitted to EFSA. The data is provided in .csv format. This dataset is compliant with EFSA SSD model and contains two additional columns documenting issues identified in the cleaning process (column: issue) and the action taken (column: outcome) to address the issue (e.g. delete record or update values in specific fields).</p> <p>The link to the catalogues of controlled terminologies can be found under "Related identifiers”.</p> <p><strong>Annex_</strong> DomoicAcid</p> <p>Table of contents</p> <p><br> Table A1</p> <p>Description of FoodEx2 codes used to describe scallop species and their anatomical parts</p> <p>Table A2</p> <p>Data cleaning steps applied to occurrence data on domoic acid in scallops</p> <p>Table A3</p> <p>Percentage of Left-Censored data and descriptive statistics for Limits of detection (LODs) and Limits of quantification (LOQs) for domoic acid in scallops (mg/kg)</p> <p>Table A4</p> <p>Descriptive statistics for domoic acid in scallops (mg/kg) as reported in the cleaned database (statistics weighted by number of units per sample)</p> <p>Table A5</p> <p>Descriptive statistics of body tissue weights (g) of scallops as submitted by data providers</p>
Text-fig. 7. Number of required character state changes under parsimony (steps) for various positions of Mugideiriflora portugallica, based on the Doyle and Endress character matrix and backbone tree (Doyle and Endress 2000, 2014). in Multiparted, Apocarpous Flowers From The Early Cretaceous Of Eastern North America And Portugal
Text-fig. 7. Number of required character state changes under parsimony (steps) for various positions of Mugideiriflora portugallica, based on the Doyle and Endress character matrix and backbone tree (Doyle and Endress 2000, 2014).
Text-fig. 8. Number of required character state changes under parsimony (steps) for various positions of Lambertiflora elegans, based on the Doyle and Endress character matrix and backbone tree (Doyle and Endress 2000, 2014). in Multiparted, Apocarpous Flowers From The Early Cretaceous Of Eastern North America And Portugal
Text-fig. 8. Number of required character state changes under parsimony (steps) for various positions of Lambertiflora elegans, based on the Doyle and Endress character matrix and backbone tree (Doyle and Endress 2000, 2014).
Text-fig. 9. Number of required character state changes under parsimony (steps) for various positions of Atlantocarpus virginiensis, based on the Doyle and Endress character matrix and backbone tree (Doyle and Endress 2000, 2014). in Multiparted, Apocarpous Flowers From The Early Cretaceous Of Eastern North America And Portugal
Text-fig. 9. Number of required character state changes under parsimony (steps) for various positions of Atlantocarpus virginiensis, based on the Doyle and Endress character matrix and backbone tree (Doyle and Endress 2000, 2014).
The LSST Dark Energy Science Collaboration (DESC) Science Requirements Document v1 Released Data Products
<p>This tarball includes software and data products associated with the DESC Science Requirements Document (SRD) v1. See the "Executive Summary and User Guide" in the enclosed PDF of the DESC SRD for instructions on how to use and cite those products. The DESC SRD is described on <a href="https://arxiv.org/abs/1809.01669">arXiv</a> as follows:</p> <p>The Large Synoptic Survey Telescope (LSST) Dark Energy Science Collaboration (DESC) will use five cosmological probes: galaxy clusters, large scale structure, supernovae, strong lensing, and weak lensing. The Science Requirements Document (SRD) quantifies the expected dark energy constraining power of these probes individually and together, with conservative assumptions about analysis methodology and follow-up observational resources based on our current understanding and the expected evolution within the field in the coming years. We then define requirements on analysis pipelines that will enable us to achieve our goal of carrying out a dark energy analysis consistent with the Dark Energy Task Force definition of a Stage IV dark energy experiment.</p>
Empirical Research on Requirements Quality: A Systematic Mapping Study - Dataset
<p>We conducted a systematic mapping study on the empirical research into the quality of requirements titled "Empirical Research on Requirements Quality: A SystematicMapping Study" in the Requirements Engineering Journal. This is our replication package.</p> <p>Full Abstract:</p> <p>Research has repeatedly shown that high quality requirements are essential for the success of development projects. While the term “quality” is pervasive in the field of requirements engineering and while the body of research on requirements quality is large, there is no meta study of the field that overviews and compares the concrete quality attributes addressed by the community. To fill this knowledge gap, we conducted a systematic mapping study of the scientific literature. We retrieved 6,905 articles from six academic databases, which we filtered down to our 105 relevant primary studies: explicitly defining, improving, or evaluating quality attributes while including an empirical research component. We found that research on requirements quality focuses on improvement techniques, with very few primary studies addressing evidence-based definitions and evaluations of quality attributes. Among the 12 quality attributes identified, the most prominent in the field are ambiguity, completeness, consistency, and correctness. We identified 111 sub-types of quality attributes such as “template conformance” for consistency or “passive voice” for ambiguity. Ambiguity has the largest share of these sub-types. The artefacts being studied are mostly referred to in the broadest sense as “requirements,” while little research targets quality attributes in specific types of requirements such as use cases or user stories. We present and discuss our detailed analysis along the various quality attributes. Our findings highlightthe need to conduct more grounded research aimed at “definitions,” to use more diverse research methods, and to address a more diverse set of requirements types.</p>
Supporting Data for Human Factors in Developing Automated Vehicles:A Requirements Engineering Perspective
<p>This data set complements our manuscript in submission with the title:</p> <p>"Human Factors in Developing Automated Vehicles: A Requirements Engineering Perspective"</p> <p>We provide two files:</p> <p>a) the interview guide</p> <p>b) an overview that maps from themes to example quotes and codes derived from particular interview subjects</p>
"Palmitoylation Mediates Membrane Association of Hepatitis E Virus ORF3 Protein and is Required for Infectious Particle Secretion"
<p><strong>Hepatitis E virus (HEV) is a positive-strand RNA virus encoding 3 open reading frames (ORF). HEV ORF3 protein is a small, hitherto poorly characterized protein involved in viral particle secretion and possibly other functions. Here, we show that HEV ORF3 protein forms membrane-associated oligomers. Immunoblot analyses of ORF3 protein expressed in cell-free <em>vs</em>. cellular systems suggested a posttranslational modification. Further analyses revealed that HEV ORF3 protein is palmitoylated at cysteine residues in its N-terminal region, as corroborated by <sup>3</sup>H-palmitate labeling, the investigation of cysteine-to-alanine substitution mutants and treatment with the palmitoylation inhibitor 2-bromopalmitate (2-BP). Abrogation of palmitoylation by site-directed mutagenesis or 2-BP treatment altered the subcellular localization of ORF3 protein, reduced the stability of the protein and strongly impaired the secretion of infectious particles. </strong><strong>Moreover, selective membrane permeabilization coupled with immunofluorescence microscopy revealed that HEV ORF3 protein is entirely exposed to the cytosolic side of the membrane, allowing to propose a model for its membrane topology and interactions required in the viral life cycle. </strong><strong>In conclusion, palmitoylation determines the subcellular localization, membrane topology and function of HEV ORF3 protein in the HEV life cycle. </strong></p>
Towards a Data-Driven Requirements Engineering Approach: Automatic Analysis of User Reviews
<p>6000 French user reviews from three applications on Google Play (Garmin Connect, Huawei Health, Samsung Health) are labelled manually. We selected four labels: rating, bug report, feature request and user experience.</p> <ul> <li><strong>Ratings</strong> are simple text which express the overall evaluation to that app, including praise, criticism, or dissuasion.</li> <li><strong>Bug reports</strong> show the problems that users have met while using the app, like loss of data, crash of app, connection error, etc.</li> <li><strong>Feature requests</strong> reflect the demande of users on new function, new content, new interface, etc.</li> <li>In <strong>user experience</strong>, users describe their experience in relation to the functionality of the app, how does certain functions be helpful.</li> </ul> <p>As we can observe from the following table, that shows examples of labelled user reviews, each review belongs to one or more categories.</p> <table> <tbody> <tr> <th>App</th> <th>Total</th> <th>Rating</th> <th>Bug report</th> <th>Feature request</th> <th>User experience</th> </tr> </tbody> <tbody> <tr> <td>Garmin Connect</td> <td>2000</td> <td>1260</td> <td>757</td> <td>170</td> <td>493</td> </tr> <tr> <td>Huawei Health</td> <td>2000</td> <td>1068</td> <td>819</td> <td>384</td> <td>289</td> </tr> <tr> <td>Samsung Health</td> <td>2000</td> <td>1324</td> <td>491</td> <td>486</td> <td>349</td> </tr> </tbody> </table> <p> </p> <h2>New Dataset</h2> <p>Based on this dataset, we developed a labeled dataset containing 6,000 English and 6,000 French reviews for classification, as well as 1,200 bilingual reviews for clustering. The new dataset has been made publicly available on Zenodo at the following link: <a href="../records/11066414">https://zenodo.org/records/11066414</a></p>
Annotation-based Modeling of Non-functional Requirements and Analysis Results in Domain-driven Design
<p>This repo contains all supplementary data sets that we have created and used throughout this thesis. In particular, it contains<br> - expert interview material (elicitation): consent form and question catalogue for requirements elicitation<br> - expert interview material (evaluation): consent form and task description for expert evaluation<br> - Diagrams related to our modeling concept and Dqualizer<br> - Screenshots of the Domain Story Modeler with our Modeling Concept</p>
Data: More than 1000 genotypes are required to derive robust relationships between yield, yield stability and physiological parameters: a computational study on wheat crop
<p>APSIM-Wheat <strong>(</strong><a href="">www.apsim.info</a><strong>)</strong> was used to simulate a data set (for details, see Casadebaig<em> et al.</em>, 2016) with 9100 virtual genotypes (<em>N</em><sub>gen</sub>= 9100) grown under 9000 environments (<em>N</em><sub>env</sub>=9000). In short, virtual genotypes were created by varying the value of 90 independent physiological parameters in a range of ±20% from the reference cultivar <em>Hartog</em>. Environments in the dataset contain historical climate data of 125 years (1889-2013) in four locations (Emerald, Narrabri, Yanco and Merredin) in Australia, in combination with two CO<sub><sup>2</sup></sub> levels (380 and 555 ppm), three nitrogen levels (low: 50%, control: 100% and high fertilization: 100% plus 50 kg‧ha<sup>-1</sup>) and three sowing dates (early, control and late).</p>
Requirements elicitation (ReqElic) in my company
<p>Questionnaire (online survey) about requirements elicitation (ReqElic) in my company, PDF generated from <https://docs.google.com/forms/d/1RH_oMgpreDCvHexh4dKe40EVhsoBXPaXbbOYMITQDlQ/edit></p>
VReqST - Requirement Specification Tool Support for Virtual Reality Products
<p>Virtual Reality (VR) Environments are challenging to build with discrete and incremental requirements. VR practitioners often need human assistance to achieve product completeness, as most VR requirements are either abstract or under specified. The slightest change to these requirement specifications tends to drastically impact the overall control-flow of the product. It exponentially increases the development cost. To address the completeness of specifying VR product requirements, we introduce VReqST, a tool for specifying requirements for VR software products. We use role base model template of bare-minimum VR Software to auto-provision all dimensions of VR as a domain on specifying VR product requirements. This tool avoids ambiguity while specifying requirements and provides seamless VR product development.</p>
Prior choice and data requirements of Bayesian multivariate mixed effects models fit to tag-recovery data: The need for power analyses
<p>1. Recent empirical studies have quantified correlation between survival and recovery by estimating these parameters as correlated random effects with hierarchical Bayesian multivariate models fit to tag-recovery data. In these applications, increasingly negative correlation between survival and recovery has been interpreted as evidence for increasingly additive harvest mortality. The power of these hierarchal models to detect non-zero correlations has rarely been evaluated and these few studies have not focused on tag-recovery data, which is a common data type.</p> <p>2. We assessed the power of multivariate hierarchical models to detect negative correlation between annual survival and recovery. Using three priors for multivariate normal distributions, we fit hierarchical effects models to a mallard (<em>Anas</em> <em>platyrhychos</em>) tag-recovery dataset and to simulated data with sample sizes corresponding to different levels of monitoring intensity. We also demonstrate more robust summary statistics for tag-recovery datasets than total individuals tagged.</p> <p>3. Different priors lead to substantially different estimates of correlation from the mallard data. Our power analysis of simulated data indicated most prior distribution and sample size combinations could not estimate strongly negative correlation with useful precision or accuracy. Many correlation estimates spanned the available parameter space (–1,1) and underestimated the magnitude of negative correlation. Only one prior combined with our most intensive monitoring scenario provided reliable results. Underestimating the magnitude of correlation coincided with overestimating the variability of annual survival, but not annual recovery.</p> <p>4. The inadequacy of prior distributions and sample size combinations previously assumed adequate for obtaining robust inference from tag-recovery data represents a concern in the application of Bayesian hierarchical models to tag-recovery data. Our analysis approach provides a means for examining prior influence and sample size on hierarchical models fit to capture-recapture data while emphasizing transferability of results between empirical and simulation studies.</p>
National Open Access Monitor Survey: Defining Requirements: Responses Dataset
<p>This dataset contains the response data from the ‘National Open Access Monitor Survey: Defining Requirements’ which was carried out between February 2-28th 2023 under the National Open Access Monitor Project: <a href="https://doi.org/10.5281/zenodo.7588787">https://doi.org/10.5281/zenodo.7588787</a></p> <p>To note: </p> <ul> <li>Email addresses have been redacted. </li> <li>Responses have been pseudonymised to the level of stakeholder-group e.g. Contributor 1, Research Funding Organisation #, where requested by the participant in the participant consent form: <a href="https://doi.org/10.5281/zenodo.7589770">https://doi.org/10.5281/zenodo.7589770</a>. </li> <li>Detail within responses by individuals who requested pseudonymisation, which might identify the individual or the organisation has been removed and marked "[redacted]".</li> <li>Responses by individuals who did not provide a signed consent form in advance of contributing to the survey were deleted immediately on receipt, as advised in the survey text: <a href="https://doi.org/10.5281/zenodo.7588787">https://doi.org/10.5281/zenodo.7588787</a>. Such responses are not included in these files.</li> </ul> <p>There are five files within in this dataset:</p> <p>- <em>Results.NationalOpenAccessMonitorSurvey.DefiningRequirements.README - </em>this PDF details the changes made to the raw data, as specified in the bullet points above and a description of the files within the dataset.</p> <p>- <em>Results.NationalOpenAccessMonitorSurvey.DefiningRequirements.Pseudonymised.100323</em> - this is the original raw data, in csv format, as downloaded from the Online Surveys platform and subsequently pseudonymised and redacted.</p> <p>- <em>NationalOpenAccessMonitor.DefiningRequirements.Contributor3Government1.270223 - </em>this PDF file contains a single pseudonymised stakeholder response to the survey, obtained by the Project Manager by email and not through the Online Surveys platform.</p> <p>- <em>NationalOpenAccessMonitorSurvey.MasterChangeFile.080323 </em>- this is a change file, in csv format, which documents the changes which participants requested to be made to their submissions after they were received and the survey was closed.</p> <p>- <em>Results.NationalOpenAccessMonitorSurvey.DefiningRequirements.Pseudonymised.Updated.100323 - </em>this is the original raw data, pseudonymised and redacted, with the requested changes implemented. This is the file on which analysis was carried out for the purposes of the <a href="http://doi.org/10.5281/zenodo.7822367">survey outcome report</a> and the resulting National Open Access Monitor tender documents. </p> <p>------------------------</p> <p>The context for the survey files is detailed in the National Open Access Monitor Project Plan: <a href="https://doi.org/10.5281/zenodo.7331431">https://doi.org/10.5281/zenodo.7331431</a></p> <p>This project is managed by <a href="http://www.irel.ie/">IReL </a>and has received funding from Ireland’s National Open Research Forum under the NORF Open Research Fund. <a href="https://norf.ie/funding/">https://norf.ie/funding/</a> <a href="https://norf.ie/orf-projects-announcement/">https://norf.ie/orf-projects-announcement/</a></p>
FIG. 2 in Molecular assessment of the tribes Streblocladieae and Polysiphonieae (Rhodomelaceae, Rhodophyta) in the British Isles reveals new records and species that require taxonomic revision
FIG. 2. — Phylogenetic tree estimated with ML analysis of rbcL sequences. Values at nodes indicate bootstrap support (BP) (only shown if ≥70). Species analysed in this study are grey-shaded and species or haplotypes found in the British Isles are in bold. For P. morrowii Harvey, the number (n) of sequences available for each haplotype is indicated. Codes for countries/regions: AD, Adriatic Sea; AR, Argentina; AUS, Australia; BC, British Columbia; CH, Chile; EN, England; FR, France; GUE, Guernsey; IR, Ireland; JA, Japan; KO, Korea; LG, Ligurian Sea; NZ, New Zealand; PO, Portugal; SP, Spain.
FIG. 1 in Molecular assessment of the tribes Streblocladieae and Polysiphonieae (Rhodomelaceae, Rhodophyta) in the British Isles reveals new records and species that require taxonomic revision
FIG. 1. — Collection sites of the species used in this study with indication of the European biogeographic regions according to van den Hoek and Breeman (1990): dark blue, cold-temperate northeast Atlantic Region; brown, warm-temperate northeast Atlantic subregion 1; green, warm-temperate northeast Atlantic subregion 2; light blue, east Mediterranean subregion.
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International Brain Laboratory public data
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OpenNeuro
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