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48 results for “user tests”
DUAL-T User Testing Dataset
<p><em><strong>The file</strong></em></p> <p>This file contains keylogging data from 21 professional literary translators, who translated three short stories in three different workflows. Data was collected between October 2023 and January 2024.</p> <p> </p> <p><em><strong>Participants</strong></em></p> <p>Participants have been assigned codes from <strong>P01 to P23</strong>. Originally, there were 24 participants, however logs for P04a, P09, and P20 had to be excluded from analysis due to technical errors, so they are not present in the spreadsheet.</p> <p> </p> <p><em><strong>Workflows</strong></em></p> <p>The workflows were:</p> <p><strong>WF01</strong>: Microsoft Word</p> <p><strong>WF02</strong>: Trados Studio 2022</p> <p><strong>WF03</strong>: Machine-Translation Postediting Platform (proprietary tool, not available on the market)</p> <p>Participants had access to an internet browser (Chrome) for all three conditions.</p> <p> </p> <p><em><strong>Source texts</strong></em></p> <p>The texts used for the experiments were taken from the short story collection <em>One More Thing</em>, by BJ Novak (2014). The three short stories used are:<br><br><strong>T01</strong>: Rome</p> <p><strong>T02</strong>: The Beautiful Girl in the Bookstore</p> <p><strong>T03</strong>: They Kept Driving Faster and They Outrun the Rain</p> <p> </p> <p><strong><em>The keylogging data</em></strong></p> <p>Keylogging data was collected using Inputlog 8.0.0.17 (<a href="https://www.inputlog.net/">https://www.inputlog.net/</a>)</p> <p>The data available in the spreadsheet includes:</p> <ul> <li>Translation time (hh:mm:ss)</li> <li>Translation time (s)</li> <li>Translation time (m)</li> <li>Total <em>n</em> keystrokes</li> <li>Total <em>n</em> mouse actions</li> <li>Total <em>n</em> pauses</li> <li>Pause duration (s)</li> <li>Mean duration of pauses (s)</li> <li>Pause ratio</li> <li>Time spent inside tool (s)</li> <li>Time spent outside tool (s)</li> <li>Source text <em>n</em> words</li> <li>Source text <em>n</em> characters</li> <li>Target text <em>n</em> words</li> <li>Target text <em>n</em> characters</li> <li>Seconds per source text character</li> </ul>
IIIF: raising awareness of the user benefits for scholarly editions - usability testing results
<p>Usability testing results of the bachelor's thesis titled <a href="https://doc.rero.ch/record/306498/"><em>"The International Image Interoperability Framework (IIIF): raising awareness of the user benefits for scholarly editions"</em></a><a href="https://doc.rero.ch/record/306498/">.</a></p> <p>Remote and in-person usability tests on the <a href="http://universalviewer.io/">Universal Viewer</a> and <a href="http://projectmirador.org/">Mirador</a>, two IIIF-compliant clients, took place between March and May 2017. The tests were conducted with Loop11 (remote testing) and Morae (in-person testing).</p> <p>The dataset is composed of Excel files, screenshots (tasks and heat maps) as well as videos.</p>
BiodivAR comparative user test (GNSS vs. RTK) dataset
<p>This dataset comprises data used to evaluate and compare the BiodivAR open source web location-based AR application in a presentation submitted to the FOSS4G 2023 conference in Pritzen, Kosovo. The application is available at <https://biodivar.heig-vd.ch> and its source code at <https://github.com/MediaComem/biodivar>.</p>
Reference datasets for consistency tests of GENAPOPOP 1.0 software: a user-friendly software to analyse genetic diversity and structure in partially clonal and selfed polyploid organisms.
<p>Datasets companion of the manuscript entitled GenAPoPop 1.0: a user-friendly software to analyse genetic diversity and structure in partially clonal and selfed polyploid organisms, used to achieve consistency test with Spagedi 1.5 software, and used as reference datasets to demonstrate the new possibilities allowed by GenAPoPop software.</p> <p>Raw datasets used for testing GenAPoPop 1.0, A user-friendly software for easily compute genetic analyses of autopolyploid populations packaged for Linux, MacOS and Windows; Results obtained from Spagedi 1.5 (Hardy & Vekemans 2001) and GenAPoPop1.0.</p> <p>Four pseudo-observed genotyping autotetrapolyploid SNP datasets, corresponding respectively to panmictic (A), highly clonal (B), highly selfed (C) and half-clonal-half-selfed (D) reproductive mode scenario. In all these four scenarios, we simulated two populations of 100 individuals each, connected with a migration rate of 0.01 and mutating at a rate of 0.01, genotyped at 10 SNPs. Datasets were recorded 1000 generations after an initial randomly drawing population with equal allele frequencies.</p> <p>One SNP tetraploid genotyping dataset from two French <em>Ludwigia grandiflora subsp. hexapetala</em> populations (aquatic plant from the Angiosperm clade): two populations in which we collected 75 individuals, each genotyped with 36 SNPs using the Hiplex method allowing confident allele dosage (Delord et al. 2018).</p> <p>One microsatellite tetraploid genotyping dataset on two Aulactinia stella populations (sea-anemone from the Cnidaria phylum), sampled on the coast of the arctic ocean. One population of 21 individuals and one population of 15 individuals, both genotyped with 10 microsatellites.</p> <p>We also report here the consistency tests with GenAlex and Spagedi, results of analyses (GPP tab) on 6300 independant simulations and inferences of the quantitative reproductive modes using the bayesian method on CEMP tab made on 6300 another independant simulations.</p>
VR Gaming Dataset - Multi-user tests
<p>This virtual reality (VR) gaming dataset includes <strong>Wireshark</strong> traces (.csv) and <strong>ALVR</strong> statistics (.json) for <strong>three users</strong> (Costas, Miguel, Daniele) playing at the same time in a <strong>Wi-Fi 6</strong> network with <strong>one access point</strong> (AP). We used multiple bitrates (50 Mbps, 100 Mbps, 200 Mbps) and multiple configurations (DCF, DL OFDMA, DL/UL OFDMA, DL/UL OFDMA with MU-MIMO). Costas plays <strong>Half-Life: Alyx</strong>, while Miguel and Daniele play <strong>SteamVR Home</strong>. Each configuration includes single-user (SU) results as well, that can be used as a baseline for the multi-user (MU) ones.</p>
Teleoperation with Baxter robot and haptic device: testing with experts user.
<p>In this video you can see the experiment with expert users developed by Robotics Group of the Universidad de León, as part of a research project that aims to demonstrate the effectiveness of the use of haptic devices in teleoperation environments.</p>
Comparing developer-provided to user-provided tests for fault localization and automated program repair: Artifacts
<p>Artifacts for the paper <em>Comparing developer-provided to user-provided tests for fault localization and automated program repair.</em></p> <p>Note that the artifacts are maintained in the following repositories:</p> <ul> <li>https://github.com/rjust/defects4j</li> <li>https://bitbucket.org/rjust/tests-tested-data</li> <li>https://bitbucket.org/rjust/fault-localization-data</li> </ul>
EUREKA regional users tests for the pilot EU-FarmBook
ZIP archive containing background info, script and questions used by EUREKA partners who conducted the user-test interviews in the 4 EU macroregions, plus their reports (the results) in an Excel file.
D6.6 - White goods pilot report - Test user feedback of 9 users
<p>During the pilot phase, usage and consumption data is generated during the use of the appliance and sent to the ConnectLife app. The logged data consists of, among others, store time stamps, program choice, program duration, washing temperature, and error codes, this provided a continuous stream of raw data. As a result of these insights, individual user consumption data can be compared to the average user consumption data of users (reference data). This allows for providing details feedback to users regarding their program choices and the timing of conducting washing cycles. In addition, average consumption values are included (in grey) in order to create a reference for evaluation and recommendation. The green and red smileys indicate if the test user is below or above the average value, resulting in a note on how to improve the environmental burden.</p>
Testing a Community-Friendly Risk Reduction Intervention for Injection Drug Users
ClinicalTrials.gov study NCT01741350. IPD Sharing: Not stated. Countries: 1. Publications: 2.
RxConnect User Testing Study
ClinicalTrials.gov study NCT05493072. IPD Sharing: NO. Countries: 1. Publications: 7.
Summary of problems and solutions from a brainstorming sessions with users having tested a basic mixed-presence setup with two wall-sized displays
<p>Summary of problems and solutions from a brainstorming session with participants having tested a basic mixed-presence setup with two wall-sized displays beforehand. The (excel) file includes descriptions, diagrams and scores used to rank the ideas.</p>
Usibility Test for User friendly interaction in intelligent digital assistance systems.
<p>Te Interview for usability test.</p>
External test datasets for "SpheroScan: A User-Friendly Deep Learning Tool for Spheroid Image Analysis"
<p>In recent years, three-dimensional (3D) spheroid models have become increasingly popular in scientific research as they provide a more physiologically relevant microenvironment that mimics in vivo conditions. The use of 3D spheroid assays has proven to be advantageous as it offers a better understanding of the cellular behavior, drug efficacy, and toxicity as compared to traditional two-dimensional cell culture methods. However, the use of 3D spheroid assays is impeded by the absence of automated and user-friendly tools for spheroid image analysis, which adversely affects the reproducibility and throughput of these assays.</p> <p>To address these issues, we have developed a fully automated, web-based tool called SpheroScan, which uses the deep learning framework called Mask Regions with Convolutional Neural Networks (R-CNN) for image detection and segmentation. To develop a deep learning model that could be applied to spheroid images from a range of experimental conditions, we trained the model using spheroid images captured using IncuCyte Live-Cell Analysis System and a conventional microscope. Performance evaluation of the trained model using validation and test datasets shows promising results.</p> <p>SpheroScan allows for easy analysis of large numbers of images and provides interactive visualization features for a more in-depth understanding of the data. Our tool represents a significant advancement in the analysis of spheroid images and will facilitate the widespread adoption of 3D spheroid models in scientific research. The source code and a detailed tutorial for SpheroScan are available at <a href="https://github.com/FunctionalUrology/SpheroScan">https://github.com/FunctionalUrology/SpheroScan</a>.</p>
User Testing and Feedback for a Mobile Health Program for Postpartum Women: A Pilot Study
ClinicalTrials.gov study NCT02384226. IPD Sharing: NO. Countries: 1. Publications: 1.
User-friendly HIV Testing and Counseling Services
ClinicalTrials.gov study NCT04585165. IPD Sharing: UNDECIDED. Countries: 1. Publications: 2.
Understanding Evaluation of Patient Information Sheets by User Testing Method
ClinicalTrials.gov study NCT03155334. IPD Sharing: YES. Countries: 2. Publications: 4.
User Site Testing Study to Evaluate Usability of the Q300™ Device Under "Real-life Conditions" in a Reproductive Laboratory Environment Use
ClinicalTrials.gov study NCT06232720. IPD Sharing: NO. Countries: 1. Publications: 2.
Data from: Analytical performance, agreement and user-friendliness of six point of care testing urine analysers for urinary tract infection in general practice.
Objective: Various point-of-care testing (POCT) urine analysers are commercially available for routine urine analysis in general practice. The present study compares analytical performance, agreement and user-friendliness of six different POCT urine analysers for diagnosing urinary tract infection in general practice. Setting: All testing procedures were performed at a diagnostic centre for primary care in the Netherlands. Urine samples were collected at four general practices. Primary and secondary outcome measures: Analytical performance and agreement of the POCT analysers regarding nitrite, leucocytes and erythrocytes, with the laboratory reference standard, was the primary outcome measure, and analysed by calculating sensitivity, specificity, positive and negative predictive value, and Cohen's κ coefficient for agreement. Secondary outcome measures were the user-friendliness of the POCT analysers, in addition to other characteristics of the analysers. Results: The following six POCT analysers were evaluated: Uryxxon Relax (Macherey Nagel), Urisys 1100 (Roche), Clinitek Status (Siemens), Aution 11 (Menarini), Aution Micro (Menarini) and Urilyzer (Analyticon). Analytical performance was good for all analysers. Compared with laboratory reference standards, overall agreement was good, but differed per parameter and per analyser. Concerning the nitrite test, the most important test for clinical practice, all but one showed perfect agreement with the laboratory standard. For leucocytes and erythrocytes specificity was high, but sensitivity was considerably lower. Agreement for leucocytes varied between good to very good, and for the erythrocyte test between fair and good. First-time users indicated that the analysers were easy to use. They expected higher productivity and accuracy when using these analysers in daily practice. Conclusions: The overall performance and user-friendliness of all six commercially available POCT urine analysers was sufficient to justify routine use in suspected urinary tract infections in general practice.
EUREKA regional users tests for the pilot EU-FarmBook
ZIP archive containing background info, script and questions used by EUREKA partners who conducted the user-test interviews in the 4 EU macroregions, plus their reports (the results) in an Excel file.
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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.