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101 results for “test quality”
Voltage and current data for IEC 62600-30 power quality monitoring from the Mutriku Wave Power Plant and Lir National Ocean Test Facility electrical laboratory
<p>This Technical Note describes the electrical data collected from the Mutriku Wave Power Plant (MWPP) and the Lir National Ocean Test Facility (NOTF) electrical laboratory at the MaREI Centre in the Environmental Research Institute, at University College Cork.</p> <p>In summary, the electrical data collect is for the purpose of analysing the power quality output of a Wave Energy Converter (WEC). The data includes voltage and current signals from the output of a WEC sampled at 15 kHz from the MWPP and a WEC emulator sampled at 20 kHz from the Lir NOTF electrical laboratory. There are 24 datasets from the MWPP taken at various sea state conditions, and there are 56 datasets from the Lir NOTF which are taken with at various sea state conditions, with different control laws, and grid connections.</p> <p>This data is published for purpose of power quality analysis and comparison for future tests. For OPERA, power quality analysis was performed as part of WP5 T5.2 and T5.5, and presented in depth in Deliverables D5.2 and D5.4.</p> <p>See accompanying technical note for more Information.</p>
Measuring Software Testability Modulo Test Quality - Replication Package
<p>This repository represents the replication package for the paper <em>Measuring Software Testability Modulo Test Quality</em>.</p> <p>It includes the dataset and the Jupyter Notebook we used for the analysis in our paper.</p>
Data for: D3.6 - Assessment of organoleptic and nutritional quality of fish products from the demonstration tests
<p>Data for: D3.6 - Assessment of organoleptic and nutritional quality of fish products from the demonstration tests </p> <p>https://ifishienci.eu/wp-content/uploads/2024/01/iFishIENCi_D3.6.pdf</p> <p>Corresponding Author</p> <p>Name: Anneli Rost<br>ttz Bremerhaven, Germany<br>Address: Knurrhahnstraß 22-24 /Packhalle X 27572 Bremerhaven<br>Email: arost@ttz-bremerhaven.de</p>
FIGURE A5 in Testing the impact of two key scan parameters on the quality and repeatability of measurements from CT scan data
FIGURE A5. Scatter plot displaying how beam shift, measured by the apparent growth (scale) of the shell in the final x-ray radiograph relative to the first x-ray radiograph, varies with (1) time of day the scan was performed, and (2) the overall scan time. We found that beam shift decreased throughout the day, likely due to the tube warming up as more scans are run. There was no correlation between overall scan time and the amount of beam shift.
FIGURE A1.2 in Testing the impact of two key scan parameters on the quality and repeatability of measurements from CT scan data
FIGURE A1.2. The range of volume measurements for each exposure times when three scans were reconstructed using ten methods. The blue dot represents the simple surface determination used for all shells in this study. The error bars represent the data range for each exposure time.
FIGURE 4. A in Testing the impact of two key scan parameters on the quality and repeatability of measurements from CT scan data
FIGURE 4. A video moving through slices of a pteropods shell scanned at 500 ms exposure time, with five xray radiographs averaged per view and an overall scan time of 75 minutes. There are streak artefacts perpendicular to the shell edge that are likely caused by beam hardening or shell movement during the scan. For video file, see https://palaeo-electronica.org/content/2020/ 2923-investigating-ct-scan-quality.
Raw results of the ORPHEUS quality of experience tests done by b<>com
<p>This Excel document contains the raw results of the ORPHEUS project Quality of Experience tests done by b<>com. The first sheet contains the results while the second contains additional information about the data presented in the first sheet. More details about the experiments and the corresponding results can be found in the project's Deliverable 5.6.</p>
Dataset for "How Instrument Transformers Influence Power Quality Measurements: A Proposal of Accuracy Verification Tests"
<p>This is dataset for paper published:</p> <p>Crotti, Gabriella, Yeying Chen, Huseyin Çayci, Giovanni D’Avanzo, Carmine Landi, Palma Sara Letizia, Mario Luiso, Enrico Mohns, Fabio Muñoz, Renata Styblikova, and Helko van den Brom. 2022. "How Instrument Transformers Influence Power Quality Measurements: A Proposal of Accuracy Verification Tests" <em>Sensors</em> 22, no. 15: 5847. https://doi.org/10.3390/s22155847</p> <p> </p> <p>Excel file provides data in the time domain for tests performed on the inductive VT</p> <p> </p>
Energy Consumption Due To Test Quality: State of Affairs, Impacts, and Ways Forward
<p>This replication package contains data and scripts used in <strong>"Energy Consumption Due To Test Quality: State of Affairs, Impacts, and Ways Forward"</strong></p> <p>For details, please read README</p>
Codes and catalogs for: Parametric testing of EQTransformer's performance against a high-quality, manually-picked catalog for reliable and accurate seismic phase picking
<p><strong>Codes and Catalogs for:</strong> "Parametric Testing of EQTransformer's Performance Against a High-Quality, Manually-Picked Catalog for Reliable and Accurate Seismic Phase Picking."</p> <p><strong>Codes:</strong></p> <ol> <li><strong>overlap_check.py:</strong> This script tests the overlap parameter of EQTransformer to help minimize detection inconsistencies.</li> <li><strong>picks_comparison_other_networks.py:</strong> This code evaluates the probability threshold of EQTransformer by obtaining the time differences between picks from a catalog and EQTransformer.</li> <li><strong>test_seisbench_eq_eqt.py:</strong> A comparative analysis between the native EQTransformer and its implementation in SeisBench.</li> </ol> <p><strong>Catalogs:</strong></p> <ol> <li><strong>picks_differences_all_years_0.01_mag_cat.csv:</strong> This catalog presents pick differences for the central Alpine Fault using the SAMBA network and manual picks from Michailos et al. (2019).</li> <li><strong>sed_picks.csv:</strong> A catalog that showcases pick differences derived from data obtained from the Swiss Seismological Service (SED).</li> </ol> <p><strong>Note:</strong> Versions <1.0 represent pre-acceptence files and should not be used.</p>
Implementation of ATP and Microbial Indicator Testing for Hygiene Monitoring in a Tofu Production Facility Improves Product Quality and Hygienic Conditions of Food Contact Surfaces: A Case Study
<p>This is the code and associated data that was used to generate conclusions for the following manuscript published in Applied and Environmental Microbiology:</p> <p>DOI: 10.1128/AEM.02278-20</p> <p>Implementation of ATP and Microbial Indicator Testing for Hygiene Monitoring in a Tofu Production Facility Improves Product Quality and Hygienic Conditions of Food Contact Surfaces: A Case Study</p> <p>Authors: Jonathan H. Sogin(a), Gabriela Lopez Velasco(b), Burcu Yordem(b), Cari K. Lingle(b), John M. David(b), Mario Cobo(a), Randy W. Worobo(a)</p> <p>(a)Department of Food Science, Cornell University, Ithaca, NY, USA</p> <p>(b)3M Company, St. Paul, MN, USA</p> <p>Address correspondence to Jonathan H. Sogin, jhs397@cornell.edu</p>
Characterizing high quality test methods, MSR'22
<p>Replication Kit for "Characterizing high quality test methods" paper.</p> <p>Number of records: 15970;</p> <p>Number of columns: 50;</p> <p>Columns list:</p> <ul> <li>Id;</li> <li>Project;</li> <li>Class;</li> <li>Method;</li> <li>Killed;</li> <li>Survived;</li> <li>TimedOut;</li> <li>Total;</li> <li>Score;</li> <li>WhileCount;</li> <li>ConditionCount;</li> <li>RedundantCount;</li> <li>AssertCount;</li> <li>IfCount;</li> <li>ExceptionCount;</li> <li>ForeachCount;</li> <li>PrintCount;</li> <li>SwitchCount;</li> <li>MysteryCount;</li> <li>ForCount;</li> <li>VerboseCount;</li> <li>ResourceOptimismCount;</li> <li>ThreadSleepCount;</li> <li>SensitiveCount;</li> <li>MagicNumberCount;</li> <li>Assertion Roulette;</li> <li>Mystery Guest;</li> <li>Sleepy Test;</li> <li>Unknown Test;</li> <li>Redundant Assertion;</li> <li>Dependent Test;</li> <li>Magic Number Test;</li> <li>Conditional Test Logic;</li> <li>EmptyTest;</li> <li>General Fixture;</li> <li>Sensitive Equality;</li> <li>Verbose Test;</li> <li>IgnoredTest;</li> <li>Resource Optimism;</li> <li>Duplicate Assert;</li> <li>Exception Catching Throwing;</li> <li>Print Statement;</li> <li>SLOC;</li> <li>Complexity;</li> <li>ModifyingCommits;</li> <li>Contributors;</li> <li>MaxExperienced;</li> <li>MinExperienced;</li> <li>MeanExperience;</li> <li>MedianExperience;</li> <li>StdevExperience</li> </ul> <p>Format: CSV</p> <p>Attributes per category:</p> <p>Size & Complexity: number of lines of code, cyclomatic complexity, loop count and conditional count;</p> <p>Exception: exception count and resource optimism;</p> <p>Contributors: Developers' expertise and number of contributors;</p> <p>Changes: Number of modifications;</p> <p>Quality: Number of asserts, mystery guest count, magic number count, print count, sleep count,<br> sensitive count</p> <p>Test Smells: Assertion Roulette, Mystery Guest, Sleepy Test, Unknown Test, Redundant Assertion, Dependent Test, Magic Number Test, Conditional Test Logic, EmptyTest, General Fixture, Sensitive Equality, Verbose Test, IgnoredTest, Resource Optimism, Duplicate Assert, Exception Catching Throwing, Print Statement; </p>
Canopy Quality Test Data
<p>Test data for Scivision canopy quality models.</p>
Empirical tests of habitat selection theory reveal that conspecific density and patch quality, but not habitat amount, drive long-distance immigration in a wild bird
<p>Individuals that disperse long distances from their natal site must select breeding patches with no prior knowledge of patch suitability. Despite decades of theoretical studies examining which cues dispersing individuals should use to select breeding patches, few empirical studies have tested the predictions of these theories at spatial scales relevant to long-distance dispersal in wild animal populations. Here, we use a novel assignment model based on multiple intrinsic markers to quantify natal dispersal distances of Wood Thrush (<i>Hylocichla mustelina</i>) breeding in forest fragments. We show that long-distance natal dispersal in this species is more frequent than commonly assumed for songbirds and that habitat selection by these individuals is driven by density-dependence and patch quality but not the amount of habitat surrounding breeding patches. These results represent an important contribution to understanding habitat selection by dispersing individuals, especially with regards to long-distance dispersal.</p>
NIOO-QingZ/Geertruidenberg_Mesocosms: Towards climate-robust water quality management: testing the efficacy of different eutrophication control measures during a heat
<p>Data and Codes used in the following open-access publication: </p> <p>https://www.sciencedirect.com/science/article/pii/S0048969722015145</p>
Datasets and Code for "Hypothesis Tests with Functional Data for Surface Quality Change Detection in Surface Finishing Processes"
<p>This is the set of data and computer code used for reproducing the results in Jin, Tuo, Tiwari, Bukkapatnam, Aracne-Ruddle, Lighty, Hamza, and Ding, 2022, “Hypothesis tests with functional data for surface quality change detection in surface finishing processes,” <em>IISE Transactions</em>, in press.</p>
The validity and reliability test of the leprosy life quality questionnaire in leprosy patients
<p>This is underlying data for study titled<strong> The validity and reliability test of the leprosy life quality questionnaire in leprosy patients</strong></p> <p> </p>
An empirical study on the influence of developers' experience on software test code quality
<p>Software developers' engagement in open-source software projects lies in different levels of participation, e.g., core or peripheral developers. Recent studies have investigated the role of developers' contributions and their influence on software quality. However, few studies investigate the relationship between the developers' experience and test code quality in software projects. In this study, we aim to investigate the relationship between the developers' experience and the test code quality from the perspective of test smells. We performed an empirical study to analyze the insertion and removal of test smells in four open-source Java projects. We collected 18 test smells and calculated their authorship through the projects' Tags. The four software projects contain 386 test classes and 5,178 test smells. We found out that the insertion of 67.28\% of test smells occurs during the test class creation, and the removal of 20.88\% of test smells occurs during the evolution of projects. In addition, core developers are responsible for inserting 88.91\% and removing 89.82\% test smells. Core developers insert and remove more test smells than the peripheral developers. Most test smell removal is due to test code deletion, which may indicate that both core and peripheral developers are unaware of test smells in test code.</p>
Data from: Understanding Test Convention Consistency as a Dimension of Test Quality
<div> <div>This archive provides additional data for the article "Understanding Test Convention Consistency</div> <div>as a Dimension of Test Quality" by Martin P. Robillard, Mathieu Nassif, and Muhammad Sohail,</div> <div>published in ACM Transactions on Software Engineering and Methodology.</div> </div>
2SPT Test Time Series: Quality Control for Community Based Sea Ice Model Development
<p>2SPT Test Time Series: Quality Control for Community Based Sea Ice Model Development</p> <p>------------------------------------------------------------------------------------</p> <p>This dataset comes from Regional Arctic System Model (RASM) simulations by Andrew F. Roberts at Naval Postgraduate School, described and used in Figure 3 in the manuscript:</p> <p>Roberts, Hunke, Allard, Bailey, Craig, Lemieux and Turner (2018): Quality Control for Community Based Sea Ice Model Development.</p> <p>Files for the series in Figure 3 as they appear in that paper to demonstrate the Two-Stage Paired Thickness Test:</p> <p>Figure 3a:</p> <p>R1009RBRcevp01a.cice.h.hi.1996_2000.North_Pole.nc</p> <p>R1009RBRcevp01a_2.cice.h.hi.1996_2000.North_Pole.nc</p> <p> </p> <p>Figure 3b:</p> <p>R1009RBRcevp01a.cice.h.hi.1996_2000.North_Pole.nc</p> <p>R1009RBRceap01a.cice.h.hi.1996_2000.North_Pole.nc</p> <p> </p> <p>Figure 3c:</p> <p>R1009RBRcevp01a.cice.h.hi.1996_2000.North_Bathurst_Island.nc</p> <p>R1009RBRceap01a.cice.h.hi.1996_2000.North_Bathurst_Island.nc</p> <p> </p> <p>Where the name "evp" or "eap" in the file name corresponds to the EVP and EAP simulations as described in the manuscript. These are selected timeseries from 1996 to 2000 from the RASM simasimulations described in section 2 of the above manuscript. CICE namelist settings are identical to the description for the dataset:</p> <p>Roberts, A. (2018). RASM simulations: Quality Control for Community Based Sea Ice Model Development [Data set]. Zenodo. http://doi.org/10.5281/zenodo.1308236</p> <p> </p>
ScienceDex guides
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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.