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8,038 results for “validation”
CI/CD Efforts for Validation, Verification and Benchmarking OpenMP implementations
<p>Software developers must adapt to keep up with the changing capabilities of platforms so that they can utilize the power of High-Performance Computers (HPC), including exascale systems. The OpenMP, a directive-based parallel programming model, allows developers to include directives to existing C, C++, or Fortran code to allow node level parallelism without compromising performance. This paper describes our CI/CD efforts to provide easy evaluation of the support of OpenMP across different compilers using existing testsuites and benchmark suites on HPC platforms. Our main contributions include (1) the set of a Continuous Integration (CI) and Continuous Development (CD) workflow that captures bugs and provides faster feedback to compiler developers, (2) an evaluation of OpenMP (offloading) implementations supported by AMD, HPE, GNU, LLVM, and Intel, and (3) evaluation of the quality of compilers across different heterogeneous HPC platforms.<br>Through the comprehensive testing through the CI/CD workflow, we aim to provide a comprehensive understanding of the current state of OpenMP (offloading) support in different compilers and heterogeneous platforms consisting of CPUs and GPUs from NVIDIA, AMD and Intel.</p>
Model for random atmospheric inhomogeneities in engine noise auralization: Audio files for validation
<p>Illustration of engine noise auralization by DLR Institute of Propulsion Technology obtained with the framework PropNoise, VIOLIN, CORAL. Data associated with the following publication: A. Prescher, A. Moreau, S. Schade, "<a href="https://doi.org/10.1007/s13272-024-00764-4" target="_blank" rel="noopener"><em>Model for random atmospheric inhomogeneities in engine noise auralization</em></a>", CEAS Aeronautical Journal, 2024.</p> <p>Selected binaural audio files to illustrate the impact of random atmospheric inhomogenities on the noise characteristics of a turbofan engine.</p> <p>The corresponding time signals and spectrograms are available in the associated paper in Figure 7.</p>
Figure 3 in A discussion on the validity of the genus Abalakeus (Acari: Erythraeidae) with a redescription of A. gonabadensis
Figure 3 Abalakeus gonabadensis (larva). A – BFe-Ge III; B – Ti and Ta III.
Fig. 6. Astyanax laticeps, ANSP 21852 in Redescription of Astyanax obscurus (Hensel, 1870) and A. laticeps (Cope, 1894) (Teleostei: Characidae): two valid freshwater species originally described from rivers of Southern Brazil
Fig. 6. Astyanax laticeps, ANSP 21852, holotype, 54.1 mm SL, Rio Grande do Sul, Brazil.
Training and validation data for MOF-801(Zr) with adsorbed water molecules.
<p>We employ MACE 0.3.5 (github.com/acesuit/mace) to train an ML potential to the extended XYZ file `data.xyz`, which contains atomic geometries and potential energy and force labels. The system is MOF-801(Zr) at various water loadings. Data was generated in an active learning fashion using psiflow (github.com/molmod/psiflow).</p>
Divide and Remaster v3: Spanish Validation & Test Set
<p>Divide and Remaster v3 is a multilingual rework of the Divide and Remaster v2 dataset by Pétermann et al.</p> <p>This repository contains the <strong>metadata, validation set audio, and test set audio of the</strong> <strong>Spanish variant </strong>of DnR v3.</p> <p>The major changes from DnR v2 are as follows:</p> <ul> <li>the dialogue stem now contains content from more than 30 languages across various language families;</li> <li>speech, vocals, and/or vocalizations have been removed from the music and effects stems;</li> <li>loudness and timing parametrization have been adjusted to approximate the distributions of real cinematic content;</li> <li>the mastering process now preserves relative loudness between stems and approximates standard industry practices.</li> </ul> <p>See the linked GitHub repository for more details.</p>
Divide and Remaster v3: English Validation & Test Set
<p>Divide and Remaster v3 is a multilingual rework of the Divide and Remaster v2 dataset by Pétermann et al.</p> <p>This repository contains the <strong>metadata, validation set audio, and test set audio of the</strong> <strong>English variant </strong>of DnR v3.</p> <p>The major changes from DnR v2 are as follows:</p> <ul> <li>the dialogue stem now contains content from more than 30 languages across various language families;</li> <li>speech, vocals, and/or vocalizations have been removed from the music and effects stems;</li> <li>loudness and timing parametrization have been adjusted to approximate the distributions of real cinematic content;</li> <li>the mastering process now preserves relative loudness between stems and approximates standard industry practices.</li> </ul> <p>See the linked GitHub repository for more details.</p>
Divide and Remaster v3: Mandarin Chinese Validation & Test Set
<p>Divide and Remaster v3 is a multilingual rework of the Divide and Remaster v2 dataset by Pétermann et al.</p> <p>This repository contains the <strong>metadata, validation set audio, and test set audio of the</strong> <strong>Mandarin Chinese variant </strong>of DnR v3.</p> <p>The major changes from DnR v2 are as follows:</p> <ul> <li>the dialogue stem now contains content from more than 30 languages across various language families;</li> <li>speech, vocals, and/or vocalizations have been removed from the music and effects stems;</li> <li>loudness and timing parametrization have been adjusted to approximate the distributions of real cinematic content;</li> <li>the mastering process now preserves relative loudness between stems and approximates standard industry practices.</li> </ul> <p>See the linked GitHub repository for more details.</p>
Divide and Remaster v3: Standard German Validation & Test Set
<p>Divide and Remaster v3 is a multilingual rework of the Divide and Remaster v2 dataset by Pétermann et al.</p> <p>This repository contains the <strong>metadata, validation set audio, and test set audio of the</strong> <strong>Standard German variant </strong>of DnR v3.</p> <p>The major changes from DnR v2 are as follows:</p> <ul> <li>the dialogue stem now contains content from more than 30 languages across various language families;</li> <li>speech, vocals, and/or vocalizations have been removed from the music and effects stems;</li> <li>loudness and timing parametrization have been adjusted to approximate the distributions of real cinematic content;</li> <li>the mastering process now preserves relative loudness between stems and approximates standard industry practices.</li> </ul> <p>See the linked GitHub repository for more details.</p>
Figure 5 in Fregetta lineata (Peale, 1848) is a valid extant species endemic to New Caledonia
Figure 5. Principal Component Analysis showing contribution of variables to axes 1 and 2.
Dataset used for the validation of stemv: An R package for calculating tree stem volume in Japan
<p>This repository contains the dataset for validating an R package "stemv", which provides the functions for calculating tree stem volume in Japan.<br>The source of the package can be found on <a href="https://github.com/dulvrq/stemv" target="_blank" rel="noopener">GitHub </a>(https://github.com/dulvrq/stemv).</p>
RUSH3D - 2P validation data
<p>Here are the synchronized data pair from a standard two-photon microscope and RUSH3D (a sort of light field microscope). </p> <p>TP_xxx.tif files are from 2p</p> <p>realign_RUSH3D.tif files are from RUSH3D</p>
Validation Videos - Robotic System for Reproducible Mobile Networking Experimentation in Anechoic Chambers (Master Thesis)
<p><strong>Note on Robot's Referential:</strong></p> <p>The robot's referential can be inferred in the recording via the "Safety Position." The safety position is the same for both the Digital Model (Gazebo) and the Real Robot (Joint Position = [0.0, -1.57, 1.57, 0.0, 0.0, 0.0]).</p> <p>In the safety position, the robot is approximately aligned with the X-axis, with its end-effector on the positive side of the axis. The end-effector faces perpendicular to the Y-axis. The positive Z-axis points upwards towards the ceiling.</p> <p> </p>
Figure 1-Validation of a Web Application by Using a Limited Number of Web Pages
<p>Figure 1 shows the GARWA for this example.</p>
Supporting material for "Pharmacological validation of individual animal locomotion, temperature and behavioural analysis in group-housed rats using a novel automated home cage analysis system: a comparison with the modified Irwin test"
<p>The data were uploaded to support the manuscript "Pharmacological validation of individual animal locomotion, temperature and behavioural analysis in group-housed rats using a novel automated home cage analysis system: a comparison with the modified Irwin test" for the submission to Journal of Pharmacological and Toxicological Methods.</p>
The Concurrent Validity of the Internet Addiction Test (IAT) and the Mobile Phone Dependence Questionnaire (MPDQ)
<p>A full raw dataset for the following research study</p> <p> </p> <p>PONE-D-17-34552R1 <br> The Concurrent Validity of the Internet Addiction Test (IAT) and the Mobile Phone Dependence Questionnaire (MPDQ)</p>
Synthetic meshes of hippocampi, for statistical shape analysis validation
<p>Those synthetic data have been generated for the validation of the iterative centroid method published in "Statistical shape analysis of large datasets based on diffeomorphic iterative centroids", which code can be found here: https://github.com/cclairec/Iterative_Centroid</p> <p>The 50 random populations are all generated from a same shape S0. We generated random deformations around S0 and symmetrised the deformations, so the centre of the populations is S0. More details in the paper.</p> <p>Each data set is composed by 50 shapes. The Matlab files contain:</p> <p>- moment: The initial momentum vector used to generate each subject of the population</p> <p>- SkelSuj_Rigid: The first line contains the vertices and faces of each subject. The second line contains the parameters to generate the initial momentum vectors and the subjects.</p>
ProbeSpec validation data
<p>Arb data used for validation of ProbeSpec. This data set is a sub-set of the data used for the environmental microarray published in Krausfeld <em>et al</em><em>. </em>(2017).</p>
Test and validation data for Robbie: A Batch Processing Work-flow for the Detection of Radio Transients and Variables
<p>Robbie: a general work-flow for the detection and characterization of radio variability and transient events in the image domain.<br> Robbie is designed to work in a batch processing paradigm with a modular design so that components can be swapped out or upgraded to adapt to different input data, whilst retaining a consistent and coherent methodological approach.<br> Robbie is based on commonly used and open software, and is encapsulated in a Makefile to aid portability and reproducibility.<br> In the description paper we describe the methodology behind Robbie, and demonstrate its use on real and simulated data.</p> <p>This repository contains the observed and simulated data that was used in the description paper.</p> <p> </p>
The supplementary data for validation of paper <The effect of the biogenic isoprene emission around the megacity on ozone pollution in Beijing>
<p>The supplementary data of paper <<strong>The effect of the biogenic isoprene emission around the megacity on ozone pollution in Beijing>. The zip bag includes the data of four figures in paper with the format of Netcdf, and the more detail could be got by connecting with Hui Wang(wanghui6@mail.bnu.edu.cn)</strong></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.