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17 results for “Experimental Techniques”
Dataset for 'Experimental Quantification of Gas Dispersion in 3D-Printed Logpile Structures Using a Noninvasive Infrared Transmission Technique'
<p>This dataset contains the infrared images of tracer flow that were taken in the investigations of transverse dispersion in 3D-printed logpile structures. Accompanying the files (which are labelled according to the convention of the camera software) is a Python script which can be used to link the images to the operating conditions at which they were obtained. Documentation of this script can be found in the file at the very top. <br> This dataset was used as basis for the journal article 'Experimental Quantification of Gas Dispersion in 3D-Printed Logpile Structures Using a Noninvasive Infrared Transmission Technique', published in ACS Engineering Au under DOI:<a href="https://doi.org/10.1021/acsengineeringau.1c00040">10.1021/acsengineeringau.1c00040</a>. This paper can also be found in this repository at https://zenodo.org/record/6517082</p> <p> </p>
Aero-engine NOx emissions in case of electrochemical suppression technique application (experimental results)
<p><span>Results of the mini engine exhaust tests with various excitation discharge type and energy application</span></p>
Oatmeal Data: Experimental cone-beam tomographic data for techniques to improve image resolution
<p><sub>This submission contains supplementary material to A.A. Hendriksen et al., (2019). Throughout the description, we mention this publication as the "referred paper". </sub></p> <p> </p> <p><strong>Description Summary</strong></p> <p>"Oatmeal Data" is a collection of experimental tomographic data of a plastic jar filled with store-bought mixed-size flake oatmeal. The dataset was collected to test methods specifically developed for improving image resolution in a reconstructed volume (primarily for machine learning).</p> <p>As well as the raw (unprocessed) tomographic data, this submission includes training and test data, weights and geometry parameters, and a text file (Makefile) to reproduce the results presented in the referred paper. The full list of contents is given below. </p> <p> </p> <p><strong>Apparatus</strong></p> <p>The dataset is acquired using the custom-built and highly flexible CT scanner, FleX-ray Laboratory, developed by XRE NV and located at CWI. This apparatus consists of a cone-beam microfocus X-ray point source that projects polychromatic X-rays onto a 1944-by-1536 pixels, 14-bit, flat detector panel. </p> <p> </p> <p><strong>Sample Information</strong></p> <p>The sample consists of a thin-walled plastic far filled with store-bought mixed-sized oatmeal flakes. This sample was chosen due to its repeating/self-similar structure. This self-similarity is an important factor and is exploited in the algorithm for improving image resolution, presented in the referred paper.</p> <p> </p> <p><strong>Experimental Plan</strong></p> <p>Three experiments at two magnification levels were performed, which are denoted by <strong>Zoom1</strong> and <strong>Zoom4</strong>: <em>Zoom1</em> is the dataset collected with magnification factor of 1.09, with the plastic jar filled with oatmeal fully in view. <em>Zoom4 - centre</em> is the sample scanned at magnification of 4.38, with the field of view aligned with the centre of the same (i.e. the centre of the original view in Zoom1). <em>Zoom4 - top</em> is where the tube and the detector are positioned to show the top of the sample (surface level of the oatmeal flakes is visible at the top of the field of view).</p> <p>The datasets were collected over a 360° in circular and continuous motion with 2000 projections distributed evenly over the full circle. The upload includes the raw data collected following the experimental plan, which includes additional projections for normalization: one dark-field (closed shutter) and two (pre- and post-) flat-field (open shutter) images. Each dataset is packaged with the full list of data and scan settings files (in .txt format). These files contain the tube settings, scan geometry and full list of motor positions at the start of the scan. In addition, ASTRA geometry format file is included for each data in the geometries folder. </p> <p> </p> <p><strong>List of Contents</strong></p> <p>The contents of the submission (sorted into folders) is given below.</p> <ul> <li><strong>data</strong>: The raw (uncorrected) datasets (including dark and flat fields) for <ul> <li><em>Zoom1,</em></li> <li><em>Zoom4-centre,</em></li> <li><em>Zoom4-top.</em></li> </ul> </li> <li><em><strong>geometries</strong></em>: The set of parameters needed for the ASTRA forward and back projectors.</li> <li><em><strong>test</strong></em>: Test dataset compiled as detailed in the referred paper, or in <a href="https://ahendriksen.github.io/on_the_fly/readme.html">On-the-fly GitHub documentation.</a></li> <li><em><strong>train</strong></em>: Training dataset as detailed in the referred paper, or in <a href="https://ahendriksen.github.io/on_the_fly/readme.html">On-the-fly GitHub documentation.</a></li> <li><em><strong>weights</strong></em>: Weights as detailed in the referred paper, or in <a href="https://ahendriksen.github.io/on_the_fly/readme.html">On-the-fly GitHub documentation.</a></li> <li><em><strong>Makefile</strong></em>: File containing steps to reproduce results presented in the referred paper.</li> </ul> <p> </p> <p><strong>Additional Links</strong></p> <p>These datasets are produced by the <a href="https://www.cwi.nl/research/groups/computational-imaging">Computational Imaging group</a> at Centrum Wiskunde & Informatica (CI-CWI). For any useful Python/MATLAB scripts for the FleX-ray datasets, we refer the reader to our group's <a href="http://github.com/cicwi">GitHub page</a>.</p> <p> </p> <p><strong>Contact Details</strong></p> <p>For more information or guidance in using these dataset, please get in touch with </p> <ul> <li>s.b.coban [at] cwi.nl</li> <li>allard.hendriksen [at] cwi.nl</li> </ul> <p> </p>
Dataset for the publication "Theory and Experimental Validation of Two Techniques for Compensating VT Nonlinearities"
<p>This is dataset for paper published:</p> <p>G. D’Avanzo <em>et al</em>., "Theory and Experimental Validation of Two Techniques for Compensating VT Nonlinearities," in <em>IEEE Transactions on Instrumentation and Measurement</em>, vol. 71, pp. 1-12, 2022, Art no. 9001312, doi: 10.1109/TIM.2022.3147883.</p>
Daily soil water content under different tillage techniques in Józsefmajor Experimental and Training Farm, Hungary
<p>Continous soil water content monitoring of a Central European chernozem type soil under mouldboard ploughing (MP) and no-tillage (NT) treatments</p> <p>Measurement frequency was 10 minutes, aggragated daily mean data are presented.</p> <p>Sampling depths: 5-10, 15-20, 30-35, 40-45 cm</p> <p><strong>Site description:</strong> Józsefmajor Experimental and Training Farm's long-term tillage experiment (Hungary, 47.688, 19.605).</p> <p>crop rotation, adaptable fertilization, Haplic Kastanozem (Aric, Pantoloamic, Pachic, Bathycalcic) soil type,</p> <p> </p>
Experimental data for "Development of Experimental Techniques for Parameterization of Multi-scale Lithium-ion Battery Models"
<p>This dataset is for the validation data in Chen et al. (2020). It contains data for three different LG M50 cells undergoing an experiment in which the cells are charged in a constant-current/constant-voltage fashion and discharge at a constant current for different C-rates (C/10, C/2, 1C and 1.5C). Apart from the current and voltage, the temperatures of the cell surface and the thermal chamber in which they are cycled is recorded too.</p> <p><strong>References:</strong></p> <p>Chang-Hui Chen <em>et al</em> 2020 <em>J. Electrochem. Soc.</em> <strong>167</strong> 080534 (<a href="https://doi.org/10.1149/1945-7111/ab9050">https://doi.org/10.1149/1945-7111/ab9050</a>)</p>
Dataset of paper "Comparison of radiant intensity in aqueous media using experimental and numerical simulation techniques"
<p>Dataset of paper "<strong>Comparison of radiant intensity in aqueous media using experimental and numerical simulation techniques</strong>":</p><ul><li>Relative spectral intensity for each light source as recorded by ILT RAA4 spectroradiometer.</li><li>Material and optical properties of the quartz tube.</li><li>Wavelength specific refractive index and quantum yield in water.</li><li>Ray tracing data vs experimental data (FX-1 265).</li><li>Plot of peak intensity vs working distance (in air) and Comparison between radiometry and ray tracing in the presence of a quartz tube in front of the light source for FX-1 265.</li><li>Recorded peak intensity at multiple working distances using radiometry and ray tracing.</li><li>Comparison between average light loss at multiple distances in radiometry, ray tracing and transmission curve due to quartz material and Plot of percentage light loss for all wavelengths at multiple working distances due to quartz material.</li><li>Data on loss of intensity in comparison with the transmission curve.</li><li>Recorded peak intensity at multiple working distances between simulation tools.</li><li>Comparison between ray tracing, DOM and radiometry for FX-1 265, Uniformity plot obtained from radiometry, ray tracing interface and DOM.</li><li>Data on comparison between actinometry measurements and ray tracing.</li><li>Plot of intensity with wavelength between the two techniques.</li><li>Comparison between measured intensity in air and water medium for FX-1 265.</li><li>Plot of change in peak intensity as light propagates through the quartz tube within the UV fixture at multiple working distances for FX-1 265.</li><li>Simulated intensity in water at different points within the tube.</li></ul><p> </p>
Material Experimental - Comparison of Goal-oriented Analysis Techniques
<p>Experimental material and dataset used to compare GRL-Quant and VeGAn techniques.</p>
Dataset of the publication "Theory and Experimental Validation of Two Techniques for Compensating VT Nonlinearities"
<p>This is a dataset for paper published:</p> <p>G. D’Avanzo <em>et al</em>., "Theory and Experimental Validation of Two Techniques for Compensating VT Nonlinearities," in <em>IEEE Transactions on Instrumentation and Measurement</em>, vol. 71, pp. 1-12, 2022, Art no. 9001312, doi: 10.1109/TIM.2022.3147883.</p> <p> </p> <p>Excel file provides data for VT_B.</p>
Artifact for paper "An Experimental Evaluation of Conformance Testing Techniques in Active Automata Learning" at MODELS 2023
<p>This is the archival artifact intended for artefact evaluation of the paper "An Experimental Evaluation of Conformance Testing Techniques in Active Automata Learning" accepted at MODELS 2023. </p>
Data from: An experimental test of buffer utility as a technique for managing pool-breeding amphibians
Open the record for dataset details and reuse information.
Application of Different Building Representation Techniques in HEC-RAS 2-D for Urban Flood Modeling Using the Toce River Experimental Case
<p>The output of numerical simulation in HEC-RAS 2-D</p>
Experimental data used in the publication :" Investigation of the Effects of Various Severe Plastic Deformation Techniques on the Microstructure of Laser Powder Bed Fusion AlSi10Mg Alloy"
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Data from: Accelerating plant DNA barcode reference library construction using herbarium specimens: improved experimental techniques
A well-covered reference library is crucial for successful identification of species by DNA barcoding. The biggest difficulty in building such a reference library is the lack of materials of organisms. Herbarium collections are potentially an enormous resource of materials. In this study, we demonstrate that it is likely to build such reference libraries using the reconstructed (self-primed PCR amplified) DNA from the herbarium specimens. We used 179 rosaceous specimens to test the effects of DNA reconstruction, 420 randomly sampled specimens to estimate the usable percentage and another 223 specimens of true cherries (Cerasus, Rosaceae) to test the coverage of usable specimens to the species. The barcode rbcLb (the central four-sevenths of rbcL gene) and matK was each amplified in two halves and sequenced on Roche GS 454 FLX+. DNA from the herbarium specimens was typically shorter than 300 bp. DNA reconstruction enabled amplification fragments of 400–500 bp without bringing or inducing any sequence errors. About one-third of specimens in the national herbarium of China (PE) were proven usable after DNA reconstruction. The specimens in PE cover all Chinese true cherry species and 91.5% of vascular species listed in Flora of China. It is very possible to build well-covered reference libraries for DNA barcoding of vascular species in China. As exemplified in this study, DNA reconstruction and DNA-labelled next-generation sequencing can accelerate the construction of local reference libraries. By putting the local reference libraries together, a global library for DNA barcoding becomes closer to reality.
Data from: Accelerating plant DNA barcode reference library construction using herbarium specimens: improved experimental techniques
Open the record for dataset details and reuse information.
The Effect of the Use of Jigsaw Technique on Nursing Students' Critical Article Reviews and Students' Opinions on the Technique- Quasi-Experimental Study
ClinicalTrials.gov study NCT06339502. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Experimental Techniques for Early Identification of Autism
ClinicalTrials.gov study NCT05712512. IPD Sharing: NO. Countries: 1. Publications: 0.
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.