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6,467 results for “process”
Maturity levels of the customized CMMI-SVC for testing services and their process areas
<p>This resource is associated with the following paper:</p> <p>Assessing the maturity of software testing services using CMMI-SVC: an industrial case study</p>
Laser Texturing Process
<p>Laser Texturing Process</p>
Ecoregional patterns of protist communities in mineral and organic soils: assembly processes, functional traits and diversity of testate amoebae in Northern Eurasia
<p>TA_Traits.csv file includes trait data for testate amoebae. TA_Abundance.csv file includes environmental variables (soil type and region) and relative abundance data of testate amoebae.</p>
Preliminary Breakdown Process of Winter Positive Cloud-to-Ground Lightning Flash and Its relation to the Following First Return Stroke
<p>The file <em>+CG statistics.xlsx</em> contains various statistical parameters for 60 +CG events.</p> <p>The files <em>3D_UPB.dat</em>, <em>3D_DPB.dat</em>, <em>3D_IRPB1.dat</em>, and <em>3D_IRPB2.dat</em> provide the 3D location results for the four example events discussed in the main text. Each file includes data organized in four lines, representing time (ms), x (m), y (m), and z (m), respectively.</p> <p><strong> </strong></p>
Processed JUMP Datasets: For Web and programmatic exploration.
Step by step tutorial on the <a href="https://broadinstitute.github.io/jump_hub/howto/1_jumprr_steps.html">jump hub</a>, and details on the code that produces this tables on our <a href="https://github.com/broadinstitute/monorepo/tree/main/libs/jump_rr#quick-data-access">monorepo</a>.
Datasets for the article "Emerging patterns of CO2:O2 dynamics in rivers and their link to ecosystem carbon processing "
<p>Datasets supporting the article "Emerging patterns of CO2:O2 dynamics in rivers and their link to ecosystem carbon processing". The datasets are analized using the acompanying repository in github (https://github.com/rocher-ros/O2_CO2_rivers).</p> <p> </p> <p>Currently the publication is under review, for further information and details on the analysis visit the github repository or the acompannying article. </p>
Linux kernels v2.6.14 v3.18.129 v6.14.2 processed by CScout
<p>This dataset contains three SQLite databases containing a full image of the <a href="https://www.kernel.org/">Linux kernel</a> in relational form, as generated by the <a href="https://www.spinellis.gr/cscout/">CScout</a> refactoring browser (version 03023d - 2024-08-30 and version afdd54 - 2025-04-19) piping its output to SQLite (version 3.46.0 2024-05-23.</p> <p>The datasets can be used to perform empirical research on the Linux kernel's source code, especially identifier semantics, which they represent in the form of equivalence classes. They form part of the replication package of the paper titled “You Are not Expected to Understand this: The Usage of the C Preprocessor in the Linux Kernel”.</p>
MAB-SWOT CPIES Level 2 Processed Data
<div> <p>These are the hourly (P#.mat) and lowpass filtered (P#lp.mat) files from the current- and pressure- sensor equipped inverted echo sounders (CPIESs) deployed as part of the MAB-SWOT program. Version 2 of this dataset (1) includes data from P3 and (2) uses corrected clock drifts to determine each instruments' time base. A description of the processing and details about the experiment can be found at: Wang, Y. D., & Andres, M. (2025). SWOT Adopt a Crossover Field Campaign—Cape Hatteras (MAB-SWOT) Current and Pressure Sensor Equipped Inverted Echo Sounder (CPIES) Technical Report (Version 2). Zenodo. <a href="https://doi.org/10.5281/zenodo.12583849" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.16851887</a></p> <p> </p> <p> </p> </div>
CCycDB (an integrative knowledgebase to fingerprint microbial carbon cycling processes)
<p>CCycDB - version 2.0 (Please see<strong> </strong><a href="https://ccycdb.github.io/"><strong>https://ccycdb.github.io/</strong></a> for more details)</p><p><strong>CCycDB</strong> is a knowledge-based functional gene database for accurate metagenomic profiling of carbon cycling microbial communities. CCycDB contains 4,676 gene families within 6 categories. These gene families are further categorized into 45 sub-categories within sub-category I and 188 sub-categories within sub-category II with a total of 10,991,724 targeted sequences. A series of validations demonstrated that CCycDB outperformed large public orthology databases in terms of coverage, specificity, and accuracy, and can be used to accurately profile carbon cycling microbial communities in real metagenomic datasets.</p>
Atlas Cortex SD processed data
Open the record for dataset details and reuse information.
Dataset for 'Hadronic processes at work in 5BZB J0630−2406'
Open the record for dataset details and reuse information.
CiP Discrete Manufacturing Dataset (CNC Miling Machine (Process Data))
<p>Dataset recorded in the process learning factory CiP at the Institute for Production Management, Technology and Machine Tools, TU Darmstadt for the purpose of demonstrating and testing InterQ developed solutions. It was used to demonstrate the framework's effectiveness in a case study, involving process monitoring of a real-world Computer Numerical Control milling process. The dataset includes accelerometer data and multiple types of realistic concept drifts. The uploaded file includes the link and password for accessing the dataset in PTW's cloud infrastructure.</p>
CiP Discrete Manufacturing Dataset (CNC Miling Machine (Process Data))
<p>Dataset recorded in the process learning factory CiP at the Institute for Production Management, Technology and Machine Tools, TU Darmstadt for the purpose of demonstrating and testing InterQ developed solutions. It was used to demonstrate the framework's effectiveness in a case study, involving process monitoring of a real-world Computer Numerical Control milling process. The dataset includes accelerometer data and multiple types of realistic concept drifts. The uploaded file includes the link and password for accessing the dataset in PTW's cloud infrastructure.</p><p> </p>
Impact of Image Processing Settings for Radiomic Features in Alzheimer's Disease Using 18F-FDG and 11C-PIB PET Scans
<p>Radiomics is an established method for calculating features for computer-aided diagnosis and has been vastly applied to oncological studies. This study aimed to assess the impact of image processing in radiomic features in neuroimaging. Fifteen Alzheimer's disease subjects and 18 healthy individuals underwent [18F]-2-fluoro-2-deoxy-D-glucose (FDG) and 11C-labelled Pittsburgh Compound B (PIB) PET scans. T1-MRI scans were used for cerebellar and grey matter (GM), and white matter (WM) tissue delineation. PET images were registered to MRI (MR space) and transformed to MNI space. All images were normalized to cerebellar uptake (SUVR). All possible combinations of the following settings were considered to extract feature values: (1)tracer: FDG or PIB; (2)space: MR or MNI space; (3)discretization: fixed bin number (BN) of 64, fixed bin sizes (BS) of 0.05 or 0.25; and (4)volume of interest (VOI): GM, WM, or BRAIN (GM+WM). Features that correlated (>0.9) to traditional metrics (average VOI SUVR and volume) in any configuration were removed. Correlation of feature values between configurations, redundancy, and harmonization of feature values were tested. Image processing settings highly affect radiomic feature values and should be carefully taken into consideration during study design and should be properly reported.</p><p> </p><p>The enclosed datasets refer to the work developed at the University Medical Center Groningen and consists of extracted feature values used in the publication.</p>
Processed data for a Slocum ocean glider campaign in the Gulf of Lion, Mediterranean Sea, 2021
<p>The data set was measured in the Gulf of Lion by a Slocum glider in February 2021. It includes processed data from a CTD and a turbulence microstructure package.</p>
STED images of foot processes
<p>The dataset is made of STED images of mouse and human foot processes. </p><p>It is made of 2 parts. </p><ol><li>288 images of mouse samples</li><li>151 binarised images of human samples, 142 original images. The numbers are different as the few original ones had much bigger size than others, so they were split into more pictures of normal size.</li></ol><p>Folder structure:</p><ul><li>zenodo-mouse-data-renal - mouse images:<ul><li>original:<ul><li>mut - samples with FSGS</li><li>ctrl - control samples</li><li>NTN</li><li>2021_PodR231Q_NTS</li><li>Adriamycin_Kuehne</li></ul></li><li>binarized:<ul><li>train - train set</li><li>test</li></ul></li></ul></li><li>zenodo-human-data-hoyer - images of human samples with foot processes:<ul><li>original</li><li>binarized:<ul><li>train</li><li>test</li></ul></li></ul></li></ul>
Simulation data for paper "Evaluation of Fendiline Treatment in VP40 System with Nucleation-Elongation Process: A Computational Model of Ebola Virus Matrix Protein Assembly"
<p>This is the original simulation data sets for paper "Evaluation of Fendiline Treatment in VP40 System with Nucleation-Elongation Process: A Computational Model of Ebola Virus Matrix Protein Assembly".</p>
Output from paper: The s process in massive stars, a benchmark for neutron capture reaction rates
<p>Title: "The s process in massive stars, a benchmark for neutron capture reaction rates"; Authors: Marco Pignatari, Roberto Gallino, Rene Reifarth</p><p>------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------</p><p>Content: tar.gz package including a README file and two folders. The folders contain all the abundance plots associated to the work Pignatari, Gallino & Reifarth, 2023 The European Physical Journal A, Special Issue on: 'From reactors to stars' in honor of Franz Kaeppeler. </p>
Ocean Heat Content Anomalies in the North Atlantic based on mapping Argo data using local Gaussian processes defined over space
<p>Monthly Ocean Heat Content Anomalies (OHCA) in the top 2000 dbar of the ocean are calculated (during 2005-2022, in the North Atlantic, north of 20N) subtracting the time mean over the period 2005-2021 from the monthly time series of OHC. OHC fields are mapped using a locally stationary Gaussian process (defined over space) with data-driven decorrelation scales (Kuusela and Stein, 2018). A linear time trend was included in the estimate of the mean field (along with spatial terms and harmonics for the annual cycle). In this product, mapping is done in latitude and longitude with monthly subsets of data. Mapping is done separately for different vertical sections: 15-20 dbar, 15-300 dbar, 300-700 dbar, 700-1850 dbar, 1800-1850 dbar. The 15-20 dbar (1800-1850 dbar) section is used to estimate OHCA for 0-15 dbar (1850-2000 dbar), where observations are sparser. Different vertical sections are combined to estimate global OHCA for 0-2000 dbar. Regions of the ocean that are shallower than 300 m or are not sufficiently well sampled by the Argo array are not included. </p>
Pepper Process Data
<p>Pepper colour factor and process group data</p>
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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.