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5,805 results for “Data model”

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zenodo20/100

Coordinated movement of a swarm of nonholonomic wheeled robots modeled as virtual visco-elastic body - raw experiment data

<p>Raw experiment data from&nbsp;verification of 2 control algorithms on 5 nonholonomic mobile robots using OptiTrack motion capture system : virtual spring damper mesh control (algorithm A1)&nbsp;with and without obsticles and swarm selforganization using worm creep algorithm (algorithm A4). Conducted experiment allowed for adjustment of the control parameters (describend in Data.m files) to achieve better performance of the swarm movement.</p> <p>Abbreviations: d1, d2 - are desired interrobot distances, NO- no obsticles, Wo - with obsticles, Sor - self-organization</p> <p>&nbsp;</p>

restrictedJan 2020View details →
zenodo20/100

Data for modeling flow rate and temperature changes in a hot spring

<p>Flow rate ,temperature and meteorological data in a hot spring that used for modeling.&nbsp;</p>

opencc-by-4.0May 2020View details →
zenodo20/100

HER2 data used in the article entitled "MSclassifier: Median-Supplement model-based Classification tool for automated knowledge discovery"

<p>This repository contains HER2 training and test sets used for evaluating MSclassifier and other packages in the software article entitled &quot;MSclassifier: median-supplement model-based classification tool for automated knowledge discovery.&quot; The training set is comprised of 100 instances and 74 attributes while the test set is comprised of 62 instances and 74 attributes. The training samples were used to obtain results from a 10-fold cross-validation testing of how MSclassifier and other packages accurately predicted HER2-receptor status phenotypes in breast cancer in the article. The data used in the software article was obtained from the supplementary data of &quot;Adabor ES, Acquaah-Mensah GK, Machine learning approaches to decipher hormone and HER2 receptor status phenotypes in breast cancer, Briefings in Bioinformatics 2019; 20 (2): 504&ndash;514, https://doi.org/10.1093/bib/bbx138&quot; by permission of Oxford University Press. Here, it is reproduced by permission of Oxford University Press.</p> <p>&nbsp;</p>

restrictedJul 2020View details →
zenodo20/100

NAEI 2016 UK Emission Data, formatted for the EMEP CTM model.

<p>National Atmospheric Emissions Inventory (NAEI) emissions data for Ammonia (NH3), Carbon Monoxide (CO), Nitrogen Oxides (NOx), Non methane VOCs (VOC), particulate matter &lt;2.5 um (pm25), and particulate matter &lt;10 um (pmco) for the UK. Inventory year is 2016. Original data available from: https://naei.beis.gov.uk/data/mapping</p> <p>This data is in netcdf format, and has been formatted for use with the EMEP air quality model (v4.33 onwards, downloadable from https://github.com/metno/emep-ctm ). The dataset consists of the (1km x 1km) gridded NAEI area sources, for each of the 11 emission sectors (agric, domcom, energyprod, indcom, indproc, nature, offshore, othertrans, roadtrans, solvents, and waste). NAEI point sources have been added to these emissions, allocated to the grid cell in which these sources occur. It is recommended that the user consults the processing scripts for details of this apportionment. The datasets also contain total area source emissions (totarea), and total area plus point source emissions (total), for illustration of the point source contributions.</p> <p>The python scripts used to create this datafiles are available in the &#39;NAEI_EMEP_Python_Script&#39; directory of this repository: https://zenodo.org/record/3996688#.X0OYQkl7nUJ</p> <p>&copy; Crown 2020 copyright Defra &amp; BEIS via naei.beis.gov.uk, licenced under the Open Government Licence (OGL).</p>

openogl-uk-2.0Aug 2020View details →
zenodo20/100

Raw Data of the Survey on the Practitioners' Expectations from the Meta-modeling Tools

<p>Here, the survey questions and the answers of 103 different participants can be found.&nbsp;</p>

opencc-by-4.0Sep 2020View details →
zenodo20/100

Exp 3 Model Data Comparison

<p>Model results for the base case of comparing with the MODEX flume data</p>

opencc-by-4.0Dec 2020View details →
zenodo20/100

meta data of 'weather_analytics' data model

<p>description of the data fields of the data model, used in the weather_analytics application</p>

opencc-by-4.0Jun 2017View details →
zenodo20/100

Synthetic Datasets from the Article titled Privacy-preserving Ground-truth Data for Evaluating Additive Feature Attribution in Regression Models with Additive CBR and CQV

<p>Synthetic datasets were generated as benchmarks capturing the intrinsic characteristics of original data to investigate the performance of additive feature attribution methods for regression tasks. The synthetic datasets were generated based on 2, 6 and 8 clusters formed with the original data. The 6-cluster dataset was used for primary analysis and the other two were used for sensitivity analysis.</p><p>The synthetic dataset was generated from the original data acquired from <a href="https://www.eurocontrol.int/dashboard/rnd-data-archive">Aviation Data for Research Repository</a>, which was collected and processed by <a href="https://www.eurocontrol.int/">EUROCONTROL</a> from the Enhanced Tactical Flow Management System (ETFMS) flight data messages containing all flights in Europe throughout the year 2019, from May to October. The original dataset consisted of fundamental details of the flights, flight status, preceding flight legs, ATFM regulations, weather conditions, calendar information, etc.&nbsp;</p><p>A brief description of the columns in the synthetic data files is presented in the file 'data_description.pdf' and a more detailed discussion on features can be found in the works of Koolen and Coliban [1] and Dalmau et al. [2].</p><p>&nbsp;</p><p><strong>References</strong><br>[1] &nbsp;H. Koolen and I. Coliban, <a href="https://www.eurocontrol.int/sites/default/files/2020-06/flight-progress-msg-update-230620.pdf">Flight Progress Messages Document</a>, EUROCONTROL, Brussels, Belgium, Tech. Rep., 2020.<br>[2] &nbsp;R. Dalmau, F. Ballerini, H. Naessens, S. Belkoura, and S. Wangnick, <a href="https://www.sciencedirect.com/science/article/pii/S0969699721000739">An Explainable Machine Learning Approach to Improve Take-off Time Predictions</a>, Journal of Air Transport Management, vol. 95, p. 102 090, Aug. 2021. doi: 10.1016/j.jairtraman.2021.102090.</p><p><br>&nbsp;</p>

restrictedcc-by-4.0Nov 2023View details →
zenodo20/100

Fig. 1. A in On the southernmost high Andean scorpion species, with the identification of a cryptic new species of Brachistosternus (Bothriuridae) through morphology, molecular data and species distribution models

Fig. 1. A. Path to Paso San Francisco international pass, 3500 m asl, Catamarca, Argentina, type locality of Brachistosternus diaguita n. sp. B. Brachistosternus diaguita n. sp. female living specimen.

opennotspecifiedJan 2023View details →
zenodo20/100

Multibeam bathymetry data, multi-channel seismic reflection profiles and pore water modeling code

<p>Supplementary material for "Complex architecture of mud volcano systems: new insights on flow pathways unravel intricate fluid circulation"</p>

restrictedcc-by-4.0Dec 2023View details →
zenodo20/100

Supporting data for the article M. Grześkowiak (2023), 'When Legal Inclusion is not Enough: the "Uganda Model" of Refugee Protection on the Brink of Failure', Refugee Survey Quarterly

<p>The set contains transcripts of in-depth, semi-structured interviews (recorded and later transcribed) as well as field notes from unstructured interviews (not recorded but documented in field notes, which were later digitalised and structured). The interviews were conducted in Uganda in 2022, with online follow-ups extending into 2023. The interviews took place in person in Kampala and in three of the country's official refugee settlements: Imvepi, Bidibidi, and Kyaka II. The participants included government officials, UNHCR representatives, NGO officials, and refugees, including those involved in refugee-led, community-based organisations.</p> <p>Due to the sensitive nature of the research, access to the files is restricted.</p>

restrictedcc-by-4.0Dec 2023View details →
zenodo20/100

Data of resulting velocity and anisotropic models, and Moho depth of the Tanlu fault zone

<p>Data of resulting velocity and anisotropic models, and travel-times for essay of Tanlu Pn tomography. These data can only be used for scientific research purposes.</p><p>1. ani_vel_model.txt &nbsp;</p><p>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Format: longitude, latitude, vel_value (km/s), ani_value (km/s), azimuth_anisotropy (degree)</p><p>2. handpicked_travel_time.txt &nbsp;</p><p>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Format: &nbsp;event_number, event_year, event_month, event_day, event_hour, event_minute, event_second (s), event_lat, event_lon, event_depth (km), event_magnitude, sta_count (for one event)</p><p>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;sta_name1, sta_lat1 (degree), sta_lon1 (degree), sta_elevation1 (m), &nbsp;travel_time1 (s)</p><p>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;sta_name2, sta_lat2 (degree), sta_lon2 (degree), sta_elevation2 (m), &nbsp;travel_time2 (s)</p><p>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;...</p>

restrictedcc-by-4.0Mar 2024View details →
zenodo20/100

Data and scripts for figures for "The modeled seasonal cycles of land biosphere and ocean N2O fluxes and atmospheric N2O"

Open the record for dataset details and reuse information.

openMar 2024View details →
zenodo20/100

Data from the thesis: Reduced-order models to predict mesoscale mechanical behavior of polycrystalline materials

<p>This record contains the data and code from the thesis: Reduced-order models to predict mesoscale mechanical behavior of polycrystalline materials. The contents of the chapter-wise zip files are described in the respective markdown files with the suffix <strong><em>_readme.md</em></strong>.</p> <p>&nbsp;</p> <p>A record containing only the code from the thesis is availabe at: <a href="https://doi.org/10.5281/zenodo.10983507" target="_blank" rel="noopener">10.5281/zenodo.10983507</a>.</p>

restrictedcc-by-4.0Apr 2024View details →
zenodo20/100

ALGORITHM OF DATA PREPARATION FOR CREATION OF CURRENT BPMN MODEL OF ADMINISTRATIVE AND AUXILIARY PROCESSES OF TELECOMMUNICATION ORGANIZATIONS MANAGEMENT.

Open the record for dataset details and reuse information.

opencc-by-4.0Apr 2024View details →
zenodo20/100

Supplementary Data for Manuscript "A relation of resistivity-hydraulic conductivity for fine-grained soil based on coupled electric double layer model and modified Kozeny-Carman model"

Open the record for dataset details and reuse information.

opencc-by-4.0Nov 2024View details →
zenodo20/100

Data set_Network-wide modulation of synaptic plasticity and spike patterns in motor circuits by pallidal deep brain stimulation in a dystonia model

<p>This study utilized deep brain stimulation (DBS) of the globus pallidus pars interna (GPi) to investigate its long-term effects on synaptic activity in motor thalamic and motor cortical neurons in an animal model of generalized dystonia (dtsz hamster). Whole-cell recordings were employed to measure synaptic spike patterns, revealing significant changes in DBS-treated animals compared to sham-treated controls. Specifically, we observed reduced interspike intervals (ISI) and increased postsynaptic current (PSC) frequencies. Fast oscillations were also detected in both thalamic and motor cortical neurons, indicating potential modulation of corticothalamocortical loops by GPi-DBS. Notably, while the overall discharge rates of spontaneous and evoked action potentials remained unchanged, DBS treatment led to increased PSC amplitudes and alterations in inhibitory synaptic currents. These findings suggest that GPi-DBS influences both presynaptic and postsynaptic mechanisms of synaptic plasticity. The results further indicate that GPi-DBS disrupts desynchronized neural activity through axonal and synaptic failures, thereby reorganizing neuronal firing patterns and synaptic connectivity within the motor circuit. This modulation provides mechanistic insights into the therapeutic effects of GPi-DBS in alleviating dystonic symptoms.</p>

restrictedDec 2024View details →
zenodo20/100

Data for the 1-D P-wave velocity model

<p>Data for the 1D P-wave velocity model</p>

restrictedcc-by-4.0Jul 2024View details →
zenodo20/100

Experimental data of manuscript "A new DL sea ice detection model OceanTDLx for SAR image"

<p>Experimental data of manuscript.</p>

opencc-by-4.0Jun 2022View details →
dryad20/100

Data from: Using a null model to recognize significant co-occurrence prior to identifying candidate areas of endemism

[No abstract entered]

opencc-zeroDec 2008View details →

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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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record