100+ datasets found
  1. TRACE-A Merge Data

    • catalog.data.gov
    • s.cnmilf.com
    • +1more
    Updated Oct 8, 2024
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    NASA/LARC/SD/ASDC (2024). TRACE-A Merge Data [Dataset]. https://catalog.data.gov/dataset/trace-a-merge-data
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    Dataset updated
    Oct 8, 2024
    Dataset provided by
    NASAhttp://nasa.gov/
    Description

    TRACE-A_Merge_Data is merge data files created from data collected onboard the DC-8 aircraft during the Transport and Atmospheric Chemistry near the Equator - Atlantic (TRACE-A) suborbital campaign. Data collection for this product is complete. The TRACE-A mission was a part of NASA’s Global Tropospheric Experiment (GTE) – an assemblage of missions conducted from 1983-2001 with various research goals and objectives. TRACE-A was conducted in the Atlantic from September 21 to October 24, 1992. TRACE-A had the objective of determining the cause and source of the high concentrations of ozone that accumulated over the Atlantic Ocean between southern Africa and South America from August to October. NASA partnered with the Brazilian Space Agency (INPE) to accomplish this goal.  The NASA DC-8 aircraft and ozonesondes were utilized during TRACE-A to collect the necessary data. The DC-8 was equipped with 19 instruments. A few instruments on the DC-8 include the Differential Absorption Lidar (DIAL), the Laser-Induced Fluorescence, the O3-NO Ethylene/Forward Scattering Spectrometer, the Modified Licor, and the DACOM IR Laser Spectrometer. The DIAL was responsible for a variety of measurements, which include Nadir IR aerosols, Nadir UV aerosols, Zenith IR aerosols, Zenith VS aerosols, ozone, and ozone column. The Laser-Induced Fluorescence instrument collected measurements on NxOy in the atmosphere. Measurements of ozone were recorded by the O3-NO Ethylene/Forward Scattering Spectrometer while the Modified Licor recorded CO2. Finally, the DACOM IR Laser Spectrometer gathered an assortment of data points, including CO, O3, N2O, CH4, and CO2. Ozonesondes played a role in data collection for TRACE-A along with the DC-8 aircraft. The sondes were dropped from the DC-8 aircraft in order to gather data on ozone, temperature, and atmospheric pressure.

  2. NASA DC-8 1 Second Data Merge

    • data.ucar.edu
    ascii
    Updated Dec 26, 2024
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    Gao Chen; Jennifer R. Olson; Langley Research Center (LaRC), NASA (2024). NASA DC-8 1 Second Data Merge [Dataset]. http://doi.org/10.5065/D6SF2TXB
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    asciiAvailable download formats
    Dataset updated
    Dec 26, 2024
    Dataset provided by
    University Corporation for Atmospheric Research
    Authors
    Gao Chen; Jennifer R. Olson; Langley Research Center (LaRC), NASA
    Time period covered
    May 18, 2012 - Jun 22, 2012
    Area covered
    Description

    This data set contains NASA DC-8 1 Second Data Merge data collected during the Deep Convective Clouds and Chemistry Experiment (DC3) from 18 May 2012 through 22 June 2012. These merges are an updated version that were provided by NASA. In most cases, variable names have been kept identical to those submitted in the raw data files. However, in some cases, names have been changed (e.g., to eliminate duplication). Units have been standardized throughout the merge. No "grand merge" has been provided for the 1-second data on the DC8 aircraft due to its prohibitive size (~1.5GB). In most cases, downloading the individual merge files for each day and simply concatenating them should suffice. This data set is in ICARTT format. Please see the header portion of the data files for details on instruments, parameters, quality assurance, quality control, contact information, and data set comments. For more information on the updates to this dataset, please see the readme file.

  3. ORACLES Merge Data Files

    • s.cnmilf.com
    • data.nasa.gov
    • +3more
    Updated Dec 7, 2023
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    NASA/LARC/SD/ASDC (2023). ORACLES Merge Data Files [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/oracles-merge-data-files-ec442
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    Dataset updated
    Dec 7, 2023
    Dataset provided by
    NASAhttp://nasa.gov/
    Description

    ORACLES_Merge_Data are pre-generated aircraft merge data files created utilizing data collected during the ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) campaign. These measurements were collected from August 19, 2016 – October 27, 2016, August 1, 2017 – September 4, 2017 and September 21, 2018 – October 27, 2018. ORACLES provides multi-year airborne observations over the complete vertical column of key parameters that drive aerosol-cloud interactions in the southeast Atlantic, an area with some of the largest inter-model differences in aerosol forcing assessments on the planet. The P-3 Orion aircraft was utilized as a low-flying platform for simultaneous in situ and remote sensing measurements of aerosols and clouds and was supplemented by ER-2 remote sensing during the 2016 campaign. Data collection for this product is complete. Southern Africa produces almost one-third of the Earth’s biomass burning aerosol particles. The ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) experiment was a five year investigation with three intensive observation periods (August 19, 2016 – October 27, 2016; August 1, 2017 – September 4, 2017; September 21, 2018 – October 27, 2018) and was designed to study key processes that determine the climate impacts of African biomass burning aerosols. ORACLES provided multi-year airborne observations over the complete vertical column of the key parameters that drive aerosol-cloud interactions in the southeast Atlantic, an area with some of the largest inter-model differences in aerosol forcing assessments. These inter-model differences in aerosol and cloud distributions, as well as their combined climatic effects in the SE Atlantic are partly due to the persistence of aerosols above clouds. The varying separation of cloud and aerosol layers sampled during ORACLES allow for a process-oriented understanding of how variations in radiative heating profiles impact cloud properties, which is expected to improve model simulations for other remote regions experience long-range aerosol transport above clouds. ORACLES utilized two NASA aircraft, the P-3 and ER-2. The P-3 was used as a low-flying platform for simultaneous in situ and remote sensing measurements of aerosols and clouds in all three campaigns, supplemented by ER-2 remote sensing in 2016. ER-2 observations will be used to enhance satellite-based remote sensing by resolving variability within a particular scene, and by guiding the development of new and improved remote sensing techniques.

  4. KORUS-AQ Aircraft Merge Data Files - Dataset - NASA Open Data Portal

    • data.staging.idas-ds1.appdat.jsc.nasa.gov
    Updated Feb 18, 2025
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    nasa.gov (2025). KORUS-AQ Aircraft Merge Data Files - Dataset - NASA Open Data Portal [Dataset]. https://data.staging.idas-ds1.appdat.jsc.nasa.gov/dataset/korus-aq-aircraft-merge-data-files
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    Dataset updated
    Feb 18, 2025
    Dataset provided by
    NASAhttp://nasa.gov/
    Description

    KORUSAQ_Merge_Data are pre-generated merge data files combining various products collected during the KORUS-AQ field campaign. This collection features pre-generated merge files for the DC-8 aircraft. Data collection for this product is complete. The KORUS-AQ field study was conducted in South Korea during May-June, 2016. The study was jointly sponsored by NASA and Korea’s National Institute of Environmental Research (NIER). The primary objectives were to investigate the factors controlling air quality in Korea (e.g., local emissions, chemical processes, and transboundary transport) and to assess future air quality observing strategies incorporating geostationary satellite observations. To achieve these science objectives, KORUS-AQ adopted a highly coordinated sampling strategy involved surface and airborne measurements including both in-situ and remote sensing instruments. Surface observations provided details on ground-level air quality conditions while airborne sampling provided an assessment of conditions aloft relevant to satellite observations and necessary to understand the role of emissions, chemistry, and dynamics in determining air quality outcomes. The sampling region covers the South Korean peninsula and surrounding waters with a primary focus on the Seoul Metropolitan Area. Airborne sampling was primarily conducted from near surface to about 8 km with extensive profiling to characterize the vertical distribution of pollutants and their precursors. The airborne observational data were collected from three aircraft platforms: the NASA DC-8, NASA B-200, and Hanseo King Air. Surface measurements were conducted from 16 ground sites and 2 ships: R/V Onnuri and R/V Jang Mok. The major data products collected from both the ground and air include in-situ measurements of trace gases (e.g., ozone, reactive nitrogen species, carbon monoxide and dioxide, methane, non-methane and oxygenated hydrocarbon species), aerosols (e.g., microphysical and optical properties and chemical composition), active remote sensing of ozone and aerosols, and passive remote sensing of NO2, CH2O, and O3 column densities. These data products support research focused on examining the impact of photochemistry and transport on ozone and aerosols, evaluating emissions inventories, and assessing the potential use of satellite observations in air quality studies.

  5. DLR Falcon 1 Minute Data Merge

    • data.ucar.edu
    ascii
    Updated Dec 26, 2024
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    Gao Chen; Jennifer R. Olson; Michael Shook (2024). DLR Falcon 1 Minute Data Merge [Dataset]. http://doi.org/10.26023/SZ09-F2G3-7X0V
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    asciiAvailable download formats
    Dataset updated
    Dec 26, 2024
    Dataset provided by
    University Corporation for Atmospheric Research
    Authors
    Gao Chen; Jennifer R. Olson; Michael Shook
    Time period covered
    May 29, 2012 - Jun 14, 2012
    Area covered
    Description

    This data set contains DLR Falcon 1 Minute Data Merge data collected during the Deep Convective Clouds and Chemistry Experiment (DC3) from 29 May 2012 through 14 June 2012. These merges were created using data in the NASA DC3 archive as of September 25, 2013. In most cases, variable names have been kept identical to those submitted in the raw data files. However, in some cases, names have been changed (e.g., to eliminate duplication). Units have been standardized throughout the merge. In addition, a "grand merge" has been provided. This includes data from all the individual merged flights throughout the mission. This grand merge will follow the following naming convention: "dc3-mrg06-falcon_merge_YYYYMMdd_R2_thruYYYYMMdd.ict" (with the comment "_thruYYYYMMdd" indicating the last flight date included). This data set is in ICARTT format. Please see the header portion of the data files for details on instruments, parameters, quality assurance, quality control, contact information, and data set comments.

  6. Top challenges of merging linear TV and digital campaign data in the U.S....

    • statista.com
    Updated Dec 6, 2024
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    Statista (2024). Top challenges of merging linear TV and digital campaign data in the U.S. 2023 [Dataset]. https://www.statista.com/statistics/1401528/leading-challenges-merging-linear-tv-digital-campaign-data-us/
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    Dataset updated
    Dec 6, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    During a survey conducted among TV marketers in the United States and released in May 2023, the main challenge of merging linear and digital data was identified by 53 percent of respondents with the lack of common metrics across channels. The creation of a holistic framework for planning and measurement was mentioned by 41 percent of respondents, while 40 percent cited data-sharing restrictions by walled gardens.

  7. SEAC4RS Merge Data Files

    • data.nasa.gov
    • cmr.earthdata.nasa.gov
    • +2more
    application/rdfxml +5
    Updated Feb 28, 2023
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    SEAC4RS Merge Data Files [Dataset]. https://data.nasa.gov/dataset/SEAC4RS-Merge-Data-Files/dr76-kt8p
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    csv, tsv, json, xml, application/rdfxml, application/rssxmlAvailable download formats
    Dataset updated
    Feb 28, 2023
    Description

    SEAC4RS_Merge_Data are pre-generated merge data files collected during the Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEA4CRS) airborne field study. This product contains merged data products collected from instruments onboard the DC-8 and ER-2 aircrafts. Data collection for this product is complete.

    Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) airborne field study was conducted in August and September of 2013. The field operation was based in Houston, Texas. The primary SEAC4RS science objectives are: to determine how pollutant emissions are redistributed via deep convection throughout the troposphere; to determine the evolution of gases and aerosols in deep convective outflow and the implications for UT/LS chemistry; to identify the influences and feedbacks of aerosol particles from anthropogenic pollution and biomass burning on meteorology and climate through changes in the atmospheric heat budget (i.e., semi-direct effect) or through microphysical changes in clouds (i.e., indirect effects); and lastly, to serve as a calibration and validation test bed for future satellite instruments and missions.

    The airborne observational data were collected from three aircraft platforms: the NASA DC-8, ER-2, and SPEC LearJet. Both the NASA DC-8 and ER-2 aircraft were instrumented for comprehensive in-situ and remote sensing measurements of the trace gas, aerosol properties, and cloud properties. In addition, radiative fluxes and meteorological parameters were also recorded. The NASA DC-8 was mostly responsible for tropospheric sampling, while the NASA ER-2 was operating in the lower stratospheric regime. The SPEC LearJet was dedicated to in-situ cloud characterizations. To accomplish the science objectives, the flight plans were designed to investigate the influence of biomass burning and pollution, their temporal evolution, and ultimately, impacts on meteorological processes which can, in turn, feedback on regional air quality. With respect to meteorological feedbacks, the opportunity to examine the impact of polluting aerosols on cloud properties and dynamics was of particular interest.

  8. h

    merged-data-v2-llama-2

    • huggingface.co
    Updated Jan 3, 2025
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    Creitin Gameplays (2025). merged-data-v2-llama-2 [Dataset]. https://huggingface.co/datasets/CreitinGameplays/merged-data-v2-llama-2
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jan 3, 2025
    Authors
    Creitin Gameplays
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    CreitinGameplays/merged-data-v2-llama-2 dataset hosted on Hugging Face and contributed by the HF Datasets community

  9. g

    Data from: Post-stack 3D merging to fast-track regional interpretation -...

    • ecat.ga.gov.au
    Updated Jul 3, 2024
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    (2024). Post-stack 3D merging to fast-track regional interpretation - offshore Otway Basin case study [Dataset]. https://ecat.ga.gov.au/geonetwork/srv/search?keyword=3D%20Mega%20merge
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    Dataset updated
    Jul 3, 2024
    Description

    Ideally when combining different 3D seismic surveys differences in acquisition parameters warrant full pre-stack reprocessing from field data. However, there are occasions where this is not possible due to time, financial or data access constraints; a valuable alternative is post-stack merging and enhancement of existing migrations. The offshore Otway Basin was the subject of such a project, the objective of which was to produce a regularised and seamless 3D dataset of the highest possible quality, within a two-month turnaround time. The input migrated volumes varied by data extent, migration methodology, angle range and grid orientation. 14 input volumes totalling 8,092 km2 were post-stack merged and processed to produce a continuous and consistent volume, enabling more efficient and effective interpretation of the region. The surveys were regularised onto a common grid, optimised for structural trend, prior to survey matching. DUG’s mis-tie analysis algorithm, applied over a time window optimised for interpretation of key
    events, was used to derive corrections for timing, phase and amplitude, using the Investigator North survey as a reference. This was followed by time-variant spectral and amplitude matching, with gain corrections applied, to improve continuity between volumes. Additional enhancements including noise removal and lateral amplitude scaling were also applied. The final merged volume offers significant uplift over the inputs providing better imaging of structure and event and dramatically improving the efficiency and quality of interpretation. This enables rapid reconnaissance of the area by explorers. Presented at the Australian Energy Producers (AEP) Conference & Exhibition

  10. Z

    Dataset of merge conflicts collected from GitHub repositories

    • data.niaid.nih.gov
    • zenodo.org
    Updated Apr 16, 2020
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    Victor Cacciari Miraldo (2020). Dataset of merge conflicts collected from GitHub repositories [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_3751037
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    Dataset updated
    Apr 16, 2020
    Dataset authored and provided by
    Victor Cacciari Miraldo
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Within each nested folder of the archive you will find files A,O,B and M. They each represent a conflict where file O was altered in two different ways, resulting in A and B. Finally, a developer solved the merge conflict committing M as the solution.

    We have selected these by manually searching for a programming language on GitHub and selecting those repositories that had a large number of forks, commits and contributors.

  11. Data Integration Market Size & Share Analysis - Industry Research Report -...

    • mordorintelligence.com
    pdf,excel,csv,ppt
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    Mordor Intelligence, Data Integration Market Size & Share Analysis - Industry Research Report - Growth Trends [Dataset]. https://www.mordorintelligence.com/industry-reports/data-integration-market
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    pdf,excel,csv,pptAvailable download formats
    Dataset authored and provided by
    Mordor Intelligence
    License

    https://www.mordorintelligence.com/privacy-policyhttps://www.mordorintelligence.com/privacy-policy

    Time period covered
    2019 - 2030
    Area covered
    Global
    Description

    Data Integration Market is Segmented by Component (tools and Services), Deployment (cloud and On-Premise), Enterprise Size (small, Medium, and Large Enterprises), Application (sales, Operations and Supply Chain, Marketing, HR, and Other Applications), and by End-User Vertical (IT and Telecom, BFSI, Healthcare, Manufacturing, Retail and E-Commerce, Government and Defense, and Other End-User Verticals) and Geography (North America, Europe, Asia-Pacific, Latin America, Middle East & Africa). The Market Sizes and Forecasts are Provided in Terms of Value in USD for all the Above Segments.

  12. ACTIVATE Falcon Aircraft Merge Data Files

    • data.staging.idas-ds1.appdat.jsc.nasa.gov
    • gimi9.com
    • +5more
    Updated Feb 19, 2025
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    data.staging.idas-ds1.appdat.jsc.nasa.gov (2025). ACTIVATE Falcon Aircraft Merge Data Files [Dataset]. https://data.staging.idas-ds1.appdat.jsc.nasa.gov/dataset/activate-falcon-aircraft-merge-data-files
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    Dataset updated
    Feb 19, 2025
    Dataset provided by
    NASAhttp://nasa.gov/
    Description

    ACTIVATE_Merge_Data is the pre-generated merge data files created from data collected onboard the HU-25 Falcon aircraft during the ACTIVATE project. ACTIVATE is a 5-year NASA Earth-Venture Sub-Orbital field campaign, with a target completion of December 2023. Data collection is still ongoing. Marine boundary layer clouds play a critical role in Earth’s energy balance and water cycle. These clouds cover more than 45% of the ocean surface and exert a net cooling effect. The Aerosol Cloud meTeorology Interactions oVer the western Atlantic Experiment (ACTIVATE) project is a five-year project (January 2019-December 2023) that will provide important globally-relevant data about changes in marine boundary layer cloud systems, atmospheric aerosols and multiple feedbacks that warm or cool the climate. ACTIVATE studies the atmosphere over the western North Atlantic and samples its broad range of aerosol, cloud and meteorological conditions using two aircraft, the UC-12 King Air and HU-25 Falcon. The UC-12 King Air will primarily be used for remote sensing measurements while the HU-25 Falcon will contain a comprehensive instrument payload for detailed in-situ measurements of aerosol, cloud properties, and atmospheric state. A few trace gas measurements will also be onboard the HU-25 Falcon for the measurements of pollution traces, which will contribute to airmass classification analysis. A total of 150 coordinated flights over the western North Atlantic are planned through 6 deployments from 2020-2022. The ACTIVATE science observing strategy intensively targets the shallow cumulus cloud regime and aims to collect sufficient statistics over a broad range of aerosol and weather conditions which enables robust characterization of aerosol-cloud-meteorology interactions. This strategy is implemented by two nominal flight patterns: Statistical Survey and Process Study. The statistical survey pattern involves close coordination between the remote sensing and in-situ aircraft to conduct near coincident sampling at and below cloud base as well as above and within cloud top. The process study pattern involves extensive vertical profiling to characterize the target cloud and surrounding aerosol and meteorological conditions.

  13. h

    merged-data

    • huggingface.co
    Updated Apr 20, 2024
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    Creitin Gameplays (2024). merged-data [Dataset]. https://huggingface.co/datasets/CreitinGameplays/merged-data
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Apr 20, 2024
    Authors
    Creitin Gameplays
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    CreitinGameplays/merged-data dataset hosted on Hugging Face and contributed by the HF Datasets community

  14. Top benefits of merging linear TV and digital campaign data in the U.S. 2023...

    • statista.com
    Updated Jul 25, 2023
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    Statista (2023). Top benefits of merging linear TV and digital campaign data in the U.S. 2023 [Dataset]. https://www.statista.com/statistics/1396370/leading-benefits-merging-linear-tv-digital-campaign-data-us/
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    Dataset updated
    Jul 25, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    During a survey conducted among TV marketers in the United States and released in May 2023, the main benefit of merging linear and digital data was identified by 70 percent of respondents with audience targeting. This was followed by measurement, cited by 58 percent of respondents, while extended reach rounded out the top three with 55 percent.

  15. d

    Alaska merged geophysical data grids

    • catalog.data.gov
    Updated Jul 5, 2023
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    Alaska Division of Geological & Geophysical Surveys (Point of Contact) (2023). Alaska merged geophysical data grids [Dataset]. https://catalog.data.gov/dataset/alaska-merged-geophysical-data-grids9
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    Dataset updated
    Jul 5, 2023
    Dataset provided by
    Alaska Division of Geological & Geophysical Surveys (Point of Contact)
    Area covered
    Alaska
    Description

    Merged grids of residual magnetic intensity, digital terrain model, and apparent resistivity compiled from the Black Mountain, Liscum, Goodpaster, SE extension of Salcha River - Pogo, and Salcha River Pogo geophysical surveys.

  16. 4

    Data underlying the publication: Modelling perceived risk and trust in...

    • data.4tu.nl
    • 4tu.edu.hpc.n-helix.com
    zip
    Updated Oct 20, 2023
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    Xiaolin He; J.C.J. (Jork) Stapel; Meng Wang; R. (Riender) Happee (2023). Data underlying the publication: Modelling perceived risk and trust in driving automation reacting to merging and braking vehicles [Dataset]. http://doi.org/10.4121/95a4bb4e-3ca4-4fcc-ba34-4be76a9ab578.v1
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    zipAvailable download formats
    Dataset updated
    Oct 20, 2023
    Dataset provided by
    4TU.ResearchData
    Authors
    Xiaolin He; J.C.J. (Jork) Stapel; Meng Wang; R. (Riender) Happee
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Dataset funded by
    European Union’s Horizon 2020
    Description

    This dataset is derived from a driving simulator study that explored the dynamics of perceived risk and trust in the context of driving automation. The study involved 25 participants who were tasked with monitoring SAE Level 2 driving automation features (Adaptive Cruise Control and Lane Centering) while encountering various driving scenarios on a motorway. These scenarios included merging and hard-braking events with different levels of criticality.

    This dataset contains kinetic data from the driving simulator, capturing variables such as vehicle position, velocity, and acceleration among others. Subjective ratings of perceived risk and trust, collected post-event for regression analysis are also included.

  17. V

    MeSH 2025 Update - Merge Report

    • data.virginia.gov
    • datadiscovery.nlm.nih.gov
    • +2more
    csv, json, rdf, xsl
    Updated Dec 16, 2024
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    National Library of Medicine (2024). MeSH 2025 Update - Merge Report [Dataset]. https://data.virginia.gov/dataset/mesh-2025-update-merge-report
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    xsl, json, rdf, csvAvailable download formats
    Dataset updated
    Dec 16, 2024
    Dataset provided by
    National Library of Medicine
    Description

    (Includes MeSH 2023 and 2024 changes) NOTE - There are no Merges for 2025 MeSH. The MeSH 2025 Update - Merge Report describes cases where two or more terms have merged into a single term. The term(s) being merged into another term become(s) an Entry Term. Merges can be between Descriptors and Supplementary Concept Records (SCRs), between Descriptors, or between SCRs. This report includes MeSH changes from previous years, starting from 2023.

  18. ARISE C-130 Aircraft Merge Data Files

    • data.nasa.gov
    • s.cnmilf.com
    • +2more
    application/rdfxml +5
    Updated Feb 28, 2023
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    ARISE C-130 Aircraft Merge Data Files [Dataset]. https://data.nasa.gov/dataset/ARISE-C-130-Aircraft-Merge-Data-Files/gjey-q884
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    tsv, csv, xml, json, application/rdfxml, application/rssxmlAvailable download formats
    Dataset updated
    Feb 28, 2023
    Description

    ARISE_Merge_Data_1 is the Arctic Radiation - IceBridge Sea & Ice Experiment (ARISE) 2014 pre-generated aircraft (C-130) merge data files. This product is a result of a joint effort of the Radiation Sciences, Cryospheric Sciences and Airborne Sciences programs of the Earth Science Division in NASA's Science Mission Directorate in Washington. Data collection is complete.

    ARISE was NASA's first Arctic airborne campaign designed to take simultaneous measurements of ice, clouds and the levels of incoming and outgoing radiation, the balance of which determined the degree of climate warming. Over the past few decades, an increase in global temperatures led to decreased Arctic summer sea ice. Typically, Arctic sea ice reflects sunlight from the Earth. However, a loss of sea ice means there is more open water to absorb heat from the sun, enhancing warming in the region. More open water can also cause the release of more moisture into the atmosphere. This additional moisture could affect cloud formation and the exchange of heat from Earth’s surface to space. Conducted during the peak of summer ice melt (August 28, 2014-October 1, 2014), ARISE was designed to study and collect data on thinning sea ice, measure cloud and atmospheric properties in the Arctic, and to address questions about the relationship between retreating sea ice and the Arctic climate. During the campaign, instruments on NASA’s C-130 aircraft conducted measurements of spectral and broadband radiative flux profiles, quantified surface characteristics, cloud properties, and atmospheric state parameters under a variety of Arctic atmospheric and surface conditions (e.g. open water, sea ice, and land ice). When possible, C-130 flights were coordinated to fly under satellite overpasses. The primary aerial focus of ARISE was over Arctic sea ice and open water, with minor coverage over Greenland land ice. Through these efforts, the ARISE field campaign helped improve cloud and sea ice computer modeling in the Arctic.

  19. CAMP2Ex Merge Data Files - Dataset - NASA Open Data Portal

    • data.staging.idas-ds1.appdat.jsc.nasa.gov
    Updated Feb 18, 2025
    + more versions
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    nasa.gov (2025). CAMP2Ex Merge Data Files - Dataset - NASA Open Data Portal [Dataset]. https://data.staging.idas-ds1.appdat.jsc.nasa.gov/dataset/camp2ex-merge-data-files
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    Dataset updated
    Feb 18, 2025
    Dataset provided by
    NASAhttp://nasa.gov/
    Description

    CAMP2Ex_Merge_Data are pre-generated aircraft merge data files created utilizing data collected during the Clouds, Aerosol and Monsoon Processes-Philippines Experiment (CAMP2Ex) NASA field study. Data collection for this product is complete. CAMP2Ex was a NASA field study, with three main science objectives: aerosol effect on cloud microphysical and optical properties, aerosol and cloud influence on radiation as well as radiative feedback, and meteorology effect on aerosol distribution and aerosol-cloud interactions. Research on these three main objectives requires a comprehensive characterization of aerosol, cloud, and precipitation properties, as well as the associated meteorological and radiative parameters. Trace gas tracers are also needed for airmass type analysis to characterize the role of anthropogenic and natural aerosols. To deliver these observations, CAMP2Ex utilized a combination of remote sensing and in-situ measurements. NASA’s P-3B aircraft was equipped with a suite of in-situ instruments to conduct measurements of aerosol and cloud properties, trace gases, meteorological parameters, and radiative fluxes. The P-3B was also equipped passive remote sensors (i.e. lidar, polarimeter, radar, and radiometers). A second aircraft, the SPEC Learjet 35A, was primarily dedicated to measuring detailed cloud microphysical properties. The sampling strategy designed for CAMP2Ex coordinated flight plans for both aircraft to maximize the science return. The P-3B was used primarily to conduct remote sensing measurements of cloud and precipitation structure and aerosol layers and vertical profiles of atmospheric state variable, while the Learjet flew below the P-3B to obtain the detailed cloud microphysical properties. During the 2019 field deployment in the vicinity of the Philippines, completed from August 20-October 10, the P-3B conducted 19 science flights and the SPEC Learjet conducted 11 flights. Ground-based aerosol observations were also recorded in 2018 and 2019. CAMP2Ex was completed in partnership with Philippine research and operational weather communities. Measurements completed during CAMP2EX provide a 4-D observational view of the environment of the Philippines and its neighboring waters in terms of microphysical, hydrological, dynamical, thermodynamical and radiative properties of the environment, targeting the environment of shallow cumulus and cumulus congestus clouds.

  20. Merged Sentinel-3A and Sentinel-3B OLCI Regional Binned Inland Waters (ILW)...

    • catalog.data.gov
    • data.nasa.gov
    • +2more
    Updated Jun 8, 2024
    + more versions
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    NASA/GSFC/SED/ESD/GCDC/OB.DAAC (2024). Merged Sentinel-3A and Sentinel-3B OLCI Regional Binned Inland Waters (ILW) Data, version 4 [Dataset]. https://catalog.data.gov/dataset/merged-sentinel-3a-and-sentinel-3b-olci-regional-binned-inland-waters-ilw-data-version-4-096a5
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    Dataset updated
    Jun 8, 2024
    Dataset provided by
    NASAhttp://nasa.gov/
    Description

    The Inland Waters dataset (ILW) provides data for lakes and other water bodies across the contiguous United States (CONUS) and Alaska. ILW significantly reduces the processing effort required by end users and is a standardized community resource for lake and reservoir algorithm development and performance assessment.The data is provided for 15,450 CONUS waterbodies with a size of at least one 300 m pixel and over 2,300 resolvable lakes with sizes greater than three 300 m pixels. Alaska has 5,874 lakes resolvable lakes. ILW is a times series containing 10 years of MERIS (2002-2012) and OLCI from both Sentinel-3a (2016-present) and Sentinel-3b (2018-present).

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NASA/LARC/SD/ASDC (2024). TRACE-A Merge Data [Dataset]. https://catalog.data.gov/dataset/trace-a-merge-data
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TRACE-A Merge Data

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Dataset updated
Oct 8, 2024
Dataset provided by
NASAhttp://nasa.gov/
Description

TRACE-A_Merge_Data is merge data files created from data collected onboard the DC-8 aircraft during the Transport and Atmospheric Chemistry near the Equator - Atlantic (TRACE-A) suborbital campaign. Data collection for this product is complete. The TRACE-A mission was a part of NASA’s Global Tropospheric Experiment (GTE) – an assemblage of missions conducted from 1983-2001 with various research goals and objectives. TRACE-A was conducted in the Atlantic from September 21 to October 24, 1992. TRACE-A had the objective of determining the cause and source of the high concentrations of ozone that accumulated over the Atlantic Ocean between southern Africa and South America from August to October. NASA partnered with the Brazilian Space Agency (INPE) to accomplish this goal.  The NASA DC-8 aircraft and ozonesondes were utilized during TRACE-A to collect the necessary data. The DC-8 was equipped with 19 instruments. A few instruments on the DC-8 include the Differential Absorption Lidar (DIAL), the Laser-Induced Fluorescence, the O3-NO Ethylene/Forward Scattering Spectrometer, the Modified Licor, and the DACOM IR Laser Spectrometer. The DIAL was responsible for a variety of measurements, which include Nadir IR aerosols, Nadir UV aerosols, Zenith IR aerosols, Zenith VS aerosols, ozone, and ozone column. The Laser-Induced Fluorescence instrument collected measurements on NxOy in the atmosphere. Measurements of ozone were recorded by the O3-NO Ethylene/Forward Scattering Spectrometer while the Modified Licor recorded CO2. Finally, the DACOM IR Laser Spectrometer gathered an assortment of data points, including CO, O3, N2O, CH4, and CO2. Ozonesondes played a role in data collection for TRACE-A along with the DC-8 aircraft. The sondes were dropped from the DC-8 aircraft in order to gather data on ozone, temperature, and atmospheric pressure.

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