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677 results for “inversion”
AEdiffuison_surrogate_DA_inversion
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Available Data for the Multi-terminal Inverse AC Josephson Effect
<p>Requested data and code for review of "The Multi-terminal Inverse AC Josephson Effect"</p>
High-rate GNSS data in seismic moment tensor inversion. The study of anthropogenic earthquakes - GNSS displacement time series
<p>The dataset of GNSS displacement time series with duration of 30 seconds before and 90 seconds after the origin time of the mining tremors. The dataset was used in the research on High-rate GNSS data in seismic moment tensor inversion. The study of anthropogenic earthquakes.</p> <p>Further description of the HR-GNSS processing can be found in the paper by Kudlacik et al. (2021) and in the research paper "High-rate GNSS data in seismic moment tensor inversion. The study of anthropogenic earthquakes".</p>
A global surface CO2 flux dataset (2015–2021) inferred from OCO-2 retrievals using the GONGGA inversion system
<p>Here we present a global spatially-resolved terrestrial and ocean carbon flux dataset for 2015–2021. The dataset is generated by the Global ObservatioN-based system for monitoring Greenhouse GAses (GONGGA) atmospheric inversion system through assimilating Observing Carbon Observatory 2 (OCO-2) v10r XCO<sub>2</sub> retrievals. The flux files contain NEE, ocean carbon fluxes, fossil fuel emissions, and biomass burning emissions. The NEE and ocean carbon fluxes include the prior and posterior estimates. The corresponding gridded uncertainty of NEE and ocean fluxes are also included in the flux files. The global gridded fluxes are 3-hourly with a resolution of 2° latitude × 2.5° longitude . Users can aggregate the gridded fluxes on their preferred regions. The GEOS-Chem simulated CO<sub>2</sub> concentrations driven by posterior NEE and ocean fluxes, as well as fossil fuel emissions and biomass burning emissions, are generated every 3 hours with a resolution of 2° latitude × 2.5° longitude at 47 vertical levels.</p>
Development of multi-physics data inversion software with optimization via artificial intelligence
<p><strong>The project proposes the development of an innovative inversion technology for the characterization and monitoring of deep water reservoirs using CSEM (Controlled-Source Electromagnetic Methods), a robust risk reduction tool in the drilling of oil basins, using multiphysics data in the 3D domain. One of the main objectives of this project is to develop, optimize and parallelize CSEM codes, aiming at improving their performance. The construction of inversion algorithms will also be performed, such as Deep Neural Networks (DNNs) trained to transform CSEM data into models.</strong></p>
Data for "Extraction and Inversion of Coherent Rayleigh Waves from Urban Anthropogenic Noise with Distributed Acoustic Sensing"
<p>Data for "Extraction and Inversion of Coherent Rayleigh Waves from Urban Anthropogenic Noise with Distributed Acoustic Sensing"</p> <p> </p>
A practical efficient elastic full-waveform inversion for multicomponent OBS data
<p>A practical efficient elastic full-waveform inversion is essential for multicomponent OBS data. It is used to obtain multiparameter estimation for the study of the seismology which can provide the much-needed insight into the earth's interior. In this letter, we present the relevant dataset to the paper. The dataset includes synthetic data which was simulated on the modified Overthrust model and the field data which was acquired from East China Sea. The synthetic data comprises 100 OBSs due to 400 sources. We present the results of our method on the synthetic data and field data and then compared it with traditional adjoint-state method and improved scattering method. </p> <p><strong>Dataset Contents</strong></p> <ul> <li>Synthetic data (common receiver gathers): <ul> <li>the number of sources: 400</li> <li>the number of OBSs: 100</li> <li>the number of total time sampling: 4s</li> </ul> </li> <li>figure1-11: <ul> <li>the dataset relevant to the plot of figures. </li> </ul> </li> </ul>
Late Permian-Early Triassic intracontinental tectonic inversion in the Junggar Basin, NW China: New insights from detrital zircon geochronology and seismic reflection data
<p>The detrital zircon U-Pb isotope data from the Mahu sag is included in the Supporting Information.</p>
Distribution, seasonality, and water-mass transformation of temperature and salinity inversions in the southern Yellow Sea
<p>This dataset contains the used data at Stn. H08 and those transect stations obtained during the spring and summer cruises from 2017 to 2022. It is a supplementary of the manuscript "Distribution, seasonality, and water-mass transformation of temperature and salinity inversions in the southern Yellow Sea". Please let me know if you need any more information.</p>
MER 1 MARS NAVIGATION CAMERA INVERSE LUT RDR OPS V1.0
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MER 1 MARS PANORAMIC CAMERA INVERSE LUT RDR OPS V1.0
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MER 2 MARS PANORAMIC CAMERA INVERSE LUT RDR OPS V1.0
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MER 1 MARS MICROSCOPIC IMAGER INVERSE LUT RDR OPS V1.0
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MER 2 MARS MICROSCOPIC IMAGER INVERSE LUT RDR OPS V1.0
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MER 2 MARS NAVIGATION CAMERA INVERSE LUT RDR OPS V1.0
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MER 2 MARS HAZARD AVOID CAMERA INVERSE LUT RDR OPS V1.0
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MER 1 MARS HAZARD AVOID CAMERA INVERSE LUT RDR OPS V1.0
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International Brain Laboratory public data
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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.