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PHOENIX MARS ROBOTIC ARM CAMERA 5 NORMAL OPS V1.0
data.nasa.gov | Last Updated 2023-01-26T20:52:37.000ZThe Robotic Arm Camera (RAC) experiment on the Mars Phoenix Lander consists of one instrument component plus command electronics. This RAC Imaging Operations RDR data set contains normal data from the Robotic Arm Camera (RAC).
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PHOENIX MARS ROBOTIC ARM CAMERA 5 XYZ OPS V1.0
data.nasa.gov | Last Updated 2023-01-26T20:09:16.000ZThe Robotic Arm Camera (RAC) experiment on the Mars Phoenix Lander consists of one instrument component plus command electronics. This RAC Imaging Operations RDR data set contains xyz data from the Robotic Arm Camera (RAC).
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Experimental and Analytical Development of a Health Management System for Electro-Mechanical Actuators
data.nasa.gov | Last Updated 2020-01-29T01:49:29.000ZExpanded deployment of Electro-Mechanical Actuators (EMAs) in critical applications has created much interest in EMA Prognostic Health Management (PHM), a key enabling technology of Condition Based Maintenance (CBM). As such, Impact Technologies, LLC is collaborating with the NASA Ames Research Center to perform a number of research efforts in support of NASA’s Integrated Vehicle Health Management (IVHM) initiatives. These efforts have combined experimental test stand development, laboratory seeded fault testing, and physical model-based health monitoring in a comprehensive PHM system development strategy. This paper discusses two closely related EMA research programs being conducted by Impact and NASA Ames. The first of these efforts resulted in the creation of an electro-mechanical actuator test stand for the Prognostics Center of Excellence at the NASA Ames Research Center. The second effort is ongoing and is utilizing physics-based modeling techniques to develop an algorithm and software package toolset for PHM of aircraft EMA systems using a hybrid (virtual sensor) approach.
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PHOENIX MARS ROBOTIC ARM CAMERA 4 LINEARIZED OPS V1.0
data.nasa.gov | Last Updated 2023-01-26T20:23:42.000ZThe Robotic Arm Camera (RAC) experiment on the Mars Phoenix Lander consists of one instrument component plus command electronics. This RAC Imaging Operations RDR data set contains linearized data from the Robotic Arm Camera (RAC).
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PHOENIX MARS ROBOTIC ARM CAMERA 5 DISPARITY OPS V1.0
data.nasa.gov | Last Updated 2023-01-26T20:39:06.000ZThe Robotic Arm Camera (RAC) experiment on the Mars Phoenix Lander consists of one instrument component plus command electronics. This RAC Imaging Operations RDR data set contains disparity data from the Robotic Arm Camera (RAC).
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PHOENIX MARS ROBOTIC ARM CAMERA 5 ROUGHNESS OPS V1.0
data.nasa.gov | Last Updated 2023-01-26T20:30:16.000ZThe Robotic Arm Camera (RAC) experiment on the Mars Phoenix Lander consists of one instrument component plus command electronics. This RAC Imaging Operations RDR data set contains roughness data from the Robotic Arm Camera (RAC).
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PHOENIX MARS ROBOTIC ARM CAMERA 5 REACHABILITY OPS V1.0
data.nasa.gov | Last Updated 2023-01-26T20:24:49.000ZThe Robotic Arm Camera (RAC) experiment on the Mars Phoenix Lander consists of one instrument component plus command electronics. This RAC Imaging Operations RDR data set contains reachability data from the Robotic Arm Camera (RAC).
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PHOENIX MARS ROBOTIC ARM CAMERA 5 XYZ OPS V1.0
data.nasa.gov | Last Updated 2023-01-26T20:09:17.000ZThe Robotic Arm Camera (RAC) experiment on the Mars Phoenix Lander consists of one instrument component plus command electronics. This RAC Imaging Operations RDR data set contains xyz data from the Robotic Arm Camera (RAC).
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MODIS/Aqua Calibrated Radiances 5-Min L1B Swath 500m - NRT
data.nasa.gov | Last Updated 2023-07-24T13:04:42.000ZThe 500 meter MODIS Level 1B Near Real Time (NRT) data set contains calibrated and geolocated at-aperture radiances for 7 discrete bands located in the 0.45 to 2.20 micron region of the electromagnetic spectrum. These data are generated from the MODIS Level 1A scans of raw radiance and in the process converted to geophysical units of W/(m^2 um sr). In addition, the Earth Bi-directional Reflectance Distribution Function (BRDF) may be determined for these solar reflective bands through knowledge of the solar irradiance (e.g., determined from MODIS solar diffuser data, and from the target illumination geometry). Additional data are provided including quality flags, error estimates and calibration data. Visible, shortwave infrared, and near infrared measurements are only made during the daytime, while radiances for the thermal infrared region (bands 20-25, 27-36) are measured continuously. Channel locations for the MODIS 500 meter data are as follows: Band Center Wavelength (um) Primary Use ---- ---------------------- ----------- 1 0.620 - 0.670 Land/Cloud Boundaries 2 0.841 - 0.876 Land/Cloud Boundaries 3 0.459 - 0.479 Land/Cloud Properties 4 0.545 - 0.565 Land/Cloud Properties 5 1.230 - 1.250 Land/Cloud Properties 6 1.628 - 1.652 Land/Cloud Properties 7 2.105 - 2.155 Land/Cloud Properties Channels 1 and 2 have 250 m resolution, channels 3 through 7 have 500 m resolution. However, for the MODIS L1B 500 m product, the 250 m band radiance data and their associated uncertainties have been aggregated to 500 m resolution. Thus the entire channel data set has been co-registered to the same spatial scale in the 500 m product. Separate L1B products are available for the 250 m resolution channels (MYD02QKM) and 1 km resolution channels (MYD021KM). For the latter product, the 250 m and 500 m channel data (bands 1 through 7) have been aggregated into equivalent 1 km pixel values. Spatial resolution for pixels at nadir is 500 km, degrading to 2.4 km in the along-scan direction at the scan extremes. However, thanks to the overlapping of consecutive swaths and respectively pixels there, the resulting resolution at the scan extremes is about 1 km. A 55 degree scanning pattern at the EOS orbit of 705 km results in a 2330 km orbital swath width and provides global coverage every one to two days. A single MODIS Level 1B 500 m granule will contain a scene built from 203 scans sampled 2708 times in the cross-track direction, corresponding to approximately 5 minutes worth of data; thus 288 granules will be produced per day. Since an individual MODIS scan will contain 20 along-track spatial elements for the 500 m channels, the scene will be composed of (2708 x 4060) pixels, resulting in a spatial coverage of (2330 km x 2040 km). Due to the MODIS scan geometry, there will be increasing scan overlap beyond about 20 degrees scan angle. To summarize, the MODIS L1B 500 m data product consists of: 1. Calibrated radiances, uncertainties and number of samples for (2) 250 m reflected solar bands aggregated to 500 m resolution 2. Calibrated radiances and uncertainties for (5) 500 m reflected solar bands 3. Geolocation for 1km pixels, that must be interpolated to get 500 m pixel locations. For the relationship of 1km pixels to 500m pixels, see the Geolocation ATBD http://modis.gsfc.nasa.gov/data/atbd/atbd_mod28_v3.pdf . 4. Calibration data for all channels (scale and offset) 5. Comprehensive set of file-level metadata summarizing the spatial, temporal and parameter attributes of the data, as well as auxiliary information pertaining to instrument status and data quality characterization The MODIS L1B 500 m data are stored in the Earth Observing System Hierarchical Data Format (HDF-EOS) which is an extension of HDF as developed by the National Center for Supercomputer Applications (NCSA) at the University of Illinois. A ty
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SIAM 2007 Text Mining Competition dataset
data.nasa.gov | Last Updated 2020-01-29T04:25:03.000Z**Subject Area:** Text Mining **Description:** This is the dataset used for the SIAM 2007 Text Mining competition. This competition focused on developing text mining algorithms for document classification. The documents in question were aviation safety reports that documented one or more problems that occurred during certain flights. The goal was to label the documents with respect to the types of problems that were described. This is a subset of the Aviation Safety Reporting System (ASRS) dataset, which is publicly available. **How Data Was Acquired:** The data for this competition came from human generated reports on incidents that occurred during a flight. **Sample Rates, Parameter Description, and Format:** There is one document per incident. The datasets are in raw text format. All documents for each set will be contained in a single file. Each row in this file corresponds to a single document. The first characters on each line of the file are the document number and a tilde separats the document number from the text itself. **Anomalies/Faults:** This is a document category classification problem.