- API
NEW HORIZONS SDC PLUTO CRUISE RAW V2.0
data.nasa.gov | Last Updated 2023-01-26T20:54:05.000ZThis data set contains Raw data taken by the New Horizons Student Dust Counter instrument during the pluto cruise mission phase. This is VERSION 2.0 of this data set. SDC collected science data intermittently during the hibernation years following the Jupiter encounter, designated as the PLUTOCRUISE phase. There were also Annual Checkouts (ACOs), STIM calibrations, Noise calibrations, and an anomaly in November, 2007. SDC's main science data collection periods were during hibernation. During ACOs, science data are taken intermittently but the user must be careful in analyzing these data since there is usually more activity on the spacecraft during hibernation. STIM and Noise refer to scheduled calibrations and are done with a regular cadence of one per year after the Jupiter encounter; they occurred sporadically in the early years of the mission. Note that some SDC data files have the same stop and start time and a zero exposure time. The reason for this is that the start and stop time for SDC data files are the event times for the first and last events in the files, so for files that contain a single event, these two values are the same. The changes in Version 2.0 were re-running of the ancillary data in the data product, updated geometry from newer SPICE kernels, minor editing of the documentation, catalogs, etc., and resolution of liens from the December, 2014 review, plus those from the May, 2016 review of the Pluto Encounter data sets. New observations added with this version (V2.0) include ongoing cruise observations from August, 2014 through January, 2015.
- API
Classification of Aeronautics System Health and Safety Documents
data.nasa.gov | Last Updated 2020-01-29T01:57:57.000ZMost complex aerospace systems have many text reports on safety, maintenance, and associated issues. The Aviation Safety Reporting System (ASRS) spans several decades and contains over 700 000 reports. The Aviation Safety Action Plan (ASAP) contains over 12 000 reports from various airlines. Problem categorizations have been developed for both ASRS and ASAP to enable identification of system problems. However, repository volume and complexity make human analysis difficult. Multiple experts are needed, and they often disagree on classifications. Even the same person has classified the same document differently at different times due to evolving experiences. Consistent classification is necessary to support tracking trends in problem categories over time. A decision support system that performs consistent document classification quickly and over large repositories would be useful. We discuss the results of two algorithms we have developed to classify ASRS and ASAP documents. The first is Mariana---a support vector machine (SVM) with simulated annealing, which is used to optimize hyperparameters for the model. The second method is classification built on top of nonnegative matrix factorization (NMF), which attempts to find a model that represents document features that add up in various combinations to form documents. We tested both methods on ASRS and ASAP documents with the latter categorized two different ways. We illustrate the potential of NMF to provide document features that are interpretable and indicative of topics. We also briefly discuss the tool that we have incorporated Mariana into in order to allow human experts to provide feedback on the document categorizations.
- API
Metrics for Evaluating Performance of Prognostic Techniques
data.nasa.gov | Last Updated 2020-01-29T03:23:28.000ZPrognostics is an emerging concept in condition basedmaintenance(CBM)ofcriticalsystems.Alongwith developing the fundamentals of being able to confidently predict Remaining Useful Life (RUL), the technology calls for fielded applications as it inches towards maturation. This requires a stringent performance evaluation so that the significance of the concept can be fully exploited. Currently, prognostics concepts lack standard definitions and suffer from ambiguous and inconsistent interpretations. This lack of standards is in part due to the varied end-user requirements for different applications, time scales, available information, domain dynamics, etc. to name a few issues. Instead, the research community has used a variety of metrics based largely on convenience with respect to their respective requirements. Very little attention has been focused on establishing a common ground to compare different efforts. This paper surveys the metrics that are already used for prognostics in a variety of domains including medicine, nuclear, automotive, aerospace, and electronics. It also considers other domains that involve prediction-related tasks, such as weather and finance. Differences and similarities between these domains and health maintenancehave been analyzed to help understand what performance evaluation methods may or may not be borrowed. Further, these metrics have been categorized in several ways that may be useful in deciding upon a suitable subset for a specific application. Some important prognostic concepts have been defined using a notational framework that enables interpretation of different metrics coherently. Last, but not the least, a list of metrics has been suggested to assess critical aspects of RUL predictions before they are fielded in real applications.
- API
NEW HORIZONS SDC PLUTO CRUISE CALIBRATED V2.0
data.nasa.gov | Last Updated 2023-01-26T20:25:34.000ZThis data set contains Calibrated data taken by the New Horizons Student Dust Counter instrument during the pluto cruise mission phase. This is VERSION 2.0 of this data set. SDC collected science data intermittently during the hibernation years following the Jupiter encounter, designated as the PLUTOCRUISE phase. There were also Annual Checkouts (ACOs), STIM calibrations, Noise calibrations, and an anomaly in November, 2007. SDC's main science data collection periods were during hibernation. During ACOs, science data are taken intermittently but the user must be careful in analyzing these data since there is usually more activity on the spacecraft during hibernation. STIM and Noise refer to scheduled calibrations and are done with a regular cadence of one per year after the Jupiter encounter; they occurred sporadically in the early years of the mission. Note that some SDC data files have the same stop and start time and a zero exposure time. The reason for this is that the start and stop time for SDC data files are the event times for the first and last events in the files, so for files that contain a single event, these two values are the same. The changes in Version 2.0 were re-running of the ancillary data in the data product, updated geometry from newer SPICE kernels, minor editing of the documentation, catalogs, etc., and resolution of liens from the December, 2014 review, plus those from the May, 2016 review of the Pluto Encounter data sets. New observations added with this version (V2.0) include ongoing cruise observations from August, 2014 through January, 2015.
- API
CORONA Satellite Photographs from the U.S. Geological Survey
data.nasa.gov | Last Updated 2022-01-17T05:16:00.000ZThe first generation of U.S. photo intelligence satellites collected more than 860,000 images of the Earth’s surface between 1960 and 1972. The classified military satellite systems code-named CORONA, ARGON, and LANYARD acquired photographic images from space and returned the film to Earth for processing and analysis. The images were originally used for reconnaissance and to produce maps for U.S. intelligence agencies. In 1992, an Environmental Task Force evaluated the application of early satellite data for environmental studies. Since the CORONA, ARGON, and LANYARD data were no longer critical to national security and could be of historical value for global change research, the images were declassified by Executive Order 12951 in 1995. The first successful CORONA mission was launched from Vandenberg Air Force Base in 1960. The satellite acquired photographs with a telescopic camera system and loaded the exposed film into recovery capsules. The capsules or buckets were de-orbited and retrieved by aircraft while the capsules parachuted to earth. The exposed film was developed and the images were analyzed for a range of military applications. The intelligence community used Keyhole (KH) designators to describe system characteristics and accomplishments. The CORONA systems were designated KH-1, KH-2, KH-3, KH-4, KH-4A, and KH-4B. The ARGON systems used the designator KH-5 and the LANYARD systems used KH-6. Mission numbers were a means for indexing the imagery and associated collateral data. A variety of camera systems were used with the satellites. Early systems (KH-1, KH-2, KH-3, and KH-6) carried a single panoramic camera or a single frame camera (KH-5). The later systems (KH-4, KH-4A, and KH-4B) carried two panoramic cameras with a separation angle of 30° with one camera looking forward and the other looking aft. The original film and technical mission-related documents are maintained by the National Archives and Records Administration (NARA). Duplicate film sources held in the USGS EROS Center archive are used to produce digital copies of the imagery. Mathematical calculations based on camera operation and satellite path were used to approximate image coordinates. Since the accuracy of the coordinates varies according to the precision of information used for the derivation, users should inspect the preview image to verify that the area of interest is contained in the selected frame. Users should also note that the images have not been georeferenced.
- API
Metrics for Offline Evaluation of Prognostic Performance
data.nasa.gov | Last Updated 2020-01-29T01:57:42.000ZPrognostic performance evaluation has gained significant attention in the past few years.*Currently, prognostics concepts lack standard definitions and suffer from ambiguous and inconsistent interpretations. This lack of standards is in part due to the varied end- user requirements for different applications, time scales, available information, domain dynamics, etc. to name a few. The research community has used a variety of metrics largely based on convenience and their respective requirements. Very little attention has been focused on establishing a standardized approach to compare different efforts. This paper presents several new evaluation metrics tailored for prognostics that were recently introduced and were shown to effectively evaluate various algorithms as compared to other conventional metrics. Specifically, this paper presents a detailed discussion on how these metrics should be interpreted and used. These metrics have the capability of incorporating probabilistic uncertainty estimates from prognostic algorithms. In addition to quantitative assessment they also offer a comprehensive visual perspective that can be used in designing the prognostic system. Several methods are suggested to customize these metrics for different applications. Guidelines are provided to help choose one method over another based on distribution characteristics. Various issues faced by prognostics and its performance evaluation are discussed followed by a formal notational framework to help standardize subsequent developments.
- API
Probabilistic Model-Based Diagnosis for Electrical Power Systems
data.nasa.gov | Last Updated 2020-01-29T02:07:39.000ZWe present in this article a case study of the probabilistic approach to model-based diagnosis. Here, the diagnosed system is a real-world electrical power system, namely the Advanced Diagnostic and Prognostic Testbed (ADAPT) located at the NASA Ames Research Center. Our probabilistic approach is formally well-founded, and based on Bayesian networks and arithmetic circuits. We pay special attention to meeting two of the main challenges model development and real-time reasoning often associated with real-world application of model-based diagnosis technologies. To address the challenge of model development, we develop a systematic approach to representing electrical power systems as Bayesian networks, supported by an easy-touse specication language. To address the real-time reasoning challenge, we compile Bayesian networks into arithmetic circuits. Arithmetic circuit evaluation supports real-time diagnosis by being predictable and fast. In experiments with the ADAPT Bayesian network, which contains 503 discrete nodes and 579 edges and produces accurate results, the time taken to compute the most probable explanation using arithmetic circuits has a mean of 0.2625 milliseconds and a standard deviation of 0.2028 milliseconds. In comparative experiments, we found that while the variable elimination and join tree propagation algorithms also perform very well in the ADAPT setting, arithmetic circuit evaluation was an order of magnitude or more faster. **Reference:** O. J. Mengshoel, M. Chavira, K. Cascio, S. Poll, A. Darwiche, and S. Uckun. "Probabilistic Model-Based Diagnosis: An Electrical Power System Case Study”. Accepted to IEEE Transactions on Systems, Man, and Cybernetics, Part A, 2009.
- API
MISR Level 3 FIRSTLOOK Global Land product in netCDF format covering a day V002
data.nasa.gov | Last Updated 2023-01-19T22:32:40.000ZThis file contains the MISR Level 3 FIRSTLOOK Component Global Land product in netCDF format covering a day
- API
Metagenomic analysis of feces from mice flown on the RR-6 mission
data.nasa.gov | Last Updated 2023-01-26T18:46:14.000ZThe objective of the Rodent Research-6 (RR-6) study was to evaluate muscle atrophy in mice during spaceflight and to test the efficacy of a novel therapeutic to mitigate muscle wasting. The experiment involved an implantable subcutaneous nanochannel delivery system (nDS; between scapula) which delivered the drug formoterol (FMT; a selective xce xb22 adrenoceptor agonist) over the course of time. To this end a cohort of forty 32-weeks-old female C57BL/6NTac mice were either sham operated or implanted with vehicle or treatment-filled nDS launched in two Transporters (20 mice per Transporter) on SpaceX-13 on December 15 2017. They were transferred to Rodent Habitats onboard the International Space Station (ISS) and maintained in microgravity for 29 days (N=20 Live Animal Return Spaceflight [LAR FLT]) or >50 days (N=20 ISS Terminal Spaceflight [ISS-T FLT]). After 29 days the 20 LAR FLT animals were returned live to back to Earth on January 13 2018. After splashdown the animals were ambulatory on-ground for ~4 days until all subjects were processed during one day of dissections. There were two Basal (BSL) groups of animals sacrificed (LAR BSL & ISS-T BSL; N=20; 40 animals; ~36 weeks old) at Kennedy Space Center (KSC; 12/9/17). LAR BSL animals were dissected and samples were collected upon euthanasia. A Ground Control (GC) group LAR GC mimicked the LAR FLT group which was housed at KSC then shipped alive to Novartis xe2 x80 x99s Facilities where both the LAR FLT and LAR GC groups were processed (~41 weeks old; 1/16/18). All were anesthetized with isoflurane blood samples were obtained by closed-chest cardiac puncture and the animals were euthanized by exsanguination and thoracotomy. The 20 ISS-T FLT mice were anesthetized via intraperitoneal injection of ketamine/xylazine/acepromazine over the course of a four days of dissections (2/6/18 until 2/9/18; 53-56 days after launch; 44 weeks old at time of on-orbit dissections). Blood samples and euthanasia were conducted the same as LAR groups. Following blood draw and hind limb dissection the ISS-T FLT animal carcasses were wrapped in aluminum foil placed in a ziploc bag and placed in storage at -80 xcb x9aC or colder until return. The ISS-T Ground Control (ISS-T GC) (at KSC) followed the same euthanasia timeline methods and preservation. The final processing of frozen ISS-T FLT frozen ISS-T GC and frozen 0-day ISS-T BSL animals were completed at Houston Methodist Research Institute in Houston TX (5/21/18 until 5/24/18). GeneLab received feces from only sham treated animals (no drug treated animals) from the following groups. FLT: LAR (n=9) ISS-T (n=7); GC: LAR (N=7) ISS-T (N=9); BSL: LAR (n=7) ISS-T (n=9). DNA was extracted and analyzed by sequencing using a variety of different targeted and un-targeted metagenome profiling assays.
- API
Transcriptional analysis of dorsal skin from mice flown on the RR-6 mission
data.nasa.gov | Last Updated 2023-01-26T18:45:51.000ZThe objective of the Rodent Research-6 (RR-6) study was to evaluate muscle atrophy in mice during spaceflight and to test the efficacy of a novel therapeutic to mitigate muscle wasting. The experiment involved an implantable subcutaneous nanochannel delivery system (nDS; between scapula) which delivered the drug formoterol (FMT; a selective Beta-2 adrenoceptor agonist) over the course of time. To this end a cohort of forty 32-weeks-old female C57BL/6NTac mice were either sham operated. or implanted with vehicle or treatment-filled nDS and launched in two Transporters (20 mice per Transporter) on SpaceX-13 on December 15 2017. They were transferred to Rodent Habitats onboard the International Space Station (ISS) and maintained in microgravity for 29 days (N=20 Live Animal Return [LAR]) or >50 days (N=20 ISS Terminal). After 29 days the 20 LAR animals were returned live to back to Earth on January 13 2018. After splashdown the animals were ambulatory on-ground for ~4 days until all subjects were processed during one day of dissections. There were two Baseline groups of animals sacrificed (LAR Baseline & FLT Baseline; N=20; 40 animals; ~36 weeks old) at Kennedy Space Center (KSC; 12/9/17). A Ground Control group mimicked the Flight LAR group which was housed at KSC then shipped alive to Novartis facilities where both the LAR and LAR Ground Control groups were processed (~41 weeks old; 1/16/18). All were anesthetized with isoflurane blood samples were obtained by closed-chest cardiac puncture and the animals were euthanized by exsanguination and thoracotomy. The 20 ISS Terminal mice were anesthetized via intraperitoneal injection of ketamine/xylazine/acepromazine over the course of a four days of dissections (2/6/18 until 2/9/18; 53-56 days after launch; 44 weeks old at time of on-orbit dissections). Blood samples and euthanasia were conducted the same as LAR and Baseline. Following blood draw and hind limb dissection the ISS-terminal animal carcasses were wrapped in aluminum foil placed in a ziploc bag and placed in storage at -80C or colder until return. The ISS-terminal Ground Controls (at KSC) followed the same euthanasia timeline methods and preservation. The final processing of frozen ISS-terminal frozen ISS-terminal Ground Controls and frozen 0-day FLT baseline animals were completed at Houston Methodist Research Institute in Houston TX (5/21/18 until 5/24/18). GeneLab received samples of dorsal skin from only sham treated animals (no drug treated animals) from the following groups Flight: LAR (n=9) ISS Terminal (n=9); Ground Controls: LAR GC (N=9) ISS Terminal GC (N=10) LAR Baseline (n=10) ISS Terminal Baseline (n=6). Total RNA was extracted and sequenced at a target depth of 60 M clusters per sample (ribodepleted paired end 150).