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At least 109 records · Page 6

NeMO-Net & Fluid Lensing: The Neural Multi-Modal Observation & Training Network for Global Coral Reef Assessment Using Fluid Lensing Augmentation of NASA EOS Data

We present preliminary results from NASA NeMO-Net, the first neural multi-modal observation and training network for global coral reef assessment. NeMO-Net is an open-source deep convolutional neural network (CNN) and interactive active learning training software in development which will assess the present and past dynamics of coral reef ecosystems. NeMO-Net exploits active learning and data fusion of mm-scale remotely sensed 3D images of coral reefs captured using fluid lensing with the NASA FluidCam instrument, presently the highest-resolution remote sensing benthic imaging technology capable of removing ocean wave distortion, as well as hyperspectral airborne remote sensing data from the ongoing NASA CORAL mission and lower-resolution satellite data to determine coral reef ecosystem makeup globally at unprecedented spatial and temporal scales. Aquatic ecosystems, particularly coral reefs, remain quantitatively misrepresented by low-resolution remote sensing as a result of refractive distortion from ocean waves, optical attenuation, and remoteness. Machine learning classification of coral reefs using FluidCam mm-scale 3D data show that present satellite and airborne remote sensing techniques poorly characterize coral reef percent living cover, morphology type, and species breakdown at the mm, cm, and meter scales. Indeed, current global assessments of coral reef cover and morphology classification based on km-scale satellite data alone can suffer from segmentation errors greater than 40%, capable of change detection only on yearly temporal scales and decameter spatial scales, significantly hindering our understanding of patterns and processes in marine biodiversity at a time when these ecosystems are experiencing unprecedented anthropogenic pressures, ocean acidification, and sea surface temperature rise. NeMO-Net leverages our augmented machine learning algorithm that demonstrates data fusion of regional FluidCam (mm, cm-scale) airborne remote sensing with global low-resolution (m, km-scale) airborne and spaceborne imagery to reduce classification errors up to 80% over regional scales. Such technologies can substantially enhance our ability to assess coral reef ecosystems dynamics.

satellite data↗

The near-Earth magnetic field at 1980 determined from MAGSAT data

Data from the MAGSAT spacecraft for November 1979 through April 1980 and from 91 magnetic observatories for 1978 through 1982 are used to derive a spherical harmonic model of the Earth's main magnetic field and its secular variation. Constant coefficients are determined through degree and order 13 and secular variation coefficients through degree and order 10. The first degree external terms and corresponding induced internal terms are given as a function of Dst. Preliminary modeling using separate data sets at dawn and dusk local time showed that the dusk data contains a substantial field contribution from the equatorial electrojet current. The final data set is selected first from dawn data and then augmented by dusk data to achieve a good geographic data distribution for each of three time periods: (1) November/December, 1979; (2) January/February; 1980; (3) March/April, 1980. A correction for the effects of the equatorial electrojet is applied to the dusk data utilized. The solution included calculation of fixed biases, or anomalies, for the observation data.

Langel, R. A.↗

The near-earth magnetic field at 1980 determined from Magsat data

Data from the Magsat spacecraft for November 1979 through April 1980 and from 91 magnetic observatories for 1978 through 1982 are used to derive a spherical harmonic model of the earth's main magnetic field and its secular variation. Constant coefficients are determined through degree and order 13 and secular variation coefficients through degree and order 10. The first degree external terms and corresponding induced internal terms are given as a function of Dst. Preliminary modeling using separate data sets at dawn and dusk local time showed that the dusk data contains a substantial field contribution from the equatorial electrojet current. The final data set is selected first from dawn data and then augmented by dusk data to achieve a good geographic data distribution for each of three time periods: (1) November/December, 1979; (2) January/February, 1980; (3) March/April, 1980. A correction for the effects of the equatorial electrojet is applied to the dusk data utilized. The solution included calculation of fixed biases, or anomalies, for the observation data.

Langel, R. A.↗

A Martian Telecommunications Network: UHF Relay Support of the Mars Exploration Rovers by the Mars Global Surveyor, Mars Odyssey, and Mars Express Orbiters

NASA and ESA have established an international network of Mars orbiters, outfitted with relay communications payloads, to support robotic exploration of the red planet. Starting in January, 2004, this network has provided the Mars Exploration Rovers with telecommunications relay services, significantly increasing rover engineering and science data return while enhancing mission robustness and operability. Augmenting the data return capabilities of their X-band direct-to-Earth links, the rovers are equipped with UHF transceivers allowing data to be relayed at high rate to the Mars Global Surveyor (MGS), Mars Odyssey, and Mars Express orbiters. As of 21 July, 2004, over 50 Gbits of MER data have been obtained, with nearly 95% of that data returned via the MGS and Odyssey UHF relay paths, allowing a large increase in science return from the Martian surface relative to the X-band direct-to-Earth link. The MGS spacecraft also supported high-rate UHF communications of MER engineering telemetry during the critical period of entry, descent, and landing (EDL), augmenting the very low-rate EDL data collected on the X-band direct-to-Earth link. Through adoption of the new CCSDS Proximity-1 Link Protocol, NASA and ESA have achieved interoperability among these Mars assets, as validated by a successful relay demonstration between Spirit and Mars Express, enabling future interagency cross-support and establishing a truly international relay network at Mars.

telecommunications↗

Reinforcement Learning Applied to Cognitive Space Communications

The future of space exploration depends on robust, reliable communication systems. As the number of such communication systems increase, automation is fast becoming a requirement to achieve this goal. A reinforcement learning solution can be employed as a possible automation method for such systems. The goal of this study is to build a reinforcement learning algorithm which optimizes data throughput of a single actor. A training environment was created to simulate a link within the NASA Space Communication and Navigation (SCaN) infrastructure, using state of the art simulation tools developed by the SCaN Center for Engineering, Networks, Integration, and Communications (SCENIC) laboratory at NASA Glenn Research Center to obtain the closest possible representation of the real operating environment. Reinforcement learning was then used to train an agent inside this environment to maximize data throughput. The simulation environment contained a single actor in low earth orbit capable of communicating with twenty-five ground stations that compose the Near-Earth Network (NEN). Initial experiments showed promising training results, so additional complexity was added by augmenting simulation data with link fading profiles obtained from real communication events with the International Space Station. A grid search was performed to find the optimal hyperparameters and model architecture for the agent. Using the results of the grid search, an agent was trained on the augmented training data. Testing shows that the agent performs well inside the training environment and can be used as a foundation for future studies with added complexity and eventually tested in the real space environment.

Schubert, Carson D.↗

Public Health Data Applications Using the CDC Tracking Network: Augmenting Environmental Hazard Information with Lower-latency NASA Data

Exposure to environmental hazards is an important determinant of health, and the frequency and severity of exposures is expected to be impacted by climate change. Through a partnership with the U.S. National Aeronautics and Space Administration, the U.S. Centers for Disease Control and Prevention’s National Environmental Public Health Tracking Network is integrating timely observations and model data of priority environmental hazards into its publicly accessible Data Explorer (https://ephtracking.cdc.gov/DataExplorer/). Newly integrated datasets over the contiguous U.S. (CONUS) include: daily 5-day forecasts of air quality based on the Goddard Earth Observing System Composition Forecast (GEOS-CF), daily historical (1980-present) concentrations of speciated PM2.5 based on the Modern Era Retrospective analysis for Research and Applications, version 2 (MERRA-2), and Moderate Resolution Imaging Spectroradiometer (MODIS) daily near real-time maps of flooding (MCDWD). Data integrated into the CDC Tracking Network are broadly intended to improve community health through action by informing both research and early warning activities, including (1) describing temporal and spatial trends in disease and potential environmental exposures, (2) identifying populations most affected, (3) generating hypotheses about associations between health and environmental exposures, and (4) developing, guiding, and assessing environmental public health policies and interventions aimed at reducing or eliminating health outcomes associated with environmental factors.

air quality↗

Improving GES Disc Data Search and Discovery Through AI Metadata Augmentation

NASA’s Goddard Earth Science (GES) Data and Information Services Center (DISC) is one of twelve data centers in NASA's Science Mission Directorate (SMD), providing vital earth science data to a diverse user base. To enhance the discoverability of this data, GES DISC employs a keyword search system, which leverages scientific keywords embedded in dataset metadata. However, the evolving nature of scientific applications of our data necessitates regular review and augmentation of these keywords. To address this, we developed a service to automatically predict missing science keywords in the metadata. This service constructs a knowledge graph from the latest GES DISC metadata within NASA’s Common Metadata Repository (CMR). Using an open-source library, we trained a machine learning model to predict absent science keywords in the metadata. Our preliminary results indicate that the model has high levels of accuracy at predicting science keywords in the dataset metadata when exposed to data not included in its training. These predicted keywords were then evaluated by GES DISC data curation scientists and compared against other AI tools for metadata augmentation. We aim to enhance the overall usability and accessibility of NASA’s earth science data by implementing this tool in our data curation processes.

Kendall Gilbert↗

The role of FGGE data in the understanding and prediction of atmospheric planetary waves

The augmented observational data base provided by FGGE offers a unique opportunity to improve the understanding and prediction of atmospheric planetary waves. Substantial progress was made, but a number of problems remain. The research on planetary waves conducted thus far with FGGE data is reviewed. Areas of progress are summarized, and some remaining problems are discussed.

Baker, W. E.↗

NASA Center for Climate Simulation (NCCS) Presentation

The NASA Center for Climate Simulation (NCCS) offers integrated supercomputing, visualization, and data interaction technologies to enhance NASA's weather and climate prediction capabilities. It serves hundreds of users at NASA Goddard Space Flight Center, as well as other NASA centers, laboratories, and universities across the US. Over the past year, NCCS has continued expanding its data-centric computing environment to meet the increasingly data-intensive challenges of climate science. We doubled our Discover supercomputer's peak performance to more than 800 teraflops by adding 7,680 Intel Xeon Sandy Bridge processor-cores and most recently 240 Intel Xeon Phi Many Integrated Core (MIG) co-processors. A supercomputing-class analysis system named Dali gives users rapid access to their data on Discover and high-performance software including the Ultra-scale Visualization Climate Data Analysis Tools (UV-CDAT), with interfaces from user desktops and a 17- by 6-foot visualization wall. NCCS also is exploring highly efficient climate data services and management with a new MapReduce/Hadoop cluster while augmenting its data distribution to the science community. Using NCCS resources, NASA completed its modeling contributions to the Intergovernmental Panel on Climate Change (IPCG) Fifth Assessment Report this summer as part of the ongoing Coupled Modellntercomparison Project Phase 5 (CMIP5). Ensembles of simulations run on Discover reached back to the year 1000 to test model accuracy and projected climate change through the year 2300 based on four different scenarios of greenhouse gases, aerosols, and land use. The data resulting from several thousand IPCC/CMIP5 simulations, as well as a variety of other simulation, reanalysis, and observationdatasets, are available to scientists and decision makers through an enhanced NCCS Earth System Grid Federation Gateway. Worldwide downloads have totaled over 110 terabytes of data.

Webster, William P.↗

A moisture analysis procedure utilizing surface and satellite data

Four analyses have been produced by a moisture analysis procedure which uses satellite, precipitation and surface specific humidity data to augment the standard radiosonde observations (RAOB) of moisture: (1) using RAOB data only, (2) using RAOB data supplemented by data obtained from the surface observations of specific humidity, (3) using RAOB data supplemented only by satellite and precipitation data, and (4) employing all sources of data. Penn State University Mesoscale Model forecasts were performed to determine the effect of the high-resolution moisture analyses. For the data set used, supplementary satellite and rainfall data was found to improve the precipitation forecast more than surface humidity data and permitted the model to produce rain rates during the first four hours of the forecast that were 100% larger and more realistic than those produced without these data.

Wolcott, S. W.↗

Oak Ridge National Laboratory EAGLE-I TM : Modeling Electric Utility County Customers for Situational Awareness

During natural hazard events (hurricanes, wildfires, earthquakes, etc.) and recent man-made events (e.g., cyber attacks), the exchange of near real-time, spatially refined data within the response community is critical. The EAGLE-I$^{TM}$ platform is one tool that facilitates this data for decision makers within the energy sector. While much information can be collected and integrated into the system directly, other pertinent data must be augmented by other derived data products to enhance the information and allow for a consistent evaluation of on-the-ground conditions. One such data set that requires the addition of other derived data is the electric utility customer outage data that is aggregated to the county level within the EAGLE-I application. Without a county customer data set, outages can only be compared on total counts, which gives greater importance to higher population outages. Including an electric utility customer data set at the county level allows for these outage counts to be converted to percent outages and brings a consistent classification of outages and equal importance to all outages. To achieve this, several available data sets were combined and spatial disaggregation techniques were employed to model customer estimates at the county scale. This paper presents the approach to produce this data for the United States and lessons learned from working with these disparate data sets. Data validation is provided, where possible, and limitations of the model and possible improvements are discussed.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Performance deterioration based on in-service engine data: JT9D jet engine diagnostics program

Results of analyses of engine performance deterioration trends and levels with respect to service usage are presented. Thirty-two JT9D-7A engines were selected for this purpose. The selection of this engine fleet provided the opportunity of obtaining engine performance data starting before the first flight through initial service such that the trend and levels of engine deterioration related to both short and long term deterioration could be more carefully defined. The performance data collected and analyzed included in-flight, on wing (ground), and test stand prerepair and postrepair performance calibrations with expanded instrumentation where feasible. The results of the analyses of these data were used to: (1) close gaps in previously obtained historical data as well as augment the historical data with more carefully obtained data; (2) refine preliminary models of performance deterioration with respect to usage; (3) establish an understanding of the relationships between ground and altitude performance deterioration trends; (4) refine preliminary recommendations concerning means to reduce and control deterioration; and (5) identify areas where additional effort is required to develop an understanding of complex deterioration issues.

Sallee, G. P.↗

Augmented baroreflex heart rate gain after moderate-intensity, dynamic exercise

The occurrence of a sustained vasodilation and hypotension after acute, dynamic exercise suggests that exercise may alter arterial baroreflex mechanisms. Therefore, we assessed systemic hemodynamics, baroreflex regulation of heart rate, and cardiac vagal tone after 60 min of cycling at 60% peak oxygen consumption in 12 healthy, untrained men and women (ages 21-28 yr). We derived sigmoidal carotid-cardiac baroreflex relations by measurement of R-R interval changes induced by ramped, stepwise, R-wave-triggered changes in external neck pressure from 40 to -65 mmHg. We estimated tonic cardiac vagal control with power spectral analysis of R-R interval variability in the respiratory frequency band (0.2-0.3 Hz) during frequency- and tidal volume-controlled breathing. Both mean arterial pressure and total peripheral resistance were reduced postexercise [pressure: from 86 +/- 2 (mean +/- SE) to 81 +/- 2 mmHg; resistance: from 23 +/- 2 to 16 +/- 1 units; both P < 0.05]. Cardiac output was increased postexercise (from 3.9 +/- 0.3 to 5.5 +/- 0.5 l/min, P < 0.05). Both slope and range of the carotid-cardiac baroreflex relation were increased postexercise (slope: from 4.7 +/- 0.7 to 6.1 +/- 0.9 ms/mmHg; range: from 186 +/- 23 to 238 +/- 30 ms, P < 0.05). Respiratory R-R interval variability (cardiac vagal tone) was not changed at any time after exercise, whereas heart rate and plasma norepinephrine levels were elevated. Thus moderate-intensity, dynamic exercise increases heart rate and cardiac output, reduces peripheral vascular resistance, and augments baroreflex responsiveness. Our data suggest that augmented baroreflex heart rate gain restrains rather than contributes to postexercise hypotension, which appears to be mediated predominately by vasodilation.

NASA Discipline Cardiopulmonary↗

Percussive Augmenter of Rotary Drills (PARoD)

A percussive augmenter is being developed and it is designed to add ultrasonic hammering to a conventional commercial rotary drill through an adapter using a piezoelectric actuator. The combination of ultrasonic hammering and rotation creates a drill that requires low power and low axial load while providing faster penetration than conventional rotary-only drills. These characteristics make percussive augmentation of rotary drills ideal for not only planetary exploration but commercial applications as well. The purpose of this internship was to produce, test, and optimize an augmenter that drives a 2 inch diameter bit. This task was part of the percussive augmenter's phase II of an ongoing contract and it involved increasing the capability of the .25 inch version of the augmenter prototype that was developed in phase I. Due to fabrication delays of the augmenter, an extensive part of the test effort was conducted using previous rotary and hammer drill prototypes. These tests focused on drilling deep over long periods of time to provide for effective stress test of the drill. Modifications were made to the drill, its components, and the testing procedure to achieve desired borehole depths. These results were used to start initial testing on the 2 inch augmenter and provide preliminary data on the augmenter's ability to significantly improve penetration rate over conventional rotary-only drills.

rotraty hammer↗

NASA flight electronics environmental stress screening survey

Data compiled by the Institute of Environmental Sciences were used to establish guidelines for identifying defective, abnormal, or marginal parts as well as manufacturing defects. These data are augmented with other available sources of similar information in conjunction with NASA centers' data and presented in a form that may be useful to all NASA centers in planning and developing effective environmental stress screens. Information relative to thermal and vibration screens as the most effective methods for surfacing latent failures in electronic equipment at the component level is considered.

Marian, E. J.↗

NEAs: Phase Angle Dependence of Asteroid Class and Diameter from Observational Studies

We will discuss the results of a planned observation campaign of Near Earth Asteroids (NEAs), 1999 CU3, 2002 GM2, 2002 FG7, and 3691 Bede with instruments on the United Kingdom Infrared Telescope (UKIRT) from 15-Mar-2015 to 28-April 2015 UT. We will study the phase-angle dependence of the reflectance and thermal emission spectra. Recent publications reveal that the assignment of the asteroid class from visible and near-IR spectroscopy can change with phase angle for NEAs with silicate-bearing minerals on their surfaces (S-class asteroids) (Thomas et al. 2014, Icarus 228, 217; Sanchez et al. 2012 Icarus 220, 36). Only three of the larger NEAs have been measured at a dozen phase angles and the trends are not all the same, so there is not yet enough information to create a phase-angle correction. Also, the phase angle effect is not characterized well for the thermal emission including determination of the albedo and the thermal emission. The few NEAs were selected for our study amongst many possible targets based on being able to observe them through a wide range of phase angles, ranging from less than about 10 degrees to greater than 45 degrees over the constrained date range. The orbits of NEAs often generate short observing windows at phase angles higher than 45 deg (i.e., whizzing by Earth and/or close to dawn or dusk). Ultimately, lowering the uncertainty of the translation of asteroid class to meteorite analog and of albedo and size determinations are amongst our science goals. On a few specific nights, we plan to observe the 0.75-2.5 micron spectra with IRTF+SpeX for comparison with UKIRT data including 5-20 micron with UKIRT+UIST/Michelle to determine as best as possible the albedos. To ensure correct phasing of spectroscopic data, we augment with TRAPPIST-telescope light curves and R-band guider image data. Our observations will contribute to understanding single epoch mid-IR and near-IR measurements to obtain albedo, size and IR beaming parameters (the outcomes of thermal models) and asteroid spectral class.

phase-angle↗