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At least 721 records · Page 40
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NASA NTRS2021

Knowledge Network Embedding of Transcriptomic Data From Spaceflown Mice Uncovers Signs and Symptoms Associated With Terrestrial Diseases

There has long been an interest in understanding how the hazards from spaceflight may trigger or exacerbate human diseases. With the goal of advancing our knowledge on physiological changes during space travel, NASA GeneLab provides an open-source repository of multi-omics data from real and simulated spaceflight studies. Alone, this data enables identification of biological changes during spaceflight, but cannot infer how that may impact an astronaut at the phenotypic level. To bridge this gap, SPOKE, a heterogeneous knowledge graph connecting biological and clinical data from over 30 databases, was used in combination with GeneLab transcriptomic data from six studies. This integration identified critical symptoms and physiological changes incurred during spaceflight.

spaceflight↗
NASA NTRS1992

Comparison of Kalman filter estimates of zenith atmospheric path delays using the global positioning system and very long baseline interferometry

Kalman filter estimates of zenith nondispersive atmospheric path delays at Westford, Massachusetts, Fort Davis, Texas, and Mojave, California, were obtained from independent analyses of data collected during January and February 1988 using the GPS and VLBI. The apparent accuracy of the path delays is inferred by examining the estimates and covariances from both sets of data. The ability of the geodetic data to resolve zenith path delay fluctuations is determined by comparing further the GPS Kalman filter estimates with corresponding wet path delays derived from water vapor radiometric data available at Mojave over two 8-hour data spans within the comparison period. GPS and VLBI zenith path delay estimates agree well within one standard deviation formal uncertainties (from 10-20 mm for GPS and 3-15 mm for VLBI) in four out of the five possible comparisons, with maximum differences of 5 and 21 mm over 8- to 12-hour data spans.

Tralli, David M.↗
NASA NTRS1980

Atmospheric variability and air-sea interaction

The topics studied include: (1) processing of Northern Hemispheric precipitation data, in order to fill in the transition seasons to provide a continuous 40 year data base on the variability of continental precipitation; (2) comparison of seasonally averaged fields of sea surface temperature obtained from ship observations in the North Atlantic and North Pacific in 1970 with the corresponding fields inferred from satellite observations; (3) estimation of seasonal average of total precipitable water at those admittedly few oceanic stations where repeated vertical soundings were made in 1970 and comparison with corresponding values inferred from satellite measurements; (4) comparison of seasonally averaged evaporation fields determined from ground based observations in 1970 with the field of divergence of the seasonal total horizontal water vapor flux inferred from satellite total water measurements and NMC wind data for the lower troposphere; (5) examination of meaning of convection-inversion index.

Middleton, J. W.↗
NASA NTRS1994

How well was total ozone abundance inferred with Mariner 9?

Ozone is a key to understanding atmospheric chemistry on Mars. Over 20 photochemical models of the martian atmosphere have been published, and O3 is often used as a benchmark for these models. O3 abundance has been inferred from instrumentation on several spacecraft, with the most complete coverage provided by Mariner 9. The Mariner 9 UV spectrometer scanned from 2100 to 3500 Angstroms with a spectral resolution of 15 Angstroms and an effective field-of-view of approximately 300 sq km. The only atmospheric absorption in the 2000 to 3000 A wavelength region was previously assumed to come from the Hartley band system of ozone, which has an opacity of order unity at winter polar latitudes. Therefore, the amount of ozone was inferred by fitting this absorption feature with laboratory data of ozone absorption. Mars O3 shows strong seasonal and latitudinal variation, with column abundances ranging from 0.2 micron-atm at equatorial latitudes to 60 micron-atm over northern winter polar latitudes (1 micron-atm is a column abundance of 2.689 x 10 exp 15 molecules cm(exp -2)). However, the O3 abundance is never great enough to significantly affect atmospheric temperatures or surface temperatures and frost amounts. Some of the previously-inferred O3 abundances are shown. A radiative transfer computer model is used to re-examine the Mariner 9 UV spectra. Assuming a constant mixing ratio for O3 and no chemical or radiative interaction between O3 and clouds/dust, it is shown that when typical amounts of dust and cloud are present that significant underestimation of O3 abundance occurs. A factor of 3 times as much O3 is needed to generate the same spectrum the spacecraft would measure for a cloudy, dusty atmosphere as for a clear atmosphere. If the scattering properties of martian clouds and dust were well known, then their appearance would not be a problem, as a model would be capable of retrieving the O3 abundance. However, these properties are not well known, which raises doubts about the effectiveness of the UV reflectance spectroscopy technique for measuring O3 abundance on Mars.

Lindner, Bernhard Lee↗
NASA NTRS1989

GPS-based system for satellite tracking and geodesy

High-performance receivers and data processing systems developed for GPS are reviewed. The GPS Inferred Positioning System (GIPSY) and the Orbiter Analysis and Simulation Software (OASIS) are described. The OASIS software is used to assess GPS system performance using GIPSY for data processing. Consideration is given to parameter estimation for multiday arcs, orbit repeatability, orbit prediction, daily baseline repeatability, agreement with VLBI, and ambiguity resolution. Also, the dual-frequency Rogue receiver, which can track up to eight GPS satellites simultaneously, is discussed.

Bertiger, Willy I.↗
NASA NTRS2018

Spatially-Explicit Monitoring of Crop Photosynthetic Capacity Through the Use of Space-Based Chlorophyll Fluorescence Data

Plant functional traits such as photosynthetic capacity are critical parameters for terrestrial biosphere models. However, their spatial and temporal characteristics are still poorly represented. In this study, we used satellite observations of sun-induced fluorescence (SIF) to estimate top-of-canopy photosynthetic capacity (maximum carboxylation rate, V(sub cmax) at a reference temperature of 25 deg C) for crops, which was in turn utilized to simulate regional gross primary production (GPP). We first estimate the key parameter, V(sub cmax), in the widely-used FvCB photosynthesis model using field measurements of CO2 and water fluxes during 2007-2012 at seven crop eddy covariance flux sites over the US Corn Belt. The results showed that satellite far-red SIF retrievals have a stronger link to V(sub cmax) at the seasonal scale (R(squared)=0.70 for C4 and R(squared)=0.63 for C3 crop) as compared with widely-used vegetation indices. We calibrate an empirical model linking V(sub cmax) with SIF that was used to estimate spatially and temporally varying crop V(sub cmax) for the US Corn Belt region. The resulting V(sub cmax) maps are used together with meteorological data from MERRA reanalysis data and vegetation structural parameters derived from the satellite- based spectral reflectance data to constrain the Soil-Canopy Observation of Photosynthesis and Energy (SCOPE) balance model in order to estimate regional crop GPP. Our results show a substantial improvement in the seasonal and spatial patterns of cropland GPP when compared with crop yield inventory data. The evaluation with tall tower atmospheric CO2 measurements further supports our estimation of spatiotemporal V(sub cmax) from space-borne SIF. Considering that SIF has a direct link to photosynthetic activity, our findings highlight the potential to infer regional V(sub cmax) using remotely sensed SIF data and to use this information for a better quantification of regional cropland carbon cycles.

Drought↗
NASA NTRS1992

An expert system shell for inferring vegetation characteristics: The learning system (tasks C and D)

This report describes the implementation of a learning system that uses a data base of historical cover type reflectance data taken at different solar zenith angles and wavelengths to learn class descriptions of classes of cover types. It has been integrated with the VEG system and requires that the VEG system be loaded to operate. VEG is the NASA VEGetation workbench - an expert system for inferring vegetation characteristics from reflectance data. The learning system provides three basic options. Using option one, the system learns class descriptions of one or more classes. Using option two, the system learns class descriptions of one or more classes and then uses the learned classes to classify an unknown sample. Using option three, the user can test the system's classification performance. The learning system can also be run in an automatic mode. In this mode, options two and three are executed on each sample from an input file. The system was developed using KEE. It is menu driven and contains a sophisticated window and mouse driven interface which guides the user through various computations. Input and output file management and data formatting facilities are also provided.

Harrison, P. Ann↗
NASA NTRS1999

Comment on "The Predicted Size of Cycle 23 Based on the Inferred three-cycle Quasiperiodicity of the Planetary Index Ap"

Recently, Ahluwalia reviewed the solar and geomagnetic data for the last 6 decades and remarked that these data "indicate the existence of a three-solar-activity-cycle quasiperiodicity in them." Furthermore, on the basis of this inferred quasiperiodicity, he asserted that cycle 23 represents the initial cycle in a new three-cycle string, implying that it "will be more modest (a la cycle 17) with an annual mean sunspot number count of 119.3 +/- 30 at the maximum", a prediction that is considerably below the consensus prediction of 160 +/- 30 by Joselin et al. and of similar predictions by others based on a variety of predictive techniques. Several major sticking points of Ahluwalia's presentation, however, must be readdressed, and these issues form the basis of this comment. First, Ahluwalia appears to have based his analysis on a data set of Ap index values that is erroneous. For example, he depicts for the interval of 1932-1997 the variation of the Ap index in terms of annual averages, contrasting them against annual averages of sunspot number (SSN), and he lists for cycles 17-23 the minimum and maximum value of each, as well as the years in which they occur and a quantity which he calls "Amplitude" (defined as the numeric difference between the maximum and minimum values). In particular, he identifies the minimum Ap index (i.e., the minimum value of the Ap index in the vicinity of sunspot cycle minimum, which usually occurs in the year following sunspot minimum and which will be called hereafter, simply, Ap min) and the year in which it occur for cycles 17 - 23 respectively.

Wilson, Robert M.↗
NASA NTRSDate not supplied

Onboard Hyperspectral Image Classification via Transfer Learning for Communication-Limited Spacecraft

Employing deep-learning and artificial-intelligence (AI) techniques onboard spacecraft can dramatically improve priority data selection to ensure more effective use of the available downlink. However, deployment of effective deep-learning models requires significant training on the ground, which may not be feasible, due to limited data available in an unexplored environment. Therefore, this research explores building robust classification models for onboard data processing where training data is highly limited using transfer-learning techniques. In this paper, we focus on the use case of hyperspectral imaging for remote sensing, a domain where the high dimensionality of the data from the sensor can rapidly saturate the downlink bandwidth. With this bottleneck, there is an impending need to autonomously and robustly classify data onboard to optimize downlink of high-impact measurements, thus maximizing the scientific utility per bit transmitted to the ground. This paper examines the use of deep neural networks onboard for hyperspectral image classification in a communication-limited scenario to analyze how the models perform with limited training data. The use of transfer learning can ameliorate the issue of poor generalization by transferring features learned from training on a large source dataset for one classification task to the target classification task with limited training data. For two deep-learning models from literature, we compare the accuracy of the models trained using transfer learning to models trained from scratch using a random weight initialization with varying amounts of training data. We demonstrate the feasibility and performance of running inference of the deep-learning models on representative flight-like hardware.

Advanced Avionics, Machine Learning, Data Processi↗
NASA NTRS1983

Computation of Jupiter interior models from gravitational inversion theory

Spacecraft measurements of Jupiter have provided the mass, standard pressure level radius, rotation law, internal mass distribution multipole moments, and internal composition and temperature distribution constraints, for the present implementation of a method for deriving planetary interior models that exactly satisfy a set of N gravitational constraints by means of appropriate iteration. The models are not forced to fit the more indirectly derived constraints, which are instead used as conistency checks. In the case of an He mass fraction in the envelope Y of 0.2, the inferred pressure at a mass density of about 0.2 g/cu cm is about a factor of 2 higher than would be indicated by experimental H compression data in the relevant pressure range of 100,000 to one million bar. The inferred pressure distribution is in better agreement with the shock data for a nominal Y value of 0.3 + or - 0.05.

Hubbard, W. B.↗
NASA NTRS1992

Evaluation of fuzzy inference systems using fuzzy least squares

Efforts to develop evaluation methods for fuzzy inference systems which are not based on crisp, quantitative data or processes (i.e., where the phenomenon the system is built to describe or control is inherently fuzzy) are just beginning. This paper suggests that the method of fuzzy least squares can be used to perform such evaluations. Regressing the desired outputs onto the inferred outputs can provide both global and local measures of success. The global measures have some value in an absolute sense, but they are particularly useful when competing solutions (e.g., different numbers of rules, different fuzzy input partitions) are being compared. The local measure described here can be used to identify specific areas of poor fit where special measures (e.g., the use of emphatic or suppressive rules) can be applied. Several examples are discussed which illustrate the applicability of the method as an evaluation tool.

Barone, Joseph M.↗
NASA NTRS2024

Evaluation of Vertical Patterns in Chlorophyll-A Derived From A Data Assimilating Model of Satellite-Based Ocean Color

Satellite-based sensors of ocean color have become the primary tool to infer changes in surface chlorophyll, while BGC-Argo floats are now filling the information gap at depth. Here we use BGC-Argo data to assess depth-resolved information on chlorophyll-a derived from an ocean biogeochemical model constrained by the assimilation of surface ocean color remote sensing. The data-assimilating model replicates well the general seasonality and meridional gradients in surface and depth-resolved chlorophyll-a inferred from the float array in the Southern Ocean. On average, the model tends to overestimate float-based chlorophyll, particularly at times and locations of high productivity such as the beginning of the spring bloom, subtropical deep chlorophyll maxima, and non-iron limited regions of the Southern Ocean. The highest model RMSE in the upper 50 m with respect to the float array is of 0.6 mg Chl m −3 , which should allow the detection of seasonal changes in float-based biomass (varying between 0.01 and >1 mg Chl m −3 ) but might hinder the identification of subtle changes in chlorophyll at narrow local scales. Both model and float profiling data show good agreement with in situ data from station ALOHA, with model estimates showing a slight accuracy edge in inferring depth-resolved observations. Uncertainties in float bio-optical estimates impede their use as a reliable benchmark for validation, but the general qualitative agreement between model and float data provides confidence in the ability of model to replicate biogeochemical features below the surface, where data is not directly constrained by the assimilation of satellite ocean color.

Lionel A Quintero↗
NASA NTRS1988

Geodetic measurement of deformation in California

The very long baseline interferometry (VLBI) measurements made in the western U.S. since 1979 as part of the NASA Crustal Dynamics Project provide discrete samples of the temporal and spatial deformation field. The interpretation of the VLBI-derived rates of deformation requires an examination of geologic information and more densely sampled ground-based geodetic data. In the first two of three related studies embodying this thesis triangulation and trilateration data measured on two regional networks are processed, one in the central Mojave Desert and one in the Coast Ranges east of the San Andreas fault. At the spatial scales spanned by these local geodetic networks, auxiliary geologic and geophysical data have been utilized to examine the relation between measured incremental strain and the accommodation of strain seen in local geological structures, strain release in earthquakes, and principal stress directions inferred from in situ measurements. In the third study, VLBI data from stations distributed across the Pacific - North American plate boundary zone in the western United States are processed. The VLBI data have been used to constrain the integrated rate of deformation across portions of the continental plate boundary in California and to provide a tectonic framework to interpret regional geodetic and geologic studies.

Sauber, Jeanne Marie↗
NASA NTRS2007

Comparisons of Instantaneous TRMM Ground Validation and Satellite Rain Rate Estimates at Different Spatial Scales

This study provides a comprehensive inter-comparison of instantaneous rain estimates from the two rain sensors aboard the TRMM satellite with ground data from thee designated Ground Validation Sites: Kwajalein Atoll, Melbourne, Florida and Houston, Texas. The satellite rain retrievals utilize rain observations collected by the TRMM microwave imager (TMI) and the Precipitation Radar (PR) aboard the TRMM satellite. Three standard instantaneous rain products are the generated from the rain information retrieved from the satellite using the TMI, PR and Combined (COM) rain algorithms. The validation data set used in this study was obtained from instantaneous rain rates inferred from ground radars at each GV site. The first comparison used 0.5(sup 0) x 0.5(sup 0) gridded data obtained from the TRMM 3668 product, and similarly gridded GV data obtained from ground-based radars. The comparisons were made at the same spatial and temporal scales in order to eliminate sampling biases in our comparisons. An additional comparison was made by averaging rain rates for the PR, COM and GV estimates within each TMI footprint (approx. 150 square kilometers). For this analysis, unconditional mean rain rates from PR, COM and GV estimates were calculated within each TMI footprint that was observed within 100 km from the respective GV site (and also observed by the PR). This analysis used all the available matching data from the period 1999-2004, representing a sample size of over 50,000 footprints for each site. In the first analysis our results showed that all of the respective rain rate estimates agree well, with some exceptions. The more salient differences were associated with heavy rain events in which one or more of the algorithms failed to properly retrieve these extreme events. Also, it appears that there is a preferred mode of precipitation for TMI rain rates at or near 2 mm per hour over the ocean. This mode was noted over ocean areas of Melbourne, Florida and Kwajalein, Republic of the Marshall Islands, and is shown to exist in TRMM tropical-global ocean areas as well. Further research by algorithm developers is needed to explain or justify the seemingly errant observed probability distributions.

Wolff, David B.↗
NASA NTRS1994

Software for Data Analysis with Graphical Models

Probabilistic graphical models are being used widely in artificial intelligence and statistics, for instance, in diagnosis and expert systems, as a framework for representing and reasoning with probabilities and independencies. They come with corresponding algorithms for performing statistical inference. This offers a unifying framework for prototyping and/or generating data analysis algorithms from graphical specifications. This paper illustrates the framework with an example and then presents some basic techniques for the task: problem decomposition and the calculation of exact Bayes factors. Other tools already developed, such as automatic differentiation, Gibbs sampling, and use of the EM algorithm, make this a broad basis for the generation of data analysis software.

Buntine, Wray L.↗
NASA NTRS1979

TWT design requirements for 30/20 GHz digital communications' satellite

The rapid growth of communication traffic (voice, data, and video) requires the development of additional frequency bands before the 1990's. The frequencies currently in use for satellite communications at 6/4 GHz are crowded and demands for 14/12 GHz systems are increasing. Projections are that these bands will be filled to capacity by the late 1980's. The next higher frequency band allocated for satellite communications is at 30/20 GHz. For interrelated reasons of efficiency, power level, and system reliability criteria, a candidate for the downlink amplifier in a 30/20 GHz communications' satellite is a dual mode traveling wave tube (TWT) equipped with a highly efficient depressed collector. A summary is given of the analyses which determine the TWT design requirements. The overall efficiency of such a tube is then inferred from a parametric study and from experimental data on multistaged depressed collectors. The expected TWT efficiency at 4 dB below output saturation is 24 percent in the high mode and 22 percent in the low mode.

Stankiewicz, N.↗
NASA NTRS2020

The Atacama Cosmology Telescope: DR4 maps and cosmological parameters

We present new arcminute-resolution maps of the Cosmic Microwave Background temperature and polarization anisotropy from the Atacama Cosmology Telescope, using data taken from 2013{2016 at 98 and 150 GHz. The maps cover more than 17,000 deg(^2), the deepest 600 deg(^2) with noise levels below 10µK-arcmin. We use the power spectrum derived from almost 6,000 deg(^2) of these maps to constrain cosmology. The ACT data enable a measurement of the angular scale of features in both the divergence-like polarization and the temperature anisotropy, tracing both the velocity and density at last-scattering. From these one can derive the distance to the last-scattering surface and thus infer the local expansion rate, H0. By combining ACT data with large-scale information from WMAP we measure H0 = 67:6±1:1 km/s/Mpc, at 68% confidence, in excellent agreement with the independently measured Planck satellite estimate (from ACT alone we find H0 = 67:9± 1:5 km/s/Mpc). The ΛCDM model provides a good fit to the ACT data, and we find no evidence for deviations: both the spatial curvature, and the departure from the standard lensing signal in the spectrum, are zero to within 1σ; the number of relativistic species, the primordial Helium fraction, and the running of the spectral index are consistent with ΛCDM predictions to within 1.5{2.2σ. We compare ACT, WMAP, and Planck at the parameter level and find good consistency; we investigate how the constraints on the correlated spectral index and baryon density parameters readjust when adding CMB large-scale information that ACT does not measure. The DR4 products presented here will be publicly released on the NASA Legacy Archive for Microwave Background Data Analysis.

Simone Aiola↗
NASA NTRS1993

Spectral emissivity of cirrus clouds

The inference of cirrus cloud properties has many important applications including global climate studies, radiation budget determination, remote sensing techniques and oceanic studies from satellites. Data taken at the Parsons Kansas site during the FIRE II project are used for this study. On November 26 there were initially clear sky conditions gradually giving way to a progressively thickening cirrus shield over a period of a few hours. Interferometer radiosonde and lidar data were taken throughout this event. Two techniques are used to infer the downward spectral emittance of the observed cirrus layer. One uses only measurements and the other involves measurements and FASCODE III calculations. FASCODE III is a line-by line radiance/transmittance model developed at the Air Force Geophysics Laboratory.

Beck, Gordon H.↗