Search NASA⌕ Search

SEARCH · Search NASA

Results for “Data Inference”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Nitrogen isotopic compositions of iron meteorites

Iron meteorites analyzed in this study have nitrogen concentrations 70 microg/g or less and delta N-15 from -90 to +150 percent. Although the iron meteorites have a large range of delta N-15, most have values more negative than -50 percent. The nitrogen isotopic compositions were established by cosmochemical processes and were little modified by fractional crystallization or other chemical processes within the parent bodies. The data do not suggest the existence of a well-mixed solar nebular reservoir for nitrogen, as was already inferred from data from stony meteorites. The range of greater than 1100 percent observed for delta N-15 in bulk meteorites is probably too large to be accounted for by physical and chemical mass-dependent fractionation processes in the solar nebula, and thus reflects nebular inhomogeneities of nucleosynthetic origin.

Prombo, Carol A.↗
NASA NTRS2011

Use of Remote Sensing/Geographical Information Systems (RS/GIS) to Identify the Distributional Limits of Soil-Transmitted Helminths (STHs) and Their Association to Prevalence of Intestinal Infection in School-Age Children in Four Rural Communities in Boaco, Nicaragua

STHs can infect all members of a population but school-age children living in poverty are at greater risk. Infection can be controlled with drug treatment, health education and sanitation. Helminth control programs often lack resources and reliable information to identify areas of highest risk to guide interventions and to monitor progress. Objectives: To use RS/GIS to identify the environmental variables that correlate with the ecology of STHs and with the prevalence of STH infections. Methods: Geo-referenced in situ prevalence data will be overlaid over an ecological map derived from the RS environmental data using ESRI s ArcGIS 9.3. Prevalence data and RS environmental data matching at the same geographical location will be analyzed for correlation and those RS environmental variables that better correlate with prevalence data will be included in a multivariate regression model. Temperature, vegetation, and distance to bodies of water will be inferred using data from the Moderate-Resolution Imaging Spectroradiometer (MODIS) onboard the Terra and Aqua satellites, and Thematic Mapper (TM) and Enhance Thematic Mapper Plus (ETM+) satellite sensors onboard Landsat 5 and Landsat 7 respectively. Elevation will be estimated with data from The Shuttle Radar Topography Mission (SRTM). Prevalence and intensity of infections will be determined by parasitological survey (Kato Katz) of children enrolled in rural schools in Boaco, Nicaragua, in the communities of El Roblar, Cumaica Norte, Malacatoya 1, and Malacatoya 2). Expected Results: Associations between RS environmental data and prevalence in situ data will be determined and their applications to public health will be discussed. Discussion/Conclusions: The use of RS/GIS data to predict the prevalence of STH infections could be useful for helminth control programs, providing improved geographical guidance of interventions while increasing cost-effectiveness. Learning Objectives: (1) To identify the RS environmental variables that can help predict the prevalence of STH infections. (2) To understand potential applications of RS/GIS to national helminth control programs. (3) To asses the applicability of RS/GIS to control STH infections.

Moreno, Max J.↗
NASA NTRS1990

Quasi-coherent structures in the turbulent boundary layer. I - Status report on a community-wide summary of the data

A review is presented of the approach, motivation and early results of a reevaluation of the knowledge collected by the research community during thirty years of research on the structure of turbulent boundary layers. Four distinctions or criteria concerning the need to improve the practices in this field are discussed: data versus inferences, possible versus actual versus significant events, one structure versus many, and one or two flows versus the totality of data. Attention given to the known quasi-coherent structures show that three factors significantly reduce the information available from laboratory data as a basis for forming a complete model of the quasi-coherent structure in the turbulent boundary layer: (1) the necessity to ensemble average probe output with resulting loss of phase information, (2) the inability to see more than one or two of the various types of structures simultaneously, and (3) the inability to see the spatial relations between the various quasi-coherent structures resulting from (1) and (2).

Kline, S. J.↗
NASA NTRSDate not supplied

Application of Satellite Gravimetry for Water Resources Monitoring

Satellite gravimetry is unique in its ability to measure, from space, mass changes in the atmosphere and on and below Earth’s surface. After accounting for atmosphere and ocean mass circulations, scientists use these measurements to estimate changes in terrestrial water storage (TWS), which comprises groundwater, soil moisture, surface waters, snow, and ice. Monthly TWS data from the GRACE and GRACE-FO missions have been available since 2002. This presentation will discuss the application of these data for inferring and attributing regional trends in TWS around the world. It will also describe how the assimilation of GRACE and GRACEFO data into a land surface model enables monitoring and forecasting droughts and flood vulnerability.

Matthew Rodell↗
DOE OSTI2026

AIF for Vis (Active Inference for simulating human interpretation of data visualization) [SWR-26-084]

AIF for Vis contains the Active Inference models and analysis scripts used to study a simple visualization-interpretation task: estimating the average value of two bars in a bar chart. The work is a proof of concept for translating hypothesized cognitive strategies into executable, inspectable process models. We implement two idealized strategies inspired by dual-process accounts of visualization-aided decision making: *Fast model: a compressed, heuristic strategy that estimates the visual midpoint of the two bars and maintains a single belief over their average. *Slow model: a sequential, analytic strategy that estimates the two bar heights separately and maintains them in working memory before computing an average. Both models use a common Active-Inference-inspired framework for sequential perception, belief updating, action selection, and reporting. Their different internal representations produce distinct predicted vulnerabilities: *the Fast model is more susceptible to tick-salience bias; *the Slow model is more susceptible to working-memory decay. The repository includes the model implementations, scripts used for the experiments reported in the paper, precomputed trial-level results, and plotting scripts.

Goldwyn, Harrison [National Laboratory of the Rock↗
NASA NTRS2011

Analysis of Association Between Remotely Sensed (RS) Data and Soil Transmitted Helminthes Infection Using Geographical Information Systems (GIS): Boaco, Nicaragua

Soil-transmitted helminths are intestinal nematodes that can infect all members of a population but specially school-age children living in poverty. Infection can be significantly reversed with anthelmintic drug treatments and sanitation improvement. Implementation of effective public health programs requires reliable and updated information to identify areas at higher risk and to calculate amount of drug required. Geo-referenced in situ prevalence data will be overlaid over an ecological map derived from RS data using ARC Map 9.3 (ESRI). Prevalence data and RS data matching at the same geographical location will be analyzed for correlation and those variables from RS data that better correlate with prevalence will be included in a multivariate regression model. Temperature, vegetation, and distance to bodies of water will be inferred using data from Moderate-Resolution Imaging Spectroradiometer (MODIS) and Landsat TM and ETM+. Elevation will be estimated with data from The Shuttle Radar Topography Mission (SRTM). Prevalence and intensity of infections are determined by parasitological survey (Kato Katz) of children enrolled in rural schools in Boaco, Nicaragua, in the communities of El Roblar, Cumaica Norte, Malacatoya 1, and Malacatoya 2). This study will demonstrate the importance of an integrated GIS/RS approach to define sampling clusters without the need for any ground-based survey. Such information is invaluable to identify areas of high risk and to geographically target control programs that maximize cost-effectiveness and sanitation efforts.

MorenoMadrinan, Max J.↗
NASA NTRS1980

Inversion of multiwavelength radiometer measurements by three-dimensional filtering

Remote sensing data from satellites typically have three dimensions: scan position, spacecraft position, and wavelength. Inversion of the radiometric data to infer geophysical parameters is a filtering problem in which the dimension of wavelength (or channel number) is transformed into a dimension of geophysical parameters, and the most general solution is a three-dimensional filter. Linear filters have the advantages of computational speed and easily described transfer functions; but often the measurements are nonlinear functions of the parameters to be inferred. To the extent that the nonlinear inversion problem is overdetermined, it can be modeled by a critically determined linear problem. As an example, inversion of Scanning Multichannel Microwave Radiometer (SMMR) data by means of a three-dimensional Wiener Filter is described. Atmospheric water vapor content, rain liquid water content, surface wind speed and surface temperature are the parameters inferred from the measurements. Nonprecipitating liquid water and water vapor scale height are also modeled but not retrieved. The a priori statistics on which the filter is trained have the effect of governing the selection of a trade-off point of noise as a function of resolution (in all three retrieval dimensions).

Rosenkranz, P. W.↗
NASA NTRS2008

Statistical Estimation of Orbital Debris Populations with a Spectrum of Object Size

Orbital debris is a real concern for the safe operations of satellites. In general, the hazard of debris impact is a function of the size and spatial distributions of the debris populations. To describe and characterize the debris environment as reliably as possible, the current NASA Orbital Debris Engineering Model (ORDEM2000) is being upgraded to a new version based on new and better quality data. The data-driven ORDEM model covers a wide range of object sizes from 10 microns to greater than 1 meter. This paper reviews the statistical process for the estimation of the debris populations in the new ORDEM upgrade, and discusses the representation of large-size (greater than or equal to 1 m and greater than or equal to 10 cm) populations by SSN catalog objects and the validation of the statistical approach. Also, it presents results for the populations with sizes of greater than or equal to 3.3 cm, greater than or equal to 1 cm, greater than or equal to 100 micrometers, and greater than or equal to 10 micrometers. The orbital debris populations used in the new version of ORDEM are inferred from data based upon appropriate reference (or benchmark) populations instead of the binning of the multi-dimensional orbital-element space. This paper describes all of the major steps used in the population-inference procedure for each size-range. Detailed discussions on data analysis, parameter definition, the correlation between parameters and data, and uncertainty assessment are included.

Xu, Y. -l↗
NASA NTRS2008

Combined Impedance Probe and Langmuir Probe Studies of the Low-Latitude E Region

The EQUIS-2 sounding rocket and radar campaign, launched from Kwajalein Atoll in 2004, included a mission to study low-latitude irregularities and electrodynamics, led by NASA GSFC. This mission included two instrumented rockets launched into the nighttime E region (apogee near 120 km), which included comprehensive electrodynamics and neutral density instrumentation. These rockets carried the first of a new generation of impedance probes, that utilize a wide-band drive signal to simultaneously measure the impedance of an antenna in a plasma as a function of frequency from 7 kEIz to 4 MHz. at a rapid cadence. This technique promises to permit true plasma spectroscopy, and resulted in the identification of multiple plasma resonances and accurate measurements of the plasma density, even in the low density nighttime E region. We present analyses of the technique and resulting spectra, and show how these data may be combined with fixed-bias Langmuir Probe data to infer the temperature structure of the E region as well as providing accurate absolute calibrations for the very high time resolution fixed-bias probe data. The data is shown to agree well with data from ionosonde, the ALTAIR radar, and the Peruvian beacon experiment.

Rowland, D. E.↗
NASA NTRS1976

DABI: A data base for image analysis with nondeterministic inference capability

A description is given of the data base used in the perception subsystem of the Mars robot vehicle prototype being implemented at the Jet Propulsion Laboratory. This data base contains two types of information. The first is generic (uninstantiated, abstract) information that specifies the general rules of perception of objects in the expected environments. The second kind of information is a specific (instantiated) description of a structure, i.e., the properties and relations of objects in the specific case being analyzed. The generic knowledge can be used by the approximate reasoning subsystem to obtain information on the specific structures which is not directly measurable by the sensory instruments. Raw measurements are input either from the sensory instruments or a human operator using a CRT or a TTY.

Yakimovsky, Y.↗
NASA NTRS1984

Block rotation by strike-slip faulting - Structural and paleomagnetic evidence

The magnitude and sense of block rotations depicted from such structural data as fault spacing and slip are noted to agree with values obtained from independent paleomagnetic determinations. The agreement between paleomagnetic rotation data and those inferred from offset and spacing data in northern Israel is excellent, suggesting that the faults and intervening blocks were rotated with progressive deformation along the levant transform. It is suggested that the rotation of blocks and the strike-slip displacement are two qualitative and quantitative contemporaneous aspects of a single deformation process.

Ron, H.↗
NASA NTRS1992

Moessbauer Spectroscopy for Lunar Resource Assessment: Measurement of Mineralogy and Soil Maturity

First-order assessment of lunar soil as a resource includes measurement of its mineralogy and maturity. Soils in which the mineral ilmenite is present in high concentrations are desirable feedstock for the production of oxygen at a lunar base. The maturity of lunar soils is a measure of their relative residence time in the upper 1 mm of the lunar surface. Increasing maturity implies increasing load of solar wind species (e.g., N, H, and He-3), decreasing mean grain size, and increasing glass content. All these physicochemical properties that vary in a regular way with maturity are important parameters for assessing lunar soil as a resource. For example, He-3 can be extracted and potentially used for nuclear fusion. A commonly used index for lunar soil maturity is I(sub s)/FeO, which is the concentration of fine-grained metal determined by ferromagnetic resonance (I(sub s)) normalized to the total iron content (as FeO). I(sub s)/FeO has been measured for virtually every soil returned by the Apollo and Luna missions to the Moon. Because the technique is sensitive to both oxidation state and mineralogy, iron Moessbauer spectroscopy (FeMS) is a viable technique for in situ lunar resource assessment. Its utility for mineralogy is apparent from examination of published FeMS data for lunar samples. From the data published, it can be inferred that FeMS data can also be used to determine soil maturity. The use of FeMS to determine mineralogy and maturity and progress on development of a FeMS instrument for lunar surface use are discussed.

Morris, R. V.↗
DOE OSTI2025

Variational autoencoders for at-source data reduction and anomaly detection in high energy particle detectors

Detectors in next-generation high-energy physics experiments face several daunting requirements, such as high data rates, damaging radiation exposure, and stringent constraints on power, space, and latency. To address these challenges, machine learning in readout electronics can be leveraged for smart detector designs, enabling intelligent inference and data reduction at-source. Variational autoencoders (VAEs) offer a variety of benefits for front-end readout; an on-sensor encoder can perform efficient lossy data compression while simultaneously providing a latent space representation that can be used for anomaly detection. Results are presented from low-latency and resource-efficient VAEs for front-end data processing in a futuristic silicon pixel detector. Encoder-based data compression is found to preserve good performance of off-detector analysis while significantly reducing the off-detector data rate as compared to a similarly sized data filtering approach. Furthermore, the latent space information is found to be a useful discriminator in the context of real-time sensor defect monitoring. Together, these results highlight the multifaceted utility of autoencoder-based front-end readout schemes and motivate their consideration in future detector designs.

47 OTHER INSTRUMENTATION↗
NASA NTRS1997

Local Interstellar Medium Properties and Deuterium Abundances for the Lines of Sight Toward HR 1099, 31 Comae, beta Ceti, and beta Cassiopeiae

We analyze Goddard High-Resolution Spectrograph data to infer the properties of local interstellar gas and the Deuterium/Hydrogen (D/H) ratio for lines of sight toward four nearby late-type stars-HR 1099, 31 Comae, beta Ceti, and beta Cassiopeiae. The data consist of spectra of the hydrogen and deuterium Lyman-(alpha) lines, and echelle spectra of the Mg IIh and k lines toward all stars except beta Cas. Spectra of the RS CVn-type spectroscopic binary system HR 1099 were obtained near opposite quadratures to determine the intrinsic stellar emission line profile and the interstellar absorption separately. Multiple-velocity components were found toward HR 1099 and beta Cet. The spectra of 31 Com and beta Cet are particularly interesting because they sample lines of sight toward the north and south Galactic poles, respectively, for which H I and D I column densities were not previously available. The north Galactic pole appears to be a region of low hydrogen density like the 'interstellar tunnel' toward epsilon CMa. The temperature and turbulent velocities of the Local InterStellar Medium (LISM) that we measure for the lines of sight toward HR 1099, 31 Com, beta Cet, and beta Cas are similar to previously measured values (T approx.7000 K and xi = 1.0-1.6 km/s). The deuterium/hydrogen ratios found for these lines of sight are also consistent with previous measurements of other short lines of sight, which suggest D/H approx. 1.6 x 10(sup -5). In contrast, the Mg abundance measured for the beta Cet line of sight (implying a logarithmic depletion of D(Mg) = +0.30 +/- 0.15) is about 5 times larger than the Mg abundance previously observed toward alpha Cen, and about 20 times larger than all other previous measurements for the LISM. These results demonstrate that metal abundances in the LISM vary greatly over distances of only a few parsecs.

Piskunov, Nikolai↗
NASA NTRS1984

Determination of cloud parameters from infrared sounder data

The World Climate Research Programme (WCRP) plan is concerned with the need to develop a uniform global cloud climatology as part of a broad research program on climate processes. The International Satellite Cloud Climatology Project (ISCCP) has been approved as the first project of the WCRP. The ISCCP has the basic objective to collect and analyze satellite radiance data to infer the global distribution of cloud radiative properties in order to improve the modeling of cloud effects on climate. Research is conducted to explore an algorithm for retrieving cloud properties by utilizing the available infrared sounder data from polar-orbiting satellites. A numerical method is developed for computing cloud top heights, amount, and emissivity on the basis of a parameterized infrared radiative transfer equation for cloudy atmospheres. Theoretical studies were carried out by considering a synthetic atmosphere.

Yeh, H.-Y. M.↗
NASA NTRS2005

Rheology of the Ronne Ice Shelf, Antarctica, Inferred from Satellite Radar Interferometry Data using an Inverse Control Method

The Antarctic Ice Sheet is surrounded by large floating ice shelves that spread under their own weight into the ocean. Ice shelf rigidity depends on ice temperature and fabrics, and is influenced by ice flow and the delicate balance between bottom and surface accumulation. Here, we use an inverse control method to infer the rigidity of the Ronne Ice Shelf that best matches observations of ice velocity from satellite radar interferometry. Ice rigidity, or flow law parameter B, is shown to vary between 300 and 900 kPa a(sup 1/3). Ice is softer along the side margins due to frictional heating, and harder along the outflow of large glaciers, which advect cold continental ice. Melting at the bottom surface of the ice shelf increases its rigidity, while freezing decreases it. Accurate numerical modelling of ice shelf flow must account for this spatial variability in mechanical characteristics.

ice velocity↗
NASA NTRS1983

Carbon monoxide mixing ratio inference from gas filter radiometer data

A new algorithm has been developed which permits, for the first time, real time data reduction of nadir measurements taken with a gas filter correlation radiometer to determine tropospheric carbon monoxide concentrations. The algorithm significantly reduces the complexity of the equations to be solved while providing accuracy comparable to line-by-line calculations. The method is based on a regression analysis technique using a truncated power series representation of the primary instrument output signals to infer directly a weighted average of trace gas concentration. The results produced by a microcomputer-based implementation of this technique are compared with those produced by the more rigorous line-by-line methods. This algorithm has been used in the reduction of Measurement of Air Pollution from Satellites, Shuttle, and aircraft data.

Wallio, H. A.↗
DOE OSTI2025

Evaluation of data driven low-rank matrix factorization for accelerated solutions of the Vlasov equation

Low-rank methods have shown success in accelerating simulations of a collisionless plasma described by the Vlasov equation, but still rely on computationally costly linear algebra every time step. We propose a data-driven factorization method using artificial neural networks, specifically with convolutional layer architecture, that trains on existing simulation data. At inference time, the model outputs a low-rank decomposition of the distribution field of the charged particles, and we demonstrate that this step is faster than the standard linear algebra technique. Numerical experiments show that the method achieves comparable reconstruction accuracy for interpolation tasks, generalizing to unseen test data in a manner beyond just memorizing training data; patterns in factorization also inherently followed the same numerical trend as those within algebraic methods (e.g., truncated singular-value decomposition). However, when training on the first 70% of a time-series data and testing on the remaining 30%, the method fails to meaningfully extrapolate. Despite this limiting result, the technique may have benefits for simulations in a statistical steady-state or otherwise showing temporal stability. These results suggest that while the model offers a computationally efficient alternative for datasets with temporal stability, its current formulation is best suited for interpolation rather than for predicting future states in time-evolving systems. This study thus lays the groundwork for further refinement of neural network-based approaches to low-rank matrix factorization in high-dimensional plasma simulations.

97 MATHEMATICS AND COMPUTING↗