SEARCH · Search NASA

Results for “Bayes Methods”

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.

SourceResearch connectionFrom yearThrough year

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

At least 163 records · Page 9

All sources NASA NTRS DOE OSTI

NASA NTRS1976

Applications of remote sensing to estuarine management

Projects for sewage outfall siting for pollution control in the lower Chesapeake Bay wetlands are reported. A dye-buoy/photogrammetry and remote sensing technique was employed to gather circulation data used in outfall siting. This technique is greatly favored over alternate methods because it is inexpensive, produces results quickly, and reveals Lagrangian current paths which are preferred in making siting decisions. Wetlands data were obtained by interpretation of color and color infrared photographic imagery from several altitudes. Historical sequences of photographs are shown that were used to document wetlands changes. Sequential infrared photography of inlet basins was employed to determine tidal prisms, which were input to mathematical models to be used by state agencies in pollution control. A direct and crucial link between remote sensing and management decisions was demonstrated in the various projects.

Munday, J. C., Jr.↗

NASA NTRS1989

Payload deployment method and system

A method and apparatus for deploying the payload of space shuttle craft or the like. The payload rotated about an axis outside of the payload but approximately longitudinally of the cargo bay of the shuttle craft. The payload may thus be rotated, through ninety degrees. In this case, that is in its rotated position, the payload may or may not have a small portion located within the cargo bay. Alternatively, the payload may be located completely outside of the bay. According to the apparatus two separable hinge-like devices connect at one longitudinal side or edge of the payload to respective ones of the payload trunnions at different longitudinally spaced locations along the length of the payload. Separation of the payload from the cargo bay is made unlatching a latch and by the use of a repulsion spring at the position of each hinge-like device. Two four-link mechanisms allow movement between payload and bay. Such accoommodative movement is required especially during launch when considerable vibration is encountered.

Barnett, Clifford J.↗

NASA NTRS2017

Fluid Lensing and Applications to Remote Sensing of Aquatic Environments

The use of fluid lensing technology on UAVs is presented as a novel means for 3D imaging of aquatic ecosystems from above the water's surface at the centimeter scale. Preliminary results are presented from airborne fluid lensing campaigns conducted over the coral reefs of Ofu Island, American Samoa (2013) and the stromatolite reefs of Shark Bay, Western Australia (2014), covering a combined area of 15km2. These reef ecosystems were revealed with centimetre-scale 2D resolution, and an accompanying 3D bathymetry model was derived using fluid lensing, Structure from Motion and UAV position data. Data products were validated from in-situ survey methods including underwater calibration targets, depth measurements and millimetre-scale high-dynamic range gigapixel photogrammetry. Fluid lensing is an experimental technology that uses water transmitting wavelengths to passively image underwater objects at high-resolution by exploiting time-varying optical lensing events caused by surface waves. Fluid lensing data are captured from low-altitude, cost-effective electric UAVs to achieve multispectral imagery and bathymetry models at the centimetre scale over regional areas. As a passive system, fluid lensing is presently limited by signal-to-noise ratio and water column inherent optical properties to approximately 10 m depth over visible wavelengths in clear waters. The datasets derived from fluid lensing present the first centimetre-scale images of a reef acquired from above the ocean surface, without wave distortion. The 3D multispectral data distinguish coral, fish and invertebrates in American Samoa, and reveal previously undocumented, morphologically distinct, stromatolite structures in Shark Bay. These findings suggest fluid lensing and multirotor electric drones represent a promising advance in the remote sensing of aquatic environments at the centimetre scale, or 'reef scale' relevant to the conservation of reef ecosystems. Pending further development and validation of fluid lensing methods, these technologies present a solution for large-scale 3D surveys of shallow aquatic habitats with centimetre-scale spatial resolution and hourly temporal sampling.

Aquatic↗

NASA NTRS1972

Relevance of ERTS to the State of Ohio

The author has identified the following significant results. The ability to delineate and inventory strip mined areas using ERTS-1 imagery has been established. This gives Ohio a method to rapidly gain an up-to-date inventory of strip mined lands for state planning purposes, which has not been available previously. Smoke plume detection and sedimentation patterns in Sandusky Bay have also been determined from initial analysis of ERTS-1 data.

Sweet, D. C.↗

NASA NTRS1976

Trapped rubber processing for advanced composites

Trapped rubber processing is a molding technique for composites in which precast silicone rubber is placed within a closed cavity where it thermally expands against the composite's surface supported by the vessel walls. The method has been applied by the Douglas Aircraft Company, under contract to NASA-Langley, to the design and fabrication of 10 DC-10 graphite/epoxy upper aft rudder assemblies. A three-bay development tool form mold die has been designed and manufactured, and tooling parameters have been established. Fabrication procedures include graphite layup, assembly of details in the tool, and a cure cycle. The technique has made it possible for the cocured fabrication of complex primary box structures otherwise impracticable via standard composite material processes.

Marra, P. J.↗

NASA NTRS1993

Using experimental modal data to detect damage in a space truss

The effects of damage on a model space truss are investigated using experimentally measured modes along with a procedure that uses the vibratory residual forces and a weighted sensitivity analysis to estimate the extent of mass and/or stiffness variations, where damage is characterized as a reduction in structural stiffness. It is shown that this approach yields excellent results for a four-bay space truss under consideration and was able to accurately predict not only the location of the damage region but also estimate the relative severity for three different configurations. In addition, the method was able to accurately detect and differentiate a shift in structural mass.

Tavares, R.↗

NASA NTRS2020

Demonstration of Autonomous Nested Search for Local Maxima using an Unmanned Underwater Vehicle, ICRA Submission

Ocean Worlds represent one of the best chances for extra-terrestrial life in our solar system. A new mission concept must be developed to explore these oceans. This mission would require traversing the 10s of km thick icy shell and releasing a submersible into the ocean below. During the transit of the icy shell and the exploration of the ocean, the vehicle(s) would be out of contact with Earth for weeks or potentially months at a time. During this time the vehicle must have sufficient autonomy to locate and study scientific targets of interest. One such target of interest is hydrothermal venting. We have previously developed an autonomous nested search method to locate and investigate sources of hydrothermal venting by locating local maxima in hydrothermal vent emissions. In this work we demonstrate this approach on board an OceanServer Iver2 AUV in Chesapeake Bay, MD using simulated sensor data from a hydrothermal plume model. This represents the first step towards the deployment of this approach in conditions analogous to those that we might expect on an Ocean World.

Branch, Andrew↗

NASA NTRSDate not supplied

Evaluation of Correction Methods for NASA GeneLab Transcriptomic Datasets

Conducting space biology experiments aboard the International Space Station, particularly those utilizing complex model organisms like mice, is expensive and difficult due to limited crew availability, hardware, and space. As a result, sample numbers from these studies are low, reducing the statistical power of any one experiment. Aggregating spaceflight datasets serves as a method to increase sample numbers, allowing for novel insights through bioinformatic analysis of ‘omics data from merged datasets. However, aggregating datasets can introduce unwanted variation including 1) differences in sample handling, processing, and sequencing platforms between datasets (technical variation) as well as 2) differences in experimental design between datasets. In the present study, NASA GeneLab-hosted RNAseq datasets from mouse liver tissues were used to evaluate several statistical methods to correct for this unwanted variation through two approaches, reference-based and standard. The following correction algorithms were applied with (reference-based) and/or without (standard) considering Universal Mouse RNA Reference samples: ComBat and ComBat_seq from the SVA package, median polish, empirical Bayes, and ANOVA-based algorithms from the MBatch package, and negative binomial regression normalization in the DESeq2 package. For each approach, after the correction algorithm was applied, differential gene expression (DGE) analysis of flight and ground control samples was performed with the combined data. The robustness of each tool was evaluated using BatchQC to determine statistical differences between datasets before and after correction, Principal Component Analysis to evaluate global gene expression in samples before and after correction, and by comparing DGE analysis of individual datasets and combined datasets before and after correction. The results showed that the reference-based approach introduced several additional (and likely artificial) DEGs when compared with the respective standard approach. Of the methods tested, standard ComBat and DESeq2 were identified as the most robust correction methods for combining spaceflight mouse liver RNAseq datasets hosted on GeneLab.

GeneLab↗

NASA NTRS1977

Application of LANDSAT MSS data to the study of oceanographical environment

The author has identified the following significant results. LANDSAT MSS data of a three year time lapse indicate change of sea surface condition in Seto Inland Sea and coastal region. The red tide which formerly concentrated in the bay or inland sea now extends into an open sea. A small ocean vortex similar to mesoscale atmospheric vortex is revealed by the band 4 image of the satellite data. A manual photographic method applied to a single band image of MSS is effective in detecting sea surface pollution.

Maruyasu, T.↗

NASA NTRS1984

Microwave reflector characterization using simple instruments in EVA

An antenna with rigid panels which can be measured under ground conditions, carried to space in a packaged condition, deployed into a form similar to the Earth-measured one, measured under space conditions, restowed, and brought back to Earth so that the original measurements can be verified is the type being proposed for this experiment. The antenna chosen will be measured under ground conditions, carried aloft, deployed into its antenna shape, lifted by the remote manipulator system to a position where it can be sighted by two astronauts at the two theodolites, and held there until the surface characterization can be completed. An alternate method would be to use photogrammetry and take pictures of the surface from the payload handling station. After the surface characterization is completed, the antenna will be folded and restowed into the Shuttle bay for return to Earth. The surface characterization will be repeated on Earth after its return for verification both of the original measurement taken on Earth and the measurement taken in space.

Goslee, J. W.↗

NASA NTRSDate not supplied

Combining RNA-SEQ Datasets from NASA GENELAB: An Evaluation of Correction Methods

Background: Conducting space biology experiments aboard the International Space Station, particularly those utilizing complex model organisms like mice, is expensive and difficult due to limited crew availability, hardware, and space. As a result, sample numbers from these studies are low, reducing the statistical power of any one experiment. Aggregating spaceflight datasets serves as a method to increase sample numbers, allowing for novel insights through bioinformatic analysis of ‘omics data from merged datasets. However, aggregating datasets can introduce unwanted variation including 1) differences in sample handling, processing, and sequencing platforms between datasets (technical variation) as well as 2) differences in experimental design between datasets. Methods: In the present study, NASA GeneLab-hosted RNAseq datasets from mouse liver tissues were used to evaluate several statistical methods to correct for this unwanted variation through two approaches, reference-based and standard. The following correction algorithms were applied with (reference-based) and/or without (standard) considering Universal Mouse RNA Reference samples: ComBat and ComBat_seq from the SVA package, the median polish, empirical Bayes, and ANOVA-based algorithms from the MBatch package, and negative binomial regression normalization in the DESeq2 package. For each approach, after the correction algorithm was applied, differential gene expression (DGE) analysis of flight and ground control samples was performed with the combined data. The robustness of each tool was evaluated using BatchQC to determine statistical differences between datasets before and after correction, Principal Component Analysis to evaluate global gene expression in samples before and after correction, and by comparing DGE analysis of individual datasets and combined datasets before and after correction. Results: The results showed that the reference-based approach introduced several additional (and likely artificial) differentially expressed genes when compared with the respective standard approach. Conclusions: Of the methods tested, standard ComBat_seq and DESeq2 were identified as the most robust correction methods for combining spaceflight mouse liver RNAseq datasets hosted on GeneLab.

Finsam Samson↗

NASA NTRS2018

Investigation of Stiffening and Curvature Effects on the Residual Strength of Composite Stiffened Panels with Large Transverse Notches

Design of robust aircraft structure requires consideration of the load-carrying capability with large damage. Large notches, typically introduced as machined cracks (aka "notches") severing a single skin bay and a central stiffening member, are often used to conservatively address the wide range of possible large damage scenarios. The objective of the current effort was to develop more generalized and rapid analysis methods addressing large-notch residual strength of stiffened panels to support preliminary design activities..

Enjuto, Patrick↗

NASA NTRS1998

Study Methods to Characterize and Implement Thermography Nondestructive Evaluation (NDE)

The limits and conditions under which an infrared thermographic nondestructive evaluation can be utilized to assess the quality of aerospace hardware is demonstrated in this research effort. The primary focus of this work is on applying thermography to the inspection of advanced composite structures such as would be found in the International Space Station Instrumentation Racks, Space Shuttle Cargo Bay Doors, Bantam RP-1 tank or RSRM Nose Cone. Here, the detection of delamination, disbond, inclusion and porosity type defects are of primary interest. In addition to composites, an extensive research effort has been initiated to determine how well a thermographic evaluation can detect leaks and disbonds in pressurized metallic systems "i.e. the Space Shuttle Main Engine Nozzles". In either case, research into developing practical inspection procedures was conducted and thermographic inspections were performed on a myriad of test samples, subscale demonstration articles and "simulated" flight hardware. All test samples were fabricated as close to their respective structural counterparts as possible except with intentional defects for NDE qualification. As an added benefit of this effort to create simulated defects, methods were devised for defect fabrication that may be useful in future NDE qualification ventures.

Walker, James L.↗

NASA NTRS2003

Application of a data-mining method based on Bayesian networks to lesion-deficit analysis

Although lesion-deficit analysis (LDA) has provided extensive information about structure-function associations in the human brain, LDA has suffered from the difficulties inherent to the analysis of spatial data, i.e., there are many more variables than subjects, and data may be difficult to model using standard distributions, such as the normal distribution. We herein describe a Bayesian method for LDA; this method is based on data-mining techniques that employ Bayesian networks to represent structure-function associations. These methods are computationally tractable, and can represent complex, nonlinear structure-function associations. When applied to the evaluation of data obtained from a study of the psychiatric sequelae of traumatic brain injury in children, this method generates a Bayesian network that demonstrates complex, nonlinear associations among lesions in the left caudate, right globus pallidus, right side of the corpus callosum, right caudate, and left thalamus, and subsequent development of attention-deficit hyperactivity disorder, confirming and extending our previous statistical analysis of these data. Furthermore, analysis of simulated data indicates that methods based on Bayesian networks may be more sensitive and specific for detecting associations among categorical variables than methods based on chi-square and Fisher exact statistics.

NASA Discipline Neuroscience↗

DOE OSTI2025

Rapid wavefield forecasting for earthquake early warning via deep sequence to sequence learning

We propose a deep learning model, WaveCastNet, to forecast high-dimensional wavefields. WaveCastNet integrates a convolutional long expressive memory architecture into a sequence-to-sequence forecasting framework, enabling it to model long-term dependencies and multiscale patterns in both space and time. By sharing weights across spatial and temporal dimensions, WaveCastNet requires significantly fewer parameters than more resource-intensive models such as transformers, resulting in faster inference times. Crucially, WaveCastNet also generalizes better than transformers to rare and critical seismic scenarios, such as high-magnitude earthquakes. Here, we show the ability of the model to predict the intensity and timing of destructive ground motions in real time, using simulated data from the San Francisco Bay Area. Furthermore, we demonstrate its zero-shot capabilities by evaluating WaveCastNet on real earthquake data. Our approach does not require estimating earthquake magnitudes and epicenters, steps that are prone to error in conventional methods, nor does it rely on empirical ground-motion models, which often fail to capture strongly heterogeneous wave propagation effects.

Geophysics↗

NASA NTRS1974

Correlation of coastal water turbidity and current circulation with ERTS-1 and Skylab imagery

The article reviews investigations of current circulation patterns, suspended sediment concentration, coastal frontal systems, and waste disposal plumes based on visual interpretation and digital analysis of ERTS-1 and Skylab/EREP imagery. Data on conditions in the Delaware Bay area were obtained from 10 ERTS-1 passes and one Skylab pass, with simultaneous surface and airborne sensing. The current patterns and sediments observed by ERTS-1 correlated well with ground-based observations. Methods are suggested which would make it possible to identify certain pollutants and sediment types from multispectral scanner data.

Klemas, V.↗

NASA NTRS1979

Learning with imperfectly labeled patterns

The problem of learning in pattern recognition using imperfectly labeled patterns is considered. The performance of the Bayes and nearest neighbor classifiers with imperfect labels is discussed using a probabilistic model for the mislabeling of the training patterns. Schemes for training the classifier using both parametric and non parametric techniques are presented. Methods for the correction of imperfect labels were developed. To gain an understanding of the learning process, expressions are derived for success probability as a function of training time for a one dimensional increment error correction classifier with imperfect labels. Feature selection with imperfectly labeled patterns is described.

Chittineni, C. B.↗

NASA NTRS1992

Tangential, semisubmerged, and internal store carriage and separation

Accounts are presented of tangential, semisubmerged, and internal store carriage drag, as well as of the results to date of stores-separation investigations employing both computational and experimental methods. It is demonstrated that CFD can contribute to the data base needed for internal stores carriage design and trade studies. Attention is given to the case of an internally carried store separating from its bay at supersonic speeds, where various kinds of interference are encountered. A code is developed for the simulation of these unsteady flows through time-accurate computations; computation results are noted to closely reproduce experiment data.

Wilcox, Floyd J., Jr.↗