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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.

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At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

The Analysis of the Patterns of Radiation-Induced DNA Damage Foci by a Stochastic Monte Carlo Model of DNA Double Strand Breaks Induction by Heavy Ions and Image Segmentation Software

To create a generalized mechanistic model of DNA damage in human cells that will generate analytical and image data corresponding to experimentally observed DNA damage foci and will help to improve the experimental foci yields by simulating spatial foci patterns and resolving problems with quantitative image analysis. Material and Methods: The analysis of patterns of RIFs (radiation-induced foci) produced by low- and high-LET (linear energy transfer) radiation was conducted by using a Monte Carlo model that combines the heavy ion track structure with characteristics of the human genome on the level of chromosomes. The foci patterns were also simulated in the maximum projection plane for flat nuclei. Some data analysis was done with the help of image segmentation software that identifies individual classes of RIFs and colocolized RIFs, which is of importance to some experimental assays that assign DNA damage a dual phosphorescent signal. Results: The model predicts the spatial and genomic distributions of DNA DSBs (double strand breaks) and associated RIFs in a human cell nucleus for a particular dose of either low- or high-LET radiation. We used the model to do analyses for different irradiation scenarios. In the beam-parallel-to-the-disk-of-a-flattened-nucleus scenario we found that the foci appeared to be merged due to their high density, while, in the perpendicular-beam scenario, the foci appeared as one bright spot per hit. The statistics and spatial distribution of regions of densely arranged foci, termed DNA foci chains, were predicted numerically using this model. Another analysis was done to evaluate the number of ion hits per nucleus, which were visible from streaks of closely located foci. In another analysis, our image segmentaiton software determined foci yields directly from images with single-class or colocolized foci. Conclusions: We showed that DSB clustering needs to be taken into account to determine the true DNA damage foci yield, which helps to determine the DSB yield. Using the model analysis, a researcher can refine the DSB yield per nucleus per particle. We showed that purely geometric artifacts, present in the experimental images, can be analytically resolved with the model, and that the quantization of track hits and DSB yields can be provided to the experimentalists who use enumeration of radiation-induced foci in immunofluorescence experiments using proteins that detect DNA damage. An automated image segmentaiton software can prove useful in a faster and more precise object counting for colocolized foci images.

Ponomarev, Artem↗
NASA NTRS2004

Fossil Signatures Using Elemental Abundance Distributions and Bayesian Probabilistic Classification

Elemental abundances (C6, N7, O8, Na11, Mg12, Al3, P15, S16, Cl17, K19, Ca20, Ti22, Mn25, Fe26, and Ni28) were obtained for a set of terrestrial fossils and the rock matrix surrounding them. Principal Component Analysis extracted five factors accounting for the 92.5% of the data variance, i.e. information content, of the elemental abundance data. Hierarchical Cluster Analysis provided unsupervised sample classification distinguishing fossil from matrix samples on the basis of either raw abundances or PCA input that agreed strongly with visual classification. A stochastic, non-linear Artificial Neural Network produced a Bayesian probability of correct sample classification. The results provide a quantitative probabilistic methodology for discriminating terrestrial fossils from the surrounding rock matrix using chemical information. To demonstrate the applicability of these techniques to the assessment of meteoritic samples or in situ extraterrestrial exploration, we present preliminary data on samples of the Orgueil meteorite. In both systems an elemental signature produces target classification decisions remarkably consistent with morphological classification by a human expert using only structural (visual) information. We discuss the possibility of implementing a complexity analysis metric capable of automating certain image analysis and pattern recognition abilities of the human eye using low magnification optical microscopy images and discuss the extension of this technique across multiple scales.

Hoover, Richard B.↗
DOE OSTI2024

Deciphering Discrepancies: A Comparative Analysis of Docker Image Security

As the use of microservices continues to grow and become a foundational approach to architecting software solutions, ensuring the security of microservices is paramount. Docker images have emerged as the predominant solution to containerize microservices–and thus, Docker images are becoming a large attack surface. Thus, reducing vulnerabilities in Docker images will reduce microservice cyberattacks. A common way to find vulnerabilities in Docker images employs static analysis tools like Trivy and Grype. However, these tools frequently generate disparate vulnerability reports when analyzing the same Docker image, thus causing uncertainty in tool selection. We collected 927 Docker images, analyzed them with Trivy and Grype, and compared the vulnerabilities reported in each image. Among the 865 images found to have vulnerabilities, Trivy and Grype disagreed on both the number of vulnerabilities and the vulnerability IDs found therein. Since both tools interface with external vulnerability databases, some discrepancies can be attributed to how the tools interface with these external resources. The external vulnerability databases partially overlap and frequently contradict one another, thereby creating challenges for static analysis tool developers and end users alike. This New Ideas and Emerging Results (NIER) study contains new and critical information that practitioners need for selecting and using static analysis tools–given that increases in the use of Docker technologies means increases in the size of the attack surfaces.

Boles, Brittany [Montana State University]↗
NASA NTRS1986

Proceedings of the Second Airborne Imaging Spectrometer Data Analysis Workshop

The Second Airborne Imaging Spectrometer (AIS) Data Analysis Workshop was held at the Jet Propulsion Laboratory on May 6, 7, and 8, 1986. It was attended by 100 people from seven countries. Papers were presented by 24 attendees; summaries of 19 of the papers are published in these Workshop Proceedings. The Second Workshop was divided into three sessions: Calibration, the Atmosphere, and Data Techniques; Geological Research; and Botanical and Geobotanical Research. Because many of the AIS researchers have had an additional year to work with their data, a general advance was seen in the utilization of the data for solving earth science problems. The major conclusions that can be drawn from the Workshop are: (1) Almost everyone now working with AIS data is attempting to take into account in data analysis the effects of the atmosphere and sensor calibration and performance. As a result, information extraction techniques are becoming more sophisticated and effective. (2) The emphasis on work in the geological disciplines is beginning to shift to the application of AIS data for solving geological problems now that the efficacy of the data for mineral identification has been demonstrated. (3) In the botanical sciences, interpretation of AIS data is becoming more quantitative. Several statistical techniques are under development for extracting the subtle differences in plant spectra in the region of the near infrared and short wavelength infrared. In summary, an overall advance was seen in the ability to effectively utilize the fundamentally new class of data acquired with imaging spectrometers. There was also a general feeling at the Workshop however, that much work remains to be done in remote sensing research before the maximum potential of these data for solving earth science problems is realized.

Gregg Vane↗
NASA NTRS1984

The APL image processing laboratory

The present and proposed capabilities of the Central Image Processing Laboratory, which provides a powerful resource for the advancement of programs in missile technology, space science, oceanography, and biomedical image analysis, are discussed. The use of image digitizing, digital image processing, and digital image output permits a variety of functional capabilities, including: enhancement, pseudocolor, convolution, computer output microfilm, presentation graphics, animations, transforms, geometric corrections, and feature extractions. The hardware and software of the Image Processing Laboratory, consisting of digitizing and processing equipment, software packages, and display equipment, is described. Attention is given to applications for imaging systems, map geometric correction, raster movie display of Seasat ocean data, Seasat and Skylab scenes of Nantucket Island, Space Shuttle imaging radar, differential radiography, and a computerized tomographic scan of the brain.

Jenkins, J. O.↗
NASA NTRS1984

Hot section viewing system

This report covers the development and testing of a prototype combustor viewing system. The system allows one to see and record images from the inside of an operating gas turbine combustor. The program proceeded through planned phases of conceptual design, preliminary testing to resolve problem areas, prototype design and fabrication, and rig testing. Successful tests were completed with the viewing system in the laboratory, in a high pressure combustor rig, and on a Pratt and Whitney PW20307 jet engine. Both film and video recordings were made during the tests. Digital image analysis techniques were used to enhance images and bring out special effects. The use of pulsed laser illumination was also demonstrated as a means for observing liner surfaces in the presence of luminous flame.

Morey, W. W.↗
NASA NTRS1990

Remote sensing science for the Nineties; Proceedings of IGARSS '90 - 10th Annual International Geoscience and Remote Sensing Symposium, University of Maryland, College Park, May 20-24, 1990. Vols. 1, 2, & 3

Various papers on remote sensing (RS) for the nineties are presented. The general topics addressed include: subsurface methods, radar scattering, oceanography, microwave models, atmospheric correction, passive microwave systems, RS in tropical forests, moderate resolution land analysis, SAR geometry and SNR improvement, image analysis, inversion and signal processing for geoscience, surface scattering, rain measurements, sensor calibration, wind measurements, terrestrial ecology, agriculture, geometric registration, subsurface sediment geology, radar modulation mechanisms, radar ocean scattering, SAR calibration, airborne radar systems, water vapor retrieval, forest ecosystem dynamics, land analysis, multisensor data fusion. Also considered are: geologic RS, RS sensor optical measurements, RS of snow, temperature retrieval, vegetation structure, global change, artificial intelligence, SAR processing techniques, geologic RS field experiment, stochastic modeling, topography and Digital Elevation model, SAR ocean waves, spaceborne lidar and optical, sea ice field measurements, millimeter waves, advanced spectroscopy, spatial analysis and data compression, SAR polarimetry techniques. Also discussed are: plant canopy modeling, optical RS techniques, optical and IR oceanography, soil moisture, sea ice back scattering, lightning cloud measurements, spatial textural analysis, SAR systems and techniques, active microwave sensing, lidar and optical, radar scatterometry, RS of estuaries, vegetation modeling, RS systems, EOS/SAR Alaska, applications for developing countries, SAR speckle and texture.

Source record↗
NASA NTRS1993

An investigative study of multispectral data compression for remotely-sensed images using vector quantization and difference-mapped shift-coding

A study is conducted to investigate the effects and advantages of data compression techniques on multispectral imagery data acquired by NASA's airborne scanners at the Stennis Space Center. The first technique used was vector quantization. The vector is defined in the multispectral imagery context as an array of pixels from the same location from each channel. The error obtained in substituting the reconstructed images for the original set is compared for different compression ratios. Also, the eigenvalues of the covariance matrix obtained from the reconstructed data set are compared with the eigenvalues of the original set. The effects of varying the size of the vector codebook on the quality of the compression and on subsequent classification are also presented. The output data from the Vector Quantization algorithm was further compressed by a lossless technique called Difference-mapped Shift-extended Huffman coding. The overall compression for 7 channels of data acquired by the Calibrated Airborne Multispectral Scanner (CAMS), with an RMS error of 15.8 pixels was 195:1 (0.41 bpp) and with an RMS error of 3.6 pixels was 18:1 (.447 bpp). The algorithms were implemented in software and interfaced with the help of dedicated image processing boards to an 80386 PC compatible computer. Modules were developed for the task of image compression and image analysis. Also, supporting software to perform image processing for visual display and interpretation of the compressed/classified images was developed.

Jaggi, S.↗
NASA NTRS1991

Design of an automated imaging system for use in a space experiment

An experiment, occurring in an orbiting platform, examines the mass transfer across gas-liquid and liquid-liquid interfaces. It employs an imaging system with real time image analysis. The design includes optical design, imager selection and integration, positioner control, image recording, software development for processing and interfaces to telemetry. It addresses the constraints of weight, volume, and electric power associated with placing the experiment in the Space Shuttle cargo bay. Challenging elements of the design are: imaging and recording of a 200-micron-diameter bubble with a resolution of 2 microns to serve a primary source of data; varying frame rates from 500 per second to 1 frame per second, depending on the experiment phase; and providing three-dimensional information to determine the shape of the bubble.

Hartz, William G.↗
NASA NTRS2012

Optical and Scanning Electron Microscopy of the Materials International Space Station Experiment (MISSE) Spacecraft Silicone Experiment

Under a microscope, atomic oxygen (AO) exposed silicone surfaces are crazed and seen as "islands" separated by numerous crack lines, much analogous to mud-tile cracks. This research characterized and compared the degree of AO degradation of silicones by analyzing optical microscope images of samples exposed to low Earth orbit (LEO) AO as part of the Spacecraft Silicone Experiment. The Spacecraft Silicone Experiment consisted of eight DC 93-500 silicone samples exposed to eight different AO fluence levels (ranged from 1.46 to 8.43 10(exp 21) atoms/sq cm) during two different Materials International Space Station Experiment (MISSE) missions. Image analysis software was used to analyze images taken using a digital camera. To describe the morphological degradation of each AO exposed flight sample, three different parameters were selected and estimated: (1) average area of islands was determined and found to be in the 1000 to 3100 sq mm range; (2) total length of crack lines per unit area of the sample surface were determined and found to be in the range of 27 to 59 mm of crack length per sq mm of sample surface; and (3) the fraction of sample surface area that is occupied by crack lines was determined and found to be in the 25 to 56 percent range. In addition, average crack width can be estimated from crack length and crack area measurements and was calculated to be about 10 mm. Among the parameters studied, the fraction of sample surface area that is occupied by crack lines is believed to be most useful in characterizing the degree of silicone conversion to silicates by AO because its value steadily increases with increasing fluence over the entire fluence range. A series of SEM images from the eight samples exposed to different AO fluences suggest a complex sequence of surface stress due to surface shrinkage and crack formation, followed by re-distribution of stress and shrinking rate on the sample surface. Energy dispersive spectra (EDS) indicated that upon AO exposure, carbon content on the surface decreased relatively quickly at the beginning, to 32 percent of the pristine value for the least exposed sample in this set of experiments (1.46 10(exp 21) atoms/sq cm), but then decreased slowly, to 22 percent of the pristine value for the most exposed sample in this set of experiment (8.43 10(exp 21) atoms/sq cm). The oxygen content appears to increase at a slower rate. The least and most AO exposed samples were, respectively, 52 and 150 percent above the pristine values. The silicone samples with the greater AO exposure (7.75 10(exp 21) atoms/sq cm and higher) appear to have a surface layer which contains SiO2 with perhaps small amounts of unreacted silicone, CO and CO2 sealed inside.

Hung, Ching-cheh↗
NASA NTRS2016

Post-Flight Assessment of Avcoat Thermal Protection System for the Exploration Flight Test-1

On December 5, 2014 NASA conducted the first flight test of its next generation human-class Orion spacecraft. The flight was called the Exploration Flight Test -1 (EFT-1) which lasted for 4 hours and culminated into a re-entry trajectory at 9 km/s. This flight test of the 5-meter Orion Crew Module demonstrated various sub-systems including the Avcoat ablative thermal protection system (TPS) on the heat shield. The Avcoat TPS had been developed from the Apollo-era recipe with a few key modifications. The engineering for thermal sizing was supported by modeling, analysis, and ground tests in arc jet facilities. This paper will describe a postlfight analysis plan and present results from post-recovery inspections, data analysis from embedded sensors, TPS sample extraction and characterization in the laboratory. After the recovery of the vehicle, a full photographic survey and surface scans of the TPS were performed. The recovered vehicle showed physical evidence of flow disturbances, varying degrees of surface roughness, and excessive recession downstream of compression pads. The TPS recession was measured at more than 200 locations of interest on the Avcoat surface. The heat shield was then processed for sample extraction prior to TPS removal using the 7-Axis Milling machine at Marshall Space Flight Center. Around 182 rectangular TPS samples were extracted for subsequent analysis and investigation. The final paper will also present results of sample analysis. The planned investigation includes sidewall imaging, followed by image analysis to characterize TPS response by quantifying different layers in the char and pyrolysis zones. A full postmortem of the instrumentation and sensor ports will also be performed to confirm no adverse effects due to the sensors themselves. A subset of the samples will undergo structural testing and perform detailed characterization of any cracks and integrity of gore seams. Finally, the material will be characterized with layer-by-layer density measurements and SEM investigations to evaluate material morphology at microstructural level including identification of elements and compounds.

Aerothermodynamics↗
NASA NTRS2016

Image Correlation Pattern Optimization for Micro-Scale In-Situ Strain Measurements

The accuracy and precision of digital image correlation (DIC) is a function of three primary ingredients: image acquisition, image analysis, and the subject of the image. Development of the first two (i.e. image acquisition techniques and image correlation algorithms) has led to widespread use of DIC; however, fewer developments have been focused on the third ingredient. Typically, subjects of DIC images are mechanical specimens with either a natural surface pattern or a pattern applied to the surface. Research in the area of DIC patterns has primarily been aimed at identifying which surface patterns are best suited for DIC, by comparing patterns to each other. Because the easiest and most widespread methods of applying patterns have a high degree of randomness associated with them (e.g., airbrush, spray paint, particle decoration, etc.), less effort has been spent on exact construction of ideal patterns. With the development of patterning techniques such as microstamping and lithography, patterns can be applied to a specimen pixel by pixel from a patterned image. In these cases, especially because the patterns are reused many times, an optimal pattern is sought such that error introduced into DIC from the pattern is minimized. DIC consists of tracking the motion of an array of nodes from a reference image to a deformed image. Every pixel in the images has an associated intensity (grayscale) value, with discretization depending on the bit depth of the image. Because individual pixel matching by intensity value yields a non-unique scale-dependent problem, subsets around each node are used for identification. A correlation criteria is used to find the best match of a particular subset of a reference image within a deformed image. The reader is referred to references for enumerations of typical correlation criteria. As illustrated by Schreier and Sutton and Lu and Cary systematic errors can be introduced by representing the underlying deformation with under-matched shape functions. An important implication, as discussed by Sutton et al., is that in the presence of highly localized deformations (e.g., crack fronts), error can be reduced by minimizing the subset size. In other words, smaller subsets allow the more accurate resolution of localized deformations. Contrarily, the choice of optimal subset size has been widely studied and a general consensus is that larger subsets with more information content are less prone to random error. Thus, an optimal subset size balances the systematic error from under matched deformations with random error from measurement noise. The alternative approach pursued in the current work is to choose a small subset size and optimize the information content within (i.e., optimizing an applied DIC pattern), rather than finding an optimal subset size. In the literature, many pattern quality metrics have been proposed, e.g., sum of square intensity gradient (SSSIG), mean subset fluctuation, gray level co-occurrence, autocorrelation-based metrics, and speckle-based metrics. The majority of these metrics were developed to quantify the quality of common pseudo-random patterns after they have been applied, and were not created with the intent of pattern generation. As such, it is found that none of the metrics examined in this study are fit to be the objective function of a pattern generation optimization. In some cases, such as with speckle-based metrics, application to pixel by pixel patterns is ill-conditioned and requires somewhat arbitrary extensions. In other cases, such as with the SSSIG, it is shown that trivial solutions exist for the optimum of the metric which are ill-suited for DIC (such as a checkerboard pattern). In the current work, a multi-metric optimization method is proposed whereby quality is viewed as a combination of individual quality metrics. Specifically, SSSIG and two auto-correlation metrics are used which have generally competitive objectives. Thus, each metric could be viewed as a constraint imposed upon the others, thereby precluding the achievement of their trivial solutions. In this way, optimization produces a pattern which balances the benefits of multiple quality metrics. The resulting pattern, along with randomly generated patterns, is subjected to numerical deformations and analyzed with DIC software. The optimal pattern is shown to outperform randomly generated patterns.

Bomarito, G. F.↗
NASA NTRS1980

Appendix E: Research papers. Manual versus digital LANDSAT analysis for modeling river flooding

The comparative value of manual versus digital image analysis for determining flood boundaries is being examined in a study of the use of LANDSAT data for modeling flooding of the Black River, in northern New York. The work is an extension of an earlier study in which Black River flooding was assessed through visually interpreted, multi-date LANDSAT band 7 images. Based on the results to date, it appears that neither color-additive viewing nor digital analysis of LANDSAT data provide improvement in accuracy over visual analysis of band 7 images, for delineating the boundaries of flood-affected areas.

Philipson, W. R.↗
NASA NTRS1981

Manual versus digital Landsat analysis for modeling river flooding

The comparative value of manual versus digital image analysis for determining flood boundaries is being examined in a study of the use of Landsat data for modeling flooding of the Black River, in northern New York. The work is an extension of an earlier study in which Black River flooding was assessed through visually interpreted, multi-date Landsat band 7 images. Based on the results to date, it appears that neither color-additive viewing nor digital analysis of Landsat data provide improvement in accuracy over visual analysis of band 7 images, for delineating the boundaries of flood-affected areas.

Philipson, W. R.↗
NASA NTRS1978

Nature of the atmospheric dynamics on Venus from power spectrum analysis of Mariner 10 images

Power spectrum analysis of Mariner 10 images for planetary zonal wavenumbers no less than 3 and for latitudes in the range 55 deg S to 25 deg N yields spectra which show a systematic and apparently significant variation with latitude. Accordingly, average spectra are determined for three latitude zones: an equatorial region, a midlatitude region, and an intermediate zone. A comparison of the results for Venus with brightness distribution spectra for terrestrial clouds reveals similarities between the Venus midlatitude region spectrum and that for the equatorial region of the earth. The only indication of a departure from a general power law behavior for the Venus spectra is a flattening of the equatorial spectrum in the region of wavenumbers 3 and 4. The characteristics of the Venus image spectra appear to be compatible with the interpretation that the observable clouds lie in a region of high static stability with the inertial eddy motions corresponding to two-dimensional turbulence.

Travis, L. D.↗
NASA NTRS1984

Search for solar signals in GOES imagery and cloud climatology analysis

The digitization and analysis of 16mm GOES IR imagery to identify spatial and temporal variation in clouds is discussed, along with a cloud climatology analysis. Recently added to the Interactive Graphics Package was a Computer Image Analysis System. This system allows many new imaging techniques. One of the possibilities is the analysis of overall light intensity variations in six 10 degree square boxes across the intertropical convergence zone. This technique is discussed, as is a preliminary analysis of unnormalized data.

Markson, R. J.↗
NASA NTRS1984

MIDAS - A microcomputer-based image display and analysis system with full Landsat frame processing capabilities

Image Display and Analysis Systems (MIDAS) developed at NASA/Ames for the analysis of Landsat MSS images is described. The MIDAS computer power and memory, graphics, resource-sharing, expansion and upgrade, environment and maintenance, and software/user-interface requirements are outlined; the implementation hardware (including 32-bit microprocessor, 512K error-correcting RAM, 70 or 140-Mbyte formatted disk drive, 512 x 512 x 24 color frame buffer, and local-area-network transceiver) and applications software (ELAS, CIE, and P-EDITOR) are characterized; and implementation problems, performance data, and costs are examined. Planned improvements in MIDAS hardware and design goals and areas of exploration for MIDAS software are discussed.

Hofman, L. B.↗
NASA NTRS2022

Microstructure Segmentation with Deep Learning Encoders Pre-Trained on a Large Microscopy Dataset

This study examined the improvement of microscopy segmentation accuracy by transfer learning from a large dataset of microscopy images called MicroNet. Many neural network encoder architectures, including VGG, Inception, and ResNet, were trained on over 100,000 labelled microscopy images from 54 classes. These pre-trained encoders were then embedded into multiple segmentation architectures including U-Net and DeepLabV3+ to evaluate segmentation performance on newly created benchmark microscopy datasets. Compared to ImageNet pre-training, models pre-trained on MicroNet generalized better to out-of-distribution micrographs taken under different imaging and sample conditions and were more accurate with less training data. When training with only a single Ni-superalloy image, pre-training on MicroNet produced a 72.2 percent reduction in relative segmentation error. These results suggest that transfer learning from large in-domain datasets generate models with learned feature representations that are more useful for downstream tasks and will likely improve any microscopy image analysis technique that can leverage pre-trained encoders.

machine learning↗