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NASA NTRS1979

HEAO 1 observations of 4U1232+07

An analysis of the NRL HEAO 1 observations of the Virgo cluster and 3C 273 has revealed X-ray emission from a region between these two objects. The most satisfactory explanation is the presence of two weak X-ray sources, for which error boxes have been obtained. One source is likely to be the peculiar galaxy IC 3576, suggested by Margon et al. (1972) as the source 2U 1231+07=4U 1232+07. The error box resulting from combining the present observations with the 4U data strengthen the X-ray identification with this extremely interesting galaxy. There are numerous possibilities for the other X-ray source, including the interacting pair of galaxies NGC 4410a and NGC 4410b (NGC 4410a/b).

Bhavsar, S. P.↗

NASA NTRS1989

Advances in image compression and automatic target recognition; Proceedings of the Meeting, Orlando, FL, Mar. 30, 31, 1989

Various papers on image compression and automatic target recognition are presented. Individual topics addressed include: target cluster detection in cluttered SAR imagery, model-based target recognition using laser radar imagery, Smart Sensor front-end processor for feature extraction of images, object attitude estimation and tracking from a single video sensor, symmetry detection in human vision, analysis of high resolution aerial images for object detection, obscured object recognition for an ATR application, neural networks for adaptive shape tracking, statistical mechanics and pattern recognition, detection of cylinders in aerial range images, moving object tracking using local windows, new transform method for image data compression, quad-tree product vector quantization of images, predictive trellis encoding of imagery, reduced generalized chain code for contour description, compact architecture for a real-time vision system, use of human visibility functions in segmentation coding, color texture analysis and synthesis using Gibbs random fields.

Tescher, Andrew G.↗

NASA NTRS1996

Adaptive grid methods for RLV environment assessment and nozzle analysis

Rapid access to highly accurate data about complex configurations is needed for multi-disciplinary optimization and design. In order to efficiently meet these requirements a closer coupling between the analysis algorithms and the discretization process is needed. In some cases, such as free surface, temporally varying geometries, and fluid structure interaction, the need is unavoidable. In other cases the need is to rapidly generate and modify high quality grids. Techniques such as unstructured and/or solution-adaptive methods can be used to speed the grid generation process and to automatically cluster mesh points in regions of interest. Global features of the flow can be significantly affected by isolated regions of inadequately resolved flow. These regions may not exhibit high gradients and can be difficult to detect. Thus excessive resolution in certain regions does not necessarily increase the accuracy of the overall solution. Several approaches have been employed for both structured and unstructured grid adaption. The most widely used involve grid point redistribution, local grid point enrichment/derefinement or local modification of the actual flow solver. However, the success of any one of these methods ultimately depends on the feature detection algorithm used to determine solution domain regions which require a fine mesh for their accurate representation. Typically, weight functions are constructed to mimic the local truncation error and may require substantial user input. Most problems of engineering interest involve multi-block grids and widely disparate length scales. Hence, it is desirable that the adaptive grid feature detection algorithm be developed to recognize flow structures of different type as well as differing intensity, and adequately address scaling and normalization across blocks. These weight functions can then be used to construct blending functions for algebraic redistribution, interpolation functions for unstructured grid generation, forcing functions to attract/repel points in an elliptic system, or to trigger local refinement, based upon application of an equidistribution principle. The popularity of solution-adaptive techniques is growing in tandem with unstructured methods. The difficultly of precisely controlling mesh densities and orientations with current unstructured grid generation systems has driven the use of solution-adaptive meshing. Use of derivatives of density or pressure are widely used for construction of such weight functions, and have been proven very successful for inviscid flows with shocks. However, less success has been realized for flowfields with viscous layers, vortices or shocks of disparate strength. It is difficult to maintain the appropriate mesh point spacing in the various regions which require a fine spacing for adequate resolution. Mesh points often migrate from important regions due to refinement of dominant features. An example of this is the well know tendency of adaptive methods to increase the resolution of shocks in the flowfield around airfoils, but in the incorrect location due to inadequate resolution of the stagnation region. This problem has been the motivation for this research.

Thornburg, Hugh J.↗

NASA NTRS2012

Simulations of Magnetic Reconnection - Kinetic Mechanisms Underlying the Fluid Description of Ions

Because of its ability to transfer the energy stored in magnetic field together with the breaking of the flux freezing constraint, magnetic reconnection is considered as one of the most important phenomena in plasma physics. When it happens in a collision less environment such as the terrestrial magnetosphere, it should a priori be modelled with in the framework of kinetic physics. The evidence of kinetic features has incidentally for a long time, been shown by researchers with the help of both numerical simulations and satellite observations. However, most of our understanding of the process comes from the more intuitive fluid interpretation with simple closure hypothesis which do not include kinetic effects. To what extent are these two separate descriptions of the same phenomenon related? What is the role of kinetic effects in the averaged/fluid dynamics of reconnection? This thesis addresses these questions for the proton population in the particular case of anti parallel merging with the help of 2D Hybrid simulations. We show that one can not assume, as is usually done, that the acceleration of the proton flow is only due to the Laplace force. Our results show, for symmetric and asymmetric connection, the importance of the pressure force, opposed to the electric one on the separatrices, in the decoupling region. In the symmetric case, we emphasize the kinetic origin of this force by analyzing the proton distribution functions and explain their structure by studying the underlying particle dynamics. Protons, as individual particles, are shown to bounce in the electric potential well created by the Hall effect. The spatial divergence of this well results in a mixing in phase space responsible for the observed structure of the pressure tensor. A detailed energy budget analysis confirms the role of the pressure force for the acceleration; but, contrary to what is sometimes assumed, it also reveals that the major part of the incoming Poynting flux is transferred to the thermal energy flux rather than to the convective kinetic energy flux, although the latter is generally supposed dominant. In the symmetric case, we propose the pressure tensor to be an additional proxy of the ion decoupling region in satellite data and verify this suggestion by studying a reconnection event encountered by the Cluster spacecrafts. Finally, the last part of this thesis is devoted to the study of the kinetic structure of asymmetric tangential current sheets where connection can develop. This theoretical part consists in finding a steady state solution to the Vlasov-Maxwell system for the protons in such a configuration. We present the theory and its first confrontation to numerical tests.

Aunai, icolas↗

NASA NTRS1986

Characteristic archaebacterial 16S rRNA oligonucleotides

A method of analyzing 16S rRNA catalog data has been developed in which groupings at various taxonomic levels can be characterized in terms of specific "signature" oligonucleotides. This approach provides an alternative means for evaluating higher order branching possibilities and can be used to assess the phylogenetic position of isolates that are poorly placed by the usual clustering procedures. This signature approach has been applied to forty archaebacterial catalogs and every oligonucleotide with significant signature value has been identified. Sets of specific oligonucleotides were identified for every major group on a dendrogram produced by cluster analysis procedures. Signatures that would establish between group relationships were also sought and found. In the case of the Methanobacteriaceae the clustering methods suggest a specific relationship to the Methanococcaceae. This inclusion is in fact supported by six strong signature oligonucleotides. However there are also significant numbers of signature oligonucleotides supporting a specific relationship of the Methanobacteriaceae to either the Halobacteriaceae or the Methanomicrobiaceae. Thus the placement of the Methanobacteriaceae is less certain than the usual dendrograms imply. The signature approach also was used to assess the phylogenetic position of Thermoplasma acidophilum which is found to be more closely related to the methanogen/halophile Division than to the sulfur dependent Division of the archaebacteria. This does not imply however that Thermoplasma acidophilum is properly regarded as being in the methanogen/halophile Division.

NASA Discipline Exobiology↗

NASA NTRS2016

Using Docker Containers to Extend Reproducibility Architecture for the NASA Earth Exchange (NEX)

NASA Earth Exchange (NEX) is a data, supercomputing and knowledge collaboratory that houses NASA satellite, climate and ancillary data where a focused community can come together to address large-scale challenges in Earth sciences. As NEX has been growing into a petabyte-size platform for analysis, experiments and data production, it has been increasingly important to enable users to easily retrace their steps, identify what datasets were produced by which process chains, and give them ability to readily reproduce their results. This can be a tedious and difficult task even for a small project, but is almost impossible on large processing pipelines. We have developed an initial reproducibility and knowledge capture solution for the NEX, however, if users want to move the code to another system, whether it is their home institution cluster, laptop or the cloud, they have to find, build and install all the required dependencies that would run their code. This can be a very tedious and tricky process and is a big impediment to moving code to data and reproducibility outside the original system. The NEX team has tried to assist users who wanted to move their code into OpenNEX on Amazon cloud by creating custom virtual machines with all the software and dependencies installed, but this, while solving some of the issues, creates a new bottleneck that requires the NEX team to be involved with any new request, updates to virtual machines and general maintenance support. In this presentation, we will describe a solution that integrates NEX and Docker to bridge the gap in code-to-data migration. The core of the solution is saemi-automatic conversion of science codes, tools and services that are already tracked and described in the NEX provenance system, to Docker - an open-source Linux container software. Docker is available on most computer platforms, easy to install and capable of seamlessly creating and/or executing any application packaged in the appropriate format. We believe this is an important step towards seamless process deployment in heterogeneous environments that will enhance community access to NASA data and tools in a scalable way, promote software reuse, and improve reproducibility of scientific results.

earth exchange↗

NASA NTRS1973

Unsupervised classification and areal measurement of land and water coastal features on the Texas coast

Multispectral scanner (MSS) digital data from ERTS-1 was used to delineate coastal land, vegetative, and water features in two portions of the Texas Coastal Zone. Data (Scene ID's 1037-16244 and 1037-16251) acquired on August 29, 1972, were analyzed on NASA Johnson Space Center systems through the use of two clustering algorithms. Seventeen to 30 spectrally homogeneous classes were so defined. Many classes were identified as being pure features such as water masses, salt marsh, beaches, pine, hardwoods, and exposed soil or construction materials. Most classes were identified to be mixtures of the pure class types. Using an objective technique for measuring the percentage of wetland along salt marsh boundaries, an analysis was made of the accuracy of areal measurement of salt marshes. Accuracies ranged from 89 to 99 percent. Aircraft photography was used as the basis for determining the true areal size of salt marshes in the study sites.

Flores, L. M.↗

NASA NTRS1995

Inductive Approaches to Improving Diagnosis and Design for Diagnosability

The first research area under this grant addresses the problem of classifying time series according to their morphological features in the time domain. A supervised learning system called CALCHAS, which induces a classification procedure for signatures from preclassified examples, was developed. For each of several signature classes, the system infers a model that captures the class's morphological features using Bayesian model induction and the minimum message length approach to assign priors. After induction, a time series (signature) is classified in one of the classes when there is enough evidence to support that decision. Time series with sufficiently novel features, belonging to classes not present in the training set, are recognized as such. A second area of research assumes two sources of information about a system: a model or domain theory that encodes aspects of the system under study and data from actual system operations over time. A model, when it exists, represents strong prior expectations about how a system will perform. Our work with a diagnostic model of the RCS (Reaction Control System) of the Space Shuttle motivated the development of SIG, a system which combines information from a model (or domain theory) and data. As it tracks RCS behavior, the model computes quantitative and qualitative values. Induction is then performed over the data represented by both the 'raw' features and the model-computed high-level features. Finally, work on clustering for operating mode discovery motivated some important extensions to the clustering strategy we had used. One modification appends an iterative optimization technique onto the clustering system; this optimization strategy appears to be novel in the clustering literature. A second modification improves the noise tolerance of the clustering system. In particular, we adapt resampling-based pruning strategies used by supervised learning systems to the task of simplifying hierarchical clusterings, thus making post-clustering analysis easier.

Fisher, Douglas H.↗

NASA NTRS2004

The Development of Two Science Investigator-led Processing Systems (SIPS) for NASA's Earth Observation System (EOS)

In 2001, NASA Goddard Space Flight Center's Laboratory for Terrestrial Physics started the construction of a science Investigator-led Processing System (SIPS) for processing data from the Ozone Monitoring Instrument (OMI) which will launch on the Aura platform in mid 2004. The Ozone Monitoring Instrument (OMI) is a contribution of the Netherlands Agency for Aerospace Programs (NIVR) in collaboration with the Finnish Meteorological Institute (FMI) to the Earth Observing System (EOS) Aura mission. It will continue the Total Ozone Monitoring System (TOMS) record for total ozone and other atmospheric parameters related to ozone chemistry and climate. OMI measurements will be highly synergistic with the other instruments on the EOS Aura platform. The LTP previously developed the Moderate Resolution Imaging Spectrometer (MODIS) Data Processing System (MODAPS), which has been in full operations since the launches of the Terra and Aqua spacecrafts in December, 1999 and May, 2002 respectively. During that time, it has continually evolved to better support the needs of the MODIS team. We now run multiple instances of the system managing faster than real time reprocessings of the data as well as continuing forward processing. The new OMI Data Processing System (OMIDAPS) was adapted from the MODAPS. It will ingest raw data from the satellite ground station and process it to produce calibrated, geolocated higher level data products. These data products will be transmitted to the Goddard Distributed Active Archive Center (GDAAC) instance of the Earth Observing System (EOS) Data and Information System (EOSDIS) for long term archive and distribution to the public. The OMIDAPS will also provide data distribution to the OMI Science Team for quality assessment, algorithm improvement, calibration, etc. We have taken advantage of lessons learned from the MODIS experience and software already developed for MODIS. We made some changes in the hardware system organization, database and software to adapt the system for OMI. We replaced the fundamental database system, Sybase, with an Open Source RDBMS called PostgreSQL, and based the entire OMIDAPS on a cluster of Linux based commodity computers rather than the large SGI servers that MODAPS uses. Rather than relying on a central I/O server host, the new system distributes its data archive among multiple server hosts in the cluster. OMI is also customizing the graphical user interfaces and reporting structure to more closely meet the needs of the OMI Science Team. Prior to 2003, simulated OMI data and the science algorithms were not ready for production testing. We initially constructed a prototype system and tested using a 25 year dataset of Total Ozone Mapping Spectrometer (TOMS) and Solar Backscatter Ultraviolet Instrument (SBUV) data. This prototype system provided a platform to support the adaptation of the algorithms for OMI, and provided reprocessing of the historical data aiding in its analysis. In a recent reanalysis of the TOMS data, the OMIDAPS processed 108,000 full orbits of data through 4 processing steps per orbit, producing about 800,000 files (400 GiB) of level 2 and greater data files. More recently we have installed two instances of the OMIDAPS for integration and testing of OM1 science processes as they get delivered from the Science Team. A Test instance of the OMIDAPS has also supported a series of "Interface Confidence Tests" (ICTs) and End-to-End Ground System tests to ensure the launch readiness of the system. This paper will discuss the high-level hardware, software, and database organization of the OMIDAPS and how it builds on the MODAPS heritage system. It will also provide an overview of the testing and implementation of the production OMIDAPS.

Tilmes, Curt↗

NASA NTRS1980

Sunspots and the physics of magnetic flux tubes. X - On the hydrodynamic instability of buoyant fields

The hydrodynamics of cylindrical buoyant bubbles (magnetic flux tubes) in an atmosphere is examined. Their dynamical stability is considered, with particular attention to the Rayleigh-Taylor and Kelvin-Helmholtz instabilities. The instabilities are sufficient to cause fragmentation in the absence of some strong stabilizing effect such as surface tension or an internal azimuthal magnetic field. The results of the stability analysis are first applied to rising gas bubbles in liquids. Then, since agreement with the experimental data is found, the results are applied to the similar problem of the rising magnetic flux in the sun. Magnetic flux tubes in a fluid velocity field are intrinsically unstable, unless twisted. With the known dynamical limits on the degree of twisting, an upper limit on the diameter of the order of a few hundred kilometers is found for the stability of individual flux tubes in the photosphere. Observations show that tubes, except when clustered to form sunspots, are generally not larger than this amount. Therefore, it is suggested that the hydrodynamic instability of larger tubes is a prime cause of their absence from the solar photosphere.

Tsinganos, K. C.↗

NASA NTRS1972

Lunar crater origin in the maria from analysis of Orbiter photographs.

Attempt to diagnose the origin of craters that are predominantly between 100 and 2000 m diam by the use of a statistical method that is capable of measuring both the chaining and clustering of craters. It is argued that craters with aligned centers that trend in parallel directions over vast distances are exclusively of internal origin. Strong evidence that a high proportion of the chains are of tectonic origin is found. Other criteria, such as a systematic change in the number density of craters over a test area or an excess of craters on a recent lava flow, are also used to argue for endogenic craters. Using all the data together, it is found that at least 33%, but not more than 51%, of the craters sampled are of endogenic origin. It is shown that the flux of meteoroids has not necessarily varied for the past few billion years.

Fielder, G.↗

NASA NTRS2011

Correlations in the (Sub)Mil1imeter Background from ACT x BLAST

We present measurements of the auto- and cross-frequency correlation power spectra of the cosmic (sub)millimeter background at: 250, 350, and 500 microns (1200, 860, and 600 GHz) from observations made with the Balloon-borne Large Aperture Submillimeter Telescope, BLAST; and at 1380 and 2030 microns (218 and 148 GHz) from observations made with the Atacama Cosmology Telescope, ACT. The overlapping observations cover 8.6 deg(sup 2) in an area relatively free of Galactic dust near the south ecliptic pole (SEP). The ACT bands are sensitive to radiation from the CMB, the Sunyaev-Zel'dovich (SZ) effect from galaxy clusters, and to emission by radio and dusty star-forming galaxies (DSFGs), while the dominant contribution to the BLAST bands is from DSFGs. We confirm and extend the BLAST analysis of clustering with an independent pipeline, and also detect correlations between the ACT and BLAST maps at over 25(sigma) significance, which we interpret as a detection of the DSFGs in the ACT maps. In addition to a Poisson component in the cross-frequency power spectra, we detect a clustered signal at 4(sigma), and using a model for the DSFG evolution and number counts, we successfully fit all our spectra with a linear clustering model and a bias that depends only on red shift and not on scale. Finally, the data are compared to, and generally agree with, phenomenological models for the DSFG population. This study represents a first of its kind, and demonstrates the constraining power of the cross-frequency correlation technique to constrain models for the DSFGs. Similar analyses with more data will impose tight constraints 011 future models.

Hajian, Amir↗

NASA NTRS1999

Analysis of Hipparcos Observations

The funds provided in this grant were used to analyze and publish results from Hipparcos observations. The PI was chosen for preferred access to Hipparcos data in 1983 for two programs. Those data, together with the published results in the Hipparcos Catalogue, were used to prepare a talk given at the Hipparcos symposium in Venice in May, 1997. The following papers also were supported by this grant: The Age-Related Properties of the HD 98800 System. HD 98800: A Unique Stellar System of Post-T Tauri Stars. High-Resolution Spectroscopy of Some Very Active Southern Stars. The Problem of Hipparcos Distances to Open Clusters. I. Constraints from Multicolor Main Sequence Fitting. The Problem of Hipparcos Distances to Open Clusters. II. Constraints from Nearby Field Stars.

Soderblom, David↗

NASA NTRS1991

Northern dwarf and low surface brightness galaxies. IV - The large-scale space distribution

Results are reported from a statistical analysis of published observational data on a sample of 860 northern dwarf and low-surface-brightness (D/LSB) galaxies with delta = 0 deg or greater and b between -40 and 40 deg, selected from the Uppsala General Catalogue of Galaxies (Nilson et al., 1973). The results are presented in extensive redshift/space maps, histograms, graphs and tables and characterized in detail. It is shown that the distribution of D/LSB galaxies closely resembles that of bright galaxies, apparently ruling out biased-star-formation models predicting a uniform distribution of D/LSBs. Although bright galaxies outside clusters are somewhat more clustered than the H I-rich D/LSBs, the latters' pairwise peculiar velocity (460 + or - 50 km/sec) is similar to that of the former.

Thuan, Trinh X.↗

NASA NTRS2004

Microbial Characterization During the Early Habitation of the International Space Station

An evaluation of the microbiota from air, water, and surface samples provided a baseline of microbial characterization onboard the International Space Station (ISS) to gain insight into bacterial and fungal contamination during the initial stages of construction and habitation. Using 16S genetic sequencing and rep-PCR, 63 bacterial strains were isolated for identification and fingerprinted for microbial tracking. Of the bacterial strains that were isolated and fingerprinted, 19 displayed similarity to each other. The use of these molecular tools allowed for the identification of bacteria not previously identified using automated biochemical analysis and provided a clear indication of the source of several ISS contaminants. Strains of Bradyrhizobium and Sphingomonas unable to be identified using sequencing were identified by comparison of rep-PCR DNA fingerprints. Distinct DNA fingerprints for several strains of Methylobacterium provided a clear indication of the source of an ISS water supply contaminant. Fungal and bacterial data acquired during monitoring do not suggest there is a current microbial hazard to the spacecraft, nor does any trend indicate a potential health risk. Previous spacecraft environmental analysis indicated that microbial contamination will increase with time and will require continued surveillance. Copyright 2004 Springer-Verlag.

Fungi/genetics↗

NASA NTRS2019

Astro2020 APC White Paper Project: The Simons Observatory

The Simons Observatory (SO) is a ground-based cosmic microwave background (CMB) experiment sited on Cerro Toco in the Atacama Desert in Chile that promises to provide breakthrough discoveries in fundamental physics, cosmology, and astrophysics. Supported by the Simons Foundation, the Heising-Simons Foundation, and with contributions from collaborating institutions, SO will see first light in 2021 and start a five year survey in 2022. SO has 287 collaborators from 12 countries and 53 institutions, including 85 students and 90 postdocs. The SO experiment in its currently funded form (‘SO-Nominal’) consists of three 0.4 m Small Aperture Telescopes (SATs) and one 6 m Large Aperture Telescope (LAT). Optimized for minimizing systematic errors in polarization measurements at large angular scales, the SATs will perform a deep, degree-scale survey of 10% of the sky to search for the signature of primordial gravitational waves. The LAT will survey 40% of the sky with arc-minute resolution. These observations will measure (or limit) the sum of neutrino masses, search for light relics, measure the early behavior of Dark Energy, and refine our understanding of the intergalactic medium, clusters and the role of feedback in galaxy formation. With up to ten times the sensitivity and five times the angular resolution of the Planck satellite, and roughly an order of magnitude increase in mapping speed over currently operating (“Stage 3”) experiments, SO will measure the CMB temperature and polarization fluctuations to exquisite precision in six frequency bands from 27 to 280 GHz. SO will rapidly advance CMB science while informing the design of future observatories such as CMB-S4. Construction of SO-Nominal is fully funded, and operations and data analysis are funded for part of the planned five-year observations. We will seek federal funding to complete the observations and analysis of SO-Nominal, at the $25M level. The SO has a low risk and cost efficient upgrade path – the 6 m LAT can accommodate almost twice the baseline number of detectors and the SATs can be duplicated at low cost. We will seek funding at the $75M level for an expansion of the SO (‘SO-Enhanced’) that fills the remaining focal plane in the LAT, adds three SATs, and extends operations by five years, substantially improving our science return. By this time SO may be operating as part of the larger CMB-S4 project. This white paper summarizes and extends material presented in, which describes the science goals of SO-Nominal, and which describe the instrument design.

Abitbol, Maximilian H.↗

NASA NTRSDate not supplied

What Went Wrong: A Survey of Wildfire UAS Mishaps through Named Entity Recognition

Increasingly, unmanned aircraft systems (UAS) are being applied to wildfire incidents for tasks such as mapping, aerial ignition, and delivery. As a result, incident reporting systems for wildfires are beginning to accumulate data related to UAS mishaps in wildfire response. In this research, we apply state-of-the-art natural language processing (NLP) techniques to develop a custom Named Entity Recognition (NER) model which extracts a Failure Modes and Effects Analysis (FMEA)-style survey of wildfire UAS mishaps reported in SAFECOM. The custom NER model is built by fine-tuning an existing (BERT) model, resulting in a generalizable NER model that can extract engineering relevant entities including failure modes, causes, effects, control processes, and recommendations from any failure-relevant text. Similar mishaps are clustered and reported as single rows within the FMEA. For each cluster, frequency, severity, and overall risk are computed. The methodology can be applied as part of a broader safety management system to track trends in mishaps and discover knowledge that can be utilized to improve safety outcomes and system performance.

Machine Learning↗

NASA NTRSDate not supplied

What Went Wrong: A Survey of Wildfire UAS Mishaps through Named Entity Recognition

Machine Learning↗