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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Image Segmentation, Registration, Compression, and Matching

A novel computational framework was developed of a 2D affine invariant matching exploiting a parameter space. Named as affine invariant parameter space (AIPS), the technique can be applied to many image-processing and computer-vision problems, including image registration, template matching, and object tracking from image sequence. The AIPS is formed by the parameters in an affine combination of a set of feature points in the image plane. In cases where the entire image can be assumed to have undergone a single affine transformation, the new AIPS match metric and matching framework becomes very effective (compared with the state-of-the-art methods at the time of this reporting). No knowledge about scaling or any other transformation parameters need to be known a priori to apply the AIPS framework. An automated suite of software tools has been created to provide accurate image segmentation (for data cleaning) and high-quality 2D image and 3D surface registration (for fusing multi-resolution terrain, image, and map data). These tools are capable of supporting existing GIS toolkits already in the marketplace, and will also be usable in a stand-alone fashion. The toolkit applies novel algorithmic approaches for image segmentation, feature extraction, and registration of 2D imagery and 3D surface data, which supports first-pass, batched, fully automatic feature extraction (for segmentation), and registration. A hierarchical and adaptive approach is taken for achieving automatic feature extraction, segmentation, and registration. Surface registration is the process of aligning two (or more) data sets to a common coordinate system, during which the transformation between their different coordinate systems is determined. Also developed here are a novel, volumetric surface modeling and compression technique that provide both quality-guaranteed mesh surface approximations and compaction of the model sizes by efficiently coding the geometry and connectivity/topology components of the generated models. The highly efficient triangular mesh compression compacts the connectivity information at the rate of 1.5-4 bits per vertex (on average for triangle meshes), while reducing the 3D geometry by 40-50 percent. Finally, taking into consideration the characteristics of 3D terrain data, and using the innovative, regularized binary decomposition mesh modeling, a multistage, pattern-drive modeling, and compression technique has been developed to provide an effective framework for compressing digital elevation model (DEM) surfaces, high-resolution aerial imagery, and other types of NASA data.

Yadegar, Jacob↗
NASA NTRS2019

Three Red Suns in the Sky: A Transiting, Terrestrial Planet in a Triple M-dwarf System at 6.9 pc

We present the discovery from Transiting Exoplanet Survey Satellite (TESS) data of LTT 1445Ab. At a distance of 6.9 pc, it is the second nearest transiting exoplanet system found to date, and the closest one known for which the primary is an M dwarf. The host stellar system consists of three mid-to-late M dwarfs in a hierarchical configuration, which are blended in one TESS pixel. We use MEarth data and results from the Science Processing Operations Center data validation report to determine that the planet transits the primary star in the system. The planet has a radius of {1.38}_{-0.12}^{+0.13} {R}_{\oplus }, an orbital period of {5.35882}_{-0.00031}^{+0.00030} days, and an equilibrium temperature of {433}_{-27}^{+28} K. With radial velocities from the High Accuracy Radial Velocity Planet Searcher, we place a 3σ upper mass limit of 8.4 {M}_{\oplus } on the planet. LTT 1445Ab provides one of the best opportunities to date for the spectroscopic study of the atmosphere of a terrestrial world. We also present a detailed characterization of the host stellar system. We use high-resolution spectroscopy and imaging to rule out the presence of any other close stellar or brown dwarf companions. Nineteen years of photometric monitoring of A and BC indicate a moderate amount of variability, in agreement with that observed in the TESS light-curve data. We derive a preliminary astrometric orbit for the BC pair that reveals an edge-on and eccentric configuration. The presence of a transiting planet in this system hints that the entire system may be co-planar, implying that the system may have formed from the early fragmentation of an individual protostellar core.

Binaries↗
NASA NTRS1993

Parallel Consensual Neural Networks

A new neural network architecture is proposed and applied in classification of remote sensing/geographic data from multiple sources. The new architecture is called the parallel consensual neural network and its relation to hierarchical and ensemble neural networks is discussed. The parallel consensual neural network architecture is based on statistical consensus theory. The input data are transformed several times and the different transformed data are applied as if they were independent inputs and are classified using stage neural networks. Finally, the outputs from the stage networks are then weighted and combined to make a decision. Experimental results based on remote sensing data and geographic data are given. The performance of the consensual neural network architecture is compared to that of a two-layer (one hidden layer) conjugate-gradient backpropagation neural network. The results with the proposed neural network architecture compare favorably in terms of classification accuracy to the backpropagation method.

Benediktsson, J. A.↗
NASA NTRS1992

Refining image segmentation by integration of edge and region data

An iterative parallel region growing (IPRG) algorithm previously developed by Tilton (1989) produces hierarchical segmentations of images from finer to coarser resolution. An ideal segmentation does not always correspond to one single iteration but to several different ones, each one producing the 'best' result for a separate part of the image. With the goal of finding this ideal segmentation, the results of the IPRG algorithm are refined by utilizing some additional information, such as edge features, and by interpreting the tree of hierarchical regions.

Le Moigne, Jacqueline↗
NASA NTRS1981

Overview of the current MITRE effort

A logical view of the applications data service (ADS) as a distributed system was adopted. A hierarchical classification scheme of ADS features comprising 70 modes was developed. The framework for a preliminary assessment of the applicability Federal, national, and international standards to ADS was provided by the classification. Approximately 300 standards were gathered, screened, and documented. The survey was enlarged to incorporate standards from NASA headquarters and centers. Two efforts were initiated to (1) survey methodologies of the three ADS pilots, and (2) identify the requirements for standards of ADS members based on a survey of the pilots and on representative future members. Preliminary results of the requirements survey were used in the development of criteria for the evaluation of candidate standards. An evaluation process was designed incorporating these criteria.

Kuch, T.↗
NASA NTRS1989

A procedure concept for local reflex control of grasping

An architecture is proposed for the control of robotic devices, and in particular of anthropomorphic hands, characterized by a hierarchical structure in which every level of the architecture contains data and control function with varying degree of abstraction. Bottom levels of the hierarchy interface directly with sensors and actuators, and process raw data and motor commands. Higher levels perform more symbolic types of tasks, such as application of boolean rules and general planning operations. Layers implementation has to be consistent with the type of operation and its requirements for real time control. It is proposed to implement the rule level with a Boolean Artificial Neural Network characterized by a response time sufficient for producing reflex corrective action at the actuator level.

Fiorini, Paolo↗
NASA NTRS1989

Autonomous organization of grasping tasks

This paper describes an architecture for the control of robotic devices, and in particular of anthropomorphic hands, characterized by a hierarchical structure in which every level of the architecture contains data and control function with varying degree of abstraction. Bottom levels of the hierarchy interface directly with sensors and actuators, and process raw data and motor commands. Higher levels perform more symbolic types of tasks, such as application of Boolean rules and general planning operations. The implementation of the layer has to be consistent with the type of operation and its requirements for real time control. One implementation of the rule level, with a Boolean artificial neural network which would have a response time sufficient for producing reflex corrective action at the actuator level is presented.

Fiorini, Paolo↗
NASA NTRS2001

Highly parallel structured adaptive mesh refinement using parallel language-based approaches

Adaptive mesh refinement (AMR) calculations carried out on structured meshes play an exceedingly important role in several areas of science and engineering. A strategy for using Fortran 90 in an object-oriented fashion is presented. This permits AMR applications to be expressed in terms of familiar abstractions that are natural to the process of solving AMR hierarchies. The OpenMP features that are useful for parallel processing of AMR hierarchies in a load balanced fashion on multiprocessors is described.

computational↗
NASA NTRS1996

Hierarchical and Parallelizable Direct Volume Rendering for Irregular and Multiple Grids

A general volume rendering technique is described that efficiently produces images of excellent quality from data defined over irregular grids having a wide variety of formats. Rendering is done in software, eliminating the need for special graphics hardware, as well as any artifacts associated with graphics hardware. Images of volumes with about one million cells can be produced in one to several minutes on a workstation with a 150 MHz processor. A significant advantage of this method for applications such as computational fluid dynamics is that it can process multiple intersecting grids. Such grids present problems for most current volume rendering techniques. Also, the wide range of cell sizes (by a factor of 10,000 or more), which is typical of such applications, does not present difficulties, as it does for many techniques. A spatial hierarchical organization makes it possible to access data from a restricted region efficiently. The tree has greater depth in regions of greater detail, determined by the number of cells in the region. It also makes it possible to render useful 'preview' images very quickly (about one second for one-million-cell grids) by displaying each region associated with a tree node as one cell. Previews show enough detail to navigate effectively in very large data sets. The algorithmic techniques include use of a kappa-d tree, with prefix-order partitioning of triangles, to reduce the number of primitives that must be processed for one rendering, coarse-grain parallelism for a shared-memory MIMD architecture, a new perspective transformation that achieves greater numerical accuracy, and a scanline algorithm with depth sorting and a new clipping technique.

Wilhelms, Jane↗
NASA NTRS2004

Hierarchical Velocity Structure in the Core of Abell 2597

We present XMM-Newton RGS and EPIC data of the putative cooling flow cluster Abell 2597. Velocities of the low-ionization emission lines in the spectrum are blue shifted with respect to the high-ionization lines by 1320 (sup +660) (sub -210) kilometers per second, which is consistent with the difference in the two peaks of the galaxy velocity distribution and may be the signature of bulk turbulence, infall, rotation or damped oscillation in the cluster. A hierarchical velocity structure such as this could be the direct result of galaxy mergers in the cluster core, or the injection of power into the cluster gas from a central engine. The uniform X-ray morphology of the cluster, the absence of fine scale temperature structure and the random distribution of the the galaxy positions, independent of velocity, suggests that our line of sight is close to the direction of motion. These results have strong implications for cooling flow models of the cluster Abell 2597. They give impetus to those models which account for the observed temperature structure of some clusters using mergers instead of cooling flows.

Still, Martin↗
NASA NTRS1978

Design representation and consistency maintenance needs

Two major issues of data base support for large-scale engineering design are considered. The first deals with the need to support multidisciplinary, hierarchical and interactive design without imposing a priori constraints on the sequence of design decisions. An abstract logical model of the data base capable of such support is outlined. The second issue deals with the role the data base must play in maintaining integrity and consistency among the data representing the emerging design. A tentative model implementing a number of consistency management functions is presented.

Eastman, C. M.↗
NASA NTRS2017

Nominal 30-M Cropland Extent Map of Continental Africa by Integrating Pixel-Based and Object-Based Algorithms Using Sentinel-2 and Landsat-8 Data on Google Earth Engine

A satellite-derived cropland extent map at high spatial resolution (30-m or better) is a must for food and water security analysis. Precise and accurate global cropland extent maps, indicating cropland and non-cropland areas, is a starting point to develop high-level products such as crop watering methods (irrigated or rainfed), cropping intensities (e.g., single, double, or continuous cropping), crop types, cropland fallows, as well as assessment of cropland productivity (productivity per unit of land), and crop water productivity (productivity per unit of water). Uncertainties associated with the cropland extent map have cascading effects on all higher-level cropland products. However, precise and accurate cropland extent maps at high spatial resolution over large areas (e.g., continents or the globe) are challenging to produce due to the small-holder dominant agricultural systems like those found in most of Africa and Asia. Cloud-based Geospatial computing platforms and multi-date, multi-sensor satellite image inventories on Google Earth Engine offer opportunities for mapping croplands with precision and accuracy over large areas that satisfy the requirements of broad range of applications. Such maps are expected to provide highly significant improvements compared to existing products, which tend to be coarser in resolution, and often fail to capture fragmented small-holder farms especially in regions with high dynamic change within and across years. To overcome these limitations, in this research we present an approach for cropland extent mapping at high spatial resolution (30-m or better) using the 10-day, 10 to 20-m, Sentinel-2 data in combination with 16-day, 30-m, Landsat-8 data on Google Earth Engine (GEE). First, nominal 30-m resolution satellite imagery composites were created from 36,924 scenes of Sentinel-2 and Landsat-8 images for the entire African continent in 2015-2016. These composites were generated using a median-mosaic of five bands (blue, green, red, near-infrared, NDVI) during each of the two periods (period 1: January-June 2016 and period 2: July-December 2015) plus a 30-m slope layer derived from the Shuttle Radar Topographic Mission (SRTM) elevation dataset. Second, we selected Cropland/Non-cropland training samples (sample size 9791) from various sources in GEE to create pixel-based classifications. As supervised classification algorithm, Random Forest (RF) was used as the primary classifier because of its efficiency, and when over-fitting issues of RF happened due to the noise of input training data, Support Vector Machine (SVM) was applied to compensate for such defects in specific areas. Third, the Recursive Hierarchical Segmentation (RHSeg) algorithm was employed to generate an object-oriented segmentation layer based on spectral and spatial properties from the same input data. This layer was merged with the pixel-based classification to improve segmentation accuracy. Accuracies of the merged 30-m crop extent product were computed using an error matrix approach in which 1754 independent validation samples were used. In addition, a comparison was performed with other available cropland maps as well as with LULC maps to show spatial similarity. Finally, the cropland area results derived from the map were compared with UN FAO statistics. The independent accuracy assessment showed a weighted overall accuracy of 94, with a producers accuracy of 85.9 (or omission error of 14.1), and users accuracy of 68.5 (commission error of 31.5) for the cropland class. The total net cropland area (TNCA) of Africa was estimated as 313 Mha for the nominal year 2015.

Cropland mapping; cropland areas; 30-m; Landsat-8;↗
NASA NTRS1997

Sulfur in Cometary Dust

The computer-intensive project consisted of the analysis and synthesis of existing data on composition of comet Halley dust particles. The main objective was to obtain a complete inventory of sulfur containing compounds in the comet Halley dust by building upon the existing classification of organic and inorganic compounds and applying a variety of statistical techniques for cluster and cross-correlational analyses. A student hired for this project wrote and tested the software to perform cluster analysis. The following tasks were carried out: (1) selecting the data from existing database for the proposed project; (2) finding access to a standard library of statistical routines for cluster analysis; (3) reformatting the data as necessary for input into the library routines; (4) performing cluster analysis and constructing hierarchical cluster trees using three methods to define the proximity of clusters; (5) presenting the output results in different formats to facilitate the interpretation of the obtained cluster trees; (6) selecting groups of data points common for all three trees as stable clusters. We have also considered the chemistry of sulfur in inorganic compounds.

Fomenkova, M. N.↗
NASA NTRS2020

Dynamic IT Security Database and Analytics for Launch Control Systems Software

During the Summer 2020 session, I worked with intern Destani S. Van Arsdalen of EGS Software. Together, we co-created a tool to aid the dynamic investigation, updated over time,of the security compliance of LCS COTS and open source software. We originally planned touse spreadsheet software for management and analysis, but through this exploratoryproject, chose to use Python and JSON after receiving feedback on our project’s current anddesired capabilities at that time.At first, the project was solely designed to help on-board new COTS software, based on aquestionnaire that could be filled out for each software package. This, combined with usingthe spreadsheet application’s web-query capabilities to fetch information from the NVD,allowed presentation and analytics cells to automatically populate as elements of themanually-filled questionnaire changed. While this system was promising, we decided tochange technologies for a few reasons. In the spreadsheet, single cells could not hold complexdata like arrays and objects. The automatic population of cells and dynamic updates made itdifficult to manage and add new features. And finally, it had limited extensibility sinceadding new software required significant understanding of how both the spreadsheet wasconstructed, and the more obscure, proprietary scripting languages packaged with it.The pivot to a standard computer science database language of JSON, aided by thescripting capabilities of Python, greatly helped to improve the project’s functionality. First,and most importantly, the script’s import and analysis of database data is easilyreproducible. Additional data analysis can be modularly added without requiringmodification of the script and is capable of routine scheduling. The revised process can besplit into three parts. First, the conversion of LCS asset and software documentation into theJSON hierarchical database format. Second, the merging of this database with the NVD,forming a new data structure, using CPEs of the CVE object as a linking element betweenthem. And third, the automatically performed analytics and analysis of the combined data,in a modular and extensible format, to produce better informed business decisions. The outputted graphs, for example, are automatically generated by the Python script inconnection with the combined database. This allows updated graphs and any analytics to be re-rendered automatically following updates to the LCS’s initial asset documentation. Afinal report can then be programmatically and easily constructed from these sources to allow fully reproducible metrics for heavily evidenced risk management decisions.

it↗
NASA NTRSDate not supplied

Open Science for Plants in Space: Improvements in NASA's Open Science Data Repository

Upcoming deep space missions will rely on plants for crew and ecosystem health. Open access space biology data enables scientists to examine the biological responses of plants to ionizing radiation, altered gravity, elevated CO2, and many other abiotic stressors. NASA has declared 2023 as the ‘Year of Open Science’ and created a 5-year Transform to Open Science (TOPS) initiative designed to rapidly transform the agency toward an inclusive culture of open science. NASA’s Open Science Data Repository (OSDR) combines two databases, GeneLab and Ames Life Sciences Data Archive (ALSDA) to maximize access to standardized ‘omics (e.g., transcriptomics, proteomics) and phenotypic data (e.g., microscopy, biomass), respectively. Current OSDR standards include the ISA (Investigation-Study-Assay) experiment model, assay metadata configurations, and standardized terminology and ontologies. In 2024 OSDR will include a new suite of features for improved FAIR compliance including downloadable plant metadata templates, data submission tools and overall improved AI-readiness of plant datasets. AI/ML methods can be helpful tools to overcome the inherent challenges of space biology research (small sample size, sparse and heterogeneous data etc.). However these methods are built on an assumption of normalized and well-curated data. OSDR’s new curation tools will improve users ability to leverage ML and AI methods to model space biology data and better understand the complex effects of spaceflight on living systems across hierarchical biological levels. We look forward to sharing our advances with the spaceflight community.

FAIR↗
NASA NTRS2022

Planet Hunters TESS IV: A Massive, Compact Hierarchical Triple Star System TIC 470710327

We report the discovery and analysis of a massive, compact, hierarchical triple system (TIC 470710327) initially identified by citizen scientists in data obtained by NASA’s Transiting Exoplanet Survey Satellite (TESS). Spectroscopic follow-up observations obtained with the HERMES spectrograph, combined with eclipse-timing variations (ETVs), confirm that the system is comprised of three OB stars, with a compact 1.10 d eclipsing binary and a non-eclipsing tertiary on a 52.04 d orbit. Dynamical modelling of the system (from radial velocity and ETVs) reveal a rare configuration wherein the tertiary star (O9.5-B0.5V; 14–17 M ꙩ ) is more massive than the combined mass of the inner binary (10.9–13.2 M ꙩ ). Given the high mass of the tertiary, we predict that this system will undergo multiple phases of mass transfer in the future, and likely end up as a double neutron star gravitational wave progenitor or an exotic Thorne–Żytkow object. Further observational characterization of this system promises constraints on both formation scenarios of massive stars as well as their exotic evolutionary end-products.

NASA's Transiting Exoplanet Survey Satellite (TESS↗
NASA NTRS1988

Multiple directed graph large-class multi-spectral processor

Numerical analysis techniques for the interpretation of high-resolution imaging-spectrometer data are described and demonstrated. The method proposed involves the use of (1) a hierarchical classifier with a tree structure generated automatically by a Fisher linear-discriminant-function algorithm and (2) a novel multiple-directed-graph scheme which reduces the local maxima and the number of perturbations required. Results for a 500-class test problem involving simulated imaging-spectrometer data are presented in tables and graphs; 100-percent-correct classification is achieved with an improvement factor of 5.

Casasent, David↗