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At least 613 records · Page 34

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NASA NTRS1992

Computer Aids Delineation Of Boundaries In Farmlands

Computer-aided stratification (CAS) procedure developmental procedure of image-processing computer equipment and programs partly automating delineation of boundaries between areas. These areas, "primary sampling units", are images of primarily agricultural lands composed by melding digital Landsat Thematic Mapper data and Digital Line Graph data from United States Geological Survey. CAS output data used as inputs for subsequent sampling procedures from which statistics on uses of agricultural lands developed.

Slyle, R.↗

NASA NTRS2009

Integration of Engine, Plume, and CFD Analyses in Conceptual Design of Low-Boom Supersonic Aircraft

This paper documents an integration of engine, plume, and computational fluid dynamics (CFD) analyses in the conceptual design of low-boom supersonic aircraft, using a variable fidelity approach. In particular, the Numerical Propulsion Simulation System (NPSS) is used for propulsion system cycle analysis and nacelle outer mold line definition, and a low-fidelity plume model is developed for plume shape prediction based on NPSS engine data and nacelle geometry. This model provides a capability for the conceptual design of low-boom supersonic aircraft that accounts for plume effects. Then a newly developed process for automated CFD analysis is presented for CFD-based plume and boom analyses of the conceptual geometry. Five test cases are used to demonstrate the integrated engine, plume, and CFD analysis process based on a variable fidelity approach, as well as the feasibility of the automated CFD plume and boom analysis capability.

Li, Wu↗

NASA NTRS2014

Verification and Validation of the General Mission Analysis Tool (GMAT)

This paper describes the processes and results of Verification and Validation (V&V) efforts for the General Mission Analysis Tool (GMAT). We describe the test program and environments, the tools used for independent test data, and comparison results. The V&V effort produced approximately 13,000 test scripts that are run as part of the nightly buildtest process. In addition, we created approximately 3000 automated GUI tests that are run every two weeks. Presenting all test results are beyond the scope of a single paper. Here we present high-level test results in most areas, and detailed test results for key areas. The final product of the V&V effort presented in this paper was GMAT version R2013a, the first Gold release of the software with completely updated documentation and greatly improved quality. Release R2013a was the staging release for flight qualification performed at Goddard Space Flight Center (GSFC) ultimately resulting in GMAT version R2013b.

GMAT↗

NASA NTRS2017

Medical Data Architecture Project Capabilities and Design

Mission constraints will challenge the delivery of medical care on a long-term, deep space exploration mission. This type of mission will be restricted in the availability of medical knowledge, skills, procedures and resources to prevent, diagnose, and treat in-flight medical events. Challenges to providing medical care are anticipated, including resource and resupply constraints, delayed communications and no ability for medical evacuation. The Medical Data Architecture (MDA) project will enable medical care capability in this constrained environment. The first version of the system, called "Test Bed 1," includes capabilities for automated data collection, data storage and data retrieval to provide information to the Crew Medical Officer (CMO). Test Bed 1 seeks to establish a data architecture foundation and develop a scalable data management system through modular design and standardized interfaces. In addition, it will demonstrate to stakeholders the potential for an improved, automated, flow of data to and from the medical system over the current methods employed on the International Space Station (ISS). It integrates a set of external devices, software and processes, and a Subjective, Objective, Assessment, and Plan (SOAP) note commonly used by clinicians. Medical data like electrocardiogram plots, heart rate, skin temperature, respiration rate, medications taken, and more are collected from devices and stored in the Electronic Medical Records (EMR) system, and reported to crew and clinician. Devices integrated include the Astroskin biosensor vest and IMED CARDIAX electrocardiogram (ECG) device with INEED MD ECG Glove, and the NASA-developed Medical Dose Tracker application. The system is designed to be operated as a standalone system, and can be deployed in a variety of environments, from a laptop to a data center. The system is primarily composed of open-source software tools, and is designed to be modular, so new capabilities can be added. The software components and integration methods will be discussed.

Data architecture↗

NASA NTRS1995

Implementation of a state of the art automated system for the production of cloud/water vapor motion winds from geostationary satellites

The research objectives in this proposal were part of a continuing program at UW-CIMSS to develop and refine an automated geostationary satellite winds processing system which can be utilized in both research and operational environments. The majority of the originally proposed tasks were successfully accomplished, and in some cases the progress exceeded the original goals. Much of the research and development supported by this grant resulted in upgrades and modifications to the existing automated satellite winds tracking algorithm. These modifications were put to the test through case study demonstrations and numerical model impact studies. After being successfully demonstrated, the modifications and upgrades were implemented into the NESDIS algorithms in Washington DC, and have become part of the operational support. A major focus of the research supported under this grant attended to the continued development of water vapor tracked winds from geostationary observations. The fully automated UW-CIMSS tracking algorithm has been tuned to provide complete upper-tropospheric coverage from this data source, with data set quality close to that of operational cloud motion winds. Multispectral water vapor observations were collected and processed from several different geostationary satellites. The tracking and quality control algorithms were tuned and refined based on ground-truth comparisons and case studies involving impact on numerical model analyses and forecasts. The results have shown the water vapor motion winds are of good quality, complement the cloud motion wind data, and can have a positive impact in NWP on many meteorological scales.

Velden, Christopher↗

NASA NTRS1993

Digraph reliability model processing advances and applications

This paper describes a new algorithm, called SourceDoubls, which efficiently solves for singletons and doubletons of a digraph reliability model. Compared with previous methods, the SourceDoubls algorithm provides up to a two order of magnitude reduction in the amount of time required to solve large digraph models. This significant increase in model solution speed allows complex digraphs containing thousands of nodes to be used as knowledge bases for real time automated monitoring and diagnosis applications. Currently, an application to provide monitoring and diagnosis of the Space Station Freedom Data Management System is under development at NASA/Ames Research Center and NASA/Johnson Space Center. This paper contains an overview of this system and provides details of how it will use digraph models processed by the SourceDoubls algorithm to accomplish its task.

Iverson, D. L.↗

NASA NTRS1996

An Automated Mapping Processor using C-Band Interferometric SAR Data

We describe a processor which has been implemented to generate map products starting from C-band interferometric data. The first stage of the processor consists of the conventional interferometric synthetic aperture radar (SAR) processing producing a digital elevation model (DEM) and a SAR brightness image in sensor coordinates. In the second stage of processing, a land use classification map is obtained by using the DEM, brightness, and interferometric correlation layers. Auxiliary layers which include a drainage layer, a height gradient layer, a height error layer, an estimated penetration layer, and a shaded relief layer are also computed. In the final step, all UTM collocated layers are combined in a geographical information system (GIS) which allows for both hard copy map products and digital applications.

Rodriguez, E.↗

NASA NTRS1996

An Automated Mapping Processor Using C-Band Interferometric SAR Data

We present the description of a processor which has been implemented to generate map products starting from C-band interferometric data. The first stage of the processor consists of the conventional interferometric SAR processing producing a Digital Elevation Model (DEMs) and a SAR brightness image in sensor coordinates. In the second stage of processing, a land use classification map is obtained by using the DEM, brightness, and interferometric correlation layers. Auxiliary layers which include a drainage layer, a height gradient layer, a height error layer, an estimated penetration layer, and a shaded relief layer are also computed. In the final step, all UTM collocated layers are combined in a GIS system which allows for both hard copy map products and for digital applications.

Rodriguez, E.↗

NASA NTRS1996

An Automated Mapping Processor Using C-Band Interferometric SAR Data

processor↗

NASA NTRS2004

Automatic Generation of Algorithms for the Statistical Analysis of Planetary Nebulae Images

Analyzing data sets collected in experiments or by observations is a Core scientific activity. Typically, experimentd and observational data are &aught with uncertainty, and the analysis is based on a statistical model of the conjectured underlying processes, The large data volumes collected by modern instruments make computer support indispensible for this. Consequently, scientists spend significant amounts of their time with the development and refinement of the data analysis programs. AutoBayes [GF+02, FS03] is a fully automatic synthesis system for generating statistical data analysis programs. Externally, it looks like a compiler: it takes an abstract problem specification and translates it into executable code. Its input is a concise description of a data analysis problem in the form of a statistical model as shown in Figure 1; its output is optimized and fully documented C/C++ code which can be linked dynamically into the Matlab and Octave environments. Internally, however, it is quite different: AutoBayes derives a customized algorithm implementing the given model using a schema-based process, and then further refines and optimizes the algorithm into code. A schema is a parameterized code template with associated semantic constraints which define and restrict the template s applicability. The schema parameters are instantiated in a problem-specific way during synthesis as AutoBayes checks the constraints against the original model or, recursively, against emerging sub-problems. AutoBayes schema library contains problem decomposition operators (which are justified by theorems in a formal logic in the domain of Bayesian networks) as well as machine learning algorithms (e.g., EM, k-Means) and nu- meric optimization methods (e.g., Nelder-Mead simplex, conjugate gradient). AutoBayes augments this schema-based approach by symbolic computation to derive closed-form solutions whenever possible. This is a major advantage over other statistical data analysis systems which use numerical approximations even in cases where closed-form solutions exist. AutoBayes is implemented in Prolog and comprises approximately 75.000 lines of code. In this paper, we take one typical scientific data analysis problem-analyzing planetary nebulae images taken by the Hubble Space Telescope-and show how AutoBayes can be used to automate the implementation of the necessary anal- ysis programs. We initially follow the analysis described by Knuth and Hajian [KHO2] and use AutoBayes to derive code for the published models. We show the details of the code derivation process, including the symbolic computations and automatic integration of library procedures, and compare the results of the automatically generated and manually implemented code. We then go beyond the original analysis and use AutoBayes to derive code for a simple image segmentation procedure based on a mixture model which can be used to automate a manual preproceesing step. Finally, we combine the original approach with the simple segmentation which yields a more detailed analysis. This also demonstrates that AutoBayes makes it easy to combine different aspects of data analysis.

Fischer, Bernd↗

NASA NTRS1976

OAST Space Theme Workshop. Volume 3: Working group summary. 2: Data handling, communications (E-2). A. Statement. B. Technology needs (form 1). C. Priority assessment (form 2)

Technologies required to support the stated OAST thrust to increase information return by X1000, while reducing costs by a factor of 10 are identified. The most significant driver is the need for an overall end-to-end data system management technology. Maximum use of LSI component technology and trade-offs between hardware and software are manifest in most all considerations of technology needs. By far, the greatest need for data handling technology was identified for the space Exploration and Global Services themes. Major advances are needed in NASA's ability to provide cost effective mass reduction of space data, and automated assessment of earth looking imagery, with a concomitant reduction in cost per useful bit. A combined approach embodying end-to-end system analysis, with onboard data set selection, onboard data processing, highly parallel image processing (both ground and space), low cost, high capacity memories, and low cost user data distribution systems would be necessary.

Source record↗

NASA NTRS1978

Monitoring gypsy moth defoliation by applying change detection techniques to Landsat imagery

The overall objective of a research effort at NASA's Goddard Space Flight Center is to develop and evaluate digital image processing techniques that will facilitate the assessment of the intensity and spatial distribution of forest insect damage in Northeastern U.S. forests using remotely sensed data from Landsats 1, 2 and C. Automated change detection techniques are presently being investigated as a method of isolating the areas of change in the forest canopy resulting from pest outbreaks. In order to follow the change detection approach, Landsat scene correction and overlay capabilities are utilized to provide multispectral/multitemporal image files of 'defoliation' and 'nondefoliation' forest stand conditions.

Williams, D. L.↗

NASA NTRS1979

Methodology for error analysis and simulation of lidar aerosol measurements

A methodology is presented for objective and automated determination of the uncertainty in lidar aerosol measurements. This methodology is based on standard error-propagation procedures, a large data base on atmospheric behavior, and long experience in lidar data processing. Algebraic expressions for probable error are derived as a function of the relevant parameters. The validity of these expressions is then tested by making simulated measurements and analyses in which random errors of appropriate size are injected at proper steps of the measurement and analysis process. An illustrative example is given where the methodology is applied to a new lidar system now being used for airborne measurements of the stratospheric aerosol.

Russell, P. B.↗

NASA NTRS1983

Satellite freeze forecast system: Executive summary

A satellite-based temperature monitoring and prediction system consisting of a computer controlled acquisition, processing, and display system and the ten automated weather stations called by that computer was developed and transferred to the national weather service. This satellite freeze forecasting system (SFFS) acquires satellite data from either one of two sources, surface data from 10 sites, displays the observed data in the form of color-coded thermal maps and in tables of automated weather station temperatures, computes predicted thermal maps when requested and displays such maps either automatically or manually, archives the data acquired, and makes comparisons with historical data. Except for the last function, SFFS handles these tasks in a highly automated fashion if the user so directs. The predicted thermal maps are the result of two models, one a physical energy budget of the soil and atmosphere interface and the other a statistical relationship between the sites at which the physical model predicts temperatures and each of the pixels of the satellite thermal map.

Martsolf, J. D.↗

NASA NTRS1985

The star system: A production engineering approach to STS

A fundamental change to the way Space Transportation System flight preparation is done is documented. It involves (1) systematic restructuring the Space Transportation System flight preparation task, to minimize its R&D content; (2) development of the Space Transportation Automated Reconfiguration (STAR) system to structure and support the remaining work flow. STAR is an integrated software system providing automation and quality control mechanisms necessary to create a production-like process. This approach was implemented using tools and methodology developed by IBM under NASA contract, to produce payload flight data requirements. It offers increased product quality, reduced cost per flight, and greater responsiveness to change.

Angier, R. C.↗

NASA NTRS1986

Transportability, distributability and rehosting experience with a kernel operating system interface set

For the past two years, PRC has been transporting and installing a software engineering environment framework, the Automated Product control Environment (APCE), at a number of PRC and government sites on a variety of different hardware. The APCE was designed using a layered architecture which is based on a standardized set of interfaces to host system services. This interface set called the APCE Interface Set (AIS), was designed to support many of the same goals as the Common Ada Programming Support Environment (APSE) Interface Set (CAIS). The APCE was developed to provide support for the full software lifecycle. Specific requirements of the APCE design included: automation of labor intensive administrative and logistical tasks: freedom for project team members to use existing tools: maximum transportability for APCE programs, interoperability of APCE database data, and distributability of both processes and data: and maximum performance on a wide variety of operating systems. A brief description is given of the APCE and AIS, a comparison of the AIS and CAIS both in terms of functionality and of philosophy and approach and a presentation of PRC's experience in rehosting AIS and transporting APCE programs and project data. Conclusions are drawn from this experience with respect to both the CAIS efforts and Space Station plans.

Blumberg, F. C.↗

NASA NTRS1993

Optimization of knowledge-based systems and expert system building tools

The objectives of the NASA-AMES Cooperative Agreement were to investigate, develop, and evaluate, via test cases, the system parameters and processing algorithms that constrain the overall performance of the Information Sciences Division's Artificial Intelligence Research Facility. Written reports covering various aspects of the grant were submitted to the co-investigators for the grant. Research studies concentrated on the field of artificial intelligence knowledge-based systems technology. Activities included the following areas: (1) AI training classes; (2) merging optical and digital processing; (3) science experiment remote coaching; (4) SSF data management system tests; (5) computer integrated documentation project; (6) conservation of design knowledge project; (7) project management calendar and reporting system; (8) automation and robotics technology assessment; (9) advanced computer architectures and operating systems; and (10) honors program.

Yasuda, Phyllis↗

NASA NTRS2005

The Optimization of Trained and Untrained Image Classification Algorithms for Use on Large Spatial Datasets

The HARVIST project seeks to automatically provide an accurate, interactive interface to predict crop yield over the entire United States. In order to accomplish this goal, large images must be quickly and automatically classified by crop type. Current trained and untrained classification algorithms, while accurate, are highly inefficient when operating on large datasets. This project sought to develop new variants of two standard trained and untrained classification algorithms that are optimized to take advantage of the spatial nature of image data. The first algorithm, harvist-cluster, utilizes divide-and-conquer techniques to precluster an image in the hopes of increasing overall clustering speed. The second algorithm, harvistSVM, utilizes support vector machines (SVMs), a type of trained classifier. It seeks to increase classification speed by applying a "meta-SVM" to a quick (but inaccurate) SVM to approximate a slower, yet more accurate, SVM. Speedups were achieved by tuning the algorithm to quickly identify when the quick SVM was incorrect, and then reclassifying low-confidence pixels as necessary. Comparing the classification speeds of both algorithms to known baselines showed a slight speedup for large values of k (the number of clusters) for harvist-cluster, and a significant speedup for harvistSVM. Future work aims to automate the parameter tuning process required for harvistSVM, and further improve classification accuracy and speed. Additionally, this research will move documents created in Canvas into ArcGIS. The launch of the Mars Reconnaissance Orbiter (MRO) will provide a wealth of image data such as global maps of Martian weather and high resolution global images of Mars. The ability to store this new data in a georeferenced format will support future Mars missions by providing data for landing site selection and the search for water on Mars.

Kocurek, Michael J.↗