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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS1978

Pattern recognition methods and air pollution source identification

Directional air samplers, used for resolving suspended particulate matter on the basis of time and wind direction were used to assess the feasibility of characterizing and identifying emission source types in urban multisource environments. Filters were evaluated for 16 elements and X-ray fluorescence methods yielded elemental concentrations for direction, day, and the interaction of direction and day. Large numbers of samples are necessary to compensate for large day-to-day variations caused by wind perturbations and/or source changes.

Leibecki, H. F.↗
NASA NTRS2003

Gene Expression Dynamics Inspector (GEDI): for integrative analysis of expression profiles

Genome-wide expression profiles contain global patterns that evade visual detection in current gene clustering analysis. Here, a Gene Expression Dynamics Inspector (GEDI) is described that uses self-organizing maps to translate high-dimensional expression profiles of time courses or sample classes into animated, coherent and robust mosaics images. GEDI facilitates identification of interesting patterns of molecular activity simultaneously across gene, time and sample space without prior assumption of any structure in the data, and then permits the user to retrieve genes of interest. Important changes in genome-wide activities may be quickly identified based on 'Gestalt' recognition and hence, GEDI may be especially useful for non-specialist end users, such as physicians. AVAILABILITY: GEDI v1.0 is written in Matlab, and binary Matlab.dll files which require Matlab to run can be downloaded for free by academic institutions at http://www.chip.org/~ge/gedihome.html Supplementary information: http://www.chip.org/~ge/gedihome.html.

Database Management Systems↗
NASA NTRS1991

Pattern-recognition techniques applied to performance monitoring of the DSS 13 34-meter antenna control assembly

The results of applying pattern recognition techniques to diagnose fault conditions in the pointing system of one of the Deep Space network's large antennas, the DSS 13 34-meter structure, are discussed. A previous article described an experiment whereby a neural network technique was used to identify fault classes by using data obtained from a simulation model of the Deep Space Network (DSN) 70-meter antenna system. Described here is the extension of these classification techniques to the analysis of real data from the field. The general architecture and philosophy of an autonomous monitoring paradigm is described and classification results are discussed and analyzed in this context. Key features of this approach include a probabilistic time-varying context model, the effective integration of signal processing and system identification techniques with pattern recognition algorithms, and the ability to calibrate the system given limited amounts of training data. Reported here are recognition accuracies in the 97 to 98 percent range for the particular fault classes included in the experiments.

Mellstrom, J. A.↗
NASA NTRS2012

QuakeSim 2.0

QuakeSim 2.0 improves understanding of earthquake processes by providing modeling tools and integrating model applications and various heterogeneous data sources within a Web services environment. QuakeSim is a multisource, synergistic, data-intensive environment for modeling the behavior of earthquake faults individually, and as part of complex interacting systems. Remotely sensed geodetic data products may be explored, compared with faults and landscape features, mined by pattern analysis applications, and integrated with models and pattern analysis applications in a rich Web-based and visualization environment. Integration of heterogeneous data products with pattern informatics tools enables efficient development of models. Federated database components and visualization tools allow rapid exploration of large datasets, while pattern informatics enables identification of subtle, but important, features in large data sets. QuakeSim is valuable for earthquake investigations and modeling in its current state, and also serves as a prototype and nucleus for broader systems under development. The framework provides access to physics-based simulation tools that model the earthquake cycle and related crustal deformation. Spaceborne GPS and Inter ferometric Synthetic Aperture (InSAR) data provide information on near-term crustal deformation, while paleoseismic geologic data provide longerterm information on earthquake fault processes. These data sources are integrated into QuakeSim's QuakeTables database system, and are accessible by users or various model applications. UAVSAR repeat pass interferometry data products are added to the QuakeTables database, and are available through a browseable map interface or Representational State Transfer (REST) interfaces. Model applications can retrieve data from Quake Tables, or from third-party GPS velocity data services; alternatively, users can manually input parameters into the models. Pattern analysis of GPS and seismicity data has proved useful for mid-term forecasting of earthquakes, and for detecting subtle changes in crustal deformation. The GPS time series analysis has also proved useful as a data-quality tool, enabling the discovery of station anomalies and data processing and distribution errors. Improved visualization tools enable more efficient data exploration and understanding. Tools provide flexibility to science users for exploring data in new ways through download links, but also facilitate standard, intuitive, and routine uses for science users and end users such as emergency responders.

Donnellan, Andrea↗
NASA NTRS2015

A Wavelet Analysis Approach for Categorizing Air Traffic Behavior

In this paper two frequency domain techniques are applied to air traffic analysis. The Continuous Wavelet Transform (CWT), like the Fourier Transform, is shown to identify changes in historical traffic patterns caused by Traffic Management Initiatives (TMIs) and weather with the added benefit of detecting when in time those changes take place. Next, with the expectation that it could detect anomalies in the network and indicate the extent to which they affect traffic flows, the Spectral Graph Wavelet Transform (SGWT) is applied to a center based graph model of air traffic. When applied to simulations based on historical flight plans, it identified the traffic flows between centers that have the greatest impact on either neighboring flows, or flows between centers many centers away. Like the CWT, however, it can be difficult to interpret SGWT results and relate them to simulations where major TMIs are implemented, and more research may be warranted in this area. These frequency analysis techniques can detect off-nominal air traffic behavior, but due to the nature of air traffic time series data, so far they prove difficult to apply in a way that provides significant insight or specific identification of traffic patterns.

wavelet analysis↗
NASA NTRS1972

Vegetation-terrain feature relationships in southeast Arizona

There are no author-identified significant results in this report. Studies of relationships of vegetation distribution to geomorphic characteristics of the landscape and of plant phenological patterns to vegetation identification of satellite imagery indicate that there exists positive relationships between certain plant species and certain terrain features. Not all species were found to exhibit positive relationships with all terrain feature variables, but enough positive relationships seem to exist to indicate that terrain feature variable-vegetation relationship studies have a definite place in plant ecological investigations. Even more importantly, the vegetation groups examined appeared to be successfully discriminated by the terrain feature variables. This would seem to indicate that spatial interpretations of vegetation groups may be possible. While vegetational distributions aren't determined by terrain feature differences, terrain features do mirror factors which directly influence vegetational response and hence distribution. As a result, those environmental features which can be readily and rapidly ascertained on relatively small-scale imagery may prove to be valuable indicators of vegetation distribution.

Schrumpf, B. J.↗
NASA NTRS1977

Investigations using data from LANDSAT-2

The author has identified the following significant results. New lands for forestation were set aside in the coastal area of Bangladesh, based on LANDSAT mosaics (Chittagong - 195,000 acres, Noakhali - 450,000 acres, Barisal - 360,000 acres, and Patuakhali - 225,000 acres). LANDSAT imageries were used for identification of drainage patterns in both the old and and new Comilla district.

Hossain, A.↗
NASA NTRS1988

European sources of halocarbons and nitrous oxide - Update 1986

New information on seasonal and secular trends in the releases of CFCl3, CF2Cl2, CCl4, CH3CCl3, and N20 from Europe was obtained as part of the Atmospheric Lifetime Experiment. Semicontinuous measurements of these pollutants were made at Adrigole, Ireland, using lean air from the Atlantic Ocean as a baseline. The results obtained include unambiguous evidence for elevated levels of N2O occurring concurrent with halocarbon pollution events; the detection of trends in the relative emission of different halocarbons; the discovery of seasonal variations in emission of CF2Cl2, CCl4, and CH3Cl3; the characterization of typical summer and winter pollution episodes; and the identification of weather patterns over Europe that are associated with high concentrations of chlorofluorocarbons at Adrigole. It was estimated that the European source of N2O represents 25 percent of the global emissions associated with combustion and 10 percent of the integrated stratospheric losses.

Prather, Michael↗
NASA NTRS1993

Develop advanced nonlinear signal analysis topographical mapping system

The SSME has been undergoing extensive flight certification and developmental testing, which involves some 250 health monitoring measurements. Under the severe temperature pressure, and dynamic environments sustained during operation, numerous major component failures have occurred, resulting in extensive engine hardware damage and scheduling losses. To enhance SSME safety and reliability, detailed analysis and evaluation of the measurements signal are mandatory to assess its dynamic characteristics and operational condition. Efficient and reliable signal detection techniques will reduce catastrophic system failure risks and expedite the evaluation of both flight and ground test data, and thereby reduce launch turn-around time. The basic objective of this contract are threefold: (1) Develop and validate a hierarchy of innovative signal analysis techniques for nonlinear and nonstationary time-frequency analysis. Performance evaluation will be carried out through detailed analysis of extensive SSME static firing and flight data. These techniques will be incorporated into a fully automated system. (2) Develop an advanced nonlinear signal analysis topographical mapping system (ATMS) to generate a Compressed SSME TOPO Data Base (CSTDB). This ATMS system will convert tremendous amounts of complex vibration signals from the entire SSME test history into a bank of succinct image-like patterns while retaining all respective phase information. A high compression ratio can be achieved to allow the minimal storage requirement, while providing fast signature retrieval, pattern comparison, and identification capabilities. (3) Integrate the nonlinear correlation techniques into the CSTDB data base with compatible TOPO input data format. Such integrated ATMS system will provide the large test archives necessary for a quick signature comparison. This study will provide timely assessment of SSME component operational status, identify probable causes of malfunction, and indicate feasible engineering solutions. The final result of this program will yield an ATMS system of nonlinear and nonstationary spectral analysis software package integrated with the Compressed SSME TOPO Data Base (CSTDB) on the same platform. This system will allow NASA engineers to retrieve any unique defect signatures and trends associated with different failure modes and anomalous phenomena over the entire SSME test history across turbo pump families.

Jong, Jen-Yi↗
NASA NTRS1994

Develop advanced nonlinear signal analysis topographical mapping system

The Space Shuttle Main Engine (SSME) has been undergoing extensive flight certification and developmental testing, which involves some 250 health monitoring measurements. Under the severe temperature, pressure, and dynamic environments sustained during operation, numerous major component failures have occurred, resulting in extensive engine hardware damage and scheduling losses. To enhance SSME safety and reliability, detailed analysis and evaluation of the measurements signal are mandatory to assess its dynamic characteristics and operational condition. Efficient and reliable signal detection techniques will reduce catastrophic system failure risks and expedite the evaluation of both flight and ground test data, and thereby reduce launch turn-around time. The basic objective of this contract are threefold: (1) develop and validate a hierarchy of innovative signal analysis techniques for nonlinear and nonstationary time-frequency analysis. Performance evaluation will be carried out through detailed analysis of extensive SSME static firing and flight data. These techniques will be incorporated into a fully automated system; (2) develop an advanced nonlinear signal analysis topographical mapping system (ATMS) to generate a Compressed SSME TOPO Data Base (CSTDB). This ATMS system will convert tremendous amount of complex vibration signals from the entire SSME test history into a bank of succinct image-like patterns while retaining all respective phase information. High compression ratio can be achieved to allow minimal storage requirement, while providing fast signature retrieval, pattern comparison, and identification capabilities; and (3) integrate the nonlinear correlation techniques into the CSTDB data base with compatible TOPO input data format. Such integrated ATMS system will provide the large test archives necessary for quick signature comparison. This study will provide timely assessment of SSME component operational status, identify probable causes of malfunction, and indicate feasible engineering solutions. The final result of this program will yield an ATMS system of nonlinear and nonstationary spectral analysis software package integrated with the Compressed SSME TOPO Data Base (CSTDB) on the same platform. This system will allow NASA engineers to retrieve any unique defect signatures and trends associated with different failure modes and anomalous phenomena over the entire SSME test history across turbo pump families.

Source record↗
NASA NTRS1994

Surface temperatures in the polar regions from Nimbus 7 temperature humidity infrared radiometer

Monthly surface temperatures in the Arctic and Antarctic regions have been derived from the 11.5 micrometer thermal infrared channel of the Nimbus 7 temperature humidity infrared radiometer (THIR) for a whole year in 1979 and for a winter and a summer month from 1980 through 1985. The data set shows interannual variability and provides spatial details that allow identification of temperature patterns over sea ice and ice sheet surfaces. For example, the coldest spot in the southern hemisphere is observed to be consistently in the Antarctic plateau in the southern hemisphere, while that in the northern hemisphere is usually located in Greenland, or one of three other general areas: Siberia, the central Arctic, or the Canadian Archipelago. Also, in the southern hemisphere, the amplitude of the seasonal fluctuation of ice sheet temperatures is about 3 times that of sea ice, while in the northern hemisphere, the corresponding fluctuations for the two surfaces are about the same. The main sources of error in the retrieval are cloud and other atmospheric effects. These were minimized by first choosing the highest radiance value from the set of measurements during the day taken within a 30 km by 30 km grid of each daily map. Then the difference of daily maps was taken and where the difference is greater than a certain threshold (which in this case is 12 C), the data element is deleted. Overall, the monthly maps derived from the resulting daily maps are spatially and temporally consistent, are coherent with the topograph y of the Antarctic continent and the location of the sea ice edge, and are in qualitative agreement with climatological data. Quantitatively, THIR data are in good agreement with Antarctic ice sheet surface air temperature station data with a correlation coefficient of 0.997 and a standard deviation of 2.0 C. The absolute values are not as good over the sea ice edges, but a comparison with Russian 2-m drift station temperatures shows very high correlation (with correlation coefficient at 0.998) and a standard deviation of 1.1 C. Overall, the rms error is estimated to be from 1 to 2 C, depending on the surface, while the average bias when compared with in situ data is less than 2 C.

Comiso, Josefino C.↗
NASA NTRS2001

On Rainfall Modification by Major Urban Areas: Observations from Space-borne Rain Radar Aboard TRMM - Part 1

A novel approach is introduced to correlating urbanization and rainfall modification. This study represents one of the first published attempts (possibly the first) to identify and quantify rainfall modification by urban areas using satellite-based rainfall measurements. Previous investigations successfully used rain gauge networks and around-based radar to investigate this phenomenon but still encountered difficulties due to limited, specialized measurements and separation of topographic and other influences. Three years of mean monthly rainfall rates derived from the first space-based rainfall radar, Tropical Rainfall Measuring Mission's (TRMM) Precipitation Radar, are employed. Analysis of data at half-degree latitude resolution enables identification of rainfall patterns around major metropolitan areas of Atlanta, Montgomery, Nashville, San Antonio, Waco, and Dallas during the warm season. Preliminary results reveal an average increase of 5.6% in monthly rainfall rates (relative to a mean upwind CONTROL area) over the metropolis but an average increase of approx. 28%, in monthly rainfall rates within 30-60 kilometers downwind of the metropolis. Some portions of the downwind area exhibit increases as high as 51%. It was also found that maximum rainfall rates found in the downwind impact area exceeded the mean value in the upwind CONTROL area by 48%-116% and were generally found at an average distance of 39 km from the edge of the urban center or 64 km from the center of the city. These results are quite consistent studies of St. Louis (e.g' METROMEX) and Chicago almost two decades ago and more recent studies in the Atlanta and Mexico City areas.

Shepherd, J. Marshell↗
NASA NTRS2001

On Rainfall Modification by Major Urban Areas: Observations from Space-borne Rain Radar on TRMM - Part 1

This study represents one of the first published attempts to identify rainfall modification by urban areas using satellite-based rainfall measurements. Data from the first space-based rain-radar, the Tropical Rainfall Measuring Mission's (TRMM) Precipitation Radar, are employed. Analysis of the data enables identification of rainfall patterns around Atlanta, Montgomery, Nashville, San Antonio, Waco, and Dallas during the warm season. Results reveal an average increase of -28% in monthly rainfall rates within 30-60 kilometers downwind of the metropolis with a modest increase of 5.6% over the metropolis. Portions of the downwind area exhibit increases as high as 51%. The percentage chances are relative to an upwind CONTROL area. It was also found that maximum rainfall rates in the downwind impact area can exceed the mean value in the upwind CONTROL area by 48%-116%. The maximum value was generally found at an average distance of 39 km from the edge of the urban center or 64 km from the center of the city. These results are consistent with METROMEX studies of St. Louis almost two decades ago and more recent studies near Atlanta. Future work will investi(yate hypothesized factors causing rainfall modification by urban areas. Additional work is also needed to provide more robust validation of space-based rain estimates near major urban areas. Such research has implications for urban planning, water resource management, and understanding human impact on the environment.

Shepherd, J. Marshall↗
NASA NTRS1974

Some after-dinner reflections on system identification

The growth of the field of system identification is discussed along with changes in methodology which have taken place in recent years. The similarity between pattern recognition and system identification is pointed out, involving the modelling in the latter and the feature selection problem in the former. It is stated that once a model is formulated, including the disturbances and measurement errors, the parameter finding can be formulated as a statistical estimation problem. The various techniques and their application are discussed.

Balakrishnan, A. V.↗
NASA NTRS1997

Optical Verification Laboratory Demonstration System for High Security Identification Cards

Document fraud including unauthorized duplication of identification cards and credit cards is a serious problem facing the government, banks, businesses, and consumers. In addition, counterfeit products such as computer chips, and compact discs, are arriving on our shores in great numbers. With the rapid advances in computers, CCD technology, image processing hardware and software, printers, scanners, and copiers, it is becoming increasingly easy to reproduce pictures, logos, symbols, paper currency, or patterns. These problems have stimulated an interest in research, development and publications in security technology. Some ID cards, credit cards and passports currently use holograms as a security measure to thwart copying. The holograms are inspected by the human eye. In theory, the hologram cannot be reproduced by an unauthorized person using commercially-available optical components; in practice, however, technology has advanced to the point where the holographic image can be acquired from a credit card-photographed or captured with by a CCD camera-and a new hologram synthesized using commercially-available optical components or hologram-producing equipment. Therefore, a pattern that can be read by a conventional light source and a CCD camera can be reproduced. An optical security and anti-copying device that provides significant security improvements over existing security technology was demonstrated. The system can be applied for security verification of credit cards, passports, and other IDs so that they cannot easily be reproduced. We have used a new scheme of complex phase/amplitude patterns that cannot be seen and cannot be copied by an intensity-sensitive detector such as a CCD camera. A random phase mask is bonded to a primary identification pattern which could also be phase encoded. The pattern could be a fingerprint, a picture of a face, or a signature. The proposed optical processing device is designed to identify both the random phase mask and the primary pattern [1-3]. We have demonstrated experimentally an optical processor for security verification of objects, products, and persons. This demonstration is very important to encourage industries to consider the proposed system for research and development.

Javidi, Bahram↗
NASA NTRS1975

CARETS: A prototype regional environmental information system. Volume 13: Utility of CARETS products to local planners; an evaluation

The Metropolitan Washington Council of Governments (MWCOG) in cooperation with and under contract to the U.S. Geological Survey, conducted an evaluation of the utility of remote-sensor derived land use data produced by the USGS Central Atlantic Regional Ecological Test Site (CARETS) project. Investigators invited representatives of Washington, D.C. metropolitan area planning agencies to a workshop, introduced them to the CARETS products, and asked them to evaluate the products. In follow-up interviews, planners from 12 participating agencies reported general support for the fulI spectrum of CARETS products but gave more positive responses towards products with which they had some familiarity. Planners considered some products of limited utility because of (1) insufficient detail, (2) too small a scale, or (3) lack of technical capability to incorporate the information and products into the current planning process. Some planners expressed doubt about the application of CARETS products in most day-to-day planning activities , which involve specific rezoning requests or site development plans requiring highly localized data. The greatest potential of the CARETS products was in the identification of broad development patterns at the county or regional level. An appendix documents the results of an inventory of local government decisions relating to land use.

Land use planning↗
NASA NTRS1991

Fuzzy logic in autonomous orbital operations

Fuzzy logic can be used advantageously in autonomous orbital operations that require the capability of handling imprecise measurements from sensors. Several applications are underway to investigate fuzzy logic approaches and develop guidance and control algorithms for autonomous orbital operations. Translational as well as rotational control of a spacecraft have been demonstrated using space shuttle simulations. An approach to a camera tracking system has been developed to support proximity operations and traffic management around the Space Station Freedom. Pattern recognition and object identification algorithms currently under development will become part of this camera system at an appropriate level in the future. A concept to control environment and life support systems for large Lunar based crew quarters is also under development. Investigations in the area of reinforcement learning, utilizing neural networks, combined with a fuzzy logic controller, are planned as a joint project with the Ames Research Center.

Lea, Robert N.↗