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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 253 records · Page 14

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NASA NTRS1989

The horse-collar aurora - A frequent pattern of the aurora in quiet times

The frequent appearance of the 'horse-collar aurora' pattern in quiet-time DE 1 images is reported, presenting a two-hour image sequence that displays the basic features and shows that it sometimes evolves toward the theta configuration. There is some evidence for interplanetary magnetic field B(y) influence on the temporal development of the pattern. A preliminary statistical analysis finds the pattern appearing in one-third or more of the image sequences recorded during quiet times.

Hones, E. W., Jr.↗

NASA NTRS1988

Capacity for patterns and sequences in Kanerva's SDM as compared to other associative memory models

The information capacity of Kanerva's Sparse Distributed Memory (SDM) and Hopfield-type neural networks is investigated. Under the approximations used here, it is shown that the total information stored in these systems is proportional to the number connections in the network. The proportionality constant is the same for the SDM and Hopfield-type models independent of the particular model, or the order of the model. The approximations are checked numerically. This same analysis can be used to show that the SDM can store sequences of spatiotemporal patterns, and the addition of time-delayed connections allows the retrieval of context dependent temporal patterns. A minor modification of the SDM can be used to store correlated patterns.

Keeler, James D.↗

NASA NTRS1990

Generating Weighted Test Patterns for VLSI Chips

Improved built-in self-testing circuitry for very-large-scale integrated (VLSI) digital circuits based on version of weighted-test-pattern-generation concept, in which ones and zeros in pseudorandom test patterns occur with probabilities weighted to enhance detection of certain kinds of faults. Requires fewer test patterns and less computation time and occupies less area on circuit chips. Easy to relate switching activity in outputs with fault-detection activity by use of probabilistic fault-detection techniques.

Siavoshi, Fardad↗

NASA NTRS1987

Capacity for patterns and sequences in Kanerva's SDM as compared to other associative memory models

The information capacity of Kanerva's Sparse Distributed Memory (SDM) and Hopfield-type neural networks is investigated. Under the approximations used, it is shown that the total information stored in these systems is proportional to the number connections in the network. The proportionality constant is the same for the SDM and Hopfield-type models independent of the particular model, or the order of the model. The approximations are checked numerically. This same analysis can be used to show that the SDM can store sequences of spatiotemporal patterns, and the addition of time-delayed connections allows the retrieval of context dependent temporal patterns. A minor modification of the SDM can be used to store correlated patterns.

Keeler, James D.↗

NASA NTRS1989

Temporal patterns of phytoplankton abundance in the North Atlantic

A time series of CZCS images is being developed to study phytoplankton distribution patterns in the North Atlantic. The goal of this study is to observe temporal variability in phytoplankton pigments and other organic particulates, and to infer from these patterns the potential flux of biogenic materials from the euphotic layer to the deep ocean. Early results of this project are presented in this paper. Specifically, the satellite data used were 13 monthly composited images of CZCS data for the North Atlantic from January 1979 to January 1980. Results are presented for seasonal patterns along the 20 deg W meridian.

Campbell, Janet W.↗

NASA NTRS1989

Possible use of pattern recognition for the analysis of Mars rover X-ray fluorescence spectra

On the Mars rover sample-return mission, the rover vehicle will collect and select samples from different locations on the Martian surface to be brought back to earth for laboratory studies. It is anticipated that an in situ energy-dispersive X-ray fluorescence (XRF) spectrometer will be on board the rover. On such a mission, sample selection is of higher priority than in situ quantitative chemical anlaysis. With this in mind, a pattern recognition technique is proposed as a simple, direct, and speedy alternative to detailed chemical analysis of the XRF spectra. The validity and efficacy of the pattern recognition technique are demonstrated by the analyses of laboratory XRF spectra obtained from a series of geological samples, in the form both of standardized pressed pellets and as unprepared rocks. It is found that pattern recognition techniques applied to the raw XRF spectra can provide for the same discrimination among samples as a knowledge of their actual chemical composition.

Yin, Lo I↗

NASA NTRS1989

Classification of data patterns using an autoassociative neural network topology

A diagnostic expert system based on neural networks is developed and applied to the real-time diagnosis of jet and rocket engines. The expert system methodologies are based on the analysis of patterns of behavior of physical mechanisms. In this approach, fault diagnosis is conceptualized as the mapping or association of patterns of sensor data to patterns representing fault conditions. The approach addresses deficiencies inherent in many feedforward neural network models and greatly reduces the number of networks necessary to identify the existence of a fault condition and estimate the duration and severity of the identified fault. The network topology used in the present implementation of the diagnostic system is described, as well as the training regimen used and the response of the system to inputs representing both previously observed and unknown fault scenarios. Noise effects on the integrity of the diagnosis are also evaluated.

Dietz, W. E.↗

NASA NTRS1991

Orthogonal Patterns In A Binary Neural Network

Report presents some recent developments in theory of binary neural networks. Subject matter relevant to associate (content-addressable) memories and to recognition of patterns - both of considerable importance in advancement of robotics and artificial intelligence. When probed by any pattern, network converges to one of stored patterns.

Baram, Yoram↗

NASA NTRS1990

General method of pattern classification using the two-domain theory

Human beings judge patterns (such as images) by complex mental processes, some of which may not be known, while computing machines extract features. By representing the human judgements with simple measurements and reducing them and the machine extracted features to a common metric space and fitting them by regression, the judgements of human experts rendered on a sample of patterns may be imposed on a pattern population to provide automatic classification.

Rorvig, Mark E.↗

NASA NTRS1990

The radiation pattern of a monopole antenna attached to a conducting box

A system investigation was undertaken to determine the radiation patterns of a monopole antenna mounted on a cubical conducting box over a ground plane. The effects of the location of the monopole and the electrical size of the box were compared with similar patterns measured over a flat ground plane and with numerically predicted values obtained from a method-of-moments patch code. It was concluded that the location at which a monopole antenna is mounted on a conducting box and the electrical size of the box clearly affect the overall radiation pattern of a monopole antenna. In general, mounting the antenna away from the center of the box will increase the depth of the nulls. In particular, planes will also increase the maximum E(phi) component of the field to the extent that it can become comparable to E(theta).

Chu, Andrew W. C.↗

NASA NTRS1990

Bioconvective patterns, synchrony, and survival

With and without bioconvective pattern formation, a theoretical model predicts growth in light-limited cultures of motile algae. At the critical density for pattern formation, the resulting doubly exponential population curves show an inflection. Such growth corresponds quantitatively to experiments in mechanically unstirred cultures. This attaches survival value to synchronized pattern formation.

Noever, David A.↗

NASA NTRS1992

Hierarchical Pattern Classifier

Hierarchical pattern classifier reduces number of comparisons between input and memory vectors without reducing detail of final classification by dividing classification process into coarse-to-fine hierarchy that comprises first "grouping" step and second classification step. Three-layer neural network reduces computation further by reducing number of vector dimensions in processing. Concept applicable to pattern-classification problems with need to reduce amount of computation necessary to classify, identify, or match patterns to desired degree of resolution.

Yates, Gigi L.↗

NASA NTRS1992

Patterns of discoloration and oxidation by direct and scattered fluxes on LDEF, including oxygen on silicon

A number of interesting discoloration patterns are clearly evident on MOOO2-1 which resides on the three faces of the Long Duration Exposure Facility (LDEF). Most interesting is the pattern of blue oxidation on polished single crystal silicon apparently produced by scattered or direct ram oxygen atoms along the earth face. A complete explanation for the patterns has not yet been obtained. All honeycomb outgassing holes have a small discoloration ring around them that varies in color. The shadow cast by a suspended wire on the earth face surface is not easily explained by either solar photons or by ram flux. The shadows and the dark/light regions cannot be explained consistently by the process of solar ultraviolet paint-darkening modulated by ram flux oxygen bleaching of the paint.

Frederickson, A. R.↗

NASA NTRS1992

Radar sensitivity and antenna scan pattern study for a satellite-based Radar Wind Sounder (RAWS)

Modeling global atmospheric circulations and forecasting the weather would improve greatly if worldwide information on winds aloft were available. Recognition of this led to the inclusion of the LAser Wind Sounder (LAWS) system to measure Doppler shifts from aerosols in the planned for Earth Observation System (EOS). However, gaps will exist in LAWS coverage where heavy clouds are present. The RAdar Wind Sensor (RAWS) is an instrument that could fill these gaps by measuring Doppler shifts from clouds and rain. Previous studies conducted at the University of Kansas show RAWS as a feasible instrument. This thesis pertains to the signal-to-noise ratio (SNR) sensitivity, transmit waveform, and limitations to the antenna scan pattern of the RAWS system. A dop-size distribution model is selected and applied to the radar range equation for the sensitivity analysis. Six frequencies are used in computing the SNR for several cloud types to determine the optimal transmit frequency. the results show the use of two frequencies, one higher (94 GHz) to obtain sensitivity for thinner cloud, and a lower frequency (24 GHz) to obtain sensitivity for thinner cloud, and a lower frequency (24 GHz) for better penetration in rain, provide ample SNR. The waveform design supports covariance estimation processing. This estimator eliminates the Doppler ambiguities compounded by the selection of such high transmit frequencies, while providing an estimate of the mean frequency. the unambiguous range and velocity computation shows them to be within acceptable limits. The design goal for the RAWS system is to limit the wind-speed error to less than 1 ms(exp -1). Due to linear dependence between vectors for a three-vector scan pattern, a reasonable wind-speed error is unattainable. Only the two-vector scan pattern falls within the wind-error limits for azimuth angles between 16 deg to 70 deg. However, this scan only allows two components of the wind to be determined. As a result, a technique is then shown, based on the Z-R-V relationships, that permit the vertical component (i.e., rain) to be computed. Thus the horizontal wind components may be obtained form the covariance estimator and the vertical component from the reflectivity factor. Finally, a new candidate system is introduced which summarizes the parameters taken from previous RAWS studies, or those modified in this thesis.

Stuart, Michael A.↗

NASA NTRS1992

Ground testing of bioconvective variables such as morphological characterizations and mechanisms which regulate macroscopic patterns

Conditions simulating low- and high-gravity, reveal changes in macroscopic pattern formation in selected microorganisms, but whether these structures are gravity dependent is not clear. Two theories have been identified in the fluid dynamics community which support macroscopic pattern formation. The first one is gravity dependent (fluid density models) where small concentrated regions of organisms sink unstably, and the second is gravity independent (wave reinforcement theory) where organisms align their movements in concert, such that either their swimming strokes beat in phase or their vortices entrain neighbors to follow parallel paths. Studies have shown that macroscopic pattern formation is consistent with the fluid density models for protozoa and algae and wave reinforcement hypothesis for caprine spermatozoa.

Johnson, Adriel D.↗

NASA NTRS1993

General method of pattern classification using the two-domain theory

Rorvig, Mark E.↗

NASA NTRS1993

Dynamic pattern matcher using incomplete data

This invention relates generally to pattern matching systems, and more particularly to a method for dynamically adapting the system to enhance the effectiveness of a pattern match. Apparatus and methods for calculating the similarity between patterns are known. There is considerable interest, however, in the storage and retrieval of data, particularly, when the search is called or initiated by incomplete information. For many search algorithms, a query initiating a data search requires exact information, and the data file is searched for an exact match. Inability to find an exact match thus results in a failure of the system or method.

Johnson, Gordon G.↗

NASA NTRS1991

Antenna pattern control using impedence surfaces

During this research period, September 16, 1990 to March 15, 1991, a design method for selecting a low-loss impedance material coating for a horn antenna pattern control has been developed. This method and the stepped waveguide technique can be employed to accurately compute the electromagnetic wave phenomenon inside the transition region of the horn antenna, with or without the impedance surfaces, from the feed to the radiating aperture. For moment method solutions of the electric and magnetic current distributions on the radiating aperture and the outer surface of the horn antenna, triangular surface-patch modes are introduced to replace the sinusoidal surface-patch modes as expansion and testing functions to provide a more physical expansion of the current distributions. In the synthesis problem, a numerical optimization process is formulated to minimize the error function between the desired waveguide modes and the modes provided by the horn transition with impedance surfaces. Since the modes generated by the horn transition with impedance surface are computed by analytical techniques, the computational error involved in the synthesis of the antenna pattern is minimum. Therefore, the instability problem can be avoided. A preliminary implementation of the techniques has demonstrated that the developed theory of the horn antenna pattern control using the impedance surfaces is realizable.

Balanis, Constantine A.↗