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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS1987

Optical and digital pattern recognition; Proceedings of the Meeting, Los Angeles, CA, Jan. 13-15, 1987

The papers presented in this volume provide an overview of current research in both optical and digital pattern recognition, with a theme of identifying overlapping research problems and methodologies. Topics discussed include image analysis and low-level vision, optical system design, object analysis and recognition, real-time hybrid architectures and algorithms, high-level image understanding, and optical matched filter design. Papers are presented on synthetic estimation filters for a control system; white-light correlator character recognition; optical AI architectures for intelligent sensors; interpreting aerial photographs by segmentation and search; and optical information processing using a new photopolymer.

Liu, Hua-Kuang↗
NASA NTRS1973

Cloud type pattern recognition using environmental satellite data

A classification analysis is conducted concerning the tropical cloud types as remotely sensed in the visual and infrared range by ITOS scanning radiometers. A statistical pattern recognition technique is used to examine the ability of coincident dual-channel and single-channel data to classify four main forms of clouds, including cumulus, stratocumulus, cumulonimbus, and cirrus.

Booth, A. L.↗
NASA NTRS1974

Computer-implemented land use classification with pattern recognition software and ERTS digital data

Significant progress has been made in the classification of surface conditions (land uses) with computer-implemented techniques based on the use of ERTS digital data and pattern recognition software. The supervised technique presently used at the NASA Earth Resources Laboratory is based on maximum likelihood ratioing with a digital table look-up approach to classification. After classification, colors are assigned to the various surface conditions (land uses) classified, and the color-coded classification is film recorded on either positive or negative 9 1/2 in. film at the scale desired. Prints of the film strips are then mosaicked and photographed to produce a land use map in the format desired. Computer extraction of statistical information is performed to show the extent of each surface condition (land use) within any given land unit that can be identified in the image. Evaluations of the product indicate that classification accuracy is well within the limits for use by land resource managers and administrators. Classifications performed with digital data acquired during different seasons indicate that the combination of two or more classifications offer even better accuracy.

Joyce, A. T.↗
NASA NTRS1983

Proceedings of the NASA/MPRIA Workshop: Pattern Recognition

Outlines of talks presented at the workshop conducted at Texas A & M University on February 3 and 4, 1983 are presented. Emphasis was given to the application of Mathematics to image processing and pattern recognition.

Guseman, L. F., Jr.↗
NASA NTRS1994

Optical Processing of Speckle Images with Bacteriorhodopsin for Pattern Recognition

Logarithmic processing of images with multiplicative noise characteristics can be utilized to transform the image into one with an additive noise distribution. This simplifies subsequent image processing steps for applications such as image restoration or correlation for pattern recognition. One particularly common form of multiplicative noise is speckle, for which the logarithmic operation not only produces additive noise, but also makes it of constant variance (signal-independent). We examine the optical transmission properties of some bacteriorhodopsin films here and find them well suited to implement such a pointwise logarithmic transformation optically in a parallel fashion. We present experimental results of the optical conversion of speckle images into transformed images with additive, signal-independent noise statistics using the real-time photochromic properties of bacteriorhodopsin. We provide an example of improved correlation performance in terms of correlation peak signal-to-noise for such a transformed speckle image.

Downie, John D.↗
NASA NTRS1973

Adaptive procedures in multispectral pattern recognition

Two types of discrete adaptive procedures are proposed for updating statistical parameters such as the means and covariance matrices. These two types include nonweighted adaptive procedures and weighted adaptive procedures. It is believed that the use of the proposed procedures will enhance the performance accuracy of a pattern recognition system. The procedures discussed include an approach for a weighted mean vector adaptation.

Chang, C. Y.↗
NASA NTRS1975

System integration of pattern recognition, adaptive aided, upper limb prostheses

The requirements for successful integration of a computer aided control system for multi degree of freedom artificial arms are discussed. Specifications are established for a system which shares control between a human amputee and an automatic control subsystem. The approach integrates the following subsystems: (1) myoelectric pattern recognition, (2) adaptive computer aiding; (3) local reflex control; (4) prosthetic sensory feedback; and (5) externally energized arm with the functions of prehension, wrist rotation, elbow extension and flexion and humeral rotation.

Lyman, J.↗
NASA NTRS1975

Applications of matrix derivatives to optimization problems in statistical pattern recognition

A necessary condition for a real valued Frechet differentiable function of a vector variable have an extremum at a vector x sub 0 is that the Frechet derivative vanishes at x sub 0. A relationship between Frechet differentials and matrix derivatives was established that obtains a necessary condition on the matrix derivative at an extrema. These results are applied to various scalar functions of matrix variables which occur in statistical pattern recognition.

Morrell, J. S.↗
DOE OSTI2020

Determination of the Maturation Status of Dendritic Cells by Applying Pattern Recognition to High-Resolution Images

The maturation or activation status of dendritic cells (DCs) directly correlates with their behavior and immunofunction. A common means to determine the maturity of dendritic cells is from high-resolution images acquired via scanning electron microscopy (SEM) or atomic force microscopy (AFM). While direct and visual, the determination has been made by directly looking at the images by researchers. Here we report a machine learning approach using pattern recognition in conjunction with cellular biophysical knowledge of dendritic cells to determine the maturation status of dendritic cells automatically. The determination from AFM images reaches 100% accuracy. The results from SEM images reaches 94.9%. The results demonstrate the accuracy of using machine learning for accelerating data analysis, extracting information, and drawing conclusions from high-resolution cellular images, paving the way for future applications requiring high-throughput and automation, such as cellular sorting and selection based on morphology, quantification of cellular structure, and DC-based immunotherapy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Temporal Pattern Recognition with Delayed-Feedback Spin-Torque Nano-Oscillators

The recent demonstration of neuromorphic computing with spin-torque nano-oscillators has opened a path to energy efficient data processing. The success of this demonstration hinged on the intrinsic short-term memory of the oscillators. We extend the memory of the spin-torque nano-oscillators through time-delayed feedback. We leverage this extrinsic memory to increase the efficiency of solving pattern recognition tasks that require memory to discriminate different inputs. Here, the large tunability of these nonlinear oscillators allows us to control and optimize the delayed-feedback memory using different operating conditions of applied current and magnetic field.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1987

Pattern recognition techniques for failure trend detection in SSME ground tests

The Space Shuttle Main Engine (SSME) is a complex power plant. To evaluate its performance 1200 hot-wire ground tests have been conducted, varying in duration from 0 to 500 secs. During the test some 500 sensors are sampled every 20 ms. The sensors are generally bounded by red lines so that an excursion beyond could lead to premature shutdown. In 27 tests it was not possible to effect an orderly premature shutdown, resulting in major incidents with serious damage to the SSME and test stand. The application of pattern recognition are investigated to detect SSME performance trends that may lead to major incidents. Based on the sensor data a set of (n) features is defined. At any time during the test, the state of the SSME is given by a point in the n-dimensional feature space. The history of a test can now be represented as a trajectory in the n-dimensional feature space. Portions of the normal trajectories and failed test trajectories would lie in different regions of the n-dimensional feature space. The latter can now be partitioned into regions of normal and failed tests. Thus, it is possible to examine the trajectory of a test in progress and predict if it is going into the normal or failure region.

Choudry, A.↗
DOE OSTI2018

Verification Data Pattern Recognition and Change Detection at the Neutron Instrument Level

As the pressure on International Atomic Energy Agency (IAEA) safeguards resources increases, there is a drive to essentially “do more with less.” New ways of using current verification instrumentation and visualizing the collected data are needed, coupled with maintaining and sustaining the current safeguards instrumentation fleet. This paper explores how to innovate with current safeguards neutron instrumentation using data-driven algorithms at the instrument level. A concept is described for upgrading current neutron counting systems with modern electronics by leveraging electronics developments in other fields (e.g., high-energy physics) to facilitate full list mode data acquisition and, therefore, expand existing analyses to pattern recognition and change detection at the instrument level. The aim is to advance correlated neutron counting by improving the reliability of detecting nuclear material diversion and, at the same time, to improve the sustainability of those systems. It is likely that upgrading existing systems with new hardware and software is more cost-effective than replacing systems with other novel systems that might meet this need. A specific project example is highlighted in which a system was upgraded by retrofitting the standard uranium neutron collar detector with new electronics; as a result, verification data can be analyzed in new ways. A new neutron analysis method, the “List Mode Response Matrix,” has been developed to analyze every pulse train from the detector array and thus enable the verification of spatial information about the assay item for safeguards inspections. This project has improved the reliability of resolving individual fuel pin locations within a given fresh fuel assembly and the percentage of partial defects detected. Herein, the overall concept of upgrading current neutron counting systems is discussed with respect to the potential increase in analysis capabilities. In addition, the details and results of the list mode collar project are discussed.

Worrall, Louise G.↗
DOE OSTI2019

Quantum Associative Memory in Hep Track Pattern Recognition

We have entered the Noisy Intermediate-Scale Quantum Era. A plethora of quantum processor prototypes allow evaluation of potential of the Quantum Computing paradigm in applications to pressing computational problems of the future. Growing data input rates and detector resolution foreseen in High-Energy LHC (2030s) experiments expose the often high time and/or space complexity of classical algorithms. Quantum algorithms can potentially become the lower-complexity alternatives in such cases. In this work we discuss the potential of Quantum Associative Memory (QuAM) in the context of LHC data triggering. We examine the practical limits of storage capacity, as well as store and recall errorless efficiency, from the viewpoints of the state-of-the-art IBM quantum processors and LHC real-time charged track pattern recognition requirements. We present a software prototype implementation of the QuAM protocols and analyze the topological limitations for porting the simplest QuAM instances to the public IBM 5Q and 14Q cloud-based superconducting chips.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1971

Pattern recognition technique

Technique operates regardless of pattern rotation, translation or magnification and successfully detects out-of-register patterns. It improves accuracy and reduces cost of various optical character recognition devices and page readers and provides data input to computer.

Hong, J. P.↗
DOE OSTI2017

A general model for retroviral capsid pattern recognition by TRIM5 proteins

Restriction factors are intrinsic cellular defense proteins that have evolved to block microbial infections. Retroviruses such as HIV-1 are restricted by TRIM5 proteins, which recognize the viral capsid shell that surrounds, organizes, and protects the viral genome. TRIM5α uses a SPRY domain to bind capsids with low intrinsic affinity ( K D >1 mM), and therefore requires higher-order assembly into a hexagonal lattice to generate sufficient avidity for productive capsid recognition. TRIMCyp, on the other hand, binds HIV-1 capsids through a cyclophilin A domain, which has a well-defined binding site and higher ( K D ~10 μM) affinity for isolated capsid subunits. It has therefore been argued that TRIMCyp proteins may have dispensed with the need for higher-order assembly to function as antiviral factors. Here, we show that, consistent with its high degree of sequence similarity with TRIM5α, the TRIMCyp B-box 2 domain shares the same ability to self-associate and facilitate assembly of a TRIMCyp hexagonal lattice that can wrap about the HIV-1 capsid. We also show that under stringent experimental conditions, TRIMCyp-mediated restriction of HIV-1 is indeed dependent on higher-order assembly. Both forms of TRIM5 therefore use the same mechanism of avidity-driven capsid pattern recognition. IMPORTANCE Rhesus macaques and owl monkeys are highly resistant to HIV-1 infection due to the activity of TRIM5 restriction factors. The rhesus macaque TRIM5α protein blocks HIV-1 through a mechanism that requires self-assembly of a hexagonal TRIM5α lattice around the invading viral core. Lattice assembly amplifies very weak interactions between the TRIM5α SPRY domain and the HIV-1 capsid. Assembly also promotes dimerization of the TRIM5α RING E3 ligase domain, resulting in synthesis of polyubiquitin chains that mediate downstream steps of restriction. In contrast to rhesus TRIM5α, the owl monkey TRIM5 homolog, TRIMCyp, binds isolated HIV-1 CA subunits more tightly through its cyclophilin A domain, and was therefore thought to act independent of higher-order assembly. Here, we show that TRIMCyp shares the assembly properties of TRIM5α and that both forms of TRIM5 use the same mechanism of hexagonal lattice formation to promote viral recognition and restriction.

Wagner, Jonathan M.↗
NASA NTRS1992

Multiresolution pattern recognition of small volcanos in Magellan data

The Magellan data is a treasure-trove for scientific analysis of venusian geology, providing far more detail than was previously available from Pioneer Venus, Venera 15/16, or ground-based radar observations. However, at this point, planetary scientists are being overwhelmed by the sheer quantities of data collected--data analysis technology has not kept pace with our ability to collect and store it. In particular, 'small-shield' volcanos (less than 20 km in diameter) are the most abundant visible geologic feature on the planet. It is estimated, based on extrapolating from previous studies and knowledge of the underlying geologic processes, that there should be on the order of 10(exp 5) to 10(exp 6) of these volcanos visible in the Magellan data. Identifying and studying these volcanos is fundamental to a proper understanding of the geologic evolution of Venus. However, locating and parameterizing them in a manual manner is very time-consuming. Hence, we have undertaken the development of techniques to partially automate this task. The goal is not the unrealistic one of total automation, but rather the development of a useful tool to aid the project scientists. The primary constraints for this particular problem are as follows: (1) the method must be reasonably robust; and (2) the method must be reasonably fast. Unlike most geological features, the small volcanos of Venus can be ascribed to a basic process that produces features with a short list of readily defined characteristics differing significantly from other surface features on Venus. For pattern recognition purposes the relevant criteria include the following: (1) a circular planimetric outline; (2) known diameter frequency distribution from preliminary studies; (3) a limited number of basic morphological shapes; and (4) the common occurrence of a single, circular summit pit at the center of the edifice.

Smyth, P.↗
NASA NTRS1987

Determine precipitation rates from visible and infrared satellite images of clouds by pattern recognition technique

A more advanced cloud pattern analysis algorithm was subsequently developed to take the shape and brightness of the various clouds into account in a manner that is more consistent with the human analyst's perception of GOES cloud imagery. The results of that classification scheme were compared with precipitation probabilities observed from ships of opportunity off the U.S. east coast to derive empirical regressions between cloud types and precipitation probability. The cloud morphology was then quantitatively and objectively used to map precipitation probabilities during two winter months during which severe cold air outbreaks were observed over the northwest Atlantic. Precipitation probabilities associated with various cloud types are summarized. Maps of precipitation probability derived from the cloud morphology analysis program for two months and the precipitation probability derived from thirty years of ship observation were observed.

Weinman, James A.↗