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Results for “Pattern recognition”

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 NTRS1972

An approach toward an analysis of the pattern recognition involved in the stellar orientation of birds

A conditioning method was used to investigate the orientational responses of ducks as affected by manipulations of the stellar patterns in a planetarium. Under simulated natural skies it was possible to train a bird to a particular direction successively under all positions of the rotating sphere at a constant latitude. The responses were independent of the phase relationships between local time, season, and appearance of the sky provided the bird had been trained under the particular sector of the sphere some time before.

Wallraff, H. G.↗
NASA NTRS1998

Probabilistic and Other Neural Nets in Multi-Hole Probe Calibration and Flow Angularity Pattern Recognition

The use of probabilistic (PNN) and multilayer feed forward (MLFNN) neural networks are investigated for calibration of multi-hole pressure probes and the prediction of associated flow angularity patterns in test flow fields. Both types of networks are studied in detail for their calibration and prediction characteristics. The current formalism can be applied to any multi-hole probe, however the test results for the most commonly used five-hole Cone and Prism probe types alone are reported in this article.

Baskaran, Subbiah↗
DOE OSTI2022

Machine learning approach to pattern recognition in nuclear dynamics from the ab initio symmetry-adapted no-core shell model

A novel machine learning approach is used to provide further insight into atomic nuclei and to detect orderly patterns amid a vast data of large-scale calculations. The method utilizes a neural network that is trained on ab initio results from the symmetry-adapted no-core shell model (SA-NCSM) for light nuclei. We show that the SA-NCSM, which expands ab initio applications up to medium-mass nuclei by using dominant symmetries of nuclear dynamics, can reach heavier nuclei when coupled with the machine learning approach. In particular, we find that a neural network trained on probability amplitudes for s- and p-shell nuclear wave functions not only predicts dominant configurations for heavier nuclei but in addition, when tested for the 20 Ne ground state, accurately reproduces the probability distribution. The non-negligible configurations predicted by the network provide an important input to the SA-NCSM for reducing ultralarge model spaces to manageable sizes that can be, in turn, utilized in SA-NCSM calculations to obtain accurate observables. The neural network is capable of describing nuclear deformation and is used to track the shape evolution along the 20-42 Mg isotopic chain, suggesting a shape coexistence that is more pronounced toward the very neutron-rich isotopes. We provide first descriptions of the structure and deformation of 24 Si and 40 Mg of interest to x-ray burst nucleosynthesis, and even of the extremely heavy nuclei such as 166,168 Er and 236 U, that build on first-principles considerations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1991

Continuous monitoring of the lunar or Martian subsurface using on-board pattern recognition and neural processing of Rover geophysical data

The overall aim is to provide base technology for an automated vision system for on-board interpretation of geophysical data. During the first year's work, it was demonstrated that geophysical data can be treated as patterns and interpreted using single neural networks. Current research is developing an integrated vision system comprising neural networks, algorithmic preprocessing, and expert knowledge. This system is to be tested incrementally using synthetic geophysical patterns, laboratory generated geophysical patterns, and field geophysical patterns.

Glass, Charles E.↗
NASA NTRS1990

Pattern recognition with parallel associative memory

An examination is conducted of the feasibility of searching targets in aerial photographs by means of a parallel associative memory (PAM) that is based on the nearest-neighbor algorithm; the Hamming distance is used as a measure of closeness, in order to discriminate patterns. Attention has been given to targets typically used for ground-control points. The method developed sorts out approximate target positions where precise localizations are needed, in the course of the data-acquisition process. The majority of control points in different images were correctly identified.

Toth, Charles K.↗
DOE OSTI2020

Spatiotemporal Pattern Recognition in the PMU Signals in the WECC system

Phasor measurement unit (PMU) data has been used by multiple power system applications, including state estimation, post event analysis, oscillation detection, model validation, and many others. Still, due to its big data nature and availability to general research institutions, comprehensive understanding of the spatiotemporal patterns and underlying mechanisms are incomplete. This study applies a set of signal processing and machine learning approaches aiming at deciphering the characteristic behaviors of multiple phasor measurement units (PMUs) attributes (e.g., voltage, frequency, rate of change of frequency, phase angle), including their auto-correlation, cross-dependence, similarities and discrepancies across units and temporal scales, and distributions of anomalies and their linkages to potential external factors such as weather events. Data analytics are applied to PMUs from the U.S. Western Electricity Coordinating Council (WECC) system. The PMU measurements, recorded events, outages, and weather extremes are all from real world datasets. The findings from the study and mechanistic understanding of the PMU dynamics help provide guidance on system control or preventing blackouts. The derived metrics can be directly used for adjusting or filtering simulated PMU data used for advanced algorithm development.

Hou, Zhangshuan↗
NASA NTRS1973

Research progress in radiation detectors, pattern recognition programs, and radiation damage determination in DNA

The radiological implications of statistical variations in energy deposition by ionizing radiation were investigated in the conduct of the following experiments: (1) study of the production of secondary particles generated by the passage of the primary radiation through bone and muscle; (2) the study of the ratio of nonreparable to reparable damage in DNA as a function of different energy deposition patterns generated by X rays versus heavy fast charged particles; (3) the use of electronic radiography systems for direct fluoroscopic tomography and for the synthesis of multiple planes and; (4) the determination of the characteristics of systems response to split fields having different contrast levels, and of minimum detectable contrast levels between the halves under realistic clinical situations.

Baily, N. A.↗
NASA NTRS1975

A study of atmospheric effects on pattern recognition devices

The author has identified the following significant results. ERTS-1 imagery can be applied in the broadscale assessment of forest resources as a supplement to aerial photography and field survey. There was no application to inventory of crop and pasture diseases mainly because of poor quality and low resolution, and unreliability of image acquisition. Inventory of soil erosion was satisfactory in humid eastern New South Wales, but not in semi-arid areas. Patterns of snow cover, areas of water in natural and artificial water bodies, extent of bushfires, and location of coastal mobile sand bodies were readily apparent. ERTS-1 imagery was judged to be a valuable addition to conventional techniques of regional small scale geological mapping. ERTS data was successfully used to map flooding and flood progression. The imagery was found suitable for mapping at 1:1,000,000 scale both on the mainland and in Antarctica, but did not meet accuracy specifications for 1:250,000 mapping.

Thomson, F. J.↗
NASA NTRS1976

Pattern recognition and control in manipulation

A new approach to the use of sensors in manipulator or robot control is discussed. The concept addresses the problem of contact or near-contact type of recognition of three-dimensional forms of objects by proprioceptive and/or exteroceptive sensors integrated with the terminal device. This recognition of object shapes both enhances and simplifies the automation of object handling. Several examples have been worked out for the 'Belgrade hand' and for a parallel jaw terminal device, both equipped with proprioceptive (position) and exteroceptive (proximity) sensors. The control applications are discussed in the framework of a multilevel man-machine system control. The control applications create interesting new issues which, in turn, invite novel theoretical considerations. An important issue is the problem of stability in control when the control is referenced to patterns.

Bejczy, A. K.↗
DOE OSTI2020

Supervised enhancer prediction with epigenetic pattern recognition and targeted validation

Enhancers are important non-coding elements, but they have traditionally been hard to characterize experimentally. The development of massively parallel assays allows the characterization of large numbers of enhancers for the first time. Here, we developed a framework using Drosophila STARR-seq to create shape-matching filters based on meta-profiles of epigenetic features. We integrated these features with supervised machine-learning algorithms to predict enhancers. We further demonstrated that our model could be transferred to predict enhancers in mammals. We comprehensively validated the predictions using a combination of in vivo and in vitro approaches, involving transgenic assays in mice and transduction-based reporter assays in human cell lines (153 enhancers in total). The results confirmed that our model can accurately predict enhancers in different species without re-parameterization. Finally, we examined the transcription factor binding patterns at predicted enhancers versus promoters. Here, we demonstrated that these patterns enable the construction of a secondary model that effectively distinguishes enhancers and promoters.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Unraveling the size fluctuation and shrinkage of nanovoids during in situ radiation of Cu by automatic pattern recognition and phase field simulation

Void formation is an important aspect of irradiation response of metals. In situ transmission electron microscopy observation for void evolution during irradiation is an effective technique for studying void evolution. However, the amount of data collected during in situ studies drastically overwhelm the current capability for manual data analyses. Here, we used a data-driven approach where a convolutional neural network combined with greedy matching to detect and track nanovoid evolutions and migrations. This approach was able to discover the surprising phenomena of void size fluctuation and shrinkage during irradiation of Cu with pre-existing nanovoids. Phase–field simulations revealed the fundamental mechanism behind this in situ observed phenomenon of void size fluctuation.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Recognition Patterns of the C1/C2 Epitopes Involved in Fc-Mediated Response in HIV-1 Natural Infection and the RV114 Vaccine Trial

Antibodies (Abs) specific for CD4-induced envelope (Env) epitopes within constant region 1 and 2 (C1/C2) were induced in the RV144 vaccine trial, where antibody-dependent cellular cytotoxicity (ADCC) correlated with reduced risk of HIV-1 infection. We combined X-ray crystallography and fluorescence resonance energy transfer-fluorescence correlation spectroscopy to describe the molecular basis for epitopes of seven RV144 Abs and compared them to A32 and C11, C1/C2 Abs induced in HIV infection. Our data indicate that most vaccine Abs recognize the 7-stranded β-sandwich of gp120, a unique hybrid epitope bridging A32 and C11 binding sites. Although primarily directed at the 7-stranded β-sandwich, some accommodate the gp120 N terminus in C11-bound 8-stranded conformation and therefore recognize a broader range of CD4-triggered Env conformations. Our data also suggest that Abs of RV144 and RV305, the RV144 follow-up study, although likely initially induced by the ALVAC-HIV prime encoding full-length gp120, matured through boosting with truncated AIDSVAX gp120 variants.

59 BASIC BIOLOGICAL SCIENCES↗