Search NASA⌕ Search

SEARCH · Search NASA

Results for “Feature detection”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
NASA NTRS1996

The Interstellar Polarization Feature Associated with the 2175 Angstrom Extinction Bump

The most successful model at fitting the wavelength dependence of interstellar extinction consists of two populations of bare silicate and graphite grains (Mathis, Rumpl & Nordsieck, (MRN)). The graphite grains are needed to fit the strong 2175 A extinction bump, with the silicates providing most of the smooth extinction seen at other wavelengths. From observations of the IR silicate absorption features, it was inferred that the silicate grains, non-spherical and aligned to the Galactic magnetic field, were responsible for the interstellar polarization. Aligned silicate grains make a very good fit to the smooth featureless UV polarization curves that comprise most of the observed sample. The lines of sight showing a UV polarization feature require something different, perhaps a second population of grains as do the fits to the extinction curve. The polarization wavelength dependence of HD 197770 can be fit by a MRN-like mixture of aligned bare silicate and graphite grains. However, none of the popular grain models including MRN envisaged an aligned bump grain population. It has been suggested that the extinction bump is not due to graphite but rather to a population of polycyclic aromatic hydrocarbons (PAHs). If the observed UV polarization features could be associated with the 2175 A bump then it would strengthen the argument that the bump must be due to grains rather than PAHs which are not likely to be aligned to the Galactic Magnetic field. The reality of ultraviolet polarization features has been confirmed by observations with ASTRO-2. The original detection toward HD 197770 has been confirmed and a new feature has been detected toward HD 147933-4. Both features have centroids lying close to 2175 A the location of the UV extinction bump. Two possibilities are considered for the source of the polarization bump, alignment of graphite grains responsible for the extinction bump or changes in the size distribution of the aligned silicate grains responsible for the continuum polarization. It seems the graphite grains are a more likely source of the polarization.

Clayton, Geoffrey C.↗
NASA NTRS2007

Liquid Bismuth Propellant Flow Sensor

Quantifying the propellant mass flow rate in liquid bismuth-fed electric propulsion systems has two challenging facets. First, the flow sensors must be capable of providing a resolvable measurement at propellant mass flow rates on the order of 10 mg/see with and uncertainty of less that 5%. The second challenge has to do with the fact that the materials from which the flow sensors are fabricated must be capable of resisting any of the corrosive effects associated with the high-temperature propellant. The measurement itself is necessary in order to properly assess the performance (thrust efficiency, Isp) of thruster systems in the laboratory environment. The hotspot sensor[I] has been designed to provide the bismuth propellant mass flow rate measurement. In the hotspot sensor, a pulse of thermal energy (derived from a current pulse and associated joule heating) is applied near the inlet of the sensor. The flow is "tagged" with a thermal feature that is convected downstream by the flowing liquid metal. Downstream, a temperature measurement is performed to detect a "ripple" in the local temperature associated with the passing "hotspot" in the propellant. By measuring the time between the upstream generation and downstream detection of the thermal feature, the flow speed can be calculated using a "time of flight" analysis. In addition, the system can be calibrated by measuring the accumulated mass exiting the system as a-function of time and correlating this with the time it takes the hotspot to convect through the sensor. The primary advantage of this technique is that it doesn't depend on an absolute measurement of temperature but, instead, relies on the observation of thermal features. This makes the technique insensitive to other externally generated thermal fluctuations. In this paper, we describe experiments performed using the hotspot flow sensor aimed at quantifying the resolution of the sensor technology. Propellant is expelled onto an electronic scale to provide an independent measure of the propellant mass flow rate as a function of time. In addition, two separate detection schemes are employed. The first uses a thermocouple to directly measure temperature in the fluid. The second involves the ,use of a fiber optic coupled to a photodiode allowing for detection of an increase in light emission from the fluid as the hotspot passes. the detection location.

Polzin, Kurt A.↗
NASA NTRS1970

Detection and identification of benthic communities and shoreline features in Biscayne Bay

Progress made in the development of a technique for identifying and delinating benthic and shoreline communities using multispectral imagery is described. Images were collected with a multispectral scanner system mounted in a C-47 aircraft. Concurrent with the overflight, ecological ground- and sea-truth information was collected at 19 sites in the bay and on the shore. Preliminary processing of the scanner imagery with a CDC 1604 digital computer provided the optimum channels for discernment among different underwater and coastal objects. Automatic mapping of the benthic plants by multiband imagery and the mapping of isotherms and hydrodynamic parameters by digital model can become an effective predictive ecological tool when coupled together. Using the two systems, it appears possible to predict conditions that could adversely affect the benthic communities. With the advent of the ERTS satellites and space platforms, imagery data could be obtained which, when used in conjunction with water-level and meteorological data, would provide for continuous ecological monitoring.

Kolipinski, M. C.↗
NASA NTRS1990

Detection of the 3.4- and 2.8-micron emission features in Comet Bradfield (1987s)

Comet Bradfield's 3.4-micron C-H emission feature at 3.4 microns, as well as the emission feature near 2.8 microns, exhibit spectral shapes similar to those noted in Comets Halley and Wilson; the derived abundances of the C-H bonds in all three comets are also comparable (within water production rate uncertainties). These data support the hypothesis that the species responsible for the 3.4- and 2.8-micron features may be common to all comets. Beyond this, the widely differing ages of the three comets suggest that the 3.4-micron feature-emitting organics are not the product of surface irradiation processes after the comets' formation.

Brooke, T. Y.↗
NASA NTRS1991

An investigation of the detection of tornadic thunderstorms by observing storm top features using geosynchronous satellite imagery

The number of tornado outbreak cases studied in detail was increased from the original 8. Detailed ground and aerial studies were carried out of two outbreak cases of considerable importance. It was demonstrated that multiple regression was able to predict the tornadic potential of a given thunderstorm cell by its cirrus anvil plume characteristics. It was also shown that the plume outflow intensity and the deviation of the plume alignment from storm relative winds at anvil altitude could account for the variance in tornadic potential for a given cell ranging from 0.37 to 0.82 for linear to values near 0.9 for quadratic regression. Several predictors were used in various discriminant analysis models and in censored regression models to obtain forecasts of whether a cell is tornadic and how strong tornadic it could be potentially. The experiments were performed with the synoptic scale vertical shear in the horizontal wind and with synoptic scale surface vorticity in the proximity of the cell.

Anderson, Charles E.↗
DOE OSTI2020

Feature Engineering and Process Mining to Enable Hazard Detection in Health Information Technology

Motivation for this work originates from a recognized need for developing data-driven approaches through analysis of complex electronic health records. Specifically, we aim to enhance the reliability of health information technology (HIT) systems by detection of plausible HIT hazards in clinical order transactions. In the absence of well-defined event logs in corporate data warehouses, our proposed approach identifies relevant timestamped data fields that could indicate transactions in the clinical order life cycle generating raw event sequences. Subsequently, we adopt state transitions of the OASIS Human Task standard to map the raw event sequences and simplify the complex process that clinical radiology orders go through. We describe how the current approach provides the potential to investigate areas of improvement and potential hazards in HIT systems. The discussion concludes with a use case and opportunities for future applications.

Ozmen, Ozgur↗
NASA NTRS1982

The evolution of Florida thunderstorms on 23 September 1979 as observed by an airborne passive microwave radiometer

The observations made by the aircraft are examined in order to determine sensing parameters for future satellite missions. Minimum brightness temperatures substantially below atmospheric temperatures are revealed in the data. Scattering by an ice layer within the clouds is postulated as the cause. A one-dimensional cloud model initialized with a representative local sounding gives reasonable values for the height and thickness of this ice layer. The model cloud is similar to the observed cloud in both cloud top height and radar reflectivity. A 'mystery' feature observed by the microwave sensors as an area of enhanced scattering, suggesting an updraft core of graupel that in turn is indicative of a convective tower is considered of particular interest. It is noted that this feature was masked in the visible and infrared sensors by the presence of upper-level semitransparent cirrus. The detection of this mystery feature is seen as suggesting that passive microwave sensing of convective areas may provide information regarding the location and/or strength of the more active towers which cannot be detected now with conventional visible or infrared instruments because of a uniform higher-level cloud cover.

Hakkarinen, I. M.↗
NASA NTRS2021

Multi-Resolution Elevation Mapping and Safe Landing Site Detection with Applications to Planetary Rotorcraft

In this paper, we propose a resource-efficient approach to provide an autonomous UAV with an on-board perception method to detect safe, hazard-free landing sites during flights over complex 3D terrain. We aggregate 3D measurements acquired from a sequence of monocular images by a Structure-from-Motion approach into a local, robot-centric, multi-resolution elevation map of the overflown terrain, which fuses depth measurements according to their lateral surface resolution (pixel-footprint) in a probabilistic framework based on the concept of dynamic Level of Detail. Map aggregation only requires depth maps and the associated poses, which are obtained from an on-board Visual Odometry algorithm. An efficient landing site detection method then exploits the features of the underlying multi-resolution map to detect safe landing sites based on the slope, roughness, and quality of the reconstructed terrain surface. The evaluation of the performance of the mapping and landing site detection modules are analyzed independently and jointly in simulated and realworld experiments in order to establish the efficacy of the proposed approach.

Brockers, Roland↗
DOE OSTI2023

Superconductivity and magnetic and transport properties of single-crystalline CaK ( Fe 1 – x Cr x ) 4 As 4

Members of the CaK (Fe 1–x Cr x ) 4 As 4 series have been synthesized by high-temperature solution growth in single-crystalline form and characterized by x-ray diffraction, elemental analysis, and magnetic and transport measurements. The effects of Cr substitution on the superconducting and magnetic ground states of CaKFe 4 As 4 (T c = 35 K) have been studied. These measurements show that the superconducting transition temperature decreases monotonically and is finally suppressed below 1.8 K as x is increased from 0 to 0.038. For x-values greater than 0.012, signatures of a magnetic transition can be detected in magnetic measurements with the associated features in the transport measurements becoming detectable for x ≥ 0.038. The magnetic transition temperature increases in a roughly linear manner as Cr substitution increases. A temperature-composition (T – x) phase diagram is constructed, revealing a half-dome of superconductivity with the magnetic transition temperature, T*, appearing near 22 K for x ~ 0.017 and rising slowly up to 60 K for x ~ 0.077. The T – x phase diagrams for CaK (Fe 1–x T x ) 4 As 4 for T = Cr and Mn are essentially the same despite the nominally different band filling; this is in marked contrast to T = Co and Ni series for which the T – x diagrams scale by a factor of 2, consistent with the different changes in band filling Co and Ni would produce when replacing Fe. Superconductivity of CaK (Fe 1–x Cr x ) 4 As 4 is also studied as a function of magnetic field. A clear change in $H^{'}_{c2}$ (T)/T c , where $H^{'}_{c2}$ (T) is dH c2 (T)/dT, at x ~ 0.012 is observed and probably is related to a change of the Fermi surface due to magnetic order. Further, coherence length and the London penetration depths are also calculated based on H c1 and H c2 data. Both of them as a function of x show changes near x = 0.012, again consistent with Fermi surface changes associated with the magnetic ordering seen for higher x-values.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1979

The 4 to 8 micron spectrum of the galactic center

Observations of the complex Sgr A W(N) with a 28-arcsec beam and 1.5% spectral resolution are reported. Neither unidentified absorption features at 6.0 and 6.8 microns nor emission features at 6.2 and 7.7 microns were detected. The absence of the absorption features demonstrates that they are not characteristic of general interstellar extinction. The absence of emission features suggests that there is considerable distance between the ionized gas and the molecular clouds. The absence of 6.2- and 7.7-micron emission features also suggests that a feature previously seen at 3.3-3.4 microns is an absorption at 3.4 microns, and this absorption is apparently characteristic of interstellar extinction. The strength of the forbidden Ar II emission indicates an overabundance of argon. CO absorption seen at 4.67 microns indicates that saturation effects are not large, and there is evidently a large velocity dispersion in the line of sight to the infrared sources.

Willner, S. P.↗
NASA NTRSDate not supplied

Interpretable Machine Learning Models for Autonomous Characterization of Analogue Ocean World Seawater Chemistry and Biosignature Potential Using Isotope Ratio Data

Background: Future missions to ocean worlds, such as Enceladus and Europa, will attempt to characterize the subsurface seawater chemistry and assess the potential for life. Such missions will be equipped with capabilities to precisely measure volatile isotopes in plumes, atmospheres, and exospheres. Motivation: While large isotopic fractionations can indicate a biological source, there are signatures resulting from abiotic geochemical processes that mimic isotopic biosignatures. While machine learning (ML) has the potential to disentangle competing effects and biotic mimicry, high-dimensional isotope ratio mass spectrometry (IRMS) data is likely to contain noise/irrelevant features and involve complex statistical interactions that make human inference and interpretation difficult. Further, ML predictions with as far-reaching implications as an extraterrestrial biosignature on an ocean world requires the use of interpretable models (i.e., not “black box” models) with physically and mathematically meaningful feature spaces along with false positive diagnostics. Methods: We use volatile CO2 IRMS data of analogue ocean world seawaters to validate an ML approach to provide biogeochemical context for biosignature detection. We employ a feature selection method called nearest-neighbor projected distance regression (NPDR) that detects statistical interactions and helps elucidate the mechanisms of the Random Forest classification models. Results: We train and validate predictive ML models on volatile CO2 IRMS data of analogue ocean world seawaters to predict major salt components (e.g., MgSO4, NaHCO3), pH, ionic strength, and the presence of biosignatures. Features derived from IRMS measurements are augmented with extracted time-series features. Our results show high test accuracy and interpretability, which is increased by interaction network visualization, sample-wise variable importance scores, and single-sample class probability estimates. We demonstrate an ML mission software solution that triggers autonomous data transmission and biogeochemical sample prediction.

geochemistry↗
DOE OSTI2022

Advancing Vision-based Feedback and Convolutional Neural Networks for Visual Outlier Detection

Machine learning has matured into a technology that has immediate applicability to the surveillance needs of nuclear material storage containers. These containers at LANL are the barrier preventing release of radioactive material to the workers, public, and environment during the storage period of the material. Annual surveillance activities can only provide coverage on a handful of containers. There is a significant need for surveillance tools to identify potential issues and precursors to containment failure that can be used during opportunistic inspections and, more generally, outside of annual surveillance activities. In this report we provide details on the advancement of our proposed embodiment that combines an automation system for taking pictures and a high-accuracy machine learning-driven object detection software. We further showcase the improvements on the software side with progress on extracting unique identification features and advances in detecting damage. The current state of the system captures subject matter expert training and a space-conscious design whose implementation is envisioned in the near future.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
NASA NTRS2013

Stellar Populations in Compact Galaxy Groups: a Multi-wavelength Study of HCGs 16, 22, and 42, Their Star Clusters, and Dwarf Galaxies

We present a multi-wavelength analysis of three compact galaxy groups, Hickson compact groups (HCGs) 16, 22, and 42, which describe a sequence in terms of gas richness, from space- (Swift, Hubble Space Telescope (HST), and Spitzer) and ground-based (Las Campanas Observatory and Cerro Tololo Inter-American Observatory) imaging and spectroscopy.We study various signs of past interactions including a faint, dusty tidal feature about HCG 16A, which we tentatively age-date at <1 Gyr. This represents the possible detection of a tidal feature at the end of its phase of optical observability. Our HST images also resolve what were thought to be double nuclei in HCG 16C and D into multiple, distinct sources, likely to be star clusters. Beyond our phenomenological treatment, we focus primarily on contrasting the stellar populations across these three groups. The star clusters show a remarkable intermediate-age population in HCG 22, and identify the time at which star formation was quenched in HCG 42. We also search for dwarf galaxies at accordant redshifts. The inclusion of 33 members and 27 "associates" (possible members) radically changes group dynamical masses, which in turn may affect previous evolutionary classifications. The extended membership paints a picture of relative isolation in HCGs 16 and 22, but shows HCG 42 to be part of a larger structure, following a dichotomy expected from recent studies. We conclude that (1) star cluster populations provide an excellent metric of evolutionary state, as they can age-date the past epochs of star formation; and (2) the extended dwarf galaxy population must be considered in assessing the dynamical state of a compact group.

Compact Galaxy↗
NASA NTRS2002

New Evidence For Proton Cyclotron Resonance In a Magnetar Strength Field From SGR 1806-20

A great deal of evidence has recently been gathered in favor of the picture that Soft Gamma Repeaters and Anomalous X-Ray Pulsars are powered by ultra-strong magnetic fields (B greater than 10(exp 14) G; i.e. magnetars). Nevertheless, present determination of the magnetic field in such magnetar candidates has been indirect and model dependent. A key prediction concerning magnetars is the detection of ion cyclotron resonance features, which would offer a decisive diagnostic of the field strength. Here we present the detection of a 5 keV absorption feature in a variety of bursts from the Soft Gamma Repeater SGR 1806-20, confirming our initial discovery and establishing the presence of the feature in the source's burst spectra. The line feature is well explained as proton cyclotron resonance in an ultra-strong magnetic field, offering a direct measurement of SGR 1806-20's magnetic field (B approx. 10(exp 15) G) and a clear evidence of a magnetar. Together with the source's spin-down rate, the feature also provides the first measurement of the gravitational redshift, mass and radius of a magnetar.

Parke, William↗
NASA NTRS2003

All in the Family: What Brown Dwarfs Teach Us About Extrasolar Giant Planets

As we await the first direct image of an extrasolar giant planet, we can turn to theory and the experience gained in the campaign to detect and understand brown dwarfs for guidance on what to expect. As with any new arrival to a family, there should be a strong family resemblance (one hopes) along with notable unique features and interesting peculiarities. The 300 or so known L and T dwarfs, combined with our own giant planets, already span much of the effective temperature range within which extrasolar planets will be found. Only objects with thick, easily detectable, water clouds have yet to be seen. Thus we already know much of the family. I will describe what we have learned from studying these objects, focusing on the important roles clouds and atmospheric chemistry play in affecting their atmospheres and emergent spectra. Relying on these findings and theoretical models, I'll sketch out what we can expect from extrasolar giant planets, focusing on easily detectable features. Some wild cards, of course, are to be expected. Photochemical hazes, in particular, may obscure the family traits on the faces of Jupiter's distant cousins and may make one wonder, at least momentarily, about the milkman.

Marley, M.↗
DOE OSTI2022

ThunderSecure: deploying real-time intrusion detection for 100G research networks by leveraging stream-based features and one-class classification network

Nowadays, data generated by large-scale scientific experiments are on the scale of petabytes per month. These data are transferred through dedicated high-bandwidth networks (40/100G) across distributed sites for processing, storage, and analysis. Like general purpose networks, research networks experience intrusions. However, monitoring anomalies in such high-speed network traffics is challenging given current cyber-infrastructure. Moreover, traditional network intrusion detection systems (NIDS) are signature based. However, anomaly patterns are difficult to define and that rulesets are often not updated frequently enough to reflect the changes of attack behaviors. We present ThunderSecure, a high-throughput, unsupervised learning-based intrusions detection system for 100G research networks. ThunderSecure implements an efficient packet processing and detection pipeline using multi-cores and GPUs. It extracts statistical and temporal features from real-time network data streams and feeds them to a one-class anomaly detection network. A baseline of normal distribution will be created based on the training observation. Testing traffic deviated from the learned profile will be marked as anomalies. We trained ThunderSecure on hundreds of billions of science data packets mirrored from two 100G network connections at Fermi National Accelerator Laboratory. The detection performance was evaluated on traffic captured from the same research network days and weeks after the training with different types of attack flows injected. Results show that ThunderSecure can recognize science data traffic captured long after the training and made nearly certain detection on the segment of the streams where anomalous flows were injected.

100G research network↗