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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS1996

Feature Selection for Classification of Polar Regions Using a Fuzzy Expert System

Labeling, feature selection, and the choice of classifier are critical elements for classification of scenes and for image understanding. This study examines several methods for feature selection in polar regions, including the list, of a fuzzy logic-based expert system for further refinement of a set of selected features. Six Advanced Very High Resolution Radiometer (AVHRR) Local Area Coverage (LAC) arctic scenes are classified into nine classes: water, snow / ice, ice cloud, land, thin stratus, stratus over water, cumulus over water, textured snow over water, and snow-covered mountains. Sixty-seven spectral and textural features are computed and analyzed by the feature selection algorithms. The divergence, histogram analysis, and discriminant analysis approaches are intercompared for their effectiveness in feature selection. The fuzzy expert system method is used not only to determine the effectiveness of each approach in classifying polar scenes, but also to further reduce the features into a more optimal set. For each selection method,features are ranked from best to worst, and the best half of the features are selected. Then, rules using these selected features are defined. The results of running the fuzzy expert system with these rules show that the divergence method produces the best set features, not only does it produce the highest classification accuracy, but also it has the lowest computation requirements. A reduction of the set of features produced by the divergence method using the fuzzy expert system results in an overall classification accuracy of over 95 %. However, this increase of accuracy has a high computation cost.

Penaloza, Mauel A.↗
NASA NTRS2002

Stimulus information contaminates summation tests of independent neural representations of features

Many models of visual processing assume that visual information is analyzed into separable and independent neural codes, or features. A common psychophysical test of independent features is known as a summation study, which measures performance in a detection, discrimination, or visual search task as the number of proposed features increases. Improvement in human performance with increasing number of available features is typically attributed to the summation, or combination, of information across independent neural coding of the features. In many instances, however, increasing the number of available features also increases the stimulus information in the task, as assessed by an optimal observer that does not include the independent neural codes. In a visual search task with spatial frequency and orientation as the component features, a particular set of stimuli were chosen so that all searches had equivalent stimulus information, regardless of the number of features. In this case, human performance did not improve with increasing number of features, implying that the improvement observed with additional features may be due to stimulus information and not the combination across independent features.

NASA Discipline Space Human Factors↗
NASA NTRS2010

Confidence-Based Feature Acquisition

Confidence-based Feature Acquisition (CFA) is a novel, supervised learning method for acquiring missing feature values when there is missing data at both training (learning) and test (deployment) time. To train a machine learning classifier, data is encoded with a series of input features describing each item. In some applications, the training data may have missing values for some of the features, which can be acquired at a given cost. A relevant JPL example is that of the Mars rover exploration in which the features are obtained from a variety of different instruments, with different power consumption and integration time costs. The challenge is to decide which features will lead to increased classification performance and are therefore worth acquiring (paying the cost). To solve this problem, CFA, which is made up of two algorithms (CFA-train and CFA-predict), has been designed to greedily minimize total acquisition cost (during training and testing) while aiming for a specific accuracy level (specified as a confidence threshold). With this method, it is assumed that there is a nonempty subset of features that are free; that is, every instance in the data set includes these features initially for zero cost. It is also assumed that the feature acquisition (FA) cost associated with each feature is known in advance, and that the FA cost for a given feature is the same for all instances. Finally, CFA requires that the base-level classifiers produce not only a classification, but also a confidence (or posterior probability).

Wagstaff, Kiri L.↗
DOE OSTI2025

Performance evaluation of automated data-driven feature extraction and selection methods for practical and scalable building energy consumption prediction models

Here, this study quantifies the impact of automated feature engineering methods (feature extraction and selection) on the quality and accuracy of machine learning models that predict building energy consumption. The case study compares model performance for three main scenarios: baseline (no feature extraction and selection), feature extraction only, and feature extraction combined with feature selection (filter and/or wrapper methods) for fully trained machine learning models for 200 metered/sub-metered energy measurements across 118 real buildings. For consistency, the same machine learning model architecture (a black box deep learning neural network with probabilistic forecast output) was used for all scenarios. Based on results, all feature engineering methods provided noticeable prediction accuracy improvements (e.g., 29%-68% median prediction improvement) compared to baseline scenarios. However, in this application, feature selection methods provide little practical value due to their limited performance gains and high computational cost. Smarter algorithm development supported by better computational environments will be needed before feature selection methods can reliably and efficiently improve predictive model performance.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1993

Parabolic features and the erosion rate on Venus

The impact cratering record on Venus consists of 919 craters covering 98 percent of the surface. These craters are remarkably well preserved, and most show pristine structures including fresh ejecta blankets. Only 35 craters (3.8 percent) have had their ejecta blankets embayed by lava and most of these occur in the Atla-Beta Regio region; an area thought to be recently active. parabolic features are associated with 66 of the 919 craters. These craters range in size from 6 to 105 km diameter. The parabolic features are thought to be the result of the deposition of fine-grained ejecta by winds in the dense venusian atmosphere. The deposits cover about 9 percent of the surface and none appear to be embayed by younger volcanic materials. However, there appears to be a paucity of these deposits in the Atla-Beta Regio region, and this may be due to the more recent volcanism in this area of Venus. Since parabolic features are probably fine-grain, wind-deposited ejecta, then all impact craters on Venus probably had these deposits at some time in the past. The older deposits have probably been either eroded or buried by eolian processes. Therefore, the present population of these features is probably associated with the most recent impact craters on the planet. Furthermore, the size/frequency distribution of craters with parabolic features is virtually identical to that of the total crater population. This suggests that there has been little loss of small parabolic features compared to large ones, otherwise there should be a significant and systematic paucity of craters with parabolic features with decreasing size compared to the total crater population. Whatever is erasing the parabolic features apparently does so uniformly regardless of the areal extent of the deposit. The lifetime of parabolic features and the eolian erosion rate on Venus can be estimated from the average age of the surface and the present population of parabolic features.

Strom, Robert G.↗
NASA NTRS1996

Unsupervised Pattern Classifier for Abnormality-Scaling of Vibration Features for Helicopter Gearbox Fault Diagnosis

A new unsupervised pattern classifier is introduced for on-line detection of abnormality in features of vibration that are used for fault diagnosis of helicopter gearboxes. This classifier compares vibration features with their respective normal values and assigns them a value in (0, 1) to reflect their degree of abnormality. Therefore, the salient feature of this classifier is that it does not require feature values associated with faulty cases to identify abnormality. In order to cope with noise and changes in the operating conditions, an adaptation algorithm is incorporated that continually updates the normal values of the features. The proposed classifier is tested using experimental vibration features obtained from an OH-58A main rotor gearbox. The overall performance of this classifier is then evaluated by integrating the abnormality-scaled features for detection of faults. The fault detection results indicate that the performance of this classifier is comparable to the leading unsupervised neural networks: Kohonen's Feature Mapping and Adaptive Resonance Theory (AR72). This is significant considering that the independence of this classifier from fault-related features makes it uniquely suited to abnormality-scaling of vibration features for fault diagnosis.

Jammu, Vinay B.↗
NASA NTRSDate not supplied

Large Impact Features on Icy Galilean Satellites: Implications for Ice Shell Thickness and Habitability.

Nowhere in the solar system are impact morphologies observed in greater variety than on the icy Galilean satellites. This is very likely a consequence of the structural and thermal state of the crust at the time of impact, and perhaps impact velocity. We have conducted a multi-disciplinary investigation to study how these features formed. The particular combination of geophysical factors and impactor characteristics that is shared by these satellites is likely responsible for these features. We have derived Digital Terrain Models for a number of these features, which have been used as a tool for producing facies maps. Impact features on Ganymede and Callisto are relatable to impact features on Europa, with implications for its ice shell history. We have identified two broad classes of these impact features: (a) Crater forms, which variously include pits, central domes, and crater rims; and (b) Palimpsests (including pene-palimpsests), which all have smooth enclosed central plains, an extensive outer undulating plains unit, concentric arcuate ridges(in the case of pene-palimpsests), and no recognizable rim. The very large, measured volume of the undulating plains unit of the pene-palimpsest Buto, Ganymede, substantially exceeds the amount of target material that could have been both melted and excavated by the impact event itself. Therefore, we conclude that the undulating plains material was derived from a fluid or “slushy” layer in the near-surface target at the time of impact. The recognition of undulating plains as the dominant unit in Memphis and Nidaba, two other palimpsests on Ganymede that we have mapped(which display highly variable crater counts, with Buto being the least cratered),leads us to a working hypothesis that these plains only form where and when the target has substantial near surface fluid or “slush.” By extension, all other impact features on Ganymede and Callisto, such as those with central pits and central domes, formed in targets with no pre-existing, or at most inconsequential, amounts of fluid or “slush.” Supporting this conclusion, modeling by members of our group indicates that the present topography of impact features with central pits and domes can be largely explained by the behavior of ice alone, with no or little contribution from fluids. Our study supports explanations for the formation and final appearance of palimpsests (and pene-palimpsests) that are entirely applicable to this feature class, and sharply distinct from explanations for other impact features (crater forms) on Ganymede and Callisto.

Jeffrey M Moore↗
NASA NTRS1989

High-spectral resolution observations of the 3.29 micron emission feature: Comparison to QCC and PAHs

Two of the most promising explanations for the origin of the interstellar emission features observed at 3.29, 3.4, 6.2, 7.7, 8.6, and 11.3 microns are: quenched carbonaceous composite (QCC) and polycyclic aromatic hydrocarbons (PAHs). High resolution spectra are given of the 3.29 micron emission feature which were taken with the Cooled Grating Array Spectrometer at the NASA Infrared Telescope Facility and previously published. These spectra show that the peak wavelength of the 3.29 micron feature is located at 3.295 + or - 0.005 micron and that it is coincident with the peak absorbance of QCC. The peak wavelength of the 3.29 micron feature appears to be the same in all of the sources observed thus far. However, the width of the feature in HD 44179 and Elias 1 is only 0.023 micron, which is smaller than the 0.043 micron width in NGC 7027, IRAS 21282+5050, the Orion nebula, and BD+30 deg 3639. Spectra of NGC 7027, QCC, and PAHs is shown. QCC matches the 3.29 micron interstellar emission feature very closely in the wavelength of the peak, and it produces a single feature. On the other hand, PAHs rarely match the peak of the interstellar emission feature, and characteristically produce multiple features.

Tokunaga, Alan T.↗
NASA NTRS1992

GATOR: Requirements capturing of telephony features

We are developing a natural language-based, requirements gathering system called GATOR (for the GATherer Of Requirements). GATOR assists in the development of more accurate and complete specifications of new telephony features. GATOR interacts with a feature designer who describes a new feature, set of features, or capability to be implemented. The system aids this individual in the specification process by asking for clarifications when potential ambiguities are present, by identifying potential conflicts with other existing features, and by presenting its understanding of the feature to the designer. Through user interaction with a model of the existing telephony feature set, GATOR constructs a formal representation of the new, 'to be implemented' feature. Ultimately GATOR will produce a requirements document and will maintain an internal representation of this feature to aid in future design and specification. This paper consists of three sections that describe (1) the structure of GATOR, (2) POND, GATOR's internal knowledge representation language, and (3) current research issues.

Dankel, Douglas D., II↗
NASA NTRS1991

Decision boundary feature selection for non-parametric classifier

Feature selection has been one of the most important topics in pattern recognition. Although many authors have studied feature selection for parametric classifiers, few algorithms are available for feature selection for nonparametric classifiers. In this paper we propose a new feature selection algorithm based on decision boundaries for nonparametric classifiers. We first note that feature selection for pattern recognition is equivalent to retaining 'discriminantly informative features', and a discriminantly informative feature is related to the decision boundary. A procedure to extract discriminantly informative features based on a decision boundary for nonparametric classification is proposed. Experiments show that the proposed algorithm finds effective features for the nonparametric classifier with Parzen density estimation.

Lee, Chulhee↗
NASA NTRS1993

Decision Boundary Feature Extraction for Nonparametric Classification

Feature extraction has long been an important topic in pattern recognition. Although many authors have studied feature extraction for parametric classifiers, relatively few feature extraction algorithms are available for nonparametric classifiers. A new feature extraction algorithm based on decision boundaries for nonparametric classifiers is proposed. It is noted that feature extraction for pattern recognition is equivalent to retaining 'discriminantly informative features' and a discriminantly informative feature is related to the decision boundary. Since nonparametric classifiers do not define decision boundaries in analytic form, the decision boundary and normal vectors must be estimated numerically. A procedure to extract discriminantly informative features based on a decision boundary for non-parametric classification is proposed. Experiments show that the proposed algorithm finds effective features for the nonparametric classifier with Parzen density estimation.

Lee, Chulhee↗
NASA NTRS1984

The mysterious 10 micron emission feature in the spectrum of Nova Aquilae 1982

Broad-band 1.2-23 micron photometry and 1 percent resolution 7-14 micron spectrophotometry of Nova Aql 1982 are presented. This nova developed similarly to other dusty novae in that the appearance of thermal infrared emission from a circumstellar dust shell was coincident with a downward transition at visual wavelengths. A strong 10 micron emission feature appeared in the spectrum of Nova Aql 1982 during the dust shell development phase. This feature was not entirely similar to emission features previously observed in other stars with circumstellar shells. The contrast of the nova's 10 micron feature was larger than those observed in the SiC-rich shells of carbon stars. On the other hand, although the nova emission feature was reminiscent of the 10 micron silicate emission feature observed in oxygen-rich supergiants, it peaked at a slightly longer wavelength and there was no corresponding 20 micron emission feature. The contrast of the feature increased with time. It is concluded that an anomalous dust grain component, tentatively identified as SiC, nucleated and grew in the circumstellar shell of Nova Aql 1982.

Ney, E. P.↗
NASA NTRS1988

Possible identifications of the 3.4 micrometer feature

A feature at 3.4 micrometer was first detected in Comet Halley by the IKS spectrometer on board the Vega 1 probe; and subsequently from the ground. The feature has since been reported in Comet Wilson. The presence of the feature is of considerable interest for a number of reasons. First, it may represent the detection of a new parent molecule, and when combined with data from Giotto and Vega yield new information on cometary chemistry and the early solar system composition. Secondly, it may represent a link to the interstellar medium, the feature corresponds in wavelength and shape with an interstellar feature seen in absorption in a luminous star, towards the Galactic center known as GC-IRS7. The feature in turn is thought to be related with a growing family of unidentified infrared emission features seen in stellar objects, planetary nebulae, reflection nebulae, HII regions and extra galactic sources. These features occur at wavelengths 3.3, 3.4, 3.5, 6.2, 7.7, 8.6, and 11.25 micrometers. Further identification theory is given.

Danks, Anthony C.↗
NASA NTRS1989

Using infrared spectral features to probe circumstellar dust shells around cool stars

IRAS observations of cool stars provide low resolution spectra in the mid-infrared and also give fluxes at four wavelength bands from which color-color diagrams are constructed. The later have been used to study the evolution of these stars: as an O-rich star evolves to become a C-rich star and its detached dust shell moves further away, its evolution can be tracked on a color-color diagram. A major factor in determining the position of either C-rich or O-rich stars on the 12-25-60 micron color-color diagram is the presence of spectral features in the mid-IR. O-rich stars show a 9.8 micron silicate feature, while C-rich stars have a SiC feature at 11.2 microns. IRAS observations indicate that the SiC feature is quite narrow and uniform in shape showing little variation from star to star. The full width at half maximum (FWHM) is 1.6 + or - 0.15 microns. On the other hand, the shape of the silicate feature varies widely among the O-rich stars, with a FWHM ranging from 2 to 3 microns. The characteristics of circumstellar dust shells should manifest themselves both in the flux spectrum and in the details of the spectral features. To provide a coherent interpretation for these IRAS observations, models were constructed (using a radiative transfer code) of dust shells around O-rich and C-rich stars. Realistic grain opacities were used which include spectral features of varying intrinsic widths (e.g., Gaussian features at 10 microns with half width at half maximum of 0.5 and 1.0 microns).

Egan, Michael P.↗
NASA NTRS1998

Mineralization of Bacteria in Terrestrial Basaltic Rocks: Comparison With Possible Biogenic Features in Martian Meteorite Allan Hills 84001

The identification of biogenic features altered by diagenesis or mineralization is important in determining whether specific features in terrestrial rocks and in meteorites may have a biogenic origin. Unfortunately, few studies have addressed the formation of biogenic features in igneous rocks, which may be important to these phenomena, including the controversy over possible biogenic features in basaltic martian meteorite ALH84001. To explore the presence of biogenic features in igneous rocks, we examined microcosms growing in basaltic small-scale experimental growth chambers or microcosms. Microbial communities were harvested from aquifers of the Columbia River Basalt (CRB) group and grown in a microcosm containing unweathered basalt chips and groundwater (technique described in. These microcosms simulated natural growth conditions in the deep subsurface of the CRB, which should be a good terrestrial analog for any putative martian subsurface ecosystem that may have once included ALH84001. Here we present new size measurements and photomicrographs comparing the putative martian fossils to biogenic material in the CRB microcosms. The range of size and shapes of the biogenic features on the CRB microcosm chips overlaps with and is similar to those on ALH84001 chips. Although this present work does not provide evidence for the biogenicity of ALH84001 features, we believe that, based on criteria of size, shape, and general morphology, a biogenic interpretation for the ALH84001 features remains plausible.

Thomas-Keprta, K. L.↗
NASA NTRS1999

Windblown Features on Venus and Geological Mapping

The objectives of this study were to: 1) develop a global data base of aeolian features by searching Magellan coverage for possible time-variable wind streaks, 2) analyze the data base to characterize aeolian features and processes on Venus, 3) apply the analysis to assessments of wind patterns near the surface and for comparisons with atmospheric circulation models, 4) analyze shuttle radar data acquired for aeolian features on Earth to determine their radar characteristics, and 5) conduct geological mapping of two quadrangles. Wind, or aeolian, features are observed on Venus and aeolian processes play a role in modifying its surface. Analysis of features resulting from aeolian processes provides insight into characteristics of both the atmosphere and the surface. Wind related features identified on Venus include erosional landforms (yardangs), depositional dune fields, and features resulting from the interaction of the atmosphere and crater ejecta at the time of impact. The most abundant aeolian features are various wind streaks. Their discovery on Venus afforded the opportunity to learn about the interaction of the atmosphere and surface, both for the identification of sediments and in mapping near-surface winds.

Greeley, Ronald↗
NASA NTRS2005

Automated Image Registration Using Morphological Region of Interest Feature Extraction

With the recent explosion in the amount of remotely sensed imagery and the corresponding interest in temporal change detection and modeling, image registration has become increasingly important as a necessary first step in the integration of multi-temporal and multi-sensor data for applications such as the analysis of seasonal and annual global climate changes, as well as land use/cover changes. The task of image registration can be divided into two major components: (1) the extraction of control points or features from images; and (2) the search among the extracted features for the matching pairs that represent the same feature in the images to be matched. Manual control feature extraction can be subjective and extremely time consuming, and often results in few usable points. Automated feature extraction is a solution to this problem, where desired target features are invariant, and represent evenly distributed landmarks such as edges, corners and line intersections. In this paper, we develop a novel automated registration approach based on the following steps. First, a mathematical morphology (MM)-based method is used to obtain a scale-orientation morphological profile at each image pixel. Next, a spectral dissimilarity metric such as the spectral information divergence is applied for automated extraction of landmark chips, followed by an initial approximate matching. This initial condition is then refined using a hierarchical robust feature matching (RFM) procedure. Experimental results reveal that the proposed registration technique offers a robust solution in the presence of seasonal changes and other interfering factors. Keywords-Automated image registration, multi-temporal imagery, mathematical morphology, robust feature matching.

Plaza, Antonio↗
NASA NTRS2010

Real-Time Feature Tracking Using Homography

This software finds feature point correspondences in sequences of images. It is designed for feature matching in aerial imagery. Feature matching is a fundamental step in a number of important image processing operations: calibrating the cameras in a camera array, stabilizing images in aerial movies, geo-registration of images, and generating high-fidelity surface maps from aerial movies. The method uses a Shi-Tomasi corner detector and normalized cross-correlation. This process is likely to result in the production of some mismatches. The feature set is cleaned up using the assumption that there is a large planar patch visible in both images. At high altitude, this assumption is often reasonable. A mathematical transformation, called an homography, is developed that allows us to predict the position in image 2 of any point on the plane in image 1. Any feature pair that is inconsistent with the homography is thrown out. The output of the process is a set of feature pairs, and the homography. The algorithms in this innovation are well known, but the new implementation improves the process in several ways. It runs in real-time at 2 Hz on 64-megapixel imagery. The new Shi-Tomasi corner detector tries to produce the requested number of features by automatically adjusting the minimum distance between found features. The homography-finding code now uses an implementation of the RANSAC algorithm that adjusts the number of iterations automatically to achieve a pre-set probability of missing a set of inliers. The new interface allows the caller to pass in a set of predetermined points in one of the images. This allows the ability to track the same set of points through multiple frames.

Clouse, Daniel S.↗