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All sourcesNASA NTRSDOE OSTI
NASA NTRS1983

The optical counterparts of compact galactic X-ray sources

Ninety-six optical identifications of X-ray sources presumed to be compact objects are presented and discussed. X-ray and optical classifications of the sources are considered, and the several types of systems are discussed. These include neutron star binaries with massive and low-mass stellar components, neutron stars in supernova remnants, cataclysmic variables, and 'isolated' hot white dwarfs. The information that can be derived from optical observations of neutron-star systems with low-mass optical companions is emphasized.

Bradt, H. V. D.↗
NASA NTRS2004

Automated Classification of ROSAT Sources Using Heterogeneous Multiwavelength Source Catalogs

We describe an on-line system for automated classification of X-ray sources, ClassX, and present preliminary results of classification of the three major catalogs of ROSAT sources, RASS BSC, RASS FSC, and WGACAT, into six class categories: stars, white dwarfs, X-ray binaries, galaxies, AGNs, and clusters of galaxies. ClassX is based on a machine learning technology. It represents a system of classifiers, each classifier consisting of a considerable number of oblique decision trees. These trees are built as the classifier is 'trained' to recognize various classes of objects using a training sample of sources of known object types. Each source is characterized by a preselected set of parameters, or attributes; the same set is then used as the classifier conducts classification of sources of unknown identity. The ClassX pipeline features an automatic search for X-ray source counterparts among heterogeneous data sets in on-line data archives using Virtual Observatory protocols; it retrieves from those archives all the attributes required by the selected classifier and inputs them to the classifier. The user input to ClassX is typically a file with target coordinates, optionally complemented with target IDs. The output contains the class name, attributes, and class probabilities for all classified targets. We discuss ways to characterize and assess the classifier quality and performance and present the respective validation procedures. Based on both internal and external validation, we conclude that the ClassX classifiers yield reasonable and reliable classifications for ROSAT sources and have the potential to broaden class representation significantly for rare object types.

McGlynn, Thomas↗
NASA NTRS1993

Classifying multispectral data by neural networks

Several energy functions for synthesizing neural networks are tested on 2-D synthetic data and on Landsat-4 Thematic Mapper data. These new energy functions, designed specifically for minimizing misclassification error, in some cases yield significant improvements in classification accuracy over the standard least mean squares energy function. In addition to operating on networks with one output unit per class, a new energy function is tested for binary encoded outputs, which result in smaller network sizes. The Thematic Mapper data (four bands were used) is classified on a single pixel basis, to provide a starting benchmark against which further improvements will be measured. Improvements are underway to make use of both subpixel and superpixel (i.e. contextual or neighborhood) information in tile processing. For single pixel classification, the best neural network result is 78.7 percent, compared with 71.7 percent for a classical nearest neighbor classifier. The 78.7 percent result also improves on several earlier neural network results on this data.

Telfer, Brian A.↗
NASA NTRS1977

The ultraviolet spectra of four binaries observed with the S59 spectrometer

Ultraviolet spectra of Omicron And, Alpha CrB, Eta Ori A, and Alpha Vir, which were obtained with the S59 spectrometer at a resolution of 1.7 A in three 100-A-wide regions centered at 2110, 2454, and 2825 A, have been studied for the presence or absence of effects due to their binary nature. As may have been anticipated from their orbital and other characteristics, no indication of strong binary interactions were seen in these observations. However, there are certain spectral peculiarities suggesting the possibility of modifications of spectral classifications for some of these objects. A rather unusual spectral behavior in Alpha Vir is also noted. In addition, based primarily on a review of available literature, attention is drawn to a remarkable property of the third component in Eta Ori A.

Herczeg, T. J.↗
NASA NTRS2009

Stereo Vision Based Terrain Mapping for Off-Road Autonomous Navigation

Successful off-road autonomous navigation by an unmanned ground vehicle (UGV) requires reliable perception and representation of natural terrain. While perception algorithms are used to detect driving hazards, terrain mapping algorithms are used to represent the detected hazards in a world model a UGV can use to plan safe paths. There are two primary ways to detect driving hazards with perception sensors mounted to a UGV: binary obstacle detection and traversability cost analysis. Binary obstacle detectors label terrain as either traversable or non-traversable, whereas, traversability cost analysis assigns a cost to driving over a discrete patch of terrain. In uncluttered environments where the non-obstacle terrain is equally traversable, binary obstacle detection is sufficient. However, in cluttered environments, some form of traversability cost analysis is necessary. The Jet Propulsion Laboratory (JPL) has explored both approaches using stereo vision systems. A set of binary detectors has been implemented that detect positive obstacles, negative obstacles, tree trunks, tree lines, excessive slope, low overhangs, and water bodies. A compact terrain map is built from each frame of stereo images. The mapping algorithm labels cells that contain obstacles as no-go regions, and encodes terrain elevation, terrain classification, terrain roughness, traversability cost, and a confidence value. The single frame maps are merged into a world map where temporal filtering is applied. In previous papers, we have described our perception algorithms that perform binary obstacle detection. In this paper, we summarize the terrain mapping capabilities that JPL has implemented during several UGV programs over the last decade and discuss some challenges to building terrain maps with stereo range data.

passive perception↗
NASA NTRS1975

Data processing large quantities of multispectral information

Method is combination of digital and optical techniques. Multispectral data is coded into binary matrix format and then encoded onto photographic film. Film is holographically correlated with spectral signature to generate single-class classification map. Number of maps are optically superimposed to produce full-color, multiclass classification map.

Haskell, R. E.↗
NASA NTRS1986

A VLA survey of unidentified HEAO-1 X-ray sources

Radio observations toward 47 unidentified sources from the HEAO-1 all-sky X-ray survey (Wood et al., 1984), obtained at 1.418 GHz using the C configuration of the VLA on May 11-14, 1983 are reported. Of the 238 radio sources detected at flux density 1-3 mJy or greater, 26 are found to be within 5 arcsec of optical objects, which are thereby considered to be candidate X-ray sources. Tentative classifications of the candidates include five RS CVn systems, three AGNs, three galaxy or cluster sources, and two X-ray binaries.

Schmelz, J. T.↗
NASA NTRS1994

Quantitative spectral types for 19 Algol secondaries

Time-resolved spectra of 19 short-period Algol-type binary star systems obtained during total eclipse are used to derive the temperature spectral class of the mass-losing secondary component. The spectral classifications employed a quantitative comparison of the strengths of absorption features in stars of known spectral class with those of the program stars. The luminosity spectral class can not be determined from these data, so both main-sequence and giant stars were used for the comparison. Our spectral types are compared with published types and found to be generally in good agreement, unless the published types are derived from the light curves. The photometrically determined types are systematically later than our directly determined types. This effect is shown also to exist in catalogs of Algol parameters.

Yoon, Tae S.↗
NASA NTRS1981

The RS Canum Venaticorum binaries

This review presents a brief up-to-date summary of observational properties of RS CVn binaries, with emphasis on the photometric. A table of the 69 systems known at this time give the orbital period, mean apparent V magnitude, spectral classification, range of amplitude determinations for the photometric wave, and an indication of known period variations and eclipses. Points considered are (1) the underlying cause of the extreme surface activity, (2) the evolutionary status, (3) the geometric configuration, (4) the temperature, size, shape, location, and lifetimes of the dark spot regions, (5) synchronization of rotational and orbital motion, (6) spectroscopic features in the optical and far ultraviolet, (7) the wave migration, (8) the search for spot cycles, and (9) the orbital period variations produced by the enhanced stellar wind.

Hall, D. S.↗
NASA NTRS1988

Multifrequency observations of symbiotic stars

The discovery of symbiotic stars is described, and the results of multifrequency observations made during the past two decades are presented. Observational data identify symbiotic stars as long-period binary systems that can be divided into two basic physical classes: detached symbiotics containing a red giant (or a Mira variable), and semidetached symbiotics containing a lobe-filling red giant and a solar-type main sequence star. Three components are typically observed: (1) the cool giant component with an effective temperature of 2500-4000 K, which can be divided by the IR spectral classification into normal M giants (S-types) and heavily reddened Mira variables (D-types); (2) the hot companion displaying a bright blue continuum at UV wavelengths, which is sometimes also an X-ray source; and (3) a gaseous nebula enveloping the binary.

Kenyon, Scott J.↗
NASA NTRS1994

The X-ray selected cataclysmic variables H0459 + 246 and H0857 - 242

We report the discovery of two cataclysmic variables located with the assistance of X-ray positions from the HEAO 1 Modulation Collimator and the Large-Area Sky Survey. Each case is distinguished by evidence of two periodic modulations that appear to represent the orbital period and the spin period of the white dwarf, respectively. The first case, H0459 + 246, has been observed optically during faint states (V approximately 16), in which there are spectral features of both an accretion disk and a K star. The light curves in the V and I bands are consistent with ellipsoidal variations in the secondary stars with a binary period of 9.952 hr. X-ray observations with EXOSAT reveal a strong pulsation with a period approximately 62 minutes. This result confirms an 'intermediate polar' classification for H0459 + 246. The pulsation is observed at 63.2 minutes in the optical I band. The long orbital period opens the possibility that H0459 + 246 is a relatively young intermediate polar that might evolve into a polar. The second case, H0857--242, shows radial velocity modulations at 1.78 hr along with photometric variations at a period approximately 49 minutes. The latter are observed only during the decay phase of dwarf nova outbursts (13 less than V less than 17), which apparently recur frequently. Given the lack of X-ray monitoring observations and the absence of proof that the 49 minute periodicity is coherent over long time-scales, we regard H0857--242 as a candidate intermediate polar. Photographic records from th e Harvard Observatory Plate Library further reveal superoutbursts for H0857--242 (V approximately 11). A bright X-ray source that is both an intermediate polar and a continually cycling dwarf nova may provide an effective means of measuring the time delay for the arrival of accreting matter at the white dwarf surface, relative to the onset of optical brightening.

Remillard, R. A.↗
NASA NTRS2002

Binarization of Gray-Scaled Digital Images Via Fuzzy Reasoning

A new fast-computational technique based on fuzzy entropy measure has been developed to find an optimal binary image threshold. In this method, the image pixel membership functions are dependent on the threshold value and reflect the distribution of pixel values in two classes; thus, this technique minimizes the classification error. This new method is compared with two of the best-known threshold selection techniques, Otsu and Huang-Wang. The performance of the proposed method supersedes the performance of Huang-Wang and Otsu methods when the image consists of textured background and poor printing quality. The three methods perform well but yield different binarization approaches if the background and foreground of the image have well-separated gray-level ranges.

Dominquez, Jesus A.↗
NASA NTRS2002

Binarization of Gray-Scaled Digital Images Via Fuzzy Reasoning

A new fast-computational technique based on fuzzy entropy measure has been developed to find an optimal binary image threshold. In this method, the image pixel membership functions are dependent on the threshold value and reflect the distribution of pixel values in two classes; thus, this technique minimizes the classification error. This new method is compared with two of the best-known threshold selection techniques, Otsu and Huang-Wang. The performance of the proposed method supersedes the performance of Huang- Wang and Otsu methods when the image consists of textured background and poor printing quality. The three methods perform well but yield different binarization approaches if the background and foreground of the image have well-separated gray-level ranges.

Dominquez, Jesus A.↗
NASA NTRS2007

SWIFT Detects a remarkable Gamma-ray Burst, GRB 060514, that introduces a New Classification Scheme

Gamma ray bursts (GFU3s) are known to come in two duration classes, separated at approx.2 s. Long bursts originate from star forming regions in galaxies, have accompanying supernovae (SNe) when near enough to observe and are likely caused by massive-star collapsars. Recent observations show that short bursts originate in regions within their host galaxies with lower star formation rates, consistent with binary neutron star (NS) or NS - black hole (BH) mergers. Moreover, although their hosts are predominantly nearby galaxies, no SNe have been so far associated with short GRBs. We report here on the bright, nearby GRB 060614 that does not fit in either class. Its approx.102 s duration groups it with long GRBs, while its temporal lag and peak luminosity fall entirely within the short GRB subclass. Moreover, very deep optical observations exclude an accompanying supernova, similar to short GRBs. This combination of a long duration event without accompanying SN poses a challenge to both a collapsar and merging NS interpretation and opens the door on a new GRB classification scheme that straddles both long and short bursts.

Gehrels, N.↗
NASA NTRS1981

The evaluation of alternate methodologies for land cover classification in an urbanizing area

The usefulness of LANDSAT in classifying land cover and in identifying and classifying land use change was investigated using an urbanizing area as the study area. The question of what was the best technique for classification was the primary focus of the study. The many computer-assisted techniques available to analyze LANDSAT data were evaluated. Techniques of statistical training (polygons from CRT, unsupervised clustering, polygons from digitizer and binary masks) were tested with minimum distance to the mean, maximum likelihood and canonical analysis with minimum distance to the mean classifiers. The twelve output images were compared to photointerpreted samples, ground verified samples and a current land use data base. Results indicate that for a reconnaissance inventory, the unsupervised training with canonical analysis-minimum distance classifier is the most efficient. If more detailed ground truth and ground verification is available, the polygons from the digitizer training with the canonical analysis minimum distance is more accurate.

Smekofski, R. M.↗
NASA NTRS1993

A Software Package for Neural Network Applications Development

Original Backprop (Version 1.2) is an MS-DOS package of four stand-alone C-language programs that enable users to develop neural network solutions to a variety of practical problems. Original Backprop generates three-layer, feed-forward (series-coupled) networks which map fixed-length input vectors into fixed length output vectors through an intermediate (hidden) layer of binary threshold units. Version 1.2 can handle up to 200 input vectors at a time, each having up to 128 real-valued components. The first subprogram, TSET, appends a number (up to 16) of classification bits to each input, thus creating a training set of input output pairs. The second subprogram, BACKPROP, creates a trilayer network to do the prescribed mapping and modifies the weights of its connections incrementally until the training set is leaned. The learning algorithm is the 'back-propagating error correction procedures first described by F. Rosenblatt in 1961. The third subprogram, VIEWNET, lets the trained network be examined, tested, and 'pruned' (by the deletion of unnecessary hidden units). The fourth subprogram, DONET, makes a TSR routine by which the finished product of the neural net design-and-training exercise can be consulted under other MS-DOS applications.

Baran, Robert H.↗
NASA NTRS1991

Tomographic separation of composite spectra - The components of the O-star spectroscopic binary AO Cassiopeiae

The UV photospheric lines of the short-period, double-lined O-star spectroscopic binary AO Cas are analyzed. Archival data from IUE (16 spectra uniformly distributed in orbital phase) were analyzed with a tomography algorithm to produce the separate spectra of the two stars in six spectral regions. The spectral classifications of the primary and secondary, O9.5 III and O8 V, respectively, were estimated through a comparison of UV line ratios with those in spectral standard stars. An intensity ratio of 0.5-0.7 (primary brighter) at 1600 A is compatible with the data.

Bagnuolo, William G., Jr.↗
NASA NTRS2018

Black Holes and Neutron Stars in Nearby Galaxies: Insights from NuSTAR

Nearby galaxy surveys have long classified X-ray binaries (XRBs) by the mass category of their donor stars (high-mass and low-mass). The NuSTAR (Nuclear Spectroscopic Telescope Array) observatory, which provides imaging data at E greater than 10 keV (kiloelectronvolts), has enabled the classification of extragalactic XRBs by their compact object type: neutron star (NS) or black hole (BH). We analyzed NuSTAR/Chandra/XMM-Newton observations from a NuSTAR-selected sample of 12 galaxies within 5 Mpc (megaparsecs) having stellar masses (M (sub asterisk)) 10 (sup 7-11) solar masses and star formation rates (SFRs) approximately 0.01-15 solar masses per year. We detected 128 NuSTAR sources to a sensitivity of 10 (sup 38) ergs per second. Using NuSTAR color-intensity and color-color diagrams we classified 43 of these sources as candidate NSs and 47 as candidate BHs. We further subdivide BHs by accretion states (soft, intermediate, and hard) and NSs by weak (Z/Atoll) and strong (accreting pulsar) magnetic field. Using eight normal (Milky Way-type) galaxies in the sample, we confirm the relation between the SFR and galaxy X-ray point source luminosity in the 4-25 and 12-25 keV energy bands. We also constrained galaxy X-ray point source luminosity using the relation L (sub X) equals M (sub asterisk) plus Beta SFR, finding agreement with previous work. The X-ray luminosity function (XLF) of all sources in the 4-25 and 12-25 keV energy bands matches the alpha = 1.6 slope for high-mass XRBs. We find that NS XLFs suggest a decline beginning at the Eddington limit for a 1.4 solar mass NS, whereas the BH fraction shows an approximate monotonic increase in the 4-25 and 12-25 keV energy bands. We calculate the overall ratio of BH to NS to be approximately 1 for 4-25 keV and approximately 2 for 12-25 keV.

Vulic, N.↗