Science.gov

Sample records for absorption features detected

  1. Detection of Variable Gaseous Absorption Features in the Debris Disks Around Young A-type Stars

    NASA Astrophysics Data System (ADS)

    Montgomery, Sharon L.; Welsh, Barry Y.

    2012-10-01

    We present medium resolution (R = 60,000) absorption measurements of the interstellar Ca II K line observed towards five nearby A-type stars (49 Ceti, 5 Vul, ι Cyg, 2 And, and HD 223884) suspected of possessing circumstellar gas debris disks. The stars were observed on a nightly basis during a six night observing run on the 2.1-meter Otto Struve telescope at the McDonald Observatory, Texas. We have detected nightly changes in the absorption strength of the Ca II K line observed near the stellar radial velocity in three of the stars (49 Ceti, i Cyg and HD 223884). Such changes in absorption suggest the presence of a circumstellar (atomic) gas disk around these stars. In addition to the absorption changes in the main Ca II K line profile, we have also observed weak transient absorption features that randomly appear at redshifted velocities in the spectra of 49 Ceti, 5 Vul, and 2 And. These absorption features are most probably associated with the presence of falling evaporated bodies (exo-comets) that liberate evaporating gas on their approach to the central star. This now brings the total number of systems in which exocomet activity has been observed at Ca II or Na I wavelengths on a nightly basis to seven (β Pic, HR 10, HD 85905, β Car, 49 Ceti, 5 Vul, and 2 And), with 2 And exhibiting weaker and less frequent changes. All of the disk systems presently known to exhibit either type of short-term variability in Ca II K line absorption are rapidly rotating A-type stars (V sin i > 120 km s-1). Most exhibit mid-IR excesses, and many of them are very young (< 20 Myr), thus supporting the argument that many of them are transitional objects between Herbig Ae and “Vega-like” A-type stars with more tenuous circumstellar disks. No mid-IR excess (due to the presence of a dust disk) has yet been detected around either 2 And or HD 223884, both of which have been classified as λ Boötis-type stars. This may indicate that the observed changes in gas absorption for these

  2. Detection of a Deep 3-μm Absorption Feature in the Spectrum of Amalthea (JV)

    NASA Astrophysics Data System (ADS)

    Takato, Naruhisa; Bus, Schelte J.; Terada, Hiroshi; Pyo, Tae-Soo; Kobayashi, Naoto

    2004-12-01

    Near-infrared spectra of Jupiter's small inner satellites Amalthea and Thebe are similar to those of D-type asteroids in the 0.8- to 2.5-micrometer wavelength range. A deep absorption feature is detected at 3 micrometers in the spectra of the trailing side of Amalthea, which is similar to that of the non-ice components of Callisto and can be attributed to hydrous minerals. These surface materials cannot be explained if the satellite formed at its present orbit by accreting from a circumjovian nebula. Amalthea and Thebe may be the remnants of Jupiter's inflowing building blocks that formed in the outer part or outside of the circumjovian nebula.

  3. Detection of a deep 3-microm absorption feature in the spectrum of Amalthea (JV).

    PubMed

    Takato, Naruhisa; Bus, Schelte J; Terada, Hiroshi; Pyo, Tae-Soo; Kobayashi, Naoto

    2004-12-24

    Near-infrared spectra of Jupiter's small inner satellites Amalthea and Thebe are similar to those of D-type asteroids in the 0.8- to 2.5-micrometer wavelength range. A deep absorption feature is detected at 3 micrometers in the spectra of the trailing side of Amalthea, which is similar to that of the non-ice components of Callisto and can be attributed to hydrous minerals. These surface materials cannot be explained if the satellite formed at its present orbit by accreting from a circumjovian nebula. Amalthea and Thebe may be the remnants of Jupiter's inflowing building blocks that formed in the outer part or outside of the circumjovian nebula.

  4. Detection of the 2175 Å Dust Feature in Mg II Absorption Systems

    NASA Astrophysics Data System (ADS)

    Malhotra, Sangeeta

    1997-10-01

    The broad absorption bump at 2175 Å due to dust, which is ubiquitous in the Galaxy and is seen in the Magellanic clouds, is also seen in a composite spectrum of Mg II absorbers. The composite absorber spectrum is obtained by taking the geometric mean of 92 quasar spectra after aligning them in the rest frame of 96 absorbers. By aligning the spectra according to absorber redshifts, we reinforce the spectral features of the absorbers and smooth over possible bumps and wiggles in the emission spectra as well as small features in the flat-fielding of the spectra. The width of the observed absorption feature is 200-300 Å (FWHM), or 0.4-0.6 μm-1, and the central wavelength is 2240 Å. These are somewhat different from the central wavelength of 2176 Å and FWHM = 0.8-1.25 μm-1 found in the Galaxy. Simulations show that this discrepancy between the properties of the 2175 Å feature in Mg II absorbers and the Galactic interstellar medium can be mostly explained by the different methods used to measure them.

  5. CAN GROUND-BASED TELESCOPES DETECT THE OXYGEN 1.27 {mu}m ABSORPTION FEATURE AS A BIOMARKER IN EXOPLANETS?

    SciTech Connect

    Kawahara, Hajime; Matsuo, Taro; Takami, Michihiro; Fujii, Yuka; Kotani, Takayuki; Tamura, Motohide; Murakami, Naoshi; Guyon, Olivier

    2012-10-10

    The oxygen absorption line imprinted in the scattered light from Earth-like planets has been considered the most promising metabolic biomarker for exolife. We examine the feasibility of the detection of the 1.27 {mu}m oxygen band from habitable exoplanets, in particular, around late-type stars observed with a future instrument on a 30 m class ground-based telescope. We analyzed the night airglow around 1.27 {mu}m with the IRCS/echelle spectrometer on Subaru and found that the strong telluric emission from atmospheric oxygen molecules declines by an order of magnitude by midnight. By compiling nearby star catalogs combined with the sky background model, we estimate the detectability of the oxygen absorption band from an Earth twin, if it exists, around nearby stars. We find that the most dominant source of photon noise for the oxygen 1.27 {mu}m band detection comes from the night airglow if the contribution of the stellar point-spread function (PSF) halo is suppressed enough to detect the planet. We conclude that the future detectors, for which the detection contrast is limited by photon noise, can detect the oxygen 1.27 {mu}m absorption band of Earth twins for {approx}50 candidates of the late-type star. This paper demonstrates the importance of deploying a small inner working angle as an efficient coronagraph and extreme adaptive optics on extremely large telescopes, and clearly shows that doing so will enable the study of potentially habitable planets.

  6. FIRST ULTRAVIOLET REFLECTANCE SPECTRA OF PLUTO AND CHARON BY THE HUBBLE SPACE TELESCOPE COSMIC ORIGINS SPECTROGRAPH: DETECTION OF ABSORPTION FEATURES AND EVIDENCE FOR TEMPORAL CHANGE

    SciTech Connect

    Stern, S. A.; Spencer, J. R.; Shinn, A.; Cunningham, N. J.; Hain, M. J.

    2012-01-15

    We have observed the mid-UV spectra of both Pluto and its large satellite, Charon, at two rotational epochs using the Hubble Space Telescope (HST) Cosmic Origins Spectrograph (COS) in 2010. These are the first HST/COS measurements of Pluto and Charon. Here we describe the observations and our reduction of them, and present the albedo spectra, average mid-UV albedos, and albedo slopes we derive from these data. These data reveal evidence for a strong absorption feature in the mid-UV spectrum of Pluto; evidence for temporal change in Pluto's spectrum since the 1990s is reported, and indirect evidence for a near-UV spectral absorption on Charon is also reported.

  7. Molecular absorption features in translucent clouds

    NASA Astrophysics Data System (ADS)

    Krelowski, Jacek

    2007-12-01

    Interstellar clouds, composed of neutral hydrogen, consist about 90% of the total mass of interstellar medium. Their absorption spectra contain: continuous extinction, atomic lines, molecular features and the unidentified diffuse interstellar bands (DIBs). The latter are also believed to be carried by some, rather complex molecules. A vast majority of DIBs is characterized by small central depths. This is why they became observable only since the solid state detectors are widely applied in astrophysics. It is to be emphasized that interstellar absorptions, seen along the same line of sight, may be in fact originated in several, different environments (clouds). The extensive database of echelle spectra allowed to prove that the CaII column density evidently correlates with parallaxes of OB-3 stars in contrast to other interstellar species. Thus CaII is quite evenly distributed in the interstellar medium while other species (NaI, KI, CaI, CH, CN, DIB carriers) are not. This fact is of basic importance as the ob- served spectra cannot be physically interpreted if they mix features originated in different clouds, i.e. in different environments. The abundance ratios of interstellar molecules (identified and DIB carriers) differ from cloud to cloud due to different physical processes which govern their formation. High resolution, high S/N spectra, prove that also profiles of diffuse bands vary from cloud to cloud - this fact strongly supports a molecular origin of these, still nidentified, features and motivates investigation of their relations to other molecules; they can reveal physical conditions which facilitate formation of the DIB carriers and lead to their identification.

  8. Novel absorption detection techniques for capillary electrophoresis

    SciTech Connect

    Xue, Yongjun

    1994-07-27

    Capillary electrophoresis (CE) has emerged as one of the most versatile separation methods. However, efficient separation is not sufficient unless coupled to adequate detection. The narrow inner diameter (I.D.) of the capillary column raises a big challenge to detection methods. For UV-vis absorption detection, the concentration sensitivity is only at the μM level. Most commercial CE instruments are equipped with incoherent UV-vis lamps. Low-brightness, instability and inefficient coupling of the light source with the capillary limit the further improvement of UV-vis absorption detection in CE. The goals of this research have been to show the utility of laser-based absorption detection. The approaches involve: on-column double-beam laser absorption detection and its application to the detection of small ions and proteins, and absorption detection with the bubble-shaped flow cell.

  9. Absorption of UV radiation by DNA: spatial and temporal features.

    PubMed

    Markovitsi, Dimitra; Gustavsson, Thomas; Banyasz, Akos

    2010-01-01

    The present review focuses on studies carried out by our group on the interaction of UV radiation with DNA. In particular, we examine the way that the energy acquired by DNA helices following direct absorption of UVC radiation is extended spatially and how its effects evolve during the time. These effects depend on the base sequence and can be revealed by the study of model helices. The experimental results were obtained by optical spectroscopy, used in a refined way which allows detection of very weak absorbance changes (10(-3)) as well as of intrinsic emission from DNA components whose fluorescence quantum yields are as low as 10(-4). Measurements were performed both under continuous irradiation and using pulsed excitation which permitted us to follow early events, occurring from 10(-14) to 10(-1)s. The experiments were guided by theoretical calculations. The spatial features concern the extent of the excited states formed immediately upon UV absorption; these were shown to be delocalized over several bases under the effect of electronic coupling. Moreover, thanks to the spectral fingerprints governed by the electronic coupling; we probed local denaturation induced on a double helix following formation of cyclobutane dimers. Regarding the temporal features, three different topics are presented: (i) ultrafast excitation energy transfer occurring among the bases in less than 100 fs, (ii) electron ejection from DNA upon absorption of one photon at 266 nm and (iii) formation of (6-4) photo-adducts involving a reaction intermediate. The most important message emerging from these studies is that DNA bases may adopt a collective behaviour versus UV radiation. Furthermore, time-resolved studies unravel processes which are undetectable by investigations using continuous irradiation. All these pieces of information change our understanding of how DNA damage occurs upon absorption of UV radiation.

  10. A new class of absorption feature in Io's near-infrared spectrum

    NASA Technical Reports Server (NTRS)

    Trafton, L. M.; Lester, D. F.; Ramseyer, T. F.; Salama, F.; Sandford, S. A.; Allamandola, L. J.

    1991-01-01

    A relatively weak IR absorption feature detected at 1200 resolving power in Io at 2.1253 microns does not correspond to any gas- or solid-phase absorption expected on the basis of previously identified Io surface constituents. The source material of the feature appears to be stable and more uniformly distributed in longitude than Io's hot spots. These characteristics imply the feature's participation in a class different from those of other Io absorption spectrum features, thereby potentially serving as a major indicator of Io's atmosphere-surface composition and interactions. Results of laboratory experiments with plausible surface ices are compared with these observations.

  11. Feature Extraction Without Edge Detection

    DTIC Science & Technology

    1993-09-01

    feature? A.I. Memo 1356, MIT Artificial Intellegence Lab, April 1992. [65] W. A. Richards, B. Dawson, and D. Whittington. Encoding contour shape by...AD-A279 842 . " Technical Report 1434 --Feature Extraction Without Edge Detection Ronald D. Chane MIT Artificial .Intelligencc Laboratory ",, 𔃾•d...Chaney 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) 8. PERFORMING ORGANIZATION REPORT NUMBER Massachusetts Institute of Technology Artificial

  12. Feature detection for spatial templates

    SciTech Connect

    Robinson, K.

    1996-02-01

    The Color Medical Image System (CMIS), a program that uses segmented mapping techniques to obtain high resolution digital images, is currently trying to develop techniques to transfer microscopic glass slides to electronic image libraries. One technique that has been attempted is to use correlation techniques to scan the image. However, when segments of high magnification are used, it is difficult and time consuming to perform correlation techniques. This project investigates feature detection in microscopic images. Various techniques are implemented to detect the section of the image containing the most feature information, thereby making the correlation process more efficient. Three tests are implemented that eliminate the background in the image and calculate the mean (1st order technique), variance (2nd order technique), and ratio test (1st order technique) of the remaining pixel values. Background elimination involves deleting all pixel values above a certain experimental value from any calculations made. The source code for each of the three tests was implemented and tested on a number of images using the green color band. Each program outputs the box containing the most features and writes that section to a file to be displayed to the screen. A visual rank was also recorded so as to compare it the output of the tests. Each of the three tests proved to be successful. After comparing the visual rank to the output of the tests, it was determined that both first and second order techniques are effective in detecting features in microscopic images. Although all of the purposes and goals were met, this investigation should be expanded to include texturized images and the use of all three color bands.

  13. A study of the absorption features of Makemake

    NASA Astrophysics Data System (ADS)

    Alvarez-Candal, A.; Pinilla-Alonso, N.; Ortiz, J.; Duffard, R.; Carvano, J.; de Pra, M.

    2014-07-01

    Most transneptunian objects do not show prominent absorption features due to the size and location [1]. Nevertheless, absorption due to water ice and volatile ices do appear on a few large objects, particularly those that have good signal-to-noise-ratio spectra. In particular, methane appears in three dwarf planets (Pluto, Eris, and Makemake), as well as in some smaller objects, such as Quaoar and probably Sedna, and in Neptune's satellite Triton. Methane has such intense absorption features that even small amounts of methane on the surface dominate the reflectance spectra in the visible and near-infrared range, making it a great tool to probe surfaces, especially, considering that the depth of the bands could be used as a proxy for physical depths and that shifts in the bands with respect to laboratory measurements could point to possible dilutions (as seen in Pluto and Eris; for instance [3] and references therein). Aiming at gaining a deeper insight into Makemake's surface through its methane absorption bands, we have observed it with X-Shooter at the VLT with a medium spectral resolution in the range of 0.4--1.8 microns. In this work, we present the results of comparing these features with those of methane in the laboratory and the same features in Eris and Pluto, within the context of methane-dominated spectra of dwarf planets.

  14. On the nature of absorption features toward nearby stars

    NASA Astrophysics Data System (ADS)

    Kohl, S.; Czesla, S.; Schmitt, J. H. M. M.

    2016-06-01

    Context. Diffuse interstellar absorption bands (DIBs) of largely unknown chemical origin are regularly observed primarily in distant early-type stars. More recently, detections in nearby late-type stars have also been claimed. These stars' spectra are dominated by stellar absorption lines. Specifically, strong interstellar atomic and DIB absorption has been reported in τ Boo. Aims: We test these claims by studying the strength of interstellar absorption in high-resolution TIGRE spectra of the nearby stars τ Boo, HD 33608, and α CrB. Methods: We focus our analysis on a strong DIB located at 5780.61 Å and on the absorption of interstellar Na. First, we carry out a differential analysis by comparing the spectra of the highly similar F-stars, τ Boo and HD 33608, whose light, however, samples different lines of sight. To obtain absolute values for the DIB absorption, we compare the observed spectra of τ Boo, HD 33608, and α CrB to PHOENIX models and carry out basic spectral modeling based on Voigt line profiles. Results: The intercomparison between τ Boo and HD 33608 reveals that the difference in the line depth is 6.85 ± 1.48 mÅ at the DIB location which is, however, unlikely to be caused by DIB absorption. The comparison between PHOENIX models and observed spectra yields an upper limit of 34.0 ± 0.3 mÅ for any additional interstellar absorption in τ Boo; similar results are obtained for HD 33608 and α CrB. For all objects we derive unrealistically large values for the radial velocity of any presumed interstellar clouds. In τ Boo we find Na D absorption with an equivalent width of 0.65 ± 0.07 mÅ and 2.3 ± 0.1 mÅ in the D2 and D1 lines. For the other Na, absorption of the same magnitude could only be detected in the D2 line. Our comparisons between model and data show that the interstellar absorption toward τ Boo is not abnormally high. Conclusions: We find no significant DIB absorption in any of our target stars. Any differences between modeled and

  15. Infrared differential absorption for atmospheric pollutant detection

    NASA Technical Reports Server (NTRS)

    Byer, R. L.

    1974-01-01

    Progress made in the generation of tunable infrared radiation and its application to remote pollutant detection by the differential absorption method are summarized. It is recognized that future remote pollutant measurements depended critically on the availability of high energy tunable transmitters. Futhermore, due to eye safety requirements, the transmitted frequency must lie in the 1.4 micron to 13 micron infrared spectral range.

  16. Spatially Resolved HCN Absorption Features in the Circumnuclear Region of NGC 1052

    NASA Astrophysics Data System (ADS)

    Sawada-Satoh, Satoko; Roh, Duk-Gyoo; Oh, Se-Jin; Lee, Sang-Sung; Byun, Do-Young; Kameno, Seiji; Yeom, Jae-Hwan; Jung, Dong-Kyu; Kim, Hyo-Ryoung; Hwang, Ju-Yeon

    2016-10-01

    We present the first VLBI detection of HCN molecular absorption in the nearby active galactic nucleus NGC 1052. Utilizing the 1 mas resolution achieved by the Korean VLBI Network, we have spatially resolved the HCN absorption against a double-sided nuclear jet structure. Two velocity features of HCN absorption are detected significantly at the radial velocity of 1656 and 1719 km s-1, redshifted by 149 and 212 km s-1 with respect to the systemic velocity of the galaxy. The column density of the HCN molecule is estimated to be 1015-1016 cm-2, assuming an excitation temperature of 100-230 K. The absorption features show high optical depth localized on the receding jet side, where the free-free absorption occurred due to the circumnuclear torus. The size of the foreground absorbing molecular gas is estimated to be on approximately one-parsec scales, which agrees well with the approximate size of the circumnuclear torus. HCN absorbing gas is likely to be several clumps smaller than 0.1 pc inside the circumnuclear torus. The redshifted velocities of the HCN absorption features imply that HCN absorbing gas traces ongoing infall motion inside the circumnuclear torus onto the central engine.

  17. Absorption Features in Spectra of Magnetized Neutron Stars

    SciTech Connect

    Suleimanov, V.; Hambaryan, V.; Neuhaeuser, R.; Potekhin, A. Y.; Pavlov, G. G.; Adelsberg, M. van; Werner, K.

    2011-09-21

    The X-ray spectra of some magnetized isolated neutron stars (NSs) show absorption features with equivalent widths (EWs) of 50-200 eV, whose nature is not yet well known.To explain the prominent absorption features in the soft X-ray spectra of the highly magnetized (B{approx}10{sup 14} G) X-ray dim isolated NSs (XDINSs), we theoretically investigate different NS local surface models, including naked condensed iron surfaces and partially ionized hydrogen model atmospheres, with semi-infinite and thin atmospheres above the condensed surface. We also developed a code for computing light curves and integral emergent spectra of magnetized neutron stars with various temperature and magnetic field distributions over the NS surface. We compare the general properties of the computed and observed light curves and integral spectra for XDINS RBS 1223 and conclude that the observations can be explained by a thin hydrogen atmosphere above the condensed iron surface, while the presence of a strong toroidal magnetic field component on the XDINS surface is unlikely.We suggest that the harmonically spaced absorption features in the soft X-ray spectrum of the central compact object (CCO) 1E 1207.4-5209 (hereafter 1E 1207) correspond to peaks in the energy dependence of the free-free opacity in a quantizing magnetic field, known as quantum oscillations. To explore observable properties of these quantum oscillations, we calculate models of hydrogen NS atmospheres with B{approx}10{sup 10}-10{sup 11} G(i.e., electron cyclotron energy E{sub c,e}{approx}0.1-1 keV) and T{sub eff} = 1-3 MK. Such conditions are thought to be typical for 1E 1207. We show that observable features at the electron cyclotron harmonics with EWs {approx_equal}100-200 eV can arise due to these quantum oscillations.

  18. Permeation absorption sampler with multiple detection

    DOEpatents

    Zaromb, Solomon

    1990-01-01

    A system for detecting analytes in air or aqueous systems includes a permeation absorption preconcentrator sampler for the analytes and analyte detectors. The preconcentrator has an inner fluid-permeable container into which a charge of analyte-sorbing liquid is intermittently injected, and a fluid-impermeable outer container. The sample is passed through the outer container and around the inner container for trapping and preconcentrating the analyte in the sorbing liquid. The analyte can be detected photometrically by injecting with the sorbing material a reagent which reacts with the analyte to produce a characteristic color or fluorescence which is detected by illuminating the contents of the inner container with a light source and measuring the absorbed or emitted light, or by producing a characteristic chemiluminescence which can be detected by a suitable light sensor. The analyte can also be detected amperometrically. Multiple inner containers may be provided into which a plurality of sorbing liquids are respectively introduced for simultaneously detecting different analytes. Baffles may be provided in the outer container. A calibration technique is disclosed.

  19. Feature Sets for Screenshot Detection

    DTIC Science & Technology

    2013-06-01

    contain large sections of pixels with identical intensities as well as a less “natural” pixel distribution overall. 2.2.1 Edge Detection Two basic and...Machine Perception of Three-Dimensional Solids” in which he proposed what would become one of the first edge detection algorithms [16]. His algorithm...presented by Sobel , involves 3x3 masks that calculate both the magnitude and direction of the egdes [15]. A number of additional edge detectors have

  20. Investigations on the 1.7 micron residual absorption feature in the vegetation reflection spectrum

    NASA Technical Reports Server (NTRS)

    Verdebout, J.; Jacquemoud, S.; Andreoli, G.; Hosgood, B.; Sieber, A.

    1993-01-01

    The detection and interpretation of the weak absorption features associated with the biochemical components of vegetation is of great potential interest to a variety of applications ranging from classification to global change studies. This recent subject is also challenging because the spectral signature of the biochemicals is only detectable as a small distortion of the infrared spectrum which is mainly governed by water. Furthermore, the interpretation is complicated by complexity of the molecules (lignin, cellulose, starch, proteins) which contain a large number of different and common chemical bonds. In this paper, we present investigations on the absorption feature centered at 1.7 micron; these were conducted both on AVIRIS data and laboratory reflectance spectra of leaves.

  1. Covariance based outlier detection with feature selection.

    PubMed

    Zwilling, Chris E; Wang, Michelle Y

    2016-08-01

    The present covariance based outlier detection algorithm selects from a candidate set of feature vectors that are best at identifying outliers. Features extracted from biomedical and health informatics data can be more informative in disease assessment and there are no restrictions on the nature and number of features that can be tested. But an important challenge for an algorithm operating on a set of features is for it to winnow the effective features from the ineffective ones. The powerful algorithm described in this paper leverages covariance information from the time series data to identify features with the highest sensitivity for outlier identification. Empirical results demonstrate the efficacy of the method.

  2. Highly sensitive detection using Herriott cell for laser absorption spectroscopy

    NASA Astrophysics Data System (ADS)

    Zhao, Chongyi; Song, Guangming; Du, Yang; Zhao, Xiaojun; Wang, Wenju; Zhong, Liujun; Hu, Mai

    2016-11-01

    The tunable diode laser absorption spectroscopy combined with the long absorption path technique is a significant method to detect harmful gas. The long optical path could come true by Herriott cell reducing the size of the spectrometers. A 15 cm long Herriott cell with 28.8 m optical absorption path after 96 times reflection was designed that enhanced detection sensitivity of absorption spectroscopy. According to the theory data of calculation, Herriott cell is analyzed and simulated by softwares Matlab and Lighttools.

  3. Sensor feature fusion for detecting buried objects

    SciTech Connect

    Clark, G.A.; Sengupta, S.K.; Sherwood, R.J.; Hernandez, J.E.; Buhl, M.R.; Schaich, P.C.; Kane, R.J.; Barth, M.J.; DelGrande, N.K.

    1993-04-01

    Given multiple registered images of the earth`s surface from dual-band sensors, our system fuses information from the sensors to reduce the effects of clutter and improve the ability to detect buried or surface target sites. The sensor suite currently includes two sensors (5 micron and 10 micron wavelengths) and one ground penetrating radar (GPR) of the wide-band pulsed synthetic aperture type. We use a supervised teaming pattern recognition approach to detect metal and plastic land mines buried in soil. The overall process consists of four main parts: Preprocessing, feature extraction, feature selection, and classification. These parts are used in a two step process to classify a subimage. Thee first step, referred to as feature selection, determines the features of sub-images which result in the greatest separability among the classes. The second step, image labeling, uses the selected features and the decisions from a pattern classifier to label the regions in the image which are likely to correspond to buried mines. We extract features from the images, and use feature selection algorithms to select only the most important features according to their contribution to correct detections. This allows us to save computational complexity and determine which of the sensors add value to the detection system. The most important features from the various sensors are fused using supervised teaming pattern classifiers (including neural networks). We present results of experiments to detect buried land mines from real data, and evaluate the usefulness of fusing feature information from multiple sensor types, including dual-band infrared and ground penetrating radar. The novelty of the work lies mostly in the combination of the algorithms and their application to the very important and currently unsolved operational problem of detecting buried land mines from an airborne standoff platform.

  4. Iron K Features in the Quasar E 1821+643: Evidence for Gravitationally Redshifted Absorption?

    NASA Technical Reports Server (NTRS)

    Yaqoob, Tahir; Serlemitsos, Peter

    2005-01-01

    We report a Chandra high-energy grating detection of a narrow, redshifted absorption line superimposed on the red wing of a broad Fe K line in the z = 0.297 quasar E 1821+643. The absorption line is detected at a confidence level, estimated by two different methods, in the range approx. 2 - 3 sigma. Although the detection significance is not high enough to exclude a non-astrophysical origin, accounting for the absorption feature when modeling the X-ray spectrum implies that the Fe-K emission line is broad, and consistent with an origin in a relativistic accretion disk. Ignoring the apparent absorption feature leads to the conclusion that the Fe-K emission line is narrower, and also affects the inferred peak energy of the line (and hence the inferred ionization state of Fe). If the absorption line (at approx. 6.2 keV in the quasar frame) is real, we argue that it could be due to gravitationally redshifted Fe XXV or Fe XXVI resonance absorption within approx. 10 - 20 gravitational radii of the putative central black hole. The absorption line is not detected in earlier ASCA and Chandra low-energy grating observations, but the absorption line is not unequivocally ruled out by these data. The Chandra high-energy grating Fe-K emission line is consistent with an origin predominantly in Fe I-XVII or so. In an ASCA observation eight years earlier, the Fe-K line peaked at approx. 6.6 keV, closer to the energies of He-like Fe triplet lines. Further, in a Chandra low-energy grating observation the Fe-K line profile was double-peaked, one peak corresponding to Fe I-XVII or so, the other peak to Fe XXVI Ly alpha. Such a wide range in ionization state of Fe is not ruled out by the HEG and ASCA data either, and is suggestive of a complex structure for the line-emitter.

  5. Fast Feature Pyramids for Object Detection.

    PubMed

    Dollár, Piotr; Appel, Ron; Belongie, Serge; Perona, Pietro

    2014-08-01

    Multi-resolution image features may be approximated via extrapolation from nearby scales, rather than being computed explicitly. This fundamental insight allows us to design object detection algorithms that are as accurate, and considerably faster, than the state-of-the-art. The computational bottleneck of many modern detectors is the computation of features at every scale of a finely-sampled image pyramid. Our key insight is that one may compute finely sampled feature pyramids at a fraction of the cost, without sacrificing performance: for a broad family of features we find that features computed at octave-spaced scale intervals are sufficient to approximate features on a finely-sampled pyramid. Extrapolation is inexpensive as compared to direct feature computation. As a result, our approximation yields considerable speedups with negligible loss in detection accuracy. We modify three diverse visual recognition systems to use fast feature pyramids and show results on both pedestrian detection (measured on the Caltech, INRIA, TUD-Brussels and ETH data sets) and general object detection (measured on the PASCAL VOC). The approach is general and is widely applicable to vision algorithms requiring fine-grained multi-scale analysis. Our approximation is valid for images with broad spectra (most natural images) and fails for images with narrow band-pass spectra (e.g., periodic textures).

  6. Monocular precrash vehicle detection: features and classifiers.

    PubMed

    Sun, Zehang; Bebis, George; Miller, Ronald

    2006-07-01

    Robust and reliable vehicle detection from images acquired by a moving vehicle (i.e., on-road vehicle detection) is an important problem with applications to driver assistance systems and autonomous, self-guided vehicles. The focus of this work is on the issues of feature extraction and classification for rear-view vehicle detection. Specifically, by treating the problem of vehicle detection as a two-class classification problem, we have investigated several different feature extraction methods such as principal component analysis, wavelets, and Gabor filters. To evaluate the extracted features, we have experimented with two popular classifiers, neural networks and support vector machines (SVMs). Based on our evaluation results, we have developed an on-board real-time monocular vehicle detection system that is capable of acquiring grey-scale images, using Ford's proprietary low-light camera, achieving an average detection rate of 10 Hz. Our vehicle detection algorithm consists of two main steps: a multiscale driven hypothesis generation step and an appearance-based hypothesis verification step. During the hypothesis generation step, image locations where vehicles might be present are extracted. This step uses multiscale techniques not only to speed up detection, but also to improve system robustness. The appearance-based hypothesis verification step verifies the hypotheses using Gabor features and SVMs. The system has been tested in Ford's concept vehicle under different traffic conditions (e.g., structured highway, complex urban streets, and varying weather conditions), illustrating good performance.

  7. Detection of linear features in aerial images

    NASA Astrophysics Data System (ADS)

    Gao, Rui

    Over the past decades, considerable progress had been made to develop automatic image interpretation tools in remote sensing. However, there is still a gap between the results and the requirements for accuracy and robustness. Noisy aerial image interpretation, especially for low resolution images, is still difficult. In this thesis, we propose a fully automatic system for linear feature detection in aerial images. We present how the system works on the application of extraction and reconstruction of road and pipeline networks. The work in this thesis is divided by three parts: line detection, feature interpretation, and feature tracking. An improved Hough transform based on orientation information is introduced for the line detection. We explore the Markov random field model and Bayesian filtering for feature interpretation and tracking. Experimental results show that our proposed system is robust and effective to deal with low resolution aerial images.

  8. Feature Detection Techniques for Preprocessing Proteomic Data

    PubMed Central

    Sellers, Kimberly F.; Miecznikowski, Jeffrey C.

    2010-01-01

    Numerous gel-based and nongel-based technologies are used to detect protein changes potentially associated with disease. The raw data, however, are abundant with technical and structural complexities, making statistical analysis a difficult task. Low-level analysis issues (including normalization, background correction, gel and/or spectral alignment, feature detection, and image registration) are substantial problems that need to be addressed, because any large-level data analyses are contingent on appropriate and statistically sound low-level procedures. Feature detection approaches are particularly interesting due to the increased computational speed associated with subsequent calculations. Such summary data corresponding to image features provide a significant reduction in overall data size and structure while retaining key information. In this paper, we focus on recent advances in feature detection as a tool for preprocessing proteomic data. This work highlights existing and newly developed feature detection algorithms for proteomic datasets, particularly relating to time-of-flight mass spectrometry, and two-dimensional gel electrophoresis. Note, however, that the associated data structures (i.e., spectral data, and images containing spots) used as input for these methods are obtained via all gel-based and nongel-based methods discussed in this manuscript, and thus the discussed methods are likewise applicable. PMID:20467457

  9. Absorption Features in the X-ray Spectrum of an Ordinary Radio Pulsar

    NASA Astrophysics Data System (ADS)

    Kargaltsev, Oleg; Durant, Martin; Misanovic, Zdenka; Pavlov, George G.

    2012-08-01

    The vast majority of known nonaccreting neutron stars (NSs) are rotation-powered radio and/or γ-ray pulsars. So far, their multiwavelength spectra have all been described satisfactorily by thermal and nonthermal continuum models, with no spectral lines. Spectral features have, however, been found in a handful of exotic NSs and were thought to be a manifestation of their unique traits. Here, we report the detection of absorption features in the x-ray spectrum of an ordinary rotation-powered radio pulsar, J1740+1000. Our findings bridge the gap between the spectra of pulsars and other, more exotic, NSs, suggesting that the features are more common in the NS spectra than they have been thought so far.

  10. Absorption features in the x-ray spectrum of an ordinary radio pulsar.

    PubMed

    Kargaltsev, Oleg; Durant, Martin; Misanovic, Zdenka; Pavlov, George G

    2012-08-24

    The vast majority of known nonaccreting neutron stars (NSs) are rotation-powered radio and/or γ-ray pulsars. So far, their multiwavelength spectra have all been described satisfactorily by thermal and nonthermal continuum models, with no spectral lines. Spectral features have, however, been found in a handful of exotic NSs and were thought to be a manifestation of their unique traits. Here, we report the detection of absorption features in the x-ray spectrum of an ordinary rotation-powered radio pulsar, J1740+1000. Our findings bridge the gap between the spectra of pulsars and other, more exotic, NSs, suggesting that the features are more common in the NS spectra than they have been thought so far.

  11. Empathic Features and Absorption in Fantasy Role-Playing.

    PubMed

    Rivers, Anissa; Wickramasekera, Ian E; Pekala, Ronald J; Rivers, Jennifer A

    2016-01-01

    This study examined the levels of empathy and absorption of individuals who regularly play fantasy and science fiction role-playing games. A hypothesis was developed that higher levels of empathy would be found in individuals who fantasy role-play based upon previous research in hypnosis such as J. R. Hilgard's (1970) imaginative involvement hypothesis, research into the "fantasy prone" personality type (Wilson & Barber, 1981), and the empathic involvement hypothesis (Wickramasekera II & Szlyk, 2003). The participants in the current study were 127 fantasy role-players who volunteered and completed the Davis Interpersonal Reactivity Index (empathy) and the Tellegen Absorption Scale (absorption). The results demonstrated that those who play fantasy role-playing games scored significantly higher than the comparison group on the IRI scale of empathy, confirming the hypothesis that fantasy role-players report experiencing higher levels of empathic involvement with others. Correlational analysis between the measures demonstrated a significant positive correlation between empathy and absorption (r = .43, p < .001). These results collectively suggest that fantasy role-players have a uniquely empathically-imaginative style. The results also confirm and extend previous findings on the relationship between empathy and absorption as predicted by the Empathic Involvement Hypothesis (Wickramasekera II & Szlyk, 2003).

  12. Detecting Nematode Features from Digital Images

    PubMed Central

    de la Blanca, N. Pérez; Fdez-Valdivia, J.; Castillo, P.; Gómez-Barcina, A.

    1992-01-01

    Procedures for estimating and calibrating nematode features from digitial images are described and evaluated by illustration and mathematical formulae. Technical problems, such as capturing and cleaning raw images, standardizing the grey level range of images, and the detection of characteristics of the body habitus, presence or absence of stylet knobs, and tail and lip region shape are discussed. This study is the first of a series aimed at developing a set of automated methods to permit more rapid, objective characterizations of nematode features than is achievable by cumbersome conventional methods. PMID:19282998

  13. Detectability of cold streams into high-redshift galaxies by absorption lines

    NASA Astrophysics Data System (ADS)

    Goerdt, Tobias; Dekel, Avishai; Sternberg, Amiel; Gnat, Orly; Ceverino, Daniel

    2012-08-01

    Cold gas streaming along the dark matter filaments of the cosmic web is predicted to be the major source of fuel for disc buildup, violent disc instability and star formation in massive galaxies at high redshift. We investigate to what extent such cold gas is detectable in the extended circumgalactic environment of galaxies via Lyα absorption and selected low-ionization metal absorption lines. We model the expected absorption signatures using high-resolution zoom-in adaptive mesh refinement cosmological simulations. In the post-processing, we distinguish between self-shielded gas and unshielded gas. In the self-shielded gas, which is optically thick to Lyman continuum radiation, we assume pure collisional ionization for species with an ionization potential greater than 13.6 eV. In the optically-thin, unshielded gas, these species are also photoionized by the metagalactic radiation. In addition to absorption of radiation from background quasars, we compute the absorption line profiles of radiation emitted by the galaxy at the centre of the same halo. We predict the strength of the absorption signal for individual galaxies without stacking. We find that the Lyα absorption profiles produced by the streams are consistent with observations of absorption and emission Lyα profiles in high-redshift galaxies. Due to the low metallicities in the streams, and their low covering factors, the metal absorption features are weak and difficult to detect.

  14. Relating water absorption features to soil moisture characteristics

    NASA Astrophysics Data System (ADS)

    Tian, Jia; Philpot, William D.

    2015-09-01

    The spectral reflectance of a sample of quartz sand was monitored as the sample progressed from air-dry to fully saturated, and then back to air-dry. Wetting was accomplished by spraying small amounts of water on the surface of the sample, and collecting spectra whenever change occurred. Drying was passive, driven by evaporation from the sand surface, with spectra collected every 5 minutes until the sample was air dry. Water content was determined by monitoring the weight of the sample through both wetting and drying. There was a pronounced difference in the pattern of change in reflectance during wetting and drying, with the differences being apparent both in spectral details (i.e., the depth of absorption bands) and in the magnitude of the reflectance for a particular water content. The differences are attributable to the disposition of water in the sample. During wetting, water initially occurred only on the surface, primarily as water adsorbed onto sand particles. With increased wetting the water infiltrated deeper into the sample, gradually covering all particles and filling the pore spaces. During drying, water and air were distributed throughout the sample for most of the drying period. The differences in water distribution are assumed to be the cause of the differences in reflectance and to the differences in the depths of four strong water absorption bands.

  15. Using high spectral resolution spectrophotometry to study broad mineral absorption features on Mars

    NASA Technical Reports Server (NTRS)

    Blaney, D. L.; Crisp, D.

    1993-01-01

    Traditionally telescopic measurements of mineralogic absorption features have been made using relatively low to moderate (R=30-300) spectral resolution. Mineralogic absorption features tend to be broad so high resolution spectroscopy (R greater than 10,000) does not provide significant additional compositional information. Low to moderate resolution spectroscopy allows an observer to obtain data over a wide wavelength range (hundreds to thousands of wavenumbers) compared to the several wavenumber intervals that are collected using high resolution spectrometers. However, spectrophotometry at high resolution has major advantages over lower resolution spectroscopy in situations that are applicable to studies of the Martian surface, i.e., at wavelengths where relatively weak surface absorption features and atmospheric gas absorption features both occur.

  16. Multimodal spectroscopy detects features of vulnerable atherosclerotic plaque

    NASA Astrophysics Data System (ADS)

    Šćepanović, Obrad R.; Fitzmaurice, Maryann; Miller, Arnold; Kong, Chae-Ryon; Volynskaya, Zoya; Dasari, Ramachandra R.; Kramer, John R.; Feld, Michael S.

    2011-01-01

    Early detection and treatment of rupture-prone vulnerable atherosclerotic plaques is critical to reducing patient mortality associated with cardiovascular disease. The combination of reflectance, fluorescence, and Raman spectroscopy-termed multimodal spectroscopy (MMS)-provides detailed biochemical information about tissue and can detect vulnerable plaque features: thin fibrous cap (TFC), necrotic core (NC), superficial foam cells (SFC), and thrombus. Ex vivo MMS spectra are collected from 12 patients that underwent carotid endarterectomy or femoral bypass surgery. Data are collected by means of a unitary MMS optical fiber probe and a portable clinical instrument. Blinded histopathological analysis is used to assess the vulnerability of each spectrally evaluated artery lesion. Modeling of the ex vivo MMS spectra produce objective parameters that correlate with the presence of vulnerable plaque features: TFC with fluorescence parameters indicative of collagen presence; NC/SFC with a combination of diffuse reflectance β-carotene/ceroid absorption and the Raman spectral signature of lipids; and thrombus with its Raman signature. Using these parameters, suspected vulnerable plaques can be detected with a sensitivity of 96% and specificity of 72%. These encouraging results warrant the continued development of MMS as a catheter-based clinical diagnostic technique for early detection of vulnerable plaques.

  17. Laser-based ultraviolet absorption detection in capillary electrophoresis

    SciTech Connect

    Xue, Y.; Yeung, E.S. )

    1994-04-01

    Laser-based UV absorption in capillary electrophoresis is demonstrated. The use of vacuum photodiodes and an all-electronic noise canceller provides adequate baseline stability despite the large inherent intensity noise in UV lasers. A 4-fold improvement in the detection limit is achieved in comparison to that of commercial instruments. The main advantage here is the better optical coupling with small capillary tubes, maximizing the available optical pathlength for absorption.

  18. A search for ultraviolet circumstellar gas absorption features in alpha Piscis Austrinus (Fomalhaut), a possible Beta Pictoris-like system

    NASA Technical Reports Server (NTRS)

    Cheng, K.-P.; Bruhweiler, Fred C.; Kondo, Yoji

    1994-01-01

    Archival high-dispersion International Ultraviolet Explorer (IUE) spectra have been used to search for circumstellar gas absorption features in alpha PsA (A3 V), a nearby (6.7 pc) proto-planetary system candidate. Recent sub-millimeter mapping observations around the region of alpha PsA indicate a spatially resolved dust disk like the one seen around Beta Pic. To determine how closely this putative disk resembles that of Beta Pic, we have searched for signatures of circumstellar gaseous absorption in all the available IUE high-dispersion data of alpha PsA. Examination of co-added IUE spectra shows weak circumstellar absorptions from excited levels in the resonance multiplet of Fe II near 2600 A. We also conclude that the sharp C I feature near 1657 A, previously identified as interstellar absorption toward alpha PsA, likely has a circumstellar origin. However, because the weakness of these absorption features, we will consider the presence of circumstellar gas as tentative and should be verified by using the Goddard High-Resolution Spectrograph aboard the Hubble Space Telescope. No corresponding circumstellar absorption is detected in higher ionization Fe III and Al III. Since the collisionally ionized nonphotospheric Al III resonance absorption seen in Beta Pic is likely formed close to the stellar surface, its absence in the UV spectra of alpha PsA could imply that, in contrast with Beta Pic, there is no active gaseous disk infall onto the central star. In the alpha PsA gaseous disk, if we assume a solar abundance for iron and all the iron is in the form of Fe II, plus a disk temperature of 5000 K, the Fe II UV1 absorption at 2611.8743 A infers a total hydrogen column density along the line of sight through the circumstellar disk of N(H) approximately equals 3.8 x 10(exp 17)/cm.

  19. Toward Automated Feature Detection in UAVSAR Images

    NASA Astrophysics Data System (ADS)

    Parker, J. W.; Donnellan, A.; Glasscoe, M. T.

    2014-12-01

    Edge detection identifies seismic or aseismic fault motion, as demonstrated in repeat-pass inteferograms obtained by the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) program. But this identification is not robust at present: it requires a flattened background image, interpolation into missing data (holes) and outliers, and background noise that is either sufficiently small or roughly white Gaussian. Identification and mitigation of nongaussian background image noise is essential to creating a robust, automated system to search for such features. Clearly a robust method is needed for machine scanning of the thousands of UAVSAR repeat-pass interferograms for evidence of fault slip, landslides, and other local features.Empirical examination of detrended noise based on 20 km east-west profiles through desert terrain with little tectonic deformation for a suite of flight interferograms shows nongaussian characteristics. Statistical measurement of curvature with varying length scale (Allan variance) shows nearly white behavior (Allan variance slope with spatial distance from roughly -1.76 to -2) from 25 to 400 meters, deviations from -2 suggesting short-range differences (such as used in detecting edges) are often freer of noise than longer-range differences. At distances longer than 400 m the Allan variance flattens out without consistency from one interferogram to another. We attribute this additional noise afflicting difference estimates at longer distances to atmospheric water vapor and uncompensated aircraft motion.Paradoxically, California interferograms made with increasing time intervals before and after the El Mayor Cucapah earthquake (2008, M7.2, Mexico) show visually stronger and more interesting edges, but edge detection methods developed for the first year do not produce reliable results over the first two years, because longer time spans suffer reduced coherence in the interferogram. The changes over time are reflecting fault slip and block

  20. Detecting Curvilinear Features Using Structure Tensors.

    PubMed

    Vicas, Cristian; Nedevschi, Sergiu

    2015-11-01

    Few published articles on curvilinear structures exist compared with works on detecting lines or corners with high accuracy. In medical ultrasound imaging, the structures that need to be detected appear as a collection of microstructures correlated along a path. In this paper, we investigated techniques that extract meaningful low-level information for curvilinear structures, using techniques based on structure tensor. We proposed a novel structure tensor enhancement inspired by bilateral filtering. We compared the proposed approach with five state-of-the-art curvilinear structure detectors. We tested the algorithms against simulated images with known ground truth and real images from three different domains (medical ultrasound, scanning electron microscope, and astronomy). For the real images, we employed experts to delineate the ground truth for each domain. Techniques borrowed from machine learning robustly assessed the performance of the methods (area under curve and cross validation). As a practical application, we used the proposed method to label a set of 5000 ultrasound images. We conclude that the proposed tensor-based approach outperforms the state-of-the-art methods in providing magnitude and orientation information for curvilinear structures. The evaluation methodology ensures that the employed feature-detection method will yield reproducible performance on new, unseen images. We published all the implemented methods as open-source software.

  1. Fourier descriptor features for acoustic landmine detection

    NASA Astrophysics Data System (ADS)

    Keller, James M.; Cheng, Zhanqi; Gader, Paul D.; Hocaoglu, Ali K.

    2002-08-01

    Signatures of buried landmines are often difficult to separate from those of clutter objects. Often, shape information is not directly obtainable from the sensors used for landmine detection. The Acoustic Sensing Technology (AST), which uses a Laser Doppler Vibrometer (LDV) that measures the spatial pattern of particle velocity amplitude of the ground surface in a variety of frequency bands, offers a unique look at subsurface phenomena. It directly records shape related information. Generally, after preprocessing the frequency band images in a downward looking LDV system, landmines have fairly regular shapes (roughly circular) over a range of frequencies while clutter tends to exhibit irregular shapes different from those of landmines. Therefore, shape description has the potential to be used in discriminating mines from clutter. Normalized Fourier Descriptors (NFD) are shape parameters independent of size, angular orientation, position, and contour starting conditions. In this paper, the stack of 2D frequency images from the LDV system are preprocessed by a linear combination of order statistics (LOS) filter, thresholding, and 2D and 3D connected labeling. Contours are extracted form the connected components and aggregated to produce evenly spaced boundary points. Two types of Normalized Fourier Descriptors are computed from the outlines. Using images obtained from a standard data collection site, these features are analyzed for their ability to discriminate landmines from background and clutter such as wood and stones. From a standard feature selection procedure, it was found that a very small number of features are required to effectively separate landmines from background and clutter using simple pattern recognition algorithms. Details of the experiments are included.

  2. Comparison of the THz absorption feature in lactose to related saccharides

    NASA Astrophysics Data System (ADS)

    Bjarnason, Jon E.; Brown, Elliott R.; Korter, Timothy M.

    2007-04-01

    Solid-state organic compounds such as α-lactose-monohydrate and biotin have been shown to have narrow and intense THz absorption features at room temperature. Interest in lineshapes in the THz region is justified not only for practical reasons, since they are of crucial importance to spectroscopy-based identification of materials, but also because of the information the line-widths contain about the solid-state physics of the materials. The line-width of THz absorption features (generally from lattice vibrations) in solids is excepted to be inversely proportional to the scattering time of optical phonons. The line-width of absorption features might thus have implications on the solid-state physics of the material, in particular, the interaction of phonons and the phonon density of states. We use a continuous wave THz photomixing system to obtain a high resolution spectrum of α-lactose-mohohydrate and analyze two of its lowest-frequency absorption lines. For comparison we measure the transmission spectra of 5 chemically related saccharides: melecitose, trehalose, maltose, cellobiose, and raffinose. Since α-lactose-monohydrate has a stronger and narrower absorption feature than any of its related saccharides, this comparison study is an important step in understanding the mechanism of THz radiation absorption by organic solids and what line-widths to expect in THz spectroscopy.

  3. Dielectronic Recombination Of Iron M-shell Ions Motivated By Absorption Features In AGN Spectra

    NASA Astrophysics Data System (ADS)

    Lukic, Dragan; Schnell, M.; Savin, D. W.; Brandau, C.; Schmidt, E. W.; Yu, D.; Bernhardt, D.; Schippers, S.; Müller, A.; Lestinsky, M.; Orlov, D.; Sprenger, F.; Grieser, M.; Repnow, R.; Hoffmann, J.; Wolf, A.

    2006-09-01

    XMM-Newton and Chandra observations of active galactic nuclei (AGN) show spectra rich with X-ray absorption features. These observations have detected a broad unresolved transition array (UTA) between 15-17 Å. This is attributed to inner-shell photoexcitation of M-shell iron ions. Modeling these UTA features is currently limited by uncertainties in the low-temperature dielectronic recombination (DR) data for M-shell iron. In order to resolve this issue, and to provide reliable iron M-shell DR data for plasma modeling, we are carrying out a series of laboratory measurements using the heavy-ion Test Storage Ring (TSR) at the Max-Plank-Institute for Nuclear Physics in Heidelberg, Germany. We use the DR data obtained at TSR, to calculate rate coefficients for plasma modeling. We are also providing our data to atomic theorist to benchmark their DR calculations. Here we report our recent experimental results for DR for several iron M-shell ions and plans for future work. This work has been supported in part by NASA, the German Federal Ministry for Education and Research, and the German Research Council

  4. IUE's View of Callisto: Detection of an SO2 Absorption Correlated to Possible Torus Neutral Wind Alterations

    NASA Technical Reports Server (NTRS)

    Lane, Arthur L.; Domingue, Deborah L.

    1997-01-01

    Observations taken with the International Ultraviolet Explorer (IUE) detected a 0.28 micron absorption feature on Callisto's leading and Jupiter-facing hemispheres. This feature is similar to Europa's 0.28 micron feature, however it shows no correlation with magnetospheric ion bombardment. The strongest 0.28 micron signature is seen in the region containing the Valhalla impact. This absorption feature also shows some spatial correlation to possible neutral wind interactions, suggestive of S implantation (rather than S(sub x)) into Callisto's water ice surface, Indications of possible temporal variations (on the 10% level) are seen at other wavelengths between the 1984-1986 and the 1996 observations.

  5. Label free detection of phospholipids by infrared absorption spectroscopy

    NASA Astrophysics Data System (ADS)

    Ahmed, Tahsin; Foster, Erick; Vigil, Genevieve; Khan, Aamir A.; Bohn, Paul; Howard, Scott S.

    2014-08-01

    We present our study on compact, label-free dissolved lipid sensing by combining capillary electrophoresis separation in a PDMS microfluidic chip online with mid-infrared (MIR) absorption spectroscopy for biomarker detection. On-chip capillary electrophoresis is used to separate the biomarkers without introducing any extrinsic contrast agent, which reduces both cost and complexity. The label free biomarker detection could be done by interrogating separated biomarkers in the channel by MIR absorption spectroscopy. Phospholipids biomarkers of degenerative neurological, kidney, and bone diseases are detectable using this label free technique. These phospholipids exhibit strong absorption resonances in the MIR and are present in biofluids including urine, blood plasma, and cerebrospinal fluid. MIR spectroscopy of a 12-carbon chain phosphatidic acid (PA) (1,2-dilauroyl-snglycero- 3-phosphate (sodium salt)) dissolved in N-methylformamide, exhibits a strong amide peak near wavenumber 1660 cm-1 (wavelength 6 μm), arising from the phosphate headgroup vibrations within a low-loss window of the solvent. PA has a similar structure to many important phospholipids molecules like phosphatidylcholine (PC), phosphatidylinositol (PI), phosphatidylethanolamine (PE), phosphatidylglycerol (PG), and phosphatidylserine (PS), making it an ideal molecule for initial proof-of-concept studies. This newly proposed detection technique can lead us to minimal sample preparation and is capable of identifying several biomarkers from the same sample simultaneously.

  6. [Research on VOC concentration detection by photoelastic modulation infrared spectrum absorption method].

    PubMed

    Hu, Miao; Wang, Tai-yong; Qiao, Zhi-feng; Geng, Bo; Xiao, Xin-hua

    2011-12-01

    In order to ensure high stability and strong anti-interference ability in static interference system for qualitative and quantitative analysis of gas, a static scans interference detection system was designed based on photoelastic modulation infrared spectrum absorption system. The system consists of infrared laser, polarizer, photoelastic modulator, polarization analyzer and CCD components. By photoelastic modulator the principal refractive index of optical crystal will change cyclically by the modulation signal, producing cyclical changes in the optical path difference. With the calculation of modulation phase variation, the authors can get the function of the crystal length, the modulation cycle, and the range of optical path difference. Based on phase delay value and the energy distribution of interference pattern, the authors got the formula for the corresponding interference light intensity. The experiment used ZnSe crystal as the photoelastic modulation crystal, the polarizer uses the DOP3212 polarizer, and the detector uses the TCD5390AP array CCD. The five groups have different concentrations with three common VOC gases (formaldehyde, benzene and xylene) for detecting the concentrations of gases. The experimental results with the traditional infrared absorption were compared with the test results of photoelastic modulation infrared spectrum absorption method. The method of photoelastic modulation infrared spectrum absorption had high stability and real-time features, while the detection accuracy is better than the traditional infrared absorption method.

  7. Structure damage detection based on random forest recursive feature elimination

    NASA Astrophysics Data System (ADS)

    Zhou, Qifeng; Zhou, Hao; Zhou, Qingqing; Yang, Fan; Luo, Linkai

    2014-05-01

    Feature extraction is a key former step in structural damage detection. In this paper, a structural damage detection method based on wavelet packet decomposition (WPD) and random forest recursive feature elimination (RF-RFE) is proposed. In order to gain the most effective feature subset and to improve the identification accuracy a two-stage feature selection method is adopted after WPD. First, the damage features are sorted according to original random forest variable importance analysis. Second, using RF-RFE to eliminate the least important feature and reorder the feature list each time, then get the new feature importance sequence. Finally, k-nearest neighbor (KNN) algorithm, as a benchmark classifier, is used to evaluate the extracted feature subset. A four-storey steel shear building model is chosen as an example in method verification. The experimental results show that using the fewer features got from proposed method can achieve higher identification accuracy and reduce the detection time cost.

  8. Plant phenolics and absorption features in vegetation reflectance spectra near 1.66 μm

    NASA Astrophysics Data System (ADS)

    Kokaly, Raymond F.; Skidmore, Andrew K.

    2015-12-01

    Past laboratory and field studies have quantified phenolic substances in vegetative matter from reflectance measurements for understanding plant response to herbivores and insect predation. Past remote sensing studies on phenolics have evaluated crop quality and vegetation patterns caused by bedrock geology and associated variations in soil geochemistry. We examined spectra of pure phenolic compounds, common plant biochemical constituents, dry leaves, fresh leaves, and plant canopies for direct evidence of absorption features attributable to plant phenolics. Using spectral feature analysis with continuum removal, we observed that a narrow feature at 1.66 μm is persistent in spectra of manzanita, sumac, red maple, sugar maple, tea, and other species. This feature was consistent with absorption caused by aromatic Csbnd H bonds in the chemical structure of phenolic compounds and non-hydroxylated aromatics. Because of overlapping absorption by water, the feature was weaker in fresh leaf and canopy spectra compared to dry leaf measurements. Simple linear regressions of feature depth and feature area with polyphenol concentration in tea resulted in high correlations and low errors (% phenol by dry weight) at the dry leaf (r2 = 0.95, RMSE = 1.0%, n = 56), fresh leaf (r2 = 0.79, RMSE = 2.1%, n = 56), and canopy (r2 = 0.78, RMSE = 1.0%, n = 13) levels of measurement. Spectra of leaves, needles, and canopies of big sagebrush and evergreens exhibited a weak absorption feature centered near 1.63 μm, short ward of the phenolic compounds, possibly consistent with terpenes. This study demonstrates that subtle variation in vegetation spectra in the shortwave infrared can directly indicate biochemical constituents and be used to quantify them. Phenolics are of lesser abundance compared to the major plant constituents but, nonetheless, have important plant functions and ecological significance. Additional research is needed to advance our understanding of the spectral influences

  9. Derivative Analysis of Absorption Features in Hyperspectral Remote Sensing Data of Carbonate Sediments

    DTIC Science & Technology

    2002-12-30

    reflectance of carbonate sediments and application to shallow water benthic habitat classification,” Doctoral Dissertation, University of Miami. Chap.3...resolve overlapping features. A primary application has been to analyze pigment and chemical composition of leaves in order to track physiological...final absorption feature was observed at 630 nm, in a region associated with the biliprotein, phycocyanin [16,17]. As biliproteins are water soluble

  10. Feature Selection and Pedestrian Detection Based on Sparse Representation

    PubMed Central

    Yao, Shihong; Wang, Tao; Shen, Weiming; Pan, Shaoming; Chong, Yanwen; Ding, Fei

    2015-01-01

    Pedestrian detection have been currently devoted to the extraction of effective pedestrian features, which has become one of the obstacles in pedestrian detection application according to the variety of pedestrian features and their large dimension. Based on the theoretical analysis of six frequently-used features, SIFT, SURF, Haar, HOG, LBP and LSS, and their comparison with experimental results, this paper screens out the sparse feature subsets via sparse representation to investigate whether the sparse subsets have the same description abilities and the most stable features. When any two of the six features are fused, the fusion feature is sparsely represented to obtain its important components. Sparse subsets of the fusion features can be rapidly generated by avoiding calculation of the corresponding index of dimension numbers of these feature descriptors; thus, the calculation speed of the feature dimension reduction is improved and the pedestrian detection time is reduced. Experimental results show that sparse feature subsets are capable of keeping the important components of these six feature descriptors. The sparse features of HOG and LSS possess the same description ability and consume less time compared with their full features. The ratios of the sparse feature subsets of HOG and LSS to their full sets are the highest among the six, and thus these two features can be used to best describe the characteristics of the pedestrian and the sparse feature subsets of the combination of HOG-LSS show better distinguishing ability and parsimony. PMID:26295480

  11. Significance of ambient conditions in uranium absorption and emission features of laser ablation plasmas

    SciTech Connect

    Skrodzki, P. J.; Shah, N. P.; Taylor, N.; Hartig, K. C.; LaHaye, N. L.; Brumfield, B. E.; Jovanovic, I.; Phillips, M. C.; Harilal, S. S.

    2016-11-01

    This study employs laser ablation (LA) to investigate mechanisms for U optical signal variation under various environmental conditions during laser absorption spectroscopy (LAS) and optical emission spectroscopy (OES). Potential explored mechanisms for signal quenching related to ambient conditions include plasma chemistry (e.g., uranium oxide formation), ambient gas confinement effects, and other collisional interactions between plasma constituents and the ambient gas. LA-LAS studies show that the persistence of the U ground state population is significantly reduced in the presence of air ambient compared to nitrogen. LA-OES results yield congested spectra from which the U I 356.18 nm transition is prominent and serves as the basis for signal tracking. LA-OES signal and persistence vary negligibly between the test gases (air and N2), unlike the LA-LAS results. The plume hydrodynamic features and plume fundamental properties showed similar results in both air and nitrogen ambient. Investigation of U oxide formation in the laser-produced plasma suggests that low U concentration in a sample hinders consistent detection of UO molecular spectra.

  12. Significance of ambient conditions in uranium absorption and emission features of laser ablation plasmas

    NASA Astrophysics Data System (ADS)

    Skrodzki, P. J.; Shah, N. P.; Taylor, N.; Hartig, K. C.; LaHaye, N. L.; Brumfield, B. E.; Jovanovic, I.; Phillips, M. C.; Harilal, S. S.

    2016-11-01

    This study employs laser ablation (LA) to investigate mechanisms for U optical signal variation under various environmental conditions during laser absorption spectroscopy (LAS) and optical emission spectroscopy (OES). Potential mechanisms explored for signal quenching related to ambient conditions include plasma chemistry (e.g., uranium oxide formation), ambient gas confinement effects, and other collisional interactions between plasma constituents and the ambient gas. LA-LAS studies show that the persistence of the U ground state population is significantly reduced in the presence of air ambient compared to nitrogen. LA-OES yields congested spectra from which the U I 356.18 nm transition is prominent and serves as the basis for signal tracking. LA-OES signal and persistence vary negligibly between the test gases (air and N2), unlike the LA-LAS results. The plume hydrodynamic features and plume fundamental properties showed similar results in both air and nitrogen ambient. Investigation of U oxide formation in the laser-produced plasma suggests that low U concentration in a sample hinders consistent detection of UO molecular spectra.

  13. Breast Cancer Detection with Reduced Feature Set.

    PubMed

    Mert, Ahmet; Kılıç, Niyazi; Bilgili, Erdem; Akan, Aydin

    2015-01-01

    This paper explores feature reduction properties of independent component analysis (ICA) on breast cancer decision support system. Wisconsin diagnostic breast cancer (WDBC) dataset is reduced to one-dimensional feature vector computing an independent component (IC). The original data with 30 features and reduced one feature (IC) are used to evaluate diagnostic accuracy of the classifiers such as k-nearest neighbor (k-NN), artificial neural network (ANN), radial basis function neural network (RBFNN), and support vector machine (SVM). The comparison of the proposed classification using the IC with original feature set is also tested on different validation (5/10-fold cross-validations) and partitioning (20%-40%) methods. These classifiers are evaluated how to effectively categorize tumors as benign and malignant in terms of specificity, sensitivity, accuracy, F-score, Youden's index, discriminant power, and the receiver operating characteristic (ROC) curve with its criterion values including area under curve (AUC) and 95% confidential interval (CI). This represents an improvement in diagnostic decision support system, while reducing computational complexity.

  14. Breast Cancer Detection with Reduced Feature Set

    PubMed Central

    Kılıç, Niyazi; Bilgili, Erdem

    2015-01-01

    This paper explores feature reduction properties of independent component analysis (ICA) on breast cancer decision support system. Wisconsin diagnostic breast cancer (WDBC) dataset is reduced to one-dimensional feature vector computing an independent component (IC). The original data with 30 features and reduced one feature (IC) are used to evaluate diagnostic accuracy of the classifiers such as k-nearest neighbor (k-NN), artificial neural network (ANN), radial basis function neural network (RBFNN), and support vector machine (SVM). The comparison of the proposed classification using the IC with original feature set is also tested on different validation (5/10-fold cross-validations) and partitioning (20%–40%) methods. These classifiers are evaluated how to effectively categorize tumors as benign and malignant in terms of specificity, sensitivity, accuracy, F-score, Youden's index, discriminant power, and the receiver operating characteristic (ROC) curve with its criterion values including area under curve (AUC) and 95% confidential interval (CI). This represents an improvement in diagnostic decision support system, while reducing computational complexity. PMID:26078774

  15. Hydrogen Fire Detection System Features Sharp Discrimination

    NASA Technical Reports Server (NTRS)

    Bright, C. S.

    1966-01-01

    Hydrogen fire detection system discovers fires by detecting the flickering ultraviolet radiation emitted by the OH molecule, a short-lived intermediate combustion product found in hydrogen-air flames. In a space application, the system discriminates against false signals from sunlight and rocket engine exhaust plume radiation.

  16. [Application of atomic absorption spectrometry in the engine knock detection].

    PubMed

    Chen, Li-Dan

    2013-02-01

    Because existing human experience diagnosis method and apparatus for auxiliary diagnosis method are difficult to diagnose quickly engine knock. Atomic absorption spectrometry was used to detect the automobile engine knock in in innovative way. After having determined Fe, Al, Cu, Cr and Pb content in the 35 groups of Audi A6 engine oil whose travel course is 2 000 -70 000 kilometers and whose sampling interval is 2 000 kilometers by atomic absorption spectrometry, the database of primary metal content in the same automobile engine at different mileage was established. The research shows that the main metal content fluctuates within a certain range. In practical engineering applications, after the determination of engine oil main metal content and comparison with its database value, it can not only help to diagnose the type and location of engine knock without the disintegration and reduce vehicle maintenance costs and improve the accuracy of engine knock fault diagnosis.

  17. Voronoi poles-based saliency feature detection from point clouds

    NASA Astrophysics Data System (ADS)

    Xu, Tingting; Wei, Ning; Dong, Fangmin; Yang, Yuanqin

    2016-12-01

    In this paper, we represent a novel algorithm for point cloud feature detection. Firstly, the algorithm estimates the local feature for each sample point by computing the ratio of the distance from the inner voronoi pole and the outer voronoi pole to the surface. Then the surface global saliency feature is detected by adding the results of the difference of Gaussian for local feature under different scales. Compared with the state of the art methods, our algorithm has higher computing efficiency and more accurate feature detection for sharp edge. The detected saliency features are applied as the weights for surface mesh simplification. The numerical results for mesh simplification show that our method keeps the more details of key features than the traditional methods.

  18. Correlation analysis of hyperspectral absorption features with the water status of coast live oak leaves

    NASA Astrophysics Data System (ADS)

    Pu, Ruiliang; Ge, Shaokui; Kelly, Nina M.; Gong, Peng

    2002-01-01

    A total of 139 reflectance spectra (between 350 and 2500 nm) from coast live oak (Quercus Agrifolia) leaves were measured in the laboratory with a spectrometer FieldSpec½Pro FR. Correlation analysis was conducted between absorption features, three-band ratio indices derived from the spectra and corresponding relative water content (RWC, %) of oak leaves. The experimental results indicate that there exist linear relationships between the RWC of oak leaves and absorption feature parameters: wavelength position (WAVE), absorption feature depth (DEP), width (WID) and the multiplication of DEP and WID (AREA) at the 975 nm, 1200 nm and 1750 nm positions and two three-band ratio indices: RATIO975 and RATIO1200, derived at 975 nm and 1200 nm. AREA has a higher and more stable correlation with RWC compared to other features. It is worthy of noting that the two three-band ratio indices, RATIO975 and RATIO1200, may have potential application in assessing water status in vegetation.

  19. Molecular detection with terahertz waves based on absorption-induced transparency metamaterials

    NASA Astrophysics Data System (ADS)

    G. Rodrigo, Sergio; Martín-Moreno, L.

    2016-10-01

    A system for the detection of spectral signatures of chemical compounds at the Terahertz regime is presented. The system consists on a holey metal film whereby the presence of a given substance provokes the appearance of spectral features in transmission and reflection induced by the molecular specimen. These induced effects can be regarded as an extraordinary optical transmission phenomenon called absorption-induced transparency (AIT). The phenomenon consist precisely in the appearance of peaks in transmission and dips in reflection after sputtering of a chemical compound onto an initially opaque holey metal film. The spectral signatures due to AIT occur unexpectedly close to the absorption energies of the molecules. The presence of a target, a chemical compound, would be thus revealed as a strong drop in reflectivity measurements. We theoretically predict the AIT based system would serve to detect amounts of hydrocyanic acid (HCN) at low rate concentrations.

  20. Understanding the features in the ultrafast transient absorption spectra of CdSe quantum dots

    NASA Astrophysics Data System (ADS)

    Zhang, Cheng; Do, Thanh Nhut; Ong, Xuanwei; Chan, Yinthai; Tan, Howe-Siang

    2016-12-01

    We describe a model to explain the features of the ultrafast transient absorption (TA) spectra of CdSe core type quantum dots (QDs). The measured TA spectrum consists of contributions by the ground state bleach (GSB), stimulated emission (SE) and excited state absorption (ESA) processes associated with the three lowest energy transition of the QDs. We model the shapes of the GSB, SE and ESA spectral components after fits to the linear absorption. The spectral positions of the ESA components take into account the biexcitonic binding energy. In order to obtain the correct weightage of the GSB, SE and ESA components to the TA spectrum, we enumerate the set of coherence transfer pathways associated with these processes. From our fits of the experimental TA spectra of 65 Å diameter QDs, biexcitonic binding energies for the three lowest energy transitions are obtained.

  1. Plant phenolics and absorption features in vegetation reflectance spectra near 1.66 μm

    USGS Publications Warehouse

    Kokaly, Raymond F.; Skidmore, Andrew K

    2015-01-01

    Past laboratory and field studies have quantified phenolic substances in vegetative matter from reflectance measurements for understanding plant response to herbivores and insect predation. Past remote sensing studies on phenolics have evaluated crop quality and vegetation patterns caused by bedrock geology and associated variations in soil geochemistry. We examined spectra of pure phenolic compounds, common plant biochemical constituents, dry leaves, fresh leaves, and plant canopies for direct evidence of absorption features attributable to plant phenolics. Using spectral feature analysis with continuum removal, we observed that a narrow feature at 1.66 μm is persistent in spectra of manzanita, sumac, red maple, sugar maple, tea, and other species. This feature was consistent with absorption caused by aromatic C-H bonds in the chemical structure of phenolic compounds and non-hydroxylated aromatics. Because of overlapping absorption by water, the feature was weaker in fresh leaf and canopy spectra compared to dry leaf measurements. Simple linear regressions of feature depth and feature area with polyphenol concentration in tea resulted in high correlations and low errors (% phenol by dry weight) at the dry leaf (r2 = 0.95, RMSE = 1.0%, n = 56), fresh leaf (r2 = 0.79, RMSE = 2.1%, n = 56), and canopy (r2 = 0.78, RMSE = 1.0%, n = 13) levels of measurement. Spectra of leaves, needles, and canopies of big sagebrush and evergreens exhibited a weak absorption feature centered near 1.63 μm, short ward of the phenolic compounds, possibly consistent with terpenes. This study demonstrates that subtle variation in vegetation spectra in the shortwave infrared can directly indicate biochemical constituents and be used to quantify them. Phenolics are of lesser abundance compared to the major plant constituents but, nonetheless, have important plant functions and ecological significance. Additional research is needed to advance our understanding of the

  2. Goddard high-resolution spectrograph observations of narrow discrete stellar wind absorption features in the ultraviolet spectrum of the O7.5 III star Xi Persei

    NASA Technical Reports Server (NTRS)

    Shore, Steven N.; Altner, Bruce; Bolton, C. T.; Cardelli, Jason A.; Ebbets, Dennis C.

    1993-01-01

    We report the observation of transient narrow absorption components (NACs) in the stellar wind of the O giant Xi Per. Two sets of GHRS observations of the Si IV ultraviolet resonance doublet have been obtained. These features are extremely weak, with column densities of approximately 10 exp 12/sq cm and optical depths of order 0.1. The features are narrow, less than 30 km/s, and seem to occur in groups. If the NACs are due to the 1393 A component, they represent previously undetected low-velocity discrete absorption components at V(rad) below -600 km/s. If they are high-velocity features on the 1402 A doublet component, they may represent the decay phase of the discrete absorption components at the terminal velocity. In either case, they are a new aspect of the NAC phenomenon that could not have been detected with previous ultraviolet spectrographs.

  3. Aberration features in directional dark matter detection

    SciTech Connect

    Bozorgnia, Nassim; Gelmini, Graciela B.; Gondolo, Paolo E-mail: gelmini@physics.ucla.edu

    2012-08-01

    The motion of the Earth around the Sun causes an annual change in the magnitude and direction of the arrival velocity of dark matter particles on Earth, in a way analogous to aberration of stellar light. In directional detectors, aberration of weakly interacting massive particles (WIMPs) modulates the pattern of nuclear recoil directions in a way that depends on the orbital velocity of the Earth and the local galactic distribution of WIMP velocities. Knowing the former, WIMP aberration can give information on the latter, besides being a curious way of confirming the revolution of the Earth and the extraterrestrial provenance of WIMPs. While observing the full aberration pattern requires extremely large exposures, we claim that the annual variation of the mean recoil direction or of the event counts over specific solid angles may be detectable with moderately large exposures. For example, integrated counts over Galactic hemispheres separated by planes perpendicular to Earth's orbit would modulate annually, resulting in Galactic Hemisphere Annual Modulations (GHAM) with amplitudes larger than the usual non-directional annual modulation.

  4. Feature Detection Systems Enhance Satellite Imagery

    NASA Technical Reports Server (NTRS)

    2009-01-01

    -resolution satellites, which provide the benefit of images detailed enough to reveal large features like highways while still broad enough for global coverage, continue to scan the entirety of the Earth s surface. In 2012, NASA plans to launch the Landsat Data Continuity Mission (LDCM), or Landsat 8, to extend the Landsat program s contributions to cartography, water management, natural disaster relief planning, and more.

  5. Changes on image texture features of breakfast flakes cereals during water absorption.

    PubMed

    Medina, Wenceslao T; Quevedo, Roberto A; Aguilera, José M

    2013-02-01

    Normally breakfast cereal flakes are consumed by pouring them into a bowl and covering them with fresh or cold milk. During this process the liquid uptake causes changes in the surface and internal matrix of breakfast cereals that influence texture and integrity. Some breakfast cereal as flakes have a translucent structure that could provide information about the solid matrix and air cells and how they change during liquid absorption. The objective of the study was to assess the image texture changes of corn flakes and frosted flakes during water absorption at 5, 15 and 25 °C, employing 11 image feature textures extracted from grey-level co-occurrence matrix and grey-level run length matrix (at three directions) and to relate the fractal dimension (FD) of images with rupture force (RF) reduction during soaking of both flakes at 5 °C. The most relevant result from principal component analysis calculated with a matrix of 54 (soaking times) × 22 (texture features), shows that it was possible to distinguish an isolated group consisting of different soaking times at the same water temperature in each breakfast cereal flakes evaluated, corroborating that superficial liquid imbibition is important during the liquid absorption process when flakes are soaked. Furthermore, standardized FD could be related to RF in the period when samples tend to search for an equilibrium state.

  6. Imaging Catalytic Surfaces by Multiplexed Capillary Electrophoresis With Absorption Detection

    SciTech Connect

    Christodoulou, Michael

    2002-01-01

    A new technique for in situ imaging and screening heterogeneous catalysts by using multiplexed capillary electrophoresis with absorption detection was developed. By bundling the inlets of a large number of capillaries, an imaging probe can be created that can be used to sample products formed directly from a catalytic surface with high spatial resolution. In this work, they used surfaces made of platinum, iron or gold wires as model catalytic surfaces for imaging. Various shapes were recorded including squares and triangles. Model catalytic surfaces consisting of both iron and platinum wires in the shape of a cross were also imaged successfully. Each of the two wires produced a different electrochemical product that was separated by capillary electrophoresis. Based on the collected data they were able to distinguish the products from each wire in the reconstructed image.

  7. Detection of electron paramagnetic resonance absorption using frequency modulation.

    PubMed

    Hirata, Hiroshi; Kuyama, Toshifumi; Ono, Mitsuhiro; Shimoyama, Yuhei

    2003-10-01

    A frequency modulation (FM) method was developed to measure electron paramagnetic resonance (EPR) absorption. The first-derivative spectrum of 1,1-diphenyl-2-picrylhydrazyl (DPPH) powder was measured with this FM method. Frequency modulation of up to 1.6 MHz (peak-to-peak) was achieved at a microwave carrier frequency of 1.1 GHz. This corresponds to a magnetic field modulation of 57microT (peak-to-peak) at 40.3 mT. By using a tunable microwave resonator and automatic control systems, we achieved a practical continuous-wave (CW) EPR spectrometer that incorporates the FM method. In the present experiments, the EPR signal intensity was proportional to the magnitude of frequency modulation. The background signal at the modulation frequency (1 kHz) for EPR detection was also proportional to the magnitude of frequency modulation. An automatic matching control (AMC) system reduced the amplitude of noise in microwave detection and improved the baseline stability. Distortion of the spectral lineshape was seen when the spectrometer settings were not appropriate, e.g., with a lack of the open-loop gain in automatic tuning control (ATC). FM is an alternative to field modulation when the side-effect of field modulation is detrimental for EPR detection. The present spectroscopic technique based on the FM scheme is useful for measuring the first derivative with respect to the microwave frequency in investigations of electron-spin-related phenomena.

  8. Detecting Image Splicing Using Merged Features in Chroma Space

    PubMed Central

    Liu, Guangjie; Dai, Yuewei

    2014-01-01

    Image splicing is an image editing method to copy a part of an image and paste it onto another image, and it is commonly followed by postprocessing such as local/global blurring, compression, and resizing. To detect this kind of forgery, the image rich models, a feature set successfully used in the steganalysis is evaluated on the splicing image dataset at first, and the dominant submodel is selected as the first kind of feature. The selected feature and the DCT Markov features are used together to detect splicing forgery in the chroma channel, which is convinced effective in splicing detection. The experimental results indicate that the proposed method can detect splicing forgeries with lower error rate compared to the previous literature. PMID:24574877

  9. Detecting image splicing using merged features in chroma space.

    PubMed

    Xu, Bo; Liu, Guangjie; Dai, Yuewei

    2014-01-01

    Image splicing is an image editing method to copy a part of an image and paste it onto another image, and it is commonly followed by postprocessing such as local/global blurring, compression, and resizing. To detect this kind of forgery, the image rich models, a feature set successfully used in the steganalysis is evaluated on the splicing image dataset at first, and the dominant submodel is selected as the first kind of feature. The selected feature and the DCT Markov features are used together to detect splicing forgery in the chroma channel, which is convinced effective in splicing detection. The experimental results indicate that the proposed method can detect splicing forgeries with lower error rate compared to the previous literature.

  10. Robust feature detection for 3D object recognition and matching

    NASA Astrophysics Data System (ADS)

    Pankanti, Sharath; Dorai, Chitra; Jain, Anil K.

    1993-06-01

    Salient surface features play a central role in tasks related to 3-D object recognition and matching. There is a large body of psychophysical evidence demonstrating the perceptual significance of surface features such as local minima of principal curvatures in the decomposition of objects into a hierarchy of parts. Many recognition strategies employed in machine vision also directly use features derived from surface properties for matching. Hence, it is important to develop techniques that detect surface features reliably. Our proposed scheme consists of (1) a preprocessing stage, (2) a feature detection stage, and (3) a feature integration stage. The preprocessing step selectively smoothes out noise in the depth data without degrading salient surface details and permits reliable local estimation of the surface features. The feature detection stage detects both edge-based and region-based features, of which many are derived from curvature estimates. The third stage is responsible for integrating the information provided by the individual feature detectors. This stage also completes the partial boundaries provided by the individual feature detectors, using proximity and continuity principles of Gestalt. All our algorithms use local support and, therefore, are inherently parallelizable. We demonstrate the efficacy and robustness of our approach by applying it to two diverse domains of applications: (1) segmentation of objects into volumetric primitives and (2) detection of salient contours on free-form surfaces. We have tested our algorithms on a number of real range images with varying degrees of noise and missing data due to self-occlusion. The preliminary results are very encouraging.

  11. Line Length: An Efficient Feature for Seizure Onset Detection

    DTIC Science & Technology

    2007-11-02

    feature was evaluated over a total of 1,215 hours of intracranial EEG signal from 10 patients. Results confirmed this feature as being useful for...of 111 seizures analyzed of which 23 were subclinical. Keywords – seizure detection, fractal dimension . I. INTRODUCTION There is a lot of...Olsen [4], and later referred to as curve length in [3]. This feature can be derived from the fractal dimension by Katz [5] studied in [6]-[7]; however

  12. Convolutional neural network features based change detection in satellite images

    NASA Astrophysics Data System (ADS)

    Mohammed El Amin, Arabi; Liu, Qingjie; Wang, Yunhong

    2016-07-01

    With the popular use of high resolution remote sensing (HRRS) satellite images, a huge research efforts have been placed on change detection (CD) problem. An effective feature selection method can significantly boost the final result. While hand-designed features have proven difficulties to design features that effectively capture high and mid-level representations, the recent developments in machine learning (Deep Learning) omit this problem by learning hierarchical representation in an unsupervised manner directly from data without human intervention. In this letter, we propose approaching the change detection problem from a feature learning perspective. A novel deep Convolutional Neural Networks (CNN) features based HR satellite images change detection method is proposed. The main guideline is to produce a change detection map directly from two images using a pretrained CNN. This method can omit the limited performance of hand-crafted features. Firstly, CNN features are extracted through different convolutional layers. Then, a concatenation step is evaluated after an normalization step, resulting in a unique higher dimensional feature map. Finally, a change map was computed using pixel-wise Euclidean distance. Our method has been validated on real bitemporal HRRS satellite images according to qualitative and quantitative analyses. The results obtained confirm the interest of the proposed method.

  13. Feature Integration Theory Revisited: Dissociating Feature Detection and Attentional Guidance in Visual Search

    ERIC Educational Resources Information Center

    Chan, Louis K. H.; Hayward, William G.

    2009-01-01

    In feature integration theory (FIT; A. Treisman & S. Sato, 1990), feature detection is driven by independent dimensional modules, and other searches are driven by a master map of locations that integrates dimensional information into salience signals. Although recent theoretical models have largely abandoned this distinction, some observed…

  14. Feature matching method in shaped light mode VFD defect detection

    NASA Astrophysics Data System (ADS)

    Jin, Xuanhong; Dai, Shuguang; Mu, Pingan

    2010-08-01

    In recent years, Vacuum Fluorescent Display (VFD) module in the car audio panel has been widely used. However, due to process reasons, VFD display production process will produce defects, not only affect the appearance, but also affect the display correctly. So building a car VFD display panel defect detection system is of great significance. Machine vision technology is introduced into the automotive VFD display defect detection in order to achieve fast and accurate detection of defects. Shaped light mode is a typical flaw detection mode which is based on characteristics of vehicle VFD panel. According to the image features, learning of the gray matching and feature matching method, we integrated use of feature matching method and the gray level matching method to achieve defect detection.

  15. The Role of Polycyclic Aromatic Hydrocarbons in Dense Cloud Absorption Features: The Last Major Unanswered Question in Interstellar Ice Spectroscopy

    NASA Astrophysics Data System (ADS)

    Chiar, Jean

    Interstellar dust plays a vital role in the star formation process and the eventual formation of planetary systems including our own. Ice mantles are an important component of the dust: reactions involving simple ices can create more complex (and astrobiologically interesting) molecules, and ices sublimated back into the gas phase influence the gas- phase chemistry. Although polycyclic aromatic hydrocarbons (PAHs) are commonly thought to be very abundant interstellar species and, as such, are likely to be important components of interstellar ices, their contribution to the infrared spectra and chemistry of ices in dense molecular clouds is an open question. This program makes extensive use of three major NASA-funded databases: the Spitzer archive, the 2MASS archive, and the NASA Ames PAH database in order to answer the last major unanswered question in interstellar ice spectroscopy: what role do PAHs play in contributing to unidentified absorption features observed in dense cloud spectra. PAHs are observed to be present and abundant in nearly all phases of the galactic and extragalactic interstellar medium. The evidence for the ubiquity of interstellar PAHs is the widespread well-known family of prominent emission bands at 3.28, 6.2, 7.7, 8.6, and 11.2 micron. To date, these PAH bands have been most easily detected in regions where individual gas phase PAH molecules (neutrals and ions) become highly vibrationally excited by the ambient radiation field. While PAHs and closely related aromatic materials should be present throughout dense interstellar regions, PAH emission is quenched in cold dark dense clouds. Also, in these regions, most PAHs should efficiently condense out onto dust grains, either as "pure" solids or as "guest molecules" in icy grain mantles, much as is the case for most other interstellar molecules. Thus, in dense molecular clouds, condensed PAHs will give rise to IR absorption bands rather than emission features. While PAH absorption has been

  16. High-Velocity Absorption Features in FUSE Spectra of Eta Carinae

    NASA Technical Reports Server (NTRS)

    Sonneborn, G.; Iping, R. C.; Gull, T. R.; Vieira, G.

    2003-01-01

    Numerous broad (200 to 1000 km/sec) features in the FUSE spectrum (905-1187 A) of eta Carinae are identified as absorption by a forest of high-velocity narrow lines formed in the expanding circumstellar envelope. These features were previously thought to be P-Cygni lines arising in the wind of the central star. The features span a heliocentric velocity range of -140 to -580 km/sec and are seen prominently in low-ionization ground-state transitions (e.g. N I 1134-35, Fe II 1145-42, 1133, 1127- 22, P II 1153, C I 1158) in addition to C III] 1176 A. The high-velocity components of the FUSE transitions have depths about 50% below the continuum. The identifications are consistent with the complex velocity structures seen in ground- and excited-state transitions of Mg I, Mg 11, Fe II, V II, etc observed in STIS/E230H spectra. The origin of other broad features of similar width and depth in the FUSE spectrum, but without low-velocity ISM absorption, are unidentified. However, they are suspected of being absorption of singly-ionized iron-peak elements (e.g. Fe II, V II, Cr II) out of excited levels 1,000 to 20,000 cmE-l above the ground state. The high-velocity features seen in Fe II 1145 are also present in Fe II 1608 (STIS/E140M), but are highly saturated in the latter. Since these transitions have nearly identical log (flambda) (1.998 vs. 2.080), the differences in the profiles are attributable to the different aperture sizes used (30 x 30 arcsec for FUSE, 0.2 x 0.2 arcsec for STIS/E140M). The high-velocity gas appears to be very patchy or has a small covering factor near the central star. Eta Carinae has been observed several times by FUSE over the past three years. The FUSE flux levels and spectral features in eta Car are essentially unchanged over the 2000 March to June 2002 period, establishing a baseline far-UV spectrum in advance of the predicted spectroscopic minimum in 2003.

  17. A ubiquitous absorption feature in the X-ray spectra of BL Lacertae objects

    NASA Technical Reports Server (NTRS)

    Madejski, Greg M.; Mushotzky, Richard F.; Weaver, Kimberly A.; Arnaud, Keith A.; Urry, C. Megan

    1991-01-01

    The paper presents the broadband (0.5-20-keV) X-ray spectra of five X-ray bright BL Lac objects observed with the Einstein Observatory Solid State Spectrometer (SSS) and Monitor Proportional Counter (MPC) detectors. The combination of moderate energy resolution and broad spectral coverage makes it possible to confirm the presence of an absorption feature at an energy of 650 eV in the BL Lac object PKS 2155-304, originally reported by Canizares and Kruper (1984) based on higher resolution Einstein Objective Grating Spectrometer (OGS) data.

  18. Picture Detection in Rapid Serial Visual Presentation: Features or Identity?

    ERIC Educational Resources Information Center

    Potter, Mary C.; Wyble, Brad; Pandav, Rijuta; Olejarczyk, Jennifer

    2010-01-01

    A pictured object can be readily detected in a rapid serial visual presentation sequence when the target is specified by a superordinate category name such as "animal" or "vehicle". Are category features the initial basis for detection, with identification of the specific object occurring in a second stage (Evans &…

  19. New approach in features extraction for EEG signal detection.

    PubMed

    Guerrero-Mosquera, Carlos; Vazquez, Angel Navia

    2009-01-01

    This paper describes a new approach in features extraction using time-frequency distributions (TFDs) for detecting epileptic seizures to identify abnormalities in electroencephalogram (EEG). Particularly, the method extracts features using the Smoothed Pseudo Wigner-Ville distribution combined with the McAulay-Quatieri sinusoidal model and identifies abnormal neural discharges. We propose a new feature based on the length of the track that, combined with energy and frequency features, allows to isolate a continuous energy trace from another oscillations when an epileptic seizure is beginning. We evaluate our approach using data consisting of 16 different seizures from 6 epileptic patients. The results show that our extraction method is a suitable approach for automatic seizure detection, and opens the possibility of formulating new criteria to detect and analyze abnormal EEGs.

  20. Moment feature based fast feature extraction algorithm for moving object detection using aerial images.

    PubMed

    Saif, A F M Saifuddin; Prabuwono, Anton Satria; Mahayuddin, Zainal Rasyid

    2015-01-01

    Fast and computationally less complex feature extraction for moving object detection using aerial images from unmanned aerial vehicles (UAVs) remains as an elusive goal in the field of computer vision research. The types of features used in current studies concerning moving object detection are typically chosen based on improving detection rate rather than on providing fast and computationally less complex feature extraction methods. Because moving object detection using aerial images from UAVs involves motion as seen from a certain altitude, effective and fast feature extraction is a vital issue for optimum detection performance. This research proposes a two-layer bucket approach based on a new feature extraction algorithm referred to as the moment-based feature extraction algorithm (MFEA). Because a moment represents the coherent intensity of pixels and motion estimation is a motion pixel intensity measurement, this research used this relation to develop the proposed algorithm. The experimental results reveal the successful performance of the proposed MFEA algorithm and the proposed methodology.

  1. HAB detection based on absorption and backscattering properties of phytoplankton

    NASA Astrophysics Data System (ADS)

    Lei, Hui; Pan, Delu; Bai, Yan; Chen, Xiaoyan; Zhou, Yan; Zhu, Qiankun

    2011-11-01

    The coastal area of East China Sea (ECS) suffers from the harmful algal blooms (HAB) frequently every year in the warm season. The most common causative phytoplankton algal species of HAB in the ECS in recent years are Prorocentrum donghaiense (dinoflagellates), Karenia mikimotoi (dinoflagellates which could produce hemolytic and ichthyotoxins) and Skeletonema costatum (diatom). The discrimination between the dinoflagellates and diatom HAB through ocean color remote sensing approach can add the knowledge of HAB events in ECS and help to the precaution. A series of in-situ measurement consisted of absorption coefficient, total scattering and particulate backscattering coefficient was conducted in the southern coast of Zhejiang Province in May 2009, and the estuary of Changjiang River in August 2009 and December 2010, which encountered two HAB events and a moderate bloom. The Inherent Optical Properties (IOPs) of the bloom waters have significant difference between phytoplankton species in absorption and backscattering properties. The chlorophyll a specific absorption coefficient (a*phy(λ)) for the bloom patches (chlorophyll a concentration >6mg m-3) differ greatly from the adjacent normal seawater, with the a*phy(λ) of bloom water lower than 0.03 m2 mg-1 while the a*phy(λ) of the adjacent normal seawater is much higher (even up to 0.06 m2 mg-1). Meanwhile, the backscattering coefficients at 6 wavebands (420, 442, 470, 510, 590 and 700nm) are also remarkably lower for bloom waters (<0.01 m-1) than the normal seawater (> 0.02 m-1). The backscattering coefficient ratio (Rbp(λ)) is much lower for diatom bloom waters than for dinoflagellates types (0.01079 vs. 0.01227). A discrimination model based on IOPs is established, and several typical dinoflagellates and diatom bloom events including Prorocentrum donghaiense, Karenia mikimotoi and Skeletonema costatum in the ECS are picked out for testing with the MODIS-L2 and L3 ocean color remote sensing products from NASA

  2. Statistical feature selection for enhanced detection of brain tumor

    NASA Astrophysics Data System (ADS)

    Chaddad, Ahmad; Colen, Rivka R.

    2014-09-01

    Feature-based methods are widely used in the brain tumor recognition system. Robust of early cancer detection is one of the most powerful image processing tools. Specifically, statistical features, such as geometric mean, harmonic mean, mean excluding outliers, median, percentiles, skewness and kurtosis, have been extracted from brain tumor glioma to aid in discriminating two levels namely, Level I and Level II using fluid attenuated inversion recovery (FLAIR) sequence in the diagnosis of brain tumor. Statistical feature describes the major characteristics of each level from glioma which is an important step to evaluate heterogeneity of cancer area pixels. In this paper, we address the task of feature selection to identify the relevant subset of features in the statistical domain, while discarding those that are either redundant or confusing, thereby improving the performance of feature-based scheme to distinguish between Level I and Level II. We apply a Decision Structure algorithm to find the optimal combination of nonhomogeneity based statistical features for the problem at hand. We employ a Naïve Bayes classifier to evaluate the performance of the optimal statistical feature based scheme in terms of its glioma Level I and Level II discrimination capability and use real-data collected from 17 patients have a glioblastoma multiforme (GBM). Dataset provided from 3 Tesla MR imaging system by MD Anderson Cancer Center. For the specific data analyzed, it is shown that the identified dominant features yield higher classification accuracy, with lower number of false alarms and missed detections, compared to the full statistical based feature set. This work has been proposed and analyzed specific GBM types which Level I and Level II and the dominant features were considered as feature aid to prognostic indicators. These features were selected automatically to be better able to determine prognosis from classical imaging studies.

  3. Ultraviolet spectra of quenched carbonaceous composite derivatives: Comparison to the '217 nanometer' interstellar absorption feature

    NASA Technical Reports Server (NTRS)

    Sakata, Akira; Wada, Setsuko; Tokunaga, Alan T.; Narisawa, Takatoshi; Nakagawa, Hidehiro; Ono, Hiroshi

    1994-01-01

    QCCs (quenched carbonaceous composite) are amorphus carbonaceous material formed from a hydrocarbon plasma. We present the UV-visible spectra of 'filmy QCC; (obtained outside of the beam ejected from the hydrocarbon plasma) and 'dark QCC' (obtained very near to the beam) for comparison to the stellar extinction curve. When filmy QCC is heated to 500-700 C (thermally altered), the wavelength of the absorption maximum increases form 204 nm to 220-222 nm. The dark QCC has an absorption maximum at 217-222 nm. In addition, the thermally altered filmy QCC has a slope change at about 500 nm which resmbles that in the interstellar extinction curve. The resemblance of the extinction curve of the QCCs to that of the interstellar medium suggests that QCC derivatives may be representative of the type of interstellar material that produces the 217 nm interstellar medium feature. The peak extinction of the dark QCC is higher than the average interstellar extinction curve while that of the thermally altered filmy QCC is lower, so that a mixture of dark and thermally altered filmy QCC can match the peak extinction observed in the interstellar medium. It is shown from electron micrographs that most of the thermally altered flimy QCC is in the form of small grainy structure less than 4 nm in diameter. This shows that the structure unit causing the 217-222 nm feature in QCC is very small.

  4. A broadband absorption spectrometer using light emitting diodes for ultrasensitive, in situ trace gas detection

    NASA Astrophysics Data System (ADS)

    Langridge, Justin M.; Ball, Stephen M.; Shillings, Alexander J. L.; Jones, Roderic L.

    2008-12-01

    A broadband absorption spectrometer has been developed for highly sensitive and target-selective in situ trace gas measurements. The instrument employs two distinct modes of operation: (i) broadband cavity enhanced absorption spectroscopy (BBCEAS) is used to quantify the concentration of gases in sample mixtures from their characteristic absorption features, and (ii) periodic measurements of the cavity mirrors' reflectivity are made using step-scan phase shift cavity ringdown spectroscopy (PSCRDS). The latter PSCRDS method provides a stand-alone alternative to the more usual method of determining mirror reflectivities by measuring BBCEAS absorption spectra for calibration samples of known composition. Moreover, the instrument's two modes of operation use light from the same light emitting diode transmitted through the cavity in the same optical alignment, hence minimizing the potential for systematic errors between mirror reflectivity determinations and concentration measurements. The ability of the instrument to quantify absorber concentrations is tested in instrument intercomparison exercises for NO2 (versus a laser broadband cavity ringdown spectrometer) and for H2O (versus a commercial hygrometer). A method is also proposed for calculating effective absorption cross sections for fitting the differential structure in BBCEAS spectra due to strong, narrow absorption lines that are under-resolved and hence exhibit non-Beer-Lambert law behavior at the resolution of the BBCEAS measurements. This approach is tested on BBCEAS spectra of water vapor's 4v+δ absorption bands around 650 nm. The most immediate analytical application of the present instrument is in quantifying the concentration of reactive trace gases in the ambient atmosphere. The instrument's detection limits for NO3 as a function of integration time are considered in detail using an Allan variance analysis. Experiments under laboratory conditions produce a 1σ detection limit of 0.25 pptv for a 10 s

  5. Optical Path Switching Based Differential Absorption Radiometry for Substance Detection

    NASA Technical Reports Server (NTRS)

    Sachse, Glen W. (Inventor)

    2000-01-01

    A system and method are provided for detecting one or more substances. An optical path switch divides sample path radiation into a time series of alternating first polarized components and second polarized components. The first polarized components are transmitted along a first optical path and the second polarized components along a second optical path. A first gasless optical filter train filters the first polarized components to isolate at least a first wavelength band thereby generating first filtered radiation. A second gasless optical filter train filters the second polarized components to isolate at least a second wavelength band thereby generating second filtered radiation. The first wavelength band and second wavelength band are unique. Further, spectral absorption of a substance of interest is different at the first wavelength band as compared to the second wavelength band. A beam combiner combines the first and second filtered radiation to form a combined beam of radiation. A detector is disposed to monitor magnitude of at least a portion of the combined beam alternately at the first wavelength band and the second wavelength band as an indication of the concentration of the substance in the sample path.

  6. Feature Parameter Optimization for Seizure Detection/Prediction

    DTIC Science & Technology

    2007-11-02

    the window length for the feature under consideration. Figure 4 illustrates the variation of the k-factor for the fractal dimension feature, as...r Figure 4: K-Factor from the Fractal Dimension for Different Window Sizes Typically, the window sizes that maximized the k-factor were...Esteller R., Ph.D dissertation “Detection of seizure onset in epileptic patients from intracranial EEG signals ”, Georgia Institute of Technology

  7. Solar Physics Automated Feature Detection: Progress and Scientific Return

    NASA Astrophysics Data System (ADS)

    Martens, P. C.; SDO Feature Finding Team

    2011-12-01

    The SDO Feature Finding Team (FFT) has been implementing 16 feature finding modules for the last two and a half years. These modules have been designed to analyze the incoming stream of SDO data in near-real-time. Several modules are in regular operation now, most others are reaching that point. Our modules detect flares, filaments, dimming regions, sigmoids, emerging flux, bright points, jets, oscillations, active regions, coronal holes, and several other solar features. We are also developing a general trainable feature detection module, which can be applied to detect any phenomenon. Automated feature recognition has several advantages over the same by humans: first, and most importantly, much larger amounts of images can be analyzed by machines; second, the codes will apply consistent criteria for the detection of phenomena, much more so than humans. Of course the second point implies that the detection criteria must be carefully calibrated, otherwise the outcome will be consistent, but consistently wrong. Examples of the scientific potential unleashed our project are: i) Draw a butterfly diagram for Active Regions, ii) Find all filaments that coincide with sigmoids, and then correlate sigmoid handedness with filament chirality, iii) Correlate EUV jets with small scale flux emergence in coronal holes, iv) Draw polarity inversion line maps with regions of high shear and large magnetic field gradients overlayed, to pinpoint potential flaring regions. Then correlate with actual flare occurrence. All of these tasks will be accomplished with great ease; the power of this method is limited merely by the imagination of the researcher. In addition our modules provide space-weather alerts for flares, dimmings (proxies for eruptions), and flux emergence. In my presentation I will present an overview of the output from our feature detection codes, as well as first results of scientific analysis from the metadata.

  8. Cascade Classification with Adaptive Feature Extraction for Arrhythmia Detection.

    PubMed

    Park, Juyoung; Kang, Mingon; Gao, Jean; Kim, Younghoon; Kang, Kyungtae

    2017-01-01

    Detecting arrhythmia from ECG data is now feasible on mobile devices, but in this environment it is necessary to trade computational efficiency against accuracy. We propose an adaptive strategy for feature extraction that only considers normalized beat morphology features when running in a resource-constrained environment; but in a high-performance environment it takes account of a wider range of ECG features. This process is augmented by a cascaded random forest classifier. Experiments on data from the MIT-BIH Arrhythmia Database showed classification accuracies from 96.59% to 98.51%, which are comparable to state-of-the art methods.

  9. Hemorrhage detection in MRI brain images using images features

    NASA Astrophysics Data System (ADS)

    Moraru, Luminita; Moldovanu, Simona; Bibicu, Dorin; Stratulat (Visan), Mirela

    2013-11-01

    The abnormalities appear frequently on Magnetic Resonance Images (MRI) of brain in elderly patients presenting either stroke or cognitive impairment. Detection of brain hemorrhage lesions in MRI is an important but very time-consuming task. This research aims to develop a method to extract brain tissue features from T2-weighted MR images of the brain using a selection of the most valuable texture features in order to discriminate between normal and affected areas of the brain. Due to textural similarity between normal and affected areas in brain MR images these operation are very challenging. A trauma may cause microstructural changes, which are not necessarily perceptible by visual inspection, but they could be detected by using a texture analysis. The proposed analysis is developed in five steps: i) in the pre-processing step: the de-noising operation is performed using the Daubechies wavelets; ii) the original images were transformed in image features using the first order descriptors; iii) the regions of interest (ROIs) were cropped from images feature following up the axial symmetry properties with respect to the mid - sagittal plan; iv) the variation in the measurement of features was quantified using the two descriptors of the co-occurrence matrix, namely energy and homogeneity; v) finally, the meaningful of the image features is analyzed by using the t-test method. P-value has been applied to the pair of features in order to measure they efficacy.

  10. Wildfire smoke detection using temporospatial features and random forest classifiers

    NASA Astrophysics Data System (ADS)

    Ko, Byoungchul; Kwak, Joon-Young; Nam, Jae-Yeal

    2012-01-01

    We propose a wildfire smoke detection algorithm that uses temporospatial visual features and an ensemble of decision trees and random forest classifiers. In general, wildfire smoke detection is particularly important for early warning systems because smoke is usually generated before flames; in addition, smoke can be detected from a long distance owing to its diffusion characteristics. In order to detect wildfire smoke using a video camera, temporospatial characteristics such as color, wavelet coefficients, motion orientation, and a histogram of oriented gradients are extracted from the preceding 100 corresponding frames and the current keyframe. Two RFs are then trained using independent temporal and spatial feature vectors. Finally, a candidate block is declared as a smoke block if the average probability of two RFs in a smoke class is maximum. The proposed algorithm was successfully applied to various wildfire-smoke and smoke-colored videos and performed better than other related algorithms.

  11. Accurate feature detection and estimation using nonlinear and multiresolution analysis

    NASA Astrophysics Data System (ADS)

    Rudin, Leonid; Osher, Stanley

    1994-11-01

    A program for feature detection and estimation using nonlinear and multiscale analysis was completed. The state-of-the-art edge detection was combined with multiscale restoration (as suggested by the first author) and robust results in the presence of noise were obtained. Successful applications to numerous images of interest to DOD were made. Also, a new market in the criminal justice field was developed, based in part, on this work.

  12. Computed Tomography Features of Incidentally Detected Diffuse Thyroid Disease

    PubMed Central

    Rho, Myung Ho

    2014-01-01

    Objective. This study aimed to evaluate the CT features of incidentally detected DTD in the patients who underwent thyroidectomy and to assess the diagnostic accuracy of CT diagnosis. Methods. We enrolled 209 consecutive patients who received preoperative neck CT and subsequent thyroid surgery. Neck CT in each case was retrospectively investigated by a single radiologist. We evaluated the diagnostic accuracy of individual CT features and the cut-off CT criteria for detecting DTD by comparing the CT features with histopathological results. Results. Histopathological examination of the 209 cases revealed normal thyroid (n = 157), Hashimoto thyroiditis (n = 17), non-Hashimoto lymphocytic thyroiditis (n = 34), and diffuse hyperplasia (n = 1). The CT features suggestive of DTD included low attenuation, inhomogeneous attenuation, increased glandular size, lobulated margin, and inhomogeneous enhancement. ROC curve analysis revealed that CT diagnosis of DTD based on the CT classification of “3 or more” abnormal CT features was superior. When the “3 or more” CT classification was selected, the sensitivity, specificity, positive and negative predictive values, and accuracy of CT diagnosis for DTD were 55.8%, 95.5%, 80.6%, 86.7%, and 85.6%, respectively. Conclusion. Neck CT may be helpful for the detection of incidental DTD. PMID:25548565

  13. Lean histogram of oriented gradients features for effective eye detection

    NASA Astrophysics Data System (ADS)

    Sharma, Riti; Savakis, Andreas

    2015-11-01

    Reliable object detection is very important in computer vision and robotics applications. The histogram of oriented gradients (HOG) is established as one of the most popular hand-crafted features, which along with support vector machine (SVM) classification provides excellent performance for object recognition. We investigate dimensionality deduction on HOG features in combination with SVM classifiers to obtain efficient feature representation and improved classification performance. In addition to lean HOG features, we explore descriptors resulting from dimensionality reduction on histograms of binary descriptors. We consider three-dimensionality reduction techniques: standard principal component analysis, random projections, a computationally efficient linear mapping that is data independent, and locality preserving projections (LPP), which learns the manifold structure of the data. Our methods focus on the application of eye detection and were tested on an eye database created using the BioID and FERET face databases. Our results indicate that manifold learning is beneficial to classification utilizing HOG features. To demonstrate the broader usefulness of lean HOG features for object class recognition, we evaluated our system's classification performance on the CalTech-101 dataset with favorable outcomes.

  14. Radial gradients in initial mass function sensitive absorption features in the Coma brightest cluster galaxies

    NASA Astrophysics Data System (ADS)

    Zieleniewski, Simon; Houghton, Ryan C. W.; Thatte, Niranjan; Davies, Roger L.; Vaughan, Sam P.

    2017-02-01

    Using the Oxford Short Wavelength Integral Field specTrograph, we trace radial variations of initial mass function (IMF)-sensitive absorption features of three galaxies in the Coma cluster. We obtain resolved spectroscopy of the central 5 kpc for the two central brightest cluster galaxies (BCGs) NGC4889, NGC4874, and the BCG in the south-west group NGC4839, as well as unresolved data for NGC4873 as a low-σ* control. We present radial measurements of the IMF-sensitive features: sodium Na ISDSS, calcium triplet CaT, and iron-hydride FeH0.99, along with the magnesium Mg I0.88 and titanium oxide TiO0.89 features. We employ two separate methods for both telluric correction and sky subtraction around the faint FeH feature to verify our analysis. Within NGC4889 we find strong gradients of Na ISDSS and CaT but a flat FeH profile, which, from comparing to stellar population synthesis models, suggests an old, α-enhanced population with a Chabrier, or even bottom-light IMF. The age and abundance are in line with previous studies but the normal IMF is in contrast to recent results suggesting an increased IMF slope with increased velocity dispersion. We measure flat Na ISDSS and FeH profiles within NGC4874, and determine an old, possibly slightly α-enhanced and Chabrier IMF population. We find an α-enhanced, Chabrier IMF population in NGC4873. Within NGC4839 we measure both strong Na ISDSS and strong FeH, although with a large systematic uncertainty, suggesting a possible heavier IMF. The IMFs we infer for these galaxies are supported by published dynamical modelling. We stress that IMF constraints should be corroborated by further spectral coverage and independent methods on a galaxy-by-galaxy basis.

  15. Combining heterogeneous features for face detection using multiscale feature selection with binary particle swarm optimization

    NASA Astrophysics Data System (ADS)

    Pan, Hong; Xia, Si-Yu; Jin, Li-Zuo; Xia, Liang-Zheng

    2011-12-01

    We propose a fast multiscale face detector that boosts a set of SVM-based hierarchy classifiers constructed with two heterogeneous features, i.e. Multi-block Local Binary Patterns (MB-LBP) and Speeded Up Robust Features (SURF), at different image resolutions. In this hierarchical architecture, simple and fast classifiers using efficient MB-LBP descriptors remove large parts of the background in low and intermediate scale layers, thus only a small percentage of background patches look similar to faces and require a more accurate but slower classifier that uses distinctive SURF descriptor to avoid false classifications in the finest scale. By propagating only those patterns that are not classified as background, we can quickly decrease the amount of data need to be processed. To lessen the training burden of the hierarchy classifier, in each scale layer, a feature selection scheme using Binary Particle Swarm Optimization (BPSO) searches the entire feature space and filters out the minimum number of discriminative features that give the highest classification rate on a validation set, then these selected distinctive features are fed into the SVM classifier. We compared detection performance of the proposed face detector with other state-of-the-art methods on the CMU+MIT face dataset. Our detector achieves the best overall detection performance. The training time of our algorithm is 60 times faster than the standard Adaboost algorithm. It takes about 70 ms for our face detector to process a 320×240 image, which is comparable to Viola and Jones' detector.

  16. Development of a Near-Ir Cavity Enhanced Absorption Spectrometer for the Detection of Atmospheric Oxidation Products and Organoamines

    NASA Astrophysics Data System (ADS)

    Eddingsaas, Nathan C.; Jewell, Breanna; Thurnherr, Emily

    2014-06-01

    An estimated 10,000 to 100,000 different compounds have been measured in the atmosphere, each one undergoes many oxidation reactions that may or may not degrade air quality. To date, the fate of even some of the most abundant hydrocarbons in the atmosphere is poorly understood. One difficulty is the detection of atmospheric oxidation products that are very labile and decompose during analysis. To study labile species under atmospheric conditions, a highly sensitive, non-destructive technique is needed. Here we describe a near-IR incoherent broadband cavity enhanced absorption spectroscopy (IBBCEAS) setup that we are developing to meet this end. We have chosen to utilize the near-IR, where vibrational overtone absorptions are observed, due to the clean spectral windows and better spectral separation of absorption features. In one spectral window we can simultaneously and continuously monitor the composition of alcohols, hydroperoxides, and carboxylic acids in an air mass. In addition, we have used our CEAS setup to detect organoamines. The long effective path length of CEAS allows for low detection limits, even of the overtone absorption features, at ppb and ppt levels.

  17. A feature-based model of symmetry detection.

    PubMed Central

    Scognamillo, Renata; Rhodes, Gillian; Morrone, Concetta; Burr, David

    2003-01-01

    Symmetry detection is important for many biological visual systems, including those of mammals, insects and birds. We constructed a symmetry-detection algorithm with two stages: location of the visually salient features of the image, then evaluating the symmetry of these features over a long range, by means of a simple Gaussian filter. The algorithm detects the axis of maximum symmetry for human faces (or any arbitrary image) and calculates the magnitude of the asymmetry. We have evaluated the algorithm on the dataset of Rhodes et al. (1998 Psychonom. Bull. Rev. 5, 659-669) and found that the algorithm is able to discriminate small variations of symmetry created by computer-manipulating the symmetry levels in individual faces, and that the values measured by the algorithm correlate well with human psycho-physical symmetry ratings. PMID:12965001

  18. Crowding with detection and coarse discrimination of simple visual features.

    PubMed

    Põder, Endel

    2008-04-24

    Some recent studies have suggested that there are actually no crowding effects with detection and coarse discrimination of simple visual features. The present study tests the generality of this idea. A target Gabor patch, surrounded by either 2 or 6 flanker Gabors, was presented briefly at 4 deg eccentricity of the visual field. Each Gabor patch was oriented either vertically or horizontally (selected randomly). Observers' task was either to detect the presence of the target (presented with probability 0.5) or to identify the orientation of the target. The target-flanker distance was varied. Results were similar for the two tasks but different for 2 and 6 flankers. The idea that feature detection and coarse discrimination are immune to crowding may be valid for the two-flanker condition only. With six flankers, a normal crowding effect was observed. It is suggested that the complexity of the full pattern (target plus flankers) could explain the difference.

  19. Metamaterial-enhanced vibrational absorption spectroscopy for the detection of protein molecules.

    PubMed

    Bui, Tung S; Dao, Thang D; Dang, Luu H; Vu, Lam D; Ohi, Akihiko; Nabatame, Toshihide; Lee, YoungPak; Nagao, Tadaaki; Hoang, Chung V

    2016-08-24

    From visible to mid-infrared frequencies, molecular sensing has been a major successful application of plasmonics because of the enormous enhancement of the surface electromagnetic nearfield associated with the induced collective motion of surface free carriers excited by the probe light. However, in the lower-energy terahertz (THz) region, sensing by detecting molecular vibrations is still challenging because of low sensitivity, complicated spectral features, and relatively little accumulated knowledge of molecules. Here, we report the use of a micron-scale thin-slab metamaterial (MM) architecture, which functions as an amplifier for enhancing the absorption signal of the THz vibration of an ultrathin adsorbed layer of large organic molecules. We examined bovine serum albumin (BSA) as a prototype large protein molecule and Rhodamine 6G (Rh6G) and 3,3'-diethylthiatricarbocyanine iodide (DTTCI) as examples of small molecules. Among them, our MM significantly magnified only the signal strength of bulky BSA. On the other hand, DTTCI and Rh6G are inactive, as they lack low-frequency vibrational modes in this frequency region. The results obtained here clearly demonstrate the promise of MM-enhanced absorption spectroscopy in the THz region for detection and structural monitoring of large biomolecules such as proteins or pathogenic enzymes.

  20. Metamaterial-enhanced vibrational absorption spectroscopy for the detection of protein molecules

    PubMed Central

    Bui, Tung S.; Dao, Thang D.; Dang, Luu H.; Vu, Lam D.; Ohi, Akihiko; Nabatame, Toshihide; Lee, YoungPak; Nagao, Tadaaki; Hoang, Chung V.

    2016-01-01

    From visible to mid-infrared frequencies, molecular sensing has been a major successful application of plasmonics because of the enormous enhancement of the surface electromagnetic nearfield associated with the induced collective motion of surface free carriers excited by the probe light. However, in the lower-energy terahertz (THz) region, sensing by detecting molecular vibrations is still challenging because of low sensitivity, complicated spectral features, and relatively little accumulated knowledge of molecules. Here, we report the use of a micron-scale thin-slab metamaterial (MM) architecture, which functions as an amplifier for enhancing the absorption signal of the THz vibration of an ultrathin adsorbed layer of large organic molecules. We examined bovine serum albumin (BSA) as a prototype large protein molecule and Rhodamine 6G (Rh6G) and 3,3′-diethylthiatricarbocyanine iodide (DTTCI) as examples of small molecules. Among them, our MM significantly magnified only the signal strength of bulky BSA. On the other hand, DTTCI and Rh6G are inactive, as they lack low-frequency vibrational modes in this frequency region. The results obtained here clearly demonstrate the promise of MM-enhanced absorption spectroscopy in the THz region for detection and structural monitoring of large biomolecules such as proteins or pathogenic enzymes. PMID:27555217

  1. Metamaterial-enhanced vibrational absorption spectroscopy for the detection of protein molecules

    NASA Astrophysics Data System (ADS)

    Bui, Tung S.; Dao, Thang D.; Dang, Luu H.; Vu, Lam D.; Ohi, Akihiko; Nabatame, Toshihide; Lee, Youngpak; Nagao, Tadaaki; Hoang, Chung V.

    2016-08-01

    From visible to mid-infrared frequencies, molecular sensing has been a major successful application of plasmonics because of the enormous enhancement of the surface electromagnetic nearfield associated with the induced collective motion of surface free carriers excited by the probe light. However, in the lower-energy terahertz (THz) region, sensing by detecting molecular vibrations is still challenging because of low sensitivity, complicated spectral features, and relatively little accumulated knowledge of molecules. Here, we report the use of a micron-scale thin-slab metamaterial (MM) architecture, which functions as an amplifier for enhancing the absorption signal of the THz vibration of an ultrathin adsorbed layer of large organic molecules. We examined bovine serum albumin (BSA) as a prototype large protein molecule and Rhodamine 6G (Rh6G) and 3,3‧-diethylthiatricarbocyanine iodide (DTTCI) as examples of small molecules. Among them, our MM significantly magnified only the signal strength of bulky BSA. On the other hand, DTTCI and Rh6G are inactive, as they lack low-frequency vibrational modes in this frequency region. The results obtained here clearly demonstrate the promise of MM-enhanced absorption spectroscopy in the THz region for detection and structural monitoring of large biomolecules such as proteins or pathogenic enzymes.

  2. The X-shooter sample of GRB afterglow spectra: Properties of the absorption features

    NASA Astrophysics Data System (ADS)

    de Ugarte Postigo, Antonio

    2015-08-01

    Since its commissioning at ESO's Very Large Telescope in 2009, the X-shooter spectrograph has become the reference instrument in gamma-ray burst (GRB) afterglow spectroscopy. During this time our collaboration has collected more than 70 spectra of GRB afterglows, with redshifts ranging from 0.06 to 6.3. Thanks to their extreme luminosity and simple intrinsic shape, GRB spectra are optimal tools for the study of galactic environments at basically any redshift. Being produced by the death of short-lived massive stars, they are also tracers of star formation.I will present the sample of absorption spectral features identified in X-shooter's GRB spectra describing observation and analysis techniques. The different features are compared with the characteristics of the explosion (duration, spectral shape, energetics, etc.) and with the properties of the host galaxy (mass, age, etc.) to improve our understanding of the nature of the explosions and how they interact with their environments. Using the large redshift range of the spectra collection we perform studies of the evolution of GRB environments across the history of the Universe and their relation with the evolution of star formation.

  3. GBT Detection of Polarization-Dependent HI Absorption and HI Outflows in Local ULIRGs and Quasars

    NASA Technical Reports Server (NTRS)

    Teng, Stacy H.; Veilleux, Sylvain; Baker, Andrew J.

    2013-01-01

    We present the results of a 21-cm HI survey of 27 local massive gas-rich late-stage mergers and merger remnants with the Green Bank Telescope (GBT). These remnants were selected from the Quasar/ULIRG Evolution Study (QUEST) sample of ultraluminous infrared galaxies (ULIRGs; L(sub 8 - 1000 micron) > 10(exp 12) solar L) and quasars; our targets are all bolometrically dominated by active galactic nuclei (AGN) and sample the later phases of the proposed ULIRG-to-quasar evolutionary sequence. We find the prevalence of HI absorption (emission) to be 100% (29%) in ULIRGs with HI detections, 100% (88%) in FIR-strong quasars, and 63% (100%) in FIR-weak quasars. The absorption features are associated with powerful neutral outflows that change from being mainly driven by star formation in ULIRGs to being driven by the AGN in the quasars. These outflows have velocities that exceed 1500 km/s in some cases. Unexpectedly, we find polarization-dependent HI absorption in 57% of our spectra (88% and 63% of the FIR-strong and FIR-weak quasars, respectively). We attribute this result to absorption of polarized continuum emission from these sources by foreground HI clouds. About 60% of the quasars displaying polarized spectra are radio-loud, far higher than the approx 10% observed in the general AGN population. This discrepancy suggests that radio jets play an important role in shaping the environments in these galaxies. These systems may represent a transition phase in the evolution of gas-rich mergers into "mature" radio galaxies.

  4. Revealing spectral features in two-photon absorption spectrum of Hoechst 33342: a combined experimental and quantum-chemical study.

    PubMed

    Olesiak-Banska, Joanna; Matczyszyn, Katarzyna; Zaleśny, Robert; Murugan, N Arul; Kongsted, Jacob; Ågren, Hans; Bartkowiak, Wojciech; Samoc, Marek

    2013-10-10

    We present the results of wide spectral range Z-scan measurements of the two-photon absorption (2PA) spectrum of the Hoechst 33342 dye. The strongest 2PA of the dye in aqueous solution is found at 575 nm, and the associated two-photon absorption cross section is 245 GM. A weak but clearly visible 2PA band at ∼850 nm is also observed, a feature that could not be anticipated from the one-photon absorption spectrum. On the basis of the results of hybrid quantum mechanics/molecular mechanics calculations, we put forward a notion that the long-wavelength feature observed in the two-photon absorption spectrum of Hoechst 33342 is due to the formation of dye aggregates.

  5. Spectroscopy of Mars form 2.04 to 2.44 micron during the 1993 opposition: Absolute calibration and atmospheric vs mineralogic origin of narrow absorption features

    NASA Technical Reports Server (NTRS)

    Bell, James F., III; Pollack, James B.; Geballe, Thomas R.; Cruikshank, Dale P.; Freedman, Richard

    1994-01-01

    We present moderate-resolution (lambda/delta lambda = 300 to 370) reflectance spectral of Mars from 2.04 to 2.44 microns that were obtained at United Kingdom Infrared Telescope (UKIRT) during the 1993 opposition. Seven narrow absorption features were detected and found to have a Mars origin. By comparison with solar and Mars atmospheric spectra, five of these features were attributed all or in part to Mars atmospheric CO2 or CO (2.052 +/- 0.003, 2.114 +/- 0.002, 2.150 +/- 0.003, 2.331 +/- 0.001, and 2.357 +/- 0.002 microns). Two of the bands (2.331 +/- 0.001 and 2.357 +/- 0.002 micron) appear to have widths and depths that are consistent with additional, nonatmospheric absorptions, although a solar contribution cannot be entirely ruled out. Two other weak bands centered at 2.278 +/- 0.002 and 2.296 +/- 0.002 microns may be at least partially mineralogic in origin. The data provide no conclusive identification of the mineralogy responsible for these absorption features. However, examination of terrestrial spectral libraries and previous mineralogy responsible for these absorption features. However, examination of terrestrial spectral libraires and previous moderate spectral resolution mineral studies indicates that the most likely origin of these features is either (bi)carbonate or (bi)sulfate anions in framework silicates of (Fe, Mg)-OH bonds in sheet silicates. If the bands are caused by phyllosilicate minerals, then an explanation must be found for the extremely narrow widths of the cation-OH features in the Mars spectra as compared to terrestrial minerals.

  6. Spectroscopy of Mars form 2.04 to 2.44 micron during the 1993 opposition: Absolute calibration and atmospheric VS mineralogic origin of narrow absorption features

    NASA Astrophysics Data System (ADS)

    Bell, James F., III; Pollack, James B.; Geballe, Thomas R.; Cruikshank, Dale P.; Freedman, Richard

    1994-09-01

    We present moderate-resolution (lambda/delta lambda = 300 to 370) reflectance spectral of Mars from 2.04 to 2.44 microns that were obtained at United Kingdom Infrared Telescope (UKIRT) during the 1993 opposition. Seven narrow absorption features were detected and found to have a Mars origin. By comparison with solar and Mars atmospheric spectra, five of these features were attributed all or in part to Mars atmospheric CO2 or CO (2.052 +/- 0.003, 2.114 +/- 0.002, 2.150 +/- 0.003, 2.331 +/- 0.001, and 2.357 +/- 0.002 microns). Two of the bands (2.331 +/- 0.001 and 2.357 +/- 0.002 micron) appear to have widths and depths that are consistent with additional, nonatmospheric absorptions, although a solar contribution cannot be entirely ruled out. Two other weak bands centered at 2.278 +/- 0.002 and 2.296 +/- 0.002 microns may be at least partially mineralogic in origin. The data provide no conclusive identification of the mineralogy responsible for these absorption features. However, examination of terrestrial spectral libraries and previous mineralogy responsible for these absorption features. However, examination of terrestrial spectral libraires and previous moderate spectral resolution mineral studies indicates that the most likely origin of these features is either (bi)carbonate or (bi)sulfate anions in framework silicates of (Fe, Mg)-OH bonds in sheet silicates. If the bands are caused by phyllosilicate minerals, then an explanation must be found for the extremely narrow widths of the cation-OH features in the Mars spectra as compared to terrestrial minerals.

  7. Breast cancer detection in rotational thermography images using texture features

    NASA Astrophysics Data System (ADS)

    Francis, Sheeja V.; Sasikala, M.; Bhavani Bharathi, G.; Jaipurkar, Sandeep D.

    2014-11-01

    Breast cancer is a major cause of mortality in young women in the developing countries. Early diagnosis is the key to improve survival rate in cancer patients. Breast thermography is a diagnostic procedure that non-invasively images the infrared emissions from breast surface to aid in the early detection of breast cancer. Due to limitations in imaging protocol, abnormality detection by conventional breast thermography, is often a challenging task. Rotational thermography is a novel technique developed in order to overcome the limitations of conventional breast thermography. This paper evaluates this technique's potential for automatic detection of breast abnormality, from the perspective of cold challenge. Texture features are extracted in the spatial domain, from rotational thermogram series, prior to and post the application of cold challenge. These features are fed to a support vector machine for automatic classification of normal and malignant breasts, resulting in a classification accuracy of 83.3%. Feature reduction has been performed by principal component analysis. As a novel attempt, the ability of this technique to locate the abnormality has been studied. The results of the study indicate that rotational thermography holds great potential as a screening tool for breast cancer detection.

  8. Like-feature detection in geo-spatial sources

    NASA Astrophysics Data System (ADS)

    Samal, Ashok; Seth, Sharad; Cueto, Kevin

    2001-06-01

    The emergence of a new generation of satellites, increased dependence on computer-aided cartography, and conversion of paper-based maps along with the universal acceptance of the World Wide Web as a distribution medium, has resulted in widespread availability of geospatial data. Geospatial information systems have the potential to use this wealth of data to provide high-level decision support in important military, agricultural, urban planning, transportation and environmental monitoring applications. There are many challenges to take full advantage of this geo-spatial data collection. The first step in integration is to determine the correspondence between features in different sources. This problem, called like-feature detection is addressed in this paper. In addition to using the individual attributes of features, we use the geographic context abstracted as proximity graphs, to improve the matching process. The proximity graph models the surroundings of a feature in a source and provides a measure of similarity between features in two sources. Pair-wise similarity between features of two sources is then extended to multiple sources in a graph- theoretic framework. Experiments conducted to demonstrate the viability of our approach using a variety of data sources including satellite imagery, maps, and gazetteers show that the approach is effective.

  9. P300 Detection Based on EEG Shape Features

    PubMed Central

    Alvarado-González, Montserrat; Garduño, Edgar; Bribiesca, Ernesto; Yáñez-Suárez, Oscar; Medina-Bañuelos, Verónica

    2016-01-01

    We present a novel approach to describe a P300 by a shape-feature vector, which offers several advantages over the feature vector used by the BCI2000 system. Additionally, we present a calibration algorithm that reduces the dimensionality of the shape-feature vector, the number of trials, and the electrodes needed by a Brain Computer Interface to accurately detect P300s; we also define a method to find a template that best represents, for a given electrode, the subject's P300 based on his/her own acquired signals. Our experiments with 21 subjects showed that the SWLDA's performance using our shape-feature vector was 93%, that is, 10% higher than the one obtained with BCI2000-feature's vector. The shape-feature vector is 34-dimensional for every electrode; however, it is possible to significantly reduce its dimensionality while keeping a high sensitivity. The validation of the calibration algorithm showed an averaged area under the ROC (AUROC) curve of 0.88. Also, most of the subjects needed less than 15 trials to have an AUROC superior to 0.8. Finally, we found that the electrode C4 also leads to better classification. PMID:26881010

  10. Regularized feature reconstruction for spatio-temporal saliency detection.

    PubMed

    Ren, Zhixiang; Gao, Shenghua; Chia, Liang-Tien; Rajan, Deepu

    2013-08-01

    Multimedia applications such as image or video retrieval, copy detection, and so forth can benefit from saliency detection, which is essentially a method to identify areas in images and videos that capture the attention of the human visual system. In this paper, we propose a new spatio-temporal saliency detection framework on the basis of regularized feature reconstruction. Specifically, for video saliency detection, both the temporal and spatial saliency detection are considered. For temporal saliency, we model the movement of the target patch as a reconstruction process using the patches in neighboring frames. A Laplacian smoothing term is introduced to model the coherent motion trajectories. With psychological findings that abrupt stimulus could cause a rapid and involuntary deployment of attention, our temporal model combines the reconstruction error, regularizer, and local trajectory contrast to measure the temporal saliency. For spatial saliency, a similar sparse reconstruction process is adopted to capture the regions with high center-surround contrast. Finally, the temporal saliency and spatial saliency are combined together to favor salient regions with high confidence for video saliency detection. We also apply the spatial saliency part of the spatio-temporal model to image saliency detection. Experimental results on a human fixation video dataset and an image saliency detection dataset show that our method achieves the best performance over several state-of-the-art approaches.

  11. MULTI-WAVELENGTH STUDIES OF SPECTACULAR RAM PRESSURE STRIPPING OF A GALAXY: DISCOVERY OF AN X-RAY ABSORPTION FEATURE

    SciTech Connect

    Gu, Liyi; Makishima, Kazuo; Yagi, Masafumi; Nakazawa, Kazuhiro; Yoshida, Michitoshi; Fujita, Yutaka; Hattori, Takashi; Akahori, Takuya

    2013-11-10

    We report the detection of an X-ray absorption feature near the galaxy M86 in the Virgo cluster. The absorber has a column density of 2-3 × 10{sup 20} cm{sup –2}, and its position coincides with the peak of an intracluster H I cloud which was removed from the galaxy NGC 4388 presumably by ram pressure. These results indicate that the H I cloud is located in front of M86 along the line-of-sight, and suggest that the stripping was primarily created by an interaction between NGC 4388 and the hot plasmas of the Virgo cluster, not the M86 halo. By calculating an X-ray temperature map, we further detected an X-ray counterpart of the H I cloud up to ≈3' south of M86. It has a temperature of 0.89 keV and a mass of ∼4.5 × 10{sup 8} M {sub ☉}, exceeding the estimated H I gas mass. The high hot-to-cold gas ratio in the cloud indicates a significant evaporation of the H I gas, probably by thermal conduction from the hotter cluster plasma with a sub-Spitzer rate.

  12. Environmental temperature effect on the far-infrared absorption features of aromatic-based Titan's aerosol analogs

    NASA Astrophysics Data System (ADS)

    Gautier, Thomas; Trainer, Melissa G.; Loeffler, Mark J.; Sebree, Joshua A.; Anderson, Carrie M.

    2017-01-01

    Benzene detection has been reported in Titan's atmosphere both in the stratosphere at ppb levels by remote sensing (Coustenis et al., 2007; Vinatier et al., 2007) and in the thermosphere at ppm levels by the Cassini's Ion and Neutral Mass Spectrometer (Waite et al., 2007). This detection supports the idea that aromatic and heteroaromatic reaction pathways may play an important role in Titan's atmospheric chemistry, especially in the formation of aerosols. Indeed, aromatic molecules are easily dissociated by ultraviolet radiation and can therefore contribute significantly to aerosol formation. It has been shown recently that aerosol analogs produced from a gas mixture containing a low concentration of aromatic and/or heteroaromatic molecules (benzene, naphthalene, pyridine, quinoline and isoquinoline) have spectral signatures below 500 cm-1, a first step towards reproducing the aerosol spectral features observed by Cassini's Composite InfraRed Spectrometer (CIRS) in the far infrared (Anderson and Samuelson 2011, and references therein). In this work we investigate the influence of environmental temperature on the absorption spectra of such aerosol samples, simulating the temperature range to which aerosols, once formed, are exposed during their transport through Titan's stratosphere. Our results show that environmental temperature does not have any major effect on the spectral shape of these aerosol analogs in the far-infrared, which is consistent with the CIRS observations.

  13. Feature Extraction and Selection From the Perspective of Explosive Detection

    SciTech Connect

    Sengupta, S K

    2009-09-01

    Features are extractable measurements from a sample image summarizing the information content in an image and in the process providing an essential tool in image understanding. In particular, they are useful for image classification into pre-defined classes or grouping a set of image samples (also called clustering) into clusters with similar within-cluster characteristics as defined by such features. At the lowest level, features may be the intensity levels of a pixel in an image. The intensity levels of the pixels in an image may be derived from a variety of sources. For example, it can be the temperature measurement (using an infra-red camera) of the area representing the pixel or the X-ray attenuation in a given volume element of a 3-d image or it may even represent the dielectric differential in a given volume element obtained from an MIR image. At a higher level, geometric descriptors of objects of interest in a scene may also be considered as features in the image. Examples of such features are: area, perimeter, aspect ratio and other shape features, or topological features like the number of connected components, the Euler number (the number of connected components less the number of 'holes'), etc. Occupying an intermediate level in the feature hierarchy are texture features which are typically derived from a group of pixels often in a suitably defined neighborhood of a pixel. These texture features are useful not only in classification but also in the segmentation of an image into different objects/regions of interest. At the present state of our investigation, we are engaged in the task of finding a set of features associated with an object under inspection ( typically a piece of luggage or a brief case) that will enable us to detect and characterize an explosive inside, when present. Our tool of inspection is an X-Ray device with provisions for computed tomography (CT) that generate one or more (depending on the number of energy levels used) digitized 3

  14. The origin of blueshifted absorption features in the X-ray spectrum of PG 1211+143: outflow or disc

    NASA Astrophysics Data System (ADS)

    Gallo, L. C.; Fabian, A. C.

    2013-07-01

    In some radio-quiet active galactic nuclei (AGN), high-energy absorption features in the X-ray spectra have been interpreted as ultrafast outflows (UFOs) - highly ionized material (e.g. Fe XXV and Fe XXVI) ejected at mildly relativistic velocities. In some cases, these outflows can carry energy in excess of the binding energy of the host galaxy. Needless to say, these features demand our attention as they are strong signatures of AGN feedback and will influence galaxy evolution. For the same reason, alternative models need to be discussed and refuted or confirmed. Gallo and Fabian proposed that some of these features could arise from resonance absorption of the reflected spectrum in a layer of ionized material located above and corotating with the accretion disc. Therefore, the absorbing medium would be subjected to similar blurring effects as seen in the disc. A priori, the existence of such plasma above the disc is as plausible as a fast wind. In this work, we highlight the ambiguity by demonstrating that the absorption model can describe the ˜7.6 keV absorption feature (and possibly other features) in the quasar PG 1211+143, an AGN that is often described as a classic example of a UFO. In this model, the 2-10 keV spectrum would be largely reflection dominated (as opposed to power law dominated in the wind models) and the resonance absorption would be originating in a layer between about 6 and 60 gravitational radii. The studies of such features constitute a cornerstone for future X-ray observatories like Astro-H and Athena+. Should our model prove correct, or at least important in some cases, then absorption will provide another diagnostic tool with which to probe the inner accretion flow with future missions.

  15. Face liveness detection using shearlet-based feature descriptors

    NASA Astrophysics Data System (ADS)

    Feng, Litong; Po, Lai-Man; Li, Yuming; Yuan, Fang

    2016-07-01

    Face recognition is a widely used biometric technology due to its convenience but it is vulnerable to spoofing attacks made by nonreal faces such as photographs or videos of valid users. The antispoof problem must be well resolved before widely applying face recognition in our daily life. Face liveness detection is a core technology to make sure that the input face is a live person. However, this is still very challenging using conventional liveness detection approaches of texture analysis and motion detection. The aim of this paper is to propose a feature descriptor and an efficient framework that can be used to effectively deal with the face liveness detection problem. In this framework, new feature descriptors are defined using a multiscale directional transform (shearlet transform). Then, stacked autoencoders and a softmax classifier are concatenated to detect face liveness. We evaluated this approach using the CASIA Face antispoofing database and replay-attack database. The experimental results show that our approach performs better than the state-of-the-art techniques following the provided protocols of these databases, and it is possible to significantly enhance the security of the face recognition biometric system. In addition, the experimental results also demonstrate that this framework can be easily extended to classify different spoofing attacks.

  16. A Robust Shape Reconstruction Method for Facial Feature Point Detection.

    PubMed

    Tan, Shuqiu; Chen, Dongyi; Guo, Chenggang; Huang, Zhiqi

    2017-01-01

    Facial feature point detection has been receiving great research advances in recent years. Numerous methods have been developed and applied in practical face analysis systems. However, it is still a quite challenging task because of the large variability in expression and gestures and the existence of occlusions in real-world photo shoot. In this paper, we present a robust sparse reconstruction method for the face alignment problems. Instead of a direct regression between the feature space and the shape space, the concept of shape increment reconstruction is introduced. Moreover, a set of coupled overcomplete dictionaries termed the shape increment dictionary and the local appearance dictionary are learned in a regressive manner to select robust features and fit shape increments. Additionally, to make the learned model more generalized, we select the best matched parameter set through extensive validation tests. Experimental results on three public datasets demonstrate that the proposed method achieves a better robustness over the state-of-the-art methods.

  17. Asymmetry features for classification of thermograms in breast cancer detection

    NASA Astrophysics Data System (ADS)

    Nowak, Robert M.; Okuniewski, Rafał; Oleszkiewicz, Witold; Cichosz, Paweł; Jagodziński, Dariusz; Matysiewicz, Mateusz; Neumann, Łukasz

    2016-09-01

    The computer system for an automatic interpretation of thermographic pictures created by the Br-aster devices uses image processing and machine learning algorithms. The huge set of attributes analyzed by this software includes the asymmetry measurements between corresponding images, and these features are analyzed in presented paper. The system was tested on real data and achieves accuracy comparable to other popular techniques used for breast tumour detection.

  18. Ultrasensitive molecular absorption detection using metal slot antenna arrays.

    PubMed

    Ahn, Kwang Jun; Bahk, Young-Mi; Kim, Dai-Sik; Kyoung, Jisoo; Rotermund, Fabian

    2015-07-27

    We theoretically study the transmission reduction of light passing through absorptive molecules embedded in a periodic metal slot array in a near infrared wavelength regime. From the analytically solved transmitted light, we present a simple relation given by the attenuation length of light at the resonance wavelength of the slot antennas with respect to the spectral width of the resonant transmission peak. This relation clearly explains that the control of the transmission reduction even with very low absorptive materials is possible. We investigate also the transmission reduction by absorptive molecules in a real metallic slot antenna array on a dielectric substrate and compare the results with finite difference time domain calculations. In numerical calculations, we demonstrate that the same amount of transmission reduction by a bulk absorptive material can be achieved only with one-hundredth thickness of the same material when it is embedded in an optimized Fano-resonant slot antenna array. Our relation presented in this study can contribute to label-free chemical and biological sensing as an efficient design and performance criterion for periodic slot antenna arrays.

  19. New detections of Galactic molecular absorption systems toward ALMA calibrator sources

    NASA Astrophysics Data System (ADS)

    Ando, Ryo; Kohno, Kotaro; Tamura, Yoichi; Izumi, Takuma; Umehata, Hideki; Nagai, Hiroshi

    2016-02-01

    We report on Atacama Large Millimeter/submillimeter Array (ALMA) detections of molecular absorption lines in Bands 3, 6, and 7 toward four radio-loud quasars, which were observed as the bandpass and complex gain calibrators. The absorption systems, three of which are newly detected, are found to be Galactic origin. Moreover, HCO absorption lines toward two objects are detected, which almost doubles the number of HCO absorption samples in the Galactic diffuse medium. In addition, high HCO-to-H13CO+ column density ratios are found, suggesting that the interstellar media (ISM) observed toward the two calibrators are in photodissociation regions, which observationally illustrates the chemistry of diffuse ISM driven by ultraviolet (UV) radiation. These results demonstrate that calibrators in the ALMA Archive are potential sources for the quest for new absorption systems and for detailed investigation of the nature of the ISM.

  20. Deep PDF parsing to extract features for detecting embedded malware.

    SciTech Connect

    Munson, Miles Arthur; Cross, Jesse S.

    2011-09-01

    The number of PDF files with embedded malicious code has risen significantly in the past few years. This is due to the portability of the file format, the ways Adobe Reader recovers from corrupt PDF files, the addition of many multimedia and scripting extensions to the file format, and many format properties the malware author may use to disguise the presence of malware. Current research focuses on executable, MS Office, and HTML formats. In this paper, several features and properties of PDF Files are identified. Features are extracted using an instrumented open source PDF viewer. The feature descriptions of benign and malicious PDFs can be used to construct a machine learning model for detecting possible malware in future PDF files. The detection rate of PDF malware by current antivirus software is very low. A PDF file is easy to edit and manipulate because it is a text format, providing a low barrier to malware authors. Analyzing PDF files for malware is nonetheless difficult because of (a) the complexity of the formatting language, (b) the parsing idiosyncrasies in Adobe Reader, and (c) undocumented correction techniques employed in Adobe Reader. In May 2011, Esparza demonstrated that PDF malware could be hidden from 42 of 43 antivirus packages by combining multiple obfuscation techniques [4]. One reason current antivirus software fails is the ease of varying byte sequences in PDF malware, thereby rendering conventional signature-based virus detection useless. The compression and encryption functions produce sequences of bytes that are each functions of multiple input bytes. As a result, padding the malware payload with some whitespace before compression/encryption can change many of the bytes in the final payload. In this study we analyzed a corpus of 2591 benign and 87 malicious PDF files. While this corpus is admittedly small, it allowed us to test a system for collecting indicators of embedded PDF malware. We will call these indicators features throughout

  1. Many-body theory of trion absorption features in two-dimensional semiconductors

    NASA Astrophysics Data System (ADS)

    Efimkin, Dmitry K.; MacDonald, Allan H.

    2017-01-01

    Recent optical studies of monolayer transition-metal dichalcogenides have demonstrated that their excitonic absorption feature splits into two widely separated peaks at finite carrier densities. The additional peak is usually attributed to the presence of trions, bound states of two electrons and a hole or an electron and two holes. Here we argue that in the density range over which the trion peak is well resolved, it cannot be interpreted in terms of weakly coupled three-body systems and that the appropriate picture is instead one in which excitons are dressed by interactions with a Fermi sea of excess carriers. This coupling splits the exciton spectrum into a lower-energy attractive exciton-polaron branch, normally identified as a trion branch, and a higher-energy repulsive exciton-polaron branch, normally identified as an exciton branch. We have calculated the frequency and doping dependence of the optical conductivity and found that (i) the splitting varies linearly with the Fermi energy of the excess quasiparticles, (ii) the trion peak is dominant at high carrier densities, and (iii) the trion peak width is considerably smaller than that of the excitonic peak. Our results are in good agreement with recent experiments.

  2. A variable absorption feature in the X-ray spectrum of a magnetar.

    PubMed

    Tiengo, Andrea; Esposito, Paolo; Mereghetti, Sandro; Turolla, Roberto; Nobili, Luciano; Gastaldello, Fabio; Götz, Diego; Israel, Gian Luca; Rea, Nanda; Stella, Luigi; Zane, Silvia; Bignami, Giovanni F

    2013-08-15

    Soft-γ-ray repeaters (SGRs) and anomalous X-ray pulsars (AXPs) are slowly rotating, isolated neutron stars that sporadically undergo episodes of long-term flux enhancement (outbursts) generally accompanied by the emission of short bursts of hard X-rays. This behaviour can be understood in the magnetar model, according to which these sources are mainly powered by their own magnetic energy. This is supported by the fact that the magnetic fields inferred from several observed properties of SGRs and AXPs are greater than-or at the high end of the range of-those of radio pulsars. In the peculiar case of SGR 0418+5729, a weak dipole magnetic moment is derived from its timing parameters, whereas a strong field has been proposed to reside in the stellar interior and in multipole components on the surface. Here we show that the X-ray spectrum of SGR 0418+5729 has an absorption line, the properties of which depend strongly on the star's rotational phase. This line is interpreted as a proton cyclotron feature and its energy implies a magnetic field ranging from 2 × 10(14) gauss to more than 10(15) gauss.

  3. Study on synchronous detection method of methane and ethane with laser absorption spectroscopy technology

    NASA Astrophysics Data System (ADS)

    He, Ying; Zhang, Yu-jun; You, Kun; Gao, Yan-wei; Chen, Chen; Liu, Jian-guo; Liu, Wen-qing

    2016-10-01

    The main ingredient of mash gas is alkenes, and methane is the most parts of mash gas and ethane is a small portion of it. Fast, accurate, real-time measurement of methane and ethane concentration is an important task for preventing coal mining disaster. In this research, a monitoring system with tunable diode laser absorption spectroscopy (TDLAS) technology has been set up for simultaneous measurement of methane and ethane, and a DFB laser at wavelength of 1.653μm was used as the laser source. The absorption spectroscopy information of methane and ethane, especially the characteristic of the spectrum peak positions and relative intensity were determined by available spectral structures from previous study and available database. Then, the concentration inversion algorithm method based on the spectral resolution and feature extraction was designed for methane and ethane synchronous detection. At last, the continuously experimental results obtained by different concentration of methane and ethane sample gases with the multiple reflection cell and the standard distribution system. In this experiment, the standard distribution system made with the standard gas and two high precision mass flow meters of D07 Sevenstar series whose flow velocity is 1l/min and 5l/min respectively. When the multiple reflection cell work stably, the biggest detection error of methane concentration inversion was 3.7%, and the biggest detection error of ethane was 4.8%. So it is verified that this concentration inversion algorithm works stably and reliably. Thus, this technology could realize the real-time, fast and continuous measurement requirement of mash gas and it will provide the effective technical support to coal mining production in safety for our country.

  4. Non-contact feature detection using ultrasonic Lamb waves

    DOEpatents

    Sinha, Dipen N.

    2011-06-28

    Apparatus and method for non-contact ultrasonic detection of features on or within the walls of hollow pipes are described. An air-coupled, high-power ultrasonic transducer for generating guided waves in the pipe wall, and a high-sensitivity, air-coupled transducer for detecting these waves, are disposed at a distance apart and at chosen angle with respect to the surface of the pipe, either inside of or outside of the pipe. Measurements may be made in reflection or transmission modes depending on the relative position of the transducers and the pipe. Data are taken by sweeping the frequency of the incident ultrasonic waves, using a tracking narrow-band filter to reduce detected noise, and transforming the frequency domain data into the time domain using fast Fourier transformation, if required.

  5. Multispectral image feature fusion for detecting land mines

    SciTech Connect

    Clark, G.A.; Fields, D.J.; Sherwood, R.J.

    1994-11-15

    Our system fuses information contained in registered images from multiple sensors to reduce the effect of clutter and improve the the ability to detect surface and buried land mines. The sensor suite currently consists if a camera that acquires images in sixible wavelength bands, du, dual-band infrared (5 micron and 10 micron) and ground penetrating radar. Past research has shown that it is extremely difficult to distinguish land mines from background clutter in images obtained from a single sensor. It is hypothesized, however, that information fused from a suite of various sensors is likely to provide better detection reliability, because the suite of sensors detects a variety of physical properties that are more separate in feature space. The materials surrounding the mines can include natural materials (soil, rocks, foliage, water, holes made by animals and natural processes, etc.) and some artifacts.

  6. Atmospheric-water absorption features near 2.2 micrometers and their importance in high spectral resolution remote sensing

    NASA Technical Reports Server (NTRS)

    Kruse, F. A.; Clark, R. N.

    1986-01-01

    Selective absorption of electromagnetic radiation by atmospheric gases and water vapor is an accepted fact in terrestrial remote sensing. Until recently, only a general knowledge of atmospheric effects was required for analysis of remote sensing data; however, with the advent of high spectral resolution imaging devices, detailed knowledge of atmospheric absorption bands has become increasingly important for accurate analysis. Detailed study of high spectral resolution aircraft data at the U.S. Geological Survey has disclosed narrow absorption features centered at approximately 2.17 and 2.20 micrometers not caused by surface mineralogy. Published atmospheric transmission spectra and atmospheric spectra derived using the LOWTRAN-5 computer model indicate that these absorption features are probably water vapor. Spectral modeling indicates that the effects of atmospheric absorption in this region are most pronounced in spectrally flat materials with only weak absorption bands. Without correction and detailed knowledge of the atmospheric effects, accurate mapping of surface mineralogy (particularly at low mineral concentrations) is not possible.

  7. XMM-Newton Spectroscopy of the X-ray Detected Broad Absorption Line QSO CSO 755

    NASA Technical Reports Server (NTRS)

    Brandt, Niel

    2005-01-01

    We present the results from XMM-Newton observations of the highly optically polarized broad absorption line quasar (BALQSO) CSO 755. By analyzing its X-ray spectrum with a total of approximately 3000 photons we find that this source has an X-ray continuum of "typical" radio-quiet quasars, with a photon index of Gamma=1.83, and a rather flat (X-ray bright) intrinsic optical-to-X-ray spectral slope of alpha_ox=- 1.51. The source shows evidence for intrinsic absorption, and fitting the spectrum with a neutral-absorption model gives a column density of N_H approximately 1.2x10^22 cm^{-2}; this is among the lowest X-ray columns measured for BALQSOs. We do not detect, with high significance, any other absorption features in the X-ray spectrum. Upper limits we place on the rest-frame equivalent width of a neutral (ionized) Fe K-alpha line, less than =180 eV (less than =120 eV), and on the Compton-reflection component parameter, R less than =0.2, suggest that most of the X-rays from the source are directly observed rather than being scattered or reflected; this is also supported by the relatively flat intrinsic alpha ox we measure. The possibility that most of the X-ray flux is scattered due to the high level of UV-optical polarization is ruled out. Considering data for 46 BALQSOs from the literature, including CSO 755, we have found that the UV-optical continuum polarization level of BALQSOs is not correlated with any of their X-ray properties. A lack of significant short-term and long-term X-ray flux variations in the source may be attributed to a large black-hole mass in CSO 755. We note that another luminous BALQSO, PG 2112+059, has both similar shallow C IV BALs and moderate X-ray absorption.

  8. Feature detection on 3D images of dental imprints

    NASA Astrophysics Data System (ADS)

    Mokhtari, Marielle; Laurendeau, Denis

    1994-09-01

    A computer vision approach for the extraction of feature points on 3D images of dental imprints is presented. The position of feature points are needed for the measurement of a set of parameters for automatic diagnosis of malocclusion problems in orthodontics. The system for the acquisition of the 3D profile of the imprint, the procedure for the detection of the interstices between teeth, and the approach for the identification of the type of tooth are described, as well as the algorithm for the reconstruction of the surface of each type of tooth. A new approach for the detection of feature points, called the watershed algorithm, is described in detail. The algorithm is a two-stage procedure which tracks the position of local minima at four different scales and produces a final map of the position of the minima. Experimental results of the application of the watershed algorithm on actual 3D images of dental imprints are presented for molars, premolars and canines. The segmentation approach for the analysis of the shape of incisors is also described in detail.

  9. Prototype explosives detection system based on nuclear resonance absorption in nitrogen

    SciTech Connect

    Morgado, R.E.; Arnone, G.; Cappiello, C.C.; Gardner, S.D.; Hollas, C.L.; Ussery, L.E.; White, J.M.; Zahrt, J.D.; Krauss, R.A.

    1993-12-01

    A-prototype explosives detection system that was developed for experimental evaluation of a nuclear resonance absorption techniques is described. The major subsystems are a proton accelerator and beam transport, high-temperature proton target, an airline-luggage tomographic inspection station, and an image-processing/detection- alarm subsystem. The detection system performance, based on a limited experimental test, is reported.

  10. Detection of metal stress in boreal forest species using the 0.67-micron chlorophyll absorption band

    NASA Technical Reports Server (NTRS)

    Singhroy, Vernon H.; Kruse, Fred A.

    1991-01-01

    Several recent studies have shown that a shift of the red-edge inflection near 0.70 micron in vegetation reflectance spectra is an indicator of metal stress, partially attributable to changes in chlorophyll concentration. This 'red-edge shift', however, is difficult to detect and has been reported both toward longer (red) and shorter (blue) wavelengths. Our work demonstrates that direct measurement of the depth and width of the chlorophyll absorption band at 0.67 micron using digital feature extraction and absorption band characterization procedures developed for the analysis of mineral spectra is a more consistent indicator of metal stress. Additionally, the magnitude of these parameters is generally greater than that of the red edge shift and thus should be more amenable to detection and mapping using field and aircraft spectrometers.

  11. First detection of ionized helium absorption lines in infrared K band spectra of O-type stars

    NASA Technical Reports Server (NTRS)

    Conti, Peter S.; Block, David L.; Geballe, T. R.; Hanson, Margaret M.

    1993-01-01

    We have obtained high SNR, moderate-resolution K band spectra of two early O-type main sequence stars, HD 46150 O5 V, and HD 46223 O4 V, in the Rosette Nebula. We report the detection, for the first time, of the 2.189 micron He II line in O-type stars. Also detected is the 2.1661 micron Br-gamma line in absorption. The 2.058 micron He I line appears to be present in absorption in both stars, although its appearance at our resolution is complicated by atmospheric features. These three lines can form the basis for a spectral classification system for hot stars in the K band that may be used at infrared wavelengths to elucidate the nature of those luminous stars in otherwise obscured H II and giant H II regions.

  12. FE K EMISSION AND ABSORPTION FEATURES IN THE XMM-EPIC SPECTRUM OF THE SEYFERT GALAXY IC 4329A

    NASA Technical Reports Server (NTRS)

    Markowitz, A.; Reeves, J. N.; Braito, V.

    2001-01-01

    We present a re-analysis of the XMM-Newton long-look of the X-ray bright Seyfert galaxy IC 4329a. The Fe K bandpass is dominated by two peaks, consistent with emission from neutral or near-neutral Fe Ka and KP. A relativistic diskline model whereby both peaks are the result of one doubly-peaked diskline profile is found to be a poor description of the data. Models using two relativistic disklines are found to describe the emission profile well. A low-inclination, moderately-relativistic dual-diskline model is possible if the contribution from narrow components, due to distant material, is small or absent. A high-inclination, moderately relativistic profile for each peak is possible if there are roughly equal contributions from both the broad and narrow components. Upper limits on Fe XXV and Fe XXVI emission and absorption at the systemic velocity of IC 4329a are obtained. We also present the results of RXTE monitoring of this source obtained so far; the combined XMM-Newton and RXTE data sets allow us to explore the time-resolved spectral behavior of this source on time scales ranging from hours to 2 years. We find no strong evidence for variability of the Fe Ka emission line on any time scale probed, likely due to the minimal level of continuum variability. We detect a narrow absorption line, at a energy of 7.68 keV in the rest frame of the source; its significance has been confirmed using Monte Carlo simulations. This feature is most likely due to absorption from Fe XXVI blueshifted to approximately 0.1c relative to the systemic velocity, making IC 4329a the lowest-redshift AGN known with a high-velocity, highly-ionized outflow component. As is often the case with similar outflows seen in high-luminosity quasars, the estimated mass outflow rate is larger than the inflow accretion rate, signaling that the outflow represents a substantial portion of the total energy budget of the AGN. The outflow could arise from a radiatively-driven disk wind, or it may be in the

  13. Dielectronic recombination measurements of iron M-shell ions motivated by active galactic nuclei X-ray absorption features

    NASA Astrophysics Data System (ADS)

    Lukic, V. D.; Schnell, M.; Savin, D. W.; Brandau, C.; Schmidt, E. W.; Bohm, S.; Muller, A.; Schippers, S.; Lestinsky, M.; Sprenger, F.; Wolf, A.; Altun, Z.; Badnell, N. R.

    2008-07-01

    XMM-Newton and Chandra observations of active galactic nuclei (AGN) show rich spectra of X-ray absorption lines. These observations have detected a broad unresolved transition array (UTA) between 15-17 A. This is attributed to inner-shell photoexcitation of M-shell iron ions. Modeling these UTA features is currently limited by uncertainties in the low-temperature dielectronic recombination (DR) data for M-shell iron. In order to resolve this issue, and to provide reliable iron M-shell DR data for plasma modeling, we are carrying out a series of laboratory measurements using the heavy-ion Test Storage Ring (TSR) at the Max-Plank-Institute for Nuclear Physics in Heidelberg, Germany. Currently, laboratory measurements of low temperature DR can only be performed at storage rings. We use the DR data obtained at TSR, to calculate rate coefficients for plasma modeling and to benchmark theoretical DR calculations. At temperatures where these ions are predicted to form in photoionized gas, we find a significant discrepancy between our experimental results and previously recommended DR rate coefficients. Here we report our recent experimental results for DR of Mg-like Fe XV forming Al-like Fe XIV.

  14. A search for weak ultraviolet interstellar absorption features in IUE spectra of Rho Ophiuchi and Zeta Ophiuchi

    NASA Technical Reports Server (NTRS)

    Welty, D. E.; Thorburn, J. A.; Hobbs, L. M.; York, D. G.

    1992-01-01

    We have applied procedures designed to reduce substantially the nonrandom, so-called 'fixed-pattern' noise present in IUE spectra to archival long-wavelength high-dispersion spectra of Rho Ophiuchi and Zeta Ophiuchi. Substantial elimination of the fixed-pattern noise via flat fielding can yield 2sigma equivalent width limits of 5-10 mA from the sum of a small number (about less than 5) of well-exposed archival spectra, and increases confidence in the reality of any weak features found. Examination of complete long-wavelength (about 2200-3250 A) spectra of these two stars has revealed, in addition to many known strong absorption lines, several lines of Fe I and Si I which had not previously been reported, as well as a small number of possible unidentified lines. We also present substantially improved upper limits to the equivalent widths of a number of other weak lines; limits an order of magnitude smaller, now achievable with the HST GHRS, should produce detections of some of these.

  15. The initial mass functions of M31 and M32 through far red stellar absorption features

    NASA Astrophysics Data System (ADS)

    Zieleniewski, Simon; Houghton, Ryan C. W.; Thatte, Niranjan; Davies, Roger L.

    2015-09-01

    Using the Oxford Short Wavelength Integral Field specTrograph, we investigate radial variations of several initial mass function (IMF) dependent absorption features in M31 and M32. We obtain high signal-to-noise spectra at six pointings along the major axis of M31 out to ˜700 arcsec (2.7 kpc) and a single pointing of the central 10 pc for M32. In M31 the sodium Na I λ8190 index shows a flat equivalent width profile at ˜0.4 Å through the majority of the bulge, with a strong gradient up to 0.8 Å in the central 10 arcsec (38 pc); the Wing-Ford FeH λ9916 index is measured to be constant at 0.4 Å for all radii; and calcium triplet CaT λλ8498, 8542, 8662 shows a gradual increase through the bulge towards the centre. M32 displays flat profiles for all three indices, with FeH at ˜0.5 Å, very high CaT at ˜0.8 Å and low Na I at ˜0.1 Å. We analyse these data using stellar population models. We find that M31 is well described on all scales by a Chabrier IMF, with a gradient in sodium enhancement of [Na/Fe] ˜ +0.3 dex in the outer bulge, rising within the central 10 arcsec to perhaps [Na/Fe] ˜ +1.0 dex in the nuclear region. We find M32 is described by a Chabrier IMF and young stellar age in line with other studies. Models show that CaT is much more sensitive to metallicity and [α/Fe] than to IMF. We note that the centres of M31 and M32 have very high stellar densities and yet we measure Chabrier IMFs in these regions.

  16. Clinical feasibility of rapid confocal melanoma feature detection

    NASA Astrophysics Data System (ADS)

    Hennessy, Ricky; Jacques, Steve; Pellacani, Giovanni; Gareau, Daniel

    2010-02-01

    In vivo reflectance confocal microscopy shows promise for the early detection of malignant melanoma. One diagnostic trait of malignancy is the presence of pagetoid melanocytes in the epidermis. For automated detection of MM, this feature must be identified quantitatively through software. Beginning with in vivo, noninvasive confocal images from 10 unequivocal MMs and benign nevi, we developed a pattern recognition algorithm that automatically identified pagetoid melanocytes in all four MMs and identified none in five benign nevi. One data set was discarded due to artifacts caused by patient movement. With future work to bring the performance of this pattern recognition technique to the level of the clinicians on difficult lesions, melanoma diagnosis could be brought to primary care facilities and save many lives by improving early diagnosis.

  17. Surface vs. atmospheric origin of 2.1-2.5 micron absorption features in the Martian spectrum

    NASA Technical Reports Server (NTRS)

    Bell, James F., III; Crisp, David

    1992-01-01

    For 20 years the origin of subtle absorption features in the spectrum of Mars near 2.3 micro-m ('K' band: 1.9-2.5 micro-m) has been debated. This spectral region contains gaseous absorption features predominantly from CO2 and CO on Mars and from telluric H2O and CO2. The authors have obtained new higher spectral resolution telescopic K band spectra of 10 surface regions using the Infrared Telescope Facility (IRTF) at Mauna Kea during 1990. The goals were to confirm the existence of broad features seen at lower spectral resolution and to determine whether these bands are caused by atmospheric gases, surface (or airborne dust) minerals, or a combination of both.

  18. Colitis detection on abdominal CT scans by rich feature hierarchies

    NASA Astrophysics Data System (ADS)

    Liu, Jiamin; Lay, Nathan; Wei, Zhuoshi; Lu, Le; Kim, Lauren; Turkbey, Evrim; Summers, Ronald M.

    2016-03-01

    Colitis is inflammation of the colon due to neutropenia, inflammatory bowel disease (such as Crohn disease), infection and immune compromise. Colitis is often associated with thickening of the colon wall. The wall of a colon afflicted with colitis is much thicker than normal. For example, the mean wall thickness in Crohn disease is 11-13 mm compared to the wall of the normal colon that should measure less than 3 mm. Colitis can be debilitating or life threatening, and early detection is essential to initiate proper treatment. In this work, we apply high-capacity convolutional neural networks (CNNs) to bottom-up region proposals to detect potential colitis on CT scans. Our method first generates around 3000 category-independent region proposals for each slice of the input CT scan using selective search. Then, a fixed-length feature vector is extracted from each region proposal using a CNN. Finally, each region proposal is classified and assigned a confidence score with linear SVMs. We applied the detection method to 260 images from 26 CT scans of patients with colitis for evaluation. The detection system can achieve 0.85 sensitivity at 1 false positive per image.

  19. Detection and analysis of diamond fingerprinting feature and its application

    NASA Astrophysics Data System (ADS)

    Li, Xin; Huang, Guoliang; Li, Qiang; Chen, Shengyi

    2011-01-01

    Before becoming a jewelry diamonds need to be carved artistically with some special geometric features as the structure of the polyhedron. There are subtle differences in the structure of this polyhedron in each diamond. With the spatial frequency spectrum analysis of diamond surface structure, we can obtain the diamond fingerprint information which represents the "Diamond ID" and has good specificity. Based on the optical Fourier Transform spatial spectrum analysis, the fingerprinting identification of surface structure of diamond in spatial frequency domain was studied in this paper. We constructed both the completely coherent diamond fingerprinting detection system illuminated by laser and the partially coherent diamond fingerprinting detection system illuminated by led, and analyzed the effect of the coherence of light source to the diamond fingerprinting feature. We studied rotation invariance and translation invariance of the diamond fingerprinting and verified the feasibility of real-time and accurate identification of diamond fingerprint. With the profit of this work, we can provide customs, jewelers and consumers with a real-time and reliable diamonds identification instrument, which will curb diamond smuggling, theft and other crimes, and ensure the healthy development of the diamond industry.

  20. A Robust Shape Reconstruction Method for Facial Feature Point Detection

    PubMed Central

    Huang, Zhiqi

    2017-01-01

    Facial feature point detection has been receiving great research advances in recent years. Numerous methods have been developed and applied in practical face analysis systems. However, it is still a quite challenging task because of the large variability in expression and gestures and the existence of occlusions in real-world photo shoot. In this paper, we present a robust sparse reconstruction method for the face alignment problems. Instead of a direct regression between the feature space and the shape space, the concept of shape increment reconstruction is introduced. Moreover, a set of coupled overcomplete dictionaries termed the shape increment dictionary and the local appearance dictionary are learned in a regressive manner to select robust features and fit shape increments. Additionally, to make the learned model more generalized, we select the best matched parameter set through extensive validation tests. Experimental results on three public datasets demonstrate that the proposed method achieves a better robustness over the state-of-the-art methods. PMID:28316615

  1. Automated Solar Feature Detection for Space Weather Applications

    NASA Astrophysics Data System (ADS)

    Pérez-Suárez, David; Higgins, Paul A.; Bloomfield, D. Shaun; McAteer, R. T. James; Krista, Larisza D.; Byrne, Jason P.; Gallagher, Peter. T.

    2011-03-01

    The solar surface and atmosphere are highly dynamic plasma environments, which evolve over a wide range of temporal and spatial scales. Large-scale eruptions, such as coronal mass ejections, can be accelerated to millions of kilometres per hour in a matter of minutes, making their automated detection and characterisation challenging. Additionally, there are numerous faint solar features, such as coronal holes and coronal dimmings, which are important for space weather monitoring and forecasting, but their low intensity and sometimes transient nature makes them problematic to detect using traditional image processing techniques. These difficulties are compounded by advances in ground- and space- based instrumentation, which have increased the volume of data that solar physicists are confronted with on a minute-by-minute basis; NASA's Solar Dynamics Observatory for example is returning many thousands of images per hour (~1.5 TB/day). This chapter reviews recent advances in the application of images processing techniques to the automated detection of active regions, coronal holes, filaments, CMEs, and coronal dimmings for the purposes of space weather monitoring and prediction.

  2. Airborne Measurements of CO2 Column Absorption and Range Using a Pulsed Direct-Detection Integrated Path Differential Absorption Lidar

    NASA Technical Reports Server (NTRS)

    Abshire, James B.; Riris, Haris; Weaver, Clark J.; Mao, Jianping; Allan, Graham R.; Hasselbrack, William E.; Browell, Edward V.

    2013-01-01

    We report on airborne CO2 column absorption measurements made in 2009 with a pulsed direct-detection lidar operating at 1572.33 nm and utilizing the integrated path differential absorption technique. We demonstrated these at different altitudes from an aircraft in July and August in flights over four locations in the central and eastern United States. The results show clear CO2 line shape and absorption signals, which follow the expected changes with aircraft altitude from 3 to 13 km. The lidar measurement statistics were also calculated for each flight as a function of altitude. The optical depth varied nearly linearly with altitude, consistent with calculations based on atmospheric models. The scatter in the optical depth measurements varied with aircraft altitude as expected, and the median measurement precisions for the column varied from 0.9 to 1.2 ppm. The altitude range with the lowest scatter was 810 km, and the majority of measurements for the column within it had precisions between 0.2 and 0.9 ppm.

  3. Detection of ocean glint and ozone absorption using LCROSS Earth observations

    SciTech Connect

    Robinson, Tyler D.; Ennico, Kimberly; Meadows, Victoria S.; Sparks, William; Schwieterman, Edward W.; Bussey, D. Ben J.; Breiner, Jonathan

    2014-06-01

    The Lunar CRater Observation and Sensing Satellite (LCROSS) observed the distant Earth on three occasions in 2009. These data span a range of phase angles, including a rare crescent phase view. For each epoch, the satellite acquired near-infrared and mid-infrared full-disk images, and partial-disk spectra at 0.26-0.65 μm (λ/Δλ ∼ 500) and 1.17-2.48 μm (λ/Δλ ∼ 50). Spectra show strong absorption features due to water vapor and ozone, which is a biosignature gas. We perform a significant recalibration of the UV-visible spectra and provide the first comparison of high-resolution visible Earth spectra to the NASA Astrobiology Institute's Virtual Planetary Laboratory three-dimensional spectral Earth model. We find good agreement with the observations, reproducing the absolute brightness and dynamic range at all wavelengths for all observation epochs, thus validating the model to within the ∼10% data calibration uncertainty. Data-model comparisons reveal a strong ocean glint signature in the crescent phase data set, which is well matched by our model predictions throughout the observed wavelength range. This provides the first observational test of a technique that could be used to determine exoplanet habitability from disk-integrated observations at visible and near-infrared wavelengths, where the glint signal is strongest. We examine the detection of the ozone 255 nm Hartley and 400-700 nm Chappuis bands. While the Hartley band is the strongest ozone feature in Earth's spectrum, false positives for its detection could exist. Finally, we discuss the implications of these findings for future exoplanet characterization missions.

  4. Influence of temperature and turbidity on water COD detection by UV absorption spectroscopy

    NASA Astrophysics Data System (ADS)

    Zhou, Kun-peng; Bi, Wei-hong; Zhang, Qi-hang; Fu, Xing-hu; Wu, Guo-qing

    2016-11-01

    Ultraviolet (UV) absorption spectroscopy is used to detect the concentration of water chemical oxygen demand (COD). The UV absorption spectra of COD solutions are analyzed qualitatively and quantitatively. The partial least square (PLS) algorithm is used to model COD solution and the modeling results are compared. The influence of environmental temperature and turbidity is analyzed. These results show that the influence of temperature on the predicted value can be ignored. However, the change of turbidity can affect the detection results of UV spectra, and the COD detection error can be effectively compensated by establishing the single-element regression model.

  5. Gas trace detection with cavity enhanced absorption spectroscopy: a review of its process in the field

    NASA Astrophysics Data System (ADS)

    Liu, Siqi; Luo, Zhifu; Tan, Zhongqi; Long, Xingwu

    2016-11-01

    Cavity-enhanced absorption spectroscopy (CEAS) is a technology in which the intracavity absorption is deduced from the intensity of light transmitted by the high finesse optical cavity. Then the samples' parameters, such as their species, concentration and absorption cross section, would be detection. It was first proposed and demonstrated by Engeln R. [1] and O'Keefe[2] in 1998. This technology has extraordinary detection sensitivity, high resolution and good practicability, so it is used in many fields , such as clinical medicine, gas detection and basic physics research. In this paper, we focus on the use of gas trace detection, including the advance of CEAS over the past twenty years, the newest research progresses, and the prediction of this technology's development direction in the future.

  6. Spectroscopic remote sensing of plant stress at leaf and canopy levels using the chlorophyll 680 nm absorption feature with continuum removal

    NASA Astrophysics Data System (ADS)

    Sanches, Ieda Del'Arco; Souza Filho, Carlos Roberto; Kokaly, Raymond Floyd

    2014-11-01

    This paper explores the use of spectral feature analysis to detect plant stress in visible/near infrared wavelengths. A time series of close range leaf and canopy reflectance data of two plant species grown in hydrocarbon-contaminated soil was acquired with a portable spectrometer. The ProSpecTIR-VS airborne imaging spectrometer was used to obtain far range hyperspectral remote sensing data over the field experiment. Parameters describing the chlorophyll 680 nm absorption feature (depth, width, and area) were derived using continuum removal applied to the spectra. A new index, the Plant Stress Detection Index (PSDI), was calculated using continuum-removed values near the chlorophyll feature centre (680 nm) and on the green-edge (560 and 575 nm). Chlorophyll feature's depth, width and area, the PSDI and a narrow-band normalised difference vegetation index were evaluated for their ability to detect stressed plants. The objective was to analyse how the parameters/indices were affected by increasing degrees of plant stress and to examine their utility as plant stress indicators at the remote sensing level (e.g. airborne sensor). For leaf data, PSDI and the chlorophyll feature area revealed the highest percentage (67-70%) of stressed plants. The PSDI also proved to be the best constraint for detecting the stress in hydrocarbon-impacted plants with field canopy spectra and airborne imaging spectroscopy data. This was particularly true using thresholds based on the ASD canopy data and considering the combination of higher percentage of stressed plants detected (across the thresholds) and fewer false-positives.

  7. Detection of tuberculosis using hybrid features from chest radiographs

    NASA Astrophysics Data System (ADS)

    Fatima, Ayesha; Akram, M. Usman; Akhtar, Mahmood; Shafique, Irrum

    2017-02-01

    Tuberculosis is an infectious disease and becomes a major threat all over the world but still diagnosis of tuberculosis is a challenging task. In literature, chest radiographs are considered as most commonly used medical images in under developed countries for the diagnosis of TB. Different methods have been proposed but they are not helpful for radiologists due to cost and accuracy issues. Our paper presents a methodology in which different combinations of features are extracted based on intensities, shape and texture of chest radiograph and given to classifier for the detection of TB. The performance of our methodology is evaluated using publically available standard dataset Montgomery Country (MC) which contains 138 CXRs among which 80 CXRs are normal and 58 CXRs are abnormal including effusion and miliary patterns etc. The accuracy of 81.16% was achieved and the results show that proposed method have outperformed existing state of the art methods on MC dataset.

  8. Measurement and feature analysis of absorption spectra of four algal species

    NASA Astrophysics Data System (ADS)

    Zhu, Jianhua; Zhou, Hongli; Han, Bing; Li, Tongji

    2016-04-01

    Two methods for particulate pigments (i.e., quantitative filter technique, QFT, and in vivo measurement, InVivo, respectively) and two methods for dissolved pigments (i.e., Acetone Extracts, AceEx, and high-performance liquid chromatography, HPLC, respectively) were used to obtain the optical absorption coefficient spectra for cultures of four typical algal species. Through normalization and analysis of the spectra, it is shown that (1) the four methods are able to measure optical absorption spectra of particulate and/or dissolved pigments; (2) that the optical absorption spectra of particulate and dissolved pigments were consistent in terms of the peak position in the blue wavelength, and the difference of the peak position in the near infrared wavelength was ~10 nm between each other; and (3) that the leveling effect of the absorption spectra of particulate pigments was significant. These four methods can all effectively measure the absorption coefficients of phytoplankton pigments, while each one has its unique advantages in different applications. Therefore, appropriate method should be carefully selected for various application due to their intrinsic difference.

  9. Measurement and feature analysis of absorption spectra of four algal species

    NASA Astrophysics Data System (ADS)

    Zhu, Jianhua; Zhou, Hongli; Han, Bing; Li, Tongji

    2017-03-01

    Two methods for particulate pigments (i.e., quantitative filter technique, QFT, and in vivo measurement, InVivo, respectively) and two methods for dissolved pigments (i.e., Acetone Extracts, AceEx, and high-performance liquid chromatography, HPLC, respectively) were used to obtain the optical absorption coefficient spectra for cultures of four typical algal species. Through normalization and analysis of the spectra, it is shown that (1) the four methods are able to measure optical absorption spectra of particulate and/or dissolved pigments; (2) that the optical absorption spectra of particulate and dissolved pigments were consistent in terms of the peak position in the blue wavelength, and the difference of the peak position in the near infrared wavelength was 10 nm between each other; and (3) that the leveling effect of the absorption spectra of particulate pigments was significant. These four methods can all effectively measure the absorption coefficients of phytoplankton pigments, while each one has its unique advantages in different applications. Therefore, appropriate method should be carefully selected for various application due to their intrinsic difference.

  10. Airborne Laser Absorption Spectrometer Measurements of CO2 Column Mixing Ratios: Source and Sink Detection in the Atmospheric Environment

    NASA Astrophysics Data System (ADS)

    Menzies, Robert T.; Spiers, Gary D.; Jacob, Joseph C.

    2016-06-01

    The JPL airborne Laser Absorption Spectrometer instrument has been flown several times in the 2007-2011 time frame for the purpose of measuring CO2 mixing ratios in the lower atmosphere. The four most recent flight campaigns were on the NASA DC-8 research aircraft, in support of the NASA ASCENDS (Active Sensing of CO2 Emissions over Nights, Days, and Seasons) mission formulation studies. This instrument operates in the 2.05-μm spectral region. The Integrated Path Differential Absorption (IPDA) method is used to retrieve weighted CO2 column mixing ratios. We present key features of the CO2LAS signal processing, data analysis, and the calibration/validation methodology. Results from flights in various U.S. locations during the past three years include observed mid-day CO2 drawdown in the Midwest, also cases of point-source and regional plume detection that enable the calculation of emission rates.

  11. Multi-epoch Detections of Water Ice Absorption in Edge-on Disks around Herbig Ae Stars: PDS 144N and PDS 453

    NASA Astrophysics Data System (ADS)

    Terada, Hiroshi; Tokunaga, Alan T.

    2017-01-01

    We report the multi-epoch detections of water ice in 2.8–4.2 μ {{m}} spectra of two Herbig Ae stars, PDS 144N (A2 IVe) and PDS 453 (F2 Ve), which have an edge-on circumstellar disk. The detected water ice absorption is found to originate from their protoplanetary disks. The spectra show a relatively shallow absorption of water ice of around 3.1 μ {{m}} for both objects. The optical depths of the water ice absorption are ∼0.1 and ∼0.2 for PDS 144N and PDS 453, respectively. Compared to the water ice previously detected in low-mass young stellar objects with an edge-on disk with a similar inclination angle, these optical depths are significantly lower. It suggests that stronger UV radiation from the central stars effectively decreases the water ice abundance around the Herbig Ae stars through photodesorption. The water ice absorption in PDS 453 shows a possible variation of the feature among the six observing epochs. This variation could be due to a change of absorption materials passing through our line of sight to the central star. The overall profile of the water ice absorption in PDS 453 is quite similar to the absorption previously reported in the edge-on disk object d216-0939, and this unique profile may be seen only at a high inclination angle in the range of 76°–80°.

  12. Supercontinuum high-speed cavity-enhanced absorption spectroscopy for sensitive multispecies detection.

    PubMed

    Werblinski, Thomas; Lämmlein, Bastian; Huber, Franz J T; Zigan, Lars; Will, Stefan

    2016-05-15

    Cavity-enhanced absorption spectroscopy is promising for many applications requiring a very high concentration sensitivity but often accompanied by low temporal resolution. In this Letter, we demonstrate a broadband cavity-enhanced absorption spectrometer capable of detection rates of up to 50 kHz, based on a spatially coherent supercontinuum (SC) light source and an in-house-built, high-speed near-infrared spectrograph. The SC spectrometer allows for the simultaneous quantitative detection of CO2, C2H2, and H2O within a spectral range from 1420 to 1570 nm. Using cavity mirrors with a specified reflectivity of R=98.0±0.3% a minimal spectrally averaged absorption coefficient of αmin=1·10-5  cm-1 can be detected at a repetition rate of 50 kHz.

  13. Spectrum sensing of trace C(2)H(2) detection in differential optical absorption spectroscopy technique.

    PubMed

    Chen, Xi; Dong, Xiaopeng

    2014-09-10

    An improved algorithm for trace C(2)H(2) detection is presented in this paper. The trace concentration is accurately calculated by focusing on the absorption spectrum from the frequency domain perspective. The advantage of the absorption spectroscopy frequency domain algorithm is its anti-interference capability. First, the influence of the background noise on the minimum detectable concentration is greatly reduced. Second, the time-consuming preprocess of spectra calibration in the differential optical absorption spectroscopy technique is skipped. Experimental results showed the detection limit of 50 ppm is achieved at a lightpath length of 0.2 m. This algorithm can be used in real-time spectrum analysis with high accuracy.

  14. Ultraviolet-visible absorptive features of water extractable and humic fractions of animal manure and compost

    Technology Transfer Automated Retrieval System (TEKTRAN)

    UV-vis spectroscopy is a useful tool for characterizing water extractable or humic fractions of natural organic matter (WEOM). Whereas the whole UV-visible spectra of these fractions are more or less featureless, the specific UV absorptivity at 254 and 280 nm as well as spectral E2/E3 and E4/E6 rat...

  15. Adaptive skin segmentation via feature-based face detection

    NASA Astrophysics Data System (ADS)

    Taylor, Michael J.; Morris, Tim

    2014-05-01

    Variations in illumination can have significant effects on the apparent colour of skin, which can be damaging to the efficacy of any colour-based segmentation approach. We attempt to overcome this issue by presenting a new adaptive approach, capable of generating skin colour models at run-time. Our approach adopts a Viola-Jones feature-based face detector, in a moderate-recall, high-precision configuration, to sample faces within an image, with an emphasis on avoiding potentially detrimental false positives. From these samples, we extract a set of pixels that are likely to be from skin regions, filter them according to their relative luma values in an attempt to eliminate typical non-skin facial features (eyes, mouths, nostrils, etc.), and hence establish a set of pixels that we can be confident represent skin. Using this representative set, we train a unimodal Gaussian function to model the skin colour in the given image in the normalised rg colour space - a combination of modelling approach and colour space that benefits us in a number of ways. A generated function can subsequently be applied to every pixel in the given image, and, hence, the probability that any given pixel represents skin can be determined. Segmentation of the skin, therefore, can be as simple as applying a binary threshold to the calculated probabilities. In this paper, we touch upon a number of existing approaches, describe the methods behind our new system, present the results of its application to arbitrary images of people with detectable faces, which we have found to be extremely encouraging, and investigate its potential to be used as part of real-time systems.

  16. Spectral feature characterization methods for blood stain detection in crime scene backgrounds

    NASA Astrophysics Data System (ADS)

    Yang, Jie; Mathew, Jobin J.; Dube, Roger R.; Messinger, David W.

    2016-05-01

    Blood stains are one of the most important types of evidence for forensic investigation. They contain valuable DNA information, and the pattern of the stains can suggest specifics about the nature of the violence that transpired at the scene. Blood spectral signatures containing unique reflectance or absorption features are important both for forensic on-site investigation and laboratory testing. They can be used for target detection and identification applied to crime scene hyperspectral imagery, and also be utilized to analyze the spectral variation of blood on various backgrounds. Non-blood stains often mislead the detection and can generate false alarms at a real crime scene, especially for dark and red backgrounds. This paper measured the reflectance of liquid blood and 9 kinds of non-blood samples in the range of 350 nm - 2500 nm in various crime scene backgrounds, such as pure samples contained in petri dish with various thicknesses, mixed samples with different colors and materials of fabrics, and mixed samples with wood, all of which are examined to provide sub-visual evidence for detecting and recognizing blood from non-blood samples in a realistic crime scene. The spectral difference between blood and non-blood samples are examined and spectral features such as "peaks" and "depths" of reflectance are selected. Two blood stain detection methods are proposed in this paper. The first method uses index to denote the ratio of "depth" minus "peak" over"depth" add"peak" within a wavelength range of the reflectance spectrum. The second method uses relative band depth of the selected wavelength ranges of the reflectance spectrum. Results show that the index method is able to discriminate blood from non-blood samples in most tested crime scene backgrounds, but is not able to detect it from black felt. Whereas the relative band depth method is able to discriminate blood from non-blood samples on all of the tested background material types and colors.

  17. On-column double-beam laser absorption detection for capillary electrophoresis

    SciTech Connect

    Xue, Y.; Yeung, E.S. )

    1993-08-01

    Double-beam laser absorption detection in capillary electrophoresis (CE) has been developed. This is based on the direct subtraction of reference and signal photocurrents by an electronic circuit, under feedback control, to reduce background noise. A simple equation for calculating concentrations has been proposed and was confirmed by experimental results. A practical noise-to-signal ratio of 1 [times] 10[sup [minus]5] in intensity is achieved. This is 5 times lower than that of commercial CE systems. For absorbance detection, as low as 2 [times] 10[sup [minus]8] M malachite green can be detected. This corresponds to a 25-fold improvement of detection limit over commercial systems. This gain in detectability results from both a reduction in intensity fluctuations (noise) and an increase in the effective absorption path length (signal). 22 refs., 6 figs.

  18. Laser Based Instruments Using Differential Absorption Detection for Above and Below Ground Monitoring of Carbon Dioxide

    NASA Astrophysics Data System (ADS)

    Humphries, S. D.; Barr, J. L.; Repasky, K. S.; Carlsten, J. L.; Spangler, L. H.; Dobeck, L. M.

    2008-12-01

    Carbon capture and sequestration in geologic formations provides a method to remove carbon dioxide (CO2) from entering the Earth's atmosphere. An important issue for the successful storage of CO2 is the ability to monitor geologic sequestration sites for leakage to verify site integrity. A field site for testing the performance of CO2 detection instruments and techniques has been developed by the Zero Emissions Research Technology (ZERT) group at Montana State University. A field experiment was conducted at the ZERT field site beginning July 9th, 2008 and ending August 7th, 2008 to test the performance of several CO2 detection instruments. The field site allows a controlled flow rate of CO2 to be released underground through a 100 m long horizontal pipe placed below the water table. A flow rate of 0.3 tons CO2/day was used for the entirety of this experiment. This paper describes the results from two laser based instruments that use differential absorption techniques to determine CO2 concentrations in real time both above and below the ground surface. Both instruments use a continuous wave (cw) temperature tunable distributed feedback (DFB) laser capable of tuning across several CO2 and water vapor absorption features between at 2003 nm and 2006 nm. The first instrument uses the DFB laser to measure path integrated atmospheric concentrations of CO2. The second instrument uses the temperature tunable DFB laser to monitor underground CO2 concentrations using a buried photonic bandgap optical fiber. The above ground instrument operated nearly continuously during the CO2 release experiment and an increase in atmospheric CO2 concentration above the release pipe of approximately 2.5 times higher than the background was observed. The underground instrument also operated continuously during the experiment and saw an increase in underground CO2 concentration of approximately 15 times higher than the background. These results from the 2008 ZERT field experiment demonstrate

  19. Determination of the in-flight spectral calibration of AVIRIS using atmospheric absorption features

    NASA Astrophysics Data System (ADS)

    Green, Robert O.

    1995-01-01

    Spectral calibration of the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) as data are acquired in flight is essential to quantitative analysis of the measured upwelling spectral radiance. In each spectrum measured by AVIRIS in flight, there are numerous atmospheric gas absorption bands that drive this requirement for accurate spectral calibration. If the surface and atmospheric properties are measured independently, these atmospheric absorption bands may be used to deduce the in-flight spectral calibration of an imaging spectrometer. Both the surface and atmospheric characteristics were measured for a calibration target during an in-flight calibration experiment held at Lunar Lake, Nevada on April 5, 1994. This paper uses upwelling spectral radiance predicted for the calibration target with the MODTRAN radiative transfer code to validate the spectral calibration of AVIRIS in flight.

  20. Monitoring of Water Content And Frozen State by using Millimeter Wave Absorption Features

    NASA Astrophysics Data System (ADS)

    Mizuno, Maya; Shindo, Kenji; Ogawa, Yuichi; Otani, Chiko; Kawase, Kodo

    In this research, we built an experimental setup for measuring the water content in plants and food, and for determining the water/ice state of a sample. The setup consists of a 35 GHz Gunn oscillator producing about 10 mW of output power, two horn antennas and a power meter. We have checked that the absorption of a leaf is directly proportional to its water content, and we could show how changes of the water content depend on photosynthesis, by intermittent illumination with a white fluorescent lamp. In another direction of research, we verified that the difference in the absorption coefficients for water and ice is significant, and we could discriminate and monitor the frozen state of water and food material. All these experiments demonstrate the possibility of applying millimeter waves to fields such as botany, agriculture, and food industry.

  1. Characteristic features of optical absorption for Gd2O3 and NiO nanoparticles

    NASA Astrophysics Data System (ADS)

    Zatsepin, A. F.; Kuznetsova, Yu. A.; Rychkov, V. N.; Sokolov, V. I.

    2017-03-01

    The technical approach to determination of the structural and optical parameters of oxides with reduced dimensionality based on optical absorption measurements is described by example of gadolinium and nickel oxides. It was established that the temperature behavior of fundamental absorption edge for oxide nanoparticles is similar with the bulk materials with crystal structure. At the same time, the energy characteristics (band gap and effective phonon energies) for low-dimensional oxides are found to be significantly different from their bulk counterparts. The presented methodological method to obtain of qualitative and quantitative correlations of structural and optical characteristics provides novel reliable knowledge of nanoscaled 3d and 4f-metal oxide materials that is useful for development of their practical applications.

  2. Features of Pc5 pulsations in the geomagnetic field, auroral luminosity, and Riometer absorption

    NASA Astrophysics Data System (ADS)

    Belakhovsky, V. B.; Pilipenko, V. A.; Samsonov, S. N.; Lorentsen, D.

    2016-01-01

    Simultaneous morning Pc5 pulsations ( f ~ 3-5 mHz) in the geomagnetic field, aurora intensities (in the 557.7 and 630.0 nm oxygen emissions and the 471.0 nm nitrogen emission), and riometer absorption, were studied based on the CARISMA, CANMOS, and NORSTAR network data for the event of January 1, 2000. According to the GOES-8 satellite observations, these Pc5 geomagnetic pulsations are observed as incompressible Alfvén waves with toroidal polarization in the magnetosphere. Although the Pc5 pulsation frequencies in auroras, the geomagnetic field, and riometer absorption are close to one another, stable phase relationships are not observed between them. Far from all trains of geomagnetic Pc5 pulsations are accompanied by corresponding auroral pulsations; consequently, geomagnetic pulsations are primary with respect to auroral pulsations. Both geomagnetic and auroral pulsations propagate poleward, and the frequency decreases with increasing geomagnetic latitude. When auroral Pc5 pulsations appear, the ratio of the 557.7/630.0 nm emission intensity sharply increases, which indicates that auroral pulsations result from not simply modulated particle precipitation but also an additional periodic acceleration of auroral electrons by the wave field. A high correlation is not observed between Pc5 pulsations in auroras and the riometer absorption, which indicates that these pulsations have a common source but different generation mechanisms. Auroral luminosity modulation is supposedly related to the interaction between Alfvén waves and the region with the field-aligned potential drop above the auroral ionosphere, and riometer absorption modulation is caused by the scattering of energetic electrons by VLF noise pulsations.

  3. Feature-based active contour model and occluding object detection.

    PubMed

    Memar, Sara; Ksantini, Riadh; Boufama, Boubakeur

    2016-04-01

    This paper presents a method for image segmentation and object detection. The proposed strategy consists of two major stages. The first one corresponds to image segmentation, which is based on the active contour model (ACM) algorithm, using an automatic selection of the best candidate features among gradient, polarity, and depth, coupled with a combination of them by the kernel support vector machine (KSVM). Although existing techniques, such as the ones based on ACM, perform well in the single-object case and non-noisy environments, these techniques fail when the scene consists of multiple occluding objects, with possibly similar colors. Thus, the second stage corresponds to the identification of salient and occluded objects based on the fuzzy C-mean algorithm (FCM). In this stage, the depth is included as another clue that allows us to estimate the cluster number and to make the clustering process more robust. In particular, complex occlusions can be handled this way, and the objects can be properly segmented and identified. Experimental results on real images and on several standard datasets have shown the success and effectiveness of the proposed method.

  4. Drowsiness detection during different times of day using multiple features.

    PubMed

    Sahayadhas, Arun; Sundaraj, Kenneth; Murugappan, Murugappan

    2013-06-01

    Driver drowsiness has been one of the major causes of road accidents that lead to severe trauma, such as physical injury, death, and economic loss, which highlights the need to develop a system that can alert drivers of their drowsy state prior to accidents. Researchers have therefore attempted to develop systems that can determine driver drowsiness using the following four measures: (1) subjective ratings from drivers, (2) vehicle-based measures, (3) behavioral measures and (4) physiological measures. In this study, we analyzed the various factors that contribute towards drowsiness. A total of 15 male subjects were asked to drive for 2 h at three different times of the day (00:00-02:00, 03:00-05:00 and 15:00-17:00 h) when the circadian rhythm is low. The less intrusive physiological signal measurements, ECG and EMG, are analyzed during this driving task. Statistically significant differences in the features of ECG and sEMG signals were observed between the alert and drowsy states of the drivers during different times of day. In the future, these physiological measures can be fused with vision-based measures for the development of an efficient drowsiness detection system.

  5. Absorption of human skin and its detecting platform in the process of laser cosmetology

    NASA Astrophysics Data System (ADS)

    Zhang, Yong-Lin; Ouyang, Li; Wang, Yang

    2000-10-01

    Because of the melanin, hemoglobin and water molecules, etc. contained, light absorption of human skin tissue changes with wavelength of light. This is the principle used in laser cosmetology for treating pigment diseases and vascular lesion diseases as well as skin decoration such as body tattooing, eyebrow tattooing, etc. The parameters of treatment used in laser cosmetology principally come from the research of the skin tissue optical characteristics of whites, and it is not suitable for the Oriental. The absorption spectrum of yellow race alive skin has been researched. The detecting platform for use in the measuring of vivi-tissue absorption spectrum has been developed which using opto-electronic nondestructive testing and virtual instrument techniques. The degree of pathological changes of skin can be detected by this platform also, thus the shortcoming of dosage selection in laser clinical treatments which have been decided only by naked eye observation and past experience of doctors can be solved.

  6. Automated colon cancer detection using hybrid of novel geometric features and some traditional features.

    PubMed

    Rathore, Saima; Hussain, Mutawarra; Khan, Asifullah

    2015-10-01

    Automatic classification of colon into normal and malignant classes is complex due to numerous factors including similar colors in different biological constituents of histopathological imagery. Therefore, such techniques, which exploit the textural and geometric properties of constituents of colon tissues, are desired. In this paper, a novel feature extraction strategy that mathematically models the geometric characteristics of constituents of colon tissues is proposed. In this study, we also show that the hybrid feature space encompassing diverse knowledge about the tissues׳ characteristics is quite promising for classification of colon biopsy images. This paper thus presents a hybrid feature space based colon classification (HFS-CC) technique, which utilizes hybrid features for differentiating normal and malignant colon samples. The hybrid feature space is formed to provide the classifier different types of discriminative features such as features having rich information about geometric structure and image texture. Along with the proposed geometric features, a few conventional features such as morphological, texture, scale invariant feature transform (SIFT), and elliptic Fourier descriptors (EFDs) are also used to develop a hybrid feature set. The SIFT features are reduced using minimum redundancy and maximum relevancy (mRMR). Various kernels of support vector machines (SVM) are employed as classifiers, and their performance is analyzed on 174 colon biopsy images. The proposed geometric features have achieved an accuracy of 92.62%, thereby showing their effectiveness. Moreover, the proposed HFS-CC technique achieves 98.07% testing and 99.18% training accuracy. The better performance of HFS-CC is largely due to the discerning ability of the proposed geometric features and the developed hybrid feature space.

  7. Wavelength calibration techniques and subtle surface and atmospheric absorption features in the Mariner 6, 7 IRS reflectance data

    NASA Technical Reports Server (NTRS)

    Bell, James F., III; Roush, T. L.; Martin, T. Z.; Pollack, James B.; Freedman, R.

    1994-01-01

    1994 marks the 25th anniversary of the Mariner 6 and 7 flyby missions to Mars. Despite its age, the Mariner 6,7 Infrared Spectrometer (IRS) data are a unique set of measurements that can provide important information about the Martian surface, atmospheric, and atmospheric aerosol composition. For certain mid-IR wavelengths, the IRS spectra are the only such spacecraft data obtained for Mars. At other wavelengths, IRS measured surface regions different from those measured by Mariner 9 or Phobos 2 and under different dust opacity conditions. We are interested in examining the IRS reflectance data in the 1.8 to 3.0 micron region because there are numerous diagnostic absorption features at these wavelengths that could be indicative of hydrated silicate minerals or of carbonate- or sulfate-bearing minerals. Groundbased telescopic data and recent Phobos ISM measurements have provided controversial and somewhat contradictory evidence for the existence of mineralogic absorption features at these wavelengths. Our goal is to determine whether any such features can be seen in the IRS data and to use their presence or absence to re-assess the quality and interpretations of previous telescopic and spacecraft measurements.

  8. Portable 4.6 Micrometers Laser Absorption Spectrometer for Carbon Monoxide Monitoring and Fire Detection

    NASA Technical Reports Server (NTRS)

    Briggs, Ryan M.; Frez, Clifford; Forouhar, Siamak; May, Randy D.; Ruff, Gary A.

    2013-01-01

    The air quality aboard manned spacecraft must be continuously monitored to ensure crew safety and identify equipment malfunctions. In particular, accurate real-time monitoring of carbon monoxide (CO) levels helps to prevent chronic exposure and can also provide early detection of combustion-related hazards. For long-duration missions, environmental monitoring grows in importance, but the mass and volume of monitoring instruments must be minimized. Furthermore, environmental analysis beyond low-Earth orbit must be performed in-situ, as sample return becomes impractical. Due to their small size, low power draw, and performance reliability, semiconductor-laser-based absorption spectrometers are viable candidates for this purpose. To reduce instrument form factor and complexity, the emission wavelength of the laser source should coincide with strong fundamental absorption lines of the target gases, which occur in the 3 to 5 micrometers wavelength range for most combustion products of interest, thereby reducing the absorption path length required for low-level concentration measurements. To address the needs of current and future NASA missions, we have developed a prototype absorption spectrometer using a semiconductor quantum cascade laser source operating near 4.6 micrometers that can be used to detect low concentrations of CO with a compact single-pass absorption cell. In this study, we present the design of the prototype instrument and report on measurements of CO emissions from the combustion of a variety of aerospace plastics.

  9. Mapping vegetation types with the multiple spectral feature mapping algorithm in both emission and absorption

    NASA Technical Reports Server (NTRS)

    Clark, Roger N.; Swayze, Gregg A.; Koch, Christopher; Ager, Cathy

    1992-01-01

    Vegetation covers a large portion of the Earth's land surface. Remotely sensing quantitative information from vegetation has proven difficult because in a broad sense, all vegetation is similar from a chemical viewpoint, and most healthy plants are green. Plant species are generally characterized by the leaf and flower or fruit morphology, not by remote sensing spectral signatures. But to the human eye, many plants show varying shades of green, so there is direct evidence for spectral differences between plant types. Quantifying these changes in a predictable manner has not been easy. The Clark spectral features mapping algorithm was applied to mapping spectral features in vegetation species.

  10. Non-degenerate two photon absorption enhancement for laser dyes by precise lock-in detection

    SciTech Connect

    Xue, B.; Katan, C.; Bjorgaard, J. A.; Kobayashi, T.

    2015-12-15

    This study demonstrates a measurement system for a non-degenerate two-photon absorption (NDTPA) spectrum. The NDTPA light sources are a white light super continuum beam (WLSC, 500 ∼ 720 nm) and a fundamental beam (798 nm) from a Ti:Sapphire laser. A reliable broadband NDTPA spectrum is acquired in a single-shot detection procedure using a 128-channel lock-in amplifier. The NDTPA spectra for several common laser dyes are measured. Two photon absorption cross section enhancements are found in the experiment and validated by theoretical calculation for all of the chromophores.

  11. Detection of Ne VIII in an Intervening Multiphase Absorption System Toward 3C 263

    NASA Astrophysics Data System (ADS)

    Narayanan, Anand; Wakker, Bart P.; Savage, Blair D.

    2009-09-01

    We report the detection of Ne VIII in an intervening multiphase absorption line system at z = 0.32566 in the Far Ultraviolet Spectroscopic Explorer spectrum of the quasar 3C 263 (zem = 0.646). The Ne VIII λ770 Å detection has a 3.9σ significance. At the same velocity, we also find absorption lines from C IV, O III, O IV, and N IV. The line parameter measurements yield log [N(Ne VIII) cm-2] = 13.98+0.10 -0.13 and b = 49.8 ± 5.5 km s-1. We find that the ionization mechanism in the gas phase giving rise to the Ne VIII absorption is inconsistent with photoionization. The absorber has a multiphase structure, with the intermediate ions produced in cool photoionized gas and the Ne VIII most likely in a warm collisionally ionized medium in the temperature range (0.5-1.0) × 106 K. This is the second ever detection of an intervening Ne VIII absorption system. Its properties resemble the previous Ne VIII absorber reported by Savage and colleagues. Direct observations of H I and O VI are needed to better constrain the physical conditions in the collisionally ionized gas phase of this absorber. Based on observations with the NASA-CNES-CSA Far Ultraviolet Spectroscopic Explorer operated by Johns Hopkins University, supported by NASA contract NAS5-32985.

  12. Standard addition/absorption detection microfluidic system for salt error-free nitrite determination.

    PubMed

    Ahn, Jae-Hoon; Jo, Kyoung Ho; Hahn, Jong Hoon

    2015-07-30

    A continuous-flow microfluidic chip-based standard addition/absorption detection system has been developed for accurate determination of nitrite in water of varying salinity. The absorption detection of nitrite is made via color development using the Griess reaction. We have found the yield of the reaction is significantly affected by salinity (e.g., -12% error for 30‰ NaCl, 50.0 μg L(-1)N-NO2(-) solution). The microchip has been designed to perform standard addition, color development, and absorbance detection in sequence. To effectively block stray light, the microchip made from black poly(dimethylsiloxane) is placed on the top of a compact housing that accommodates a light-emitting diode, a photomultiplier tube, and an interference filter, where the light source and the detector are optically isolated. An 80-mm liquid-core waveguide mounted on the chip externally has been employed as the absorption detection flow cell. These designs for optics secure a wide linear response range (up to 500 μg L(-1)N-NO2(-)) and a low detection limit (0.12 μg L(-1)N-NO2(-) = 8.6 nM N-NO2(-), S/N = 3). From determination of nitrite in standard samples and real samples collected from an estuary, it has been demonstrated that our microfluidic system is highly accurate (<1% RSD, n = 3) and precise (<1% RSD, n = 3).

  13. Reconfiguration of spectral absorption features using a frequency-chirped laser pulse.

    PubMed

    Tian, Mingzhen; Chang, Tiejun; Merkel, Kristian D; Babbitt, W Randall

    2011-12-20

    A technique is proposed to manipulate atomic population in an inhomogeneously broadened medium, which can set an arbitrary absorption spectrum to a uniform transparency (erasure) or to a nearly complete inversion. These reconfigurations of atomic spectral distribution are achieved through excitation of electronic transitions using a laser pulse with chirped frequency, which precisely affects selected spectral regions while leaving the rest of the spectrum unperturbed. An erasure operation sets the final atomic population inversion to zero and the inversion operation flips the population between the ground and the excited states, regardless of the previously existing population distribution. This technique finds important applications both in optical signal processing, where fast, recursive processing and high dynamic range are desirable and in quantum memory and quantum computing, which both require high efficiency and high fidelity in quantum state preparation of atomic ensembles. Proof-of-concept demonstrations were performed in a rare-earth doped crystal.

  14. Structural, thermal and optical absorption features of heavy metal oxides doped tellurite rich glasses

    NASA Astrophysics Data System (ADS)

    Kaky, Kawa M.; Lakshminarayana, G.; Baki, S. O.; Kityk, I. V.; Taufiq-Yap, Y. H.; Mahdi, M. A.

    In order to improve tellurite glass stability to be applicable for optical fiber amplifier applications, glasses with the composition of (70 - x)TeO2. (10)ZnO. (10)WO3. (5)Na2O. (5)TiO2. (x)Bi2O3 (x = 1, 2, 3, 4, and 5 mol%) have been produced and characterized using the related methods. Structural properties were investigated using X-ray diffraction (XRD) which confirms the non-crystalline structure and scanning electron microscopy (SEM) micrographs also confirm the XRD results. The energy dispersive X-ray (EDX) analysis profiles show that all the mentioned elements are present in the prepared glasses. Following the IR spectra, all the tellurium bonds such as stretching vibrations of TeO4 tbp and TeO3/TeO3+1 unit are revealed. Raman spectra confirm the presence of different functional groups, actually, it shows bands mainly in four spectral regions: R1 (65-150) cm-1, R2 (280-550) cm-1, R3 (880-950) cm-1 and R4 (916-926) cm-1 and the identified bands are assigned to respective molecular groups. The thermal study was carried out using Differential scanning calorimetry (DSC) which indicates good thermal stability of the synthesized glasses with increasing Bi concentration. From the optical absorption spectra, we evaluated cut-off edge wavelengths and found increasing cutoff wavelength with an increase in Bi2O3 concentration. In the UV-Visible region, optical band gap energy and allowed transitions were investigated using three methods; direct, indirect, and absorption spectrum fitting (ASF), and band gaps from indirect and ASF were matched.

  15. Magnetic feature and near-infrared absorption of a [Pt(mnt)2]--based H-bond supramolecular crystal

    NASA Astrophysics Data System (ADS)

    Li, Cui-Ping; Nie, Li; Pei, Wen-Bo; Li, Li; Tian, Zheng-Fang; Liu, Jian-Lan; Gao, Xu-Sheng; Ren, Xiao-Ming

    2016-11-01

    A new salt [H2DABCO][Pt(mnt)2]2 (1) (mnt2-=maleonitriledithiolate and H2DABCO2+ is diprotonated 1,4-diazabicyclo[2.2.2]octane) has been synthesized; its crystal structure, magnetic and near-IR absorption properties have been investigated. Two different [Pt(mnt)2]- anions form the strong π-dimers, labeled as Pt(1)-dimer and Pt(2)-dimer, with quite shorter Pt…Pt and S…S distances and molecular plane-to-plane distance (<3.5 Å) within a dimer. The [Pt(mnt)2]22- π-dimers are connected through the cations in the strong H-bond manner to form three-dimensional H-bond supramolecular crystal. The salt shows weak paramagnetism in 1.99-300 K and this is due to the existence of strong antiferromagnetic coupling within a π-dimer. In addition, a small thermal hysteresis loop is observed at ca. 120 K, indicating that a phase transition probably occurs that is further confirmed by variable-temperature IR spectra. Another fascinating functionality of 1 is the intense near-IR absorption in the region of 750-2500 nm, and this near-IR absorption feature makes it to be a promising optical material.

  16. Automated extraction of absorption features from Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and Geophysical and Environmental Research Imaging Spectrometer (GERIS) data

    NASA Technical Reports Server (NTRS)

    Kruse, Fred A.; Calvin, Wendy M.; Seznec, Olivier

    1988-01-01

    Automated techniques were developed for the extraction and characterization of absorption features from reflectance spectra. The absorption feature extraction algorithms were successfully tested on laboratory, field, and aircraft imaging spectrometer data. A suite of laboratory spectra of the most common minerals was analyzed and absorption band characteristics tabulated. A prototype expert system was designed, implemented, and successfully tested to allow identification of minerals based on the extracted absorption band characteristics. AVIRIS spectra for a site in the northern Grapevine Mountains, Nevada, have been characterized and the minerals sericite (fine grained muscovite) and dolomite were identified. The minerals kaolinite, alunite, and buddingtonite were identified and mapped for a site at Cuprite, Nevada, using the feature extraction algorithms on the new Geophysical and Environmental Research 64 channel imaging spectrometer (GERIS) data. The feature extraction routines (written in FORTRAN and C) were interfaced to the expert system (written in PROLOG) to allow both efficient processing of numerical data and logical spectrum analysis.

  17. Wavelet Based Feature Extraction for Target Recognition and Minefield Detection

    DTIC Science & Technology

    2007-11-02

    with Ron Gross (NSWC); presentation of course "Wavelets and Filter Banks " to NSWC personnel; application of simulated annealing to optimize RF absorption...characteristics of multilayer surfaces; generalization of wavelet transform to M-band wavelets; algorithm to generate a wavelet filter bank using any...filter whatsoever as the analysis filter; implementation of an algorithm to parameterize all M-band paraunitary filter banks .

  18. Selective detection of linear features in geological remote sensing data

    NASA Astrophysics Data System (ADS)

    Parikh, Jo Ann; DaPonte, John S.; DiNicola, Emily G.; Pedersen, Robert A.

    1992-09-01

    One of the major problems in the development of computer-assisted systems for geologic mapping is how to individualize the system to meet user needs. Ideally, the system should be responsive to specifications of desired types of output structures. Also, the system should be able to incorporate the user's knowledge of regional characteristics into the feature extraction/selection and classification components. Automatic techniques for classification of remote sensing data typically require relatively large, labeled training sets which are well- organized with respect to the desired mapping between input and output patterns. The present paper focuses on the feature extraction/selection component of the system. Kohonen self- organizing feature maps in conjunction with image processing procedures for linear feature extraction are used for explorative data analysis, feature selection, and construction of exemplar patterns. The results of training Kohonen feature maps with different pattern sets and different feature combinations provide insight into the nature of pattern relationships which enables the user to develop sets of positive and negative training patterns for the classification component.

  19. THE 217.5 nm BAND, INFRARED ABSORPTION, AND INFRARED EMISSION FEATURES IN HYDROGENATED AMORPHOUS CARBON NANOPARTICLES

    SciTech Connect

    Duley, W. W.; Hu, Anming E-mail: a2hu@uwaterloo.ca

    2012-12-20

    We report on the preparation of hydrogenated amorphous carbon nanoparticles whose spectral characteristics include an absorption band at 217.5 nm with the profile and characteristics of the interstellar 217.5 nm feature. Vibrational spectra of these particles also contain the features commonly observed in absorption and emission from dust in the diffuse interstellar medium. These materials are produced under ''slow'' deposition conditions by minimizing the flux of incident carbon atoms and by reducing surface mobility. The initial chemistry leads to the formation of carbon chains, together with a limited range of small aromatic ring molecules, and eventually results in carbon nanoparticles having an sp {sup 2}/sp {sup 3} ratio Almost-Equal-To 0.4. Spectroscopic analysis of particle composition indicates that naphthalene and naphthalene derivatives are important constituents of this material. We suggest that carbon nanoparticles with similar composition are responsible for the appearance of the interstellar 217.5 nm band and outline how these particles can form in situ under diffuse cloud conditions by deposition of carbon on the surface of silicate grains. Spectral data from carbon nanoparticles formed under these conditions accurately reproduce IR emission spectra from a number of Galactic sources. We provide the first detailed fits to observational spectra of Type A and B emission sources based entirely on measured spectra of a carbonaceous material that can be produced in the laboratory.

  20. Evidence for cyclotron absorption from spectral features in gamma-ray bursts seen with Ginga

    NASA Technical Reports Server (NTRS)

    Murakami, T.; Fujii, M.; Hayashida, K.; Itoh, M.; Nishimura, J.

    1988-01-01

    New observations by the gamma-ray burst detector on board the Ginga satellite, which has two well-calibrated detectors covering a wide energy range of 1.5 to 375 keV, are reported. The spectral features obtained are consistent with first and second cyclotron harmonics. This finding is taken as strong evidence for the magnetized neutron star model of gamma-ray bursts.

  1. Feature Detection, Characterization and Confirmation Methodology: Final Report

    SciTech Connect

    Karasaki, Kenzi; Apps, John; Doughty, Christine; Gwatney, Hope; Onishi, Celia Tiemi; Trautz, Robert; Tsang, Chin-Fu

    2007-03-01

    This is the final report of the NUMO-LBNL collaborative project: Feature Detection, Characterization and Confirmation Methodology under NUMO-DOE/LBNL collaboration agreement, the task description of which can be found in the Appendix. We examine site characterization projects from several sites in the world. The list includes Yucca Mountain in the USA, Tono and Horonobe in Japan, AECL in Canada, sites in Sweden, and Olkiluoto in Finland. We identify important geologic features and parameters common to most (or all) sites to provide useful information for future repository siting activity. At first glance, one could question whether there was any commonality among the sites, which are in different rock types at different locations. For example, the planned Yucca Mountain site is a dry repository in unsaturated tuff, whereas the Swedish sites are situated in saturated granite. However, the study concludes that indeed there are a number of important common features and parameters among all the sites--namely, (1) fault properties, (2) fracture-matrix interaction (3) groundwater flux, (4) boundary conditions, and (5) the permeability and porosity of the materials. We list the lessons learned from the Yucca Mountain Project and other site characterization programs. Most programs have by and large been quite successful. Nonetheless, there are definitely 'should-haves' and 'could-haves', or lessons to be learned, in all these programs. Although each site characterization program has some unique aspects, we believe that these crosscutting lessons can be very useful for future site investigations to be conducted in Japan. One of the most common lessons learned is that a repository program should allow for flexibility, in both schedule and approach. We examine field investigation technologies used to collect site characterization data in the field. An extensive list of existing field technologies is presented, with some discussion on usage and limitations. Many of the

  2. Investigation of kinematic features for dismount detection and tracking

    NASA Astrophysics Data System (ADS)

    Narayanaswami, Ranga; Tyurina, Anastasia; Diel, David; Mehra, Raman K.; Chinn, Janice M.

    2012-05-01

    With recent changes in threats and methods of warfighting and the use of unmanned aircrafts, ISR (Intelligence, Surveillance and Reconnaissance) activities have become critical to the military's efforts to maintain situational awareness and neutralize the enemy's activities. The identification and tracking of dismounts from surveillance video is an important step in this direction. Our approach combines advanced ultra fast registration techniques to identify moving objects with a classification algorithm based on both static and kinematic features of the objects. Our objective was to push the acceptable resolution beyond the capability of industry standard feature extraction methods such as SIFT (Scale Invariant Feature Transform) based features and inspired by it, SURF (Speeded-Up Robust Feature). Both of these methods utilize single frame images. We exploited the temporal component of the video signal to develop kinematic features. Of particular interest were the easily distinguishable frequencies characteristic of bipedal human versus quadrupedal animal motion. We examine limits of performance, frame rates and resolution required for human, animal and vehicles discrimination. A few seconds of video signal with the acceptable frame rate allow us to lower resolution requirements for individual frames as much as by a factor of five, which translates into the corresponding increase of the acceptable standoff distance between the sensor and the object of interest.

  3. Deep imaging of absorption and scattering features by multispectral multiple scattering low coherence interferometry

    PubMed Central

    Zhao, Yang; Maher, Jason R.; Ibrahim, Mohamed M.; Chien, Jennifer S.; Levinson, Howard; Wax, Adam

    2016-01-01

    We have developed frequency domain multispectral multiple scattering low coherence interferometry (ms2/LCI) for deep imaging of absorption and scattering contrast. Using tissue-mimicking phantoms that match the full scattering phase function of human dermal tissue, we demonstrate that ms2/LCI can provide a signal/noise ratio (SNR) improvement of 15.4 dB over conventional OCT at an imaging depth of 1 mm. The enhanced SNR and penetration depth provided by ms2/LCI could be leveraged for a variety of clinical applications including the assessment of burn injuries where current clinical classification of severity only provides limited accuracy. The utility of the approach was demonstrated by imaging a tissue phantom simulating a partial-thickness burn revealing good spectroscopic contrast between healthy and injured tissue regions deep below the sample surface. Finally, healthy rat skin was imaged in vivo with both a commercial OCT instrument and our custom ms2/LCI system. The results demonstrate that ms2/LCI is capable of obtaining spectroscopic information far beyond the penetration depth provided by conventional OCT. PMID:27867703

  4. Automated feature detection and identification in digital point-ordered signals

    DOEpatents

    Oppenlander, Jane E.; Loomis, Kent C.; Brudnoy, David M.; Levy, Arthur J.

    1998-01-01

    A computer-based automated method to detect and identify features in digital point-ordered signals. The method is used for processing of non-destructive test signals, such as eddy current signals obtained from calibration standards. The signals are first automatically processed to remove noise and to determine a baseline. Next, features are detected in the signals using mathematical morphology filters. Finally, verification of the features is made using an expert system of pattern recognition methods and geometric criteria. The method has the advantage that standard features can be, located without prior knowledge of the number or sequence of the features. Further advantages are that standard features can be differentiated from irrelevant signal features such as noise, and detected features are automatically verified by parameters extracted from the signals. The method proceeds fully automatically without initial operator set-up and without subjective operator feature judgement.

  5. Mid and Near-IR Absorption Spectra of PAH Neutrals and Ions in H20 Ice to Facilitate their Astronomical Detection

    NASA Technical Reports Server (NTRS)

    Bernstein, Max P.; Sandford, Scott A.; Allamandola, Louis J.

    2004-01-01

    Polycyclic aromatic hydrocarbons (PAHs) are believed to be the most abundant and widespread class of organic compounds in the universe, having been observed in emission towards energetic regions and absorption towards colder ones.We will present IR spectra of PAHs and their cations in H20 ice measured in the laboratory in the hopes that this will facilitate the detection of these features in the interstellar medium.

  6. Unsupervised Spectral-Spatial Feature Selection-Based Camouflaged Object Detection Using VNIR Hyperspectral Camera

    PubMed Central

    2015-01-01

    The detection of camouflaged objects is important for industrial inspection, medical diagnoses, and military applications. Conventional supervised learning methods for hyperspectral images can be a feasible solution. Such approaches, however, require a priori information of a camouflaged object and background. This letter proposes a fully autonomous feature selection and camouflaged object detection method based on the online analysis of spectral and spatial features. The statistical distance metric can generate candidate feature bands and further analysis of the entropy-based spatial grouping property can trim the useless feature bands. Camouflaged objects can be detected better with less computational complexity by optical spectral-spatial feature analysis. PMID:25879073

  7. Detection of Lyman continuum absorption in the BL Lacertae object PKS 0735+178

    NASA Technical Reports Server (NTRS)

    Bregman, J. N.; Glassgold, A. E.; Huggins, P. J.

    1981-01-01

    The detection of the Lyman edge in the BL Lac object PKS 0735+178 at the absorption red shift determined by optical measurements leads to a lower limit for the column density of atomic hydrogen, N(H I) not less than 4(17)/sq cm. The Lyman-alpha absorption line appears to have been detected, but only an approximate upper limit can be obtained from the data, of the order of 2(19)/sq cm. This amount of atomic hydrogen is less than that for a line of sight through the disk of a normal spiral galaxy. It is suggested that the absorbing material exists either in the halo of a galaxy or in the tenuous, extended, gaseous disk of a galaxy.

  8. Far-IR Absorption Features of Titan Aerosol Analogs Produced from Aromatic Precursors

    NASA Astrophysics Data System (ADS)

    Sebree, Joshua; Trainer, M. G.; Anderson, C. M.; Loeffler, M. J.

    2012-10-01

    The arrival of the Cassini spacecraft in orbit around Saturn has led to the discovery of benzene (C6H6) at ppm levels, as well as large positive ions in Titan’s atmosphere, tentatively identified as polycyclic aromatic hydrocarbons (PAHs).[1] The presence of aromatic molecules, which are photolytically active in the ultraviolet, may be an important part of the formation of aerosol particles in Titan’s haze layers, even at these low concentrations. To date, there have been no laboratory experiments in the literature exploring this area of study. The analysis of data from the Composite Infrared Spectrometer (CIRS) on-board Cassini has recently uncovered a broad emission feature centered at 140 cm-1 in the far-IR that is unique to the aerosol layers of Titan’s atmosphere.[2] Current optical constants from laboratory-generated aerosol analogs have been unable to reproduce this feature.[3,4] From the broadness of this feature, we speculate that the emission is a blended composite of low-energy vibrations of large molecules such as PAHs and their nitrogen containing counterparts, polycyclic aromatic nitrogen heterocycles (PANHs). We hypothesize that the inclusion of trace amounts of aromatic precursors will aid in the production of these large structures in the laboratory-generated aerosols. In this study, we perform UV irradiation of several aromatic precursors, both with and without nitrogen heteroatoms, to understand their influence on the observable characteristics of the aerosol. Measured optical and chemical properties will be compared to those formed from CH4/N2 mixtures [5,6] as well as to those from Cassini observations. [1] Waite, J. H., et al. (2007) Science 316 870-875. [2] Anderson, C.M, et al. (2011) Icarus 212 762-778. [3] Khare, B.N., et al. (1984) Icarus 60 127-137. [4] Imanaka, H., et al. (2012) Icarus 218 247-261. [5] Trainer, M.G., et al. (2006) PNAS 103 18035-18042. [6] Trainer, M.G., et al. (2012) Astrobiology 12 315-326.

  9. Ultraviolet Broad Absorption Features and the Spectral Energy Distribution of the QSO PG 1351+641. 2.5

    NASA Technical Reports Server (NTRS)

    Zheng, W.; Kriss, G. A.; Wang, J. X.; Brotherton, M.; Oegerle, W. R.; Blair, W. P.; Davidsen, A. F.; Green, R. F.; Hutchings, J. B.; Kaiser, M. E.; Fisher, Richard R. (Technical Monitor)

    2001-01-01

    We present a moderate-resolution (approximately 20 km/s) spectrum of the broad-absorption line QSO PG 1351+64 between 915-1180 angstroms, obtained with the Far Ultraviolet Spectroscopic Explorer (FUSE). Additional low-resolution spectra at longer wavelengths were also obtained with the Hubble Space Telescope (HST) and ground-based telescopes. Broad absorption is present on the blue wings of C III lambda977, Ly-beta, O VI lambda-lambda-1032,1038, Ly-alpha, N V lambda-lambda-1238,1242, Si IV lambda-lambda-1393,1402, and C IV lambda-lambda-1548,1450. The absorption profile can be fitted with five components at velocities of approximately -780, -1049, -1629, -1833, and -3054 km/s with respect to the emission-line redshift of z = 0.088. All the absorption components cover a large fraction of the continuum source as well as the broad-line region. The O VI emission feature is very weak, and the O VI/Ly-alpha flux ratio is 0.08, one of the lowest among low-redshift active galaxies and QSOs. The ultraviolet continuum shows a significant change in slope near 1050 angstroms in the restframe. The steeper continuum shortward of the Lyman limit extrapolates well to the observed weak X-ray flux level. The absorbers' properties are similar to those of high-redshift broad absorption-line QSOs. The derived total column density of the UV absorbers is on the order of 10(exp 21)/s, unlikely to produce significant opacity above 1 keV in the X-ray. Unless there is a separate, high-ionization X-ray absorber, the QSO's weak X-ray flux may be intrinsic. The ionization level of the absorbing components is comparable to that anticipated in the broad-line region, therefore the absorbers may be related to broad-line clouds along the line of sight.

  10. Ultraviolet Broad Absorption Features and the Spectral Energy Distribution of the QSO PG 1351+64. 3.1

    NASA Technical Reports Server (NTRS)

    Zheng, W.; Kriss, G. A.; Wang, J. X.; Brotherton, M.; Oegerle, W. R.; Blair, W. P.; Davidsen, A. F.; Green, R. F.; Hutchings, J. B.; Kaiser, M. E.; Fisher, R. (Technical Monitor)

    2001-01-01

    We present a moderate-resolution (approximately 20 km s(exp -1) spectrum of the mini broad absorption line QSO PG 1351+64 between 915-1180 A, obtained with the Far Ultraviolet Spectroscopic Explorer (FUSE). Additional low-resolution spectra at longer wavelengths were also obtained with the Hubble Space Telescope (HST) and ground-based telescopes. Broad absorption is present on the blue wings of C III (lambda)977, Ly(beta), O VI (lambda)(lambda)1032,1038, Ly(alpha), N V (lambda)(lambda)1238,1242, Si IV (lambda)(lambda)1393,1402, and C IV (lambda)(lambda)1548,1450. The absorption profile can be fitted with five components at velocities of approximately -780, -1049, -1629, -1833, and -3054 km s(exp -1) with respect to the emission-line redshift of z = 0.088. All the absorption components cover a large fraction of the continuum source as well as the broad-line region. The O VI emission feature is very weak, and the O VI/Ly(alpha) flux ratio is 0.08, one of the lowest among low-redshift active galaxies and QSOs. The UV (ultraviolet) continuum shows a significant change in slope near 1050 A in the restframe. The steeper continuum shortward of the Lyman limit extrapolates well to the observed weak X-ray flux level. The absorbers' properties are similar to those of high-redshift broad absorption-line QSOs. The derived total column density of the UV absorbers is on the order of 10(exp 21) cm(exp -2), unlikely to produce significant opacity above 1 keV in the X-ray. Unless there is a separate, high-ionization X-ray absorber, the QSO's weak X-ray flux may be intrinsic. The ionization level of the absorbing components is comparable to that anticipated in the broad-line region, therefore the absorbers may be related to broad-line clouds along the line of sight.

  11. The Features of the Frequency-Modulation Method When Studying the Shapes of the Spectral Lines of Nonlinear Absorption

    NASA Astrophysics Data System (ADS)

    Golubiatnikov, G. Yu.; Belov, S. P.; Lapinov, A. V.

    2017-01-01

    We briefly consider the method of the frequency (phase) modulation and signal detection at the second harmonic of the modulation frequency for recording and analyzing the spectral-line shapes. The precision sub-Doppler spectrometer in the millimeter- and submillimeter-wave ranges, which operated in the regime of nonlinear saturation of the spectral transitions in a standing wave (the Lamb-dip method), was used during the measurements. The influence of the saturation degree on the value and shape of the recorded frequency-modulated signals in the quadrature channels during the synchronous detection is demonstrated. Variation in the relationships among the signals determined by dispersion and absorption was observed. The necessity of allowance for the influence of the group-velocity dispersion and coherent effects on the shape of the recorded spectral lines is experimentally shown.

  12. Self-calibration wavelength modulation spectroscopy for acetylene detection based on tunable diode laser absorption spectroscopy

    NASA Astrophysics Data System (ADS)

    Huang, Qin-Bin; Xu, Xue-Mei; Li, Chen-Jing; Ding, Yi-Peng; Cao, Can; Yin, Lin-Zi; Ding, Jia-Feng

    2016-11-01

    The expressions of the second harmonic (2f) signal are derived on the basis of absorption spectral and lock-in theories. A parametric study indicates that the phase shift between the intensity and wavelength modulation makes a great contribution to the 2f signal. A self-calibration wavelength modulation spectroscopy (WMS) method based on tunable diode laser absorption spectroscopy (TDLAS) is applied, combining the advantages of ambient pressure, temperature suppression, and phase-shift influences elimination. Species concentration is retrieved simultaneously from selected 2f signal pairs of measured and reference WMS-2f spectra. The absorption line of acetylene (C2H2) at 1530.36 nm near-infrared is selected to detect C2H2 concentrations in the range of 0-400 ppmv. System sensitivity, detection precision and limit are markedly improved, demonstrating that the self-calibration method has better detecting performance than the conventional WMS. Project supported by the National Natural Science Foundation of China (Grant Nos. 61172047, 61502538, and 61501525).

  13. Detection of water vapour absorption around 363nm in measured atmospheric absorption spectra and its effect on DOAS evaluations

    NASA Astrophysics Data System (ADS)

    Lampel, Johannes; Polyansky, Oleg. L.; Kyuberis, Alexandra A.; Zobov, Nikolai F.; Tennyson, Jonathan; Lodi, Lorenzo; Pöhler, Denis; Frieß, Udo; Platt, Ulrich; Beirle, Steffen; Wagner, Thomas

    2016-04-01

    Water vapour is known to absorb light from the microwave region to the blue part of the visible spectrum at a decreasing magnitude. Ab-initio approaches to model individual absorption lines of the gaseous water molecule predict absorption lines until its dissociation limit at 243 nm. We present first evidence of water vapour absorption at 363 nm from field measurements based on the POKAZATEL absorption line list by Polyansky et al. (2016) using data from Multi-Axis differential optical absorption spectroscopy (MAX-DOAS) and Longpath (LP)-DOAS measurements. The predicted absorptions contribute significantly to the observed optical depths with up to 2 × 10-3. Their magnitude correlates well (R2 = 0.89) to simultaneously measured well-established water vapour absorptions in the blue spectral range from 452-499 nm, but is underestimated by a factor of 2.6 ± 0.6 in the ab-initio model. At a spectral resolution of 0.5nm this leads to a maximum absorption cross-section value of 5.4 × 10-27 cm2/molec at 362.3nm. The results are independent of the employed cross-section data to compensate for the overlayed absorption of the oxygen dimer O4. The newly found absorption can have a significant impact on the spectral retrieval of absorbing trace-gas species in the spectral range around 363 nm. Its effect on the spectral analysis of O4, HONO and OClO are discussed.

  14. Detection of hypertensive retinopathy using vessel measurements and textural features.

    PubMed

    Agurto, Carla; Joshi, Vinayak; Nemeth, Sheila; Soliz, Peter; Barriga, Simon

    2014-01-01

    Features that indicate hypertensive retinopathy have been well described in the medical literature. This paper presents a new system to automatically classify subjects with hypertensive retinopathy (HR) using digital color fundus images. Our method consists of the following steps: 1) normalization and enhancement of the image; 2) determination of regions of interest based on automatic location of the optic disc; 3) segmentation of the retinal vasculature and measurement of vessel width and tortuosity; 4) extraction of color features; 5) classification of vessel segments as arteries or veins; 6) calculation of artery-vein ratios using the six widest (major) vessels for each category; 7) calculation of mean red intensity and saturation values for all arteries; 8) calculation of amplitude-modulation frequency-modulation (AM-FM) features for entire image; and 9) classification of features into HR and non-HR using linear regression. This approach was tested on 74 digital color fundus photographs taken with TOPCON and CANON retinal cameras using leave-one out cross validation. An area under the ROC curve (AUC) of 0.84 was achieved with sensitivity and specificity of 90% and 67%, respectively.

  15. Detection of Abnormal Events via Optical Flow Feature Analysis

    PubMed Central

    Wang, Tian; Snoussi, Hichem

    2015-01-01

    In this paper, a novel algorithm is proposed to detect abnormal events in video streams. The algorithm is based on the histogram of the optical flow orientation descriptor and the classification method. The details of the histogram of the optical flow orientation descriptor are illustrated for describing movement information of the global video frame or foreground frame. By combining one-class support vector machine and kernel principal component analysis methods, the abnormal events in the current frame can be detected after a learning period characterizing normal behaviors. The difference abnormal detection results are analyzed and explained. The proposed detection method is tested on benchmark datasets, then the experimental results show the effectiveness of the algorithm. PMID:25811227

  16. Wavelength modulation spectroscopy--digital detection of gas absorption harmonics based on Fourier analysis.

    PubMed

    Mei, Liang; Svanberg, Sune

    2015-03-20

    This work presents a detailed study of the theoretical aspects of the Fourier analysis method, which has been utilized for gas absorption harmonic detection in wavelength modulation spectroscopy (WMS). The lock-in detection of the harmonic signal is accomplished by studying the phase term of the inverse Fourier transform of the Fourier spectrum that corresponds to the harmonic signal. The mathematics and the corresponding simulation results are given for each procedure when applying the Fourier analysis method. The present work provides a detailed view of the WMS technique when applying the Fourier analysis method.

  17. Spectroscopic determination of leaf biochemistry using band-depth analysis of absorption features and stepwise multiple linear regression

    USGS Publications Warehouse

    Kokaly, R.F.; Clark, R.N.

    1999-01-01

    We develop a new method for estimating the biochemistry of plant material using spectroscopy. Normalized band depths calculated from the continuum-removed reflectance spectra of dried and ground leaves were used to estimate their concentrations of nitrogen, lignin, and cellulose. Stepwise multiple linear regression was used to select wavelengths in the broad absorption features centered at 1.73 ??m, 2.10 ??m, and 2.30 ??m that were highly correlated with the chemistry of samples from eastern U.S. forests. Band depths of absorption features at these wavelengths were found to also be highly correlated with the chemistry of four other sites. A subset of data from the eastern U.S. forest sites was used to derive linear equations that were applied to the remaining data to successfully estimate their nitrogen, lignin, and cellulose concentrations. Correlations were highest for nitrogen (R2 from 0.75 to 0.94). The consistent results indicate the possibility of establishing a single equation capable of estimating the chemical concentrations in a wide variety of species from the reflectance spectra of dried leaves. The extension of this method to remote sensing was investigated. The effects of leaf water content, sensor signal-to-noise and bandpass, atmospheric effects, and background soil exposure were examined. Leaf water was found to be the greatest challenge to extending this empirical method to the analysis of fresh whole leaves and complete vegetation canopies. The influence of leaf water on reflectance spectra must be removed to within 10%. Other effects were reduced by continuum removal and normalization of band depths. If the effects of leaf water can be compensated for, it might be possible to extend this method to remote sensing data acquired by imaging spectrometers to give estimates of nitrogen, lignin, and cellulose concentrations over large areas for use in ecosystem studies.We develop a new method for estimating the biochemistry of plant material using

  18. Investigation of the mica x-ray absorption near-edge structure spectral features at the Al K-edge

    NASA Astrophysics Data System (ADS)

    Wu, Ziyu; Marcelli, A.; Cibin, G.; Mottana, A.; Della Ventura, G.

    2003-10-01

    Near-edge features of Al x-ray absorption near-edge structure (XANES) spectra in aluminosilicate compounds with mixed coordination number are usually assigned to a fourfold coordinated site contribution followed by a sixfold coordinated site contribution that is displaced towards higher energy because of the increasing ligand nucleus potentials, neglecting possible contributions due to bond distance variations and local geometrical distortion. Here we present and discuss the Al K-edge XANES spectra of synthetic micas with either fourfold coordinated Al (phlogopite), or with sixfold coordinated Al (polylithionite), as well as with mixed coordination (preiswerkite). Multiple scattering simulations of XANES spectra demonstrate that octahedral contributions may overlap the tetrahedral ones so that the lower energy structures in mixed coordination compounds may be associated with the octahedral sites. This unexpected behaviour can be described as due to the effect of a significant reduction of the ligand field strength (i.e. large local distortion and Al-O bond distances).

  19. DETECTION AND TRACKING OF SUBTLE CLOUD FEATURES ON URANUS

    SciTech Connect

    Fry, P. M.; Sromovsky, L. A.; De Pater, I.; Hammel, H. B.; Rages, K. A.

    2012-06-15

    The recently updated Uranus zonal wind profile (Sromovsky et al.) samples latitudes from 71 Degree-Sign S to 73 Degree-Sign N. But many latitudes remain grossly undersampled (outside 20 Degree-Sign -45 Degree-Sign S and 20 Degree-Sign -50 Degree-Sign N) due to a lack of trackable cloud features. Offering some hope of filling these gaps is our recent discovery of low-contrast cloud that can be revealed by imaging at much higher signal-to-noise ratios (S/Ns) than previously obtained. This is demonstrated using an average of 2007 Keck II NIRC2 near-IR observations. Eleven one-minute H-band exposures, acquired over a 1.6 hr time span, were rectilinearly remapped and zonally shifted to account for planetary rotation. This increased the S/N by about a factor of 3.3. A new fine structure in latitude bands appeared, small previously unobservable cloud tracers became discernible, and some faint cloud features became prominent. While we could produce one such high-quality average, we could not produce enough to actually track the newly revealed features. This requires a specially designed observational effort. We have designed recent Hubble Space Telescope WFC3 F845M observations to allow application of the technique. We measured eight zonal winds by tracking features in these images and found that several fall off of the current zonal wind profile of Sromovsky et al., and are consistent with a partial reversal of their hemispherically asymmetric profile.

  20. Tunable Diode Laser Atomic Absorption Spectroscopy for Detection of Potassium under Optically Thick Conditions.

    PubMed

    Qu, Zhechao; Steinvall, Erik; Ghorbani, Ramin; Schmidt, Florian M

    2016-04-05

    Potassium (K) is an important element related to ash and fine-particle formation in biomass combustion processes. In situ measurements of gaseous atomic potassium, K(g), using robust optical absorption techniques can provide valuable insight into the K chemistry. However, for typical parts per billion K(g) concentrations in biomass flames and reactor gases, the product of atomic line strength and absorption path length can give rise to such high absorbance that the sample becomes opaque around the transition line center. We present a tunable diode laser atomic absorption spectroscopy (TDLAAS) methodology that enables accurate, calibration-free species quantification even under optically thick conditions, given that Beer-Lambert's law is valid. Analyte concentration and collisional line shape broadening are simultaneously determined by a least-squares fit of simulated to measured absorption profiles. Method validation measurements of K(g) concentrations in saturated potassium hydroxide vapor in the temperature range 950-1200 K showed excellent agreement with equilibrium calculations, and a dynamic range from 40 pptv cm to 40 ppmv cm. The applicability of the compact TDLAAS sensor is demonstrated by real-time detection of K(g) concentrations close to biomass pellets during atmospheric combustion in a laboratory reactor.

  1. Chromatic Information and Feature Detection in Fast Visual Analysis

    PubMed Central

    Del Viva, Maria M.; Punzi, Giovanni; Shevell, Steven K.

    2016-01-01

    The visual system is able to recognize a scene based on a sketch made of very simple features. This ability is likely crucial for survival, when fast image recognition is necessary, and it is believed that a primal sketch is extracted very early in the visual processing. Such highly simplified representations can be sufficient for accurate object discrimination, but an open question is the role played by color in this process. Rich color information is available in natural scenes, yet artist's sketches are usually monochromatic; and, black-and-white movies provide compelling representations of real world scenes. Also, the contrast sensitivity of color is low at fine spatial scales. We approach the question from the perspective of optimal information processing by a system endowed with limited computational resources. We show that when such limitations are taken into account, the intrinsic statistical properties of natural scenes imply that the most effective strategy is to ignore fine-scale color features and devote most of the bandwidth to gray-scale information. We find confirmation of these information-based predictions from psychophysics measurements of fast-viewing discrimination of natural scenes. We conclude that the lack of colored features in our visual representation, and our overall low sensitivity to high-frequency color components, are a consequence of an adaptation process, optimizing the size and power consumption of our brain for the visual world we live in. PMID:27478891

  2. Chromatic Information and Feature Detection in Fast Visual Analysis.

    PubMed

    Del Viva, Maria M; Punzi, Giovanni; Shevell, Steven K

    2016-01-01

    The visual system is able to recognize a scene based on a sketch made of very simple features. This ability is likely crucial for survival, when fast image recognition is necessary, and it is believed that a primal sketch is extracted very early in the visual processing. Such highly simplified representations can be sufficient for accurate object discrimination, but an open question is the role played by color in this process. Rich color information is available in natural scenes, yet artist's sketches are usually monochromatic; and, black-and-white movies provide compelling representations of real world scenes. Also, the contrast sensitivity of color is low at fine spatial scales. We approach the question from the perspective of optimal information processing by a system endowed with limited computational resources. We show that when such limitations are taken into account, the intrinsic statistical properties of natural scenes imply that the most effective strategy is to ignore fine-scale color features and devote most of the bandwidth to gray-scale information. We find confirmation of these information-based predictions from psychophysics measurements of fast-viewing discrimination of natural scenes. We conclude that the lack of colored features in our visual representation, and our overall low sensitivity to high-frequency color components, are a consequence of an adaptation process, optimizing the size and power consumption of our brain for the visual world we live in.

  3. Chromatic information and feature detection in fast visual analysis

    DOE PAGES

    Del Viva, Maria M.; Punzi, Giovanni; Shevell, Steven K.; ...

    2016-08-01

    The visual system is able to recognize a scene based on a sketch made of very simple features. This ability is likely crucial for survival, when fast image recognition is necessary, and it is believed that a primal sketch is extracted very early in the visual processing. Such highly simplified representations can be sufficient for accurate object discrimination, but an open question is the role played by color in this process. Rich color information is available in natural scenes, yet artist's sketches are usually monochromatic; and, black-andwhite movies provide compelling representations of real world scenes. Also, the contrast sensitivity ofmore » color is low at fine spatial scales. We approach the question from the perspective of optimal information processing by a system endowed with limited computational resources. We show that when such limitations are taken into account, the intrinsic statistical properties of natural scenes imply that the most effective strategy is to ignore fine-scale color features and devote most of the bandwidth to gray-scale information. We find confirmation of these information-based predictions from psychophysics measurements of fast-viewing discrimination of natural scenes. As a result, we conclude that the lack of colored features in our visual representation, and our overall low sensitivity to high-frequency color components, are a consequence of an adaptation process, optimizing the size and power consumption of our brain for the visual world we live in.« less

  4. Chromatic information and feature detection in fast visual analysis

    SciTech Connect

    Del Viva, Maria M.; Punzi, Giovanni; Shevell, Steven K.; Solomon, Samuel G.

    2016-08-01

    The visual system is able to recognize a scene based on a sketch made of very simple features. This ability is likely crucial for survival, when fast image recognition is necessary, and it is believed that a primal sketch is extracted very early in the visual processing. Such highly simplified representations can be sufficient for accurate object discrimination, but an open question is the role played by color in this process. Rich color information is available in natural scenes, yet artist's sketches are usually monochromatic; and, black-andwhite movies provide compelling representations of real world scenes. Also, the contrast sensitivity of color is low at fine spatial scales. We approach the question from the perspective of optimal information processing by a system endowed with limited computational resources. We show that when such limitations are taken into account, the intrinsic statistical properties of natural scenes imply that the most effective strategy is to ignore fine-scale color features and devote most of the bandwidth to gray-scale information. We find confirmation of these information-based predictions from psychophysics measurements of fast-viewing discrimination of natural scenes. As a result, we conclude that the lack of colored features in our visual representation, and our overall low sensitivity to high-frequency color components, are a consequence of an adaptation process, optimizing the size and power consumption of our brain for the visual world we live in.

  5. Feature Sampling in Detection: Implications for the Measurement of Perceptual Independence

    ERIC Educational Resources Information Center

    Macho, Siegfried

    2007-01-01

    The article presents the feature sampling signal detection (FS-SDT) model, an extension of the multivariate signal detection (SDT) model. The FS-SDT model assumes that, because of attentional shifts, different subsets of features are sampled for different presentations of the same multidimensional stimulus. Contrary to the SDT model, the FS-SDT…

  6. Bipyridine hydrogel for selective and visible detection and absorption of Cd2+

    NASA Astrophysics Data System (ADS)

    Miao, Qingqing; Wu, Ziye; Hai, Zijuan; Tao, Changlu; Yuan, Qingpan; Gong, Yadi; Guan, Yafeng; Jiang, Jun; Liang, Gaolin

    2015-01-01

    Herein, we report for the first time the use of bipyridine-based hydrogel for selective and visible detection and absorption of Cd2+. At low concentrations, hydrogelator 1 was applied for selective detection of Cd2+in vitro and in living cells with high sensitivity. In the absence of metal ions, 1 is nonfluorescent at 470 nm. Upon addition of metal ions, 1 selectively coordinates to Cd2+, causing an 86-fold increase of fluorescence intensity at 470 nm via the chelation enhanced fluorescence (CHEF) effect, as revealed by first-principles simulations. At 1.5 wt% and pH 5.5, 1 self-assembles into nanofibers to form hydrogel Gel I. Since Cd2+ could actively participate in the hydrogelation and promote the self-assembly, we also successfully applied Gel I for visible detection and absorption of Cd2+. With these excellent properties, Gel I is expected to be explored as one type of versatile biomaterial for not only environmental monitoring but also for pollution treatment in the near future.Herein, we report for the first time the use of bipyridine-based hydrogel for selective and visible detection and absorption of Cd2+. At low concentrations, hydrogelator 1 was applied for selective detection of Cd2+in vitro and in living cells with high sensitivity. In the absence of metal ions, 1 is nonfluorescent at 470 nm. Upon addition of metal ions, 1 selectively coordinates to Cd2+, causing an 86-fold increase of fluorescence intensity at 470 nm via the chelation enhanced fluorescence (CHEF) effect, as revealed by first-principles simulations. At 1.5 wt% and pH 5.5, 1 self-assembles into nanofibers to form hydrogel Gel I. Since Cd2+ could actively participate in the hydrogelation and promote the self-assembly, we also successfully applied Gel I for visible detection and absorption of Cd2+. With these excellent properties, Gel I is expected to be explored as one type of versatile biomaterial for not only environmental monitoring but also for pollution treatment in the near future

  7. Pair normalized channel feature and statistics-based learning for high-performance pedestrian detection

    NASA Astrophysics Data System (ADS)

    Zeng, Bobo; Wang, Guijin; Ruan, Zhiwei; Lin, Xinggang; Meng, Long

    2012-07-01

    High-performance pedestrian detection with good accuracy and fast speed is an important yet challenging task in computer vision. We design a novel feature named pair normalized channel feature (PNCF), which simultaneously combines and normalizes two channel features in image channels, achieving a highly discriminative power and computational efficiency. PNCF applies to both gradient channels and color channels so that shape and appearance information are described and integrated in the same feature. To efficiently explore the formidably large PNCF feature space, we propose a statistics-based feature learning method to select a small number of potentially discriminative candidate features, which are fed into the boosting algorithm. In addition, channel compression and a hybrid pyramid are employed to speed up the multiscale detection. Experiments illustrate the effectiveness of PNCF and its learning method. Our proposed detector outperforms the state-of-the-art on several benchmark datasets in both detection accuracy and efficiency.

  8. Study of Prominence Detection Based on Various Phone-Specific Features

    NASA Astrophysics Data System (ADS)

    Kim, Sung Soo; Han, Chang Woo; Kim, Nam Soo

    In this letter, we present useful features accounting for pronunciation prominence and propose a classification technique for prominence detection. A set of phone-specific features are extracted based on a forced alignment of the test pronunciation provided by a speech recognition system. These features are then applied to the traditional classifiers such as the support vector machine (SVM), artificial neural network (ANN) and adaptive boosting (Adaboost) for detecting the place of prominence.

  9. Spatially resolved micro-absorption spectroscopy with a broadband source and confocal detection

    NASA Astrophysics Data System (ADS)

    Arora, Silki; Mauser, Jennifer; Chakrabarti, Debopam; Schulte, Alfons

    2015-11-01

    We present a novel approach to measure optical absorption spectra with spatial resolution at the micron scale. The setup combines a continuous white light excitation beam in transmission geometry with a confocal microscope. The spatial resolution is found to be better than 1.4 μm in the lateral and 3.6 μm in the axial direction. Employing multichannel detection the absorption spectrum of hemoglobin in a single red blood cell is measured on the timescale of seconds. Through measurements of the transmitted intensity in solutions in nanoliter quantities we establish that the absorbance varies linearly with concentration. Our setup enables the investigation of spatial variations in the optical density of small samples on the micron scale and can be applied to the study of biological assemblies at the single cell level, in optical diagnostics, and in micro-fluidics.

  10. Hydration-dependent far-infrared absorption in lysozyme detected using synchrotron radiation.

    PubMed Central

    Moeller, K D; Williams, G P; Steinhauser, S; Hirschmugl, C; Smith, J C

    1992-01-01

    Using the National Synchrotron Light Source (NSLS) at Brookhaven far-infrared absorption in the frequency range 15-45 cm-1 was detected in samples of lysozyme at different hydrations and in water. The absorption is due to the presence of low-frequency (picosecond timescale) motion in the samples, such as are calculated in molecular dynamics simulations. The form of the transmission profile is temperature independent but varies significantly with the degree of hydration of the protein. At higher hydrations the profile resembles closely that of pure water in the region 20-45 cm-1. At a low hydration marked differences are seen with, in particular, the appearance of a transmission minimum at 19 cm-1. The possible origins of the hydration dependence are discussed. The results demonstrate the usefulness of long-wavelength synchrotron radiation for the characterisation of biologically-important low-frequency motions in protein samples. PMID:1540696

  11. Parallel algorithm for linear feature detection from airborne LiDAR data

    NASA Astrophysics Data System (ADS)

    Mareboyana, Manohar; Chi, Paul

    2006-05-01

    Linear features from airport images correspond to runways, taxiways and roads. Detecting runways helps pilots to focus on runway incursions in poor visibility conditions. In this work, we attempt to detect linear features from LiDAR swath in near real time using parallel implementation on G5-based apple cluster called Xseed. Data from LiDAR swath is converted into a uniform grid with nearest neighbor interpolation. The edges and gradient directions are computed using standard edge detection algorithms such as Canny's detector. Edge linking and detecting straight-line features are described. Preliminary results on Reno, Nevada airport data are included.

  12. Detection of cyclotron resonance scattering feature in high-mass X-ray binary pulsar SMC X-2

    NASA Astrophysics Data System (ADS)

    Jaisawal, Gaurava K.; Naik, Sachindra

    2016-09-01

    We report broad-band spectral properties of the high-mass X-ray binary pulsar SMC X-2 by using three simultaneous Nuclear Spectroscopy Telescope Array and Swift/XRT observations during its 2015 outburst. The pulsar was significantly bright, reaching a luminosity up to as high as ˜5.5 × 1038 erg s-1 in 1-70 keV range. Spin period of the pulsar was estimated to be 2.37 s. Pulse profiles were found to be strongly luminosity dependent. The 1-70 keV energy spectrum of the pulsar was well described with three different continuum models such as (i) negative and positive power law with exponential cutoff, (ii) Fermi-Dirac cutoff power law and (iii) cutoff power-law models. Apart from the presence of an iron line at ˜6.4 keV, a model independent absorption like feature at ˜27 keV was detected in the pulsar spectrum. This feature was identified as a cyclotron absorption line and detected for the first time in this pulsar. Corresponding magnetic field of the neutron star was estimated to be ˜2.3 × 1012 G. The cyclotron line energy showed a marginal negative dependence on the luminosity. The cyclotron line parameters were found to be variable with pulse phase and interpreted as due to the effect of emission geometry or complicated structure of the pulsar magnetic field.

  13. A light-emitting diode- (LED-) based absorption sensor for simultaneous detection of carbon monoxide and carbon dioxide

    DOE PAGES

    Thurmond, Kyle; Loparo, Zachary; Partridge, Jr., William P.; ...

    2016-04-18

    Here, a sensor was developed for simultaneous measurements of carbon monoxide (CO) and carbon dioxide (CO2) fluctuations in internal combustion engine exhaust gases. This sensor utilizes low-cost and compact light-emitting diodes (LEDs) that emit in the 3–5 µm wavelength range. An affordable, fast response sensor that can measure these gases has a broad application that can lead to more efficient, fuel-flexible engines and regulation of harmful emissions. Light emission from LEDs is spectrally broader and more spatially divergent when compared to that of lasers, which presented many design challenges. Optical design studies addressed some of the non-ideal characteristics of themore » LED emissions. Measurements of CO and CO2 were conducted using their fundamental absorption bands centered at 4.7 µm and 4.3 µm, respectively, while a 3.6 µm reference LED was used to account for scattering losses (due to soot, window deposits, etc.) common to the three measurement LEDs. Instrument validation and calibration was performed using a laboratory flow cell and bottled-gas mixtures. The sensor was able to detect CO2 and CO concentration changes as small as 30 ppm and 400 ppm, respectively. Because of the many control and monitor species with infra-red absorption features, which can be measured using the strategy described, this work demonstrates proof of concept for a wider range of fast (250 Hz) and low-cost sensors for gas measurement and process monitoring.« less

  14. Radar absorption due to a corotating interaction region encounter with Mars detected by MARSIS

    NASA Astrophysics Data System (ADS)

    Morgan, David D.; Gurnett, Donald A.; Kirchner, Donald L.; David Winningham, J.; Frahm, Rudy A.; Brain, David A.; Mitchell, David L.; Luhmann, Janet G.; Nielsen, Erling; Espley, Jared R.; Acuña, Mario H.; Plaut, Jeffrey J.

    2010-03-01

    Mars Advanced Radar for Subsurface and Ionospheric Sounding (MARSIS) is a subsurface and topside ionosphere radar sounder aboard the European Space Agency spacecraft Mars Express, in orbit at Mars since 25 December 2003, and in operation since 17 June 2005. The ionospheric sounding mode of MARSIS is capable of detecting the reflection of the sounding wave from the martian surface. This ability has been used in previous work to show that the surface reflection is absorbed and disappears during periods when high fluxes of energetic particles are incident on the ionosphere of Mars. These absorption events are believed to be the result of increased collisional damping of the sounding wave, caused by increased electron density below the spacecraft, in turn caused by impact ionization from the impinging particles. In this work we identify two absorption events that were isolated during periods when the surface reflection is consistently visible and when Mars is nearly at opposition. The visibility of the surface reflection is viewed in conjunction with particle and photon measurements taken at both Mars and Earth. Both absorption events are found to coincide with Earth passing through solar wind speed and ion flux signatures indicative of a corotating interaction region (CIR). The two events are separated by an interval of approximately 27 days, corresponding to one solar rotation. The first of the two events coincides with abruptly enhanced particle fluxes seen in situ at Mars. Simultaneous with the particle enhancement there are an abrupt decrease in the intensity of electron oscillations, typically seen by the Mars Express particle instrument ASPERA-3 between the magnetic pileup boundary and the martian bow shock, and a sharp drop in the solar wind pressure, seen in the proxy quantity based on MGS magnetometer observations. The decrease in oscillation intensity is therefore the probable effect of a relaxation of the martian bow shock. The second absorption event does

  15. New narrow infrared absorption features in the spectrum of Io between 3600 and 3100 cm (2.8-3.2 micrometers)

    NASA Technical Reports Server (NTRS)

    Sandford, Scott A.; Geballe, Thomas R.; Salama, Farid; Goorvitch, David

    1994-01-01

    We report the discovery of a series of infrared absorption bands between 3600 and 3100/cm (2.8-3.2 micrometers) in the spectrum of Io. Individual narrow bands are detected at 3553, 3514.5, 3438, 3423, 3411.5, and 3401/cm (2.815, 2.845, 2.909, 2.921, 2.931, and 2.940 micrometers, respectively). The positions and relative strengths of these bands, and the difference of their absolute strengths between the leading and trailing faces of Io, indicate that they are due to SO2. The band at 3438/cm (2.909 micrometers) could potentially have a contribution from an additional molecular species. The existence of these bands in the spectrum of Io indicates that a substantial fraction of the SO2 on Io must reside in transparent ices having relatively large crystal sizes. The decrease in the continuum observed at the high frequency ends of the spectra is probably due to the low frequency side of the recently detected, strong 3590/cm (2.79 micrometer) feature. This band is likely due to the combination of a moderately strong SO2 band and an additional absorption from another molecular species, perhaps H2O isolated in SO2 at low concentrations. A broad (FWHM approximately = 40-60/cm), weak band is seen near 3160/cm (3.16 micrometers) and is consistent with the presence of small quantities of H2O isolated in SO2-rich ices. There is no evidence in the spectra for the presence of H2O vapor on Io. Thus, the spectra presented here neither provide unequivocal evidence for the presence of H2O on Io nor preclude it at the low concentrations suggested by past studies.

  16. Quantum cascade laser-based multipass absorption system for hydrogen peroxide detection

    NASA Astrophysics Data System (ADS)

    Cao, Yingchun; Sanchez, Nancy P.; Jiang, Wenzhe; Ren, Wei; Lewicki, Rafal; Jiang, Dongfang; Griffin, Robert J.; Tittel, Frank K.

    2015-01-01

    Hydrogen peroxide (H2O2) is a relevant molecular trace gas species, that is related to the oxidative capacity of the atmosphere, the production of radical species such as OH, the generation of sulfate aerosol via oxidation of S(IV) to S(VI), and the formation of acid rain. The detection of atmospheric H2O2 involves specific challenges due to its high reactivity and low concentration (ppbv to sub-ppbv level). Traditional methods for measuring atmospheric H2O2 concentration are often based on wet-chemistry methods that require a transfer from the gas- to liquid-phase for a subsequent determination by techniques such as fluorescence spectroscopy, which can lead to problems such as sampling artifacts and interference by other atmospheric constituents. A quartz-enhanced photoacoustic spectroscopy-based system for the measurement of atmospheric H2O2 with a detection limit of 75 ppb for 1-s integration time was previously reported. In this paper, an updated H2O2 detection system based on long-optical-path-length absorption spectroscopy by using a distributed feedback quantum cascade laser (DFB-QCL) will be described. A 7.73-μm CW-DFB-QCL and a thermoelectrically cooled infrared detector, optimized for a wavelength of 8 μm, are employed for theH2O2 sensor system. A commercial astigmatic Herriott multi-pass cell with an effective optical path-length of 76 m is utilized for the reported QCL multipass absorption system. Wavelength modulation spectroscopy (WMS) with second harmonic detection is used for enhancing the signal-to-noise-ratio. A minimum detection limit of 13.4 ppb is achieved with a 2 s sampling time. Based on an Allan-Werle deviation analysis the minimum detection limit can be improved to 1.5 ppb when using an averaging time of 300 s.

  17. Peroxy radical detection for airborne atmospheric measurements using absorption spectroscopy of NO2

    NASA Astrophysics Data System (ADS)

    Horstjann, M.; Andrés Hernández, M. D.; Nenakhov, V.; Chrobry, A.; Burrows, J. P.

    2014-05-01

    Development of an airborne instrument for the determination of peroxy radicals (PeRCEAS - peroxy radical chemical enhancement and absorption spectroscopy) is reported. Ambient peroxy radicals (HO2 and RO2, R being an organic chain) are converted to NO2 in a reactor using a chain reaction involving NO and CO. Provided that the amplification factor, called effective chain length (eCL), is known, the concentration of NO2 can be used as a proxy for the peroxy radical concentration in the sampled air. The eCL depends on radical surface losses and must thus be determined experimentally for each individual setup. NO2 is detected by continuous-wave cavity ring-down spectroscopy (cw-CRDS) using an extended cavity diode laser (ECDL) at 408.9 nm. Optical feedback from a V-shaped resonator maximizes transmission and allows for a simple detector setup. CRDS directly yields absorption coefficients, thus providing NO2 concentrations without additional calibration. The optimum 1σ detection limit is 0.3 ppbv at an averaging time of 40 s and an inlet pressure of 300 hPa. Effective chain lengths were determined for HO2 and CH3O2 at different inlet pressures. The 1σ detection limit at an inlet pressure of 300 hPa for HO2 is 3 pptv for an averaging time of 120 s.

  18. CH3 and CFx Detection in Low Pressure RF Discharges by Broadband Ultraviolet Absorption Spectroscopy

    NASA Astrophysics Data System (ADS)

    Cappelli, M. A.; Kim, J. S.; Sharma, S. P.

    1998-10-01

    The detection of reactive radicals in low-pressure radio-frequency (RF) discharges is of importance to the understanding of the chemical processes involved in discharge applications such as reactive ion etching (RIE) and plasma-enhanced chemical vapor deposition (PECVD). Furthermore, the quantitative measurement of radical concentrations and their spatial distributions provide a test of theoretical models that describe the kinetics of such discharges and their ability to predict the overall reactor-scale performance. In this presentation, we describe preliminary studies of the quantitative detection of CH3 and CF2, which are the products of electron collisional dissociation of methane (CH4) and tetrafluoromethane (CF4), respectively, in low-pressure RF plasma discharges. The discharge studied is an inductively (transformer) coupled plasma (ICP) source, operating on either pure methane or pure tetrafluoromethane, in some cases, with argon dilution. Such discharges are commonly employed in RIE and PECVD applications, and these data contribute to the growing database on properties of such discharges, for which sophisticated models of their operation are presently under development at many laboratories. The detection method employed in these experiments relies on the relatively well studied, X -> B uv-absorption band of CH3 near 216 nm, and the A(0,2,0) -> X(0,0,0) uv-absorption band of CF2 at 234.3 nm.

  19. Detection of interstellar sodium hydroxide in self-absorption toward the galactic center

    NASA Technical Reports Server (NTRS)

    Hollis, J. M.; Rhodes, P. J.

    1982-01-01

    A weak self-absorbed emission line, which is identified as the J = 4-3 transition of sodium hydroxide, has been detected in the direction of Sgr B2(OH). The correspondingly weak Sgr B2(QH) emission line U75406, previously reported as an unidentified spectral feature by other investigators, is consistent with the J = 3-2 transition of sodium hydroxide. This detection may represent the first evidence of a grain reaction formation mechanism for simple metal hydroxides. The detection of H62 Delta toward Orion A is also reported.

  20. Multiplexed selective detection and identification of TCE and xylene in water by on-chip absorption spectroscopy

    NASA Astrophysics Data System (ADS)

    Lai, Wei-Cheng; Chakravarty, Swapnajit; Zou, Yi; Chen, Ray T.

    2013-03-01

    We demonstrate a device which can do multiplexed detection of two different chemicals on one chip by using infrared absorption spectroscopy. The signature of Trichloroethylene(TCE) and xylene in water enable multiplexed detection on one chip. We use the slow light effect in the photonic crystal design which enhances the absorption of the analytes by a factor of 30 as demonstrated by our previous works. In order to match the absorption peaks of these two analytes, photonic crystal slow light regions are designed at 1644nm and 1674nm with a SU8 cladding on top. Multiplexed detection is enabled by using a multimode interference (MMI) optical power splitter at the input, which divides optical power into two arms, and Y combiner at the output. Consequently, the absorption of these two chemicals can be enhanced by the slow light effect. The MMI structure and Y combiner also enable the multiplexed detection of two analytes on one chip.

  1. The Azimuthal Dependence of Outflows and Accretion Detected Using O VI Absorption

    NASA Astrophysics Data System (ADS)

    Kacprzak, Glenn G.; Muzahid, Sowgat; Churchill, Christopher W.; Nielsen, Nikole M.; Charlton, Jane C.

    2015-12-01

    We report a bimodality in the azimuthal angle (Φ) distribution of gas around galaxies traced by O vi absorption. We present the mean Φ probability distribution function of 29 Hubble Space Telescope-imaged O vi absorbing (EW > 0.1 Å) and 24 non-absorbing (EW < 0.1 Å) isolated galaxies (0.08 \\lt z \\lt 0.67) within ˜200 kpc of background quasars. We show that equivalent width (EW) is anti-correlated with impact parameter and O vi covering fraction decreases from 80% within 50 kpc to 33% at 200 kpc. The presence of O vi absorption is azimuthally dependent and occurs between ±10°-20° of the galaxy projected major axis and within ±30° of the projected minor axis. We find higher EWs along the projected minor axis with weaker EWs along the project major axis. Highly inclined galaxies have the lowest covering fractions due to minimized outflow/inflow cross-section geometry. Absorbing galaxies also have bluer colors while non-absorbers have redder colors, suggesting that star formation is a key driver in the O vi detection rate. O vi surrounding blue galaxies exists primarily along the projected minor axis with wide opening angles while O vi surrounding red galaxies exists primarily along the projected major axis with smaller opening angles, which may explain why absorption around red galaxies is less frequently detected. Our results are consistent with a circumgalactic medium (CGM) originating from major axis-fed inflows/recycled gas and from minor axis-driven outflows. Non-detected O vi occurs between Φ = 20°-60°, suggesting that O vi is not mixed throughout the CGM and remains confined within the outflows and the disk-plane. We find low O vi covering fractions within +/- 10^\\circ of the projected major axis, suggesting that cool dense gas resides in a narrow planer geometry surrounded by diffuse O vi gas.

  2. Radial Trends in IMF-sensitive Absorption Features in Two Early-type Galaxies: Evidence for Abundance-driven Gradients

    NASA Astrophysics Data System (ADS)

    McConnell, Nicholas J.; Lu, Jessica R.; Mann, Andrew W.

    2016-04-01

    Samples of early-type galaxies show a correlation between stellar velocity dispersion and the stellar initial mass function (IMF) as inferred from gravity-sensitive absorption lines in the galaxies’ central regions. To search for spatial variations in the IMF, we have observed two early-type galaxies with Keck/LRIS and measured radial gradients in the strengths of absorption features from 4000-5500 Å and 8000-10000 Å. We present spatially resolved measurements of the dwarf-sensitive spectral indices {Na} {{I}} (8190 Å) and Wing-Ford {{FeH}} (9915 Å), as well as indices for species of H, C2, CN, Mg, Ca, {{TiO}}, and Fe. Our measurements show a metallicity gradient in both objects, and Mg/Fe consistent with a shallow gradient in α-enhancement, matching widely observed trends for massive early-type galaxies. The {Na} {{I}} index and the CN1 index at 4160 Å exhibit significantly steeper gradients, with a break at r˜ 0.1 {r}{{eff}} (r˜ 300 pc). Inside this radius, {Na} {{I}} strength increases sharply toward the galaxy center, consistent with a rapid central rise in [Na/Fe]. In contrast, the ratio of the {{FeH}} to Fe index strength decreases toward the galaxy center. This behavior cannot be reproduced by a steepening IMF inside of 0.1 {r}{{eff}} if the IMF is a single power law. While gradients in the mass function above ˜ 0.4 {M}⊙ may occur, exceptional care is required to disentangle these IMF variations from the extreme variations in individual element abundances near the galaxies’ centers.

  3. Fiber-optic thermometer using temperature dependent absorption, broadband detection, and time domain referencing

    NASA Technical Reports Server (NTRS)

    Adamovsky, Grigory; Piltch, Nancy D.

    1986-01-01

    A fiber-optic thermometer based on temperature dependent absorption in Nd(3+) doped glass is demonstrated over the 298-573 K range. A broadband detection technique allows the use of the complete spectrum of a pulse modulated light emitting diode. A fiber-optic recirculating loop is employed to construct a reference channel in the time domain by generating a train of pulses from one initial pulse. A theoretical model is developed, and experimental data are shown to compare well with the theory. Possible sources of error and instability are identified, and ways to enhance the performance of the system are proposed.

  4. Multiplexed detection of xylene and trichloroethylene in water by photonic crystal absorption spectroscopy.

    PubMed

    Lai, Wei-Cheng; Chakravarty, Swapnajit; Zou, Yi; Chen, Ray T

    2013-10-01

    We experimentally demonstrate simultaneous selective detection of xylene and trichloroethylene (TCE) using multiplexed photonic crystal waveguides (PCWs) by near-infrared optical absorption spectroscopy on a chip. Based on the slow light effect of photonic crystal structure, the sensitivity of our device is enhanced to 1 ppb (v/v) for xylene and 10 ppb (v/v) for TCE in water. Multiplexing is enabled by multimode interference power splitters and Y-combiners that integrate multiple PCWs on a silicon chip in a silicon-on-insulator platform.

  5. Mid-infrared carbon monoxide detection system using differential absorption spectroscopy technique

    NASA Astrophysics Data System (ADS)

    Dong, Ming; Sui, Yue; Li, Guo-lin; Zheng, Chuan-tao; Chen, Mei-mei; Wang, Yi-ding

    2015-11-01

    A differential carbon monoxide (CO) concentration sensing device using a self-fabricated spherical mirror (e.g. light-collector) and a multi-pass gas-chamber is presented in this paper. Single-source dual-channel detection method is adopted to suppress the interferences from light source, optical path and environmental changes. Detection principle of the device is described, and both the optical part and the electrical part are developed. Experiments are carried out to evaluate the sensing performance on CO concentration. The results indicate that at 1.013×105 Pa and 298 K, the limit of detection (LoD) is about 11.5 mg/m3 with an absorption length of 40 cm. As the gas concentration gets larger than 115 mg/m3 (1.013×105 Pa, 298 K), the relative detection error falls into the range of -1.7%—+1.9%. Based on 12 h long-term measurement on the 115 mg/m3 and 1 150 mg/m3 CO samples, the maximum detection errors are about 0.9% and 5.5%, respectively. Due to the low cost and competitive characteristics, the proposed device shows potential applications in CO detection in the circumstances of coal-mine production and environmental protection.

  6. Possible Detection of an Emission Cyclotron Resonance Scattering Feature from the Accretion-Powered Pulsar 4U 1626-67

    NASA Technical Reports Server (NTRS)

    Iwakiri, W. B.; Terada, Y.; Tashiro, M. S.; Mihara, T.; Angelini, L.; Yamada, S.; Enoto, T.; Makishima, K.; Nakajima, M.; Yoshida, A.

    2012-01-01

    We present analysis of 4U 1626-67, a 7.7 s pulsar in a low-mass X-ray binary system, observed with the hard X-ray detector of the Japanese X-ray satellite Suzaku in 2006 March for a net exposure of 88 ks. The source was detected at an average 10-60 keY flux of approx 4 x 10-10 erg / sq cm/ s. The phase-averaged spectrum is reproduced well by combining a negative and positive power-law times exponential cutoff (NPEX) model modified at approx 37 keY by a cyclotron resonance scattering feature (CRSF). The phase-resolved analysis shows that the spectra at the bright phases are well fit by the NPEX with CRSF model. On the other hand. the spectrum in the dim phase lacks the NPEX high-energy cutoff component, and the CRSF can be reproduced by either an emission or an absorption profile. When fitting the dim phase spectrum with the NPEX plus Gaussian model. we find that the feature is better described in terms of an emission rather than an absorption profile. The statistical significance of this result, evaluated by means of an F test, is between 2.91 x 10(exp -3) and 1.53 x 10(exp -5), taking into account the systematic errors in the background evaluation of HXD-PIN. We find that the emission profile is more feasible than the absorption one for comparing the physical parameters in other phases. Therefore, we have possibly detected an emission line at the cyclotron resonance energy in the dim phase.

  7. H I emission and absorption in nearby, gas-rich galaxies - II. Sample completion and detection of intervening absorption in NGC 5156

    NASA Astrophysics Data System (ADS)

    Reeves, S. N.; Sadler, E. M.; Allison, J. R.; Koribalski, B. S.; Curran, S. J.; Pracy, M. B.; Phillips, C. J.; Bignall, H. E.; Reynolds, C.

    2016-04-01

    We present the results of a survey for intervening 21 cm H I absorption in a sample of 10 nearby, gas-rich galaxies selected from the H I Parkes All-Sky Survey (HIPASS). This follows the six HIPASS galaxies searched in previous work and completes our full sample. In this paper, we searched for absorption along 17 sightlines with impact parameters between 6 and 46 kpc, making one new detection. We also obtained simultaneous H I emission-line data, allowing us to directly relate the absorption-line detection rate to the H I distribution. From this, we find the majority of the non-detections in the current sample are because sightline does not intersect the H I disc of the galaxy at sufficiently high column density, but that source structure is also an important factor. The detected absorption-line arises in the galaxy NGC 5156 (z = 0.01) at an impact parameter of 19 kpc. The line is deep and narrow with an integrated optical depth of 0.82 km s-1. High-resolution Australia Telescope Compact Array (ATCA) images at 5 and 8 GHz reveal that the background source is resolved into two components with a separation of 2.6 arcsec (500 pc at the redshift of the galaxy), with the absorption likely occurring against a single component. We estimate that the ratio of the spin temperature and covering factor, TS/f, is approximately 950 K in the outer disc of NGC 5156, but further observations using very long baseline interferometry would allow us to accurately measure the covering factor and spin temperature of the gas.

  8. Application of modified difference absorption method to stand-off detection of alcohol in simulated car cabins

    NASA Astrophysics Data System (ADS)

    Kubicki, Jan; Młyńczak, Jaroslaw; Kopczyński, Krzysztof

    2013-01-01

    Some aspects of stand-off detection of alcohol in simulated car cabins are described. The proposed method is the well-known "difference absorption" method applied to the differential absorption lidar system, modified by taking advantage of a third laser beam. The modification was motivated by the familiar physical phenomena such as dispersion and different absorption coefficients in window panes for applied laser wavelengths. The mathematical expressions for the method were derived and confirmed by experiments. The presented investigations indicate that the method can be successfully applied to stand-off detection of ethyl alcohol in moving cars.

  9. Thermal stability of soils and detectability of intrinsic soil features

    NASA Astrophysics Data System (ADS)

    Siewert, Christian; Kucerik, Jiri

    2014-05-01

    applicability of thermogravimetry for soil property determination. Despite of the extreme diversity of individual substances in soils, the thermal decay can be predicted with simple mathematical models. For example, the sum of mass losses in the large temperature interval from 100 °C to 550 °C (known from organic matter determination by ignition mass loss in past) can be predicted using TML in two small temperature intervals: 130 - 140 °C and 320 - 330 °C. In this case, the coefficient of determination between measured and calculated results reached an R2 above 0.97. Further, we found close autocorrelations between thermal mass losses in different temperature intervals. They refer to interrelations between evaporation of bound water and thermal decay of organo-mineral complexes in soils less affected by human influence. In contrast, deviations from such interrelations were found under extreme environmental conditions and in soils under human use. Those results confirm current knowledge about influence of clay on both water binding and organic matter accumulation during natural soil formation. Therefore, these interrelations between soil components are discussed as intrinsic features of soils which open the opportunity for experimental distinction of natural soils from organic and inorganic materials which do not have pedogenetic origin.

  10. Application of atomic absorption spectroscopy for detection of multimetal traces in low-voltage electrical marks.

    PubMed

    Jakubeniene, Marija; Zakaras, Algirdas; Minkuviene, Zita Nijole; Benoshys, Alvydas

    2006-08-10

    Application of atomic absorption spectroscopy to detect multimetal traces in injured skin is a promising tool for investigation of fatalities caused by electrocution. The present paper is aimed at testing the reliability of this method for metal traces detection in electric current marks and is focused on study of peculiarities of metal penetration into the skin exposed to a current impact. Bare aluminum wire, tin-lead coated copper multistrand wire, and zinc-plated steel rope were used to make electrical marks on pig skin. It is demonstrated that amount of copper, zinc, lead, and iron may serve as statistically reliable indicators for the type of wire, which caused the electrical mark, in spite of the background content of these metals in the skin without injury. Different penetration rates for different metals contained in the wire inflicting an electrical mark were observed.

  11. Automatic layout feature extraction for lithography hotspot detection based on deep neural network

    NASA Astrophysics Data System (ADS)

    Matsunawa, Tetsuaki; Nojima, Shigeki; Kotani, Toshiya

    2016-03-01

    Lithography hotspot detection in the physical verification phase is one of the most important techniques in today's optical lithography based manufacturing process. Although lithography simulation based hotspot detection is widely used, it is also known to be time-consuming. To detect hotspots in a short runtime, several machine learning based methods have been proposed. However, it is difficult to realize highly accurate detection without an increase in false alarms because an appropriate layout feature is undefined. This paper proposes a new method to automatically extract a proper layout feature from a given layout for improvement in detection performance of machine learning based methods. Experimental results show that using a deep neural network can achieve better performance than other frameworks using manually selected layout features and detection algorithms, such as conventional logistic regression or artificial neural network.

  12. Comparison of two absorption imaging methods to detect cold atoms in magnetic trap

    NASA Astrophysics Data System (ADS)

    Wang, Yan; Hu, Zhao-Hui; Qi, Lu

    2015-02-01

    Two methods of absorption imaging to detect cold atoms in a magnetic trap are implemented for a high-precision cold atom interferometer. In the first method, a probe laser which is in resonance with a cycle transition frequency is used to evaluate the quantity and distribution of the atom sample. In the second method, the probe laser is tuned to an open transition frequency, which stimulates a few and constant number of photons per atom. This method has a shorter interaction time and results in absorption images which are not affected by the magnetic field and the light field. We make a comparison of performance between these two imaging methods in the sense of parameters such as pulse duration, light intensity, and magnetic field strength. The experimental results show that the second method is more reliable when detecting the quantity and density profiles of the atoms. These results fit well to the theoretical analysis. Project supported by the National Natural Science Foundation of China (Grant Nos. 61227902 and 61121003) and the National Defense Basic Scientific Research Program of China (Grant No. B2120132005).

  13. [The application of atomic absorption spectrometry in automatic transmission fault detection].

    PubMed

    Chen, Li-dan; Chen, Kai-kao

    2012-01-01

    The authors studied the innovative applications of atomic absorption spectrometry in the automatic transmission fault detection. After the authors have determined Fe, Cu and Cr contents in the five groups of Audi A6 main metal in automatic transmission fluid whose travel course is respectively 10-15 thousand kilometers, 20-26 thousand kilometers, 32-38 thousand kilometers, 43-49 thousand kilometers, and 52-58 thousand kilometers by atomic absorption spectrometry, the authors founded the database of primary metal content in the Audi A6 different mileage automatic transmission fluid (ATF). The research discovered that the main metal content in the automatic transmission fluid increased with the vehicles mileage and its normal metal content level in the automatic transmission fluid is between the two trend lines. The authors determined the main metal content of automatic transmission fluid which had faulty symptoms and compared it with its database value. Those can not only judge the wear condition of the automatic transmission which had faulty symptoms but also help the automobile detection and maintenance personnel to diagnose automatic transmission failure reasons without disintegration. This reduced automobile maintenance costs, and improved the quality of automobile maintenance.

  14. GSH 006-15+7: a local Galactic supershell featuring transition from H I emission to absorption

    NASA Astrophysics Data System (ADS)

    Moss, V. A.; McClure-Griffiths, N. M.; Braun, R.; Hill, A. S.; Madsen, G. J.

    2012-04-01

    We report on the discovery of a new Galactic supershell, GSH 006-15+7, from the Galactic All-Sky Survey data. Observed and derived properties are presented, and we find that GSH 006-15+7 is one of the nearest physically large supershells known, with dimensions of ˜780 × 520 pc at a distance of ˜ 1.5 kpc. The shell wall appears in HI emission at b≲-6?5 and in HI self-absorption (HISA) at b≳-6?5. We use this feature along with HISA diagnostics to estimate an optical depth of τ˜ 3, a spin temperature of ˜40 K and a swept-up mass of M˜ 3 × 106 M⊙. We also investigate the origin of GSH 006-15+7, assessing the energy contribution of candidate powering sources and finding evidence in favour of a formation energy of ˜1052 erg. We find that this structure provides evidence for the transfer of mass and energy from the Galactic disc into the halo.

  15. Harmonic and anharmonic features of IR and NIR absorption and VCD spectra of chiral 4-X-[2.2]paracyclophanes.

    PubMed

    Abbate, Sergio; Castiglioni, Ettore; Gangemi, Fabrizio; Gangemi, Roberto; Longhi, Giovanna; Ruzziconi, Renzo; Spizzichino, Sara

    2007-08-02

    The vibrational absorption spectra and vibrational circular dichroism (VCD) spectra of both enantiomers of 4-X-[2.2]paracyclophanes (X = COOCD3, Cl, I) have been recorded for a few regions in the range of 900-12000 cm(-1). The analysis of the VCD spectra for the two IR regions, 900-1600 cm(-1) and 2800-3200 cm(-1), is conducted by comparing with DFT calculations of the corresponding spectra; the latter region reveals common motifs of vibrational modes for the three molecules for aliphatic CH stretching fundamentals, whereas in the mid-IR region, one is able to identify specific signatures arising from the substituent groups X. In the CH stretching region between 2900 and 2800 cm(-1), we identify and interpret a group of three IR VCD bands due to HCH bending overtone transitions in Fermi resonance with CH stretching fundamental transitions. The analysis of the NIR region between approximately 8000 and approximately 9000 cm(-1) for X = COOCD3 reveals important features of the aromatic CH stretching overtones that are of value since the aromatic CH stretching fundamentals are almost silent. The intensifying of such overtones is attributed to electrical anharmonicity terms, which are evaluated here by ab initio methods and compared with literature data.

  16. Detection of linear features using a localized radon transform with a wavelet filter

    SciTech Connect

    Warrick, A L; Delaney, P A

    1999-12-13

    One problem of interest to the oceanic engineering community is the detection and enhancement of internal wakes in open water synthetic aperture radar (SAR) images. Internal wakes, which occur when a ship travels in a stratified medium, have a V shape extending from the ship, and a chirp-like feature across each arm. The Radon transform has been applied to the detection and the enhancement problems in internal wake images to account for the linear features while the wavelet transform has been applied to the enhancement problem in internal wake images to account for the chirp-like features. In this paper, a new transform, a localized Radon transform with a wavelet filter (LRTWF), is developed which accounts for both the linear and the chirp-like features of the internal wake. This transform is then incorporated into optimal and sub-optimal detection schemes for images (with these features) which are contaminated by additive Gaussian noise.

  17. Synthetic aperture radar target detection, feature extraction, and image formation techniques

    NASA Technical Reports Server (NTRS)

    Li, Jian

    1994-01-01

    This report presents new algorithms for target detection, feature extraction, and image formation with the synthetic aperture radar (SAR) technology. For target detection, we consider target detection with SAR and coherent subtraction. We also study how the image false alarm rates are related to the target template false alarm rates when target templates are used for target detection. For feature extraction from SAR images, we present a computationally efficient eigenstructure-based 2D-MODE algorithm for two-dimensional frequency estimation. For SAR image formation, we present a robust parametric data model for estimating high resolution range signatures of radar targets and for forming high resolution SAR images.

  18. Synthetic aperture radar target detection, feature extraction, and image formation techniques

    NASA Astrophysics Data System (ADS)

    Li, Jian

    1994-09-01

    This report presents new algorithms for target detection, feature extraction, and image formation with the synthetic aperture radar (SAR) technology. For target detection, we consider target detection with SAR and coherent subtraction. We also study how the image false alarm rates are related to the target template false alarm rates when target templates are used for target detection. For feature extraction from SAR images, we present a computationally efficient eigenstructure-based 2D-MODE algorithm for two-dimensional frequency estimation. For SAR image formation, we present a robust parametric data model for estimating high resolution range signatures of radar targets and for forming high resolution SAR images.

  19. Fluorescence detection of white-beam X-ray absorption anisotropy: towards element-sensitive projections of local atomic structure

    PubMed Central

    Korecki, P.; Tolkiehn, M.; Dąbrowski, K. M.; Novikov, D. V.

    2011-01-01

    Projections of the atomic structure around Nb atoms in a LiNbO3 single crystal were obtained from a white-beam X-ray absorption anisotropy (XAA) pattern detected using Nb K fluorescence. This kind of anisotropy results from the interference of X-rays inside a sample and, owing to the short coherence length of a white beam, is visible only at small angles around interatomic directions. Consequently, the main features of the recorded XAA corresponded to distorted real-space projections of dense-packed atomic planes and atomic rows. A quantitative analysis of XAA was carried out using a wavelet transform and allowed well resolved projections of Nb atoms to be obtained up to distances of 10 Å. The signal of nearest O atoms was detected indirectly by a comparison with model calculations. The measurement of white-beam XAA using characteristic radiation indicates the possibility of obtaining element-sensitive projections of the local atomic structure in more complex samples. PMID:21997909

  20. Fuzzy Logic-Supported Detection of Complex Geospatial Features in a Web Service Environment

    NASA Astrophysics Data System (ADS)

    He, L. L.; Di, L. P.; Yue, P.; Zhang, M. D.

    2013-10-01

    Spatial relations among simple features can be used to characterize complex geospatial features. These spatial relations are often represented using linguistic terms such as near, which have inherent vagueness and imprecision. Fuzzy logic can be used to modeling fuzziness of the terms. Once simple features are extracted from remote sensing imagery, degree of satisfaction of spatial relations among these simple features can be derived to detect complex features. The derivation process can be performed in a distributed service environment, which benefits Earth science society in the last decade. Workflow-based service can provide ondemand uncertainty-aware discovery of complex features in a distributed environment. A use case on the complex facility detection illustrates the applicability of the fuzzy logic-supported service-oriented approach.

  1. Earth analysis methods, subsurface feature detection methods, earth analysis devices, and articles of manufacture

    DOEpatents

    West, Phillip B.; Novascone, Stephen R.; Wright, Jerry P.

    2011-09-27

    Earth analysis methods, subsurface feature detection methods, earth analysis devices, and articles of manufacture are described. According to one embodiment, an earth analysis method includes engaging a device with the earth, analyzing the earth in a single substantially lineal direction using the device during the engaging, and providing information regarding a subsurface feature of the earth using the analysis.

  2. Earth analysis methods, subsurface feature detection methods, earth analysis devices, and articles of manufacture

    DOEpatents

    West, Phillip B [Idaho Falls, ID; Novascone, Stephen R [Idaho Falls, ID; Wright, Jerry P [Idaho Falls, ID

    2012-05-29

    Earth analysis methods, subsurface feature detection methods, earth analysis devices, and articles of manufacture are described. According to one embodiment, an earth analysis method includes engaging a device with the earth, analyzing the earth in a single substantially lineal direction using the device during the engaging, and providing information regarding a subsurface feature of the earth using the analysis.

  3. Specific absorption spectra of hemoglobin at different PO2 levels: potential noninvasive method to detect PO2 in tissues.

    PubMed

    Liu, Peipei; Zhu, Zhirong; Zeng, Changchun; Nie, Guang

    2012-12-01

    Hemoglobin (Hb), as one of main components of blood, has a unique quaternary structure. Its release of oxygen is controlled by oxygen partial pressure (PO2). We investigate the specific spectroscopic changes in Hb under different PO2 levels to optimize clinical methods of measuring tissue PO2. The transmissivity of Hb under different PO2 levels is measured with a UV/Vis fiber optic spectrometer. Its plotted absorption spectral curve shows two high absorption peaks at 540 and 576 nm and an absorption valley at 560 nm when PO2 is higher than 100 mm Hg. The two high absorption peaks decrease gradually with a decrease in PO2, whereas the absorption valley at 560 nm increases. When PO2 decreases to approximately 0 mm Hg, the two high absorption peaks disappear completely, while the absorption valley has a hypochromic shift (8 to 10 nm) and forms a specific high absorption peak at approximately 550 nm. The same phenomena can be observed in visible reflectance spectra of finger-tip microcirculation. Specific changes in extinction coefficient and absorption spectra of Hb occur along with variations in PO2, which could be used to explain pathological changes caused by tissue hypoxia and for early detection of oxygen deficiency diseases in clinical monitoring.

  4. Specific absorption spectra of hemoglobin at different PO2 levels: potential noninvasive method to detect PO2 in tissues

    NASA Astrophysics Data System (ADS)

    Liu, Peipei; Zhu, Zhirong; Zeng, Changchun; Nie, Guang

    2012-12-01

    Hemoglobin (Hb), as one of main components of blood, has a unique quaternary structure. Its release of oxygen is controlled by oxygen partial pressure (PO2). We investigate the specific spectroscopic changes in Hb under different PO2 levels to optimize clinical methods of measuring tissue PO2. The transmissivity of Hb under different PO2 levels is measured with a UV/Vis fiber optic spectrometer. Its plotted absorption spectral curve shows two high absorption peaks at 540 and 576 nm and an absorption valley at 560 nm when PO2 is higher than 100 mm Hg. The two high absorption peaks decrease gradually with a decrease in PO2, whereas the absorption valley at 560 nm increases. When PO2 decreases to approximately 0 mm Hg, the two high absorption peaks disappear completely, while the absorption valley has a hypochromic shift (8 to 10 nm) and forms a specific high absorption peak at approximately 550 nm. The same phenomena can be observed in visible reflectance spectra of finger-tip microcirculation. Specific changes in extinction coefficient and absorption spectra of Hb occur along with variations in PO2, which could be used to explain pathological changes caused by tissue hypoxia and for early detection of oxygen deficiency diseases in clinical monitoring.

  5. Integration of local and global features for anatomical object detection in ultrasound.

    PubMed

    Rahmatullah, Bahbibi; Papageorghiou, Aris T; Noble, J Alison

    2012-01-01

    The use of classifier-based object detection has found to be a promising approach in medical anatomy detection. In ultrasound images, the detection task is very challenging due to speckle, shadows and low contrast characteristic features. Typical detection algorithms that use purely intensity-based image features with an exhaustive scan of the image (sliding window approach) tend not to perform very well and incur a very high computational cost. The proposed approach in this paper achieves a significant improvement in detection rates while avoiding exhaustive scanning, thereby gaining a large increase in speed. Our approach uses the combination of local features from an intensity image and global features derived from a local phase-based image known as feature symmetry. The proposed approach has been applied to 2384 two-dimensional (2D) fetal ultrasound abdominal images for the detection of the stomach and the umbilical vein. The results presented show that it outperforms prior related work that uses only local or only global features.

  6. Computer-aided detection of lung nodules using outer surface features.

    PubMed

    Demir, Önder; Yılmaz Çamurcu, Ali

    2015-01-01

    In this study, a computer-aided detection (CAD) system was developed for the detection of lung nodules in computed tomography images. The CAD system consists of four phases, including two-dimensional and three-dimensional preprocessing phases. In the feature extraction phase, four different groups of features are extracted from volume of interests: morphological features, statistical and histogram features, statistical and histogram features of outer surface, and texture features of outer surface. The support vector machine algorithm is optimized using particle swarm optimization for classification. The CAD system provides 97.37% sensitivity, 86.38% selectivity, 88.97% accuracy and 2.7 false positive per scan using three groups of classification features. After the inclusion of outer surface texture features, classification results of the CAD system reaches 98.03% sensitivity, 87.71% selectivity, 90.12% accuracy and 2.45 false positive per scan. Experimental results demonstrate that outer surface texture features of nodule candidates are useful to increase sensitivity and decrease the number of false positives in the detection of lung nodules in computed tomography images.

  7. Cloud Detection Method Based on Feature Extraction in Remote Sensing Images

    NASA Astrophysics Data System (ADS)

    Changhui, Y.; Yuan, Y.; Minjing, M.; Menglu, Z.

    2013-05-01

    In remote sensing images, the existence of the clouds has a great impact on the image quality and subsequent image processing, as the images covered with clouds contain little useful information. Therefore, the detection and recognition of clouds is one of the major problems in the application of remote sensing images. Present there are two categories of method to cloud detection. One is setting spectrum thresholds based on the characteristics of the clouds to distinguish them. However, the instability and uncertainty of the practical clouds makes this kind of method complexity and weak adaptability. The other method adopts the features in the images to identify the clouds. Since there will be significant overlaps in some features of the clouds and grounds, the detection result is highly dependent on the effectiveness of the features. This paper presented a cloud detection method based on feature extraction for remote sensing images. At first, find out effective features through training pattern, the features are selected from gray, frequency and texture domains. The different features in the three domains of the training samples are calculated. Through the result of statistical analysis of all the features, the useful features are picked up to form a feature set. In concrete, the set includes three feature vectors, respectively, the gray feature vector constituted of average gray, variance, first-order difference, entropy and histogram, the frequency feature vector constituted of DCT high frequency coefficient and wavelet high frequency coefficient, and the texture feature vector constituted of the hybrid entropy and difference of the gray-gradient co-occurrence matrix and the image fractal dimension. Secondly, a thumbnail will be obtained by down sampling the original image and its features of gray, frequency and texture are computed. Last but not least, the cloud region will be judged by the comparison between the actual feature values and the thresholds

  8. Hydrazine detection limits in the cigarette smoke matrix using infrared tunable diode laser absorption spectroscopy.

    PubMed

    Plunkett, Susan; Parrish, Milton E; Shafer, Kenneth H; Shorter, Joanne H; Nelson, David D; Zahniser, Mark S

    2002-09-01

    Infrared absorption lines of hydrazine are broad and typically not baseline resolved, with line strengths approximately 100 times weaker than the more widely studied compound ammonia. Hardware and software improvements have been made to a two-color infrared tunable diode laser (IR-TDL) spectrometer in order to improve the limit of detection (LOD) of hydrazine (N2H4) in the cigarette smoke matrix. The detection limit in the smoke matrix was improved from 25 parts-per-million-by-volume (ppmv) to 4.2 ppmv using a 100 m pathlength cell with acquisition of background spectra immediately prior to each sample and 100 ms temporal resolution. This study did not detect hydrazine in cigarette smoke in the 964.4-964.9 cm(-1) spectral region, after mathematically subtracting the spectral contributions of ethylene, ammonia, carbon dioxide, methanol, acrolein, and acetaldehyde. These compounds are found in cigarette smoke and absorb in this spectral region. The LOD is limited by remaining spectral structure from unidentified smoke species. The pseudo random noise (root mean square) in the improved instrument was 2 x 10(-4) absorbance units (base e) which is equivalent to a 0.09 ppmv hydrazine gas sample in the multipass cell. This would correspond to a detection limit of 0.44 ppmv of hydrazine, given the dilution of the smoke by a factor of 5 by the sampling system. This is a factor of 10 less than the 4.2 ppmv detection limit for hydrazine in the smoke matrix, and indicates that the detection limit is primarily a result of the complexity of the matrix rather than the random noise of the TDL instrument.

  9. LC-IMS-MS Feature Finder. Detecting Multidimensional Liquid Chromatography, Ion Mobility, and Mass Spectrometry Features in Complex Datasets

    SciTech Connect

    Crowell, Kevin L.; Slysz, Gordon W.; Baker, Erin Shammel; Lamarche, Brian L.; Monroe, Matthew E.; Ibrahim, Yehia M.; Payne, Samuel H.; Anderson, Gordon A.; Smith, Richard D.

    2013-09-05

    We introduce a command line software application LC-IMS-MS Feature Finder that searches for molecular ion signatures in multidimensional liquid chromatography-ion mobility spectrometry-mass spectrometry (LC-IMS-MS) data by clustering deisotoped peaks with similar monoisotopic mass, charge state, LC elution time, and ion mobility drift time values. The software application includes an algorithm for detecting and quantifying co-eluting chemical species, including species that exist in multiple conformations that may have been separated in the IMS dimension.

  10. Robust Ground Target Detection by SAR and IR Sensor Fusion Using Adaboost-Based Feature Selection

    PubMed Central

    Kim, Sungho; Song, Woo-Jin; Kim, So-Hyun

    2016-01-01

    Long-range ground targets are difficult to detect in a noisy cluttered environment using either synthetic aperture radar (SAR) images or infrared (IR) images. SAR-based detectors can provide a high detection rate with a high false alarm rate to background scatter noise. IR-based approaches can detect hot targets but are affected strongly by the weather conditions. This paper proposes a novel target detection method by decision-level SAR and IR fusion using an Adaboost-based machine learning scheme to achieve a high detection rate and low false alarm rate. The proposed method consists of individual detection, registration, and fusion architecture. This paper presents a single framework of a SAR and IR target detection method using modified Boolean map visual theory (modBMVT) and feature-selection based fusion. Previous methods applied different algorithms to detect SAR and IR targets because of the different physical image characteristics. One method that is optimized for IR target detection produces unsuccessful results in SAR target detection. This study examined the image characteristics and proposed a unified SAR and IR target detection method by inserting a median local average filter (MLAF, pre-filter) and an asymmetric morphological closing filter (AMCF, post-filter) into the BMVT. The original BMVT was optimized to detect small infrared targets. The proposed modBMVT can remove the thermal and scatter noise by the MLAF and detect extended targets by attaching the AMCF after the BMVT. Heterogeneous SAR and IR images were registered automatically using the proposed RANdom SAmple Region Consensus (RANSARC)-based homography optimization after a brute-force correspondence search using the detected target centers and regions. The final targets were detected by feature-selection based sensor fusion using Adaboost. The proposed method showed good SAR and IR target detection performance through feature selection-based decision fusion on a synthetic database generated

  11. Robust Ground Target Detection by SAR and IR Sensor Fusion Using Adaboost-Based Feature Selection.

    PubMed

    Kim, Sungho; Song, Woo-Jin; Kim, So-Hyun

    2016-07-19

    Long-range ground targets are difficult to detect in a noisy cluttered environment using either synthetic aperture radar (SAR) images or infrared (IR) images. SAR-based detectors can provide a high detection rate with a high false alarm rate to background scatter noise. IR-based approaches can detect hot targets but are affected strongly by the weather conditions. This paper proposes a novel target detection method by decision-level SAR and IR fusion using an Adaboost-based machine learning scheme to achieve a high detection rate and low false alarm rate. The proposed method consists of individual detection, registration, and fusion architecture. This paper presents a single framework of a SAR and IR target detection method using modified Boolean map visual theory (modBMVT) and feature-selection based fusion. Previous methods applied different algorithms to detect SAR and IR targets because of the different physical image characteristics. One method that is optimized for IR target detection produces unsuccessful results in SAR target detection. This study examined the image characteristics and proposed a unified SAR and IR target detection method by inserting a median local average filter (MLAF, pre-filter) and an asymmetric morphological closing filter (AMCF, post-filter) into the BMVT. The original BMVT was optimized to detect small infrared targets. The proposed modBMVT can remove the thermal and scatter noise by the MLAF and detect extended targets by attaching the AMCF after the BMVT. Heterogeneous SAR and IR images were registered automatically using the proposed RANdom SAmple Region Consensus (RANSARC)-based homography optimization after a brute-force correspondence search using the detected target centers and regions. The final targets were detected by feature-selection based sensor fusion using Adaboost. The proposed method showed good SAR and IR target detection performance through feature selection-based decision fusion on a synthetic database generated

  12. Invisible ink mark detection in the visible spectrum using absorption difference.

    PubMed

    Lee, Joong; Kong, Seong G; Kang, Tae-Yi; Kim, Byounghyun; Jeon, Oc-Yeub

    2014-03-01

    One of popular techniques in gambling fraud involves the use of invisible ink marks printed on the back surface of playing cards. Such covert patterns are transparent in the visible spectrum and therefore invisible to unaided human eyes. Invisible patterns can be made visible with ultraviolet (UV) illumination or a CCD camera installed with an infrared (IR) filter depending on the type of ink materials used. Cheating gamers often wear contact lenses or eyeglasses made of IR or UV filters to recognize the secret marks on the playing cards. This paper presents an image processing technique to reveal invisible ink patterns in the visible spectrum without the aid of special equipment such as UV lighting or IR filters. A printed invisible ink pattern leaves a thin coating on the surface with different refractive index for different wavelengths of light, which results in color dispersion or absorption difference. The proposed method finds the differences of color components caused by absorption difference to detect invisible ink patterns on the surface. Experiment results show that the proposed scheme is effective for both UV-active and IR-active invisible ink materials.

  13. Detection of Emotional Faces: Salient Physical Features Guide Effective Visual Search

    ERIC Educational Resources Information Center

    Calvo, Manuel G.; Nummenmaa, Lauri

    2008-01-01

    In this study, the authors investigated how salient visual features capture attention and facilitate detection of emotional facial expressions. In a visual search task, a target emotional face (happy, disgusted, fearful, angry, sad, or surprised) was presented in an array of neutral faces. Faster detection of happy and, to a lesser extent,…

  14. Change detection in high resolution SAR images based on multiscale texture features

    NASA Astrophysics Data System (ADS)

    Wen, Caihuan; Gao, Ziqiang

    2011-12-01

    This paper studied on change detection algorithm of high resolution (HR) Synthetic Aperture Radar (SAR) images based on multi-scale texture features. Firstly, preprocessed multi-temporal Terra-SAR images were decomposed by 2-D dual tree complex wavelet transform (DT-CWT), and multi-scale texture features were extracted from those images. Then, log-ratio operation was utilized to get difference images, and the Bayes minimum error theory was used to extract change information from difference images. Lastly, precision assessment was done. Meanwhile, we compared with the result of method based on texture features extracted from gray-level cooccurrence matrix (GLCM). We had a conclusion that, change detection algorithm based on multi-scale texture features has a great more improvement, which proves an effective method to change detect of high spatial resolution SAR images.

  15. Shape and texture based novel features for automated juxtapleural nodule detection in lung CTs.

    PubMed

    Taşcı, Erdal; Uğur, Aybars

    2015-05-01

    Lung cancer is one of the types of cancer with highest mortality rate in the world. In case of early detection and diagnosis, the survival rate of patients significantly increases. In this study, a novel method and system that provides automatic detection of juxtapleural nodule pattern have been developed from cross-sectional images of lung CT (Computerized Tomography). Shape-based and both shape and texture based 7 features are contributed to the literature for lung nodules. System that we developed consists of six main stages called preprocessing, lung segmentation, detection of nodule candidate regions, feature extraction, feature selection (with five feature ranking criteria) and classification. LIDC dataset containing cross-sectional images of lung CT has been utilized, 1410 nodule candidate regions and 40 features have been extracted from 138 cross-sectional images for 24 patients. Experimental results for 10 classifiers are obtained and presented. Adding our derived features to known 33 features has increased nodule recognition performance from 0.9639 to 0.9679 AUC value on generalized linear model regression (GLMR) for 22 selected features and being reached one of the most successful results in the literature.

  16. A Light-Emitting Diode- (LED-) Based Absorption Sensor for Simultaneous Detection of Carbon Monoxide and Carbon Dioxide.

    PubMed

    Thurmond, Kyle; Loparo, Zachary; Partridge, William; Vasu, Subith S

    2016-06-01

    A sensor was developed for simultaneous measurements of carbon monoxide (CO) and carbon dioxide (CO2) fluctuations in internal combustion engine exhaust gases. This sensor utilizes low-cost and compact light-emitting diodes (LEDs) that emit in the 3-5 µm wavelength range. An affordable, fast response sensor that can measure these gases has a broad application that can lead to more efficient, fuel-flexible engines and regulation of harmful emissions. Light emission from LEDs is spectrally broader and more spatially divergent when compared to that of lasers, which presented many design challenges. Optical design studies addressed some of the non-ideal characteristics of the LED emissions. Measurements of CO and CO2 were conducted using their fundamental absorption bands centered at 4.7 µm and 4.3 µm, respectively, while a 3.6 µm reference LED was used to account for scattering losses (due to soot, window deposits, etc.) common to the three measurement LEDs. Instrument validation and calibration was performed using a laboratory flow cell and bottled-gas mixtures. The sensor was able to detect CO2 and CO concentration changes as small as 30 ppm and 400 ppm, respectively. Because of the many control and monitor species with infra-red absorption features, which can be measured using the strategy described, this work demonstrates proof of concept for a wider range of fast (250 Hz) and low-cost sensors for gas measurement and process monitoring.

  17. A light-emitting diode- (LED-) based absorption sensor for simultaneous detection of carbon monoxide and carbon dioxide

    SciTech Connect

    Thurmond, Kyle; Loparo, Zachary; Partridge, Jr., William P.; Vasu, Subith S.

    2016-04-18

    Here, a sensor was developed for simultaneous measurements of carbon monoxide (CO) and carbon dioxide (CO2) fluctuations in internal combustion engine exhaust gases. This sensor utilizes low-cost and compact light-emitting diodes (LEDs) that emit in the 3–5 µm wavelength range. An affordable, fast response sensor that can measure these gases has a broad application that can lead to more efficient, fuel-flexible engines and regulation of harmful emissions. Light emission from LEDs is spectrally broader and more spatially divergent when compared to that of lasers, which presented many design challenges. Optical design studies addressed some of the non-ideal characteristics of the LED emissions. Measurements of CO and CO2 were conducted using their fundamental absorption bands centered at 4.7 µm and 4.3 µm, respectively, while a 3.6 µm reference LED was used to account for scattering losses (due to soot, window deposits, etc.) common to the three measurement LEDs. Instrument validation and calibration was performed using a laboratory flow cell and bottled-gas mixtures. The sensor was able to detect CO2 and CO concentration changes as small as 30 ppm and 400 ppm, respectively. Because of the many control and monitor species with infra-red absorption features, which can be measured using the strategy described, this work demonstrates proof of concept for a wider range of fast (250 Hz) and low-cost sensors for gas measurement and process monitoring.

  18. Method of analyzing multiple sample simultaneously by detecting absorption and systems for use in such a method

    DOEpatents

    Yeung, Edward S.; Gong, Xiaoyi

    2004-09-07

    The present invention provides a method of analyzing multiple samples simultaneously by absorption detection. The method comprises: (i) providing a planar array of multiple containers, each of which contains a sample comprising at least one absorbing species, (ii) irradiating the planar array of multiple containers with a light source and (iii) detecting absorption of light with a detetion means that is in line with the light source at a distance of at leaat about 10 times a cross-sectional distance of a container in the planar array of multiple containers. The absorption of light by a sample indicates the presence of an absorbing species in it. The method can further comprise: (iv) measuring the amount of absorption of light detected in (iii) indicating the amount of the absorbing species in the sample. Also provided by the present invention is a system for use in the abov metho.The system comprises; (i) a light source comrnpising or consisting essentially of at leaat one wavelength of light, the absorption of which is to be detected, (ii) a planar array of multiple containers, and (iii) a detection means that is in line with the light source and is positioned in line with and parallel to the planar array of multiple contiainers at a distance of at least about 10 times a cross-sectional distance of a container.

  19. Detection, identification and mapping of iron anomalies in brain tissue using X-ray absorption spectroscopy

    SciTech Connect

    Mikhaylova, A.; Davidson, M.; Toastmann, H.; Channell, J.E.T.; Guyodo, Y.; Batich, C.; Dobson, J.

    2008-06-16

    This work describes a novel method for the detection, identification and mapping of anomalous iron compounds in mammalian brain tissue using X-ray absorption spectroscopy. We have located and identified individual iron anomalies in an avian tissue model associated with ferritin, biogenic magnetite and haemoglobin with a pixel resolution of less than 5 {micro}m. This technique represents a breakthrough in the study of both intra- and extra-cellular iron compounds in brain tissue. The potential for high-resolution iron mapping using microfocused X-ray beams has direct application to investigations of the location and structural form of iron compounds associated with human neurodegenerative disorders - a problem which has vexed researchers for 50 years.

  20. Broadband magnetometry by infrared-absorption detection of nitrogen-vacancy ensembles in diamond

    SciTech Connect

    Acosta, V. M.; Bauch, E.; Jarmola, A.; Zipp, L. J.; Ledbetter, M. P.; Budker, D.

    2010-10-25

    We demonstrate magnetometry by detection of the spin state of high-density nitrogen-vacancy ensembles in diamond using optical absorption at 1042 nm. With this technique, measurement contrast, and collection efficiency can approach unity, leading to an increase in magnetic sensitivity compared to the more common method of collecting red fluorescence. Working at 75 K with a sensor with effective volume 50x50x300 {mu}m{sup 3}, we project photon shot-noise limited sensitivity of 5 pT in one second of acquisition and bandwidth from dc to a few megahertz. Operation in a gradiometer configuration yields a noise floor of 7 nT{sub rms} at {approx}110 Hz in one second of acquisition.

  1. Detection of the transient PNO molecule by infrared laser absorption spectroscopy

    NASA Astrophysics Data System (ADS)

    Bell, I. S.; Hamilton, P. A.; Davies, P. B.

    The PNO molecule has been observed in the gas phase for the first time. Some 200 vibrationrotation transitions were detected in the 1760cm-1 region using infrared diode laser absorption spectroscopy in a long path cell. Most of the lines can be assigned to the (001)←(000) stretching fundamental and (011)←(010) hot band transitions. The fundamental band exhibits a perturbation at high rotational levels which leads to a unique assignment of the rotational numbering. The effective rotational constants determined are in good agreement with ab initio predictions and the band origin, 1756.64586(24)cm-1, is very close to the matrix value. A tentative rotational assignment of the hot band transitions has been made which gives a band origin of 1748.388cm-1.

  2. The relationship study between image features and detection probability based on psychology experiments

    NASA Astrophysics Data System (ADS)

    Lin, Wei; Chen, Yu-hua; Wang, Ji-yuan; Gao, Hong-sheng; Wang, Ji-jun; Su, Rong-hua; Mao, Wei

    2011-04-01

    Detection probability is an important index to represent and estimate target viability, which provides basis for target recognition and decision-making. But it will expend a mass of time and manpower to obtain detection probability in reality. At the same time, due to the different interpretation of personnel practice knowledge and experience, a great difference will often exist in the datum obtained. By means of studying the relationship between image features and perception quantity based on psychology experiments, the probability model has been established, in which the process is as following.Firstly, four image features have been extracted and quantified, which affect directly detection. Four feature similarity degrees between target and background were defined. Secondly, the relationship between single image feature similarity degree and perception quantity was set up based on psychological principle, and psychological experiments of target interpretation were designed which includes about five hundred people for interpretation and two hundred images. In order to reduce image features correlativity, a lot of artificial synthesis images have been made which include images with single brightness feature difference, images with single chromaticity feature difference, images with single texture feature difference and images with single shape feature difference. By analyzing and fitting a mass of experiments datum, the model quantitys have been determined. Finally, by applying statistical decision theory and experimental results, the relationship between perception quantity with target detection probability has been found. With the verification of a great deal of target interpretation in practice, the target detection probability can be obtained by the model quickly and objectively.

  3. Enhancement of the Feature Extraction Capability in Global Damage Detection Using Wavelet Theory

    NASA Technical Reports Server (NTRS)

    Saleeb, Atef F.; Ponnaluru, Gopi Krishna

    2006-01-01

    The main objective of this study is to assess the specific capabilities of the defect energy parameter technique for global damage detection developed by Saleeb and coworkers. The feature extraction is the most important capability in any damage-detection technique. Features are any parameters extracted from the processed measurement data in order to enhance damage detection. The damage feature extraction capability was studied extensively by analyzing various simulation results. The practical significance in structural health monitoring is that the detection at early stages of small-size defects is always desirable. The amount of changes in the structure's response due to these small defects was determined to show the needed level of accuracy in the experimental methods. The arrangement of fine/extensive sensor network to measure required data for the detection is an "unlimited" ability, but there is a difficulty to place extensive number of sensors on a structure. Therefore, an investigation was conducted using the measurements of coarse sensor network. The white and the pink noises, which cover most of the frequency ranges that are typically encountered in the many measuring devices used (e.g., accelerometers, strain gauges, etc.) are added to the displacements to investigate the effect of noisy measurements in the detection technique. The noisy displacements and the noisy damage parameter values are used to study the signal feature reconstruction using wavelets. The enhancement of the feature extraction capability was successfully achieved by the wavelet theory.

  4. Evidence for ultra-fast outflows in radio-quiet AGNs. I. Detection and statistical incidence of Fe K-shell absorption lines

    NASA Astrophysics Data System (ADS)

    Tombesi, F.; Cappi, M.; Reeves, J. N.; Palumbo, G. G. C.; Yaqoob, T.; Braito, V.; Dadina, M.

    2010-10-01

    Context. Blue-shifted Fe K absorption lines have been detected in recent years between 7 and 10 keV in the X-ray spectra of several radio-quiet AGNs. The derived blue-shifted velocities of the lines can often reach mildly relativistic values, up to 0.2-0.4c. These findings are important because they suggest the presence of a previously unknown massive and highly ionized absorbing material outflowing from their nuclei, possibly connected with accretion disk winds/outflows. Aims: The scope of the present work is to statistically quantify the parameters and incidence of the blue-shifted Fe K absorption lines through a uniform analysis on a large sample of radio-quiet AGNs. This allows us to assess their global detection significance and to overcome any possible publication bias. Methods: We performed a blind search for narrow absorption features at energies greater than 6.4 keV in a sample of 42 radio-quiet AGNs observed with XMM-Newton. A simple uniform model composed by an absorbed power-law plus Gaussian emission and absorption lines provided a good fit for all the data sets. We derived the absorption lines parameters and calculated their detailed detection significance making use of the classical F-test and extensive Monte Carlo simulations. Results: We detect 36 narrow absorption lines on a total of 101 XMM-Newton EPIC pn observations. The number of absorption lines at rest-frame energies higher than 7 keV is 22. Their global probability to be generated by random fluctuations is very low, less than 3 × 10-8, and their detection have been independently confirmed by a spectral analysis of the MOS data, with associated random probability <10-7. We identify the lines as Fe XXV and Fe XXVI K-shell resonant absorption. They are systematically blue-shifted, with a velocity distribution ranging from zero up to ~0.3c, with a peak and mean value at ~0.1c. We detect variability of the lines on both EWs and blue-shifted velocities among different XMM-Newton observations

  5. Robustness of chemometrics-based feature selection methods in early cancer detection and biomarker discovery.

    PubMed

    Lee, Hae Woo; Lawton, Carl; Na, Young Jeong; Yoon, Seongkyu

    2013-03-13

    In omics studies aimed at the early detection and diagnosis of cancer, bioinformatics tools play a significant role when analyzing high dimensional, complex datasets, as well as when identifying a small set of biomarkers. However, in many cases, there are ambiguities in the robustness and the consistency of the discovered biomarker sets, since the feature selection methods often lead to irreproducible results. To address this, both the stability and the classification power of several chemometrics-based feature selection algorithms were evaluated using the Monte Carlo sampling technique, aiming at finding the most suitable feature selection methods for early cancer detection and biomarker discovery. To this end, two data sets were analyzed, which comprised of MALDI-TOF-MS and LC/TOF-MS spectra measured on serum samples in order to diagnose ovarian cancer. Using these datasets, the stability and the classification power of multiple feature subsets found by different feature selection methods were quantified by varying either the number of selected features, or the number of samples in the training set, with special emphasis placed on the property of stability. The results show that high consistency does not necessarily guarantee high predictive power. In addition, differences in the stability, as well as agreement in feature lists between several feature selection methods, depend on several factors, such as the number of available samples, feature sizes, quality of the information in the dataset, etc. Among the tested methods, only the variable importance in projection (VIP)-based method shows complementary properties, providing both highly consistent and accurate subsets of features. In addition, successive projection analysis (SPA) was excellent with regards to maintaining high stability over a wide range of experimental conditions. The stability of several feature selection methods is highly variable, stressing the importance of making the proper choice among

  6. Performance Comparison of Feature Extraction Algorithms for Target Detection and Classification

    DTIC Science & Technology

    2013-01-01

    Succi, D. Clapp, R. Gampert, and G. Prado, “ Footstep detection and tracking,” Unattended Ground Sensor Technologies and Applications III, vol. 4393... Detection and Classification⋆ Soheil Bahrampour1 Asok Ray2 Soumalya Sarkar2 Thyagaraju Damarla3 Nasser M. Nasrabadi3 Keywords: Feature Extraction...rithm, symbolic dynamic filtering (SDF), is investigated for target detection and classification by using unmanned ground sensors (UGS). In SDF, sensor

  7. Exploration of available feature detection and identification systems and their performance on radiographs

    NASA Astrophysics Data System (ADS)

    Wantuch, Andrew C.; Vita, Joshua A.; Jimenez, Edward S.; Bray, Iliana E.

    2016-10-01

    Despite object detection, recognition, and identification being very active areas of computer vision research, many of the available tools to aid in these processes are designed with only photographs in mind. Although some algorithms used specifically for feature detection and identification may not take explicit advantage of the colors available in the image, they still under-perform on radiographs, which are grayscale images. We are especially interested in the robustness of these algorithms, specifically their performance on a preexisting database of X-ray radiographs in compressed JPEG form, with multiple ways of describing pixel information. We will review various aspects of the performance of available feature detection and identification systems, including MATLABs Computer Vision toolbox, VLFeat, and OpenCV on our non-ideal database. In the process, we will explore possible reasons for the algorithms' lessened ability to detect and identify features from the X-ray radiographs.

  8. Intensity-Stabilized Fast-Scanned Direct Absorption Spectroscopy Instrumentation Based on a Distributed Feedback Laser with Detection Sensitivity down to 4 × 10−6

    PubMed Central

    Zhao, Gang; Tan, Wei; Jia, Mengyuan; Hou, Jiajuan; Ma, Weiguang; Dong, Lei; Zhang, Lei; Feng, Xiaoxia; Wu, Xuechun; Yin, Wangbao; Xiao, Liantuan; Axner, Ove; Jia, Suotang

    2016-01-01

    A novel, intensity-stabilized, fast-scanned, direct absorption spectroscopy (IS-FS-DAS) instrumentation, based on a distributed feedback (DFB) diode laser, is developed. A fiber-coupled polarization rotator and a fiber-coupled polarizer are used to stabilize the intensity of the laser, which significantly reduces its relative intensity noise (RIN). The influence of white noise is reduced by fast scanning over the spectral feature (at 1 kHz), followed by averaging. By combining these two noise-reducing techniques, it is demonstrated that direct absorption spectroscopy (DAS) can be swiftly performed down to a limit of detection (LOD) (1σ) of 4 × 10−6, which opens up a number of new applications. PMID:27657082

  9. Textural feature selection for enhanced detection of stationary humans in through-the-wall radar imagery

    NASA Astrophysics Data System (ADS)

    Chaddad, A.; Ahmad, F.; Amin, M. G.; Sevigny, P.; DiFilippo, D.

    2014-05-01

    Feature-based methods have been recently considered in the literature for detection of stationary human targets in through-the-wall radar imagery. Specifically, textural features, such as contrast, correlation, energy, entropy, and homogeneity, have been extracted from gray-level co-occurrence matrices (GLCMs) to aid in discriminating the true targets from multipath ghosts and clutter that closely mimic the target in size and intensity. In this paper, we address the task of feature selection to identify the relevant subset of features in the GLCM domain, while discarding those that are either redundant or confusing, thereby improving the performance of feature-based scheme to distinguish between targets and ghosts/clutter. We apply a Decision Tree algorithm to find the optimal combination of co-occurrence based textural features for the problem at hand. We employ a K-Nearest Neighbor classifier to evaluate the performance of the optimal textural feature based scheme in terms of its target and ghost/clutter discrimination capability and use real-data collected with the vehicle-borne multi-channel through-the-wall radar imaging system by Defence Research and Development Canada. For the specific data analyzed, it is shown that the identified dominant features yield a higher classification accuracy, with lower number of false alarms and missed detections, compared to the full GLCM based feature set.

  10. Possible detection of a cyclotron resonance scattering feature in the X-ray pulsar 4U 1909+07

    SciTech Connect

    Jaisawal, Gaurava K.; Naik, Sachindra; Paul, Biswajit

    2013-12-10

    We present timing and broad band spectral studies of the high-mass X-ray binary pulsar 4U 1909+07 using data from Suzaku observations during 2010 November 2-3. The pulse period of the pulsar is estimated to be 604.11 ± 0.14 s. Pulsations are seen in the X-ray light curve up to ∼70 keV. The pulse profile is found to be strongly energy-dependent: a complex, multi-peaked structure at low energy becomes a simple single peak at higher energy. We found that the 1-70 keV pulse-averaged continuum can be fit by the sum of a blackbody and a partial covering Negative and Positive power law with Exponential cutoff model. A weak iron fluorescence emission line at 6.4 keV was detected in the spectrum. An absorption-like feature at ∼44 keV was clearly seen in the residuals of the spectral fitting, independent of the continuum model adopted. To check the possible presence of a cyclotron resonance scattering feature (CRSF) in the spectrum, we normalized the pulsar spectrum with the spectrum of the Crab Nebula. The resulting Crab ratio also showed a clear dip centered at ∼44 keV. We performed statistical tests on the residuals of the spectral fitting and also on the Crab spectral ratio to determine the significance of the absorption-like feature and identified it as a CRSF of the pulsar. We estimated the corresponding surface magnetic field of the pulsar to be 3.8 × 10{sup 12} G.

  11. Landmine detection with Bayesian cross-categorization on point-wise, contextual and spatial features

    NASA Astrophysics Data System (ADS)

    Léveillé, Jasmin; Yu, Ssu-Hsin; Gandhe, Avinash

    2016-05-01

    Recently developed feature extraction methods proposed in the explosive hazard detection community have yielded many features that potentially provide complementary information for explosive detection. Finding the right combination of features that is most effective in distinguishing targets from clutter, on the other hand, is extremely challenging due to a large number of potential features to explore. Furthermore, sensors employed for mine and buried explosive hazard detection are typically sensitive to environmental conditions such as soil properties and weather as well as other operating parameters. In this work, we applied Bayesian cross-categorization (CrossCat) to a heterogeneous set of features derived from electromagnetic induction (EMI) sensor time-series for purposes of buried explosive hazard detection. The set of features used here includes simple, point-wise measurements such as the overall magnitude of the EMI response, contextual information such as soil type, and a new feature consisting of spatially aggregated Discrete Spectra of Relaxation Frequencies (DSRFs). Previous work showed that the DSRF characterizes target properties with some invariance to orientation and position. We have developed a novel approach to aggregate point-wise DSRF estimates. The spatial aggregation is based on the Bag-of-Words (BoW) model found in the machine learning and computer vision literatures and aims to enhance the invariance properties of point-wise DSRF estimates. We considered various refinements to the BoW model for purpose of buried explosive hazard detection and tested their usefulness as part of a Bayesian cross-categorization framework on data collected from two different sites. The results show improved performance over classifiers using only point-wise features.

  12. Feature Selection and Classifier Parameters Estimation for EEG Signals Peak Detection Using Particle Swarm Optimization

    PubMed Central

    Adam, Asrul; Mohd Tumari, Mohd Zaidi; Mohamad, Mohd Saberi

    2014-01-01

    Electroencephalogram (EEG) signal peak detection is widely used in clinical applications. The peak point can be detected using several approaches, including time, frequency, time-frequency, and nonlinear domains depending on various peak features from several models. However, there is no study that provides the importance of every peak feature in contributing to a good and generalized model. In this study, feature selection and classifier parameters estimation based on particle swarm optimization (PSO) are proposed as a framework for peak detection on EEG signals in time domain analysis. Two versions of PSO are used in the study: (1) standard PSO and (2) random asynchronous particle swarm optimization (RA-PSO). The proposed framework tries to find the best combination of all the available features that offers good peak detection and a high classification rate from the results in the conducted experiments. The evaluation results indicate that the accuracy of the peak detection can be improved up to 99.90% and 98.59% for training and testing, respectively, as compared to the framework without feature selection adaptation. Additionally, the proposed framework based on RA-PSO offers a better and reliable classification rate as compared to standard PSO as it produces low variance model. PMID:25243236

  13. [The frequency features and application of edge detection differential operators in medical image].

    PubMed

    Wu, Jian; Ding, Hui; Wang, Guangzhi; Ding, Haishu; Zhou, Yiyi

    2005-02-01

    Edge detection is an absolutely necessary step in medical image processing, and the use of differential operators to detect edge is one of the most common and effective methods. In this paper are analyzed the frequency features of the Roberts operator, Prewitt operator, Sobel operator and Laplacian operator from the viewpoint of frequency domain, and it is proposed that the frequency features of the differential operators should be considered when differential operator is being used and/or constructed. Because edge detection operator is sensitive to the edge type, the appropriate operator should be adopted in different edge type detection. Finally, the importance and necessity of selecting edge detection operator are validated in the MRI image edge processing.

  14. Detection and Classification of Cancer from Microscopic Biopsy Images Using Clinically Significant and Biologically Interpretable Features

    PubMed Central

    Kumar, Rajesh; Srivastava, Subodh

    2015-01-01

    A framework for automated detection and classification of cancer from microscopic biopsy images using clinically significant and biologically interpretable features is proposed and examined. The various stages involved in the proposed methodology include enhancement of microscopic images, segmentation of background cells, features extraction, and finally the classification. An appropriate and efficient method is employed in each of the design steps of the proposed framework after making a comparative analysis of commonly used method in each category. For highlighting the details of the tissue and structures, the contrast limited adaptive histogram equalization approach is used. For the segmentation of background cells, k-means segmentation algorithm is used because it performs better in comparison to other commonly used segmentation methods. In feature extraction phase, it is proposed to extract various biologically interpretable and clinically significant shapes as well as morphology based features from the segmented images. These include gray level texture features, color based features, color gray level texture features, Law's Texture Energy based features, Tamura's features, and wavelet features. Finally, the K-nearest neighborhood method is used for classification of images into normal and cancerous categories because it is performing better in comparison to other commonly used methods for this application. The performance of the proposed framework is evaluated using well-known parameters for four fundamental tissues (connective, epithelial, muscular, and nervous) of randomly selected 1000 microscopic biopsy images. PMID:27006938

  15. Detection of Harbours from High Resolution Remote Sensing Imagery via Saliency Analysis and Feature Learning

    NASA Astrophysics Data System (ADS)

    Wang, Yetianjian; Pan, Li; Wang, Dagang; Kang, Yifei

    2016-06-01

    Harbours are very important objects in civil and military fields. To detect them from high resolution remote sensing imagery is important in various fields and also a challenging task. Traditional methods of detecting harbours mainly focus on the segmentation of water and land and the manual selection of knowledge. They do not make enough use of other features of remote sensing imagery and often fail to describe the harbours completely. In order to improve the detection, a new method is proposed. First, the image is transformed to Hue, Saturation, Value (HSV) colour space and saliency analysis is processed via the generation and enhancement of the co-occurrence histogram to help detect and locate the regions of interest (ROIs) that is salient and may be parts of the harbour. Next, SIFT features are extracted and feature learning is processed to help represent the ROIs. Then, by using classified feature of the harbour, a classifier is trained and used to check the ROIs to find whether they belong to the harbour. Finally, if the ROIs belong to the harbour, a minimum bounding rectangle is formed to include all the harbour ROIs and detect and locate the harbour. The experiment on high resolution remote sensing imagery shows that the proposed method performs better than other methods in precision of classifying ROIs and accuracy of completely detecting and locating harbours.

  16. GridMass: a fast two-dimensional feature detection method for LC/MS.

    PubMed

    Treviño, Victor; Yañez-Garza, Irma-Luz; Rodriguez-López, Carlos E; Urrea-López, Rafael; Garza-Rodriguez, Maria-Lourdes; Barrera-Saldaña, Hugo-Alberto; Tamez-Peña, José G; Winkler, Robert; Díaz de-la-Garza, Rocío-Isabel

    2015-01-01

    One of the initial and critical procedures for the analysis of metabolomics data using liquid chromatography and mass spectrometry is feature detection. Feature detection is the process to detect boundaries of the mass surface from raw data. It consists of detected abundances arranged in a two-dimensional (2D) matrix of mass/charge and elution time. MZmine 2 is one of the leading software environments that provide a full analysis pipeline for these data. However, the feature detection algorithms provided in MZmine 2 are based mainly on the analysis of one-dimension at a time. We propose GridMass, an efficient algorithm for 2D feature detection. The algorithm is based on landing probes across the chromatographic space that are moved to find local maxima providing accurate boundary estimations. We tested GridMass on a controlled marker experiment, on plasma samples, on plant fruits, and in a proteome sample. Compared with other algorithms, GridMass is faster and may achieve comparable or better sensitivity and specificity. As a proof of concept, GridMass has been implemented in Java under the MZmine 2 environment and is available at http://www.bioinformatica.mty.itesm.mx/GridMass and MASSyPup. It has also been submitted to the MZmine 2 developing community.

  17. Multipolarimetric SAR image change detection based on multiscale feature-level fusion

    NASA Astrophysics Data System (ADS)

    Sun, X.; Zhang, J.; Zhai, L.

    2015-06-01

    Many methodologies of change detection have been discussed in the literature, but most of them are tested on only optical images or traditional synthetic-aperture radar (SAR) images. Few studies have investigated multipolarimetric SAR image change detection. In this study, we presented a type of multipolarimetric SAR image change detection approach based on nonsubsampled contourlet transform and multiscale feature-level fusion techniques. In this approach, Instead of denoising an image in advance, the nonsubsampled contourlet transform multiscale decomposition was used to reduce the effect of speckle noise by processing only the low-frequency sub-band coefficients of the decomposed image, and the multiscale feature-level fusion technique was employed to integrate the rich information obtained from various polarization images. Because SAR image information is dependent on scale, a multiscale multipolarimetric feature-level fusion strategy is introduced into the change detection to improve change detection precision; this feature-level fusion can not only achieve complementation of information with different polarizations and on different scales, but also has better robustness against noise. Compared with PCA methods, the proposed method constructs better differential images, resulting in higher change detection precision.

  18. Detection of Glucose with Atomic Absorption Spectroscopy by Using Oligonucleotide Functionalized Gold Nanoparticle.

    PubMed

    Zhang, Hong; Yan, Honglian; Ling, Liansheng

    2016-06-01

    A novel method for the detection of glucose was established with atomic absorption spectroscopy by using the label of gold nanoparticle (AuNP). Silver-coated glass assembled with oligonucleotide 5'-SH-T12-AGA CAA GAG AGG-3' (Oligo 1) was acted as separation probe, oligonucleotide 5'-CAA CAG AGA ACG-T12-SH-3' modified gold nanoparticle (AuNP-Oligo 2) was acted as signal-reporting probe. Oligonucleotide 5'-CGT TCT CTG TTG CCT CTC TTG TCT-3' (Oligo 3) could hybridize with Oligo 1 on the surface of silver-coated glass and AuNP-Oligo 2, and free AuNP-Oligo 2 could be removed by rinsing with buffer. Hence the concentration of Oligo 3 was transformed into the concentration of gold element. In addition, Oligo 3 could be cleaved into DNA fragments by glucose, glucose oxidase and Fe(2+)-EDTA through Fenton reaction. Thereby the concentration of glucose could be transformed to the absorbance of gold element. Under the optimum conditions, the integrated absorbance decreased proportionally to the concentration of glucose over the range from 50.0 μM to 1.0 mM with a detection limit of 40.0 μM. Moreover, satisfactory result was obtained when the assay was used to determinate glucose in human serum.

  19. Detection of obstacles on runway using Ego-Motion compensation and tracking of significant features

    NASA Technical Reports Server (NTRS)

    Kasturi, Rangachar (Principal Investigator); Camps, Octavia (Principal Investigator); Gandhi, Tarak; Devadiga, Sadashiva

    1996-01-01

    This report describes a method for obstacle detection on a runway for autonomous navigation and landing of an aircraft. Detection is done in the presence of extraneous features such as tiremarks. Suitable features are extracted from the image and warping using approximately known camera and plane parameters is performed in order to compensate ego-motion as far as possible. Residual disparity after warping is estimated using an optical flow algorithm. Features are tracked from frame to frame so as to obtain more reliable estimates of their motion. Corrections are made to motion parameters with the residual disparities using a robust method, and features having large residual disparities are signaled as obstacles. Sensitivity analysis of the procedure is also studied. Nelson's optical flow constraint is proposed to separate moving obstacles from stationary ones. A Bayesian framework is used at every stage so that the confidence in the estimates can be determined.

  20. A general purpose feature extractor for light detection and ranging data.

    PubMed

    Li, Yangming; Olson, Edwin B

    2010-01-01

    Feature extraction is a central step of processing Light Detection and Ranging (LIDAR) data. Existing detectors tend to exploit characteristics of specific environments: corners and lines from indoor (rectilinear) environments, and trees from outdoor environments. While these detectors work well in their intended environments, their performance in different environments can be poor. We describe a general purpose feature detector for both 2D and 3D LIDAR data that is applicable to virtually any environment. Our method adapts classic feature detection methods from the image processing literature, specifically the multi-scale Kanade-Tomasi corner detector. The resulting method is capable of identifying highly stable and repeatable features at a variety of spatial scales without knowledge of environment, and produces principled uncertainty estimates and corner descriptors at same time. We present results on both software simulation and standard datasets, including the 2D Victoria Park and Intel Research Center datasets, and the 3D MIT DARPA Urban Challenge dataset.

  1. First and second-order features for detection of masses in digital breast tomosynthesis

    NASA Astrophysics Data System (ADS)

    Samala, Ravi K.; Wei, Jun; Chan, Heang-Ping; Hadjiiski, Lubomir; Cha, Kenny; Helvie, Mark A.

    2016-03-01

    We are developing novel methods for prescreening of mass candidates in computer-aided detection (CAD) system for digital breast tomosynthesis (DBT). With IRB approval and written informed consent, 186 views from 94 breasts were imaged using a GE GEN2 prototype DBT system. The data set was randomly separated into training and test sets by cases. Gradient field convergence features based on first-order features were used to select the initial set of mass candidates. Eigenvalues based on second-order features from the Hessian matrix were extracted for the mass candidate locations in the DBT volume. The features from the first- and second-order analysis form the feature vector that was input to a linear discriminant analysis (LDA) classifier to generate a candidate-likelihood score. The likelihood scores were ranked and the top N candidates were passed onto the subsequent detection steps. The improvement between using only first-order features and the combination of first and second-order features was analyzed using a rank-sensitivity plot. 3D objects were obtained with two-stage 3D clustering followed by active contour segmentation. Morphological, gradient field, and texture features were extracted and feature selection was performed using stepwise feature selection. A combination of LDA and rule-based classifiers was used for FP reduction. The LDA classifier output a masslikelihood score for each object that was used as a decision variable for FROC analysis. At breast-based sensitivities of 70% and 80%, prescreening using first-order and second-order features resulted in 0.7 and 1.0 FPs/DBT.

  2. Spectrum and Image Texture Features Analysis for Early Blight Disease Detection on Eggplant Leaves.

    PubMed

    Xie, Chuanqi; He, Yong

    2016-05-11

    This study investigated both spectrum and texture features for detecting early blight disease on eggplant leaves. Hyperspectral images for healthy and diseased samples were acquired covering the wavelengths from 380 to 1023 nm. Four gray images were identified according to the effective wavelengths (408, 535, 624 and 703 nm). Hyperspectral images were then converted into RGB, HSV and HLS images. Finally, eight texture features (mean, variance, homogeneity, contrast, dissimilarity, entropy, second moment and correlation) based on gray level co-occurrence matrix (GLCM) were extracted from gray images, RGB, HSV and HLS images, respectively. The dependent variables for healthy and diseased samples were set as 0 and 1. K-Nearest Neighbor (KNN) and AdaBoost classification models were established for detecting healthy and infected samples. All models obtained good results with the classification rates (CRs) over 88.46% in the testing sets. The results demonstrated that spectrum and texture features were effective for early blight disease detection on eggplant leaves.

  3. A new and fast image feature selection method for developing an optimal mammographic mass detection scheme

    PubMed Central

    Tan, Maxine; Pu, Jiantao; Zheng, Bin

    2014-01-01

    Purpose: Selecting optimal features from a large image feature pool remains a major challenge in developing computer-aided detection (CAD) schemes of medical images. The objective of this study is to investigate a new approach to significantly improve efficacy of image feature selection and classifier optimization in developing a CAD scheme of mammographic masses. Methods: An image dataset including 1600 regions of interest (ROIs) in which 800 are positive (depicting malignant masses) and 800 are negative (depicting CAD-generated false positive regions) was used in this study. After segmentation of each suspicious lesion by a multilayer topographic region growth algorithm, 271 features were computed in different feature categories including shape, texture, contrast, isodensity, spiculation, local topological features, as well as the features related to the presence and location of fat and calcifications. Besides computing features from the original images, the authors also computed new texture features from the dilated lesion segments. In order to select optimal features from this initial feature pool and build a highly performing classifier, the authors examined and compared four feature selection methods to optimize an artificial neural network (ANN) based classifier, namely: (1) Phased Searching with NEAT in a Time-Scaled Framework, (2) A sequential floating forward selection (SFFS) method, (3) A genetic algorithm (GA), and (4) A sequential forward selection (SFS) method. Performances of the four approaches were assessed using a tenfold cross validation method. Results: Among these four methods, SFFS has highest efficacy, which takes 3%–5% of computational time as compared to GA approach, and yields the highest performance level with the area under a receiver operating characteristic curve (AUC) = 0.864 ± 0.034. The results also demonstrated that except using GA, including the new texture features computed from the dilated mass segments improved the AUC

  4. Object-Based Analysis of LIDAR Geometric Features for Vegetation Detection in Shaded Areas

    NASA Astrophysics Data System (ADS)

    Lin, Yu-Ching; Lin, ChinSu; Tsai, Ming-Da; Lin, Chun-Lin

    2016-06-01

    The extraction of land cover information from remote sensing data is a complex process. Spectral information has been widely utilized in classifying remote sensing images. However, shadows limit the use of multispectral images because they result in loss of spectral radiometric information. In addition, true reflectance may be underestimated in shaded areas. In land cover classification, shaded areas are often left unclassified or simply assigned as a shadow class. Vegetation indices from remote sensing measurement are radiation-based measurements computed through spectral combination. They indicate vegetation properties and play an important role in remote sensing of forests. Airborne light detection and ranging (LiDAR) technology is an active remote sensing technique that produces a true orthophoto at a single wavelength. This study investigated three types of geometric lidar features where NDVI values fail to represent meaningful forest information. The three features include echo width, normalized eigenvalue, and standard deviation of the unit weight observation of the plane adjustment, and they can be derived from waveform data and discrete point clouds. Various feature combinations were carried out to evaluate the compensation of the three lidar features to vegetation detection in shaded areas. Echo width was found to outperform the other two features. Furthermore, surface characteristics estimated by echo width were similar to that by normalized eigenvalues. Compared to the combination of only NDVI and mean height difference, those including one of the three features had a positive effect on the detection of vegetation class.

  5. Automatic detection of suspicious behavior of pickpockets with track-based features in a shopping mall

    NASA Astrophysics Data System (ADS)

    Bouma, Henri; Baan, Jan; Burghouts, Gertjan J.; Eendebak, Pieter T.; van Huis, Jasper R.; Dijk, Judith; van Rest, Jeroen H. C.

    2014-10-01

    Proactive detection of incidents is required to decrease the cost of security incidents. This paper focusses on the automatic early detection of suspicious behavior of pickpockets with track-based features in a crowded shopping mall. Our method consists of several steps: pedestrian tracking, feature computation and pickpocket recognition. This is challenging because the environment is crowded, people move freely through areas which cannot be covered by a single camera, because the actual snatch is a subtle action, and because collaboration is complex social behavior. We carried out an experiment with more than 20 validated pickpocket incidents. We used a top-down approach to translate expert knowledge in features and rules, and a bottom-up approach to learn discriminating patterns with a classifier. The classifier was used to separate the pickpockets from normal passers-by who are shopping in the mall. We performed a cross validation to train and evaluate our system. In this paper, we describe our method, identify the most valuable features, and analyze the results that were obtained in the experiment. We estimate the quality of these features and the performance of automatic detection of (collaborating) pickpockets. The results show that many of the pickpockets can be detected at a low false alarm rate.

  6. Computer-aided diagnosis in CT colonography: detection of polyps based on geometric and texture features

    NASA Astrophysics Data System (ADS)

    Yoshida, Hiroyuki; Naeppi, Janne J.; Frimmel, Hans; Dachman, Abraham H.

    2002-05-01

    A computer-aided diagnosis scheme for the detection of colonic polyps in CT colonography has been developed, and its performance has been assessed based on clinical cases with colonoscopy-confirmed polyps. In the scheme, the colon was automatically segmented by use of knowledge-guided segmentation from 3-dimensional isotropic volumes reconstructed from axial CT slices in CT colonography. Polyp candidates are detected by first computing of 3-dimensional geometric features that characterize polyps, and then segmenting of connected components corresponding to suspicious regions by hysteresis thresholding and fuzzy clustering based on these geometric features. False-positive detections are reduced by computation of 3-dimensional texture features characterizing the internal structures of the polyp candidates, followed by application of discriminant analysis to the feature space generated by the geometric and texture features. We applied our scheme to 43 CT colonographic cases with cleansed colon, including 12 polyps larger than 5 mm. In a by-dataset analysis, the CAD scheme yielded a sensitivity of 95% with 1.2 false positives per data set. The false negative was one of the two polyps in a single patient. Consequently, in by-patient analysis, our method yielded 100% sensitivity with 2.0 false positives per patient. The results indicate that our CAD scheme has the potential to detect clinically important polyp cases with a high sensitivity and a relatively low false-positive rate.

  7. Automated retrieval of cloud and aerosol properties from the ARM Raman lidar, part 1: feature detection

    SciTech Connect

    Thorsen, Tyler J.; Fu, Qiang; Newsom, Rob K.; Turner, David D.; Comstock, Jennifer M.

    2015-11-01

    A Feature detection and EXtinction retrieval (FEX) algorithm for the Atmospheric Radiation Measurement (ARM) program’s Raman lidar (RL) has been developed. Presented here is part 1 of the FEX algorithm: the detection of features including both clouds and aerosols. The approach of FEX is to use multiple quantities— scattering ratios derived using elastic and nitro-gen channel signals from two fields of view, the scattering ratio derived using only the elastic channel, and the total volume depolarization ratio— to identify features using range-dependent detection thresholds. FEX is designed to be context-sensitive with thresholds determined for each profile by calculating the expected clear-sky signal and noise. The use of multiple quantities pro-vides complementary depictions of cloud and aerosol locations and allows for consistency checks to improve the accuracy of the feature mask. The depolarization ratio is shown to be particularly effective at detecting optically-thin features containing non-spherical particles such as cirrus clouds. Improve-ments over the existing ARM RL cloud mask are shown. The performance of FEX is validated against a collocated micropulse lidar and observations from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite over the ARM Darwin, Australia site. While we focus on a specific lidar system, the FEX framework presented here is suitable for other Raman or high spectral resolution lidars.

  8. The use of linear feature detection to investigate thematic mapper data performance and processing

    NASA Technical Reports Server (NTRS)

    Gurney, C. M.

    1983-01-01

    The geometric and radiometric characteristics of thematic mapper data through analysis of linear features in the data are investigated. The particular aspects considered are: (1) thematic mapper ground IFOV; (2) radiometric contrast between linear features and background; (3) precision of system geometric correction; (4) band-to-band registration; and (5) potential utility of TM data for linear feature detection especially as compared to MSS data. It is shown that TM data may be used to estimate TM pixel size and to illustrate band-band mis-registration. Further, the geometry and radiometry of the data are sufficiently precise to allow accurate estimation of the widths of linear features. In optimum conditions features one quarter of a pixel in width may be accurately measured. These results have considerable potential for applications for hydrological and topographic mapping.

  9. Change Detection in Uav Video Mosaics Combining a Feature Based Approach and Extended Image Differencing

    NASA Astrophysics Data System (ADS)

    Saur, Günter; Krüger, Wolfgang

    2016-06-01

    Change detection is an important task when using unmanned aerial vehicles (UAV) for video surveillance. We address changes of short time scale using observations in time distances of a few hours. Each observation (previous and current) is a short video sequence acquired by UAV in near-Nadir view. Relevant changes are, e.g., recently parked or moved vehicles. Examples for non-relevant changes are parallaxes caused by 3D structures of the scene, shadow and illumination changes, and compression or transmission artifacts. In this paper we present (1) a new feature based approach to change detection, (2) a combination with extended image differencing (Saur et al., 2014), and (3) the application to video sequences using temporal filtering. In the feature based approach, information about local image features, e.g., corners, is extracted in both images. The label "new object" is generated at image points, where features occur in the current image and no or weaker features are present in the previous image. The label "vanished object" corresponds to missing or weaker features in the current image and present features in the previous image. This leads to two "directed" change masks and differs from image differencing where only one "undirected" change mask is extracted which combines both label types to the single label "changed object". The combination of both algorithms is performed by merging the change masks of both approaches. A color mask showing the different contributions is used for visual inspection by a human image interpreter.

  10. A Solitary Feature-based Lung Nodule Detection Approach for Chest X-Ray Radiographs.

    PubMed

    Li, Xuechen; Shen, Linlin; Luo, Suhuai

    2017-01-31

    Lung cancer is one of the most deadly diseases. It has a high death rate and its incidence rate has been increasing all over the world. Lung cancer appears as a solitary nodule in chest x-ray radiograph (CXR). Therefore, lung nodule detection in CXR could have a significant impact on early detection of lung cancer. Radiologists define a lung nodule in chest x-ray radiographs as "solitary white nodule-like blob". However, the solitary feature has not been employed for lung nodule detection before. In this paper, a solitary feature-based lung nodule detection method was proposed. We employed stationary wavelet transform and convergence index filter to extract the texture features and used AdaBoost to generate white nodule-likeness map. A solitary feature was defined to evaluate the isolation degree of candidates. Both the isolation degree and the white nodule-likeness were used as final evaluation of lung nodule candidates. The proposed method shows better performance and robustness than those reported in previous research. More than 80% and 93% of lung nodules in the lung field in the JSRT database were detected when the false positives per image was two and five, respectively. The proposed approach has the potential of being used in clinical practice.

  11. Real-time face detection and lip feature extraction using field-programmable gate arrays.

    PubMed

    Nguyen, Duy; Halupka, David; Aarabi, Parham; Sheikholeslami, Ali

    2006-08-01

    This paper proposes a new technique for face detection and lip feature extraction. A real-time field-programmable gate array (FPGA) implementation of the two proposed techniques is also presented. Face detection is based on a naive Bayes classifier that classifies an edge-extracted representation of an image. Using edge representation significantly reduces the model's size to only 5184 B, which is 2417 times smaller than a comparable statistical modeling technique, while achieving an 86.6% correct detection rate under various lighting conditions. Lip feature extraction uses the contrast around the lip contour to extract the height and width of the mouth, metrics that are useful for speech filtering. The proposed FPGA system occupies only 15050 logic cells, or about six times less than a current comparable FPGA face detection system.

  12. Systematic comparison of automated geological feature detection methods for impact craters

    NASA Astrophysics Data System (ADS)

    Vinogradova, T.; Mjolsness, E.

    2001-12-01

    Accurate, automated crater counts will be essential in extrapolating from existing Mars crater catalogs to much larger catalogs of impact craters in high-resolution orbital imagery for use in relative dating of surfaces in such imagery. Once validated, automatic methods for performing crater counts could be integrated into tools such as the Planetary Image Atlas, which is designed to be a convenient interface through which a user can search for, display, and download images and other ancillary data for planetary Missions, and the Diamond Eye image mining system. Here we report on preliminary computational experiments in using a trainable feature detection algorithm [Burl et al. 2001] to detect craters in real and simulated Mars orbital imagery, and to derive approximate impact crater counts for geological use. In these experiments, we consider two uses of the trainable feature detector: first, directly as a crater detector, and second, as two detectors for sunlit and shadowed inner walls of craters which can then be assembled into a single crater detection based on multiple pieces of evidence. For both of these methods, we consider two data sources: one consisting of real Viking Orbiter imagery of Mars with human expert-supplied ground truth labels, and the other consisting of computer generated renderings of simplified, synthetic cratered terrain with 100% accurate ground truth labels and known, controllable crater density. Each detector reports out a numeric detection ``likelihood'' for every candidate crater. This likelihood must then be thresholded to produce a detection decision. For each combination of two data sources (one natural and one synthetic) and two crater detection methods (whole-crater and parts-model), we vary image complexity and finally measure detection accuracy. Detection accuracy is measured by a Receiver Operator Characteristic (ROC) curve in which detection efficiency (the fraction of true craters detected) and purity (the fraction of

  13. Mitosis detection in breast cancer pathology images by combining handcrafted and convolutional neural network features

    PubMed Central

    Wang, Haibo; Cruz-Roa, Angel; Basavanhally, Ajay; Gilmore, Hannah; Shih, Natalie; Feldman, Mike; Tomaszewski, John; Gonzalez, Fabio; Madabhushi, Anant

    2014-01-01

    Abstract. Breast cancer (BCa) grading plays an important role in predicting disease aggressiveness and patient outcome. A key component of BCa grade is the mitotic count, which involves quantifying the number of cells in the process of dividing (i.e., undergoing mitosis) at a specific point in time. Currently, mitosis counting is done manually by a pathologist looking at multiple high power fields (HPFs) on a glass slide under a microscope, an extremely laborious and time consuming process. The development of computerized systems for automated detection of mitotic nuclei, while highly desirable, is confounded by the highly variable shape and appearance of mitoses. Existing methods use either handcrafted features that capture certain morphological, statistical, or textural attributes of mitoses or features learned with convolutional neural networks (CNN). Although handcrafted features are inspired by the domain and the particular application, the data-driven CNN models tend to be domain agnostic and attempt to learn additional feature bases that cannot be represented through any of the handcrafted features. On the other hand, CNN is computationally more complex and needs a large number of labeled training instances. Since handcrafted features attempt to model domain pertinent attributes and CNN approaches are largely supervised feature generation methods, there is an appeal in attempting to combine these two distinct classes of feature generation strategies to create an integrated set of attributes that can potentially outperform either class of feature extraction strategies individually. We present a cascaded approach for mitosis detection that intelligently combines a CNN model and handcrafted features (morphology, color, and texture features). By employing a light CNN model, the proposed approach is far less demanding computationally, and the cascaded strategy of combining handcrafted features and CNN-derived features enables the possibility of maximizing the

  14. Cascaded ensemble of convolutional neural networks and handcrafted features for mitosis detection

    NASA Astrophysics Data System (ADS)

    Wang, Haibo; Cruz-Roa, Angel; Basavanhally, Ajay; Gilmore, Hannah; Shih, Natalie; Feldman, Mike; Tomaszewski, John; Gonzalez, Fabio; Madabhushi, Anant

    2014-03-01

    Breast cancer (BCa) grading plays an important role in predicting disease aggressiveness and patient outcome. A key component of BCa grade is mitotic count, which involves quantifying the number of cells in the process of dividing (i.e. undergoing mitosis) at a specific point in time. Currently mitosis counting is done manually by a pathologist looking at multiple high power fields on a glass slide under a microscope, an extremely laborious and time consuming process. The development of computerized systems for automated detection of mitotic nuclei, while highly desirable, is confounded by the highly variable shape and appearance of mitoses. Existing methods use either handcrafted features that capture certain morphological, statistical or textural attributes of mitoses or features learned with convolutional neural networks (CNN). While handcrafted features are inspired by the domain and the particular application, the data-driven CNN models tend to be domain agnostic and attempt to learn additional feature bases that cannot be represented through any of the handcrafted features. On the other hand, CNN is computationally more complex and needs a large number of labeled training instances. Since handcrafted features attempt to model domain pertinent attributes and CNN approaches are largely unsupervised feature generation methods, there is an appeal to attempting to combine these two distinct classes of feature generation strategies to create an integrated set of attributes that can potentially outperform either class of feature extraction strategies individually. In this paper, we present a cascaded approach for mitosis detection that intelligently combines a CNN model and handcrafted features (morphology, color and texture features). By employing a light CNN model, the proposed approach is far less demanding computationally, and the cascaded strategy of combining handcrafted features and CNN-derived features enables the possibility of maximizing performance by

  15. FRaC: a feature-modeling approach for semi-supervised and unsupervised anomaly detection

    PubMed Central

    Brodley, Carla; Slonim, Donna

    2011-01-01

    Anomaly detection involves identifying rare data instances (anomalies) that come from a different class or distribution than the majority (which are simply called “normal” instances). Given a training set of only normal data, the semi-supervised anomaly detection task is to identify anomalies in the future. Good solutions to this task have applications in fraud and intrusion detection. The unsupervised anomaly detection task is different: Given unlabeled, mostly-normal data, identify the anomalies among them. Many real-world machine learning tasks, including many fraud and intrusion detection tasks, are unsupervised because it is impractical (or impossible) to verify all of the training data. We recently presented FRaC, a new approach for semi-supervised anomaly detection. FRaC is based on using normal instances to build an ensemble of feature models, and then identifying instances that disagree with those models as anomalous. In this paper, we investigate the behavior of FRaC experimentally and explain why FRaC is so successful. We also show that FRaC is a superior approach for the unsupervised as well as the semi-supervised anomaly detection task, compared to well-known state-of-the-art anomaly detection methods, LOF and one-class support vector machines, and to an existing feature-modeling approach. PMID:22639542

  16. Detection and clustering of features in aerial images by neuron network-based algorithm

    NASA Astrophysics Data System (ADS)

    Vozenilek, Vit

    2015-12-01

    The paper presents the algorithm for detection and clustering of feature in aerial photographs based on artificial neural networks. The presented approach is not focused on the detection of specific topographic features, but on the combination of general features analysis and their use for clustering and backward projection of clusters to aerial image. The basis of the algorithm is a calculation of the total error of the network and a change of weights of the network to minimize the error. A classic bipolar sigmoid was used for the activation function of the neurons and the basic method of backpropagation was used for learning. To verify that a set of features is able to represent the image content from the user's perspective, the web application was compiled (ASP.NET on the Microsoft .NET platform). The main achievements include the knowledge that man-made objects in aerial images can be successfully identified by detection of shapes and anomalies. It was also found that the appropriate combination of comprehensive features that describe the colors and selected shapes of individual areas can be useful for image analysis.

  17. Using Activity-Related Behavioural Features towards More Effective Automatic Stress Detection

    PubMed Central

    Giakoumis, Dimitris; Drosou, Anastasios; Cipresso, Pietro; Tzovaras, Dimitrios; Hassapis, George; Gaggioli, Andrea; Riva, Giuseppe

    2012-01-01

    This paper introduces activity-related behavioural features that can be automatically extracted from a computer system, with the aim to increase the effectiveness of automatic stress detection. The proposed features are based on processing of appropriate video and accelerometer recordings taken from the monitored subjects. For the purposes of the present study, an experiment was conducted that utilized a stress-induction protocol based on the stroop colour word test. Video, accelerometer and biosignal (Electrocardiogram and Galvanic Skin Response) recordings were collected from nineteen participants. Then, an explorative study was conducted by following a methodology mainly based on spatiotemporal descriptors (Motion History Images) that are extracted from video sequences. A large set of activity-related behavioural features, potentially useful for automatic stress detection, were proposed and examined. Experimental evaluation showed that several of these behavioural features significantly correlate to self-reported stress. Moreover, it was found that the use of the proposed features can significantly enhance the performance of typical automatic stress detection systems, commonly based on biosignal processing. PMID:23028461

  18. Confocal Light Absorption and Scattering Spectroscopic (CLASS) imaging: From cancer detection to sub-cellular function

    NASA Astrophysics Data System (ADS)

    Qiu, Le

    Light scattering spectroscopy (LSS), an optical technique that relates the spectroscopic properties of light elastically scattered by small particles to their size, refractive index and shape, has been recently successfully employed for sensing morphological and biochemical properties of epithelial tissues and cells in vivo. LSS does not require exogenous markers, is non-invasive, and, due to its multispectral nature, can sense biological structures well beyond the diffraction limit. All that makes LSS be a very good candidate to be used both in clinical medicine for in vivo detection of disease and in cell biology to monitor cell function on the organelle scale. Recently we developed two LSS-based imaging modalities: clinical Polarized LSS (PLSS) Endoscopic Technique for locating early pre-cancerous changes in GI tract and Confocal Light Absorption and Scattering Spectroscopic (CLASS) Microscopy for studying cells in vivo without exogenous markers. One important application of the clinical PLSS endoscopic instrument, a noncontact scanning imaging device compatible with the standard clinical endoscopes and capable of detecting dysplastic changes, is to serve as a guide for biopsy in Barrett's esophagus (BE). The instrument detects parallel and perpendicular components of the polarized light, backscattered from epithelial tissues, and determines characteristics of epithelial nuclei from the residual spectra. It also can find tissue oxygenation, hemoglobin content and other properties from the diffuse light component. By rapidly scanning esophagus the PLSS endoscopic instrument makes sure the entire BE portion is scanned and examined for the presence of dysplasia. CLASS microscopy, on the other hand, combines principles of light scattering spectroscopy (LSS) with confocal microscopy. Its main purpose is to image cells on organelle scale in vivo without the use of exogenous labels which may affect the cell function. The confocal geometry selects specific region and

  19. Characterizing Protein Complexes with UV absorption, Light Scattering, and Refractive Index Detection.

    NASA Astrophysics Data System (ADS)

    Trainoff, Steven

    2009-03-01

    Many modern pharmaceuticals and naturally occurring biomolecules consist of complexes of proteins and polyethylene glycol or carbohydrates. In the case of vaccine development, these complexes are often used to induce or amplify immune responses. For protein therapeutics they are used to modify solubility and function, or to control the rate of degradation and elimination of a drug from the body. Characterizing the stoichiometry of these complexes is an important industrial problem that presents a formidable challenge to analytical instrument designers. Traditional analytical methods, such as using florescent tagging, chemical assays, and mass spectrometry perturb the system so dramatically that the complexes are often destroyed or uncontrollably modified by the measurement. A solution to this problem consists of fractionating the samples and then measuring the fractions using sequential non-invasive detectors that are sensitive to different components of the complex. We present results using UV absorption, which is primarily sensitive to the protein fraction, Light Scattering, which measures the total weight average molar mass, and Refractive Index detection, which measures the net concentration. We also present a solution of the problem inter-detector band-broadening problem that has heretofore made this approach impractical. Presented will be instrumentation and an analysis method that overcome these obstacles and make this technique a reliable and robust way of non-invasively characterizing these industrially important compounds.

  20. Application of tunable diode laser absorption spectroscopy in the detection of oxygen

    NASA Astrophysics Data System (ADS)

    Zhou, Xin; Jin, Xing

    2015-10-01

    Most aircrafts is driven by chemic energy which is released in the combustion process. For improving the capability of engine and controlling the running on-time, the processes of fuel physics and chemistry need to be analysis by kinds of high quality sensor. In the research of designing and improving the processes of fuel physics and chemistry, the concentration, temperature and velocity of kinds of gas in the combustor need to be detected and measured. In addition, these engines and research equipments are always in the harsh environment of high temperature, high pressure and high speed. The harsh environment needs the sensor to be high reliability, well repetition, no cross- sensitivity between gases, and the traditional measurement system can't satisfy the metrical requirement well. Tunable diode laser absorption spectroscopy (TDLAS) analytic measurement technology can well satisfy the measurement in the harsh environment, which can support the whole measurement plan and high quality measurement system. Because the TDLAS sensor has the excellence of small bulk, light weight, high reliability and well specifically measurement, the TDLAS measurement technology has wide prospects. Different from most measurements, only a beam of laser can be pass through the measured environment by TDLAS, and the measurement equipment needn't be set in the harsh environment. So, the TDLAS equipment can't be interrupted by the measured equipment. The ability of subsistence in the harsh environment is very valuable, especially in the measurement on the subject of aerospace with environment of high speed, combustion and plasma. This paper focuses on the collecting the articles on the subject of oxygen detection of TDLAS. By analyzing the research and results of the articles, we conclude the central issues, difficulties and results. And we can get some instructive conclusions.

  1. Computer-aided detection of polyps in CT colonography based on geometric features

    NASA Astrophysics Data System (ADS)

    Yoshida, Hiroyuki; Masutani, Yoshitaka; MacEneaney, Peter; Dachman, Abraham H.

    2001-05-01

    CT colonography is a promising technique with a long-term goal to provide mass screening for colorectal carcinoma. Colorectal screening by CT colonography requires that the examination be cost-effective. The correct interpretation time is excessive for a screening test. Therefore, a computerized detection method capable of indicating regions of suspicion is attractive as a diagnostic aid for radiologists. We have developed a new CAD scheme for automated detection of polyps based on CT colonographic data sets. Our method characterizes polyps by geometric features of volumetric data including the volumetric shape index and curvedness. Polyps were detected by fuzzy clustering in a feature space generated by the feature values and spatial coordinates, followed by a rule-based test in the feature space. In an analysis of 41 patients, 9 of whom had at least one biopsy-proved polyp, our CAD scheme detected 100% of polyps with 2.5 false positives per patient. Our preliminary result indicates that the CAD scheme is potentially useful for highlighting areas of suspicion in the colon and, therefore, facilitates widespread screening by reducing the reading time substantially.

  2. Gain of the human dura in vivo and its effects on invasive brain signal feature detection.

    PubMed

    Torres Valderrama, Aldemar; Oostenveld, Robert; Vansteensel, Mariska J; Huiskamp, Geertjan M; Ramsey, Nicolas Franciscus

    2010-03-30

    Invasive brain signal recordings generally rely on bioelectrodes implanted on the cortex underneath the dura. Subdural recordings have strong advantages in terms of bandwidth, spatial resolution and signal quality. However, subdural electrodes also have the drawback of compromising the long-term stability of such implants and heighten the risk of infection. Epidurally implanted electrodes might provide a viable alternative to subdural electrodes, offering a compromise between signal quality and invasiveness. Determining the feasibility of epidural electrode implantation for e.g., clinical research, brain-computer interfacing (BCI) and cognitive experiments, requires the characterization of the electrical properties of the dura, and its effect on signal feature detection. In this paper we report measurements of brain signal attenuation by the human dura in vivo. In addition, we use signal detection theory to study how the presence of the dura between the sources and the recording electrodes affects signal power features in motor BCI experiments. For noise levels typical of clinical brain signal recording equipment, we observed no detrimental effects on signal feature detection due to the dura. Subdural recordings were found to be more robust with respect to increased instrumentation noise level as compared to their epidural counterpart nonetheless. Our findings suggest that epidural electrode implantation is a viable alternative to subdural implants from the feature detection viewpoint.

  3. Detection of object-based manipulation by the statistical features of object contour.

    PubMed

    Richao, Chen; Gaobo, Yang; Ningbo, Zhu

    2014-03-01

    Object-based manipulations, such as adding or removing objects for digital video, are usually malicious forgery operations. Compared with the conventional double MPEG compression or frame-based tampering, it makes more sense to detect these object-based manipulations because they might directly affect our understanding towards the video content. In this paper, a passive video forensics scheme is proposed for object-based forgery operations. After extracting the adjustable width areas around object boundary, several statistical features such as the moment features of detailed wavelet coefficients and the average gradient of each colour channel are obtained and input into support vector machine (SVM) as feature vectors for the classification of natural objects and forged ones. Experimental results on several videos sequence with static background show that the proposed approach can achieve an accuracy of correct detection from 70% to 95%.

  4. New feature extraction approach for epileptic EEG signal detection using time-frequency distributions.

    PubMed

    Guerrero-Mosquera, Carlos; Trigueros, Armando Malanda; Franco, Jorge Iriarte; Navia-Vázquez, Angel

    2010-04-01

    This paper describes a new method to identify seizures in electroencephalogram (EEG) signals using feature extraction in time-frequency distributions (TFDs). Particularly, the method extracts features from the Smoothed Pseudo Wigner-Ville distribution using tracks estimated from the McAulay-Quatieri sinusoidal model. The proposed features are the length, frequency, and energy of the principal track. We evaluate the proposed scheme using several datasets and we compute sensitivity, specificity, F-score, receiver operating characteristics (ROC) curve, and percentile bootstrap confidence to conclude that the proposed scheme generalizes well and is a suitable approach for automatic seizure detection at a moderate cost, also opening the possibility of formulating new criteria to detect, classify or analyze abnormal EEGs.

  5. Feature discrimination and detection probability in synthetic aperture radar imaging system

    NASA Technical Reports Server (NTRS)

    Lipes, R. G.; Butman, S. A.

    1977-01-01

    Images obtained using synthetic aperture radar (SAR) systems can only represent the intensities of resolution cells in the scene of interest probabilistically since radar receiver noise and Rayleigh scattering of the transmitted radiation are always present. Consequently, when features to be identified differ only by their contribution to the mean power of the radar return, discrimination can be treated by detection theory. In this paper, we develop a 'sufficient statistic' for discriminating between competing features and compare it with some suboptimal methods frequently used. Discrimination is measured by probability of detection error and depends on number of samples or 'looks', signal-to-noise ratio (SNR), and ratio of mean power returns from the competing features. Our results show discrimination and image quality rapidly saturate with SNR (very small improvement for SNR not less than 10 dB) but continue to improve with increasing number of looks.

  6. On the use of log-gabor features for subsurface object detection using ground penetrating radar

    NASA Astrophysics Data System (ADS)

    Harris, Samuel; Ho, K. C.; Zare, Alina

    2016-05-01

    regions with significant amount of metal debris. The challenge for the handheld GPR is to reduce the false alarm rate and limit the undesirable human operator effect. This paper proposes the use of log-Gabor features to improve the detection performance. In particular, we apply 36 log-Gabor filters to the B-scan of the GPR data in the time domain for the purpose to extract the edge behaviors of a prescreener alarm. The 36 log-Gabor filters cover the entire frequency plane with different bandwidths and orientations. The energy of each filter output forms an element of the feature vector and an SVM is trained to perform target vs non-target classification. Experimental results using the experimental hand held demonstrator data collected at a government site supports the increase in detection performance by using the log-Gabor features.

  7. Hybrid image representation learning model with invariant features for basal cell carcinoma detection

    NASA Astrophysics Data System (ADS)

    Arevalo, John; Cruz-Roa, Angel; González, Fabio A.

    2013-11-01

    This paper presents a novel method for basal-cell carcinoma detection, which combines state-of-the-art methods for unsupervised feature learning (UFL) and bag of features (BOF) representation. BOF, which is a form of representation learning, has shown a good performance in automatic histopathology image classi cation. In BOF, patches are usually represented using descriptors such as SIFT and DCT. We propose to use UFL to learn the patch representation itself. This is accomplished by applying a topographic UFL method (T-RICA), which automatically learns visual invariance properties of color, scale and rotation from an image collection. These learned features also reveals these visual properties associated to cancerous and healthy tissues and improves carcinoma detection results by 7% with respect to traditional autoencoders, and 6% with respect to standard DCT representations obtaining in average 92% in terms of F-score and 93% of balanced accuracy.

  8. Vehicle detection by means of stereo vision-based obstacles features extraction and monocular pattern analysis.

    PubMed

    Toulminet, Gwenaëlle; Bertozzi, Massimo; Mousset, Stéphane; Bensrhair, Abdelaziz; Broggi, Alberto

    2006-08-01

    This paper presents a stereo vision system for the detection and distance computation of a preceding vehicle. It is divided in two major steps. Initially, a stereo vision-based algorithm is used to extract relevant three-dimensional (3-D) features in the scene, these features are investigated further in order to select the ones that belong to vertical objects only and not to the road or background. These 3-D vertical features are then used as a starting point for preceding vehicle detection; by using a symmetry operator, a match against a simplified model of a rear vehicle's shape is performed using a monocular vision-based approach that allows the identification of a preceding vehicle. In addition, using the 3-D information previously extracted, an accurate distance computation is performed.

  9. Two-Dimensional UV Absorption Correlation Spectroscopy as a Method for the Detection of Thiamethoxam Residue in Tea

    NASA Astrophysics Data System (ADS)

    Zhang, J.; Zhao, Zh.; Wang, L.; Zhu, X.; Shen, L.; Yu, Y.

    2015-05-01

    Two-dimensional correlation spectroscopy (2D-COS) combined with UV absorption spectroscopy was evaluated as a technique for the identification of spectral regions associated with the residues of thiamethoxam in tea. There is only one absorption peak at 275 nm in the absorption spectrum of a mixture of thiamethoxam and tea, which is the absorption peak of tea. Based on 2D-COS, the absorption peak of thiamethoxam at 250 nm is extracted from the UV spectra of the mixture. To determine the residue of thiamethoxam in tea, 250 nm is selected as the measured wavelength, at which the fitting result is as follows: the residual sum of squares is 0.01375, standard deviation R2 is 0.99068, and F value is 426. Statistical analysis shows that there is a significant linear relationship between the concentration of thiamethoxam in tea and the absorbance at 250 nm in the UV spectra of the mixture. Moreover, the average prediction error is 0.0033 and the prediction variance is 0.1654, indicating good predictive result. Thus, the UV absorption spectrum can be used as a measurement method for rapid detection of thiamethoxam residues in tea.

  10. Absolute determination of charge-coupled device quantum detection efficiency using Si K-edge x-ray absorption fine structure

    SciTech Connect

    Dunn, J; Steel, A B

    2012-05-06

    We report a method to determine the quantum detection efficiency and the absorbing layers on a front-illuminated charge-coupled device (CCD). The CCD under study, as part of a crystal spectrometer, measures intense continuum x-ray emission from a picosecond laser-produced plasma and spectrally resolves the Si K-edge x-ray absorption fine structure features due to the electrode gate structure of the device. The CCD response across the Si K-edge shows a large discontinuity as well as a number of oscillations that are identified individually and uniquely from Si, SiO{sub 2}, and Si{sub 3}N{sub 4} layers. From the spectral analysis of the structure and K-edge discontinuity, the active layer thickness and the different absorbing layers thickness can be determined precisely. A precise CCD detection model from 0.2-10 keV can be deduced from this highly sensitive technique.

  11. Automatic Feature Detection, Description and Matching from Mobile Laser Scanning Data and Aerial Imagery

    NASA Astrophysics Data System (ADS)

    Hussnain, Zille; Oude Elberink, Sander; Vosselman, George

    2016-06-01

    In mobile laser scanning systems, the platform's position is measured by GNSS and IMU, which is often not reliable in urban areas. Consequently, derived Mobile Laser Scanning Point Cloud (MLSPC) lacks expected positioning reliability and accuracy. Many of the current solutions are either semi-automatic or unable to achieve pixel level accuracy. We propose an automatic feature extraction method which involves utilizing corresponding aerial images as a reference data set. The proposed method comprise three steps; image feature detection, description and matching between corresponding patches of nadir aerial and MLSPC ortho images. In the data pre-processing step the MLSPC is patch-wise cropped and converted to ortho images. Furthermore, each aerial image patch covering the area of the corresponding MLSPC patch is also cropped from the aerial image. For feature detection, we implemented an adaptive variant of Harris-operator to automatically detect corner feature points on the vertices of road markings. In feature description phase, we used the LATCH binary descriptor, which is robust to data from different sensors. For descriptor matching, we developed an outlier filtering technique, which exploits the arrangements of relative Euclidean-distances and angles between corresponding sets of feature points. We found that the positioning accuracy of the computed correspondence has achieved the pixel level accuracy, where the image resolution is 12cm. Furthermore, the developed approach is reliable when enough road markings are available in the data sets. We conclude that, in urban areas, the developed approach can reliably extract features necessary to improve the MLSPC accuracy to pixel level.

  12. Fast detection of covert visuospatial attention using hybrid N2pc and SSVEP features

    NASA Astrophysics Data System (ADS)

    Xu, Minpeng; Wang, Yijun; Nakanishi, Masaki; Wang, Yu-Te; Qi, Hongzhi; Jung, Tzyy-Ping; Ming, Dong

    2016-12-01

    Objective. Detecting the shift of covert visuospatial attention (CVSA) is vital for gaze-independent brain-computer interfaces (BCIs), which might be the only communication approach for severely disabled patients who cannot move their eyes. Although previous studies had demonstrated that it is feasible to use CVSA-related electroencephalography (EEG) features to control a BCI system, the communication speed remains very low. This study aims to improve the speed and accuracy of CVSA detection by fusing EEG features of N2pc and steady-state visual evoked potential (SSVEP). Approach. A new paradigm was designed to code the left and right CVSA with the N2pc and SSVEP features, which were then decoded by a classification strategy based on canonical correlation analysis. Eleven subjects were recruited to perform an offline experiment in this study. Temporal waves, amplitudes, and topographies for brain responses related to N2pc and SSVEP were analyzed. The classification accuracy derived from the hybrid EEG features (SSVEP and N2pc) was compared with those using the single EEG features (SSVEP or N2pc). Main results. The N2pc could be significantly enhanced under certain conditions of SSVEP modulations. The hybrid EEG features achieved significantly higher accuracy than the single features. It obtained an average accuracy of 72.9% by using a data length of 400 ms after the attention shift. Moreover, the average accuracy reached ˜80% (peak values above 90%) when using 2 s long data. Significance. The results indicate that the combination of N2pc and SSVEP is effective for fast detection of CVSA. The proposed method could be a promising approach for implementing a gaze-independent BCI.

  13. Computerized detection of unruptured aneurysms in MRA images: reduction of false positives using anatomical location features

    NASA Astrophysics Data System (ADS)

    Uchiyama, Yoshikazu; Gao, Xin; Hara, Takeshi; Fujita, Hiroshi; Ando, Hiromichi; Yamakawa, Hiroyasu; Asano, Takahiko; Kato, Hiroki; Iwama, Toru; Kanematsu, Masayuki; Hoshi, Hiroaki

    2008-03-01

    The detection of unruptured aneurysms is a major subject in magnetic resonance angiography (MRA). However, their accurate detection is often difficult because of the overlapping between the aneurysm and the adjacent vessels on maximum intensity projection images. The purpose of this study is to develop a computerized method for the detection of unruptured aneurysms in order to assist radiologists in image interpretation. The vessel regions were first segmented using gray-level thresholding and a region growing technique. The gradient concentration (GC) filter was then employed for the enhancement of the aneurysms. The initial candidates were identified in the GC image using a gray-level threshold. For the elimination of false positives (FPs), we determined shape features and an anatomical location feature. Finally, rule-based schemes and quadratic discriminant analysis were employed along with these features for distinguishing between the aneurysms and the FPs. The sensitivity for the detection of unruptured aneurysms was 90.0% with 1.52 FPs per patient. Our computerized scheme can be useful in assisting the radiologists in the detection of unruptured aneurysms in MRA images.

  14. Volume-based Feature Analysis of Mucosa for Automatic Initial Polyp Detection in Virtual Colonoscopy

    PubMed Central

    Wang, Su; Zhu, Hongbin; Lu, Hongbing; Liang, Zhengrong

    2009-01-01

    In this paper, we present a volume-based mucosa-based polyp candidate determination scheme for automatic polyp detection in computed colonography. Different from most of the existing computer-aided detection (CAD) methods where mucosa layer is a one-layer surface, a thick mucosa of 3-5 voxels wide fully reflecting partial volume effect is intentionally extracted, which excludes the direct applications of the traditional geometrical features. In order to address this dilemma, fast marching-based adaptive gradient/curvature and weighted integral curvature along normal directions (WICND) are developed for volume-based mucosa. In doing so, polyp candidates are optimally determined by computing and clustering these fast marching-based adaptive geometrical features. By testing on 52 patients datasets in which 26 patients were found with polyps of size 4-22 mm, both the locations and number of polyp candidates detected by WICND and previously developed linear integral curvature (LIC) were compared. The results were promising that WICND outperformed LIC mainly in two aspects: (1) the number of detected false positives was reduced from 706 to 132 on average, which significantly released our burden of machine learning in the feature space, and (2) both the sensitivity and accuracy of polyp detection have been slightly improved, especially for those polyps smaller than 5mm. PMID:19774204

  15. Glaucoma detection using novel optic disc localization, hybrid feature set and classification techniques.

    PubMed

    Akram, M Usman; Tariq, Anam; Khalid, Shehzad; Javed, M Younus; Abbas, Sarmad; Yasin, Ubaid Ullah

    2015-12-01

    Glaucoma is a chronic and irreversible neuro-degenerative disease in which the neuro-retinal nerve that connects the eye to the brain (optic nerve) is progressively damaged and patients suffer from vision loss and blindness. The timely detection and treatment of glaucoma is very crucial to save patient's vision. Computer aided diagnostic systems are used for automated detection of glaucoma that calculate cup to disc ratio from colored retinal images. In this article, we present a novel method for early and accurate detection of glaucoma. The proposed system consists of preprocessing, optic disc segmentation, extraction of features from optic disc region of interest and classification for detection of glaucoma. The main novelty of the proposed method lies in the formation of a feature vector which consists of spatial and spectral features along with cup to disc ratio, rim to disc ratio and modeling of a novel mediods based classier for accurate detection of glaucoma. The performance of the proposed system is tested using publicly available fundus image databases along with one locally gathered database. Experimental results using a variety of publicly available and local databases demonstrate the superiority of the proposed approach as compared to the competitors.

  16. Feature selection and definition for contours classification of thermograms in breast cancer detection

    NASA Astrophysics Data System (ADS)

    Jagodziński, Dariusz; Matysiewicz, Mateusz; Neumann, Łukasz; Nowak, Robert M.; Okuniewski, Rafał; Oleszkiewicz, Witold; Cichosz, Paweł

    2016-09-01

    This contribution introduces the method of cancer pathologies detection on breast skin temperature distribution images. The use of thermosensitive foils applied to the breasts skin allows to create thermograms, which displays the amount of infrared energy emitted by all breast cells. The significant foci of hyperthermia or inflammation are typical for cancer cells. That foci can be recognized on thermograms as a contours, which are the areas of higher temperature. Every contour can be converted to a feature set that describe it, using the raw, central, Hu, outline, Fourier and colour moments of image pixels processing. This paper defines also the new way of describing a set of contours through theirs neighbourhood relations. Contribution introduces moreover the way of ranking and selecting most relevant features. Authors used Neural Network with Gevrey`s concept and recursive feature elimination, to estimate feature importance.

  17. Computerized lung nodule detection using 3D feature extraction and learning based algorithms.

    PubMed

    Ozekes, Serhat; Osman, Onur

    2010-04-01

    In this paper, a Computer Aided Detection (CAD) system based on three-dimensional (3D) feature extraction is introduced to detect lung nodules. First, eight directional search was applied in order to extract regions of interests (ROIs). Then, 3D feature extraction was performed which includes 3D connected component labeling, straightness calculation, thickness calculation, determining the middle slice, vertical and horizontal widths calculation, regularity calculation, and calculation of vertical and horizontal black pixel ratios. To make a decision for each ROI, feed forward neural networks (NN), support vector machines (SVM), naive Bayes (NB) and logistic regression (LR) methods were used. These methods were trained and tested via k-fold cross validation, and results were compared. To test the performance of the proposed system, 11 cases, which were taken from Lung Image Database Consortium (LIDC) dataset, were used. ROC curves were given for all methods and 100% detection sensitivity was reached except naive Bayes.

  18. [Method of automatic detection of brain lesion based on wavelet feature vector].

    PubMed

    Fan, Ya; Liu, Wei; Feng, Huanqing

    2011-06-01

    A new method of automatic detection of brain lesion based on wavelet feature vector of CT images has been proposed in the present paper. Firstly, we created training samples by manually segmenting normal CT images into gray matter, white matter and cerebrospinal fluid sub images. Then, we obtained the cluster centers using FCM clustering algorithm. When detecting lesions, the CT images to be detected was automatically segmented into sub images, with a certain degree of over-segmenting allowed under the premise of ensuring accuracy as much as possible. Then we extended these sub images and extracted the features to compute the distances with the cluster centers and to determine whether they belonged to the three kinds of normal samples, or, otherwise, belonged to lesions. The proposed method was verified by experiments.

  19. Automatic solar feature detection using image processing and pattern recognition techniques

    NASA Astrophysics Data System (ADS)

    Qu, Ming

    The objective of the research in this dissertation is to develop a software system to automatically detect and characterize solar flares, filaments and Corona Mass Ejections (CMEs), the core of so-called solar activity. These tools will assist us to predict space weather caused by violent solar activity. Image processing and pattern recognition techniques are applied to this system. For automatic flare detection, the advanced pattern recognition techniques such as Multi-Layer Perceptron (MLP), Radial Basis Function (RBF), and Support Vector Machine (SVM) are used. By tracking the entire process of flares, the motion properties of two-ribbon flares are derived automatically. In the applications of the solar filament detection, the Stabilized Inverse Diffusion Equation (SIDE) is used to enhance and sharpen filaments; a new method for automatic threshold selection is proposed to extract filaments from background; an SVM classifier with nine input features is used to differentiate between sunspots and filaments. Once a filament is identified, morphological thinning, pruning, and adaptive edge linking methods are applied to determine filament properties. Furthermore, a filament matching method is proposed to detect filament disappearance. The automatic detection and characterization of flares and filaments have been successfully applied on Halpha full-disk images that are continuously obtained at Big Bear Solar Observatory (BBSO). For automatically detecting and classifying CMEs, the image enhancement, segmentation, and pattern recognition techniques are applied to Large Angle Spectrometric Coronagraph (LASCO) C2 and C3 images. The processed LASCO and BBSO images are saved to file archive, and the physical properties of detected solar features such as intensity and speed are recorded in our database. Researchers are able to access the solar feature database and analyze the solar data efficiently and effectively. The detection and characterization system greatly improves

  20. Blind Detection of Region Duplication Forgery Using Fractal Coding and Feature Matching.

    PubMed

    Jenadeleh, Mohsen; Ebrahimi Moghaddam, Mohsen

    2016-05-01

    Digital image forgery detection is important because of its wide use in applications such as medical diagnosis, legal investigations, and entertainment. Copy-move forgery is one of the famous techniques, which is used in region duplication. Many of the existing copy-move detection algorithms cannot effectively blind detect duplicated regions that are made by powerful image manipulation software like Photoshop. In this study, a new method is proposed for blind detecting manipulations in digital images based on modified fractal coding and feature vector matching. The proposed method not only detects typical copy-move forgery, but also finds multiple copied forgery regions for images that are subjected to rotation, scaling, reflection, and a mixture of these postprocessing operations. The proposed method is robust against tampered images undergoing attacks such as Gaussian blurring, contrast scaling, and brightness adjustment. The experimental results demonstrated the validity and efficiency of the method.

  1. EEG error potentials detection and classification using time-frequency features for robot reinforcement learning.

    PubMed

    Boubchir, Larbi; Touati, Youcef; Daachi, Boubaker; Chérif, Arab Ali

    2015-08-01

    In thought-based steering of robots, error potentials (ErrP) can appear when the action resulting from the brain-machine interface (BMI) classifier/controller does not correspond to the user's thought. Using the Steady State Visual Evoked Potentials (SSVEP) techniques, ErrP, which appear when a classification error occurs, are not easily recognizable by only examining the temporal or frequency characteristics of EEG signals. A supplementary classification process is therefore needed to identify them in order to stop the course of the action and back up to a recovery state. This paper presents a set of time-frequency (t-f) features for the detection and classification of EEG ErrP in extra-brain activities due to misclassification observed by a user exploiting non-invasive BMI and robot control in the task space. The proposed features are able to characterize and detect ErrP activities in the t-f domain. These features are derived from the information embedded in the t-f representation of EEG signals, and include the Instantaneous Frequency (IF), t-f information complexity, SVD information, energy concentration and sub-bands' energies. The experiment results on real EEG data show that the use of the proposed t-f features for detecting and classifying EEG ErrP achieved an overall classification accuracy up to 97% for 50 EEG segments using 2-class SVM classifier.

  2. Matching-range-constrained real-time loop closure detection with CNNs features.

    PubMed

    Bai, Dongdong; Wang, Chaoqun; Zhang, Bo; Yi, Xiaodong; Tang, Yuhua

    2016-01-01

    The loop closure detection (LCD) is an essential part of visual simultaneous localization and mapping systems (SLAM). LCD is capable of identifying and compensating the accumulation drift of localization algorithms to produce an consistent map if the loops are checked correctly. Deep convolutional neural networks (CNNs) have outperformed state-of-the-art solutions that use traditional hand-crafted features in many computer vision and pattern recognition applications. After the great success of CNNs, there has been much interest in applying CNNs features to robotic fields such as visual LCD. Some researchers focus on using a pre-trained CNNs model as a method of generating an image representation appropriate for visual loop closure detection in SLAM. However, there are many fundamental differences and challenges involved in character between simple computer vision applications and robotic applications. Firstly, the adjacent images in the dataset of loop closure detection might have more resemblance than the images that form the loop closure. Secondly, real-time performance is one of the most critical demands for robots. In this paper, we focus on making use of the feature generated by CNNs layers to implement LCD in real environment. In order to address the above challenges, we explicitly provide a value to limit the matching range of images to solve the first problem; meanwhile we get better results than state-of-the-art methods and improve the real-time performance using an efficient feature compression method.

  3. Solid waste bin level detection using gray level co-occurrence matrix feature extraction approach.

    PubMed

    Arebey, Maher; Hannan, M A; Begum, R A; Basri, Hassan

    2012-08-15

    This paper presents solid waste bin level detection and classification using gray level co-occurrence matrix (GLCM) feature extraction methods. GLCM parameters, such as displacement, d, quantization, G, and the number of textural features, are investigated to determine the best parameter values of the bin images. The parameter values and number of texture features are used to form the GLCM database. The most appropriate features collected from the GLCM are then used as inputs to the multi-layer perceptron (MLP) and the K-nearest neighbor (KNN) classifiers for bin image classification and grading. The classification and grading performance for DB1, DB2 and DB3 features were selected with both MLP and KNN classifiers. The results demonstrated that the KNN classifier, at KNN = 3, d = 1 and maximum G values, performs better than using the MLP classifier with the same database. Based on the results, this method has the potential to be used in solid waste bin level classification and grading to provide a robust solution for solid waste bin level detection, monitoring and management.

  4. The Physical Nature of the Sharp Spectral Feature at 7 keV Detected in 1H0707-495

    NASA Technical Reports Server (NTRS)

    Brandt, Niel

    2005-01-01

    XMM-Newton acquired data on the accepted target, 1H0707-495, on 2002 October 13 during revolution 0521. The observation was successful, with only about 5% data loss due to background flaring. We compared the data from this observation with earlier data taken on this Narrow-Line Seyfert 1 about two years before, performing interpretation studies in the context of the partial-covering model. Our second longer observation once again displays a sharp (< 200 eV) spectral drop above 7 keV. However, in comparison to the first observation, the edge depth and energy have changed significantly. In addition to changes in the edge parameters, the high-energy spectrum appears steeper. The changes in the high-energy spectrum can be adequately explained in terms of a partial-covering absorber out-flowing from the central region. The low-energy spectrum also shows significant long-term spectral variability, including (1) a substantial increase in the disk temperature, (2) detection of an approx. 0.9 keV emission feature, and (3) the presence of ionized absorption that was detected during the ASCA mission. The large increase in disk temperature, and the more modest rise in luminosity, can be understood if we consider a slim-disk model for 1H0707-495. In addition, the higher disk luminosity could be the driving force behind the outflow and the re-appearance of an ionized medium during the second XMM-Newton observation.

  5. Detection of Cardiac Abnormalities from Multilead ECG using Multiscale Phase Alternation Features.

    PubMed

    Tripathy, R K; Dandapat, S

    2016-06-01

    The cardiac activities such as the depolarization and the relaxation of atria and ventricles are observed in electrocardiogram (ECG). The changes in the morphological features of ECG are the symptoms of particular heart pathology. It is a cumbersome task for medical experts to visually identify any subtle changes in the morphological features during 24 hours of ECG recording. Therefore, the automated analysis of ECG signal is a need for accurate detection of cardiac abnormalities. In this paper, a novel method for automated detection of cardiac abnormalities from multilead ECG is proposed. The method uses multiscale phase alternation (PA) features of multilead ECG and two classifiers, k-nearest neighbor (KNN) and fuzzy KNN for classification of bundle branch block (BBB), myocardial infarction (MI), heart muscle defect (HMD) and healthy control (HC). The dual tree complex wavelet transform (DTCWT) is used to decompose the ECG signal of each lead into complex wavelet coefficients at different scales. The phase of the complex wavelet coefficients is computed and the PA values at each wavelet scale are used as features for detection and classification of cardiac abnormalities. A publicly available multilead ECG database (PTB database) is used for testing of the proposed method. The experimental results show that, the proposed multiscale PA features and the fuzzy KNN classifier have better performance for detection of cardiac abnormalities with sensitivity values of 78.12 %, 80.90 % and 94.31 % for BBB, HMD and MI classes. The sensitivity value of proposed method for MI class is compared with the state-of-art techniques from multilead ECG.

  6. Evaluation of ammonia absorption coefficients by photoacoustic spectroscopy for detection of ammonia levels in human breath

    NASA Astrophysics Data System (ADS)

    Dumitras, D. C.; Dutu, D. C.; Matei, C.; Cernat, R.; Banita, S.; Patachia, M.; Bratu, A. M.; Petrus, M.; Popa, C.

    2011-04-01

    Photoacoustic spectroscopy represents a powerful technique for measuring extremely low absorptions independent of the path length and offers a degree of parameter control that cannot be attained by other methods. We report precise measurements of the ammonia absorption coefficients at the CO2 laser wavelengths by using a photoacoustic (PA) cell in an extracavity configuration and we compare our results with other values reported in the literature. Ammonia presents a clear fingerprint spectrum and high absorption strengths in the CO2 wavelengths region. Because more than 250 molecular gases of environmental concern for atmospheric, industrial, medical, military, and scientific spheres exhibit strong absorption bands in the region 9.2-10.8 μm, we have chosen a frequency tunable CO2 laser. In the present work, ammonia absorption coefficients were measured at both branches of the CO2 laser lines by using a calibrated mixture of 10 ppm NH3 in N2. We found the maximum absorption in the 9 μm region, at 9R(30) line of the CO2 laser. One of the applications based on the ammonia absorption coefficients is used to measure the ammonia levels in exhaled human breath. This can be used to determine the exact time necessary at every session for an optimal degree of dialysis at patients with end-stage renal disease.

  7. Karst features detection and mapping using airphotos, DSMs and GIS techniques

    NASA Astrophysics Data System (ADS)

    Kakavas, M. P.; Nikolakopoulos, K. G.; Zagana, E.

    2015-10-01

    The aim of this work is to detect and qualify natural karst depressions in the Aitoloakarnania Prefecture, Western Greece, using remote sensing data in conjunction with the Geographical Information Systems - GIS. The study area is a part of the Ionian geotectonic zone, and its geological background consists of the Triassic Evaporates. The Triassic carbonate breccias where formed as a result of the tectonic and orogenetic setting of the external Hellenides and the diaper phenomena of the Triassic Evaporates. The landscape characterized by exokarst features closed depressions in the Triassic carbonate breccias. At the threshold of this study, an in situ observation was performed in order to identify dolines and swallow holes. The creation of sinkholes, in general, is based on the collapse of the surface layer due to chemical dissolution of carbonate rocks. In the current study airphotos stereopairs, DSMs and GIS were combined in order to detect and map the karst features. Thirty seven airphotos were imported in Leica Photogrammetry Suite and a stereo model of the study area was created. Then in 3D view possible karst features were detected and digitized. Those sites were verified during the in situ survey. ASTER GDEM, SRTM DEM, high resolution airphoto DSM created from the Greek Cadastral and a DEM from digitized contours from the 1/50,000 topographic were also evaluated in GIS environment for the automatic detection of the karst depressions. The results are presented in this study.

  8. Efficient epileptic seizure detection by a combined IMF-VoE feature.

    PubMed

    Qi, Yu; Wang, Yueming; Zheng, Xiaoxiang; Zhang, Jianmin; Zhu, Junming; Guo, Jianping

    2012-01-01

    Automatic seizure detection from the electroen-cephalogram (EEG) plays an important role in an on-demand closed-loop therapeutic system. A new feature, called IMF-VoE, is proposed to predict the occurrence of seizures. The IMF-VoE feature combines three intrinsic mode functions (IMFs) from the empirical mode decomposition of a EEG signal and the variance of the range between the upper and lower envelopes (VoE) of the signal. These multiple cues encode the intrinsic characteristics of seizure states, thus are able to distinguish them from the background. The feature is tested on 80.4 hours of EEG data with 10 seizures of 4 patients. The sensitivity of 100% is obtained with a low false detection rate of 0.16 per hour. Average time delays are 19.4s, 13.2s, and 10.7s at the false detection rates of 0.16 per hour, 0.27 per hour, and 0.41 per hour respectively, when different thresholds are used. The result is competitive among recent studies. In addition, since the IMF-VoE is compact, the detection system is of high computational efficiency and able to run in real time.

  9. Can digital image forgery detection unevadable? A case study: color filter array interpolation statistical feature recovery

    NASA Astrophysics Data System (ADS)

    Huang, Yizhen

    2005-07-01

    Digital image forgery detection is becoming increasing important. In recently 2 years, a new upsurge has been started to study direct detection methods, which utilize the hardware features of digital cameras. Such features may be weakened or lost once tampered, or they may not be consistent if synthesizing several images into a single one. This manuscript first clarifies the concept of trueness of digital images and summarizes these methods with their crack by a general model. The recently proposed EM algorithm plus Fourier transform that checks the Color Filter Array (CFA) interpolation statistical feature (ISF) is taken as a case study. We propose 3 methods to recover the CFA-ISF of a fake image: (1) artificial CFA interpolation (2) a linear CFA-ISF recovery model with optimal uniform measure (3) a quadratic CFA-ISF recovery model with least square measure. A software prototype CFA-ISF Indicator & Adjustor integrating the detection and anti-detection algorithms is developed and shown. Experiments under our product validate the effectiveness of our methods.

  10. Robust and fast license plate detection based on the fusion of color and edge feature

    NASA Astrophysics Data System (ADS)

    Cai, De; Shi, Zhonghan; Liu, Jin; Hu, Chuanping; Mei, Lin; Qi, Li

    2014-11-01

    Extracting a license plate is an important stage in automatic vehicle identification. The degradation of images and the computation intense make this task difficult. In this paper, a robust and fast license plate detection based on the fusion of color and edge feature is proposed. Based on the dichromatic reflection model, two new color ratios computed from the RGB color model are introduced and proved to be two color invariants. The global color feature extracted by the new color invariants improves the method's robustness. The local Sobel edge feature guarantees the method's accuracy. In the experiment, the detection performance is good. The detection results show that this paper's method is robust to the illumination, object geometry and the disturbance around the license plates. The method can also detect license plates when the color of the car body is the same as the color of the plates. The processing time for image size of 1000x1000 by pixels is nearly 0.2s. Based on the comparison, the performance of the new ratios is comparable to the common used HSI color model.

  11. DETECTION OF MOLECULAR ABSORPTION IN THE DAYSIDE OF EXOPLANET 51 PEGASI b?

    SciTech Connect

    Brogi, M.; Snellen, I. A. G.; Birkby, J. L.; De Kok, R. J.; Albrecht, S.; De Mooij, E. J. W.

    2013-04-10

    In this paper, we present ground-based high-resolution spectroscopy of 51 Pegasi using CRIRES at the Very Large Telescope. The system was observed for 3 Multiplication-Sign 5 hr at 2.3 {mu}m at a spectral resolution of R = 100,000, targeting potential signatures from carbon monoxide, water vapor, and methane in the planet's dayside spectrum. In the first 2 Multiplication-Sign 5 hr of data, we find a combined signal from carbon monoxide and water in absorption at a formal 5.9{sigma} confidence level, indicating a non-inverted atmosphere. We derive a planet mass of M{sub P} = (0.46 {+-} 0.02)M{sub Jup} and an orbital inclination i between 79. Degree-Sign 6 and 82. Degree-Sign 2, with the upper limit set by the non-detection of the planet transit in previous photometric monitoring. However, there is no trace of the signal in the final five hours of data. A statistical analysis indicates that the signal from the first two nights is robust, but we find no compelling explanation for its absence in the final night. The latter suffers from stronger noise residuals and greater instrumental instability than the first two nights, but these cannot fully account for the missing signal. It is possible that the integrated dayside emission from 51 Peg b is instead strongly affected by weather. However, more data are required before we can claim any time variability in the planet's atmosphere.

  12. Computerized detection of diffuse lung disease in MDCT: the usefulness of statistical texture features

    NASA Astrophysics Data System (ADS)

    Wang, Jiahui; Li, Feng; Doi, Kunio; Li, Qiang

    2009-11-01

    Accurate detection of diffuse lung disease is an important step for computerized diagnosis and quantification of this disease. It is also a difficult clinical task for radiologists. We developed a computerized scheme to assist radiologists in the detection of diffuse lung disease in multi-detector computed tomography (CT). Two radiologists selected 31 normal and 37 abnormal CT scans with ground glass opacity, reticular, honeycombing and nodular disease patterns based on clinical reports. The abnormal cases in our database must contain at least an abnormal area with a severity of moderate or severe level that was subjectively rated by the radiologists. Because statistical texture features may lack the power to distinguish a nodular pattern from a normal pattern, the abnormal cases that contain only a nodular pattern were excluded. The areas that included specific abnormal patterns in the selected CT images were then delineated as reference standards by an expert chest radiologist. The lungs were first segmented in each slice by use of a thresholding technique, and then divided into contiguous volumes of interest (VOIs) with a 64 × 64 × 64 matrix size. For each VOI, we determined and employed statistical texture features, such as run-length and co-occurrence matrix features, to distinguish abnormal from normal lung parenchyma. In particular, we developed new run-length texture features with clear physical meanings to considerably improve the accuracy of our detection scheme. A quadratic classifier was employed for distinguishing between normal and abnormal VOIs by the use of a leave-one-case-out validation scheme. A rule-based criterion was employed to further determine whether a case was normal or abnormal. We investigated the impact of new and conventional texture features, VOI size and the dimensionality for regions of interest on detecting diffuse lung disease. When we employed new texture features for 3D VOIs of 64 × 64 × 64 voxels, our system achieved the

  13. Infrared small target's detection and identification with moving platform based on motion features

    NASA Astrophysics Data System (ADS)

    Jia, Yan; Zou, Xu; Zhong, Sheng; Lu, Hongqiang

    2015-10-01

    The infrared small target's detection and tracking are important parts of the automatic target recognition. When the camera platform equipped with an infrared camera moves, the small target's position change in the imaging plane is affected by the composite motion of the small target and the camera platform. Traditional detection and tracking algorithms may lose the small target and make the follow-up detection and tracking fail because of not considering the camera platform's movement. Moreover, when there exist small targets with different motion features in the camera's view, some detection and tracking algorithms can't recognize different targets based on their motion features because there are no trajectories in a unified coordinate system, which may lead to the true small targets undetected or detected incorrectly . To solve those problems, we present a method under the condition of moving camera platform. Firstly, get the camera platform's motion information from the inertial measurement values, and then decouple to remove the motion of the camera platform itself by means of coordinate transformation. Next, estimate the trajectories of the small targets with different motion features based on their position changes in the same imaging plane coordinate system. Finally, recognize different small targets preliminarily based on their different trajectories. Experimental results show that this method can improve the small target's detection probability. Furthermore, when the camera platform fails to track the small target, it's possible to predict the position of the small target in the next frame based on the fitted motion equation and realize sustained and stable tracking.

  14. Aircraft Detection from VHR Images Based on Circle-Frequency Filter and Multilevel Features

    PubMed Central

    Gao, Feng; Li, Bo

    2013-01-01

    Aircraft automatic detection from very high-resolution (VHR) images plays an important role in a wide variety of applications. This paper proposes a novel detector for aircraft detection from very high-resolution (VHR) remote sensing images. To accurately distinguish aircrafts from background, a circle-frequency filter (CF-filter) is used to extract the candidate locations of aircrafts from a large size image. A multi-level feature model is then employed to represent both local appearance and spatial layout of aircrafts by means of Robust Hue Descriptor and Histogram of Oriented Gradients. The experimental results demonstrate the superior performance of the proposed method. PMID:24163637

  15. Modeling and Detecting Feature Interactions among Integrated Services of Home Network Systems

    NASA Astrophysics Data System (ADS)

    Igaki, Hiroshi; Nakamura, Masahide

    This paper presents a framework for formalizing and detecting feature interactions (FIs) in the emerging smart home domain. We first establish a model of home network system (HNS), where every networked appliance (or the HNS environment) is characterized as an object consisting of properties and methods. Then, every HNS service is defined as a sequence of method invocations of the appliances. Within the model, we next formalize two kinds of FIs: (a) appliance interactions and (b) environment interactions. An appliance interaction occurs when two method invocations conflict on the same appliance, whereas an environment interaction arises when two method invocations conflict indirectly via the environment. Finally, we propose offline and online methods that detect FIs before service deployment and during execution, respectively. Through a case study with seven practical services, it is shown that the proposed framework is generic enough to capture feature interactions in HNS integrated services. We also discuss several FI resolution schemes within the proposed framework.

  16. Improving the detection of wind fields from LIDAR aerosol backscatter using feature extraction

    NASA Astrophysics Data System (ADS)

    Bickel, Brady R.; Rotthoff, Eric R.; Walters, Gage S.; Kane, Timothy J.; Mayor, Shane D.

    2016-04-01

    The tracking of winds and atmospheric features has many applications, from predicting and analyzing weather patterns in the upper and lower atmosphere to monitoring air movement from pig and chicken farms. Doppler LIDAR systems exist to quantify the underlying wind speeds, but cost of these systems can sometimes be relatively high, and processing limitations exist. The alternative is using an incoherent LIDAR system to analyze aerosol backscatter. Improving the detection and analysis of wind information from aerosol backscatter LIDAR systems will allow for the adoption of these relatively low cost instruments in environments where the size, complexity, and cost of other options are prohibitive. Using data from a simple aerosol backscatter LIDAR system, we attempt to extend the processing capabilities by calculating wind vectors through image correlation techniques to improve the detection of wind features.

  17. A Speech Endpoint Detection Algorithm Based on BP Neural Network and Multiple Features

    NASA Astrophysics Data System (ADS)

    Shi, Yong-Qiang; Li, Ru-Wei; Zhang, Shuang; Wang, Shuai; Yi, Xiao-Qun

    Focusing on a sharp decline in the performance of endpoint detection algorithm in a complicated noise environment, a new speech endpoint detection method based on BPNN (back propagation neural network) and multiple features is presented. Firstly, maximum of short-time autocorrelation function and spectrum variance of speech signals are extracted respectively. Secondly, these feature vectors as the input of BP neural network are trained and modeled and then the Genetic Algorithm is used to optimize the BP Neural Network. Finally, the signal's type is determined according to the output of Neural Network. The experiments show that the correct rate of this proposed algorithm is improved, because this method has better robustness and adaptability than algorithm based on maximum of short-time autocorrelation function or spectrum variance.

  18. Digital Image Forgery Detection Using JPEG Features and Local Noise Discrepancies

    PubMed Central

    Liu, Bo; Pun, Chi-Man; Yuan, Xiao-Chen

    2014-01-01

    Wide availability of image processing software makes counterfeiting become an easy and low-cost way to distort or conceal facts. Driven by great needs for valid forensic technique, many methods have been proposed to expose such forgeries. In this paper, we proposed an integrated algorithm which was able to detect two commonly used fraud practices: copy-move and splicing forgery in digital picture. To achieve this target, a special descriptor for each block was created combining the feature from JPEG block artificial grid with that from noise estimation. And forehand image quality assessment procedure reconciled these different features by setting proper weights. Experimental results showed that, compared to existing algorithms, our proposed method is effective on detecting both copy-move and splicing forgery regardless of JPEG compression ratio of the input image. PMID:24955389

  19. Digital image forgery detection using JPEG features and local noise discrepancies.

    PubMed

    Liu, Bo; Pun, Chi-Man; Yuan, Xiao-Chen

    2014-01-01

    Wide availability of image processing software makes counterfeiting become an easy and low-cost way to distort or conceal facts. Driven by great needs for valid forensic technique, many methods have been proposed to expose such forgeries. In this paper, we proposed an integrated algorithm which was able to detect two commonly used fraud practices: copy-move and splicing forgery in digital picture. To achieve this target, a special descriptor for each block was created combining the feature from JPEG block artificial grid with that from noise estimation. And forehand image quality assessment procedure reconciled these different features by setting proper weights. Experimental results showed that, compared to existing algorithms, our proposed method is effective on detecting both copy-move and splicing forgery regardless of JPEG compression ratio of the input image.

  20. A General Purpose Feature Extractor for Light Detection and Ranging Data

    DTIC Science & Technology

    2010-11-17

    Similarly, the family of stochastic gradient descent (SGD) algorithms [15,16] and Gauss - Seidel relaxation [17,18] have runtimes that are directly...proposed method . The observation positions are indicated by the black triangle. Grey ellipses indicate 3δ uncertainties and numbers and letters are index of...detector for both 2D and 3D LIDAR data that is applicable to virtually any environment. Our method adapts classic feature detection methods from the image

  1. Detection of braking intention in diverse situations during simulated driving based on EEG feature combination

    NASA Astrophysics Data System (ADS)

    Kim, Il-Hwa; Kim, Jeong-Woo; Haufe, Stefan; Lee, Seong-Whan

    2015-02-01

    Objective. We developed a simulated driving environment for studying neural correlates of emergency braking in diversified driving situations. We further investigated to what extent these neural correlates can be used to detect a participant's braking intention prior to the behavioral response. Approach. We measured electroencephalographic (EEG) and electromyographic signals during simulated driving. Fifteen participants drove a virtual vehicle and were exposed to several kinds of traffic situations in a simulator system, while EEG signals were measured. After that, we extracted characteristic features to categorize whether the driver intended to brake or not. Main results. Our system shows excellent detection performance in a broad range of possible emergency situations. In particular, we were able to distinguish three different kinds of emergency situations (sudden stop of a preceding vehicle, sudden cutting-in of a vehicle from the side and unexpected appearance of a pedestrian) from non-emergency (soft) braking situations, as well as from situations in which no braking was required, but the sensory stimulation was similar to stimulations inducing an emergency situation (e.g., the sudden stop of a vehicle on a neighboring lane). Significance. We proposed a novel feature combination comprising movement-related potentials such as the readiness potential, event-related desynchronization features besides the event-related potentials (ERP) features used in a previous study. The performance of predicting braking intention based on our proposed feature combination was superior compared to using only ERP features. Our study suggests that emergency situations are characterized by specific neural patterns of sensory perception and processing, as well as motor preparation and execution, which can be utilized by neurotechnology based braking assistance systems.

  2. Sequential Filtering Processes Shape Feature Detection in Crickets: A Framework for Song Pattern Recognition

    PubMed Central

    Hedwig, Berthold G.

    2016-01-01

    Intraspecific acoustic communication requires filtering processes and feature detectors in the auditory pathway of the receiver for the recognition of species-specific signals. Insects like acoustically communicating crickets allow describing and analysing the mechanisms underlying auditory processing at the behavioral and neural level. Female crickets approach male calling song, their phonotactic behavior is tuned to the characteristic features of the song, such as the carrier frequency and the temporal pattern of sound pulses. Data from behavioral experiments and from neural recordings at different stages of processing in the auditory pathway lead to a concept of serially arranged filtering mechanisms. These encompass a filter for the carrier frequency at the level of the hearing organ, and the pulse duration through phasic onset responses of afferents and reciprocal inhibition of thoracic interneurons. Further, processing by a delay line and coincidence detector circuit in the brain leads to feature detecting neurons that specifically respond to the species-specific pulse rate, and match the characteristics of the phonotactic response. This same circuit may also control the response to the species-specific chirp pattern. Based on these serial filters and the feature detecting mechanism, female phonotactic behavior is shaped and tuned to the characteristic properties of male calling song. PMID:26941647

  3. Spike detection, characterization, and discrimination using feature analysis software written in LabVIEW.

    PubMed

    Stewart, C M; Newlands, S D; Perachio, A A

    2004-12-01

    Rapid and accurate discrimination of single units from extracellular recordings is a fundamental process for the analysis and interpretation of electrophysiological recordings. We present an algorithm that performs detection, characterization, discrimination, and analysis of action potentials from extracellular recording sessions. The program was entirely written in LabVIEW (National Instruments), and requires no external hardware devices or a priori information about action potential shapes. Waveform events are detected by scanning the digital record for voltages that exceed a user-adjustable trigger. Detected events are characterized to determine nine different time and voltage levels for each event. Various algebraic combinations of these waveform features are used as axis choices for 2-D Cartesian plots of events. The user selects axis choices that generate distinct clusters. Multiple clusters may be defined as action potentials by manually generating boundaries of arbitrary shape. Events defined as action potentials are validated by visual inspection of overlain waveforms. Stimulus-response relationships may be identified by selecting any recorded channel for comparison to continuous and average cycle histograms of binned unit data. The algorithm includes novel aspects of feature analysis and acquisition, including higher acquisition rates for electrophysiological data compared to other channels. The program confirms that electrophysiological data may be discriminated with high-speed and efficiency using algebraic combinations of waveform features derived from high-speed digital records.

  4. Robust detection of premature ventricular contractions using sparse signal decomposition and temporal features

    PubMed Central

    Ramkumar, Barathram; Deshpande, Pranav S.; Choudhary, Tilendra

    2015-01-01

    An automated noise-robust premature ventricular contraction (PVC) detection method is proposed based on the sparse signal decomposition, temporal features, and decision rules. In this Letter, the authors exploit sparse expansion of electrocardiogram (ECG) signals on mixed dictionaries for simultaneously enhancing the QRS complex and reducing the influence of tall P and T waves, baseline wanders, and muscle artefacts. They further investigate a set of ten generalised temporal features combined with decision-rule-based detection algorithm for discriminating PVC beats from non-PVC beats. The accuracy and robustness of the proposed method is evaluated using 47 ECG recordings from the MIT/BIH arrhythmia database. Evaluation results show that the proposed method achieves an average sensitivity of 89.69%, and specificity 99.63%. Results further show that the proposed decision-rule-based algorithm with ten generalised features can accurately detect different patterns of PVC beats (uniform and multiform, couplets, triplets, and ventricular tachycardia) in presence of other normal and abnormal heartbeats. PMID:26713158

  5. Spectrum and Image Texture Features Analysis for Early Blight Disease Detection on Eggplant Leaves

    PubMed Central

    Xie, Chuanqi; He, Yong

    2016-01-01

    This study investigated both spectrum and texture features for detecting early blight disease on eggplant leaves. Hyperspectral images for healthy and diseased samples were acquired covering the wavelengths from 380 to 1023 nm. Four gray images were identified according to the effective wavelengths (408, 535, 624 and 703 nm). Hyperspectral images were then converted into RGB, HSV and HLS images. Finally, eight texture features (mean, variance, homogeneity, contrast, dissimilarity, entropy, second moment and correlation) based on gray level co-occurrence matrix (GLCM) were extracted from gray images, RGB, HSV and HLS images, respectively. The dependent variables for healthy and diseased samples were set as 0 and 1. K-Nearest Neighbor (KNN) and AdaBoost classification models were established for detecting healthy and infected samples. All models obtained good results with the classification rates (CRs) over 88.46% in the testing sets. The results demonstrated that spectrum and texture features were effective for early blight disease detection on eggplant leaves. PMID:27187387

  6. Regions of micro-calcifications clusters detection based on new features from imbalance data in mammograms

    NASA Astrophysics Data System (ADS)

    Wang, Keju; Dong, Min; Yang, Zhen; Guo, Yanan; Ma, Yide

    2017-02-01

    Breast cancer is the most common cancer among women. Micro-calcification cluster on X-ray mammogram is one of the most important abnormalities, and it is effective for early cancer detection. Surrounding Region Dependence Method (SRDM), a statistical texture analysis method is applied for detecting Regions of Interest (ROIs) containing microcalcifications. Inspired by the SRDM, we present a method that extract gray and other features which are effective to predict the positive and negative regions of micro-calcifications clusters in mammogram. By constructing a set of artificial images only containing micro-calcifications, we locate the suspicious pixels of calcifications of a SRDM matrix in original image map. Features are extracted based on these pixels for imbalance date and then the repeated random subsampling method and Random Forest (RF) classifier are used for classification. True Positive (TP) rate and False Positive (FP) can reflect how the result will be. The TP rate is 90% and FP rate is 88.8% when the threshold q is 10. We draw the Receiver Operating Characteristic (ROC) curve and the Area Under the ROC Curve (AUC) value reaches 0.9224. The experiment indicates that our method is effective. A novel regions of micro-calcifications clusters detection method is developed, which is based on new features for imbalance data in mammography, and it can be considered to help improving the accuracy of computer aided diagnosis breast cancer.

  7. Multi-channels statistical and morphological features based mitosis detection in breast cancer histopathology.

    PubMed

    Irshad, Humayun; Roux, Ludovic; Racoceanu, Daniel

    2013-01-01

    Accurate counting of mitosis in breast cancer histopathology plays a critical role in the grading process. Manual counting of mitosis is tedious and subject to considerable inter- and intra-reader variations. This work aims at improving the accuracy of mitosis detection by selecting the color channels that better capture the statistical and morphological features having mitosis discrimination from other objects. The proposed framework includes comprehensive analysis of first and second order statistical features together with morphological features in selected color channels and a study on balancing the skewed dataset using SMOTE method for increasing the predictive accuracy of mitosis classification. The proposed framework has been evaluated on MITOS data set during an ICPR 2012 contest and ranked second from 17 finalists. The proposed framework achieved 74% detection rate, 70% precision and 72% F-Measure. In future work, we plan to apply our mitosis detection tool to images produced by different types of slide scanners, including multi-spectral and multi-focal microscopy.

  8. Detection of HO2 in an atmospheric pressure plasma jet using optical feedback cavity-enhanced absorption spectroscopy

    NASA Astrophysics Data System (ADS)

    Gianella, Michele; Reuter, Stephan; Lawry Aguila, Ana; Ritchie, Grant A. D.; van Helden, Jean-Pierre H.

    2016-11-01

    Cold non-equilibrium atmospheric pressure plasma jets are increasingly applied in material processing and plasma medicine. However, their small dimensions make diagnosing the fluxes of generated species a challenge. Here we report on the detection of the hydroperoxyl radical, HO2, in the effluent of a plasma jet by the use of optical feedback cavity-enhanced absorption spectroscopy. The spectrometer has a minimum detectable absorption coefficient {α }\\min of 2.25× {10}-10 cm-1 with a 100 second acquisition, equivalent to 5.5× {10}12 {{cm}}-3 of HO2 (under ideal conditions). Concentrations in the range of (3.1-7.8) × 1013 cm-3 were inferred in the 4 mm wide effluent of the plasma jet.

  9. Obscenity Detection Using Haar-Like Features and Gentle Adaboost Classifier

    PubMed Central

    Min, Yang; Zhu, Dingju

    2014-01-01

    Large exposure of skin area of an image is considered obscene. This only fact may lead to many false images having skin-like objects and may not detect those images which have partially exposed skin area but have exposed erotogenic human body parts. This paper presents a novel method for detecting nipples from pornographic image contents. Nipple is considered as an erotogenic organ to identify pornographic contents from images. In this research Gentle Adaboost (GAB) haar-cascade classifier and haar-like features used for ensuring detection accuracy. Skin filter prior to detection made the system more robust. The experiment showed that, considering accuracy, haar-cascade classifier performs well, but in order to satisfy detection time, train-cascade classifier is suitable. To validate the results, we used 1198 positive samples containing nipple objects and 1995 negative images. The detection rates for haar-cascade and train-cascade classifiers are 0.9875 and 0.8429, respectively. The detection time for haar-cascade is 0.162 seconds and is 0.127 seconds for train-cascade classifier. PMID:25003153

  10. Multi-heterodyne molecular absorption spectrum detection of H13C14N based on dual frequency combs

    NASA Astrophysics Data System (ADS)

    Yang, Honglei; Wei, Haoyun; Li, Yan

    2014-11-01

    In order to acquire high-resolution molecular absorption spectrum, a measurement system consisting of two Erbium-doped fiber optical frequency combs based on multi-heterodyne detection method is established. Preliminary result shows that the specific line in the RF spectrum corresponding to 6452.59 cm-1 in the optical region, where there is an error of 0.14 cm-1 compared with the simulation result. And the further improvement of this system will be discussed in the end.

  11. Thermography based breast cancer detection using texture features and minimum variance quantization

    PubMed Central

    Milosevic, Marina; Jankovic, Dragan; Peulic, Aleksandar

    2014-01-01

    In this paper, we present a system based on feature extraction techniques and image segmentation techniques for detecting and diagnosing abnormal patterns in breast thermograms. The proposed system consists of three major steps: feature extraction, classification into normal and abnormal pattern and segmentation of abnormal pattern. Computed features based on gray-level co-occurrence matrices are used to evaluate the effectiveness of textural information possessed by mass regions. A total of 20 GLCM features are extracted from thermograms. The ability of feature set in differentiating abnormal from normal tissue is investigated using a Support Vector Machine classifier, Naive Bayes classifier and K-Nearest Neighbor classifier. To evaluate the classification performance, five-fold cross validation method and Receiver operating characteristic analysis was performed. The verification results show that the proposed algorithm gives the best classification results using K-Nearest Neighbor classifier and a accuracy of 92.5%. Image segmentation techniques can play an important role to segment and extract suspected hot regions of interests in the breast infrared images. Three image segmentation techniques: minimum variance quantization, dilation of image and erosion of image are discussed. The hottest regions of thermal breast images are extracted and compared to the original images. According to the results, the proposed method has potential to extract almost exact shape of tumors. PMID:26417334

  12. EEG-based Drowsiness Detection for Safe Driving Using Chaotic Features and Statistical Tests.

    PubMed

    Mardi, Zahra; Ashtiani, Seyedeh Naghmeh Miri; Mikaili, Mohammad

    2011-05-01

    Electro encephalography (EEG) is one of the most reliable sources to detect sleep onset while driving. In this study, we have tried to demonstrate that sleepiness and alertness signals are separable with an appropriate margin by extracting suitable features. So, first of all, we have recorded EEG signals from 10 volunteers. They were obliged to avoid sleeping for about 20 hours before the test. We recorded the signals while subjects did a virtual driving game. They tried to pass some barriers that were shown on monitor. Process of recording was ended after 45 minutes. Then, after preprocessing of recorded signals, we labeled them by drowsiness and alertness by using times associated with pass times of the barriers or crash times to them. Then, we extracted some chaotic features (include Higuchi's fractal dimension and Petrosian's fractal dimension) and logarithm of energy of signal. By applying the two-tailed t-test, we have shown that these features can create 95% significance level of difference between drowsiness and alertness in each EEG channels. Ability of each feature has been evaluated by artificial neural network and accuracy of classification with all features was about 83.3% and this accuracy has been obtained without performing any optimization process on classifier.

  13. Comparison of Different Features and Classifiers for Driver Fatigue Detection Based on a Single EEG Channel

    PubMed Central

    2017-01-01

    Driver fatigue has become an important factor to traffic accidents worldwide, and effective detection of driver fatigue has major significance for public health. The purpose method employs entropy measures for feature extraction from a single electroencephalogram (EEG) channel. Four types of entropies measures, sample entropy (SE), fuzzy entropy (FE), approximate entropy (AE), and spectral entropy (PE), were deployed for the analysis of original EEG signal and compared by ten state-of-the-art classifiers. Results indicate that optimal performance of single channel is achieved using a combination of channel CP4, feature FE, and classifier Random Forest (RF). The highest accuracy can be up to 96.6%, which has been able to meet the needs of real applications. The best combination of channel + features + classifier is subject-specific. In this work, the accuracy of FE as the feature is far greater than the Acc of other features. The accuracy using classifier RF is the best, while that of classifier SVM with linear kernel is the worst. The impact of channel selection on the Acc is larger. The performance of various channels is very different. PMID:28255330

  14. Automated detection of Martian water ice clouds using Support Vector Machine and simple feature vectors

    NASA Astrophysics Data System (ADS)

    Ogohara, Kazunori; Munetomo, Takafumi; Hatanaka, Yuji; Okumura, Susumu

    2016-12-01

    We present a method for evaluating the presence of Martian water ice clouds using difference images and cross-correlation distributions calculated from blue band images of the Valles Marineris obtained by the Mars Orbiter Camera onboard the Mars Global Surveyor (MGS/MOC). We derived one subtracted image and one cross-correlation distribution from two reflectance images. The difference between the maximum and the average, variance, kurtosis, and skewness of the subtracted image were calculated. Those of the cross-correlation distribution were also calculated. These eight statistics were used as feature vectors for training Support Vector Machine because they were the simplest of features that was expected to be closely associated with the physical properties of water ice clouds. The generalization ability was tested using 10-fold cross-validation. F-measure and accuracy tended to be approximately 0.8 if the maximum in the normalized reflectance and the difference of the maximum and the average in the cross-correlation were selected as features. This result can be physically explained because the blue band as well as the red band is sensitive to water ice clouds. A simple and low-dimensional feature vector enables us to understand the detected water ice clouds physically and presents the lower bound of the score that classifiers trained using more sophisticated feature vectors have to achieve.

  15. Thermography based breast cancer detection using texture features and minimum variance quantization.

    PubMed

    Milosevic, Marina; Jankovic, Dragan; Peulic, Aleksandar

    2014-01-01

    In this paper, we present a system based on feature extraction techniques and image segmentation techniques for detecting and diagnosing abnormal patterns in breast thermograms. The proposed system consists of three major steps: feature extraction, classification into normal and abnormal pattern and segmentation of abnormal pattern. Computed features based on gray-level co-occurrence matrices are used to evaluate the effectiveness of textural information possessed by mass regions. A total of 20 GLCM features are extracted from thermograms. The ability of feature set in differentiating abnormal from normal tissue is investigated using a Support Vector Machine classifier, Naive Bayes classifier and K-Nearest Neighbor classifier. To evaluate the classification performance, five-fold cross validation method and Receiver operating characteristic analysis was performed. The verification results show that the proposed algorithm gives the best classification results using K-Nearest Neighbor classifier and a accuracy of 92.5%. Image segmentation techniques can play an important role to segment and extract suspected hot regions of interests in the breast infrared images. Three image segmentation techniques: minimum variance quantization, dilation of image and erosion of image are discussed. The hottest regions of thermal breast images are extracted and compared to the original images. According to the results, the proposed method has potential to extract almost exact shape of tumors.

  16. L-asparagine crystals with wide gap semiconductor features: Optical absorption measurements and density functional theory computations

    SciTech Connect

    Zanatta, G.; Gottfried, C.; Silva, A. M.; Caetano, E. W. S.; Sales, F. A. M.; Freire, V. N.

    2014-03-28

    Results of optical absorption measurements are presented together with calculated structural, electronic, and optical properties for the anhydrous monoclinic L-asparagine crystal. Density functional theory (DFT) within the generalized gradient approximation (GGA) including dispersion effects (TS, Grimme) was employed to perform the calculations. The optical absorption measurements revealed that the anhydrous monoclinic L-asparagine crystal is a wide band gap material with 4.95 eV main gap energy. DFT-GGA+TS simulations, on the other hand, produced structural parameters in very good agreement with X-ray data. The lattice parameter differences Δa, Δb, Δc between theory and experiment were as small as 0.020, 0.051, and 0.022 Å, respectively. The calculated band gap energy is smaller than the experimental data by about 15%, with a 4.23 eV indirect band gap corresponding to Z → Γ and Z → β transitions. Three other indirect band gaps of 4.30 eV, 4.32 eV, and 4.36 eV are assigned to α3 → Γ, α1 → Γ, and α2 → Γ transitions, respectively. Δ-sol computations, on the other hand, predict a main band gap of 5.00 eV, just 50 meV above the experimental value. Electronic wavefunctions mainly originating from O 2p–carboxyl, C 2p–side chain, and C 2p–carboxyl orbitals contribute most significantly to the highest valence and lowest conduction energy bands, respectively. By varying the lattice parameters from their converged equilibrium values, we show that the unit cell is less stiff along the b direction than for the a and c directions. Effective mass calculations suggest that hole transport behavior is more anisotropic than electron transport, but the mass values allow for some charge mobility except along a direction perpendicular to the molecular layers of L-asparagine which form the crystal, so anhydrous monoclinic L-asparagine crystals could behave as wide gap semiconductors. Finally, the calculations point to a high degree of optical

  17. Atmospheric Profiling Combining the Features of GPS ro & Mls: Satellite to Satellite Occultations Near Water & Ozone Absorption Lines

    NASA Astrophysics Data System (ADS)

    Kursinski, E. R.; Ward, D.; Otarola, A. C.; McGhee, J.; Reed, H.; Erickson, D.

    2015-12-01

    Assessing climate models & their predictions requires observations that determine the state of the real climate system precisely and unambiguously, independently from models. For this purpose, we have been developing a new orbiting remote sensing system called the Active Temperature, Ozone & Moisture Microwave Spectrometer (ATOMMS) which is a cross between GPS RO and the Microwave Limb Sounder. ATOMMS actively probes water vapor, ozone & other absorption lines at cm & mm wavelengths in a satellite to satellite occultation geometry to simultaneously profile temperature, pressure, water vapor and ozone as well as other important constituents. Individual profiles of water vapor, temperature & pressure heights will extend from near the surface into the mesosphere with ~1%, 0.4K and 10 m precision respectively and still better accuracy, with 100 m vertical resolution. Ozone profiles will extend upward from the upper troposphere. Line of sight wind profiles will extend upwards from the mid-stratosphere. ATOMMS is a doubly differential absorption system which eliminates drift and both sees clouds and sees thru them, to deliver performance in clouds within a factor of 2 of the performance in clear skies. This all-weather sampling combined with insensitivity to surface emissivity avoids sampling biases that limit most existing satellite records. ATOMMS will profile slant liquid water in clouds & rain and as well as turbulence via scintillations ("twinkling of a star"). Using prototype ATOMMS instrumentation that we developed with funding from NSF, several ATOMMS ground field campaigns precisely measured water vapor, cloud amount, rainfall, turbulence and absorption line spectroscopy. ATOMMS's dynamic range was demonstrated as water vapor was derived to 1% precision in optical depths up to 17. We are developing high altitude aircraft to aircraft instrumentation to further demonstrate ATOMMS performance, refine spectroscopy & support future field campaigns. Our vision is a

  18. L-Asparagine crystals with wide gap semiconductor features: optical absorption measurements and density functional theory computations.

    PubMed

    Zanatta, G; Gottfried, C; Silva, A M; Caetano, E W S; Sales, F A M; Freire, V N

    2014-03-28

    Results of optical absorption measurements are presented together with calculated structural, electronic, and optical properties for the anhydrous monoclinic L-asparagine crystal. Density functional theory (DFT) within the generalized gradient approximation (GGA) including dispersion effects (TS, Grimme) was employed to perform the calculations. The optical absorption measurements revealed that the anhydrous monoclinic L-asparagine crystal is a wide band gap material with 4.95 eV main gap energy. DFT-GGA+TS simulations, on the other hand, produced structural parameters in very good agreement with X-ray data. The lattice parameter differences Δa, Δb, Δc between theory and experiment were as small as 0.020, 0.051, and 0.022 Å, respectively. The calculated band gap energy is smaller than the experimental data by about 15%, with a 4.23 eV indirect band gap corresponding to Z → Γ and Z → β transitions. Three other indirect band gaps of 4.30 eV, 4.32 eV, and 4.36 eV are assigned to α3 → Γ, α1 → Γ, and α2 → Γ transitions, respectively. Δ-sol computations, on the other hand, predict a main band gap of 5.00 eV, just 50 meV above the experimental value. Electronic wavefunctions mainly originating from O 2p-carboxyl, C 2p-side chain, and C 2p-carboxyl orbitals contribute most significantly to the highest valence and lowest conduction energy bands, respectively. By varying the lattice parameters from their converged equilibrium values, we show that the unit cell is less stiff along the b direction than for the a and c directions. Effective mass calculations suggest that hole transport behavior is more anisotropic than electron transport, but the mass values allow for some charge mobility except along a direction perpendicular to the molecular layers of L-asparagine which form the crystal, so anhydrous monoclinic L-asparagine crystals could behave as wide gap semiconductors. Finally, the calculations point to a high degree of optical

  19. Random feature subspace ensemble based Extreme Learning Machine for liver tumor detection and segmentation.

    PubMed

    Huang, Weimin; Yang, Yongzhong; Lin, Zhiping; Huang, Guang-Bin; Zhou, Jiayin; Duan, Yuping; Xiong, Wei

    2014-01-01

    This paper presents a new approach to detect and segment liver tumors. The detection and segmentation of liver tumors can be formulized as novelty detection or two-class classification problem. Each voxel is characterized by a rich feature vector, and a classifier using random feature subspace ensemble is trained to classify the voxels. Since Extreme Learning Machine (ELM) has advantages of very fast learning speed and good generalization ability, it is chosen to be the base classifier in the ensemble. Besides, majority voting is incorporated for fusion of classification results from the ensemble of base classifiers. In order to further increase testing accuracy, ELM autoencoder is implemented as a pre-training step. In automatic liver tumor detection, ELM is trained as a one-class classifier with only healthy liver samples, and the performance is compared with two-class ELM. In liver tumor segmentation, a semi-automatic approach is adopted by selecting samples in 3D space to train the classifier. The proposed method is tested and evaluated on a group of patients' CT data and experiment show promising results.

  20. Detection of absorption by H2 in molecular clouds: A direct measurement of the H2:CO ratio

    NASA Technical Reports Server (NTRS)

    Lacy, J. H.; Knacke, R.; Geballe, T. R.; Tokunaga, A. T.

    1994-01-01

    Vibrational absorption by H2 and CO has been searched for toward infrared sources embedded in molecular clouds. H2 was detected toward NGC 2024 IRS 2 and possibly toward NGC 2264 (GL 989). CO was detected toward both sources. The results are consistent with the H2 ortho:para ratio being equilibrated at the cloud temperature. Toward NGC 2024, H2:CO = (3700(sub -2600)(sup +3100)) (2 sigma limits), and toward NGC 2264, H2:CO less than 6000. Approximately one-third of all carbon is in gas-phase CO.

  1. Near-infrared diode laser based spectroscopic detection of ammonia: a comparative study of photoacoustic and direct optical absorption methods

    NASA Technical Reports Server (NTRS)

    Bozoki, Zoltan; Mohacsi, Arpad; Szabo, Gabor; Bor, Zsolt; Erdelyi, Miklos; Chen, Weidong; Tittel, Frank K.

    2002-01-01

    A photoacoustic spectroscopic (PAS) and a direct optical absorption spectroscopic (OAS) gas sensor, both using continuous-wave room-temperature diode lasers operating at 1531.8 nm, were compared on the basis of ammonia detection. Excellent linear correlation between the detector signals of the two systems was found. Although the physical properties and the mode of operation of both sensors were significantly different, their performances were found to be remarkably similar, with a sub-ppm level minimum detectable concentration of ammonia and a fast response time in the range of a few minutes.

  2. Efficient Fine Arrhythmia Detection Based on DCG P-T Features.

    PubMed

    Bie, Rongfang; Xu, Shuaijing; Zhang, Guangzhi; Zhang, Meng; Ma, Xianlin; Zhang, Xialin

    2016-07-01

    Due to the high mortality associated with heart disease, there is an urgent demand for advanced detection of abnormal heart beats. The use of dynamic electrocardiogram (DCG) provides a useful indicator of heart condition from long-term monitoring techniques commonly used in the clinic. However, accurately distinguishing sparse abnormal heart beats from large DCG data sets remains difficult. Herein, we propose an efficient fine solution based on 11 geometrical features of the DCG PQRST(P-T) waves and an improved hierarchical clustering method for arrhythmia detection. Data sets selected from MIT-BIH are used to validate the effectiveness of this approach. Experimental results show that the detection procedure of arrhythmia is fast and with accurate clustering.

  3. Wave field features of shallow vertical discontinuity and their application in non-destructive detection

    USGS Publications Warehouse

    Liu, J.; Xia, J.; Luo, Y.; Chen, C.; Li, X.; Huang, Y.

    2007-01-01

    The geotechnical integrity of critical infrastructure can be seriously compromised by the presence of fractures or crevices. Non-destructive techniques to accurately detect fractures in critical infrastructure such as dams and highways could be of significant benefit to the geotechnical industry. This paper investigates the application of shallow seismic and georadar methods to the detection of a vertical discontinuity using numerical simulations. The objective is to address the kinematical analysis of a vertical discontinuity, determine the resulting wave field characteristics, and provide the basis for determining the existence of vertical discontinuities based on the recorded signals. Simulation results demonstrate that: (1) A reflection from a vertical discontinuity produces a hyperbolic feature on a seismic or georadar profile; (2) In order for a reflection from a vertical discontinuity to be produced, a reflecting horizon below the discontinuity must exist, the offset between source and receiver (x0) must be non-zero, on the same side of the vertical discontinuity; (3) The range of distances from the vertical discontinuity where a reflection event is observed is proportional to its length and to x0; (4) Should the vertical crevice (or fracture) pass through a reflecting horizon, dual hyperbolic features can be observed on the records, and this can be used as a determining factor that the vertical crevice passes through the interface; and (5) diffractions from the edges of the discontinuity can be recorded with relatively smaller amplitude than reflections and their ranges are not constrained by the length of discontinuity. If the length of discontinuity is short enough, diffractions are the dominant feature. Real-world examples show that the shallow seismic reflection method and the georadar method are capable of recording the hyperbolic feature, which can be interpreted as vertical discontinuity. Thus, these methods show some promise as effective non

  4. Interobserver Agreement in Detecting Spectral-Domain Optical Coherence Tomography Features of Diabetic Macular Edema

    PubMed Central

    Heng, Ling Zhi; Pefianaki, Maria; Hykin, Philip; Patel, Praveen J.

    2015-01-01

    Purpose To evaluate interobserver agreement for the detection of spectral-domain optical coherence tomography (SDOCT) features of diabetic macular edema (DME). Method Cross-sectional study in which 2 retinal specialists evaluated SDOCT scans from eyes receiving treatment for DME. Scans from 50 eyes with DME of 39 patients were graded for features of DME including intra-retinal fluid (IRF), diffuse retinal oedema (DRE), hyper-reflective foci (HRF), subretinal fluid (SRF), macular fluid and vitreomacular traction (VMT). Features were graded as present or absent at zones involving the fovea, 1mm from the fovea and the whole scan of 49 line scans. Analysis was performed using cross-tabulations for percentage concordance and kappa values (κ). Results In the 2950 line scans analysed, there was an increase in percentage concordance for DRE and HRF when moving from a foveal line scan, 1mm zone and then to a whole scan analysis (88% vs 94% vs 96%) and (88% vs 94% vs 94%) respectively with κ ranging from substantial to almost perfect. Percentage concordance for SRF was 96% at all 3 regions analysed, whilst IRF was 96% at fovea and 98% at higher number of line-scans analysed. Concordance for MF was 100% at fovea and 98% at 1mm zone and whole scan with almost perfect and substantial κ respectively. κ agreement was substantial for VMT at all regions analysed. Conclusion We report a high level of interobserver agreement in the detection of SDOCT features of DME. This finding is important as detection of macular fluid is used to guide retreatment with anti-angiogenic agents. PMID:25996150

  5. A two-view ultrasound CAD system for spina bifida detection using Zernike features

    NASA Astrophysics Data System (ADS)

    Konur, Umut; Gürgen, Fikret; Varol, Füsun

    2011-03-01

    In this work, we address a very specific CAD (Computer Aided Detection/Diagnosis) problem and try to detect one of the relatively common birth defects - spina bifida, in the prenatal period. To do this, fetal ultrasound images are used as the input imaging modality, which is the most convenient so far. Our approach is to decide using two particular types of views of the fetal neural tube. Transcerebellar head (i.e. brain) and transverse (axial) spine images are processed to extract features which are then used to classify healthy (normal), suspicious (probably defective) and non-decidable cases. Decisions raised by two independent classifiers may be individually treated, or if desired and data related to both modalities are available, those decisions can be combined to keep matters more secure. Even more security can be attained by using more than two modalities and base the final decision on all those potential classifiers. Our current system relies on feature extraction from images for cases (for particular patients). The first step is image preprocessing and segmentation to get rid of useless image pixels and represent the input in a more compact domain, which is hopefully more representative for good classification performance. Next, a particular type of feature extraction, which uses Zernike moments computed on either B/W or gray-scale image segments, is performed. The aim here is to obtain values for indicative markers that signal the presence of spina bifida. Markers differ depending on the image modality being used. Either shape or texture information captured by moments may propose useful features. Finally, SVM is used to train classifiers to be used as decision makers. Our experimental results show that a promising CAD system can be actualized for the specific purpose. On the other hand, the performance of such a system would highly depend on the qualities of image preprocessing, segmentation, feature extraction and comprehensiveness of image data.

  6. Automated detection of broadband clicks of freshwater fish using spectro-temporal features.

    PubMed

    Kottege, Navinda; Jurdak, Raja; Kroon, Frederieke; Jones, Dean

    2015-05-01

    Large scale networks of embedded wireless sensor nodes can passively capture sound for species detection. However, the acoustic recordings result in large amounts of data requiring in-network classification for such systems to be feasible. The current state of the art in the area of in-network bioacoustics classification targets narrowband or long-duration signals, which render it unsuitable for detecting species that emit impulsive broadband signals. In this study, impulsive broadband signals were classified using a small set of spectral and temporal features to aid in their automatic detection and classification. A prototype system is presented along with an experimental evaluation of automated classification methods. The sound used was recorded from a freshwater invasive fish in Australia, the spotted tilapia (Tilapia mariae). Results show a high degree of accuracy after evaluating the proposed detection and classification method for T. mariae sounds and comparing its performance against the state of the art. Moreover, performance slightly improves when the original signal was down-sampled from 44.1 to 16 kHz. This indicates that the proposed method is well-suited for detection and classification on embedded devices, which can be deployed to implement a large scale wireless sensor network for automated species detection.

  7. LMD based features for the automatic seizure detection of EEG signals using SVM.

    PubMed

    Zhang, Tao; Chen, Wanzhong

    2016-09-20

    Achieving the goal of detecting seizure activity automatically using electroencephalogram (EEG) signals is of great importance and significance for the treatment of epileptic seizures. To realize this aim, a newly-developed time-frequency analytical algorithm, namely local mean decomposition (LMD), is employed in the presented study. LMD is able to decompose an arbitrary signal into a series of product functions (PFs). Primarily, the raw EEG signal is decomposed into several PFs, and then the temporal statistical and non-linear features of the first five PFs are calculated. The features of each PF are fed into five classifiers, including back propagation neural network (BPNN), K-nearest neighbor (KNN), linear discriminant analysis (LDA), un-optimized support vector machine (SVM) and SVM optimized by genetic algorithm (GA-SVM), for five classification cases, respectively. Confluent features of all PFs are further passed into the high-performance GA-SVM for the same classification tasks. Experimental results on the international public Bonn epilepsy EEG dataset show that the average classification accuracy of the presented approach are equal to or higher than 98.10% in all the five cases, and this indicates the effectiveness of the proposed approach for automated seizure detection.

  8. Face detection on distorted images using perceptual quality-aware features

    NASA Astrophysics Data System (ADS)

    Gunasekar, Suriya; Ghosh, Joydeep; Bovik, Alan C.

    2014-02-01

    We quantify the degradation in performance of a popular and effective face detector when human-perceived image quality is degraded by distortions due to additive white gaussian noise, gaussian blur or JPEG compression. It is observed that, within a certain range of perceived image quality, a modest increase in image quality can drastically improve face detection performance. These results can be used to guide resource or bandwidth allocation in a communication/delivery system that is associated with face detection tasks. A new face detector based on QualHOG features is also proposed that augments face-indicative HOG features with perceptual quality-aware spatial Natural Scene Statistics (NSS) features, yielding improved tolerance against image distortions. The new detector provides statistically significant improvements over a strong baseline on a large database of face images representing a wide range of distortions. To facilitate this study, we created a new Distorted Face Database, containing face and non-face patches from images impaired by a variety of common distortion types and levels. This new dataset is available for download and further experimentation at www.ideal.ece.utexas.edu/˜suriya/DFD/.

  9. Breast cancer mitosis detection in histopathological images with spatial feature extraction

    NASA Astrophysics Data System (ADS)

    Albayrak, Abdülkadir; Bilgin, Gökhan

    2013-12-01

    In this work, cellular mitosis detection in histopathological images has been investigated. Mitosis detection is very expensive and time consuming process. Development of digital imaging in pathology has enabled reasonable and effective solution to this problem. Segmentation of digital images provides easier analysis of cell structures in histopathological data. To differentiate normal and mitotic cells in histopathological images, feature extraction step is very crucial step for the system accuracy. A mitotic cell has more distinctive textural dissimilarities than the other normal cells. Hence, it is important to incorporate spatial information in feature extraction or in post-processing steps. As a main part of this study, Haralick texture descriptor has been proposed with different spatial window sizes in RGB and La*b* color spaces. So, spatial dependencies of normal and mitotic cellular pixels can be evaluated within different pixel neighborhoods. Extracted features are compared with various sample sizes by Support Vector Machines using k-fold cross validation method. According to the represented results, it has been shown that separation accuracy on mitotic and non-mitotic cellular pixels gets better with the increasing size of spatial window.

  10. Enhanced flyby science with onboard computer vision: Tracking and surface feature detection at small bodies

    NASA Astrophysics Data System (ADS)

    Fuchs, Thomas J.; Thompson, David R.; Bue, Brian D.; Castillo-Rogez, Julie; Chien, Steve A.; Gharibian, Dero; Wagstaff, Kiri L.

    2015-10-01

    Spacecraft autonomy is crucial to increase the science return of optical remote sensing observations at distant primitive bodies. To date, most small bodies exploration has involved short timescale flybys that execute prescripted data collection sequences. Light time delay means that the spacecraft must operate completely autonomously without direct control from the ground, but in most cases the physical properties and morphologies of prospective targets are unknown before the flyby. Surface features of interest are highly localized, and successful observations must account for geometry and illumination constraints. Under these circumstances onboard computer vision can improve science yield by responding immediately to collected imagery. It can reacquire bad data or identify features of opportunity for additional targeted measurements. We present a comprehensive framework for onboard computer vision for flyby missions at small bodies. We introduce novel algorithms for target tracking, target segmentation, surface feature detection, and anomaly detection. The performance and generalization power are evaluated in detail using expert annotations on data sets from previous encounters with primitive bodies.

  11. Wood Texture Features Extraction by Using GLCM Combined With Various Edge Detection Methods

    NASA Astrophysics Data System (ADS)

    Fahrurozi, A.; Madenda, S.; Ernastuti; Kerami, D.

    2016-06-01

    An image forming specific texture can be distinguished manually through the eye. However, sometimes it is difficult to do if the texture owned quite similar. Wood is a natural material that forms a unique texture. Experts can distinguish the quality of wood based texture observed in certain parts of the wood. In this study, it has been extracted texture features of the wood image that can be used to identify the characteristics of wood digitally by computer. Feature extraction carried out using Gray Level Co-occurrence Matrices (GLCM) built on an image from several edge detection methods applied to wood image. Edge detection methods used include Roberts, Sobel, Prewitt, Canny and Laplacian of Gaussian. The image of wood taken in LE2i laboratory, Universite de Bourgogne from the wood sample in France that grouped by their quality by experts and divided into four types of quality. Obtained a statistic that illustrates the distribution of texture features values of each wood type which compared according to the edge operator that is used and selection of specified GLCM parameters.

  12. Object detection via feature synthesis using MDL-based genetic programming.

    PubMed

    Lin, Yingqiang; Bhanu, Bir

    2005-06-01

    In this paper, we use genetic programming (GP) to synthesize composite operators and composite features from combinations of primitive operations and primitive features for object detection. The motivation for using GP is to overcome the human experts' limitations of focusing only on conventional combinations of primitive image processing operations in the feature synthesis. GP attempts many unconventional combinations that in some cases yield exceptionally good results. To improve the efficiency of GP and prevent its well-known code bloat problem without imposing severe restriction on the GP search, we design a new fitness function based on minimum description length principle to incorporate both the pixel labeling error and the size of a composite operator into the fitness evaluation process. To further improve the efficiency of GP, smart crossover, smart mutation and a public library ideas are incorporated to identify and keep the effective components of composite operators. Our experiments, which are performed on selected training regions of a training image to reduce the training time, show that compared to normal GP, our GP algorithm finds effective composite operators more quickly and the learned composite operators can be applied to the whole training image and other similar testing images. Also, compared to a traditional region-of-interest extraction algorithm, the composite operators learned by GP are more effective and efficient for object detection.

  13. Identification of Fourier transform infrared photoacoustic spectral features for detection of Aspergillus flavus infection in corn.

    PubMed

    Gordon, S H; Schudy, R B; Wheeler, B C; Wicklow, D T; Greene, R V

    1997-04-01

    Aspergillus flavus and other pathogenic fungi display typical infrared spectra which differ significantly from spectra of substrate materials such as corn. On this basis, specific spectral features have been identified which permit detection of fungal infection on the surface of corn kernels by photoacoustic infrared spectroscopy. In a blind study, ten corn kernels showing bright greenish yellow fluorescence (BGYF) in the germ or endosperm and ten BGYF-negative kernels were correctly classified as infected or not infected by Fourier transform infrared photoacoustic spectroscopy. Earlier studies have shown that BGYF-positive kernels contain the bulk of the aflatoxin contaminating grain at harvest. Ten major spectral features, identified by visual inspection of the photoacoustic spectra of A. flavus mycelium grown in culture versus uninfected corn, were interpreted and assigned by theoretical comparisons of the relative chemical compositions of fungi and corn. The spectral features can be built into either empirical or knowledge-based computer models (expert systems) for automatic infrared detection and segregation of grains or kernels containing aflatoxin from the food and feed supply.

  14. Detection of significant differences between absorption spectra of neutral helium and low temperature photoionized helium plasmas

    SciTech Connect

    Bartnik, A.; Wachulak, P.; Fiedorowicz, H.; Fok, T.; Jarocki, R.; Szczurek, M.

    2013-11-15

    In this work, spectral investigations of photoionized He plasmas were performed. The photoionized plasmas were created by irradiation of helium stream, with intense pulses from laser-plasma extreme ultraviolet (EUV) source. The EUV source was based on a double-stream Xe/Ne gas-puff target irradiated with 10 ns/10 J Nd:YAG laser pulses. The most intense emission from the source spanned a relatively narrow spectral region below 20 nm, however, spectrally integrated intensity at longer wavelengths was also significant. The EUV radiation was focused onto a gas stream, injected into a vacuum chamber synchronously with the EUV pulse. The long-wavelength part of the EUV radiation was used for backlighting of the photoionized plasmas to obtain absorption spectra. Both emission and absorption spectra in the EUV range were investigated. Significant differences between absorption spectra acquired for neutral helium and low temperature photoionized plasmas were demonstrated for the first time. Strong increase of intensities and spectral widths of absorption lines, together with a red shift of the K-edge, was shown.

  15. Bayesian Nonnegative CP Decomposition-based Feature Extraction Algorithm for Drowsiness Detection.

    PubMed

    Qian, Dong; Wang, Bei; Qing, Yun; Zhang, Tao; Zhang, Yu; Wang, Xing; Nakamura, Masatoshi

    2016-10-19

    Daytime short nap involves physiological processes, such as alertness, drowsiness and sleep. The study of the relationship between drowsiness and nap based on physiological signals is a great way to have a better understanding of the periodical rhymes of physiological states. A model of Bayesian nonnegative CP decomposition (BNCPD) was proposed to extract common multiway features from the group-level electroencephalogram (EEG) signals. As an extension of the nonnegative CP decomposition, the BNCPD model involves prior distributions of factor matrices, while the underlying CP rank could be determined automatically based on a Bayesian nonparametric approach. In terms of computational speed, variational inference was applied to approximate the posterior distributions of unknowns. Extensive simulations on the synthetic data illustrated the capability of our model to recover the true CP rank. As a real-world application, the performance of drowsiness detection during daytime short nap by using the BNCPD-based features was compared with that of other traditional feature extraction methods. Experimental results indicated that the BNCPD model outperformed other methods for feature extraction in terms of two evaluation metrics, as well as different parameter settings. Our approach is likely to be a useful tool for automatic CP rank determination and offering a plausible multiway physiological information of individual states.

  16. Comparing features extractors in EEG-based cognitive fatigue detection of demanding computer tasks.

    PubMed

    Rifai Chai; Smith, Mitchell R; Nguyen, Tuan N; Sai Ho Ling; Coutts, Aaron J; Nguyen, Hung T

    2015-01-01

    An electroencephalography (EEG)-based classification system could be used as a tool for detecting cognitive fatigue from demanding computer tasks. The most widely used feature extractor in EEG-based fatigue classification is power spectral density (PSD). This paper investigates PSD and three alternative feature extraction methods, in order to find the best feature extractor for the classification of cognitive fatigue during cognitively demanding tasks. These compared methods are power spectral entropy (PSE), wavelet, and autoregressive (AR). Bayesian neural network was selected as the classifier in this study. The results showed that the use of PSD and PSE methods provide an average accuracy of 60% for each computer task. This finding is slightly improved using the wavelet method which has an average accuracy of 61%. The AR method is the best feature extractor compared with the PSD, PSE and wavelet in this study with accuracy of 75.95% in AX-continuous performance test (AX-CPT), 75.23% in psychomotor vigilance test (PVT) and 76.02% in Stroop task (p-value <; 0.05).

  17. Advanced signal processing method for ground penetrating radar feature detection and enhancement

    NASA Astrophysics Data System (ADS)

    Zhang, Yu; Venkatachalam, Anbu Selvam; Huston, Dryver; Xia, Tian

    2014-03-01

    This paper focuses on new signal processing algorithms customized for an air coupled Ultra-Wideband (UWB) Ground Penetrating Radar (GPR) system targeting highway pavements and bridge deck inspections. The GPR hardware consists of a high-voltage pulse generator, a high speed 8 GSps real time data acquisition unit, and a customized field-programmable gate array (FPGA) control element. In comparison to most existing GPR system with low survey speeds, this system can survey at normal highway speed (60 mph) with a high horizontal resolution of up to 10 scans per centimeter. Due to the complexity and uncertainty of subsurface media, the GPR signal processing is important but challenging. In this GPR system, an adaptive GPR signal processing algorithm using Curvelet Transform, 2D high pass filtering and exponential scaling is proposed to alleviate noise and clutter while the subsurface features are preserved and enhanced. First, Curvelet Transform is used to remove the environmental and systematic noises while maintain the range resolution of the B-Scan image. Then, mathematical models for cylinder-shaped object and clutter are built. A two-dimension (2D) filter based on these models removes clutter and enhances the hyperbola feature in a B-Scan image. Finally, an exponential scaling method is applied to compensate the signal attenuation in subsurface materials and to improve the desired signal feature. For performance test and validation, rebar detection experiments and subsurface feature inspection in laboratory and field configurations are performed.

  18. Multi-object Feature Detection and Error Correction for NIF Automatic Optical Alignment

    SciTech Connect

    Awwal, A S

    2006-07-17

    Fiducials imprinted on laser beams are used to perform video image based alignment of the beams in the National Ignition Facility (NIF) of Lawrence Livermore National Laboratory. In any laser beam alignment operation, a beam needs to be aligned to a reference location. Generally, the beam and reference fiducials are composed of separate beams, as a result only a single feature of each beam needs to be identified for determining the position of the beam or reference. However, it is possible to have the same beam image contain both the beam and reference fiducials. In such instances, it is essential to separately identify these features. In the absence of wavefront correction or when image quality is poor, the features of such beams may get distorted making it difficult to distinguish between different fiducials. Error checking and correction mechanism must be implemented to avoid misidentification of one type of feature as the other. This work presents the algorithm for multi-object detection and error correction implemented for such a beam line image in the NIF facility. Additionally, we show how when the original algorithm fails a secondary algorithm takes over and provides required location outputs.

  19. Land Cover Change Detection Based on Genetically Feature Aelection and Image Algebra Using Hyperion Hyperspectral Imagery

    NASA Astrophysics Data System (ADS)

    Seydi, S. T.; Hasanlou, M.

    2015-12-01

    The Earth has always been under the influence of population growth and human activities. This process causes the changes in land use. Thus, for optimal management of the use of resources, it is necessary to be aware of these changes. Satellite remote sensing has several advantages for monitoring land use/cover resources, especially for large geographic areas. Change detection and attribution of cultivation area over time present additional challenges for correctly analyzing remote sensing imagery. In this regards, for better identifying change in multi temporal images we use hyperspectral images. Hyperspectral images due to high spectral resolution created special placed in many of field. Nevertheless, selecting suitable and adequate features/bands from this data is crucial for any analysis and especially for the change detection algorithms. This research aims to automatically feature selection for detect land use changes are introduced. In this study, the optimal band images using hyperspectral sensor using Hyperion hyperspectral images by using genetic algorithms and Ratio bands, we select the optimal band. In addition, the results reveal the superiority of the implemented method to extract change map with overall accuracy by a margin of nearly 79% using multi temporal hyperspectral imagery.

  20. Real-Time Lane Region Detection Using a Combination of Geometrical and Image Features

    PubMed Central

    Cáceres Hernández, Danilo; Kurnianggoro, Laksono; Filonenko, Alexander; Jo, Kang Hyun

    2016-01-01

    Over the past few decades, pavement markings have played a key role in intelligent vehicle applications such as guidance, navigation, and control. However, there are still serious issues facing the problem of lane marking detection. For example, problems include excessive processing time and false detection due to similarities in color and edges between traffic signs (channeling lines, stop lines, crosswalk, arrows, etc.). This paper proposes a strategy to extract the lane marking information taking into consideration its features such as color, edge, and width, as well as the vehicle speed. Firstly, defining the region of interest is a critical task to achieve real-time performance. In this sense, the region of interest is dependent on vehicle speed. Secondly, the lane markings are detected by using a hybrid color-edge feature method along with a probabilistic method, based on distance-color dependence and a hierarchical fitting model. Thirdly, the following lane marking information is extracted: the number of lane markings to both sides of the vehicle, the respective fitting model, and the centroid information of the lane. Using these parameters, the region is computed by using a road geometric model. To evaluate the proposed method, a set of consecutive frames was used in order to validate the performance. PMID:27869657

  1. Singular Value Decomposition Based Features for Automatic Tumor Detection in Wireless Capsule Endoscopy Images

    PubMed Central

    Karimian Khosroshahi, Ghader; Zolfy Lighvan, Mina

    2016-01-01

    Wireless capsule endoscopy (WCE) is a new noninvasive instrument which allows direct observation of the gastrointestinal tract to diagnose its relative diseases. Because of the large number of images obtained from the capsule endoscopy per patient, doctors need too much time to investigate all of them. So, it would be worthwhile to design a system for detecting diseases automatically. In this paper, a new method is presented for automatic detection of tumors in the WCE images. This method will utilize the advantages of the discrete wavelet transform (DWT) and singular value decomposition (SVD) algorithms to extract features from different color channels of the WCE images. Therefore, the extracted features are invariant to rotation and can describe multiresolution characteristics of the WCE images. In order to classify the WCE images, the support vector machine (SVM) method is applied to a data set which includes 400 normal and 400 tumor WCE images. The experimental results show proper performance of the proposed algorithm for detection and isolation of the tumor images which, in the best way, shows 94%, 93%, and 93.5% of sensitivity, specificity, and accuracy in the RGB color space, respectively. PMID:27478364

  2. Automatic Detection and Classification of Breast Tumors in Ultrasonic Images Using Texture and Morphological Features

    PubMed Central

    Su, Yanni; Wang, Yuanyuan; Jiao, Jing; Guo, Yi

    2011-01-01

    Due to severe presence of speckle noise, poor image contrast and irregular lesion shape, it is challenging to build a fully automatic detection and classification system for breast ultrasonic images. In this paper, a novel and effective computer-aided method including generation of a region of interest (ROI), segmentation and classification of breast tumor is proposed without any manual intervention. By incorporating local features of texture and position, a ROI is firstly detected using a self-organizing map neural network. Then a modified Normalized Cut approach considering the weighted neighborhood gray values is proposed to partition the ROI into clusters and get the initial boundary. In addition, a regional-fitting active contour model is used to adjust the few inaccurate initial boundaries for the final segmentation. Finally, three textures and five morphologic features are extracted from each breast tumor; whereby a highly efficient Affinity Propagation clustering is used to fulfill the malignancy and benign classification for an existing database without any training process. The proposed system is validated by 132 cases (67 benignancies and 65 malignancies) with its performance compared to traditional methods such as level set segmentation, artificial neural network classifiers, and so forth. Experiment results show that the proposed system, which needs no training procedure or manual interference, performs best in detection and classification of ultrasonic breast tumors, while having the lowest computation complexity. PMID:21892371

  3. Effective method for detecting regions of given colors and the features of the region surfaces

    NASA Astrophysics Data System (ADS)

    Gong, Yihong; Zhang, HongJiang

    1994-03-01

    Color can be used as a very important cue for image recognition. In industrial and commercial areas, color is widely used as a trademark or identifying feature in objects, such as packaged goods, advertising signs, etc. In image database systems, one may retrieve an image of interest by specifying prominent colors and their locations in the image (image retrieval by contents). These facts enable us to detect or identify a target object using colors. However, this task depends mainly on how effectively we can identify a color and detect regions of the given color under possibly non-uniform illumination conditions such as shade, highlight, and strong contrast. In this paper, we present an effective method to detect regions matching given colors, along with the features of the region surfaces. We adopt the HVC color coordinates in the method because of its ability of completely separating the luminant and chromatic components of colors. Three basis functions functionally serving as the low-pass, high-pass, and band-pass filters, respectively, are introduced.

  4. Simultaneous soft and hard X-ray spectroscopy of AM Herculis with EXOSAT: Discovery of photospheric absorption features

    NASA Technical Reports Server (NTRS)

    Paerels, Frits; Heise, John; Teeseling, Andre Van

    1994-01-01

    We present 0.1-10 keV spectroscopic observations of AM Herculis obtained with the Transmission Grating Spectrometers and Medium Energy experiments on EXOSAT, taken when the object was in its 'reversed X-ray mode.' The observation covers over six binary orbits without interruption, enabling us to analyze the phase and intensity dependence of both the hard and the soft spectrum simultaneously. We resolve the optically thick soft X-ray spectrum, and find definite evidence for time- and phase-dependent photospheric absorption structure arising in the white dwarf atmosphere. We present a simple empirical analysis of the combined soft and hard X-ray spectra, to examine whether the effect of a better determination of the column density of neutral absorbing material, afforded by our data, would solve the problem of the large relative soft X-ray overluminosity previously observed in AM Her. We find that a single absorbing column fits the entire spectrum, and that the column densities implied are indeed substantially lower than previously estimated. However, during half the binary orbit we still determine a strong lower limit to the soft-to-hard luminosity ratio of L(sub soft)/L(sub hard) is greater than or approximately equal to 10, in conflict with the simple radiative shock models for the accretion region. We argue that this indicates the need to reexamine the luminosity problem using explicit models for the emission spectrum based on a full solution of the atmospheric radiative transfer problem.

  5. Detection of hydrogen peroxide based on long-path absorption spectroscopy using a CW EC-QCL

    NASA Astrophysics Data System (ADS)

    Sanchez, N. P.; Yu, Y.; Dong, L.; Griffin, R.; Tittel, F. K.

    2016-02-01

    A sensor system based on a CW EC-QCL (mode-hop-free range 1225-1285 cm-1) coupled with long-path absorption spectroscopy was developed for the monitoring of gas-phase hydrogen peroxide (H2O2) using an interference-free absorption line located at 1234.055 cm-1. Wavelength modulation spectroscopy (WMS) with second harmonic detection was implemented for data processing. Optimum levels of pressure and modulation amplitude of the sensor system led to a minimum detection limit (MDL) of 25 ppb using an integration time of 280 sec. The selected absorption line for H2O2, which exhibits no interference from H2O, makes this sensor system suitable for sensitive and selective monitoring of H2O2 levels in decontamination and sterilization processes based on Vapor Phase Hydrogen Peroxide (VPHP) units, in which a mixture of H2O and H2O2 is generated. Furthermore, continuous realtime monitoring of H2O2 concentrations in industrial facilities employing this species can be achieved with this sensing system in order to evaluate average permissible exposure levels (PELs) and potential exceedances of guidelines established by the US Occupational Safety and Health Administration for H2O2.

  6. Bright Retinal Lesions Detection using Colour Fundus Images Containing Reflective Features

    SciTech Connect

    Giancardo, Luca; Karnowski, Thomas Paul; Chaum, Edward; Meriaudeau, Fabrice; Tobin Jr, Kenneth William; Li, Yaquin

    2009-01-01

    In the last years the research community has developed many techniques to detect and diagnose diabetic retinopathy with retinal fundus images. This is a necessary step for the implementation of a large scale screening effort in rural areas where ophthalmologists are not available. In the United States of America, the incidence of diabetes is worryingly increasing among the young population. Retina fundus images of patients younger than 20 years old present a high amount of reflection due to the Nerve Fibre Layer (NFL), the younger the patient the more these reflections are visible. To our knowledge we are not aware of algorithms able to explicitly deal with this type of reflection artefact. This paper presents a technique to detect bright lesions also in patients with a high degree of reflective NFL. First, the candidate bright lesions are detected using image equalization and relatively simple histogram analysis. Then, a classifier is trained using texture descriptor (Multi-scale Local Binary Patterns) and other features in order to remove the false positives in the lesion detection. Finally, the area of the lesions is used to diagnose diabetic retinopathy. Our database consists of 33 images from a telemedicine network currently developed. When determining moderate to high diabetic retinopathy using the bright lesions detected the algorithm achieves a sensitivity of 100% at a specificity of 100% using hold-one-out testing.

  7. Research on Copy-Move Image Forgery Detection Using Features of Discrete Polar Complex Exponential Transform

    NASA Astrophysics Data System (ADS)

    Gan, Yanfen; Zhong, Junliu

    2015-12-01

    With the aid of sophisticated photo-editing software, such as Photoshop, copy-move image forgery operation has been widely applied and has become a major concern in the field of information security in the modern society. A lot of work on detecting this kind of forgery has gained great achievements, but the detection results of geometrical transformations of copy-move regions are not so satisfactory. In this paper, a new method based on the Polar Complex Exponential Transform is proposed. This method addresses issues in image geometric moment, focusing on constructing rotation invariant moment and extracting features of the rotation invariant moment. In order to reduce rounding errors of the transform from the Polar coordinate system to the Cartesian coordinate system, a new transformation method is presented and discussed in detail at the same time. The new method constructs a 9 × 9 shrunk template to transform the Cartesian coordinate system back to the Polar coordinate system. It can reduce transform errors to a much greater degree. Forgery detection, such as copy-move image forgery detection, is a difficult procedure, but experiments prove our method is a great improvement in detecting and identifying forgery images affected by the rotated transform.

  8. Truncated feature representation for automatic target detection using transformed data-based decomposition

    NASA Astrophysics Data System (ADS)

    Riasati, Vahid R.

    2016-05-01

    In this work, the data covariance matrix is diagonalized to provide an orthogonal bases set using the eigen vectors of the data. The eigen-vector decomposition of the data is transformed and filtered in the transform domain to truncate the data for robust features related to a specified set of targets. These truncated eigen features are then combined and reconstructed to utilize in a composite filter and consequently utilized for the automatic target detection of the same class of targets. The results associated with the testing of the current technique are evaluated using the peak-correlation and peak-correlation energy metrics and are presented in this work. The inverse transformed eigen-bases of the current technique may be thought of as an injected sparsity to minimize data in representing the skeletal data structure information associated with the set of targets under consideration.

  9. Feature extraction using adaptive multiwavelets and synthetic detection index for rotor fault diagnosis of rotating machinery

    NASA Astrophysics Data System (ADS)

    Lu, Na; Xiao, Zhihuai; Malik, O. P.

    2015-02-01

    State identification to diagnose the condition of rotating machinery is often converted to a classification problem of values of non-dimensional symptom parameters (NSPs). To improve the sensitivity of the NSPs to the changes in machine condition, a novel feature extraction method based on adaptive multiwavelets and the synthetic detection index (SDI) is proposed in this paper. Based on the SDI maximization principle, optimal multiwavelets are searched by genetic algorithms (GAs) from an adaptive multiwavelets library and used for extracting fault features from vibration signals. By the optimal multiwavelets, more sensitive NSPs can be extracted. To examine the effectiveness of the optimal multiwavelets, conventional methods are used for comparison study. The obtained NSPs are fed into K-means classifier to diagnose rotor faults. The results show that the proposed method can effectively improve the sensitivity of the NSPs and achieve a higher discrimination rate for rotor fault diagnosis than the conventional methods.

  10. Enhanced retinal modeling for face recognition and facial feature point detection under complex illumination conditions

    NASA Astrophysics Data System (ADS)

    Cheng, Yong; Li, Zuoyong; Jiao, Liangbao; Lu, Hong; Cao, Xuehong

    2016-07-01

    We improved classic retinal modeling to alleviate the adverse effect of complex illumination on face recognition and extracted robust image features. Our improvements on classic retinal modeling included three aspects. First, a combined filtering scheme was applied to simulate functions of horizontal and amacrine cells for accurate local illumination estimation. Second, we developed an optimal threshold method for illumination classification. Finally, we proposed an adaptive factor acquisition model based on the arctangent function. Experimental results on the combined Yale B; the Carnegie Mellon University poses, illumination, and expression; and the Labeled Face Parts in the Wild databases show that the proposed method can effectively alleviate illumination difference of images under complex illumination conditions, which is helpful for improving the accuracy of face recognition and that of facial feature point detection.

  11. Label-free assay for the detection of glucose mediated by the effects of narrowband absorption on quantum dot photoluminescence

    NASA Astrophysics Data System (ADS)

    Khan, Saara A.; Smith, Gennifer T.; Ellerbee, Audrey K.

    2014-03-01

    We present a novel strategy for label-free detection of glucose based on CdSe/ZnS core/shell quantum dots (QDs). We exploit the concentration-dependent, narrowband absorption of the hexokinase-glucose 6-phosphate dehydrogenase enzymatic assay to selectively filter a 365-nm excitation source, leading to a proportional decrease in the photoluminescence intensity of the QDs. The visible wavelength emission of the QDs enables quantitative readout using standard visible detectors (e.g., CCD). Experimental results show highly linear QD photoluminescence over the clinically relevant glucose concentration range of 1-25mM, in excellent agreement with detection methods demonstrated by others. The method has a demonstrated limit of detection of 3.5μM, also on par with the best proposed methods. A significant advantage of our strategy is the complete elimination of QDs as a consumable. In contrast with other methods of QD-based measurement of glucose, our system does not require the glucose solution to be mixed with the QDs, thereby decreasing its overall cost and making it an ideal strategy for point-of-care detection of glucose in low-resource areas. Furthermore, readout can be accomplished with low-cost, portable detectors such as cellular phones, eliminating the need for expensive and bulky spectrophotometers to output quantitative information. The general strategy we present is useful for other biosensing applications involving chemistries with unique absorption peaks falling within the excitation band of available QDs.

  12. Hydrophilic Indolium Cycloruthenated Complex System for Visual Detection of Bisulfite with a Large Red Shift in Absorption.

    PubMed

    Su, Xianlong; Hu, Rongrong; Li, Xianghong; Zhu, Jun; Luo, Facheng; Niu, Xuehu; Li, Mei; Zhao, Qiang

    2016-01-19

    Bisulfite, as an important additive in foodstuffs, is one of the most widely distributed environmental pollutants. The excessive intake of bisulfite may cause asthmatic attacks and allergic reactions. Therefore, the determination and visual detection of bisulfite are very important. Herein, a newly designed hydrophilic indolium cycloruthenated complex, [Ru(mepbi)(bpy)2](+) [1; bpy = 2,2'-bipyridine and Hmepbi = 3,3-dimethyl-1-ethyl-2-[4-(pyridin-2-yl)styryl]benzo[e]indolium iodide (3)], was successfully synthesized and used as a bisulfite probe. The bisulfite underwent a 1,4-addition reaction with complex 1 in PBS buffer (10 mM, pH 7.40), resulting in a dramatic change in absorption spectra with a red shift of over 100 nm and a remarkable change in solution color from yellow to pink. It is worth noting that this obvious bathochromic shift is rarely observed in the detection of bisulfite through an addition reaction. The detection limit was calculated to be as low as 0.12 μM by UV-vis absorption spectroscopy. Moreover, complex 1 was also used to detect bisulfite in sugar samples (granulated and crystal sugar) with good recovery.

  13. Fault detection and classification in chemical processes based on neural networks with feature extraction.

    PubMed

    Zhou, Yifeng; Hahn, Juergen; Mannan, M Sam

    2003-10-01

    Feed forward neural networks are investigated here for fault diagnosis in chemical processes, especially batch processes. The use of the neural model prediction error as the residual for fault diagnosis of sensor and component is analyzed. To reduce the training time required for the neural process model, an input feature extraction process for the neural model is implemented. An additional radial basis function neural classifier is developed to isolate faults from the residual generated, and results are presented to demonstrate the satisfactory detection and isolation of faults using this approach.

  14. Absorption features in the quasar HS 1603 + 3820 II. Distance to the absorber obtained from photoionisation modelling

    NASA Astrophysics Data System (ADS)

    Różańska, A.; Nikołajuk, M.; Czerny, B.; Dobrzycki, A.; Hryniewicz, K.; Bechtold, J.; Ebeling, H.

    2014-04-01

    We present the photoionisation modelling of the intrinsic absorber in the bright quasar HS 1603 + 3820. We constructed the broad-band spectral energy distribution using the optical/UV/X-ray observations from different instruments as inputs for the photoionisation calculations. The spectra from the Keck telescope show extremely high CIV to HI ratios, for the first absorber in system A, named A1. This value, together with high column density of CIV ion, place strong constraints on the photoionisation model. We used two photoionisation codes to derive the hydrogen number density at the cloud illuminated surface. By estimating bolometric luminosity of HS 1603 + 3820 using the typical formula for quasars, we calculated the distance to A1. We could find one photoionization solution, by assuming either a constant density cloud (which was modelled using CLOUDY), or a stratified cloud (which was modelled using TITAN), as well as the solar abundances. This model explained both the ionic column density of CIV and the high CIV to HI ratio. The location of A1 is 0.1 pc, and it is situated even closer to the nucleus than the possible location of the Broad Line Region in this object. The upper limit of the distance is sensitive to the adopted covering factor and the carbon abundance. Photoionisation modelling always prefers dense clouds with the number density n0 = 1010 - 1012 cm-3, which explains intrinsic absorption in HS 1603 + 3820. This number density is of the same order as that in the disk atmosphere at the implied distance of A1. Therefore, our results show that the disk wind that escapes from the outermost accretion disk atmosphere can build up dense absorber in quasars.

  15. A Widely Applicable Silver Sol for TLC Detection with Rich and Stable SERS Features

    NASA Astrophysics Data System (ADS)

    Zhu, Qingxia; Li, Hao; Lu, Feng; Chai, Yifeng; Yuan, Yongfang

    2016-04-01

    Thin-layer chromatography (TLC) coupled with surface-enhanced Raman spectroscopy (SERS) has gained tremendous popularity in the study of various complex systems. However, the detection of hydrophobic analytes is difficult, and the specificity still needs to be improved. In this study, a SERS-active non-aqueous silver sol which could activate the analytes to produce rich and stable spectral features was rapidly synthesized. Then, the optimized silver nanoparticles (AgNPs)-DMF sol was employed for TLC-SERS detection of hydrophobic (and also hydrophilic) analytes. SERS performance of this sol was superior to that of traditional Lee-Meisel AgNPs due to its high specificity, acceptable stability, and wide applicability. The non-aqueous AgNPs would be suitable for the TLC-SERS method, which shows great promise for applications in food safety assurance, environmental monitoring, medical diagnoses, and many other fields.

  16. Application of rich feature descriptors to small target detection in wide-area persistent ISR systems

    NASA Astrophysics Data System (ADS)

    Miller, Christopher W.; Edelberg, Jason A.; Wilson, Michael L.; Novak, Kyle

    2014-06-01

    One of the desired capabilities for wide-area persistent ISR systems is to reliably locate and subsequently track the movement of targets within the field of view. Current wide-area persistent ISR systems are characterized by large pixel overall counts and very large fields of view. This leads to a large ground sample distance with few pixels-on-target. Locating targets under these constraints is extremely difficult due to the fact that the targets present very little detailed structure. In this paper we will present the application of rich image feature descriptors combined with advanced statistical target detection methodologies to the airborne ISR problem. We will demonstrate that these algorithms can reliably locate targets in the scene without relying on the target's motion to form a detection. This is useful in ISR application where it is desirable to be able to continuously track a target through stops and maneuvers.

  17. Acoustic Longitudinal Field NIF Optic Feature Detection Map Using Time-Reversal & MUSIC

    SciTech Connect

    Lehman, S K

    2006-02-09

    We developed an ultrasonic longitudinal field time-reversal and MUltiple SIgnal Classification (MUSIC) based detection algorithm for identifying and mapping flaws in fused silica NIF optics. The algorithm requires a fully multistatic data set, that is one with multiple, independently operated, spatially diverse transducers, each transmitter of which, in succession, launches a pulse into the optic and the scattered signal measured and recorded at every receiver. We have successfully localized engineered ''defects'' larger than 1 mm in an optic. We confirmed detection and localization of 3 mm and 5 mm features in experimental data, and a 0.5 mm in simulated data with sufficiently high signal-to-noise ratio. We present the theory, experimental results, and simulated results.

  18. Multi-feature-based robust face detection and coarse alignment method via multiple kernel learning

    NASA Astrophysics Data System (ADS)

    Sun, Bo; Zhang, Di; He, Jun; Yu, Lejun; Wu, Xuewen

    2015-10-01

    Face detection and alignment are two crucial tasks to face recognition which is a hot topic in the field of defense and security, whatever for the safety of social public, personal property as well as information and communication security. Common approaches toward the treatment of these tasks in recent years are often of three types: template matching-based, knowledge-based and machine learning-based, which are always separate-step, high computation cost or fragile robust. After deep analysis on a great deal of Chinese face images without hats, we propose a novel face detection and coarse alignment method, which is inspired by those three types of methods. It is multi-feature fusion with Simple Multiple Kernel Learning1 (Simple-MKL) algorithm. The proposed method is contrasted with competitive and related algorithms, and demonstrated to achieve promising results.

  19. A Widely Applicable Silver Sol for TLC Detection with Rich and Stable SERS Features.

    PubMed

    Zhu, Qingxia; Li, Hao; Lu, Feng; Chai, Yifeng; Yuan, Yongfang

    2016-12-01

    Thin-layer chromatography (TLC) coupled with surface-enhanced Raman spectroscopy (SERS) has gained tremendous popularity in the study of various complex systems. However, the detection of hydrophobic analytes is difficult, and the specificity still needs to be improved. In this study, a SERS-active non-aqueous silver sol which could activate the analytes to produce rich and stable spectral features was rapidly synthesized. Then, the optimized silver nanoparticles (AgNPs)-DMF sol was employed for TLC-SERS detection of hydrophobic (and also hydrophilic) analytes. SERS performance of this sol was superior to that of traditional Lee-Meisel AgNPs due to its high specificity, acceptable stability, and wide applicability. The non-aqueous AgNPs would be suitable for the TLC-SERS method, which shows great promise for applications in food safety assurance, environmental monitoring, medical diagnoses, and many other fields.

  20. On the use of feature selection to improve the detection of sea oil spills in SAR images

    NASA Astrophysics Data System (ADS)

    Mera, David; Bolon-Canedo, Veronica; Cotos, J. M.; Alonso-Betanzos, Amparo

    2017-03-01

    Fast and effective oil spill detection systems are crucial to ensure a proper response to environmental emergencies caused by hydrocarbon pollution on the ocean's surface. Typically, these systems uncover not only oil spills, but also a high number of look-alikes. The feature extraction is a critical and computationally intensive phase where each detected dark spot is independently examined. Traditionally, detection systems use an arbitrary set of features to discriminate between oil spills and look-alikes phenomena. However, Feature Selection (FS) methods based on Machine Learning (ML) have proved to be very useful in real domains for enhancing the generalization capabilities of the classifiers, while discarding the existing irrelevant features. In this work, we present a generic and systematic approach, based on FS methods, for choosing a concise and relevant set of features to improve the oil spill detection systems. We have compared five FS methods: Correlation-based feature selection (CFS), Consistency-based filter, Information Gain, ReliefF and Recursive Feature Elimination for Support Vector Machine (SVM-RFE). They were applied on a 141-input vector composed of features from a collection of outstanding studies. Selected features were validated via a Support Vector Machine (SVM) classifier and the results were compared with previous works. Test experiments revealed that the classifier trained with the 6-input feature vector proposed by SVM-RFE achieved the best accuracy and Cohen's kappa coefficient (87.1% and 74.06% respectively). This is a smaller feature combination with similar or even better classification accuracy than previous works. The presented finding allows to speed up the feature extraction phase without reducing the classifier accuracy. Experiments also confirmed the significance of the geometrical features since 75.0% of the different features selected by the applied FS methods as well as 66.67% of the proposed 6-input feature vector belong to

  1. Modeling absorption spectra for detection of the combustion products of jet engines by laser remote sensing.

    PubMed

    Voitsekhovskaya, Olga K; Kashirskii, Danila E; Egorov, Oleg V; Shefer, Olga V

    2016-05-10

    The absorption spectra of exhaust gases (H2O, CO, CO2, NO, NO2, and SO2) and aerosol (soot and Al2O3) particles were modeled at different temperatures for the first time and suitable spectral ranges were determined for conducting laser remote sensing of the combustion products of jet engines. The calculations were conducted on the basis of experimental concentrations of the substances and the sizes of the aerosol particles. The temperature and geometric parameters of jet engine exhausts were also taken from the literature. The absorption spectra were obtained via the line-by-line method, making use of the spectral line parameters from the authors' own high-temperature databases (for NO2 and SO2 gases) and the HITEMP 2010 database, and taking into account atmospheric transmission. Finally, the theoretical absorption spectra of the exhaust gases were plotted at temperatures of 400, 700, and 1000 K, and the impact of aerosol particles on the total exhaust spectra was estimated in spectral ranges suitable for remote sensing applications.

  2. Application of Geologic Mapping Techniques and Autonomous Feature Detection to Future Exploration of Europa

    NASA Astrophysics Data System (ADS)

    Bunte, M. K.; Tanaka, K. L.; Doggett, T.; Figueredo, P. H.; Lin, Y.; Greeley, R.; Saripalli, S.; Bell, J. F.

    2013-12-01

    Europa's extremely young surface age, evidence for extensive resurfacing, and indications of a sub-surface ocean elevate its astrobiological potential for habitable environments and make it a compelling focus for study. Knowledge of the global distribution and timing of Europan geologic units is a key step in understanding the history of the satellite and for identifying areas relevant for exploration. I have produced a 1:15M scale global geologic map of Europa which represents a proportionate distribution of four unit types and associated features: plains, linea, chaos, and crater materials. Mapping techniques differ somewhat from other planetary maps but do provide a method to establish stratigraphic markers and to illustrate the surface history through four periods of formation as a function of framework lineament cross-cutting relationships. Correlations of observed features on Europa with Earth analogs enforce a multi-process theory for formation rather than the typical reliance on the principle of parsimony. Lenticulae and microchaos are genetically similar and most likely form by diapirism. Platy and blocky chaos units, endmembers of archetypical chaos, are best explained by brine mobilization. Ridges account for the majority of lineaments and may form by a number of methods indicative of local conditions; most form by either tidal pumping or shear heating. The variety of morphologies exhibited by bands indicates that multiple formation mechanisms apply once fracturing of the brittle surface over a ductile subsurface is initiated. Mapping results support the interpretation that Europa's shell has thickened over time resulting in changes in the style and intensity of deformation. Mapping serves as an index for change detection and classification, aids in pre-encounter targeting, and supports the selection of potential landing sites. Highest priority target areas are those which indicate geophysical activity by the presence of volcanic plumes, outgassing, or

  3. Rotation-Invariant Features for Multi-Oriented Text Detection in Natural Images

    PubMed Central

    Yao, Cong; Zhang, Xin; Bai, Xiang; Liu, Wenyu; Ma, Yi; Tu, Zhuowen

    2013-01-01

    Texts in natural scenes carry rich semantic information, which can be used to assist a wide range of applications, such as object recognition, image/video retrieval, mapping/navigation, and human computer interaction. However, most existing systems are designed to detect and recognize horizontal (or near-horizontal) texts. Due to the increasing popularity of mobile-computing devices and applications, detecting texts of varying orientations from natural images under less controlled conditions has become an important but challenging task. In this paper, we propose a new algorithm to detect texts of varying orientations. Our algorithm is based on a two-level classification scheme and two sets of features specially designed for capturing the intrinsic characteristics of texts. To better evaluate the proposed method and compare it with the competing algorithms, we generate a comprehensive dataset with various types of texts in diverse real-world scenes. We also propose a new evaluation protocol, which is more suitable for benchmarking algorithms for detecting texts in varying orientations. Experiments on benchmark datasets demonstrate that our system compares favorably with the state-of-the-art algorithms when handling horizontal texts and achieves significantly enhanced performance on variant texts in complex natural scenes. PMID:23940544

  4. [Spectral features analysis of Pinus massoniana with pest of Dendrolimus punctatus Walker and levels detection].

    PubMed

    Xu, Zhang-Hua; Liu, Jian; Yu, Kun-Yong; Gong, Cong-Hong; Xie, Wan-Jun; Tang, Meng-Ya; Lai, Ri-Wen; Li, Zeng-Lu

    2013-02-01

    Taking 51 field measured hyperspectral data with different pest levels in Yanping, Fujian Province as objects, the spectral reflectance and first derivative features of 4 levels of healthy, mild, moderate and severe insect pest were analyzed. On the basis of 7 detecting parameters construction, the pest level detecting models were built. The results showed that (1) the spectral reflectance of Pinus massoniana with pests were significantly lower than that of healthy state, and the higher the pest level, the lower the reflectance; (2) with the increase in pest level, the spectral reflectance curves' "green peak" and "red valley" of Pinus massoniana gradually disappeared, and the red edge was leveleds (3) the pest led to spectral "green peak" red shift, red edge position blue shift, but the changes in "red valley" and near-infrared position were complicated; (4) CARI, RES, REA and REDVI were highly relevant to pest levels, and the correlations between REP, RERVI, RENDVI and pest level were weak; (5) the multiple linear regression model with the variables of the 7 detection parameters could effectively detect the pest levels of Dendrolimus punctatus Walker, with both the estimation rate and accuracy above 0.85.

  5. Road detection in arid environments using uniformly distributed random based features

    NASA Astrophysics Data System (ADS)

    Plodpradista, P.; Keller, J. M.; Popescu, M.

    2016-05-01

    The capability of detecting an unpaved road in arid environments can greatly enhance an explosive hazard detection system. One approach is to segment out the off-road area and the area above the horizon, which is considered to be irrelevant for the task in hand. Segmenting out irrelevant areas, such as the region above the horizon, allows the explosive hazard detection system to process a smaller region in a scene, enabling a more computationally complex approach. In this paper, we propose a novel approach for speeding up the detection algorithms based on random projection and random selection. Both methods have a low computational cost and reduce the dimensionality of the data while approximately preserving, with a certain probability, the pair-wise point distances. Dimensionality reduction allows any classifier employed in our proposed algorithm to consume fewer computational resources. Furthermore, by applying the random projections directly to image intensity patches, there is no feature extraction needed. The data used in our proposed algorithms are obtained from sensors on board a U.S. Army countermine vehicle. We tested our proposed algorithms on data obtained from several runs on an arid climate road. In our experiments we compare our algorithms based on random projection and random selection to Principal Component Analysis (PCA), a popular dimensionality reduction method.

  6. Cortical feature analysis and machine learning improves detection of "MRI-negative" focal cortical dysplasia.

    PubMed

    Ahmed, Bilal; Brodley, Carla E; Blackmon, Karen E; Kuzniecky, Ruben; Barash, Gilad; Carlson, Chad; Quinn, Brian T; Doyle, Werner; French, Jacqueline; Devinsky, Orrin; Thesen, Thomas

    2015-07-01

    Focal cortical dysplasia (FCD) is the most common cause of pediatric epilepsy and the third most common lesion in adults with treatment-resistant epilepsy. Advances in MRI have revolutionized the diagnosis of FCD, resulting in higher success rates for resective epilepsy surgery. However, many patients with histologically confirmed FCD have normal presurgical MRI studies ('MRI-negative'), making presurgical diagnosis difficult. The purpose of this study was to test whether a novel MRI postprocessing method successfully detects histopathologically verified FCD in a sample of patients without visually appreciable lesions. We applied an automated quantitative morphometry approach which computed five surface-based MRI features and combined them in a machine learning model to classify lesional and nonlesional vertices. Accuracy was defined by classifying contiguous vertices as "lesional" when they fell within the surgical resection region. Our multivariate method correctly detected the lesion in 6 of 7 MRI-positive patients, which is comparable with the detection rates that have been reported in univariate vertex-based morphometry studies. More significantly, in patients that were MRI-negative, machine learning correctly identified 14 out of 24 FCD lesions (58%). This was achieved after separating abnormal thickness and thinness into distinct classifiers, as well as separating sulcal and gyral regions. Results demonstrate that MRI-negative images contain sufficient information to aid in the in vivo detection of visually elusive FCD lesions.

  7. Volume-based features for detection of bladder wall abnormal regions via MR cystography.

    PubMed

    Duan, Chaijie; Yuan, Kehong; Liu, Fanghua; Xiao, Ping; Lv, Guoqing; Liang, Zhengrong

    2011-09-01

    This paper proposes a framework for detecting the suspected abnormal region of the bladder wall via magnetic resonance (MR) cystography. Volume-based features are used. First, the bladder wall is divided into several layers, based on which a path from each voxel on the inner border to the outer border is found. By using the path length to measure the wall thickness and a bent rate (BR) term to measure the geometry property of the voxels on the inner border, the seed voxels representing the abnormalities on the inner border are determined. Then, by tracing the path from each seed, a weighted BR term is constructed to determine the suspected voxels, which are on the path and inside the bladder wall. All the suspected voxels are grouped together for the abnormal region. This work is significantly different from most of the previous computer-aided bladder tumor detection reports on two aspects. First of all, the T (1)-weighted MR images are used which give better image contrast and texture information for the bladder wall, comparing with the computed tomography images. Second, while most previous reports detected the abnormalities and indicated them on the reconstructed 3-D bladder model by surface rendering, we further determine the possible region of the abnormality inside the bladder wall. This study aims at a noninvasive procedure for bladder tumor detection and abnormal region delineation, which has the potential for further clinical analysis such as the invasion depth of the tumor and virtual cystoscopy diagnosis. Five datasets including two patients and three volunteers were used to test the presented method, all the tumors were detected by the method, and the overlap rates of the regions delineated by the computer against the experts were measured. The results demonstrated the potential of the method for detecting bladder wall abnormal regions via MR cystography.

  8. A research of selected textural features for detection of asbestos-cement roofing sheets using orthoimages

    NASA Astrophysics Data System (ADS)

    Książek, Judyta

    2015-10-01

    At present, there has been a great interest in the development of texture based image classification methods in many different areas. This study presents the results of research carried out to assess the usefulness of selected textural features for detection of asbestos-cement roofs in orthophotomap classification. Two different orthophotomaps of southern Poland (with ground resolution: 5 cm and 25 cm) were used. On both orthoimages representative samples for two classes: asbestos-cement roofing sheets and other roofing materials were selected. Estimation of texture analysis usefulness was conducted using machine learning methods based on decision trees (C5.0 algorithm). For this purpose, various sets of texture parameters were calculated in MaZda software. During the calculation of decision trees different numbers of texture parameters groups were considered. In order to obtain the best settings for decision trees models cross-validation was performed. Decision trees models with the lowest mean classification error were selected. The accuracy of the classification was held based on validation data sets, which were not used for the classification learning. For 5 cm ground resolution samples, the lowest mean classification error was 15.6%. The lowest mean classification error in the case of 25 cm ground resolution was 20.0%. The obtained results confirm potential usefulness of the texture parameter image processing for detection of asbestos-cement roofing sheets. In order to improve the accuracy another extended study should be considered in which additional textural features as well as spectral characteristics should be analyzed.

  9. Source and path corrections, feature selection, and outlier detection applied to regional event discrimination in China

    SciTech Connect

    Hartse, H.E.; Taylor, S.R.; Phillips, W.S.; Velasco, A.A.

    1999-03-01

    The authors are investigating techniques to improve regional discrimination performance in uncalibrated regions. These include combined source and path corrections, spatial path corrections, path-specific waveguide corrections to construct frequency-dependent amplitude corrections that remove attenuation, corner frequency scaling, and source region/path effects (such as blockages). The spatial method and the waveguide method address corrections for specific source regions and along specific paths. After applying the above corrections to phase amplitudes, the authors form amplitude ratios and use a combination of feature selection and outlier detection to choose the best-performing combination of discriminants. Feature selection remains an important issue. Most stations have an inadequate population of nuclear explosions on which to base discriminant selection. Additionally, mining explosions are probably not good surrogates for nuclear explosions. The authors are exploring the feasibility of sampling the source and path corrected amplitudes for each phase as a function of frequency in an outlier detection framework. In this case, the source identification capability will be based on the inability of the earthquake source model to fit data from explosion sources.

  10. Automatic epileptic seizure detection in EEGs based on line length feature and artificial neural networks.

    PubMed

    Guo, Ling; Rivero, Daniel; Dorado, Julián; Rabuñal, Juan R; Pazos, Alejandro

    2010-08-15

    About 1% of the people in the world suffer from epilepsy. The main characteristic of epilepsy is the recurrent seizures. Careful analysis of the electroencephalogram (EEG) recordings can provide valuable information for understanding the mechanisms behind epileptic disorders. Since epileptic seizures occur irregularly and unpredictably, automatic seizure detection in EEG recordings is highly required. Wavelet transform (WT) is an effective analysis tool for non-stationary signals, such as EEGs. The line length feature reflects the waveform dimensionality changes and is a measure sensitive to variation of the signal amplitude and frequency. This paper presents a novel method for automatic epileptic seizure detection, which uses line length features based on wavelet transform multiresolution decomposition and combines with an artificial neural network (ANN) to classify the EEG signals regarding the existence of seizure or not. To the knowledge of the authors, there exists no similar work in the literature. A famous public dataset was used to evaluate the proposed method. The high accuracy obtained for three different classification problems testified the great success of the method.

  11. Spinal focal lesion detection in multiple myeloma using multimodal image features

    NASA Astrophysics Data System (ADS)

    Fränzle, Andrea; Hillengass, Jens; Bendl, Rolf

    2015-03-01

    Multiple myeloma is a tumor disease in the bone marrow that affects the skeleton systemically, i.e. multiple lesions can occur in different sites in the skeleton. To quantify overall tumor mass for determining degree of disease and for analysis of therapy response, volumetry of all lesions is needed. Since the large amount of lesions in one patient impedes manual segmentation of all lesions, quantification of overall tumor volume is not possible until now. Therefore development of automatic lesion detection and segmentation methods is necessary. Since focal tumors in multiple myeloma show different characteristics in different modalities (changes in bone structure in CT images, hypointensity in T1 weighted MR images and hyperintensity in T2 weighted MR images), multimodal image analysis is necessary for the detection of focal tumors. In this paper a pattern recognition approach is presented that identifies focal lesions in lumbar vertebrae based on features from T1 and T2 weighted MR images. Image voxels within bone are classified using random forests based on plain intensities and intensity value derived features (maximum, minimum, mean, median) in a 5 x 5 neighborhood around a voxel from both T1 and T2 weighted MR images. A test data sample of lesions in 8 lumbar vertebrae from 4 multiple myeloma patients can be classified at an accuracy of 95% (using a leave-one-patient-out test). The approach provides a reasonable delineation of the example lesions. This is an important step towards automatic tumor volume quantification in multiple myeloma.

  12. Computing network-based features from physiological time series: application to sepsis detection.

    PubMed

    Santaniello, Sabato; Granite, Stephen J; Sarma, Sridevi V; Winslow, Raimond L

    2014-01-01

    Sepsis is a systemic deleterious host response to infection. It is a major healthcare problem that affects millions of patients every year in the intensive care units (ICUs) worldwide. Despite the fact that ICU patients are heavily instrumented with physiological sensors, early sepsis detection remains challenging, perhaps because clinicians identify sepsis by using static scores derived from bed-side measurements individually, i.e., without systematically accounting for potential interactions between these signals and their dynamics. In this study, we apply network-based data analysis to take into account interactions between bed-side physiological time series (PTS) data collected in ICU patients, and we investigate features to distinguish between sepsis and non-sepsis conditions. We treated each PTS source as a node on a graph and we retrieved the graph connectivity matrix over time by tracking the correlation between each pair of sources' signals over consecutive time windows. Then, for each connectivity matrix, we computed the eigenvalue decomposition. We found that, even though raw PTS measurements may have indistinguishable distributions in non-sepsis and early sepsis states, the median /I of the eigenvalues computed from the same data is statistically different (p <; 0.001) in the two states and the evolution of /I may reflect the disease progression. Although preliminary, these findings suggest that network-based features computed from continuous PTS data may be useful for early sepsis detection.

  13. Detecting abnormality in optic nerve head images using a feature extraction analysis.

    PubMed

    Zhu, Haogang; Poostchi, Ali; Vernon, Stephen A; Crabb, David P

    2014-07-01

    Imaging and evaluation of the optic nerve head (ONH) plays an essential part in the detection and clinical management of glaucoma. The morphological characteristics of ONHs vary greatly from person to person and this variability means it is difficult to quantify them in a standardized way. We developed and evaluated a feature extraction approach using shift-invariant wavelet packet and kernel principal component analysis to quantify the shape features in ONH images acquired by scanning laser ophthalmoscopy (Heidelberg Retina Tomograph [HRT]). The methods were developed and tested on 1996 eyes from three different clinical centers. A shape abnormality score (SAS) was developed from extracted features using a Gaussian process to identify glaucomatous abnormality. SAS can be used as a diagnostic index to quantify the overall likelihood of ONH abnormality. Maps showing areas of likely abnormality within the ONH were also derived. Diagnostic performance of the technique, as estimated by ROC analysis, was significantly better than the classification tools currently used in the HRT software - the technique offers the additional advantage of working with all images and is fully automated.

  14. Automatic Road Area Extraction from Printed Maps Based on Linear Feature Detection

    NASA Astrophysics Data System (ADS)

    Callier, Sebastien; Saito, Hideo

    Raster maps are widely available in the everyday life, and can contain a huge amount of information of any kind using labels, pictograms, or color code e.g. However, it is not an easy task to extract roads from those maps due to those overlapping features. In this paper, we focus on an automated method to extract roads by using linear features detection to search for seed points having a high probability to belong to roads. Those linear features are lines of pixels of homogenous color in each direction around each pixel. After that, the seeds are then expanded before choosing to keep or to discard the extracted element. Because this method is not mainly based on color segmentation, it is also suitable for handwritten maps for example. The experimental results demonstrate that in most cases our method gives results similar to usual methods without needing any previous data or user input, but do need some knowledge on the target maps; and does work with handwritten maps if drawn following some basic rules whereas usual methods fail.

  15. Object orientation detection and character recognition using optimal feedforward network and Kohonen's feature map

    NASA Astrophysics Data System (ADS)

    Baykal, Nazife; Yalabik, Nese

    1992-09-01

    A neural network model, namely, Kohonen's Feature Map, together with the optimal feedforward network is used for variable font machine printed character recognition with tolerance to rotation, shift in position, and size errors. The determination of object orientation is found using the many rotated versions of individual symbols. Orientations are detected from printed text, but no knowledge of the context is used. The optimal Bayesian detector is derived, and it is shown that the optimal detector has the form of a feedforward network. This network together with the learning vector quantization (LVQ) approach is able to implement an inspection system which determines the orientation of the fonts. After the size normalization, rotation, and component finding process as a preprocessing step, the text becomes the input for the feature map. The feature map is trained first in an unsupervised manner. The algorithm is then adapted for supervised learning using improved LVQ technique. Rectangular and minimal spanning tree (MST) neighborhood topologies are experimented with. The results are encouraging, 87% of the characters of various fonts are correctly recognized even though the pattern is distorted in shape and transformed in a shift, size, and rotation invariant manner. Experimental results and comparisons are described.

  16. Modelling the Emission And/or Absorption Features in the High Resolution Spectra of the Southern Binary System: HH Car

    NASA Astrophysics Data System (ADS)

    Koseoglu, Dogan; Bakış, Hicran

    2016-07-01

    High-resolution spectra (R=48000) of the southern close binary system, HH Car, has been analyzed with modern analysis techniques. Precise absolute parameters were derived from the simultaneous solution of the radial velocity, produced in this study and the light curves, published. According to the results of these analyses, the primary component is an O9 type main sequence star while the secondary component is a giant/subgiant star with a spectral type of B0. Hα emissions can be seen explicitly in the spectra of HH Car. These features were modelled using the absolute parameters of the components. Since components of HH Car are massive early-type stars, mass loss through stellar winds can be expected. This study revealed that the components of HH Car have stellar winds and the secondary component loses mass to the primary. Stellar winds and the gas stream between the components were modelled as a hot shell around the system. It is determined that the interaction between the winds and the gas stream leads to formation of a high temperature impact region.

  17. A carbon monoxide detection device based on mid-infrared absorption spectroscopy at 4.6 μm

    NASA Astrophysics Data System (ADS)

    Li, Guo-Lin; Sui, Yue; Dong, Ming; Ye, Wei-Lin; Zheng, Chuan-Tao; Wang, Yi-Ding

    2015-05-01

    We present a differential carbon monoxide (CO) concentration sensing device using a self-fabricated spherical mirror (e.g., light collector) and a multi-pass gas chamber. Single-source dual-channel detection method is adopted to suppress the interferences from light source, optical path, and environmental changes. The detection principle of the device is described, and both the optical part and the electrical part are designed and developed. Experiments are carried out to evaluate the sensing performances on CO concentration. The results indicate that the limit of detection is about 10 ppm with an absorption length of 40 cm. As the gas concentration gets larger than 100 ppm, the relative detection error falls into the range of -1.7 to +1.9 %. Based on 12-h long-term measurements on the 100 and 1000 ppm CO samples, the maximum detection errors are about 0.9 and 5.5 %, respectively. Benefit from low cost and competitive characteristics, the proposed device shows potential applications in CO detection under the circumstances of coal-mine production and environmental protection.

  18. Demonstration of a portable near-infrared CH4 detection sensor based on tunable diode laser absorption spectroscopy

    NASA Astrophysics Data System (ADS)

    Zheng, Chuan-Tao; Huang, Jian-Qiang; Ye, Wei-Lin; Lv, Mo; Dang, Jing-Min; Cao, Tian-Shu; Chen, Chen; Wang, Yi-Ding

    2013-11-01

    A portable near-infrared (NIR) CH4 detection sensor based on a distributed feedback (DFB) laser modulated at 1.654 μm is experimentally demonstrated. Intelligent temperature controller with an accuracy of -0.07 to +0.09 °C as well as a scan and modulation module generating saw-wave and cosine-wave signals are developed to drive the DFB laser, and a cost effective lock-in amplifier used to extract the second harmonic signal is integrated. Thorough experiments are carried out to obtain detection performances, including detection range, accuracy, stability and the minimum detection limit (MDL). Measurement results show that the absolute detection error relative to the standard value is less than 7% within the range of 0-100%, and the MDL is estimated to be about 11 ppm under an absorption length of 0.2 m and a noise level of 2 mVpp. Twenty-four hours monitoring on two gas samples (0.1% and 20%) indicates that the absolute errors are less than 7% and 2.5%, respectively, suggesting good long term stability. The sensor reveals competitive characteristics compared with other reported portable or handheld sensors. The developed sensor can also be used for the detection of other gases by adopting other DFB lasers with different center-wavelength using the same hardware and slightly modified software.

  19. Detection of cancerous biological tissue areas by means of infrared absorption and SERS spectroscopy of intercellular fluid

    NASA Astrophysics Data System (ADS)

    Velicka, M.; Urboniene, V.; Ceponkus, J.; Pucetaite, M.; Jankevicius, F.; Sablinskas, V.

    2015-08-01

    We present a novel approach to the detection of cancerous kidney tissue areas by measuring vibrational spectra (IR absorption or SERS) of intercellular fluid taken from the tissue. The method is based on spectral analysis of cancerous and normal tissue areas in order to find specific spectral markers. The samples were prepared by sliding the kidney tissue over a substrate - surface of diamond ATR crystal in case of IR absorption or calcium fluoride optical window in case of SERS. For producing the SERS signal the dried fluid film was covered by silver nanoparticle colloidal solution. In order to suppress fluorescence background the measurements were performed in the NIR spectral region with the excitation wavelength of 1064 nm. The most significant spectral differences - spectral markers - were found in the region between 400 and 1800 cm-1, where spectral bands related to various vibrations of fatty acids, glycolipids and carbohydrates are located. Spectral markers in the IR and SERS spectra are different and the methods can complement each other. Both of them have potential to be used directly during surgery. Additionally, IR absorption spectroscopy in ATR mode can be combined with waveguide probe what makes this method usable in vivo.

  20. [A line-by-line trace gas absorption model and its application in NDIR gas detection technology].

    PubMed

    Fang, Jing; Liu, Wen-qing; Zhang, Tian-shu

    2008-06-01

    An accurate line-by-line integral trace gas absorption model is presented in the present article. It is for mid-infrared band and can be used in the study on and application to detecting trace gas (or pollution gas). First of all, two algorithms of trace gas radioactive properties, line-by-line integral method and band model method, were introduced. The merits and demerits of each were compared. Several recent developed line-by-line integral calculation models were also introduced. Secondly, the basic principle of line-by-line integral trace gas absorption calculation model was described in detail. The absorption coefficient is a function of temperature, frequency (wave number), pressure, gas volume mixing ratio and constants associated with all contributing line transitions. The average monochromatic absorption coefficient at a given frequency of a given gas species can be written as the product of the number density of the molecular species to which the spectral line belongs, the line intensity and a line shape factor. Efficient calculation of the line shape factor may be required for different atmospheric conditions. In the lower atmosphere, the shape of spectral lines is dominated by pressure broadening and can be represented most simply by the Lorentz line shape factor. At high altitudes, the shape of spectral lines is governed by Doppler broadening At intermediate altitudes, they can be modeled using the Voigt line shape factor, a convolution of the Lorentz and Doppler line shape factors. Finally, in the section of experiment, the results calculated by model were compared with that measured by Fourier transform infrared spectrometer. As an instance, the model was applied to the detectors design of NDIR (non-dispersive infrared) technology and the relationship between signal intensity of detectors and concentration of CO2/CO was simulated by model. Available concentration range of detector was given by calculating the results of the model. It is based on

  1. Development of gas fire detection system using tunable diode laser absorption spectroscopy

    NASA Astrophysics Data System (ADS)

    Jiang, Y. L.; Li, G.; Yang, T.; Wang, J. J.

    2017-01-01

    The conventional fire detection methods mainly produce an alarm through detecting the changes in smoke concentration, flame radiation, heat and other physical parameters in the environment, but are unable to provide an early warning of a fire emergency. We have designed a gas fire detection system with a high detection sensitivity and high selectivity using the tunable semiconductor diode laser as a light source and combining wavelength modulation and harmonic detection technology. This system can invert the second harmonic signal obtained to obtain the concentration of carbon monoxide gas (a fire characteristic gas) so as to provide an early warning of fire. We reduce the system offset noise and the background noise generated due to the laser interference by deducting the system background spectrum lines from the second harmonic signal. This can also eliminate the interference of other gas spectral lines to a large extent. We detected the concentration of the carbon monoxide gas generated in smoldering sandalwood fire and open beech wood fire with the homemade fire simulator, and tested the lowest detectable limit of system. The test results show that the lowest detectable limit can reach 5×10-6 the system can maintain stable operation for a long period of time and can automatically trigger a water mist fire extinguishing system, which can fully meet the needs of early fire warning.

  2. Improved Feature Extraction, Feature Selection, and Identification Techniques That Create a Fast Unsupervised Hyperspectral Target Detection Algorithm

    DTIC Science & Technology

    2008-03-01

    According to Stein, Beaven, Hoff, Winter, Schaum , and Stocker (2002:62), the local Gaussian model may not be a valid for hyperspectral data if relatively...David W.J., Scott G. Beaven, Lawrence E. Hoff, Edwin M. Winter, Alan P. Schaum and Alan D. Stocker. “Anomaly Detection for Hyperspectral Imagery

  3. Locally centred Mahalanobis distance: a new distance measure with salient features towards outlier detection.

    PubMed

    Todeschini, Roberto; Ballabio, Davide; Consonni, Viviana; Sahigara, Faizan; Filzmoser, Peter

    2013-07-17

    Outlier detection is a prerequisite to identify the presence of aberrant samples in a given set of data. The identification of such diverse data samples is significant particularly for multivariate data analysis where increasing data dimensionality can easily hinder the data exploration and such outliers often go undetected. This paper is aimed to introduce a novel Mahalanobis distance measure (namely, a pseudo-distance) termed as locally centred Mahalanobis distance, derived by centering the covariance matrix at each data sample rather than at the data centroid as in the classical covariance matrix. Two parameters, called as Remoteness and Isolation degree, were derived from the resulting pairwise distance matrix and their salient features facilitated a better identification of atypical samples isolated from the rest of the data, thus reflecting their potential application towards outlier detection. The Isolation degree demonstrated to be able to detect a new kind of outliers, that is, isolated samples within the data domain, thus resulting in a useful diagnostic tool to evaluate the reliability of predictions obtained by local models (e.g. k-NN models). To better understand the role of Remoteness and Isolation degree in identification of such aberrant data samples, some simulated and published data sets from literature were considered as case studies and the results were compared with those obtained by using Euclidean distance and classical Mahalanobis distance.

  4. A Hybrid Swarm Intelligence Algorithm for Intrusion Detection Using Significant Features

    PubMed Central

    Amudha, P.; Karthik, S.; Sivakumari, S.

    2015-01-01

    Intrusion detection has become a main part of network security due to the huge number of attacks which affects the computers. This is due to the extensive growth of internet connectivity and accessibility to information systems worldwide. To deal with this problem, in this paper a hybrid algorithm is proposed to integrate Modified Artificial Bee Colony (MABC) with Enhanced Particle Swarm Optimization (EPSO) to predict the intrusion detection problem. The algorithms are combined together to find out better optimization results and the classification accuracies are obtained by 10-fold cross-validation method. The purpose of this paper is to select the most relevant features that can represent the pattern of the network traffic and test its effect on the success of the proposed hybrid classification algorithm. To investigate the performance of the proposed method, intrusion detection KDDCup'99 benchmark dataset from the UCI Machine Learning repository is used. The performance of the proposed method is compared with the other machine learning algorithms and found to be significantly different. PMID:26221625

  5. Evaluation of automatic feature detection algorithms in EEG: application to interburst intervals.

    PubMed

    Chauvet, Pierre E; Tich, Sylvie Nguyen The; Schang, Daniel; Clément, Alain

    2014-11-01

    In this paper, we present a new method to compare and improve algorithms for feature detection in neonatal EEG. The method is based on the algorithm׳s ability to compute accurate statistics to predict the results of EEG visual analysis. This method is implemented inside a Java software called EEGDiag, as part of an e-health Web portal dedicated to neonatal EEG. EEGDiag encapsulates a component-based implementation of the detection algorithms called analyzers. Each analyzer is defined by a list of modules executed sequentially. As the libraries of modules are intended to be enriched by its users, we developed a process to evaluate the performance of new modules and analyzers using a database of expertized and categorized EEGs. The evaluation is based on the Davies-Bouldin index (DBI) which measures the quality of cluster separation, so that it will ease the building of classifiers on risk categories. For the first application we tested this method on the detection of interburst intervals (IBI) using a database of 394 EEG acquired on premature newborns. We have defined a class of IBI detectors based on a threshold of the standard deviation on contiguous short time windows, inspired by previous work. Then we determine which detector and what threshold values are the best regarding DBI, as well as the robustness of this choice. This method allows us to make counter-intuitive choices, such as removing the 50 Hz filter (power supply) to save time.

  6. Depth-based human fall detection via shape features and improved extreme learning machine.

    PubMed

    Ma, Xin; Wang, Haibo; Xue, Bingxia; Zhou, Mingang; Ji, Bing; Li, Yibin

    2014-11-01

    Falls are one of the major causes leading to injury of elderly people. Using wearable devices for fall detection has a high cost and may cause inconvenience to the daily lives of the elderly. In this paper, we present an automated fall detection approach that requires only a low-cost depth camera. Our approach combines two computer vision techniques-shape-based fall characterization and a learning-based classifier to distinguish falls from other daily actions. Given a fall video clip, we extract curvature scale space (CSS) features of human silhouettes at each frame and represent the action by a bag of CSS words (BoCSS). Then, we utilize the extreme learning machine (ELM) classifier to identify the BoCSS representation of a fall from those of other actions. In order to eliminate the sensitivity of ELM to its hyperparameters, we present a variable-length particle swarm optimization algorithm to optimize the number of hidden neurons, corresponding input weights, and biases of ELM. Using a low-cost Kinect depth camera, we build an action dataset that consists of six types of actions (falling, bending, sitting, squatting, walking, and lying) from ten subjects. Experimenting with the dataset shows that our approach can achieve up to 91.15% sensitivity, 77.14% specificity, and 86.83% accuracy. On a public dataset, our approach performs comparably to state-of-the-art fall detection methods that need multiple cameras.

  7. Heterodyne detection of the 752.033-GHz H2O rotational absorption line

    NASA Astrophysics Data System (ADS)

    Dionne, G. F.; Fitzgerald, J. F.; Chang, T. S.; Litvak, M. M.; Fetterman, H. R.

    1980-08-01

    A tunable high resolution two stage heterodyne radiometer was developed for the purpose of investigating the intensity and lineshape of the 752.033 GHz rotational transition of water vapor. Single-sideband system noise temperatures of approximately 45,000 K were obtained using a sensitive GaAs Schottky diode as the first stage mixer. First local oscillator power was supplied by a CO2 laser pumped formic acid laser (761.61 GHz), generating an X-band IF signal with theoretical line center at 9.5744 GHz. Second local oscillator power was provided by means of a 3 GHz waveguide cavity filter with only 9 dB insertion loss. In absorption measurements of the H2O taken from a laboratory simulation of a high altitude rocket plume, the center frequency of the 752 GHz line was determined to within 1 MHz of the reported value. A rotational temperature 75 K, a linewidth 5 MHz and a Doppler shift 3 MHz were measured with the line-of-sight intersecting the simulated-plume axis at a distance downstream of 30 nozzle diameters. These absorption data were obtained against continuum background radiation sources at temperatures of 1175 and 300 K.

  8. Heterodyne detection of the 752.033-GHz H2O rotational absorption line

    NASA Technical Reports Server (NTRS)

    Dionne, G. F.; Fitzgerald, J. F.; Chang, T. S.; Litvak, M. M.; Fetterman, H. R.

    1980-01-01

    A tunable high resolution two stage heterodyne radiometer was developed for the purpose of investigating the intensity and lineshape of the 752.033 GHz rotational transition of water vapor. Single-sideband system noise temperatures of approximately 45,000 K were obtained using a sensitive GaAs Schottky diode as the first stage mixer. First local oscillator power was supplied by a CO2 laser pumped formic acid laser (761.61 GHz), generating an X-band IF signal with theoretical line center at 9.5744 GHz. Second local oscillator power was provided by means of a 3 GHz waveguide cavity filter with only 9 dB insertion loss. In absorption measurements of the H2O taken from a laboratory simulation of a high altitude rocket plume, the center frequency of the 752 GHz line was determined to within 1 MHz of the reported value. A rotational temperature 75 K, a linewidth 5 MHz and a Doppler shift 3 MHz were measured with the line-of-sight intersecting the simulated-plume axis at a distance downstream of 30 nozzle diameters. These absorption data were obtained against continuum background radiation sources at temperatures of 1175 and 300 K.

  9. New Cloud Activity on Uranus in 2004: First Detection of a Southern Feature at 2.2 microns

    SciTech Connect

    Hammel, H B; de Pater, I; Gibbard, S; Lockwood, G; Rages, K

    2005-02-02

    On 4 July 2004 UT, we detected one of Uranus' southern hemispheric features at K' (2.2 {micro}m); this is the first such detection in half a decade of adaptive optics imaging of Uranus at the Keck 10-m telescope. When we observed again on 8 July UT the core had faded, and by 9 July UT it was not seen at K' and barely detectable at H. The detection and subsequent disappearance of the feature indicates rapid dynamical processes in the localized vertical aerosol structure.

  10. Towards real-time detection and tracking of spatio-temporal features: Blob-filaments in fusion plasma

    SciTech Connect

    Wu, Lingfei; Wu, Kesheng; Sim, Alex; Churchill, Michael; Choi, Jong Youl; Stathopoulos, Andreas; Chang, Choong -Seock; Klasky, Scott A.

    2016-06-01

    A novel algorithm and implementation of real-time identification and tracking of blob-filaments in fusion reactor data is presented. Similar spatio-temporal features are important in many other applications, for example, ignition kernels in combustion and tumor cells in a medical image. This work presents an approach for extracting these features by dividing the overall task into three steps: local identification of feature cells, grouping feature cells into extended feature, and tracking movement of feature through overlapping in space. Through our extensive work in parallelization, we demonstrate that this approach can effectively make use of a large number of compute nodes to detect and track blob-filaments in real time in fusion plasma. Here, on a set of 30GB fusion simulation data, we observed linear speedup on 1024 processes and completed blob detection in less than three milliseconds using Edison, a Cray XC30 system at NERSC.

  11. Towards real-time detection and tracking of spatio-temporal features: Blob-filaments in fusion plasma

    DOE PAGES

    Wu, Lingfei; Wu, Kesheng; Sim, Alex; ...

    2016-06-01

    A novel algorithm and implementation of real-time identification and tracking of blob-filaments in fusion reactor data is presented. Similar spatio-temporal features are important in many other applications, for example, ignition kernels in combustion and tumor cells in a medical image. This work presents an approach for extracting these features by dividing the overall task into three steps: local identification of feature cells, grouping feature cells into extended feature, and tracking movement of feature through overlapping in space. Through our extensive work in parallelization, we demonstrate that this approach can effectively make use of a large number of compute nodes tomore » detect and track blob-filaments in real time in fusion plasma. Here, on a set of 30GB fusion simulation data, we observed linear speedup on 1024 processes and completed blob detection in less than three milliseconds using Edison, a Cray XC30 system at NERSC.« less

  12. The detection of carbon dioxide leaks using quasi-tomographic laser absorption spectroscopy measurements in variable wind

    PubMed Central

    Levine, Zachary H.; Pintar, Adam L.; Dobler, Jeremy T.; Blume, Nathan; Braun, Michael; Scott Zaccheo, T.; Pernini, Timothy G.

    2016-01-01

    Laser absorption spectroscopy (LAS) has been used over the last several decades for the measurement of trace gasses in the atmosphere. For over a decade, LAS measurements from multiple sources and tens of retroreflectors have been combined with sparse-sample tomography methods to estimate the 2-D distribution of trace gas concentrations and underlying fluxes from point-like sources. In this work, we consider the ability of such a system to detect and estimate the position and rate of a single point leak which may arise as a failure mode for carbon dioxide storage. The leak is assumed to be at a constant rate giving rise to a plume with a concentration and distribution that depend on the wind velocity. We demonstrate the ability of our approach to detect a leak using numerical simulation and also present a preliminary measurement. PMID:27453761

  13. The detection of carbon dioxide leaks using quasi-tomographic laser absorption spectroscopy measurements in variable wind

    DOE PAGES

    Levine, Zachary H.; Pintar, Adam L.; Dobler, Jeremy T.; ...

    2016-04-13

    Laser absorption spectroscopy (LAS) has been used over the last several decades for the measurement of trace gasses in the atmosphere. For over a decade, LAS measurements from multiple sources and tens of retroreflectors have been combined with sparse-sample tomography methods to estimate the 2-D distribution of trace gas concentrations and underlying fluxes from point-like sources. In this work, we consider the ability of such a system to detect and estimate the position and rate of a single point leak which may arise as a failure mode for carbon dioxide storage. The leak is assumed to be at a constant ratemore » giving rise to a plume with a concentration and distribution that depend on the wind velocity. We demonstrate the ability of our approach to detect a leak using numerical simulation and also present a preliminary measurement.« less

  14. High Explosives Mixtures Detection Using Fiber Optics Coupled: Grazing Angle Probe/Fourier Transform Reflection Absorption Infrared Spectroscopy

    NASA Astrophysics Data System (ADS)

    Primera-Pedrozo, Oliva M.; Soto-Feliciano, Yadira M.; Pacheco-Londoño, Leonardo C.; Hernández-Rivera, Samuel P.

    2008-12-01

    Fourier Transform Infrared Spectroscopy operating in Reflection-Absorption mode has been demonstrated as a potential spectroscopic technique to develop new methodologies for detection of chemicals deposited on metallic surfaces. Mid-IR transmitting optical fiber bundle coupled to an external Grazing Angle Probe and an MCT detector together with a bench Michelson interferometer have been used to develop a highly sensitive and selective methodology for detecting traces of organic compounds on metal surfaces. The methodology is remote sensed, in situ and can detect surface loading concentrations of nanograms/cm2 of most target compounds. It is an environmentally friendly, solvent free technique that does not require sample preparation. In this work, the ever-important task of high explosives detection, present as traces of neat crystalline forms and in lab-made mixtures, equivalent to the important explosive formulation Pentolite, has been addressed. The sample set consisted of TNT, PETN (both pure samples) and the formulation based on them: Pentolite, present in various loading concentrations. The spectral data collected was subjected to a number of statistical pre-treatments, including first derivative and normalization transformations to make the data more suitable for the analysis. Principal Components Analysis combined with Linear Discriminant Analysis allowed the classification and discrimination of the target analytes contained in the sample set. Loading concentrations as 220 ng/cm2 were detected for each explosive in neat form and the in the simulated mixture of Pentolite.

  15. Boolean map saliency combined with motion feature used for dim and small target detection in infrared video sequences

    NASA Astrophysics Data System (ADS)

    Wang, Xiaoyang; Peng, Zhenming; Zhang, Ping

    2016-10-01

    Infrared dim and small target detection plays an important role in infrared search and tracking systems. In this paper, a novel infrared dim and small target detection method based on Boolean map saliency and motion feature is proposed. Infrared targets are the most salient parts in images, with high gray level and continuous moving trajectory. Utilizing this property, we build a feature space containing gray level feature and motion feature. The gray level feature is the intensity of input images, while the motion feature is obtained by motion charge in consecutive frames. In the second step, the Boolean map saliency approach is implemented on the gray level feature and motion feature to obtain the gray saliency map and motion saliency map. In the third step, two saliency maps are combined together to get the final result. Numerical experiments have verified the effectiveness of the proposed method. The final detection result can not only get an accurate detection result, but also with fewer false alarms, which is suitable for practical use.

  16. Feasibility of detecting near-surface feature with Rayleigh-wave diffraction

    USGS Publications Warehouse

    Xia, J.; Nyquist, J.E.; Xu, Y.; Roth, M.J.S.; Miller, R.D.

    2007-01-01

    Detection of near-surfaces features such as voids and faults is challenging due to the complexity of near-surface materials and the limited resolution of geophysical methods. Although multichannel, high-frequency, surface-wave techniques can provide reliable shear (S)-wave velocities in different geological settings, they are not suitable for detecting voids directly based on anomalies of the S-wave velocity because of limitations on the resolution of S-wave velocity profiles inverted from surface-wave phase velocities. Therefore, we studied the feasibility of directly detecting near-surfaces features with surface-wave diffractions. Based on the properties of surface waves, we have derived a Rayleigh-wave diffraction traveltime equation. We also have solved the equation for the depth to the top of a void and an average velocity of Rayleigh waves. Using these equations, the depth to the top of a void/fault can be determined based on traveltime data from a diffraction curve. In practice, only two diffraction times are necessary to define the depth to the top of a void/fault and the average Rayleigh-wave velocity that generates the diffraction curve. We used four two-dimensional square voids to demonstrate the feasibility of detecting a void with Rayleigh-wave diffractions: a 2??m by 2??m with a depth to the top of the void of 2??m, 4??m by 4??m with a depth to the top of the void of 7??m, and 6??m by 6??m with depths to the top of the void 12??m and 17??m. We also modeled surface waves due to a vertical fault. Rayleigh-wave diffractions were recognizable for all these models after FK filtering was applied to the synthetic data. The Rayleigh-wave diffraction traveltime equation was verified by the modeled data. Modeling results suggested that FK filtering is critical to enhance diffracted surface waves. A real-world example is presented to show how to utilize the derived equation of surface-wave diffractions. ?? 2006 Elsevier B.V. All rights reserved.

  17. Hyperspectral Feature Detection Onboard the Earth Observing One Spacecraft using Superpixel Segmentation and Endmember Extraction

    NASA Technical Reports Server (NTRS)

    Thompson, David R.; Bornstein, Benjamin; Bue, Brian D.; Tran, Daniel Q.; Chien, Steve A.; Castano, Rebecca

    2012-01-01

    We present a demonstration of onboard hyperspectral image processing with the potential to reduce mission downlink requirements. The system detects spectral endmembers and then uses them to map units of surface material. This summarizes the content of the scene, reveals spectral anomalies warranting fast response, and reduces data volume by two orders of magnitude. We have integrated this system into the Autonomous Science craft Experiment for operational use onboard the Earth Observing One (EO-1) Spacecraft. The system does not require prior knowledge about spectra of interest. We report on a series of trial overflights in which identical spacecraft commands are effective for autonomous spectral discovery and mapping for varied target features, scenes and imaging conditions.

  18. Adaptive Parameter Identification Based on Morlet Wavelet and Application in Gearbox Fault Feature Detection

    NASA Astrophysics Data System (ADS)

    Wang, Shibin; Zhu, Z. K.; He, Yingping; Huang, Weiguo

    2010-12-01

    Localized defects in rotating mechanical parts tend to result in impulse response in vibration signal, which contain important information about system dynamics being analyzed. Thus, parameter identification of impulse response provides a potential approach for localized fault diagnosis. A method combining the Morlet wavelet and correlation filtering, named Cyclic Morlet Wavelet Correlation Filtering (CMWCF), is proposed for identifying both parameters of impulse response and the cyclic period between adjacent impulses. Simulation study concerning cyclic impulse response signal with different SNR shows that CMWCF is effective in identifying the impulse response parameters and the cyclic period. Applications in parameter identification of gearbox vibration signal for localized fault diagnosis show that CMWCF is effective in identifying the parameters and thus provides a feature detection method for gearbox fault diagnosis.

  19. Pulmonary Nodule Detection Model Based on SVM and CT Image Feature-Level Fusion with Rough Sets

    PubMed Central

    Lu, Huiling; Zhang, Junjie; Shi, Hongbin

    2016-01-01

    In order to improve the detection accuracy of pulmonary nodules in CT image, considering two problems of pulmonary nodules detection model, including unreasonable feature structure and nontightness of feature representation, a pulmonary nodules detection algorithm is proposed based on SVM and CT image feature-level fusion with rough sets. Firstly, CT images of pulmonary nodule are analyzed, and 42-dimensional feature components are extracted, including six new 3-dimensional features proposed by this paper and others 2-dimensional and 3-dimensional features. Secondly, these features are reduced for five times with rough set based on feature-level fusion. Thirdly, a grid optimization model is used to optimize the kernel function of support vector machine (SVM), which is used as a classifier to identify pulmonary nodules. Finally, lung CT images of 70 patients with pulmonary nodules are collected as the original samples, which are used to verify the effectiveness and stability of the proposed model by four groups' comparative experiments. The experimental results show that the effectiveness and stability of the proposed model based on rough set feature-level fusion are improved in some degrees. PMID:27722173

  20. [Gastric cancer detection using kubelka-Munk spectral function of DNA and protein absorption bands].

    PubMed

    Li, Lan-quan; Wei, Hua-jiang; Guo, Zhou-yi; Yang, Hong-qin; Xie, Shu-sen; Chen, Xue-mei; Li, Li-bo; He, Bol-hua; Wu, Guo-yong; Lu, Jian-jun

    2009-09-01

    Differential diagnosis for epithelial tissues of normal human gastric, undifferentiation gastric adenocarcinoma, gastric squamous cell carcinomas, and poorly differentiated gastric adenocarcinoma were studied using the Kubelka-Munk spectral function of the DNA and protein absorption bands at 260 and 280 nm in vitro. Diffuse reflectance spectra of tissue were measured using a spectrophotometer with an integrating sphere attachment. The results of measurement showed that for the spectral range from 250 to 650 nm, pathological changes of gastric epithelial tissues induced that there were significant differences in the averaged value of the Kubelka-Munk function f(r infinity) and logarithmic Kubelka-Munk function log[f(r infinity)] of the DNA absorption bands at 260 nm between epithelial tissues of normal human stomach and human undifferentiation gastric cancer, between epithelial tissues of normal human stomach and human gastric squamous cell carcinomas, and between epithelial tissues of normal human stomach and human poorly differentiated cancer. Their differences were 68.5% (p < 0.05), 146.5% (p < 0.05), 282.4% (p < 0.05), 32.4% (p < 0.05), 56.00 (p < 0.05) and 83.0% (p < 0.05) respectively. And pathological changes of gastric epithelial tissues induced that there were significant differences in the averaged value of the Kubelka-Munk function f(r infinity) and logarithmic Kubelka-Munk function log[f(r infinity)] of the protein absorption bands at 280 nm between epithelial tissues of normal human stomach and human undifferentiation gastric cancer, between epithelial tissues of normal human stomach and human gastric squamous cell carcinomas, and between epithelial tissues of normal human stomach and human poorly differentiated cancer. Their differences were 86.8% (p < 0.05), 262.9% (p < 0.05), 660.1% (p < 0.05) and 34% (p < 0.05), 72. 2% (p < 0.05), 113.5% (p < 0.05) respectively. And pathological changes of gastric epithelial tissues induced that there were

  1. Breaking of symmetrical charge distribution in xanthylocyanine chromophores detecting by their absorption spectra

    NASA Astrophysics Data System (ADS)

    Vasyluk, S. V.; Viniychuk, O. O.; Poronik, Ye. M.; Kovtun, Yu. P.; Shandura, M. P.; Yashchuk, V. M.; Kachkovsky, O. D.

    2011-03-01

    A detailed experimental investigation and quantum-chemical analysis of symmetrical cyanines with xanthylium and its substituted derivatives and with different polymethine chain (containing 1 and 2 vinylene groups) have been performed with the goal of understanding the nature of the electronic transitions in molecules. It is established electronic transitions in carbocyanines are similar to that in the typical Brooker's cyanines. In contrast, the absorption spectra of dicarbocyanines demonstrate a strong solvent dependence and substantial band broadening represented by the growth of the short wavelength shoulder. Basing on the results of the quantum-chemical calculation and conception of the mobile solitonic-like charge waves, we have concluded that the dicarbocyanines exist in two charged forms in the ground state with symmetrical and unsymmetrical distributions of the charge density. These are the examples of the cationic cyanines with the shortest chain when the symmetry breaking occurs.

  2. Synthesis temperature effect on the structural features and optical absorption of Zn(1-x)Co(x)Al2O4 oxides.

    PubMed

    Gaudon, M; Apheceixborde, A; Ménétrier, M; Le Nestour, A; Demourgues, A

    2009-10-05

    Zinc/cobalt aluminates with spinel-type structure were prepared by a polymeric route, leading to a pure phase with controlled grain size. The prepared pigments were characterized by powder X-ray diffraction Rietveld analyses in order to determine structural features, scanning electron microscopy for morphological investigation, helium pycnometry and (27)Al MAS NMR in order to highlight the occurrence of defects inside the structure, and UV-visible-near-IR spectroscopy to identify electronic transitions responsible for the compounds' color. The green-blue coloration of these pigments is known to be dependent on the sample thermal history. Here, for the first time, the Zn(1-x)Co(x)Al(2)O(4) color is newly interpreted. The pigment is green once synthesized at low temperature (i.e., with diminution of the pigment grain size); this variation was attributed to the appearance of a new absorption band located at about 500 nm, linked to a complex network feature involving Co ions in octahedral sites as well as oxygen and cationic vacancies. Hence, this work shows the possibility of easily getting a nonstoichiometric network with an abnormal cationic distribution from "chimie douce" processes with moderate synthesis temperature, and so various colorations for the same composition.

  3. A MapReduce scheme for image feature extraction and its application to man-made object detection

    NASA Astrophysics Data System (ADS)

    Cai, Fei; Chen, Honghui

    2013-07-01

    A fundamental challenge in image engineering is how to locate interested objects from high-resolution images with efficient detection performance. Several man-made objects detection approaches have been proposed while the majority of these methods are not truly timesaving and suffer low degree of detection precision. To address this issue, we propose a novel approach for man-made object detection in aerial image involving MapReduce scheme for large scale image analysis to support image feature extraction, which can be widely used to compute-intensive tasks in a highly parallel way, and texture feature extraction and clustering. Comprehensive experiments show that the parallel framework saves voluminous time for feature extraction with satisfied objects detection performance.

  4. Affective video retrieval: violence detection in Hollywood movies by large-scale segmental feature extraction.

    PubMed

    Eyben, Florian; Weninger, Felix; Lehment, Nicolas; Schuller, Björn; Rigoll, Gerhard

    2013-01-01

    Without doubt general video and sound, as found in large multimedia archives, carry emotional information. Thus, audio and video retrieval by certain emotional categories or dimensions could play a central role for tomorrow's intelligent systems, enabling search for movies with a particular mood, computer aided scene and sound design in order to elicit certain emotions in the audience, etc. Yet, the lion's share of research in affective computing is exclusively focusing on signals conveyed by humans, such as affective speech. Uniting the fields of multimedia retrieval and affective computing is believed to lend to a multiplicity of interesting retrieval applications, and at the same time to benefit affective computing research, by moving its methodology "out of the lab" to real-world, diverse data. In this contribution, we address the problem of finding "disturbing" scenes in movies, a scenario that is highly relevant for computer-aided parental guidance. We apply large-scale segmental feature extraction combined with audio-visual classification to the particular task of detecting violence. Our system performs fully data-driven analysis including automatic segmentation. We evaluate the system in terms of mean average precision (MAP) on the official data set of the MediaEval 2012 evaluation campaign's Affect Task, which consists of 18 original Hollywood movies, achieving up to .398 MAP on unseen test data in full realism. An in-depth analysis of the worth of individual features with respect to the target class and the system errors is carried out and reveals the importance of peak-related audio feature extraction and low-level histogram-based video analysis.

  5. Affective Video Retrieval: Violence Detection in Hollywood Movies by Large-Scale Segmental Feature Extraction

    PubMed Central

    Eyben, Florian; Weninger, Felix; Lehment, Nicolas; Schuller, Björn; Rigoll, Gerhard

    2013-01-01

    Without doubt general video and sound, as found in large multimedia archives, carry emotional information. Thus, audio and video retrieval by certain emotional categories or dimensions could play a central role for tomorrow's intelligent systems, enabling search for movies with a particular mood, computer aided scene and sound design in order to elicit certain emotions in the audience, etc. Yet, the lion's share of research in affective computing is exclusively focusing on signals conveyed by humans, such as affective speech. Uniting the fields of multimedia retrieval and affective computing is believed to lend to a multiplicity of interesting retrieval applications, and at the same time to benefit affective computing research, by moving its methodology “out of the lab” to real-world, diverse data. In this contribution, we address the problem of finding “disturbing” scenes in movies, a scenario that is highly relevant for computer-aided parental guidance. We apply large-scale segmental feature extraction combined with audio-visual classification to the particular task of detecting violence. Our system performs fully data-driven analysis including automatic segmentation. We evaluate the system in terms of mean average precision (MAP) on the official data set of the MediaEval 2012 evaluation campaign's Affect Task, which consists of 18 original Hollywood movies, achieving up to .398 MAP on unseen test data in full realism. An in-depth analysis of the worth of individual features with respect to the target class and the system errors is carried out and reveals the importance of peak-related audio feature extraction and low-level histogram-based video analysis. PMID:24391704

  6. Investigation of automated feature extraction techniques for applications in cancer detection from multispectral histopathology images

    NASA Astrophysics Data System (ADS)

    Harvey, Neal R.; Levenson, Richard M.; Rimm, David L.

    2003-05-01

    Recent developments in imaging technology mean that it is now possible to obtain high-resolution histological image data at multiple wavelengths. This allows pathologists to image specimens over a full spectrum, thereby revealing (often subtle) distinctions between different types of tissue. With this type of data, the spectral content of the specimens, combined with quantitative spatial feature characterization may make it possible not only to identify the presence of an abnormality, but also to classify it accurately. However, such are the quantities and complexities of these data, that without new automated techniques to assist in the data analysis, the information contained in the data will remain inaccessible to those who need it. We investigate the application of a recently developed system for the automated analysis of multi-/hyper-spectral satellite image data to the problem of cancer detection from multispectral histopathology image data. The system provides a means for a human expert to provide training data simply by highlighting regions in an image using a computer mouse. Application of these feature extraction techniques to examples of both training and out-of-training-sample data demonstrate that these, as yet unoptimized, techniques already show promise in the discrimination between benign and malignant cells from a variety of samples.

  7. DETECTION OF SHARP SYMMETRIC FEATURES IN THE CIRCUMBINARY DISK AROUND AK Sco

    SciTech Connect

    Janson, Markus; Asensio-Torres, Ruben; Thalmann, Christian; Meyer, Michael R.; Garufi, Antonio; Boccaletti, Anthony; Maire, Anne-Lise; Henning, Thomas; Pohl, Adriana; Zurlo, Alice; Marzari, Francesco; Carson, Joseph C.; Augereau, Jean-Charles; Desidera, Silvano

    2016-01-01

    The Search for Planets Orbiting Two Stars survey aims to study the formation and distribution of planets in binary systems by detecting and characterizing circumbinary planets and their formation environments through direct imaging. With the SPHERE Extreme Adaptive Optics instrument, a good contrast can be achieved even at small (<300 mas) separations from bright stars, which enables studies of planets and disks in a separation range that was previously inaccessible. Here, we report the discovery of resolved scattered light emission from the circumbinary disk around the well-studied young double star AK Sco, at projected separations in the ∼13–40 AU range. The sharp morphology of the imaged feature is surprising, given the smooth appearance of the disk in its spectral energy distribution. We show that the observed morphology can be represented either as a highly eccentric ring around AK Sco, or as two separate spiral arms in the disk, wound in opposite directions. The relative merits of these interpretations are discussed, as well as whether these features may have been caused by one or several circumbinary planets interacting with the disk.

  8. Noise-robust speech recognition through auditory feature detection and spike sequence decoding.

    PubMed

    Schafer, Phillip B; Jin, Dezhe Z

    2014-03-01

    Speech recognition in noisy conditions is a major challenge for computer systems, but the human brain performs it routinely and accurately. Automatic speech recognition (ASR) systems that are inspired by neuroscience can potentially bridge the performance gap between humans and machines. We present a system for noise-robust isolated word recognition that works by decoding sequences of spikes from a population of simulated auditory feature-detecting neurons. Each neuron is trained to respond selectively to a brief spectrotemporal pattern, or feature, drawn from the simulated auditory nerve response to speech. The neural population conveys the time-dependent structure of a sound by its sequence of spikes. We compare two methods for decoding the spike sequences--one using a hidden Markov model-based recognizer, the other using a novel template-based recognition scheme. In the latter case, words are recognized by comparing their spike sequences to template sequences obtained from clean training data, using a similarity measure based on the length of the longest common sub-sequence. Using isolated spoken digits from the AURORA-2 database, we show that our combined system outperforms a state-of-the-art robust speech recognizer at low signal-to-noise ratios. Both the spike-based encoding scheme and the template-based decoding offer gains in noise robustness over traditional speech recognition methods. Our system highlights potential advantages of spike-based acoustic coding and provides a biologically motivated framework for robust ASR development.

  9. A Study of Feature Combination for Vehicle Detection Based on Image Processing

    PubMed Central

    2014-01-01

    Video analytics play a critical role in most recent traffic monitoring and driver assistance systems. In this context, the correct detection and classification of surrounding vehicles through image analysis has been the focus of extensive research in the last years. Most of the pieces of work reported for image-based vehicle verification make use of supervised classification approaches and resort to techniques, such as histograms of oriented gradients (HOG), principal component analysis (PCA), and Gabor filters, among others. Unfortunately, existing approaches are lacking in two respects: first, comparison between methods using a common body of work has not been addressed; second, no study of the combination potentiality of popular features for vehicle classification has been reported. In this study the performance of the different techniques is first reviewed and compared using a common public database. Then, the combination capabilities of these techniques are explored and a methodology is presented for the fusion of classifiers built upon them, taking into account also the vehicle pose. The study unveils the limitations of single-feature based classification and makes clear that fusion of classifiers is highly beneficial for vehicle verification. PMID:24672299

  10. Infrared absorption spectra of the CO(2)/H(2)O complex in a cryogenic nitrogen matrix--detection of a new bending frequency.

    PubMed

    Zhang, Xu; Sander, Stanley P

    2011-09-08

    Infrared absorption spectra have been measured for the mixture of CO(2) and H(2)O in a cryogenic nitrogen matrix. The 1:1 CO(2)/H(2)O complex has been observed. Each structure of this complex should have two bending frequencies corresponding to the CO(2) fundamental bending mode (ν(2)). In this work, three bending frequencies corresponding to the CO(2) fundamental bending mode (ν(2)) have been detected; one of them at 660.3 cm(-1) is reported here for the first time. This finding helps confirm the existence of two structures for this complex. A new feature attributed to a CO(2) and H(2)O complex is observed at 3604.4 cm(-1) and is tentatively assigned to the CO(2)/H(2)O complex band corresponding to the CO(2) combination mode (ν(3) + 2ν(2)). In addition, a band that belongs to a CO(2) and H(2)O complex is detected at 3623.8 cm(-1) for the first time and is tentatively assigned to the (CO(2))(2)/H(2)O complex band corresponding to the symmetric stretching mode (ν(1)) of H(2)O.

  11. A primitive study of voxel feature generation by multiple stacked denoising autoencoders for detecting cerebral aneurysms on MRA

    NASA Astrophysics Data System (ADS)

    Nemoto, Mitsutaka; Hayashi, Naoto; Hanaoka, Shouhei; Nomura, Yukihiro; Miki, Soichiro; Yoshikawa, Takeharu; Ohtomo, Kuni

    2016-03-01

    The purpose of this study is to evaluate the feasibility of a novel feature generation, which is based on multiple deep neural networks (DNNs) with boosting, for computer-assisted detection (CADe). It is hard and time-consuming to optimize the hyperparameters for DNNs such as stacked denoising autoencoder (SdA). The proposed method allows using SdA based features without the burden of the hyperparameter setting. The proposed method was evaluated by an application for detecting cerebral aneurysms on magnetic resonance angiogram (MRA). A baseline CADe process included four components; scaling, candidate area limitation, candidate detection, and candidate classification. Proposed feature generation method was applied to extract the optimal features for candidate classification. Proposed method only required setting range of the hyperparameters for SdA. The optimal feature set was selected from a large quantity of SdA based features by multiple SdAs, each of which was trained using different hyperparameter set. The feature selection was operated through ada-boost ensemble learning method. Training of the baseline CADe process and proposed feature generation were operated with 200 MRA cases, and the evaluation was performed with 100 MRA cases. Proposed method successfully provided SdA based features just setting the range of some hyperparameters for SdA. The CADe process by using both previous voxel features and SdA based features had the best performance with 0.838 of an area under ROC curve and 0.312 of ANODE score. The results showed that proposed method was effective in the application for detecting cerebral aneurysms on MRA.

  12. Contaminant detection on poultry carcasses using hyperspectral data: Part II. Algorithms for selection of sets of ratio features

    NASA Astrophysics Data System (ADS)

    Nakariyakul, Songyot; Casasent, David P.

    2007-09-01

    We consider new methods to select useful sets of ratio features in hyperspectral data to detect contaminant regions on chicken carcasses using data provided by ARS (Athens, GA). A ratio feature is the ratio of the response at each pixel for two different wavebands. Ratio features perform a type of normalization and can thus help reduce false alarms, if a good normalization algorithm is not available. Thus, they are of interest. We present a new algorithm for the general problem of such feature selection in high-dimensional data. The four contaminant types of interest are three types of feces from different gastrointestinal regions (duodenum, ceca, and colon) and ingesta (undigested food) from the gizzard. To select the best two sets of ratio features from this 492-band HS data requires an exhaustive search of more than seven billion combinations of two sets of ratio features, which is very excessive. Thus, we propose our new fast ratio feature selection algorithm that requires evaluation of a much fewer number of sets of ratio features and is capable of giving quasi-optimal or optimal sets of ratio features. This new feature selection method has not been previously presented. It is shown to offer promise for an excellent detection rate and a low false alarm rate for this application. Our tests use data with different feed types and different contaminant types.

  13. Detection of copper in water using on-line plasma-excited atomic absorption spectroscopy (AAS).

    PubMed

    Porento, Mika; Sutinen, Veijo; Julku, Timo; Oikari, Risto

    2011-06-01

    A measurement method and apparatus was developed to measure continuously toxic metal compounds in industrial water samples. The method was demonstrated by using copper as a sample metal. Water was injected into the sample line and subsequently into a nitrogen plasma jet, in which the samples comprising the metal compound dissolved in water were decomposed. The transmitted monochromatic light was detected and the absorbance caused by copper atoms was measured. The absorbance and metal concentration were used to calculate sensitivity and detection limits for the studied metal. The sensitivity, limit of detection, and quantification for copper were 0.45 ± 0.02, 0.25 ± 0.01, and 0.85 ± 0.04 ppm, respectively.

  14. Sensitive landscape features for detecting biotic effects of global change. Final report

    SciTech Connect

    Ferson, S.; Kurtz, C.; Slice, D.

    1995-10-01

    Although several global climate models have forecast dramatic changes in future climatological conditions, very little can be predicted with any confidence about the effects on the earth`s vegetation from such environmental changes. Therefore some means is needed by which to monitor the biotic effects of global change, especially at its early stages. Ecotones, the transitional zones between larger, more compositionally well-defined biological communities, may be useful structures for monitoring the effects of climatic and other environmental impacts due to global as well as local perturbations. However, theoretical consideration of the ecological processes that determine the location and form of these structures suggests that ecotones that are sharp and therefore obvious to observers may be relatively insensitive to the types of environmental changes they might be asked to detect. It is necessary, therefore, to develop methods to identify ecotones according to the processes that generate them so that their usefulness in a particular environmental monitoring program can be assessed. This report summarizes the development of analytical methods for the detection, localization and characterization of these potentially important landscape features.

  15. GPS Signal Feature Analysis to Detect Volcanic Plume on Mount Etna

    NASA Astrophysics Data System (ADS)

    Cannavo', Flavio; Aranzulla, Massimo; Scollo, Simona; Puglisi, Giuseppe; Imme', Giuseppina

    2014-05-01

    Volcanic ash produced during explosive eruptions can cause disruptions to aviation operations and to population living around active volcanoes. Thus, detection of volcanic plume becomes a crucial issue to reduce troubles connected to its presence. Nowadays, the volcanic plume detection is carried out by using different approaches such as satellites, radars and lidars. Recently, the capability of GPS to retrieve volcanic plumes has been also investigated and some tests applied to explosive activity of Etna have demonstrated that also the GPS may give useful information. In this work, we use the permanent and continuous GPS network of the Istituto Nazionale di Geofisica e Vulcanologia, Osservatorio Etneo (Italy) that consists of 35 stations located all around volcano flanks. Data are processed by the GAMIT package developed by Massachusetts Institute of Technology. Here we investigate the possibility to quantify the volcanic plume through the GPS signal features and to estimate its spatial distribution by means of a tomographic inversion algorithm. The method is tested on volcanic plumes produced during the lava fountain of 4-5 September 2007, already used to confirm if weak explosive activity may or may not affect the GPS signals.

  16. Non-invasive health status detection system using Gabor filters based on facial block texture features.

    PubMed

    Shu, Ting; Zhang, Bob

    2015-04-01

    Blood tests allow doctors to check for certain diseases and conditions. However, using a syringe to extract the blood can be deemed invasive, slightly painful, and its analysis time consuming. In this paper, we propose a new non-invasive system to detect the health status (Healthy or Diseased) of an individual based on facial block texture features extracted using the Gabor filter. Our system first uses a non-invasive capture device to collect facial images. Next, four facial blocks are located on these images to represent them. Afterwards, each facial block is convolved with a Gabor filter bank to calculate its texture value. Classification is finally performed using K-Nearest Neighbor and Support Vector Machines via a Library for Support Vector Machines (with four kernel functions). The system was tested on a dataset consisting of 100 Healthy and 100 Diseased (with 13 forms of illnesses) samples. Experimental results show that the proposed system can detect the health status with an accuracy of 93 %, a sensitivity of 94 %, a specificity of 92 %, using a combination of the Gabor filters and facial blocks.

  17. A new feature extraction method for signal classification applied to cord dorsum potential detection

    NASA Astrophysics Data System (ADS)

    Vidaurre, D.; Rodríguez, E. E.; Bielza, C.; Larrañaga, P.; Rudomin, P.

    2012-10-01

    In the spinal cord of the anesthetized cat, spontaneous cord dorsum potentials (CDPs) appear synchronously along the lumbo-sacral segments. These CDPs have different shapes and magnitudes. Previous work has indicated that some CDPs appear to be specially associated with the activation of spinal pathways that lead to primary afferent depolarization and presynaptic inhibition. Visual detection and classification of these CDPs provides relevant information on the functional organization of the neural networks involved in the control of sensory information and allows the characterization of the changes produced by acute nerve and spinal lesions. We now present a novel feature extraction approach for signal classification, applied to CDP detection. The method is based on an intuitive procedure. We first remove by convolution the noise from the CDPs recorded in each given spinal segment. Then, we assign a coefficient for each main local maximum of the signal using its amplitude and distance to the most important maximum of the signal. These coefficients will be the input for the subsequent classification algorithm. In particular, we employ gradient boosting classification trees. This combination of approaches allows a faster and more accurate discrimination of CDPs than is obtained by other methods.

  18. A new feature extraction method for signal classification applied to cord dorsum potentials detection

    PubMed Central

    Vidaurre, D.; Rodríguez, E. E.; Bielza, C.; Larrañaga, P.; Rudomin, P.

    2012-01-01

    In the spinal cord of the anesthetized cat, spontaneous cord dorsum potentials (CDPs) appear synchronously along the lumbo-sacral segments. These CDPs have different shapes and magnitudes. Previous work has indicated that some CDPs appear to be specially associated with the activation of spinal pathways that lead to primary afferent depolarization and presynaptic inhibition. Visual detection and classification of these CDPs provides relevant information on the functional organization of the neural networks involved in the control of sensory information and allows the characterization of the changes produced by acute nerve and spinal lesions. We now present a novel feature extraction approach for signal classification, applied to CDP detection. The method is based on an intuitive procedure. We first remove by convolution the noise from the CDPs recorded in each given spinal segment. Then, we assign a coefficient for each main local maximum of the signal using its amplitude and distance to the most important maximum of the signal. These coefficients will be the input for the subsequent classification algorithm. In particular, we employ gradient boosting classification trees. This combination of approaches allows a faster and more accurate discrimination of CDPs than is obtained by other methods. PMID:22929924

  19. A new feature extraction method for signal classification applied to cord dorsum potential detection.

    PubMed

    Vidaurre, D; Rodríguez, E E; Bielza, C; Larrañaga, P; Rudomin, P

    2012-10-01

    In the spinal cord of the anesthetized cat, spontaneous cord dorsum potentials (CDPs) appear synchronously along the lumbo-sacral segments. These CDPs have different shapes and magnitudes. Previous work has indicated that some CDPs appear to be specially associated with the activation of spinal pathways that lead to primary afferent depolarization and presynaptic inhibition. Visual detection and classification of these CDPs provides relevant information on the functional organization of the neural networks involved in the control of sensory information and allows the characterization of the changes produced by acute nerve and spinal lesions. We now present a novel feature extraction approach for signal classification, applied to CDP detection. The method is based on an intuitive procedure. We first remove by convolution the noise from the CDPs recorded in each given spinal segment. Then, we assign a coefficient for each main local maximum of the signal using its amplitude and distance to the most important maximum of the signal. These coefficients will be the input for the subsequent classification algorithm. In particular, we employ gradient boosting classification trees. This combination of approaches allows a faster and more accurate discrimination of CDPs than is obtained by other methods.

  20. Optical detection of potassium chloride vapor using collinear photofragmentation and atomic absorption spectroscopy.

    PubMed

    Sorvajärvi, Tapio; Saarela, Jaakko; Toivonen, Juha

    2012-10-01

    A sensitive and selective optical technique to detect potassium chloride (KCl) vapor is introduced. The technique is based on the photofragmentation of KCl molecules, using a pulsed UV laser, and optical probing of the temporarily increased amount of potassium atoms with a near-infrared laser. The two laser beams are aligned to go through the sample volume along the same optical path. The performance of the technique is demonstrated by detecting KCl concentrations from 25 ppb to 30 ppm in a temperature-controlled cell.

  1. Effectiveness of Empirical Mode Decomposition Based Features Compared to Kurtosis Based Features for Diagnosis of Pinion Crack Detection in a Helicopter

    DTIC Science & Technology

    2010-10-01

    algorithms for fault diagnosis and failure prognosis, antenna design, superresolution algorithms 80 82 84 86 88 90 92 94 96 98 0 20 40 60 80 Accelerometer...to Kurtosis Based Features for Diagnosis of Pinion Crack Detection in a Helicopter Canh Ly* 1 , Kenneth Ranney 1 , Kwok Tom 1 , Hiralal Khatri 1...rotor gearbox . A tooth on the input pinion of the gearbox was notched and run for an extended period at several over-torque conditions to induce a

  2. Selection of the optimal combination of water vapor absorption lines for detection of temperature in combustion zones of mixing supersonic gas flows by diode laser absorption spectrometry

    NASA Astrophysics Data System (ADS)

    Mironenko, V. R.; Kuritsyn, Yu. A.; Bolshov, M. A.; Liger, V. V.

    2016-12-01

    Determination of a gas medium temperature by diode laser absorption spectrometry (DLAS) is based on the measurement of integral intensities of the absorption lines of a test molecule (generally water vapor molecule). In case of local thermodynamic equilibrium temperature is inferred from the ratio of the integral intensities of two lines with different low energy levels. For the total gas pressure above 1 atm the absorption lines are broadened and one cannot find isolated well resolved water vapor absorption lines within relatively narrow spectral interval of fast diode laser (DL) tuning range (about 3 cm-1). For diagnostics of a gas object in the case of high temperature and pressure DLAS technique can be realized with two diode lasers working in different spectral regions with strong absorption lines. In such situation the criteria of the optimal line selection differs significantly from the case of narrow lines. These criteria are discussed in our work. The software for selection the optimal spectral regions using the HITRAN-2012 and HITEMP data bases is developed. The program selects spectral regions of DL tuning, minimizing the error of temperature determination δT/T, basing on the attainable experimental error of line intensity measurement δS. Two combinations of optimal spectral regions were selected - (1.392 & 1.343 μm) and (1.392 & 1.339 μm). Different algorithms of experimental data processing are discussed.

  3. Ion chromatography with the indirect ultraviolet detection of alkali metal ions and ammonium using imidazolium ionic liquid as ultraviolet absorption reagent and eluent.

    PubMed

    Liu, Yong-Qiang; Yu, Hong

    2016-08-01

    Indirect ultraviolet detection was conducted in ultraviolet-absorption-agent-added mobile phase to complete the detection of the absence of ultraviolet absorption functional group in analytes. Compared with precolumn derivatization or postcolumn derivatization, this method can be widely used, has the advantages of simple operation and good linear relationship. Chromatographic separation of Li(+) , Na(+) , K(+) , and NH4 (+) was performed on a carboxylic acid base cation exchange column using imidazolium ionic liquid/acid/organic solvent as the mobile phase, in which imidazolium ionic liquids acted as ultraviolet absorption reagent and eluting agent. The retention behaviors of four kinds of cations are discussed, and the mechanism of separation and detection are described. The main factors influencing the separation and detection were the background ultraviolet absorption reagent and the concentration of hydrogen ion in the ion chromatography-indirect ultraviolet detection. The successful separation and detection of Li(+) , Na(+) , K(+) , and NH4 (+) within 13 min was achieved using the selected chromatographic conditions, and the detection limits (S/N = 3) were 0.02, 0.11, 0.30, and 0.06 mg/L, respectively. A new separation and analysis method of alkali metal ions and ammonium by ion chromatography with indirect ultraviolet detection method was developed, and the application range of ionic liquid was expanded.

  4. Genetic Particle Swarm Optimization–Based Feature Selection for Very-High-Resolution Remotely Sensed Imagery Object Change Detection

    PubMed Central

    Chen, Qiang; Chen, Yunhao; Jiang, Weiguo

    2016-01-01

    In the field of multiple features Object-Based Change Detection (OBCD) for very-high-resolution remotely sensed images, image objects have abundant features and feature selection affects the precision and efficiency of OBCD. Through object-based image analysis, this paper proposes a Genetic Particle Swarm Optimization (GPSO)-based feature selection algorithm to solve the optimization problem of feature selection in multiple features OBCD. We select the Ratio of Mean to Variance (RMV) as the fitness function of GPSO, and apply the proposed algorithm to the object-based hybrid multivariate alternative detection model. Two experiment cases on Worldview-2/3 images confirm that GPSO can significantly improve the speed of convergence, and effectively avoid the problem of premature convergence, relative to other feature selection algorithms. According to the accuracy evaluation of OBCD, GPSO is superior at overall accuracy (84.17% and 83.59%) and Kappa coefficient (0.6771 and 0.6314) than other algorithms. Moreover, the sensitivity analysis results show that the proposed algorithm is not easily influenced by the initial parameters, but the number of features to be selected and the size of the particle swarm would affect the algorithm. The comparison experiment results reveal that RMV is more suitable than other functions as the fitness function of GPSO-based feature selection algorithm. PMID:27483285

  5. Design of Advanced Atmospheric Water Vapor Differential Absorption Lidar (DIAL) Detection System

    NASA Technical Reports Server (NTRS)

    Refaat, Tamer F.; Luck, William S., Jr.; DeYoung, Russell J.

    1999-01-01

    The measurement of atmospheric water vapor is very important for understanding the Earth's climate and water cycle. The lidar atmospheric sensing experiment (LASE) is an instrument designed and operated by the Langley Research Center for high precision water vapor measurements. The design details of a new water vapor lidar detection system that improves the measurement sensitivity of the LASE instrument by a factor of 10 are discussed. The new system consists of an advanced, very low noise, avalanche photodiode (APD) and a state-of-the-art signal processing circuit. The new low-power system is also compact and lightweight so that it would be suitable for space flight and unpiloted atmospheric vehicles (UAV) applications. The whole system is contained on one small printed circuit board (9 x 15 sq cm). The detection system is mounted at the focal plane of a lidar receiver telescope, and the digital output is read by a personal computer with a digital data acquisition card.

  6. Multilayer Cloud Detection with the MODIS Near-Infrared Water Vapor Absorption Band

    NASA Technical Reports Server (NTRS)

    Wind, Galina; Platnick, Steven; King, Michael D.; Hubanks, Paul A,; Pavolonis, Michael J.; Heidinger, Andrew K.; Yang, Ping; Baum, Bryan A.

    2009-01-01

    Data Collection 5 processing for the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the NASA Earth Observing System EOS Terra and Aqua spacecraft includes an algorithm for detecting multilayered clouds in daytime. The main objective of this algorithm is to detect multilayered cloud scenes, specifically optically thin ice cloud overlying a lower-level water cloud, that presents difficulties for retrieving cloud effective radius using single layer plane-parallel cloud models. The algorithm uses the MODIS 0.94 micron water vapor band along with CO2 bands to obtain two above-cloud precipitable water retrievals, the difference of which, in conjunction with additional tests, provides a map of where multilayered clouds might potentially exist. The presence of a multilayered cloud results in a large difference in retrievals of above-cloud properties between the CO2 and the 0.94 micron methods. In this paper the MODIS multilayered cloud algorithm is described, results of using the algorithm over example scenes are shown, and global statistics for multilayered clouds as observed by MODIS are discussed. A theoretical study of the algorithm behavior for simulated multilayered clouds is also given. Results are compared to two other comparable passive imager methods. A set of standard cloudy atmospheric profiles developed during the course of this investigation is also presented. The results lead to the conclusion that the MODIS multilayer cloud detection algorithm has some skill in identifying multilayered clouds with different thermodynamic phases

  7. Detection of gastrointestinal cancer by elastic scattering and absorption spectroscopies with the Los Alamos Optical Biopsy System

    SciTech Connect

    Mourant, J.R.; Boyer, J.; Johnson, T.M.; Lacey, J.; Bigio, I.J.; Bohorfoush, A.; Mellow, M.

    1995-03-01

    The Los Alamos National Laboratory has continued the development of the Optical Biopsy System (OBS) for noninvasive, real-time in situ diagnosis of tissue pathologies. In proceedings of earlier SPIE conferences we reported on clinical measurements in the bladder, and we report here on recent results of clinical tests in the gastrointestinal tract. With the OBS, tissue pathologies are detected/diagnosed using spectral measurements of the elastic optical transport properties (scattering and absorption) of the tissue over a wide range of wavelengths. The use of elastic scattering as the key to optical tissue diagnostics in the OBS is based on the fact that many tissue pathologies, including a majority of cancer forms, exhibit significant architectural changes at the cellular and sub-cellular level. Since the cellular components that cause elastic scattering have dimensions typically on the order of visible to near-IR wavelengths, the elastic (Mie) scattering properties will be wavelength dependent. Thus, morphology and size changes can be expected to cause significant changes m an optical signature that is derived from the wavelength-dependence of elastic scattering. Additionally, the optical geometry of the OBS beneficially enhances its sensitivity for measuring absorption bands. The OBS employs a small fiber-optic probe that is amenable to use with any endoscope or catheter, or to direct surface examination, as well as interstitial needle insertion. Data acquistion/display time is <1 second.

  8. Glacier surface feature detection and classification from airborne LiDAR data

    NASA Astrophysics Data System (ADS)

    Höfle, B.; Sailer, R.; Vetter, M.; Rutzinger, M.; Pfeifer, N.

    2009-04-01

    In recent years airborne LiDAR evolved to the state-of-the-art technology for topographic data acquisition. Up to now mainly the derived elevation information has been used in glaciology (e.g. roughness determination, multitemporal elevation and volume changes). Few studies have already shown the potential of using LiDAR signal intensities for glacier surface differentiation, primarily based on visual interpretation of signal intensity images. This contribution brings together the spatial and radiometric information provided by airborne LiDAR, in order to make an automatic glacier surface feature detection and classification possible. The automation of the processing workflow and the standardization of the used input data become important particularly for multitemporal analysis where surface changes and feature tracking are of major interest. This study is carried out at the Hintereisferner, Ötztal Alps/Austria, where 16 airborne LiDAR acquisitions have taken place since 2001. We aim at detecting the main glacier surface classes as defined by crevasses, snow, firn, ice and debris covered ice areas. Prior to the glacier facies differentiation, an automated glacier delineation based on roughness constraints is performed. It is assumed that the glacier surface, except the crevasse zone, tends to a smoother surface than the adjacent slopes and represents one large connected spatial unit. The developed method combines raster and point cloud based processing steps in an object-based segmentation and classification procedure where elevation and calibrated signal intensity are used as complementary input. The calibration of the recorded signal intensity removes known effects originating from the atmosphere, topography and scan geometry (e.g. distance to target) and hence provides a value proportional to surface reflectance in the wavelength of the laser system. Since the Bidirectional Reflectance Distribution Function (BRDF) of the scanned surface is not known beforehand

  9. A quick eye to anger: An investigation of a differential effect of facial features in detecting angry and happy expressions.

    PubMed

    Lo, L Y; Cheng, M Y

    2015-08-11

    Detection of angry and happy faces is generally found to be easier and faster than that of faces expressing emotions other than anger or happiness. This can be explained by the threatening account and the feature account. Few empirical studies have explored the interaction between these two accounts which are seemingly, but not necessarily, mutually exclusive. The present studies hypothesised that prominent facial features are important in facilitating the detection process of both angry and happy expressions; yet the detection of happy faces was more facilitated by the prominent features than angry faces. Results confirmed the hypotheses and indicated that participants reacted faster to the emotional expressions with prominent features (in Study 1) and the detection of happy faces was more facilitated by the prominent feature than angry faces (in Study 2). The findings are compatible with evolutionary speculation which suggests that the angry expression is an alarming signal of potential threats to survival. Compared to the angry faces, the happy faces need more salient physical features to obtain a similar level of processing efficiency.

  10. Feature-Based Change Detection Reveals Inconsistent Individual Differences in Visual Working Memory Capacity.

    PubMed

    Ambrose, Joseph P; Wijeakumar, Sobanawartiny; Buss, Aaron T; Spencer, John P

    2016-01-01

    Visual working memory (VWM) is a key cognitive system that enables people to hold visual information in mind after a stimulus has been removed and compare past and present to detect changes that have occurred. VWM is severely capacity limited to around 3-4 items, although there are robust individual differences in this limit. Importantly, these individual differences are evident in neural measures of VWM capacity. Here, we capitalized on recent work showing that capacity is lower for more complex stimulus dimension. In particular, we asked whether individual differences in capacity remain consistent if capacity is shifted by a more demanding task, and, further, whether the correspondence between behavioral and neural measures holds across a shift in VWM capacity. Participants completed a change detection (CD) task with simple colors and complex shapes in an fMRI experiment. As expected, capacity was significantly lower for the shape dimension. Moreover, there were robust individual differences in behavioral estimates of VWM capacity across dimensions. Similarly, participants with a stronger BOLD response for color also showed a strong neural response for shape within the lateral occipital cortex, intraparietal sulcus (IPS), and superior IPS. Although there were robust individual differences in the behavioral and neural measures, we found little evidence of systematic brain-behavior correlations across feature dimensions. This suggests that behavioral and neural measures of capacity provide different views onto the processes that underlie VWM and CD. Recent theoretical approaches that attempt to bridge between behavioral and neural measures are well positioned to address these findings in future work.

  11. Feature-Based Change Detection Reveals Inconsistent Individual Differences in Visual Working Memory Capacity

    PubMed Central

    Ambrose, Joseph P.; Wijeakumar, Sobanawartiny; Buss, Aaron T.; Spencer, John P.

    2016-01-01

    Visual working memory (VWM) is a key cognitive system that enables people to hold visual information in mind after a stimulus has been removed and compare past and present to detect changes that have occurred. VWM is severely capacity limited to around 3–4 items, although there are robust individual differences in this limit. Importantly, these individual differences are evident in neural measures of VWM capacity. Here, we capitalized on recent work showing that capacity is lower for more complex stimulus dimension. In particular, we asked whether individual differences in capacity remain consistent if capacity is shifted by a more demanding task, and, further, whether the correspondence between behavioral and neural measures holds across a shift in VWM capacity. Participants completed a change detection (CD) task with simple colors and complex shapes in an fMRI experiment. As expected, capacity was significantly lower for the shape dimension. Moreover, there were robust individual differences in behavioral estimates of VWM capacity across dimensions. Similarly, participants with a stronger BOLD response for color also showed a strong neural response for shape within the lateral occipital cortex, intraparietal sulcus (IPS), and superior IPS. Although there were robust individual differences in the behavioral and neural measures, we found little evidence of systematic brain-behavior correlations across feature dimensions. This suggests that behavioral and neural measures of capacity provide different views onto the processes that underlie VWM and CD. Recent theoretical approaches that attempt to bridge between behavioral and neural measures are well positioned to address these findings in future work. PMID:27147986

  12. Detecting Small-Scale Topographic Changes and Relict Geomorphic Features on Barrier Islands Using SAR

    NASA Technical Reports Server (NTRS)

    Gibeaut, James C.; Crawford, Melba M.; Gutierrez, Roberto; Slatton, K. Clint; Neuenschwander, Amy L.; Ricard, Michael R.

    1997-01-01

    The shapes and elevations of barrier islands may change dramatically over a short period of time during a storm. Coastal scientists and engineers, however, are currently unable to measure these changes occurring over an entire barrier island at once. This three-year project, which is funded by NASA and jointly conducted by the Bureau of Economic Geology and the Center for Space Research at The University of Texas at Austin, is designed to overcome this problem by developing the use of interferometry from airborne synthetic aperture radar (AIRSAR) to measure coastal topography and to detect storm-induced changes in topography. Surrogate measures of topography observed in multiband, fully polarimetric AIRSAR (This type of data are now referred to as POLSAR data.) are also being investigated. Digital elevation models (DEM) of Galveston Island and Bolivar Peninsula, Texas obtained with Topographic SAR (TOPSAR) are compared with measurements by Global Positioning System (GPS) ground surveys and electronic total station surveys. In addition to topographic mapping, this project is evaluating the use of POLSAR to detect old features such as storm scarps, storm channels, former tidal inlets, and beach ridges that have been obscured by vegetation, erosion, deposition, and artificial filling. We have also expanded the work from the original proposal to include the mapping of coastal wetland vegetation and depositional environments. Methods developed during this project will provide coastal geologists with an unprecedented tool for monitoring and understanding barrier island systems. This understanding will improve overall coastal management policies and will help reduce the effects of natural and man-induced coastal hazards. This report summarizes our accomplishments during the second year of the study. Also included is a discussion of our planned activities for year 3 and a revised budget.

  13. Evaluating the Nature of So-Called S*-State Feature in Transient Absorption of Carotenoids in Light-Harvesting Complex 2 (LH2) from Purple Photosynthetic Bacteria.

    PubMed

    Niedzwiedzki, Dariusz M; Hunter, C Neil; Blankenship, Robert E

    2016-11-03

    Carotenoids are a class of natural pigments present in all phototrophic organisms, mainly in their light-harvesting proteins in which they play roles of accessory light absorbers and photoprotectors. Extensive time-resolved spectroscopic studies of these pigments have revealed unexpectedly complex photophysical properties, particularly for carotenoids in light-harvesting LH2 complexes from purple bacteria. An ambiguous, optically forbidden electronic excited state designated as S* has been postulated to be involved in carotenoid excitation relaxation and in an alternative carotenoid-to-bacteriochlorophyll energy transfer pathway, as well as being a precursor of the carotenoid triplet state. However, no definitive and satisfactory origin of the carotenoid S* state in these complexes has been established, despite a wide-ranging series of studies. Here, we resolve the ambiguous origin of the carotenoid S* state in LH2 complex from Rba. sphaeroides by showing that the S* feature can be seen as a combination of ground state absorption bleaching of the carotenoid pool converted to cations and the Stark spectrum of neighbor neutral carotenoids, induced by temporal electric field brought by the carotenoid cation-bacteriochlorophyll anion pair. These findings remove the need to assign an S* state, and thereby significantly simplify the photochemistry of carotenoids in these photosynthetic antenna complexes.

  14. Evaluating the Nature of So-Called S*-State Feature in Transient Absorption of Carotenoids in Light-Harvesting Complex 2 (LH2) from Purple Photosynthetic Bacteria

    PubMed Central

    2016-01-01

    Carotenoids are a class of natural pigments present in all phototrophic organisms, mainly in their light-harvesting proteins in which they play roles of accessory light absorbers and photoprotectors. Extensive time-resolved spectroscopic studies of these pigments have revealed unexpectedly complex photophysical properties, particularly for carotenoids in light-harvesting LH2 complexes from purple bacteria. An ambiguous, optically forbidden electronic excited state designated as S* has been postulated to be involved in carotenoid excitation relaxation and in an alternative carotenoid-to-bacteriochlorophyll energy transfer pathway, as well as being a precursor of the carotenoid triplet state. However, no definitive and satisfactory origin of the carotenoid S* state in these complexes has been established, despite a wide-ranging series of studies. Here, we resolve the ambiguous origin of the carotenoid S* state in LH2 complex from Rba. sphaeroides by showing that the S* feature can be seen as a combination of ground state absorption bleaching of the carotenoid pool converted to cations and the Stark spectrum of neighbor neutral carotenoids, induced by temporal electric field brought by the carotenoid cation–bacteriochlorophyll anion pair. These findings remove the need to assign an S* state, and thereby significantly simplify the photochemistry of carotenoids in these photosynthetic antenna complexes. PMID:27726397

  15. Real-Time Sensor Validation, Signal Reconstruction, and Feature Detection for an RLV Propulsion Testbed

    NASA Technical Reports Server (NTRS)

    Jankovsky, Amy L.; Fulton, Christopher E.; Binder, Michael P.; Maul, William A., III; Meyer, Claudia M.

    1998-01-01

    A real-time system for validating sensor health has been developed in support of the reusable launch vehicle program. This system was designed for use in a propulsion testbed as part of an overall effort to improve the safety, diagnostic capability, and cost of operation of the testbed. The sensor validation system was designed and developed at the NASA Lewis Research Center and integrated into a propulsion checkout and control system as part of an industry-NASA partnership, led by Rockwell International for the Marshall Space Flight Center. The system includes modules for sensor validation, signal reconstruction, and feature detection and was designed to maximize portability to other applications. Review of test data from initial integration testing verified real-time operation and showed the system to perform correctly on both hard and soft sensor failure test cases. This paper discusses the design of the sensor validation and supporting modules developed at LeRC and reviews results obtained from initial test cases.

  16. Visual acuity of the honey bee retina and the limits for feature detection

    PubMed Central

    Rigosi, Elisa; Wiederman, Steven D.; O’Carroll, David C.

    2017-01-01

    Visual abilities of the honey bee have been studied for more than 100 years, recently revealing unexpectedly sophisticated cognitive skills rivalling those of vertebrates. However, the physiological limits of the honey bee eye have been largely unaddressed and only studied in an unnatural, dark state. Using a bright display and intracellular recordings, we here systematically investigated the angular sensitivity across the light adapted eye of honey bee foragers. Angular sensitivity is a measure of photoreceptor receptive field size and thus small values indicate higher visual acuity. Our recordings reveal a fronto-ventral acute zone in which angular sensitivity falls below 1.9°, some 30% smaller than previously reported. By measuring receptor noise and responses to moving dark objects, we also obtained direct measures of the smallest features detectable by the retina. In the frontal eye, single photoreceptors respond to objects as small as 0.6° × 0.6°, with >99% reliability. This indicates that honey bee foragers possess significantly better resolution than previously reported or estimated behaviourally, and commonly assumed in modelling of bee acuity. PMID:28383025

  17. Combined optimization of image-gathering and image-processing systems for scene feature detection

    NASA Technical Reports Server (NTRS)

    Halyo, Nesim; Arduini, Robert F.; Samms, Richard W.

    1987-01-01

    The relationship between the image gathering and image processing systems for minimum mean squared error estimation of scene characteristics is investigated. A stochastic optimization problem is formulated where the objective is to determine a spatial characteristic of the scene rather than a feature of the already blurred, sampled and noisy image data. An analytical solution for the optimal characteristic image processor is developed. The Wiener filter for the sampled image case is obtained as a special case, where the desired characteristic is scene restoration. Optimal edge detection is investigated using the Laplacian operator x G as the desired characteristic, where G is a two dimensional Gaussian distribution function. It is shown that the optimal edge detector compensates for the blurring introduced by the image gathering optics, and notably, that it is not circularly symmetric. The lack of circular symmetry is largely due to the geometric effects of the sampling lattice used in image acquisition. The optimal image gathering optical transfer function is also investigated and the results of a sensitivity analysis are shown.

  18. FIRST SIMULTANEOUS DETECTION OF MOVING MAGNETIC FEATURES IN PHOTOSPHERIC INTENSITY AND MAGNETIC FIELD DATA

    SciTech Connect

    Lim, Eun-Kyung; Yurchyshyn, Vasyl; Goode, Philip

    2012-07-01

    The formation and the temporal evolution of a bipolar moving magnetic feature (MMF) was studied with high-spatial and temporal resolution. The photometric properties were observed with the New Solar Telescope at Big Bear Solar Observatory using a broadband TiO filter (705.7 nm), while the magnetic field was analyzed using the spectropolarimetric data obtained by Hinode. For the first time, we observed a bipolar MMF simultaneously in intensity images and magnetic field data, and studied the details of its structure. The vector magnetic field and the Doppler velocity of the MMF were also studied. A bipolar MMF with its positive polarity closer to the negative penumbra formed, accompanied by a bright, filamentary structure in the TiO data connecting the MMF and a dark penumbral filament. A fast downflow ({<=}2 km s{sup -1}) was detected at the positive polarity. The vector magnetic field obtained from the full Stokes inversion revealed that a bipolar MMF has a U-shaped magnetic field configuration. Our observations provide a clear intensity counterpart of the observed MMF in the photosphere, and strong evidence of the connection between the MMF and the penumbral filament as a serpentine field.

  19. Textural Feature Selection for Enhanced Detection of Stationary Humans in Through the Wall Radar Imagery

    DTIC Science & Technology

    Specifically, textural features , such as contrast, correlation, energy, entropy, and homogeneity, have been extracted from gray-level co-occurrence...paper, we address the task of feature selection to identify the relevant subset of features in the GLCM domain, while discarding those that are either...Decision Tree algorithm to find the optimal combination of co-occurrence based textural features for the problem at hand. We employ a K-Nearest Neighbor

  20. Improving Detection of Axillary Lymph Nodes by Computer-Aided Kinetic Feature Identification in Positron Emission Tomography

    DTIC Science & Technology

    2004-08-01

    Detection<