Spectral mineral mapping for characterization of subtle geothermal prospects using ASTER data

NASA Astrophysics Data System (ADS)

Abubakar, A. J.; Hashim, M.; Pour, A. B.

2017-05-01

In this study, the performance of ASTER data is evaluated for mapping subtle geothermal prospects in an unexplored tropical region having a number of thermal springs. The study employed a simple Decorrelation stretch with specific absorptions to highlight possible alteration zones of interest related to Geothermal (GT) systems. Hydrothermal alteration minerals are subsequently mapped using Spectral Angle Mapper (SAM) and Linear Spectral Unmixing (LSU) algorithms to target representative minerals such as clays, carbonates and AL-OH minerals as indicators of GT activity. The results were validated through field GPS survey, rock sampling and laboratory analysis using latest smart lab X-Ray Diffractometer technology. The study indicates that ASTER broadband satellite data could be used to map subtle GT prospects with the aid of an in-situ verification. However, it also shows that ASTER could not discriminate within specie minerals especially for clays using SWIR bands. Subsequent studies are aimed at looking at both ASTER and Hyperion hyperspectral data in the same area as this could have significant implications for GT resource detection in unmapped aseismic and inaccessible tropical regions using available spaceborne data.

Spectral Characterization of Suspected Acid Deposition Damage in Red Spruce (picea Rubens) Stands from Vermont

NASA Technical Reports Server (NTRS)

Vogelmann, J. E.; Rock, B. N.

1985-01-01

In an attempt to demonstrate the utility of remote sensing systems to monitor sites of suspected acid rain deposition damage, intensive field activities, coupled with aircraft overflights, were centered on red spruce stands in Vermont during August and September of 1984. Remote sensing data were acquired using the Airborne Imaging Spectrometer, Thematic Mapper Simulator, Barnes Model 12 to 1000 Modular Multiband Radiometer and Spectron Engineering Spectrometer (the former two flown on the NASA C-130; the latter two on A Bell UH-1B Iroquois Helicopter). Field spectral data were acquired during the week of the August overflights using a high spectral resolution spectrometer and two broad-band radiometers. Preliminary analyses of these data indicate a number of spectral differences in vegetation between high and low damage sites. Some of these differences are subtle, and are observable only with high spectral resolution sensors; others are less subtle and are observable using broad-band sensors.

Revealing the ultrafast outflow in IRAS 13224-3809 through spectral variability

NASA Astrophysics Data System (ADS)

Parker, M. L.; Alston, W. N.; Buisson, D. J. K.; Fabian, A. C.; Jiang, J.; Kara, E.; Lohfink, A.; Pinto, C.; Reynolds, C. S.

2017-08-01

We present an analysis of the long-term X-ray variability of the extreme narrow-line Seyfert 1 galaxy IRAS 13224-3809 using principal component analysis (PCA) and fractional excess variability (Fvar) spectra to identify model-independent spectral components. We identify a series of variability peaks in both the first PCA component and Fvar spectrum which correspond to the strongest predicted absorption lines from the ultrafast outflow (UFO) discovered by Parker et al. (2017). We also find higher order PCA components, which correspond to variability of the soft excess and reflection features. The subtle differences between RMS and PCA results argue that the observed flux-dependence of the absorption is due to increased ionization of the gas, rather than changes in column density or covering fraction. This result demonstrates that we can detect outflows from variability alone and that variability studies of UFOs are an extremely promising avenue for future research.

Wavelength feature mapping as a proxy to mineral chemistry for investigating geologic systems: An example from the Rodalquilar epithermal system

NASA Astrophysics Data System (ADS)

van der Meer, Freek; Kopačková, Veronika; Koucká, Lucie; van der Werff, Harald M. A.; van Ruitenbeek, Frank J. A.; Bakker, Wim H.

2018-02-01

The final product of a geologic remote sensing data analysis using multi spectral and hyperspectral images is a mineral (abundance) map. Multispectral data, such as ASTER, Landsat, SPOT, Sentinel-2, typically allow to determine qualitative estimates of what minerals are in a pixel, while hyperspectral data allow to quantify this. As input to most image classification or spectral processing approach, endmembers are required. An alternative approach to classification is to derive absorption feature characteristics such as the wavelength position of the deepest absorption, depth of the absorption and symmetry of the absorption feature from hyperspectral data. Two approaches are presented, tested and compared in this paper: the 'Wavelength Mapper' and the 'QuanTools'. Although these algorithms use a different mathematical solution to derive absorption feature wavelength and depth, and use different image post-processing, the results are consistent, comparable and reproducible. The wavelength images can be directly linked to mineral type and abundance, but more importantly also to mineral chemical composition and subtle changes thereof. This in turn allows to interpret hyperspectral data in terms of mineral chemistry changes which is a proxy to pressure-temperature of formation of minerals. We show the case of the Rodalquilar epithermal system of the southern Spanish Gabo de Gata volcanic area using HyMAP airborne hyperspectral images.

Classification of the LCVF AVIRIS test site with a Kohonen artificial neural network

NASA Technical Reports Server (NTRS)

Merenyi, Erzsebet; Singer, Robert B.; Farrand, William H.

1993-01-01

We present a classification of an AVIRIS spectral image of the Lunar Crater Volcanic Field (LCVF). Geologic mapping from such data is made possible by distinctive mineral signatures: absorption features and the shape of the spectral continuum. The subtle spectral shape differences between some of the geological units in this scene along with the high dimensionality of the spectral presents a challenging pattern recognition task. We found an artificial neural network powerful in separating 13 geological units based on the full spectral resolution. The LCVF, in northern Nye County, Nevada, was the primary focus of the NASA-sponsored Geologic Remote Sensing Field Experiment in the summer of 1989. It consists of over 100 square miles of Quaternary basaltic pyroclastic and flow deposits. These deposits lie atop ignimbrites and silicic lava flows of Tertiary age and in turn are overlain by Quaternary alluvial and playa deposits. This AVIRIS image was collected on September 29, 1989 at 11:44 at 11:44 PDT. The 256-by-256 pixel subsection in this study contains oxidized basaltic cinder deposits, the southern half of the Lunar Lake playa, and outcrops of the Rhyollite of Big Sand Spring Valley. Vegetation in LCVF is sparse, but locally abundant within washes and near springs.

Unique spectral signatures of the nucleic acid dye acridine orange can distinguish cell death by apoptosis and necroptosis

PubMed Central

Caprariello, Andrew V.; Henry, Tyler J.; Tsutsui, Shigeki; Chu, Tak H.; Schenk, Geert J.; Yong, V. Wee

2017-01-01

Cellular injury and death are ubiquitous features of disease, yet tools to detect them are limited and insensitive to subtle pathological changes. Acridine orange (AO), a nucleic acid dye with unique spectral properties, enables real-time measurement of RNA and DNA as proxies for cell viability during exposure to various noxious stimuli. This tool illuminates spectral signatures unique to various modes of cell death, such as cells undergoing apoptosis versus necrosis/necroptosis. This new approach also shows that cellular RNA decreases during necrotic, necroptotic, and apoptotic cell death caused by demyelinating, ischemic, and traumatic injuries, implying its involvement in a wide spectrum of tissue pathologies. Furthermore, cells with pathologically low levels of cytoplasmic RNA are detected earlier and in higher numbers than with standard markers including TdT-mediated dUTP biotin nick-end labeling and cleaved caspase 3 immunofluorescence. Our technique highlights AO-labeled cytoplasmic RNA as an important early marker of cellular injury and a sensitive indicator of various modes of cell death in a range of experimental models. PMID:28264914

Stratigraphic Correlation via Opportunity's Pancam of the Burns Formation, Meridiani Planum, Mars

NASA Astrophysics Data System (ADS)

Thompson, S. D.; Calvin, W. M.; Farrand, W. H.

2006-12-01

Spectral properties of Meridiani Planum hematite-rich Burns formation observed by Opportunity's Pancam have been described previously but not at minimum spatial scales. This study is of the fine scale visible and near- infrared spectral features within the sedimentary structures over the entire lateral extent explored by Opportunity across an 8 km traverse from Endurance to Victoria craters. Investigation of the bedrock has shown sub-centimeter thinly laminated evaporite deposits with few occurrences of festoon cross-bedding, massive bedding, and subtle differences in color and texture. Pancam data analyses of rock targets where sufficient spatial resolution (<10 mm) is achieved (within 10 m) constrain spectral parameters of laminar, erosional, and possible secondary diagenetic features. Results show differences of statistical significance in iron mineral varieties and phases in both vertical section and lateral extent of the Burns formation. Spectra exhibit a steep positive slope in the visible (432-753 nm) region and subtle changes in the near infrared (753-1009 nm) region ranging from flat, concave, to convex profiles. Maxima are typically in the 750-850 nm region but can occur as low as 673 nm and as high as 1009 nm with the latter usually from the lower albedo materials (i.e., spherules and basaltic sands). Positive slopes from 934-1009 nm in this region are consistent with the presence of hematite, commonly associated with the spherules. The higher albedo surfaces tend to have greatest negative slope in the longer wavelengths. This could result from intrinsic characteristics of the outcrop material or a significantly thick (i.e. >100 micron) dust deposit. Band depth images centered at 535 nm and 904 nm provide statistics on the relative occurrences of crystalline ferric oxide minerals. Rarely iron-rich signatures are present in individual laminations and not in the adjacent layers. Such occurrences could result from multiple iron-rich sedimentary events, secondary diagenetic products such as cementation or recrystallization, or an invasive fracture fill material. Comparisons of geomorphologic and spectroscopic mapping will be presented to show overall relationships of the Meridiani plains materials.

Spectral and timing properties of atoll source 4U 1705-44: LAXPC/AstroSat results

NASA Astrophysics Data System (ADS)

Agrawal, V. K.; Nandi, Anuj; Girish, V.; Ramadevi, M. C.

2018-07-01

In this paper, we present the first results of spectral and timing properties of the atoll source 4U 1705-44 using ˜100 ks data obtained with the Large Area X-ray Proportional Counter (LAXPC) onboard AstroSat. The source was in the high soft state during our observations and traced out a banana track in the hardness intensity diagram (HID). We study the evolution of the power density spectra (PDS) and the energy spectra along the HID. PDS show the presence of a broad Lorentzian feature (peaked noise or PN) centred at 1-13 Hz and very low-frequency noise (VLFN). The energy spectra can be described by the sum of a thermal Comptonized component, a power-law and a broad iron line. The hard tail seen in the energy spectra is variable and contributes 4-30 per cent of the total flux. The iron line seen in this source is broad (FWHM ˜ 2 keV) and strong (EW ˜ 369-512 eV). Relativistic smearing in the accretion disc cannot explain the origin of this feature on its own and another mechanism is required, such as broadening by the Comptonization process in the external part of the `Comptonized corona'. A subtle and systematic evolution of the spectral parameters (optical depth, electron temperature etc.) is seen as the source moves along the HID. We study the correlation between the frequency of the PN and the spectral parameters. The PN frequency seems to be correlated with the strength of the corona. We discuss the implication of these results.

The dielectric signature of glass density

NASA Astrophysics Data System (ADS)

Rams-Baron, M.; Wojnarowska, Z.; Knapik-Kowalczuk, J.; Jurkiewicz, K.; Burian, A.; Wojtyniak, M.; Pionteck, J.; Jaworska, M.; Rodríguez-Tinoco, C.; Paluch, M.

2017-09-01

At present, we are witnessing a renewed interest in the properties of densified glasses prepared by isobaric cooling of a liquid at elevated pressure. As high-pressure densification emerges as a promising approach in the development of glasses with customized features, understanding and controlling their unique properties represent a contemporary scientific and technological goal. The results presented herein indicate that the applied high-pressure preparation route leads to a glassy state with higher density (˜1%) and a reduced free volume of about 7%. We show that these subtle structural changes remarkably influence the dielectric response and spectral features of β-relaxation in etoricoxib glass. Our study, combining dynamical and structural techniques, reveal that β-relaxation in etoricoxib is extremely sensitive to the variations in molecular packing and can be used to probe the changes in glass density. Such connection is technologically relevant and may advance further progress in the field.

Long-time stability effects of quadrature and artificial viscosity on nodal discontinuous Galerkin methods for gas dynamics

NASA Astrophysics Data System (ADS)

Durant, Bradford; Hackl, Jason; Balachandar, Sivaramakrishnan

2017-11-01

Nodal discontinuous Galerkin schemes present an attractive approach to robust high-order solution of the equations of fluid mechanics, but remain accompanied by subtle challenges in their consistent stabilization. The effect of quadrature choices (full mass matrix vs spectral elements), over-integration to manage aliasing errors, and explicit artificial viscosity on the numerical solution of a steady homentropic vortex are assessed over a wide range of resolutions and polynomial orders using quadrilateral elements. In both stagnant and advected vortices in periodic and non-periodic domains the need arises for explicit stabilization beyond the numerical surface fluxes of discontinuous Galerkin spectral elements. Artificial viscosity via the entropy viscosity method is assessed as a stabilizing mechanism. It is shown that the regularity of the artificial viscosity field is essential to its use for long-time stabilization of small-scale features in nodal discontinuous Galerkin solutions of the Euler equations of gas dynamics. Supported by the Department of Energy Predictive Science Academic Alliance Program Contract DE-NA0002378.

Derivative component analysis for mass spectral serum proteomic profiles.

PubMed

Han, Henry

2014-01-01

As a promising way to transform medicine, mass spectrometry based proteomics technologies have seen a great progress in identifying disease biomarkers for clinical diagnosis and prognosis. However, there is a lack of effective feature selection methods that are able to capture essential data behaviors to achieve clinical level disease diagnosis. Moreover, it faces a challenge from data reproducibility, which means that no two independent studies have been found to produce same proteomic patterns. Such reproducibility issue causes the identified biomarker patterns to lose repeatability and prevents it from real clinical usage. In this work, we propose a novel machine-learning algorithm: derivative component analysis (DCA) for high-dimensional mass spectral proteomic profiles. As an implicit feature selection algorithm, derivative component analysis examines input proteomics data in a multi-resolution approach by seeking its derivatives to capture latent data characteristics and conduct de-noising. We further demonstrate DCA's advantages in disease diagnosis by viewing input proteomics data as a profile biomarker via integrating it with support vector machines to tackle the reproducibility issue, besides comparing it with state-of-the-art peers. Our results show that high-dimensional proteomics data are actually linearly separable under proposed derivative component analysis (DCA). As a novel multi-resolution feature selection algorithm, DCA not only overcomes the weakness of the traditional methods in subtle data behavior discovery, but also suggests an effective resolution to overcoming proteomics data's reproducibility problem and provides new techniques and insights in translational bioinformatics and machine learning. The DCA-based profile biomarker diagnosis makes clinical level diagnostic performances reproducible across different proteomic data, which is more robust and systematic than the existing biomarker discovery based diagnosis. Our findings demonstrate the feasibility and power of the proposed DCA-based profile biomarker diagnosis in achieving high sensitivity and conquering the data reproducibility issue in serum proteomics. Furthermore, our proposed derivative component analysis suggests the subtle data characteristics gleaning and de-noising are essential in separating true signals from red herrings for high-dimensional proteomic profiles, which can be more important than the conventional feature selection or dimension reduction. In particular, our profile biomarker diagnosis can be generalized to other omics data for derivative component analysis (DCA)'s nature of generic data analysis.

Site-specific incorporation of uranyl carbonate species at the calcite surface

NASA Astrophysics Data System (ADS)

Reeder, Richard J.; Elzinga, Evert J.; Tait, C. Drew; Rector, K. D.; Donohoe, Robert J.; Morris, David E.

2004-12-01

Spatially resolved luminescence spectra from U(VI) co-precipitated at the (101¯4) growth surface of synthetic calcite single crystals confirm heterogeneous incorporation corresponding to the distribution of structurally non-equivalent steps composing the vicinal surfaces of spiral growth hillocks. Spectral structure from U(VI) luminescence at the "-" vicinal regions and featureless, weak luminescence at the "+" vicinal regions are consistent with previously reported observations of enrichment at the former sites during calcite growth. Luminescence spectra differ between the non-equivalent regions of the crystal, with the spectral features from the "-" vicinal region corresponding to those observed in bulk calcite samples. Subtle spectral shifts are observed from U(VI) co-precipitated with microcrystalline calcite synthesized by a different method, and all of the U(VI)-calcite sample spectra differ significantly from that of U(VI) co-precipitated with aragonite. The step-selective incorporation of U(VI) can be explained by a proposed model in which the allowed orientation for adsorption of the dominant calcium uranyl triscarbonate species is controlled by the atomic arrangement at step edges. Differences in the tilt angles of carbonate groups between non-equivalent growth steps favor adsorption of the calcium uranyl triscarbonate species at "-" steps, as observed in experiments.

Sports Stars: Analyzing the Performance of Astronomers at Visualization-based Discovery

NASA Astrophysics Data System (ADS)

Fluke, C. J.; Parrington, L.; Hegarty, S.; MacMahon, C.; Morgan, S.; Hassan, A. H.; Kilborn, V. A.

2017-05-01

In this data-rich era of astronomy, there is a growing reliance on automated techniques to discover new knowledge. The role of the astronomer may change from being a discoverer to being a confirmer. But what do astronomers actually look at when they distinguish between “sources” and “noise?” What are the differences between novice and expert astronomers when it comes to visual-based discovery? Can we identify elite talent or coach astronomers to maximize their potential for discovery? By looking to the field of sports performance analysis, we consider an established, domain-wide approach, where the expertise of the viewer (i.e., a member of the coaching team) plays a crucial role in identifying and determining the subtle features of gameplay that provide a winning advantage. As an initial case study, we investigate whether the SportsCode performance analysis software can be used to understand and document how an experienced Hi astronomer makes discoveries in spectral data cubes. We find that the process of timeline-based coding can be applied to spectral cube data by mapping spectral channels to frames within a movie. SportsCode provides a range of easy to use methods for annotation, including feature-based codes and labels, text annotations associated with codes, and image-based drawing. The outputs, including instance movies that are uniquely associated with coded events, provide the basis for a training program or team-based analysis that could be used in unison with discipline specific analysis software. In this coordinated approach to visualization and analysis, SportsCode can act as a visual notebook, recording the insight and decisions in partnership with established analysis methods. Alternatively, in situ annotation and coding of features would be a valuable addition to existing and future visualization and analysis packages.

Evaluation of the airborne visible-infrared imaging spectrometer for mapping subtle lithological variation

NASA Technical Reports Server (NTRS)

Kruse, Fred A.

1990-01-01

The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), flown aboard the NASA ER-2 aircraft in 1987 and 1989, used four linear arrays and four individual spectrometers to collect data simultaneously from the 224 bands in a scanned 614 pixel-wide swath perpendicular to the aircraft direction. The research had two goals. One was to evaluate the AVIRIS data. The other was to look at the subtle lithological variation at the two test sites to develop a better understanding of the regional geology and surficial processes. The geometric characteristics of the data, adequacy of the spatial resolution, and adequacy of the spectral sampling interval are evaluated. Geologic differences at the test sites were mapped. They included lithological variation caused by primary sedimentary layering, facies variation, and weathering; and subtle mineralogical differences caused by hydrothermal alterations of igneous and sedimentary rocks. The investigation used laboratory, field, and aircraft spectral measurements; known properties of geological materials; digital image processing and spectrum processing techniques; and field geologic data to evaluate the selected characteristics of the AVIRIS data.

Library Search Prefilters for Vehicle Manufacturers to Assist in the Forensic Examination of Automotive Paints.

PubMed

Lavine, Barry K; White, Collin G; Ding, Tao

2018-03-01

Pattern recognition techniques have been applied to the infrared (IR) spectral libraries of the Paint Data Query (PDQ) database to differentiate between nonidentical but similar IR spectra of automotive paints. To tackle the problem of library searching, search prefilters were developed to identify the vehicle make from IR spectra of the clear coat, surfacer-primer, and e-coat layers. To develop these search prefilters with the appropriate degree of accuracy, IR spectra from the PDQ database were preprocessed using the discrete wavelet transform to enhance subtle but significant features in the IR spectral data. Wavelet coefficients characteristic of vehicle make were identified using a genetic algorithm for pattern recognition and feature selection. Search prefilters to identify automotive manufacturer through IR spectra obtained from a paint chip recovered at a crime scene were developed using 1596 original manufacturer's paint systems spanning six makes (General Motors, Chrysler, Ford, Honda, Nissan, and Toyota) within a limited production year range (2000-2006). Search prefilters for vehicle manufacturer that were developed as part of this study were successfully validated using IR spectra obtained directly from the PDQ database. Information obtained from these search prefilters can serve to quantify the discrimination power of original automotive paint encountered in casework and further efforts to succinctly communicate trace evidential significance to the courts.

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 of plant phenolics and terpenes relative to dominant leaf biochemistry (water, chlorophyll, protein/nitrogen, cellulose, and lignin).

Spectral-temporal EEG dynamics of speech discrimination processing in infants during sleep.

PubMed

Gilley, Phillip M; Uhler, Kristin; Watson, Kaylee; Yoshinaga-Itano, Christine

2017-03-22

Oddball paradigms are frequently used to study auditory discrimination by comparing event-related potential (ERP) responses from a standard, high probability sound and to a deviant, low probability sound. Previous research has established that such paradigms, such as the mismatch response or mismatch negativity, are useful for examining auditory processes in young children and infants across various sleep and attention states. The extent to which oddball ERP responses may reflect subtle discrimination effects, such as speech discrimination, is largely unknown, especially in infants that have not yet acquired speech and language. Mismatch responses for three contrasts (non-speech, vowel, and consonant) were computed as a spectral-temporal probability function in 24 infants, and analyzed at the group level by a modified multidimensional scaling. Immediately following an onset gamma response (30-50 Hz), the emergence of a beta oscillation (12-30 Hz) was temporally coupled with a lower frequency theta oscillation (2-8 Hz). The spectral-temporal probability of this coupling effect relative to a subsequent theta modulation corresponds with discrimination difficulty for non-speech, vowel, and consonant contrast features. The theta modulation effect suggests that unexpected sounds are encoded as a probabilistic measure of surprise. These results support the notion that auditory discrimination is driven by the development of brain networks for predictive processing, and can be measured in infants during sleep. The results presented here have implications for the interpretation of discrimination as a probabilistic process, and may provide a basis for the development of single-subject and single-trial classification in a clinically useful context. An infant's brain is processing information about the environment and performing computations, even during sleep. These computations reflect subtle differences in acoustic feature processing that are necessary for language-learning. Results from this study suggest that brain responses to deviant sounds in an oddball paradigm follow a cascade of oscillatory modulations. This cascade begins with a gamma response that later emerges as a beta synchronization, which is temporally coupled with a theta modulation, and followed by a second, subsequent theta modulation. The difference in frequency and timing of the theta modulations appears to reflect a measure of surprise. These insights into the neurophysiological mechanisms of auditory discrimination provide a basis for exploring the clinically utility of the MMR TF and other auditory oddball responses.

Hungaria Asteroid Region Telescopic Spectral Survey (HARTSS) II: Spectral Homogeneity Among Hungaria Family Asteroids

NASA Astrophysics Data System (ADS)

Lucas, Michael P.; Emery, Joshua; Pinilla-Alonso, Noemi; Lindsay, Sean S.; MacLennan, Eric M.; Cartwright, Richard; Reddy, Vishnu; Sanchez, Juan A.; Thomas, Cristina A.; Lorenzi, Vania

2017-10-01

Spectral observations of asteroid family members provide valuable information regarding parent body interiors, the source regions of near-Earth asteroids, and the link between meteorites and their parent bodies. Hungaria family asteroids constitute the closest samples to the Earth from a collisional family (~1.94 AU), permitting observations of smaller fragments than accessible for Main Belt families. We have carried out a ground-based observational campaign - Hungaria Asteroid Region Telescopic Spectral Survey (HARTSS) - to record reflectance spectra of these preserved samples from the inner-most primordial asteroid belt. During HARTSS phase one (Lucas et al. [2017]. Icarus 291, 268-287) we found that ~80% of the background population is comprised of stony S-complex asteroids that exhibit considerable spectral and mineralogical diversity. In HARTSS phase two, we turn our attention to family members and hypothesize that the Hungaria collisional family is homogeneous. We test this hypothesis through taxonomic classification, albedo estimates, and spectral properties.During phase two of HARTSS we acquired near-infrared (NIR) spectra of 50 new Hungarias (19 family; 31 background) with SpeX/IRTF and NICS/TNG. We analyzed X-type family spectra for NIR color indices (0.85-J J-K), and a subtle ~0.9 µm absorption feature that may be attributed to Fe-poor orthopyroxene. Surviving fragments of an asteroid collisional family typically exhibit similar taxonomies, albedos, and spectral properties. Spectral analysis of X-type Hungaria family members and independently calculated WISE albedo determinations for 428 Hungaria asteroids is consistent with this scenario. Furthermore, ~1/4 of the background population exhibit similar spectral properties and albedos to family X-types.Spectral observations of 92 Hungaria region asteroids acquired during both phases of HARTSS uncover a compositionally heterogeneous background and spectral homogeneity down to ~2 km for collisional family members. Taxonomy, albedos, and spectral properties reveal that the Hungaria family progenitor was an igneous body that formed under reduced conditions, and was compositionally consistent with the enstatite achondrite (i.e., aubrite) meteorite group.

Improving the signal subtle feature extraction performance based on dual improved fractal box dimension eigenvectors

NASA Astrophysics Data System (ADS)

Chen, Xiang; Li, Jingchao; Han, Hui; Ying, Yulong

2018-05-01

Because of the limitations of the traditional fractal box-counting dimension algorithm in subtle feature extraction of radiation source signals, a dual improved generalized fractal box-counting dimension eigenvector algorithm is proposed. First, the radiation source signal was preprocessed, and a Hilbert transform was performed to obtain the instantaneous amplitude of the signal. Then, the improved fractal box-counting dimension of the signal instantaneous amplitude was extracted as the first eigenvector. At the same time, the improved fractal box-counting dimension of the signal without the Hilbert transform was extracted as the second eigenvector. Finally, the dual improved fractal box-counting dimension eigenvectors formed the multi-dimensional eigenvectors as signal subtle features, which were used for radiation source signal recognition by the grey relation algorithm. The experimental results show that, compared with the traditional fractal box-counting dimension algorithm and the single improved fractal box-counting dimension algorithm, the proposed dual improved fractal box-counting dimension algorithm can better extract the signal subtle distribution characteristics under different reconstruction phase space, and has a better recognition effect with good real-time performance.

Soft X-ray and cathodoluminescence measurement, optimisation and analysis at liquid nitrogen temperatures

NASA Astrophysics Data System (ADS)

MacRae, C. M.; Wilson, N. C.; Torpy, A.; Delle Piane, C.

2018-01-01

Advances in field emission gun electron microprobes have led to significant gains in the beam power density and when analysis at high resolution is required then low voltages are often selected. The resulting beam power can lead to damage and this can be minimised by cooling the sample down to cryogenic temperatures allowing sub-micrometre imaging using a variety of spectrometers. Recent advances in soft X-ray emission spectrometers (SXES) offer a spectral tool to measure both chemistry and bonding and when combined with spectral cathodoluminescence the complementary techniques enable new knowledge to be gained from both mineral and materials. Magnesium and aluminium metals have been examined at both room and liquid nitrogen temperatures by SXES and the L-emission Fermi-edge has been observed to sharpen at the lower temperatures directly confirming thermal broadening of the X-ray spectra. Gains in emission intensity and resolution have been observed in cathodoluminescence for liquid nitrogen cooled quartz grains compared to ambient temperature quartz. This has enabled subtle growth features at quartz to quartz-cement boundaries to be imaged for the first time.

Hints at Ceres Composition from Color

NASA Image and Video Library

2015-09-30

This map-projected view of Ceres was created from images taken by NASA's Dawn spacecraft during its high-altitude mapping orbit, in August and September, 2015. Images taken using infrared (920 nanometers), red (750 nanometers) and blue (440 nanometers) spectral filters were combined to create this false-color view. Redder colors indicate places on Ceres' surface that reflect light strongly in the infrared, while bluish colors indicate enhanced reflectivity at short (bluer) wavelengths; green indicates places where albedo, or overall brightness, is strongly enhanced. Scientists use this technique in order to highlight subtle color differences across Ceres, which would appear fairly uniform in natural color. This can provide valuable insights into the mineral composition of the surface, as well as the relative ages of surface features. http://photojournal.jpl.nasa.gov/catalog/PIA19977

Multi-contrast light profile microscopy for the depth-resolved imaging of the properties of multi-ply thin films.

PubMed

Power, J F

2009-06-01

Light profile microscopy (LPM) is a direct method for the spectral depth imaging of thin film cross-sections on the micrometer scale. LPM uses a perpendicular viewing configuration that directly images a source beam propagated through a thin film. Images are formed in dark field contrast, which is highly sensitive to subtle interfacial structures that are invisible to reference methods. The independent focusing of illumination and imaging systems allows multiple registered optical sources to be hosted on a single platform. These features make LPM a powerful multi-contrast (MC) imaging technique, demonstrated in this work with six modes of imaging in a single instrument, based on (1) broad-band elastic scatter; (2) laser excited wideband luminescence; (3) coherent elastic scatter; (4) Raman scatter (three channels with RGB illumination); (5) wavelength resolved luminescence; and (6) spectral broadband scatter, resolved in immediate succession. MC-LPM integrates Raman images with a wider optical and morphological picture of the sample than prior art microprobes. Currently, MC-LPM resolves images at an effective spectral resolution better than 9 cm(-1), at a spatial resolution approaching 1 microm, with optics that operate in air at half the maximum numerical aperture of the prior art microprobes.

Spectral response of fiber-coupled Fabry-Perot etalons.

PubMed

Ionov, Pavel

2014-03-01

In many remote sensing applications one or multiple Fabry-Perot etalons are used as high-spectral-resolution filter elements. These etalons are often coupled to a receiving telescope with a multimode fiber, leading to subtle effects of the fiber mode order on the overall spectral response of the system. A theoretical model is developed to treat the spectral response of the combined system: fiber, collimator, and etalon. The method is based on a closed-form expression of the diffracted mode in terms of a Hankel transform. In this representation, it is shown how the spectral effect of the fiber and collimator can be separated from the details of the etalon and can be viewed as a mode-dependent spectral broadening and shift.

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 spectral influences of plant phenolics and terpenes relative to dominant leaf biochemistry (water, chlorophyll, protein/nitrogen, cellulose, and lignin).

Spectral properties of the massless relativistic quartic oscillator

NASA Astrophysics Data System (ADS)

Durugo, Samuel O.; Lőrinczi, József

2018-03-01

An explicit solution of the spectral problem of the non-local Schrödinger operator obtained as the sum of the square root of the Laplacian and a quartic potential in one dimension is presented. The eigenvalues are obtained as zeroes of special functions related to the fourth order Airy function, and closed formulae for the Fourier transform of the eigenfunctions are derived. These representations allow to derive further spectral properties such as estimates of spectral gaps, heat trace and the asymptotic distribution of eigenvalues, as well as a detailed analysis of the eigenfunctions. A subtle spectral effect is observed which manifests in an exponentially tight approximation of the spectrum by the zeroes of the dominating term in the Fourier representation of the eigenfunctions and its derivative.

Theoretical modeling of UV-Vis absorption and emission spectra in liquid state systems including vibrational and conformational effects: explicit treatment of the vibronic transitions.

PubMed

D'Abramo, Marco; Aschi, Massimiliano; Amadei, Andrea

2014-04-28

Here, we extend a recently introduced theoretical-computational procedure [M. D'Alessandro, M. Aschi, C. Mazzuca, A. Palleschi, and A. Amadei, J. Chem. Phys. 139, 114102 (2013)] to include quantum vibrational transitions in modelling electronic spectra of atomic molecular systems in condensed phase. The method is based on the combination of Molecular Dynamics simulations and quantum chemical calculations within the Perturbed Matrix Method approach. The main aim of the presented approach is to reproduce as much as possible the spectral line shape which results from a subtle combination of environmental and intrinsic (chromophore) mechanical-dynamical features. As a case study, we were able to model the low energy UV-vis transitions of pyrene in liquid acetonitrile in good agreement with the experimental data.

Ion-absorption band analysis for the discrimination of iron-rich zones. [Nevada

NASA Technical Reports Server (NTRS)

Rowan, L. C. (Principal Investigator); Wetlaufer, P. H.

1974-01-01

The author has identified the following significant results. A technique which combines digital computer processing and color composition was devised for detecting hydrothermally altered areas and for discriminating among many rock types in an area in south-central Nevada. Subtle spectral reflectance differences among the rock types are enhanced by ratioing and contrast-stretching MSS radiance values for form ratio images which subsequently are displayed in color-ratio composites. Landform analysis of Nevada shows that linear features compiled without respect to length results in approximately 25 percent coincidence with mapped faults. About 80 percent of the major lineaments coincides with mapped faults, and substantial extension of locally mapped faults is commonly indicated. Seven major lineament systems appear to be old zones of crustal weakness which have provided preferred conduits for rising magma through periodic reactivation.

Airborne-biogeochemical survey test-case results

USGS Publications Warehouse

Collins, William E.; Chang, Sheng-Huei; Raines, Gary L.; Canney, Frank C.; Ashley, Roger; Barringer, Anthony R.

1980-01-01

Airborne spectroradiometer surveys over several forest-covered sulfide bodies indicate that mineralization has affected the overlying vegetation; anomalous spectral reflectivity properties can be detected in the vegetation using appropriate remote-sensing interments and data-reduction techniques. Mineralization induces subtle changes in the shape of the chlorophyll a and b absorption spectrum between 550 and 750 nm. The observed spectral variations appear specifically to be on the wings of the broad red chlorophyll bars, centered at about 680 nm.

AIS Spectra for Stressed and Unstressed Plant Communities in the Carolina Slate Belt

NASA Technical Reports Server (NTRS)

Wickland, D. E.

1985-01-01

Airborne imaging spectrometer (AIS) data were collected over a number of derelict heavy metal mine sites in the Carolina slate belt of North Carolina. A 32 channel (1156 to 1456 nm) data set was acquired in October, 1983 at the time of peak fall foliage display, and a 128 channel (1220 to 2420) data set was acquired near the end of the spring leaf flush in May, 1984. Spectral curves were extracted from the AIS data for differing ground cover types (e.g., pine forests, mixed deciduous forests, mine sites, and pastures). Variation in the width of an absorption feature located at approximately 1190 nm has been related to differences in forest type. Small differences in the location and shape of features in the near infrared plateau (1156 to 1300 nm) and the region 2000 to 2420 nm have yet to be evaluated. Because these variations were subtle, and because atmospheric effects were apparent in the data, high priority must be assigned to devising a means of removing atmospheric effects from AIS spectra.

FTIR microspectroscopic characterization of Spitz nevi

NASA Astrophysics Data System (ADS)

Giorgini, Elisabetta; Tosi, Giorgio; Conti, Carla; Staibano, Stefania; Ilardi, Gennaro; Sabbatini, Simona

2015-04-01

In the last 10 years, few efforts have been carried out to apply vibrational spectroscopy in the study of dermal pathologies in order to characterize the most relevant spectral markers for distinguishing benign from cancerous lesions. Spitz nevi are a special group of benign melanocytic lesions, characterized by spindled and/or epithelioid nevomelanocytes, with peculiar clinical, dermoscopic and histopathological features. The "atypical forms" of Spitz nevi are among the commonest problems of differential diagnosis with the so-called "spitzoid melanomas". The clinical and histological criteria for discriminating these two entities are very subtle and often still quite subjective, and, in a significant percentage of cases, can lead to diagnostic pitfalls and inadequate therapies. Therefore, it is noteworthy to outline that the diagnosis of melanocytic lesions still represents a challenging problem and a continue matter of discussion. We exploited FTIR microspectroscopy to study the different kinds of spitzoid melanocytes, in order to define the most relevant spectral markers of each specimen and to achieve objective information on "borderline" histologically atypical lesions. In particular, the spectroscopic investigation was carried out on melanocytes deriving from normal skin (as a normal control), malignant melanoma and Spitz nevi. The presence of the characteristic bands of melanin was investigated, too.

Parahippocampal epilepsy with subtle dysplasia: A cause of "imaging negative" partial epilepsy.

PubMed

Pillay, Neelan; Fabinyi, Gavin C A; Myles, Terry S; Fitt, Gregory J; Berkovic, Samuel F; Jackson, Graeme D

2009-12-01

Lesion-negative refractory partial epilepsy is a major challenge in the assessment of patients for potential surgery. Finding a potential epileptogenic lesion simplifies assessment and is associated with good outcome. Here we describe imaging features of subtle parahippocampal dysplasia in five cases that were initially assessed as having imaging-negative frontal or temporal lobe epilepsy. We analyzed the clinical and imaging features of five patients with seizures from the parahippocampal region. Five patients had subtle but distinctive magnetic resonance imaging (MRI) abnormalities in the parahippocampal gyrus. This was a unilateral signal abnormality in the parahippocampal white matter extending into gray matter on heavily T(1)- and T(2)-weighted images with relative preservation of the gray-white matter boundary on T(1)-weighted volume sequences. Only one of these patients had typical electroclinical unilateral temporal lobe epilepsy (TLE); one mimicked frontal lobe epilepsy, two showed bitemporal seizures, and one had unlocalized partial seizures. All have had surgery; four are seizure-free (one has occasional auras only, follow-up 6 months to 10 years), and one has a >50% seizure reduction. Histopathologic evaluation suggested dysplastic features in the surgical specimens in all. In patients with lesion-negative partial epilepsy with frontal or temporal semiology, or in cases with apparent bitemporal seizures, subtle parahippocampal abnormalities should be carefully excluded. Recognizing the MRI findings of an abnormal parahippocampal gyrus can lead to successful surgery without invasive monitoring, despite apparently incongruent electroclinical features.

Mapping ephemeral stream networks in desert environments using very-high-spatial-resolution multispectral remote sensing

DOE PAGES

Hamada, Yuki; O'Connor, Ben L.; Orr, Andrew B.; ...

2016-03-26

In this paper, understanding the spatial patterns of ephemeral streams is crucial for understanding how hydrologic processes influence the abundance and distribution of wildlife habitats in desert regions. Available methods for mapping ephemeral streams at the watershed scale typically underestimate the size of channel networks. Although remote sensing is an effective means of collecting data and obtaining information on large, inaccessible areas, conventional techniques for extracting channel features are not sufficient in regions that have small topographic gradients and subtle target-background spectral contrast. By using very high resolution multispectral imagery, we developed a new algorithm that applies landscape information tomore » map ephemeral channels in desert regions of the Southwestern United States where utility-scale solar energy development is occurring. Knowledge about landscape features and structures was integrated into the algorithm using a series of spectral transformation and spatial statistical operations to integrate information about landscape features and structures. The algorithm extracted ephemeral stream channels at a local scale, with the result that approximately 900% more ephemeral streams was identified than what were identified by using the U.S. Geological Survey’s National Hydrography Dataset. The accuracy of the algorithm in detecting channel areas was as high as 92%, and its accuracy in delineating channel center lines was 91% when compared to a subset of channel networks that were digitized by using the very high resolution imagery. Although the algorithm captured stream channels in desert landscapes across various channel sizes and forms, it often underestimated stream headwaters and channels obscured by bright soils and sparse vegetation. While further improvement is warranted, the algorithm provides an effective means of obtaining detailed information about ephemeral streams, and it could make a significant contribution toward improving the hydrological modelling of desert environments.« less

Mapping ephemeral stream networks in desert environments using very-high-spatial-resolution multispectral remote sensing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hamada, Yuki; O'Connor, Ben L.; Orr, Andrew B.

In this paper, understanding the spatial patterns of ephemeral streams is crucial for understanding how hydrologic processes influence the abundance and distribution of wildlife habitats in desert regions. Available methods for mapping ephemeral streams at the watershed scale typically underestimate the size of channel networks. Although remote sensing is an effective means of collecting data and obtaining information on large, inaccessible areas, conventional techniques for extracting channel features are not sufficient in regions that have small topographic gradients and subtle target-background spectral contrast. By using very high resolution multispectral imagery, we developed a new algorithm that applies landscape information tomore » map ephemeral channels in desert regions of the Southwestern United States where utility-scale solar energy development is occurring. Knowledge about landscape features and structures was integrated into the algorithm using a series of spectral transformation and spatial statistical operations to integrate information about landscape features and structures. The algorithm extracted ephemeral stream channels at a local scale, with the result that approximately 900% more ephemeral streams was identified than what were identified by using the U.S. Geological Survey’s National Hydrography Dataset. The accuracy of the algorithm in detecting channel areas was as high as 92%, and its accuracy in delineating channel center lines was 91% when compared to a subset of channel networks that were digitized by using the very high resolution imagery. Although the algorithm captured stream channels in desert landscapes across various channel sizes and forms, it often underestimated stream headwaters and channels obscured by bright soils and sparse vegetation. While further improvement is warranted, the algorithm provides an effective means of obtaining detailed information about ephemeral streams, and it could make a significant contribution toward improving the hydrological modelling of desert environments.« less

Characterization of Isomeric Glycans by Reversed Phase Liquid Chromatography-Electronic Excitation Dissociation Tandem Mass Spectrometry

NASA Astrophysics Data System (ADS)

Tang, Yang; Wei, Juan; Costello, Catherine E.; Lin, Cheng

2018-04-01

The occurrence of numerous structural isomers in glycans from biological sources presents a severe challenge for structural glycomics. The subtle differences among isomeric structures demand analytical methods that can provide structural details while working efficiently with on-line glycan separation methods. Although liquid chromatography-tandem mass spectrometry (LC-MS/MS) is a powerful tool for mixture analysis, the commonly utilized collision-induced dissociation (CID) method often does not generate a sufficient number of fragments at the MS2 level for comprehensive structural characterization. Here, we studied the electronic excitation dissociation (EED) behaviors of metal-adducted, permethylated glycans, and identified key spectral features that could facilitate both topology and linkage determinations. We developed an EED-based, nanoscale, reversed phase (RP)LC-MS/MS platform, and demonstrated its ability to achieve complete structural elucidation of up to five structural isomers in a single LC-MS/MS analysis. [Figure not available: see fulltext.

Interdisciplinary applications and interpretations of EREP data within the Susquehanna River Basin

NASA Technical Reports Server (NTRS)

Mcmurtry, G. J.; Petersen, G. W. (Principal Investigator)

1976-01-01

The author has identified the following significant results. Photography from the S190A and S190B sensors was compared, for terrain analysis. The S190B photographs were used for terrain mapping of three test areas selected as being representative of major physiographic regions in Pennsylvania. Skylab photography was superior to both LANDSAT imagery and high altitude aircraft photography for purposes of accurate location of lineaments. Analysis of Skylab imagery has shown that long lineaments originally plotted on LANDSAT images are actually made up of shorter segments. Correlation of lineaments with ore deposits was determined following the preparation of a Pennsylvania mineral deposit map. Digital wave number analysis (spatial filtering) was attempted to determine if it can be used to enhance certain subtle features, and in particular, to locate and verify lineaments. Various spectral bands and channels of the MSS digital data were evaluated for their value in the classification and thematic mapping.

Spectral Mapping at Asteroid 101955 Bennu

NASA Astrophysics Data System (ADS)

Clark, Beth Ellen; Hamilton, Victoria E.; Emery, Joshua P.; Hawley, C. Luke; Howell, Ellen S.; Lauretta, Dante; Simon, Amy A.; Christensen, Philip R.; Reuter, Dennis

2017-10-01

The OSIRIS-REx Asteroid Sample Return mission was launched in September 2016. The main science surveys of asteroid 101955 Bennu start in March 2019. Science instruments include a Visible-InfraRed Spectrometer (OVIRS) and a Thermal Emission Spectrometer (OTES) that will produce observations that will be co-registered to the tessellated shape model of Bennu (the fundamental unit of which is a triangular facet). One task of the science team is to synthesize the results in real time during proximity operations to contribute to selection of the sampling site. Hence, we will be focused on quickly producing spectral maps for: (1) mineral abundances; (2) band strengths of minerals and chemicals (including a search for the subtle ~5% absorption feature produced by organics in meteorites); and (3) temperature and thermal inertia values. In sum, we will be producing on the order of ~60 spectral maps of Bennu’s surface composition and thermophysical properties. Due to overlapping surface spots, simulations of our spectral maps show there may be an opportunity to perform spectral super-resolution. We have a large parameter space of choices available in creating spectral maps of Bennu, including: (a) mean facet size (shape model resolution), (b) percentage of overlap between subsequent spot measurements, (c) the number of spectral spots measured per facet, and (d) the mathematical algorithm used to combine the overlapping spots (or bin them on a per-facet basis). Projection effects -- caused by irregular sampling of an irregularly shaped object with circular spectrometer fields-of-view and then mapping these circles onto triangular facets -- can be intense. To prepare for prox ops, we are simulating multiple mineralogical “truth worlds” of Bennu to study the projection effects that result from our planned methods of spectral mapping. This presentation addresses: Can we combine the three planned global surveys of the asteroid (to be obtained at different phase angles) to create a spectral map with higher spatial resolution than the native spectrometer field-of-view in order to increase our confidence in detection of a spatially small occurrence of organics on Bennu?

Potential of FTIR spectroscopy for analysis of tears for diagnosis purposes.

PubMed

Travo, Adrian; Paya, Clément; Déléris, Gérard; Colin, Joseph; Mortemousque, Bruno; Forfar, Isabelle

2014-04-01

It has been widely reported that the tear film, which is crucially important as a protective barrier of the eye, undergoes biochemical changes as a result of a wide range of ocular pathology. This tends to suggest the possibility of early detection of ocular diseases on the basis of biochemical analysis of tears. However, studies of tears by conventional methods of biomolecular and biochemical analysis are often limited by methodological difficulties. Moreover, such analysis could not be applied in the clinic, where structural and morphological analyses by, mainly, slit-lamp biomicroscopy remains the recommended method. In this study, we assessed, for the first time, the potential of FTIR spectroscopy combined with advanced chemometric processing of spectral data for analysis of raw tears for diagnosis purposes. We first optimized sampling and spectral acquisition (tears collection method, tear sample volume, and preservation of the samples) for accurate spectral measurement. On the basis of the results, we focused our study on the possibility of discriminating tears from normal individuals from those of patients with different ocular pathologies, and showed that the most discriminating spectral range is that corresponding to variations of CH2 and CH3 of lipid aliphatic chains. We also report more subtle discrimination of tears from patients with keratoconus and those from patients with non-specific inflammatory ocular diseases, on the basis of variations in spectral ranges attributed notably to lipid and carbohydrate vibrations. Finally, we also succeeded in distinguishing tears from patients with early-stage and late-stage keratoconus on the basis of spectral features attributed to protein structure. Therefore, this study strongly suggests that FTIR spectral analysis of tears could be developed as a valuable and cost-saving tool for biochemical-based detection of ocular diseases, potentially before the appearance of the first morphological signs of diseases. Combined with supervised modelling methods and with use of a spectral data base acquired for representative patients, such a spectral approach could be a useful addition to current methods of clinical analysis for improvement of patient care.

Analysis of Shuttle Multispecral Infrared Radiometer measurements of the western Saudi Arabian shield.

USGS Publications Warehouse

Rowan, Lawrence C.; Goetz, Alexander F.H.; Abbott, Elsa

1987-01-01

During the November 12–14, 1981, mission of the space shuttle Columbia, the Shuttle Multispectral Infrared Radiometer (SMIRR) recorded radiances in ten channels along a 100 m wide groundtrack across the western Saudi Arabian shield. The ten channels are located in the 0.5 to 2.4 μm region, with five positioned between 2.0 and 2.40 μm for measuring absorption features that are diagnostic of OH‐bearing and CO3‐bearing">CO3‐bearing minerals. This exceptionally well exposed area consists of late Proterozoic metamorphic, intermediate to silicic intrusive, and interlayered clastic sedimentary and intermediate silicic volcanic rocks that have not been studied previously using SMIRR data. Plots or traces of unnormalized SMIRR channel ratios were examined before field studies to locate areas with high spectral contrast, especially in the 2.0 μm to 2.40 μm channels. Reflectance spectra were measured in the laboratory for rock and soil samples collected in these areas, and the mineralogic causes of the main absorption features were determined using X‐ray diffraction. Laboratory SMIRR spectra were produced by convolving the ten SMIRR filters with the laboratory spectra. Then, normalized SMIRR reflectance spectra were generated along the groundtrack using normalization coefficients calculated for a field sample representing a uniform, low‐spectral contrast area. Field evaluation shows that unnormalized SMIRR ratio traces are useful, even without specific mineralogic information, for distinguishing rocks that are characterized by Al‐OH, Mg‐OH, and/or CO3">CO3">CO3, Fe3+">Fe3+, and Fe2+ absorption features. Analysis of field samples permits suites of minerals causing absorption features to be identified. However, specific mineral identification cannot be achieved consistently using the SMIRR ratio traces or normalized SMIRR spectra, because the Al‐OH and Mg‐OH absorption features can be caused by more than one of the minerals commonly present. The normalized SMIRR spectra are especially useful for identifying subtle Al‐OH and Mg‐OH absorption features that are difficult to identify in the unnormalized ratio traces and for comparing the relative intensities of absorption features. Al‐OH absorption is related to muscovite, smectite, illite, and kaolinite, whereas Mg‐OH absorption is caused by chlorite, amphibole, and biotite. The principal sources of error in using SMIRR spectral measurements for identifying mineral groups along the orbit 27 groundtrack are inaccuracies in field location and lithologic heterogeneity that is not represented adequately by field samples. Calibration errors may account for systematic albedo and absorption intensity differences between calculated laboratory SMIRR spectra and normalized SMIRR spectra. SMIRR instrument noise and atmospheric factors appear to be less important sources of error. However, as higher spectral and spatial resolution systems are developed for mineral identification, radiometric precision and atmospheric factors will become more important.

Signature Optical Cues: Emerging Technologies for Monitoring Plant Health

PubMed Central

Liew, Oi Wah; Chong, Pek Ching Jenny; Li, Bingqing; Asundi, Anand K.

2008-01-01

Optical technologies can be developed as practical tools for monitoring plant health by providing unique spectral signatures that can be related to specific plant stresses. Signatures from thermal and fluorescence imaging have been used successfully to track pathogen invasion before visual symptoms are observed. Another approach for non-invasive plant health monitoring involves elucidating the manner with which light interacts with the plant leaf and being able to identify changes in spectral characteristics in response to specific stresses. To achieve this, an important step is to understand the biochemical and anatomical features governing leaf reflectance, transmission and absorption. Many studies have opened up possibilities that subtle changes in leaf reflectance spectra can be analyzed in a plethora of ways for discriminating nutrient and water stress, but with limited success. There has also been interest in developing transgenic phytosensors to elucidate plant status in relation to environmental conditions. This approach involves unambiguous signal creation whereby genetic modification to generate reporter plants has resulted in distinct optical signals emitted in response to specific stressors. Most of these studies are limited to laboratory or controlled greenhouse environments at leaf level. The practical translation of spectral cues for application under field conditions at canopy and regional levels by remote aerial sensing remains a challenge. The movement towards technology development is well exemplified by the Controlled Ecological Life Support System under development by NASA which brings together technologies for monitoring plant status concomitantly with instrumentation for environmental monitoring and feedback control. PMID:27879874

Search prefilters to assist in library searching of infrared spectra of automotive clear coats.

PubMed

Lavine, Barry K; Fasasi, Ayuba; Mirjankar, Nikhil; White, Collin; Sandercock, Mark

2015-01-01

Clear coat searches of the infrared (IR) spectral library of the paint data query (PDQ) forensic database often generate an unusable number of hits that span multiple manufacturers, assembly plants, and years. To improve the accuracy of the hit list, pattern recognition methods have been used to develop search prefilters (i.e., principal component models) that differentiate between similar but non-identical IR spectra of clear coats on the basis of manufacturer (e.g., General Motors, Ford, Chrysler) or assembly plant. A two step procedure to develop these search prefilters was employed. First, the discrete wavelet transform was used to decompose each IR spectrum into wavelet coefficients to enhance subtle but significant features in the spectral data. Second, a genetic algorithm for IR spectral pattern recognition was employed to identify wavelet coefficients characteristic of the manufacturer or assembly plant of the vehicle. Even in challenging trials where the paint samples evaluated were all from the same manufacturer (General Motors) within a limited production year range (2000-2006), the respective assembly plant of the vehicle was correctly identified. Search prefilters to identify assembly plants were successfully validated using 10 blind samples provided by the Royal Canadian Mounted Police (RCMP) as part of a study to populate PDQ to current production years, whereas the search prefilter to discriminate among automobile manufacturers was successfully validated using IR spectra obtained directly from the PDQ database. Copyright © 2014 Elsevier B.V. All rights reserved.

Spectral Properties and Dynamics of Gold Nanorods Revealed by EMCCD Based Spectral-Phasor Method

PubMed Central

Chen, Hongtao; Digman, Michelle A.

2015-01-01

Gold nanorods (NRs) with tunable plasmon-resonant absorption in the near-infrared region have considerable advantages over organic fluorophores as imaging agents. However, the luminescence spectral properties of NRs have not been fully explored at the single particle level in bulk due to lack of proper analytic tools. Here we present a global spectral phasor analysis method which allows investigations of NRs' spectra at single particle level with their statistic behavior and spatial information during imaging. The wide phasor distribution obtained by the spectral phasor analysis indicates spectra of NRs are different from particle to particle. NRs with different spectra can be identified graphically in corresponding spatial images with high spectral resolution. Furthermore, spectral behaviors of NRs under different imaging conditions, e.g. different excitation powers and wavelengths, were carefully examined by our laser-scanning multiphoton microscope with spectral imaging capability. Our results prove that the spectral phasor method is an easy and efficient tool in hyper-spectral imaging analysis to unravel subtle changes of the emission spectrum. Moreover, we applied this method to study the spectral dynamics of NRs during direct optical trapping and by optothermal trapping. Interestingly, spectral shifts were observed in both trapping phenomena. PMID:25684346

Feature: Post Traumatic Stres Disorder PTSD: Symptoms, Diagnosis, Treatment

MedlinePlus

... Navigation Bar Home Current Issue Past Issues Feature PTSD Symptoms, Diagnosis , Treatment Past Issues / Winter 2009 Table ... Symptoms As with mild traumatic brain injury (TBI), PTSD symptoms can be very subtle. "For example, some ...

Advancing Glaciological Applications of Remote Sensing with EO-1: (1) Mapping Snow Grain Size and Albedo on the Greenland Ice Sheet Using an Imaging Spectrometer, and (2) ALI Evaluation for Subtle Surface Topographic Mapping via Shape-from Shading

NASA Technical Reports Server (NTRS)

2003-01-01

The Hyperion sensor, onboard NASA's Earth Observing-1 (EO-1) satellite,is an imaging spectroradiometer with 220 spectral bands over the spectral range from 0.4 - 2.5 microns. Over the course of summer 2001, the instrument acquired numerous images over the Greenland ice sheet. Our main motivation is to develop an accurate and robust approach for measuring the broadband albedo of snow from satellites. Satellite-derived estimates of broadband have typically been plagued with three problems: errors resulting from inaccurate atmospheric correction, particularly in the visible wavelengths from the conversion of reflectance to albedo (accounting for snow BRDE); and errors resulting from regression-based approaches used to convert narrowband albedo to broadband albedo. A typerspectral method has been developed that substantially reduces these three main sources of error and produces highly accurate estimates of snow albedo. This technique uses hyperspectral data from 0.98 - 1.06 microns, spanning a spectral absorption feature centered at 1.03 microns. A key aspect of this work is that this spectral range is within an atmospheric transmission window and reflectances are largely unaffected by atmospheric aerosols, water vapor, or ozone. In this investigation, we make broadband albedo measurements at four sites on the Greenland ice sheet: Summit, a high altitude station in central Greenland; the ETH/CU camp, a camp on the equilibrium line in western Greenland; Crawford Point, a site located between Summit and the ETH/CU camp; and Tunu, a site located in northeastern Greenland at 2000 m. altitude. Each of these sites has an automated weather station (AWS) that continually measures broadband albedo thereby providing validation data.

Highly tunable colloidal perovskite nanoplatelets through variable cation, metal, and halide composition

DOE PAGES

Weidman, Mark C.; Seitz, Michael; Stranks, Samuel D.; ...

2016-07-29

Here, colloidal perovskite nanoplatelets are a promising class of semiconductor nanomaterials-exhibiting bright luminescence, tunable and spectrally narrow absorption and emission features, strongly confined excitonic states, and facile colloidal synthesis. Here, we demonstrate the high degree of spectral tunability achievable through variation of the cation, metal, and halide composition as well as nanoplatelet thickness. We synthesize nanoplatelets of the form L 2[ABX 3] n-1BX 4, where L is an organic ligand (octylammonium, butylammonium), A is a monovalent metal or organic molecular cation (cesium, methylammonium, formamidinium), B is a divalent metal cation (lead, tin), X is a halide anion (chloride, bromide, iodide),more » and n-1 is the number of unit cells in thickness. We show that variation of n, B, and X leads to large changes in the absorption and emission energy, while variation of the A cation leads to only subtle changes but can significantly impact the nanoplatelet stability and photoluminescence quantum yield (with values over 20%). Furthermore, mixed halide nanoplatelets exhibit continuous spectral tunability over a 1.5 eV spectral range, from 2.2 to 3.7 eV. The nanoplatelets have relatively large lateral dimensions (100 nm to 1 μm), which promote self-assembly into stacked superlattice structures-the periodicity of which can be adjusted based on the nanoplatelet surface ligand length. These results demonstrate the versatility of colloidal perovskite nanoplatelets as a material platform, with tunability extending from the deep-UV, across the visible, into the near-IR. In particular, the tin-containing nanoplatelets represent a significant addition to the small but increasingly important family of lead- and cadmium-free colloidal semiconductors.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Abeysekara, A. U.; Flinders, A.; Archambault, S.

Blazars are variable emitters across all wavelengths over a wide range of timescales, from months down to minutes. It is therefore essential to observe blazars simultaneously at different wavelengths, especially in the X-ray and gamma-ray bands, where the broadband spectral energy distributions usually peak. In this work, we report on three “target-of-opportunity” observations of Mrk 421, one of the brightest TeV blazars, triggered by a strong flaring event at TeV energies in 2014. These observations feature long, continuous, and simultaneous exposures with XMM-Newton (covering the X-ray and optical/ultraviolet bands) and VERITAS (covering the TeV gamma-ray band), along with contemporaneous observationsmore » from other gamma-ray facilities (MAGIC and Fermi -Large Area Telescope) and a number of radio and optical facilities. Although neither rapid flares nor significant X-ray/TeV correlation are detected, these observations reveal subtle changes in the X-ray spectrum of the source over the course of a few days. We search the simultaneous X-ray and TeV data for spectral hysteresis patterns and time delays, which could provide insight into the emission mechanisms and the source properties (e.g., the radius of the emitting region, the strength of the magnetic field, and related timescales). The observed broadband spectra are consistent with a one-zone synchrotron self-Compton model. We find that the power spectral density distribution at ≳4 × 10{sup −4} Hz from the X-ray data can be described by a power-law model with an index value between 1.2 and 1.8, and do not find evidence for a steepening of the power spectral index (often associated with a characteristic length scale) compared to the previously reported values at lower frequencies.« less

Fruit ripening using hyperspectral imaging

NASA Astrophysics Data System (ADS)

., Swetha; Chidangil, Santhosh; Karpate, Tanvi; Asundi, Anand

2017-06-01

The ripening of fruits is associated with changes, in some cases subtle, in the color of the fruit. Traditionally spectroscopy used to measure these subtle changes and infer the ripeness of fruits. Spectrometers provides high-resolution but only measure a small area of the fruit. That might not be a good indicator of the overall ripeness. In this paper, we propose a compact tunable LED based hyper spectral imaging system that scans through a set of wavelengths and images, the reflectance from the whole fruit. Based on the type of fruit, only specific wavelengths need to be scanned. Following a validation using a Rubik's cube, an example banana going through its ripening cycles is used to demonstrate the system.

Characterization of Interfacial Chemistry of Adhesive/Dentin Bond Using FTIR Chemical Imaging With Univariate and Multivariate Data Processing

PubMed Central

Wang, Yong; Yao, Xiaomei; Parthasarathy, Ranganathan

2008-01-01

Fourier transform infrared (FTIR) chemical imaging can be used to investigate molecular chemical features of the adhesive/dentin interfaces. However, the information is not straightforward, and is not easily extracted. The objective of this study was to use multivariate analysis methods, principal component analysis and fuzzy c-means clustering, to analyze spectral data in comparison with univariate analysis. The spectral imaging data collected from both the adhesive/healthy dentin and adhesive/caries-affected dentin specimens were used and compared. The univariate statistical methods such as mapping of intensities of specific functional group do not always accurately identify functional group locations and concentrations due to more or less band overlapping in adhesive and dentin. Apart from the ease with which information can be extracted, multivariate methods highlight subtle and often important changes in the spectra that are difficult to observe using univariate methods. The results showed that the multivariate methods gave more satisfactory, interpretable results than univariate methods and were conclusive in showing that they can discriminate and classify differences between healthy dentin and caries-affected dentin within the interfacial regions. It is demonstrated that the multivariate FTIR imaging approaches can be used in the rapid characterization of heterogeneous, complex structure. PMID:18980198

Wavelets in music analysis and synthesis: timbre analysis and perspectives

NASA Astrophysics Data System (ADS)

Alves Faria, Regis R.; Ruschioni, Ruggero A.; Zuffo, Joao A.

1996-10-01

Music is a vital element in the process of comprehending the world where we live and interact with. Frequency it exerts a subtle but expressive influence over a society's evolution line. Analysis and synthesis of music and musical instruments has always been associated with forefront technologies available at each period of human history, and there is no surprise in witnessing now the use of digital technologies and sophisticated mathematical tools supporting its development. Fourier techniques have been employed for years as a tool to analyze timbres' spectral characteristics, and re-synthesize them from these extracted parameters. Recently many modern implementations, based on spectral modeling techniques, have been leading to the development of new generations of music synthesizers, capable of reproducing natural sounds with high fidelity, and producing novel timbres as well. Wavelets are a promising tool on the development of new generations of music synthesizers, counting on its advantages over the Fourier techniques in representing non-periodic and transient signals, with complex fine textures, as found in music. In this paper we propose and introduce the use of wavelets addressing its perspectives towards musical applications. The central idea is to investigate the capacities of wavelets in analyzing, extracting features and altering fine timbre components in a multiresolution time- scale, so as to produce high quality synthesized musical sounds.

Subtle evidence for paleoseismicity in the cratonic interior, U.S. A

NASA Astrophysics Data System (ADS)

Jacobson, W. Z.; Cowan, C. A.; Runkel, A. C.

2009-12-01

Intrastratal deformation features in Cambrian-Ordovician boundary strata in southeastern Minnesota, U.S.A., may be evidence for mid-continent paleoseismicity. Deformation features are present tens of kilometers east of the Midcontinent Rift zone, and include sand blows, water escape, and convolute lamination, as well as more subtle structures indicative of sand-on-sand density contrasts. The stratigraphic interval of interest is the uppermost Jordan Formation (Furongian), a very fine- to coarse-grained quartzose sandstone, and the basal Oneota Formation (Tremadocian), a heterolithic sandstone and dolostone that grades upward into bedded dolostone. Along the Jordan-Oneota boundary, deformation features are extensive, and the result of sand liquefaction and fluidization. Upward migration of excess pore water was obstructed in places by shale drapes that locally ruptured, causing sand to be injected into overlying beds. Movement of sand in this manner created voids that were filled by a chaotic mixture of sand, shale, and pebbles that collapsed from above. Where upwardly percolating water was not confined by shale, intrastratal flow produced water escape pillars. Other deformation features are present up to ~3 m below the Jordan-Oneota boundary, in well-sorted, pure quartzose sandstone. These features are inconspicuous because of the uniform texture and minerology of the sediment, and some were previously interpreted as synsedimentary phenomena. These features are common along foreset boundaries in large-scale (>3 m) cross-strata, and include cm-scale digitate interfaces (interfingering) and in situ rounded forms interpreted as sand-on-sand boudinage. They formed from density contrasts between individual foresets within the cross-bedded sand. The top of the lower foreset was less dense but more viscous than the base of the succeeding foreset. Such contrasts were the result of subtle packing and grain size differences formed during the avalanche process during dune migration. We interpret the trigger for deformation, however, to be a post-depositional (post-Oneota) event because of the association of these subtle features with the more obvious liquefaction features in the immediately overlying boundary strata (and the increased intensity of deformation along foresets upward toward the boundary). Although these features cannot be unambiguously attributed to a paleoseismic event, some other common possibilities can be eliminated, including slumping and loading by sediment, tides, and storm waves. These intrastratal deformation features are documented in one outcrop in southeastern Minnesota. The subtlety of some of these features suggests that similar features may have been overlooked in nearby outcrops. Indeed, we are now revisiting unusual features in some localities that we previously interpreted as synsedimentary phenomena. Seismites may be difficult to generate, and to recognize, in quartoze sandstones of the mid-continent due to the lack of significantly thick clay beds to serve as permeability barriers, and the homogenous textural and mineralogical attributes of these units.

California coast nearshore processes study. [nearshore currents, sediment transport, estuaries, and river discharge

NASA Technical Reports Server (NTRS)

Pirie, D. M.; Steller, D. D. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Large scale sediment plumes from intermittent streams and rivers form detectable seasonal patterns on ERTS-1 imagery. The ocean current systems, as plotted from three California coast ERTS mosaics, were identified. Offshore patterns of sediment in areas such as the Santa Barbara Channel are traceable. These patterns extend offshore to heretofore unanticipated ranges as shown on the ERTS-1 imagery. Flying spot scanner enhancements of NASA tapes resulted in details of subtle and often invisible (to the eye) nearshore features. The suspended sediments off San Francisco and in Monterey Bay are emphasized in detail. These are areas of extremely changeable offshore sediment transport patterns. Computer generated contouring of radiance levels resulted in maps that can be used in determining surface and nearsurface suspended sediment distribution. Tentative calibrations of ERTS-1 spectral brightness against sediment load have been made using shipboard measurements. Information from the combined enhancement and interpretation techniques is applicable to operational coastal engineering programs.

Rayleigh-enhanced attosecond sum-frequency polarization beats via twin color-locking noisy lights

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang Yanpeng; Li Long; Ma Ruiqiong

2005-07-15

Based on color-locking noisy field correlation, a time-delayed method is proposed to suppress the thermal effect, and the ultrafast longitudinal relaxation time can be measured even in an absorbing medium. One interesting feature in field-correlation effects is that Rayleigh-enhanced four-wave mixing (RFWM) with color-locking noisy light exhibits spectral symmetry and temporal asymmetry with no coherence spike at {tau}=0. Due to the interference between the Rayleigh-resonant signal and the nonresonant background, RFWM exhibits hybrid radiation-matter detuning with terahertz damping oscillations. The subtle Markovian high-order correlation effects have been investigated in the homodyne- or heterodyne-detected Rayleigh-enhanced attosecond sum-frequency polarization beats (RASPBs). Analyticmore » closed forms of fourth-order Markovian stochastic correlations are characterized for homodyne (quadratic) and heterodyne (linear) detection, respectively. Based on the polarization interference between two four-wave mixing processes, the phase-sensitive detection of RASPBs has also been used to obtain the real and imaginary parts of the Rayleigh resonance.« less

Spectral-Spatial Scale Invariant Feature Transform for Hyperspectral Images.

PubMed

Al-Khafaji, Suhad Lateef; Jun Zhou; Zia, Ali; Liew, Alan Wee-Chung

2018-02-01

Spectral-spatial feature extraction is an important task in hyperspectral image processing. In this paper we propose a novel method to extract distinctive invariant features from hyperspectral images for registration of hyperspectral images with different spectral conditions. Spectral condition means images are captured with different incident lights, viewing angles, or using different hyperspectral cameras. In addition, spectral condition includes images of objects with the same shape but different materials. This method, which is named spectral-spatial scale invariant feature transform (SS-SIFT), explores both spectral and spatial dimensions simultaneously to extract spectral and geometric transformation invariant features. Similar to the classic SIFT algorithm, SS-SIFT consists of keypoint detection and descriptor construction steps. Keypoints are extracted from spectral-spatial scale space and are detected from extrema after 3D difference of Gaussian is applied to the data cube. Two descriptors are proposed for each keypoint by exploring the distribution of spectral-spatial gradient magnitude in its local 3D neighborhood. The effectiveness of the SS-SIFT approach is validated on images collected in different light conditions, different geometric projections, and using two hyperspectral cameras with different spectral wavelength ranges and resolutions. The experimental results show that our method generates robust invariant features for spectral-spatial image matching.

Fractal based modelling and analysis of electromyography (EMG) to identify subtle actions.

PubMed

Arjunan, Sridhar P; Kumar, Dinesh K

2007-01-01

The paper reports the use of fractal theory and fractal dimension to study the non-linear properties of surface electromyogram (sEMG) and to use these properties to classify subtle hand actions. The paper reports identifying a new feature of the fractal dimension, the bias that has been found to be useful in modelling the muscle activity and of sEMG. Experimental results demonstrate that the feature set consisting of bias values and fractal dimension of the recordings is suitable for classification of sEMG against the different hand gestures. The scatter plots demonstrate the presence of simple relationships of these features against the four hand gestures. The results indicate that there is small inter-experimental variation but large inter-subject variation. This may be due to differences in the size and shape of muscles for different subjects. The possible applications of this research include use in developing prosthetic hands, controlling machines and computers.

A Novel EEG Based Spectral Analysis of Persistent Brain Function Alteration in Athletes with Concussion History.

PubMed

Munia, Tamanna T K; Haider, Ali; Schneider, Charles; Romanick, Mark; Fazel-Rezai, Reza

2017-12-08

The neurocognitive sequelae of a sport-related concussion and its management are poorly defined. Detecting deficits are vital in making a decision about the treatment plan as it can persist one year or more following a brain injury. The reliability of traditional cognitive assessment tools is debatable, and thus attention has turned to assessments based on electroencephalogram (EEG) to evaluate subtle post-concussive alterations. In this study, we calculated neurocognitive deficits combining EEG analysis with three standard post-concussive assessment tools. Data were collected for all testing modalities from 21 adolescent athletes (seven concussive and fourteen healthy) in three different trials. For EEG assessment, along with linear frequency-based features, we introduced a set of time-frequency (Hjorth Parameters) and nonlinear features (approximate entropy and Hurst exponent) for the first time to explore post-concussive deficits. Besides traditional frequency-band analysis, we also presented a new individual frequency-based approach for EEG assessment. While EEG analysis exhibited significant discrepancies between the groups, none of the cognitive assessment resulted in significant deficits. Therefore, the evidence from the study highlights that our proposed EEG analysis and markers are more efficient at deciphering post-concussion residual neurocognitive deficits and thus has a potential clinical utility of proper concussion assessment and management.

Visualizing spatial correlation: structural and electronic orders in iron-based superconductors on atomic scale

NASA Astrophysics Data System (ADS)

Maksov, Artem; Ziatdinov, Maxim; Li, Li; Sefat, Athena; Maksymovych, Petro; Kalinin, Sergei

Crystalline matter on the nanoscale level often exhibits strongly inhomogeneous structural and electronic orders, which have a profound effect on macroscopic properties. This may be caused by subtle interplay between chemical disorder, strain, magnetic, and structural order parameters. We present a novel approach based on combination of high resolution scanning tunneling microscopy/spectroscopy (STM/S) and deep data style analysis for automatic separation, extraction, and correlation of structural and electronic behavior which might lead us to uncovering the underlying sources of inhomogeneity in in iron-based family of superconductors (FeSe, BaFe2As2) . We identify STS spectral features using physically robust Bayesian linear unmixing, and show their direct relevance to the fundamental physical properties of the system, including electronic states associated with individual defects and impurities. We collect structural data from individual unit cells on the crystalline lattice, and calculate both global and local indicators of spatial correlation with electronic features, demonstrating, for the first time, a direct quantifiable connection between observed structural order parameters extracted from the STM data and electronic order parameters identified within the STS data. This research was sponsored by the Division of Materials Sciences and Engineering, Office of Science, Basic Energy Sciences, US DOE.

Simultaneous Spectral-Spatial Feature Selection and Extraction for Hyperspectral Images.

PubMed

Zhang, Lefei; Zhang, Qian; Du, Bo; Huang, Xin; Tang, Yuan Yan; Tao, Dacheng

2018-01-01

In hyperspectral remote sensing data mining, it is important to take into account of both spectral and spatial information, such as the spectral signature, texture feature, and morphological property, to improve the performances, e.g., the image classification accuracy. In a feature representation point of view, a nature approach to handle this situation is to concatenate the spectral and spatial features into a single but high dimensional vector and then apply a certain dimension reduction technique directly on that concatenated vector before feed it into the subsequent classifier. However, multiple features from various domains definitely have different physical meanings and statistical properties, and thus such concatenation has not efficiently explore the complementary properties among different features, which should benefit for boost the feature discriminability. Furthermore, it is also difficult to interpret the transformed results of the concatenated vector. Consequently, finding a physically meaningful consensus low dimensional feature representation of original multiple features is still a challenging task. In order to address these issues, we propose a novel feature learning framework, i.e., the simultaneous spectral-spatial feature selection and extraction algorithm, for hyperspectral images spectral-spatial feature representation and classification. Specifically, the proposed method learns a latent low dimensional subspace by projecting the spectral-spatial feature into a common feature space, where the complementary information has been effectively exploited, and simultaneously, only the most significant original features have been transformed. Encouraging experimental results on three public available hyperspectral remote sensing datasets confirm that our proposed method is effective and efficient.

Spectral dependence of texture features integrated with hyperspectral data for area target classification improvement

NASA Astrophysics Data System (ADS)

Bangs, Corey F.; Kruse, Fred A.; Olsen, Chris R.

2013-05-01

Hyperspectral data were assessed to determine the effect of integrating spectral data and extracted texture feature data on classification accuracy. Four separate spectral ranges (hundreds of spectral bands total) were used from the Visible and Near Infrared (VNIR) and Shortwave Infrared (SWIR) portions of the electromagnetic spectrum. Haralick texture features (contrast, entropy, and correlation) were extracted from the average gray-level image for each of the four spectral ranges studied. A maximum likelihood classifier was trained using a set of ground truth regions of interest (ROIs) and applied separately to the spectral data, texture data, and a fused dataset containing both. Classification accuracy was measured by comparison of results to a separate verification set of test ROIs. Analysis indicates that the spectral range (source of the gray-level image) used to extract the texture feature data has a significant effect on the classification accuracy. This result applies to texture-only classifications as well as the classification of integrated spectral data and texture feature data sets. Overall classification improvement for the integrated data sets was near 1%. Individual improvement for integrated spectral and texture classification of the "Urban" class showed approximately 9% accuracy increase over spectral-only classification. Texture-only classification accuracy was highest for the "Dirt Path" class at approximately 92% for the spectral range from 947 to 1343nm. This research demonstrates the effectiveness of texture feature data for more accurate analysis of hyperspectral data and the importance of selecting the correct spectral range to be used for the gray-level image source to extract these features.

A new automated spectral feature extraction method and its application in spectral classification and defective spectra recovery

NASA Astrophysics Data System (ADS)

Wang, Ke; Guo, Ping; Luo, A.-Li

2017-03-01

Spectral feature extraction is a crucial procedure in automated spectral analysis. This procedure starts from the spectral data and produces informative and non-redundant features, facilitating the subsequent automated processing and analysis with machine-learning and data-mining techniques. In this paper, we present a new automated feature extraction method for astronomical spectra, with application in spectral classification and defective spectra recovery. The basic idea of our approach is to train a deep neural network to extract features of spectra with different levels of abstraction in different layers. The deep neural network is trained with a fast layer-wise learning algorithm in an analytical way without any iterative optimization procedure. We evaluate the performance of the proposed scheme on real-world spectral data. The results demonstrate that our method is superior regarding its comprehensive performance, and the computational cost is significantly lower than that for other methods. The proposed method can be regarded as a new valid alternative general-purpose feature extraction method for various tasks in spectral data analysis.

Investigating the Origin of Silica Occurrences on Mars through Laboratory Observations

NASA Astrophysics Data System (ADS)

Ruff, S. W.; Milliken, R. E.; Farmer, J. D.; Mills, V. W.; Robertson, K.

2012-12-01

Natural amorphous "opaline" silica is a non-crystalline, typically hydrated phase of nearly pure SiO2 that is a common product of aqueous alteration of basaltic materials [e.g., 1]. It has been identified on Mars with orbital spectral data [2] and in situ measurements from the Spirit rover [3]. On Earth, opaline silica is produced over a range of temperature, pH, and water-to-rock ratio conditions that occur in hot springs, fumaroles, volcanic exhalations, low temperature weathering, and diagenesis [e.g., 4 and references therein]. The mere identification of silica on Mars therefore does not indicate a unique geologic environment or setting. However, various attributes of a given silica occurrence can be used to narrow or perhaps uniquely define the conditions in which it formed. Field relationships, microtexture, bulk and trace element chemistry, and spectral characteristics provide clues to the geologic environment in which the silica formed. Here we focus on the opaline silica in outcrops and soil at the Home Plate feature in Gusev crater where there is good evidence for past hydrothermal processes [3]. Unresolved is whether fumaroles, hot springs, geysers, or some combination of these features were present and responsible for the emplacement of opaline silica there. Knowing the answer has implications for understanding ancient climate and habitability of Mars. We have begun an investigation involving a range of laboratory measurements on natural silica-rich samples collected from various settings in Yellowstone and Hawaii Volcanoes National Parks. Visible and near infrared (VNIR) and thermal infrared (TIR) spectral measurements are supplemented with X-ray powder diffraction, scanning electron microscopy, petrographic microscopy, and ultimately with bulk and trace element measurements. Among our emerging results: 1) both VNIR and TIR spectra can detect the presence of <2 μm silica coatings on altered basalts; 2) VNIR spectra of silica from different environments exhibit only subtle differences, likely controlled primarily by variations in water content; and 3) fumarolic silica appears to have TIR spectral characteristics distinct from hot spring silica. This last result applies to samples of basaltic rocks enriched in silica by acid-sulfate leaching from Sulfur Banks, HI, which has been suggested as an analog for the Home Plate silica [3]. TIR spectra of four samples display only a weak feature near 8 μm related to high emission angle compared to that observed in hot spring silica sinter from Yellowstone. This spectral behavior may arise from microtextural or contaminant differences between the two kinds of silica. TIR spectra of Home Plate silica display a strong 8-μm feature like those of hot spring silica. If this preliminary result survives subsequent scrutiny, it may provide additional insight into the nature of the Home Plate hydrothermal system, the first to be investigated in situ on Mars. [1] McLennan, S. M. (2003), Geology, 31, 4, 315-318, [2] Milliken, R. E., et al. (2008), Geology, 36, 11, 847-850, 10.1130/G24967A.1. [3] Squyres, S. W., et al. (2008), Science, 320, 1063-1067, [4] Ruff, S. W., et al. (2011), J. Geophys. Res., 116, E00F23, 10.1029/2010JE003767.

Invisible Colors of the Moon

NASA Image and Video Library

2009-09-24

Data from NASA Moon Mineralogy Mapper instrument on the Indian Space Research Organization Chandrayaan-1 spacecraft reveal subtle and previously unknown lunar diversity and features. Animation available at the Photojournal.

Mimas Showing False Colors #1

NASA Technical Reports Server (NTRS)

2005-01-01

False color images of Saturn's moon, Mimas, reveal variation in either the composition or texture across its surface.

During its approach to Mimas on Aug. 2, 2005, the Cassini spacecraft narrow-angle camera obtained multi-spectral views of the moon from a range of 228,000 kilometers (142,500 miles).

The image at the left is a narrow angle clear-filter image, which was separately processed to enhance the contrast in brightness and sharpness of visible features. The image at the right is a color composite of narrow-angle ultraviolet, green, infrared and clear filter images, which have been specially processed to accentuate subtle changes in the spectral properties of Mimas' surface materials. To create this view, three color images (ultraviolet, green and infrared) were combined into a single black and white picture that isolates and maps regional color differences. This 'color map' was then superimposed over the clear-filter image at the left.

The combination of color map and brightness image shows how the color differences across the Mimas surface materials are tied to geological features. Shades of blue and violet in the image at the right are used to identify surface materials that are bluer in color and have a weaker infrared brightness than average Mimas materials, which are represented by green.

Herschel crater, a 140-kilometer-wide (88-mile) impact feature with a prominent central peak, is visible in the upper right of each image. The unusual bluer materials are seen to broadly surround Herschel crater. However, the bluer material is not uniformly distributed in and around the crater. Instead, it appears to be concentrated on the outside of the crater and more to the west than to the north or south. The origin of the color differences is not yet understood. It may represent ejecta material that was excavated from inside Mimas when the Herschel impact occurred. The bluer color of these materials may be caused by subtle differences in the surface composition or the sizes of grains making up the icy soil.

The images were obtained when the Cassini spacecraft was above 25 degrees south, 134 degrees west latitude and longitude. The Sun-Mimas-spacecraft angle was 45 degrees and north is at the top.

The Cassini-Huygens mission is a cooperative project of NASA, the European Space Agency and the Italian Space Agency. The Jet Propulsion Laboratory, a division of the California Institute of Technology in Pasadena, manages the mission for NASA's Science Mission Directorate, Washington, D.C. The Cassini orbiter and its two onboard cameras were designed, developed and assembled at JPL. The imaging operations center is based at the Space Science Institute in Boulder, Colo.

For more information about the Cassini-Huygens mission visit http://saturn.jpl.nasa.gov . The Cassini imaging team homepage is at http://ciclops.org .

Geologic interpretation of Seasat SAR imagery near the Rio Lacantum, Mexico

NASA Technical Reports Server (NTRS)

Rebillard, PH.; Dixon, T.

1984-01-01

A mosaic of the Seasat Synthetic Aperture Radar (SAR) optically processed images over Central America is presented. A SAR image of the Rio Lacantum area (southeastern Mexico) has been digitally processed and its interpretation is presented. The region is characterized by low relief and a dense vegetation canopy. Surface is believed to be indicative of subsurface structural features. The Seasat-SAR system had a steep imaging geometry (incidence angle 23 + or - 3 deg off-nadir) which is favorable for detection of subtle topographic variations. Subtle textural features in the image corresponding to surface topography were enhanced by image processing techniques. A structural and lithologic interpretation of the processed images is presented. Lineaments oriented NE-SW dominate and intersect broad folds trending NW-SE. Distinctive karst topography characterizes one high relief area

Biogenic iron oxide transformation by hyperthermophiles: spectral and physiological potentials

NASA Astrophysics Data System (ADS)

Kashyap, S.; Sklute, E.; Dyar, M. D.; Holden, J. F.

2017-12-01

It is likely that any putative life in our Solar System beyond Earth, extinct or extant, is microbial. However, to detect such life, distinct organic or mineral biosignatures need to be established. Microbe-mineral interactions and mineral transformations deserve further examination in this regard. This study focused on hyperthermophilic iron oxide-reducing archaea and addressed the types of iron-oxide minerals that are favored for growth, the kinetics of such reactions, and the mineral transformations that occur depending upon the electron acceptor. Two hyperthermophilic archaea (Pyrodictium delaneyi and Pyrobaculum islandicum) and six laboratory-synthesized nanophase iron oxide minerals (2-line ferrihydrite, lepidocrocite, akaganéite, goethite, hematite and maghemite) were tested for cell growth and Fe(II) production. The mineral end-products were further characterized by examining the spectral signatures associated with these transformations using reflectance, Raman, and Mössbauer spectroscopies and electron diffraction patterns. Additionally, we critically examined how sample preparation techniques influence the end products of these transformations by comparing freeze-dried samples against those still in solution. Results showed that both organisms utilize all six nanophase iron oxides, although with varying success. The best candidates for microbial reduction were ferrihydrite, akaganéite, and lepidocrocite. The mineral transformation products and the extent of reduction varied and showed subtle differences based on organism and the type of iron oxide used. The subtle spectral differences were best characterized using combined spectroscopy techniques. This research provides new insights into microbe-mineral interactions and the discrimination of potential biosignatures in the search for life beyond Earth.

Multi-energy spectral CT: adding value in emergency body imaging.

PubMed

Punjabi, Gopal V

2018-04-01

Most vendors offer scanners capable of dual- or multi-energy computed tomography (CT) imaging. Advantages of multi-energy CT scanning include superior tissue characterization, detection of subtle iodine uptake differences, and opportunities to reduce contrast dose. However, utilization of this technology in the emergency department (ED) remains low. The purpose of this pictorial essay is to illustrate the value of multi-energy CT scanning in emergency body imaging.

Discrepancy between fluorescein angiography and optical coherence tomography in detection of macular disease.

PubMed

Kozak, Igor; Morrison, Victoria L; Clark, Thomas M; Bartsch, Dirk-Uwe; Lee, Byung Ro; Falkenstein, Iryna; Tammewar, Ajay M; Mojana, Francesca; Freeman, William R

2008-04-01

To compare high-resolution optical coherence tomography (OCT) and fluorescein angiography (FA) in detection of macular edema (ME) of various etiologies. In a retrospective study over a 12-month period at one retina center, data for consecutive eyes that had undergone simultaneous conventional FA (HRA; Heidelberg Engineering, Vista, CA) and StratusOCT (Carl Zeiss Meditec, Dublin, CA) to rule out ME were reviewed. A subset of patients underwent additional examination with extremely high-resolution (6-microm)/ultrahigh-speed spectral OCT/scanning laser ophthalmoscopy (OTI, Inc., Toronto, Ontario, Canada). Of 1,272 eyes, 1,208 (94.97%) had the finding of ME or subretinal fluid confirmed by both techniques. There were 49 eyes (3.86%) for which FA showed dye leakage in the macular area and OCT showed normal foveal contour. Of 10 eyes in this group that underwent imaging with ultrahigh-speed spectral OCT/scanning laser ophthalmoscopy, 8 had subtle diffuse lucencies in the retina. For 15 eyes (1.17%), OCT showed intraretinal and subretinal fluid, which was missed by FA. Both FA and high-resolution OCT are highly sensitive techniques and correlate well in detection of ME. However, there is a small chance that when performed alone they might miss existing subtle ME.

Subtle Sex-Role Cues in Children's Commercials.

ERIC Educational Resources Information Center

And Others; Welch, Renate L.

1979-01-01

Examines forms of communication used in commercials to convey social stereotypes. (Forms refer to production techniques such as level of action or movement, pacing, camera techniques, and auditory features.) (PD)

[The research on separating and extracting overlapping spectral feature lines in LIBS using damped least squares method].

PubMed

Wang, Yin; Zhao, Nan-jing; Liu, Wen-qing; Yu, Yang; Fang, Li; Meng, De-shuo; Hu, Li; Zhang, Da-hai; Ma, Min-jun; Xiao, Xue; Wang, Yu; Liu, Jian-guo

2015-02-01

In recent years, the technology of laser induced breakdown spectroscopy has been developed rapidly. As one kind of new material composition detection technology, laser induced breakdown spectroscopy can simultaneously detect multi elements fast and simply without any complex sample preparation and realize field, in-situ material composition detection of the sample to be tested. This kind of technology is very promising in many fields. It is very important to separate, fit and extract spectral feature lines in laser induced breakdown spectroscopy, which is the cornerstone of spectral feature recognition and subsequent elements concentrations inversion research. In order to realize effective separation, fitting and extraction of spectral feature lines in laser induced breakdown spectroscopy, the original parameters for spectral lines fitting before iteration were analyzed and determined. The spectral feature line of' chromium (Cr I : 427.480 nm) in fly ash gathered from a coal-fired power station, which was overlapped with another line(FeI: 427.176 nm), was separated from the other one and extracted by using damped least squares method. Based on Gauss-Newton iteration, damped least squares method adds damping factor to step and adjust step length dynamically according to the feedback information after each iteration, in order to prevent the iteration from diverging and make sure that the iteration could converge fast. Damped least squares method helps to obtain better results of separating, fitting and extracting spectral feature lines and give more accurate intensity values of these spectral feature lines: The spectral feature lines of chromium in samples which contain different concentrations of chromium were separated and extracted. And then, the intensity values of corresponding spectral lines were given by using damped least squares method and least squares method separately. The calibration curves were plotted, which showed the relationship between spectral line intensity values and chromium concentrations in different samples. And then their respective linear correlations were compared. The experimental results showed that the linear correlation of the intensity values of spectral feature lines and the concentrations of chromium in different samples, which was obtained by damped least squares method, was better than that one obtained by least squares method. And therefore, damped least squares method was stable, reliable and suitable for separating, fitting and extracting spectral feature lines in laser induced breakdown spectroscopy.

Detection of subtle nocturnal motor activity from 3-D accelerometry recordings in epilepsy patients.

PubMed

Nijsen, Tamara M E; Cluitmans, Pierre J M; Arends, Johan B A M; Griep, Paul A M

2007-11-01

This paper presents a first step towards reliable detection of nocturnal epileptic seizures based on 3-D accelerometry (ACM) recordings. The main goal is to distinguish between data with and without subtle nocturnal motor activity, thus reducing the amount of data that needs further (more complex) analysis for seizure detection. From 15 ACM signals (measured on five positions on the body), two features are computed, the variance and the jerk. In the resulting 2-D feature space, a linear threshold function is used for classification. For training and testing, the algorithm ACM data along with video data is used from nocturnal registrations in seven mentally retarded patients with severe epilepsy. Per patient, the algorithm detected 100% of the periods of motor activity that are marked in video recordings and the ACM signals by experts. From all the detections, 43%-89% was correct (mean =65%). We were able to reduce the amount of data that need to be analyzed considerably. The results show that our approach can be used for detection of subtle nocturnal motor activity. Furthermore, our results indicate that our algorithm is robust for fluctuations across patients. Consequently, there is no need for training the algorithm for each new patient.

Data Field Modeling and Spectral-Spatial Feature Fusion for Hyperspectral Data Classification.

PubMed

Liu, Da; Li, Jianxun

2016-12-16

Classification is a significant subject in hyperspectral remote sensing image processing. This study proposes a spectral-spatial feature fusion algorithm for the classification of hyperspectral images (HSI). Unlike existing spectral-spatial classification methods, the influences and interactions of the surroundings on each measured pixel were taken into consideration in this paper. Data field theory was employed as the mathematical realization of the field theory concept in physics, and both the spectral and spatial domains of HSI were considered as data fields. Therefore, the inherent dependency of interacting pixels was modeled. Using data field modeling, spatial and spectral features were transformed into a unified radiation form and further fused into a new feature by using a linear model. In contrast to the current spectral-spatial classification methods, which usually simply stack spectral and spatial features together, the proposed method builds the inner connection between the spectral and spatial features, and explores the hidden information that contributed to classification. Therefore, new information is included for classification. The final classification result was obtained using a random forest (RF) classifier. The proposed method was tested with the University of Pavia and Indian Pines, two well-known standard hyperspectral datasets. The experimental results demonstrate that the proposed method has higher classification accuracies than those obtained by the traditional approaches.

FOCUSR: Feature Oriented Correspondence using Spectral Regularization–A Method for Precise Surface Matching

PubMed Central

Lombaert, Herve; Grady, Leo; Polimeni, Jonathan R.; Cheriet, Farida

2013-01-01

Existing methods for surface matching are limited by the trade-off between precision and computational efficiency. Here we present an improved algorithm for dense vertex-to-vertex correspondence that uses direct matching of features defined on a surface and improves it by using spectral correspondence as a regularization. This algorithm has the speed of both feature matching and spectral matching while exhibiting greatly improved precision (distance errors of 1.4%). The method, FOCUSR, incorporates implicitly such additional features to calculate the correspondence and relies on the smoothness of the lowest-frequency harmonics of a graph Laplacian to spatially regularize the features. In its simplest form, FOCUSR is an improved spectral correspondence method that nonrigidly deforms spectral embeddings. We provide here a full realization of spectral correspondence where virtually any feature can be used as additional information using weights on graph edges, but also on graph nodes and as extra embedded coordinates. As an example, the full power of FOCUSR is demonstrated in a real case scenario with the challenging task of brain surface matching across several individuals. Our results show that combining features and regularizing them in a spectral embedding greatly improves the matching precision (to a sub-millimeter level) while performing at much greater speed than existing methods. PMID:23868776

Low-temperature and low atmospheric pressure infrared reflectance spectroscopy of Mars soil analog materials

NASA Technical Reports Server (NTRS)

Bishop, Janice L.; Pieters, Carle M.

1995-01-01

Infrared reflectance spectra of carefully selected Mars soil analog materials have been measured under low atmospheric pressures and temperatures. Chemically altered montmorillonites containing ferrihydrite and hydrated ferric sulfate complexes are examined, as well as synthetic ferrihydrite and a palagonitic soil from Haleakala, Maui. Reflectance spectra of these analog materials exhibit subtle visible to near-infrared features, which are indicative of nanophase ferric oxides or oxyhydroxides and are similar to features observed in the spectra of the bright regions of Mars. Infrared reflectance spectra of these analogs include hydration features due to structural OH, bound H2O, and adsorbed H2O. The spectral character of these hydration features is highly dependent on the sample environment and on the nature of the H2O/OH in the analogs. The behavior of the hydration features near 1.9 micron, 2.2 micron, 2.7 micron, 3 micron, and 6 microns are reported here in spectra measured under a Marslike atmospheric environment. In spectra of these analogs measured under dry Earth atmospheric conditions the 1.9-micron band depth is 8-17%; this band is much stronger under moist conditions. Under Marslike atmospheric conditions the 1.9-micron feature is broad and barely discernible (1-3% band depth) in spectra of the ferrihydrite and palagonitic soil samples. In comparable spectra of the ferric sulfate-bearing montmorillonite the 1.9-micron feature is also broad, but stronger (6% band depth). In the low atmospheric pressure and temperature spectra of the ferrihydrite-bearing montmorillonite this feature is sharper than the other analogs and relatively stronger (6% band depth). Although the intensity of the 3-micron band is weaker in spectra of each of the analogs when measured under Marslike conditions, the 3-micron band remains a dominant feature and is especially broad in spectra of the ferrihydrite and palagonitic soil. The structural OH features observed in these materials at 2.2-2.3 micron and 2.75 microns remain largely unaffected by the environmental conditions. A shift in the Christiansen feature towards shorter wavelengths has also been observed with decreasing atmospheric pressure and temperature in the midinfrared spectra of these samples.

Quantitative lithologic mapping in spectral ratio feature space - Volcanic, sedimentary and metamorphic terrains

NASA Technical Reports Server (NTRS)

Campos-Marquetti, Raul, Jr.; Rockwell, Barnaby

1990-01-01

The nature of spectral lithologic mapping is studied utilizing ratios centered around the wavelength means of TM imagery. Laboratory-derived spectra are analyzed to determine the two-dimensional relationships and distributions visible in spectral ratio feature space. The spectral distributions of various rocks and minerals in ratio feature space are found to be controlled by several spectrally dominant molecules. Three study areas were examined: Rawhide Mining District, Nevada; Manzano Mountains, New Mexico; and the Sevilleta Long Term Ecological Research site in New Mexico. It is shown that, in the comparison of two ratio plots of laboratory reflectance spectra, i.e., 0.66/0.485 micron versus 1.65/2.22 microns with those derived from TM data, several molecules spectrally dominate the reflectance characteristic of surface lithologic units. Utilizing the above ratio combination, two areas are successfully mapped based on their distribution in spectral ratio feature space.

Fine Spectral Properties of Langmuir Waves Observed Upstream of the Saturn's Bowshock by the Cassini Wideband Receiver

NASA Astrophysics Data System (ADS)

Hospodarsky, G. B.; Pisa, D.; Santolik, O.; Kurth, W. S.; Soucek, J.; Basovnik, M.; Gurnett, D. A.; Arridge, C. S.

2015-12-01

Langmuir waves are commonly observed in the upstream regions of planetary and interplanetary shock. Solar wind electrons accelerated at the shock front are reflected back into the solar wind and can form electron beams. In regions with beams, the electron distribution becomes unstable and electrostatic waves can be generated. The process of generation and the evolution of electrostatic waves strongly depends on the solar wind electron distribution and generally exhibits complex behavior. Langmuir waves can be identified as intense narrowband emission at a frequency very close to the local plasma frequency and weaker broadband waves below and above the plasma frequency deeper in the downstream region. We present a detailed study of Langmuir waves detected upstream of the Saturnian bowshock by the Cassini spacecraft. Using data from the Radio and Plasma Wave Science (RPWS), Magnetometer (MAG) and Cassini Plasma Spectrometer (CAPS) instruments we have analyzed several periods containing the extended waveform captures by the Wideband Receiver. Langmuir waves are a bursty emission highly controlled by variations in solar wind conditions. Unfortunately due to a combination of instrumental field of view and sampling period, it is often difficult to identify the electron distribution function that is unstable and able to generate Langmuir waves. We used an electrostatic version of particle-in-cell simulation of the Langmuir wave generation process to reproduce some of the more subtle observed spectral features and help understand the late stages of the instability and interactions in the solar wind plasma.

Optical maturity variation in lunar spectra as measured by Moon Mineralogy Mapper data

USGS Publications Warehouse

Nettles, J.W.; Staid, M.; Besse, S.; Boardman, J.; Clark, R.N.; Dhingra, D.; Isaacson, P.; Klima, R.; Kramer, G.; Pieters, C.M.; Taylor, L.A.

2011-01-01

High spectral and spatial resolution data from the Moon Mineralogy Mapper (M3) instrument on Chandrayaan-1 are used to investigate in detail changes in the optical properties of lunar materials accompanying space weathering. Three spectral parameters were developed and used to quantify spectral effects commonly thought to be associated with increasing optical maturity: an increase in spectral slope ("reddening"), a decrease in albedo ("darkening"), and loss of spectral contrast (decrease in absorption band depth). Small regions of study were defined that sample the ejecta deposits of small fresh craters that contain relatively crystalline (immature) material that grade into local background (mature) soils. Selected craters are small enough that they can be assumed to be of constant composition and thus are useful for evaluating trends in optical maturity. Color composites were also used to identify the most immature material in a region and show that maturity trends can also be identified using regional soil trends. The high resolution M3 data are well suited to quantifying the spectral changes that accompany space weathering and are able to capture subtle spectral variations in maturity trends. However, the spectral changes that occur as a function of maturity were observed to be dependent on local composition. Given the complexity of space weathering processes, this was not unexpected but poses challenges for absolute measures of optical maturity across diverse lunar terrains. Copyright 2011 by the American Geophysical Union.

Mapping minerals, amorphous materials, environmental materials, vegetation, water, ice and snow, and other materials: The USGS tricorder algorithm

NASA Technical Reports Server (NTRS)

Clark, Roger N.; Swayze, Gregg A.

1995-01-01

One of the challenges of Imaging Spectroscopy is the identification, mapping and abundance determination of materials, whether mineral, vegetable, or liquid, given enough spectral range, spectral resolution, signal to noise, and spatial resolution. Many materials show diagnostic absorption features in the visual and near infrared region (0.4 to 2.5 micrometers) of the spectrum. This region is covered by the modern imaging spectrometers such as AVIRIS. The challenge is to identify the materials from absorption bands in their spectra, and determine what specific analyses must be done to derive particular parameters of interest, ranging from simply identifying its presence to deriving its abundance, or determining specific chemistry of the material. Recently, a new analysis algorithm was developed that uses a digital spectral library of known materials and a fast, modified-least-squares method of determining if a single spectral feature for a given material is present. Clark et al. made another advance in the mapping algorithm: simultaneously mapping multiple minerals using multiple spectral features. This was done by a modified-least-squares fit of spectral features, from data in a digital spectral library, to corresponding spectral features in the image data. This version has now been superseded by a more comprehensive spectral analysis system called Tricorder.

CASPER: computer-aided segmentation of imperceptible motion-a learning-based tracking of an invisible needle in ultrasound.

PubMed

Beigi, Parmida; Rohling, Robert; Salcudean, Septimiu E; Ng, Gary C

2017-11-01

This paper presents a new micro-motion-based approach to track a needle in ultrasound images captured by a handheld transducer. We propose a novel learning-based framework to track a handheld needle by detecting microscale variations of motion dynamics over time. The current state of the art on using motion analysis for needle detection uses absolute motion and hence work well only when the transducer is static. We have introduced and evaluated novel spatiotemporal and spectral features, obtained from the phase image, in a self-supervised tracking framework to improve the detection accuracy in the subsequent frames using incremental training. Our proposed tracking method involves volumetric feature selection and differential flow analysis to incorporate the neighboring pixels and mitigate the effects of the subtle tremor motion of a handheld transducer. To evaluate the detection accuracy, the method is tested on porcine tissue in-vivo, during the needle insertion in the biceps femoris muscle. Experimental results show the mean, standard deviation and root-mean-square errors of [Formula: see text], [Formula: see text] and [Formula: see text] in the insertion angle, and 0.82, 1.21, 1.47 mm, in the needle tip, respectively. Compared to the appearance-based detection approaches, the proposed method is especially suitable for needles with ultrasonic characteristics that are imperceptible in the static image and to the naked eye.

Hyperspectral remote sensing image retrieval system using spectral and texture features.

PubMed

Zhang, Jing; Geng, Wenhao; Liang, Xi; Li, Jiafeng; Zhuo, Li; Zhou, Qianlan

2017-06-01

Although many content-based image retrieval systems have been developed, few studies have focused on hyperspectral remote sensing images. In this paper, a hyperspectral remote sensing image retrieval system based on spectral and texture features is proposed. The main contributions are fourfold: (1) considering the "mixed pixel" in the hyperspectral image, endmembers as spectral features are extracted by an improved automatic pixel purity index algorithm, then the texture features are extracted with the gray level co-occurrence matrix; (2) similarity measurement is designed for the hyperspectral remote sensing image retrieval system, in which the similarity of spectral features is measured with the spectral information divergence and spectral angle match mixed measurement and in which the similarity of textural features is measured with Euclidean distance; (3) considering the limited ability of the human visual system, the retrieval results are returned after synthesizing true color images based on the hyperspectral image characteristics; (4) the retrieval results are optimized by adjusting the feature weights of similarity measurements according to the user's relevance feedback. The experimental results on NASA data sets can show that our system can achieve comparable superior retrieval performance to existing hyperspectral analysis schemes.

Feature Transformation Detection Method with Best Spectral Band Selection Process for Hyper-spectral Imaging

NASA Astrophysics Data System (ADS)

Chen, Hai-Wen; McGurr, Mike; Brickhouse, Mark

2015-11-01

We present a newly developed feature transformation (FT) detection method for hyper-spectral imagery (HSI) sensors. In essence, the FT method, by transforming the original features (spectral bands) to a different feature domain, may considerably increase the statistical separation between the target and background probability density functions, and thus may significantly improve the target detection and identification performance, as evidenced by the test results in this paper. We show that by differentiating the original spectral, one can completely separate targets from the background using a single spectral band, leading to perfect detection results. In addition, we have proposed an automated best spectral band selection process with a double-threshold scheme that can rank the available spectral bands from the best to the worst for target detection. Finally, we have also proposed an automated cross-spectrum fusion process to further improve the detection performance in lower spectral range (<1000 nm) by selecting the best spectral band pair with multivariate analysis. Promising detection performance has been achieved using a small background material signature library for concept-proving, and has then been further evaluated and verified using a real background HSI scene collected by a HYDICE sensor.

Temporal variation in spectral detection thresholds of substrate and vegetation in AVIRIS images

NASA Technical Reports Server (NTRS)

Sabol, Donald E., Jr.; Roberts, Dar A.; Smith, Milton O.; Adams, John B.

1992-01-01

The ability to map changes over large surface areas over time is one of the advantages in using remote sensing as a monitoring tool. Temporal changes in the surface may be gradual, making them difficult to detect in the short-term, and because they commonly occur at the subpixel scale, they may be difficult to detect in the long-term as well. Also, subtle changes may be real or merely an artifact of image noise. It is, therefore, necessary to understand the factors that limit the detection of surface materials in evaluating temporal data. The spectral detectability of vegetation and soil in the 1990 July and October Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data of Jasper Ridge, CA was evaluated and compared.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Imara, Nia; Loeb, Abraham, E-mail: nimara@cfa.harvard.edu

Infrared emission from intergalactic dust might compromise the ability of future experiments to detect subtle spectral distortions in the Cosmic Microwave Background (CMB) from the early universe. We provide the first estimate of foreground contamination of the CMB signal due to diffuse dust emission in the intergalactic medium. We use models of the extragalactic background light to calculate the intensity of intergalactic dust emission and find that emission by intergalactic dust at z ≲ 0.5 exceeds the sensitivity of the planned Primordial Inflation Explorer to CMB spectral distortions by 1–3 orders of magnitude. In the frequency range ν = 150–2400more » GHz, we place an upper limit of 0.06% on the contribution to the far-infrared background from intergalactic dust emission.« less

Fatigue crack detection by nonlinear spectral correlation with a wideband input

NASA Astrophysics Data System (ADS)

Liu, Peipei; Sohn, Hoon

2017-04-01

Due to crack-induced nonlinearity, ultrasonic wave can distort, create accompanying harmonics, multiply waves of different frequencies, and, under resonance conditions, change resonance frequencies as a function of driving amplitude. All these nonlinear ultrasonic features have been widely studied and proved capable of detecting fatigue crack at its very early stage. However, in noisy environment, the nonlinear features might be drown in the noise, therefore it is difficult to extract those features using a conventional spectral density function. In this study, nonlinear spectral correlation is defined as a new nonlinear feature, which considers not only nonlinear modulations in ultrasonic waves but also spectral correlation between the nonlinear modulations. The proposed nonlinear feature is associated with the following two advantages: (1) stationary noise in the ultrasonic waves has little effect on nonlinear spectral correlation; and (2) the contrast of nonlinear spectral correlation between damage and intact conditions can be enhanced simply by using a wideband input. To validate the proposed nonlinear feature, micro fatigue cracks are introduced to aluminum plates by repeated tensile loading, and the experiment is conducted using surface-mounted piezoelectric transducers for ultrasonic wave generation and measurement. The experimental results confirm that the nonlinear spectral correlation can successfully detect fatigue crack with a higher sensitivity than the classical nonlinear coefficient.

Mapping Terpenes over the Teakettle Experimental Forest

NASA Astrophysics Data System (ADS)

Tycner, J.; Ustin, S.; Grigsby, S.

2015-12-01

Terpenes are a category of biogenic volatile organic compounds (BVOC) produced by many plants, most notably coniferous plants. Commonly, these terpenes are aromatic compounds. The intensity of terpene emission varies depending greatly on light and temperature. Through remote sensing data as well as ASD spectroradiometry data this study focuses on locating sources of terpene emissions in the Teakettle Experimental Forest. These emissions are of particular concern because of their influence on the chemical concentration of the lower troposphere, as well as being an indicator of tree health. A novel approach has been designed through this study in order to locate and further understand these terpene emissions. Terpenes such as camphene have been reported to have subtle spectral features located at around 1.7 μm. For the first time, a map of terpene sources has been constructed by accentuating this particular feature. A continuum interpolated band ratio (CIBR) was used in order to compute a relative abundance of terpenes from the AVIRIS data. The CIBR equation showed promise, as terpenes were most strongly concentrated in areas of coniferous vegetation (a primary source of terpenes) and were less prominent over bodies of water or industrialized areas. The greatest concentrations were focused over treetops and other woody vegetation. Although it is known that terpenes have weak absorption features in the SWIR, there is little information available regarding the mapping of terpene emissions. This project addresses a novel approach to observing biochemical components in the lower troposphere and could potentially give more information to explain the health of forest ecosystems.

Detection and mapping of mineralized areas in the Cortez-Uinta Belt, Utah-Nevada, using computer-enhanced ERTS imagery

NASA Technical Reports Server (NTRS)

Rowan, L. C. (Principal Investigator)

1976-01-01

The author has identified the following significant results. Preliminary analysis indicates that mineralogical differences between altered rocks and most unaltered rocks in south-central Nevada cause visible and near infrared spectral reflectance differences, which can be used to discriminate these broad categories of rocks in multispectral images. The most important mineralogical differences are the increased abundance of goethite, hematite, and jarosite, and the presence of alunite, montmorillonite, and kaolinite in the altered rock. The technique to enhance subtle spectral differences combines ratioing of the MSS bands and contrast stretching. The stretched ratio values are used to produce black and white images that depict materials according to spectral reflectance; rationing minimizes the influence of topography and overall albedo on the grouping of spectrally similar materials. Field evaluation of color-ratio composite shows that, excluding alluvial areas, approximately 80 percent of the green and brown color patterns are related to hydrothermal alternation. The remaining 20 percent consists mainly of pink hematitic crystallized tuff, a result of vapor phase crystallization, and of tan and red ferruginous shale and siltstone.

Classification of hyperspectral imagery with neural networks: comparison to conventional tools

NASA Astrophysics Data System (ADS)

Merényi, Erzsébet; Farrand, William H.; Taranik, James V.; Minor, Timothy B.

2014-12-01

Efficient exploitation of hyperspectral imagery is of great importance in remote sensing. Artificial intelligence approaches have been receiving favorable reviews for classification of hyperspectral data because the complexity of such data challenges the limitations of many conventional methods. Artificial neural networks (ANNs) were shown to outperform traditional classifiers in many situations. However, studies that use the full spectral dimensionality of hyperspectral images to classify a large number of surface covers are scarce if non-existent. We advocate the need for methods that can handle the full dimensionality and a large number of classes to retain the discovery potential and the ability to discriminate classes with subtle spectral differences. We demonstrate that such a method exists in the family of ANNs. We compare the maximum likelihood, Mahalonobis distance, minimum distance, spectral angle mapper, and a hybrid ANN classifier for real hyperspectral AVIRIS data, using the full spectral resolution to map 23 cover types and using a small training set. Rigorous evaluation of the classification accuracies shows that the ANN outperforms the other methods and achieves ≈90% accuracy on test data.

Documentation of procedures for textural/spatial pattern recognition techniques

NASA Technical Reports Server (NTRS)

Haralick, R. M.; Bryant, W. F.

1976-01-01

A C-130 aircraft was flown over the Sam Houston National Forest on March 21, 1973 at 10,000 feet altitude to collect multispectral scanner (MSS) data. Existing textural and spatial automatic processing techniques were used to classify the MSS imagery into specified timber categories. Several classification experiments were performed on this data using features selected from the spectral bands and a textural transform band. The results indicate that (1) spatial post-processing a classified image can cut the classification error to 1/2 or 1/3 of its initial value, (2) spatial post-processing the classified image using combined spectral and textural features produces a resulting image with less error than post-processing a classified image using only spectral features and (3) classification without spatial post processing using the combined spectral textural features tends to produce about the same error rate as a classification without spatial post processing using only spectral features.

Automated Detection of Diabetic Retinopathy using Deep Learning.

PubMed

Lam, Carson; Yi, Darvin; Guo, Margaret; Lindsey, Tony

2018-01-01

Diabetic retinopathy is a leading cause of blindness among working-age adults. Early detection of this condition is critical for good prognosis. In this paper, we demonstrate the use of convolutional neural networks (CNNs) on color fundus images for the recognition task of diabetic retinopathy staging. Our network models achieved test metric performance comparable to baseline literature results, with validation sensitivity of 95%. We additionally explored multinomial classification models, and demonstrate that errors primarily occur in the misclassification of mild disease as normal due to the CNNs inability to detect subtle disease features. We discovered that preprocessing with contrast limited adaptive histogram equalization and ensuring dataset fidelity by expert verification of class labels improves recognition of subtle features. Transfer learning on pretrained GoogLeNet and AlexNet models from ImageNet improved peak test set accuracies to 74.5%, 68.8%, and 57.2% on 2-ary, 3-ary, and 4-ary classification models, respectively.

An improved feature extraction algorithm based on KAZE for multi-spectral image

NASA Astrophysics Data System (ADS)

Yang, Jianping; Li, Jun

2018-02-01

Multi-spectral image contains abundant spectral information, which is widely used in all fields like resource exploration, meteorological observation and modern military. Image preprocessing, such as image feature extraction and matching, is indispensable while dealing with multi-spectral remote sensing image. Although the feature matching algorithm based on linear scale such as SIFT and SURF performs strong on robustness, the local accuracy cannot be guaranteed. Therefore, this paper proposes an improved KAZE algorithm, which is based on nonlinear scale, to raise the number of feature and to enhance the matching rate by using the adjusted-cosine vector. The experiment result shows that the number of feature and the matching rate of the improved KAZE are remarkably than the original KAZE algorithm.

Fractal Complexity-Based Feature Extraction Algorithm of Communication Signals

NASA Astrophysics Data System (ADS)

Wang, Hui; Li, Jingchao; Guo, Lili; Dou, Zheng; Lin, Yun; Zhou, Ruolin

How to analyze and identify the characteristics of radiation sources and estimate the threat level by means of detecting, intercepting and locating has been the central issue of electronic support in the electronic warfare, and communication signal recognition is one of the key points to solve this issue. Aiming at accurately extracting the individual characteristics of the radiation source for the increasingly complex communication electromagnetic environment, a novel feature extraction algorithm for individual characteristics of the communication radiation source based on the fractal complexity of the signal is proposed. According to the complexity of the received signal and the situation of environmental noise, use the fractal dimension characteristics of different complexity to depict the subtle characteristics of the signal to establish the characteristic database, and then identify different broadcasting station by gray relation theory system. The simulation results demonstrate that the algorithm can achieve recognition rate of 94% even in the environment with SNR of -10dB, and this provides an important theoretical basis for the accurate identification of the subtle features of the signal at low SNR in the field of information confrontation.

Classification of fresh and frozen-thawed pork muscles using visible and near infrared hyperspectral imaging and textural analysis.

PubMed

Pu, Hongbin; Sun, Da-Wen; Ma, Ji; Cheng, Jun-Hu

2015-01-01

The potential of visible and near infrared hyperspectral imaging was investigated as a rapid and nondestructive technique for classifying fresh and frozen-thawed meats by integrating critical spectral and image features extracted from hyperspectral images in the region of 400-1000 nm. Six feature wavelengths (400, 446, 477, 516, 592 and 686 nm) were identified using uninformative variable elimination and successive projections algorithm. Image textural features of the principal component images from hyperspectral images were obtained using histogram statistics (HS), gray level co-occurrence matrix (GLCM) and gray level-gradient co-occurrence matrix (GLGCM). By these spectral and textural features, probabilistic neural network (PNN) models for classification of fresh and frozen-thawed pork meats were established. Compared with the models using the optimum wavelengths only, optimum wavelengths with HS image features, and optimum wavelengths with GLCM image features, the model integrating optimum wavelengths with GLGCM gave the highest classification rate of 93.14% and 90.91% for calibration and validation sets, respectively. Results indicated that the classification accuracy can be improved by combining spectral features with textural features and the fusion of critical spectral and textural features had better potential than single spectral extraction in classifying fresh and frozen-thawed pork meat. Copyright © 2014 Elsevier Ltd. All rights reserved.

Why Are Some GCSE Examination Questions Harder to Mark Accurately than Others? Using Kelly's Repertory Grid Technique to Identify Relevant Question Features

ERIC Educational Resources Information Center

Suto, W. M. Irenka; Nadas, Rita

2009-01-01

It has long been established that marking accuracy in public examinations varies considerably among subjects and markers. This is unsurprising, given the diverse cognitive strategies that the marking process can entail, but what makes some questions harder to mark accurately than others? Are there distinct but subtle features of questions and…

Hyperspectral Features of Oil-Polluted Sea Ice and the Response to the Contamination Area Fraction

PubMed Central

Li, Ying; Liu, Chengyu; Xie, Feng

2018-01-01

Researchers have studied oil spills in open waters using remote sensors, but few have focused on extracting reflectance features of oil pollution on sea ice. An experiment was conducted on natural sea ice in Bohai Bay, China, to obtain the spectral reflectance of oil-contaminated sea ice. The spectral absorption index (SAI), spectral peak height (SPH), and wavelet detail coefficient (DWT d5) were calculated using stepwise multiple linear regression. The reflectances of some false targets were measured and analysed. The simulated false targets were sediment, iron ore fines, coal dust, and the melt pool. The measured reflectances were resampled using five common sensors (GF-2, Landsat8-OLI, Sentinel3-OLCI, MODIS, and AVIRIS). Some significant spectral features could discriminate between oil-polluted and clean sea ice. The indices correlated well with the oil area fractions. All of the adjusted R2 values exceeded 0.9. The SPH model1, based on spectral features at 507–670 and 1627–1746 nm, displayed the best fitting. The resampled data indicated that these multi-spectral and hyper-spectral sensors could be used to detect crude oil on the sea ice if the effect of noise and spatial resolution are neglected. The spectral features and their identified changes may provide reference on sensor design and band selection. PMID:29342945

A Real-Time Infrared Ultra-Spectral Signature Classification Method via Spatial Pyramid Matching

PubMed Central

Mei, Xiaoguang; Ma, Yong; Li, Chang; Fan, Fan; Huang, Jun; Ma, Jiayi

2015-01-01

The state-of-the-art ultra-spectral sensor technology brings new hope for high precision applications due to its high spectral resolution. However, it also comes with new challenges, such as the high data dimension and noise problems. In this paper, we propose a real-time method for infrared ultra-spectral signature classification via spatial pyramid matching (SPM), which includes two aspects. First, we introduce an infrared ultra-spectral signature similarity measure method via SPM, which is the foundation of the matching-based classification method. Second, we propose the classification method with reference spectral libraries, which utilizes the SPM-based similarity for the real-time infrared ultra-spectral signature classification with robustness performance. Specifically, instead of matching with each spectrum in the spectral library, our method is based on feature matching, which includes a feature library-generating phase. We calculate the SPM-based similarity between the feature of the spectrum and that of each spectrum of the reference feature library, then take the class index of the corresponding spectrum having the maximum similarity as the final result. Experimental comparisons on two publicly-available datasets demonstrate that the proposed method effectively improves the real-time classification performance and robustness to noise. PMID:26205263

Machine learning reveals cyclic changes in seismic source spectra in Geysers geothermal field.

PubMed

Holtzman, Benjamin K; Paté, Arthur; Paisley, John; Waldhauser, Felix; Repetto, Douglas

2018-05-01

The earthquake rupture process comprises complex interactions of stress, fracture, and frictional properties. New machine learning methods demonstrate great potential to reveal patterns in time-dependent spectral properties of seismic signals and enable identification of changes in faulting processes. Clustering of 46,000 earthquakes of 0.3 < M L < 1.5 from the Geysers geothermal field (CA) yields groupings that have no reservoir-scale spatial patterns but clear temporal patterns. Events with similar spectral properties repeat on annual cycles within each cluster and track changes in the water injection rates into the Geysers reservoir, indicating that changes in acoustic properties and faulting processes accompany changes in thermomechanical state. The methods open new means to identify and characterize subtle changes in seismic source properties, with applications to tectonic and geothermal seismicity.

Detection and mapping of mineralized areas in the Cortez-Uinta Belt, Utah-Nevada, using computer-enhanced ERTS imagery

NASA Technical Reports Server (NTRS)

Rowan, L. C. (Principal Investigator)

1976-01-01

The author has identified the following significant results. Mineralogical differences between hydrothermally altered rocks and most unaltered rocks in south central Nevada cause visible and near infrared (0.45-2.4 micron) spectral reflectance differences which can be used to discriminate broad categories of rocks in multispectral images. The most important mineralogical differences are the increased abundance of goethite, hematite, jarosite, alunite, montmorillonite, and kaolinite in the altered zones. Because of the wavelength positions and widths of the LANDSAT MSS bands, these spectral differences are not apparent in individual or color infrared composite MSS images. The technique developed to enhance these subtle spectral differences combines ratioing of the MSS bands and contrast stretching. Field evaluation of color-ratio composite shows that, after exclusion of alluvial areas, approximately 80% of the green and brown color patterns are related to hydrothermal alteration. The remaining 20% consists mainly of pink hematitic crystallized tuff and tan or red ferruginous shale and siltstone.

Temporal evolution of ion spectral structures during a geomagnetic storm: Observations and modeling

NASA Astrophysics Data System (ADS)

Ferradas, C.; Zhang, J.; Spence, H. E.; Kistler, L. M.; Larsen, B.; Reeves, G. D.; Skoug, R. M.; Funsten, H. O.

2016-12-01

During the last decades several missions have recorded the presence of dynamic spectral features of energetic ions in the inner magnetosphere. We present a case study of the temporal evolution of H+, He+, and O+ spectral structures throughout the geomagnetic storm of 2 October 2013. We use data from the Helium, Oxygen, Proton, and Electron (HOPE) mass spectrometer onboard Van Allen Probe A to analyze the spectral structures in the energy range of 1- 50 keV. We find that the characteristics of the ion structures follow a cyclic pattern, the observed features changing dramatically as the storm starts and then returning to its initial pre-storm state. Quiet, pre-storm times are characterized by multiple and often complex flux structures at narrow energy bands. During the storm main phase, the observed features become simple, with no nose structures or only one nose structure present in the energy-time spectrograms. As the inner magnetosphere recovers from the storm, more complex structures appear once again. Additionally, the heavy ion spectral features are generally more complex than the H+ features, with multiple noses being observed more often in the heavy ion spectra. We use a model of ion drift and losses due to charge exchange to understand the formation of the spectral features and their species dependence.

[The application of wavelet analysis of remote detection of pollution clouds].

PubMed

Zhang, J; Jiang, F

2001-08-01

The discrete wavelet transform (DWT) is used to analyse the spectra of pollution clouds in complicated environment and extract the small-features. The DWT is a time-frequency analysis technology, which detects the subtle small changes in the target spectrum. The results show that the DWT is a quite effective method to extract features of target-cloud and improve the reliability of monitoring alarm system.

Laboratory Reflectance Spectra in the Middle-infrared: Effects of Grain Size on Spectral Features

NASA Astrophysics Data System (ADS)

Le Bras, A.; Erard, S.; Fulchignoni, M.

2000-10-01

Since spectral mineral features are sensitive to surface parameters, interpretation of remote-sensing asteroids spectra in terms of mineral composition is not easy nor unique, and laboratory spectra are needed in order to understand the influence of each parameter. We developped an experimental program at IAS, using the 2.5-120 microns interferometer spectrometer, to study the influence of surface parameters on mineral features. We present here the results obtained variing the grain size. We studied grain size effects with two types of terrestrial rocks: anorthosite (bright) and basalte (dark) in the 2-40 microns range. We observed variations of the spectral contrast with grain size, shifts in wavelengths and variations of the intensity of some characteristic spectral features, and appearence of transparency features at wavelengths longer than 8 microns.

Analysis of the electrodeposition and surface chemistry of CdTe, CdSe, and CdS thin films through substrate-overlayer surface-enhanced Raman spectroscopy.

PubMed

Gu, Junsi; Fahrenkrug, Eli; Maldonado, Stephen

2014-09-02

The substrate-overlayer approach has been used to acquire surface enhanced Raman spectra (SERS) during and after electrochemical atomic layer deposition (ECALD) of CdSe, CdTe, and CdS thin films. The collected data suggest that SERS measurements performed with off-resonance (i.e. far from the surface plasmonic wavelength of the underlying SERS substrate) laser excitation do not introduce perturbations to the ECALD processes. Spectra acquired in this way afford rapid insight on the quality of the semiconductor film during the course of an ECALD process. For example, SERS data are used to highlight ECALD conditions that yield crystalline CdSe and CdS films. In contrast, SERS measurements with short wavelength laser excitation show evidence of photoelectrochemical effects that were not germane to the intended ECALD process. Using the semiconductor films prepared by ECALD, the substrate-overlayer SERS approach also affords analysis of semiconductor surface adsorbates. Specifically, Raman spectra of benzenethiol adsorbed onto CdSe, CdTe, and CdS films are detailed. Spectral shifts in the vibronic features of adsorbate bonding suggest subtle differences in substrate-adsorbate interactions, highlighting the sensitivity of this methodology.

Ultra High-Resolution Anterior Segment Optical Coherence Tomography in the Diagnosis and Management of Ocular Surface Squamous Neoplasia

PubMed Central

Thomas, Benjamin J.; Galor, Anat; Nanji, Afshan A.; Sayyad, Fouad El; Wang, Jianhua; Dubovy, Sander R.; Joag, Madhura G.; Karp, Carol L.

2014-01-01

The development of optical coherence tomography (OCT) technology has helped to usher in a new era of in vivo diagnostic imaging of the eye. The utilization of OCT for imaging of the anterior segment and ocular surface has evolved from time-domain devices to spectral-domain devices with greater penetrance and resolution, providing novel images of anterior segment pathology to assist in diagnosis and management of disease. Ocular surface squamous neoplasia (OSSN) is one such pathology that has proven demonstrable by certain anterior segment OCT machines, specifically the newer devices capable of performing ultra high-resolution OCT (UHR-OCT). Distinctive features of OSSN on high resolution OCT allow for diagnosis and differentiation from other ocular surface pathologies. Subtle findings on these images help to characterize the OSSN lesions beyond what is apparent with the clinical examination, providing guidance for clinical management. The purpose of this review is to examine the published literature on the utilization of UHR-OCT for the diagnosis and management of OSSN, as well as to report novel uses of this technology and potential directions for its future development. PMID:24439046

Spectral Characteristics of Titan's Surface

NASA Astrophysics Data System (ADS)

Griffith, Caitlin A.; Turner, Jake D.; Penteado, Paulo; Khamsi, Tymon B.; Soderblom, Jason M.

2014-11-01

Cassini/Huygens and ground-based measurements of Titan reveal an eroded surface, with lakes, dunes, and sinuous washes. These features, coupled with measurements of clouds and rain, indicate the transfer of methane between Titan’s surface and atmosphere. The presence of methane-damp lowlands suggests further that the atmospheric methane (which is continually depleted through photolysis) may be supplied by sub-surface reservoirs. The byproducts of methane photolysis condense onto the surface, leaving layers of organic sediments that record Titan’s past atmospheres.Thus knowledge of the source and history of Titan's atmosphere requires measurements of the large scale compositional makeup of Titan's surface, which is shrouded by a thick and hazy atmosphere. Towards this goal, we analyzed roughly 100,000 spectra recorded by Cassini’s Visual and Infrared Mapping Spectrometer (VIMS). Our study is confined to the latitude region (20S—20N) surrounding the landing site of the Huygens probe (at 10S, 192W), which supplied only measurement of the vertical profiles of the methane abundance and haze scattering characteristics. VIMS near-IR spectral images indicate subtle latitudinal and temporal variations in the haze characteristics in the tropics. We constrain these small changes with full radiative transfer analyses of each of the thousands of VIMS spectra, which were recorded of different terrains and at different lighting conditions. The resulting models of Titan’s atmosphere as a function of latitude and year indicate the seasonal migration of Titan’s tropical haze and enable the derivation of Titan’s surface albedo at 8 near-IR wavelength regions where Titan’s atmosphere is transparent enough to allow visibility to the surface. The resultant maps of Titan’s surface indicate a number of terrain types with distinct spectral characteristics that are suggestive of atmospheric and surficial processes, including the deposition of organic material, erosion of sediments and potential sources of methane.

Application of a two-stream radiative transfer model for leaf lignin and cellulose concentrations from spectral reflectance measurements, part 2

NASA Technical Reports Server (NTRS)

Conel, James E.; Vandenbosch, Jeannette; Grove, Cindy I.

1993-01-01

We used the Kubelka-Munk theory of diffuse spectral reflectance in layers to analyze influences of multiple chemical components in leaves. As opposed to empirical approaches to estimation of plant chemistry, the full spectral resolution of laboratory reflectance data was retained in an attempt to estimate lignin or other constituent concentrations from spectral band positions. A leaf water reflectance spectrum was derived from theoretical mixing rules, reflectance observations, and calculations from theory of intrinsic k- and s-functions. Residual reflectance bands were then isolated from spectra of fresh green leaves. These proved hard to interpret for composition in terms of simple two component mixtures such as lignin and cellulose. We next investigated spectral and dilution influences of other possible components (starch, protein). These components, among others, added to cellulose in hypothetical mixtures, produce band displacements similar to lignin, but will disguise by dilution the actual abundance of lignin present in a multicomponent system. This renders interpretation of band positions problematical. Knowledge of end-members and their spectra, and a more elaborate mixture analysis procedure may be called for. Good observational atmospheric and instrumental conditions and knowledge thereof are required for retrieval of expected subtle reflectance variations present in spectra of green vegetation.

Photoplethysmographic imaging via spectrally demultiplexed erythema fluctuation analysis for remote heart rate monitoring

NASA Astrophysics Data System (ADS)

Deglint, Jason; Chung, Audrey G.; Chwyl, Brendan; Amelard, Robert; Kazemzadeh, Farnoud; Wang, Xiao Yu; Clausi, David A.; Wong, Alexander

2016-03-01

Traditional photoplethysmographic imaging (PPGI) systems use the red, green, and blue (RGB) broadband measurements of a consumer digital camera to remotely estimate a patients heart rate; however, these broadband RGB signals are often corrupted by ambient noise, making the extraction of subtle fluctuations indicative of heart rate difficult. Therefore, the use of narrow-band spectral measurements can significantly improve the accuracy. We propose a novel digital spectral demultiplexing (DSD) method to infer narrow-band spectral information from acquired broadband RGB measurements in order to estimate heart rate via the computation of motion- compensated skin erythema fluctuation. Using high-resolution video recordings of human participants, multiple measurement locations are automatically identified on the cheeks of an individual, and motion-compensated broadband reflectance measurements are acquired at each measurement location over time via measurement location tracking. The motion-compensated broadband reflectance measurements are spectrally demultiplexed using a non-linear inverse model based on the spectral sensitivity of the camera's detector. A PPG signal is then computed from the demultiplexed narrow-band spectral information via skin erythema fluctuation analysis, with improved signal-to-noise ratio allowing for reliable remote heart rate measurements. To assess the effectiveness of the proposed system, a set of experiments involving human motion in a front-facing position were performed under ambient lighting conditions. Experimental results indicate that the proposed system achieves robust and accurate heart rate measurements and can provide additional information about the participant beyond the capabilities of traditional PPGI methods.

Scattering and absorption measurements of cervical tissues measures using low cost multi-spectral imaging

NASA Astrophysics Data System (ADS)

Bernat, Amir S.; Bar-Am, Kfir; Cataldo, Leigh; Bolton, Frank J.; Kahn, Bruce S.; Levitz, David

2018-02-01

Cervical cancer is a leading cause of death for women in low resource settings. In order to better detect cervical dysplasia, a low cost multi-spectral colposcope was developed utilizing low costs LEDs and an area scan camera. The device is capable of both traditional colposcopic imaging and multi-spectral image capture. Following initial bench testing, the device was deployed to a gynecology clinic where it was used to image patients in a colposcopy setting. Both traditional colposcopic images and spectral data from patients were uploaded to a cloud server for remote analysis. Multi-spectral imaging ( 30 second capture) took place before any clinical procedure; the standard of care was followed thereafter. If acetic acid was used in the standard of care, a post-acetowhitening colposcopic image was also captured. In analyzing the data, normal and abnormal regions were identified in the colposcopic images by an expert clinician. Spectral data were fit to a theoretical model based on diffusion theory, yielding information on scattering and absorption parameters. Data were grouped according to clinician labeling of the tissue, as well as any additional clinical test results available (Pap, HPV, biopsy). Altogether, N=20 patients were imaged in this study, with 9 of them abnormal. In comparing normal and abnormal regions of interest from patients, substantial differences were measured in blood content, while differences in oxygen saturation parameters were more subtle. These results suggest that optical measurements made using low cost spectral imaging systems can distinguish between normal and pathological tissues.

Forest tree species clssification based on airborne hyper-spectral imagery

NASA Astrophysics Data System (ADS)

Dian, Yuanyong; Li, Zengyuan; Pang, Yong

2013-10-01

Forest precision classification products were the basic data for surveying of forest resource, updating forest subplot information, logging and design of forest. However, due to the diversity of stand structure, complexity of the forest growth environment, it's difficult to discriminate forest tree species using multi-spectral image. The airborne hyperspectral images can achieve the high spatial and spectral resolution imagery of forest canopy, so it will good for tree species level classification. The aim of this paper was to test the effective of combining spatial and spectral features in airborne hyper-spectral image classification. The CASI hyper spectral image data were acquired from Liangshui natural reserves area. Firstly, we use the MNF (minimum noise fraction) transform method for to reduce the hyperspectral image dimensionality and highlighting variation. And secondly, we use the grey level co-occurrence matrix (GLCM) to extract the texture features of forest tree canopy from the hyper-spectral image, and thirdly we fused the texture and the spectral features of forest canopy to classify the trees species using support vector machine (SVM) with different kernel functions. The results showed that when using the SVM classifier, MNF and texture-based features combined with linear kernel function can achieve the best overall accuracy which was 85.92%. It was also confirm that combine the spatial and spectral information can improve the accuracy of tree species classification.

Stacked sparse autoencoder in hyperspectral data classification using spectral-spatial, higher order statistics and multifractal spectrum features

NASA Astrophysics Data System (ADS)

Wan, Xiaoqing; Zhao, Chunhui; Wang, Yanchun; Liu, Wu

2017-11-01

This paper proposes a novel classification paradigm for hyperspectral image (HSI) using feature-level fusion and deep learning-based methodologies. Operation is carried out in three main steps. First, during a pre-processing stage, wave atoms are introduced into bilateral filter to smooth HSI, and this strategy can effectively attenuate noise and restore texture information. Meanwhile, high quality spectral-spatial features can be extracted from HSI by taking geometric closeness and photometric similarity among pixels into consideration simultaneously. Second, higher order statistics techniques are firstly introduced into hyperspectral data classification to characterize the phase correlations of spectral curves. Third, multifractal spectrum features are extracted to characterize the singularities and self-similarities of spectra shapes. To this end, a feature-level fusion is applied to the extracted spectral-spatial features along with higher order statistics and multifractal spectrum features. Finally, stacked sparse autoencoder is utilized to learn more abstract and invariant high-level features from the multiple feature sets, and then random forest classifier is employed to perform supervised fine-tuning and classification. Experimental results on two real hyperspectral data sets demonstrate that the proposed method outperforms some traditional alternatives.

Spectral feature measurements and analyses of the East Lake

NASA Astrophysics Data System (ADS)

Fang, Shenghui; Zhou, Yuan; Zhu, Wu

2005-10-01

It is one of basis of water color remote sensing to investigate the method to obtain and analyze the spectral features of the water bodies. This paper concerns the above-water method for the spectral measurements of inland water. A series of experiments were taken in areas of the East Lake with the EPP2000CCD radiometer, and the geometry attitude of the observation and the method of the elimination of the noise of the water Signals will be discussed. The method of the above-water spectral measurements was studied from the point of view of error source. On the basis of the experiments of the water depth and the observing direction form the sun and surface, it is suggested to remove the radiances of the whitecaps, surface-reflected sun glint and skylight which have not the spectral features of water from the lake surface by specialized observing attitude and data processing. At last, a suit of methods is concluded for the water body of the East Lake in measuring and analyzing the spectral features from above-water.

Neural representations of emotion are organized around abstract event features.

PubMed

Skerry, Amy E; Saxe, Rebecca

2015-08-03

Research on emotion attribution has tended to focus on the perception of overt expressions of at most five or six basic emotions. However, our ability to identify others' emotional states is not limited to perception of these canonical expressions. Instead, we make fine-grained inferences about what others feel based on the situations they encounter, relying on knowledge of the eliciting conditions for different emotions. In the present research, we provide convergent behavioral and neural evidence concerning the representations underlying these concepts. First, we find that patterns of activity in mentalizing regions contain information about subtle emotional distinctions conveyed through verbal descriptions of eliciting situations. Second, we identify a space of abstract situation features that well captures the emotion discriminations subjects make behaviorally and show that this feature space outperforms competing models in capturing the similarity space of neural patterns in these regions. Together, the data suggest that our knowledge of others' emotions is abstract and high dimensional, that brain regions selective for mental state reasoning support relatively subtle distinctions between emotion concepts, and that the neural representations in these regions are not reducible to more primitive affective dimensions such as valence and arousal. Copyright © 2015 Elsevier Ltd. All rights reserved.

An Energy-Based Approach for Detection and Characterization of Subtle Entities Within Laser Scanning Point-Clouds

NASA Astrophysics Data System (ADS)

Arav, Reuma; Filin, Sagi

2016-06-01

Airborne laser scans present an optimal tool to describe geomorphological features in natural environments. However, a challenge arises in the detection of such phenomena, as they are embedded in the topography, tend to blend into their surroundings and leave only a subtle signature within the data. Most object-recognition studies address mainly urban environments and follow a general pipeline where the data are partitioned into segments with uniform properties. These approaches are restricted to man-made domain and are capable to handle limited features that answer a well-defined geometric form. As natural environments present a more complex set of features, the common interpretation of the data is still manual at large. In this paper, we propose a data-aware detection scheme, unbound to specific domains or shapes. We define the recognition question as an energy optimization problem, solved by variational means. Our approach, based on the level-set method, characterizes geometrically local surfaces within the data, and uses these characteristics as potential field for minimization. The main advantage here is that it allows topological changes of the evolving curves, such as merging and breaking. We demonstrate the proposed methodology on the detection of collapse sinkholes.

Neural Representations of Emotion Are Organized around Abstract Event Features

PubMed Central

Skerry, Amy E.; Saxe, Rebecca

2016-01-01

Summary Research on emotion attribution has tended to focus on the perception of overt expressions of at most five or six basic emotions. However, our ability to identify others' emotional states is not limited to perception of these canonical expressions. Instead, we make fine-grained inferences about what others feel based on the situations they encounter, relying on knowledge of the eliciting conditions for different emotions. In the present research, we provide convergent behavioral and neural evidence concerning the representations underlying these concepts. First, we find that patterns of activity in mentalizing regions contain information about subtle emotional distinctions conveyed through verbal descriptions of eliciting situations. Second, we identify a space of abstract situation features that well captures the emotion discriminations subjects make behaviorally and show that this feature space outperforms competing models in capturing the similarity space of neural patterns in these regions. Together, the data suggest that our knowledge of others' emotions is abstract and high dimensional, that brain regions selective for mental state reasoning support relatively subtle distinctions between emotion concepts, and that the neural representations in these regions are not reducible to more primitive affective dimensions such as valence and arousal. PMID:26212878

VizieR Online Data Catalog: Berkeley supernova Ia program. II. (Silverman+, 2012)

NASA Astrophysics Data System (ADS)

Silverman, J. M.; Kong, J. J.; Filippenko, A. V.

2013-08-01

In this second paper in a series, we present measurements of spectral features of 432 low-redshift (z<0.1) optical spectra of 261 Type Ia supernovae (SNe Ia) within 20d of maximum brightness. The data were obtained from 1989 to the end of 2008 as part of the Berkeley Supernova Ia Program (BSNIP) and are presented in BSNIP I by Silverman et al. (J/MNRAS/425/1789). We describe in detail our method of automated, robust spectral feature definition and measurement which expands upon similar previous studies. Using this procedure, we attempt to measure expansion velocities, pseudo-equivalent widths (pEWs), spectral feature depths and fluxes at the centre and endpoints of each of nine major spectral feature complexes. (10 data files).

Population Distribution Analyses Reveal a Hierarchy of Molecular Players Underlying Parallel Endocytic Pathways

PubMed Central

Gupta, Gagan D.; Howes, Mark T.; Chandran, Ruma; Das, Anupam; Menon, Sindhu; Parton, Robert G.; Sowdhamini, R.; Thattai, Mukund; Mayor, Satyajit

2014-01-01

Single-cell-resolved measurements reveal heterogeneous distributions of clathrin-dependent (CD) and -independent (CLIC/GEEC: CG) endocytic activity in Drosophila cell populations. dsRNA-mediated knockdown of core versus peripheral endocytic machinery induces strong changes in the mean, or subtle changes in the shapes of these distributions, respectively. By quantifying these subtle shape changes for 27 single-cell features which report on endocytic activity and cell morphology, we organize 1072 Drosophila genes into a tree-like hierarchy. We find that tree nodes contain gene sets enriched in functional classes and protein complexes, providing a portrait of core and peripheral control of CD and CG endocytosis. For 470 genes we obtain additional features from separate assays and classify them into early- or late-acting genes of the endocytic pathways. Detailed analyses of specific genes at intermediate levels of the tree suggest that Vacuolar ATPase and lysosomal genes involved in vacuolar biogenesis play an evolutionarily conserved role in CG endocytosis. PMID:24971745

Multi range spectral feature fitting for hyperspectral imagery in extracting oilseed rape planting area

NASA Astrophysics Data System (ADS)

Pan, Zhuokun; Huang, Jingfeng; Wang, Fumin

2013-12-01

Spectral feature fitting (SFF) is a commonly used strategy for hyperspectral imagery analysis to discriminate ground targets. Compared to other image analysis techniques, SFF does not secure higher accuracy in extracting image information in all circumstances. Multi range spectral feature fitting (MRSFF) from ENVI software allows user to focus on those interesting spectral features to yield better performance. Thus spectral wavelength ranges and their corresponding weights must be determined. The purpose of this article is to demonstrate the performance of MRSFF in oilseed rape planting area extraction. A practical method for defining the weighted values, the variance coefficient weight method, was proposed to set up criterion. Oilseed rape field canopy spectra from the whole growth stage were collected prior to investigating its phenological varieties; oilseed rape endmember spectra were extracted from the Hyperion image as identifying samples to be used in analyzing the oilseed rape field. Wavelength range divisions were determined by the difference between field-measured spectra and image spectra, and image spectral variance coefficient weights for each wavelength range were calculated corresponding to field-measured spectra from the closest date. By using MRSFF, wavelength ranges were classified to characterize the target's spectral features without compromising spectral profile's entirety. The analysis was substantially successful in extracting oilseed rape planting areas (RMSE ≤ 0.06), and the RMSE histogram indicated a superior result compared to a conventional SFF. Accuracy assessment was based on the mapping result compared with spectral angle mapping (SAM) and the normalized difference vegetation index (NDVI). The MRSFF yielded a robust, convincible result and, therefore, may further the use of hyperspectral imagery in precision agriculture.

Machine learning reveals cyclic changes in seismic source spectra in Geysers geothermal field

PubMed Central

Paisley, John

2018-01-01

The earthquake rupture process comprises complex interactions of stress, fracture, and frictional properties. New machine learning methods demonstrate great potential to reveal patterns in time-dependent spectral properties of seismic signals and enable identification of changes in faulting processes. Clustering of 46,000 earthquakes of 0.3 < ML < 1.5 from the Geysers geothermal field (CA) yields groupings that have no reservoir-scale spatial patterns but clear temporal patterns. Events with similar spectral properties repeat on annual cycles within each cluster and track changes in the water injection rates into the Geysers reservoir, indicating that changes in acoustic properties and faulting processes accompany changes in thermomechanical state. The methods open new means to identify and characterize subtle changes in seismic source properties, with applications to tectonic and geothermal seismicity. PMID:29806015

Thermal Infrared Spectral Band Detection Limits for Unidentified Surface Materials

NASA Technical Reports Server (NTRS)

Kirkland, Laurel E.; Herr, Kenneth C.; Salisbury, John W.

2001-01-01

Infrared emission spectra recorded by airborne or satellite spectrometers can be searched for spectral features to determine the composition of rocks on planetary surfaces. Surface materials are identified by detections of characteristic spectral bands. We show how to define whether to accept an observed spectral feature as a detection when the target material is unknown. We also use remotely sensed spectra measured by the Thermal Emission Spectrometer (TES) and the Spatially Enhanced Broadband Array Spectrograph System to illustrate the importance of instrument parameters and surface properties on band detection limits and how the variation in signal-to-noise ratio with wavelength affects the bands that are most detectable for a given instrument. The spectrometer's sampling interval, spectral resolution, signal-to-noise ratio as a function of wavelength, and the sample's surface properties influence whether the instrument can detect a spectral feature exhibited by a material. As an example, in the 6-13 micrometer wavelength region, massive carbonates exhibit two bands: a very strong, broad feature at approximately 6.5 micrometers and a less intense, sharper band at approximately 11.25 micrometers. Although the 6.5-micrometer band is stronger and broader in laboratory-measured spectra, the 11.25-micrometer band will cause a more detectable feature in TES spectra.

Optical filter for highlighting spectral features part I: design and development of the filter for discrimination of human skin with and without an application of cosmetic foundation.

PubMed

Nishino, Ken; Nakamura, Mutsuko; Matsumoto, Masayuki; Tanno, Osamu; Nakauchi, Shigeki

2011-03-28

Light reflected from an object's surface contains much information about its physical and chemical properties. Changes in the physical properties of an object are barely detectable in spectra. Conventional trichromatic systems, on the other hand, cannot detect most spectral features because spectral information is compressively represented as trichromatic signals forming a three-dimensional subspace. We propose a method for designing a filter that optically modulates a camera's spectral sensitivity to find an alternative subspace highlighting an object's spectral features more effectively than the original trichromatic space. We designed and developed a filter that detects cosmetic foundations on human face. Results confirmed that the filter can visualize and nondestructively inspect the foundation distribution.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Foxley, Sean, E-mail: sean.foxley@ndcn.ox.ac.uk; Karczmar, Gregory S.; Domowicz, Miriam

Purpose: Widely used MRI methods show brain morphology both in vivo and ex vivo at very high resolution. Many of these methods (e.g., T{sub 2}{sup *}-weighted imaging, phase-sensitive imaging, or susceptibility-weighted imaging) are sensitive to local magnetic susceptibility gradients produced by subtle variations in tissue composition. However, the spectral resolution of commonly used methods is limited to maintain reasonable run-time combined with very high spatial resolution. Here, the authors report on data acquisition at increased spectral resolution, with 3-dimensional high spectral and spatial resolution MRI, in order to analyze subtle variations in water proton resonance frequency and lineshape that reflectmore » local anatomy. The resulting information compliments previous studies based on T{sub 2}{sup *} and resonance frequency. Methods: The proton free induction decay was sampled at high resolution and Fourier transformed to produce a high-resolution water spectrum for each image voxel in a 3D volume. Data were acquired using a multigradient echo pulse sequence (i.e., echo-planar spectroscopic imaging) with a spatial resolution of 50 × 50 × 70 μm{sup 3} and spectral resolution of 3.5 Hz. Data were analyzed in the spectral domain, and images were produced from the various Fourier components of the water resonance. This allowed precise measurement of local variations in water resonance frequency and lineshape, at the expense of significantly increased run time (16–24 h). Results: High contrast T{sub 2}{sup *}-weighted images were produced from the peak of the water resonance (peak height image), revealing a high degree of anatomical detail, specifically in the hippocampus and cerebellum. In images produced from Fourier components of the water resonance at −7.0 Hz from the peak, the contrast between deep white matter tracts and the surrounding tissue is the reverse of the contrast in water peak height images. This indicates the presence of a shoulder in the water resonance that is not present at +7.0 Hz and may be specific to white matter anatomy. Moreover, a frequency shift of 6.76 ± 0.55 Hz was measured between the molecular and granular layers of the cerebellum. This shift is demonstrated in corresponding spectra; water peaks from voxels in the molecular and granular layers are consistently 2 bins apart (7.0 Hz, as dictated by the spectral resolution) from one another. Conclusions: High spectral and spatial resolution MR imaging has the potential to accurately measure the changes in the water resonance in small voxels. This information can guide optimization and interpretation of more commonly used, more rapid imaging methods that depend on image contrast produced by local susceptibility gradients. In addition, with improved sampling methods, high spectral and spatial resolution data could be acquired in reasonable run times, and used for in vivo scans to increase sensitivity to variations in local susceptibility.« less

A Spectral Method for Color Quantitation of a Protein Drug Solution.

PubMed

Swartz, Trevor E; Yin, Jian; Patapoff, Thomas W; Horst, Travis; Skieresz, Susan M; Leggett, Gordon; Morgan, Charles J; Rahimi, Kimia; Marhoul, Joseph; Kabakoff, Bruce

2016-01-01

Color is an important quality attribute for biotherapeutics. In the biotechnology industry, a visual method is most commonly utilized for color characterization of liquid drug protein solutions. The color testing method is used for both batch release and on stability testing for quality control. Using that method, an analyst visually determines the color of the sample by choosing the closest matching European Pharmacopeia reference color solution. The requirement to judge the best match makes it a subjective method. Furthermore, the visual method does not capture data on hue or chroma that would allow for improved product characterization and the ability to detect subtle differences between samples. To overcome these challenges, we describe a quantitative method for color determination that greatly reduces the variability in measuring color and allows for a more precise understanding of color differences. Following color industry standards established by International Commission on Illumination, this method converts a protein solution's visible absorption spectra to L*a*b* color space. Color matching is achieved within the L*a*b* color space, a practice that is already widely used in other industries. The work performed here is to facilitate the adoption and transition for the traditional visual assessment method to a quantitative spectral method. We describe here the algorithm used such that the quantitative spectral method correlates with the currently used visual method. In addition, we provide the L*a*b* values for the European Pharmacopeia reference color solutions required for the quantitative method. We have determined these L*a*b* values by gravimetrically preparing and measuring multiple lots of the reference color solutions. We demonstrate that the visual assessment and the quantitative spectral method are comparable using both low- and high-concentration antibody solutions and solutions with varying turbidity. In the biotechnology industry, a visual assessment is the most commonly used method for color characterization, batch release, and stability testing of liquid protein drug solutions. Using this method, an analyst visually determines the color of the sample by choosing the closest match to a standard color series. This visual method can be subjective because it requires an analyst to make a judgment of the best match of color of the sample to the standard color series, and it does not capture data on hue and chroma that would allow for improved product characterization and the ability to detect subtle differences between samples. To overcome these challenges, we developed a quantitative spectral method for color determination that greatly reduces the variability in measuring color and allows for a more precise understanding of color differences. The details of the spectral quantitative method are described. A comparison between the visual assessment method and spectral quantitative method is presented. This study supports the transition to a quantitative spectral method from the visual assessment method for quality testing of protein solutions. © PDA, Inc. 2016.

Spectral feature design in high dimensional multispectral data

NASA Technical Reports Server (NTRS)

Chen, Chih-Chien Thomas; Landgrebe, David A.

1988-01-01

The High resolution Imaging Spectrometer (HIRIS) is designed to acquire images simultaneously in 192 spectral bands in the 0.4 to 2.5 micrometers wavelength region. It will make possible the collection of essentially continuous reflectance spectra at a spectral resolution sufficient to extract significantly enhanced amounts of information from return signals as compared to existing systems. The advantages of such high dimensional data come at a cost of increased system and data complexity. For example, since the finer the spectral resolution, the higher the data rate, it becomes impractical to design the sensor to be operated continuously. It is essential to find new ways to preprocess the data which reduce the data rate while at the same time maintaining the information content of the high dimensional signal produced. Four spectral feature design techniques are developed from the Weighted Karhunen-Loeve Transforms: (1) non-overlapping band feature selection algorithm; (2) overlapping band feature selection algorithm; (3) Walsh function approach; and (4) infinite clipped optimal function approach. The infinite clipped optimal function approach is chosen since the features are easiest to find and their classification performance is the best. After the preprocessed data has been received at the ground station, canonical analysis is further used to find the best set of features under the criterion that maximal class separability is achieved. Both 100 dimensional vegetation data and 200 dimensional soil data were used to test the spectral feature design system. It was shown that the infinite clipped versions of the first 16 optimal features had excellent classification performance. The overall probability of correct classification is over 90 percent while providing for a reduced downlink data rate by a factor of 10.

Subtle imitation behaviour in convenience samples of normal, demented, and currently depressed elderly subjects.

PubMed

von Gunten, Armin; Duc, René

2007-06-01

The clinical significance of imitation behaviour (IB) is unclear. The aim of this study was to investigate the prevalence of subtle naïve and obstinate IB in convenience samples of normal elderly, demented, and depressed subjects. Subtle IB was assessed using a protocol constructed ad hoc in 146 patients, consecutively referred to a memory clinic having received an ICD-10 diagnosis of either dementia or depression, and in 241 healthy subjects. The prevalence of IB in the three groups was determined and the association with possible demographic, cognitive, and non-cognitive variables analysed. Subtle naïve IB was frequent in the elderly with dementia, intermediate in the depressed, and rare in the normal elderly except that the latter frequently stretched out their arms. Obstinate IB never occurred in the normal elderly. IB was predicted by none of the variables used. The groups included were convenience samples with the depressed being a small group precluding further distinction of depressive subtypes. Although naïve IB is a frequent clinical feature in the demented, it also accompanies depressive disorders in the elderly. It can be observed as context-specific IB in the normal elderly. Obstinate IB does not occur in the normal elderly. Copyright 2006 John Wiley & Sons, Ltd.

Neuropsychological Features of Dyslexia.

ERIC Educational Resources Information Center

Feifer, Steven G.

This literature review provides support for the idea that subtle anatomical and functional deviations in the brain correlate with specific types of reading disorders. It finds evidence that symmetry or reversed asymmetry in the plana temporale may be associated with difficulty in acquiring sound/symbol relationships. Studies are reported to show…

Developmental Regression in Autism Spectrum Disorders

ERIC Educational Resources Information Center

Rogers, Sally J.

2004-01-01

The occurrence of developmental regression in autism is one of the more puzzling features of this disorder. Although several studies have documented the validity of parental reports of regression using home videos, accumulating data suggest that most children who demonstrate regression also demonstrated previous, subtle, developmental differences.…

Stratified Mucin-Producing Intraepithelial Lesion of the Cervix: Subtle Features Not to Be Missed.

PubMed

Schwock, Joerg; Ko, Hyang Mi; Dubé, Valérie; Rouzbahman, Marjan; Cesari, Matthew; Ghorab, Zeina; Geddie, William R

2016-01-01

Stratified mucin-producing intraepithelial lesion (SMILE) is an uncommon premalignant lesion of the uterine cervix. A detailed examination of preinvasive SMILE cases including a comparison of the cytologic features with usual-type adenocarcinoma in situ (AIS) and human papillomavirus (HPV) genotyping was performed. Excisions and preceding Papanicolaou (Pap) tests were retrieved from the files of 2 tertiary care centers. Histologic review estimated the lesional SMILE proportion. Pap tests were reviewed and assessed for architectural, cellular and background features. Cobas® HPV test was performed. 13 cases were identified. Mean/median patient age was 35/33 years (range 23-51 years). Concurrent high-grade squamous intraepithelial lesion was found in 10/13 (77%) and AIS in 8/13 (62%) cases. In 6 cases, SMILE was dominant (≥50%) and represented in 5/6 corresponding Pap tests. Cytology interpretations differed more often in the SMILE-dominant group (p < 0.05). SMILE and AIS had overlapping features. Feathering and prominent nucleoli were absent in SMILE. HPV DNA was detected in all 12 cases tested. HPV 18 was most common (7/12). Excisions with positive/suspicious margins were reported in 5/6 SMILE-dominant versus 3/7 nondominant cases. SMILE is best considered as an AIS variant for cytologic, etiologic and management purposes. Cytologic features overlap with AIS, but are more subtle and easily missed. HPV testing may play a role in facilitating SMILE detection. © 2016 S. Karger AG, Basel.

Assessing the performance of multiple spectral-spatial features of a hyperspectral image for classification of urban land cover classes using support vector machines and artificial neural network

NASA Astrophysics Data System (ADS)

Pullanagari, Reddy; Kereszturi, Gábor; Yule, Ian J.; Ghamisi, Pedram

2017-04-01

Accurate and spatially detailed mapping of complex urban environments is essential for land managers. Classifying high spectral and spatial resolution hyperspectral images is a challenging task because of its data abundance and computational complexity. Approaches with a combination of spectral and spatial information in a single classification framework have attracted special attention because of their potential to improve the classification accuracy. We extracted multiple features from spectral and spatial domains of hyperspectral images and evaluated them with two supervised classification algorithms; support vector machines (SVM) and an artificial neural network. The spatial features considered are produced by a gray level co-occurrence matrix and extended multiattribute profiles. All of these features were stacked, and the most informative features were selected using a genetic algorithm-based SVM. After selecting the most informative features, the classification model was integrated with a segmentation map derived using a hidden Markov random field. We tested the proposed method on a real application of a hyperspectral image acquired from AisaFENIX and on widely used hyperspectral images. From the results, it can be concluded that the proposed framework significantly improves the results with different spectral and spatial resolutions over different instrumentation.

MindDigger: Feature Identification and Opinion Association for Chinese Movie Reviews

NASA Astrophysics Data System (ADS)

Zhao, Lili; Li, Chunping

In this paper, we present a prototype system called MindDigger, which can be used to analyze the opinions in Chinese movie reviews. Different from previous research that employed techniques on product reviews, we focus on Chinese movie reviews, in which opinions are expressed in subtle and varied ways. The system designed in this work aims to extract the opinion expressions and assign them to the corresponding features. The core tasks include feature and opinion extraction, and feature-opinion association. To deal with Chinese effectively, several novel approaches based on syntactic analysis are proposed in this paper. Running results show the performance is satisfactory.

Hyperspectral image classification by a variable interval spectral average and spectral curve matching combined algorithm

NASA Astrophysics Data System (ADS)

Senthil Kumar, A.; Keerthi, V.; Manjunath, A. S.; Werff, Harald van der; Meer, Freek van der

2010-08-01

Classification of hyperspectral images has been receiving considerable attention with many new applications reported from commercial and military sectors. Hyperspectral images are composed of a large number of spectral channels, and have the potential to deliver a great deal of information about a remotely sensed scene. However, in addition to high dimensionality, hyperspectral image classification is compounded with a coarse ground pixel size of the sensor for want of adequate sensor signal to noise ratio within a fine spectral passband. This makes multiple ground features jointly occupying a single pixel. Spectral mixture analysis typically begins with pixel classification with spectral matching techniques, followed by the use of spectral unmixing algorithms for estimating endmembers abundance values in the pixel. The spectral matching techniques are analogous to supervised pattern recognition approaches, and try to estimate some similarity between spectral signatures of the pixel and reference target. In this paper, we propose a spectral matching approach by combining two schemes—variable interval spectral average (VISA) method and spectral curve matching (SCM) method. The VISA method helps to detect transient spectral features at different scales of spectral windows, while the SCM method finds a match between these features of the pixel and one of library spectra by least square fitting. Here we also compare the performance of the combined algorithm with other spectral matching techniques using a simulated and the AVIRIS hyperspectral data sets. Our results indicate that the proposed combination technique exhibits a stronger performance over the other methods in the classification of both the pure and mixed class pixels simultaneously.

Fake/Bogus Conferences: Their Features and Some Subtle Ways to Differentiate Them from Real Ones.

PubMed

Asadi, Amin; Rahbar, Nader; Rezvani, Mohammad Javad; Asadi, Fahime

2018-04-01

The main objective of the present paper is to introduce some features of fake/bogus conferences and some viable approaches to differentiate them from the real ones. These fake/bogus conferences introduce themselves as international conferences, which are multidisciplinary and indexed in major scientific digital libraries. Furthermore, most of the fake/bogus conference holders offer publishing the accepted papers in ISI journals and use other techniques in their advertisement e-mails.

Vesta's UV Lightcurve: Hemispheric Variation in Brightness and Spectral Reversal

NASA Technical Reports Server (NTRS)

Hendrix, Amanda R.; Vilas, Faith; Festou, Michael

2003-01-01

Spectra of asteroid 4 Vesta obtained in October 1990 with the International Ultraviolet Explorer are reanalyzed and reinterpreted. A large portion of the eastern hemisphere (based on the prime meridian definition of Thomas et al., 1997a) is darker at UV Wavelengths than much of the western hemisphere. The UV lightcurve is in contrast with the visible lightcurve, which shows that the eastern hemisphere is brighter than the western. These IUE spectra of Vesta thus may be evidence for the "spectral reversal." first seen on the Moon by Apollo 17. where the visibly brighter lunar highlands are darker than the maria at far-UV wavelengths. This effect was linked to space weathering when it was noted (Wagner et al., 1987) that the spectral reversal appears in the laboratory spectra of lunar soils but not powdered lunar rocks. We investigate Vesta's UV lightcurve and spectral reversal, and its possible connection with space weathering. The addition to grain coatings of small amounts of submicroscopic iron (SMFe) through vapor deposition causes drastic spectral changes at UV-visible wavelengths (Hapke, 2001). while the longer wavelength spectrum remains largely unaffected. Other laboratory results (e.g., Hiroi and Pieters, 1998) indicate that the UV-visible wavelength range is affected by simulated weathering processes in a manner similar to what is seen on Vesta. It is likely that Vesta has experienced relatively minor amounts of space weathering, as indicated by the spectral reversal, along with the subtle visible-near infrared weathering effects (e.g., Binzel et al., 1997).

Chemometric Analysis of Gas Chromatography – Mass Spectrometry Data using Fast Retention Time Alignment via a Total Ion Current Shift Function

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nadeau, Jeremy S.; Wright, Bob W.; Synovec, Robert E.

2010-04-15

A critical comparison of methods for correcting severely retention time shifted gas chromatography-mass spectrometry (GC-MS) data is presented. The method reported herein is an adaptation to the Piecewise Alignment Algorithm to quickly align severely shifted one-dimensional (1D) total ion current (TIC) data, then applying these shifts to broadly align all mass channels throughout the separation, referred to as a TIC shift function (SF). The maximum shift varied from (-) 5 s in the beginning of the chromatographic separation to (+) 20 s toward the end of the separation, equivalent to a maximum shift of over 5 peak widths. Implementing themore » TIC shift function (TIC SF) prior to Fisher Ratio (F-Ratio) feature selection and then principal component analysis (PCA) was found to be a viable approach to classify complex chromatograms, that in this study were obtained from GC-MS separations of three gasoline samples serving as complex test mixtures, referred to as types C, M and S. The reported alignment algorithm via the TIC SF approach corrects for large dynamic shifting in the data as well as subtle peak-to-peak shifts. The benefits of the overall TIC SF alignment and feature selection approach were quantified using the degree-of-class separation (DCS) metric of the PCA scores plots using the type C and M samples, since they were the most similar, and thus the most challenging samples to properly classify. The DCS values showed an increase from an initial value of essentially zero for the unaligned GC-TIC data to a value of 7.9 following alignment; however, the DCS was unchanged by feature selection using F-Ratios for the GC-TIC data. The full mass spectral data provided an increase to a final DCS of 13.7 after alignment and two-dimensional (2D) F-Ratio feature selection.« less

Annoyance from industrial noise: indicators for a wide variety of industrial sources.

PubMed

Alayrac, M; Marquis-Favre, C; Viollon, S; Morel, J; Le Nost, G

2010-09-01

In the study of noises generated by industrial sources, one issue is the variety of industrial noise sources and consequently the complexity of noises generated. Therefore, characterizing the environmental impact of an industrial plant requires better understanding of the noise annoyance caused by industrial noise sources. To deal with the variety of industrial sources, the proposed approach is set up by type of spectral features and based on a perceptive typology of steady and permanent industrial noises comprising six categories. For each perceptive category, listening tests based on acoustical factors are performed on noise annoyance. Various indicators are necessary to predict noise annoyance due to various industrial noise sources. Depending on the spectral features of the industrial noise sources, noise annoyance indicators are thus assessed. In case of industrial noise sources without main spectral features such as broadband noise, noise annoyance is predicted by the A-weighted sound pressure level L(Aeq) or the loudness level L(N). For industrial noises with spectral components such as low-frequency noises with a main component at 100 Hz or noises with spectral components in middle frequencies, indicators are proposed here that allow good prediction of noise annoyance by taking into account spectral features.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Malashkevich, Vladimir N.; Higgins, Chelsea D.; Almo, Steven C.

The coiled-coil is one of the most ubiquitous and well studied protein structural motifs. Significant effort has been devoted to dissecting subtle variations of the typical heptad repeat sequence pattern that can designate larger topological features such as relative α-helical orientation and oligomer size. Here in this paper we report the X-ray structure of a model coiled-coil peptide, HA2-Del-L2seM, which forms an unanticipated core antiparallel dimer with potential sites for discrete higher-order multimerization (trimer or tetramer). In the X-ray structure, a third, partially-ordered α-helix is weakly associated with the antiparallel dimer and analytical ultracentrifugation experiments indicate the peptide forms amore » well-defined tetramer in solution. The HA2-Del-L2seM sequence is closely related to a parent model peptide, HA2-Del, which we previously reported adopts a parallel trimer; HA2-Del-L2seM differs by only hydrophobic leucine to selenomethione mutations and thus this subtle difference is sufficient to switch both relative α-helical topology and number of α-helices participating in the coiled-coil. Comparison of the X-ray structures of HA2-Del-L2seM (reported here) with the HA2-Del parent (reported previously) reveals novel interactions involving the selenomethionine residues that promote antiparallel coiled-coil configuration and preclude parallel trimer formation. Finally, these novel atomic insights are instructive for understanding subtle features that can affect coiled-coil topology and provide additional information for design of antiparallel coiled-coils.« less

Ship Detection Based on Multiple Features in Random Forest Model for Hyperspectral Images

NASA Astrophysics Data System (ADS)

Li, N.; Ding, L.; Zhao, H.; Shi, J.; Wang, D.; Gong, X.

2018-04-01

A novel method for detecting ships which aim to make full use of both the spatial and spectral information from hyperspectral images is proposed. Firstly, the band which is high signal-noise ratio in the range of near infrared or short-wave infrared spectrum, is used to segment land and sea on Otsu threshold segmentation method. Secondly, multiple features that include spectral and texture features are extracted from hyperspectral images. Principal components analysis (PCA) is used to extract spectral features, the Grey Level Co-occurrence Matrix (GLCM) is used to extract texture features. Finally, Random Forest (RF) model is introduced to detect ships based on the extracted features. To illustrate the effectiveness of the method, we carry out experiments over the EO-1 data by comparing single feature and different multiple features. Compared with the traditional single feature method and Support Vector Machine (SVM) model, the proposed method can stably achieve the target detection of ships under complex background and can effectively improve the detection accuracy of ships.

Whittle Communications and Channel One: Rhetorical Strategies of Innovation.

ERIC Educational Resources Information Center

Adams, Scott

A study examined the message features that influence an innovation's acceptance by a mass audience. The study looked at three strategies of innovational rhetoric (denial of controversy, subtle criticism of existing institutions, and projection of a rhetorical vision) used by a commercial broadcasting company, called Whittle Communications in 1989,…

Managing Students' Learning in Classrooms: Reframing Classroom Research.

ERIC Educational Resources Information Center

Fawns, Rod; Salder, Jo

1996-01-01

Analyzes Australian students' public and private statements to themselves and their peers collected in the course of a multiyear study of teacher management of communication in cooperative learning groups. Data reflect how students perceived and responded to subtle features in the public enactment of the curriculum, the task, and the setting…

Raman spectral evidence of methyl rotation in liquid toluene.

PubMed

Kapitán, Josef; Hecht, Lutz; Bour, Petr

2008-02-21

In order to rationalize subtle details in the liquid phase toluene Raman backscattering spectra, an analysis was performed based on a quantum-mechanical Hamiltonian operator comprising rotation of the methyl group and the angular dependence of vibrational frequencies and polarizability derivatives. The separation of the methyl torsion from the other vibrational motions appears to be necessary in order to explain relative intensity ratios of several bands and an anomalous broadening of spectral intensity observed at 1440 cm(-1). These results suggest that the CH3 group in the liquid phase rotates almost freely, similarly as in the gaseous phase, and that the molecule consequently exhibits effectively C(2v) point group symmetry. A classical description and an adiabatic separation of the methyl rotation from other molecular motion previously used in peptide models is not applicable to toluene because of a strong coupling with other vibrational motions. Density functional computations, particularly the BPW91 functional, provide reasonable estimates of harmonic frequencies and spectral intensities, as well as qualitatively correct fourth-order anharmonic corrections to the vibrational potential.

Hyperspectral image denoising and anomaly detection based on low-rank and sparse representations

NASA Astrophysics Data System (ADS)

Zhuang, Lina; Gao, Lianru; Zhang, Bing; Bioucas-Dias, José M.

2017-10-01

The very high spectral resolution of Hyperspectral Images (HSIs) enables the identification of materials with subtle differences and the extraction subpixel information. However, the increasing of spectral resolution often implies an increasing in the noise linked with the image formation process. This degradation mechanism limits the quality of extracted information and its potential applications. Since HSIs represent natural scenes and their spectral channels are highly correlated, they are characterized by a high level of self-similarity and are well approximated by low-rank representations. These characteristic underlies the state-of-the-art in HSI denoising. However, in presence of rare pixels, the denoising performance of those methods is not optimal and, in addition, it may compromise the future detection of those pixels. To address these hurdles, we introduce RhyDe (Robust hyperspectral Denoising), a powerful HSI denoiser, which implements explicit low-rank representation, promotes self-similarity, and, by using a form of collaborative sparsity, preserves rare pixels. The denoising and detection effectiveness of the proposed robust HSI denoiser is illustrated using semi-real data.

Use of feature extraction techniques for the texture and context information in ERTS imagery: Spectral and textural processing of ERTS imagery. [classification of Kansas land use

NASA Technical Reports Server (NTRS)

Haralick, R. H. (Principal Investigator); Bosley, R. J.

1974-01-01

The author has identified the following significant results. A procedure was developed to extract cross-band textural features from ERTS MSS imagery. Evolving from a single image texture extraction procedure which uses spatial dependence matrices to measure relative co-occurrence of nearest neighbor grey tones, the cross-band texture procedure uses the distribution of neighboring grey tone N-tuple differences to measure the spatial interrelationships, or co-occurrences, of the grey tone N-tuples present in a texture pattern. In both procedures, texture is characterized in such a way as to be invariant under linear grey tone transformations. However, the cross-band procedure complements the single image procedure by extracting texture information and spectral information contained in ERTS multi-images. Classification experiments show that when used alone, without spectral processing, the cross-band texture procedure extracts more information than the single image texture analysis. Results show an improvement in average correct classification from 86.2% to 88.8% for ERTS image no. 1021-16333 with the cross-band texture procedure. However, when used together with spectral features, the single image texture plus spectral features perform better than the cross-band texture plus spectral features, with an average correct classification of 93.8% and 91.6%, respectively.

Low complexity feature extraction for classification of harmonic signals

NASA Astrophysics Data System (ADS)

William, Peter E.

In this dissertation, feature extraction algorithms have been developed for extraction of characteristic features from harmonic signals. The common theme for all developed algorithms is the simplicity in generating a significant set of features directly from the time domain harmonic signal. The features are a time domain representation of the composite, yet sparse, harmonic signature in the spectral domain. The algorithms are adequate for low-power unattended sensors which perform sensing, feature extraction, and classification in a standalone scenario. The first algorithm generates the characteristic features using only the duration between successive zero-crossing intervals. The second algorithm estimates the harmonics' amplitudes of the harmonic structure employing a simplified least squares method without the need to estimate the true harmonic parameters of the source signal. The third algorithm, resulting from a collaborative effort with Daniel White at the DSP Lab, University of Nebraska-Lincoln, presents an analog front end approach that utilizes a multichannel analog projection and integration to extract the sparse spectral features from the analog time domain signal. Classification is performed using a multilayer feedforward neural network. Evaluation of the proposed feature extraction algorithms for classification through the processing of several acoustic and vibration data sets (including military vehicles and rotating electric machines) with comparison to spectral features shows that, for harmonic signals, time domain features are simpler to extract and provide equivalent or improved reliability over the spectral features in both the detection probabilities and false alarm rate.

Mimas Showing False Colors #2

NASA Technical Reports Server (NTRS)

2005-01-01

This false color image of Saturn's moon Mimas reveals variation in either the composition or texture across its surface.

During its approach to Mimas on Aug. 2, 2005, the Cassini spacecraft narrow-angle camera obtained multi-spectral views of the moon from a range of 228,000 kilometers (142,500 miles).

This image is a color composite of narrow-angle ultraviolet, green, infrared and clear filter images, which have been specially processed to accentuate subtle changes in the spectral properties of Mimas' surface materials. To create this view, three color images (ultraviolet, green and infrared) were combined with a single black and white picture that isolates and maps regional color differences to create the final product.

Shades of blue and violet in the image at the right are used to identify surface materials that are bluer in color and have a weaker infrared brightness than average Mimas materials, which are represented by green.

Herschel crater, a 140-kilometer-wide (88-mile) impact feature with a prominent central peak, is visible in the upper right of the image. The unusual bluer materials are seen to broadly surround Herschel crater. However, the bluer material is not uniformly distributed in and around the crater. Instead, it appears to be concentrated on the outside of the crater and more to the west than to the north or south. The origin of the color differences is not yet understood. It may represent ejecta material that was excavated from inside Mimas when the Herschel impact occurred. The bluer color of these materials may be caused by subtle differences in the surface composition or the sizes of grains making up the icy soil.

This image was obtained when the Cassini spacecraft was above 25 degrees south, 134 degrees west latitude and longitude. The Sun-Mimas-spacecraft angle was 45 degrees and north is at the top.

The Cassini-Huygens mission is a cooperative project of NASA, the European Space Agency and the Italian Space Agency. The Jet Propulsion Laboratory, a division of the California Institute of Technology in Pasadena, manages the mission for NASA's Science Mission Directorate, Washington, D.C. The Cassini orbiter and its two onboard cameras were designed, developed and assembled at JPL. The imaging operations center is based at the Space Science Institute in Boulder, Colo.

For more information about the Cassini-Huygens mission visit http://saturn.jpl.nasa.gov . The Cassini imaging team homepage is at http://ciclops.org .

Solar Spectral Irradiance Changes During Cycle 24

NASA Technical Reports Server (NTRS)

Marchenko, Sergey; Deland, Matthew

2014-01-01

We use solar spectra obtained by the Ozone Monitoring Instrument (OMI) on board the Aura satellite to detect and follow long-term (years) and short-term (weeks) changes in the solar spectral irradiance (SSI) in the 265-500 nm spectral range. During solar Cycle 24, in the relatively line-free regions the SSI changed by approximately 0.6% +/- 0.2% around 265 nm. These changes gradually diminish to 0.15% +/- 0.20% at 500 nm. All strong spectral lines and blends, with the notable exception of the upper Balmer lines, vary in unison with the solar "continuum." Besides the lines with strong chromospheric components, the most involved species include Fe I blends and all prominent CH, NH, and CN spectral bands. Following the general trend seen in the solar "continuum," the variability of spectral lines also decreases toward longer wavelengths. The long-term solar cycle SSI changes are closely, to within the quoted 0.1%-0.2% uncertainties, matched by the appropriately adjusted short-term SSI variations derived from the 27 day rotational modulation cycles. This further strengthens and broadens the prevailing notion about the general scalability of the UV SSI variability to the emissivity changes in the Mg II 280 nm doublet on timescales from weeks to years. We also detect subtle deviations from this general rule: the prominent spectral lines and blends at lambda approximately or greater than 350 nm show slightly more pronounced 27 day SSI changes when compared to the long-term (years) trends. We merge the solar data from Cycle 21 with the current Cycle 24 OMI and GOME-2 observations and provide normalized SSI variations for the 170-795 nm spectral region.

Spectral-spatial classification of hyperspectral data with mutual information based segmented stacked autoencoder approach

NASA Astrophysics Data System (ADS)

Paul, Subir; Nagesh Kumar, D.

2018-04-01

Hyperspectral (HS) data comprises of continuous spectral responses of hundreds of narrow spectral bands with very fine spectral resolution or bandwidth, which offer feature identification and classification with high accuracy. In the present study, Mutual Information (MI) based Segmented Stacked Autoencoder (S-SAE) approach for spectral-spatial classification of the HS data is proposed to reduce the complexity and computational time compared to Stacked Autoencoder (SAE) based feature extraction. A non-parametric dependency measure (MI) based spectral segmentation is proposed instead of linear and parametric dependency measure to take care of both linear and nonlinear inter-band dependency for spectral segmentation of the HS bands. Then morphological profiles are created corresponding to segmented spectral features to assimilate the spatial information in the spectral-spatial classification approach. Two non-parametric classifiers, Support Vector Machine (SVM) with Gaussian kernel and Random Forest (RF) are used for classification of the three most popularly used HS datasets. Results of the numerical experiments carried out in this study have shown that SVM with a Gaussian kernel is providing better results for the Pavia University and Botswana datasets whereas RF is performing better for Indian Pines dataset. The experiments performed with the proposed methodology provide encouraging results compared to numerous existing approaches.

Radio-nuclide mixture identification using medium energy resolution detectors

DOEpatents

Nelson, Karl Einar

2013-09-17

According to one embodiment, a method for identifying radio-nuclides includes receiving spectral data, extracting a feature set from the spectral data comparable to a plurality of templates in a template library, and using a branch and bound method to determine a probable template match based on the feature set and templates in the template library. In another embodiment, a device for identifying unknown radio-nuclides includes a processor, a multi-channel analyzer, and a memory operatively coupled to the processor, the memory having computer readable code stored thereon. The computer readable code is configured, when executed by the processor, to receive spectral data, to extract a feature set from the spectral data comparable to a plurality of templates in a template library, and to use a branch and bound method to determine a probable template match based on the feature set and templates in the template library.

Assessment of seasonal features based on Landsat time series for tree crown cover mapping in Burkina Faso

NASA Astrophysics Data System (ADS)

Liu, Jinxiu; Heiskanen, Janne; Aynekuly, Ermias; Pellikka, Petri

2016-04-01

Tree crown cover (CC) is an important vegetation attribute for land cover characterization, and for mapping and monitoring forest cover. Free data from Landsat and Sentinel-2 allow construction of fine resolution satellite image time series and extraction of seasonal features for predicting vegetation attributes. In the savannas, surface reflectance vary distinctively according to the rainy and dry seasons, and seasonal features are useful information for CC mapping. However, it is unclear if it is better to use spectral bands or vegetation indices (VI) for computation of seasonal features, and how feasible different VI are for CC prediction in the savanna woodlands and agroforestry parklands of West Africa. In this study, the objective was to compare seasonal features based on spectral bands and VI for CC mapping in southern Burkina Faso. A total of 35 Landsat images from November 2013 to October 2014 were processed. Seasonal features were computed using a harmonic model with three parameters (mean, amplitude and phase), and spectral bands, normalized difference vegetation index (NDVI), green normalized difference vegetation index (GNDVI), normalized difference water index (NDWI), tasseled cap (TC) indices (brightness, greenness, wetness) as input data. The seasonal features were employed to predict field estimated CC (n = 160) using Random Forest algorithm. The most accurate results were achieved when using seasonal features based on TC indices (R2: 0.65; RMSE: 10.7%) and spectral bands (R2: 0.64; RMSE: 10.8%). GNDVI performed better than NDVI or NDWI, and NDWI resulted in the poorest results (R2: 0.56; RMSE: 11.9%). The results indicate that spectral features should be carefully selected for CC prediction as shown by relatively poor performance of commonly used NDVI. The seasonal features based on three TC indices and all the spectral bands provided superior accuracy in comparison to single VI. The method presented in this study provides a feasible method to map CC based on seasonal features with possibility to integrate medium resolution satellite observation from several sensors (e.g. Landsat and Sentinel-2) in the future.

Factors in life science textbooks that may deter girls' interest in science

NASA Astrophysics Data System (ADS)

Potter, Ellen F.; Rosser, Sue V.

In order to examine factors that may deter girls' interest in science, five seventh-grade life science textbooks were analyzed for sexism in language, images, and curricular content, and for features of activities that have been found to be useful for motivating girls. Although overt sexism was not apparent, subtle forms of sexism in the selection of language, images, and curricular content were found. Activities had some features useful to girls, but other features were seldom included. Teachers may wish to use differences that were found among texts as one basis for text selection.

Silica-rich deposits and hydrated minerals at Gusev Crater, Mars: Vis-NIR spectral characterization and regional mapping

USGS Publications Warehouse

Rice, M.S.; Bell, J.F.; Cloutis, E.A.; Wang, A.; Ruff, S.W.; Craig, M.A.; Bailey, D.T.; Johnson, J. R.; De Souza, P.A.; Farrand, W. H.

2010-01-01

The Mars Exploration Rover (MER) Spirit has discovered surprisingly high concentrations of amorphous silica in soil and nodular outcrops in the Inner Basin of the Columbia Hills. In Pancam multispectral observations, we find that an absorption feature at the longest Pancam wavelength (1009 nm) appears to be characteristic of these silica-rich materials; however, spectral analyses of amorphous silica suggest that the ???1009 nm spectral feature is not a direct reflection of their silica-rich nature. Based on comparisons with spectral databases, we hypothesize that the presence of H2O or OH, either free (as water ice), adsorbed or bound in a mineral structure, is responsible for the spectral feature observed by Pancam. The Gertrude Weise soil, which is nearly pure opaline silica, may have adsorbed water cold-trapped on mineral grains. The origin of the ???1009 nm Pancam feature observed in the silica-rich nodular outcrops may result from the presence of additional hydrated minerals (specific sulfates, halides, chlorides, sodium silicates, carbonates or borates). Using the ???1009 nm feature with other spectral parameters as a "hydration signature" we have mapped the occurrence of hydrated materials along the extent of Spirit's traverse across the Columbia Hills from West Spur to Home Plate (sols 155-1696). We have also mapped this hydration signature across large panoramic images to understand the regional distribution of materials that are spectrally similar to the silica-rich soil and nodular outcrops. Our results suggest that hydrated materials are common in the Columbia Hills. ?? 2009 Elsevier Inc.

Mapping accuracy via spectrally and structurally based filtering techniques: comparisons through visual observations

NASA Astrophysics Data System (ADS)

Chockalingam, Letchumanan

2005-01-01

The data of Gunung Ledang region of Malaysia acquired through LANDSAT are considered to map certain hydrogeolocial features. To map these significant features, image-processing tools such as contrast enhancement, edge detection techniques are employed. The advantages of these techniques over the other methods are evaluated from the point of their validity in properly isolating features of hydrogeolocial interest are discussed. As these techniques take the advantage of spectral aspects of the images, these techniques have several limitations to meet the objectives. To discuss these limitations, a morphological transformation, which generally considers the structural aspects rather than spectral aspects from the image, are applied to provide comparisons between the results derived from spectral based and the structural based filtering techniques.

An Exercise on Calibration: DRIFTS Study of Binary Mixtures of Calcite and Dolomite with Partially Overlapping Spectral Features

ERIC Educational Resources Information Center

De Lorenzi Pezzolo, Alessandra

2013-01-01

Unlike most spectroscopic calibrations that are based on the study of well-separated features ascribable to the different components, this laboratory experience is especially designed to exploit spectral features that are nearly overlapping. The investigated system consists of a binary mixture of two commonly occurring minerals, calcite and…

Deep Learning Based Binaural Speech Separation in Reverberant Environments.

PubMed

Zhang, Xueliang; Wang, DeLiang

2017-05-01

Speech signal is usually degraded by room reverberation and additive noises in real environments. This paper focuses on separating target speech signal in reverberant conditions from binaural inputs. Binaural separation is formulated as a supervised learning problem, and we employ deep learning to map from both spatial and spectral features to a training target. With binaural inputs, we first apply a fixed beamformer and then extract several spectral features. A new spatial feature is proposed and extracted to complement the spectral features. The training target is the recently suggested ideal ratio mask. Systematic evaluations and comparisons show that the proposed system achieves very good separation performance and substantially outperforms related algorithms under challenging multi-source and reverberant environments.

Infrared reflectivity investigation of the phase transition sequence in Pr0.5Ca0.5MnO3

NASA Astrophysics Data System (ADS)

Ribeiro, J. L.; Vieira, L. G.; Gomes, I. T.; Araújo, J. P.; Tavares, P.; Almeida, B. G.

2016-06-01

This work reports an infrared reflectivity study of the phase transition sequence observed in Pr0.5Ca0.5MnO3. The need to measure over an extended spectral range in order to properly take into account the effects of the high frequency polaronic absorption is circumvented by adopting a simple approximate method, based on the asymmetry present in the Kramers Kronig inversion of the phonon spectrum. The temperature dependence of the phonon optical conductivity is then investigated by monitoring the behavior of three relevant spectral moments of the optical conductivity. This combined methodology allows us to disclose subtle effects of the orbital, charge and magnetic orders on the lattice dynamics of the compound. The characteristic transition temperatures inferred from the spectroscopic measurements are compared and correlated with those obtained from the temperature dependence of the induced magnetization and electrical resistivity.

How to distinguish between cloudy mini-Neptunes and water/volatile-dominated super-Earths

DOE Office of Scientific and Technical Information (OSTI.GOV)

Benneke, Björn; Seager, Sara, E-mail: bbenneke@mit.edu

One of the most profound questions about the newly discovered class of low-density super-Earths is whether these exoplanets are predominately H{sub 2}-dominated mini-Neptunes or volatile-rich worlds with gas envelopes dominated by H{sub 2}O, CO{sub 2}, CO, CH{sub 4}, or N{sub 2}. Transit observations of the super-Earth GJ 1214b rule out cloud-free H{sub 2}-dominated scenarios, but are not able to determine whether the lack of deep spectral features is due to high-altitude clouds or the presence of a high mean molecular mass atmosphere. Here, we demonstrate that one can unambiguously distinguish between cloudy mini-Neptunes and volatile-dominated worlds based on wing steepnessmore » and relative depths of absorption features in moderate-resolution near-infrared transmission spectra (R ∼ 100). In a numerical retrieval study, we show for GJ 1214b that an unambiguous distinction between a cloudy H{sub 2}-dominated atmosphere and cloud-free H{sub 2}O atmosphere will be possible if the uncertainties in the spectral transit depth measurements can be reduced by a factor of ∼3 compared to the published Hubble Space Telescope Wide-Field Camera 3 and Very Large Telescope transit observations by Berta et al. and Bean et al. We argue that the required precision for the distinction may be achievable with currently available instrumentation by stacking 10-15 repeated transit observations. We provide a scaling law that scales our quantitative results to other transiting super-Earths and Neptunes such as HD 97658b, 55 Cnc e, GJ 3470b and GJ 436b. The analysis in this work is performed using an improved version of our Bayesian atmospheric retrieval framework. The new framework not only constrains the gas composition and cloud/haze parameters, but also determines our confidence in having detected molecules and cloud/haze species through Bayesian model comparison. Using the Bayesian tool, we demonstrate quantitatively that the subtle transit depth variation in the Berta et al. data is not sufficient to claim the detection of water absorption.« less

Tall Mountain: Enhanced View

NASA Image and Video Library

2015-08-06

Among the highest features seen on Ceres so far is a mountain about 4 miles (6 kilometers) high, which is roughly the elevation of Mount McKinley in Alaska's Denali National Park. This image comes from an animation, shown in PIA19619, generated using data from NASA's Dawn spacecraft. Vertical relief has been exaggerated by a factor of five. Exaggerating the relief helps scientists understand and visualize the topography much more easily, and highlights features that are sometimes subtle. http://photojournal.jpl.nasa.gov/catalog/PIA19618

A spectral-structural bag-of-features scene classifier for very high spatial resolution remote sensing imagery

NASA Astrophysics Data System (ADS)

Zhao, Bei; Zhong, Yanfei; Zhang, Liangpei

2016-06-01

Land-use classification of very high spatial resolution remote sensing (VHSR) imagery is one of the most challenging tasks in the field of remote sensing image processing. However, the land-use classification is hard to be addressed by the land-cover classification techniques, due to the complexity of the land-use scenes. Scene classification is considered to be one of the expected ways to address the land-use classification issue. The commonly used scene classification methods of VHSR imagery are all derived from the computer vision community that mainly deal with terrestrial image recognition. Differing from terrestrial images, VHSR images are taken by looking down with airborne and spaceborne sensors, which leads to the distinct light conditions and spatial configuration of land cover in VHSR imagery. Considering the distinct characteristics, two questions should be answered: (1) Which type or combination of information is suitable for the VHSR imagery scene classification? (2) Which scene classification algorithm is best for VHSR imagery? In this paper, an efficient spectral-structural bag-of-features scene classifier (SSBFC) is proposed to combine the spectral and structural information of VHSR imagery. SSBFC utilizes the first- and second-order statistics (the mean and standard deviation values, MeanStd) as the statistical spectral descriptor for the spectral information of the VHSR imagery, and uses dense scale-invariant feature transform (SIFT) as the structural feature descriptor. From the experimental results, the spectral information works better than the structural information, while the combination of the spectral and structural information is better than any single type of information. Taking the characteristic of the spatial configuration into consideration, SSBFC uses the whole image scene as the scope of the pooling operator, instead of the scope generated by a spatial pyramid (SP) commonly used in terrestrial image classification. The experimental results show that the whole image as the scope of the pooling operator performs better than the scope generated by SP. In addition, SSBFC codes and pools the spectral and structural features separately to avoid mutual interruption between the spectral and structural features. The coding vectors of spectral and structural features are then concatenated into a final coding vector. Finally, SSBFC classifies the final coding vector by support vector machine (SVM) with a histogram intersection kernel (HIK). Compared with the latest scene classification methods, the experimental results with three VHSR datasets demonstrate that the proposed SSBFC performs better than the other classification methods for VHSR image scenes.

Looking into the future: An inward bias in aesthetic experience driven only by gaze cues.

PubMed

Chen, Yi-Chia; Colombatto, Clara; Scholl, Brian J

2018-07-01

The inward bias is an especially powerful principle of aesthetic experience: In framed images (e.g. photographs), we prefer peripheral figures that face inward (vs. outward). Why does this bias exist? Since agents tend to act in the direction in which they are facing, one intriguing possibility is that the inward bias reflects a preference to view scenes from a perspective that will allow us to witness those predicted future actions. This account has been difficult to test with previous displays, in which facing direction is often confounded with either global shape profiles or the relative locations of salient features (since e.g. someone's face is generally more visually interesting than the back of their head). But here we demonstrate a robust inward bias in aesthetic judgment driven by a cue that is socially powerful but visually subtle: averted gaze. Subjects adjusted the positions of people in images to maximize the images' aesthetic appeal. People with direct gaze were not placed preferentially in particular regions, but people with averted gaze were reliably placed so that they appeared to be looking inward. This demonstrates that the inward bias can arise from visually subtle features, when those features signal how future events may unfold. Copyright © 2018. Published by Elsevier B.V.

Age, Health and Attractiveness Perception of Virtual (Rendered) Human Hair

PubMed Central

Fink, Bernhard; Hufschmidt, Carla; Hirn, Thomas; Will, Susanne; McKelvey, Graham; Lankhof, John

2016-01-01

The social significance of physical appearance and beauty has been documented in many studies. It is known that even subtle manipulations of facial morphology and skin condition can alter people’s perception of a person’s age, health and attractiveness. While the variation in facial morphology and skin condition cues has been studied quite extensively, comparably little is known on the effect of hair on social perception. This has been partly caused by the technical difficulty of creating appropriate stimuli for investigations of people’s response to systematic variation of certain hair characteristics, such as color and style, while keeping other features constant. Here, we present a modeling approach to the investigation of human hair perception using computer-generated, virtual (rendered) human hair. In three experiments, we manipulated hair diameter (Experiment 1), hair density (Experiment 2), and hair style (Experiment 3) of human (female) head hair and studied perceptions of age, health and attractiveness. Our results show that even subtle changes in these features have an impact on hair perception. We discuss our findings with reference to previous studies on condition-dependent quality cues in women that influence human social perception, thereby suggesting that hair is a salient feature of human physical appearance, which contributes to the perception of beauty. PMID:28066276

Astrophysical data on 5 eV to 1 keV radiation from the radiative decay of fundamental particles - Current limits and prospects for improvement

NASA Technical Reports Server (NTRS)

Bowyer, Stuart; Malina, Roger F.

1986-01-01

Line emission from the decay of fundamental particles, integrated over cosmological distances, can give rise to detectable spectral features in the diffuse astronomical background between 5 eV and 1 keV. Spectroscopic observations may allow these features to be separated from line emission from the numerous local sources of radiation. The current observational status and existing evidence for such features are reviewed. No definitive detections of nongalactic line features have been made. Several local sources of background mask the features at many wavelengths and confuse the interpretation of the data. No systematic spectral observations have been carried out to date. Upcoming experiments which can be expected to provide significantly better constraints on the presence of spectral features in the diffuse background from 5 eV to 1 keV are reviewed.

Neurologic and developmental features of the Smith-Magenis syndrome (del 17p11.2).

PubMed

Gropman, Andrea L; Duncan, Wallace C; Smith, Ann C M

2006-05-01

The Smith-Magenis syndrome is a rare, complex multisystemic disorder featuring, mental retardation and multiple congenital anomalies caused by a heterozygous interstitial deletion of chromosome 17p11.2. The phenotype of Smith-Magenis syndrome is characterized by a distinct pattern of features including infantile hypotonia, generalized complacency and lethargy in infancy, minor skeletal (brachycephaly, brachydactyly) and craniofacial features, ocular abnormalities, middle ear and laryngeal abnormalities including hoarse voice, as well as marked early expressive speech and language delays, psychomotor and growth retardation, and a 24-hour sleep disturbance. A striking neurobehavioral pattern of stereotypies, hyperactivity, polyembolokoilamania, onychotillomania, maladaptive and self-injurious and aggressive behavior is observed with increasing age. The diagnosis of Smith-Magenis syndrome is based upon the clinical recognition of a constellation of physical, developmental, and behavioral features in combination with a sleep disorder characterized by inverted circadian rhythm of melatonin secretion. Many of the features of Smith-Magenis syndrome are subtle in infancy and early childhood, and become more recognizable with advancing age. Infants are described as looking "cherubic" with a Down syndrome-like appearance, whereas with age the facial appearance is that of relative prognathism. Early diagnosis requires awareness of the often subtle clinical and neurobehavioral phenotype of the infant period. Speech delay with or without hearing loss is common. Most children are diagnosed in mid-childhood when the features of the disorder are most recognizable and striking. While improvements in cytogenetic analysis help to bring cases to clinical recognition at an earlier age, this review seeks to increase clinical awareness about Smith-Magenis syndrome by presenting the salient features observed at different ages including descriptions of the neurologic and behavioral features. Detailed review of the circadian rhythm disturbance unique to Smith-Magenis syndrome is presented. Suggestions for management of the behavioral and sleep difficulties are discussed in the context of the authors' personal experience in the setting of an ongoing Smith-Magenis syndrome natural history study.

Spectral feature variations in x-ray diffraction imaging systems

NASA Astrophysics Data System (ADS)

Wolter, Scott D.; Greenberg, Joel A.

2016-05-01

Materials with different atomic or molecular structures give rise to unique scatter spectra when measured by X-ray diffraction. The details of these spectra, though, can vary based on both intrinsic (e.g., degree of crystallinity or doping) and extrinsic (e.g., pressure or temperature) conditions. While this sensitivity is useful for detailed characterizations of the material properties, these dependences make it difficult to perform more general classification tasks, such as explosives threat detection in aviation security. A number of challenges, therefore, currently exist for reliable substance detection including the similarity in spectral features among some categories of materials combined with spectral feature variations from materials processing and environmental factors. These factors complicate the creation of a material dictionary and the implementation of conventional classification and detection algorithms. Herein, we report on two prominent factors that lead to variations in spectral features: crystalline texture and temperature variations. Spectral feature comparisons between materials categories will be described for solid metallic sheet, aqueous liquids, polymer sheet, and metallic, organic, and inorganic powder specimens. While liquids are largely immune to texture effects, they are susceptible to temperature changes that can modify their density or produce phase changes. We will describe in situ temperature-dependent measurement of aqueous-based commercial goods in the temperature range of -20°C to 35°C.

[Road Extraction in Remote Sensing Images Based on Spectral and Edge Analysis].

PubMed

Zhao, Wen-zhi; Luo, Li-qun; Guo, Zhou; Yue, Jun; Yu, Xue-ying; Liu, Hui; Wei, Jing

2015-10-01

Roads are typically man-made objects in urban areas. Road extraction from high-resolution images has important applications for urban planning and transportation development. However, due to the confusion of spectral characteristic, it is difficult to distinguish roads from other objects by merely using traditional classification methods that mainly depend on spectral information. Edge is an important feature for the identification of linear objects (e. g. , roads). The distribution patterns of edges vary greatly among different objects. It is crucial to merge edge statistical information into spectral ones. In this study, a new method that combines spectral information and edge statistical features has been proposed. First, edge detection is conducted by using self-adaptive mean-shift algorithm on the panchromatic band, which can greatly reduce pseudo-edges and noise effects. Then, edge statistical features are obtained from the edge statistical model, which measures the length and angle distribution of edges. Finally, by integrating the spectral and edge statistical features, SVM algorithm is used to classify the image and roads are ultimately extracted. A series of experiments are conducted and the results show that the overall accuracy of proposed method is 93% comparing with only 78% overall accuracy of the traditional. The results demonstrate that the proposed method is efficient and valuable for road extraction, especially on high-resolution images.

Use of feature extraction techniques for the texture and context information in ERTS imagery. [discrimination of land use categories in Kansas from MSS textural-spectral features

NASA Technical Reports Server (NTRS)

Haralick, R. M.; Kelly, G. L. (Principal Investigator); Bosley, R. J.

1973-01-01

The author has identified the following significant results. The land use category of subimage regions over Kansas within an MSS image can be identified with an accuracy of about 70% using the textural-spectral features of the multi-images from the four MSS bands.

GENIE: a hybrid genetic algorithm for feature classification in multispectral images

NASA Astrophysics Data System (ADS)

Perkins, Simon J.; Theiler, James P.; Brumby, Steven P.; Harvey, Neal R.; Porter, Reid B.; Szymanski, John J.; Bloch, Jeffrey J.

2000-10-01

We consider the problem of pixel-by-pixel classification of a multi- spectral image using supervised learning. Conventional spuervised classification techniques such as maximum likelihood classification and less conventional ones s uch as neural networks, typically base such classifications solely on the spectral components of each pixel. It is easy to see why: the color of a pixel provides a nice, bounded, fixed dimensional space in which these classifiers work well. It is often the case however, that spectral information alone is not sufficient to correctly classify a pixel. Maybe spatial neighborhood information is required as well. Or maybe the raw spectral components do not themselves make for easy classification, but some arithmetic combination of them would. In either of these cases we have the problem of selecting suitable spatial, spectral or spatio-spectral features that allow the classifier to do its job well. The number of all possible such features is extremely large. How can we select a suitable subset? We have developed GENIE, a hybrid learning system that combines a genetic algorithm that searches a space of image processing operations for a set that can produce suitable feature planes, and a more conventional classifier which uses those feature planes to output a final classification. In this paper we show that the use of a hybrid GA provides significant advantages over using either a GA alone or more conventional classification methods alone. We present results using high-resolution IKONOS data, looking for regions of burned forest and for roads.

Optical Coherence Tomography in Glaucoma

NASA Astrophysics Data System (ADS)

Berisha, Fatmire; Hoffmann, Esther M.; Pfeiffer, Norbert

Retinal nerve fiber layer (RNFL) thinning and optic nerve head cupping are key diagnostic features of glaucomatous optic neuropathy. The higher resolution of the recently introduced SD-OCT offers enhanced visualization and improved segmentation of the retinal layers, providing a higher accuracy in identification of subtle changes of the optic disc and RNFL thinning associated with glaucoma.

Prosody Predicts Contest Outcome in Non-Verbal Dialogs

PubMed Central

Dreiss, Amélie N.; Chatelain, Philippe G.

2016-01-01

Non-verbal communication has important implications for inter-individual relationships and negotiation success. However, to what extent humans can spontaneously use rhythm and prosody as a sole communication tool is largely unknown. We analysed human ability to resolve a conflict without verbal dialogs, independently of semantics. We invited pairs of subjects to communicate non-verbally using whistle sounds. Along with the production of more whistles, participants unwittingly used a subtle prosodic feature to compete over a resource (ice-cream scoops). Winners can be identified by their propensity to accentuate the first whistles blown when replying to their partner, compared to the following whistles. Naive listeners correctly identified this prosodic feature as a key determinant of which whistler won the interaction. These results suggest that in the absence of other communication channels, individuals spontaneously use a subtle variation of sound accentuation (prosody), instead of merely producing exuberant sounds, to impose themselves in a conflict of interest. We discuss the biological and cultural bases of this ability and their link with verbal communication. Our results highlight the human ability to use non-verbal communication in a negotiation process. PMID:27907039

Prosody Predicts Contest Outcome in Non-Verbal Dialogs.

PubMed

Dreiss, Amélie N; Chatelain, Philippe G; Roulin, Alexandre; Richner, Heinz

2016-01-01

Non-verbal communication has important implications for inter-individual relationships and negotiation success. However, to what extent humans can spontaneously use rhythm and prosody as a sole communication tool is largely unknown. We analysed human ability to resolve a conflict without verbal dialogs, independently of semantics. We invited pairs of subjects to communicate non-verbally using whistle sounds. Along with the production of more whistles, participants unwittingly used a subtle prosodic feature to compete over a resource (ice-cream scoops). Winners can be identified by their propensity to accentuate the first whistles blown when replying to their partner, compared to the following whistles. Naive listeners correctly identified this prosodic feature as a key determinant of which whistler won the interaction. These results suggest that in the absence of other communication channels, individuals spontaneously use a subtle variation of sound accentuation (prosody), instead of merely producing exuberant sounds, to impose themselves in a conflict of interest. We discuss the biological and cultural bases of this ability and their link with verbal communication. Our results highlight the human ability to use non-verbal communication in a negotiation process.

Mineral shock signatures in rocks from Dhala (Mohar) impact structure, Shivpuri district, Madhya Pradesh, India

NASA Astrophysics Data System (ADS)

Roy, Madhuparna; Pandey, Pradeep; Kumar, Shailendra; Parihar, P. S.

2017-12-01

A concrete study combining optical microscopy, Raman spectroscopy and X-ray diffractometry, was carried out on subsurface samples of basement granite and melt breccia from Mohar (Dhala) impact structure, Shivpuri district, Madhya Pradesh, India. Optical microscopy reveals aberrations in the optical properties of quartz and feldspar in the form of planar deformation feature-like structures, lowered birefringence and mosaics in quartz, toasting, planar fractures and ladder texture in alkali feldspar and near-isotropism in bytownite. It also brings to light incidence of parisite, a radioactive rare mineral in shocked granite. Raman spectral pattern, peak positions, peak widths and multiplicity of peak groups of all minerals, suggest subtle structural/crystallographic deviations. XRD data further reveals minute deviations of unit cell parameters of quartz, alkali feldspar and plagioclase, with respect to standard α-quartz, high- and low albite and microcline. Reduced cell volumes in these minerals indicate compression due to pressure. The c0/a0 values indicate an inter-tetrahedral angle roughly between 120o and 144o, further pointing to a possible pressure maxima of around 12 GPa. The observed unit cell aberration of minerals may indicate an intermediate stage between crystalline and amorphous stages, thereby, signifying possible overprinting of decompression signatures over shock compression effects, from a shock recovery process.

Object-Based Paddy Rice Mapping Using HJ-1A/B Data and Temporal Features Extracted from Time Series MODIS NDVI Data

PubMed Central

Singha, Mrinal; Wu, Bingfang; Zhang, Miao

2016-01-01

Accurate and timely mapping of paddy rice is vital for food security and environmental sustainability. This study evaluates the utility of temporal features extracted from coarse resolution data for object-based paddy rice classification of fine resolution data. The coarse resolution vegetation index data is first fused with the fine resolution data to generate the time series fine resolution data. Temporal features are extracted from the fused data and added with the multi-spectral data to improve the classification accuracy. Temporal features provided the crop growth information, while multi-spectral data provided the pattern variation of paddy rice. The achieved overall classification accuracy and kappa coefficient were 84.37% and 0.68, respectively. The results indicate that the use of temporal features improved the overall classification accuracy of a single-date multi-spectral image by 18.75% from 65.62% to 84.37%. The minimum sensitivity (MS) of the paddy rice classification has also been improved. The comparison showed that the mapped paddy area was analogous to the agricultural statistics at the district level. This work also highlighted the importance of feature selection to achieve higher classification accuracies. These results demonstrate the potential of the combined use of temporal and spectral features for accurate paddy rice classification. PMID:28025525

Object-Based Paddy Rice Mapping Using HJ-1A/B Data and Temporal Features Extracted from Time Series MODIS NDVI Data.

PubMed

Singha, Mrinal; Wu, Bingfang; Zhang, Miao

2016-12-22

Accurate and timely mapping of paddy rice is vital for food security and environmental sustainability. This study evaluates the utility of temporal features extracted from coarse resolution data for object-based paddy rice classification of fine resolution data. The coarse resolution vegetation index data is first fused with the fine resolution data to generate the time series fine resolution data. Temporal features are extracted from the fused data and added with the multi-spectral data to improve the classification accuracy. Temporal features provided the crop growth information, while multi-spectral data provided the pattern variation of paddy rice. The achieved overall classification accuracy and kappa coefficient were 84.37% and 0.68, respectively. The results indicate that the use of temporal features improved the overall classification accuracy of a single-date multi-spectral image by 18.75% from 65.62% to 84.37%. The minimum sensitivity (MS) of the paddy rice classification has also been improved. The comparison showed that the mapped paddy area was analogous to the agricultural statistics at the district level. This work also highlighted the importance of feature selection to achieve higher classification accuracies. These results demonstrate the potential of the combined use of temporal and spectral features for accurate paddy rice classification.

Multi scales based sparse matrix spectral clustering image segmentation

NASA Astrophysics Data System (ADS)

Liu, Zhongmin; Chen, Zhicai; Li, Zhanming; Hu, Wenjin

2018-04-01

In image segmentation, spectral clustering algorithms have to adopt the appropriate scaling parameter to calculate the similarity matrix between the pixels, which may have a great impact on the clustering result. Moreover, when the number of data instance is large, computational complexity and memory use of the algorithm will greatly increase. To solve these two problems, we proposed a new spectral clustering image segmentation algorithm based on multi scales and sparse matrix. We devised a new feature extraction method at first, then extracted the features of image on different scales, at last, using the feature information to construct sparse similarity matrix which can improve the operation efficiency. Compared with traditional spectral clustering algorithm, image segmentation experimental results show our algorithm have better degree of accuracy and robustness.

Remote sensing for environmental site screening and watershed evaluation in Utah Mine lands - East Tintic mountains, Oquirrh mountains, and Tushar mountains

USGS Publications Warehouse

Rockwell, Barnaby W.; McDougal, Robert R.; Gent, Carol A.

2005-01-01

Imaging spectroscopy-a powerful remote-sensing tool for mapping subtle variations in the composition of minerals, vegetation, and man-made materials on the Earth's surface-was applied in support of environmental assessments and watershed evaluations in several mining districts in the State of Utah. Three areas were studied through the use of Landsat 7 ETM+ and Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data: (1) the Tintic mining district in the East Tintic Mountains southwest of Provo, (2) the Camp Floyd mining district (including the Mercur mine) and the Stockton (or Rush Valley) mining district in the Oquirrh Mountains south of the Great Salt Lake, and (3) the Tushar Mountains and Antelope Range near Marysvale. The Landsat 7 ETM+ data were used for initial site screening and the planning of AVIRIS surveys. The AVIRIS data were analyzed to create spectrally defined maps of surface minerals with special emphasis on locating and characterizing rocks and soils with acid-producing potential (APP) and acid-neutralizing potential (ANP). These maps were used by the United States Environmental Protection Agency (USEPA) for three primary purposes: (1) to identify unmined and anthropogenic sources of acid generation in the form of iron sulfide and (or) ferric iron sulfate-bearing minerals such as jarosite and copiapite; (2) to seek evidence for downstream or downwind movement of minerals associated with acid generation, mine waste, and (or) tailings from mines, mill sites, and zones of unmined hydrothermally altered rocks; and (3) to identify carbonate and other acid-buffering minerals that neutralize acidic, potentially metal bearing, solutions and thus mitigate potential environmental effects of acid generation. Calibrated AVIRIS surface-reflectance data were spectrally analyzed to identify and map selected surface materials. Two maps were produced from each flightline of AVIRIS data: a map of iron-bearing minerals and water having absorption features in the spectral region from 0.35 ?m to 1.35 ?m and a map of minerals (including clays, sulfates, micas, and carbonates) having absorptions in the spectral region from 1.45 ?m to 2.51 ?m. Several methods were used to verify the AVIRIS mapping results, including field checking of selected locations with a portable spectrometer, visual inspection of the AVIRIS reflectance spectra, and X-ray diffraction (XRD) analysis of field samples. The maps of iron-bearing minerals derived from analysis of the visible (VIS) and near-infrared (NIR) regions of the electromagnetic spectrum were shown to be more consistently reliable in indicating the presence of jarosite than were the maps generated from analysis of the short-wave infrared (SWIR) region. When present in abundance, phyllosilicate minerals tend to dominate the SWIR and mask the spectral features of jarosite in that wavelength region. The crystal field absorptions of jarosite in the VIS and NIR spectral regions will commonly be present regardless of whether the Fe-OH absorption feature near 2.27 ?m can be detected. For this reason, the VIS and NIR were preferable to the SWIR for the remote spectroscopic identification of jarosite (and other iron-bearing minerals). Large exposures of unmined hydrothermally altered rocks occur throughout the three study areas. These rocks commonly contain sulfide or sulfate minerals that produce sulfuric acid upon subaerial oxidation. The acid may be introduced into local surface and ground water and thus lower the baseline (that is, the premining) pH for a watershed. The three study areas also have widespread exposures of rocks with acid-neutralizing potential. Lithologies containing carbonates and (or) other acid-buffering minerals-such as sedimentary limestones and dolomites and propylitically altered igneous rocks-were mapped with the AVIRIS data throughout the Oquirrh and East Tintic Mountains and locally in the Antelope Range and Tushar Mountains. Because elevated levels o

Feature-based and statistical methods for analyzing the Deepwater Horizon oil spill with AVIRIS imagery

USGS Publications Warehouse

Rand, R.S.; Clark, R.N.; Livo, K.E.

2011-01-01

The Deepwater Horizon oil spill covered a very large geographical area in the Gulf of Mexico creating potentially serious environmental impacts on both marine life and the coastal shorelines. Knowing the oil's areal extent and thickness as well as denoting different categories of the oil's physical state is important for assessing these impacts. High spectral resolution data in hyperspectral imagery (HSI) sensors such as Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) provide a valuable source of information that can be used for analysis by semi-automatic methods for tracking an oil spill's areal extent, oil thickness, and oil categories. However, the spectral behavior of oil in water is inherently a highly non-linear and variable phenomenon that changes depending on oil thickness and oil/water ratios. For certain oil thicknesses there are well-defined absorption features, whereas for very thin films sometimes there are almost no observable features. Feature-based imaging spectroscopy methods are particularly effective at classifying materials that exhibit specific well-defined spectral absorption features. Statistical methods are effective at classifying materials with spectra that exhibit a considerable amount of variability and that do not necessarily exhibit well-defined spectral absorption features. This study investigates feature-based and statistical methods for analyzing oil spills using hyperspectral imagery. The appropriate use of each approach is investigated and a combined feature-based and statistical method is proposed.

On the Perception of Religious Group Membership from Faces

PubMed Central

Rule, Nicholas O.; Garrett, James V.; Ambady, Nalini

2010-01-01

Background The study of social categorization has largely been confined to examining groups distinguished by perceptually obvious cues. Yet many ecologically important group distinctions are less clear, permitting insights into the general processes involved in person perception. Although religious group membership is thought to be perceptually ambiguous, folk beliefs suggest that Mormons and non-Mormons can be categorized from their appearance. We tested whether Mormons could be distinguished from non-Mormons and investigated the basis for this effect to gain insight to how subtle perceptual cues can support complex social categorizations. Methodology/Principal Findings Participants categorized Mormons' and non-Mormons' faces or facial features according to their group membership. Individuals could distinguish between the two groups significantly better than chance guessing from their full faces and faces without hair, with eyes and mouth covered, without outer face shape, and inverted 180°; but not from isolated features (i.e., eyes, nose, or mouth). Perceivers' estimations of their accuracy did not match their actual accuracy. Exploration of the remaining features showed that Mormons and non-Mormons significantly differed in perceived health and that these perceptions were related to perceptions of skin quality, as demonstrated in a structural equation model representing the contributions of skin color and skin texture. Other judgments related to health (facial attractiveness, facial symmetry, and structural aspects related to body weight) did not differ between the two groups. Perceptions of health were also responsible for differences in perceived spirituality, explaining folk hypotheses that Mormons are distinct because they appear more spiritual than non-Mormons. Conclusions/Significance Subtle markers of group membership can influence how others are perceived and categorized. Perceptions of health from non-obvious and minimal cues distinguished individuals according to their religious group membership. These data illustrate how the non-conscious detection of very subtle differences in others' appearances supports cognitively complex judgments such as social categorization. PMID:21151864

Color and chemistry on Triton

NASA Technical Reports Server (NTRS)

Thompson, W. Reid; Sagan, Carl

1990-01-01

The surface of Triton is very bright but shows subtle yellow to peach hues which probably arise from the production of colored organic compounds from CH4 + N2 and other simple species. In order to investigate possible relationships between chemical processes and the observed surface distribution of chromophores, the surface units are classified according to color/albedo properties, the rates of production of organic chromophores by the action of ultraviolet light and high-energy charged particles is estimated, and rates, spectral properties, and expected seasonal redistribution processes are compared to suggest possible origins of the colors seen on Triton's surface.

Digitally enhanced GLORIA images for petroleum exploration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Prindle, R.O.; Lanz, K

1990-05-01

This poster presentation graphically depicts the geological and structural information that can be derived from digitally enhanced Geological Long Range Inclined Asdic (GLORIA) sonar images. This presentation illustrates the advantages of scale enlargement as an interpreter's tool in an offshore area within the Eel River Basin, Northern California. Sonographs were produced from digital tapes originally collected for the exclusive economic zone (EEZ)-SCAN 1984 survey, which was published in the Atlas of the Western Conterminous US at a scale of 1:500,000. This scale is suitable for displaying regional offshore tectonic features but does not have the resolution required for detailed geologicalmore » mapping necessary for petroleum exploration. Applications of digital enhancing techniques which utilize contrast stretching and assign false colors to wide-swath sonar imagery (approximately 40 km) with 50-m resolution enables the acquisition and interpretation of significantly more geological and structural data. This, combined with a scale enlargement to 1:100,000 and high contrast contact prints vs. the offset prints of the atlas, increases the resolution and sharpness of bathymetric features so that many more subtle features may be mapped in detail. A tectonic interpretation of these digitally enhanced GLORIA sonographs from the Eel River basin is presented, displaying anticlines, lineaments, ridge axis, pathways of sediment flow, and subtle doming. Many of these features are not present on published bathymetric maps and have not been derived from seismic data because the plan view spatial resolution is much less than that available from the GLORIA imagery.« less

Understanding Climate Trends Using IR Brightness Temperature Spectra from AIRS, IASI and CrIS

NASA Astrophysics Data System (ADS)

Deslover, D. H.; Nikolla, E.; Knuteson, R. O.; Revercomb, H. E.; Tobin, D. C.

2016-12-01

NASA's Atmospheric Infrared Sounder (AIRS) provides a data record that extends from its 2002 launch to the present. The Infrared Atmospheric Sounding Interferometer (IASI) onboard Metop- (A launched in 2006, B in 2012), as well as the Joint Polar Satellite System (JPSS) Cross-track Infrared Sounder (CrIS) launched in 2011, complement this data record. Future infrared sounders with similar capabilities will augment these measurements into the near future. We have created a global data set from these infrared measurements, using the nadir-most observations for each of the aforementioned instruments. We can filter the data based upon spatial, diurnal and seasonal properties to discern trends for a given spectral channel and, therefore, a specific atmospheric layer. Subtle differences between spectral sampling among the three instruments can lead significant differences in the resultant probability distribution functions for similar spectral channels. We take advantage of the higher (0.25 cm-1) IASI spectral resolution to subsample the IASI spectra onto AIRS and CrIS spectral grids to better compare AIRS/IASI and CrIS/IASI trends in the brightness temperature anomalies. To better understand the dependance of trace gases on the measured brightness temperature spectral time-series, a companion study has utilized coincident vertical profiles of stratospheric carbon dioxide, water vapor and ozone concentration are used to infer a correlation with the CrIS brightness temperatures. The goal was to investigate the role of ozone heating and carbon dioxide cooling on the observed brightness temperature spectra. Results from that study will be presented alongside the climate trend analysis.

Algorithms for Spectral Decomposition with Applications to Optical Plume Anomaly Detection

NASA Technical Reports Server (NTRS)

Srivastava, Askok N.; Matthews, Bryan; Das, Santanu

2008-01-01

The analysis of spectral signals for features that represent physical phenomenon is ubiquitous in the science and engineering communities. There are two main approaches that can be taken to extract relevant features from these high-dimensional data streams. The first set of approaches relies on extracting features using a physics-based paradigm where the underlying physical mechanism that generates the spectra is used to infer the most important features in the data stream. We focus on a complementary methodology that uses a data-driven technique that is informed by the underlying physics but also has the ability to adapt to unmodeled system attributes and dynamics. We discuss the following four algorithms: Spectral Decomposition Algorithm (SDA), Non-Negative Matrix Factorization (NMF), Independent Component Analysis (ICA) and Principal Components Analysis (PCA) and compare their performance on a spectral emulator which we use to generate artificial data with known statistical properties. This spectral emulator mimics the real-world phenomena arising from the plume of the space shuttle main engine and can be used to validate the results that arise from various spectral decomposition algorithms and is very useful for situations where real-world systems have very low probabilities of fault or failure. Our results indicate that methods like SDA and NMF provide a straightforward way of incorporating prior physical knowledge while NMF with a tuning mechanism can give superior performance on some tests. We demonstrate these algorithms to detect potential system-health issues on data from a spectral emulator with tunable health parameters.

Separable spectro-temporal Gabor filter bank features: Reducing the complexity of robust features for automatic speech recognition.

PubMed

Schädler, Marc René; Kollmeier, Birger

2015-04-01

To test if simultaneous spectral and temporal processing is required to extract robust features for automatic speech recognition (ASR), the robust spectro-temporal two-dimensional-Gabor filter bank (GBFB) front-end from Schädler, Meyer, and Kollmeier [J. Acoust. Soc. Am. 131, 4134-4151 (2012)] was de-composed into a spectral one-dimensional-Gabor filter bank and a temporal one-dimensional-Gabor filter bank. A feature set that is extracted with these separate spectral and temporal modulation filter banks was introduced, the separate Gabor filter bank (SGBFB) features, and evaluated on the CHiME (Computational Hearing in Multisource Environments) keywords-in-noise recognition task. From the perspective of robust ASR, the results showed that spectral and temporal processing can be performed independently and are not required to interact with each other. Using SGBFB features permitted the signal-to-noise ratio (SNR) to be lowered by 1.2 dB while still performing as well as the GBFB-based reference system, which corresponds to a relative improvement of the word error rate by 12.8%. Additionally, the real time factor of the spectro-temporal processing could be reduced by more than an order of magnitude. Compared to human listeners, the SNR needed to be 13 dB higher when using Mel-frequency cepstral coefficient features, 11 dB higher when using GBFB features, and 9 dB higher when using SGBFB features to achieve the same recognition performance.

Spectral properties near the Mott transition in the two-dimensional t-J model with next-nearest-neighbor hopping

NASA Astrophysics Data System (ADS)

Kohno, Masanori

2018-05-01

The single-particle spectral properties of the two-dimensional t-J model with next-nearest-neighbor hopping are investigated near the Mott transition by using cluster perturbation theory. The spectral features are interpreted by considering the effects of the next-nearest-neighbor hopping on the shift of the spectral-weight distribution of the two-dimensional t-J model. Various anomalous features observed in hole-doped and electron-doped high-temperature cuprate superconductors are collectively explained in the two-dimensional t-J model with next-nearest-neighbor hopping near the Mott transition.

Exploring the relationship between vegetation spectra and eco-geo-environmental conditions in karst region, Southwest China.

PubMed

Yue, Yuemin; Wang, Kelin; Zhang, Bing; Chen, Zhengchao; Jiao, Quanjun; Liu, Bo; Chen, Hongsong

2010-01-01

Remote sensing of local environmental conditions is not accessible if substrates are covered with vegetation. This study explored the relationship between vegetation spectra and karst eco-geo-environmental conditions. Hyperspectral remote sensing techniques showed that there were significant differences between spectral features of vegetation mainly distributed in karst and non-karst regions, and combination of 1,300- to 2,500-nm reflectance and 400- to 680-nm first-derivative spectra could delineate karst and non-karst vegetation groups. Canonical correspondence analysis (CCA) successfully assessed to what extent the variation of vegetation spectral features can be explained by associated eco-geo-environmental variables, and it was found that soil moisture and calcium carbonate contents had the most significant effects on vegetation spectral features in karst region. Our study indicates that vegetation spectra is tightly linked to eco-geo-environmental conditions and CCA is an effective means of studying the relationship between vegetation spectral features and eco-geo-environmental variables. Employing a combination of spectral and spatial analysis, it is anticipated that hyperspectral imagery can be used in interpreting or mapping eco-geo-environmental conditions covered with vegetation in karst region.

Selected issues connected with determination of requirements of spectral properties of camouflage patterns

NASA Astrophysics Data System (ADS)

Racek, František; Jobánek, Adam; Baláž, Teodor; Krejčí, Jaroslav

2017-10-01

Traditionally spectral reflectance of the material is measured and compared with permitted spectral reflectance boundaries. The boundaries are limited by upper and lower curve of spectral reflectance. The boundaries for unique color has to fulfil the operational requirements as a versatility of utilization through the all year seasons, day and weather condition on one hand and chromatic and spectral matching with background as well as the manufacturability on the other hand. The interval between the boundaries suffers with ambivalent feature. Camouflage pattern producer would be happy to see it much wider, but blending effect into its particular background could be better with narrower tolerance limits. From the point of view of long time user of camouflage pattern battledress, there seems to be another ambivalent feature. Width of the tolerance zone reflecting natural dispersion of spectral reflectance values allows the significant distortions of shape of the spectral curve inside the given boundaries.

Intrinsic fluorescence excitation-emission matrix spectral features of cottonseed protein fractions and the effects of denaturants

USDA-ARS?s Scientific Manuscript database

To better understand the functional and physicochemical properties of cottonseed protein, we investigated the intrinsic fluorescence excitation-emission matrix (EEM) spectral features of cottonseed protein isolate (CSPI) and sequentially extracted water (CSPw) and alkali (CSPa) protein fractions, an...

SPOT satellite mapping of Ice Stream B

NASA Technical Reports Server (NTRS)

Merry, Carolyn J.

1993-01-01

Numerous features of glaciological significance appear on two adjoining SPOT High Resolution Visible (HRV) images that cover the onset region of ice stream B. Many small-scale features, such as crevasses and drift plumes, have been previously observed in aerial photography. Subtle features, such as long flow traces that have not been mapped previously, are also clear in the satellite imagery. Newly discovered features include ladder-like runners and rungs within certain shear margins, flow traces that are parallel to ice flow, unusual crevasse patterns, and flow traces originating within shear margins. An objective of our work is to contribute to an understanding of the genesis of the features observed in satellite imagery. The genetic possibilities for flow traces, other lineations, bands of transverse crevasses, shear margins, mottles, and lumps and warps are described.

Hyperspectral feature mapping classification based on mathematical morphology

NASA Astrophysics Data System (ADS)

Liu, Chang; Li, Junwei; Wang, Guangping; Wu, Jingli

2016-03-01

This paper proposed a hyperspectral feature mapping classification algorithm based on mathematical morphology. Without the priori information such as spectral library etc., the spectral and spatial information can be used to realize the hyperspectral feature mapping classification. The mathematical morphological erosion and dilation operations are performed respectively to extract endmembers. The spectral feature mapping algorithm is used to carry on hyperspectral image classification. The hyperspectral image collected by AVIRIS is applied to evaluate the proposed algorithm. The proposed algorithm is compared with minimum Euclidean distance mapping algorithm, minimum Mahalanobis distance mapping algorithm, SAM algorithm and binary encoding mapping algorithm. From the results of the experiments, it is illuminated that the proposed algorithm's performance is better than that of the other algorithms under the same condition and has higher classification accuracy.

O2 on ganymede: Spectral characteristics and plasma formation mechanisms

USGS Publications Warehouse

Calvin, W.M.; Johnson, R.E.; Spencer, J.R.

1996-01-01

Weak absorption features in the visible reflectance spectrum of Jupiter's satellite Ganymede have been correlated to those observed in the spectrum of molecular oxygen. We examine the spectral characteristics of these absorption features in all phases of O2 and conclude that the molecular oxygen is most likely present at densities similar to the liquid or solid ??-phase. The contribution of O2 to spectral features observed on Ganymede in the near-infrared wavelength region affects the previous estimates of photon pathlength in ice. The concentration of the visible absorption features on the trailing hemisphere of Ganymede suggests an origin due to bombardment by magneto-spheric ions. We derive an approximate O2 formation rate from this mechanism and consider the state of O2 within the surface.

Congenital dysplasias and dwarfism.

PubMed

Clark, R N

1990-11-01

This paper has presented the characteristic features of those types of dwarfism that are manifest at birth. This information has been presented in a fashion that should assist the pediatrician in arriving at an appropriate diagnosis without excessive delay or extensive diagnostic studies. However, variable expressivity may result in subtle presentation and, in those cases, diagnosis may be more challenging.

Black Hole Interior in Quantum Gravity.

PubMed

Nomura, Yasunori; Sanches, Fabio; Weinberg, Sean J

2015-05-22

We discuss the interior of a black hole in quantum gravity, in which black holes form and evaporate unitarily. The interior spacetime appears in the sense of complementarity because of special features revealed by the microscopic degrees of freedom when viewed from a semiclassical standpoint. The relation between quantum mechanics and the equivalence principle is subtle, but they are still consistent.

An Extended Spectral-Spatial Classification Approach for Hyperspectral Data

NASA Astrophysics Data System (ADS)

Akbari, D.

2017-11-01

In this paper an extended classification approach for hyperspectral imagery based on both spectral and spatial information is proposed. The spatial information is obtained by an enhanced marker-based minimum spanning forest (MSF) algorithm. Three different methods of dimension reduction are first used to obtain the subspace of hyperspectral data: (1) unsupervised feature extraction methods including principal component analysis (PCA), independent component analysis (ICA), and minimum noise fraction (MNF); (2) supervised feature extraction including decision boundary feature extraction (DBFE), discriminate analysis feature extraction (DAFE), and nonparametric weighted feature extraction (NWFE); (3) genetic algorithm (GA). The spectral features obtained are then fed into the enhanced marker-based MSF classification algorithm. In the enhanced MSF algorithm, the markers are extracted from the classification maps obtained by both SVM and watershed segmentation algorithm. To evaluate the proposed approach, the Pavia University hyperspectral data is tested. Experimental results show that the proposed approach using GA achieves an approximately 8 % overall accuracy higher than the original MSF-based algorithm.

A method for fast selecting feature wavelengths from the spectral information of crop nitrogen

USDA-ARS?s Scientific Manuscript database

Research on a method for fast selecting feature wavelengths from the nitrogen spectral information is necessary, which can determine the nitrogen content of crops. Based on the uniformity of uniform design, this paper proposed an improved particle swarm optimization (PSO) method. The method can ch...

Infrared spectral imaging as a novel approach for histopathological recognition in colon cancer diagnosis

NASA Astrophysics Data System (ADS)

Nallala, Jayakrupakar; Gobinet, Cyril; Diebold, Marie-Danièle; Untereiner, Valérie; Bouché, Olivier; Manfait, Michel; Sockalingum, Ganesh Dhruvananda; Piot, Olivier

2012-11-01

Innovative diagnostic methods are the need of the hour that could complement conventional histopathology for cancer diagnosis. In this perspective, we propose a new concept based on spectral histopathology, using IR spectral micro-imaging, directly applied to paraffinized colon tissue array stabilized in an agarose matrix without any chemical pre-treatment. In order to correct spectral interferences from paraffin and agarose, a mathematical procedure is implemented. The corrected spectral images are then processed by a multivariate clustering method to automatically recover, on the basis of their intrinsic molecular composition, the main histological classes of the normal and the tumoral colon tissue. The spectral signatures from different histological classes of the colonic tissues are analyzed using statistical methods (Kruskal-Wallis test and principal component analysis) to identify the most discriminant IR features. These features allow characterizing some of the biomolecular alterations associated with malignancy. Thus, via a single analysis, in a label-free and nondestructive manner, main changes associated with nucleotide, carbohydrates, and collagen features can be identified simultaneously between the compared normal and the cancerous tissues. The present study demonstrates the potential of IR spectral imaging as a complementary modern tool, to conventional histopathology, for an objective cancer diagnosis directly from paraffin-embedded tissue arrays.

Application of multispectral photography to mineral and land resources of South Carolina

NASA Technical Reports Server (NTRS)

Olson, N. K. (Principal Investigator)

1975-01-01

The author has identified the following significant results. Good results were obtained from using Skylab photography in conjunction with LANDSAT imagery for visual interpretation of various geologic features, particularly lineaments. It was concluded that visual interpretation alone of Skylab photographs was quite limited, and much of this was because of the low contrast, heavily vegetated terrain in southeastern United States. Lineaments of major structural features are detectable but subtle. An intimate knowledge of the geologic field relationships is needed before a meaningful analysis is feasible using current satellite photography alone.

Blood characterization using UV/vis spectroscopy

NASA Astrophysics Data System (ADS)

Mattley, Yvette D.; Mitrani-Gold, F.; Orton, S.; Bacon, Christina P.; Leparc, German F.; Bayona, M.; Potter, Robert L.; Garcia-Rubio, Luis H.

1995-05-01

The current methods used for typing blood involve an agglutination reaction which results from the association of specific antibodies with antigens present on the erythrocyte cell surface. While this method is effective, it requires involved laboratory procedures to detect the cell surface antigens. As an alternative technique, uv/vis spectroscopy has been investigated as a novel way to characterize and differentiate the blood types. Typing with this technique is based on spectral differences which appear throughout portions of both the ultraviolet and visible range. The origin of these spectral differences is unknown and presently under investigation. They may be due to intrinsic absorption differences at the molecular level, and/or they may be due to scattering differences brought about by either subtle variation in cell surface characteristics, cell shape or state of aggregation. As the background optical density in these samples is identified and accounted for, the spectral differences become more defined. This work and the continuation of this project will be included in a general database encompassing a wide range of blood samples. In addition, long term goals involve the investigation of diseased blood with the potential of providing a more rapid diagnosis for blood borne pathogens.

EEG resolutions in detecting and decoding finger movements from spectral analysis

PubMed Central

Xiao, Ran; Ding, Lei

2015-01-01

Mu/beta rhythms are well-studied brain activities that originate from sensorimotor cortices. These rhythms reveal spectral changes in alpha and beta bands induced by movements of different body parts, e.g., hands and limbs, in electroencephalography (EEG) signals. However, less can be revealed in them about movements of different fine body parts that activate adjacent brain regions, such as individual fingers from one hand. Several studies have reported spatial and temporal couplings of rhythmic activities at different frequency bands, suggesting the existence of well-defined spectral structures across multiple frequency bands. In the present study, spectral principal component analysis (PCA) was applied on EEG data, obtained from a finger movement task, to identify cross-frequency spectral structures. Features from identified spectral structures were examined in their spatial patterns, cross-condition pattern changes, detection capability of finger movements from resting, and decoding performance of individual finger movements in comparison to classic mu/beta rhythms. These new features reveal some similar, but more different spatial and spectral patterns as compared with classic mu/beta rhythms. Decoding results further indicate that these new features (91%) can detect finger movements much better than classic mu/beta rhythms (75.6%). More importantly, these new features reveal discriminative information about movements of different fingers (fine body-part movements), which is not available in classic mu/beta rhythms. The capability in decoding fingers (and hand gestures in the future) from EEG will contribute significantly to the development of non-invasive BCI and neuroprosthesis with intuitive and flexible controls. PMID:26388720

Bipolar gas outflow from the nova V458 Vul

NASA Astrophysics Data System (ADS)

Goranskij, V. P.; Barsukova, E. A.; Fatkhullin, T. A.

2010-06-01

Classical nova V458 Vul (N Vul 2007 No.1) was detected as a supersoft X-ray source by the Swift XRT (ATel#1246, #1603). This star is interesting with its spectral class change: features of Fe II class nova completely changed by features of He/N class in the SSS phase (T.N. Tarasova, IBVS No.5807). We performed spectral observations of V458 Vul with the Russian 6-m telescope BTA and spectral camera SCORPIO on 2010 June 9.84 UT.

Surface materials map of Afghanistan: carbonates, phyllosilicates, sulfates, altered minerals, and other materials

USGS Publications Warehouse

Kokaly, Raymond F.; King, Trude V.V.; Hoefen, Todd M.; Dudek, Kathleen B.; Livo, Keith E.

2012-01-01

This map shows the distribution of selected carbonates, phyllosilicates, sulfates, altered minerals, and other materials derived from analysis of HyMap imaging spectrometer data of Afghanistan. Using a NASA (National Aeronautics and Space Administration) WB-57 aircraft flown at an altitude of ~15,240 meters or ~50,000 feet, 218 flight lines of data were collected over Afghanistan between August 22 and October 2, 2007. The HyMap data were converted to apparent surface reflectance, then further empirically adjusted using ground-based reflectance measurements. The reflectance spectrum of each pixel of HyMap data was compared to the spectral features of reference entries in a spectral library of minerals, vegetation, water, ice, and snow. This map shows the spatial distribution of minerals that have diagnostic absorption features in the shortwave infrared wavelengths. These absorption features result primarily from characteristic chemical bonds and mineralogical vibrations. Several criteria, including (1) the reliability of detection and discrimination of minerals using the HyMap spectrometer data, (2) the relative abundance of minerals, and (3) the importance of particular minerals to studies of Afghanistan's natural resources, guided the selection of entries in the reference spectral library and, therefore, guided the selection of mineral classes shown on this map. Minerals occurring abundantly at the surface and those having unique spectral features were easily detected and discriminated. Minerals having similar spectral features were less easily discriminated, especially where the minerals were not particularly abundant and (or) where vegetation cover reduced the absorption strength of mineral features. Complications in reflectance calibration also affected the detection and identification of minerals.

Spectra of Particulate Backscattering in Natural Waters

NASA Technical Reports Server (NTRS)

Gordon, Howard, R.; Lewis, Marlon R.; McLean, Scott D.; Twardowski, Michael S.; Freeman, Scott A.; Voss, Kenneth J.; Boynton, Chris G.

2009-01-01

Hyperspectral profiles of downwelling irradiance and upwelling radiance in natural waters (oligotrophic and mesotrophic) are combined with inverse radiative transfer to obtain high resolution spectra of the absorption coefficient (a) and the backscattering coefficient (bb) of the water and its constituents. The absorption coefficient at the mesotrophic station clearly shows spectral absorption features attributable to several phytoplankton pigments (Chlorophyll a, b, c, and Carotenoids). The backscattering shows only weak spectral features and can be well represented by a power-law variation with wavelength (lambda): b(sub b) approx. Lambda(sup -n), where n is a constant between 0.4 and 1.0. However, the weak spectral features in b(sub b), suggest that it is depressed in spectral regions of strong particle absorption. The applicability of the present inverse radiative transfer algorithm, which omits the influence of Raman scattering, is limited to lambda < 490 nm in oligotrophic waters and lambda < 575 nm in mesotrophic waters.

Spectral Analysis of Breast Cancer on Tissue Microarrays: Seeing Beyond Morphology

DTIC Science & Technology

2005-04-01

Harvey N., Szymanski J.J., Bloch J.J., Mitchell M. investigation of image feature extraction by a genetic algorithm. Proc. SPIE 1999;3812:24-31. 11...automated feature extraction using multiple data sources. Proc. SPIE 2003;5099:190-200. 15 4 Spectral-Spatial Analysis of Urine Cytology Angeletti et al...Appendix Contents: 1. Harvey, N.R., Levenson, R.M., Rimm, D.L. (2003) Investigation of Automated Feature Extraction Techniques for Applications in

IRAS Low Resolution Spectra of Asteroids

NASA Technical Reports Server (NTRS)

Cohen, Martin; Walker, Russell G.

2002-01-01

Optical/near-infrared studies of asteroids are based on reflected sunlight and surface albedo variations create broad spectral features, suggestive of families of materials. There is a significant literature on these features, but there is very little work in the thermal infrared that directly probes the materials emitting on the surfaces of asteroids. We have searched for and extracted 534 thermal spectra of 245 asteroids from the original Dutch (Groningen) archive of spectra observed by the IRAS Low Resolution Spectrometer (LRS). We find that, in general, the observed shapes of the spectral continua are inconsistent with that predicted by the standard thermal model used by IRAS. Thermal models such as proposed by Harris (1998) and Harris et al.(1998) for the near-earth asteroids with the "beaming parameter" in the range of 1.0 to 1.2 best represent the observed spectral shapes. This implies that the IRAS Minor Planet Survey (IMPS, Tedesco, 1992) and the Supplementary IMPS (SIMPS, Tedesco, et al., 2002) derived asteroid diameters are systematically underestimated, and the albedos are overestimated. We have tentatively identified several spectral features that appear to be diagnostic of at least families of materials. The variation of spectral features with taxonomic class hints that thermal infrared spectra can be a valuable tool for taxonomic classification of asteroids.

Probing collective oscillation of d-orbital electrons at the nanoscale

NASA Astrophysics Data System (ADS)

Dhall, Rohan; Vigil-Fowler, Derek; Houston Dycus, J.; Kirste, Ronny; Mita, Seiji; Sitar, Zlatko; Collazo, Ramon; LeBeau, James M.

2018-02-01

Here, we demonstrate that high energy electrons can be used to explore the collective oscillation of s, p, and d orbital electrons at the nanometer length scale. Using epitaxial AlGaN/AlN quantum wells as a test system, we observe the emergence of additional features in the loss spectrum with the increasing Ga content. A comparison of the observed spectra with ab-initio theory reveals that the origin of these spectral features lies in excitations of 3d-electrons contributed by Ga. We find that these modes differ in energy from the valence electron plasmons in Al1-xGaxN due to the different polarizabilities of the d electrons. Finally, we study the dependence of observed spectral features on the Ga content, lending insights into the origin of these spectral features, and their coupling with electron-hole excitations.

Modification of spectral features by nonhuman primates

PubMed Central

Weiss, Daniel J.; Hotchkin, Cara F.; Parks, Susan E.

2017-01-01

Ackermann et al. discuss the lack of evidence for vocal control in nonhuman primates. We suggest that nonhuman primates may be capable of achieving greater vocal control than previously supposed. In support of this assertion, we discuss new evidence that nonhuman primates are capable of modifying spectral features in their vocalizations. PMID:25514964

Analysis of substrate and plant spectral features of semi-arid shrub communities in the Owens Valley, California

NASA Technical Reports Server (NTRS)

Ustin, S. L.; Rock, B. N.; Woodward, R. A.

1986-01-01

Airborne Imaging Spectrometer (AIS) data were analyzed to deduce plant density and species composition in three semi-arid shrub-dominated communities of Owens Valley, CA, occurring on either a sand, granite alluvium, or basalt substrate. The high-spectral resolution AIS data were related to spectra obtained with field portable spectrometers, which in turn were related to plant and soil characteristics of the communities. Many of the dominant species have unique spectral features which permit their identification in AIS pixel images. The canopy-induced shadow may be a major factor influencing substrate spectral properties during fall and winter, because of low sun angles. Moreover, changes in spectral signatures following dormancy and leaf senescence tend to decrease contrasts between the plant community and the geologic substrate, also suggesting that fall and winter are a difficult time of year for spectral analyses.

Design of a multi-spectral imager built using the compressive sensing single-pixel camera architecture

NASA Astrophysics Data System (ADS)

McMackin, Lenore; Herman, Matthew A.; Weston, Tyler

2016-02-01

We present the design of a multi-spectral imager built using the architecture of the single-pixel camera. The architecture is enabled by the novel sampling theory of compressive sensing implemented optically using the Texas Instruments DLP™ micro-mirror array. The array not only implements spatial modulation necessary for compressive imaging but also provides unique diffractive spectral features that result in a multi-spectral, high-spatial resolution imager design. The new camera design provides multi-spectral imagery in a wavelength range that extends from the visible to the shortwave infrared without reduction in spatial resolution. In addition to the compressive imaging spectrometer design, we present a diffractive model of the architecture that allows us to predict a variety of detailed functional spatial and spectral design features. We present modeling results, architectural design and experimental results that prove the concept.

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.

Evidence of differentiated near-surface plutons on Vesta in integrated Dawn color images and spectral datasets

NASA Astrophysics Data System (ADS)

Cheek, L.; Sunshine, J.

2014-07-01

Introduction: Recent analyses of Visible and Infrared Mapping Spectrometer (VIR) data from the Dawn mission [1] revealed isolated areas on the asteroid (4) Vesta that contain enhanced abundances of olivine [2,3]. However, this olivine component is only subtly expressed in the VIR data, superimposed on spectrally dominant pyroxene absorptions. The highly ''mixed'' nature of these spectra is likely due, in part, to the relatively coarse spatial resolution of VIR (˜190 m/pixel in HAMO-2) [4], which averages the spectral characteristics of potentially heterogeneous meter-scale outcrops. The capability to resolve the olivine-enhanced regions at a finer scale may reveal a spectrally-dominant olivine component that would facilitate characterization of 1) the distribution and context of the olivine-enhanced exposures, and 2) the spectral properties of the olivine component, providing clues to mineral composition. In order to access finer spatial scales while preserving the detailed mineralogic information offered by the hyperspectral VIR instrument, we use an approach developed for the Moon by [5] that is based on an inversion of the Spectral Mixture Analysis (SMA) framework [6]. Here, we project the VIR data onto co-located, multispectral Framing Camera (FC) data with a spatial resolution of ˜50 m/pixel (HAMO-2) [7]. The analysis was carried out using georeferenced VIR and FC calibrated mosaics for the olivine-enhanced region containing Bellicia and Arruntia craters in the northern hemisphere of Vesta. The approach produces a set of four calculated VIR end members, as well as a projected image cube that contains a calculated VIR spectrum for each FC pixel in the scene. An important advantage of this approach is that it can be applied to co-located multi- and hyperspectral datasets on other planetary bodies. Initial Results: We find that VIR observations for diverse areas across the scene are well described by the following hyperspectral end members: two spectra resembling pyroxenes, one of which has a subtle ˜600-nm absorption; one spectrum that resembles a pyroxene but displays a somewhat distorted 1000-nm band shape that may be indicative of residual calibration issues in the VIR data; and one spectrum strongly resembling a pure olivine. The olivine-like calculated end member spectrum provides important validation of the interpretation that the spectral character of VIR data in the Bellicia/Arruntia region is due to the spectral influence of an olivine component. In addition, the ˜600-nm feature in one of the calculated pyroxene end members is an unexpected and compelling result. Coordinated petrologic and spectral analyses of unbrecciated eucrites by [8] indicate that a similar ˜600-nm absorption is observable in relatively primitive, Cr-rich pyroxenes. This observation suggested that the presence of a ˜600-nm absorption in remote-sensing data for Dawn may be a straightforward indicator of the presence of primitive materials - a prediction that is borne out in these results. Evaluation of the hyperspectral projected cube reveals that discrete regions of spectrally pure olivine are indeed present throughout the walls of Bellicia and, to a lesser extent, Arruntia. Spectra of the Arruntia ejecta in the projected cube contain less of an olivine component than the walls, but important spatial variations are apparent. In particular, the proximal Arruntia ejecta (< 1 crater radius) appear to contain very little olivine, whereas spectra of the more distal ejecta (> 1 crater radius) do display an apparent olivine component. This observation strongly suggests that the Arruntia impact has revealed a compositionally stratified subsurface, with an enhanced olivine component occurring at slightly deeper levels. Projected spectra displaying pyroxene bands with a superimposed ˜600-nm feature occur primarily on crater walls, often in association with olivine- dominated spectra. The co-occurrence of Cr-rich pyroxene and olivine in this unique region of Vesta suggests that a primitive lithology is locally exposed at the surface. We interpret these observations as indicating the presence of one or more differentiated plutons in the Bellicia/Arruntia region.

Separation of Atmospheric and Surface Spectral Features in Mars Global Surveyor Thermal Emission Spectrometer (TES) Spectra

NASA Technical Reports Server (NTRS)

Smith, Michael D.; Bandfield, Joshua L.; Christensen, Philip R.

2000-01-01

We present two algorithms for the separation of spectral features caused by atmospheric and surface components in Thermal Emission Spectrometer (TES) data. One algorithm uses radiative transfer and successive least squares fitting to find spectral shapes first for atmospheric dust, then for water-ice aerosols, and then, finally, for surface emissivity. A second independent algorithm uses a combination of factor analysis, target transformation, and deconvolution to simultaneously find dust, water ice, and surface emissivity spectral shapes. Both algorithms have been applied to TES spectra, and both find very similar atmospheric and surface spectral shapes. For TES spectra taken during aerobraking and science phasing periods in nadir-geometry these two algorithms give meaningful and usable surface emissivity spectra that can be used for mineralogical identification.

Single-Molecule Spectroscopy Unmasks the Lowest Exciton State of the B850 Assembly in LH2 from Rps. acidophila

PubMed Central

Kunz, Ralf; Timpmann, Kõu; Southall, June; Cogdell, Richard J.; Freiberg, Arvi; Köhler, Jürgen

2014-01-01

We have recorded fluorescence-excitation and emission spectra from single LH2 complexes from Rhodopseudomonas (Rps.) acidophila. Both types of spectra show strong temporal spectral fluctuations that can be visualized as spectral diffusion plots. Comparison of the excitation and emission spectra reveals that for most of the complexes the lowest exciton transition is not observable in the excitation spectra due to the cutoff of the detection filter characteristics. However, from the spectral diffusion plots we have the full spectral and temporal information at hand and can select those complexes for which the excitation spectra are complete. Correlating the red most spectral feature of the excitation spectrum with the blue most spectral feature of the emission spectrum allows an unambiguous assignment of the lowest exciton state. Hence, application of fluorescence-excitation and emission spectroscopy on the same individual LH2 complex allows us to decipher spectral subtleties that are usually hidden in traditional ensemble spectroscopy. PMID:24806933

Spectral reflectance properties (0.4-2.5 um) of secondary Fe-oxide, Fe-hydroxide, and Fe-sulfate-hydrate minerals associated with sulfide-bearing mine waste

USGS Publications Warehouse

Crowley, J.K.; Williams, D.E.; Hammarstrom1, J.M.; Piatak, N.; Mars, J.C.; Chou, I-Ming

2006-01-01

Fifteen Fe-oxide, Fe-hydroxide, and Fe-sulphate-hydrate mineral species commonly associated with sulphide bearing mine wastes were characterized by using X-ray powder diffraction and scanning electron microscope methods. Diffuse reflectance spectra of the samples show diagnostic absorption features related to electronic processes involving ferric and/or ferrous iron, and to vibrational processes involving water and hydroxyl ions. Such spectral features enable field and remote sensing based studies of the mineral distributions. Because secondary minerals are sensitive indicators of pH, Eh, relative humidity, and other environmental conditions, spectral mapping of these minerals promises to have important applications to mine waste remediation studies. This report releases digital (ascii) spectra (spectral_data_files.zip) of the fifteen mineral samples to facilitate usage of the data with spectral libraries and spectral analysis software. The spectral data are provided in a two-column format listing wavelength (in micrometers) and reflectance, respectively.

Study on Remote Sensing Image Characteristics of Ecological Land: Case Study of Original Ecological Land in the Yellow River Delta

NASA Astrophysics Data System (ADS)

An, G. Q.

2018-04-01

Takes the Yellow River Delta as an example, this paper studies the characteristics of remote sensing imagery with dominant ecological functional land use types, compares the advantages and disadvantages of different image in interpreting ecological land use, and uses research results to analyse the changing trend of ecological land in the study area in the past 30 years. The main methods include multi-period, different sensor images and different seasonal spectral curves, vegetation index, GIS and data analysis methods. The results show that the main ecological land in the Yellow River Delta included coastal beaches, saline-alkaline lands, and water bodies. These lands have relatively distinct spectral and texture features. The spectral features along the beach show characteristics of absorption in the green band and reflection in the red band. This feature is less affected by the acquisition year, season, and sensor type. Saline-alkali land due to the influence of some saline-alkaline-tolerant plants such as alkali tent, Tamarix and other vegetation, the spectral characteristics have a certain seasonal changes, winter and spring NDVI index is less than the summer and autumn vegetation index. The spectral characteristics of a water body generally decrease rapidly with increasing wavelength, and the reflectance in the red band increases with increasing sediment concentration. In conclusion, according to the spectral characteristics and image texture features of the ecological land in the Yellow River Delta, the accuracy of image interpretation of such ecological land can be improved.

[The changes in spectral features of the staple-food bamboos of giant panda after flowering].

PubMed

Liu, Xue-Hua; Wu, Yan

2012-12-01

Large-area flowering of the giant pandas' staple food is an important factor which can influence their survival. Therefore, it is necessary to predict the bamboo flowering. Foping Nature Reserve was taken as the study area. The research selected the giant pandas' staple-food bamboos Bashania fargesii, Fargesia qinlingensis and Fargesia dracocephala with different flowering situations (i. e., flowering, potential flowering, non-flowering with far distance) to measure the spectral reflectance of bamboo leaves. We studied the influence of bamboo flowering on the spectral features of three bamboo species through analyzing the original spectral reflectance and their red edge parameters. The results showed that (1) the flowering changed the spectra features of bamboo species. The spectral reflectance of B. fargesii shows a pattern: flowering bamboo < potential flowering bamboo < non-flowering bamboo with far distance, while F. qinlingensis and F. dracocephala show the different pattern: flowering bamboo > or = potential flowering bamboo > non-flowering bamboo with far distance. Among three bamboo species, F. dracocephala showed the greatest change, and then F. qinlingensis. (2) After bamboo flowering, the red edge of B. fargesii has no obvious shifting, while the other two bamboos have distinctive shifting towards the shorter waves. The study found that the original spectral feature and the red edge all changed under various flowering states, which can be used to provide the experimental basis and theoretic support for the future prediction of bamboo flowering through remote sensing.

Effects of band selection on endmember extraction for forestry applications

NASA Astrophysics Data System (ADS)

Karathanassi, Vassilia; Andreou, Charoula; Andronis, Vassilis; Kolokoussis, Polychronis

2014-10-01

In spectral unmixing theory, data reduction techniques play an important role as hyperspectral imagery contains an immense amount of data, posing many challenging problems such as data storage, computational efficiency, and the so called "curse of dimensionality". Feature extraction and feature selection are the two main approaches for dimensionality reduction. Feature extraction techniques are used for reducing the dimensionality of the hyperspectral data by applying transforms on hyperspectral data. Feature selection techniques retain the physical meaning of the data by selecting a set of bands from the input hyperspectral dataset, which mainly contain the information needed for spectral unmixing. Although feature selection techniques are well-known for their dimensionality reduction potentials they are rarely used in the unmixing process. The majority of the existing state-of-the-art dimensionality reduction methods set criteria to the spectral information, which is derived by the whole wavelength, in order to define the optimum spectral subspace. These criteria are not associated with any particular application but with the data statistics, such as correlation and entropy values. However, each application is associated with specific land c over materials, whose spectral characteristics present variations in specific wavelengths. In forestry for example, many applications focus on tree leaves, in which specific pigments such as chlorophyll, xanthophyll, etc. determine the wavelengths where tree species, diseases, etc., can be detected. For such applications, when the unmixing process is applied, the tree species, diseases, etc., are considered as the endmembers of interest. This paper focuses on investigating the effects of band selection on the endmember extraction by exploiting the information of the vegetation absorbance spectral zones. More precisely, it is explored whether endmember extraction can be optimized when specific sets of initial bands related to leaf spectral characteristics are selected. Experiments comprise application of well-known signal subspace estimation and endmember extraction methods on a hyperspectral imagery that presents a forest area. Evaluation of the extracted endmembers showed that more forest species can be extracted as endmembers using selected bands.

Constraining Cometary Crystal Shapes from IR Spectral Features

NASA Technical Reports Server (NTRS)

Wooden, Diane H.; Lindsay, Sean; Harker, David E.; Kelley, Michael S. P.; Woodward, Charles E.; Murphy, James Richard

2013-01-01

A major challenge in deriving the silicate mineralogy of comets is ascertaining how the anisotropic nature of forsterite crystals affects the spectral features' wavelength, relative intensity, and asymmetry. Forsterite features are identified in cometary comae near 10, 11.05-11.2, 16, 19, 23.5, 27.5 and 33 microns [1-10], so accurate models for forsterite's absorption efficiency (Qabs) are a primary requirement to compute IR spectral energy distributions (SEDs, lambdaF lambda vs. lambda) and constrain the silicate mineralogy of comets. Forsterite is an anisotropic crystal, with three crystallographic axes with distinct indices of refraction for the a-, b-, and c-axis. The shape of a forsterite crystal significantly affects its spectral features [13-16]. We need models that account for crystal shape. The IR absorption efficiencies of forsterite are computed using the discrete dipole approximation (DDA) code DDSCAT [11,12]. Starting from a fiducial crystal shape of a cube, we systematically elongate/reduce one of the crystallographic axes. Also, we elongate/reduce one axis while the lengths of the other two axes are slightly asymmetric (0.8:1.2). The most significant grain shape characteristic that affects the crystalline spectral features is the relative lengths of the crystallographic axes. The second significant grain shape characteristic is breaking the symmetry of all three axes [17]. Synthetic spectral energy distributions using seven crystal shape classes [17] are fit to the observed SED of comet C/1995 O1 (Hale-Bopp). The Hale-Bopp crystalline residual better matches equant, b-platelets, c-platelets, and b-columns spectral shape classes, while a-platelets, a-columns and c-columns worsen the spectral fits. Forsterite condensation and partial evaporation experiments demonstrate that environmental temperature and grain shape are connected [18-20]. Thus, grain shape is a potential probe for protoplanetary disk temperatures where the cometary crystalline forsterite formed. The forsterite crystal shapes (equant, b-platelets, c-platelets, b-columns - excluding a- and c-columns) derived from our modeling [17] of comet Hale- Bopp, compared to laboratory synthesis experiments [18], suggests that these crystals are high temperature condensates. By observing and modeling the crystalline features in comet ISON, we may constrain forsterite crystal shape(s) and link to their formation temperature(s) and environment(s).

Skin condition measurement by using multispectral imaging system (Conference Presentation)

NASA Astrophysics Data System (ADS)

Jung, Geunho; Kim, Sungchul; Kim, Jae Gwan

2017-02-01

There are a number of commercially available low level light therapy (LLLT) devices in a market, and face whitening or wrinkle reduction is one of targets in LLLT. The facial improvement could be known simply by visual observation of face, but it cannot provide either quantitative data or recognize a subtle change. Clinical diagnostic instruments such as mexameter can provide a quantitative data, but it costs too high for home users. Therefore, we designed a low cost multi-spectral imaging device by adding additional LEDs (470nm, 640nm, white LED, 905nm) to a commercial USB microscope which has two LEDs (395nm, 940nm) as light sources. Among various LLLT skin treatments, we focused on getting melanin and wrinkle information. For melanin index measurements, multi-spectral images of nevus were acquired and melanin index values from color image (conventional method) and from multi-spectral images were compared. The results showed that multi-spectral analysis of melanin index can visualize nevus with a different depth and concentration. A cross section of wrinkle on skin resembles a wedge which can be a source of high frequency components when the skin image is Fourier transformed into a spatial frequency domain map. In that case, the entropy value of the spatial frequency map can represent the frequency distribution which is related with the amount and thickness of wrinkle. Entropy values from multi-spectral images can potentially separate the percentage of thin and shallow wrinkle from thick and deep wrinkle. From the results, we found that this low cost multi-spectral imaging system could be beneficial for home users of LLLT by providing the treatment efficacy in a quantitative way.

Features and dimensions of the Hayward Fault Zone in the Strawberry and Blackberry Creek Area, Berkeley, California

DOE Office of Scientific and Technical Information (OSTI.GOV)

Williams, P.L.

1995-03-01

This report presents an examination of the geometry of the Hayward fault adjacent to the Lawrence Berkeley Laboratory and University of California campuses in central Berkeley. The fault crosses inside the eastern border of the UC campus. Most subtle geomorphic (landform) expressions of the fault have been removed by development and by the natural processes of landsliding and erosion. Some clear expressions of the fault remain however, and these are key to mapping the main trace through the campus area. In addition, original geomorphic evidence of the fault`s location was recovered from large scale mapping of the site dating frommore » 1873 to 1897. Before construction obscured and removed natural landforms, the fault was expressed by a linear, northwest-tending zone of fault-related geomorphic features. There existed well-defined and subtle stream offsets and beheaded channels, fault scarps, and a prominent ``shutter ridge``. To improve our confidence in fault locations interpreted from landforms, we referred to clear fault exposures revealed in trenching, revealed during the construction of the Foothill Housing Complex, and revealed along the length of the Lawson Adit mining tunnel. Also utilized were the locations of offset cultural features. At several locations across the study area, distress features in buildings and streets have been used to precisely locate the fault. Recent published mapping of the fault (Lienkaemper, 1992) was principally used for reference to evidence of the fault`s location to the northwest and southeast of Lawrence Berkeley Laboratory.« less

Research on oral test modeling based on multi-feature fusion

NASA Astrophysics Data System (ADS)

Shi, Yuliang; Tao, Yiyue; Lei, Jun

2018-04-01

In this paper, the spectrum of speech signal is taken as an input of feature extraction. The advantage of PCNN in image segmentation and other processing is used to process the speech spectrum and extract features. And a new method combining speech signal processing and image processing is explored. At the same time of using the features of the speech map, adding the MFCC to establish the spectral features and integrating them with the features of the spectrogram to further improve the accuracy of the spoken language recognition. Considering that the input features are more complicated and distinguishable, we use Support Vector Machine (SVM) to construct the classifier, and then compare the extracted test voice features with the standard voice features to achieve the spoken standard detection. Experiments show that the method of extracting features from spectrograms using PCNN is feasible, and the fusion of image features and spectral features can improve the detection accuracy.

The Influence of Social Cues and Cognitive Processes in Computer Mediated Second Language Learning

ERIC Educational Resources Information Center

Murakami, Janel Rachel Goodman

2017-01-01

This dissertation investigated the effects of technological mediation on second language (L2) learning, focusing, as a case study, on gains in listening perception of the subtle but important feature of pitch placement in Japanese. Pitch accent can be difficult to perceive for non-native speakers whose first language (L1) does not rely on pitch or…

The Breast Health Intervention Evaluation Study

DTIC Science & Technology

2001-08-01

content due to its subtle almost subliminal impact even though this issue did not surface in the various pre-tests during video development. A third...A. (1990). Involuntary attention and physiological arousal evoked by structural features and emotional content in TV commercials. Communication...Human communication research, 13, 399-420. Pezdek, K., and Stevens, E. (1984). Children=s memory for auditory and visual information on television

Detection of CN emission from (2060) Chiron

NASA Technical Reports Server (NTRS)

Bowell, Edward

1991-01-01

Spectrophotometric observations of (2060) Chiron were obtained. Their primary goal was to look for the subtle differences in color between Chiron and its surrounding coma, and to search for possible absorption or emission features in Chiron's spectrum. The presence of the CN(0-0) emission band was identified. It proves Chiron's cometary nature and breaks the record heliocentric distance for cometary gaseous emission.

Evolution of certain typical and atypical features in a case of subacute sclerosing panencephalitis

PubMed Central

Raut, Tushar Premraj; Singh, Maneesh Kumar; Garg, Ravindra Kumar; Rai, Dheeraj

2012-01-01

Subacute sclerosing panencephalitis (SSPE) is a slowly progressive inflammatory disease of the central nervous system caused by a persistent measles virus usually affecting the childhood and adolescent age group. Clinical features at onset are very subtle and non-specific. Certain atypical features can occur at onset or during the course of illness which can be misleading. Neuroimaging features often are non-specific. Features like myoclonic jerks, cognitive decline and typical EEG findings lead to a strong suspicion of SSPE. Here, we describe the stagewise progression of a case of SSPE in a 14-year-old girl who had myoclonic jerks and cognitive decline at onset. During the course of disease, the patient developed cortical vision loss, atypical extrapyramidal features like segmental and hemifacial dystonia ultimately leading to a bedbound vegetative state. EEG showed typical periodic discharges along with positive cerebrospinal fluid serology for measles. PMID:23266775

Evolution of certain typical and atypical features in a case of subacute sclerosing panencephalitis.

PubMed

Raut, Tushar Premraj; Singh, Maneesh Kumar; Garg, Ravindra Kumar; Rai, Dheeraj

2012-12-23

Subacute sclerosing panencephalitis (SSPE) is a slowly progressive inflammatory disease of the central nervous system caused by a persistent measles virus usually affecting the childhood and adolescent age group. Clinical features at onset are very subtle and non-specific. Certain atypical features can occur at onset or during the course of illness which can be misleading. Neuroimaging features often are non-specific. Features like myoclonic jerks, cognitive decline and typical EEG findings lead to a strong suspicion of SSPE. Here, we describe the stagewise progression of a case of SSPE in a 14-year-old girl who had myoclonic jerks and cognitive decline at onset. During the course of disease, the patient developed cortical vision loss, atypical extrapyramidal features like segmental and hemifacial dystonia ultimately leading to a bedbound vegetative state. EEG showed typical periodic discharges along with positive cerebrospinal fluid serology for measles.

Contamination of the 5394 Å spectral region by telluric lines

NASA Astrophysics Data System (ADS)

Vince, I.; Vince, O.

2010-11-01

The spectral region in the vicinity of 5394 Å contains three prominent photospheric spectral lines, which can be used as a solar plasma diagnostic tool. The occurrence of telluric lines in this region is a potential source of systematic and random errors in these solar spectral lines. The goal of our investigation was to determine the telluric line contamination of this interesting spectral region. Several series of high-resolution solar spectra within an interval of about 4 Å around the 5394 Å wavelength were observed at different zenith distances of the Sun. Comparison of these spectra has permitted identification of telluric lines in this spectral interval. The observations were carried out with the horizontal solar spectrograph of the Heliophysical Observatory in Debrecen. Telluric feature blending was identified in the blue and red wings of the Fe I 5393.2 Å line, and in the local continuum of the Mn I 5394.7 Å line. The blue wing of the Fe I 5395.2 Å line is contaminated by a weak telluric feature too. The red continuum of this line has a more prominent telluric contamination. A dozen of water vapor telluric lines that determined the observed telluric features were identified in this spectral interval. The profiles of three telluric lines that have a significant influence on both the profiles of solar spectral lines and the level of local continuum were derived, and the variation of their parameters (equivalent width and central depth) with air mass were analyzed.

An oil film information retrieval method overcoming the influence of sun glitter, based on AISA+ airborne hyper-spectral image

NASA Astrophysics Data System (ADS)

Zhan, Yuanzeng; Mao, Tianming; Gong, Fang; Wang, Difeng; Chen, Jianyu

2010-10-01

As an effective survey tool for oil spill detection, the airborne hyper-spectral sensor affords the potentiality for retrieving the quantitative information of oil slick which is useful for the cleanup of spilled oil. But many airborne hyper-spectral images are affected by sun glitter which distorts radiance values and spectral ratios used for oil slick detection. In 2005, there's an oil spill event leaking at oil drilling platform in The South China Sea, and an AISA+ airborne hyper-spectral image recorded this event will be selected for studying in this paper, which is affected by sun glitter terribly. Through a spectrum analysis of the oil and water samples, two features -- "spectral rotation" and "a pair of fixed points" can be found in spectral curves between crude oil film and water. Base on these features, an oil film information retrieval method which can overcome the influence of sun glitter is presented. Firstly, the radiance of the image is converted to normal apparent reflectance (NormAR). Then, based on the features of "spectral rotation" (used for distinguishing oil film and water) and "a pair of fixed points" (used for overcoming the effect of sun glitter), NormAR894/NormAR516 is selected as an indicator of oil film. Finally, by using a threshold combined with the technologies of image filter and mathematic morphology, the distribution and relative thickness of oil film are retrieved.

A switch from parallel to antiparallel strand orientation in a coiled-coil X-ray structure via two core hydrophobic mutations

DOE PAGES

Malashkevich, Vladimir N.; Higgins, Chelsea D.; Almo, Steven C.; ...

2015-05-06

The coiled-coil is one of the most ubiquitous and well studied protein structural motifs. Significant effort has been devoted to dissecting subtle variations of the typical heptad repeat sequence pattern that can designate larger topological features such as relative α-helical orientation and oligomer size. Here in this paper we report the X-ray structure of a model coiled-coil peptide, HA2-Del-L2seM, which forms an unanticipated core antiparallel dimer with potential sites for discrete higher-order multimerization (trimer or tetramer). In the X-ray structure, a third, partially-ordered α-helix is weakly associated with the antiparallel dimer and analytical ultracentrifugation experiments indicate the peptide forms amore » well-defined tetramer in solution. The HA2-Del-L2seM sequence is closely related to a parent model peptide, HA2-Del, which we previously reported adopts a parallel trimer; HA2-Del-L2seM differs by only hydrophobic leucine to selenomethione mutations and thus this subtle difference is sufficient to switch both relative α-helical topology and number of α-helices participating in the coiled-coil. Comparison of the X-ray structures of HA2-Del-L2seM (reported here) with the HA2-Del parent (reported previously) reveals novel interactions involving the selenomethionine residues that promote antiparallel coiled-coil configuration and preclude parallel trimer formation. Finally, these novel atomic insights are instructive for understanding subtle features that can affect coiled-coil topology and provide additional information for design of antiparallel coiled-coils.« less

Diagnosing subtle palatal anomalies: Validation of video-analysis and assessment protocol for diagnosing occult submucous cleft palate.

PubMed

Rourke, Ryan; Weinberg, Seth M; Marazita, Mary L; Jabbour, Noel

2017-09-01

Submucous cleft palate (SMCP) classically involves bifid uvula, zona pellucida, and notched hard palate. However, patients may present with more subtle anatomic abnormalities. The ability to detect these abnormalities is important for surgeons managing velopharyngeal dysfunction (VPD) or considering adenoidectomy. Validate an assessment protocol for diagnosis of occult submucous cleft palate (OSMCP) and identify physical examination features present in patients with OSMCP in the relaxed and activated palate positions. Study participants included patients referred to a pediatric VPD clinic with concern for hypernasality or SMCP. Using an appropriately encrypted iPod touch, transoral video was obtained for each patient with the palate in the relaxed and activated positions. The videos were reviewed by two otolaryngologists in normal speed and slow-motion, as needed, and a questionnaire was completed by each reviewer pertaining to the anatomy and function of the palate. 47 patients, with an average age of 4.6 years, were included in the study over a one-year period. Four videos were unusable due to incomplete view of the palate. The most common palatal abnormality noted was OSMCP, diagnosed by each reviewer in 26/43 and 30/43 patients respectively. Using the assessment protocol, agreement on palatal diagnosis was 83.7% (kappa = 0.68), indicating substantial agreement, with the most prevalent anatomic features being vaulted palate elevation (96%) and visible notching of hard palate (75%). The diagnosis of subtle palatal anomalies is difficult and can be subjective. Using the proposed video-analysis method and assessment protocol may improve reliability of diagnosis of OSMCP. Copyright © 2017 Elsevier B.V. All rights reserved.

Characterization of protein and carbohydrate mid-IR spectral features in crop residues

NASA Astrophysics Data System (ADS)

Xin, Hangshu; Zhang, Yonggen; Wang, Mingjun; Li, Zhongyu; Wang, Zhibo; Yu, Peiqiang

2014-08-01

To the best of our knowledge, a few studies have been conducted on inherent structure spectral traits related to biopolymers of crop residues. The objective of this study was to characterize protein and carbohydrate structure spectral features of three field crop residues (rice straw, wheat straw and millet straw) in comparison with two crop vines (peanut vine and pea vine) by using Fourier transform infrared spectroscopy (FTIR) technique with attenuated total reflectance (ATR). Also, multivariate analyses were performed on spectral data sets within the regions mainly related to protein and carbohydrate in this study. The results showed that spectral differences existed in mid-IR peak intensities that are mainly related to protein and carbohydrate among these crop residue samples. With regard to protein spectral profile, peanut vine showed the greatest mid-IR band intensities that are related to protein amide and protein secondary structures, followed by pea vine and the rest three field crop straws. The crop vines had 48-134% higher spectral band intensity than the grain straws in spectral features associated with protein. Similar trends were also found in the bands that are mainly related to structural carbohydrates (such as cellulosic compounds). However, the field crop residues had higher peak intensity in total carbohydrates region than the crop vines. Furthermore, spectral ratios varied among the residue samples, indicating that these five crop residues had different internal structural conformation. However, multivariate spectral analyses showed that structural similarities still exhibited among crop residues in the regions associated with protein biopolymers and carbohydrate. Further study is needed to find out whether there is any relationship between spectroscopic information and nutrition supply in various kinds of crop residue when fed to animals.

Characterization of protein and carbohydrate mid-IR spectral features in crop residues.

PubMed

Xin, Hangshu; Zhang, Yonggen; Wang, Mingjun; Li, Zhongyu; Wang, Zhibo; Yu, Peiqiang

2014-08-14

To the best of our knowledge, a few studies have been conducted on inherent structure spectral traits related to biopolymers of crop residues. The objective of this study was to characterize protein and carbohydrate structure spectral features of three field crop residues (rice straw, wheat straw and millet straw) in comparison with two crop vines (peanut vine and pea vine) by using Fourier transform infrared spectroscopy (FTIR) technique with attenuated total reflectance (ATR). Also, multivariate analyses were performed on spectral data sets within the regions mainly related to protein and carbohydrate in this study. The results showed that spectral differences existed in mid-IR peak intensities that are mainly related to protein and carbohydrate among these crop residue samples. With regard to protein spectral profile, peanut vine showed the greatest mid-IR band intensities that are related to protein amide and protein secondary structures, followed by pea vine and the rest three field crop straws. The crop vines had 48-134% higher spectral band intensity than the grain straws in spectral features associated with protein. Similar trends were also found in the bands that are mainly related to structural carbohydrates (such as cellulosic compounds). However, the field crop residues had higher peak intensity in total carbohydrates region than the crop vines. Furthermore, spectral ratios varied among the residue samples, indicating that these five crop residues had different internal structural conformation. However, multivariate spectral analyses showed that structural similarities still exhibited among crop residues in the regions associated with protein biopolymers and carbohydrate. Further study is needed to find out whether there is any relationship between spectroscopic information and nutrition supply in various kinds of crop residue when fed to animals. Copyright © 2014 Elsevier B.V. All rights reserved.

Mapping the Similarities of Spectra: Global and Locally-biased Approaches to SDSS Galaxies

NASA Astrophysics Data System (ADS)

Lawlor, David; Budavári, Tamás; Mahoney, Michael W.

2016-12-01

We present a novel approach to studying the diversity of galaxies. It is based on a novel spectral graph technique, that of locally-biased semi-supervised eigenvectors. Our method introduces new coordinates that summarize an entire spectrum, similar to but going well beyond the widely used Principal Component Analysis (PCA). Unlike PCA, however, this technique does not assume that the Euclidean distance between galaxy spectra is a good global measure of similarity. Instead, we relax that condition to only the most similar spectra, and we show that doing so yields more reliable results for many astronomical questions of interest. The global variant of our approach can identify very finely numerous astronomical phenomena of interest. The locally-biased variants of our basic approach enable us to explore subtle trends around a set of chosen objects. The power of the method is demonstrated in the Sloan Digital Sky Survey Main Galaxy Sample, by illustrating that the derived spectral coordinates carry an unprecedented amount of information.

Cardiac reserve during weightlessness simulation and shuttle flight

NASA Technical Reports Server (NTRS)

Goldberger, A. L.

1985-01-01

Bedrest deconditioning is suspected to reduce cardiac function. However, quantitation of subtle decreases in cardiac reserve may be difficult. Normal subjects show considerable variability in heart rate response, reflected by a relatively broadband interbeat interval power spectrum. We hypothesized that the deconditioning effects of bedrest would induce narrowing of this spectrum, reflecting a reduction in the autonomically-modulated variability in heart rate. Ten aerobically conditioned men (average 35-50 years) underwent orthostatic tolerance testing with lower body negative pressure pre-bedrest and after 10 days of bedrest, while on placebo and after intravenous atropine. Spectra were derived by Fourier analysis of 128 interbeat interval data sets from subjects with sufficient numbers of beats during matched periods of the protocol. Data suggest that atropine unmasks the deconditioning effect of bedrest in athletic men, evidenced by a reduction in interbeat interval spectral power compared with placebo. Spectral analysis offers a new means of quantitating the effects of bedrest deconditioning and autonomic perturbations on cardiac dynamics.

Landsat thematic mapper (TM) soil variability analysis over Webster County, Iowa

NASA Technical Reports Server (NTRS)

Thompson, D. R.; Henderson, K. E.; Pitts, D. E.

1984-01-01

Thematic mapper simulator (TMS) data acquired June 7, June 23, and July 31, 1982, and Landsat thematic mapper (TM) data acquired August 2, September 3, and October 21, 1982, over Webster County, Iowa, were examined for within-field soil effects on corn and soybean spectral signatures. It was found that patterns displayed on various computer-generated map products were in close agreement with the detailed soil survey of the area. The difference in spectral values appears to be due to a combination of subtle soil properties and crop growth patterns resulting from the different soil properties. Bands 4 (0.76-.90 micron), 5 (1.55-1.75 micron), and 7 (2.08-2.35 micron) were found to be responding to the within-field soil variability even with increasing ground cover. While these results are preliminary, they do indicate that the soil influence on the vegetation is being detected by TM and should provide improved information relating to crop and soil properties.

Color imaging of Mars by the High Resolution Imaging Science Experiment (HiRISE)

USGS Publications Warehouse

Delamere, W.A.; Tornabene, L.L.; McEwen, A.S.; Becker, K.; Bergstrom, J.W.; Bridges, N.T.; Eliason, E.M.; Gallagher, D.; Herkenhoff, K. E.; Keszthelyi, L.; Mattson, S.; McArthur, G.K.; Mellon, M.T.; Milazzo, M.; Russell, P.S.; Thomas, N.

2010-01-01

HiRISE has been producing a large number of scientifically useful color products of Mars and other planetary objects. The three broad spectral bands, coupled with the highly sensitive 14 bit detectors and time delay integration, enable detection of subtle color differences. The very high spatial resolution of HiRISE can augment the mineralogic interpretations based on multispectral (THEMIS) and hyperspectral datasets (TES, OMEGA and CRISM) and thereby enable detailed geologic and stratigraphic interpretations at meter scales. In addition to providing some examples of color images and their interpretation, we describe the processing techniques used to produce them and note some of the minor artifacts in the output. We also provide an example of how HiRISE color products can be effectively used to expand mineral and lithologic mapping provided by CRISM data products that are backed by other spectral datasets. The utility of high quality color data for understanding geologic processes on Mars has been one of the major successes of HiRISE. ?? 2009 Elsevier Inc.

How Does the Shape of the Stellar Spectrum Affect the Raman Scattering Features in the Albedo of Exoplanets?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Oklopčić, Antonija; Hirata, Christopher M.; Heng, Kevin, E-mail: oklopcic@astro.caltech.edu

The diagnostic potential of the spectral signatures of Raman scattering, imprinted in planetary albedo spectra at short optical wavelengths, has been demonstrated in research on planets in the solar system, and has recently been proposed as a probe of exoplanet atmospheres, complementary to albedo studies at longer wavelengths. Spectral features caused by Raman scattering offer insight into the properties of planetary atmospheres, such as the atmospheric depth, composition, and temperature, as well as the possibility of detecting and spectroscopically identifying spectrally inactive species, such as H{sub 2} and N{sub 2}, in the visible wavelength range. Raman albedo features, however, dependmore » on both the properties of the atmosphere and the shape of the incident stellar spectrum. Identical planetary atmospheres can produce very different albedo spectra depending on the spectral properties of the host star. Here we present a set of geometric albedo spectra calculated for atmospheres with H{sub 2}/He, N{sub 2}, and CO{sub 2} composition, irradiated by different stellar types ranging from late A to late K stars. Prominent albedo features caused by Raman scattering appear at different wavelengths for different types of host stars. We investigate how absorption due to the alkali elements sodium and potassium may affect the intensity of Raman features, and we discuss the preferred strategies for detecting Raman features in future observations.« less

A spectral reflectance estimation technique using multispectral data from the Viking lander camera

NASA Technical Reports Server (NTRS)

Park, S. K.; Huck, F. O.

1976-01-01

A technique is formulated for constructing spectral reflectance curve estimates from multispectral data obtained with the Viking lander camera. The multispectral data are limited to six spectral channels in the wavelength range from 0.4 to 1.1 micrometers and most of these channels exhibit appreciable out-of-band response. The output of each channel is expressed as a linear (integral) function of the (known) solar irradiance, atmospheric transmittance, and camera spectral responsivity and the (unknown) spectral responsivity and the (unknown) spectral reflectance. This produces six equations which are used to determine the coefficients in a representation of the spectral reflectance as a linear combination of known basis functions. Natural cubic spline reflectance estimates are produced for a variety of materials that can be reasonably expected to occur on Mars. In each case the dominant reflectance features are accurately reproduced, but small period features are lost due to the limited number of channels. This technique may be a valuable aid in selecting the number of spectral channels and their responsivity shapes when designing a multispectral imaging system.

Processing of multispectral thermal IR data for geologic applications

NASA Technical Reports Server (NTRS)

Kahle, A. B.; Madura, D. P.; Soha, J. M.

1979-01-01

Multispectral thermal IR data were acquired with a 24-channel scanner flown in an aircraft over the E. Tintic Utah mining district. These digital image data required extensive computer processing in order to put the information into a format useful for a geologic photointerpreter. Simple enhancement procedures were not sufficient to reveal the total information content because the data were highly correlated in all channels. The data were shown to be dominated by temperature variations across the scene, while the much more subtle spectral variations between the different rock types were of interest. The image processing techniques employed to analyze these data are described.

Spectral distortion of the CMB by the cumulative CO emission from galaxies throughout cosmic history

NASA Astrophysics Data System (ADS)

Mashian, Natalie; Loeb, Abraham; Sternberg, Amiel

2016-05-01

We show that the cumulative CO emission from galaxies throughout cosmic history distorts the spectrum of the cosmic microwave background at a level that is well above the detection limit of future instruments, such as the Primordial Inflation Explorer. The modelled CO signal has a prominent bump in the frequency interval 100-200 GHz, with a characteristic peak intensity of ˜2 × 10-23 W m-2 Hz-1 sr-1. Most of the CO foreground originates from modest redshifts, z ˜ 2-5, and needs to be efficiently removed for more subtle distortions from the earlier Universe to be detected.

Probing the electronic and local structural changes across the pressure-induced insulator-to-metal transition in VO2

NASA Astrophysics Data System (ADS)

Marini, C.; Bendele, M.; Joseph, B.; Kantor, I.; Mitrano, M.; Mathon, O.; Baldini, M.; Malavasi, L.; Pascarelli, S.; Postorino, P.

2014-11-01

Local and electronic structures of vanadium in \\text{VO}2 are studied across the high-pressure insulator-to-metal (IMT) transition using V K-edge x-ray absorption spectroscopy. Unlike the temperature-induced IMT, pressure-induced metallization leads to only subtle changes in the V K-edge prepeak structure, indicating a different mechanism involving smaller electronic spectral weight transfer close to the chemical potential. Intriguingly, upon application of the hydrostatic pressure, the electronic structure begins to show substantial changes well before the occurrence of the IMT and the associated structural transition to an anisotropic compression of the monoclinic metallic phase.

Angiogenesis - a crucial step in breast cancer growth, progression and dissemination by Raman imaging

NASA Astrophysics Data System (ADS)

Kopeć, Monika; Abramczyk, Halina

2018-06-01

Combined micro-Raman imaging and AFM imaging are efficient methods for analyzing human tissue due to their high spatial and spectral resolution as well as sensitivity to subtle chemical, structural and topographical changes. The aim of this study was to determine biochemical composition and mechanical topography around blood vessels in the tumor mass of human breast tissue. Significant alterations of the chemical composition and structural architecture around the blood vessel were found compared to the normal breast tissue. A pronounced increase of collagen-fibroblast-glycocalyx network, as well as enhanced lactic acid, and glycogen activity in patients affected by breast cancer were reported.

USGS Digital Spectral Library splib06a

USGS Publications Warehouse

Clark, Roger N.; Swayze, Gregg A.; Wise, Richard A.; Livo, K. Eric; Hoefen, Todd M.; Kokaly, Raymond F.; Sutley, Stephen J.

2007-01-01

Introduction We have assembled a digital reflectance spectral library that covers the wavelength range from the ultraviolet to far infrared along with sample documentation. The library includes samples of minerals, rocks, soils, physically constructed as well as mathematically computed mixtures, plants, vegetation communities, microorganisms, and man-made materials. The samples and spectra collected were assembled for the purpose of using spectral features for the remote detection of these and similar materials. Analysis of spectroscopic data from laboratory, aircraft, and spacecraft instrumentation requires a knowledge base. The spectral library discussed here forms a knowledge base for the spectroscopy of minerals and related materials of importance to a variety of research programs being conducted at the U.S. Geological Survey. Much of this library grew out of the need for spectra to support imaging spectroscopy studies of the Earth and planets. Imaging spectrometers, such as the National Aeronautics and Space Administration (NASA) Airborne Visible/Infra Red Imaging Spectrometer (AVIRIS) or the NASA Cassini Visual and Infrared Mapping Spectrometer (VIMS) which is currently orbiting Saturn, have narrow bandwidths in many contiguous spectral channels that permit accurate definition of absorption features in spectra from a variety of materials. Identification of materials from such data requires a comprehensive spectral library of minerals, vegetation, man-made materials, and other subjects in the scene. Our research involves the use of the spectral library to identify the components in a spectrum of an unknown. Therefore, the quality of the library must be very good. However, the quality required in a spectral library to successfully perform an investigation depends on the scientific questions to be answered and the type of algorithms to be used. For example, to map a mineral using imaging spectroscopy and the mapping algorithm of Clark and others (1990a, 2003b), one simply needs a diagnostic absorption band. The mapping system uses continuum-removed reference spectral features fitted to features in observed spectra. Spectral features for such algorithms can be obtained from a spectrum of a sample containing large amounts of contaminants, including those that add other spectral features, as long as the shape of the diagnostic feature of interest is not modified. If, however, the data are needed for radiative transfer models to derive mineral abundances from reflectance spectra, then completely uncontaminated spectra are required. This library contains spectra that span a range of quality, with purity indicators to flag spectra for (or against) particular uses. Acquiring spectral measurements and performing sample characterizations for this library has taken about 15 person-years of effort. Software to manage the library and provide scientific analysis capability is provided (Clark, 1980, 1993). A personal computer (PC) reader for the library is also available (Livo and others, 1993). The program reads specpr binary files (Clark, 1980, 1993) and plots spectra. Another program that reads the specpr format is written in IDL (Kokaly, 2005). In our view, an ideal spectral library consists of samples covering a very wide range of materials, has large wavelength range with very high precision, and has enough sample analyses and documentation to establish the quality of the spectra. Time and available resources limit what can be achieved. Ideally, for each mineral, the sample analysis would include X-ray diffraction (XRD), electron microprobe (EM) or X-ray fluorescence (XRF), and petrographic microscopic analyses. For some minerals, such as iron oxides, additional analyses such as Mossbauer would be helpful. We have found that to make the basic spectral measurements, provide XRD, EM or XRF analyses, and microscopic analyses, document the results, and complete an entry of one spectral library sample, all takes about

Isolated cortical visual loss with subtle brain MRI abnormalities in a case of hypoxic-ischemic encephalopathy.

PubMed

Margolin, Edward; Gujar, Sachin K; Trobe, Jonathan D

2007-12-01

A 16-year-old boy who was briefly asystolic and hypotensive after a motor vehicle accident complained of abnormal vision after recovering consciousness. Visual acuity was normal, but visual fields were severely constricted without clear hemianopic features. The ophthalmic examination was otherwise normal. Brain MRI performed 11 days after the accident showed no pertinent abnormalities. At 6 months after the event, brain MRI demonstrated brain volume loss in the primary visual cortex and no other abnormalities. One year later, visual fields remained severely constricted; neurologic examination, including formal neuropsychometric testing, was normal. This case emphasizes the fact that hypoxic-ischemic encephalopathy (HIE) may cause enduring damage limited to primary visual cortex and that the MRI abnormalities may be subtle. These phenomena should be recognized in the management of patients with HIE.

The Past, Present, and Future of Image-Enhanced Endoscopy

PubMed Central

Jang, Jae-Young

2015-01-01

Despite the remarkable progress recently made to enhance the resolution of white-light endoscopy, detection, and diagnosis of premalignant lesions, such as adenomas and subtle early-stage cancers, remains a great challenge. As for example, although chromoendoscopy, such as endoscopy using indigo carmine, is useful for the early diagnosis of subtle lesions, the technique presents various disadvantages ranging from the time required for spray application of the dye and suctioning of excess dye to the increased difficulty in identifying lesions in the presence of severe inflammation and obstruction of visual field due to the pooling of solution in depressed-type lesions. To overcome these diagnostic problems associated with chromoendoscopy, research has focused on the development of endoscopes based on new optical technologies. Several types of image-enhanced endoscopy methods have recently been presented. In particular, image-enhanced endoscopy has emerged as a new paradigm for the diagnosis of gastrointestinal disorders. Image-enhanced endoscopes provide high-contrast images of lesions by means of optical or electronic technologies, including the contrast enhancement of the mucosal surface and of blood vessels. Chromoendoscopy, narrow-band imaging, i-SCAN, and flexible spectral imaging color enhancement are representative examples of image-enhanced endoscopy discussed in this paper. PMID:26668791

Device, Algorithm and Integrated Modeling Research for Performance-Drive Multi-Modal Optical Sensors

DTIC Science & Technology

2012-12-17

to!feature!aided!tracking! using !spectral! information .! ! !iii! •! A!novel!technique!for!spectral!waveband!selection!was!developed!and! used !as! part! of ... of !spectral! information ! using !the!tunable!single;pixel!spectrometer!concept.! •! A! database! was! developed! of ! spectral! reflectance! measurements...exploring! the! utility! of ! spectral! and! polarimetric! information !to!help!with!the!vehicle!tracking!application.!Through!the! use ! of ! both

A Study on Spectral Signature Analysis of Wetland Vegetation Based on Ground Imaging Spectrum Data

NASA Astrophysics Data System (ADS)

Ling, Chengxing; Liu, Hua; Ju, Hongbo; Zhang, Huaiqing; You, Jia; Li, Weina

2017-10-01

The objective of this study was to verify the application of imaging spectrometer in wetland vegetation remote sensing monitoring, based on analysis of wetland vegetation spectral features. Spectral information of Carex vegetation spectral data under different water environment was collected bySOC710VP and ASD FieldSpec 3; Meanwhile, the chlorophyll contents of wheat leaves were tested in the lab. A total 9 typical vegetation indices were calculated by using two instruments’ data which were spectral values from 400nm to 1000 nm. Then features between the same vegetation indices and soil water contents for two applications were analyzed and compared. The results showed that there were same spectrum curve trends of Carex vegetation (soil moisture content of 51%, 32%, 14% and three regional comparative analysis)reflectance between SOC710VP and ASD FieldSpec 3, including the two reflectance peak of 550nm and 730 nm, two reflectance valley of 690 nm and 970nm, and continuous near infrared reflectance platform. However, The two also have a very clear distinction: (1) The reflection spectra of SOC710VP leaves of Carex Carex leaf spectra in the three soil moisture environment values are greater than ASD FieldSpec 3 collected value; (2) The SOC710VP reflectivity curve does not have the smooth curve of the original spectrum measured by the ASD FieldSpec 3, the amplitude of fluctuation is bigger, and it is more obvious in the near infrared band. It is concluded that SOC710VP spectral data are reliable, with the image features, spectral curve features reliable. It has great potential in the research of hyperspectral remote sensing technology in the development of wetland near earth, remote sensing monitoring of wetland resources.

The effect of time-variant acoustical properties on orchestral instrument timbres

NASA Astrophysics Data System (ADS)

Hajda, John Michael

1999-06-01

The goal of this study was to investigate the timbre of orchestral instrument tones. Kendall (1986) showed that time-variant features are important to instrument categorization. But the relative salience of specific time-variant features to each other and to other acoustical parameters is not known. As part of a convergence strategy, a battery of experiments was conducted to assess the importance of global amplitude envelope, spectral frequencies, and spectral amplitudes. An omnibus identification experiment investigated the salience of global envelope partitions (attack, steady state, and decay). Valid partitioning models should identify important boundary conditions in the evolution of a signal; therefore, these models should be based on signal characteristics. With the use of such a model for sustained continuant tones, the steady-state segment was more salient than the attack. These findings contradicted previous research, which used questionable operational definitions for signal partitioning. For the next set of experiments, instrument tones were analyzed by phase vocoder, and stimuli were created by additive synthesis. Edits and combinations of edits controlled global amplitude envelope, spectral frequencies, and relative spectral amplitudes. Perceptual measurements were made with distance estimation, Verbal Attribute Magnitude Estimation, and similarity scaling. Results indicated that the primary acoustical attribute was the long-time-average spectral centroid. Spectral centroid is a measure of the center of energy distribution for spectral frequency components. Instruments with high values of spectral centroid (bowed strings) sound nasal while instruments with low spectral centroid (flute, clarinet) sound not nasal. The secondary acoustical attribute was spectral amplitude time variance. Predictably, time variance correlated highly with subject ratings of vibrato. The control of relative spectral amplitudes was more salient than the control of global envelope and spectral frequencies. Both amplitude phase relationships and time- variant spectral centroid were affected by the control of relative spectral amplitudes. Further experimentation is required to determine the salience of these features. The finding that instrumental vibrato is a manifestation of spectral amplitude time variance contradicts the common belief that vibrato is due to frequency (pitch) and intensity (loudness) modulation. This study suggests that vibrato is due to a periodic modulation in timbre. Future research should employ musical contexts.

Mapping the mineralogy and lithology of Canyonlands, Utah with imaging spectrometer data and the multiple spectral feature mapping algorithm

NASA Technical Reports Server (NTRS)

Clark, Roger N.; Swayze, Gregg A.; Gallagher, Andrea

1992-01-01

The sedimentary sections exposed in the Canyonlands and Arches National Parks region of Utah (generally referred to as 'Canyonlands') consist of sandstones, shales, limestones, and conglomerates. Reflectance spectra of weathered surfaces of rocks from these areas show two components: (1) variations in spectrally detectable mineralogy, and (2) variations in the relative ratios of the absorption bands between minerals. Both types of information can be used together to map each major lithology and the Clark spectral features mapping algorithm is applied to do the job.

The very high rotators in the late-B and early-A stars: Shell stars with Si IV and C IV features the case of HD 119921

NASA Technical Reports Server (NTRS)

Freireferrero, R.; Bruhweiler, Frederick C.; Grady, C. A.

1990-01-01

Study of several stars in the late B and early A spectral types shows that very high rotators are associated with shell characteristics (sometimes not detected at all in the visible spectra) and also with C IV and some Si IV spectral absorption features which can be explained by circumstellar phenomena superimposed over stellar metallic blends. These particularities are evidenced by comparison with other spectra of low and high rotators in the same spectral range. HD 119921, a star with similar characteristics to the other ones of the sample, is given special attention. A possible scenario is suggested to explain the observed superionization features.

Progressively expanded neural network for automatic material identification in hyperspectral imagery

NASA Astrophysics Data System (ADS)

Paheding, Sidike

The science of hyperspectral remote sensing focuses on the exploitation of the spectral signatures of various materials to enhance capabilities including object detection, recognition, and material characterization. Hyperspectral imagery (HSI) has been extensively used for object detection and identification applications since it provides plenty of spectral information to uniquely identify materials by their reflectance spectra. HSI-based object detection algorithms can be generally classified into stochastic and deterministic approaches. Deterministic approaches are comparatively simple to apply since it is usually based on direct spectral similarity such as spectral angles or spectral correlation. In contrast, stochastic algorithms require statistical modeling and estimation for target class and non-target class. Over the decades, many single class object detection methods have been proposed in the literature, however, deterministic multiclass object detection in HSI has not been explored. In this work, we propose a deterministic multiclass object detection scheme, named class-associative spectral fringe-adjusted joint transform correlation. Human brain is capable of simultaneously processing high volumes of multi-modal data received every second of the day. In contrast, a machine sees input data simply as random binary numbers. Although machines are computationally efficient, they are inferior when comes to data abstraction and interpretation. Thus, mimicking the learning strength of human brain has been current trend in artificial intelligence. In this work, we present a biological inspired neural network, named progressively expanded neural network (PEN Net), based on nonlinear transformation of input neurons to a feature space for better pattern differentiation. In PEN Net, discrete fixed excitations are disassembled and scattered in the feature space as a nonlinear line. Each disassembled element on the line corresponds to a pattern with similar features. Unlike the conventional neural network where hidden neurons need to be iteratively adjusted to achieve better accuracy, our proposed PEN Net does not require hidden neurons tuning which achieves better computational efficiency, and it has also shown superior performance in HSI classification tasks compared to the state-of-the-arts. Spectral-spatial features based HSI classification framework has shown stronger strength compared to spectral-only based methods. In our lastly proposed technique, PEN Net is incorporated with multiscale spatial features (i.e., multiscale complete local binary pattern) to perform a spectral-spatial classification of HSI. Several experiments demonstrate excellent performance of our proposed technique compared to the more recent developed approaches.

ON THE LATE-TIME SPECTRAL SOFTENING FOUND IN X-RAY AFTERGLOWS OF GAMMA-RAY BURSTS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Yuan-Zhu; Liang, En-Wei; Lu, Zu-Jia

2016-02-20

Strong spectral softening has been revealed in the late X-ray afterglows of some gamma-ray bursts (GRBs). The scenario of X-ray scattering around the circumburst dusty medium has been supported by previous works due to its overall successful prediction of both the temporal and spectral evolution of some X-ray afterglows. To further investigate the observed feature of spectral softening we now systematically search the X-ray afterglows detected by the X-ray telescope aboard Swift and collect 12 GRBs with significant late-time spectral softening. We find that dust scattering could be the dominant radiative mechanism for these X-ray afterglows regarding their temporal andmore » spectral features. For some well-observed bursts with high-quality data, the time-resolved spectra could be well-produced within the scattering scenario by taking into account the X-ray absorption from the circumburst medium. We also find that during spectral softening the power-law index in the high-energy end of the spectra does not vary much. The spectral softening is mainly manifested by the spectral peak energy continually moving to the soft end.« less

Probing collective oscillation of d -orbital electrons at the nanoscale

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dhall, Rohan; Vigil-Fowler, Derek; Houston Dycus, J.

Here, we demonstrate that high energy electrons can be used to explore the collective oscillation of s, p, and d orbital electrons at the nanometer length scale. Using epitaxial AlGaN/AlN quantum wells as a test system, we observe the emergence of additional features in the loss spectrum with the increasing Ga content. A comparison of the observed spectra with ab-initio theory reveals that the origin of these spectral features lies in excitations of 3d-electrons contributed by Ga. We find that these modes differ in energy from the valence electron plasmons in Al1-xGaxN due to the different polarizabilities of the dmore » electrons. Finally, we study the dependence of observed spectral features on the Ga content, lending insights into the origin of these spectral features, and their coupling with electron-hole excitations.« less

Modeling Seasonal Thermal Radiance Cycles for Change Detection at Volcanic / Geothermal Areas

NASA Astrophysics Data System (ADS)

Vaughan, R.; Beuttel, B. S.

2013-12-01

Remote sensing observations of thermal features associated with (and often preceding) volcanic activity have been used for decades to detect and monitor volcanism. However, anomalous thermal precursors to volcanic eruptions are usually only recognized retrospectively. One of the reasons for this is that precursor thermal activity is often too subtle in magnitude (spatially, temporally, or in absolute temperature) to be unambiguously detected in time to issue warnings or forecasts. Part of the reason for this is the trade-off between high spatial and high temporal resolution associated with satellite imaging systems. Thus, the goal of this work has been to develop some techniques for using high-temporal-resolution, coarse-spatial-resolution imagery to try to detect subtle thermal anomalies. To identify anomalies, background thermal activity must first be characterized. Every active, or potentially active, volcano has a unique thermal history that provides information about normal background thermal activity due to seasonal or diurnal variations. Understanding these normal variations allows recognition of anomalous activity that may be due to volcanic / hydrothermal processes - ultimately with a lead time that may be sufficient to issue eruption warnings or forecasts. Archived MODIS data, acquired ~daily from 2000 to 2012, were used to investigate seasonal thermal cycles at three volcanic areas with different types of thermal features: Mount St. Helens, which had a dacite dome-building eruption from 2004-2008; Mount Ruapehu, which has a 500-m diameter active summit crater lake; and Yellowstone, which is a large active geothermal system that has hundreds of hot springs and fumarole fields spread out over a very large area. The focus has been on using MODIS 1-km sensor radiance data in the MIR and TIR wavelength regions that are sensitive to thermal emission from features that range in temperature from hundreds of °C, down to tens of °C (below the boiling temperature of water). To detect such features it is best to use data acquired at night, as this maximizes the delta T between the thermal target and non-thermal background and minimizes the effects of the Sun. Decadal time-series plots of nighttime MODIS sensor radiance data over the target areas show that seasonal thermal cycles due to varying solar incidence angle can be modeled with a sine function and removed to reveal subtle changes in TIR radiance. The seasonal sine function is unique to each volcanic / geothermal area and can be modeled iteratively using a least squares fit to the cloud of radiance data. The sine function model can also be used to generate a first-order cloud cover approximation for the nighttime TIR data. This work helps establish a framework for improved thermal alarm algorithms, automated thermal detection methods, and operational monitoring techniques for active, or potentially active, volcanoes throughout the world. This type of background study is a step toward establishing a global volcanic eruption forecasting system using satellite-based remote sensing data that are sensitive to subtle precursor thermal anomalies.

Surface Composition of Trojan Asteroids from Thermal-Infrared Spectroscopy

NASA Astrophysics Data System (ADS)

Martin, A.; Emery, J. P.; Lindsay, S. S.

2017-12-01

Asteroid origins provide an effective means of constraining the events that dynamically shaped the solar system. Jupiter Trojan asteroids (hereafter Trojans) may help in determining the extent of radial mixing that occurred during giant planet migration. Previous studies aimed at characterizing surface composition show that Trojans have low albedo surfaces and fall into two distinct spectral groups the near infrared (NIR). Though, featureless in this spectral region, NIR spectra of Trojans either exhibit a red or less-red slope. Typically, red-sloped spectra are associated with organics, but it has been shown that Trojans are not host to much, if any, organic material. Instead, the red slope is likely due to anhydrous silicates. The thermal infrared (TIR) wavelength range has advantages for detecting silicates on low albedo asteroids such as Trojans. The 10 µm region exhibits strong features due to the Si-O fundamental molecular vibrations. We hypothesize that the two Trojan spectral groups have different compositions (silicate mineralogy). With TIR spectra from the Spitzer Space Telescope, we identify mineralogical features from the surface of 11 Trojan asteroids, five red and six less-red. Preliminary results from analysis of the 10 µm region indicate red-sloped Trojans have a higher spectral contrast compared to less-red-sloped Trojans. Fine-grain mixtures of crystalline pyroxene and olivine exhibit a 10 µm feature with sharp cutoffs between about 9 µm and 12 µm, which create a broad flat plateau. Amorphous phases, when present, smooth the sharp emission features, resulting in a dome-like shape. Further spectral analysis in the 10 µm, 18 µm, and 30 µm band region will be performed for a more robust analysis. If all Trojans come from the same region, it is expected that they share spectral and compositional characteristics. Therefore, if spectral analysis in the TIR reinforce the NIR spectral slope dichotomy, it is likely that Trojans were sourced from two different regions of the solar system. This result would provide new constraints for dynamical models that explain giant planet migration.

Evaluating some computer exhancement algorithms that improve the visibility of cometary morphology

NASA Technical Reports Server (NTRS)

Larson, Stephen M.; Slaughter, Charles D.

1992-01-01

Digital enhancement of cometary images is a necessary tool in studying cometary morphology. Many image processing algorithms, some developed specifically for comets, have been used to enhance the subtle, low contrast coma and tail features. We compare some of the most commonly used algorithms on two different images to evaluate their strong and weak points, and conclude that there currently exists no single 'ideal' algorithm, although the radial gradient spatial filter gives the best overall result. This comparison should aid users in selecting the best algorithm to enhance particular features of interest.

Pathologic features of early inflammatory bowel disease.

PubMed

Finkelstein, Sydney D; Sasatomi, Eizaburo; Regueiro, Miguel

2002-03-01

Often the pathologic changes of IBD are subtle and may not be present in a proportion of biopsy specimens. In cases of early disease, the changes may be missed, and additional specimens should be taken after a period of time. Modifying factors, such as prebiopsy treatment and coexisting disease, should be considered. A forum to review cases and allow for communication between gastroenterologists and pathologists is especially useful for clinicopathologic correlation and assignment of a working diagnosis to each case. Careful attention to the pathologic features of early UC and CD would be most useful when evaluating new therapies for IBD.

The Hierarchical Cortical Organization of Human Speech Processing

PubMed Central

de Heer, Wendy A.; Huth, Alexander G.; Griffiths, Thomas L.

2017-01-01

Speech comprehension requires that the brain extract semantic meaning from the spectral features represented at the cochlea. To investigate this process, we performed an fMRI experiment in which five men and two women passively listened to several hours of natural narrative speech. We then used voxelwise modeling to predict BOLD responses based on three different feature spaces that represent the spectral, articulatory, and semantic properties of speech. The amount of variance explained by each feature space was then assessed using a separate validation dataset. Because some responses might be explained equally well by more than one feature space, we used a variance partitioning analysis to determine the fraction of the variance that was uniquely explained by each feature space. Consistent with previous studies, we found that speech comprehension involves hierarchical representations starting in primary auditory areas and moving laterally on the temporal lobe: spectral features are found in the core of A1, mixtures of spectral and articulatory in STG, mixtures of articulatory and semantic in STS, and semantic in STS and beyond. Our data also show that both hemispheres are equally and actively involved in speech perception and interpretation. Further, responses as early in the auditory hierarchy as in STS are more correlated with semantic than spectral representations. These results illustrate the importance of using natural speech in neurolinguistic research. Our methodology also provides an efficient way to simultaneously test multiple specific hypotheses about the representations of speech without using block designs and segmented or synthetic speech. SIGNIFICANCE STATEMENT To investigate the processing steps performed by the human brain to transform natural speech sound into meaningful language, we used models based on a hierarchical set of speech features to predict BOLD responses of individual voxels recorded in an fMRI experiment while subjects listened to natural speech. Both cerebral hemispheres were actively involved in speech processing in large and equal amounts. Also, the transformation from spectral features to semantic elements occurs early in the cortical speech-processing stream. Our experimental and analytical approaches are important alternatives and complements to standard approaches that use segmented speech and block designs, which report more laterality in speech processing and associated semantic processing to higher levels of cortex than reported here. PMID:28588065

Improved P300 speller performance using electrocorticography, spectral features, and natural language processing.

PubMed

Speier, William; Fried, Itzhak; Pouratian, Nader

2013-07-01

The P300 speller is a system designed to restore communication to patients with advanced neuromuscular disorders. This study was designed to explore the potential improvement from using electrocorticography (ECoG) compared to the more traditional usage of electroencephalography (EEG). We tested the P300 speller on two epilepsy patients with temporary subdural electrode arrays over the occipital and temporal lobes respectively. We then performed offline analysis to determine the accuracy and bit rate of the system and integrated spectral features into the classifier and used a natural language processing (NLP) algorithm to further improve the results. The subject with the occipital grid achieved an accuracy of 82.77% and a bit rate of 41.02, which improved to 96.31% and 49.47 respectively using a language model and spectral features. The temporal grid patient achieved an accuracy of 59.03% and a bit rate of 18.26 with an improvement to 75.81% and 27.05 respectively using a language model and spectral features. Spatial analysis of the individual electrodes showed best performance using signals generated and recorded near the occipital pole. Using ECoG and integrating language information and spectral features can improve the bit rate of a P300 speller system. This improvement is sensitive to the electrode placement and likely depends on visually evoked potentials. This study shows that there can be an improvement in BCI performance when using ECoG, but that it is sensitive to the electrode location. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Behavioral state classification in epileptic brain using intracranial electrophysiology

NASA Astrophysics Data System (ADS)

Kremen, Vaclav; Duque, Juliano J.; Brinkmann, Benjamin H.; Berry, Brent M.; Kucewicz, Michal T.; Khadjevand, Fatemeh; Van Gompel, Jamie; Stead, Matt; St. Louis, Erik K.; Worrell, Gregory A.

2017-04-01

Objective. Automated behavioral state classification can benefit next generation implantable epilepsy devices. In this study we explored the feasibility of automated awake (AW) and slow wave sleep (SWS) classification using wide bandwidth intracranial EEG (iEEG) in patients undergoing evaluation for epilepsy surgery. Approach. Data from seven patients (age 34+/- 12 , 4 women) who underwent intracranial depth electrode implantation for iEEG monitoring were included. Spectral power features (0.1-600 Hz) spanning several frequency bands from a single electrode were used to train and test a support vector machine classifier. Main results. Classification accuracy of 97.8  ±  0.3% (normal tissue) and 89.4  ±  0.8% (epileptic tissue) across seven subjects using multiple spectral power features from a single electrode was achieved. Spectral power features from electrodes placed in normal temporal neocortex were found to be more useful (accuracy 90.8  ±  0.8%) for sleep-wake state classification than electrodes located in normal hippocampus (87.1  ±  1.6%). Spectral power in high frequency band features (Ripple (80-250 Hz), Fast Ripple (250-600 Hz)) showed comparable performance for AW and SWS classification as the best performing Berger bands (Alpha, Beta, low Gamma) with accuracy  ⩾90% using a single electrode contact and single spectral feature. Significance. Automated classification of wake and SWS should prove useful for future implantable epilepsy devices with limited computational power, memory, and number of electrodes. Applications include quantifying patient sleep patterns and behavioral state dependent detection, prediction, and electrical stimulation therapies.

Factorization-based texture segmentation

DOE PAGES

Yuan, Jiangye; Wang, Deliang; Cheriyadat, Anil M.

2015-06-17

This study introduces a factorization-based approach that efficiently segments textured images. We use local spectral histograms as features, and construct an M × N feature matrix using M-dimensional feature vectors in an N-pixel image. Based on the observation that each feature can be approximated by a linear combination of several representative features, we factor the feature matrix into two matrices-one consisting of the representative features and the other containing the weights of representative features at each pixel used for linear combination. The factorization method is based on singular value decomposition and nonnegative matrix factorization. The method uses local spectral histogramsmore » to discriminate region appearances in a computationally efficient way and at the same time accurately localizes region boundaries. Finally, the experiments conducted on public segmentation data sets show the promise of this simple yet powerful approach.« less

Cryogenic terahertz spectrum of (+)-methamphetamine hydrochloride and assignment using solid-state density functional theory.

PubMed

Hakey, Patrick M; Allis, Damian G; Ouellette, Wayne; Korter, Timothy M

2009-04-30

The cryogenic terahertz spectrum of (+)-methamphetamine hydrochloride from 10.0 to 100.0 cm(-1) is presented, as is the complete structural analysis and vibrational assignment of the compound using solid-state density functional theory. This cryogenic investigation reveals multiple spectral features that were not previously reported in room-temperature terahertz studies of the title compound. Modeling of the compound employed eight density functionals utilizing both solid-state and isolated-molecule methods. The results clearly indicate the necessity of solid-state simulations for the accurate assignment of solid-state THz spectra. Assignment of the observed spectral features to specific atomic motions is based on the BP density functional, which provided the best-fit solid-state simulation of the experimental spectrum. The seven experimental spectral features are the result of thirteen infrared-active vibrational modes predicted at a BP/DNP level of theory with more than 90% of the total spectral intensity associated with external crystal vibrations.

Spectral reflectance properties of major objects in desert oasis: a case study of the Weigan-Kuqa river delta oasis in Xinjiang, China.

PubMed

Zhang, Fei; Tiyip, Tashpolat; Ding, Jianli; Sawut, Mamat; Tashpolat, Nigara; Kung, Hsiangte; Han, Guihong; Gui, Dongwei

2012-08-01

Aiming at the remote sensing application has been increasingly relying on ground object spectral characteristics. In order to further research the spectral reflectance characteristics in arid area, this study was performed in the typical delta oasis of Weigan and Kuqa rivers located north of Tarim Basin. Data were collected from geo-targets at multiple sites in various field conditions. The spectra data were collected for different soil types including saline-alkaline soil, silt sandy soil, cotton field, and others; vegetations of Alhagi sparsifolia, Phragmites australis, Tamarix, Halostachys caspica, etc., and water bodies. Next, the data were processed to remove high-frequency noise, and the spectral curves were smoothed with the moving average method. The derivative spectrum was generated after eliminating environmental background noise so that to distinguish the original overlap spectra. After continuum removal of the undesirable absorbance, the spectrum curves were able to highlight features for both optical absorbance and reflectance. The spectrum information of each ground object is essential for fully utilizing the multispectrum data generated by remote sensing, which will need a representative spectral library. In this study using ENVI 4.5 software, a preliminary spectral library of surface features was constructed using the data surveyed in the study area. This library can support remote sensing activities such as feature investigation, vegetation classification, and environmental monitoring in the delta oasis region. Future plan will focus on sharing and standardizing the criteria of professional spectral library and to expand and promote the utilization of the spectral databases.

Parameterization of the Voice Source by Combining Spectral Decay and Amplitude Features of the Glottal Flow.

ERIC Educational Resources Information Center

Alku, Paavo; Vilkman, Erkki; Laukkanen, Anne-Maria

1998-01-01

A new method is presented for the parameterization of glottal volume velocity waveforms that have been estimated by inverse filtering acoustic speech pressure signals. The new technique combines two features of voice production: the AC value and the spectral decay of the glottal flow. Testing found the new parameter correlates strongly with the…

Painting with Frost

NASA Image and Video Library

2016-12-07

Subtle variations in color look like brush strokes as the lightly frosted terrain reflects light. These variations provide a backdrop to some exotic features referred to colloquially as "spiders." The radial channels branching out from a central depression are formed when the seasonal layer of dry ice turns to gas in the spring and erodes the surface, which is a uniquely Martian landform. http://photojournal.jpl.nasa.gov/catalog/PIA21214

Use of the Primitive Unit Cell in Understanding Subtle Features of the Cubic Closest-Packed Structure

ERIC Educational Resources Information Center

Hawkins, John A.; Rittenhouse, Jeffrey L.; Soper, Linda M.; Rittenhouse, Robert C.

2008-01-01

One of the most important crystal structures adopted by metals is characterized by the "abcabc"...stacking of close-packed layers. This structure is commonly referred to in textbooks as the cubic close-packed (ccp) or face-centered cubic (fcc) structure, since the entire lattice can be generated by replication of a face-centered cubic unit cell…

Spectral analysis of ground penetrating radar signals in concrete, metallic and plastic targets

NASA Astrophysics Data System (ADS)

Santos, Vinicius Rafael N. dos; Al-Nuaimy, Waleed; Porsani, Jorge Luís; Hirata, Nina S. Tomita; Alzubi, Hamzah S.

2014-01-01

The accuracy of detecting buried targets using ground penetrating radar (GPR) depends mainly on features that are extracted from the data. The objective of this study is to test three spectral features and evaluate the quality to provide a good discrimination among three types of materials (concrete, metallic and plastic) using the 200 MHz GPR system. The spectral features which were selected to check the interaction of the electromagnetic wave with the type of material are: the power spectral density (PSD), short-time Fourier transform (STFT) and the Wigner-Ville distribution (WVD). The analyses were performed with simulated data varying the sizes of the targets and the electrical properties (relative dielectric permittivity and electrical conductivity) of the soil. To check if the simulated data are in accordance with the real data, the same approach was applied on the data obtained in the IAG/USP test site. A noticeable difference was found in the amplitude of the studies' features in the frequency domain and these results show the strength of the signal processing to try to differentiate buried materials using GPR, and so can be used in urban planning and geotechnical studies.

Microscopic and macroscopic spectral peculiarities of cutaneous tumours

NASA Astrophysics Data System (ADS)

Borisova, Ekaterina; Genova, Tsanislava; Troyanova, Petranka; Terziev, Ivan; Zakharov, Valery; Bratchenko, Ivan; Lomova, Maria; Gorin, Dmitry; Avramov, Latchezar

2017-12-01

Autofluorescence spectral and confocal microscopic measurements were made on different cutaneous neoplastic lesions, namely basal cell carcinoma, squamous cell carcinoma, malignant melanoma, and their dysplastic forms - keratoacantoma, dysplastic nevi and benign lesions related - basal cell papiloma, seboreic keratosa and compound nevi using excitation at 405 nm. Spectroscopic investigations were made on in vivo and ex vivo tissue samples, and confocal microscopy investigations were made on ex vivo and eosin-haematoxilin stained thin slices of the tumours detected. Correlation between the spectral data received and the microscopic features observed was found, related to the morphological and biochemical alterations during neoplasia growth. Specific spectral features observed in each type of lesion investigated on micro and macro level would be presented and discussed.

Spectral lags in different episodes of gamma-ray bursts

NASA Astrophysics Data System (ADS)

Jia, LanWei; Yi, TingFeng; Liang, EnWei

2013-08-01

A systematical analysis of the spectral lags in different episodes within a gamma-ray burst (GRB) for the BATSE GRB sample is given. The identified episodes are usually a single pulse with mixing of small fluctuations. The spectral lags were calculated for lightcurves in the 25-55 keV and 110-320 keV bands. No universal spectral lag evolution feature in different episodes within a GRB were found for most GRBs. Among 362 bright GRBs that have at least three well-identified episodes, 19 of them show long-to-short lag and 19 of them show short-to-long lag in successive episodes. The other 324 GRBs have no clear evolution trend. Defining the specified lag with the ratio of the spectral lag to the episode duration in 110-320 keV band, no prominent case of specified lag was found showing clear evolution features. The results suggest that the observed spectral lag may contribute to the dynamics and/or the radiation physics of a given emission episode.

Near-infrared spectral reflectance of mineral mixtures - Systematic combinations of pyroxenes, olivine, and iron oxides

NASA Technical Reports Server (NTRS)

Singer, R. B.

1981-01-01

Near-infrared spectral reflectance data are presented for systematic variations in weight percent of two component mixtures of ferromagnesium and iron oxide minerals used to study the dark materials on Mars. Olivine spectral features are greatly reduced in contrast by admixture of other phases but remain distinctive even for low olivine contents. Clinopyroxene and orthopyroxene mixtures show resolved pyroxene absorptions near 2 microns. Limonite greatly modifies pyroxene and olivine reflectance, but does not fully eliminate distinctive spectral characteristics. Using only spectral data in the 1 micron region, it is difficult to differentiate orthopyroxene and limonite in a mixture. All composite mineral absorptions were either weaker than or intermediate in strength to the end-member absorptions and have bandwidths greater than or equal to those for the end members. In general, spectral properties in an intimate mixture combine in a complex, nonadditive manner, with features demonstrating a regular but usually nonlinear variation as a function of end-member phase proportions.

High-angular-resolution stellar imaging with occultations from the Cassini spacecraft - III. Mira

NASA Astrophysics Data System (ADS)

Stewart, Paul N.; Tuthill, Peter G.; Nicholson, Philip D.; Hedman, Matthew M.

2016-04-01

We present an analysis of spectral and spatial data of Mira obtained by the Cassini spacecraft, which not only observed the star's spectra over a broad range of near-infrared wavelengths, but was also able to obtain high-resolution spatial information by watching the star pass behind Saturn's rings. The observed spectral range of 1-5 microns reveals the stellar atmosphere in the crucial water-bands which are unavailable to terrestrial observers, and the simultaneous spatial sampling allows the origin of spectral features to be located in the stellar environment. Models are fitted to the data, revealing the spectral and spatial structure of molecular layers surrounding the star. High-resolution imagery is recovered revealing the layered and asymmetric nature of the stellar atmosphere. The observational data set is also used to confront the state-of-the-art cool opacity-sampling dynamic extended atmosphere models of Mira variables through a detailed spectral and spatial comparison, revealing in general a good agreement with some specific departures corresponding to particular spectral features.

Cloud cover analysis with Arctic Advanced Very High Resolution Radiometer data. II - Classification with spectral and textural measures

NASA Technical Reports Server (NTRS)

Key, J.

1990-01-01

The spectral and textural characteristics of polar clouds and surfaces for a 7-day summer series of AVHRR data in two Arctic locations are examined, and the results used in the development of a cloud classification procedure for polar satellite data. Since spatial coherence and texture sensitivity tests indicate that a joint spectral-textural analysis based on the same cell size is inappropriate, cloud detection with AVHRR data and surface identification with passive microwave data are first done on the pixel level as described by Key and Barry (1989). Next, cloud patterns within 250-sq-km regions are described, then the spectral and local textural characteristics of cloud patterns in the image are determined and each cloud pixel is classified by statistical methods. Results indicate that both spectral and textural features can be utilized in the classification of cloudy pixels, although spectral features are most useful for the discrimination between cloud classes.

Single-molecule spectroscopy unmasks the lowest exciton state of the B850 assembly in LH2 from Rps. acidophila.

PubMed

Kunz, Ralf; Timpmann, Kõu; Southall, June; Cogdell, Richard J; Freiberg, Arvi; Köhler, Jürgen

2014-05-06

We have recorded fluorescence-excitation and emission spectra from single LH2 complexes from Rhodopseudomonas (Rps.) acidophila. Both types of spectra show strong temporal spectral fluctuations that can be visualized as spectral diffusion plots. Comparison of the excitation and emission spectra reveals that for most of the complexes the lowest exciton transition is not observable in the excitation spectra due to the cutoff of the detection filter characteristics. However, from the spectral diffusion plots we have the full spectral and temporal information at hand and can select those complexes for which the excitation spectra are complete. Correlating the red most spectral feature of the excitation spectrum with the blue most spectral feature of the emission spectrum allows an unambiguous assignment of the lowest exciton state. Hence, application of fluorescence-excitation and emission spectroscopy on the same individual LH2 complex allows us to decipher spectral subtleties that are usually hidden in traditional ensemble spectroscopy. Copyright © 2014 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Biologically-inspired data decorrelation for hyper-spectral imaging

NASA Astrophysics Data System (ADS)

Picon, Artzai; Ghita, Ovidiu; Rodriguez-Vaamonde, Sergio; Iriondo, Pedro Ma; Whelan, Paul F.

2011-12-01

Hyper-spectral data allows the construction of more robust statistical models to sample the material properties than the standard tri-chromatic color representation. However, because of the large dimensionality and complexity of the hyper-spectral data, the extraction of robust features (image descriptors) is not a trivial issue. Thus, to facilitate efficient feature extraction, decorrelation techniques are commonly applied to reduce the dimensionality of the hyper-spectral data with the aim of generating compact and highly discriminative image descriptors. Current methodologies for data decorrelation such as principal component analysis (PCA), linear discriminant analysis (LDA), wavelet decomposition (WD), or band selection methods require complex and subjective training procedures and in addition the compressed spectral information is not directly related to the physical (spectral) characteristics associated with the analyzed materials. The major objective of this article is to introduce and evaluate a new data decorrelation methodology using an approach that closely emulates the human vision. The proposed data decorrelation scheme has been employed to optimally minimize the amount of redundant information contained in the highly correlated hyper-spectral bands and has been comprehensively evaluated in the context of non-ferrous material classification

Acoustic Database for Turbofan Engine Core-Noise Sources. I; Volume

NASA Technical Reports Server (NTRS)

Gordon, Grant

2015-01-01

In this program, a database of dynamic temperature and dynamic pressure measurements were acquired inside the core of a TECH977 turbofan engine to support investigations of indirect combustion noise. Dynamic temperature and pressure measurements were recorded for engine gas dynamics up to temperatures of 3100 degrees Fahrenheit and transient responses as high as 1000 hertz. These measurements were made at the entrance of the high pressure turbine (HPT) and at the entrance and exit of the low pressure turbine (LPT). Measurements were made at two circumferential clocking positions. In the combustor and inter-turbine duct (ITD), measurements were made at two axial locations to enable the exploration of time delays. The dynamic temperature measurements were made using dual thin-wire thermocouple probes. The dynamic pressure measurements were made using semi-infinite probes. Prior to the engine test, a series of bench, oven, and combustor rig tests were conducted to characterize the performance of the dual wire temperature probes and to define and characterize the data acquisition systems. A measurement solution for acquiring dynamic temperature and pressure data on the engine was defined. A suite of hardware modifications were designed to incorporate the dynamic temperature and pressure instrumentation into the TECH977 engine. In particular, a probe actuation system was developed to protect the delicate temperature probes during engine startup and transients in order to maximize sensor life. A set of temperature probes was procured and the TECH977 engine was assembled with the suite of new and modified hardware. The engine was tested at four steady state operating speeds, with repeats. Dynamic pressure and temperature data were acquired at each condition for at least one minute. At the two highest power settings, temperature data could not be obtained at the forward probe locations since the mean temperatures exceeded the capability of the probes. The temperature data were processed using software that accounts for the effects of convective and conductive heat transfer. The software was developed under previous NASA sponsored programs. Compensated temperature spectra and compensated time histories corresponding to the dynamic temperature of the gas stream were generated. Auto-spectral and cross-spectral analyses of the data were performed to investigate spectral features, acoustic circumferential mode content, signal coherence, and time delays. The dynamic temperature data exhibit a wideband and fairly flat spectral content. The temperature spectra do not change substantially with operating speed. The pressure spectra in the combustor and ITD exhibit generally similar shapes and amplitudes, making it difficult to identify any features that suggest the presence of indirect combustion noise. Cross-spectral analysis reveal a strong correlation between pressure and temperature fluctuations in the ITD, but little correlation between temperature fluctuations at the entrance of the HPT and pressure fluctuations downstream of it. Temperature fluctuations at the entrance of the low pressure turbine were an order of magnitude smaller than those at the entrance to the high pressure turbine. Time delay analysis of the temperature fluctuations in the combustor was inconclusive, perhaps due to the substantial mixing that occurs between the upstream and downstream locations. Time delay analysis of the temperature fluctuations in the ITD indicate that they convect at the mean flow speed. Analysis of the data did not reveal any convincing indications of the presence of indirect combustion noise. However, this analysis has been preliminary and additional exploration of the data is recommended including the use of more sophisticated signal processing to explore subtle issues that have been revealed but which are not yet fully understood or explained.

Going Deeper With Contextual CNN for Hyperspectral Image Classification.

PubMed

Lee, Hyungtae; Kwon, Heesung

2017-10-01

In this paper, we describe a novel deep convolutional neural network (CNN) that is deeper and wider than other existing deep networks for hyperspectral image classification. Unlike current state-of-the-art approaches in CNN-based hyperspectral image classification, the proposed network, called contextual deep CNN, can optimally explore local contextual interactions by jointly exploiting local spatio-spectral relationships of neighboring individual pixel vectors. The joint exploitation of the spatio-spectral information is achieved by a multi-scale convolutional filter bank used as an initial component of the proposed CNN pipeline. The initial spatial and spectral feature maps obtained from the multi-scale filter bank are then combined together to form a joint spatio-spectral feature map. The joint feature map representing rich spectral and spatial properties of the hyperspectral image is then fed through a fully convolutional network that eventually predicts the corresponding label of each pixel vector. The proposed approach is tested on three benchmark data sets: the Indian Pines data set, the Salinas data set, and the University of Pavia data set. Performance comparison shows enhanced classification performance of the proposed approach over the current state-of-the-art on the three data sets.

First results of the observations of trace gases in the Martian atmosphere by the Planetary Fourier Spectrometer onboard the Mars Express

NASA Astrophysics Data System (ADS)

Titov, D. V.; Ignatiev, N.; Formisano, V.; Grassi, D.; Giuranna, M.; Maturilli, A.; Piccioni, G.; Moroz, V. I.; Lellouch, E.; Encrenaz, T.; Pfs Team

High spectral resolution observations of Mars by the PFS/Mars Express provide new insight into the atmospheric composition. Spectral features of atmospheric CO2 and its isotopes at 15, 4.3, 2.7, 1.4 μ m, CO at 4.7 and 2.35 μ m, and H2O at 40, 2.56, and 1.38 μ m as well as solar spectral features are clearly identified in the PFS spectra. HDO spectral details at 3.7 μ m were also tentatively detected. The paper will present qualitative and quantitative analysis of the PFS spectra in the regions of spectral bands of trace gases. Abundance of minor constituents will be determined using complete radiative transfer modeling including possible non-LTE effects. We will also present results of search for other minor species with emphasis on the limb observations that provide higher air mass factor.

Space-Weathered Anorthosite as Spectral D-Type Material on the Martian Satellites

NASA Astrophysics Data System (ADS)

Yamamoto, S.; Watanabe, S.; Matsunaga, T.

2018-02-01

Spectral D-type asteroids are characterized by dark, red-sloped, and featureless spectra at visible and near-infrared wavelengths and are thought to be composed of rocks rich in organic compounds. The Martian satellites, Phobos and Deimos, spectrally resemble D-type asteroids, suggesting that they are captured D-type asteroids from outside the Martian system. Here we show that the spectral features of lunar space-weathered anorthosite are consistent with D-type spectra, including those of Phobos and Deimos. This can also explain the distinct spectral features on Phobos, the red and blue units, as arising from different degrees of space weathering. Thus, D-type spectra of the Martian satellites can be explained by space-weathered anorthosite, indicating that D-type spectra do not necessarily support the existence of organic compounds, which would be strong evidence for the capture scenario.

Understanding innate preferences of wild bee species: responses to wavelength-dependent selective excitation of blue and green photoreceptor types.

PubMed

Ostroverkhova, Oksana; Galindo, Gracie; Lande, Claire; Kirby, Julie; Scherr, Melissa; Hoffman, George; Rao, Sujaya

2018-06-05

Bees have a trichromatic vision with ultraviolet, blue, and green photoreceptors in their compound eyes. While the three photoreceptor types comprise the 'color space' at the perceptual level, preferential excitation of one or two of the photoreceptor types has been shown to play an important role in innate color preferences of bumble bees. Bees have been shown to exhibit strong attraction to fluorescence emission exclusively in the blue spectral region. It is not known if emission exclusively in the green spectral region produces similar attraction. Here, we examined responses of wild bees to traps designed to selectively stimulate either the blue or the green photoreceptor using sunlight-induced fluorescence in the 420-480 or 510-540 nm region, respectively. Additionally, we probed how subtle changes in the spectral characteristics of the traps affect the bee captures once a highly selective excitation of the blue photoreceptor is achieved. It was established that selective excitation of the green photoreceptor type was not attractive, in contrast to that of the blue photoreceptor type. However, once a highly selective excitation of the blue photoreceptor type (at ~ 400-480 nm) was achieved, the wild bees favored strong excitation at 430-480 nm over that in the 400-420 nm region.

[Comparison of Three Spectroscopies for the Determination of Composition of LDPE/PP Blend with Partial Least-Squares].

PubMed

Chen, Ru-huang; Jin, Gang

2015-08-01

This paper presented an application of mid-infrared (MIR), near-infrared (NIR) and Raman spectroscopies for collecting the spectra of 31 kinds of low density polyethylene/polyprolene (LDPE/PP) samples with different proportions. The different pre-processing methods (multiplicative scatter correction, mean centering and Savitzky-Golay first derivative) and spectral region were explored to develop partial least-squares (PLS) model for LDPE, their influence on the accuracy of PLS model also being discussed. Three spectroscopies were compared about the accuracy of quantitative measurement. Consequently, the pre-processing methods and spectral region have a great impact on the accuracy of PLS model, especially the spectra with subtle difference, random noise and baseline variation. After being pre-processed and spectral region selected, the calibration model of MIR, NIR and Raman exhibited R2/RMSEC values of 0.9906/2.941, 0.9973/1.561 and 0.9972/1.598 respectively, which corrsponding to 0.8876/10.15, 0.8493/11.75 and 0.8757/10.67 before any treatment. The results also suggested MIR, NIR and Raman are three strong tools to predict the content of LDPE in LDPE/PP blend. However, NIR and Raman showed higher accuracy after being pre-processed and more suitability to fast quantitative characterization due to their high measuring speed.

Multispectral fluorescence imaging techniques for nondestructive food safety inspection

NASA Astrophysics Data System (ADS)

Kim, Moon S.; Lefcourt, Alan M.; Chen, Yud-Ren

2004-03-01

The use of spectral sensing has gained acceptance as a rapid means for nondestructive inspection of postharvest food produce. Current technologies generally use color or a single wavelength camera technology. The applicability and sensitivity of these techniques can be expanded through the use of multiple wavelengths. Reflectance in the Vis/NIR is the prevalent spectral technique. Fluorescence, compared to reflectance, is regarded as a more sensitive technique due to its dynamic responses to subtle changes in biological entities. Our laboratory has been exploring fluorescence as a potential means for detection of quality and wholesomeness of food products. Applications of fluorescence sensing require an understanding of the spectral characteristics emanating from constituents and potential contaminants. A number of factors affecting fluorescence emission characteristics are discussed. Because of relatively low fluorescence quantum yield from biological samples, a system with a powerful pulse light source such as a laser coupled with a gated detection device is used to harvest fluorescence, in the presence of ambient light. Several fluorescence sensor platforms developed in our laboratory, including hyperspectral imaging, and laser-induced fluorescence (LIF) and steady-state fluorescence imaging systems with multispectral capabilities are presented. We demonstrate the potential uses of recently developed fluorescence imaging platforms in food safety inspection of apples contaminated with animal feces.

Impacts of Brown Carbon from Biomass Burning on Surface UV and Ozone Photochemistry in the Amazon Basin

NASA Technical Reports Server (NTRS)

Mok, Jungbin; Krotkov, Nickolay A.; Arola, Antti; Torres, Omar; Jethva, Hiren; Andrade, Marcos; Labow, Gordon; Eck, Thomas F.; Li, Zhangqing; Dickerson, Russell R.;

Impacts of brown carbon from biomass burning on surface UV and ozone photochemistry in the Amazon Basin.

PubMed

Mok, Jungbin; Krotkov, Nickolay A; Arola, Antti; Torres, Omar; Jethva, Hiren; Andrade, Marcos; Labow, Gordon; Eck, Thomas F; Li, Zhanqing; Dickerson, Russell R; Stenchikov, Georgiy L; Osipov, Sergey; Ren, Xinrong

2016-11-11

The spectral dependence of light absorption by atmospheric particulate matter has major implications for air quality and climate forcing, but remains uncertain especially in tropical areas with extensive biomass burning. In the September-October 2007 biomass-burning season in Santa Cruz, Bolivia, we studied light absorbing (chromophoric) organic or "brown" carbon (BrC) with surface and space-based remote sensing. We found that BrC has negligible absorption at visible wavelengths, but significant absorption and strong spectral dependence at UV wavelengths. Using the ground-based inversion of column effective imaginary refractive index in the range 305-368 nm, we quantified a strong spectral dependence of absorption by BrC in the UV and diminished ultraviolet B (UV-B) radiation reaching the surface. Reduced UV-B means less erythema, plant damage, and slower photolysis rates. We use a photochemical box model to show that relative to black carbon (BC) alone, the combined optical properties of BrC and BC slow the net rate of production of ozone by up to 18% and lead to reduced concentrations of radicals OH, HO 2 , and RO 2 by up to 17%, 15%, and 14%, respectively. The optical properties of BrC aerosol change in subtle ways the generally adverse effects of smoke from biomass burning.

Utilizing spatial and spectral features of photoacoustic imaging for ovarian cancer detection and diagnosis

NASA Astrophysics Data System (ADS)

Li, Hai; Kumavor, Patrick; Salman Alqasemi, Umar; Zhu, Quing

2015-01-01

A composite set of ovarian tissue features extracted from photoacoustic spectral data, beam envelope, and co-registered ultrasound and photoacoustic images are used to characterize malignant and normal ovaries using logistic and support vector machine (SVM) classifiers. Normalized power spectra were calculated from the Fourier transform of the photoacoustic beamformed data, from which the spectral slopes and 0-MHz intercepts were extracted. Five features were extracted from the beam envelope and another 10 features were extracted from the photoacoustic images. These 17 features were ranked by their p-values from t-tests on which a filter type of feature selection method was used to determine the optimal feature number for final classification. A total of 169 samples from 19 ex vivo ovaries were randomly distributed into training and testing groups. Both classifiers achieved a minimum value of the mean misclassification error when the seven features with lowest p-values were selected. Using these seven features, the logistic and SVM classifiers obtained sensitivities of 96.39±3.35% and 97.82±2.26%, and specificities of 98.92±1.39% and 100%, respectively, for the training group. For the testing group, logistic and SVM classifiers achieved sensitivities of 92.71±3.55% and 92.64±3.27%, and specificities of 87.52±8.78% and 98.49±2.05%, respectively.

Optimizing Radiometric Processing and Feature Extraction of Drone Based Hyperspectral Frame Format Imagery for Estimation of Yield Quantity and Quality of a Grass Sward

NASA Astrophysics Data System (ADS)

Näsi, R.; Viljanen, N.; Oliveira, R.; Kaivosoja, J.; Niemeläinen, O.; Hakala, T.; Markelin, L.; Nezami, S.; Suomalainen, J.; Honkavaara, E.

2018-04-01

Light-weight 2D format hyperspectral imagers operable from unmanned aerial vehicles (UAV) have become common in various remote sensing tasks in recent years. Using these technologies, the area of interest is covered by multiple overlapping hypercubes, in other words multiview hyperspectral photogrammetric imagery, and each object point appears in many, even tens of individual hypercubes. The common practice is to calculate hyperspectral orthomosaics utilizing only the most nadir areas of the images. However, the redundancy of the data gives potential for much more versatile and thorough feature extraction. We investigated various options of extracting spectral features in the grass sward quantity evaluation task. In addition to the various sets of spectral features, we used photogrammetry-based ultra-high density point clouds to extract features describing the canopy 3D structure. Machine learning technique based on the Random Forest algorithm was used to estimate the fresh biomass. Results showed high accuracies for all investigated features sets. The estimation results using multiview data provided approximately 10 % better results than the most nadir orthophotos. The utilization of the photogrammetric 3D features improved estimation accuracy by approximately 40 % compared to approaches where only spectral features were applied. The best estimation RMSE of 239 kg/ha (6.0 %) was obtained with multiview anisotropy corrected data set and the 3D features.

Coherent Synchrotron Radiation in Laboratory Accelerators and the Double-Spectral Feature in Solar Flares

NASA Astrophysics Data System (ADS)

Cruz, Wellington; Szpigel, Sérgio; Kaufmann, Pierre; Raulin, Jean-Pierre; Klopf, Michael

2017-10-01

Recent observations of solar flares at high-frequencies have provided evidence of a new spectral component with fluxes increasing with frequency in the sub-THz to THz range. This new component occurs simultaneously but is separated from the well-known microwave spectral component that maximizes at frequencies of a few to tens of GHz. The aim of this work is to study in detail a mechanism recently suggested to describe the double-spectrum feature observed in solar flares based on the physical process known as microbunching instability, which occurs with high-energy electron beams in laboratory accelerators.

Multispectral atmospheric mapping sensor of mesoscale water vapor features

NASA Technical Reports Server (NTRS)

Menzel, P.; Jedlovec, G.; Wilson, G.; Atkinson, R.; Smith, W.

1985-01-01

The Multispectral atmospheric mapping sensor was checked out for specified spectral response and detector noise performance in the eight visible and three infrared (6.7, 11.2, 12.7 micron) spectral bands. A calibration algorithm was implemented for the infrared detectors. Engineering checkout flights on board the ER-2 produced imagery at 50 m resolution in which water vapor features in the 6.7 micron spectral band are most striking. These images were analyzed on the Man computer Interactive Data Access System (McIDAS). Ground truth and ancillary data was accessed to verify the calibration.

TBC1D24 mutation associated with focal epilepsy, cognitive impairment and a distinctive cerebro-cerebellar malformation.

PubMed

Afawi, Zaid; Mandelstam, Simone; Korczyn, Amos D; Kivity, Sara; Walid, Simri; Shalata, Adel; Oliver, Karen L; Corbett, Mark; Gecz, Jozef; Berkovic, Samuel F; Jackson, Graeme D

2013-07-01

We describe the clinical and radiological features of a family with a homozygous mutation in TBC1D24. The phenotype comprised onset of focal seizures at 2 months with prominent eye-blinking, facial and limb jerking with an oral sensory aura. These were controllable with medication but persisted into adult life. Associated features were mild to moderate intellectual disability and cerebellar features. MRI showed subtle cortical thickening with cerebellar atrophy and high signal confined to the ansiform lobule. The disorder is allelic with familial infantile myoclonic epilepsy, where intellect and neurologic examination are normal, highlighting the phenotypic variation with mutations of TBC1D24. Copyright © 2013 Elsevier B.V. All rights reserved.

Ultrastructural diversity between centrioles of eukaryotes.

PubMed

Gupta, Akshari; Kitagawa, Daiju

2018-02-16

Several decades of centriole research have revealed the beautiful symmetry present in these microtubule-based organelles, which are required to form centrosomes, cilia, and flagella in many eukaryotes. Centriole architecture is largely conserved across most organisms, however, individual centriolar features such as the central cartwheel or microtubule walls exhibit considerable variability when examined with finer resolution. Here, we review the ultrastructural characteristics of centrioles in commonly studied organisms, highlighting the subtle and not-so-subtle differences between specific structural components of these centrioles. Additionally, we survey some non-canonical centriole structures that have been discovered in various species, from the coaxial bicentrioles of protists and lower land plants to the giant irregular centrioles of the fungus gnat Sciara. Finally, we speculate on the functional significance of these differences between centrioles, and the contribution of individual structural elements such as the cartwheel or microtubules towards the stability of centrioles.Centriole structure, cartwheel, triplet microtubules, SAS-6, centrosome.

Deriving leaf mass per area (LMA) from foliar reflectance across a variety of plant species using continuous wavelet analysis

NASA Astrophysics Data System (ADS)

Cheng, Tao; Rivard, Benoit; Sánchez-Azofeifa, Arturo G.; Féret, Jean-Baptiste; Jacquemoud, Stéphane; Ustin, Susan L.

2014-01-01

Leaf mass per area (LMA), the ratio of leaf dry mass to leaf area, is a trait of central importance to the understanding of plant light capture and carbon gain. It can be estimated from leaf reflectance spectroscopy in the infrared region, by making use of information about the absorption features of dry matter. This study reports on the application of continuous wavelet analysis (CWA) to the estimation of LMA across a wide range of plant species. We compiled a large database of leaf reflectance spectra acquired within the framework of three independent measurement campaigns (ANGERS, LOPEX and PANAMA) and generated a simulated database using the PROSPECT leaf optical properties model. CWA was applied to the measured and simulated databases to extract wavelet features that correlate with LMA. These features were assessed in terms of predictive capability and robustness while transferring predictive models from the simulated database to the measured database. The assessment was also conducted with two existing spectral indices, namely the Normalized Dry Matter Index (NDMI) and the Normalized Difference index for LMA (NDLMA). Five common wavelet features were determined from the two databases, which showed significant correlations with LMA (R2: 0.51-0.82, p < 0.0001). The best robustness (R2 = 0.74, RMSE = 18.97 g/m2 and Bias = 0.12 g/m2) was obtained using a combination of two low-scale features (1639 nm, scale 4) and (2133 nm, scale 5), the first being predominantly important. The transferability of the wavelet-based predictive model to the whole measured database was either better than or comparable to those based on spectral indices. Additionally, only the wavelet-based model showed consistent predictive capabilities among the three measured data sets. In comparison, the models based on spectral indices were sensitive to site-specific data sets. Integrating the NDLMA spectral index and the two robust wavelet features improved the LMA prediction. One of the bands used by this spectral index, 1368 nm, was located in a strong atmospheric water absorption region and replacing it with the next available band (1340 nm) led to lower predictive accuracies. However, the two wavelet features were not affected by data quality in the atmospheric absorption regions and therefore showed potential for canopy-level investigations. The wavelet approach provides a different perspective into spectral responses to LMA variation than the traditional spectral indices and holds greater promise for implementation with airborne or spaceborne imaging spectroscopy data for mapping canopy foliar dry biomass.

Littoral assessment of mine burial signatures (LAMBS): buried landmine/background spectral-signature analyses

NASA Astrophysics Data System (ADS)

Kenton, Arthur C.; Geci, Duane M.; Ray, Kristofer J.; Thomas, Clayton M.; Salisbury, John W.; Mars, John C.; Crowley, James K.; Witherspoon, Ned H.; Holloway, John H., Jr.

2004-09-01

The objective of the Office of Naval Research (ONR) Rapid Overt Reconnaissance (ROR) program and the Airborne Littoral Reconnaissance Technologies (ALRT) project's LAMBS effort is to determine if electro-optical spectral discriminants exist that are useful for the detection of land mines in littoral regions. Statistically significant buried mine overburden and background signature data were collected over a wide spectral range (0.35 to 14 μm) to identify robust spectral features that might serve as discriminants for new airborne sensor concepts. LAMBS has expanded previously collected databases to littoral areas - primarily dry and wet sandy soils - where tidal, surf, and wind conditions can severely modify spectral signatures. At AeroSense 2003, we reported completion of three buried mine collections at an inland bay, Atlantic and Gulf of Mexico beach sites. We now report LAMBS spectral database analyses results using metrics which characterize the detection performance of general types of spectral detection algorithms. These metrics include mean contrast, spectral signal-to-clutter, covariance, information content, and spectral matched filter analyses. Detection performance of the buried land mines was analyzed with regard to burial age, background type, and environmental conditions. These analyses considered features observed due to particle size differences, surface roughness, surface moisture, and compositional differences.

A linear spectral matching technique for retrieving equivalent water thickness and biochemical constituents of green vegetation

NASA Technical Reports Server (NTRS)

Gao, Bo-Cai; Goetz, Alexander F. H.

1992-01-01

Over the last decade, technological advances in airborne imaging spectrometers, having spectral resolution comparable with laboratory spectrometers, have made it possible to estimate biochemical constituents of vegetation canopies. Wessman estimated lignin concentration from data acquired with NASA's Airborne Imaging Spectrometer (AIS) over Blackhawk Island in Wisconsin. A stepwise linear regression technique was used to determine the single spectral channel or channels in the AIS data that best correlated with measured lignin contents using chemical methods. The regression technique does not take advantage of the spectral shape of the lignin reflectance feature as a diagnostic tool nor the increased discrimination among other leaf components with overlapping spectral features. A nonlinear least squares spectral matching technique was recently reported for deriving both the equivalent water thicknesses of surface vegetation and the amounts of water vapor in the atmosphere from contiguous spectra measured with the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). The same technique was applied to a laboratory reflectance spectrum of fresh, green leaves. The result demonstrates that the fresh leaf spectrum in the 1.0-2.5 microns region consists of spectral components of dry leaves and the spectral component of liquid water. A linear least squares spectral matching technique for retrieving equivalent water thickness and biochemical components of green vegetation is described.

Littoral Assessment of Mine Burial Signatures (LAMBS) buried land mine/background spectral signature analyses

USGS Publications Warehouse

Kenton, A.C.; Geci, D.M.; Ray, K.J.; Thomas, C.M.; Salisbury, J.W.; Mars, J.C.; Crowley, J.K.; Witherspoon, N.H.; Holloway, J.H.; Harmon R.S.Broach J.T.Holloway, Jr. J.H.

2004-01-01

The objective of the Office of Naval Research (ONR) Rapid Overt Reconnaissance (ROR) program and the Airborne Littoral Reconnaissance Technologies (ALRT) project's LAMBS effort is to determine if electro-optical spectral discriminants exist that are useful for the detection of land mines in littoral regions. Statistically significant buried mine overburden and background signature data were collected over a wide spectral range (0.35 to 14 ??m) to identify robust spectral features that might serve as discriminants for new airborne sensor concepts. LAMBS has expanded previously collected databases to littoral areas - primarily dry and wet sandy soils - where tidal, surf, and wind conditions can severely modify spectral signatures. At AeroSense 2003, we reported completion of three buried mine collections at an inland bay, Atlantic and Gulf of Mexico beach sites.1 We now report LAMBS spectral database analyses results using metrics which characterize the detection performance of general types of spectral detection algorithms. These metrics include mean contrast, spectral signal-to-clutter, covariance, information content, and spectral matched filter analyses. Detection performance of the buried land mines was analyzed with regard to burial age, background type, and environmental conditions. These analyses considered features observed due to particle size differences, surface roughness, surface moisture, and compositional differences.

Single trial decoding of belief decision making from EEG and fMRI data using independent components features

PubMed Central

Douglas, Pamela K.; Lau, Edward; Anderson, Ariana; Head, Austin; Kerr, Wesley; Wollner, Margalit; Moyer, Daniel; Li, Wei; Durnhofer, Mike; Bramen, Jennifer; Cohen, Mark S.

2013-01-01

The complex task of assessing the veracity of a statement is thought to activate uniquely distributed brain regions based on whether a subject believes or disbelieves a given assertion. In the current work, we present parallel machine learning methods for predicting a subject's decision response to a given propositional statement based on independent component (IC) features derived from EEG and fMRI data. Our results demonstrate that IC features outperformed features derived from event related spectral perturbations derived from any single spectral band, yet were similar to accuracy across all spectral bands combined. We compared our diagnostic IC spatial maps with our conventional general linear model (GLM) results, and found that informative ICs had significant spatial overlap with our GLM results, yet also revealed unique regions like amygdala that were not statistically significant in GLM analyses. Overall, these results suggest that ICs may yield a parsimonious feature set that can be used along with a decision tree structure for interpretation of features used in classifying complex cognitive processes such as belief and disbelief across both fMRI and EEG neuroimaging modalities. PMID:23914164

Is Tridymite at Gale Crater Evidence for Silicic Volcanism on Mars?

NASA Technical Reports Server (NTRS)

Morris, Richard V.; Vaniman, David T.; Ming, Douglas W.; Graff, Trevor G.; Downs, Robert T.; Fendrich, Kim; Mertzman, Stanley A.

2016-01-01

The X-ray diffraction (XRD) instrument (CheMin) onboard the MSL rover Curiosity detected 17 wt% of the SiO2 polymorph tridymite (relative to bulk sample) for the Buckskin drill sample (73 wt% SiO2) obtained from sedimentary rock in the Murray formation at Gale Crater, Mars. Other detected crystalline materials are plagioclase, sanidine, cristobalite, cation-deficient magnetite, and anhydrite. XRD amorphous material constitutes approx. 60 wt% of bulk sample, and the position of its broad diffraction peak near approx. 26 deg. 2-theta is consistent with opal-A. Tridymite is a lowpressure, high-temperature mineral (approx. 870 to 1670 deg. C) whose XRD-identified occurrence on the Earth is usually associated with silicic (e.g., rhyolitic) volcanism. High SiO2 deposits have been detected at Gale crater by remote sensing from martian orbit and interpreted as opal-A on the basis H2O and Si-OH spectral features. Proposed opal-A formation pathways include precipitation of silica from lake waters and high-SiO2 residues of acid-sulfate leaching. Tridymite is nominally anhydrous and would not exhibit these spectral features. We have chemically and spectrally analyzed rhyolitic samples from New Mexico and Iwodake volcano (Japan). The glassy (by XRD) NM samples have H2O spectral features similar to opal-A. The Iwodake sample, which has been subjected to high-temperature acid sulfate leaching, also has H2O spectral features similar to opal-A. The Iwodake sample has approx. 98 wt% SiO2 and 1% wt% TiO2 (by XRF), tridymite (>80 wt.% of crystalline material without detectable quartz by XRD), and H2O and Si-OH spectral features. These results open the working hypothesis that the opal-A-like high-SiO2 deposits at Gale crater detected from martian orbit are products of alteration associated with silicic volcanism. The presence or absence of tridymite will depend on lava crystallization temperatures (NM) and post crystallization alteration temperatures (Iwodake).

DOE Office of Scientific and Technical Information (OSTI.GOV)

Honorio, J.; Goldstein, R.; Honorio, J.

We propose a simple, well grounded classification technique which is suited for group classification on brain fMRI data sets that have high dimensionality, small number of subjects, high noise level, high subject variability, imperfect registration and capture subtle cognitive effects. We propose threshold-split region as a new feature selection method and majority voteas the classification technique. Our method does not require a predefined set of regions of interest. We use average acros ssessions, only one feature perexperimental condition, feature independence assumption, and simple classifiers. The seeming counter-intuitive approach of using a simple design is supported by signal processing and statisticalmore » theory. Experimental results in two block design data sets that capture brain function under distinct monetary rewards for cocaine addicted and control subjects, show that our method exhibits increased generalization accuracy compared to commonly used feature selection and classification techniques.« less

Spectral Measurements of Geosynchronous Satellites During Glint Season

DTIC Science & Technology

2015-01-01

the satellite solar panels and has been observed in the past using broadband photometry techniques. In this paper, we present the first observations... photometry . We believe that these small-scale features can be exploited to discern satellite features such as solar panel orientation and secondary...Spectral Measurements of Geosynchronous Satellites During Glint Season Ryan M. Tucker, Evan M. Weld, Francis K. Chun, and Roger D. Tippets

Red Arcs on Tethys

NASA Image and Video Library

2015-07-29

Unusual arc-shaped, reddish streaks cut across the surface of Saturn's ice-rich moon Tethys in this enhanced-color mosaic. The red streaks are narrow, curved lines on the moon's surface, only a few miles (or kilometers) wide but several hundred miles (or kilometers) long. The red streaks are among the most unusual color features on Saturn's moons to be revealed by Cassini's cameras. A few of the red arcs can be faintly seen in Cassini imaging observations made earlier in the mission, but the color images for this observation, which were obtained in April 2015, were the first to show large northern areas of Tethys under the illumination and viewing conditions necessary to see the features clearly. As the Saturn system moved into its northern hemisphere summer over the past few years, northern latitudes have become increasingly well illuminated. As a result, the red arc features have become clearly visible for the first time. The origin of the features and their reddish color is currently a mystery to Cassini scientists. Possibilities being studied include ideas that the reddish material is exposed ice with chemical impurities, or the result of outgassing from inside Tethys. The streaks could also be associated with features like fractures that are below the resolution of the available images. Except for a few small craters on Dione, reddish tinted features are rare on other moons of Saturn. However, many reddish features are observed on the geologically young surface of Jupiter's moon Europa. Images taken using clear, green, infrared and ultraviolet spectral filters were combined to create the view, which highlights subtle color differences across Tethys' surface at wavelengths not visible to human eyes. The moon's surface is fairly uniform in natural color. The yellowish tones on the left side of the view are a result of alteration of the moon's surface by high-energy particles from Saturn's magnetosphere. This particle radiation slams into the moon's trailing hemisphere, modifying it chemically and changing its appearance in enhanced-color views like this one. The area of Tethys shown here is centered on 30 degrees north latitude, 187 degrees west longitude, and measures 305 by 258 miles (490 by 415 kilometers) across. The original color images were obtained at a resolution of about 2,300 feet (700 meters) per pixel on April 11, 2015. This is a cropped close-up of an area visible in PIA19636. This is a mosaic of images that have been photometrically calibrated and map-projected. http://photojournal.jpl.nasa.gov/catalog/PIA19637

Quality assessment of remote sensing image fusion using feature-based fourth-order correlation coefficient

NASA Astrophysics Data System (ADS)

Ma, Dan; Liu, Jun; Chen, Kai; Li, Huali; Liu, Ping; Chen, Huijuan; Qian, Jing

2016-04-01

In remote sensing fusion, the spatial details of a panchromatic (PAN) image and the spectrum information of multispectral (MS) images will be transferred into fused images according to the characteristics of the human visual system. Thus, a remote sensing image fusion quality assessment called feature-based fourth-order correlation coefficient (FFOCC) is proposed. FFOCC is based on the feature-based coefficient concept. Spatial features related to spatial details of the PAN image and spectral features related to the spectrum information of MS images are first extracted from the fused image. Then, the fourth-order correlation coefficient between the spatial and spectral features is calculated and treated as the assessment result. FFOCC was then compared with existing widely used indices, such as Erreur Relative Globale Adimensionnelle de Synthese, and quality assessed with no reference. Results of the fusion and distortion experiments indicate that the FFOCC is consistent with subjective evaluation. FFOCC significantly outperforms the other indices in evaluating fusion images that are produced by different fusion methods and that are distorted in spatial and spectral features by blurring, adding noise, and changing intensity. All the findings indicate that the proposed method is an objective and effective quality assessment for remote sensing image fusion.

Hyperspectral data mining to identify relevant canopy spectral features for estimating durum wheat growth, nitrogen status, and yield

USDA-ARS?s Scientific Manuscript database

Modern hyperspectral sensors permit reflectance measurements of crop canopies in hundreds of narrow spectral wavebands. While these sensors describe plant canopy reflectance in greater detail than multispectral sensors, they also suffer from issues with data redundancy and spectral autocorrelation. ...

Identification of spectrally similar materials using the USGS Tetracorder algorithm: The calcite-epidote-chlorite problem

USGS Publications Warehouse

Dalton, J.B.; Bove, D.J.; Mladinich, C.S.; Rockwell, B.W.

2004-01-01

A scheme to discriminate and identify materials having overlapping spectral absorption features has been developed and tested based on the U.S. Geological Survey (USGS) Tetracorder system. The scheme has been applied to remotely sensed imaging spectroscopy data acquired by the Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) instrument. This approach was used to identify the minerals calcite, epidote, and chlorite in the upper Animas River watershed, Colorado. The study was motivated by the need to characterize the distribution of calcite in the watershed and assess its acid-neutralizing potential with regard to acidic mine drainage. Identification of these three minerals is difficult because their diagnostic spectral features are all centered at 2.3 ??m, and have similar shapes and widths. Previous studies overestimated calcite abundance as a result of these spectral overlaps. The use of a reference library containing synthetic mixtures of the three minerals in varying proportions was found to simplify the task of identifying these minerals when used in conjunction with a rule-based expert system. Some inaccuracies in the mineral distribution maps remain, however, due to the influence of a fourth spectral component, sericite, which exhibits spectral absorption features at 2.2 and 2.4 ??m that overlap the 2.3-??m absorption features of the other three minerals. Whereas the endmember minerals calcite, epidote, chlorite, and sericite can be identified by the method presented here, discrepancies occur in areas where all four occur together as intimate mixtures. It is expected that future work will be able to reduce these discrepancies by including reference mixtures containing sericite. ?? 2004 Elsevier Inc. All rights reserved.

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.

Mapping vegetation in Yellowstone National Park using spectral feature analysis of AVIRIS data

USGS Publications Warehouse

Kokaly, Raymond F.; Despain, Don G.; Clark, Roger N.; Livo, K. Eric

2003-01-01

Knowledge of the distribution of vegetation on the landscape can be used to investigate ecosystem functioning. The sizes and movements of animal populations can be linked to resources provided by different plant species. This paper demonstrates the application of imaging spectroscopy to the study of vegetation in Yellowstone National Park (Yellowstone) using spectral feature analysis of data from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). AVIRIS data, acquired on August 7, 1996, were calibrated to surface reflectance using a radiative transfer model and field reflectance measurements of a ground calibration site. A spectral library of canopy reflectance signatures was created by averaging pixels of the calibrated AVIRIS data over areas of known forest and nonforest vegetation cover types in Yellowstone. Using continuum removal and least squares fitting algorithms in the US Geological Survey's Tetracorder expert system, the distributions of these vegetation types were determined by comparing the absorption features of vegetation in the spectral library with the spectra from the AVIRIS data. The 0.68 μm chlorophyll absorption feature and leaf water absorption features, centered near 0.98 and 1.20 μm, were analyzed. Nonforest cover types of sagebrush, grasslands, willows, sedges, and other wetland vegetation were mapped in the Lamar Valley of Yellowstone. Conifer cover types of lodgepole pine, whitebark pine, Douglas fir, and mixed Engelmann spruce/subalpine fir forests were spectrally discriminated and their distributions mapped in the AVIRIS images. In the Mount Washburn area of Yellowstone, a comparison of the AVIRIS map of forest cover types to a map derived from air photos resulted in an overall agreement of 74.1% (kappa statistic=0.62).

Ground-Based VIS/NIR Reflectance Spectra of 25143 Itokawa: What Hayabusa will See and How Ground-Based Data can Augment Analyses

NASA Technical Reports Server (NTRS)

Vilas, Faith; Abell, P. A.; Jarvis, K. S.

2004-01-01

Planning for the arrival of the Hayabusa spacecraft at asteroid 25143 Itokawa includes consideration of the expected spectral information to be obtained using the AMICA and NIRS instruments. The rotationally-resolved spatial coverage the asteroid we have obtained with ground-based telescopic spectrophotometry in the visible and near-infrared can be utilized here to address expected spacecraft data. We use spectrophotometry to simulate the types of data that Hayabusa will receive with the NIRS and AMICA instruments, and will demonstrate them here. The NIRS will cover a wavelength range from 0.85 m, and have a dispersion per element of 250 Angstroms. Thus, we are limited in coverage of the 1.0 micrometer and 2.0 micrometer mafic silicate absorption features. The ground-based reflectance spectra of Itokawa show a large component of olivine in its surface material, and the 2.0 micrometer feature is shallow. Determining the olivine to pyroxene abundance ratio is critically dependent on the attributes of the 1.0- and 2.0 micrometer features. With a cut-off near 2,1 micrometer the longer edge of the 2.0- feature will not be obtained by NIRS. Reflectance spectra obtained using ground-based telescopes can be used to determine the regional composition around space-based spectral observations, and possibly augment the longer wavelength spectral attributes. Similarly, the shorter wavelength end of the 1.0 micrometer absorption feature will be partially lost to the NIRS. The AMICA filters mimic the ECAS filters, and have wavelength coverage overlapping with the NIRS spectral range. We demonstrate how merging photometry from AMICA will extend the spectral coverage of the NIRS. Lessons learned from earlier spacecraft to asteroids should be considered.

Hyperspectral analysis of the ultramafic complex and adjacent lithologies at Mordor, NT, Australia

USGS Publications Warehouse

Rowan, L.C.; Simpson, C.J.; Mars, J.C.

2004-01-01

The Mordor Complex consists of a series of potassic ultramafic rocks which were intruded into Proterozoic felsic gneisses and amphibolite and are overlain by quartzite and unconsolidated deposits. In situ and laboratory 0.4 to 2.5 ??m reflectance spectra show Al-OH absorption features caused by absorption in muscovite, kaolinite, and illite/smectite in syenite, granitic gneiss, quartzite and unconsolidated sedimentary deposits, and Fe,Mg-OH features due to phlogopite, biotite, epidote, and hornblende in the mafic and ultramafic rocks. Ferrous-iron absorption positioned near 1.05 ??m is most intense in peridotite reflectance spectra. Ferric-iron absorption is intense in most of the felsic lithologies. HyMap data were recorded in 126 narrow bands from 0.43 to 2.5 ??m along a 7-km-wide swath with approximately 6-m spatial resolution. Correction of the data to spectral reflectance was accomplished by reference to in situ measurements of an extensive, alluvial plain. Spectral classes for matched filter processing were selected by using the pixel purity index procedure and analysis of in situ and laboratory spectra. Considering the spatial distribution of the resulting 14 classes, some classes were combined, which produced eight classes characterized by Al-OH absorption features, and three Fe,Mg-OH absorption-feature classes. Comparison of the distribution of these 11 spectral classes to a generalized lithologic map of the study area shows that the spectral distinction among the eight Al-OH classes is related to variations in primary lithology, weathering products, and vegetation density. Quartzite is represented in three classes, syenite corresponds to a single scattered class, quartz-muscovite-biotite schist defines a single very coherent class, and unconsolidated sediments are portrayed in four classes. The three mafic-ultramafic classes are distinguished on the basis of generally intense Fe,Mg-OH and ferrous-iron absorption features. A single class represents the main Mordor ultramafic mass. Epidote-bearing rocks define another class, which corresponds to biotite gneiss and, in the southern part of the area, to fracture zones. The third class, which exhibits Al-OH, as well as Fe,Mg-OH features, represents hornblende gneiss and other mafic gneisses. These results indicate the importance of analyzing the VNIR and SWIR spectral shape and albedo, as well as analyzing specific spectral features, for mapping lithologic units in this weathered terrain. ?? 2004 Elsevier Inc. All rights reserved.

Characterizing multivariate decoding models based on correlated EEG spectral features

PubMed Central

McFarland, Dennis J.

2013-01-01

Objective Multivariate decoding methods are popular techniques for analysis of neurophysiological data. The present study explored potential interpretative problems with these techniques when predictors are correlated. Methods Data from sensorimotor rhythm-based cursor control experiments was analyzed offline with linear univariate and multivariate models. Features were derived from autoregressive (AR) spectral analysis of varying model order which produced predictors that varied in their degree of correlation (i.e., multicollinearity). Results The use of multivariate regression models resulted in much better prediction of target position as compared to univariate regression models. However, with lower order AR features interpretation of the spectral patterns of the weights was difficult. This is likely to be due to the high degree of multicollinearity present with lower order AR features. Conclusions Care should be exercised when interpreting the pattern of weights of multivariate models with correlated predictors. Comparison with univariate statistics is advisable. Significance While multivariate decoding algorithms are very useful for prediction their utility for interpretation may be limited when predictors are correlated. PMID:23466267

Angiogenesis - a crucial step in breast cancer growth, progression and dissemination by Raman imaging.

PubMed

Kopeć, Monika; Abramczyk, Halina

2018-06-05

Combined micro-Raman imaging and AFM imaging are efficient methods for analyzing human tissue due to their high spatial and spectral resolution as well as sensitivity to subtle chemical, structural and topographical changes. The aim of this study was to determine biochemical composition and mechanical topography around blood vessels in the tumor mass of human breast tissue. Significant alterations of the chemical composition and structural architecture around the blood vessel were found compared to the normal breast tissue. A pronounced increase of collagen-fibroblast-glycocalyx network, as well as enhanced lactic acid, and glycogen activity in patients affected by breast cancer were reported. Copyright © 2018 Elsevier B.V. All rights reserved.

In-flight spectral performance monitoring of the Airborne Prism Experiment.

PubMed

D'Odorico, Petra; Alberti, Edoardo; Schaepman, Michael E

2010-06-01

Spectral performance of an airborne dispersive pushbroom imaging spectrometer cannot be assumed to be stable over a whole flight season given the environmental stresses present during flight. Spectral performance monitoring during flight is commonly accomplished by looking at selected absorption features present in the Sun, atmosphere, or ground, and their stability. The assessment of instrument performance in two different environments, e.g., laboratory and airborne, using precisely the same calibration reference, has not been possible so far. The Airborne Prism Experiment (APEX), an airborne dispersive pushbroom imaging spectrometer, uses an onboard in-flight characterization (IFC) facility, which makes it possible to monitor the sensor's performance in terms of spectral, radiometric, and geometric stability in flight and in the laboratory. We discuss in detail a new method for the monitoring of spectral instrument performance. The method relies on the monitoring of spectral shifts by comparing instrument-induced movements of absorption features on ground and in flight. Absorption lines originate from spectral filters, which intercept the full field of view (FOV) illuminated using an internal light source. A feature-fitting algorithm is used for the shift estimation based on Pearson's correlation coefficient. Environmental parameter monitoring, coregistered on board with the image and calibration data, revealed that differential pressure and temperature in the baffle compartment are the main driving parameters explaining the trend in spectral performance deviations in the time and the space (across-track) domains, respectively. The results presented in this paper show that the system in its current setup needs further improvements to reach a stable performance. Findings provided useful guidelines for the instrument revision currently under way. The main aim of the revision is the stabilization of the instrument for a range of temperature and pressure conditions to be encountered during operation.

The Rest of the C2 Iceberg

DTIC Science & Technology

2014-08-01

Iceberg Feature ones—another documented cognitive bias that is largely subconscious . A final opportunity lost by not having a forward geographic presence...leading to a subtle bias towards the tip-of-the-iceberg systems that most individuals have more famil- iarity with from their tactical backgrounds...as soon as possible to maintain career viability in a system biased more towards tactical achievement. Acknowledge That the Heart of Operational C2 Is

Mining and Querying Multimedia Data

DTIC Science & Technology

2011-09-29

able to capture more subtle spatial variations such as repetitiveness. Local feature descriptors such as SIFT [74] and SURF [12] have also been widely...empirically set to s = 90%, r = 50%, K = 20, where small variations lead to little perturbation of the output. The pseudo-code of the algorithm is...by constructing a three-layer graph based on clustering outputs, and executing a slight variation of random walk with restart algorithm. It provided

Characterization of 24-h cortisol release in obese and non-obese hyperandrogenic women.

PubMed

Miller, J E; Bray, M A; Faiman, C; Reyes, F I

1994-12-01

Excessive androgen output is a well-recognized feature of adrenocortical oversecretion in women with ovarian hyperandrogenism, or polycystic ovary disease (PCOD). However, evidence of a concomitant alteration of cortisol secretion is lacking even though obesity per se, a common clinical feature of PCOD, has been shown to be associated with cortisol oversecretion. To clarify whether a subtle alteration in cortisol secretion exists, a study of 24-h episodic cortisol release and post-prandial cortisol responses was undertaken in eight women with PCOD and eight normal women comprising equal numbers of obese and non-obese subjects. All four groups showed normal biphasic 24-h cortisol secretion profiles but cortisol pulse frequency was increased in the PCOD groups. Independently, both hyperandrogenism and obesity were associated with an accelerated cortisol clearance rate. These changes, together with normal or only slightly elevated 24-h cortisol integrated area under the curve, suggest an increased compensatory cortisol production in women with PCOD. Furthermore, subjects with PCOD and subjects with obesity showed different post-prandial cortisol responses to normal non-obese women. In conclusion, these subtle cortisol abnormalities may be a manifestation of altered central regulation of the hypothalamic-pituitary-adrenal axis and peripheral metabolic abnormalities, and may be linked to the pathophysiology of PCOD.

SPECTRAL DOMAIN VERSUS SWEPT SOURCE OPTICAL COHERENCE TOMOGRAPHY ANGIOGRAPHY OF THE RETINAL CAPILLARY PLEXUSES IN SICKLE CELL MACULOPATHY.

PubMed

Jung, Jesse J; Chen, Michael H; Frambach, Caroline R; Rofagha, Soraya; Lee, Scott S

2018-01-01

To compare the spectral domain and swept source optical coherence tomography angiography findings in two cases of sickle cell maculopathy. A 53-year-old man and a 24-year-old man both with sickle cell disease (hemoglobin SS) presented with no visual complaints; Humphrey visual field testing demonstrated asymptomatic paracentral scotomas that extended nasally in the involved eyes. Clinical examination and multimodal imaging including spectral domain and swept source optical coherence tomography, and spectral domain optical coherence tomography angiography and swept source optical coherence tomography angiography (Carl Zeiss Meditec Inc, Dublin, CA) were performed. Fundus examination of both patients revealed subtle thinning of the macula. En-face swept source optical coherence tomography confirmed the extent of the thinning correlating with the functional paracentral scotomas on Humphrey visual field. Swept source optical coherence tomography B-scan revealed multiple confluent areas of inner nuclear thinning and significant temporal retinal atrophy. En-face 6 × 6-mm spectral domain optical coherence tomography angiography of the macula demonstrated greater loss of the deep capillary plexus compared with the superficial capillary plexus. Swept source optical coherence tomography angiography 12 × 12-mm imaging captured the same macular findings and loss of both plexuses temporally outside the macula. In these two cases of sickle cell maculopathy, deep capillary plexus ischemia is more extensive within the macula, whereas both the superficial capillary plexus and deep capillary plexus are involved outside the macula likely due to the greater oxygen demands and watershed nature of these areas. Swept source optical coherence tomography angiography clearly demonstrates the angiographic extent of the disease correlating with the Humphrey visual field scotomas and confluent areas of inner nuclear atrophy.

Using ATR-FT/IR to detect carbohydrate-related molecular structure features of carinata meal and their in situ residues of ruminal fermentation in comparison with canola meal

NASA Astrophysics Data System (ADS)

Xin, Hangshu; Yu, Peiqiang

2013-10-01

There is no information on the co-products from carinata bio-fuel and bio-oil processing (carinata meal) in molecular structural profiles mainly related to carbohydrate biopolymers in relation to ruminant nutrition. Molecular analyses with Fourier transform infrared spectroscopy (FT/IR) technique with attenuated total reflectance (ATR) and chemometrics enable to detect structural features on a molecular basis. The objectives of this study were to: (1) determine carbohydrate conformation spectral features in original carinata meal, co-products from bio-fuel/bio-oil processing; and (2) investigate differences in carbohydrate molecular composition and functional group spectral intensities after in situ ruminal fermentation at 0, 12, 24 and 48 h compared to canola meal as a reference. The molecular spectroscopic parameters of carbohydrate profiles detected were structural carbohydrates (STCHO, mainly associated with hemi-cellulosic and cellulosic compounds; region and baseline ca. 1483-1184 cm-1), cellulosic compounds (CELC, region and baseline ca. 1304-1184 cm-1), total carbohydrates (CHO, region and baseline ca. 1193-889 cm-1) as well as the spectral ratios calculated based on respective spectral intensity data. The results showed that the spectral profiles of carinata meal were significantly different from that of canola meal in CHO 2nd peak area (center at ca. 1091 cm-1, region: 1102-1083 cm-1) and functional group peak intensity ratios such as STCHO 1st peak (ca. 1415 cm-1) to 2nd peak (ca. 1374 cm-1) height ratio, CHO 1st peak (ca. 1149 cm-1) to 3rd peak (ca. 1032 cm-1) height ratio, CELC to total CHO area ratio and STCHO to CELC area ratio, indicating that carinata meal may not in full accord with canola meal in carbohydrate utilization and availability in ruminants. Carbohydrate conformation and spectral features were changed by significant interaction of meal type and incubation time and almost all the spectral parameters were significantly decreased (P < 0.05) during 48 h ruminal degradation in both carinata meal and canola meal. Although carinata meal differed from canola meal in some carbohydrate spectral parameters, multivariate results from agglomerative hierarchical cluster analysis and principal component analysis showed that both original and in situ residues of two meals were not fully distinguished from each other within carbohydrate spectral regions. It was concluded that carbohydrate structural conformation could be detected in carinata meal by using ATR-FT/IR techniques and further study is needed to explore more information on molecular spectral features of other functional group such as protein structure profile and their association with potential nutrient supply and availability of carinata meal in animals.

Using ATR-FT/IR to detect carbohydrate-related molecular structure features of carinata meal and their in situ residues of ruminal fermentation in comparison with canola meal.

PubMed

Xin, Hangshu; Yu, Peiqiang

2013-10-01

There is no information on the co-products from carinata bio-fuel and bio-oil processing (carinata meal) in molecular structural profiles mainly related to carbohydrate biopolymers in relation to ruminant nutrition. Molecular analyses with Fourier transform infrared spectroscopy (FT/IR) technique with attenuated total reflectance (ATR) and chemometrics enable to detect structural features on a molecular basis. The objectives of this study were to: (1) determine carbohydrate conformation spectral features in original carinata meal, co-products from bio-fuel/bio-oil processing; and (2) investigate differences in carbohydrate molecular composition and functional group spectral intensities after in situ ruminal fermentation at 0, 12, 24 and 48 h compared to canola meal as a reference. The molecular spectroscopic parameters of carbohydrate profiles detected were structural carbohydrates (STCHO, mainly associated with hemi-cellulosic and cellulosic compounds; region and baseline ca. 1483-1184 cm(-1)), cellulosic compounds (CELC, region and baseline ca. 1304-1184 cm(-1)), total carbohydrates (CHO, region and baseline ca. 1193-889cm(-1)) as well as the spectral ratios calculated based on respective spectral intensity data. The results showed that the spectral profiles of carinata meal were significantly different from that of canola meal in CHO 2nd peak area (center at ca. 1091 cm(-1), region: 1102-1083 cm(-1)) and functional group peak intensity ratios such as STCHO 1st peak (ca. 1415 cm(-1)) to 2nd peak (ca. 1374 cm(-1)) height ratio, CHO 1st peak (ca. 1149 cm(-1)) to 3rd peak (ca. 1032 cm(-1)) height ratio, CELC to total CHO area ratio and STCHO to CELC area ratio, indicating that carinata meal may not in full accord with canola meal in carbohydrate utilization and availability in ruminants. Carbohydrate conformation and spectral features were changed by significant interaction of meal type and incubation time and almost all the spectral parameters were significantly decreased (P<0.05) during 48 h ruminal degradation in both carinata meal and canola meal. Although carinata meal differed from canola meal in some carbohydrate spectral parameters, multivariate results from agglomerative hierarchical cluster analysis and principal component analysis showed that both original and in situ residues of two meals were not fully distinguished from each other within carbohydrate spectral regions. It was concluded that carbohydrate structural conformation could be detected in carinata meal by using ATR-FT/IR techniques and further study is needed to explore more information on molecular spectral features of other functional group such as protein structure profile and their association with potential nutrient supply and availability of carinata meal in animals. Copyright © 2013 Elsevier B.V. All rights reserved.

An analysis-by-synthesis approach to the estimation of vocal cord polyp features.

PubMed

Koizumi, T; Taniguchi, S; Itakura, F

1993-09-01

This paper deals with a new noninvasive method of estimating vocal cord polyp features through hoarse-voice analysis. A noteworthy feature of this method is that it enables us not only to discriminate hoarse voices caused by pathological vocal cords with a single golf-ball-like polyp from normal voices, but also to estimate polyp features such as the mass and dimension of polyp through the use of a novel model of pathological vocal cords which has been devised to simulate the subtle movement of the vocal cords. A synthetic hoarse voice produced with a hoarse-voice synthesizer is compared with a natural hoarse voice caused by the vocal cord polyp in terms of a distance measure and the polyp features are estimated by minimizing the distance measure. Some estimates of polyp dimension that have been obtained by applying this procedure to hoarse voices are found to compare favorably with actual polyp dimensions, demonstrating that the procedure is effective for estimating the features of golf-ball-like vocal cord polyps.

Multisensor Analysis of Spectral Dimensionality and Soil Diversity in the Great Central Valley of California.

PubMed

Sousa, Daniel; Small, Christopher

2018-02-14

Planned hyperspectral satellite missions and the decreased revisit time of multispectral imaging offer the potential for data fusion to leverage both the spectral resolution of hyperspectral sensors and the temporal resolution of multispectral constellations. Hyperspectral imagery can also be used to better understand fundamental properties of multispectral data. In this analysis, we use five flight lines from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) archive with coincident Landsat 8 acquisitions over a spectrally diverse region of California to address the following questions: (1) How much of the spectral dimensionality of hyperspectral data is captured in multispectral data?; (2) Is the characteristic pyramidal structure of the multispectral feature space also present in the low order dimensions of the hyperspectral feature space at comparable spatial scales?; (3) How much variability in rock and soil substrate endmembers (EMs) present in hyperspectral data is captured by multispectral sensors? We find nearly identical partitions of variance, low-order feature space topologies, and EM spectra for hyperspectral and multispectral image composites. The resulting feature spaces and EMs are also very similar to those from previous global multispectral analyses, implying that the fundamental structure of the global feature space is present in our relatively small spatial subset of California. Finally, we find that the multispectral dataset well represents the substrate EM variability present in the study area - despite its inability to resolve narrow band absorptions. We observe a tentative but consistent physical relationship between the gradation of substrate reflectance in the feature space and the gradation of sand versus clay content in the soil classification system.

Multisensor Analysis of Spectral Dimensionality and Soil Diversity in the Great Central Valley of California

PubMed Central

Small, Christopher

2018-01-01

Planned hyperspectral satellite missions and the decreased revisit time of multispectral imaging offer the potential for data fusion to leverage both the spectral resolution of hyperspectral sensors and the temporal resolution of multispectral constellations. Hyperspectral imagery can also be used to better understand fundamental properties of multispectral data. In this analysis, we use five flight lines from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) archive with coincident Landsat 8 acquisitions over a spectrally diverse region of California to address the following questions: (1) How much of the spectral dimensionality of hyperspectral data is captured in multispectral data?; (2) Is the characteristic pyramidal structure of the multispectral feature space also present in the low order dimensions of the hyperspectral feature space at comparable spatial scales?; (3) How much variability in rock and soil substrate endmembers (EMs) present in hyperspectral data is captured by multispectral sensors? We find nearly identical partitions of variance, low-order feature space topologies, and EM spectra for hyperspectral and multispectral image composites. The resulting feature spaces and EMs are also very similar to those from previous global multispectral analyses, implying that the fundamental structure of the global feature space is present in our relatively small spatial subset of California. Finally, we find that the multispectral dataset well represents the substrate EM variability present in the study area – despite its inability to resolve narrow band absorptions. We observe a tentative but consistent physical relationship between the gradation of substrate reflectance in the feature space and the gradation of sand versus clay content in the soil classification system. PMID:29443900

The Berkeley SuperNova Ia Program (BSNIP): Dataset and Initial Analysis

NASA Astrophysics Data System (ADS)

Silverman, Jeffrey; Ganeshalingam, M.; Kong, J.; Li, W.; Filippenko, A.

2012-01-01

I will present spectroscopic data from the Berkeley SuperNova Ia Program (BSNIP), their initial analysis, and the results of attempts to use spectral information to improve cosmological distance determinations to Type Ia supernova (SNe Ia). The dataset consists of 1298 low-redshift (z< 0.2) optical spectra of 582 SNe Ia observed from 1989 through the end of 2008. Many of the SNe have well-calibrated light curves with measured distance moduli as well as spectra that have been corrected for host-galaxy contamination. I will also describe the spectral classification scheme employed (using the SuperNova Identification code, SNID; Blondin & Tonry 2007) which utilizes a newly constructed set of SNID spectral templates. The sheer size of the BSNIP dataset and the consistency of the observation and reduction methods make this sample unique among all other published SN Ia datasets. I will also discuss measurements of the spectral features of about one-third of the spectra which were obtained within 20 days of maximum light. I will briefly describe the adopted method of automated, robust spectral-feature definition and measurement which expands upon similar previous studies. Comparisons of these measurements of SN Ia spectral features to photometric observables will be presented with an eye toward using spectral information to calculate more accurate cosmological distances. Finally, I will comment on related projects which also utilize the BSNIP dataset that are planned for the near future. This research was supported by NSF grant AST-0908886 and the TABASGO Foundation. I am grateful to Marc J. Staley for a Graduate Fellowship.

Fourier-transform-infrared-spectroscopy based spectral-biomarker selection towards optimum diagnostic differentiation of oral leukoplakia and cancer.

PubMed

Banerjee, Satarupa; Pal, Mousumi; Chakrabarty, Jitamanyu; Petibois, Cyril; Paul, Ranjan Rashmi; Giri, Amita; Chatterjee, Jyotirmoy

2015-10-01

In search of specific label-free biomarkers for differentiation of two oral lesions, namely oral leukoplakia (OLK) and oral squamous-cell carcinoma (OSCC), Fourier-transform infrared (FTIR) spectroscopy was performed on paraffin-embedded tissue sections from 47 human subjects (eight normal (NOM), 16 OLK, and 23 OSCC). Difference between mean spectra (DBMS), Mann-Whitney's U test, and forward feature selection (FFS) techniques were used for optimising spectral-marker selection. Classification of diseases was performed with linear and quadratic support vector machine (SVM) at 10-fold cross-validation, using different combinations of spectral features. It was observed that six features obtained through FFS enabled differentiation of NOM and OSCC tissue (1782, 1713, 1665, 1545, 1409, and 1161 cm(-1)) and were most significant, able to classify OLK and OSCC with 81.3 % sensitivity, 95.7 % specificity, and 89.7 % overall accuracy. The 43 spectral markers extracted through Mann-Whitney's U Test were the least significant when quadratic SVM was used. Considering the high sensitivity and specificity of the FFS technique, extracting only six spectral biomarkers was thus most useful for diagnosis of OLK and OSCC, and to overcome inter and intra-observer variability experienced in diagnostic best-practice histopathological procedure. By considering the biochemical assignment of these six spectral signatures, this work also revealed altered glycogen and keratin content in histological sections which could able to discriminate OLK and OSCC. The method was validated through spectral selection by the DBMS technique. Thus this method has potential for diagnostic cost minimisation for oral lesions by label-free biomarker identification.

Search for Feo and Pyroxene on MERCURY?S Surface

NASA Astrophysics Data System (ADS)

Sprague, Ann L.; Emery, Joshua P.

Results from spectral observations of Mercury's surface in the wavelength range 0.8 to 5.5 micrometers will be reported. The data were obtained at the NASA Infrared Telescope Facility on Mauna Kea Hawaii. We used SpeX a long slit imaging system developed at the IRTF for high resolving power spatially resolved spectroscopy throughout the solar system. We aligned the spectral slit with Mercury's geographic longitude and systematically moved it across the Earth-facing disk to obtain multiple disk-resolved spectral images. The entire data set provides spatial coverage of the Earth-facing disk limited only by atmospheric turbulence and the diffraction limit for each wavelength. We used SpeX in two spectral regions in the R 2000 mode. In the first case between 0.8 and 2.5 micrometer to search for the 0.9 to 1.0 micrometer reflectance absorption feature caused by the Fe2+ electronic transfer in FeO. We also measured the 4.5 to 5.5 micrometer flux from Mercury. This is a region of diagnostic features caused by the presence of volume scattering in pyroxene and olivine. These data will be compared to previous observations that showed an anomalous emission feature at 5.5 micrometer and to others that exhibited a feature closely resembling that from pyroxene.

Neural network modeling of a dolphin's sonar discrimination capabilities.

PubMed

Au, W W; Andersen, L N; Rasmussen, A R; Roitblat, H L; Nachtigall, P E

1995-07-01

The capability of an echolocating dolphin to discriminate differences in the wall thickness of cylinders was previously modeled by a counterpropagation neural network using only spectral information from the echoes. In this study, both time and frequency information were used to model the dolphin discrimination capabilities. Echoes from the same cylinders were digitized using a broadband simulated dolphin sonar signal with the transducer mounted on the dolphin's pen. The echoes were filtered by a bank of continuous constant-Q digital filters and the energy from each filter was computed in time increments of 1/bandwidth. Echo features of the standard and each comparison target were analyzed in pairs by a counterpropagation neural network, a backpropagation neural network, and a model using Euclidean distance measures. The backpropagation network performed better than both the counterpropagation network, and the Euclidean model, using either spectral-only features or combined temporal and spectral features. All models performed better using features containing both temporal and spectral information. The backpropagation network was able to perform better than the dolphins for noise-free echoes with Q values as low as 2 and 3. For a Q of 2, only temporal information was available. However, with noisy data, the network required a Q of 8 in order to perform as well as the dolphin.

Breast-Lesion Characterization using Textural Features of Quantitative Ultrasound Parametric Maps.

PubMed

Sadeghi-Naini, Ali; Suraweera, Harini; Tran, William Tyler; Hadizad, Farnoosh; Bruni, Giancarlo; Rastegar, Rashin Fallah; Curpen, Belinda; Czarnota, Gregory J

2017-10-20

This study evaluated, for the first time, the efficacy of quantitative ultrasound (QUS) spectral parametric maps in conjunction with texture-analysis techniques to differentiate non-invasively benign versus malignant breast lesions. Ultrasound B-mode images and radiofrequency data were acquired from 78 patients with suspicious breast lesions. QUS spectral-analysis techniques were performed on radiofrequency data to generate parametric maps of mid-band fit, spectral slope, spectral intercept, spacing among scatterers, average scatterer diameter, and average acoustic concentration. Texture-analysis techniques were applied to determine imaging biomarkers consisting of mean, contrast, correlation, energy and homogeneity features of parametric maps. These biomarkers were utilized to classify benign versus malignant lesions with leave-one-patient-out cross-validation. Results were compared to histopathology findings from biopsy specimens and radiology reports on MR images to evaluate the accuracy of technique. Among the biomarkers investigated, one mean-value parameter and 14 textural features demonstrated statistically significant differences (p < 0.05) between the two lesion types. A hybrid biomarker developed using a stepwise feature selection method could classify the legions with a sensitivity of 96%, a specificity of 84%, and an AUC of 0.97. Findings from this study pave the way towards adapting novel QUS-based frameworks for breast cancer screening and rapid diagnosis in clinic.

Hidden flexion injury of the cervical spine.

PubMed

Webb, J K; Broughton, R B; McSweeney, T; Park, W M

1976-08-01

This paper describes seven patients who developed late vertebral deformity after flexion injuries of the cervical spine. In four the clinical and radiological features were subtle and because the patients walked into an emergency department the severity of the injury was not initially appreciated. Certain specific clinical and radiological features of flexion injury are described and emphasis is placed on the importance of correct management. A radiological tetrad is described which should alert the surgeon to the possibility of damage to the posterior interspinous complex of the cervical spine and so lead to further radiological investigations. Despite the frequency of flexion injuries the alarming complications described in this paper are rare.

Atmospheric Sensitivity to Spectral Top-of-Atmosphere Solar Irradiance Perturbations, Using MODTRAN-5 Radiative Transfer Algorithm

NASA Astrophysics Data System (ADS)

Anderson, G.; Berk, A.; Harder, G.; Fontenla, J.; Shettle, E.; Pilewski, P.; Kindel, B.; Chetwynd, J.; Gardner, J.; Hoke, M.; Jordan, A.; Lockwood, R.; Felde, G.; Archarya, P.

2006-12-01

The opportunity to insert state-of-the-art solar irradiance measurements and calculations, with subtle perturbations, into a narrow spectral resolution radiative transfer model has recently been facilitated through release of MODTRAN-5 (MOD5). The new solar data are from: (1) SORCE satellite measurements of solar variability over solar rotation cycle, & (2) ultra-narrow calculation of a new solar source irradiance, extending over the full MOD5 spectral range, from 0.2 um to far-IR. MODTRAN-5, MODerate resolution radiance and TRANsmittance code, has been developed collaboratively by Air Force Research Laboratory and Spectral Sciences, Inc., with history dating back to LOWTRAN. It includes approximations for all local thermodynamic equilibrium terms associated with molecular, cloud, aerosol and surface components for emission, scattering, and reflectance, including multiple scattering, refraction and a statistical implementation of Correlated-k averaging. The band model is based on 0.1 cm-1 (also 1.0, 5.0 and 15.0 cm-1 statistical binning for line centers within the interval, captured through an exact formulation of the full Voigt line shape. Spectroscopic parameters are from HITRAN 2004 with user-defined options for additional gases. Recent validation studies show MOD5 replicates line-by-line brightness temperatures to within ~0.02ºK average and <1.0ºK RMS. MOD5 can then serve as a surrogate for a variety of perturbation studies, including the two modes for the solar source function, Io. (1) Data from the Solar Radiation and Climate Experiment (SORCE) satellite mission provide state-of-the-art measurements of UV, visible, near-IR, plus total solar radiation, on near real-time basis. These internally consistent estimates of Sun's output over solar rotation and longer time scales are valuable inputs for studying effects of Sun's radiation on Earth's atmosphere and climate. When solar rotation encounters bright plage and dark sunspots, relative variations are expected to be very small in visible wavelengths, although absolute power is substantial. SORCE's Spectral Irradiance Monitor measurements are readily included in comparative MOD5 calculations. (2) The embedded solar irradiance within MOD5 must be compatible with the chosen band model resolution binning. By matching resolutions some issues related to the correlated-k band model parameterizations can be tested. Two high resolution solar irradiances, the MOD5 default irradiance (Kurucz) and a new compilation associated with Solar Radiation Physical Modeling project (Fontenla), are compared to address the potential impact of discrepancies between any sets of irradiances. The magnitude of solar variability, as measured and calculated, can lead to subtle changes in heating/cooling rates throughout the atmosphere, as a function of altitude and wavelength. By holding chemical & dynamical responses constant, only controlled distributions of absorbing gases, aerosols and clouds will contribute to observed 1st order radiative effects.

The discovery of a new infrared emission feature at 1905 wavenumbers (5.25 microns) in the spectrum of BD + 30 deg 3639 and its relation to the polycyclic aromatic hydrocarbon model

NASA Technical Reports Server (NTRS)

Allamandola, L. J.; Bregman, J. D.; Sandford, S. A.; Tielens, A. G. G. M.; Witteborn, F. C.

1989-01-01

A new IR emission feature at 1905/cm (5.25 microns) has been discovered in the spectrum of BD + 30 deg 3639. This feature joins the family of well-known IR emission features at 3040, 2940, 1750, 1610, '1310', 1160, and 890/cm. The origin of this new feature is discussed and it is assigned to an overtone or combination band involving C-H bending modes of polycyclic aromatic hydrocarbons (PAHs). Laboratory work suggests that spectral studies of the 2000-1650/cm region may be very useful in elucidating the molecular structure of interstellar PAHs. The new feature, in conjunction with other recently discovered spectral structures, suggests that the narrow IR emission features originate in PAH molecules rather than large carbon grains.

Feature Selection for Ridge Regression with Provable Guarantees.

PubMed

Paul, Saurabh; Drineas, Petros

2016-04-01

We introduce single-set spectral sparsification as a deterministic sampling-based feature selection technique for regularized least-squares classification, which is the classification analog to ridge regression. The method is unsupervised and gives worst-case guarantees of the generalization power of the classification function after feature selection with respect to the classification function obtained using all features. We also introduce leverage-score sampling as an unsupervised randomized feature selection method for ridge regression. We provide risk bounds for both single-set spectral sparsification and leverage-score sampling on ridge regression in the fixed design setting and show that the risk in the sampled space is comparable to the risk in the full-feature space. We perform experiments on synthetic and real-world data sets; a subset of TechTC-300 data sets, to support our theory. Experimental results indicate that the proposed methods perform better than the existing feature selection methods.

Multivariate pattern analysis reveals subtle brain anomalies relevant to the cognitive phenotype in neurofibromatosis type 1.

PubMed

Duarte, João V; Ribeiro, Maria J; Violante, Inês R; Cunha, Gil; Silva, Eduardo; Castelo-Branco, Miguel

2014-01-01

Neurofibromatosis Type 1 (NF1) is a common genetic condition associated with cognitive dysfunction. However, the pathophysiology of the NF1 cognitive deficits is not well understood. Abnormal brain structure, including increased total brain volume, white matter (WM) and grey matter (GM) abnormalities have been reported in the NF1 brain. These previous studies employed univariate model-driven methods preventing detection of subtle and spatially distributed differences in brain anatomy. Multivariate pattern analysis allows the combination of information from multiple spatial locations yielding a discriminative power beyond that of single voxels. Here we investigated for the first time subtle anomalies in the NF1 brain, using a multivariate data-driven classification approach. We used support vector machines (SVM) to classify whole-brain GM and WM segments of structural T1 -weighted MRI scans from 39 participants with NF1 and 60 non-affected individuals, divided in children/adolescents and adults groups. We also employed voxel-based morphometry (VBM) as a univariate gold standard to study brain structural differences. SVM classifiers correctly classified 94% of cases (sensitivity 92%; specificity 96%) revealing the existence of brain structural anomalies that discriminate NF1 individuals from controls. Accordingly, VBM analysis revealed structural differences in agreement with the SVM weight maps representing the most relevant brain regions for group discrimination. These included the hippocampus, basal ganglia, thalamus, and visual cortex. This multivariate data-driven analysis thus identified subtle anomalies in brain structure in the absence of visible pathology. Our results provide further insight into the neuroanatomical correlates of known features of the cognitive phenotype of NF1. Copyright © 2012 Wiley Periodicals, Inc.

Changes in the Spectral Features of Zinc Phthalocyanine Induced by Nitrogen Dioxide Gas in Solution and in Solid Polymer Nanofiber Media.

PubMed

Zugle, Ruphino; Tetteh, Samuel

2017-03-01

The changes in the spectral features of zinc phthalocyanine in the visible domain as a result of its interaction with nitrogen dioxide gas were assessed in this work. This was done both in solution and when the phthalocyanine was incorporated into a solid polystyrene polymer nanofiber matrix. The spectral changes were found to be spontaneous and marked in both cases suggesting a rapid response criterion for the detection of the gas. In particular, the functionalised nano-fabric material could serve as a practical fire alarm system as it rapidly detects the nitrogen dioxide gas generated during burning.

Mid-infrared (5.0-7.0 microns) imaging spectroscopy of the moon from the KAO

NASA Technical Reports Server (NTRS)

Bell, James F., III; Bregman, Jesse D.; Rank, David M.; Temi, Pasquale; Roush, Ted L.; Hawke, B. Ray; Lucey, Paul G.; Pollack, James B.

1995-01-01

A series of 71 mid-infrared images of a small region of the Moon were obtained from the KAO in October, 1993. These images have been assembled into a 5.0 to 7.0 micron image cube that has been calibrated relative to the average spectrum of this region of the Moon at these wavelengths. The data show that clear, detectable spectral differences exist on the Moon in the mid-IR. Some of the spectral differences are correlated with morphologic features such as craters. Specific spectral features near 5.6 and 6.7 microns may be related to the presence of plagioclase or pyroxene.

Adaptation to spectrally-rotated speech.

PubMed

Green, Tim; Rosen, Stuart; Faulkner, Andrew; Paterson, Ruth

2013-08-01

Much recent interest surrounds listeners' abilities to adapt to various transformations that distort speech. An extreme example is spectral rotation, in which the spectrum of low-pass filtered speech is inverted around a center frequency (2 kHz here). Spectral shape and its dynamics are completely altered, rendering speech virtually unintelligible initially. However, intonation, rhythm, and contrasts in periodicity and aperiodicity are largely unaffected. Four normal hearing adults underwent 6 h of training with spectrally-rotated speech using Continuous Discourse Tracking. They and an untrained control group completed pre- and post-training speech perception tests, for which talkers differed from the training talker. Significantly improved recognition of spectrally-rotated sentences was observed for trained, but not untrained, participants. However, there were no significant improvements in the identification of medial vowels in /bVd/ syllables or intervocalic consonants. Additional tests were performed with speech materials manipulated so as to isolate the contribution of various speech features. These showed that preserving intonational contrasts did not contribute to the comprehension of spectrally-rotated speech after training, and suggested that improvements involved adaptation to altered spectral shape and dynamics, rather than just learning to focus on speech features relatively unaffected by the transformation.

Using spectral information in forensic imaging.

PubMed

Miskelly, Gordon M; Wagner, John H

2005-12-20

Improved detection of forensic evidence by combining narrow band photographic images taken at a range of wavelengths is dependent on the substance of interest having a significantly different spectrum from the underlying substrate. While some natural substances such as blood have distinctive spectral features which are readily distinguished from common colorants, this is not true for visualization agents commonly used in forensic science. We now show that it is possible to select reagents with narrow spectral features that lead to increased visibility using digital cameras and computer image enhancement programs even if their coloration is much less intense to the unaided eye than traditional reagents. The concept is illustrated by visualising latent fingermarks on paper with the zinc complex of Ruhemann's Purple, cyanoacrylate-fumed fingerprints with Eu(tta)(3)(phen), and soil prints with 2,6-bis(benzimidazol-2-yl)-4-[4'-(dimethylamino)phenyl]pyridine [BBIDMAPP]. In each case background correction is performed at one or two wavelengths bracketing the narrow absorption or emission band of these compounds. However, compounds with sharp spectral features would also lead to improved detection using more advanced algorithms such as principal component analysis.

Multitaper scan-free spectrum estimation using a rotational shear interferometer.

PubMed

Lepage, Kyle; Thomson, David J; Kraut, Shawn; Brady, David J

2006-05-01

Multitaper methods for a scan-free spectrum estimation that uses a rotational shear interferometer are investigated. Before source spectra can be estimated the sources must be detected. A source detection algorithm based upon the multitaper F-test is proposed. The algorithm is simulated, with additive, white Gaussian detector noise. A source with a signal-to-noise ratio (SNR) of 0.71 is detected 2.9 degrees from a source with a SNR of 70.1, with a significance level of 10(-4), approximately 4 orders of magnitude more significant than the source detection obtained with a standard detection algorithm. Interpolation and the use of prewhitening filters are investigated in the context of rotational shear interferometer (RSI) source spectra estimation. Finally, a multitaper spectrum estimator is proposed, simulated, and compared with untapered estimates. The multitaper estimate is found via simulation to distinguish a spectral feature with a SNR of 1.6 near a large spectral feature. The SNR of 1.6 spectral feature is not distinguished by the untapered spectrum estimate. The findings are consistent with the strong capability of the multitaper estimate to reduce out-of-band spectral leakage.

Multitaper scan-free spectrum estimation using a rotational shear interferometer

NASA Astrophysics Data System (ADS)

Lepage, Kyle; Thomson, David J.; Kraut, Shawn; Brady, David J.

2006-05-01

Multitaper methods for a scan-free spectrum estimation that uses a rotational shear interferometer are investigated. Before source spectra can be estimated the sources must be detected. A source detection algorithm based upon the multitaper F-test is proposed. The algorithm is simulated, with additive, white Gaussian detector noise. A source with a signal-to-noise ratio (SNR) of 0.71 is detected 2.9° from a source with a SNR of 70.1, with a significance level of 10-4, ˜4 orders of magnitude more significant than the source detection obtained with a standard detection algorithm. Interpolation and the use of prewhitening filters are investigated in the context of rotational shear interferometer (RSI) source spectra estimation. Finally, a multitaper spectrum estimator is proposed, simulated, and compared with untapered estimates. The multitaper estimate is found via simulation to distinguish a spectral feature with a SNR of 1.6 near a large spectral feature. The SNR of 1.6 spectral feature is not distinguished by the untapered spectrum estimate. The findings are consistent with the strong capability of the multitaper estimate to reduce out-of-band spectral leakage.

Hyperspectral Imaging Sensors and the Marine Coastal Zone

NASA Technical Reports Server (NTRS)

Richardson, Laurie L.

2000-01-01

Hyperspectral imaging sensors greatly expand the potential of remote sensing to assess, map, and monitor marine coastal zones. Each pixel in a hyperspectral image contains an entire spectrum of information. As a result, hyperspectral image data can be processed in two very different ways: by image classification techniques, to produce mapped outputs of features in the image on a regional scale; and by use of spectral analysis of the spectral data embedded within each pixel of the image. The latter is particularly useful in marine coastal zones because of the spectral complexity of suspended as well as benthic features found in these environments. Spectral-based analysis of hyperspectral (AVIRIS) imagery was carried out to investigate a marine coastal zone of South Florida, USA. Florida Bay is a phytoplankton-rich estuary characterized by taxonomically distinct phytoplankton assemblages and extensive seagrass beds. End-member spectra were extracted from AVIRIS image data corresponding to ground-truth sample stations and well-known field sites. Spectral libraries were constructed from the AVIRIS end-member spectra and used to classify images using the Spectral Angle Mapper (SAM) algorithm, a spectral-based approach that compares the spectrum, in each pixel of an image with each spectrum in a spectral library. Using this approach different phytoplankton assemblages containing diatoms, cyanobacteria, and green microalgae, as well as benthic community (seagrasses), were mapped.

Spectra of late type dwarf stars of known abundance for stellar population models

NASA Technical Reports Server (NTRS)

Oconnell, R. W.

1990-01-01

The project consisted of two parts. The first was to obtain new low-dispersion, long-wavelength, high S/N IUE spectra of F-G-K dwarf stars with previously determined abundances, temperatures, and gravities. To insure high quality, the spectra are either trailed, or multiple exposures are taken within the large aperture. Second, the spectra are assembled into a library which combines the new data with existing IUE Archive data to yield mean spectral energy distributions for each important type of star. My principal responsibility is the construction and maintenance of this UV spectral library. It covers the spectral range 1200-3200A and is maintained in two parts: a version including complete wavelength coverage at the full spectral resolution of the Low Resolution cameras; and a selected bandpass version, consisting of the mean flux in pre-selected 20A bands. These bands are centered on spectral features or continuum regions of special utility - e.g. the C IV lambda 1550 or Mg II lambda 2800 feature. In the middle-UV region, special emphasis is given to those features (including continuum 'breaks') which are most useful in the study of F-G-K star spectra in the integrated light of old stellar populations.

Determination of Primary Spectral Bands for Remote Sensing of Aquatic Environments

DTIC Science & Technology

2007-12-20

spectral bands are always facing the possibility of missing important spectral features of special cases, such as some coral reefs and/or seagrass ...Res. 1998, 103(C 10), 21,601-621,609. 16. Kirk, J. T. 0. 1994 Light & Photosynthesis in Aquatic Ecosystems, University Press, Cambridge. 17. Lee, Z

Onboard spectral imager data processor

NASA Astrophysics Data System (ADS)

Otten, Leonard J.; Meigs, Andrew D.; Franklin, Abraham J.; Sears, Robert D.; Robison, Mark W.; Rafert, J. Bruce; Fronterhouse, Donald C.; Grotbeck, Ronald L.

1999-10-01

Previous papers have described the concept behind the MightySat II.1 program, the satellite's Fourier Transform imaging spectrometer's optical design, the design for the spectral imaging payload, and its initial qualification testing. This paper discusses the on board data processing designed to reduce the amount of downloaded data by an order of magnitude and provide a demonstration of a smart spaceborne spectral imaging sensor. Two custom components, a spectral imager interface 6U VME card that moves data at over 30 MByte/sec, and four TI C-40 processors mounted to a second 6U VME and daughter card, are used to adapt the sensor to the spacecraft and provide the necessary high speed processing. A system architecture that offers both on board real time image processing and high-speed post data collection analysis of the spectral data has been developed. In addition to the on board processing of the raw data into a usable spectral data volume, one feature extraction technique has been incorporated. This algorithm operates on the basic interferometric data. The algorithm is integrated within the data compression process to search for uploadable feature descriptions.

Spectrum recovery method based on sparse representation for segmented multi-Gaussian model

NASA Astrophysics Data System (ADS)

Teng, Yidan; Zhang, Ye; Ti, Chunli; Su, Nan

2016-09-01

Hyperspectral images can realize crackajack features discriminability for supplying diagnostic characteristics with high spectral resolution. However, various degradations may generate negative influence on the spectral information, including water absorption, bands-continuous noise. On the other hand, the huge data volume and strong redundancy among spectrums produced intense demand on compressing HSIs in spectral dimension, which also leads to the loss of spectral information. The reconstruction of spectral diagnostic characteristics has irreplaceable significance for the subsequent application of HSIs. This paper introduces a spectrum restoration method for HSIs making use of segmented multi-Gaussian model (SMGM) and sparse representation. A SMGM is established to indicating the unsymmetrical spectral absorption and reflection characteristics, meanwhile, its rationality and sparse property are discussed. With the application of compressed sensing (CS) theory, we implement sparse representation to the SMGM. Then, the degraded and compressed HSIs can be reconstructed utilizing the uninjured or key bands. Finally, we take low rank matrix recovery (LRMR) algorithm for post processing to restore the spatial details. The proposed method was tested on the spectral data captured on the ground with artificial water absorption condition and an AVIRIS-HSI data set. The experimental results in terms of qualitative and quantitative assessments demonstrate that the effectiveness on recovering the spectral information from both degradations and loss compression. The spectral diagnostic characteristics and the spatial geometry feature are well preserved.

Spectral-spatial hyperspectral image classification using super-pixel-based spatial pyramid representation

NASA Astrophysics Data System (ADS)

Fan, Jiayuan; Tan, Hui Li; Toomik, Maria; Lu, Shijian

2016-10-01

Spatial pyramid matching has demonstrated its power for image recognition task by pooling features from spatially increasingly fine sub-regions. Motivated by the concept of feature pooling at multiple pyramid levels, we propose a novel spectral-spatial hyperspectral image classification approach using superpixel-based spatial pyramid representation. This technique first generates multiple superpixel maps by decreasing the superpixel number gradually along with the increased spatial regions for labelled samples. By using every superpixel map, sparse representation of pixels within every spatial region is then computed through local max pooling. Finally, features learned from training samples are aggregated and trained by a support vector machine (SVM) classifier. The proposed spectral-spatial hyperspectral image classification technique has been evaluated on two public hyperspectral datasets, including the Indian Pines image containing 16 different agricultural scene categories with a 20m resolution acquired by AVIRIS and the University of Pavia image containing 9 land-use categories with a 1.3m spatial resolution acquired by the ROSIS-03 sensor. Experimental results show significantly improved performance compared with the state-of-the-art works. The major contributions of this proposed technique include (1) a new spectral-spatial classification approach to generate feature representation for hyperspectral image, (2) a complementary yet effective feature pooling approach, i.e. the superpixel-based spatial pyramid representation that is used for the spatial correlation study, (3) evaluation on two public hyperspectral image datasets with superior image classification performance.

Classification of tree species based on longwave hyperspectral data from leaves, a case study for a tropical dry forest

NASA Astrophysics Data System (ADS)

Harrison, D.; Rivard, B.; Sánchez-Azofeifa, A.

2018-04-01

Remote sensing of the environment has utilized the visible, near and short-wave infrared (IR) regions of the electromagnetic (EM) spectrum to characterize vegetation health, vigor and distribution. However, relatively little research has focused on the use of the longwave infrared (LWIR, 8.0-12.5 μm) region for studies of vegetation. In this study LWIR leaf reflectance spectra were collected in the wet seasons (May through December) of 2013 and 2014 from twenty-six tree species located in a high species diversity environment, a tropical dry forest in Costa Rica. A continuous wavelet transformation (CWT) was applied to all spectra to minimize noise and broad amplitude variations attributable to non-compositional effects. Species discrimination was then explored with Random Forest classification and accuracy improved was observed with preprocessing of reflectance spectra with continuous wavelet transformation. Species were found to share common spectral features that formed the basis for five spectral types that were corroborated with linear discriminate analysis. The source of most of the observed spectral features is attributed to cell wall or cuticle compounds (cellulose, cutin, matrix glycan, silica and oleanolic acid). Spectral types could be advantageous for the analysis of airborne hyperspectral data because cavity effects will lower the spectral contrast thus increasing the reliance of classification efforts on dominant spectral features. Spectral types specifically derived from leaf level data are expected to support the labeling of spectral classes derived from imagery. The results of this study and that of Ribeiro Da Luz (2006), Ribeiro Da Luz and Crowley (2007, 2010), Ullah et al. (2012) and Rock et al. (2016) have now illustrated success in tree species discrimination across a range of ecosystems using leaf-level spectral observations. With advances in LWIR sensors and concurrent improvements in their signal to noise, applications to large-scale species detection from airborne imagery appear feasible.

Automatic classification of spectra from the Infrared Astronomical Satellite (IRAS)

NASA Technical Reports Server (NTRS)

Cheeseman, Peter; Stutz, John; Self, Matthew; Taylor, William; Goebel, John; Volk, Kevin; Walker, Helen

1989-01-01

A new classification of Infrared spectra collected by the Infrared Astronomical Satellite (IRAS) is presented. The spectral classes were discovered automatically by a program called Auto Class 2. This program is a method for discovering (inducing) classes from a data base, utilizing a Bayesian probability approach. These classes can be used to give insight into the patterns that occur in the particular domain, in this case, infrared astronomical spectroscopy. The classified spectra are the entire Low Resolution Spectra (LRS) Atlas of 5,425 sources. There are seventy-seven classes in this classification and these in turn were meta-classified to produce nine meta-classes. The classification is presented as spectral plots, IRAS color-color plots, galactic distribution plots and class commentaries. Cross-reference tables, listing the sources by IRAS name and by Auto Class class, are also given. These classes show some of the well known classes, such as the black-body class, and silicate emission classes, but many other classes were unsuspected, while others show important subtle differences within the well known classes.

CHAMP: a locally adaptive unmixing-based hyperspectral anomaly detection algorithm

NASA Astrophysics Data System (ADS)

Crist, Eric P.; Thelen, Brian J.; Carrara, David A.

1998-10-01

Anomaly detection offers a means by which to identify potentially important objects in a scene without prior knowledge of their spectral signatures. As such, this approach is less sensitive to variations in target class composition, atmospheric and illumination conditions, and sensor gain settings than would be a spectral matched filter or similar algorithm. The best existing anomaly detectors generally fall into one of two categories: those based on local Gaussian statistics, and those based on linear mixing moles. Unmixing-based approaches better represent the real distribution of data in a scene, but are typically derived and applied on a global or scene-wide basis. Locally adaptive approaches allow detection of more subtle anomalies by accommodating the spatial non-homogeneity of background classes in a typical scene, but provide a poorer representation of the true underlying background distribution. The CHAMP algorithm combines the best attributes of both approaches, applying a linear-mixing model approach in a spatially adaptive manner. The algorithm itself, and teste results on simulated and actual hyperspectral image data, are presented in this paper.

Mueller matrix approach for probing multifractality in the underlying anisotropic connective tissue

NASA Astrophysics Data System (ADS)

Das, Nandan Kumar; Dey, Rajib; Ghosh, Nirmalya

2016-09-01

Spatial variation of refractive index (RI) in connective tissues exhibits multifractality, which encodes useful morphological and ultrastructural information about the disease. We present a spectral Mueller matrix (MM)-based approach in combination with multifractal detrended fluctuation analysis (MFDFA) to exclusively pick out the signature of the underlying connective tissue multifractality through the superficial epithelium layer. The method is based on inverse analysis on selected spectral scattering MM elements encoding the birefringence information on the anisotropic connective tissue. The light scattering spectra corresponding to the birefringence carrying MM elements are then subjected to the Born approximation-based Fourier domain preprocessing to extract ultrastructural RI fluctuations of anisotropic tissue. The extracted RI fluctuations are subsequently analyzed via MFDFA to yield the multifractal tissue parameters. The approach was experimentally validated on a simple tissue model comprising of TiO2 as scatterers of the superficial isotropic layer and rat tail collagen as an underlying anisotropic layer. Finally, the method enabled probing of precancer-related subtle alterations in underlying connective tissue ultrastructural multifractality from intact tissues.

Textural signatures for wetland vegetation

NASA Technical Reports Server (NTRS)

Whitman, R. I.; Marcellus, K. L.

1973-01-01

This investigation indicates that unique textural signatures do exist for specific wetland communities at certain times in the growing season. When photographs with the proper resolution are obtained, the textural features can identify the spectral features of the vegetation community seen with lower resolution mapping data. The development of a matrix of optimum textural signatures is the goal of this research. Seasonal variations of spectral and textural features are particularly important when performing a vegetations analysis of fresh water marshes. This matrix will aid in flight planning, since expected seasonal variations and resolution requirements can be established prior to a given flight mission.

Visible and Near-IR Reflectance Spectra of Smectite Acquired Under Dry Conditions for Interpretation of Martian Surface Mineralogy

NASA Technical Reports Server (NTRS)

Morris, Richard V.; Achilles, Cherie N; Archer, Paul D.; Graff, Trevor G.; Agresti, David G.; Ming, Douglas W; Golden, Dadi C.; Mertzman, Stanley A.

2011-01-01

Visible and near-IR (VNIR) spectra from the MEx OMEGA and the MRO CRISM hyper-spectral imaging instruments have spectral features associated with the H2O molecule and M OH functional groups (M = Mg, Fe, Al, and Si). Mineralogical assignments of martian spectral features are made on the basis of laboratory VNIR spectra, which were often acquired under ambient (humid) conditions. Smectites like nontronite, saponite, and montmorillionite have interlayer H2O that is exchangeable with their environment, and we have acquired smectite reflectance spectra under dry environmental conditions for interpretation of martian surface mineralogy. We also obtained chemical, Moessbauer (MB), powder X-ray diffraction (XRD), and thermogravimetric (TG) data to understand variations in spectral properties. VNIR spectra were recorded in humid lab air at 25-35C, in a dynamic dry N2 atmosphere (50-150 ppmv H2O) after exposing the smectite samples (5 nontronites, 3 montmorillionites, and 1 saponite) to that atmosphere for up to approximately l000 hr each at 25-35C, approximately 105C, and approximately 215C, and after re-exposure to humid lab air. Heating at 105C and 215C for approximately 1000 hr is taken as a surrogate for geologic time scales at lower temperatures. Upon exposure to dry N2, the position and intensity of spectral features associated with M-OH were relatively insensitive to the dry environment, and the spectral features associated with H2O (e.g., approximately 1.90 micrometers) decreased in intensity and are sometimes not detectable by the end of the 215C heating step. The position and intensity of H2O spectral features recovered upon re-exposure to lab air. XRD data show interlayer collapse for the nontronites and Namontmorillionites, with the interlayer remaining collapsed for the latter after re-exposure to lab air. The interlayer did not collapse for the saponite and Ca-montmorillionite. TG data show that the concentration of H2O derived from structural OH was invariant to the dry N2 treatment for saponite and the montmorillionites, but the nontronites had additional structural OH after treatment. Upon exposure to dry N2, the VNIR spectra also acquired a red slope with decreasing albedo between approximately 0.4 and approximately 2.0 micrometers. The magnitude of the effects covaries with exposure time to dry N2 and heating temperature. Upon re-exposure to lab air, the slope and albedo do not completely recover to pre-exposure values. MB data show that these effects do not result from partial reduction of ferric to ferrous iron, and TG data show they do not result from loss of structural OH. Possible explanations include formation of small clusters of (superparamagnetic) ferric oxide and reduced smectite crystallinity. The difference in spectral properties between spectra acquired in humid lab air and under dry conditions are consequential for interpretation of CRISM and OMEGA spectra. For example, nontronite by itself and not nontronite plus ferrihydrite can account for the red spectral slope in martian spectra where nontronite is indicated by the Fe-OH spectral features.

Examination of the spectral features of vegetation in 1987 AVIRIS data

NASA Technical Reports Server (NTRS)

Elvidge, Christopher D.

1988-01-01

Equations for converting AVIRIS digital numbers to percent reflectance were developed using a set of three calibration targets. AVIRIS reflectance spectra from five plant communities exhibit distinct spectral differences.

Spectral features of solar plasma flows

NASA Astrophysics Data System (ADS)

Barkhatov, N. A.; Revunov, S. E.

2014-11-01

Research to the identification of plasma flows in the Solar wind by spectral characteristics of solar plasma flows in the range of magnetohydrodynamics is devoted. To do this, the wavelet skeleton pattern of Solar wind parameters recorded on Earth orbit by patrol spacecraft and then executed their neural network classification differentiated by bandwidths is carry out. This analysis of spectral features of Solar plasma flows in the form of magnetic clouds (MC), corotating interaction regions (CIR), shock waves (Shocks) and highspeed streams from coronal holes (HSS) was made. The proposed data processing and the original correlation-spectral method for processing information about the Solar wind flows for further classification as online monitoring of near space can be used. This approach will allow on early stages in the Solar wind flow detect geoeffective structure to predict global geomagnetic disturbances.

The design and application of a multi-band IR imager

NASA Astrophysics Data System (ADS)

Li, Lijuan

2018-02-01

Multi-band IR imaging system has many applications in security, national defense, petroleum and gas industry, etc. So the relevant technologies are getting more and more attention in rent years. As we know, when used in missile warning and missile seeker systems, multi-band IR imaging technology has the advantage of high target recognition capability and low false alarm rate if suitable spectral bands are selected. Compared with traditional single band IR imager, multi-band IR imager can make use of spectral features in addition to space and time domain features to discriminate target from background clutters and decoys. So, one of the key work is to select the right spectral bands in which the feature difference between target and false target is evident and is well utilized. Multi-band IR imager is a useful instrument to collect multi-band IR images of target, backgrounds and decoys for spectral band selection study at low cost and with adjustable parameters and property compared with commercial imaging spectrometer. In this paper, a multi-band IR imaging system is developed which is suitable to collect 4 spectral band images of various scenes at every turn and can be expanded to other short-wave and mid-wave IR spectral bands combination by changing filter groups. The multi-band IR imaging system consists of a broad band optical system, a cryogenic InSb large array detector, a spinning filter wheel and electronic processing system. The multi-band IR imaging system's performance is tested in real data collection experiments.

Less is more: Avoiding the LIBS dimensionality curse through judicious feature selection for explosive detection.

PubMed

Kumar Myakalwar, Ashwin; Spegazzini, Nicolas; Zhang, Chi; Kumar Anubham, Siva; Dasari, Ramachandra R; Barman, Ishan; Kumar Gundawar, Manoj

2015-08-19

Despite its intrinsic advantages, translation of laser induced breakdown spectroscopy for material identification has been often impeded by the lack of robustness of developed classification models, often due to the presence of spurious correlations. While a number of classifiers exhibiting high discriminatory power have been reported, efforts in establishing the subset of relevant spectral features that enable a fundamental interpretation of the segmentation capability and avoid the 'curse of dimensionality' have been lacking. Using LIBS data acquired from a set of secondary explosives, we investigate judicious feature selection approaches and architect two different chemometrics classifiers -based on feature selection through prerequisite knowledge of the sample composition and genetic algorithm, respectively. While the full spectral input results in classification rate of ca.92%, selection of only carbon to hydrogen spectral window results in near identical performance. Importantly, the genetic algorithm-derived classifier shows a statistically significant improvement to ca. 94% accuracy for prospective classification, even though the number of features used is an order of magnitude smaller. Our findings demonstrate the impact of rigorous feature selection in LIBS and also hint at the feasibility of using a discrete filter based detector thereby enabling a cheaper and compact system more amenable to field operations.

Less is more: Avoiding the LIBS dimensionality curse through judicious feature selection for explosive detection

PubMed Central

Kumar Myakalwar, Ashwin; Spegazzini, Nicolas; Zhang, Chi; Kumar Anubham, Siva; Dasari, Ramachandra R.; Barman, Ishan; Kumar Gundawar, Manoj

2015-01-01

Despite its intrinsic advantages, translation of laser induced breakdown spectroscopy for material identification has been often impeded by the lack of robustness of developed classification models, often due to the presence of spurious correlations. While a number of classifiers exhibiting high discriminatory power have been reported, efforts in establishing the subset of relevant spectral features that enable a fundamental interpretation of the segmentation capability and avoid the ‘curse of dimensionality’ have been lacking. Using LIBS data acquired from a set of secondary explosives, we investigate judicious feature selection approaches and architect two different chemometrics classifiers –based on feature selection through prerequisite knowledge of the sample composition and genetic algorithm, respectively. While the full spectral input results in classification rate of ca.92%, selection of only carbon to hydrogen spectral window results in near identical performance. Importantly, the genetic algorithm-derived classifier shows a statistically significant improvement to ca. 94% accuracy for prospective classification, even though the number of features used is an order of magnitude smaller. Our findings demonstrate the impact of rigorous feature selection in LIBS and also hint at the feasibility of using a discrete filter based detector thereby enabling a cheaper and compact system more amenable to field operations. PMID:26286630

Evaluation of wavelet spectral features in pathological detection and discrimination of yellow rust and powdery mildew in winter wheat with hyperspectral reflectance data

NASA Astrophysics Data System (ADS)

Shi, Yue; Huang, Wenjiang; Zhou, Xianfeng

2017-04-01

Hyperspectral absorption features are important indicators of characterizing plant biophysical variables for the automatic diagnosis of crop diseases. Continuous wavelet analysis has proven to be an advanced hyperspectral analysis technique for extracting absorption features; however, specific wavelet features (WFs) and their relationship with pathological characteristics induced by different infestations have rarely been summarized. The aim of this research is to determine the most sensitive WFs for identifying specific pathological lesions from yellow rust and powdery mildew in winter wheat, based on 314 hyperspectral samples measured in field experiments in China in 2002, 2003, 2005, and 2012. The resultant WFs could be used as proxies to capture the major spectral absorption features caused by infestation of yellow rust or powdery mildew. Multivariate regression analysis based on these WFs outperformed conventional spectral features in disease detection; meanwhile, a Fisher discrimination model exhibited considerable potential for generating separable clusters for each infestation. Optimal classification returned an overall accuracy of 91.9% with a Kappa of 0.89. This paper also emphasizes the WFs and their relationship with pathological characteristics in order to provide a foundation for the further application of this approach in monitoring winter wheat diseases at the regional scale.

Fusion of LBP and SWLD using spatio-spectral information for hyperspectral face recognition

NASA Astrophysics Data System (ADS)

Xie, Zhihua; Jiang, Peng; Zhang, Shuai; Xiong, Jinquan

2018-01-01

Hyperspectral imaging, recording intrinsic spectral information of the skin cross different spectral bands, become an important issue for robust face recognition. However, the main challenges for hyperspectral face recognition are high data dimensionality, low signal to noise ratio and inter band misalignment. In this paper, hyperspectral face recognition based on LBP (Local binary pattern) and SWLD (Simplified Weber local descriptor) is proposed to extract discriminative local features from spatio-spectral fusion information. Firstly, the spatio-spectral fusion strategy based on statistical information is used to attain discriminative features of hyperspectral face images. Secondly, LBP is applied to extract the orientation of the fusion face edges. Thirdly, SWLD is proposed to encode the intensity information in hyperspectral images. Finally, we adopt a symmetric Kullback-Leibler distance to compute the encoded face images. The hyperspectral face recognition is tested on Hong Kong Polytechnic University Hyperspectral Face database (PolyUHSFD). Experimental results show that the proposed method has higher recognition rate (92.8%) than the state of the art hyperspectral face recognition algorithms.

Insight into resolution enhancement in generalized two-dimensional correlation spectroscopy.

PubMed

Ma, Lu; Sikirzhytski, Vitali; Hong, Zhenmin; Lednev, Igor K; Asher, Sanford A

2013-03-01

Generalized two-dimensional correlation spectroscopy (2D-COS) can be used to enhance spectral resolution in order to help differentiate highly overlapped spectral bands. Despite the numerous extensive 2D-COS investigations, the origin of the 2D spectral resolution enhancement mechanism(s) is not completely understood. In the work here, we studied the 2D-COS of simulated spectra in order to develop new insights into the dependence of 2D-COS spectral features on the overlapping band separations, their intensities and bandwidths, and their band intensity change rates. We found that the features in the 2D-COS maps that are derived from overlapping bands were determined by the spectral normalized half-intensities and the total intensity changes of the correlated bands. We identified the conditions required to resolve overlapping bands. In particular, 2D-COS peak resolution requires that the normalized half-intensities of a correlating band have amplitudes between the maxima and minima of the normalized half-intensities of the overlapping bands.

Insight into Resolution Enhancement in Generalized Two-Dimensional Correlation Spectroscopy

PubMed Central

Ma, Lu; Sikirzhytski, Vitali; Hong, Zhenmin; Lednev, Igor K.; Asher, Sanford A.

2014-01-01

Generalized two-dimensional correlation spectroscopy (2D COS) can be used to enhance spectral resolution in order to help differentiate highly overlapped spectral bands. Despite the numerous extensive 2D COS investigations, the origin of the 2D spectral resolution enhancement mechanism(s) are not completely understood. In the work here we studied the 2D COS of simulated spectra in order to develop new insights into the dependence of the 2D COS spectral features on the overlapping band separations, their intensities and bandwidths, and their band intensity change rates. We find that the features in the 2D COS maps that derive from overlapping bands are determined by the spectral normalized half-intensities and the total intensity changes of the correlated bands. We identify the conditions required to resolve overlapping bands. In particular, 2D COS peak resolution requires that the normalized half-intensities of a correlating band have amplitudes between the maxima and minima of the normalized half-intensities of the overlapping bands. PMID:23452492

Print Advertisements for Alzheimer’s Disease Drugs: Informational and Transformational Features

PubMed Central

Gooblar, Jonathan; Carpenter, Brian D.

2014-01-01

Purpose We examined print advertisements for Alzheimer’s disease drugs published in journals and magazines between January 2008 and February 2012, using an informational versus transformational theoretical framework to identify objective and persuasive features. Methods In 29 unique advertisements, we used qualitative methods to code and interpret identifying information, charts, benefit and side effect language, and persuasive appeals embedded in graphics and narratives. Results Most elements contained a mixture of informational and transformational features. Charts were used infrequently, but when they did appear the accompanying text often exaggerated the data. Benefit statements covered an array of symptoms, drug properties, and caregiver issues. Side effect statements often used positive persuasive appeals. Graphics and narrative features emphasized positive emotions and outcomes. Implications We found subtle and sophisticated attempts both to educate and to persuade readers. It is important for consumers and prescribing physicians to read print advertisements critically so that they can make informed treatment choices. PMID:23687184

Print advertisements for Alzheimer's disease drugs: informational and transformational features.

PubMed

Gooblar, Jonathan; Carpenter, Brian D

2013-06-01

We examined print advertisements for Alzheimer's disease drugs published in journals and magazines between January 2008 and February 2012, using an informational versus transformational theoretical framework to identify objective and persuasive features. In 29 unique advertisements, we used qualitative methods to code and interpret identifying information, charts, benefit and side effect language, and persuasive appeals embedded in graphics and narratives. Most elements contained a mixture of informational and transformational features. Charts were used infrequently, but when they did appear the accompanying text often exaggerated the data. Benefit statements covered an array of symptoms, drug properties, and caregiver issues. Side effect statements often used positive persuasive appeals. Graphics and narrative features emphasized positive emotions and outcomes. We found subtle and sophisticated attempts both to educate and to persuade readers. It is important for consumers and prescribing physicians to read print advertisements critically so that they can make informed treatment choices.

Spatial Variability in Enceladus' Plume Material: Convergence of Evidence or Coincidence?

NASA Astrophysics Data System (ADS)

Dhingra, Deepak; Hedman, Matthew M.; Clark, Roger Nelson

2016-10-01

Systematic spatial trends in the properties of the plume material emerging from Enceladus' tiger stripes can be observed in multiple observations from the Cassini mission. Subtle near infrared spectral differences within the plume have been reported across tiger stripes based on Visual and Infrared Mapping Spectrometer (VIMS) observations at high spatial resolution [1]. These spectral differences are likely due to variable water-ice grain size distribution along the source fissures (i.e. tiger stripes) and perhaps by the presence/absence of water vapor emission [2]. We now report a correlation of this spatial trend (along tiger stripes) with several other published results including (a) differences in the ice particle sizes across tiger stripes on Enceladus' surface [3, 4], (b) the surface abundance of organic material [3] and finally, (c) the relative proportion of type II grains (associated with organic/siliceous material) in the plume [5] from Damascus to Alexandria as measured by the Cosmic Dust Analyzer (CDA) instrument.The general trend indicates that at least some of the plume properties (viz. particle size, organic abundance) achieve a peak over Damascus and then become gradually subtle towards Alexandria. The observed differences between tiger stripes eruptions and the nature of correlations (trends from Damascus to Alexandria) hold important clues to the subsurface environment at Enceladus including differences in the geological setting of the individual tiger stripes [6]. The latter is a likely possibility given the large spatial spread of eruptions in Encealdus' South Polar Terrain (SPT).[1] Dhingra et al., (2015) 46th Lunar Planet. Sci. Conf., Abstract#1648[2] Dhingra et al. (2016) Icarus, submitted[3] Brown et al. (2006) Science, 311, 1425-1428[4] Jaumann et al. (2008) Icarus, 193, 407-419[5] Postberg et al. (2011) Nature, doi:10.1038/nature10175[6] Yin and Pappalardo (2015) Icarus, 260, 409-439

High-Energy Density science at the Linac Coherent Light Source

NASA Astrophysics Data System (ADS)

Glenzer, S. H.; Fletcher, L. B.; Hastings, J. B.

2016-03-01

The Matter in Extreme Conditions end station at the Linac Coherent Light Source holds great promise for novel pump-probe experiments to make new discoveries in high- energy density science. In recent experiments we have demonstrated the first spectrally- resolved measurements of plasmons using a seeded 8-keV x-ray laser beam. Forward x-ray Thomson scattering spectra from isochorically heated solid aluminum show a well-resolved plasmon feature that is down-shifted in energy by 19 eV from the incident 8 keV elastic scattering feature. In this spectral range, the simultaneously measured backscatter spectrum shows no spectral features indicating observation of collective plasmon oscillations on a scattering length comparable to the screening length. This technique is a prerequisite for Thomson scattering measurements in compressed matter where the plasmon shift is a sensitive function of the free electron density and where the plasmon intensity provides information on temperature.

High-Energy Density science at the Linac Coherent Light Source

DOE PAGES

Glenzer, S. H.; Fletcher, L. B.; Hastings, J. B.

2016-04-01

The Matter in Extreme Conditions end station at the Linac Coherent Light Source holds great promise for novel pump-probe experiments to make new discoveries in high- energy density science. Recently, our experiments have demonstrated the first spectrally- resolved measurements of plasmons using a seeded 8-keV x-ray laser beam. Forward x-ray Thomson scattering spectra from isochorically heated solid aluminum show a well-resolved plasmon feature that is down-shifted in energy by 19 eV from the incident 8 keV elastic scattering feature. In this spectral range, the simultaneously measured backscatter spectrum shows no spectral features indicating observation of collective plasmon oscillations on amore » scattering length comparable to the screening length. Moreover, this technique is a prerequisite for Thomson scattering measurements in compressed matter where the plasmon shift is a sensitive function of the free electron density and where the plasmon intensity provides information on temperature.« less

A Comparison of the Near-Infrared Spectral Features of Early-Type Galaxies in the Virgo and Coma Clusters

NASA Astrophysics Data System (ADS)

Houdashelt, M. L.

1992-05-01

Initial results are presented from an examination of near-infrared spectra (6800 - 9200 Angstroms) of 34 early-type galaxies - 17 in the Virgo cluster, 10 in the Coma cluster and seven field members. It has previously been speculated that E/S0 galaxies of similar luminosity in the Virgo and Coma clusters have different red stellar populations. To explore this possibility, pseudo-equivalent widths of a number of near-IR spectral features have been measured. The important features studied include the TiO bands near 7100, 7890, 8197, 8500 and 8950 Angstroms, which are mainly produced by the late-type stars whose flux contributes only about 10-20\\ the near-IR. The strengths of the Ca triplet (8498, 8542, 8662 Angstroms) and Na I doublet (8183, 8195 Angstroms) are also measured, since these features are affected by the relative contribution of dwarf stars to the red light. Although the main focus of this work is the search for spectral differences among the Coma, Virgo and field E/S0 populations, each subgroup of galaxies (and the sample as a whole) are also examined for correlations among the feature strengths, galaxy color and luminosity.

Spectrum Analyzers Incorporating Tunable WGM Resonators

NASA Technical Reports Server (NTRS)

Savchenkov, Anatoliy; Matsko, Andrey; Strekalov, Dmitry; Maleki, Lute

2009-01-01

A photonic instrument is proposed to boost the resolution for ultraviolet/ optical/infrared spectral analysis and spectral imaging allowing the detection of narrow (0.00007-to-0.07-picometer wavelength resolution range) optical spectral signatures of chemical elements in space and planetary atmospheres. The idea underlying the proposal is to exploit the advantageous spectral characteristics of whispering-gallery-mode (WGM) resonators to obtain spectral resolutions at least three orders of magnitude greater than those of optical spectrum analyzers now in use. Such high resolutions would enable measurement of spectral features that could not be resolved by prior instruments.

Hyperspectral sensing of heavy metals in soil and vegetation: Feasibility and challenges

NASA Astrophysics Data System (ADS)

Wang, Fenghe; Gao, Jay; Zha, Yong

2018-02-01

Remote sensing of heavy metal contamination of soils has been widely studied. These studies concentrate heavily on the hyperspectral reflectance of typical metals in soils and in plants measured either in situ or in the laboratory. The most used wavebands lie within the visible-near infrared portion of the spectrum, especially the red edge. In comparison, mid- and far-infrared wavelengths are used far less frequently. Hyperspectral data are optimized to suppress noises and enhance the signal of the targeted metals through spectral derivatives and vegetation indexing. It is found that only subtle disparity exists in spectral responses for some metals at a sufficiently high content level. Not all metals have their own unique spectral response. Their detection has to rely on their co-variation with the spectrally responsive metals or organic matter in the soils. The closeness of the correlation dictates the accuracy of prediction. Without any theoretical grounding, this correlation is site-specific. Various analytical methods, including stepwise multi-linear regression, partial least squares regression, and neural networks have been used to model metal content level from the identified spectrally sensitive bands and/or their transformed indices. Both the model and the explanatory variables vary with the metal under detection and the area from which in situ samples are collected. Despite the amply demonstrated feasibility of estimating several metals by a large number of authors, only a few have succeeded in mapping the spatial distribution of metals from HyMAP, HJ-1A and Hyperion images to a satisfactory accuracy using complex algorithms and after taking environmental variables into account. The large number of reported failures testifies the difficulty in the detection of heavy metals in soils and plants, especially when their concentration level is low. The reasons or factors responsible for the success or failure have not been systematically analyzed, including the minimal spectral resolution required.

Shaded Relief of Rio Sao Francisco, Brazil

NASA Image and Video Library

2000-02-14

This topographic image acquired by SRTM shows an area south of the Sao Francisco River in Brazil. The scrub forest terrain shows relief of about 400 meters (1300 feet). Areas such as these are difficult to map by traditional methods because of frequent cloud cover and local inaccessibility. This region has little topographic relief, but even subtle changes in topography have far-reaching effects on regional ecosystems. The image covers an area of 57 km x 79 km and represents one quarter of the 225 km SRTM swath. Colors range from dark blue at water level to white and brown at hill tops. The terrain features that are clearly visible in this image include tributaries of the Sao Francisco, the dark-blue branch-like features visible from top right to bottom left, and on the left edge of the image, and hills rising up from the valley floor. The San Francisco River is a major source of water for irrigation and hydroelectric power. Mapping such regions will allow scientists to better understand the relationships between flooding cycles, forestation and human influences on ecosystems. This shaded relief image was generated using topographic data from the Shuttle Radar Topography Mission. A computer-generated artificial light source illuminates the elevation data to produce a pattern of light and shadows. Slopes facing the light appear bright, while those facing away are shaded. On flatter surfaces, the pattern of light and shadows can reveal subtle features in the terrain. Shaded relief maps are commonly used in applications such as geologic mapping and land use planning. http://photojournal.jpl.nasa.gov/catalog/PIA02700

The Spitzer Atlas of Stellar Spectra (SASS)

NASA Astrophysics Data System (ADS)

Ardila, D. R.; van Dyk, S. D., Makowiecki, W.; Stauffer, J.; Song, I.; Ro, J.; Fajardo-Acosta, S.; Hoard, D. W.; Wachter, S.

2011-11-01

We present the Spitzer Atlas of Stellar Spectra (SASS), which includes 159 stellar spectra (5 to 32 micron; R about 100) taken with the Infrared Spectrograph on the Spitzer Space Telescope. This Atlas gathers representative spectra of a broad section of the Hertzsprung-Russell diagram, intended to serve as a general stellar spectral reference in the mid-infrared. It includes stars from all luminosity classes, as well as Wolf-Rayet (WR) objects. Furthermore, it includes some objects of intrinsic interest, like blue stragglers and certain pulsating variables. All the spectra have been uniformly reduced, and all are available online. For dwarfs and giants, the spectra of early-type objects are relatively featureless, dominated by Hydrogen lines around A spectral types. Besides these, the most noticeable photospheric features correspond to water vapor and silicon monoxide in late-type objects and methane and ammonia features at the latest spectral types. Most supergiant spectra in the Atlas present evidence of circumstellar gas. The sample includes five M supergiant spectra, which show strong dust excesses and in some cases PAH features. Sequences of WR stars present the well-known pattern of lines of He I and He II, as well as forbidden lines of ionized metals. The characteristic flat-top shape of the [Ne III] line is evident even at these low spectral resolutions. Several Luminous Blue Variables and other transition stars are present in the Atlas and show very diverse spectra, dominated by circumstellar gas and dust features. We show that the [8]-[24] Spitzer colors (IRAC and MIPS) are poor predictors of spectral type for most luminosity classes.

Surface materials map of Afghanistan: iron-bearing minerals and other materials

USGS Publications Warehouse

King, Trude V.V.; Kokaly, Raymond F.; Hoefen, Todd M.; Dudek, Kathleen B.; Livo, Keith E.

2012-01-01

This map shows the distribution of selected iron-bearing minerals and other materials derived from analysis of HyMap imaging spectrometer data of Afghanistan. Using a NASA (National Aeronautics and Space Administration) WB-57 aircraft flown at an altitude of ~15,240 meters or ~50,000 feet, 218 flight lines of data were collected over Afghanistan between August 22 and October 2, 2007. The HyMap data were converted to apparent surface reflectance, then further empirically adjusted using ground-based reflectance measurements. The reflectance spectrum of each pixel of HyMap data was compared to the spectral features of reference entries in a spectral library of minerals, vegetation, water, ice, and snow. This map shows the spatial distribution of iron-bearing minerals and other materials having diagnostic absorptions at visible and near-infrared wavelengths. These absorptions result from electronic processes in the minerals. Several criteria, including (1) the reliability of detection and discrimination of minerals using the HyMap spectrometer data, (2) the relative abundance of minerals, and (3) the importance of particular minerals to studies of Afghanistan's natural resources, guided the selection of entries in the reference spectral library and, therefore, guided the selection of mineral classes shown on this map. Minerals occurring abundantly at the surface and those having unique spectral features were easily detected and discriminated. Minerals having similar spectral features were less easily discriminated, especially where the minerals were not particularly abundant and (or) where vegetation cover reduced the absorption strength of mineral features. Complications in reflectance calibration also affected the detection and identification of minerals.

Cocaine Exposure Is Associated with Subtle Compromises of Infants' and Mothers' Social-Emotional Behavior and Dyadic Features of Their Interaction in the Face-to-Face Still-Face Paradigm

ERIC Educational Resources Information Center

Tronick, E. Z.; Messinger, D. S.; Weinberg, M. K.; Lester, B. M.; LaGasse, L.; Seifer, R.; Bauer, C. R.; Shankaran, S.; Bada, H.; Wright, L. L.; Poole, K.; Liu, J.

2005-01-01

Prenatal cocaine and opiate exposure are thought to subtly compromise social and emotional development. The authors observed a large sample of 236 cocaine-exposed and 459 nonexposed infants (49 were opiate exposed and 646 nonexposed) with their mothers in the face-to-face still-face paradigm. Infant and maternal behaviors were microanalytically…

Spectral Domain RF Fingerprinting for 802.11 Wireless Devices

DTIC Science & Technology

2010-03-01

induce unintentional modulation effects . If these effects (features) are sufficiently unique, it becomes possible to identify a device us- ing its...Previous AFIT research has demonstrated the effectiveness of RF Fin- gerprinting using 802.11A signals with 1) spectral correlation on Power Spectral...32 4.5. SD Intra-manufacturer Classification: Effects of Burst Location Error

Improved classification accuracy of powdery mildew infection levels of wine grapes by spatial-spectral analysis of hyperspectral images.

PubMed

Knauer, Uwe; Matros, Andrea; Petrovic, Tijana; Zanker, Timothy; Scott, Eileen S; Seiffert, Udo

2017-01-01

Hyperspectral imaging is an emerging means of assessing plant vitality, stress parameters, nutrition status, and diseases. Extraction of target values from the high-dimensional datasets either relies on pixel-wise processing of the full spectral information, appropriate selection of individual bands, or calculation of spectral indices. Limitations of such approaches are reduced classification accuracy, reduced robustness due to spatial variation of the spectral information across the surface of the objects measured as well as a loss of information intrinsic to band selection and use of spectral indices. In this paper we present an improved spatial-spectral segmentation approach for the analysis of hyperspectral imaging data and its application for the prediction of powdery mildew infection levels (disease severity) of intact Chardonnay grape bunches shortly before veraison. Instead of calculating texture features (spatial features) for the huge number of spectral bands independently, dimensionality reduction by means of Linear Discriminant Analysis (LDA) was applied first to derive a few descriptive image bands. Subsequent classification was based on modified Random Forest classifiers and selective extraction of texture parameters from the integral image representation of the image bands generated. Dimensionality reduction, integral images, and the selective feature extraction led to improved classification accuracies of up to [Formula: see text] for detached berries used as a reference sample (training dataset). Our approach was validated by predicting infection levels for a sample of 30 intact bunches. Classification accuracy improved with the number of decision trees of the Random Forest classifier. These results corresponded with qPCR results. An accuracy of 0.87 was achieved in classification of healthy, infected, and severely diseased bunches. However, discrimination between visually healthy and infected bunches proved to be challenging for a few samples, perhaps due to colonized berries or sparse mycelia hidden within the bunch or airborne conidia on the berries that were detected by qPCR. An advanced approach to hyperspectral image classification based on combined spatial and spectral image features, potentially applicable to many available hyperspectral sensor technologies, has been developed and validated to improve the detection of powdery mildew infection levels of Chardonnay grape bunches. The spatial-spectral approach improved especially the detection of light infection levels compared with pixel-wise spectral data analysis. This approach is expected to improve the speed and accuracy of disease detection once the thresholds for fungal biomass detected by hyperspectral imaging are established; it can also facilitate monitoring in plant phenotyping of grapevine and additional crops.

Comparative study of icy patches on comet nuclei

NASA Astrophysics Data System (ADS)

Oklay, Nilda; Pommerol, Antoine; Barucci, Maria Antonietta; Sunshine, Jessica; Sierks, Holger; Pajola, Maurizio

2016-07-01

Cometary missions Deep Impact, EPOXI and Rosetta investigated the nuclei of comets 9P/Tempel 1, 103P/Hartley 2 and 67P/Churyumov-Gerasimenko respectively. Bright patches were observed on the surfaces of each of these three comets [1-5]. Of these, the surface of 67P is mapped at the highest spatial resolution via narrow angle camera (NAC) of the Optical, Spectroscopic, and Infrared Remote Imaging System (OSIRIS, [6]) on board the Rosetta spacecraft. OSIRIS NAC is equipped with twelve filters covering the wavelength range of 250 nm to 1000 nm. Various filters combinations are used during surface mapping. With high spatial resolution data of comet 67P, three types of bright features were detected on the comet surface: Clustered, isolated and bright boulders [2]. In the visible spectral range, clustered bright features on comet 67P display bluer spectral slopes than the average surface [2, 4] while isolated bright features on comet 67P have flat spectra [4]. Icy patches observed on the surface of comets 9P and 103P display bluer spectral slopes than the average surface [1, 5]. Clustered and isolated bright features are blue in the RGB composites generated by using the images taken in NIR, visible and NUV wavelengths [2, 4]. This is valid for the icy patches observed on comets 9P and 103P [1, 5]. Spectroscopic observations of bright patches on comets 9P and 103P confirmed the existence of water [1, 5]. There were more than a hundred of bright features detected on the northern hemisphere of comet 67P [2]. Analysis of those features from both multispectral data and spectroscopic data is an ongoing work. Water ice is detected in eight of the bright features so far [7]. Additionally, spectroscopic observations of two clustered bright features on the surface of comet 67P revealed the existence of water ice [3]. The spectral properties of one of the icy patches were studied by [4] using OSIRIS NAC images and compared with the spectral properties of the active regions observed on comet 67P. Additionally jets rising from the same clustered bright feature were detected visually [4]. We analyzed bright patches on the surface of comets 9P, 103P and 67P using multispectral data obtained by the high-resolution instrument (HRI), medium- resolution instrument (MRI) and OSIRIS NAC using various spectral analysis techniques. Clustered bright features on comet 67P have similar visible spectra to the bright patches on comets 9P and 103P. The comparison of the bright patches includes the published results of the IR spectra. References: [1] Sunshine et al., 2006, Science, 311, 1453 [2] Pommerol et al., 2015, A&A, 583, A25 [3] Filacchione et al., 2016, Nature, 529, 368-372 [4] Oklay et al., 2016, A&A, 586, A80 [5] Sunshine et al. 2012, ACM [6] Keller et al., 2007, Space Sci. Rev., 128, 433 [7] Barucci et al., 2016, COSPAR, B04

National-scale cropland mapping based on spectral-temporal features and outdated land cover information.

PubMed

Waldner, François; Hansen, Matthew C; Potapov, Peter V; Löw, Fabian; Newby, Terence; Ferreira, Stefanus; Defourny, Pierre

2017-01-01

The lack of sufficient ground truth data has always constrained supervised learning, thereby hindering the generation of up-to-date satellite-derived thematic maps. This is all the more true for those applications requiring frequent updates over large areas such as cropland mapping. Therefore, we present a method enabling the automated production of spatially consistent cropland maps at the national scale, based on spectral-temporal features and outdated land cover information. Following an unsupervised approach, this method extracts reliable calibration pixels based on their labels in the outdated map and their spectral signatures. To ensure spatial consistency and coherence in the map, we first propose to generate seamless input images by normalizing the time series and deriving spectral-temporal features that target salient cropland characteristics. Second, we reduce the spatial variability of the class signatures by stratifying the country and by classifying each stratum independently. Finally, we remove speckle with a weighted majority filter accounting for per-pixel classification confidence. Capitalizing on a wall-to-wall validation data set, the method was tested in South Africa using a 16-year old land cover map and multi-sensor Landsat time series. The overall accuracy of the resulting cropland map reached 92%. A spatially explicit validation revealed large variations across the country and suggests that intensive grain-growing areas were better characterized than smallholder farming systems. Informative features in the classification process vary from one stratum to another but features targeting the minimum of vegetation as well as short-wave infrared features were consistently important throughout the country. Overall, the approach showed potential for routinely delivering consistent cropland maps over large areas as required for operational crop monitoring.

National-scale cropland mapping based on spectral-temporal features and outdated land cover information

PubMed Central

Hansen, Matthew C.; Potapov, Peter V.; Löw, Fabian; Newby, Terence; Ferreira, Stefanus; Defourny, Pierre

2017-01-01

The lack of sufficient ground truth data has always constrained supervised learning, thereby hindering the generation of up-to-date satellite-derived thematic maps. This is all the more true for those applications requiring frequent updates over large areas such as cropland mapping. Therefore, we present a method enabling the automated production of spatially consistent cropland maps at the national scale, based on spectral-temporal features and outdated land cover information. Following an unsupervised approach, this method extracts reliable calibration pixels based on their labels in the outdated map and their spectral signatures. To ensure spatial consistency and coherence in the map, we first propose to generate seamless input images by normalizing the time series and deriving spectral-temporal features that target salient cropland characteristics. Second, we reduce the spatial variability of the class signatures by stratifying the country and by classifying each stratum independently. Finally, we remove speckle with a weighted majority filter accounting for per-pixel classification confidence. Capitalizing on a wall-to-wall validation data set, the method was tested in South Africa using a 16-year old land cover map and multi-sensor Landsat time series. The overall accuracy of the resulting cropland map reached 92%. A spatially explicit validation revealed large variations across the country and suggests that intensive grain-growing areas were better characterized than smallholder farming systems. Informative features in the classification process vary from one stratum to another but features targeting the minimum of vegetation as well as short-wave infrared features were consistently important throughout the country. Overall, the approach showed potential for routinely delivering consistent cropland maps over large areas as required for operational crop monitoring. PMID:28817618

Raman spectral signatures as conformational probes of gas phase flexible molecules

NASA Astrophysics Data System (ADS)

Golan, Amir; Mayorkas, Nitzan; Rosenwaks, Salman; Bar, Ilana

2009-07-01

A novel application of ionization-loss stimulated Raman spectroscopy (ILSRS) for monitoring the spectral features of four conformers of a gas phase flexible molecule is reported. The Raman spectral signatures of four conformers of 2-phenylethylamine are well matched by the results of density functional theory calculations, showing bands uniquely identifying the structures. The measurement of spectral signatures by ILSRS in an extended spectral range, with a conventional laser source, is instrumental in facilitating the unraveling of intra- and intermolecular interactions that are significant in biological structure and activity.

Mass selective separation applied to radioisotopes of cesium: Mass selective applied to radioisotopes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dion, Michael; Eiden, Greg; Farmer, Orville

2016-07-22

A developed technique that uses the intrinsic mass-based separation capability of a quadrupole mass spectrometer has been used to resolve spectral radiometric interference of two isotopes of the same element. In this work the starting sample was a combination of 137Cs and 134Cs and was (activity) dominated by 137Cs and this methodology separated and “implanted” 134Cs that was later quantified for spectral features and ac- tivity with traditional radiometric techniques. This work demonstrated a 134Cs/137Cs activity ratio enhancement of >4 orders of magnitude and complete removal of 137Cs spectral features from the implanted target mass (i.e., 134).

X-Ray Spectra from MHD Simulations of Accreting Black Holes

NASA Technical Reports Server (NTRS)

Schnittman, Jeremy D.; Noble, Scott C.; Krolik, Julian H.

2011-01-01

We present new global calculations of X-ray spectra from fully relativistic magneto-hydrodynamic (MHO) simulations of black hole (BH) accretion disks. With a self consistent radiative transfer code including Compton scattering and returning radiation, we can reproduce the predominant spectral features seen in decades of X-ray observations of stellar-mass BHs: a broad thermal peak around 1 keV, power-law continuum up to >100 keV, and a relativistically broadened iron fluorescent line. By varying the mass accretion rate, different spectral states naturally emerge: thermal-dominant, steep power-law, and low/hard. In addition to the spectral features, we briefly discuss applications to X-ray timing and polarization.

Near-infrared spectra of the Martian surface: Reading between the lines

NASA Technical Reports Server (NTRS)

Crisp, D.; Bell, J. F., III

1993-01-01

Moderate-resolution near-infrared (NIR) spectra of Mars have been widely used in studies of the Martian surface because many candidate surface materials have distinctive absorption features at these wavelengths. Recent advances in NIR detector technology and instrumentation have also encouraged studies in this spectral region. The use of moderate spectral resolution has often been justified for NIR surface observations because the spectral features produced by most surface materials are relatively broad, and easily discriminated at this resolution. In spite of this, NIR spectra of Mars are usually very difficult to interpret quantitatively. One problem is that NIR surface absorption features are often only a few percent deep, requiring observations with great signal-to-noise ratios. A more significant problem is that gases in the Martian atmosphere contribute numerous absorption features at these wavelengths. Ground-based observers must also contend with variable absorption by several gases in the Earth's atmosphere (H2O, CO2, O3, N2O, CH4, O2). The strong CO2 bands near 1.4, 1.6, 2.0, 2.7, 4.3, and 4.8 micrometers largely preclude the analysis of surface spectral features at these wavelengths. Martian atmospheric water vapor also contributes significant absorption near 1.33, 1.88, and 2.7 micrometers, but water vapor in the Earth's atmosphere poses a much larger problem to ground-based studies of these spectral regions. The third most important NIR absorber in the Martian atmosphere is CO. This gas absorbs most strongly in the relatively-transparent spectral windows near 4.6 and 2.3 micrometers. It also produces 1-10 percent absorption in the solar spectrum at these NIR wavelengths. This solar CO absorption cannot be adequately removed by dividing the Martian spectrum by that of a star, as is commonly done to calibrate ground-based spectroscopic observations, because most stars do not have identical amounts of CO absorption in their spectra. Here, we describe tow effective methods for eliminating contamination of Martian surface spectra by absorption in the solar, terrestrial, and Martian atmospheres. Both methods involve the use of very-high-resolution spectra that completely resolve the narrow atmospheric absorption lines.

Altered cerebral blood flow velocity features in fibromyalgia patients in resting-state conditions

PubMed Central

Rodríguez, Alejandro; Tembl, José; Mesa-Gresa, Patricia; Muñoz, Miguel Ángel; Montoya, Pedro

2017-01-01

The aim of this study is to characterize in resting-state conditions the cerebral blood flow velocity (CBFV) signals of fibromyalgia patients. The anterior and middle cerebral arteries of both hemispheres from 15 women with fibromyalgia and 15 healthy women were monitored using Transcranial Doppler (TCD) during a 5-minute eyes-closed resting period. Several signal processing methods based on time, information theory, frequency and time-frequency analyses were used in order to extract different features to characterize the CBFV signals in the different vessels. Main results indicated that, in comparison with control subjects, fibromyalgia patients showed a higher complexity of the envelope CBFV and a different distribution of the power spectral density. In addition, it has been observed that complexity and spectral features show correlations with clinical pain parameters and emotional factors. The characterization features were used in a lineal model to discriminate between fibromyalgia patients and healthy controls, providing a high accuracy. These findings indicate that CBFV signals, specifically their complexity and spectral characteristics, contain information that may be relevant for the assessment of fibromyalgia patients in resting-state conditions. PMID:28700720

Musical ability and non-native speech-sound processing are linked through sensitivity to pitch and spectral information.

PubMed

Kempe, Vera; Bublitz, Dennis; Brooks, Patricia J

2015-05-01

Is the observed link between musical ability and non-native speech-sound processing due to enhanced sensitivity to acoustic features underlying both musical and linguistic processing? To address this question, native English speakers (N = 118) discriminated Norwegian tonal contrasts and Norwegian vowels. Short tones differing in temporal, pitch, and spectral characteristics were used to measure sensitivity to the various acoustic features implicated in musical and speech processing. Musical ability was measured using Gordon's Advanced Measures of Musical Audiation. Results showed that sensitivity to specific acoustic features played a role in non-native speech-sound processing: Controlling for non-verbal intelligence, prior foreign language-learning experience, and sex, sensitivity to pitch and spectral information partially mediated the link between musical ability and discrimination of non-native vowels and lexical tones. The findings suggest that while sensitivity to certain acoustic features partially mediates the relationship between musical ability and non-native speech-sound processing, complex tests of musical ability also tap into other shared mechanisms. © 2014 The British Psychological Society.

Characterizing multivariate decoding models based on correlated EEG spectral features.

PubMed

McFarland, Dennis J

2013-07-01

Multivariate decoding methods are popular techniques for analysis of neurophysiological data. The present study explored potential interpretative problems with these techniques when predictors are correlated. Data from sensorimotor rhythm-based cursor control experiments was analyzed offline with linear univariate and multivariate models. Features were derived from autoregressive (AR) spectral analysis of varying model order which produced predictors that varied in their degree of correlation (i.e., multicollinearity). The use of multivariate regression models resulted in much better prediction of target position as compared to univariate regression models. However, with lower order AR features interpretation of the spectral patterns of the weights was difficult. This is likely to be due to the high degree of multicollinearity present with lower order AR features. Care should be exercised when interpreting the pattern of weights of multivariate models with correlated predictors. Comparison with univariate statistics is advisable. While multivariate decoding algorithms are very useful for prediction their utility for interpretation may be limited when predictors are correlated. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Fourier transform infrared spectroscopy microscopic imaging classification based on spatial-spectral features

NASA Astrophysics Data System (ADS)

Liu, Lian; Yang, Xiukun; Zhong, Mingliang; Liu, Yao; Jing, Xiaojun; Yang, Qin

2018-04-01

The discrete fractional Brownian incremental random (DFBIR) field is used to describe the irregular, random, and highly complex shapes of natural objects such as coastlines and biological tissues, for which traditional Euclidean geometry cannot be used. In this paper, an anisotropic variable window (AVW) directional operator based on the DFBIR field model is proposed for extracting spatial characteristics of Fourier transform infrared spectroscopy (FTIR) microscopic imaging. Probabilistic principal component analysis first extracts spectral features, and then the spatial features of the proposed AVW directional operator are combined with the former to construct a spatial-spectral structure, which increases feature-related information and helps a support vector machine classifier to obtain more efficient distribution-related information. Compared to Haralick’s grey-level co-occurrence matrix, Gabor filters, and local binary patterns (e.g. uniform LBPs, rotation-invariant LBPs, uniform rotation-invariant LBPs), experiments on three FTIR spectroscopy microscopic imaging datasets show that the proposed AVW directional operator is more advantageous in terms of classification accuracy, particularly for low-dimensional spaces of spatial characteristics.

Altered cerebral blood flow velocity features in fibromyalgia patients in resting-state conditions.

PubMed

Rodríguez, Alejandro; Tembl, José; Mesa-Gresa, Patricia; Muñoz, Miguel Ángel; Montoya, Pedro; Rey, Beatriz

2017-01-01

The aim of this study is to characterize in resting-state conditions the cerebral blood flow velocity (CBFV) signals of fibromyalgia patients. The anterior and middle cerebral arteries of both hemispheres from 15 women with fibromyalgia and 15 healthy women were monitored using Transcranial Doppler (TCD) during a 5-minute eyes-closed resting period. Several signal processing methods based on time, information theory, frequency and time-frequency analyses were used in order to extract different features to characterize the CBFV signals in the different vessels. Main results indicated that, in comparison with control subjects, fibromyalgia patients showed a higher complexity of the envelope CBFV and a different distribution of the power spectral density. In addition, it has been observed that complexity and spectral features show correlations with clinical pain parameters and emotional factors. The characterization features were used in a lineal model to discriminate between fibromyalgia patients and healthy controls, providing a high accuracy. These findings indicate that CBFV signals, specifically their complexity and spectral characteristics, contain information that may be relevant for the assessment of fibromyalgia patients in resting-state conditions.

Impacts of brown carbon from biomass burning on surface UV and ozone photochemistry in the Amazon Basin

PubMed Central

Mok, Jungbin; Krotkov, Nickolay A.; Arola, Antti; Torres, Omar; Jethva, Hiren; Andrade, Marcos; Labow, Gordon; Eck, Thomas F.; Li, Zhanqing; Dickerson, Russell R.; Stenchikov, Georgiy L.; Osipov, Sergey; Ren, Xinrong

2016-01-01

The spectral dependence of light absorption by atmospheric particulate matter has major implications for air quality and climate forcing, but remains uncertain especially in tropical areas with extensive biomass burning. In the September-October 2007 biomass-burning season in Santa Cruz, Bolivia, we studied light absorbing (chromophoric) organic or “brown” carbon (BrC) with surface and space-based remote sensing. We found that BrC has negligible absorption at visible wavelengths, but significant absorption and strong spectral dependence at UV wavelengths. Using the ground-based inversion of column effective imaginary refractive index in the range 305–368 nm, we quantified a strong spectral dependence of absorption by BrC in the UV and diminished ultraviolet B (UV-B) radiation reaching the surface. Reduced UV-B means less erythema, plant damage, and slower photolysis rates. We use a photochemical box model to show that relative to black carbon (BC) alone, the combined optical properties of BrC and BC slow the net rate of production of ozone by up to 18% and lead to reduced concentrations of radicals OH, HO2, and RO2 by up to 17%, 15%, and 14%, respectively. The optical properties of BrC aerosol change in subtle ways the generally adverse effects of smoke from biomass burning. PMID:27833145

A Stochastic Fractional Dynamics Model of Space-time Variability of Rain

NASA Technical Reports Server (NTRS)

Kundu, Prasun K.; Travis, James E.

2013-01-01

Rainfall varies in space and time in a highly irregular manner and is described naturally in terms of a stochastic process. A characteristic feature of rainfall statistics is that they depend strongly on the space-time scales over which rain data are averaged. A spectral model of precipitation has been developed based on a stochastic differential equation of fractional order for the point rain rate, that allows a concise description of the second moment statistics of rain at any prescribed space-time averaging scale. The model is thus capable of providing a unified description of the statistics of both radar and rain gauge data. The underlying dynamical equation can be expressed in terms of space-time derivatives of fractional orders that are adjusted together with other model parameters to fit the data. The form of the resulting spectrum gives the model adequate flexibility to capture the subtle interplay between the spatial and temporal scales of variability of rain but strongly constrains the predicted statistical behavior as a function of the averaging length and times scales. We test the model with radar and gauge data collected contemporaneously at the NASA TRMM ground validation sites located near Melbourne, Florida and in Kwajalein Atoll, Marshall Islands in the tropical Pacific. We estimate the parameters by tuning them to the second moment statistics of radar data. The model predictions are then found to fit the second moment statistics of the gauge data reasonably well without any further adjustment.

Mothers Consistently Alter Their Unique Vocal Fingerprints When Communicating with Infants.

PubMed

Piazza, Elise A; Iordan, Marius Cătălin; Lew-Williams, Casey

2017-10-23

The voice is the most direct link we have to others' minds, allowing us to communicate using a rich variety of speech cues [1, 2]. This link is particularly critical early in life as parents draw infants into the structure of their environment using infant-directed speech (IDS), a communicative code with unique pitch and rhythmic characteristics relative to adult-directed speech (ADS) [3, 4]. To begin breaking into language, infants must discern subtle statistical differences about people and voices in order to direct their attention toward the most relevant signals. Here, we uncover a new defining feature of IDS: mothers significantly alter statistical properties of vocal timbre when speaking to their infants. Timbre, the tone color or unique quality of a sound, is a spectral fingerprint that helps us instantly identify and classify sound sources, such as individual people and musical instruments [5-7]. We recorded 24 mothers' naturalistic speech while they interacted with their infants and with adult experimenters in their native language. Half of the participants were English speakers, and half were not. Using a support vector machine classifier, we found that mothers consistently shifted their timbre between ADS and IDS. Importantly, this shift was similar across languages, suggesting that such alterations of timbre may be universal. These findings have theoretical implications for understanding how infants tune in to their local communicative environments. Moreover, our classification algorithm for identifying infant-directed timbre has direct translational implications for speech recognition technology. Copyright © 2017 Elsevier Ltd. All rights reserved.

Influence of the substrate material on the optical properties of tungsten diselenide monolayers

NASA Astrophysics Data System (ADS)

Lippert, Sina; Schneider, Lorenz Maximilian; Renaud, Dylan; Kang, Kyung Nam; Ajayi, Obafunso; Kuhnert, Jan; Halbich, Marc-Uwe; Abdulmunem, Oday M.; Lin, Xing; Hassoon, Khaleel; Edalati-Boostan, Saeideh; Duck Kim, Young; Heimbrodt, Wolfram; Yang, Eui-Hyeok; Hone, James C.; Rahimi-Iman, Arash

2017-06-01

Monolayers of transition-metal dichalcogenides such as WSe2 have become increasingly attractive due to their potential in electrical and optical applications. Because the properties of these 2D systems are known to be affected by their surroundings, we report how the choice of the substrate material affects the optical properties of monolayer WSe2. To accomplish this study, pump-density-dependent micro-photoluminescence measurements are performed with time-integrating and time-resolving acquisition techniques. Spectral information and power-dependent mode intensities are compared at 290 K and 10 K for exfoliated WSe2 on SiO2/Si, sapphire (Al2O3), hBN/Si3N4/Si, and MgF2, indicating substrate-dependent appearance and strength of exciton, trion, and biexciton modes. Additionally, one CVD-grown WSe2 monolayer on sapphire is included in this study for direct comparison with its exfoliated counterpart. Time-resolved micro-photoluminescence shows how radiative decay times strongly differ for different substrate materials. Our data indicates exciton-exciton annihilation as a shortening mechanism at room temperature, and subtle trends in the decay rates in correlation to the dielectric environment at cryogenic temperatures. On the measureable time scales, trends are also related to the extent of the respective 2D-excitonic modes’ appearance. This result highlights the importance of further detailed characterization of exciton features in 2D materials, particularly with respect to the choice of substrate.

A fully-coupled discontinuous Galerkin spectral element method for two-phase flow in petroleum reservoirs

NASA Astrophysics Data System (ADS)

Taneja, Ankur; Higdon, Jonathan

2018-01-01

A high-order spectral element discontinuous Galerkin method is presented for simulating immiscible two-phase flow in petroleum reservoirs. The governing equations involve a coupled system of strongly nonlinear partial differential equations for the pressure and fluid saturation in the reservoir. A fully implicit method is used with a high-order accurate time integration using an implicit Rosenbrock method. Numerical tests give the first demonstration of high order hp spatial convergence results for multiphase flow in petroleum reservoirs with industry standard relative permeability models. High order convergence is shown formally for spectral elements with up to 8th order polynomials for both homogeneous and heterogeneous permeability fields. Numerical results are presented for multiphase fluid flow in heterogeneous reservoirs with complex geometric or geologic features using up to 11th order polynomials. Robust, stable simulations are presented for heterogeneous geologic features, including globally heterogeneous permeability fields, anisotropic permeability tensors, broad regions of low-permeability, high-permeability channels, thin shale barriers and thin high-permeability fractures. A major result of this paper is the demonstration that the resolution of the high order spectral element method may be exploited to achieve accurate results utilizing a simple cartesian mesh for non-conforming geological features. Eliminating the need to mesh to the boundaries of geological features greatly simplifies the workflow for petroleum engineers testing multiple scenarios in the face of uncertainty in the subsurface geology.

Optical spectral singularities as threshold resonances

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mostafazadeh, Ali

2011-04-15

Spectral singularities are among generic mathematical features of complex scattering potentials. Physically they correspond to scattering states that behave like zero-width resonances. For a simple optical system, we show that a spectral singularity appears whenever the gain coefficient coincides with its threshold value and other parameters of the system are selected properly. We explore a concrete realization of spectral singularities for a typical semiconductor gain medium and propose a method of constructing a tunable laser that operates at threshold gain.

Analysis of spectrally resolved autofluorescence images by support vector machines

NASA Astrophysics Data System (ADS)

Mateasik, A.; Chorvat, D.; Chorvatova, A.

2013-02-01

Spectral analysis of the autofluorescence images of isolated cardiac cells was performed to evaluate and to classify the metabolic state of the cells in respect to the responses to metabolic modulators. The classification was done using machine learning approach based on support vector machine with the set of the automatically calculated features from recorded spectral profile of spectral autofluorescence images. This classification method was compared with the classical approach where the individual spectral components contributing to cell autofluorescence were estimated by spectral analysis, namely by blind source separation using non-negative matrix factorization. Comparison of both methods showed that machine learning can effectively classify the spectrally resolved autofluorescence images without the need of detailed knowledge about the sources of autofluorescence and their spectral properties.

High-resolution CASSINI-VIMS mosaics of Titan and the icy Saturnian satellites

USGS Publications Warehouse

Jaumann, R.; Stephan, K.; Brown, R.H.; Buratti, B.J.; Clark, R.N.; McCord, T.B.; Coradini, A.; Capaccioni, F.; Filacchione, G.; Cerroni, P.; Baines, K.H.; Bellucci, G.; Bibring, J.-P.; Combes, M.; Cruikshank, D.P.; Drossart, P.; Formisano, V.; Langevin, Y.; Matson, D.L.; Nelson, R.M.; Nicholson, P.D.; Sicardy, B.; Sotin, Christophe; Soderbloom, L.A.; Griffith, C.; Matz, K.-D.; Roatsch, Th.; Scholten, F.; Porco, C.C.

2006-01-01

The Visual Infrared Mapping Spectrometer (VIMS) onboard the CASSINI spacecraft obtained new spectral data of the icy satellites of Saturn after its arrival at Saturn in June 2004. VIMS operates in a spectral range from 0.35 to 5.2 ??m, generating image cubes in which each pixel represents a spectrum consisting of 352 contiguous wavebands. As an imaging spectrometer VIMS combines the characteristics of both a spectrometer and an imaging instrument. This makes it possible to analyze the spectrum of each pixel separately and to map the spectral characteristics spatially, which is important to study the relationships between spectral information and geological and geomorphologic surface features. The spatial analysis of the spectral data requires the determination of the exact geographic position of each pixel on the specific surface and that all 352 spectral elements of each pixel show the same region of the target. We developed a method to reproject each pixel geometrically and to convert the spectral data into map projected image cubes. This method can also be applied to mosaic different VIMS observations. Based on these mosaics, maps of the spectral properties for each Saturnian satellite can be derived and attributed to geographic positions as well as to geological and geomorphologic surface features. These map-projected mosaics are the basis for all further investigations. ?? 2006 Elsevier Ltd. All rights reserved.

Retrieval of spheroid particle size distribution from spectral extinction data in the independent mode using PCA approach

NASA Astrophysics Data System (ADS)

Tang, Hong; Lin, Jian-Zhong

2013-01-01

An improved anomalous diffraction approximation (ADA) method is presented for calculating the extinction efficiency of spheroids firstly. In this approach, the extinction efficiency of spheroid particles can be calculated with good accuracy and high efficiency in a wider size range by combining the Latimer method and the ADA theory, and this method can present a more general expression for calculating the extinction efficiency of spheroid particles with various complex refractive indices and aspect ratios. Meanwhile, the visible spectral extinction with varied spheroid particle size distributions and complex refractive indices is surveyed. Furthermore, a selection principle about the spectral extinction data is developed based on PCA (principle component analysis) of first derivative spectral extinction. By calculating the contribution rate of first derivative spectral extinction, the spectral extinction with more significant features can be selected as the input data, and those with less features is removed from the inversion data. In addition, we propose an improved Tikhonov iteration method to retrieve the spheroid particle size distributions in the independent mode. Simulation experiments indicate that the spheroid particle size distributions obtained with the proposed method coincide fairly well with the given distributions, and this inversion method provides a simple, reliable and efficient method to retrieve the spheroid particle size distributions from the spectral extinction data.

Spectral characteristics and feature selection of satellite remote sensing data for climate and anthropogenic changes assessment in Bucharest area

NASA Astrophysics Data System (ADS)

Zoran, Maria; Savastru, Roxana; Savastru, Dan; Tautan, Marina; Miclos, Sorin; Cristescu, Luminita; Carstea, Elfrida; Baschir, Laurentiu

2010-05-01

Urban systems play a vital role in social and economic development in all countries. Their environmental changes can be investigated on different spatial and temporal scales. Urban and peri-urban environment dynamics is of great interest for future planning and decision making as well as in frame of local and regional changes. Changes in urban land cover include changes in biotic diversity, actual and potential primary productivity, soil quality, runoff, and sedimentation rates, and cannot be well understood without the knowledge of land use change that drives them. The study focuses on the assessment of environmental features changes for Bucharest metropolitan area, Romania by satellite remote sensing and in-situ monitoring data. Rational feature selection from the varieties of spectral channels in the optical wavelengths of electromagnetic spectrum (VIS and NIR) is very important for effective analysis and information extraction of remote sensing data. Based on comprehensively analyses of the spectral characteristics of remote sensing data is possibly to derive environmental changes in urban areas. The information quantity contained in a band is an important parameter in evaluating the band. The deviation and entropy are often used to show information amount. Feature selection is one of the most important steps in recognition and classification of remote sensing images. Therefore, it is necessary to select features before classification. The optimal features are those that can be used to distinguish objects easily and correctly. Three factors—the information quantity of bands, the correlation between bands and the spectral characteristic (e.g. absorption specialty) of classified objects in test area Bucharest have been considered in our study. As, the spectral characteristic of an object is influenced by many factors, being difficult to define optimal feature parameters to distinguish all the objects in a whole area, a method of multi-level feature selection was suggested. On the basis of analyzing the information quantity of bands, correlation between different bands, spectral absorption characteristics of objects and object separability in bands, a fundamental method of optimum band selection and feature extraction from remote sensing data was discussed. Spectral signatures of different terrain features have been used to extract structural patterns aiming to separate surface units and to classify the general categories. The synergetic analysis and interpretation of the different satellite images (LANDSAT: TM, ETM; MODIS, IKONOS) acquired over a period of more than 20 years reveals significant aspects regarding impacts of climate and anthropogenic changes on urban/periurban environment. It was delimited residential zones of industrial zones which are very often a source of pollution. An important role has urban green cover assessment. Have been emphasized the particularities of the functional zones from different points of view: architectural, streets and urban surface traffic, some components of urban infrastructure as well as habitat quality. The growth of Bucharest urban area in Romania has been a result of a rapid process of industrialization, and also of the increase of urban population. Information on the spatial pattern and temporal dynamics of land cover and land use of urban areas is critical to address a wide range of practical problems relating to urban regeneration, urban sustainability and rational planning policy.

Multi-Centrality Graph Spectral Decompositions and Their Application to Cyber Intrusion Detection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Pin-Yu; Choudhury, Sutanay; Hero, Alfred

Many modern datasets can be represented as graphs and hence spectral decompositions such as graph principal component analysis (PCA) can be useful. Distinct from previous graph decomposition approaches based on subspace projection of a single topological feature, e.g., the centered graph adjacency matrix (graph Laplacian), we propose spectral decomposition approaches to graph PCA and graph dictionary learning that integrate multiple features, including graph walk statistics, centrality measures and graph distances to reference nodes. In this paper we propose a new PCA method for single graph analysis, called multi-centrality graph PCA (MC-GPCA), and a new dictionary learning method for ensembles ofmore » graphs, called multi-centrality graph dictionary learning (MC-GDL), both based on spectral decomposition of multi-centrality matrices. As an application to cyber intrusion detection, MC-GPCA can be an effective indicator of anomalous connectivity pattern and MC-GDL can provide discriminative basis for attack classification.« less

Analysis of cosmetic residues on a single human hair by ATR FT-IR microspectroscopy

NASA Astrophysics Data System (ADS)

Pienpinijtham, Prompong; Thammacharoen, Chuchaat; Naranitad, Suwimol; Ekgasit, Sanong

2018-05-01

In this work, ATR FT-IR spectra of single human hair and cosmetic residues on hair surface are successfully collected using a homemade dome-shaped Ge μIRE accessary installed on an infrared microscope. By collecting ATR spectra of hairs from the same person, the spectral patterns are identical and superimposed while different spectral features are observed from ATR spectra of hairs collected from different persons. The spectral differences depend on individual hair characteristics, chemical treatments, and cosmetics on hair surface. The "Contact-and-Collect" technique that transfers remarkable materials on the hair surface to the tip of the Ge μIRE enables an identification of cosmetics on a single hair. Moreover, the differences between un-split and split hairs are also studied in this report. These highly specific spectral features can be employed for unique identification or for differentiation of hairs based on the molecular structures of hairs and cosmetics on hairs.

Formation of spectral lines in planetary atmospheres. I - Theory for cloudy atmospheres: Application to Venus.

NASA Technical Reports Server (NTRS)

Hunt, G. E.

1972-01-01

The theory of the formation of spectral lines in a cloudy planetary atmosphere is studied in detail. It is shown that models based upon homogeneous, isotropically scattering atmospheres cannot be used to reproduce observed spectroscopic features of phase effect and the shape of spectral lines for weak and strong bands. The theory must, therefore, be developed using an inhomogeneous (gravitational) model of a planetary atmosphere, accurately incorporating all the physical processes of radiative transfer. Such a model of the lower Venus atmosphere, consistent with our present knowledge, is constructed. The results discussed in this article demonstrate the effects of the parameters that describe the atmospheric model on the spectroscopic features of spectral line profile and phase effect, at visible and near infrared wavelengths. This information enables us to develop a comprehensive theory of line formation in a Venus atmosphere.

a Novel Deep Convolutional Neural Network for Spectral-Spatial Classification of Hyperspectral Data

NASA Astrophysics Data System (ADS)

Li, N.; Wang, C.; Zhao, H.; Gong, X.; Wang, D.

2018-04-01

Spatial and spectral information are obtained simultaneously by hyperspectral remote sensing. Joint extraction of these information of hyperspectral image is one of most import methods for hyperspectral image classification. In this paper, a novel deep convolutional neural network (CNN) is proposed, which extracts spectral-spatial information of hyperspectral images correctly. The proposed model not only learns sufficient knowledge from the limited number of samples, but also has powerful generalization ability. The proposed framework based on three-dimensional convolution can extract spectral-spatial features of labeled samples effectively. Though CNN has shown its robustness to distortion, it cannot extract features of different scales through the traditional pooling layer that only have one size of pooling window. Hence, spatial pyramid pooling (SPP) is introduced into three-dimensional local convolutional filters for hyperspectral classification. Experimental results with a widely used hyperspectral remote sensing dataset show that the proposed model provides competitive performance.

The basal ganglia is necessary for learning spectral, but not temporal features of birdsong

PubMed Central

Ali, Farhan; Fantana, Antoniu L.; Burak, Yoram; Ölveczky, Bence P.

2013-01-01

Executing a motor skill requires the brain to control which muscles to activate at what times. How these aspects of control - motor implementation and timing - are acquired, and whether the learning processes underlying them differ, is not well understood. To address this we used a reinforcement learning paradigm to independently manipulate both spectral and temporal features of birdsong, a complex learned motor sequence, while recording and perturbing activity in underlying circuits. Our results uncovered a striking dissociation in how neural circuits underlie learning in the two domains. The basal ganglia was required for modifying spectral, but not temporal structure. This functional dissociation extended to the descending motor pathway, where recordings from a premotor cortex analogue nucleus reflected changes to temporal, but not spectral structure. Our results reveal a strategy in which the nervous system employs different and largely independent circuits to learn distinct aspects of a motor skill. PMID:24075977

Regarding Rhea

NASA Image and Video Library

2016-08-01

Rhea, like many moons in the outer solar system, appears dazzlingly bright in full sunlight. This is the signature of the water ice that forms most of the moon's surface. Rhea (949 miles or 1,527 kilometers across) is Saturn's second largest moon after Titan. Its ancient surface is one of the most heavily cratered of all of Saturn's moons. Subtle albedo variations across the disk of Rhea hint at past geologic activity. This view looks toward the anti-Saturn hemisphere of Rhea. North on Rhea is up and rotated 36 degrees to the right. The image was taken with the Cassini spacecraft narrow-angle camera on June 3, 2016 using a spectral filter which preferentially admits wavelengths of ultraviolet light centered at 338 nanometers. http://photojournal.jpl.nasa.gov/catalog/PIA20495

Gravity's Rainbow

NASA Image and Video Library

2018-04-23

Saturn's rings display their subtle colors in this view captured on Aug. 22, 2009, by NASA's Cassini spacecraft. The particles that make up the rings range in size from smaller than a grain of sand to as large as mountains, and are mostly made of water ice. The exact nature of the material responsible for bestowing color on the rings remains a matter of intense debate among scientists. Images taken using red, green and blue spectral filters were combined to create this natural color view. Cassini's narrow-angle camera took the images at a distance of approximately 1.27 million miles (2.05 million kilometers) from the center of the rings. The Cassini spacecraft ended its mission on Sept. 15, 2017 https://photojournal.jpl.nasa.gov/catalog/PIA22418

Near-field hyperspectral quantum probing of multimodal plasmonic resonators

NASA Astrophysics Data System (ADS)

Cuche, A.; Berthel, M.; Kumar, U.; Colas des Francs, G.; Huant, S.; Dujardin, E.; Girard, C.; Drezet, A.

2017-03-01

Quantum systems, excited by an external source of photons, display a photodynamics that is ruled by a subtle balance between radiative or nonradiative energy channels when interacting with metallic nanostructures. We apply and generalize this concept to achieve a quantum probing of multimodal plasmonic resonators by collecting and filtering the broad emission spectra generated by a nanodiamond (ND) hosting a small set of nitrogen-vacancy (NV) color centers attached at the apex of an optical tip. Spatially and spectrally resolved information on the photonic local density of states (ph-LDOS) can be recorded with this technique in the immediate vicinity of plasmonic resonators, paving the way for a complete near-field optical characterization of any kind of nanoresonators in the single photon regime.

Characterization of the Titan's VIMS - units: Using Spectral Slopes

NASA Astrophysics Data System (ADS)

Brossier, Jérémy F.; Jaumann, Ralf; Stephan, Katrin; Le Mouélic, Stéphane; Brown, Robert H.

2016-04-01

Since the equatorial regions of Titan have been fully observed by the Visible and Infrared Mapping Spectrometer (VIMS) [1], the analysis of false-color composites enables distinguishing four main spectral units: the equatorial bright, brown, blue, and 5 μm-bright spectral units [2-4]. More precisely, the equatorial bright plateaus and inselbergs correspond to water-ice substrate coated by a layer of organic sediments. Moreover, the blue materials are more likely enriched in water-ice, which consist of icy particles exposition derived from the high standing plateaus and deposited into the lowlands after fluvial/pluvial processes [5] and/or impact cratering [6]. These blue materials are mainly located at the frontier of the large bright plateaus, and hence considered as transition zones to the brown areas corresponding to the radar dunes [7]. Whereas these brown dunes consist on atmospheric aerosols (i.e. tholins) [4] contaminated with particles of water-ice. Here we try to better characterize these spectral units, through VIMS observations at high resolution from TA (Oct. 2004) to T114 (Nov. 2015). Regions of interest show local transition zones between the equatorial bright areas, the blue materials, and the brown dunes, suggesting weathering and erosional processes (e.g. the Huygens landing site; areas at the east of Xanadu province; and Bohai Sinus at the south of Quivira plateau) [5,8], and impact cratering (e.g. Sinlap, Selk, Menrva, and Paxsi craters) [6,9]. Areas exposing large (i.e. Tui and Hotei Regiones) and small (e.g. Yalaing Terra, NW Belet, and NW Fensal) 5 μm-bright units - presumed evaporitic deposits - are also included in this study [9-11]. Subtle differences in the spectral behavior of these four units can be enhanced by using ratios of VIMS channels. At short wavelengths (i.e. below 2 μm), brown and blue materials seem to correspond to a granular mixture of organic sediments - similar to the atmospheric aerosols - and water-ice particles [7]. As for the 5 μm-bright units, they show paucity in water-ice at the longer wavelengths, implying that these features cannot be related to cryovolcanic processes, as it has been originally suggested for Hotei and Tui Regiones, arguing for an evaporitic origin [9-11]. References: [1] Brown, R. H. et al. (2005) SSR. [2] Barnes, J. W. et al. (2007) Icarus, 186 (1). [3] Soderblom, L. A. et al. (2007) PSS, 55 (13). [4] Langhans, M. H. et al. (2011) PSS, 60. [5] Jaumann, R. et al. (2008) Icarus, 197. [6] Le Mouélic, S. et al. (2008) JGR, 113 (E04003). [7] Rodriguez, S. et al. (2013) Icarus, 230. [8] Jaumann, R. et al. (2009) LPSC. [9] Soderblom, L. A. et al. (2009) Icarus, 204. [10] Solomonidou, A. et al. (2013) PSS, 77. [11] McKenzie, M. S. et al. (2014) Icarus.

The Colors of Tethys II

NASA Image and Video Library

2015-07-29

This enhanced-color mosaic of Saturn's icy moon Tethys shows a range of features on the moon's trailing hemisphere. Tethys is tidally locked to Saturn, so the trailing hemisphere is the side of the moon that always faces opposite its direction of motion as it orbits the planet. This view was obtained about two and a half hours earlier than PIA19636 and shows terrain slightly farther to the west and south of that view. Two versions of the mosaic are presented here: one with standard image processing (Figure 1), and one that strongly enhances the relief of craters and other surface features (Figure 2). Images taken using clear, green, infrared and ultraviolet spectral filters were combined to create the view, which highlights subtle color differences across Tethys' surface at wavelengths not visible to human eyes. The moon's surface is fairly uniform in natural color. The color of the surface can be seen to change across the disk, from yellowish hues to nearly white. These broad color changes are affected by a number of external processes. First, Saturn's diffuse E-ring preferentially bombards Tethys' leading hemisphere, toward the right side in this image, with ice bright ice grains. At the same time, charged particles from Saturn's radiation belt bombard the surface on the trailing side, causing color changes due to chemical alteration of the materials there. The albedo -- a measure of the surface's reflectivity -- drops by 10 to 15 percent from the moon's leading side to the trailing side. Similar global color patterns exist on other Saturnian moons. On a much smaller scale, enigmatic, arc-shaped reddish streaks are faintly visible across the heavily-cratered surface, particularly in the upper right quarter of the image (see PIA19637 for a close-up view of these features). The origin of this localized color contrast is not yet understood. This mosaic is an orthographic projection constructed from 52 Cassini images obtained on April 11, 2015 with the Cassini spacecraft narrow-angle camera. Image scale is about 1,000 feet (300 meters) per pixel. The images were obtained at a distance of approximately 33,000 miles (53,000 kilometers) from Tethys. http://photojournal.jpl.nasa.gov/catalog/PIA19638

Automated method for the systematic interpretation of resonance peaks in spectrum data

DOEpatents

Damiano, B.; Wood, R.T.

1997-04-22

A method is described for spectral signature interpretation. The method includes the creation of a mathematical model of a system or process. A neural network training set is then developed based upon the mathematical model. The neural network training set is developed by using the mathematical model to generate measurable phenomena of the system or process based upon model input parameter that correspond to the physical condition of the system or process. The neural network training set is then used to adjust internal parameters of a neural network. The physical condition of an actual system or process represented by the mathematical model is then monitored by extracting spectral features from measured spectra of the actual process or system. The spectral features are then input into said neural network to determine the physical condition of the system or process represented by the mathematical model. More specifically, the neural network correlates the spectral features (i.e. measurable phenomena) of the actual process or system with the corresponding model input parameters. The model input parameters relate to specific components of the system or process, and, consequently, correspond to the physical condition of the process or system. 1 fig.

Accurate palm vein recognition based on wavelet scattering and spectral regression kernel discriminant analysis

NASA Astrophysics Data System (ADS)

Elnasir, Selma; Shamsuddin, Siti Mariyam; Farokhi, Sajad

2015-01-01

Palm vein recognition (PVR) is a promising new biometric that has been applied successfully as a method of access control by many organizations, which has even further potential in the field of forensics. The palm vein pattern has highly discriminative features that are difficult to forge because of its subcutaneous position in the palm. Despite considerable progress and a few practical issues, providing accurate palm vein readings has remained an unsolved issue in biometrics. We propose a robust and more accurate PVR method based on the combination of wavelet scattering (WS) with spectral regression kernel discriminant analysis (SRKDA). As the dimension of WS generated features is quite large, SRKDA is required to reduce the extracted features to enhance the discrimination. The results based on two public databases-PolyU Hyper Spectral Palmprint public database and PolyU Multi Spectral Palmprint-show the high performance of the proposed scheme in comparison with state-of-the-art methods. The proposed approach scored a 99.44% identification rate and a 99.90% verification rate [equal error rate (EER)=0.1%] for the hyperspectral database and a 99.97% identification rate and a 99.98% verification rate (EER=0.019%) for the multispectral database.

Automated method for the systematic interpretation of resonance peaks in spectrum data

DOEpatents

Damiano, Brian; Wood, Richard T.

1997-01-01

A method for spectral signature interpretation. The method includes the creation of a mathematical model of a system or process. A neural network training set is then developed based upon the mathematical model. The neural network training set is developed by using the mathematical model to generate measurable phenomena of the system or process based upon model input parameter that correspond to the physical condition of the system or process. The neural network training set is then used to adjust internal parameters of a neural network. The physical condition of an actual system or process represented by the mathematical model is then monitored by extracting spectral features from measured spectra of the actual process or system. The spectral features are then input into said neural network to determine the physical condition of the system or process represented by the mathematical. More specifically, the neural network correlates the spectral features (i.e. measurable phenomena) of the actual process or system with the corresponding model input parameters. The model input parameters relate to specific components of the system or process, and, consequently, correspond to the physical condition of the process or system.

Real-time evaluation of polyphenol oxidase (PPO) activity in lychee pericarp based on weighted combination of spectral data and image features as determined by fuzzy neural network.

PubMed

Yang, Yi-Chao; Sun, Da-Wen; Wang, Nan-Nan; Xie, Anguo

2015-07-01

A novel method of using hyperspectral imaging technique with the weighted combination of spectral data and image features by fuzzy neural network (FNN) was proposed for real-time prediction of polyphenol oxidase (PPO) activity in lychee pericarp. Lychee images were obtained by a hyperspectral reflectance imaging system operating in the range of 400-1000nm. A support vector machine-recursive feature elimination (SVM-RFE) algorithm was applied to eliminating variables with no or little information for the prediction from all bands, resulting in a reduced set of optimal wavelengths. Spectral information at the optimal wavelengths and image color features were then used respectively to develop calibration models for the prediction of PPO in pericarp during storage, and the results of two models were compared. In order to improve the prediction accuracy, a decision strategy was developed based on weighted combination of spectral data and image features, in which the weights were determined by FNN for a better estimation of PPO activity. The results showed that the combined decision model was the best among all of the calibration models, with high R(2) values of 0.9117 and 0.9072 and low RMSEs of 0.45% and 0.459% for calibration and prediction, respectively. These results demonstrate that the proposed weighted combined decision method has great potential for improving model performance. The proposed technique could be used for a better prediction of other internal and external quality attributes of fruits. Copyright © 2015 Elsevier B.V. All rights reserved.

Absorption Efficiencies of Forsterite. I: DDA Explorations in Grain Shape and Size

NASA Technical Reports Server (NTRS)

Lindsay, Sean S.; Wooden, Diane; Harker, David E.; Kelley, Michael S.; Woodward, Charles E.; Murphy, Jim R.

2013-01-01

We compute the absorption efficiency (Q(sub abs)) of forsterite using the discrete dipole approximation (DDA) in order to identify and describe what characteristics of crystal grain shape and size are important to the shape, peak location, and relative strength of spectral features in the 8 - 40 micron wavelength range. Using the DDSCAT code, we compute Q(sub abs) for non-spherical polyhedral grain shapes with a(sub eff) = 0.1 micron. The shape characteristics identified are: 1) elongation/reduction along one of three crystallographic axes; 2) asymmetry, such that all three crystallographic axes are of different lengths; and 3) the presence of crystalline faces that are not parallel to a specific crystallographic axis, e.g., non-rectangular prisms and (di)pyramids. Elongation/reduction dominates the locations and shapes of spectral features near 10, 11, 16, 23.5, 27, and 33.5 micron, while asymmetry and tips are secondary shape effects. Increasing grain sizes (0.1 - 1.0 micron) shifts the 10, 11 micron features systematically towards longer wavelengths and relative to the 11 micron feature increases the strengths and slightly broadens the longer wavelength features. Seven spectral shape classes are established for crystallographic a-, b-, and c-axes and include columnar and platelet shapes plus non-elongated or equant grain shapes. The spectral shape classes and the effects of grain size have practical application in identifying or excluding columnar, platelet or equant forsterite grain shapes in astrophysical environs. Identification of the shape characteristics of forsterite from 8 - 40 micron spectra provides a potential means to probe the temperatures at which forsterite formed.

An electron spin resonance study of gamma-irradiated grapes

NASA Astrophysics Data System (ADS)

Tabner, Brian J.; Tabner, Vivienne A.

The ESR spectra of the seeds, skins and stalks of unirradiated and γ-irradiated Cape black grapes have been obtained. In the spectra of all parts of the grape a single line (g ca. 2.004) is observed both before and after irradiation. New spectral features are observed after irradiation with doses of between 2 and 10 kGy. Some of these features decline in intensity over a period of several days. However, in the case of stalks, new spectral features are readily observed over the shelf-life of the fruit and in samples irradiated to a dose of only 2kGy.

The Copernicus ultraviolet spectral atlas of Sirius

NASA Technical Reports Server (NTRS)

Rogerson, John B., Jr.

1987-01-01

A near-ultraviolet spectral atlas for the A1 V star Alpha CMa (Sirius) has been prepared from data taken by the Princeton spectrometer aboard the Copernicus satellite. The spectral region from 1649 to 3170 A has been scanned with a resolution of 0.1 A. The atlas is presented in graphs, and line identifications for the absorption features have been tabulated.

Feature selection methods for object-based classification of sub-decimeter resolution digital aerial imagery

USDA-ARS?s Scientific Manuscript database

Due to the availability of numerous spectral, spatial, and contextual features, the determination of optimal features and class separabilities can be a time consuming process in object-based image analysis (OBIA). While several feature selection methods have been developed to assist OBIA, a robust c...

Development of a new approach based on midwave infrared spectroscopy for post-consumer black plastic waste sorting in the recycling industry.

PubMed

Rozenstein, Offer; Puckrin, Eldon; Adamowski, Jan

2017-10-01

Waste sorting is key to the process of waste recycling. Exact identification of plastic resin and wood products using Near Infrared (NIR, 1-1.7µm) sensing is currently in use. Yet, dark targets characterized by low reflectance, such as black plastics, are hard to identify by this method. Following the recent success of Midwave Infrared (MWIR, 3-12µm) measurements to identify coloured plastic polymers, the aim of this study was to assess whether this technique is applicable to sorting black plastic polymers and wood products. We performed infrared reflectance contact measurements of 234 plastic samples and 29 samples of wood and paper products. Plastic samples included black, coloured and transparent Polyethylene Terephthalate (PET), Polyethylene (PE), Polyvinyl Chloride (PVC), Polypropylene (PP), Polylactic acid (PLA) and Polystyrene (PS). The spectral signatures of the black and coloured plastic samples were compared with clear plastic samples and signatures documented in the literature to identify the polymer spectral features in the presence of coloured material. This information was used to determine the spectral bands that best suit the sorting of black plastic polymers. The main NIR-MWIR absorption features of wood, cardboard and paper were identified as well according to the spectral measurements. Good agreement was found between our measurements and the absorption features documented in the literature. The new approach using MWIR spectral features appears to be useful for black plastics as it overcomes some of the limitations in the NIR region to identify them. The main limitation of this technique for industrial applications is the trade-off between the signal-to-noise ratio of the sensor operating in standoff mode and the speed at which waste is moved under the sensor. This limitation can be resolved by reducing the system's spectral resolution to 16cm -1 , which allows for faster spectra acquisition while maintaining a reasonable signal-to-noise ratio. Copyright © 2017 Elsevier Ltd. All rights reserved.

INSTRUMENTS AND METHODS OF INVESTIGATION: Spectral and spectral-frequency methods of investigating atmosphereless bodies of the Solar system

NASA Astrophysics Data System (ADS)

Busarev, Vladimir V.; Prokof'eva-Mikhailovskaya, Valentina V.; Bochkov, Valerii V.

2007-06-01

A method of reflectance spectrophotometry of atmosphereless bodies of the Solar system, its specificity, and the means of eliminating basic spectral noise are considered. As a development, joining the method of reflectance spectrophotometry with the frequency analysis of observational data series is proposed. The combined spectral-frequency method allows identification of formations with distinctive spectral features, and estimations of their sizes and distribution on the surface of atmospherelss celestial bodies. As applied to investigations of asteroids 21 Lutetia and 4 Vesta, the spectral frequency method has given us the possibility of obtaining fundamentally new information about minor planets.

SpecViz: Interactive Spectral Data Analysis

NASA Astrophysics Data System (ADS)

Earl, Nicholas Michael; STScI

2016-06-01

The astronomical community is about to enter a new generation of scientific enterprise. With next-generation instrumentation and advanced capabilities, the need has arisen to equip astronomers with the necessary tools to deal with large, multi-faceted data. The Space Telescope Science Institute has initiated a data analysis forum for the creation, development, and maintenance of software tools for the interpretation of these new data sets. SpecViz is a spectral 1-D interactive visualization and analysis application built with Python in an open source development environment. A user-friendly GUI allows for a fast, interactive approach to spectral analysis. SpecViz supports handling of unique and instrument-specific data, incorporation of advanced spectral unit handling and conversions in a flexible, high-performance interactive plotting environment. Active spectral feature analysis is possible through interactive measurement and statistical tools. It can be used to build wide-band SEDs, with the capability of combining or overplotting data products from various instruments. SpecViz sports advanced toolsets for filtering and detrending spectral lines; identifying, isolating, and manipulating spectral features; as well as utilizing spectral templates for renormalizing data in an interactive way. SpecViz also includes a flexible model fitting toolset that allows for multi-component models, as well as custom models, to be used with various fitting and decomposition routines. SpecViz also features robust extension via custom data loaders and connection to the central communication system underneath the interface for more advanced control. Incorporation with Jupyter notebooks via connection with the active iPython kernel allows for SpecViz to be used in addition to a user’s normal workflow without demanding the user drastically alter their method of data analysis. In addition, SpecViz allows the interactive analysis of multi-object spectroscopy in the same straight-forward, consistent way. Through the development of such tools, STScI hopes to unify astronomical data analysis software for JWST and other instruments, allowing for efficient, reliable, and consistent scientific results.

Microstructure-property relationships in directionally solidified single crystal nickel-base superalloys

NASA Technical Reports Server (NTRS)

Mackay, R. A.; Nathal, M. V.

1986-01-01

Some of the microstructural features which influence the creep properties of directionally solidified and single crystal nickel-base superalloys are discussed. Gamma precipitate size and morphology, gamma-gamma lattice mismatch, phase instability, alloy composition, and processing variations are among the factors considered. Recent experimental results are reviewed and related to the operative deformation mechanisms and to the corresponding mechanical properties. Special emphasis is placed on the creep behavior of single crystal superalloys at high temperatures, where directional gamma coarsening is prominent, and at lower temperatures, where gamma coarsening rates are significantly reduced. It can be seen that very subtle changes in microstructural features can have profound effects on the subsequent properties of these materials.

Mars analog minerals' spectral reflectance characteristics under Martian surface conditions

NASA Astrophysics Data System (ADS)

Poitras, J. T.; Cloutis, E. A.; Salvatore, M. R.; Mertzman, S. A.; Applin, D. M.; Mann, P.

2018-05-01

We investigated the spectral reflectance properties of minerals under a simulated Martian environment. Twenty-eight different hydrated or hydroxylated phases of carbonates, sulfates, and silica minerals were selected based on past detection on Mars through spectral remote sensing data. Samples were ground and dry sieved to <45 μm grain size and characterized by XRD before and after 133 days inside a simulated Martian surface environment (pressure 5 Torr and CO2 fed). Reflectance spectra from 0.35 to 4 μm were taken periodically through a sapphire (0.35-2.5 μm) and zinc selenide (2.5-4 μm) window over a 133-day period. Mineral stability on the Martian surface was assessed through changes in spectral characteristics. Results indicate that the hydrated carbonates studied would be stable on the surface of Mars, only losing adsorbed H2O while maintaining their diagnostic spectral features. Sulfates were less stable, often with shifts in the band position of the SO, Fe, and OH absorption features. Silicas displayed spectral shifts related to SiOH and hydration state of the mineral surface, while diagnostic bands for quartz were stable. Previous detection of carbonate minerals based on 2.3-2.5 μm and 3.4-3.9 μm features appears to be consistent with our results. Sulfate mineral detection is more questionable since there can be shifts in band position related to SO4. The loss of the 0.43 μm Fe3+ band in many of the sulfates indicate that there are fewer potential candidates for Fe3+ sulfates to permanently exist on the Martian surface based on this band. The gypsum sample changed phase to basanite during desiccation as demonstrated by both reflectance and XRD. Silica on Mars has been detected using band depth ratio at 1.91 and 1.96 μm and band minimum position of the 1.4 μm feature, and the properties are also used to determine their age. This technique continues to be useful for positive silica identifications, however, silica age appears to be less consistent with our laboratory data. These results will be useful in spectral libraries for characterizing Martian remote sensed data.

3-µm Spectroscopy of Asteroid 16 Psyche

NASA Astrophysics Data System (ADS)

Takir, Driss; Reddy, Vishnu; Sanchez, Juan; Shepard, Michael K.

2016-10-01

Asteroid 16 Psyche, an M-type asteroid, is thought to be one of the most massive exposed iron metal object in the asteroid belt. The high radar albedos of Psyche suggest that this differentiated asteroid is dominantly composed of metal. Psyche was previously found to be featureless in the 3-µm spectral region. However, in our study we found that this asteroid exhibits a 3-µm absorption feature, possibly indicating the presence of hydrated silicates.We have observed Psyche in the 3-µm spectral region, using the long-wavelength cross-dispersed (LXD:1.9-4.2 µm) mode of the SpeX spectrograph/imager at the NASA Infrared Telescope Facility (IRTF). For data reduction, we used the IDL (Interactive Data Language)-based spectral reduction tool Spextool (v4.1). Psyche was observed over the course of three nights with an apparent visual magnitude of ~9.50: 8 December 2015 (3 sets), 9 December 2015 (1 set), and 10 March 2016 (1 set). These observations have revealed that Psyche may exhibit a 3-µm absorption feature, similar to the sharp group in the 2.9-3.3-µm spectral range. Psyche also exhibits an absorption feature similar to the one in Ceres and Ceres-like group in the spectral 3.3-4.0-µm range. These 3-µm observational results revealed that Psyche may not be as featureless as once thought in the 3-µm spectral region.Evidence for the 3-µm band was found on the surfaces of many M-type asteroids and a number of plausible alternative interpretations for the presence of this 3-µm band were previously suggested. These interpretations include the presence of anhydrous silicates containing structural OH, the presence of fluid inclusions, the presence of xenolithic hydrous meteorite components on asteroid surfaces from impacts, solar wind-implanted H, or the presence of troilite. The detection of the Ceres-like feature in the 3.3-4.0-µm spectral range, however, would rule out some of these alternative interpretations, especially the solar wind-implanted H.

Recent Observations and Modeling of Narrowband Stimulated Electromagnetic Emissions SEEs at HAARP and EISCAT

NASA Astrophysics Data System (ADS)

Scales, W.; Mahmoudian, A.; Fu, H.; Bordikar, M. R.; Samimi, A.; Bernhardt, P. A.; Briczinski, S. J., Jr.; Kosch, M. J.; Senior, A.; Isham, B.

2014-12-01

There has been significant interest in so-called narrowband Stimulated Electromagnetic Emission SEE over the past several years due to recent discoveries at the High Frequency Active Auroral Research Program HAARP facility near Gakone, Alaska. Narrowband SEE (NSEE) has been defined as spectral features in the SEE spectrum typically within 1 kHz of the transmitter (or pump) frequency. SEE is due to nonlinear processes leading to re-radiation at frequencies other than the pump wave frequency during heating the ionospheric plasma with high power HF radio waves. Although NSEE exhibits a richly complex structure, it has now been shown after a substantial number of observations at HAARP, that NSEE can be grouped into two basic classes. The first are those spectral features, associated with Stimulated Brillouin Scatter SBS, which typically occur when the pump frequency is not close to electron gyro-harmonic frequencies. Typically, these spectral features are within roughly 50 Hz of the pump wave frequency where it is to be noted that the O+ ion gyro-frequency is roughly 50 Hz. The second class of spectral features corresponds to the case when the pump wave frequency is typically within roughly 10 kHz of electron gyro-harmonic frequencies. In this case, spectral features ordered by harmonics of ion gyro-frequencies are typically observed, and termed Stimulated Ion Bernstein Scatter SIBS. This presentation will first provide an overview of the recent NSEE experimental observations at HAARP. Both Stimulated Brillouin Scatter SBS and Stimulated Ion Bernstein Scatter SIBS observations will be discussed as well as their relationship to each other. Possible theoretical formulation in terms of parametric decay instabilities and computational modeling will be provided. Possible applications of NSEE will be pointed out including triggering diagnostics for artificial ionization layer formation, proton precipitation event diagnostics, electron temperature measurements in the heated volume and detection of heavy ion species. Finally potential for observing such SEE at the European Incoherent Scatter EISCAT facility will be discussed.

Dimensionality-varied convolutional neural network for spectral-spatial classification of hyperspectral data

NASA Astrophysics Data System (ADS)

Liu, Wanjun; Liang, Xuejian; Qu, Haicheng

2017-11-01

Hyperspectral image (HSI) classification is one of the most popular topics in remote sensing community. Traditional and deep learning-based classification methods were proposed constantly in recent years. In order to improve the classification accuracy and robustness, a dimensionality-varied convolutional neural network (DVCNN) was proposed in this paper. DVCNN was a novel deep architecture based on convolutional neural network (CNN). The input of DVCNN was a set of 3D patches selected from HSI which contained spectral-spatial joint information. In the following feature extraction process, each patch was transformed into some different 1D vectors by 3D convolution kernels, which were able to extract features from spectral-spatial data. The rest of DVCNN was about the same as general CNN and processed 2D matrix which was constituted by by all 1D data. So that the DVCNN could not only extract more accurate and rich features than CNN, but also fused spectral-spatial information to improve classification accuracy. Moreover, the robustness of network on water-absorption bands was enhanced in the process of spectral-spatial fusion by 3D convolution, and the calculation was simplified by dimensionality varied convolution. Experiments were performed on both Indian Pines and Pavia University scene datasets, and the results showed that the classification accuracy of DVCNN improved by 32.87% on Indian Pines and 19.63% on Pavia University scene than spectral-only CNN. The maximum accuracy improvement of DVCNN achievement was 13.72% compared with other state-of-the-art HSI classification methods, and the robustness of DVCNN on water-absorption bands noise was demonstrated.

Terra Cimmeria - False Color

NASA Image and Video Library

2016-10-11

The THEMIS VIS camera contains 5 filters. The data from different filters can be combined in multiple ways to create a false color image. These false color images may reveal subtle variations of the surface not easily identified in a single band image. Today's false color image shows dust devil tracks (dark blue linear feature) in Terra Cimmeria. Orbit Number: 43463 Latitude: -53.1551 Longitude: 125.069 Instrument: VIS Captured: 2011-10-01 23:55 http://photojournal.jpl.nasa.gov/catalog/PIA21009

Out-of-time-ordered measurements as a probe of quantum dynamics

NASA Astrophysics Data System (ADS)

Bordia, Pranjal; Alet, Fabien; Hosur, Pavan

2018-03-01

Probing the out-of-equilibrium dynamics of quantum matter has gained renewed interest owing to immense experimental progress in artificial quantum systems. Dynamical quantum measures such as the growth of entanglement entropy and out-of-time-ordered correlators (OTOCs) have been shown to provide great insight by exposing subtle quantum features invisible to traditional measures such as mass transport. However, measuring them in experiments requires either identical copies of the system, an ancilla qubit coupled to the whole system, or many measurements on a single copy, thereby making scalability extremely complex and hence, severely limiting their potential. Here, we introduce an alternative quantity, the out-of-time-ordered measurement (OTOM), which involves measuring a single observable on a single copy of the system, while retaining the distinctive features of the OTOCs. We show, theoretically, that OTOMs are closely related to OTOCs in a doubled system with the same quantum statistical properties as the original system. Using exact diagonalization, we numerically simulate classical mass transport, as well as quantum dynamics through computations of the OTOC, the OTOM, and the entanglement entropy in quantum spin chain models in various interesting regimes (including chaotic and many-body localized systems). Our results demonstrate that an OTOM can successfully reveal subtle aspects of quantum dynamics hidden to classical measures and, crucially, provide experimental access to them.

Comparison of two feature selection methods for the separability analysis of intertidal sediments with spectrometric datasets in the German Wadden Sea

NASA Astrophysics Data System (ADS)

Jung, Richard; Ehlers, Manfred

2016-10-01

The spectral features of intertidal sediments are all influenced by the same biophysical properties, such as water, salinity, grain size or vegetation and therefore they are hard to separate by using only multispectral sensors. This could be shown by a previous study of Jung et al. (2015). A more detailed analysis of their characteristic spectral feature has to be carried out to understand the differences and similarities. Spectrometry data (i.e., hyperspectral sensors), for instance, have the opportunity to measure the reflection of the landscape as a continuous spectral pattern for each pixel of an image built from dozen to hundreds of narrow spectral bands. This reveals a high potential to measure unique spectral responses of different ecological conditions (Hennig et al., 2007). In this context, this study uses spectrometric datasets to distinguish between 14 different sediment classes obtained from a study area in the German Wadden Sea. A new feature selection method is proposed (Jeffries-Matusita distance bases feature selection; JMDFS), which uses the Euclidean distance to eliminate the wavelengths with the most similar reflectance values in an iterative process. Subsequent to each iteration, the separation capability is estimated by the Jeffries-Matusita distance (JMD). Two classes can be separated if the JMD is greater than 1.9 and if less than four wavelengths remain, no separation can be assumed. The results of the JMDFS are compared with a state-of-the-art feature selection method called ReliefF. Both methods showed the ability to improve the separation by achieving overall accuracies greater than 82%. The accuracies are 4%-13% better than the results with all wavelengths applied. The number of remaining wavelengths is very diverse and ranges from 14 to 213 of 703. The advantage of JMDFS compared with ReliefF is clearly the processing time. ReliefF needs 30 min for one temporary result. It is necessary to repeat the process several times and to average all temporary results to achieve a final result. In this study 50 iterations were carried out, which makes four days of processing. In contrast, JMDFS needs only 30 min for a final result.

Distribution of hydrothermally altered rocks in the Reko Diq, Pakistan mineralized area based on spectral analysis of ASTER data

USGS Publications Warehouse

Rowan, L.C.; Schmidt, R.G.; Mars, J.C.

2006-01-01

The Reko Diq, Pakistan mineralized study area, approximately 10??km in diameter, is underlain by a central zone of hydrothermally altered rocks associated with Cu-Au mineralization. The surrounding country rocks are a variable mixture of unaltered volcanic rocks, fluvial deposits, and eolian quartz sand. Analysis of 15-band Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data of the study area, aided by laboratory spectral reflectance and spectral emittance measurements of field samples, shows that phyllically altered rocks are laterally extensive, and contain localized areas of argillically altered rocks. In the visible through shortwave-infrared (VNIR + SWIR) phyllically altered rocks are characterized by Al-OH absorption in ASTER band 6 because of molecular vibrations in muscovite, whereas argillically altered rocks have an absorption feature in band 5 resulting from alunite. Propylitically altered rocks form a peripheral zone and are present in scattered exposures within the main altered area. Chlorite and muscovite cause distinctive absorption features at 2.33 and 2.20????m, respectively, although less intense 2.33????m absorption is also present in image spectra of country rocks. Important complementary lithologic information was derived by analysis of the spectral emittance data in the 5 thermal-infrared (TIR) bands. Silicified rocks were not distinguished in the 9 VNIR + SWIR bands because of the lack of diagnostic spectral absorption features in quartz in this wavelength region. Quartz-bearing surficial deposits, as well as hydrothermally silicified rocks, were mapped in the TIR bands by using a band 13/band 12 ratio image, which is sensitive to the intensity of the quartz reststrahlen feature. Improved distinction between the quartzose surficial deposits and silicified bedrock was achieved by using matched-filter processing with TIR image spectra for reference. ?? 2006 Elsevier Inc. All rights reserved.

Ultraviolet spectral reflectance of carbonaceous materials

NASA Astrophysics Data System (ADS)

Applin, Daniel M.; Izawa, Matthew R. M.; Cloutis, Edward A.; Gillis-Davis, Jeffrey J.; Pitman, Karly M.; Roush, Ted L.; Hendrix, Amanda R.; Lucey, Paul G.

2018-06-01

A number of planetary spacecraft missions have carried instruments with sensors covering the ultraviolet (UV) wavelength range. However, there exists a general lack of relevant UV reflectance laboratory data to compare against these planetary surface remote sensing observations in order to make confident material identifications. To address this need, we have systematically analyzed reflectance spectra of carbonaceous materials in the 200-500 nm spectral range, and found spectral-compositional-structural relationships that suggest this wavelength region could distinguish between otherwise difficult-to-identify carbon phases. In particular (and by analogy with the infrared spectral region), large changes over short wavelength intervals in the refractive indices associated with the trigonal sp2π-π* transition of carbon can lead to Fresnel peaks and Christiansen-like features in reflectance. Previous studies extending to shorter wavelengths also show that anomalous dispersion caused by the σ-σ* transition associated with both the trigonal sp2 and tetrahedral sp3 sites causes these features below λ = 200 nm. The peak wavelength positions and shapes of π-π* and σ-σ* features contain information on sp3/sp2, structure, crystallinity, and powder grain size. A brief comparison with existing observational data indicates that the carbon fraction of the surface of Mercury is likely amorphous and submicroscopic, as is that on the surface of the martian satellites Phobos and Deimos, and possibly comet 67P/Churyumov-Gerasimenko, while further coordinated observations and laboratory experiments should refine these feature assignments and compositional hypotheses. The new laboratory diffuse reflectance data reported here provide an important new resource for interpreting UV reflectance measurements from planetary surfaces throughout the solar system, and confirm that the UV can be rich in important spectral information.

THE SPITZER ATLAS OF STELLAR SPECTRA (SASS)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ardila, David R.; Van Dyk, Schuyler D.; Makowiecki, Wojciech

2010-12-15

We present the Spitzer Atlas of Stellar Spectra, which includes 159 stellar spectra (5-32 {mu}m; R {approx} 100) taken with the Infrared Spectrograph on the Spitzer Space Telescope. This Atlas gathers representative spectra of a broad section of the Hertzsprung-Russell diagram, intended to serve as a general stellar spectral reference in the mid-infrared. It includes stars from all luminosity classes, as well as Wolf-Rayet (WR) objects. Furthermore, it includes some objects of intrinsic interest, such as blue stragglers and certain pulsating variables. All of the spectra have been uniformly reduced, and all are available online. For dwarfs and giants, themore » spectra of early-type objects are relatively featureless, characterized by the presence of hydrogen lines in A spectral types. Besides these, the most noticeable photospheric features correspond to water vapor and silicon monoxide in late-type objects and methane and ammonia features at the latest spectral types. Most supergiant spectra in the Atlas present evidence of circumstellar gas and/or dust. The sample includes five M supergiant spectra, which show strong dust excesses and in some cases polycyclic aromatic hydrocarbon features. Sequences of WR stars present the well-known pattern of lines of He I and He II, as well as forbidden lines of ionized metals. The characteristic flat-top shape of the [Ne III] line is evident even at these low spectral resolutions. Several Luminous Blue Variables and other transition stars are present in the Atlas and show very diverse spectra, dominated by circumstellar gas and dust features. We show that the [8]-[24] Spitzer colors (IRAC and MIPS) are poor predictors of spectral type for most luminosity classes.« less

The Spitzer Atlas of Stellar Spectra (SASS)

NASA Astrophysics Data System (ADS)

Ardila, David R.; Van Dyk, Schuyler D.; Makowiecki, Wojciech; Stauffer, John; Song, Inseok; Rho, Jeonghee; Fajardo-Acosta, Sergio; Hoard, D. W.; Wachter, Stefanie

2010-12-01

We present the Spitzer Atlas of Stellar Spectra, which includes 159 stellar spectra (5-32 μm R ~ 100) taken with the Infrared Spectrograph on the Spitzer Space Telescope. This Atlas gathers representative spectra of a broad section of the Hertzsprung-Russell diagram, intended to serve as a general stellar spectral reference in the mid-infrared. It includes stars from all luminosity classes, as well as Wolf-Rayet (WR) objects. Furthermore, it includes some objects of intrinsic interest, such as blue stragglers and certain pulsating variables. All of the spectra have been uniformly reduced, and all are available online. For dwarfs and giants, the spectra of early-type objects are relatively featureless, characterized by the presence of hydrogen lines in A spectral types. Besides these, the most noticeable photospheric features correspond to water vapor and silicon monoxide in late-type objects and methane and ammonia features at the latest spectral types. Most supergiant spectra in the Atlas present evidence of circumstellar gas and/or dust. The sample includes five M supergiant spectra, which show strong dust excesses and in some cases polycyclic aromatic hydrocarbon features. Sequences of WR stars present the well-known pattern of lines of He I and He II, as well as forbidden lines of ionized metals. The characteristic flat-top shape of the [Ne III] line is evident even at these low spectral resolutions. Several Luminous Blue Variables and other transition stars are present in the Atlas and show very diverse spectra, dominated by circumstellar gas and dust features. We show that the [8]-[24] Spitzer colors (IRAC and MIPS) are poor predictors of spectral type for most luminosity classes.

Berkeley SuperNova Ia Program (BSNIP): Initial Spectral Analysis

NASA Astrophysics Data System (ADS)

Silverman, Jeffrey; Kong, J.; Ganeshalingam, M.; Li, W.; Filippenko, A. V.

2011-01-01

The Berkeley SuperNova Ia Program (BSNIP) has been observing nearby (z < 0.1) Type Ia supernovae (SNe Ia) both photometrically and spectroscopically for over two decades. Using telescopes at both Lick and Keck Observatories, we have amassed an extensive collection of well-sampled optical light curves with complementary spectra covering, on average, 3400-10,000 Å. In total, we have obtained nearly 600 spectra of over 200 SNe Ia with densely sampled multi-color light curves. The initial analysis of this dataset consists of accurately and robustly measuring the strength and position of various spectral features near maximum brightness. We determine the endpoints, pseudo-continuum, expansion velocity, equivalent width, and depth of each major feature observed in our wavelength range. For objects with multiple spectra near maximum brightness we investigate how these values change with time. From these measurements we also calculate velocity gradients and various flux ratios within a given spectrum which will allow us to explore correlations between spectral and photometric observables. Some possible correlations have been studied previously, but our dataset is unique in how self-consistent the data reduction and spectral feature measurements have been, and it is a factor of a few larger than most earlier studies. We will briefly summarize the contents of the full dataset as an introduction to our initial analysis. Some of our measurements of SN Ia spectral features, along with a few initial results from those measurements, will be presented. Finally, we will comment on our current progress and planned future work. We gratefully acknowledge the financial support of NSF grant AST-0908886, the TABASGO Foundation, and the Marc J. Staley Graduate Fellowship in Astronomy.

CCD reflectance spectra of selected asteroids. I - Presentation and data analysis considerations

NASA Technical Reports Server (NTRS)

Vilas, Faith; Mcfadden, Lucy A.

1992-01-01

Narrowband reflectance spectra have been acquired which contribute to the library of asteroid data in the visible and near-IR spectral regions. The spectra support the existence of aqueous alteration products on asteroids located in the outer part of the main asteroid belt out to at least 4 AU. No evidence for features similar to the spectral features of ordinary chondrite meteorites was found in the spectra of asteroids located near the 3:1 Kirkwood Gap chaotic zone.

Evaluation and Improvement of Spectral Features for the Detection of Buried Explosive Hazards Using Forward-Looking Ground-Penetrating Radar

DTIC Science & Technology

2012-07-01

cross track direction is calculated. This is accomplished by taking a 101 point horizontal slice of pixels centered on the alarm. Then, a 101 point...Hamming window, is the 101 -length row vector of FLGPR image pixels surrounding alarm A. We then store the first 50 frequency values (excluding the...Figure 3. Illustration of spectral features in the cross track direction and the difference between actual targets and FAs. Eleven rows of 101

Thermal infrared spectral character of Hawaiian basaltic glasses

NASA Technical Reports Server (NTRS)

Crisp, Joy; Kahle, Anne B.; Abbott, Elsa A.

1990-01-01

Thermal IR reflectance spectra of exposed surfaces of Hawaiian basalt samples from Mauna Loa and Kilauea show systematic changes with age. Spectra of fresh glass collected from active lava flows showed evidence of a strong degree of disorder. After a few weeks of exposure to the laboratory environment, spectra of the top surfaces of these samples began to exhibit spectral features suggestive of ordering into silicate chainlike ansd sheetlike units. With progressive aging, features of apparent sheetlike structures became the preferred mode.

Novel Spectral Representations and Sparsity-Driven Algorithms for Shape Modeling and Analysis

NASA Astrophysics Data System (ADS)

Zhong, Ming

In this dissertation, we focus on extending classical spectral shape analysis by incorporating spectral graph wavelets and sparsity-seeking algorithms. Defined with the graph Laplacian eigenbasis, the spectral graph wavelets are localized both in the vertex domain and graph spectral domain, and thus are very effective in describing local geometry. With a rich dictionary of elementary vectors and forcing certain sparsity constraints, a real life signal can often be well approximated by a very sparse coefficient representation. The many successful applications of sparse signal representation in computer vision and image processing inspire us to explore the idea of employing sparse modeling techniques with dictionary of spectral basis to solve various shape modeling problems. Conventional spectral mesh compression uses the eigenfunctions of mesh Laplacian as shape bases, which are highly inefficient in representing local geometry. To ameliorate, we advocate an innovative approach to 3D mesh compression using spectral graph wavelets as dictionary to encode mesh geometry. The spectral graph wavelets are locally defined at individual vertices and can better capture local shape information than Laplacian eigenbasis. The multi-scale SGWs form a redundant dictionary as shape basis, so we formulate the compression of 3D shape as a sparse approximation problem that can be readily handled by greedy pursuit algorithms. Surface inpainting refers to the completion or recovery of missing shape geometry based on the shape information that is currently available. We devise a new surface inpainting algorithm founded upon the theory and techniques of sparse signal recovery. Instead of estimating the missing geometry directly, our novel method is to find this low-dimensional representation which describes the entire original shape. More specifically, we find that, for many shapes, the vertex coordinate function can be well approximated by a very sparse coefficient representation with respect to the dictionary comprising its Laplacian eigenbasis, and it is then possible to recover this sparse representation from partial measurements of the original shape. Taking advantage of the sparsity cue, we advocate a novel variational approach for surface inpainting, integrating data fidelity constraints on the shape domain with coefficient sparsity constraints on the transformed domain. Because of the powerful properties of Laplacian eigenbasis, the inpainting results of our method tend to be globally coherent with the remaining shape. Informative and discriminative feature descriptors are vital in qualitative and quantitative shape analysis for a large variety of graphics applications. We advocate novel strategies to define generalized, user-specified features on shapes. Our new region descriptors are primarily built upon the coefficients of spectral graph wavelets that are both multi-scale and multi-level in nature, consisting of both local and global information. Based on our novel spectral feature descriptor, we developed a user-specified feature detection framework and a tensor-based shape matching algorithm. Through various experiments, we demonstrate the competitive performance of our proposed methods and the great potential of spectral basis and sparsity-driven methods for shape modeling.

Extracting the frequencies of the pinna spectral notches in measured head related impulse responses

NASA Astrophysics Data System (ADS)

Raykar, Vikas C.; Duraiswami, Ramani; Yegnanarayana, B.

2005-07-01

The head related impulse response (HRIR) characterizes the auditory cues created by scattering of sound off a person's anatomy. The experimentally measured HRIR depends on several factors such as reflections from body parts (torso, shoulder, and knees), head diffraction, and reflection/diffraction effects due to the pinna. Structural models (Algazi et al., 2002; Brown and Duda, 1998) seek to establish direct relationships between the features in the HRIR and the anatomy. While there is evidence that particular features in the HRIR can be explained by anthropometry, the creation of such models from experimental data is hampered by the fact that the extraction of the features in the HRIR is not automatic. One of the prominent features observed in the HRIR, and one that has been shown to be important for elevation perception, are the deep spectral notches attributed to the pinna. In this paper we propose a method to robustly extract the frequencies of the pinna spectral notches from the measured HRIR, distinguishing them from other confounding features. The method also extracts the resonances described by Shaw (1997). The techniques are applied to the publicly available CIPIC HRIR database (Algazi et al., 2001c). The extracted notch frequencies are related to the physical dimensions and shape of the pinna.

A new multi-spectral feature level image fusion method for human interpretation

NASA Astrophysics Data System (ADS)

Leviner, Marom; Maltz, Masha

2009-03-01

Various different methods to perform multi-spectral image fusion have been suggested, mostly on the pixel level. However, the jury is still out on the benefits of a fused image compared to its source images. We present here a new multi-spectral image fusion method, multi-spectral segmentation fusion (MSSF), which uses a feature level processing paradigm. To test our method, we compared human observer performance in a three-task experiment using MSSF against two established methods: averaging and principle components analysis (PCA), and against its two source bands, visible and infrared. The three tasks that we studied were: (1) simple target detection, (2) spatial orientation, and (3) camouflaged target detection. MSSF proved superior to the other fusion methods in all three tests; MSSF also outperformed the source images in the spatial orientation and camouflaged target detection tasks. Based on these findings, current speculation about the circumstances in which multi-spectral image fusion in general and specific fusion methods in particular would be superior to using the original image sources can be further addressed.

THE VIEWING ANGLES OF BROAD ABSORPTION LINE VERSUS UNABSORBED QUASARS

DOE Office of Scientific and Technical Information (OSTI.GOV)

DiPompeo, M. A.; Brotherton, M. S.; De Breuck, C.

2012-06-10

It was recently shown that there is a significant difference in the radio spectral index distributions of broad absorption line (BAL) quasars and unabsorbed quasars, with an overabundance of BAL quasars with steeper radio spectra. This result suggests that source orientation does play into the presence or absence of BAL features. In this paper, we provide more quantitative analysis of this result based on Monte Carlo simulations. While the relationship between viewing angle and spectral index does indeed contain a lot of scatter, the spectral index distributions are different enough to overcome that intrinsic variation. Utilizing two different models ofmore » the relationship between spectral index and viewing angle, the simulations indicate that the difference in spectral index distributions can be explained by allowing BAL quasar viewing angles to extend about 10 Degree-Sign farther from the radio jet axis than non-BAL sources, though both can be seen at small angles. These results show that orientation cannot be the only factor determining whether BAL features are present, but it does play a role.« less

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.

A Developed Spectral Identification Tree for Mineral Mapping using Hyperspectral Data

NASA Astrophysics Data System (ADS)

Gan, Fuping; Wang, Runsheng; Yan, Bokun; Shang, Kun

2016-04-01

The relationship between the spectral features and the composition of minerals are the basis of mineral identification using hyperspectral data. The reflectance spectrum of minerals results from the systematic combination of several modes of interaction between electromagnetic energy and mineral particles in the form of reflection and absorption. Minerals tend to have absorbing features at specific wavelengths with a characteristic shape, which can be used as diagnostic indicators for identification. The spectral identification tree (SIT) method for mineral identification is developed in our research to map minerals accurately and applied in some typical mineral deposits in China. The SIT method is based on the diagnostic absorption features of minerals through comparing and statistically analyzing characteristic spectral data of minerals. We establish several levels of identification rules for the type, group and species of minerals using IF-THEN rule according to the spectral identification criteria so that the developed SIT can be further used to map minerals at different levels of detail from mineral type to mineral species. Identifiable minerals can be grouped into six types: Fe2+-bearing, Fe3+-bearing, Mn2+-bearing, Al-OH-bearing, Mg-OH-bearing and carbonate minerals. Each type can be further divided into several mineral groups. Each group contains several mineral species or specific minerals. A mineral spectral series, therefore, can be constructed as "type-group-species-specific mineral (mineral variety)" for mineral spectral identification. It is noted that the mineral classification is based mainly on spectral reflectance characteristics of minerals which may not be consistent with the classification in mineralogy. We applied the developed SIT method to the datasets acquired at the Eastern Tianshan Mountains of Xinjiang (HyMap data) and the Qulong district of Xizang (Hyperion data). In Xinjiang, the two major classes of Al-OH and Mg-OH minerals were mapped firstly. Then montmorillonite, kaolinite and muscovite were identified in the area of the Al-OH bearing minerals, and chlorite and epidote were identified in the area of the Mg-OH bearing minerals. Muscovite of rich Al and poor Al were further identified in the area of muscovite. In Xizang, Al-rich and Al-poor muscovite, kaolinite, chlorite and malachite were identified using SIT method. In all, the developed SIT method can further reduce the effect of other materials and focus on targeted minerals. In particular, the discrimination accuracy will be improved when the most diagnostic absorption spectral features are used in the developed SIT method.

Study and simulation results for video landmark acquisition and tracking technology (Vilat-2)

NASA Technical Reports Server (NTRS)

Lowrie, J. W.; Tietz, J. C.; Thomas, H. M.; Gremban, K. D.; Hughes, C.; Chang, C. Y.

1983-01-01

The results of several investigations and hardware developments which supported new technology for Earth feature recognition and classification are described. Data analysis techniques and procedures were developed for processing the Feature Identification and Location Experiment (FILE) data. This experiment was flown in November 1981, on the second Shuttle flight and a second instrument, designed for aircraft flights, was flown over the United States in 1981. Ground tests were performed to provide the basis for designing a more advanced version (four spectral bands) of the FILE which would be capable of classifying clouds and snow (and possibly ice) as distinct features, in addition to the features classified in the Shuttle experiment (two spectral bands). The Shuttle instrument classifies water, bare land, vegetation, and clouds/snow/ice (grouped).

USGS Digital Spectral Library splib05a

USGS Publications Warehouse

Clark, Roger N.; Swayze, Gregg A.; Wise, Richard K.; Livo, Eric; Hoefen, Todd M.; Kokaly, Raymond F.; Sutley, Steve J.

2003-01-01

We have assembled a digital reflectance spectral library of spectra that covers wavelengths from the ultraviolet to near-infrared along with sample documentation. The library includes samples of minerals, rocks, soils, physically constructed as well as mathematically computed mixtures, vegetation, microorganisms, and man-made materials. The samples and spectra collected were assembled for the purpose of using spectral features for the remote detection of these and similar materials.

Cloud classification in polar regions using AVHRR textural and spectral signatures

NASA Technical Reports Server (NTRS)

Welch, R. M.; Sengupta, S. K.; Weger, R. C.; Christopher, S. A.; Kuo, K. S.; Carsey, F. D.

1990-01-01

Arctic clouds and ice-covered surfaces are classified on the basis of textural and spectral features obtained with AVHRR 1.1-km spatial resolution imagery over the Beaufort Sea during May-October, 1989. Scenes were acquired about every 5 days, for a total of 38 cases. A list comprising 20 arctic-surface and cloud classes is compiled using spectral measures defined by Garand (1988).

The Copernicus ultraviolet spectral atlas of Vega

NASA Technical Reports Server (NTRS)

Rogerson, John B., Jr.

1989-01-01

A near-ultraviolet spectral atlas for the A0 V star Alpha Lyr (Vega) has been prepared from data taken by the Princeton spectrometer aboard the Copernicus satellite. The spectral region from 2000 to 3187 A has been scanned with a resolution of 0.1 A. The atlas is presented in graphs with a normalized continuum, and an identification table for the absorption features has been prepared.

Indirect searches of dark matter via polynomial spectral features

DOE Office of Scientific and Technical Information (OSTI.GOV)

Garcia-Cely, Camilo; Heeck, Julian

2016-08-11

We derive the spectra arising from non-relativistic dark matter annihilations or decays into intermediary particles with arbitrary spin, which subsequently produce neutrinos or photons via two-body decays. Our approach is model independent and predicts spectral features restricted to a kinematic box. The overall shape within that box is a polynomial determined by the polarization of the decaying particle. We illustrate our findings with two examples. First, with the neutrino spectra arising from dark matter annihilations into the massive Standard Model gauge bosons. Second, with the gamma-ray and neutrino spectra generated by dark matter annihilations into hypothetical massive spin-2 particles. Ourmore » results are in particular applicable to the 750 GeV diphoton excess observed at the LHC if interpreted as a spin-0 or spin-2 particle coupled to dark matter. We also derive limits on the dark matter annihilation cross section into this resonance from the non-observation of the associated gamma-ray spectral features by the H.E.S.S. telescope.« less

Spectrally queued feature selection for robotic visual odometery

NASA Astrophysics Data System (ADS)

Pirozzo, David M.; Frederick, Philip A.; Hunt, Shawn; Theisen, Bernard; Del Rose, Mike

2011-01-01

Over the last two decades, research in Unmanned Vehicles (UV) has rapidly progressed and become more influenced by the field of biological sciences. Researchers have been investigating mechanical aspects of varying species to improve UV air and ground intrinsic mobility, they have been exploring the computational aspects of the brain for the development of pattern recognition and decision algorithms and they have been exploring perception capabilities of numerous animals and insects. This paper describes a 3 month exploratory applied research effort performed at the US ARMY Research, Development and Engineering Command's (RDECOM) Tank Automotive Research, Development and Engineering Center (TARDEC) in the area of biologically inspired spectrally augmented feature selection for robotic visual odometry. The motivation for this applied research was to develop a feasibility analysis on multi-spectrally queued feature selection, with improved temporal stability, for the purposes of visual odometry. The intended application is future semi-autonomous Unmanned Ground Vehicle (UGV) control as the richness of data sets required to enable human like behavior in these systems has yet to be defined.

A comparison of three feature selection methods for object-based classification of sub-decimeter resolution UltraCam-L imagery

USDA-ARS?s Scientific Manuscript database

The availability of numerous spectral, spatial, and contextual features with object-based image analysis (OBIA) renders the selection of optimal features a time consuming and subjective process. While several feature election methods have been used in conjunction with OBIA, a robust comparison of th...

Discriminating Induced-Microearthquakes Using New Seismic Features

NASA Astrophysics Data System (ADS)

Mousavi, S. M.; Horton, S.

2016-12-01

We studied characteristics of induced-microearthquakes on the basis of the waveforms recorded on a limited number of surface receivers using machine-learning techniques. Forty features in the time, frequency, and time-frequency domains were measured on each waveform, and several techniques such as correlation-based feature selection, Artificial Neural Networks (ANNs), Logistic Regression (LR) and X-mean were used as research tools to explore the relationship between these seismic features and source parameters. The results show that spectral features have the highest correlation to source depth. Two new measurements developed as seismic features for this study, spectral centroids and 2D cross-correlations in the time-frequency domain, performed better than the common seismic measurements. These features can be used by machine learning techniques for efficient automatic classification of low energy signals recorded at one or more seismic stations. We applied the technique to 440 microearthquakes-1.7Reference: Mousavi, S.M., S.P. Horton, C. A. Langston, B. Samei, (2016) Seismic features and automatic discrimination of deep and shallow induced-microearthquakes using neural network and logistic regression, Geophys. J. Int. doi: 10.1093/gji/ggw258.

Intercomparison of Carbonate Deposits on Mars: VNIR Spectral Character and Geologic Context

NASA Astrophysics Data System (ADS)

Wiseman, S.; Mustard, J. F.; Ehlmann, B. L.

2012-12-01

Carbonate-bearing deposits were identified on Mars at multiple locations using CRISM VNIR spectral data [1,2,3,4,5]. Carbonates exhibit distinctive C-O related absorption features near 2300, 2500, 3400 and 3900nm that can be used to identify specific carbonate phases (e.g., Mg-carbonates have band minima at 2300/2500nm and Fe-carbonates have minima at 2330/2530nm [6]). The features at 2300 and 2500nm are the focus of most CRISM analyses because this part of the spectral range is well calibrated, lacks strong contributions from thermal emission, and is not impacted by strong water-related absorptions near 3000nm (e.g., in Fe/Mg phyllosilicates). However, multiple other phases also exhibit features near 2300 and 2500nm.For carbonates, the depth of the 2500nm feature is stronger than at 2300nm as opposed to most Fe/Mg phyllosilicates. Mixing of the carbonate with other phases in CRISM pixels impacts the band centers and strengths of the 2300 and 2500nm features and therefore complicates identification of the carbonate phase(s) responsible for observed CRISM spectral features. In this study we analyze CRISM data fully corrected for the atmosphere using DISORT radiative transfer modeling [7,8] to evaluate CRISM spectra of multiple carbonate-bearing deposits. Rigorous intercomparison of CRISM spectra extracted from different images is affected by variable aerosol, CO2 and water vapor features left by the standard volcano scan empirical atmospheric correction [9]. While residual gas absorptions are commonly suppressed by ratioing, the appearance of spectral features in ratio spectra is impacted by spectral features in the dominator spectrum compromising detailed assessments of ratio spectra derived from different images. Atmospheric correction is particularly important for interpreting carbonate deposits because the 2500nm carbonate feature overlaps with atmospheric water vapor absorptions. In Nili Fossae, carbonates occur in association with olivine, smectite, serpentine [1,10], and possibly talc [11].These carbonates are hypothesized to have formed via alteration of olivine and/or serpentine under surface or low temperature hydrothermal conditions [1,11,12] Laboratory spectra of Mg carbonates (magnesite/hydromagnesite) are the closest matches to the Nili Fossae carbonates [1]. CRISM spectra of carbonates in and around Huygens basin are interpreted to be Fe and/or Ca carbonates [3], similar to carbonate spectra described by [2]. However, the CRISM carbonate-bearing spectra are mixed with Fe/Mg phyllosilicates [1,2,3], making a one to one comparison among Martian and laboratory carbonate spectra challenging. [1] Ehlmann et al. (2008), Sci., 322, 1828-1831, [2] Michalski and. Niles (2010), Nat. Geo., 3, 751-55, [3] Wray et al. (2011), LPSC, #2635, [4] Bishop et al. (2012), LPSC, #2330, [5] Carter and Poulet (2012), Icarus, [6] Gaffey (1987), JGR, 92, 1429-1440, [7] Stamnes et al. (1999), Appl. Opt., 27, 2502-2509, [8] Wolff et al. (2009), JGR, 11, [9] Wiseman et al., 2010, LPSC , #2461, [10] Ehlmann et al. (2010), GRL, 37, [11] Brown et al. (2010), EPSL, 297, 174-182. [12] Ehlmann et al. (2009), JGR, 114.

Linking Spectral Features with Composition, Crystallinity, and Roughness Properties of Silica and Implications for Candidate Hydrothermal Systems on Mars

NASA Astrophysics Data System (ADS)

Hamilton, V. E.; McDowell, M. L.; Berger, J. A.; Cady, S. L.; Knauth, L. P.

2011-12-01

We have collected visible to near infrared reflectance (VNIR, ~0.4 - 2.5 um), thermal infrared emissivity (TIR, ~5 - 45 um), SEM, XRD, surface roughness, and petrographic data for 18 silica samples. These rocks (e.g., replacement chert, geyserite, opal-A/-CT) represent a variety of geologic formation environments, including hydrothermal, and have XRD-determined crystallinities ranging from <1 to >10 according to the quartz crystallinity index. Our findings are relevant to the interpretation of orbital and in situ spectral observations of crystalline or amorphous silica on the Martian surface, some of which may have formed in hydrothermal systems. Almost all of our samples' VNIR spectra contain discernible bands. The most common features are related to hydration (H2O and/or OH) of silica (e.g., at ~1.4, 1.9, and 2.2 um). The visibility and strength of these bands is not always constant between spectra from different areas of a sample. Other features include those of carbonate, phyllosilicate, and iron oxide impurities. All of our amorphous silica samples have hydration features in the VNIR, but we note that the absorptions around ~2.2 um can be very weak in amorphous samples relative to features at other wavelengths and relative to ~2.2-um features observed in Martian data, suggesting that some amorphous silica on Mars could go undetected. Deposits containing significant anhydrous, crystalline silica (chert) may be assumed to lack features in the VNIR, but many of our cherts have spectral features and could be misidentified as materials dominated by what is a minor contaminant. Thermal infrared spectra of chert and opaline silica differ from each other as a result of the loss of long-range Si-O order in increasingly amorphous samples. Our samples display a clear trend in TIR band shapes where features attributable to crystalline quartz and amorphous silica are blended in samples with intermediate crystallinities. Most diagnostic TIR spectral features observable in laboratory data typically are recognizable in hyperspectral remote sensing data. These features are more difficult to distinguish (or are not included) at multispectral resolutions, but in nearly all uncontaminated samples, the positions of Si-O emissivity minima shift towards longer wavelengths with decreasing crystallinity. Contaminating phases with strong VNIR spectral features are observed in some of the TIR spectra but have a negligible effect in others, suggesting that TIR spectroscopy helps constrain the abundances of these phases. In addition to compositional and crystallinity information, our laboratory data demonstrate that TIR spectra can be used to deduce important information on silica phases' texture and orientation. If used in combination, VNIR and TIR spectroscopy can detect and characterize silica phases, allowing us to estimate conditions of silica formation, e.g., high- or low-temperature aqueous systems.

The Colors of Tethys I

NASA Image and Video Library

2015-07-29

This enhanced-color mosaic of Saturn's icy moon Tethys shows a range of features on the moon's trailing hemisphere. Tethys is tidally locked to Saturn, so the trailing hemisphere is the side of the moon that always faces opposite its direction of motion as it orbits the planet. Images taken using clear, green, infrared and ultraviolet spectral filters were combined to create the view, which highlights subtle color differences across Tethys' surface at wavelengths not visible to human eyes. The moon's surface is fairly uniform in natural color. The color of the surface changes conspicuously across the disk, from yellowish hues to nearly white. These broad color changes are affected by a number of external processes. First, Saturn's diffuse E-ring preferentially bombards Tethys' leading hemisphere, toward the right side of this image, with ice bright ice grains. At the same time, charged particles from Saturn's radiation belt bombard the surface on the trailing side, causing color changes due to chemical alteration of the materials there. The albedo -- a measure of the surface's reflectivity -- drops by 10 to 15 percent from the moon's leading side to the trailing side. Similar global color patterns exist on other Saturnian moons. On a much smaller scale, enigmatic, arc-shaped, reddish streaks also are faintly visible across the heavily-cratered surface, particularly if one enhances color saturation in the image (see PIA19637 for a close-up view of these features). The origin of this localized color contrast is not yet understood. Mountains on the floor of the 280 mile- (450 kilometer-) wide Odysseus impact basin are visible at upper right, around the two o'clock position. This mosaic is an orthographic projection constructed from 52 Cassini images obtained on April 11, 2015 with the Cassini spacecraft narrow-angle camera. Resolution is about 1,000 feet (300 meters) per pixel. The images were obtained at a distance of approximately 33,000 miles (53,000 kilometers) from Tethys. http://photojournal.jpl.nasa.gov/catalog/PIA19636

Mineralogical Composition and Potential Dust Source of Playas in the Western U.S. and Australia as Remotely Identified Through Imaging Spectroscopy.

NASA Astrophysics Data System (ADS)

Raming, L. W.; Farrand, W. H.; Bowen, B.

2015-12-01

Playas are significant dust sources and as a result are potentially hazardous to human health. The composition of the dust is a function of the mineralogical content of the playa and associated brines. Playas are found in arid climates globally, however they are challenging to map geologically as they are often hard to access, have subtle variations in mineralogy, and are topographically featureless. This study uses remote sensing in the form of imaging spectroscopy to map the mineralogical composition of five playas from different geologic settings: Railroad Valley Playa, Nevada, USA; Bonneville Salt Flats, Utah, USA; White Sands National Monument, New Mexico, USA; Lake Brown, Western Australia, Australia; and Lake Tyrrell, Victoria, Australia.Multiple spectrometers were used for this study; these include the multispectral sensor ASTER, and the hyperspectral sensors AVIRIS, HICO, and HyMap. All scenes were processed in ENVI and corrected to at surface reflectance using FLAASH, QUAC or Empirical Line methods. Minerals were identified through a standard end-member extraction approach and mapped using multi-range spectral feature fitting and other methods. Additionally, remote data are combined with in-situ field-based spectra and sample-based laboratory spectra.Initial results suggest various and differing mineralogy between playas. The most abundant mineralogy includes clay minerals such as illite and montmorillonite and evaporites such as gypsum. Additionally there has been identification of Fe absorption bands in the visible / near infrared at White Sands National Monument, and Lake Brown and Lake Tyrell, suggesting the presence of iron bearing minerals. Further research will provide a more comprehensive list of minerals identified by absorption features as related to specific sensors. Collectively, these analyses will be used characterize overall patterns in playa surface mineralogy and to evaluate the parameters that influence playa dust source composition.

Morphological similarity and ecological overlap in two rotifer species.

PubMed

Gabaldón, Carmen; Montero-Pau, Javier; Serra, Manuel; Carmona, María José

2013-01-01

Co-occurrence of cryptic species raises theoretically relevant questions regarding their coexistence and ecological similarity. Given their great morphological similitude and close phylogenetic relationship (i.e., niche retention), these species will have similar ecological requirements and are expected to have strong competitive interactions. This raises the problem of finding the mechanisms that may explain the coexistence of cryptic species and challenges the conventional view of coexistence based on niche differentiation. The cryptic species complex of the rotifer Brachionus plicatilis is an excellent model to study these questions and to test hypotheses regarding ecological differentiation. Rotifer species within this complex are filtering zooplankters commonly found inhabiting the same ponds across the Iberian Peninsula and exhibit an extremely similar morphology-some of them being even virtually identical. Here, we explore whether subtle differences in body size and morphology translate into ecological differentiation by comparing two extremely morphologically similar species belonging to this complex: B. plicatilis and B. manjavacas. We focus on three key ecological features related to body size: (1) functional response, expressed by clearance rates; (2) tolerance to starvation, measured by growth and reproduction; and (3) vulnerability to copepod predation, measured by the number of preyed upon neonates. No major differences between B. plicatilis and B. manjavacas were found in the response to these features. Our results demonstrate the existence of a substantial niche overlap, suggesting that the subtle size differences between these two cryptic species are not sufficient to explain their coexistence. This lack of evidence for ecological differentiation in the studied biotic niche features is in agreement with the phylogenetic limiting similarity hypothesis but requires a mechanistic explanation of the coexistence of these species not based on differentiation related to biotic niche axes.

Systemic lupus erythematosus-associated neutrophilic dermatosis--an underrecognized neutrophilic dermatosis in patients with systemic lupus erythematosus.

PubMed

Larson, Allison R; Granter, Scott R

2014-03-01

Neutrophilic dermatoses are an uncommon manifestation of lupus. We describe the clinical and histopathologic features of 14 patients with systemic lupus erythematosus (SLE) and neutrophilic dermatoses, 2 of whom had no prior history of SLE. Thirteen patients were female, ranging in age from 27 to 62 years (mean age, 42.8 years). One patient was a 20-year-old man. Most lesions were described as erythematous papules and plaques and showed annular morphology in 6 patients and a photodistribution in 2 patients. Histopathologic examination in all cases showed an interstitial neutrophilic infiltrate with leukocytoclasis that ranged from sparse in 5 cases and moderate to dense in 9 cases. With one exception, those cases with moderate to dense infiltrates resembled Sweet's syndrome at scanning magnification. Two cases resembled bullous SLE, and 1 case showed overlapping features of bullous SLE and Sweet's syndrome. Interface changes were seen in 8 patients, which were subtle and vacuolar in 7. One case was associated with a florid interface tissue reaction. Dermal mucin was seen in 4 cases and was a prominent feature in only one of these. One case showed a minute discrete focus resembling palisaded neutrophilic and granulomatous dermatitis. It is important to consider SLE-associated neutrophilic dermatosis in the differential diagnosis of neutrophilic tissue reactions particularly because some patients will have no prior history of lupus. It is also important to be aware of the broad histologic spectrum that may be encountered in SLE-associated neutrophilic dermatosis, ranging from subtle paucicellular lesions to florid Sweet's-like lesions associated with a dense neutrophilic infiltrate. Copyright © 2014 Elsevier Inc. All rights reserved.

Neural Measures Reveal Implicit Learning during Language Processing.

PubMed

Batterink, Laura J; Cheng, Larry Y; Paller, Ken A

2016-10-01

Language input is highly variable; phonological, lexical, and syntactic features vary systematically across different speakers, geographic regions, and social contexts. Previous evidence shows that language users are sensitive to these contextual changes and that they can rapidly adapt to local regularities. For example, listeners quickly adjust to accented speech, facilitating comprehension. It has been proposed that this type of adaptation is a form of implicit learning. This study examined a similar type of adaptation, syntactic adaptation, to address two issues: (1) whether language comprehenders are sensitive to a subtle probabilistic contingency between an extraneous feature (font color) and syntactic structure and (2) whether this sensitivity should be attributed to implicit learning. Participants read a large set of sentences, 40% of which were garden-path sentences containing temporary syntactic ambiguities. Critically, but unbeknownst to participants, font color probabilistically predicted the presence of a garden-path structure, with 75% of garden-path sentences (and 25% of normative sentences) appearing in a given font color. ERPs were recorded during sentence processing. Almost all participants indicated no conscious awareness of the relationship between font color and sentence structure. Nonetheless, after sufficient time to learn this relationship, ERPs time-locked to the point of syntactic ambiguity resolution in garden-path sentences differed significantly as a function of font color. End-of-sentence grammaticality judgments were also influenced by font color, suggesting that a match between font color and sentence structure increased processing fluency. Overall, these findings indicate that participants can implicitly detect subtle co-occurrences between physical features of sentences and abstract, syntactic properties, supporting the notion that implicit learning mechanisms are generally operative during online language processing.

Morphological Similarity and Ecological Overlap in Two Rotifer Species

PubMed Central

Gabaldón, Carmen; Montero-Pau, Javier; Serra, Manuel; Carmona, María José

2013-01-01

Co-occurrence of cryptic species raises theoretically relevant questions regarding their coexistence and ecological similarity. Given their great morphological similitude and close phylogenetic relationship (i.e., niche retention), these species will have similar ecological requirements and are expected to have strong competitive interactions. This raises the problem of finding the mechanisms that may explain the coexistence of cryptic species and challenges the conventional view of coexistence based on niche differentiation. The cryptic species complex of the rotifer Brachionus plicatilis is an excellent model to study these questions and to test hypotheses regarding ecological differentiation. Rotifer species within this complex are filtering zooplankters commonly found inhabiting the same ponds across the Iberian Peninsula and exhibit an extremely similar morphology—some of them being even virtually identical. Here, we explore whether subtle differences in body size and morphology translate into ecological differentiation by comparing two extremely morphologically similar species belonging to this complex: B. plicatilis and B. manjavacas. We focus on three key ecological features related to body size: (1) functional response, expressed by clearance rates; (2) tolerance to starvation, measured by growth and reproduction; and (3) vulnerability to copepod predation, measured by the number of preyed upon neonates. No major differences between B. plicatilis and B. manjavacas were found in the response to these features. Our results demonstrate the existence of a substantial niche overlap, suggesting that the subtle size differences between these two cryptic species are not sufficient to explain their coexistence. This lack of evidence for ecological differentiation in the studied biotic niche features is in agreement with the phylogenetic limiting similarity hypothesis but requires a mechanistic explanation of the coexistence of these species not based on differentiation related to biotic niche axes. PMID:23451154

Use of field reflectance data for crop mapping using airborne hyperspectral image

NASA Astrophysics Data System (ADS)

Nidamanuri, Rama Rao; Zbell, Bernd

2011-09-01

Recent developments in hyperspectral remote sensing technologies enable acquisition of image with high spectral resolution, which is typical to the laboratory or in situ reflectance measurements. There has been an increasing interest in the utilization of in situ reference reflectance spectra for rapid and repeated mapping of various surface features. Here we examined the prospect of classifying airborne hyperspectral image using field reflectance spectra as the training data for crop mapping. Canopy level field reflectance measurements of some important agricultural crops, i.e. alfalfa, winter barley, winter rape, winter rye, and winter wheat collected during four consecutive growing seasons are used for the classification of a HyMAP image acquired for a separate location by (1) mixture tuned matched filtering (MTMF), (2) spectral feature fitting (SFF), and (3) spectral angle mapper (SAM) methods. In order to answer a general research question "what is the prospect of using independent reference reflectance spectra for image classification", while focussing on the crop classification, the results indicate distinct aspects. On the one hand, field reflectance spectra of winter rape and alfalfa demonstrate excellent crop discrimination and spectral matching with the image across the growing seasons. On the other hand, significant spectral confusion detected among the winter barley, winter rye, and winter wheat rule out the possibility of existence of a meaningful spectral matching between field reflectance spectra and image. While supporting the current notion of "non-existence of characteristic reflectance spectral signatures for vegetation", results indicate that there exist some crops whose spectral signatures are similar to characteristic spectral signatures with possibility of using them in image classification.

Processing of spectral and amplitude envelope of animal vocalizations in the human auditory cortex.

PubMed

Altmann, Christian F; Gomes de Oliveira Júnior, Cícero; Heinemann, Linda; Kaiser, Jochen

2010-08-01

In daily life, we usually identify sounds effortlessly and efficiently. Two properties are particularly salient and of importance for sound identification: the sound's overall spectral envelope and its temporal amplitude envelope. In this study, we aimed at investigating the representation of these two features in the human auditory cortex by using a functional magnetic resonance imaging adaptation paradigm. We presented pairs of sound stimuli derived from animal vocalizations that preserved the time-averaged frequency spectrum of the animal vocalizations and the amplitude envelope. We presented the pairs in four different conditions: (a) pairs with the same amplitude envelope and mean spectral envelope, (b) same amplitude envelope, but different mean spectral envelope, (c) different amplitude envelope, but same mean spectral envelope and (d) both different amplitude envelope and mean spectral envelope. We found fMRI adaptation effects for both the mean spectral envelope and the amplitude envelope of animal vocalizations in overlapping cortical areas in the bilateral superior temporal gyrus posterior to Heschl's gyrus. Areas sensitive to the amplitude envelope extended further anteriorly along the lateral superior temporal gyrus in the left hemisphere, while areas sensitive to the spectral envelope extended further anteriorly along the right lateral superior temporal gyrus. Posterior tonotopic areas within the left superior temporal lobe displayed sensitivity for the mean spectrum. Our findings suggest involvement of primary auditory areas in the representation of spectral cues and encoding of general spectro-temporal features of natural sounds in non-primary posterior and lateral superior temporal cortex. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Characterization of Cryptosporidium parvum by Matrix-Assisted Laser Desorption Ionization–Time of Flight Mass Spectrometry

PubMed Central

Magnuson, Matthew L.; Owens, James H.; Kelty, Catherine A.

2000-01-01

Matrix-assisted laser desorption ionization–time of flight mass spectrometry (MALDI-TOF MS) was used to investigate whole and freeze-thawed Cryptosporidium parvum oocysts. Whole oocysts revealed some mass spectral features. Reproducible patterns of spectral markers and increased sensitivity were obtained after the oocysts were lysed with a freeze-thaw procedure. Spectral-marker patterns for C. parvum were distinguishable from those obtained for Cryptosporidium muris. One spectral marker appears specific for the genus, while others appear specific at the species level. Three different C. parvum lots were investigated, and similar spectral markers were observed in each. Disinfection of the oocysts reduced and/or eliminated the patterns of spectral markers. PMID:11055915

Demonstration of spectral correlation control in a source of polarization-entangled photon pairs at telecom wavelength.

PubMed

Lutz, Thomas; Kolenderski, Piotr; Jennewein, Thomas

2014-03-15

Spectrally correlated photon pairs can be used to improve the performance of long-range fiber-based quantum communication protocols. We present a source based on spontaneous parametric downconversion, which allows one to control spectral correlations within the entangled photon pair without spectral filtering by changing the pump-pulse duration or the characteristics of the coupled spatial modes. The spectral correlations and polarization entanglement are characterized. We find that the generated photon pairs can feature both positive spectral correlations, decorrelation, or negative correlations at the same time as polarization entanglement with a high fidelity of 0.97 (no background subtraction) with the expected Bell state.

A TALE OF THREE MYSTERIOUS SPECTRAL FEATURES IN CARBON-RICH EVOLVED STARS: THE 21 μm, 30 μm, AND “UNIDENTIFIED INFRARED” EMISSION FEATURES

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mishra, Ajay; Li, Aigen; Jiang, B. W., E-mail: amishra@mail.missouri.edu, E-mail: lia@missouri.edu, E-mail: bjiang@bnu.edu.cn

2015-03-20

The mysterious “21 μm” emission feature seen almost exclusively in the short-lived protoplanetary nebula (PPN) phase of stellar evolution remains unidentified since its discovery two decades ago. This feature is always accompanied by the equally mysterious, unidentified “30 μm” feature and the so-called “unidentified infrared” (UIR) features at 3.3, 6.2, 7.7, 8.6, and 11.3 μm which are generally attributed to polycyclic aromatic hydrocarbon (PAH) molecules. The 30 μm feature is commonly observed in all stages of stellar evolution from the asymptotic giant branch through PPN to the planetary nebula phase. We explore the interrelations among the mysterious 21, 30 μm,more » and UIR features of the 21 μm sources. We derive the fluxes emitted in the observed UIR, 21, and 30 μm features from published Infrared Space Observatory or Spitzer/IRS spectra. We find that none of these spectral features correlate with each other. This argues against a common carrier (e.g., thiourea) for both the 21 μm feature and the 30 μm feature. This also does not support large PAH clusters as a possible carrier for the 21 μm feature.« less

Long-term follow-up of two patients with oligocone trichromacy.

PubMed

Smirnov, Vasily; Drumare, Isabelle; Bouacha, Ikram; Puech, Bernard; Defoort-Dhellemmes, Sabine

2015-10-01

Oligocone trichromacy (OT) is an uncommon cone dysfunction disorder, the mechanism of which remains poorly understood. OT has been thought to be non-progressive, but its long-term visual outcome has been seldom reported in the literature. Our aim was to present two OT patients followed at our institution over 18 years. Complete ocular examination, color vision, visual fields, and full-field electroretinography (ERG) were performed at initial presentation and follow-up. Spectral-domain optical coherence tomography (OCT) was performed during follow-up when available at our institution. Initial ocular examination showed satisfactory visual acuities with normal fundus examination and near-to-normal color vision. However, computerized perimetry demonstrated a ring-shaped scotoma around fixation, and ERG showed a profound cone dysfunction. The discrepancy between preserved color vision and profound cone dysfunction leads to the diagnosis of OT. Subsequent follow-ups over 18 years showed subtle degradation of visual acuities along with progression of the myopia in both patients and slight worsening of color vision in one patient. Initial OCT revealed a focal interruption of the ellipsoid line along with decreased thickness of the perifoveal macula. Subsequent OCT imaging performed 2 years later did not show any macular changes. Although OT is known to be a non-progressive cone dysfunction, our results suggest that subtle degradation of the visual function might happen over time.

Responses of Middle-Frequency Modulations in Vocal Fundamental Frequency to Different Vocal Intensities and Auditory Feedback.

PubMed

Lee, Shao-Hsuan; Fang, Tuan-Jen; Yu, Jen-Fang; Lee, Guo-She

2017-09-01

Auditory feedback can make reflexive responses on sustained vocalizations. Among them, the middle-frequency power of F0 (MFP) may provide a sensitive index to access the subtle changes in different auditory feedback conditions. Phonatory airflow temperature was obtained from 20 healthy adults at two vocal intensity ranges under four auditory feedback conditions: (1) natural auditory feedback (NO); (2) binaural speech noise masking (SN); (3) bone-conducted feedback of self-generated voice (BAF); and (4) SN and BAF simultaneously. The modulations of F0 in low-frequency (0.2 Hz-3 Hz), middle-frequency (3 Hz-8 Hz), and high-frequency (8 Hz-25 Hz) bands were acquired using power spectral analysis of F0. Acoustic and aerodynamic analyses were used to acquire vocal intensity, maximum phonation time (MPT), phonatory airflow, and MFP-based vocal efficiency (MBVE). SN and high vocal intensity decreased MFP and raised MBVE and MPT significantly. BAF showed no effect on MFP but significantly lowered MBVE. Moreover, BAF significantly increased the perception of voice feedback and the sensation of vocal effort. Altered auditory feedback significantly changed the middle-frequency modulations of F0. MFP and MBVE could well detect these subtle responses of audio-vocal feedback. Copyright © 2017 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

Hyperspectral imaging of endogenous fluorescent metabolic molecules to identify pain states in central nervous system tissue

NASA Astrophysics Data System (ADS)

Staikopoulos, Vasiliki; Gosnell, Martin E.; Anwer, Ayad G.; Mustafa, Sanam; Hutchinson, Mark R.; Goldys, Ewa M.

2016-12-01

Fluorescence-based bio-imaging methods have been extensively used to identify molecular changes occurring in biological samples in various pathological adaptations. Auto-fluorescence generated by endogenous fluorescent molecules within these samples can interfere with signal to background noise making positive antibody based fluorescent staining difficult to resolve. Hyperspectral imaging uses spectral and spatial imaging information for target detection and classification, and can be used to resolve changes in endogenous fluorescent molecules such as flavins, bound and free NADH and retinoids that are involved in cell metabolism. Hyperspectral auto-fluorescence imaging of spinal cord slices was used in this study to detect metabolic differences within pain processing regions of non-pain versus sciatic chronic constriction injury (CCI) animals, an established animal model of peripheral neuropathy. By using an endogenous source of contrast, subtle metabolic variations were detected between tissue samples, making it possible to distinguish between animals from non-injured and injured groups. Tissue maps of native fluorophores, flavins, bound and free NADH and retinoids unveiled subtle metabolic signatures and helped uncover significant tissue regions with compromised mitochondrial function. Taken together, our results demonstrate that hyperspectral imaging provides a new non-invasive method to investigate central changes of peripheral neuropathic injury and other neurodegenerative disease models, and paves the way for novel cellular characterisation in health, disease and during treatment, with proper account of intrinsic cellular heterogeneity.

Simulation of the hyperspectral data from multispectral data using Python programming language

NASA Astrophysics Data System (ADS)

Tiwari, Varun; Kumar, Vinay; Pandey, Kamal; Ranade, Rigved; Agarwal, Shefali

2016-04-01

Multispectral remote sensing (MRS) sensors have proved their potential in acquiring and retrieving information of Land Use Land (LULC) Cover features in the past few decades. These MRS sensor generally acquire data within limited broad spectral bands i.e. ranging from 3 to 10 number of bands. The limited number of bands and broad spectral bandwidth in MRS sensors becomes a limitation in detailed LULC studies as it is not capable of distinguishing spectrally similar LULC features. On the counterpart, fascinating detailed information available in hyperspectral (HRS) data is spectrally over determined and able to distinguish spectrally similar material of the earth surface. But presently the availability of HRS sensors is limited. This is because of the requirement of sensitive detectors and large storage capability, which makes the acquisition and processing cumbersome and exorbitant. So, there arises a need to utilize the available MRS data for detailed LULC studies. Spectral reconstruction approach is one of the technique used for simulating hyperspectral data from available multispectral data. In the present study, spectral reconstruction approach is utilized for the simulation of hyperspectral data using EO-1 ALI multispectral data. The technique is implemented using python programming language which is open source in nature and possess support for advanced imaging processing libraries and utilities. Over all 70 bands have been simulated and validated using visual interpretation, statistical and classification approach.

Laboratory Spectroscopy of Astrophysically-Relevant Materials: Developing Dust as a Diagnostic

NASA Technical Reports Server (NTRS)

Rinehart, Stephen A.

2010-01-01

Over forty years ago, observations in the new field of infrared astronomy showed a broad spectral feature at 10 microns; the feature was quickly associated with the presence of silicate-rich dust. Since that time, improvements in infrared astronomy have led to the discovery of a plethora of additional spectral features attributable to dust. By combining these observations with spectroscopic data acquired in the laboratory, astronomers have a diagnostic tool that can be used to explore underlying astronomical phenomena. As the laboratory data improves, so does our ability to interpret the astronomical observations. Here, we discuss some recent progress in laboratory spectroscopy and attempt to identify future research directions.

Color heterogeneity of the surface of Phobos - Relationships to geologic features and comparison to meteorite analogs

NASA Technical Reports Server (NTRS)

Murchie, Scott L.; Britt, Daniel T.; Head, James W.; Pratt, Stephen F.; Fisher, Paul C.

1991-01-01

Color ratio images created from multispectral observations of Phobos are analyzed in order to characterize the spectral properties of Phobos' surface, to assess their spatial distributions and relationships with geologic features, and to compare Phobos' surface materials with possible meteorite analogs. Data calibration and processing is briefly discussed, and the observed spectral properties of Phobos and their lateral variations are examined. Attention is then given to the color properties of different types of impact craters, the origin of lateral variations in surface color, the relation between the spatial distribution of color properties and independently identifiable geologic features, and the relevance of color variation spatial distribution to the origin of the grooves.

Multivariable passive RFID vapor sensors: roll-to-roll fabrication on a flexible substrate.

PubMed

Potyrailo, Radislav A; Burns, Andrew; Surman, Cheryl; Lee, D J; McGinniss, Edward

2012-06-21

We demonstrate roll-to-roll (R2R) fabrication of highly selective, battery-free radio frequency identification (RFID) sensors on a flexible polyethylene terephthalate (PET) polymeric substrate. Selectivity of our developed RFID sensors is provided by measurements of their resonance impedance spectra, followed by the multivariate analysis of spectral features, and correlation of these spectral features to the concentrations of vapors of interest. The multivariate analysis of spectral features also provides the ability for the rejection of ambient interferences. As a demonstration of our R2R fabrication process, we employed polyetherurethane (PEUT) as a "classic" sensing material, extruded this sensing material as 25, 75, and 125-μm thick films, and thermally laminated the films onto RFID inlays, rapidly producing approximately 5000 vapor sensors. We further tested these RFID vapor sensors for their response selectivity toward several model vapors such as toluene, acetone, and ethanol as well as water vapor as an abundant interferent. Our RFID sensing concept features 16-bit resolution provided by the sensor reader, granting a highly desired independence from costly proprietary RFID memory chips with a low-resolution analog input. Future steps are being planned for field-testing of these sensors in numerous conditions.

UV Spectroscopy of Lucy Mission Targets

NASA Astrophysics Data System (ADS)

Thomas, Cristina

2017-08-01

The Trojan asteroids are a significant population of primitive bodies trapped in Jupiter's stable L4 and L5 Lagrange regions. Their physical properties and existence in these particular orbits constrain the chemical and dynamical processes in our early Solar System. NASA's recently selected Lucy mission will perform the first reconnaissance of these asteroids and will answer many fundamental questions about the population. The compositions of the Trojans are not well understood. Spectroscopy and spectrophotometry in visible and near-infrared wavelengths show red slopes (spectra with reflectivity increasing towards the long wavelength end of the spectrum) and no diagnostic spectral absorption features. However, past spectral and photometric observations suggest there are unobserved features in ultraviolet wavelengths. We propose to obtain ultraviolet spectroscopy with WFC3 of four Trojan asteroids that are targets of the Lucy mission. Lucy will not have the capability to obtain ultraviolet spectra. The proposed observations can only be made using Hubble. We will determine if there are UV spectral features, as suggested by visible wavelength observations, and connect these features to candidate compositional components. These observations will enable connections between the compositions of Trojans and dynamical models of the early Solar System.

Can the bump in the composite spectrum of GRB 910503 be an emission line feature of gamma-ray bursts?

NASA Astrophysics Data System (ADS)

Qin, Yi-Ping; Zhang, Fu-Wen

2005-12-01

Appearing in the composite spectral data of BATSE, EGRET and COMPTEL for GRB 910503, there is a bump at around 1600 keV. We perform a statistical analysis on the spectral data, trying to find out if the bump could be accounted for by a blue-shifted and significantly broadened rest frame line due to the Doppler effect of an expanding fireball surface. We made an F-test and adopted previously proposed criteria. The study reveals that the criteria are well satisfied and the feature can be interpreted as the blue shifted 6.4 keV line. From the fit with this line taken into account, we find the Lorentz factor of this source to be Γ = 116+9-9 (at the 68% confident level, triangleχ2 = 1) and the rest frame spectral peak energy to be E0,p = 2.96+0.24-0.18 keV. Although the existence of the emission line feature requires other independent tests to confirm, the analysis suggests that it is feasible to detect emission line features in the high energy range of GRB spectra when taking into account the Doppler effect of fireball expansion.

CHARACTERIZATION OF CRYPTOSPORIDIUM PARVUM BY MATRIX-ASSISTED LASER DESORPTION -- IONIZATION TIME OF FLIGHT MASS SPECTROMETRY

EPA Science Inventory

Matrix assisted laser desorption/ionization (MALDI) mass spectrometry was used to investigate whole and freeze thawed Cryptosporidium parvum oocysts. Whole oocysts revealed some mass spectral features. Reproducible patterns of spectral markers and increased sensitivity were obtai...

The U. S. Geological Survey, Digital Spectral Library: Version 1 (0.2 to 3.0um)

USGS Publications Warehouse

Clark, Roger N.; Swayze, Gregg A.; Gallagher, Andrea J.; King, Trude V.V.; Calvin, Wendy M.

1993-01-01

We have developed a digital reflectance spectral library, with management and spectral analysis software. The library includes 498 spectra of 444 samples (some samples include a series of grain sizes) measured from approximately 0.2 to 3.0 um . The spectral resolution (Full Width Half Maximum) of the reflectance data is <= 4 nm in the visible (0.2-0.8 um) and <= 10 nm in the NIR (0.8-2.35 um). All spectra were corrected to absolute reflectance using an NIST Halon standard. Library management software lets users search on parameters (e.g. chemical formulae, chemical analyses, purity of samples, mineral groups, etc.) as well as spectral features. Minerals from borate, carbonate, chloride, element, halide, hydroxide, nitrate, oxide, phosphate, sulfate, sulfide, sulfosalt, and the silicate (cyclosilicate, inosilicate, nesosilicate, phyllosilicate, sorosilicate, and tectosilicate) classes are represented. X-Ray and chemical analyses are tabulated for many of the entries, and all samples have been evaluated for spectral purity. The library also contains end and intermediate members for the olivine, garnet, scapolite, montmorillonite, muscovite, jarosite, and alunite solid-solution series. We have included representative spectra of H2O ice, kerogen, ammonium-bearing minerals, rare-earth oxides, desert varnish coatings, kaolinite crystallinity series, kaolinite-smectite series, zeolite series, and an extensive evaporite series. Because of the importance of vegetation to climate-change studies we have include 17 spectra of tree leaves, bushes, and grasses. The library and software are available as a series of U.S.G.S. Open File reports. PC user software is available to convert the binary data to ascii files (a separate U.S.G.S. open file report). Additionally, a binary data files are on line at the U.S.G.S. in Denver for anonymous ftp to users on the Internet. The library search software enables a user to search on documentation parameters as well as spectral features. The analysis system includes general spectral analysis routines, plotting packages, radiative transfer software for computing intimate mixtures, routines to derive optical constants from reflectance spectra, tools to analyze spectral features, and the capability to access imaging spectrometer data cubes for spectral analysis. Users may build customized libraries (at specific wavelengths and spectral resolution) for their own instruments using the library software. We are currently extending spectral coverage to 150 um. The libraries (original and convolved) will be made available in the future on a CD-ROM.

Emotion Recognition from Single-Trial EEG Based on Kernel Fisher's Emotion Pattern and Imbalanced Quasiconformal Kernel Support Vector Machine

PubMed Central

Liu, Yi-Hung; Wu, Chien-Te; Cheng, Wei-Teng; Hsiao, Yu-Tsung; Chen, Po-Ming; Teng, Jyh-Tong

2014-01-01

Electroencephalogram-based emotion recognition (EEG-ER) has received increasing attention in the fields of health care, affective computing, and brain-computer interface (BCI). However, satisfactory ER performance within a bi-dimensional and non-discrete emotional space using single-trial EEG data remains a challenging task. To address this issue, we propose a three-layer scheme for single-trial EEG-ER. In the first layer, a set of spectral powers of different EEG frequency bands are extracted from multi-channel single-trial EEG signals. In the second layer, the kernel Fisher's discriminant analysis method is applied to further extract features with better discrimination ability from the EEG spectral powers. The feature vector produced by layer 2 is called a kernel Fisher's emotion pattern (KFEP), and is sent into layer 3 for further classification where the proposed imbalanced quasiconformal kernel support vector machine (IQK-SVM) serves as the emotion classifier. The outputs of the three layer EEG-ER system include labels of emotional valence and arousal. Furthermore, to collect effective training and testing datasets for the current EEG-ER system, we also use an emotion-induction paradigm in which a set of pictures selected from the International Affective Picture System (IAPS) are employed as emotion induction stimuli. The performance of the proposed three-layer solution is compared with that of other EEG spectral power-based features and emotion classifiers. Results on 10 healthy participants indicate that the proposed KFEP feature performs better than other spectral power features, and IQK-SVM outperforms traditional SVM in terms of the EEG-ER accuracy. Our findings also show that the proposed EEG-ER scheme achieves the highest classification accuracies of valence (82.68%) and arousal (84.79%) among all testing methods. PMID:25061837

A decision support system for automatic sleep staging from EEG signals using tunable Q-factor wavelet transform and spectral features.

PubMed

Hassan, Ahnaf Rashik; Bhuiyan, Mohammed Imamul Hassan

2016-09-15

Automatic sleep scoring is essential owing to the fact that conventionally a large volume of data have to be analyzed visually by the physicians which is onerous, time-consuming and error-prone. Therefore, there is a dire need of an automated sleep staging scheme. In this work, we decompose sleep-EEG signal segments using tunable-Q factor wavelet transform (TQWT). Various spectral features are then computed from TQWT sub-bands. The performance of spectral features in the TQWT domain has been determined by intuitive and graphical analyses, statistical validation, and Fisher criteria. Random forest is used to perform classification. Optimal choices and the effects of TQWT and random forest parameters have been determined and expounded. Experimental outcomes manifest the efficacy of our feature generation scheme in terms of p-values of ANOVA analysis and Fisher criteria. The proposed scheme yields 90.38%, 91.50%, 92.11%, 94.80%, 97.50% for 6-stage to 2-stage classification of sleep states on the benchmark Sleep-EDF data-set. In addition, its performance on DREAMS Subjects Data-set is also promising. The performance of the proposed method is significantly better than the existing ones in terms of accuracy and Cohen's kappa coefficient. Additionally, the proposed scheme gives high detection accuracy for sleep stages non-REM 1 and REM. Spectral features in the TQWT domain can discriminate sleep-EEG signals corresponding to various sleep states efficaciously. The proposed scheme will alleviate the burden of the physicians, speed-up sleep disorder diagnosis, and expedite sleep research. Copyright © 2016 Elsevier B.V. All rights reserved.

Emotion recognition from single-trial EEG based on kernel Fisher's emotion pattern and imbalanced quasiconformal kernel support vector machine.

PubMed

Liu, Yi-Hung; Wu, Chien-Te; Cheng, Wei-Teng; Hsiao, Yu-Tsung; Chen, Po-Ming; Teng, Jyh-Tong

2014-07-24

Electroencephalogram-based emotion recognition (EEG-ER) has received increasing attention in the fields of health care, affective computing, and brain-computer interface (BCI). However, satisfactory ER performance within a bi-dimensional and non-discrete emotional space using single-trial EEG data remains a challenging task. To address this issue, we propose a three-layer scheme for single-trial EEG-ER. In the first layer, a set of spectral powers of different EEG frequency bands are extracted from multi-channel single-trial EEG signals. In the second layer, the kernel Fisher's discriminant analysis method is applied to further extract features with better discrimination ability from the EEG spectral powers. The feature vector produced by layer 2 is called a kernel Fisher's emotion pattern (KFEP), and is sent into layer 3 for further classification where the proposed imbalanced quasiconformal kernel support vector machine (IQK-SVM) serves as the emotion classifier. The outputs of the three layer EEG-ER system include labels of emotional valence and arousal. Furthermore, to collect effective training and testing datasets for the current EEG-ER system, we also use an emotion-induction paradigm in which a set of pictures selected from the International Affective Picture System (IAPS) are employed as emotion induction stimuli. The performance of the proposed three-layer solution is compared with that of other EEG spectral power-based features and emotion classifiers. Results on 10 healthy participants indicate that the proposed KFEP feature performs better than other spectral power features, and IQK-SVM outperforms traditional SVM in terms of the EEG-ER accuracy. Our findings also show that the proposed EEG-ER scheme achieves the highest classification accuracies of valence (82.68%) and arousal (84.79%) among all testing methods.

Quantitative characterization of crude oils and fuels in mineral substrates using reflectance spectroscopy: Implications for remote sensing

NASA Astrophysics Data System (ADS)

Scafutto, Rebecca Del'Papa Moreira; Souza Filho, Carlos Roberto de

2016-08-01

The near and shortwave infrared spectral reflectance properties of several mineral substrates impregnated with crude oils (°APIs 19.2, 27.5 and 43.2), diesel, gasoline and ethanol were measured and assembled in a spectral library. These data were examined using Principal Component Analysis (PCA) and Partial Least Squares (PLS) Regression. Unique and characteristic absorption features were identified in the mixtures, besides variations of the spectral signatures related to the compositional difference of the crude oils and fuels. These features were used for qualitative and quantitative determination of the contaminant impregnated in the substrates. Specific wavelengths, where key absorption bands occur, were used for the individual characterization of oils and fuels. The intensity of these features can be correlated to the abundance of the contaminant in the mixtures. Grain size and composition of the impregnated substrate directly influence the variation of the spectral signatures. PCA models applied to the spectral library proved able to differentiate the type and density of the hydrocarbons. The calibration models generated by PLS are robust, of high quality and can also be used to predict the concentration of oils and fuels in mixtures with mineral substrates. Such data and models are employable as a reference for classifying unknown samples of contaminated substrates. The results of this study have important implications for onshore exploration and environmental monitoring of oil and fuels leaks using proximal and far range multispectral, hyperspectral and ultraespectral remote sensing.

Infrared (2.08-14 micron) spectra of powered stony meteorites

NASA Technical Reports Server (NTRS)

Salisbury, J. W.; Daria, D. M.; Jarosewich, E.

1991-01-01

Infrared biconical reflectance spectra of 60 powdered meteorite samples, representing 50 different stony meteorites, were measured as analogues of asteroidal regolith. Representative samples were measured in directional hemispherical reflectance to assure that Kirchhoff's Law can be used to predict relative emissivity from the reflectance spectra. These spectral data confirm that the O-H fundamental absorption band near 2.9 microns is an extremely sensitive indicator of incipient alteration, which often has taken place in powdered meteorite samples exposed only to water vapor in the air. Such non-carbonaceous samples typically contain less than 1 percent water by weight. Likewise, the C-H fundamental absorption bands near 3.4 and 3.5 microns are equally sensitive indicators of contamination with volatile hydrocarbons, which can also be absorbed from the air. The heavy, macromolecular hydrocarbons native to chondrites do not display such heavy bands, making detection of these bands in remote sensing of asteroids unlikely. Despite the spectral artifacts introduced by alteration and hydrocarbon contamination, powdered stony meteorites display a wide variety of real spectral features that can be used for their identification, including residual reststrahlen bands, absorption bands, and the Christiansen feature. Researchers found that the wavelengths of the peaks or troughs of each of these spectral features can be used independently to infer meteorite composition, but the best results are obtained when the entire spectral curve is used, or at least the portion of it encompassed by the 8 to 14 micron atmospheric window, in a digital search library.

Leigh syndrome: MRI findings in two children.

PubMed

Kartikasalwah, Al; Lh, Ngu

2010-01-01

Leigh syndrome is a progressive neurodegenerative disorder of childhood. The symmetrical necrotic lesions in the basal ganglia and/or brainstem which appear as hyperintense lesions on T2-weighted MRI is characteristic and one of the essential diagnostic criteria. Recognising this MR imaging pattern in a child with neurological problems should prompt the clinician to investigate for Leigh syndrome. We present here two cases of Leigh syndrome due to different biochemical/genetic defects, and discuss the subtle differences in their MR neuroimaging features.

Mapped minerals at Questa, New Mexico, using airborne visible-infrared imaging spectrometer (AVIRIS) data -- Preliminary report

USGS Publications Warehouse

Livo, K. Eric; Clark, Roger N.

2002-01-01

This preliminary study for the First Quarterly Report has spectrally mapped hydrothermally altered minerals useful in assisting in assessment of water quality of the Red River. Airborne Visible-Infrared Imaging Spectrometer (AVIRIS) data was analyzed to characterize mined and unmined ground at Questa, New Mexico. AVIRIS data covers the Red River drainage north of the river, from between the town of Questa on the west, to east of the town of Red River. The data was calibrated and analyzed using U.S. Geological Survey custom software and spectral mineral library. AVIRIS data was tested for spectral features that matched similar features in the spectral mineral library. Goodness-of-fit and band-depth were calculated for each comparison of spectral features and used to identify surface mineralogy. Mineral distribution, mineral associations, and AVIRIS pixel spectra were examined. Mineral maps show the distribution of iron hydroxides, iron sulfates, clays, micas, carbonates, and other minerals. Initial results show a system of alteration suites that overprint each other. Quartz-sericite-pyrite (QSP) alteration grading out to propylitic alteration (epidote and calcite) was identified at the Questa Mine (molybdenum porphyry) and a similar alteration pattern was mapped at the landslide (?scar?) areas. Supergene weathering overprints the altered rock, as shown by jarosite, kaolinite, and gypsum. In the spectral analysis, hydrothermally altered ground appears to be more extensive at the unmined Goat Hill Gulch and the mined ground, than the ?scars? to the east. Though the ?scars? have similar overall altered mineral suites, there are differences between the ?scars? in sericite, kaolinite, jarosite, gypsum, and calcite abundance. Fieldwork has verified the results at the central unmined ?scar? areas.

Spectral separability and mapping potential of cassava leaf damage symptoms caused by whiteflies (Bemisia tabaci).

PubMed

Sims, Neil C; De Barro, Paul; Newnham, Glenn J; Kalyebi, Andrew; Macfadyen, Sarina; Malthus, Tim J

2018-01-01

This study examines whether leaf spectra can be used to measure damage to cassava plants from whitefly (Bemisia tabaci), and the potential to translate measurements from leaf to landscape scale in eastern Africa. Symptoms of the cassava brown streak disease (CBSD) and cassava mosaic disease (CMD) viruses, and sooty mould (SM) blackening of lower leaves from whiteflies feeding on the upper leaves, were measured at the leaf scale with a high-resolution spectroradiometer and a single photon avalanche diode (SPAD) meter, which retrieves relative chlorophyll concentration. Spectral measurements were compared to the five-level visual scores used to assess the severity of each of the three damaging agents in the field, and also to leaf chemistry data. Leaves exhibiting severe CBSD and CMD were spectrally indistinguishable from leaves without any symptoms. Severe SM was spectrally distinctive but is likely to be difficult to map because of its occurrence in the lower crown. SPAD measurements were highly correlated with most foliar chemistry measurements and field scores of disease severity. Regression models between simulated Sentinel 2 bands, field scores and SPAD measurements were strongest using wavelengths with high importance weightings in random forest models. SPAD measurements are highly correlated to many foliar chemistry parameters, and should be considered for use in mapping disease severity over larger areas. Remaining challenges for mapping relate to the subtle expression of symptoms, the spatial distribution of disease severity within fields, and the small size and complex structure of the cassava fields themselves. © 2017 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry. © 2017 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Spectral separability and mapping potential of cassava leaf damage symptoms caused by whiteflies (Bemisia tabaci)

PubMed Central

De Barro, Paul; Newnham, Glenn J; Kalyebi, Andrew; Macfadyen, Sarina; Malthus, Tim J

2017-01-01

Abstract BACKGROUND This study examines whether leaf spectra can be used to measure damage to cassava plants from whitefly (Bemisia tabaci), and the potential to translate measurements from leaf to landscape scale in eastern Africa. Symptoms of the cassava brown streak disease (CBSD) and cassava mosaic disease (CMD) viruses, and sooty mould (SM) blackening of lower leaves from whiteflies feeding on the upper leaves, were measured at the leaf scale with a high‐resolution spectroradiometer and a single photon avalanche diode (SPAD) meter, which retrieves relative chlorophyll concentration. Spectral measurements were compared to the five‐level visual scores used to assess the severity of each of the three damaging agents in the field, and also to leaf chemistry data. RESULTS Leaves exhibiting severe CBSD and CMD were spectrally indistinguishable from leaves without any symptoms. Severe SM was spectrally distinctive but is likely to be difficult to map because of its occurrence in the lower crown. SPAD measurements were highly correlated with most foliar chemistry measurements and field scores of disease severity. Regression models between simulated Sentinel 2 bands, field scores and SPAD measurements were strongest using wavelengths with high importance weightings in random forest models. CONCLUSION SPAD measurements are highly correlated to many foliar chemistry parameters, and should be considered for use in mapping disease severity over larger areas. Remaining challenges for mapping relate to the subtle expression of symptoms, the spatial distribution of disease severity within fields, and the small size and complex structure of the cassava fields themselves. © 2017 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry. PMID:28851022

Comparative Analysis of EO-1 ALI and Hyperion, and Landsat ETM+ Data for Mapping Forest Crown Closure and Leaf Area Index

PubMed Central

Pu, Ruiliang; Gong, Peng; Yu, Qian

2008-01-01

In this study, a comparative analysis of capabilities of three sensors for mapping forest crown closure (CC) and leaf area index (LAI) was conducted. The three sensors are Hyperspectral Imager (Hyperion) and Advanced Land Imager (ALI) onboard EO-1 satellite and Landsat-7 Enhanced Thematic Mapper Plus (ETM+). A total of 38 mixed coniferous forest CC and 38 LAI measurements were collected at Blodgett Forest Research Station, University of California at Berkeley, USA. The analysis method consists of (1) extracting spectral vegetation indices (VIs), spectral texture information and maximum noise fractions (MNFs), (2) establishing multivariate prediction models, (3) predicting and mapping pixel-based CC and LAI values, and (4) validating the mapped CC and LAI results with field validated photo-interpreted CC and LAI values. The experimental results indicate that the Hyperion data are the most effective for mapping forest CC and LAI (CC mapped accuracy (MA) = 76.0%, LAI MA = 74.7%), followed by ALI data (CC MA = 74.5%, LAI MA = 70.7%), with ETM+ data results being least effective (CC MA = 71.1%, LAI MA = 63.4%). This analysis demonstrates that the Hyperion sensor outperforms the other two sensors: ALI and ETM+. This is because of its high spectral resolution with rich subtle spectral information, of its short-wave infrared data for constructing optimal VIs that are slightly affected by the atmosphere, and of its more available MNFs than the other two sensors to be selected for establishing prediction models. Compared to ETM+ data, ALI data are better for mapping forest CC and LAI due to ALI data with more bands and higher signal-to-noise ratios than those of ETM+ data. PMID:27879906

Comparative Analysis of EO-1 ALI and Hyperion, and Landsat ETM+ Data for Mapping Forest Crown Closure and Leaf Area Index.

PubMed

Pu, Ruiliang; Gong, Peng; Yu, Qian

2008-06-06

In this study, a comparative analysis of capabilities of three sensors for mapping forest crown closure (CC) and leaf area index (LAI) was conducted. The three sensors are Hyperspectral Imager (Hyperion) and Advanced Land Imager (ALI) onboard EO-1 satellite and Landsat-7 Enhanced Thematic Mapper Plus (ETM+). A total of 38 mixed coniferous forest CC and 38 LAI measurements were collected at Blodgett Forest Research Station, University of California at Berkeley, USA. The analysis method consists of (1) extracting spectral vegetation indices (VIs), spectral texture information and maximum noise fractions (MNFs), (2) establishing multivariate prediction models, (3) predicting and mapping pixel-based CC and LAI values, and (4) validating the mapped CC and LAI results with field validated photo-interpreted CC and LAI values. The experimental results indicate that the Hyperion data are the most effective for mapping forest CC and LAI (CC mapped accuracy (MA) = 76.0%, LAI MA = 74.7%), followed by ALI data (CC MA = 74.5%, LAI MA = 70.7%), with ETM+ data results being least effective (CC MA = 71.1%, LAI MA = 63.4%). This analysis demonstrates that the Hyperion sensor outperforms the other two sensors: ALI and ETM+. This is because of its high spectral resolution with rich subtle spectral information, of its short-wave infrared data for constructing optimal VIs that are slightly affected by the atmosphere, and of its more available MNFs than the other two sensors to be selected for establishing prediction models. Compared to ETM+ data, ALI data are better for mapping forest CC and LAI due to ALI data with more bands and higher signal-to-noise ratios than those of ETM+ data.

Identification of spectral phenotypes in age-related macular degeneration patients

NASA Astrophysics Data System (ADS)

Davis, Bert; Russell, Steven; Abramoff, Michael; Nemeth, Sheila C.; Barriga, E. Simon; Soliz, Peter

2007-02-01

The purpose of this study is to show that there exists a spectral characteristic that differentiates normal macular tissue from various types of genetic-based macular diseases. This paper demonstrates statistically that hyperspectral images of macular and other retinal tissue can be used to spectrally differentiate different forms of age-related macular degeneration. A hyperspectral fundus imaging device has been developed and tested for the purpose of collecting hyperspectral images of the human retina. A methodology based on partial least squares and ANOVA has been applied to determine the hyperspectral representation of individual spectral characteristics of retinal features. Each discrete tissue type in the retina has an identifiable spectral shape or signature which, when combined with spatial context, aids in detection of pathological features. Variations in the amount and distribution of various ocular pigments or the inclusion of additional biochemical substances will allow detection of pathological conditions prior to traditional histological presentation. Fundus imaging cameras are ubiquitous and are one of the most common imaging modalities used in documenting a patient's retinal state for diagnosis, e.g. remotely, or for monitoring the progression of an ocular disease. The added diagnostic information obtained with only a minor retro-fit of a specialized spectral camera will lead to new diagnostic information to the clinical ophthalmologist or eye-care specialist.

Arrhythmia Mechanism and Scaling Effect on the Spectral Properties of Electroanatomical Maps With Manifold Harmonics.

PubMed

Sanroman-Junquera, Margarita; Mora-Jimenez, Inmaculada; Garcia-Alberola, Arcadio; Caamano, Antonio J; Trenor, Beatriz; Rojo-Alvarez, Jose L

2018-04-01

Spatial and temporal processing of intracardiac electrograms provides relevant information to support the arrhythmia ablation during electrophysiological studies. Current cardiac navigation systems (CNS) and electrocardiographic imaging (ECGI) build detailed 3-D electroanatomical maps (EAM), which represent the spatial anatomical distribution of bioelectrical features, such as activation time or voltage. We present a principled methodology for spectral analysis of both EAM geometry and bioelectrical feature in CNS or ECGI, including their spectral representation, cutoff frequency, or spatial sampling rate (SSR). Existing manifold harmonic techniques for spectral mesh analysis are adapted to account for a fourth dimension, corresponding to the EAM bioelectrical feature. Appropriate scaling is required to address different magnitudes and units. With our approach, simulated and real EAM showed strong SSR dependence on both the arrhythmia mechanism and the cardiac anatomical shape. For instance, high frequencies increased significantly the SSR because of the "early-meets-late" in flutter EAM, compared with the sinus rhythm. Besides, higher frequency components were obtained for the left atrium (more complex anatomy) than for the right atrium in sinus rhythm. The proposed manifold harmonics methodology opens the field toward new signal processing tools for principled EAM spatiofeature analysis in CNS and ECGI, and to an improved knowledge on arrhythmia mechanisms.

Fluorescence and reflectance properties of hemoglobin-pigmented skin disorders

NASA Astrophysics Data System (ADS)

Troyanova, P.; Borisova, E.; Avramov, L.

2007-06-01

There has been growing interest in clinical application of laser-induced autofluorescence (LIAF) and reflectance spectroscopy (RS) to differentiate disease from normal surrounding tissue, including skin pathologies. Pigmented cutaneous lesions diagnosis plays important role in clinical practice, as malignant melanoma, which is characterized with greatest mortality from all skin cancer types, must be carefully discriminated form other colorized pathologies. The goals of this work were investigation of cutaneous hemoglobin-pigmented lesions (heamangioma, angiokeratoma, and fibroma) by the methods of LIAFS and RS. Spectra from healthy skin areas near to the lesion were detected to be used posteriori in analysis. Fluorescence and reflectance of cutaneous hemoglobin-pigmented lesions are used to develop criterion for differentiation from other pigmented pathologies. Origins of the spectral features obtained are discussed and determination of lesion types is achieved using selected spectral features. The spectral results, obtained were used to develop multispectral diagnostic algorithms based on the most prominent spectral features from the fluorescence and reflectance spectra of the lesions investigated. In comparison between normal skin and different cutaneous lesion types and between lesion types themselves sensitivities and specificities higher than 90 % were achieved. These results show a perspective possibility to differentiate hemoglobin-pigmented lesions from other pigmented pathologies using non-invasive and real time discrimination procedure.

Near-infrared spectral image analysis of pork marbling based on Gabor filter and wide line detector techniques.

PubMed

Huang, Hui; Liu, Li; Ngadi, Michael O; Gariépy, Claude; Prasher, Shiv O

2014-01-01

Marbling is an important quality attribute of pork. Detection of pork marbling usually involves subjective scoring, which raises the efficiency costs to the processor. In this study, the ability to predict pork marbling using near-infrared (NIR) hyperspectral imaging (900-1700 nm) and the proper image processing techniques were studied. Near-infrared images were collected from pork after marbling evaluation according to current standard chart from the National Pork Producers Council. Image analysis techniques-Gabor filter, wide line detector, and spectral averaging-were applied to extract texture, line, and spectral features, respectively, from NIR images of pork. Samples were grouped into calibration and validation sets. Wavelength selection was performed on calibration set by stepwise regression procedure. Prediction models of pork marbling scores were built using multiple linear regressions based on derivatives of mean spectra and line features at key wavelengths. The results showed that the derivatives of both texture and spectral features produced good results, with correlation coefficients of validation of 0.90 and 0.86, respectively, using wavelengths of 961, 1186, and 1220 nm. The results revealed the great potential of the Gabor filter for analyzing NIR images of pork for the effective and efficient objective evaluation of pork marbling.

Dimensionality-varied deep convolutional neural network for spectral-spatial classification of hyperspectral data

NASA Astrophysics Data System (ADS)

Qu, Haicheng; Liang, Xuejian; Liang, Shichao; Liu, Wanjun

2018-01-01

Many methods of hyperspectral image classification have been proposed recently, and the convolutional neural network (CNN) achieves outstanding performance. However, spectral-spatial classification of CNN requires an excessively large model, tremendous computations, and complex network, and CNN is generally unable to use the noisy bands caused by water-vapor absorption. A dimensionality-varied CNN (DV-CNN) is proposed to address these issues. There are four stages in DV-CNN and the dimensionalities of spectral-spatial feature maps vary with the stages. DV-CNN can reduce the computation and simplify the structure of the network. All feature maps are processed by more kernels in higher stages to extract more precise features. DV-CNN also improves the classification accuracy and enhances the robustness to water-vapor absorption bands. The experiments are performed on data sets of Indian Pines and Pavia University scene. The classification performance of DV-CNN is compared with state-of-the-art methods, which contain the variations of CNN, traditional, and other deep learning methods. The experiment of performance analysis about DV-CNN itself is also carried out. The experimental results demonstrate that DV-CNN outperforms state-of-the-art methods for spectral-spatial classification and it is also robust to water-vapor absorption bands. Moreover, reasonable parameters selection is effective to improve classification accuracy.

[Bare Soil Moisture Inversion Model Based on Visible-Shortwave Infrared Reflectance].

PubMed

Zheng, Xiao-po; Sun, Yue-jun; Qin, Qi-ming; Ren, Hua-zhong; Gao, Zhong-ling; Wu, Ling; Meng, Qing-ye; Wang, Jin-liang; Wang, Jian-hua

2015-08-01

Soil is the loose solum of land surface that can support plants. It consists of minerals, organics, atmosphere, moisture, microbes, et al. Among its complex compositions, soil moisture varies greatly. Therefore, the fast and accurate inversion of soil moisture by using remote sensing is very crucial. In order to reduce the influence of soil type on the retrieval of soil moisture, this paper proposed a normalized spectral slope and absorption index named NSSAI to estimate soil moisture. The modeling of the new index contains several key steps: Firstly, soil samples with different moisture level were artificially prepared, and soil reflectance spectra was consequently measured using spectroradiometer produced by ASD Company. Secondly, the moisture absorption spectral feature located at shortwave wavelengths and the spectral slope of visible wavelengths were calculated after analyzing the regular spectral feature change patterns of different soil at different moisture conditions. Then advantages of the two features at reducing soil types' effects was synthesized to build the NSSAI. Thirdly, a linear relationship between NSSAI and soil moisture was established. The result showed that NSSAI worked better (correlation coefficient is 0.93) than most of other traditional methods in soil moisture extraction. It can weaken the influences caused by soil types at different moisture levels and improve the bare soil moisture inversion accuracy.

ION Configuration Editor

NASA Technical Reports Server (NTRS)

Borgen, Richard L.

2013-01-01

The configuration of ION (Inter - planetary Overlay Network) network nodes is a manual task that is complex, time-consuming, and error-prone. This program seeks to accelerate this job and produce reliable configurations. The ION Configuration Editor is a model-based smart editor based on Eclipse Modeling Framework technology. An ION network designer uses this Eclipse-based GUI to construct a data model of the complete target network and then generate configurations. The data model is captured in an XML file. Intrinsic editor features aid in achieving model correctness, such as field fill-in, type-checking, lists of valid values, and suitable default values. Additionally, an explicit "validation" feature executes custom rules to catch more subtle model errors. A "survey" feature provides a set of reports providing an overview of the entire network, enabling a quick assessment of the model s completeness and correctness. The "configuration" feature produces the main final result, a complete set of ION configuration files (eight distinct file types) for each ION node in the network.

Understanding Deep Representations Learned in Modeling Users Likes.

PubMed

Guntuku, Sharath Chandra; Zhou, Joey Tianyi; Roy, Sujoy; Lin, Weisi; Tsang, Ivor W

2016-08-01

Automatically understanding and discriminating different users' liking for an image is a challenging problem. This is because the relationship between image features (even semantic ones extracted by existing tools, viz., faces, objects, and so on) and users' likes is non-linear, influenced by several subtle factors. This paper presents a deep bi-modal knowledge representation of images based on their visual content and associated tags (text). A mapping step between the different levels of visual and textual representations allows for the transfer of semantic knowledge between the two modalities. Feature selection is applied before learning deep representation to identify the important features for a user to like an image. The proposed representation is shown to be effective in discriminating users based on images they like and also in recommending images that a given user likes, outperforming the state-of-the-art feature representations by  ∼ 15 %-20%. Beyond this test-set performance, an attempt is made to qualitatively understand the representations learned by the deep architecture used to model user likes.

Raman Spectral Signatures as Conformational Probes of Biomolecules

NASA Astrophysics Data System (ADS)

Golan, Amir; Mayorkas, Nitzan; Rosenwaks, Salman; Bar, Ilana

2009-06-01

A first application of ionization-loss stimulated Raman spectroscopy (ILSRS) for monitoring the spectral features of four conformers of a gas phase neurotransmitter (2-phenylethylamine) is reported. The Raman spectra of the conformers show bands that uniquely identify the conformational structure of the molecule and are well matched by density functional theory calculations. The measurement of spectral signatures by ILSRS in an extended spectral range, with a relatively convenient laser source, is extremely important, allowing enhanced accessibility to intra- and inter-molecular forces, which are significant in biological structure and activity.

Raman Spectral Signatures as Conformational Probes of Biomolecules

NASA Astrophysics Data System (ADS)

Bar, Ilana; Golan, Amir; Mayorkas, Nitzan; Rosenwaks, Salman

2009-03-01

A first application of ionization-loss stimulated Raman spectroscopy (ILSRS) monitoring the spectral features of four conformers of a gas phase neurotransmitter (2-phenylethylamine) is reported. The Raman spectra of the conformers show bands that uniquely identify the conformational structure of the molecule and are well matched by density functional theory calculations. The measurement of spectral signatures by ILSRS in an extended spectral range, with a relatively convenient laser source, is extremely important, allowing enhanced accessibility to intra- and inter-molecular forces, which are significant in biological structure and activity.

SDP_mharwit_1: Demonstration of HIFI Linear Polarization Analysis of Spectral Features

NASA Astrophysics Data System (ADS)

Harwit, M.

2010-03-01

We propose to observe the polarization of the 621 GHz water vapor maser in VY Canis Majoris to demonstrate the capability of HIFI to make polarization observations of Far-Infrared/Submillimeter spectral lines. The proposed Demonstration Phase would: - Show that HIFI is capable of interesting linear polarization measurements of spectral lines; - Test out the highest spectral resolving power to sort out closely spaced Doppler components; - Determine whether the relative intensities predicted by Neufeld and Melnick are correct; - Record the degree and direction of linear polarization for the closely-Doppler shifted peaks.

Koopmans' analysis of chemical hardness with spectral-like resolution.

PubMed

Putz, Mihai V

2013-01-01

Three approximation levels of Koopmans' theorem are explored and applied: the first referring to the inner quantum behavior of the orbitalic energies that depart from the genuine ones in Fock space when the wave-functions' Hilbert-Banach basis set is specified to solve the many-electronic spectra of spin-orbitals' eigenstates; it is the most subtle issue regarding Koopmans' theorem as it brings many critics and refutation in the last decades, yet it is shown here as an irrefutable "observational" effect through computation, specific to any in silico spectra of an eigenproblem; the second level assumes the "frozen spin-orbitals" approximation during the extracting or adding of electrons to the frontier of the chemical system through the ionization and affinity processes, respectively; this approximation is nevertheless workable for great deal of chemical compounds, especially organic systems, and is justified for chemical reactivity and aromaticity hierarchies in an homologue series; the third and the most severe approximation regards the extension of the second one to superior orders of ionization and affinities, here studied at the level of chemical hardness compact-finite expressions up to spectral-like resolution for a paradigmatic set of aromatic carbohydrates.

Koopmans' Analysis of Chemical Hardness with Spectral-Like Resolution

PubMed Central

2013-01-01

Three approximation levels of Koopmans' theorem are explored and applied: the first referring to the inner quantum behavior of the orbitalic energies that depart from the genuine ones in Fock space when the wave-functions' Hilbert-Banach basis set is specified to solve the many-electronic spectra of spin-orbitals' eigenstates; it is the most subtle issue regarding Koopmans' theorem as it brings many critics and refutation in the last decades, yet it is shown here as an irrefutable “observational” effect through computation, specific to any in silico spectra of an eigenproblem; the second level assumes the “frozen spin-orbitals” approximation during the extracting or adding of electrons to the frontier of the chemical system through the ionization and affinity processes, respectively; this approximation is nevertheless workable for great deal of chemical compounds, especially organic systems, and is justified for chemical reactivity and aromaticity hierarchies in an homologue series; the third and the most severe approximation regards the extension of the second one to superior orders of ionization and affinities, here studied at the level of chemical hardness compact-finite expressions up to spectral-like resolution for a paradigmatic set of aromatic carbohydrates. PMID:23970834

Interpreting the Subtle Spectral Variations of the 11.2 and 12.7 μm Polycyclic Aromatic Hydrocarbon Bands

NASA Astrophysics Data System (ADS)

Shannon, M. J.; Stock, D. J.; Peeters, E.

2016-06-01

We report new properties of the 11 and 12.7 μm emission complexes of polycyclic aromatic hydrocarbons (PAHs) by applying a Gaussian-based decomposition technique. Using high-resolution Spitzer Space Telescope data, we study in detail the spectral and spatial characteristics of the 11 and 12.7 μm emission bands in maps of reflection nebulae NGC 7023 and NGC 2023 (north and south) and the star-forming region M17. Profile variations are observed in both the 11 and 12.7 μm emission bands. We identify a neutral contribution to the traditional 11.0 μm PAH band and a cationic contribution to the traditional 11.2 μm band, the latter of which affects the PAH class of the 11.2 μm emission in our sample. The peak variations of the 12.7 μm complex are explained by the competition between two underlying blended components. The spatial distributions of these components link them to cations and neutrals. We conclude that the 12.7 μm emission originates in both neutral and cationic PAHs, lending support to the use of the 12.7/11.2 intensity ratio as a charge proxy.

Observational aspects of outbursting black hole sources: Evolution of spectro-temporal features and X-ray variability

NASA Astrophysics Data System (ADS)

Sreehari, H.; Nandi, Anuj; Radhika, D.; Iyer, Nirmal; Mandal, Samir

2018-02-01

We report on our attempt to understand the outbursting profile of Galactic Black Hole sources, keeping in mind the evolution of temporal and spectral features during the outburst. We present results of evolution of quasi-periodic oscillations, spectral states and possible connection with jet ejections during the outburst phase. Further, we attempt to connect the observed X-ray variabilities (i.e., `class'/`structured' variabilities, similar to GRS 1915+105) with spectral states of black hole sources. Towards these studies, we consider three black hole sources that have undergone single (XTE J1859+226), a few (IGR J17091-3624) and many (GX 339-4) outbursts since the start of RXTE era. Finally, we model the broadband energy spectra (3-150 keV) of different spectral states using RXTE and NuSTAR observations. Results are discussed in the context of two-component advective flow model, while constraining the mass of the three black hole sources.