NASA Astrophysics Data System (ADS)
Dafu, Shen; Leihong, Zhang; Dong, Liang; Bei, Li; Yi, Kang
2017-07-01
The purpose of this study is to improve the reconstruction precision and better copy the color of spectral image surfaces. A new spectral reflectance reconstruction algorithm based on an iterative threshold combined with weighted principal component space is presented in this paper, and the principal component with weighted visual features is the sparse basis. Different numbers of color cards are selected as the training samples, a multispectral image is the testing sample, and the color differences in the reconstructions are compared. The channel response value is obtained by a Mega Vision high-accuracy, multi-channel imaging system. The results show that spectral reconstruction based on weighted principal component space is superior in performance to that based on traditional principal component space. Therefore, the color difference obtained using the compressive-sensing algorithm with weighted principal component analysis is less than that obtained using the algorithm with traditional principal component analysis, and better reconstructed color consistency with human eye vision is achieved.
Component Cell-Based Restriction of Spectral Conditions and the Impact on CPV Module Power Rating
DOE Office of Scientific and Technical Information (OSTI.GOV)
Muller, Matthew T; Steiner, Marc; Siefer, Gerald
One approach to consider the prevailing spectral conditions when performing CPV module power ratings according to the standard IEC 62670-3 is based on spectral matching ratios (SMRs) determined by the means of component cell sensors. In this work, an uncertainty analysis of the SMR approach is performed based on a dataset of spectral irradiances created with SMARTS2. Using these illumination spectra, the respective efficiencies of multijunction solar cells with different cell architectures are calculated. These efficiencies were used to analyze the influence of different component cell sensors and SMR filtering methods. The 3 main findings of this work are asmore » follows. First, component cells based on the lattice-matched triple-junction (LM3J) cell are suitable for restricting spectral conditions and are qualified for the standardized power rating of CPV modules - even if the CPV module is using multijunction cells other than LM3J. Second, a filtering of all 3 SMRs with +/-3.0% of unity results in the worst case scenario in an underestimation of -1.7% and overestimation of +2.4% compared to AM1.5d efficiency. Third, there is no benefit in matching the component cells to the module cell in respect to the measurement uncertainty.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Holden, H.; LeDrew, E.
1997-06-01
Remote discrimination of substrate types in relatively shallow coastal waters has been limited by the spatial and spectral resolution of available sensors. An additional limiting factor is the strong attenuating influence of the water column over the substrate. As a result, there have been limited attempts to map submerged ecosystems such as coral reefs based on spectral characteristics. Both healthy and bleached corals were measured at depth with a hand-held spectroradiometer, and their spectra compared. Two separate principal components analyses (PCA) were performed on two sets of spectral data. The PCA revealed that there is indeed a spectral difference basedmore » on health. In the first data set, the first component (healthy coral) explains 46.82%, while the second component (bleached coral) explains 46.35% of the variance. In the second data set, the first component (bleached coral) explained 46.99%; the second component (healthy coral) explained 36.55%; and the third component (healthy coral) explained 15.44 % of the total variance in the original data. These results are encouraging with respect to using an airborne spectroradiometer to identify areas of bleached corals thus enabling accurate monitoring over time.« less
NASA Astrophysics Data System (ADS)
Yang, Tao; Peng, Jing-xiao; Ho, Ho-pui; Song, Chun-yuan; Huang, Xiao-li; Zhu, Yong-yuan; Li, Xing-ao; Huang, Wei
2018-01-01
By using a preaggregated silver nanoparticle monolayer film and an infrared sensor card, we demonstrate a miniature spectrometer design that covers a broad wavelength range from visible to infrared with high spectral resolution. The spectral contents of an incident probe beam are reconstructed by solving a matrix equation with a smoothing simulated annealing algorithm. The proposed spectrometer offers significant advantages over current instruments that are based on Fourier transform and grating dispersion, in terms of size, resolution, spectral range, cost and reliability. The spectrometer contains three components, which are used for dispersion, frequency conversion and detection. Disordered silver nanoparticles in dispersion component reduce the fabrication complexity. An infrared sensor card in the conversion component broaden the operational spectral range of the system into visible and infrared bands. Since the CCD used in the detection component provides very large number of intensity measurements, one can reconstruct the final spectrum with high resolution. An additional feature of our algorithm for solving the matrix equation, which is suitable for reconstructing both broadband and narrowband signals, we have adopted a smoothing step based on a simulated annealing algorithm. This algorithm improve the accuracy of the spectral reconstruction.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Núñez, Rubén, E-mail: ruben.nunez@ies-def.upm.es; Antón, Ignacio; Askins, Steve
In the frame of the European project SOPHIA, a spectral network based on component (also called isotypes) cells has been created. Among the members of this project, several spectral sensors based on component cells and collimating tubes, so-called spectroheliometers, were installed in the last years, allowing the collection of minute-resolution spectral data useful for CPV systems characterization across Europe. The use of spectroheliometers has been proved useful to establish the necessary spectral conditions to perform power rating of CPV modules and systems. If enough data in a given period of time is collected, ideally a year, it is possible tomore » characterize spectrally the place where measurements are taken, in the same way that hours of annual irradiation can be estimated using a pyrheliometer.« less
Color Restoration of RGBN Multispectral Filter Array Sensor Images Based on Spectral Decomposition.
Park, Chulhee; Kang, Moon Gi
2016-05-18
A multispectral filter array (MSFA) image sensor with red, green, blue and near-infrared (NIR) filters is useful for various imaging applications with the advantages that it obtains color information and NIR information simultaneously. Because the MSFA image sensor needs to acquire invisible band information, it is necessary to remove the IR cut-offfilter (IRCF). However, without the IRCF, the color of the image is desaturated by the interference of the additional NIR component of each RGB color channel. To overcome color degradation, a signal processing approach is required to restore natural color by removing the unwanted NIR contribution to the RGB color channels while the additional NIR information remains in the N channel. Thus, in this paper, we propose a color restoration method for an imaging system based on the MSFA image sensor with RGBN filters. To remove the unnecessary NIR component in each RGB color channel, spectral estimation and spectral decomposition are performed based on the spectral characteristics of the MSFA sensor. The proposed color restoration method estimates the spectral intensity in NIR band and recovers hue and color saturation by decomposing the visible band component and the NIR band component in each RGB color channel. The experimental results show that the proposed method effectively restores natural color and minimizes angular errors.
Color Restoration of RGBN Multispectral Filter Array Sensor Images Based on Spectral Decomposition
Park, Chulhee; Kang, Moon Gi
2016-01-01
A multispectral filter array (MSFA) image sensor with red, green, blue and near-infrared (NIR) filters is useful for various imaging applications with the advantages that it obtains color information and NIR information simultaneously. Because the MSFA image sensor needs to acquire invisible band information, it is necessary to remove the IR cut-offfilter (IRCF). However, without the IRCF, the color of the image is desaturated by the interference of the additional NIR component of each RGB color channel. To overcome color degradation, a signal processing approach is required to restore natural color by removing the unwanted NIR contribution to the RGB color channels while the additional NIR information remains in the N channel. Thus, in this paper, we propose a color restoration method for an imaging system based on the MSFA image sensor with RGBN filters. To remove the unnecessary NIR component in each RGB color channel, spectral estimation and spectral decomposition are performed based on the spectral characteristics of the MSFA sensor. The proposed color restoration method estimates the spectral intensity in NIR band and recovers hue and color saturation by decomposing the visible band component and the NIR band component in each RGB color channel. The experimental results show that the proposed method effectively restores natural color and minimizes angular errors. PMID:27213381
Separation of β-amyloid binding and white matter uptake of 18F-flutemetamol using spectral analysis
Heurling, Kerstin; Buckley, Christopher; Vandenberghe, Rik; Laere, Koen Van; Lubberink, Mark
2015-01-01
The kinetic components of the β-amyloid ligand 18F-flutemetamol binding in grey and white matter were investigated through spectral analysis, and a method developed for creation of parametric images separating grey and white matter uptake. Tracer uptake in grey and white matter and cerebellar cortex was analyzed through spectral analysis in six subjects, with (n=4) or without (n=2) apparent β-amyloid deposition, having undergone dynamic 18F-flutemetamol scanning with arterial blood sampling. The spectra were divided into three components: slow, intermediate and fast basis function rates. The contribution of each of the components to total volume of distribution (VT) was assessed for different tissue types. The slow component dominated in white matter (average 90%), had a higher contribution to grey matter VT in subjects with β-amyloid deposition (average 44%) than without (average 6%) and was absent in cerebellar cortex, attributing the slow component of 18F-flutemetamol uptake in grey matter to β-amyloid binding. Parametric images of voxel-based spectral analysis were created for VT, the slow component and images segmented based on the slow component contribution; confirming that grey matter and white matter uptake can be discriminated on voxel-level using a threshold for the contribution from the slow component to VT. PMID:26550542
Widjaja, Effendi; Garland, Marc
2008-02-01
Raman microscopy was used in mapping mode to collect more than 1000 spectra in a 100 microm x 100 microm area from a commercial stamp. Band-target entropy minimization (BTEM) was then employed to unmix the mixture spectra in order to extract the pure component spectra of the samples. Three pure component spectral patterns with good signal-to-noise ratios were recovered, and their spatial distributions were determined. The three pure component spectral patterns were then identified as copper phthalocyanine blue, calcite-like material, and yellow organic dye material by comparison to known spectral libraries. The present investigation, consisting of (1) advanced curve resolution (blind-source separation) followed by (2) spectral data base matching, readily suggests extensions to authenticity and counterfeit studies of other types of commercial objects. The presence or absence of specific observable components form the basis for assessment. The present spectral analysis (BTEM) is applicable to highly overlapping spectral information. Since a priori information such as the number of components present and spectral libraries are not needed in BTEM, and since minor signals arising from trace components can be reconstructed, this analysis offers a robust approach to a wide variety of material problems involving authenticity and counterfeit issues.
Retrieval of the atmospheric compounds using a spectral optical thickness information
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ioltukhovski, A.A.
A spectral inversion technique for retrieval of the atmospheric gases and aerosols contents is proposed. This technique based upon the preliminary measurement or retrieval of the spectral optical thickness. The existence of a priori information about the spectral cross sections for some of the atmospheric components allows to retrieve the relative contents of these components in the atmosphere. Method of smooth filtration makes possible to estimate contents of atmospheric aerosols with known cross sections and to filter out other aerosols; this is done independently from their relative contribution to the optical thickness.
NASA Astrophysics Data System (ADS)
Lim, Hoong-Ta; Murukeshan, Vadakke Matham
2017-06-01
Hyperspectral imaging combines imaging and spectroscopy to provide detailed spectral information for each spatial point in the image. This gives a three-dimensional spatial-spatial-spectral datacube with hundreds of spectral images. Probe-based hyperspectral imaging systems have been developed so that they can be used in regions where conventional table-top platforms would find it difficult to access. A fiber bundle, which is made up of specially-arranged optical fibers, has recently been developed and integrated with a spectrograph-based hyperspectral imager. This forms a snapshot hyperspectral imaging probe, which is able to form a datacube using the information from each scan. Compared to the other configurations, which require sequential scanning to form a datacube, the snapshot configuration is preferred in real-time applications where motion artifacts and pixel misregistration can be minimized. Principal component analysis is a dimension-reducing technique that can be applied in hyperspectral imaging to convert the spectral information into uncorrelated variables known as principal components. A confidence ellipse can be used to define the region of each class in the principal component feature space and for classification. This paper demonstrates the use of the snapshot hyperspectral imaging probe to acquire data from samples of different colors. The spectral library of each sample was acquired and then analyzed using principal component analysis. Confidence ellipse was then applied to the principal components of each sample and used as the classification criteria. The results show that the applied analysis can be used to perform classification of the spectral data acquired using the snapshot hyperspectral imaging probe.
Annoyance from industrial noise: indicators for a wide variety of industrial sources.
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.
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.
Kim, Mooeung; Chung, Hoeil
2013-03-07
The use of selectivity-enhanced Raman spectra of lube base oil (LBO) samples achieved by the spectral collection under frozen conditions at low temperatures was effective for improving accuracy for the determination of the kinematic viscosity at 40 °C (KV@40). A collection of Raman spectra from samples cooled around -160 °C provided the most accurate measurement of KV@40. Components of the LBO samples were mainly long-chain hydrocarbons with molecular structures that were deformable when these were frozen, and the different structural deformabilities of the components enhanced spectral selectivity among the samples. To study the structural variation of components according to the change of sample temperature from cryogenic to ambient condition, n-heptadecane and pristane (2,6,10,14-tetramethylpentadecane) were selected as representative components of LBO samples, and their temperature-induced spectral features as well as the corresponding spectral loadings were investigated. A two-dimensional (2D) correlation analysis was also employed to explain the origin for the improved accuracy. The asynchronous 2D correlation pattern was simplest at the optimal temperature, indicating the occurrence of distinct and selective spectral variations, which enabled the variation of KV@40 of LBO samples to be more accurately assessed.
Stabilized diode seed laser for flight and space-based remote lidar sensing applications
NASA Astrophysics Data System (ADS)
McNeil, Shirley; Pandit, Pushkar; Battle, Philip; Rudd, Joe; Hovis, Floyd
2017-08-01
AdvR, through support of the NASA SBIR program, has developed fiber-based components and sub-systems that are routinely used on NASA's airborne missions, and is now developing an environmentally hardened, diode-based, locked wavelength, seed laser for future space-based high spectral resolution lidar applications. The seed laser source utilizes a fiber-coupled diode laser, a fiber-coupled, calibrated iodine reference module to provide an absolute wavelength reference, and an integrated, dual-element, nonlinear optical waveguide component for second harmonic generation, spectral formatting and wavelength locking. The diode laser operates over a range close to 1064.5 nm, provides for stabilization of the seed to the desired iodine transition and allows for a highly-efficient, fully-integrated seed source that is well-suited for use in airborne and space-based environments. A summary of component level environmental testing and spectral purity measurements with a seeded Nd:YAG laser will be presented. A direct-diode, wavelength-locked seed laser will reduce the overall size weight and power (SWaP) requirements of the laser transmitter, thus directly addressing the need for developing compact, efficient, lidar component technologies for use in airborne and space-based environments.
NASA Astrophysics Data System (ADS)
Hirose, Misa; Toyota, Saori; Tsumura, Norimichi
2018-02-01
In this research, we evaluate the visibility of age spot and freckle with changing the blood volume based on simulated spectral reflectance distribution and the actual facial color images, and compare these results. First, we generate three types of spatial distribution of age spot and freckle in patch-like images based on the simulated spectral reflectance. The spectral reflectance is simulated using Monte Carlo simulation of light transport in multi-layered tissue. Next, we reconstruct the facial color image with changing the blood volume. We acquire the concentration distribution of melanin, hemoglobin and shading components by applying the independent component analysis on a facial color image. We reproduce images using the obtained melanin and shading concentration and the changed hemoglobin concentration. Finally, we evaluate the visibility of pigmentations using simulated spectral reflectance distribution and facial color images. In the result of simulated spectral reflectance distribution, we found that the visibility became lower as the blood volume increases. However, we can see that a specific blood volume reduces the visibility of the actual pigmentations from the result of the facial color images.
NASA Astrophysics Data System (ADS)
Feng, Ximeng; Li, Gang; Yu, Haixia; Wang, Shaohui; Yi, Xiaoqing; Lin, Ling
2018-03-01
Noninvasive blood component analysis by spectroscopy has been a hotspot in biomedical engineering in recent years. Dynamic spectrum provides an excellent idea for noninvasive blood component measurement, but studies have been limited to the application of broadband light sources and high-resolution spectroscopy instruments. In order to remove redundant information, a more effective wavelength selection method has been presented in this paper. In contrast to many common wavelength selection methods, this method is based on sensing mechanism which has a clear mechanism and can effectively avoid the noise from acquisition system. The spectral difference coefficient was theoretically proved to have a guiding significance for wavelength selection. After theoretical analysis, the multi-band spectral difference coefficient-wavelength selection method combining with the dynamic spectrum was proposed. An experimental analysis based on clinical trial data from 200 volunteers has been conducted to illustrate the effectiveness of this method. The extreme learning machine was used to develop the calibration models between the dynamic spectrum data and hemoglobin concentration. The experiment result shows that the prediction precision of hemoglobin concentration using multi-band spectral difference coefficient-wavelength selection method is higher compared with other methods.
Fine structure of the low-frequency spectra of heart rate and blood pressure
Kuusela, Tom A; Kaila, Timo J; Kähönen, Mika
2003-01-01
Background The aim of this study was to explore the principal frequency components of the heart rate and blood pressure variability in the low frequency (LF) and very low frequency (VLF) band. The spectral composition of the R–R interval (RRI) and systolic arterial blood pressure (SAP) in the frequency range below 0.15 Hz were carefully analyzed using three different spectral methods: Fast Fourier transform (FFT), Wigner-Ville distribution (WVD), and autoregression (AR). All spectral methods were used to create time–frequency plots to uncover the principal spectral components that are least dependent on time. The accurate frequencies of these components were calculated from the pole decomposition of the AR spectral density after determining the optimal model order – the most crucial factor when using this method – with the help of FFT and WVD methods. Results Spectral analysis of the RRI and SAP of 12 healthy subjects revealed that there are always at least three spectral components below 0.15 Hz. The three principal frequency components are 0.026 ± 0.003 (mean ± SD) Hz, 0.076 ± 0.012 Hz, and 0.117 ± 0.016 Hz. These principal components vary only slightly over time. FFT-based coherence and phase-function analysis suggests that the second and third components are related to the baroreflex control of blood pressure, since the phase difference between SAP and RRI was negative and almost constant, whereas the origin of the first component is different since no clear SAP–RRI phase relationship was found. Conclusion The above data indicate that spontaneous fluctuations in heart rate and blood pressure within the standard low-frequency range of 0.04–0.15 Hz typically occur at two frequency components rather than only at one as widely believed, and these components are not harmonically related. This new observation in humans can help explain divergent results in the literature concerning spontaneous low-frequency oscillations. It also raises methodological and computational questions regarding the usability and validity of the low-frequency spectral band when estimating sympathetic activity and baroreflex gain. PMID:14552660
Fine structure of the low-frequency spectra of heart rate and blood pressure.
Kuusela, Tom A; Kaila, Timo J; Kähönen, Mika
2003-10-13
The aim of this study was to explore the principal frequency components of the heart rate and blood pressure variability in the low frequency (LF) and very low frequency (VLF) band. The spectral composition of the R-R interval (RRI) and systolic arterial blood pressure (SAP) in the frequency range below 0.15 Hz were carefully analyzed using three different spectral methods: Fast Fourier transform (FFT), Wigner-Ville distribution (WVD), and autoregression (AR). All spectral methods were used to create time-frequency plots to uncover the principal spectral components that are least dependent on time. The accurate frequencies of these components were calculated from the pole decomposition of the AR spectral density after determining the optimal model order--the most crucial factor when using this method--with the help of FFT and WVD methods. Spectral analysis of the RRI and SAP of 12 healthy subjects revealed that there are always at least three spectral components below 0.15 Hz. The three principal frequency components are 0.026 +/- 0.003 (mean +/- SD) Hz, 0.076 +/- 0.012 Hz, and 0.117 +/- 0.016 Hz. These principal components vary only slightly over time. FFT-based coherence and phase-function analysis suggests that the second and third components are related to the baroreflex control of blood pressure, since the phase difference between SAP and RRI was negative and almost constant, whereas the origin of the first component is different since no clear SAP-RRI phase relationship was found. The above data indicate that spontaneous fluctuations in heart rate and blood pressure within the standard low-frequency range of 0.04-0.15 Hz typically occur at two frequency components rather than only at one as widely believed, and these components are not harmonically related. This new observation in humans can help explain divergent results in the literature concerning spontaneous low-frequency oscillations. It also raises methodological and computational questions regarding the usability and validity of the low-frequency spectral band when estimating sympathetic activity and baroreflex gain.
Fast and accurate spectral estimation for online detection of partial broken bar in induction motors
NASA Astrophysics Data System (ADS)
Samanta, Anik Kumar; Naha, Arunava; Routray, Aurobinda; Deb, Alok Kanti
2018-01-01
In this paper, an online and real-time system is presented for detecting partial broken rotor bar (BRB) of inverter-fed squirrel cage induction motors under light load condition. This system with minor modifications can detect any fault that affects the stator current. A fast and accurate spectral estimator based on the theory of Rayleigh quotient is proposed for detecting the spectral signature of BRB. The proposed spectral estimator can precisely determine the relative amplitude of fault sidebands and has low complexity compared to available high-resolution subspace-based spectral estimators. Detection of low-amplitude fault components has been improved by removing the high-amplitude fundamental frequency using an extended-Kalman based signal conditioner. Slip is estimated from the stator current spectrum for accurate localization of the fault component. Complexity and cost of sensors are minimal as only a single-phase stator current is required. The hardware implementation has been carried out on an Intel i7 based embedded target ported through the Simulink Real-Time. Evaluation of threshold and detectability of faults with different conditions of load and fault severity are carried out with empirical cumulative distribution function.
Kopriva, Ivica; Persin, Antun; Puizina-Ivić, Neira; Mirić, Lina
2010-07-02
This study was designed to demonstrate robust performance of the novel dependent component analysis (DCA)-based approach to demarcation of the basal cell carcinoma (BCC) through unsupervised decomposition of the red-green-blue (RGB) fluorescent image of the BCC. Robustness to intensity fluctuation is due to the scale invariance property of DCA algorithms, which exploit spectral and spatial diversities between the BCC and the surrounding tissue. Used filtering-based DCA approach represents an extension of the independent component analysis (ICA) and is necessary in order to account for statistical dependence that is induced by spectral similarity between the BCC and surrounding tissue. This generates weak edges what represents a challenge for other segmentation methods as well. By comparative performance analysis with state-of-the-art image segmentation methods such as active contours (level set), K-means clustering, non-negative matrix factorization, ICA and ratio imaging we experimentally demonstrate good performance of DCA-based BCC demarcation in two demanding scenarios where intensity of the fluorescent image has been varied almost two orders of magnitude. Copyright 2010 Elsevier B.V. All rights reserved.
A hybrid spatial-spectral denoising method for infrared hyperspectral images using 2DPCA
NASA Astrophysics Data System (ADS)
Huang, Jun; Ma, Yong; Mei, Xiaoguang; Fan, Fan
2016-11-01
The traditional noise reduction methods for 3-D infrared hyperspectral images typically operate independently in either the spatial or spectral domain, and such methods overlook the relationship between the two domains. To address this issue, we propose a hybrid spatial-spectral method in this paper to link both domains. First, principal component analysis and bivariate wavelet shrinkage are performed in the 2-D spatial domain. Second, 2-D principal component analysis transformation is conducted in the 1-D spectral domain to separate the basic components from detail ones. The energy distribution of noise is unaffected by orthogonal transformation; therefore, the signal-to-noise ratio of each component is used as a criterion to determine whether a component should be protected from over-denoising or denoised with certain 1-D denoising methods. This study implements the 1-D wavelet shrinking threshold method based on Stein's unbiased risk estimator, and the quantitative results on publicly available datasets demonstrate that our method can improve denoising performance more effectively than other state-of-the-art methods can.
Component separation of a isotropic Gravitational Wave Background
DOE Office of Scientific and Technical Information (OSTI.GOV)
Parida, Abhishek; Jhingan, Sanjay; Mitra, Sanjit, E-mail: abhishek@jmi.ac.in, E-mail: sanjit@iucaa.in, E-mail: sjhingan@jmi.ac.in
2016-04-01
A Gravitational Wave Background (GWB) is expected in the universe from the superposition of a large number of unresolved astrophysical sources and phenomena in the early universe. Each component of the background (e.g., from primordial metric perturbations, binary neutron stars, milli-second pulsars etc.) has its own spectral shape. Many ongoing experiments aim to probe GWB at a variety of frequency bands. In the last two decades, using data from ground-based laser interferometric gravitational wave (GW) observatories, upper limits on GWB were placed in the frequency range of 0∼ 50−100 Hz, considering one spectral shape at a time. However, one strong componentmore » can significantly enhance the estimated strength of another component. Hence, estimation of the amplitudes of the components with different spectral shapes should be done jointly. Here we propose a method for 'component separation' of a statistically isotropic background, that can, for the first time, jointly estimate the amplitudes of many components and place upper limits. The method is rather straightforward and needs negligible amount of computation. It utilises the linear relationship between the measurements and the amplitudes of the actual components, alleviating the need for a sampling based method, e.g., Markov Chain Monte Carlo (MCMC) or matched filtering, which are computationally intensive and cumbersome in a multi-dimensional parameter space. Using this formalism we could also study how many independent components can be separated using a given dataset from a network of current and upcoming ground based interferometric detectors.« less
Short-Term EEG Spectral Pattern as a Single Event in EEG Phenomenology
Fingelkurts, Al. A; Fingelkurts, An. A
2010-01-01
Spectral decomposition, to this day, still remains the main analytical paradigm for the analysis of EEG oscillations. However, conventional spectral analysis assesses the mean characteristics of the EEG power spectra averaged out over extended periods of time and/or broad frequency bands, thus resulting in a “static” picture which cannot reflect adequately the underlying neurodynamic. A relatively new promising area in the study of EEG is based on reducing the signal to elementary short-term spectra of various types in accordance with the number of types of EEG stationary segments instead of using averaged power spectrum for the whole EEG. It is suggested that the various perceptual and cognitive operations associated with a mental or behavioural condition constitute a single distinguishable neurophysiological state with a distinct and reliable spectral pattern. In this case, one type of short-term spectral pattern may be considered as a single event in EEG phenomenology. To support this assumption the following issues are considered in detail: (a) the relations between local EEG short-term spectral pattern of particular type and the actual state of the neurons in underlying network and a volume conduction; (b) relationship between morphology of EEG short-term spectral pattern and the state of the underlying neurodynamical system i.e. neuronal assembly; (c) relation of different spectral pattern components to a distinct physiological mechanism; (d) relation of different spectral pattern components to different functional significance; (e) developmental changes of spectral pattern components; (f) heredity of the variance in the individual spectral pattern and its components; (g) intra-individual stability of the sets of EEG short-term spectral patterns and their percent ratio; (h) discrete dynamics of EEG short-term spectral patterns. Functional relevance (consistency) of EEG short-term spectral patterns in accordance with the changes of brain functional state, cognitive task and with different neuropsychopathologies is demonstrated. PMID:21379390
Astrometric Discovery of GJ 164B
NASA Technical Reports Server (NTRS)
Pravdo, Steven H.; Shaklan, Stuart B.; Henry, Todd; Benedict, G. Fritz
2004-01-01
We discovered a low-mass companion to the M dwarf GJ 164 with the CCD-based imaging system of the Stellar Planet Survey astrometric program. The existence of GJ 164B was confirmed with Hubble Space Telescope NICMOS imaging observations. A high-dispersion spectral observation in V sets a lower limit of Deltam > 2.2 mag between the two components of the system. Based on our parallax value of 82 +/- 8 mas, we derive the following orbital parameters: P = 2.04 +/- 0.03 yr, a = 103 +/- 0.03, and M-total 0.265 +/- 0.020 M-circle dot. The component masses are M-A = 0.170 +/- 0.015 M-circle dot and M-B = 0.095 +/- 0/015 M-circle dot. Based on its mass, colors, and spectral properties, GJ 164B has spectral type M6-M8 V.
Multispectral processing without spectra.
Drew, Mark S; Finlayson, Graham D
2003-07-01
It is often the case that multiplications of whole spectra, component by component, must be carried out,for example when light reflects from or is transmitted through materials. This leads to particularly taxing calculations, especially in spectrally based ray tracing or radiosity in graphics, making a full-spectrum method prohibitively expensive. Nevertheless, using full spectra is attractive because of the many important phenomena that can be modeled only by using all the physics at hand. We apply to the task of spectral multiplication a method previously used in modeling RGB-based light propagation. We show that we can often multiply spectra without carrying out spectral multiplication. In previous work [J. Opt. Soc. Am. A 11, 1553 (1994)] we developed a method called spectral sharpening, which took camera RGBs to a special sharp basis that was designed to render illuminant change simple to model. Specifically, in the new basis, one can effectively model illuminant change by using a diagonal matrix rather than the 3 x 3 linear transform that results from a three-component finite-dimensional model [G. Healey and D. Slater, J. Opt. Soc. Am. A 11, 3003 (1994)]. We apply this idea of sharpening to the set of principal components vectors derived from a representative set of spectra that might reasonably be encountered in a given application. With respect to the sharp spectral basis, we show that spectral multiplications can be modeled as the multiplication of the basis coefficients. These new product coefficients applied to the sharp basis serve to accurately reconstruct the spectral product. Although the method is quite general, we show how to use spectral modeling by taking advantage of metameric surfaces, ones that match under one light but not another, for tasks such as volume rendering. The use of metamers allows a user to pick out or merge different volume structures in real time simply by changing the lighting.
Multispectral processing without spectra
NASA Astrophysics Data System (ADS)
Drew, Mark S.; Finlayson, Graham D.
2003-07-01
It is often the case that multiplications of whole spectra, component by component, must be carried out, for example when light reflects from or is transmitted through materials. This leads to particularly taxing calculations, especially in spectrally based ray tracing or radiosity in graphics, making a full-spectrum method prohibitively expensive. Nevertheless, using full spectra is attractive because of the many important phenomena that can be modeled only by using all the physics at hand. We apply to the task of spectral multiplication a method previously used in modeling RGB-based light propagation. We show that we can often multiply spectra without carrying out spectral multiplication. In previous work J. Opt. Soc. Am. A 11 , 1553 (1994) we developed a method called spectral sharpening, which took camera RGBs to a special sharp basis that was designed to render illuminant change simple to model. Specifically, in the new basis, one can effectively model illuminant change by using a diagonal matrix rather than the 33 linear transform that results from a three-component finite-dimensional model G. Healey and D. Slater, J. Opt. Soc. Am. A 11 , 3003 (1994). We apply this idea of sharpening to the set of principal components vectors derived from a representative set of spectra that might reasonably be encountered in a given application. With respect to the sharp spectral basis, we show that spectral multiplications can be modeled as the multiplication of the basis coefficients. These new product coefficients applied to the sharp basis serve to accurately reconstruct the spectral product. Although the method is quite general, we show how to use spectral modeling by taking advantage of metameric surfaces, ones that match under one light but not another, for tasks such as volume rendering. The use of metamers allows a user to pick out or merge different volume structures in real time simply by changing the lighting. 2003 Optical Society of America
Pepper seed variety identification based on visible/near-infrared spectral technology
NASA Astrophysics Data System (ADS)
Li, Cuiling; Wang, Xiu; Meng, Zhijun; Fan, Pengfei; Cai, Jichen
2016-11-01
Pepper is a kind of important fruit vegetable, with the expansion of pepper hybrid planting area, detection of pepper seed purity is especially important. This research used visible/near infrared (VIS/NIR) spectral technology to detect the variety of single pepper seed, and chose hybrid pepper seeds "Zhuo Jiao NO.3", "Zhuo Jiao NO.4" and "Zhuo Jiao NO.5" as research sample. VIS/NIR spectral data of 80 "Zhuo Jiao NO.3", 80 "Zhuo Jiao NO.4" and 80 "Zhuo Jiao NO.5" pepper seeds were collected, and the original spectral data was pretreated with standard normal variable (SNV) transform, first derivative (FD), and Savitzky-Golay (SG) convolution smoothing methods. Principal component analysis (PCA) method was adopted to reduce the dimension of the spectral data and extract principal components, according to the distribution of the first principal component (PC1) along with the second principal component(PC2) in the twodimensional plane, similarly, the distribution of PC1 coupled with the third principal component(PC3), and the distribution of PC2 combined with PC3, distribution areas of three varieties of pepper seeds were divided in each twodimensional plane, and the discriminant accuracy of PCA was tested through observing the distribution area of samples' principal components in validation set. This study combined PCA and linear discriminant analysis (LDA) to identify single pepper seed varieties, results showed that with the FD preprocessing method, the discriminant accuracy of pepper seed varieties was 98% for validation set, it concludes that using VIS/NIR spectral technology is feasible for identification of single pepper seed varieties.
NASA Astrophysics Data System (ADS)
Li, Cuiling; Jiang, Kai; Zhao, Xueguan; Fan, Pengfei; Wang, Xiu; Liu, Chuan
2017-10-01
Impurity of melon seeds variety will cause reductions of melon production and economic benefits of farmers, this research aimed to adopt spectral technology combined with chemometrics methods to identify melon seeds variety. Melon seeds whose varieties were "Yi Te Bai", "Yi Te Jin", "Jing Mi NO.7", "Jing Mi NO.11" and " Yi Li Sha Bai "were used as research samples. A simple spectral system was developed to collect reflective spectral data of melon seeds, including a light source unit, a spectral data acquisition unit and a data processing unit, the detection wavelength range of this system was 200-1100nm with spectral resolution of 0.14 7.7nm. The original reflective spectral data was pre-treated with de-trend (DT), multiple scattering correction (MSC), first derivative (FD), normalization (NOR) and Savitzky-Golay (SG) convolution smoothing methods. Principal Component Analysis (PCA) method was adopted to reduce the dimensions of reflective spectral data and extract principal components. K-nearest neighbour (KNN) and Fisher discriminant analysis (FDA) methods were used to develop discriminant models of melon seeds variety based on PCA. Spectral data pretreatments improved the discriminant effects of KNN and FDA, FDA generated better discriminant results than KNN, both KNN and FDA methods produced discriminant accuracies reaching to 90.0% for validation set. Research results showed that using spectral technology in combination with KNN and FDA modelling methods to identify melon seeds variety was feasible.
NASA Astrophysics Data System (ADS)
Kawabe, Yutaka; Yoshikawa, Toshio; Chida, Toshifumi; Tada, Kazuhiro; Kawamoto, Masuki; Fujihara, Takashi; Sassa, Takafumi; Tsutsumi, Naoto
2015-10-01
In order to analyze the spectra of inseparable chemical mixtures, many mathematical methods have been developed to decompose them into the components relevant to species from series of spectral data obtained under different conditions. We formulated a method based on singular value decomposition (SVD) of linear algebra, and applied it to two example systems of organic dyes, being successful in reproducing absorption spectra assignable to cis/trans azocarbazole dyes from the spectral data after photoisomerization and to monomer/dimer of cyanine dyes from those during photodegaradation process. For the example of photoisomerization, polymer films containing the azocarbazole dyes were prepared, which have showed updatable holographic stereogram for real images with high performance. We made continuous monitoring of absorption spectrum after optical excitation and found that their spectral shapes varied slightly after the excitation and during recovery process, of which fact suggested the contribution from a generated photoisomer. Application of the method was successful to identify two spectral components due to trans and cis forms of azocarbazoles. Temporal evolution of their weight factors suggested important roles of long lifetimed cis states in azocarbazole derivatives. We also applied the method to the photodegradation of cyanine dyes doped in DNA-lipid complexes which have shown efficient and durable optical amplification and/or lasing under optical pumping. The same SVD method was successful in the extraction of two spectral components presumably due to monomer and H-type dimer. During the photodegradation process, absorption magnitude gradually decreased due to decomposition of molecules and their decaying rates strongly depended on the spectral components, suggesting that the long persistency of the dyes in DNA-complex related to weak tendency of aggregate formation.
NASA Astrophysics Data System (ADS)
Mao, Mingzhi; Qian, Chen; Cao, Bingyao; Zhang, Qianwu; Song, Yingxiong; Wang, Min
2017-09-01
A digital signal process enabled dual-drive Mach-Zehnder modulator (DD-MZM)-based spectral converter is proposed and extensively investigated to realize dynamically reconfigurable and high transparent spectral conversion. As another important innovation point of the paper, to optimize the converter performance, the optimum operation conditions of the proposed converter are deduced, statistically simulated, and experimentally verified. The optimum conditions supported-converter performances are verified by detail numerical simulations and experiments in intensity-modulation and direct-detection-based network in terms of frequency detuning range-dependent conversion efficiency, strict operation transparency for user signal characteristics, impact of parasitic components on the conversion performance, as well as the converted component waveform are almost nondistortion. It is also found that the converter has the high robustness to the input signal power, optical signal-to-noise ratio variations, extinction ratio, and driving signal frequency.
Color characterization of coatings with diffraction pigments.
Ferrero, A; Bernad, B; Campos, J; Perales, E; Velázquez, J L; Martínez-Verdú, F M
2016-10-01
Coatings with diffraction pigments present high iridescence, which needs to be characterized in order to describe their appearance. The spectral bidirectional reflectance distribution functions (BRDFs) of six coatings with SpectraFlair diffraction pigments were measured using the robot-arm-based goniospectrophotometer GEFE, designed and developed at CSIC. Principal component analysis has been applied to study the coatings of BRDF data. From data evaluation and based on theoretical considerations, we propose a relevant geometric factor to study the spectral reflectance and color gamut variation of coatings with diffraction pigments. At fixed values of this geometric factor, the spectral BRDF component due to diffraction is almost constant. Commercially available portable goniospectrophotometers, extensively used in several industries (automotive and others), should be provided with more aspecular measurement angles to characterize the complex reflectance of goniochromatic coatings based on diffraction pigments, but they would not require either more than one irradiation angle or additional out-of-plane geometries.
Spectral decomposition of asteroid Itokawa based on principal component analysis
NASA Astrophysics Data System (ADS)
Koga, Sumire C.; Sugita, Seiji; Kamata, Shunichi; Ishiguro, Masateru; Hiroi, Takahiro; Tatsumi, Eri; Sasaki, Sho
2018-01-01
The heliocentric stratification of asteroid spectral types may hold important information on the early evolution of the Solar System. Asteroid spectral taxonomy is based largely on principal component analysis. However, how the surface properties of asteroids, such as the composition and age, are projected in the principal-component (PC) space is not understood well. We decompose multi-band disk-resolved visible spectra of the Itokawa surface with principal component analysis (PCA) in comparison with main-belt asteroids. The obtained distribution of Itokawa spectra projected in the PC space of main-belt asteroids follows a linear trend linking the Q-type and S-type regions and is consistent with the results of space-weathering experiments on ordinary chondrites and olivine, suggesting that this trend may be a space-weathering-induced spectral evolution track for S-type asteroids. Comparison with space-weathering experiments also yield a short average surface age (< a few million years) for Itokawa, consistent with the cosmic-ray-exposure time of returned samples from Itokawa. The Itokawa PC score distribution exhibits asymmetry along the evolution track, strongly suggesting that space weathering has begun saturated on this young asteroid. The freshest spectrum found on Itokawa exhibits a clear sign for space weathering, indicating again that space weathering occurs very rapidly on this body. We also conducted PCA on Itokawa spectra alone and compared the results with space-weathering experiments. The obtained results indicate that the first principal component of Itokawa surface spectra is consistent with spectral change due to space weathering and that the spatial variation in the degree of space weathering is very large (a factor of three in surface age), which would strongly suggest the presence of strong regional/local resurfacing process(es) on this small asteroid.
Satellite image fusion based on principal component analysis and high-pass filtering.
Metwalli, Mohamed R; Nasr, Ayman H; Allah, Osama S Farag; El-Rabaie, S; Abd El-Samie, Fathi E
2010-06-01
This paper presents an integrated method for the fusion of satellite images. Several commercial earth observation satellites carry dual-resolution sensors, which provide high spatial resolution or simply high-resolution (HR) panchromatic (pan) images and low-resolution (LR) multi-spectral (MS) images. Image fusion methods are therefore required to integrate a high-spectral-resolution MS image with a high-spatial-resolution pan image to produce a pan-sharpened image with high spectral and spatial resolutions. Some image fusion methods such as the intensity, hue, and saturation (IHS) method, the principal component analysis (PCA) method, and the Brovey transform (BT) method provide HR MS images, but with low spectral quality. Another family of image fusion methods, such as the high-pass-filtering (HPF) method, operates on the basis of the injection of high frequency components from the HR pan image into the MS image. This family of methods provides less spectral distortion. In this paper, we propose the integration of the PCA method and the HPF method to provide a pan-sharpened MS image with superior spatial resolution and less spectral distortion. The experimental results show that the proposed fusion method retains the spectral characteristics of the MS image and, at the same time, improves the spatial resolution of the pan-sharpened image.
Methods for spectral image analysis by exploiting spatial simplicity
Keenan, Michael R.
2010-05-25
Several full-spectrum imaging techniques have been introduced in recent years that promise to provide rapid and comprehensive chemical characterization of complex samples. One of the remaining obstacles to adopting these techniques for routine use is the difficulty of reducing the vast quantities of raw spectral data to meaningful chemical information. Multivariate factor analysis techniques, such as Principal Component Analysis and Alternating Least Squares-based Multivariate Curve Resolution, have proven effective for extracting the essential chemical information from high dimensional spectral image data sets into a limited number of components that describe the spectral characteristics and spatial distributions of the chemical species comprising the sample. There are many cases, however, in which those constraints are not effective and where alternative approaches may provide new analytical insights. For many cases of practical importance, imaged samples are "simple" in the sense that they consist of relatively discrete chemical phases. That is, at any given location, only one or a few of the chemical species comprising the entire sample have non-zero concentrations. The methods of spectral image analysis of the present invention exploit this simplicity in the spatial domain to make the resulting factor models more realistic. Therefore, more physically accurate and interpretable spectral and abundance components can be extracted from spectral images that have spatially simple structure.
Methods for spectral image analysis by exploiting spatial simplicity
Keenan, Michael R.
2010-11-23
Several full-spectrum imaging techniques have been introduced in recent years that promise to provide rapid and comprehensive chemical characterization of complex samples. One of the remaining obstacles to adopting these techniques for routine use is the difficulty of reducing the vast quantities of raw spectral data to meaningful chemical information. Multivariate factor analysis techniques, such as Principal Component Analysis and Alternating Least Squares-based Multivariate Curve Resolution, have proven effective for extracting the essential chemical information from high dimensional spectral image data sets into a limited number of components that describe the spectral characteristics and spatial distributions of the chemical species comprising the sample. There are many cases, however, in which those constraints are not effective and where alternative approaches may provide new analytical insights. For many cases of practical importance, imaged samples are "simple" in the sense that they consist of relatively discrete chemical phases. That is, at any given location, only one or a few of the chemical species comprising the entire sample have non-zero concentrations. The methods of spectral image analysis of the present invention exploit this simplicity in the spatial domain to make the resulting factor models more realistic. Therefore, more physically accurate and interpretable spectral and abundance components can be extracted from spectral images that have spatially simple structure.
Harmonic component detection: Optimized Spectral Kurtosis for operational modal analysis
NASA Astrophysics Data System (ADS)
Dion, J.-L.; Tawfiq, I.; Chevallier, G.
2012-01-01
This work is a contribution in the field of Operational Modal Analysis to identify the modal parameters of mechanical structures using only measured responses. The study deals with structural responses coupled with harmonic components amplitude and frequency modulated in a short range, a common combination for mechanical systems with engines and other rotating machines in operation. These harmonic components generate misleading data interpreted erroneously by the classical methods used in OMA. The present work attempts to differentiate maxima in spectra stemming from harmonic components and structural modes. The detection method proposed is based on the so-called Optimized Spectral Kurtosis and compared with others definitions of Spectral Kurtosis described in the literature. After a parametric study of the method, a critical study is performed on numerical simulations and then on an experimental structure in operation in order to assess the method's performance.
Zhou, Yan; Cao, Hui
2013-01-01
We propose an augmented classical least squares (ACLS) calibration method for quantitative Raman spectral analysis against component information loss. The Raman spectral signals with low analyte concentration correlations were selected and used as the substitutes for unknown quantitative component information during the CLS calibration procedure. The number of selected signals was determined by using the leave-one-out root-mean-square error of cross-validation (RMSECV) curve. An ACLS model was built based on the augmented concentration matrix and the reference spectral signal matrix. The proposed method was compared with partial least squares (PLS) and principal component regression (PCR) using one example: a data set recorded from an experiment of analyte concentration determination using Raman spectroscopy. A 2-fold cross-validation with Venetian blinds strategy was exploited to evaluate the predictive power of the proposed method. The one-way variance analysis (ANOVA) was used to access the predictive power difference between the proposed method and existing methods. Results indicated that the proposed method is effective at increasing the robust predictive power of traditional CLS model against component information loss and its predictive power is comparable to that of PLS or PCR.
Hyperspectral Image Denoising Using a Nonlocal Spectral Spatial Principal Component Analysis
NASA Astrophysics Data System (ADS)
Li, D.; Xu, L.; Peng, J.; Ma, J.
2018-04-01
Hyperspectral images (HSIs) denoising is a critical research area in image processing duo to its importance in improving the quality of HSIs, which has a negative impact on object detection and classification and so on. In this paper, we develop a noise reduction method based on principal component analysis (PCA) for hyperspectral imagery, which is dependent on the assumption that the noise can be removed by selecting the leading principal components. The main contribution of paper is to introduce the spectral spatial structure and nonlocal similarity of the HSIs into the PCA denoising model. PCA with spectral spatial structure can exploit spectral correlation and spatial correlation of HSI by using 3D blocks instead of 2D patches. Nonlocal similarity means the similarity between the referenced pixel and other pixels in nonlocal area, where Mahalanobis distance algorithm is used to estimate the spatial spectral similarity by calculating the distance in 3D blocks. The proposed method is tested on both simulated and real hyperspectral images, the results demonstrate that the proposed method is superior to several other popular methods in HSI denoising.
NASA Technical Reports Server (NTRS)
Liu, Xu; Smith, William L.; Zhou, Daniel K.; Larar, Allen
2005-01-01
Modern infrared satellite sensors such as Atmospheric Infrared Sounder (AIRS), Cosmic Ray Isotope Spectrometer (CrIS), Thermal Emission Spectrometer (TES), Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS) and Infrared Atmospheric Sounding Interferometer (IASI) are capable of providing high spatial and spectral resolution infrared spectra. To fully exploit the vast amount of spectral information from these instruments, super fast radiative transfer models are needed. This paper presents a novel radiative transfer model based on principal component analysis. Instead of predicting channel radiance or transmittance spectra directly, the Principal Component-based Radiative Transfer Model (PCRTM) predicts the Principal Component (PC) scores of these quantities. This prediction ability leads to significant savings in computational time. The parameterization of the PCRTM model is derived from properties of PC scores and instrument line shape functions. The PCRTM is very accurate and flexible. Due to its high speed and compressed spectral information format, it has great potential for super fast one-dimensional physical retrievals and for Numerical Weather Prediction (NWP) large volume radiance data assimilation applications. The model has been successfully developed for the National Polar-orbiting Operational Environmental Satellite System Airborne Sounder Testbed - Interferometer (NAST-I) and AIRS instruments. The PCRTM model performs monochromatic radiative transfer calculations and is able to include multiple scattering calculations to account for clouds and aerosols.
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.
Spectrum slicer for snapshot spectral imaging
NASA Astrophysics Data System (ADS)
Tamamitsu, Miu; Kitagawa, Yutaro; Nakagawa, Keiichi; Horisaki, Ryoichi; Oishi, Yu; Morita, Shin-ya; Yamagata, Yutaka; Motohara, Kentaro; Goda, Keisuke
2015-12-01
We propose and demonstrate an optical component that overcomes critical limitations in our previously demonstrated high-speed multispectral videography-a method in which an array of periscopes placed in a prism-based spectral shaper is used to achieve snapshot multispectral imaging with the frame rate only limited by that of an image-recording sensor. The demonstrated optical component consists of a slicing mirror incorporated into a 4f-relaying lens system that we refer to as a spectrum slicer (SS). With its simple design, we can easily increase the number of spectral channels without adding fabrication complexity while preserving the capability of high-speed multispectral videography. We present a theoretical framework for the SS and its experimental utility to spectral imaging by showing real-time monitoring of a dynamic colorful event through five different visible windows.
Ferrero, Alejandro; Rabal, Ana; Campos, Joaquín; Martínez-Verdú, Francisco; Chorro, Elísabet; Perales, Esther; Pons, Alicia; Hernanz, María Luisa
2013-02-01
A reduced set of measurement geometries allows the spectral reflectance of special effect coatings to be predicted for any other geometry. A physical model based on flake-related parameters has been used to determine nonredundant measurement geometries for the complete description of the spectral bidirectional reflectance distribution function (BRDF). The analysis of experimental spectral BRDF was carried out by means of principal component analysis. From this analysis, a set of nine measurement geometries was proposed to characterize special effect coatings. It was shown that, for two different special effect coatings, these geometries provide a good prediction of their complete color shift.
Guzmán-Venegas, Rodrigo A; Palma, Felipe H; Biotti P, Jorge L; de la Rosa, Francisco J Berral
2018-06-01
To compare the frequency or spectral components between different regions of the superficial masseter in young natural dentate and total edentulous older adults rehabilitated with removable prostheses and fixed-implant support. A secondary objective was to compare these components between the three groups. 21 young natural dentate and 28 edentulous (14 with removable prostheses and 14 with fixed-implant support) were assessed. High-density surface electromyography (sEMG) was recorded in four portions of the superficial masseter during submaximal isometric bites. Spectral components were obtained through a spectral analysis of the sEMG signals. An analysis of mixed models was used to compare the spectral components. In all groups, the spectral components of the anterior portion were lower than in the posterior region (p < 0.05). Both edentulous groups showed lower spectral components and median frequency slope than the natural dentate group (p < 0.05). The removable prostheses group showed the greatest differences with natural dentate group. There were significant differences in the spectral components recorded in the different regions of the superficial masseter. The lower spectral components and fatigability of older adults rehabilitated with prostheses could be a cause of a greater loss of type II fibers, especially in the removable prostheses group. Copyright © 2018 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Abeysekara, Saman; Damiran, Daalkhaijav; Yu, Peiqiang
2013-02-01
The objectives of this study were (i) to determine lipid related molecular structures components (functional groups) in feed combination of cereal grain (barley, Hordeum vulgare) and wheat (Triticum aestivum) based dried distillers grain solubles (wheat DDGSs) from bioethanol processing at five different combination ratios using univariate and multivariate molecular spectral analyses with infrared Fourier transform molecular spectroscopy, and (ii) to correlate lipid-related molecular-functional structure spectral profile to nutrient profiles. The spectral intensity of (i) CH3 asymmetric, CH2 asymmetric, CH3 symmetric and CH2 symmetric groups, (ii) unsaturation (Cdbnd C) group, and (iii) carbonyl ester (Cdbnd O) group were determined. Spectral differences of functional groups were detected by hierarchical cluster analysis (HCA) and principal components analysis (PCA). The results showed that the combination treatments significantly inflicted modifications (P < 0.05) in nutrient profile and lipid related molecular spectral intensity (CH2 asymmetric stretching peak height, CH2 symmetric stretching peak height, ratio of CH2 to CH3 symmetric stretching peak intensity, and carbonyl peak area). Ratio of CH2 to CH3 symmetric stretching peak intensity, and carbonyl peak significantly correlated with nutrient profiles. Both PCA and HCA differentiated lipid-related spectrum. In conclusion, the changes of lipid molecular structure spectral profiles through feed combination could be detected using molecular spectroscopy. These changes were associated with nutrient profiles and functionality.
Pei, Yan-Ling; Wu, Zhi-Sheng; Shi, Xin-Yuan; Zhou, Lu-Wei; Qiao, Yan-Jiang
2014-09-01
The present paper firstly reviewed the research progress and main methods of NIR spectral assignment coupled with our research results. Principal component analysis was focused on characteristic signal extraction to reflect spectral differences. Partial least squares method was concerned with variable selection to discover characteristic absorption band. Two-dimensional correlation spectroscopy was mainly adopted for spectral assignment. Autocorrelation peaks were obtained from spectral changes, which were disturbed by external factors, such as concentration, temperature and pressure. Density functional theory was used to calculate energy from substance structure to establish the relationship between molecular energy and spectra change. Based on the above reviewed method, taking a NIR spectral assignment of chlorogenic acid as example, a reliable spectral assignment for critical quality attributes of Chinese materia medica (CMM) was established using deuterium technology and spectral variable selection. The result demonstrated the assignment consistency according to spectral features of different concentrations of chlorogenic acid and variable selection region of online NIR model in extract process. Although spectral assignment was initial using an active pharmaceutical ingredient, it is meaningful to look forward to the futurity of the complex components in CMM. Therefore, it provided methodology for NIR spectral assignment of critical quality attributes in CMM.
NASA Astrophysics Data System (ADS)
Tsukanov, A. A.; Gorbatnikov, A. V.
2018-01-01
Study of the statistical parameters of the Earth's random microseismic field makes it possible to obtain estimates of the properties and structure of the Earth's crust and upper mantle. Different approaches are used to observe and process the microseismic records, which are divided into several groups of passive seismology methods. Among them are the well-known methods of surface-wave tomography, the spectral H/ V ratio of the components in the surface wave, and microseismic sounding, currently under development, which uses the spectral ratio V/ V 0 of the vertical components between pairs of spatially separated stations. In the course of previous experiments, it became clear that these ratios are stable statistical parameters of the random field that do not depend on the properties of microseism sources. This paper proposes to expand the mentioned approach and study the possibilities for using the ratio of the horizontal components H 1/ H 2 of the microseismic field. Numerical simulation was used to study the influence of an embedded velocity inhomogeneity on the spectral ratio of the horizontal components of the random field of fundamental Rayleigh modes, based on the concept that the Earth's microseismic field is represented by these waves in a significant part of the frequency spectrum.
[Study on Application of NIR Spectral Information Screening in Identification of Maca Origin].
Wang, Yuan-zhong; Zhao, Yan-li; Zhang, Ji; Jin, Hang
2016-02-01
Medicinal and edible plant Maca is rich in various nutrients and owns great medicinal value. Based on near infrared diffuse reflectance spectra, 139 Maca samples collected from Peru and Yunnan were used to identify their geographical origins. Multiplication signal correction (MSC) coupled with second derivative (SD) and Norris derivative filter (ND) was employed in spectral pretreatment. Spectrum range (7,500-4,061 cm⁻¹) was chosen by spectrum standard deviation. Combined with principal component analysis-mahalanobis distance (PCA-MD), the appropriate number of principal components was selected as 5. Based on the spectrum range and the number of principal components selected, two abnormal samples were eliminated by modular group iterative singular sample diagnosis method. Then, four methods were used to filter spectral variable information, competitive adaptive reweighted sampling (CARS), monte carlo-uninformative variable elimination (MC-UVE), genetic algorithm (GA) and subwindow permutation analysis (SPA). The spectral variable information filtered was evaluated by model population analysis (MPA). The results showed that RMSECV(SPA) > RMSECV(CARS) > RMSECV(MC-UVE) > RMSECV(GA), were 2. 14, 2. 05, 2. 02, and 1. 98, and the spectral variables were 250, 240, 250 and 70, respectively. According to the spectral variable filtered, partial least squares discriminant analysis (PLS-DA) was used to build the model, with random selection of 97 samples as training set, and the other 40 samples as validation set. The results showed that, R²: GA > MC-UVE > CARS > SPA, RMSEC and RMSEP: GA < MC-UVE < CARS
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.
Multi-spectrometer calibration transfer based on independent component analysis.
Liu, Yan; Xu, Hao; Xia, Zhenzhen; Gong, Zhiyong
2018-02-26
Calibration transfer is indispensable for practical applications of near infrared (NIR) spectroscopy due to the need for precise and consistent measurements across different spectrometers. In this work, a method for multi-spectrometer calibration transfer is described based on independent component analysis (ICA). A spectral matrix is first obtained by aligning the spectra measured on different spectrometers. Then, by using independent component analysis, the aligned spectral matrix is decomposed into the mixing matrix and the independent components of different spectrometers. These differing measurements between spectrometers can then be standardized by correcting the coefficients within the independent components. Two NIR datasets of corn and edible oil samples measured with three and four spectrometers, respectively, were used to test the reliability of this method. The results of both datasets reveal that spectra measurements across different spectrometers can be transferred simultaneously and that the partial least squares (PLS) models built with the measurements on one spectrometer can predict that the spectra can be transferred correctly on another.
Optimal wavelength band clustering for multispectral iris recognition.
Gong, Yazhuo; Zhang, David; Shi, Pengfei; Yan, Jingqi
2012-07-01
This work explores the possibility of clustering spectral wavelengths based on the maximum dissimilarity of iris textures. The eventual goal is to determine how many bands of spectral wavelengths will be enough for iris multispectral fusion and to find these bands that will provide higher performance of iris multispectral recognition. A multispectral acquisition system was first designed for imaging the iris at narrow spectral bands in the range of 420 to 940 nm. Next, a set of 60 human iris images that correspond to the right and left eyes of 30 different subjects were acquired for an analysis. Finally, we determined that 3 clusters were enough to represent the 10 feature bands of spectral wavelengths using the agglomerative clustering based on two-dimensional principal component analysis. The experimental results suggest (1) the number, center, and composition of clusters of spectral wavelengths and (2) the higher performance of iris multispectral recognition based on a three wavelengths-bands fusion.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bottacini, E.; Schady, P.; Rau, A.
1ES 1959+650 is one of the most remarkable high-peaked BL Lacertae objects (HBL). In 2002, it exhibited a TeV {gamma}-ray flare without a similar brightening of the synchrotron component at lower energies. This orphan TeV flare remained a mystery. We present the results of a multifrequency campaign, triggered by the INTEGRAL IBIS detection of 1ES 1959+650. Our data range from the optical to hard X-ray energies, thus covering the synchrotron and inverse-Compton components simultaneously. We observed the source with INTEGRAL, the Swift X-Ray Telescope, and the UV-Optical Telescope, and nearly simultaneously with a ground-based optical telescope. The steep spectral componentmore » at X-ray energies is most likely due to synchrotron emission, while at soft {gamma}-ray energies the hard spectral index may be interpreted as the onset of the high-energy component of the blazar spectral energy distribution (SED). This is the first clear measurement of a concave X-ray-soft {gamma}-ray spectrum for an HBL. The SED can be well modeled with a leptonic synchrotron self-Compton model. When the SED is fitted this model requires a very hard electron spectral index of q {approx} 1.85, possibly indicating the relevance of second-order Fermi acceleration.« less
Multi-layer imager design for mega-voltage spectral imaging
NASA Astrophysics Data System (ADS)
Myronakis, Marios; Hu, Yue-Houng; Fueglistaller, Rony; Wang, Adam; Baturin, Paul; Huber, Pascal; Morf, Daniel; Star-Lack, Josh; Berbeco, Ross
2018-05-01
The architecture of multi-layer imagers (MLIs) can be exploited to provide megavoltage spectral imaging (MVSPI) for specific imaging tasks. In the current work, we investigated bone suppression and gold fiducial contrast enhancement as two clinical tasks which could be improved with spectral imaging. A method based on analytical calculations that enables rapid investigation of MLI component materials and thicknesses was developed and validated against Monte Carlo computations. The figure of merit for task-specific imaging performance was the contrast-to-noise ratio (CNR) of the gold fiducial when the CNR of bone was equal to zero after a weighted subtraction of the signals obtained from each MLI layer. Results demonstrated a sharp increase in the CNR of gold when the build-up component or scintillation materials and thicknesses were modified. The potential for low-cost, prompt implementation of specific modifications (e.g. composition of the build-up component) could accelerate clinical translation of MVSPI.
Kur'yanova, E V; Zhukova, Yu D; Teplyi, D L
2017-07-01
The effects of intraperitoneal DSP-4 (N-(2-chloroethyl)-N-ethyl-2-bromobenzylamine, a noradrenergic neurotoxin) and maprotiline (an inhibitor of norepinephrine reuptake in synapses) on spectral components of heart rhythm variability were examined in outbred male and female rats treated with these agents in daily doses of 10 mg/kg for 3 days. At rest, DSP-4 elevated LF and VLF spectral components in male and female rats. Maprotiline elevated LF and VLF components in males at rest, increased HR and reduced all spectral components in resting females. Stress against the background of DSP-4 treatment sharply increased heart rate and reduced the powers of all spectral components (especially LF and VLF components). In maprotiline-treated rats, stress increased the powers of LF and VLF components. Thus, the central noradrenergic system participates in the formation of LF and VLF spectral components of heart rate variability at rest and especially during stressful stimulation, which can determine the phasic character of changes in the heart rate variability observed in stressed organism.
Spectral combination of spherical gravitational curvature boundary-value problems
NASA Astrophysics Data System (ADS)
PitoÅák, Martin; Eshagh, Mehdi; Šprlák, Michal; Tenzer, Robert; Novák, Pavel
2018-04-01
Four solutions of the spherical gravitational curvature boundary-value problems can be exploited for the determination of the Earth's gravitational potential. In this article we discuss the combination of simulated satellite gravitational curvatures, i.e., components of the third-order gravitational tensor, by merging these solutions using the spectral combination method. For this purpose, integral estimators of biased- and unbiased-types are derived. In numerical studies, we investigate the performance of the developed mathematical models for the gravitational field modelling in the area of Central Europe based on simulated satellite measurements. Firstly, we verify the correctness of the integral estimators for the spectral downward continuation by a closed-loop test. Estimated errors of the combined solution are about eight orders smaller than those from the individual solutions. Secondly, we perform a numerical experiment by considering the Gaussian noise with the standard deviation of 6.5× 10-17 m-1s-2 in the input data at the satellite altitude of 250 km above the mean Earth sphere. This value of standard deviation is equivalent to a signal-to-noise ratio of 10. Superior results with respect to the global geopotential model TIM-r5 are obtained by the spectral downward continuation of the vertical-vertical-vertical component with the standard deviation of 2.104 m2s-2, but the root mean square error is the largest and reaches 9.734 m2s-2. Using the spectral combination of all gravitational curvatures the root mean square error is more than 400 times smaller but the standard deviation reaches 17.234 m2s-2. The combination of more components decreases the root mean square error of the corresponding solutions while the standard deviations of the combined solutions do not improve as compared to the solution from the vertical-vertical-vertical component. The presented method represents a weight mean in the spectral domain that minimizes the root mean square error of the combined solutions and improves standard deviation of the solution based only on the least accurate components.
Automated road network extraction from high spatial resolution multi-spectral imagery
NASA Astrophysics Data System (ADS)
Zhang, Qiaoping
For the last three decades, the Geomatics Engineering and Computer Science communities have considered automated road network extraction from remotely-sensed imagery to be a challenging and important research topic. The main objective of this research is to investigate the theory and methodology of automated feature extraction for image-based road database creation, refinement or updating, and to develop a series of algorithms for road network extraction from high resolution multi-spectral imagery. The proposed framework for road network extraction from multi-spectral imagery begins with an image segmentation using the k-means algorithm. This step mainly concerns the exploitation of the spectral information for feature extraction. The road cluster is automatically identified using a fuzzy classifier based on a set of predefined road surface membership functions. These membership functions are established based on the general spectral signature of road pavement materials and the corresponding normalized digital numbers on each multi-spectral band. Shape descriptors of the Angular Texture Signature are defined and used to reduce the misclassifications between roads and other spectrally similar objects (e.g., crop fields, parking lots, and buildings). An iterative and localized Radon transform is developed for the extraction of road centerlines from the classified images. The purpose of the transform is to accurately and completely detect the road centerlines. It is able to find short, long, and even curvilinear lines. The input image is partitioned into a set of subset images called road component images. An iterative Radon transform is locally applied to each road component image. At each iteration, road centerline segments are detected based on an accurate estimation of the line parameters and line widths. Three localization approaches are implemented and compared using qualitative and quantitative methods. Finally, the road centerline segments are grouped into a road network. The extracted road network is evaluated against a reference dataset using a line segment matching algorithm. The entire process is unsupervised and fully automated. Based on extensive experimentation on a variety of remotely-sensed multi-spectral images, the proposed methodology achieves a moderate success in automating road network extraction from high spatial resolution multi-spectral imagery.
Spatial-spectral preprocessing for endmember extraction on GPU's
NASA Astrophysics Data System (ADS)
Jimenez, Luis I.; Plaza, Javier; Plaza, Antonio; Li, Jun
2016-10-01
Spectral unmixing is focused in the identification of spectrally pure signatures, called endmembers, and their corresponding abundances in each pixel of a hyperspectral image. Mainly focused on the spectral information contained in the hyperspectral images, endmember extraction techniques have recently included spatial information to achieve more accurate results. Several algorithms have been developed for automatic or semi-automatic identification of endmembers using spatial and spectral information, including the spectral-spatial endmember extraction (SSEE) where, within a preprocessing step in the technique, both sources of information are extracted from the hyperspectral image and equally used for this purpose. Previous works have implemented the SSEE technique in four main steps: 1) local eigenvectors calculation in each sub-region in which the original hyperspectral image is divided; 2) computation of the maxima and minima projection of all eigenvectors over the entire hyperspectral image in order to obtain a candidates pixels set; 3) expansion and averaging of the signatures of the candidate set; 4) ranking based on the spectral angle distance (SAD). The result of this method is a list of candidate signatures from which the endmembers can be extracted using various spectral-based techniques, such as orthogonal subspace projection (OSP), vertex component analysis (VCA) or N-FINDR. Considering the large volume of data and the complexity of the calculations, there is a need for efficient implementations. Latest- generation hardware accelerators such as commodity graphics processing units (GPUs) offer a good chance for improving the computational performance in this context. In this paper, we develop two different implementations of the SSEE algorithm using GPUs. Both are based on the eigenvectors computation within each sub-region of the first step, one using the singular value decomposition (SVD) and another one using principal component analysis (PCA). Based on our experiments with hyperspectral data sets, high computational performance is observed in both cases.
Spectral calibration of the fluorescence telescopes of the Pierre Auger Observatory
NASA Astrophysics Data System (ADS)
Aab, A.; Abreu, P.; Aglietta, M.; Al Samarai, I.; Albuquerque, I. F. M.; Allekotte, I.; Almela, A.; Alvarez Castillo, J.; Alvarez-Muñiz, J.; Anastasi, G. A.; Anchordoqui, L.; Andrada, B.; Andringa, S.; Aramo, C.; Arqueros, F.; Arsene, N.; Asorey, H.; Assis, P.; Aublin, J.; Avila, G.; Badescu, A. M.; Balaceanu, A.; Barbato, F.; Barreira Luz, R. J.; Beatty, J. J.; Becker, K. H.; Bellido, J. A.; Berat, C.; Bertaina, M. E.; Biermann, P. L.; Biteau, J.; Blaess, S. G.; Blanco, A.; Blazek, J.; Bleve, C.; Boháčová, M.; Boncioli, D.; Bonifazi, C.; Borodai, N.; Botti, A. M.; Brack, J.; Brancus, I.; Bretz, T.; Bridgeman, A.; Briechle, F. L.; Buchholz, P.; Bueno, A.; Buitink, S.; Buscemi, M.; Caballero-Mora, K. S.; Caccianiga, L.; Cancio, A.; Canfora, F.; Caramete, L.; Caruso, R.; Castellina, A.; Catalani, F.; Cataldi, G.; Cazon, L.; Chavez, A. G.; Chinellato, J. A.; Chudoba, J.; Clay, R. W.; Cobos, A.; Colalillo, R.; Coleman, A.; Collica, L.; Coluccia, M. R.; Conceição, R.; Consolati, G.; Contreras, F.; Cooper, M. J.; Coutu, S.; Covault, C. E.; Cronin, J.; D'Amico, S.; Daniel, B.; Dasso, S.; Daumiller, K.; Dawson, B. R.; de Almeida, R. M.; de Jong, S. J.; De Mauro, G.; de Mello Neto, J. R. T.; De Mitri, I.; de Oliveira, J.; de Souza, V.; Debatin, J.; Deligny, O.; Díaz Castro, M. L.; Diogo, F.; Dobrigkeit, C.; D'Olivo, J. C.; Dorosti, Q.; dos Anjos, R. C.; Dova, M. T.; Dundovic, A.; Ebr, J.; Engel, R.; Erdmann, M.; Erfani, M.; Escobar, C. O.; Espadanal, J.; Etchegoyen, A.; Falcke, H.; Farmer, J.; Farrar, G.; Fauth, A. C.; Fazzini, N.; Fenu, F.; Fick, B.; Figueira, J. M.; Filipčič, A.; Fratu, O.; Freire, M. M.; Fujii, T.; Fuster, A.; Gaior, R.; García, B.; Garcia-Pinto, D.; Gaté, F.; Gemmeke, H.; Gherghel-Lascu, A.; Giaccari, U.; Giammarchi, M.; Giller, M.; Głas, D.; Glaser, C.; Golup, G.; Gómez Berisso, M.; Gómez Vitale, P. F.; González, N.; Gookin, B.; Gorgi, A.; Gorham, P.; Grillo, A. F.; Grubb, T. D.; Guarino, F.; Guedes, G. P.; Halliday, R.; Hampel, M. R.; Hansen, P.; Harari, D.; Harrison, T. A.; Harton, J. L.; Haungs, A.; Hebbeker, T.; Heck, D.; Heimann, P.; Herve, A. E.; Hill, G. C.; Hojvat, C.; Holt, E.; Homola, P.; Hörandel, J. R.; Horvath, P.; Hrabovský, M.; Huege, T.; Hulsman, J.; Insolia, A.; Isar, P. G.; Jandt, I.; Johnsen, J. A.; Josebachuili, M.; Jurysek, J.; Kääpä, A.; Kambeitz, O.; Kampert, K. H.; Keilhauer, B.; Kemmerich, N.; Kemp, E.; Kemp, J.; Kieckhafer, R. M.; Klages, H. O.; Kleifges, M.; Kleinfeller, J.; Krause, R.; Krohm, N.; Kuempel, D.; Kukec Mezek, G.; Kunka, N.; Kuotb Awad, A.; Lago, B. L.; LaHurd, D.; Lang, R. G.; Lauscher, M.; Legumina, R.; Leigui de Oliveira, M. A.; Letessier-Selvon, A.; Lhenry-Yvon, I.; Link, K.; Lo Presti, D.; Lopes, L.; López, R.; López Casado, A.; Lorek, R.; Luce, Q.; Lucero, A.; Malacari, M.; Mallamaci, M.; Mandat, D.; Mantsch, P.; Mariazzi, A. G.; Mariş, I. C.; Marsella, G.; Martello, D.; Martinez, H.; Martínez Bravo, O.; Masías Meza, J. J.; Mathes, H. J.; Mathys, S.; Matthews, J.; Matthews, J. A. J.; Matthiae, G.; Mayotte, E.; Mazur, P. O.; Medina, C.; Medina-Tanco, G.; Melo, D.; Menshikov, A.; Merenda, K.-D.; Michal, S.; Micheletti, M. I.; Middendorf, L.; Miramonti, L.; Mitrica, B.; Mockler, D.; Mollerach, S.; Montanet, F.; Morello, C.; Mostafá, M.; Müller, A. L.; Müller, G.; Muller, M. A.; Müller, S.; Mussa, R.; Naranjo, I.; Nellen, L.; Nguyen, P. H.; Niculescu-Oglinzanu, M.; Niechciol, M.; Niemietz, L.; Niggemann, T.; Nitz, D.; Nosek, D.; Novotny, V.; Nožka, L.; Núñez, L. A.; Ochilo, L.; Oikonomou, F.; Olinto, A.; Palatka, M.; Pallotta, J.; Papenbreer, P.; Parente, G.; Parra, A.; Paul, T.; Pech, M.; Pedreira, F.; Pȩkala, J.; Pelayo, R.; Peña-Rodriguez, J.; Pereira, L. A. S.; Perlin, M.; Perrone, L.; Peters, C.; Petrera, S.; Phuntsok, J.; Piegaia, R.; Pierog, T.; Pimenta, M.; Pirronello, V.; Platino, M.; Plum, M.; Porowski, C.; Prado, R. R.; Privitera, P.; Prouza, M.; Quel, E. J.; Querchfeld, S.; Quinn, S.; Ramos-Pollan, R.; Rautenberg, J.; Ravignani, D.; Ridky, J.; Riehn, F.; Risse, M.; Ristori, P.; Rizi, V.; Rodrigues de Carvalho, W.; Rodriguez Fernandez, G.; Rodriguez Rojo, J.; Rogozin, D.; Roncoroni, M. J.; Roth, M.; Roulet, E.; Rovero, A. C.; Ruehl, P.; Saffi, S. J.; Saftoiu, A.; Salamida, F.; Salazar, H.; Saleh, A.; Salesa Greus, F.; Salina, G.; Sánchez, F.; Sanchez-Lucas, P.; Santos, E. M.; Santos, E.; Sarazin, F.; Sarmento, R.; Sarmiento-Cano, C.; Sato, R.; Schauer, M.; Scherini, V.; Schieler, H.; Schimp, M.; Schmidt, D.; Scholten, O.; Schovánek, P.; Schröder, F. G.; Schröder, S.; Schulz, A.; Schumacher, J.; Sciutto, S. J.; Segreto, A.; Shadkam, A.; Shellard, R. C.; Sigl, G.; Silli, G.; Sima, O.; Śmiałkowski, A.; Šmída, R.; Snow, G. R.; Sommers, P.; Sonntag, S.; Squartini, R.; Stanca, D.; Stanič, S.; Stasielak, J.; Stassi, P.; Stolpovskiy, M.; Strafella, F.; Streich, A.; Suarez, F.; Suarez Durán, M.; Sudholz, T.; Suomijärvi, T.; Supanitsky, A. D.; Šupík, J.; Swain, J.; Szadkowski, Z.; Taboada, A.; Taborda, O. A.; Theodoro, V. M.; Timmermans, C.; Todero Peixoto, C. J.; Tomankova, L.; Tomé, B.; Torralba Elipe, G.; Travnicek, P.; Trini, M.; Ulrich, R.; Unger, M.; Urban, M.; Valdés Galicia, J. F.; Valiño, I.; Valore, L.; van Aar, G.; van Bodegom, P.; van den Berg, A. M.; van Vliet, A.; Varela, E.; Vargas Cárdenas, B.; Varner, G.; Vázquez, R. A.; Veberič, D.; Ventura, C.; Vergara Quispe, I. D.; Verzi, V.; Vicha, J.; Villaseñor, L.; Vorobiov, S.; Wahlberg, H.; Wainberg, O.; Walz, D.; Watson, A. A.; Weber, M.; Weindl, A.; Wiencke, L.; Wilczyński, H.; Wirtz, M.; Wittkowski, D.; Wundheiler, B.; Yang, L.; Yushkov, A.; Zas, E.; Zavrtanik, D.; Zavrtanik, M.; Zepeda, A.; Zimmermann, B.; Ziolkowski, M.; Zong, Z.; Zuccarello, F.; Pierre Auger Collaboration
2017-10-01
We present a novel method to measure precisely the relative spectral response of the fluorescence telescopes of the Pierre Auger Observatory. We used a portable light source based on a xenon flasher and a monochromator to measure the relative spectral efficiencies of eight telescopes in steps of 5 nm from 280 nm to 440 nm. Each point in a scan had approximately 2 nm FWHM out of the monochromator. Different sets of telescopes in the observatory have different optical components, and the eight telescopes measured represent two each of the four combinations of components represented in the observatory. We made an end-to-end measurement of the response from different combinations of optical components, and the monochromator setup allowed for more precise and complete measurements than our previous multi-wavelength calibrations. We find an overall uncertainty in the calibration of the spectral response of most of the telescopes of 1.5% for all wavelengths; the six oldest telescopes have larger overall uncertainties of about 2.2%. We also report changes in physics measurables due to the change in calibration, which are generally small.
Abeysekara, Saman; Damiran, Daalkhaijav; Yu, Peiqiang
2013-02-01
The objectives of this study were (i) to determine lipid related molecular structures components (functional groups) in feed combination of cereal grain (barley, Hordeum vulgare) and wheat (Triticum aestivum) based dried distillers grain solubles (wheat DDGSs) from bioethanol processing at five different combination ratios using univariate and multivariate molecular spectral analyses with infrared Fourier transform molecular spectroscopy, and (ii) to correlate lipid-related molecular-functional structure spectral profile to nutrient profiles. The spectral intensity of (i) CH(3) asymmetric, CH(2) asymmetric, CH(3) symmetric and CH(2) symmetric groups, (ii) unsaturation (CC) group, and (iii) carbonyl ester (CO) group were determined. Spectral differences of functional groups were detected by hierarchical cluster analysis (HCA) and principal components analysis (PCA). The results showed that the combination treatments significantly inflicted modifications (P<0.05) in nutrient profile and lipid related molecular spectral intensity (CH(2) asymmetric stretching peak height, CH(2) symmetric stretching peak height, ratio of CH(2) to CH(3) symmetric stretching peak intensity, and carbonyl peak area). Ratio of CH(2) to CH(3) symmetric stretching peak intensity, and carbonyl peak significantly correlated with nutrient profiles. Both PCA and HCA differentiated lipid-related spectrum. In conclusion, the changes of lipid molecular structure spectral profiles through feed combination could be detected using molecular spectroscopy. These changes were associated with nutrient profiles and functionality. Copyright © 2012 Elsevier B.V. All rights reserved.
Fusion of multi-spectral and panchromatic images based on 2D-PWVD and SSIM
NASA Astrophysics Data System (ADS)
Tan, Dongjie; Liu, Yi; Hou, Ruonan; Xue, Bindang
2016-03-01
A combined method using 2D pseudo Wigner-Ville distribution (2D-PWVD) and structural similarity(SSIM) index is proposed for fusion of low resolution multi-spectral (MS) image and high resolution panchromatic (PAN) image. First, the intensity component of multi-spectral image is extracted with generalized IHS transform. Then, the spectrum diagrams of the intensity components of multi-spectral image and panchromatic image are obtained with 2D-PWVD. Different fusion rules are designed for different frequency information of the spectrum diagrams. SSIM index is used to evaluate the high frequency information of the spectrum diagrams for assigning the weights in the fusion processing adaptively. After the new spectrum diagram is achieved according to the fusion rule, the final fusion image can be obtained by inverse 2D-PWVD and inverse GIHS transform. Experimental results show that, the proposed method can obtain high quality fusion images.
Identification of mineral compositions in some renal calculi by FT Raman and IR spectral analysis
NASA Astrophysics Data System (ADS)
Tonannavar, J.; Deshpande, Gouri; Yenagi, Jayashree; Patil, Siddanagouda B.; Patil, Nikhil A.; Mulimani, B. G.
2016-02-01
We present in this paper accurate and reliable Raman and IR spectral identification of mineral constituents in nine samples of renal calculi (kidney stones) removed from patients suffering from nephrolithiasis. The identified mineral components include Calcium Oxalate Monohydrate (COM, whewellite), Calcium Oxalate Dihydrate (COD, weddellite), Magnesium Ammonium Phosphate Hexahydrate (MAPH, struvite), Calcium Hydrogen Phosphate Dihydrate (CHPD, brushite), Pentacalcium Hydroxy Triphosphate (PCHT, hydroxyapatite) and Uric Acid (UA). The identification is based on a satisfactory assignment of all the observed IR and Raman bands (3500-400 cm- 1) to chemical functional groups of mineral components in the samples, aided by spectral analysis of pure materials of COM, MAPH, CHPD and UA. It is found that the eight samples are composed of COM as the common component, the other mineral species as common components are: MAPH in five samples, PCHT in three samples, COD in three samples, UA in three samples and CHPD in two samples. One sample is wholly composed of UA as a single component; this inference is supported by the good agreement between ab initio density functional theoretical spectra and experimental spectral measurements of both sample and pure material. A combined application of Raman and IR techniques has shown that, where the IR is ambiguous, the Raman analysis can differentiate COD from COM and PCHT from MAPH.
Identification of mineral compositions in some renal calculi by FT Raman and IR spectral analysis.
Tonannavar, J; Deshpande, Gouri; Yenagi, Jayashree; Patil, Siddanagouda B; Patil, Nikhil A; Mulimani, B G
2016-02-05
We present in this paper accurate and reliable Raman and IR spectral identification of mineral constituents in nine samples of renal calculi (kidney stones) removed from patients suffering from nephrolithiasis. The identified mineral components include Calcium Oxalate Monohydrate (COM, whewellite), Calcium Oxalate Dihydrate (COD, weddellite), Magnesium Ammonium Phosphate Hexahydrate (MAPH, struvite), Calcium Hydrogen Phosphate Dihydrate (CHPD, brushite), Pentacalcium Hydroxy Triphosphate (PCHT, hydroxyapatite) and Uric Acid (UA). The identification is based on a satisfactory assignment of all the observed IR and Raman bands (3500-400c m(-1)) to chemical functional groups of mineral components in the samples, aided by spectral analysis of pure materials of COM, MAPH, CHPD and UA. It is found that the eight samples are composed of COM as the common component, the other mineral species as common components are: MAPH in five samples, PCHT in three samples, COD in three samples, UA in three samples and CHPD in two samples. One sample is wholly composed of UA as a single component; this inference is supported by the good agreement between ab initio density functional theoretical spectra and experimental spectral measurements of both sample and pure material. A combined application of Raman and IR techniques has shown that, where the IR is ambiguous, the Raman analysis can differentiate COD from COM and PCHT from MAPH. Copyright © 2015 Elsevier B.V. All rights reserved.
Ferrero, Alejandro; Rabal, Ana María; Campos, Joaquín; Pons, Alicia; Hernanz, María Luisa
2012-06-01
A type of representation of the spectral bidirectional reflectance distribution function (BRDF) is proposed that distinctly separates the spectral variable (wavelength) from the geometrical variables (spherical coordinates of the irradiation and viewing directions). Principal components analysis (PCA) is used in order to decompose the spectral BRDF in decorrelated spectral components, and the weight that they have at every geometrical configuration of irradiation/viewing is established. This method was applied to the spectral BRDF measurement of a special effect pigment sample, and four principal components with relevant variance were identified. These four components are enough to reproduce the great diversity of spectral reflectances observed at different geometrical configurations. Since this representation is able to separate spectral and geometrical variables, it facilitates the interpretation of the color variation of special effect pigments coatings versus the geometrical configuration of irradiation/viewing.
3D tensor-based blind multispectral image decomposition for tumor demarcation
NASA Astrophysics Data System (ADS)
Kopriva, Ivica; Peršin, Antun
2010-03-01
Blind decomposition of multi-spectral fluorescent image for tumor demarcation is formulated exploiting tensorial structure of the image. First contribution of the paper is identification of the matrix of spectral responses and 3D tensor of spatial distributions of the materials present in the image from Tucker3 or PARAFAC models of 3D image tensor. Second contribution of the paper is clustering based estimation of the number of the materials present in the image as well as matrix of their spectral profiles. 3D tensor of the spatial distributions of the materials is recovered through 3-mode multiplication of the multi-spectral image tensor and inverse of the matrix of spectral profiles. Tensor representation of the multi-spectral image preserves its local spatial structure that is lost, due to vectorization process, when matrix factorization-based decomposition methods (such as non-negative matrix factorization and independent component analysis) are used. Superior performance of the tensor-based image decomposition over matrix factorization-based decompositions is demonstrated on experimental red-green-blue (RGB) image with known ground truth as well as on RGB fluorescent images of the skin tumor (basal cell carcinoma).
Fixed Pattern Noise pixel-wise linear correction for crime scene imaging CMOS sensor
NASA Astrophysics Data System (ADS)
Yang, Jie; Messinger, David W.; Dube, Roger R.; Ientilucci, Emmett J.
2017-05-01
Filtered multispectral imaging technique might be a potential method for crime scene documentation and evidence detection due to its abundant spectral information as well as non-contact and non-destructive nature. Low-cost and portable multispectral crime scene imaging device would be highly useful and efficient. The second generation crime scene imaging system uses CMOS imaging sensor to capture spatial scene and bandpass Interference Filters (IFs) to capture spectral information. Unfortunately CMOS sensors suffer from severe spatial non-uniformity compared to CCD sensors and the major cause is Fixed Pattern Noise (FPN). IFs suffer from "blue shift" effect and introduce spatial-spectral correlated errors. Therefore, Fixed Pattern Noise (FPN) correction is critical to enhance crime scene image quality and is also helpful for spatial-spectral noise de-correlation. In this paper, a pixel-wise linear radiance to Digital Count (DC) conversion model is constructed for crime scene imaging CMOS sensor. Pixel-wise conversion gain Gi,j and Dark Signal Non-Uniformity (DSNU) Zi,j are calculated. Also, conversion gain is divided into four components: FPN row component, FPN column component, defects component and effective photo response signal component. Conversion gain is then corrected to average FPN column and row components and defects component so that the sensor conversion gain is uniform. Based on corrected conversion gain and estimated image incident radiance from the reverse of pixel-wise linear radiance to DC model, corrected image spatial uniformity can be enhanced to 7 times as raw image, and the bigger the image DC value within its dynamic range, the better the enhancement.
Guo, Tong; Chen, Zhuo; Li, Minghui; Wu, Juhong; Fu, Xing; Hu, Xiaotang
2018-04-20
Based on white-light spectral interferometry and the Linnik microscopic interference configuration, the nonlinear phase components of the spectral interferometric signal were analyzed for film thickness measurement. The spectral interferometric signal was obtained using a Linnik microscopic white-light spectral interferometer, which includes the nonlinear phase components associated with the effective thickness, the nonlinear phase error caused by the double-objective lens, and the nonlinear phase of the thin film itself. To determine the influence of the effective thickness, a wavelength-correction method was proposed that converts the effective thickness into a constant value; the nonlinear phase caused by the effective thickness can then be determined and subtracted from the total nonlinear phase. A method for the extraction of the nonlinear phase error caused by the double-objective lens was also proposed. Accurate thickness measurement of a thin film can be achieved by fitting the nonlinear phase of the thin film after removal of the nonlinear phase caused by the effective thickness and by the nonlinear phase error caused by the double-objective lens. The experimental results demonstrated that both the wavelength-correction method and the extraction method for the nonlinear phase error caused by the double-objective lens improve the accuracy of film thickness measurements.
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…
Membrane Electrical Noise in Chara corallina1
Ross, Stephen; Dainty, Jack
1986-01-01
Certain inhibitors have been found to affect the low frequency spectral component of the electrical noise power spectrum in Chara corallina. Application of the ATPase inhibitor N,N′-dicyclohexylcarbodiimide removed the low frequency spectral component, strengthening the case that the component is produced by active proton pumping. Cytocholasin B, which inhibits cyclosis in internodes of C. corallina, removed the low frequency spectral component in a time-dependent fashion which was correlated with the cessation of streaming. The protonophore carbonyl cyanide m-chlorophenylhydrazone did not produce consistent effects on the low frequency spectral component in these cells. PMID:16664898
Wei, Feifei; Ito, Kengo; Sakata, Kenji; Date, Yasuhiro; Kikuchi, Jun
2015-03-03
Extracting useful information from high dimensionality and large data sets is a major challenge for data-driven approaches. The present study was aimed at developing novel integrated analytical strategies for comprehensively characterizing seaweed similarities based on chemical diversity. The chemical compositions of 107 seaweed and 2 seagrass samples were analyzed using multiple techniques, including Fourier transform infrared (FT-IR) and solid- and solution-state nuclear magnetic resonance (NMR) spectroscopy, thermogravimetry-differential thermal analysis (TG-DTA), inductively coupled plasma-optical emission spectrometry (ICP-OES), CHNS/O total elemental analysis, and isotope ratio mass spectrometry (IR-MS). The spectral data were preprocessed using non-negative matrix factorization (NMF) and NMF combined with multivariate curve resolution-alternating least-squares (MCR-ALS) methods in order to separate individual component information from the overlapping and/or broad spectral peaks. Integrated analysis of the preprocessed chemical data demonstrated distinct discrimination of differential seaweed species. Further network analysis revealed a close correlation between the heavy metal elements and characteristic components of brown algae, such as cellulose, alginic acid, and sulfated mucopolysaccharides, providing a componential basis for its metal-sorbing potential. These results suggest that this integrated analytical strategy is useful for extracting and identifying the chemical characteristics of diverse seaweeds based on large chemical data sets, particularly complicated overlapping spectral data.
Analysis of the Zeeman effect on D α spectra on the EAST tokamak
NASA Astrophysics Data System (ADS)
Gao, Wei; Huang, Juan; Wu, Chengrui; Xu, Zong; Hou, Yumei; Jin, Zhao; Chen, Yingjie; Zhang, Pengfei; Zhang, Ling; Wu, Zhenwei; EAST Team
2017-04-01
Based on the passive spectroscopy, the {{{D}}}α atomic emission spectra in the boundary region of the plasma have been measured by a high resolution optical spectroscopic multichannel analysis (OSMA) system in EAST tokamak. The Zeeman splitting of the {{{D}}}α spectral lines has been observed. A fitting procedure by using a nonlinear least squares method was applied to fit and analyze all polarization π and +/- σ components of the {{{D}}}α atomic spectra to acquire the information of the local plasma. The spectral line shape was investigated according to emission spectra from different regions (e.g., low-field side and high-field side) along the viewing chords. Each polarization component was fitted and classified into three energy categories (the cold, warm, and hot components) based on different atomic production processes, in consistent with the transition energy distribution by calculating the gradient of the {{{D}}}α spectral profile. The emission position, magnetic field intensity, and flow velocity of a deuterium atom were also discussed in the context. Project supported by the National Natural Science Foundation of China (Grant Nos. 11275231 and 11575249) and the National Magnetic Confinement Fusion Energy Research Program of China (Grant No. 2015GB110005).
NASA Technical Reports Server (NTRS)
Fichtl, G. H.; Holland, R. L.
1978-01-01
A stochastic model of spacecraft motion was developed based on the assumption that the net torque vector due to crew activity and rocket thruster firings is a statistically stationary Gaussian vector process. The process had zero ensemble mean value, and the components of the torque vector were mutually stochastically independent. The linearized rigid-body equations of motion were used to derive the autospectral density functions of the components of the spacecraft rotation vector. The cross-spectral density functions of the components of the rotation vector vanish for all frequencies so that the components of rotation were mutually stochastically independent. The autospectral and cross-spectral density functions of the induced gravity environment imparted to scientific apparatus rigidly attached to the spacecraft were calculated from the rotation rate spectral density functions via linearized inertial frame to body-fixed principal axis frame transformation formulae. The induced gravity process was a Gaussian one with zero mean value. Transformation formulae were used to rotate the principal axis body-fixed frame to which the rotation rate and induced gravity vector were referred to a body-fixed frame in which the components of the induced gravity vector were stochastically independent. Rice's theory of exceedances was used to calculate expected exceedance rates of the components of the rotation and induced gravity vector processes.
NASA Astrophysics Data System (ADS)
Voitsekhovskaya, O. K.; Egorov, O. V.; Kashirskii, D. E.; Shefer, O. V.
2015-11-01
Calculated absorption spectra of the mixture of gases (H2O, CO, CO2, NO, NO2, and SO2) and aerosol (soot and Al2O3), contained in the exhausts of aircraft and rocket engines are demonstrated. Based on the model of gas-aerosol medium, a numerical study of the spectral dependence of the absorptance for different ratios of gas and aerosol components was carried out. The influence of microphysical and optical properties of the components of the mixture on the spectral features of absorption of gas-aerosol medium was established.
NASA Astrophysics Data System (ADS)
Polyakov, M.; Odinokov, S.
2017-05-01
The report focuses on special printing industry, which is called secure printing, which uses printing techniques to prevent forgery or falsification of security documents. The report considered the possibility of establishing a spectral device for determining the authenticity of certain documents that are protected by machine-readable luminophor labels. The device works in two spectral ranges - visible and near infrared that allows to register Stokes and anti-Stokes spectral components of protective tags. The proposed device allows verification of the authenticity of security documents based on multiple criteria in different spectral ranges. It may be used at enterprises related to the production of security printing products, expert units of law enforcement bodies at check of authenticity of banknotes and other structures.
NASA Technical Reports Server (NTRS)
Moran, M. Susan; Jackson, Ray D.; Raymond, Lee H.; Gay, Lloyd W.; Slater, Philip N.
1989-01-01
Surface energy balance components were evaluated by combining satellite-based spectral data with on-site measurements of solar irradiance, air temperature, wind speed, and vapor pressure. Maps of latent heat flux density and net radiant flux density were produced using Landsat TM data for three dates. The TM-based estimates differed from Bowen-ratio and aircraft-based estimates by less than 12 percent over mature fields of cotton, wheat, and alfalfa.
Spectral calibration of the fluorescence telescopes of the Pierre Auger Observatory
DOE Office of Scientific and Technical Information (OSTI.GOV)
Aab, A.; Abreu, P.; Aglietta, M.
We present a novel method to measure precisely the relative spectral response of the fluorescence telescopes of the Pierre Auger Observatory. Here, we used a portable light source based on a xenon flasher and a monochromator to measure the relative spectral efficiencies of eight telescopes in steps of 5 nm from 280 nm to 440 nm. Each point in a scan had approximately 2 nm FWHM out of the monochromator. Different sets of telescopes in the observatory have different optical components, and the eight telescopes measured represent two each of the four combinations of components represented in the observatory. Wemore » made an end-to-end measurement of the response from different combinations of optical components, and the monochromator setup allowed for more precise and complete measurements than our previous multi-wavelength calibrations. We find an overall uncertainty in the calibration of the spectral response of most of the telescopes of 1.5% for all wavelengths; the six oldest telescopes have larger overall uncertainties of about 2.2%. We also report changes in physics measureables due to the change in calibration, which are generally small.« less
Spectral calibration of the fluorescence telescopes of the Pierre Auger Observatory
Aab, A.; Abreu, P.; Aglietta, M.; ...
2017-09-08
We present a novel method to measure precisely the relative spectral response of the fluorescence telescopes of the Pierre Auger Observatory. Here, we used a portable light source based on a xenon flasher and a monochromator to measure the relative spectral efficiencies of eight telescopes in steps of 5 nm from 280 nm to 440 nm. Each point in a scan had approximately 2 nm FWHM out of the monochromator. Different sets of telescopes in the observatory have different optical components, and the eight telescopes measured represent two each of the four combinations of components represented in the observatory. Wemore » made an end-to-end measurement of the response from different combinations of optical components, and the monochromator setup allowed for more precise and complete measurements than our previous multi-wavelength calibrations. We find an overall uncertainty in the calibration of the spectral response of most of the telescopes of 1.5% for all wavelengths; the six oldest telescopes have larger overall uncertainties of about 2.2%. We also report changes in physics measureables due to the change in calibration, which are generally small.« less
An adaptive band selection method for dimension reduction of hyper-spectral remote sensing image
NASA Astrophysics Data System (ADS)
Yu, Zhijie; Yu, Hui; Wang, Chen-sheng
2014-11-01
Hyper-spectral remote sensing data can be acquired by imaging the same area with multiple wavelengths, and it normally consists of hundreds of band-images. Hyper-spectral images can not only provide spatial information but also high resolution spectral information, and it has been widely used in environment monitoring, mineral investigation and military reconnaissance. However, because of the corresponding large data volume, it is very difficult to transmit and store Hyper-spectral images. Hyper-spectral image dimensional reduction technique is desired to resolve this problem. Because of the High relation and high redundancy of the hyper-spectral bands, it is very feasible that applying the dimensional reduction method to compress the data volume. This paper proposed a novel band selection-based dimension reduction method which can adaptively select the bands which contain more information and details. The proposed method is based on the principal component analysis (PCA), and then computes the index corresponding to every band. The indexes obtained are then ranked in order of magnitude from large to small. Based on the threshold, system can adaptively and reasonably select the bands. The proposed method can overcome the shortcomings induced by transform-based dimension reduction method and prevent the original spectral information from being lost. The performance of the proposed method has been validated by implementing several experiments. The experimental results show that the proposed algorithm can reduce the dimensions of hyper-spectral image with little information loss by adaptively selecting the band images.
PCA/HEXTE Observations of Coma and A2319
NASA Technical Reports Server (NTRS)
Rephaeli, Yoel
1998-01-01
The Coma cluster was observed in 1996 for 90 ks by the PCA and HEXTE instruments aboard the RXTE satellite, the first simultaneous, pointing measurement of Coma in the broad, 2-250 keV, energy band. The high sensitivity achieved during this long observation allows precise determination of the spectrum. Our analysis of the measurements clearly indicates that in addition to the main thermal emission from hot intracluster gas at kT=7.5 keV, a second spectral component is required to best-fit the data. If thermal, it can be described with a temperature of 4.7 keV contributing about 20% of the total flux. The additional spectral component can also be described by a power-law, possibly due to Compton scattering of relativistic electrons by the CMB. This interpretation is based on the diffuse radio synchrotron emission, which has a spectral index of 2.34, within the range allowed by fits to the RXTE spectral data. A Compton origin of the measured nonthermal component would imply that the volume-averaged magnetic field in the central region of Coma is B =0.2 micro-Gauss, a value deduced directly from the radio and X-ray measurements (and thus free of the usual assumption of energy equipartition). Barring the presence of unknown systematic errors in the RXTE source or background measurements, our spectral analysis yields considerable evidence for Compton X-ray emission in the Coma cluster.
Multiple Scattering Principal Component-based Radiative Transfer Model (PCRTM) from Far IR to UV-Vis
NASA Astrophysics Data System (ADS)
Liu, X.; Wu, W.; Yang, Q.
2017-12-01
Modern satellite hyperspectral satellite remote sensors such as AIRS, CrIS, IASI, CLARREO all require accurate and fast radiative transfer models that can deal with multiple scattering of clouds and aerosols to explore the information contents. However, performing full radiative transfer calculations using multiple stream methods such as discrete ordinate (DISORT), doubling and adding (AD), successive order of scattering order of scattering (SOS) are very time consuming. We have developed a principal component-based radiative transfer model (PCRTM) to reduce the computational burden by orders of magnitudes while maintain high accuracy. By exploring spectral correlations, the PCRTM reduce the number of radiative transfer calculations in frequency domain. It further uses a hybrid stream method to decrease the number of calls to the computational expensive multiple scattering calculations with high stream numbers. Other fast parameterizations have been used in the infrared spectral region reduce the computational time to milliseconds for an AIRS forward simulation (2378 spectral channels). The PCRTM has been development to cover spectral range from far IR to UV-Vis. The PCRTM model have been be used for satellite data inversions, proxy data generation, inter-satellite calibrations, spectral fingerprinting, and climate OSSE. We will show examples of applying the PCRTM to single field of view cloudy retrievals of atmospheric temperature, moisture, traces gases, clouds, and surface parameters. We will also show how the PCRTM are used for the NASA CLARREO project.
Integrated fluorescence analysis system
Buican, Tudor N.; Yoshida, Thomas M.
1992-01-01
An integrated fluorescence analysis system enables a component part of a sample to be virtually sorted within a sample volume after a spectrum of the component part has been identified from a fluorescence spectrum of the entire sample in a flow cytometer. Birefringent optics enables the entire spectrum to be resolved into a set of numbers representing the intensity of spectral components of the spectrum. One or more spectral components are selected to program a scanning laser microscope, preferably a confocal microscope, whereby the spectrum from individual pixels or voxels in the sample can be compared. Individual pixels or voxels containing the selected spectral components are identified and an image may be formed to show the morphology of the sample with respect to only those components having the selected spectral components. There is no need for any physical sorting of the sample components to obtain the morphological information.
NASA Astrophysics Data System (ADS)
Laoufi, Fatiha; Belbachir, Ahmed-Hafid; Benabadji, Noureddine; Zanoun, Abdelouahab
2011-10-01
We have mapped the region of Oran, Algeria, using multispectral remote sensing with different resolutions. For the identification of objects on the ground using their spectral signatures, two methods were applied to images from SPOT, LANDSAT, IRS-1 C and ASTER. The first one is called Base Rule method (BR method) and is based on a set of rules that must be met at each pixel in the different bands reflectance calibrated and henceforth it is assigned to a given class. The construction of these rules is based on the spectral profiles of popular classes in the scene studied. The second one is called Spectral Angle Mapper method (SAM method) and is based on the direct calculation of the spectral angle between the target vector representing the spectral profile of the desired class and the pixel vector whose components are numbered accounts in the different bands of the calibrated image reflectance. This new method was performed using PCSATWIN software developed by our own laboratory LAAR. After collecting a library of spectral signatures with multiple libraries, a detailed study of the principles and physical processes that can influence the spectral signature has been conducted. The final goal is to establish the range of variation of a spectral profile of a well-defined class and therefore to get precise bases for spectral rules. From the results we have obtained, we find that the supervised classification of these pixels by BR method derived from spectral signatures reduces the uncertainty associated with identifying objects by enhancing significantly the percentage of correct classification with very distinct classes.
Hybrid least squares multivariate spectral analysis methods
Haaland, David M.
2004-03-23
A set of hybrid least squares multivariate spectral analysis methods in which spectral shapes of components or effects not present in the original calibration step are added in a following prediction or calibration step to improve the accuracy of the estimation of the amount of the original components in the sampled mixture. The hybrid method herein means a combination of an initial calibration step with subsequent analysis by an inverse multivariate analysis method. A spectral shape herein means normally the spectral shape of a non-calibrated chemical component in the sample mixture but can also mean the spectral shapes of other sources of spectral variation, including temperature drift, shifts between spectrometers, spectrometer drift, etc. The shape can be continuous, discontinuous, or even discrete points illustrative of the particular effect.
Hybrid least squares multivariate spectral analysis methods
Haaland, David M.
2002-01-01
A set of hybrid least squares multivariate spectral analysis methods in which spectral shapes of components or effects not present in the original calibration step are added in a following estimation or calibration step to improve the accuracy of the estimation of the amount of the original components in the sampled mixture. The "hybrid" method herein means a combination of an initial classical least squares analysis calibration step with subsequent analysis by an inverse multivariate analysis method. A "spectral shape" herein means normally the spectral shape of a non-calibrated chemical component in the sample mixture but can also mean the spectral shapes of other sources of spectral variation, including temperature drift, shifts between spectrometers, spectrometer drift, etc. The "shape" can be continuous, discontinuous, or even discrete points illustrative of the particular effect.
[Design of a Component and Transmission Imaging Spectrometer].
Sun, Bao-peng; Zhang, Yi; Yue, Jiang; Han, Jing; Bai, Lian-fa
2015-05-01
In the reflection-based imaging spectrometer, multiple reflection(diffraction) produces stray light and it is difficult to assemble. To address that, a high performance transmission spectral imaging system based on general optical components was developed. On the basis of simple structure, the system is easy to assemble. And it has wide application and low cost compared to traditional imaging spectrometers. All components in the design can be replaced according to different application situations, having high degree of freedom. In order to reduce the influence of stray light, a method based on transmission was introduced. Two sets of optical systems with different objective lenses were simulated; the parameters such as distortion, MTF and aberration.were analyzed and optimized in the ZEMAX software. By comparing the performance of system with different objective len 25 and 50 mm, it can be concluded that the replacement of telescope lens has little effect on imaging quality of whole system. An imaging spectrometer is developed successfully according design parameters. The telescope lens uses double Gauss structures, which is beneficial to reduce field curvature and distortion. As the craftsmanship of transmission-type plane diffraction grating is mature, it can be used without modification and it is easy to assemble, so it is used as beam-split. component of the imaging spectrometer. In addition, the real imaging spectrometer was tested for spectral resolution and distortion. The result demonstrates that the system has good ability in distortion control, and spectral resolution is 2 nm. These data satisfy the design requirement, and obtained spectrum of deuterium lamp through calibrated system are ideal results.
NASA Astrophysics Data System (ADS)
Chen, Q. G.; Zhu, H. H.; Xu, Y.; Lin, B.; Chen, H.
2015-08-01
A quantitative method to discriminate caries lesions for a fluorescence imaging system is proposed in this paper. The autofluorescence spectral investigation of 39 teeth samples classified by the International Caries Detection and Assessment System levels was performed at 405 nm excitation. The major differences in the different caries lesions focused on the relative spectral intensity range of 565-750 nm. The spectral parameter, defined as the ratio of wavebands at 565-750 nm to the whole spectral range, was calculated. The image component ratio R/(G + B) of color components was statistically computed by considering the spectral parameters (e.g. autofluorescence, optical filter, and spectral sensitivity) in our fluorescence color imaging system. Results showed that the spectral parameter and image component ratio presented a linear relation. Therefore, the image component ratio was graded as <0.66, 0.66-1.06, 1.06-1.62, and >1.62 to quantitatively classify sound, early decay, established decay, and severe decay tissues, respectively. Finally, the fluorescence images of caries were experimentally obtained, and the corresponding image component ratio distribution was compared with the classification result. A method to determine the numerical grades of caries using a fluorescence imaging system was proposed. This method can be applied to similar imaging systems.
NASA Astrophysics Data System (ADS)
Jia, S.
2015-12-01
As an effective method of extracting land cover fractions based on spectral endmembers, spectral mixture analysis (SMA) has been applied using remotely sensed imagery in different spatial, temporal, and spectral resolutions. A number of studies focused on arid/semiarid ecosystem have used SMA to obtain the land cover fractions of GV, NPV/litter, and bare soil (BS) using MODIS reflectance products to understand ecosystem phenology, track vegetation dynamics, and evaluate the impact of major disturbances. However, several challenges remain in the application of SMA in studying ecosystem phenology, including obtaining high quality endmembers and increasing computational efficiency when considering to long time series that cover a broad spatial extent. Okin (2007) proposes a variation of SMA, named as relative spectra mixture analysis (RSMA) to address the latter challenge by calculating the relative change of fraction of GV, NPV/litter, and BS compared with a baseline date. This approach assumes that the baseline image contains the spectral information of the bare soil that can be used as an endmember for spectral mixture analysis though it is mixed with the spectral reflectance of other non-soil land cover types. Using the baseline image, one can obtain the change of fractions of GV, NPV/litter, BS, and snow compared with the baseline image. However, RSMA results depend on the selection of baseline date and the fractional components during this date. In this study, we modified the strategy of implementing RSMA by introducing a step of obtaining a soil map as the baseline image using multiple-endmember SMA (MESMA) before applying RSMA. The fractions of land cover components from this modified RSMA are also validated using the field observations from two study area in semiarid savanna and grassland of Queensland, Australia.
NASA Astrophysics Data System (ADS)
Zhang, Ying; Li, Zhengqiang; Sun, Yele; Lv, Yang; Xie, Yisong
2018-04-01
Aerosols have adverse effects on human health and air quality, changing Earth's energy balance and lead to climate change. The components of aerosol are important because of the different spectral characteristics. Based on the low hygroscopic and high scattering properties of organic matter (OM) in fine modal atmospheric aerosols, we develop an inversion algorithm using remote sensing to obtain aerosol components including black carbon (BC), organic matter (OM), ammonium nitrate-like (AN), dust-like (DU) components and aerosol water content (AW). In the algorithm, the microphysical characteristics (i.e. volume distribution and complex refractive index) of particulates are preliminarily separated to fine and coarse modes, and then aerosol components are retrieved using bimodal parameters. We execute the algorithm using remote sensing measurements of sun-sky radiometer at AERONET site (Beijing RADI) in a period from October of 2014 to January of 2015. The results show a reasonable distribution of aerosol components and a good fit for spectral feature calculations. The mean OM mass concentration in atmospheric column is account for 14.93% of the total and 56.34% of dry and fine-mode aerosol, being a fairly good correlation (R = 0.56) with the in situ observations near the surface layer.
Chen, Shaoqiang; Yoshita, Masahiro; Sato, Aya; Ito, Takashi; Akiyama, Hidefumi; Yokoyama, Hiroyuki
2013-05-06
Picosecond-pulse-generation dynamics and pulse-width limiting factors via spectral filtering from intensely pulse-excited gain-switched 1.55-μm distributed-feedback laser diodes were studied. The spectral and temporal characteristics of the spectrally filtered pulses indicated that the short-wavelength component stems from the initial part of the gain-switched main pulse and has a nearly linear down-chirp of 5.2 ps/nm, whereas long-wavelength components include chirped pulse-lasing components and steady-state-lasing components. Rate-equation calculations with a model of linear change in refractive index with carrier density explained the major features of the experimental results. The analysis of the expected pulse widths with optimum spectral widths was also consistent with the experimental data.
NASA Astrophysics Data System (ADS)
Chung, Hyunkoo; Lu, Guolan; Tian, Zhiqiang; Wang, Dongsheng; Chen, Zhuo Georgia; Fei, Baowei
2016-03-01
Hyperspectral imaging (HSI) is an emerging imaging modality for medical applications. HSI acquires two dimensional images at various wavelengths. The combination of both spectral and spatial information provides quantitative information for cancer detection and diagnosis. This paper proposes using superpixels, principal component analysis (PCA), and support vector machine (SVM) to distinguish regions of tumor from healthy tissue. The classification method uses 2 principal components decomposed from hyperspectral images and obtains an average sensitivity of 93% and an average specificity of 85% for 11 mice. The hyperspectral imaging technology and classification method can have various applications in cancer research and management.
Preliminary Results Of PCA On MRO CRISM Multispectral Images
NASA Astrophysics Data System (ADS)
Klassen, David R.; Smith, M. D.
2008-09-01
Mars Reconnaissance Orbiter arrived at Mars in March 2006 and by September had achieved its science-phase orbit with the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) beginning its visible to near-infrared (VIS/NIR) spectral imaging shortly thereafter. One of the goals of CRISM is to fill in the spatial gaps between the various targeted observations, eventually mapping the entire surface. Due to the large volume of data this would create, the instrument works in a reduced spectral sampling mode creating "multispectral” images. From this data we can create image cubes using 70 wavelengths from 0.410 to 3.504 µm. We present here a preliminary analysis of these multispectral mode data products using the technique of Principal Components Analysis. Previous work with ground-based images has shown that over an entire visible hemisphere, there are only three to four meaningful components out of 32-105 wavelengths over 1.5-4.1 µm. The first two of these components are fairly consistent over all time intervals from day-to-day and season-to-season. [1-4] The preliminary work on the CRISM images cubes implies similar results_three to four significant principal components that are fairly consistent over time. We will show these components and a rough linear mixture modeling based on in-data spectral endmembers derived from the extrema of the principal components [5]. References: [1] Klassen, D. R. and Bell III, J. F. (2001) BAAS 33, 1069. [2] Klassen, D. R. and Bell III, J. F. (2003) BAAS, 35, 936. [3] Klassen, D. R., Wark, T. J., Cugliotta, C. G. (2005) BAAS, 37, 693. [4] Klassen, D. R. and Bell III, J. F. (2007) in preparation. [5] Klassen, D. R. and Bell III, J. F. (2000) BAAS, 32, 1105.
NASA Astrophysics Data System (ADS)
Haneishi, Hideaki; Sakuda, Yasunori; Honda, Toshio
2002-06-01
Spectral reflectance of most reflective objects such as natural objects and color hardcopy is relatively smooth and can be approximated by several numbers of principal components with high accuracy. Though the subspace spanned by those principal components represents a space in which reflective objects can exist, it dos not provide the bound in which the samples distribute. In this paper we propose to represent the gamut of reflective objects in more distinct form, i.e., as a polyhedron in the subspace spanned by several principal components. Concept of the polyhedral gamut representation and its application to calculation of metamer ensemble are described. Color-mismatch volume caused by different illuminant and/or observer for a metamer ensemble is also calculated and compared with theoretical one.
Zhang, Jian; Hou, Dibo; Wang, Ke; Huang, Pingjie; Zhang, Guangxin; Loáiciga, Hugo
2017-05-01
The detection of organic contaminants in water distribution systems is essential to protect public health from potential harmful compounds resulting from accidental spills or intentional releases. Existing methods for detecting organic contaminants are based on quantitative analyses such as chemical testing and gas/liquid chromatography, which are time- and reagent-consuming and involve costly maintenance. This study proposes a novel procedure based on discrete wavelet transform and principal component analysis for detecting organic contamination events from ultraviolet spectral data. Firstly, the spectrum of each observation is transformed using discrete wavelet with a coiflet mother wavelet to capture the abrupt change along the wavelength. Principal component analysis is then employed to approximate the spectra based on capture and fusion features. The significant value of Hotelling's T 2 statistics is calculated and used to detect outliers. An alarm of contamination event is triggered by sequential Bayesian analysis when the outliers appear continuously in several observations. The effectiveness of the proposed procedure is tested on-line using a pilot-scale setup and experimental data.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Klopf, J. Michael; Kaufmann, Pierre; Raulin, Jean-Pierre
2014-07-01
Recent solar flare observations in the sub-terahertz range have provided evidence of a new spectral component with fluxes increasing for larger frequencies, separated from the well-known microwave emission that maximizes in the gigahertz range. Suggested interpretations explain the terahertz spectral component but do not account for the simultaneous microwave component. We present a mechanism for producing the observed "double spectra." Based on coherent enhancement of synchrotron emission at long wavelengths in laboratory accelerators, we consider how similar processes may occur within a solar flare. The instability known as microbunching arises from perturbations that produce electron beam density modulations, giving risemore » to broadband coherent synchrotron emission at wavelengths comparable to the characteristic size of the microbunch structure. The spectral intensity of this coherent synchrotron radiation (CSR) can far exceed that of the incoherent synchrotron radiation (ISR), which peaks at a higher frequency, thus producing a double-peaked spectrum. Successful CSR simulations are shown to fit actual burst spectral observations, using typical flaring physical parameters and power-law energy distributions for the accelerated electrons. The simulations consider an energy threshold below which microbunching is not possible because of Coulomb repulsion. Only a small fraction of the radiating charges accelerated to energies above the threshold is required to produce the microwave component observed for several events. The ISR/CSR mechanism can occur together with other emission processes producing the microwave component. It may bring an important contribution to microwaves, at least for certain events where physical conditions for the occurrence of the ISR/CSR microbunching mechanism are possible.« less
Multimodal Spectral Imaging of Cells Using a Transmission Diffraction Grating on a Light Microscope
Isailovic, Dragan; Xu, Yang; Copus, Tyler; Saraswat, Suraj; Nauli, Surya M.
2011-01-01
A multimodal methodology for spectral imaging of cells is presented. The spectral imaging setup uses a transmission diffraction grating on a light microscope to concurrently record spectral images of cells and cellular organelles by fluorescence, darkfield, brightfield, and differential interference contrast (DIC) spectral microscopy. Initially, the setup was applied for fluorescence spectral imaging of yeast and mammalian cells labeled with multiple fluorophores. Fluorescence signals originating from fluorescently labeled biomolecules in cells were collected through triple or single filter cubes, separated by the grating, and imaged using a charge-coupled device (CCD) camera. Cellular components such as nuclei, cytoskeleton, and mitochondria were spatially separated by the fluorescence spectra of the fluorophores present in them, providing detailed multi-colored spectral images of cells. Additionally, the grating-based spectral microscope enabled measurement of scattering and absorption spectra of unlabeled cells and stained tissue sections using darkfield and brightfield or DIC spectral microscopy, respectively. The presented spectral imaging methodology provides a readily affordable approach for multimodal spectral characterization of biological cells and other specimens. PMID:21639978
Spectral negentropy based sidebands and demodulation analysis for planet bearing fault diagnosis
NASA Astrophysics Data System (ADS)
Feng, Zhipeng; Ma, Haoqun; Zuo, Ming J.
2017-12-01
Planet bearing vibration signals are highly complex due to intricate kinematics (involving both revolution and spinning) and strong multiple modulations (including not only the fault induced amplitude modulation and frequency modulation, but also additional amplitude modulations due to load zone passing, time-varying vibration transfer path, and time-varying angle between the gear pair mesh lines of action and fault impact force vector), leading to difficulty in fault feature extraction. Rolling element bearing fault diagnosis essentially relies on detection of fault induced repetitive impulses carried by resonance vibration, but they are usually contaminated by noise and therefor are hard to be detected. This further adds complexity to planet bearing diagnostics. Spectral negentropy is able to reveal the frequency distribution of repetitive transients, thus providing an approach to identify the optimal frequency band of a filter for separating repetitive impulses. In this paper, we find the informative frequency band (including the center frequency and bandwidth) of bearing fault induced repetitive impulses using the spectral negentropy based infogram. In Fourier spectrum, we identify planet bearing faults according to sideband characteristics around the center frequency. For demodulation analysis, we filter out the sensitive component based on the informative frequency band revealed by the infogram. In amplitude demodulated spectrum (squared envelope spectrum) of the sensitive component, we diagnose planet bearing faults by matching the present peaks with the theoretical fault characteristic frequencies. We further decompose the sensitive component into mono-component intrinsic mode functions (IMFs) to estimate their instantaneous frequencies, and select a sensitive IMF with an instantaneous frequency fluctuating around the center frequency for frequency demodulation analysis. In the frequency demodulated spectrum (Fourier spectrum of instantaneous frequency) of selected IMF, we discern planet bearing fault reasons according to the present peaks. The proposed spectral negentropy infogram based spectrum and demodulation analysis method is illustrated via a numerical simulated signal analysis. Considering the unique load bearing feature of planet bearings, experimental validations under both no-load and loading conditions are done to verify the derived fault symptoms and the proposed method. The localized faults on outer race, rolling element and inner race are successfully diagnosed.
Real-time high-resolution heterodyne-based measurements of spectral dynamics in fibre lasers
Sugavanam, Srikanth; Fabbri, Simon; Le, Son Thai; Lobach, Ivan; Kablukov, Sergey; Khorev, Serge; Churkin, Dmitry
2016-01-01
Conventional tools for measurement of laser spectra (e.g. optical spectrum analysers) capture data averaged over a considerable time period. However, the generation spectrum of many laser types may involve spectral dynamics whose relatively fast time scale is determined by their cavity round trip period, calling for instrumentation featuring both high temporal and spectral resolution. Such real-time spectral characterisation becomes particularly challenging if the laser pulses are long, or they have continuous or quasi-continuous wave radiation components. Here we combine optical heterodyning with a technique of spatio-temporal intensity measurements that allows the characterisation of such complex sources. Fast, round-trip-resolved spectral dynamics of cavity-based systems in real-time are obtained, with temporal resolution of one cavity round trip and frequency resolution defined by its inverse (85 ns and 24 MHz respectively are demonstrated). We also show how under certain conditions for quasi-continuous wave sources, the spectral resolution could be further increased by a factor of 100 by direct extraction of phase information from the heterodyned dynamics or by using double time scales within the spectrogram approach. PMID:26984634
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.
Multispectral and polarimetric photodetection using a plasmonic metasurface
NASA Astrophysics Data System (ADS)
Pelzman, Charles; Cho, Sang-Yeon
2018-01-01
We present a metasurface-integrated Si 2-D CMOS sensor array for multispectral and polarimetric photodetection applications. The demonstrated sensor is based on the polarization selective extraordinary optical transmission from periodic subwavelength nanostructures, acting as artificial atoms, known as meta-atoms. The meta-atoms were created by patterning periodic rectangular apertures that support optical resonance at the designed spectral bands. By spatially separating meta-atom clusters with different lattice constants and orientations, the demonstrated metasurface can convert the polarization and spectral information of an optical input into a 2-D intensity pattern. As a proof-of-concept experiment, we measured the linear components of the Stokes parameters directly from captured images using a CMOS camera at four spectral bands. Compared to existing multispectral polarimetric sensors, the demonstrated metasurface-integrated CMOS system is compact and does not require any moving components, offering great potential for advanced photodetection applications.
Makkai, Géza; Buzády, Andrea; Erostyák, János
2010-01-01
Determination of concentrations of spectrally overlapping compounds has special difficulties. Several methods are available to calculate the constituents' concentrations in moderately complex mixtures. A method which can provide information about spectrally hidden components in mixtures is very useful. Two methods powerful in resolving spectral components are compared in this paper. The first method tested is the Derivative Matrix Isopotential Synchronous Fluorimetry (DMISF). It is based on derivative analysis of MISF spectra, which are constructed using isopotential trajectories in the Excitation-Emission Matrix (EEM) of background solution. For DMISF method, a mathematical routine fitting the 3D data of EEMs was developed. The other method tested uses classical Least Squares Fitting (LSF) algorithm, wherein Rayleigh- and Raman-scattering bands may lead to complications. Both methods give excellent sensitivity and have advantages against each other. Detection limits of DMISF and LSF have been determined at very different concentration and noise levels.
NASA Astrophysics Data System (ADS)
Zhu, Zhenyu; Wang, Jianyu
1996-11-01
In this paper, two compression schemes are presented to meet the urgent needs of compressing the huge volume and high data rate of imaging spectrometer images. According to the multidimensional feature of the images and the high fidelity requirement of the reconstruction, both schemes were devised to exploit the high redundancy in both spatial and spectral dimension based on the mature wavelet transform technology. Wavelet transform was applied here in two ways: First, with the spatial wavelet transform and the spectral DPCM decorrelation, a ratio up to 84.3 with PSNR > 48db's near-lossless result was attained. This is based ont he fact that the edge structure among all the spectral bands are similar while WT has higher resolution in high frequency components. Secondly, with the wavelet's high efficiency in processing the 'wideband transient' signals, it was used to transform the raw nonstationary signals in the spectral dimension. A good result was also attained.
Contribution of LANDSAT-4 thematic mapper data to geologic exploration
NASA Technical Reports Server (NTRS)
Everett, J. R.; Dykstra, J. D.; Sheffield, C. A.
1983-01-01
The increased number of carefully selected narrow spectral bands and the increased spatial resolution of thematic mapper data over previously available satellite data contribute greatly to geologic exploration, both by providing spectral information that permits lithologic differentiation and recognition of alteration and spatial information that reveals structure. As vegetation and soil cover increase, the value of spectral components of TM data decreases relative to the value of the spatial component of the data. However, even in vegetated areas, the greater spectral breadth and discrimination of TM data permits improved recognition and mapping of spatial elements of the terrain. As our understanding of the spectral manifestations of the responses of soils and vegetation to unusual chemical environments increases, the value of spectral components of TM data to exploration will greatly improve in covered areas.
NASA Astrophysics Data System (ADS)
Aizimu, Tuerxun; Adachi, Makoto; Nakano, Kazuya; Ohnishi, Takashi; Nakaguchi, Toshiya; Takahashi, Nozomi; Nakada, Taka-aki; Oda, Shigeto; Haneishi, Hideaki
2018-02-01
Near-infrared spectroscopy (NIRS) is a noninvasive method for monitoring tissue oxygen saturation (StO2). Many commercial NIRS devices are presently available. However, the precision of those devices is relatively poor because they are using the reflectance-model with which it is difficult to obtain the blood volume and other unchanged components of the tissue. Human webbing is a thin part of the hand and suitable to measure spectral transmittance. In this paper, we present a method for measuring StO2 of human webbing from a transmissive continuous-wave nearinfrared spectroscopy (CW-NIRS) data. The method is based on the modified Beer-Lambert law (MBL) and it consists of two steps. In the first step, we give a pressure to the upstream region of the measurement point to perturb the concentration of deoxy- and oxy-hemoglobin as remaining the other components and measure the spectral signals. From the measured data, spectral absorbance due to the components other than hemoglobin is calculated. In the second step, spectral measurement is performed at arbitrary time instance and the spectral absorbance obtained in the step 1 is subtracted from the measured absorbance. The tissue oxygen saturation (StO2) is estimated from the remained data. The method was evaluated on an arterial occlusion test (AOT) and a venous occlusion test (VOT). In the evaluation experiment, we confirmed that reasonable values of StO2 were obtained by the proposed method.
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
NASA Astrophysics Data System (ADS)
Ma, Weiwei; Gong, Cailan; Hu, Yong; Meng, Peng; Xu, Feifei
2013-08-01
Hyperspectral data, consisting of hundreds of spectral bands with a high spectral resolution, enables acquisition of continuous spectral characteristic curves, and therefore have served as a powerful tool for vegetation classification. The difficulty of using hyperspectral data is that they are usually redundant, strongly correlated and subject to Hughes phenomenon where classification accuracy increases gradually in the beginning as the number of spectral bands or dimensions increases, but decreases dramatically when the band number reaches some value. In recent years,some algorithms have been proposed to overcome the Hughes phenomenon in classification, such as selecting several bands from full bands, PCA- and MNF-based feature transformations. Up to date, however, few studies have been conducted to investigate the turning point of Hughes phenomenon (i.e., the point at which the classification accuracy begins to decline). In this paper, we firstly analyze reasons for occurrence of Hughes phenomenon, and then based on the Mahalanobis classifier, classify the ground spectrum of several grasslands which were recorded in September 2012 using FieldSpec3 spectrometer in the regions around Qinghai Lake,a important pasturing area in the north of China. Before classification, we extract features from hyperspectral data by bands selecting and PCA- based feature transformations, and In the process of classification, we analyze how the correlation coefficient between wavebands, the number of waveband channels and the number of principal components affect the classification result. The results show that Hushes phenomenon may occur when the correlation coefficient between wavebands is greater than 94%,the number of wavebands is greater than 6, or the number of principal components is greater than 6. Best classification result can be achieved (overall accuracy of grasslands 90%) if the number of wavebands equals to 3 (the band positions are 370nm, 509nm and 886nm respectively) or the number of principal components ranges from 4 to 6.
Planck 2013 results. IX. HFI spectral response
NASA Astrophysics Data System (ADS)
Planck Collaboration; Ade, P. A. R.; Aghanim, N.; Armitage-Caplan, C.; Arnaud, M.; Ashdown, M.; Atrio-Barandela, F.; Aumont, J.; Baccigalupi, C.; Banday, A. J.; Barreiro, R. B.; Battaner, E.; Benabed, K.; Benoît, A.; Benoit-Lévy, A.; Bernard, J.-P.; Bersanelli, M.; Bielewicz, P.; Bobin, J.; Bock, J. J.; Bond, J. R.; Borrill, J.; Bouchet, F. R.; Boulanger, F.; Bridges, M.; Bucher, M.; Burigana, C.; Cardoso, J.-F.; Catalano, A.; Challinor, A.; Chamballu, A.; Chary, R.-R.; Chen, X.; Chiang, H. C.; Chiang, L.-Y.; Christensen, P. R.; Church, S.; Clements, D. L.; Colombi, S.; Colombo, L. P. L.; Combet, C.; Comis, B.; Couchot, F.; Coulais, A.; Crill, B. P.; Curto, A.; Cuttaia, F.; Danese, L.; Davies, R. D.; de Bernardis, P.; de Rosa, A.; de Zotti, G.; Delabrouille, J.; Delouis, J.-M.; Désert, F.-X.; Dickinson, C.; Diego, J. M.; Dole, H.; Donzelli, S.; Doré, O.; Douspis, M.; Dupac, X.; Efstathiou, G.; Enßlin, T. A.; Eriksen, H. K.; Falgarone, E.; Finelli, F.; Forni, O.; Frailis, M.; Franceschi, E.; Galeotta, S.; Ganga, K.; Giard, M.; Giraud-Héraud, Y.; González-Nuevo, J.; Górski, K. M.; Gratton, S.; Gregorio, A.; Gruppuso, A.; Hansen, F. K.; Hanson, D.; Harrison, D.; Henrot-Versillé, S.; Hernández-Monteagudo, C.; Herranz, D.; Hildebrandt, S. R.; Hivon, E.; Hobson, M.; Holmes, W. A.; Hornstrup, A.; Hovest, W.; Huffenberger, K. M.; Hurier, G.; Jaffe, A. H.; Jaffe, T. R.; Jones, W. C.; Juvela, M.; Keihänen, E.; Keskitalo, R.; Kisner, T. S.; Kneissl, R.; Knoche, J.; Knox, L.; Kunz, M.; Kurki-Suonio, H.; Lagache, G.; Lamarre, J.-M.; Lasenby, A.; Laureijs, R. J.; Lawrence, C. R.; Leahy, J. P.; Leonardi, R.; Leroy, C.; Lesgourgues, J.; Liguori, M.; Lilje, P. B.; Linden-Vørnle, M.; López-Caniego, M.; Lubin, P. M.; Macías-Pérez, J. F.; Maffei, B.; Mandolesi, N.; Maris, M.; Marshall, D. J.; Martin, P. G.; Martínez-González, E.; Masi, S.; Massardi, M.; Matarrese, S.; Matthai, F.; Mazzotta, P.; McGehee, P.; Melchiorri, A.; Mendes, L.; Mennella, A.; Migliaccio, M.; Mitra, S.; Miville-Deschênes, M.-A.; Moneti, A.; Montier, L.; Morgante, G.; Mortlock, D.; Munshi, D.; Murphy, J. A.; Naselsky, P.; Nati, F.; Natoli, P.; Netterfield, C. B.; Nørgaard-Nielsen, H. U.; North, C.; Noviello, F.; Novikov, D.; Novikov, I.; Osborne, S.; Oxborrow, C. A.; Paci, F.; Pagano, L.; Pajot, F.; Paoletti, D.; Pasian, F.; Patanchon, G.; Perdereau, O.; Perotto, L.; Perrotta, F.; Piacentini, F.; Piat, M.; Pierpaoli, E.; Pietrobon, D.; Plaszczynski, S.; Pointecouteau, E.; Polenta, G.; Ponthieu, N.; Popa, L.; Poutanen, T.; Pratt, G. W.; Prézeau, G.; Prunet, S.; Puget, J.-L.; Rachen, J. P.; Reinecke, M.; Remazeilles, M.; Renault, C.; Ricciardi, S.; Riller, T.; Ristorcelli, I.; Rocha, G.; Rosset, C.; Roudier, G.; Rusholme, B.; Santos, D.; Savini, G.; Scott, D.; Shellard, E. P. S.; Spencer, L. D.; Starck, J.-L.; Stolyarov, V.; Stompor, R.; Sudiwala, R.; Sureau, F.; Sutton, D.; Suur-Uski, A.-S.; Sygnet, J.-F.; Tauber, J. A.; Tavagnacco, D.; Terenzi, L.; Tomasi, M.; Tristram, M.; Tucci, M.; Umana, G.; Valenziano, L.; Valiviita, J.; Van Tent, B.; Vielva, P.; Villa, F.; Vittorio, N.; Wade, L. A.; Wandelt, B. D.; Yvon, D.; Zacchei, A.; Zonca, A.
2014-11-01
The Planck High Frequency Instrument (HFI) spectral response was determined through a series of ground based tests conducted with the HFI focal plane in a cryogenic environment prior to launch. The main goal of the spectral transmission tests was to measure the relative spectral response (includingthe level of out-of-band signal rejection) of all HFI detectors to a known source of electromagnetic radiation individually. This was determined by measuring the interferometric output of a continuously scanned Fourier transform spectrometer with all HFI detectors. As there is no on-board spectrometer within HFI, the ground-based spectral response experiments provide the definitive data set for the relative spectral calibration of the HFI. Knowledge of the relative variations in the spectral response between HFI detectors allows for a more thorough analysis of the HFI data. The spectral response of the HFI is used in Planck data analysis and component separation, this includes extraction of CO emission observed within Planck bands, dust emission, Sunyaev-Zeldovich sources, and intensity to polarization leakage. The HFI spectral response data have also been used to provide unit conversion and colour correction analysis tools. While previous papers describe the pre-flight experiments conducted on the Planck HFI, this paper focusses on the analysis of the pre-flight spectral response measurements and the derivation of data products, e.g. band-average spectra, unit conversion coefficients, and colour correction coefficients, all with related uncertainties. Verifications of the HFI spectral response data are provided through comparisons with photometric HFI flight data. This validation includes use of HFI zodiacal emission observations to demonstrate out-of-band spectral signal rejection better than 108. The accuracy of the HFI relative spectral response data is verified through comparison with complementary flight-data based unit conversion coefficients and colour correction coefficients. These coefficients include those based upon HFI observations of CO, dust, and Sunyaev-Zeldovich emission. General agreement is observed between the ground-based spectral characterization of HFI and corresponding in-flight observations, within the quoted uncertainty of each; explanations are provided for any discrepancies.
Multi-spectral endogenous fluorescence imaging for bacterial differentiation
NASA Astrophysics Data System (ADS)
Chernomyrdin, Nikita V.; Babayants, Margarita V.; Korotkov, Oleg V.; Kudrin, Konstantin G.; Rimskaya, Elena N.; Shikunova, Irina A.; Kurlov, Vladimir N.; Cherkasova, Olga P.; Komandin, Gennady A.; Reshetov, Igor V.; Zaytsev, Kirill I.
2017-07-01
In this paper, the multi-spectral endogenous fluorescence imaging was implemented for bacterial differentiation. The fluorescence imaging was performed using a digital camera equipped with a set of visual bandpass filters. Narrowband 365 nm ultraviolet radiation passed through a beam homogenizer was used to excite the sample fluorescence. In order to increase a signal-to-noise ratio and suppress a non-fluorescence background in images, the intensity of the UV excitation was modulated using a mechanical chopper. The principal components were introduced for differentiating the samples of bacteria based on the multi-spectral endogenous fluorescence images.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Katsuda, Satoru; Tsuboi, Yohko; Maeda, Keiichi
2016-12-01
We present multi-epoch X-ray spectral observations of three Type IIn supernovae (SNe), SN 2005kd, SN 2006jd, and SN 2010jl, acquired with Chandra , XMM-Newton , Suzaku , and Swift . Previous extensive X-ray studies of SN 2010jl have revealed that X-ray spectra are dominated by thermal emission, which likely arises from a hot plasma heated by a forward shock propagating into a massive circumstellar medium (CSM). Interestingly, an additional soft X-ray component was required to reproduce the spectra at a period of ∼1–2 years after the SN explosion. Although this component is likely associated with the SN, its origin remained an open question. Wemore » find a similar, additional soft X-ray component from the other two SNe IIn as well. Given this finding, we present a new interpretation for the origin of this component; it is thermal emission from a forward shock essentially identical to the hard X-ray component, but directly reaches us from a void of the dense CSM. Namely, the hard and soft components are responsible for the heavily and moderately absorbed components, respectively. The co-existence of the two components with distinct absorptions as well as the delayed emergence of the moderately absorbed X-ray component could be evidence for asphericity of the CSM. We show that the X-ray spectral evolution can be qualitatively explained by considering a torus-like geometry for the dense CSM. Based on our X-ray spectral analyses, we estimate the radius of the torus-like CSM to be on the order of ∼5 × 10{sup 16} cm.« less
NASA Astrophysics Data System (ADS)
Zhang, Y.; Wen, J.; Xiao, Q.; You, D.
2016-12-01
Operational algorithms for land surface BRDF/Albedo products are mainly developed from kernel-driven model, combining atmospherically corrected, multidate, multiband surface reflectance to extract BRDF parameters. The Angular and Spectral Kernel Driven model (ASK model), which incorporates the component spectra as a priori knowledge, provides a potential way to make full use of the multi-sensor data with multispectral information and accumulated observations. However, the ASK model is still not feasible for global BRDF/Albedo inversions due to the lack of sufficient field measurements of component spectra at the large scale. This research outlines a parameterization scheme on the component spectra for global scale BRDF/Albedo inversions in the frame of ASK. The parameter γ(λ) can be derived from the ratio of the leaf reflectance and soil reflectance, supported by globally distributed soil spectral library, ANGERS and LOPEX leaf optical properties database. To consider the intrinsic variability in both the land cover and spectral dimension, the mean and standard deviation of γ(λ) for 28 soil units and 4 leaf types in seven MODIS bands were calculated, with a world soil map used for global BRDF/Albedo products retrieval. Compared to the retrievals from BRF datasets simulated by the PROSAIL model, ASK model shows an acceptable accuracy on the parameterization strategy, with the RMSE 0.007 higher at most than inversion by true component spectra. The results indicate that the classification on ratio contributed to capture the spectral characteristics in BBRDF/Albedo retrieval, whereas the ratio range should be controlled within 8% in each band. Ground-based measurements in Heihe river basin were used to validate the accuracy of the improved ASK model, and the generated broadband albedo products shows good agreement with in situ data, which suggests that the improvement of the component spectra on the ASK model has potential for global scale BRDF/Albedo inversions.
Preliminary PCA/TT Results on MRO CRISM Multispectral Images
NASA Astrophysics Data System (ADS)
Klassen, David R.; Smith, M. D.
2010-10-01
Mars Reconnaissance Orbiter arrived at Mars in March 2006 and by September had achieved its science-phase orbit with the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) beginning its visible to near-infrared (VIS/NIR) spectral imaging shortly thereafter. One goal of CRISM is to fill in the spatial gaps between the various targeted observations, eventually mapping the entire surface. Due to the large volume of data this would create, the instrument works in a reduced spectral sampling mode creating "multispectral” images. From these data we can create image cubes using 64 wavelengths from 0.410 to 3.923 µm. We present here our analysis of these multispectral mode data products using Principal Components Analysis (PCA) and Target Transformation (TT) [1]. Previous work with ground-based images [2-5] has shown that over an entire visible hemisphere, there are only three to four meaningful components using 32-105 wavelengths over 1.5-4.1 µm the first two are consistent over all temporal scales. The TT retrieved spectral endmembers show nearly the same level of consistency [5]. The preliminary work on the CRISM images cubes implies similar results; three to four significant principal components that are fairly consistent over time. These components are then used in TT to find spectral endmembers which can be used to characterize the surface reflectance for future use in radiative transfer cloud optical depth retrievals. We present here the PCA/TT results comparing the principal components and recovered endmembers from six reconstructed CRISM multi-spectral image cubes. References: [1] Bandfield, J. L., et al. (2000) JGR, 105, 9573. [2] Klassen, D. R. and Bell III, J. F. (2001) BAAS 33, 1069. [3] Klassen, D. R. and Bell III, J. F. (2003) BAAS, 35, 936. [4] Klassen, D. R., Wark, T. J., Cugliotta, C. G. (2005) BAAS, 37, 693. [5] Klassen, D. R. (2009) Icarus, 204, 32.
Augmented classical least squares multivariate spectral analysis
Haaland, David M.; Melgaard, David K.
2004-02-03
A method of multivariate spectral analysis, termed augmented classical least squares (ACLS), provides an improved CLS calibration model when unmodeled sources of spectral variation are contained in a calibration sample set. The ACLS methods use information derived from component or spectral residuals during the CLS calibration to provide an improved calibration-augmented CLS model. The ACLS methods are based on CLS so that they retain the qualitative benefits of CLS, yet they have the flexibility of PLS and other hybrid techniques in that they can define a prediction model even with unmodeled sources of spectral variation that are not explicitly included in the calibration model. The unmodeled sources of spectral variation may be unknown constituents, constituents with unknown concentrations, nonlinear responses, non-uniform and correlated errors, or other sources of spectral variation that are present in the calibration sample spectra. Also, since the various ACLS methods are based on CLS, they can incorporate the new prediction-augmented CLS (PACLS) method of updating the prediction model for new sources of spectral variation contained in the prediction sample set without having to return to the calibration process. The ACLS methods can also be applied to alternating least squares models. The ACLS methods can be applied to all types of multivariate data.
Augmented Classical Least Squares Multivariate Spectral Analysis
Haaland, David M.; Melgaard, David K.
2005-07-26
A method of multivariate spectral analysis, termed augmented classical least squares (ACLS), provides an improved CLS calibration model when unmodeled sources of spectral variation are contained in a calibration sample set. The ACLS methods use information derived from component or spectral residuals during the CLS calibration to provide an improved calibration-augmented CLS model. The ACLS methods are based on CLS so that they retain the qualitative benefits of CLS, yet they have the flexibility of PLS and other hybrid techniques in that they can define a prediction model even with unmodeled sources of spectral variation that are not explicitly included in the calibration model. The unmodeled sources of spectral variation may be unknown constituents, constituents with unknown concentrations, nonlinear responses, non-uniform and correlated errors, or other sources of spectral variation that are present in the calibration sample spectra. Also, since the various ACLS methods are based on CLS, they can incorporate the new prediction-augmented CLS (PACLS) method of updating the prediction model for new sources of spectral variation contained in the prediction sample set without having to return to the calibration process. The ACLS methods can also be applied to alternating least squares models. The ACLS methods can be applied to all types of multivariate data.
Augmented Classical Least Squares Multivariate Spectral Analysis
Haaland, David M.; Melgaard, David K.
2005-01-11
A method of multivariate spectral analysis, termed augmented classical least squares (ACLS), provides an improved CLS calibration model when unmodeled sources of spectral variation are contained in a calibration sample set. The ACLS methods use information derived from component or spectral residuals during the CLS calibration to provide an improved calibration-augmented CLS model. The ACLS methods are based on CLS so that they retain the qualitative benefits of CLS, yet they have the flexibility of PLS and other hybrid techniques in that they can define a prediction model even with unmodeled sources of spectral variation that are not explicitly included in the calibration model. The unmodeled sources of spectral variation may be unknown constituents, constituents with unknown concentrations, nonlinear responses, non-uniform and correlated errors, or other sources of spectral variation that are present in the calibration sample spectra. Also, since the various ACLS methods are based on CLS, they can incorporate the new prediction-augmented CLS (PACLS) method of updating the prediction model for new sources of spectral variation contained in the prediction sample set without having to return to the calibration process. The ACLS methods can also be applied to alternating least squares models. The ACLS methods can be applied to all types of multivariate data.
NASA Astrophysics Data System (ADS)
Ivanov, M. P.; Tolmachev, Yu. A.
2018-05-01
We consider the most feasible ways to significantly improve the sensitivity of spectroscopic methods for detection and measurement of trace concentrations of greenhouse gas molecules in the atmosphere. The proposed methods are based on combining light fluxes from a number of spectral components of the specified molecule on the same photodetector, taking into account the characteristic features of the transmission spectrum of devices utilizing multipath interference effects.
Method for Balancing Detector Output to a Desired Level of Balance at a Frequency
NASA Technical Reports Server (NTRS)
Sachse, Glenn W. (Inventor)
2003-01-01
A multi-gas sensor is provided which modulates a polarized light beam over a broadband of wavelengths between two alternating orthogonal polarization components. The two orthogonal polarization components of the polarization modulated beam are directed along two distinct optical paths. At least one optical path contains one or more spectral discrimination elements, with each spectral discrimination element having spectral absorption features of one or more gases of interest being measured. The two optical paths then intersect, and one orthogonal component of the intersected components is transmitted and the other orthogonal component is reflected. The combined polarization modulated beam is partitioned into one or more smaller spectral regions of interest where one or more gases of interest has an absorption band. The difference in intensity between the two orthogonal polarization components is then determined in each partitioned spectral region of interest as an indication of the spectral emission/absorption of the light beam by the gases of interest in the measurement path. The spectral emission/absorption is indicative of the concentration of the one or more gases of interest in the measurement path. More specifically, one embodiment of the present invention is a gas filter correlation radiometer which comprises a polarizer, a polarization modulator, a polarization beam splitter, a beam combiner, wavelength partitioning element, and detection element. The gases of interest are measured simultaneously and, further, can be measured independently or non-independently. Furthermore, optical or electronic element are provided to balance optical intensities between the two optical paths.
NASA Technical Reports Server (NTRS)
Sachse, Glenn W. (Inventor); Wang, Liang-Guo (Inventor); LeBel, Peter J. (Inventor); Steele, Tommy C. (Inventor); Rana, Mauro (Inventor)
1999-01-01
A multi-gas sensor is provided which modulates a polarized light beam over a broadband of wavelengths between two alternating orthogonal polarization components. The two orthogonal polarization components of the polarization modulated beam are directed along two distinct optical paths. At least one optical path contains one or more spectral discrimination element, with each spectral discrimination element having spectral absorption features of one or more gases of interest being measured. The two optical paths then intersect, and one orthogonal component of the intersected components is transmitted and the other orthogonal component is reflected. The combined polarization modulated beam is partitioned into one or more smaller spectral regions of interest where one or more gases of interest has an absorption band. The difference in intensity between the two orthogonal polarization components is then determined in each partitioned spectral region of interest as an indication of the spectral emission/absorption of the light beam by the gases of interest in the measurement path. The spectral emission/absorption is indicative of the concentration of the one or more gases of interest in the measurement path. More specifically, one embodiment of the present invention is a gas filter correlation radiometer which comprises a polarizer, a polarization modulator, a polarization beam splitter, a beam combiner, wavelength partitioning element, and detection element. The gases of interest are measured simultaneously and, further, can be measured independently or non-independently. Furthermore, optical or electronic element are provided to balance optical intensities between the two optical paths.
Colniță, Alia; Dina, Nicoleta Elena; Leopold, Nicolae; Vodnar, Dan Cristian; Bogdan, Diana; Porav, Sebastian Alin; David, Leontin
2017-09-01
Raman scattering and its particular effect, surface-enhanced Raman scattering (SERS), are whole-organism fingerprinting spectroscopic techniques that gain more and more popularity in bacterial detection. In this work, two relevant Gram-positive bacteria species, Lactobacillus casei ( L. casei ) and Listeria monocytogenes ( L. monocytogenes ) were characterized based on their Raman and SERS spectral fingerprints. The SERS spectra were used to identify the biochemical structures of the bacterial cell wall. Two synthesis methods of the SERS-active nanomaterials were used and the recorded spectra were analyzed. L. casei and L. monocytogenes were successfully discriminated by applying Principal Component Analysis (PCA) to their specific spectral data.
Leopold, Nicolae; Vodnar, Dan Cristian; Bogdan, Diana; Porav, Sebastian Alin; David, Leontin
2017-01-01
Raman scattering and its particular effect, surface-enhanced Raman scattering (SERS), are whole-organism fingerprinting spectroscopic techniques that gain more and more popularity in bacterial detection. In this work, two relevant Gram-positive bacteria species, Lactobacillus casei (L. casei) and Listeria monocytogenes (L. monocytogenes) were characterized based on their Raman and SERS spectral fingerprints. The SERS spectra were used to identify the biochemical structures of the bacterial cell wall. Two synthesis methods of the SERS-active nanomaterials were used and the recorded spectra were analyzed. L. casei and L. monocytogenes were successfully discriminated by applying Principal Component Analysis (PCA) to their specific spectral data. PMID:28862655
An Improved Spectral Analysis Method for Fatigue Damage Assessment of Details in Liquid Cargo Tanks
NASA Astrophysics Data System (ADS)
Zhao, Peng-yuan; Huang, Xiao-ping
2018-03-01
Errors will be caused in calculating the fatigue damages of details in liquid cargo tanks by using the traditional spectral analysis method which is based on linear system, for the nonlinear relationship between the dynamic stress and the ship acceleration. An improved spectral analysis method for the assessment of the fatigue damage in detail of a liquid cargo tank is proposed in this paper. Based on assumptions that the wave process can be simulated by summing the sinusoidal waves in different frequencies and the stress process can be simulated by summing the stress processes induced by these sinusoidal waves, the stress power spectral density (PSD) is calculated by expanding the stress processes induced by the sinusoidal waves into Fourier series and adding the amplitudes of each harmonic component with the same frequency. This analysis method can take the nonlinear relationship into consideration and the fatigue damage is then calculated based on the PSD of stress. Take an independent tank in an LNG carrier for example, the accuracy of the improved spectral analysis method is proved much better than that of the traditional spectral analysis method by comparing the calculated damage results with the results calculated by the time domain method. The proposed spectral analysis method is more accurate in calculating the fatigue damages in detail of ship liquid cargo tanks.
Characterizing CDOM Spectral Variability Across Diverse Regions and Spectral Ranges
NASA Astrophysics Data System (ADS)
Grunert, Brice K.; Mouw, Colleen B.; Ciochetto, Audrey B.
2018-01-01
Satellite remote sensing of colored dissolved organic matter (CDOM) has focused on CDOM absorption (aCDOM) at a reference wavelength, as its magnitude provides insight into the underwater light field and large-scale biogeochemical processes. CDOM spectral slope, SCDOM, has been treated as a constant or semiconstant parameter in satellite retrievals of aCDOM despite significant regional and temporal variabilities. SCDOM and other optical metrics provide insights into CDOM composition, processing, food web dynamics, and carbon cycling. To date, much of this work relies on fluorescence techniques or aCDOM in spectral ranges unavailable to current and planned satellite sensors (e.g., <300 nm). In preparation for anticipated future hyperspectral satellite missions, we take the first step here of exploring global variability in SCDOM and fit deviations in the aCDOM spectra using the recently proposed Gaussian decomposition method. From this, we investigate if global variability in retrieved SCDOM and Gaussian components is significant and regionally distinct. We iteratively decreased the spectral range considered and analyzed the number, location, and magnitude of fitted Gaussian components to understand if a reduced spectral range impacts information obtained within a common spectral window. We compared the fitted slope from the Gaussian decomposition method to absorption-based indices that indicate CDOM composition to determine the ability of satellite-derived slope to inform the analysis and modeling of large-scale biogeochemical processes. Finally, we present implications of the observed variability for remote sensing of CDOM characteristics via SCDOM.
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.
Spectral characterization of the LANDSAT thematic mapper sensors
NASA Technical Reports Server (NTRS)
Markham, B. L.; Barker, J. L.
1983-01-01
Data collected on the spectral characteristics of the LANDSAT-4 and LANDSAT-4 backup thematic mapper instruments, the protoflight (TM/PF) and flight (TM/F) models, respectively, are presented and analyzed. Tests were conducted on the instruments and their components to determine compliance with two sets of spectral specifications: band-by-band spectral coverage and channel-by-channel within-band spectral matching. Spectral coverage specifications were placed on: (1) band edges--points at 50% of peak response, (2) band edge slopes--steepness of rise and fall-off of response, (3) spectral flatness--evenness of response between edges, and (4) spurious system response--ratio of out-of-band response to in-band response. Compliance with the spectral coverage specifications was determined by analysis of spectral measurements on the individual components contributing to the overall spectral response: filters, detectors, and optical surfaces.
Algorithm based on the short-term Rényi entropy and IF estimation for noisy EEG signals analysis.
Lerga, Jonatan; Saulig, Nicoletta; Mozetič, Vladimir
2017-01-01
Stochastic electroencephalogram (EEG) signals are known to be nonstationary and often multicomponential. Detecting and extracting their components may help clinicians to localize brain neurological dysfunctionalities for patients with motor control disorders due to the fact that movement-related cortical activities are reflected in spectral EEG changes. A new algorithm for EEG signal components detection from its time-frequency distribution (TFD) has been proposed in this paper. The algorithm utilizes the modification of the Rényi entropy-based technique for number of components estimation, called short-term Rényi entropy (STRE), and upgraded by an iterative algorithm which was shown to enhance existing approaches. Combined with instantaneous frequency (IF) estimation, the proposed method was applied to EEG signal analysis both in noise-free and noisy environments for limb movements EEG signals, and was shown to be an efficient technique providing spectral description of brain activities at each electrode location up to moderate additive noise levels. Furthermore, the obtained information concerning the number of EEG signal components and their IFs show potentials to enhance diagnostics and treatment of neurological disorders for patients with motor control illnesses. Copyright © 2016 Elsevier Ltd. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Shumway, R.H.; McQuarrie, A.D.
Robust statistical approaches to the problem of discriminating between regional earthquakes and explosions are developed. We compare linear discriminant analysis using descriptive features like amplitude and spectral ratios with signal discrimination techniques using the original signal waveforms and spectral approximations to the log likelihood function. Robust information theoretic techniques are proposed and all methods are applied to 8 earthquakes and 8 mining explosions in Scandinavia and to an event from Novaya Zemlya of unknown origin. It is noted that signal discrimination approaches based on discrimination information and Renyi entropy perform better in the test sample than conventional methods based onmore » spectral ratios involving the P and S phases. Two techniques for identifying the ripple-firing pattern for typical mining explosions are proposed and shown to work well on simulated data and on several Scandinavian earthquakes and explosions. We use both cepstral analysis in the frequency domain and a time domain method based on the autocorrelation and partial autocorrelation functions. The proposed approach strips off underlying smooth spectral and seasonal spectral components corresponding to the echo pattern induced by two simple ripple-fired models. For two mining explosions, a pattern is identified whereas for two earthquakes, no pattern is evident.« less
Multivariate Analysis of Mixed Lipid Aggregate Phase Transitions Monitored Using Raman Spectroscopy.
Neal, Sharon L
2018-01-01
The phase behavior of aqueous 1,2-dimyristoyl-sn-glycero-3-phosphorylcholine (DMPC)/1,2-dihexanoyl-sn-glycero-3-phosphocholine (DHPC) mixtures between 8.0 ℃ and 41.0 ℃ were monitored using Raman spectroscopy. Temperature-dependent Raman matrices were assembled from series of spectra and subjected to multivariate analysis. The consensus of pseudo-rank estimation results is that seven to eight components account for the temperature-dependent changes observed in the spectra. The spectra and temperature response profiles of the mixture components were resolved by applying a variant of the non-negative matrix factorization (NMF) algorithm described by Lee and Seung (1999). The rotational ambiguity of the data matrix was reduced by augmenting the original temperature-dependent spectral matrix with its cumulative counterpart, i.e., the matrix formed by successive integration of the spectra across the temperature index (columns). Successive rounds of constrained NMF were used to isolate component spectra from a significant fluorescence background. Five major components exhibiting varying degrees of gel and liquid crystalline lipid character were resolved. Hydrogen-bonded water networks exhibiting varying degrees of organization are associated with the lipid components. Spectral parameters were computed to compare the chain conformation, packing, and hydration indicated by the resolved spectra. Based on spectral features and relative amounts of the components observed, four components reflect long chain lipid response. The fifth component could reflect the response of the short chain lipid, DHPC, but there were no definitive spectral features confirming this assignment. A minor component of uncertain assignment that exhibits a striking response to the DMPC pre-transition and chain melting transition also was recovered. While none of the spectra resolved exhibit features unequivocally attributable to a specific aggregate morphology or step in the gelation process, the results are consistent with the evolution of mixed phase bicelles (nanodisks) and small amounts of worm-like DMPC/DHPC aggregates, and perhaps DHPC micelles, at low temperature to suspensions of branched and entangled worm-like aggregates above the DMPC gel phase transition and perforated multi-lamellar aggregates at high temperature.
Wavelet packets for multi- and hyper-spectral imagery
NASA Astrophysics Data System (ADS)
Benedetto, J. J.; Czaja, W.; Ehler, M.; Flake, C.; Hirn, M.
2010-01-01
State of the art dimension reduction and classification schemes in multi- and hyper-spectral imaging rely primarily on the information contained in the spectral component. To better capture the joint spatial and spectral data distribution we combine the Wavelet Packet Transform with the linear dimension reduction method of Principal Component Analysis. Each spectral band is decomposed by means of the Wavelet Packet Transform and we consider a joint entropy across all the spectral bands as a tool to exploit the spatial information. Dimension reduction is then applied to the Wavelet Packets coefficients. We present examples of this technique for hyper-spectral satellite imaging. We also investigate the role of various shrinkage techniques to model non-linearity in our approach.
Multispectral Wavefronts Retrieval in Digital Holographic Three-Dimensional Imaging Spectrometry
NASA Astrophysics Data System (ADS)
Yoshimori, Kyu
2010-04-01
This paper deals with a recently developed passive interferometric technique for retrieving a set of spectral components of wavefronts that are propagating from a spatially incoherent, polychromatic object. The technique is based on measurement of 5-D spatial coherence function using a suitably designed interferometer. By applying signal processing, including aperture synthesis and spectral decomposition, one may obtains a set of wavefronts of different spectral bands. Since each wavefront is equivalent to the complex Fresnel hologram at a particular spectrum of the polychromatic object, application of the conventional Fresnel transform yields 3-D image of different spectrum. Thus, this technique of multispectral wavefronts retrieval provides a new type of 3-D imaging spectrometry based on a fully passive interferometry. Experimental results are also shown to demonstrate the validity of the method.
NASA Astrophysics Data System (ADS)
Ramos, António L. L.; Holm, Sverre; Gudvangen, Sigmund; Otterlei, Ragnvald
2013-06-01
Acoustical sniper positioning is based on the detection and direction-of-arrival estimation of the shockwave and the muzzle blast acoustical signals. In real-life situations, the detection and direction-of-arrival estimation processes is usually performed under the influence of background noise sources, e.g., vehicles noise, and might result in non-negligible inaccuracies than can affect the system performance and reliability negatively, specially when detecting the muzzle sound under long range distance and absorbing terrains. This paper introduces a multi-band spectral subtraction based algorithm for real-time noise reduction, applied to gunshot acoustical signals. The ballistic shockwave and the muzzle blast signals exhibit distinct frequency contents that are affected differently by additive noise. In most real situations, the noise component is colored and a multi-band spectral subtraction approach for noise reduction contributes to reducing the presence of artifacts in denoised signals. The proposed algorithm is tested using a dataset generated by combining signals from real gunshots and real vehicle noise. The noise component was generated using a steel tracked military tank running on asphalt and includes, therefore, the sound from the vehicle engine, which varies slightly in frequency over time according to the engine's rpm, and the sound from the steel tracks as the vehicle moves.
Method for enhancing signals transmitted over optical fibers
Ogle, James W.; Lyons, Peter B.
1983-01-01
A method for spectral equalization of high frequency spectrally broadband signals transmitted through an optical fiber. The broadband signal input is first dispersed by a grating. Narrow spectral components are collected into an array of equalizing fibers. The fibers serve as optical delay lines compensating for material dispersion of each spectral component during transmission. The relative lengths of the individual equalizing fibers are selected to compensate for such prior dispersion. The output of the equalizing fibers couple the spectrally equalized light onto a suitable detector for subsequent electronic processing of the enhanced broadband signal.
A comparison of autonomous techniques for multispectral image analysis and classification
NASA Astrophysics Data System (ADS)
Valdiviezo-N., Juan C.; Urcid, Gonzalo; Toxqui-Quitl, Carina; Padilla-Vivanco, Alfonso
2012-10-01
Multispectral imaging has given place to important applications related to classification and identification of objects from a scene. Because of multispectral instruments can be used to estimate the reflectance of materials in the scene, these techniques constitute fundamental tools for materials analysis and quality control. During the last years, a variety of algorithms has been developed to work with multispectral data, whose main purpose has been to perform the correct classification of the objects in the scene. The present study introduces a brief review of some classical as well as a novel technique that have been used for such purposes. The use of principal component analysis and K-means clustering techniques as important classification algorithms is here discussed. Moreover, a recent method based on the min-W and max-M lattice auto-associative memories, that was proposed for endmember determination in hyperspectral imagery, is introduced as a classification method. Besides a discussion of their mathematical foundation, we emphasize their main characteristics and the results achieved for two exemplar images conformed by objects similar in appearance, but spectrally different. The classification results state that the first components computed from principal component analysis can be used to highlight areas with different spectral characteristics. In addition, the use of lattice auto-associative memories provides good results for materials classification even in the cases where some spectral similarities appears in their spectral responses.
NASA Astrophysics Data System (ADS)
He, Shiyuan; Wang, Lifan; Huang, Jianhua Z.
2018-04-01
With growing data from ongoing and future supernova surveys, it is possible to empirically quantify the shapes of SNIa light curves in more detail, and to quantitatively relate the shape parameters with the intrinsic properties of SNIa. Building such relationships is critical in controlling systematic errors associated with supernova cosmology. Based on a collection of well-observed SNIa samples accumulated in the past years, we construct an empirical SNIa light curve model using a statistical method called the functional principal component analysis (FPCA) for sparse and irregularly sampled functional data. Using this method, the entire light curve of an SNIa is represented by a linear combination of principal component functions, and the SNIa is represented by a few numbers called “principal component scores.” These scores are used to establish relations between light curve shapes and physical quantities such as intrinsic color, interstellar dust reddening, spectral line strength, and spectral classes. These relations allow for descriptions of some critical physical quantities based purely on light curve shape parameters. Our study shows that some important spectral feature information is being encoded in the broad band light curves; for instance, we find that the light curve shapes are correlated with the velocity and velocity gradient of the Si II λ6355 line. This is important for supernova surveys (e.g., LSST and WFIRST). Moreover, the FPCA light curve model is used to construct the entire light curve shape, which in turn is used in a functional linear form to adjust intrinsic luminosity when fitting distance models.
NASA Technical Reports Server (NTRS)
Jethva, H.; Torres, O.
2012-01-01
We provide satellite-based evidence of the spectral dependence of absorption in biomass burning aerosols over South America using near-UV measurements made by the Ozone Monitoring Instrument (OMI) during 2005-2007. In the current near-UV OMI aerosol algorithm (OMAERUV), it is implicitly assumed that the only absorbing component in carbonaceous aerosols is black carbon whose imaginary component of the refractive index is wavelength independent. With this assumption, OMI-derived aerosol optical depth (AOD) is found to be significantly over-estimated compared to that of AERONET at several sites during intense biomass burning events (August-September). Other well-known sources of error affecting the near-UV method of aerosol retrieval do not explain the large observed AOD discrepancies between the satellite and the ground-based observations. A number of studies have revealed strong spectral dependence in carbonaceous aerosol absorption in the near-UV region suggesting the presence of organic carbon in biomass burning generated aerosols. A sensitivity analysis examining the importance of accounting for the presence of wavelength-dependent aerosol absorption in carbonaceous particles in satellite-based remote sensing was carried out in this work. The results convincingly show that the inclusion of spectrally-dependent aerosol absorption in the radiative transfer calculations leads to a more accurate characterization of the atmospheric load of carbonaceous aerosols.
Msimanga, Huggins Z; Ollis, Robert J
2010-06-01
Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were used to classify acetaminophen-containing medicines using their attenuated total reflection Fourier transform infrared (ATR-FT-IR) spectra. Four formulations of Tylenol (Arthritis Pain Relief, Extra Strength Pain Relief, 8 Hour Pain Relief, and Extra Strength Pain Relief Rapid Release) along with 98% pure acetaminophen were selected for this study because of the similarity of their spectral features, with correlation coefficients ranging from 0.9857 to 0.9988. Before acquiring spectra for the predictor matrix, the effects on spectral precision with respect to sample particle size (determined by sieve size opening), force gauge of the ATR accessory, sample reloading, and between-tablet variation were examined. Spectra were baseline corrected and normalized to unity before multivariate analysis. Analysis of variance (ANOVA) was used to study spectral precision. The large particles (35 mesh) showed large variance between spectra, while fine particles (120 mesh) indicated good spectral precision based on the F-test. Force gauge setting did not significantly affect precision. Sample reloading using the fine particle size and a constant force gauge setting of 50 units also did not compromise precision. Based on these observations, data acquisition for the predictor matrix was carried out with the fine particles (sieve size opening of 120 mesh) at a constant force gauge setting of 50 units. After removing outliers, PCA successfully classified the five samples in the first and second components, accounting for 45.0% and 24.5% of the variances, respectively. The four-component PLS-DA model (R(2)=0.925 and Q(2)=0.906) gave good test spectra predictions with an overall average of 0.961 +/- 7.1% RSD versus the expected 1.0 prediction for the 20 test spectra used.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hernán-Caballero, Antonio; Alonso-Herrero, Almudena; Hatziminaoglou, Evanthia
2015-04-20
We present results on the spectral decomposition of 118 Spitzer Infrared Spectrograph (IRS) spectra from local active galactic nuclei (AGNs) using a large set of Spitzer/IRS spectra as templates. The templates are themselves IRS spectra from extreme cases where a single physical component (stellar, interstellar, or AGN) completely dominates the integrated mid-infrared emission. We show that a linear combination of one template for each physical component reproduces the observed IRS spectra of AGN hosts with unprecedented fidelity for a template fitting method with no need to model extinction separately. We use full probability distribution functions to estimate expectation values andmore » uncertainties for observables, and find that the decomposition results are robust against degeneracies. Furthermore, we compare the AGN spectra derived from the spectral decomposition with sub-arcsecond resolution nuclear photometry and spectroscopy from ground-based observations. We find that the AGN component derived from the decomposition closely matches the nuclear spectrum with a 1σ dispersion of 0.12 dex in luminosity and typical uncertainties of ∼0.19 in the spectral index and ∼0.1 in the silicate strength. We conclude that the emission from the host galaxy can be reliably removed from the IRS spectra of AGNs. This allows for unbiased studies of the AGN emission in intermediate- and high-redshift galaxies—currently inaccesible to ground-based observations—with archival Spitzer/IRS data and in the future with the Mid-InfraRed Instrument of the James Webb Space Telescope. The decomposition code and templates are available at http://denebola.org/ahc/deblendIRS.« less
Simultaneous acquisition of differing image types
Demos, Stavros G
2012-10-09
A system in one embodiment includes an image forming device for forming an image from an area of interest containing different image components; an illumination device for illuminating the area of interest with light containing multiple components; at least one light source coupled to the illumination device, the at least one light source providing light to the illumination device containing different components, each component having distinct spectral characteristics and relative intensity; an image analyzer coupled to the image forming device, the image analyzer decomposing the image formed by the image forming device into multiple component parts based on type of imaging; and multiple image capture devices, each image capture device receiving one of the component parts of the image. A method in one embodiment includes receiving an image from an image forming device; decomposing the image formed by the image forming device into multiple component parts based on type of imaging; receiving the component parts of the image; and outputting image information based on the component parts of the image. Additional systems and methods are presented.
SaaS Platform for Time Series Data Handling
NASA Astrophysics Data System (ADS)
Oplachko, Ekaterina; Rykunov, Stanislav; Ustinin, Mikhail
2018-02-01
The paper is devoted to the description of MathBrain, a cloud-based resource, which works as a "Software as a Service" model. It is designed to maximize the efficiency of the current technology and to provide a tool for time series data handling. The resource provides access to the following analysis methods: direct and inverse Fourier transforms, Principal component analysis and Independent component analysis decompositions, quantitative analysis, magnetoencephalography inverse problem solution in a single dipole model based on multichannel spectral data.
Image sharpening for mixed spatial and spectral resolution satellite systems
NASA Technical Reports Server (NTRS)
Hallada, W. A.; Cox, S.
1983-01-01
Two methods of image sharpening (reconstruction) are compared. The first, a spatial filtering technique, extrapolates edge information from a high spatial resolution panchromatic band at 10 meters and adds it to the low spatial resolution narrow spectral bands. The second method, a color normalizing technique, is based on the ability to separate image hue and brightness components in spectral data. Using both techniques, multispectral images are sharpened from 30, 50, 70, and 90 meter resolutions. Error rates are calculated for the two methods and all sharpened resolutions. The results indicate that the color normalizing method is superior to the spatial filtering technique.
Hsieh, Sheng-Hsun; Li, Yung-Hui; Wang, Wei; Tien, Chung-Hao
2018-03-06
In this study, we maneuvered a dual-band spectral imaging system to capture an iridal image from a cosmetic-contact-lens-wearing subject. By using the independent component analysis to separate individual spectral primitives, we successfully distinguished the natural iris texture from the cosmetic contact lens (CCL) pattern, and restored the genuine iris patterns from the CCL-polluted image. Based on a database containing 200 test image pairs from 20 CCL-wearing subjects as the proof of concept, the recognition accuracy (False Rejection Rate: FRR) was improved from FRR = 10.52% to FRR = 0.57% with the proposed ICA anti-spoofing scheme.
An Analysis of Periodic Components in BL Lac Object S5 0716 +714 with MUSIC Method
NASA Astrophysics Data System (ADS)
Tang, J.
2012-01-01
Multiple signal classification (MUSIC) algorithms are introduced to the estimation of the period of variation of BL Lac objects.The principle of MUSIC spectral analysis method and theoretical analysis of the resolution of frequency spectrum using analog signals are included. From a lot of literatures, we have collected a lot of effective observation data of BL Lac object S5 0716 + 714 in V, R, I bands from 1994 to 2008. The light variation periods of S5 0716 +714 are obtained by means of the MUSIC spectral analysis method and periodogram spectral analysis method. There exist two major periods: (3.33±0.08) years and (1.24±0.01) years for all bands. The estimation of the period of variation of the algorithm based on the MUSIC spectral analysis method is compared with that of the algorithm based on the periodogram spectral analysis method. It is a super-resolution algorithm with small data length, and could be used to detect the period of variation of weak signals.
Spectral State Evolution of 4U 1820-30: the Stability of the Spectral Index of Comptonization Tail
NASA Technical Reports Server (NTRS)
Titarchuk, Lev G.; Seifina, Elena; Frontera, Filippo
2013-01-01
We analyze the X-ray spectra and their timing properties of the compact Xray binary 4U 1820-30. We establish spectral transitions in this source seen with BeppoSAX and the Rossi X-ray Timing Explorer (RXTE). During the RXTE observations (1996 - 2009), the source were approximately approximately 75% of its time in the soft state making the lower banana and upper banana transitions combined with long-term low-high state transitions. We reveal that all of the X-ray spectra of 4U 1820-30 are fit by a composition of a thermal (blackbody) component, a Comptonization component (COMPTB) and a Gaussian-line component. Thus using this spectral analysis we find that the photon power-law index Gamma of the Comptonization component is almost unchangeable (Gamma approximately 2) while the electron temperature kTe changes from 2.9 to 21 keV during these spectral events. We also establish that for these spectral events the normalization of COMPTB component (which is proportional to mass accretion rate ?M) increases by factor 8 when kTe decreases from 21 keV to 2.9 keV. Before this index stability effect was also found analyzing X-ray data for Z-source GX 340+0 and for atolls, 4U 1728-34, GX 3+1. Thus, we can suggest that this spectral stability property is a spectral signature of an accreting neutron star source. On the other hand in a black hole binary G monotonically increases with ?Mand ultimately its value saturates at large ?M.
NASA Astrophysics Data System (ADS)
Becker, Brian L.
Great Lakes wetlands are increasingly being recognized as vital ecosystem components that provide valuable functions such as sediment retention, wildlife habitat, and nutrient removal. Aerial photography has traditionally provided a cost effective means to inventory and monitor coastal wetlands, but is limited by its broad spectral sensitivity and non-digital format. Airborne sensor advancements have now made the acquisition of digital imagery with high spatial and spectral resolution a reality. In this investigation, we selected two Lake Huron coastal wetlands, each from a distinct eco-region, over which, digital, airborne imagery (AISA or CASI-II) was acquired. The 1-meter images contain approximately twenty, 10-nanometer-wide spectral bands strategically located throughout the visible and near-infrared. The 4-meter hyperspectral imagery contains 48 contiguous bands across the visible and short-wavelength near-infrared. Extensive, in-situ, reflectance spectra (SE-590) and sub-meter GPS locations were acquired for the dominant botanical and substrate classes field-delineated at each location. Normalized in-situ spectral signatures were subjected to Principal Components and 2nd Derivative analyses in order to identify the most botanically explanative image bands. Three image-based investigations were implemented in order to evaluate the ability of three classification algorithms (ISODATA, Spectral Angle Mapper and Maximum-Likelihood) to differentiate botanical regions-of-interest. Two additional investigations were completed in order to assess classification changes associated with the independent manipulation of both spatial and spectral resolution. Of the three algorithms tested, the Maximum-Likelihood classifier best differentiated (89%) the regions-of-interest in both study sites. Covariance-based PCA rotation consistently enhanced the performance of the Maximum-Likelihood classifier. Seven non-overlapping bands (425.4, 514.9, 560.1, 685.5, 731.5, 812.3 and 916.7 nanometers) were identified that represented the best performing bands with respect to classification performance. A spatial resolution of 2 meters or less was determined to be the as being most appropriate in Great Lakes coastal wetland environments. This research represents the first step in evaluating the effectiveness of applying high-resolution, narrow-band imagery to the detailed mapping of coastal wetlands in the Great Lakes region.
NASA Astrophysics Data System (ADS)
Sidko, Aleksandr; Pisman, Tamara; Botvich, Irina; Shevyrnogov, Anatoly
In order to develop satellite technology for monitoring of terrestrial plant canopies and land-based optical remote sensing techniques, one should employ new approaches to identifying farmlands and determining the plant species composition. The results present a study on polarized characteristics of spectral reflection factor of plant canopies (forests and farm crop canopies) under field conditions, using optical remote sensing techniques. The polarized components of the reflectance factor and the degree of polarization were calculated. Measurements were performed using a spectrophotometer with a polarized light filter attachment. Measurements were done within the spectral range from 400 to 840 nm. The viewing angle was no greater than 200 with respect to the nadir. Measurements of the polarization characteristics of the vegetation on the test ranges were conducted during June-July month when the height of the sun was at its zenith. Different wavelength dependences of the spectral reflection factor polarized component (Rq) and degree of polarization (P) were found both for the coniferous and broadleaf forests (pine and birch) and for farm crops (wheat and corn) and grass canopies. These differences can be used to determine species composition of plant canopies.
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
MULTI-FREQUENCY, MULTI-EPOCH STUDY OF Mrk 501: HINTS FOR A TWO-COMPONENT NATURE OF THE EMISSION
DOE Office of Scientific and Technical Information (OSTI.GOV)
Shukla, A.; Chitnis, V. R.; Singh, B. B.
2015-01-01
Since the detection of very high energy (VHE) γ-rays from Mrk 501, its broadband emission of radiation was mostly and quite effectively modeled using the one zone emission scenario. However, broadband spectral and flux variability studies enabled by the multi-wavelength campaigns carried out during the recent years have revealed the rather complex behavior of Mrk 501. The observed emission from Mrk 501 could be due to a complex superposition of multiple emission zones. Moreover, new evidence of detection of very hard intrinsic γ-ray spectra obtained from Fermi-LAT observations has challenged the theories about the origin of VHE γ-rays. Our studiesmore » based on Fermi-LAT data indicate the existence of two separate components in the spectrum, one for low-energy γ-rays and the other for high-energy γ-rays. Using multi-waveband data from several ground- and space-based instruments, in addition to HAGAR data, the spectral energy distribution of Mrk 501 is obtained for various flux states observed during 2011. In the present work, this observed broadband spectral energy distribution is reproduced with a leptonic, multi-zone synchrotron self-Compton (SSC) model.« less
NASA Astrophysics Data System (ADS)
Sametoglu, Ferhat; Celikel, Oguz; Witt, Florian
2017-10-01
A differential spectral responsivity (DSR) measurement system has been designed and constructed at National Metrology Institute of Turkey (TUBITAK UME) to determine the spectral responsivity (SR) of a single- or a multi-junction photovoltaic device (solar cell). The DSR setup contains a broad band light bias source composed of a constructed Solar Simulator based on a 1000 W Xe-arc lamp owning a AM-1.5 filter and 250 W quartz-tungsten-halogen lamp, a designed and constructed LED-based Bias Light Sources, a DC voltage bias circuit, and a probe beam optical power tracking and correction circuit controlled with an ADuC847 microcontroller card together with an embedded C based software, designed and constructed in TUBITAK UME under this project. By using the constructed DSR measurement system, the SR calibration of solar cells, the monolitic triple-junction solar cell GaInP/GaInAs/Ge and its corresponding component cells have been performed within the EURAMET Joint Research Project SolCell.
Asymptotic stability of spectral-based PDF modeling for homogeneous turbulent flows
NASA Astrophysics Data System (ADS)
Campos, Alejandro; Duraisamy, Karthik; Iaccarino, Gianluca
2015-11-01
Engineering models of turbulence, based on one-point statistics, neglect spectral information inherent in a turbulence field. It is well known, however, that the evolution of turbulence is dictated by a complex interplay between the spectral modes of velocity. For example, for homogeneous turbulence, the pressure-rate-of-strain depends on the integrated energy spectrum weighted by components of the wave vectors. The Interacting Particle Representation Model (IPRM) (Kassinos & Reynolds, 1996) and the Velocity/Wave-Vector PDF model (Van Slooten & Pope, 1997) emulate spectral information in an attempt to improve the modeling of turbulence. We investigate the evolution and asymptotic stability of the IPRM using three different approaches. The first approach considers the Lagrangian evolution of individual realizations (idealized as particles) of the stochastic process defined by the IPRM. The second solves Lagrangian evolution equations for clusters of realizations conditional on a given wave vector. The third evolves the solution of the Eulerian conditional PDF corresponding to the aforementioned clusters. This last method avoids issues related to discrete particle noise and slow convergence associated with Lagrangian particle-based simulations.
The minimum bandwidths of auroral kilometric radiation
NASA Technical Reports Server (NTRS)
Baumback, M. M.; Calvert, W.
1987-01-01
The bandwidths of the discrete spectral components of the auroral kilometric radiation can sometimes be as narrow as 5 Hz. Since this would imply an apparent source thickness of substantially less than the wavelength, it is inconsistent with the previous explanation for such discrete components based simply upon vertical localization of a cyclotron source. Instead, such narrow bandwidths can only be explained by radio lasing.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Fast, J; Zhang, Q; Tilp, A
Significantly improved returns in their aerosol chemistry data can be achieved via the development of a value-added product (VAP) of deriving OA components, called Organic Aerosol Components (OACOMP). OACOMP is primarily based on multivariate analysis of the measured organic mass spectral matrix. The key outputs of OACOMP are the concentration time series and the mass spectra of OA factors that are associated with distinct sources, formation and evolution processes, and physicochemical properties.
Global characteristics of zonal flows due to the effect of finite bandwidth in drift wave turbulence
DOE Office of Scientific and Technical Information (OSTI.GOV)
Uzawa, K.; Li Jiquan; Kishimoto, Y.
2009-04-15
The spectral effect of the zonal flow (ZF) on its generation is investigated based on the Charney-Hasegawa-Mima turbulence model. It is found that the effect of finite ZF bandwidth qualitatively changes the characteristics of ZF instability. A spatially localized (namely, global) nonlinear ZF state with an enhanced, unique growth rate for all spectral components is created under a given turbulent fluctuation. It is identified that such state originates from the successive cross couplings among Fourier components of the ZF and turbulence spectra through the sideband modulation. Furthermore, it is observed that the growth rate of the global ZF is determinedmore » not only by the spectral distribution and amplitudes of turbulent pumps as usual, but also statistically by the turbulence structure, namely, their probabilistic initial phase factors. A ten-wave coupling model of the ZF modulation instability involving the essential effect of the ZF spectrum is developed to clarify the basic features of the global nonlinear ZF state.« less
Blind decomposition of Herschel-HIFI spectral maps of the NGC 7023 nebula
NASA Astrophysics Data System (ADS)
Berné, O.; Joblin, C.; Deville, Y.; Pilleri, P.; Pety, J.; Teyssier, D.; Gerin, M.; Fuente, A.
2012-12-01
Large spatial-spectral surveys are more and more common in astronomy. This calls for the need of new methods to analyze such mega- to giga-pixel data-cubes. In this paper we present a method to decompose such observations into a limited and comprehensive set of components. The original data can then be interpreted in terms of linear combinations of these components. The method uses non-negative matrix factorization (NMF) to extract latent spectral end-members in the data. The number of needed end-members is estimated based on the level of noise in the data. A Monte-Carlo scheme is adopted to estimate the optimal end-members, and their standard deviations. Finally, the maps of linear coefficients are reconstructed using non-negative least squares. We apply this method to a set of hyperspectral data of the NGC 7023 nebula, obtained recently with the HIFI instrument onboard the Herschel space observatory, and provide a first interpretation of the results in terms of 3-dimensional dynamical structure of the region.
Method for enhancing signals transmitted over optical fibers
Ogle, J.W.; Lyons, P.B.
1981-02-11
A method for spectral equalization of high frequency spectrally broadband signals transmitted through an optical fiber is disclosed. The broadband signal input is first dispersed by a grating. Narrow spectral components are collected into an array of equalizing fibers. The fibers serve as optical delay lines compensating for material dispersion of each spectral component during transmission. The relative lengths of the individual equalizing fibers are selected to compensate for such prior dispersion. The output of the equalizing fibers couple the spectrally equalized light onto a suitable detector for subsequent electronic processing of the enhanced broadband signal.
Optical network scaling: roles of spectral and spatial aggregation.
Arık, Sercan Ö; Ho, Keang-Po; Kahn, Joseph M
2014-12-01
As the bit rates of routed data streams exceed the throughput of single wavelength-division multiplexing channels, spectral and spatial traffic aggregation become essential for optical network scaling. These aggregation techniques reduce network routing complexity by increasing spectral efficiency to decrease the number of fibers, and by increasing switching granularity to decrease the number of switching components. Spectral aggregation yields a modest decrease in the number of fibers but a substantial decrease in the number of switching components. Spatial aggregation yields a substantial decrease in both the number of fibers and the number of switching components. To quantify routing complexity reduction, we analyze the number of multi-cast and wavelength-selective switches required in a colorless, directionless and contentionless reconfigurable optical add-drop multiplexer architecture. Traffic aggregation has two potential drawbacks: reduced routing power and increased switching component size.
DOE Office of Scientific and Technical Information (OSTI.GOV)
B. R. Marshall
Spectral reflectance was used to determine the thickness of thin glue layers in a study of the effect of the glue on radiance and reflectance measurements of shocked-tin substrates attached to lithium fluoride windows. Measurements based on profilometry of the components were found to be inaccurate due to flatness variations and deformation of the tin substrate under pressure during the gluing process. The accuracy of the spectral reflectance measurements were estimated to be ±0.5 μm, which was sufficient to demonstrate a convincing correlation between glue thickness and shock-generated light.
NASA Technical Reports Server (NTRS)
Kirkpatrick, J. Davy; Mccarthy, Donald W., Jr.
1994-01-01
The relationship between mass and spectral class for main-sequence stars has never been obtained for dwarfs cooler than M6; currently, the true nature of objects classified as M7, M8, M9, or later (be they stellar or substellar) is not known. In this paper, spectral types for the components in five low mass binary systems are estimated based on previously published infrared speckle measurements, red/infrared photometry, and parallax data, together with newly acquired high signal-to-noise composite spectra of the systems and revised magnitude difference relations for M dwarfs. For two of these binaries, the secondary has a smaller mass (less than 0.09 solar mass) than any object having a dynamically measured mass and a known spectral type, thus extending the spectral class/mass relation to lower masses than has previously been possible. Data from the higher mass components (0.09 solar mass less than M less than 0.40 solar mass) are consistent with earlier results; the two lowest mass objects -- though having mass errors which could place them on either side of the M dwarf/brown dwarf dividing line (Mass is about 0.08 solar mass) -- are found to have spectral types no cooler than M6.5 V. An extrapolation of the updated spectral class/mass relation to the hydrogen-burning limit suggests that objects of type M7 and later may be substellar. Direct confirmation of this awaits the discovery of a close, very late-type binary for which dynamical masses can be measured.
Chen, Sheng-Bo; Wang, Jing-Ran; Guo, Peng-Ju; Wang, Ming-Chang
2014-09-01
The Moon may be considered as the frontier base for the deep space exploration. The spectral analysis is one of the key techniques to determine the lunar surface rock and mineral compositions. But the lunar topographic relief is more remarkable than that of the Earth. It is necessary to conduct the topographic correction for lunar spectral data before they are used to retrieve the compositions. In the present paper, a lunar Sandmeier model was proposed by considering the radiance effect from the macro and ambient topographic relief. And the reflectance correction model was also reduced based on the Sandmeier model. The Spectral Profile (SP) data from KAGUYA satellite in the Sinus Iridum quadrangle was taken as an example. And the digital elevation data from Lunar Orbiter Laser Altimeter are used to calculate the slope, aspect, incidence and emergence angles, and terrain-viewing factor for the topographic correction Thus, the lunar surface reflectance from the SP data was corrected by the proposed model after the direct component of irradiance on a horizontal surface was derived. As a result, the high spectral reflectance facing the sun is decreased and low spectral reflectance back to the sun is compensated. The statistical histogram of reflectance-corrected pixel numbers presents Gaussian distribution Therefore, the model is robust to correct lunar topographic effect and estimate lunar surface reflectance.
Chavez, P.S.; Sides, S.C.; Anderson, J.A.
1991-01-01
The merging of multisensor image data is becoming a widely used procedure because of the complementary nature of various data sets. Ideally, the method used to merge data sets with high-spatial and high-spectral resolution should not distort the spectral characteristics of the high-spectral resolution data. This paper compares the results of three different methods used to merge the information contents of the Landsat Thematic Mapper (TM) and Satellite Pour l'Observation de la Terre (SPOT) panchromatic data. The comparison is based on spectral characteristics and is made using statistical, visual, and graphical analyses of the results. The three methods used to merge the information contents of the Landsat TM and SPOT panchromatic data were the Hue-Intensity-Saturation (HIS), Principal Component Analysis (PCA), and High-Pass Filter (HPF) procedures. The HIS method distorted the spectral characteristics of the data the most. The HPF method distorted the spectral characteristics the least; the distortions were minimal and difficult to detect. -Authors
NASA Astrophysics Data System (ADS)
Bengulescu, Marc; Blanc, Philippe; Wald, Lucien
2016-04-01
An analysis of the variability of the surface solar irradiance (SSI) at different local time-scales is presented in this study. Since geophysical signals, such as long-term measurements of the SSI, are often produced by the non-linear interaction of deterministic physical processes that may also be under the influence of non-stationary external forcings, the Hilbert-Huang transform (HHT), an adaptive, noise-assisted, data-driven technique, is employed to extract locally - in time and in space - the embedded intrinsic scales at which a signal oscillates. The transform consists of two distinct steps. First, by means of the Empirical Mode Decomposition (EMD), the time-series is "de-constructed" into a finite number - often small - of zero-mean components that have distinct temporal scales of variability, termed hereinafter the Intrinsic Mode Functions (IMFs). The signal model of the components is an amplitude modulation - frequency modulation (AM - FM) one, and can also be thought of as an extension of a Fourier series having both time varying amplitude and frequency. Following the decomposition, Hilbert spectral analysis is then employed on the IMFs, yielding a time-frequency-energy representation that portrays changes in the spectral contents of the original data, with respect to time. As measurements of surface solar irradiance may possibly be contaminated by the manifestation of different type of stochastic processes (i.e. noise), the identification of real, physical processes from this background of random fluctuations is of interest. To this end, an adaptive background noise null hypothesis is assumed, based on the robust statistical properties of the EMD when applied to time-series of different classes of noise (e.g. white, red or fractional Gaussian). Since the algorithm acts as an efficient constant-Q dyadic, "wavelet-like", filter bank, the different noise inputs are decomposed into components having the same spectral shape, but that are translated to the next lower octave in the spectral domain. Thus, when the sampling step is increased, the spectral shape of IMFs cannot remain at its original position, due to the new lower Nyquist frequency, and is instead pushed toward the lower scaled frequency. Based on these features, the identification of potential signals within the data should become possible without any prior knowledge of the background noises. When applying the above outlined procedure to decennial time-series of surface solar irradiance, only the component that has an annual time-scale of variability is shown to have statistical properties that diverge from those of noise. Nevertheless, the noise-like components are not completely devoid of information, as it is found that their AM components have a non-null rank correlation coefficient with the annual mode, i.e. the background noise intensity seems to be modulated by the seasonal cycle. The findings have possible implications on the modelling and forecast of the surface solar irradiance, by discriminating its deterministic from its quasi-stochastic constituents, at distinct local time-scales.
Measurement analysis of two radials with a common-origin point and its application.
Liu, Zhenyao; Yang, Jidong; Zhu, Weiwei; Zhou, Shang; Tan, Xuanping
2017-08-01
In spectral analysis, a chemical component is usually identified by its characteristic spectra, especially the peaks. If two components have overlapping spectral peaks, they are generally considered to be indiscriminate in current analytical chemistry textbooks and related literature. However, if the intensities of the overlapping major spectral peaks are additive, and have different rates of change with respect to variations in the concentration of the individual components, a simple method, named the 'common-origin ray', for the simultaneous determination of two components can be established. Several case studies highlighting its applications are presented. Copyright © 2017 John Wiley & Sons, Ltd.
Nonlocal low-rank and sparse matrix decomposition for spectral CT reconstruction
NASA Astrophysics Data System (ADS)
Niu, Shanzhou; Yu, Gaohang; Ma, Jianhua; Wang, Jing
2018-02-01
Spectral computed tomography (CT) has been a promising technique in research and clinics because of its ability to produce improved energy resolution images with narrow energy bins. However, the narrow energy bin image is often affected by serious quantum noise because of the limited number of photons used in the corresponding energy bin. To address this problem, we present an iterative reconstruction method for spectral CT using nonlocal low-rank and sparse matrix decomposition (NLSMD), which exploits the self-similarity of patches that are collected in multi-energy images. Specifically, each set of patches can be decomposed into a low-rank component and a sparse component, and the low-rank component represents the stationary background over different energy bins, while the sparse component represents the rest of the different spectral features in individual energy bins. Subsequently, an effective alternating optimization algorithm was developed to minimize the associated objective function. To validate and evaluate the NLSMD method, qualitative and quantitative studies were conducted by using simulated and real spectral CT data. Experimental results show that the NLSMD method improves spectral CT images in terms of noise reduction, artifact suppression and resolution preservation.
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.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Titarchuk, Lev; Frontera, Filippo; Seifina, Elena, E-mail: titarchuk@fe.infn.it, E-mail: lev@milkyway.gsfc.nasa.gov, E-mail: frontera@fe.infn.it, E-mail: seif@sai.msu.ru
We analyze the X-ray spectra and their timing properties of the compact X-ray binary 4U 1820-30. We establish spectral transitions in this source seen with BeppoSAX and the Rossi X-ray Timing Explorer (RXTE). During the RXTE observations (1996-2009), the source was in the soft state approximately {approx}75% of the time making the lower banana and upper banana transitions combined with long-term low-high state transitions. We reveal that all of the X-ray spectra of 4U 1820-30 are fit by a combination of a thermal (Blackbody) component, a Comptonization component (COMPTB), and a Gaussian-line component. Thus, using this spectral analysis, we findmore » that the photon power-law index {Gamma} of the Comptonization component is almost unchangeable ({Gamma} {approx} 2), while the electron temperature kT{sub e} changes from 2.9 to 21 keV during these spectral events. We also establish that for these spectral events the normalization of the COMPTB component (which is proportional to the mass accretion rate M-dot ) increases by a factor of eight when kT{sub e} decreases from 21 keV to 2.9 keV. Previously, this index stability effect was also found analyzing X-ray data for the Z-source GX 340+0 and for the atolls 4U 1728-34 and GX 3+1. Thus, we can suggest that this spectral stability property is a spectral signature of an accreting neutron star source. On the other hand, in a black hole binary {Gamma} monotonically increases with M-dot and ultimately its value saturates at large M-dot .« less
Blind source separation of ex-vivo aorta tissue multispectral images
Galeano, July; Perez, Sandra; Montoya, Yonatan; Botina, Deivid; Garzón, Johnson
2015-01-01
Blind Source Separation methods (BSS) aim for the decomposition of a given signal in its main components or source signals. Those techniques have been widely used in the literature for the analysis of biomedical images, in order to extract the main components of an organ or tissue under study. The analysis of skin images for the extraction of melanin and hemoglobin is an example of the use of BSS. This paper presents a proof of concept of the use of source separation of ex-vivo aorta tissue multispectral Images. The images are acquired with an interference filter-based imaging system. The images are processed by means of two algorithms: Independent Components analysis and Non-negative Matrix Factorization. In both cases, it is possible to obtain maps that quantify the concentration of the main chromophores present in aortic tissue. Also, the algorithms allow for spectral absorbance of the main tissue components. Those spectral signatures were compared against the theoretical ones by using correlation coefficients. Those coefficients report values close to 0.9, which is a good estimator of the method’s performance. Also, correlation coefficients lead to the identification of the concentration maps according to the evaluated chromophore. The results suggest that Multi/hyper-spectral systems together with image processing techniques is a potential tool for the analysis of cardiovascular tissue. PMID:26137366
NASA Astrophysics Data System (ADS)
Kong, Yun; Wang, Tianyang; Li, Zheng; Chu, Fulei
2017-09-01
Planetary transmission plays a vital role in wind turbine drivetrains, and its fault diagnosis has been an important and challenging issue. Owing to the complicated and coupled vibration source, time-variant vibration transfer path, and heavy background noise masking effect, the vibration signal of planet gear in wind turbine gearboxes exhibits several unique characteristics: Complex frequency components, low signal-to-noise ratio, and weak fault feature. In this sense, the periodic impulsive components induced by a localized defect are hard to extract, and the fault detection of planet gear in wind turbines remains to be a challenging research work. Aiming to extract the fault feature of planet gear effectively, we propose a novel feature extraction method based on spectral kurtosis and time wavelet energy spectrum (SK-TWES) in the paper. Firstly, the spectral kurtosis (SK) and kurtogram of raw vibration signals are computed and exploited to select the optimal filtering parameter for the subsequent band-pass filtering. Then, the band-pass filtering is applied to extrude periodic transient impulses using the optimal frequency band in which the corresponding SK value is maximal. Finally, the time wavelet energy spectrum analysis is performed on the filtered signal, selecting Morlet wavelet as the mother wavelet which possesses a high similarity to the impulsive components. The experimental signals collected from the wind turbine gearbox test rig demonstrate that the proposed method is effective at the feature extraction and fault diagnosis for the planet gear with a localized defect.
NASA Astrophysics Data System (ADS)
Bürmen, Miran; Pernuš, Franjo; Likar, Boštjan
2010-02-01
Near-infrared spectroscopy is a promising, rapidly developing, reliable and noninvasive technique, used extensively in the biomedicine and in pharmaceutical industry. With the introduction of acousto-optic tunable filters (AOTF) and highly sensitive InGaAs focal plane sensor arrays, real-time high resolution hyper-spectral imaging has become feasible for a number of new biomedical in vivo applications. However, due to the specificity of the AOTF technology and lack of spectral calibration standardization, maintaining long-term stability and compatibility of the acquired hyper-spectral images across different systems is still a challenging problem. Efficiently solving both is essential as the majority of methods for analysis of hyper-spectral images relay on a priori knowledge extracted from large spectral databases, serving as the basis for reliable qualitative or quantitative analysis of various biological samples. In this study, we propose and evaluate fast and reliable spectral calibration of hyper-spectral imaging systems in the short wavelength infrared spectral region. The proposed spectral calibration method is based on light sources or materials, exhibiting distinct spectral features, which enable robust non-rigid registration of the acquired spectra. The calibration accounts for all of the components of a typical hyper-spectral imaging system such as AOTF, light source, lens and optical fibers. The obtained results indicated that practical, fast and reliable spectral calibration of hyper-spectral imaging systems is possible, thereby assuring long-term stability and inter-system compatibility of the acquired hyper-spectral images.
2014-04-01
13. SUPPLEMENTARY NOTES Author’s email: grace.d.metcalfe.civ@mail.mil 14. ABSTRACT Polarimetry is the analysis of the polarization state of...been virtually no polarimetry work at terahertz (THz) frequencies because, until recently, it has been difficult to create components to control the...develop the essential components such that THz polarimetry may enhance the ability to study previously unexploited spectral responses in the THz
Application of Time-Frequency Representations To Non-Stationary Radar Cross Section
2009-03-01
The three- dimensional plot produced by a TFR allows one to determine which spectral components of a signal vary with time [25... a range bin ( of width cT 2 ) from the stepped frequency waveform. 2. Cancel the clutter (stationary components) by zeroing out points associated with ...generating an infinite number of bilinear Time Frequency distributions based on a generalized equation and a change- able
Shot noise limited characterization of ultraweak femtosecond pulse trains.
Schwartz, Osip; Raz, Oren; Katz, Ori; Dudovich, Nirit; Oron, Dan
2011-01-17
Ultrafast science is inherently, due to the lack of fast enough detectors and electronics, based on nonlinear interactions. Typically, however, nonlinear measurements require significant powers and often operate in a limited spectral range. Here we overcome the difficulties of ultraweak ultrafast measurements by precision time-domain localization of spectral components. We utilize this for linear self-referenced characterization of pulse trains having ∼ 1 photon per pulse, a regime in which nonlinear techniques are impractical, at a temporal resolution of ∼ 10 fs. This technique does not only set a new scale of sensitivity in ultrashort pulse characterization, but is also applicable in any spectral range from the near-infrared to the deep UV.
NASA Astrophysics Data System (ADS)
Judycka, U.; Jagiello, K.; Bober, L.; Błażejowski, J.; Puzyn, T.
2018-06-01
Chemometric tools were applied to investigate the biological behaviour of ampholytic substances in relation to their physicochemical and spectral properties. Results of the Principal Component Analysis suggest that size of molecules and their electronic and spectral characteristics are the key properties required to predict therapeutic relevance of the compounds examined. These properties were used for developing the structure-activity classification model. The classification model allows assessing the therapeutic behaviour of ampholytic substances on the basis of solely values of descriptors that can be obtained computationally. Thus, the prediction is possible without necessity of carrying out time-consuming and expensive laboratory tests, which is its main advantage.
Hsieh, Sheng-Hsun; Wang, Wei; Tien, Chung-Hao
2018-01-01
In this study, we maneuvered a dual-band spectral imaging system to capture an iridal image from a cosmetic-contact-lens-wearing subject. By using the independent component analysis to separate individual spectral primitives, we successfully distinguished the natural iris texture from the cosmetic contact lens (CCL) pattern, and restored the genuine iris patterns from the CCL-polluted image. Based on a database containing 200 test image pairs from 20 CCL-wearing subjects as the proof of concept, the recognition accuracy (False Rejection Rate: FRR) was improved from FRR = 10.52% to FRR = 0.57% with the proposed ICA anti-spoofing scheme. PMID:29509692
NASA Astrophysics Data System (ADS)
Xu, Jingjiang; Guo, Baoshan; Wong, Kenneth K. Y.; Tsia, Kevin K.
2014-02-01
Routine procedures in standard histopathology involve laborious steps of tissue processing and staining for final examination. New techniques which can bypass these procedures and thus minimize the tissue handling error would be of great clinical value. Coherent anti-Stokes Raman scattering (CARS) microscopy is an attractive tool for label-free biochemical-specific characterization of biological specimen. However, a vast majority of prior works on CARS (or stimulated Raman scattering (SRS)) bioimaging restricted analyses on a narrowband or well-distinctive Raman spectral signatures. Although hyperspectral SRS/CARS imaging has recently emerged as a better solution to access wider-band spectral information in the image, studies mostly focused on a limited spectral range, e.g. CH-stretching vibration of lipids, or non-biological samples. Hyperspectral image information in the congested fingerprint spectrum generally remains untapped for biological samples. In this regard, we further explore ultrabroadband hyperspectral multiplex (HM-CARS) to perform chemoselective histological imaging with the goal of exploring its utility in stain-free clinical histopathology. Using the supercontinuum Stokes, our system can access the CARS spectral window as wide as >2000cm-1. In order to unravel the congested CARS spectra particularly in the fingerprint region, we first employ a spectral phase-retrieval algorithm based on Kramers-Kronig (KK) transform to minimize the non-resonant background in the CARS spectrum. We then apply principal component analysis (PCA) to identify and map the spatial distribution of different biochemical components in the tissues. We demonstrate chemoselective HM-CARS imaging of a colon tissue section which displays the key cellular structures that correspond well with standard stained-tissue observation.
Prokhorov, Alexander; Prokhorova, Nina I
2012-11-20
We applied the bidirectional reflectance distribution function (BRDF) model consisting of diffuse, quasi-specular, and glossy components to the Monte Carlo modeling of spectral effective emissivities for nonisothermal cavities. A method for extension of a monochromatic three-component (3C) BRDF model to a continuous spectral range is proposed. The initial data for this method are the BRDFs measured in the plane of incidence at a single wavelength and several incidence angles and directional-hemispherical reflectance measured at one incidence angle within a finite spectral range. We proposed the Monte Carlo algorithm for calculation of spectral effective emissivities for nonisothermal cavities whose internal surface is described by the wavelength-dependent 3C BRDF model. The results obtained for a cylindroconical nonisothermal cavity are discussed and compared with results obtained using the conventional specular-diffuse model.
Dhanapal, Arun Prabhu; Ray, Jeffery D; Singh, Shardendu K; Hoyos-Villegas, Valerio; Smith, James R; Purcell, Larry C; Fritschi, Felix B
2016-08-04
Chlorophyll is a major component of chloroplasts and a better understanding of the genetic basis of chlorophyll in soybean [Glycine max (L.) Merr.] might contribute to improving photosynthetic capacity and yield in regions with adverse environmental conditions. A collection of 332 diverse soybean genotypes were grown in 2 years (2009 and 2010) and chlorophyll a (eChl_A), chlorophyll b (eChl_B), and total chlorophyll (eChl_T) content as well as chlorophyll a/b ratio (eChl_R) in leaf tissues were determined by extraction and spectrometric determination. Total chlorophyll was also derived from canopy spectral reflectance measurements using a model of wavelet transformed spectra (tChl_T) as well as with a spectral reflectance index (iChl_T). A genome-wide associating mapping approach was employed using 31,253 single nucleotide polymorphisms (SNPs) to identify loci associated with the extract based eChl_A, eChl_B, eChl_R and eChl_T measurements and the two canopy spectral reflectance-based methods (tChl_T and iChl_T). A total of 23 (14 loci), 15 (7 loci) and 14 SNPs (10 loci) showed significant association with eChl_A, eChl_B and eChl_R respectively. A total of 52 unique SNPs were significantly associated with total chlorophyll content based on at least one of the three approaches (eChl_T, tChl_T and iChl_T) and likely tagged 27 putative loci for total chlorophyll content, four of which were indicated by all three approaches. Results presented here show that markers for chlorophyll traits can be identified in soybean using both extract-based and canopy spectral reflectance-based phenotypes, and confirm that high-throughput phenotyping-amenable canopy spectral reflectance measurements can be used for association mapping.
Subpixel target detection and enhancement in hyperspectral images
NASA Astrophysics Data System (ADS)
Tiwari, K. C.; Arora, M.; Singh, D.
2011-06-01
Hyperspectral data due to its higher information content afforded by higher spectral resolution is increasingly being used for various remote sensing applications including information extraction at subpixel level. There is however usually a lack of matching fine spatial resolution data particularly for target detection applications. Thus, there always exists a tradeoff between the spectral and spatial resolutions due to considerations of type of application, its cost and other associated analytical and computational complexities. Typically whenever an object, either manmade, natural or any ground cover class (called target, endmembers, components or class) gets spectrally resolved but not spatially, mixed pixels in the image result. Thus, numerous manmade and/or natural disparate substances may occur inside such mixed pixels giving rise to mixed pixel classification or subpixel target detection problems. Various spectral unmixing models such as Linear Mixture Modeling (LMM) are in vogue to recover components of a mixed pixel. Spectral unmixing outputs both the endmember spectrum and their corresponding abundance fractions inside the pixel. It, however, does not provide spatial distribution of these abundance fractions within a pixel. This limits the applicability of hyperspectral data for subpixel target detection. In this paper, a new inverse Euclidean distance based super-resolution mapping method has been presented that achieves subpixel target detection in hyperspectral images by adjusting spatial distribution of abundance fraction within a pixel. Results obtained at different resolutions indicate that super-resolution mapping may effectively aid subpixel target detection.
NASA Technical Reports Server (NTRS)
Hellman, R. P.
1985-01-01
A large scale laboratory investigation of loudness, annoyance, and noisiness produced by single-tone-noise complexes was undertaken to establish a broader data base for quanitification and prediction of perceived annoyance of sounds containing tonal components. Loudness, annoyance, and noisiness were distinguished as separate, distinct, attributes of sound. Three different spectral patterns of broadband noise with and without added tones were studied: broadband-flat, low-pass, and high-pass. Judgments were obtained by absolute magnitude estimation supplement by loudness matching. The data were examined and evaluated to determine the potential effects of (1) the overall sound pressure level (SPL) of the noise-tone complex, (2) tone SPL, (3) noise SPL, (4) tone-to-noise ratio, (5) the frequency of the added tone, (6) noise spectral shape, and (7) subjective attribute judged on absolute magnitude of annoyance. Results showed that, in contrast to noisiness, loudness and annoyance growth behavior depends on the relationship between the frequency of the added tone and the spectral shape of the noise. The close correspondence between the frequency of the added tone and the spectral shape of the noise. The close correspondence between loundness and annoyance suggests that, to better understand perceived annoyance of sound mixtures, it is necessary to relate the results to basic auditory mechanisms governing loudness and masking.
NASA Technical Reports Server (NTRS)
Thejappa, G.; MacDowall, R. J.; Bergamo, M.
2012-01-01
We present the high time resolution observations of one of the Langmuir wave packets obtained in the source region of a solar type III radio burst. This wave packet satisfies the threshold condition of the supersonic modulational instability, as well as the criterion of a collapsing Langmuir soliton, i.e., the spatial scale derived from its peak intensity is less than that derived from its short time scale. The spectrum of t his wave packet contains an intense spectral peak at local electron plasma frequency, f(sub pe) and relatively weaker peaks at 2f(sub pe) and 3f(sub pe). We apply the wavelet based bispectral analysis technique on this wave packet and compute the bicoherence between its spectral components. It is found that the bicoherence exhibits two peaks at (approximately f(sub pe), approximately f(sub pe)) and (approximately f(sub pe) approximately 2f(sub pe)), which strongly suggest that the spectral peak at 2f(sub pe) probably corresponds to the second harmonic radio emission, generated as a result of the merging of antiparallel propagating Langmuir waves trapped in the collapsing Langmuir soliton, and, the spectral peak at 3f(sub pe) probably corresponds to the third harmonic radio emission, generated as a result of merging of a trapped Langmuir wave and a second harmonic electromagnetic wave.
Compact terahertz spectrometer based on disordered rough surfaces
NASA Astrophysics Data System (ADS)
Yang, Tao; Jiang, Bing; Ge, Jia-cheng; Zhu, Yong-yuan; Li, Xing-ao; Huang, Wei
2018-01-01
In this paper, a compact spectrometer based on disordered rough surfaces for operation in the terahertz band is presented. The proposed spectrometer consists of three components, which are used for dispersion, modulation and detection respectively. The disordered rough surfaces, which are acted as the dispersion component, are modulated by the modulation component. Different scattering intensities are captured by the detection component with different extent of modulation. With a calibration measurement process, one can reconstruct the spectra of the probe terahertz beam by solving a system of simultaneous linear equations. A Tikhonov regularization approach has been implemented to improve the accuracy of the spectral reconstruction. The reported broadband, compact, high-resolution terahertz spectrometer is well suited for portable terahertz spectroscopy applications.
NASA Technical Reports Server (NTRS)
Jin, Zhonghai; Wielicki, Bruce A.; Loukachine, Constantin; Charlock, Thomas P.; Young, David; Noeel, Stefan
2011-01-01
The radiative kernel approach provides a simple way to separate the radiative response to different climate parameters and to decompose the feedback into radiative and climate response components. Using CERES/MODIS/Geostationary data, we calculated and analyzed the solar spectral reflectance kernels for various climate parameters on zonal, regional, and global spatial scales. The kernel linearity is tested. Errors in the kernel due to nonlinearity can vary strongly depending on climate parameter, wavelength, surface, and solar elevation; they are large in some absorption bands for some parameters but are negligible in most conditions. The spectral kernels are used to calculate the radiative responses to different climate parameter changes in different latitudes. The results show that the radiative response in high latitudes is sensitive to the coverage of snow and sea ice. The radiative response in low latitudes is contributed mainly by cloud property changes, especially cloud fraction and optical depth. The large cloud height effect is confined to absorption bands, while the cloud particle size effect is found mainly in the near infrared. The kernel approach, which is based on calculations using CERES retrievals, is then tested by direct comparison with spectral measurements from Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY) (a different instrument on a different spacecraft). The monthly mean interannual variability of spectral reflectance based on the kernel technique is consistent with satellite observations over the ocean, but not over land, where both model and data have large uncertainty. RMS errors in kernel ]derived monthly global mean reflectance over the ocean compared to observations are about 0.001, and the sampling error is likely a major component.
NASA Technical Reports Server (NTRS)
Kao, G. C.
1973-01-01
Method has been developed for predicting interaction between components and corresponding support structures subjected to acoustic excitations. Force environments determined in spectral form are called force spectra. Force-spectra equation is determined based on one-dimensional structural impedance model.
Smith, Zachary J; Strombom, Sven; Wachsmann-Hogiu, Sebastian
2011-08-29
A multivariate optical computer has been constructed consisting of a spectrograph, digital micromirror device, and photomultiplier tube that is capable of determining absolute concentrations of individual components of a multivariate spectral model. We present experimental results on ternary mixtures, showing accurate quantification of chemical concentrations based on integrated intensities of fluorescence and Raman spectra measured with a single point detector. We additionally show in simulation that point measurements based on principal component spectra retain the ability to classify cancerous from noncancerous T cells.
Evaluation of the robustness of estimating five components from a skin spectral image
NASA Astrophysics Data System (ADS)
Akaho, Rina; Hirose, Misa; Tsumura, Norimichi
2018-04-01
We evaluated the robustness of a method used to estimate five components (i.e., melanin, oxy-hemoglobin, deoxy-hemoglobin, shading, and surface reflectance) from the spectral reflectance of skin at five wavelengths against noise and a change in epidermis thickness. We also estimated the five components from recorded images of age spots and circles under the eyes using the method. We found that noise in the image must be no more 0.1% to accurately estimate the five components and that the thickness of the epidermis affects the estimation. We acquired the distribution of major causes for age spots and circles under the eyes by applying the method to recorded spectral images.
NASA Technical Reports Server (NTRS)
Lichtenstein, J. H.
1975-01-01
Power-spectral-density calculations were made of the lateral responses to atmospheric turbulence for several conventional and short take-off and landing (STOL) airplanes. The turbulence was modeled as three orthogonal velocity components, which were uncorrelated, and each was represented with a one-dimensional power spectrum. Power spectral densities were computed for displacements, rates, and accelerations in roll, yaw, and sideslip. In addition, the power spectral density of the transverse acceleration was computed. Evaluation of ride quality based on a specific ride quality criterion was also made. The results show that the STOL airplanes generally had larger values for the rate and acceleration power spectra (and, consequently, larger corresponding root-mean-square values) than the conventional airplanes. The ride quality criterion gave poorer ratings to the STOL airplanes than to the conventional airplanes.
The MIND PALACE: A Multi-Spectral Imaging and Spectroscopy Database for Planetary Science
NASA Astrophysics Data System (ADS)
Eshelman, E.; Doloboff, I.; Hara, E. K.; Uckert, K.; Sapers, H. M.; Abbey, W.; Beegle, L. W.; Bhartia, R.
2017-12-01
The Multi-Instrument Database (MIND) is the web-based home to a well-characterized set of analytical data collected by a suite of deep-UV fluorescence/Raman instruments built at the Jet Propulsion Laboratory (JPL). Samples derive from a growing body of planetary surface analogs, mineral and microbial standards, meteorites, spacecraft materials, and other astrobiologically relevant materials. In addition to deep-UV spectroscopy, datasets stored in MIND are obtained from a variety of analytical techniques obtained over multiple spatial and spectral scales including electron microscopy, optical microscopy, infrared spectroscopy, X-ray fluorescence, and direct fluorescence imaging. Multivariate statistical analysis techniques, primarily Principal Component Analysis (PCA), are used to guide interpretation of these large multi-analytical spectral datasets. Spatial co-referencing of integrated spectral/visual maps is performed using QGIS (geographic information system software). Georeferencing techniques transform individual instrument data maps into a layered co-registered data cube for analysis across spectral and spatial scales. The body of data in MIND is intended to serve as a permanent, reliable, and expanding database of deep-UV spectroscopy datasets generated by this unique suite of JPL-based instruments on samples of broad planetary science interest.
Reconstruction of hyperspectral image using matting model for classification
NASA Astrophysics Data System (ADS)
Xie, Weiying; Li, Yunsong; Ge, Chiru
2016-05-01
Although hyperspectral images (HSIs) captured by satellites provide much information in spectral regions, some bands are redundant or have large amounts of noise, which are not suitable for image analysis. To address this problem, we introduce a method for reconstructing the HSI with noise reduction and contrast enhancement using a matting model for the first time. The matting model refers to each spectral band of an HSI that can be decomposed into three components, i.e., alpha channel, spectral foreground, and spectral background. First, one spectral band of an HSI with more refined information than most other bands is selected, and is referred to as an alpha channel of the HSI to estimate the hyperspectral foreground and hyperspectral background. Finally, a combination operation is applied to reconstruct the HSI. In addition, the support vector machine (SVM) classifier and three sparsity-based classifiers, i.e., orthogonal matching pursuit (OMP), simultaneous OMP, and OMP based on first-order neighborhood system weighted classifiers, are utilized on the reconstructed HSI and the original HSI to verify the effectiveness of the proposed method. Specifically, using the reconstructed HSI, the average accuracy of the SVM classifier can be improved by as much as 19%.
Prediction of spectral acceleration response ordinates based on PGA attenuation
Graizer, V.; Kalkan, E.
2009-01-01
Developed herein is a new peak ground acceleration (PGA)-based predictive model for 5% damped pseudospectral acceleration (SA) ordinates of free-field horizontal component of ground motion from shallow-crustal earthquakes. The predictive model of ground motion spectral shape (i.e., normalized spectrum) is generated as a continuous function of few parameters. The proposed model eliminates the classical exhausted matrix of estimator coefficients, and provides significant ease in its implementation. It is structured on the Next Generation Attenuation (NGA) database with a number of additions from recent Californian events including 2003 San Simeon and 2004 Parkfield earthquakes. A unique feature of the model is its new functional form explicitly integrating PGA as a scaling factor. The spectral shape model is parameterized within an approximation function using moment magnitude, closest distance to the fault (fault distance) and VS30 (average shear-wave velocity in the upper 30 m) as independent variables. Mean values of its estimator coefficients were computed by fitting an approximation function to spectral shape of each record using robust nonlinear optimization. Proposed spectral shape model is independent of the PGA attenuation, allowing utilization of various PGA attenuation relations to estimate the response spectrum of earthquake recordings.
Saito, Yasunori; Kakuda, Kei; Yokoyama, Mizuho; Kubota, Tomoki; Tomida, Takayuki; Park, Ho-Dong
2016-08-20
In this work, we developed mobile laser-induced fluorescence spectrum (LIFS) lidar based on preliminary experiments on the excitation emission matrix of a water sample and a method for reducing solar background light using the synchronous detection technique. The combination of a UV short-pulse laser (355 nm, 6 ns) for fluorescence excitation with a 10-100 ns short-time synchronous detection using a gated image-intensified multi-channel CCD of the fluorescence made the LIFS lidar operation possible even in daytime. The LIFS lidar with this construction demonstrated the potential of natural river/lake water quality monitoring at the Tenryu River/Lake Suwa. Three main components in the fluorescence data of the water, dissolved organic matter, phycocyanin, and chlorophyll, were extracted by spectral analysis using the standard spectral functions of these components. Their concentrations were estimated by adapting experimentally calibrated data. Results of long-term field observations using our LIFS lidar from 2010 to 2012 show the necessity of simultaneous multi-component detection to understand the natural water environment.
Spectral optimization simulation of white light based on the photopic eye-sensitivity curve
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dai, Qi, E-mail: qidai@tongji.edu.cn; Institute for Advanced Study, Tongji University, 1239 Siping Road, Shanghai 200092; Key Laboratory of Ecology and Energy-saving Study of Dense Habitat
Spectral optimization simulation of white light is studied to boost maximum attainable luminous efficacy of radiation at high color-rendering index (CRI) and various color temperatures. The photopic eye-sensitivity curve V(λ) is utilized as the dominant portion of white light spectra. Emission spectra of a blue InGaN light-emitting diode (LED) and a red AlInGaP LED are added to the spectrum of V(λ) to match white color coordinates. It is demonstrated that at the condition of color temperature from 2500 K to 6500 K and CRI above 90, such white sources can achieve spectral efficacy of 330–390 lm/W, which is higher than the previously reportedmore » theoretical maximum values. We show that this eye-sensitivity-based approach also has advantages on component energy conversion efficiency compared with previously reported optimization solutions.« less
Spectral variations of LMC X-3 observed with Ginga
NASA Technical Reports Server (NTRS)
Ebisawa, Ken; Makino, Fumiyoshi; Mitsuda, Kazuhisa; Belloni, Tomaso; Cowley, Anne P.; Schmidtke, Paul C.; Treves, Aldo
1993-01-01
The prime black hole candidate LMC X-3 was observed over three years with the Ginga satellite, and a characteristic spectral variation was found accompanying the periodic intensity variation of about 198 (or possibly about 99) days (Cowley et al., 1991). The energy spectrum of LMC X-3 consists of the soft, thermal component and the hard, power-law component, which are respectively dominant below and above about 9 keV. The soft component, which carries most of the X-ray intensity, shows a clear correlation between the intensity and the hardness, while the hard component varies independently of the soft component. It was found that the spectral variation of the soft component is well described by an optically thick accretion disk model with a remarkably constant innermost radius and variable mass accretion rate. The constancy of the innermost radius suggests it is related to the mass of the central object.
NASA Astrophysics Data System (ADS)
Dykema, John A.; Anderson, James G.
2006-06-01
A methodology to achieve spectral thermal radiance measurements from space with demonstrable on-orbit traceability to the International System of Units (SI) is described. This technique results in measurements of infrared spectral radiance R(\\tilde {\\upsilon }) , with spectral index \\tilde {\\upsilon } in cm-1, with a relative combined uncertainty u_c[R(\\tilde {\\upsilon })] of 0.0015 (k = 1) for the average mid-infrared radiance emitted by the Earth. This combined uncertainty, expressed in brightness temperature units, is equivalent to ±0.1 K at 250 K at 750 cm-1. This measurement goal is achieved by utilizing a new method for infrared scale realization combined with an instrument design optimized to minimize component uncertainties and admit tests of radiometric performance. The SI traceability of the instrument scale is established by evaluation against source-based and detector-based infrared scales in defined laboratory protocols before launch. A novel strategy is executed to ensure fidelity of on-orbit calibration to the pre-launch scale. This strategy for on-orbit validation relies on the overdetermination of instrument calibration. The pre-launch calibration against scales derived from physically independent paths to the base SI units provides the foundation for a critical analysis of the overdetermined on-orbit calibration to establish an SI-traceable estimate of the combined measurement uncertainty. Redundant calibration sources and built-in diagnostic tests to assess component measurement uncertainties verify the SI traceability of the instrument calibration over the mission lifetime. This measurement strategy can be realized by a practical instrument, a prototype Fourier-transform spectrometer under development for deployment on a small satellite. The measurement record resulting from the methodology described here meets the observational requirements for climate monitoring and climate model testing and improvement.
NASA Astrophysics Data System (ADS)
Sheiner, Olga; Snegirev, Sergei; Smirnova, Anna
The importance problem of Solar-terrestrial physics is regular forecasting of solar activity phenomena, which negatively influence the human’s health, operating safety, communication, radar sets and others. We previously reported the existence of long-period pulsations of H component of the geomagnetic field recorded at stations tested 2-3 days before the proton solar flares. There are the increasing of pulsation amplitude of the horizontal component of the magnetic field with periods of 30-60 minutes. The spectrum of the flux of ultraviolet solar radiation on the eve of proton flares was conducted to determine the presence of oscillations - precursors of flares, as one of the possible agents causing amplification of large periods pulsations of H component of the geomagnetic field. Used data on ultraviolet radiation of the sun with a wavelength of 115-127 nm are obtained from a geostationary satellite GOES 15, the method of wavelet analysis is used. It is found the congruence in the behavior of spectral components with periods of 30-60 minutes in the ground-based measurements and in UV emission for 3-1 days before the proton flare.
Lee, Norman; Schrode, Katrina M; Bee, Mark A
2017-09-01
Diverse animals communicate using multicomponent signals. How a receiver's central nervous system integrates multiple signal components remains largely unknown. We investigated how female green treefrogs (Hyla cinerea) integrate the multiple spectral components present in male advertisement calls. Typical calls have a bimodal spectrum consisting of formant-like low-frequency (~0.9 kHz) and high-frequency (~2.7 kHz) components that are transduced by different sensory organs in the inner ear. In behavioral experiments, only bimodal calls reliably elicited phonotaxis in no-choice tests, and they were selectively chosen over unimodal calls in two-alternative choice tests. Single neurons in the inferior colliculus of awake, passively listening subjects were classified as combination-insensitive units (27.9%) or combination-sensitive units (72.1%) based on patterns of relative responses to the same bimodal and unimodal calls. Combination-insensitive units responded similarly to the bimodal call and one or both unimodal calls. In contrast, combination-sensitive units exhibited both linear responses (i.e., linear summation) and, more commonly, nonlinear responses (e.g., facilitation, compressive summation, or suppression) to the spectral combination in the bimodal call. These results are consistent with the hypothesis that nonlinearities play potentially critical roles in spectral integration and in the neural processing of multicomponent communication signals.
UV-vis spectroscopic studies of CaF2 photo-thermo-refractive glass
NASA Astrophysics Data System (ADS)
Stoica, Martina; Herrmann, Andreas; Hein, Joachim; Rüssel, Christian
2016-12-01
A photo-thermo-refractive glass based on the system Na2O/K2O/CaO/CaF2/Al2O3/ZnO/SiO2 doped with Ag2O, CeO2, SnO2, Sb2O3 and KBr was investigated. This glass undergoes a permanent refractive index change after UV irradiation and subsequent two step heat treatment at temperatures above Tg. This is due to the formation of Ag metal clusters which act as nucleation centers for CaF2 crystallization. Oxidation of Ce3+ by UV light is the initial reaction and acts as photosensitizer in the glass. The UV-vis absorption spectra during this photo-induced crystallization process were measured. The spectral components that form the absorption spectra of cerium were studied in detail by a band separation with Gaussian functions. Deconvolution of the cerium absorption bands shows an envelope of five spectral components for the trivalent cerium due to the 4f-5d transitions and two spectral components for the tetravalent cerium caused by charge transfer transitions. The effect of different dopants and melting conditions on the photo-thermal process were studied to investigate the influence of glass technology on the photoprocess.
Zu, Qin; Zhao, Chun-Jiang; Deng, Wei; Wang, Xiu
2013-05-01
The automatic identification of weeds forms the basis for precision spraying of crops infest. The canopy spectral reflectance within the 350-2 500 nm band of two strains of cabbages and five kinds of weeds such as barnyard grass, setaria, crabgrass, goosegrass and pigweed was acquired by ASD spectrometer. According to the spectral curve characteristics, the data in different bands were compressed with different levels to improve the operation efficiency. Firstly, the spectrum was denoised in accordance with the different order of multiple scattering correction (MSC) method and Savitzky-Golay (SG) convolution smoothing method set by different parameters, then the model was built by combining the principal component analysis (PCA) method to extract principal components, finally all kinds of plants were classified by using the soft independent modeling of class analogy (SIMCA) taxonomy and the classification results were compared. The tests results indicate that after the pretreatment of the spectral data with the method of the combination of MSC and SG set with 3rd order, 5th degree polynomial, 21 smoothing points, and the top 10 principal components extraction using PCA as a classification model input variable, 100% correct classification rate was achieved, and it is able to identify cabbage and several kinds of common weeds quickly and nondestructively.
Separation of musical instruments based on amplitude and frequency comodulation
NASA Astrophysics Data System (ADS)
Jacobson, Barry D.; Cauwenberghs, Gert; Quatieri, Thomas F.
2002-05-01
In previous work, amplitude comodulation was investigated as a basis for monaural source separation. Amplitude comodulation refers to similarities in amplitude envelopes of individual spectral components emitted by particular types of sources. In many types of musical instruments, amplitudes of all resonant modes rise/fall, and start/stop together during the course of normal playing. We found that under certain well-defined conditions, a mixture of constant frequency, amplitude comodulated sources can unambiguously be decomposed into its constituents on the basis of these similarities. In this work, system performance was improved by relaxing the constant frequency requirement. String instruments, for example, which are normally played with vibrato, are both amplitude and frequency comodulated sources, and could not be properly tracked under the constant frequency assumption upon which our original algorithm was based. Frequency comodulation refers to similarities in frequency variations of individual harmonics emitted by these types of sources. The analytical difficulty is in defining a representation of the source which properly tracks frequency varying components. A simple, fixed filter bank can only track an individual spectral component for the duration in which it is within the passband of one of the filters. Alternatives are therefore explored which are amenable to real-time implementation.
A semi-supervised classification algorithm using the TAD-derived background as training data
NASA Astrophysics Data System (ADS)
Fan, Lei; Ambeau, Brittany; Messinger, David W.
2013-05-01
In general, spectral image classification algorithms fall into one of two categories: supervised and unsupervised. In unsupervised approaches, the algorithm automatically identifies clusters in the data without a priori information about those clusters (except perhaps the expected number of them). Supervised approaches require an analyst to identify training data to learn the characteristics of the clusters such that they can then classify all other pixels into one of the pre-defined groups. The classification algorithm presented here is a semi-supervised approach based on the Topological Anomaly Detection (TAD) algorithm. The TAD algorithm defines background components based on a mutual k-Nearest Neighbor graph model of the data, along with a spectral connected components analysis. Here, the largest components produced by TAD are used as regions of interest (ROI's),or training data for a supervised classification scheme. By combining those ROI's with a Gaussian Maximum Likelihood (GML) or a Minimum Distance to the Mean (MDM) algorithm, we are able to achieve a semi supervised classification method. We test this classification algorithm against data collected by the HyMAP sensor over the Cooke City, MT area and University of Pavia scene.
Principal components analysis of Jupiter VIMS spectra
Bellucci, G.; Formisano, V.; D'Aversa, E.; Brown, R.H.; Baines, K.H.; Bibring, J.-P.; Buratti, B.J.; Capaccioni, F.; Cerroni, P.; Clark, R.N.; Coradini, A.; Cruikshank, D.P.; Drossart, P.; Jaumann, R.; Langevin, Y.; Matson, D.L.; McCord, T.B.; Mennella, V.; Nelson, R.M.; Nicholson, P.D.; Sicardy, B.; Sotin, Christophe; Chamberlain, M.C.; Hansen, G.; Hibbits, K.; Showalter, M.; Filacchione, G.
2004-01-01
During Cassini - Jupiter flyby occurred in December 2000, Visual-Infrared mapping spectrometer (VIMS) instrument took several image cubes of Jupiter at different phase angles and distances. We have analysed the spectral images acquired by the VIMS visual channel by means of a principal component analysis technique (PCA). The original data set consists of 96 spectral images in the 0.35-1.05 ??m wavelength range. The product of the analysis are new PC bands, which contain all the spectral variance of the original data. These new components have been used to produce a map of Jupiter made of seven coherent spectral classes. The map confirms previously published work done on the Great Red Spot by using NIMS data. Some other new findings, presently under investigation, are presented. ?? 2004 Published by Elsevier Ltd on behalf of COSPAR.
SCOUSE: Semi-automated multi-COmponent Universal Spectral-line fitting Engine
NASA Astrophysics Data System (ADS)
Henshaw, J. D.; Longmore, S. N.; Kruijssen, J. M. D.; Davies, B.; Bally, J.; Barnes, A.; Battersby, C.; Burton, M.; Cunningham, M. R.; Dale, J. E.; Ginsburg, A.; Immer, K.; Jones, P. A.; Kendrew, S.; Mills, E. A. C.; Molinari, S.; Moore, T. J. T.; Ott, J.; Pillai, T.; Rathborne, J.; Schilke, P.; Schmiedeke, A.; Testi, L.; Walker, D.; Walsh, A.; Zhang, Q.
2016-01-01
The Semi-automated multi-COmponent Universal Spectral-line fitting Engine (SCOUSE) is a spectral line fitting algorithm that fits Gaussian files to spectral line emission. It identifies the spatial area over which to fit the data and generates a grid of spectral averaging areas (SAAs). The spatially averaged spectra are fitted according to user-provided tolerance levels, and the best fit is selected using the Akaike Information Criterion, which weights the chisq of a best-fitting solution according to the number of free-parameters. A more detailed inspection of the spectra can be performed to improve the fit through an iterative process, after which SCOUSE integrates the new solutions into the solution file.
Opto-mechanical design of the MTG FCI spectral separation assembly
NASA Astrophysics Data System (ADS)
Riguet, François; Brousse, Emmanuel; Carel, Jean-Louis; Cottenye, Justine; Harmann, David; Joncour, Marc; Makhlouf, Houssine; Mouricaud, Daniel; Oussalah, Meihdi; Rodolfo, Jacques
2015-09-01
The Spectral Separation Assembly is a key component of the Flexible Combined Imager, an instrument that will be on-board Meteosat Third Generation. It splits the input beam coming from the telescope into five spectral groups, for a total of 16 channels, from 0.4 to 13.3 μm. It comprises a set of four dichroics separators followed by four collimating optics for the infrared spectral groups, which feed the cold imaging optics. The visible spectral group is directly imaged on a detector. This paper presents the optical design of the assembly, the mechanical mounting of the optical components, and the coatings developed for the dichroics, mirrors and lenses.
NASA Astrophysics Data System (ADS)
Kuznetsov, A. G.; Babin, Sergei A.; Shelemba, Ivan S.
2009-11-01
We demonstrate a Raman-based all-fibre temperature sensor utilising a pulsed erbium fibre laser. The sensor is made of a standard single-mode telecom fibre, SMF-28, and includes a number of directional couplers as band-pass filters. The temperature profile along a 7-km fibreoptic line is measured with an accuracy of 2oC and a spatial resolution of 10 m. In data processing, we take into account the difference in attenuation between the spectral components of the backscatter signal.
Testing of motor unit synchronization model for localized muscle fatigue.
Naik, Ganesh R; Kumar, Dinesh K; Yadav, Vivek; Wheeler, Katherine; Arjunan, Sridhar
2009-01-01
Spectral compression of surface electromyogram (sEMG) is associated with onset of localized muscle fatigue. The spectral compression has been explained based on motor unit synchronization theory. According to this theory, motor units are pseudo randomly excited during muscle contraction, and with the onset of muscle fatigue the recruitment pattern changes such that motor unit firings become more synchronized. While this is widely accepted, there is little experimental proof of this phenomenon. This paper has used source dependence measures developed in research related to independent component analysis (ICA) to test this theory.
NASA Astrophysics Data System (ADS)
Rao, Roshan
2016-04-01
Aerosol radiative forcing estimates with high certainty are required in climate change studies. The approach in estimating the aerosol radiative forcing by using the chemical composition of aerosols is not effective as the chemical composition data with radiative properties are not widely available. We look into the approach where ground based spectral radiation flux measurement is made and along with an Radtiative transfer (RT) model, radiative forcing is estimated. Measurements of spectral flux were made using an ASD spectroradiometer with 350 - 1050 nm wavelength range and a 3nm resolution during around 54 clear-sky days during which AOD range was around 0.01 to 0.7. Simultaneous measurements of black carbon were also made using Aethalometer (Magee Scientific) which ranged from around 1.5 ug/m3 to 8 ug/m3. The primary study involved in understanding the sensitivity of spectral flux due to change in individual aerosol species (Optical properties of Aerosols and Clouds (OPAC) classified aerosol species) using the SBDART RT model. This made us clearly distinguish the influence of different aerosol species on the spectral flux. Following this, a new technique has been introduced to estimate an optically equivalent mixture of aerosol species for the given location. The new method involves matching different combinations of aerosol species in OPAC model and RT model as long as the combination which gives the minimum root mean squared deviation from measured spectral flux is obtained. Using the optically equivalent aerosol mixture and RT model, aerosol radiative forcing is estimated. Also an alternate method to estimate the spectral SSA is discussed. Here, the RT model, the observed spectral flux and spectral AOD is used. Spectral AOD is input to RT model and SSA is varied till the minimum root mean squared difference between observed and simulated spectral flux from RT model is obtained. The methods discussed are limited to clear sky scenes and its accuracy to derive an optically equivalent aerosol mixture reduces when diffuse component of flux increases. In our analysis, RT model clearly shows that direct component of spectral flux is more sensitive to different aerosol species than total spectral flux which is also supported by our observed data.
Separate Spectra of the Components of the Low-mass Binary L722-22
NASA Astrophysics Data System (ADS)
Chance, D.; Hershey, J.
1996-12-01
Separate spectra have been acquired of the components of the low-mass binary L722-22A,B. Using the Hubble Space Telescope Faint Object Spectrograph in the same manner described in BAAS 27,1341 for Ross 614A,B a small aperture was placed on each star, excluding the light from the other. L722-22 was discovered to be a binary by Ianna (1988, AJ 95,1226) from a small photographic photocentric orbit found in parallax observations. The ground-based work indicated L722-22B might have a mass in the brown-dwarf range, at 0.06 M_⊙ which motivated the FOS observations. However, current HST astrometric work indicates L722-22B is at the 0.1 M_⊙ level (Taff, Hershey Space Telescope Astrometry Team 75th Meeting Report, Apr 1996). Ground based CCD spectra of M dwarf standards have been provided to us by J. Davy Kirkpatrick in the 6300 to 8500 Angstroms range. Apart from the telluric lines the FOS spectra interpolate very closely into the ground-based series across this spectral range. A classification program has been written which defines a series of spectral interval ratios, does fits for the indices of the standards as a function of spectral subtype across the M3 to M7 range of standards, and inverts the fits for the four unknown spectra of Ross 614A,B and L722-22A,B. The internal formal error of the mean from the series of indices is a small fraction of a spectral subtype. The spectral types of L722-22A and B are found to be earlier by about 3/4 of a spectral subtype than Ross 614A and B, respectively. The HST astrometry and spectroscopy yield points for these 4 binary members which lie in a very narrow locus in the mass-spectral type plane and imply that single stars of types dM6 and later, have masses less than 0.08 M_⊙, presumably substellar. Support for this work was provided by NASA through grant number 06048 from the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc. under NASA contract NAS5-26555.
Yue, Zheng-Bo; Zhang, Meng-Lin; Sheng, Guo-Ping; Liu, Rong-Hua; Long, Ying; Xiang, Bing-Ren; Wang, Jin; Yu, Han-Qing
2010-04-01
A near-infrared-reflectance (NIR) spectroscopy-based method is established to determine the main components of aquatic plants as well as their anaerobic rumen biodegradability. The developed method is more rapid and accurate compared to the conventional chemical analysis and biodegradability tests. Moisture, volatile solid, Klason lignin and ash in entire aquatic plants could be accurately predicted using this method with coefficient of determination (r(2)) values of 0.952, 0.916, 0.939 and 0.950, respectively. In addition, the anaerobic rumen biodegradability of aquatic plants, represented as biogas and methane yields, could also be predicted well. The algorithm of continuous wavelet transform for the NIR spectral data pretreatment is able to greatly enhance the robustness and predictive ability of the NIR spectral analysis. These results indicate that NIR spectroscopy could be used to predict the main components of aquatic plants and their anaerobic biodegradability. Copyright (c) 2009 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Cao, Qian; Wan, Xiaoxia; Li, Junfeng; Liu, Qiang; Liang, Jingxing; Li, Chan
2016-10-01
This paper proposed two weight functions based on principal component analysis (PCA) to reserve more colorimetric information in spectral data compression process. One weight function consisted of the CIE XYZ color-matching functions representing the characteristic of the human visual system, while another was made up of the CIE XYZ color-matching functions of human visual system and relative spectral power distribution of the CIE standard illuminant D65. The improvement obtained from the proposed two methods were tested to compress and reconstruct the reflectance spectra of 1600 glossy Munsell color chips and 1950 Natural Color System color chips as well as six multispectral images. The performance was evaluated by the mean values of color difference under the CIE 1931 standard colorimetric observer and the CIE standard illuminant D65 and A. The mean values of root mean square errors between the original and reconstructed spectra were also calculated. The experimental results show that the proposed two methods significantly outperform the standard PCA and another two weighted PCA in the aspects of colorimetric reconstruction accuracy with very slight degradation in spectral reconstruction accuracy. In addition, weight functions with the CIE standard illuminant D65 can improve the colorimetric reconstruction accuracy compared to weight functions without the CIE standard illuminant D65.
Buchholz, Jörg M
2011-07-01
Coloration detection thresholds (CDTs) were measured for a single reflection as a function of spectral content and reflection delay for diotic stimulus presentation. The direct sound was a 320-ms long burst of bandpass-filtered noise with varying lower and upper cut-off frequencies. The resulting threshold data revealed that: (1) sensitivity decreases with decreasing bandwidth and increasing reflection delay and (2) high-frequency components contribute less to detection than low-frequency components. The auditory processes that may be involved in coloration detection (CD) are discussed in terms of a spectrum-based auditory model, which is conceptually similar to the pattern-transformation model of pitch (Wightman, 1973). Hence, the model derives an auto-correlation function of the input stimulus by applying a frequency analysis to an auditory representation of the power spectrum. It was found that, to successfully describe the quantitative behavior of the CDT data, three important mechanisms need to be included: (1) auditory bandpass filters with a narrower bandwidth than classic Gammatone filters, the increase in spectral resolution was here linked to cochlear suppression, (2) a spectral contrast enhancement process that reflects neural inhibition mechanisms, and (3) integration of information across auditory frequency bands. Copyright © 2011 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Eisler, K.; Goldammer, M.; Rothenfusser, M.; Arnold, W.; Homma, C.
2012-05-01
The spectral selective thermography with infrared filters can be used to determine or to distinguish materials such as contaminations on a metallic component. With additional visual information, the indications by the IR signal can be selectively accentuated or suppressed for easier evaluation of passive and active thermography measurements. For flash thermography the detected IR signal between 3.4 and 5.1 μm is analyzed with regard to the spectral material information. The presented hybrid camera uses beam overlapping to obtain combined images of both in the infrared and the visual range.
Fast sparse Raman spectral unmixing for chemical fingerprinting and quantification
NASA Astrophysics Data System (ADS)
Yaghoobi, Mehrdad; Wu, Di; Clewes, Rhea J.; Davies, Mike E.
2016-10-01
Raman spectroscopy is a well-established spectroscopic method for the detection of condensed phase chemicals. It is based on scattered light from exposure of a target material to a narrowband laser beam. The information generated enables presumptive identification from measuring correlation with library spectra. Whilst this approach is successful in identification of chemical information of samples with one component, it is more difficult to apply to spectral mixtures. The capability of handling spectral mixtures is crucial for defence and security applications as hazardous materials may be present as mixtures due to the presence of degradation, interferents or precursors. A novel method for spectral unmixing is proposed here. Most modern decomposition techniques are based on the sparse decomposition of mixture and the application of extra constraints to preserve the sum of concentrations. These methods have often been proposed for passive spectroscopy, where spectral baseline correction is not required. Most successful methods are computationally expensive, e.g. convex optimisation and Bayesian approaches. We present a novel low complexity sparsity based method to decompose the spectra using a reference library of spectra. It can be implemented on a hand-held spectrometer in near to real-time. The algorithm is based on iteratively subtracting the contribution of selected spectra and updating the contribution of each spectrum. The core algorithm is called fast non-negative orthogonal matching pursuit, which has been proposed by the authors in the context of nonnegative sparse representations. The iteration terminates when the maximum number of expected chemicals has been found or the residual spectrum has a negligible energy, i.e. in the order of the noise level. A backtracking step removes the least contributing spectrum from the list of detected chemicals and reports it as an alternative component. This feature is particularly useful in detection of chemicals with small contributions, which are normally not detected. The proposed algorithm is easily reconfigurable to include new library entries and optional preferential threat searches in the presence of predetermined threat indicators. Under Ministry of Defence funding, we have demonstrated the algorithm for fingerprinting and rough quantification of the concentration of chemical mixtures using a set of reference spectral mixtures. In our experiments, the algorithm successfully managed to detect the chemicals with concentrations below 10 percent. The running time of the algorithm is in the order of one second, using a single core of a desktop computer.
Deconstructing the Spectrum of the Soft X-ray Background
NASA Technical Reports Server (NTRS)
Kuntz, K. D.; Snowden, S. L.
2000-01-01
The soft X-ray background in the 0.1-1.0 keV band is known to be produced by at least three sources; the Local Hot Bubble (LHB), the extragalactic power law (EPL), and a seemingly galactic component that lies outside the bulk of the absorption that is due to the ISM of the galactic disk. This last component, which we call the Trans-Absorption Emission (TAE), has been modeled by a number of groups who have derived disparate measures of its temperature. The differences have arisen from differing assumptions about the structure of the emitting gas and unrecognized methodological difficulties. In particular, spectral fitting methods do not uniquely separate the TAE from the foreground emission that is due the LHB. This "degeneracy" can be resolved using the angular variation of the absorption of the TAE. We show that the TAE cannot be characterized by a single thermal component; no single-component model can be consistent with both the spectral energy distribution of the TAE emission and the angular variation due to absorption by the galactic disk. We use the angular anticorrelation of the ROSAT All-Sky Survey with the galactic absorption to separate local from distant emission components, and to fit the spectral energy distribution of the resulting distant emission. We find that the emission is best described by a two-thermal-component model with logT(sub S) = 6.06(sup +0.14, sub -0.12) and log T(sub H) = 6.42(sup +0.14, sub -0.12). This two-thermal-component TAE fits the ROSAT spectral energy distribution significantly better than single-component models, and is consistent with both angular variation and spectral constraints.
Wójcicki, Krzysztof; Khmelinskii, Igor; Sikorski, Marek; Sikorska, Ewa
2015-11-15
Infrared spectroscopic techniques and chemometric methods were used to study oxidation of olive, sunflower and rapeseed oils. Accelerated oxidative degradation of oils at 60°C was monitored using peroxide values and FT-MIR ATR and FT-NIR transmittance spectroscopy. Principal component analysis (PCA) facilitated visualization and interpretation of spectral changes occurring during oxidation. Multivariate curve resolution (MCR) method found three spectral components in the NIR and MIR spectral matrix, corresponding to the oxidation products, and saturated and unsaturated structures. Good quantitative relation was found between peroxide value and contribution of oxidation products evaluated using MCR--based on NIR (R(2) = 0.890), MIR (R(2) = 0.707) and combined NIR and MIR (R(2) = 0.747) data. Calibration models for prediction peroxide value established using partial least squares (PLS) regression were characterized for MIR (R(2) = 0.701, RPD = 1.7), NIR (R(2) = 0.970, RPD = 5.3), and combined NIR and MIR data (R(2) = 0.954, RPD = 3.1). Copyright © 2015 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Barbini, L.; Eltabach, M.; Hillis, A. J.; du Bois, J. L.
2018-03-01
In rotating machine diagnosis different spectral tools are used to analyse vibration signals. Despite the good diagnostic performance such tools are usually refined, computationally complex to implement and require oversight of an expert user. This paper introduces an intuitive and easy to implement method for vibration analysis: amplitude cyclic frequency decomposition. This method firstly separates vibration signals accordingly to their spectral amplitudes and secondly uses the squared envelope spectrum to reveal the presence of cyclostationarity in each amplitude level. The intuitive idea is that in a rotating machine different components contribute vibrations at different amplitudes, for instance defective bearings contribute a very weak signal in contrast to gears. This paper also introduces a new quantity, the decomposition squared envelope spectrum, which enables separation between the components of a rotating machine. The amplitude cyclic frequency decomposition and the decomposition squared envelope spectrum are tested on real word signals, both at stationary and varying speeds, using data from a wind turbine gearbox and an aircraft engine. In addition a benchmark comparison to the spectral correlation method is presented.
NASA Technical Reports Server (NTRS)
Nalepka, R. F. (Principal Investigator); Sadowski, F. G.; Malila, W. A.
1977-01-01
The author has identified the following significant results. Effects of vegetation density on overall canopy reflectance differed dramatically, depending on spectral band, base material, and vegetation type. For example, reflectance changes caused by variations in vegetation density were hardly apparant for a simulated burned surface in LANDSAT band 5, while large changes occurred in band 7. When increasing densities of tree overstory were placed over understories, intermediate to dense overstories effectively masked the understories and dominated the spectral signatures. Dramatic changes in reflectance occurred for canopies placed on a number of varying topographic positions. Such changes were seen to result in the spectral overlap of some nonforested with densely forested situations.
Advancement of Optical Component Control for an Imaging Fabry-Perot Interferometer
NASA Technical Reports Server (NTRS)
Larar, Allen M.; Cook, William B.; Flood, Michael A.; Campbell, Joel F.; Boyer, Charles M.
2009-01-01
Risk mitigation activities associated with a prototype imaging Fabry-Perot Interferometer (FPI) system are continuing at the NASA Langley Research Center. The system concept and technology center about enabling and improving future space-based atmospheric composition missions, with a current focus on observing tropospheric ozone around 9.6 micron, while having applicability toward measurement in different spectral regions and other applications. Recent activities have focused on improving an optical element control subsystem to enable precise and accurate positioning and control of etalon plates; this is needed to provide high system spectral fidelity critical for enabling the required ability to spectrally-resolve atmospheric line structure. The latest results pertaining to methodology enhancements, system implementation, and laboratory characterization testing will be reported
NASA Astrophysics Data System (ADS)
Chen, Gang; Metz, Margaret R.; Rizzo, David M.; Dillon, Whalen W.; Meentemeyer, Ross K.
2015-04-01
Forest ecosystems are subject to a variety of disturbances with increasing intensities and frequencies, which may permanently change the trajectories of forest recovery and disrupt the ecosystem services provided by trees. Fire and invasive species, especially exotic disease-causing pathogens and insects, are examples of disturbances that together could pose major threats to forest health. This study examines the impacts of fire and exotic disease (sudden oak death) on forests, with an emphasis on the assessment of post-fire burn severity in a forest where trees have experienced three stages of disease progression pre-fire: early-stage (trees retaining dried foliage and fine twigs), middle-stage (trees losing fine crown fuels), and late-stage (trees falling down). The research was conducted by applying Geographic Object-Based Image Analysis (GEOBIA) to MASTER airborne images that were acquired immediately following the fire for rapid assessment and contained both high-spatial (4 m) and high-spectral (50 bands) resolutions. Although GEOBIA has gradually become a standard tool for analyzing high-spatial resolution imagery, high-spectral resolution data (dozens to hundreds of bands) can dramatically reduce computation efficiency in the process of segmentation and object-based variable extraction, leading to complicated variable selection for succeeding modeling. Hence, we also assessed two widely used band reduction algorithms, PCA (principal component analysis) and MNF (minimum noise fraction), for the delineation of image objects and the subsequent performance of burn severity models using either PCA or MNF derived variables. To increase computation efficiency, only the top 5 PCA and MNF and top 10 PCA and MNF components were evaluated, which accounted for 10% and 20% of the total number of the original 50 spectral bands, respectively. Results show that if no band reduction was applied the models developed for the three stages of disease progression had relatively similar performance, where both spectral responses and texture contributed to burn assessments. However, the application of PCA and MNF introduced much greater variation among models across the three stages. For the early-stage disease progression, neither band reduction algorithms improved or retained the accuracy of burn severity modeling (except for the use of 10 MNF components). Compared to the no-band-reduction scenario, band reduction led to a greater level of overestimation of low-degree burns and underestimation of medium-degree burns, suggesting that the spectral variation removed by PCA and MNF was vital for distinguishing between the spectral reflectance from disease-induced dried crowns (still retaining high structural complexity) and fire ash. For the middle-stage, both algorithms improved the model R2 values by 2-37%, while the late-stage models had comparable or better performance to those using the original 50 spectral bands. This could be explained by the loss of tree crowns enabling better signal penetration, thus leading to reduced spectral variation from canopies. Hence, spectral bands containing a high degree of random noise were correctly removed by the band reduction algorithms. Compared to the middle-stage, the late-stage forest stands were covered by large piles of fallen trees and branches, resulting in higher variability of MASTER imagery. The ability of band reduction to improve the model performance for these late-stage forest stands was reduced, because the valuable spectral variation representing the actual late-stage forest status was partially removed by both algorithms as noise. Our results indicate that PCA and MNF are promising for balancing computation efficiency and the performance of burn severity models in forest stands subject to the middle and late stages of sudden oak death disease progression. Compared to PCA, MNF dramatically reduced image spectral variation, generating larger image objects with less complexity of object shapes. Whereas, PCA-based models delivered superior performance in most evaluated cases suggesting that some key spectral variability contributing to the accuracy of burn severity models in diseased forests may have been removed together with true spectral noise through MNF transformations.
Grimbergen, M C M; van Swol, C F P; Kendall, C; Verdaasdonk, R M; Stone, N; Bosch, J L H R
2010-01-01
The overall quality of Raman spectra in the near-infrared region, where biological samples are often studied, has benefited from various improvements to optical instrumentation over the past decade. However, obtaining ample spectral quality for analysis is still challenging due to device requirements and short integration times required for (in vivo) clinical applications of Raman spectroscopy. Multivariate analytical methods, such as principal component analysis (PCA) and linear discriminant analysis (LDA), are routinely applied to Raman spectral datasets to develop classification models. Data compression is necessary prior to discriminant analysis to prevent or decrease the degree of over-fitting. The logical threshold for the selection of principal components (PCs) to be used in discriminant analysis is likely to be at a point before the PCs begin to introduce equivalent signal and noise and, hence, include no additional value. Assessment of the signal-to-noise ratio (SNR) at a certain peak or over a specific spectral region will depend on the sample measured. Therefore, the mean SNR over the whole spectral region (SNR(msr)) is determined in the original spectrum as well as for spectra reconstructed from an increasing number of principal components. This paper introduces a method of assessing the influence of signal and noise from individual PC loads and indicates a method of selection of PCs for LDA. To evaluate this method, two data sets with different SNRs were used. The sets were obtained with the same Raman system and the same measurement parameters on bladder tissue collected during white light cystoscopy (set A) and fluorescence-guided cystoscopy (set B). This method shows that the mean SNR over the spectral range in the original Raman spectra of these two data sets is related to the signal and noise contribution of principal component loads. The difference in mean SNR over the spectral range can also be appreciated since fewer principal components can reliably be used in the low SNR data set (set B) compared to the high SNR data set (set A). Despite the fact that no definitive threshold could be found, this method may help to determine the cutoff for the number of principal components used in discriminant analysis. Future analysis of a selection of spectral databases using this technique will allow optimum thresholds to be selected for different applications and spectral data quality levels.
Väliviita, Jussi; Muhonen, Vesa
2003-09-26
In general correlated models, in addition to the usual adiabatic component with a spectral index n(ad1) there is another adiabatic component with a spectral index n(ad2) generated by entropy perturbation during inflation. We extend the analysis of a correlated mixture of adiabatic and isocurvature cosmic microwave background fluctuations of the Wilkinson Microwave Anisotropy Probe (WMAP) group, who set the two adiabatic spectral indices equal. Allowing n(ad1) and n(ad2) to vary independently we find that the WMAP data favor models where the two adiabatic components have opposite spectral tilts. Using the WMAP data only, the 2sigma upper bound for the isocurvature fraction f(iso) of the initial power spectrum at k(0)=0.05 Mpc(-1) increases somewhat, e.g., from 0.76 of n(ad2)=n(ad1) models to 0.84 with a prior n(iso)<1.84 for the isocurvature spectral index.
Multispectral image fusion for target detection
NASA Astrophysics Data System (ADS)
Leviner, Marom; Maltz, Masha
2009-09-01
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 an experiment using MSSF against two established methods: Averaging and Principle Components Analysis (PCA), and against its two source bands, visible and infrared. The task that we studied was: target detection in the cluttered environment. MSSF proved superior to the other fusion methods. 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.
Energy-Discriminative Performance of a Spectral Micro-CT System
He, Peng; Yu, Hengyong; Bennett, James; Ronaldson, Paul; Zainon, Rafidah; Butler, Anthony; Butler, Phil; Wei, Biao; Wang, Ge
2013-01-01
Experiments were performed to evaluate the energy-discriminative performance of a spectral (multi-energy) micro-CT system. The system, designed by MARS (Medipix All Resolution System) Bio-Imaging Ltd. (Christchurch, New Zealand), employs a photon-counting energy-discriminative detector technology developed by CERN (European Organization for Nuclear Research). We used the K-edge attenuation characteristic of some known materials to calibrate the detector’s photon energy discrimination. For tomographic analysis, we used the compressed sensing (CS) based ordered-subset simultaneous algebraic reconstruction techniques (OS-SART) to reconstruct sample images, which is effective to reduce noise and suppress artifacts. Unlike conventional CT, the principal component analysis (PCA) method can be applied to extract and quantify additional attenuation information from a spectral CT dataset. Our results show that the spectral CT has a good energy-discriminative performance and provides more attenuation information than the conventional CT. PMID:24004864
NASA Astrophysics Data System (ADS)
Velicu, S.; Buurma, C.; Bergeson, J. D.; Kim, Tae Sung; Kubby, J.; Gupta, N.
2014-05-01
Imaging spectrometry can be utilized in the midwave infrared (MWIR) and long wave infrared (LWIR) bands to detect, identify and map complex chemical agents based on their rotational and vibrational emission spectra. Hyperspectral datasets are typically obtained using grating or Fourier transform spectrometers to separate the incoming light into spectral bands. At present, these spectrometers are large, cumbersome, slow and expensive, and their resolution is limited by bulky mechanical components such as mirrors and gratings. As such, low-cost, miniaturized imaging spectrometers are of great interest. Microfabrication of micro-electro-mechanicalsystems (MEMS)-based components opens the door for producing low-cost, reliable optical systems. We present here our work on developing a miniaturized IR imaging spectrometer by coupling a mercury cadmium telluride (HgCdTe)-based infrared focal plane array (FPA) with a MEMS-based Fabry-Perot filter (FPF). The two membranes are fabricated from silicon-oninsulator (SOI) wafers using bulk micromachining technology. The fixed membrane is a standard silicon membrane, fabricated using back etching processes. The movable membrane is implemented as an X-beam structure to improve mechanical stability. The geometries of the distributed Bragg reflector (DBR)-based tunable FPFs are modeled to achieve the desired spectral resolution and wavelength range. Additionally, acceptable fabrication tolerances are determined by modeling the spectral performance of the FPFs as a function of DBR surface roughness and membrane curvature. These fabrication non-idealities are then mitigated by developing an optimized DBR process flow yielding high-performance FPF cavities. Zinc Sulfide (ZnS) and Germanium (Ge) are chosen as the low and the high index materials, respectively, and are deposited using an electron beam process. Simulations are presented showing the impact of these changes and non-idealities in both a device and systems level.
HST/STIS ULTRAVIOLET SPECTROSCOPY OF THE COMPONENTS OF THE MASSIVE TRIPLE STAR δ ORI A
DOE Office of Scientific and Technical Information (OSTI.GOV)
Richardson, Noel D.; Moffat, Anthony F. J.; Gull, Theodore R.
2015-07-20
The multiple star system of δ Orionis is one of the closest examples of a system containing a luminous O-type, bright giant star (component Aa1). It is often used as a spectral-type standard and has the highest observed X-ray flux of any hot-star binary. The main component Aa1 is orbited by two lower mass stars, faint Aa2 in a 5.7 day eclipsing binary, and Ab, an astrometric companion with an estimated period of 346 years. Generally the flux from all three stars is recorded in ground-based spectroscopy, and the spectral decomposition of the components has proved difficult. Here we presentmore » Hubble Space Telescope/Space Telescope Imaging Spectrograph ultraviolet spectroscopy of δ Ori A that provides us with spatially separated spectra of Aa and Ab for the first time. We measured radial velocities for Aa1 and Ab in two observations made near the velocity extrema of Aa1. We show tentative evidence for the detection of the Aa2 component in cross-correlation functions of the observed and model spectra. We discuss the appearance of the UV spectra of Aa1 and Ab with reference to model spectra. Both stars have similar effective temperatures, but Ab is fainter and is a rapid rotator. The results will help in the interpretation of ground-based spectroscopy and in understanding the physical and evolutionary parameters of these massive stars.« less
NASA Astrophysics Data System (ADS)
Wang, Yin-Ge; Wang, Yue-Hua; Tao, Tao; Qian, Hui-Fen; Huang, Wei
2015-09-01
A pair of isomeric heterocyclic compounds, namely 3-amino-5-nitro-[2,1]-benzisothiazole and 2-amino-6-nitrobenzothiazole, are used as the diazonium components to couple with two N-substituted 4-aminobenzene derivatives. As a result, two pairs of isomeric aromatic heterocyclic azo dyes have been produced and they are structurally and spectrally characterized and compared including single-crystal structures, electronic spectra, solvatochromism and reversible acid-base discoloration, thermal stability and theoretically calculations. It is concluded that both benzisothiazole and benzothiazole based dyes show planar molecular structures and offset π-π stacking interactions, solvatochromism and reversible acid-base discoloration. Furthermore, benzisothiazole based aromatic heterocyclic dyes exhibit higher thermal stability, larger solvatochromic effects and maximum absorption wavelengths than corresponding benzothiazole based ones, which can be explained successfully by the differences of their calculated isomerization energy, dipole moment and molecular band gaps.
Spectral broadening of VLF transmitter signals observed on DE 1 - A quasi-electrostatic phenomenon?
NASA Technical Reports Server (NTRS)
Inan, U. S.; Bell, T. F.
1985-01-01
Spectrally broadened VLF transmitter signals are observed on the DE 1 satellite using alternatively both electric and magnetic field sensors. It is found that at times when the electric field component undergoes significant bandwidth expansion (up to about 110 Hz) the magnetic field component has a bandwidth of less than 10 Hz. The results support the theory that the off-carrier components are quasi-electrostatic in nature. Measurement of the absolute E and B field magnitudes of the broadened signals are used to determine the wave Poynting vector. It is found that the observed power levels can be understood without invoking any strong amplification process that operates in conjunction with the spectral broadening. The implications of this finding in distinguishing among the various possible mechanisms for spectral broadening are discussed.
Observation of Multimode Quantum Correlations in Fiber Optical Solitons
NASA Astrophysics Data System (ADS)
Spälter, S.; Korolkova, N.; König, F.; Sizmann, A.; Leuchs, G.
1998-07-01
Quantum correlations of photon numbers in different spectral components of ultrashort optical solitons have been observed experimentally. These correlations are crucial for the understanding and characterization of the internal quantum structure of soliton pulses and contribute significantly to soliton squeezing by spectral filtering. The accessible information on the nonclassical state of the correlated spectral components is discussed with the example of two modes. The method may be generalized to obtain a complete quantum description of a multimode field.
1990-08-01
the spectral domain is extended to include the effects of two-dimensional, two-component current flow in planar transmission line discontinuities 6n...PROFESSOR: Tatsuo Itoh A deterministic formulation of the method of moments carried out in the spectral domain is extended to include the effects of...two-dimensional, two- component current flow in planar transmission line discontinuities on open substrates. The method includes the effects of space
NASA Astrophysics Data System (ADS)
Bittel, Amy M.; Saldivar, Isaac S.; Nan, Xiaolin; Gibbs, Summer L.
2016-02-01
Single-molecule localization microscopy (SMLM) utilizes photoswitchable fluorophores to detect biological entities with 10-20 nm resolution. Multispectral superresolution microscopy (MSSRM) extends SMLM functionality by improving its spectral resolution up to 5 fold facilitating imaging of multicomponent cellular structures or signaling pathways. Current commercial fluorophores are not ideal for MSSRM as they are not designed to photoswitch and do not adequately cover the visible and far-red spectral regions required for MSSRM imaging. To obtain optimal MSSRM spatial and spectral resolution, fluorophores with narrow emission spectra and controllable photoswitching properties are necessary. Herein, a library of BODIPY-based fluorophores was synthesized and characterized to create optimal photoswitchable fluorophores for MSSRM. BODIPY was chosen as the core structure as it is photostable, has high quantum yield, and controllable photoswitching. The BODIPY core was modified through the addition of various aromatic moieties, resulting in a spectrally diverse library. Photoswitching properties were characterized using a novel polyvinyl alcohol (PVA) based film methodology to isolate single molecules. The PVA film methodology enabled photoswitching assessment without the need for protein conjugation, greatly improving screening efficiency of the BODIPY library. Additionally, image buffer conditions were optimized for the BODIPY-based fluorophores through systematic testing of oxygen scavenger systems, redox components, and additives. Through screening the photoswitching properties of BODIPY-based compounds in PVA films with optimized imaging buffer we identified novel fluorophores well suited for SMLM and MSSRM.
NASA Astrophysics Data System (ADS)
Yang, Jian; He, Yuhong
2017-02-01
Quantifying impervious surfaces in urban and suburban areas is a key step toward a sustainable urban planning and management strategy. With the availability of fine-scale remote sensing imagery, automated mapping of impervious surfaces has attracted growing attention. However, the vast majority of existing studies have selected pixel-based and object-based methods for impervious surface mapping, with few adopting sub-pixel analysis of high spatial resolution imagery. This research makes use of a vegetation-bright impervious-dark impervious linear spectral mixture model to characterize urban and suburban surface components. A WorldView-3 image acquired on May 9th, 2015 is analyzed for its potential in automated unmixing of meaningful surface materials for two urban subsets and one suburban subset in Toronto, ON, Canada. Given the wide distribution of shadows in urban areas, the linear spectral unmixing is implemented in non-shadowed and shadowed areas separately for the two urban subsets. The results indicate that the accuracy of impervious surface mapping in suburban areas reaches up to 86.99%, much higher than the accuracies in urban areas (80.03% and 79.67%). Despite its merits in mapping accuracy and automation, the application of our proposed vegetation-bright impervious-dark impervious model to map impervious surfaces is limited due to the absence of soil component. To further extend the operational transferability of our proposed method, especially for the areas where plenty of bare soils exist during urbanization or reclamation, it is still of great necessity to mask out bare soils by automated classification prior to the implementation of linear spectral unmixing.
True resolution enhancement for optical spectroscopy
NASA Astrophysics Data System (ADS)
Cooper, Justin T.; Oleske, Jeffrey B.
2018-02-01
Resolving spectrally adjacent peaks is important for techniques, such as tracking small shifts in Raman or fluorescence spectra, quantifying pharmaceutical polymorph ratios, or molecular orientation studies. Thus, suitable spectral resolution is a vital consideration when designing most spectroscopic systems. Most parameters that influence spectral resolution are fixed for a given system (spectrometer length, grating groove density, excitation source, CCD pixel size, etc.). Inflexible systems are non-problematic if the spectrometer is dedicated for a single purpose; however, these specifications cannot be optimized for different applications with wider range resolution requirements. Data processing techniques, including peak fitting, partial least squares, or principal component analysis, are typically used to achieve sub-optical resolution information. These techniques can be plagued by spectral artifacts introduced by post-processing as well as the subjective implementation of statistical parameters. TruRes™, from Andor Technology, uses an innovative optical means to greatly improve and expand the range of spectral resolutions accessible on a single setup. True spectral resolution enhancement of >30% is achieved without mathematical spectral alteration, dataprocessing, or spectrometer component changes. Discreet characteristic spectral lines from Laser-Induced Breakdown Spectroscopy (LIBS) and atomic calibration sources are now fully resolved from spectrally-adjacent peaks under otherwise identical configuration. TruRes™ has added advantage of increasing the spectral resolution without sacrificing bandpass. Using TruRes™ the Kymera 328i resolution can approach that of a 500 mm focal spectrometer. Furthermore, the bandpass of a 500 mm spectrograph with would be 50% narrower than the Kymera 328i with all other spectrometer components constant. However, the Kymera 328i with TruRes™ is able to preserve a 50% wider bandpass.
Nébouy, David; Hébert, Mathieu; Fournel, Thierry; Larina, Nina; Lesur, Jean-Luc
2015-09-01
Recent color printing technologies based on the principle of revealing colors on pre-functionalized achromatic supports by laser irradiation offer advanced functionalities, especially for security applications. However, for such technologies, the color prediction is challenging, compared to classic ink-transfer printing systems. The spectral properties of the coloring materials modified by the lasers are not precisely known and may strongly vary, depending on the laser settings, in a nonlinear manner. We show in this study, through the example of the color laser marking (CLM) technology, based on laser bleaching of a mixture of pigments, that the combination of an adapted optical reflectance model and learning methods to get the model's parameters enables prediction of the spectral reflectance of any printable color with rather good accuracy. Even though the pigment mixture is formulated from three colored pigments, an analysis of the dimensionality of the spectral space generated by CLM printing, thanks to a principal component analysis decomposition, shows that at least four spectral primaries are needed for accurate spectral reflectance predictions. A polynomial interpolation is then used to relate RGB laser intensities with virtual coordinates of new basis vectors. By studying the influence of the number of calibration patches on the prediction accuracy, we can conclude that a reasonable number of 130 patches are enough to achieve good accuracy in this application.
NASA Astrophysics Data System (ADS)
Rao, R. R.
2015-12-01
Aerosol radiative forcing estimates with high certainty are required in climate change studies. The approach in estimating the aerosol radiative forcing by using the chemical composition of aerosols is not effective as the chemical composition data with radiative properties are not widely available. In this study we look into the approach where ground based spectral radiation flux measurements along with an RT model is used to estimate radiative forcing. Measurements of spectral flux were made using an ASD spectroradiometer with 350 - 1050 nm wavelength range and 3nm resolution for around 54 clear-sky days during which AOD range was around 0.1 to 0.7. Simultaneous measurements of black carbon were also made using Aethalometer (Magee Scientific) which ranged from around 1.5 ug/m3 to 8 ug/m3. All the measurements were made in the campus of Indian Institute of Science which is in the heart of Bangalore city. The primary study involved in understanding the sensitivity of spectral flux to change in the mass concentration of individual aerosol species (Optical properties of Aerosols and Clouds -OPAC classified aerosol species) using the SBDART RT model. This made us clearly distinguish the region of influence of different aerosol species on the spectral flux. Following this, a new technique has been introduced to estimate an optically equivalent mixture of aerosol species for the given location. The new method involves an iterative process where the mixture of aerosol species are changed in OPAC model and RT model is run as long as the mixture which mimics the measured spectral flux within 2-3% deviation from measured spectral flux is obtained. Using the optically equivalent aerosol mixture and RT model aerosol radiative forcing is estimated. The new method is limited to clear sky scenes and its accuracy to derive an optically equivalent aerosol mixture reduces when diffuse component of flux increases. Our analysis also showed that direct component of spectral flux is more sensitive to different aerosol species than total spectral flux which was also supported by our observed data.
2001-10-25
considered static or invariant because the spectral behavior of EMG data is dependent on the specific muscle , contraction level, and limb function. However...produced at the onset of the muscle contraction . Because the units with lower conduction velocity (lower frequency components) are recruited first, the
Andreoli, Daria; Volpe, Giorgio; Popoff, Sébastien; Katz, Ori; Grésillon, Samuel; Gigan, Sylvain
2015-01-01
We present a method to measure the spectrally-resolved transmission matrix of a multiply scattering medium, thus allowing for the deterministic spatiospectral control of a broadband light source by means of wavefront shaping. As a demonstration, we show how the medium can be used to selectively focus one or many spectral components of a femtosecond pulse, and how it can be turned into a controllable dispersive optical element to spatially separate different spectral components to arbitrary positions. PMID:25965944
NASA Technical Reports Server (NTRS)
Gardner, D. G.; Tejwani, G. D.; Bircher, F. E.; Loboda, J. A.; Van Dyke, D. B.; Chenevert, D. J.
1991-01-01
Details are presented of the approach used in a comprehensive program to utilize exhaust plume diagnostics for rocket engine health-and-condition monitoring and assessing SSME component wear and degradation. This approach incorporates both spectral and video monitoring of the exhaust plume. Video monitoring provides qualitative data for certain types of component wear while spectral monitoring allows both quantitative and qualitative information. Consideration is given to spectral identification of SSME materials and baseline plume emissions.
NASA Astrophysics Data System (ADS)
Penttilä, Antti; Martikainen, Julia; Gritsevich, Maria; Muinonen, Karri
2018-02-01
Meteorite samples are measured with the University of Helsinki integrating-sphere UV-vis-NIR spectrometer. The resulting spectra of 30 meteorites are compared with selected spectra from the NASA Planetary Data System meteorite spectra database. The spectral measurements are transformed with the principal component analysis, and it is shown that different meteorite types can be distinguished from the transformed data. The motivation is to improve the link between asteroid spectral observations and meteorite spectral measurements.
Prediction of Soil pH Hyperspectral Spectrum in Guanzhong Area of Shaanxi Province Based on PLS
NASA Astrophysics Data System (ADS)
Liu, Jinbao; Zhang, Yang; Wang, Huanyuan; Cheng, Jie; Tong, Wei; Wei, Jing
2017-12-01
The soil pH of Fufeng County, Yangling County and Wugong County in Shaanxi Province was studied. The spectral reflectance was measured by ASD Field Spec HR portable terrain spectrum, and its spectral characteristics were analyzed. The first deviation of the original spectral reflectance of the soil, the second deviation, the logarithm of the reciprocal logarithm, the first order differential of the reciprocal logarithm and the second order differential of the reciprocal logarithm were used to establish the soil pH Spectral prediction model. The results showed that the correlation between the reflectance spectra after SNV pre-treatment and the soil pH was significantly improved. The optimal prediction model of soil pH established by partial least squares method was a prediction model based on the first order differential of the reciprocal logarithm of spectral reflectance. The principal component factor was 10, the decision coefficient Rc2 = 0.9959, the model root means square error RMSEC = 0.0076, the correction deviation SEC = 0.0077; the verification decision coefficient Rv2 = 0.9893, the predicted root mean square error RMSEP = 0.0157, The deviation of SEP = 0.0160, the model was stable, the fitting ability and the prediction ability were high, and the soil pH can be measured quickly.
NASA Astrophysics Data System (ADS)
Saager, Rolf B.; Baldado, Melissa L.; Rowland, Rebecca A.; Kelly, Kristen M.; Durkin, Anthony J.
2018-04-01
With recent proliferation in compact and/or low-cost clinical multispectral imaging approaches and commercially available components, questions remain whether they adequately capture the requisite spectral content of their applications. We present a method to emulate the spectral range and resolution of a variety of multispectral imagers, based on in-vivo data acquired from spatial frequency domain spectroscopy (SFDS). This approach simulates spectral responses over 400 to 1100 nm. Comparing emulated data with full SFDS spectra of in-vivo tissue affords the opportunity to evaluate whether the sparse spectral content of these imagers can (1) account for all sources of optical contrast present (completeness) and (2) robustly separate and quantify sources of optical contrast (crosstalk). We validate the approach over a range of tissue-simulating phantoms, comparing the SFDS-based emulated spectra against measurements from an independently characterized multispectral imager. Emulated results match the imager across all phantoms (<3 % absorption, <1 % reduced scattering). In-vivo test cases (burn wounds and photoaging) illustrate how SFDS can be used to evaluate different multispectral imagers. This approach provides an in-vivo measurement method to evaluate the performance of multispectral imagers specific to their targeted clinical applications and can assist in the design and optimization of new spectral imaging devices.
Land surface temperature measurements from EOS MODIS data
NASA Technical Reports Server (NTRS)
Wan, Zhengming
1995-01-01
A significant progress has been made in TIR instrumentation which is required to establish the spectral BRDF/emissivity knowledge base of land-surface materials and to validate the land-surface temperature (LST) algorithms. The SIBRE (spectral Infrared Bidirectional Reflectance and Emissivity) system and a TIR system for measuring spectral directional-hemispherical emissivity have been completed and tested successfully. Optical properties and performance features of key components (including spectrometer, and TIR source) of these systems have been characterized by integrated use of local standards (blackbody and reference plates). The stabilization of the spectrometer performance was improved by a custom designed and built liquid cooling system. Methods and procedures for measuring spectral TIR BRDF and directional-hemispheric emissivity with these two systems have been verified in sample measurements. These TIR instruments have been used in the laboratory and the field, giving very promising results. The measured spectral emissivities of water surface are very close to the calculated values based on well established water refractive index values in published papers. Preliminary results show that the TIR instruments can be used for validation of the MODIS LST algorithm in homogeneous test sites. The beta-3 version of the MODIS LST software is being prepared for its delivery scheduled in the early second half of this year.
NASA Astrophysics Data System (ADS)
Hassan Mohammed, Mohammed Ahmed
For an efficient maintenance of a diverse fleet of air- and rotorcraft, effective condition based maintenance (CBM) must be established based on rotating components monitored vibration signals. In this dissertation, we present theory and applications of polyspectral signal processing techniques for condition monitoring of critical components in the AH-64D helicopter tail rotor drive train system. Currently available vibration-monitoring tools are mostly built around auto- and cross-power spectral analysis which have limited performance in detecting frequency correlations higher than second order. Studying higher order correlations and their Fourier transforms, higher order spectra, provides more information about the vibration signals which helps in building more accurate diagnostic models of the mechanical system. Based on higher order spectral analysis, different signal processing techniques are developed to assess health conditions of different critical rotating-components in the AH-64D helicopter drive-train. Based on cross-bispectrum, quadratic nonlinear transfer function is presented to model second order nonlinearity in a drive-shaft running between the two hanger bearings. Then, quadratic-nonlinearity coupling coefficient between frequency harmonics of the rotating shaft is used as condition metric to study different seeded shaft faults compared to baseline case, namely: shaft misalignment, shaft imbalance, and combination of shaft misalignment and imbalance. The proposed quadratic-nonlinearity metric shows better capabilities in distinguishing the four studied shaft settings than the conventional linear coupling based on cross-power spectrum. We also develop a new concept of Quadratic-Nonlinearity Power-Index spectrum, QNLPI(f), that can be used in signal detection and classification, based on bicoherence spectrum. The proposed QNLPI(f) is derived as a projection of the three-dimensional bicoherence spectrum into two-dimensional spectrum that quantitatively describes how much of the mean square power at certain frequency f is generated due to nonlinear quadratic interaction between different frequency components. The proposed index, QNLPI(f), can be used to simplify the study of bispectrum and bicoherence signal spectra. It also inherits useful characteristics from the bicoherence such as high immunity to additive Gaussian noise, high capability of nonlinear-systems identifications, and amplification invariance. The quadratic-nonlinear power spectral density PQNL(f) and percentage of quadratic nonlinear power PQNLP are also introduced based on the QNLPI(f). Concept of the proposed indices and their computational considerations are discussed first using computer generated data, and then applied to real-world vibration data to assess health conditions of different rotating components in the drive train including drive-shaft, gearbox, and hanger bearing faults. The QNLPI(f) spectrum enables us to gain more details about nonlinear harmonic generation patterns that can be used to distinguish between different cases of mechanical faults, which in turn helps to gaining more diagnostic/prognostic capabilities.
Hyperspectral image compressing using wavelet-based method
NASA Astrophysics Data System (ADS)
Yu, Hui; Zhang, Zhi-jie; Lei, Bo; Wang, Chen-sheng
2017-10-01
Hyperspectral imaging sensors can acquire images in hundreds of continuous narrow spectral bands. Therefore each object presented in the image can be identified from their spectral response. However, such kind of imaging brings a huge amount of data, which requires transmission, processing, and storage resources for both airborne and space borne imaging. Due to the high volume of hyperspectral image data, the exploration of compression strategies has received a lot of attention in recent years. Compression of hyperspectral data cubes is an effective solution for these problems. Lossless compression of the hyperspectral data usually results in low compression ratio, which may not meet the available resources; on the other hand, lossy compression may give the desired ratio, but with a significant degradation effect on object identification performance of the hyperspectral data. Moreover, most hyperspectral data compression techniques exploits the similarities in spectral dimensions; which requires bands reordering or regrouping, to make use of the spectral redundancy. In this paper, we explored the spectral cross correlation between different bands, and proposed an adaptive band selection method to obtain the spectral bands which contain most of the information of the acquired hyperspectral data cube. The proposed method mainly consist three steps: First, the algorithm decomposes the original hyperspectral imagery into a series of subspaces based on the hyper correlation matrix of the hyperspectral images between different bands. And then the Wavelet-based algorithm is applied to the each subspaces. At last the PCA method is applied to the wavelet coefficients to produce the chosen number of components. The performance of the proposed method was tested by using ISODATA classification method.
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.
Kmeans-ICA based automatic method for ocular artifacts removal in a motorimagery classification.
Bou Assi, Elie; Rihana, Sandy; Sawan, Mohamad
2014-01-01
Electroencephalogram (EEG) recordings aroused as inputs of a motor imagery based BCI system. Eye blinks contaminate the spectral frequency of the EEG signals. Independent Component Analysis (ICA) has been already proved for removing these artifacts whose frequency band overlap with the EEG of interest. However, already ICA developed methods, use a reference lead such as the ElectroOculoGram (EOG) to identify the ocular artifact components. In this study, artifactual components were identified using an adaptive thresholding by means of Kmeans clustering. The denoised EEG signals have been fed into a feature extraction algorithm extracting the band power, the coherence and the phase locking value and inserted into a linear discriminant analysis classifier for a motor imagery classification.
Compressive Spectral Method for the Simulation of the Nonlinear Gravity Waves
Bayındır, Cihan
2016-01-01
In this paper an approach for decreasing the computational effort required for the spectral simulations of the fully nonlinear ocean waves is introduced. The proposed approach utilizes the compressive sampling algorithm and depends on the idea of using a smaller number of spectral components compared to the classical spectral method. After performing the time integration with a smaller number of spectral components and using the compressive sampling technique, it is shown that the ocean wave field can be reconstructed with a significantly better efficiency compared to the classical spectral method. For the sparse ocean wave model in the frequency domain the fully nonlinear ocean waves with Jonswap spectrum is considered. By implementation of a high-order spectral method it is shown that the proposed methodology can simulate the linear and the fully nonlinear ocean waves with negligible difference in the accuracy and with a great efficiency by reducing the computation time significantly especially for large time evolutions. PMID:26911357
Method to analyze remotely sensed spectral data
Stork, Christopher L [Albuquerque, NM; Van Benthem, Mark H [Middletown, DE
2009-02-17
A fast and rigorous multivariate curve resolution (MCR) algorithm is applied to remotely sensed spectral data. The algorithm is applicable in the solar-reflective spectral region, comprising the visible to the shortwave infrared (ranging from approximately 0.4 to 2.5 .mu.m), midwave infrared, and thermal emission spectral region, comprising the thermal infrared (ranging from approximately 8 to 15 .mu.m). For example, employing minimal a priori knowledge, notably non-negativity constraints on the extracted endmember profiles and a constant abundance constraint for the atmospheric upwelling component, MCR can be used to successfully compensate thermal infrared hyperspectral images for atmospheric upwelling and, thereby, transmittance effects. Further, MCR can accurately estimate the relative spectral absorption coefficients and thermal contrast distribution of a gas plume component near the minimum detectable quantity.
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.
NASA Astrophysics Data System (ADS)
Schiering, David W.; Walton, Robert B.; Brown, Christopher W.; Norman, Mark L.; Brewer, Joseph; Scott, James
2004-12-01
IR spectroscopy is a broadly applicable technique for the identification of covalent materials. Recent advances in instrumentation have made Fourier Transform infrared (FT-IR) spectroscopy available for field characterization of suspect materials. Presently, this instrumentation is broadly deployed and used for the identification of potential chemical hazards. This discussion concerns work towards expanding the analytical utility of field-based FT-IR spectrometry in the characterization of biological threats. Two classes of materials were studied: biologically produced chemical toxins which were non-peptide in nature and peptide toxin. The IR spectroscopic identification of aflatoxin-B1, trichothecene T2 mycotoxin, and strychnine was evaluated using the approach of spectral searching against large libraries of materials. For pure components, the IR method discriminated the above toxins at better than the 99% confidence level. The ability to identify non-peptide toxins in mixtures was also evaluated using a "spectral stripping" search approach. For the mixtures evaluated, this method was able to identify the mixture components from ca. 32K spectral library entries. Castor bean extract containing ricin was used as a representative peptide toxin. Due to similarity in protein spectra, a SIMCA pattern recognition methodology was evaluated for classifying peptide toxins. In addition to castor bean extract the method was validated using bovine serum albumin and myoglobin as simulants. The SIMCA approach was successful in correctly classifying these samples at the 95% confidence level.
Influence of grain boundaries on the distribution of components in binary alloys
NASA Astrophysics Data System (ADS)
L'vov, P. E.; Svetukhin, V. V.
2017-12-01
Based on the free-energy density functional method (the Cahn-Hilliard equation), a phenomenological model that describes the influence of grain boundaries on the distribution of components in binary alloys has been developed. The model is built on the assumption of the difference between the interaction parameters of solid solution components in the bulk and at the grain boundary. The difference scheme based on the spectral method is proposed to solve the Cahn-Hilliard equation with interaction parameters depending on coordinates. Depending on the ratio between the interaction parameters in the bulk and at the grain boundary, temperature, and alloy composition, the model can give rise to different types of distribution of a dissolved component, namely, either depletion or enrichment of the grain-boundary area, preferential grainboundary precipitation, competitive precipitation in the bulk and at the grain boundary, etc.
On the IceCube spectral anomaly
NASA Astrophysics Data System (ADS)
Palladino, Andrea; Spurio, Maurizio; Vissani, Francesco
2016-12-01
Recently it was noted that different IceCube datasets are not consistent with the same power law spectrum of the cosmic neutrinos: this is the IceCube spectral anomaly, that suggests that they observe a multicomponent spectrum. In this work, the main possibilities to enhance the description in terms of a single extragalactic neutrino component are examined. The hypothesis of a sizable contribution of Galactic high-energy neutrino events distributed as E-2.7 [Astrophys. J. 826 (2016) 185] is critically analyzed and its natural generalization is considered. The stability of the expectations is studied by introducing free parameters, motivated by theoretical considerations and observational facts. The upgraded model here examined has 1) a Galactic component with different normalization and shape E-2.4 2) an extragalactic neutrino spectrum based on new data; 3) a non-zero prompt component of atmospheric neutrinos. The two key predictions of the model concern the `high-energy starting events' collected from the Southern sky. The Galactic component produces a softer spectrum and a testable angular anisotropy. A second, radically different class of models, where the second component is instead isotropic, plausibly extragalactic and with a relatively soft spectrum, is disfavored instead by existing observations of muon neutrinos from the Northern sky and below few 100 TeV.
Evaluation of skin melanoma in spectral range 450-950 nm using principal component analysis
NASA Astrophysics Data System (ADS)
Jakovels, D.; Lihacova, I.; Kuzmina, I.; Spigulis, J.
2013-06-01
Diagnostic potential of principal component analysis (PCA) of multi-spectral imaging data in the wavelength range 450- 950 nm for distant skin melanoma recognition is discussed. Processing of the measured clinical data by means of PCA resulted in clear separation between malignant melanomas and pigmented nevi.
Skupsky, Stanley; Kessler, Terrance J.; Letzring, Samuel A.
1993-01-01
A temporally shaped or modified optical output pulse is generated from a bandwidth-encoded optical input pulse in a system in which the input pulse is in the form of a beam which is spectrally spread into components contained within the bandwidth, followed by deflection of the spectrally spread beam (SBD) thereby spatially mapping the components in correspondence with the temporal input pulse profile in the focal plane of a lens, and by spatially selective attenuation of selected components in that focal plane. The shaped or modified optical output pulse is then reconstructed from the attenuated spectral components. The pulse-shaping system is particularly useful for generating optical pulses of selected temporal shape over a wide range of pulse duration, such pulses finding application in the fields of optical communication, optical recording and data storage, atomic and molecular spectroscopy and laser fusion. An optical streak camera is also provided which uses SBD to display the beam intensity in the focal plane as a function of time during the input pulse.
Skupsky, S.; Kessler, T.J.; Letzring, S.A.
1993-11-16
A temporally shaped or modified optical output pulse is generated from a bandwidth-encoded optical input pulse in a system in which the input pulse is in the form of a beam which is spectrally spread into components contained within the bandwidth, followed by deflection of the spectrally spread beam (SBD) thereby spatially mapping the components in correspondence with the temporal input pulse profile in the focal plane of a lens, and by spatially selective attenuation of selected components in that focal plane. The shaped or modified optical output pulse is then reconstructed from the attenuated spectral components. The pulse-shaping system is particularly useful for generating optical pulses of selected temporal shape over a wide range of pulse duration, such pulses finding application in the fields of optical communication, optical recording and data storage, atomic and molecular spectroscopy and laser fusion. An optical streak camera is also provided which uses SBD to display the beam intensity in the focal plane as a function of time during the input pulse. 10 figures.
NASA Technical Reports Server (NTRS)
Gregg, Watson W.; Suarez, Max J. (Editor)
2002-01-01
An ocean-atmosphere radiative model (OARM) evaluates irradiance availability and quality in the water column to support phytoplankton growth and drive ocean thermodynamics. An atmospheric component incorporates spectral and directional effects of clear and cloudy skies as a function of atmospheric optical constituents, and spectral reflectance across the air-sea interface. An oceanic component evaluates the propagation of spectral and directional irradiance through the water column as a function of water, five phytoplankton groups, and chromophoric dissolved organic matter. It tracks the direct and diffuse streams from the atmospheric component, and a third stream, upwelling diffuse irradiance. The atmospheric component of OARM was compared to data sources at the ocean surface with a coefficient of determination (r2) of 0.97 and a root mean square of 12.1%.
NASA Astrophysics Data System (ADS)
Ozeki, Yasuyuki; Otsuka, Yoichi; Sato, Shuya; Hashimoto, Hiroyuki; Umemura, Wataru; Sumimura, Kazuhiko; Nishizawa, Norihiko; Fukui, Kiichi; Itoh, Kazuyoshi
2013-02-01
We have developed a video-rate stimulated Raman scattering (SRS) microscope with frame-by-frame wavenumber tunability. The system uses a 76-MHz picosecond Ti:sapphire laser and a subharmonically synchronized, 38-MHz Yb fiber laser. The Yb fiber laser pulses are spectrally sliced by a fast wavelength-tunable filter, which consists of a galvanometer scanner, a 4-f optical system and a reflective grating. The spectral resolution of the filter is ~ 3 cm-1. The wavenumber was scanned from 2800 to 3100 cm-1 with an arbitrary waveform synchronized to the frame trigger. For imaging, we introduced a 8-kHz resonant scanner and a galvanometer scanner. We were able to acquire SRS images of 500 x 480 pixels at a frame rate of 30.8 frames/s. Then these images were processed by principal component analysis followed by a modified algorithm of independent component analysis. This algorithm allows blind separation of constituents with overlapping Raman bands from SRS spectral images. The independent component (IC) spectra give spectroscopic information, and IC images can be used to produce pseudo-color images. We demonstrate various label-free imaging modalities such as 2D spectral imaging of the rat liver, two-color 3D imaging of a vessel in the rat liver, and spectral imaging of several sections of intestinal villi in the mouse. Various structures in the tissues such as lipid droplets, cytoplasm, fibrous texture, nucleus, and water-rich region were successfully visualized.
Detection of urban expansion in an urban-rural landscape with multitemporal QuickBird images
Lu, Dengsheng; Hetrick, Scott; Moran, Emilio; Li, Guiying
2011-01-01
Accurately detecting urban expansion with remote sensing techniques is a challenge due to the complexity of urban landscapes. This paper explored methods for detecting urban expansion with multitemporal QuickBird images in Lucas do Rio Verde, Mato Grosso, Brazil. Different techniques, including image differencing, principal component analysis (PCA), and comparison of classified impervious surface images with the matched filtering method, were used to examine urbanization detection. An impervious surface image classified with the hybrid method was used to modify the urbanization detection results. As a comparison, the original multispectral image and segmentation-based mean-spectral images were used during the detection of urbanization. This research indicates that the comparison of classified impervious surface images with matched filtering method provides the best change detection performance, followed by the image differencing method based on segmentation-based mean spectral images. The PCA is not a good method for urban change detection in this study. Shadows and high spectral variation within the impervious surfaces represent major challenges to the detection of urban expansion when high spatial resolution images are used. PMID:21799706
Wilkes, Thomas C; McGonigle, Andrew J S; Willmott, Jon R; Pering, Tom D; Cook, Joseph M
2017-11-01
We report on the development of a low-cost spectrometer, based on off-the-shelf optical components, a 3D printed housing, and a modified Raspberry Pi camera module. With a bandwidth and spectral resolution of ≈60 nm and 1 nm, respectively, this device was designed for ultraviolet (UV) remote sensing of atmospheric sulphur dioxide (SO 2 ), ≈310 nm. To the best of our knowledge, this is the first report of both a UV spectrometer and a nanometer resolution spectrometer based on smartphone sensor technology. The device performance was assessed and validated by measuring column amounts of SO 2 within quartz cells with a differential optical absorption spectroscopy processing routine. This system could easily be reconfigured to cover other UV-visible-near-infrared spectral regions, as well as alternate spectral ranges and/or linewidths. Hence, our intention is also to highlight how this framework could be applied to build bespoke, low-cost, spectrometers for a range of scientific applications.
Chavez, P.S.; Kwarteng, A.Y.
1989-01-01
A challenge encountered with Landsat Thematic Mapper (TM) data, which includes data from size reflective spectral bands, is displaying as much information as possible in a three-image set for color compositing or digital analysis. Principal component analysis (PCA) applied to the six TM bands simultaneously is often used to address this problem. However, two problems that can be encountered using the PCA method are that information of interest might be mathematically mapped to one of the unused components and that a color composite can be difficult to interpret. "Selective' PCA can be used to minimize both of these problems. The spectral contrast among several spectral regions was mapped for a northern Arizona site using Landsat TM data. Field investigations determined that most of the spectral contrast seen in this area was due to one of the following: the amount of iron and hematite in the soils and rocks, vegetation differences, standing and running water, or the presence of gypsum, which has a higher moisture retention capability than do the surrounding soils and rocks. -from Authors
Xie, Xiaoliang Sunney; Freudiger, Christian; Min, Wei
2016-03-15
A microscopy imaging system is disclosed that includes a light source system, a spectral shaper, a modulator system, an optics system, an optical detector and a processor. The light source system is for providing a first train of pulses and a second train of pulses. The spectral shaper is for spectrally modifying an optical property of at least some frequency components of the broadband range of frequency components such that the broadband range of frequency components is shaped producing a shaped first train of pulses to specifically probe a spectral feature of interest from a sample, and to reduce information from features that are not of interest from the sample. The modulator system is for modulating a property of at least one of the shaped first train of pulses and the second train of pulses at a modulation frequency. The optical detector is for detecting an integrated intensity of substantially all optical frequency components of a train of pulses of interest transmitted or reflected through the common focal volume. The processor is for detecting a modulation at the modulation frequency of the integrated intensity of substantially all of the optical frequency components of the train of pulses of interest due to the non-linear interaction of the shaped first train of pulses with the second train of pulses as modulated in the common focal volume, and for providing an output signal for a pixel of an image for the microscopy imaging system.
Evaluation of inflammatory processes by FTIR spectroscopy.
Rodrigues, Laís Morandini; Carvalho, Luís Felipe das Chagas E Silva; Bonnier, Franck; Anbinder, Ana Lia; Martinho, Herculano da Silva; Almeida, Janete Dias
2018-04-01
Fourier transform infrared (FTIR) spectroscopy is a powerful diagnosis technique and has been used to identify patterns of molecular changes based on vibration modes. The objective of this study was to evaluate inflammatory fibrous hyperplasia (IFH) lesions and oral normal mucosa (NM) initially with histopathological exam and then using micro-FTIR spectroscopy to analyse the samples. Eleven IFH and 11 NM samples were analysed at five different points to cover the largest area possible by the micro-FTIR technique. Bands were observed between 970 and 1743 cm -1 which corresponded to different structural components like collagen, lipids, fatty acids, proteins and amino acids. Spectral bands were more intense mostly for IFH lesions, including collagen bands, which are an important component of inflammatory fibrous hyperplasia. This study demonstrated that differentiation in the inflammatory tissue was observed in FTIR spectral differences, in terms of biochemical composition.
NASA Astrophysics Data System (ADS)
Dutta Banik, Gourab; Maity, Abhijit; Som, Suman; Pal, Mithun; Pradhan, Manik
2018-04-01
We report on the performance of a widely tunable continuous wave mode-hop-free external-cavity quantum cascade laser operating at λ ~ 5.2 µm combined with cavity ring-down spectroscopy (CRDS) technique for high-resolution molecular spectroscopy. The CRDS system has been utilized for simultaneous and molecule-specific detection of several environmentally and bio-medically important trace molecular species such as nitric oxide, nitrous oxide, carbonyl sulphide and acetylene (C2H2) at ultra-low concentrations by probing numerous rotationally resolved ro-vibrational transitions in the mid-IR spectral region within a relatively small spectral range of ~0.035 cm-1. This continuous wave external-cavity quantum cascade laser-based multi-component CRDS sensor with high sensitivity and molecular specificity promises applications in environmental sensing as well as non-invasive medical diagnosis through human breath analysis.
Kouveliotou, Chryssa; Granot, J.; Racusin, J. L.; ...
2013-11-21
Here, GRB 130427A occurred in a relatively nearby galaxy; its prompt emission had the largest GRB fluence ever recorded. The afterglow of GRB 130427A was bright enough for the Nuclear Spectroscopic Telescope ARray ( NuSTAR) to observe it in the 3-79 keV energy range long after its prompt emission (~1.5 and 5 days). This range, where afterglow observations were previously not possible, bridges an important spectral gap. Combined with Swift, Fermi, and ground-based optical data, NuSTAR observations unambiguously establish a single afterglow spectral component from optical to multi-GeV energies a day after the event, which is almost certainly synchrotron radiation.more » Such an origin of the late-time Fermi/Large Area Telescope >10 GeV photons requires revisions in our understanding of collisionless relativistic shock physics.« less
The possible ocular hazards of LED dental illumination applications.
Stamatacos, Catherine; Harrison, Janet L
2014-04-01
The use of high-intensity illumination via Light-Emitting Diode (LED) headlamps is gaining in popularity with dentists and student dentists. Practitioners are using LED headlamps together with magnifying loupes, overhead LED illumination and fiber-optic dental handpieces for long periods of time. Although most manufacturers of these LED illuminators advertise that their devices emit "white" light, these still consist of two spectral bands - the blue spectral band, with its peak at 445 nm, and the green with its peak at 555 nm. While manufacturers suggest that their devices emit "white" light, spectral components of LED lights from different companies are significantly different. Dental headlamp manufacturers strive to create a white LED, and they advertise that this type of light emitted from their product offers bright white-light illumination. However, the manufacturing of a white LED light is done through selection of a white LED-type based on the peak blue strength in combination with the green peak strength and thus creating a beam-forming optic, which determines the beam quality. Some LED illuminators have a strong blue-light component versus the green-light component. Blue-light is highly energized and is close in the color spectrum to ultraviolet-light. The hazards of retinal damage with the use of high-intensity blue-lights has been well-documented. There is limited research regarding the possible ocular hazards of usage of high-intensity illuminating LED devices. Furthermore, the authors have found little research, standards, or guidelines examining the possible safety issues regarding the unique dental practice setting consisting of the combined use of LED illumination systems. Another unexamined component is the effect of high-intensity light reflective glare and magnification back to the practitioner's eyes due to the use of water during dental procedures. Based on the result of Dr. Janet Harrison's observations of beginning dental students in a laboratory setting, the aim of this review is to raise awareness of the potential risk for eye damage when singular or combinations of LED illumination are used.
The possible ocular hazards of LED dental illumination applications.
Stamatacos, Catherine; Harrison, Janet L
2013-01-01
The use of high-intensity illumination via Light-Emitting Diode (LED) headlamps is gaining in popularity with dentists and student dentists. Practitioners are using LED headlamps together with magnifying loupes, overhead LED illumination and fiber-optic dental handpieces for long periods of time. Although most manufacturers of these LED illuminators advertise that their devices emit "white" light, these still consist of two spectral bands--the blue spectral band, with its peak at 445 nm, and the green with its peak at 555 nm. While manufacturers suggest that their devices emit "white" light, spectral components of LED lights from different companies are significantly different. Dental headlamp manufacturers strive to create a white LED, and they advertise that this type of light emitted from their product offers bright white-light illumination. However, the manufacturing of a white LED light is done through selection of a white LED-type based on the peak blue strength in combination with the green peak strength and thus creating a beam-forming optic, which determines the beam quality. Some LED illuminators have a strong blue-light component versus the green-light component. Blue-light is highly energized and is close in the color spectrum to ultraviolet-light. The hazards of retinal damage with the use of high-intensity blue-lights has been well-documented. There is limited research regarding the possible ocular hazards of usage of high-intensity illuminating LED devices. Furthermore, the authors have found little research, standards, or guidelines examining the possible safety issues regarding the unique dental practice setting consisting of the combined use of LED illumination systems. Another unexamined component is the effect of high-intensity light reflective glare and magnification back to the practitioner's eyes due to the use of water during dental procedures. Based on the result of Dr. Janet Harrison's observations of beginning dental students in a laboratory setting, the aim of this review is to raise awareness of the potential risk for eye damage when singular or combinations of LED illumination are used.
Monakhova, Yulia B; Mushtakova, Svetlana P
2017-05-01
A fast and reliable spectroscopic method for multicomponent quantitative analysis of targeted compounds with overlapping signals in complex mixtures has been established. The innovative analytical approach is based on the preliminary chemometric extraction of qualitative and quantitative information from UV-vis and IR spectral profiles of a calibration system using independent component analysis (ICA). Using this quantitative model and ICA resolution results of spectral profiling of "unknown" model mixtures, the absolute analyte concentrations in multicomponent mixtures and authentic samples were then calculated without reference solutions. Good recoveries generally between 95% and 105% were obtained. The method can be applied to any spectroscopic data that obey the Beer-Lambert-Bouguer law. The proposed method was tested on analysis of vitamins and caffeine in energy drinks and aromatic hydrocarbons in motor fuel with 10% error. The results demonstrated that the proposed method is a promising tool for rapid simultaneous multicomponent analysis in the case of spectral overlap and the absence/inaccessibility of reference materials.
NASA Astrophysics Data System (ADS)
Lisimenka, Aliaksandr; Kubicki, Adam
2017-02-01
A new spectral analysis technique is proposed for rhythmic bedform quantification, based on the 2D Fourier transform involving the calculation of a set of low-order spectral moments. The approach provides a tool for efficient quantification of bedform length and height as well as spatial crest-line alignment. Contrary to the conventional method, it not only describes the most energetic component of an undulating seabed surface but also retrieves information on its secondary structure without application of any band-pass filter of which the upper and lower cut-off frequencies are a priori unknown. Validation is based on bathymetric data collected in the main Vistula River mouth area (Przekop Wisły), Poland. This revealed two generations (distinct groups) of dunes which are migrating seawards along distinct paths, probably related to the hydrological regime of the river. The data enable the identification of dune divergence and convergence zones. The approach proved successful in the parameterisation of topographic roughness, an essential aspect in numerical modelling studies.
Multispectral image enhancement for H&E stained pathological tissue specimens
NASA Astrophysics Data System (ADS)
Bautista, Pinky A.; Abe, Tokiya; Yamaguchi, Masahiro; Ohyama, Nagaaki; Yagi, Yukako
2008-03-01
The presence of a liver disease such as cirrhosis can be determined by examining the proliferation of collagen fiber from a tissue slide stained with special stain such as the Masson's trichrome(MT) stain. Collagen fiber and smooth muscle, which are both stained the same in an H&E stained slide, are stained blue and pink respectively in an MT-stained slide. In this paper we show that with multispectral imaging the difference between collagen fiber and smooth muscle can be visualized even from an H&E stained image. In the method M KL bases are derived using the spectral data of those H&E stained tissue components which can be easily differentiated from each other, i.e. nucleus, cytoplasm, red blood cells, etc. and based on the spectral residual error of fiber weighting factors are determined to enhance spectral features at certain wavelengths. Results of our experiment demonstrate the capability of multispectral imaging and its advantage compared to the conventional RGB imaging systems to delineate tissue structures with subtle colorimetric difference.
Laser-based volumetric flow visualization by digital color imaging of a spectrally coded volume.
McGregor, T J; Spence, D J; Coutts, D W
2008-01-01
We present the framework for volumetric laser-based flow visualization instrumentation using a spectrally coded volume to achieve three-component three-dimensional particle velocimetry. By delivering light from a frequency doubled Nd:YAG laser with an optical fiber, we exploit stimulated Raman scattering within the fiber to generate a continuum spanning the visible spectrum from 500 to 850 nm. We shape and disperse the continuum light to illuminate a measurement volume of 20 x 10 x 4 mm(3), in which light sheets of differing spectral properties overlap to form an unambiguous color variation along the depth direction. Using a digital color camera we obtain images of particle fields in this volume. We extract the full spatial distribution of particles with depth inferred from particle color. This paper provides a proof of principle of this instrument, examining the spatial distribution of a static field and a spray field of water droplets ejected by the nozzle of an airbrush.
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.
NASA Astrophysics Data System (ADS)
Yu, Peiqiang
2011-11-01
To date, there is no study on bioethanol processing-induced changes in molecular structural profiles mainly related to lipid biopolymer. The objectives of this study were to: (1) determine molecular structural changes of lipid related functional groups in the co-products that occurred during bioethanol processing; (2) relatively quantify the antisymmetric CH 3 and CH 2 (ca. 2959 and 2928 cm -1, respectively), symmetric CH 3 and CH 2 (ca. 2871 and 2954 cm -1, respectively) functional groups, carbonyl C dbnd O ester (ca. 1745 cm -1) and unsaturated groups (CH attached to C dbnd C) (ca. 3007 cm -1) spectral intensities as well as their ratios of antisymmetric CH 3 to antisymmetric CH 2, and (3) illustrate the molecular spectral analyses as a research tool to detect for the sensitivity of individual moleculars to the bioethanol processing in a complex plant-based feed and food system without spectral parameterization. The hypothesis of this study was that bioethanol processing changed the molecular structure profiles in the co-products as opposed to original cereal grains. These changes could be detected by infrared molecular spectroscopy and will be related to nutrient utilization. The results showed that bioethanol processing had effects on the functional groups spectral profiles in the co-products. It was found that the CH 3-antisymmetric to CH 2-antisymmetric stretching intensity ratio was changed. The spectral features of carbonyl C dbnd O ester group and unsaturated group were also different. Since the different types of cereal grains (wheat vs. corn) had different sensitivity to the bioethanol processing, the spectral patterns and band component profiles differed between their co-products (wheat DDGS vs. corn DDGS). The multivariate molecular spectral analyses, cluster analysis and principal component analysis of original spectra (without spectral parameterization), distinguished the structural differences between the wheat and wheat DDGS and between the corn and corn DDGS in the antisymmetric and symmetric CH 3 and CH 2 spectral region (ca. 2994-2800 cm -1) and unsaturated group band region (3025-2996 cm -1). Further study is needed to quantify molecular structural changes in relation to nutrient utilization of lipid biopolymer.
A Thorough View of the Nuclear Region of NGC 253: Combined Herschel, SOFIA, and APEX Data Set
NASA Astrophysics Data System (ADS)
Pérez-Beaupuits, J. P.; Güsten, R.; Harris, A.; Requena-Torres, M. A.; Menten, K. M.; Weiß, A.; Polehampton, E.; van der Wiel, M. H. D.
2018-06-01
We present a large set of spectral lines detected in the 40″ central region of the starburst galaxy NGC 253. Observations were obtained with the three instruments SPIRE, PACS, and HIFI on board the Herschel Space Observatory, upGREAT on board the SOFIA airborne observatory, and the ground-based Atacama Pathfinder EXperiment telescope. Combining the spectral and photometry products of SPIRE and PACS, we model the dust continuum spectral energy distribution (SED) and the most complete 12CO line SED reported so far toward the nuclear region of NGC 253. The properties and excitation of the molecular gas were derived from a three-component non-LTE radiative transfer model, using the SPIRE 13CO lines and ground-based observations of the lower-J 13CO and HCN lines, to constrain the model parameters. Three dust temperatures were identified from the continuum emission, and three components are needed to fit the full CO line SED. Only the third CO component (fitting mostly the HCN and PACS 12CO lines) is consistent with a shock-/mechanical-heating scenario. A hot core chemistry is also argued as a plausible scenario to explain the high-J 12CO lines detected with PACS. The effect of enhanced cosmic-ray ionization rates, however, cannot be ruled out and is expected to play a significant role in the diffuse and dense gas chemistry. This is supported by the detection of ionic species like OH+ and H2O+, as well as the enhanced fluxes of the OH lines with respect to those of H2O lines detected in both PACS and SPIRE spectra.
Transcutaneous Raman Spectroscopy of Bone
NASA Astrophysics Data System (ADS)
Maher, Jason R.
Clinical diagnoses of bone health and fracture risk typically rely upon measurements of bone density or structure, but the strength of a bone is also dependent upon its chemical composition. One technology that has been used extensively in ex vivo, exposed-bone studies to measure the chemical composition of bone is Raman spectroscopy. This spectroscopic technique provides chemical information about a sample by probing its molecular vibrations. In the case of bone tissue, Raman spectra provide chemical information about both the inorganic mineral and organic matrix components, which each contribute to bone strength. To explore the relationship between bone strength and chemical composition, our laboratory has contributed to ex vivo, exposed-bone animal studies of rheumatoid arthritis, glucocorticoid-induced osteoporosis, and prolonged lead exposure. All of these studies suggest that Raman-based predictions of biomechanical strength may be more accurate than those produced by the clinically-used parameter of bone mineral density. The utility of Raman spectroscopy in ex vivo, exposed-bone studies has inspired attempts to perform bone spectroscopy transcutaneously. Although the results are promising, further advancements are necessary to make non-invasive, in vivo measurements of bone that are of sufficient quality to generate accurate predictions of fracture risk. In order to separate the signals from bone and soft tissue that contribute to a transcutaneous measurement, we developed an overconstrained extraction algorithm that is based upon fitting with spectral libraries derived from separately-acquired measurements of the underlying tissue components. This approach allows for accurate spectral unmixing despite the fact that similar chemical components (e.g., type I collagen) are present in both soft tissue and bone and was applied to experimental data in order to transcutaneously detect, to our knowledge for the first time, age- and disease-related spectral differences in murine bone.
Optical Characterization of Paper Aging Based on Laser-Induced Fluorescence (LIF) Spectroscopy.
Zhang, Hao; Wang, Shun; Chang, Keke; Sun, Haifeng; Guo, Qingqian; Ma, Liuzheng; Yang, Yatao; Zou, Caihong; Wang, Ling; Hu, Jiandong
2018-06-01
Paper aging and degradation are growing concerns for those who are responsible for the conservation of documents, archives, and libraries. In this study, the paper aging was investigated using laser-induced fluorescence spectroscopy (LIFS), where the fluorescence properties of 47 paper samples with different ages were explored. The paper exhibits fluorescence in the blue-green spectral region with two peaks at about 448 nm and 480 nm under the excitation of 405 nm laser. Both fluorescence peaks changed in absolute intensities and thus the ratio of peak intensities was also influenced with the increasing ages. By applying principal component analysis (PCA) and k-means clustering algorithm, all 47 paper samples were classified into nine groups based on the differences in paper age. Then the first-derivative fluorescence spectral curves were proposed to figure out the relationship between the spectral characteristic and the paper age, and two quantitative models were established based on the changes of first-derivative spectral peak at 443 nm, where one is an exponential fitting curve with an R-squared value of 0.99 and another is a linear fitting curve with an R-squared value of 0.88. The results demonstrated that the combination of fluorescence spectroscopy and PCA can be used for the classification of paper samples with different ages. Moreover, the first-derivative fluorescence spectral curves can be used to quantitatively evaluate the age-related changes of paper samples.
USDA-ARS?s Scientific Manuscript database
Chlorophyll is one of the major components of chloroplasts and a better understanding of the genetic basis of chlorophyll in soybean [Glycine max (L.) Merr.] might contribute to improving photosynthetic capacity and yield in regions with adverse environmental conditions. A collection of 332 diverse ...
NASA Astrophysics Data System (ADS)
Chang, Anteng; Li, Huajun; Wang, Shuqing; Du, Junfeng
2017-08-01
Both wave-frequency (WF) and low-frequency (LF) components of mooring tension are in principle non-Gaussian due to nonlinearities in the dynamic system. This paper conducts a comprehensive investigation of applicable probability density functions (PDFs) of mooring tension amplitudes used to assess mooring-line fatigue damage via the spectral method. Short-term statistical characteristics of mooring-line tension responses are firstly investigated, in which the discrepancy arising from Gaussian approximation is revealed by comparing kurtosis and skewness coefficients. Several distribution functions based on present analytical spectral methods are selected to express the statistical distribution of the mooring-line tension amplitudes. Results indicate that the Gamma-type distribution and a linear combination of Dirlik and Tovo-Benasciutti formulas are suitable for separate WF and LF mooring tension components. A novel parametric method based on nonlinear transformations and stochastic optimization is then proposed to increase the effectiveness of mooring-line fatigue assessment due to non-Gaussian bimodal tension responses. Using time domain simulation as a benchmark, its accuracy is further validated using a numerical case study of a moored semi-submersible platform.
NASA Astrophysics Data System (ADS)
Wakisaka, Yoshifumi; Suzuki, Yuta; Tokunaga, Kyoya; Hirose, Misa; Domon, Ryota; Akaho, Rina; Kuroshima, Mai; Tsumura, Norimichi; Shimobaba, Tomoyoshi; Iwata, Osamu; Suzuki, Kengo; Nakashima, Ayaka; Goda, Keisuke; Ozeki, Yasuyuki
2016-03-01
Microbes, especially microalgae, have recently been of great interest for developing novel biofuels, drugs, and biomaterials. Imaging-based screening of live cells can provide high selectivity and is attractive for efficient bio-production from microalgae. Although conventional cellular screening techniques use cell labeling, labeling of microbes is still under development and can interfere with their cellular functions. Furthermore, since live microbes move and change their shapes rapidly, a high-speed imaging technique is required to suppress motion artifacts. Stimulated Raman scattering (SRS) microscopy allows for label-free and high-speed spectral imaging, which helps us visualize chemical components inside biological cells and tissues. Here we demonstrate high-speed SRS imaging, with temporal resolution of 0.14 seconds, of intracellular distributions of lipid, polysaccharide, and chlorophyll concentrations in rapidly moving Euglena gracilis, a unicellular phytoflagellate. Furthermore, we show that our method allows us to analyze the amount of chemical components inside each living cell. Our results indicate that SRS imaging may be applied to label-free screening of living microbes based on chemical information.
NASA Technical Reports Server (NTRS)
Eguchi, Satoshi; Ueda, Yoshihiro; Terashima, Yuichi; Mushotzky, Richard F.; Tueller, Jack
2009-01-01
We present a systematic spectral analysis with Suzaku of six AGNs detected in the Swift/BAT hard X-ray (15-200 keV) survey, Swift J0138.6-4001, J0255.2-0011, J0350.1-5019, J0505.7-2348, J0601.9-8636, and J1628.1-5145. This is considered to be a representative sample of new AGNs without X-ray spectral information before the BAT survey. We find that the 0.5-200 keV spectra of these sources can be uniformly fit with a base model consisting of heavily absorbed (log NH >23.5/sq cm) transmitted components, scattered lights, a reflection component, and an iron-K emission line. There are two distinct groups, three "new type" AGNs (including the two sources reported by Ueda et al. 2007) with an extremely small scattered fraction (f(sub scat) < 0:5%) and strong reflection component (R = omega/2pi > or equal to 0.8 where omega is the solid angle of the reflector), and three "classical type" ones with f(sub scat > 0.5% and R < or approx. 0.8. The spectral parameters suggest that the new type has an optically thick torus for Thomson scattering (N(sub H) approx. 10(exp 25)/sq cm) with a small opening angle theta approx. 20deg viewed in a rather face-on geometry, while the classical type has a thin torus (N(sub H) approx. 10(exp 23-24)/sq cm) with theta > or approx. 30deg. We infer that a significant number of new type AGNs with an edge-on view is missing in the current all-sky hard X-ray surveys. Subject headings: galaxies: active . gamma rays: observations . X-rays: galaxies . X-rays: general
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.
Classification of Hyperspectral Data Based on Guided Filtering and Random Forest
NASA Astrophysics Data System (ADS)
Ma, H.; Feng, W.; Cao, X.; Wang, L.
2017-09-01
Hyperspectral images usually consist of more than one hundred spectral bands, which have potentials to provide rich spatial and spectral information. However, the application of hyperspectral data is still challengeable due to "the curse of dimensionality". In this context, many techniques, which aim to make full use of both the spatial and spectral information, are investigated. In order to preserve the geometrical information, meanwhile, with less spectral bands, we propose a novel method, which combines principal components analysis (PCA), guided image filtering and the random forest classifier (RF). In detail, PCA is firstly employed to reduce the dimension of spectral bands. Secondly, the guided image filtering technique is introduced to smooth land object, meanwhile preserving the edge of objects. Finally, the features are fed into RF classifier. To illustrate the effectiveness of the method, we carry out experiments over the popular Indian Pines data set, which is collected by Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) sensor. By comparing the proposed method with the method of only using PCA or guided image filter, we find that effect of the proposed method is better.
Automated method for the systematic interpretation of resonance peaks in spectrum data
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.
Automated method for the systematic interpretation of resonance peaks in spectrum data
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.
The Global Signature of Ocean Wave Spectra
NASA Astrophysics Data System (ADS)
Portilla-Yandún, Jesús
2018-01-01
A global atlas of ocean wave spectra is developed and presented. The development is based on a new technique for deriving wave spectral statistics, which is applied to the extensive ERA-Interim database from European Centre of Medium-Range Weather Forecasts. Spectral statistics is based on the idea of long-term wave systems, which are unique and distinct at every geographical point. The identification of those wave systems allows their separation from the overall spectrum using the partition technique. Their further characterization is made using standard integrated parameters, which turn out much more meaningful when applied to the individual components than to the total spectrum. The parameters developed include the density distribution of spectral partitions, which is the main descriptor; the identified wave systems; the individual distribution of the characteristic frequencies, directions, wave height, wave age, seasonal variability of wind and waves; return periods derived from extreme value analysis; and crossing-sea probabilities. This information is made available in web format for public use at http://www.modemat.epn.edu.ec/#/nereo. It is found that wave spectral statistics offers the possibility to synthesize data while providing a direct and comprehensive view of the local and regional wave conditions.
NASA Astrophysics Data System (ADS)
Guha, Arindam; Singh, Vivek Kr.; Parveen, Reshma; Kumar, K. Vinod; Jeyaseelan, A. T.; Dhanamjaya Rao, E. N.
2013-04-01
Bauxite deposits of Jharkhand in India are resulted from the lateritization process and therefore are often associated with the laterites. In the present study, ASTER (Advanced Space borne Thermal Emission and Reflection Radiometer) image is processed to delineate bauxite rich pockets within the laterites. In this regard, spectral signatures of lateritic bauxite samples are analyzed in the laboratory with reference to the spectral features of gibbsite (main mineral constituent of bauxite) and goethite (main mineral constituent of laterite) in VNIR-SWIR (visible-near infrared and short wave infrared) electromagnetic domain. The analysis of spectral signatures of lateritic bauxite samples helps in understanding the differences in the spectral features of bauxites and laterites. Based on these differences; ASTER data based relative band depth and simple ratio images are derived for spatial mapping of the bauxites developed within the lateritic province. In order to integrate the complementary information of different index image, an index based principal component (IPC) image is derived to incorporate the correlative information of these indices to delineate bauxite rich pockets. The occurrences of bauxite rich pockets derived from density sliced IPC image are further delimited by the topographic controls as it has been observed that the major bauxite occurrences of the area are controlled by slope and altitude. In addition to above, IPC image is draped over the digital elevation model (DEM) to illustrate how bauxite rich pockets are distributed with reference to the topographic variability of the terrain. Bauxite rich pockets delineated in the IPC image are also validated based on the known mine occurrences and existing geological map of the bauxite. It is also conceptually validated based on the spectral similarity of the bauxite pixels delineated in the IPC image with the ASTER convolved laboratory spectra of bauxite samples.
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.
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 and Geological Characterization of Beach Components in Northern Puerto Rico
NASA Astrophysics Data System (ADS)
Caraballo Álvarez, I. O.; Torres-Perez, J. L.; Barreto, M.
2015-12-01
Understanding how changes in beach components may reflect beach processes is essential since variations along beach profiles can shed light on river and ocean processes influencing beach sedimentation and beachrock formation. It is likely these influences are related to beach proximity within the Río Grande de Manatí river mouth. Therefore, this study focuses on characterizing beach components at two sites in Manatí, Puerto Rico. Playa Machuca and Playa Tombolo, which are separated by eolianites, differ greatly in sediment size, mineralogy, and beachrock morphology. Several approaches were taken to geologically and spectrally characterize main beach components at each site. These approaches included field and microscopic laboratory identification, granulometry, and a comparison between remote sensing reflectance (Rrs) obtained with a field spectroradiometer and pre-existing spectral library signatures. Preliminary results indicate a positive correlation between each method. This study may help explore the possibility of using only Rrs to characterize beach and shallow submarine components for detailed image analysis and management of coastal features.This study focuses on characterizing beach components at two sites in Manatí, Puerto Rico. Playa Machuca and Playa Tombolo, two beaches that are separated by eolianites, differ greatly in sediment size and mineralogy, as well as in beachrock morphology. Understanding how changes in beach components may reflect beach processes is essential, since it is likely that differences are mostly related to each beaches' proximity to the Río Grande de Manatí river mouth. Hence, changes in components along beach profiles can shed light on the river's and the ocean's influence on beach sedimentation and beachrock formation. Several approaches were taken to properly geologically and spectrally characterize the main beach components at each site. These approaches included field and microscopic laboratory identification, granulometry, and a comparison between remote sensing reflectance (Rrs) obtained with a field spectroradiometer and the ENVI spectral library. Preliminary results show a positive correlation between each method. This study may help explore the possibility of using only Rrs to characterize beach and shallow submarine components for detailed image analysis and management of coastal features.
NASA Astrophysics Data System (ADS)
Pan, M.-Ch.; Chu, W.-Ch.; Le, Duc-Do
2016-12-01
The paper presents an alternative Vold-Kalman filter order tracking (VKF_OT) method, i.e. adaptive angular-velocity VKF_OT technique, to extract and characterize order components in an adaptive manner for the condition monitoring and fault diagnosis of rotary machinery. The order/spectral waveforms to be tracked can be recursively solved by using Kalman filter based on the one-step state prediction. The paper comprises theoretical derivation of computation scheme, numerical implementation, and parameter investigation. Comparisons of the adaptive VKF_OT scheme with two other ones are performed through processing synthetic signals of designated order components. Processing parameters such as the weighting factor and the correlation matrix of process noise, and data conditions like the sampling frequency, which influence tracking behavior, are explored. The merits such as adaptive processing nature and computation efficiency brought by the proposed scheme are addressed although the computation was performed in off-line conditions. The proposed scheme can simultaneously extract multiple spectral components, and effectively decouple close and crossing orders associated with multi-axial reference rotating speeds.
Vibrational response of a rectangular duct of finite length excited by a turbulent internal flow
NASA Astrophysics Data System (ADS)
David, Antoine; Hugues, Florian; Dauchez, Nicolas; Perrey-Debain, Emmanuel
2018-05-01
Gas transport ductwork in industrial plants or air conditioning networks can be subject to vibrations induced by the internal flow. Most studies in this matter have been carried out on circular ducts. This paper focuses specifically on the vibratory response of a rectangular duct of finite length excited by an internal turbulent flow. A semi-analytical model taking into account the modal response of the structure due to both aerodynamic and acoustic contributions is derived. The aerodynamic component of the excitation is applied on the basis of Corcos model where the power spectral density of the wall pressure is determined experimentally. The acoustic component is based on the propagating modes in the duct where the acoustic modal contribution are extracted via cross-spectral densities. The vibrational response is given for a 0.2 × 0.1 × 0.5 m3 duct made of 3 mm steel plates excited by 20 m/s or 30 m/s flows. Comparisons between experimental results and numerical predictions show a good agreement. The competition between acoustic and aerodynamic components is highlighted.
Spectral gene set enrichment (SGSE).
Frost, H Robert; Li, Zhigang; Moore, Jason H
2015-03-03
Gene set testing is typically performed in a supervised context to quantify the association between groups of genes and a clinical phenotype. In many cases, however, a gene set-based interpretation of genomic data is desired in the absence of a phenotype variable. Although methods exist for unsupervised gene set testing, they predominantly compute enrichment relative to clusters of the genomic variables with performance strongly dependent on the clustering algorithm and number of clusters. We propose a novel method, spectral gene set enrichment (SGSE), for unsupervised competitive testing of the association between gene sets and empirical data sources. SGSE first computes the statistical association between gene sets and principal components (PCs) using our principal component gene set enrichment (PCGSE) method. The overall statistical association between each gene set and the spectral structure of the data is then computed by combining the PC-level p-values using the weighted Z-method with weights set to the PC variance scaled by Tracy-Widom test p-values. Using simulated data, we show that the SGSE algorithm can accurately recover spectral features from noisy data. To illustrate the utility of our method on real data, we demonstrate the superior performance of the SGSE method relative to standard cluster-based techniques for testing the association between MSigDB gene sets and the variance structure of microarray gene expression data. Unsupervised gene set testing can provide important information about the biological signal held in high-dimensional genomic data sets. Because it uses the association between gene sets and samples PCs to generate a measure of unsupervised enrichment, the SGSE method is independent of cluster or network creation algorithms and, most importantly, is able to utilize the statistical significance of PC eigenvalues to ignore elements of the data most likely to represent noise.
2MASS J20261584-2943124: an Unresolved L0.5 + T6 Spectral Binary
NASA Astrophysics Data System (ADS)
Gelino, Christopher R.; Burgasser, Adam J.
2010-07-01
We identify the L dwarf 2MASS J20261584-2943124 as an unresolved spectral binary, based on low-resolution, near-infrared spectroscopy from IRTF/SpeX. The data reveal a peculiar absorption feature at 1.6 μm, previously noted in the spectra of other very low-mass spectral binaries, which likely arises from overlapping FeH and CH4 absorption bands in the blended light of an L dwarf/T dwarf pair. Spectral template matching analysis indicates component types of L0.5 and T6, with relative brightness ΔH = 4.2 ± 0.6. Laser guide star adaptive optics imaging observations with Keck/NIRC2 fail to resolve the source, indicating a maximum separation at the observing epoch of 0farcs25, or a projected separation of 9 AU assuming a distance of 36 ± 5 pc. With an age that is likely to be relatively older (gsim5 Gyr) based on the system's large V tan and mass ratio arguments, the relative motion of the potentially "massive" (0.06-0.08 M sun) components of 2MASS J2026-2943 may be detectable through radial velocity variations, like its earlier-type counterpart 2MASS J03202839-0446358 (M8+T5), providing dynamical mass measurements that span the hydrogen burning limit. Some of the data presented herein were obtained at the W. M. Keck Observatory, which is operated as a scientific partnership among the California Institute of Technology, the University of California, and the National Aeronautics and Space Administration. The Observatory was made possible by the generous financial support of the W. M. Keck Foundation.
On the Origin and Evolution of Stellar Chromospheres, Coronae and Winds
NASA Technical Reports Server (NTRS)
Musielak, Z. E.
1997-01-01
The final report discusses work completed on proposals to construct state-of-the-art, theoretical, two-component, chromospheric models for single stars of different spectral types and different evolutionary status. We suggested to use these models to predict the level of the "basal flux", the observed range of variation of chromospheric activity for a given spectral type, and the decrease of this activity with stellar age. In addition, for red giants and supergiants, we also proposed to construct self-consistent, purely theoretical, chromosphere-wind models, and investigate the origin of "dividing lines" in the H-R diagram. In the report, we list the following six specific goals for the first and second year of the proposed research and then describe the completed work: (1) To calculate the acoustic and magnetic wave energy fluxes for stars located in different regions of the H-R diagram; (2) To investigate the transfer of this non-radiative energy through stellar photospheres and to estimate the amount of energy that reaches the chromosphere; (3) To identify major sources of radiative losses in stellar chromospheres and calculate the amount of emitted energy; (4) To use (1) through (3) to construct purely theoretical, two-component, chromospheric models based on the local energy balance. The models will be constructed for stars of different spectral types and different evolutionary status; (5) To explain theoretically the "basal flux", the location of stellar temperature minima and the observed range of chromospheric activity for stars of the same spectral type; and (6) To construct self-consistent, time-dependent stellar wind models based on the momentum deposition by finite amplitude Alfven waves.
Stayman, J Webster; Tilley, Steven; Siewerdsen, Jeffrey H
2014-01-01
Previous investigations [1-3] have demonstrated that integrating specific knowledge of the structure and composition of components like surgical implants, devices, and tools into a model-based reconstruction framework can improve image quality and allow for potential exposure reductions in CT. Using device knowledge in practice is complicated by uncertainties in the exact shape of components and their particular material composition. Such unknowns in the morphology and attenuation properties lead to errors in the forward model that limit the utility of component integration. In this work, a methodology is presented to accommodate both uncertainties in shape as well as unknown energy-dependent attenuation properties of the surgical devices. This work leverages the so-called known-component reconstruction (KCR) framework [1] with a generalized deformable registration operator and modifications to accommodate a spectral transfer function in the component model. Moreover, since this framework decomposes the object into separate background anatomy and "known" component factors, a mixed fidelity forward model can be adopted so that measurements associated with projections through the surgical devices can be modeled with much greater accuracy. A deformable KCR (dKCR) approach using the mixed fidelity model is introduced and applied to a flexible wire component with unknown structure and composition. Image quality advantages of dKCR over traditional reconstruction methods are illustrated in cone-beam CT (CBCT) data acquired on a testbench emulating a 3D-guided needle biopsy procedure - i.e., a deformable component (needle) with strong energy-dependent attenuation characteristics (steel) within a complex soft-tissue background.
Lim, Liang; Nichols, Brandon; Migden, Michael R.; Rajaram, Narasimhan; Reichenberg, Jason S.; Markey, Mia K.; Ross, Merrick I.; Tunnell, James W.
2014-01-01
Abstract. The goal of this study was to determine the diagnostic capability of a multimodal spectral diagnosis (SD) for in vivo noninvasive disease diagnosis of melanoma and nonmelanoma skin cancers. We acquired reflectance, fluorescence, and Raman spectra from 137 lesions in 76 patients using custom-built optical fiber-based clinical systems. Biopsies of lesions were classified using standard histopathology as malignant melanoma (MM), nonmelanoma pigmented lesion (PL), basal cell carcinoma (BCC), actinic keratosis (AK), and squamous cell carcinoma (SCC). Spectral data were analyzed using principal component analysis. Using multiple diagnostically relevant principal components, we built leave-one-out logistic regression classifiers. Classification results were compared with histopathology of the lesion. Sensitivity/specificity for classifying MM versus PL (12 versus 17 lesions) was 100%/100%, for SCC and BCC versus AK (57 versus 14 lesions) was 95%/71%, and for AK and SCC and BCC versus normal skin (71 versus 71 lesions) was 90%/85%. The best classification for nonmelanoma skin cancers required multiple modalities; however, the best melanoma classification occurred with Raman spectroscopy alone. The high diagnostic accuracy for classifying both melanoma and nonmelanoma skin cancer lesions demonstrates the potential for SD as a clinical diagnostic device. PMID:25375350
Galievsky, Victor A; Stasheuski, Alexander S; Krylov, Sergey N
2017-10-17
The limit-of-detection (LOD) in analytical instruments with fluorescence detection can be improved by reducing noise of optical background. Efficiently reducing optical background noise in systems with spectrally nonuniform background requires complex optimization of an emission filter-the main element of spectral filtration. Here, we introduce a filter-optimization method, which utilizes an expression for the signal-to-noise ratio (SNR) as a function of (i) all noise components (dark, shot, and flicker), (ii) emission spectrum of the analyte, (iii) emission spectrum of the optical background, and (iv) transmittance spectrum of the emission filter. In essence, the noise components and the emission spectra are determined experimentally and substituted into the expression. This leaves a single variable-the transmittance spectrum of the filter-which is optimized numerically by maximizing SNR. Maximizing SNR provides an accurate way of filter optimization, while a previously used approach based on maximizing a signal-to-background ratio (SBR) is the approximation that can lead to much poorer LOD specifically in detection of fluorescently labeled biomolecules. The proposed filter-optimization method will be an indispensable tool for developing new and improving existing fluorescence-detection systems aiming at ultimately low LOD.
NASA Astrophysics Data System (ADS)
Lim, Liang; Nichols, Brandon; Migden, Michael R.; Rajaram, Narasimhan; Reichenberg, Jason S.; Markey, Mia K.; Ross, Merrick I.; Tunnell, James W.
2014-11-01
The goal of this study was to determine the diagnostic capability of a multimodal spectral diagnosis (SD) for in vivo noninvasive disease diagnosis of melanoma and nonmelanoma skin cancers. We acquired reflectance, fluorescence, and Raman spectra from 137 lesions in 76 patients using custom-built optical fiber-based clinical systems. Biopsies of lesions were classified using standard histopathology as malignant melanoma (MM), nonmelanoma pigmented lesion (PL), basal cell carcinoma (BCC), actinic keratosis (AK), and squamous cell carcinoma (SCC). Spectral data were analyzed using principal component analysis. Using multiple diagnostically relevant principal components, we built leave-one-out logistic regression classifiers. Classification results were compared with histopathology of the lesion. Sensitivity/specificity for classifying MM versus PL (12 versus 17 lesions) was 100%;/100%;, for SCC and BCC versus AK (57 versus 14 lesions) was 95%;/71%, and for AK and SCC and BCC versus normal skin (71 versus 71 lesions) was 90%/85%. The best classification for nonmelanoma skin cancers required multiple modalities; however, the best melanoma classification occurred with Raman spectroscopy alone. The high diagnostic accuracy for classifying both melanoma and nonmelanoma skin cancer lesions demonstrates the potential for SD as a clinical diagnostic device.
NASA Technical Reports Server (NTRS)
Rampe, E. B.; Lanza, N. L.
2012-01-01
Orbital near-infrared (NIR) reflectance spectra of the martian surface from the OMEGA and CRISM instruments have identified a variety of phyllosilicates in Noachian terrains. The types of phyllosilicates present on Mars have important implications for the aqueous environments in which they formed, and, thus, for recognizing locales that may have been habitable. Current identifications of phyllosilicates from martian NIR data are based on the positions of spectral absorptions relative to laboratory data of well-characterized samples and from spectral ratios; however, some phyllosilicates can be difficult to distinguish from one another with these methods (i.e. illite vs. muscovite). Here we employ a multivariate statistical technique, principal component analysis (PCA), to differentiate between spectrally similar phyllosilicate minerals. PCA is commonly used in a variety of industries (pharmaceutical, agricultural, viticultural) to discriminate between samples. Previous work using PCA to analyze raw NIR reflectance data from mineral mixtures has shown that this is a viable technique for identifying mineral types, abundances, and particle sizes. Here, we evaluate PCA of second-derivative NIR reflectance data as a method for classifying phyllosilicates and test whether this method can be used to identify phyllosilicates on Mars.
NASA Astrophysics Data System (ADS)
Matsuoka, M.
2012-07-01
A considerable number of methods for pansharpening remote-sensing images have been developed to generate higher spatial resolution multispectral images by the fusion of lower resolution multispectral images and higher resolution panchromatic images. Because pansharpening alters the spectral properties of multispectral images, method selection is one of the key factors influencing the accuracy of subsequent analyses such as land-cover classification or change detection. In this study, seven pixel-based pansharpening methods (additive wavelet intensity, additive wavelet principal component, generalized Laplacian pyramid with spectral distortion minimization, generalized intensity-hue-saturation (GIHS) transform, GIHS adaptive, Gram-Schmidt spectral sharpening, and block-based synthetic variable ratio) were compared using AVNIR-2 and PRISM onboard ALOS from the viewpoint of the preservation of spectral properties of AVNIR-2. A visual comparison was made between pansharpened images generated from spatially degraded AVNIR-2 and original images over urban, agricultural, and forest areas. The similarity of the images was evaluated in terms of the image contrast, the color distinction, and the brightness of the ground objects. In the quantitative assessment, three kinds of statistical indices, correlation coefficient, ERGAS, and Q index, were calculated by band and land-cover type. These scores were relatively superior in bands 2 and 3 compared with the other two bands, especially over urban and agricultural areas. Band 4 showed a strong dependency on the land-cover type. This was attributable to the differences in the observing spectral wavelengths of the sensors and local scene variances.
Spectral Analysis of Vector Magnetic Field Profiles
NASA Technical Reports Server (NTRS)
Parker, Robert L.; OBrien, Michael S.
1997-01-01
We investigate the power spectra and cross spectra derived from the three components of the vector magnetic field measured on a straight horizontal path above a statistically stationary source. All of these spectra, which can be estimated from the recorded time series, are related to a single two-dimensional power spectral density via integrals that run in the across-track direction in the wavenumber domain. Thus the measured spectra must obey a number of strong constraints: for example, the sum of the two power spectral densities of the two horizontal field components equals the power spectral density of the vertical component at every wavenumber and the phase spectrum between the vertical and along-track components is always pi/2. These constraints provide powerful checks on the quality of the measured data; if they are violated, measurement or environmental noise should be suspected. The noise due to errors of orientation has a clear characteristic; both the power and phase spectra of the components differ from those of crustal signals, which makes orientation noise easy to detect and to quantify. The spectra of the crustal signals can be inverted to obtain information about the cross-track structure of the field. We illustrate these ideas using a high-altitude Project Magnet profile flown in the southeastern Pacific Ocean.
Multi-timescale data assimilation for atmosphere–ocean state estimates
DOE Office of Scientific and Technical Information (OSTI.GOV)
Steiger, Nathan; Hakim, Gregory
2016-06-24
Paleoclimate proxy data span seasonal to millennial timescales, and Earth's climate system has both high- and low-frequency components. Yet it is currently unclear how best to incorporate multiple timescales of proxy data into a single reconstruction framework and to also capture both high- and low-frequency components of reconstructed variables. Here we present a data assimilation approach that can explicitly incorporate proxy data at arbitrary timescales. The principal advantage of using such an approach is that it allows much more proxy data to inform a climate reconstruction, though there can be additional benefits. Through a series of offline data-assimilation-based pseudoproxy experiments,more » we find that atmosphere–ocean states are most skillfully reconstructed by incorporating proxies across multiple timescales compared to using proxies at short (annual) or long (~ decadal) timescales alone. Additionally, reconstructions that incorporate long-timescale pseudoproxies improve the low-frequency components of the reconstructions relative to using only high-resolution pseudoproxies. We argue that this is because time averaging high-resolution observations improves their covariance relationship with the slowly varying components of the coupled-climate system, which the data assimilation algorithm can exploit. These results are consistent across the climate models considered, despite the model variables having very different spectral characteristics. Furthermore, our results also suggest that it may be possible to reconstruct features of the oceanic meridional overturning circulation based on atmospheric surface temperature proxies, though here we find such reconstructions lack spectral power over a broad range of frequencies.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tahani, K.; Plume, R.; Bergin, E. A.
2016-11-20
We present results from a comprehensive submillimeter spectral survey toward the source Orion South, based on data obtained with the Heterodyne Instrument for the Far-Infrared instrument on board the Herschel Space Observatory , covering the frequency range of 480 to 1900 GHz. We detect 685 spectral lines with signal-to-noise ratios (S/Ns) > 3 σ , originating from 52 different molecular and atomic species. We model each of the detected species assuming conditions of Local Thermodynamic Equilibrium. This analysis provides an estimate of the physical conditions of Orion South (column density, temperature, source size, and V {sub LSR}). We find evidencemore » for three different cloud components: a cool ( T {sub ex} ∼ 20–40 K), spatially extended (>60″), and quiescent (Δ V {sub FWHM} ∼ 4 km s{sup -1}) component; a warmer ( T {sub ex} ∼ 80–100 K), less spatially extended (∼30″), and dynamic (Δ V {sub FWHM} ∼ 8 km s{sup -1}) component, which is likely affected by embedded outflows; and a kinematically distinct region ( T {sub ex} > 100 K; V {sub LSR} ∼ 8 km s{sup -1}), dominated by emission from species that trace ultraviolet irradiation, likely at the surface of the cloud. We find little evidence for the existence of a chemically distinct “hot-core” component, likely due to the small filling factor of the hot core or hot cores within the Herschel beam. We find that the chemical composition of the gas in the cooler, quiescent component of Orion South more closely resembles that of the quiescent ridge in Orion-KL. The gas in the warmer, dynamic component, however, more closely resembles that of the Compact Ridge and Plateau regions of Orion-KL, suggesting that higher temperatures and shocks also have an influence on the overall chemistry of Orion South.« less
Design, fabrication and testing of hierarchical micro-optical structures and systems
NASA Astrophysics Data System (ADS)
Cannistra, Aaron Thomas
Micro-optical systems are becoming essential components in imaging, sensing, communications, computing, and other applications. Optically based designs are replacing electronic, chemical and mechanical systems for a variety of reasons, including low power consumption, reduced maintenance, and faster operation. However, as the number and variety of applications increases, micro-optical system designs are becoming smaller, more integrated, and more complicated. Micro and nano-optical systems found in nature, such as the imaging systems found in many insects and crustaceans, can have highly integrated optical structures that vary in size by orders of magnitude. These systems incorporate components such as compound lenses, anti-reflective lens surface structuring, spectral filters, and polarization selective elements. For animals, these hybrid optical systems capable of many optical functions in a compact package have been repeatedly selected during the evolutionary process. Understanding the advantages of these designs gives motivation for synthetic optical systems with comparable functionality. However, alternative fabrication methods that deviate from conventional processes are needed to create such systems. Further complicating the issue, the resulting device geometry may not be readily compatible with existing measurement techniques. This dissertation explores several nontraditional fabrication techniques for optical components with hierarchical geometries and measurement techniques to evaluate performance of such components. A micro-transfer molding process is found to produce high-fidelity micro-optical structures and is used to fabricate a spectral filter on a curved surface. By using a custom measurement setup we demonstrate that the spectral filter retains functionality despite the nontraditional geometry. A compound lens is fabricated using similar fabrication techniques and the imaging performance is analyzed. A spray coating technique for photoresist application to curved surfaces combined with interference lithography is also investigated. Using this technique, we generate polarizers on curved surfaces and measure their performance. This work furthers an understanding of how combining multiple optical components affects the performance of each component, the final integrated devices, and leads towards realization of biomimetically inspired imaging systems.
SpectralNET – an application for spectral graph analysis and visualization
Forman, Joshua J; Clemons, Paul A; Schreiber, Stuart L; Haggarty, Stephen J
2005-01-01
Background Graph theory provides a computational framework for modeling a variety of datasets including those emerging from genomics, proteomics, and chemical genetics. Networks of genes, proteins, small molecules, or other objects of study can be represented as graphs of nodes (vertices) and interactions (edges) that can carry different weights. SpectralNET is a flexible application for analyzing and visualizing these biological and chemical networks. Results Available both as a standalone .NET executable and as an ASP.NET web application, SpectralNET was designed specifically with the analysis of graph-theoretic metrics in mind, a computational task not easily accessible using currently available applications. Users can choose either to upload a network for analysis using a variety of input formats, or to have SpectralNET generate an idealized random network for comparison to a real-world dataset. Whichever graph-generation method is used, SpectralNET displays detailed information about each connected component of the graph, including graphs of degree distribution, clustering coefficient by degree, and average distance by degree. In addition, extensive information about the selected vertex is shown, including degree, clustering coefficient, various distance metrics, and the corresponding components of the adjacency, Laplacian, and normalized Laplacian eigenvectors. SpectralNET also displays several graph visualizations, including a linear dimensionality reduction for uploaded datasets (Principal Components Analysis) and a non-linear dimensionality reduction that provides an elegant view of global graph structure (Laplacian eigenvectors). Conclusion SpectralNET provides an easily accessible means of analyzing graph-theoretic metrics for data modeling and dimensionality reduction. SpectralNET is publicly available as both a .NET application and an ASP.NET web application from . Source code is available upon request. PMID:16236170
SpectralNET--an application for spectral graph analysis and visualization.
Forman, Joshua J; Clemons, Paul A; Schreiber, Stuart L; Haggarty, Stephen J
2005-10-19
Graph theory provides a computational framework for modeling a variety of datasets including those emerging from genomics, proteomics, and chemical genetics. Networks of genes, proteins, small molecules, or other objects of study can be represented as graphs of nodes (vertices) and interactions (edges) that can carry different weights. SpectralNET is a flexible application for analyzing and visualizing these biological and chemical networks. Available both as a standalone .NET executable and as an ASP.NET web application, SpectralNET was designed specifically with the analysis of graph-theoretic metrics in mind, a computational task not easily accessible using currently available applications. Users can choose either to upload a network for analysis using a variety of input formats, or to have SpectralNET generate an idealized random network for comparison to a real-world dataset. Whichever graph-generation method is used, SpectralNET displays detailed information about each connected component of the graph, including graphs of degree distribution, clustering coefficient by degree, and average distance by degree. In addition, extensive information about the selected vertex is shown, including degree, clustering coefficient, various distance metrics, and the corresponding components of the adjacency, Laplacian, and normalized Laplacian eigenvectors. SpectralNET also displays several graph visualizations, including a linear dimensionality reduction for uploaded datasets (Principal Components Analysis) and a non-linear dimensionality reduction that provides an elegant view of global graph structure (Laplacian eigenvectors). SpectralNET provides an easily accessible means of analyzing graph-theoretic metrics for data modeling and dimensionality reduction. SpectralNET is publicly available as both a .NET application and an ASP.NET web application from http://chembank.broad.harvard.edu/resources/. Source code is available upon request.
Understanding the Long-Term Spectral Variability of Cygnus X-1 from BATSE and ASM Observations
NASA Technical Reports Server (NTRS)
Zdziarski, Andrzej A.; Poutanen, Juri; Paciesas, William S.; Wen, Linqing; Six, N. Frank (Technical Monitor)
2002-01-01
We present a spectral analysis of observations of Cygnus X-1 by the RXTE/ASM (1.5-12 keV) and CGRO/BATSE (20-300 keV), including about 1200 days of simultaneous data. We find a number of correlations between intensities and hardnesses in different energy bands from 1.5 keV to 300 keV. In the hard (low) spectral state, there is a negative correlation between the ASM 1.5-12 keV flux and the hardness at any energy. In the soft (high) spectral state, the ASM flux is positively correlated with the ASM hardness (as previously reported) but uncorrelated with the BATSE hardness. In both spectral states, the BATSE hardness correlates with the flux above 100 keV, while it shows no correlation with the flux in the 20-100 keV range. At the same time, there is clear correlation between the BATSE fluxes below and above 100 keV. In the hard state, most of the variability can be explained by softening the overall spectrum with a pivot at approximately 50 keV. The observations show that there has to be another, independent variability pattern of lower amplitude where the spectral shape does not change when the luminosity changes. In the soft state, the variability is mostly caused by a variable hard (Comptonized) spectral component of a constant shape superimposed on a constant soft blackbody component. These variability patterns are in agreement with the dependence of the rms variability on the photon energy in the two states. We interpret the observed correlations in terms of theoretical Comptonization models. In the hard state, the variability appears to be driven mostly by changing flux in seed photons Comptonized in a hot thermal plasma cloud with an approximately constant power supply. In the soft state, the variability is consistent with flares of hybrid, thermal/nonthermal, plasma with variable power above a stable cold disk. Also, based on broadband pointed observations simultaneous with those of the ASM and BATSE, we find the intrinsic bolometric luminosity increases by a factor of approximately 3-4 from the hard state to the soft one, which supports models of the state transition based on a change of the accretion rate.
Laser- and Multi-Spectral Monitoring of Natural Objects from UAVs
NASA Astrophysics Data System (ADS)
Reiterer, Alexander; Frey, Simon; Koch, Barbara; Stemmler, Simon; Weinacker, Holger; Hoffmann, Annemarie; Weiler, Markus; Hergarten, Stefan
2016-04-01
The paper describes the research, development and evaluation of a lightweight sensor system for UAVs. The system is composed of three main components: (1) a laser scanning module, (2) a multi-spectral camera system, and (3) a processing/storage unit. All three components are newly developed. Beside measurement precision and frequency, the low weight has been one of the challenging tasks. The current system has a total weight of about 2.5 kg and is designed as a self-contained unit (incl. storage and battery units). The main features of the system are: laser-based multi-echo 3D measurement by a wavelength of 905 nm (totally eye save), measurement range up to 200 m, measurement frequency of 40 kHz, scanning frequency of 16 Hz, relative distance accuracy of 10 mm. The system is equipped with both GNSS and IMU. Alternatively, a multi-visual-odometry system has been integrated to estimate the trajectory of the UAV by image features (based on this system a calculation of 3D-coordinates without GNSS is possible). The integrated multi-spectral camera system is based on conventional CMOS-image-chips equipped with a special sets of band-pass interference filters with a full width half maximum (FWHM) of 50 nm. Good results for calculating the normalized difference vegetation index (NDVI) and the wide dynamic range vegetation index (WDRVI) have been achieved using the band-pass interference filter-set with a FWHM of 50 nm and an exposure times between 5.000 μs and 7.000 μs. The system is currently used for monitoring of natural objects and surfaces, like forest, as well as for geo-risk analysis (landslides). By measuring 3D-geometric and multi-spectral information a reliable monitoring and interpretation of the data-set is possible. The paper gives an overview about the development steps, the system, the evaluation and first results.
A SPECTRAL GRAPH APPROACH TO DISCOVERING GENETIC ANCESTRY1
Lee, Ann B.; Luca, Diana; Roeder, Kathryn
2010-01-01
Mapping human genetic variation is fundamentally interesting in fields such as anthropology and forensic inference. At the same time, patterns of genetic diversity confound efforts to determine the genetic basis of complex disease. Due to technological advances, it is now possible to measure hundreds of thousands of genetic variants per individual across the genome. Principal component analysis (PCA) is routinely used to summarize the genetic similarity between subjects. The eigenvectors are interpreted as dimensions of ancestry. We build on this idea using a spectral graph approach. In the process we draw on connections between multidimensional scaling and spectral kernel methods. Our approach, based on a spectral embedding derived from the normalized Laplacian of a graph, can produce more meaningful delineation of ancestry than by using PCA. The method is stable to outliers and can more easily incorporate different similarity measures of genetic data than PCA. We illustrate a new algorithm for genetic clustering and association analysis on a large, genetically heterogeneous sample. PMID:20689656
NASA Astrophysics Data System (ADS)
Devpura, Suneetha; Thakur, Jagdish S.; Poulik, Janet M.; Rabah, Raja; Naik, Vaman M.; Naik, Ratna
2012-02-01
We have investigated the cellular regions in neuroblastoma and ganglioneuroma using Raman spectroscopy and compared their spectral characteristics with those of normal adrenal gland. Thin sections from both frozen and deparaffinized tissues, obtained from the same tissue specimen, were studied in conjunction with the pathological examination of the tissues. We found a significant difference in the spectral features of frozen sections of normal adrenal gland, neuroblastoma, and ganglioneuroma when compared to deparaffinized tissues. The quantitative analysis of the Raman data using chemometric methods of principal component analysis and discriminant function analysis obtained from the frozen tissues show a sensitivity and specificity of 100% each. The biochemical identification based on the spectral differences shows that the normal adrenal gland tissues have higher levels of carotenoids, lipids, and cholesterol compared to the neuroblastoma and ganglioneuroma frozen tissues. However, deparaffinized tissues show complete removal of these biochemicals in adrenal tissues. This study demonstrates that Raman spectroscopy combined with chemometric methods can successfully distinguish neuroblastoma and ganglioneuroma at cellular level.
NASA Astrophysics Data System (ADS)
Ashley, P. R.; Temmen, M. G.; Diffey, W. M.; Sanghadasa, M.; Bramson, M. D.
2007-10-01
Active and passive polymer materials have been successfully used in the development of highly accurate, compact and low cost guided-wave components: an optical transceiver and a phase modulator, for inertial measurement units (IMUs) based on the interferometric fibre optic gyroscope (IFOG) technology for precision guidance in navigation systems. High performance and low noise transceivers with high optical power and good spectral quality were fabricated using a silicon-bench architecture. Low loss phase modulators with low halfwave drive voltage (Vπ) have been fabricated with a backscatter compensated design using polarizing waveguides consisting of CLD- and FTC-type high performance electro-optic (E-O) chromophores. Gyro bias stability of less than 0.02° h-1 has been demonstrated with these guided-wave components.
Coherent energy exchange between components of a vector soliton in fiber lasers.
Zhang, H; Tang, D Y; Zhao, L M; Xiang, N
2008-08-18
We report on the experimental evidence of four wave mixing (FWM) between the two polarization components of a vector soliton formed in a passively mode-locked fiber laser. Extra spectral sidebands with out-of-phase intensity variation between the polarization resolved soliton spectra was firstly observed, which was identified to be caused by the energy exchange between the two soliton polarization components. Other features of the FWM spectral sidebands and the soliton internal FWM were also experimentally investigated and numerically confirmed.
1992-12-01
spectral components. Spectral components were selected on the basis of their relation to states of alertness. In normal human adults , diffuse low...deterioration of handwriting , and ultimately, loss of consciousness. Belyavin and Wright (1987) reported that while EEG changes could not predict vigilance in...a function of alertness level. In human adults , two independent laboratories have shown that MLR components Pa (30 to 35 ms) and Nb (40 to 50 ms
Bautista, Pinky A; Yagi, Yukako
2011-01-01
In this paper we introduced a digital staining method for histopathology images captured with an n-band multispectral camera. The method consisted of two major processes: enhancement of the original spectral transmittance and the transformation of the enhanced transmittance to its target spectral configuration. Enhancement is accomplished by shifting the original transmittance with the scaled difference between the original transmittance and the transmittance estimated with m dominant principal component (PC) vectors;the m-PC vectors were determined from the transmittance samples of the background image. Transformation of the enhanced transmittance to the target spectral configuration was done using an nxn transformation matrix, which was derived by applying a least square method to the enhanced and target spectral training data samples of the different tissue components. Experimental results on the digital conversion of a hematoxylin and eosin (H&E) stained multispectral image to its Masson's trichrome stained (MT) equivalent shows the viability of the method.
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.
NASA Astrophysics Data System (ADS)
Bell, J. F.; Fraeman, A. A.; Grossman, L.; Herkenhoff, K. E.; Sullivan, R. J.; Mer/Athena Science Team
2010-12-01
The Mars Exploration Rovers Spirit and Opportunity have enabled more than six and a half years of detailed, in situ field study of two specific landing sites and traverse paths within Gusev crater and Meridiani Planum, respectively. Much of the study has relied on high-resolution, multispectral imaging of fine-grained regolith components--the dust, sand, cobbles, clasts, and other components collectively referred to as "soil"--at both sites using the rovers' Panoramic Camera (Pancam) and Microscopic Imager (MI) imaging systems. As of early September 2010, the Pancam systems have acquired more than 1300 and 1000 "13 filter" multispectral imaging sequences of surfaces in Gusev and Meridiani, respectively, with each sequence consisting of co-located images at 11 unique narrowband wavelengths between 430 nm and 1009 nm and having a maximum spatial resolution of about 500 microns per pixel. The MI systems have acquired more than 5900 and 6500 monochromatic images, respectively, at about 31 microns per pixel scale. Pancam multispectral image cubes are calibrated to radiance factor (I/F, where I is the measured radiance and π*F is the incident solar irradiance) using observations of the onboard calibration targets, and then corrected to relative reflectance (assuming Lambertian photometric behavior) for comparison with laboratory rock and mineral measurements. Specifically, Pancam spectra can be used to detect the possible presence of some iron-bearing minerals (e.g., some ferric oxides/oxyhydroxides and pyroxenes) as well as structural water or OH in some hydrated alteration products, providing important inputs on the choice of targets for more quantitative compositional and mineralogic follow-up using the rover's other in situ and remote sensing analysis tools. Pancam 11-band spectra are being analyzed using a variety of standard as well as specifically-tailored analysis methods, including color ratio and band depth parameterizations, spectral similarity and principal components clustering, and simple visual inspection based on correlations with false color unit boundaries and textural variations seen in both Pancam and MI imaging. Approximately 20 distinct spectral classes of fine-grained surface components were identified at each site based on these methods. In this presentation we describe these spectral classes, their geologic and textural context and distribution based on supporting high-res MI and other Pancam imaging, and their potential compositional/mineralogic interpretations based on a variety of rover data sets.
NASA Astrophysics Data System (ADS)
Kovács, G.
2009-09-01
Current status of (the lack of) understanding Blazhko effect is reviewed. We focus mostly on the various components of the failure of the models and touch upon the observational issues only at a degree needed for the theoretical background. Attention is to be paid to models based on radial mode resonances, since they seem to be not fully explored yet, especially if we consider possible non-standard effects (e.g., heavy element enhancement). To aid further modeling efforts, we stress the need for accurate time-series spectral line analysis to reveal any possible non-radial component(s) and thereby let to include (or exclude) non-radial modes in explaining the Blazhko phenomenon.
Breast tissue decomposition with spectral distortion correction: A postmortem study
Ding, Huanjun; Zhao, Bo; Baturin, Pavlo; Behroozi, Farnaz; Molloi, Sabee
2014-01-01
Purpose: To investigate the feasibility of an accurate measurement of water, lipid, and protein composition of breast tissue using a photon-counting spectral computed tomography (CT) with spectral distortion corrections. Methods: Thirty-eight postmortem breasts were imaged with a cadmium-zinc-telluride-based photon-counting spectral CT system at 100 kV. The energy-resolving capability of the photon-counting detector was used to separate photons into low and high energy bins with a splitting energy of 42 keV. The estimated mean glandular dose for each breast ranged from 1.8 to 2.2 mGy. Two spectral distortion correction techniques were implemented, respectively, on the raw images to correct the nonlinear detector response due to pulse pileup and charge-sharing artifacts. Dual energy decomposition was then used to characterize each breast in terms of water, lipid, and protein content. In the meantime, the breasts were chemically decomposed into their respective water, lipid, and protein components to provide a gold standard for comparison with dual energy decomposition results. Results: The accuracy of the tissue compositional measurement with spectral CT was determined by comparing to the reference standard from chemical analysis. The averaged root-mean-square error in percentage composition was reduced from 15.5% to 2.8% after spectral distortion corrections. Conclusions: The results indicate that spectral CT can be used to quantify the water, lipid, and protein content in breast tissue. The accuracy of the compositional analysis depends on the applied spectral distortion correction technique. PMID:25281953
A framelet-based iterative maximum-likelihood reconstruction algorithm for spectral CT
NASA Astrophysics Data System (ADS)
Wang, Yingmei; Wang, Ge; Mao, Shuwei; Cong, Wenxiang; Ji, Zhilong; Cai, Jian-Feng; Ye, Yangbo
2016-11-01
Standard computed tomography (CT) cannot reproduce spectral information of an object. Hardware solutions include dual-energy CT which scans the object twice in different x-ray energy levels, and energy-discriminative detectors which can separate lower and higher energy levels from a single x-ray scan. In this paper, we propose a software solution and give an iterative algorithm that reconstructs an image with spectral information from just one scan with a standard energy-integrating detector. The spectral information obtained can be used to produce color CT images, spectral curves of the attenuation coefficient μ (r,E) at points inside the object, and photoelectric images, which are all valuable imaging tools in cancerous diagnosis. Our software solution requires no change on hardware of a CT machine. With the Shepp-Logan phantom, we have found that although the photoelectric and Compton components were not perfectly reconstructed, their composite effect was very accurately reconstructed as compared to the ground truth and the dual-energy CT counterpart. This means that our proposed method has an intrinsic benefit in beam hardening correction and metal artifact reduction. The algorithm is based on a nonlinear polychromatic acquisition model for x-ray CT. The key technique is a sparse representation of iterations in a framelet system. Convergence of the algorithm is studied. This is believed to be the first application of framelet imaging tools to a nonlinear inverse problem.
NASA Astrophysics Data System (ADS)
Nandi, Anuj; Mandal, S.; Sreehari, H.; Radhika, D.; Das, Santabrata; Chattopadhyay, I.; Iyer, N.; Agrawal, V. K.; Aktar, R.
2018-05-01
We examine the dynamical behavior of accretion flow around XTE J1859+226 during the 1999 outburst by analyzing the entire outburst data (˜166 days) from RXTE Satellite. Towards this, we study the hysteresis behavior in the hardness intensity diagram (HID) based on the broadband (3-150 keV) spectral modeling, spectral signature of jet ejection and the evolution of Quasi-periodic Oscillation (QPO) frequencies using the two-component advective flow model around a black hole. We compute the flow parameters, namely Keplerian accretion rate (\\dot{m}d), sub-Keplerian accretion rate (\\dot{m}h), shock location (rs) and black hole mass (M_{bh}) from the spectral modeling and study their evolution along the q-diagram. Subsequently, the kinetic jet power is computed as L^{obs}_{jet} ˜3-6 ×10^{37} erg s^{-1} during one of the observed radio flares which indicates that jet power corresponds to 8-16% mass outflow rate from the disc. This estimate of mass outflow rate is in close agreement with the change in total accretion rate (˜14%) required for spectral modeling before and during the flare. Finally, we provide a mass estimate of the source XTE J1859+226 based on the spectral modeling that lies in the range of 5.2-7.9 M_{⊙} with 90% confidence.
Classical least squares multivariate spectral analysis
Haaland, David M.
2002-01-01
An improved classical least squares multivariate spectral analysis method that adds spectral shapes describing non-calibrated components and system effects (other than baseline corrections) present in the analyzed mixture to the prediction phase of the method. These improvements decrease or eliminate many of the restrictions to the CLS-type methods and greatly extend their capabilities, accuracy, and precision. One new application of PACLS includes the ability to accurately predict unknown sample concentrations when new unmodeled spectral components are present in the unknown samples. Other applications of PACLS include the incorporation of spectrometer drift into the quantitative multivariate model and the maintenance of a calibration on a drifting spectrometer. Finally, the ability of PACLS to transfer a multivariate model between spectrometers is demonstrated.
NASA Astrophysics Data System (ADS)
Malinina, A. A.; Malinin, A. N.
2016-09-01
The results of studies of spectral, temporal, and energy characteristics of radiation in a gas discharge plasma based on a mixture of mercury diiodide vapor with helium and nitrogen in the spectral range of 350-800 nm are presented. Plasma was produced by a barrier discharge in a device with a cylindrical aperture. The electrodes 0.2 m in length were placed at a distance of 0.015 m. The amplitude of the pump pulses, their duration, and frequency were equal to 20-30 kV, 150 ns, and 1-20 kHz, respectively. Radiation of mercury monoiodide exciplex molecules was revealed in the visible spectra region. Dependences of the plasma optical characteristics on the partial pressures of the mixture components were established.
Compact and portable multiline UV and visible Raman lasers in hydrogen-filled HC-PCF.
Wang, Y Y; Couny, F; Light, P S; Mangan, B J; Benabid, F
2010-04-15
We report on the realization of compact UV visible multiline Raman lasers based on two types of hydrogen-filled hollow-core photonic crystal fiber. The first, with a large pitch Kagome lattice structure, offers a broad spectral coverage from near IR through to the much sought after yellow, deep-blue and UV, whereas the other, based on photonic bandgap guidance, presents a pump conversion concentrated in the visible region. The high Raman efficiency achieved through these fibers allows for compact, portable diode-pumped solid-state lasers to be used as pumps. Each discrete component of this laser system exhibits a spectral density several orders of magnitude larger than what is achieved with supercontinuum sources and a narrow linewidth, making it an ideal candidate for forensics and biomedical applications.
NASA Astrophysics Data System (ADS)
Zakhozhay, O. V.
2017-07-01
We study spectral energy distributions of two young systems Sz54 and Sz59, that belong to Chameleon II star forming region. The results of the modeling indicate that protoplanetary disks of these systems contain gaps in the dust component. These gaps could be a result of a planetary or brown dwarf companion formation, because the companion would accumulate a disk material, moving along its orbit. In a present work we have determined physical characteristics of the disks. We also discuss possible companion characteristics, based on the geometrical parameters of the gaps.
Functionalized xenon as a biosensor
Spence, Megan M.; Rubin, Seth M.; Dimitrov, Ivan E.; Ruiz, E. Janette; Wemmer, David E.; Pines, Alexander; Yao, Shao Qin; Tian, Feng; Schultz, Peter G.
2001-01-01
The detection of biological molecules and their interactions is a significant component of modern biomedical research. In current biosensor technologies, simultaneous detection is limited to a small number of analytes by the spectral overlap of their signals. We have developed an NMR-based xenon biosensor that capitalizes on the enhanced signal-to-noise, spectral simplicity, and chemical-shift sensitivity of laser-polarized xenon to detect specific biomolecules at the level of tens of nanomoles. We present results using xenon “functionalized” by a biotin-modified supramolecular cage to detect biotin–avidin binding. This biosensor methodology can be extended to a multiplexing assay for multiple analytes. PMID:11535830
NASA Astrophysics Data System (ADS)
Roy, Ankita
2007-12-01
This research using Hyperspectral imaging involves recognizing targets through spatial and spectral matching and spectral un-mixing of data ranging from remote sensing to medical imaging kernels for clinical studies based on Hyperspectral data-sets generated using the VFTHSI [Visible Fourier Transform Hyperspectral Imager], whose high resolution Si detector makes the analysis achievable. The research may be broadly classified into (I) A Physically Motivated Correlation Formalism (PMCF), which places both spatial and spectral data on an equivalent mathematical footing in the context of a specific Kernel and (II) An application in RF plasma specie detection during carbon nanotube growing process. (III) Hyperspectral analysis for assessing density and distribution of retinopathies like age related macular degeneration (ARMD) and error estimation enabling the early recognition of ARMD, which is treated as an ill-conditioned inverse imaging problem. The broad statistical scopes of this research are two fold-target recognition problems and spectral unmixing problems. All processes involve experimental and computational analysis of Hyperspectral data sets is presented, which is based on the principle of a Sagnac Interferometer, calibrated to obtain high SNR levels. PMCF computes spectral/spatial/cross moments and answers the question of how optimally the entire hypercube should be sampled and finds how many spatial-spectral pixels are required precisely for a particular target recognition. Spectral analysis of RF plasma radicals, typically Methane plasma and Argon plasma using VFTHSI has enabled better process monitoring during growth of vertically aligned multi-walled carbon nanotubes by instant registration of the chemical composition or density changes temporally, which is key since a significant correlation can be found between plasma state and structural properties. A vital focus of this dissertation is towards medical Hyperspectral imaging applied to retinopathies like age related macular degeneration targets taken with a Fundus imager, which is akin to the VFTHSI. Detection of the constituent components in the diseased hyper-pigmentation area is also computed. The target or reflectance matrix is treated as a highly ill-conditioned spectral un-mixing problem, to which methodologies like inverse techniques, principal component analysis (PCA) and receiver operating curves (ROC) for precise spectral recognition of infected area. The region containing ARMD was easily distinguishable from the spectral mesh plots over the entire band-pass area. Once the location was detected the PMCF coefficients were calculated by cross correlating a target of normal oxygenated retina with the deoxygenated one. The ROCs generated using PMCF shows 30% higher detection probability with improved accuracy than ROCs based on Spectral Angle Mapper (SAM). By spectral unmixing methods, the important endmembers/carotenoids of the MD pigment were found to be Xanthophyl and lutein, while beta-carotene which showed a negative correlation in the unconstrained inverse problem is a supplement given to ARMD patients to prevent the disease and does not occur in the eye. Literature also shows degeneration of meso-zeaxanthin. Ophthalmologists may assert the presence of ARMD and commence the diagnosis process if the Xanthophyl pigment have degenerated 89.9%, while the lutein has decayed almost 80%, as found deduced computationally. This piece of current research takes it to the next level of precise investigation in the continuing process of improved clinical findings by correlating the microanatomy of the diseased fovea and shows promise of an early detection of this disease.
Saturation-resolved-fluorescence spectroscopy of Cr3+:mullite glass ceramic
NASA Astrophysics Data System (ADS)
Liu, Huimin; Knutson, Robert; Yen, W. M.
1990-01-01
We present a saturation-based technique designed to isolate and uncouple individual components of inhomogeneously broadened spectra that are simultaneously coupled to each other through spectral overlap and energy-transfer interactions. We have termed the technique saturation-resolved-fluorescence spectroscopy; we demonstrate its usefulness in deconvoluting the complex spectra of Cr3+:mullite glass ceramic.
Invasive species detection in Hawaiian rainforests using airborne imaging spectroscopy and LiDAR
Gregory P. Asner; David E. Knapp; Ty Kennedy-Bodoin; Matthew O. Jones; Roberta E. Martin; Joseph Boardman; Flint Hughes
2008-01-01
Remote sensing of invasive species is a critical component of conservation and management efforts, but reliable methods for the detection of invaders have not been widely established. In Hawaiian forests, we recently found that invasive trees often have hyperspectral signatures unique from that of native trees, but mapping based on spectral reflectance properties alone...
Infrared Spectral Signatures for Io's Dark and Green Spots
NASA Technical Reports Server (NTRS)
Granahan, J. C.; Fanale, F. P.; Carlson, R.; Smythe, W. D.
2001-01-01
This spectral study of Io identifies the infrared components of the visible spectral units (green and dark) as identified by Galileo. The green units possess sulfur dioxide and the dark units are associated with infrared thermal signatures. Additional information is contained in the original extended abstract.
Spatial-spectral characterization of focused spatially chirped broadband laser beams.
Greco, Michael J; Block, Erica; Meier, Amanda K; Beaman, Alex; Cooper, Samuel; Iliev, Marin; Squier, Jeff A; Durfee, Charles G
2015-11-20
Proper alignment is critical to obtain the desired performance from focused spatially chirped beams, for example in simultaneous spatial and temporal focusing (SSTF). We present a simple technique for inspecting the beam paths and focusing conditions for the spectral components of a broadband beam. We spectrally resolve the light transmitted past a knife edge as it was scanned across the beam at several axial positions. The measurement yields information about spot size, M2, and the propagation paths of different frequency components. We also present calculations to illustrate the effects of defocus aberration on SSTF beams.
Desova, A A; Dorofeyuk, A A; Anokhin, A M
2017-01-01
We performed a comparative analysis of the types of spectral density typical of various parameters of pulse signal. The experimental material was obtained during the examination of school age children with various psychosomatic disorders. We also performed a typological analysis of the spectral density functions corresponding to the time series of different parameters of a single oscillation of pulse signals; the results of their comparative analysis are presented. We determined the most significant spectral components for two disordersin children: arterial hypertension and mitral valve prolapse.
NASA Astrophysics Data System (ADS)
Martín-Luis, Antonio; Arbelo, Manuel; Hernández-Leal, Pedro; Arbelo-Bayó, Manuel
2016-10-01
Reliable and updated maps of vegetation in protected natural areas are essential for a proper management and conservation. Remote sensing is a valid tool for this purpose. In this study, a methodology based on a WorldView-2 (WV-2) satellite image and in situ spectral signatures measurements was applied to map the Canarian Monteverde ecosystem located in the north of the Tenerife Island (Canary Islands, Spain). Due to the high spectral similarity of vegetation species in the study zone, a Multiple Endmember Spectral Mixture Analysis (MESMA) was performed. MESMA determines the fractional cover of different components within one pixel and it allows for a pixel-by-pixel variation of endmembers. Two libraries of endmembers were collected for the most abundant species in the test area. The first library was collected from in situ spectral signatures measured with an ASD spectroradiometer during a field campaign in June 2015. The second library was obtained from pure pixels identified in the satellite image for the same species. The accuracy of the mapping process was assessed from a set of independent validation plots. The overall accuracy for the ASD-based method was 60.51 % compared to the 86.67 % reached for the WV-2 based mapping. The results suggest the possibility of using WV-2 images for monitoring and regularly updating the maps of the Monteverde forest on the island of Tenerife.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dean, A.P.; Martin, Michael C.; Sigee, D.C.
2006-10-09
Synchrotron-based Fourier-transform infrared (FTIR)microspectroscopy was used to distinguish micropopulations of thecodominant algae Microcystis aeruginosa (Cyanophyceae) and Ceratiumhirundinella (Dinophyceae) in mixed phytoplankton samples taken from thewater column of a stratified eutrophic lake (Rostherne Mere, UK). FTIRspectra of the two algae showed a closely similar sequence of 10 bandsover the wave-number range 4000-900 cm-1. These were assigned to a rangeof vibrationally active chemical groups using published band assignmentsand on the basis of correlation and factor analysis. In both algae,intracellular concentrations of macromolecular components (determined asband intensity) varied considerably within the same population,indicating substantial intraspecific heterogeneity. Interspecificdifferences were separately analysed in relation tomore » discrete bands and bymultivariate analysis of the entire spectral region 1750-900 cm-1. Interms of discrete bands, comparison of individual intensities (normalisedto amide 1) demonstrated significant (99 percent probability level)differences in relation to six bands between the two algal species. Keyinterspecific differences were also noted in relation to the positions ofbands 2, 10 (carbohydrate) and 7 (protein) and in the 3-D plots derivedby principal component analysis (PCA) of the sequence of bandintensities. PCA of entire spectral regions showed clear resolutionofspecies in the PCA plot, with indication of separation on the basis ofprotein (region 1700-1500 cm1) and carbohydrate (region 1150-900 cm1)composition in the loading plot. Hierarchical cluster analysis (Wardalgorithm) of entire spectral regions also showed clear discrimination ofthe two species within the resulting dendrogram.« less
Target detection using the background model from the topological anomaly detection algorithm
NASA Astrophysics Data System (ADS)
Dorado Munoz, Leidy P.; Messinger, David W.; Ziemann, Amanda K.
2013-05-01
The Topological Anomaly Detection (TAD) algorithm has been used as an anomaly detector in hyperspectral and multispectral images. TAD is an algorithm based on graph theory that constructs a topological model of the background in a scene, and computes an anomalousness ranking for all of the pixels in the image with respect to the background in order to identify pixels with uncommon or strange spectral signatures. The pixels that are modeled as background are clustered into groups or connected components, which could be representative of spectral signatures of materials present in the background. Therefore, the idea of using the background components given by TAD in target detection is explored in this paper. In this way, these connected components are characterized in three different approaches, where the mean signature and endmembers for each component are calculated and used as background basis vectors in Orthogonal Subspace Projection (OSP) and Adaptive Subspace Detector (ASD). Likewise, the covariance matrix of those connected components is estimated and used in detectors: Constrained Energy Minimization (CEM) and Adaptive Coherence Estimator (ACE). The performance of these approaches and the different detectors is compared with a global approach, where the background characterization is derived directly from the image. Experiments and results using self-test data set provided as part of the RIT blind test target detection project are shown.
USDA-ARS?s Scientific Manuscript database
Six methods were compared with respect to spectral fingerprinting of a well-characterized series of broccoli samples. Spectral fingerprints were acquired for finely-powdered solid samples using Fourier transform-infrared (IR) and Fourier transform-near infrared (NIR) spectrometry and for aqueous met...
Determination of seasonals using wavelets in terms of noise parameters changeability
NASA Astrophysics Data System (ADS)
Klos, Anna; Bogusz, Janusz; Figurski, Mariusz
2015-04-01
The reliable velocities of GNSS-derived observations are becoming of high importance nowadays. The fact on how we determine and subtract the seasonals may all cause the time series autocorrelation and affect uncertainties of linear parameters. The periodic changes in GNSS time series are commonly assumed as the sum of annual and semi-annual changes with amplitudes and phases being constant in time and the Least-Squares Estimation (LSE) is used in general to model these sine waves. However, not only seasonals' time-changeability, but also their higher harmonics should be considered. In this research, we focused on more than 230 globally distributed IGS stations that were processed at the Military University of Technology EPN Local Analysis Centre (MUT LAC) in Bernese 5.0 software. The network was divided into 7 different sub-networks with few of overlapping stations and processed separately with newest models. Here, we propose a wavelet-based trend and seasonals determination and removal of whole frequency spectrum between Chandler and quarter-annual periods from North, East and Up components and compare it with LSE-determined values. We used a Meyer symmetric, orthogonal wavelet and assumed nine levels of decomposition. The details from 6 up to 9 were analyzed here as periodic components with frequencies between 0.3-2.5 cpy. The characteristic oscillations for each of frequency band were pointed out. The details lower than 6 summed together with detrended approximation were considered as residua. The power spectral densities (PSDs) of original and decomposed data were stacked for North, East and Up components for each of sub-networks so as to show what power was removed with each of decomposition levels. Moreover, the noises that the certain frequency band follows (in terms of spectral indices of power-law dependencies) were estimated here using a spectral method and compared for all processed sub-networks. It seems, that lowest frequencies up to 0.7 cpy are characterized by lower spectral indices in comparison to higher ones being close to white noise. Basing on the fact, that decomposition levels overlap each other, the frequency-window choice becomes a main point in spectral index estimation. Our results were compared with those obtained by Maximum Likelihood Estimation (MLE) and possible differences as well as their impact on velocity uncertainties pointed out. The results show that the spectral indices estimated in time and frequency domains differ of 0.15 in maximum. Moreover, we compared the removed power basing on wavelet decomposition levels with the one subtracted with LSE, assuming the same periodicities. In comparison to LSE, the wavelet-based approach leaves the residua being closer to white noise with lower power-law amplitudes of them, what strictly reduces velocity uncertainties. The last approximation was analyzed here as long-term trend, being the non-linear and compared with LSE-determined linear one. It seems that these two trends differ at the level of 0.3 mm/yr in the most extreme case, what makes wavelet decomposition being useful for velocity determination.
Adventitious sounds identification and extraction using temporal-spectral dominance-based features.
Jin, Feng; Krishnan, Sridhar Sri; Sattar, Farook
2011-11-01
Respiratory sound (RS) signals carry significant information about the underlying functioning of the pulmonary system by the presence of adventitious sounds (ASs). Although many studies have addressed the problem of pathological RS classification, only a limited number of scientific works have focused on the analysis of the evolution of symptom-related signal components in joint time-frequency (TF) plane. This paper proposes a new signal identification and extraction method for various ASs based on instantaneous frequency (IF) analysis. The presented TF decomposition method produces a noise-resistant high definition TF representation of RS signals as compared to the conventional linear TF analysis methods, yet preserving the low computational complexity as compared to those quadratic TF analysis methods. The discarded phase information in conventional spectrogram has been adopted for the estimation of IF and group delay, and a temporal-spectral dominance spectrogram has subsequently been constructed by investigating the TF spreads of the computed time-corrected IF components. The proposed dominance measure enables the extraction of signal components correspond to ASs from noisy RS signal at high noise level. A new set of TF features has also been proposed to quantify the shapes of the obtained TF contours, and therefore strongly, enhances the identification of multicomponents signals such as polyphonic wheezes. An overall accuracy of 92.4±2.9% for the classification of real RS recordings shows the promising performance of the presented method.
NASA Astrophysics Data System (ADS)
Aparanji, Santosh; Balaswamy, V.; Arun, S.; Supradeepa, V. R.
2018-02-01
In this work, we report and analyse the surprising observation of a rainbow of visible colors, spanning 390nm to 620nm, in silica-based, Near Infrared, continuous-wave, cascaded Raman fiber lasers. The cascaded Raman laser is pumped at 1117nm at around 200W and at full power we obtain 100 W at 1480nm. With increasing pump power at 1117nm, the fiber constituting the Raman laser glows in various hues along its length. From spectroscopic analysis of the emitted visible light, it was identified to be harmonic and sum-frequency components of various locally propagating wavelength components. In addition to third harmonic components, surprisingly, even 2nd harmonic components were observed. Despite being a continuous-wave laser, we expect the phase-matching occurring between the core-propagating NIR light with the cladding-propagating visible wavelengths and the intensity fluctuations characteristic of Raman lasers to have played a major role in generation of visible light. In addition, this surprising generation of visible light provides us a powerful non-contact method to deduce the spectrum of light propagating in the fiber. Using static images of the fiber captured by a standard visible camera such as a DSLR, we demonstrate novel, image-processing based techniques to deduce the wavelength component propagating in the fiber at any given spatial location. This provides a powerful diagnostic tool for both length and power resolved spectral analysis in Raman fiber lasers. This helps accurate prediction of the optimal length of fiber required for complete and efficient conversion to a given Stokes wavelength.
Site response and attenuation in the Puget Lowland, Washington State
Pratt, T.L.; Brocher, T.M.
2006-01-01
Simple spectral ratio (SSR) and horizontal-to-vertical (HN) site-response estimates at 47 sites in the Puget Lowland of Washington State document significant attenuation of 1.5- to 20-Hz shear waves within sedimentary basins there. Amplitudes of the horizontal components of shear-wave arrivals from three local earthquakes were used to compute SSRs with respect to the average of two bedrock sites and H/V spectral ratios with respect to the vertical component of the shear-wave arrivals at each site. SSR site-response curves at thick basin sites show peak amplifications of 2 to 6 at frequencies of 3 to 6 Hz, and decreasing spectra amplification with increasing frequency above 6 Hz. SSRs at nonbasin sites show a variety of shapes and larger resonance peaks. We attribute the spectral decay at frequencies above the amplification peak at basin sites to attenuation within the basin strata. Computing the frequency-independent, depth-dependent attenuation factor (Qs,int) from the SSR spectral decay between 2 and 20 Hz gives values of 5 to 40 for shallow sedimentary deposits and about 250 for the deepest sedimentary strata (7 km depth). H/V site responses show less spectral decay than the SSR responses but contain many of the same resonance peaks. We hypothesize that the H/V method yields a flatter response across the frequency spectrum than SSRs because the H/V reference signal (vertical component of the shear-wave arrivals) has undergone a degree of attenuation similar to the horizontal component recordings. Correcting the SSR site responses for attenuation within the basins by removing the spectral decay improves agreement between SSR and H/V estimates.
NASA Astrophysics Data System (ADS)
Ma, Long; Zhao, Deping
2011-12-01
Spectral imaging technology have been used mostly in remote sensing, but have recently been extended to new area requiring high fidelity color reproductions like telemedicine, e-commerce, etc. These spectral imaging systems are important because they offer improved color reproduction quality not only for a standard observer under a particular illuminantion, but for any other individual exhibiting normal color vision capability under another illuminantion. A possibility for browsing of the archives is needed. In this paper, the authors present a new spectral image browsing architecture. The architecture for browsing is expressed as follow: (1) The spectral domain of the spectral image is reduced with the PCA transform. As a result of the PCA transform the eigenvectors and the eigenimages are obtained. (2) We quantize the eigenimages with the original bit depth of spectral image (e.g. if spectral image is originally 8bit, then quantize eigenimage to 8bit), and use 32bit floating numbers for the eigenvectors. (3) The first eigenimage is lossless compressed by JPEG-LS, the other eigenimages were lossy compressed by wavelet based SPIHT algorithm. For experimental evalution, the following measures were used. We used PSNR as the measurement for spectral accuracy. And for the evaluation of color reproducibility, ΔE was used.here standard D65 was used as a light source. To test the proposed method, we used FOREST and CORAL spectral image databases contrain 12 and 10 spectral images, respectively. The images were acquired in the range of 403-696nm. The size of the images were 128*128, the number of bands was 40 and the resolution was 8 bits per sample. Our experiments show the proposed compression method is suitable for browsing, i.e., for visual purpose.
NASA Astrophysics Data System (ADS)
Jardin, A.; Mazon, D.; Malard, P.; O'Mullane, M.; Chernyshova, M.; Czarski, T.; Malinowski, K.; Kasprowicz, G.; Wojenski, A.; Pozniak, K.
2017-08-01
The tokamak WEST aims at testing ITER divertor high heat flux component technology in long pulse operation. Unfortunately, heavy impurities like tungsten (W) sputtered from the plasma facing components can pollute the plasma core by radiation cooling in the soft x-ray (SXR) range, which is detrimental for the energy confinement and plasma stability. SXR diagnostics give valuable information to monitor impurities and study their transport. The WEST SXR diagnostic is composed of two new cameras based on the Gas Electron Multiplier (GEM) technology. The WEST GEM cameras will be used for impurity transport studies by performing 2D tomographic reconstructions with spectral resolution in tunable energy bands. In this paper, we characterize the GEM spectral response and investigate W density reconstruction thanks to a synthetic diagnostic recently developed and coupled with a tomography algorithm based on the minimum Fisher information (MFI) inversion method. The synthetic diagnostic includes the SXR source from a given plasma scenario, the photoionization, electron cloud transport and avalanche in the detection volume using Magboltz, and tomographic reconstruction of the radiation from the GEM signal. Preliminary studies of the effect of transport on the W ionization equilibrium and on the reconstruction capabilities are also presented.
NASA Astrophysics Data System (ADS)
Hegazy, Maha Abdel Monem; Fayez, Yasmin Mohammed
2015-04-01
Two different methods manipulating spectrophotometric data have been developed, validated and compared. One is capable of removing the signal of any interfering components at the selected wavelength of the component of interest (univariate). The other includes more variables and extracts maximum information to determine the component of interest in the presence of other components (multivariate). The applied methods are smart, simple, accurate, sensitive, precise and capable of determination of spectrally overlapped antihypertensives; hydrochlorothiazide (HCT), irbesartan (IRB) and candesartan (CAN). Mean centering of ratio spectra (MCR) and concentration residual augmented classical least-squares method (CRACLS) were developed and their efficiency was compared. CRACLS is a simple method that is capable of extracting the pure spectral profiles of each component in a mixture. Correlation was calculated between the estimated and pure spectra and was found to be 0.9998, 0.9987 and 0.9992 for HCT, IRB and CAN, respectively. The methods were successfully determined the three components in bulk powder, laboratory-prepared mixtures, and combined dosage forms. The results obtained were compared statistically with each other and to those of the official methods.
GIFTS SM EDU Data Processing and Algorithms
NASA Technical Reports Server (NTRS)
Tian, Jialin; Johnson, David G.; Reisse, Robert A.; Gazarik, Michael J.
2007-01-01
The Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS) Sensor Module (SM) Engineering Demonstration Unit (EDU) is a high resolution spectral imager designed to measure infrared (IR) radiances using a Fourier transform spectrometer (FTS). The GIFTS instrument employs three Focal Plane Arrays (FPAs), which gather measurements across the long-wave IR (LWIR), short/mid-wave IR (SMWIR), and visible spectral bands. The raw interferogram measurements are radiometrically and spectrally calibrated to produce radiance spectra, which are further processed to obtain atmospheric profiles via retrieval algorithms. This paper describes the processing algorithms involved in the calibration stage. The calibration procedures can be subdivided into three stages. In the pre-calibration stage, a phase correction algorithm is applied to the decimated and filtered complex interferogram. The resulting imaginary part of the spectrum contains only the noise component of the uncorrected spectrum. Additional random noise reduction can be accomplished by applying a spectral smoothing routine to the phase-corrected blackbody reference spectra. In the radiometric calibration stage, we first compute the spectral responsivity based on the previous results, from which, the calibrated ambient blackbody (ABB), hot blackbody (HBB), and scene spectra can be obtained. During the post-processing stage, we estimate the noise equivalent spectral radiance (NESR) from the calibrated ABB and HBB spectra. We then implement a correction scheme that compensates for the effect of fore-optics offsets. Finally, for off-axis pixels, the FPA off-axis effects correction is performed. To estimate the performance of the entire FPA, we developed an efficient method of generating pixel performance assessments. In addition, a random pixel selection scheme is designed based on the pixel performance evaluation.
NASA Astrophysics Data System (ADS)
Usenik, Peter; Bürmen, Miran; Vrtovec, Tomaž; Fidler, Aleš; Pernuš, Franjo; Likar, Boštjan
2011-03-01
Despite major improvements in dental healthcare and technology, dental caries remains one of the most prevalent chronic diseases of modern society. The initial stages of dental caries are characterized by demineralization of enamel crystals, commonly known as white spots which are difficult to diagnose. If detected early enough, such demineralization can be arrested and reversed by non-surgical means through well established dental treatments (fluoride therapy, anti-bacterial therapy, low intensity laser irradiation). Near-infrared (NIR) hyper-spectral imaging is a new promising technique for early detection of demineralization based on distinct spectral features of healthy and pathological dental tissues. In this study, we apply NIR hyper-spectral imaging to classify and visualize healthy and pathological dental tissues including enamel, dentin, calculus, dentin caries, enamel caries and demineralized areas. For this purpose, a standardized teeth database was constructed consisting of 12 extracted human teeth with different degrees of natural dental lesions imaged by NIR hyper-spectral system, X-ray and digital color camera. The color and X-ray images of teeth were presented to a clinical expert for localization and classification of the dental tissues, thereby obtaining the gold standard. Principal component analysis was used for multivariate local modeling of healthy and pathological dental tissues. Finally, the dental tissues were classified by employing multiple discriminant analysis. High agreement was observed between the resulting classification and the gold standard with the classification sensitivity and specificity exceeding 85 % and 97 %, respectively. This study demonstrates that NIR hyper-spectral imaging has considerable diagnostic potential for imaging hard dental tissues.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Shilyagin, P A; Gelikonov, G V; Gelikonov, V M
2014-07-31
We have thoroughly investigated the method of simultaneous reception of spectral components with the achromatised quadrature phase shift between two portions of a reference wave, designed for the effective suppression of the 'mirror' artefact in the resulting image obtained by means of spectral domain optical coherence tomography (SD OCT). We have developed and experimentally tested a phase-shifting element consisting of a beam divider, which splits the reference optical beam into the two beams, and of delay lines being individual for each beam, which create a mutual phase difference of π/2 in the double pass of the reference beam. The phasemore » shift achromatism over a wide spectral range is achieved by using in the delay lines the individual elements with different dispersion characteristics. The ranges of admissible adjustment parameters of the achromatised delay line are estimated for exact and inexact conformity of the geometric characteristics of its components to those calculated. A possibility of simultaneous recording of the close-to-quadrature spectral components with a single linear photodetector element is experimentally confirmed. The suppression of the artefact mirror peak in the OCT-signal by an additional 9 dB relative to the level of its suppression is experimentally achieved when the air delay line is used. Two-dimensional images of the surface positioned at an angle to the axis of the probe beam are obtained with the correction of the 'mirror' artefact while maintaining the dynamic range of the image. (laser biophotonics)« less
Ferrero, Alejandro; Rabal, Ana María; Campos, Joaquín; Pons, Alicia; Hernanz, María Luisa
2012-12-20
A study on the variation of the spectral bidirectional reflectance distribution function (BRDF) of four diffuse reflectance standards (matte ceramic, BaSO(4), Spectralon, and white Russian opal glass) is accomplished through this work. Spectral BRDF measurements were carried out and, using principal components analysis, its spectral and geometrical variation respect to a reference geometry was assessed from the experimental data. Several descriptors were defined in order to compare the spectral BRDF variation of the four materials.
An algorithm for extraction of periodic signals from sparse, irregularly sampled data
NASA Technical Reports Server (NTRS)
Wilcox, J. Z.
1994-01-01
Temporal gaps in discrete sampling sequences produce spurious Fourier components at the intermodulation frequencies of an oscillatory signal and the temporal gaps, thus significantly complicating spectral analysis of such sparsely sampled data. A new fast Fourier transform (FFT)-based algorithm has been developed, suitable for spectral analysis of sparsely sampled data with a relatively small number of oscillatory components buried in background noise. The algorithm's principal idea has its origin in the so-called 'clean' algorithm used to sharpen images of scenes corrupted by atmospheric and sensor aperture effects. It identifies as the signal's 'true' frequency that oscillatory component which, when passed through the same sampling sequence as the original data, produces a Fourier image that is the best match to the original Fourier space. The algorithm has generally met with succession trials with simulated data with a low signal-to-noise ratio, including those of a type similar to hourly residuals for Earth orientation parameters extracted from VLBI data. For eight oscillatory components in the diurnal and semidiurnal bands, all components with an amplitude-noise ratio greater than 0.2 were successfully extracted for all sequences and duty cycles (greater than 0.1) tested; the amplitude-noise ratios of the extracted signals were as low as 0.05 for high duty cycles and long sampling sequences. When, in addition to these high frequencies, strong low-frequency components are present in the data, the low-frequency components are generally eliminated first, by employing a version of the algorithm that searches for non-integer multiples of the discrete FET minimum frequency.
Going Deeper With Contextual CNN for Hyperspectral Image Classification.
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.
Diagnosis of Breast Cancer Based on FT-IR Spectroscopy
NASA Astrophysics Data System (ADS)
Venkatachalam, P.; Rao, L. Lakshmana; Kumar, N. Krishna; Jose, Anupama; Nazeer, Shaiju S.
2008-11-01
Breast cancer is one of the most important malignant forms of cancer and a great threat to life for women. In the present study, the spectral characteristics of human breast tissues in normal and cancerous state have been investigated by Fourier transform infrared (FT-IR) absorption spectroscopy in the spectral region from 4000 to 400 cm-1. Several spectral differences were detected in the frequency regions N-H stretching, C-H vibrations, amide bands and 900-1300 cm-1. The ratio of intensities of the bands of A3300/A3015 & A1650/A1550, A2924/A2853, A1080/A1236, A1204/A1650, A1055/A1467 and A1045/A1467 provide conformational changes of protein, lipids, nucleic acids, collagen, carbohydrates and glycogen respectively in the human breast tissues. There are obvious differences in the spectral features between normal and cancerous tissues because of changes in molecular compositions and structures that accompany the transformation from a normal to a cancerous state. The differences suggest that the spectral information are useful for the diagnosis of breast cancer and may serve as a basis for conformational changes in tissue components during carcinogenesis.
NASA Astrophysics Data System (ADS)
Nielsen, Krister E.; Carpenter, Ken G.; Kober, Gladys V.; Rau, Gioia
2018-01-01
The HST/STIS treasury program ASTRAL enables investigations of the character and dynamics of the wind and chromosphere of cool stars, using high quality spectral data. This paper shows how the wind features change with spectral class by comparing the non-coronal objects (Alpha Ori, Gamma Cru) with the hybrid stars (Gamma Dra, Beta Gem). In particular we study the intrinsic strength variation of the numerous FeII profiles observed in the near-ultraviolet HST spectrum that are sensitive to the wind opacity, turbulence and flow velocity. The FeII relative emission strength and wavelengths shifts between the absorption and emission components reflects the acceleration of the wind from the base of the chromosphere. We present the analysis of the outflowing wind characteristics when transitioning from the cool non-coronal objects toward the warmer objects with chromospheric emission from significantly hotter environments.
NASA Astrophysics Data System (ADS)
Vaishali, S.; Narendranath, S.; Sreekumar, P.
An IDL (interactive data language) based widget application developed for the calibration of C1XS (Narendranath et al., 2010) instrument on Chandrayaan-1 is modified to provide a generic package for the analysis of data from x-ray detectors. The package supports files in ascii as well as FITS format. Data can be fitted with a list of inbuilt functions to derive the spectral redistribution function (SRF). We have incorporated functions such as `HYPERMET' (Philips & Marlow 1976) including non Gaussian components in the SRF such as low energy tail, low energy shelf and escape peak. In addition users can incorporate additional models which may be required to model detector specific features. Spectral fits use a routine `mpfit' which uses Leven-Marquardt least squares fitting method. The SRF derived from this tool can be fed into an accompanying program to generate a redistribution matrix file (RMF) compatible with the X-ray spectral analysis package XSPEC. The tool provides a user friendly interface of help to beginners and also provides transparency and advanced features for experts.
Peak picking NMR spectral data using non-negative matrix factorization.
Tikole, Suhas; Jaravine, Victor; Rogov, Vladimir; Dötsch, Volker; Güntert, Peter
2014-02-11
Simple peak-picking algorithms, such as those based on lineshape fitting, perform well when peaks are completely resolved in multidimensional NMR spectra, but often produce wrong intensities and frequencies for overlapping peak clusters. For example, NOESY-type spectra have considerable overlaps leading to significant peak-picking intensity errors, which can result in erroneous structural restraints. Precise frequencies are critical for unambiguous resonance assignments. To alleviate this problem, a more sophisticated peaks decomposition algorithm, based on non-negative matrix factorization (NMF), was developed. We produce peak shapes from Fourier-transformed NMR spectra. Apart from its main goal of deriving components from spectra and producing peak lists automatically, the NMF approach can also be applied if the positions of some peaks are known a priori, e.g. from consistently referenced spectral dimensions of other experiments. Application of the NMF algorithm to a three-dimensional peak list of the 23 kDa bi-domain section of the RcsD protein (RcsD-ABL-HPt, residues 688-890) as well as to synthetic HSQC data shows that peaks can be picked accurately also in spectral regions with strong overlap.
Masè, Michela; Cristoforetti, Alessandro; Avogaro, Laura; Tessarolo, Francesco; Piccoli, Federico; Caola, Iole; Pederzolli, Carlo; Graffigna, Angelo; Ravelli, Flavia
2015-01-01
The assessment of collagen structure in cardiac pathology, such as atrial fibrillation (AF), is essential for a complete understanding of the disease. This paper introduces a novel methodology for the quantitative description of collagen network properties, based on the combination of nonlinear optical microscopy with a spectral approach of image processing and analysis. Second-harmonic generation (SHG) microscopy was applied to atrial tissue samples from cardiac surgery patients, providing label-free, selective visualization of the collagen structure. The spectral analysis framework, based on 2D-FFT, was applied to the SHG images, yielding a multiparametric description of collagen fiber orientation (angle and anisotropy indexes) and texture scale (dominant wavelength and peak dispersion indexes). The proof-of-concept application of the methodology showed the capability of our approach to detect and quantify differences in the structural properties of the collagen network in AF versus sinus rhythm patients. These results suggest the potential of our approach in the assessment of collagen properties in cardiac pathologies related to a fibrotic structural component.
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.
Temporal expectation and spectral expectation operate in distinct fashion on neuronal populations.
Hsu, Yi-Fang; Hämäläinen, Jarmo A; Waszak, Florian
2013-11-01
The formation of temporal expectation (i.e., the prediction of "when") is of prime importance to sensory processing. It can modulate sensory processing at early processing stages probably via the entrainment of low-frequency neuronal oscillations in the brain. However, sensory predictions involve not only temporal expectation but also spectral expectation (i.e., the prediction of "what"). Here we investigated how temporal expectation may interrelate with spectral expectation by explicitly setting up temporal expectation and spectral expectation in a target detection task. We found that reaction time (RT) was shorter when targets were temporally expected than when they were temporally unexpected. The temporal expectation effect was larger with than without spectral expectation. However, this interaction in the behavioural data did not result from an interaction in the electroencephalography (EEG), where we observed independent main effects of temporal expectation and spectral expectation. More precisely, we found that the N1 and P2 event-related potential (ERP) components and the entrainment of low-frequency neuronal oscillations were exclusively modulated by temporal expectation, whilst only the P3 ERP component was modulated by spectral expectation. Our results, thus, support the idea that temporal expectation and spectral expectation operate in distinct fashion on neuronal populations. © 2013 Elsevier Ltd. All rights reserved.
QCL-based standoff and proximal chemical detectors
NASA Astrophysics Data System (ADS)
Dupuis, Julia R.; Hensley, Joel; Cosofret, Bogdan R.; Konno, Daisei; Mulhall, Phillip; Schmit, Thomas; Chang, Shing; Allen, Mark; Marinelli, William J.
2016-05-01
The development of two longwave infrared quantum cascade laser (QCL) based surface contaminant detection platforms supporting government programs will be discussed. The detection platforms utilize reflectance spectroscopy with application to optically thick and thin materials including solid and liquid phase chemical warfare agents, toxic industrial chemicals and materials, and explosives. Operation at standoff (10s of m) and proximal (1 m) ranges will be reviewed with consideration given to the spectral signatures contained in the specular and diffusely reflected components of the signal. The platforms comprise two variants: Variant 1 employs a spectrally tunable QCL source with a broadband imaging detector, and Variant 2 employs an ensemble of broadband QCLs with a spectrally selective detector. Each variant employs a version of the Adaptive Cosine Estimator for detection and discrimination in high clutter environments. Detection limits of 5 μg/cm2 have been achieved through speckle reduction methods enabling detector noise limited performance. Design considerations for QCL-based standoff and proximal surface contaminant detectors are discussed with specific emphasis on speckle-mitigated and detector noise limited performance sufficient for accurate detection and discrimination regardless of the surface coverage morphology or underlying surface reflectivity. Prototype sensors and developmental test results will be reviewed for a range of application scenarios. Future development and transition plans for the QCL-based surface detector platforms are discussed.
Sensing systems using chip-based spectrometers
NASA Astrophysics Data System (ADS)
Nitkowski, Arthur; Preston, Kyle J.; Sherwood-Droz, Nicolás.; Behr, Bradford B.; Bismilla, Yusuf; Cenko, Andrew T.; DesRoches, Brandon; Meade, Jeffrey T.; Munro, Elizabeth A.; Slaa, Jared; Schmidt, Bradley S.; Hajian, Arsen R.
2014-06-01
Tornado Spectral Systems has developed a new chip-based spectrometer called OCTANE, the Optical Coherence Tomography Advanced Nanophotonic Engine, built using a planar lightwave circuit with integrated waveguides fabricated on a silicon wafer. While designed for spectral domain optical coherence tomography (SD-OCT) systems, the same miniaturized technology can be applied to many other spectroscopic applications. The field of integrated optics enables the design of complex optical systems which are monolithically integrated on silicon chips. The form factors of these systems can be significantly smaller, more robust and less expensive than their equivalent free-space counterparts. Fabrication techniques and material systems developed for microelectronics have previously been adapted for integrated optics in the telecom industry, where millions of chip-based components are used to power the optical backbone of the internet. We have further adapted the photonic technology platform for spectroscopy applications, allowing unheard-of economies of scale for these types of optical devices. Instead of changing lenses and aligning systems, these devices are accurately designed programmatically and are easily customized for specific applications. Spectrometers using integrated optics have large advantages in systems where size, robustness and cost matter: field-deployable devices, UAVs, UUVs, satellites, handheld scanning and more. We will discuss the performance characteristics of our chip-based spectrometers and the type of spectral sensing applications enabled by this technology.
NASA Astrophysics Data System (ADS)
Mu, Hongqian; Wang, Muguang; Tang, Yu; Zhang, Jing; Jian, Shuisheng
2018-03-01
A novel scheme for the generation of FCC-compliant UWB pulse is proposed based on modified Gaussian quadruplet and incoherent wavelength-to-time conversion. The modified Gaussian quadruplet is synthesized based on linear sum of a broad Gaussian pulse and two narrow Gaussian pulses with the same pulse-width and amplitude peak. Within specific parameter range, FCC-compliant UWB with spectral power efficiency of higher than 39.9% can be achieved. In order to realize the designed waveform, a UWB generator based on spectral shaping and incoherent wavelength-to-time mapping is proposed. The spectral shaper is composed of a Gaussian filter and a programmable filter. Single-mode fiber functions as both dispersion device and transmission medium. Balanced photodetection is employed to combine linearly the broad Gaussian pulse and two narrow Gaussian pulses, and at same time to suppress pulse pedestals that result in low-frequency components. The proposed UWB generator can be reconfigured for UWB doublet by operating the programmable filter as a single-band Gaussian filter. The feasibility of proposed UWB generator is demonstrated experimentally. Measured UWB pulses match well with simulation results. FCC-compliant quadruplet with 10-dB bandwidth of 6.88-GHz, fractional bandwidth of 106.8% and power efficiency of 51% is achieved.
Coelho Neto, José; Lisboa, Fernanda L C
2017-07-01
Viagra and Cialis are among the most counterfeited medicines in many parts of the world, including Brazil. Despite the many studies that have been made regarding discrimination between genuine and counterfeit samples, most published works do not contemplate generic and similar versions of these medicines and also do not explore excipients/adjuvants contributions when characterizing genuine and suspected samples. In this study, we present our findings in exploring ATR-FTIR spectral profiles for characterizing both genuine and questioned samples of several generic and brand-name sildenafil- and tadalafil-based tablets available on the Brazilian market, including Viagra and Cialis. Multi-component spectral matching (deconvolution), objective visual comparison and correlation tests were used during analysis. Besides from allowing simple and quick identification of counterfeits, results obtained evidenced the strong spectral similarities between generic and brand-named tablets employing the same active ingredient and the indistinguishability between samples produced by the same manufacturer, generic or not. For all sildenafil-based and some tadalafil-based tablets tested, differentiation between samples from different manufacturers, attributed to slight variations in excipients/adjuvants proportions, was achieved, thus allowing the possibility of tracing an unknown/unidentified tablet back to a specific manufacturer. Copyright © 2017 The Chartered Society of Forensic Sciences. Published by Elsevier B.V. All rights reserved.
Nasirudin, Radin A.; Mei, Kai; Panchev, Petar; Fehringer, Andreas; Pfeiffer, Franz; Rummeny, Ernst J.; Fiebich, Martin; Noël, Peter B.
2015-01-01
Purpose The exciting prospect of Spectral CT (SCT) using photon-counting detectors (PCD) will lead to new techniques in computed tomography (CT) that take advantage of the additional spectral information provided. We introduce a method to reduce metal artifact in X-ray tomography by incorporating knowledge obtained from SCT into a statistical iterative reconstruction scheme. We call our method Spectral-driven Iterative Reconstruction (SPIR). Method The proposed algorithm consists of two main components: material decomposition and penalized maximum likelihood iterative reconstruction. In this study, the spectral data acquisitions with an energy-resolving PCD were simulated using a Monte-Carlo simulator based on EGSnrc C++ class library. A jaw phantom with a dental implant made of gold was used as an object in this study. A total of three dental implant shapes were simulated separately to test the influence of prior knowledge on the overall performance of the algorithm. The generated projection data was first decomposed into three basis functions: photoelectric absorption, Compton scattering and attenuation of gold. A pseudo-monochromatic sinogram was calculated and used as input in the reconstruction, while the spatial information of the gold implant was used as a prior. The results from the algorithm were assessed and benchmarked with state-of-the-art reconstruction methods. Results Decomposition results illustrate that gold implant of any shape can be distinguished from other components of the phantom. Additionally, the result from the penalized maximum likelihood iterative reconstruction shows that artifacts are significantly reduced in SPIR reconstructed slices in comparison to other known techniques, while at the same time details around the implant are preserved. Quantitatively, the SPIR algorithm best reflects the true attenuation value in comparison to other algorithms. Conclusion It is demonstrated that the combination of the additional information from Spectral CT and statistical reconstruction can significantly improve image quality, especially streaking artifacts caused by the presence of materials with high atomic numbers. PMID:25955019
Spectacle and SpecViz: New Spectral Analysis and Visualization Tools
NASA Astrophysics Data System (ADS)
Earl, Nicholas; Peeples, Molly; JDADF Developers
2018-01-01
A new era of spectroscopic exploration of our universe is being ushered in with advances in instrumentation and next-generation space telescopes. The advent of new spectroscopic instruments has highlighted a pressing need for tools scientists can use to analyze and explore these new data. We have developed Spectacle, a software package for analyzing both synthetic spectra from hydrodynamic simulations as well as real COS data with an aim of characterizing the behavior of the circumgalactic medium. It allows easy reduction of spectral data and analytic line generation capabilities. Currently, the package is focused on automatic determination of absorption regions and line identification with custom line list support, simultaneous line fitting using Voigt profiles via least-squares or MCMC methods, and multi-component modeling of blended features. Non-parametric measurements, such as equivalent widths, delta v90, and full-width half-max are available. Spectacle also provides the ability to compose compound models used to generate synthetic spectra allowing the user to define various LSF kernels, uncertainties, and to specify sampling.We also present updates to the visualization tool SpecViz, developed in conjunction with the JWST data analysis tools development team, to aid in the exploration of spectral data. SpecViz is an open source, Python-based spectral 1-D interactive visualization and analysis application built around high-performance interactive plotting. It supports handling general and instrument-specific data and includes advanced tool-sets for filtering and detrending one-dimensional data, along with the ability to isolate absorption regions using slicing and manipulate spectral features via spectral arithmetic. Multi-component modeling is also possible using a flexible model fitting tool-set that supports custom models to be used with various fitting routines. It also features robust user extensions such as custom data loaders and support for user-created plugins that add new functionality.This work was supported in part by HST AR #13919, HST GO #14268, and HST AR #14560.
Sequencing the Cortical Processing of Pitch-Evoking Stimuli using EEG Analysis and Source Estimation
Butler, Blake E.; Trainor, Laurel J.
2012-01-01
Cues to pitch include spectral cues that arise from tonotopic organization and temporal cues that arise from firing patterns of auditory neurons. fMRI studies suggest a common pitch center is located just beyond primary auditory cortex along the lateral aspect of Heschl’s gyrus, but little work has examined the stages of processing for the integration of pitch cues. Using electroencephalography, we recorded cortical responses to high-pass filtered iterated rippled noise (IRN) and high-pass filtered complex harmonic stimuli, which differ in temporal and spectral content. The two stimulus types were matched for pitch saliency, and a mismatch negativity (MMN) response was elicited by infrequent pitch changes. The P1 and N1 components of event-related potentials (ERPs) are thought to arise from primary and secondary auditory areas, respectively, and to result from simple feature extraction. MMN is generated in secondary auditory cortex and is thought to act on feature-integrated auditory objects. We found that peak latencies of both P1 and N1 occur later in response to IRN stimuli than to complex harmonic stimuli, but found no latency differences between stimulus types for MMN. The location of each ERP component was estimated based on iterative fitting of regional sources in the auditory cortices. The sources of both the P1 and N1 components elicited by IRN stimuli were located dorsal to those elicited by complex harmonic stimuli, whereas no differences were observed for MMN sources across stimuli. Furthermore, the MMN component was located between the P1 and N1 components, consistent with fMRI studies indicating a common pitch region in lateral Heschl’s gyrus. These results suggest that while the spectral and temporal processing of different pitch-evoking stimuli involves different cortical areas during early processing, by the time the object-related MMN response is formed, these cues have been integrated into a common representation of pitch. PMID:22740836
Ground based mid-IR heterodyne spectrometer concept for planetary atmospheres observations
NASA Astrophysics Data System (ADS)
Garamov, V.; Benderov, O.; Semenov, V.; Spiridonov, M.; Rodin, A.; Stepanov, B.
2017-09-01
We present a heterodyne spectrometer concept based on distributed feedback (DFB) quantum cascade lasers (QCL) operated in midle infrared region (MIR). The instrument is assumed to be mount on the Russian infrared observatories. The core features of the concept are compact design, utilizing a novel mid-IR fiber optical components and dynamic local oscillator frequency locking using reference molecule absorption line. The instrument characteristics are similar to modern heterodyne devices THIS (Cologne University, Germany) and MILAHI (Tohoku University, Japan) in terms of fundamental parameters, including spectral resolution, spectral coverage in a single observation. At present moment we created laboratory setup including all necessary elements of MIR heterodyne spectrometer. We have studied different components of noises of our system and found optimal value of LO power. The measured signal to noise ratio (SNR) with MCT PD was about 10 times greater than LO's shot noise (theoretical limit of heterodyne technique SNR) and limited by QCL relative intensity noise (RIN). However, applying additional filtering it is possible to reduce this value better than 5 shot noise level, which is typical to TEC cooled MCT PD. Also we demonstrate heterodyne signal measurements using laboratory black body with temperature of 400 oC.
Building an EEG-fMRI Multi-Modal Brain Graph: A Concurrent EEG-fMRI Study
Yu, Qingbao; Wu, Lei; Bridwell, David A.; Erhardt, Erik B.; Du, Yuhui; He, Hao; Chen, Jiayu; Liu, Peng; Sui, Jing; Pearlson, Godfrey; Calhoun, Vince D.
2016-01-01
The topological architecture of brain connectivity has been well-characterized by graph theory based analysis. However, previous studies have primarily built brain graphs based on a single modality of brain imaging data. Here we develop a framework to construct multi-modal brain graphs using concurrent EEG-fMRI data which are simultaneously collected during eyes open (EO) and eyes closed (EC) resting states. FMRI data are decomposed into independent components with associated time courses by group independent component analysis (ICA). EEG time series are segmented, and then spectral power time courses are computed and averaged within 5 frequency bands (delta; theta; alpha; beta; low gamma). EEG-fMRI brain graphs, with EEG electrodes and fMRI brain components serving as nodes, are built by computing correlations within and between fMRI ICA time courses and EEG spectral power time courses. Dynamic EEG-fMRI graphs are built using a sliding window method, versus static ones treating the entire time course as stationary. In global level, static graph measures and properties of dynamic graph measures are different across frequency bands and are mainly showing higher values in eyes closed than eyes open. Nodal level graph measures of a few brain components are also showing higher values during eyes closed in specific frequency bands. Overall, these findings incorporate fMRI spatial localization and EEG frequency information which could not be obtained by examining only one modality. This work provides a new approach to examine EEG-fMRI associations within a graph theoretic framework with potential application to many topics. PMID:27733821
VizieR Online Data Catalog: Spectral evolution of 4U 1543-47 in 2002 (Lipunova+, 2017)
NASA Astrophysics Data System (ADS)
Lipunova, G. V.; Malanchev, K. L.
2017-08-01
Evolution of the spectral parameters obtained from the fitting of the spectral data obtained with RXTE/PCA in the 2.9-25keV energy band. Some spectral parameters are plotted in Figure 1 of the paper. The black hole mass is 9.4 solar masses, the Kerr parameter is 0.4, the disc inclination is 20.7 grad. The spectral fitting is done using XSPEC 12.9.0. The XSPEC spectral model consists of the following spectral components: TBabs((simpl*kerrbb+laor)smedge). Full description of the spectral parameters can be found in Table A1 and Appendix A of the paper. (1 data file).
Noise in the passenger cars of high-speed trains.
Hong, Joo Young; Cha, Yongwon; Jeon, Jin Yong
2015-12-01
The aim of this study is to investigate the effects of both room acoustic conditions and spectral characteristics of noises on acoustic discomfort in a high-speed train's passenger car. Measurement of interior noises in a high-speed train was performed when the train was operating at speeds of 100 km/h and 300 km/h. Acoustic discomfort caused by interior noises was evaluated by paired comparison methods based on the variation of reverberation time (RT) in a passenger car and the spectral differences in interior noises. The effect of RT on acoustic discomfort was not significant, whereas acoustic discomfort significantly varied depending on spectral differences in noise. Acoustic discomfort increased with increment of the sound pressure level (SPL) ratio at high frequencies, and variation in high-frequency noise components were described using sharpness. Just noticeable differences of SPL with low- and high-frequency components were determined to be 3.7 and 2.9 dB, respectively. This indicates that subjects were more sensitive to differences in SPLs at the high-frequency range than differences at the low-frequency range. These results support that, for interior noises, reduction in SPLs at high frequencies would significantly contribute to improved acoustic quality in passenger cars of high-speed trains.
Henze Bancroft, Leah C; Strigel, Roberta M; Hernando, Diego; Johnson, Kevin M; Kelcz, Frederick; Kijowski, Richard; Block, Walter F
2016-03-01
Chemical shift based fat/water decomposition methods such as IDEAL are frequently used in challenging imaging environments with large B0 inhomogeneity. However, they do not account for the signal modulations introduced by a balanced steady state free precession (bSSFP) acquisition. Here we demonstrate improved performance when the bSSFP frequency response is properly incorporated into the multipeak spectral fat model used in the decomposition process. Balanced SSFP allows for rapid imaging but also introduces a characteristic frequency response featuring periodic nulls and pass bands. Fat spectral components in adjacent pass bands will experience bulk phase offsets and magnitude modulations that change the expected constructive and destructive interference between the fat spectral components. A bSSFP signal model was incorporated into the fat/water decomposition process and used to generate images of a fat phantom, and bilateral breast and knee images in four normal volunteers at 1.5 Tesla. Incorporation of the bSSFP signal model into the decomposition process improved the performance of the fat/water decomposition. Incorporation of this model allows rapid bSSFP imaging sequences to use robust fat/water decomposition methods such as IDEAL. While only one set of imaging parameters were presented, the method is compatible with any field strength or repetition time. © 2015 Wiley Periodicals, Inc.
Geostatistical estimation of signal-to-noise ratios for spectral vegetation indices
Ji, Lei; Zhang, Li; Rover, Jennifer R.; Wylie, Bruce K.; Chen, Xuexia
2014-01-01
In the past 40 years, many spectral vegetation indices have been developed to quantify vegetation biophysical parameters. An ideal vegetation index should contain the maximum level of signal related to specific biophysical characteristics and the minimum level of noise such as background soil influences and atmospheric effects. However, accurate quantification of signal and noise in a vegetation index remains a challenge, because it requires a large number of field measurements or laboratory experiments. In this study, we applied a geostatistical method to estimate signal-to-noise ratio (S/N) for spectral vegetation indices. Based on the sample semivariogram of vegetation index images, we used the standardized noise to quantify the noise component of vegetation indices. In a case study in the grasslands and shrublands of the western United States, we demonstrated the geostatistical method for evaluating S/N for a series of soil-adjusted vegetation indices derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. The soil-adjusted vegetation indices were found to have higher S/N values than the traditional normalized difference vegetation index (NDVI) and simple ratio (SR) in the sparsely vegetated areas. This study shows that the proposed geostatistical analysis can constitute an efficient technique for estimating signal and noise components in vegetation indices.
Unmixing of spectral components affecting AVIRIS imagery of Tampa Bay
NASA Astrophysics Data System (ADS)
Carder, Kendall L.; Lee, Z. P.; Chen, Robert F.; Davis, Curtiss O.
1993-09-01
According to Kirk's as well as Morel and Gentili's Monte Carlo simulations, the popular simple expression, R approximately equals 0.33 bb/a, relating subsurface irradiance reflectance (R) to the ratio of the backscattering coefficient (bb) to absorption coefficient (a), is not valid for bb/a > 0.25. This means that it may no longer be valid for values of remote-sensing reflectance (above-surface ratio of water-leaving radiance to downwelling irradiance) where Rrs4/ > 0.01. Since there has been no simple Rrs expression developed for very turbid waters, we developed one based in part on Monte Carlo simulations and empirical adjustments to an Rrs model and applied it to rather turbid coastal waters near Tampa Bay to evaluate its utility for unmixing the optical components affecting the water- leaving radiance. With the high spectral (10 nm) and spatial (20 m2) resolution of Airborne Visible-InfraRed Imaging Spectrometer (AVIRIS) data, the water depth and bottom type were deduced using the model for shallow waters. This research demonstrates the necessity of further research to improve interpretations of scenes with highly variable turbid waters, and it emphasizes the utility of high spectral-resolution data as from AVIRIS for better understanding complicated coastal environments such as the west Florida shelf.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hornemann, Andrea, E-mail: andrea.hornemann@ptb.de; Hoehl, Arne, E-mail: arne.hoehl@ptb.de; Ulm, Gerhard, E-mail: gerhard.ulm@ptb.de
Bio-diagnostic assays of high complexity rely on nanoscaled assay recognition elements that can provide unique selectivity and design-enhanced sensitivity features. High throughput performance requires the simultaneous detection of various analytes combined with appropriate bioassay components. Nanoparticle induced sensitivity enhancement, and subsequent multiplexed capability Surface-Enhanced InfraRed Absorption (SEIRA) assay formats are fitting well these purposes. SEIRA constitutes an ideal platform to isolate the vibrational signatures of targeted bioassay and active molecules. The potential of several targeted biolabels, here fluorophore-labeled antibody conjugates, chemisorbed onto low-cost biocompatible gold nano-aggregates substrates have been explored for their use in assay platforms. Dried films were analyzedmore » by synchrotron radiation based FTIR/SEIRA spectro-microscopy and the resulting complex hyperspectral datasets were submitted to automated statistical analysis, namely Principal Components Analysis (PCA). The relationships between molecular fingerprints were put in evidence to highlight their spectral discrimination capabilities. We demonstrate that robust spectral encoding via SEIRA fingerprints opens up new opportunities for fast, reliable and multiplexed high-end screening not only in biodiagnostics but also in vitro biochemical imaging.« less
Radiation damage of gallium arsenide production cells
NASA Technical Reports Server (NTRS)
Mardesich, N.; Garlick, G. F. J.
1987-01-01
High-efficiency gallium arsenide cells, made by the liquid epitaxy method (LPE), have been irradiated with 1-MeV electrons up to fluences of 10 to the 16th e/sq cm. Measurements have been made of cell spectral response and dark and light-excited current-voltage characteristics and analyzed using computer-based models to determine underlying parameters such as damage coefficients. It is possible to use spectral response to sort out damage effects in the different cell component layers. Damage coefficients are similar to other reported in the literature for the emitter and buffer (base). However, there is also a damage effect in the window layer and possibly at the window emitter interface similar to that found for proton-irradiated liquid-phase epitaxy-grown cells. Depletion layer recombination is found to be less than theoretically expected at high fluence.
Design and performance of the collective Thomson scattering receiver at ASDEX Upgrade.
Furtula, V; Salewski, M; Leipold, F; Michelsen, P K; Korsholm, S B; Meo, F; Moseev, D; Nielsen, S K; Stejner, M; Johansen, T
2012-01-01
Here we present the design of the fast-ion collective Thomson scattering receiver for millimeter wave radiation installed at ASDEX Upgrade, a tokamak for fusion plasma experiments. The receiver can detect spectral power densities of a few eV against the electron cyclotron emission background on the order of 100 eV under presence of gyrotron stray radiation that is several orders of magnitude stronger than the signal to be detected. The receiver down converts the frequencies of scattered radiation (100-110 GHz) to intermediate frequencies (IF) (4.5-14.5 GHz) by heterodyning. The IF signal is divided into 50 IF channels tightly spaced in frequency space. The channels are terminated by square-law detector diodes that convert the signal power into DC voltages. We present measurements of the transmission characteristics and performance of the main receiver components operating at mm-wave frequencies (notch, bandpass, and lowpass filters, a voltage-controlled variable attenuator, and an isolator), the down-converter unit, and the IF components (amplifiers, bandpass filters, and detector diodes). Furthermore, we determine the performance of the receiver as a unit through spectral response measurements and find reasonable agreement with the expectation based on the individual component measurements.
Hyperspectral imaging of polymer banknotes for building and analysis of spectral library
NASA Astrophysics Data System (ADS)
Lim, Hoong-Ta; Murukeshan, Vadakke Matham
2017-11-01
The use of counterfeit banknotes increases crime rates and cripples the economy. New countermeasures are required to stop counterfeiters who use advancing technologies with criminal intent. Many countries started adopting polymer banknotes to replace paper notes, as polymer notes are more durable and have better quality. The research on authenticating such banknotes is of much interest to the forensic investigators. Hyperspectral imaging can be employed to build a spectral library of polymer notes, which can then be used for classification to authenticate these notes. This is however not widely reported and has become a research interest in forensic identification. This paper focuses on the use of hyperspectral imaging on polymer notes to build spectral libraries, using a pushbroom hyperspectral imager which has been previously reported. As an initial study, a spectral library will be built from three arbitrarily chosen regions of interest of five circulated genuine polymer notes. Principal component analysis is used for dimension reduction and to convert the information in the spectral library to principal components. A 99% confidence ellipse is formed around the cluster of principal component scores of each class and then used as classification criteria. The potential of the adopted methodology is demonstrated by the classification of the imaged regions as training samples.
NASA Astrophysics Data System (ADS)
Liu, Xi; Zhou, Mei; Qiu, Song; Sun, Li; Liu, Hongying; Li, Qingli; Wang, Yiting
2017-12-01
Red blood cell counting, as a routine examination, plays an important role in medical diagnoses. Although automated hematology analyzers are widely used, manual microscopic examination by a hematologist or pathologist is still unavoidable, which is time-consuming and error-prone. This paper proposes a full-automatic red blood cell counting method which is based on microscopic hyperspectral imaging of blood smears and combines spatial and spectral information to achieve high precision. The acquired hyperspectral image data of the blood smear in the visible and near-infrared spectral range are firstly preprocessed, and then a quadratic blind linear unmixing algorithm is used to get endmember abundance images. Based on mathematical morphological operation and an adaptive Otsu’s method, a binaryzation process is performed on the abundance images. Finally, the connected component labeling algorithm with magnification-based parameter setting is applied to automatically select the binary images of red blood cell cytoplasm. Experimental results show that the proposed method can perform well and has potential for clinical applications.
Apple variety and maturity profiling of base ciders using UV spectroscopy.
Girschik, Lachlan; Jones, Joanna E; Kerslake, Fiona L; Robertson, Mark; Dambergs, Robert G; Swarts, Nigel D
2017-08-01
Varietal base ciders were produced from three varieties of dessert apples ('Pink Lady®', 'Royal Gala' and 'Red Delicious') at pre-commercial, commercial and post-commercial harvest timings. Rapid analytical methods were used to categorise the base ciders, and data analysed using principal component analysis (PCA). The titratable acidity of apple must was significantly higher for the pre-commercial harvest fruit for both the 'Royal Gala' and 'Red Delicious' varieties. The base cider phenolic content was highest in the pre-commercial harvest fruit for all varieties. 'Red Delicious' had the highest total phenolics as determined by spectral analysis and supported by the classification provided by the PCA analysis. The spectral fingerprints of the ciders showed two main peaks at approximately 280nm and 320nm indicating phenolic concentrations. Studies analysing characteristics of dessert apple varieties with relevance for cider production will allow for informed decision making for both apple producers and cider makers. Copyright © 2017 Elsevier Ltd. All rights reserved.
Integrated Central-Autonomic Multifractal Complexity in the Heart Rate Variability of Healthy Humans
Lin, D. C.; Sharif, A.
2012-01-01
Purpose of Study: The aim of this study was to characterize the central-autonomic interaction underlying the multifractality in heart rate variability (HRV) of healthy humans. Materials and Methods: Eleven young healthy subjects participated in two separate ~40 min experimental sessions, one in supine (SUP) and one in, head-up-tilt (HUT), upright (UPR) body positions. Surface scalp electroencephalography (EEG) and electrocardiogram (ECG) were collected and fractal correlation of brain and heart rate data was analyzed based on the idea of relative multifractality. The fractal correlation was further examined with the EEG, HRV spectral measures using linear regression of two variables and principal component analysis (PCA) to find clues for the physiological processing underlying the central influence in fractal HRV. Results: We report evidence of a central-autonomic fractal correlation (CAFC) where the HRV multifractal complexity varies significantly with the fractal correlation between the heart rate and brain data (P = 0.003). The linear regression shows significant correlation between CAFC measure and EEG Beta band spectral component (P = 0.01 for SUP and P = 0.002 for UPR positions). There is significant correlation between CAFC measure and HRV LF component in the SUP position (P = 0.04), whereas the correlation with the HRV HF component approaches significance (P = 0.07). The correlation between CAFC measure and HRV spectral measures in the UPR position is weak. The PCA results confirm these findings and further imply multiple physiological processes underlying CAFC, highlighting the importance of the EEG Alpha, Beta band, and the HRV LF, HF spectral measures in the supine position. Discussion and Conclusion: The findings of this work can be summarized into three points: (i) Similar fractal characteristics exist in the brain and heart rate fluctuation and the change toward stronger fractal correlation implies the change toward more complex HRV multifractality. (ii) CAFC is likely contributed by multiple physiological mechanisms, with its central elements mainly derived from the EEG Alpha, Beta band dynamics. (iii) The CAFC in SUP and UPR positions is qualitatively different, with a more predominant central influence in the fractal HRV of the UPR position. PMID:22403548
Principal Components Analysis Studies of Martian Clouds
NASA Astrophysics Data System (ADS)
Klassen, D. R.; Bell, J. F., III
2001-11-01
We present the principal components analysis (PCA) of absolutely calibrated multi-spectral images of Mars as a function of Martian season. The PCA technique is a mathematical rotation and translation of the data from a brightness/wavelength space to a vector space of principal ``traits'' that lie along the directions of maximal variance. The first of these traits, accounting for over 90% of the data variance, is overall brightness and represented by an average Mars spectrum. Interpretation of the remaining traits, which account for the remaining ~10% of the variance, is not always the same and depends upon what other components are in the scene and thus, varies with Martian season. For example, during seasons with large amounts of water ice in the scene, the second trait correlates with the ice and anti-corrlates with temperature. We will investigate the interpretation of the second, and successive important PCA traits. Although these PCA traits are orthogonal in their own vector space, it is unlikely that any one trait represents a singular, mineralogic, spectral end-member. It is more likely that there are many spectral endmembers that vary identically to within the noise level, that the PCA technique will not be able to distinguish them. Another possibility is that similar absorption features among spectral endmembers may be tied to one PCA trait, for example ''amount of 2 \\micron\\ absorption''. We thus attempt to extract spectral endmembers by matching linear combinations of the PCA traits to USGS, JHU, and JPL spectral libraries as aquired through the JPL Aster project. The recovered spectral endmembers are then linearly combined to model the multi-spectral image set. We present here the spectral abundance maps of the water ice/frost endmember which allow us to track Martian clouds and ground frosts. This work supported in part through NASA Planetary Astronomy Grant NAG5-6776. All data gathered at the NASA Infrared Telescope Facility in collaboration with the telescope operators and with thanks to the support staff and day crew.
NASA Technical Reports Server (NTRS)
Sabol, Donald E., Jr.; Adams, John B.; Smith, Milton O.
1992-01-01
The conditions that affect the spectral detection of target materials at the subpixel scale are examined. Two levels of spectral mixture analysis for determining threshold detection limits of target materials in a spectral mixture are presented, the cases where the target is detected as: (1) a component of a spectral mixture (continuum threshold analysis) and (2) residuals (residual threshold analysis). The results of these two analyses are compared under various measurement conditions. The examples illustrate the general approach that can be used for evaluating the spectral detectability of terrestrial and planetary targets at the subpixel scale.
Tomographic separation of composite spectra. 2: The components of 29 UW Canis Majoris
NASA Technical Reports Server (NTRS)
Bagnuolo, William G., Jr.; Gies, Douglas R.; Hahula, Michael E.; Wiemker, Rafael; Wiggs, Michael S.
1994-01-01
We have analyzed the UV photospheric lines of 29 CMa, a 4.39 day period, double-lined O-type spectroscopic binary. Archival data from International Ultraviolet Explorer (IUE)(28 spectra well distributed in oribital phase) were analyzed with several techniques. We find that the mass ratio is q = 1.20 +/- 0.16 (secondary more massive) based on three independent arguments. A tomography algorithm was used to produce the separate spectra of the two stars in six UV spectral regions. The MK spectral classifications of the primary and secondary, O7.5-8 Iab and O9.7 Ib, respectively, were estimated through a comparison of UV line ratios with those in spectral standard stars. The flux ratio of the stars in the UV is 0.36 +/- 0.07 (primary brighter). The primary has a strong P Cygni NIV wavelength 1718 feature, indicating a strong stellar wind. We also present tomographic reconstructions of visual spectral data in the range 4300-4950 A, based on seven observations of differing orbital phases, which confirm the UV classifications, and show that the primary is an Of star. From the spectral classifications, we estimate the temperatures of the stars to be 33,750 K and 29,000 K for primary and secondary, respectively. We then fit visual and UV light curves and show that reasonably good fits can be obtained with these temperatures, a semicontact configuration, an inclination of 74 deg. +/- 2 deg., and an intensity ratio r is less than 0.5.
NASA Astrophysics Data System (ADS)
Garcia, C. G.; Canals, M.; Irizarry, A. A.
2016-02-01
Nowadays a significant amount of wave energy assessments have taken place due to the development of the ocean energy markets worldwide. Energy contained in surface gravity waves is scattered along frequency components that can be described using wave spectra. Correspondingly, characterization and quantification of harvestable wave energy is inherently dictated by the nature of the two-dimensional wave spectrum. The present study uses spectral wave data from the operational SWAN-based CariCOOS Nearshore Wave Model to evaluate the capture efficiency of multiple wave energy converters (WEC). This study revolves around accurately estimating available wave energy as a function of varying spectral distributions, effectively providing a detailed insight concerning local wave conditions for PR and USVI and the resulting available-energy to generated-power ratio. Results in particular, provide a comprehensive characterization of three years' worth of SWAN-based datasets by outlining where higher concentrations of wave energy are localized in the spectrum. Subsequently, the aforementioned datasets were processed to quantify the amount of energy incident on two proposed sites located in PR and USVI. Results were largely influenced by local trade wind activity, which drive predominant sea states, and the amount of North-Atlantic swells that propagate towards the region. Each wave event was numerically analyzed in the frequency domain to evaluate the capacity of a WEC to perform under different spectral distribution scenarios, allowing for a correlation between electrical power output and spectral energy distribution to be established.
Community structure from spectral properties in complex networks
NASA Astrophysics Data System (ADS)
Servedio, V. D. P.; Colaiori, F.; Capocci, A.; Caldarelli, G.
2005-06-01
We analyze the spectral properties of complex networks focusing on their relation to the community structure, and develop an algorithm based on correlations among components of different eigenvectors. The algorithm applies to general weighted networks, and, in a suitably modified version, to the case of directed networks. Our method allows to correctly detect communities in sharply partitioned graphs, however it is useful to the analysis of more complex networks, without a well defined cluster structure, as social and information networks. As an example, we test the algorithm on a large scale data-set from a psychological experiment of free word association, where it proves to be successful both in clustering words, and in uncovering mental association patterns.
Calibration of space instruments at the Metrology Light Source
DOE Office of Scientific and Technical Information (OSTI.GOV)
Klein, R., E-mail: roman.klein@ptb.de; Fliegauf, R.; Gottwald, A.
2016-07-27
PTB has more than 20 years of experience in the calibration of space-based instruments using synchrotron radiation to cover the UV, VUV and X-ray spectral range. New instrumentation at the electron storage ring Metrology Light Source (MLS) opens up extended calibration possibilities within this framework. In particular, the set-up of a large vacuum vessel that can accommodate entire space instruments opens up new prospects. Moreover, a new facility for the calibration of radiation transfer source standards with a considerably extended spectral range has been put into operation. Besides, characterization and calibration of single components like e.g. mirrors, filters, gratings, andmore » detectors is continued.« less
The Raman spectrum character of skin tumor induced by UVB
NASA Astrophysics Data System (ADS)
Wu, Shulian; Hu, Liangjun; Wang, Yunxia; Li, Yongzeng
2016-03-01
In our study, the skin canceration processes induced by UVB were analyzed from the perspective of tissue spectrum. A home-made Raman spectral system with a millimeter order excitation laser spot size combined with a multivariate statistical analysis for monitoring the skin changed irradiated by UVB was studied and the discrimination were evaluated. Raman scattering signals of the SCC and normal skin were acquired. Spectral differences in Raman spectra were revealed. Linear discriminant analysis (LDA) based on principal component analysis (PCA) were employed to generate diagnostic algorithms for the classification of skin SCC and normal. The results indicated that Raman spectroscopy combined with PCA-LDA demonstrated good potential for improving the diagnosis of skin cancers.
NASA Astrophysics Data System (ADS)
Bonnefoy, M.; Chauvin, G.; Dumas, C.; Lagrange, A.-M.; Beust, H.; Desort, M.; Teixeira, R.; Ducourant, C.; Beuzit, J.-L.; Song, I.
2009-11-01
Context: Tight binaries discovered in young, nearby associations are ideal targets for providing dynamical mass measurements to test the physics of evolutionary models at young ages and very low masses. Aims: We report the binarity of TWA22 for the first time. We aim at monitoring the orbit of this young and tight system to determine its total dynamical mass using an accurate distance determination. We also intend to characterize the physical properties (luminosity, effective temperature, and surface gravity) of each component based on near-infrared photometric and spectroscopic observations. Methods: We used the adaptive-optics assisted imager NACO to resolve the components, to monitor the complete orbit and to obtain the relative near-infrared photometry of TWA22 AB. The adaptive-optics assisted integral field spectrometer SINFONI was also used to obtain medium-resolution (Rλ=1500-2000) spectra in JHK bands. Comparison with empirical and synthetic librairies were necessary for deriving the spectral type, the effective temperature, and the surface gravity for each component of the system. Results: Based on an accurate trigonometric distance (17.5 ± 0.2 pc) determination, we infer a total dynamical mass of 220 ± 21 MJup for the system. From the complete set of spectra, we find an effective temperature T_eff=2900+200-200 K for TWA22 A and T_eff=2900+200-100 K for TWA22 B and surface gravities between 4.0 and 5.5 dex. From our photometry and an M6 ± 1 spectral type for both components, we find luminosities of log(L/L⊙) = -2.11 ± 0.13 dex and log(L/L⊙) = -2.30 ± 0.16 dex for TWA22 A and B, respectively. By comparing these parameters with evolutionary models, we question the age and the multiplicity of this system. We also discuss a possible underestimation of the mass predicted by evolutionary models for young stars close to the substellar boundary. Based on service-mode observations (072.C-0644, 073.C-0469, 075.C-0521, 076.C-0554, 078.C-0510, 080.C-0581) collected at the European Organisation for Astronomical Research in the Southern Hemisphere, Chile.
Comparative study of human blood Raman spectra and biochemical analysis of patients with cancer
NASA Astrophysics Data System (ADS)
Shamina, Lyudmila A.; Bratchenko, Ivan A.; Artemyev, Dmitry N.; Myakinin, Oleg O.; Moryatov, Alexander A.; Orlov, Andrey E.; Kozlov, Sergey V.; Zakharov, Valery P.
2018-04-01
In this study we measured spectral features of blood by Raman spectroscopy. Correlation of the obtained spectral data and biochemical studies results is investigated. Analysis of specific spectra allows for identification of informative spectral bands proportional to components whose content is associated with body fluids homeostasis changes at various pathological conditions. Regression analysis of the obtained spectral data allows for discriminating the lung cancer from other tumors with a posteriori probability of 88.3%. The potentiality of applying surface-enhanced Raman spectroscopy with utilized experimental setup for further studies of the body fluids component composition was estimated. The greatest signal amplification was achieved for the gold substrate with a surface roughness of 1 μm. In general, the developed approach of body fluids analysis provides the basis of a useful and minimally invasive method of pathologies screening.
The rocks of Gusev Crater as viewed by the Mini-TES instrument
Ruff, S.W.; Christensen, P.R.; Blaney, D.L.; Farrand, W. H.; Johnson, J. R.; Michalski, J.R.; Moersch, J.E.; Wright, S.P.; Squyres, S. W.
2006-01-01
The Miniature Thermal Emission Spectrometer (Mini-TES) on board the Mars Exploration Rover Spirit is part of a payload designed to investigate whether a lake once existed in Gusev Crater. Mini-TES has observed hundreds of rocks along the rover's traverse into the Columbia Hills, yielding information on their distribution, bulk mineralogy, and the potential role of water at the site. Although dust in various forms produces contributions to the spectra, we have established techniques for dealing with it. All of the rocks encountered on the plains traverse from the lander to the base of the Columbia Hills share common spectral features consistent with an olivine-rich basaltic rock known as Adirondack Class. Beginning at the base of the West Spur of the Columbia Hills and across its length, the rocks are spectrally distinct from the plains but can be grouped into a common type called Clovis Class. These rocks, some of which appear as in-place outcrop, are dominated by a component whose spectral character is consistent with unaltered basaltic glass despite evidence from other rover instruments for significant alteration. The northwest flank of Husband Hill is covered in float rocks known as Wishstone Class with spectral features that can be attributed uniquely to plagioclase feldspar, a phase that represents more than half of the bulk mineralogy. Rare exceptions are three classes of basaltic "exotics" found scattered across Husband Hill that may represent impact ejecta and/or float derived from local intrusions within the hills. The rare outcrops observed on Husband Hill display distinctive spectral characteristics. The outcrop called Peace shows a feature attributable to molecular bound water, and the outcrop that hosts the rock called Watchtower displays a dominant basaltic glass component. Despite evidence from the rover's payload for significant alteration of some of the rocks, no unambiguous detection of crystalline phyllosilicates or other secondary silicates has been observed by Mini-TES. The mineralogical results supplied by Mini-TES provide no clear evidence that a lake once existed in Gusev Crater. Copyright 2006 by the American Geophysical Union.
Raz, O; Herrera, J; Dorren, H J S
2009-02-02
By using a tunable filter with tunability of both bandwidth and wavelength and a very sharp filter roll-off, considerable improvement of all optical Wavelength Conversion, based on Cross Gain and Phase Modulation effects in a Semiconductor Optical Amplifier and spectral slicing, is shown. At 40 Gb/s slicing of blue spectral components is shown to result in a small penalty of 0.7 dB, with a minimal eye broadening, and at 80 Gb/s the low demonstrated 0.5 dB penalty is a dramatic improvement over previously reported wavelength converters using the same principal. Additionally, we give for the first time quantitative results for the case of red spectral slicing at 40 Gb/s which we found to have only 0.5 dB penalty and a narrower time response, as anticipated by previously published theoretical papers. Numerical simulations for the dependence of the eye opening on the filter characteristics highlight the importance of the combination of a sharp filter roll-off and a broad passband.
ASD FieldSpec Calibration Setup and Techniques
NASA Technical Reports Server (NTRS)
Olive, Dan
2001-01-01
This paper describes the Analytical Spectral Devices (ASD) Fieldspec Calibration Setup and Techniques. The topics include: 1) ASD Fieldspec FR Spectroradiometer; 2) Components of Calibration; 3) Equipment list; 4) Spectral Setup; 5) Spectral Calibration; 6) Radiometric and Linearity Setup; 7) Radiometric setup; 8) Datadets Required; 9) Data files; and 10) Field of View Measurement. This paper is in viewgraph form.
Detecting anthropogenic footprints in regional and global sea level rise since 1900
NASA Astrophysics Data System (ADS)
Dangendorf, S.; Marcos, M.; Piecuch, C. G.; Jensen, J.
2015-12-01
While there is scientific consensus that global and local mean sea level (GMSL and LMSL) is rising since the late 19th century, it remains unclear how much of this rise is due to natural variability or anthropogenic forcing. Distinguishing both contributions requires an extensive knowledge about the persistence of natural high and low stands in GMSL and LMSL. This is challenging, since observational time series represent the superposition of various processes with different spectral properties. Here we provide a probabilistic upper range of long-term persistent natural GMSL/LMSL variability (P=0.99), which in turn determines the minimum/maximum anthropogenic contribution since 1900. To account for different spectral characteristics of various contributing processes, we separate LMSL (corrected for vertical land motion) into a slowly varying volumetric (mass and density changes) and a more rapidly changing atmospheric component. Based on a combination of spectral analyses of tide gauge records, barotropic and baroclinic ocean models and numerical Monte-Carlo experiments, we find that in records where transient atmospheric processes dominate the spectra, the persistence of natural volumetric changes tends to be underestimated. If each component is assessed separately, natural centennial trends are locally up to ~1.0 mm/yr larger than in case of an integrated assessment, therefore erroneously enhancing the significance of anthropogenic footprints. The GMSL, however, remains unaffected by such biases. On the basis of a model assessment of the separate components, we conclude that it is virtually certain (P=0.99) that at least 45% of the observed increase in GMSL is of anthropogenic origin.
Chan, H L; Lin, J L; Huang, H H; Wu, C P
1997-09-01
A new technique for interference-term suppression in Wigner-Ville distribution (WVD) is proposed for the signal with 1/f spectrum shape. The spectral characteristic of the signal is altered by f alpha filtering before time-frequency analysis and compensated after analysis. With the utilization of the proposed technique in smoothed pseudo Wigner-Ville distribution, an excellent suppression of interference component can be achieved.
Ground-based Observations of Large Solar Flares Precursors
NASA Astrophysics Data System (ADS)
Sheyner, Olga; Smirnova, Anna; Snegirev, Sergey
2010-05-01
The importance problem of Solar-terrestrial physics is regular forecasting of solar activity phenomena, which negatively influence the human's health, operating safety, communication, radar sets and others. The opportunity of development of short-term forecasting technique of geoeffective solar flares is presented in this study. This technique is based on the effect of growth of pulsations of horizontal component of geomagnetic field before the solar proton flares. The long-period (30-60 minutes) pulsations of H-component of geomagnetic field are detected for the events of different intensity on March 22, 1991, November 4, 2001, and November 17, 2001 using the method of wavelet-analysis. Amplitudes of fluctuations of horizontal component of geomagnetic field with the 30-60 minute's periods grow at the most of tested stations during 0.5-3.5 days before the solar flares. The particularities of spectral component are studied for the stations situated on different latitudes. The assumptions about the reason of such precursors-fluctuations appearance are made.
Optically reconfigurable metasurfaces and photonic devices based on phase change materials
NASA Astrophysics Data System (ADS)
Wang, Qian; Rogers, Edward T. F.; Gholipour, Behrad; Wang, Chih-Ming; Yuan, Guanghui; Teng, Jinghua; Zheludev, Nikolay I.
2016-01-01
Photonic components with adjustable parameters, such as variable-focal-length lenses or spectral filters, which can change functionality upon optical stimulation, could offer numerous useful applications. Tuning of such components is conventionally achieved by either micro- or nanomechanical actuation of their constituent parts, by stretching or by heating. Here, we report a novel approach for making reconfigurable optical components that are created with light in a non-volatile and reversible fashion. Such components are written, erased and rewritten as two-dimensional binary or greyscale patterns into a nanoscale film of phase-change material by inducing a refractive-index-changing phase transition with tailored trains of femtosecond pulses. We combine germanium-antimony-tellurium-based films with a diffraction-limited resolution optical writing process to demonstrate a variety of devices: visible-range reconfigurable bichromatic and multi-focus Fresnel zone plates, a super-oscillatory lens with subwavelength focus, a greyscale hologram, and a dielectric metamaterial with on-demand reflection and transmission resonances.
Fluorescence/depolarization lidar for mid-range stand-off detection of biological agents
NASA Astrophysics Data System (ADS)
Mierczyk, Z.; Kopczyński, K.; Zygmunt, M.; Wojtanowski, J.; Młynczak, J.; Gawlikowski, A.; Młodzianko, A.; Piotrowski, W.; Gietka, A.; Knysak, P.; Drozd, T.; Muzal, M.; Kaszczuk, M.; Ostrowski, R.; Jakubaszek, M.
2011-06-01
LIDAR system for real-time standoff detection of bio-agents is presented and preliminary experimental results are discussed. The detection approach is based on two independent physical phenomena: (1) laser induced fluorescence (LIF), (2) depolarization resulting from elastic scattering on non-spherical particles. The device includes three laser sources, two receiving telescopes, depolarization component and spectral signature analyzing spectrograph. It was designed to provide the stand-off detection capability at ranges from 200 m up to several kilometers. The system as a whole forms a mobile platform for vehicle or building installation. Additionally, it's combined with a scanning mechanics and advanced software, which enable to conduct the semi-automatic monitoring of a specified space sector. For fluorescence excitation, 3-rd (355 nm) and 4-th (266 nm) harmonics of Nd:YAG pulsed lasers are used. They emit short (~6 ns) pulses with the repetition rate of 20 Hz. Collecting optics for fluorescence echo detection and spectral content analysis includes 25 mm diameter f/4 Newton telescope, Czerny Turner spectrograph and 32-channel PMT. Depending on the grating applied, the spectral resolution from 20 nm up to 3 nm per channel can be achieved. The system is also equipped with an eye-safe (1.5 μm) Nd:YAG OPO laser for elastic backscattering/depolarization detection. The optical echo signal is collected by Cassegrain telescope with aperture diameter of 12.5 mm. Depolarization detection component based on polarizing beam-splitter serves as the stand-off particle-shape analyzer, which is very valuable in case of non-spherical bio-aerosols sensing.
Time-Dependent Cryospheric Longwave Surface Emissivity Feedback in the Community Earth System Model
NASA Astrophysics Data System (ADS)
Kuo, Chaincy; Feldman, Daniel R.; Huang, Xianglei; Flanner, Mark; Yang, Ping; Chen, Xiuhong
2018-01-01
Frozen and unfrozen surfaces exhibit different longwave surface emissivities with different spectral characteristics, and outgoing longwave radiation and cooling rates are reduced for unfrozen scenes relative to frozen ones. Here physically realistic modeling of spectrally resolved surface emissivity throughout the coupled model components of the Community Earth System Model (CESM) is advanced, and implications for model high-latitude biases and feedbacks are evaluated. It is shown that despite a surface emissivity feedback amplitude that is, at most, a few percent of the surface albedo feedback amplitude, the inclusion of realistic, harmonized longwave, spectrally resolved emissivity information in CESM1.2.2 reduces wintertime Arctic surface temperature biases from -7.2 ± 0.9 K to -1.1 ± 1.2 K, relative to observations. The bias reduction is most pronounced in the Arctic Ocean, a region for which Coupled Model Intercomparison Project version 5 (CMIP5) models exhibit the largest mean wintertime cold bias, suggesting that persistent polar temperature biases can be lessened by including this physically based process across model components. The ice emissivity feedback of CESM1.2.2 is evaluated under a warming scenario with a kernel-based approach, and it is found that emissivity radiative kernels exhibit water vapor and cloud cover dependence, thereby varying spatially and decreasing in magnitude over the course of the scenario from secular changes in atmospheric thermodynamics and cloud patterns. Accounting for the temporally varying radiative responses can yield diagnosed feedbacks that differ in sign from those obtained from conventional climatological feedback analysis methods.
Terahertz spectral characteristics of two kinds of important functional oligosaccharides
NASA Astrophysics Data System (ADS)
Li, Ge; Liu, Wei; Wang, Wenai
2018-01-01
The absorption spectra of two kinds of important functional oligosaccharides were firstly acquired based on Fourier transform infrared spectroscopy in the range of 0.15-10THz. The simulation results of their infrared spectra were given based on Gaussian software, which were in good agreement with the experiment results. The rotation spectra and some perssad vibration spectra of these molecules were analyzed, and their absorption peaks were exactly identified. The components information was obtained by comparing the simulation results of different molecules.
Spectral types of four binaries based on photometric observations
NASA Astrophysics Data System (ADS)
Shimanskii, V. V.; Bikmaev, I. F.; Borisov, N. V.; Vlasyuk, V. V.; Galeev, A. I.; Sakhibullin, N. A.; Spiridonova, O. I.
2008-09-01
We present results of photometric and spectroscopic observations of four close binaries with subdwarf B components: PG 0918+029, PG 1000+408, PG 1116+301, PG 0001+275. We discovered that PG 1000+408 is a close binary, with the most probable orbital period being P orb = 1.041145 day. Based on a comparison of the observed light curves at selected orbital phases and theoretical predictions for their variations, all the systems are classified as doubly degenerate binaries with low-luminosity white-dwarf secondaries.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Xu, Q; Stanford University School of Medicine, Stanford, CA; Liu, H
Purpose: Spectral CT enabled by an energy-resolved photon-counting detector outperforms conventional CT in terms of material discrimination, contrast resolution, etc. One reconstruction method for spectral CT is to generate a color image from a reconstructed component in each energy channel. However, given the radiation dose, the number of photons in each channel is limited, which will result in strong noise in each channel and affect the final color reconstruction. Here we propose a novel dictionary learning method for spectral CT that combines dictionary-based sparse representation method and the patch based low-rank constraint to simultaneously improve the reconstruction in each channelmore » and to address the inter-channel correlations to further improve the reconstruction. Methods: The proposed method has two important features: (1) guarantee of the patch based sparsity in each energy channel, which is the result of the dictionary based sparse representation constraint; (2) the explicit consideration of the correlations among different energy channels, which is realized by patch-by-patch nuclear norm-based low-rank constraint. For each channel, the dictionary consists of two sub-dictionaries. One is learned from the average of the images in all energy channels, and the other is learned from the average of the images in all energy channels except the current channel. With average operation to reduce noise, these two dictionaries can effectively preserve the structural details and get rid of artifacts caused by noise. Combining them together can express all structural information in current channel. Results: Dictionary learning based methods can obtain better results than FBP and the TV-based method. With low-rank constraint, the image quality can be further improved in the channel with more noise. The final color result by the proposed method has the best visual quality. Conclusion: The proposed method can effectively improve the image quality of low-dose spectral CT. This work is partially supported by the National Natural Science Foundation of China (No. 61302136), and the Natural Science Basic Research Plan in Shaanxi Province of China (No. 2014JQ8317).« less
MIR and FIR Analysis of Inorganic Species in a Single Data Acquisition
NASA Astrophysics Data System (ADS)
Wang, Peng; Shilov, Sergey
2017-06-01
The extension of the mid IR towards the far IR spectral range below 400 \\wn is of great interest for molecular vibrational analysis for inorganic and organometallic chemistry, for geological, pharmaceutical, and physical applications, polymorph screening and crystallinity analysis as well as for matrix isolation spectroscopy. In these cases, the additional far infrared region offers insight to low energy vibrations which are observable only there. This includes inorganic species, lattice vibrations or intermolecular vibrations in the ordered solid state. The spectral range of a FTIR spectrometer is defined by the major optical components such as the source, beamsplitter, and detector. The globar source covers a broad spectral range from 8000 to 20 \\wn. However a bottle neck exists with respect to the beamsplitter and detector. To extend the spectral range further into the far IR and THz spectral ranges, one or more additional far IR beam splitters and detectors have been previously required. Two new optic components have been incorporated in a spectrometer to achieve coverage of both the mid and far infrared in a single scan: a wide range MIR-FIR beam splitter and the wide range DLaTGS detector that utilizes a diamond window. The use of a standard SiC IR source with these components yields a spectral range of 6000 down to 50 \\wn in one step for all types of transmittance, reflectance and ATR measurements. Utilizing the external water cooled mercury arc high power lamp the spectral range can be ultimately extended down to 10 \\wn. Examples of application will include emission in MIR-THz range, identification of pigments, additives in polymers, and polymorphism studies.
Spence, Jeffrey S; Brier, Matthew R; Hart, John; Ferree, Thomas C
2013-03-01
Linear statistical models are used very effectively to assess task-related differences in EEG power spectral analyses. Mixed models, in particular, accommodate more than one variance component in a multisubject study, where many trials of each condition of interest are measured on each subject. Generally, intra- and intersubject variances are both important to determine correct standard errors for inference on functions of model parameters, but it is often assumed that intersubject variance is the most important consideration in a group study. In this article, we show that, under common assumptions, estimates of some functions of model parameters, including estimates of task-related differences, are properly tested relative to the intrasubject variance component only. A substantial gain in statistical power can arise from the proper separation of variance components when there is more than one source of variability. We first develop this result analytically, then show how it benefits a multiway factoring of spectral, spatial, and temporal components from EEG data acquired in a group of healthy subjects performing a well-studied response inhibition task. Copyright © 2011 Wiley Periodicals, Inc.
Components for IFOG based inertial measurement units using active and passive polymer materials
NASA Astrophysics Data System (ADS)
Ashley, Paul R.; Temmen, Mark G.; Diffey, William M.; Sanghadasa, Mohan; Bramson, Michael D.; Lindsay, Geoffrey A.; Guenthner, Andrew J.
2006-08-01
Highly accurate, compact, and low cost inertial measurement units (IMUs) are needed for precision guidance in navigation systems. Active and passive polymer materials have been successfully used in fabricating two of the key guided-wave components, the phase modulator and the optical transceiver, for IMUs based on the interferometric fiber optic gyroscope (IFOG) technology. Advanced hybrid waveguide fabrication processes and novel optical integration techniques have been introduced. Backscatter compensated low loss phase modulators with low half-wave drive voltage (V π) have been fabricated with CLD- and FTC- type high performance electro-optic chromophores. A silicon-bench architecture has been used in fabricating high gain low noise transceivers with high optical power while maintaining the spectral quality and long lifetime. Gyro bias stability of less than 0.02 deg/hr has been demonstrated with these components. A review of the novel concepts introduced, fabrication and integration techniques developed and performance achieved are presented.
Computational electronics and electromagnetics
DOE Office of Scientific and Technical Information (OSTI.GOV)
Shang, C. C.
The Computational Electronics and Electromagnetics thrust area at Lawrence Livermore National Laboratory serves as the focal point for engineering R&D activities for developing computer-based design, analysis, and tools for theory. Key representative applications include design of particle accelerator cells and beamline components; engineering analysis and design of high-power components, photonics, and optoelectronics circuit design; EMI susceptibility analysis; and antenna synthesis. The FY-96 technology-base effort focused code development on (1) accelerator design codes; (2) 3-D massively parallel, object-oriented time-domain EM codes; (3) material models; (4) coupling and application of engineering tools for analysis and design of high-power components; (5) 3-D spectral-domainmore » CEM tools; and (6) enhancement of laser drilling codes. Joint efforts with the Power Conversion Technologies thrust area include development of antenna systems for compact, high-performance radar, in addition to novel, compact Marx generators. 18 refs., 25 figs., 1 tab.« less
Color image display and visual perception in computer graphics
NASA Astrophysics Data System (ADS)
Bouatouch, Kadi; Tellier, Pierre
1996-03-01
This paper put an emphasis on the importance of two points which are crucial when the aim is physically based lighting simulation. The first one is the spectral approach which considers emitted, reflected, diffused and transmitted light as wavelength dependent. The second corresponds to the different steps aiming at converting into RGB components the radiance arriving at the viewpoint through the pixels of a screen.
NASA Astrophysics Data System (ADS)
Mwaniki, M. W.; Kuria, D. N.; Boitt, M. K.; Ngigi, T. G.
2017-04-01
Image enhancements lead to improved performance and increased accuracy of feature extraction, recognition, identification, classification and hence change detection. This increases the utility of remote sensing to suit environmental applications and aid disaster monitoring of geohazards involving large areas. The main aim of this study was to compare the effect of image enhancement applied to synthetic aperture radar (SAR) data and Landsat 8 imagery in landslide identification and mapping. The methodology involved pre-processing Landsat 8 imagery, image co-registration, despeckling of the SAR data, after which Landsat 8 imagery was enhanced by Principal and Independent Component Analysis (PCA and ICA), a spectral index involving bands 7 and 4, and using a False Colour Composite (FCC) with the components bearing the most geologic information. The SAR data were processed using textural and edge filters, and computation of SAR incoherence. The enhanced spatial, textural and edge information from the SAR data was incorporated to the spectral information from Landsat 8 imagery during the knowledge based classification. The methodology was tested in the central highlands of Kenya, characterized by rugged terrain and frequent rainfall induced landslides. The results showed that the SAR data complemented Landsat 8 data which had enriched spectral information afforded by the FCC with enhanced geologic information. The SAR classification depicted landslides along the ridges and lineaments, important information lacking in the Landsat 8 image classification. The success of landslide identification and classification was attributed to the enhanced geologic features by spectral, textural and roughness properties.
Sun, Weifang; Yao, Bin; He, Yuchao; Chen, Binqiang; Zeng, Nianyin; He, Wangpeng
2017-08-09
Power generation using waste-gas is an effective and green way to reduce the emission of the harmful blast furnace gas (BFG) in pig-iron producing industry. Condition monitoring of mechanical structures in the BFG power plant is of vital importance to guarantee their safety and efficient operations. In this paper, we describe the detection of crack growth of bladed machinery in the BFG power plant via vibration measurement combined with an enhanced spectral correction technique. This technique enables high-precision identification of amplitude, frequency, and phase information (the harmonic information) belonging to deterministic harmonic components within the vibration signals. Rather than deriving all harmonic information using neighboring spectral bins in the fast Fourier transform spectrum, this proposed active frequency shift spectral correction method makes use of some interpolated Fourier spectral bins and has a better noise-resisting capacity. We demonstrate that the identified harmonic information via the proposed method is of suppressed numerical error when the same level of noises is presented in the vibration signal, even in comparison with a Hanning-window-based correction method. With the proposed method, we investigated vibration signals collected from a centrifugal compressor. Spectral information of harmonic tones, related to the fundamental working frequency of the centrifugal compressor, is corrected. The extracted spectral information indicates the ongoing development of an impeller blade crack that occurred in the centrifugal compressor. This method proves to be a promising alternative to identify blade cracks at early stages.
NASA Astrophysics Data System (ADS)
Beigi, Parmida; Salcudean, Tim; Rohling, Robert; Lessoway, Victoria A.; Ng, Gary C.
2015-03-01
This paper presents a new needle detection technique for ultrasound guided interventions based on the spectral properties of small displacements arising from hand tremour or intentional motion. In a block-based approach, the displacement map is computed for each block of interest versus a reference frame, using an optical flow technique. To compute the flow parameters, the Lucas-Kanade approach is used in a multiresolution and regularized form. A least-squares fit is used to estimate the flow parameters from the overdetermined system of spatial and temporal gradients. Lateral and axial components of the displacement are obtained for each block of interest at consecutive frames. Magnitude-squared spectral coherency is derived between the median displacements of the reference block and each block of interest, to determine the spectral correlation. In vivo images were obtained from the tissue near the abdominal aorta to capture the extreme intrinsic body motion and insertion images were captured from a tissue-mimicking agar phantom. According to the analysis, both the involuntary and intentional movement of the needle produces coherent displacement with respect to a reference window near the insertion site. Intrinsic body motion also produces coherent displacement with respect to a reference window in the tissue; however, the coherency spectra of intrinsic and needle motion are distinguishable spectrally. Blocks with high spectral coherency at high frequencies are selected, estimating a channel for needle trajectory. The needle trajectory is detected from locally thresholded absolute displacement map within the initial estimate. Experimental results show the RMS localization accuracy of 1:0 mm, 0:7 mm, and 0:5 mm for hand tremour, vibrational and rotational needle movements, respectively.
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.
SHJAR Jet Noise Data and Power Spectral Laws
NASA Technical Reports Server (NTRS)
Khavaran, Abbas; Bridges, James
2009-01-01
High quality jet noise spectral data measured at the Aeroacoustic Propulsion Laboratory at the NASA Glenn Research Center is used to examine a number of jet noise scaling laws. Configurations considered in the present study consist of convergent and convergent-divergent axisymmetric nozzles. The measured spectral data are shown in narrow band and cover 8193 equally spaced points in a typical Strouhal number range of 0.0 to 10.0. The measured data are reported as lossless (i.e., atmospheric attenuation is added to measurements), and at 24 equally spaced angles (50deg to 165deg) on a 100-diameter (200-in.) arc. Following the work of Viswanathan, velocity power factors are evaluated using a least squares fit on spectral power density as a function of jet temperature and observer angle. The goodness of the fit and the confidence margins for the two regression parameters are studied at each angle, and alternative relationships are proposed to improve the spectral collapse when certain conditions are met. As an immediate application of the velocity power laws, spectral density in shockcontaining jets are decomposed into components attributed to jet mixing noise and shock noise. From this analysis, jet noise prediction tools can be developed with different spectral components derived from different physics.
MIR and NIR group spectra of n-alkanes and 1-chloroalkanes.
Kwaśniewicz, Michał; Czarnecki, Mirosław A
2015-05-15
Numerous attempts were undertaken to resolve the absorption originating from different parts of alkanes. The separation of the contributions from the terminal and midchain methylene units was observed only in the spectra of solid alkanes at low temperatures. On the other hand, for liquid alkanes this effect was not reported as yet. In this study, ATR-IR, Raman and NIR spectra of eight n-alkanes and seven 1-chloroalkanes in the liquid phase were measured from 1000 to 12,000cm(-1). The spectra were analyzed by using two-dimensional (2D) correlation approach and chemometrics methods. It was shown that in 2D asynchronous contour plots, constructed from the spectra of n-alkanes and 1-chloroalkanes, the methylene band was resolved into two components. These two components were assigned to the terminal and midchain methylene groups. For the first time, the contributions from these two molecular fragments were resolved in the spectra of liquid n-alkanes and 1-chloroalkanes. MCR-ALS resolved these spectra into two components that were assigned to the ethyl and midchain methylene groups. These components represent the group spectra that can be used for assignment, spectral analysis and prediction of unknown spectra. The spectral prediction based on the group spectra provides very good results for n-alkanes, especially in the first and second overtone regions. Copyright © 2015 Elsevier B.V. All rights reserved.
MJO Signals in Latent Heating: Results from TRMM Retrievals
NASA Technical Reports Server (NTRS)
Zhang, Chidong; Ling, Jian; Hagos, Samson; Tao, Wei-Kuo; Lang, Steve; Takayabu, Yukari N.; Shige, Shoichi; Katsumata, Masaki; Olson, William S.; L'Ecuyer, Tristan
2010-01-01
The Madden-Julian Oscillation (MJO) is the dominant intraseasonal signal in the global tropical atmosphere. Almost all numerical climate models have difficulty to simulate realistic MJO. Four TRMM datasets of latent heating were diagnosed for signals in the MJO. In all four datasets, vertical structures of latent heating are dominated by two components, one deep with its peak above the melting level and one shallow with its peak below. Profiles of the two components are nearly ubiquitous in longitude, allowing a separation of the vertical and zonal/temporal variations when the latitudinal dependence is not considered. All four datasets exhibit robust MJO spectral signals in the deep component as eastward propagating spectral peaks centered at period of 50 days and zonal wavenumber 1, well distinguished from lower- and higher-frequency power and much stronger than the corresponding westward power. The shallow component shows similar but slightly less robust MJO spectral peaks. MJO signals were further extracted from a combination of band-pass (30 - 90 day) filtered deep and shallow components. Largest amplitudes of both deep and shallow components of the MJO are confined to the Indian and western Pacific Oceans. There is a local minimum in the deep components over the Maritime Continent. The shallow components of the MJO differ substantially among the four TRMM datasets in their detailed zonal distributions in the eastern hemisphere. In composites of the heating evolution through the life cycle of the MJO, the shallow components lead the deep ones in some datasets and at certain longitudes. In many respects, the four TRMM datasets agree well in their deep components, but not in their shallow components and the phase relations between the deep and shallow components. These results indicate that caution must be exercised in applications of these latent heating data.
Utilization of all Spectral Channels of IASI for the Retrieval of the Atmospheric State
NASA Astrophysics Data System (ADS)
Del Bianco, S.; Cortesi, U.; Carli, B.
2010-12-01
The retrieval of atmospheric state parameters from broadband measurements acquired by high spectral resolution sensors, such as the Infrared Atmospheric Sounding Interferometer (IASI) onboard the Meteorological Operational (MetOp) platform, generally requires to deal with a prohibitively large number of spectral elements available from a single observation (8461 samples in the case of IASI, covering the 645-2760 cm-1 range with a resolution of 0.5 cm-1 and a spectral sampling of 0.25 cm-1). Most inversion algorithms developed for both operational and scientific analysis of IASI spectra perform a reduction of the data - typically based on channel selection, super-channel clustering or Principal Component Analysis (PCA) techniques - in order to handle the high dimensionality of the problem. Accordingly, simultaneous processing of all IASI channels received relatively low attention. Here we prove the feasibility of a retrieval approach exploiting all spectral channels of IASI, to extract information on water vapor, temperature and ozone profiles. This multi-target retrieval removes the systematic errors due to interfering parameters and makes the channel selection no longer necessary. The challenging computation is made possible by the use of a coarse spectral grid for the forward model calculation and by the abatement of the associated modeling errors through the use of a variance-covariance matrix of the residuals that takes into account all the forward model errors.
The Spectral Energy Distribution of Fermi bright blazars
Abdo, A. A.; Ackermann, M.; Agudo, I.; ...
2010-05-13
We have conducted a detailed investigation of the broadband spectral properties of the γ-ray selected blazars of the Fermi LAT Bright AGN Sample (LBAS). By combining our accurately estimated Fermi γ-ray spectra with Swift, radio, infra-red, optical, and other hard X-ray/γ-ray data, collected within 3 months of the LBAS data taking period, we were able to assemble high-quality and quasi-simultaneous spectral energy distributions (SED) for 48 LBAS blazars. The SED of these γ-ray sources is similar to that of blazars discovered at other wavelengths, clearly showing, in the usual log ν-log ν F ν representation, the typical broadband spectral signaturesmore » normally attributed to a combination of low-energy synchrotron radiation followed by inverse Compton emission of one or more components. Here, we have used these SED to characterize the peak intensity of both the low- and the high-energy components. The results have been used to derive empirical relationships that estimate the position of the two peaks from the broadband colors (i.e., the radio to optical, α ro, and optical to X-ray, α ox, spectral slopes) and from the γ-ray spectral index. Our data show that the synchrotron peak frequency (ν S peak) is positioned between 10 12.5 and 10 14.5 Hz in broad-lined flat spectrum radio quasars (FSRQs) and between 10 13 and 10 17 Hz in featureless BL Lacertae objects. We find that the γ-ray spectral slope is strongly correlated with the synchrotron peak energy and with the X-ray spectral index, as expected at first order in synchrotron-inverse Compton scenarios. However, simple homogeneous, one-zone, synchrotron self-Compton (SSC) models cannot explain most of our SED, especially in the case of FSRQs and low energy peaked (LBL) BL Lacs. More complex models involving external Compton radiation or multiple SSC components are required to reproduce the overall SED and the observed spectral variability. While more than 50% of known radio bright high energy peaked (HBL) BL Lacs are detected in the LBAS sample, only less than 13% of known bright FSRQs and LBL BL Lacs are included. This suggests that the latter sources, as a class, may be much fainter γ-ray emitters than LBAS blazars, and could in fact radiate close to the expectations of simple SSC models. We categorized all our sources according to a new physical classification scheme based on the generally accepted paradigm for Active Galactic Nuclei and on the results of this SED study. Since the LAT detector is more sensitive to flat spectrum γ-ray sources, the correlation between ν S peak and γ-ray spectral index strongly favors the detection of high energy peaked blazars, thus explaining the Fermi overabundance of this type of sources compared to radio and EGRET samples. Finally, this selection effect is similar to that experienced in the soft X-ray band where HBL BL Lacs are the dominant type of blazars.« less
The Spectral Energy Distribution of Fermi Bright Blazars
NASA Technical Reports Server (NTRS)
Abdo, A. A.; Ackermann, M.; Agudo, I.; Ajello, M.; Aller, H. D.; Aller, M. F.; Angelakis, E.; Arkharov, A. A.; Axelsson, M.; Bach, U.;
2010-01-01
We have conducted a detailed investigation of the broadband spectral properties of the gamma-ray selected blazars of the Fermi LAT Bright AGN Sample (LBAS). By combining our accurately estimated Fermi gamma-ray spectra with Swift, radio, infra-red, optical, and other hard X-ray /gamma-ray data, collected within 3 months of the LBAS data taking period, we were able to assemble high-quality and quasi-simultaneous spectral energy distributions (SED) for 48 LBAS blazars. The SED of these gamma-ray sources is similar to that of blazars discovered at other wavelengths, clearly showing, in the usual log v-log v Fv representation, the typical broadband spectral signatures normally attributed to a combination of low-energy synchrotron radiation followed by inverse Compton emission of one or more components. We have used these SED to characterize the peak intensity of both the low- and the high-energy components. The results have been used to derive empirical relationships that estimate the position of the two peaks from the broadband colors (i.e., the radio to optical, alpha(sub ro) , and optical to X-ray, alpha(sub ox), spectral slopes) and from the gamma-ray spectral index. Our data show that the synchrotron peak frequency (v(sup S) (sub peak)) is positioned between 10(exp 12.5) and 10(exp 14) Hz in broad-lined flat spectrum radio quasars (FSRQs) and between 10(exp 13) and 10(exp 17) Hz in featureless BL Lacertae objects. We find that the gamma-ray spectral slope is strongly correlated with the synchrotron peak energy and with the X-ray spectral index, as expected at first order in synchrotron-inverse Compton scenarios. However, simple homogeneous, one-zone, synchrotron self-Compton (SSC) models cannot explain most of our SED, especially in the case of FSRQs and low energy peaked (LBL) BL Lacs. More complex models involving external Compton radiation or multiple SSC components are required to reproduce the overall SED and the observed spectral variability. While more than 50% of known radio bright high energy peaked (HBL) BL Lacs are detected in the LBAS sample, only less than 13% of known bright FSRQs and LBL BL Lacs are included. This suggests that the latter sources, as a class, may be much fainter gamma-ray emitters than LBAS blazars, and could in fact radiate close to the expectations of simple SSC models. We categorized all our sources according to a new physical classification scheme based on the generally accepted paradigm for Active Galactic Nuclei and on the results of this SED study. Since the LAT detector is more sensitive to flat spectrum gamma-ray sources, the correlation between v(sup S) (sub peak) and gamma-ray spectral index strongly favors the detection of high energy peaked blazars, thus explaining the Fermi overabundance of this type of sources compared to radio and EGRET samples. This selection effect is similar to that experienced in the soft X-ray band where HBL BL Lacs are the dominant type of blazars.
The Rhythm of Fairall 9. I. Observing the Spectral Variability With XMM-Newton and NuSTAR
NASA Technical Reports Server (NTRS)
Lohfink, A. M.; Reynolds, S. C.; Pinto, C.; Alston, W.; Boggs, S. E.; Christensen, F. E.; Craig, W. W.; Fabian, A.C; Hailey, C. J.; Harrison, F. A.;
2016-01-01
We present a multi-epoch X-ray spectral analysis of the Seyfert 1 galaxy Fairall 9. Our analysis shows that Fairall 9 displays unique spectral variability in that its ratio residuals to a simple absorbed power law in the 0.510 keV band remain constant with time in spite of large variations in flux. This behavior implies an unchanging source geometry and the same emission processes continuously at work at the timescale probed. With the constraints from NuSTAR on the broad-band spectral shape, it is clear that the soft excess in this source is a superposition of two different processes, one being blurred ionized reflection in the innermost parts of the accretion disk, and the other a continuum component such as a spatially distinct Comptonizing region. Alternatively, a more complex primary Comptonization component together with blurred ionized reflection could be responsible.
NASA Astrophysics Data System (ADS)
Chernomyrdin, Nikita V.; Zaytsev, Kirill I.; Lesnichaya, Anastasiya D.; Kudrin, Konstantin G.; Cherkasova, Olga P.; Kurlov, Vladimir N.; Shikunova, Irina A.; Perchik, Alexei V.; Yurchenko, Stanislav O.; Reshetov, Igor V.
2016-09-01
In present paper, an ability to differentiate basal cell carcinoma (BCC) and healthy skin by combining multi-spectral autofluorescence imaging, principle component analysis (PCA), and linear discriminant analysis (LDA) has been demonstrated. For this purpose, the experimental setup, which includes excitation and detection branches, has been assembled. The excitation branch utilizes a mercury arc lamp equipped with a 365-nm narrow-linewidth excitation filter, a beam homogenizer, and a mechanical chopper. The detection branch employs a set of bandpass filters with the central wavelength of spectral transparency of λ = 400, 450, 500, and 550 nm, and a digital camera. The setup has been used to study three samples of freshly excised BCC. PCA and LDA have been implemented to analyze the data of multi-spectral fluorescence imaging. Observed results of this pilot study highlight the advantages of proposed imaging technique for skin cancer diagnosis.
Fabry-Perot interferometer measurement of static temperature and velocity for ASTOVL model tests
NASA Technical Reports Server (NTRS)
Kourous, Helen E.; Seacholtz, Richard G.
1995-01-01
A spectrally resolved Rayleigh/Mie scattering diagnostic was developed to measure temperature and wing-spanwise velocity in the vicinity of an ASTOVL aircraft model in the Lewis 9 x 15 Low Speed Wind Tunnel. The spectrum of argon-ion laser light scattered by the air molecules and particles in the flow was resolved with a Fabry-Perot interferometer. Temperature was extracted from the spectral width of the Rayleigh scattering component, and spanwise gas velocity from the gross spectral shift. Nozzle temperature approached 800 K, and the velocity component approached 30 m/s. The measurement uncertainty was about 5 percent for the gas temperature, and about 10 m/s for the velocity. The large difference in the spectral width of the Mie scattering from particles and the Rayleigh scattering from gas molecules allowed the gas temperature to be measured in flow containing both naturally occurring dust and LDV seed (both were present).
NASA Astrophysics Data System (ADS)
Li, Jiangtong; Luo, Yongdao; Dai, Honglin
2018-01-01
Water is the source of life and the essential foundation of all life. With the development of industrialization, the phenomenon of water pollution is becoming more and more frequent, which directly affects the survival and development of human. Water quality detection is one of the necessary measures to protect water resources. Ultraviolet (UV) spectral analysis is an important research method in the field of water quality detection, which partial least squares regression (PLSR) analysis method is becoming predominant technology, however, in some special cases, PLSR's analysis produce considerable errors. In order to solve this problem, the traditional principal component regression (PCR) analysis method was improved by using the principle of PLSR in this paper. The experimental results show that for some special experimental data set, improved PCR analysis method performance is better than PLSR. The PCR and PLSR is the focus of this paper. Firstly, the principal component analysis (PCA) is performed by MATLAB to reduce the dimensionality of the spectral data; on the basis of a large number of experiments, the optimized principal component is extracted by using the principle of PLSR, which carries most of the original data information. Secondly, the linear regression analysis of the principal component is carried out with statistic package for social science (SPSS), which the coefficients and relations of principal components can be obtained. Finally, calculating a same water spectral data set by PLSR and improved PCR, analyzing and comparing two results, improved PCR and PLSR is similar for most data, but improved PCR is better than PLSR for data near the detection limit. Both PLSR and improved PCR can be used in Ultraviolet spectral analysis of water, but for data near the detection limit, improved PCR's result better than PLSR.
NASA Astrophysics Data System (ADS)
D'Sa, E. J.; Kim, H. C.; Ha, S. Y.
2016-12-01
Colored dissolved organic matter (CDOM) spectral absorption and excitation-emission matrix (EEMs) fluorescence with parallel factor analysis (PARAFAC) were examined in the Ross Sea during a survey conducted on board the R/V Araon in the austral summer of 14/15. CDOM absorption at 355 nm ranged from 0.06 to 1.14 m-1 while spectral slope S calculated between 275-295 nm wavelength ranged from 18.83 to 33.32 µm-1 with water masses playing an important role in its variability. Spectral slope S decreased with increasing CDOM absorption indicating the strong role of photo-oxidation on CDOM abundance during the summer. PARAFAC analysis of EEM data identified two humic-like (terrestrial and marine-like) and a protein-like (tryptophan-like) component. The two humic-like components were well correlated with little variability spatially and across the water column ( 0-100 m) likely indicating more refractory material. The protein-like fluorescent component was relatively quite variable supporting the autochthonous production of this fluorescent component in the highly productive Ross Sea waters.
Multivariate Analysis of Solar Spectral Irradiance Measurements
NASA Technical Reports Server (NTRS)
Pilewskie, P.; Rabbette, M.
2001-01-01
Principal component analysis is used to characterize approximately 7000 downwelling solar irradiance spectra retrieved at the Southern Great Plains site during an Atmospheric Radiation Measurement (ARM) shortwave intensive operating period. This analysis technique has proven to be very effective in reducing a large set of variables into a much smaller set of independent variables while retaining the information content. It is used to determine the minimum number of parameters necessary to characterize atmospheric spectral irradiance or the dimensionality of atmospheric variability. It was found that well over 99% of the spectral information was contained in the first six mutually orthogonal linear combinations of the observed variables (flux at various wavelengths). Rotation of the principal components was effective in separating various components by their independent physical influences. The majority of the variability in the downwelling solar irradiance (380-1000 nm) was explained by the following fundamental atmospheric parameters (in order of their importance): cloud scattering, water vapor absorption, molecular scattering, and ozone absorption. In contrast to what has been proposed as a resolution to a clear-sky absorption anomaly, no unexpected gaseous absorption signature was found in any of the significant components.
NASA Technical Reports Server (NTRS)
Lubin, Dan
2001-01-01
This study has used a combination of ocean color, backscattered ultraviolet, and passive microwave satellite data to investigate the impact of the springtime Antarctic ozone depletion on the base of the Antarctic marine food web - primary production by phytoplankton. Spectral ultraviolet (UV) radiation fields derived from the satellite data are propagated into the water column where they force physiologically-based numerical models of phytoplankton growth. This large-scale study has been divided into two components: (1) the use of Total Ozone Mapping Spectrometer (TOMS) and Special Sensor Microwave Imager (SSM/I) data in conjunction with radiative transfer theory to derive the surface spectral UV irradiance throughout the Southern Ocean; and (2) the merging of these UV irradiances with the climatology of chlorophyll derived from SeaWiFS data to specify the input data for the physiological models.
Sakhteman, Amirhossein; Faridi, Pouya; Daneshamouz, Saeid; Akbarizadeh, Amin Reza; Borhani-Haghighi, Afshin; Mohagheghzadeh, Abdolali
2017-01-01
Herbal oils have been widely used in Iran as medicinal compounds dating back to thousands of years in Iran. Chamomile oil is widely used as an example of traditional oil. We remade chamomile oils and tried to modify it with current knowledge and facilities. Six types of oil (traditional and modified) were prepared. Microbial limit tests and physicochemical tests were performed on them. Also, principal component analysis, hierarchical cluster analysis, and partial least squares discriminant analysis were done on the spectral data of attenuated total reflectance–infrared in order to obtain insight based on classification pattern of the samples. The results show that we can use modified versions of the chamomile oils (modified Clevenger-type apparatus method and microwave method) with the same content of traditional ones and with less microbial contaminations and better physicochemical properties. PMID:28585466
Zargaran, Arman; Sakhteman, Amirhossein; Faridi, Pouya; Daneshamouz, Saeid; Akbarizadeh, Amin Reza; Borhani-Haghighi, Afshin; Mohagheghzadeh, Abdolali
2017-10-01
Herbal oils have been widely used in Iran as medicinal compounds dating back to thousands of years in Iran. Chamomile oil is widely used as an example of traditional oil. We remade chamomile oils and tried to modify it with current knowledge and facilities. Six types of oil (traditional and modified) were prepared. Microbial limit tests and physicochemical tests were performed on them. Also, principal component analysis, hierarchical cluster analysis, and partial least squares discriminant analysis were done on the spectral data of attenuated total reflectance-infrared in order to obtain insight based on classification pattern of the samples. The results show that we can use modified versions of the chamomile oils (modified Clevenger-type apparatus method and microwave method) with the same content of traditional ones and with less microbial contaminations and better physicochemical properties.
Sid'ko, A F; Botvich, I Yu; Pisman, T I; Shevyrnogov, A P
2015-01-01
The paper presents analysis of a study of the polarized component of the reflectance factor (Rq) and the degree of polarization (P) of wheat and maize crops depending on the wavelength. Registration of polarization characteristics was carried out in the field from the elevated work platform at heights of 10 to 18 m in June and July. Measurements were performed using a double-beam spectrophotometer with a polarized light filter attachment, within the spectral range from 400 to 820-nm. The viewing angle was no greater than 20 degree with respect to the nadir. The reflection spectra of wheat and maize crops obtained using a polarizer adjusted to transmit the maximum and minimum amounts of light (R(max) and R(min)) were studied. Based on these reflection spectra polarization characteristics, which. differ in the visible and infrared spectral region, were determined and analyzed.
NASA Astrophysics Data System (ADS)
Liu, Tingting; Liu, Hai; Chen, Zengzhao; Chen, Yingying; Wang, Shengming; Liu, Zhi; Zhang, Hao
2018-05-01
Infrared (IR) spectra are the fingerprints of the molecules, and the spectral band location closely relates to the structure of a molecule. Thus, specimen identification can be performed based on IR spectroscopy. However, spectrally overlapping components prevent the specific identification of hyperfine molecular information of different substances. In this paper, we propose a fast blind reconstruction approach for IR spectra, which is based on sparse and redundant representations over a dictionary. The proposed method recovers the spectrum with the discrete wavelet transform dictionary on its content. The experimental results demonstrate that the proposed method is superior because of the better performance when compared with other state-of-the-art methods. The method the authors used remove the instrument aging issue to a large extent, thus leading the reconstruction IR spectra a more convenient tool for extracting features of an unknown material and interpreting it.
Origins of spectral broadening of incoherent waves: Catastrophic process of coherence degradation
NASA Astrophysics Data System (ADS)
Xu, G.; Garnier, J.; Rumpf, B.; Fusaro, A.; Suret, P.; Randoux, S.; Kudlinski, A.; Millot, G.; Picozzi, A.
2017-08-01
We revisit the mechanisms underlying the process of spectral broadening of incoherent optical waves propagating in nonlinear media on the basis of nonequilibrium thermodynamic considerations. A simple analysis reveals that a prerequisite for the existence of a significant spectral broadening of the waves is that the linear part of the energy (Hamiltonian) has different contributions of opposite signs. It turns out that, at variance with the expected soliton turbulence scenario, an increase of the amount of disorder (incoherence) in the system does not require the generation of a coherent soliton structure. We illustrate the idea by considering the propagation of two wave components in an optical fiber with opposite dispersion coefficients. A wave turbulence approach to the problem reveals that the increase of kinetic energy in one component is offset by the negative reduction in the other component, so that the waves exhibit, as a general rule, virtually unlimited spectral broadening. More precisely, a self-similar solution of the kinetic equations reveals that the spectra of the incoherent waves tend to relax toward a homogeneous distribution in the wake of a front that propagates in frequency space with a decelerating velocity. We discuss this catastrophic process of spectral broadening in the light of different important phenomena, in particular supercontinuum generation, soliton turbulence, wave condensation, and the runaway motion of mechanical systems composed of positive and negative masses.
Liu, Lianghong; Zhang, Jiayu; Zheng, Binjie; Guan, Ying; Wang, Liting; Chen, Lei; Cai, Wei
2018-04-01
Duhaldea nervosa (Wallich ex Candolle) A. Anderberg has been traditionally used as a food spice and also in folk medicine for treating traumatic injury and relieving rheumatism, especially accelerating the healing of a fracture. However, so far as we are aware, the chemical constituents have not been fully investigated. In this study, a practical method of mass spectral trees similarity filter, a data-mining technique, was developed and evaluated for the rapid detection and identification complicated constituents based on ultra-high-performance liquid chromatography-linear trap quadropole-Orbitrap-mass spectrometry. Finally, a total of 47 chlorogenic acids, including 19 monoacyl-quinic acids, 22 diacyl-quinic acids, and six triacyl-quinic acids, were unambiguously or tentatively identified based on their accurate mass measurement, chromatographic retention, MS n spectra, and bibliography data. To our best knowledge, it is the first time to report the chlorogenic acids of D. nervosa, which would be beneficial for the further material basis and quality research. Meanwhile, this mass spectral trees similarity filter method could be envisioned to exhibit a wide application for the identification of complicated components from botanical extracts. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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.
Moran, M.S.; Jackson, R. D.; Raymond, L.H.; Gay, L.W.; Slater, P.N.
1989-01-01
Surface energy balance components were evaluated by combining satellite-based spectral data with on-site measurements of solar irradiance, air temperature, wind speed, and vapor pressure. Maps of latent heat flux density (??E) and net radiant flux density (Rn) were produced using Landsat Thematic Mapper (TM) data for three dates: 23 July 1985, 5 April 1986, and 24 June 1986. On each date, a Bowen-ratio apparatus, located in a vegetated field, was used to measure ??E and Rn at a point within the field. Estimates of ??E and Rn were also obtained using radiometers aboard an aircraft flown at 150 m above ground level. The TM-based estimates differed from the Bowen-ratio and aircraft-based estimates by less than 12 % over mature fields of cotton, wheat, and alfalfa, where ??E and Rn ranged from 400 to 700 Wm-2. ?? 1989.
An integrtated approach to the use of Landsat TM data for gold exploration in west central Nevada
NASA Technical Reports Server (NTRS)
Mouat, D. A.; Myers, J. S.; Miller, N. L.
1987-01-01
This paper represents an integration of several Landsat TM image processing techniques with other data to discriminate the lithologies and associated areas of hydrothermal alteration in the vicinity of the Paradise Peak gold mine in west central Nevada. A microprocessor-based image processing system and an IDIMS system were used to analyze data from a 512 X 512 window of a Landsat-5 TM scene collected on June 30, 1984. Image processing techniques included simple band composites, band ratio composites, principal components composites, and baseline-based composites. These techniques were chosen based on their ability to discriminate the spectral characteristics of the products of hydrothermal alteration as well as of the associated regional lithologies. The simple band composite, ratio composite, two principal components composites, and the baseline-based composites separately can define the principal areas of alteration. Combined, they provide a very powerful exploration tool.
Remotely sensed and laboratory spectral signatures of an ocean-dumped acid waste
NASA Technical Reports Server (NTRS)
Lewis, B. W.; Collins, V. G.
1977-01-01
An ocean-dumped acid waste plume was studied by using a rapid scanning spectrometer to remotely measure ocean radiance from a helicopter. The results of these studies are presented and compared with results from sea truth samples and laboratory experiments. An ocean spectral reflectance signature and a laboratory spectral transmission signature were established for the iron-acid waste pollutant. The spectrally and chemically significant component of the acid waste pollutant was determined to be ferric iron.
NASA Astrophysics Data System (ADS)
Hegazy, Maha A.; Abdelwahab, Nada S.; Fayed, Ahmed S.
2015-04-01
A novel method was developed for spectral resolution and further determination of five-component mixture including Vitamin B complex (B1, B6, B12 and Benfotiamine) along with the commonly co-formulated Diclofenac. The method is simple, sensitive, precise and could efficiently determine the five components by a complementary application of two different techniques. The first is univariate second derivative method that was successfully applied for determination of Vitamin B12. The second is Multivariate Curve Resolution using the Alternating Least Squares method (MCR-ALS) by which an efficient resolution and quantitation of the quaternary spectrally overlapped Vitamin B1, Vitamin B6, Benfotiamine and Diclofenac sodium were achieved. The effect of different constraints was studied and the correlation between the true spectra and the estimated spectral profiles were found to be 0.9998, 0.9983, 0.9993 and 0.9933 for B1, B6, Benfotiamine and Diclofenac, respectively. All components were successfully determined in tablets and capsules and the results were compared to HPLC methods and they were found to be statistically non-significant.
Spectral Optical Readout of Rectangular–Miniature Hollow Glass Tubing for Refractive Index Sensing
Rigamonti, Giulia; Bello, Valentina
2018-01-01
For answering the growing demand of innovative micro-fluidic devices able to measure the refractive index of samples in extremely low volumes, this paper presents an overview of the performances of a micro-opto-fluidic sensing platform that employs rectangular, miniature hollow glass tubings. The operating principle is described by showing the analytical model of the tubing, obtained as superposition of different optical cavities, and the optical readout method based on spectral reflectivity detection. We have analyzed, in particular, the theoretical and experimental optical features of rectangular tubings with asymmetrical geometry, thus with channel depth larger than the thickness of the glass walls, though all of them in the range of a few tens of micrometers. The origins of the complex line-shape of the spectral response in reflection, due to the different cavities formed by the tubing flat walls and channel, have been investigated using a Fourier transform analysis. The implemented instrumental configuration, based on standard telecom fiberoptic components and a semiconductor broadband optical source emitting in the near infrared wavelength region centered at 1.55 µm, has allowed acquisition of reflectivity spectra for experimental verification of the expected theoretical behavior. We have achieved detection of refractive index variations related to the change of concentration of glucose-water solutions flowing through the tubing by monitoring the spectral shift of the optical resonances. PMID:29462907
Spectral Optical Readout of Rectangular-Miniature Hollow Glass Tubing for Refractive Index Sensing.
Rigamonti, Giulia; Bello, Valentina; Merlo, Sabina
2018-02-16
For answering the growing demand of innovative micro-fluidic devices able to measure the refractive index of samples in extremely low volumes, this paper presents an overview of the performances of a micro-opto-fluidic sensing platform that employs rectangular, miniature hollow glass tubings. The operating principle is described by showing the analytical model of the tubing, obtained as superposition of different optical cavities, and the optical readout method based on spectral reflectivity detection. We have analyzed, in particular, the theoretical and experimental optical features of rectangular tubings with asymmetrical geometry, thus with channel depth larger than the thickness of the glass walls, though all of them in the range of a few tens of micrometers. The origins of the complex line-shape of the spectral response in reflection, due to the different cavities formed by the tubing flat walls and channel, have been investigated using a Fourier transform analysis. The implemented instrumental configuration, based on standard telecom fiberoptic components and a semiconductor broadband optical source emitting in the near infrared wavelength region centered at 1.55 µm, has allowed acquisition of reflectivity spectra for experimental verification of the expected theoretical behavior. We have achieved detection of refractive index variations related to the change of concentration of glucose-water solutions flowing through the tubing by monitoring the spectral shift of the optical resonances.
NASA Technical Reports Server (NTRS)
Scaife, Bradley James
1999-01-01
In any satellite communication, the Doppler shift associated with the satellite's position and velocity must be calculated in order to determine the carrier frequency. If the satellite state vector is unknown then some estimate must be formed of the Doppler-shifted carrier frequency. One elementary technique is to examine the signal spectrum and base the estimate on the dominant spectral component. If, however, the carrier is spread (as in most satellite communications) this technique may fail unless the chip rate-to-data rate ratio (processing gain) associated with the carrier is small. In this case, there may be enough spectral energy to allow peak detection against a noise background. In this thesis, we present a method to estimate the frequency (without knowledge of the Doppler shift) of a spread-spectrum carrier assuming a small processing gain and binary-phase shift keying (BPSK) modulation. Our method relies on an averaged discrete Fourier transform along with peak detection on spectral match filtered data. We provide theory and simulation results indicating the accuracy of this method. In addition, we will describe an all-digital hardware design based around a Motorola DSP56303 and high-speed A/D which implements this technique in real-time. The hardware design is to be used in NMSU's implementation of NASA's demand assignment, multiple access (DAMA) service.
Derivative component analysis for mass spectral serum proteomic profiles.
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.
Low-Frequency Components in Rat Pial Arteriolar Rhythmic Diameter Changes.
Lapi, Dominga; Mastantuono, Teresa; Di Maro, Martina; Varanini, Maurizio; Colantuoni, Antonio
2017-01-01
This study aimed to analyze the frequency components present in spontaneous rhythmic diameter changes in rat pial arterioles. Pial microcirculation was visualized by fluorescence microscopy. Rhythmic luminal variations were evaluated via computer-assisted methods. Spectral analysis was carried out on 30-min recordings under baseline conditions and after administration of acetylcholine (Ach), papaverine (Pap), Nω-nitro-L-arginine (L-NNA) prior to Ach, indomethacin (INDO), INDO prior to Ach, charybdotoxin and apamin, and charybdotoxin and apamin prior to Ach. Under baseline conditions all arteriolar orders showed 3 frequency components in the ranges of 0.0095-0.02, 0.02-0.06, and 0.06-0.2 Hz, another 2 in the ranges of 0.2-2.0 and 2.5-4.5 Hz, and another ultra-low-frequency component in the range of 0.001-0.0095 Hz. Ach caused a significant increase in the spectral density of the frequency components in the range of 0.001-0.2 Hz. Pap was able to slightly increase spectral density in the ranges of 0.001-0.0095 and 0.0095-0.02 Hz. L-NNA mainly attenuated arteriolar responses to Ach. INDO prior to Ach did not affect the endothelial response to Ach. Charybdotoxin and apamin, suggested as endothelium-derived hyperpolarizing factor inhibitors, reduced spectral density in the range of 0.001-0.0095 Hz before and after Ach administration. In conclusion, regulation of the blood flow distribution is due to several mechanisms, one of which is affected by charibdotoxin and apamin, modulating the vascular tone. © 2017 S. Karger AG, Basel.
NASA Astrophysics Data System (ADS)
Crockett, R. G. M.; Perrier, F.; Richon, P.
2009-04-01
Building on independent investigations by research groups at both IPGP, France, and the University of Northampton, UK, hourly-sampled radon time-series of durations exceeding one year have been investigated for periodic and anomalous phenomena using a variety of established and novel techniques. These time-series have been recorded in locations having no routine human behaviour and thus are effectively free of significant anthropogenic influences. With regard to periodic components, the long durations of these time-series allow, in principle, very high frequency resolutions for established spectral-measurement techniques such as Fourier and maximum-entropy. However, as has been widely observed, the stochastic nature of radon emissions from rocks and soils, coupled with sensitivity to a wide variety influences such as temperature, wind-speed and soil moisture-content has made interpretation of the results obtained by such techniques very difficult, with uncertain results, in many cases. We here report developments in the investigation of radon-time series for periodic and anomalous phenomena using spectral-decomposition techniques. These techniques, in variously separating ‘high', ‘middle' and ‘low' frequency components, effectively ‘de-noise' the data by allowing components of interest to be isolated from others which (might) serve to obscure weaker information-containing components. Once isolated, these components can be investigated using a variety of techniques. Whilst this is very much work in early stages of development, spectral decomposition methods have been used successfully to indicate the presence of diurnal and sub-diurnal cycles in radon concentration which we provisionally attribute to tidal influences. Also, these methods have been used to enhance the identification of short-duration anomalies, attributable to a variety of causes including, for example, earthquakes and rapid large-magnitude changes in weather conditions. Keywords: radon; earthquakes; tidal-influences; anomalies; time series; spectral-decomposition.
Conjugation of fiber-coupled wide-band light sources and acousto-optical spectral elements
NASA Astrophysics Data System (ADS)
Machikhin, Alexander; Batshev, Vladislav; Polschikova, Olga; Khokhlov, Demid; Pozhar, Vitold; Gorevoy, Alexey
2017-12-01
Endoscopic instrumentation is widely used for diagnostics and surgery. The imaging systems, which provide the hyperspectral information of the tissues accessible by endoscopes, are particularly interesting and promising for in vivo photoluminescence diagnostics and therapy of tumour and inflammatory diseases. To add the spectral imaging feature to standard video endoscopes, we propose to implement acousto-optical (AO) filtration of wide-band illumination of incandescent-lamp-based light sources. To collect maximum light and direct it to the fiber-optic light guide inside the endoscopic probe, we have developed and tested the optical system for coupling the light source, the acousto-optical tunable filter (AOTF) and the light guide. The system is compact and compatible with the standard endoscopic components.
Tunable thin-film optical filters for hyperspectral microscopy
NASA Astrophysics Data System (ADS)
Favreau, Peter F.; Rich, Thomas C.; Prabhat, Prashant; Leavesley, Silas J.
2013-02-01
Hyperspectral imaging was originally developed for use in remote sensing applications. More recently, it has been applied to biological imaging systems, such as fluorescence microscopes. The ability to distinguish molecules based on spectral differences has been especially advantageous for identifying fluorophores in highly autofluorescent tissues. A key component of hyperspectral imaging systems is wavelength filtering. Each filtering technology used for hyperspectral imaging has corresponding advantages and disadvantages. Recently, a new optical filtering technology has been developed that uses multi-layered thin-film optical filters that can be rotated, with respect to incident light, to control the center wavelength of the pass-band. Compared to the majority of tunable filter technologies, these filters have superior optical performance including greater than 90% transmission, steep spectral edges and high out-of-band blocking. Hence, tunable thin-film optical filters present optical characteristics that may make them well-suited for many biological spectral imaging applications. An array of tunable thin-film filters was implemented on an inverted fluorescence microscope (TE 2000, Nikon Instruments) to cover the full visible wavelength range. Images of a previously published model, GFP-expressing endothelial cells in the lung, were acquired using a charge-coupled device camera (Rolera EM-C2, Q-Imaging). This model sample presents fluorescently-labeled cells in a highly autofluorescent environment. Linear unmixing of hyperspectral images indicates that thin-film tunable filters provide equivalent spectral discrimination to our previous acousto-optic tunable filter-based approach, with increased signal-to-noise characteristics. Hence, tunable multi-layered thin film optical filters may provide greatly improved spectral filtering characteristics and therefore enable wider acceptance of hyperspectral widefield microscopy.
Spectral definition of the ArTeMiS instrument
NASA Astrophysics Data System (ADS)
Haynes, Vic; Maffei, Bruno; Pisano, Giampaolo; Dubreuil, Didier; Delisle, Cyrille; Le Pennec, Jean; Hurtado, Norma
2014-07-01
ArTeMiS is a sub-millimetre camera to be operated, on the Atacama Pathfinder Experiment Telescope (APEX). The ultimate goal is to observe simultaneously in three atmospheric spectral windows in the region of 200, 350 and 450 microns. We present the filtering scheme, which includes the cryostat window, thermal rejection elements, band separation and spectral isolation, which has been adopted for this instrument. This was achieved using a combination of scattering, Yoshinaga filters, organic dyes and Ulrich type embedded metallic mesh devices. Design of the quasi-optical mesh components has been developed by modelling with an in-house developed code. For the band separating dichroics, which are used with an incidence angle of 35 deg, further modelling has been performed with HFSS (Ansoft). Spectral characterization of the components for the 350 and 450 bands have been performed with a Martin-Puplett Polarizing Fourier Transform Spectrometer. While for the first commissioning and observation campaign, one spectral band only was operational (350 microns), we report on the design of the 200, 350 and 450 micron bands.
Jet Mixing Noise Scaling Laws SHJAR Data Vs. Predictions
NASA Technical Reports Server (NTRS)
Khavaran, Abbas; Bridges, James
2008-01-01
High quality jet noise spectral data measured at the anechoic dome at the NASA Glenn Research Center is used to examine a number of jet noise scaling laws. Configurations considered in the present study consist of convergent as well as convergent-divergent axisymmetric nozzles. The spectral measurements are shown in narrow band and cover 8193 equally spaced points in a typical Strouhal number range of (0.01 10.0). Measurements are reported as lossless (i.e. atmospheric attenuation is added to as-measured data), and at 24 equally spaced angles (50deg to 165deg) on a 100-diameter arc. Following the work of Viswanathan [Ref. 1], velocity power laws are derived using a least square fit on spectral power density as a function of jet temperature and observer angle. The goodness of the fit is studied at each angle, and alternative relationships are proposed to improve the spectral collapse when certain conditions are met. On the application side, power laws are extremely useful in identifying components from various noise generation mechanisms. From this analysis, jet noise prediction tools can be developed with physics derived from the different spectral components.
[Integration design and diffraction characteristics analysis of prism-grating-prism].
He, Tian-Bo; Bayanheshig; Li, Wen-Hao; Kong, Peng; Tang, Yu-Guo
2014-01-01
Prism-grating-prism (PGP) module is the important dispersing component in the hyper spectral imager. In order to effectively predict the distribution of diffraction efficiency of the whole PGP component and its diffraction characteristics before fabrication, a method of the PGP integration design is proposed. From the point of view of the volume phase holographic grating (VPHG) design, combined with the restrictive correlation between the various parameters of prisms and grating, we compiled the analysis software for calculating the whole PGP's diffraction efficiency. Furthermore, the effects of the structure parameters of prisms and grating on the PGP's diffraction characteristics were researched in detail. In particular we discussed the Bragg wavelength shift behaviour of the grating and a broadband PGP spectral component with high diffraction efficiency was designed for the imaging spectrometers. The result of simulation indicated that the spectral bandwidth of the PGP becomes narrower with the dispersion coefficient of prism 1 material decreasing; Bragg wavelength shift characteristics broaden the bandwidth of VPHG both spectrally and angularly, higher angular selectivity is desirable for selection requirements of the prism 1 material, and it can be easily tuned to achieve spectral bandwidth suitable for imaging PGP spectrograph; the vertex angle of prism 1, the film thickness and relative permittivity modulation of the grating have a significant impact on the distribution of PGP's diffraction efficiency, so precision control is necessary when fabrication. The diffraction efficiency of the whole PGP component designed by this method is no less than 50% in the wavelength range from 400 to 1000 nm, the specific design parameters have been given in this paper that have a certain reference value for PGP fabrication.
Decision strategies of hearing-impaired listeners in spectral shape discrimination
NASA Astrophysics Data System (ADS)
Lentz, Jennifer J.; Leek, Marjorie R.
2002-03-01
The ability to discriminate between sounds with different spectral shapes was evaluated for normal-hearing and hearing-impaired listeners. Listeners detected a 920-Hz tone added in phase to a single component of a standard consisting of the sum of five tones spaced equally on a logarithmic frequency scale ranging from 200 to 4200 Hz. An overall level randomization of 10 dB was either present or absent. In one subset of conditions, the no-perturbation conditions, the standard stimulus was the sum of equal-amplitude tones. In the perturbation conditions, the amplitudes of the components within a stimulus were randomly altered on every presentation. For both perturbation and no-perturbation conditions, thresholds for the detection of the 920-Hz tone were measured to compare sensitivity to changes in spectral shape between normal-hearing and hearing-impaired listeners. To assess whether hearing-impaired listeners relied on different regions of the spectrum to discriminate between sounds, spectral weights were estimated from the perturbed standards by correlating the listener's responses with the level differences per component across two intervals of a two-alternative forced-choice task. Results showed that hearing-impaired and normal-hearing listeners had similar sensitivity to changes in spectral shape. On average, across-frequency correlation functions also were similar for both groups of listeners, suggesting that as long as all components are audible and well separated in frequency, hearing-impaired listeners can use information across frequency as well as normal-hearing listeners. Analysis of the individual data revealed, however, that normal-hearing listeners may be better able to adopt optimal weighting schemes. This conclusion is only tentative, as differences in internal noise may need to be considered to interpret the results obtained from weighting studies between normal-hearing and hearing-impaired listeners.
NASA Technical Reports Server (NTRS)
Seifina, Elena; Titarchuk, Lev; Shaposhnikov, Nikolai
2014-01-01
We present the results of a comprehensive investigation on the evolution of spectral and timing properties of the Galactic black hole candidate 4U 1630-47 during its spectral transitions. In particular, we show how a scaling of the correlation of the photon index of the Comptonized spectral component gamma with low-frequency quasi-periodic oscillations (QPOs), ?(sub L), and mass accretion rate, M, can be applied to the black hole mass and the inclination angle estimates.We analyze the transition episodes observed with the Rossi X-Ray Timing Explorer and BeppoSAX satellites.We find that the broadband X-ray energy spectra of 4U 1630-47 during all spectral states can be modeled by a combination of a thermal component, a Comptonized component, and a red-skewed iron-line component. We also establish that gamma monotonically increases during transition from the low-hard state to the high-soft state and then saturates for high mass accretion rates. The index saturation levels vary for different transition episodes. Correlations of gamma versus ?(sub L) also show saturation at gamma (is) approximately 3. Gamma -M and gamma -?(sub L) correlations with their index saturation revealed in 4U 1630-47 are similar to those established in a number of other black hole candidates and can be considered as an observational evidence for the presence of a black hole in these sources. The scaling technique, which relies on XTE J1550-564, GRO 1655-40, and H1743-322 as reference sources, allows us to evaluate a black hole mass in 4U 1630-47 yielding M(sub BH) (is) approximately 10 +/- 0.1 solar masses and to constrain the inclination angle of i (is) approximately less than 70 deg.
NASA Astrophysics Data System (ADS)
Debernardi, N.; Dunias, P.; van El, B.; Statham, A. E.
2014-03-01
A novel methodology is presented to mimic diffuse reflectance spectra of arbitrary biological tissues in the visible and near-infrared ranges. The prerequisite for this method is that the spectral information of basic components is sufficient to mimic an arbitrary tissue. Using a sterile disposable fiber optic probe the diffuse reflectance spectrum of a tissue (either in vivo or ex vivo) is measured, which forms the target spectrum. With the same type of fiber probe, a wide variety of basic components (ingredients) has been previously measured and all together forms a spectral database. A "recipe" for the optimal mixture of ingredients can then be derived using an algorithm that fits the absorption and scattering behavior of the target spectrum using the spectra of the basic components in the database. The spectral mimicking accuracy refines by adding more ingredients to the database. The validity of the principle is demonstrated by mimicking an arbitrary mixture of components. The method can be applied with different kinds of materials, e.g. gelatins, waxes and silicones, thus providing the possibility of mimicking the mechanical properties of target tissues as well. The algorithm can be extended from single point contact spectral measurement to contactless multi- and hyper-spectral camera acquisition. It can be applied to produce portable and durable tissue-like phantoms that provides consistent results over time for calibration, demonstration, comparison of instruments or other such tasks. They are also more readily available than living tissue or a cadaver and are not so limited by ease of handling and legislation; hence they are highly useful when developing new devices.
NASA Astrophysics Data System (ADS)
Gutiérrez, Claudia P.; Anderson, Joseph P.; Hamuy, Mario; Morrell, Nidia; González-Gaitan, Santiago; Stritzinger, Maximilian D.; Phillips, Mark M.; Galbany, Lluis; Folatelli, Gastón; Dessart, Luc; Contreras, Carlos; Della Valle, Massimo; Freedman, Wendy L.; Hsiao, Eric Y.; Krisciunas, Kevin; Madore, Barry F.; Maza, José; Suntzeff, Nicholas B.; Prieto, Jose Luis; González, Luis; Cappellaro, Enrico; Navarrete, Mauricio; Pizzella, Alessandro; Ruiz, Maria T.; Smith, R. Chris; Turatto, Massimo
2017-11-01
We present 888 visual-wavelength spectra of 122 nearby type II supernovae (SNe II) obtained between 1986 and 2009, and ranging between 3 and 363 days post-explosion. In this first paper, we outline our observations and data reduction techniques, together with a characterization based on the spectral diversity of SNe II. A statistical analysis of the spectral matching technique is discussed as an alternative to nondetection constraints for estimating SN explosion epochs. The time evolution of spectral lines is presented and analyzed in terms of how this differs for SNe of different photometric, spectral, and environmental properties: velocities, pseudo-equivalent widths, decline rates, magnitudes, time durations, and environment metallicity. Our sample displays a large range in ejecta expansion velocities, from ˜9600 to ˜1500 km s-1 at 50 days post-explosion with a median {{{H}}}α value of 7300 km s-1. This is most likely explained through differing explosion energies. Significant diversity is also observed in the absolute strength of spectral lines, characterized through their pseudo-equivalent widths. This implies significant diversity in both temperature evolution (linked to progenitor radius) and progenitor metallicity between different SNe II. Around 60% of our sample shows an extra absorption component on the blue side of the {{{H}}}α P-Cygni profile (“Cachito” feature) between 7 and 120 days since explosion. Studying the nature of Cachito, we conclude that these features at early times (before ˜35 days) are associated with Si II λ 6355, while past the middle of the plateau phase they are related to high velocity (HV) features of hydrogen lines. This paper includes data gathered with the 6.5 m Magellan Telescopes located at Las Campanas Observatory, Chile; and the Gemini Observatory, Cerro Pachon, Chile (Gemini Program GS-2008B-Q-56). Based on observations collected at the European Organisation for Astronomical Research in the Southern Hemisphere, Chile (ESO Programs 076.A-0156, 078.D-0048, 080.A-0516, and 082.A-0526).
Generating Vegetation Leaf Area Index Earth System Data Record from Multiple Sensors. Part 1; Theory
NASA Technical Reports Server (NTRS)
Ganguly, Sangram; Schull, Mitchell A.; Samanta, Arindam; Shabanov, Nikolay V.; Milesi, Cristina; Nemani, Ramakrishna R.; Knyazikhin, Yuri; Myneni, Ranga B.
2008-01-01
The generation of multi-decade long Earth System Data Records (ESDRs) of Leaf Area Index (LAI) and Fraction of Photosynthetically Active Radiation absorbed by vegetation (FPAR) from remote sensing measurements of multiple sensors is key to monitoring long-term changes in vegetation due to natural and anthropogenic influences. Challenges in developing such ESDRs include problems in remote sensing science (modeling of variability in global vegetation, scaling, atmospheric correction) and sensor hardware (differences in spatial resolution, spectral bands, calibration, and information content). In this paper, we develop a physically based approach for deriving LAI and FPAR products from the Advanced Very High Resolution Radiometer (AVHRR) data that are of comparable quality to the Moderate resolution Imaging Spectroradiometer (MODIS) LAI and FPAR products, thus realizing the objective of producing a long (multi-decadal) time series of these products. The approach is based on the radiative transfer theory of canopy spectral invariants which facilitates parameterization of the canopy spectral bidirectional reflectance factor (BRF). The methodology permits decoupling of the structural and radiometric components and obeys the energy conservation law. The approach is applicable to any optical sensor, however, it requires selection of sensor-specific values of configurable parameters, namely, the single scattering albedo and data uncertainty. According to the theory of spectral invariants, the single scattering albedo is a function of the spatial scale, and thus, accounts for the variation in BRF with sensor spatial resolution. Likewise, the single scattering albedo accounts for the variation in spectral BRF with sensor bandwidths. The second adjustable parameter is data uncertainty, which accounts for varying information content of the remote sensing measurements, i.e., Normalized Difference Vegetation Index (NDVI, low information content), vs. spectral BRF (higher information content). Implementation of this approach indicates good consistency in LAI values retrieved from NDVI (AVHRRmode) and spectral BRF (MODIS-mode). Specific details of the implementation and evaluation of the derived products are detailed in the second part of this two-paper series.
GIFTS SM EDU Level 1B Algorithms
NASA Technical Reports Server (NTRS)
Tian, Jialin; Gazarik, Michael J.; Reisse, Robert A.; Johnson, David G.
2007-01-01
The Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS) SensorModule (SM) Engineering Demonstration Unit (EDU) is a high resolution spectral imager designed to measure infrared (IR) radiances using a Fourier transform spectrometer (FTS). The GIFTS instrument employs three focal plane arrays (FPAs), which gather measurements across the long-wave IR (LWIR), short/mid-wave IR (SMWIR), and visible spectral bands. The raw interferogram measurements are radiometrically and spectrally calibrated to produce radiance spectra, which are further processed to obtain atmospheric profiles via retrieval algorithms. This paper describes the GIFTS SM EDU Level 1B algorithms involved in the calibration. The GIFTS Level 1B calibration procedures can be subdivided into four blocks. In the first block, the measured raw interferograms are first corrected for the detector nonlinearity distortion, followed by the complex filtering and decimation procedure. In the second block, a phase correction algorithm is applied to the filtered and decimated complex interferograms. The resulting imaginary part of the spectrum contains only the noise component of the uncorrected spectrum. Additional random noise reduction can be accomplished by applying a spectral smoothing routine to the phase-corrected spectrum. The phase correction and spectral smoothing operations are performed on a set of interferogram scans for both ambient and hot blackbody references. To continue with the calibration, we compute the spectral responsivity based on the previous results, from which, the calibrated ambient blackbody (ABB), hot blackbody (HBB), and scene spectra can be obtained. We now can estimate the noise equivalent spectral radiance (NESR) from the calibrated ABB and HBB spectra. The correction schemes that compensate for the fore-optics offsets and off-axis effects are also implemented. In the third block, we developed an efficient method of generating pixel performance assessments. In addition, a random pixel selection scheme is designed based on the pixel performance evaluation. Finally, in the fourth block, the single pixel algorithms are applied to the entire FPA.
NASA Astrophysics Data System (ADS)
Díaz-Ayil, G.; Amouroux, M.; Blondel, W. C. P. M.; Bourg-Heckly, G.; Leroux, A.; Guillemin, F.; Granjon, Y.
2009-07-01
This paper deals with the development and application of in vivo spatially-resolved bimodal spectroscopy (AutoFluorescence AF and Diffuse Reflectance DR), to discriminate various stages of skin precancer in a preclinical model (UV-irradiated mouse): Compensatory Hyperplasia CH, Atypical Hyperplasia AH and Dysplasia D. A programmable instrumentation was developed for acquiring AF emission spectra using 7 excitation wavelengths: 360, 368, 390, 400, 410, 420 and 430 nm, and DR spectra in the 390-720 nm wavelength range. After various steps of intensity spectra preprocessing (filtering, spectral correction and intensity normalization), several sets of spectral characteristics were extracted and selected based on their discrimination power statistically tested for every pair-wise comparison of histological classes. Data reduction with Principal Components Analysis (PCA) was performed and 3 classification methods were implemented (k-NN, LDA and SVM), in order to compare diagnostic performance of each method. Diagnostic performance was studied and assessed in terms of sensitivity (Se) and specificity (Sp) as a function of the selected features, of the combinations of 3 different inter-fibers distances and of the numbers of principal components, such that: Se and Sp ≈ 100% when discriminating CH vs. others; Sp ≈ 100% and Se > 95% when discriminating Healthy vs. AH or D; Sp ≈ 74% and Se ≈ 63%for AH vs. D.
NASA Astrophysics Data System (ADS)
Meadows, Alexander R.; Cupal, Josef; Hříbek, Petr; Durák, Michal; Kramer, Daniel; Rus, Bedřich
2017-05-01
We present the design of a collinear femtosecond optical parametric amplification (OPA) system producing a tunable output at wavelengths between 1030 nm and 1080 nm from a Ti:Sapphire pump laser at a wavelength of 795 nm. Generation of a supercontinuum seed pulse is followed by one stage of amplification in Beta Barium Borate (BBO) and two stages of amplification in Potassium Titanyle Arsenate (KTA), resulting in a 225 μJ output pulse with a duration of 90 fs. The output of the system has been measured by self-referenced spectral interferometry to yield the complete spectrum and spectral phase of the pulse. When compared to KTP, the greater transparency of KTA in the spectral range from 3 - 4 μm allows for reduced idler absorption and enhanced gain from the OPA process when it is pumped by the fundamental frequency of a Ti:sapphire laser. In turn, the use of the Ti:sapphire fundamental at 795 nm as a pump improves the efficiency with which light can be converted to wavelengths between 1030 nm and 1080 nm and subsequently used to test components for Nd-based laser systems. This OPA system is operated at 1 kHz for diagnostic development and laser-induced damage threshold testing of optical components for the ELI-Beamlines project.
Accuracy Enhancement of Inertial Sensors Utilizing High Resolution Spectral Analysis
Noureldin, Aboelmagd; Armstrong, Justin; El-Shafie, Ahmed; Karamat, Tashfeen; McGaughey, Don; Korenberg, Michael; Hussain, Aini
2012-01-01
In both military and civilian applications, the inertial navigation system (INS) and the global positioning system (GPS) are two complementary technologies that can be integrated to provide reliable positioning and navigation information for land vehicles. The accuracy enhancement of INS sensors and the integration of INS with GPS are the subjects of widespread research. Wavelet de-noising of INS sensors has had limited success in removing the long-term (low-frequency) inertial sensor errors. The primary objective of this research is to develop a novel inertial sensor accuracy enhancement technique that can remove both short-term and long-term error components from inertial sensor measurements prior to INS mechanization and INS/GPS integration. A high resolution spectral analysis technique called the fast orthogonal search (FOS) algorithm is used to accurately model the low frequency range of the spectrum, which includes the vehicle motion dynamics and inertial sensor errors. FOS models the spectral components with the most energy first and uses an adaptive threshold to stop adding frequency terms when fitting a term does not reduce the mean squared error more than fitting white noise. The proposed method was developed, tested and validated through road test experiments involving both low-end tactical grade and low cost MEMS-based inertial systems. The results demonstrate that in most cases the position accuracy during GPS outages using FOS de-noised data is superior to the position accuracy using wavelet de-noising.
Ground-Based Correction of Remote-Sensing Spectral Imagery
NASA Technical Reports Server (NTRS)
Alder-Golden, Steven M.; Rochford, Peter; Matthew, Michael; Berk, Alexander
2007-01-01
Software has been developed for an improved method of correcting for the atmospheric optical effects (primarily, effects of aerosols and water vapor) in spectral images of the surface of the Earth acquired by airborne and spaceborne remote-sensing instruments. In this method, the variables needed for the corrections are extracted from the readings of a radiometer located on the ground in the vicinity of the scene of interest. The software includes algorithms that analyze measurement data acquired from a shadow-band radiometer. These algorithms are based on a prior radiation transport software model, called MODTRAN, that has been developed through several versions up to what are now known as MODTRAN4 and MODTRAN5 . These components have been integrated with a user-friendly Interactive Data Language (IDL) front end and an advanced version of MODTRAN4. Software tools for handling general data formats, performing a Langley-type calibration, and generating an output file of retrieved atmospheric parameters for use in another atmospheric-correction computer program known as FLAASH have also been incorporated into the present soft-ware. Concomitantly with the soft-ware described thus far, there has been developed a version of FLAASH that utilizes the retrieved atmospheric parameters to process spectral image data.
Peak picking NMR spectral data using non-negative matrix factorization
2014-01-01
Background Simple peak-picking algorithms, such as those based on lineshape fitting, perform well when peaks are completely resolved in multidimensional NMR spectra, but often produce wrong intensities and frequencies for overlapping peak clusters. For example, NOESY-type spectra have considerable overlaps leading to significant peak-picking intensity errors, which can result in erroneous structural restraints. Precise frequencies are critical for unambiguous resonance assignments. Results To alleviate this problem, a more sophisticated peaks decomposition algorithm, based on non-negative matrix factorization (NMF), was developed. We produce peak shapes from Fourier-transformed NMR spectra. Apart from its main goal of deriving components from spectra and producing peak lists automatically, the NMF approach can also be applied if the positions of some peaks are known a priori, e.g. from consistently referenced spectral dimensions of other experiments. Conclusions Application of the NMF algorithm to a three-dimensional peak list of the 23 kDa bi-domain section of the RcsD protein (RcsD-ABL-HPt, residues 688-890) as well as to synthetic HSQC data shows that peaks can be picked accurately also in spectral regions with strong overlap. PMID:24511909
Development and bench testing of a multi-spectral imaging technology built on a smartphone platform
NASA Astrophysics Data System (ADS)
Bolton, Frank J.; Weiser, Reuven; Kass, Alex J.; Rose, Donny; Safir, Amit; Levitz, David
2016-03-01
Cervical cancer screening presents a great challenge for clinicians across the developing world. In many countries, cervical cancer screening is done by visualization with the naked eye. Simple brightfield white light imaging with photo documentation has been shown to make a significant impact on cervical cancer care. Adoption of smartphone based cervical imaging devices is increasing across Africa. However, advanced imaging technologies such as multispectral imaging systems, are seldom deployed in low resource settings, where they are needed most. To address this challenge, the optical system of a smartphone-based mobile colposcopy imaging system was refined, integrating components required for low cost, portable multi-spectral imaging of the cervix. This paper describes the refinement of the mobile colposcope to enable it to acquire images of the cervix at multiple illumination wavelengths, including modeling and laboratory testing. Wavelengths were selected to enable quantifying the main absorbers in tissue (oxyand deoxy-hemoglobin, and water), as well as scattering parameters that describe the size distribution of scatterers. The necessary hardware and software modifications are reviewed. Initial testing suggests the multi-spectral mobile device holds promise for use in low-resource settings.
Bayesian approach to non-Gaussian field statistics for diffusive broadband terahertz pulses.
Pearce, Jeremy; Jian, Zhongping; Mittleman, Daniel M
2005-11-01
We develop a closed-form expression for the probability distribution function for the field components of a diffusive broadband wave propagating through a random medium. We consider each spectral component to provide an individual observation of a random variable, the configurationally averaged spectral intensity. Since the intensity determines the variance of the field distribution at each frequency, this random variable serves as the Bayesian prior that determines the form of the non-Gaussian field statistics. This model agrees well with experimental results.
NASA Astrophysics Data System (ADS)
Lebedeva, R. V.; Tumanova, A. N.; Mashin, N. I.
2007-07-01
We carried out a systematic study of the influence of the main component on the change of analytical signal during atomic-emission analysis of boron compounds. Changes in the intensity of spectral lines of microimpurities as functions of their concentrations in the analytical system based on graphite powder with a variable content of boric acid and boron oxide are presented.
Discovery of Photon Index Saturation in the Black Hole Binary GRS 1915+105
NASA Technical Reports Server (NTRS)
Titarchuk, Lev; Seifina, Elena
2009-01-01
We present a study of the correlations between spectral, timing properties and mass accretion rate observed in X-rays from the Galactic Black Hole (BH) binary GRS 1915+105 during the transition between hard and soft states. We analyze all transition episodes from this source observed with Rossi X-ray Timing Explorer (RXTE), coordinated with Ryle Radio Telescope (RT) observations. We show that broad-band energy spectra of GRS 1915+105 during all these spectral states can be adequately presented by two Bulk Motion Comptonization (BMC) components: a hard component (BMC1, photon index Gamma(sub 1) = 1.7 -- 3.0) with turnover at high energies and soft thermal component (BMC2, Gamma(sub 2) = 2.7 -- 4.2) with characteristic color temperature < or = 1 keV, and the red-skewed iron line (LAOR) component. We also present observable correlations between the index and the normalization of the disk "seed" component. The use of "seed" disk normalization, which is presumably proportional to mass accretion rate in the disk, is crucial to establish the index saturation effect during the transition to the soft state. We discovered the photon index saturation of the soft and hard spectral components at values of < or approximately equal 4.2 and 3 respectively. We present a physical model which explains the index-seed photon normalization correlations. We argue that the index saturation effect of the hard component (BMC1) is due to the soft photon Comptonization in the converging inflow close to 1311 and that of soft component is due to matter accumulation in the transition layer when mass accretion rate increases. Furthermore we demonstrate a strong correlation between equivalent width of the iron line and radio flux in GRS 1915+105. In addition to our spectral model components we also find a strong feature of "blackbody-like" bump which color temperature is about 4.5 keV in eight observations of the intermediate and soft states. We discuss a possible origin of this "blackbody-like" emission.
Chen, Shaoqiang; Sato, Aya; Ito, Takashi; Yoshita, Masahiro; Akiyama, Hidefumi; Yokoyama, Hiroyuki
2012-10-22
This paper reports generation of sub-5-ps Fourier-transform limited optical pulses from a 1.55-µm gain-switched single-mode distributed-feedback laser diode via nanosecond electric excitation and a simple spectral-filtering technique. Typical damped oscillations of the whole lasing spectrum were observed in the time-resolved waveform. Through a spectral-filtering technique, the initial relaxation oscillation pulse and the following components in the output pulse can be well separated, and the initial short pulse can be selectively extracted by filtering out the short-wavelength components in the spectrum. Short pulses generated by this simple method are expected to have wide potential applications comparable to mode-locking lasers.
NASA Technical Reports Server (NTRS)
Fymat, A. L.; Mease, K. D.
1978-01-01
The technique proposed by Fymat (1976) for retrieving the complex refractive index of atmospheric aerosols using narrowband spectral transmission ratios, taken within an overall narrow spectral interval, is investigated in the case of modelled polydispersions of rural, maritime-continental, maritime-sea spray and meteoric dust aerosols. It is confirmed that for not too broad size distributions most of the information comes from a narrow size range of 'active' aerosols so that, under these circumstances, the refractive index components can indeed be retrieved essentially independently of the size distribution. For 0.1% accurate data in three colors, the technique can provide the real and imaginary components of the index respectively within 0.07% and 0.3% accuracy.
Spectral structure of laser light scattering revisited: bandwidths of nonresonant scattering lidars.
She, C Y
2001-09-20
It is well known that scattering lidars, i.e., Mie, aerosol-wind, Rayleigh, high-spectral-resolution, molecular-wind, rotational Raman, and vibrational Raman lidars, are workhorses for probing atmospheric properties, including the backscatter ratio, aerosol extinction coefficient, temperature, pressure, density, and winds. The spectral structure of molecular scattering (strength and bandwidth) and its constituent spectra associated with Rayleigh and vibrational Raman scattering are reviewed. Revisiting the correct name by distinguishing Cabannes scattering from Rayleigh scattering, and sharpening the definition of each scattering component in the Rayleigh scattering spectrum, the review allows a systematic, logical, and useful comparison in strength and bandwidth between each scattering component and in receiver bandwidths (for both nighttime and daytime operation) between the various scattering lidars for atmospheric sensing.
Optical perception for detection of cutaneous T-cell lymphoma by multi-spectral imaging
NASA Astrophysics Data System (ADS)
Hsiao, Yu-Ping; Wang, Hsiang-Chen; Chen, Shih-Hua; Tsai, Chung-Hung; Yang, Jen-Hung
2014-12-01
In this study, the spectrum of each picture element of the patient’s skin image was obtained by multi-spectral imaging technology. Spectra of normal or pathological skin were collected from 15 patients. Principal component analysis and principal component scores of skin spectra were employed to distinguish the spectral characteristics with different diseases. Finally, skin regions with suspected cutaneous T-cell lymphoma (CTCL) lesions were successfully predicted by evaluation and classification of the spectra of pathological skin. The sensitivity and specificity of this technique were 89.65% and 95.18% after the analysis of about 109 patients. The probability of atopic dermatitis and psoriasis patients misinterpreted as CTCL were 5.56% and 4.54%, respectively.
Pietrowska, M; Marczak, L; Polanska, J; Nowicka, E; Behrent, K; Tarnawski, R; Stobiecki, M; Polanski, A; Widlak, P
2010-01-01
Mass spectrometry-based analysis of the serum proteome allows identifying multi-peptide patterns/signatures specific for blood of cancer patients, thus having high potential value for cancer diagnostics. However, because of problems with optimization and standardization of experimental and computational design, none of identified proteome patterns/signatures was approved for diagnostics in clinical practice as yet. Here we compared two methods of serum sample preparation for mass spectrometry-based proteome pattern analysis aimed to identify biomarkers that could be used in early detection of breast cancer patients. Blood samples were collected in a group of 92 patients diagnosed at early (I and II) stages of the disease before the start of therapy, and in a group of age-matched healthy controls (104 women). Serum specimens were purified and analyzed using MALDI-ToF spectrometry, either directly or after membrane filtration (50 kDa cut-off) to remove albumin and other large serum proteins. Mass spectra of the low-molecular-weight fraction (2-10 kDa) of the serum proteome were resolved using the Gaussian mixture decomposition, and identified spectral components were used to build classifiers that differentiated samples from breast cancer patients and healthy persons. Mass spectra of complete serum and membrane-filtered albumin-depleted samples have apparently different structure and peaks specific for both types of samples could be identified. The optimal classifier built for the complete serum specimens consisted of 8 spectral components, and had 81% specificity and 72% sensitivity, while that built for the membrane-filtered samples consisted of 4 components, and had 80% specificity and 81% sensitivity. We concluded that pre-processing of samples to remove albumin might be recommended before MALDI-ToF mass spectrometric analysis of the low-molecular-weight components of human serum Keywords: albumin removal; breast cancer; clinical proteomics; mass spectrometry; pattern analysis; serum proteome.
Long-term millimeter VLBI monitoring of M 87 with KVN at milliarcsecond resolution: nuclear spectrum
NASA Astrophysics Data System (ADS)
Kim, Jae-Young; Lee, Sang-Sung; Hodgson, Jeffrey A.; Algaba, Juan-Carlos; Zhao, Guang-Yao; Kino, Motoki; Byun, Do-Young; Kang, Sincheol
2018-02-01
We study the centimeter- to millimeter-wavelength synchrotron spectrum of the core of the radio galaxy M 87 at ≲0.8 mas 110Rs spatial scales using four years of fully simultaneous, multi-frequency VLBI data obtained by the Korean VLBI Network (KVN). We find a core spectral index α of ≳‑0.37 (S ∝ ν+α) between 22 and 129 GHz. By combining resolution-matched flux measurements from the Very Long Baseline Array (VLBA) at 15 GHz and taking the Event Horizon Telescope (EHT) 230 GHz core flux measurements in epochs 2009 and 2012 as lower limits, we find evidence of a nearly flat core spectrum across 15 and 129 GHz, which could naturally connect the 230 GHz VLBI core flux. The extremely flat spectrum is a strong indication that the jet base does not consist of a simple homogeneous plasma, but of inhomogeneous multi-energy components, with at least one component with the turn-over frequency ≳ 100 GHz. The spectral shape can be qualitatively explained if both the strongly (compact, optically thick at >100 GHz) and the relatively weakly magnetized (more extended, optically thin at <100 GHz) plasma components are colocated in the footprint of the relativistic jet.
An endophytic Coniochaeta velutina producing broad spectrum antimycotics.
Xie, Jie; Strobel, Gary A; Feng, Tao; Ren, Huishuang; Mends, Morgan T; Zhou, Zeyang; Geary, Brad
2015-06-01
An endophyte (PC27-5) was isolated from stem tissue of Western hemlock (Tsuga heterophylla) in a Pacific Northwest temperate rainforest. Phylogenetic analyses, based on ITS-5.8S rDNA and 18S rDNA sequence data, combined with cultural and morphological analysis showed that endophyte PC27-5 exhibited all characteristics of a fungus identical to Coniochaeta velutina. Furthermore, wide spectrum antimycotics were produced by this endophyte that were active against such plant pathogens as Sclerotinia sclerotiorum, Pythium ultimum, and Verticillium dahliae and lethal to Phythophthora cinnamomi, Pythium ultimum, and Phytophthora palmivora in plate tests. The bioactive components were purified through organic solvent extraction, followed by silica column chromatography, and finally preparative HPLC. The minimum inhibitory concentration of the active fraction to Pythium ultimum, which was gained from preparative HPLC, was 11 μg/ml. UPLC-HRMS analysis showed there were two similar components in the antimycotic fraction. Their molecular formulae were established as C30H22O11 (compound I) and C30H22O10 (compound II) respectively, and preliminary spectral results indicate that they are anthroquinone glycosides. Other non-biologically active compounds were identified in culture fluids of this fungus by spectral means as emodin and chrysophanol--anthroquinone derivatives. This is the first report that Coniochaeta velutina as an endophyte produces bioactive antifungal components.
Kiendler-Scharr, Astrid; Zhang, Qi; Hohaus, Thorsten; Kleist, Einhard; Mensah, Amewu; Mentel, Thomas F; Spindler, Christian; Uerlings, Ricarda; Tillmann, Ralf; Wildt, Jürgen
2009-11-01
Secondary organic aerosol (SOA) is known to form from a variety of anthropogenic and biogenic precursors. Current estimates of global SOA production vary over 2 orders of magnitude. Since no direct measurement technique for SOA exists, quantifying SOA remains a challenge for atmospheric studies. The identification of biogenic SOA (BSOA) based on mass spectral signatures offers the possibility to derive source information of organic aerosol (OA) with high time resolution. Here we present data from simulation experiments. The BSOA from tree emissions was characterized with an Aerodyne quadrupole aerosol mass spectrometer (Q-AMS). Collection efficiencies were close to 1, and effective densities of the BSOA were found to be 1.3 +/- 0.1 g/cm(3). The mass spectra of SOA from different trees were found to be highly similar. The average BSOA mass spectrum from tree emissions is compared to a BSOA component spectrum extracted from field data. It is shown that overall the spectra agree well and that the mass spectral features of BSOA are distinctively different from those of OA components related to fresh fossil fuel and biomass combustions. The simulation chamber mass spectrum may potentially be useful for the identification and interpretation of biogenic SOA components in ambient data sets.
Nonlinear spectral imaging of biological tissues
NASA Astrophysics Data System (ADS)
Palero, J. A.
2007-07-01
The work presented in this thesis demonstrates live high resolution 3D imaging of tissue in its native state and environment. The nonlinear interaction between focussed femtosecond light pulses and the biological tissue results in the emission of natural autofluorescence and second-harmonic signal. Because biological intrinsic emission is generally very weak and extends from the ultraviolet to the visible spectral range, a broad-spectral range and high sensitivity 3D spectral imaging system is developed. Imaging the spectral characteristics of the biological intrinsic emission reveals the structure and biochemistry of the cells and extra-cellular components. By using different methods in visualizing the spectral images, discrimination between different tissue structures is achieved without the use of any stain or fluorescent label. For instance, RGB real color spectral images of the intrinsic emission of mouse skin tissues show blue cells, green hair follicles, and purple collagen fibers. The color signature of each tissue component is directly related to its characteristic emission spectrum. The results of this study show that skin tissue nonlinear intrinsic emission is mainly due to the autofluorescence of reduced nicotinamide adenine dinucleotide (phosphate), flavins, keratin, melanin, phospholipids, elastin and collagen and nonlinear Raman scattering and second-harmonic generation in Type I collagen. In vivo time-lapse spectral imaging is implemented to study metabolic changes in epidermal cells in tissues. Optical scattering in tissues, a key factor in determining the maximum achievable imaging depth, is also investigated in this work.
Fourier resolved spectroscopy of 4U 1543-47 during the 2002 outburst
NASA Technical Reports Server (NTRS)
Reig, P.; Papadakis, I. E.; Shrader, C. R.; Kazanas, D.
2006-01-01
We have obtained Fourier-resolved spectra of the black-hole binary 4U 1543-47 in the canonical states (high/soft, very high, intermediate and low/hard) observed in this source during the decay of an outburst that took place in 2002. Our objective is to investigate the variability of the spectral components generally used to describe the energy spectra of black-hole systems, namely a disk component, a power-law component attributed to Comptonization by a hot corona and the contribution of the iron line due to reprocessing of the high energy (E greater than or approx, equal to 7 keV) radiation. We find that i) the disk component is not variable on time scales shorter than approx. 100 seconds, ii) the reprocessing emission as manifest by the variability of the Fe K(alpha) line responds to the primary radiation variations down to time scales of approx. 70 ms in the high and very-high states, but longer than 2 s in the low state, iii) the low-frequency QPOs are associated with variations of the X-ray power law spectral component and not to the disk component and iv) the spectra corresponding to the highest Fourier frequency are the hardest (show the flatter spectra) at a given spectral state. These results questions the models that explain the observed power spectra as due to modulations of the accretion rate only.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jassal, Anjali Rao; Vadawale, Santosh V.; Mithun, N. P. S.
Low-frequency quasi-periodic oscillations (QPOs) are commonly observed during the hard states of black hole binaries. Several studies have established various observational/empirical correlations between spectral parameters and QPO properties, indicating a close link between the two. However, the exact mechanism of generation of QPOs is not yet well understood. In this paper, we present our attempts to comprehend the connection between the spectral components and the low-frequency QPO (LFQPO) observed in GRS 1915+105 using the data from NuSTAR. Detailed spectral modeling as well as the presence of the LFQPO and its energy dependence during this observation have been reported by Millermore » et al. and Zhang et al., respectively. We investigate the compatibility of the spectral model and the energy dependence of the QPO by simulating light curves in various energy bands for small variation of the spectral parameters. The basic concept here is to establish the connection, if any, between the QPO and the variation of either a spectral component or a specific parameter, which in turn can shed some light on the origin of the QPO. We begin with the best-fit spectral model of Miller et al. and simulate the light curve by varying the spectral parameters at frequencies close to the observed QPO frequency in order to generate the simulated QPO. Furthermore we simulate similar light curves in various energy bands in order to reproduce the observed energy dependence of the rms amplitude of the QPO. We find that the observed trend of increasing rms amplitude with energy can be reproduced qualitatively if the spectral index is assumed to be varying with the phases of the QPO. Variation of any other spectral parameter does not reproduce the observed energy dependence.« less
A spectral nudging method for the ACCESS1.3 atmospheric model
NASA Astrophysics Data System (ADS)
Uhe, P.; Thatcher, M.
2015-06-01
A convolution-based method of spectral nudging of atmospheric fields is developed in the Australian Community Climate and Earth Systems Simulator (ACCESS) version 1.3 which uses the UK Met Office Unified Model version 7.3 as its atmospheric component. The use of convolutions allow for flexibility in application to different atmospheric grids. An approximation using one-dimensional convolutions is applied, improving the time taken by the nudging scheme by 10-30 times compared with a version using a two-dimensional convolution, without measurably degrading its performance. Care needs to be taken in the order of the convolutions and the frequency of nudging to obtain the best outcome. The spectral nudging scheme is benchmarked against a Newtonian relaxation method, nudging winds and air temperature towards ERA-Interim reanalyses. We find that the convolution approach can produce results that are competitive with Newtonian relaxation in both the effectiveness and efficiency of the scheme, while giving the added flexibility of choosing which length scales to nudge.
A spectral nudging method for the ACCESS1.3 atmospheric model
NASA Astrophysics Data System (ADS)
Uhe, P.; Thatcher, M.
2014-10-01
A convolution based method of spectral nudging of atmospheric fields is developed in the Australian Community Climate and Earth Systems Simulator (ACCESS) version 1.3 which uses the UK Met Office Unified Model version 7.3 as its atmospheric component. The use of convolutions allow flexibility in application to different atmospheric grids. An approximation using one-dimensional convolutions is applied, improving the time taken by the nudging scheme by 10 to 30 times compared with a version using a two-dimensional convolution, without measurably degrading its performance. Care needs to be taken in the order of the convolutions and the frequency of nudging to obtain the best outcome. The spectral nudging scheme is benchmarked against a Newtonian relaxation method, nudging winds and air temperature towards ERA-Interim reanalyses. We find that the convolution approach can produce results that are competitive with Newtonian relaxation in both the effectiveness and efficiency of the scheme, while giving the added flexibility of choosing which length scales to nudge.
A biological rationale for musical scales.
Gill, Kamraan Z; Purves, Dale
2009-12-03
Scales are collections of tones that divide octaves into specific intervals used to create music. Since humans can distinguish about 240 different pitches over an octave in the mid-range of hearing, in principle a very large number of tone combinations could have been used for this purpose. Nonetheless, compositions in Western classical, folk and popular music as well as in many other musical traditions are based on a relatively small number of scales that typically comprise only five to seven tones. Why humans employ only a few of the enormous number of possible tone combinations to create music is not known. Here we show that the component intervals of the most widely used scales throughout history and across cultures are those with the greatest overall spectral similarity to a harmonic series. These findings suggest that humans prefer tone combinations that reflect the spectral characteristics of conspecific vocalizations. The analysis also highlights the spectral similarity among the scales used by different cultures.
Detectability of Noble Gases in Jovian Atmospheres Utilizing Dimer Spectral Structures
NASA Astrophysics Data System (ADS)
Kim, S. J.; Min, Y.; Kim, Y.; Lee, Y.; Trafton, L.; Miller, S.; McKellar, A. R. W.
1997-07-01
The detection of jovian hydrogen-hydrogen dimers through the clear telluric 2-micron window (Kim et al. 1995; Trafton et al. 1997) suggests possibility to detect noble gases in the form of dimer with hydrogen in jovian atmospheres. Since noble gases do not have spectral structures in the infrared, it has been difficult to derive their abundances in the atmospheres of jovian planets. If there is a significant component of noble gases other than helium in the jovian atmospheres, it might be detected through its dimer spectrum with hydrogen molecule. The relatively sharp spectral structures of hydrogen-argon and hydrogen-neon dimers compared with those of hydrogen-hydrogen dimers are useful for the detection, if adequate S/N is obtained. However, these dimer structures should be much weaker than the nearby hydrogen-hydrogen features because noble gases are expected to be minor constituents of these atmospheres. We will discuss the detectability of these dimers based on laboratory measurements (McKellar, 1994; 1996), and current technology of infrared observations.
A thermal/nonthermal model for solar microwave bursts
NASA Technical Reports Server (NTRS)
Benka, Stephen G.; Holman, Gordon D.
1992-01-01
A theoretical framework is developed for modeling high-resolution spectra of microwave bursts from the Owens Valley Radio Observatory which can account for departures from expectations based on simple thermal or nonthermal models. Specifically, 80 percent of the events show more than one spectral peak; many bursts have a low-side spectral index steeper than the maximum expected slope; and the peak frequency stays relatively constant and changes intensity in concert with the secondary peaks throughout a given event's solution. It is shown that the observed spectral features can be explained through gyrosynchrotron radiation. The 'secondary' components seen on the LF side of many spectra are nonthermal enhancements superposed upon thermal radiation, occurring between the thermal harmonics. A steep optically thick slope is accounted for by the thermal absorption of nonthermal radiation. If the coexistence of thermal and nonthermal particles is interpreted in terms of electron heating and acceleration in current sheets, a changing electric field strength can account for the gross evolution of the microwave spectra.
A Biological Rationale for Musical Scales
Gill, Kamraan Z.; Purves, Dale
2009-01-01
Scales are collections of tones that divide octaves into specific intervals used to create music. Since humans can distinguish about 240 different pitches over an octave in the mid-range of hearing [1], in principle a very large number of tone combinations could have been used for this purpose. Nonetheless, compositions in Western classical, folk and popular music as well as in many other musical traditions are based on a relatively small number of scales that typically comprise only five to seven tones [2]–[6]. Why humans employ only a few of the enormous number of possible tone combinations to create music is not known. Here we show that the component intervals of the most widely used scales throughout history and across cultures are those with the greatest overall spectral similarity to a harmonic series. These findings suggest that humans prefer tone combinations that reflect the spectral characteristics of conspecific vocalizations. The analysis also highlights the spectral similarity among the scales used by different cultures. PMID:19997506
Integrated Optics Achromatic Nuller for Stellar Interferometry
NASA Technical Reports Server (NTRS)
Ksendzov, Alexander
2012-01-01
This innovation will replace a beam combiner, a phase shifter, and a mode conditioner, thus simplifying the system design and alignment, and saving weight and space in future missions. This nuller is a dielectric-waveguide-based, four-port asymmetric coupler. Its nulling performance is based on the mode-sorting property of adiabatic asymmetric couplers that are intrinsically achromatic. This nuller has been designed, and its performance modeled, in the 6.5-micrometer to 9.25-micrometer spectral interval (36% bandwidth). The calculated suppression of starlight for this 15-cm-long device is 10(exp -5) or better through the whole bandwidth. This is enough to satisfy requirements of a flagship exoplanet-characterization mission. Nulling interferometry is an approach to starlight suppression that will allow the detection and spectral characterization of Earth-like exoplanets. Nulling interferometers separate the light originating from a dim planet from the bright starlight by placing the star at the bottom of a deep, destructive interference fringe, where the starlight is effectively cancelled, or nulled, thus allowing the faint off-axis light to be much more easily seen. This process is referred to as nulling of the starlight. Achromatic nulling technology is a critical component that provides the starlight suppression in interferometer-based observatories. Previously considered space-based interferometers are aimed at approximately 6-to-20-micrometer spectral range. While containing the spectral features of many gases that are considered to be signatures of life, it also offers better planet-to-star brightness ratio than shorter wavelengths. In the Integrated Optics Achromatic Nuller (IOAN) device, the two beams from the interferometer's collecting telescopes pass through the same focusing optic and are incident on the input of the nuller.
FISM 2.0: Improved Spectral Range, Resolution, and Accuracy
NASA Technical Reports Server (NTRS)
Chamberlin, Phillip C.
2012-01-01
The Flare Irradiance Spectral Model (FISM) was first released in 2005 to provide accurate estimates of the solar VUV (0.1-190 nm) irradiance to the Space Weather community. This model was based on TIMED SEE as well as UARS and SORCE SOLSTICE measurements, and was the first model to include a 60 second temporal variation to estimate the variations due to solar flares. Along with flares, FISM also estimates the tradition solar cycle and solar rotational variations over months and decades back to 1947. This model has been highly successful in providing driving inputs to study the affect of solar irradiance variations on the Earth's ionosphere and thermosphere, lunar dust charging, as well as the Martian ionosphere. The second version of FISM, FISM2, is currently being updated to be based on the more accurate SDO/EVE data, which will provide much more accurate estimations in the 0.1-105 nm range, as well as extending the 'daily' model variation up to 300 nm based on the SOLSTICE measurements. with the spectral resolution of SDO/EVE along with SOLSTICE and the TIMED and SORCE XPS 'model' products, the entire range from 0.1-300 nm will also be available at 0.1 nm, allowing FISM2 to be improved a similar 0.1nm spectral bins. FISM also will have a TSI component that will estimate the total radiated energy during flares based on the few TSI flares observed to date. Presented here will be initial results of the FISM2 modeling efforts, as well as some challenges that will need to be overcome in order for FISM2 to accurately model the solar variations on time scales of seconds to decades.
Black light - How sensors filter spectral variation of the illuminant
NASA Technical Reports Server (NTRS)
Brainard, David H.; Wandell, Brian A.; Cowan, William B.
1989-01-01
Visual sensor responses may be used to classify objects on the basis of their surface reflectance functions. In a color image, the image data are represented as a vector of sensor responses at each point in the image. This vector depends both on the surface reflectance functions and on the spectral power distribution of the ambient illumination. Algorithms designed to classify objects on the basis of their surface reflectance functions typically attempt to overcome the dependence of the sensor responses on the illuminant by integrating sensor data collected from multiple surfaces. In machine vision applications, it is shown that it is often possible to design the sensor spectral responsivities so that the vector direction of the sensor responses does not depend upon the illuminant. The conditions under which this is possible are given and an illustrative calculation is performed. In biological systems, where the sensor responsivities are fixed, it is shown that some changes in the illumination cause no change in the sensor responses. Such changes in illuminant are called black illuminants. It is possible to express any illuminant as the sum of two unique components. One component is a black illuminant. The second component is called the visible component. The visible component of an illuminant completely characterizes the effect of the illuminant on the vector of sensor responses.
Miller, Patrick J O; Samarra, Filipa I P; Perthuison, Aurélie D
2007-06-01
This study investigates how particular received spectral characteristics of stereotyped calls of sexually dimorphic adult killer whales may be influenced by caller sex, orientation, and range. Calls were ascribed to individuals during natural behavior using a towed beamforming array. The fundamental frequency of both high-frequency and low-frequency components did not differ consistently by sex. The ratio of peak energy within the fundamental of the high-frequency component relative to summed peak energy in the first two low-frequency component harmonics, and the number of modulation bands off the high-frequency component, were significantly greater when whales were oriented towards the array, while range and adult sex had little effect. In contrast, the ratio of peak energy in the first versus second harmonics of the low-frequency component was greater in calls produced by adult females than adult males, while orientation and range had little effect. The dispersion of energy across harmonics has been shown to relate to body size or sex in terrestrial species, but pressure effects during diving are thought to make such a signal unreliable in diving animals. The observed spectral differences by signaler sex and orientation suggest that these types of information may be transmitted acoustically by freely diving killer whales.
Jia, Zhixin; Wu, Caisheng; Jin, Hongtao; Zhang, Jinlan
2014-11-15
Saussurea involucrata is a rare traditional Chinese medicine (TCM) that displays anti-fatigue, anti-inflammatory and anti-tumor effects. In this paper, the different chemical components of Saussurea involucrata were characterized and identified over a wide dynamic range by high-performance liquid chromatography coupled with high-resolution hybrid mass spectrometry (HPLC/HRMS/MS(n)) and the mass spectral trees similarity filter (MTSF) technique. The aerial parts of Saussurea involucrata were extracted with 75% ethanol. The partial extract was separated on a chromatography column to concentrate the low-concentration compounds. Mass data were acquired using full-scan mass analysis (resolving power 50,000) with data-dependent incorporation of dynamic exclusion analysis. The identified compounds were used as templates to construct a database of mass spectral trees. Data for the unknown compounds were matched with those templates and matching candidate structures were obtained. The detected compounds were characterized based on matching to candidate structures by the MTSF technique and were further identified by their accurate mass weight, multiple-stage analysis and fragmentation patterns and through comparison with literature data. A total of 38 compounds were identified including 19 flavones, 11 phenylpropanoids and 8 sphingolipids. Among them, 7 flavonoids, 8 phenylpropanoids and 8 sphingolipids were identified for the first time in Saussurea involucrata. HPLC/HRMS/MS(n) combined with MTSF was successfully used to discover and identify the chemical compounds in Saussurea involucrata. The results indicated that this combined technique was extremely useful for the rapid detection and identification of the chemical components in TCMs. Copyright © 2014 John Wiley & Sons, Ltd.
Raman spectra of single cells with autofluorescence suppression by modulated wavelength excitation
NASA Astrophysics Data System (ADS)
Krafft, Christoph; Dochow, Sebastian; Bergner, Norbert; Clement, Joachim H.; Praveen, Bavishna B.; Mazilu, Michael; Marchington, Rob; Dholakia, Kishan; Popp, Jürgen
2012-01-01
Raman spectroscopy is a non-invasive technique offering great potential in the biomedical field for label-free discrimination between normal and tumor cells based on their biochemical composition. First, this contribution describes Raman spectra of lymphocytes after drying, in laser tweezers, and trapped in a microfluidic environment. Second, spectral differences between lymphocytes and acute myeloid leukemia cells (OCI-AML3) are compared for these three experimental conditions. Significant similarities of difference spectra are consistent with the biological relevance of the spectral features. Third, modulated wavelength Raman spectroscopy has been applied to this model system to demonstrate background suppression. Here, the laser excitation wavelength of 785 nm was modulated with a frequency of 40 mHz by 0.6 nm. 40 spectra were accumulated with an exposure time of 5 seconds each. These data were subjected to principal component analysis to calculate modulated Raman signatures. The loading of the principal component shows characteristics of first derivatives with derivative like band shapes. The derivative of this loading corresponds to a pseudo-second derivative spectrum and enables to determine band positions.
Rezaeian, Sanaz; Bozorgnia, Yousef; Idriss, I.M.; Abrahamson, Norman; Campbell, Kenneth; Silva, Walter
2014-01-01
Ground motion prediction equations (GMPEs) for elastic response spectra are typically developed at a 5% viscous damping ratio. In reality, however, structural and nonstructural systems can have other damping ratios. This paper develops a new model for a damping scaling factor (DSF) that can be used to adjust the 5% damped spectral ordinates predicted by a GMPE for damping ratios between 0.5% to 30%. The model is developed based on empirical data from worldwide shallow crustal earthquakes in active tectonic regions. Dependencies of the DSF on potential predictor variables, such as the damping ratio, spectral period, ground motion duration, moment magnitude, source-to-site distance, and site conditions, are examined. The strong influence of duration is captured by the inclusion of both magnitude and distance in the DSF model. Site conditions show weak influence on the DSF. The proposed damping scaling model provides functional forms for the median and logarithmic standard deviation of DSF, and is developed for both RotD50 and GMRotI50 horizontal components. A follow-up paper develops a DSF model for vertical ground motion.
NASA Astrophysics Data System (ADS)
Díaz-Ayil, Gilberto; Amouroux, Marine; Clanché, Fabien; Granjon, Yves; Blondel, Walter C. P. M.
2009-07-01
Spatially-resolved bimodal spectroscopy (multiple AutoFluorescence AF excitation and Diffuse Reflectance DR), was used in vivo to discriminate various healthy and precancerous skin stages in a pre-clinical model (UV-irradiated mouse): Compensatory Hyperplasia CH, Atypical Hyperplasia AH and Dysplasia D. A specific data preprocessing scheme was applied to intensity spectra (filtering, spectral correction and intensity normalization), and several sets of spectral characteristics were automatically extracted and selected based on their discrimination power, statistically tested for every pair-wise comparison of histological classes. Data reduction with Principal Components Analysis (PCA) was performed and 3 classification methods were implemented (k-NN, LDA and SVM), in order to compare diagnostic performance of each method. Diagnostic performance was studied and assessed in terms of Sensibility (Se) and Specificity (Sp) as a function of the selected features, of the combinations of 3 different inter-fibres distances and of the numbers of principal components, such that: Se and Sp ~ 100% when discriminating CH vs. others; Sp ~ 100% and Se > 95% when discriminating Healthy vs. AH or D; Sp ~ 74% and Se ~ 63% for AH vs. D.
A novel method for determining the phase-noise behavior of resonator-oscillators
NASA Astrophysics Data System (ADS)
Hoffmann, Michael H. W.
2005-05-01
A novel approach to the theory of phase-noise in resonator-oscillators will be given that is based on a combination of a large-signal-small-signal method, harmonic balance, and a modified Rice-model of signals plus noise. The method will be explained using a simple example. Since the type of oscillator under consideration not only de-attenuates eigen-oscillations but also noise in the spectral vicinity of the eigen-frequency, a signal is generated that is quasi-harmonic, and that might be described by means of a pseudo-Fourier-series expansion. Due to the specific description of the internal noise-sources, it is possible to use a time-domain description that at the same time reveals information about the spectral components of the signal. By comparison of these components, the spectrum of the oscillation might be determined. Relations between the spectrum of internal noise sources and the generated oscillator-signal will be recognized. The novel method will thus enable the designer to predict the phase-noise behavior of a specific oscillator-design.
X-ray spectrum of Capella and its relation to coronal structure and ultraviolet emission
NASA Technical Reports Server (NTRS)
Mewe, R.; Gronenschild, E. H. B. M.; Heise, J.; Brinkman, A. C.; Dijkstra, J. H.; Westergaard, N. J.; Schnopper, H. W.; Seward, F. D.; Chlebowski, T.; Kuin, N. P. M.
1982-01-01
The binary system Capella has been observed on 1979 March 15 and on 1980 March 15-17, with the objective grating spectrometer on board the Einstein Observatory. The spectrum measured with the 1000 1/mm grating covers the range 5-30 A with a resolution less than 1 A. The spectra show evidence for a bimodal temperature distribution of emission measure in an optically thin plasma with one component about 5,000,000 K and the other one about 10,000,000 K. Spectral features can be identified with line emissions from O VIII, Fe XVII, Fe XVIII, Fe XXIV, and Ne X ions. Good spectral fits have been obtained assuming standard cosmic abundances. The data are interpreted in terms of emission from hot static coronal loops rather similar to the magnetic arch structures found on the sun. It is shown that the conditions for such a model can exist on Capella. Typical values of loop base pressure and half-length are derived for both temperature components and discussed in relation to UV observations.
TADIR: a second-generation 480 x 4 TDI FLIR
NASA Astrophysics Data System (ADS)
Sarusi, Gabby
1997-08-01
'TADIR' is an El-Op's new second generation thermal imager based on 480 by 4 TDI MCT detector operated in the 8 - 10.5 micrometer spectral range. Although the prototype configuration design of TADIR is aimed toward the light weight low volume applications, TADIR is a generic modular technology of which the future El-Op second generation FLIR applications will be derived from. Beside the detector, what put the system in the second generation category are the state of the art features implemented in every component. This paper describes the system concept and design consideration have been taken during the development of its components.
NASA Astrophysics Data System (ADS)
Kopriva, Ivica; Popović Hadžija, Marijana; Hadžija, Mirko; Aralica, Gorana
2015-06-01
Low-contrast images, such as color microscopic images of unstained histological specimens, are composed of objects with highly correlated spectral profiles. Such images are very hard to segment. Here, we present a method that nonlinearly maps low-contrast color image into an image with an increased number of non-physical channels and a decreased correlation between spectral profiles. The method is a proof-of-concept validated on the unsupervised segmentation of color images of unstained specimens, in which case the tissue components appear colorless when viewed under the light microscope. Specimens of human hepatocellular carcinoma, human liver with metastasis from colon and gastric cancer and mouse fatty liver were used for validation. The average correlation between the spectral profiles of the tissue components was greater than 0.9985, and the worst case correlation was greater than 0.9997. The proposed method can potentially be applied to the segmentation of low-contrast multichannel images with high spatial resolution that arise in other imaging modalities.
CORRELATIONS IN HORIZONTAL BRANCH OSCILLATIONS AND BREAK COMPONENTS IN XTE J1701-462 AND GX 17+2
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bu, Qing-cui; Chen, Li; Zhang, Liang
2015-01-20
We studied the horizontal branch oscillations (HBO) and the band-limited components observed in the power spectra of the transient neutron star low-mass X-ray binary XTE J1701-462 and the persistent ''Sco-like'' Z source GX 17+2. These two components were studied based on the state-resolved spectra. We found that the frequencies of XTE J1701-462 lie on the known correlations (WK and PBK), showing consistency with other types of X-ray binaries (black holes, atoll sources, and millisecond X-ray pulsars). However, GX 17+2 is shifted from the WK correlation like other typical Z sources. We suggest that the WK/PBK main track forms a boundarymore » that separates persistent sources from transient sources. The characteristic frequencies of break and HBO are independent of accretion rate in both sources, though it depends on spectral models. We also report the energy dependence of the HBO and break frequencies in XTE J1701-462 and how the temporal properties change with spectral state in XTE J1701-462 and GX 17+2. We studied the correlation between rms at the break and the HBO frequency. We suggest that HBO and break components for both sources probably arise from a similar physical mechanism: Comptonization emission from the corona. These two components could be caused by the same kind of oscillation in a corona with uneven density, and they could be generated from different areas of the corona. We further suggest that different proportions of the Comptonization component in the total flux cause the different distribution between GX 17+2 and XTE J1701-462 in the rms{sub break}-rms{sub HBO} diagram.« less
NASA Astrophysics Data System (ADS)
He, Minyou; Chen, Liang; Su, Lingai; Yin, Lin; Qian, Yunsheng
2017-06-01
To theoretically research the influence of a varied Al component on the active layer of AlGaN photocathodes, the first principle based on density functional theory is used to calculate the formation energy and band structure of Al x Ga1-x N with x at 0, 0.125, 0.25, 0.325, and 0.5. The calculation results show that the formation energy declines along with the Al component rise, while the band gap is increasing with Al component increasing. Al x Ga1-x N with x at 0, 0.125, 0.25, 0.325, and 0.5 are direct band gap semiconductors, and their absorption coefficient curves have the same variation tendency. For further study, we designed two kinds of reflection-mode AlGaN photocathode samples. Sample 1 has an Al x Ga1-x N active layer with varied Al component ranging from 0.5 to 0 and decreasing from the bulk to the surface, while sample 2 has an Al x Ga1-x N active layer with the fixed Al component of 0.25. Using the multi-information measurement system, we measured the spectral response of the activated samples at room temperature. Their photocathode parameters were obtained by fitting quantum efficiency curves. Results show that sample 1 has a better spectral response than sample 2 at the range of short-wavelength. This work provides a reference for the structure design of the AlGaN photocathode. Project supported by the National Natural Science Foundation of China (Nos. 61308089, 6144005) and the Public Technology Applied Research Project of Zhejiang Province (No. 2013C31068).
NASA Astrophysics Data System (ADS)
Leja, Joel; Johnson, Benjamin D.; Conroy, Charlie; van Dokkum, Pieter
2018-02-01
Forward modeling of the full galaxy SED is a powerful technique, providing self-consistent constraints on stellar ages, dust properties, and metallicities. However, the accuracy of these results is contingent on the accuracy of the model. One significant source of uncertainty is the contribution of obscured AGN, as they are relatively common and can produce substantial mid-IR (MIR) emission. Here we include emission from dusty AGN torii in the Prospector SED-fitting framework, and fit the UV–IR broadband photometry of 129 nearby galaxies. We find that 10% of the fitted galaxies host an AGN contributing >10% of the observed galaxy MIR luminosity. We demonstrate the necessity of this AGN component in the following ways. First, we compare observed spectral features to spectral features predicted from our model fit to the photometry. We find that the AGN component greatly improves predictions for observed Hα and Hβ luminosities, as well as mid-infrared Akari and Spitzer/IRS spectra. Second, we show that inclusion of the AGN component changes stellar ages and SFRs by up to a factor of 10, and dust attenuations by up to a factor of 2.5. Finally, we show that the strength of our model AGN component correlates with independent AGN indicators, suggesting that these galaxies truly host AGN. Notably, only 46% of the SED-detected AGN would be detected with a simple MIR color selection. Based on these results, we conclude that SED models which fit MIR data without AGN components are vulnerable to substantial bias in their derived parameters.
How specific Raman spectroscopic models are: a comparative study between different cancers
NASA Astrophysics Data System (ADS)
Singh, S. P.; Kumar, K. Kalyan; Chowdary, M. V. P.; Maheedhar, K.; Krishna, C. Murali
2010-02-01
Optical spectroscopic methods are being contemplated as adjunct/ alternative to existing 'Gold standard' of cancer diagnosis, histopathological examination. Several groups are actively pursuing diagnostic applications of Ramanspectroscopy in cancers. We have developed Raman spectroscopic models for diagnosis of breast, oral, stomach, colon and larynx cancers. So far, specificity and applicability of spectral- models has been limited to particular tissue origin. In this study we have evaluated explicitly of spectroscopic-models by analyzing spectra from already developed spectralmodels representing normal and malignant tissues of breast (46), cervix (52), colon (25), larynx (53), and oral (47). Spectral data was analyzed by Principal Component Analysis (PCA) using scores of factor, Mahalanobis distance and Spectral residuals as discriminating parameters. Multiparametric limit test approach was also explored. The preliminary unsupervised PCA of pooled data indicates that normal tissue types were always exclusive from their malignant counterparts. But when we consider tissue of different origin, large overlap among clusters was found. Supervised analysis by Mahalanobis distance and spectral residuals gave similar results. The 'limit test' approach where classification is based on match / mis-match of the given spectrum against all the available spectra has revealed that spectral models are very exclusive and specific. For example breast normal spectral model show matches only with breast normal spectra and mismatch to rest of the spectra. Same pattern was seen for most of spectral models. Therefore, results of the study indicate the exclusiveness and efficacy of Raman spectroscopic-models. Prospectively, these findings might open new application of Raman spectroscopic models in identifying a tumor as primary or metastatic.
Sun, Weifang; Yao, Bin; He, Yuchao; Zeng, Nianyin; He, Wangpeng
2017-01-01
Power generation using waste-gas is an effective and green way to reduce the emission of the harmful blast furnace gas (BFG) in pig-iron producing industry. Condition monitoring of mechanical structures in the BFG power plant is of vital importance to guarantee their safety and efficient operations. In this paper, we describe the detection of crack growth of bladed machinery in the BFG power plant via vibration measurement combined with an enhanced spectral correction technique. This technique enables high-precision identification of amplitude, frequency, and phase information (the harmonic information) belonging to deterministic harmonic components within the vibration signals. Rather than deriving all harmonic information using neighboring spectral bins in the fast Fourier transform spectrum, this proposed active frequency shift spectral correction method makes use of some interpolated Fourier spectral bins and has a better noise-resisting capacity. We demonstrate that the identified harmonic information via the proposed method is of suppressed numerical error when the same level of noises is presented in the vibration signal, even in comparison with a Hanning-window-based correction method. With the proposed method, we investigated vibration signals collected from a centrifugal compressor. Spectral information of harmonic tones, related to the fundamental working frequency of the centrifugal compressor, is corrected. The extracted spectral information indicates the ongoing development of an impeller blade crack that occurred in the centrifugal compressor. This method proves to be a promising alternative to identify blade cracks at early stages. PMID:28792453
Nepusz, Tamás; Sasidharan, Rajkumar; Paccanaro, Alberto
2010-03-09
An important problem in genomics is the automatic inference of groups of homologous proteins from pairwise sequence similarities. Several approaches have been proposed for this task which are "local" in the sense that they assign a protein to a cluster based only on the distances between that protein and the other proteins in the set. It was shown recently that global methods such as spectral clustering have better performance on a wide variety of datasets. However, currently available implementations of spectral clustering methods mostly consist of a few loosely coupled Matlab scripts that assume a fair amount of familiarity with Matlab programming and hence they are inaccessible for large parts of the research community. SCPS (Spectral Clustering of Protein Sequences) is an efficient and user-friendly implementation of a spectral method for inferring protein families. The method uses only pairwise sequence similarities, and is therefore practical when only sequence information is available. SCPS was tested on difficult sets of proteins whose relationships were extracted from the SCOP database, and its results were extensively compared with those obtained using other popular protein clustering algorithms such as TribeMCL, hierarchical clustering and connected component analysis. We show that SCPS is able to identify many of the family/superfamily relationships correctly and that the quality of the obtained clusters as indicated by their F-scores is consistently better than all the other methods we compared it with. We also demonstrate the scalability of SCPS by clustering the entire SCOP database (14,183 sequences) and the complete genome of the yeast Saccharomyces cerevisiae (6,690 sequences). Besides the spectral method, SCPS also implements connected component analysis and hierarchical clustering, it integrates TribeMCL, it provides different cluster quality tools, it can extract human-readable protein descriptions using GI numbers from NCBI, it interfaces with external tools such as BLAST and Cytoscape, and it can produce publication-quality graphical representations of the clusters obtained, thus constituting a comprehensive and effective tool for practical research in computational biology. Source code and precompiled executables for Windows, Linux and Mac OS X are freely available at http://www.paccanarolab.org/software/scps.
The Traceable Radiometry Underpinning Terrestrial and Helio Studies (TRUTHS) mission
NASA Astrophysics Data System (ADS)
Green, Paul D.; Fox, Nigel P.; Lobb, Daniel; Friend, Jonathan
2015-10-01
TRUTHS (Traceable Radiometry Underpinning Terrestrial- and Helio-Studies) is a proposed small satellite mission to enable a space-based climate observing system capable of delivering data of the quality needed to provide the information needed by policy makers to make robust mitigation and adaptation decisions. This is achieved by embedding trust and confidence in the data and derived information (tied to international standards) from both its own measurements and by upgrading the performance and interoperability of other EO platforms, such as the Sentinels by in-flight reference calibration. TRUTHS would provide measurements of incoming (total and spectrally resolved) and global reflected spectrally and spatially (50 m) solar radiation at the 0.3% uncertainty level. These fundamental climate data products can be convolved into the building blocks for many ECVs and EO applications as envisaged by the 2015 ESA science strategy; in a cost effective manner. We describe the scientific drivers for the TRUTHS mission and how the requirements for the climate benchmarking and cross-calibration reference sensor are both complementary and simply implemented, with a small additional complexity on top of heritage calibration schemes. The calibration scheme components and the route to SI-traceable Earth-reflected solar spectral radiance and solar spectral irradiance are described.
Free Flyer Total and Spectral Solar Irradiance Sensor (TSIS) and Climate Services Mission
NASA Technical Reports Server (NTRS)
Cahalan, R.; Pilewskie, P.; Woods, T.
2012-01-01
NOAA's planned Total and Spectral Solar Irradiance Sensor (TSIS) mission will fly along with the NOAA user service payloads Advanced Data Collection System (ADCS) and Search and Rescue Satellite Aided Tracking (SARSAT). In ' order to guarantee continuity in the 33-year solar irradiance climate data record, TSIS must be launched in time to overlap with current on-orbit solar irradiance instruments. Currently TSIS is moving towards a launch rcadinss date of January 2015. TSIS provides for continuation of the Total Irradiance Monitor (TIM) and the Spectral Irradiance Monitor (SIM) ,currently onboard NASA's Solar Radiation and Climate Experiment (SORCE) platform, launched in January 2003. The difficulty of ensuring continuity has increased due to the launch failure of NASA's Glory mission with its improved TIM. Achieving the needed overlap must now rely on extending SORCE. and maintaining the TSIS schedule. TSIS is one component of a NASA-NOAA joint program (JPSS) planned to transition certain climate observations to operational mode. We summarize issues of continuity, improvements being made to the TIM and 81M sensors, and plans to provide for traceability of total and spectral irradiance measurements to ground-based cryogenic standards.
Torres-Lapasió, J R; Pous-Torres, S; Ortiz-Bolsico, C; García-Alvarez-Coque, M C
2015-01-16
The optimisation of the resolution in high-performance liquid chromatography is traditionally performed attending only to the time information. However, even in the optimal conditions, some peak pairs may remain unresolved. Such incomplete resolution can be still accomplished by deconvolution, which can be carried out with more guarantees of success by including spectral information. In this work, two-way chromatographic objective functions (COFs) that incorporate both time and spectral information were tested, based on the peak purity (analyte peak fraction free of overlapping) and the multivariate selectivity (figure of merit derived from the net analyte signal) concepts. These COFs are sensitive to situations where the components that coelute in a mixture show some spectral differences. Therefore, they are useful to find out experimental conditions where the spectrochromatograms can be recovered by deconvolution. Two-way multivariate selectivity yielded the best performance and was applied to the separation using diode-array detection of a mixture of 25 phenolic compounds, which remained unresolved in the chromatographic order using linear and multi-linear gradients of acetonitrile-water. Peak deconvolution was carried out using the combination of orthogonal projection approach and alternating least squares. Copyright © 2014 Elsevier B.V. All rights reserved.
Discrimination among Panax species using spectral fingerprinting
USDA-ARS?s Scientific Manuscript database
Spectral fingerprints of samples of three Panax species (P. quinquefolius L., P. ginseng, and P. notoginseng) were acquired using UV, NIR, and MS spectrometry. With principal components analysis (PCA), all three methods allowed visual discrimination between all three species. All three methods wer...
Space weathering trends on carbonaceous asteroids: A possible explanation for Bennu's blue slope?
NASA Astrophysics Data System (ADS)
Lantz, C.; Binzel, R. P.; DeMeo, F. E.
2018-03-01
We compare primitive near-Earth asteroid spectral properties to the irradiated carbonaceous chondrite samples of Lantz et al. (2017) in order to assess how space weathering processes might influence taxonomic classification. Using the same eigenvectors from the asteroid taxonomy by DeMeo et al. (2009), we calculate the principal components for fresh and irradiated meteorites and find that change in spectral slope (blueing or reddening) causes a corresponding shift in the two first principal components along the same line that the C- and X-complexes track. Using a sample of B-, C-, X-, and D-type NEOs with visible and near-infrared spectral data, we further investigated the correlation between prinicipal components and the spectral curvature for the primitive asteroids. We find that space weathering effects are not just slope and albedo, but also include spectral curvature. We show how, through space weathering, surfaces having an original "C-type" reflectance can thus turn into a redder P-type or a bluer B-type, and that space weathering can also decrease (and disguise) the D-type population. Finally we take a look at the case of OSIRIS-REx target (101955) Bennu and propose an explanation for the blue and possibly red spectra that were previously observed on different locations of its surface: parts of Bennu's surface could have become blue due to space weathering, while fresher areas are redder. No clear prediction can be made on Hayabusa-2 target (162173) Ryugu.
The Uranian satellites and Hyperion - New spectrophotometry and compositional implications
NASA Astrophysics Data System (ADS)
Brown, R. H.
1983-12-01
New reflectance spectra at 3.5 percent resolution have been obtained for Ariel, Titania, Oberon, and Hyperion in the 0.8 to 1.6-micron spectrum region. The new spectra show no absorptions other than the 1.5 micron water-ice feature (within the precision of the data), and demonstrate extension into the 0.8- to 1.6 micron region of the 1.5- to 2.5 micron spectral similarity ofo Ariel to Hyperion (Brown and Cruikshank, 1983). The new data confirm the presence of a dark, spectrally bland component on/in the water-ice surfaces of the Uranian satellites, which, with some reservations, has spectral similarities to the dark substance on the leading side of lapetus and the dark material on/in the surface of Hyperion, as well as other dark, spectrally neutral substances such as charcoal. Attempts were made to match the spectra of Ariel, Titania, and Oberon with additive reflectance mixes (aeral coverage) of fine-grained water frost and various dark components such as charcoal, lampblack, and charcoal-water-ice mixtures. The results were broad limits on the amounts of possible areal coverage of a charcoal-like spectral component on the surfaces of the Uranian satellites, but the data are not of sufficient precision to conclusively determine whether the dominant mode of contaminant dispersal is areal or voluminal. The effect of highly variegated albedos on the diameters derived by Brown, Cruikshank, and Morrison (1982) is found to be small.
The Uranian satellites and Hyperion - New spectrophotometry and compositional implications
NASA Technical Reports Server (NTRS)
Brown, R. H.
1983-01-01
New reflectance spectra at 3.5 percent resolution have been obtained for Ariel, Titania, Oberon, and Hyperion in the 0.8 to 1.6-micron spectrum region. The new spectra show no absorptions other than the 1.5 micron water-ice feature (within the precision of the data), and demonstrate extension into the 0.8- to 1.6 micron region of the 1.5- to 2.5 micron spectral similarity ofo Ariel to Hyperion (Brown and Cruikshank, 1983). The new data confirm the presence of a dark, spectrally bland component on/in the water-ice surfaces of the Uranian satellites, which, with some reservations, has spectral similarities to the dark substance on the leading side of lapetus and the dark material on/in the surface of Hyperion, as well as other dark, spectrally neutral substances such as charcoal. Attempts were made to match the spectra of Ariel, Titania, and Oberon with additive reflectance mixes (aeral coverage) of fine-grained water frost and various dark components such as charcoal, lampblack, and charcoal-water-ice mixtures. The results were broad limits on the amounts of possible areal coverage of a charcoal-like spectral component on the surfaces of the Uranian satellites, but the data are not of sufficient precision to conclusively determine whether the dominant mode of contaminant dispersal is areal or voluminal. The effect of highly variegated albedos on the diameters derived by Brown, Cruikshank, and Morrison (1982) is found to be small.
Anisotropic Developments for Homogeneous Shear Flows
NASA Technical Reports Server (NTRS)
Cambon, Claude; Rubinstein, Robert
2006-01-01
The general decomposition of the spectral correlation tensor R(sub ij)(k) by Cambon et al. (J. Fluid Mech., 202, 295; J. Fluid Mech., 337, 303) into directional and polarization components is applied to the representation of R(sub ij)(k) by spherically averaged quantities. The decomposition splits the deviatoric part H(sub ij)(k) of the spherical average of R(sub ij)(k) into directional and polarization components H(sub ij)(sup e)(k) and H(sub ij)(sup z)(k). A self-consistent representation of the spectral tensor in the limit of weak anisotropy is constructed in terms of these spherically averaged quantities. The directional polarization components must be treated independently: models that attempt the same representation of the spectral tensor using the spherical average H(sub ij)(k) alone prove to be inconsistent with Navier-Stokes dynamics. In particular, a spectral tensor consistent with a prescribed Reynolds stress is not unique. The degree of anisotropy permitted by this theory is restricted by realizability requirements. Since these requirements will be less severe in a more accurate theory, a preliminary account is given of how to generalize the formalism of spherical averages to higher expansion of the spectral tensor. Directionality is described by a conventional expansion in spherical harmonics, but polarization requires an expansion in tensorial spherical harmonics generated by irreducible representations of the spatial rotation group SO(exp 3). These expansions are considered in more detail in the special case of axial symmetry.
Spectral Effects for an Ultrashort Pulse Train Propagating in a Two-Level Atom Medium
NASA Astrophysics Data System (ADS)
Liu, Bing-Xin; Gong, Shang-Qing; Song, Xiao-Hong; Li, Ru-Xin; Xu, Zhi-Zhan
2005-06-01
We investigate the spectra of a femtosecond pulse train propagating in a resonant two-level atom (TLA) medium. It is found that higher spectral components can be produced even for a 2π femtosecond pulse train. Furthermore, the spectral effects depend crucially on both the relative shift Φ and the delay time τ between the successive pulses of the femtosecond pulse train.
Bautista, Pinky A; Yagi, Yukako
2012-05-01
Hematoxylin and eosin (H&E) stain is currently the most popular for routine histopathology staining. Special and/or immuno-histochemical (IHC) staining is often requested to further corroborate the initial diagnosis on H&E stained tissue sections. Digital simulation of staining (or digital staining) can be a very valuable tool to produce the desired stained images from the H&E stained tissue sections instantaneously. We present an approach to digital staining of histopathology multispectral images by combining the effects of spectral enhancement and spectral transformation. Spectral enhancement is accomplished by shifting the N-band original spectrum of the multispectral pixel with the weighted difference between the pixel's original and estimated spectrum; the spectrum is estimated using M < N principal component (PC) vectors. The pixel's enhanced spectrum is transformed to the spectral configuration associated to its reaction to a specific stain by utilizing an N × N transformation matrix, which is derived through application of least mean squares method to the enhanced and target spectral transmittance samples of the different tissue components found in the image. Results of our experiments on the digital conversion of an H&E stained multispectral image to its Masson's trichrome stained equivalent show the viability of the method.
Pattern recognition in volcano seismology - Reducing spectral dimensionality
NASA Astrophysics Data System (ADS)
Unglert, K.; Radic, V.; Jellinek, M.
2015-12-01
Variations in the spectral content of volcano seismicity can relate to changes in volcanic activity. Low-frequency seismic signals often precede or accompany volcanic eruptions. However, they are commonly manually identified in spectra or spectrograms, and their definition in spectral space differs from one volcanic setting to the next. Increasingly long time series of monitoring data at volcano observatories require automated tools to facilitate rapid processing and aid with pattern identification related to impending eruptions. Furthermore, knowledge transfer between volcanic settings is difficult if the methods to identify and analyze the characteristics of seismic signals differ. To address these challenges we evaluate whether a machine learning technique called Self-Organizing Maps (SOMs) can be used to characterize the dominant spectral components of volcano seismicity without the need for any a priori knowledge of different signal classes. This could reduce the dimensions of the spectral space typically analyzed by orders of magnitude, and enable rapid processing and visualization. Preliminary results suggest that the temporal evolution of volcano seismicity at Kilauea Volcano, Hawai`i, can be reduced to as few as 2 spectral components by using a combination of SOMs and cluster analysis. We will further refine our methodology with several datasets from Hawai`i and Alaska, among others, and compare it to other techniques.
Spectral modelling of multicomponent landscapes in the Sahel
NASA Technical Reports Server (NTRS)
Hanan, N. P.; Prince, S. D.; Hiernaux, P. H. Y.
1991-01-01
Simple additive models are used to examine the infuence of differing soil types on the spatial average spectral reflectance and normalized difference vegetation index (NDVI). The spatial average NDVI is shown to be a function of the brightness (red plus near-infrared reflectances), the NDVI, and the fractional cover of the components. In landscapes where soil and vegetation can be considered the only components, the NDVI-brightness model can be inverted to obtain the NDVI of vegetation. The red and near-infrared component reflectances of soil and vegetation are determined on the basis of aerial photoradiometer data from Mali. The relationship between the vegetation component NDVI and plant cover is found to be better than between the NDVI of the entire landscape and plant cover. It is concluded that the usefulness of this modeling approach depends on the existence of clearly distinguishable landscape components.
In Situ Detection of Strong Langmuir Turbulence Processes in Solar Type III Radio Bursts
NASA Technical Reports Server (NTRS)
Golla, Thejappa; Macdowall, Robert J.; Bergamo, M.
2012-01-01
The high time resolution observations obtained by the WAVES experiment of the STEREO spacecraft in solar type III radio bursts show that Langmuir waves often occur as intense localized wave packets. These wave packets are characterized by short durations of only a few ms and peak intensities, which well exceed the supersonic modulational instability (MI) thresholds. These timescales and peak intensities satisfy the criterion of the solitons collapsed to spatial scales of a few hundred Debye lengths. The spectra of these wave packets consist of primary spectral peaks corresponding to beam-resonant Langmuir waves, two or more sidebands corresponding to down-shifted and up-shifted daughter Langmuir waves, and low frequency enhancements below a few hundred Hz corresponding to daughter ion sound waves. The frequencies and wave numbers of these spectral components satisfy the resonance conditions of the modulational instability (MI). Moreover, the tricoherences, computed using trispectral analysis techniques show that these spectral components are coupled to each other with a high degree of coherency as expected of the MI type of four wave interactions. The high intensities, short scale lengths, sideband spectral structures and low frequency spectral enhancements and, high levels of tricoherences amongst the spectral components of these wave packets provide unambiguous evidence for the supersonic MI and related strong turbulence processes in type III radio bursts. The implication of these observations include: (1) the MI and related strong turbulence processes often occur in type III source regions, (2) the strong turbulence processes probably play very important roles in beam stabilization as well as conversion of Langmuir waves into escaping radiation at the fundamental and second harmonic of the electron plasma frequency, fpe, and (3) the Langmuir collapse probably follows the route of MI in type III radio bursts.
NASA Technical Reports Server (NTRS)
Liang, Z.; Fixsen, D. J.; Gold, B.
2012-01-01
We show that a one-component variable-emissivity-spectral-index model (the free- model) provides more physically motivated estimates of dust temperature at the Galactic polar caps than one- or two-component fixed-emissivity-spectral-index models (fixed- models) for interstellar dust thermal emission at far-infrared and millimeter wavelengths. For the comparison we have fit all-sky one-component dust models with fixed or variable emissivity spectral index to a new and improved version of the 210-channel dust spectra from the COBE-FIRAS, the 100-240 micrometer maps from the COBE-DIRBE and the 94 GHz dust map from the WMAP. The best model, the free-alpha model, is well constrained by data at 60-3000 GHz over 86 per cent of the total sky area. It predicts dust temperature (T(sub dust)) to be 13.7-22.7 (plus or minus 1.3) K, the emissivity spectral index (alpha) to be 1.2-3.1 (plus or minus 0.3) and the optical depth (tau) to range 0.6-46 x 10(exp -5) with a 23 per cent uncertainty. Using these estimates, we present all-sky evidence for an inverse correlation between the emissivity spectral index and dust temperature, which fits the relation alpha = 1/(delta + omega (raised dot) T(sub dust) with delta = -.0.510 plus or minus 0.011 and omega = 0.059 plus or minus 0.001. This best model will be useful to cosmic microwave background experiments for removing foreground dust contamination and it can serve as an all-sky extended-frequency reference for future higher resolution dust models.
Garcia, Jair E; Greentree, Andrew D; Shrestha, Mani; Dorin, Alan; Dyer, Adrian G
2014-01-01
The study of the signal-receiver relationship between flowering plants and pollinators requires a capacity to accurately map both the spectral and spatial components of a signal in relation to the perceptual abilities of potential pollinators. Spectrophotometers can typically recover high resolution spectral data, but the spatial component is difficult to record simultaneously. A technique allowing for an accurate measurement of the spatial component in addition to the spectral factor of the signal is highly desirable. Consumer-level digital cameras potentially provide access to both colour and spatial information, but they are constrained by their non-linear response. We present a robust methodology for recovering linear values from two different camera models: one sensitive to ultraviolet (UV) radiation and another to visible wavelengths. We test responses by imaging eight different plant species varying in shape, size and in the amount of energy reflected across the UV and visible regions of the spectrum, and compare the recovery of spectral data to spectrophotometer measurements. There is often a good agreement of spectral data, although when the pattern on a flower surface is complex a spectrophotometer may underestimate the variability of the signal as would be viewed by an animal visual system. Digital imaging presents a significant new opportunity to reliably map flower colours to understand the complexity of these signals as perceived by potential pollinators. Compared to spectrophotometer measurements, digital images can better represent the spatio-chromatic signal variability that would likely be perceived by the visual system of an animal, and should expand the possibilities for data collection in complex, natural conditions. However, and in spite of its advantages, the accuracy of the spectral information recovered from camera responses is subject to variations in the uncertainty levels, with larger uncertainties associated with low radiance levels.
Hertog, W; Llenas, A; Carreras, J
2015-11-30
This article demonstrates the benefits of complementing a daylight-lit environment with a spectrally tunable illumination system. The spectral components of daylight present in the room are measured by a low-cost miniature spectrophotometer and processed through a number of optimization algorithms, carefully trading color fidelity for energy efficiency. Spectrally-tunable luminaires provide only those wavelengths that ensure that either the final illumination spectrum inside the room is kept constant or carefully follows the dynamic spectral pattern of natural daylight. Analyzing the measured data proves that such a hybrid illumination system brings both unprecendented illumination quality and significant energy savings.
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.
Spectral compression algorithms for the analysis of very large multivariate images
Keenan, Michael R.
2007-10-16
A method for spectrally compressing data sets enables the efficient analysis of very large multivariate images. The spectral compression algorithm uses a factored representation of the data that can be obtained from Principal Components Analysis or other factorization technique. Furthermore, a block algorithm can be used for performing common operations more efficiently. An image analysis can be performed on the factored representation of the data, using only the most significant factors. The spectral compression algorithm can be combined with a spatial compression algorithm to provide further computational efficiencies.
ASPECT spectral imaging satellite proposal to AIDA/AIM CubeSat payload
NASA Astrophysics Data System (ADS)
Kohout, Tomas; Näsilä, Antti; Tikka, Tuomas; Penttilä, Antti; Muinonen, Karri; Kestilä, Antti; Granvik, Mikael; Kallio, Esa
2016-04-01
ASPECT (Asteroid Spectral Imaging Mission) is a part of AIDA/AIM project and aims to study the composition of the Didymos binary asteroid and the effects of space weathering and shock metamorphism in order to gain understanding of the formation and evolution of the Solar System. The joint ESA/NASA AIDA (Asteroid Impact & Deflection Assessment) mission to binary asteroid Didymos consists of AIM (Asteroid Impact Mission, ESA) and DART (Double Asteroid Redirection Test, NASA). DART is targeted to impact Didymos secondary component (Didymoon) and serve as a kinetic impactor to demonstrate deflection of potentially hazardous asteroids. AIM will serve as an observational spacecraft to evaluate the effects of the impact and resulting changes in the Didymos dynamic parameters. The AIM mission will also carry two CubeSat miniaturized satellites, released in Didymoon proximity. This arrangement opens up a possibility for secondary scientific experiments. ASPECT is one of the proposed CubeSat payloads. Whereas Didymos is a space-weathered binary asteroid, the DART impactor is expected to produce a crater and excavate fresh material from the secondary component (Didymoon). Spectral comparison of the mature surface to the freshly exposed material will allow to directly deter-mine space weathering effects. It will be also possible to study spectral shock effects within the impact crater. ASPECT will also demonstrate for the first time the joint spacecraft - CubeSat operations in asteroid proximity and miniature spectral imager operation in deep-space environment. Science objectives: 1. Study of the surface composition of the Didymos system. 2. Photometric observations (and modeling) under varying phase angle and distance. 3. Study of space weathering effects on asteroids (comparison of mature / freshly exposed material). 4. Study of shock effects (spectral properties of crater interior). 5. Observations during the DART impact. Engineering objectives: 1. Demonstration of CubeSat semi-autonomous operations in deep space environment. 2. Navigation in the vicinity of a binary asteroid. 3. Demonstration of a satellite survival during impact. 4. Demonstration of joint spacecraft - CubeSat operations. ASPECT is a 3U CubeSat (size of 3 units, Fig. 1) equipped with a spectral imager from 500 nm to 1600 nm (spatial resolution < 2 m, spectral resolution 10 - 30 nm; VIS channel 512 x 512 pixels, NIR channel 256 x 256 pixels), and a non-imaging spectrometer from 1600 - 2500 nm. The design is based on the Aalto-1 CubeSat Spectral Imager heritage. ASPECT will also demonstrate the capabilities of a CubeSat and a miniature spectral imager for the first time in deep-space environment. Acknowledgements: This work is done under Sys-Nova: R&D Studies Competition for Innovation contract with ESA.