On the upper ocean turbulent dissipation rate due to microscale breakers and small whitecaps

NASA Astrophysics Data System (ADS)

Banner, Michael L.; Morison, Russel P.

2018-06-01

In ocean wave modelling, accurately computing the evolution of the wind-wave spectrum depends on the source terms and the spectral bandwidth used. The wave dissipation rate source term which spectrally quantifies wave breaking and other dissipative processes remains poorly understood, including the spectral bandwidth needed to capture the essential model physics. The observational study of Sutherland and Melville (2015a) investigated the relative dissipation rate contributions of breaking waves, from large-scale whitecaps to microbreakers. They concluded that a large fraction of wave energy was dissipated by microbreakers. However, in strong contrast with their findings, our analysis of their data and other recent data sets shows that for young seas, microbreakers and small whitecaps contribute only a small fraction of the total breaking wave dissipation rate. For older seas, we find microbreakers and small whitecaps contribute a large fraction of the breaking wave dissipation rate, but this is only a small fraction of the total dissipation rate, which is now dominated by non-breaking contributions. Hence, for all the wave age conditions observed, microbreakers make an insignificant contribution to the total wave dissipation rate in the wave boundary layer. We tested the sensitivity of the results to the SM15a whitecap analysis methodology by transforming the SM15a breaking data using our breaking crest processing methodology. This resulted in the small-scale breaking waves making an even smaller contribution to the total wave dissipation rate, and so the result is independent of the breaker processing methodology. Comparison with other near-surface total TKE dissipation rate observations also support this conclusion. These contributions to the spectral dissipation rate in ocean wave models are small and need not be explicitly resolved.

Analysis of effects of impurities intentionally incorporated into silicon

NASA Technical Reports Server (NTRS)

Uno, F.

1977-01-01

A methodology was developed and implemented to allow silicon samples containing intentionally incorporated impurities to be fabricated into finished solar cells under carefully controlled conditions. The electrical and spectral properties were then measured for each group processed.

Relationship between perceived politeness and spectral characteristics of voice

NASA Astrophysics Data System (ADS)

Ito, Mika

2005-04-01

This study investigates the role of voice quality in perceiving politeness under conditions of varying relative social status among Japanese male speakers. The work focuses on four important methodological issues: experimental control of sociolinguistic aspects, eliciting natural spontaneous speech, obtaining recording quality suitable for voice quality analysis, and assessment of glottal characteristics through the use of non-invasive direct measurements of the speech spectrum. To obtain natural, unscripted utterances, the speech data were collected with a Map Task. This methodology allowed us to study the effect of manipulating relative social status among participants in the same community. We then computed the relative amplitudes of harmonics and formant peaks in spectra obtained from the Map Task recordings. Finally, an experiment was conducted to observe the alignment between acoustic measures and the perceived politeness of the voice samples. The results suggest that listeners' perceptions of politeness are determined by spectral characteristics of speakers, in particular, spectral tilts obtained by computing the difference in amplitude between the first harmonic and the third formant.

A Multiscale Vibrational Spectroscopic Approach for Identification and Biochemical Characterization of Pollen

PubMed Central

Bağcıoğlu, Murat; Zimmermann, Boris; Kohler, Achim

2015-01-01

Background Analysis of pollen grains reveals valuable information on biology, ecology, forensics, climate change, insect migration, food sources and aeroallergens. Vibrational (infrared and Raman) spectroscopies offer chemical characterization of pollen via identifiable spectral features without any sample pretreatment. We have compared the level of chemical information that can be obtained by different multiscale vibrational spectroscopic techniques. Methodology Pollen from 15 different species of Pinales (conifers) were measured by seven infrared and Raman methodologies. In order to obtain infrared spectra, both reflectance and transmission measurements were performed on ground and intact pollen grains (bulk measurements), in addition, infrared spectra were obtained by microspectroscopy of multigrain and single pollen grain measurements. For Raman microspectroscopy measurements, spectra were obtained from the same pollen grains by focusing two different substructures of pollen grain. The spectral data from the seven methodologies were integrated into one data model by the Consensus Principal Component Analysis, in order to obtain the relations between the molecular signatures traced by different techniques. Results The vibrational spectroscopy enabled biochemical characterization of pollen and detection of phylogenetic variation. The spectral differences were clearly connected to specific chemical constituents, such as lipids, carbohydrates, carotenoids and sporopollenins. The extensive differences between pollen of Cedrus and the rest of Pinaceae family were unambiguously connected with molecular composition of sporopollenins in pollen grain wall, while pollen of Picea has apparently higher concentration of carotenoids than the rest of the family. It is shown that vibrational methodologies have great potential for systematic collection of data on ecosystems and that the obtained phylogenetic variation can be well explained by the biochemical composition of pollen. Out of the seven tested methodologies, the best taxonomical differentiation of pollen was obtained by infrared measurements on bulk samples, as well as by Raman microspectroscopy measurements of the corpus region of the pollen grain. Raman microspectroscopy measurements indicate that measurement area, as well as the depth of focus, can have crucial influence on the obtained data. PMID:26376486

Spectroscopy by joint spectral and time domain optical coherence tomography

NASA Astrophysics Data System (ADS)

Szkulmowski, Maciej; Tamborski, Szymon; Wojtkowski, Maciej

2015-03-01

We present the methodology for spectroscopic examination of absorbing media being the combination of Spectral Optical Coherence Tomography and Fourier Transform Spectroscopy. The method bases on the joint Spectral and Time OCT computational scheme and simplifies data analysis procedure as compared to the mostly used windowing-based Spectroscopic OCT methods. The proposed experimental setup is self-calibrating in terms of wavelength-pixel assignment. The performance of the method in measuring absorption spectrum was checked with the use of the reflecting phantom filled with the absorbing agent (indocyanine green). The results show quantitative accordance with the controlled exact results provided by the reference method.

FT-IR spectroscopy and multivariate analysis as an auxiliary tool for diagnosis of mental disorders: Bipolar and schizophrenia cases

NASA Astrophysics Data System (ADS)

Ogruc Ildiz, G.; Arslan, M.; Unsalan, O.; Araujo-Andrade, C.; Kurt, E.; Karatepe, H. T.; Yilmaz, A.; Yalcinkaya, O. B.; Herken, H.

2016-01-01

In this study, a methodology based on Fourier-transform infrared spectroscopy and principal component analysis and partial least square methods is proposed for the analysis of blood plasma samples in order to identify spectral changes correlated with some biomarkers associated with schizophrenia and bipolarity. Our main goal was to use the spectral information for the calibration of statistical models to discriminate and classify blood plasma samples belonging to bipolar and schizophrenic patients. IR spectra of 30 samples of blood plasma obtained from each, bipolar and schizophrenic patients and healthy control group were collected. The results obtained from principal component analysis (PCA) show a clear discrimination between the bipolar (BP), schizophrenic (SZ) and control group' (CG) blood samples that also give possibility to identify three main regions that show the major differences correlated with both mental disorders (biomarkers). Furthermore, a model for the classification of the blood samples was calibrated using partial least square discriminant analysis (PLS-DA), allowing the correct classification of BP, SZ and CG samples. The results obtained applying this methodology suggest that it can be used as a complimentary diagnostic tool for the detection and discrimination of these mental diseases.

Quantitative Analysis of Spectral Interference of Spontaneous Raman Scattering in High-Pressure Fuel-Rich H2-Air Combustion

NASA Technical Reports Server (NTRS)

Kojima, Jun; Nguyen, Quang-Viet

2004-01-01

We present a theoretical study of the spectral interferences in the spontaneous Raman scattering spectra of major combustion products in 30-atm fuel-rich hydrogen-air flames. An effective methodology is introduced to choose an appropriate line-shape model for simulating Raman spectra in high-pressure combustion environments. The Voigt profile with the additive approximation assumption was found to provide a reasonable model of the spectral line shape for the present analysis. The rotational/vibrational Raman spectra of H2, N2, and H2O were calculated using an anharmonic-oscillator model using the latest collisional broadening coefficients. The calculated spectra were validated with data obtained in a 10-atm fuel-rich H2-air flame and showed excellent agreement. Our quantitative spectral analysis for equivalence ratios ranging from 1.5 to 5.0 revealed substantial amounts of spectral cross-talk between the rotational H2 lines and the N2 O-/Q-branch; and between the vibrational H2O(0,3) line and the vibrational H2O spectrum. We also address the temperature dependence of the spectral cross-talk and extend our analysis to include a cross-talk compensation technique that removes the nterference arising from the H2 Raman spectra onto the N2, or H2O spectra.

Analytical robustness of quantitative NIR chemical imaging for Islamic paper characterization

NASA Astrophysics Data System (ADS)

Mahgoub, Hend; Gilchrist, John R.; Fearn, Thomas; Strlič, Matija

2017-07-01

Recently, spectral imaging techniques such as Multispectral (MSI) and Hyperspectral Imaging (HSI) have gained importance in the field of heritage conservation. This paper explores the analytical robustness of quantitative chemical imaging for Islamic paper characterization by focusing on the effect of different measurement and processing parameters, i.e. acquisition conditions and calibration on the accuracy of the collected spectral data. This will provide a better understanding of the technique that can provide a measure of change in collections through imaging. For the quantitative model, special calibration target was devised using 105 samples from a well-characterized reference Islamic paper collection. Two material properties were of interest: starch sizing and cellulose degree of polymerization (DP). Multivariate data analysis methods were used to develop discrimination and regression models which were used as an evaluation methodology for the metrology of quantitative NIR chemical imaging. Spectral data were collected using a pushbroom HSI scanner (Gilden Photonics Ltd) in the 1000-2500 nm range with a spectral resolution of 6.3 nm using a mirror scanning setup and halogen illumination. Data were acquired at different measurement conditions and acquisition parameters. Preliminary results showed the potential of the evaluation methodology to show that measurement parameters such as the use of different lenses and different scanning backgrounds may not have a great influence on the quantitative results. Moreover, the evaluation methodology allowed for the selection of the best pre-treatment method to be applied to the data.

Spectral imaging: principles and applications.

PubMed

Garini, Yuval; Young, Ian T; McNamara, George

2006-08-01

Spectral imaging extends the capabilities of biological and clinical studies to simultaneously study multiple features such as organelles and proteins qualitatively and quantitatively. Spectral imaging combines two well-known scientific methodologies, namely spectroscopy and imaging, to provide a new advantageous tool. The need to measure the spectrum at each point of the image requires combining dispersive optics with the more common imaging equipment, and introduces constrains as well. The principles of spectral imaging and a few representative applications are described. Spectral imaging analysis is necessary because the complex data structure cannot be analyzed visually. A few of the algorithms are discussed with emphasis on the usage for different experimental modes (fluorescence and bright field). Finally, spectral imaging, like any method, should be evaluated in light of its advantages to specific applications, a selection of which is described. Spectral imaging is a relatively new technique and its full potential is yet to be exploited. Nevertheless, several applications have already shown its potential. (c) 2006 International Society for Analytical Cytology.

Optical characterization of agricultural pest insects: a methodological study in the spectral and time domains

NASA Astrophysics Data System (ADS)

Li, Y. Y.; Zhang, H.; Duan, Z.; Lian, M.; Zhao, G. Y.; Sun, X. H.; Hu, J. D.; Gao, L. N.; Feng, H. Q.; Svanberg, S.

2016-08-01

Identification of agricultural pest insects is an important aspect in insect research and agricultural monitoring. We have performed a methodological study of how spectroscopic techniques and wing-beat frequency analysis might provide relevant information. An optical system based on the combination of close-range remote sensing and reflectance spectroscopy was developed to study the optical characteristics of different flying insects, collected in Southern China. The results demonstrate that the combination of wing-beat frequency assessment and reflectance spectral analysis has the potential to successfully differentiate between insect species. Further, studies of spectroscopic characteristics of fixed specimen of insects, also from Central China, showed the possibility of refined agricultural pest identification. Here, in addition to reflectance recordings also laser-induced fluorescence spectra were investigated for all the species of insects under study and found to provide complementary information to optically distinguish insects. In order to prove the practicality of the techniques explored, clearly fieldwork aiming at elucidating the variability of parameters, even within species, must be performed.

Limits of clinical tests to screen autonomic function in diabetes type 1.

PubMed

Ducher, M; Bertram, D; Sagnol, I; Cerutti, C; Thivolet, C; Fauvel, J P

2001-11-01

A precocious detection of cardiac autonomic dysfunction is of major clinical interest that could lead to a more intensive supervision of diabetic patients. However, classical clinical exploration of cardiac autonomic function is not easy to undertake in a reproducible way. Thus, respective interests of autonomic nervous parameters provided by both clinical tests and computerized analysis of resting blood pressure were checked in type 1 diabetic patients without orthostatic hypotension and microalbuminuria. Thirteen diabetic subjects matched for age and gender to thirteen healthy subjects volunteered to participate to the study. From clinical tests (standing up, deep breathing, Valsalva maneuver, handgrip test), autonomic function was scored according to Ewing's methodology. Analysis of resting beat to beat blood pressure provided autonomic indices of the cardiac function (spectral analysis or Z analysis). 5 of the 13 diabetic patients exhibited a pathological score (more than one pathological response) suggesting the presence of cardiovascular autonomic dysfunction. The most discriminative test was the deep breathing test. However, spectral indices of BP recordings and baro-reflex sensitivity (BRS) of these 5 subjects were similar to those of healthy subjects and of remaining diabetic subjects. Alteration in Ewing's score given by clinical tests may not reflect an alteration of cardiac autonomic function in asymptomatic type 1 diabetic patients, because spectral indices of sympathetic and parasympathetic (including BRS) function were within normal range. Our results strongly suggest to confront results provided by both methodologies before concluding to an autonomic cardiac impairment in asymptomatic diabetic patients.

Corrigendum to "Enhancing endmember selection in multiple endmember spectral mixture analysis (MESMA) for urban impervious surface area mapping using spectral angle and spectral distance parameters" [Int. J. Appl. Earth Observ. Geoinf. 33 (2014) 290-301

NASA Astrophysics Data System (ADS)

Fan, Fenglei; Deng, Yingbin

2015-04-01

Since publication, the authors have been advised of one prior methodological article not cited in our original paper. The missed reference from the paper is "Andreou, C., Karathanassi, V., 2012. A novel multiple endmember spectral mixture analysis using spectral angle distance. Geoscience and Remote Sensing Symposium (IGARSS) 2012 IEEE International, 4110-4113." This reference "Andreou, C., Karathanassi, V., 2012 in proceeding of IGARSS" should be cited in the Part 3 and Table 1, whereby in the fist sentence of Part 3 and the last sentence of caption of Table 1. The following should be added (in Part 3: According to the traditional MESMA and referring to MESMA-SAD method which is reported by Andreou and Karathanassi; in caption of Table 1: Based on the MESMA-SAD method of Andreou and Karathanassi). We apologize to the authors and workers concerned for this oversight and are pleased to acknowledge their contributions.

Spectral analysis software improves confidence in plant and soil water stable isotope analyses performed by isotope ratio infrared spectroscopy (IRIS).

PubMed

West, A G; Goldsmith, G R; Matimati, I; Dawson, T E

2011-08-30

Previous studies have demonstrated the potential for large errors to occur when analyzing waters containing organic contaminants using isotope ratio infrared spectroscopy (IRIS). In an attempt to address this problem, IRIS manufacturers now provide post-processing spectral analysis software capable of identifying samples with the types of spectral interference that compromises their stable isotope analysis. Here we report two independent tests of this post-processing spectral analysis software on two IRIS systems, OA-ICOS (Los Gatos Research Inc.) and WS-CRDS (Picarro Inc.). Following a similar methodology to a previous study, we cryogenically extracted plant leaf water and soil water and measured the δ(2)H and δ(18)O values of identical samples by isotope ratio mass spectrometry (IRMS) and IRIS. As an additional test, we analyzed plant stem waters and tap waters by IRMS and IRIS in an independent laboratory. For all tests we assumed that the IRMS value represented the "true" value against which we could compare the stable isotope results from the IRIS methods. Samples showing significant deviations from the IRMS value (>2σ) were considered to be contaminated and representative of spectral interference in the IRIS measurement. Over the two studies, 83% of plant species were considered contaminated on OA-ICOS and 58% on WS-CRDS. Post-analysis, spectra were analyzed using the manufacturer's spectral analysis software, in order to see if the software correctly identified contaminated samples. In our tests the software performed well, identifying all the samples with major errors. However, some false negatives indicate that user evaluation and testing of the software are necessary. Repeat sampling of plants showed considerable variation in the discrepancies between IRIS and IRMS. As such, we recommend that spectral analysis of IRIS data must be incorporated into standard post-processing routines. Furthermore, we suggest that the results from spectral analysis be included when reporting stable isotope data from IRIS. Copyright © 2011 John Wiley & Sons, Ltd.

Detecting Unknown Artificial Urban Surface Materials Based on Spectral Dissimilarity Analysis.

PubMed

Jilge, Marianne; Heiden, Uta; Habermeyer, Martin; Mende, André; Juergens, Carsten

2017-08-08

High resolution imaging spectroscopy data have been recognised as a valuable data resource for augmenting detailed material inventories that serve as input for various urban applications. Image-specific urban spectral libraries are successfully used in urban imaging spectroscopy studies. However, the regional- and sensor-specific transferability of such libraries is limited due to the wide range of different surface materials. With the developed methodology, incomplete urban spectral libraries can be utilised by assuming that unknown surface material spectra are dissimilar to the known spectra in a basic spectral library (BSL). The similarity measure SID-SCA (Spectral Information Divergence-Spectral Correlation Angle) is applied to detect image-specific unknown urban surfaces while avoiding spectral mixtures. These detected unknown materials are categorised into distinct and identifiable material classes based on their spectral and spatial metrics. Experimental results demonstrate a successful redetection of material classes that had been previously erased in order to simulate an incomplete BSL. Additionally, completely new materials e.g., solar panels were identified in the data. It is further shown that the level of incompleteness of the BSL and the defined dissimilarity threshold are decisive for the detection of unknown material classes and the degree of spectral intra-class variability. A detailed accuracy assessment of the pre-classification results, aiming to separate natural and artificial materials, demonstrates spectral confusions between spectrally similar materials utilizing SID-SCA. However, most spectral confusions occur between natural or artificial materials which are not affecting the overall aim. The dissimilarity analysis overcomes the limitations of working with incomplete urban spectral libraries and enables the generation of image-specific training databases.

Detecting Unknown Artificial Urban Surface Materials Based on Spectral Dissimilarity Analysis

PubMed Central

Jilge, Marianne; Heiden, Uta; Habermeyer, Martin; Mende, André; Juergens, Carsten

2017-01-01

High resolution imaging spectroscopy data have been recognised as a valuable data resource for augmenting detailed material inventories that serve as input for various urban applications. Image-specific urban spectral libraries are successfully used in urban imaging spectroscopy studies. However, the regional- and sensor-specific transferability of such libraries is limited due to the wide range of different surface materials. With the developed methodology, incomplete urban spectral libraries can be utilised by assuming that unknown surface material spectra are dissimilar to the known spectra in a basic spectral library (BSL). The similarity measure SID-SCA (Spectral Information Divergence-Spectral Correlation Angle) is applied to detect image-specific unknown urban surfaces while avoiding spectral mixtures. These detected unknown materials are categorised into distinct and identifiable material classes based on their spectral and spatial metrics. Experimental results demonstrate a successful redetection of material classes that had been previously erased in order to simulate an incomplete BSL. Additionally, completely new materials e.g., solar panels were identified in the data. It is further shown that the level of incompleteness of the BSL and the defined dissimilarity threshold are decisive for the detection of unknown material classes and the degree of spectral intra-class variability. A detailed accuracy assessment of the pre-classification results, aiming to separate natural and artificial materials, demonstrates spectral confusions between spectrally similar materials utilizing SID-SCA. However, most spectral confusions occur between natural or artificial materials which are not affecting the overall aim. The dissimilarity analysis overcomes the limitations of working with incomplete urban spectral libraries and enables the generation of image-specific training databases. PMID:28786947

FTIR-ATR infrared spectroscopy for the detection of ochratoxin A in dried vine fruit.

PubMed

Galvis-Sánchez, Andrea C; Barros, Antonio; Delgadillo, Ivonne

2007-11-01

A method of screening sultanas for ochratoxin A (OTA) contamination, using mid-infrared spectroscopy/Golden Gate single-reflection ATR (attenuated total reflection), is described. The main spectral characteristics of sultanas from different sources were identified in a preliminary acquisition and spectral analysis study. Principal component analysis (PCA) showed that samples of various origins had different spectral characteristics, especially in water content and the fingerprint region. A lack of reproducibility was observed in the spectra acquired on different days. However, spectral repeatability was greatly improved when water activity of the sample was set at 0.62. A calibration curve of OTA was constructed in the range 10-40 microg OTA kg(-1). Samples with OTA levels higher than 20 microg kg(-1) were separated from samples contaminated with a lower concentration (10 microg OTA kg(-1)) and from uncontaminated samples. The reported methodology is a reliable and simple technique for screening dried vine fruit for OTA.

Extension of least squares spectral resolution algorithm to high-resolution lipidomics data.

PubMed

Zeng, Ying-Xu; Mjøs, Svein Are; David, Fabrice P A; Schmid, Adrien W

2016-03-31

Lipidomics, which focuses on the global study of molecular lipids in biological systems, has been driven tremendously by technical advances in mass spectrometry (MS) instrumentation, particularly high-resolution MS. This requires powerful computational tools that handle the high-throughput lipidomics data analysis. To address this issue, a novel computational tool has been developed for the analysis of high-resolution MS data, including the data pretreatment, visualization, automated identification, deconvolution and quantification of lipid species. The algorithm features the customized generation of a lipid compound library and mass spectral library, which covers the major lipid classes such as glycerolipids, glycerophospholipids and sphingolipids. Next, the algorithm performs least squares resolution of spectra and chromatograms based on the theoretical isotope distribution of molecular ions, which enables automated identification and quantification of molecular lipid species. Currently, this methodology supports analysis of both high and low resolution MS as well as liquid chromatography-MS (LC-MS) lipidomics data. The flexibility of the methodology allows it to be expanded to support more lipid classes and more data interpretation functions, making it a promising tool in lipidomic data analysis. Copyright © 2016 Elsevier B.V. All rights reserved.

Development of hazard-compatible building fragility and vulnerability models

USGS Publications Warehouse

Karaca, E.; Luco, N.

2008-01-01

We present a methodology for transforming the structural and non-structural fragility functions in HAZUS into a format that is compatible with conventional seismic hazard analysis information. The methodology makes use of the building capacity (or pushover) curves and related building parameters provided in HAZUS. Instead of the capacity spectrum method applied in HAZUS, building response is estimated by inelastic response history analysis of corresponding single-degree-of-freedom systems under a large number of earthquake records. Statistics of the building response are used with the damage state definitions from HAZUS to derive fragility models conditioned on spectral acceleration values. Using the developed fragility models for structural and nonstructural building components, with corresponding damage state loss ratios from HAZUS, we also derive building vulnerability models relating spectral acceleration to repair costs. Whereas in HAZUS the structural and nonstructural damage states are treated as if they are independent, our vulnerability models are derived assuming "complete" nonstructural damage whenever the structural damage state is complete. We show the effects of considering this dependence on the final vulnerability models. The use of spectral acceleration (at selected vibration periods) as the ground motion intensity parameter, coupled with the careful treatment of uncertainty, makes the new fragility and vulnerability models compatible with conventional seismic hazard curves and hence useful for extensions to probabilistic damage and loss assessment.

Remote sensing applied to agriculture: Basic principles, methodology, and applications

NASA Technical Reports Server (NTRS)

Dejesusparada, N. (Principal Investigator); Mendonca, F. J.

1981-01-01

The general principles of remote sensing techniques as applied to agriculture and the methods of data analysis are described. the theoretical spectral responses of crops; reflectance, transmittance, and absorbtance of plants; interactions of plants and soils with reflectance energy; leaf morphology; and factors which affect the reflectance of vegetation cover are dicussed. The methodologies of visual and computer-aided analyses of LANDSAT data are presented. Finally, a case study wherein infrared film was used to detect crop anomalies and other data applications are described.

Methodological framework for heart rate variability analysis during exercise: application to running and cycling stress testing.

PubMed

Hernando, David; Hernando, Alberto; Casajús, Jose A; Laguna, Pablo; Garatachea, Nuria; Bailón, Raquel

2018-05-01

Standard methodologies of heart rate variability analysis and physiological interpretation as a marker of autonomic nervous system condition have been largely published at rest, but not so much during exercise. A methodological framework for heart rate variability (HRV) analysis during exercise is proposed, which deals with the non-stationary nature of HRV during exercise, includes respiratory information, and identifies and corrects spectral components related to cardiolocomotor coupling (CC). This is applied to 23 male subjects who underwent different tests: maximal and submaximal, running and cycling; where the ECG, respiratory frequency and oxygen consumption were simultaneously recorded. High-frequency (HF) power results largely modified from estimations with the standard fixed band to those obtained with the proposed methodology. For medium and high levels of exercise and recovery, HF power results in a 20 to 40% increase. When cycling, HF power increases around 40% with respect to running, while CC power is around 20% stronger in running.

Development and exploration of a new methodology for the fitting and analysis of XAS data.

PubMed

Delgado-Jaime, Mario Ulises; Kennepohl, Pierre

2010-01-01

A new data analysis methodology for X-ray absorption near-edge spectroscopy (XANES) is introduced and tested using several examples. The methodology has been implemented within the context of a new Matlab-based program discussed in a companion related article [Delgado-Jaime et al. (2010), J. Synchrotron Rad. 17, 132-137]. The approach makes use of a Monte Carlo search method to seek appropriate starting points for a fit model, allowing for the generation of a large number of independent fits with minimal user-induced bias. The applicability of this methodology is tested using various data sets on the Cl K-edge XAS data for tetragonal CuCl(4)(2-), a common reference compound used for calibration and covalency estimation in M-Cl bonds. A new background model function that effectively blends together background profiles with spectral features is an important component of the discussed methodology. The development of a robust evaluation function to fit multiple-edge data is discussed and the implications regarding standard approaches to data analysis are discussed and explored within these examples.

Development and exploration of a new methodology for the fitting and analysis of XAS data

PubMed Central

Delgado-Jaime, Mario Ulises; Kennepohl, Pierre

2010-01-01

A new data analysis methodology for X-ray absorption near-edge spectroscopy (XANES) is introduced and tested using several examples. The methodology has been implemented within the context of a new Matlab-based program discussed in a companion related article [Delgado-Jaime et al. (2010 ▶), J. Synchrotron Rad. 17, 132–137]. The approach makes use of a Monte Carlo search method to seek appropriate starting points for a fit model, allowing for the generation of a large number of independent fits with minimal user-induced bias. The applicability of this methodology is tested using various data sets on the Cl K-edge XAS data for tetragonal CuCl4 2−, a common reference compound used for calibration and covalency estimation in M—Cl bonds. A new background model function that effectively blends together background profiles with spectral features is an important component of the discussed methodology. The development of a robust evaluation function to fit multiple-edge data is discussed and the implications regarding standard approaches to data analysis are discussed and explored within these examples. PMID:20029120

Diagnosis of skin cancer using image processing

NASA Astrophysics Data System (ADS)

Guerra-Rosas, Esperanza; Álvarez-Borrego, Josué; Coronel-Beltrán, Ángel

2014-10-01

In this papera methodology for classifying skin cancerin images of dermatologie spots based on spectral analysis using the K-law Fourier non-lineartechnique is presented. The image is segmented and binarized to build the function that contains the interest area. The image is divided into their respective RGB channels to obtain the spectral properties of each channel. The green channel contains more information and therefore this channel is always chosen. This information is point to point multiplied by a binary mask and to this result a Fourier transform is applied written in nonlinear form. If the real part of this spectrum is positive, the spectral density takeunit values, otherwise are zero. Finally the ratio of the sum of the unit values of the spectral density with the sum of values of the binary mask are calculated. This ratio is called spectral index. When the value calculated is in the spectral index range three types of cancer can be detected. Values found out of this range are benign injure.

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.

Application of self-organizing maps to the study of U-Zr-Ti-Nb distribution in sandstone-hosted uranium ores

NASA Astrophysics Data System (ADS)

Klus, Jakub; Pořízka, Pavel; Prochazka, David; Mikysek, Petr; Novotný, Jan; Novotný, Karel; Slobodník, Marek; Kaiser, Jozef

2017-05-01

This paper presents a novel approach for processing the spectral information obtained from high-resolution elemental mapping performed by means of Laser-Induced Breakdown Spectroscopy. The proposed methodology is aimed at the description of possible elemental associations within a heterogeneous sample. High-resolution elemental mapping provides a large number of measurements. Moreover, typical laser-induced plasma spectrum consists of several thousands of spectral variables. Analysis of heterogeneous samples, where valuable information is hidden in a limited fraction of sample mass, requires special treatment. The sample under study is a sandstone-hosted uranium ore that shows irregular distribution of ore elements such as zirconium, titanium, uranium and niobium. Presented processing methodology shows the way to reduce the dimensionality of data and retain the spectral information by utilizing self-organizing maps (SOM). The spectral information from SOM is processed further to detect either simultaneous or isolated presence of elements. Conclusions suggested by SOM are in good agreement with geological studies of mineralization phases performed at the deposit. Even deeper investigation of the SOM results enables discrimination of interesting measurements and reveals new possibilities in the visualization of chemical mapping information. Suggested approach improves the description of elemental associations in mineral phases, which is crucial for the mining industry.

Study of archaeological coins of different dynasties using libs coupled with multivariate analysis

NASA Astrophysics Data System (ADS)

Awasthi, Shikha; Kumar, Rohit; Rai, G. K.; Rai, A. K.

2016-04-01

Laser Induced Breakdown Spectroscopy (LIBS) is an atomic emission spectroscopic technique having unique capability of an in-situ monitoring tool for detection and quantification of elements present in different artifacts. Archaeological coins collected form G.R. Sharma Memorial Museum; University of Allahabad, India has been analyzed using LIBS technique. These coins were obtained from excavation of Kausambi, Uttar Pradesh, India. LIBS system assembled in the laboratory (laser Nd:YAG 532 nm, 4 ns pulse width FWHM with Ocean Optics LIBS 2000+ spectrometer) is employed for spectral acquisition. The spectral lines of Ag, Cu, Ca, Sn, Si, Fe and Mg are identified in the LIBS spectra of different coins. LIBS along with Multivariate Analysis play an effective role for classification and contribution of spectral lines in different coins. The discrimination between five coins with Archaeological interest has been carried out using Principal Component Analysis (PCA). The results show the potential relevancy of the methodology used in the elemental identification and classification of artifacts with high accuracy and robustness.

Classification of narcotics in solid mixtures using principal component analysis and Raman spectroscopy.

PubMed

Ryder, Alan G

2002-03-01

Eighty-five solid samples consisting of illegal narcotics diluted with several different materials were analyzed by near-infrared (785 nm excitation) Raman spectroscopy. Principal Component Analysis (PCA) was employed to classify the samples according to narcotic type. The best sample discrimination was obtained by using the first derivative of the Raman spectra. Furthermore, restricting the spectral variables for PCA to 2 or 3% of the original spectral data according to the most intense peaks in the Raman spectrum of the pure narcotic resulted in a rapid discrimination method for classifying samples according to narcotic type. This method allows for the easy discrimination between cocaine, heroin, and MDMA mixtures even when the Raman spectra are complex or very similar. This approach of restricting the spectral variables also decreases the computational time by a factor of 30 (compared to the complete spectrum), making the methodology attractive for rapid automatic classification and identification of suspect materials.

Single-chip source-free terahertz spectroscope across 0.04-0.99 THz: combining sub-wavelength near-field sensing and regression analysis.

PubMed

Wu, Xue; Sengupta, Kaushik

2018-03-19

This paper demonstrates a methodology to miniaturize THz spectroscopes into a single silicon chip by eliminating traditional solid-state architectural components such as complex tunable THz and optical sources, nonlinear mixing and amplifiers. The proposed method achieves this by extracting incident THz spectral signatures from the surface of an on-chip antenna itself. The information is sensed through the spectrally-sensitive 2D distribution of the impressed current surface under the THz incident field. By converting the antenna from a single-port to a massively multi-port architecture with integrated electronics and deep subwavelength sensing, THz spectral estimation is converted into a linear estimation problem. We employ rigorous regression techniques and analysis to demonstrate a single silicon chip system operating at room temperature across 0.04-0.99 THz with 10 MHz accuracy in spectrum estimation of THz tones across the entire spectrum.

Multimodal Spectral Imaging of Cells Using a Transmission Diffraction Grating on a Light Microscope

PubMed Central

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

Improved Surface Parameter Retrievals using AIRS/AMSU Data

NASA Technical Reports Server (NTRS)

Susskind, Joel; Blaisdell, John

2008-01-01

The AIRS Science Team Version 5.0 retrieval algorithm became operational at the Goddard DAAC in July 2007 generating near real-time products from analysis of AIRS/AMSU sounding data. This algorithm contains many significant theoretical advances over the AIRS Science Team Version 4.0 retrieval algorithm used previously. Two very significant developments of Version 5 are: 1) the development and implementation of an improved Radiative Transfer Algorithm (RTA) which allows for accurate treatment of non-Local Thermodynamic Equilibrium (non-LTE) effects on shortwave sounding channels; and 2) the development of methodology to obtain very accurate case by case product error estimates which are in turn used for quality control. These theoretical improvements taken together enabled a new methodology to be developed which further improves soundings in partially cloudy conditions. In this methodology, longwave C02 channel observations in the spectral region 700 cm(exp -1) to 750 cm(exp -1) are used exclusively for cloud clearing purposes, while shortwave C02 channels in the spectral region 2195 cm(exp -1) 2395 cm(exp -1) are used for temperature sounding purposes. This allows for accurate temperature soundings under more difficult cloud conditions. This paper further improves on the methodology used in Version 5 to derive surface skin temperature and surface spectral emissivity from AIRS/AMSU observations. Now, following the approach used to improve tropospheric temperature profiles, surface skin temperature is also derived using only shortwave window channels. This produces improved surface parameters, both day and night, compared to what was obtained in Version 5. These in turn result in improved boundary layer temperatures and retrieved total O3 burden.

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

PubMed

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

2014-04-01

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

Metabolomics of Ulva lactuca Linnaeus (Chlorophyta) exposed to oil fuels: Fourier transform infrared spectroscopy and multivariate analysis as tools for metabolic fingerprint.

PubMed

Pilatti, Fernanda Kokowicz; Ramlov, Fernanda; Schmidt, Eder Carlos; Costa, Christopher; Oliveira, Eva Regina de; Bauer, Claudia M; Rocha, Miguel; Bouzon, Zenilda Laurita; Maraschin, Marcelo

2017-01-30

Fossil fuels, e.g. gasoline and diesel oil, account for substantial share of the pollution that affects marine ecosystems. Environmental metabolomics is an emerging field that may help unravel the effect of these xenobiotics on seaweeds and provide methodologies for biomonitoring coastal ecosystems. In the present study, FTIR and multivariate analysis were used to discriminate metabolic profiles of Ulva lactuca after in vitro exposure to diesel oil and gasoline, in combinations of concentrations (0.001%, 0.01%, 0.1%, and 1.0% - v/v) and times of exposure (30min, 1h, 12h, and 24h). PCA and HCA performed on entire mid-infrared spectral window were able to discriminate diesel oil-exposed thalli from the gasoline-exposed ones. HCA performed on spectral window related to the protein absorbance (1700-1500cm -1 ) enabled the best discrimination between gasoline-exposed samples regarding the time of exposure, and between diesel oil-exposed samples according to the concentration. The results indicate that the combination of FTIR with multivariate analysis is a simple and efficient methodology for metabolic profiling with potential use for biomonitoring strategies. Copyright © 2016 Elsevier Ltd. All rights reserved.

Multi-frequency data analysis in AFM by wavelet transform

NASA Astrophysics Data System (ADS)

Pukhova, V.; Ferrini, G.

2017-10-01

Interacting cantilevers in AFM experiments generate non-stationary, multi-frequency signals consisting of numerous excited flexural and torsional modes and their harmonics. The analysis of such signals is challenging, requiring special methodological approaches and a powerful mathematical apparatus. The most common approach to the signal analysis is to apply Fourier transform analysis. However, FT gives accurate spectra for stationary signals, and for signals changing their spectral content over time, FT provides only an averaged spectrum. Hence, for non-stationary and rapidly varying signals, such as those from interacting cantilevers, a method that shows the spectral evolution in time is needed. One of the most powerful techniques, allowing detailed time-frequency representation of signals, is the wavelet transform. It is a method of analysis that allows representation of energy associated to the signal at a particular frequency and time, providing correlation between the spectral and temporal features of the signal, unlike FT. This is particularly important in AFM experiments because signals nonlinearities contains valuable information about tip-sample interactions and consequently surfaces properties. The present work is aimed to show the advantages of wavelet transform in comparison with FT using as an example the force curve analysis in dynamic force spectroscopy.

Network Data: Statistical Theory and New Models

DTIC Science & Technology

2016-02-17

SECURITY CLASSIFICATION OF: During this period of review, Bin Yu worked on many thrusts of high-dimensional statistical theory and methodologies. Her...research covered a wide range of topics in statistics including analysis and methods for spectral clustering for sparse and structured networks...2,7,8,21], sparse modeling (e.g. Lasso) [4,10,11,17,18,19], statistical guarantees for the EM algorithm [3], statistical analysis of algorithm leveraging

[Rapid assessment of critical quality attributes of Chinese materia medica (II): strategy of NIR assignment].

PubMed

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.

Shear-wave velocity profiling according to three alternative approaches: A comparative case study

NASA Astrophysics Data System (ADS)

Dal Moro, G.; Keller, L.; Al-Arifi, N. S.; Moustafa, S. S. R.

2016-11-01

The paper intends to compare three different methodologies which can be used to analyze surface-wave propagation, thus eventually obtaining the vertical shear-wave velocity (VS) profile. The three presented methods (currently still quite unconventional) are characterized by different field procedures and data processing. The first methodology is a sort of evolution of the classical Multi-channel Analysis of Surface Waves (MASW) here accomplished by jointly considering Rayleigh and Love waves (analyzed according to the Full Velocity Spectrum approach) and the Horizontal-to-Vertical Spectral Ratio (HVSR). The second method is based on the joint analysis of the HVSR curve together with the Rayleigh-wave dispersion determined via Miniature Array Analysis of Microtremors (MAAM), a passive methodology that relies on a small number (4 to 6) of vertical geophones deployed along a small circle (for the common near-surface application the radius usually ranges from 0.6 to 5 m). Finally, the third considered approach is based on the active data acquired by a single 3-component geophone and relies on the joint inversion of the group-velocity spectra of the radial and vertical components of the Rayleigh waves, together with the Radial-to-Vertical Spectral Ratio (RVSR). The results of the analyses performed while considering these approaches (completely different both in terms of field procedures and data analysis) appear extremely consistent thus mutually validating their performances. Pros and cons of each approach are summarized both in terms of computational aspects as well as with respect to practical considerations regarding the specific character of the pertinent field procedures.

Methodology for processing pressure traces used as inputs for combustion analyses in diesel engines

NASA Astrophysics Data System (ADS)

Rašić, Davor; Vihar, Rok; Žvar Baškovič, Urban; Katrašnik, Tomaž

2017-05-01

This study proposes a novel methodology for designing an optimum equiripple finite impulse response (FIR) filter for processing in-cylinder pressure traces of a diesel internal combustion engine, which serve as inputs for high-precision combustion analyses. The proposed automated workflow is based on an innovative approach of determining the transition band frequencies and optimum filter order. The methodology is based on discrete Fourier transform analysis, which is the first step to estimate the location of the pass-band and stop-band frequencies. The second step uses short-time Fourier transform analysis to refine the estimated aforementioned frequencies. These pass-band and stop-band frequencies are further used to determine the most appropriate FIR filter order. The most widely used existing methods for estimating the FIR filter order are not effective in suppressing the oscillations in the rate- of-heat-release (ROHR) trace, thus hindering the accuracy of combustion analyses. To address this problem, an innovative method for determining the order of an FIR filter is proposed in this study. This method is based on the minimization of the integral of normalized signal-to-noise differences between the stop-band frequency and the Nyquist frequency. Developed filters were validated using spectral analysis and calculation of the ROHR. The validation results showed that the filters designed using the proposed innovative method were superior compared with those using the existing methods for all analyzed cases. Highlights • Pressure traces of a diesel engine were processed by finite impulse response (FIR) filters with different orders • Transition band frequencies were determined with an innovative method based on discrete Fourier transform and short-time Fourier transform • Spectral analyses showed deficiencies of existing methods in determining the FIR filter order • A new method of determining the FIR filter order for processing pressure traces was proposed • The efficiency of the new method was demonstrated by spectral analyses and calculations of rate-of-heat-release traces

Rational Variety Mapping for Contrast-Enhanced Nonlinear Unsupervised Segmentation of Multispectral Images of Unstained Specimen

PubMed Central

Kopriva, Ivica; Hadžija, Mirko; Popović Hadžija, Marijana; Korolija, Marina; Cichocki, Andrzej

2011-01-01

A methodology is proposed for nonlinear contrast-enhanced unsupervised segmentation of multispectral (color) microscopy images of principally unstained specimens. The methodology exploits spectral diversity and spatial sparseness to find anatomical differences between materials (cells, nuclei, and background) present in the image. It consists of rth-order rational variety mapping (RVM) followed by matrix/tensor factorization. Sparseness constraint implies duality between nonlinear unsupervised segmentation and multiclass pattern assignment problems. Classes not linearly separable in the original input space become separable with high probability in the higher-dimensional mapped space. Hence, RVM mapping has two advantages: it takes implicitly into account nonlinearities present in the image (ie, they are not required to be known) and it increases spectral diversity (ie, contrast) between materials, due to increased dimensionality of the mapped space. This is expected to improve performance of systems for automated classification and analysis of microscopic histopathological images. The methodology was validated using RVM of the second and third orders of the experimental multispectral microscopy images of unstained sciatic nerve fibers (nervus ischiadicus) and of unstained white pulp in the spleen tissue, compared with a manually defined ground truth labeled by two trained pathophysiologists. The methodology can also be useful for additional contrast enhancement of images of stained specimens. PMID:21708116

A methodology for obtaining on-orbit SI-traceable spectral radiance measurements in the thermal infrared

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.

Quality assurance of temporal variability of natural decay chain and neutron induced background for low-level NORM analysis

DOE PAGES

Yoho, Michael; Porterfield, Donivan R.; Landsberger, Sheldon

2015-09-22

In this study, twenty-one high purity germanium (HPGe) background spectra were collected over 2 years at Los Alamos National Laboratory. A quality assurance methodology was developed to monitor spectral background levels from thermal and fast neutron flux levels and naturally occurring radioactive material decay series radionuclides. 238U decay products above 222Rn demonstrated minimal temporal variability beyond that expected from counting statistics. 238U and 232Th progeny below Rn gas displayed at most twice the expected variability. Further, an analysis of the 139 keV 74Ge(n, γ) and 691 keV 72Ge(n, n') spectral features demonstrated temporal stability for both thermal and fastmore » neutron fluxes.« less

Processing Satellite Imagery To Detect Waste Tire Piles

NASA Technical Reports Server (NTRS)

Skiles, Joseph; Schmidt, Cynthia; Wuinlan, Becky; Huybrechts, Catherine

2007-01-01

A methodology for processing commercially available satellite spectral imagery has been developed to enable identification and mapping of waste tire piles in California. The California Integrated Waste Management Board initiated the project and provided funding for the method s development. The methodology includes the use of a combination of previously commercially available image-processing and georeferencing software used to develop a model that specifically distinguishes between tire piles and other objects. The methodology reduces the time that must be spent to initially survey a region for tire sites, thereby increasing inspectors and managers time available for remediation of the sites. Remediation is needed because millions of used tires are discarded every year, waste tire piles pose fire hazards, and mosquitoes often breed in water trapped in tires. It should be possible to adapt the methodology to regions outside California by modifying some of the algorithms implemented in the software to account for geographic differences in spectral characteristics associated with terrain and climate. The task of identifying tire piles in satellite imagery is uniquely challenging because of their low reflectance levels: Tires tend to be spectrally confused with shadows and deep water, both of which reflect little light to satellite-borne imaging systems. In this methodology, the challenge is met, in part, by use of software that implements the Tire Identification from Reflectance (TIRe) model. The development of the TIRe model included incorporation of lessons learned in previous research on the detection and mapping of tire piles by use of manual/ visual and/or computational analysis of aerial and satellite imagery. The TIRe model is a computational model for identifying tire piles and discriminating between tire piles and other objects. The input to the TIRe model is the georeferenced but otherwise raw satellite spectral images of a geographic region to be surveyed. The TIRe model identifies the darkest objects in the images and, on the basis of spatial and spectral image characteristics, discriminates against other dark objects, which can include vegetation, some bodies of water, and dark soils. The TIRe model can identify piles of as few as 100 tires. The output of the TIRe model is a binary mask showing areas containing suspected tire piles and spectrally similar features. This mask is overlaid on the original satellite imagery and examined by a trained image analyst, who strives to further discriminate against non-tire objects that the TIRe model tentatively identified as tire piles. After the analyst has made adjustments, the mask is used to create a synoptic, geographically accurate tire-pile survey map, which can be overlaid with a road map and/or any other map or set of georeferenced data, according to a customer s preferences.

An approach to estimate spatial distribution of analyte within cells using spectrally-resolved fluorescence microscopy.

PubMed

Sharma, Dharmendar Kumar; Irfanullah, Mir; Basu, Santanu Kumar; Madhu, Sheri; De, Suman; Jadhav, Sameer; Ravikanth, Mangalampalli; Chowdhury, Arindam

2017-01-18

While fluorescence microscopy has become an essential tool amongst chemists and biologists for the detection of various analyte within cellular environments, non-uniform spatial distribution of sensors within cells often restricts extraction of reliable information on relative abundance of analytes in different subcellular regions. As an alternative to existing sensing methodologies such as ratiometric or FRET imaging, where relative proportion of analyte with respect to the sensor can be obtained within cells, we propose a methodology using spectrally-resolved fluorescence microscopy, via which both the relative abundance of sensor as well as their relative proportion with respect to the analyte can be simultaneously extracted for local subcellular regions. This method is exemplified using a BODIPY sensor, capable of detecting mercury ions within cellular environments, characterized by spectral blue-shift and concurrent enhancement of emission intensity. Spectral emission envelopes collected from sub-microscopic regions allowed us to compare the shift in transition energies as well as integrated emission intensities within various intracellular regions. Construction of a 2D scatter plot using spectral shifts and emission intensities, which depend on the relative amount of analyte with respect to sensor and the approximate local amounts of the probe, respectively, enabled qualitative extraction of relative abundance of analyte in various local regions within a single cell as well as amongst different cells. Although the comparisons remain semi-quantitative, this approach involving analysis of multiple spectral parameters opens up an alternative way to extract spatial distribution of analyte in heterogeneous systems. The proposed method would be especially relevant for fluorescent probes that undergo relatively nominal shift in transition energies compared to their emission bandwidths, which often restricts their usage for quantitative ratiometric imaging in cellular media due to strong cross-talk between energetically separated detection channels.

An approach to estimate spatial distribution of analyte within cells using spectrally-resolved fluorescence microscopy

NASA Astrophysics Data System (ADS)

Sharma, Dharmendar Kumar; Irfanullah, Mir; Basu, Santanu Kumar; Madhu, Sheri; De, Suman; Jadhav, Sameer; Ravikanth, Mangalampalli; Chowdhury, Arindam

2017-03-01

While fluorescence microscopy has become an essential tool amongst chemists and biologists for the detection of various analyte within cellular environments, non-uniform spatial distribution of sensors within cells often restricts extraction of reliable information on relative abundance of analytes in different subcellular regions. As an alternative to existing sensing methodologies such as ratiometric or FRET imaging, where relative proportion of analyte with respect to the sensor can be obtained within cells, we propose a methodology using spectrally-resolved fluorescence microscopy, via which both the relative abundance of sensor as well as their relative proportion with respect to the analyte can be simultaneously extracted for local subcellular regions. This method is exemplified using a BODIPY sensor, capable of detecting mercury ions within cellular environments, characterized by spectral blue-shift and concurrent enhancement of emission intensity. Spectral emission envelopes collected from sub-microscopic regions allowed us to compare the shift in transition energies as well as integrated emission intensities within various intracellular regions. Construction of a 2D scatter plot using spectral shifts and emission intensities, which depend on the relative amount of analyte with respect to sensor and the approximate local amounts of the probe, respectively, enabled qualitative extraction of relative abundance of analyte in various local regions within a single cell as well as amongst different cells. Although the comparisons remain semi-quantitative, this approach involving analysis of multiple spectral parameters opens up an alternative way to extract spatial distribution of analyte in heterogeneous systems. The proposed method would be especially relevant for fluorescent probes that undergo relatively nominal shift in transition energies compared to their emission bandwidths, which often restricts their usage for quantitative ratiometric imaging in cellular media due to strong cross-talk between energetically separated detection channels. Dedicated to Professor Kankan Bhattacharyya.

Improved Atmospheric Soundings and Error Estimates from Analysis of AIRS/AMSU Data

NASA Technical Reports Server (NTRS)

Susskind, Joel

2007-01-01

The AIRS Science Team Version 5.0 retrieval algorithm became operational at the Goddard DAAC in July 2007 generating near real-time products from analysis of AIRS/AMSU sounding data. This algorithm contains many significant theoretical advances over the AIRS Science Team Version 4.0 retrieval algorithm used previously. Three very significant developments of Version 5 are: 1) the development and implementation of an improved Radiative Transfer Algorithm (RTA) which allows for accurate treatment of non-Local Thermodynamic Equilibrium (non-LTE) effects on shortwave sounding channels; 2) the development of methodology to obtain very accurate case by case product error estimates which are in turn used for quality control; and 3) development of an accurate AIRS only cloud clearing and retrieval system. These theoretical improvements taken together enabled a new methodology to be developed which further improves soundings in partially cloudy conditions, without the need for microwave observations in the cloud clearing step as has been done previously. In this methodology, longwave C02 channel observations in the spectral region 700 cm-' to 750 cm-' are used exclusively for cloud clearing purposes, while shortwave C02 channels in the spectral region 2195 cm-' to 2395 cm-' are used for temperature sounding purposes. The new methodology for improved error estimates and their use in quality control is described briefly and results are shown indicative of their accuracy. Results are also shown of forecast impact experiments assimilating AIRS Version 5.0 retrieval products in the Goddard GEOS 5 Data Assimilation System using different quality control thresholds.

The Synchrotron Shock Model Confronts a "Line of Death" in the BATSE Gamma-Ray Burst Data

NASA Technical Reports Server (NTRS)

Preece, Robert D.; Briggs, Michael S.; Mallozzi, Robert S.; Pendleton, Geoffrey N.; Paciesas, W. S.; Band, David L.

1998-01-01

The synchrotron shock model (SSM) for gamma-ray burst emission makes a testable prediction: that the observed low-energy power-law photon number spectral index cannot exceed -2/3 (where the photon model is defined with a positive index: $dN/dE \\propto E{alpha}$). We have collected time-resolved spectral fit parameters for over 100 bright bursts observed by the Burst And Transient Source Experiment on board the {\\it Compton Gamma Ray Observatory}. Using this database, we find 23 bursts in which the spectral index limit of the SSM is violated, We discuss elements of the analysis methodology that affect the robustness of this result, as well as some of the escape hatches left for the SSM by theory.

Improving the representation of clouds, radiation, and precipitation using spectral nudging in the Weather Research and Forecasting model

NASA Astrophysics Data System (ADS)

Spero, Tanya L.; Otte, Martin J.; Bowden, Jared H.; Nolte, Christopher G.

2014-10-01

Spectral nudging—a scale-selective interior constraint technique—is commonly used in regional climate models to maintain consistency with large-scale forcing while permitting mesoscale features to develop in the downscaled simulations. Several studies have demonstrated that spectral nudging improves the representation of regional climate in reanalysis-forced simulations compared with not using nudging in the interior of the domain. However, in the Weather Research and Forecasting (WRF) model, spectral nudging tends to produce degraded precipitation simulations when compared to analysis nudging—an interior constraint technique that is scale indiscriminate but also operates on moisture fields which until now could not be altered directly by spectral nudging. Since analysis nudging is less desirable for regional climate modeling because it dampens fine-scale variability, changes are proposed to the spectral nudging methodology to capitalize on differences between the nudging techniques and aim to improve the representation of clouds, radiation, and precipitation without compromising other fields. These changes include adding spectral nudging toward moisture, limiting nudging to below the tropopause, and increasing the nudging time scale for potential temperature, all of which collectively improve the representation of mean and extreme precipitation, 2 m temperature, clouds, and radiation, as demonstrated using a model-simulated 20 year historical period. Such improvements to WRF may increase the fidelity of regional climate data used to assess the potential impacts of climate change on human health and the environment and aid in climate change mitigation and adaptation studies.

Clinical measurements analysis of multi-spectral photoplethysmograph biosensors

NASA Astrophysics Data System (ADS)

Asare, Lasma; Kviesis-Kipge, Edgars; Spigulis, Janis

2014-05-01

The developed portable multi-spectral photoplethysmograph (MS-PPG) optical biosensor device, intended for analysis of peripheral blood volume pulsations at different vascular depths, has been clinically verified. Multi-spectral monitoring was performed by means of a four - wavelengths (454 nm, 519 nm, 632 nm and 888 nm) light emitted diodes and photodiode with multi-channel signal output processing. Two such sensors can be operated in parallel and imposed on the patient's skin. The clinical measurements confirmed ability to detect PPG signals at four wavelengths simultaneously and to record temporal differences in the signal shapes (corresponding to different penetration depths) in normal and pathological skin. This study analyzed wavelengths relations between systole and diastole peak difference at various tissue depths in normal and pathological skin. The difference between parameters of healthy and pathological skin at various skin depths could be explain by oxy- and deoxyhemoglobin dominance at different wavelengths operated in sensor. The proposed methodology and potential clinical applications in dermatology for skin assessment are discussed.

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.

Novel hyperspectral prediction method and apparatus

NASA Astrophysics Data System (ADS)

Kemeny, Gabor J.; Crothers, Natalie A.; Groth, Gard A.; Speck, Kathy A.; Marbach, Ralf

2009-05-01

Both the power and the challenge of hyperspectral technologies is the very large amount of data produced by spectral cameras. While off-line methodologies allow the collection of gigabytes of data, extended data analysis sessions are required to convert the data into useful information. In contrast, real-time monitoring, such as on-line process control, requires that compression of spectral data and analysis occur at a sustained full camera data rate. Efficient, high-speed practical methods for calibration and prediction are therefore sought to optimize the value of hyperspectral imaging. A novel method of matched filtering known as science based multivariate calibration (SBC) was developed for hyperspectral calibration. Classical (MLR) and inverse (PLS, PCR) methods are combined by spectroscopically measuring the spectral "signal" and by statistically estimating the spectral "noise." The accuracy of the inverse model is thus combined with the easy interpretability of the classical model. The SBC method is optimized for hyperspectral data in the Hyper-CalTM software used for the present work. The prediction algorithms can then be downloaded into a dedicated FPGA based High-Speed Prediction EngineTM module. Spectral pretreatments and calibration coefficients are stored on interchangeable SD memory cards, and predicted compositions are produced on a USB interface at real-time camera output rates. Applications include minerals, pharmaceuticals, food processing and remote sensing.

Spatial and Temporal Evolution of Earthquake Dynamics: Case Study of the Mw 8.3 Illapel Earthquake, Chile

NASA Astrophysics Data System (ADS)

Yin, Jiuxun; Denolle, Marine A.; Yao, Huajian

2018-01-01

We develop a methodology that combines compressive sensing backprojection (CS-BP) and source spectral analysis of teleseismic P waves to provide metrics relevant to earthquake dynamics of large events. We improve the CS-BP method by an autoadaptive source grid refinement as well as a reference source adjustment technique to gain better spatial and temporal resolution of the locations of the radiated bursts. We also use a two-step source spectral analysis based on (i) simple theoretical Green's functions that include depth phases and water reverberations and on (ii) empirical P wave Green's functions. Furthermore, we propose a source spectrogram methodology that provides the temporal evolution of dynamic parameters such as radiated energy and falloff rates. Bridging backprojection and spectrogram analysis provides a spatial and temporal evolution of these dynamic source parameters. We apply our technique to the recent 2015 Mw 8.3 megathrust Illapel earthquake (Chile). The results from both techniques are consistent and reveal a depth-varying seismic radiation that is also found in other megathrust earthquakes. The low-frequency content of the seismic radiation is located in the shallow part of the megathrust, propagating unilaterally from the hypocenter toward the trench while most of the high-frequency content comes from the downdip part of the fault. Interpretation of multiple rupture stages in the radiation is also supported by the temporal variations of radiated energy and falloff rates. Finally, we discuss the possible mechanisms, either from prestress, fault geometry, and/or frictional properties to explain our observables. Our methodology is an attempt to bridge kinematic observations with earthquake dynamics.

Non-invasive identification of organic materials in historical stringed musical instruments by reflection infrared spectroscopy: a methodological approach.

PubMed

Invernizzi, Claudia; Daveri, Alessia; Vagnini, Manuela; Malagodi, Marco

2017-05-01

The analysis of historical musical instruments is becoming more relevant and the interest is increasingly moving toward the non-invasive reflection FTIR spectroscopy, especially for the analysis of varnishes. In this work, a specific infrared reflectance spectral library of organic compounds was created with the aim of identifying musical instrument materials in a totally non-invasive way. The analyses were carried out on pure organic compounds, as bulk samples and laboratory wooden models, to evaluate the diagnostic reflection mid-infrared (MIR) bands of proteins, polysaccharides, lipids, and resins by comparing reflection spectra before and after the KK correction. This methodological approach was applied to real case studies represented by four Stradivari violins and a Neapolitan mandolin.

Improving the automated detection of refugee/IDP dwellings using the multispectral bands of the WorldView-2 satellite

NASA Astrophysics Data System (ADS)

Kemper, Thomas; Gueguen, Lionel; Soille, Pierre

2012-06-01

The enumeration of the population remains a critical task in the management of refugee/IDP camps. Analysis of very high spatial resolution satellite data proofed to be an efficient and secure approach for the estimation of dwellings and the monitoring of the camp over time. In this paper we propose a new methodology for the automated extraction of features based on differential morphological decomposition segmentation for feature extraction and interactive training sample selection from the max-tree and min-tree structures. This feature extraction methodology is tested on a WorldView-2 scene of an IDP camp in Darfur Sudan. Special emphasis is given to the additional available bands of the WorldView-2 sensor. The results obtained show that the interactive image information tool is performing very well by tuning the feature extraction to the local conditions. The analysis of different spectral subsets shows that it is possible to obtain good results already with an RGB combination, but by increasing the number of spectral bands the detection of dwellings becomes more accurate. Best results were obtained using all eight bands of WorldView-2 satellite.

Sum frequency generation vibrational spectroscopy (SFG-VS) for complex molecular surfaces and interfaces: Spectral lineshape measurement and analysis plus some controversial issues

NASA Astrophysics Data System (ADS)

Wang, Hong-Fei

2016-12-01

Sum-frequency generation vibrational spectroscopy (SFG-VS) was first developed in the 1980s and it has been proven a uniquely sensitive and surface/interface selective spectroscopic probe for characterization of the structure, conformation and dynamics of molecular surfaces and interfaces. In recent years, there have been many progresses in the development of methodology and instrumentation in the SFG-VS toolbox that have significantly broadened the application to complex molecular surfaces and interfaces. In this review, after presenting a unified view on the theory and methodology focusing on the SFG-VS spectral lineshape, as well as the new opportunities in SFG-VS applications with such developments, some of the controversial issues that have been puzzling the community are discussed. The aim of this review is to present to the researchers and students interested in molecular surfaces and interfacial sciences up-to-date perspectives complementary to the existing textbooks and reviews on SFG-VS.

Sum frequency generation vibrational spectroscopy (SFG-VS) for complex molecular surfaces and interfaces: Spectral lineshape measurement and analysis plus some controversial issues

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

Wang, Hong-Fei

Sum-frequency generation vibrational spectroscopy (SFG-VS) was first developed in the 1980s and it has been proven a uniquely sensitive and surface/interface selective spectroscopic probe for characterization of the structure, conformation and dynamics of molecular surfaces and interfaces. In recent years, there has been significant progress in the development of methodology and instrumentation in the SFG-VS toolbox that has significantly broadened the application to complex molecular surfaces and interfaces. In this review, after presenting a unified view on the theory and methodology focusing on the SFG-VS spectral lineshape, as well as the new opportunities in SFG-VS applications with such developments, somemore » of the controversial issues that have been puzzling the community are to be discussed. The aim of this review is to present to the researchers and students interested in molecular surfaces and interfacial sciences up-to-date perspectives complementary to the existing textbooks and reviews on SFG-VS.« less

Rational variety mapping for contrast-enhanced nonlinear unsupervised segmentation of multispectral images of unstained specimen.

PubMed

Kopriva, Ivica; Hadžija, Mirko; Popović Hadžija, Marijana; Korolija, Marina; Cichocki, Andrzej

2011-08-01

A methodology is proposed for nonlinear contrast-enhanced unsupervised segmentation of multispectral (color) microscopy images of principally unstained specimens. The methodology exploits spectral diversity and spatial sparseness to find anatomical differences between materials (cells, nuclei, and background) present in the image. It consists of rth-order rational variety mapping (RVM) followed by matrix/tensor factorization. Sparseness constraint implies duality between nonlinear unsupervised segmentation and multiclass pattern assignment problems. Classes not linearly separable in the original input space become separable with high probability in the higher-dimensional mapped space. Hence, RVM mapping has two advantages: it takes implicitly into account nonlinearities present in the image (ie, they are not required to be known) and it increases spectral diversity (ie, contrast) between materials, due to increased dimensionality of the mapped space. This is expected to improve performance of systems for automated classification and analysis of microscopic histopathological images. The methodology was validated using RVM of the second and third orders of the experimental multispectral microscopy images of unstained sciatic nerve fibers (nervus ischiadicus) and of unstained white pulp in the spleen tissue, compared with a manually defined ground truth labeled by two trained pathophysiologists. The methodology can also be useful for additional contrast enhancement of images of stained specimens. Copyright © 2011 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.

Chromatographic background drift correction coupled with parallel factor analysis to resolve coelution problems in three-dimensional chromatographic data: quantification of eleven antibiotics in tap water samples by high-performance liquid chromatography coupled with a diode array detector.

PubMed

Yu, Yong-Jie; Wu, Hai-Long; Fu, Hai-Yan; Zhao, Juan; Li, Yuan-Na; Li, Shu-Fang; Kang, Chao; Yu, Ru-Qin

2013-08-09

Chromatographic background drift correction has been an important field of research in chromatographic analysis. In the present work, orthogonal spectral space projection for background drift correction of three-dimensional chromatographic data was described in detail and combined with parallel factor analysis (PARAFAC) to resolve overlapped chromatographic peaks and obtain the second-order advantage. This strategy was verified by simulated chromatographic data and afforded significant improvement in quantitative results. Finally, this strategy was successfully utilized to quantify eleven antibiotics in tap water samples. Compared with the traditional methodology of introducing excessive factors for the PARAFAC model to eliminate the effect of background drift, clear improvement in the quantitative performance of PARAFAC was observed after background drift correction by orthogonal spectral space projection. Copyright © 2013 Elsevier B.V. All rights reserved.

Aspiring to Spectral Ignorance in Earth Observation

NASA Astrophysics Data System (ADS)

Oliver, S. A.

2016-12-01

Enabling robust, defensible and integrated decision making in the Era of Big Earth Data requires the fusion of data from multiple and diverse sensor platforms and networks. While the application of standardised global grid systems provides a common spatial analytics framework that facilitates the computationally efficient and statistically valid integration and analysis of these various data sources across multiple scales, there remains the challenge of sensor equivalency; particularly when combining data from different earth observation satellite sensors (e.g. combining Landsat and Sentinel-2 observations). To realise the vision of a sensor ignorant analytics platform for earth observation we require automation of spectral matching across the available sensors. Ultimately, the aim is to remove the requirement for the user to possess any sensor knowledge in order to undertake analysis. This paper introduces the concept of spectral equivalence and proposes a methodology through which equivalent bands may be sourced from a set of potential target sensors through application of equivalence metrics and thresholds. A number of parameters can be used to determine whether a pair of spectra are equivalent for the purposes of analysis. A baseline set of thresholds for these parameters and how to apply them systematically to enable relation of spectral bands amongst numerous different sensors is proposed. The base unit for comparison in this work is the relative spectral response. From this input, determination of a what may constitute equivalence can be related by a user, based on their own conceptualisation of equivalence.

Extracting chemical information from high-resolution Kβ X-ray emission spectroscopy

NASA Astrophysics Data System (ADS)

Limandri, S.; Robledo, J.; Tirao, G.

2018-06-01

High-resolution X-ray emission spectroscopy allows studying the chemical environment of a wide variety of materials. Chemical information can be obtained by fitting the X-ray spectra and observing the behavior of some spectral features. Spectral changes can also be quantified by means of statistical parameters calculated by considering the spectrum as a probability distribution. Another possibility is to perform statistical multivariate analysis, such as principal component analysis. In this work the performance of these procedures for extracting chemical information in X-ray emission spectroscopy spectra for mixtures of Mn2+ and Mn4+ oxides are studied. A detail analysis of the parameters obtained, as well as the associated uncertainties is shown. The methodologies are also applied for Mn oxidation state characterization of double perovskite oxides Ba1+xLa1-xMnSbO6 (with 0 ≤ x ≤ 0.7). The results show that statistical parameters and multivariate analysis are the most suitable for the analysis of this kind of spectra.

Using 2D correlation analysis to enhance spectral information available from highly spatially resolved AFM-IR spectra

NASA Astrophysics Data System (ADS)

Marcott, Curtis; Lo, Michael; Hu, Qichi; Kjoller, Kevin; Boskey, Adele; Noda, Isao

2014-07-01

The recent combination of atomic force microscopy and infrared spectroscopy (AFM-IR) has led to the ability to obtain IR spectra with nanoscale spatial resolution, nearly two orders-of-magnitude better than conventional Fourier transform infrared (FT-IR) microspectroscopy. This advanced methodology can lead to significantly sharper spectral features than are typically seen in conventional IR spectra of inhomogeneous materials, where a wider range of molecular environments are coaveraged by the larger sample cross section being probed. In this work, two-dimensional (2D) correlation analysis is used to examine position sensitive spectral variations in datasets of closely spaced AFM-IR spectra. This analysis can reveal new key insights, providing a better understanding of the new spectral information that was previously hidden under broader overlapped spectral features. Two examples of the utility of this new approach are presented. Two-dimensional correlation analysis of a set of AFM-IR spectra were collected at 200-nm increments along a line through a nucleation site generated by remelting a small spot on a thin film of poly(3-hydroxybutyrate-co-3-hydroxyhexanoate). There are two different crystalline carbonyl band components near 1720 cm-1 that sequentially disappear before a band at 1740 cm-1 due to more disordered material appears. In the second example, 2D correlation analysis of a series of AFM-IR spectra spaced every 1 μm of a thin cross section of a bone sample measured outward from an osteon center of bone growth. There are many changes in the amide I and phosphate band contours, suggesting changes in the bone structure are occurring as the bone matures.

Spectral methods on arbitrary grids

NASA Technical Reports Server (NTRS)

Carpenter, Mark H.; Gottlieb, David

1995-01-01

Stable and spectrally accurate numerical methods are constructed on arbitrary grids for partial differential equations. These new methods are equivalent to conventional spectral methods but do not rely on specific grid distributions. Specifically, we show how to implement Legendre Galerkin, Legendre collocation, and Laguerre Galerkin methodology on arbitrary grids.

Improving the Accuracy of Mapping Urban Vegetation Carbon Density by Combining Shadow Remove, Spectral Unmixing Analysis and Spatial Modeling

NASA Astrophysics Data System (ADS)

Qie, G.; Wang, G.; Wang, M.

2016-12-01

Mixed pixels and shadows due to buildings in urban areas impede accurate estimation and mapping of city vegetation carbon density. In most of previous studies, these factors are often ignored, which thus result in underestimation of city vegetation carbon density. In this study we presented an integrated methodology to improve the accuracy of mapping city vegetation carbon density. Firstly, we applied a linear shadow remove analysis (LSRA) on remotely sensed Landsat 8 images to reduce the shadow effects on carbon estimation. Secondly, we integrated a linear spectral unmixing analysis (LSUA) with a linear stepwise regression (LSR), a logistic model-based stepwise regression (LMSR) and k-Nearest Neighbors (kNN), and utilized and compared the integrated models on shadow-removed images to map vegetation carbon density. This methodology was examined in Shenzhen City of Southeast China. A data set from a total of 175 sample plots measured in 2013 and 2014 was used to train the models. The independent variables statistically significantly contributing to improving the fit of the models to the data and reducing the sum of squared errors were selected from a total of 608 variables derived from different image band combinations and transformations. The vegetation fraction from LSUA was then added into the models as an important independent variable. The estimates obtained were evaluated using a cross-validation method. Our results showed that higher accuracies were obtained from the integrated models compared with the ones using traditional methods which ignore the effects of mixed pixels and shadows. This study indicates that the integrated method has great potential on improving the accuracy of urban vegetation carbon density estimation. Key words: Urban vegetation carbon, shadow, spectral unmixing, spatial modeling, Landsat 8 images

Characterizing pigments with hyperspectral imaging variable false-color composites

NASA Astrophysics Data System (ADS)

Hayem-Ghez, Anita; Ravaud, Elisabeth; Boust, Clotilde; Bastian, Gilles; Menu, Michel; Brodie-Linder, Nancy

2015-11-01

Hyperspectral imaging has been used for pigment characterization on paintings for the last 10 years. It is a noninvasive technique, which mixes the power of spectrophotometry and that of imaging technologies. We have access to a visible and near-infrared hyperspectral camera, ranging from 400 to 1000 nm in 80-160 spectral bands. In order to treat the large amount of data that this imaging technique generates, one can use statistical tools such as principal component analysis (PCA). To conduct the characterization of pigments, researchers mostly use PCA, convex geometry algorithms and the comparison of resulting clusters to database spectra with a specific tolerance (like the Spectral Angle Mapper tool on the dedicated software ENVI). Our approach originates from false-color photography and aims at providing a simple tool to identify pigments thanks to imaging spectroscopy. It can be considered as a quick first analysis to see the principal pigments of a painting, before using a more complete multivariate statistical tool. We study pigment spectra, for each kind of hue (blue, green, red and yellow) to identify the wavelength maximizing spectral differences. The case of red pigments is most interesting because our methodology can discriminate the red pigments very well—even red lakes, which are always difficult to identify. As for the yellow and blue categories, it represents a good progress of IRFC photography for pigment discrimination. We apply our methodology to study the pigments on a painting by Eustache Le Sueur, a French painter of the seventeenth century. We compare the results to other noninvasive analysis like X-ray fluorescence and optical microscopy. Finally, we draw conclusions about the advantages and limits of the variable false-color image method using hyperspectral imaging.

Information content in spectral dependencies of optical unit volume parameters under action of He-Ne laser on blood

NASA Astrophysics Data System (ADS)

Khairullina, Alphiya Y.; Oleinik, Tatiana V.

1995-01-01

Our previous works concerned with the development of methods for studying blood and action of low-intensity laser radiation on blood and erythrocyte suspensions had shown the light- scattering methods gave a large body of information on a medium studied due to the methodological relationship between irradiation processes and techniques for investigations. Detail analysis of spectral diffuse reflectivities and transmissivities of optically thick blood layers, spectral absorptivities calculated on this basis over 600 - 900 nm, by using different approximations, for a pathological state owing to hypoxia testifies to the optical significance of not only hemoglobin derivatives but also products of hemoglobin decomposition. Laser action on blood is specific and related to an initial state of blood absorption due to different composition of chromoproteids. This work gives the interpretation of spectral observations. Analysis of spectral dependencies of the exinction coefficient e, mean cosine m of phase function, and parameter Q equals (epsilon) (1-(mu) )H/(lambda) (H - hematocrit) testifies to decreasing the relative index of refraction of erythrocytes and to morphological changes during laser action under pathology owing to hypoxia. The possibility to obtain physical and chemical information on the state of blood under laser action in vivo is shown to be based on the method proposed by us for calculating multilayered structures modeling human organs and on the technical implementation of this method.

Spectral reconstruction of dental X-ray tubes using laplace inverse transform of the attenuation curve

NASA Astrophysics Data System (ADS)

Malezan, A.; Tomal, A.; Antoniassi, M.; Watanabe, P. C. A.; Albino, L. D.; Poletti, M. E.

2015-11-01

In this work, a spectral reconstruction methodology for diagnostic X-ray, using Laplace inverse transform of the attenuation, was successfully applied to dental X-ray equipments. The attenuation curves of 8 commercially available dental X-ray equipment, from 3 different manufactures (Siemens, Gnatus and Dabi Atlante), were obtained by using an ionization chamber and high purity aluminium filters, while the kVp was obtained with a specific meter. A computational routine was implemented in order to adjust a model function, whose inverse Laplace transform is analytically known, to the attenuation curve. This methodology was validated by comparing the reconstructed and the measured (using semiconductor detector of cadmium telluride) spectra of a given dental X-ray unit. The spectral reconstruction showed the Dabi Atlante equipments generating similar shape spectra. This is a desirable feature from clinic standpoint because it produces similar levels of image quality and dose. We observed that equipments from Siemens and Gnatus generate significantly different spectra, suggesting that, for a given operating protocol, these units will present different levels of image quality and dose. This fact claims for the necessity of individualized operating protocols that maximize image quality and dose. The proposed methodology is suitable to perform a spectral reconstruction of dental X-ray equipments from the simple measurements of attenuation curve and kVp. The simplified experimental apparatus and the low level of technical difficulty make this methodology accessible to a broad range of users. The knowledge of the spectral distribution can help in the development of operating protocols that maximize image quality and dose.

Application of survival analysis methodology to the quantitative analysis of LC-MS proteomics data.

PubMed

Tekwe, Carmen D; Carroll, Raymond J; Dabney, Alan R

2012-08-01

Protein abundance in quantitative proteomics is often based on observed spectral features derived from liquid chromatography mass spectrometry (LC-MS) or LC-MS/MS experiments. Peak intensities are largely non-normal in distribution. Furthermore, LC-MS-based proteomics data frequently have large proportions of missing peak intensities due to censoring mechanisms on low-abundance spectral features. Recognizing that the observed peak intensities detected with the LC-MS method are all positive, skewed and often left-censored, we propose using survival methodology to carry out differential expression analysis of proteins. Various standard statistical techniques including non-parametric tests such as the Kolmogorov-Smirnov and Wilcoxon-Mann-Whitney rank sum tests, and the parametric survival model and accelerated failure time-model with log-normal, log-logistic and Weibull distributions were used to detect any differentially expressed proteins. The statistical operating characteristics of each method are explored using both real and simulated datasets. Survival methods generally have greater statistical power than standard differential expression methods when the proportion of missing protein level data is 5% or more. In particular, the AFT models we consider consistently achieve greater statistical power than standard testing procedures, with the discrepancy widening with increasing missingness in the proportions. The testing procedures discussed in this article can all be performed using readily available software such as R. The R codes are provided as supplemental materials. ctekwe@stat.tamu.edu.

Estimation of spectral kurtosis

NASA Astrophysics Data System (ADS)

Sutawanir

2017-03-01

Rolling bearings are the most important elements in rotating machinery. Bearing frequently fall out of service for various reasons: heavy loads, unsuitable lubrications, ineffective sealing. Bearing faults may cause a decrease in performance. Analysis of bearing vibration signals has attracted attention in the field of monitoring and fault diagnosis. Bearing vibration signals give rich information for early detection of bearing failures. Spectral kurtosis, SK, is a parameter in frequency domain indicating how the impulsiveness of a signal varies with frequency. Faults in rolling bearings give rise to a series of short impulse responses as the rolling elements strike faults, SK potentially useful for determining frequency bands dominated by bearing fault signals. SK can provide a measure of the distance of the analyzed bearings from a healthy one. SK provides additional information given by the power spectral density (psd). This paper aims to explore the estimation of spectral kurtosis using short time Fourier transform known as spectrogram. The estimation of SK is similar to the estimation of psd. The estimation falls in model-free estimation and plug-in estimator. Some numerical studies using simulations are discussed to support the methodology. Spectral kurtosis of some stationary signals are analytically obtained and used in simulation study. Kurtosis of time domain has been a popular tool for detecting non-normality. Spectral kurtosis is an extension of kurtosis in frequency domain. The relationship between time domain and frequency domain analysis is establish through power spectrum-autocovariance Fourier transform. Fourier transform is the main tool for estimation in frequency domain. The power spectral density is estimated through periodogram. In this paper, the short time Fourier transform of the spectral kurtosis is reviewed, a bearing fault (inner ring and outer ring) is simulated. The bearing response, power spectrum, and spectral kurtosis are plotted to visualize the pattern of each fault. Keywords: frequency domain Fourier transform, spectral kurtosis, bearing fault

Automated computation of autonomous spectral submanifolds for nonlinear modal analysis

NASA Astrophysics Data System (ADS)

Ponsioen, Sten; Pedergnana, Tiemo; Haller, George

2018-04-01

We discuss an automated computational methodology for computing two-dimensional spectral submanifolds (SSMs) in autonomous nonlinear mechanical systems of arbitrary degrees of freedom. In our algorithm, SSMs, the smoothest nonlinear continuations of modal subspaces of the linearized system, are constructed up to arbitrary orders of accuracy, using the parameterization method. An advantage of this approach is that the construction of the SSMs does not break down when the SSM folds over its underlying spectral subspace. A further advantage is an automated a posteriori error estimation feature that enables a systematic increase in the orders of the SSM computation until the required accuracy is reached. We find that the present algorithm provides a major speed-up, relative to numerical continuation methods, in the computation of backbone curves, especially in higher-dimensional problems. We illustrate the accuracy and speed of the automated SSM algorithm on lower- and higher-dimensional mechanical systems.

Albedos and spectral signatures determination and it connection to geological processes: Simile between Earth and other solar system bodies

NASA Astrophysics Data System (ADS)

Suarez, J.; Ochoa, L.; Saavedra, F.

2017-07-01

Remote sensing has always been the best investigation tool for planetary sciences. In this research have been used data of Surface albedo, electromagnetic spectra and satelital imagery in search of understanding glacier dynamics in some bodies of the solar system, and how it's related to their compositions and associated geological processes, this methodology is very common in icy moons studies. Through analytic software's some albedos map's and geomorphological analysis were made that allow interpretation of different types of ice in the glacier's and it's interaction with other materials, almost all the images were worked in the visible and infrared ranges of the spectrum; spectral data were later used to connect the reflectance whit chemical and reologic properties of the compounds studied. It have been concluded that the albedo analysis is an effective tool to differentiate materials in the bodies surfaces, but the application of spectral data is necessary to know the exact compounds of the glaciers and to have a better understanding of the icy bodies.

Applications of Quantum Cascade Laser Spectroscopy in the Analysis of Pharmaceutical Formulations.

PubMed

Galán-Freyle, Nataly J; Pacheco-Londoño, Leonardo C; Román-Ospino, Andrés D; Hernandez-Rivera, Samuel P

2016-09-01

Quantum cascade laser spectroscopy was used to quantify active pharmaceutical ingredient content in a model formulation. The analyses were conducted in non-contact mode by mid-infrared diffuse reflectance. Measurements were carried out at a distance of 15 cm, covering the spectral range 1000-1600 cm(-1) Calibrations were generated by applying multivariate analysis using partial least squares models. Among the figures of merit of the proposed methodology are the high analytical sensitivity equivalent to 0.05% active pharmaceutical ingredient in the formulation, high repeatability (2.7%), high reproducibility (5.4%), and low limit of detection (1%). The relatively high power of the quantum-cascade-laser-based spectroscopic system resulted in the design of detection and quantification methodologies for pharmaceutical applications with high accuracy and precision that are comparable to those of methodologies based on near-infrared spectroscopy, attenuated total reflection mid-infrared Fourier transform infrared spectroscopy, and Raman spectroscopy. © The Author(s) 2016.

Multivariate space - time analysis of PRE-STORM precipitation

NASA Technical Reports Server (NTRS)

Polyak, Ilya; North, Gerald R.; Valdes, Juan B.

1994-01-01

This paper presents the methodologies and results of the multivariate modeling and two-dimensional spectral and correlation analysis of PRE-STORM rainfall gauge data. Estimated parameters of the models for the specific spatial averages clearly indicate the eastward and southeastward wave propagation of rainfall fluctuations. A relationship between the coefficients of the diffusion equation and the parameters of the stochastic model of rainfall fluctuations is derived that leads directly to the exclusive use of rainfall data to estimate advection speed (about 12 m/s) as well as other coefficients of the diffusion equation of the corresponding fields. The statistical methodology developed here can be used for confirmation of physical models by comparison of the corresponding second-moment statistics of the observed and simulated data, for generating multiple samples of any size, for solving the inverse problem of the hydrodynamic equations, and for application in some other areas of meteorological and climatological data analysis and modeling.

Fast and Simple Discriminative Analysis of Anthocyanins-Containing Berries Using LC/MS Spectral Data.

PubMed

Yang, Heejung; Kim, Hyun Woo; Kwon, Yong Soo; Kim, Ho Kyong; Sung, Sang Hyun

2017-09-01

Anthocyanins are potent antioxidant agents that protect against many degenerative diseases; however, they are unstable because they are vulnerable to external stimuli including temperature, pH and light. This vulnerability hinders the quality control of anthocyanin-containing berries using classical high-performance liquid chromatography (HPLC) analytical methodologies based on UV or MS chromatograms. To develop an alternative approach for the quality assessment and discrimination of anthocyanin-containing berries, we used MS spectral data acquired in a short analytical time rather than UV or MS chromatograms. Mixtures of anthocyanins were separated from other components in a short gradient time (5 min) due to their higher polarity, and the representative MS spectrum was acquired from the MS chromatogram corresponding to the mixture of anthocyanins. The chemometric data from the representative MS spectra contained reliable information for the identification and relative quantification of anthocyanins in berries with good precision and accuracy. This fast and simple methodology, which consists of a simple sample preparation method and short gradient analysis, could be applied to reliably discriminate the species and geographical origins of different anthocyanin-containing berries. These features make the technique useful for the food industry. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Image enhancements of Landsat 8 (OLI) and SAR data for preliminary landslide identification and mapping applied to the central region of Kenya

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.

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.

Frequency analysis of a two-stage planetary gearbox using two different methodologies

NASA Astrophysics Data System (ADS)

Feki, Nabih; Karray, Maha; Khabou, Mohamed Tawfik; Chaari, Fakher; Haddar, Mohamed

2017-12-01

This paper is focused on the characterization of the frequency content of vibration signals issued from a two-stage planetary gearbox. To achieve this goal, two different methodologies are adopted: the lumped-parameter modeling approach and the phenomenological modeling approach. The two methodologies aim to describe the complex vibrations generated by a two-stage planetary gearbox. The phenomenological model describes directly the vibrations as measured by a sensor fixed outside the fixed ring gear with respect to an inertial reference frame, while results from a lumped-parameter model are referenced with respect to a rotating frame and then transferred into an inertial reference frame. Two different case studies of the two-stage planetary gear are adopted to describe the vibration and the corresponding spectra using both models. Each case presents a specific geometry and a specific spectral structure.

Analysis of CrIs/ATMS Using AIRS Version-7 Retrieval and QC Methodology

NASA Technical Reports Server (NTRS)

Susskind, Joel; Kouvaris, Louis; Blaisdell, John M.; Iredell, Lena

2017-01-01

The objective of this research is to develop and implement an algorithm to analyze a long term data record of CrIS/ATMS observations so as to produce monthly mean gridded Level-3 products which are consistent with, and will serve as a seamless follow on to, those of AIRS Version-7. We feel the best way to achieve this result is to analyze CrIS/ATMS data using retrieval and Quality Control (QC) methodologies which are scientifically equivalent to those used in AIRS Version-7. We developed and implemented a single retrieval program that uses as input either AIRS/AMSU or CrIS/ATMS radiance observations, and has appropriate switches that take into account the spectral and radiometric differences between CrIS and AIRS. Our methodology is call CHART (Climate Heritage AIRS Retrieval Technique).

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

Cameron, Maria K., E-mail: cameron@math.umd.edu

We develop computational tools for spectral analysis of stochastic networks representing energy landscapes of atomic and molecular clusters. Physical meaning and some properties of eigenvalues, left and right eigenvectors, and eigencurrents are discussed. We propose an approach to compute a collection of eigenpairs and corresponding eigencurrents describing the most important relaxation processes taking place in the system on its way to the equilibrium. It is suitable for large and complex stochastic networks where pairwise transition rates, given by the Arrhenius law, vary by orders of magnitude. The proposed methodology is applied to the network representing the Lennard-Jones-38 cluster created bymore » Wales's group. Its energy landscape has a double funnel structure with a deep and narrow face-centered cubic funnel and a shallower and wider icosahedral funnel. However, the complete spectrum of the generator matrix of the Lennard-Jones-38 network has no appreciable spectral gap separating the eigenvalue corresponding to the escape from the icosahedral funnel. We provide a detailed description of the escape process from the icosahedral funnel using the eigencurrent and demonstrate a superexponential growth of the corresponding eigenvalue. The proposed spectral approach is compared to the methodology of the Transition Path Theory. Finally, we discuss whether the Lennard-Jones-38 cluster is metastable from the points of view of a mathematician and a chemical physicist, and make a connection with experimental works.« less

A Reliable Methodology for Determining Seed Viability by Using Hyperspectral Data from Two Sides of Wheat Seeds.

PubMed

Zhang, Tingting; Wei, Wensong; Zhao, Bin; Wang, Ranran; Li, Mingliu; Yang, Liming; Wang, Jianhua; Sun, Qun

2018-03-08

This study investigated the possibility of using visible and near-infrared (VIS/NIR) hyperspectral imaging techniques to discriminate viable and non-viable wheat seeds. Both sides of individual seeds were subjected to hyperspectral imaging (400-1000 nm) to acquire reflectance spectral data. Four spectral datasets, including the ventral groove side, reverse side, mean (the mean of two sides' spectra of every seed), and mixture datasets (two sides' spectra of every seed), were used to construct the models. Classification models, partial least squares discriminant analysis (PLS-DA), and support vector machines (SVM), coupled with some pre-processing methods and successive projections algorithm (SPA), were built for the identification of viable and non-viable seeds. Our results showed that the standard normal variate (SNV)-SPA-PLS-DA model had high classification accuracy for whole seeds (>85.2%) and for viable seeds (>89.5%), and that the prediction set was based on a mixed spectral dataset by only using 16 wavebands. After screening with this model, the final germination of the seed lot could be higher than 89.5%. Here, we develop a reliable methodology for predicting the viability of wheat seeds, showing that the VIS/NIR hyperspectral imaging is an accurate technique for the classification of viable and non-viable wheat seeds in a non-destructive manner.

A Reliable Methodology for Determining Seed Viability by Using Hyperspectral Data from Two Sides of Wheat Seeds

PubMed Central

Zhang, Tingting; Wei, Wensong; Zhao, Bin; Wang, Ranran; Li, Mingliu; Yang, Liming; Wang, Jianhua; Sun, Qun

2018-01-01

This study investigated the possibility of using visible and near-infrared (VIS/NIR) hyperspectral imaging techniques to discriminate viable and non-viable wheat seeds. Both sides of individual seeds were subjected to hyperspectral imaging (400–1000 nm) to acquire reflectance spectral data. Four spectral datasets, including the ventral groove side, reverse side, mean (the mean of two sides’ spectra of every seed), and mixture datasets (two sides’ spectra of every seed), were used to construct the models. Classification models, partial least squares discriminant analysis (PLS-DA), and support vector machines (SVM), coupled with some pre-processing methods and successive projections algorithm (SPA), were built for the identification of viable and non-viable seeds. Our results showed that the standard normal variate (SNV)-SPA-PLS-DA model had high classification accuracy for whole seeds (>85.2%) and for viable seeds (>89.5%), and that the prediction set was based on a mixed spectral dataset by only using 16 wavebands. After screening with this model, the final germination of the seed lot could be higher than 89.5%. Here, we develop a reliable methodology for predicting the viability of wheat seeds, showing that the VIS/NIR hyperspectral imaging is an accurate technique for the classification of viable and non-viable wheat seeds in a non-destructive manner. PMID:29517991

Optimal methodologies for terahertz time-domain spectroscopic analysis of traditional pigments in powder form

NASA Astrophysics Data System (ADS)

Ha, Taewoo; Lee, Howon; Sim, Kyung Ik; Kim, Jonghyeon; Jo, Young Chan; Kim, Jae Hoon; Baek, Na Yeon; Kang, Dai-ill; Lee, Han Hyoung

2017-05-01

We have established optimal methods for terahertz time-domain spectroscopic analysis of highly absorbing pigments in powder form based on our investigation of representative traditional Chinese pigments, such as azurite [blue-based color pigment], Chinese vermilion [red-based color pigment], and arsenic yellow [yellow-based color pigment]. To accurately extract the optical constants in the terahertz region of 0.1 - 3 THz, we carried out transmission measurements in such a way that intense absorption peaks did not completely suppress the transmission level. This required preparation of pellet samples with optimized thicknesses and material densities. In some cases, mixing the pigments with polyethylene powder was required to minimize absorption due to certain peak features. The resulting distortion-free terahertz spectra of the investigated set of pigment species exhibited well-defined unique spectral fingerprints. Our study will be useful to future efforts to establish non-destructive analysis methods of traditional pigments, to construct their spectral databases, and to apply these tools to restoration of cultural heritage materials.

Spectral Target Detection using Schroedinger Eigenmaps

NASA Astrophysics Data System (ADS)

Dorado-Munoz, Leidy P.

Applications of optical remote sensing processes include environmental monitoring, military monitoring, meteorology, mapping, surveillance, etc. Many of these tasks include the detection of specific objects or materials, usually few or small, which are surrounded by other materials that clutter the scene and hide the relevant information. This target detection process has been boosted lately by the use of hyperspectral imagery (HSI) since its high spectral dimension provides more detailed spectral information that is desirable in data exploitation. Typical spectral target detectors rely on statistical or geometric models to characterize the spectral variability of the data. However, in many cases these parametric models do not fit well HSI data that impacts the detection performance. On the other hand, non-linear transformation methods, mainly based on manifold learning algorithms, have shown a potential use in HSI transformation, dimensionality reduction and classification. In target detection, non-linear transformation algorithms are used as preprocessing techniques that transform the data to a more suitable lower dimensional space, where the statistical or geometric detectors are applied. One of these non-linear manifold methods is the Schroedinger Eigenmaps (SE) algorithm that has been introduced as a technique for semi-supervised classification. The core tool of the SE algorithm is the Schroedinger operator that includes a potential term that encodes prior information about the materials present in a scene, and enables the embedding to be steered in some convenient directions in order to cluster similar pixels together. A completely novel target detection methodology based on SE algorithm is proposed for the first time in this thesis. The proposed methodology does not just include the transformation of the data to a lower dimensional space but also includes the definition of a detector that capitalizes on the theory behind SE. The fact that target pixels and those similar pixels are clustered in a predictable region of the low-dimensional representation is used to define a decision rule that allows one to identify target pixels over the rest of pixels in a given image. In addition, a knowledge propagation scheme is used to combine spectral and spatial information as a means to propagate the "potential constraints" to nearby points. The propagation scheme is introduced to reinforce weak connections and improve the separability between most of the target pixels and the background. Experiments using different HSI data sets are carried out in order to test the proposed methodology. The assessment is performed from a quantitative and qualitative point of view, and by comparing the SE-based methodology against two other detection methodologies that use linear/non-linear algorithms as transformations and the well-known Adaptive Coherence/Cosine Estimator (ACE) detector. Overall results show that the SE-based detector outperforms the other two detection methodologies, which indicates the usefulness of the SE transformation in spectral target detection problems.

Proof-of-Concept Study for Uncertainty Quantification and Sensitivity Analysis using the BRL Shaped-Charge Example

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

Hughes, Justin Matthew

These are the slides for a graduate presentation at Mississippi State University. It covers the following: the BRL Shaped-Charge Geometry in PAGOSA, mesh refinement study, surrogate modeling using a radial basis function network (RBFN), ruling out parameters using sensitivity analysis (equation of state study), uncertainty quantification (UQ) methodology, and sensitivity analysis (SA) methodology. In summary, a mesh convergence study was used to ensure that solutions were numerically stable by comparing PDV data between simulations. A Design of Experiments (DOE) method was used to reduce the simulation space to study the effects of the Jones-Wilkins-Lee (JWL) Parameters for the Composition Bmore » main charge. Uncertainty was quantified by computing the 95% data range about the median of simulation output using a brute force Monte Carlo (MC) random sampling method. Parameter sensitivities were quantified using the Fourier Amplitude Sensitivity Test (FAST) spectral analysis method where it was determined that detonation velocity, initial density, C1, and B1 controlled jet tip velocity.« less

Depth Cue Integration in an Active Control Paradigm

NASA Technical Reports Server (NTRS)

Kaiser, Mary K.; Sweet, Barabara T.; Shafto, Meredith; Null, Cynthia H. (Technical Monitor)

1995-01-01

Numerous models of depth cue integration have been proposed. Of particular interest is how the visual system processes discrepent cues, as might arise when viewing synthetic displays. A powerful paradigm for examining this integration process can be adapted from manual control research. This methodology introduces independent disturbances in the candidate cues, then performs spectral analysis of subjects' resulting motoric responses (e.g., depth matching). We will describe this technique and present initial findings.

Statistical analysis of spectral data: a methodology for designing an intelligent monitoring system for the diabetic foot

NASA Astrophysics Data System (ADS)

Liu, Chanjuan; van Netten, Jaap J.; Klein, Marvin E.; van Baal, Jeff G.; Bus, Sicco A.; van der Heijden, Ferdi

2013-12-01

Early detection of (pre-)signs of ulceration on a diabetic foot is valuable for clinical practice. Hyperspectral imaging is a promising technique for detection and classification of such (pre-)signs. However, the number of the spectral bands should be limited to avoid overfitting, which is critical for pixel classification with hyperspectral image data. The goal was to design a detector/classifier based on spectral imaging (SI) with a small number of optical bandpass filters. The performance and stability of the design were also investigated. The selection of the bandpass filters boils down to a feature selection problem. A dataset was built, containing reflectance spectra of 227 skin spots from 64 patients, measured with a spectrometer. Each skin spot was annotated manually by clinicians as "healthy" or a specific (pre-)sign of ulceration. Statistical analysis on the data set showed the number of required filters is between 3 and 7, depending on additional constraints on the filter set. The stability analysis revealed that shot noise was the most critical factor affecting the classification performance. It indicated that this impact could be avoided in future SI systems with a camera sensor whose saturation level is higher than 106, or by postimage processing.

Novel methodologies for spectral classification of exon and intron sequences

NASA Astrophysics Data System (ADS)

Kwan, Hon Keung; Kwan, Benjamin Y. M.; Kwan, Jennifer Y. Y.

2012-12-01

Digital processing of a nucleotide sequence requires it to be mapped to a numerical sequence in which the choice of nucleotide to numeric mapping affects how well its biological properties can be preserved and reflected from nucleotide domain to numerical domain. Digital spectral analysis of nucleotide sequences unfolds a period-3 power spectral value which is more prominent in an exon sequence as compared to that of an intron sequence. The success of a period-3 based exon and intron classification depends on the choice of a threshold value. The main purposes of this article are to introduce novel codes for 1-sequence numerical representations for spectral analysis and compare them to existing codes to determine appropriate representation, and to introduce novel thresholding methods for more accurate period-3 based exon and intron classification of an unknown sequence. The main findings of this study are summarized as follows: Among sixteen 1-sequence numerical representations, the K-Quaternary Code I offers an attractive performance. A windowed 1-sequence numerical representation (with window length of 9, 15, and 24 bases) offers a possible speed gain over non-windowed 4-sequence Voss representation which increases as sequence length increases. A winner threshold value (chosen from the best among two defined threshold values and one other threshold value) offers a top precision for classifying an unknown sequence of specified fixed lengths. An interpolated winner threshold value applicable to an unknown and arbitrary length sequence can be estimated from the winner threshold values of fixed length sequences with a comparable performance. In general, precision increases as sequence length increases. The study contributes an effective spectral analysis of nucleotide sequences to better reveal embedded properties, and has potential applications in improved genome annotation.

Spectral and cross-spectral analysis of uneven time series with the smoothed Lomb-Scargle periodogram and Monte Carlo evaluation of statistical significance

NASA Astrophysics Data System (ADS)

Pardo-Igúzquiza, Eulogio; Rodríguez-Tovar, Francisco J.

2012-12-01

Many spectral analysis techniques have been designed assuming sequences taken with a constant sampling interval. However, there are empirical time series in the geosciences (sediment cores, fossil abundance data, isotope analysis, …) that do not follow regular sampling because of missing data, gapped data, random sampling or incomplete sequences, among other reasons. In general, interpolating an uneven series in order to obtain a succession with a constant sampling interval alters the spectral content of the series. In such cases it is preferable to follow an approach that works with the uneven data directly, avoiding the need for an explicit interpolation step. The Lomb-Scargle periodogram is a popular choice in such circumstances, as there are programs available in the public domain for its computation. One new computer program for spectral analysis improves the standard Lomb-Scargle periodogram approach in two ways: (1) It explicitly adjusts the statistical significance to any bias introduced by variance reduction smoothing, and (2) it uses a permutation test to evaluate confidence levels, which is better suited than parametric methods when neighbouring frequencies are highly correlated. Another novel program for cross-spectral analysis offers the advantage of estimating the Lomb-Scargle cross-periodogram of two uneven time series defined on the same interval, and it evaluates the confidence levels of the estimated cross-spectra by a non-parametric computer intensive permutation test. Thus, the cross-spectrum, the squared coherence spectrum, the phase spectrum, and the Monte Carlo statistical significance of the cross-spectrum and the squared-coherence spectrum can be obtained. Both of the programs are written in ANSI Fortran 77, in view of its simplicity and compatibility. The program code is of public domain, provided on the website of the journal (http://www.iamg.org/index.php/publisher/articleview/frmArticleID/112/). Different examples (with simulated and real data) are described in this paper to corroborate the methodology and the implementation of these two new programs.

Setting up a proper power spectral density (PSD) and autocorrelation analysis for material and process characterization

NASA Astrophysics Data System (ADS)

Rutigliani, Vito; Lorusso, Gian Francesco; De Simone, Danilo; Lazzarino, Frederic; Rispens, Gijsbert; Papavieros, George; Gogolides, Evangelos; Constantoudis, Vassilios; Mack, Chris A.

2018-03-01

Power spectral density (PSD) analysis is playing more and more a critical role in the understanding of line-edge roughness (LER) and linewidth roughness (LWR) in a variety of applications across the industry. It is an essential step to get an unbiased LWR estimate, as well as an extremely useful tool for process and material characterization. However, PSD estimate can be affected by both random to systematic artifacts caused by image acquisition and measurement settings, which could irremediably alter its information content. In this paper, we report on the impact of various setting parameters (smoothing image processing filters, pixel size, and SEM noise levels) on the PSD estimate. We discuss also the use of PSD analysis tool in a variety of cases. Looking beyond the basic roughness estimate, we use PSD and autocorrelation analysis to characterize resist blur[1], as well as low and high frequency roughness contents and we apply this technique to guide the EUV material stack selection. Our results clearly indicate that, if properly used, PSD methodology is a very sensitive tool to investigate material and process variations

A Methodology to Assess the Accuracy with which Remote Data Characterize a Specific Surface, as a Function of Full Width at Half Maximum (FWHM): Application to Three Italian Coastal Waters

PubMed Central

Cavalli, Rosa Maria; Betti, Mattia; Campanelli, Alessandra; Di Cicco, Annalisa; Guglietta, Daniela; Penna, Pierluigi; Piermattei, Viviana

2014-01-01

This methodology assesses the accuracy with which remote data characterizes a surface, as a function of Full Width at Half Maximum (FWHM). The purpose is to identify the best remote data that improves the characterization of a surface, evaluating the number of bands in the spectral range. The first step creates an accurate dataset of remote simulated data, using in situ hyperspectral reflectances. The second step evaluates the capability of remote simulated data to characterize this surface. The spectral similarity measurements, which are obtained using classifiers, provide this capability. The third step examines the precision of this capability. The assumption is that in situ hyperspectral reflectances are considered the “real” reflectances. They are resized with the same spectral range of the remote data. The spectral similarity measurements which are obtained from “real” resized reflectances, are considered “real” measurements. Therefore, the quantity and magnitude of “errors” (i.e., differences between spectral similarity measurements obtained from “real” resized reflectances and from remote data) provide the accuracy as a function of FWHM. This methodology was applied to evaluate the accuracy with which CHRIS-mode1, CHRIS-mode2, Landsat5-TM, MIVIS and PRISMA data characterize three coastal waters. Their mean values of uncertainty are 1.59%, 3.79%, 7.75%, 3.15% and 1.18%, respectively. PMID:24434875

Infrared Spectroscopy of Pollen Identifies Plant Species and Genus as Well as Environmental Conditions

PubMed Central

Zimmermann, Boris; Kohler, Achim

2014-01-01

Background It is imperative to have reliable and timely methodologies for analysis and monitoring of seed plants in order to determine climate-related plant processes. Moreover, impact of environment on plant fitness is predominantly based on studies of female functions, while the contribution of male gametophytes is mostly ignored due to missing data on pollen quality. We explored the use of infrared spectroscopy of pollen for an inexpensive and rapid characterization of plants. Methodology The study was based on measurement of pollen samples by two Fourier transform infrared techniques: single reflectance attenuated total reflectance and transmission measurement of sample pellets. The experimental set, with a total of 813 samples, included five pollination seasons and 300 different plant species belonging to all principal spermatophyte clades (conifers, monocotyledons, eudicots, and magnoliids). Results The spectroscopic-based methodology enables detection of phylogenetic variations, including the separation of confamiliar and congeneric species. Furthermore, the methodology enables measurement of phenotypic plasticity by the detection of inter-annual variations within the populations. The spectral differences related to environment and taxonomy are interpreted biochemically, specifically variations of pollen lipids, proteins, carbohydrates, and sporopollenins. The study shows large variations of absolute content of nutrients for congenital species pollinating in the same environmental conditions. Moreover, clear correlation between carbohydrate-to-protein ratio and pollination strategy has been detected. Infrared spectral database with respect to biochemical variation among the range of species, climate and biogeography will significantly improve comprehension of plant-environment interactions, including impact of global climate change on plant communities. PMID:24748390

Multispectral information for gas and aerosol retrieval from TANSO-FTS instrument

NASA Astrophysics Data System (ADS)

Herbin, H.; Labonnote, L. C.; Dubuisson, P.

2012-11-01

The Greenhouse gases Observing SATellite (GOSAT) mission and in particular TANSO-FTS instrument has the advantage to measure simultaneously the same field of view in different spectral ranges with a high spectral resolution. These features are promising to improve, not only, gaseous retrieval in clear sky or scattering atmosphere, but also to retrieve aerosol parameters. Therefore, this paper is dedicated to an Information Content (IC) analysis of potential synergy between thermal infrared, shortwave infrared and visible, in order to obtain a more accurate retrieval of gas and aerosol. The latter is based on Shannon theory and used a sophisticated radiative transfer algorithm developed at "Laboratoire d'Optique Atmosphérique", dealing with multiple scattering. This forward model can be relied to an optimal estimation method, which allows simultaneously retrieving gases profiles and aerosol granulometry and concentration. The analysis of the information provided by the spectral synergy is based on climatology of dust, volcanic ash and biomass burning aerosols. This work was conducted in order to develop a powerful tool that allows retrieving simultaneously not only the gas concentrations but also the aerosol characteristics by selecting the so called "best channels", i.e. the channels that bring most of the information concerning gas and aerosol. The methodology developed in this paper could also be used to define the specifications of future high spectral resolution mission to reach a given accuracy on retrieved parameters.

An analysis of IGBP global land-cover characterization process

USGS Publications Warehouse

Loveland, Thomas R.; Zhu, Zhiliang; Ohlen, Donald O.; Brown, Jesslyn F.; Reed, Bradley C.; Yang, Limin

1999-01-01

The international Geosphere Biosphere Programme (IGBP) has called for the development of improved global land-cover data for use in increasingly sophisticated global environmental models. To meet this need, the staff of the U.S. Geological Survey and the University of Nebraska-Lincoln developed and applied a global land-cover characterization methodology using 1992-1993 1-km resolution Advanced Very High Resolution Radiometer (AVHRR) and other spatial data. The methodology, based on unsupervised classification with extensive postclassification refinement, yielded a multi-layer database consisting of eight land-cover data sets, descriptive attributes, and source data. An independent IGBP accuracy assessment reports a global accuracy of 73.5 percent, and continental results vary from 63 percent to 83 percent. Although data quality, methodology, interpreter performance, and logistics affected the results, significant problems were associated with the relationship between AVHRR data and fine-scale, spectrally similar land-cover patterns in complex natural or disturbed landscapes.

Modification of kaolinite surfaces through mechanochemical activation with quartz: A diffuse reflectance infrared fourier transform and chemometrics study.

PubMed

Carmody, Onuma; Frost, Ray L; Kristóf, János; Kokot, Serge; Kloprogge, J Theo; Makó, Eva

2006-12-01

Studies of kaolinite surfaces are of industrial importance. One useful method for studying the changes in kaolinite surface properties is to apply chemometric analyses to the kaolinite surface infrared spectra. A comparison is made between the mechanochemical activation of Kiralyhegy kaolinites with significant amounts of natural quartz and the mechanochemical activation of Zettlitz kaolinite with added quartz. Diffuse reflectance infrared Fourier transform (DRIFT) spectra were analyzed using principal component analysis (PCA) and multi-criteria decision making (MCDM) methods, the preference ranking organization method for enrichment evaluations (PROMETHEE) and geometrical analysis for interactive assistance (GAIA). The clear discrimination of the Kiralyhegy spectral objects on the two PC scores plots (400-800 and 800-2030 cm(-1)) indicated the dominance of quartz. Importantly, no ordering of any spectral objects appeared to be related to grinding time in the PC plots of these spectral regions. Thus, neither the kaolinite nor the quartz are systematically responsive to grinding time according to the spectral criteria investigated. The third spectral region (2600-3800 cm(-1), OH vibrations), showed apparent systematic ordering of the Kiralyhegy and, to a lesser extent, Zettlitz spectral objects with grinding time. This was attributed to the effect of the natural quartz on the delamination of kaolinite and the accompanying phenomena (i.e., formation of kaolinite spheres and water). The mechanochemical activation of kaolinite and quartz, through dry grinding, results in changes to the surface structure. Different grinding times were adopted to study the rate of destruction of the kaolinite and quartz structures. This relationship (i.e., grinding time) was classified using PROMETHEE and GAIA methodology.

Statistical analysis of Thematic Mapper Simulator data for the geobotanical discrimination of rock types in southwest Oregon

NASA Technical Reports Server (NTRS)

Morrissey, L. A.; Weinstock, K. J.; Mouat, D. A.; Card, D. H.

1984-01-01

An evaluation of Thematic Mapper Simulator (TMS) data for the geobotanical discrimination of rock types based on vegetative cover characteristics is addressed in this research. A methodology for accomplishing this evaluation utilizing univariate and multivariate techniques is presented. TMS data acquired with a Daedalus DEI-1260 multispectral scanner were integrated with vegetation and geologic information for subsequent statistical analyses, which included a chi-square test, an analysis of variance, stepwise discriminant analysis, and Duncan's multiple range test. Results indicate that ultramafic rock types are spectrally separable from nonultramafics based on vegetative cover through the use of statistical analyses.

A Multivariate Methodological Workflow for the Analysis of FTIR Chemical Mapping Applied on Historic Paint Stratigraphies

PubMed Central

Sciutto, Giorgia; Oliveri, Paolo; Catelli, Emilio; Bonacini, Irene

2017-01-01

In the field of applied researches in heritage science, the use of multivariate approach is still quite limited and often chemometric results obtained are often underinterpreted. Within this scenario, the present paper is aimed at disseminating the use of suitable multivariate methodologies and proposes a procedural workflow applied on a representative group of case studies, of considerable importance for conservation purposes, as a sort of guideline on the processing and on the interpretation of this FTIR data. Initially, principal component analysis (PCA) is performed and the score values are converted into chemical maps. Successively, the brushing approach is applied, demonstrating its usefulness for a deep understanding of the relationships between the multivariate map and PC score space, as well as for the identification of the spectral bands mainly involved in the definition of each area localised within the score maps. PMID:29333162

Nonlinear Computerized Methodology. A. Angle of Arrival Estimation. B. Data Modeling and Identification

DTIC Science & Technology

1991-06-10

essentially In the Wianer- Ville distribution ( WVD ). A preliminary analysis indicates that the simple operation of autoconvolution can enhance spectral...many troublesome cases as a supplement to MUSIC (and its adaptations) and as a simple alternative (or representation of) the Wigner - Ville ... WVD is a time-frequency distribution which provides an unbiased spectrum estimate by W(t,W) = f H,(u) X (t - u/2) X (t + u/2) e -iwu du , where the

Forecasting daily passenger traffic volumes in the Moscow metro

NASA Astrophysics Data System (ADS)

Ivanov, V. V.; Osetrov, E. S.

2018-01-01

In this paper we have developed a methodology for the medium-term prediction of daily volumes of passenger traffic in the Moscow metro. It includes three options for the forecast: (1) based on artificial neural networks (ANNs), (2) singular-spectral analysis implemented in the Caterpillar-SSA package, and (3) a combination of the ANN and Caterpillar-SSA approaches. The methods and algorithms allow the mediumterm forecasting of passenger traffic flows in the Moscow metro with reasonable accuracy.

Cancer diagnosis by infrared spectroscopy: methodological aspects

NASA Astrophysics Data System (ADS)

Jackson, Michael; Kim, Keith; Tetteh, John; Mansfield, James R.; Dolenko, Brion; Somorjai, Raymond L.; Orr, F. W.; Watson, Peter H.; Mantsch, Henry H.

1998-04-01

IR spectroscopy is proving to be a powerful tool for the study and diagnosis of cancer. The application of IR spectroscopy to the analysis of cultured tumor cells and grading of breast cancer sections is outlined. Potential sources of error in spectral interpretation due to variations in sample histology and artifacts associated with sample storage and preparation are discussed. The application of statistical techniques to assess differences between spectra and to non-subjectively classify spectra is demonstrated.

High-Order Moving Overlapping Grid Methodology in a Spectral Element Method

NASA Astrophysics Data System (ADS)

Merrill, Brandon E.

A moving overlapping mesh methodology that achieves spectral accuracy in space and up to second-order accuracy in time is developed for solution of unsteady incompressible flow equations in three-dimensional domains. The targeted applications are in aerospace and mechanical engineering domains and involve problems in turbomachinery, rotary aircrafts, wind turbines and others. The methodology is built within the dual-session communication framework initially developed for stationary overlapping meshes. The methodology employs semi-implicit spectral element discretization of equations in each subdomain and explicit treatment of subdomain interfaces with spectrally-accurate spatial interpolation and high-order accurate temporal extrapolation, and requires few, if any, iterations, yet maintains the global accuracy and stability of the underlying flow solver. Mesh movement is enabled through the Arbitrary Lagrangian-Eulerian formulation of the governing equations, which allows for prescription of arbitrary velocity values at discrete mesh points. The stationary and moving overlapping mesh methodologies are thoroughly validated using two- and three-dimensional benchmark problems in laminar and turbulent flows. The spatial and temporal global convergence, for both methods, is documented and is in agreement with the nominal order of accuracy of the underlying solver. Stationary overlapping mesh methodology was validated to assess the influence of long integration times and inflow-outflow global boundary conditions on the performance. In a turbulent benchmark of fully-developed turbulent pipe flow, the turbulent statistics are validated against the available data. Moving overlapping mesh simulations are validated on the problems of two-dimensional oscillating cylinder and a three-dimensional rotating sphere. The aerodynamic forces acting on these moving rigid bodies are determined, and all results are compared with published data. Scaling tests, with both methodologies, show near linear strong scaling, even for moderately large processor counts. The moving overlapping mesh methodology is utilized to investigate the effect of an upstream turbulent wake on a three-dimensional oscillating NACA0012 extruded airfoil. A direct numerical simulation (DNS) at Reynolds Number 44,000 is performed for steady inflow incident upon the airfoil oscillating between angle of attack 5.6° and 25° with reduced frequency k=0.16. Results are contrasted with subsequent DNS of the same oscillating airfoil in a turbulent wake generated by a stationary upstream cylinder.

Cells and biofluids analyzed in aqueous environment by infrared spectroscopy

NASA Astrophysics Data System (ADS)

Naumann, D.; Lasch, P.; Fabian, H.

2006-02-01

Infrared transmission/absorption measurements of cells and biofluids in water are restricted to very short optical pathlengths. When the amide I and amide II bands of protein constituents have to be analysed, path-lengths of less than 8 μm are necessary. Infrared spectra of cancer cells were collected from physiological buffer solutions utilizing custom-made mid-infrared compatible IR-cuvettes. The technology permitted to obtain cell-type specific spectral signatures and probe biochemical changes induced by varying temperatures or cell-drug interaction. Optical path-lengths of 8-30 μm were used on a set of microbial test strains to evaluate, whether the methodology can also be used to discriminate and identify micro-organisms. A semi-automatic methodology was developed for the analysis of liquid serum samples, which combines simple sample handling with high sample throughput and extreme measurement reproducibility. The applicability of this infrared technology to the analysis of liquid serum samples from cattle and human beings suffering from various acute viral or bacterial infections was explored testing the interrelationship between α-helical and β-sheet specific spectral signatures in the amide I band contour and total albumin and globulin content in serum. The technical details, advantages, and limitations of the new technology are described in the context of developing a routine, IR-based biodiagnostic technique for biofluids and biological cells.

Radiometric spectral and band rendering of targets using anisotropic BRDFs and measured backgrounds

NASA Astrophysics Data System (ADS)

Hilgers, John W.; Hoffman, Jeffrey A.; Reynolds, William R.; Jafolla, James C.

2000-07-01

Achievement of ultra-high fidelity signature modeling of targets requires a significant level of complexity for all of the components required in the rendering process. Specifically, the reflectance of the surface must be described using the bi-directional distribution function (BRDF). In addition, the spatial representation of the background must be high fidelity. A methodology and corresponding model for spectral and band rendering of targets using both isotropic and anisotropic BRDFs is presented. In addition, a set of tools will be described for generating theoretical anisotropic BRDFs and for reducing data required for a description of an anisotropic BRDF by 5 orders of magnitude. This methodology is hybrid using a spectrally measured panoramic of the background mapped to a large hemisphere. Both radiosity and ray-tracing approaches are incorporated simultaneously for a robust solution. In the thermal domain the spectral emission is also included in the solution. Rendering examples using several BRDFs will be presented.

Spatial and Temporal Dust Source Variability in Northern China Identified Using Advanced Remote Sensing Analysis

NASA Technical Reports Server (NTRS)

Taramelli, A.; Pasqui, M.; Barbour, J.; Kirschbaum, D.; Bottai, L.; Busillo, C.; Calastrini, F.; Guarnieri, F.; Small, C.

2013-01-01

The aim of this research is to provide a detailed characterization of spatial patterns and temporal trends in the regional and local dust source areas within the desert of the Alashan Prefecture (Inner Mongolia, China). This problem was approached through multi-scale remote sensing analysis of vegetation changes. The primary requirements for this regional analysis are high spatial and spectral resolution data, accurate spectral calibration and good temporal resolution with a suitable temporal baseline. Landsat analysis and field validation along with the low spatial resolution classifications from MODIS and AVHRR are combined to provide a reliable characterization of the different potential dust-producing sources. The representation of intra-annual and inter-annual Normalized Difference Vegetation Index (NDVI) trend to assess land cover discrimination for mapping potential dust source using MODIS and AVHRR at larger scale is enhanced by Landsat Spectral Mixing Analysis (SMA). The combined methodology is to determine the extent to which Landsat can distinguish important soils types in order to better understand how soil reflectance behaves at seasonal and inter-annual timescales. As a final result mapping soil surface properties using SMA is representative of responses of different land and soil cover previously identified by NDVI trend. The results could be used in dust emission models even if they are not reflecting aggregate formation, soil stability or particle coatings showing to be critical for accurately represent dust source over different regional and local emitting areas.

Evaluating sensor linearity of chosen infrared sensors

NASA Astrophysics Data System (ADS)

Walczykowski, P.; Orych, A.; Jenerowicz, A.; Karcz, P.

2014-11-01

The paper describes a series of experiments conducted as part of the IRAMSWater Project, the aim of which is to establish methodologies for detecting and identifying pollutants in water bodies using aerial imagery data. The main idea is based on the hypothesis, that it is possible to identify certain types of physical, biological and chemical pollutants based on their spectral reflectance characteristics. The knowledge of these spectral curves is then used to determine very narrow spectral bands in which greatest reflectance variations occur between these pollutants. A frame camera is then equipped with a band pass filter, which allows only the selected bandwidth to be registered. In order to obtain reliable reflectance data straight from the images, the team at the Military University of Technology had developed a methodology for determining the necessary acquisition parameters for the sensor (integration time and f-stop depending on the distance from the scene and it's illumination). This methodology however is based on the assumption, that the imaging sensors have a linear response. This paper shows the results of experiments used to evaluate this linearity.

Non-invasive assessment of thromboembolism in rotary blood pumps: case study

NASA Astrophysics Data System (ADS)

Gawlikowski, Maciej; Kustosz, Roman; Głowacki, Maciej; Pydziński, Paweł; Kubacki, Krzysztof; Zakliczyński, Michał; Copik, Izabela; Pacholewicz, Jerzy

2017-08-01

Thromboembolic complications are one of the major problems in mechanical heart support of patients suffering from critical heart failure. The goal of the study was to present and discuss methodology of non-invasive assessment of embolization in rotary blood pumps. The study was carried out based on power consumption trend analysis as well as spectral analysis of acoustic signal produced by the pump during its operation. It has been demonstrated that the trend of power rising and presence of 3rd harmonic in acoustic spectrum corresponds to the clinical symptoms of pump embolization.

Implemented Lomb-Scargle periodogram: a valuable tool for improving cyclostratigraphic research on unevenly sampled deep-sea stratigraphic sequences

NASA Astrophysics Data System (ADS)

Pardo-Iguzquiza, Eulogio; Rodríguez-Tovar, Francisco J.

2011-12-01

One important handicap when working with stratigraphic sequences is the discontinuous character of the sedimentary record, especially relevant in cyclostratigraphic analysis. Uneven palaeoclimatic/palaeoceanographic time series are common, their cyclostratigraphic analysis being comparatively difficult because most spectral methodologies are appropriate only when working with even sampling. As a means to solve this problem, a program for calculating the smoothed Lomb-Scargle periodogram and cross-periodogram, which additionally evaluates the statistical confidence of the estimated power spectrum through a Monte Carlo procedure (the permutation test), has been developed. The spectral analysis of a short uneven time series calls for assessment of the statistical significance of the spectral peaks, since a periodogram can always be calculated but the main challenge resides in identifying true spectral features. To demonstrate the effectiveness of this program, two case studies are presented: the one deals with synthetic data and the other with paleoceanographic/palaeoclimatic proxies. On a simulated time series of 500 data, two uneven time series (with 100 and 25 data) were generated by selecting data at random. Comparative analysis between the power spectra from the simulated series and from the two uneven time series demonstrates the usefulness of the smoothed Lomb-Scargle periodogram for uneven sequences, making it possible to distinguish between statistically significant and spurious spectral peaks. Fragmentary time series of Cd/Ca ratios and δ18O from core AII107-131 of SPECMAP were analysed as a real case study. The efficiency of the direct and cross Lomb-Scargle periodogram in recognizing Milankovitch and sub-Milankovitch signals related to palaeoclimatic/palaeoceanographic changes is demonstrated. As implemented, the Lomb-Scargle periodogram may be applied to any palaeoclimatic/palaeoceanographic proxies, including those usually recovered from contourites, and it holds special interest in the context of centennial- to millennial-scale climatic changes affecting contouritic currents.

New insights into soil temperature time series modeling: linear or nonlinear?

NASA Astrophysics Data System (ADS)

Bonakdari, Hossein; Moeeni, Hamid; Ebtehaj, Isa; Zeynoddin, Mohammad; Mahoammadian, Abdolmajid; Gharabaghi, Bahram

2018-03-01

Soil temperature (ST) is an important dynamic parameter, whose prediction is a major research topic in various fields including agriculture because ST has a critical role in hydrological processes at the soil surface. In this study, a new linear methodology is proposed based on stochastic methods for modeling daily soil temperature (DST). With this approach, the ST series components are determined to carry out modeling and spectral analysis. The results of this process are compared with two linear methods based on seasonal standardization and seasonal differencing in terms of four DST series. The series used in this study were measured at two stations, Champaign and Springfield, at depths of 10 and 20 cm. The results indicate that in all ST series reviewed, the periodic term is the most robust among all components. According to a comparison of the three methods applied to analyze the various series components, it appears that spectral analysis combined with stochastic methods outperformed the seasonal standardization and seasonal differencing methods. In addition to comparing the proposed methodology with linear methods, the ST modeling results were compared with the two nonlinear methods in two forms: considering hydrological variables (HV) as input variables and DST modeling as a time series. In a previous study at the mentioned sites, Kim and Singh Theor Appl Climatol 118:465-479, (2014) applied the popular Multilayer Perceptron (MLP) neural network and Adaptive Neuro-Fuzzy Inference System (ANFIS) nonlinear methods and considered HV as input variables. The comparison results signify that the relative error projected in estimating DST by the proposed methodology was about 6%, while this value with MLP and ANFIS was over 15%. Moreover, MLP and ANFIS models were employed for DST time series modeling. Due to these models' relatively inferior performance to the proposed methodology, two hybrid models were implemented: the weights and membership function of MLP and ANFIS (respectively) were optimized with the particle swarm optimization (PSO) algorithm in conjunction with the wavelet transform and nonlinear methods (Wavelet-MLP & Wavelet-ANFIS). A comparison of the proposed methodology with individual and hybrid nonlinear models in predicting DST time series indicates the lowest Akaike Information Criterion (AIC) index value, which considers model simplicity and accuracy simultaneously at different depths and stations. The methodology presented in this study can thus serve as an excellent alternative to complex nonlinear methods that are normally employed to examine DST.

Laboratory calibration of pyrgeometers with known spectral responsivities.

PubMed

Gröbner, Julian; Los, Alexander

2007-10-20

A methodology is presented to calibrate pyrgeometers measuring atmospheric long-wave radiation, if their spectral dome transmission is known. The new calibration procedure is based on a black-body cavity to retrieve the sensitivity of the pyrgeometer, combined with calculated atmospheric long-wave spectra to determine a correction function in dependence of the integrated atmospheric water vapor to convert Planck radiation spectra to atmospheric long-wave spectra. The methodology was validated with two custom CG4 pyrgeometers with known dome transmissions by a comparison to the World Infrared Standard Group of Pyrgeometers at the World Radiation Center-Infrared Radiometry Section. The responses retrieved using the new laboratory calibration agree to within 1% with the responses determined by a comparison to the WISG, which is well within the uncertainties of both methodologies.

Towards a non-invasive quantitative analysis of the organic components in museum objects varnishes by vibrational spectroscopies: methodological approach.

PubMed

Daher, Céline; Pimenta, Vanessa; Bellot-Gurlet, Ludovic

2014-11-01

The compositions of ancient varnishes are mainly determined destructively by separation methods coupled to mass spectrometry. In this study, a methodology for non-invasive quantitative analyses of varnishes by vibrational spectroscopies is proposed. For that, experimental simplified varnishes of colophony and linseed oil were prepared according to 18th century traditional recipes with an increasing mass concentration ratio of colophony/linseed oil. FT-Raman and IR analyses using ATR and non-invasive reflectance modes were done on the "pure" materials and on the different mixtures. Then, a new approach involving spectral decomposition calculation was developed considering the mixture spectra as a linear combination of the pure materials ones, and giving a relative amount of each component. Specific spectral regions were treated and the obtained results show a good accuracy between the prepared and calculated amounts of the two compounds. We were thus able to detect and quantify from 10% to 50% of colophony in linseed oil using non-invasive techniques that can also be conducted in situ with portable instruments when it comes to museum varnished objects and artifacts. Copyright © 2014 Elsevier B.V. All rights reserved.

Intelligent image processing for vegetation classification using multispectral LANDSAT data

NASA Astrophysics Data System (ADS)

Santos, Stewart R.; Flores, Jorge L.; Garcia-Torales, G.

2015-09-01

We propose an intelligent computational technique for analysis of vegetation imaging, which are acquired with multispectral scanner (MSS) sensor. This work focuses on intelligent and adaptive artificial neural network (ANN) methodologies that allow segmentation and classification of spectral remote sensing (RS) signatures, in order to obtain a high resolution map, in which we can delimit the wooded areas and quantify the amount of combustible materials present into these areas. This could provide important information to prevent fires and deforestation of wooded areas. The spectral RS input data, acquired by the MSS sensor, are considered in a random propagation remotely sensed scene with unknown statistics for each Thematic Mapper (TM) band. Performing high-resolution reconstruction and adding these spectral values with neighbor pixels information from each TM band, we can include contextual information into an ANN. The biggest challenge in conventional classifiers is how to reduce the number of components in the feature vector, while preserving the major information contained in the data, especially when the dimensionality of the feature space is high. Preliminary results show that the Adaptive Modified Neural Network method is a promising and effective spectral method for segmentation and classification in RS images acquired with MSS sensor.

Evaluating hybrid bermudagrass using spectral reflectance under different mowing heights and trinexapac-ethyl applications

USDA-ARS?s Scientific Manuscript database

Quantitative spectral reflectance data has the potential to improve the evaluation of turfgrass variety trials when management practices are factors in the testing of turf aesthetics and functionality. However, the practical application of this methodology has not been well-developed. The objectives...

Spectral fractionation detection of gold nanorod contrast agents using optical coherence tomography

PubMed Central

Jia, Yali; Liu, Gangjun; Gordon, Andrew Y.; Gao, Simon S.; Pechauer, Alex D.; Stoddard, Jonathan; McGill, Trevor J.; Jayagopal, Ashwath; Huang, David

2015-01-01

We demonstrate the proof of concept of a novel Fourier-domain optical coherence tomography contrast mechanism using gold nanorod contrast agents and a spectral fractionation processing technique. The methodology detects the spectral shift of the backscattered light from the nanorods by comparing the ratio between the short and long wavelength halves of the optical coherence tomography signal intensity. Spectral fractionation further divides the halves into sub-bands to improve spectral contrast and suppress speckle noise. Herein, we show that this technique can detect gold nanorods in intralipid tissue phantoms. Furthermore, cellular labeling by gold nanorods was demonstrated using retinal pigment epithelial cells in vitro. PMID:25836459

Near-infrared hyperspectral imaging for quality analysis of agricultural and food products

NASA Astrophysics Data System (ADS)

Singh, C. B.; Jayas, D. S.; Paliwal, J.; White, N. D. G.

2010-04-01

Agricultural and food processing industries are always looking to implement real-time quality monitoring techniques as a part of good manufacturing practices (GMPs) to ensure high-quality and safety of their products. Near-infrared (NIR) hyperspectral imaging is gaining popularity as a powerful non-destructive tool for quality analysis of several agricultural and food products. This technique has the ability to analyse spectral data in a spatially resolved manner (i.e., each pixel in the image has its own spectrum) by applying both conventional image processing and chemometric tools used in spectral analyses. Hyperspectral imaging technique has demonstrated potential in detecting defects and contaminants in meats, fruits, cereals, and processed food products. This paper discusses the methodology of hyperspectral imaging in terms of hardware, software, calibration, data acquisition and compression, and development of prediction and classification algorithms and it presents a thorough review of the current applications of hyperspectral imaging in the analyses of agricultural and food products.

Sensitivity of VIIRS Polarization Measurements

NASA Technical Reports Server (NTRS)

Waluschka, Eugene

2010-01-01

The design of an optical system typically involves a sensitivity analysis where the various lens parameters, such as lens spacing and curvatures, to name two parameters, are (slightly) varied to see what, if any, effect this has on the performance and to establish manufacturing tolerances. A sinular analysis was performed for the VIIRS instruments polarization measurements to see how real world departures from perfectly linearly polarized light entering VIIRS effects the polarization measurement. The methodology and a few of the results of this polarization sensitivity analysis are presented and applied to the construction of a single polarizer which will cover the VIIRS VIS/NIR spectral range. Keywords: VIIRS, polarization, ray, trace; polarizers, Bolder Vision, MOXTEK

Statistical analysis of modal parameters of a suspension bridge based on Bayesian spectral density approach and SHM data

NASA Astrophysics Data System (ADS)

Li, Zhijun; Feng, Maria Q.; Luo, Longxi; Feng, Dongming; Xu, Xiuli

2018-01-01

Uncertainty of modal parameters estimation appear in structural health monitoring (SHM) practice of civil engineering to quite some significant extent due to environmental influences and modeling errors. Reasonable methodologies are needed for processing the uncertainty. Bayesian inference can provide a promising and feasible identification solution for the purpose of SHM. However, there are relatively few researches on the application of Bayesian spectral method in the modal identification using SHM data sets. To extract modal parameters from large data sets collected by SHM system, the Bayesian spectral density algorithm was applied to address the uncertainty of mode extraction from output-only response of a long-span suspension bridge. The posterior most possible values of modal parameters and their uncertainties were estimated through Bayesian inference. A long-term variation and statistical analysis was performed using the sensor data sets collected from the SHM system of the suspension bridge over a one-year period. The t location-scale distribution was shown to be a better candidate function for frequencies of lower modes. On the other hand, the burr distribution provided the best fitting to the higher modes which are sensitive to the temperature. In addition, wind-induced variation of modal parameters was also investigated. It was observed that both the damping ratios and modal forces increased during the period of typhoon excitations. Meanwhile, the modal damping ratios exhibit significant correlation with the spectral intensities of the corresponding modal forces.

Quantitative spectral and orientational analysis in surface sum frequency generation vibrational spectroscopy (SFG-VS)

NASA Astrophysics Data System (ADS)

Wang, Hong-Fei; Gan, Wei; Lu, Rong; Rao, Yi; Wu, Bao-Hua

Sum frequency generation vibrational spectroscopy (SFG-VS) has been proven to be a uniquely effective spectroscopic technique in the investigation of molecular structure and conformations, as well as the dynamics of molecular interfaces. However, the ability to apply SFG-VS to complex molecular interfaces has been limited by the ability to abstract quantitative information from SFG-VS experiments. In this review, we try to make assessments of the limitations, issues and techniques as well as methodologies in quantitative orientational and spectral analysis with SFG-VS. Based on these assessments, we also try to summarize recent developments in methodologies on quantitative orientational and spectral analysis in SFG-VS, and their applications to detailed analysis of SFG-VS data of various vapour/neat liquid interfaces. A rigorous formulation of the polarization null angle (PNA) method is given for accurate determination of the orientational parameter D = /, and comparison between the PNA method with the commonly used polarization intensity ratio (PIR) method is discussed. The polarization and incident angle dependencies of the SFG-VS intensity are also reviewed, in the light of how experimental arrangements can be optimized to effectively abstract crucial information from the SFG-VS experiments. The values and models of the local field factors in the molecular layers are discussed. In order to examine the validity and limitations of the bond polarizability derivative model, the general expressions for molecular hyperpolarizability tensors and their expression with the bond polarizability derivative model for C3v, C2v and C∞v molecular groups are given in the two appendixes. We show that the bond polarizability derivative model can quantitatively describe many aspects of the intensities observed in the SFG-VS spectrum of the vapour/neat liquid interfaces in different polarizations. Using the polarization analysis in SFG-VS, polarization selection rules or guidelines are developed for assignment of the SFG-VS spectrum. Using the selection rules, SFG-VS spectra of vapour/diol, and vapour/n-normal alcohol (n˜ 1-8) interfaces are assigned, and some of the ambiguity and confusion, as well as their implications in previous IR and Raman assignment, are duly discussed. The ability to assign a SFG-VS spectrum using the polarization selection rules makes SFG-VS not only an effective and useful vibrational spectroscopy technique for interface studies, but also a complementary vibrational spectroscopy method in general condensed phase studies. These developments will put quantitative orientational and spectral analysis in SFG-VS on a more solid foundation. The formulations, concepts and issues discussed in this review are expected to find broad applications for investigations on molecular interfaces in the future.

Assessment of low back muscle fatigue by surface EMG signal analysis: methodological aspects.

PubMed

Farina, Dario; Gazzoni, Marco; Merletti, Roberto

2003-08-01

This paper focuses on methodological issues related to surface electromyographic (EMG) signal detection from the low back muscles. In particular, we analysed (1) the characteristics (in terms of propagating components) of the signals detected from these muscles; (2) the effect of electrode location on the variables extracted from surface EMG; (3) the effect of the inter-electrode distance (IED) on the same variables; (4) the possibility of assessing fatigue during high and very low force level contractions. To address these issues, we detected single differential surface EMG signals by arrays of eight electrodes from six locations on the two sides of the spine, at the levels of the first (L1), the second (L2), and the fifth (L5) lumbar vertebra. In total, 42 surface EMG channels were acquired at the same time during both high and low force, short and long duration contractions. The main results were: (1) signal quality is poor with predominance of non-travelling components; (2) as a consequence of point (1), in the majority of the cases it is not possible to reliably estimate muscle fiber conduction velocity; (3) despite the poor signal quality, it was possible to distinguish the fatigue properties of the investigated muscles and the fatigability at different contraction levels; (4) IED affects the sensitivity of surface EMG variables to electrode location and large IEDs are suggested when spectral and amplitude analysis is performed; (5) the sensitivity of surface EMG variables to changes in electrode location is on average larger than for other muscles with less complex architecture; (6) IED influences amplitude initial values and slopes, and spectral variable initial values; (7) normalized slopes for both amplitude and spectral variables are not affected by IED and, thus, are suggested for fatigue analysis at different postures or during movement, when IED may change in different conditions (in case of separated electrodes); (8) the surface EMG technique at the global level of amplitude and spectral analysis cannot be used to characterize fatigue properties of low back muscles during very low level, long duration contractions since in these cases the non-stable MU pool has a major influence on the EMG variables. These considerations clarify issues only partially investigated in past studies. The limitations indicated above are important and should be carefully discussed when presenting surface EMG results as a means for low back muscle assessment in clinical practice.

Simulation of multi-element multispectral UV radiation source for optical-electronic system of minerals luminescence analysis

NASA Astrophysics Data System (ADS)

Peretyagin, Vladimir S.; Korolev, Timofey K.; Chertov, Aleksandr N.

2017-02-01

The problems of dressability the solid minerals are attracted attention of specialists, where the extraction of mineral raw materials is a significant sector of the economy. There are a significant amount of mineral ore dressability methods. At the moment the radiometric dressability methods are considered the most promising. One of radiometric methods is method photoluminescence. This method is based on the spectral analysis, amplitude and kinetic parameters luminescence of minerals (under UV radiation), as well as color parameters of radiation. The absence of developed scientific and methodological approaches of analysis irradiation area to UV radiation as well as absence the relevant radiation sources are the factors which hinder development and use of photoluminescence method. The present work is devoted to the development of multi-element UV radiation source designed for the solution problem of analysis and sorting minerals by their selective luminescence. This article is presented a method of theoretical modeling of the radiation devices based on UV LEDs. The models consider such factors as spectral component, the spatial and energy parameters of the LEDs. Also, this article is presented the results of experimental studies of the some samples minerals.

Analysis of crystalline lens coloration using a black and white charge-coupled device camera.

PubMed

Sakamoto, Y; Sasaki, K; Kojima, M

1994-01-01

To analyze lens coloration in vivo, we used a new type of Scheimpflug camera that is a black and white type of charge-coupled device (CCD) camera. A new methodology was proposed. Scheimpflug images of the lens were taken three times through red (R), green (G), and blue (B) filters, respectively. Three images corresponding with the R, G, and B channels were combined into one image on the cathode-ray tube (CRT) display. The spectral transmittance of the tricolor filters and the spectral sensitivity of the CCD camera were used to correct the scattering-light intensity of each image. Coloration of the lens was expressed on a CIE standard chromaticity diagram. The lens coloration of seven eyes analyzed by this method showed values almost the same as those obtained by the previous method using color film.

PlanetServer: Innovative approaches for the online analysis of hyperspectral satellite data from Mars

NASA Astrophysics Data System (ADS)

Oosthoek, J. H. P.; Flahaut, J.; Rossi, A. P.; Baumann, P.; Misev, D.; Campalani, P.; Unnithan, V.

2014-06-01

PlanetServer is a WebGIS system, currently under development, enabling the online analysis of Compact Reconnaissance Imaging Spectrometer (CRISM) hyperspectral data from Mars. It is part of the EarthServer project which builds infrastructure for online access and analysis of huge Earth Science datasets. Core functionality consists of the rasdaman Array Database Management System (DBMS) for storage, and the Open Geospatial Consortium (OGC) Web Coverage Processing Service (WCPS) for data querying. Various WCPS queries have been designed to access spatial and spectral subsets of the CRISM data. The client WebGIS, consisting mainly of the OpenLayers javascript library, uses these queries to enable online spatial and spectral analysis. Currently the PlanetServer demonstration consists of two CRISM Full Resolution Target (FRT) observations, surrounding the NASA Curiosity rover landing site. A detailed analysis of one of these observations is performed in the Case Study section. The current PlanetServer functionality is described step by step, and is tested by focusing on detecting mineralogical evidence described in earlier Gale crater studies. Both the PlanetServer methodology and its possible use for mineralogical studies will be further discussed. Future work includes batch ingestion of CRISM data and further development of the WebGIS and analysis tools.

Characterizing Aeroallergens by Infrared Spectroscopy of Fungal Spores and Pollen

PubMed Central

Zimmermann, Boris; Tkalčec, Zdenko; Mešić, Armin; Kohler, Achim

2015-01-01

Background Fungal spores and plant pollen cause respiratory diseases in susceptible individuals, such as asthma, allergic rhinitis and hypersensitivity pneumonitis. Aeroallergen monitoring networks are an important part of treatment strategies, but unfortunately traditional analysis is time consuming and expensive. We have explored the use of infrared spectroscopy of pollen and spores for an inexpensive and rapid characterization of aeroallergens. Methodology The study is based on measurement of spore and pollen samples by single reflectance attenuated total reflectance Fourier transform infrared spectroscopy (SR-ATR FTIR). The experimental set includes 71 spore (Basidiomycota) and 121 pollen (Pinales, Fagales and Poales) samples. Along with fresh basidiospores, the study has been conducted on the archived samples collected within the last 50 years. Results The spectroscopic-based methodology enables clear spectral differentiation between pollen and spores, as well as the separation of confamiliar and congeneric species. In addition, the analysis of the scattering signals inherent in the infrared spectra indicates that the FTIR methodology offers indirect estimation of morphology of pollen and spores. The analysis of fresh and archived spores shows that chemical composition of spores is well preserved even after decades of storage, including the characteristic taxonomy-related signals. Therefore, biochemical analysis of fungal spores by FTIR could provide economical, reliable and timely methodologies for improving fungal taxonomy, as well as for fungal identification and monitoring. This proof of principle study shows the potential for using FTIR as a rapid tool in aeroallergen studies. In addition, the presented method is ready to be immediately implemented in biological and ecological studies for direct measurement of pollen and spores from flowers and sporocarps. PMID:25867755

Fine structure of the low-frequency spectra of heart rate and blood pressure

PubMed Central

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.

PubMed

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.

Analysis of Aerospike Plume Induced Base-Heating Environment

NASA Technical Reports Server (NTRS)

Wang, Ten-See

1998-01-01

Computational analysis is conducted to study the effect of an aerospike engine plume on X-33 base-heating environment during ascent flight. To properly account for the effect of forebody and aftbody flowfield such as shocks and to allow for potential plume-induced flow-separation, thermo-flowfield of trajectory points is computed. The computational methodology is based on a three-dimensional finite-difference, viscous flow, chemically reacting, pressure-base computational fluid dynamics formulation, and a three-dimensional, finite-volume, spectral-line based weighted-sum-of-gray-gases radiation absorption model computational heat transfer formulation. The predicted convective and radiative base-heat fluxes are presented.

Modal Parameters Evaluation in a Full-Scale Aircraft Demonstrator under Different Environmental Conditions Using HS 3D-DIC.

PubMed

Molina-Viedma, Ángel Jesús; López-Alba, Elías; Felipe-Sesé, Luis; Díaz, Francisco A; Rodríguez-Ahlquist, Javier; Iglesias-Vallejo, Manuel

2018-02-02

In real aircraft structures the comfort and the occupational performance of crewmembers and passengers are affected by the presence of noise. In this sense, special attention is focused on mechanical and material design for isolation and vibration control. Experimental characterization and, in particular, experimental modal analysis, provides information for adequate cabin noise control. Traditional sensors employed in the aircraft industry for this purpose are invasive and provide a low spatial resolution. This paper presents a methodology for experimental modal characterization of a front fuselage full-scale demonstrator using high-speed 3D digital image correlation, which is non-invasive, ensuring that the structural response is unperturbed by the instrumentation mass. Specifically, full-field measurements on the passenger window area were conducted when the structure was excited using an electrodynamic shaker. The spectral analysis of the measured time-domain displacements made it possible to identify natural frequencies and full-field operational deflection shapes. Changes in the modal parameters due to cabin pressurization and the behavior of different local structural modifications were assessed using this methodology. The proposed full-field methodology allowed the characterization of relevant dynamic response patterns, complementing the capabilities provided by accelerometers.

Modal Parameters Evaluation in a Full-Scale Aircraft Demonstrator under Different Environmental Conditions Using HS 3D-DIC

PubMed Central

López-Alba, Elías; Felipe-Sesé, Luis; Díaz, Francisco A.; Rodríguez-Ahlquist, Javier; Iglesias-Vallejo, Manuel

2018-01-01

In real aircraft structures the comfort and the occupational performance of crewmembers and passengers are affected by the presence of noise. In this sense, special attention is focused on mechanical and material design for isolation and vibration control. Experimental characterization and, in particular, experimental modal analysis, provides information for adequate cabin noise control. Traditional sensors employed in the aircraft industry for this purpose are invasive and provide a low spatial resolution. This paper presents a methodology for experimental modal characterization of a front fuselage full-scale demonstrator using high-speed 3D digital image correlation, which is non-invasive, ensuring that the structural response is unperturbed by the instrumentation mass. Specifically, full-field measurements on the passenger window area were conducted when the structure was excited using an electrodynamic shaker. The spectral analysis of the measured time-domain displacements made it possible to identify natural frequencies and full-field operational deflection shapes. Changes in the modal parameters due to cabin pressurization and the behavior of different local structural modifications were assessed using this methodology. The proposed full-field methodology allowed the characterization of relevant dynamic response patterns, complementing the capabilities provided by accelerometers. PMID:29393897

Likelihood Ratios for Glaucoma Diagnosis Using Spectral Domain Optical Coherence Tomography

PubMed Central

Lisboa, Renato; Mansouri, Kaweh; Zangwill, Linda M.; Weinreb, Robert N.; Medeiros, Felipe A.

2014-01-01

Purpose To present a methodology for calculating likelihood ratios for glaucoma diagnosis for continuous retinal nerve fiber layer (RNFL) thickness measurements from spectral domain optical coherence tomography (spectral-domain OCT). Design Observational cohort study. Methods 262 eyes of 187 patients with glaucoma and 190 eyes of 100 control subjects were included in the study. Subjects were recruited from the Diagnostic Innovations Glaucoma Study. Eyes with preperimetric and perimetric glaucomatous damage were included in the glaucoma group. The control group was composed of healthy eyes with normal visual fields from subjects recruited from the general population. All eyes underwent RNFL imaging with Spectralis spectral-domain OCT. Likelihood ratios for glaucoma diagnosis were estimated for specific global RNFL thickness measurements using a methodology based on estimating the tangents to the Receiver Operating Characteristic (ROC) curve. Results Likelihood ratios could be determined for continuous values of average RNFL thickness. Average RNFL thickness values lower than 86μm were associated with positive LRs, i.e., LRs greater than 1; whereas RNFL thickness values higher than 86μm were associated with negative LRs, i.e., LRs smaller than 1. A modified Fagan nomogram was provided to assist calculation of post-test probability of disease from the calculated likelihood ratios and pretest probability of disease. Conclusion The methodology allowed calculation of likelihood ratios for specific RNFL thickness values. By avoiding arbitrary categorization of test results, it potentially allows for an improved integration of test results into diagnostic clinical decision-making. PMID:23972303

Novel thermal annealing methodology for permanent tuning polymer optical fiber Bragg gratings to longer wavelengths.

PubMed

Pospori, A; Marques, C A F; Sagias, G; Lamela-Rivera, H; Webb, D J

2018-01-22

The Bragg wavelength of a polymer optical fiber Bragg grating can be permanently shifted by utilizing the thermal annealing method. In all the reported fiber annealing cases, the authors were able to tune the Bragg wavelength only to shorter wavelengths, since the polymer fiber shrinks in length during the annealing process. This article demonstrates a novel thermal annealing methodology for permanently tuning polymer optical fiber Bragg gratings to any desirable spectral position, including longer wavelengths. Stretching the polymer optical fiber during the annealing process, the period of Bragg grating, which is directly related with the Bragg wavelength, can become permanently longer. The methodology presented in this article can be used to multiplex polymer optical fiber Bragg gratings at any desirable spectral position utilizing only one phase-mask for their photo-inscription, reducing thus their fabrication cost in an industrial setting.

Use of Spectral/Cepstral Analyses for Differentiating Normal from Hypofunctional Voices in Sustained Vowel and Continuous Speech Contexts

ERIC Educational Resources Information Center

Watts, Christopher R.; Awan, Shaheen N.

2011-01-01

Purpose: In this study, the authors evaluated the diagnostic value of spectral/cepstral measures to differentiate dysphonic from nondysphonic voices using sustained vowels and continuous speech samples. Methodology: Thirty-two age- and gender-matched individuals (16 participants with dysphonia and 16 controls) were recorded reading a standard…

Convectively Coupled Equatorial Waves in Reanalysis and CMIP5 Simulations

NASA Astrophysics Data System (ADS)

Castanheira, J. M.; Marques, C. A. F.

2014-12-01

Convectively coupled equatorial waves (CCEWs) are a result of the interplay between the physics and dynamics in the tropical atmosphere. As a result of such interplay, tropical convection appears often organized into synoptic to planetary-scale disturbances with time scales matching those of equatorial shallow water waves. CCEWs have broad impacts within the tropics, and their simulation in general circulation models is still problematic. Several studies showed that dispersion of those waves characteristics fit the dispersion curves derived from the Matsuno's (1966) solutions of the shallow water equations on the equatorial beta plane, namely, Kelvin, equatorial Rossby, mixed Rossby-gravity, and inertio-gravity waves. However, the more common methodology used to identify those waves is yet controversial. In this communication a new methodology for the diagnosis of CCEWs will be presented. It is based on a pre-filtering of the geopotential and horizontal wind, using 3--D normal modes functions of the adiabatic linearized equations of a resting atmosphere, followed by a space--time spectral analysis to identify the spectral regions of coherence. The methodology permits a direct detection of various types of equatorial waves, compares the dispersion characteristics of the coupled waves with the theoretical dispersion curves and allows an identification of which vertical modes are more involved in the convection. Moreover, the proposed methodology is able to show the existence of free dry waves and moist coupled waves with a common vertical structure, which is in conformity with the effect of convective heating/cooling on the effective static stability, as traduced in the gross moist stability concept. The methodology is also sensible to Doppler shifting effects. The methodology has been applied to the ERA-Interim horizontal wind and geopotential height fields and to the interpolated Outgoing Longwave Radiation (OLR) data produced by the National Oceanic and Atmospheric Administration. The same type of data (i.e. u, v, Φ and OLR) from CMIP5 historical experiments (1976-2005) were analyzed. The obtained results provide examples of the aforementioned effects and points deficiencies in the models.

Classification of riparian forest species and health condition using multi-temporal and hyperspatial imagery from unmanned aerial system.

PubMed

Michez, Adrien; Piégay, Hervé; Lisein, Jonathan; Claessens, Hugues; Lejeune, Philippe

2016-03-01

Riparian forests are critically endangered many anthropogenic pressures and natural hazards. The importance of riparian zones has been acknowledged by European Directives, involving multi-scale monitoring. The use of this very-high-resolution and hyperspatial imagery in a multi-temporal approach is an emerging topic. The trend is reinforced by the recent and rapid growth of the use of the unmanned aerial system (UAS), which has prompted the development of innovative methodology. Our study proposes a methodological framework to explore how a set of multi-temporal images acquired during a vegetative period can differentiate some of the deciduous riparian forest species and their health conditions. More specifically, the developed approach intends to identify, through a process of variable selection, which variables derived from UAS imagery and which scale of image analysis are the most relevant to our objectives.The methodological framework is applied to two study sites to describe the riparian forest through two fundamental characteristics: the species composition and the health condition. These characteristics were selected not only because of their use as proxies for the riparian zone ecological integrity but also because of their use for river management.The comparison of various scales of image analysis identified the smallest object-based image analysis (OBIA) objects (ca. 1 m(2)) as the most relevant scale. Variables derived from spectral information (bands ratios) were identified as the most appropriate, followed by variables related to the vertical structure of the forest. Classification results show good overall accuracies for the species composition of the riparian forest (five classes, 79.5 and 84.1% for site 1 and site 2). The classification scenario regarding the health condition of the black alders of the site 1 performed the best (90.6%).The quality of the classification models developed with a UAS-based, cost-effective, and semi-automatic approach competes successfully with those developed using more expensive imagery, such as multi-spectral and hyperspectral airborne imagery. The high overall accuracy results obtained by the classification of the diseased alders open the door to applications dedicated to monitoring of the health conditions of riparian forest. Our methodological framework will allow UAS users to manage large imagery metric datasets derived from those dense time series.

Generation, Validation, and Application of Abundance Map Reference Data for Spectral Unmixing

NASA Astrophysics Data System (ADS)

Williams, McKay D.

Reference data ("ground truth") maps traditionally have been used to assess the accuracy of imaging spectrometer classification algorithms. However, these reference data can be prohibitively expensive to produce, often do not include sub-pixel abundance estimates necessary to assess spectral unmixing algorithms, and lack published validation reports. Our research proposes methodologies to efficiently generate, validate, and apply abundance map reference data (AMRD) to airborne remote sensing scenes. We generated scene-wide AMRD for three different remote sensing scenes using our remotely sensed reference data (RSRD) technique, which spatially aggregates unmixing results from fine scale imagery (e.g., 1-m Ground Sample Distance (GSD)) to co-located coarse scale imagery (e.g., 10-m GSD or larger). We validated the accuracy of this methodology by estimating AMRD in 51 randomly-selected 10 m x 10 m plots, using seven independent methods and observers, including field surveys by two observers, imagery analysis by two observers, and RSRD using three algorithms. Results indicated statistically-significant differences between all versions of AMRD, suggesting that all forms of reference data need to be validated. Given these significant differences between the independent versions of AMRD, we proposed that the mean of all (MOA) versions of reference data for each plot and class were most likely to represent true abundances. We then compared each version of AMRD to MOA. Best case accuracy was achieved by a version of imagery analysis, which had a mean coverage area error of 2.0%, with a standard deviation of 5.6%. One of the RSRD algorithms was nearly as accurate, achieving a mean error of 3.0%, with a standard deviation of 6.3%, showing the potential of RSRD-based AMRD generation. Application of validated AMRD to specific coarse scale imagery involved three main parts: 1) spatial alignment of coarse and fine scale imagery, 2) aggregation of fine scale abundances to produce coarse scale imagery-specific AMRD, and 3) demonstration of comparisons between coarse scale unmixing abundances and AMRD. Spatial alignment was performed using our scene-wide spectral comparison (SWSC) algorithm, which aligned imagery with accuracy approaching the distance of a single fine scale pixel. We compared simple rectangular aggregation to coarse sensor point spread function (PSF) aggregation, and found that the PSF approach returned lower error, but that rectangular aggregation more accurately estimated true abundances at ground level. We demonstrated various metrics for comparing unmixing results to AMRD, including mean absolute error (MAE) and linear regression (LR). We additionally introduced reference data mean adjusted MAE (MA-MAE), and reference data confidence interval adjusted MAE (CIA-MAE), which account for known error in the reference data itself. MA-MAE analysis indicated that fully constrained linear unmixing of coarse scale imagery across all three scenes returned an error of 10.83% per class and pixel, with regression analysis yielding a slope = 0.85, intercept = 0.04, and R2 = 0.81. Our reference data research has demonstrated a viable methodology to efficiently generate, validate, and apply AMRD to specific examples of airborne remote sensing imagery, thereby enabling direct quantitative assessment of spectral unmixing performance.

Binary Population and Spectral Synthesis Version 2.1: Construction, Observational Verification, and New Results

NASA Astrophysics Data System (ADS)

Eldridge, J. J.; Stanway, E. R.; Xiao, L.; McClelland, L. A. S.; Taylor, G.; Ng, M.; Greis, S. M. L.; Bray, J. C.

2017-11-01

The Binary Population and Spectral Synthesis suite of binary stellar evolution models and synthetic stellar populations provides a framework for the physically motivated analysis of both the integrated light from distant stellar populations and the detailed properties of those nearby. We present a new version 2.1 data release of these models, detailing the methodology by which Binary Population and Spectral Synthesis incorporates binary mass transfer and its effect on stellar evolution pathways, as well as the construction of simple stellar populations. We demonstrate key tests of the latest Binary Population and Spectral Synthesis model suite demonstrating its ability to reproduce the colours and derived properties of resolved stellar populations, including well-constrained eclipsing binaries. We consider observational constraints on the ratio of massive star types and the distribution of stellar remnant masses. We describe the identification of supernova progenitors in our models, and demonstrate a good agreement to the properties of observed progenitors. We also test our models against photometric and spectroscopic observations of unresolved stellar populations, both in the local and distant Universe, finding that binary models provide a self-consistent explanation for observed galaxy properties across a broad redshift range. Finally, we carefully describe the limitations of our models, and areas where we expect to see significant improvement in future versions.

Quantitative methods and detection techniques in hyperspectral imaging involving medical and other applications

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.

Methodology of remote sensing data interpretation and geological applications. [Brazil

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Veneziani, P.; Dosanjos, C. E.

1982-01-01

Elements of photointerpretation discussed include the analysis of photographic texture and structure as well as film tonality. The method used is based on conventional techniques developed for interpreting aerial black and white photographs. By defining the properties which characterize the form and individuality of dual images, homologous zones can be identified. Guy's logic method (1966) was adapted and used on functions of resolution, scale, and spectral characteristics of remotely sensed products. Applications of LANDSAT imagery are discussed for regional geological mapping, mineral exploration, hydrogeology, and geotechnical engineering in Brazil.

Differentiation of aflatoxigenic and non-aflatoxigenic strains of Aspergilli by FT-IR spectroscopy.

PubMed

Atkinson, Curtis; Pechanova, Olga; Sparks, Darrell L; Brown, Ashli; Rodriguez, Jose M

2014-01-01

Fourier transform infrared spectroscopy (FT-IR) is a well-established and widely accepted methodology to identify and differentiate diverse microbial species. In this study, FT-IR was used to differentiate 20 strains of ubiquitous and agronomically important phytopathogens of Aspergillus flavus and Aspergillus parasiticus. By analyzing their spectral profiles via principal component and cluster analysis, differentiation was achieved between the aflatoxin-producing and nonproducing strains of both fungal species. This study thus indicates that FT-IR coupled to multivariate statistics can rapidly differentiate strains of Aspergilli based on their toxigenicity.

Landsat-based trend analysis of lake dynamics across northern permafrost regions

USGS Publications Warehouse

Nitze, Ingmar; Grosse, Guido; Jones, Benjamin M.; Arp, Christopher D.; Ulrich, Mathias; Federov, Alexander; Veremeeva, Alexandra

2017-01-01

Lakes are a ubiquitous landscape feature in northern permafrost regions. They have a strong impact on carbon, energy and water fluxes and can be quite responsive to climate change. The monitoring of lake change in northern high latitudes, at a sufficiently accurate spatial and temporal resolution, is crucial for understanding the underlying processes driving lake change. To date, lake change studies in permafrost regions were based on a variety of different sources, image acquisition periods and single snapshots, and localized analysis, which hinders the comparison of different regions. Here we present, a methodology based on machine-learning based classification of robust trends of multi-spectral indices of Landsat data (TM,ETM+, OLI) and object-based lake detection, to analyze and compare the individual, local and regional lake dynamics of four different study sites (Alaska North Slope, Western Alaska, Central Yakutia, Kolyma Lowland) in the northern permafrost zone from 1999 to 2014. Regional patterns of lake area change on the Alaska North Slope (-0.69%), Western Alaska (-2.82%), and Kolyma Lowland (-0.51%) largely include increases due to thermokarst lake expansion, but more dominant lake area losses due to catastrophic lake drainage events. In contrast, Central Yakutia showed a remarkable increase in lake area of 48.48%, likely resulting from warmer and wetter climate conditions over the latter half of the study period. Within all study regions, variability in lake dynamics was associated with differences in permafrost characteristics, landscape position (i.e. upland vs. lowland), and surface geology. With the global availability of Landsat data and a consistent methodology for processing the input data derived from robust trends of multi-spectral indices, we demonstrate a transferability, scalability and consistency of lake change analysis within the northern permafrost region.

Weld defect identification in friction stir welding using power spectral density

NASA Astrophysics Data System (ADS)

Das, Bipul; Pal, Sukhomay; Bag, Swarup

2018-04-01

Power spectral density estimates are powerful in extraction of useful information retained in signal. In the current research work classical periodogram and Welch periodogram algorithms are used for the estimation of power spectral density for vertical force signal and transverse force signal acquired during friction stir welding process. The estimated spectral densities reveal notable insight in identification of defects in friction stir welded samples. It was observed that higher spectral density against each process signals is a key indication in identifying the presence of possible internal defects in the welded samples. The developed methodology can offer preliminary information regarding presence of internal defects in friction stir welded samples can be best accepted as first level of safeguard in monitoring the friction stir welding process.

Space station integrated wall design and penetration damage control. Task 4: Impact detection/location system

NASA Technical Reports Server (NTRS)

Nelson, J. M.; Lempriere, B. M.

1987-01-01

A program to develop a methodology is documented for detecting and locating meteoroid and debris impacts and penetrations of a wall configuration currently specified for use on space station. Testing consisted of penetrating and non-penetrating hypervelocity impacts on single and dual plate test configurations, including a prototype 1.22 m x 2.44 m x 3.56 mm (4 ft x 8 ft x 0.140 in) aluminum waffle grid backwall with multilayer insulation and a 0.063-in shield. Acoustic data were gathered with transducers and associated data acquisition systems and stored for later analysis with a multichannel digitizer. Preliminary analysis of test data included sensor evaluation, impact repeatability, first waveform arrival, and Fourier spectral analysis.

LANDSAT applications to wetlands classification in the upper Mississippi River Valley. Ph.D. Thesis. Final Report

NASA Technical Reports Server (NTRS)

Lillesand, T. M.; Werth, L. F. (Principal Investigator)

1980-01-01

A 25% improvement in average classification accuracy was realized by processing double-date vs. single-date data. Under the spectrally and spatially complex site conditions characterizing the geographical area used, further improvement in wetland classification accuracy is apparently precluded by the spectral and spatial resolution restrictions of the LANDSAT MSS. Full scene analysis of scanning densitometer data extracted from scale infrared photography failed to permit discrimination of many wetland and nonwetland cover types. When classification of photographic data was limited to wetland areas only, much more detailed and accurate classification could be made. The integration of conventional image interpretation (to simply delineate wetland boundaries) and machine assisted classification (to discriminate among cover types present within the wetland areas) appears to warrant further research to study the feasibility and cost of extending this methodology over a large area using LANDSAT and/or small scale photography.

A long-term study of the impact of solar flares on ionospheric characteristics measured by digisondes and GNSS receivers

NASA Astrophysics Data System (ADS)

Tripathi, Sharad Chandra; Haralambous, Haris; Das, Tanmay

2016-07-01

Solar Flares are highly transient phenomena radiating over a wide spectrum of wavelengths with EUV and X-rays imposing the most significant effect on ionospheric characteristics. This study presents an attempt to examine qualitatively and quantitatively these effects as measured by digisondes and GNSS receivers on a global scale. For this purpose we have divided the whole globe in three sectors (American, African-European and Asian) based on longitude. We have extracted data for ionospheric characteristics by scaling, manually, the ionograms being provided by DIDBase (Digital Ionogram Database) as provided by the Global Ionospheric Radio Observatory (GIRO) during X-class flares for an approximate period of a solar cycle . We have also used TEC data extracted from GPS observations from collocated IGS Stations. Spectral analysis of Solar Flares are added to the methodology to compare the effects in terms of spectral characteristics.

Hyperspectral imaging to investigate the distribution of organic matter and iron down the soil profile

NASA Astrophysics Data System (ADS)

Hobley, Eleanor; Kriegs, Stefanie; Steffens, Markus

2017-04-01

Obtaining reliable and accurate data regarding the spatial distribution of different soil components is difficult due to issues related with sampling scale and resolution on the one hand and laboratory analysis on the other. When investigating the chemical composition of soil, studies frequently limit themselves to two dimensional characterisations, e.g. spatial variability near the surface or depth distribution down the profile, but rarely combine both approaches due to limitations to sampling and analytical capacities. Furthermore, when assessing depth distributions, samples are taken according to horizon or depth increments, resulting in a mixed sample across the sampling depth. Whilst this facilitates mean content estimation per depth increment and therefore reduces analytical costs, the sample information content with regards to heterogeneity within the profile is lost. Hyperspectral imaging can overcome these sampling limitations, yielding high resolution spectral data of down the soil profile, greatly enhancing the information content of the samples. This can then be used to augment horizontal spatial characterisation of a site, yielding three dimensional information into the distribution of spectral characteristics across a site and down the profile. Soil spectral characteristics are associated with specific chemical components of soil, such as soil organic matter or iron contents. By correlating the content of these soil components with their spectral behaviour, high resolution multi-dimensional analysis of soil chemical composition can be obtained. Here we present a hyperspectral approach to the characterisation of soil organic matter and iron down different soil profiles, outlining advantages and issues associated with the methodology.

Performance analysis of improved methodology for incorporation of spatial/spectral variability in synthetic hyperspectral imagery

NASA Astrophysics Data System (ADS)

Scanlan, Neil W.; Schott, John R.; Brown, Scott D.

2004-01-01

Synthetic imagery has traditionally been used to support sensor design by enabling design engineers to pre-evaluate image products during the design and development stages. Increasingly exploitation analysts are looking to synthetic imagery as a way to develop and test exploitation algorithms before image data are available from new sensors. Even when sensors are available, synthetic imagery can significantly aid in algorithm development by providing a wide range of "ground truthed" images with varying illumination, atmospheric, viewing and scene conditions. One limitation of synthetic data is that the background variability is often too bland. It does not exhibit the spatial and spectral variability present in real data. In this work, four fundamentally different texture modeling algorithms will first be implemented as necessary into the Digital Imaging and Remote Sensing Image Generation (DIRSIG) model environment. Two of the models to be tested are variants of a statistical Z-Score selection model, while the remaining two involve a texture synthesis and a spectral end-member fractional abundance map approach, respectively. A detailed comparative performance analysis of each model will then be carried out on several texturally significant regions of the resultant synthetic hyperspectral imagery. The quantitative assessment of each model will utilize a set of three peformance metrics that have been derived from spatial Gray Level Co-Occurrence Matrix (GLCM) analysis, hyperspectral Signal-to-Clutter Ratio (SCR) measures, and a new concept termed the Spectral Co-Occurrence Matrix (SCM) metric which permits the simultaneous measurement of spatial and spectral texture. Previous research efforts on the validation and performance analysis of texture characterization models have been largely qualitative in nature based on conducting visual inspections of synthetic textures in order to judge the degree of similarity to the original sample texture imagery. The quantitative measures used in this study will in combination attempt to determine which texture characterization models best capture the correct statistical and radiometric attributes of the corresponding real image textures in both the spatial and spectral domains. The motivation for this work is to refine our understanding of the complexities of texture phenomena so that an optimal texture characterization model that can accurately account for these complexities can be eventually implemented into a synthetic image generation (SIG) model. Further, conclusions will be drawn regarding which of the candidate texture models are able to achieve realistic levels of spatial and spectral clutter, thereby permitting more effective and robust testing of hyperspectral algorithms in synthetic imagery.

Performance analysis of improved methodology for incorporation of spatial/spectral variability in synthetic hyperspectral imagery

NASA Astrophysics Data System (ADS)

Scanlan, Neil W.; Schott, John R.; Brown, Scott D.

2003-12-01

Synthetic imagery has traditionally been used to support sensor design by enabling design engineers to pre-evaluate image products during the design and development stages. Increasingly exploitation analysts are looking to synthetic imagery as a way to develop and test exploitation algorithms before image data are available from new sensors. Even when sensors are available, synthetic imagery can significantly aid in algorithm development by providing a wide range of "ground truthed" images with varying illumination, atmospheric, viewing and scene conditions. One limitation of synthetic data is that the background variability is often too bland. It does not exhibit the spatial and spectral variability present in real data. In this work, four fundamentally different texture modeling algorithms will first be implemented as necessary into the Digital Imaging and Remote Sensing Image Generation (DIRSIG) model environment. Two of the models to be tested are variants of a statistical Z-Score selection model, while the remaining two involve a texture synthesis and a spectral end-member fractional abundance map approach, respectively. A detailed comparative performance analysis of each model will then be carried out on several texturally significant regions of the resultant synthetic hyperspectral imagery. The quantitative assessment of each model will utilize a set of three peformance metrics that have been derived from spatial Gray Level Co-Occurrence Matrix (GLCM) analysis, hyperspectral Signal-to-Clutter Ratio (SCR) measures, and a new concept termed the Spectral Co-Occurrence Matrix (SCM) metric which permits the simultaneous measurement of spatial and spectral texture. Previous research efforts on the validation and performance analysis of texture characterization models have been largely qualitative in nature based on conducting visual inspections of synthetic textures in order to judge the degree of similarity to the original sample texture imagery. The quantitative measures used in this study will in combination attempt to determine which texture characterization models best capture the correct statistical and radiometric attributes of the corresponding real image textures in both the spatial and spectral domains. The motivation for this work is to refine our understanding of the complexities of texture phenomena so that an optimal texture characterization model that can accurately account for these complexities can be eventually implemented into a synthetic image generation (SIG) model. Further, conclusions will be drawn regarding which of the candidate texture models are able to achieve realistic levels of spatial and spectral clutter, thereby permitting more effective and robust testing of hyperspectral algorithms in synthetic imagery.

Geodiametris: an integrated geoinformatic approach for monitoring land pollution from the disposal of olive oil mill wastes

NASA Astrophysics Data System (ADS)

Alexakis, Dimitrios D.; Sarris, Apostolos; Papadopoulos, Nikos; Soupios, Pantelis; Doula, Maria; Cavvadias, Victor

2014-08-01

The olive-oil industry is one of the most important sectors of agricultural production in Greece, which is the third in olive-oil production country worldwide. Olive oil mill wastes (OOMW) constitute a major factor in pollution in olivegrowing regions and an important problem to be solved for the agricultural industry. The olive-oil mill wastes are normally deposited at tanks, or directly in the soil or even on adjacent torrents, rivers and lakes posing a high risk to the environmental pollution and the community health. GEODIAMETRIS project aspires to develop integrated geoinformatic methodologies for performing monitoring of land pollution from the disposal of OOMW in the island of Crete -Greece. These methodologies integrate GPS surveys, satellite remote sensing and risk assessment analysis in GIS environment, application of in situ and laboratory geophysical methodologies as well as soil and water physicochemical analysis. Concerning project's preliminary results, all the operating OOMW areas located in Crete have been already registered through extensive GPS field campaigns. Their spatial and attribute information has been stored in an integrated GIS database and an overall OOMW spectral signature database has been constructed through the analysis of multi-temporal Landsat-8 OLI satellite images. In addition, a specific OOMW area located in Alikianos village (Chania-Crete) has been selected as one of the main case study areas. Various geophysical methodologies, such as Electrical Resistivity Tomography, Induced Polarization, multifrequency electromagnetic, Self Potential measurements and Ground Penetrating Radar have been already implemented. Soil as well as liquid samples have been collected for performing physico-chemical analysis. The preliminary results have already contributed to the gradual development of an integrated environmental monitoring tool for studying and understanding environmental degradation from the disposal of OOMW.

The EEG Split Alpha Peak: Phenomenological Origins and Methodological Aspects of Detection and Evaluation.

PubMed

Olejarczyk, Elzbieta; Bogucki, Piotr; Sobieszek, Aleksander

2017-01-01

Electroencephalographic (EEG) patterns were analyzed in a group of ambulatory patients who ranged in age and sex using spectral analysis as well as Directed Transfer Function, a method used to evaluate functional brain connectivity. We tested the impact of window size and choice of reference electrode on the identification of two or more peaks with close frequencies in the spectral power distribution, so called "split alpha." Together with the connectivity analysis, examination of spatiotemporal maps showing the distribution of amplitudes of EEG patterns allowed for better explanation of the mechanisms underlying the generation of split alpha peaks. It was demonstrated that the split alpha spectrum can be generated by two or more independent and interconnected alpha wave generators located in different regions of the cerebral cortex, but not necessarily in the occipital cortex. We also demonstrated the importance of appropriate reference electrode choice during signal recording. In addition, results obtained using the original data were compared with results obtained using re-referenced data, using average reference electrode and reference electrode standardization techniques.

Integrating remote sensing and subsurface geological data to characterize a tidally-influenced paleodrainage from the mid-late Holocene succession of the Po Delta Plain (Italy)

NASA Astrophysics Data System (ADS)

Giacomelli, Serena; Rossi, Veronica; Amorosi, Alessandro; Bruno, Luigi; Campo, Bruno; Ciampalini, Andrea; Civa, Andrea; de Souza Filho, Roberto Carlos; Sgavetti, Maria

2017-04-01

A tidally-influenced, mid-late Holocene paleodrainage system from the Po Delta Plain (N Adriatic Sea, Italy) is reconstructed coupling remote sensing (RS) and subsurface geological data. Optical satellite images, DTM LiDAR, soil reflectance spectral features and core stratigraphy were combined in a GIS environment following a fully integrated methodological approach. The stratigraphic significance of RS-derived data (traces) was defined in terms of both depositional facies and depth, furnishing new insights on the role of RS in reconstructing the recent evolution of paleodrainages in coastal-deltaic settings. Sixteen images from Landsat 7 ETM+ (Enhanced Thematic Mapper Plus), Landsat 8 OLI (Operational Land Imager), Sentinel-2 MSI (Multispectral Instruments), and Hyperion satellites were collected from the USGS and the Scientific Hub ESA-Copernicus on-line databases, and integrated with Google Earth imagery. The visual interpretation of the images, mostly based on the brightness contrast (high and low reflectance values) and aimed to the recognition of traces, has been facilitated by the RGB combinations of the spectral bands most sensitive to lithology and moisture content and supported by a semi-automatic processing, including unsupervised classification and the spectral bands Principal Component Analysis (PCA). Multitemporal analysis of satellite imagery have been also performed. Two main traces, interpreted as meanders, have been analyzed for their sedimentological and stratigraphic characteristics. Following a field survey aimed to describe the morphology, grain-size, colors, and accessory materials of surface deposits, 11 soil samples have been collected for the extraction of the reflectance spectral signature and coring along the traces and in adjacent areas (bright and dark portions). Cores have been sampled for benthic foraminifer/ostracod analysis (42 samples) and stratigraphic cross-sections were constructed transversal to the meandering traces. Nine radiocarbon ages allowed to set the depositional evolution of the two meanders into a definite chronological framework. The integrated, RS-stratigraphic methodological approach revealed a meandering paleodrainage system buried > 2 m below the ground level. Its surface visibility is guided by the spatial distribution of surface moisture, which mainly depends on subsurface stratigraphic architecture and, in particular, on the distribution of organic-rich deposits laterally to the migrating meanders. The formation and activity of the buried paleochannels dates back to the early Holocene highstand (6000-2500 cal yr BP), when a drainage system likely developed under tide-influenced conditions.

SPLAT: Using Spectral Indices to Identify and Characterize Ultracool Stars, Brown Dwarfs and Exoplanets in Deep Surveys and as Companions to Nearby Stars

NASA Astrophysics Data System (ADS)

Aganze, Christian; Burgasser, Adam J.; Martin, Eduardo; Konopacky, Quinn; Masters, Daniel C.

2016-06-01

The majority of ultracool dwarf stars and brown dwarfs currently known were identified in wide-field red optical and infrared surveys, enabling measures of the local, typically isolated, population in a relatively shallow (<100 pc radius) volume. Constraining the properties of the wider Galactic population (scale height, radial distribution, Population II sources), and close brown dwarf and exoplanet companions to nearby stars, requires specialized instrumentation, such as high-contrast, coronagraphic spectrometers (e.g., Gemini/GPI, VLT/Sphere, Project 1640); and deep spectral surveys (e.g., HST/WFC3 parallel fields, Euclid). We present a set of quantitative methodologies to identify and robustly characterize sources for these specific populations, based on templates and tools developed as part of the SpeX Prism Library Analysis Toolkit. In particular, we define and characterize specifically-tuned sets spectral indices that optimize selection of cool dwarfs and distinguish rare populations (subdwarfs, young planetary-mass objects) based on low-resolution, limited-wavelength-coverage spectral data; and present a template-matching classification method for these instruments. We apply these techniques to HST/WFC3 parallel fields data in the WISPS and HST-3D programs, where our spectral index set allows high completeness and low contamination for searches of late M, L and T dwarfs to distances out to ~3 kpc.The material presented here is based on work supported by the National Aeronautics and Space Administration under Grant No. NNX15AI75G.

Likelihood ratios for glaucoma diagnosis using spectral-domain optical coherence tomography.

PubMed

Lisboa, Renato; Mansouri, Kaweh; Zangwill, Linda M; Weinreb, Robert N; Medeiros, Felipe A

2013-11-01

To present a methodology for calculating likelihood ratios for glaucoma diagnosis for continuous retinal nerve fiber layer (RNFL) thickness measurements from spectral-domain optical coherence tomography (spectral-domain OCT). Observational cohort study. A total of 262 eyes of 187 patients with glaucoma and 190 eyes of 100 control subjects were included in the study. Subjects were recruited from the Diagnostic Innovations Glaucoma Study. Eyes with preperimetric and perimetric glaucomatous damage were included in the glaucoma group. The control group was composed of healthy eyes with normal visual fields from subjects recruited from the general population. All eyes underwent RNFL imaging with Spectralis spectral-domain OCT. Likelihood ratios for glaucoma diagnosis were estimated for specific global RNFL thickness measurements using a methodology based on estimating the tangents to the receiver operating characteristic (ROC) curve. Likelihood ratios could be determined for continuous values of average RNFL thickness. Average RNFL thickness values lower than 86 μm were associated with positive likelihood ratios (ie, likelihood ratios greater than 1), whereas RNFL thickness values higher than 86 μm were associated with negative likelihood ratios (ie, likelihood ratios smaller than 1). A modified Fagan nomogram was provided to assist calculation of posttest probability of disease from the calculated likelihood ratios and pretest probability of disease. The methodology allowed calculation of likelihood ratios for specific RNFL thickness values. By avoiding arbitrary categorization of test results, it potentially allows for an improved integration of test results into diagnostic clinical decision making. Copyright © 2013. Published by Elsevier Inc.

Mapping plastic greenhouse with medium spatial resolution satellite data: Development of a new spectral index

NASA Astrophysics Data System (ADS)

Yang, Dedi; Chen, Jin; Zhou, Yuan; Chen, Xiang; Chen, Xuehong; Cao, Xin

2017-06-01

Plastic greenhouses (PGs) are an important agriculture development technique to protect and control the growing environment for food crops. The extensive use of PGs can change the agriculture landscape and affects the local environment. Accurately mapping and estimating the coverage of PGs is a necessity to the strategic planning of modern agriculture. Unfortunately, PG mapping over large areas is methodologically challenging, as the medium spatial resolution satellite imagery (such as Landsat data) used for analysis lacks spatial details and spectral variations. To fill the gap, the paper proposes a new plastic greenhouse index (PGI) based on the spectral, sensitivity, and separability analysis of PGs using medium spatial resolution images. In the context of the Landsat Enhanced Thematic Mapper Plus (ETM+) imagery, the paper examines the effectiveness and capability of the proposed PGI. The results indicate that PGs in Landsat ETM+ image can be successfully detected by the PGI if the PG fraction is greater than 12% in a mixed pixel. A kappa coefficient of 0.83 and overall accuracy of 91.2% were achieved when applying the proposed PGI in the case of Weifang District, Shandong, China. These results show that the proposed index can be applied to identifying transparent PGs in atmospheric corrected Landsat image and has the potential for the digital mapping of plastic greenhouse coverage over a large area.

Spectral Analysis of Dynamic PET Studies: A Review of 20 Years of Method Developments and Applications.

PubMed

Veronese, Mattia; Rizzo, Gaia; Bertoldo, Alessandra; Turkheimer, Federico E

2016-01-01

In Positron Emission Tomography (PET), spectral analysis (SA) allows the quantification of dynamic data by relating the radioactivity measured by the scanner in time to the underlying physiological processes of the system under investigation. Among the different approaches for the quantification of PET data, SA is based on the linear solution of the Laplace transform inversion whereas the measured arterial and tissue time-activity curves of a radiotracer are used to calculate the input response function of the tissue. In the recent years SA has been used with a large number of PET tracers in brain and nonbrain applications, demonstrating that it is a very flexible and robust method for PET data analysis. Differently from the most common PET quantification approaches that adopt standard nonlinear estimation of compartmental models or some linear simplifications, SA can be applied without defining any specific model configuration and has demonstrated very good sensitivity to the underlying kinetics. This characteristic makes it useful as an investigative tool especially for the analysis of novel PET tracers. The purpose of this work is to offer an overview of SA, to discuss advantages and limitations of the methodology, and to inform about its applications in the PET field.

Hyperspectral imaging and multivariate analysis in the dried blood spots investigations

NASA Astrophysics Data System (ADS)

Majda, Alicja; Wietecha-Posłuszny, Renata; Mendys, Agata; Wójtowicz, Anna; Łydżba-Kopczyńska, Barbara

2018-04-01

The aim of this study was to apply a new methodology using the combination of the hyperspectral imaging and the dry blood spot (DBS) collecting. Application of the hyperspectral imaging is fast and non-destructive. DBS method offers the advantage also on the micro-invasive blood collecting and low volume of required sample. During experimental step, the reflected light was recorded by two hyperspectral systems. The collection of 776 spectral bands in the VIS-NIR range (400-1000 nm) and 256 spectral bands in the SWIR range (970-2500 nm) was applied. Pixel has the size of 8 × 8 and 30 × 30 µm for VIS-NIR and SWIR camera, respectively. The obtained data in the form of hyperspectral cubes were treated with chemometric methods, i.e., minimum noise fraction and principal component analysis. It has been shown that the application of these methods on this type of data, by analyzing the scatter plots, allows a rapid analysis of the homogeneity of DBS, and the selection of representative areas for further analysis. It also gives the possibility of tracking the dynamics of changes occurring in biological traces applied on the surface. For the analyzed 28 blood samples, described method allowed to distinguish those blood stains because of time of apply.

New robust bilinear least squares method for the analysis of spectral-pH matrix data.

PubMed

Goicoechea, Héctor C; Olivieri, Alejandro C

2005-07-01

A new second-order multivariate method has been developed for the analysis of spectral-pH matrix data, based on a bilinear least-squares (BLLS) model achieving the second-order advantage and handling multiple calibration standards. A simulated Monte Carlo study of synthetic absorbance-pH data allowed comparison of the newly proposed BLLS methodology with constrained parallel factor analysis (PARAFAC) and with the combination multivariate curve resolution-alternating least-squares (MCR-ALS) technique under different conditions of sample-to-sample pH mismatch and analyte-background ratio. The results indicate an improved prediction ability for the new method. Experimental data generated by measuring absorption spectra of several calibration standards of ascorbic acid and samples of orange juice were subjected to second-order calibration analysis with PARAFAC, MCR-ALS, and the new BLLS method. The results indicate that the latter method provides the best analytical results in regard to analyte recovery in samples of complex composition requiring strict adherence to the second-order advantage. Linear dependencies appear when multivariate data are produced by using the pH or a reaction time as one of the data dimensions, posing a challenge to classical multivariate calibration models. The presently discussed algorithm is useful for these latter systems.

Quad-polarized synthetic aperture radar and multispectral data classification using classification and regression tree and support vector machine-based data fusion system

NASA Astrophysics Data System (ADS)

Bigdeli, Behnaz; Pahlavani, Parham

2017-01-01

Interpretation of synthetic aperture radar (SAR) data processing is difficult because the geometry and spectral range of SAR are different from optical imagery. Consequently, SAR imaging can be a complementary data to multispectral (MS) optical remote sensing techniques because it does not depend on solar illumination and weather conditions. This study presents a multisensor fusion of SAR and MS data based on the use of classification and regression tree (CART) and support vector machine (SVM) through a decision fusion system. First, different feature extraction strategies were applied on SAR and MS data to produce more spectral and textural information. To overcome the redundancy and correlation between features, an intrinsic dimension estimation method based on noise-whitened Harsanyi, Farrand, and Chang determines the proper dimension of the features. Then, principal component analysis and independent component analysis were utilized on stacked feature space of two data. Afterward, SVM and CART classified each reduced feature space. Finally, a fusion strategy was utilized to fuse the classification results. To show the effectiveness of the proposed methodology, single classification on each data was compared to the obtained results. A coregistered Radarsat-2 and WorldView-2 data set from San Francisco, USA, was available to examine the effectiveness of the proposed method. The results show that combinations of SAR data with optical sensor based on the proposed methodology improve the classification results for most of the classes. The proposed fusion method provided approximately 93.24% and 95.44% for two different areas of the data.

A unified framework for physical print quality

NASA Astrophysics Data System (ADS)

Eid, Ahmed; Cooper, Brian; Rippetoe, Ed

2007-01-01

In this paper we present a unified framework for physical print quality. This framework includes a design for a testbed, testing methodologies and quality measures of physical print characteristics. An automatic belt-fed flatbed scanning system is calibrated to acquire L* data for a wide range of flat field imagery. Testing methodologies based on wavelet pre-processing and spectral/statistical analysis are designed. We apply the proposed framework to three common printing artifacts: banding, jitter, and streaking. Since these artifacts are directional, wavelet based approaches are used to extract one artifact at a time and filter out other artifacts. Banding is characterized as a medium-to-low frequency, vertical periodic variation down the page. The same definition is applied to the jitter artifact, except that the jitter signal is characterized as a high-frequency signal above the banding frequency range. However, streaking is characterized as a horizontal aperiodic variation in the high-to-medium frequency range. Wavelets at different levels are applied to the input images in different directions to extract each artifact within specified frequency bands. Following wavelet reconstruction, images are converted into 1-D signals describing the artifact under concern. Accurate spectral analysis using a DFT with Blackman-Harris windowing technique is used to extract the power (strength) of periodic signals (banding and jitter). Since streaking is an aperiodic signal, a statistical measure is used to quantify the streaking strength. Experiments on 100 print samples scanned at 600 dpi from 10 different printers show high correlation (75% to 88%) between the ranking of these samples by the proposed metrologies and experts' visual ranking.

Space-time interpolation of satellite winds in the tropics

NASA Astrophysics Data System (ADS)

Patoux, Jérôme; Levy, Gad

2013-09-01

A space-time interpolator for creating average geophysical fields from satellite measurements is presented and tested. It is designed for optimal spatiotemporal averaging of heterogeneous data. While it is illustrated with satellite surface wind measurements in the tropics, the methodology can be useful for interpolating, analyzing, and merging a wide variety of heterogeneous and satellite data in the atmosphere and ocean over the entire globe. The spatial and temporal ranges of the interpolator are determined by averaging satellite and in situ measurements over increasingly larger space and time windows and matching the corresponding variability at each scale. This matching provides a relationship between temporal and spatial ranges, but does not provide a unique pair of ranges as a solution to all averaging problems. The pair of ranges most appropriate for a given application can be determined by performing a spectral analysis of the interpolated fields and choosing the smallest values that remove any or most of the aliasing due to the uneven sampling by the satellite. The methodology is illustrated with the computation of average divergence fields over the equatorial Pacific Ocean from SeaWinds-on-QuikSCAT surface wind measurements, for which 72 h and 510 km are suggested as optimal interpolation windows. It is found that the wind variability is reduced over the cold tongue and enhanced over the Pacific warm pool, consistent with the notion that the unstably stratified boundary layer has generally more variable winds and more gustiness than the stably stratified boundary layer. It is suggested that the spectral analysis optimization can be used for any process where time-space correspondence can be assumed.

Fiber-optic Fourier transform infrared (FO-FTIR) spectroscopy for detecting endotoxin contamination in ophthalmic viscosurgical devices (OVDS) (Conference Presentation)

NASA Astrophysics Data System (ADS)

Hassan, Moinuddin; Ilev, Ilko

2016-03-01

Ophthalmic Viscosurgical Devices (OVDs) in clinical setting are a major health risk factor for potential endotoxin contamination in the eye, due to their extensive applications in cataract surgery for space creation, stabilization and protection of intraocular tissue and intraocular lens (IOL) during implantation. Endotoxin contamination of OVDs is implicated in toxic anterior syndrome (TASS), a severe complication of cataract surgery that leads to intraocular damage and even blindness. Current standard methods for endotoxin contamination detection utilize rabbit assay or Limulus amoebocyte lysate (LAL) assays. These endotoxin detection strategies are extremely difficult for gel-like type devices such as OVDs. To overcome the endotoxin detection limitations in OVDs, we have developed an alternative optical detection methodology for label-free and real-time sensing of bacterial endotoxin in OVDs, based on fiber-optic Fourier transform infrared (FO-FTIR) transmission spectrometry in the mid-IR spectral range from 2.5 micron to 12 micron. Endotoxin contaminated OVD test samples were prepared by serial dilutions of endotoxins on OVDs. The major results of this study revealed two salient spectral peak shifts (in the regions 2925 to 2890 cm^-1 and 1125 to 1100 cm^-1), which are associated with endotoxin in OVDs. In addition, FO-FTIR experimental results processed using a multivariate analysis confirmed the observed specific peak shifts associated with endotoxin contamination in OVDs. Thus, employing the FO-FTIR sensing methodology integrated with a multivariate analysis could potentially be used as an alternative endotoxin detection technique in OVD.

Methodology for fault detection in induction motors via sound and vibration signals

NASA Astrophysics Data System (ADS)

Delgado-Arredondo, Paulo Antonio; Morinigo-Sotelo, Daniel; Osornio-Rios, Roque Alfredo; Avina-Cervantes, Juan Gabriel; Rostro-Gonzalez, Horacio; Romero-Troncoso, Rene de Jesus

2017-01-01

Nowadays, timely maintenance of electric motors is vital to keep up the complex processes of industrial production. There are currently a variety of methodologies for fault diagnosis. Usually, the diagnosis is performed by analyzing current signals at a steady-state motor operation or during a start-up transient. This method is known as motor current signature analysis, which identifies frequencies associated with faults in the frequency domain or by the time-frequency decomposition of the current signals. Fault identification may also be possible by analyzing acoustic sound and vibration signals, which is useful because sometimes this information is the only available. The contribution of this work is a methodology for detecting faults in induction motors in steady-state operation based on the analysis of acoustic sound and vibration signals. This proposed approach uses the Complete Ensemble Empirical Mode Decomposition for decomposing the signal into several intrinsic mode functions. Subsequently, the frequency marginal of the Gabor representation is calculated to obtain the spectral content of the IMF in the frequency domain. This proposal provides good fault detectability results compared to other published works in addition to the identification of more frequencies associated with the faults. The faults diagnosed in this work are two broken rotor bars, mechanical unbalance and bearing defects.

Predicting epileptic seizures from scalp EEG based on attractor state analysis.

PubMed

Chu, Hyunho; Chung, Chun Kee; Jeong, Woorim; Cho, Kwang-Hyun

2017-05-01

Epilepsy is the second most common disease of the brain. Epilepsy makes it difficult for patients to live a normal life because it is difficult to predict when seizures will occur. In this regard, if seizures could be predicted a reasonable period of time before their occurrence, epilepsy patients could take precautions against them and improve their safety and quality of life. In this paper, we investigate a novel seizure precursor based on attractor state analysis for seizure prediction. We analyze the transition process from normal to seizure attractor state and investigate a precursor phenomenon seen before reaching the seizure attractor state. From the result of an analysis, we define a quantified spectral measure in scalp EEG for seizure prediction. From scalp EEG recordings, the Fourier coefficients of six EEG frequency bands are extracted, and the defined spectral measure is computed based on the coefficients for each half-overlapped 20-second-long window. The computed spectral measure is applied to seizure prediction using a low-complexity methodology. Within scalp EEG, we identified an early-warning indicator before an epileptic seizure occurs. Getting closer to the bifurcation point that triggers the transition from normal to seizure state, the power spectral density of low frequency bands of the perturbation of an attractor in the EEG, showed a relative increase. A low-complexity seizure prediction algorithm using this feature was evaluated, using ∼583h of scalp EEG in which 143 seizures in 16 patients were recorded. With the test dataset, the proposed method showed high sensitivity (86.67%) with a false prediction rate of 0.367h -1 and average prediction time of 45.3min. A novel seizure prediction method using scalp EEG, based on attractor state analysis, shows potential for application with real epilepsy patients. This is the first study in which the seizure-precursor phenomenon of an epileptic seizure is investigated based on attractor-based analysis of the macroscopic dynamics of the brain. With the scalp EEG, we first propose use of a spectral feature identified for seizure prediction, in which the dynamics of an attractor are excluded, and only the perturbation dynamics from the attractor are considered. Copyright © 2017 Elsevier B.V. All rights reserved.

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

Espinosa-Paredes, Gilberto; Prieto-Guerrero, Alfonso; Nunez-Carrera, Alejandro

This paper introduces a wavelet-based method to analyze instability events in a boiling water reactor (BWR) during transient phenomena. The methodology to analyze BWR signals includes the following: (a) the short-time Fourier transform (STFT) analysis, (b) decomposition using the continuous wavelet transform (CWT), and (c) application of multiresolution analysis (MRA) using discrete wavelet transform (DWT). STFT analysis permits the study, in time, of the spectral content of analyzed signals. The CWT provides information about ruptures, discontinuities, and fractal behavior. To detect these important features in the signal, a mother wavelet has to be chosen and applied at several scales tomore » obtain optimum results. MRA allows fast implementation of the DWT. Features like important frequencies, discontinuities, and transients can be detected with analysis at different levels of detail coefficients. The STFT was used to provide a comparison between a classic method and the wavelet-based method. The damping ratio, which is an important stability parameter, was calculated as a function of time. The transient behavior can be detected by analyzing the maximum contained in detail coefficients at different levels in the signal decomposition. This method allows analysis of both stationary signals and highly nonstationary signals in the timescale plane. This methodology has been tested with the benchmark power instability event of Laguna Verde nuclear power plant (NPP) Unit 1, which is a BWR-5 NPP.« less

Simultaneous compression and encryption of closely resembling images: application to video sequences and polarimetric images.

PubMed

Aldossari, M; Alfalou, A; Brosseau, C

2014-09-22

This study presents and validates an optimized method of simultaneous compression and encryption designed to process images with close spectra. This approach is well adapted to the compression and encryption of images of a time-varying scene but also to static polarimetric images. We use the recently developed spectral fusion method [Opt. Lett.35, 1914-1916 (2010)] to deal with the close resemblance of the images. The spectral plane (containing the information to send and/or to store) is decomposed in several independent areas which are assigned according a specific way. In addition, each spectrum is shifted in order to minimize their overlap. The dual purpose of these operations is to optimize the spectral plane allowing us to keep the low- and high-frequency information (compression) and to introduce an additional noise for reconstructing the images (encryption). Our results show that not only can the control of the spectral plane enhance the number of spectra to be merged, but also that a compromise between the compression rate and the quality of the reconstructed images can be tuned. We use a root-mean-square (RMS) optimization criterion to treat compression. Image encryption is realized at different security levels. Firstly, we add a specific encryption level which is related to the different areas of the spectral plane, and then, we make use of several random phase keys. An in-depth analysis at the spectral fusion methodology is done in order to find a good trade-off between the compression rate and the quality of the reconstructed images. Our new proposal spectral shift allows us to minimize the image overlap. We further analyze the influence of the spectral shift on the reconstructed image quality and compression rate. The performance of the multiple-image optical compression and encryption method is verified by analyzing several video sequences and polarimetric images.

Compressive Spectral Method for the Simulation of the Nonlinear Gravity Waves

PubMed Central

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

Geospatial analysis of spaceborne remote sensing data for assessing disaster impacts and modeling surface runoff in the built-environment

NASA Astrophysics Data System (ADS)

Wodajo, Bikila Teklu

Every year, coastal disasters such as hurricanes and floods claim hundreds of lives and severely damage homes, businesses, and lifeline infrastructure. This research was motivated by the 2005 Hurricane Katrina disaster, which devastated the Mississippi and Louisiana Gulf Coast. The primary objective was to develop a geospatial decision-support system for extracting built-up surfaces and estimating disaster impacts using spaceborne remote sensing satellite imagery. Pre-Katrina 1-m Ikonos imagery of a 5km x 10km area of Gulfport, Mississippi, was used as source data to develop the built-up area and natural surfaces or BANS classification methodology. Autocorrelation of 0.6 or higher values related to spectral reflectance values of groundtruth pixels were used to select spectral bands and establish the BANS decision criteria of unique ranges of reflectance values. Surface classification results using GeoMedia Pro geospatial analysis for Gulfport sample areas, based on BANS criteria and manually drawn polygons, were within +/-7% of the groundtruth. The difference between the BANS results and the groundtruth was statistically not significant. BANS is a significant improvement over other supervised classification methods, which showed only 50% correctly classified pixels. The storm debris and erosion estimation or SDE methodology was developed from analysis of pre- and post-Katrina surface classification results of Gulfport samples. The SDE severity level criteria considered hurricane and flood damages and vulnerability of inhabited built-environment. A linear regression model, with +0.93 Pearson R-value, was developed for predicting SDE as a function of pre-disaster percent built-up area. SDE predictions for Gulfport sample areas, used for validation, were within +/-4% of calculated values. The damage cost model considered maintenance, rehabilitation and reconstruction costs related to infrastructure damage and community impacts of Hurricane Katrina. The developed models were implemented for a study area along I-10 considering the predominantly flood-induced damages in New Orleans. The BANS methodology was calibrated for 0.6-m QuickBird2 multispectral imagery of Karachi Port area in Pakistan. The results were accurate within +/-6% of the groundtruth. Due to its computational simplicity, the unit hydrograph method is recommended for geospatial visualization of surface runoff in the built-environment using BANS surface classification maps and elevations data. Key words. geospatial analysis, satellite imagery, built-environment, hurricane, disaster impacts, runoff.

Mapping species distribution of Canarian Monteverde forest by field spectroradiometry and satellite imagery

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.

Optical spectral analysis of ultra-weak photon emission from tissue culture and yeast cells

NASA Astrophysics Data System (ADS)

Nerudová, Michaela; Červinková, Kateřina; Hašek, Jiří; Cifra, Michal

2015-01-01

Optical spectral analysis of the ultra-weak photon emission (UPE) could be utilized for non-invasive diagnostic of state of biological systems and for elucidation of underlying mechanisms of UPE generation. Optical spectra of UPE from differentiated HL-60 cells and yeast cells (Saccharomyces cerevisiae) were investigated. Induced photon emission of neutrophil-like cells and spontaneous photon emission of yeast cells were measured using highly sensitive photomultiplier module Hamamatsu H7360-01 in a thermally regulated light-tight chamber. The respiratory burst of neutrophil-like HL-60 cells was induced with the PMA (phorbol 12-myristate, 13-acetate). PMA activates an assembly of NADPH oxidase, which induces a rapid formation of reactive oxygen species (ROS). Long-pass edge filters (wavelength 350, from 400 to 600 with 25 nm resolution and 650 nm) were used for optical spectral analysis. Propagation of error of indirect measurements and standard deviation were used to assess reliability of the measured spectra. Results indicate that the photon emission from both cell cultures is detectable in the six from eight examined wavelength ranges with different percentage distribution of cell suspensions, particularly 450-475, 475-500, 500-525, 525-550, 550-575 and 575-600 nm. The wavelength range of spectra from 450 to 550 nm coincides with the range of photon emission from triplet excited carbonyls (350-550 nm). The both cells cultures emitted photons in wavelength range from 550 to 600 nm but this range does not correspond with any known emitter. To summarize, we have demonstrated a clear difference in the UPE spectra between two organisms using rigorous methodology and error analysis.

Methods and methodology for FTIR spectral correction of channel spectra and uncertainty, applied to ferrocene.

PubMed

Islam, M T; Trevorah, R M; Appadoo, D R T; Best, S P; Chantler, C T

2017-04-15

We present methodology for the first FTIR measurements of ferrocene using dilute wax solutions for dispersion and to preserve non-crystallinity; a new method for removal of channel spectra interference for high quality data; and a consistent approach for the robust estimation of a defined uncertainty for advanced structural χ r 2 analysis and mathematical hypothesis testing. While some of these issues have been investigated previously, the combination of novel approaches gives markedly improved results. Methods for addressing these in the presence of a modest signal and how to quantify the quality of the data irrespective of preprocessing for subsequent hypothesis testing are applied to the FTIR spectra of Ferrocene (Fc) and deuterated ferrocene (dFc, Fc-d 10 ) collected at the THz/Far-IR beam-line of the Australian Synchrotron at operating temperatures of 7K through 353K. Copyright © 2017 Elsevier B.V. All rights reserved.

Methods and methodology for FTIR spectral correction of channel spectra and uncertainty, applied to ferrocene

NASA Astrophysics Data System (ADS)

Islam, M. T.; Trevorah, R. M.; Appadoo, D. R. T.; Best, S. P.; Chantler, C. T.

2017-04-01

We present methodology for the first FTIR measurements of ferrocene using dilute wax solutions for dispersion and to preserve non-crystallinity; a new method for removal of channel spectra interference for high quality data; and a consistent approach for the robust estimation of a defined uncertainty for advanced structural χr2 analysis and mathematical hypothesis testing. While some of these issues have been investigated previously, the combination of novel approaches gives markedly improved results. Methods for addressing these in the presence of a modest signal and how to quantify the quality of the data irrespective of preprocessing for subsequent hypothesis testing are applied to the FTIR spectra of Ferrocene (Fc) and deuterated ferrocene (dFc, Fc-d10) collected at the THz/Far-IR beam-line of the Australian Synchrotron at operating temperatures of 7 K through 353 K.

Precise and rapid isotopomic analysis by (1)H-(13)C 2D NMR: Application to triacylglycerol matrices.

PubMed

Merchak, Noelle; Silvestre, Virginie; Rouger, Laetitia; Giraudeau, Patrick; Rizk, Toufic; Bejjani, Joseph; Akoka, Serge

2016-08-15

An optimized HSQC sequence was tested and applied to triacylglycerol matrices to determine their isotopic and metabolomic profiles. Spectral aliasing and non-uniform sampling approaches were used to decrease the experimental time and to improve the resolution, respectively. An excellent long-term repeatability of signal integrals was achieved enabling to perform isotopic measurements. Thirty-two commercial vegetable oils were analyzed by this methodology. The results show that this method can be used to classify oil samples according to their geographical and botanical origins. Copyright © 2016 Elsevier B.V. All rights reserved.

A new approach to aid the characterisation and identification of metabolites of a model drug; partial isotope enrichment combined with novel formula elucidation software.

PubMed

Hobby, Kirsten; Gallagher, Richard T; Caldwell, Patrick; Wilson, Ian D

2009-01-01

This work describes the identification of 'isotopically enriched' metabolites of 4-cyanoaniline using the unique features of the software package 'Spectral Simplicity'. The software is capable of creating the theoretical mass spectra for partially isotope-enriched compounds, and subsequently performing an elemental composition analysis to give the elemental formula for the 'isotopically enriched' metabolite. A novel mass spectral correlation method, called 'FuzzyFit', was employed. 'FuzzyFit' utilises the expected experimental distribution of errors in both mass accuracy and isotope pattern and enables discrimination between statistically probable and improbable candidate formulae. The software correctly determined the molecular formulae of ten previously described metabolites of 4-cyanoaniline confirming the technique of partial isotope enrichment can produce results analogous to standard methodologies. Six previously unknown species were also identified, based on the presence of the unique 'designer' isotope ratio. Three of the unknowns were tentatively identified as N-acetylglutamine, O-methyl-N acetylglucuronide and a putative fatty acid conjugate. The discovery of a significant number of unknown species of a model drug with a comprehensive history of investigation highlights the potential for enhancement to the analytical process by the use of 'designer' isotope ratio compounds. The 'FuzzyFit' methodology significantly aided the elucidation of candidate formulae, by provision of a vastly simplified candidate formula data set. Copyright (c) 2008 John Wiley & Sons, Ltd.

Spectral reconstruction of phase response curves reveals the synchronization properties of mouse globus pallidus neurons

PubMed Central

Atherton, Jeremy F.; Surmeier, D. James

2013-01-01

The propensity of a neuron to synchronize is captured by its infinitesimal phase response curve (iPRC). Determining whether an iPRC is biphasic, meaning that small depolarizing perturbations can actually delay the next spike, if delivered at appropriate phases, is a daunting experimental task because negative lobes in the iPRC (unlike positive ones) tend to be small and may be occluded by the normal discharge variability of a neuron. To circumvent this problem, iPRCs are commonly derived from numerical models of neurons. Here, we propose a novel and natural method to estimate the iPRC by direct estimation of its spectral modes. First, we show analytically that the spectral modes of the iPRC of an arbitrary oscillator are readily measured by applying weak harmonic perturbations. Next, applying this methodology to biophysical neuronal models, we show that a low-dimensional spectral reconstruction is sufficient to capture the structure of the iPRC. This structure was preserved reasonably well even with added physiological scale jitter in the neuronal models. To validate the methodology empirically, we applied it first to a low-noise electronic oscillator with a known design and then to cortical pyramidal neurons, recorded in whole cell configuration, that are known to possess a monophasic iPRC. Finally, using the methodology in conjunction with perforated-patch recordings from pallidal neurons, we show, in contrast to recent modeling studies, that these neurons have biphasic somatic iPRCs. Biphasic iPRCs would cause lateral somatically targeted pallidal inhibition to desynchronize pallidal neurons, providing a plausible explanation for their lack of synchrony in vivo. PMID:23966679

Field determination of optimal dates for the discrimination of invasive wetland plant species using derivative spectral analysis

USGS Publications Warehouse

Laba, M.; Tsai, F.; Ogurcak, D.; Smith, S.; Richmond, M.E.

2005-01-01

Mapping invasive plant species in aquatic and terrestrial ecosystems helps to understand the causes of their progression, manage some of their negative consequences, and control them. In recent years, a variety of new remote-sensing techniques, like Derivative Spectral Analysis (DSA) of hyperspectral data, have been developed to facilitate this mapping. A number of questions related to these techniques remain to be addressed. This article attempts to answer one of these questions: Is the application of DSA optimal at certain times of the year? Field radiometric data gathered weekly during the summer of 1999 at selected field sites in upstate New York, populated with purple loosestrife (Lythrum salicaria L.), common reed (Phragmites australis (Cav.)) and cattail (Typha L.) are analyzed using DSA to differentiate among plant community types. First, second and higher-order derivatives of the reflectance spectra of nine field plots, varying in plant composition, are calculated and analyzed in detail to identify spectral ranges in which one or more community types have distinguishing features. On the basis of the occurrence and extent of these spectral ranges, experimental observations suggest that a satisfactory differentiation among community types was feasible on 30 August, when plants experienced characteristic phenological changes (transition from flowers to seed heads). Generally, dates in August appear optimal from the point of view of species differentiability and could be selected for image acquisitions. This observation, as well as the methodology adopted in this article, should provide a firm basis for the acquisition of hyperspectral imagery and for mapping the targeted species over a broad range of spatial scales. ?? 2005 American Society for Photogrammetry and Remote Sensing.

De Novo Peptide Sequencing: Deep Mining of High-Resolution Mass Spectrometry Data.

PubMed

Islam, Mohammad Tawhidul; Mohamedali, Abidali; Fernandes, Criselda Santan; Baker, Mark S; Ranganathan, Shoba

2017-01-01

High resolution mass spectrometry has revolutionized proteomics over the past decade, resulting in tremendous amounts of data in the form of mass spectra, being generated in a relatively short span of time. The mining of this spectral data for analysis and interpretation though has lagged behind such that potentially valuable data is being overlooked because it does not fit into the mold of traditional database searching methodologies. Although the analysis of spectra by de novo sequences removes such biases and has been available for a long period of time, its uptake has been slow or almost nonexistent within the scientific community. In this chapter, we propose a methodology to integrate de novo peptide sequencing using three commonly available software solutions in tandem, complemented by homology searching, and manual validation of spectra. This simplified method would allow greater use of de novo sequencing approaches and potentially greatly increase proteome coverage leading to the unearthing of valuable insights into protein biology, especially of organisms whose genomes have been recently sequenced or are poorly annotated.

Liquid crystal-based Mueller matrix spectral imaging polarimetry for parameterizing mineral structural organization.

PubMed

Gladish, James C; Duncan, Donald D

2017-01-20

Herein, we discuss the remote assessment of the subwavelength organizational structure of a medium. Specifically, we use spectral imaging polarimetry, as the vector nature of polarized light enables it to interact with optical anisotropies within a medium, while the spectral aspect of polarization is sensitive to small-scale structure. The ability to image these effects allows for inference of spatial structural organization parameters. This work describes a methodology for revealing structural organization by exploiting the Stokes/Mueller formalism and by utilizing measurements from a spectral imaging polarimeter constructed from liquid crystal variable retarders and a liquid crystal tunable filter. We provide results to validate the system and then show results from measurements on a mineral sample.

Spectral radiation analyses of the GOES solar illuminated hexagonal cell scan mirror back

NASA Technical Reports Server (NTRS)

Fantano, Louis G.

1993-01-01

A ray tracing analytical tool has been developed for the simulation of spectral radiation exchange in complex systems. Algorithms are used to account for heat source spectral energy, surface directional radiation properties, and surface spectral absorptivity properties. This tool has been used to calculate the effective solar absorptivity of the geostationary operational environmental satellites (GOES) scan mirror in the calibration position. The development and design of Sounder and Imager instruments on board GOES is reviewed and the problem of calculating the effective solar absorptivity associated with the GOES hexagonal cell configuration is presented. The analytical methodology based on the Monte Carlo ray tracing technique is described and results are presented and verified by experimental measurements for selected solar incidence angles.

Bayesian wavelet PCA methodology for turbomachinery damage diagnosis under uncertainty

NASA Astrophysics Data System (ADS)

Xu, Shengli; Jiang, Xiaomo; Huang, Jinzhi; Yang, Shuhua; Wang, Xiaofang

2016-12-01

Centrifugal compressor often suffers various defects such as impeller cracking, resulting in forced outage of the total plant. Damage diagnostics and condition monitoring of such a turbomachinery system has become an increasingly important and powerful tool to prevent potential failure in components and reduce unplanned forced outage and further maintenance costs, while improving reliability, availability and maintainability of a turbomachinery system. This paper presents a probabilistic signal processing methodology for damage diagnostics using multiple time history data collected from different locations of a turbomachine, considering data uncertainty and multivariate correlation. The proposed methodology is based on the integration of three advanced state-of-the-art data mining techniques: discrete wavelet packet transform, Bayesian hypothesis testing, and probabilistic principal component analysis. The multiresolution wavelet analysis approach is employed to decompose a time series signal into different levels of wavelet coefficients. These coefficients represent multiple time-frequency resolutions of a signal. Bayesian hypothesis testing is then applied to each level of wavelet coefficient to remove possible imperfections. The ratio of posterior odds Bayesian approach provides a direct means to assess whether there is imperfection in the decomposed coefficients, thus avoiding over-denoising. Power spectral density estimated by the Welch method is utilized to evaluate the effectiveness of Bayesian wavelet cleansing method. Furthermore, the probabilistic principal component analysis approach is developed to reduce dimensionality of multiple time series and to address multivariate correlation and data uncertainty for damage diagnostics. The proposed methodology and generalized framework is demonstrated with a set of sensor data collected from a real-world centrifugal compressor with impeller cracks, through both time series and contour analyses of vibration signal and principal components.

Raman spectroscopy of normal oral buccal mucosa tissues: study on intact and incised biopsies

NASA Astrophysics Data System (ADS)

Deshmukh, Atul; Singh, S. P.; Chaturvedi, Pankaj; Krishna, C. Murali

2011-12-01

Oral squamous cell carcinoma is one of among the top 10 malignancies. Optical spectroscopy, including Raman, is being actively pursued as alternative/adjunct for cancer diagnosis. Earlier studies have demonstrated the feasibility of classifying normal, premalignant, and malignant oral ex vivo tissues. Spectral features showed predominance of lipids and proteins in normal and cancer conditions, respectively, which were attributed to membrane lipids and surface proteins. In view of recent developments in deep tissue Raman spectroscopy, we have recorded Raman spectra from superior and inferior surfaces of 10 normal oral tissues on intact, as well as incised, biopsies after separation of epithelium from connective tissue. Spectral variations and similarities among different groups were explored by unsupervised (principal component analysis) and supervised (linear discriminant analysis, factorial discriminant analysis) methodologies. Clusters of spectra from superior and inferior surfaces of intact tissues show a high overlap; whereas spectra from separated epithelium and connective tissue sections yielded clear clusters, though they also overlap on clusters of intact tissues. Spectra of all four groups of normal tissues gave exclusive clusters when tested against malignant spectra. Thus, this study demonstrates that spectra recorded from the superior surface of an intact tissue may have contributions from deeper layers but has no bearing from the classification of a malignant tissues point of view.

Network representations of angular regions for electromagnetic scattering

PubMed Central

2017-01-01

Network modeling in electromagnetics is an effective technique in treating scattering problems by canonical and complex structures. Geometries constituted of angular regions (wedges) together with planar layers can now be approached with the Generalized Wiener-Hopf Technique supported by network representation in spectral domain. Even if the network representations in spectral planes are of great importance by themselves, the aim of this paper is to present a theoretical base and a general procedure for the formulation of complex scattering problems using network representation for the Generalized Wiener Hopf Technique starting basically from the wave equation. In particular while the spectral network representations are relatively well known for planar layers, the network modelling for an angular region requires a new theory that will be developed in this paper. With this theory we complete the formulation of a network methodology whose effectiveness is demonstrated by the application to a complex scattering problem with practical solutions given in terms of GTD/UTD diffraction coefficients and total far fields for engineering applications. The methodology can be applied to other physics fields. PMID:28817573

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.

Attenuation analysis of real GPR wavelets: The equivalent amplitude spectrum (EAS)

NASA Astrophysics Data System (ADS)

Economou, Nikos; Kritikakis, George

2016-03-01

Absorption of a Ground Penetrating Radar (GPR) pulse is a frequency dependent attenuation mechanism which causes a spectral shift on the dominant frequency of GPR data. Both energy variation of GPR amplitude spectrum and spectral shift were used for the estimation of Quality Factor (Q*) and subsequently the characterization of the subsurface material properties. The variation of the amplitude spectrum energy has been studied by Spectral Ratio (SR) method and the frequency shift by the estimation of the Frequency Centroid Shift (FCS) or the Frequency Peak Shift (FPS) methods. The FPS method is more automatic, less robust. This work aims to increase the robustness of the FPS method by fitting a part of the amplitude spectrum of GPR data with Ricker, Gaussian, Sigmoid-Gaussian or Ricker-Gaussian functions. These functions fit different parts of the spectrum of a GPR reference wavelet and the Equivalent Amplitude Spectrum (EAS) is selected, reproducing Q* values used in forward Q* modeling analysis. Then, only the peak frequencies and the time differences between the reference wavelet and the subsequent reflected wavelets are used to estimate Q*. As long as the EAS is estimated, it is used for Q* evaluation in all the GPR section, under the assumption that the selected reference wavelet is representative. De-phasing and constant phase shift, for obtaining symmetrical wavelets, proved useful in the sufficiency of the horizons picking. Synthetic, experimental and real GPR data were examined in order to demonstrate the effectiveness of the proposed methodology.

Resolution Measurement from a Single Reconstructed Cryo-EM Density Map with Multiscale Spectral Analysis.

PubMed

Yang, Yu-Jiao; Wang, Shuai; Zhang, Biao; Shen, Hong-Bin

2018-06-25

As a relatively new technology to solve the three-dimensional (3D) structure of a protein or protein complex, single-particle reconstruction (SPR) of cryogenic electron microscopy (cryo-EM) images shows much superiority and is in a rapidly developing stage. Resolution measurement in SPR, which evaluates the quality of a reconstructed 3D density map, plays a critical role in promoting methodology development of SPR and structural biology. Because there is no benchmark map in the generation of a new structure, how to realize the resolution estimation of a new map is still an open problem. Existing approaches try to generate a hypothetical benchmark map by reconstructing two 3D models from two halves of the original 2D images for cross-reference, which may result in a premature estimation with a half-data model. In this paper, we report a new self-reference-based resolution estimation protocol, called SRes, that requires only a single reconstructed 3D map. The core idea of SRes is to perform a multiscale spectral analysis (MSSA) on the map through multiple size-variable masks segmenting the map. The MSSA-derived multiscale spectral signal-to-noise ratios (mSSNRs) reveal that their corresponding estimated resolutions will show a cliff jump phenomenon, indicating a significant change in the SSNR properties. The critical point on the cliff borderline is demonstrated to be the right estimator for the resolution of the map.

Development of Noninvasive Classification Methods for Different Roasting Degrees of Coffee Beans Using Hyperspectral Imaging

PubMed Central

Chu, Bingquan; Yu, Keqiang; Zhao, Yanru

2018-01-01

This study aimed to develop an approach for quickly and noninvasively differentiating the roasting degrees of coffee beans using hyperspectral imaging (HSI). The qualitative properties of seven roasting degrees of coffee beans (unroasted, light, moderately light, light medium, medium, moderately dark, and dark) were assayed, including moisture, crude fat, trigonelline, chlorogenic acid, and caffeine contents. These properties were influenced greatly by the respective roasting degree. Their hyperspectral images (874–1734 nm) were collected using a hyperspectral reflectance imaging system. The spectra of the regions of interest were manually extracted from the HSI images. Then, principal components analysis was employed to compress the spectral data and select the optimal wavelengths based on loading weight analysis. Meanwhile, the random frog (RF) methodology and the successive projections algorithm were also adopted to pick effective wavelengths from the spectral data. Finally, least squares support vector machine (LS-SVM) was utilized to establish discriminative models using spectral reflectance and corresponding labeled classes for each degree of roast sample. The results showed that the LS-SVM model, established by the RF selecting method, with eight wavelengths performed very well, achieving an overall classification accuracy of 90.30%. In conclusion, HSI was illustrated as a potential technique for noninvasively classifying the roasting degrees of coffee beans and might have an important application for the development of nondestructive, real-time, and portable sensors to monitor the roasting process of coffee beans. PMID:29671781

Development of Noninvasive Classification Methods for Different Roasting Degrees of Coffee Beans Using Hyperspectral Imaging.

PubMed

Chu, Bingquan; Yu, Keqiang; Zhao, Yanru; He, Yong

2018-04-19

This study aimed to develop an approach for quickly and noninvasively differentiating the roasting degrees of coffee beans using hyperspectral imaging (HSI). The qualitative properties of seven roasting degrees of coffee beans (unroasted, light, moderately light, light medium, medium, moderately dark, and dark) were assayed, including moisture, crude fat, trigonelline, chlorogenic acid, and caffeine contents. These properties were influenced greatly by the respective roasting degree. Their hyperspectral images (874⁻1734 nm) were collected using a hyperspectral reflectance imaging system. The spectra of the regions of interest were manually extracted from the HSI images. Then, principal components analysis was employed to compress the spectral data and select the optimal wavelengths based on loading weight analysis. Meanwhile, the random frog (RF) methodology and the successive projections algorithm were also adopted to pick effective wavelengths from the spectral data. Finally, least squares support vector machine (LS-SVM) was utilized to establish discriminative models using spectral reflectance and corresponding labeled classes for each degree of roast sample. The results showed that the LS-SVM model, established by the RF selecting method, with eight wavelengths performed very well, achieving an overall classification accuracy of 90.30%. In conclusion, HSI was illustrated as a potential technique for noninvasively classifying the roasting degrees of coffee beans and might have an important application for the development of nondestructive, real-time, and portable sensors to monitor the roasting process of coffee beans.

Multisensor satellite data for water quality analysis and water pollution risk assessment: decision making under deep uncertainty with fuzzy algorithm in framework of multimodel approach

NASA Astrophysics Data System (ADS)

Kostyuchenko, Yuriy V.; Sztoyka, Yulia; Kopachevsky, Ivan; Artemenko, Igor; Yuschenko, Maxim

2017-10-01

Multi-model approach for remote sensing data processing and interpretation is described. The problem of satellite data utilization in multi-modeling approach for socio-ecological risks assessment is formally defined. Observation, measurement and modeling data utilization method in the framework of multi-model approach is described. Methodology and models of risk assessment in framework of decision support approach are defined and described. Method of water quality assessment using satellite observation data is described. Method is based on analysis of spectral reflectance of aquifers. Spectral signatures of freshwater bodies and offshores are analyzed. Correlations between spectral reflectance, pollutions and selected water quality parameters are analyzed and quantified. Data of MODIS, MISR, AIRS and Landsat sensors received in 2002-2014 have been utilized verified by in-field spectrometry and lab measurements. Fuzzy logic based approach for decision support in field of water quality degradation risk is discussed. Decision on water quality category is making based on fuzzy algorithm using limited set of uncertain parameters. Data from satellite observations, field measurements and modeling is utilizing in the framework of the approach proposed. It is shown that this algorithm allows estimate water quality degradation rate and pollution risks. Problems of construction of spatial and temporal distribution of calculated parameters, as well as a problem of data regularization are discussed. Using proposed approach, maps of surface water pollution risk from point and diffuse sources are calculated and discussed.

Evaluation of a Change Detection Methodology by Means of Binary Thresholding Algorithms and Informational Fusion Processes

PubMed Central

Molina, Iñigo; Martinez, Estibaliz; Arquero, Agueda; Pajares, Gonzalo; Sanchez, Javier

2012-01-01

Landcover is subject to continuous changes on a wide variety of temporal and spatial scales. Those changes produce significant effects in human and natural activities. Maintaining an updated spatial database with the occurred changes allows a better monitoring of the Earth’s resources and management of the environment. Change detection (CD) techniques using images from different sensors, such as satellite imagery, aerial photographs, etc., have proven to be suitable and secure data sources from which updated information can be extracted efficiently, so that changes can also be inventoried and monitored. In this paper, a multisource CD methodology for multiresolution datasets is applied. First, different change indices are processed, then different thresholding algorithms for change/no_change are applied to these indices in order to better estimate the statistical parameters of these categories, finally the indices are integrated into a change detection multisource fusion process, which allows generating a single CD result from several combination of indices. This methodology has been applied to datasets with different spectral and spatial resolution properties. Then, the obtained results are evaluated by means of a quality control analysis, as well as with complementary graphical representations. The suggested methodology has also been proved efficiently for identifying the change detection index with the higher contribution. PMID:22737023

Evaluation of a change detection methodology by means of binary thresholding algorithms and informational fusion processes.

PubMed

Molina, Iñigo; Martinez, Estibaliz; Arquero, Agueda; Pajares, Gonzalo; Sanchez, Javier

2012-01-01

Landcover is subject to continuous changes on a wide variety of temporal and spatial scales. Those changes produce significant effects in human and natural activities. Maintaining an updated spatial database with the occurred changes allows a better monitoring of the Earth's resources and management of the environment. Change detection (CD) techniques using images from different sensors, such as satellite imagery, aerial photographs, etc., have proven to be suitable and secure data sources from which updated information can be extracted efficiently, so that changes can also be inventoried and monitored. In this paper, a multisource CD methodology for multiresolution datasets is applied. First, different change indices are processed, then different thresholding algorithms for change/no_change are applied to these indices in order to better estimate the statistical parameters of these categories, finally the indices are integrated into a change detection multisource fusion process, which allows generating a single CD result from several combination of indices. This methodology has been applied to datasets with different spectral and spatial resolution properties. Then, the obtained results are evaluated by means of a quality control analysis, as well as with complementary graphical representations. The suggested methodology has also been proved efficiently for identifying the change detection index with the higher contribution.

Determination of real-time predictors of the wind turbine wake meandering

NASA Astrophysics Data System (ADS)

Muller, Yann-Aël; Aubrun, Sandrine; Masson, Christian

2015-03-01

The present work proposes an experimental methodology to characterize the unsteady properties of a wind turbine wake, called meandering, and particularly its ability to follow the large-scale motions induced by large turbulent eddies contained in the approach flow. The measurements were made in an atmospheric boundary layer wind tunnel. The wind turbine model is based on the actuator disc concept. One part of the work has been dedicated to the development of a methodology for horizontal wake tracking by mean of a transverse hot wire rake, whose dynamic response is adequate for spectral analysis. Spectral coherence analysis shows that the horizontal position of the wake correlates well with the upstream transverse velocity, especially for wavelength larger than three times the diameter of the disc but less so for smaller scales. Therefore, it is concluded that the wake is actually a rather passive tracer of the large surrounding turbulent structures. The influence of the rotor size and downstream distance on the wake meandering is studied. The fluctuations of the lateral force and the yawing torque affecting the wind turbine model are also measured and correlated with the wake meandering. Two approach flow configurations are then tested: an undisturbed incoming flow (modelled atmospheric boundary layer) and a disturbed incoming flow, with a wind turbine model located upstream. Results showed that the meandering process is amplified by the presence of the upstream wake. It is shown that the coherence between the lateral force fluctuations and the horizontal wake position is significant up to length scales larger than twice the wind turbine model diameter. This leads to the conclusion that the lateral force is a better candidate than the upstream transverse velocity to predict in real time the meandering process, for either undisturbed (wake free) or disturbed incoming atmospheric flows.

Proceedings of the Airborne Imaging Spectrometer Data Analysis Workshop

NASA Technical Reports Server (NTRS)

Vane, G. (Editor); Goetz, A. F. H. (Editor)

1985-01-01

The Airborne Imaging Spectrometer (AIS) Data Analysis Workshop was held at the Jet Propulsion Laboratory on April 8 to 10, 1985. It was attended by 92 people who heard reports on 30 investigations currently under way using AIS data that have been collected over the past two years. Written summaries of 27 of the presentations are in these Proceedings. Many of the results presented at the Workshop are preliminary because most investigators have been working with this fundamentally new type of data for only a relatively short time. Nevertheless, several conclusions can be drawn from the Workshop presentations concerning the value of imaging spectrometry to Earth remote sensing. First, work with AIS has shown that direct identification of minerals through high spectral resolution imaging is a reality for a wide range of materials and geological settings. Second, there are strong indications that high spectral resolution remote sensing will enhance the ability to map vegetation species. There are also good indications that imaging spectrometry will be useful for biochemical studies of vegetation. Finally, there are a number of new data analysis techniques under development which should lead to more efficient and complete information extraction from imaging spectrometer data. The results of the Workshop indicate that as experience is gained with this new class of data, and as new analysis methodologies are developed and applied, the value of imaging spectrometry should increase.

The First FERMI-LAT Gamma-Ray Burst Catalog

NASA Technical Reports Server (NTRS)

Ackermann, M.; Ajello, M.; Asano, K.; Axelsson, M.; Baldini, L.; Ballet, J.; Barbiellini, G.; Bastieri, D.; Bechtol, K.; Bellazzini, R.;

The first Fermi-LAT Gamma-Ray burst catalog

DOE PAGES

Ackermann, M.; Ajello, M.; Asano, K.; ...

2013-10-23

In three years of observations since the beginning of nominal science operations in 2008 August, the Large Area Telescope (LAT) on board the Fermi Gamma-Ray Space Telescope has observed high-energy (gsim 20 MeV) γ-ray emission from 35 gamma-ray bursts (GRBs). Among these, 28 GRBs have been detected above 100 MeV and 7 GRBs above ~20 MeV. The first Fermi-LAT catalog of GRBs is a compilation of these detections and provides a systematic study of high-energy emission from GRBs for the first time. To generate the catalog, we examined 733 GRBs detected by the Gamma-Ray Burst Monitor (GBM) on Fermi andmore » processed each of them using the same analysis sequence. Details of the methodology followed by the LAT collaboration for the GRB analysis are provided. Here, we summarize the temporal and spectral properties of the LAT-detected GRBs. We also discuss characteristics of LAT-detected emission such as its delayed onset and longer duration compared with emission detected by the GBM, its power-law temporal decay at late times, and the fact that it is dominated by a power-law spectral component that appears in addition to the usual Band model.« less

The effects of AVIRIS atmospheric calibration methodology on identification and quantitative mapping of surface mineralogy, Drum Mountains, Utah

NASA Technical Reports Server (NTRS)

Kruse, Fred A.; Dwyer, John L.

1993-01-01

The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) measures reflected light in 224 contiguous spectra bands in the 0.4 to 2.45 micron region of the electromagnetic spectrum. Numerous studies have used these data for mineralogic identification and mapping based on the presence of diagnostic spectral features. Quantitative mapping requires conversion of the AVIRIS data to physical units (usually reflectance) so that analysis results can be compared and validated with field and laboratory measurements. This study evaluated two different AVIRIS calibration techniques to ground reflectance: an empirically-based method and an atmospheric model based method to determine their effects on quantitative scientific analyses. Expert system analysis and linear spectral unmixing were applied to both calibrated data sets to determine the effect of the calibration on the mineral identification and quantitative mapping results. Comparison of the image-map results and image reflectance spectra indicate that the model-based calibrated data can be used with automated mapping techniques to produce accurate maps showing the spatial distribution and abundance of surface mineralogy. This has positive implications for future operational mapping using AVIRIS or similar imaging spectrometer data sets without requiring a priori knowledge.

Effects of different analysis techniques and recording duty cycles on passive acoustic monitoring of killer whales.

PubMed

Riera, Amalis; Ford, John K; Ross Chapman, N

2013-09-01

Killer whales in British Columbia are at risk, and little is known about their winter distribution. Passive acoustic monitoring of their year-round habitat is a valuable supplemental method to traditional visual and photographic surveys. However, long-term acoustic studies of odontocetes have some limitations, including the generation of large amounts of data that require highly time-consuming processing. There is a need to develop tools and protocols to maximize the efficiency of such studies. Here, two types of analysis, real-time and long term spectral averages, were compared to assess their performance at detecting killer whale calls in long-term acoustic recordings. In addition, two different duty cycles, 1/3 and 2/3, were tested. Both the use of long term spectral averages and a lower duty cycle resulted in a decrease in call detection and positive pod identification, leading to underestimations of the amount of time the whales were present. The impact of these limitations should be considered in future killer whale acoustic surveys. A compromise between a lower resolution data processing method and a higher duty cycle is suggested for maximum methodological efficiency.

Optimisation and evaluation of hyperspectral imaging system using machine learning algorithm

NASA Astrophysics Data System (ADS)

Suthar, Gajendra; Huang, Jung Y.; Chidangil, Santhosh

2017-10-01

Hyperspectral imaging (HSI), also called imaging spectrometer, originated from remote sensing. Hyperspectral imaging is an emerging imaging modality for medical applications, especially in disease diagnosis and image-guided surgery. HSI acquires a three-dimensional dataset called hypercube, with two spatial dimensions and one spectral dimension. Spatially resolved spectral imaging obtained by HSI provides diagnostic information about the objects physiology, morphology, and composition. The present work involves testing and evaluating the performance of the hyperspectral imaging system. The methodology involved manually taking reflectance of the object in many images or scan of the object. The object used for the evaluation of the system was cabbage and tomato. The data is further converted to the required format and the analysis is done using machine learning algorithm. The machine learning algorithms applied were able to distinguish between the object present in the hypercube obtain by the scan. It was concluded from the results that system was working as expected. This was observed by the different spectra obtained by using the machine-learning algorithm.

Mapping alteration minerals at prospect, outcrop and drill core scales using imaging spectrometry

PubMed Central

Kruse, Fred A.; L. Bedell, Richard; Taranik, James V.; Peppin, William A.; Weatherbee, Oliver; Calvin, Wendy M.

2011-01-01

Imaging spectrometer data (also known as ‘hyperspectral imagery’ or HSI) are well established for detailed mineral mapping from airborne and satellite systems. Overhead data, however, have substantial additional potential when used together with ground-based measurements. An imaging spectrometer system was used to acquire airborne measurements and to image in-place outcrops (mine walls) and boxed drill core and rock chips using modified sensor-mounting configurations. Data were acquired at 5 nm nominal spectral resolution in 360 channels from 0.4 to 2.45 μm. Analysis results using standardized hyperspectral methodologies demonstrate rapid extraction of representative mineral spectra and mapping of mineral distributions and abundances in map-plan, with core depth, and on the mine walls. The examples shown highlight the capabilities of these data for mineral mapping. Integration of these approaches promotes improved understanding of relations between geology, alteration and spectral signatures in three dimensions and should lead to improved efficiency of mine development, operations and ultimately effective mine closure. PMID:25937681

Spectral filtering for plant production

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

Young, R.E.; McMahon, M.J.; Rajapakse, N.C.

1994-12-31

Research to date suggests that spectral filtering can be an effective alternative to chemical growth regulators for altering plant development. If properly implemented, it can be nonchemical and environmentally friendly. The aqueous CuSO{sub 4}, and CuCl{sub 2} solutions in channelled plastic panels have been shown to be effective filters, but they can be highly toxic if the solutions contact plants. Some studies suggest that spectral filtration limited to short EOD intervals can also alter plant development. Future research should be directed toward confirmation of the influence of spectral filters and exposure times on a broader range of plant species andmore » cultivars. Efforts should also be made to identify non-noxious alternatives to aqueous copper solutions and/or to incorporate these chemicals permanently into plastic films and panels that can be used in greenhouse construction. It would also be informative to study the impacts of spectral filters on insect and microbal populations in plant growth facilities. The economic impacts of spectral filtering techniques should be assessed for each delivery methodology.« less

Spectral Dynamics Inc., ships hybrid, 316-channel data acquisition system to Sandia Labs.

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

Schwartz, Douglas

2003-09-01

Spectral Dynamics announced the shipment of a 316-channel data acquisition system. The system was custom designed for the Light Initiated High Explosive (LIHE) facility at Sandia Labs in Albuquerque, New Mexico by Spectral Dynamics Advanced Research Products Group. This Spectral Dynamics data acquisition system was tailored to meet the unique LIHE environmental and testing requirements utilizing Spectral Dynamics commercial off the shelf (COTS) Jaguar and VIDAS products supplemented by SD Alliance partner's (COTS) products. 'This system is just the beginning of our cutting edge merged technology solutions,' stated Mark Remelman, Manager for the Spectral Dynamics Advanced Research Products Group. 'Thismore » Hybrid system has 316-channels of data acquisition capability, comprised of 102.4kHz direct to disk acquisition and 2.5MHz, 200Mhz & 500Mhz RAM based capabilities. In addition it incorporates the advanced bridge conditioning and dynamic configuration capabilities offered by Spectral Dynamics new Smart Interface Panel System (SIPS{trademark}).' After acceptance testing, Tony King, the Instrumentation Engineer facilitating the project for the Sandia LIHE group commented; 'The LIHE staff was very impressed with the design, construction, attention to detail and overall performance of the instrumentation system'. This system combines VIDAS, a leading edge fourth generation SD-VXI hardware and field-proven software system from SD's Advanced Research Products Group with SD's Jaguar, a multiple Acquisition Control Peripheral (ACP) system that allows expansion to hundreds of channels without sacrificing signal processing performance. Jaguar incorporates dedicated throughput disks for each ACP providing time streaming to disk at up to the maximum sample rate. Spectral Dynamics, Inc. is a leading worldwide supplier of systems and software for advanced computer-automated data acquisition, vibration testing, structural dynamics, explosive shock, high-speed transient capture, acoustic analysis, monitoring, measurement, control and backup. Spectral Dynamics products are used for research, design verification, product testing and process improvement by manufacturers of all types of electrical, electronic and mechanical products, as well as by universities and government-funded agencies. The Advanced Research Products Group is the newest addition to the Spectral Dynamics family. Their newest VXI data acquisition hardware pushes the envelope on capabilities and embodies the same rock solid design methodologies, which have always differentiated Spectral Dynamics from its competition.« less

Remote Sensing Data Fusion to Detect Illicit Crops and Unauthorized Airstrips

NASA Astrophysics Data System (ADS)

Pena, J. A.; Yumin, T.; Liu, H.; Zhao, B.; Garcia, J. A.; Pinto, J.

2018-04-01

Remote sensing data fusion has been playing a more and more important role in crop planting area monitoring, especially for crop area information acquisition. Multi-temporal data and multi-spectral time series are two major aspects for improving crop identification accuracy. Remote sensing fusion provides high quality multi-spectral and panchromatic images in terms of spectral and spatial information, respectively. In this paper, we take one step further and prove the application of remote sensing data fusion in detecting illicit crop through LSMM, GOBIA, and MCE analyzing of strategic information. This methodology emerges as a complementary and effective strategy to control and eradicate illicit crops.

Clinical evaluation of melanomas and common nevi by spectral imaging

PubMed Central

Diebele, Ilze; Kuzmina, Ilona; Lihachev, Alexey; Kapostinsh, Janis; Derjabo, Alexander; Valeine, Lauma; Spigulis, Janis

2012-01-01

A clinical trial on multi-spectral imaging of malignant and non-malignant skin pathologies comprising 17 melanomas and 65 pigmented common nevi was performed. Optical density data of skin pathologies were obtained in the spectral range 450–950 nm using the multispectral camera Nuance EX. An image parameter and maps capable of distinguishing melanoma from pigmented nevi were proposed. The diagnostic criterion is based on skin optical density differences at three fixed wavelengths: 540nm, 650nm and 950nm. The sensitivity and specificity of this method were estimated to be 94% and 89%, respectively. The proposed methodology and potential clinical applications are discussed. PMID:22435095

RUSHMAPS: Real-Time Uploadable Spherical Harmonic Moment Analysis for Particle Spectrometers

NASA Technical Reports Server (NTRS)

Figueroa-Vinas, Adolfo

2013-01-01

RUSHMAPS is a new onboard data reduction scheme that gives real-time access to key science parameters (e.g. moments) of a class of heliophysics science and/or solar system exploration investigation that includes plasma particle spectrometers (PPS), but requires moments reporting (density, bulk-velocity, temperature, pressure, etc.) of higher-level quality, and tolerates a lowpass (variable quality) spectral representation of the corresponding particle velocity distributions, such that telemetry use is minimized. The proposed methodology trades access to the full-resolution velocity distribution data, saving on telemetry, for real-time access to both the moments and an adjustable-quality (increasing quality increases volume) spectral representation of distribution functions. Traditional onboard data storage and downlink bandwidth constraints severely limit PPS system functionality and drive cost, which, as a consequence, drives a limited data collection and lower angular energy and time resolution. This prototypical system exploit, using high-performance processing technology at GSFC (Goddard Space Flight Center), uses a SpaceCube and/or Maestro-type platform for processing. These processing platforms are currently being used on the International Space Station as a technology demonstration, and work is currently ongoing in a new onboard computation system for the Earth Science missions, but they have never been implemented in heliospheric science or solar system exploration missions. Preliminary analysis confirms that the targeted processor platforms possess the processing resources required for realtime application of these algorithms to the spectrometer data. SpaceCube platforms demonstrate that the target architecture possesses the sort of compact, low-mass/power, radiation-tolerant characteristics needed for flight. These high-performing hybrid systems embed unprecedented amounts of onboard processing power in the CPU (central processing unit), FPGAs (field programmable gate arrays), and DSP (digital signal processing) elements. The fundamental computational algorithm de constructs 3D velocity distributions in terms of spherical harmonic spectral coefficients (which are analogous to a Fourier sine-cosine decomposition), but uses instead spherical harmonics Legendre polynomial orthogonal functions as a basis for the expansion, portraying each 2D angular distribution at every energy or, geometrically, spherical speed-shell swept by the particle spectrometer. Optionally, these spherical harmonic spectral coefficients may be telemetered to the ground. These will provide a smoothed description of the velocity distribution function whose quality will depend on the number of coefficients determined. Successfully implemented on the GSFC-developed processor, the capability to integrate the proposed methodology with both heritage and anticipated future plasma particle spectrometer designs is demonstrated (with sufficiently detailed design analysis to advance TRL) to show specific science relevancy with future HSD (Heliophysics Science Division) solar-interplanetary, planetary missions, sounding rockets and/or CubeSat missions.

Quantification of rare earth elements using laser-induced breakdown spectroscopy

DOE PAGES

Martin, Madhavi; Martin, Rodger C.; Allman, Steve; ...

2015-10-21

In this paper, a study of the optical emission as a function of concentration of laser-ablated yttrium (Y) and of six rare earth elements, europium (Eu), gadolinium (Gd), lanthanum (La), praseodymium (Pr), neodymium (Nd), and samarium (Sm), has been evaluated using the laser-induced breakdown spectroscopy (LIBS) technique. Statistical methodology using multivariate analysis has been used to obtain the sampling errors, coefficient of regression, calibration, and cross-validation of measurements as they relate to the LIBS analysis in graphite-matrix pellets that were doped with elements at several concentrations. Each element (in oxide form) was mixed in the graphite matrix in percentages rangingmore » from 1% to 50% by weight and the LIBS spectra obtained for each composition as well as for pure oxide samples. Finally, a single pellet was mixed with all the elements in equal oxide masses to determine if we can identify the elemental peaks in a mixed pellet. This dataset is relevant for future application to studies of fission product content and distribution in irradiated nuclear fuels. These results demonstrate that LIBS technique is inherently well suited for the future challenge of in situ analysis of nuclear materials. Finally, these studies also show that LIBS spectral analysis using statistical methodology can provide quantitative results and suggest an approach in future to the far more challenging multielemental analysis of ~ 20 primary elements in high-burnup nuclear reactor fuel.« less

Lattice Boltzmann methods for global linear instability analysis

NASA Astrophysics Data System (ADS)

Pérez, José Miguel; Aguilar, Alfonso; Theofilis, Vassilis

2017-12-01

Modal global linear instability analysis is performed using, for the first time ever, the lattice Boltzmann method (LBM) to analyze incompressible flows with two and three inhomogeneous spatial directions. Four linearization models have been implemented in order to recover the linearized Navier-Stokes equations in the incompressible limit. Two of those models employ the single relaxation time and have been proposed previously in the literature as linearization of the collision operator of the lattice Boltzmann equation. Two additional models are derived herein for the first time by linearizing the local equilibrium probability distribution function. Instability analysis results are obtained in three benchmark problems, two in closed geometries and one in open flow, namely the square and cubic lid-driven cavity flow and flow in the wake of the circular cylinder. Comparisons with results delivered by classic spectral element methods verify the accuracy of the proposed new methodologies and point potential limitations particular to the LBM approach. The known issue of appearance of numerical instabilities when the SRT model is used in direct numerical simulations employing the LBM is shown to be reflected in a spurious global eigenmode when the SRT model is used in the instability analysis. Although this mode is absent in the multiple relaxation times model, other spurious instabilities can also arise and are documented herein. Areas of potential improvements in order to make the proposed methodology competitive with established approaches for global instability analysis are discussed.

Probabilistic seismic vulnerability and risk assessment of stone masonry structures

NASA Astrophysics Data System (ADS)

Abo El Ezz, Ahmad

Earthquakes represent major natural hazards that regularly impact the built environment in seismic prone areas worldwide and cause considerable social and economic losses. The high losses incurred following the past destructive earthquakes promoted the need for assessment of the seismic vulnerability and risk of the existing buildings. Many historic buildings in the old urban centers in Eastern Canada such as Old Quebec City are built of stone masonry and represent un-measurable architectural and cultural heritage. These buildings were built to resist gravity loads only and generally offer poor resistance to lateral seismic loads. Seismic vulnerability assessment of stone masonry buildings is therefore the first necessary step in developing seismic retrofitting and pre-disaster mitigation plans. The objective of this study is to develop a set of probability-based analytical tools for efficient seismic vulnerability and uncertainty analysis of stone masonry buildings. A simplified probabilistic analytical methodology for vulnerability modelling of stone masonry building with systematic treatment of uncertainties throughout the modelling process is developed in the first part of this study. Building capacity curves are developed using a simplified mechanical model. A displacement based procedure is used to develop damage state fragility functions in terms of spectral displacement response based on drift thresholds of stone masonry walls. A simplified probabilistic seismic demand analysis is proposed to capture the combined uncertainty in capacity and demand on fragility functions. In the second part, a robust analytical procedure for the development of seismic hazard compatible fragility and vulnerability functions is proposed. The results are given by sets of seismic hazard compatible vulnerability functions in terms of structure-independent intensity measure (e.g. spectral acceleration) that can be used for seismic risk analysis. The procedure is very efficient for conducting rapid vulnerability assessment of stone masonry buildings. With modification of input structural parameters, it can be adapted and applied to any other building class. A sensitivity analysis of the seismic vulnerability modelling is conducted to quantify the uncertainties associated with each of the input parameters. The proposed methodology was validated for a scenario-based seismic risk assessment of existing buildings in Old Quebec City. The procedure for hazard compatible vulnerability modelling was used to develop seismic fragility functions in terms of spectral acceleration representative of the inventoried buildings. A total of 1220 buildings were considered. The assessment was performed for a scenario event of magnitude 6.2 at distance 15km with a probability of exceedance of 2% in 50 years. The study showed that most of the expected damage is concentrated in the old brick and stone masonry buildings.

Fourier Transform Infrared Spectroscopy (FTIR) and Multivariate Analysis for Identification of Different Vegetable Oils Used in Biodiesel Production

PubMed Central

Mueller, Daniela; Ferrão, Marco Flôres; Marder, Luciano; da Costa, Adilson Ben; de Cássia de Souza Schneider, Rosana

2013-01-01

The main objective of this study was to use infrared spectroscopy to identify vegetable oils used as raw material for biodiesel production and apply multivariate analysis to the data. Six different vegetable oil sources—canola, cotton, corn, palm, sunflower and soybeans—were used to produce biodiesel batches. The spectra were acquired by Fourier transform infrared spectroscopy using a universal attenuated total reflectance sensor (FTIR-UATR). For the multivariate analysis principal component analysis (PCA), hierarchical cluster analysis (HCA), interval principal component analysis (iPCA) and soft independent modeling of class analogy (SIMCA) were used. The results indicate that is possible to develop a methodology to identify vegetable oils used as raw material in the production of biodiesel by FTIR-UATR applying multivariate analysis. It was also observed that the iPCA found the best spectral range for separation of biodiesel batches using FTIR-UATR data, and with this result, the SIMCA method classified 100% of the soybean biodiesel samples. PMID:23539030

New methodology for adjusting rotating shadowband irradiometer measurements

NASA Astrophysics Data System (ADS)

Vignola, Frank; Peterson, Josh; Wilbert, Stefan; Blanc, Philippe; Geuder, Norbert; Kern, Chris

2017-06-01

A new method is developed for correcting systematic errors found in rotating shadowband irradiometer measurements. Since the responsivity of photodiode-based pyranometers typically utilized for RST sensors is dependent upon the wavelength of the incident radiation and the spectral distribution of the incident radiation is different for the Direct Normal Trradiance and the Diffuse Horizontal Trradiance, spectral effects have to be considered. These cause the most problematic errors when applying currently available correction functions to RST measurements. Hence, direct normal and diffuse contributions are analyzed and modeled separately. An additional advantage of this methodology is that it provides a prescription for how to modify the adjustment algorithms to locations with different atmospheric characteristics from the location where the calibration and adjustment algorithms were developed. A summary of results and areas for future efforts are then discussed.

Estimating the hydraulic parameters of a confined aquifer based on the response of groundwater levels to seismic Rayleigh waves

NASA Astrophysics Data System (ADS)

Sun, Xiaolong; Xiang, Yang; Shi, Zheming

2018-05-01

Groundwater flow models implemented to manage regional water resources require aquifer hydraulic parameters. Traditional methods for obtaining these parameters include laboratory experiments, field tests and model inversions, and each are potentially hindered by their unique limitations. Here, we propose a methodology for estimating hydraulic conductivity and storage coefficients using the spectral characteristics of the coseismic groundwater-level oscillations and seismic Rayleigh waves. The results from Well X10 are consistent with the variations and spectral characteristics of the water-level oscillations and seismic waves and present an estimated hydraulic conductivity of approximately 1 × 10-3 m s-1 and storativity of 15 × 10-6. The proposed methodology for estimating hydraulic parameters in confined aquifers is a practical and novel approach for groundwater management and seismic precursor anomaly analyses.

Screening photoswitching properties of synthesized BODIPY-based fluorophores for multispectral superresolution microscopy (MSSRM) (Conference Presentation)

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.

HMM for hyperspectral spectrum representation and classification with endmember entropy vectors

NASA Astrophysics Data System (ADS)

Arabi, Samir Y. W.; Fernandes, David; Pizarro, Marco A.

2015-10-01

The Hyperspectral images due to its good spectral resolution are extensively used for classification, but its high number of bands requires a higher bandwidth in the transmission data, a higher data storage capability and a higher computational capability in processing systems. This work presents a new methodology for hyperspectral data classification that can work with a reduced number of spectral bands and achieve good results, comparable with processing methods that require all hyperspectral bands. The proposed method for hyperspectral spectra classification is based on the Hidden Markov Model (HMM) associated to each Endmember (EM) of a scene and the conditional probabilities of each EM belongs to each other EM. The EM conditional probability is transformed in EM vector entropy and those vectors are used as reference vectors for the classes in the scene. The conditional probability of a spectrum that will be classified is also transformed in a spectrum entropy vector, which is classified in a given class by the minimum ED (Euclidian Distance) among it and the EM entropy vectors. The methodology was tested with good results using AVIRIS spectra of a scene with 13 EM considering the full 209 bands and the reduced spectral bands of 128, 64 and 32. For the test area its show that can be used only 32 spectral bands instead of the original 209 bands, without significant loss in the classification process.

Fluorescence imaging spectroscopy (FIS) for comparing spectra from corn ears naturally and artificially infected with aflatoxin producing fungus.

PubMed

Hruska, Zuzana; Yao, Haibo; Kincaid, Russell; Darlington, Dawn; Brown, Robert L; Bhatnagar, Deepak; Cleveland, Thomas E

2013-08-01

In an effort to address the problem of rapid detection of aflatoxin in grain, particularly oilseeds, the current study assessed the spectral differences of aflatoxin production in kernels from a cornfield inoculated with spores from 2 different strains of toxigenic Aspergillus flavus. Aflatoxin production in corn from the same field due to natural infestation was also assessed. A small corn plot in Baton Rouge, La., U.S.A., was used during the 2008-growing season. Two groups of 400 plants were inoculated with 2 different inocula and 1 group of 400 plants was designated as controls. Any contamination detected in the controls was attributed to natural infestation. A subset of each group was imaged with a visible near infra red (VNIR) hyperspectral system under ultra violet (UV) excitation and subsequently analyzed for aflatoxin using affinity column fluorometry. Group differences were statistically analyzed. Results indicate that when all the spectral data across all groups were averaged, any potential differences between groups (treated and untreated) were obscured. However, spectral analysis based on contaminated "hot" pixel classification showed a distinct spectral shift/separation between contaminated and clean ears with fluorescence peaks at 501 and 478 nm, respectively. All inoculated and naturally infected control ears had fluorescence peaks at 501 nm that differed from uninfected corn ears. Results from this study may be useful in evaluating rapid, noninvasive instrumentation and/or methodology for aflatoxin detection in grain. © 2013 Institute of Food Technologists®

Quantifying mineral abundances of complex mixtures by coupling spectral deconvolution of SWIR spectra (2.1-2.4 μm) and regression tree analysis

USGS Publications Warehouse

Mulder, V.L.; Plotze, Michael; de Bruin, Sytze; Schaepman, Michael E.; Mavris, C.; Kokaly, Raymond F.; Egli, Markus

2013-01-01

This paper presents a methodology for assessing mineral abundances of mixtures having more than two constituents using absorption features in the 2.1-2.4 μm wavelength region. In the first step, the absorption behaviour of mineral mixtures is parameterised by exponential Gaussian optimisation. Next, mineral abundances are predicted by regression tree analysis using these parameters as inputs. The approach is demonstrated on a range of prepared samples with known abundances of kaolinite, dioctahedral mica, smectite, calcite and quartz and on a set of field samples from Morocco. The latter contained varying quantities of other minerals, some of which did not have diagnostic absorption features in the 2.1-2.4 μm region. Cross validation showed that the prepared samples of kaolinite, dioctahedral mica, smectite and calcite were predicted with a root mean square error (RMSE) less than 9 wt.%. For the field samples, the RMSE was less than 8 wt.% for calcite, dioctahedral mica and kaolinite abundances. Smectite could not be well predicted, which was attributed to spectral variation of the cations within the dioctahedral layered smectites. Substitution of part of the quartz by chlorite at the prediction phase hardly affected the accuracy of the predicted mineral content; this suggests that the method is robust in handling the omission of minerals during the training phase. The degree of expression of absorption components was different between the field sample and the laboratory mixtures. This demonstrates that the method should be calibrated and trained on local samples. Our method allows the simultaneous quantification of more than two minerals within a complex mixture and thereby enhances the perspectives of spectral analysis for mineral abundances.

Cloud Retrieval Information Content Studies with the Pre-Aerosol, Cloud and ocean Ecosystem (PACE) Ocean Color Imager (OCI)

NASA Astrophysics Data System (ADS)

Coddington, Odele; Platnick, Steven; Pilewskie, Peter; Schmidt, Sebastian

2016-04-01

The NASA Pre-Aerosol, Cloud and ocean Ecosystem (PACE) Science Definition Team (SDT) report released in 2012 defined imager stability requirements for the Ocean Color Instrument (OCI) at the sub-percent level. While the instrument suite and measurement requirements are currently being determined, the PACE SDT report provided details on imager options and spectral specifications. The options for a threshold instrument included a hyperspectral imager from 350-800 nm, two near-infrared (NIR) channels, and three short wave infrared (SWIR) channels at 1240, 1640, and 2130 nm. Other instrument options include a variation of the threshold instrument with 3 additional spectral channels at 940, 1378, and 2250 nm and the inclusion of a spectral polarimeter. In this work, we present cloud retrieval information content studies of optical thickness, droplet effective radius, and thermodynamic phase to quantify the potential for continuing the low cloud climate data record established by the MOderate Resolution and Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) missions with the PACE OCI instrument (i.e., non-polarized cloud reflectances and in the absence of midwave and longwave infrared channels). The information content analysis is performed using the GEneralized Nonlinear Retrieval Analysis (GENRA) methodology and the Collection 6 simulated cloud reflectance data for the common MODIS/VIIRS algorithm (MODAWG) for Cloud Mask, Cloud-Top, and Optical Properties. We show that using both channels near 2 microns improves the probability of cloud phase discrimination with shortwave-only cloud reflectance retrievals. Ongoing work will extend the information content analysis, currently performed for dark ocean surfaces, to different land surface types.

Spatial Prediction of Soil Classes by Using Soil Weathering Parameters Derived from vis-NIR Spectroscopy

NASA Astrophysics Data System (ADS)

Ramirez-Lopez, Leonardo; Alexandre Dematte, Jose

2010-05-01

There is consensus in the scientific community about the great need of spatial soil information. Conventional mapping methods are time consuming and involve high costs. Digital soil mapping has emerged as an area in which the soil mapping is optimized by the application of mathematical and statistical approaches, as well as the application of expert knowledge in pedology. In this sense, the objective of the study was to develop a methodology for the spatial prediction of soil classes by using soil spectroscopy methodologies related with fieldwork, spectral data from satellite image and terrain attributes in simultaneous. The studied area is located in São Paulo State, and comprised an area of 473 ha, which was covered by a regular grid (100 x 100 m). In each grid node was collected soil samples at two depths (layers A and B). There were extracted 206 samples from transect sections and submitted to soil analysis (clay, Al2O3, Fe2O3, SiO2 TiO2, and weathering index). The first analog soil class map (ASC-N) contains only soil information regarding from orders to subgroups of the USDA Soil Taxonomy System. The second (ASC-H) map contains some additional information related to some soil attributes like color, ferric levels and base sum. For the elaboration of the digital soil maps the data was divided into three groups: i) Predicted soil attributes of the layer B (related to the soil weathering) which were obtained by using a local soil spectral library; ii) Spectral bands data extracted from a Landsat image; and iii) Terrain parameters. This information was summarized by a principal component analysis (PCA) in each group. Digital soil maps were generated by supervised classification using a maximum likelihood method. The trainee information for this classification was extracted from five toposequences based on the analog soil class maps. The spectral models of weathering soil attributes shown a high predictive performance with low error (R2 0.71 to 0.90). The spatial prediction of these attributes also showed a high performance (validations with R2> 0.78). These models allowed to increase spatial resolution of soil weathering information. On the other hand, the comparison between the analog and digital soil maps showed a global accuracy of 69% for the ASC-N map and 62% in the ASC-H map, with kappa indices of 0.52 and 0.45 respectively.

Ultrasensitive low noise voltage amplifier for spectral analysis.

PubMed

Giusi, G; Crupi, F; Pace, C

2008-08-01

Recently we have proposed several voltage noise measurement methods that allow, at least in principle, the complete elimination of the noise introduced by the measurement amplifier. The most severe drawback of these methods is that they require a multistep measurement procedure. Since environmental conditions may change in the different measurement steps, the final result could be affected by these changes. This problem is solved by the one-step voltage noise measurement methodology based on a novel amplifier topology proposed in this paper. Circuit implementations for the amplifier building blocks based on operational amplifiers are critically discussed. The proposed approach is validated through measurements performed on a prototype circuit.

Fluorescence Spectroscopy for the Monitoring of Food Processes.

PubMed

Ahmad, Muhammad Haseeb; Sahar, Amna; Hitzmann, Bernd

Different analytical techniques have been used to examine the complexity of food samples. Among them, fluorescence spectroscopy cannot be ignored in developing rapid and non-invasive analytical methodologies. It is one of the most sensitive spectroscopic approaches employed in identification, classification, authentication, quantification, and optimization of different parameters during food handling, processing, and storage and uses different chemometric tools. Chemometrics helps to retrieve useful information from spectral data utilized in the characterization of food samples. This contribution discusses in detail the potential of fluorescence spectroscopy of different foods, such as dairy, meat, fish, eggs, edible oil, cereals, fruit, vegetables, etc., for qualitative and quantitative analysis with different chemometric approaches.

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

NASA Astrophysics Data System (ADS)

Paul, Subir; Nagesh Kumar, D.

2018-04-01

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

Comparison of hearing and voicing ranges in singing

NASA Astrophysics Data System (ADS)

Hunter, Eric J.; Titze, Ingo R.

2003-04-01

The spectral and dynamic ranges of the human voice of professional and nonprofessional vocalists were compared to the auditory hearing and feeling thresholds at a distance of one meter. In order to compare these, an analysis was done in true dB SPL, not just relative dB as is usually done in speech analysis. The methodology of converting the recorded acoustic signal to absolute pressure units was described. The human voice range of a professional vocalist appeared to match the dynamic range of the auditory system at some frequencies. In particular, it was demonstrated that professional vocalists were able to make use of the most sensitive part of the hearing thresholds (around 4 kHz) through the use of a learned vocal ring or singer's formant. [Work sponsored by NIDCD.

Quenching or Bursting: Star Formation Acceleration—A New Methodology for Tracing Galaxy Evolution

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

Martin, D. Christopher; Darvish, Behnam; Seibert, Mark

We introduce a new methodology for the direct extraction of galaxy physical parameters from multiwavelength photometry and spectroscopy. We use semianalytic models that describe galaxy evolution in the context of large-scale cosmological simulation to provide a catalog of galaxies, star formation histories, and physical parameters. We then apply models of stellar population synthesis and a simple extinction model to calculate the observable broadband fluxes and spectral indices for these galaxies. We use a linear regression analysis to relate physical parameters to observed colors and spectral indices. The result is a set of coefficients that can be used to translate observedmore » colors and indices into stellar mass, star formation rate, and many other parameters, including the instantaneous time derivative of the star formation rate, which we denote the Star Formation Acceleration (SFA), We apply the method to a test sample of galaxies with GALEX photometry and SDSS spectroscopy, deriving relationships between stellar mass, specific star formation rate, and SFA. We find evidence for a mass-dependent SFA in the green valley, with low-mass galaxies showing greater quenching and higher-mass galaxies greater bursting. We also find evidence for an increase in average quenching in galaxies hosting an active galactic nucleus. A simple scenario in which lower-mass galaxies accrete and become satellite galaxies, having their star-forming gas tidally and/or ram-pressure stripped, while higher-mass galaxies receive this gas and react with new star formation, can qualitatively explain our results.« less

Quenching or Bursting: Star Formation Acceleration—A New Methodology for Tracing Galaxy Evolution

NASA Astrophysics Data System (ADS)

Martin, D. Christopher; Gonçalves, Thiago S.; Darvish, Behnam; Seibert, Mark; Schiminovich, David

2017-06-01

We introduce a new methodology for the direct extraction of galaxy physical parameters from multiwavelength photometry and spectroscopy. We use semianalytic models that describe galaxy evolution in the context of large-scale cosmological simulation to provide a catalog of galaxies, star formation histories, and physical parameters. We then apply models of stellar population synthesis and a simple extinction model to calculate the observable broadband fluxes and spectral indices for these galaxies. We use a linear regression analysis to relate physical parameters to observed colors and spectral indices. The result is a set of coefficients that can be used to translate observed colors and indices into stellar mass, star formation rate, and many other parameters, including the instantaneous time derivative of the star formation rate, which we denote the Star Formation Acceleration (SFA), We apply the method to a test sample of galaxies with GALEX photometry and SDSS spectroscopy, deriving relationships between stellar mass, specific star formation rate, and SFA. We find evidence for a mass-dependent SFA in the green valley, with low-mass galaxies showing greater quenching and higher-mass galaxies greater bursting. We also find evidence for an increase in average quenching in galaxies hosting an active galactic nucleus. A simple scenario in which lower-mass galaxies accrete and become satellite galaxies, having their star-forming gas tidally and/or ram-pressure stripped, while higher-mass galaxies receive this gas and react with new star formation, can qualitatively explain our results.

Physics Notes.

ERIC Educational Resources Information Center

School Science Review, 1982

1982-01-01

Outlines methodology, demonstrations, and materials including: an inexpensive wave machine; speed of sound in carbon dioxide; diffraction grating method for measuring spectral line wavelength; linear electronic thermometer; analogy for bromine diffusion; direct reading refractice index meter; inexpensive integrated circuit spectrophotometer; and…

Cellular neural network-based hybrid approach toward automatic image registration

NASA Astrophysics Data System (ADS)

Arun, Pattathal VijayaKumar; Katiyar, Sunil Kumar

2013-01-01

Image registration is a key component of various image processing operations that involve the analysis of different image data sets. Automatic image registration domains have witnessed the application of many intelligent methodologies over the past decade; however, inability to properly model object shape as well as contextual information has limited the attainable accuracy. A framework for accurate feature shape modeling and adaptive resampling using advanced techniques such as vector machines, cellular neural network (CNN), scale invariant feature transform (SIFT), coreset, and cellular automata is proposed. CNN has been found to be effective in improving feature matching as well as resampling stages of registration and complexity of the approach has been considerably reduced using coreset optimization. The salient features of this work are cellular neural network approach-based SIFT feature point optimization, adaptive resampling, and intelligent object modelling. Developed methodology has been compared with contemporary methods using different statistical measures. Investigations over various satellite images revealed that considerable success was achieved with the approach. This system has dynamically used spectral and spatial information for representing contextual knowledge using CNN-prolog approach. This methodology is also illustrated to be effective in providing intelligent interpretation and adaptive resampling.

Uncertainty propagation by using spectral methods: A practical application to a two-dimensional turbulence fluid model

NASA Astrophysics Data System (ADS)

Riva, Fabio; Milanese, Lucio; Ricci, Paolo

2017-10-01

To reduce the computational cost of the uncertainty propagation analysis, which is used to study the impact of input parameter variations on the results of a simulation, a general and simple to apply methodology based on decomposing the solution to the model equations in terms of Chebyshev polynomials is discussed. This methodology, based on the work by Scheffel [Am. J. Comput. Math. 2, 173-193 (2012)], approximates the model equation solution with a semi-analytic expression that depends explicitly on time, spatial coordinates, and input parameters. By employing a weighted residual method, a set of nonlinear algebraic equations for the coefficients appearing in the Chebyshev decomposition is then obtained. The methodology is applied to a two-dimensional Braginskii model used to simulate plasma turbulence in basic plasma physics experiments and in the scrape-off layer of tokamaks, in order to study the impact on the simulation results of the input parameter that describes the parallel losses. The uncertainty that characterizes the time-averaged density gradient lengths, time-averaged densities, and fluctuation density level are evaluated. A reasonable estimate of the uncertainty of these distributions can be obtained with a single reduced-cost simulation.

Uncertainties in shoreline position analysis: the role of run-up and tide in a gentle slope beach

NASA Astrophysics Data System (ADS)

Manno, Giorgio; Lo Re, Carlo; Ciraolo, Giuseppe

2017-09-01

In recent decades in the Mediterranean Sea, high anthropic pressure from increasing economic and touristic development has affected several coastal areas. Today the erosion phenomena threaten human activities and existing structures, and interdisciplinary studies are needed to better understand actual coastal dynamics. Beach evolution analysis can be conducted using GIS methodologies, such as the well-known Digital Shoreline Analysis System (DSAS), in which error assessment based on shoreline positioning plays a significant role. In this study, a new approach is proposed to estimate the positioning errors due to tide and wave run-up influence. To improve the assessment of the wave run-up uncertainty, a spectral numerical model was used to propagate waves from deep to intermediate water and a Boussinesq-type model for intermediate water up to the swash zone. Tide effects on the uncertainty of shoreline position were evaluated using data collected by a nearby tide gauge. The proposed methodology was applied to an unprotected, dissipative Sicilian beach far from harbors and subjected to intense human activities over the last 20 years. The results show wave run-up and tide errors ranging from 0.12 to 4.5 m and from 1.20 to 1.39 m, respectively.

Remote sensing of methane emissions by combining optical similitude absorption spectroscopy (OSAS) and lidar

NASA Astrophysics Data System (ADS)

Galtier, Sandrine; Anselmo, Christophe; Welschinger, Jean-Yves; Cariou, Jean-Pierre; Sivignon, Jean-François; Miffre, Alain; Rairoux, Patrick

2018-04-01

Monitoring the emission of gases is difficult to achieve in industrial sites and in environments presenting poor infrastructures. Hence, robust methodologies should be developed and coupled to Lidar technology to allow remote sensing of gas emission. OSAS is a new methodology to evaluate gas concentration emission from spectrally integrated differential absorption measurements. Proof of concept of OSAS-Lidar for CH4 emission monitoring is here presented.

Quality monitoring of extra-virgin olive oil using an optical sensor

NASA Astrophysics Data System (ADS)

Mignani, A. G.; Ciaccheri, L.; Mencaglia, A. A.; Paolesse, R.; Di Natale, C.; Del Nobile, A.; Benedetto, A.; Mentana, A.

2006-04-01

An optical sensor for the detection of olive oil aroma is presented. It is capable of distinguishing different ageing levels of extra-virgin olive oils, and shows effective potential for achieving a non destructive olfactory perception of oil ageing. The sensor is an optical scanner, fitted with an array of metalloporphyrin-based sensors. The scanner provides exposure of the sensors to the flow of the oil vapor being tested, and their sequential spectral interrogation. Spectral data are then processed using chemometric methodologies.

Spectral mapping tools from the earth sciences applied to spectral microscopy data.

PubMed

Harris, A Thomas

2006-08-01

Spectral imaging, originating from the field of earth remote sensing, is a powerful tool that is being increasingly used in a wide variety of applications for material identification. Several workers have used techniques like linear spectral unmixing (LSU) to discriminate materials in images derived from spectral microscopy. However, many spectral analysis algorithms rely on assumptions that are often violated in microscopy applications. This study explores algorithms originally developed as improvements on early earth imaging techniques that can be easily translated for use with spectral microscopy. To best demonstrate the application of earth remote sensing spectral analysis tools to spectral microscopy data, earth imaging software was used to analyze data acquired with a Leica confocal microscope with mechanical spectral scanning. For this study, spectral training signatures (often referred to as endmembers) were selected with the ENVI (ITT Visual Information Solutions, Boulder, CO) "spectral hourglass" processing flow, a series of tools that use the spectrally over-determined nature of hyperspectral data to find the most spectrally pure (or spectrally unique) pixels within the data set. This set of endmember signatures was then used in the full range of mapping algorithms available in ENVI to determine locations, and in some cases subpixel abundances of endmembers. Mapping and abundance images showed a broad agreement between the spectral analysis algorithms, supported through visual assessment of output classification images and through statistical analysis of the distribution of pixels within each endmember class. The powerful spectral analysis algorithms available in COTS software, the result of decades of research in earth imaging, are easily translated to new sources of spectral data. Although the scale between earth imagery and spectral microscopy is radically different, the problem is the same: mapping material locations and abundances based on unique spectral signatures. (c) 2006 International Society for Analytical Cytology.

Mass selective separation applied to radioisotopes of cesium: Mass selective applied to radioisotopes

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

Dion, Michael; Eiden, Greg; Farmer, Orville

2016-07-22

A developed technique that uses the intrinsic mass-based separation capability of a quadrupole mass spectrometer has been used to resolve spectral radiometric interference of two isotopes of the same element. In this work the starting sample was a combination of 137Cs and 134Cs and was (activity) dominated by 137Cs and this methodology separated and “implanted” 134Cs that was later quantified for spectral features and ac- tivity with traditional radiometric techniques. This work demonstrated a 134Cs/137Cs activity ratio enhancement of >4 orders of magnitude and complete removal of 137Cs spectral features from the implanted target mass (i.e., 134).

Global Monitoring of Terrestrial Chlorophyll Fluorescence from Moderate-spectral-resolution Near-infrared Satellite Measurements: Methodology, Simulations, and Application to GOME-2

NASA Technical Reports Server (NTRS)

Joiner, J.; Gaunter, L.; Lindstrot, R.; Voigt, M.; Vasilkov, A. P.; Middleton, E. M.; Huemmrich, K. F.; Yoshida, Y.; Frankenberg, C.

2013-01-01

Globally mapped terrestrial chlorophyll fluorescence retrievals are of high interest because they can provide information on the functional status of vegetation including light-use efficiency and global primary productivity that can be used for global carbon cycle modeling and agricultural applications. Previous satellite retrievals of fluorescence have relied solely upon the filling-in of solar Fraunhofer lines that are not significantly affected by atmospheric absorption. Although these measurements provide near-global coverage on a monthly basis, they suffer from relatively low precision and sparse spatial sampling. Here, we describe a new methodology to retrieve global far-red fluorescence information; we use hyperspectral data with a simplified radiative transfer model to disentangle the spectral signatures of three basic components: atmospheric absorption, surface reflectance, and fluorescence radiance. An empirically based principal component analysis approach is employed, primarily using cloudy data over ocean, to model and solve for the atmospheric absorption. Through detailed simulations, we demonstrate the feasibility of the approach and show that moderate-spectral-resolution measurements with a relatively high signal-to-noise ratio can be used to retrieve far-red fluorescence information with good precision and accuracy. The method is then applied to data from the Global Ozone Monitoring Instrument 2 (GOME-2). The GOME-2 fluorescence retrievals display similar spatial structure as compared with those from a simpler technique applied to the Greenhouse gases Observing SATellite (GOSAT). GOME-2 enables global mapping of far-red fluorescence with higher precision over smaller spatial and temporal scales than is possible with GOSAT. Near-global coverage is provided within a few days. We are able to show clearly for the first time physically plausible variations in fluorescence over the course of a single month at a spatial resolution of 0.5 deg × 0.5 deg. We also show some significant differences between fluorescence and coincident normalized difference vegetation indices (NDVI) retrievals.

Global Monitoring of Terrestrial Chlorophyll Fluorescence from Moderate-Spectral-Resolution Near-Infrared Satellite Measurements: Methodology, Simulations, and Application to GOME-2

NASA Technical Reports Server (NTRS)

Joiner, J.; Guanter, L.; Lindstrot, R.; Voigt, M.; Vasilkov, A. P.; Middleton, E. M.; Huemmrich, K. F.; Yoshida, Y.; Frankenberg, C.

2013-01-01

Globally mapped terrestrial chlorophyll fluorescence retrievals are of high interest because they can provide information on the functional status of vegetation including light-use efficiency and global primary productivity that can be used for global carbon cycle modeling and agricultural applications. Previous satellite retrievals of fluorescence have relied solely upon the filling-in of solar Fraunhofer lines that are not significantly affected by atmospheric absorption. Although these measurements provide near-global coverage on a monthly basis, they suffer from relatively low precision and sparse spatial sampling. Here, we describe a new methodology to retrieve global far-red fluorescence information; we use hyperspectral data with a simplified radiative transfer model to disentangle the spectral signatures of three basic components: atmospheric absorption, surface reflectance, and fluorescence radiance. An empirically based principal component analysis approach is employed, primarily using cloudy data over ocean, to model and solve for the atmospheric absorption. Through detailed simulations, we demonstrate the feasibility of the approach and show that moderate-spectral-resolution measurements with a relatively high signal-to-noise ratio can be used to retrieve far-red fluorescence information with good precision and accuracy. The method is then applied to data from the Global Ozone Monitoring Instrument 2 (GOME-2). The GOME-2 fluorescence retrievals display similar spatial structure as compared with those from a simpler technique applied to the Greenhouse gases Observing SATellite (GOSAT). GOME-2 enables global mapping of far-red fluorescence with higher precision over smaller spatial and temporal scales than is possible with GOSAT. Near-global coverage is provided within a few days. We are able to show clearly for the first time physically plausible variations in fluorescence over the course of a single month at a spatial resolution of 0.5 0.5. We also show some significant differences between fluorescence and coincident normalized difference vegetation indices (NDVI) retrievals.

Collision-induced dissociative chemical cross-linking reagents and methodology: Applications to protein structural characterization using tandem mass spectrometry analysis.

PubMed

Soderblom, Erik J; Goshe, Michael B

2006-12-01

Chemical cross-linking combined with mass spectrometry is a viable approach to study the low-resolution structure of protein and protein complexes. However, unambiguous identification of the residues involved in a cross-link remains analytically challenging. To enable a more effective analysis across various MS platforms, we have developed a novel set of collision-induced dissociative cross-linking reagents and methodology for chemical cross-linking experiments using tandem mass spectrometry (CID-CXL-MS/MS). These reagents incorporate a single gas-phase cleavable bond within their linker region that can be selectively fragmented within the in-source region of the mass spectrometer, enabling independent MS/MS analysis for each peptide. Initial design concepts were characterized using a synthesized cross-linked peptide complex. Following verification and subsequent optimization of cross-linked peptide complex dissociation, our reagents were applied to homodimeric glutathione S-transferase and monomeric bovine serum albumin. Cross-linked residues identified by our CID-CXL-MS/MS method were in agreement with published crystal structures and previous cross-linking studies using conventional approaches. Common LC/MS/MS acquisition approaches such as data-dependent acquisition experiments using ion trap mass spectrometers and product ion spectral analysis using SEQUEST were shown to be compatible with our CID-CXL-MS/MS reagents, obviating the requirement for high resolution and high mass accuracy measurements to identify both intra- and interpeptide cross-links.

Infrared spectroscopy as a tool to characterise starch ordered structure--a joint FTIR-ATR, NMR, XRD and DSC study.

PubMed

Warren, Frederick J; Gidley, Michael J; Flanagan, Bernadine M

2016-03-30

Starch has a heterogeneous, semi-crystalline granular structure and the degree of ordered structure can affect its behaviour in foods and bioplastics. A range of methodologies are employed to study starch structure; differential scanning calorimetry, (13)C nuclear magnetic resonance, X-ray diffraction and Fourier transform infrared spectroscopy (FTIR). Despite the appeal of FTIR as a rapid, non-destructive methodology, there is currently no systematically defined quantitative relationship between FTIR spectral features and other starch structural measures. Here, we subject 61 starch samples to structural analysis, and systematically correlate FTIR spectra with other measures of starch structure. A hydration dependent peak position shift in the FTIR spectra of starch is observed, resulting from increased molecular order, but with complex, non-linear behaviour. We demonstrate that FTIR is a tool that can quantitatively probe short range interactions in starch structure. However, the assumptions of linear relationships between starch ordered structure and peak ratios are overly simplistic. Copyright © 2015 Elsevier Ltd. All rights reserved.

Methodology for modeling the mechanical interaction between a reaction wheel and a flexible structure

NASA Astrophysics Data System (ADS)

Elias, Laila M.; Dekens, Frank G.; Basdogan, Ipek; Sievers, Lisa A.; Neville, Timothy

2003-02-01

This paper presents a modeling methodology used to predict the performance of a flexible structure, such as a space telescope, in the presence of an on-board vibrational disturbance source, such as a reaction wheel assembly (RWA). Both decoupled and coupled analysis methods are presented. The decoupled method relies on blocked RWA disturbances, measured with the RWA hardmounted to a rigid surface. The coupled method corrects the blocked RWA disturbance boundary conditions using 'force filters' which depend on estimates of the interface accelerances of the RWA and spacecraft. Both methods were validated on the Micro-Precision Interferometer testbed at the Jet Propulsion Laboratory. Experimental results are encouraging, indicating that both methods provide sufficient accuracy compared to measured values; however, the coupled method provides the best results when the gyroscopic nature of the spinning RWA is captured in the RWA accelerance model. Additionally, the RWA disturbance cross spectral density terms are found to be influential.

Pathological speech signal analysis and classification using empirical mode decomposition.

PubMed

Kaleem, Muhammad; Ghoraani, Behnaz; Guergachi, Aziz; Krishnan, Sridhar

2013-07-01

Automated classification of normal and pathological speech signals can provide an objective and accurate mechanism for pathological speech diagnosis, and is an active area of research. A large part of this research is based on analysis of acoustic measures extracted from sustained vowels. However, sustained vowels do not reflect real-world attributes of voice as effectively as continuous speech, which can take into account important attributes of speech such as rapid voice onset and termination, changes in voice frequency and amplitude, and sudden discontinuities in speech. This paper presents a methodology based on empirical mode decomposition (EMD) for classification of continuous normal and pathological speech signals obtained from a well-known database. EMD is used to decompose randomly chosen portions of speech signals into intrinsic mode functions, which are then analyzed to extract meaningful temporal and spectral features, including true instantaneous features which can capture discriminative information in signals hidden at local time-scales. A total of six features are extracted, and a linear classifier is used with the feature vector to classify continuous speech portions obtained from a database consisting of 51 normal and 161 pathological speakers. A classification accuracy of 95.7 % is obtained, thus demonstrating the effectiveness of the methodology.

Detection of counterfeit brand spirits using 1H NMR fingerprints in comparison to sensory analysis.

PubMed

Kuballa, Thomas; Hausler, Thomas; Okaru, Alex O; Neufeld, Maria; Abuga, Kennedy O; Kibwage, Isaac O; Rehm, Jürgen; Luy, Burkhard; Walch, Stephan G; Lachenmeier, Dirk W

2018-04-15

Beverage fraud involving counterfeiting of brand spirits is an increasing problem not only due to deception of the consumer but also because it poses health risks e.g. from possible methanol admixture. Suspicious spirit samples from Russia and Kenya were analysed using 1 H nuclear magnetic resonance (NMR) spectroscopy in comparison to authentic products. Using linear regression analysis of spectral integral values, 4 counterfeited samples from Russia and 2 from Kenya were easily identifiable with R 2  < 0.7. Sensory analysis using triangle test methodology confirmed significant taste differences between counterfeited and authentic samples but the assessors were unable to correctly identify the counterfeited product in the majority of cases. An important conclusion is that consumers cannot assumed to be self-responsible when consuming counterfeit alcohol because there is no general ability to organoleptically detect counterfeit alcohol. Copyright © 2017 Elsevier Ltd. All rights reserved.

Topological data analysis: A promising big data exploration tool in biology, analytical chemistry and physical chemistry.

PubMed

Offroy, Marc; Duponchel, Ludovic

2016-03-03

An important feature of experimental science is that data of various kinds is being produced at an unprecedented rate. This is mainly due to the development of new instrumental concepts and experimental methodologies. It is also clear that the nature of acquired data is significantly different. Indeed in every areas of science, data take the form of always bigger tables, where all but a few of the columns (i.e. variables) turn out to be irrelevant to the questions of interest, and further that we do not necessary know which coordinates are the interesting ones. Big data in our lab of biology, analytical chemistry or physical chemistry is a future that might be closer than any of us suppose. It is in this sense that new tools have to be developed in order to explore and valorize such data sets. Topological data analysis (TDA) is one of these. It was developed recently by topologists who discovered that topological concept could be useful for data analysis. The main objective of this paper is to answer the question why topology is well suited for the analysis of big data set in many areas and even more efficient than conventional data analysis methods. Raman analysis of single bacteria should be providing a good opportunity to demonstrate the potential of TDA for the exploration of various spectroscopic data sets considering different experimental conditions (with high noise level, with/without spectral preprocessing, with wavelength shift, with different spectral resolution, with missing data). Copyright © 2016 Elsevier B.V. All rights reserved.

Spectral Correlation of Thermal and Magnetotelluric Responses in a 2D Geothermal System

NASA Astrophysics Data System (ADS)

Pacheco, M. A.

2008-05-01

A methodology of thermal response observations at regional scale in geothermal systems was implemented using magnetotelluric(MT) data that was analyzed by spectral correlation of EM anomalies. Local favorability indices were obtained enhancing the anomalies of thermal flow and their corresponding magnetotelluric responses related to a common source. A C++ code was developed to compute magnetotelluric and thermal responses using finite differences of a geothermal field model. The problem of thermal convection was solved numerically using the approach of Boussinesq and temperature and thermal flow profiles are obtained, also is solved to the equations of electromagnetic induction 2D that govern the wave equation for the H-polarization case in a two-dimensional model of the system. This methodology is useful to find thermal anomalies in conductive or resistive structures of a geothermal system, which is directly associated with the litology of the model such as magmatic chamber, basement and hydrothermal reservoir.

Simulating Colour Vision Deficiency from a Spectral Image.

PubMed

Shrestha, Raju

2016-01-01

People with colour vision deficiency (CVD) have difficulty seeing full colour contrast and can miss some of the features in a scene. As a part of universal design, researcher have been working on how to modify and enhance the colour of images in order to make them see the scene with good contrast. For this, it is important to know how the original colour image is seen by different individuals with CVD. This paper proposes a methodology to simulate accurate colour deficient images from a spectral image using cone sensitivity of different cases of deficiency. As the method enables generation of accurate colour deficient image, the methodology is believed to help better understand the limitations of colour vision deficiency and that in turn leads to the design and development of more effective imaging technologies for better and wider accessibility in the context of universal design.

Spatial/Spectral Identification of Endmembers from AVIRIS Data using Mathematical Morphology

NASA Technical Reports Server (NTRS)

Plaza, Antonio; Martinez, Pablo; Gualtieri, J. Anthony; Perez, Rosa M.

2001-01-01

During the last several years, a number of airborne and satellite hyperspectral sensors have been developed or improved for remote sensing applications. Imaging spectrometry allows the detection of materials, objects and regions in a particular scene with a high degree of accuracy. Hyperspectral data typically consist of hundreds of thousands of spectra, so the analysis of this information is a key issue. Mathematical morphology theory is a widely used nonlinear technique for image analysis and pattern recognition. Although it is especially well suited to segment binary or grayscale images with irregular and complex shapes, its application in the classification/segmentation of multispectral or hyperspectral images has been quite rare. In this paper, we discuss a new completely automated methodology to find endmembers in the hyperspectral data cube using mathematical morphology. The extension of classic morphology to the hyperspectral domain allows us to integrate spectral and spatial information in the analysis process. In Section 3, some basic concepts about mathematical morphology and the technical details of our algorithm are provided. In Section 4, the accuracy of the proposed method is tested by its application to real hyperspectral data obtained from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) imaging spectrometer. Some details about these data and reference results, obtained by well-known endmember extraction techniques, are provided in Section 2. Finally, in Section 5 we expose the main conclusions at which we have arrived.

Estimating the spatial distribution of field-applied mushroom compost in the Brandywine-Christina River Basin using multispectral remote sensing

NASA Astrophysics Data System (ADS)

Moxey, Kelsey A.

The world's greatest concentration of mushroom farms is settled within the Brandywine-Christina River Basin in Chester County in southeastern Pennsylvania. This industry produces a nutrient-rich byproduct known as spent mushroom compost, which has been traditionally applied to local farm fields as an organic fertilizer and soil amendment. While mushroom compost has beneficial properties, the possible over-application to farm fields could potentially degrade stream water quality. The goal of this study was to estimate the spatial extent and intensity of field-applied mushroom compost. We applied a remote sensing approach using Landsat multispectral imagery. We utilized the soil line technique, using the red and near-infrared bands, to estimate differences in soil wetness as a result of increased soil organic matter content from mushroom compost. We validated soil wetness estimates by examining the spectral response of references sites. We performed a second independent validation analysis using expert knowledge from agricultural extension agents. Our results showed that the soil line based wetness index worked well. The spectral validation illustrated that compost changes the spectral response of soil because of changes in wetness. The independent expert validation analysis produced a strong significant correlation between our remotely-sensed wetness estimates and the empirical ratings of compost application intensities. Overall, the methodology produced realistic spatial distributions of field-applied compost application intensities across the study area. These spatial distributions will be used for follow-up studies to assess the effect of spent mushroom compost on stream water quality.

High performance multi-spectral interrogation for surface plasmon resonance imaging sensors.

PubMed

Sereda, A; Moreau, J; Canva, M; Maillart, E

2014-04-15

Surface plasmon resonance (SPR) sensing has proven to be a valuable tool in the field of surface interactions characterization, especially for biomedical applications where label-free techniques are of particular interest. In order to approach the theoretical resolution limit, most SPR-based systems have turned to either angular or spectral interrogation modes, which both offer very accurate real-time measurements, but at the expense of the 2-dimensional imaging capability, therefore decreasing the data throughput. In this article, we show numerically and experimentally how to combine the multi-spectral interrogation technique with 2D-imaging, while finding an optimum in terms of resolution, accuracy, acquisition speed and reduction in data dispersion with respect to the classical reflectivity interrogation mode. This multi-spectral interrogation methodology is based on a robust five parameter fitting of the spectral reflectivity curve which enables monitoring of the reflectivity spectral shift with a resolution of the order of ten picometers, and using only five wavelength measurements per point. In fine, such multi-spectral based plasmonic imaging system allows biomolecular interaction monitoring in a linear regime independently of variations of buffer optical index, which is illustrated on a DNA-DNA model case. © 2013 Elsevier B.V. All rights reserved.

Automated flood extent identification using WorldView imagery for the insurance industry

NASA Astrophysics Data System (ADS)

Geller, Christina

2017-10-01

Flooding is the most common and costly natural disaster around the world, causing the loss of human life and billions in economic and insured losses each year. In 2016, pluvial and fluvial floods caused an estimated 5.69 billion USD in losses worldwide with the most severe events occurring in Germany, France, China, and the United States. While catastrophe modeling has begun to help bridge the knowledge gap about the risk of fluvial flooding, understanding the extent of a flood - pluvial and fluvial - in near real-time allows insurance companies around the world to quantify the loss of property that their clients face during a flooding event and proactively respond. To develop this real-time, global analysis of flooded areas and the associated losses, a new methodology utilizing optical multi-spectral imagery from DigitalGlobe (DGI) WorldView satellite suite is proposed for the extraction of pluvial and fluvial flood extents. This methodology involves identifying flooded areas visible to the sensor, filling in the gaps left by the built environment (i.e. buildings, trees) with a nearest neighbor calculation, and comparing the footprint against an Industry Exposure Database (IE) to calculate a loss estimate. Full-automation of the methodology allows production of flood extents and associated losses anywhere around the world as required. The methodology has been tested and proven effective for the 2016 flood in Louisiana, USA.

Wavelet Analysis Used for Spectral Background Removal in the Determination of Glucose from Near-Infrared Single-Beam Spectra

PubMed Central

Wan, Boyong; Small, Gary W.

2010-01-01

Wavelet analysis is developed as a preprocessing tool for use in removing background information from near-infrared (near-IR) single-beam spectra before the construction of multivariate calibration models. Three data sets collected with three different near-IR spectrometers are investigated that involve the determination of physiological levels of glucose (1-30 mM) in a simulated biological matrix containing alanine, ascorbate, lactate, triacetin, and urea in phosphate buffer. A factorial design is employed to optimize the specific wavelet function used and the level of decomposition applied, in addition to the spectral range and number of latent variables associated with a partial least-squares calibration model. The prediction performance of the computed models is studied with separate data acquired after the collection of the calibration spectra. This evaluation includes one data set collected over a period of more than six months. Preprocessing with wavelet analysis is also compared to the calculation of second-derivative spectra. Over the three data sets evaluated, wavelet analysis is observed to produce better-performing calibration models, with improvements in concentration predictions on the order of 30% being realized relative to models based on either second-derivative spectra or spectra preprocessed with simple additive and multiplicative scaling correction. This methodology allows the construction of stable calibrations directly with single-beam spectra, thereby eliminating the need for the collection of a separate background or reference spectrum. PMID:21035604

Wavelet analysis used for spectral background removal in the determination of glucose from near-infrared single-beam spectra.

PubMed

Wan, Boyong; Small, Gary W

2010-11-29

Wavelet analysis is developed as a preprocessing tool for use in removing background information from near-infrared (near-IR) single-beam spectra before the construction of multivariate calibration models. Three data sets collected with three different near-IR spectrometers are investigated that involve the determination of physiological levels of glucose (1-30 mM) in a simulated biological matrix containing alanine, ascorbate, lactate, triacetin, and urea in phosphate buffer. A factorial design is employed to optimize the specific wavelet function used and the level of decomposition applied, in addition to the spectral range and number of latent variables associated with a partial least-squares calibration model. The prediction performance of the computed models is studied with separate data acquired after the collection of the calibration spectra. This evaluation includes one data set collected over a period of more than 6 months. Preprocessing with wavelet analysis is also compared to the calculation of second-derivative spectra. Over the three data sets evaluated, wavelet analysis is observed to produce better-performing calibration models, with improvements in concentration predictions on the order of 30% being realized relative to models based on either second-derivative spectra or spectra preprocessed with simple additive and multiplicative scaling correction. This methodology allows the construction of stable calibrations directly with single-beam spectra, thereby eliminating the need for the collection of a separate background or reference spectrum. Copyright © 2010 Elsevier B.V. All rights reserved.

Hybrid least squares multivariate spectral analysis methods

DOEpatents

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.

Quantum mechanical computations and spectroscopy: from small rigid molecules in the gas phase to large flexible molecules in solution.

PubMed

Barone, Vincenzo; Improta, Roberto; Rega, Nadia

2008-05-01

Interpretation of structural properties and dynamic behavior of molecules in solution is of fundamental importance to understand their stability, chemical reactivity, and catalytic action. While information can be gained, in principle, by a variety of spectroscopic techniques, the interpretation of the rich indirect information that can be inferred from the analysis of experimental spectra is seldom straightforward because of the subtle interplay of several different effects, whose specific role is not easy to separate and evaluate. In such a complex scenario, theoretical studies can be very helpful at two different levels: (i) supporting and complementing experimental results to determine the structure of the target molecule starting from its spectral properties; (ii) dissecting and evaluating the role of different effects in determining the observed spectroscopic properties. This is the reason why computational spectroscopy is rapidly evolving from a highly specialized research field into a versatile and widespread tool for the assignment of experimental spectra and their interpretation in terms of chemical physical effects. In such a situation, it becomes important that both computationally and experimentally oriented chemists are aware that new methodological advances and integrated computational strategies are available, providing reliable estimates of fundamental spectral parameters not only for relatively small molecules in the gas phase but also for large and flexible molecules in condensed phases. In this Account, we review the most significant methodological contributions from our research group in this field, and by exploiting some recent results of their application to the computation of IR, UV-vis, NMR, and EPR spectral parameters, we discuss the microscopic mechanisms underlying solvent and vibrational effects on the spectral parameters. After reporting some recent achievements for the study of excited states by first principle quantum mechanical approaches, we focus on the treatment of environmental effects by means of mixed discrete-continuum solvent models and on effective methods for computing vibronic contributions to the spectra. We then discuss some new developments, mainly based on time-dependent approaches, allowing us to go beyond the determination of spectroscopic parameters toward the simulation of line widths and shapes. Although further developments are surely needed to improve the accuracy and effectiveness of several items in the proposed approach, we try to show that the first important steps toward a direct comparison between the results obtained in vitro and those obtained in silico have been made, making easier fruitful crossovers among experiments, computations and theoretical models, which would be decisive for a deeper understanding of the spectral behavior associated with complex systems and processes.

Three-dimensional spectral analysis of compositional heterogeneity at Arruntia crater on (4) Vesta using Dawn FC

NASA Astrophysics Data System (ADS)

Thangjam, Guneshwar; Nathues, Andreas; Mengel, Kurt; Schäfer, Michael; Hoffmann, Martin; Cloutis, Edward A.; Mann, Paul; Müller, Christian; Platz, Thomas; Schäfer, Tanja

2016-03-01

We introduce an innovative three-dimensional spectral approach (three band parameter space with polyhedrons) that can be used for both qualitative and quantitative analyzes improving the characterization of surface compositional heterogeneity of (4) Vesta. It is an advanced and more robust methodology compared to the standard two-dimensional spectral approach (two band parameter space). The Dawn Framing Camera (FC) color data obtained during High Altitude Mapping Orbit (resolution ∼ 60 m/pixel) is used. The main focus is on the howardite-eucrite-diogenite (HED) lithologies containing carbonaceous chondritic material, olivine, and impact-melt. The archived spectra of HEDs and their mixtures, from RELAB, HOSERLab and USGS databases as well as our laboratory-measured spectra are used for this study. Three-dimensional convex polyhedrons are defined using computed band parameter values of laboratory spectra. Polyhedrons based on the parameters of Band Tilt (R0.92μm/R0.96μm), Mid Ratio ((R0.75μm/R0.83μm)/(R0.83μm/R0.92μm)) and reflectance at 0.55 μm (R0.55μm) are chosen for the present analysis. An algorithm in IDL programming language is employed to assign FC data points to the respective polyhedrons. The Arruntia region in the northern hemisphere of Vesta is selected for a case study because of its geological and mineralogical importance. We observe that this region is eucrite-dominated howarditic in composition. The extent of olivine-rich exposures within an area of 2.5 crater radii is ∼12% larger than the previous finding (Thangjam, G. et al. [2014]. Meteorit. Planet. Sci. 49, 1831-1850). Lithologies of nearly pure CM2-chondrite, olivine, glass, and diogenite are not found in this region. Although there are no unambiguous spectral features of impact melt, the investigation of morphological features using FC clear filter data from Low Altitude Mapping Orbit (resolution ∼ 18 m/pixel) suggests potential impact-melt features inside and outside of the crater. Our spectral approach can be extended to the entire Vestan surface to study the heterogeneous surface composition and its geology.

Flower Colours through the Lens: Quantitative Measurement with Visible and Ultraviolet Digital Photography

PubMed Central

Garcia, Jair E.; Greentree, Andrew D.; Shrestha, Mani; Dorin, Alan; Dyer, Adrian G.

2014-01-01

Background 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. Methodology/Principal findings 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. Conclusion 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. PMID:24827828

Time-varying bispectral analysis of visually evoked multi-channel EEG

NASA Astrophysics Data System (ADS)

Chandran, Vinod

2012-12-01

Theoretical foundations of higher order spectral analysis are revisited to examine the use of time-varying bicoherence on non-stationary signals using a classical short-time Fourier approach. A methodology is developed to apply this to evoked EEG responses where a stimulus-locked time reference is available. Short-time windowed ensembles of the response at the same offset from the reference are considered as ergodic cyclostationary processes within a non-stationary random process. Bicoherence can be estimated reliably with known levels at which it is significantly different from zero and can be tracked as a function of offset from the stimulus. When this methodology is applied to multi-channel EEG, it is possible to obtain information about phase synchronization at different regions of the brain as the neural response develops. The methodology is applied to analyze evoked EEG response to flash visual stimulii to the left and right eye separately. The EEG electrode array is segmented based on bicoherence evolution with time using the mean absolute difference as a measure of dissimilarity. Segment maps confirm the importance of the occipital region in visual processing and demonstrate a link between the frontal and occipital regions during the response. Maps are constructed using bicoherence at bifrequencies that include the alpha band frequency of 8Hz as well as 4 and 20Hz. Differences are observed between responses from the left eye and the right eye, and also between subjects. The methodology shows potential as a neurological functional imaging technique that can be further developed for diagnosis and monitoring using scalp EEG which is less invasive and less expensive than magnetic resonance imaging.

High temperature polymer degradation: Rapid IR flow-through method for volatile quantification

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

Giron, Nicholas H.; Celina, Mathew C.

Accelerated aging of polymers at elevated temperatures often involves the generation of volatiles. These can be formed as the products of oxidative degradation reactions or intrinsic pyrolytic decomposition as part of polymer scission reactions. A simple analytical method for the quantification of water, CO 2, and CO as fundamental signatures of degradation kinetics is required. Here, we describe an analytical framework and develops a rapid mid-IR based gas analysis methodology to quantify volatiles that are contained in small ampoules after aging exposures. The approach requires identification of unique spectral signatures, systematic calibration with known concentrations of volatiles, and a rapidmore » acquisition FTIR spectrometer for time resolved successive spectra. Furthermore, the volatiles are flushed out from the ampoule with dry N2 carrier gas and are then quantified through spectral and time integration. This method is sufficiently sensitive to determine absolute yields of ~50 μg water or CO 2, which relates to probing mass losses of less than 0.01% for a 1 g sample, i.e. the early stages in the degradation process. Such quantitative gas analysis is not easily achieved with other approaches. Our approach opens up the possibility of quantitative monitoring of volatile evolution as an avenue to explore polymer degradation kinetics and its dependence on time and temperature.« less

High temperature polymer degradation: Rapid IR flow-through method for volatile quantification

DOE PAGES

Giron, Nicholas H.; Celina, Mathew C.

2017-05-19

Accelerated aging of polymers at elevated temperatures often involves the generation of volatiles. These can be formed as the products of oxidative degradation reactions or intrinsic pyrolytic decomposition as part of polymer scission reactions. A simple analytical method for the quantification of water, CO 2, and CO as fundamental signatures of degradation kinetics is required. Here, we describe an analytical framework and develops a rapid mid-IR based gas analysis methodology to quantify volatiles that are contained in small ampoules after aging exposures. The approach requires identification of unique spectral signatures, systematic calibration with known concentrations of volatiles, and a rapidmore » acquisition FTIR spectrometer for time resolved successive spectra. Furthermore, the volatiles are flushed out from the ampoule with dry N2 carrier gas and are then quantified through spectral and time integration. This method is sufficiently sensitive to determine absolute yields of ~50 μg water or CO 2, which relates to probing mass losses of less than 0.01% for a 1 g sample, i.e. the early stages in the degradation process. Such quantitative gas analysis is not easily achieved with other approaches. Our approach opens up the possibility of quantitative monitoring of volatile evolution as an avenue to explore polymer degradation kinetics and its dependence on time and temperature.« less

A hierarchical classification approach for recognition of low-density (LDPE) and high-density polyethylene (HDPE) in mixed plastic waste based on short-wave infrared (SWIR) hyperspectral imaging

NASA Astrophysics Data System (ADS)

Bonifazi, Giuseppe; Capobianco, Giuseppe; Serranti, Silvia

2018-06-01

The aim of this work was to recognize different polymer flakes from mixed plastic waste through an innovative hierarchical classification strategy based on hyperspectral imaging, with particular reference to low density polyethylene (LDPE) and high-density polyethylene (HDPE). A plastic waste composition assessment, including also LDPE and HDPE identification, may help to define optimal recycling strategies for product quality control. Correct handling of plastic waste is essential for its further "sustainable" recovery, maximizing the sorting performance in particular for plastics with similar characteristics as LDPE and HDPE. Five different plastic waste samples were chosen for the investigation: polypropylene (PP), LDPE, HDPE, polystyrene (PS) and polyvinyl chloride (PVC). A calibration dataset was realized utilizing the corresponding virgin polymers. Hyperspectral imaging in the short-wave infrared range (1000-2500 nm) was thus applied to evaluate the different plastic spectral attributes finalized to perform their recognition/classification. After exploring polymer spectral differences by principal component analysis (PCA), a hierarchical partial least squares discriminant analysis (PLS-DA) model was built allowing the five different polymers to be recognized. The proposed methodology, based on hierarchical classification, is very powerful and fast, allowing to recognize the five different polymers in a single step.

Correlation analysis between forest carbon stock and spectral vegetation indices in Xuan Lien Nature Reserve, Thanh Hoa, Viet Nam

NASA Astrophysics Data System (ADS)

Dung Nguyen, The; Kappas, Martin

2017-04-01

In the last several years, the interest in forest biomass and carbon stock estimation has increased due to its importance for forest management, modelling carbon cycle, and other ecosystem services. However, no estimates of biomass and carbon stocks of deferent forest cover types exist throughout in the Xuan Lien Nature Reserve, Thanh Hoa, Viet Nam. This study investigates the relationship between above ground carbon stock and different vegetation indices and to identify the most likely vegetation index that best correlate with forest carbon stock. The terrestrial inventory data come from 380 sample plots that were randomly sampled. Individual tree parameters such as DBH and tree height were collected to calculate the above ground volume, biomass and carbon for different forest types. The SPOT6 2013 satellite data was used in the study to obtain five vegetation indices NDVI, RDVI, MSR, RVI, and EVI. The relationships between the forest carbon stock and vegetation indices were investigated using a multiple linear regression analysis. R-square, RMSE values and cross-validation were used to measure the strength and validate the performance of the models. The methodology presented here demonstrates the possibility of estimating forest volume, biomass and carbon stock. It can also be further improved by addressing more spectral bands data and/or elevation.

Model-Based Speech Signal Coding Using Optimized Temporal Decomposition for Storage and Broadcasting Applications

NASA Astrophysics Data System (ADS)

Athaudage, Chandranath R. N.; Bradley, Alan B.; Lech, Margaret

2003-12-01

A dynamic programming-based optimization strategy for a temporal decomposition (TD) model of speech and its application to low-rate speech coding in storage and broadcasting is presented. In previous work with the spectral stability-based event localizing (SBEL) TD algorithm, the event localization was performed based on a spectral stability criterion. Although this approach gave reasonably good results, there was no assurance on the optimality of the event locations. In the present work, we have optimized the event localizing task using a dynamic programming-based optimization strategy. Simulation results show that an improved TD model accuracy can be achieved. A methodology of incorporating the optimized TD algorithm within the standard MELP speech coder for the efficient compression of speech spectral information is also presented. The performance evaluation results revealed that the proposed speech coding scheme achieves 50%-60% compression of speech spectral information with negligible degradation in the decoded speech quality.

Using Fourier transform IR spectroscopy to analyze biological materials

PubMed Central

Baker, Matthew J; Trevisan, Júlio; Bassan, Paul; Bhargava, Rohit; Butler, Holly J; Dorling, Konrad M; Fielden, Peter R; Fogarty, Simon W; Fullwood, Nigel J; Heys, Kelly A; Hughes, Caryn; Lasch, Peter; Martin-Hirsch, Pierre L; Obinaju, Blessing; Sockalingum, Ganesh D; Sulé-Suso, Josep; Strong, Rebecca J; Walsh, Michael J; Wood, Bayden R; Gardner, Peter; Martin, Francis L

2015-01-01

IR spectroscopy is an excellent method for biological analyses. It enables the nonperturbative, label-free extraction of biochemical information and images toward diagnosis and the assessment of cell functionality. Although not strictly microscopy in the conventional sense, it allows the construction of images of tissue or cell architecture by the passing of spectral data through a variety of computational algorithms. Because such images are constructed from fingerprint spectra, the notion is that they can be an objective reflection of the underlying health status of the analyzed sample. One of the major difficulties in the field has been determining a consensus on spectral pre-processing and data analysis. This manuscript brings together as coauthors some of the leaders in this field to allow the standardization of methods and procedures for adapting a multistage approach to a methodology that can be applied to a variety of cell biological questions or used within a clinical setting for disease screening or diagnosis. We describe a protocol for collecting IR spectra and images from biological samples (e.g., fixed cytology and tissue sections, live cells or biofluids) that assesses the instrumental options available, appropriate sample preparation, different sampling modes as well as important advances in spectral data acquisition. After acquisition, data processing consists of a sequence of steps including quality control, spectral pre-processing, feature extraction and classification of the supervised or unsupervised type. A typical experiment can be completed and analyzed within hours. Example results are presented on the use of IR spectra combined with multivariate data processing. PMID:24992094

Air-coupled laser vibrometry: analysis and applications.

PubMed

Solodov, Igor; Döring, Daniel; Busse, Gerd

2009-03-01

Acousto-optic interaction between a narrow laser beam and acoustic waves in air is analyzed theoretically. The photoelastic relation in air is used to derive the phase modulation of laser light in air-coupled reflection vibrometry induced by angular spatial spectral components comprising the acoustic beam. Maximum interaction was found for the zero spatial acoustic component propagating normal to the laser beam. The angular dependence of the imaging efficiency is determined for the axial and nonaxial acoustic components with the regard for the laser beam steering in the scanning mode. The sensitivity of air-coupled vibrometry is compared with conventional "Doppler" reflection vibrometry. Applications of the methodology for visualization of linear and nonlinear air-coupled fields are demonstrated.

Bayesian Techniques for Plasma Theory to Bridge the Gap Between Space and Lab Plasmas

NASA Astrophysics Data System (ADS)

Crabtree, Chris; Ganguli, Gurudas; Tejero, Erik

2017-10-01

We will show how Bayesian techniques provide a general data analysis methodology that is better suited to investigate phenomena that require a nonlinear theory for an explanation. We will provide short examples of how Bayesian techniques have been successfully used in the radiation belts to provide precise nonlinear spectral estimates of whistler mode chorus and how these techniques have been verified in laboratory plasmas. We will demonstrate how Bayesian techniques allow for the direct competition of different physical theories with data acting as the necessary arbitrator. This work is supported by the Naval Research Laboratory base program and by the National Aeronautics and Space Administration under Grant No. NNH15AZ90I.

Assessment of seismic risk in Tashkent, Uzbekistan and Bishkek, Kyrgyz Republic

USGS Publications Warehouse

Erdik, M.; Rashidov, T.; Safak, E.; Turdukulov, A.

2005-01-01

The impact of earthquakes in urban centers prone to disastrous earthquakes necessitates the analysis of associated risk for rational formulation of contingency plans and mitigation strategies. In urban centers the seismic risk is best quantified and portrayed through the preparation of 'Earthquake damage and Loss Scenarios'. The components of such scenarios are the assessment of the hazard, inventories and the vulnerabilities of elements at risk. For the development of earthquake risk scenario in Tashkent-Uzbekistan and Bishkek-Kyrgyzstan an approach based on spectral displacements is utilized. This paper will present the important features of a comprehensive study, highlight the methodology, discuss the results and provide insights to the future developments. ?? 2005 Elsevier Ltd. All rights reserved.

Simultaneous Retrieval of Temperature, Water Vapor and Ozone Atmospheric Profiles from IASI: Compression, De-noising, First Guess Retrieval and Inversion Algorithms

NASA Technical Reports Server (NTRS)

Aires, F.; Rossow, W. B.; Scott, N. A.; Chedin, A.; Hansen, James E. (Technical Monitor)

2001-01-01

A fast temperature water vapor and ozone atmospheric profile retrieval algorithm is developed for the high spectral resolution Infrared Atmospheric Sounding Interferometer (IASI) space-borne instrument. Compression and de-noising of IASI observations are performed using Principal Component Analysis. This preprocessing methodology also allows, for a fast pattern recognition in a climatological data set to obtain a first guess. Then, a neural network using first guess information is developed to retrieve simultaneously temperature, water vapor and ozone atmospheric profiles. The performance of the resulting fast and accurate inverse model is evaluated with a large diversified data set of radiosondes atmospheres including rare events.

Vegetation mapping of Nowitna National Wildlife Reguge, Alaska using Landsat MSS digital data

USGS Publications Warehouse

Talbot, S. S.; Markon, Carl J.

1986-01-01

A Landsat-derived vegetation map was prepared for Nowitna National Wildlife Refuge. The refuge lies within the middle boreal subzone of north central Alaska. Seven major vegetation classes and sixteen subclasses were recognized: forest (closed needleleaf, open needleleaf, needleleaf woodland, mixed, and broadleaf); broadleaf scrub (lowland, alluvial, subalpine); dwarf scrub (prostrate dwarf shrub tundra, dwarf shrub-graminoid tussock peatland); herbaceous (graminoid bog, marsh and meadow); scarcely vegetated areas (scarcely vegetated scree and floodplain); water (clear, turbid); and other areas (mountain shadow). The methodology employed a cluster-block technique. Sample areas were described based on a combination of helicopter-ground survey, aerial photointerpretation, and digital Landsat data. Major steps in the Landsat analysis involved preprocessing (geometric correction), derivation of statistical parameters for spectral classes, spectral class labeling of sample areas, preliminary classification of the entire study area using a maximum-likelihood algorithm, and final classification utilizing ancillary information such as digital elevation data. The final product is a 1:250,000-scale vegetation map representative of distinctive regional patterns and suitable for use in comprehensive conservation planning.

Probing dynamics in colloidal crystals with pump-probe experiments at LCLS: Methodology and analysis

DOE PAGES

Mukharamova, Nastasia; Lazarev, Sergey; Meijer, Janne -Mieke; ...

2017-05-19

We present results of the studies of dynamics in colloidal crystals performed by pump-probe experiments using an X-ray free-electron laser (XFEL). Colloidal crystals were pumped with an infrared laser at a wavelength of 800 nm with varying power and probed by XFEL pulses at an energy of 8 keV with a time delay up to 1000 ps. The positions of the Bragg peaks, and their radial and azimuthal widths were analyzed as a function of the time delay. The spectral analysis of the data did not reveal significant enhancement of frequencies expected in this experiment. As a result, this allowedmore » us to conclude that the amplitude of vibrational modes excited in colloidal crystals was less than the systematic error caused by the noise level.« less

Analysis of forest disturbance using TM and AVHRR data

NASA Technical Reports Server (NTRS)

Spanner, Michael A.; Hlavka, Christine A.; Pierce, Lars L.

1989-01-01

A methodology that will be used to determine the proportions of undisturbed, successional vegetation and recently disturbed land cover within coniferous forests using remotely sensed data from the advanced very high resolution radiometer (AVHRR) is presented. The method uses thematic mapper (TM) data to determine the proportions of the three stages of forest disturbance and regrowth for each AVHRR pixel in the sample areas, and is then applied to interpret all AVHRR imagery. Preliminary results indicate that there are predictable relationships between TM spectral response and the disturbance classes. Analysis of ellipse plots from a TM classification of the disturbed forested landscape indicates that the forest classes are separable in the red (0.63-0.69 micron) and near-infrared (0.76-0.90 micron) bands, providing evidence that the proportion of disturbance classes may be determined from AVHRR data.

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

Concurrent measurement of "real-world" stress and arousal in individuals with psychosis: assessing the feasibility and validity of a novel methodology.

PubMed

Kimhy, David; Delespaul, Philippe; Ahn, Hongshik; Cai, Shengnan; Shikhman, Marina; Lieberman, Jeffrey A; Malaspina, Dolores; Sloan, Richard P

2010-11-01

Psychosis has been repeatedly suggested to be affected by increases in stress and arousal. However, there is a dearth of evidence supporting the temporal link between stress, arousal, and psychosis during "real-world" functioning. This paucity of evidence may stem from limitations of current research methodologies. Our aim is to the test the feasibility and validity of a novel methodology designed to measure concurrent stress and arousal in individuals with psychosis during "real-world" daily functioning. Twenty patients with psychosis completed a 36-hour ambulatory assessment of stress and arousal. We used experience sampling method with palm computers to assess stress (10 times per day, 10 AM → 10 PM) along with concurrent ambulatory measurement of cardiac autonomic regulation using a Holter monitor. The clocks of the palm computer and Holter monitor were synchronized, allowing the temporal linking of the stress and arousal data. We used power spectral analysis to determine the parasympathetic contributions to autonomic regulation and sympathovagal balance during 5 minutes before and after each experience sample. Patients completed 79% of the experience samples (75% with a valid concurrent arousal data). Momentary increases in stress had inverse correlation with concurrent parasympathetic activity (ρ = -.27, P < .0001) and positive correlation with sympathovagal balance (ρ = .19, P = .0008). Stress and heart rate were not significantly related (ρ = -.05, P = .3875). The findings support the feasibility and validity of our methodology in individuals with psychosis. The methodology offers a novel way to study in high time resolution the concurrent, "real-world" interactions between stress, arousal, and psychosis. The authors discuss the methodology's potential applications and future research directions.

Direct Detection of Pharmaceuticals and Personal Care Products from Aqueous Samples with Thermally-Assisted Desorption Electrospray Ionization Mass Spectrometry

NASA Astrophysics Data System (ADS)

Campbell, Ian S.; Ton, Alain T.; Mulligan, Christopher C.

2011-07-01

An ambient mass spectrometric method based on desorption electrospray ionization (DESI) has been developed to allow rapid, direct analysis of contaminated water samples, and the technique was evaluated through analysis of a wide array of pharmaceutical and personal care product (PPCP) contaminants. Incorporating direct infusion of aqueous sample and thermal assistance into the source design has allowed low ppt detection limits for the target analytes in drinking water matrices. With this methodology, mass spectral information can be collected in less than 1 min, consuming ~100 μL of total sample. Quantitative ability was also demonstrated without the use of an internal standard, yielding decent linearity and reproducibility. Initial results suggest that this source configuration is resistant to carryover effects and robust towards multi-component samples. The rapid, continuous analysis afforded by this method offers advantages in terms of sample analysis time and throughput over traditional hyphenated mass spectrometric techniques.

Direct detection of pharmaceuticals and personal care products from aqueous samples with thermally-assisted desorption electrospray ionization mass spectrometry.

PubMed

Campbell, Ian S; Ton, Alain T; Mulligan, Christopher C

2011-07-01

An ambient mass spectrometric method based on desorption electrospray ionization (DESI) has been developed to allow rapid, direct analysis of contaminated water samples, and the technique was evaluated through analysis of a wide array of pharmaceutical and personal care product (PPCP) contaminants. Incorporating direct infusion of aqueous sample and thermal assistance into the source design has allowed low ppt detection limits for the target analytes in drinking water matrices. With this methodology, mass spectral information can be collected in less than 1 min, consuming ~100 μL of total sample. Quantitative ability was also demonstrated without the use of an internal standard, yielding decent linearity and reproducibility. Initial results suggest that this source configuration is resistant to carryover effects and robust towards multi-component samples. The rapid, continuous analysis afforded by this method offers advantages in terms of sample analysis time and throughput over traditional hyphenated mass spectrometric techniques.

Apparatus and system for multivariate spectral analysis

DOEpatents

Keenan, Michael R.; Kotula, Paul G.

2003-06-24

An apparatus and system for determining the properties of a sample from measured spectral data collected from the sample by performing a method of multivariate spectral analysis. The method can include: generating a two-dimensional matrix A containing measured spectral data; providing a weighted spectral data matrix D by performing a weighting operation on matrix A; factoring D into the product of two matrices, C and S.sup.T, by performing a constrained alternating least-squares analysis of D=CS.sup.T, where C is a concentration intensity matrix and S is a spectral shapes matrix; unweighting C and S by applying the inverse of the weighting used previously; and determining the properties of the sample by inspecting C and S. This method can be used by a spectrum analyzer to process X-ray spectral data generated by a spectral analysis system that can include a Scanning Electron Microscope (SEM) with an Energy Dispersive Detector and Pulse Height Analyzer.

Pulsational mode fluctuations and their basic conservation laws

NASA Astrophysics Data System (ADS)

Borah, B.; Karmakar, P. K.

2015-01-01

We propose a theoretical hydrodynamic model for investigating the basic features of nonlinear pulsational mode stability in a partially charged dust molecular cloud within the framework of the Jeans homogenization assumption. The inhomogeneous cloud is modeled as a quasi-neutral multifluid consisting of the warm electrons, warm ions, and identical inertial cold dust grains with partial ionization in a neutral gaseous background. The grain-charge is assumed not to vary in the fluctuation evolution time scale. The active inertial roles of the thermal species are included. We apply a standard multiple scaling technique centered on the gravito-electrostatic equilibrium to understand the fluctuations on the astrophysical scales of space and time. This is found that electrostatic and self-gravitational eigenmodes co-exist as diverse solitary spectral patterns governed by a pair of Korteweg-de Vries (KdV) equations. In addition, all the relevant classical conserved quantities associated with the KdV system under translational invariance are methodologically derived and numerically analyzed. A full numerical shape-analysis of the fluctuations, scale lengths and perturbed densities with multi-parameter variation of judicious plasma conditions is carried out. A correlation of the perturbed densities and gravito-electrostatic spectral patterns is also graphically indicated. It is demonstrated that the solitary mass, momentum and energy densities also evolve like solitary spectral patterns which remain conserved throughout the spatiotemporal scales of the fluctuation dynamics. Astrophysical and space environments significant to our results are briefly highlighted.

A simple and low cost dual-wavelength β-correction spectrophotometric determination and speciation of mercury(II) in water using chromogenic reagent 4-(2-thiazolylazo) resorcinol

NASA Astrophysics Data System (ADS)

Al-Bagawi, A. H.; Ahmad, W.; Saigl, Z. M.; Alwael, H.; Al-Harbi, E. A.; El-Shahawi, M. S.

2017-12-01

The most common problems in spectrophotometric determination of various complex species originate from the background spectral interference. Thus, the present study aimed to overcome the spectral matrix interference for the precise analysis and speciation of mercury(II) in water by dual-wavelength β-correction spectrophotometry using 4-(2-thiazolylazo) resorcinol (TAR) as chromogenic reagent. The principle was based on measuring the correct absorbance for the formed complex of mercury(II) ions with TAR reagent at 547 nm (lambda max). Under optimized conditions, a linear dynamic range of 0.1-2.0 μg mL- 1 with correlation coefficient (R2) of 0.997 were obtained with lower limits of detection (LOD) of 0.024 μg mL- 1 and limit of quantification (LOQ) of 0.081 μg mL- 1. The values of RSD and relative error (RE) obtained for β-correction method and single wavelength spectrophotometry were 1.3, 1.32% and 4.7, 5.9%, respectively. The method was validated in tap and sea water in terms of the data obtained from inductively coupled plasma-optical emission spectrometry (ICP-OES) using student's t and F tests. The developed methodology satisfactorily overcomes the spectral interference in trace determination and speciation of mercury(II) ions in water.

Spatial-scanning hyperspectral imaging probe for bio-imaging applications

NASA Astrophysics Data System (ADS)

Lim, Hoong-Ta; Murukeshan, Vadakke Matham

2016-03-01

The three common methods to perform hyperspectral imaging are the spatial-scanning, spectral-scanning, and snapshot methods. However, only the spectral-scanning and snapshot methods have been configured to a hyperspectral imaging probe as of today. This paper presents a spatial-scanning (pushbroom) hyperspectral imaging probe, which is realized by integrating a pushbroom hyperspectral imager with an imaging probe. The proposed hyperspectral imaging probe can also function as an endoscopic probe by integrating a custom fabricated image fiber bundle unit. The imaging probe is configured by incorporating a gradient-index lens at the end face of an image fiber bundle that consists of about 50 000 individual fiberlets. The necessary simulations, methodology, and detailed instrumentation aspects that are carried out are explained followed by assessing the developed probe's performance. Resolution test targets such as United States Air Force chart as well as bio-samples such as chicken breast tissue with blood clot are used as test samples for resolution analysis and for performance validation. This system is built on a pushbroom hyperspectral imaging system with a video camera and has the advantage of acquiring information from a large number of spectral bands with selectable region of interest. The advantages of this spatial-scanning hyperspectral imaging probe can be extended to test samples or tissues residing in regions that are difficult to access with potential diagnostic bio-imaging applications.

Hybrid least squares multivariate spectral analysis methods

DOEpatents

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.

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.

Physical parameter determinations of young Ms. Taking advantage of the Virtual Observatory to compare methodologies

NASA Astrophysics Data System (ADS)

Bayo, A.; Rodrigo, C.; Barrado, D.; Allard, F.

One of the very first steps astronomers working in stellar physics perform to advance in their studies, is to determine the most common/relevant physical parameters of the objects of study (effective temperature, bolometric luminosity, surface gravity, etc.). Different methodologies exist depending on the nature of the data, intrinsic properties of the objects, etc. One common approach is to compare the observational data with theoretical models passed through some simulator that will leave in the synthetic data the same imprint than the observational data carries, and see what set of parameters reproduce the observations best. Even in this case, depending on the kind of data the astronomer has, the methodology changes slightly. After parameters are published, the community tend to quote, praise and criticize them, sometimes paying little attention on whether the possible discrepancies come from the theoretical models, the data themselves or just the methodology used in the analysis. In this work we perform the simple, yet interesting, exercise of comparing the effective temperatures obtained via SED and more detailed spectral fittings (to the same grid of models), of a sample of well known and characterized young M-type objects members to different star forming regions and show how differences in temperature of up to 350 K can be expected just from the difference in methodology/data used. On the other hand we show how these differences are smaller for colder objects even when the complexity of the fit increases like for example introducing differential extinction. To perform this exercise we benefit greatly from the framework offered by the Virtual Observaotry.

A tool for selective inline quantification of co-eluting proteins in chromatography using spectral analysis and partial least squares regression.

PubMed

Brestrich, Nina; Briskot, Till; Osberghaus, Anna; Hubbuch, Jürgen

2014-07-01

Selective quantification of co-eluting proteins in chromatography is usually performed by offline analytics. This is time-consuming and can lead to late detection of irregularities in chromatography processes. To overcome this analytical bottleneck, a methodology for selective protein quantification in multicomponent mixtures by means of spectral data and partial least squares regression was presented in two previous studies. In this paper, a powerful integration of software and chromatography hardware will be introduced that enables the applicability of this methodology for a selective inline quantification of co-eluting proteins in chromatography. A specific setup consisting of a conventional liquid chromatography system, a diode array detector, and a software interface to Matlab® was developed. The established tool for selective inline quantification was successfully applied for a peak deconvolution of a co-eluting ternary protein mixture consisting of lysozyme, ribonuclease A, and cytochrome c on SP Sepharose FF. Compared to common offline analytics based on collected fractions, no loss of information regarding the retention volumes and peak flanks was observed. A comparison between the mass balances of both analytical methods showed, that the inline quantification tool can be applied for a rapid determination of pool yields. Finally, the achieved inline peak deconvolution was successfully applied to make product purity-based real-time pooling decisions. This makes the established tool for selective inline quantification a valuable approach for inline monitoring and control of chromatographic purification steps and just in time reaction on process irregularities. © 2014 Wiley Periodicals, Inc.

Asteroid (21) Lutetia: Semi-Automatic Impact Craters Detection and Classification

NASA Astrophysics Data System (ADS)

Jenerowicz, M.; Banaszkiewicz, M.

2018-05-01

The need to develop an automated method, independent of lighting and surface conditions, for the identification and measurement of impact craters, as well as the creation of a reliable and efficient tool, has become a justification of our studies. This paper presents a methodology for the detection of impact craters based on their spectral and spatial features. The analysis aims at evaluation of the algorithm capabilities to determinate the spatial parameters of impact craters presented in a time series. In this way, time-consuming visual interpretation of images would be reduced to the special cases. The developed algorithm is tested on a set of OSIRIS high resolution images of asteroid Lutetia surface which is characterized by varied landforms and the abundance of craters created by collisions with smaller bodies of the solar system.The proposed methodology consists of three main steps: characterisation of objects of interest on limited set of data, semi-automatic extraction of impact craters performed for total set of data by applying the Mathematical Morphology image processing (Serra, 1988, Soille, 2003), and finally, creating libraries of spatial and spectral parameters for extracted impact craters, i.e. the coordinates of the crater center, semi-major and semi-minor axis, shadow length and cross-section. The overall accuracy of the proposed method is 98 %, the Kappa coefficient is 0.84, the correlation coefficient is ∼ 0.80, the omission error 24.11 %, the commission error 3.45 %. The obtained results show that methods based on Mathematical Morphology operators are effective also with a limited number of data and low-contrast images.

Strategies for cloud-top phase determination: differentiation between thin cirrus clouds and snow in manual (ground truth) analyses

NASA Astrophysics Data System (ADS)

Hutchison, Keith D.; Etherton, Brian J.; Topping, Phillip C.

1996-12-01

Quantitative assessments on the performance of automated cloud analysis algorithms require the creation of highly accurate, manual cloud, no cloud (CNC) images from multispectral meteorological satellite data. In general, the methodology to create ground truth analyses for the evaluation of cloud detection algorithms is relatively straightforward. However, when focus shifts toward quantifying the performance of automated cloud classification algorithms, the task of creating ground truth images becomes much more complicated since these CNC analyses must differentiate between water and ice cloud tops while ensuring that inaccuracies in automated cloud detection are not propagated into the results of the cloud classification algorithm. The process of creating these ground truth CNC analyses may become particularly difficult when little or no spectral signature is evident between a cloud and its background, as appears to be the case when thin cirrus is present over snow-covered surfaces. In this paper, procedures are described that enhance the researcher's ability to manually interpret and differentiate between thin cirrus clouds and snow-covered surfaces in daytime AVHRR imagery. The methodology uses data in up to six AVHRR spectral bands, including an additional band derived from the daytime 3.7 micron channel, which has proven invaluable for the manual discrimination between thin cirrus clouds and snow. It is concluded that while the 1.6 micron channel remains essential to differentiate between thin ice clouds and snow. However, this capability that may be lost if the 3.7 micron data switches to a nighttime-only transmission with the launch of future NOAA satellites.

Assessment of the Spectral Stability of Libya 4, Libya 1, and Mauritania 2 Sites Using Earth Observing One Hyperion

NASA Technical Reports Server (NTRS)

Choi, Taeyoung; Xiong, Xiaoxiong; Angal, Amit; Chander, Gyanesh; Qu, John J.

2014-01-01

The objective of this paper is to formulate a methodology to assess the spectral stability of the Libya 4, Libya 1, and Mauritania 2 pseudo-invariant calibration sites (PICS) using Earth Observing One (EO-1) Hyperion sensor. All the available Hyperion collections, downloaded from the Earth Explorer website, were utilized for the three PICS. In each site, a reference spectrum is selected at a specific day in the vicinity of the region of interest (ROI) defined by Committee on Earth Observation Satellites (CEOS). A series of ROIs are predefined in the along-track direction with 196 spectral top-of-atmosphere reflectance values in each ROI. Based on the reference ROI spectrum, the spectral stability of these ROIs is evaluated by average deviations (ADs) and spectral angle mapper (SAM) methods in the specific ranges of time and geo-spatial locations. Time and ROI location-dependent SAM and AD results are very stable within +/- 2 deg and +/-1.7% of 1sigma standard deviations. Consequently, the Libya 4, Mauritania 2, and Libya 1 CEOS selected PICS are spectrally stable targets within the time and spatial swath ranges of the Hyperion collections.

Quantitative subpixel spectral detection of targets in multispectral images. [terrestrial and planetary surfaces

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.

An Automated Directed Spectral Search Methodology for Small Target Detection

NASA Astrophysics Data System (ADS)

Grossman, Stanley I.

Much of the current efforts in remote sensing tackle macro-level problems such as determining the extent of wheat in a field, the general health of vegetation or the extent of mineral deposits in an area. However, for many of the remaining remote sensing challenges being studied currently, such as border protection, drug smuggling, treaty verification, and the war on terror, most targets are very small in nature - a vehicle or even a person. While in typical macro-level problems the objective vegetation is in the scene, for small target detection problems it is not usually known if the desired small target even exists in the scene, never mind finding it in abundance. The ability to find specific small targets, such as vehicles, typifies this problem. Complicating the analyst's life, the growing number of available sensors is generating mountains of imagery outstripping the analysts' ability to visually peruse them. This work presents the important factors influencing spectral exploitation using multispectral data and suggests a different approach to small target detection. The methodology of directed search is presented, including the use of scene-modeled spectral libraries, various search algorithms, and traditional statistical and ROC curve analysis. The work suggests a new metric to calibrate analysis labeled the analytic sweet spot as well as an estimation method for identifying the sweet spot threshold for an image. It also suggests a new visualization aid for highlighting the target in its entirety called nearest neighbor inflation (NNI). It brings these all together to propose that these additions to the target detection arena allow for the construction of a fully automated target detection scheme. This dissertation next details experiments to support the hypothesis that the optimum detection threshold is the analytic sweet spot and that the estimation method adequately predicts it. Experimental results and analysis are presented for the proposed directed search techniques of spectral image based small target detection. It offers evidence of the functionality of the NNI visualization and also provides evidence that the increased spectral dimensionality of the 8-band Worldview-2 datasets provides noteworthy improvement in results over traditional 4-band multispectral datasets. The final experiment presents the results from a prototype fully automated target detection scheme in support of the overarching premise. This work establishes the analytic sweet spot as the optimum threshold defined as the point where error detection rate curves -- false detections vs. missing detections -- cross. At this point the errors are minimized while the detection rate is maximized. It then demonstrates that taking the first moment statistic of the histogram of calculated target detection values from a detection search with test threshold set arbitrarily high will estimate the analytic sweet spot for that image. It also demonstrates that directed search techniques -- when utilized with appropriate scene-specific modeled signatures and atmospheric compensations -- perform at least as well as in-scene search techniques 88% of the time and grossly under-performing only 11% of the time; the in-scene only performs as well or better 50% of the time. It further demonstrates the clear advantage increased multispectral dimensionality brings to detection searches improving performance in 50% of the cases while performing at least as well 72% of the time. Lastly, it presents evidence that a fully automated prototype performs as anticipated laying the groundwork for further research into fully automated processes for small target detection.

Automated Control of the Organic and Inorganic Composition of Aloe vera Extracts Using (1)H NMR Spectroscopy.

PubMed

Monakhova, Yulia B; Randel, Gabriele; Diehl, Bernd W K

2016-09-01

Recent classification of Aloe vera whole-leaf extract by the International Agency for Research and Cancer as a possible carcinogen to humans as well as the continuous adulteration of A. vera's authentic material have generated renewed interest in controlling A. vera. The existing NMR spectroscopic method for the analysis of A. vera, which is based on a routine developed at Spectral Service, was extended. Apart from aloverose, glucose, malic acid, lactic acid, citric acid, whole-leaf material (WLM), acetic acid, fumaric acid, sodium benzoate, and potassium sorbate, the quantification of Mg(2+), Ca(2+), and fructose is possible with the addition of a Cs-EDTA solution to sample. The proposed methodology was automated, which includes phasing, baseline-correction, deconvolution (based on the Lorentzian function), integration, quantification, and reporting. The NMR method was applied to 41 A. vera preparations in the form of liquid A. vera juice and solid A. vera powder. The advantages of the new NMR methodology over the previous method were discussed. Correlation between the new and standard NMR methodologies was significant for aloverose, glucose, malic acid, lactic acid, citric acid, and WLM (P < 0.0001, R(2) = 0.99). NMR was found to be suitable for the automated simultaneous quantitative determination of 13 parameters in A. vera.

Spectroscopic and Chemometric Analysis of Binary and Ternary Edible Oil Mixtures: Qualitative and Quantitative Study.

PubMed

Jović, Ozren; Smolić, Tomislav; Primožič, Ines; Hrenar, Tomica

2016-04-19

The aim of this study was to investigate the feasibility of FTIR-ATR spectroscopy coupled with the multivariate numerical methodology for qualitative and quantitative analysis of binary and ternary edible oil mixtures. Four pure oils (extra virgin olive oil, high oleic sunflower oil, rapeseed oil, and sunflower oil), as well as their 54 binary and 108 ternary mixtures, were analyzed using FTIR-ATR spectroscopy in combination with principal component and discriminant analysis, partial least-squares, and principal component regression. It was found that the composition of all 166 samples can be excellently represented using only the first three principal components describing 98.29% of total variance in the selected spectral range (3035-2989, 1170-1140, 1120-1100, 1093-1047, and 930-890 cm(-1)). Factor scores in 3D space spanned by these three principal components form a tetrahedral-like arrangement: pure oils being at the vertices, binary mixtures at the edges, and ternary mixtures on the faces of a tetrahedron. To confirm the validity of results, we applied several cross-validation methods. Quantitative analysis was performed by minimization of root-mean-square error of cross-validation values regarding the spectral range, derivative order, and choice of method (partial least-squares or principal component regression), which resulted in excellent predictions for test sets (R(2) > 0.99 in all cases). Additionally, experimentally more demanding gas chromatography analysis of fatty acid content was carried out for all specimens, confirming the results obtained by FTIR-ATR coupled with principal component analysis. However, FTIR-ATR provided a considerably better model for prediction of mixture composition than gas chromatography, especially for high oleic sunflower oil.

Autonomous frequency domain identification: Theory and experiment

NASA Technical Reports Server (NTRS)

Yam, Yeung; Bayard, D. S.; Hadaegh, F. Y.; Mettler, E.; Milman, M. H.; Scheid, R. E.

1989-01-01

The analysis, design, and on-orbit tuning of robust controllers require more information about the plant than simply a nominal estimate of the plant transfer function. Information is also required concerning the uncertainty in the nominal estimate, or more generally, the identification of a model set within which the true plant is known to lie. The identification methodology that was developed and experimentally demonstrated makes use of a simple but useful characterization of the model uncertainty based on the output error. This is a characterization of the additive uncertainty in the plant model, which has found considerable use in many robust control analysis and synthesis techniques. The identification process is initiated by a stochastic input u which is applied to the plant p giving rise to the output. Spectral estimation (h = P sub uy/P sub uu) is used as an estimate of p and the model order is estimated using the produce moment matrix (PMM) method. A parametric model unit direction vector p is then determined by curve fitting the spectral estimate to a rational transfer function. The additive uncertainty delta sub m = p - unit direction vector p is then estimated by the cross spectral estimate delta = P sub ue/P sub uu where e = y - unit direction vectory y is the output error, and unit direction vector y = unit direction vector pu is the computed output of the parametric model subjected to the actual input u. The experimental results demonstrate the curve fitting algorithm produces the reduced-order plant model which minimizes the additive uncertainty. The nominal transfer function estimate unit direction vector p and the estimate delta of the additive uncertainty delta sub m are subsequently available to be used for optimization of robust controller performance and stability.

Developing Methods for Fraction Cover Estimation Toward Global Mapping of Ecosystem Composition

NASA Astrophysics Data System (ADS)

Roberts, D. A.; Thompson, D. R.; Dennison, P. E.; Green, R. O.; Kokaly, R. F.; Pavlick, R.; Schimel, D.; Stavros, E. N.

2016-12-01

Terrestrial vegetation seldom covers an entire pixel due to spatial mixing at many scales. Estimating the fractional contributions of photosynthetic green vegetation (GV), non-photosynthetic vegetation (NPV), and substrate (soil, rock, etc.) to mixed spectra can significantly improve quantitative remote measurement of terrestrial ecosystems. Traditional methods for estimating fractional vegetation cover rely on vegetation indices that are sensitive to variable substrate brightness, NPV and sun-sensor geometry. Spectral mixture analysis (SMA) is an alternate framework that provides estimates of fractional cover. However, simple SMA, in which the same set of endmembers is used for an entire image, fails to account for natural spectral variability within a cover class. Multiple Endmember Spectral Mixture Analysis (MESMA) is a variant of SMA that allows the number and types of pure spectra to vary on a per-pixel basis, thereby accounting for endmember variability and generating more accurate cover estimates, but at a higher computational cost. Routine generation and delivery of GV, NPV, and substrate (S) fractions using MESMA is currently in development for large, diverse datasets acquired by the Airborne Visible Infrared Imaging Spectrometer (AVIRIS). We present initial results, including our methodology for ensuring consistency and generalizability of fractional cover estimates across a wide range of regions, seasons, and biomes. We also assess uncertainty and provide a strategy for validation. GV, NPV, and S fractions are an important precursor for deriving consistent measurements of ecosystem parameters such as plant stress and mortality, functional trait assessment, disturbance susceptibility and recovery, and biomass and carbon stock assessment. Copyright 2016 California Institute of Technology. All Rights Reserved. We acknowledge support of the US Government, NASA, the Earth Science Division and Terrestrial Ecology program.

Chemometric analysis for discrimination of extra virgin olive oils from whole and stoned olive pastes.

PubMed

De Luca, Michele; Restuccia, Donatella; Clodoveo, Maria Lisa; Puoci, Francesco; Ragno, Gaetano

2016-07-01

Chemometric discrimination of extra virgin olive oils (EVOO) from whole and stoned olive pastes was carried out by using Fourier transform infrared (FTIR) data and partial least squares-discriminant analysis (PLS1-DA) approach. Four Italian commercial EVOO brands, all in both whole and stoned version, were considered in this study. The adopted chemometric methodologies were able to describe the different chemical features in phenolic and volatile compounds contained in the two types of oil by using unspecific IR spectral information. Principal component analysis (PCA) was employed in cluster analysis to capture data patterns and to highlight differences between technological processes and EVOO brands. The PLS1-DA algorithm was used as supervised discriminant analysis to identify the different oil extraction procedures. Discriminant analysis was extended to the evaluation of possible adulteration by addition of aliquots of oil from whole paste to the most valuable oil from stoned olives. The statistical parameters from external validation of all the PLS models were very satisfactory, with low root mean square error of prediction (RMSEP) and relative error (RE%). Copyright © 2016 Elsevier Ltd. All rights reserved.

Influence of stereoelectronic effects on the non-opioid analgesics gaboxadol and gaboxadol hydrochloride: Spectral and DFT study

NASA Astrophysics Data System (ADS)

Leenaraj, D. R.; Joe, I. Hubert

2018-05-01

The stereoelectronic properties of the molecular structure of most stable conformers of gaboxadol and gaboxadol hydrochloride have been studied using DFT/B3P86-LANL2DZ methodology. The energies of stable conformers of gaboxadol and gaboxadol hydrochloride are -494.2689 and -510.0117 hartrees, respectively. The stability of the molecules arising from stereoelectronic interactions, leading to its bioactivity, has been confirmed using natural bond orbital analysis. The natural bond orbital analysis of donor-acceptor (σ→σ* and n→σ*) interactions showed that the stereoelectronic hyperconjugative and anomeric interactions are exhibited in gaboxadol hydrochloride and gaboxadol, respectively. Lengthening of the axial and equatorial C-H bond lengths and natural population analysis support these results. Spectral features of gaboxadol hydrochloride have been explored by the Fourier transform infrared, Raman and Nuclear magnetic resonance spectroscopic techniques combined with density functional theory computations. NH+ … Cl- hydrogen bonding has been noticeable as a broad and strong absorption in the 2800-2400 cm-1 region. Broad peaks obtained by proton NMR are a result of the quadrupole effect of the N+ atom. Docking studies using representative GABA receptor crystal structures revealed that molecules containing azinane and isoxazole cores fit within the ligand binding domains, and the gaboxadol hydrochloride molecule shows the best binding energy with the 3D32 GABA receptor. Also, gaboxadol hydrochloride has obtained a high value of HOMO energy and a narrow HOMO- LUMO energy gap, which enhances reactivity.

Preliminary evaluation of the Environmental Research Institute of Michigan crop calendar shift algorithm for estimation of spring wheat development stage. [North Dakota, South Dakota, Montana, and Minnesota

NASA Technical Reports Server (NTRS)

Phinney, D. E. (Principal Investigator)

1980-01-01

An algorithm for estimating spectral crop calendar shifts of spring small grains was applied to 1978 spring wheat fields. The algorithm provides estimates of the date of peak spectral response by maximizing the cross correlation between a reference profile and the observed multitemporal pattern of Kauth-Thomas greenness for a field. A methodology was developed for estimation of crop development stage from the date of peak spectral response. Evaluation studies showed that the algorithm provided stable estimates with no geographical bias. Crop development stage estimates had a root mean square error near 10 days. The algorithm was recommended for comparative testing against other models which are candidates for use in AgRISTARS experiments.

Spectral diffraction efficiency characterization of broadband diffractive optical elements.

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

Choi, Junoh; Cruz-Cabrera, Alvaro Augusto; Tanbakuchi, Anthony

Diffractive optical elements, with their thin profile and unique dispersion properties, have been studied and utilized in a number of optical systems, often yielding smaller and lighter systems. Despite the interest in and study of diffractive elements, the application has been limited to narrow spectral bands. This is due to the etch depths, which are optimized for optical path differences of only a single wavelength, consequently leading to rapid decline in efficiency as the working wavelength shifts away from the design wavelength. Various broadband diffractive design methodologies have recently been developed that improve spectral diffraction efficiency and expand the workingmore » bandwidth of diffractive elements. We have developed diffraction efficiency models and utilized the models to design, fabricate, and test two such extended bandwidth diffractive designs.« less

Statistical Frequency-Dependent Analysis of Trial-to-Trial Variability in Single Time Series by Recurrence Plots.

PubMed

Tošić, Tamara; Sellers, Kristin K; Fröhlich, Flavio; Fedotenkova, Mariia; Beim Graben, Peter; Hutt, Axel

2015-01-01

For decades, research in neuroscience has supported the hypothesis that brain dynamics exhibits recurrent metastable states connected by transients, which together encode fundamental neural information processing. To understand the system's dynamics it is important to detect such recurrence domains, but it is challenging to extract them from experimental neuroscience datasets due to the large trial-to-trial variability. The proposed methodology extracts recurrent metastable states in univariate time series by transforming datasets into their time-frequency representations and computing recurrence plots based on instantaneous spectral power values in various frequency bands. Additionally, a new statistical inference analysis compares different trial recurrence plots with corresponding surrogates to obtain statistically significant recurrent structures. This combination of methods is validated by applying it to two artificial datasets. In a final study of visually-evoked Local Field Potentials in partially anesthetized ferrets, the methodology is able to reveal recurrence structures of neural responses with trial-to-trial variability. Focusing on different frequency bands, the δ-band activity is much less recurrent than α-band activity. Moreover, α-activity is susceptible to pre-stimuli, while δ-activity is much less sensitive to pre-stimuli. This difference in recurrence structures in different frequency bands indicates diverse underlying information processing steps in the brain.

Statistical Frequency-Dependent Analysis of Trial-to-Trial Variability in Single Time Series by Recurrence Plots

PubMed Central

Tošić, Tamara; Sellers, Kristin K.; Fröhlich, Flavio; Fedotenkova, Mariia; beim Graben, Peter; Hutt, Axel

2016-01-01

For decades, research in neuroscience has supported the hypothesis that brain dynamics exhibits recurrent metastable states connected by transients, which together encode fundamental neural information processing. To understand the system's dynamics it is important to detect such recurrence domains, but it is challenging to extract them from experimental neuroscience datasets due to the large trial-to-trial variability. The proposed methodology extracts recurrent metastable states in univariate time series by transforming datasets into their time-frequency representations and computing recurrence plots based on instantaneous spectral power values in various frequency bands. Additionally, a new statistical inference analysis compares different trial recurrence plots with corresponding surrogates to obtain statistically significant recurrent structures. This combination of methods is validated by applying it to two artificial datasets. In a final study of visually-evoked Local Field Potentials in partially anesthetized ferrets, the methodology is able to reveal recurrence structures of neural responses with trial-to-trial variability. Focusing on different frequency bands, the δ-band activity is much less recurrent than α-band activity. Moreover, α-activity is susceptible to pre-stimuli, while δ-activity is much less sensitive to pre-stimuli. This difference in recurrence structures in different frequency bands indicates diverse underlying information processing steps in the brain. PMID:26834580

A simplified calculation procedure for mass isotopomer distribution analysis (MIDA) based on multiple linear regression.

PubMed

Fernández-Fernández, Mario; Rodríguez-González, Pablo; García Alonso, J Ignacio

2016-10-01

We have developed a novel, rapid and easy calculation procedure for Mass Isotopomer Distribution Analysis based on multiple linear regression which allows the simultaneous calculation of the precursor pool enrichment and the fraction of newly synthesized labelled proteins (fractional synthesis) using linear algebra. To test this approach, we used the peptide RGGGLK as a model tryptic peptide containing three subunits of glycine. We selected glycine labelled in two 13 C atoms ( 13 C 2 -glycine) as labelled amino acid to demonstrate that spectral overlap is not a problem in the proposed methodology. The developed methodology was tested first in vitro by changing the precursor pool enrichment from 10 to 40% of 13 C 2 -glycine. Secondly, a simulated in vivo synthesis of proteins was designed by combining the natural abundance RGGGLK peptide and 10 or 20% 13 C 2 -glycine at 1 : 1, 1 : 3 and 3 : 1 ratios. Precursor pool enrichments and fractional synthesis values were calculated with satisfactory precision and accuracy using a simple spreadsheet. This novel approach can provide a relatively rapid and easy means to measure protein turnover based on stable isotope tracers. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Stability analysis of a deterministic dose calculation for MRI-guided radiotherapy.

PubMed

Zelyak, O; Fallone, B G; St-Aubin, J

2017-12-14

Modern effort in radiotherapy to address the challenges of tumor localization and motion has led to the development of MRI guided radiotherapy technologies. Accurate dose calculations must properly account for the effects of the MRI magnetic fields. Previous work has investigated the accuracy of a deterministic linear Boltzmann transport equation (LBTE) solver that includes magnetic field, but not the stability of the iterative solution method. In this work, we perform a stability analysis of this deterministic algorithm including an investigation of the convergence rate dependencies on the magnetic field, material density, energy, and anisotropy expansion. The iterative convergence rate of the continuous and discretized LBTE including magnetic fields is determined by analyzing the spectral radius using Fourier analysis for the stationary source iteration (SI) scheme. The spectral radius is calculated when the magnetic field is included (1) as a part of the iteration source, and (2) inside the streaming-collision operator. The non-stationary Krylov subspace solver GMRES is also investigated as a potential method to accelerate the iterative convergence, and an angular parallel computing methodology is investigated as a method to enhance the efficiency of the calculation. SI is found to be unstable when the magnetic field is part of the iteration source, but unconditionally stable when the magnetic field is included in the streaming-collision operator. The discretized LBTE with magnetic fields using a space-angle upwind stabilized discontinuous finite element method (DFEM) was also found to be unconditionally stable, but the spectral radius rapidly reaches unity for very low-density media and increasing magnetic field strengths indicating arbitrarily slow convergence rates. However, GMRES is shown to significantly accelerate the DFEM convergence rate showing only a weak dependence on the magnetic field. In addition, the use of an angular parallel computing strategy is shown to potentially increase the efficiency of the dose calculation.

Stability analysis of a deterministic dose calculation for MRI-guided radiotherapy

NASA Astrophysics Data System (ADS)

Zelyak, O.; Fallone, B. G.; St-Aubin, J.

2018-01-01

Modern effort in radiotherapy to address the challenges of tumor localization and motion has led to the development of MRI guided radiotherapy technologies. Accurate dose calculations must properly account for the effects of the MRI magnetic fields. Previous work has investigated the accuracy of a deterministic linear Boltzmann transport equation (LBTE) solver that includes magnetic field, but not the stability of the iterative solution method. In this work, we perform a stability analysis of this deterministic algorithm including an investigation of the convergence rate dependencies on the magnetic field, material density, energy, and anisotropy expansion. The iterative convergence rate of the continuous and discretized LBTE including magnetic fields is determined by analyzing the spectral radius using Fourier analysis for the stationary source iteration (SI) scheme. The spectral radius is calculated when the magnetic field is included (1) as a part of the iteration source, and (2) inside the streaming-collision operator. The non-stationary Krylov subspace solver GMRES is also investigated as a potential method to accelerate the iterative convergence, and an angular parallel computing methodology is investigated as a method to enhance the efficiency of the calculation. SI is found to be unstable when the magnetic field is part of the iteration source, but unconditionally stable when the magnetic field is included in the streaming-collision operator. The discretized LBTE with magnetic fields using a space-angle upwind stabilized discontinuous finite element method (DFEM) was also found to be unconditionally stable, but the spectral radius rapidly reaches unity for very low-density media and increasing magnetic field strengths indicating arbitrarily slow convergence rates. However, GMRES is shown to significantly accelerate the DFEM convergence rate showing only a weak dependence on the magnetic field. In addition, the use of an angular parallel computing strategy is shown to potentially increase the efficiency of the dose calculation.

Corrigendum to "Stability analysis of a deterministic dose calculation for MRI-guided radiotherapy".

PubMed

Zelyak, Oleksandr; Fallone, B Gino; St-Aubin, Joel

2018-03-12

Modern effort in radiotherapy to address the challenges of tumor localization and motion has led to the development of MRI guided radiotherapy technologies. Accurate dose calculations must properly account for the effects of the MRI magnetic fields. Previous work has investigated the accuracy of a deterministic linear Boltzmann transport equation (LBTE) solver that includes magnetic field, but not the stability of the iterative solution method. In this work, we perform a stability analysis of this deterministic algorithm including an investigation of the convergence rate dependencies on the magnetic field, material density, energy, and anisotropy expansion. The iterative convergence rate of the continuous and discretized LBTE including magnetic fields is determined by analyzing the spectral radius using Fourier analysis for the stationary source iteration (SI) scheme. The spectral radius is calculated when the magnetic field is included (1) as a part of the iteration source, and (2) inside the streaming-collision operator. The non-stationary Krylov subspace solver GMRES is also investigated as a potential method to accelerate the iterative convergence, and an angular parallel computing methodology is investigated as a method to enhance the efficiency of the calculation. SI is found to be unstable when the magnetic field is part of the iteration source, but unconditionally stable when the magnetic field is included in the streaming-collision operator. The discretized LBTE with magnetic fields using a space-angle upwind stabilized discontinuous finite element method (DFEM) was also found to be unconditionally stable, but the spectral radius rapidly reaches unity for very low density media and increasing magnetic field strengths indicating arbitrarily slow convergence rates. However, GMRES is shown to significantly accelerate the DFEM convergence rate showing only a weak dependence on the magnetic field. In addition, the use of an angular parallel computing strategy is shown to potentially increase the efficiency of the dose calculation. © 2018 Institute of Physics and Engineering in Medicine.

Advanced methodology to determine plant stresses using in-situ spectral data

NASA Astrophysics Data System (ADS)

Polinova, Maria; Brook, Anna; Housh, Mashor

2017-04-01

Fluorescence method in remote sensing has long been a traditional method estimating plant state. Vegetation indices (VIs) are tool for assessment plants' state based on its spectral characteristics. During the last half-century, in this domain were developed many vegetation indices and even more modifications of these indices. Nowadays, visible range across electromagnetic waves allows assessing plants' health and calculating its physical parameters. One of the VI's capabilities is detecting stress in plants. This approach has application in different areas. For discerning external environment (unnatural) stress from features of plant's development most of VIs have border values for greenness and health. This is the reason for these methods to be superficial and insufficient detecting and estimating stresses on the early stages. This limits plays especial importance in agriculture. Late stress detection leads to irreversible damage in crops and yield loss. We propose new principle of VI analysis for determination unnatural stress on early stages. Novelty of this method is common consideration several VIs related to plant's pigmentation: chlorophyll, carotenoids and anthocyanins. We have tasted this method on two agriculture fields: tomatoes and cotton. The goal of study was to determinate water crop stress at its beginning. A single VI shows reactions on emergence growth stage, fruit producing and ripening phase. It was hard to isolate crops' reaction on water from reaction on growth changes. Nevertheless, we have noted that there is correlation between chlorophyll VIs and carotenoid VIs. The correlation strength was depended on stress type. Based on common VIs analysis we were able to identify dryness and over irrigation stress. In addition, we have determine reaction on fertilizers input. Common VIs analysis can improve existing fluorescence method of remote sensing monitoring. It can find application in areas where the early plant's stress detection is very impotent (e.g. agriculture). Another advantage of this method is identifying stress type. It can increase the role of spectral data for design making.

Free and Convectively Coupled Equatorial Waves Simulated by CMIP5 Climate Models

NASA Astrophysics Data System (ADS)

Marques, Carlos A. F.; Castanheira, José M.

2015-04-01

It is well known that precipitation in the equatorial belt does not occur randomly, but is often organized into synoptic to planetary-scale disturbances with time scales smaller than a season. Several studies have shown that a large fraction of the convection variability in such disturbances is associated with dynamical Equatorial Waves, such as the Kelvin, Equatorial Rossby, Mixed Rossby-Gravity, Eastward and Westward Inertio-Gravity waves (e.g. Kiladis et al., Rev. Geophys., 2009). The horizontal structures and dispersion characteristics of such Convectively Coupled Equatorial Waves (CCEWs) correspond to the solutions of the shallow water (SW) equations on an equatorial β-plane obtained by Matsuno (J. Meteor. Soc. Japan, 1966). CCEWs have broad impacts within the tropics, but their simulation in general circulation models is still problematic. Using space-time spectral analyses of a proxy field for tropical convection (e.g. outgoing long wave radiation (OLR)), it has been shown the existence of spectral peaks aligned along the dispersion curves of equatorially trapped wave modes of SW theory, which have been interpreted as the effect of equatorial wave processes (e.g. Takayabu, J. Meteor. Soc. Japan, 1994; Wheeler and Kiladis, JAS, 1999). However, different equatorial modes may not be well separated in the wavenumber-frequency domain due to a vertical variation of the horizontal basic flow, that may introduce Doppler shiftings and changes in the vertical heating profiles which may distort the theoretical dispersion curves (Yang et al., JAS, 2003). In this communication, we present a new methodology for the diagnosis of CCEWs, which is based on a pre-filtering of the geopotential and horizontal wind, via three-dimensional (3-D) normal mode functions of the adiabatic linearized equations of a resting atmosphere, followed by a space-time power and cross spectral analysis applied to the 3-D normal mode filtered fields and the OLR (or other fields that may be proxies of tropical convection) to identify the spectral regions of coherence. The advantage of such an approach is that the theoretical vertical as well as horizontal structure functions are taken into account in the projection method, and so the structures obtained are better defined with respect to the theoretical normal modes of a 3-D atmosphere compared to other approaches. The methodology has been applied to the (u,v,φ) and OLR fields simulated by various of the most recent climate models (CMIP5). The methodology has been also applied to the ERA-Interim geopotential and horizontal wind fields and to the interpolated OLR data produced by the National Oceanic and Atmospheric Administration, against which model simulations are evaluated. This new diagnosis method permits a direct detection of various types of equatorial waves, compares the dispersion characteristics of the coupled waves with the theoretical dispersion curves and allows an identification of which vertical modes are more involved in the convection. Moreover, it is able to show the existence of free dry waves and moist coupled waves with a common vertical structure, which is in conformity with the effect of convective heating/cooling on the effective static stability, as deduced from the gross moist stability concept (Kiladis et al., Rev. Geophys., 2009). The methodology is also sensitive to wave's interactions. Deficiencies found in the models' simulations should help the identification of which physical processes need to be improved in climate models.

Possibility of successive SRXFA use along with chemical-spectral methods for palladium analysis in geological samples

NASA Astrophysics Data System (ADS)

Kislov, E. V.; Kulikov, A. A.; Kulikova, A. B.

1989-10-01

Samples of basit-ultrabasit rocks and NiCu ores of the Ioko-Dovyren and Chaya massifs were analysed by SRXFA and a chemical-spectral method. SRXFA perfectly satisfies the quantitative noble-metals analysis of ore-free rocks. Combination of SRXFA and chemical-spectral analysis has good prospects. After analysis of a great number of samples by SRXFA it is necessary to select samples which would show minimal and maximal results for the chemical-spectral method.

The vibrational spectroscopic studies and molecular property analysis of Estradiol, Tamoxifen and their interaction by density functional theory

NASA Astrophysics Data System (ADS)

Borah, Mukunda Madhab; Gomti Devi, Th.

2018-07-01

In the present work Tamoxifen, Estradiol and their interaction are studied using the experimental and theoretical methodologies. The spectral characterization was made by using Raman, FTIR, DFT and VEDA calculation. The optimization of the molecules have been studied using basis set B3LYP/6-31 G(d,p). Complete vibrational assignment of Tamoxifen, Estradiol and Estradiol + Tamoxifen have been attempted and the potential energy distribution and normal mode analysis had also been carried out to determine the contributions of bond oscillators in each normal mode. We have optimized several binding modes of Estradiol and Tamoxifen and taken the lowest energy conformer in our interest. The molecular geometry, HOMO-LUMO energy gap, molecular hardness (η), ionization energy (IE), electron affinity (EA), total energy and dipole moment were analyzed. The observed experimental and the scaled theoretical results were found in good agreement.

Evaluation of reforested areas using LANDSAT imagery

NASA Technical Reports Server (NTRS)

Dejesusparada, N. (Principal Investigator); Filho, P. H.; Shimabukuro, Y. E.

1978-01-01

The author has identified the following significant results. Visual and automatic interpretation of LANDSAT imagery was used to classify the general Pinus and Eucalyptus according to their age and species. A methodology was derived, based on training areas, to define the legend and spectral characteristics of the analyzed classes. Imager analysis of the training areas show that Pinus taeda is separable from the other Pinus species based on JM distance measurement. No difference of JM measurements was observed among Eucalyptus species. Two classes of Eucalyptus were separated according to their ages: those under and those over two years of age. Channel 6 and 7 were suitable for the discrimination of the reforested classes. Channel 5 was efficient to separated reforested areas from nonforested targets in the region. The automatic analysis shows the highest classification precision was obtained for Eucalyptus over two years of age (95.12 percent).

Fiber optic spectrophotometry monitoring of plant nutrient deficiency under hydroponic culture conditions

NASA Astrophysics Data System (ADS)

Liew, Oi Wah; Boey, William S. L.; Asundi, Anand K.; Chen, Jun-Wei; He, Duo-Min

1999-05-01

In this paper, fiber optic spectrophotometry (FOSpectr) was adapted to provide early detection of plant nutrient deficiency by measuring leaf spectral reflectance variation resulting from nutrient stress. Leaf reflectance data were obtained form a local vegetable crop, Brassica chinensis var parachinensis (Bailey), grown in nitrate-nitrogen (N)- and calcium (Ca)- deficient hydroponics nutrient solution. FOSpectr analysis showed significant differences in leaf reflectance within the first four days after subjecting plants to nutrient-deficient media. Recovery of the nutrient-stressed plants could also be detected after transferring them back to complete nutrient solution. In contrast to FOSpectr, plant response to nitrogen and calcium deficiency in terms of reduced growth and tissue elemental levels was slower and less pronounced. Thus, this study demonstrated the feasibility of using FOSpectr methodology as a non-destructive alternative to augment current methods of plant nutrient analysis.

An efficient approach to integrated MeV ion imaging.

PubMed

Nikbakht, T; Kakuee, O; Solé, V A; Vosuoghi, Y; Lamehi-Rachti, M

2018-03-01

An ionoluminescence (IL) spectral imaging system, besides the common MeV ion imaging facilities such as µ-PIXE and µ-RBS, is implemented at the Van de Graaff laboratory of Tehran. A versatile processing software is required to handle the large amount of data concurrently collected in µ-IL and common MeV ion imaging measurements through the respective methodologies. The open-source freeware PyMca, with image processing and multivariate analysis capabilities, is employed to simultaneously process common MeV ion imaging and µ-IL data. Herein, the program was adapted to support the OM_DAQ listmode data format. The appropriate performance of the µ-IL data acquisition system is confirmed through a case study. Moreover, the capabilities of the software for simultaneous analysis of µ-PIXE and µ-RBS experimental data are presented. Copyright © 2017 Elsevier B.V. All rights reserved.

A comparison of different strategies in multivariate regression models for the direct determination of Mn, Cr, and Ni in steel samples using laser-induced breakdown spectroscopy

NASA Astrophysics Data System (ADS)

Luna, Aderval S.; Gonzaga, Fabiano B.; da Rocha, Werickson F. C.; Lima, Igor C. A.

2018-01-01

Laser-induced breakdown spectroscopy (LIBS) analysis was carried out on eleven steel samples to quantify the concentrations of chromium, nickel, and manganese. LIBS spectral data were correlated to known concentrations of the samples using different strategies in partial least squares (PLS) regression models. For the PLS analysis, one predictive model was separately generated for each element, while different approaches were used for the selection of variables (VIP: variable importance in projection and iPLS: interval partial least squares) in the PLS model to quantify the contents of the elements. The comparison of the performance of the models showed that there was no significant statistical difference using the Wilcoxon signed rank test. The elliptical joint confidence region (EJCR) did not detect systematic errors in these proposed methodologies for each metal.

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

Ferreras, Ignacio; Trujillo, Ignacio, E-mail: i.ferreras@ucl.ac.uk

At the core of the standard cosmological model lies the assumption that the redshift of distant galaxies is independent of photon wavelength. This invariance of cosmological redshift with wavelength is routinely found in all galaxy spectra with a precision of Δ z ∼ 10{sup −4}. The combined use of approximately half a million high-quality galaxy spectra from the Sloan Digital Sky Survey (SDSS) allows us to explore this invariance down to a nominal precision in redshift of 10{sup −6} (statistical). Our analysis is performed over the redshift interval 0.02 < z < 0.25. We use the centroids of spectral linesmore » over the 3700–6800 Å rest-frame optical window. We do not find any difference in redshift between the blue and red sides down to a precision of 10{sup −6} at z ≲ 0.1 and 10{sup −5} at 0.1 ≲ z ≲ 0.25 (i.e., at least an order of magnitude better than with single galaxy spectra). This is the first time the wavelength-independence of the (1 + z ) redshift law is confirmed over a wide spectral window at this precision level. This result holds independently of the stellar population of the galaxies and their kinematical properties. This result is also robust against wavelength calibration issues. The limited spectral resolution ( R ∼ 2000) of the SDSS data, combined with the asymmetric wavelength sampling of the spectral features in the observed restframe due to the (1 + z ) stretching of the lines, prevent our methodology from achieving a precision higher than 10{sup −5}, at z > 0.1. Future attempts to constrain this law will require high quality galaxy spectra at higher resolution ( R ≳ 10,000).« less

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

PubMed Central

Chen, Hongtao; Digman, Michelle A.

2015-01-01

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

Structural zeros in high-dimensional data with applications to microbiome studies.

PubMed

Kaul, Abhishek; Davidov, Ori; Peddada, Shyamal D

2017-07-01

This paper is motivated by the recent interest in the analysis of high-dimensional microbiome data. A key feature of these data is the presence of "structural zeros" which are microbes missing from an observation vector due to an underlying biological process and not due to error in measurement. Typical notions of missingness are unable to model these structural zeros. We define a general framework which allows for structural zeros in the model and propose methods of estimating sparse high-dimensional covariance and precision matrices under this setup. We establish error bounds in the spectral and Frobenius norms for the proposed estimators and empirically verify them with a simulation study. The proposed methodology is illustrated by applying it to the global gut microbiome data of Yatsunenko and others (2012. Human gut microbiome viewed across age and geography. Nature 486, 222-227). Using our methodology we classify subjects according to the geographical location on the basis of their gut microbiome. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Context-sensitive extraction of tree crown objects in urban areas using VHR satellite images

NASA Astrophysics Data System (ADS)

Ardila, Juan P.; Bijker, Wietske; Tolpekin, Valentyn A.; Stein, Alfred

2012-04-01

Municipalities need accurate and updated inventories of urban vegetation in order to manage green resources and estimate their return on investment in urban forestry activities. Earlier studies have shown that semi-automatic tree detection using remote sensing is a challenging task. This study aims to develop a reproducible geographic object-based image analysis (GEOBIA) methodology to locate and delineate tree crowns in urban areas using high resolution imagery. We propose a GEOBIA approach that considers the spectral, spatial and contextual characteristics of tree objects in the urban space. The study presents classification rules that exploit object features at multiple segmentation scales modifying the labeling and shape of image-objects. The GEOBIA methodology was implemented on QuickBird images acquired over the cities of Enschede and Delft (The Netherlands), resulting in an identification rate of 70% and 82% respectively. False negative errors concentrated on small trees and false positive errors in private gardens. The quality of crown boundaries was acceptable, with an overall delineation error <0.24 outside of gardens and backyards.

Optimization of process parameters for the production of collagen peptides from fish skin (Epinephelus malabaricus) using response surface methodology and its characterization.

PubMed

Hema, G S; Joshy, C G; Shyni, K; Chatterjee, Niladri S; Ninan, George; Mathew, Suseela

2017-02-01

The study optimized the hydrolysis conditions for the production of fish collagen peptides from skin of Malabar grouper ( Epinephelus malabaricus ) using response surface methodology. The hydrolysis was done with enzymes pepsin, papain and protease from bovine pancreas. Effects of process parameters viz: pH, temperature, enzyme substrate ratio and hydrolysis time of the three different enzymes on degree of hydrolysis were investigated. The optimum response of degree of hydrolysis was estimated to be 10, 20 and 28% respectively for pepsin, papain and protease. The functional properties of the product developed were analysed which showed changes in the properties from proteins to peptides. SDS-PAGE combined with MALDI TOF method was successfully applied to determine the molecular weight distribution of the hydrolysate. The electrophoretic pattern indicated that the molecular weights of peptides formed due to hydrolysis were nearly 2 kDa. MALDI TOF spectral analysis showed the developed hydrolysate contains peptides having molecular weight in the range below 2 kDa.

Application of Optimization Techniques to Spectrally Modulated, Spectrally Encoded Waveform Design

DTIC Science & Technology

2008-09-01

means y1 and y2 do indeed differ [22]. 43 To compare means for more than two populations, the Least Significant Difference ( LSD ) test may be used...case, the LSD test for a full-factorial design is given by LSD = tα 2 ,Ne−a √ 2 eTe n(Ne − a) , (2.41) where α is the significance level and ν = Ne − a...rejected if the means differ by more than the LSD [22]. 44 III. Methodology In many respects, the goal of this dissertation is to develop and

TES observations of the martian surface and atmosphere

USGS Publications Warehouse

Christensen, P.R.; Kieffer, H.H.; Pearl, J.C.; Conrath, B.; Malin, M.C.; Clark, R.C.; Morris, R.V.; Banfield, J.L.; Lane, M.D.; Smith, M.D.; Hamilton, V.E.; Kuzmin, R.O.

2000-01-01

The TES instrument is a Fourier transform Michelson interferometer operating with 10 or 5 cm-1 sampling int he thermal infared spectral region from 1700 to 200 cm-1 (~6 to 50 μm) where virtually all minerals have characteristic fundamental vibrational absorption bands (1, 2, 3, 4, 5, 6, 7, 8). The TES data used in this paper are among the 6x107 spectra collected during the early mapping phase of the MGS mission from southern hemisphere winter to early summer (aerocentric longitude, Ls, 107° to 297°. The methodology for separating the surface and atmospheric components of the radiance from Mars, which allows detailed analysis and interpretation of surface mineralogy (9, 10), is described in previous papers (10, 11).

A performance analysis of ensemble averaging for high fidelity turbulence simulations at the strong scaling limit

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

Makarashvili, Vakhtang; Merzari, Elia; Obabko, Aleksandr

We analyze the potential performance benefits of estimating expected quantities in large eddy simulations of turbulent flows using true ensembles rather than ergodic time averaging. Multiple realizations of the same flow are simulated in parallel, using slightly perturbed initial conditions to create unique instantaneous evolutions of the flow field. Each realization is then used to calculate statistical quantities. Provided each instance is sufficiently de-correlated, this approach potentially allows considerable reduction in the time to solution beyond the strong scaling limit for a given accuracy. This study focuses on the theory and implementation of the methodology in Nek5000, a massively parallelmore » open-source spectral element code.« less

A performance analysis of ensemble averaging for high fidelity turbulence simulations at the strong scaling limit

DOE PAGES

Makarashvili, Vakhtang; Merzari, Elia; Obabko, Aleksandr; ...

2017-06-07

We analyze the potential performance benefits of estimating expected quantities in large eddy simulations of turbulent flows using true ensembles rather than ergodic time averaging. Multiple realizations of the same flow are simulated in parallel, using slightly perturbed initial conditions to create unique instantaneous evolutions of the flow field. Each realization is then used to calculate statistical quantities. Provided each instance is sufficiently de-correlated, this approach potentially allows considerable reduction in the time to solution beyond the strong scaling limit for a given accuracy. This study focuses on the theory and implementation of the methodology in Nek5000, a massively parallelmore » open-source spectral element code.« less

Traveling reference spectroradiometer for routine quality assurance of spectral solar ultraviolet irradiance measurements.

PubMed

Gröbner, Julian; Schreder, Josef; Kazadzis, Stelios; Bais, Alkiviadis F; Blumthaler, Mario; Görts, Peter; Tax, Rick; Koskela, Tapani; Seckmeyer, Gunther; Webb, Ann R; Rembges, Diana

2005-09-01

A transportable reference spectroradiometer for measuring spectral solar ultraviolet irradiance has been developed and validated. The expanded uncertainty of solar irradiance measurements with this reference spectroradiometer, based on the described methodology, is 8.8% to 4.6%, depending on the wavelength and the solar zenith angle. The accuracy of the spectroradiometer was validated by repeated site visits to two European UV monitoring sites as well as by regular comparisons with the reference spectroradiometer of the European Reference Centre for UV radiation measurements in Ispra, Italy. The spectral solar irradiance measurements of the Quality Assurance of Spectral Ultraviolet Measurements in Europe through the Development of a Transportable Unit (QASUME) spectroradiometer and these three spectroradiometers have agreed to better than 6% during the ten intercomparison campaigns held from 2002 to 2004. If the differences in irradiance scales of as much as 2% are taken into account, the agreement is of the order of 4% over the wavelength range of 300-400 nm.

Aerosol properties from spectral extinction and backscatter estimated by an inverse Monte Carlo method.

PubMed

Ligon, D A; Gillespie, J B; Pellegrino, P

2000-08-20

The feasibility of using a generalized stochastic inversion methodology to estimate aerosol size distributions accurately by use of spectral extinction, backscatter data, or both is examined. The stochastic method used, inverse Monte Carlo (IMC), is verified with both simulated and experimental data from aerosols composed of spherical dielectrics with a known refractive index. Various levels of noise are superimposed on the data such that the effect of noise on the stability and results of inversion can be determined. Computational results show that the application of the IMC technique to inversion of spectral extinction or backscatter data or both can produce good estimates of aerosol size distributions. Specifically, for inversions for which both spectral extinction and backscatter data are used, the IMC technique was extremely accurate in determining particle size distributions well outside the wavelength range. Also, the IMC inversion results proved to be stable and accurate even when the data had significant noise, with a signal-to-noise ratio of 3.

Image-derived input function with factor analysis and a-priori information.

PubMed

Simončič, Urban; Zanotti-Fregonara, Paolo

2015-02-01

Quantitative PET studies often require the cumbersome and invasive procedure of arterial cannulation to measure the input function. This study sought to minimize the number of necessary blood samples by developing a factor-analysis-based image-derived input function (IDIF) methodology for dynamic PET brain studies. IDIF estimation was performed as follows: (a) carotid and background regions were segmented manually on an early PET time frame; (b) blood-weighted and tissue-weighted time-activity curves (TACs) were extracted with factor analysis; (c) factor analysis results were denoised and scaled using the voxels with the highest blood signal; (d) using population data and one blood sample at 40 min, whole-blood TAC was estimated from postprocessed factor analysis results; and (e) the parent concentration was finally estimated by correcting the whole-blood curve with measured radiometabolite concentrations. The methodology was tested using data from 10 healthy individuals imaged with [(11)C](R)-rolipram. The accuracy of IDIFs was assessed against full arterial sampling by comparing the area under the curve of the input functions and by calculating the total distribution volume (VT). The shape of the image-derived whole-blood TAC matched the reference arterial curves well, and the whole-blood area under the curves were accurately estimated (mean error 1.0±4.3%). The relative Logan-V(T) error was -4.1±6.4%. Compartmental modeling and spectral analysis gave less accurate V(T) results compared with Logan. A factor-analysis-based IDIF for [(11)C](R)-rolipram brain PET studies that relies on a single blood sample and population data can be used for accurate quantification of Logan-V(T) values.

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

Jornet, N; Carrasco de Fez, P; Jordi, O

Purpose: To evaluate the accuracy in total scatter factor (Sc,p) determination for small fields using commercial plastic scintillator detector (PSD). The manufacturer's spectral discrimination method to subtract Cerenkov light from the signal is discussed. Methods: Sc,p for field sizes ranging from 0.5 to 10 cm were measured using PSD Exradin (Standard Imaging) connected to two channel electrometer measuring the signals in two different spectral regions to subtract the Cerenkov signal from the PSD signal. A Pinpoint ionisation chamber 31006 (PTW) and a non-shielded semiconductor detector EFD (Scanditronix) were used for comparison. Measures were performed for a 6 MV X-ray beam.more » The Sc,p are measured at 10 cm depth in water for a SSD=100 cm and normalized to a 10'10 cm{sup 2} field size at the isocenter. All detectors were placed with their symmetry axis parallel to the beam axis.We followed the manufacturer's recommended calibration methodology to subtract the Cerenkov contribution to the signal as well as a modified method using smaller field sizes. The Sc,p calculated by using both calibration methodologies were compared. Results: Sc,p measured with the semiconductor and the PinPoint detectors agree, within 1.5%, for field sizes between 10'10 and 1'1 cm{sup 2}. Sc,p measured with the PSD using the manufacturer's calibration methodology were systematically 4% higher than those measured with the semiconductor detector for field sizes smaller than 5'5 cm{sup 2}. By using a modified calibration methodology for smalls fields and keeping the manufacturer calibration methodology for fields larger than 5'5cm{sup 2} field Sc,p matched semiconductor results within 2% field sizes larger than 1.5 cm. Conclusion: The calibration methodology proposed by the manufacturer is not appropriate for dose measurements in small fields. The calibration parameters are not independent of the incident radiation spectrum for this PSD. This work was partially financed by grant 2012 of Barcelona board of the AECC.« less

Inferring hidden causal relations between pathway members using reduced Google matrix of directed biological networks

PubMed Central

2018-01-01

Signaling pathways represent parts of the global biological molecular network which connects them into a seamless whole through complex direct and indirect (hidden) crosstalk whose structure can change during development or in pathological conditions. We suggest a novel methodology, called Googlomics, for the structural analysis of directed biological networks using spectral analysis of their Google matrices, using parallels with quantum scattering theory, developed for nuclear and mesoscopic physics and quantum chaos. We introduce analytical “reduced Google matrix” method for the analysis of biological network structure. The method allows inferring hidden causal relations between the members of a signaling pathway or a functionally related group of genes. We investigate how the structure of hidden causal relations can be reprogrammed as a result of changes in the transcriptional network layer during cancerogenesis. The suggested Googlomics approach rigorously characterizes complex systemic changes in the wiring of large causal biological networks in a computationally efficient way. PMID:29370181

Optical, Fluorescence with quantum analysis of hydrazine (1, 3- Dinitro Phenyl) by DFT and Ab initio approach

NASA Astrophysics Data System (ADS)

Cecily Mary Glory, D.; Sambathkumar, K.; Madivanane, R.; Velmurugan, G.; Gayathri, R.; Nithiyanantham, S.; Venkatachalapathy, M.; Rajkamal, N.

2018-07-01

Experimental and computational study of molecular structure, vibrational and UV-spectral analysis of Hydrazine (1, 3- Dinitrophenyl) (HDP) derivatives. The crystal was grown by slow cooling method and the crystalline perfection of single crystals was evaluated by high resolution X-ray diffractometry (HRXRD) using a multicrystal X-ray diffractometer. Fluorescence, FT-IR and FT-Raman spectra of HDP crystal were recorded. The assignments of the vibrational spectra have been carried out with the help of normal co-ordinate analysis (NCA) followed by scaled quantum force field methodology (SQMFF). NMR studies have confirmed respectively the crystal structure and functional groups of the grown crystal. The energy and oscillator strength calculated by Time-Dependent Density Functional Theory (TD-DFT) result complements the experimental findings. The calculated MESP, UV, HOMO-LUMO energies show that charge transfer done within the molecule. And various thermodynamic parameters are studied. Fukui determines the local reactive site of electrophilic, nucleophilic, descriptor.

Comprehensive gas chromatography coupled to mass spectrometry for the separation of pesticides in a very complex matrix.

PubMed

Mondello, Luigi; Casilli, Alessandro; Tranchida, Peter Quinto; Lo Presti, Maria; Dugo, Paola; Dugo, Giovanni

2007-11-01

The present research is focused on the development of a comprehensive two-dimensional gas chromatography-rapid scanning quadrupole mass spectrometric (GC x GC-qMS) methodology for the analysis of trace-amount pesticides contained in a complex real-world sample. Reliable peak assignment was carried out by using a recently developed, dedicated pesticide MS library (for comprehensive GC analysis), characterized by a twin-filter search procedure, the first based on a minimum degree of spectral similarity and the second on the interactive use of linear retention indices (LRI). The library was constructed by subjecting mixtures of commonly used pesticides to GC x GC-qMS analysis and then deriving their pure mass spectra and LRI values. In order to verify the effectiveness of the approach, a pesticide-contaminated red grapefruit extract was analysed. The certainty of peak assignment was attained by exploiting both the enhanced separation power of dual-oven GC x GC and the highly effective search procedure.

The E3Σ1+ (63S1)←A3Π0+(53P1) transition in CdAr revisited: The spectrum and new analysis of the E3Σ1+ Rydberg state interatomic potential.

PubMed

Urbańczyk, T; Krośnicki, M; Kędziorski, A; Koperski, J

2018-05-05

Revisited study of the E 3 Σ 1 + (6 3 S 1 )←A 3 Π 0+ (5 3 P 1 ) transition in CdAr using both theoretical and experimental approach is presented. Systematic detection of the E 3 Σ 1 + in ,υ'←A 3 Π 0+ ,υ″=6 transition frequencies with higher accuracy and spectrally narrower laser extended and improved analysis and simulation of the LIF excitation spectrum. More consistent characterization of the E 3 Σ 1 + in -Rydberg state inner well using inversed perturbation approach methodology was achieved. Free←bound transitions in the E 3 Σ 1 + in ←A 3 Π 0+ ,υ″=6 excitation were taken into account in the analysis and simulation of the recorded spectrum. The updated spectroscopic characterization of the A 3 Π 0+ state was also revisited. Copyright © 2018 Elsevier B.V. All rights reserved.

The E3Σ1+ (63S1) ← A3Π0+(53P1) transition in CdAr revisited: The spectrum and new analysis of the E3Σ1+ Rydberg state interatomic potential

NASA Astrophysics Data System (ADS)

Urbańczyk, T.; Krośnicki, M.; Kędziorski, A.; Koperski, J.

2018-05-01

Revisited study of the E3Σ1+ (63S1) ← A3Π0+(53P1) transition in CdAr using both theoretical and experimental approach is presented. Systematic detection of the E3Σ1+in,υ' ← A3Π0+,υ″ = 6 transition frequencies with higher accuracy and spectrally narrower laser extended and improved analysis and simulation of the LIF excitation spectrum. More consistent characterization of the E3Σ1+in-Rydberg state inner well using inversed perturbation approach methodology was achieved. Free ← bound transitions in the E3Σ1+in ← A3Π0+,υ″ = 6 excitation were taken into account in the analysis and simulation of the recorded spectrum. The updated spectroscopic characterization of the A3Π0+ state was also revisited.

Sustained modelling ability of artificial neural networks in the analysis of two pharmaceuticals (dextropropoxyphene and dipyrone) present in unequal concentrations.

PubMed

Cámara, María S; Ferroni, Félix M; De Zan, Mercedes; Goicoechea, Héctor C

2003-07-01

An improvement is presented on the simultaneous determination of two active ingredients present in unequal concentrations in injections. The analysis was carried out with spectrophotometric data and non-linear multivariate calibration methods, in particular artificial neural networks (ANNs). The presence of non-linearities caused by the major analyte concentrations which deviate from Beer's law was confirmed by plotting actual vs. predicted concentrations, and observing curvatures in the residuals for the estimated concentrations with linear methods. Mixtures of dextropropoxyphene and dipyrone have been analysed by using linear and non-linear partial least-squares (PLS and NPLSs) and ANNs. Notwithstanding the high degree of spectral overlap and the occurrence of non-linearities, rapid and simultaneous analysis has been achieved, with reasonably good accuracy and precision. A commercial sample was analysed by using the present methodology, and the obtained results show reasonably good agreement with those obtained by using high-performance liquid chromatography (HPLC) and a UV-spectrophotometric comparative methods.

Remote sensing of key grassland nutrients using hyperspectral techniques in KwaZulu-Natal, South Africa

NASA Astrophysics Data System (ADS)

Singh, Leeth; Mutanga, Onisimo; Mafongoya, Paramu; Peerbhay, Kabir

2017-07-01

The concentration of forage fiber content is critical in explaining the palatability of forage quality for livestock grazers in tropical grasslands. Traditional methods of determining forage fiber content are usually time consuming, costly, and require specialized laboratory analysis. With the potential of remote sensing technologies, determination of key fiber attributes can be made more accurately. This study aims to determine the effectiveness of known absorption wavelengths for detecting forage fiber biochemicals, neutral detergent fiber, acid detergent fiber, and lignin using hyperspectral data. Hyperspectral reflectance spectral measurements (350 to 2500 nm) of grass were collected and implemented within the random forest (RF) ensemble. Results show successful correlations between the known absorption features and the biochemicals with coefficients of determination (R2) ranging from 0.57 to 0.81 and root mean square errors ranging from 6.97 to 3.03 g/kg. In comparison, using the entire dataset, the study identified additional wavelengths for detecting fiber biochemicals, which contributes to the accurate determination of forage quality in a grassland environment. Overall, the results showed that hyperspectral remote sensing in conjunction with the competent RF ensemble could discriminate each key biochemical evaluated. This study shows the potential to upscale the methodology to a space-borne multispectral platform with similar spectral configurations for an accurate and cost effective mapping analysis of forage quality.

A hierarchical classification approach for recognition of low-density (LDPE) and high-density polyethylene (HDPE) in mixed plastic waste based on short-wave infrared (SWIR) hyperspectral imaging.

PubMed

Bonifazi, Giuseppe; Capobianco, Giuseppe; Serranti, Silvia

2018-06-05

The aim of this work was to recognize different polymer flakes from mixed plastic waste through an innovative hierarchical classification strategy based on hyperspectral imaging, with particular reference to low density polyethylene (LDPE) and high-density polyethylene (HDPE). A plastic waste composition assessment, including also LDPE and HDPE identification, may help to define optimal recycling strategies for product quality control. Correct handling of plastic waste is essential for its further "sustainable" recovery, maximizing the sorting performance in particular for plastics with similar characteristics as LDPE and HDPE. Five different plastic waste samples were chosen for the investigation: polypropylene (PP), LDPE, HDPE, polystyrene (PS) and polyvinyl chloride (PVC). A calibration dataset was realized utilizing the corresponding virgin polymers. Hyperspectral imaging in the short-wave infrared range (1000-2500nm) was thus applied to evaluate the different plastic spectral attributes finalized to perform their recognition/classification. After exploring polymer spectral differences by principal component analysis (PCA), a hierarchical partial least squares discriminant analysis (PLS-DA) model was built allowing the five different polymers to be recognized. The proposed methodology, based on hierarchical classification, is very powerful and fast, allowing to recognize the five different polymers in a single step. Copyright © 2018 Elsevier B.V. All rights reserved.

Laser desorption/ionization mass spectrometry for direct profiling and imaging of small molecules from raw biological materials

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

Cha, Sangwon

2008-01-01

Matrix-assisted laser desorption/ionization(MALDI) mass spectrometry(MS) has been widely used for analysis of biological molecules, especially macromolecules such as proteins. However, MALDI MS has a problem in small molecule (less than 1 kDa) analysis because of the signal saturation by organic matrixes in the low mass region. In imaging MS (IMS), inhomogeneous surface formation due to the co-crystallization process by organic MALDI matrixes limits the spatial resolution of the mass spectral image. Therefore, to make laser desorption/ionization (LDI) MS more suitable for mass spectral profiling and imaging of small molecules directly from raw biological tissues, LDI MS protocols with various alternativemore » assisting materials were developed and applied to many biological systems of interest. Colloidal graphite was used as a matrix for IMS of small molecules for the first time and methodologies for analyses of small metabolites in rat brain tissues, fruits, and plant tissues were developed. With rat brain tissues, the signal enhancement for cerebroside species by colloidal graphite was observed and images of cerebrosides were successfully generated by IMS. In addition, separation of isobaric lipid ions was performed by imaging tandem MS. Directly from Arabidopsis flowers, flavonoids were successfully profiled and heterogeneous distribution of flavonoids in petals was observed for the first time by graphite-assisted LDI(GALDI) IMS.« less

Optimal attributes for the object based detection of giant reed in riparian habitats: A comparative study between Airborne High Spatial Resolution and WorldView-2 imagery

NASA Astrophysics Data System (ADS)

Fernandes, Maria Rosário; Aguiar, Francisca C.; Silva, João M. N.; Ferreira, Maria Teresa; Pereira, José M. C.

2014-10-01

Giant reed is an aggressive invasive plant of riparian ecosystems in many sub-tropical and warm-temperate regions, including Mediterranean Europe. In this study we tested a set of geometric, spectral and textural attributes in an object based image analysis (OBIA) approach to map giant reed invasions in riparian habitats. Bagging Classification and Regression Tree were used to select the optimal attributes and to build the classification rules sets. Mapping accuracy was performed using landscape metrics and the Kappa coefficient to compare the topographical and geometric similarity between the giant reed patches obtained with the OBIA map and with a validation map derived from on-screen digitizing. The methodology was applied in two high spatial resolution images: an airborne multispectral imagery and the newly WorldView-2 imagery. A temporal coverage of the airborne multispectral images was radiometrically calibrated with the IR-Mad transformation and used to assess the influence of the phenological variability of the invader. We found that optimal attributes for giant reed OBIA detection are a combination of spectral, geometric and textural information, with different scoring selection depending on the spectral and spatial characteristics of the imagery. WorldView-2 showed higher mapping accuracy (Kappa coefficient of 77%) and spectral attributes, including the newly yellow band, were preferentially selected, although a tendency to overestimate the total invaded area, due to the low spatial resolution (2 m of pixel size vs. 50 cm) was observed. When airborne images were used, geometric attributes were primarily selected and a higher spatial detail of the invasive patches was obtained, due to the higher spatial resolution. However, in highly heterogeneous landscapes, the low spectral resolution of the airborne images (4 bands instead of the 8 of WorldView-2) reduces the capability to detect giant reed patches. Giant reed displays peculiar spectral and geometric traits, at leaf, canopy and stand level, which makes the OBIA approach a very suitable technique for management purposes.

PACKAGING CERTIFICATION PROGRAM METHODOLOGY FOR DETERMINING DOSE RATES FOR SMALL GRAM QUANTITIES IN SHIPPING PACKAGINGS

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

Nathan, S.; Loftin, B.; Abramczyk, G.

The Small Gram Quantity (SGQ) concept is based on the understanding that small amounts of hazardous materials, in this case radioactive materials (RAM), are significantly less hazardous than large amounts of the same materials. This paper describes a methodology designed to estimate an SGQ for several neutron and gamma emitting isotopes that can be shipped in a package compliant with 10 CFR Part 71 external radiation level limits regulations. These regulations require packaging for the shipment of radioactive materials, under both normal and accident conditions, to perform the essential functions of material containment, subcriticality, and maintain external radiation levels withinmore » the specified limits. By placing the contents in a helium leak-tight containment vessel, and limiting the mass to ensure subcriticality, the first two essential functions are readily met. Some isotopes emit sufficiently strong photon radiation that small amounts of material can yield a large dose rate outside the package. Quantifying the dose rate for a proposed content is a challenging issue for the SGQ approach. It is essential to quantify external radiation levels from several common gamma and neutron sources that can be safely placed in a specific packaging, to ensure compliance with federal regulations. The Packaging Certification Program (PCP) Methodology for Determining Dose Rate for Small Gram Quantities in Shipping Packagings provides bounding shielding calculations that define mass limits compliant with 10 CFR 71.47 for a set of proposed SGQ isotopes. The approach is based on energy superposition with dose response calculated for a set of spectral groups for a baseline physical packaging configuration. The methodology includes using the MCNP radiation transport code to evaluate a family of neutron and photon spectral groups using the 9977 shipping package and its associated shielded containers as the base case. This results in a set of multipliers for 'dose per particle' for each spectral group. For a given isotope, the source spectrum is folded with the response for each group. The summed contribution from all isotopes determines the total dose from the RAM in the container.« less

A stable pattern of EEG spectral coherence distinguishes children with autism from neuro-typical controls - a large case control study.

PubMed

Duffy, Frank H; Als, Heidelise

2012-06-26

The autism rate has recently increased to 1 in 100 children. Genetic studies demonstrate poorly understood complexity. Environmental factors apparently also play a role. Magnetic resonance imaging (MRI) studies demonstrate increased brain sizes and altered connectivity. Electroencephalogram (EEG) coherence studies confirm connectivity changes. However, genetic-, MRI- and/or EEG-based diagnostic tests are not yet available. The varied study results likely reflect methodological and population differences, small samples and, for EEG, lack of attention to group-specific artifact. Of the 1,304 subjects who participated in this study, with ages ranging from 1 to 18 years old and assessed with comparable EEG studies, 463 children were diagnosed with autism spectrum disorder (ASD); 571 children were neuro-typical controls (C). After artifact management, principal components analysis (PCA) identified EEG spectral coherence factors with corresponding loading patterns. The 2- to 12-year-old subsample consisted of 430 ASD- and 554 C-group subjects (n = 984). Discriminant function analysis (DFA) determined the spectral coherence factors' discrimination success for the two groups. Loading patterns on the DFA-selected coherence factors described ASD-specific coherence differences when compared to controls. Total sample PCA of coherence data identified 40 factors which explained 50.8% of the total population variance. For the 2- to 12-year-olds, the 40 factors showed highly significant group differences (P < 0.0001). Ten randomly generated split half replications demonstrated high-average classification success (C, 88.5%; ASD, 86.0%). Still higher success was obtained in the more restricted age sub-samples using the jackknifing technique: 2- to 4-year-olds (C, 90.6%; ASD, 98.1%); 4- to 6-year-olds (C, 90.9%; ASD 99.1%); and 6- to 12-year-olds (C, 98.7%; ASD, 93.9%). Coherence loadings demonstrated reduced short-distance and reduced, as well as increased, long-distance coherences for the ASD-groups, when compared to the controls. Average spectral loading per factor was wide (10.1 Hz). Classification success suggests a stable coherence loading pattern that differentiates ASD- from C-group subjects. This might constitute an EEG coherence-based phenotype of childhood autism. The predominantly reduced short-distance coherences may indicate poor local network function. The increased long-distance coherences may represent compensatory processes or reduced neural pruning. The wide average spectral range of factor loadings may suggest over-damped neural networks.

Identification of spectral phenotypes in age-related macular degeneration patients

NASA Astrophysics Data System (ADS)

Davis, Bert; Russell, Steven; Abramoff, Michael; Nemeth, Sheila C.; Barriga, E. Simon; Soliz, Peter

2007-02-01

The purpose of this study is to show that there exists a spectral characteristic that differentiates normal macular tissue from various types of genetic-based macular diseases. This paper demonstrates statistically that hyperspectral images of macular and other retinal tissue can be used to spectrally differentiate different forms of age-related macular degeneration. A hyperspectral fundus imaging device has been developed and tested for the purpose of collecting hyperspectral images of the human retina. A methodology based on partial least squares and ANOVA has been applied to determine the hyperspectral representation of individual spectral characteristics of retinal features. Each discrete tissue type in the retina has an identifiable spectral shape or signature which, when combined with spatial context, aids in detection of pathological features. Variations in the amount and distribution of various ocular pigments or the inclusion of additional biochemical substances will allow detection of pathological conditions prior to traditional histological presentation. Fundus imaging cameras are ubiquitous and are one of the most common imaging modalities used in documenting a patient's retinal state for diagnosis, e.g. remotely, or for monitoring the progression of an ocular disease. The added diagnostic information obtained with only a minor retro-fit of a specialized spectral camera will lead to new diagnostic information to the clinical ophthalmologist or eye-care specialist.

Spectral compression algorithms for the analysis of very large multivariate images

DOEpatents

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.

A Steady-State Kalman Predictor-Based Filtering Strategy for Non-Overlapping Sub-Band Spectral Estimation

PubMed Central

Li, Zenghui; Xu, Bin; Yang, Jian; Song, Jianshe

2015-01-01

This paper focuses on suppressing spectral overlap for sub-band spectral estimation, with which we can greatly decrease the computational complexity of existing spectral estimation algorithms, such as nonlinear least squares spectral analysis and non-quadratic regularized sparse representation. Firstly, our study shows that the nominal ability of the high-order analysis filter to suppress spectral overlap is greatly weakened when filtering a finite-length sequence, because many meaningless zeros are used as samples in convolution operations. Next, an extrapolation-based filtering strategy is proposed to produce a series of estimates as the substitutions of the zeros and to recover the suppression ability. Meanwhile, a steady-state Kalman predictor is applied to perform a linearly-optimal extrapolation. Finally, several typical methods for spectral analysis are applied to demonstrate the effectiveness of the proposed strategy. PMID:25609038

Method of multivariate spectral analysis

DOEpatents

Keenan, Michael R.; Kotula, Paul G.

2004-01-06

A method of determining the properties of a sample from measured spectral data collected from the sample by performing a multivariate spectral analysis. The method can include: generating a two-dimensional matrix A containing measured spectral data; providing a weighted spectral data matrix D by performing a weighting operation on matrix A; factoring D into the product of two matrices, C and S.sup.T, by performing a constrained alternating least-squares analysis of D=CS.sup.T, where C is a concentration intensity matrix and S is a spectral shapes matrix; unweighting C and S by applying the inverse of the weighting used previously; and determining the properties of the sample by inspecting C and S. This method can be used to analyze X-ray spectral data generated by operating a Scanning Electron Microscope (SEM) with an attached Energy Dispersive Spectrometer (EDS).

Using Reflectance Measurements to Determine Ecosystem Light Use Efficiency

NASA Astrophysics Data System (ADS)

Huemmrich, K. F.; Middleton, E. M.; Hall, F. G.; Knox, R. G.; Walter-Shea, E.; Verma, S. B.

2006-05-01

Understanding the dynamics of the global carbon cycle requires an accurate determination of the spatial and temporal distribution of photosynthetic CO2 uptake by terrestrial vegetation. Remote sensing observations may provide the spatially extensive observations required for this type of analysis. A light use efficiency model is one approach to modeling carbon fluxes driven by remotely sensed inputs. Photosynthetic down-regulation has been associated with changes in the apparent spectral reflectance of leaves and these responses may permit the estimation of ecosystem photosynthetic light use efficiency (LUE). At a prairie site in Oklahoma, CO2 flux measurements from an eddy covariance system along with biophysical data were collected through 1998 and 1999. During the growing seasons hyperspectral reflectance measurements were collected in nearby plots at multiple times in a day at approximately monthly intervals. LUE is calculated as the ratio of carbon uptake by the ecosystem and the fraction of photosynthetically active radiation (PAR) absorbed by green leaves. The LUE values are compared with reflectance indexes examining how relationships vary over hours, months, and years. For this system a number of different reflectance indexes have been found to correlate with LUE; including the Photochemical Reflectance Index (PRI) and the Structure Independent Pigment Index (SIPI); as well as spectral first derivatives at 460, 550, and 615nm; and second derivatives at 510 and 620nm. This methodology provides a nondestructive, repeatable, direct comparison between ecosystem carbon fluxes and spectral reflectance at scales relevant to remote sensing.

Modelling of celestial backgrounds

NASA Astrophysics Data System (ADS)

Hickman, Duncan L.; Smith, Moira I.; Lim, Jae-Wan; Jeon, Yun-Ho

2018-05-01

For applications where a sensor's image includes the celestial background, stars and Solar System Bodies compromise the ability of the sensor system to correctly classify a target. Such false targets are particularly significant for the detection of weak target signatures which only have a small relative angular motion. The detection of celestial features is well established in the visible spectral band. However, given the increasing sensitivity and low noise afforded by emergent infrared focal plane array technology together with larger and more efficient optics, the signatures of celestial features can also impact performance at infrared wavelengths. A methodology has been developed which allows the rapid generation of celestial signatures in any required spectral band using star data from star catalogues and other open-source information. Within this paper, the radiometric calculations are presented to determine the irradiance values of stars and planets in any spectral band.

The Critical Importance of Data Reduction Calibrations in the Interpretability of S-type Asteroid Spectra

NASA Technical Reports Server (NTRS)

Gaffey, Michael J.

2005-01-01

There is significant dispute concerning the interpretation and meteoritic affinities of S-type asteroids. Some of this arises from the use of inappropriate analysis methods and the derivation of conclusions which cannot be supported by those interpretive methodologies [1]. The most frequently applied inappropriate technique is curve matching. Whether matching spectra from a spectral library or mixing end-member spectra to match the asteroid spectrum, curve matching for S-type spectra suffers from a suite of weaknesses that are virtually impossible to overcome. Chief among these is the lack of a comprehensive comparison set. Lacking a complete library that includes both the mineralogical variations and the spectrally significant physical variations (e.g., particle size, petrographic relationships, etc.), curve matches are plagued with potential unresolved ambiguities. The other major weakness of virtually all curve matching efforts is that equal weight is given to matching all portions of the spectrum. In actuality, some portions of the spectrum (e.g., centers of absorption features) must be matched very accurately while other portions of the spectrum (e.g., continuum regions and overall slopes) do not require good matches since they are strongly effected by parameters unrelated to the mineralogy of the sample.

Landsat-faciliated vegetation classification of the Kenai National Wildlife Refuge and adjacent areas, Alaska

USGS Publications Warehouse

Talbot, S. S.; Shasby, M.B.; Bailey, T.N.

1985-01-01

A Landsat-based vegetation map was prepared for Kenai National Wildlife Refuge and adjacent lands, 2 million and 2.5 million acres respectively. The refuge lies within the middle boreal sub zone of south central Alaska. Seven major classes and sixteen subclasses were recognized: forest (closed needleleaf, needleleaf woodland, mixed); deciduous scrub (lowland and montane, subalpine); dwarf scrub (dwarf shrub tundra, lichen tundra, dwarf shrub and lichen tundra, dwarf shrub peatland, string bog/wetlands); herbaceous (graminoid meadows and marshes); scarcely vegetated areas ; water (clear, moderately turbid, highly turbid); and glaciers. The methodology employed a cluster-block technique. Sample areas were described based on a combination of helicopter-ground survey, aerial photo interpretation, and digital Landsat data. Major steps in the Landsat analysis involved: preprocessing (geometric connection), spectral class labeling of sample areas, derivation of statistical parameters for spectral classes, preliminary classification of the entree study area using a maximum-likelihood algorithm, and final classification through ancillary information such as digital elevation data. The vegetation map (scale 1:250,000) was a pioneering effort since there were no intermediate-sclae maps of the area. Representative of distinctive regional patterns, the map was suitable for use in comprehensive conservation planning and wildlife management.

Investigation of Solar Radiation Properties at the Battleship Promontory Area, Antarctica

NASA Technical Reports Server (NTRS)

VanNortwick, Sara S.

2005-01-01

JPL scientists in January 2005 visited the unique Battleship Promontory Area of the Antarctic Dry Valleys at 76 deg. 54 min. S one of the few places on the Antarctic continent home to viable life. Cryptoendolithic microorganisms manage to survive on and inside rocks in Antarctica's harsh conditions of extreme dryness and cold that are not So different from the past and present conditions on Mars. We are investigating the physical properties of these biological creatures through analysis of optical spectra collected from a variety of rock samples over the deep UV, visible, and near-infrared regions with the intent of gaining key insights into the environmental factors that make such a habitat viable for life. The LabView programming environment is equipped with the tools necessary to create an interface to visualize, manipulate, and normalize extensive raw reflectance and corresponding incident spectral data. We are determining the meaning of the colors observed and their relationship to the ability to acquire energy and investigating differences between the photosynthetic processes in full sunlight and diffuse/shadow lighting. Comparisons between spectral data collected in the field and from returned samples in the lab validate the accuracy of our field collection methodology.

Three junction holographic micro-scale PV system

NASA Astrophysics Data System (ADS)

Wu, Yuechen; Vorndran, Shelby; Ayala Pelaez, Silvana; Kostuk, Raymond K.

2016-09-01

In this work a spectrum splitting micro-scale concentrating PV system is evaluated to increase the conversion efficiency of flat panel PV systems. In this approach, the dispersed spectrum splitting concentration systems is scaled down to a small size and structured in an array. The spectrum splitting configuration allows the use of separate single bandgap PV cells that increase spectral overlap with the incident solar spectrum. This results in an overall increase in the spectral conversion efficiency of the resulting system. In addition other benefits of the micro-scale PV system are retained such reduced PV cell material requirements, more versatile interconnect configurations, and lower heat rejection requirements that can lead to a lower cost system. The system proposed in this work consists of two cascaded off-axis holograms in combination with a micro lens array, and three types of PV cells. An aspherical lens design is made to minimize the dispersion so that higher concentration ratios can be achieved for a three-junction system. An analysis methodology is also developed to determine the optical efficiency of the resulting system, the characteristics of the dispersed spectrum, and the overall system conversion efficiency for a combination of three types of PV cells.

A detailed mechanistic fragmentation analysis of methamphetamine and select regioisomers by GC/MS.

PubMed

Sachs, Sandra B; Woo, Francis

2007-03-01

A novel ring-substituted methamphetamine regioisomer, N,alpha,4-trimethyl phenmethylamine, was synthesized in order to study the validity of proposed structures for various mass spectrometry (MS)-derived peaks in a methamphetamine fragmentation pattern. While other research efforts have studied aspects of methamphetamine in detail, a full fragmentation study has not been reported previously. In addition to showing molecular structures represented by fragment peaks, mechanisms for selected processes are detailed. An empirically derived procedure to easily determine by simple spectral peak pattern recognition the geometry of dimethyl- or ethyl-substituted immonium ions (RRC = N+ RR) where m/z = 58 is outlined. These results are platform independent for electron ionization (EI) instruments, but have also proven to be helpful in explaining spectral peaks observed in spectra from ion trap systems. The spectrum for the synthesized methamphetamine regioisomer was accurately predicted using this methodology. While this approach is useful in some casework, the converse may be more useful: when an unexpected or unusual peak pattern arises in a spectrum, being able to analyze it to determine the structure of the molecule. This paper gives an analyst the means to begin such retro-synthetic analyses.

Intermediate-scale vegetation mapping of Innoko National Wildlife Refuge, Alaska using Landsat MSS digital data

USGS Publications Warehouse

Talbot, Stephen S.; Markon, Carl J.

1988-01-01

A Landsat-derived vegetation map was prepared for lnnoko National Wildlife Refuge. The refuge lies within the northern boreal subzone of northwestern central Alaska. Six major vegetation classes and 21 subclasses were recognized: forest (closed needleleaf, open needleleaf, needleleaf woodland, mixed, and broadleaf); broadleaf scrub (lowland, upland burn regeneration, subalpine); dwarf scrub (prostrate dwarf shrub tundra, erect dwarf shrub heath, dwarf shrub-graminoid peatland, dwarf shrub-graminoid tussock peatland, dwarf shrub raised bog with scattered trees, dwarf shrub-graminoid marsh); herbaceous (graminoid bog, graminoid marsh, graminoid tussock-dwarf shrub peatland); scarcely vegetated areas (scarcely vegetated scree and floodplain); and water (clear, sedimented). The methodology employed a cluster-block technique. Sample areas were described based on a combination of helicopter-ground survey, aerial photo-interpretation, and digital Landsat data. Major steps in the Landsat analysis involved preprocessing (geometric correction), derivation of statistical parameters for spectral classes, spectral class labeling of sample areas, preliminary classification of the entire study area using a maximum-likelihood algorithm, and final classification utilizing ancillary information such as digital elevation data. The final product is 1:250,000-scale vegetation map representative of distinctive regional patterns and suitable for use in comprehensive conservation planning.

Spectral Interferometry with Electron Microscopes

PubMed Central

Talebi, Nahid

2016-01-01

Interference patterns are not only a defining characteristic of waves, but also have several applications; characterization of coherent processes and holography. Spatial holography with electron waves, has paved the way towards space-resolved characterization of magnetic domains and electrostatic potentials with angstrom spatial resolution. Another impetus in electron microscopy has been introduced by ultrafast electron microscopy which uses pulses of sub-picosecond durations for probing a laser induced excitation of the sample. However, attosecond temporal resolution has not yet been reported, merely due to the statistical distribution of arrival times of electrons at the sample, with respect to the laser time reference. This is however, the very time resolution which will be needed for performing time-frequency analysis. These difficulties are addressed here by proposing a new methodology to improve the synchronization between electron and optical excitations through introducing an efficient electron-driven photon source. We use focused transition radiation of the electron as a pump for the sample. Due to the nature of transition radiation, the process is coherent. This technique allows us to perform spectral interferometry with electron microscopes, with applications in retrieving the phase of electron-induced polarizations and reconstructing dynamics of the induced vector potential. PMID:27649932

Hot-stage microscopy for determination of API fragmentation: comparison with other methods.

PubMed

Šimek, Michal; Grünwaldová, Veronika; Kratochvíl, Bohumil

2016-08-01

Although the fragmentation of the active pharmaceutical ingredient (API) is a phenomenon that is mentioned in many literature sources, no well-suited analytical tools for its investigation are currently known. We used the hot-stage microscopy method, already presented in our previous work, and studied the real fragmentation of the tadalafil particles in model tablets which were prepared under different compaction pressures. The morphology, spectral imaging and evaluation of plastic and elastic energies were also analyzed to support the hot-stage method. The prepared blend of tadalafil and excipients was compacted under a several forces from 5 to 35 kN to reveal the trend of fragmentation. The exact fragmentation of tadalafil with increased compaction pressure was revealed by the hot-stage microscopic method and it was in good agreement with plastic and elastic energies. Conversely, spectral imaging, which is being used for this analysis, was considered to be inaccurate methodology as mainly agglomerates, not individual particles, were measured. The availability of the hot-stage microscopic method equips pharmaceutical scientists with an in vitro assessment technique that will more reliably determine the fragmentation of the API in finished tablets and the behavior of the particles when compacted.

Spectral and Temporal Laser Fluorescence Analysis Such as for Natural Aquatic Environments

NASA Technical Reports Server (NTRS)

Chekalyuk, Alexander (Inventor)

2015-01-01

An Advanced Laser Fluorometer (ALF) can combine spectrally and temporally resolved measurements of laser-stimulated emission (LSE) for characterization of dissolved and particulate matter, including fluorescence constituents, in liquids. Spectral deconvolution (SDC) analysis of LSE spectral measurements can accurately retrieve information about individual fluorescent bands, such as can be attributed to chlorophyll-a (Chl-a), phycobiliprotein (PBP) pigments, or chromophoric dissolved organic matter (CDOM), among others. Improved physiological assessments of photosynthesizing organisms can use SDC analysis and temporal LSE measurements to assess variable fluorescence corrected for SDC-retrieved background fluorescence. Fluorescence assessments of Chl-a concentration based on LSE spectral measurements can be improved using photo-physiological information from temporal measurements. Quantitative assessments of PBP pigments, CDOM, and other fluorescent constituents, as well as basic structural characterizations of photosynthesizing populations, can be performed using SDC analysis of LSE spectral measurements.

THE SDSS-III APOGEE SPECTRAL LINE LIST FOR H-BAND SPECTROSCOPY

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

Shetrone, M.; Bizyaev, D.; Chojnowski, D.

We present the H-band spectral line lists adopted by the Apache Point Observatory Galactic Evolution Experiment (APOGEE). The APOGEE line lists comprise astrophysical, theoretical, and laboratory sources from the literature, as well as newly evaluated astrophysical oscillator strengths and damping parameters. We discuss the construction of the APOGEE line list, which is one of the critical inputs for the APOGEE Stellar Parameters and Chemical Abundances Pipeline, and present three different versions that have been used at various stages of the project. The methodology for the newly calculated astrophysical line lists is reviewed. The largest of these three line lists containsmore » 134,457 molecular and atomic transitions. In addition to the format adopted to store the data, the line lists are available in MOOG, Synspec, and Turbospectrum formats. The limitations of the line lists along with guidance for its use on different spectral types are discussed. We also present a list of H-band spectral features that are either poorly represented or completely missing in our line list. This list is based on the average of a large number of spectral fit residuals for APOGEE observations spanning a wide range of stellar parameters.« less

Evidence of orbital forcing in 510 to 530 million year old shallow marine cycles, Utah and western Canada

NASA Technical Reports Server (NTRS)

Bond, Gerard C.; Beavan, John; Kominz, Michelle A.; Devlin, William

1992-01-01

Spectral analyses of two sequences of shallow marine sedimentary cycles that were deposited between 510 and 530 million years ago were completed. One sequence is from Middle Cambrian rocks in southern Utah and the other is from Upper Cambrian rocks in the southern Canadian Rockies. In spite of the antiquity of these strata, and even though there are differences in the age, location, and cycle facies between the two sequences, both records have distinct spectral peaks with surprisingly similar periodicities. A null model constructed to test for significance of the spectral peaks and circulatory in the methodology indicates that all but one of the spectral peaks are significant at the 90 percent confidence level. When the ratios between the statistically significant peaks are measured, we find a consistent relation to orbital forcing; specifically, the spectral peak ratios in both the Utah and Canadian examples imply that a significant amount of the variance in the cyclic records is driven by the short eccentricity (approximately 109 ky) and by the precessional (approximately 21 ky) components of the Earth's orbital variations. Neither section contains a significant component of variance at the period of the obliquity cycle, however.

Classification of river water pollution using Hyperion data

NASA Astrophysics Data System (ADS)

Kar, Soumyashree; Rathore, V. S.; Champati ray, P. K.; Sharma, Richa; Swain, S. K.

2016-06-01

A novel attempt is made to use hyperspectral remote sensing to identify the spatial variability of metal pollutants present in river water. It was also attempted to classify the hyperspectral image - Earth Observation-1 (EO-1) Hyperion data of an 8 km stretch of the river Yamuna, near Allahabad city in India depending on its chemical composition. For validating image analysis results, a total of 10 water samples were collected and chemically analyzed using Inductively Coupled Plasma-Optical Emission Spectroscopy (ICP-OES). Two different spectral libraries from field and image data were generated for the 10 sample locations. Advanced per-pixel supervised classifications such as Spectral Angle Mapper (SAM), SAM target finder using BandMax and Support Vector Machine (SVM) were carried out along with the unsupervised clustering procedure - Iterative Self-Organizing Data Analysis Technique (ISODATA). The results were compared and assessed with respect to ground data. Analytical Spectral Devices (ASD), Inc. spectroradiometer, FieldSpec 4 was used to generate the spectra of the water samples which were compiled into a spectral library and used for Spectral Absorption Depth (SAD) analysis. The spectral depth pattern of image and field spectral libraries was found to be highly correlated (correlation coefficient, R2 = 0.99) which validated the image analysis results with respect to the ground data. Further, we carried out a multivariate regression analysis to assess the varying concentrations of metal ions present in water based on the spectral depth of the corresponding absorption feature. Spectral Absorption Depth (SAD) analysis along with metal analysis of field data revealed the order in which the metals affected the river pollution, which was in conformity with the findings of Central Pollution Control Board (CPCB). Therefore, it is concluded that hyperspectral imaging provides opportunity that can be used for satellite based remote monitoring of water quality from space.

Automatic classification of spectral units in the Aristarchus plateau

NASA Astrophysics Data System (ADS)

Erard, S.; Le Mouelic, S.; Langevin, Y.

1999-09-01

A reduction scheme has been recently proposed for the NIR images of Clementine (Le Mouelic et al, JGR 1999). This reduction has been used to build an integrated UVvis-NIR image cube of the Aristarchus region, from which compositional and maturity variations can be studied (Pinet et al, LPSC 1999). We will present an analysis of this image cube, providing a classification in spectral types and spectral units. The image cube is processed with Gmode analysis using three different data sets: Normalized spectra provide a classification based mainly on spectral slope variations (ie. maturity and volcanic glasses). This analysis discriminates between craters plus ejecta, mare basalts, and DMD. Olivine-rich areas and Aristarchus central peak are also recognized. Continuum-removed spectra provide a classification more related to compositional variations, which correctly identifies olivine and pyroxenes-rich areas (in Aristarchus, Krieger, Schiaparelli\\ldots). A third analysis uses spectral parameters related to maturity and Fe composition (reflectance, 1 mu m band depth, and spectral slope) rather than intensities. It provides the most spatially consistent picture, but fails in detecting Vallis Schroeteri and DMDs. A supplementary unit, younger and rich in pyroxene, is found on Aristarchus south rim. In conclusion, Gmode analysis can discriminate between different spectral types already identified with more classic methods (PCA, linear mixing\\ldots). No previous assumption is made on the data structure, such as endmembers number and nature, or linear relationship between input variables. The variability of the spectral types is intrinsically accounted for, so that the level of analysis is always restricted to meaningful limits. A complete classification should integrate several analyses based on different sets of parameters. Gmode is therefore a powerful light toll to perform first look analysis of spectral imaging data. This research has been partly founded by the French Programme National de Planetologie.

[Estimation of Hunan forest carbon density based on spectral mixture analysis of MODIS data].

PubMed

Yan, En-ping; Lin, Hui; Wang, Guang-xing; Chen, Zhen-xiong

2015-11-01

With the fast development of remote sensing technology, combining forest inventory sample plot data and remotely sensed images has become a widely used method to map forest carbon density. However, the existence of mixed pixels often impedes the improvement of forest carbon density mapping, especially when low spatial resolution images such as MODIS are used. In this study, MODIS images and national forest inventory sample plot data were used to conduct the study of estimation for forest carbon density. Linear spectral mixture analysis with and without constraint, and nonlinear spectral mixture analysis were compared to derive the fractions of different land use and land cover (LULC) types. Then sequential Gaussian co-simulation algorithm with and without the fraction images from spectral mixture analyses were employed to estimate forest carbon density of Hunan Province. Results showed that 1) Linear spectral mixture analysis with constraint, leading to a mean RMSE of 0.002, more accurately estimated the fractions of LULC types than linear spectral and nonlinear spectral mixture analyses; 2) Integrating spectral mixture analysis model and sequential Gaussian co-simulation algorithm increased the estimation accuracy of forest carbon density to 81.5% from 74.1%, and decreased the RMSE to 5.18 from 7.26; and 3) The mean value of forest carbon density for the province was 30.06 t · hm(-2), ranging from 0.00 to 67.35 t · hm(-2). This implied that the spectral mixture analysis provided a great potential to increase the estimation accuracy of forest carbon density on regional and global level.

Spectral analysis for GNSS coordinate time series using chirp Fourier transform

NASA Astrophysics Data System (ADS)

Feng, Shengtao; Bo, Wanju; Ma, Qingzun; Wang, Zifan

2017-12-01

Spectral analysis for global navigation satellite system (GNSS) coordinate time series provides a principal tool to understand the intrinsic mechanism that affects tectonic movements. Spectral analysis methods such as the fast Fourier transform, Lomb-Scargle spectrum, evolutionary power spectrum, wavelet power spectrum, etc. are used to find periodic characteristics in time series. Among spectral analysis methods, the chirp Fourier transform (CFT) with less stringent requirements is tested with synthetic and actual GNSS coordinate time series, which proves the accuracy and efficiency of the method. With the length of series only limited to even numbers, CFT provides a convenient tool for windowed spectral analysis. The results of ideal synthetic data prove CFT accurate and efficient, while the results of actual data show that CFT is usable to derive periodic information from GNSS coordinate time series.

ComDim for explorative multi-block data analysis of Cantal-type cheeses: Effects of salts, gentle heating and ripening.

PubMed

Loudiyi, M; Rutledge, D N; Aït-Kaddour, A

2018-10-30

Common Dimension (ComDim) chemometrics method for multi-block data analysis was employed to evaluate the impact of different added salts and ripening times on physicochemical, color, dynamic low amplitude oscillatory rheology, texture profile, and molecular structure (fluorescence and MIR spectroscopies) of five Cantal-type cheeses. Firstly, Independent Components Analysis (ICA) was applied separately on fluorescence and MIR spectra in order to extract the relevant signal source and the associated proportions related to molecular structure characteristics. ComDim was then applied on the 31 data tables corresponding to the proportion of ICA signals obtained for spectral methods and the global analysis of cheeses by the other techniques. The ComDim results indicated that generally cheeses made with 50% NaCl or with 75:25% NaCl/KCl exhibit the equivalent characteristics in structural, textural, meltability and color properties. The proposed methodology demonstrates the applicability of ComDim for the characterization of samples when different techniques describe the same samples. Copyright © 2018 Elsevier Ltd. All rights reserved.

Independent component analysis-based algorithm for automatic identification of Raman spectra applied to artistic pigments and pigment mixtures.

PubMed

González-Vidal, Juan José; Pérez-Pueyo, Rosanna; Soneira, María José; Ruiz-Moreno, Sergio

2015-03-01

A new method has been developed to automatically identify Raman spectra, whether they correspond to single- or multicomponent spectra. The method requires no user input or judgment. There are thus no parameters to be tweaked. Furthermore, it provides a reliability factor on the resulting identification, with the aim of becoming a useful support tool for the analyst in the decision-making process. The method relies on the multivariate techniques of principal component analysis (PCA) and independent component analysis (ICA), and on some metrics. It has been developed for the application of automated spectral analysis, where the analyzed spectrum is provided by a spectrometer that has no previous knowledge of the analyzed sample, meaning that the number of components in the sample is unknown. We describe the details of this method and demonstrate its efficiency by identifying both simulated spectra and real spectra. The method has been applied to artistic pigment identification. The reliable and consistent results that were obtained make the methodology a helpful tool suitable for the identification of pigments in artwork or in paint in general.

Surface Enhanced Raman Spectroscopy (SERS) and multivariate analysis as a screening tool for detecting Sudan I dye in culinary spices

NASA Astrophysics Data System (ADS)

Di Anibal, Carolina V.; Marsal, Lluís F.; Callao, M. Pilar; Ruisánchez, Itziar

2012-02-01

Raman spectroscopy combined with multivariate analysis was evaluated as a tool for detecting Sudan I dye in culinary spices. Three Raman modalities were studied: normal Raman, FT-Raman and SERS. The results show that SERS is the most appropriate modality capable of providing a proper Raman signal when a complex matrix is analyzed. To get rid of the spectral noise and background, Savitzky-Golay smoothing with polynomial baseline correction and wavelet transform were applied. Finally, to check whether unadulterated samples can be differentiated from samples adulterated with Sudan I dye, an exploratory analysis such as principal component analysis (PCA) was applied to raw data and data processed with the two mentioned strategies. The results obtained by PCA show that Raman spectra need to be properly treated if useful information is to be obtained and both spectra treatments are appropriate for processing the Raman signal. The proposed methodology shows that SERS combined with appropriate spectra treatment can be used as a practical screening tool to distinguish samples suspicious to be adulterated with Sudan I dye.

Application of a methodology for categorizing and differentiating urban soundscapes using acoustical descriptors and semantic-differential attributes.

PubMed

Torija, Antonio J; Ruiz, Diego P; Ramos-Ridao, A F

2013-07-01

A subjective and physical categorization of an ambient sound is the first step to evaluate the soundscape and provides a basis for designing or adapting this ambient sound to match people's expectations. For this reason, the main goal of this work is to develop a categorization and differentiation analysis of soundscapes on the basis of acoustical and perceptual variables. A hierarchical cluster analysis, using 15 semantic-differential attributes and acoustical descriptors to include an equivalent sound-pressure level, maximum-minimum sound-pressure level, impulsiveness of the sound-pressure level, sound-pressure level time course, and spectral composition, was conducted to classify soundscapes into different typologies. This analysis identified 15 different soundscape typologies. Furthermore, based on a discriminant analysis the acoustical descriptors, the crest factor (impulsiveness of the sound-pressure level), and the sound level at 125 Hz were found to be the acoustical variables with the highest impact in the differentiation of the recognized types of soundscapes. Finally, to determine how the different soundscape typologies differed from each other, both subjectively and acoustically, a study was performed.

Determination of awareness in patients with severe brain injury using EEG power spectral analysis

PubMed Central

Goldfine, Andrew M.; Victor, Jonathan D.; Conte, Mary M.; Bardin, Jonathan C.; Schiff, Nicholas D.

2011-01-01

Objective To determine whether EEG spectral analysis could be used to demonstrate awareness in patients with severe brain injury. Methods We recorded EEG from healthy controls and three patients with severe brain injury, ranging from minimally conscious state (MCS) to locked-in-state (LIS), while they were asked to imagine motor and spatial navigation tasks. We assessed EEG spectral differences from 4 to 24 Hz with univariate comparisons (individual frequencies) and multivariate comparisons (patterns across the frequency range). Results In controls, EEG spectral power differed at multiple frequency bands and channels during performance of both tasks compared to a resting baseline. As patterns of signal change were inconsistent between controls, we defined a positive response in patient subjects as consistent spectral changes across task performances. One patient in MCS and one in LIS showed evidence of motor imagery task performance, though with patterns of spectral change different from the controls. Conclusion EEG power spectral analysis demonstrates evidence for performance of mental imagery tasks in healthy controls and patients with severe brain injury. Significance EEG power spectral analysis can be used as a flexible bedside tool to demonstrate awareness in brain-injured patients who are otherwise unable to communicate. PMID:21514214

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.

Optical and laser spectroscopic diagnostics for energy applications

NASA Astrophysics Data System (ADS)

Tripathi, Markandey Mani

The continuing need for greater energy security and energy independence has motivated researchers to develop new energy technologies for better energy resource management and efficient energy usage. The focus of this dissertation is the development of optical (spectroscopic) sensing methodologies for various fuels, and energy applications. A fiber-optic NIR sensing methodology was developed for predicting water content in bio-oil. The feasibility of using the designed near infrared (NIR) system for estimating water content in bio-oil was tested by applying multivariate analysis to NIR spectral data. The calibration results demonstrated that the spectral information can successfully predict the bio-oil water content (from 16% to 36%). The effect of ultraviolet (UV) light on the chemical stability of bio-oil was studied by employing laser-induced fluorescence (LIF) spectroscopy. To simulate the UV light exposure, a laser in the UV region (325 nm) was employed for bio-oil excitation. The LIF, as a signature of chemical change, was recorded from bio-oil. From this study, it was concluded that phenols present in the bio-oil show chemical instability, when exposed to UV light. A laser-induced breakdown spectroscopy (LIBS)-based optical sensor was designed, developed, and tested for detection of four important trace impurities in rocket fuel (hydrogen). The sensor can simultaneously measure the concentrations of nitrogen, argon, oxygen, and helium in hydrogen from storage tanks and supply lines. The sensor had estimated lower detection limits of 80 ppm for nitrogen, 97 ppm for argon, 10 ppm for oxygen, and 25 ppm for helium. A chemiluminescence-based spectroscopic diagnostics were performed to measure equivalence ratios in methane-air premixed flames. A partial least-squares regression (PLS-R)-based multivariate sensing methodology was investigated. It was found that the equivalence ratios predicted with the PLS-R-based multivariate calibration model matched with the experimentally measured equivalence ratios within 7 %. A comparative study was performed for equivalence ratios measurement in atmospheric premixed methane-air flames with ungated LIBS and chemiluminescence spectroscopy. It was reported that LIBS-based calibration, which carries spectroscopic information from a "point-like-volume," provides better predictions of equivalence ratios compared to chemiluminescence-based calibration, which is essentially a "line-of-sight" measurement.

Combining Field Monitoring with Remote Sensing to Reconstruct Historical Hydroperiod: a Case Study in a Degrading Tropical Wetland

NASA Astrophysics Data System (ADS)

Alonso, A.; Munoz-Carpena, R.; Kaplan, D. A.

2017-12-01

Wetland ecosystem structure and function are primarily governed by water regime. Characterizing past and current wetland hydrology is thus crucial for identifying the drivers of long-term wetland degradation. Critically, a lack of spatially distributed and long-term data has impeded such characterization in most wetland systems across the world. The publically accessible Moderate Resolution Imaging Spectroradiometer (MODIS) satellite products encode spatial and temporal data for landscape monitoring, but it was unclear whether it could be used to reliably predict the hydric status of wetland due to the mixture of spectral signatures existing within and between such systems. We proposed and tested a methodological framework for the identification of site-specific wetness status spectral identification rule (WSSIR) using two recent technical innovations: affordable, easily deployable field water level sensors to train the WSSIR with supervised learning, and the powerful cloud-based Google Earth Engine (GEE) platform to rapidly access and process the MODIS imagery. This methodological framework was used in a study case of the globally important Palo Verde National Park tropical wetland in Costa Rica. Results showed that a site-specific WISSR could reliably detect wetland wet or dry status (hydroperiod) and capture the temporal variability of the wetness status. We applied it on the 500 m 2000-2016 MODIS Land Surface Reflectance daily product to reconstruct hydroperiod history, hence reaching a temporal resolution rarely matched in remote sensing for environmental studies. The analysis of the resulting long-term, spatially distributed MODIS-derived data, coupled with shorter-term, 15-minute resolution field water level time-series provided new insights into the drivers controlling the spatiotemporal dynamics of hydrology within Palo Verde National Park's degrading wetlands. This new knowledge is critical to make informed restoration and management decisions. Specifically, we identified a significant influence of the surrounding rivers and irrigation district, which emphasised the importance of considering the wetland in the watershed context when elaborating management strategies. The methodological framework can be applied to any other mid- to large-scale wetland systems worldwide.

Functionalized xenon as a biosensor

PubMed Central

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

Sparse polynomial space approach to dissipative quantum systems: application to the sub-ohmic spin-boson model.

PubMed

Alvermann, A; Fehske, H

2009-04-17

We propose a general numerical approach to open quantum systems with a coupling to bath degrees of freedom. The technique combines the methodology of polynomial expansions of spectral functions with the sparse grid concept from interpolation theory. Thereby we construct a Hilbert space of moderate dimension to represent the bath degrees of freedom, which allows us to perform highly accurate and efficient calculations of static, spectral, and dynamic quantities using standard exact diagonalization algorithms. The strength of the approach is demonstrated for the phase transition, critical behavior, and dissipative spin dynamics in the spin-boson model.

Imaging of lipids in atherosclerotic lesion in aorta from ApoE/LDLR-/- mice by FT-IR spectroscopy and Hierarchical Cluster Analysis.

PubMed

P Wrobel, Tomasz; Mateuszuk, Lukasz; Chlopicki, Stefan; Malek, Kamilla; Baranska, Malgorzata

2011-12-21

Spectroscopy-based approaches can provide an insight into the biochemical composition of a tissue sample. In the present work Fourier transform infrared (FT-IR) spectroscopy was used to develop a reliable methodology to study the content of free fatty acids, triglycerides, cholesteryl esters as well as cholesterol in aorta from mice with atherosclerosis (ApoE/LDLR(-/-) mice). In particular, distribution and concentration of palmitic, oleic and linoleic acid derivatives were analyzed. Spectral analysis of pure compounds allowed for clear discrimination between free fatty acids and other similar moieties based on the carbonyl band position (1699-1710 cm(-1) range). In order to distinguish cholesteryl esters from triglycerides a ratio of carbonyl band to signal at 1010 cm(-1) was used. Imaging of lipids in atherosclerotic aortic lesions in ApoE/LDLR(-/-) mice was followed by Hierarchical Cluster Analysis (HCA). The aorta from C57Bl/6J control mice (fed with chow diet) was used for comparison. The measurements were completed with an FT-IR spectrometer equipped with a 128 × 128 FPA detector. In cross-section of aorta from ApoE/LDLR(-/-) mice a region of atherosclerotic plaque was clearly identified by HCA, which was later divided into 2 sub-regions, one characterized by the higher content of cholesterol, while the other by higher contents of cholesteryl esters. HCA of tissues deposited on normal microscopic glass, hence limited to the 2200-3800 cm(-1) spectral range, also identified a region of atherosclerotic plaque. Importantly, this region correlates with the area stained by standard histological staining for atherosclerotic plaque (Oil Red O). In conclusion, the use of FT-IR and HCA may provide a novel tool for qualitative and quantitative analysis of contents and distribution of lipids in atherosclerotic plaque.

Microsoft Kinect Visual and Depth Sensors for Breathing and Heart Rate Analysis

PubMed Central

Procházka, Aleš; Schätz, Martin; Vyšata, Oldřich; Vališ, Martin

2016-01-01

This paper is devoted to a new method of using Microsoft (MS) Kinect sensors for non-contact monitoring of breathing and heart rate estimation to detect possible medical and neurological disorders. Video sequences of facial features and thorax movements are recorded by MS Kinect image, depth and infrared sensors to enable their time analysis in selected regions of interest. The proposed methodology includes the use of computational methods and functional transforms for data selection, as well as their denoising, spectral analysis and visualization, in order to determine specific biomedical features. The results that were obtained verify the correspondence between the evaluation of the breathing frequency that was obtained from the image and infrared data of the mouth area and from the thorax movement that was recorded by the depth sensor. Spectral analysis of the time evolution of the mouth area video frames was also used for heart rate estimation. Results estimated from the image and infrared data of the mouth area were compared with those obtained by contact measurements by Garmin sensors (www.garmin.com). The study proves that simple image and depth sensors can be used to efficiently record biomedical multidimensional data with sufficient accuracy to detect selected biomedical features using specific methods of computational intelligence. The achieved accuracy for non-contact detection of breathing rate was 0.26% and the accuracy of heart rate estimation was 1.47% for the infrared sensor. The following results show how video frames with depth data can be used to differentiate different kinds of breathing. The proposed method enables us to obtain and analyse data for diagnostic purposes in the home environment or during physical activities, enabling efficient human–machine interaction. PMID:27367687

Microsoft Kinect Visual and Depth Sensors for Breathing and Heart Rate Analysis.

PubMed

Procházka, Aleš; Schätz, Martin; Vyšata, Oldřich; Vališ, Martin

2016-06-28

This paper is devoted to a new method of using Microsoft (MS) Kinect sensors for non-contact monitoring of breathing and heart rate estimation to detect possible medical and neurological disorders. Video sequences of facial features and thorax movements are recorded by MS Kinect image, depth and infrared sensors to enable their time analysis in selected regions of interest. The proposed methodology includes the use of computational methods and functional transforms for data selection, as well as their denoising, spectral analysis and visualization, in order to determine specific biomedical features. The results that were obtained verify the correspondence between the evaluation of the breathing frequency that was obtained from the image and infrared data of the mouth area and from the thorax movement that was recorded by the depth sensor. Spectral analysis of the time evolution of the mouth area video frames was also used for heart rate estimation. Results estimated from the image and infrared data of the mouth area were compared with those obtained by contact measurements by Garmin sensors (www.garmin.com). The study proves that simple image and depth sensors can be used to efficiently record biomedical multidimensional data with sufficient accuracy to detect selected biomedical features using specific methods of computational intelligence. The achieved accuracy for non-contact detection of breathing rate was 0.26% and the accuracy of heart rate estimation was 1.47% for the infrared sensor. The following results show how video frames with depth data can be used to differentiate different kinds of breathing. The proposed method enables us to obtain and analyse data for diagnostic purposes in the home environment or during physical activities, enabling efficient human-machine interaction.

Smart Bandwidth Assignation in an Underlay Cellular Network for Internet of Vehicles.

PubMed

de la Iglesia, Idoia; Hernandez-Jayo, Unai; Osaba, Eneko; Carballedo, Roberto

2017-09-27

The evolution of the IoT (Internet of Things) paradigm applied to new scenarios as VANETs (Vehicular Ad Hoc Networks) has gained momentum in recent years. Both academia and industry have triggered advanced studies in the IoV (Internet of Vehicles), which is understood as an ecosystem where different types of users (vehicles, elements of the infrastructure, pedestrians) are connected. How to efficiently share the available radio resources among the different types of eligible users is one of the important issues to be addressed. This paper briefly analyzes various concepts presented hitherto in the literature and it proposes an enhanced algorithm for ensuring a robust co-existence of the aforementioned system users. Therefore, this paper introduces an underlay RRM (Radio Resource Management) methodology which is capable of (1) improving cellular spectral efficiency while making a minimal impact on cellular communications and (2) ensuring the different QoS (Quality of Service) requirements of ITS (Intelligent Transportation Systems) applications. Simulation results, where we compare the proposed algorithm to the other two RRM, show the promising spectral efficiency performance of the proposed RRM methodology.

Smart Bandwidth Assignation in an Underlay Cellular Network for Internet of Vehicles

PubMed Central

de la Iglesia, Idoia; Hernandez-Jayo, Unai

2017-01-01

The evolution of the IoT (Internet of Things) paradigm applied to new scenarios as VANETs (Vehicular Ad Hoc Networks) has gained momentum in recent years. Both academia and industry have triggered advanced studies in the IoV (Internet of Vehicles), which is understood as an ecosystem where different types of users (vehicles, elements of the infrastructure, pedestrians) are connected. How to efficiently share the available radio resources among the different types of eligible users is one of the important issues to be addressed. This paper briefly analyzes various concepts presented hitherto in the literature and it proposes an enhanced algorithm for ensuring a robust co-existence of the aforementioned system users. Therefore, this paper introduces an underlay RRM (Radio Resource Management) methodology which is capable of (1) improving cellular spectral efficiency while making a minimal impact on cellular communications and (2) ensuring the different QoS (Quality of Service) requirements of ITS (Intelligent Transportation Systems) applications. Simulation results, where we compare the proposed algorithm to the other two RRM, show the promising spectral efficiency performance of the proposed RRM methodology. PMID:28953256

Calculating the habitable zones of multiple star systems with a new interactive Web site

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

Müller, Tobias W. A.; Haghighipour, Nader

We have developed a comprehensive methodology and an interactive Web site for calculating the habitable zone (HZ) of multiple star systems. Using the concept of spectral weight factor, as introduced in our previous studies of the calculations of HZ in and around binary star systems, we calculate the contribution of each star (based on its spectral energy distribution) to the total flux received at the top of the atmosphere of an Earth-like planet, and use the models of the HZ of the Sun to determine the boundaries of the HZ in multiple star systems. Our interactive Web site for carryingmore » out these calculations is publicly available at http://astro.twam.info/hz. We discuss the details of our methodology and present its application to some of the multiple star systems detected by the Kepler space telescope. We also present the instructions for using our interactive Web site, and demonstrate its capabilities by calculating the HZ for two interesting analytical solutions of the three-body problem.« less

Spectral anomaly methods for aerial detection using KUT nuisance rejection

NASA Astrophysics Data System (ADS)

Detwiler, R. S.; Pfund, D. M.; Myjak, M. J.; Kulisek, J. A.; Seifert, C. E.

2015-06-01

This work discusses the application and optimization of a spectral anomaly method for the real-time detection of gamma radiation sources from an aerial helicopter platform. Aerial detection presents several key challenges over ground-based detection. For one, larger and more rapid background fluctuations are typical due to higher speeds, larger field of view, and geographically induced background changes. As well, the possible large altitude or stand-off distance variations cause significant steps in background count rate as well as spectral changes due to increased gamma-ray scatter with detection at higher altitudes. The work here details the adaptation and optimization of the PNNL-developed algorithm Nuisance-Rejecting Spectral Comparison Ratios for Anomaly Detection (NSCRAD), a spectral anomaly method previously developed for ground-based applications, for an aerial platform. The algorithm has been optimized for two multi-detector systems; a NaI(Tl)-detector-based system and a CsI detector array. The optimization here details the adaptation of the spectral windows for a particular set of target sources to aerial detection and the tailoring for the specific detectors. As well, the methodology and results for background rejection methods optimized for the aerial gamma-ray detection using Potassium, Uranium and Thorium (KUT) nuisance rejection are shown. Results indicate that use of a realistic KUT nuisance rejection may eliminate metric rises due to background magnitude and spectral steps encountered in aerial detection due to altitude changes and geographically induced steps such as at land-water interfaces.

Spectral Properties of Limit-Periodic Schrödinger Operators (PhD Thesis)

NASA Astrophysics Data System (ADS)

Gideonse, Hendrik David, XIX

The Acoustic Ramp is a wedge-shaped, number-theoretical quadratic-residue-type acoustic diffuser. Since the late 1970's, several methodologies for the testing and analysis of diffusers have been developed including, the ISO Scattering Coefficient and the AES Diffusion Coefficient. These coefficients are the source of some controversy today and this paper makes the attempt to investigate the benefits and weaknesses of these tools by using them to research and test the Acoustic Ramp. Several issues are exposed in using the coefficients, the most important of which being the validity of the comparison of the diffuser's behavior to that of a like sized flat panel. Further issues comprise of an intuitive disconnect between the perceived merits of polar plots and the numerical value of coefficients derived from the plots.

Methods for Retrievals of CO2 Mixing Ratios from JPL Laser Absorption Spectrometer Flights During a Summer 2011 Campaign

NASA Technical Reports Server (NTRS)

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

2013-01-01

The JPL airborne Laser Absorption Spectrometer instrument has been flown several times in the 2007-2011 time frame for the purpose of measuring CO2 mixing ratios in the lower atmosphere. This instrument employs CW laser transmitters and coherent detection receivers in the 2.05- micro m spectral region. The Integrated Path Differential Absorption (IPDA) method is used to retrieve weighted CO2 column mixing ratios. We present key features of the evolving LAS signal processing and data analysis algorithms and the calibration/validation methodology. Results from 2011 flights in various U.S. locations include observed mid-day CO2 drawdown in the Midwest and high spatial resolution plume detection during a leg downwind of the Four Corners power plant in New Mexico.

Earthquake stress via event ratio levels: Application to the 2011 and 2016 Oklahoma seismic sequences

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

Walter, William R.; Yoo, Seung -Hoon; Mayeda, Kevin

Here, we develop a new methodology for determining earthquake stress drop and apparent stress values via spectral ratio asymptotic levels. With sufficient bandwidth, the stress ratio for a pair of events can be directly related to these low- and high-frequency levels. This avoids the need to assume a particular spectral model and derive stress drop from cubed corner frequency measures. The method can be applied to spectral ratios for any pair of closely related earthquakes and is particularly well suited for coda envelope methods that provide good azimuthally averaged, point-source measures. We apply the new method to the 2011 Praguemore » and 2016 Pawnee earthquake sequences in Oklahoma. The sequences show stress scaling with size and depth, with the largest events having apparent stress levels near 1 MPa and smaller and/or shallower events having systematically lower stress values.« less

Nonlinear model identification and spectral submanifolds for multi-degree-of-freedom mechanical vibrations

NASA Astrophysics Data System (ADS)

Szalai, Robert; Ehrhardt, David; Haller, George

2017-06-01

In a nonlinear oscillatory system, spectral submanifolds (SSMs) are the smoothest invariant manifolds tangent to linear modal subspaces of an equilibrium. Amplitude-frequency plots of the dynamics on SSMs provide the classic backbone curves sought in experimental nonlinear model identification. We develop here, a methodology to compute analytically both the shape of SSMs and their corresponding backbone curves from a data-assimilating model fitted to experimental vibration signals. This model identification utilizes Taken's delay-embedding theorem, as well as a least square fit to the Taylor expansion of the sampling map associated with that embedding. The SSMs are then constructed for the sampling map using the parametrization method for invariant manifolds, which assumes that the manifold is an embedding of, rather than a graph over, a spectral subspace. Using examples of both synthetic and real experimental data, we demonstrate that this approach reproduces backbone curves with high accuracy.

Earthquake stress via event ratio levels: Application to the 2011 and 2016 Oklahoma seismic sequences

DOE PAGES

Walter, William R.; Yoo, Seung -Hoon; Mayeda, Kevin; ...

2017-04-03

Here, we develop a new methodology for determining earthquake stress drop and apparent stress values via spectral ratio asymptotic levels. With sufficient bandwidth, the stress ratio for a pair of events can be directly related to these low- and high-frequency levels. This avoids the need to assume a particular spectral model and derive stress drop from cubed corner frequency measures. The method can be applied to spectral ratios for any pair of closely related earthquakes and is particularly well suited for coda envelope methods that provide good azimuthally averaged, point-source measures. We apply the new method to the 2011 Praguemore » and 2016 Pawnee earthquake sequences in Oklahoma. The sequences show stress scaling with size and depth, with the largest events having apparent stress levels near 1 MPa and smaller and/or shallower events having systematically lower stress values.« less

Stroke type differentiation using spectrally constrained multifrequency EIT: evaluation of feasibility in a realistic head model.

PubMed

Malone, Emma; Jehl, Markus; Arridge, Simon; Betcke, Timo; Holder, David

2014-06-01

We investigate the application of multifrequency electrical impedance tomography (MFEIT) to imaging the brain in stroke patients. The use of MFEIT could enable early diagnosis and thrombolysis of ischaemic stroke, and therefore improve the outcome of treatment. Recent advances in the imaging methodology suggest that the use of spectral constraints could allow for the reconstruction of a one-shot image. We performed a simulation study to investigate the feasibility of imaging stroke in a head model with realistic conductivities. We introduced increasing levels of modelling errors to test the robustness of the method to the most common sources of artefact. We considered the case of errors in the electrode placement, spectral constraints, and contact impedance. The results indicate that errors in the position and shape of the electrodes can affect image quality, although our imaging method was successful in identifying tissues with sufficiently distinct spectra.

Authentication of Closely Related Fish and Derived Fish Products Using Tandem Mass Spectrometry and Spectral Library Matching.

PubMed

Nessen, Merel A; van der Zwaan, Dennis J; Grevers, Sander; Dalebout, Hans; Staats, Martijn; Kok, Esther; Palmblad, Magnus

2016-05-11

Proteomics methodology has seen increased application in food authentication, including tandem mass spectrometry of targeted species-specific peptides in raw, processed, or mixed food products. We have previously described an alternative principle that uses untargeted data acquisition and spectral library matching, essentially spectral counting, to compare and identify samples without the need for genomic sequence information in food species populations. Here, we present an interlaboratory comparison demonstrating how a method based on this principle performs in a realistic context. We also increasingly challenge the method by using data from different types of mass spectrometers, by trying to distinguish closely related and commercially important flatfish, and by analyzing heavily contaminated samples. The method was found to be robust in different laboratories, and 94-97% of the analyzed samples were correctly identified, including all processed and contaminated samples.

Multispectral analysis tools can increase utility of RGB color images in histology

NASA Astrophysics Data System (ADS)

Fereidouni, Farzad; Griffin, Croix; Todd, Austin; Levenson, Richard

2018-04-01

Multispectral imaging (MSI) is increasingly finding application in the study and characterization of biological specimens. However, the methods typically used come with challenges on both the acquisition and the analysis front. MSI can be slow and photon-inefficient, leading to long imaging times and possible phototoxicity and photobleaching. The resulting datasets can be large and complex, prompting the development of a number of mathematical approaches for segmentation and signal unmixing. We show that under certain circumstances, just three spectral channels provided by standard color cameras, coupled with multispectral analysis tools, including a more recent spectral phasor approach, can efficiently provide useful insights. These findings are supported with a mathematical model relating spectral bandwidth and spectral channel number to achievable spectral accuracy. The utility of 3-band RGB and MSI analysis tools are demonstrated on images acquired using brightfield and fluorescence techniques, as well as a novel microscopy approach employing UV-surface excitation. Supervised linear unmixing, automated non-negative matrix factorization and phasor analysis tools all provide useful results, with phasors generating particularly helpful spectral display plots for sample exploration.

Blast investigation by fast multispectral radiometric analysis

NASA Astrophysics Data System (ADS)

Devir, A. D.; Bushlin, Y.; Mendelewicz, I.; Lessin, A. B.; Engel, M.

2011-06-01

Knowledge regarding the processes involved in blasts and detonations is required in various applications, e.g. missile interception, blasts of high-explosive materials, final ballistics and IED identification. Blasts release large amount of energy in short time duration. Some part of this energy is released as intense radiation in the optical spectral bands. This paper proposes to measure the blast radiation by a fast multispectral radiometer. The measurement is made, simultaneously, in appropriately chosen spectral bands. These spectral bands provide extensive information on the physical and chemical processes that govern the blast through the time-dependence of the molecular and aerosol contributions to the detonation products. Multi-spectral blast measurements are performed in the visible, SWIR and MWIR spectral bands. Analysis of the cross-correlation between the measured multi-spectral signals gives the time dependence of the temperature, aerosol and gas composition of the blast. Farther analysis of the development of these quantities in time may indicate on the order of the detonation and amount and type of explosive materials. Examples of analysis of measured explosions are presented to demonstrate the power of the suggested fast multispectral radiometric analysis approach.

Combining optimization methods with response spectra curve-fitting toward improved damping ratio estimation

NASA Astrophysics Data System (ADS)

Brewick, Patrick T.; Smyth, Andrew W.

2016-12-01

The authors have previously shown that many traditional approaches to operational modal analysis (OMA) struggle to properly identify the modal damping ratios for bridges under traffic loading due to the interference caused by the driving frequencies of the traffic loads. This paper presents a novel methodology for modal parameter estimation in OMA that overcomes the problems presented by driving frequencies and significantly improves the damping estimates. This methodology is based on finding the power spectral density (PSD) of a given modal coordinate, and then dividing the modal PSD into separate regions, left- and right-side spectra. The modal coordinates were found using a blind source separation (BSS) algorithm and a curve-fitting technique was developed that uses optimization to find the modal parameters that best fit each side spectra of the PSD. Specifically, a pattern-search optimization method was combined with a clustering analysis algorithm and together they were employed in a series of stages in order to improve the estimates of the modal damping ratios. This method was used to estimate the damping ratios from a simulated bridge model subjected to moving traffic loads. The results of this method were compared to other established OMA methods, such as Frequency Domain Decomposition (FDD) and BSS methods, and they were found to be more accurate and more reliable, even for modes that had their PSDs distorted or altered by driving frequencies.

Associative image analysis: a method for automated quantification of 3D multi-parameter images of brain tissue

PubMed Central

Bjornsson, Christopher S; Lin, Gang; Al-Kofahi, Yousef; Narayanaswamy, Arunachalam; Smith, Karen L; Shain, William; Roysam, Badrinath

2009-01-01

Brain structural complexity has confounded prior efforts to extract quantitative image-based measurements. We present a systematic ‘divide and conquer’ methodology for analyzing three-dimensional (3D) multi-parameter images of brain tissue to delineate and classify key structures, and compute quantitative associations among them. To demonstrate the method, thick (~100 μm) slices of rat brain tissue were labeled using 3 – 5 fluorescent signals, and imaged using spectral confocal microscopy and unmixing algorithms. Automated 3D segmentation and tracing algorithms were used to delineate cell nuclei, vasculature, and cell processes. From these segmentations, a set of 23 intrinsic and 8 associative image-based measurements was computed for each cell. These features were used to classify astrocytes, microglia, neurons, and endothelial cells. Associations among cells and between cells and vasculature were computed and represented as graphical networks to enable further analysis. The automated results were validated using a graphical interface that permits investigator inspection and corrective editing of each cell in 3D. Nuclear counting accuracy was >89%, and cell classification accuracy ranged from 81–92% depending on cell type. We present a software system named FARSIGHT implementing our methodology. Its output is a detailed XML file containing measurements that may be used for diverse quantitative hypothesis-driven and exploratory studies of the central nervous system. PMID:18294697

Spectral analysis using the CCD Chirp Z-transform

NASA Technical Reports Server (NTRS)

Eversole, W. L.; Mayer, D. J.; Bosshart, P. W.; Dewit, M.; Howes, C. R.; Buss, D. D.

1978-01-01

The charge coupled device (CCD) Chirp Z transformation (CZT) spectral analysis techniques were reviewed and results on state-of-the-art CCD CZT technology are presented. The CZT algorithm was examined and the advantages of CCD implementation are discussed. The sliding CZT which is useful in many spectral analysis applications is described, and the performance limitations of the CZT are studied.

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

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

Spectral analysis of variable-length coded digital signals

NASA Astrophysics Data System (ADS)

Cariolaro, G. L.; Pierobon, G. L.; Pupolin, S. G.

1982-05-01

A spectral analysis is conducted for a variable-length word sequence by an encoder driven by a stationary memoryless source. A finite-state sequential machine is considered as a model of the line encoder, and the spectral analysis of the encoded message is performed under the assumption that the sourceword sequence is composed of independent identically distributed words. Closed form expressions for both the continuous and discrete parts of the spectral density are derived in terms of the encoder law and sourceword statistics. The jump part exhibits jumps at multiple integers of per lambda(sub 0)T, where lambda(sub 0) is the greatest common divisor of the possible codeword lengths, and T is the symbol period. The derivation of the continuous part can be conveniently factorized, and the theory is applied to the spectral analysis of BnZS and HDBn codes.

Spectral classifying base on color of live corals and dead corals covered with algae

NASA Astrophysics Data System (ADS)

Nurdin, Nurjannah; Komatsu, Teruhisa; Barille, Laurent; Akbar, A. S. M.; Sawayama, Shuhei; Fitrah, Muh. Nur; Prasyad, Hermansyah

2016-05-01

Pigments in the host tissues of corals can make a significant contribution to their spectral signature and can affect their apparent color as perceived by a human observer. The aim of this study is classifying the spectral reflectance of corals base on different color. It is expected that they can be used as references in discriminating between live corals, dead coral covered with algae Spectral reflectance data was collected in three small islands, Spermonde Archipelago, Indonesia by using a hyperspectral radiometer underwater. First and second derivative analysis resolved the wavelength locations of dominant features contributing to reflectance in corals and support the distinct differences in spectra among colour existed. Spectral derivative analysis was used to determine the specific wavelength regions ideal for remote identification of substrate type. The analysis results shown that yellow, green, brown and violet live corals are spectrally separable from each other, but they are similar with dead coral covered with algae spectral.

Improving the Accuracy of Cloud Detection Using Machine Learning

NASA Astrophysics Data System (ADS)

Craddock, M. E.; Alliss, R. J.; Mason, M.

2017-12-01

Cloud detection from geostationary satellite imagery has long been accomplished through multi-spectral channel differencing in comparison to the Earth's surface. The distinction of clear/cloud is then determined by comparing these differences to empirical thresholds. Using this methodology, the probability of detecting clouds exceeds 90% but performance varies seasonally, regionally and temporally. The Cloud Mask Generator (CMG) database developed under this effort, consists of 20 years of 4 km, 15minute clear/cloud images based on GOES data over CONUS and Hawaii. The algorithms to determine cloudy pixels in the imagery are based on well-known multi-spectral techniques and defined thresholds. These thresholds were produced by manually studying thousands of images and thousands of man-hours to determine the success and failure of the algorithms to fine tune the thresholds. This study aims to investigate the potential of improving cloud detection by using Random Forest (RF) ensemble classification. RF is the ideal methodology to employ for cloud detection as it runs efficiently on large datasets, is robust to outliers and noise and is able to deal with highly correlated predictors, such as multi-spectral satellite imagery. The RF code was developed using Python in about 4 weeks. The region of focus selected was Hawaii and includes the use of visible and infrared imagery, topography and multi-spectral image products as predictors. The development of the cloud detection technique is realized in three steps. First, tuning of the RF models is completed to identify the optimal values of the number of trees and number of predictors to employ for both day and night scenes. Second, the RF models are trained using the optimal number of trees and a select number of random predictors identified during the tuning phase. Lastly, the model is used to predict clouds for an independent time period than used during training and compared to truth, the CMG cloud mask. Initial results show 97% accuracy during the daytime, 94% accuracy at night, and 95% accuracy for all times. The total time to train, tune and test was approximately one week. The improved performance and reduced time to produce results is testament to improved computer technology and the use of machine learning as a more efficient and accurate methodology of cloud detection.

MODIS In-flight Calibration Methodologies

NASA Technical Reports Server (NTRS)

Xiong, X.; Barnes, W.

2004-01-01

MODIS is a key instrument for the NASA's Earth Observing System (EOS) currently operating on the Terra spacecraft launched in December 1999 and Aqua spacecraft launched in May 2002. It is a cross-track scanning radiometer, making measurements over a wide field of view in 36 spectral bands with wavelengths from 0.41 to 14.5 micrometers and providing calibrated data products for science and research communities in their studies of the Earth s system of land, oceans, and atmosphere. A complete suite of on-board calibrators (OBC) have been designed for the instruments in-flight calibration and characterization, including a solar diffuser (SD) and solar diffuser stability monitor (SDSM) system for the radiometric calibration of the 20 reflective solar bands (RSB), a blackbody (BB) for the radiometric calibration of the 16 thermal emissive bands (TEB), and a spectro-radiometric calibration assembly (SRCA) for the spatial (all bands) and spectral (RSB only) characterization. This paper discusses MODIS in-flight Cali bration methodologies of using its on-board calibrators. Challenging issues and examples of tracking and correcting instrument on-orbit response changes are presented, including SD degradation (20% at 412nm, 12% at 466nm, and 7% at 530nm over four and a half years) and response versus scan angle changes (10%, 4%, and 1% differences between beginning of the scan and end of the scan at 412nm, 466nm, and 530nm) in the VIS spectral region. Current instrument performance and lessons learned are also provided.

Developing a spectroradiometer data uncertainty methodology

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

Peterson, Josh; Vignola, Frank; Habte, Aron

The proper calibration and measurement uncertainty of spectral data obtained from spectroradiometers is essential in accurately quantifying the output of photovoltaic (PV) devices. PV cells and modules are initially characterized using solar simulators but field performance is evaluated using natural sunlight. Spectroradiometers are used to measure the spectrum of both these light sources in an effort to understand the spectral dependence of various PV output capabilities. These chains of characterization and measurement are traceable to National Metrology Institutes such as National Institute of Standards and Technology, and therefore there is a need for a comprehensive uncertainty methodology to determine themore » accuracy of spectroradiometer data. In this paper, the uncertainties associated with the responsivity of a spectroradiometer are examined using the Guide to the Expression of Uncertainty in Measurement (GUM) protocols. This is first done for a generic spectroradiometer, and then, to illustrate the methodology, the calibration of a LI-COR 1800 spectroradiometer is performed. The reader should be aware that the implementation of this methodology will be specific to the spectroradiometer being analyzed and the experimental setup that is used. Depending of the characteristics of the spectroradiometer being evaluated additional sources of uncertainty may need to be included, but the general GUM methodology is the same. Several sources of uncertainty are associated with the spectroradiometer responsivity. Major sources of uncertainty associated with the LI-COR spectroradiometer are noise in the signal at wavelengths less than 400 nm. At wavelengths more than 400 nm, the responsivity can vary drastically, and it is dependent on the wavelength of light, the temperature dependence, the angle of incidence, and the azimuthal orientation of the sensor to the light source. As a result, the expanded uncertainties in the responsivity of the LI-COR spectroradiometer in the wavelength range of 400-1050 nm can range from 4% to 14% at the 95% confidence level.« less

Developing a spectroradiometer data uncertainty methodology

DOE PAGES

Peterson, Josh; Vignola, Frank; Habte, Aron; ...

2017-04-11

The proper calibration and measurement uncertainty of spectral data obtained from spectroradiometers is essential in accurately quantifying the output of photovoltaic (PV) devices. PV cells and modules are initially characterized using solar simulators but field performance is evaluated using natural sunlight. Spectroradiometers are used to measure the spectrum of both these light sources in an effort to understand the spectral dependence of various PV output capabilities. These chains of characterization and measurement are traceable to National Metrology Institutes such as National Institute of Standards and Technology, and therefore there is a need for a comprehensive uncertainty methodology to determine themore » accuracy of spectroradiometer data. In this paper, the uncertainties associated with the responsivity of a spectroradiometer are examined using the Guide to the Expression of Uncertainty in Measurement (GUM) protocols. This is first done for a generic spectroradiometer, and then, to illustrate the methodology, the calibration of a LI-COR 1800 spectroradiometer is performed. The reader should be aware that the implementation of this methodology will be specific to the spectroradiometer being analyzed and the experimental setup that is used. Depending of the characteristics of the spectroradiometer being evaluated additional sources of uncertainty may need to be included, but the general GUM methodology is the same. Several sources of uncertainty are associated with the spectroradiometer responsivity. Major sources of uncertainty associated with the LI-COR spectroradiometer are noise in the signal at wavelengths less than 400 nm. At wavelengths more than 400 nm, the responsivity can vary drastically, and it is dependent on the wavelength of light, the temperature dependence, the angle of incidence, and the azimuthal orientation of the sensor to the light source. As a result, the expanded uncertainties in the responsivity of the LI-COR spectroradiometer in the wavelength range of 400-1050 nm can range from 4% to 14% at the 95% confidence level.« less

On Hilbert-Huang Transform Based Synthesis of a Signal Contaminated by Radio Frequency Interference or Fringes

NASA Technical Reports Server (NTRS)

Kizhner, Semion; Shiri, Ron S.; Vootukuru, Meg; Coletti, Alessandro

2015-01-01

Norden E. Huang et al. had proposed and published the Hilbert-Huang Transform (HHT) concept correspondently in 1996, 1998. The HHT is a novel method for adaptive spectral analysis of non-linear and non-stationary signals. The HHT comprises two components: - the Huang Empirical Mode Decomposition (EMD), resulting in an adaptive data-derived basis of Intrinsic Mode functions (IMFs), and the Hilbert Spectral Analysis (HSA1) based on the Hilbert Transform for 1-dimension (1D) applied to the EMD IMF's outcome. Although paper describes the HHT concept in great depth, it does not contain all needed methodology to implement the HHT computer code. In 2004, Semion Kizhner and Karin Blank implemented the reference digital HHT real-time data processing system for 1D (HHT-DPS Version 1.4). The case for 2-Dimension (2D) (HHT2) proved to be difficult due to the computational complexity of EMD for 2D (EMD2) and absence of a suitable Hilbert Transform for 2D spectral analysis (HSA2). The real-time EMD2 and HSA2 comprise the real-time HHT2. Kizhner completed the real-time EMD2 and the HSA2 reference digital implementations respectively in 2013 & 2014. Still, the HHT2 outcome synthesis remains an active research area. This paper presents the initial concepts and preliminary results of HHT2-based synthesis and its application to processing of signals contaminated by Radio-Frequency Interference (RFI), as well as optical systems' fringe detection and mitigation at design stage. The Soil Moisture Active Passive (SMAP mission (SMAP) carries a radiometer instrument that measures Earth soil moisture at L1 frequency (1.4 GHz polarimetric - H, V, 3rd and 4th Stokes parameters). There is abundant RFI at L1 and because soil moisture is a strategic parameter, it is important to be able to recover the RFI-contaminated measurement samples (15% of telemetry). State-of-the-art only allows RFI detection and removes RFI-contaminated measurements. The HHT-based analysis and synthesis facilitates recovery of measurements contaminated by all kinds of RFI, including jamming [7-8]. The fringes are inherent in optical systems and multi-layer complex contour expensive coatings are employed to remove the unwanted fringes. HHT2-based analysis allows test image decomposition to analyze and detect fringes, and HHT2-based synthesis of useful image.

The Spectral Image Processing System (SIPS): Software for integrated analysis of AVIRIS data

NASA Technical Reports Server (NTRS)

Kruse, F. A.; Lefkoff, A. B.; Boardman, J. W.; Heidebrecht, K. B.; Shapiro, A. T.; Barloon, P. J.; Goetz, A. F. H.

1992-01-01

The Spectral Image Processing System (SIPS) is a software package developed by the Center for the Study of Earth from Space (CSES) at the University of Colorado, Boulder, in response to a perceived need to provide integrated tools for analysis of imaging spectrometer data both spectrally and spatially. SIPS was specifically designed to deal with data from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and the High Resolution Imaging Spectrometer (HIRIS), but was tested with other datasets including the Geophysical and Environmental Research Imaging Spectrometer (GERIS), GEOSCAN images, and Landsat TM. SIPS was developed using the 'Interactive Data Language' (IDL). It takes advantage of high speed disk access and fast processors running under the UNIX operating system to provide rapid analysis of entire imaging spectrometer datasets. SIPS allows analysis of single or multiple imaging spectrometer data segments at full spatial and spectral resolution. It also allows visualization and interactive analysis of image cubes derived from quantitative analysis procedures such as absorption band characterization and spectral unmixing. SIPS consists of three modules: SIPS Utilities, SIPS_View, and SIPS Analysis. SIPS version 1.1 is described below.

Hierarchical Processing of Auditory Objects in Humans

PubMed Central

Kumar, Sukhbinder; Stephan, Klaas E; Warren, Jason D; Friston, Karl J; Griffiths, Timothy D

2007-01-01

This work examines the computational architecture used by the brain during the analysis of the spectral envelope of sounds, an important acoustic feature for defining auditory objects. Dynamic causal modelling and Bayesian model selection were used to evaluate a family of 16 network models explaining functional magnetic resonance imaging responses in the right temporal lobe during spectral envelope analysis. The models encode different hypotheses about the effective connectivity between Heschl's Gyrus (HG), containing the primary auditory cortex, planum temporale (PT), and superior temporal sulcus (STS), and the modulation of that coupling during spectral envelope analysis. In particular, we aimed to determine whether information processing during spectral envelope analysis takes place in a serial or parallel fashion. The analysis provides strong support for a serial architecture with connections from HG to PT and from PT to STS and an increase of the HG to PT connection during spectral envelope analysis. The work supports a computational model of auditory object processing, based on the abstraction of spectro-temporal “templates” in the PT before further analysis of the abstracted form in anterior temporal lobe areas. PMID:17542641

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.

Object-based habitat mapping using very high spatial resolution multispectral and hyperspectral imagery with LiDAR data

NASA Astrophysics Data System (ADS)

Onojeghuo, Alex Okiemute; Onojeghuo, Ajoke Ruth

2017-07-01

This study investigated the combined use of multispectral/hyperspectral imagery and LiDAR data for habitat mapping across parts of south Cumbria, North West England. The methodology adopted in this study integrated spectral information contained in pansharp QuickBird multispectral/AISA Eagle hyperspectral imagery and LiDAR-derived measures with object-based machine learning classifiers and ensemble analysis techniques. Using the LiDAR point cloud data, elevation models (such as the Digital Surface Model and Digital Terrain Model raster) and intensity features were extracted directly. The LiDAR-derived measures exploited in this study included Canopy Height Model, intensity and topographic information (i.e. mean, maximum and standard deviation). These three LiDAR measures were combined with spectral information contained in the pansharp QuickBird and Eagle MNF transformed imagery for image classification experiments. A fusion of pansharp QuickBird multispectral and Eagle MNF hyperspectral imagery with all LiDAR-derived measures generated the best classification accuracies, 89.8 and 92.6% respectively. These results were generated with the Support Vector Machine and Random Forest machine learning algorithms respectively. The ensemble analysis of all three learning machine classifiers for the pansharp QuickBird and Eagle MNF fused data outputs did not significantly increase the overall classification accuracy. Results of the study demonstrate the potential of combining either very high spatial resolution multispectral or hyperspectral imagery with LiDAR data for habitat mapping.

Spectral Knowledge (SK-UTALCA): Software for Exploratory Analysis of High-Resolution Spectral Reflectance Data on Plant Breeding

PubMed Central

Lobos, Gustavo A.; Poblete-Echeverría, Carlos

2017-01-01

This article describes public, free software that provides efficient exploratory analysis of high-resolution spectral reflectance data. Spectral reflectance data can suffer from problems such as poor signal to noise ratios in various wavebands or invalid measurements due to changes in incoming solar radiation or operator fatigue leading to poor orientation of sensors. Thus, exploratory data analysis is essential to identify appropriate data for further analyses. This software overcomes the problem that analysis tools such as Excel are cumbersome to use for the high number of wavelengths and samples typically acquired in these studies. The software, Spectral Knowledge (SK-UTALCA), was initially developed for plant breeding, but it is also suitable for other studies such as precision agriculture, crop protection, ecophysiology plant nutrition, and soil fertility. Various spectral reflectance indices (SRIs) are often used to relate crop characteristics to spectral data and the software is loaded with 255 SRIs which can be applied quickly to the data. This article describes the architecture and functions of SK-UTALCA and the features of the data that led to the development of each of its modules. PMID:28119705

Spectral Knowledge (SK-UTALCA): Software for Exploratory Analysis of High-Resolution Spectral Reflectance Data on Plant Breeding.

PubMed

Lobos, Gustavo A; Poblete-Echeverría, Carlos

2016-01-01

This article describes public, free software that provides efficient exploratory analysis of high-resolution spectral reflectance data. Spectral reflectance data can suffer from problems such as poor signal to noise ratios in various wavebands or invalid measurements due to changes in incoming solar radiation or operator fatigue leading to poor orientation of sensors. Thus, exploratory data analysis is essential to identify appropriate data for further analyses. This software overcomes the problem that analysis tools such as Excel are cumbersome to use for the high number of wavelengths and samples typically acquired in these studies. The software, Spectral Knowledge (SK-UTALCA), was initially developed for plant breeding, but it is also suitable for other studies such as precision agriculture, crop protection, ecophysiology plant nutrition, and soil fertility. Various spectral reflectance indices (SRIs) are often used to relate crop characteristics to spectral data and the software is loaded with 255 SRIs which can be applied quickly to the data. This article describes the architecture and functions of SK-UTALCA and the features of the data that led to the development of each of its modules.

Robust and transferable quantification of NMR spectral quality using IROC analysis

NASA Astrophysics Data System (ADS)

Zambrello, Matthew A.; Maciejewski, Mark W.; Schuyler, Adam D.; Weatherby, Gerard; Hoch, Jeffrey C.

2017-12-01

Non-Fourier methods are increasingly utilized in NMR spectroscopy because of their ability to handle nonuniformly-sampled data. However, non-Fourier methods present unique challenges due to their nonlinearity, which can produce nonrandom noise and render conventional metrics for spectral quality such as signal-to-noise ratio unreliable. The lack of robust and transferable metrics (i.e. applicable to methods exhibiting different nonlinearities) has hampered comparison of non-Fourier methods and nonuniform sampling schemes, preventing the identification of best practices. We describe a novel method, in situ receiver operating characteristic analysis (IROC), for characterizing spectral quality based on the Receiver Operating Characteristic curve. IROC utilizes synthetic signals added to empirical data as "ground truth", and provides several robust scalar-valued metrics for spectral quality. This approach avoids problems posed by nonlinear spectral estimates, and provides a versatile quantitative means of characterizing many aspects of spectral quality. We demonstrate applications to parameter optimization in Fourier and non-Fourier spectral estimation, critical comparison of different methods for spectrum analysis, and optimization of nonuniform sampling schemes. The approach will accelerate the discovery of optimal approaches to nonuniform sampling experiment design and non-Fourier spectrum analysis for multidimensional NMR.

Non-traditional applications of laser desorption/ionization mass spectrometry

NASA Astrophysics Data System (ADS)

McAlpin, Casey R.

Seven studies were carried out using laser desorption/ionization mass spectrometry (LDI MS) to develop enhanced methodologies for a variety of analyte systems by investigating analyte chemistries, ionization processes, and elimination of spectral interferences. Applications of LDI and matrix assisted laser/desorption/ionization (MALDI) have been previously limited by poorly understood ionization phenomena, and spectral interferences from matrices. Matrix assisted laser desorption ionization MS is well suited to the analysis of proteins. However, the proteins associated with bacteriophages often form complexes which are too massive for detection with a standard MALDI mass spectrometer. As such, methodologies for pretreatment of these samples are discussed in detail in the first chapter. Pretreatment of bacteriophage samples with reducing agents disrupted disulfide linkages and allowed enhanced detection of bacteriophage proteins. The second chapter focuses on the use of MALDI MS for lipid compounds whose molecular mass is significantly less than the proteins for which MALDI is most often applied. The use of MALDI MS for lipid analysis presented unique challenges such as matrix interference and differential ionization efficiencies. It was observed that optimization of the matrix system, and addition of cationization reagents mitigated these challenges and resulted in an enhanced methodology for MALDI MS of lipids. One of the challenges commonly encountered in efforts to expand MALDI MS applications is as previously mentioned interferences introduced by organic matrix molecules. The third chapter focuses on the development of a novel inorganic matrix replacement system called metal oxide laser ionization mass spectrometry (MOLI MS). In contrast to other matrix replacements, considerable effort was devoted to elucidating the ionization mechanism. It was shown that chemisorption of analytes to the metal oxide surface produced acidic adsorbed species which then protonated free analyte molecules. Expanded applications of MOLI MS were developed following description of the ionization mechanism. A series of experiments were carried out involving treatment of metal oxide surfaces with reagent molecules to expand MOLI MS and develop enhanced MOLI MS methodologies. It was found that treatment of the metal oxide surface with a small molecule to act as a proton source expanded MOLI MS to analytes which did not form acidic adsorbed species. Proton-source pretreated MOLI MS was then used for the analysis of oils obtained from the fast, anoxic pyrolysis of biomass (py-oil). These samples are complex and produce MOLI mass spectra with many peaks. In this experiment, methods of data reduction including Kendrick mass defects and nominal mass z*-scores, which are commonly used for the study of petroleum fractions, were used to interpret these spectra and identify the major constituencies of py-oils. Through data reduction and collision induced dissociation (CID), homologous series of compounds were rapidly identified. The final chapter involves using metal oxides to catalytically cleave the ester linkage on lipids containing fatty acids in addition to ionization. The cleavage process results in the production of spectra similar to those observed with saponification/methylation. Fatty acid profiles were generated for a variety of micro-organisms to differentiate between bacterial species. (Abstract shortened by UMI.)

SPAM- SPECTRAL ANALYSIS MANAGER (DEC VAX/VMS VERSION)

NASA Technical Reports Server (NTRS)

Solomon, J. E.

1994-01-01

The Spectral Analysis Manager (SPAM) was developed to allow easy qualitative analysis of multi-dimensional imaging spectrometer data. Imaging spectrometers provide sufficient spectral sampling to define unique spectral signatures on a per pixel basis. Thus direct material identification becomes possible for geologic studies. SPAM provides a variety of capabilities for carrying out interactive analysis of the massive and complex datasets associated with multispectral remote sensing observations. In addition to normal image processing functions, SPAM provides multiple levels of on-line help, a flexible command interpretation, graceful error recovery, and a program structure which can be implemented in a variety of environments. SPAM was designed to be visually oriented and user friendly with the liberal employment of graphics for rapid and efficient exploratory analysis of imaging spectrometry data. SPAM provides functions to enable arithmetic manipulations of the data, such as normalization, linear mixing, band ratio discrimination, and low-pass filtering. SPAM can be used to examine the spectra of an individual pixel or the average spectra over a number of pixels. SPAM also supports image segmentation, fast spectral signature matching, spectral library usage, mixture analysis, and feature extraction. High speed spectral signature matching is performed by using a binary spectral encoding algorithm to separate and identify mineral components present in the scene. The same binary encoding allows automatic spectral clustering. Spectral data may be entered from a digitizing tablet, stored in a user library, compared to the master library containing mineral standards, and then displayed as a timesequence spectral movie. The output plots, histograms, and stretched histograms produced by SPAM can be sent to a lineprinter, stored as separate RGB disk files, or sent to a Quick Color Recorder. SPAM is written in C for interactive execution and is available for two different machine environments. There is a DEC VAX/VMS version with a central memory requirement of approximately 242K of 8 bit bytes and a machine independent UNIX 4.2 version. The display device currently supported is the Raster Technologies display processor. Other 512 x 512 resolution color display devices, such as De Anza, may be added with minor code modifications. This program was developed in 1986.

SPAM- SPECTRAL ANALYSIS MANAGER (UNIX VERSION)

NASA Technical Reports Server (NTRS)

Solomon, J. E.

1994-01-01

The Spectral Analysis Manager (SPAM) was developed to allow easy qualitative analysis of multi-dimensional imaging spectrometer data. Imaging spectrometers provide sufficient spectral sampling to define unique spectral signatures on a per pixel basis. Thus direct material identification becomes possible for geologic studies. SPAM provides a variety of capabilities for carrying out interactive analysis of the massive and complex datasets associated with multispectral remote sensing observations. In addition to normal image processing functions, SPAM provides multiple levels of on-line help, a flexible command interpretation, graceful error recovery, and a program structure which can be implemented in a variety of environments. SPAM was designed to be visually oriented and user friendly with the liberal employment of graphics for rapid and efficient exploratory analysis of imaging spectrometry data. SPAM provides functions to enable arithmetic manipulations of the data, such as normalization, linear mixing, band ratio discrimination, and low-pass filtering. SPAM can be used to examine the spectra of an individual pixel or the average spectra over a number of pixels. SPAM also supports image segmentation, fast spectral signature matching, spectral library usage, mixture analysis, and feature extraction. High speed spectral signature matching is performed by using a binary spectral encoding algorithm to separate and identify mineral components present in the scene. The same binary encoding allows automatic spectral clustering. Spectral data may be entered from a digitizing tablet, stored in a user library, compared to the master library containing mineral standards, and then displayed as a timesequence spectral movie. The output plots, histograms, and stretched histograms produced by SPAM can be sent to a lineprinter, stored as separate RGB disk files, or sent to a Quick Color Recorder. SPAM is written in C for interactive execution and is available for two different machine environments. There is a DEC VAX/VMS version with a central memory requirement of approximately 242K of 8 bit bytes and a machine independent UNIX 4.2 version. The display device currently supported is the Raster Technologies display processor. Other 512 x 512 resolution color display devices, such as De Anza, may be added with minor code modifications. This program was developed in 1986.

Simulation of time-dispersion spectral device with sample spectra accumulation

NASA Astrophysics Data System (ADS)

Zhdanov, Arseny; Khansuvarov, Ruslan; Korol, Georgy

2014-09-01

This research is conducted in order to design a spectral device for light sources power spectrum analysis. The spectral device should process radiation from sources, direct contact with radiation of which is either impossible or undesirable. Such sources include jet blast of an aircraft, optical radiation in metallurgy and textile industry. In proposed spectral device optical radiation is guided out of unfavorable environment via a piece of optical fiber with high dispersion. It is necessary for analysis to make samples of analyzed radiation as short pulses. Dispersion properties of such optical fiber cause spectral decomposition of input optical pulses. The faster time of group delay vary the stronger the spectral decomposition effect. This effect allows using optical fiber with high dispersion as a major element of proposed spectral device. Duration of sample must be much shorter than group delay time difference of a dispersive system. In the given frequency range this characteristic has to be linear. The frequency range is 400 … 500 THz for typical optical fiber. Using photonic-crystal fiber (PCF) gives much wider spectral range for analysis. In this paper we propose simulation of single pulse transmission through dispersive system with linear dispersion characteristic and quadratic-detected output responses accumulation. During simulation we propose studying influence of optical fiber dispersion characteristic angle on spectral measurement results. We also consider pulse duration and group delay time difference impact on output pulse shape and duration. Results show the most suitable dispersion characteristic that allow choosing the structure of PCF - major element of time-dispersion spectral analysis method and required number of samples for reliable assessment of measured spectrum.

A statistical evaluation of spectral fingerprinting methods using analysis of variance and principal component analysis

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...

What drives high flow events in the Swiss Alps? Recent developments in wavelet spectral analysis and their application to hydrology

NASA Astrophysics Data System (ADS)

Schaefli, B.; Maraun, D.; Holschneider, M.

2007-12-01

Extreme hydrological events are often triggered by exceptional co-variations of the relevant hydrometeorological processes and in particular by exceptional co-oscillations at various temporal scales. Wavelet and cross wavelet spectral analysis offers promising time-scale resolved analysis methods to detect and analyze such exceptional co-oscillations. This paper presents the state-of-the-art methods of wavelet spectral analysis, discusses related subtleties, potential pitfalls and recently developed solutions to overcome them and shows how wavelet spectral analysis, if combined to a rigorous significance test, can lead to reliable new insights into hydrometeorological processes for real-world applications. The presented methods are applied to detect potentially flood triggering situations in a high Alpine catchment for which a recent re-estimation of design floods encountered significant problems simulating the observed high flows. For this case study, wavelet spectral analysis of precipitation, temperature and discharge offers a powerful tool to help detecting potentially flood producing meteorological situations and to distinguish between different types of floods with respect to the prevailing critical hydrometeorological conditions. This opens very new perspectives for the analysis of model performances focusing on the occurrence and non-occurrence of different types of high flow events. Based on the obtained results, the paper summarizes important recommendations for future applications of wavelet spectral analysis in hydrology.

Open Rotor Computational Aeroacoustic Analysis with an Immersed Boundary Method

NASA Technical Reports Server (NTRS)

Brehm, Christoph; Barad, Michael F.; Kiris, Cetin C.

2016-01-01

Reliable noise prediction capabilities are essential to enable novel fuel efficient open rotor designs that can meet the community and cabin noise standards. Toward this end, immersed boundary methods have reached a level of maturity where more and more complex flow problems can be tackled with this approach. This paper demonstrates that our higher-order immersed boundary method provides the ability for aeroacoustic analysis of wake-dominated flow fields generated by a contra-rotating open rotor. This is the first of a kind aeroacoustic simulation of an open rotor propulsion system employing an immersed boundary method. In addition to discussing the methodologies of how to apply the immersed boundary method to this moving boundary problem, we will provide a detailed validation of the aeroacoustic analysis approach employing the Launch Ascent and Vehicle Aerodynamics (LAVA) solver. Two free-stream Mach numbers with M=0.2 and M=0.78 are considered in this analysis that are based on the nominally take-off and cruise flow conditions. The simulation data is compared to available experimental data and other computational results employing more conventional CFD methods. Spectral analysis is used to determine the dominant wave propagation pattern in the acoustic near-field.

Enhancement of long period components of recorded and synthetic ground motions using InSAR

USGS Publications Warehouse

Abell, J.A.; Carlos de la Llera, J.; Wicks, C.W.

2011-01-01

Tall buildings and flexible structures require a better characterization of long period ground motion spectra than the one provided by current seismic building codes. Motivated by that, a methodology is proposed and tested to improve recorded and synthetic ground motions which are consistent with the observed co-seismic displacement field obtained from interferometric synthetic aperture radar (InSAR) analysis of image data for the Tocopilla 2007 earthquake (Mw=7.7) in Northern Chile. A methodology is proposed to correct the observed motions such that, after double integration, they are coherent with the local value of the residual displacement. Synthetic records are generated by using a stochastic finite-fault model coupled with a long period pulse to capture the long period fling effect. It is observed that the proposed co-seismic correction yields records with more accurate long-period spectral components as compared with regular correction schemes such as acausal filtering. These signals provide an estimate for the velocity and displacement spectra, which are essential for tall-building design. Furthermore, hints are provided as to the shape of long-period spectra for seismic zones prone to large co-seismic displacements such as the Nazca-South American zone. ?? 2011 Elsevier Ltd.

The characteristics and interpretability of land surface change and implications for project design

USGS Publications Warehouse

Sohl, Terry L.; Gallant, Alisa L.; Loveland, Thomas R.

2004-01-01

The need for comprehensive, accurate information on land-cover change has never been greater. While remotely sensed imagery affords the opportunity to provide information on land-cover change over large geographic expanses at a relatively low cost, the characteristics of land-surface change bring into question the suitability of many commonly used methodologies. Algorithm-based methodologies to detect change generally cannot provide the same level of accuracy as the analyses done by human interpreters. Results from the Land Cover Trends project, a cooperative venture that includes the U.S. Geological Survey, Environmental Protection Agency, and National Aeronautics and Space Administration, have shown that land-cover conversion is a relatively rare event, occurs locally in small patches, varies geographically and temporally, and is spectrally ambiguous. Based on these characteristics of change and the type of information required, manual interpretation was selected as the primary means of detecting change in the Land Cover Trends project. Mixtures of algorithm-based detection and manual interpretation may often prove to be the most feasible and appropriate design for change-detection applications. Serious examination of the expected characteristics and measurability of change must be considered during the design and implementation phase of any change analysis project.

Sand/cement ratio evaluation on mortar using neural networks and ultrasonic transmission inspection.

PubMed

Molero, M; Segura, I; Izquierdo, M A G; Fuente, J V; Anaya, J J

2009-02-01

The quality and degradation state of building materials can be determined by nondestructive testing (NDT). These materials are composed of a cementitious matrix and particles or fragments of aggregates. Sand/cement ratio (s/c) provides the final material quality; however, the sand content can mask the matrix properties in a nondestructive measurement. Therefore, s/c ratio estimation is needed in nondestructive characterization of cementitious materials. In this study, a methodology to classify the sand content in mortar is presented. The methodology is based on ultrasonic transmission inspection, data reduction, and features extraction by principal components analysis (PCA), and neural network classification. This evaluation is carried out with several mortar samples, which were made while taking into account different cement types and s/c ratios. The estimated s/c ratio is determined by ultrasonic spectral attenuation with three different broadband transducers (0.5, 1, and 2 MHz). Statistical PCA to reduce the dimension of the captured traces has been applied. Feed-forward neural networks (NNs) are trained using principal components (PCs) and their outputs are used to display the estimated s/c ratios in false color images, showing the s/c ratio distribution of the mortar samples.

Microstructure measurements in natural waters: Methodology and applications

NASA Astrophysics Data System (ADS)

Roget, Elena; Lozovatsky, Iossif; Sanchez, Xavier; Figueroa, Manuel

2006-08-01

Modern approaches to microstructure data processing, including wavelet denoising, are discussed. The wavelet procedure is applied to small-scale shear signals before estimating the dissipation rate ε and to the temperature/density profiles used to calculate Thorpe scales. Microstructure data obtained on the Mediterranean shelf of Catalonia are used to illustrate various approaches to the Thorpe displacement calculations. It is suggested that the Weibull probability function is an appropriate model for the Thorpe scale distribution. Microstructure measurements from the upper layer of the Boadella reservoir (Catalonia, Spain) support this finding. A new analytical approximation for the 1D Panchev-Kesich spectrum is deduced and the results of ε computation are compared with spectral fitting by the widely used Nasmyth spectrum. Applying the Kraichnan spectral model to compute ε from temperature spectra in the convective-viscous sub-range is examined as an alternative to the Batchelor spectrum. Microstructure measurements taken in Lake Banyoles (Catalonia, Spain) and in the North Atlantic were used for spectral calculations. Statistical analysis of eddy Kb and thermal Kθ diffusivities measured on a shallow shelf of the Black Sea shows the importance of process-orientated domain averaging of the diffusivities in obtaining good correspondence between Kb and Kθ in active turbulent regions. In weakly turbulent, stratified interior layers, the averaged Kb and Kθ differ significantly, which may point to the inapplicability of isotropic formulae used for ε and temperature dissipation χθ estimates, as well as to a dependence of the mixing efficiency γ on the Richardson number or in some cases on regions of fossil turbulence.

Raman-spectroscopy-based chemical contaminant detection in milk powder

NASA Astrophysics Data System (ADS)

Dhakal, Sagar; Chao, Kuanglin; Qin, Jianwei; Kim, Moon S.

2015-05-01

Addition of edible and inedible chemical contaminants in food powders for purposes of economic benefit has become a recurring trend. In recent years, severe health issues have been reported due to consumption of food powders contaminated with chemical substances. This study examines the effect of spatial resolution used during spectral collection to select the optimal spatial resolution for detecting melamine in milk powder. Sample depth of 2mm, laser intensity of 200mw, and exposure time of 0.1s were previously determined as optimal experimental parameters for Raman imaging. Spatial resolution of 0.25mm was determined as the optimal resolution for acquiring spectral signal of melamine particles from a milk-melamine mixture sample. Using the optimal resolution of 0.25mm, sample depth of 2mm and laser intensity of 200mw obtained from previous study, spectral signal from 5 different concentration of milk-melamine mixture (1%, 0.5%, 0.1%, 0.05%, and 0.025%) were acquired to study the relationship between number of detected melamine pixels and corresponding sample concentration. The result shows that melamine concentration has a linear relation with detected number of melamine pixels with correlation coefficient of 0.99. It can be concluded that the quantitative analysis of powder mixture is dependent on many factors including physical characteristics of mixture, experimental parameters, and sample depth. The results obtained in this study are promising. We plan to apply the result obtained from this study to develop quantitative detection model for rapid screening of melamine in milk powder. This methodology can also be used for detection of other chemical contaminants in milk powders.

Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) with Raman Imaging Applied to Lunar Meteorites.

PubMed

Smith, Joseph P; Smith, Frank C; Booksh, Karl S

2018-03-01

Lunar meteorites provide a more random sampling of the surface of the Moon than do the returned lunar samples, and they provide valuable information to help estimate the chemical composition of the lunar crust, the lunar mantle, and the bulk Moon. As of July 2014, ∼96 lunar meteorites had been documented and ten of these are unbrecciated mare basalts. Using Raman imaging with multivariate curve resolution-alternating least squares (MCR-ALS), we investigated portions of polished thin sections of paired, unbrecciated, mare-basalt lunar meteorites that had been collected from the LaPaz Icefield (LAP) of Antarctica-LAP 02205 and LAP 04841. Polarized light microscopy displays that both meteorites are heterogeneous and consist of polydispersed sized and shaped particles of varying chemical composition. For two distinct probed areas within each meteorite, the individual chemical species and associated chemical maps were elucidated using MCR-ALS applied to Raman hyperspectral images. For LAP 02205, spatially and spectrally resolved clinopyroxene, ilmenite, substrate-adhesive epoxy, and diamond polish were observed within the probed areas. Similarly, for LAP 04841, spatially resolved chemical images with corresponding resolved Raman spectra of clinopyroxene, troilite, a high-temperature polymorph of anorthite, substrate-adhesive epoxy, and diamond polish were generated. In both LAP 02205 and LAP 04841, substrate-adhesive epoxy and diamond polish were more readily observed within fractures/veinlet features. Spectrally diverse clinopyroxenes were resolved in LAP 04841. Factors that allow these resolved clinopyroxenes to be differentiated include crystal orientation, spatially distinct chemical zoning of pyroxene crystals, and/or chemical and molecular composition. The minerals identified using this analytical methodology-clinopyroxene, anorthite, ilmenite, and troilite-are consistent with the results of previous studies of the two meteorites using electron microprobe analysis. To our knowledge, this is the first report of MCR-ALS with Raman imaging used for the investigation of both lunar and other types of meteorites. We have demonstrated the use of multivariate analysis methods, namely MCR-ALS, with Raman imaging to investigate heterogeneous lunar meteorites. Our analytical methodology can be used to elucidate the chemical, molecular, and structural characteristics of phases in a host of complex, heterogeneous geological, geochemical, and extraterrestrial materials.

Rapid Prototyping of Hyperspectral Image Analysis Algorithms for Improved Invasive Species Decision Support Tools

NASA Astrophysics Data System (ADS)

Bruce, L. M.; Ball, J. E.; Evangilista, P.; Stohlgren, T. J.

2006-12-01

Nonnative invasive species adversely impact ecosystems, causing loss of native plant diversity, species extinction, and impairment of wildlife habitats. As a result, over the past decade federal and state agencies and nongovernmental organizations have begun to work more closely together to address the management of invasive species. In 2005, approximately 500M dollars was budgeted by U.S. Federal Agencies for the management of invasive species. Despite extensive expenditures, most of the methods used to detect and quantify the distribution of these invaders are ad hoc, at best. Likewise, decisions on the type of management techniques to be used or evaluation of the success of these methods are typically non-systematic. More efficient methods to detect or predict the occurrence of these species, as well as the incorporation of this knowledge into decision support systems, are greatly needed. In this project, rapid prototyping capabilities (RPC) are utilized for an invasive species application. More precisely, our recently developed analysis techniques for hyperspectral imagery are being prototyped for inclusion in the national Invasive Species Forecasting System (ISFS). The current ecological forecasting tools in ISFS will be compared to our hyperspectral-based invasives prediction algorithms to determine if/how the newer algorithms enhance the performance of ISFS. The PIs have researched the use of remotely sensed multispectral and hyperspectral reflectance data for the detection of invasive vegetative species. As a result, the PI has designed, implemented, and benchmarked various target detection systems that utilize remotely sensed data. These systems have been designed to make decisions based on a variety of remotely sensed data, including high spectral/spatial resolution hyperspectral signatures (1000's of spectral bands, such as those measured using ASD handheld devices), moderate spectral/spatial resolution hyperspectral images (100's of spectral bands, such as Hyperion imagery), and low spectral/spatial resolution images (such as MODIS imagery). These algorithms include hyperspectral exploitation methods such as stepwise-LDA band selection, optimized spectral band grouping, and stepwise PCA component selection. The PIs have extensive experience with combining these recently- developed methods with conventional classifiers to form an end-to-end automated target recognition (ATR) system for detecting invasive species. The outputs of these systems can be invasive prediction maps, as well as quantitative accuracy assessments like confusion matrices, user accuracies, and producer accuracies. For all of these research endeavors, the PIs have developed numerous advanced signal and image processing methodologies, as well a suite of associated software modules. However, the use of the prototype software modules has been primarily contained to Mississippi State University. The project described in this presentation and paper will enable future systematic inclusion of these software modules into a DSS with national scope.

Shape selection in Landsat time series: A tool for monitoring forest dynamics

Treesearch

Gretchen G. Moisen; Mary C. Meyer; Todd A. Schroeder; Xiyue Liao; Karen G. Schleeweis; Elizabeth A. Freeman; Chris Toney

2016-01-01

We present a new methodology for fitting nonparametric shape-restricted regression splines to time series of Landsat imagery for the purpose of modeling, mapping, and monitoring annual forest disturbance dynamics over nearly three decades. For each pixel and spectral band or index of choice in temporal Landsat data, our method delivers a smoothed rendition of...

Digital techniques for ULF wave polarization analysis

NASA Technical Reports Server (NTRS)

Arthur, C. W.

1979-01-01

Digital power spectral and wave polarization analysis are powerful techniques for studying ULF waves in the earth's magnetosphere. Four different techniques for using the spectral matrix to perform such an analysis have been presented in the literature. Three of these techniques are similar in that they require transformation of the spectral matrix to the principal axis system prior to performing the polarization analysis. The differences in the three techniques lie in the manner in which determine this transformation. A comparative study of these three techniques using both simulated and real data has shown them to be approximately equal in quality of performance. The fourth technique does not require transformation of the spectral matrix. Rather, it uses the measured spectral matrix and state vectors for a desired wave type to design a polarization detector function in the frequency domain. The design of various detector functions and their application to both simulated and real data will be presented.

Global spectral graph wavelet signature for surface analysis of carpal bones

NASA Astrophysics Data System (ADS)

Masoumi, Majid; Rezaei, Mahsa; Ben Hamza, A.

2018-02-01

Quantitative shape comparison is a fundamental problem in computer vision, geometry processing and medical imaging. In this paper, we present a spectral graph wavelet approach for shape analysis of carpal bones of the human wrist. We employ spectral graph wavelets to represent the cortical surface of a carpal bone via the spectral geometric analysis of the Laplace-Beltrami operator in the discrete domain. We propose global spectral graph wavelet (GSGW) descriptor that is isometric invariant, efficient to compute, and combines the advantages of both low-pass and band-pass filters. We perform experiments on shapes of the carpal bones of ten women and ten men from a publicly-available database of wrist bones. Using one-way multivariate analysis of variance (MANOVA) and permutation testing, we show through extensive experiments that the proposed GSGW framework gives a much better performance compared to the global point signature embedding approach for comparing shapes of the carpal bones across populations.

Global spectral graph wavelet signature for surface analysis of carpal bones.

PubMed

Masoumi, Majid; Rezaei, Mahsa; Ben Hamza, A

2018-02-05

Quantitative shape comparison is a fundamental problem in computer vision, geometry processing and medical imaging. In this paper, we present a spectral graph wavelet approach for shape analysis of carpal bones of the human wrist. We employ spectral graph wavelets to represent the cortical surface of a carpal bone via the spectral geometric analysis of the Laplace-Beltrami operator in the discrete domain. We propose global spectral graph wavelet (GSGW) descriptor that is isometric invariant, efficient to compute, and combines the advantages of both low-pass and band-pass filters. We perform experiments on shapes of the carpal bones of ten women and ten men from a publicly-available database of wrist bones. Using one-way multivariate analysis of variance (MANOVA) and permutation testing, we show through extensive experiments that the proposed GSGW framework gives a much better performance compared to the global point signature embedding approach for comparing shapes of the carpal bones across populations.

GEOS-2 C-band radar system project. Spectral analysis as related to C-band radar data analysis

NASA Technical Reports Server (NTRS)

1972-01-01

Work performed on spectral analysis of data from the C-band radars tracking GEOS-2 and on the development of a data compaction method for the GEOS-2 C-band radar data is described. The purposes of the spectral analysis study were to determine the optimum data recording and sampling rates for C-band radar data and to determine the optimum method of filtering and smoothing the data. The optimum data recording and sampling rate is defined as the rate which includes an optimum compromise between serial correlation and the effects of frequency folding. The goal in development of a data compaction method was to reduce to a minimum the amount of data stored, while maintaining all of the statistical information content of the non-compacted data. A digital computer program for computing estimates of the power spectral density function of sampled data was used to perform the spectral analysis study.

Different techniques of multispectral data analysis for vegetation fraction retrieval

NASA Astrophysics Data System (ADS)

Kancheva, Rumiana; Georgiev, Georgi

2012-07-01

Vegetation monitoring is one of the most important applications of remote sensing technologies. In respect to farmlands, the assessment of crop condition constitutes the basis of growth, development, and yield processes monitoring. Plant condition is defined by a set of biometric variables, such as density, height, biomass amount, leaf area index, and etc. The canopy cover fraction is closely related to these variables, and is state-indicative of the growth process. At the same time it is a defining factor of the soil-vegetation system spectral signatures. That is why spectral mixtures decomposition is a primary objective in remotely sensed data processing and interpretation, specifically in agricultural applications. The actual usefulness of the applied methods depends on their prediction reliability. The goal of this paper is to present and compare different techniques for quantitative endmember extraction from soil-crop patterns reflectance. These techniques include: linear spectral unmixing, two-dimensional spectra analysis, spectral ratio analysis (vegetation indices), spectral derivative analysis (red edge position), colorimetric analysis (tristimulus values sum, chromaticity coordinates and dominant wavelength). The objective is to reveal their potential, accuracy and robustness for plant fraction estimation from multispectral data. Regression relationships have been established between crop canopy cover and various spectral estimators.

Perceptual aspects of reproduced sound in car cabin acoustics.

PubMed

Kaplanis, Neofytos; Bech, Søren; Tervo, Sakari; Pätynen, Jukka; Lokki, Tapio; van Waterschoot, Toon; Jensen, Søren Holdt

2017-03-01

An experiment was conducted to determine the perceptual effects of car cabin acoustics on the reproduced sound field. In-car measurements were conducted whilst the cabin's interior was physically modified. The captured sound fields were recreated in the laboratory using a three-dimensional loudspeaker array. A panel of expert assessors followed a rapid sensory analysis protocol, the flash profile, to perceptually characterize and evaluate 12 acoustical conditions of the car cabin using individually elicited attributes. A multivariate analysis revealed the panel's consensus and the identified perceptual constructs. Six perceptual constructs characterize the differences between the acoustical conditions of the cabin, related to bass, ambience, transparency, width and envelopment, brightness, and image focus. The current results indicate the importance of several acoustical properties of a car's interior on the perceived sound qualities. Moreover, they signify the capacity of the applied methodology in assessing spectral and spatial properties of automotive environments in laboratory settings using a time-efficient and flexible protocol.

Preliminary JIRAM results from Juno polar observations: 1. Methodology and analysis applied to the Jovian northern polar region

NASA Astrophysics Data System (ADS)

Dinelli, B. M.; Fabiano, F.; Adriani, A.; Altieri, F.; Moriconi, M. L.; Mura, A.; Sindoni, G.; Filacchione, G.; Tosi, F.; Migliorini, A.; Grassi, D.; Piccioni, G.; Noschese, R.; Cicchetti, A.; Bolton, S. J.; Connerney, J. E. P.; Atreya, S. K.; Bagenal, F.; Gladstone, G. R.; Hansen, C. J.; Kurth, W. S.; Levin, S. M.; Mauk, B. H.; McComas, D. J.; Gèrard, J.-C.; Turrini, D.; Stefani, S.; Amoroso, M.; Olivieri, A.

2017-05-01

During the first orbit around Jupiter of the NASA/Juno mission, the Jovian Auroral Infrared Mapper (JIRAM) instrument observed the auroral regions with a large number of measurements. The measured spectra show both the emission of the H3+ ion and of methane in the 3-4 μm spectral region. In this paper we describe the analysis method developed to retrieve temperature and column density (CD) of the H3+ ion from JIRAM spectra in the northern auroral region. The high spatial resolution of JIRAM shows an asymmetric aurora, with CD and temperature ovals not superimposed and not exactly located where models and previous observations suggested. On the main oval averaged H3+ CDs span between 1.8 × 1012 cm-2 and 2.8 × 1012 cm-2, while the retrieved temperatures show values between 800 and 950 K. JIRAM indicates a complex relationship among H3+ CDs and temperatures on the Jupiter northern aurora.

Three-dimensional Noninvasive Monitoring Iodine-131 Uptake in the Thyroid Using a Modified Cerenkov Luminescence Tomography Approach

PubMed Central

Qu, Xiaochao; Yang, Weidong; Liang, Jimin; Wang, Jing; Tian, Jie

2012-01-01

Background Cerenkov luminescence tomography (CLT) provides the three-dimensional (3D) radiopharmaceutical biodistribution in small living animals, which is vital to biomedical imaging. However, existing single-spectral and multispectral methods are not very efficient and effective at reconstructing the distribution of the radionuclide tracer. In this paper, we present a semi-quantitative Cerenkov radiation spectral characteristic-based source reconstruction method named the hybrid spectral CLT, to efficiently reconstruct the radionuclide tracer with both encouraging reconstruction results and less acquisition and image reconstruction time. Methodology/Principal Findings We constructed the implantation mouse model implanted with a 400 µCi Na131I radioactive source and the physiological mouse model received an intravenous tail injection of 400 µCi radiopharmaceutical Iodine-131 (I-131) to validate the performance of the hybrid spectral CLT and compared the reconstruction results, acquisition, and image reconstruction time with that of single-spectral and multispectral CLT. Furthermore, we performed 3D noninvasive monitoring of I-131 uptake in the thyroid and quantified I-131 uptake in vivo using hybrid spectral CLT. Results showed that the reconstruction based on the hybrid spectral CLT was more accurate in localization and quantification than using single-spectral CLT, and was more efficient in the in vivo experiment compared with multispectral CLT. Additionally, 3D visualization of longitudinal observations suggested that the reconstructed energy of I-131 uptake in the thyroid increased with acquisition time and there was a robust correlation between the reconstructed energy versus the gamma ray counts of I-131 (). The ex vivo biodistribution experiment further confirmed the I-131 uptake in the thyroid for hybrid spectral CLT. Conclusions/Significance Results indicated that hybrid spectral CLT could be potentially used for thyroid imaging to evaluate its function and monitor its treatment for thyroid cancer. PMID:22629431

The NPP and J1 CrIS Operational High-Resolution Channel Selection for the NUCAPS algorithm: A demonstration of global applicability to meet users needs

NASA Astrophysics Data System (ADS)

Smith, J.; Gambacorta, A.; Barnet, C.; Smith, N.; Goldberg, M.; Pierce, B.; Wolf, W.; King, T.

2016-12-01

This work presents an overview of the NPP and J1 CrIS high resolution operational channel selection. Our methodology focuses on the spectral sensitivity characteristics of the available channels in order to maximize information content and spectral purity. These aspects are key to ensure accuracy in the retrieval products, particularly for trace gases. We will provide a demonstration of its global optimality by analyzing different test cases that are of particular interests to our JPSS Proving Ground and Risk Reduction user applications. A focus will be on high resolution trace gas retrieval capability in the context of the Alaska fire initiatives.

Model reductions using a projection formulation

NASA Technical Reports Server (NTRS)

De Villemagne, Christian; Skelton, Robert E.

1987-01-01

A new methodology for model reduction of MIMO systems exploits the notion of an oblique projection. A reduced model is uniquely defined by a projector whose range space and orthogonal to the null space are chosen among the ranges of generalized controllability and observability matrices. The reduced order models match various combinations (chosen by the designer) of four types of parameters of the full order system associated with (1) low frequency response, (2) high frequency response, (3) low frequency power spectral density, and (4) high frequency power spectral density. Thus, the proposed method is a computationally simple substitute for many existing methods, has an extreme flexibility to embrace combinations of existing methods and offers some new features.

Aerosol Retrievals over the Ocean using Channel 1 and 2 AVHRR Data: A Sensitivity Analysis and Preliminary Results

NASA Technical Reports Server (NTRS)

Mishchenko, Michael I.; Geogdzhayev, Igor V.; Cairns, Brian; Rossow, William B.; Lacis, Andrew A.

1999-01-01

This paper outlines the methodology of interpreting channel 1 and 2 AVHRR radiance data over the oceans and describes a detailed analysis of the sensitivity of monthly averages of retrieved aerosol parameters to the assumptions made in different retrieval algorithms. The analysis is based on using real AVHRR data and exploiting accurate numerical techniques for computing single and multiple scattering and spectral absorption of light in the vertically inhomogeneous atmosphere-ocean system. We show that two-channel algorithms can be expected to provide significantly more accurate and less biased retrievals of the aerosol optical thickness than one-channel algorithms and that imperfect cloud screening and calibration uncertainties are by far the largest sources of errors in the retrieved aerosol parameters. Both underestimating and overestimating aerosol absorption as well as the potentially strong variability of the real part of the aerosol refractive index may lead to regional and/or seasonal biases in optical thickness retrievals. The Angstrom exponent appears to be the most invariant aerosol size characteristic and should be retrieved along with optical thickness as the second aerosol parameter.

Integrated Path Differential Absorption Lidar Optimizations Based on Pre-Analyzed Atmospheric Data for ASCENDS Mission Applications

NASA Technical Reports Server (NTRS)

Pliutau, Denis; Prasad, Narasimha S.

2012-01-01

In this paper a modeling method based on data reductions is investigated which includes pre analyzed MERRA atmospheric fields for quantitative estimates of uncertainties introduced in the integrated path differential absorption methods for the sensing of various molecules including CO2. This approach represents the extension of our existing lidar modeling framework previously developed and allows effective on- and offline wavelength optimizations and weighting function analysis to minimize the interference effects such as those due to temperature sensitivity and water vapor absorption. The new simulation methodology is different from the previous implementation in that it allows analysis of atmospheric effects over annual spans and the entire Earth coverage which was achieved due to the data reduction methods employed. The effectiveness of the proposed simulation approach is demonstrated with application to the mixing ratio retrievals for the future ASCENDS mission. Independent analysis of multiple accuracy limiting factors including the temperature, water vapor interferences, and selected system parameters is further used to identify favorable spectral regions as well as wavelength combinations facilitating the reduction in total errors in the retrieved XCO2 values.

The Hierarchical Cortical Organization of Human Speech Processing

PubMed Central

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

2017-01-01

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

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.

Mapping the spatial distribution and activity of (226)Ra at legacy sites through Machine Learning interpretation of gamma-ray spectrometry data.

PubMed

Varley, Adam; Tyler, Andrew; Smith, Leslie; Dale, Paul; Davies, Mike

2016-03-01

Radium ((226)Ra) contamination derived from military, industrial, and pharmaceutical products can be found at a number of historical sites across the world posing a risk to human health. The analysis of spectral data derived using gamma-ray spectrometry can offer a powerful tool to rapidly estimate and map the activity, depth, and lateral distribution of (226)Ra contamination covering an extensive area. Subsequently, reliable risk assessments can be developed for individual sites in a fraction of the timeframe compared to traditional labour-intensive sampling techniques: for example soil coring. However, local heterogeneity of the natural background, statistical counting uncertainty, and non-linear source response are confounding problems associated with gamma-ray spectral analysis. This is particularly challenging, when attempting to deal with enhanced concentrations of a naturally occurring radionuclide such as (226)Ra. As a result, conventional surveys tend to attribute the highest activities to the largest total signal received by a detector (Gross counts): an assumption that tends to neglect higher activities at depth. To overcome these limitations, a methodology was developed making use of Monte Carlo simulations, Principal Component Analysis and Machine Learning based algorithms to derive depth and activity estimates for (226)Ra contamination. The approach was applied on spectra taken using two gamma-ray detectors (Lanthanum Bromide and Sodium Iodide), with the aim of identifying an optimised combination of detector and spectral processing routine. It was confirmed that, through a combination of Neural Networks and Lanthanum Bromide, the most accurate depth and activity estimates could be found. The advantage of the method was demonstrated by mapping depth and activity estimates at a case study site in Scotland. There the method identified significantly higher activity (<3 Bq g(-1)) occurring at depth (>0.4m), that conventional gross counting algorithms failed to identify. It was concluded that the method could easily be employed to identify areas of high activity potentially occurring at depth, prior to intrusive investigation using conventional sampling techniques. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

Combining random forest and 2D correlation analysis to identify serum spectral signatures for neuro-oncology.

PubMed

Smith, Benjamin R; Ashton, Katherine M; Brodbelt, Andrew; Dawson, Timothy; Jenkinson, Michael D; Hunt, Neil T; Palmer, David S; Baker, Matthew J

2016-06-07

Fourier transform infrared (FTIR) spectroscopy has long been established as an analytical technique for the measurement of vibrational modes of molecular systems. More recently, FTIR has been used for the analysis of biofluids with the aim of becoming a tool to aid diagnosis. For the clinician, this represents a convenient, fast, non-subjective option for the study of biofluids and the diagnosis of disease states. The patient also benefits from this method, as the procedure for the collection of serum is much less invasive and stressful than traditional biopsy. This is especially true of patients in whom brain cancer is suspected. A brain biopsy is very unpleasant for the patient, potentially dangerous and can occasionally be inconclusive. We therefore present a method for the diagnosis of brain cancer from serum samples using FTIR and machine learning techniques. The scope of the study involved 433 patients from whom were collected 9 spectra each in the range 600-4000 cm(-1). To begin the development of the novel method, various pre-processing steps were investigated and ranked in terms of final accuracy of the diagnosis. Random forest machine learning was utilised as a classifier to separate patients into cancer or non-cancer categories based upon the intensities of wavenumbers present in their spectra. Generalised 2D correlational analysis was then employed to further augment the machine learning, and also to establish spectral features important for the distinction between cancer and non-cancer serum samples. Using these methods, sensitivities of up to 92.8% and specificities of up to 91.5% were possible. Furthermore, ratiometrics were also investigated in order to establish any correlations present in the dataset. We show a rapid, computationally light, accurate, statistically robust methodology for the identification of spectral features present in differing disease states. With current advances in IR technology, such as the development of rapid discrete frequency collection, this approach is of importance to enable future clinical translation and enables IR to achieve its potential.

SpecViz: Interactive Spectral Data Analysis

NASA Astrophysics Data System (ADS)

Earl, Nicholas Michael; STScI

2016-06-01

The astronomical community is about to enter a new generation of scientific enterprise. With next-generation instrumentation and advanced capabilities, the need has arisen to equip astronomers with the necessary tools to deal with large, multi-faceted data. The Space Telescope Science Institute has initiated a data analysis forum for the creation, development, and maintenance of software tools for the interpretation of these new data sets. SpecViz is a spectral 1-D interactive visualization and analysis application built with Python in an open source development environment. A user-friendly GUI allows for a fast, interactive approach to spectral analysis. SpecViz supports handling of unique and instrument-specific data, incorporation of advanced spectral unit handling and conversions in a flexible, high-performance interactive plotting environment. Active spectral feature analysis is possible through interactive measurement and statistical tools. It can be used to build wide-band SEDs, with the capability of combining or overplotting data products from various instruments. SpecViz sports advanced toolsets for filtering and detrending spectral lines; identifying, isolating, and manipulating spectral features; as well as utilizing spectral templates for renormalizing data in an interactive way. SpecViz also includes a flexible model fitting toolset that allows for multi-component models, as well as custom models, to be used with various fitting and decomposition routines. SpecViz also features robust extension via custom data loaders and connection to the central communication system underneath the interface for more advanced control. Incorporation with Jupyter notebooks via connection with the active iPython kernel allows for SpecViz to be used in addition to a user’s normal workflow without demanding the user drastically alter their method of data analysis. In addition, SpecViz allows the interactive analysis of multi-object spectroscopy in the same straight-forward, consistent way. Through the development of such tools, STScI hopes to unify astronomical data analysis software for JWST and other instruments, allowing for efficient, reliable, and consistent scientific results.

Highly sensitive index of sympathetic activity based on time-frequency spectral analysis of electrodermal activity.

PubMed

Posada-Quintero, Hugo F; Florian, John P; Orjuela-Cañón, Álvaro D; Chon, Ki H

2016-09-01

Time-domain indices of electrodermal activity (EDA) have been used as a marker of sympathetic tone. However, they often show high variation between subjects and low consistency, which has precluded their general use as a marker of sympathetic tone. To examine whether power spectral density analysis of EDA can provide more consistent results, we recently performed a variety of sympathetic tone-evoking experiments (43). We found significant increase in the spectral power in the frequency range of 0.045 to 0.25 Hz when sympathetic tone-evoking stimuli were induced. The sympathetic tone assessed by the power spectral density of EDA was found to have lower variation and more sensitivity for certain, but not all, stimuli compared with the time-domain analysis of EDA. We surmise that this lack of sensitivity in certain sympathetic tone-inducing conditions with time-invariant spectral analysis of EDA may lie in its inability to characterize time-varying dynamics of the sympathetic tone. To overcome the disadvantages of time-domain and time-invariant power spectral indices of EDA, we developed a highly sensitive index of sympathetic tone, based on time-frequency analysis of EDA signals. Its efficacy was tested using experiments designed to elicit sympathetic dynamics. Twelve subjects underwent four tests known to elicit sympathetic tone arousal: cold pressor, tilt table, stand test, and the Stroop task. We hypothesize that a more sensitive measure of sympathetic control can be developed using time-varying spectral analysis. Variable frequency complex demodulation, a recently developed technique for time-frequency analysis, was used to obtain spectral amplitudes associated with EDA. We found that the time-varying spectral frequency band 0.08-0.24 Hz was most responsive to stimulation. Spectral power for frequencies higher than 0.24 Hz were determined to be not related to the sympathetic dynamics because they comprised less than 5% of the total power. The mean value of time-varying spectral amplitudes in the frequency band 0.08-0.24 Hz were used as the index of sympathetic tone, termed TVSymp. TVSymp was found to be overall the most sensitive to the stimuli, as evidenced by a low coefficient of variation (0.54), and higher consistency (intra-class correlation, 0.96) and sensitivity (Youden's index > 0.75), area under the receiver operating characteristic (ROC) curve (>0.8, accuracy > 0.88) compared with time-domain and time-invariant spectral indices, including heart rate variability. Copyright © 2016 the American Physiological Society.

Spectral Analysis of Rich Network Topology in Social Networks

ERIC Educational Resources Information Center

Wu, Leting

2013-01-01

Social networks have received much attention these days. Researchers have developed different methods to study the structure and characteristics of the network topology. Our focus is on spectral analysis of the adjacency matrix of the underlying network. Recent work showed good properties in the adjacency spectral space but there are few…

A stable pattern of EEG spectral coherence distinguishes children with autism from neuro-typical controls - a large case control study

PubMed Central

2012-01-01

Background The autism rate has recently increased to 1 in 100 children. Genetic studies demonstrate poorly understood complexity. Environmental factors apparently also play a role. Magnetic resonance imaging (MRI) studies demonstrate increased brain sizes and altered connectivity. Electroencephalogram (EEG) coherence studies confirm connectivity changes. However, genetic-, MRI- and/or EEG-based diagnostic tests are not yet available. The varied study results likely reflect methodological and population differences, small samples and, for EEG, lack of attention to group-specific artifact. Methods Of the 1,304 subjects who participated in this study, with ages ranging from 1 to 18 years old and assessed with comparable EEG studies, 463 children were diagnosed with autism spectrum disorder (ASD); 571 children were neuro-typical controls (C). After artifact management, principal components analysis (PCA) identified EEG spectral coherence factors with corresponding loading patterns. The 2- to 12-year-old subsample consisted of 430 ASD- and 554 C-group subjects (n = 984). Discriminant function analysis (DFA) determined the spectral coherence factors' discrimination success for the two groups. Loading patterns on the DFA-selected coherence factors described ASD-specific coherence differences when compared to controls. Results Total sample PCA of coherence data identified 40 factors which explained 50.8% of the total population variance. For the 2- to 12-year-olds, the 40 factors showed highly significant group differences (P < 0.0001). Ten randomly generated split half replications demonstrated high-average classification success (C, 88.5%; ASD, 86.0%). Still higher success was obtained in the more restricted age sub-samples using the jackknifing technique: 2- to 4-year-olds (C, 90.6%; ASD, 98.1%); 4- to 6-year-olds (C, 90.9%; ASD 99.1%); and 6- to 12-year-olds (C, 98.7%; ASD, 93.9%). Coherence loadings demonstrated reduced short-distance and reduced, as well as increased, long-distance coherences for the ASD-groups, when compared to the controls. Average spectral loading per factor was wide (10.1 Hz). Conclusions Classification success suggests a stable coherence loading pattern that differentiates ASD- from C-group subjects. This might constitute an EEG coherence-based phenotype of childhood autism. The predominantly reduced short-distance coherences may indicate poor local network function. The increased long-distance coherences may represent compensatory processes or reduced neural pruning. The wide average spectral range of factor loadings may suggest over-damped neural networks. PMID:22730909

Methodological problems with gamma-ray burst hardness/intensity correlations

NASA Technical Reports Server (NTRS)

Schaefer, Bradley E.

1993-01-01

The hardness and intensity are easily measured quantities for all gamma-ray bursts (GRBs), and so, many past and current studies have sought correlations between them. This Letter presents many serious methodological problems with the practical definitions for both hardness and intensity. These difficulties are such that significant correlations can be easily introduced as artifacts of the reduction procedure. In particular, cosmological models of GRBs cannot be tested with hardness/intensity correlations with current instrumentation and the time evolution of the hardness in a given burst may be correlated with intensity for reasons that are unrelated to intrinsic change in the spectral shape.

Building Loss Estimation for Earthquake Insurance Pricing

NASA Astrophysics Data System (ADS)

Durukal, E.; Erdik, M.; Sesetyan, K.; Demircioglu, M. B.; Fahjan, Y.; Siyahi, B.

2005-12-01

After the 1999 earthquakes in Turkey several changes in the insurance sector took place. A compulsory earthquake insurance scheme was introduced by the government. The reinsurance companies increased their rates. Some even supended operations in the market. And, most important, the insurance companies realized the importance of portfolio analysis in shaping their future market strategies. The paper describes an earthquake loss assessment methodology that can be used for insurance pricing and portfolio loss estimation that is based on our work esperience in the insurance market. The basic ingredients are probabilistic and deterministic regional site dependent earthquake hazard, regional building inventory (and/or portfolio), building vulnerabilities associated with typical construction systems in Turkey and estimations of building replacement costs for different damage levels. Probable maximum and average annualized losses are estimated as the result of analysis. There is a two-level earthquake insurance system in Turkey, the effect of which is incorporated in the algorithm: the national compulsory earthquake insurance scheme and the private earthquake insurance system. To buy private insurance one has to be covered by the national system, that has limited coverage. As a demonstration of the methodology we look at the case of Istanbul and use its building inventory data instead of a portfolio. A state-of-the-art time depent earthquake hazard model that portrays the increased earthquake expectancies in Istanbul is used. Intensity and spectral displacement based vulnerability relationships are incorporated in the analysis. In particular we look at the uncertainty in the loss estimations that arise from the vulnerability relationships, and at the effect of the implemented repair cost ratios.

Quantitative determination of band distortions in diamond attenuated total reflectance infrared spectra.

PubMed

Boulet-Audet, Maxime; Buffeteau, Thierry; Boudreault, Simon; Daugey, Nicolas; Pézolet, Michel

2010-06-24

Due to its unmatched hardness and chemical inertia, diamond offers many advantages over other materials for extreme conditions and routine analysis by attenuated total reflection (ATR) infrared spectroscopy. Its low refractive index can offer up to a 6-fold absorbance increase compared to germanium. Unfortunately, it also results for strong bands in spectral distortions compared to transmission experiments. The aim of this paper is to present a methodological approach to determine quantitatively the degree of the spectral distortions in ATR spectra. This approach requires the determination of the optical constants (refractive index and extinction coefficient) of the investigated sample. As a typical example, the optical constants of the fibroin protein of the silk worm Bombyx mori have been determined from the polarized ATR spectra obtained using both diamond and germanium internal reflection elements. The positions found for the amide I band by germanium and diamond ATR are respectively 6 and 17 cm(-1) lower than the true value dtermined from the k(nu) spectrum, which is calculated to be 1659 cm(-1). To determine quantitatively the effect of relevant parameters such as the film thickness and the protein concentration, various spectral simulations have also been performed. The use of a thinner film probed by light polarized in the plane of incidence and diluting the protein sample can help in obtaining ATR spectra that are closer to their transmittance counterparts. To extend this study to any system, the ATR distortion amplitude has been evaluated using spectral simulations performed for bands of various intensities and widths. From these simulations, a simple empirical relationship has been found to estimate the band shift from the experimental band height and width that could be of practical use for ATR users. This paper shows that the determination of optical constants provides an efficient way to recover the true spectrum shape and band frequencies of distorted ATR spectra.

Low Dimensional Study of a Supersonic Multi-Stream Jet Flow

NASA Astrophysics Data System (ADS)

Tenney, Andrew; Berry, Matthew; Aycock-Rizzo, Halley; Glauser, Mark; Lewalle, Jacques

2017-11-01

In this study, the near field of a two stream supersonic jet flow is examined using low dimensional tools. The flow issues from a multi-stream nozzle as described in A near-field investigation of a supersonic, multi-stream jet: locating turbulence mechanisms through velocity and density measurements by Magstadt et al., with the bulk flow Mach number, M1, being 1.6, and the second stream Mach number, M2, reaching the sonic condition. The flow field is visualized using Particle Image Velocimetry (PIV), with frames captured at a rate of 4Hz. Time-resolved pressure measurements are made just aft of the nozzle exit, as well as in the far-field, 86.6 nozzle hydraulic diameters away from the exit plane. The methodologies used in the analysis of this flow include Proper Orthogonal Decomposition (POD), and the continuous wavelet transform. The results from this ``no deck'' case are then compared to those found in the study conducted by Berry et al. From this comparison, we draw conclusions about the effects of the presence of an aft deck on the low dimensional flow description, and near field spectral content. Supported by AFOSR Grant FA9550-15-1-0435, and AFRL, through an SBIR Grant with Spectral Energies, LLC.

seismo-live: Training in Computational Seismology using Jupyter Notebooks

NASA Astrophysics Data System (ADS)

Igel, H.; Krischer, L.; van Driel, M.; Tape, C.

2016-12-01

Practical training in computational methodologies is still underrepresented in Earth science curriculae despite the increasing use of sometimes highly sophisticated simulation technologies in research projects. At the same time well-engineered community codes make it easy to return simulation-based results yet with the danger that the inherent traps of numerical solutions are not well understood. It is our belief that training with highly simplified numerical solutions (here to the equations describing elastic wave propagation) with carefully chosen elementary ingredients of simulation technologies (e.g., finite-differencing, function interpolation, spectral derivatives, numerical integration) could substantially improve this situation. For this purpose we have initiated a community platform (www.seismo-live.org) where Python-based Jupyter notebooks can be accessed and run without and necessary downloads or local software installations. The increasingly popular Jupyter notebooks allow combining markup language, graphics, equations with interactive, executable python codes. We demonstrate the potential with training notebooks for the finite-difference method, pseudospectral methods, finite/spectral element methods, the finite-volume and the discontinuous Galerkin method. The platform already includes general Python training, introduction to the ObsPy library for seismology as well as seismic data processing and noise analysis. Submission of Jupyter notebooks for general seismology are encouraged. The platform can be used for complementary teaching in Earth Science courses on compute-intensive research areas.

Multiobjective generalized extremal optimization algorithm for simulation of daylight illuminants

NASA Astrophysics Data System (ADS)

Kumar, Srividya Ravindra; Kurian, Ciji Pearl; Gomes-Borges, Marcos Eduardo

2017-10-01

Daylight illuminants are widely used as references for color quality testing and optical vision testing applications. Presently used daylight simulators make use of fluorescent bulbs that are not tunable and occupy more space inside the quality testing chambers. By designing a spectrally tunable LED light source with an optimal number of LEDs, cost, space, and energy can be saved. This paper describes an application of the generalized extremal optimization (GEO) algorithm for selection of the appropriate quantity and quality of LEDs that compose the light source. The multiobjective approach of this algorithm tries to get the best spectral simulation with minimum fitness error toward the target spectrum, correlated color temperature (CCT) the same as the target spectrum, high color rendering index (CRI), and luminous flux as required for testing applications. GEO is a global search algorithm based on phenomena of natural evolution and is especially designed to be used in complex optimization problems. Several simulations have been conducted to validate the performance of the algorithm. The methodology applied to model the LEDs, together with the theoretical basis for CCT and CRI calculation, is presented in this paper. A comparative result analysis of M-GEO evolutionary algorithm with the Levenberg-Marquardt conventional deterministic algorithm is also presented.

Multivendor Spectral-Domain Optical Coherence Tomography Dataset, Observer Annotation Performance Evaluation, and Standardized Evaluation Framework for Intraretinal Cystoid Fluid Segmentation.

PubMed

Wu, Jing; Philip, Ana-Maria; Podkowinski, Dominika; Gerendas, Bianca S; Langs, Georg; Simader, Christian; Waldstein, Sebastian M; Schmidt-Erfurth, Ursula M

2016-01-01

Development of image analysis and machine learning methods for segmentation of clinically significant pathology in retinal spectral-domain optical coherence tomography (SD-OCT), used in disease detection and prediction, is limited due to the availability of expertly annotated reference data. Retinal segmentation methods use datasets that either are not publicly available, come from only one device, or use different evaluation methodologies making them difficult to compare. Thus we present and evaluate a multiple expert annotated reference dataset for the problem of intraretinal cystoid fluid (IRF) segmentation, a key indicator in exudative macular disease. In addition, a standardized framework for segmentation accuracy evaluation, applicable to other pathological structures, is presented. Integral to this work is the dataset used which must be fit for purpose for IRF segmentation algorithm training and testing. We describe here a multivendor dataset comprised of 30 scans. Each OCT scan for system training has been annotated by multiple graders using a proprietary system. Evaluation of the intergrader annotations shows a good correlation, thus making the reproducibly annotated scans suitable for the training and validation of image processing and machine learning based segmentation methods. The dataset will be made publicly available in the form of a segmentation Grand Challenge.

Multivendor Spectral-Domain Optical Coherence Tomography Dataset, Observer Annotation Performance Evaluation, and Standardized Evaluation Framework for Intraretinal Cystoid Fluid Segmentation

PubMed Central

Wu, Jing; Philip, Ana-Maria; Podkowinski, Dominika; Gerendas, Bianca S.; Langs, Georg; Simader, Christian

2016-01-01

Development of image analysis and machine learning methods for segmentation of clinically significant pathology in retinal spectral-domain optical coherence tomography (SD-OCT), used in disease detection and prediction, is limited due to the availability of expertly annotated reference data. Retinal segmentation methods use datasets that either are not publicly available, come from only one device, or use different evaluation methodologies making them difficult to compare. Thus we present and evaluate a multiple expert annotated reference dataset for the problem of intraretinal cystoid fluid (IRF) segmentation, a key indicator in exudative macular disease. In addition, a standardized framework for segmentation accuracy evaluation, applicable to other pathological structures, is presented. Integral to this work is the dataset used which must be fit for purpose for IRF segmentation algorithm training and testing. We describe here a multivendor dataset comprised of 30 scans. Each OCT scan for system training has been annotated by multiple graders using a proprietary system. Evaluation of the intergrader annotations shows a good correlation, thus making the reproducibly annotated scans suitable for the training and validation of image processing and machine learning based segmentation methods. The dataset will be made publicly available in the form of a segmentation Grand Challenge. PMID:27579177

Determination of persimmon leaf chloride contents using near-infrared spectroscopy (NIRS).

PubMed

de Paz, José Miguel; Visconti, Fernando; Chiaravalle, Mara; Quiñones, Ana

2016-05-01

Early diagnosis of specific chloride toxicity in persimmon trees requires the reliable and fast determination of the leaf chloride content, which is usually performed by means of a cumbersome, expensive and time-consuming wet analysis. A methodology has been developed in this study as an alternative to determine chloride in persimmon leaves using near-infrared spectroscopy (NIRS) in combination with multivariate calibration techniques. Based on a training dataset of 134 samples, a predictive model was developed from their NIR spectral data. For modelling, the partial least squares regression (PLSR) method was used. The best model was obtained with the first derivative of the apparent absorbance and using just 10 latent components. In the subsequent external validation carried out with 35 external data this model reached r(2) = 0.93, RMSE = 0.16% and RPD = 3.6, with standard error of 0.026% and bias of -0.05%. From these results, the model based on NIR spectral readings can be used for speeding up the laboratory determination of chloride in persimmon leaves with only a modest loss of precision. The intermolecular interaction between chloride ions and the peptide bonds in leaf proteins through hydrogen bonding, i.e. N-H···Cl, explains the ability for chloride determinations on the basis of NIR spectra.

A practical approach to spectral calibration of short wavelength infrared hyper-spectral imaging systems

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.

Power Spectral Density Error Analysis of Spectral Subtraction Type of Speech Enhancement Methods

NASA Astrophysics Data System (ADS)

Händel, Peter

2006-12-01

A theoretical framework for analysis of speech enhancement algorithms is introduced for performance assessment of spectral subtraction type of methods. The quality of the enhanced speech is related to physical quantities of the speech and noise (such as stationarity time and spectral flatness), as well as to design variables of the noise suppressor. The derived theoretical results are compared with the outcome of subjective listening tests as well as successful design strategies, performed by independent research groups.

[Analysis of software for identifying spectral line of laser-induced breakdown spectroscopy based on LabVIEW].

PubMed

Hu, Zhi-yu; Zhang, Lei; Ma, Wei-guang; Yan, Xiao-juan; Li, Zhi-xin; Zhang, Yong-zhi; Wang, Le; Dong, Lei; Yin, Wang-bao; Jia, Suo-tang

2012-03-01

Self-designed identifying software for LIBS spectral line was introduced. Being integrated with LabVIEW, the soft ware can smooth spectral lines and pick peaks. The second difference and threshold methods were employed. Characteristic spectrum of several elements matches the NIST database, and realizes automatic spectral line identification and qualitative analysis of the basic composition of sample. This software can analyze spectrum handily and rapidly. It will be a useful tool for LIBS.

Cardiovascular response to acute stress in freely moving rats: time-frequency analysis.

PubMed

Loncar-Turukalo, Tatjana; Bajic, Dragana; Japundzic-Zigon, Nina

2008-01-01

Spectral analysis of cardiovascular series is an important tool for assessing the features of the autonomic control of the cardiovascular system. In this experiment Wistar rats ecquiped with intraarterial catheter for blood pressure (BP) recording were exposed to stress induced by blowing air. The problem of non stationary data was overcomed applying the Smoothed Pseudo Wigner Villle (SPWV) time-frequency distribution. Spectral analysis was done before stress, during stress, immediately after stress and later in recovery. The spectral indices were calculated for both systolic blood pressure (SBP) and pulse interval (PI) series. The time evolution of spectral indices showed perturbed sympathovagal balance.

Spectral BRDF-based determination of proper measurement geometries to characterize color shift of special effect coatings.

PubMed

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.

Methods for spectral image analysis by exploiting spatial simplicity

DOEpatents

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

DOEpatents

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.

Spectral Electroencephalogram Analysis for the Evaluation of Encephalopathy Grade in Children With Acute Liver Failure.

PubMed

Press, Craig A; Morgan, Lindsey; Mills, Michele; Stack, Cynthia V; Goldstein, Joshua L; Alonso, Estella M; Wainwright, Mark S

2017-01-01

Spectral electroencephalogram analysis is a method for automated analysis of electroencephalogram patterns, which can be performed at the bedside. We sought to determine the utility of spectral electroencephalogram for grading hepatic encephalopathy in children with acute liver failure. Retrospective cohort study. Tertiary care pediatric hospital. Patients between 0 and 18 years old who presented with acute liver failure and were admitted to the PICU. None. Electroencephalograms were analyzed by spectral analysis including total power, relative δ, relative θ, relative α, relative β, θ-to-Δ ratio, and α-to-Δ ratio. Normal values and ranges were first derived using normal electroencephalograms from 70 children of 0-18 years old. Age had a significant effect on each variable measured (p < 0.03). Electroencephalograms from 33 patients with acute liver failure were available for spectral analysis. The median age was 4.3 years, 14 of 33 were male, and the majority had an indeterminate etiology of acute liver failure. Neuroimaging was performed in 26 cases and was normal in 20 cases (77%). The majority (64%) survived, and 82% had a good outcome with a score of 1-3 on the Pediatric Glasgow Outcome Scale-Extended at the time of discharge. Hepatic encephalopathy grade correlated with the qualitative visual electroencephalogram scores assigned by blinded neurophysiologists (rs = 0.493; p < 0.006). Spectral electroencephalogram characteristics varied significantly with the qualitative electroencephalogram classification (p < 0.05). Spectral electroencephalogram variables including relative Δ, relative θ, relative α, θ-to-Δ ratio, and α-to-Δ ratio all significantly varied with the qualitative electroencephalogram (p < 0.025). Moderate to severe hepatic encephalopathy was correlated with a total power of less than or equal to 50% of normal for children 0-3 years old, and with a relative θ of less than or equal to 50% normal for children more than 3 years old (p > 0.05). Spectral electroencephalogram classification correlated with outcome (p < 0.05). Spectral electroencephalogram analysis can be used to evaluate even young patients for hepatic encephalopathy and correlates with outcome. Spectral electroencephalogram may allow improved quantitative and reproducible assessment of hepatic encephalopathy grade in children with acute liver failure.

Seismic hazard assessment of the Province of Murcia (SE Spain): analysis of source contribution to hazard

NASA Astrophysics Data System (ADS)

García-Mayordomo, J.; Gaspar-Escribano, J. M.; Benito, B.

2007-10-01

A probabilistic seismic hazard assessment of the Province of Murcia in terms of peak ground acceleration (PGA) and spectral accelerations [SA( T)] is presented in this paper. In contrast to most of the previous studies in the region, which were performed for PGA making use of intensity-to-PGA relationships, hazard is here calculated in terms of magnitude and using European spectral ground-motion models. Moreover, we have considered the most important faults in the region as specific seismic sources, and also comprehensively reviewed the earthquake catalogue. Hazard calculations are performed following the Probabilistic Seismic Hazard Assessment (PSHA) methodology using a logic tree, which accounts for three different seismic source zonings and three different ground-motion models. Hazard maps in terms of PGA and SA(0.1, 0.2, 0.5, 1.0 and 2.0 s) and coefficient of variation (COV) for the 475-year return period are shown. Subsequent analysis is focused on three sites of the province, namely, the cities of Murcia, Lorca and Cartagena, which are important industrial and tourism centres. Results at these sites have been analysed to evaluate the influence of the different input options. The most important factor affecting the results is the choice of the attenuation relationship, whereas the influence of the selected seismic source zonings appears strongly site dependant. Finally, we have performed an analysis of source contribution to hazard at each of these cities to provide preliminary guidance in devising specific risk scenarios. We have found that local source zones control the hazard for PGA and SA( T ≤ 1.0 s), although contribution from specific fault sources and long-distance north Algerian sources becomes significant from SA(0.5 s) onwards.

Better Spectrometers, Beautiful Spectra and Confusion for All

NASA Technical Reports Server (NTRS)

Pearson, J. C.; Brauer, C. S.; Drouin, B. J.; Yu, S.

2009-01-01

The confluence of enormous improvements in submillimeter receivers and the development of powerful large scale observatories is about to force astrophysics and the sciences that support it to develop novel approaches for interpretation of data. The historical method of observing one or two lines and carefully analyzing them in the context of a simple model is now only applicable for distant objects where only a few lines are strong enough to be observable. Modern observatories collect many GHz of high signal-to-noise spectra in a single observation and in many cases, at sufficiently high spatial resolution to start resolving chemically distinct regions. The observatories planned for the near future and the inevitable upgrades of existing facilities will make large spectral data sets the rule rather than the exception in many areas of molecular astrophysics. The methodology and organization required to fully extract the available information and interpret these beautiful spectra represents a challenge to submillimeter astrophysics similar in magnitude to the last few decades of effort in improving receivers. The quality and abundance of spectra effectively prevents line-by-line analysis from being a time efficient proposition, however, global analysis of complex spectra is a science in its infancy. Spectroscopy at several other wavelengths have developed a number of techniques to analyze complex spectra, which can provide a great deal of guidance to the molecular astrophysics community on how to attack the complex spectrum problem. Ultimately, the challenge is one of organization, similar to building observatories, requiring teams of specialists combining their knowledge of dynamical, structural, chemical and radiative models with detailed knowledge in molecular physics and gas and grain surface chemistry to extract and exploit the enormous information content of complex spectra. This paper presents a spectroscopists view of the necessary elements in a tool for complex spectral analysis.

HEAO-1 analysis of Low Energy Detectors (LED)

NASA Technical Reports Server (NTRS)

Nousek, John A.

1992-01-01

The activities at Penn State University are described. During the period Oct. 1990 to Dec. 1991 work on HEAO-1 analysis of the Low Energy Detectors (LED) concentrated on using the improved detector spectral simulation model and fitting diffuse x-ray background spectral data. Spectral fitting results, x-ray point sources, and diffuse x-ray sources are described.

Single-hole spectral function and spin-charge separation in the t-J model

NASA Astrophysics Data System (ADS)

Mishchenko, A. S.; Prokof'ev, N. V.; Svistunov, B. V.

2001-07-01

Worm algorithm Monte Carlo simulations of the hole Green function with subsequent spectral analysis were performed for 0.1<=J/t<=0.4 on lattices with up to L×L=32×32 sites at a temperature as low as T=J/40, and present, apparently, the hole spectral function in the thermodynamic limit. Spectral analysis reveals a δ-function-sharp quasiparticle peak at the lower edge of the spectrum that is incompatible with the power-law singularity and thus rules out the possibility of spin-charge separation in this parameter range. Spectral continuum features two peaks separated by a gap ~4÷5 t.

Compact full-motion video hyperspectral cameras: development, image processing, and applications

NASA Astrophysics Data System (ADS)

Kanaev, A. V.

2015-10-01

Emergence of spectral pixel-level color filters has enabled development of hyper-spectral Full Motion Video (FMV) sensors operating in visible (EO) and infrared (IR) wavelengths. The new class of hyper-spectral cameras opens broad possibilities of its utilization for military and industry purposes. Indeed, such cameras are able to classify materials as well as detect and track spectral signatures continuously in real time while simultaneously providing an operator the benefit of enhanced-discrimination-color video. Supporting these extensive capabilities requires significant computational processing of the collected spectral data. In general, two processing streams are envisioned for mosaic array cameras. The first is spectral computation that provides essential spectral content analysis e.g. detection or classification. The second is presentation of the video to an operator that can offer the best display of the content depending on the performed task e.g. providing spatial resolution enhancement or color coding of the spectral analysis. These processing streams can be executed in parallel or they can utilize each other's results. The spectral analysis algorithms have been developed extensively, however demosaicking of more than three equally-sampled spectral bands has been explored scarcely. We present unique approach to demosaicking based on multi-band super-resolution and show the trade-off between spatial resolution and spectral content. Using imagery collected with developed 9-band SWIR camera we demonstrate several of its concepts of operation including detection and tracking. We also compare the demosaicking results to the results of multi-frame super-resolution as well as to the combined multi-frame and multiband processing.

Spectral identification of melon seeds variety based on k-nearest neighbor and Fisher discriminant analysis

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.

Examination of Spectral Transformations on Spectral Mixture Analysis

NASA Astrophysics Data System (ADS)

Deng, Y.; Wu, C.

2018-04-01

While many spectral transformation techniques have been applied on spectral mixture analysis (SMA), few study examined their necessity and applicability. This paper focused on exploring the difference between spectrally transformed schemes and untransformed scheme to find out which transformed scheme performed better in SMA. In particular, nine spectrally transformed schemes as well as untransformed scheme were examined in two study areas. Each transformed scheme was tested 100 times using different endmember classes' spectra under the endmember model of vegetation- high albedo impervious surface area-low albedo impervious surface area-soil (V-ISAh-ISAl-S). Performance of each scheme was assessed based on mean absolute error (MAE). Statistical analysis technique, Paired-Samples T test, was applied to test the significance of mean MAEs' difference between transformed and untransformed schemes. Results demonstrated that only NSMA could exceed the untransformed scheme in all study areas. Some transformed schemes showed unstable performance since they outperformed the untransformed scheme in one area but weakened the SMA result in another region.

Quantitative Doppler Analysis Using Conventional Color Flow Imaging Acquisitions.

PubMed

Karabiyik, Yucel; Ekroll, Ingvild Kinn; Eik-Nes, Sturla H; Lovstakken, Lasse

2018-05-01

Interleaved acquisitions used in conventional triplex mode result in a tradeoff between the frame rate and the quality of velocity estimates. On the other hand, workflow becomes inefficient when the user has to switch between different modes, and measurement variability is increased. This paper investigates the use of power spectral Capon estimator in quantitative Doppler analysis using data acquired with conventional color flow imaging (CFI) schemes. To preserve the number of samples used for velocity estimation, only spatial averaging was utilized, and clutter rejection was performed after spectral estimation. The resulting velocity spectra were evaluated in terms of spectral width using a recently proposed spectral envelope estimator. The spectral envelopes were also used for Doppler index calculations using in vivo and string phantom acquisitions. In vivo results demonstrated that the Capon estimator can provide spectral estimates with sufficient quality for quantitative analysis using packet-based CFI acquisitions. The calculated Doppler indices were similar to the values calculated using spectrograms estimated on a commercial ultrasound scanner.

Sleep Neurophysiological Dynamics Through the Lens of Multitaper Spectral Analysis

PubMed Central

Prerau, Michael J.; Brown, Ritchie E.; Bianchi, Matt T.; Ellenbogen, Jeffrey M.; Purdon, Patrick L.

2016-01-01

During sleep, cortical and subcortical structures within the brain engage in highly structured oscillatory dynamics that can be observed in the electroencephalogram (EEG). The ability to accurately describe changes in sleep state from these oscillations has thus been a major goal of sleep medicine. While numerous studies over the past 50 years have shown sleep to be a continuous, multifocal, dynamic process, long-standing clinical practice categorizes sleep EEG into discrete stages through visual inspection of 30-s epochs. By representing sleep as a coarsely discretized progression of stages, vital neurophysiological information on the dynamic interplay between sleep and arousal is lost. However, by using principled time-frequency spectral analysis methods, the rich dynamics of the sleep EEG are immediately visible—elegantly depicted and quantified at time scales ranging from a full night down to individual microevents. In this paper, we review the neurophysiology of sleep through this lens of dynamic spectral analysis. We begin by reviewing spectral estimation techniques traditionally used in sleep EEG analysis and introduce multitaper spectral analysis, a method that makes EEG spectral estimates clearer and more accurate than traditional approaches. Through the lens of the multitaper spectrogram, we review the oscillations and mechanisms underlying the traditional sleep stages. In doing so, we will demonstrate how multitaper spectral analysis makes the oscillatory structure of traditional sleep states instantaneously visible, closely paralleling the traditional hypnogram, but with a richness of information that suggests novel insights into the neural mechanisms of sleep, as well as novel clinical and research applications. PMID:27927806

Structure-level fuel load assessment in the wildland-urban interface: a fusion of airborne laser scanning and spectral remote-sensing methodologies

Treesearch

Nicholas S. Skowronski; Scott Haag; Jim Trimble; Kenneth L. Clark; Michael R. Gallagher; Richard G. Lathrop

2015-01-01

Large-scale fuel assessments are useful for developing policy aimed at mitigating wildfires in the wildland-urban interface (WUI), while finer-scale characterisation is necessary for maximising the effectiveness of fuel reduction treatments and directing suppression activities. We developed and tested an objective, consistent approach for characterising hazardous fuels...

Spatial, spectral and temporal patterns of tropical forest cover change as observed with multiple scales of optical satellite data.

Treesearch

D.J. Hayes; W.B. Cohen

2006-01-01

This article describes the development of a methodology for scaling observations of changes in tropical forest cover to large areas at high temporal frequency from coarse-resolution satellite imagery. The approach for estimating proportional forest cover change as a continuous variable is based on a regression model that relates multispectral, multitemporal Moderate...

An automated real-time microscopy system for analysis of fluorescence resonance energy transfer

NASA Astrophysics Data System (ADS)

Bernardini, André; Wotzlaw, Christoph; Lipinski, Hans-Gerd; Fandrey, Joachim

2010-05-01

Molecular imaging based on Fluorescence Resonance Energy Transfer (FRET) is widely used in cellular physiology both for protein-protein interaction analysis and detecting conformational changes of single proteins, e.g. during activation of signaling cascades. However, getting reliable results from FRET measurements is still hampered by methodological problems such as spectral bleed through, chromatic aberration, focal plane shifts and false positive FRET. Particularly false positive FRET signals caused by random interaction of the fluorescent dyes can easily lead to misinterpretation of the data. This work introduces a Nipkow Disc based FRET microscopy system, that is easy to operate without expert knowledge of FRET. The system automatically accounts for all relevant sources of errors and provides various result presentations of two, three and four dimensional FRET data. Two examples are given to demonstrate the scope of application. An interaction analysis of the two subunits of the hypoxia-inducible transcription factor 1 demonstrates the use of the system as a tool for protein-protein interaction analysis. As an example for time lapse observations, the conformational change of the fluorophore labeled heat shock protein 33 in the presence of oxidant stress is shown.

Vibrations Detection in Industrial Pumps Based on Spectral Analysis to Increase Their Efficiency

NASA Astrophysics Data System (ADS)

Rachid, Belhadef; Hafaifa, Ahmed; Boumehraz, Mohamed

2016-03-01

Spectral analysis is the key tool for the study of vibration signals in rotating machinery. In this work, the vibration analysis applied for conditional preventive maintenance of such machines is proposed, as part of resolved problems related to vibration detection on the organs of these machines. The vibration signal of a centrifugal pump was treated to mount the benefits of the approach proposed. The obtained results present the signal estimation of a pump vibration using Fourier transform technique compared by the spectral analysis methods based on Prony approach.

Acoustic emission spectral analysis of fiber composite failure mechanisms

NASA Technical Reports Server (NTRS)

Egan, D. M.; Williams, J. H., Jr.

1978-01-01

The acoustic emission of graphite fiber polyimide composite failure mechanisms was investigated with emphasis on frequency spectrum analysis. Although visual examination of spectral densities could not distinguish among fracture sources, a paired-sample t statistical analysis of mean normalized spectral densities did provide quantitative discrimination among acoustic emissions from 10 deg, 90 deg, and plus or minus 45 deg, plus or minus 45 deg sub s specimens. Comparable discrimination was not obtained for 0 deg specimens.

Spectral and correlation analysis with applications to middle-atmosphere radars

NASA Technical Reports Server (NTRS)

Rastogi, Prabhat K.

1989-01-01

The correlation and spectral analysis methods for uniformly sampled stationary random signals, estimation of their spectral moments, and problems arising due to nonstationary are reviewed. Some of these methods are already in routine use in atmospheric radar experiments. Other methods based on the maximum entropy principle and time series models have been used in analyzing data, but are just beginning to receive attention in the analysis of radar signals. These methods are also briefly discussed.

Spectral signature verification using statistical analysis and text mining

NASA Astrophysics Data System (ADS)

DeCoster, Mallory E.; Firpi, Alexe H.; Jacobs, Samantha K.; Cone, Shelli R.; Tzeng, Nigel H.; Rodriguez, Benjamin M.

2016-05-01

In the spectral science community, numerous spectral signatures are stored in databases representative of many sample materials collected from a variety of spectrometers and spectroscopists. Due to the variety and variability of the spectra that comprise many spectral databases, it is necessary to establish a metric for validating the quality of spectral signatures. This has been an area of great discussion and debate in the spectral science community. This paper discusses a method that independently validates two different aspects of a spectral signature to arrive at a final qualitative assessment; the textual meta-data and numerical spectral data. Results associated with the spectral data stored in the Signature Database1 (SigDB) are proposed. The numerical data comprising a sample material's spectrum is validated based on statistical properties derived from an ideal population set. The quality of the test spectrum is ranked based on a spectral angle mapper (SAM) comparison to the mean spectrum derived from the population set. Additionally, the contextual data of a test spectrum is qualitatively analyzed using lexical analysis text mining. This technique analyzes to understand the syntax of the meta-data to provide local learning patterns and trends within the spectral data, indicative of the test spectrum's quality. Text mining applications have successfully been implemented for security2 (text encryption/decryption), biomedical3 , and marketing4 applications. The text mining lexical analysis algorithm is trained on the meta-data patterns of a subset of high and low quality spectra, in order to have a model to apply to the entire SigDB data set. The statistical and textual methods combine to assess the quality of a test spectrum existing in a database without the need of an expert user. This method has been compared to other validation methods accepted by the spectral science community, and has provided promising results when a baseline spectral signature is present for comparison. The spectral validation method proposed is described from a practical application and analytical perspective.

Statistical Analysis of Spectral Properties and Prosodic Parameters of Emotional Speech

NASA Astrophysics Data System (ADS)

Přibil, J.; Přibilová, A.

2009-01-01

The paper addresses reflection of microintonation and spectral properties in male and female acted emotional speech. Microintonation component of speech melody is analyzed regarding its spectral and statistical parameters. According to psychological research of emotional speech, different emotions are accompanied by different spectral noise. We control its amount by spectral flatness according to which the high frequency noise is mixed in voiced frames during cepstral speech synthesis. Our experiments are aimed at statistical analysis of cepstral coefficient values and ranges of spectral flatness in three emotions (joy, sadness, anger), and a neutral state for comparison. Calculated histograms of spectral flatness distribution are visually compared and modelled by Gamma probability distribution. Histograms of cepstral coefficient distribution are evaluated and compared using skewness and kurtosis. Achieved statistical results show good correlation comparing male and female voices for all emotional states portrayed by several Czech and Slovak professional actors.

Random Initialisation of the Spectral Variables: an Alternate Approach for Initiating Multivariate Curve Resolution Alternating Least Square (MCR-ALS) Analysis.

PubMed

Kumar, Keshav

2017-11-01

Multivariate curve resolution alternating least square (MCR-ALS) analysis is the most commonly used curve resolution technique. The MCR-ALS model is fitted using the alternate least square (ALS) algorithm that needs initialisation of either contribution profiles or spectral profiles of each of the factor. The contribution profiles can be initialised using the evolve factor analysis; however, in principle, this approach requires that data must belong to the sequential process. The initialisation of the spectral profiles are usually carried out using the pure variable approach such as SIMPLISMA algorithm, this approach demands that each factor must have the pure variables in the data sets. Despite these limitations, the existing approaches have been quite a successful for initiating the MCR-ALS analysis. However, the present work proposes an alternate approach for the initialisation of the spectral variables by generating the random variables in the limits spanned by the maxima and minima of each spectral variable of the data set. The proposed approach does not require that there must be pure variables for each component of the multicomponent system or the concentration direction must follow the sequential process. The proposed approach is successfully validated using the excitation-emission matrix fluorescence data sets acquired for certain fluorophores with significant spectral overlap. The calculated contribution and spectral profiles of these fluorophores are found to correlate well with the experimental results. In summary, the present work proposes an alternate way to initiate the MCR-ALS analysis.

Speleothem stable isotope records for east-central Europe: resampling sedimentary proxy records to obtain evenly spaced time series with spectral guidance

NASA Astrophysics Data System (ADS)

Gábor Hatvani, István; Kern, Zoltán; Leél-Őssy, Szabolcs; Demény, Attila

2018-01-01

Uneven spacing is a common feature of sedimentary paleoclimate records, in many cases causing difficulties in the application of classical statistical and time series methods. Although special statistical tools do exist to assess unevenly spaced data directly, the transformation of such data into a temporally equidistant time series which may then be examined using commonly employed statistical tools remains, however, an unachieved goal. The present paper, therefore, introduces an approach to obtain evenly spaced time series (using cubic spline fitting) from unevenly spaced speleothem records with the application of a spectral guidance to avoid the spectral bias caused by interpolation and retain the original spectral characteristics of the data. The methodology was applied to stable carbon and oxygen isotope records derived from two stalagmites from the Baradla Cave (NE Hungary) dating back to the late 18th century. To show the benefit of the equally spaced records to climate studies, their coherence with climate parameters is explored using wavelet transform coherence and discussed. The obtained equally spaced time series are available at https://doi.org/10.1594/PANGAEA.875917.

Robust Spectral Unmixing of Sparse Multispectral Lidar Waveforms using Gamma Markov Random Fields

DOE PAGES

Altmann, Yoann; Maccarone, Aurora; McCarthy, Aongus; ...

2017-05-10

Here, this paper presents a new Bayesian spectral un-mixing algorithm to analyse remote scenes sensed via sparse multispectral Lidar measurements. To a first approximation, in the presence of a target, each Lidar waveform consists of a main peak, whose position depends on the target distance and whose amplitude depends on the wavelength of the laser source considered (i.e, on the target reflectivity). Besides, these temporal responses are usually assumed to be corrupted by Poisson noise in the low photon count regime. When considering multiple wavelengths, it becomes possible to use spectral information in order to identify and quantify the mainmore » materials in the scene, in addition to estimation of the Lidar-based range profiles. Due to its anomaly detection capability, the proposed hierarchical Bayesian model, coupled with an efficient Markov chain Monte Carlo algorithm, allows robust estimation of depth images together with abundance and outlier maps associated with the observed 3D scene. The proposed methodology is illustrated via experiments conducted with real multispectral Lidar data acquired in a controlled environment. The results demonstrate the possibility to unmix spectral responses constructed from extremely sparse photon counts (less than 10 photons per pixel and band).« less

Climate Change Detection and Attribution of Infrared Spectrum Measurements

NASA Technical Reports Server (NTRS)

Phojanamongkolkij, Nipa; Parker, Peter A.; Mlynczak, Martin G.

2012-01-01

Climate change occurs when the Earth's energy budget changes due to natural or possibly anthropogenic forcings. These forcings cause the climate system to adjust resulting in a new climate state that is warmer or cooler than the original. The key question is how to detect and attribute climate change. The inference of infrared spectral signatures of climate change has been discussed in the literature for nearly 30 years. Pioneering work in the 1980s noted that distinct spectral signatures would be evident in changes in the infrared radiance emitted by the Earth and its atmosphere, and that these could be observed from orbiting satellites. Since then, a number of other studies have advanced the concepts of spectral signatures of climate change. Today the concept of using spectral signatures to identify and attribute atmospheric composition change is firmly accepted and is the foundation of the Climate Absolute Radiance and Refractivity Observatory (CLARREO) satellite mission being developed at NASA. In this work, we will present an overview of the current climate change detection concept using climate model calculations as surrogates for climate change. Any future research work improving the methodology to achieve this concept will be valuable to our society.

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

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

Chemiluminescence-based multivariate sensing of local equivalence ratios in premixed atmospheric methane-air flames

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

Tripathi, Markandey M.; Krishnan, Sundar R.; Srinivasan, Kalyan K.

Chemiluminescence emissions from OH*, CH*, C2, and CO2 formed within the reaction zone of premixed flames depend upon the fuel-air equivalence ratio in the burning mixture. In the present paper, a new partial least square regression (PLS-R) based multivariate sensing methodology is investigated and compared with an OH*/CH* intensity ratio-based calibration model for sensing equivalence ratio in atmospheric methane-air premixed flames. Five replications of spectral data at nine different equivalence ratios ranging from 0.73 to 1.48 were used in the calibration of both models. During model development, the PLS-R model was initially validated with the calibration data set using themore » leave-one-out cross validation technique. Since the PLS-R model used the entire raw spectral intensities, it did not need the nonlinear background subtraction of CO2 emission that is required for typical OH*/CH* intensity ratio calibrations. An unbiased spectral data set (not used in the PLS-R model development), for 28 different equivalence ratio conditions ranging from 0.71 to 1.67, was used to predict equivalence ratios using the PLS-R and the intensity ratio calibration models. It was found that the equivalence ratios predicted with the PLS-R based multivariate calibration model matched the experimentally measured equivalence ratios within 7%; whereas, the OH*/CH* intensity ratio calibration grossly underpredicted equivalence ratios in comparison to measured equivalence ratios, especially under rich conditions ( > 1.2). The practical implications of the chemiluminescence-based multivariate equivalence ratio sensing methodology are also discussed.« less

Remote sensing technologies applied to the irrigation water management on a golf course

NASA Astrophysics Data System (ADS)

Pedras, Celestina; Lança, Rui; Martins, Fernando; Soares, Cristina; Guerrero, Carlos; Paixão, Helena

2015-04-01

An adequate irrigation water management in a golf course is a complex task that depends upon climate (multiple microclimates) and land cover (where crops differ in morphology, physiology, plant density, sensitivity to water stress, etc.). These factors change both in time and space on a landscape. A direct measurement provides localized values of the evapotranspiration and climate conditions. Therefore this is not a practical or economical methodology for large-scale use due to spatial and temporal variability of vegetation, soils, and irrigation management strategies. Remote sensing technology combines large scale with ground measurement of vegetation indexes. These indexes are mathematical combinations of different spectral bands mostly in the visible and near infrared regions of the electromagnetic spectrum. They represent the measures of vegetation activity that vary not only with the seasonal variability of green foliage, but also across space, thus they are suitable for detecting spatial landscape variability. The spectral vegetation indexes may enhance irrigation management through the information contained in spectral reflectance data. This study was carried out on the 18th fairway of the Royal Golf Course, Vale do Lobo, Portugal, and it aims to establish the relationship between direct measurements and vegetation indexes. For that it is required (1) to characterize the soil and climatic conditions, (2) to assessment of the irrigation system, (3) to estimate the evapotranspiration (4) and to calculate the vegetation indices. The vegetation indices were determined with basis on spectral bands red, green and blue, RGB, and near Infrared, NIR, obtained from the analysis of images acquired from a unpiloted aerial vehicle, UAV, platform. The measurements of reference evapotranspiration (ETo) were obtained from two meteorological stations located in the study area. The landscape evapotranspiration, ETL, was determined in the fairway with multiple microclimates and managed stress. The ETL was obtained thru the use of mobile reference ET stations and also by the development of the surface renewal (SR) measurement technique. The sprinkler irrigation system installed was evaluated according to the methodology described by ASAE. The Normalized Difference Vegetation Index, NDVI, and Visible atmospherically Resistant Index, VARI, are confronted with the direct localized measurements. The NDVI is the most used indicator to assess the vigor status of the vegetation. However, this index depends of the use of NIR bands which demands quite expensive sensors. The use vegetation indexes obtained by sensors that collect data in the visible wavelength, such as VARI is less expensive and allow the vegetative vigor evaluation with a similar rigor. The information of vegetation indices is crossed with edafoclimatic data obtained in situ, in order to improve the irrigation water management based on aerial imagery.

Kinetics of T-cell receptor-dependent antigen recognition determined in vivo by multi-spectral normalized epifluorescence laser scanning

NASA Astrophysics Data System (ADS)

Favicchio, Rosy; Zacharakis, Giannis; Oikonomaki, Katerina; Zacharopoulos, Athanasios; Mamalaki, Clio; Ripoll, Jorge

2012-07-01

Detection of multiple fluorophores in conditions of low signal represents a limiting factor for the application of in vivo optical imaging techniques in immunology where fluorescent labels report for different functional characteristics. A noninvasive in vivo Multi-Spectral Normalized Epifluorescence Laser scanning (M-SNELS) method was developed for the simultaneous and quantitative detection of multiple fluorophores in low signal to noise ratios and used to follow T-cell activation and clonal expansion. Colocalized DsRed- and GFP-labeled T cells were followed in tandem during the mounting of an immune response. Spectral unmixing was used to distinguish the overlapping fluorescent emissions representative of the two distinct cell populations and longitudinal data reported the discrete pattern of antigen-driven proliferation. Retrieved values were validated both in vitro and in vivo with flow cytometry and significant correlation between all methodologies was achieved. Noninvasive M-SNELS successfully quantified two colocalized fluorescent populations and provides a valid alternative imaging approach to traditional invasive methods for detecting T cell dynamics.

Ultra compact spectrometer using linear variable filters

NASA Astrophysics Data System (ADS)

Dami, M.; De Vidi, R.; Aroldi, G.; Belli, F.; Chicarella, L.; Piegari, A.; Sytchkova, A.; Bulir, J.; Lemarquis, F.; Lequime, M.; Abel Tibérini, L.; Harnisch, B.

2017-11-01

The Linearly Variable Filters (LVF) are complex optical devices that, integrated in a CCD, can realize a "single chip spectrometer". In the framework of an ESA Study, a team of industries and institutes led by SELEX-Galileo explored the design principles and manufacturing techniques, realizing and characterizing LVF samples based both on All-Dielectric (AD) and Metal-Dielectric (MD) Coating Structures in the VNIR and SWIR spectral ranges. In particular the achieved performances on spectral gradient, transmission bandwidth and Spectral Attenuation (SA) are presented and critically discussed. Potential improvements will be highlighted. In addition the results of a feasibility study of a SWIR Linear Variable Filter are presented with the comparison of design prediction and measured performances. Finally criticalities related to the filter-CCD packaging are discussed. The main achievements reached during these activities have been: - to evaluate by design, manufacturing and test of LVF samples the achievable performances compared with target requirements; - to evaluate the reliability of the projects by analyzing their repeatability; - to define suitable measurement methodologies

Atmospheric correction for JPSS-2 VIIRS response versus scan angle measurements

NASA Astrophysics Data System (ADS)

McIntire, Jeffrey; Moeller, Chris; Oudrari, Hassan; Xiong, Xiaoxiong

2017-09-01

The Joint Polar Satellite System 2 (JPSS-2) Visible Infrared Imaging Radiometer Suite (VIIRS) includes one spectral band centered in a strong atmospheric absorption region. As much of the pre-launch calibration is performed under laboratory ambient conditions, accurately accounting for the absorption, and thereby ensuring the transfer of the sensor calibration to on-orbit operations, is necessary to generate science quality data products. This work is focused on the response versus scan angle (RVS) measurements, which characterize the relative scan angle dependent reflectance of the JPSS-2 VIIRS instrument optics. The spectral band of interest, centered around 1378 nm, is within a spectral region strongly effected by water vapor absorption. The methodology used to model the absolute humidity and the atmospheric transmittance under the laboratory conditions is detailed. The application of this transmittance to the RVS determination is then described including an uncertainty estimate; a comparison to the pre-launch measurements from earlier sensor builds is also performed.

Fast Fourier Transform Spectral Analysis Program

NASA Technical Reports Server (NTRS)

Daniel, J. A., Jr.; Graves, M. L.; Hovey, N. M.

1969-01-01

Fast Fourier Transform Spectral Analysis Program is used in frequency spectrum analysis of postflight, space vehicle telemetered trajectory data. This computer program with a digital algorithm can calculate power spectrum rms amplitudes and cross spectrum of sampled parameters at even time increments.

Interactive Spectral Analysis and Computation (ISAAC)

NASA Technical Reports Server (NTRS)

Lytle, D. M.

1992-01-01

Isaac is a task in the NSO external package for IRAF. A descendant of a FORTRAN program written to analyze data from a Fourier transform spectrometer, the current implementation has been generalized sufficiently to make it useful for general spectral analysis and other one dimensional data analysis tasks. The user interface for Isaac is implemented as an interpreted mini-language containing a powerful, programmable vector calculator. Built-in commands provide much of the functionality needed to produce accurate line lists from input spectra. These built-in functions include automated spectral line finding, least squares fitting of Voigt profiles to spectral lines including equality constraints, various filters including an optimal filter construction tool, continuum fitting, and various I/O functions.

Program Package for the Analysis of High Resolution High Signal-To-Noise Stellar Spectra

NASA Astrophysics Data System (ADS)

Piskunov, N.; Ryabchikova, T.; Pakhomov, Yu.; Sitnova, T.; Alekseeva, S.; Mashonkina, L.; Nordlander, T.

2017-06-01

The program package SME (Spectroscopy Made Easy), designed to perform an analysis of stellar spectra using spectral fitting techniques, was updated due to adding new functions (isotopic and hyperfine splittins) in VALD and including grids of NLTE calculations for energy levels of few chemical elements. SME allows to derive automatically stellar atmospheric parameters: effective temperature, surface gravity, chemical abundances, radial and rotational velocities, turbulent velocities, taking into account all the effects defining spectral line formation. SME package uses the best grids of stellar atmospheres that allows us to perform spectral analysis with the similar accuracy in wide range of stellar parameters and metallicities - from dwarfs to giants of BAFGK spectral classes.

Signature extraction of ocean pollutants by eigenvector transformation of remote spectra

NASA Technical Reports Server (NTRS)

Grew, G. W.

1978-01-01

Spectral signatures of suspended matter in the ocean are being extracted through characteristic vector analysis of remote ocean color data collected with MOCS (Multichannel Ocean Color Sensor). Spectral signatures appear to be obtainable through analyses of 'linear' clusters that appear on scatter diagrams associated with eigenvectors. Signatures associated with acid waste, sewage sludge, oil, and algae are presented. The application of vector analysis to two acid waste dumps overflown two years apart is examined in some detail. The relationships between eigenvectors and spectral signatures for these examples are analyzed. These cases demonstrate the value of characteristic vector analysis in remotely identifying pollutants in the ocean and in determining the consistency of their spectral signatures.

Updating National Topographic Data Base Using Change Detection Methods

NASA Astrophysics Data System (ADS)

Keinan, E.; Felus, Y. A.; Tal, Y.; Zilberstien, O.; Elihai, Y.

2016-06-01

The traditional method for updating a topographic database on a national scale is a complex process that requires human resources, time and the development of specialized procedures. In many National Mapping and Cadaster Agencies (NMCA), the updating cycle takes a few years. Today, the reality is dynamic and the changes occur every day, therefore, the users expect that the existing database will portray the current reality. Global mapping projects which are based on community volunteers, such as OSM, update their database every day based on crowdsourcing. In order to fulfil user's requirements for rapid updating, a new methodology that maps major interest areas while preserving associated decoding information, should be developed. Until recently, automated processes did not yield satisfactory results, and a typically process included comparing images from different periods. The success rates in identifying the objects were low, and most were accompanied by a high percentage of false alarms. As a result, the automatic process required significant editorial work that made it uneconomical. In the recent years, the development of technologies in mapping, advancement in image processing algorithms and computer vision, together with the development of digital aerial cameras with NIR band and Very High Resolution satellites, allow the implementation of a cost effective automated process. The automatic process is based on high-resolution Digital Surface Model analysis, Multi Spectral (MS) classification, MS segmentation, object analysis and shape forming algorithms. This article reviews the results of a novel change detection methodology as a first step for updating NTDB in the Survey of Israel.

Spectral Phasor approach for fingerprinting of photo-activatable fluorescent proteins Dronpa, Kaede and KikGR

PubMed Central

Cutrale, Francesco; Salih, Anya; Gratton, Enrico

2013-01-01

The phasor global analysis algorithm is common for fluorescence lifetime applications, but has only been recently proposed for spectral analysis. Here the phasor representation and fingerprinting is exploited in its second harmonic to determine the number and spectra of photo-activated states as well as their conversion dynamics. We follow the sequence of photo-activation of proteins over time by rapidly collecting multiple spectral images. The phasor representation of the cumulative images provides easy identification of the spectral signatures of each photo-activatable protein. PMID:24040513

SpectralNET – an application for spectral graph analysis and visualization

PubMed Central

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.

PubMed

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.

UV spectroscopy including ISM line absorption: of the exciting star of Abell 35

NASA Astrophysics Data System (ADS)

Ziegler, M.; Rauch, T.; Werner, K.; Kruk, J. W.

Reliable spectral analysis that is based on high-resolution UV observations requires an adequate, simultaneous modeling of the interstellar line absorption and reddening. In the case of the central star of the planetary nebula Abell 35, BD-22 3467, we demonstrate our current standard spectral-analysis method that is based on the Tübingen NLTE Model-Atmosphere Package (TMAP). We present an on- going spectral analysis of FUSE and HST/STIS observations of BD-22 3467.

Laboratory spectroscopy of meteorite samples at UV-vis-NIR wavelengths: Analysis and discrimination by principal components analysis

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.

Determining cantilever stiffness from thermal noise.

PubMed

Lübbe, Jannis; Temmen, Matthias; Rahe, Philipp; Kühnle, Angelika; Reichling, Michael

2013-01-01

We critically discuss the extraction of intrinsic cantilever properties, namely eigenfrequency f n , quality factor Q n and specifically the stiffness k n of the nth cantilever oscillation mode from thermal noise by an analysis of the power spectral density of displacement fluctuations of the cantilever in contact with a thermal bath. The practical applicability of this approach is demonstrated for several cantilevers with eigenfrequencies ranging from 50 kHz to 2 MHz. As such an analysis requires a sophisticated spectral analysis, we introduce a new method to determine k n from a spectral analysis of the demodulated oscillation signal of the excited cantilever that can be performed in the frequency range of 10 Hz to 1 kHz regardless of the eigenfrequency of the cantilever. We demonstrate that the latter method is in particular useful for noncontact atomic force microscopy (NC-AFM) where the required simple instrumentation for spectral analysis is available in most experimental systems.

Wide field-of-view dual-band multispectral muzzle flash detection

NASA Astrophysics Data System (ADS)

Montoya, J.; Melchor, J.; Spiliotis, P.; Taplin, L.

2013-06-01

Sensor technologies are undergoing revolutionary advances, as seen in the rapid growth of multispectral methodologies. Increases in spatial, spectral, and temporal resolution, and in breadth of spectral coverage, render feasible sensors that function with unprecedented performance. A system was developed that addresses many of the key hardware requirements for a practical dual-band multispectral acquisition system, including wide field of view and spectral/temporal shift between dual bands. The system was designed using a novel dichroic beam splitter and dual band-pass filter configuration that creates two side-by-side images of a scene on a single sensor. A high-speed CMOS sensor was used to simultaneously capture data from the entire scene in both spectral bands using a short focal-length lens that provided a wide field-of-view. The beam-splitter components were arranged such that the two images were maintained in optical alignment and real-time intra-band processing could be carried out using only simple arithmetic on the image halves. An experiment related to limitations of the system to address multispectral detection requirements was performed. This characterized the system's low spectral variation across its wide field of view. This paper provides lessons learned on the general limitation of key hardware components required for multispectral muzzle flash detection, using the system as a hardware example combined with simulated multispectral muzzle flash and background signatures.

Spatio-temporally resolved spectral measurements of laser-produced plasma and semiautomated spectral measurement-control and analysis software

NASA Astrophysics Data System (ADS)

Cao, S. Q.; Su, M. G.; Min, Q.; Sun, D. X.; O'Sullivan, G.; Dong, C. Z.

2018-02-01

A spatio-temporally resolved spectral measurement system of highly charged ions from laser-produced plasmas is presented. Corresponding semiautomated computer software for measurement control and spectral analysis has been written to achieve the best synchronicity possible among the instruments. This avoids the tedious comparative processes between experimental and theoretical results. To demonstrate the capabilities of this system, a series of spatio-temporally resolved experiments of laser-produced Al plasmas have been performed and applied to benchmark the software. The system is a useful tool for studying the spectral structures of highly charged ions and for evaluating the spatio-temporal evolution of laser-produced plasmas.

Land use in the Paraiba Valley through remotely sensed data. [Brazil

NASA Technical Reports Server (NTRS)

Dejesusparada, N. (Principal Investigator); Lombardo, M. A.; Novo, E. M. L. D.; Niero, M.; Foresti, C.

1980-01-01

A methodology for land use survey was developed and land use modification rates were determined using LANDSAT imagery of the Paraiba Valley (state of Sao Paulo). Both visual and automatic interpretation methods were employed to analyze seven land use classes: urban area, industrial area, bare soil, cultivated area, pastureland, reforestation and natural vegetation. By means of visual interpretation, little spectral differences are observed among those classes. The automatic classification of LANDSAT MSS data using maximum likelihood algorithm shows a 39% average error of omission and a 3.4% error of inclusion for the seven classes. The complexity of land uses in the study area, the large spectral variations of analyzed classes, and the low resolution of LANDSAT data influenced the classification results.

Determining nucleosynthesis yields in supernovae with spectral modelling

NASA Astrophysics Data System (ADS)

Jerkstrand, Anders

2018-04-01

The methodology to estimate element masses in supernova ejecta from nebular spectroscopy is discussed. Results using the SUMO spectral synthesis code are reviewed with regard to two key elements; oxygen (a hydrostatic burning ash) and nickel (an explosive burning ash). The typical oxygen mass in both Type IIP and IIb supernovae is found to be ˜0.5 M⊙, and points to progenitor stars in the 8 - 17 M⊙ range. For nickel, a new diagnostic method has been developed that shows Ni/Fe production close to solar in most cases, but sometimes larger by a factor of a few. It is shown that the larger values require the burning of silicon shell layers in the progenitor, a unique constraint on explosion theory.

Single-step fabrication of thin-film linear variable bandpass filters based on metal-insulator-metal geometry.

PubMed

Williams, Calum; Rughoobur, Girish; Flewitt, Andrew J; Wilkinson, Timothy D

2016-11-10

A single-step fabrication method is presented for ultra-thin, linearly variable optical bandpass filters (LVBFs) based on a metal-insulator-metal arrangement using modified evaporation deposition techniques. This alternate process methodology offers reduced complexity and cost in comparison to conventional techniques for fabricating LVBFs. We are able to achieve linear variation of insulator thickness across a sample, by adjusting the geometrical parameters of a typical physical vapor deposition process. We demonstrate LVBFs with spectral selectivity from 400 to 850 nm based on Ag (25 nm) and MgF₂ (75-250 nm). Maximum spectral transmittance is measured at ∼70% with a Q-factor of ∼20.

Spectral reconstruction analysis for enhancing signal-to-noise in time-resolved spectroscopies

NASA Astrophysics Data System (ADS)

Wilhelm, Michael J.; Smith, Jonathan M.; Dai, Hai-Lung

2015-09-01

We demonstrate a new spectral analysis for the enhancement of the signal-to-noise ratio (SNR) in time-resolved spectroscopies. Unlike the simple linear average which produces a single representative spectrum with enhanced SNR, this Spectral Reconstruction analysis (SRa) improves the SNR (by a factor of ca. 0 . 6 √{ n } ) for all n experimentally recorded time-resolved spectra. SRa operates by eliminating noise in the temporal domain, thereby attenuating noise in the spectral domain, as follows: Temporal profiles at each measured frequency are fit to a generic mathematical function that best represents the temporal evolution; spectra at each time are then reconstructed with data points from the fitted profiles. The SRa method is validated with simulated control spectral data sets. Finally, we apply SRa to two distinct experimentally measured sets of time-resolved IR emission spectra: (1) UV photolysis of carbonyl cyanide and (2) UV photolysis of vinyl cyanide.