Multispectral scanner system parameter study and analysis software system description, volume 2

NASA Technical Reports Server (NTRS)

Landgrebe, D. A. (Principal Investigator); Mobasseri, B. G.; Wiersma, D. J.; Wiswell, E. R.; Mcgillem, C. D.; Anuta, P. E.

1978-01-01

The author has identified the following significant results. The integration of the available methods provided the analyst with the unified scanner analysis package (USAP), the flexibility and versatility of which was superior to many previous integrated techniques. The USAP consisted of three main subsystems; (1) a spatial path, (2) a spectral path, and (3) a set of analytic classification accuracy estimators which evaluated the system performance. The spatial path consisted of satellite and/or aircraft data, data correlation analyzer, scanner IFOV, and random noise model. The output of the spatial path was fed into the analytic classification and accuracy predictor. The spectral path consisted of laboratory and/or field spectral data, EXOSYS data retrieval, optimum spectral function calculation, data transformation, and statistics calculation. The output of the spectral path was fended into the stratified posterior performance estimator.

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.

A distributed microcomputer-controlled system for data acquisition and power spectral analysis of EEG.

PubMed

Vo, T D; Dwyer, G; Szeto, H H

1986-04-01

A relatively powerful and inexpensive microcomputer-based system for the spectral analysis of the EEG is presented. High resolution and speed is achieved with the use of recently available large-scale integrated circuit technology with enhanced functionality (INTEL Math co-processors 8087) which can perform transcendental functions rapidly. The versatility of the system is achieved with a hardware organization that has distributed data acquisition capability performed by the use of a microprocessor-based analog to digital converter with large resident memory (Cyborg ISAAC-2000). Compiled BASIC programs and assembly language subroutines perform on-line or off-line the fast Fourier transform and spectral analysis of the EEG which is stored as soft as well as hard copy. Some results obtained from test application of the entire system in animal studies are presented.

Optimal wavelength band clustering for multispectral iris recognition.

PubMed

Gong, Yazhuo; Zhang, David; Shi, Pengfei; Yan, Jingqi

2012-07-01

This work explores the possibility of clustering spectral wavelengths based on the maximum dissimilarity of iris textures. The eventual goal is to determine how many bands of spectral wavelengths will be enough for iris multispectral fusion and to find these bands that will provide higher performance of iris multispectral recognition. A multispectral acquisition system was first designed for imaging the iris at narrow spectral bands in the range of 420 to 940 nm. Next, a set of 60 human iris images that correspond to the right and left eyes of 30 different subjects were acquired for an analysis. Finally, we determined that 3 clusters were enough to represent the 10 feature bands of spectral wavelengths using the agglomerative clustering based on two-dimensional principal component analysis. The experimental results suggest (1) the number, center, and composition of clusters of spectral wavelengths and (2) the higher performance of iris multispectral recognition based on a three wavelengths-bands fusion.

A theoretical-experimental methodology for assessing the sensitivity of biomedical spectral imaging platforms, assays, and analysis methods.

PubMed

Leavesley, Silas J; Sweat, Brenner; Abbott, Caitlyn; Favreau, Peter; Rich, Thomas C

2018-01-01

Spectral imaging technologies have been used for many years by the remote sensing community. More recently, these approaches have been applied to biomedical problems, where they have shown great promise. However, biomedical spectral imaging has been complicated by the high variance of biological data and the reduced ability to construct test scenarios with fixed ground truths. Hence, it has been difficult to objectively assess and compare biomedical spectral imaging assays and technologies. Here, we present a standardized methodology that allows assessment of the performance of biomedical spectral imaging equipment, assays, and analysis algorithms. This methodology incorporates real experimental data and a theoretical sensitivity analysis, preserving the variability present in biomedical image data. We demonstrate that this approach can be applied in several ways: to compare the effectiveness of spectral analysis algorithms, to compare the response of different imaging platforms, and to assess the level of target signature required to achieve a desired performance. Results indicate that it is possible to compare even very different hardware platforms using this methodology. Future applications could include a range of optimization tasks, such as maximizing detection sensitivity or acquisition speed, providing high utility for investigators ranging from design engineers to biomedical scientists. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Design framework for a spectral mask for a plenoptic camera

NASA Astrophysics Data System (ADS)

Berkner, Kathrin; Shroff, Sapna A.

2012-01-01

Plenoptic cameras are designed to capture different combinations of light rays from a scene, sampling its lightfield. Such camera designs capturing directional ray information enable applications such as digital refocusing, rotation, or depth estimation. Only few address capturing spectral information of the scene. It has been demonstrated that by modifying a plenoptic camera with a filter array containing different spectral filters inserted in the pupil plane of the main lens, sampling of the spectral dimension of the plenoptic function is performed. As a result, the plenoptic camera is turned into a single-snapshot multispectral imaging system that trades-off spatial with spectral information captured with a single sensor. Little work has been performed so far on analyzing diffraction effects and aberrations of the optical system on the performance of the spectral imager. In this paper we demonstrate simulation of a spectrally-coded plenoptic camera optical system via wave propagation analysis, evaluate quality of the spectral measurements captured at the detector plane, and demonstrate opportunities for optimization of the spectral mask for a few sample applications.

Spectral analysis comparisons of Fourier-theory-based methods and minimum variance (Capon) methods

NASA Astrophysics Data System (ADS)

Garbanzo-Salas, Marcial; Hocking, Wayne. K.

2015-09-01

In recent years, adaptive (data dependent) methods have been introduced into many areas where Fourier spectral analysis has traditionally been used. Although the data-dependent methods are often advanced as being superior to Fourier methods, they do require some finesse in choosing the order of the relevant filters. In performing comparisons, we have found some concerns about the mappings, particularly when related to cases involving many spectral lines or even continuous spectral signals. Using numerical simulations, several comparisons between Fourier transform procedures and minimum variance method (MVM) have been performed. For multiple frequency signals, the MVM resolves most of the frequency content only for filters that have more degrees of freedom than the number of distinct spectral lines in the signal. In the case of Gaussian spectral approximation, MVM will always underestimate the width, and can misappropriate the location of spectral line in some circumstances. Large filters can be used to improve results with multiple frequency signals, but are computationally inefficient. Significant biases can occur when using MVM to study spectral information or echo power from the atmosphere. Artifacts and artificial narrowing of turbulent layers is one such impact.

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.

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.

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.

Investigation of Periodic Nuclear Decay Data with Spectral Analysis Techniques

NASA Astrophysics Data System (ADS)

Javorsek, D.; Sturrock, P.; Buncher, J.; Fischbach, E.; Gruenwald, T.; Hoft, A.; Horan, T.; Jenkins, J.; Kerford, J.; Lee, R.; Mattes, J.; Morris, D.; Mudry, R.; Newport, J.; Petrelli, M.; Silver, M.; Stewart, C.; Terry, B.; Willenberg, H.

2009-12-01

We provide the results from a spectral analysis of nuclear decay experiments displaying unexplained periodic fluctuations. The analyzed data was from 56Mn decay reported by the Children's Nutrition Research Center in Houston, 32Si decay reported by an experiment performed at the Brookhaven National Laboratory, and 226Ra decay reported by an experiment performed at the Physikalisch-Technische-Bundesanstalt in Germany. All three data sets possess the same primary frequency mode consisting of an annual period. Additionally a spectral comparison of the local ambient temperature, atmospheric pressure, relative humidity, Earth-Sun distance, and the plasma speed and latitude of the heliospheric current sheet (HCS) was performed. Following analysis of these six possible causal factors, their reciprocals, and their linear combinations, a possible link between nuclear decay rate fluctuations and the linear combination of the HCS latitude and 1/R motivates searching for a possible mechanism with such properties.

Power spectral density analysis of the electromyogram from a work task performed in a full pressure suit. Ph.D. Thesis - Houston Univ.; [for determining muscular fatigue

NASA Technical Reports Server (NTRS)

Lafevers, E. V.

1974-01-01

Surface electromyograms (EMG) taken from three upper torso muscles during a push-pull task were analyzed by a power spectral density technique to determine the utility of the spectral analysis for identifying changes in the EMG caused by muscular fatigue. The results confirmed the value of the frequency analysis for identifying fatigue producing muscular performance. Data revealed reliable differences between muscles in fatigue induced responses to various locations in the reach envelope at which the subjects were required to perform the push-pull exercise, and the differential sensitivity of individual muscles to the various reach positions; i.e., certain reach positions imposed more fatigue related shifts in EMG power than did others. It was found that a pressurized space suit changed the pattern of normal shirtsleeve muscle fatigue responses in all three of the muscles.

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

NASA Astrophysics Data System (ADS)

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

2015-11-01

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

An experiment with spectral analysis of emotional speech affected by orthodontic appliances

NASA Astrophysics Data System (ADS)

Přibil, Jiří; Přibilová, Anna; Ďuračková, Daniela

2012-11-01

The contribution describes the effect of the fixed and removable orthodontic appliances on spectral properties of emotional speech. Spectral changes were analyzed and evaluated by spectrograms and mean Welch’s periodograms. This alternative approach to the standard listening test enables to obtain objective comparison based on statistical analysis by ANOVA and hypothesis tests. Obtained results of analysis performed on short sentences of a female speaker in four emotional states (joyous, sad, angry, and neutral) show that, first of all, the removable orthodontic appliance affects the spectrograms of produced speech.

Documentation and user's guide for interactive spectral analysis and filter program package useful in the processing of seismic reflection data

USGS Publications Warehouse

Miller, J.J.

1982-01-01

The spectral analysis and filter program package is written in the BASIC language for the HP-9845T desktop computer. The program's main purpose is to perform spectral analyses on digitized time-domain data. In addition, band-pass filtering of the data can be performed in the time domain. Various other processes such as autocorrelation can be performed to the time domain data in order to precondition them for spectral analyses. The frequency domain data can also be transformed back into the time domain if desired. Any data can be displayed on the CRT in graphic form using a variety of plot routines. A hard copy can be obtained immediately using the internal thermal printer. Data can also be displayed in tabular form on the CRT or internal thermal printer or it can be stored permanently on a mass storage device like a tape or disk. A list of the processes performed in the order in which they occurred can be displayed at any time.

Development of spectral analysis math models and software program and spectral analyzer, digital converter interface equipment design

NASA Technical Reports Server (NTRS)

Hayden, W. L.; Robinson, L. H.

1972-01-01

Spectral analyses of angle-modulated communication systems is studied by: (1) performing a literature survey of candidate power spectrum computational techniques, determining the computational requirements, and formulating a mathematical model satisfying these requirements; (2) implementing the model on UNIVAC 1230 digital computer as the Spectral Analysis Program (SAP); and (3) developing the hardware specifications for a data acquisition system which will acquire an input modulating signal for SAP. The SAP computational technique uses extended fast Fourier transform and represents a generalized approach for simple and complex modulating signals.

Spectral element multigrid. Part 2: Theoretical justification

NASA Technical Reports Server (NTRS)

Maday, Yvon; Munoz, Rafael

1988-01-01

A multigrid algorithm is analyzed which is used for solving iteratively the algebraic system resulting from tha approximation of a second order problem by spectral or spectral element methods. The analysis, performed here in the one dimensional case, justifies the good smoothing properties of the Jacobi preconditioner that was presented in Part 1 of this paper.

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.

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.

Comparative Analysis of Haar and Daubechies Wavelet for Hyper Spectral Image Classification

NASA Astrophysics Data System (ADS)

Sharif, I.; Khare, S.

2014-11-01

With the number of channels in the hundreds instead of in the tens Hyper spectral imagery possesses much richer spectral information than multispectral imagery. The increased dimensionality of such Hyper spectral data provides a challenge to the current technique for analyzing data. Conventional classification methods may not be useful without dimension reduction pre-processing. So dimension reduction has become a significant part of Hyper spectral image processing. This paper presents a comparative analysis of the efficacy of Haar and Daubechies wavelets for dimensionality reduction in achieving image classification. Spectral data reduction using Wavelet Decomposition could be useful because it preserves the distinction among spectral signatures. Daubechies wavelets optimally capture the polynomial trends while Haar wavelet is discontinuous and resembles a step function. The performance of these wavelets are compared in terms of classification accuracy and time complexity. This paper shows that wavelet reduction has more separate classes and yields better or comparable classification accuracy. In the context of the dimensionality reduction algorithm, it is found that the performance of classification of Daubechies wavelets is better as compared to Haar wavelet while Daubechies takes more time compare to Haar wavelet. The experimental results demonstrate the classification system consistently provides over 84% classification accuracy.

EEG Correlates of Fluctuation in Cognitive Performance in an Air Traffic Control Task

DTIC Science & Technology

2014-11-01

using non-parametric statistical analysis to identify neurophysiological patterns due to the time-on-task effect. Significant changes in EEG power...EEG, Cognitive Performance, Power Spectral Analysis , Non-Parametric Analysis Document is available to the public through the Internet...3 Performance Data Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 EEG

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.

Spectral Entropy Can Predict Changes of Working Memory Performance Reduced by Short-Time Training in the Delayed-Match-to-Sample Task

PubMed Central

Tian, Yin; Zhang, Huiling; Xu, Wei; Zhang, Haiyong; Yang, Li; Zheng, Shuxing; Shi, Yupan

2017-01-01

Spectral entropy, which was generated by applying the Shannon entropy concept to the power distribution of the Fourier-transformed electroencephalograph (EEG), was utilized to measure the uniformity of power spectral density underlying EEG when subjects performed the working memory tasks twice, i.e., before and after training. According to Signed Residual Time (SRT) scores based on response speed and accuracy trade-off, 20 subjects were divided into two groups, namely high-performance and low-performance groups, to undertake working memory (WM) tasks. We found that spectral entropy derived from the retention period of WM on channel FC4 exhibited a high correlation with SRT scores. To this end, spectral entropy was used in support vector machine classifier with linear kernel to differentiate these two groups. Receiver operating characteristics analysis and leave-one out cross-validation (LOOCV) demonstrated that the averaged classification accuracy (CA) was 90.0 and 92.5% for intra-session and inter-session, respectively, indicating that spectral entropy could be used to distinguish these two different WM performance groups successfully. Furthermore, the support vector regression prediction model with radial basis function kernel and the root-mean-square error of prediction revealed that spectral entropy could be utilized to predict SRT scores on individual WM performance. After testing the changes in SRT scores and spectral entropy for each subject by short-time training, we found that 16 in 20 subjects’ SRT scores were clearly promoted after training and 15 in 20 subjects’ SRT scores showed consistent changes with spectral entropy before and after training. The findings revealed that spectral entropy could be a promising indicator to predict individual’s WM changes by training and further provide a novel application about WM for brain–computer interfaces. PMID:28912701

Fusion and quality analysis for remote sensing images using contourlet transform

NASA Astrophysics Data System (ADS)

Choi, Yoonsuk; Sharifahmadian, Ershad; Latifi, Shahram

2013-05-01

Recent developments in remote sensing technologies have provided various images with high spatial and spectral resolutions. However, multispectral images have low spatial resolution and panchromatic images have low spectral resolution. Therefore, image fusion techniques are necessary to improve the spatial resolution of spectral images by injecting spatial details of high-resolution panchromatic images. The objective of image fusion is to provide useful information by improving the spatial resolution and the spectral information of the original images. The fusion results can be utilized in various applications, such as military, medical imaging, and remote sensing. This paper addresses two issues in image fusion: i) image fusion method and ii) quality analysis of fusion results. First, a new contourlet-based image fusion method is presented, which is an improvement over the wavelet-based fusion. This fusion method is then applied to a case study to demonstrate its fusion performance. Fusion framework and scheme used in the study are discussed in detail. Second, quality analysis for the fusion results is discussed. We employed various quality metrics in order to analyze the fusion results both spatially and spectrally. Our results indicate that the proposed contourlet-based fusion method performs better than the conventional wavelet-based fusion methods.

Using spectral imaging for the analysis of abnormalities for colorectal cancer: When is it helpful?

PubMed

Awan, Ruqayya; Al-Maadeed, Somaya; Al-Saady, Rafif

2018-01-01

The spectral imaging technique has been shown to provide more discriminative information than the RGB images and has been proposed for a range of problems. There are many studies demonstrating its potential for the analysis of histopathology images for abnormality detection but there have been discrepancies among previous studies as well. Many multispectral based methods have been proposed for histopathology images but the significance of the use of whole multispectral cube versus a subset of bands or a single band is still arguable. We performed comprehensive analysis using individual bands and different subsets of bands to determine the effectiveness of spectral information for determining the anomaly in colorectal images. Our multispectral colorectal dataset consists of four classes, each represented by infra-red spectrum bands in addition to the visual spectrum bands. We performed our analysis of spectral imaging by stratifying the abnormalities using both spatial and spectral information. For our experiments, we used a combination of texture descriptors with an ensemble classification approach that performed best on our dataset. We applied our method to another dataset and got comparable results with those obtained using the state-of-the-art method and convolutional neural network based method. Moreover, we explored the relationship of the number of bands with the problem complexity and found that higher number of bands is required for a complex task to achieve improved performance. Our results demonstrate a synergy between infra-red and visual spectrum by improving the classification accuracy (by 6%) on incorporating the infra-red representation. We also highlight the importance of how the dataset should be divided into training and testing set for evaluating the histopathology image-based approaches, which has not been considered in previous studies on multispectral histopathology images.

Simultaneous screening of targeted and non-targeted contaminants using an LC-QTOF-MS system and automated MS/MS library searching.

PubMed

Herrera-Lopez, S; Hernando, M D; García-Calvo, E; Fernández-Alba, A R; Ulaszewska, M M

2014-09-01

Simultaneous high-resolution full-scan and tandem mass spectrometry (MS/MS) analysis using time of flight mass spectrometry brings an answer for increasing demand of retrospective and non-targeted data analysis. Such analysis combined with spectral library searching is a promising tool for targeted and untargeted screening of small molecules. Despite considerable extension of the panel of compounds of tandem mass spectral libraries, the heterogeneity of spectral data poses a major challenge against the effective usage of spectral libraries. Performance evaluation of available LC-MS/MS libraries will significantly increase credibility in the search results. The present work was aimed to evaluate fluctuation of MS/MS pattern, in the peak intensities distribution together with mass accuracy measurements, and in consequence, performance compliant with ion ratio and mass error criteria as principles in identification processes for targeted and untargeted contaminants at trace levels. Matrix effect and ultra-trace levels of concentration (from 50 ng l(-1) to 1000 ng l(-1) were evaluated as potential source of inaccuracy in the performance of spectral matching. Matrix-matched samples and real samples were screened for proof of applicability. By manual review of data and application of ion ratio and ppm error criteria, false negatives were obtained; this number diminished when in-house library was used, while with on-line MS/MS databases 100% of positive samples were found. In our experience, intensity of peaks across spectra was highly correlated to the concentration effect and matrix complexity. In turn, analysis of spectra acquired at trace concentrations and in different matrices results in better performance in providing correct and reliable identification. Copyright © 2014 John Wiley & Sons, Ltd.

Using spectral imaging for the analysis of abnormalities for colorectal cancer: When is it helpful?

PubMed Central

Al-Maadeed, Somaya; Al-Saady, Rafif

2018-01-01

The spectral imaging technique has been shown to provide more discriminative information than the RGB images and has been proposed for a range of problems. There are many studies demonstrating its potential for the analysis of histopathology images for abnormality detection but there have been discrepancies among previous studies as well. Many multispectral based methods have been proposed for histopathology images but the significance of the use of whole multispectral cube versus a subset of bands or a single band is still arguable. We performed comprehensive analysis using individual bands and different subsets of bands to determine the effectiveness of spectral information for determining the anomaly in colorectal images. Our multispectral colorectal dataset consists of four classes, each represented by infra-red spectrum bands in addition to the visual spectrum bands. We performed our analysis of spectral imaging by stratifying the abnormalities using both spatial and spectral information. For our experiments, we used a combination of texture descriptors with an ensemble classification approach that performed best on our dataset. We applied our method to another dataset and got comparable results with those obtained using the state-of-the-art method and convolutional neural network based method. Moreover, we explored the relationship of the number of bands with the problem complexity and found that higher number of bands is required for a complex task to achieve improved performance. Our results demonstrate a synergy between infra-red and visual spectrum by improving the classification accuracy (by 6%) on incorporating the infra-red representation. We also highlight the importance of how the dataset should be divided into training and testing set for evaluating the histopathology image-based approaches, which has not been considered in previous studies on multispectral histopathology images. PMID:29874262

Water quality parameter measurement using spectral signatures

NASA Technical Reports Server (NTRS)

White, P. E.

1973-01-01

Regression analysis is applied to the problem of measuring water quality parameters from remote sensing spectral signature data. The equations necessary to perform regression analysis are presented and methods of testing the strength and reliability of a regression are described. An efficient algorithm for selecting an optimal subset of the independent variables available for a regression is also presented.

Spectral characteristics of Shuttle glow

NASA Technical Reports Server (NTRS)

Viereck, R. A.; Mende, S. B.; Murad, E.; Swenson, G. R.; Pike, C. P.; Culbertson, F. L.; Springer, R. C.

1992-01-01

The glowing cloud near the ram surfaces of the Space Shuttle was observed with a hand-held, intensified spectrograph operated by the astronauts from the aft-flight-deck of the Space Shuttle. The spectral measurements were made between 400 and 800 nm with a resolution of 3 nm. Analysis of the spectral response of the instrument and the transmission of the Shuttle window was performed on orbit using earth-airglow OH Meinel bands. This analysis resulted in a correction of the Shuttle glow intensity in the spectral region between 700 and 800 nm. The data presented in this report is in better agreement with laboratory measurements of the NO2 continuum.

Spectral analysis of epicardial 60-lead electrograms in dogs with 4-week-old myocardial infarction.

PubMed

Hosoya, Y; Ikeda, K; Komatsu, T; Yamaki, M; Kubota, I

2001-01-01

There were few studies on the spectral analysis of multiple-lead epicardial electrograms in chronic myocardial infarction. Spectral analysis of multi-lead epicardial electrograms was performed in 6 sham-operated dogs (N group) and 8 dogs with 4-week-old myocardial infarction (MI group). Four weeks after the ligation of left anterior descending coronary artery, fast Fourier transform was performed on 60-lead epicardial electrograms, and then inverse transform was performed on 5 frequency ranges from 0 to 250 Hz. From the QRS onset to QRS offset, the time integration of unsigned value of reconstructed waveform was calculated and displayed as AQRS maps. On 0-25 Hz AQRS map, there was no significant difference between the 2 groups. In the frequency ranges of 25-250 Hz, MI group had significantly smaller AQRS values than N group solely in the infarct zone. It was shown that high frequency potentials (25-250 Hz) within QRS complex were reduced in the infarct zone.

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.

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

NASA Astrophysics Data System (ADS)

Pan, Zhuokun; Huang, Jingfeng; Wang, Fumin

2013-12-01

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

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.

Robust demarcation of basal cell carcinoma by dependent component analysis-based segmentation of multi-spectral fluorescence images.

PubMed

Kopriva, Ivica; Persin, Antun; Puizina-Ivić, Neira; Mirić, Lina

2010-07-02

This study was designed to demonstrate robust performance of the novel dependent component analysis (DCA)-based approach to demarcation of the basal cell carcinoma (BCC) through unsupervised decomposition of the red-green-blue (RGB) fluorescent image of the BCC. Robustness to intensity fluctuation is due to the scale invariance property of DCA algorithms, which exploit spectral and spatial diversities between the BCC and the surrounding tissue. Used filtering-based DCA approach represents an extension of the independent component analysis (ICA) and is necessary in order to account for statistical dependence that is induced by spectral similarity between the BCC and surrounding tissue. This generates weak edges what represents a challenge for other segmentation methods as well. By comparative performance analysis with state-of-the-art image segmentation methods such as active contours (level set), K-means clustering, non-negative matrix factorization, ICA and ratio imaging we experimentally demonstrate good performance of DCA-based BCC demarcation in two demanding scenarios where intensity of the fluorescent image has been varied almost two orders of magnitude. Copyright 2010 Elsevier B.V. All rights reserved.

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.

Performance enhancement of optical code-division multiple-access systems using transposed modified Walsh code

NASA Astrophysics Data System (ADS)

Sikder, Somali; Ghosh, Shila

2018-02-01

This paper presents the construction of unipolar transposed modified Walsh code (TMWC) and analysis of its performance in optical code-division multiple-access (OCDMA) systems. Specifically, the signal-to-noise ratio, bit error rate (BER), cardinality, and spectral efficiency were investigated. The theoretical analysis demonstrated that the wavelength-hopping time-spreading system using TMWC was robust against multiple-access interference and more spectrally efficient than systems using other existing OCDMA codes. In particular, the spectral efficiency was calculated to be 1.0370 when TMWC of weight 3 was employed. The BER and eye pattern for the designed TMWC were also successfully obtained using OptiSystem simulation software. The results indicate that the proposed code design is promising for enhancing network capacity.

DoE Phase II SBIR: Spectrally-Assisted Vehicle Tracking

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

Villeneuve, Pierre V.

2013-02-28

The goal of this Phase II SBIR is to develop a prototype software package to demonstrate spectrally-aided vehicle tracking performance. The primary application is to demonstrate improved target vehicle tracking performance in complex environments where traditional spatial tracker systems may show reduced performance. Example scenarios in Figure 1 include a) the target vehicle obscured by a large structure for an extended period of time, or b), the target engaging in extreme maneuvers amongst other civilian vehicles. The target information derived from spatial processing is unable to differentiate between the green versus the red vehicle. Spectral signature exploitation enables comparison ofmore » new candidate targets with existing track signatures. The ambiguity in this confusing scenario is resolved by folding spectral analysis results into each target nomination and association processes. Figure 3 shows a number of example spectral signatures from a variety of natural and man-made materials. The work performed over the two-year effort was divided into three general areas: algorithm refinement, software prototype development, and prototype performance demonstration. The tasks performed under this Phase II to accomplish the program goals were as follows: 1. Acquire relevant vehicle target datasets to support prototype. 2. Refine algorithms for target spectral feature exploitation. 3. Implement a prototype multi-hypothesis target tracking software package. 4. Demonstrate and quantify tracking performance using relevant data.« less

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.

EZ and GOSSIP, two new VO compliant tools for spectral analysis

NASA Astrophysics Data System (ADS)

Franzetti, P.; Garill, B.; Fumana, M.; Paioro, L.; Scodeggio, M.; Paltani, S.; Scaramella, R.

2008-10-01

We present EZ and GOSSIP, two new VO compliant tools dedicated to spectral analysis. EZ is a tool to perform automatic redshift measurement; GOSSIP is a tool created to perform the SED fitting procedure in a simple, user friendly and efficient way. These two tools have been developed by the PANDORA Group at INAF-IASF (Milano); EZ has been developed in collaboration with Osservatorio Monte Porzio (Roma) and Integral Science Data Center (Geneve). EZ is released to the astronomical community; GOSSIP is currently in beta-testing.

Fusion of spectral models for dynamic modeling of sEMG and skeletal muscle force.

PubMed

Potluri, Chandrasekhar; Anugolu, Madhavi; Chiu, Steve; Urfer, Alex; Schoen, Marco P; Naidu, D Subbaram

2012-01-01

In this paper, we present a method of combining spectral models using a Kullback Information Criterion (KIC) data fusion algorithm. Surface Electromyographic (sEMG) signals and their corresponding skeletal muscle force signals are acquired from three sensors and pre-processed using a Half-Gaussian filter and a Chebyshev Type- II filter, respectively. Spectral models - Spectral Analysis (SPA), Empirical Transfer Function Estimate (ETFE), Spectral Analysis with Frequency Dependent Resolution (SPFRD) - are extracted from sEMG signals as input and skeletal muscle force as output signal. These signals are then employed in a System Identification (SI) routine to establish the dynamic models relating the input and output. After the individual models are extracted, the models are fused by a probability based KIC fusion algorithm. The results show that the SPFRD spectral models perform better than SPA and ETFE models in modeling the frequency content of the sEMG/skeletal muscle force data.

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.

The browning value changes and spectral analysis on the Maillard reaction product from glucose and methionine model system

NASA Astrophysics Data System (ADS)

Al-Baarri, A. N.; Legowo, A. M.; Widayat

2018-01-01

D-glucose has been understood to provide the various effect on the reactivity in Maillard reaction resulting in the changes in physical performance of food product. Therefore this research was done to analyse physical appearance of Maillard reaction product made of D-glucose and methionine as a model system. The changes in browning value and spectral analysis model system were determined. The glucose-methionine model system was produced through the heating treatment at 50°C and RH 70% for 24 hours. The data were collected for every three hour using spectrophotometer. As result, browning value was elevated with the increase of heating time and remarkably high if compare to the D-glucose only. Furthermore, the spectral analysis showed that methionine turned the pattern of peak appearance. As conclusion, methionine raised the browning value and changed the pattern of spectral analysis in Maillard reaction model system.

Characterizing the performance of ecosystem models across time scales: A spectral analysis of the North American Carbon Program site-level synthesis

Treesearch

Michael C. Dietze; Rodrigo Vargas; Andrew D. Richardson; Paul C. Stoy; Alan G. Barr; Ryan S. Anderson; M. Altaf Arain; Ian T. Baker; T. Andrew Black; Jing M. Chen; Philippe Ciais; Lawrence B. Flanagan; Christopher M. Gough; Robert F. Grant; David Hollinger; R. Cesar Izaurralde; Christopher J. Kucharik; Peter Lafleur; Shugang Liu; Erandathie Lokupitiya; Yiqi Luo; J. William Munger; Changhui Peng; Benjamin Poulter; David T. Price; Daniel M. Ricciuto; William J. Riley; Alok Kumar Sahoo; Kevin Schaefer; Andrew E. Suyker; Hanqin Tian; Christina Tonitto; Hans Verbeeck; Shashi B. Verma; Weifeng Wang; Ensheng Weng

2011-01-01

Ecosystem models are important tools for diagnosing the carbon cycle and projecting its behavior across space and time. Despite the fact that ecosystems respond to drivers at multiple time scales, most assessments of model performance do not discriminate different time scales. Spectral methods, such as wavelet analyses, present an alternative approach that enables the...

Relevance of Spectral Cues for Auditory Spatial Processing in the Occipital Cortex of the Blind

PubMed Central

Voss, Patrice; Lepore, Franco; Gougoux, Frédéric; Zatorre, Robert J.

2011-01-01

We have previously shown that some blind individuals can localize sounds more accurately than their sighted counterparts when one ear is obstructed, and that this ability is strongly associated with occipital cortex activity. Given that spectral cues are important for monaurally localizing sounds when one ear is obstructed, and that blind individuals are more sensitive to small spectral differences, we hypothesized that enhanced use of spectral cues via occipital cortex mechanisms could explain the better performance of blind individuals in monaural localization. Using positron-emission tomography (PET), we scanned blind and sighted persons as they discriminated between sounds originating from a single spatial position, but with different spectral profiles that simulated different spatial positions based on head-related transfer functions. We show here that a sub-group of early blind individuals showing superior monaural sound localization abilities performed significantly better than any other group on this spectral discrimination task. For all groups, performance was best for stimuli simulating peripheral positions, consistent with the notion that spectral cues are more helpful for discriminating peripheral sources. PET results showed that all blind groups showed cerebral blood flow increases in the occipital cortex; but this was also the case in the sighted group. A voxel-wise covariation analysis showed that more occipital recruitment was associated with better performance across all blind subjects but not the sighted. An inter-regional covariation analysis showed that the occipital activity in the blind covaried with that of several frontal and parietal regions known for their role in auditory spatial processing. Overall, these results support the notion that the superior ability of a sub-group of early-blind individuals to localize sounds is mediated by their superior ability to use spectral cues, and that this ability is subserved by cortical processing in the occipital cortex. PMID:21716600

Metric for evaluation of filter efficiency in spectral cameras.

PubMed

Nahavandi, Alireza Mahmoudi; Tehran, Mohammad Amani

2016-11-10

Although metric functions that show the performance of a colorimetric imaging device have been investigated, a metric for performance analysis of a set of filters in wideband filter-based spectral cameras has rarely been studied. Based on a generalization of Vora's Measure of Goodness (MOG) and the spanning theorem, a single function metric that estimates the effectiveness of a filter set is introduced. The improved metric, named MMOG, varies between one, for a perfect, and zero, for the worst possible set of filters. Results showed that MMOG exhibits a trend that is more similar to the mean square of spectral reflectance reconstruction errors than does Vora's MOG index, and it is robust to noise in the imaging system. MMOG as a single metric could be exploited for further analysis of manufacturing errors.

Reliable Quantitative Mineral Abundances of the Martian Surface using THEMIS

NASA Astrophysics Data System (ADS)

Smith, R. J.; Huang, J.; Ryan, A. J.; Christensen, P. R.

2013-12-01

The following presents a proof of concept that given quality data, Thermal Emission Imaging System (THEMIS) data can be used to derive reliable quantitative mineral abundances of the Martian surface using a limited mineral library. The THEMIS instrument aboard the Mars Odyssey spacecraft is a multispectral thermal infrared imager with a spatial resolution of 100 m/pixel. The relatively high spatial resolution along with global coverage makes THEMIS datasets powerful tools for comprehensive fine scale petrologic analyses. However, the spectral resolution of THEMIS is limited to 8 surface sensitive bands between 6.8 and 14.0 μm with an average bandwidth of ~ 1 μm, which complicates atmosphere-surface separation and spectral analysis. This study utilizes the atmospheric correction methods of both Bandfield et al. [2004] and Ryan et al. [2013] joined with the iterative linear deconvolution technique pioneered by Huang et al. [in review] in order to derive fine-scale quantitative mineral abundances of the Martian surface. In general, it can be assumed that surface emissivity combines in a linear fashion in the thermal infrared (TIR) wavelengths such that the emitted energy is proportional to the areal percentage of the minerals present. TIR spectra are unmixed using a set of linear equations involving an endmember library of lab measured mineral spectra. The number of endmembers allowed in a spectral library are restricted to a quantity of n-1 (where n = the number of spectral bands of an instrument), preserving one band for blackbody. Spectral analysis of THEMIS data is thus allowed only seven endmembers. This study attempts to prove that this limitation does not prohibit the derivation of meaningful spectral analyses from THEMIS data. Our study selects THEMIS stamps from a region of Mars that is well characterized in the TIR by the higher spectral resolution, lower spatial resolution Thermal Emission Spectrometer (TES) instrument (143 bands at 10 cm-1 sampling and 3x5 km pixel). Multiple atmospheric corrections are performed for one image using the methods of Bandfield et al. [2004] and Ryan et al. [2013]. 7x7 pixel areas were selected, averaged, and compared using each atmospherically corrected image to ensure consistency. Corrections that provided reliable data were then used for spectral analyses. Linear deconvolution is performed using an iterative spectral analysis method [Huang et al. in review] that takes an endmember spectral library, and creates mineral combinations based on prescribed mineral group selections. The script then performs a spectral mixture analysis on each surface spectrum using all possible mineral combinations, and reports the best modeled fit to the measured spectrum. Here we present initial results from Syrtis Planum where multiple atmospherically corrected THEMIS images were deconvolved to produce similar spectral analysis results, within the detection limit of the instrument. THEMIS mineral abundances are comparable to TES-derived abundances. References: Bandfield, JL et al. [2004], JGR 109, E10008 Huang, J et al., JGR, in review Ryan, AJ et al. [2013], AGU Fall Meeting

An Excel‐based implementation of the spectral method of action potential alternans analysis

PubMed Central

Pearman, Charles M.

2014-01-01

Abstract Action potential (AP) alternans has been well established as a mechanism of arrhythmogenesis and sudden cardiac death. Proper interpretation of AP alternans requires a robust method of alternans quantification. Traditional methods of alternans analysis neglect higher order periodicities that may have greater pro‐arrhythmic potential than classical 2:1 alternans. The spectral method of alternans analysis, already widely used in the related study of microvolt T‐wave alternans, has also been used to study AP alternans. Software to meet the specific needs of AP alternans analysis is not currently available in the public domain. An AP analysis tool is implemented here, written in Visual Basic for Applications and using Microsoft Excel as a shell. This performs a sophisticated analysis of alternans behavior allowing reliable distinction of alternans from random fluctuations, quantification of alternans magnitude, and identification of which phases of the AP are most affected. In addition, the spectral method has been adapted to allow detection and quantification of higher order regular oscillations. Analysis of action potential morphology is also performed. A simple user interface enables easy import, analysis, and export of collated results. PMID:25501439

An accurate evaluation of the performance of asynchronous DS-CDMA systems with zero-correlation-zone coding in Rayleigh fading

NASA Astrophysics Data System (ADS)

Walker, Ernest; Chen, Xinjia; Cooper, Reginald L.

2010-04-01

An arbitrarily accurate approach is used to determine the bit-error rate (BER) performance for generalized asynchronous DS-CDMA systems, in Gaussian noise with Raleigh fading. In this paper, and the sequel, new theoretical work has been contributed which substantially enhances existing performance analysis formulations. Major contributions include: substantial computational complexity reduction, including a priori BER accuracy bounding; an analytical approach that facilitates performance evaluation for systems with arbitrary spectral spreading distributions, with non-uniform transmission delay distributions. Using prior results, augmented by these enhancements, a generalized DS-CDMA system model is constructed and used to evaluated the BER performance, in a variety of scenarios. In this paper, the generalized system modeling was used to evaluate the performance of both Walsh- Hadamard (WH) and Walsh-Hadamard-seeded zero-correlation-zone (WH-ZCZ) coding. The selection of these codes was informed by the observation that WH codes contain N spectral spreading values (0 to N - 1), one for each code sequence; while WH-ZCZ codes contain only two spectral spreading values (N/2 - 1,N/2); where N is the sequence length in chips. Since these codes span the spectral spreading range for DS-CDMA coding, by invoking an induction argument, the generalization of the system model is sufficiently supported. The results in this paper, and the sequel, support the claim that an arbitrary accurate performance analysis for DS-CDMA systems can be evaluated over the full range of binary coding, with minimal computational complexity.

Simulation and analysis of Au-MgF2 structure in plasmonic sensor in near infrared spectral region

NASA Astrophysics Data System (ADS)

Sharma, Anuj K.

2018-05-01

Plasmonic sensor based on metal-dielectric combination of gold and MgF2 layers is studied in near infrared (NIR) spectral region. An emphasis is given on the effect of variable thickness of MgF2 layer in combination with operating wavelength and gold layer thickness on the sensor's performance in NIR. It is established that the variation in MgF2 thickness in connection with plasmon penetration depth leads to significant variation in sensor's performance. The analysis leads to a conclusion that taking smaller values of MgF2 layer thickness and operating at longer NIR wavelength leads to enhanced sensing performance. Also, fluoride glass can provide better sensing performance than chalcogenide glass and silicon substrate.

Nonlinear single-spin spectrum analyzer.

PubMed

Kotler, Shlomi; Akerman, Nitzan; Glickman, Yinnon; Ozeri, Roee

2013-03-15

Qubits have been used as linear spectrum analyzers of their environments. Here we solve the problem of nonlinear spectral analysis, required for discrete noise induced by a strongly coupled environment. Our nonperturbative analytical model shows a nonlinear signal dependence on noise power, resulting in a spectral resolution beyond the Fourier limit as well as frequency mixing. We develop a noise characterization scheme adapted to this nonlinearity. We then apply it using a single trapped ion as a sensitive probe of strong, non-Gaussian, discrete magnetic field noise. Finally, we experimentally compared the performance of equidistant vs Uhrig modulation schemes for spectral analysis.

Proton exchange membrane fuel cell diagnosis by spectral characterization of the electrochemical noise

NASA Astrophysics Data System (ADS)

Maizia, R.; Dib, A.; Thomas, A.; Martemianov, S.

2017-02-01

Electrochemical noise analysis (ENA) has been performed for the diagnosis of proton-exchange membrane fuel cell (PEMFC) under various operating conditions. Its interest is related with the possibility of a non-invasive on-line diagnosis of a commercial fuel cell. A methodology of spectral analysis has been developed and an evaluation of the stationarity of the signal has been proposed. It has been revealed that the spectral signature of fuel cell, is a linear slope with a fractional power dependence 1/fα where α = 2 for different relative humidities and current densities. Experimental results reveal that the electrochemical noise is sensitive to the water management, especially under dry conditions. At RHH2 = 20% and RHair = 20%, spectral analysis shows a three linear slopes signature on the spectrum at low frequency range (f < 100 Hz). This results indicates that power spectral density, calculated thanks to FFT, can be used for the detection of an incorrect fuel cell water balance.

Spectral analysis of sinus arrhythmia - A measure of mental effort

NASA Technical Reports Server (NTRS)

Vicente, Kim J.; Craig Thornton, D.; Moray, Neville

1987-01-01

The validity of the spectral analysis of sinus arrhythmia as a measure of mental effort was investigated using a computer simulation of a hovercraft piloted along a river as the experimental task. Strong correlation was observed between the subjective effort-ratings and the heart-rate variability (HRV) power spectrum between 0.06 and 0.14 Hz. Significant correlations were observed not only between subjects but, more importantly, within subjects as well, indicating that the spectral analysis of HRV is an accurate measure of the amount of effort being invested by a subject. Results also indicate that the intensity of effort invested by subjects cannot be inferred from the objective ratings of task difficulty or from performance.

Synthesis and spectral characterization of hydrazone derivative of furfural using experimental and DFT methods.

PubMed

Babu, N Ramesh; Subashchandrabose, S; Ali Padusha, M Syed; Saleem, H; Erdoğdu, Y

2014-01-01

The Spectral Characterization of (E)-1-(Furan-2-yl) methylene)-2-(1-phenylvinyl) hydrazine (FMPVH) were carried out by using FT-IR, FT-Raman and UV-Vis., Spectrometry. The B3LYP/6-311++G(d,p) level of optimization has been performed on the title compound. The conformational analysis was performed for this molecule, in which the cis and trans conformers were studied for spectral characterization. The recorded spectral results were compared with calculated results. The optimized bond parameters of FMPVH molecule was compared with X-ray diffraction data of related molecule. To study the intra-molecular charge transfers within the molecule the Lewis (bonding) and Non-Lewis (anti-bonding) structural calculation was performed. The Non-linear optical behavior of the title compound was measured using first order hyperpolarizability calculation. The atomic charges were calculated and analyzed. Copyright © 2013 Elsevier B.V. All rights reserved.

Distinguishability of stacks in ZnTe/ZnSe quantum dots via spectral analysis of Aharonov-Bohm oscillations

NASA Astrophysics Data System (ADS)

Roy, Bidisha; Ji, Haojie; Dhomkar, Siddharth; Cadieu, Fred J.; Peng, Le; Moug, Richard; Tamargo, Maria C.; Kuskovsky, Igor L.

2013-02-01

A spectral analysis of the Aharonov-Bohm (AB) oscillations in photoluminescence intensity was performed for stacked type-II ZnTe/ZnSe quantum dots (QDs) fabricated within multilayered Zn-Se-Te system with sub-monolayer insertions of Te. Robust AB oscillations allowed for fine probing of distinguishable QDs stacks within the ensemble of QDs. The AB transition magnetic field, B AB , changed from the lower energy side to the higher energy side of the PL spectra revealing the presence of different sets of QDs stacks. The change occurs within the spectral range, where the contributing green and blue bands of the spectra overlapped. "Bundling" in lifetime measurements is seen at transition spectral regions confirming the results.

A review of materials for spectral design coatings in signature management applications

NASA Astrophysics Data System (ADS)

Andersson, Kent E.; Škerlind, Christina

2014-10-01

The current focus in Swedish policy towards national security and high-end technical systems, together with a rapid development in multispectral sensor technology, adds to the utility of developing advanced materials for spectral design in signature management applications. A literature study was performed probing research databases for advancements. Qualitative text analysis was performed using a six-indicator instrument: spectrally selective reflectance; low gloss; low degree of polarization; low infrared emissivity; non-destructive properties in radar and in general controllability of optical properties. Trends are identified and the most interesting materials and coating designs are presented with relevant performance metrics. They are sorted into categories in the order of increasing complexity: pigments and paints, one-dimensional structures, multidimensional structures (including photonic crystals), and lastly biomimic and metamaterials. The military utility of the coatings is assessed qualitatively. The need for developing a framework for assessing the military utility of incrementally increasing the performance of spectrally selective coatings is identified.

Thermal control design of the Lightning Mapper Sensor narrow-band spectral filter

NASA Technical Reports Server (NTRS)

Flannery, Martin R.; Potter, John; Raab, Jeff R.; Manlief, Scott K.

1992-01-01

The performance of the Lightning Mapper Sensor is dependent on the temperature shifts of its narrowband spectral filter. To perform over a 10 degree FOV with an 0.8 nm bandwidth, the filter must be 15 cm in diameter and mounted externally to the telescope optics. The filter thermal control required a filter design optimized for minimum bandpass shift with temperature, a thermal analysis of substrate materials for maximum temperature uniformity, and a thermal radiation analysis to determine the parameter sensitivity of the radiation shield for the filter, the filter thermal recovery time after occultation, and heater power to maintain filter performance in the earth-staring geosynchronous environment.

Trade-off studies of a hyperspectral infrared sounder on a geostationary satellite.

PubMed

Wang, Fang; Li, Jun; Schmit, Timothy J; Ackerman, Steven A

2007-01-10

Trade-off studies on spectral coverage, signal-to-noise ratio (SNR), and spectral resolution for a hyperspectral infrared (IR) sounder on a geostationary satellite are summarized. The data density method is applied for the vertical resolution analysis, and the rms error between true and retrieved profiles is used to represent the retrieval accuracy. The effects of spectral coverage, SNR, and spectral resolution on vertical resolution and retrieval accuracy are investigated. The advantages of IR and microwave sounder synergy are also demonstrated. When focusing on instrument performance and data processing, the results from this study show that the preferred spectral coverage combines long-wave infrared (LWIR) with the shorter middle-wave IR (SMidW). Using the appropriate spectral coverage, a hyperspectral IR sounder with appropriate SNR can achieve the required science performance (1 km vertical resolution, 1 K temperature, and 10% relative humidity retrieval accuracy). The synergy of microwave and IR sounders can improve the vertical resolution and retrieval accuracy compared to either instrument alone.

Marker-Based Hierarchical Segmentation and Classification Approach for Hyperspectral Imagery

NASA Technical Reports Server (NTRS)

Tarabalka, Yuliya; Tilton, James C.; Benediktsson, Jon Atli; Chanussot, Jocelyn

2011-01-01

The Hierarchical SEGmentation (HSEG) algorithm, which is a combination of hierarchical step-wise optimization and spectral clustering, has given good performances for hyperspectral image analysis. This technique produces at its output a hierarchical set of image segmentations. The automated selection of a single segmentation level is often necessary. We propose and investigate the use of automatically selected markers for this purpose. In this paper, a novel Marker-based HSEG (M-HSEG) method for spectral-spatial classification of hyperspectral images is proposed. First, pixelwise classification is performed and the most reliably classified pixels are selected as markers, with the corresponding class labels. Then, a novel constrained marker-based HSEG algorithm is applied, resulting in a spectral-spatial classification map. The experimental results show that the proposed approach yields accurate segmentation and classification maps, and thus is attractive for hyperspectral image analysis.

An MS-DOS-based program for analyzing plutonium gamma-ray spectra

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

Ruhter, W.D.; Buckley, W.M.

1989-09-07

A plutonium gamma-ray analysis system that operates on MS-DOS-based computers has been developed for the International Atomic Energy Agency (IAEA) to perform in-field analysis of plutonium gamma-ray spectra for plutonium isotopics. The program titled IAEAPU consists of three separate applications: a data-transfer application for transferring spectral data from a CICERO multichannel analyzer to a binary data file, a data-analysis application to analyze plutonium gamma-ray spectra, for plutonium isotopic ratios and weight percents of total plutonium, and a data-quality assurance application to check spectral data for proper data-acquisition setup and performance. Volume 3 contains the software listings for these applications.

Suomi NPP VIIRS spectral characterization: understanding multiple RSR releases

NASA Astrophysics Data System (ADS)

Moeller, Chris; McIntire, Jeff; Schwarting, Tom; Moyer, Dave; Costa, Juliette

2012-09-01

The Suomi National Polar-orbiting Partnership (S-NPP) satellite was successfully launched on October 28, 2011, beginning the on-orbit era of the Visible Infrared Imager Radiometer Suite (VIIRS). In support of atlaunch readiness, VIIRS underwent a rigorous pre-launch test program to characterize its spatial, radiometric, and spectral performance. Spectral measurements, the subject of this paper, were collected during instrument level testing at Raytheon Corp. (summer 2009), and then again in a special spectral test for VisNIR bands during spacecraft level testing at Ball Aerospace and Technologies Corp. (spring 2010). These spectral performance measurements were analyzed by industry (Northrop Grumman, NG) and by the Relative Spectral Response (RSR) subgroup of the Government team, (NASA, Aerospace Corp., MIT/Lincoln Lab, Univ. Wisconsin) leading to releases of the S-NPP VIIRS RSR characterization by both NG and the Government team. The NG RSR analysis was planned to populate the Look-Up-Tables (LUTs) that support the various VIIRS operational products, while the Government team analysis was initially intended as a verification of the NG RSR product as well as an early release RSR characterization for the science community's pre-launch application. While the Government team deemed the NG December 2010 RSR release as acceptable for the "at-launch" RSR characterization during the pre-launch phase, the Government team has now (post-launch checkout phase) recommended for using the NG October 2011 RSR release as an update for the LUTs used in VIIRS SDR and EDR operational processing. Meanwhile the Government team RSR releases remain available to the community for their investigative interests, and may evolve if new understanding of VIIRS spectral performance is revealed in the S-NPP post-launch era.

A graphical method to evaluate spectral preprocessing in multivariate regression calibrations: example with Savitzky-Golay filters and partial least squares regression

USDA-ARS?s Scientific Manuscript database

In multivariate regression analysis of spectroscopy data, spectral preprocessing is often performed to reduce unwanted background information (offsets, sloped baselines) or accentuate absorption features in intrinsically overlapping bands. These procedures, also known as pretreatments, are commonly ...

Effects of Salinity on Leaf Spectral Reflectance and Biochemical Parameters of Nitrogen Fixing Soybean Plants (Glycine max L.)

NASA Astrophysics Data System (ADS)

Krezhova, Dora D.; Kirova, Elisaveta B.; Yanev, Tony K.; Iliev, Ilko Ts.

2010-01-01

Measurements of physiology and hyperspectral leaf reflectance were used to detect salinity stress in nitrogen fixing soybean plants. Seedlings were inoculated with suspension of Bradyrhizobium japonicum strain 273. Salinity was performed at the stage of 2nd-4th trifoliate expanded leaves by adding of NaCl in the nutrient solution of Helrigel in concentrations 40 mM and 80 mM. A comparative analysis was performed between the changes in the biochemical parameters - stress markers (phenols, proline, malondialdehyde, thiol groups), chlorophyll a and b, hydrogen peroxide, and leaf spectral reflectance in the spectral range 450-850 nm. The spectral measurements were carried out by an USB2000 spectrometer. The reflectance data of the control and treated plants in the red, green, red-edge and the near infrared ranges of the spectrum were subjected to statistical analysis. Statistically significant differences were found through the Student's t-criterion at the two NaCl concentrations in all of the ranges examined with the exception of the near infrared range at 40 mM NaCl concentration. Similar results were obtained through linear discriminant analysis. The tents of the phenols, malondialdehyde and chlorophyll a and b were found to decrease at both salinity treatments. In the spectral data this effect is manifested by decrease of the reflectance values in the green and red ranges. The contents of proline, hydrogen peroxide and thiol groups rose with the NaCl concentration increase. At 80 mM NaCl concentration the values of these markers showed a considerable increase giving evidence that the soybean plants were stressed in comparison with the control. This finding is in agreement with the results from the spectral reflectance analysis.

Ratiometric spectral imaging for fast tumor detection and chemotherapy monitoring in vivo

PubMed Central

Hwang, Jae Youn; Gross, Zeev; Gray, Harry B.; Medina-Kauwe, Lali K.; Farkas, Daniel L.

2011-01-01

We report a novel in vivo spectral imaging approach to cancer detection and chemotherapy assessment. We describe and characterize a ratiometric spectral imaging and analysis method and evaluate its performance for tumor detection and delineation by quantitatively monitoring the specific accumulation of targeted gallium corrole (HerGa) into HER2-positive (HER2 +) breast tumors. HerGa temporal accumulation in nude mice bearing HER2 + breast tumors was monitored comparatively by a. this new ratiometric imaging and analysis method; b. established (reflectance and fluorescence) spectral imaging; c. more commonly used fluorescence intensity imaging. We also tested the feasibility of HerGa imaging in vivo using the ratiometric spectral imaging method for tumor detection and delineation. Our results show that the new method not only provides better quantitative information than typical spectral imaging, but also better specificity than standard fluorescence intensity imaging, thus allowing enhanced in vivo outlining of tumors and dynamic, quantitative monitoring of targeted chemotherapy agent accumulation into them. PMID:21721808

Spectral imaging as a potential tool for optical sentinel lymph node biopsies

NASA Astrophysics Data System (ADS)

O'Sullivan, Jack D.; Hoy, Paul R.; Rutt, Harvey N.

2011-07-01

Sentinel Lymph Node Biopsy (SLNB) is an increasingly standard procedure to help oncologists accurately stage cancers. It is performed as an alternative to full axillary lymph node dissection in breast cancer patients, reducing the risk of longterm health problems associated with lymph node removal. Intraoperative analysis is currently performed using touchprint cytology, which can introduce significant delay into the procedure. Spectral imaging is forming a multi-plane image where reflected intensities from a number of spectral bands are recorded at each pixel in the spatial plane. We investigate the possibility of using spectral imaging to assess sentinel lymph nodes of breast cancer patients with a view to eventually developing an optical technique that could significantly reduce the time required to perform this procedure. We investigate previously reported spectra of normal and metastatic tissue in the visible and near infrared region, using them as the basis of dummy spectral images. We analyse these images using the spectral angle map (SAM), a tool routinely used in other fields where spectral imaging is prevalent. We simulate random noise in these images in order to determine whether the SAM can discriminate between normal and metastatic pixels as the quality of the images deteriorates. We show that even in cases where noise levels are up to 20% of the maximum signal, the spectral angle map can distinguish healthy pixels from metastatic. We believe that this makes spectral imaging a good candidate for further study in the development of an optical SLNB.

Transitions in effective scaling behavior of accelerometric time series across sleep and wake

NASA Astrophysics Data System (ADS)

Wohlfahrt, Patrick; Kantelhardt, Jan W.; Zinkhan, Melanie; Schumann, Aicko Y.; Penzel, Thomas; Fietze, Ingo; Pillmann, Frank; Stang, Andreas

2013-09-01

We study the effective scaling behavior of high-resolution accelerometric time series recorded at the wrists and hips of 100 subjects during sleep and wake. Using spectral analysis and detrended fluctuation analysis we find long-term correlated fluctuations with a spectral exponent \\beta \\approx 1.0 (1/f noise). On short time scales, β is larger during wake (\\approx 1.4 ) and smaller during sleep (\\approx 0.6 ). In addition, characteristic peaks at 0.2-0.3 Hz (due to respiration) and 4-10 Hz (probably due to physiological tremor) are observed in periods of weak activity. Because of these peaks, spectral analysis is superior in characterizing effective scaling during sleep, while detrending analysis performs well during wake. Our findings can be exploited to detect sleep-wake transitions.

Spectral contents readout of birefringent sensor

NASA Technical Reports Server (NTRS)

Redner, Alex S.

1989-01-01

The technical objective of this research program was to develop a birefringent sensor, capable of measuring strain/stress up to 2000 F and a readout system based on Spectral Contents analysis. As a result of the research work, a data acquisition system was developed, capable of measuring strain birefringence in a sensor at 2000 F, with multi-point static and dynamic capabilities. The system uses a dedicated spectral analyzer for evaluation of stress-birefringence and a PC-based readout. Several sensor methods were evaluated. Fused silica was found most satisfactory. In the final evaluation, measurements were performed up to 2000 F and the system performance exceeded expectations.

Scintillation index and performance analysis of wireless optical links over non-Kolmogorov weak turbulence based on generalized atmospheric spectral model.

PubMed

Cang, Ji; Liu, Xu

2011-09-26

Based on the generalized spectral model for non-Kolmogorov atmospheric turbulence, analytic expressions of the scintillation index (SI) are derived for plane, spherical optical waves and a partially coherent Gaussian beam propagating through non-Kolmogorov turbulence horizontally in the weak fluctuation regime. The new expressions relate the SI to the finite turbulence inner and outer scales, spatial coherence of the source and spectral power-law and then used to analyze the effects of atmospheric condition and link length on the performance of wireless optical communication links. © 2011 Optical Society of America

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.

Development of seismic fragility curves for low-rise masonry infilled reinforced concrete buildings by a coefficient-based method

NASA Astrophysics Data System (ADS)

Su, Ray Kai Leung; Lee, Chien-Liang

2013-06-01

This study presents a seismic fragility analysis and ultimate spectral displacement assessment of regular low-rise masonry infilled (MI) reinforced concrete (RC) buildings using a coefficient-based method. The coefficient-based method does not require a complicated finite element analysis; instead, it is a simplified procedure for assessing the spectral acceleration and displacement of buildings subjected to earthquakes. A regression analysis was first performed to obtain the best-fitting equations for the inter-story drift ratio (IDR) and period shift factor of low-rise MI RC buildings in response to the peak ground acceleration of earthquakes using published results obtained from shaking table tests. Both spectral acceleration- and spectral displacement-based fragility curves under various damage states (in terms of IDR) were then constructed using the coefficient-based method. Finally, the spectral displacements of low-rise MI RC buildings at the ultimate (or nearcollapse) state obtained from this paper and the literature were compared. The simulation results indicate that the fragility curves obtained from this study and other previous work correspond well. Furthermore, most of the spectral displacements of low-rise MI RC buildings at the ultimate state from the literature fall within the bounded spectral displacements predicted by the coefficient-based method.

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

NASA Astrophysics Data System (ADS)

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

2010-08-01

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

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

PubMed

Speier, William; Fried, Itzhak; Pouratian, Nader

2013-07-01

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

An Excel-based implementation of the spectral method of action potential alternans analysis.

PubMed

Pearman, Charles M

2014-12-01

Action potential (AP) alternans has been well established as a mechanism of arrhythmogenesis and sudden cardiac death. Proper interpretation of AP alternans requires a robust method of alternans quantification. Traditional methods of alternans analysis neglect higher order periodicities that may have greater pro-arrhythmic potential than classical 2:1 alternans. The spectral method of alternans analysis, already widely used in the related study of microvolt T-wave alternans, has also been used to study AP alternans. Software to meet the specific needs of AP alternans analysis is not currently available in the public domain. An AP analysis tool is implemented here, written in Visual Basic for Applications and using Microsoft Excel as a shell. This performs a sophisticated analysis of alternans behavior allowing reliable distinction of alternans from random fluctuations, quantification of alternans magnitude, and identification of which phases of the AP are most affected. In addition, the spectral method has been adapted to allow detection and quantification of higher order regular oscillations. Analysis of action potential morphology is also performed. A simple user interface enables easy import, analysis, and export of collated results. © 2014 The Author. Physiological Reports published by Wiley Periodicals, Inc. on behalf of the American Physiological Society and The Physiological Society.

Spectral analysis of the Crab Nebula and GRB 160530A with the Compton Spectrometer and Imager

NASA Astrophysics Data System (ADS)

Sleator, Clio; Boggs, Steven E.; Chiu, Jeng-Lun; Kierans, Carolyn; Lowell, Alexander; Tomsick, John; Zoglauer, Andreas; Amman, Mark; Chang, Hsiang-Kuang; Tseng, Chao-Hsiung; Yang, Chien-Ying; Lin, Chih H.; Jean, Pierre; von Ballmoos, Peter

2017-08-01

The Compton Spectrometer and Imager (COSI) is a balloon-borne soft gamma-ray (0.2-5 MeV) telescope designed to study astrophysical sources including gamma-ray bursts and compact objects. As a compact Compton telescope, COSI has inherent sensitivity to polarization. COSI utilizes 12 germanium detectors to provide excellent spectral resolution. On May 17, 2016, COSI was launched from Wanaka, New Zealand and completed a successful 46-day flight on NASA’s new Superpressure balloon. To perform spectral analysis with COSI, we have developed an accurate instrument model as required for the response matrix. With carefully chosen background regions, we are able to fit the background-subtracted spectra in XSPEC. We have developed a model of the atmosphere above COSI based on the NRLMSISE-00 Atmosphere Model to include in our spectral fits. The Crab and GRB 160530A are among the sources detected during the 2016 flight. We present spectral analysis of these two point sources. Our GRB 160530A results are consistent with those from other instruments, confirming COSI’s spectral abilities. Furthermore, we discuss prospects for measuring the Crab polarization with COSI.

Easily extensible unix software for spectral analysis, display, modification, and synthesis of musical sounds

NASA Astrophysics Data System (ADS)

Beauchamp, James W.

2002-11-01

Software has been developed which enables users to perform time-varying spectral analysis of individual musical tones or successions of them and to perform further processing of the data. The package, called sndan, is freely available in source code, uses EPS graphics for display, and is written in ansi c for ease of code modification and extension. Two analyzers, a fixed-filter-bank phase vocoder (''pvan'') and a frequency-tracking analyzer (''mqan'') constitute the analysis front end of the package. While pvan's output consists of continuous amplitudes and frequencies of harmonics, mqan produces disjoint ''tracks.'' However, another program extracts a fundamental frequency and separates harmonics from the tracks, resulting in a continuous harmonic output. ''monan'' is a program used to display harmonic data in a variety of formats, perform various spectral modifications, and perform additive resynthesis of the harmonic partials, including possible pitch-shifting and time-scaling. Sounds can also be synthesized according to a musical score using a companion synthesis language, Music 4C. Several other programs in the sndan suite can be used for specialized tasks, such as signal display and editing. Applications of the software include producing specialized sounds for music compositions or psychoacoustic experiments or as a basis for developing new synthesis algorithms.

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.

Harmonic component detection: Optimized Spectral Kurtosis for operational modal analysis

NASA Astrophysics Data System (ADS)

Dion, J.-L.; Tawfiq, I.; Chevallier, G.

2012-01-01

This work is a contribution in the field of Operational Modal Analysis to identify the modal parameters of mechanical structures using only measured responses. The study deals with structural responses coupled with harmonic components amplitude and frequency modulated in a short range, a common combination for mechanical systems with engines and other rotating machines in operation. These harmonic components generate misleading data interpreted erroneously by the classical methods used in OMA. The present work attempts to differentiate maxima in spectra stemming from harmonic components and structural modes. The detection method proposed is based on the so-called Optimized Spectral Kurtosis and compared with others definitions of Spectral Kurtosis described in the literature. After a parametric study of the method, a critical study is performed on numerical simulations and then on an experimental structure in operation in order to assess the method's performance.

Atmospheric Properties Of T Dwarfs Inferred From Model Fits At Low Spectral Resolution

NASA Astrophysics Data System (ADS)

Giorla Godfrey, Paige A.; Rice, Emily L.; Filippazzo, Joseph C.; Douglas, Stephanie E.

2016-09-01

Brown dwarf spectral types (M, L, T, Y) correlate with spectral morphology, and generally appear to correspond with decreasing mass and effective temperature (Teff). Model fits to observed spectra suggest, however, that spectral subclasses do not share this monotonic temperature correlation, indicating that secondary parameters (gravity, metallicity, dust) significantly influence spectral morphology. We seekto disentangle the fundamental parameters that underlie the spectral type sequence of the coolest fully populated spectral class of brown dwarfs using atmosphere models. We investigate the relationship between spectral type and best fit model parameters for a sample of over 150 T dwarfs with low resolution (R 75-100) near-infrared ( 0.8-2.5 micron) SpeX Prism spectra. We use synthetic spectra from four model grids (Saumon & Marley 2008, Morley+ 2012, Saumon+ 2012, BT Settl 2013) and a Markov-Chain Monte Carlo (MCMC) analysis to determine robust best fit parameters and their uncertainties. We compare the consistency of each model grid by performing our analysis on the full spectrum and also on individual wavelength bands (Y,J,H,K). We find more consistent results between the J band and full spectrum fits and that our best fit spectral type-Teff results agree with the polynomial relationships of Stephens+2009 and Filippazzo+ 2015 using bolometric luminosities. Our analysis consists of the most extensive low resolution T dwarf model comparison to date, and lays the foundation for interpretation of cool brown dwarf and exoplanet spectra.

A spectral analysis of the domain decomposed Monte Carlo method for linear systems

DOE PAGES

Slattery, Stuart R.; Evans, Thomas M.; Wilson, Paul P. H.

2015-09-08

The domain decomposed behavior of the adjoint Neumann-Ulam Monte Carlo method for solving linear systems is analyzed using the spectral properties of the linear oper- ator. Relationships for the average length of the adjoint random walks, a measure of convergence speed and serial performance, are made with respect to the eigenvalues of the linear operator. In addition, relationships for the effective optical thickness of a domain in the decomposition are presented based on the spectral analysis and diffusion theory. Using the effective optical thickness, the Wigner rational approxi- mation and the mean chord approximation are applied to estimate the leakagemore » frac- tion of random walks from a domain in the decomposition as a measure of parallel performance and potential communication costs. The one-speed, two-dimensional neutron diffusion equation is used as a model problem in numerical experiments to test the models for symmetric operators with spectral qualities similar to light water reactor problems. We find, in general, the derived approximations show good agreement with random walk lengths and leakage fractions computed by the numerical experiments.« less

A hybrid spatial-spectral denoising method for infrared hyperspectral images using 2DPCA

NASA Astrophysics Data System (ADS)

Huang, Jun; Ma, Yong; Mei, Xiaoguang; Fan, Fan

2016-11-01

The traditional noise reduction methods for 3-D infrared hyperspectral images typically operate independently in either the spatial or spectral domain, and such methods overlook the relationship between the two domains. To address this issue, we propose a hybrid spatial-spectral method in this paper to link both domains. First, principal component analysis and bivariate wavelet shrinkage are performed in the 2-D spatial domain. Second, 2-D principal component analysis transformation is conducted in the 1-D spectral domain to separate the basic components from detail ones. The energy distribution of noise is unaffected by orthogonal transformation; therefore, the signal-to-noise ratio of each component is used as a criterion to determine whether a component should be protected from over-denoising or denoised with certain 1-D denoising methods. This study implements the 1-D wavelet shrinking threshold method based on Stein's unbiased risk estimator, and the quantitative results on publicly available datasets demonstrate that our method can improve denoising performance more effectively than other state-of-the-art methods can.

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.

Systems and methods for detection of blowout precursors in combustors

DOEpatents

Lieuwen, Tim C.; Nair, Suraj

2006-08-15

The present invention comprises systems and methods for detecting flame blowout precursors in combustors. The blowout precursor detection system comprises a combustor, a pressure measuring device, and blowout precursor detection unit. A combustion controller may also be used to control combustor parameters. The methods of the present invention comprise receiving pressure data measured by an acoustic pressure measuring device, performing one or a combination of spectral analysis, statistical analysis, and wavelet analysis on received pressure data, and determining the existence of a blowout precursor based on such analyses. The spectral analysis, statistical analysis, and wavelet analysis further comprise their respective sub-methods to determine the existence of blowout precursors.

RXTE Observations of A1744-361: Correlated Spectral and Timing Behavior

NASA Technical Reports Server (NTRS)

Bhattacharyya, Sudip; Strohmayer, Tod E.; Swank, Jean H.; Markwardt, Craig B.

2007-01-01

We analyze Rossi X-ray Timing Explorer (RXTE) Proportional Counter Array (PCA) data of the transient low mass X-ray binary (LMXB) system A1744-361. We explore the X-ray intensity and spectral evolution of the source, perform timing analysis, and find that A1744-361 is a weak LMXB, that shows atoll behavior at high intensity states. The color-color diagram indicates that this LMXB was observed in a low intensity spectrally hard (low-hard) state and in a high intensity banana state. The low-hard state shows a horizontal pattern in the color-color diagram, and the previously reported dipper QPO appears only during this state. We also perform energy spectral analyses, and report the first detection of broad iron emission line and iron absorption edge from A1744-361.

Spectral line polarimetry with a channeled polarimeter.

PubMed

van Harten, Gerard; Snik, Frans; Rietjens, Jeroen H H; Martijn Smit, J; Keller, Christoph U

2014-07-01

Channeled spectropolarimetry or spectral polarization modulation is an accurate technique for measuring the continuum polarization in one shot with no moving parts. We show how a dual-beam implementation also enables spectral line polarimetry at the intrinsic resolution, as in a classic beam-splitting polarimeter. Recording redundant polarization information in the two spectrally modulated beams of a polarizing beam-splitter even provides the possibility to perform a postfacto differential transmission correction that improves the accuracy of the spectral line polarimetry. We perform an error analysis to compare the accuracy of spectral line polarimetry to continuum polarimetry, degraded by a residual dark signal and differential transmission, as well as to quantify the impact of the transmission correction. We demonstrate the new techniques with a blue sky polarization measurement around the oxygen A absorption band using the groundSPEX instrument, yielding a polarization in the deepest part of the band of 0.160±0.010, significantly different from the polarization in the continuum of 0.2284±0.0004. The presented methods are applicable to any dual-beam channeled polarimeter, including implementations for snapshot imaging polarimetry.

Novel full-spectral flow cytometry with multiple spectrally-adjacent fluorescent proteins and fluorochromes and visualization of in vivo cellular movement.

PubMed

Futamura, Koji; Sekino, Masashi; Hata, Akihiro; Ikebuchi, Ryoyo; Nakanishi, Yasutaka; Egawa, Gyohei; Kabashima, Kenji; Watanabe, Takeshi; Furuki, Motohiro; Tomura, Michio

2015-09-01

Flow cytometric analysis with multicolor fluoroprobes is an essential method for detecting biological signatures of cells. Here, we present a new full-spectral flow cytometer (spectral-FCM). Unlike conventional flow cytometer, this spectral-FCM acquires the emitted fluorescence for all probes across the full-spectrum from each cell with 32 channels sequential PMT unit after dispersion with prism, and extracts the signals of each fluoroprobe based on the spectral shape of each fluoroprobe using unique algorithm in high speed, high sensitive, accurate, automatic and real-time. The spectral-FCM detects the continuous changes in emission spectra from green to red of the photoconvertible protein, KikGR with high-spectral resolution and separates spectrally-adjacent fluoroprobes, such as FITC (Emission peak (Em) 519 nm) and EGFP (Em 507 nm). Moreover, the spectral-FCM can measure and subtract autofluorescence of each cell providing increased signal-to-noise ratios and improved resolution of dim samples, which leads to a transformative technology for investigation of single cell state and function. These advances make it possible to perform 11-color fluorescence analysis to visualize movement of multilinage immune cells by using KikGR-expressing mice. Thus, the novel spectral flow cytometry improves the combinational use of spectrally-adjacent various FPs and multicolor fluorochromes in metabolically active cell for the investigation of not only the immune system but also other research and clinical fields of use. © 2015 International Society for Advancement of Cytometry.

Gas and dust spectral analysis of galactic and extragalactic symbiotic stars

NASA Astrophysics Data System (ADS)

Angeloni, Rodolfo

2009-02-01

Symbiotic stars are recognized as unique laboratories for studying a large variety of phenomena that are relevant to a number of important astro-physical problems. This PhD thesis deals with a spectral analysis of galactic and extragalactic symbiotic stars. The former are mainly D-type symbiotic stars for which a comprehensive study, from radio to X-ray spectral region, has been performed. With the latter, we refer to symbiotic stars in the Magellanic Clouds, to be analyzed mainly in the IR range. The common theoretical scenario that lies in the background of this work is the colliding-wind model, developed already during the 80's, supported by first observational evidence at the beginning of 90's (mainly thanks to Nussbaumer and collaborators), and finally completed with detailed and powerful hydrodynamical simulations by various authors in these recent years. In the light of this scenario, we have tried to interpret gas and dust spectra of our targets in a unique and self-consistent way. The spectral analysis has been performed by means of the numerical code SUMA, developed at the Instituto Astronomico e Geofisico of the University of Sao Paulo by Sueli M. Viegas (Aldrovandi) and Marcella Contini from the School of Physics and Astronomy of the Tel-Aviv University.

Improvements to an earth observing statistical performance model with applications to LWIR spectral variability

NASA Astrophysics Data System (ADS)

Zhao, Runchen; Ientilucci, Emmett J.

2017-05-01

Hyperspectral remote sensing systems provide spectral data composed of hundreds of narrow spectral bands. Spectral remote sensing systems can be used to identify targets, for example, without physical interaction. Often it is of interested to characterize the spectral variability of targets or objects. The purpose of this paper is to identify and characterize the LWIR spectral variability of targets based on an improved earth observing statistical performance model, known as the Forecasting and Analysis of Spectroradiometric System Performance (FASSP) model. FASSP contains three basic modules including a scene model, sensor model and a processing model. Instead of using mean surface reflectance only as input to the model, FASSP transfers user defined statistical characteristics of a scene through the image chain (i.e., from source to sensor). The radiative transfer model, MODTRAN, is used to simulate the radiative transfer based on user defined atmospheric parameters. To retrieve class emissivity and temperature statistics, or temperature / emissivity separation (TES), a LWIR atmospheric compensation method is necessary. The FASSP model has a method to transform statistics in the visible (ie., ELM) but currently does not have LWIR TES algorithm in place. This paper addresses the implementation of such a TES algorithm and its associated transformation of statistics.

Plant leaf chlorophyll content retrieval based on a field imaging spectroscopy system.

PubMed

Liu, Bo; Yue, Yue-Min; Li, Ru; Shen, Wen-Jing; Wang, Ke-Lin

2014-10-23

A field imaging spectrometer system (FISS; 380-870 nm and 344 bands) was designed for agriculture applications. In this study, FISS was used to gather spectral information from soybean leaves. The chlorophyll content was retrieved using a multiple linear regression (MLR), partial least squares (PLS) regression and support vector machine (SVM) regression. Our objective was to verify the performance of FISS in a quantitative spectral analysis through the estimation of chlorophyll content and to determine a proper quantitative spectral analysis method for processing FISS data. The results revealed that the derivative reflectance was a more sensitive indicator of chlorophyll content and could extract content information more efficiently than the spectral reflectance, which is more significant for FISS data compared to ASD (analytical spectral devices) data, reducing the corresponding RMSE (root mean squared error) by 3.3%-35.6%. Compared with the spectral features, the regression methods had smaller effects on the retrieval accuracy. A multivariate linear model could be the ideal model to retrieve chlorophyll information with a small number of significant wavelengths used. The smallest RMSE of the chlorophyll content retrieved using FISS data was 0.201 mg/g, a relative reduction of more than 30% compared with the RMSE based on a non-imaging ASD spectrometer, which represents a high estimation accuracy compared with the mean chlorophyll content of the sampled leaves (4.05 mg/g). Our study indicates that FISS could obtain both spectral and spatial detailed information of high quality. Its image-spectrum-in-one merit promotes the good performance of FISS in quantitative spectral analyses, and it can potentially be widely used in the agricultural sector.

Plant Leaf Chlorophyll Content Retrieval Based on a Field Imaging Spectroscopy System

PubMed Central

Liu, Bo; Yue, Yue-Min; Li, Ru; Shen, Wen-Jing; Wang, Ke-Lin

2014-01-01

A field imaging spectrometer system (FISS; 380–870 nm and 344 bands) was designed for agriculture applications. In this study, FISS was used to gather spectral information from soybean leaves. The chlorophyll content was retrieved using a multiple linear regression (MLR), partial least squares (PLS) regression and support vector machine (SVM) regression. Our objective was to verify the performance of FISS in a quantitative spectral analysis through the estimation of chlorophyll content and to determine a proper quantitative spectral analysis method for processing FISS data. The results revealed that the derivative reflectance was a more sensitive indicator of chlorophyll content and could extract content information more efficiently than the spectral reflectance, which is more significant for FISS data compared to ASD (analytical spectral devices) data, reducing the corresponding RMSE (root mean squared error) by 3.3%–35.6%. Compared with the spectral features, the regression methods had smaller effects on the retrieval accuracy. A multivariate linear model could be the ideal model to retrieve chlorophyll information with a small number of significant wavelengths used. The smallest RMSE of the chlorophyll content retrieved using FISS data was 0.201 mg/g, a relative reduction of more than 30% compared with the RMSE based on a non-imaging ASD spectrometer, which represents a high estimation accuracy compared with the mean chlorophyll content of the sampled leaves (4.05 mg/g). Our study indicates that FISS could obtain both spectral and spatial detailed information of high quality. Its image-spectrum-in-one merit promotes the good performance of FISS in quantitative spectral analyses, and it can potentially be widely used in the agricultural sector. PMID:25341439

Paleo-productivity changes revealed by spectral analysis performed on coccoliths assemblages

NASA Astrophysics Data System (ADS)

Palumbo, Eliana; Ornella Amore, Filomena; Perugia, Carmen

2010-05-01

Several climate changes occurred over geological time at different time-scales. Spectral analyses performed on paleo-climate data suggested that these cyclicities verify irregularly into time-space domain. Paleo-climate oscillations occur with high or low frequencies dues to the oscillation of the major orbital parameters (characterized by low frequencies and high period) and some minor high-frequencies events. During last years, analyses on frequencies domain have been performed also on coccoliths assemblages. Coccolithophores are a special phytoplankton group living today at all latitude regions within the photic zone (0-200 m of depth) (Winter & Siesser, 1994). They are sensitive indicators of environmental conditions because they directly depend on temperature, salinity and nutrients as well as the availability of sunlight (McIntyre and Bé, 1967; Giradeau et al., 1993; Winter & Siesser, 1994; Baumann & Freitag, 2004). Therefore coccolithophores quickly respond to fluctuations in climate as well as changes in surface-water conditions (Baumann & Freitag, 2004). Thus coccoliths can be clearly used as paleo-climate data because of their power of recordering and amplifying climatic change signals. In addition, primary productivity depends on the amount of insolation received by Earth surface. In this study Sun insolation has been calculated in terms of intensity and energy, in order to compare them with maximum productivity activity. Precession controls sun intensity insolation, while the energy is controlled by obliquity. Thus, the intensity depends on the duration of the insolation,while the energy is connected to the amount of insolation (Berger, 1978; Loutre et al., 2004; Huybers, 2006). In this study, spectral analyses have been performed on coccoliths data with the result of individuating high and low frequencies content in productivity signals. Auto-spectral and cross-spectral analyses have been performed through Matlab software using several available functions plus a new function created in order to evaluate cross-wavelet power spectra. Auto-spectral analysis aims to describe the distribution of variance contained in each single signal over frequency or wavelength, while cross-spectral analysis correlates two time series in the frequency domain (Trauth, 2009). We have performed spectral analyses using the complex Fourier transform and the Short time Fourier transform. Both the transforms lose any kind of time information in transforming the signal from time to frequency domain (Jenkins and Watt, 1968). These transforms don't allow us to individuate when an event occurred in the past. In order to overcome this limit we have also applied Wavelet analysis which represents frequency content of a signal over the time thus it allows us to visualize when an event occurred into time domain (Torrence and Compo, 1998; Prokoph and El Bilali, 2008; Grinsted et al., 2004). Moreover we have performed a simple cross and a cross-spectral analysis between different proxy groups to discover their possible correlations into time and frequency domains. References. Berger, A., 1978. J. Atmos. Sc., 35 (12): 2362-2367. Baumann, K.-H., and Freitag, T., 2004. Marine Micropaleontology 52: 195-215. Giraudeau, J., Monteiro, P.M.S., Nikodemus, K., 1993. Mar. Micropalaeontol. 22: 93- 110. Grinsted, A., Moore, J. C., and Jevrejeva, S., 2004. Nonlinear Processes in Geophysics 11: 561-566. Huybers, P., 2006. Science 313: 508-511. Jenkins, G. M., and Watt, D. G., 1968. Holden Day, pp. 410, Oakland. Loutre, M. F., Paillard, D., Vimeux, F., and Cortijo, E., 2004. Earth Planet. Sci. Lett., 221, 1-14. McIntyre, A., and Bè, A.H.W., 1967. Deep-Sea Res. 14, pp. 561-597. Prokoph, A., and El Bilali, H., 2008. Math Geosciences 40: 575-586. Torrence, C., and Compo, G. P., 1998. Bulletin of American Meteorological Society 79:61-78. Trauth, M.H., 2009. Springer 288 p. Winter, A., and Siesser, W., 1994. Cambridge University Press 242 p.

A solar radio dynamic spectrograph with flexible temporal-spectral resolution

NASA Astrophysics Data System (ADS)

Du, Qing-Fu; Chen, Lei; Zhao, Yue-Chang; Li, Xin; Zhou, Yan; Zhang, Jun-Rui; Yan, Fa-Bao; Feng, Shi-Wei; Li, Chuan-Yang; Chen, Yao

2017-09-01

Observation and research on solar radio emission have unique scientific values in solar and space physics and related space weather forecasting applications, since the observed spectral structures may carry important information about energetic electrons and underlying physical mechanisms. In this study, we present the design of a novel dynamic spectrograph that has been installed at the Chashan Solar Radio Observatory operated by the Laboratory for Radio Technologies, Institute of Space Sciences at Shandong University. The spectrograph is characterized by real-time storage of digitized radio intensity data in the time domain and its capability to perform off-line spectral analysis of the radio spectra. The analog signals received via antennas and amplified with a low-noise amplifier are converted into digital data at a speed reaching up to 32 k data points per millisecond. The digital data are then saved into a high-speed electronic disk for further off-line spectral analysis. Using different word lengths (1-32 k) and time cadences (5 ms-10 s) for off-line fast Fourier transform analysis, we can obtain the dynamic spectrum of a radio burst with different (user-defined) temporal (5 ms-10 s) and spectral (3 kHz˜320 kHz) resolutions. This enables great flexibility and convenience in data analysis of solar radio bursts, especially when some specific fine spectral structures are under study.

Standoff analysis of laser-produced plasmas using laser-induced fluorescence

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

Harilal, S. S.; Brumfield, B. E.; Phillips, M. C.

We report the use of laser-induced fluorescence (LIF) of laser ablation plumes for standoff applications. The standoff analysis of Al species, as major and minor species in samples, is performed in a nanosecond laser-produced plasma created at a distance ~10 m. The LIF analysis is performed by resonantly exciting an Al transition at 394.4 nm using a continuous wave (cw) tunable laser and by collecting the direct-line fluorescence signal at 396.15 nm. The spectral resolution of LIF is obtained by scanning the cw tunable LIF laser across the selected Al transition. Our results highlight that LIF provides enhanced signal intensity,more » emission persistence, and spectral resolution when compared to thermally-excited emission, and these are crucial considerations for using laser-produced plasma for standoff isotopic analysis.« less

Application of principal component regression and partial least squares regression in ultraviolet spectrum water quality detection

NASA Astrophysics Data System (ADS)

Li, Jiangtong; Luo, Yongdao; Dai, Honglin

2018-01-01

Water is the source of life and the essential foundation of all life. With the development of industrialization, the phenomenon of water pollution is becoming more and more frequent, which directly affects the survival and development of human. Water quality detection is one of the necessary measures to protect water resources. Ultraviolet (UV) spectral analysis is an important research method in the field of water quality detection, which partial least squares regression (PLSR) analysis method is becoming predominant technology, however, in some special cases, PLSR's analysis produce considerable errors. In order to solve this problem, the traditional principal component regression (PCR) analysis method was improved by using the principle of PLSR in this paper. The experimental results show that for some special experimental data set, improved PCR analysis method performance is better than PLSR. The PCR and PLSR is the focus of this paper. Firstly, the principal component analysis (PCA) is performed by MATLAB to reduce the dimensionality of the spectral data; on the basis of a large number of experiments, the optimized principal component is extracted by using the principle of PLSR, which carries most of the original data information. Secondly, the linear regression analysis of the principal component is carried out with statistic package for social science (SPSS), which the coefficients and relations of principal components can be obtained. Finally, calculating a same water spectral data set by PLSR and improved PCR, analyzing and comparing two results, improved PCR and PLSR is similar for most data, but improved PCR is better than PLSR for data near the detection limit. Both PLSR and improved PCR can be used in Ultraviolet spectral analysis of water, but for data near the detection limit, improved PCR's result better than PLSR.

Hyperspectral cytometry.

PubMed

Grégori, Gérald; Rajwa, Bartek; Patsekin, Valery; Jones, James; Furuki, Motohiro; Yamamoto, Masanobu; Paul Robinson, J

2014-01-01

Hyperspectral cytometry is an emerging technology for single-cell analysis that combines ultrafast optical spectroscopy and flow cytometry. Spectral cytometry systems utilize diffraction gratings or prism-based monochromators to disperse fluorescence signals from multiple labels (organic dyes, nanoparticles, or fluorescent proteins) present in each analyzed bioparticle onto linear detector arrays such as multianode photomultipliers or charge-coupled device sensors. The resultant data, consisting of a series of characterizing every analyzed cell, are not compensated by employing the traditional cytometry approach, but rather are spectrally unmixed utilizing algorithms such as constrained Poisson regression or non-negative matrix factorization. Although implementations of spectral cytometry were envisioned as early as the 1980s, only recently has the development of highly sensitive photomultiplier tube arrays led to design and construction of functional prototypes and subsequently to introduction of commercially available systems. This chapter summarizes the historical efforts and work in the field of spectral cytometry performed at Purdue University Cytometry Laboratories and describes the technology developed by Sony Corporation that resulted in release of the first commercial spectral cytometry system-the Sony SP6800. A brief introduction to spectral data analysis is also provided, with emphasis on the differences between traditional polychromatic and spectral cytometry approaches.

Recognizing stationary and locomotion activities using combinational of spectral analysis with statistical descriptors features

NASA Astrophysics Data System (ADS)

Zainudin, M. N. Shah; Sulaiman, Md Nasir; Mustapha, Norwati; Perumal, Thinagaran

2017-10-01

Prior knowledge in pervasive computing recently garnered a lot of attention due to its high demand in various application domains. Human activity recognition (HAR) considered as the applications that are widely explored by the expertise that provides valuable information to the human. Accelerometer sensor-based approach is utilized as devices to undergo the research in HAR since their small in size and this sensor already build-in in the various type of smartphones. However, the existence of high inter-class similarities among the class tends to degrade the recognition performance. Hence, this work presents the method for activity recognition using our proposed features from combinational of spectral analysis with statistical descriptors that able to tackle the issue of differentiating stationary and locomotion activities. The noise signal is filtered using Fourier Transform before it will be extracted using two different groups of features, spectral frequency analysis, and statistical descriptors. Extracted signal later will be classified using random forest ensemble classifier models. The recognition results show the good accuracy performance for stationary and locomotion activities based on USC HAD datasets.

Simultaneous separation by reversed-phase high-performance liquid chromatography and mass spectral identification of anthocyanins and flavonols in Shiraz grape skin.

PubMed

Downey, Mark O; Rochfort, Simone

2008-08-01

A limitation of large-scale viticultural trials is the time and cost of comprehensive compositional analysis of the fruit by high-performance liquid chromatography (HPLC). In addition, separate methods have generally been required to identify and quantify different classes of metabolites. To address these shortcomings a reversed-phase HPLC method was developed to simultaneously separate the anthocyanins and flavonols present in grape skins. The method employs a methanol and water gradient acidified with 10% formic acid with a run-time of 48 min including re-equilibration. Identity of anthocyanins and flavonols in Shiraz (Vitis vinifera L.) skin was confirmed by mass spectral analysis.

Local and Global Gestalt Laws: A Neurally Based Spectral Approach.

PubMed

Favali, Marta; Citti, Giovanna; Sarti, Alessandro

2017-02-01

This letter presents a mathematical model of figure-ground articulation that takes into account both local and global gestalt laws and is compatible with the functional architecture of the primary visual cortex (V1). The local gestalt law of good continuation is described by means of suitable connectivity kernels that are derived from Lie group theory and quantitatively compared with long-range connectivity in V1. Global gestalt constraints are then introduced in terms of spectral analysis of a connectivity matrix derived from these kernels. This analysis performs grouping of local features and individuates perceptual units with the highest salience. Numerical simulations are performed, and results are obtained by applying the technique to a number of stimuli.

Analysis on the optical aberration effect on spectral resolution of coded aperture spectroscopy

NASA Astrophysics Data System (ADS)

Hao, Peng; Chi, Mingbo; Wu, Yihui

2017-10-01

The coded aperture spectrometer can achieve high throughput and high spectral resolution by replacing the traditional single slit with two-dimensional array slits manufactured by MEMS technology. However, the sampling accuracy of coding spectrum image will be distorted due to the existence of system aberrations, machining error, fixing errors and so on, resulting in the declined spectral resolution. The influence factor of the spectral resolution come from the decode error, the spectral resolution of each column, and the column spectrum offset correction. For the Czerny-Turner spectrometer, the spectral resolution of each column most depend on the astigmatism, in this coded aperture spectroscopy, the uncorrected astigmatism does result in degraded performance. Some methods must be used to reduce or remove the limiting astigmatism. The curvature of field and the spectral curvature can be result in the spectrum revision errors.

Autoregressive modeling for the spectral analysis of oceanographic data

NASA Technical Reports Server (NTRS)

Gangopadhyay, Avijit; Cornillon, Peter; Jackson, Leland B.

1989-01-01

Over the last decade there has been a dramatic increase in the number and volume of data sets useful for oceanographic studies. Many of these data sets consist of long temporal or spatial series derived from satellites and large-scale oceanographic experiments. These data sets are, however, often 'gappy' in space, irregular in time, and always of finite length. The conventional Fourier transform (FT) approach to the spectral analysis is thus often inapplicable, or where applicable, it provides questionable results. Here, through comparative analysis with the FT for different oceanographic data sets, the possibilities offered by autoregressive (AR) modeling to perform spectral analysis of gappy, finite-length series, are discussed. The applications demonstrate that as the length of the time series becomes shorter, the resolving power of the AR approach as compared with that of the FT improves. For the longest data sets examined here, 98 points, the AR method performed only slightly better than the FT, but for the very short ones, 17 points, the AR method showed a dramatic improvement over the FT. The application of the AR method to a gappy time series, although a secondary concern of this manuscript, further underlines the value of this approach.

Simultaneous acquisition of EEG and NIRS during cognitive tasks for an open access dataset.

PubMed

Shin, Jaeyoung; von Lühmann, Alexander; Kim, Do-Won; Mehnert, Jan; Hwang, Han-Jeong; Müller, Klaus-Robert

2018-02-13

We provide an open access multimodal brain-imaging dataset of simultaneous electroencephalography (EEG) and near-infrared spectroscopy (NIRS) recordings. Twenty-six healthy participants performed three cognitive tasks: 1) n-back (0-, 2- and 3-back), 2) discrimination/selection response task (DSR) and 3) word generation (WG) tasks. The data provided includes: 1) measured data, 2) demographic data, and 3) basic analysis results. For n-back (dataset A) and DSR tasks (dataset B), event-related potential (ERP) analysis was performed, and spatiotemporal characteristics and classification results for 'target' versus 'non-target' (dataset A) and symbol 'O' versus symbol 'X' (dataset B) are provided. Time-frequency analysis was performed to show the EEG spectral power to differentiate the task-relevant activations. Spatiotemporal characteristics of hemodynamic responses are also shown. For the WG task (dataset C), the EEG spectral power and spatiotemporal characteristics of hemodynamic responses are analyzed, and the potential merit of hybrid EEG-NIRS BCIs was validated with respect to classification accuracy. We expect that the dataset provided will facilitate performance evaluation and comparison of many neuroimaging analysis techniques.

Simultaneous acquisition of EEG and NIRS during cognitive tasks for an open access dataset

PubMed Central

Shin, Jaeyoung; von Lühmann, Alexander; Kim, Do-Won; Mehnert, Jan; Hwang, Han-Jeong; Müller, Klaus-Robert

2018-01-01

We provide an open access multimodal brain-imaging dataset of simultaneous electroencephalography (EEG) and near-infrared spectroscopy (NIRS) recordings. Twenty-six healthy participants performed three cognitive tasks: 1) n-back (0-, 2- and 3-back), 2) discrimination/selection response task (DSR) and 3) word generation (WG) tasks. The data provided includes: 1) measured data, 2) demographic data, and 3) basic analysis results. For n-back (dataset A) and DSR tasks (dataset B), event-related potential (ERP) analysis was performed, and spatiotemporal characteristics and classification results for ‘target’ versus ‘non-target’ (dataset A) and symbol ‘O’ versus symbol ‘X’ (dataset B) are provided. Time-frequency analysis was performed to show the EEG spectral power to differentiate the task-relevant activations. Spatiotemporal characteristics of hemodynamic responses are also shown. For the WG task (dataset C), the EEG spectral power and spatiotemporal characteristics of hemodynamic responses are analyzed, and the potential merit of hybrid EEG-NIRS BCIs was validated with respect to classification accuracy. We expect that the dataset provided will facilitate performance evaluation and comparison of many neuroimaging analysis techniques. PMID:29437166

Multispectral image fusion for target detection

NASA Astrophysics Data System (ADS)

Leviner, Marom; Maltz, Masha

2009-09-01

Various different methods to perform multi-spectral image fusion have been suggested, mostly on the pixel level. However, the jury is still out on the benefits of a fused image compared to its source images. We present here a new multi-spectral image fusion method, multi-spectral segmentation fusion (MSSF), which uses a feature level processing paradigm. To test our method, we compared human observer performance in an experiment using MSSF against two established methods: Averaging and Principle Components Analysis (PCA), and against its two source bands, visible and infrared. The task that we studied was: target detection in the cluttered environment. MSSF proved superior to the other fusion methods. Based on these findings, current speculation about the circumstances in which multi-spectral image fusion in general and specific fusion methods in particular would be superior to using the original image sources can be further addressed.

Scaling earthquake ground motions for performance-based assessment of buildings

USGS Publications Warehouse

Huang, Y.-N.; Whittaker, A.S.; Luco, N.; Hamburger, R.O.

2011-01-01

The impact of alternate ground-motion scaling procedures on the distribution of displacement responses in simplified structural systems is investigated. Recommendations are provided for selecting and scaling ground motions for performance-based assessment of buildings. Four scaling methods are studied, namely, (1)geometric-mean scaling of pairs of ground motions, (2)spectrum matching of ground motions, (3)first-mode-period scaling to a target spectral acceleration, and (4)scaling of ground motions per the distribution of spectral demands. Data were developed by nonlinear response-history analysis of a large family of nonlinear single degree-of-freedom (SDOF) oscillators that could represent fixed-base and base-isolated structures. The advantages and disadvantages of each scaling method are discussed. The relationship between spectral shape and a ground-motion randomness parameter, is presented. A scaling procedure that explicitly considers spectral shape is proposed. ?? 2011 American Society of Civil Engineers.

Signal-to-noise analysis of a birefringent spectral zooming imaging spectrometer

NASA Astrophysics Data System (ADS)

Li, Jie; Zhang, Xiaotong; Wu, Haiying; Qi, Chun

2018-05-01

Study of signal-to-noise ratio (SNR) of a novel spectral zooming imaging spectrometer (SZIS) based on two identical Wollaston prisms is conducted. According to the theory of radiometry and Fourier transform spectroscopy, we deduce the theoretical equations of SNR of SZIS in spectral domain with consideration of the incident wavelength and the adjustable spectral resolution. An example calculation of SNR of SZIS is performed over 400-1000 nm. The calculation results indicate that SNR with different spectral resolutions of SZIS can be optionally selected by changing the spacing between the two identical Wollaston prisms. This will provide theoretical basis for the design, development and engineering of the developed imaging spectrometer for broad spectrum and SNR requirements.

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.

Nearest clusters based partial least squares discriminant analysis for the classification of spectral data.

PubMed

Song, Weiran; Wang, Hui; Maguire, Paul; Nibouche, Omar

2018-06-07

Partial Least Squares Discriminant Analysis (PLS-DA) is one of the most effective multivariate analysis methods for spectral data analysis, which extracts latent variables and uses them to predict responses. In particular, it is an effective method for handling high-dimensional and collinear spectral data. However, PLS-DA does not explicitly address data multimodality, i.e., within-class multimodal distribution of data. In this paper, we present a novel method termed nearest clusters based PLS-DA (NCPLS-DA) for addressing the multimodality and nonlinearity issues explicitly and improving the performance of PLS-DA on spectral data classification. The new method applies hierarchical clustering to divide samples into clusters and calculates the corresponding centre of every cluster. For a given query point, only clusters whose centres are nearest to such a query point are used for PLS-DA. Such a method can provide a simple and effective tool for separating multimodal and nonlinear classes into clusters which are locally linear and unimodal. Experimental results on 17 datasets, including 12 UCI and 5 spectral datasets, show that NCPLS-DA can outperform 4 baseline methods, namely, PLS-DA, kernel PLS-DA, local PLS-DA and k-NN, achieving the highest classification accuracy most of the time. Copyright © 2018 Elsevier B.V. All rights reserved.

Analysis for signal-to-noise ratio of hyper-spectral imaging FTIR interferometer

NASA Astrophysics Data System (ADS)

Li, Xun-niu; Zheng, Wei-jian; Lei, Zheng-gang; Wang, Hai-yang; Fu, Yan-peng

2013-08-01

Signal-to-noise Ratio of hyper-spectral imaging FTIR interferometer system plays a decisive role on the performance of the instrument. It is necessary to analyze them in the development process. Based on the simplified target/background model, the energy transfer model of the LWIR hyper-spectral imaging interferometer has been discussed. The noise equivalent spectral radiance (NESR) and its influencing factors of the interferometer system was analyzed, and the signal-to-noise（SNR） was calculated by using the properties of NESR and incident radiance. In a typical application environment, using standard atmospheric model of USA(1976 COESA) as a background, and set a reasonable target/background temperature difference, and take Michelson spatial modulation Fourier Transform interferometer as an example, the paper had calculated the NESR and the SNR of the interferometer system which using the commercially LWIR cooled FPA and UFPA detector. The system noise sources of the instrument were also analyzed in the paper. The results of those analyses can be used to optimize and pre-estimate the performance of the interferometer system, and analysis the applicable conditions of use different detectors. It has important guiding significance for the LWIR interferometer spectrometer design.

The MIND PALACE: A Multi-Spectral Imaging and Spectroscopy Database for Planetary Science

NASA Astrophysics Data System (ADS)

Eshelman, E.; Doloboff, I.; Hara, E. K.; Uckert, K.; Sapers, H. M.; Abbey, W.; Beegle, L. W.; Bhartia, R.

2017-12-01

The Multi-Instrument Database (MIND) is the web-based home to a well-characterized set of analytical data collected by a suite of deep-UV fluorescence/Raman instruments built at the Jet Propulsion Laboratory (JPL). Samples derive from a growing body of planetary surface analogs, mineral and microbial standards, meteorites, spacecraft materials, and other astrobiologically relevant materials. In addition to deep-UV spectroscopy, datasets stored in MIND are obtained from a variety of analytical techniques obtained over multiple spatial and spectral scales including electron microscopy, optical microscopy, infrared spectroscopy, X-ray fluorescence, and direct fluorescence imaging. Multivariate statistical analysis techniques, primarily Principal Component Analysis (PCA), are used to guide interpretation of these large multi-analytical spectral datasets. Spatial co-referencing of integrated spectral/visual maps is performed using QGIS (geographic information system software). Georeferencing techniques transform individual instrument data maps into a layered co-registered data cube for analysis across spectral and spatial scales. The body of data in MIND is intended to serve as a permanent, reliable, and expanding database of deep-UV spectroscopy datasets generated by this unique suite of JPL-based instruments on samples of broad planetary science interest.

Considerations on the quantitative analysis of apparent amorphicity of milled lactose by Raman spectroscopy.

PubMed

Pazesh, Samaneh; Lazorova, Lucia; Berggren, Jonas; Alderborn, Göran; Gråsjö, Johan

2016-09-10

The main purpose of the study was to evaluate various pre-processing and quantification approaches of Raman spectrum to quantify low level of amorphous content in milled lactose powder. To improve the quantification analysis, several spectral pre-processing methods were used to adjust background effects. The effects of spectral noise on the variation of determined amorphous content were also investigated theoretically by propagation of error analysis and were compared to the experimentally obtained values. Additionally, the applicability of calibration method with crystalline or amorphous domains in the estimation of amorphous content in milled lactose powder was discussed. Two straight baseline pre-processing methods gave the best and almost equal performance. By the succeeding quantification methods, PCA performed best, although the classical least square analysis (CLS) gave comparable results, while peak parameter analysis displayed to be inferior. The standard deviations of experimental determined percentage amorphous content were 0.94% and 0.25% for pure crystalline and pure amorphous samples respectively, which was very close to the standard deviation values from propagated spectral noise. The reasonable conformity between the milled samples spectra and synthesized spectra indicated representativeness of physical mixtures with crystalline or amorphous domains in the estimation of apparent amorphous content in milled lactose. Copyright © 2016 The Author(s). Published by Elsevier B.V. All rights reserved.

Analysis of stimulated Raman backscatter and stimulated Brillouin backscatter in experiments performed on SG-III prototype facility with a spectral analysis code

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

Hao, Liang; Zhao, Yiqing; Hu, Xiaoyan

2014-07-15

Experiments about the observations of stimulated Raman backscatter (SRS) and stimulated Brillouin backscatter (SBS) in Hohlraum were performed on Shenguang-III (SG-III) prototype facility for the first time in 2011. In this paper, relevant experimental results are analyzed for the first time with a one-dimension spectral analysis code, which is developed to study the coexistent process of SRS and SBS in Hohlraum plasma condition. Spectral features of the backscattered light are discussed with different plasma parameters. In the case of empty Hohlraum experiments, simulation results indicate that SBS, which grows fast at the energy deposition region near the Hohlraum wall, ismore » the dominant instability process. The time resolved spectra of SRS and SBS are numerically obtained, which agree with the experimental observations. For the gas-filled Hohlraum experiments, simulation results show that SBS grows fastest in Au plasma and amplifies convectively in C{sub 5}H{sub 12} gas, whereas SRS mainly grows in the high density region of the C{sub 5}H{sub 12} gas. Gain spectra and the spectra of backscattered light are simulated along the ray path, which clearly show the location where the intensity of scattered light with a certain wavelength increases. This work is helpful to comprehend the observed spectral features of SRS and SBS. The experiments and relevant analysis provide references for the ignition target design in future.« less

Informatic analysis for hidden pulse attack exploiting spectral characteristics of optics in plug-and-play quantum key distribution system

NASA Astrophysics Data System (ADS)

Ko, Heasin; Lim, Kyongchun; Oh, Junsang; Rhee, June-Koo Kevin

2016-10-01

Quantum channel loopholes due to imperfect implementations of practical devices expose quantum key distribution (QKD) systems to potential eavesdropping attacks. Even though QKD systems are implemented with optical devices that are highly selective on spectral characteristics, information theory-based analysis about a pertinent attack strategy built with a reasonable framework exploiting it has never been clarified. This paper proposes a new type of trojan horse attack called hidden pulse attack that can be applied in a plug-and-play QKD system, using general and optimal attack strategies that can extract quantum information from phase-disturbed quantum states of eavesdropper's hidden pulses. It exploits spectral characteristics of a photodiode used in a plug-and-play QKD system in order to probe modulation states of photon qubits. We analyze the security performance of the decoy-state BB84 QKD system under the optimal hidden pulse attack model that shows enormous performance degradation in terms of both secret key rate and transmission distance.

Systolic Processor Array For Recognition Of Spectra

NASA Technical Reports Server (NTRS)

Chow, Edward T.; Peterson, John C.

1995-01-01

Spectral signatures of materials detected and identified quickly. Spectral Analysis Systolic Processor Array (SPA2) relatively inexpensive and satisfies need to analyze large, complex volume of multispectral data generated by imaging spectrometers to extract desired information: computational performance needed to do this in real time exceeds that of current supercomputers. Locates highly similar segments or contiguous subsegments in two different spectra at time. Compares sampled spectra from instruments with data base of spectral signatures of known materials. Computes and reports scores that express degrees of similarity between sampled and data-base spectra.

Endoplasmic motility spectral characteristics in plasmodium of Physarum polycephalum

NASA Astrophysics Data System (ADS)

Avsievich, T. I.; Ghaleb, K. E. S.; Frolov, S. V.; Proskurin, S. G.

2015-03-01

Spectral Fourier analysis of experimentally acquired velocity time dependencies, V(t), of shuttle endoplasmic motility in an isolated strand of plasmodium of slime mold Physarum Polycephalum has been realized. V(t) registration was performed in normal conditions and after the treatment by respiration inhibitors, which lead to a complete cessation of endoplasmic motion in the strand. Spectral analysis of the velocity time dependences of the endoplasm allows obtaining two distinct harmonic components in the spectra. Their ratio appeared to be constant in all cases, ν2/ν1=1.97±0.17. After the inhibitors are washed out respiratory system becomes normal, gradually restoring the activity of both harmonic oscillatory sources with time. Simulated velocity time dependences correspond to experimental data with good accuracy.

Solution to the indexing problem of frequency domain simulation experiments

NASA Technical Reports Server (NTRS)

Mitra, Mousumi; Park, Stephen K.

1991-01-01

A frequency domain simulation experiment is one in which selected system parameters are oscillated sinusoidally to induce oscillations in one or more system statistics of interest. A spectral (Fourier) analysis of these induced oscillations is then performed. To perform this spectral analysis, all oscillation frequencies must be referenced to a common, independent variable - an oscillation index. In a discrete-event simulation, the global simulation clock is the most natural choice for the oscillation index. However, past efforts to reference all frequencies to the simulation clock generally yielded unsatisfactory results. The reason for these unsatisfactory results is explained in this paper and a new methodology which uses the simulation clock as the oscillation index is presented. Techniques for implementing this new methodology are demonstrated by performing a frequency domain simulation experiment for a network of queues.

Flow Cytometry Data Preparation Guidelines for Improved Automated Phenotypic Analysis.

PubMed

Jimenez-Carretero, Daniel; Ligos, José M; Martínez-López, María; Sancho, David; Montoya, María C

2018-05-15

Advances in flow cytometry (FCM) increasingly demand adoption of computational analysis tools to tackle the ever-growing data dimensionality. In this study, we tested different data input modes to evaluate how cytometry acquisition configuration and data compensation procedures affect the performance of unsupervised phenotyping tools. An analysis workflow was set up and tested for the detection of changes in reference bead subsets and in a rare subpopulation of murine lymph node CD103 + dendritic cells acquired by conventional or spectral cytometry. Raw spectral data or pseudospectral data acquired with the full set of available detectors by conventional cytometry consistently outperformed datasets acquired and compensated according to FCM standards. Our results thus challenge the paradigm of one-fluorochrome/one-parameter acquisition in FCM for unsupervised cluster-based analysis. Instead, we propose to configure instrument acquisition to use all available fluorescence detectors and to avoid integration and compensation procedures, thereby using raw spectral or pseudospectral data for improved automated phenotypic analysis. Copyright © 2018 by The American Association of Immunologists, Inc.

SearchLight: a freely available web-based quantitative spectral analysis tool (Conference Presentation)

NASA Astrophysics Data System (ADS)

Prabhat, Prashant; Peet, Michael; Erdogan, Turan

2016-03-01

In order to design a fluorescence experiment, typically the spectra of a fluorophore and of a filter set are overlaid on a single graph and the spectral overlap is evaluated intuitively. However, in a typical fluorescence imaging system the fluorophores and optical filters are not the only wavelength dependent variables - even the excitation light sources have been changing. For example, LED Light Engines may have a significantly different spectral response compared to the traditional metal-halide lamps. Therefore, for a more accurate assessment of fluorophore-to-filter-set compatibility, all sources of spectral variation should be taken into account simultaneously. Additionally, intuitive or qualitative evaluation of many spectra does not necessarily provide a realistic assessment of the system performance. "SearchLight" is a freely available web-based spectral plotting and analysis tool that can be used to address the need for accurate, quantitative spectral evaluation of fluorescence measurement systems. This tool is available at: http://searchlight.semrock.com/. Based on a detailed mathematical framework [1], SearchLight calculates signal, noise, and signal-to-noise ratio for multiple combinations of fluorophores, filter sets, light sources and detectors. SearchLight allows for qualitative and quantitative evaluation of the compatibility of filter sets with fluorophores, analysis of bleed-through, identification of optimized spectral edge locations for a set of filters under specific experimental conditions, and guidance regarding labeling protocols in multiplexing imaging assays. Entire SearchLight sessions can be shared with colleagues and collaborators and saved for future reference. [1] Anderson, N., Prabhat, P. and Erdogan, T., Spectral Modeling in Fluorescence Microscopy, http://www.semrock.com (2010).

Use of spectral analysis with iterative filter for voxelwise determination of regional rates of cerebral protein synthesis with L-[1-11C]leucine PET.

PubMed

Veronese, Mattia; Schmidt, Kathleen C; Smith, Carolyn Beebe; Bertoldo, Alessandra

2012-06-01

A spectral analysis approach was used to estimate kinetic parameters of the L-[1-(11)C]leucine positron emission tomography (PET) method and regional rates of cerebral protein synthesis (rCPS) on a voxel-by-voxel basis. Spectral analysis applies to both heterogeneous and homogeneous tissues; it does not require prior assumptions concerning number of tissue compartments. Parameters estimated with spectral analysis can be strongly affected by noise, but numerical filters improve estimation performance. Spectral analysis with iterative filter (SAIF) was originally developed to improve estimation of leucine kinetic parameters and rCPS in region-of-interest (ROI) data analyses. In the present study, we optimized SAIF for application at the voxel level. In measured L-[1-(11)C]leucine PET data, voxel-level SAIF parameter estimates averaged over all voxels within a ROI (mean voxel-SAIF) generally agreed well with corresponding estimates derived by applying the originally developed SAIF to ROI time-activity curves (ROI-SAIF). Region-of-interest-SAIF and mean voxel-SAIF estimates of rCPS were highly correlated. Simulations showed that mean voxel-SAIF rCPS estimates were less biased and less variable than ROI-SAIF estimates in the whole brain and cortex; biases were similar in white matter. We conclude that estimation of rCPS with SAIF is improved when the method is applied at voxel level than in ROI analysis.

Statistical properties of Fermi GBM GRBs' spectra

NASA Astrophysics Data System (ADS)

Rácz, István I.; Balázs, Lajos G.; Horvath, Istvan; Tóth, L. Viktor; Bagoly, Zsolt

2018-03-01

Statistical studies of gamma-ray burst (GRB) spectra may result in important information on the physics of GRBs. The Fermi GBM catalogue contains GRB parameters (peak energy, spectral indices, and intensity) estimated fitting the gamma-ray spectral energy distribution of the total emission (fluence, flnc), and during the time of the peak flux (pflx). Using contingency tables, we studied the relationship of the models best-fitting pflx and flnc time intervals. Our analysis revealed an ordering of the spectra into a power law - Comptonized - smoothly broken power law - Band series. This result was further supported by a correspondence analysis of the pflx and flnc spectra categorical variables. We performed a linear discriminant analysis (LDA) to find a relationship between categorical (spectral) and model independent physical data. LDA resulted in highly significant physical differences among the spectral types, that is more pronounced in the case of the pflx spectra, than for the flnc spectra. We interpreted this difference as caused by the temporal variation of the spectrum during the outburst. This spectral variability is confirmed by the differences in the low-energy spectral index and peak energy, between the pflx and flnc spectra. We found that the synchrotron radiation is significant in GBM spectra. The mean low-energy spectral index is close to the canonical value of α = -2/3 during the peak flux. However, α is ˜ -0.9 for the spectra of the fluences. We interpret this difference as showing that the effect of cooling is important only for the fluence spectra.

The measurement of solar spectral irradiances at wavelengths between 40 and 4000 A

NASA Technical Reports Server (NTRS)

Timothy, J. G.

1983-01-01

Two 1/8-meter Ebert-Fastie spectrometers were refurbished and upgraded in order to measure the solar spectral irradiances between 1160 A and 3100 A. An evacuated 1/4-meter normal-incidence spectrometer was also fabricated for spectral irradiance measurements over the wavelength range from 1250 A to 250 A. Procedures were developed for the calibration of all three instruments utilizing standards at the National Bureau of Standards. The two 1/8-meter spectrometers were flown to measure the solar spectral irradiances near solar maximum on two different dates. Data from these flights were analyzed. The performance of the spectrometers, and the results of an analysis of the variabilities of the solar spectral irradiances over the solar cycles 20 and 21 are discussed.

A new multi-spectral feature level image fusion method for human interpretation

NASA Astrophysics Data System (ADS)

Leviner, Marom; Maltz, Masha

2009-03-01

Various different methods to perform multi-spectral image fusion have been suggested, mostly on the pixel level. However, the jury is still out on the benefits of a fused image compared to its source images. We present here a new multi-spectral image fusion method, multi-spectral segmentation fusion (MSSF), which uses a feature level processing paradigm. To test our method, we compared human observer performance in a three-task experiment using MSSF against two established methods: averaging and principle components analysis (PCA), and against its two source bands, visible and infrared. The three tasks that we studied were: (1) simple target detection, (2) spatial orientation, and (3) camouflaged target detection. MSSF proved superior to the other fusion methods in all three tests; MSSF also outperformed the source images in the spatial orientation and camouflaged target detection tasks. Based on these findings, current speculation about the circumstances in which multi-spectral image fusion in general and specific fusion methods in particular would be superior to using the original image sources can be further addressed.

Multiscale Characterization of PM2.5 in Southern Taiwan based on Noise-assisted Multivariate Empirical Mode Decomposition and Time-dependent Intrinsic Correlation

NASA Astrophysics Data System (ADS)

Hsiao, Y. R.; Tsai, C.

2017-12-01

As the WHO Air Quality Guideline indicates, ambient air pollution exposes world populations under threat of fatal symptoms (e.g. heart disease, lung cancer, asthma etc.), raising concerns of air pollution sources and relative factors. This study presents a novel approach to investigating the multiscale variations of PM2.5 in southern Taiwan over the past decade, with four meteorological influencing factors (Temperature, relative humidity, precipitation and wind speed),based on Noise-assisted Multivariate Empirical Mode Decomposition(NAMEMD) algorithm, Hilbert Spectral Analysis(HSA) and Time-dependent Intrinsic Correlation(TDIC) method. NAMEMD algorithm is a fully data-driven approach designed for nonlinear and nonstationary multivariate signals, and is performed to decompose multivariate signals into a collection of channels of Intrinsic Mode Functions (IMFs). TDIC method is an EMD-based method using a set of sliding window sizes to quantify localized correlation coefficients for multiscale signals. With the alignment property and quasi-dyadic filter bank of NAMEMD algorithm, one is able to produce same number of IMFs for all variables and estimates the cross correlation in a more accurate way. The performance of spectral representation of NAMEMD-HSA method is compared with Complementary Empirical Mode Decomposition/ Hilbert Spectral Analysis (CEEMD-HSA) and Wavelet Analysis. The nature of NAMAMD-based TDICC analysis is then compared with CEEMD-based TDIC analysis and the traditional correlation analysis.

Method and system for calibrating acquired spectra for use in spectral analysis

DOEpatents

Reber, Edward L.; Rohde, Kenneth W.; Blackwood, Larry G.

2010-09-14

A method for calibrating acquired spectra for use in spectral analysis includes performing Gaussian peak fitting to spectra acquired by a plurality of NaI detectors to define peak regions. A Na and annihilation doublet may be located among the peak regions. A predetermined energy level may be applied to one of the peaks in the doublet and a location of a hydrogen peak may be predicted based on the location of at least one of the peaks of the doublet. Control systems for calibrating spectra are also disclosed.

Pulmonary-impedance power spectral analysis: A facile means of detecting radiation-induced gastrointestinal distress and performance decrement in man

NASA Technical Reports Server (NTRS)

Rick, R. C.; Lushbaugh, C. C.; Mcdow, E.; Frome, E.

1972-01-01

Changes in respiratory variance revealed by power spectral analysis of the pulmonary impedance pneumogram can be used to detect and measure stresses directly or indirectly affecting human respiratory function. When gastrointestinal distress occurred during a series of 5 total-body exposures of 30 R at a rate of 1.5 R/min, it was accompanied by typical shifts in pulmonary impedance power spectra. These changes did not occur after protracted exposure of 250 R (30 R daily) at 1.5 R/hr that failed to cause radiation sickness. This system for quantitating respiratory effort can also be used to detect alterations in one's ability to perform under controlled exercise conditions.

Performance optimization of spectral amplitude coding OCDMA system using new enhanced multi diagonal code

NASA Astrophysics Data System (ADS)

Imtiaz, Waqas A.; Ilyas, M.; Khan, Yousaf

2016-11-01

This paper propose a new code to optimize the performance of spectral amplitude coding-optical code division multiple access (SAC-OCDMA) system. The unique two-matrix structure of the proposed enhanced multi diagonal (EMD) code and effective correlation properties, between intended and interfering subscribers, significantly elevates the performance of SAC-OCDMA system by negating multiple access interference (MAI) and associated phase induce intensity noise (PIIN). Performance of SAC-OCDMA system based on the proposed code is thoroughly analyzed for two detection techniques through analytic and simulation analysis by referring to bit error rate (BER), signal to noise ratio (SNR) and eye patterns at the receiving end. It is shown that EMD code while using SDD technique provides high transmission capacity, reduces the receiver complexity, and provides better performance as compared to complementary subtraction detection (CSD) technique. Furthermore, analysis shows that, for a minimum acceptable BER of 10-9 , the proposed system supports 64 subscribers at data rates of up to 2 Gbps for both up-down link transmission.

Theoretical analysis of the performance of code division multiple access communications over multimode optical fiber channels. Part 1: Transmission and detection

NASA Astrophysics Data System (ADS)

Walker, Ernest L.

1994-05-01

This paper presents results of a theoretical investigation to evaluate the performance of code division multiple access communications over multimode optical fiber channels in an asynchronous, multiuser communication network environment. The system is evaluated using Gold sequences for spectral spreading of the baseband signal from each user employing direct-sequence biphase shift keying and intensity modulation techniques. The transmission channel model employed is a lossless linear system approximation of the field transfer function for the alpha -profile multimode optical fiber. Due to channel model complexity, a correlation receiver model employing a suboptimal receive filter was used in calculating the peak output signal at the ith receiver. In Part 1, the performance measures for the system, i.e., signal-to-noise ratio and bit error probability for the ith receiver, are derived as functions of channel characteristics, spectral spreading, number of active users, and the bit energy to noise (white) spectral density ratio. In Part 2, the overall system performance is evaluated.

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.

Comparative shotgun proteomics using spectral count data and quasi-likelihood modeling.

PubMed

Li, Ming; Gray, William; Zhang, Haixia; Chung, Christine H; Billheimer, Dean; Yarbrough, Wendell G; Liebler, Daniel C; Shyr, Yu; Slebos, Robbert J C

2010-08-06

Shotgun proteomics provides the most powerful analytical platform for global inventory of complex proteomes using liquid chromatography-tandem mass spectrometry (LC-MS/MS) and allows a global analysis of protein changes. Nevertheless, sampling of complex proteomes by current shotgun proteomics platforms is incomplete, and this contributes to variability in assessment of peptide and protein inventories by spectral counting approaches. Thus, shotgun proteomics data pose challenges in comparing proteomes from different biological states. We developed an analysis strategy using quasi-likelihood Generalized Linear Modeling (GLM), included in a graphical interface software package (QuasiTel) that reads standard output from protein assemblies created by IDPicker, an HTML-based user interface to query shotgun proteomic data sets. This approach was compared to four other statistical analysis strategies: Student t test, Wilcoxon rank test, Fisher's Exact test, and Poisson-based GLM. We analyzed the performance of these tests to identify differences in protein levels based on spectral counts in a shotgun data set in which equimolar amounts of 48 human proteins were spiked at different levels into whole yeast lysates. Both GLM approaches and the Fisher Exact test performed adequately, each with their unique limitations. We subsequently compared the proteomes of normal tonsil epithelium and HNSCC using this approach and identified 86 proteins with differential spectral counts between normal tonsil epithelium and HNSCC. We selected 18 proteins from this comparison for verification of protein levels between the individual normal and tumor tissues using liquid chromatography-multiple reaction monitoring mass spectrometry (LC-MRM-MS). This analysis confirmed the magnitude and direction of the protein expression differences in all 6 proteins for which reliable data could be obtained. Our analysis demonstrates that shotgun proteomic data sets from different tissue phenotypes are sufficiently rich in quantitative information and that statistically significant differences in proteins spectral counts reflect the underlying biology of the samples.

Comparative Shotgun Proteomics Using Spectral Count Data and Quasi-Likelihood Modeling

PubMed Central

2010-01-01

Shotgun proteomics provides the most powerful analytical platform for global inventory of complex proteomes using liquid chromatography−tandem mass spectrometry (LC−MS/MS) and allows a global analysis of protein changes. Nevertheless, sampling of complex proteomes by current shotgun proteomics platforms is incomplete, and this contributes to variability in assessment of peptide and protein inventories by spectral counting approaches. Thus, shotgun proteomics data pose challenges in comparing proteomes from different biological states. We developed an analysis strategy using quasi-likelihood Generalized Linear Modeling (GLM), included in a graphical interface software package (QuasiTel) that reads standard output from protein assemblies created by IDPicker, an HTML-based user interface to query shotgun proteomic data sets. This approach was compared to four other statistical analysis strategies: Student t test, Wilcoxon rank test, Fisher’s Exact test, and Poisson-based GLM. We analyzed the performance of these tests to identify differences in protein levels based on spectral counts in a shotgun data set in which equimolar amounts of 48 human proteins were spiked at different levels into whole yeast lysates. Both GLM approaches and the Fisher Exact test performed adequately, each with their unique limitations. We subsequently compared the proteomes of normal tonsil epithelium and HNSCC using this approach and identified 86 proteins with differential spectral counts between normal tonsil epithelium and HNSCC. We selected 18 proteins from this comparison for verification of protein levels between the individual normal and tumor tissues using liquid chromatography−multiple reaction monitoring mass spectrometry (LC−MRM-MS). This analysis confirmed the magnitude and direction of the protein expression differences in all 6 proteins for which reliable data could be obtained. Our analysis demonstrates that shotgun proteomic data sets from different tissue phenotypes are sufficiently rich in quantitative information and that statistically significant differences in proteins spectral counts reflect the underlying biology of the samples. PMID:20586475

Intra-operative on-line discrimination of kidney cancer from normal tissue by IR ATR spectroscopy of extracellular fluid

NASA Astrophysics Data System (ADS)

Urboniene, V.; Velicka, M.; Ceponkus, J.; Pucetaite, M.; Jankevicius, F.; Sablinskas, V.; Steiner, G.

2016-03-01

Determination of cancerous and normal kidney tissues during partial, simple or radical nephrectomy surgery was performed by using differences in the IR absorption spectra of extracellular fluid taken from the corresponding tissue areas. The samples were prepared by stamping of the kidney tissue on ATR diamond crystal. The spectral measurements were performed directly in the OR during surgery for 58 patients. It was found that intensities of characteristic spectral bands of glycogen (880-1200 cm-1) in extracellular fluid are sensitive to the type of the tissue and can be used as spectral markers of tumours. Characteristic spectral band of lactic acid (1730 cm-1) - product of the anaerobic glycolysis, taking place in the cancer cells is not suitable for use as a spectral marker of cancerous tissue, since it overlaps with the band of carbonyl stretch in phospholipids and fatty acids. Results of hierarchical cluster analysis of the spectra show that the spectra of healthy and tumour tissue films can be reliably separated into two groups. On the other hand, possibility to differentiate between tumours of different types and grades remains in question. While the fluid from highly malignant G3 tumour tissue contains highly pronounced glycogen spectral bands and can be well separated from benign and G1 tumours by principal component analysis, the variations between spectra from sample to sample prevent from obtaining conclusive results about the grouping between different tumour types and grades. The proposed method is instant and can be used in situ and even in vivo.

JPSS-1 VIIRS Version 2 At-Launch Relative Spectral Response Characterization and Performance

NASA Technical Reports Server (NTRS)

Moeller, Chris; Schwarting, Thomas; McIntire, Jeff; Moyer, Dave; Zeng, Jinan

2017-01-01

The relative spectral response (RSR) characterization of the JPSS-1 VIIRS spectral bands has achieved at launch status in the VIIRS Data Analysis Working Group February 2016 Version 2 RSR release. The Version 2 release improves upon the June 2015 Version 1 release by including December 2014 NIST TSIRCUS spectral measurements of VIIRS VisNIR bands in the analysis plus correcting CO2 influence on the band M13 RSR. The T-SIRCUS based characterization is merged with the summer 2014 SpMA based characterization of VisNIR bands (Version 1 release) to yield a fused RSR for these bands, combining the strengths of the T-SIRCUS and the SpMA measurement systems. The M13 RSR is updated by applying a model-based correction to mitigate CO2 attenuation of the SpMA source signal that occurred during M13 spectral measurements. The Version 2 release carries forward the Version 1 RSR for those bands that were not updated (M8-M12, M14-M16AB, I3-I5, DNBMGS). The Version 2 release includes band average (overall detectors and subsamples) RSR plus supporting RSR for each detector and subsample. The at-launch band average RSR have been used to populate Look-Up Tables supporting the sensor data record and environmental data record at-launch science products. Spectral performance metrics show that JPSS-1VIIRS RSR are compliant on specifications with a few minor exceptions. The Version 2 release, which replaces the Version 1 release, is currently available on the password-protected NASA JPSS-1 eRooms under EAR99 control.

Group Independent Component Analysis (gICA) and Current Source Density (CSD) in the study of EEG in ADHD adults.

PubMed

Ponomarev, Valery A; Mueller, Andreas; Candrian, Gian; Grin-Yatsenko, Vera A; Kropotov, Juri D

2014-01-01

To investigate the performance of the spectral analysis of resting EEG, Current Source Density (CSD) and group independent components (gIC) in diagnosing ADHD adults. Power spectra of resting EEG, CSD and gIC (19 channels, linked ears reference, eyes open/closed) from 96 ADHD and 376 healthy adults were compared between eyes open and eyes closed conditions, and between groups of subjects. Pattern of differences in gIC and CSD spectral power between conditions was approximately similar, whereas it was more widely spatially distributed for EEG. Size effect (Cohen's d) of differences in gIC and CSD spectral power between groups of subjects was considerably greater than in the case of EEG. Significant reduction of gIC and CSD spectral power depending on conditions was found in ADHD patients. Reducing power in a wide frequency range in the fronto-central areas is a common phenomenon regardless of whether the eyes were open or closed. Spectral power of local EEG activity isolated by gICA or CSD in the fronto-central areas may be a suitable marker for discrimination of ADHD and healthy adults. Spectral analysis of gIC and CSD provides better sensitivity to discriminate ADHD and healthy adults. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

A Spectral Element Ocean Model on the Cray T3D: the interannual variability of the Mediterranean Sea general circulation

NASA Astrophysics Data System (ADS)

Molcard, A. J.; Pinardi, N.; Ansaloni, R.

A new numerical model, SEOM (Spectral Element Ocean Model, (Iskandarani et al, 1994)), has been implemented in the Mediterranean Sea. Spectral element methods combine the geometric flexibility of finite element techniques with the rapid convergence rate of spectral schemes. The current version solves the shallow water equations with a fifth (or sixth) order accuracy spectral scheme and about 50.000 nodes. The domain decomposition philosophy makes it possible to exploit the power of parallel machines. The original MIMD master/slave version of SEOM, written in F90 and PVM, has been ported to the Cray T3D. When critical for performance, Cray specific high-performance one-sided communication routines (SHMEM) have been adopted to fully exploit the Cray T3D interprocessor network. Tests performed with highly unstructured and irregular grid, on up to 128 processors, show an almost linear scalability even with unoptimized domain decomposition techniques. Results from various case studies on the Mediterranean Sea are shown, involving realistic coastline geometry, and monthly mean 1000mb winds from the ECMWF's atmospheric model operational analysis from the period January 1987 to December 1994. The simulation results show that variability in the wind forcing considerably affect the circulation dynamics of the Mediterranean Sea.

A Review on Spectral Amplitude Coding Optical Code Division Multiple Access

NASA Astrophysics Data System (ADS)

Kaur, Navpreet; Goyal, Rakesh; Rani, Monika

2017-06-01

This manuscript deals with analysis of Spectral Amplitude Coding Optical Code Division Multiple Access (SACOCDMA) system. The major noise source in optical CDMA is co-channel interference from other users known as multiple access interference (MAI). The system performance in terms of bit error rate (BER) degrades as a result of increased MAI. It is perceived that number of users and type of codes used for optical system directly decide the performance of system. MAI can be restricted by efficient designing of optical codes and implementing them with unique architecture to accommodate more number of users. Hence, it is a necessity to design a technique like spectral direct detection (SDD) technique with modified double weight code, which can provide better cardinality and good correlation property.

Assessment of Infrared Sounder Radiometric Noise from Analysis of Spectral Residuals

NASA Astrophysics Data System (ADS)

Dufour, E.; Klonecki, A.; Standfuss, C.; Tournier, B.; Serio, C.; Masiello, G.; Tjemkes, S.; Stuhlmann, R.

2016-08-01

For the preparation and performance monitoring of the future generation of hyperspectral InfraRed sounders dedicated to the precise vertical profiling of the atmospheric state, such as the Meteosat Third Generation hyperspectral InfraRed Sounder, a reliable assessment of the instrument radiometric error covariance matrix is needed.Ideally, an inflight estimation of the radiometrric noise is recommended as certain sources of noise can be driven by the spectral signature of the observed Earth/ atmosphere radiance. Also, unknown correlated noise sources, generally related to incomplete knowledge of the instrument state, can be present, so a caracterisation of the noise spectral correlation is also neeed.A methodology, relying on the analysis of post-retreival spectral residuals, is designed and implemented to derive in-flight the covariance matrix on the basis of Earth scenes measurements. This methodology is successfully demonstrated using IASI observations as MTG-IRS proxy data and made it possible to highlight anticipated correlation structures explained by apodization and micro-vibration effects (ghost). This analysis is corroborated by a parallel estimation based on an IASI black body measurement dataset and the results of an independent micro-vibration model.

Decoding magnetoencephalographic rhythmic activity using spectrospatial information.

PubMed

Kauppi, Jukka-Pekka; Parkkonen, Lauri; Hari, Riitta; Hyvärinen, Aapo

2013-12-01

We propose a new data-driven decoding method called Spectral Linear Discriminant Analysis (Spectral LDA) for the analysis of magnetoencephalography (MEG). The method allows investigation of changes in rhythmic neural activity as a result of different stimuli and tasks. The introduced classification model only assumes that each "brain state" can be characterized as a combination of neural sources, each of which shows rhythmic activity at one or several frequency bands. Furthermore, the model allows the oscillation frequencies to be different for each such state. We present decoding results from 9 subjects in a four-category classification problem defined by an experiment involving randomly alternating epochs of auditory, visual and tactile stimuli interspersed with rest periods. The performance of Spectral LDA was very competitive compared with four alternative classifiers based on different assumptions concerning the organization of rhythmic brain activity. In addition, the spectral and spatial patterns extracted automatically on the basis of trained classifiers showed that Spectral LDA offers a novel and interesting way of analyzing spectrospatial oscillatory neural activity across the brain. All the presented classification methods and visualization tools are freely available as a Matlab toolbox. © 2013.

Analysis of bias voltage dependent spectral response in Ga0.51In0.49P/Ga0.99In0.01As/Ge triple junction solar cell

NASA Astrophysics Data System (ADS)

Sogabe, Tomah; Ogura, Akio; Okada, Yoshitaka

2014-02-01

Spectral response measurement plays great role in characterizing solar cell device because it directly reflects the efficiency by which the device converts the sunlight into an electrical current. Based on the spectral response results, the short circuit current of each subcell can be quantitatively determined. Although spectral response dependence on wavelength, i.e., the well-known external quantum efficiency (EQE), has been widely used in characterizing multijunction solar cell and has been well interpreted, detailed analysis of spectral response dependence on bias voltage (SR -Vbias) has not been reported so far. In this work, we have performed experimental and numerical studies on the SR -Vbias for Ga0.51In0.49P/Ga0.99In0.01As/Ge triple junction solar cell. Phenomenological description was given to clarify the mechanism of operation matching point variation in SR -Vbias measurements. The profile of SR-Vbias curve was explained in detail by solving the coupled two-diode current-voltage characteristic transcend formula for each subcell.

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

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

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.

Global analysis of microscopic fluorescence lifetime images using spectral segmentation and a digital micromirror spatial illuminator.

PubMed

Bednarkiewicz, Artur; Whelan, Maurice P

2008-01-01

Fluorescence lifetime imaging (FLIM) is very demanding from a technical and computational perspective, and the output is usually a compromise between acquisition/processing time and data accuracy and precision. We present a new approach to acquisition, analysis, and reconstruction of microscopic FLIM images by employing a digital micromirror device (DMD) as a spatial illuminator. In the first step, the whole field fluorescence image is collected by a color charge-coupled device (CCD) camera. Further qualitative spectral analysis and sample segmentation are performed to spatially distinguish between spectrally different regions on the sample. Next, the fluorescence of the sample is excited segment by segment, and fluorescence lifetimes are acquired with a photon counting technique. FLIM image reconstruction is performed by either raster scanning the sample or by directly accessing specific regions of interest. The unique features of the DMD illuminator allow the rapid on-line measurement of global good initial parameters (GIP), which are supplied to the first iteration of the fitting algorithm. As a consequence, a decrease of the computation time required to obtain a satisfactory quality-of-fit is achieved without compromising the accuracy and precision of the lifetime measurements.

Spatial-spectral preprocessing for endmember extraction on GPU's

NASA Astrophysics Data System (ADS)

Jimenez, Luis I.; Plaza, Javier; Plaza, Antonio; Li, Jun

2016-10-01

Spectral unmixing is focused in the identification of spectrally pure signatures, called endmembers, and their corresponding abundances in each pixel of a hyperspectral image. Mainly focused on the spectral information contained in the hyperspectral images, endmember extraction techniques have recently included spatial information to achieve more accurate results. Several algorithms have been developed for automatic or semi-automatic identification of endmembers using spatial and spectral information, including the spectral-spatial endmember extraction (SSEE) where, within a preprocessing step in the technique, both sources of information are extracted from the hyperspectral image and equally used for this purpose. Previous works have implemented the SSEE technique in four main steps: 1) local eigenvectors calculation in each sub-region in which the original hyperspectral image is divided; 2) computation of the maxima and minima projection of all eigenvectors over the entire hyperspectral image in order to obtain a candidates pixels set; 3) expansion and averaging of the signatures of the candidate set; 4) ranking based on the spectral angle distance (SAD). The result of this method is a list of candidate signatures from which the endmembers can be extracted using various spectral-based techniques, such as orthogonal subspace projection (OSP), vertex component analysis (VCA) or N-FINDR. Considering the large volume of data and the complexity of the calculations, there is a need for efficient implementations. Latest- generation hardware accelerators such as commodity graphics processing units (GPUs) offer a good chance for improving the computational performance in this context. In this paper, we develop two different implementations of the SSEE algorithm using GPUs. Both are based on the eigenvectors computation within each sub-region of the first step, one using the singular value decomposition (SVD) and another one using principal component analysis (PCA). Based on our experiments with hyperspectral data sets, high computational performance is observed in both cases.

The Chandra Source Catalog 2.0: Spectral Properties

NASA Astrophysics Data System (ADS)

McCollough, Michael L.; Siemiginowska, Aneta; Burke, Douglas; Nowak, Michael A.; Primini, Francis Anthony; Laurino, Omar; Nguyen, Dan T.; Allen, Christopher E.; Anderson, Craig S.; Budynkiewicz, Jamie A.; Chen, Judy C.; Civano, Francesca Maria; D'Abrusco, Raffaele; Doe, Stephen M.; Evans, Ian N.; Evans, Janet D.; Fabbiano, Giuseppina; Gibbs, Danny G., II; Glotfelty, Kenny J.; Graessle, Dale E.; Grier, John D.; Hain, Roger; Hall, Diane M.; Harbo, Peter N.; Houck, John C.; Lauer, Jennifer L.; Lee, Nicholas P.; Martínez-Galarza, Juan Rafael; McDowell, Jonathan C.; Miller, Joseph; McLaughlin, Warren; Morgan, Douglas L.; Mossman, Amy E.; Nichols, Joy S.; Paxson, Charles; Plummer, David A.; Rots, Arnold H.; Sundheim, Beth A.; Tibbetts, Michael; Van Stone, David W.; Zografou, Panagoula; Chandra Source Catalog Team

2018-01-01

The second release of the Chandra Source Catalog (CSC) contains all sources identified from sixteen years' worth of publicly accessible observations. The vast majority of these sources have been observed with the ACIS detector and have spectral information in 0.5-7 keV energy range. Here we describe the methods used to automatically derive spectral properties for each source detected by the standard processing pipeline and included in the final CSC. The sources with high signal to noise ratio (exceeding 150 net counts) were fit in Sherpa (the modeling and fitting application from the Chandra Interactive Analysis of Observations package) using wstat as a fit statistic and Bayesian draws method to determine errors. Three models were fit to each source: an absorbed power-law, blackbody, and Bremsstrahlung emission. The fitted parameter values for the power-law, blackbody, and Bremsstrahlung models were included in the catalog with the calculated flux for each model. The CSC also provides the source energy fluxes computed from the normalizations of predefined absorbed power-law, black-body, Bremsstrahlung, and APEC models needed to match the observed net X-ray counts. For sources that have been observed multiple times we performed a Bayesian Blocks analysis will have been performed (see the Primini et al. poster) and the most significant block will have a joint fit performed for the mentioned spectral models. In addition, we provide access to data products for each source: a file with source spectrum, the background spectrum, and the spectral response of the detector. Hardness ratios were calculated for each source between pairs of energy bands (soft, medium and hard). This work has been supported by NASA under contract NAS 8-03060 to the Smithsonian Astrophysical Observatory for operation of the Chandra X-ray Center.

Time-resolved lidar fluorosensor for sea pollution detection

NASA Technical Reports Server (NTRS)

Ferrario, A.; Pizzolati, P. L.; Zanzottera, E.

1986-01-01

A contemporary time and spectral analysis of oil fluorescence is useful for the detection and the characterization of oil spills on the sea surface. Nevertheless the fluorosensor lidars, which were realized up to now, have only partial capability to perform this double analysis. The main difficulties are the high resolution required (of the order of 1 nanosecond) and the complexity of the detection system for the recording of a two-dimensional matrix of data for each laser pulse. An airborne system whose major specifications were: time range, 30 to 75 ns; time resolution, 1 ns; spectral range, 350 to 700 nm; and spectral resolution, 10 nm was designed and constructed. The designed system of a short pulse ultraviolet laser source and a streak camera based detector are described.

A hyperspectral image projector for hyperspectral imagers

NASA Astrophysics Data System (ADS)

Rice, Joseph P.; Brown, Steven W.; Neira, Jorge E.; Bousquet, Robert R.

2007-04-01

We have developed and demonstrated a Hyperspectral Image Projector (HIP) intended for system-level validation testing of hyperspectral imagers, including the instrument and any associated spectral unmixing algorithms. HIP, based on the same digital micromirror arrays used in commercial digital light processing (DLP*) displays, is capable of projecting any combination of many different arbitrarily programmable basis spectra into each image pixel at up to video frame rates. We use a scheme whereby one micromirror array is used to produce light having the spectra of endmembers (i.e. vegetation, water, minerals, etc.), and a second micromirror array, optically in series with the first, projects any combination of these arbitrarily-programmable spectra into the pixels of a 1024 x 768 element spatial image, thereby producing temporally-integrated images having spectrally mixed pixels. HIP goes beyond conventional DLP projectors in that each spatial pixel can have an arbitrary spectrum, not just arbitrary color. As such, the resulting spectral and spatial content of the projected image can simulate realistic scenes that a hyperspectral imager will measure during its use. Also, the spectral radiance of the projected scenes can be measured with a calibrated spectroradiometer, such that the spectral radiance projected into each pixel of the hyperspectral imager can be accurately known. Use of such projected scenes in a controlled laboratory setting would alleviate expensive field testing of instruments, allow better separation of environmental effects from instrument effects, and enable system-level performance testing and validation of hyperspectral imagers as used with analysis algorithms. For example, known mixtures of relevant endmember spectra could be projected into arbitrary spatial pixels in a hyperspectral imager, enabling tests of how well a full system, consisting of the instrument + calibration + analysis algorithm, performs in unmixing (i.e. de-convolving) the spectra in all pixels. We discuss here the performance of a visible prototype HIP. The technology is readily extendable to the ultraviolet and infrared spectral ranges, and the scenes can be static or dynamic.

High-speed vibrational imaging and spectral analysis of lipid bodies by compound Raman microscopy.

PubMed

Slipchenko, Mikhail N; Le, Thuc T; Chen, Hongtao; Cheng, Ji-Xin

2009-05-28

Cells store excess energy in the form of cytoplasmic lipid droplets. At present, it is unclear how different types of fatty acids contribute to the formation of lipid droplets. We describe a compound Raman microscope capable of both high-speed chemical imaging and quantitative spectral analysis on the same platform. We used a picosecond laser source to perform coherent Raman scattering imaging of a biological sample and confocal Raman spectral analysis at points of interest. The potential of the compound Raman microscope was evaluated on lipid bodies of cultured cells and live animals. Our data indicate that the in vivo fat contains much more unsaturated fatty acids (FAs) than the fat formed via de novo synthesis in 3T3-L1 cells. Furthermore, in vivo analysis of subcutaneous adipocytes and glands revealed a dramatic difference not only in the unsaturation level but also in the thermodynamic state of FAs inside their lipid bodies. Additionally, the compound Raman microscope allows tracking of the cellular uptake of a specific fatty acid and its abundance in nascent cytoplasmic lipid droplets. The high-speed vibrational imaging and spectral analysis capability renders compound Raman microscopy an indispensible analytical tool for the study of lipid-droplet biology.

Performance evaluation of object based greenhouse detection from Sentinel-2 MSI and Landsat 8 OLI data: A case study from Almería (Spain)

NASA Astrophysics Data System (ADS)

Novelli, Antonio; Aguilar, Manuel A.; Nemmaoui, Abderrahim; Aguilar, Fernando J.; Tarantino, Eufemia

2016-10-01

This paper shows the first comparison between data from Sentinel-2 (S2) Multi Spectral Instrument (MSI) and Landsat 8 (L8) Operational Land Imager (OLI) headed up to greenhouse detection. Two closely related in time scenes, one for each sensor, were classified by using Object Based Image Analysis and Random Forest (RF). The RF input consisted of several object-based features computed from spectral bands and including mean values, spectral indices and textural features. S2 and L8 data comparisons were also extended using a common segmentation dataset extracted form VHR World-View 2 (WV2) imagery to test differences only due to their specific spectral contribution. The best band combinations to perform segmentation were found through a modified version of the Euclidian Distance 2 index. Four different RF classifications schemes were considered achieving 89.1%, 91.3%, 90.9% and 93.4% as the best overall accuracies respectively, evaluated over the whole study area.

An Improved Variational Method for Hyperspectral Image Pansharpening with the Constraint of Spectral Difference Minimization

NASA Astrophysics Data System (ADS)

Huang, Z.; Chen, Q.; Shen, Y.; Chen, Q.; Liu, X.

2017-09-01

Variational pansharpening can enhance the spatial resolution of a hyperspectral (HS) image using a high-resolution panchromatic (PAN) image. However, this technology may lead to spectral distortion that obviously affect the accuracy of data analysis. In this article, we propose an improved variational method for HS image pansharpening with the constraint of spectral difference minimization. We extend the energy function of the classic variational pansharpening method by adding a new spectral fidelity term. This fidelity term is designed following the definition of spectral angle mapper, which means that for every pixel, the spectral difference value of any two bands in the HS image is in equal proportion to that of the two corresponding bands in the pansharpened image. Gradient descent method is adopted to find the optimal solution of the modified energy function, and the pansharpened image can be reconstructed. Experimental results demonstrate that the constraint of spectral difference minimization is able to preserve the original spectral information well in HS images, and reduce the spectral distortion effectively. Compared to original variational method, our method performs better in both visual and quantitative evaluation, and achieves a good trade-off between spatial and spectral information.

Comparison of Portable and Bench-Top Spectrometers for Mid-Infrared Diffuse Reflectance Measurements of Soils.

PubMed

Hutengs, Christopher; Ludwig, Bernard; Jung, András; Eisele, Andreas; Vohland, Michael

2018-03-27

Mid-infrared (MIR) spectroscopy has received widespread interest as a method to complement traditional soil analysis. Recently available portable MIR spectrometers additionally offer potential for on-site applications, given sufficient spectral data quality. We therefore tested the performance of the Agilent 4300 Handheld FTIR (DRIFT spectra) in comparison to a Bruker Tensor 27 bench-top instrument in terms of (i) spectral quality and measurement noise quantified by wavelet analysis; (ii) accuracy of partial least squares (PLS) calibrations for soil organic carbon (SOC), total nitrogen (N), pH, clay and sand content with a repeated cross-validation analysis; and (iii) key spectral regions for these soil properties identified with a Monte Carlo spectral variable selection approach. Measurements and multivariate calibrations with the handheld device were as good as or slightly better than Bruker equipped with a DRIFT accessory, but not as accurate as with directional hemispherical reflectance (DHR) data collected with an integrating sphere. Variations in noise did not markedly affect the accuracy of multivariate PLS calibrations. Identified key spectral regions for PLS calibrations provided a good match between Agilent and Bruker DHR data, especially for SOC and N. Our findings suggest that portable FTIR instruments are a viable alternative for MIR measurements in the laboratory and offer great potential for on-site applications.

A comparison of spectral mixture analysis an NDVI for ascertaining ecological variables

NASA Technical Reports Server (NTRS)

Wessman, Carol A.; Bateson, C. Ann; Curtiss, Brian; Benning, Tracy L.

1993-01-01

In this study, we compare the performance of spectral mixture analysis to the Normalized Difference Vegetation Index (NDVI) in detecting change in a grassland across topographically-induced nutrient gradients and different management schemes. The Konza Prairie Research Natural Area, Kansas, is a relatively homogeneous tallgrass prairie in which change in vegetation productivity occurs with respect to topographic positions in each watershed. The area is the site of long-term studies of the influence of fire and grazing on tallgrass production and was the site of the First ISLSCP (International Satellite Land Surface Climatology Project) Field Experiment (FIFE) from 1987 to 1989. Vegetation indices such as NDVI are commonly used with imagery collected in few (less than 10) spectral bands. However, the use of only two bands (e.g. NDVI) does not adequately account for the complex of signals making up most surface reflectance. Influences from background spectral variation and spatial heterogeneity may confound the direct relationship with biological or biophysical variables. High dimensional multispectral data allows for the application position of techniques such as derivative analysis and spectral curve fitting, thereby increasing the probability of successfully modeling the reflectance from mixed surfaces. The higher number of bands permits unmixing of a greater number of surface components, separating the vegetation signal for further analyses relevant to biological variables.

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.

Can unaided non-linguistic measures predict cochlear implant candidacy?

PubMed Central

Shim, Hyun Joon; Won, Jong Ho; Moon, Il Joon; Anderson, Elizabeth S.; Drennan, Ward R.; McIntosh, Nancy E.; Weaver, Edward M.; Rubinstein, Jay T.

2014-01-01

Objective To determine if unaided, non-linguistic psychoacoustic measures can be effective in evaluating cochlear implant (CI) candidacy. Study Design Prospective split-cohort study including predictor development subgroup and independent predictor validation subgroup. Setting Tertiary referral center. Subjects Fifteen subjects (28 ears) with hearing loss were recruited from patients visiting the University of Washington Medical Center for CI evaluation. Methods Spectral-ripple discrimination (using a 13-dB modulation depth) and temporal modulation detection using 10- and 100-Hz modulation frequencies were assessed with stimuli presented through insert earphones. Correlations between performance for psychoacoustic tasks and speech perception tasks were assessed. Receiver operating characteristic (ROC) curve analysis was performed to estimate the optimal psychoacoustic score for CI candidacy evaluation in the development subgroup and then tested in an independent sample. Results Strong correlations were observed between spectral-ripple thresholds and both aided sentence recognition and unaided word recognition. Weaker relationships were found between temporal modulation detection and speech tests. ROC curve analysis demonstrated that the unaided spectral ripple discrimination shows a good sensitivity, specificity, positive predictive value, and negative predictive value compared to the current gold standard, aided sentence recognition. Conclusions Results demonstrated that the unaided spectral-ripple discrimination test could be a promising tool for evaluating CI candidacy. PMID:24901669

A filter spectrometer concept for facsimile cameras

NASA Technical Reports Server (NTRS)

Jobson, D. J.; Kelly, W. L., IV; Wall, S. D.

1974-01-01

A concept which utilizes interference filters and photodetector arrays to integrate spectrometry with the basic imagery function of a facsimile camera is described and analyzed. The analysis considers spectral resolution, instantaneous field of view, spectral range, and signal-to-noise ratio. Specific performance predictions for the Martian environment, the Viking facsimile camera design parameters, and a signal-to-noise ratio for each spectral band equal to or greater than 256 indicate the feasibility of obtaining a spectral resolution of 0.01 micrometers with an instantaneous field of view of about 0.1 deg in the 0.425 micrometers to 1.025 micrometers range using silicon photodetectors. A spectral resolution of 0.05 micrometers with an instantaneous field of view of about 0.6 deg in the 1.0 to 2.7 micrometers range using lead sulfide photodetectors is also feasible.

Snapshot hyperspectral imaging probe with principal component analysis and confidence ellipse for classification

NASA Astrophysics Data System (ADS)

Lim, Hoong-Ta; Murukeshan, Vadakke Matham

2017-06-01

Hyperspectral imaging combines imaging and spectroscopy to provide detailed spectral information for each spatial point in the image. This gives a three-dimensional spatial-spatial-spectral datacube with hundreds of spectral images. Probe-based hyperspectral imaging systems have been developed so that they can be used in regions where conventional table-top platforms would find it difficult to access. A fiber bundle, which is made up of specially-arranged optical fibers, has recently been developed and integrated with a spectrograph-based hyperspectral imager. This forms a snapshot hyperspectral imaging probe, which is able to form a datacube using the information from each scan. Compared to the other configurations, which require sequential scanning to form a datacube, the snapshot configuration is preferred in real-time applications where motion artifacts and pixel misregistration can be minimized. Principal component analysis is a dimension-reducing technique that can be applied in hyperspectral imaging to convert the spectral information into uncorrelated variables known as principal components. A confidence ellipse can be used to define the region of each class in the principal component feature space and for classification. This paper demonstrates the use of the snapshot hyperspectral imaging probe to acquire data from samples of different colors. The spectral library of each sample was acquired and then analyzed using principal component analysis. Confidence ellipse was then applied to the principal components of each sample and used as the classification criteria. The results show that the applied analysis can be used to perform classification of the spectral data acquired using the snapshot hyperspectral imaging probe.

Classification of Peronospora infected grapevine leaves with the use of hyperspectral imaging analysis

NASA Astrophysics Data System (ADS)

Serranti, S.; Bonifazi, G.; Luciani, V.; D'Aniello, L.

2017-05-01

The present work explores the possible utilization of hyperspectral devices, following a proximity based approach, for the diagnosis of Peronospora infection in the vineyards. It compares the performance of two hyperspectral cameras, characterized by different spectral acquisition ranges, in the identification of different levels of infection as detectable from the analysis of the leaf surface. For this purpose, healthy grapevine leaves and leaves affected by a different grade of Peronospora infection have been acquired in laboratory conditions using two different sensing devices: a Specim Imspector V10™ and a Specim Spectral Camera N17™ working in the region between 400-1000 nm and 1000-1700 nm, respectively. A Partial Least Squares Discriminant Analysis (PLS-DA) model has been built to perform the classification of healthy, infected and necrotic leaves.

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.

MR-guided dynamic PET reconstruction with the kernel method and spectral temporal basis functions

NASA Astrophysics Data System (ADS)

Novosad, Philip; Reader, Andrew J.

2016-06-01

Recent advances in dynamic positron emission tomography (PET) reconstruction have demonstrated that it is possible to achieve markedly improved end-point kinetic parameter maps by incorporating a temporal model of the radiotracer directly into the reconstruction algorithm. In this work we have developed a highly constrained, fully dynamic PET reconstruction algorithm incorporating both spectral analysis temporal basis functions and spatial basis functions derived from the kernel method applied to a co-registered T1-weighted magnetic resonance (MR) image. The dynamic PET image is modelled as a linear combination of spatial and temporal basis functions, and a maximum likelihood estimate for the coefficients can be found using the expectation-maximization (EM) algorithm. Following reconstruction, kinetic fitting using any temporal model of interest can be applied. Based on a BrainWeb T1-weighted MR phantom, we performed a realistic dynamic [18F]FDG simulation study with two noise levels, and investigated the quantitative performance of the proposed reconstruction algorithm, comparing it with reconstructions incorporating either spectral analysis temporal basis functions alone or kernel spatial basis functions alone, as well as with conventional frame-independent reconstruction. Compared to the other reconstruction algorithms, the proposed algorithm achieved superior performance, offering a decrease in spatially averaged pixel-level root-mean-square-error on post-reconstruction kinetic parametric maps in the grey/white matter, as well as in the tumours when they were present on the co-registered MR image. When the tumours were not visible in the MR image, reconstruction with the proposed algorithm performed similarly to reconstruction with spectral temporal basis functions and was superior to both conventional frame-independent reconstruction and frame-independent reconstruction with kernel spatial basis functions. Furthermore, we demonstrate that a joint spectral/kernel model can also be used for effective post-reconstruction denoising, through the use of an EM-like image-space algorithm. Finally, we applied the proposed algorithm to reconstruction of real high-resolution dynamic [11C]SCH23390 data, showing promising results.

MR-guided dynamic PET reconstruction with the kernel method and spectral temporal basis functions.

PubMed

Novosad, Philip; Reader, Andrew J

2016-06-21

Recent advances in dynamic positron emission tomography (PET) reconstruction have demonstrated that it is possible to achieve markedly improved end-point kinetic parameter maps by incorporating a temporal model of the radiotracer directly into the reconstruction algorithm. In this work we have developed a highly constrained, fully dynamic PET reconstruction algorithm incorporating both spectral analysis temporal basis functions and spatial basis functions derived from the kernel method applied to a co-registered T1-weighted magnetic resonance (MR) image. The dynamic PET image is modelled as a linear combination of spatial and temporal basis functions, and a maximum likelihood estimate for the coefficients can be found using the expectation-maximization (EM) algorithm. Following reconstruction, kinetic fitting using any temporal model of interest can be applied. Based on a BrainWeb T1-weighted MR phantom, we performed a realistic dynamic [(18)F]FDG simulation study with two noise levels, and investigated the quantitative performance of the proposed reconstruction algorithm, comparing it with reconstructions incorporating either spectral analysis temporal basis functions alone or kernel spatial basis functions alone, as well as with conventional frame-independent reconstruction. Compared to the other reconstruction algorithms, the proposed algorithm achieved superior performance, offering a decrease in spatially averaged pixel-level root-mean-square-error on post-reconstruction kinetic parametric maps in the grey/white matter, as well as in the tumours when they were present on the co-registered MR image. When the tumours were not visible in the MR image, reconstruction with the proposed algorithm performed similarly to reconstruction with spectral temporal basis functions and was superior to both conventional frame-independent reconstruction and frame-independent reconstruction with kernel spatial basis functions. Furthermore, we demonstrate that a joint spectral/kernel model can also be used for effective post-reconstruction denoising, through the use of an EM-like image-space algorithm. Finally, we applied the proposed algorithm to reconstruction of real high-resolution dynamic [(11)C]SCH23390 data, showing promising results.

Relationship between Auditory and Cognitive Abilities in Older Adults

PubMed Central

Sheft, Stanley

2015-01-01

Objective The objective was to evaluate the association of peripheral and central hearing abilities with cognitive function in older adults. Methods Recruited from epidemiological studies of aging and cognition at the Rush Alzheimer’s Disease Center, participants were a community-dwelling cohort of older adults (range 63–98 years) without diagnosis of dementia. The cohort contained roughly equal numbers of Black (n=61) and White (n=63) subjects with groups similar in terms of age, gender, and years of education. Auditory abilities were measured with pure-tone audiometry, speech-in-noise perception, and discrimination thresholds for both static and dynamic spectral patterns. Cognitive performance was evaluated with a 12-test battery assessing episodic, semantic, and working memory, perceptual speed, and visuospatial abilities. Results Among the auditory measures, only the static and dynamic spectral-pattern discrimination thresholds were associated with cognitive performance in a regression model that included the demographic covariates race, age, gender, and years of education. Subsequent analysis indicated substantial shared variance among the covariates race and both measures of spectral-pattern discrimination in accounting for cognitive performance. Among cognitive measures, working memory and visuospatial abilities showed the strongest interrelationship to spectral-pattern discrimination performance. Conclusions For a cohort of older adults without diagnosis of dementia, neither hearing thresholds nor speech-in-noise ability showed significant association with a summary measure of global cognition. In contrast, the two auditory metrics of spectral-pattern discrimination ability significantly contributed to a regression model prediction of cognitive performance, demonstrating association of central auditory ability to cognitive status using auditory metrics that avoided the confounding effect of speech materials. PMID:26237423

A wavelet and least square filter based spatial-spectral denoising approach of hyperspectral imagery

NASA Astrophysics Data System (ADS)

Li, Ting; Chen, Xiao-Mei; Chen, Gang; Xue, Bo; Ni, Guo-Qiang

2009-11-01

Noise reduction is a crucial step in hyperspectral imagery pre-processing. Based on sensor characteristics, the noise of hyperspectral imagery represents in both spatial and spectral domain. However, most prevailing denosing techniques process the imagery in only one specific domain, which have not utilized multi-domain nature of hyperspectral imagery. In this paper, a new spatial-spectral noise reduction algorithm is proposed, which is based on wavelet analysis and least squares filtering techniques. First, in the spatial domain, a new stationary wavelet shrinking algorithm with improved threshold function is utilized to adjust the noise level band-by-band. This new algorithm uses BayesShrink for threshold estimation, and amends the traditional soft-threshold function by adding shape tuning parameters. Comparing with soft or hard threshold function, the improved one, which is first-order derivable and has a smooth transitional region between noise and signal, could save more details of image edge and weaken Pseudo-Gibbs. Then, in the spectral domain, cubic Savitzky-Golay filter based on least squares method is used to remove spectral noise and artificial noise that may have been introduced in during the spatial denoising. Appropriately selecting the filter window width according to prior knowledge, this algorithm has effective performance in smoothing the spectral curve. The performance of the new algorithm is experimented on a set of Hyperion imageries acquired in 2007. The result shows that the new spatial-spectral denoising algorithm provides more significant signal-to-noise-ratio improvement than traditional spatial or spectral method, while saves the local spectral absorption features better.

Spectroradiometric calibration of the Thematic Mapper and Multispectral Scanner system. [White Sands, New Mexico

NASA Technical Reports Server (NTRS)

Palmer, J. M. (Principal Investigator); Slater, P. N.

1984-01-01

The newly built Caste spectropolarimeters gave satisfactory performance during tests in the solar radiometer and helicopter modes. A bandwidth normalization technique based on analysis of the moments of the spectral responsivity curves was used to analyze the spectral bands of the MSS and TM subsystems of LANDSAT 4 and 5 satellites. Results include the effective wavelength, the bandpass, the wavelength limits, and the normalized responsivity for each spectral channel. Temperature coefficients for TM PF channel 6 were also derived. The moments normalization method used yields sensor parameters whose derivation is independent of source characteristics (i.e., incident solar spectral irradiance, atmospheric transmittance, or ground reflectance). The errors expected using these parameters are lower than those expected using other normalization methods.

Dimensionality-varied deep convolutional neural network for spectral-spatial classification of hyperspectral data

NASA Astrophysics Data System (ADS)

Qu, Haicheng; Liang, Xuejian; Liang, Shichao; Liu, Wanjun

2018-01-01

Many methods of hyperspectral image classification have been proposed recently, and the convolutional neural network (CNN) achieves outstanding performance. However, spectral-spatial classification of CNN requires an excessively large model, tremendous computations, and complex network, and CNN is generally unable to use the noisy bands caused by water-vapor absorption. A dimensionality-varied CNN (DV-CNN) is proposed to address these issues. There are four stages in DV-CNN and the dimensionalities of spectral-spatial feature maps vary with the stages. DV-CNN can reduce the computation and simplify the structure of the network. All feature maps are processed by more kernels in higher stages to extract more precise features. DV-CNN also improves the classification accuracy and enhances the robustness to water-vapor absorption bands. The experiments are performed on data sets of Indian Pines and Pavia University scene. The classification performance of DV-CNN is compared with state-of-the-art methods, which contain the variations of CNN, traditional, and other deep learning methods. The experiment of performance analysis about DV-CNN itself is also carried out. The experimental results demonstrate that DV-CNN outperforms state-of-the-art methods for spectral-spatial classification and it is also robust to water-vapor absorption bands. Moreover, reasonable parameters selection is effective to improve classification accuracy.

Surface Composition of Trojan Asteroids from Thermal-Infrared Spectroscopy

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Reconstructing spectral cues for sound localization from responses to rippled noise stimuli.

PubMed

Van Opstal, A John; Vliegen, Joyce; Van Esch, Thamar

2017-01-01

Human sound localization in the mid-saggital plane (elevation) relies on an analysis of the idiosyncratic spectral shape cues provided by the head and pinnae. However, because the actual free-field stimulus spectrum is a-priori unknown to the auditory system, the problem of extracting the elevation angle from the sensory spectrum is ill-posed. Here we test different spectral localization models by eliciting head movements toward broad-band noise stimuli with randomly shaped, rippled amplitude spectra emanating from a speaker at a fixed location, while varying the ripple bandwidth between 1.5 and 5.0 cycles/octave. Six listeners participated in the experiments. From the distributions of localization responses toward the individual stimuli, we estimated the listeners' spectral-shape cues underlying their elevation percepts, by applying maximum-likelihood estimation. The reconstructed spectral cues resulted to be invariant to the considerable variation in ripple bandwidth, and for each listener they had a remarkable resemblance to the idiosyncratic head-related transfer functions (HRTFs). These results are not in line with models that rely on the detection of a single peak or notch in the amplitude spectrum, nor with a local analysis of first- and second-order spectral derivatives. Instead, our data support a model in which the auditory system performs a cross-correlation between the sensory input at the eardrum-auditory nerve, and stored representations of HRTF spectral shapes, to extract the perceived elevation angle.

Quantum walks with an anisotropic coin I: spectral theory

NASA Astrophysics Data System (ADS)

Richard, S.; Suzuki, A.; Tiedra de Aldecoa, R.

2018-02-01

We perform the spectral analysis of the evolution operator U of quantum walks with an anisotropic coin, which include one-defect models, two-phase quantum walks, and topological phase quantum walks as special cases. In particular, we determine the essential spectrum of U, we show the existence of locally U-smooth operators, we prove the discreteness of the eigenvalues of U outside the thresholds, and we prove the absence of singular continuous spectrum for U. Our analysis is based on new commutator methods for unitary operators in a two-Hilbert spaces setting, which are of independent interest.

JPSS-1 VIIRS version 2 at-launch relative spectral response characterization and performance

NASA Astrophysics Data System (ADS)

Moeller, Chris; Schwarting, Tom; McIntire, Jeff; Moyer, David I.; Zeng, Jinan

2016-09-01

The relative spectral response (RSR) characterization of the JPSS-1 VIIRS spectral bands has achieved "at launch" status in the VIIRS Data Analysis Working Group February 2016 Version 2 RSR release. The Version 2 release improves upon the June 2015 Version 1 release by including December 2014 NIST TSIRCUS spectral measurements of VIIRS VisNIR bands in the analysis plus correcting CO2 influence on the band M13 RSR. The T-SIRCUS based characterization is merged with the summer 2014 SpMA based characterization of VisNIR bands (Version 1 release) to yield a "fused" RSR for these bands, combining the strengths of the T-SIRCUS and the SpMA measurement systems. The M13 RSR is updated by applying a model-based correction to mitigate CO2 attenuation of the SpMA source signal that occurred during M13 spectral measurements. The Version 2 release carries forward the Version 1 RSR for those bands that were not updated (M8-M12, M14-M16A/B, I3-I5, DNBMGS). The Version 2 release includes band average (over all detectors and subsamples) RSR plus supporting RSR for each detector and subsample. The at-launch band average RSR have been used to populate Look-Up Tables supporting the sensor data record and environmental data record at-launch science products. Spectral performance metrics show that JPSS-1 VIIRS RSR are compliant on specifications with a few minor exceptions. The Version 2 release, which replaces the Version 1 release, is currently available on the password-protected NASA JPSS-1 eRooms under EAR99 control.

Analysis of Solar Spectral Irradiance Measurements from the SBUV/2-Series and the SSBUV Instruments

NASA Technical Reports Server (NTRS)

Cebula, Richard P.; DeLand, Matthew T.; Hilsenrath, Ernest

1997-01-01

During this period of performance, 1 March 1997 - 31 August 1997, the NOAA-11 SBUV/2 solar spectral irradiance data set was validated using both internal and external assessments. Initial quality checking revealed minor problems with the data (e.g. residual goniometric errors, that were manifest as differences between the two scans acquired each day). The sources of these errors were determined and the errors were corrected. Time series were constructed for selected wavelengths and the solar irradiance changes measured by the instrument were compared to a Mg II proxy-based model of short- and long-term solar irradiance variations. This analysis suggested that errors due to residual, uncorrected long-term instrument drift have been reduced to less than 1-2% over the entire 5.5 year NOAA-11 data record. Detailed statistical analysis was performed. This analysis, which will be documented in a manuscript now in preparation, conclusively demonstrates the evolution of solar rotation periodicity and strength during solar cycle 22.

freeQuant: A Mass Spectrometry Label-Free Quantification Software Tool for Complex Proteome Analysis.

PubMed

Deng, Ning; Li, Zhenye; Pan, Chao; Duan, Huilong

2015-01-01

Study of complex proteome brings forward higher request for the quantification method using mass spectrometry technology. In this paper, we present a mass spectrometry label-free quantification tool for complex proteomes, called freeQuant, which integrated quantification with functional analysis effectively. freeQuant consists of two well-integrated modules: label-free quantification and functional analysis with biomedical knowledge. freeQuant supports label-free quantitative analysis which makes full use of tandem mass spectrometry (MS/MS) spectral count, protein sequence length, shared peptides, and ion intensity. It adopts spectral count for quantitative analysis and builds a new method for shared peptides to accurately evaluate abundance of isoforms. For proteins with low abundance, MS/MS total ion count coupled with spectral count is included to ensure accurate protein quantification. Furthermore, freeQuant supports the large-scale functional annotations for complex proteomes. Mitochondrial proteomes from the mouse heart, the mouse liver, and the human heart were used to evaluate the usability and performance of freeQuant. The evaluation showed that the quantitative algorithms implemented in freeQuant can improve accuracy of quantification with better dynamic range.

Real time automatic detection of bearing fault in induction machine using kurtogram analysis.

PubMed

Tafinine, Farid; Mokrani, Karim

2012-11-01

A proposed signal processing technique for incipient real time bearing fault detection based on kurtogram analysis is presented in this paper. The kurtogram is a fourth-order spectral analysis tool introduced for detecting and characterizing non-stationarities in a signal. This technique starts from investigating the resonance signatures over selected frequency bands to extract the representative features. The traditional spectral analysis is not appropriate for non-stationary vibration signal and for real time diagnosis. The performance of the proposed technique is examined by a series of experimental tests corresponding to different bearing conditions. Test results show that this signal processing technique is an effective bearing fault automatic detection method and gives a good basis for an integrated induction machine condition monitor.

Compact hybrid solar simulator with the spectral match beyond class A

NASA Astrophysics Data System (ADS)

Baguckis, Artūras; Novičkovas, Algirdas; Mekys, Algirdas; Tamošiūnas, Vincas

2016-07-01

A compact hybrid solar simulator with the spectral match beyond class A is proposed. Six types of high-power light-emitting diodes (LEDs) and tungsten halogen lamps in total were employed to obtain spectral match with <25% deviation from the standardized one in twelve spectral ranges between 400 and 1100 nm. All spectral ranges were twice as narrow than required by IEC 60904-9 Ed.2.0 and ASTM E927-10(2015) standards. Nonuniformity of the irradiance was evaluated and <2% deviation from the average value of the irradiance (corresponding to A class nonuniformity) can be obtained for the area of >3-cm diameter. A theoretical analysis was performed to evaluate possible performance of our simulator in the case of GaInP/GaAs/GaInAsP/GaInAs four-junction tandem solar cells and AM1.5D (ASTM G173-03 standard) spectrum. Lack of ultraviolet radiation in comparison to standard spectrum leads to 6.94% reduction of short-circuit current, which could be remedied with 137% increase of the output from blue LEDs. Excess of infrared radiation from halogen lamps outside ranges specified by standards is expected to lead to ˜0.77% voltage increase.

The MEM of spectral analysis applied to L.O.D.

NASA Astrophysics Data System (ADS)

Fernandez, L. I.; Arias, E. F.

The maximum entropy method (MEM) has been widely applied for polar motion studies taking advantage of its performance on the management of complex time series. The authors used the algorithm of the MEM to estimate Cross Spectral function in order to compare interannual Length-of-Day (LOD) time series with Southern Oscillation Index (SOI) and Sea Surface Temperature (SST) series, which are close related to El Niño-Southern Oscillation (ENSO) events.

Post-analysis report on Chesapeake Bay data processing. [spectral analysis and recognition computer signature extension

NASA Technical Reports Server (NTRS)

Thomson, F.

1972-01-01

The additional processing performed on data collected over the Rhode River Test Site and Forestry Site in November 1970 is reported. The techniques and procedures used to obtain the processed results are described. Thermal data collected over three approximately parallel lines of the site were contoured, and the results color coded, for the purpose of delineating important scene constituents and to identify trees attacked by pine bark beetles. Contouring work and histogram preparation are reviewed and the important conclusions from the spectral analysis and recognition computer (SPARC) signature extension work are summarized. The SPARC setup and processing records are presented and recommendations are made for future data collection over the site.

Advances in Mid-Infrared Spectroscopy for Chemical Analysis

NASA Astrophysics Data System (ADS)

Haas, Julian; Mizaikoff, Boris

2016-06-01

Infrared spectroscopy in the 3-20 μm spectral window has evolved from a routine laboratory technique into a state-of-the-art spectroscopy and sensing tool by benefitting from recent progress in increasingly sophisticated spectra acquisition techniques and advanced materials for generating, guiding, and detecting mid-infrared (MIR) radiation. Today, MIR spectroscopy provides molecular information with trace to ultratrace sensitivity, fast data acquisition rates, and high spectral resolution catering to demanding applications in bioanalytics, for example, and to improved routine analysis. In addition to advances in miniaturized device technology without sacrificing analytical performance, selected innovative applications for MIR spectroscopy ranging from process analysis to biotechnology and medical diagnostics are highlighted in this review.

Factor analysis as a tool for spectral line component separation 21cm emission in the direction of L1780

NASA Technical Reports Server (NTRS)

Toth, L. V.; Mattila, K.; Haikala, L.; Balazs, L. G.

1992-01-01

The spectra of the 21cm HI radiation from the direction of L1780, a small high-galactic latitude dark/molecular cloud, were analyzed by multivariate methods. Factor analysis was performed on HI (21cm) spectra in order to separate the different components responsible for the spectral features. The rotated, orthogonal factors explain the spectra as a sum of radiation from the background (an extended HI emission layer), and from the L1780 dark cloud. The coefficients of the cloud-indicator factors were used to locate the HI 'halo' of the molecular cloud. Our statistically derived 'background' and 'cloud' spectral profiles, as well as the spatial distribution of the HI halo emission distribution were compared to the results of a previous study which used conventional methods analyzing nearly the same data set.

[Application of AOTF in spectral analysis. 3. Application of AOTF in atomic emission spectral analysis].

PubMed

Chen, Ze-yong; Peng, Rong-fei; Zhang, Zhan-xia

2002-06-01

An atomic emission spectrometer based on acousto-optic tunable filter (AOTF) was self-constructed and was used to evaluate its practical use in atomic emission analysis. The AOTF used was of model TEAF5-0.36-0.52-S (Brimrose, USA) and the frequency of the direct digital RF synthesizer ranges from 100 MHz to 200 MHz. ICP and PMT were used as light source and detector respectively. The software, written in Visual C++ and running on the Windows 98 platform, is of an utility program system having two data banks and multiwindows. The wavelength calibration was performed with 14 emission lines of Ca, Y, Li, Eu, Sr and Ba using a tenth-order polynomial for line fitting method. The absolute error of the peak position was less than 0.1 nm, and the peak deviation was only 0.04 nm as the PMT varied from 337.5 V to 412.5 V. The scanning emission spectra and the calibration curves of Ba, Y, Eu, Sc and Sr are presented. Their average correlation coefficient was 0.9991 and their detection limits were in the range of 0.051 to 0.97 micrograms.mL-1 respectively. The detection limit can be improved under optimized operating conditions. However, the spectral resolution is only 2.1 nm at the wavelength of 488 nm. Evidently, this poor spectral resolution would restrict the application of AOTF in atomic emission spectral analysis, unless an enhancing techniques is integrated in it.

Direct comparison of low- and mid-frequency Raman spectroscopy for quantitative solid-state pharmaceutical analysis.

PubMed

Lipiäinen, Tiina; Fraser-Miller, Sara J; Gordon, Keith C; Strachan, Clare J

2018-02-05

This study considers the potential of low-frequency (terahertz) Raman spectroscopy in the quantitative analysis of ternary mixtures of solid-state forms. Direct comparison between low-frequency and mid-frequency spectral regions for quantitative analysis of crystal form mixtures, without confounding sampling and instrumental variations, is reported for the first time. Piroxicam was used as a model drug, and the low-frequency spectra of piroxicam forms β, α2 and monohydrate are presented for the first time. These forms show clear spectral differences in both the low- and mid-frequency regions. Both spectral regions provided quantitative models suitable for predicting the mixture compositions using partial least squares regression (PLSR), but the low-frequency data gave better models, based on lower errors of prediction (2.7, 3.1 and 3.2% root-mean-square errors of prediction [RMSEP] values for the β, α2 and monohydrate forms, respectively) than the mid-frequency data (6.3, 5.4 and 4.8%, for the β, α2 and monohydrate forms, respectively). The better performance of low-frequency Raman analysis was attributed to larger spectral differences between the solid-state forms, combined with a higher signal-to-noise ratio. Copyright © 2017 Elsevier B.V. All rights reserved.

[State Recognition of Solid Fermentation Process Based on Near Infrared Spectroscopy with Adaboost and Spectral Regression Discriminant Analysis].

PubMed

Yu, Shuang; Liu, Guo-hai; Xia, Rong-sheng; Jiang, Hui

2016-01-01

In order to achieve the rapid monitoring of process state of solid state fermentation (SSF), this study attempted to qualitative identification of process state of SSF of feed protein by use of Fourier transform near infrared (FT-NIR) spectroscopy analysis technique. Even more specifically, the FT-NIR spectroscopy combined with Adaboost-SRDA-NN integrated learning algorithm as an ideal analysis tool was used to accurately and rapidly monitor chemical and physical changes in SSF of feed protein without the need for chemical analysis. Firstly, the raw spectra of all the 140 fermentation samples obtained were collected by use of Fourier transform near infrared spectrometer (Antaris II), and the raw spectra obtained were preprocessed by use of standard normal variate transformation (SNV) spectral preprocessing algorithm. Thereafter, the characteristic information of the preprocessed spectra was extracted by use of spectral regression discriminant analysis (SRDA). Finally, nearest neighbors (NN) algorithm as a basic classifier was selected and building state recognition model to identify different fermentation samples in the validation set. Experimental results showed as follows: the SRDA-NN model revealed its superior performance by compared with other two different NN models, which were developed by use of the feature information form principal component analysis (PCA) and linear discriminant analysis (LDA), and the correct recognition rate of SRDA-NN model achieved 94.28% in the validation set. In this work, in order to further improve the recognition accuracy of the final model, Adaboost-SRDA-NN ensemble learning algorithm was proposed by integrated the Adaboost and SRDA-NN methods, and the presented algorithm was used to construct the online monitoring model of process state of SSF of feed protein. Experimental results showed as follows: the prediction performance of SRDA-NN model has been further enhanced by use of Adaboost lifting algorithm, and the correct recognition rate of the Adaboost-SRDA-NN model achieved 100% in the validation set. The overall results demonstrate that SRDA algorithm can effectively achieve the spectral feature information extraction to the spectral dimension reduction in model calibration process of qualitative analysis of NIR spectroscopy. In addition, the Adaboost lifting algorithm can improve the classification accuracy of the final model. The results obtained in this work can provide research foundation for developing online monitoring instruments for the monitoring of SSF process.

Feasibility of UltraFast Doppler in Post-operative Evaluation of Hepatic Artery in Recipients following Liver Transplantation.

PubMed

Kim, Se-Young; Kim, Kyoung Won; Choi, Sang Hyun; Kwon, Jae Hyun; Song, Gi-Won; Kwon, Heon-Ju; Yun, Young Ju; Lee, Jeongjin; Lee, Sung-Gyu

2017-11-01

To determine the feasibility of using UltraFast Doppler in post-operative evaluation of the hepatic artery (HA) after liver transplantation (LT), we evaluated 283 simultaneous conventional and UltraFast Doppler sessions in 126 recipients over a 2-mo period after LT, using an Aixplorer scanner The Doppler indexes of the HA (peak systolic velocity [PSV], end-diastolic velocity [EDV], resistive index [RI] and systolic acceleration time [SAT]) by retrospective analysis of retrieved waves from UltraFast Doppler clips were compared with those obtained by conventional spectral Doppler. Correlation, performance in diagnosing the pathologic wave, examination time and reproducibility were evaluated. The PSV, EDV, RI and SAT of spectral and UltraFast Doppler measurements exhibited excellent correlation with favorable diagnostic performance. During the bedside examination, the mean time spent for UltraFast clip storing was significantly shorter than that for conventional Doppler US measurements. Both conventional and UltraFast Doppler exhibited good to excellent inter-analysis consistency. In conclusion, compared with conventional spectral Doppler, UltraFast Doppler values correlated excellently and yielded acceptable pathologic wave diagnostic performance with reduced examination time at the bedside and excellent reproducibility. Copyright © 2017 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Advanced signal processing analysis of laser-induced breakdown spectroscopy data for the discrimination of obsidian sources.

PubMed

Remus, Jeremiah J; Harmon, Russell S; Hark, Richard R; Haverstock, Gregory; Baron, Dirk; Potter, Ian K; Bristol, Samantha K; East, Lucille J

2012-03-01

Obsidian is a natural glass of volcanic origin and a primary resource used by indigenous peoples across North America for making tools. Geochemical studies of obsidian enhance understanding of artifact production and procurement and remain a priority activity within the archaeological community. Laser-induced breakdown spectroscopy (LIBS) is an analytical technique being examined as a means for identifying obsidian from different sources on the basis of its 'geochemical fingerprint'. This study tested whether two major California obsidian centers could be distinguished from other obsidian localities and the extent to which subsources could be recognized within each of these centers. LIBS data sets were collected in two different spectral bands (350±130 nm and 690±115 nm) using a Nd:YAG 1064 nm laser operated at ~23 mJ, a Czerny-Turner spectrograph with 0.2-0.3 nm spectral resolution and a high performance imaging charge couple device (ICCD) detector. Classification of the samples was performed using partial least-squares discriminant analysis (PLSDA), a common chemometric technique for performing statistical regression on high-dimensional data. Discrimination of samples from the Coso Volcanic Field, Bodie Hills, and other major obsidian areas in north-central California was possible with an accuracy of greater than 90% using either spectral band. © 2012 Optical Society of America

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

Shumway, R.H.; McQuarrie, A.D.

Robust statistical approaches to the problem of discriminating between regional earthquakes and explosions are developed. We compare linear discriminant analysis using descriptive features like amplitude and spectral ratios with signal discrimination techniques using the original signal waveforms and spectral approximations to the log likelihood function. Robust information theoretic techniques are proposed and all methods are applied to 8 earthquakes and 8 mining explosions in Scandinavia and to an event from Novaya Zemlya of unknown origin. It is noted that signal discrimination approaches based on discrimination information and Renyi entropy perform better in the test sample than conventional methods based onmore » spectral ratios involving the P and S phases. Two techniques for identifying the ripple-firing pattern for typical mining explosions are proposed and shown to work well on simulated data and on several Scandinavian earthquakes and explosions. We use both cepstral analysis in the frequency domain and a time domain method based on the autocorrelation and partial autocorrelation functions. The proposed approach strips off underlying smooth spectral and seasonal spectral components corresponding to the echo pattern induced by two simple ripple-fired models. For two mining explosions, a pattern is identified whereas for two earthquakes, no pattern is evident.« less

Automatic sub-pixel coastline extraction based on spectral mixture analysis using EO-1 Hyperion data

NASA Astrophysics Data System (ADS)

Hong, Zhonghua; Li, Xuesu; Han, Yanling; Zhang, Yun; Wang, Jing; Zhou, Ruyan; Hu, Kening

2018-06-01

Many megacities (such as Shanghai) are located in coastal areas, therefore, coastline monitoring is critical for urban security and urban development sustainability. A shoreline is defined as the intersection between coastal land and a water surface and features seawater edge movements as tides rise and fall. Remote sensing techniques have increasingly been used for coastline extraction; however, traditional hard classification methods are performed only at the pixel-level and extracting subpixel accuracy using soft classification methods is both challenging and time consuming due to the complex features in coastal regions. This paper presents an automatic sub-pixel coastline extraction method (ASPCE) from high-spectral satellite imaging that performs coastline extraction based on spectral mixture analysis and, thus, achieves higher accuracy. The ASPCE method consists of three main components: 1) A Water- Vegetation-Impervious-Soil (W-V-I-S) model is first presented to detect mixed W-V-I-S pixels and determine the endmember spectra in coastal regions; 2) The linear spectral mixture unmixing technique based on Fully Constrained Least Squares (FCLS) is applied to the mixed W-V-I-S pixels to estimate seawater abundance; and 3) The spatial attraction model is used to extract the coastline. We tested this new method using EO-1 images from three coastal regions in China: the South China Sea, the East China Sea, and the Bohai Sea. The results showed that the method is accurate and robust. Root mean square error (RMSE) was utilized to evaluate the accuracy by calculating the distance differences between the extracted coastline and the digitized coastline. The classifier's performance was compared with that of the Multiple Endmember Spectral Mixture Analysis (MESMA), Mixture Tuned Matched Filtering (MTMF), Sequential Maximum Angle Convex Cone (SMACC), Constrained Energy Minimization (CEM), and one classical Normalized Difference Water Index (NDWI). The results from the three test sites indicated that the proposed ASPCE method extracted coastlines more efficiently than did the compared methods, and its coastline extraction accuracy corresponded closely to the digitized coastline, with 0.39 pixels, 0.40 pixels, and 0.35 pixels in the three test regions, showing that the ASPCE method achieves an accuracy below 12.0 m (0.40 pixels). Moreover, in the quantitative accuracy assessment for the three test sites, the ASPCE method shows the best performance in coastline extraction, achieving a 0.35 pixel-level at the Bohai Sea, China test site. Therefore, the proposed ASPCE method can extract coastline more accurately than can the hard classification methods or other spectral unmixing methods.

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.

Illumination analysis of LAPAN's IR micro bolometer

NASA Astrophysics Data System (ADS)

Bustanul, A.; Irwan, P.; Andi M., T.

2016-10-01

We have since 2 years ago been doing a research in term of an IR Micrometer Bolometer which aims to fulfill our office, LAPAN, desire to put it as one of payloads into LAPAN's next micro satellite project, either at LAPAN A4 or at LAPAN A5. Due to the lack of experience on the subject, everything had been initiated by spectral radiance analysis adjusted by catastrophes sources in Indonesia, mainly wild fire (forest fire) and active volcano. Based on the result of the appropriate spectral radiance wavelength, 3.8 - 4 μm, and field of view (FOV), we, then, went through the further analysis, optical analysis. Focusing in illumination matter, the process was done by using Zemax software. Optical pass Interference and Stray light were two things that become our concern throughout the work. They could also be an evaluation of the performance optimization of illumination analysis of our optical design. The results, graphs, show that our design performance is close diffraction limited and the image blur of the geometrical produced by Lapan's IR Micro Bolometer lenses is in the pixel area range. Therefore, our optical design performance is relatively good and will produce image with high quality. In this paper, the Illumination analysis and process of LAPAN's Infra Red (IR) Micro Bolometer is presented.

Aging behavior of near atmospheric N2 ambient sputtered/patterned Au IR absorber thin films

NASA Astrophysics Data System (ADS)

Gaur, Surender P.; Kothari, Prateek; Rangra, Kamaljit; Kumar, Dinesh

2018-03-01

Near atmospheric N2 ambient sputtered Au thin films exhibit significant spectral absorptivity over medium to long wave infrared radiations. Thin films were found adequately robust for micropatterning using conventional photolithography and metal lift off processes. Since long term spectral absorptivity is major practical concern for Au blacks, this paper reports on aging behavior of near atmospheric Ar and Ar + N2 (1:1) ambient sputtered infrared absorber Au thin films. Comparative analysis on electrical, morphological and spectral absorption behavior of twenty-five weeks room temperature/vacuum aged Au infrared absorber thin films is performed. The Ar and Ar + N2 ambient sputtered Au thing films have shown anticipated consistency in their physical, electrical and spectral properties regardless the long term aging in this work.

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.

Polychromatic spectral pattern analysis of ultra-weak photon emissions from a human body.

PubMed

Kobayashi, Masaki; Iwasa, Torai; Tada, Mika

2016-06-01

Ultra-weak photon emission (UPE), often designated as biophoton emission, is generally observed in a wide range of living organisms, including human beings. This phenomenon is closely associated with reactive oxygen species (ROS) generated during normal metabolic processes and pathological states induced by oxidative stress. Application of UPE extracting the pathophysiological information has long been anticipated because of its potential non-invasiveness, facilitating its diagnostic use. Nevertheless, its weak intensity and UPE mechanism complexity hinder its use for practical applications. Spectroscopy is crucially important for UPE analysis. However, filter-type spectroscopy technique, used as a conventional method for UPE analysis, intrinsically limits its performance because of its monochromatic scheme. To overcome the shortcomings of conventional methods, the authors developed a polychromatic spectroscopy system for UPE spectral pattern analysis. It is based on a highly efficient lens systems and a transmission-type diffraction grating with a highly sensitive, cooled, charge-coupled-device (CCD) camera. Spectral pattern analysis of the human body was done for a fingertip using the developed system. The UPE spectrum covers the spectral range of 450-750nm, with a dominant emission region of 570-670nm. The primary peak is located in the 600-650nm region. Furthermore, application of UPE source exploration was demonstrated with the chemiluminescence spectrum of melanin and coexistence with oxidized linoleic acid. Copyright © 2016 Elsevier B.V. All rights reserved.

Does the Blazar Gamma-ray Spectrum Harden with Increasing Flux? - Analysis of Nine Years of EGRET Data

NASA Technical Reports Server (NTRS)

Nandikotkur, Giridhar; Jahoda, Keith M.; Hartman, R. C.; Mukherjee, R.; Sreekumar, P.; Boettcher, M.

2007-01-01

The Energetic Gamma Ray Experiment Telescope (EGRET) on the Compton Gamma Ray Observatory (CGRO) discovered gamma-ray emission from more than 67 blazars during its nine-year lifetime. We conducted an exhaustive search of the EGRET archives and selected all the blazars that were observed multiple times and were bright enough to enable a spectral analysis using standard powerlaw models. The sample consists of 18 flat-spectrum radio quasars (FSRQs), 6 low-frequency-peaked BL Lacs (LBLs) and 2 high-frequency-peaked BL Lacs (HBLs). We do not detect any clear pattern in'the variation of spectral index with flux. Some of the blazars do not show any statistical evidence for spectral variability. The spectrum hardens with increasing flux in a few cases. There is also evidence for a flux-hardness anticorrelation at lo\\v fluxes in five blazars. The well observed blazars (3C 279,3C 273, PKS 0528-i-134, PKS 1622-297, PKS 0208- 512) do not show any overall trend in the long-term spectral dependence on flux, but the sample shows a mixture of hard and soft states. We observed spectral hysteresis at weekly timescales in all the three FSRQs for which data from flares lasting for 3 approx. 4 weeks were available. All three sources show a counterclockwise rotation despite the widely different flux profiles. Hysteresis in the spectral index vs. flux space has never been observed in FSRQs in gamma-rays at weekly timescales. itre analyze the observed spectral behavior in the context of various inverse-Compton mechanisms believed to be responsible for emission in the EGRET energy range. Our analysis uses the EGRET skymaps that were regenerated to include the changes in performance during the mission.

Structural, spectral, NLO and MEP analysis of the [MgO2Ti2(OPri)6], [MgO2Ti2(OPri)2(acac)4] and [MgO2Ti2(OPri)2(bzac)4] by DFT method

NASA Astrophysics Data System (ADS)

Sayin, Koray; Karakaş, Duran

2015-06-01

Quantum chemical calculations are performed on [MgO2Ti2(OPri)6] and [MgO2Ti2(OPri)2(L)4] complexes. L is acetylacetonate (acac) and benzoylacetonate (bzac) anion. The crystal structures of these complexes have not been obtained as experimentally but optimized structures of these complexes are obtained as theoretically in this study. Universal force field (UFF) and DFT/B3LYP method are used to obtain optimized structures. Theoretical spectral analysis (IR, 1H and 13C NMR) is compared with their experimental values. A good agreement is found between experimental and theoretical spectral analysis. These results mean that the optimized structures of mentioned complexes are appropriate. Additionally, the active sites of mentioned complexes are determined by molecular electrostatic potential (MEP) diagrams and non-linear optical (NLO) properties are investigated.

Groupwise shape analysis of the hippocampus using spectral matching

NASA Astrophysics Data System (ADS)

Shakeri, Mahsa; Lombaert, Hervé; Lippé, Sarah; Kadoury, Samuel

2014-03-01

The hippocampus is a prominent subcortical feature of interest in many neuroscience studies. Its subtle morphological changes often predicate illnesses, including Alzheimer's, schizophrenia or epilepsy. The precise location of structural differences requires a reliable correspondence between shapes across a population. In this paper, we propose an automated method for groupwise hippocampal shape analysis based on a spectral decomposition of a group of shapes to solve the correspondence problem between sets of meshes. The framework generates diffeomorphic correspondence maps across a population, which enables us to create a mean shape. Morphological changes are then located between two groups of subjects. The performance of the proposed method was evaluated on a dataset of 42 hippocampus shapes and compared with a state-of-the-art structural shape analysis approach, using spherical harmonics. Difference maps between mean shapes of two test groups demonstrates that the two approaches showed results with insignificant differences, while Gaussian curvature measures calculated between matched vertices showed a better fit and reduced variability with spectral matching.

Recovery of a spectrum based on a compressive-sensing algorithm with weighted principal component analysis

NASA Astrophysics Data System (ADS)

Dafu, Shen; Leihong, Zhang; Dong, Liang; Bei, Li; Yi, Kang

2017-07-01

The purpose of this study is to improve the reconstruction precision and better copy the color of spectral image surfaces. A new spectral reflectance reconstruction algorithm based on an iterative threshold combined with weighted principal component space is presented in this paper, and the principal component with weighted visual features is the sparse basis. Different numbers of color cards are selected as the training samples, a multispectral image is the testing sample, and the color differences in the reconstructions are compared. The channel response value is obtained by a Mega Vision high-accuracy, multi-channel imaging system. The results show that spectral reconstruction based on weighted principal component space is superior in performance to that based on traditional principal component space. Therefore, the color difference obtained using the compressive-sensing algorithm with weighted principal component analysis is less than that obtained using the algorithm with traditional principal component analysis, and better reconstructed color consistency with human eye vision is achieved.

Sensor performance analysis

NASA Technical Reports Server (NTRS)

Montgomery, H. E.; Ostrow, H.; Ressler, G. M.

1990-01-01

The theory is described and the equations required to design are developed and the performance of electro-optical sensor systems that operate from the visible through the thermal infrared spectral regions are analyzed. Methods to compute essential optical and detector parameters, signal-to-noise ratio, MTF, and figures of merit such as NE delta rho and NE delta T are developed. A set of atmospheric tables are provided to determine scene radiance in the visible spectral region. The Planck function is used to determine radiance in the infrared. The equations developed were incorporated in a spreadsheet so that a wide variety of sensor studies can be rapidly and efficiently conducted.

Statistical Investigation of Supersonic Downflows in the Transition Region above Sunspots

NASA Astrophysics Data System (ADS)

Samanta, Tanmoy; Tian, Hui; Prasad Choudhary, Debi

2018-06-01

Downflows at supersonic speeds have been observed in the transition region (TR) above sunspots for more than three decades. These downflows are often seen in different TR spectral lines above sunspots. We have performed a statistical investigation of these downflows using a large sample that was missing previously. The Interface Region Imaging Spectrograph (IRIS) has provided a wealth of observational data of sunspots at high spatial and spectral resolutions in the past few years. We have identified 60 data sets obtained with IRIS raster scans. Using an automated code, we identified the locations of strong downflows within these sunspots. We found that around 80% of our sample shows supersonic downflows in the Si IV 1403 Å line. These downflows mostly appear in the penumbral regions, though some of them are found in the umbrae. We also found that almost half of these downflows show signatures in chromospheric lines. Furthermore, a detailed spectral analysis was performed by selecting a small spectral window containing the O IV 1400/1401 Å and Si IV 1403 Å lines. Six Gaussian functions were simultaneously fitted to these three spectral lines and their satellite lines associated with the supersonic downflows. We calculated the intensity, Doppler velocity, and line width for these lines. Using the O IV 1400/1401 Å line ratio, we find that the downflow components are around one order of magnitude less dense than the regular components. Results from our statistical analysis suggest that these downflows may originate from the corona and that they are independent of the background TR plasma.

Customized Consensus Spectral Library Building for Untargeted Quantitative Metabolomics Analysis with Data Independent Acquisition Mass Spectrometry and MetaboDIA Workflow.

PubMed

Chen, Gengbo; Walmsley, Scott; Cheung, Gemmy C M; Chen, Liyan; Cheng, Ching-Yu; Beuerman, Roger W; Wong, Tien Yin; Zhou, Lei; Choi, Hyungwon

2017-05-02

Data independent acquisition-mass spectrometry (DIA-MS) coupled with liquid chromatography is a promising approach for rapid, automatic sampling of MS/MS data in untargeted metabolomics. However, wide isolation windows in DIA-MS generate MS/MS spectra containing a mixed population of fragment ions together with their precursor ions. This precursor-fragment ion map in a comprehensive MS/MS spectral library is crucial for relative quantification of fragment ions uniquely representative of each precursor ion. However, existing reference libraries are not sufficient for this purpose since the fragmentation patterns of small molecules can vary in different instrument setups. Here we developed a bioinformatics workflow called MetaboDIA to build customized MS/MS spectral libraries using a user's own data dependent acquisition (DDA) data and to perform MS/MS-based quantification with DIA data, thus complementing conventional MS1-based quantification. MetaboDIA also allows users to build a spectral library directly from DIA data in studies of a large sample size. Using a marine algae data set, we show that quantification of fragment ions extracted with a customized MS/MS library can provide as reliable quantitative data as the direct quantification of precursor ions based on MS1 data. To test its applicability in complex samples, we applied MetaboDIA to a clinical serum metabolomics data set, where we built a DDA-based spectral library containing consensus spectra for 1829 compounds. We performed fragment ion quantification using DIA data using this library, yielding sensitive differential expression analysis.

Linear Spectral Analysis of Plume Emissions Using an Optical Matrix Processor

NASA Technical Reports Server (NTRS)

Gary, C. K.

1992-01-01

Plume spectrometry provides a means to monitor the health of a burning rocket engine, and optical matrix processors provide a means to analyze the plume spectra in real time. By observing the spectrum of the exhaust plume of a rocket engine, researchers have detected anomalous behavior of the engine and have even determined the failure of some equipment before it would normally have been noticed. The spectrum of the plume is analyzed by isolating information in the spectrum about the various materials present to estimate what materials are being burned in the engine. Scientists at the Marshall Space Flight Center (MSFC) have implemented a high resolution spectrometer to discriminate the spectral peaks of the many species present in the plume. Researchers at the Stennis Space Center Demonstration Testbed Facility (DTF) have implemented a high resolution spectrometer observing a 1200-lb. thrust engine. At this facility, known concentrations of contaminants can be introduced into the burn, allowing for the confirmation of diagnostic algorithms. While the high resolution of the measured spectra has allowed greatly increased insight into the functioning of the engine, the large data flows generated limit the ability to perform real-time processing. The use of an optical matrix processor and the linear analysis technique described below may allow for the detailed real-time analysis of the engine's health. A small optical matrix processor can perform the required mathematical analysis both quicker and with less energy than a large electronic computer dedicated to the same spectral analysis routine.

Rapid screening of guar gum using portable Raman spectral identification methods.

PubMed

Srivastava, Hirsch K; Wolfgang, Steven; Rodriguez, Jason D

2016-01-25

Guar gum is a well-known inactive ingredient (excipient) used in a variety of oral pharmaceutical dosage forms as a thickener and stabilizer of suspensions and as a binder of powders. It is also widely used as a food ingredient in which case alternatives with similar properties, including chemically similar gums, are readily available. Recent supply shortages and price fluctuations have caused guar gum to come under increasing scrutiny for possible adulteration by substitution of cheaper alternatives. One way that the U.S. FDA is attempting to screen pharmaceutical ingredients at risk for adulteration or substitution is through field-deployable spectroscopic screening. Here we report a comprehensive approach to evaluate two field-deployable Raman methods--spectral correlation and principal component analysis--to differentiate guar gum from other gums. We report a comparison of the sensitivity of the spectroscopic screening methods with current compendial identification tests. The ability of the spectroscopic methods to perform unambiguous identification of guar gum compared to other gums makes them an enhanced surveillance alternative to the current compendial identification tests, which are largely subjective in nature. Our findings indicate that Raman spectral identification methods perform better than compendial identification methods and are able to distinguish guar gum from other gums with 100% accuracy for samples tested by spectral correlation and principal component analysis. Published by Elsevier B.V.

Continous Monitoring of Melt Composition

NASA Technical Reports Server (NTRS)

Frazer, R. E.; Andrews, T. W.

1984-01-01

Compositions of glasses and alloys analyzed and corrected in real time. Spectral analysis and temperature measurement performed simultaneously on molten material in container, such as open-hearth furnace, crucible or tank of continuous furnace. Speed of analysis makes it possible to quickly measure concentration of volatile elements depleted by prolonged heating.

Processing TES Level-1B Data

NASA Technical Reports Server (NTRS)

DeBaca, Richard C.; Sarkissian, Edwin; Madatyan, Mariyetta; Shepard, Douglas; Gluck, Scott; Apolinski, Mark; McDuffie, James; Tremblay, Dennis

2006-01-01

TES L1B Subsystem is a computer program that performs several functions for the Tropospheric Emission Spectrometer (TES). The term "L1B" (an abbreviation of "level 1B"), refers to data, specific to the TES, on radiometric calibrated spectral radiances and their corresponding noise equivalent spectral radiances (NESRs), plus ancillary geolocation, quality, and engineering data. The functions performed by TES L1B Subsystem include shear analysis, monitoring of signal levels, detection of ice build-up, and phase correction and radiometric and spectral calibration of TES target data. Also, the program computes NESRs for target spectra, writes scientific TES level-1B data to hierarchical- data-format (HDF) files for public distribution, computes brightness temperatures, and quantifies interpixel signal variability for the purpose of first-order cloud and heterogeneous land screening by the level-2 software summarized in the immediately following article. This program uses an in-house-developed algorithm, called "NUSRT," to correct instrument line-shape factors.

Investigation of computational and spectral analysis methods for aeroacoustic wave propagation

NASA Technical Reports Server (NTRS)

Vanel, Florence O.

1995-01-01

Most computational fluid dynamics (CFD) schemes are not adequately accurate for solving aeroacoustics problems, which have wave amplitudes several orders of magnitude smaller yet with frequencies larger than the flow field variations generating the sound. Hence, a computational aeroacoustics (CAA) algorithm should have minimal dispersion and dissipation features. A dispersion relation preserving (DRP) scheme is, therefore, applied to solve the linearized Euler equations in order to simulate the propagation of three types of waves, namely: acoustic, vorticity, and entropy waves. The scheme is derived using an optimization procedure to ensure that the numerical derivatives preserve the wave number and angular frequency of the partial differential equations being discretized. Consequently, simulated waves propagate with the correct wave speeds and exhibit their appropriate properties. A set of radiation and outflow boundary conditions, compatible with the DRP scheme and derived from the asymptotic solutions of the governing equations, are also implemented. Numerical simulations are performed to test the effectiveness of the DRP scheme and its boundary conditions. The computed solutions are shown to agree favorably with the exact solutions. The major restriction appears to be that the dispersion relations can be preserved only for waves with wave lengths longer than four or five spacings. The boundary conditions are found to be transparent to the outgoing disturbances. However, when the disturbance source is placed closer to a boundary, small acoustic reflections start appearing. CAA generates enormous amounts of temporal data which needs to be reduced to understand the physical problem being simulated. Spectral analysis is one approach that helps us in extracting information which often can not be easily interpreted in the time domain. Thus, three different methods for the spectral analysis of numerically generated aeroacoustic data are studied. First, the capabilities of two traditional methods for spectral analysis, namely, the Blackman-Tukey method and periodogram method, are compared in estimating the spectra of a simple-periodic process. The periodogram is then applied to analyze transitory-deterministic processes. Finally, these two methods are compared with a more recent method, referred as the Weighted-Overlapped-Segment-Averaging (WOSA) method, in estimating the spectra of a chaotic (random-like) process. From the demonstrative case for the spectral analyses of data generated by simple-periodic process, the periodogram method is found to give a better estimate of the steep-sloped spectra than the Blackman-Tukey method. Also, for this problem, the Hanning window is found to perform better with the periodogram method than with the Blackman-Tukey method. Finally, for the spectral analysis of data generated by the chaotic process, the periodogram method does not perform well, whereas, the WOSA and Blackman-Tukey methods give equivalently good results.

Ground-based Observation System Development for the Moon Hyper-spectral Imaging

NASA Astrophysics Data System (ADS)

Wang, Yang; Huang, Yu; Wang, Shurong; Li, Zhanfeng; Zhang, Zihui; Hu, Xiuqing; Zhang, Peng

2017-05-01

The Moon provides a suitable radiance source for on-orbit calibration of space-borne optical instruments. A ground-based observation system dedicated to the hyper-spectral radiometry of the Moon has been developed for improving and validating the current lunar model. The observation instrument using a dispersive imaging spectrometer is particularly designed for high-accuracy observations of the lunar radiance. The simulation and analysis of the push-broom mechanism is made in detail for lunar observations, and the automated tracking and scanning is well accomplished in different observational condition. A three-month series of hyper-spectral imaging experiments of the Moon have been performed in the wavelength range from 400 to 1000 nm near Lijiang Observatory (Yunnan, China) at phase angles -83°-87°. Preliminary results and data comparison are presented, and it shows the instrument performance and lunar observation capability of this system are well validated. Beyond previous measurements, this observation system provides the entire lunar disk images of continuous spectral coverage by adopting the push-broom mode with special scanning scheme and leads to the further research of lunar photometric model.

Low loss GaN waveguides at the visible spectral wavelengths for integrated photonics applications.

PubMed

Chen, Hong; Fu, Houqiang; Huang, Xuanqi; Zhang, Xiaodong; Yang, Tsung-Han; Montes, Jossue A; Baranowski, Izak; Zhao, Yuji

2017-12-11

We perform comprehensive studies on the fundamental loss mechanisms in III-nitride waveguides in the visible spectral region. Theoretical analysis shows that free carrier loss dominates for GaN under low photon power injection. When optical power increases, the two photon absorption loss becomes important and eventually dominates when photon energy above half-bandgap of GaN. When the dimensions of the waveguides reduce, the sidewall scattering loss will start to dominate. To verify the theoretical results, a high performance GaN-on-sapphire waveguide was fabricated and characterized. Experimental results are consistent with the theoretical findings, showing that under high power injection the optical loss changed significantly for GaN waveguides. A low optical loss ~2 dB/cm was achieved on the GaN waveguide, which is the lowest value ever reported for the visible spectral range. The results and fabrication processes developed in this work pave the way for the development of III-nitride integrated photonics in the visible and potentially ultraviolet spectral range for nonlinear optics and quantum photonics applications.

Effectiveness of Spectral Similarity Measures to Develop Precise Crop Spectra for Hyperspectral Data Analysis

NASA Astrophysics Data System (ADS)

Chauhan, H.; Krishna Mohan, B.

2014-11-01

The present study was undertaken with the objective to check effectiveness of spectral similarity measures to develop precise crop spectra from the collected hyperspectral field spectra. In Multispectral and Hyperspectral remote sensing, classification of pixels is obtained by statistical comparison (by means of spectral similarity) of known field or library spectra to unknown image spectra. Though these algorithms are readily used, little emphasis has been placed on use of various spectral similarity measures to select precise crop spectra from the set of field spectra. Conventionally crop spectra are developed after rejecting outliers based only on broad-spectrum analysis. Here a successful attempt has been made to develop precise crop spectra based on spectral similarity. As unevaluated data usage leads to uncertainty in the image classification, it is very crucial to evaluate the data. Hence, notwithstanding the conventional method, the data precision has been performed effectively to serve the purpose of the present research work. The effectiveness of developed precise field spectra was evaluated by spectral discrimination measures and found higher discrimination values compared to spectra developed conventionally. Overall classification accuracy for the image classified by field spectra selected conventionally is 51.89% and 75.47% for the image classified by field spectra selected precisely based on spectral similarity. KHAT values are 0.37, 0.62 and Z values are 2.77, 9.59 for image classified using conventional and precise field spectra respectively. Reasonable higher classification accuracy, KHAT and Z values shows the possibility of a new approach for field spectra selection based on spectral similarity measure.

Reconstructing spectral cues for sound localization from responses to rippled noise stimuli

PubMed Central

Vliegen, Joyce; Van Esch, Thamar

2017-01-01

Human sound localization in the mid-saggital plane (elevation) relies on an analysis of the idiosyncratic spectral shape cues provided by the head and pinnae. However, because the actual free-field stimulus spectrum is a-priori unknown to the auditory system, the problem of extracting the elevation angle from the sensory spectrum is ill-posed. Here we test different spectral localization models by eliciting head movements toward broad-band noise stimuli with randomly shaped, rippled amplitude spectra emanating from a speaker at a fixed location, while varying the ripple bandwidth between 1.5 and 5.0 cycles/octave. Six listeners participated in the experiments. From the distributions of localization responses toward the individual stimuli, we estimated the listeners’ spectral-shape cues underlying their elevation percepts, by applying maximum-likelihood estimation. The reconstructed spectral cues resulted to be invariant to the considerable variation in ripple bandwidth, and for each listener they had a remarkable resemblance to the idiosyncratic head-related transfer functions (HRTFs). These results are not in line with models that rely on the detection of a single peak or notch in the amplitude spectrum, nor with a local analysis of first- and second-order spectral derivatives. Instead, our data support a model in which the auditory system performs a cross-correlation between the sensory input at the eardrum-auditory nerve, and stored representations of HRTF spectral shapes, to extract the perceived elevation angle. PMID:28333967

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

NASA Astrophysics Data System (ADS)

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

2016-03-01

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

Ventilatory thresholds determined from HRV: comparison of 2 methods in obese adolescents.

PubMed

Quinart, S; Mourot, L; Nègre, V; Simon-Rigaud, M-L; Nicolet-Guénat, M; Bertrand, A-M; Meneveau, N; Mougin, F

2014-03-01

The development of personalised training programmes is crucial in the management of obesity. We evaluated the ability of 2 heart rate variability analyses to determine ventilatory thresholds (VT) in obese adolescents. 20 adolescents (mean age 14.3±1.6 years and body mass index z-score 4.2±0.1) performed an incremental test to exhaustion before and after a 9-month multidisciplinary management programme. The first (VT1) and second (VT2) ventilatory thresholds were identified by the reference method (gas exchanges). We recorded RR intervals to estimate VT1 and VT2 from heart rate variability using time-domain analysis and time-varying spectral-domain analysis. The coefficient correlations between thresholds were higher with spectral-domain analysis compared to time-domain analysis: Heart rate at VT1: r=0.91 vs. =0.66 and VT2: r=0.91 vs. =0.66; power at VT1: r=0.91 vs. =0.74 and VT2: r=0.93 vs. =0.78; spectral-domain vs. time-domain analysis respectively). No systematic bias in heart rate at VT1 and VT2 with standard deviations <6 bpm were found, confirming that spectral-domain analysis could replace the reference method for the detection of ventilatory thresholds. Furthermore, this technique is sensitive to rehabilitation and re-training, which underlines its utility in clinical practice. This inexpensive and non-invasive tool is promising for prescribing physical activity programs in obese adolescents. © Georg Thieme Verlag KG Stuttgart · New York.

Analysis of fusion neutron spectral widths in high-foot implosions at the National Ignition Facility

NASA Astrophysics Data System (ADS)

Grim, Gary; Caggiano, Joseph; Callahan, Debra; Casey, Daniel; Cerjan, Charles; Clark, Daniel; Tilo, Doeppner; Eckart, Mark; Field, John; Frenje, Lars; Gatu-Johnson, Maria; Hartouni, Edward; Hatarik, Robert; Hurricane, Omar; Kilkenny, Joseph; Knauer, James; Ma, Tammy; Mannion, Owen; Munro, David; Park, Hye-Sook; Sayre, Daniel; Spears, Brian; Yeamans, Charles

2015-11-01

We present the latest results of thermal temperature analyses of cryogenically layered deuterium-tritium implosions at the NIF using data from the ``High Foot'' campaign. Data from new analysis methods and interpreted in the context of new theoretical developments will be reported. These data will include DD and DT apparent ion temperatures, their uniformity with direction, inferred plasma thermal temperature, as well as the magnitude of non-thermal contributions to the spectral widths. Work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under contract DE-AC52-07NA27344.

RIBAVIRIN: The analysis of a polymorphic substance by LC-MS and FTIR spectroscopy

NASA Astrophysics Data System (ADS)

Machal, A. C.; Flurer, R. A.; Brueggemeyer, T. W.; Ellis, L. E.; Satzger, R. D.; Stewart, K. R.

1998-06-01

The FTIR laboratory often has the task of identifying unknown pharmaceuticals. This case involves unknown capsules received at the Forensic Chemistry Center. Through extensive searching of pharmaceutical data bases, it was concluded that the capsules might contain ribavirin, which is classified as an anti-viral agent. Mass spectral analysis (LC-MS) concluded that the capsules contained ribavirin; however, the FTIR results did not agree with the mass spectral results. Additional experiments were performed and the results demonstrate the capabilities of FTIR to discern differences between polymorphic forms of a substance, such as ribavirin, when other techniques are unable to provide this information.

The analysis on the relation between the compression method and the performance enhancement of MSC (Multi-Spectral Camera) image data

NASA Astrophysics Data System (ADS)

Yong, Sang-Soon; Ra, Sung-Woong

2007-10-01

Multi-Spectral Camera(MSC) is a main payload on the KOMPSAT-2 satellite to perform the earth remote sensing. The MSC instrument has one(1) channel for panchromatic imaging and four(4) channel for multi-spectral imaging covering the spectral range from 450nm to 900nm using TDI CCD Focal Plane Array (FPA). The instrument images the earth using a push-broom motion with a swath width of 15 km and a ground sample distance (GSD) of 1 m over the entire field of view (FOV) at altitude 685 Km. The instrument is designed to have an on-orbit operation duty cycle of 20% over the mission lifetime of 3 years with the functions of programmable gain/ offset and on-board image data compression/ storage. The compression method on KOMPSAT-2 MSC was selected and used to match EOS input rate and PDTS output data rate on MSC image data chain. At once the MSC performance was carefully handled to minimize any degradation so that it was analyzed and restored in KGS(KOMPSAT Ground Station) during LEOP and Cal./Val.(Calibration and Validation) phase. In this paper, on-orbit image data chain in MSC and image data processing on KGS including general MSC description is briefly described. The influences on image performance between on-board compression algorithms and between performance restoration methods in ground station are analyzed, and the relation between both methods is to be analyzed and discussed.

Thematic Mapper Data Quality and Performance Assessment in Renewable Resources/agriculture/remote Sensing

NASA Technical Reports Server (NTRS)

Bizzell, R. M.; Prior, H. L.

1985-01-01

Analysis of the early thematic mapper (TM) data indicate the TM sensor and associated ground processing are performing equal to the high expectations and within advertised specifications. The overall TM system with improved resolution, together with additional and more optimumly placed spectral bands shows much promise for benefits in future analysis activities. By selecting man-made features of known dimensions (e.g., highways, airfields, buildings, and isolated water bodies), an assessment was made of the TM performance relative to the specified 30-meter (98-foot) resolution. The increase of spatial resolution of TM (30 m) over MSS (80 M) appears to be significant not only in resolving spectrally distinct classes that were previously undefinable but also in distinguishing within-field variability. An Important result of the early TM evaluation and pre-TM analyses was the development of an integrated system to receive LANDSAT-4 TM (as well as MSS) data and analyze the data via various approaches.

LASER METHODS IN BIOLOGY: Optical anisotropy of fibrous biological tissues: analysis of the influence of structural properties

NASA Astrophysics Data System (ADS)

Zimnyakov, D. A.; Sinichkin, Yu P.; Ushakova, O. V.

2007-08-01

The results of theoretical analysis of the optical anisotropy of multiply scattering fibrillar biological tissues based on the model of an effective anisotropic medium are compared with the experimental in vivo birefringence data for the rat derma obtained earlier in spectral polarisation measurements of rat skin samples in the visible region. The disordered system of parallel dielectric cylinders embedded into an isotropic dielectric medium was considered as a model medium. Simulations were performed taking into account the influence of a partial mutual disordering of the bundles of collagen and elastin fibres in derma on birefringence in samples. The theoretical optical anisotropy averaged over the spectral interval 550-650 nm for the model medium with parameters corresponding to the structural parameters of derma is in good agreement with the results of spectral polarisation measurements of skin samples in the corresponding wavelength range.

Polarimetric Thomson scattering for high Te fusion plasmas

NASA Astrophysics Data System (ADS)

Giudicotti, L.

2017-11-01

Polarimetric Thomson scattering (TS) is a technique for the analysis of TS spectra in which the electron temperature Te is determined from the depolarization of the scattered radiation, a relativistic effect noticeable only in very hot (Te >= 10 keV) fusion plasmas. It has been proposed as a complementary technique to supplement the conventional spectral analysis in the ITER CPTS (Core Plasma Thomson Scattering) system for measurements in high Te, low ne plasma conditions. In this paper we review the characteristics of the depolarized TS radiation with special emphasis to the conditions of the ITER CPTS system and we describe a possible implementation of this diagnostic method suitable to significantly improve the performances of the conventional TS spectral analysis in the high Te range.

Utilization of all Spectral Channels of IASI for the Retrieval of the Atmospheric State

NASA Astrophysics Data System (ADS)

Del Bianco, S.; Cortesi, U.; Carli, B.

2010-12-01

The retrieval of atmospheric state parameters from broadband measurements acquired by high spectral resolution sensors, such as the Infrared Atmospheric Sounding Interferometer (IASI) onboard the Meteorological Operational (MetOp) platform, generally requires to deal with a prohibitively large number of spectral elements available from a single observation (8461 samples in the case of IASI, covering the 645-2760 cm-1 range with a resolution of 0.5 cm-1 and a spectral sampling of 0.25 cm-1). Most inversion algorithms developed for both operational and scientific analysis of IASI spectra perform a reduction of the data - typically based on channel selection, super-channel clustering or Principal Component Analysis (PCA) techniques - in order to handle the high dimensionality of the problem. Accordingly, simultaneous processing of all IASI channels received relatively low attention. Here we prove the feasibility of a retrieval approach exploiting all spectral channels of IASI, to extract information on water vapor, temperature and ozone profiles. This multi-target retrieval removes the systematic errors due to interfering parameters and makes the channel selection no longer necessary. The challenging computation is made possible by the use of a coarse spectral grid for the forward model calculation and by the abatement of the associated modeling errors through the use of a variance-covariance matrix of the residuals that takes into account all the forward model errors.

Discrimination of common Mediterranean plant species using field spectroradiometry

NASA Astrophysics Data System (ADS)

Manevski, Kiril; Manakos, Ioannis; Petropoulos, George P.; Kalaitzidis, Chariton

2011-12-01

Field spectroradiometry of land surface objects supports remote sensing analysis, facilitates the discrimination of vegetation species, and enhances the mapping efficiency. Especially in the Mediterranean, spectral discrimination of common vegetation types, such as phrygana and maquis species, remains a challenge. Both phrygana and maquis may be used as a direct indicator for grazing management, fire history and severity, and the state of the wider ecosystem equilibrium. This study aims to investigate the capability of field spectroradiometry supporting remote sensing analysis of the land cover of a characteristic Mediterranean area. Five common Mediterranean maquis and phrygana species were examined. Spectra acquisition was performed during an intensive field campaign deployed in spring 2010, supported by a novel platform MUFSPEM@MED (Mobile Unit for Field SPEctral Measurements at the MEDiterranean) for high canopy measurements. Parametric and non-parametric statistical tests have been applied to the continuum-removed reflectance of the species in the visible to shortwave infrared spectral range. Interpretation of the results indicated distinct discrimination between the studied species at specific spectral regions. Statistically significant wavelengths were principally found in both the visible and the near infrared regions of the electromagnetic spectrum. Spectral bands in the shortwave infrared demonstrated significant discrimination features for the examined species adapted to Mediterranean drought. All in all, results confirmed the prospect for a more accurate mapping of the species spatial distribution using remote sensing imagery coupled with in situ spectral information.

Analysis of JPSS J1 VIIRS Polarization Sensitivity Using the NIST T-SIRCUS

NASA Technical Reports Server (NTRS)

McIntire, Jeffrey W.; Young, James B.; Moyer, David; Waluschka, Eugene; Oudrari, Hassan; Xiong, Xiaoxiong

2015-01-01

The polarization sensitivity of the Joint Polar Satellite System (JPSS) J1 Visible Infrared Imaging Radiometer Suite (VIIRS) measured pre-launch using a broadband source was observed to be larger than expected for many reflective bands. Ray trace modeling predicted that the observed polarization sensitivity was the result of larger diattenuation at the edges of the focal plane filter spectral bandpass. Additional ground measurements were performed using a monochromatic source (the NIST T-SIRCUS) to input linearly polarized light at a number of wavelengths across the bandpass of two VIIRS spectral bands and two scan angles. This work describes the data processing, analysis, and results derived from the T-SIRCUS measurements, comparing them with broadband measurements. Results have shown that the observed degree of linear polarization, when weighted by the sensor's spectral response function, is generally larger on the edges and smaller in the center of the spectral bandpass, as predicted. However, phase angle changes in the center of the bandpass differ between model and measurement. Integration of the monochromatic polarization sensitivity over wavelength produced results consistent with the broadband source measurements, for all cases considered.

Signal noise ratio analysis and on-orbit performance estimation of a solar occultation Fourier transform spectrometer

NASA Astrophysics Data System (ADS)

Li, Bicen; Xu, Pengmei; Hou, Lizhou; Wang, Caiqin

2017-10-01

Taking the advantages of high spectral resolution, high sensitivity and wide spectral coverage, space borne Fourier transform infrared spectrometer (FTS) plays more and more important role in atmospheric composition sounding. The combination of solar occultation and FTS technique improves the sensitivity of instrument. To achieve both high spectral resolution and high signal to noise ratio (SNR), reasonable allocation and optimization for instrument parameters are the foundation and difficulty. The solar occultation FTS (SOFTS) is a high spectral resolution (0.03 cm-1) FTS operating from 2.4 to 13.3 μm (750-4100cm-1), which will determine the altitude profile information of typical 10-100km for temperature, pressure, and the volume mixing ratios for several dozens of atmospheric compositions. As key performance of SOFTS, SNR is crucially important to high accuracy retrieval of atmospheric composition, which is required to be no less than 100:1 at the radiance of 5800K blackbody. Based on the study of various parameters and its interacting principle, according to interference theory and operation principle of time modulated FTS, a simulation model of FTS SNR has been built, which considers satellite orbit, spectral radiometric features of sun and atmospheric composition, optical system, interferometer and its control system, measurement duration, detector sensitivity, noise of detector and electronic system and so on. According to the testing results of SNR at the illuminating of 1000 blackbody, the on-orbit SNR performance of SOFTS is estimated, which can meet the mission requirement.

Spectral multi-energy CT texture analysis with machine learning for tissue classification: an investigation using classification of benign parotid tumours as a testing paradigm.

PubMed

Al Ajmi, Eiman; Forghani, Behzad; Reinhold, Caroline; Bayat, Maryam; Forghani, Reza

2018-06-01

There is a rich amount of quantitative information in spectral datasets generated from dual-energy CT (DECT). In this study, we compare the performance of texture analysis performed on multi-energy datasets to that of virtual monochromatic images (VMIs) at 65 keV only, using classification of the two most common benign parotid neoplasms as a testing paradigm. Forty-two patients with pathologically proven Warthin tumour (n = 25) or pleomorphic adenoma (n = 17) were evaluated. Texture analysis was performed on VMIs ranging from 40 to 140 keV in 5-keV increments (multi-energy analysis) or 65-keV VMIs only, which is typically considered equivalent to single-energy CT. Random forest (RF) models were constructed for outcome prediction using separate randomly selected training and testing sets or the entire patient set. Using multi-energy texture analysis, tumour classification in the independent testing set had accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of 92%, 86%, 100%, 100%, and 83%, compared to 75%, 57%, 100%, 100%, and 63%, respectively, for single-energy analysis. Multi-energy texture analysis demonstrates superior performance compared to single-energy texture analysis of VMIs at 65 keV for classification of benign parotid tumours. • We present and validate a paradigm for texture analysis of DECT scans. • Multi-energy dataset texture analysis is superior to single-energy dataset texture analysis. • DECT texture analysis has high accura\\cy for diagnosis of benign parotid tumours. • DECT texture analysis with machine learning can enhance non-invasive diagnostic tumour evaluation.

Object-based assessment of burn severity in diseased forests using high-spatial and high-spectral resolution MASTER airborne imagery

NASA Astrophysics Data System (ADS)

Chen, Gang; Metz, Margaret R.; Rizzo, David M.; Dillon, Whalen W.; Meentemeyer, Ross K.

2015-04-01

Forest ecosystems are subject to a variety of disturbances with increasing intensities and frequencies, which may permanently change the trajectories of forest recovery and disrupt the ecosystem services provided by trees. Fire and invasive species, especially exotic disease-causing pathogens and insects, are examples of disturbances that together could pose major threats to forest health. This study examines the impacts of fire and exotic disease (sudden oak death) on forests, with an emphasis on the assessment of post-fire burn severity in a forest where trees have experienced three stages of disease progression pre-fire: early-stage (trees retaining dried foliage and fine twigs), middle-stage (trees losing fine crown fuels), and late-stage (trees falling down). The research was conducted by applying Geographic Object-Based Image Analysis (GEOBIA) to MASTER airborne images that were acquired immediately following the fire for rapid assessment and contained both high-spatial (4 m) and high-spectral (50 bands) resolutions. Although GEOBIA has gradually become a standard tool for analyzing high-spatial resolution imagery, high-spectral resolution data (dozens to hundreds of bands) can dramatically reduce computation efficiency in the process of segmentation and object-based variable extraction, leading to complicated variable selection for succeeding modeling. Hence, we also assessed two widely used band reduction algorithms, PCA (principal component analysis) and MNF (minimum noise fraction), for the delineation of image objects and the subsequent performance of burn severity models using either PCA or MNF derived variables. To increase computation efficiency, only the top 5 PCA and MNF and top 10 PCA and MNF components were evaluated, which accounted for 10% and 20% of the total number of the original 50 spectral bands, respectively. Results show that if no band reduction was applied the models developed for the three stages of disease progression had relatively similar performance, where both spectral responses and texture contributed to burn assessments. However, the application of PCA and MNF introduced much greater variation among models across the three stages. For the early-stage disease progression, neither band reduction algorithms improved or retained the accuracy of burn severity modeling (except for the use of 10 MNF components). Compared to the no-band-reduction scenario, band reduction led to a greater level of overestimation of low-degree burns and underestimation of medium-degree burns, suggesting that the spectral variation removed by PCA and MNF was vital for distinguishing between the spectral reflectance from disease-induced dried crowns (still retaining high structural complexity) and fire ash. For the middle-stage, both algorithms improved the model R2 values by 2-37%, while the late-stage models had comparable or better performance to those using the original 50 spectral bands. This could be explained by the loss of tree crowns enabling better signal penetration, thus leading to reduced spectral variation from canopies. Hence, spectral bands containing a high degree of random noise were correctly removed by the band reduction algorithms. Compared to the middle-stage, the late-stage forest stands were covered by large piles of fallen trees and branches, resulting in higher variability of MASTER imagery. The ability of band reduction to improve the model performance for these late-stage forest stands was reduced, because the valuable spectral variation representing the actual late-stage forest status was partially removed by both algorithms as noise. Our results indicate that PCA and MNF are promising for balancing computation efficiency and the performance of burn severity models in forest stands subject to the middle and late stages of sudden oak death disease progression. Compared to PCA, MNF dramatically reduced image spectral variation, generating larger image objects with less complexity of object shapes. Whereas, PCA-based models delivered superior performance in most evaluated cases suggesting that some key spectral variability contributing to the accuracy of burn severity models in diseased forests may have been removed together with true spectral noise through MNF transformations.

Component Cell-Based Restriction of Spectral Conditions and the Impact on CPV Module Power Rating

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

Muller, Matthew T; Steiner, Marc; Siefer, Gerald

One approach to consider the prevailing spectral conditions when performing CPV module power ratings according to the standard IEC 62670-3 is based on spectral matching ratios (SMRs) determined by the means of component cell sensors. In this work, an uncertainty analysis of the SMR approach is performed based on a dataset of spectral irradiances created with SMARTS2. Using these illumination spectra, the respective efficiencies of multijunction solar cells with different cell architectures are calculated. These efficiencies were used to analyze the influence of different component cell sensors and SMR filtering methods. The 3 main findings of this work are asmore » follows. First, component cells based on the lattice-matched triple-junction (LM3J) cell are suitable for restricting spectral conditions and are qualified for the standardized power rating of CPV modules - even if the CPV module is using multijunction cells other than LM3J. Second, a filtering of all 3 SMRs with +/-3.0% of unity results in the worst case scenario in an underestimation of -1.7% and overestimation of +2.4% compared to AM1.5d efficiency. Third, there is no benefit in matching the component cells to the module cell in respect to the measurement uncertainty.« less

Do slow orbital periodicities appear in the record of earth's magnetic reversals?

NASA Technical Reports Server (NTRS)

Stothers, Richard B.

1987-01-01

Time-series spectral analysis has been performed on the dates of geomagnetic reversals of the last 20 Myr BP and earlier. Possible evidence is found from the presence of high spectral peaks for two very long periodicities, 0.4 Myr and 1.3 Myr, that may be associated with slow variations of the earth's orbital eccentricity as predicted by Berger. However, statistical significance tests and a number of other arguments do not confirm the two detections.

Relationships Among Peripheral and Central Electrophysiological Measures of Spatial and Spectral Selectivity and Speech Perception in Cochlear Implant Users.

PubMed

Scheperle, Rachel A; Abbas, Paul J

2015-01-01

The ability to perceive speech is related to the listener's ability to differentiate among frequencies (i.e., spectral resolution). Cochlear implant (CI) users exhibit variable speech-perception and spectral-resolution abilities, which can be attributed in part to the extent of electrode interactions at the periphery (i.e., spatial selectivity). However, electrophysiological measures of peripheral spatial selectivity have not been found to correlate with speech perception. The purpose of this study was to evaluate auditory processing at the periphery and cortex using both simple and spectrally complex stimuli to better understand the stages of neural processing underlying speech perception. The hypotheses were that (1) by more completely characterizing peripheral excitation patterns than in previous studies, significant correlations with measures of spectral selectivity and speech perception would be observed, (2) adding information about processing at a level central to the auditory nerve would account for additional variability in speech perception, and (3) responses elicited with spectrally complex stimuli would be more strongly correlated with speech perception than responses elicited with spectrally simple stimuli. Eleven adult CI users participated. Three experimental processor programs (MAPs) were created to vary the likelihood of electrode interactions within each participant. For each MAP, a subset of 7 of 22 intracochlear electrodes was activated: adjacent (MAP 1), every other (MAP 2), or every third (MAP 3). Peripheral spatial selectivity was assessed using the electrically evoked compound action potential (ECAP) to obtain channel-interaction functions for all activated electrodes (13 functions total). Central processing was assessed by eliciting the auditory change complex with both spatial (electrode pairs) and spectral (rippled noise) stimulus changes. Speech-perception measures included vowel discrimination and the Bamford-Kowal-Bench Speech-in-Noise test. Spatial and spectral selectivity and speech perception were expected to be poorest with MAP 1 (closest electrode spacing) and best with MAP 3 (widest electrode spacing). Relationships among the electrophysiological and speech-perception measures were evaluated using mixed-model and simple linear regression analyses. All electrophysiological measures were significantly correlated with each other and with speech scores for the mixed-model analysis, which takes into account multiple measures per person (i.e., experimental MAPs). The ECAP measures were the best predictor. In the simple linear regression analysis on MAP 3 data, only the cortical measures were significantly correlated with speech scores; spectral auditory change complex amplitude was the strongest predictor. The results suggest that both peripheral and central electrophysiological measures of spatial and spectral selectivity provide valuable information about speech perception. Clinically, it is often desirable to optimize performance for individual CI users. These results suggest that ECAP measures may be most useful for within-subject applications when multiple measures are performed to make decisions about processor options. They also suggest that if the goal is to compare performance across individuals based on a single measure, then processing central to the auditory nerve (specifically, cortical measures of discriminability) should be considered.

Joint spatial-spectral hyperspectral image clustering using block-diagonal amplified affinity matrix

NASA Astrophysics Data System (ADS)

Fan, Lei; Messinger, David W.

2018-03-01

The large number of spectral channels in a hyperspectral image (HSI) produces a fine spectral resolution to differentiate between materials in a scene. However, difficult classes that have similar spectral signatures are often confused while merely exploiting information in the spectral domain. Therefore, in addition to spectral characteristics, the spatial relationships inherent in HSIs should also be considered for incorporation into classifiers. The growing availability of high spectral and spatial resolution of remote sensors provides rich information for image clustering. Besides the discriminating power in the rich spectrum, contextual information can be extracted from the spatial domain, such as the size and the shape of the structure to which one pixel belongs. In recent years, spectral clustering has gained popularity compared to other clustering methods due to the difficulty of accurate statistical modeling of data in high dimensional space. The joint spatial-spectral information could be effectively incorporated into the proximity graph for spectral clustering approach, which provides a better data representation by discovering the inherent lower dimensionality from the input space. We embedded both spectral and spatial information into our proposed local density adaptive affinity matrix, which is able to handle multiscale data by automatically selecting the scale of analysis for every pixel according to its neighborhood of the correlated pixels. Furthermore, we explored the "conductivity method," which aims at amplifying the block diagonal structure of the affinity matrix to further improve the performance of spectral clustering on HSI datasets.

A new analysis of heart rate variability in the assessment of fetal parasympathetic activity: An experimental study in a fetal sheep model.

PubMed

Garabedian, C; Champion, C; Servan-Schreiber, E; Butruille, L; Aubry, E; Sharma, D; Logier, R; Deruelle, P; Storme, L; Houfflin-Debarge, V; De Jonckheere, J

2017-01-01

Analysis of heart rate variability (HRV) is a recognized tool in the assessment of autonomic nervous system (ANS) activity. Indeed, both time and spectral analysis techniques enable us to obtain indexes that are related to the way the ANS regulates the heart rate. However, these techniques are limited in terms of the lack of thresholds of the numerical indexes, which is primarily due to high inter-subject variability. We proposed a new fetal HRV analysis method related to the parasympathetic activity of the ANS. The aim of this study was to evaluate the performance of our method compared to commonly used HRV analysis, with regard to i) the ability to detect changes in ANS activity and ii) inter-subject variability. This study was performed in seven sheep fetuses. In order to evaluate the sensitivity and specificity of our index in evaluating parasympathetic activity, we directly administered 2.5 mg intravenous atropine, to inhibit parasympathetic tone, and 5 mg propranolol to block sympathetic activity. Our index, as well as time analysis (root mean square of the successive differences; RMSSD) and spectral analysis (high frequency (HF) and low frequency (LF) spectral components obtained via fast Fourier transform), were measured before and after injection. Inter-subject variability was estimated by the coefficient of variance (%CV). In order to evaluate the ability of HRV parameters to detect fetal parasympathetic decrease, we also estimated the effect size for each HRV parameter before and after injections. As expected, our index, the HF spectral component, and the RMSSD were reduced after the atropine injection. Moreover, our index presented a higher effect size. The %CV was far lower for our index than for RMSSD, HF, and LF. Although LF decreased after propranolol administration, fetal stress index, RMSSD, and HF were not significantly different, confirming the fact that those indexes are specific to the parasympathetic nervous system. In conclusion, our method appeared to be effective in detecting parasympathetic inhibition. Moreover, inter-subject variability was much lower, and effect size higher, with our method compared to other HRV analysis methods.

Evaluation of spectral channels and wavelength regions for separability of agricultural cover types

NASA Technical Reports Server (NTRS)

Dejesusparada, N. (Principal Investigator); Kumar, R.

1977-01-01

The author has identified the following significant results. Multispectral scanner data in twelve spectral channels in the wavelength range of 0.4 to 11.7 microns acquired in the middle of July for three flightlines were analyzed by applying automatic pattern recognition techniques. The same analysis was performed for the data acquired in mid August, over the same three flightlines, to investigate the effect of time on the results. The effect of deletion of each spectral channel, as well as each wavelength region on P sub c, is given. Values of P sub c for all possible combinations of wavelength regions in the subsets of one to twelve spectral channels are also given. The overall values of P sub c were found to be greater for the data of mid August than the data from mid July.

Arc-welding quality assurance by means of embedded fiber sensor and spectral processing combining feature selection and neural networks

NASA Astrophysics Data System (ADS)

Mirapeix, J.; García-Allende, P. B.; Cobo, A.; Conde, O.; López-Higuera, J. M.

2007-07-01

A new spectral processing technique designed for its application in the on-line detection and classification of arc-welding defects is presented in this paper. A non-invasive fiber sensor embedded within a TIG torch collects the plasma radiation originated during the welding process. The spectral information is then processed by means of two consecutive stages. A compression algorithm is first applied to the data allowing real-time analysis. The selected spectral bands are then used to feed a classification algorithm, which will be demonstrated to provide an efficient weld defect detection and classification. The results obtained with the proposed technique are compared to a similar processing scheme presented in a previous paper, giving rise to an improvement in the performance of the monitoring system.

Iodine concentration: a new, important characteristic of the spot sign that predicts haematoma expansion.

PubMed

Fu, Fan; Sun, Shengjun; Liu, Liping; Li, Jianying; Su, Yaping; Li, Yingying

2018-04-19

The computed tomography angiography (CTA) spot sign is a validated predictor of haematoma expansion (HE) in spontaneous intracerebral haemorrhage (SICH). We investigated whether defining the iodine concentration (IC) inside the spot sign and the haematoma on Gemstone spectral imaging (GSI) would improve its sensitivity and specificity for predicting HE. From 2014 to 2016, we prospectively enrolled 65 SICH patients who underwent single-phase spectral CTA within 6 h. Logistic regression was performed to assess the risk factors for HE. The predictive performance of individual spot sign characteristics was examined via receiver operating characteristic (ROC) analysis. The spot sign was detected in 46.1% (30/65) of patients. ROC analysis indicated that IC inside the spot sign had the greatest area under the ROC curve for HE (0.858; 95% confidence interval, 0.727-0.989; p = 0.003). Multivariate analysis found that spot sign with higher IC (i.e. IC > 7.82 100 μg/ml) was an independent predictor of HE (odds ratio = 34.27; 95% confidence interval, 5.608-209.41; p < 0.001) with sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of 0.81, 0.75, 0.90 and 0.60, respectively; while the spot sign showed sensitivity, specificity, PPV and NPV of 0.81, 0.79, 0.73 and 0.86. Logistic regression analysis indicated that the IC in haematomas was independently associated with HE (odds ratio = 1.525; 95% confidence interval, 1.041-2.235; p = 0.030). ICs in haematoma and in spot sign were all independently associated with HE. IC analysis in spectral imaging may help to identify SICH patients for targeted haemostatic therapy. • Iodine concentration in spot sign and haematoma can predict haematoma expansion • Spectral imaging could measure the IC inside the spot sign and haematoma • IC in spot sign improved the positive predictive value (PPV) cf. CTA.

Improved quantitative analysis of spectra using a new method of obtaining derivative spectra based on a singular perturbation technique.

PubMed

Li, Zhigang; Wang, Qiaoyun; Lv, Jiangtao; Ma, Zhenhe; Yang, Linjuan

2015-06-01

Spectroscopy is often applied when a rapid quantitative analysis is required, but one challenge is the translation of raw spectra into a final analysis. Derivative spectra are often used as a preliminary preprocessing step to resolve overlapping signals, enhance signal properties, and suppress unwanted spectral features that arise due to non-ideal instrument and sample properties. In this study, to improve quantitative analysis of near-infrared spectra, derivatives of noisy raw spectral data need to be estimated with high accuracy. A new spectral estimator based on singular perturbation technique, called the singular perturbation spectra estimator (SPSE), is presented, and the stability analysis of the estimator is given. Theoretical analysis and simulation experimental results confirm that the derivatives can be estimated with high accuracy using this estimator. Furthermore, the effectiveness of the estimator for processing noisy infrared spectra is evaluated using the analysis of beer spectra. The derivative spectra of the beer and the marzipan are used to build the calibration model using partial least squares (PLS) modeling. The results show that the PLS based on the new estimator can achieve better performance compared with the Savitzky-Golay algorithm and can serve as an alternative choice for quantitative analytical applications.

Study on the influence of X-ray tube spectral distribution on the analysis of bulk samples and thin films: Fundamental parameters method and theoretical coefficient algorithms

NASA Astrophysics Data System (ADS)

Sitko, Rafał

2008-11-01

Knowledge of X-ray tube spectral distribution is necessary in theoretical methods of matrix correction, i.e. in both fundamental parameter (FP) methods and theoretical influence coefficient algorithms. Thus, the influence of X-ray tube distribution on the accuracy of the analysis of thin films and bulk samples is presented. The calculations are performed using experimental X-ray tube spectra taken from the literature and theoretical X-ray tube spectra evaluated by three different algorithms proposed by Pella et al. (X-Ray Spectrom. 14 (1985) 125-135), Ebel (X-Ray Spectrom. 28 (1999) 255-266), and Finkelshtein and Pavlova (X-Ray Spectrom. 28 (1999) 27-32). In this study, Fe-Cr-Ni system is selected as an example and the calculations are performed for X-ray tubes commonly applied in X-ray fluorescence analysis (XRF), i.e., Cr, Mo, Rh and W. The influence of X-ray tube spectra on FP analysis is evaluated when quantification is performed using various types of calibration samples. FP analysis of bulk samples is performed using pure-element bulk standards and multielement bulk standards similar to the analyzed material, whereas for FP analysis of thin films, the bulk and thin pure-element standards are used. For the evaluation of the influence of X-ray tube spectra on XRF analysis performed by theoretical influence coefficient methods, two algorithms for bulk samples are selected, i.e. Claisse-Quintin (Can. Spectrosc. 12 (1967) 129-134) and COLA algorithms (G.R. Lachance, Paper Presented at the International Conference on Industrial Inorganic Elemental Analysis, Metz, France, June 3, 1981) and two algorithms (constant and linear coefficients) for thin films recently proposed by Sitko (X-Ray Spectrom. 37 (2008) 265-272).

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.

A comparison of autonomous techniques for multispectral image analysis and classification

NASA Astrophysics Data System (ADS)

Valdiviezo-N., Juan C.; Urcid, Gonzalo; Toxqui-Quitl, Carina; Padilla-Vivanco, Alfonso

2012-10-01

Multispectral imaging has given place to important applications related to classification and identification of objects from a scene. Because of multispectral instruments can be used to estimate the reflectance of materials in the scene, these techniques constitute fundamental tools for materials analysis and quality control. During the last years, a variety of algorithms has been developed to work with multispectral data, whose main purpose has been to perform the correct classification of the objects in the scene. The present study introduces a brief review of some classical as well as a novel technique that have been used for such purposes. The use of principal component analysis and K-means clustering techniques as important classification algorithms is here discussed. Moreover, a recent method based on the min-W and max-M lattice auto-associative memories, that was proposed for endmember determination in hyperspectral imagery, is introduced as a classification method. Besides a discussion of their mathematical foundation, we emphasize their main characteristics and the results achieved for two exemplar images conformed by objects similar in appearance, but spectrally different. The classification results state that the first components computed from principal component analysis can be used to highlight areas with different spectral characteristics. In addition, the use of lattice auto-associative memories provides good results for materials classification even in the cases where some spectral similarities appears in their spectral responses.

Mapping invasive species and spectral mixture relationships with neotropical woody formations in southeastern Brazil

NASA Astrophysics Data System (ADS)

Amaral, Cibele H.; Roberts, Dar A.; Almeida, Teodoro I. R.; Souza Filho, Carlos R.

2015-10-01

Biological invasion substantially contributes to the increasing extinction rates of native vegetative species. The remote detection and mapping of invasive species is critical for environmental monitoring. This study aims to assess the performance of a Multiple Endmember Spectral Mixture Analysis (MESMA) applied to imaging spectroscopy data for mapping Dendrocalamus sp. (bamboo) and Pinus elliottii L. (slash pine), which are invasive plant species, in a Brazilian neotropical landscape within the tropical Brazilian savanna biome. The work also investigates the spectral mixture between these exotic species and the native woody formations, including woodland savanna, submontane and alluvial seasonal semideciduous forests (SSF). Visible to Shortwave Infrared (VSWIR) imaging spectroscopy data at one-meter spatial resolution were atmospherically corrected and subset into the different spectral ranges (VIS-NIR1: 530-919 nm; and NIR2-SWIR: 1141-2352 nm). The data were further normalized via continuum removal (CR). Multiple endmember selection methods, including Interactive Endmember Selection (IES), Endmember average root mean square error (EAR), Minimum average spectral angle (MASA) and Count-based (CoB) (collectively called EMC), were employed to create endmember libraries for the targeted vegetation classes. The performance of the MESMA was assessed at the pixel and crown scales. Statistically significant differences (α = 0.05) were observed between overall accuracies that were obtained at various spectral ranges. The infrared region (IR) was critical for detecting the vegetation classes using spectral data. The invasive species endmembers exhibited spectral patterns in the IR that were not observed in the native formations. Bamboo was characterized as having a high green vegetation (GV) fraction, lower non-photosynthetic vegetation (NPV) and a low shade fraction, while pine exhibited higher NPV and shade fractions. The invasive species showed a statistically significant larger number of spectra erroneously assigned to the woodland savanna class versus the alluvial and submontane SSF classes. Consequently, the invasive species tended to be overestimated, especially in the woodland savanna. Bamboo was best classified using the VSWIR(CR) data with the EMC endmember selection method (User's accuracy and Producer's accuracy = 98.11% and 72.22%, respectively). Pine was best classified using NIR2-SWIR(CR) data with the IES selected endmembers (97.06% and 62.26%, respectively). The results obtained during the two-endmember modeling were fully translated into the three-endmember unmixed images. The sub-pixel invasive species abundance analysis showed that MESMA performs well when unmixing at the pixel scale and for mapping invasive species fractions in a complex neotropical environment, at pixel and crown scales with 1-m spatial resolution data.

Spectral analysis-based risk score enables early prediction of mortality and cerebral performance in patients undergoing therapeutic hypothermia for ventricular fibrillation and comatose status

PubMed Central

Filgueiras-Rama, David; Calvo, Conrado J.; Salvador-Montañés, Óscar; Cádenas, Rosalía; Ruiz-Cantador, Jose; Armada, Eduardo; Rey, Juan Ramón; Merino, J.L.; Peinado, Rafael; Pérez-Castellano, Nicasio; Pérez-Villacastín, Julián; Quintanilla, Jorge G.; Jiménez, Santiago; Castells, Francisco; Chorro, Francisco J.; López-Sendón, J.L.; Berenfeld, Omer; Jalife, José; López de Sá, Esteban; Millet, José

2017-01-01

Background Early prognosis in comatose survivors after cardiac arrest due to ventricular fibrillation (VF) is unreliable, especially in patients undergoing mild hypothermia. We aimed at developing a reliable risk-score to enable early prediction of cerebral performance and survival. Methods Sixty-one out of 239 consecutive patients undergoing mild hypothermia after cardiac arrest, with eventual return of spontaneous circulation (ROSC), and comatose status on admission fulfilled the inclusion criteria. Background clinical variables, VF time and frequency domain fundamental variables were considered. The primary and secondary outcomes were a favorable neurological performance (FNP) during hospitalization and survival to hospital discharge, respectively. The predictive model was developed in a retrospective cohort (n=32; September 2006–September 2011, 48.5 ± 10.5 months of follow-up) and further validated in a prospective cohort (n = 29; October 2011–July 2013, 5 ± 1.8 months of follow-up). Results FNP was present in 16 (50.0%) and 21 patients (72.4%) in the retrospective and prospective cohorts, respectively. Seventeen (53.1%) and 21 patients (72.4%), respectively, survived to hospital discharge. Both outcomes were significantly associated (p < 0.001). Retrospective multivariate analysis provided a prediction model (sensitivity= 0.94, specificity = 1) that included spectral dominant frequency, derived power density and peak ratios between high and low frequency bands, and the number of shocks delivered before ROSC. Validation on the prospective cohort showed sensitivity = 0.88 and specificity = 0.91. A model-derived risk-score properly predicted 93% of FNP. Testing the model on follow-up showed a c-statistic ≥ 0.89. Conclusions A spectral analysis-based model reliably correlates time-dependent VF spectral changes with acute cerebral injury in comatose survivors undergoing mild hypothermia after cardiac arrest. PMID:25828128

Study of different operational modes of the IAP 2-port-DOAS instrument for atmospheric trace gases investigation during CINDI-2 campaign basing on residual noise analysis

NASA Astrophysics Data System (ADS)

Borovski, A.; Postylyakov, O.; Elokhov, A.; Bruchkovski, I.

2017-11-01

An instrument for measuring atmospheric trace gases by DOAS method using scattered solar radiation was developed in A.M.Obukhov IAP RAS. The instrument layout is based on the lab Shamrock 303i spectrograph supplemented by 2-port radiation input system employing optical fiber. Optical ports may be used with a telescope with fixed field of view or with a scanning MAX-DOAS unit. MAX-DOAS unit port will be used for investigation of gas contents and profiles in the low troposphere. In September 2016 the IAP instrument participated in the CINDI-2 campaign, held in the Netherlands. CINDI 2 (2nd Cabauw Intercomparison of Nitrogen Dioxide Measuring Instruments) involves about 40 instruments quasi-synchronously performing DOAS measurements of NO2 and other trace gases. During the campaign the instrument ports had telescopes A and B with similar field of view of about 0.3°. Telescope A was always directed to the zenith. Telescope B was directed at 5° elevation angle. Two gratings were installed in the spectrometer. They provide different spectral resolution (FWHM 0.4 and 0.8 nm respectively) and spectral window width ( 70 and 140 nm respectively). During CINDI-2 campaign we performed test measurements in UV and visible wavelength ranges to investigate instrument stability and retrieval errors of NO2 and HCHO contents. We perform the preliminary error analysis of retrieval of the NO2 and HCHO differential slant column densities using spectra measured in four modes of the instrument basing on residual noise analysis in this paper. It was found that rotation of grating turret does not significantly affected on quality of NO2 DSCD retrieval from spectra which measured in visible spectral region. Influence of grating turret rotation is much more significant for gas DSCD retrieval from spectra which measured in UV spectral region. Standard deviation of retrieval error points to presence of some systematic error.

Stochastic response analysis, order reduction, and output feedback controllers for flexible spacecraft

NASA Technical Reports Server (NTRS)

Hablani, H. B.

1985-01-01

Real disturbances and real sensors have finite bandwidths. The first objective of this paper is to incorporate this finiteness in the 'open-loop modal cost analysis' as applied to a flexible spacecraft. Analysis based on residue calculus shows that among other factors, significance of a mode depends on the power spectral density of disturbances and the response spectral density of sensors at the modal frequency. The second objective of this article is to compare performances of an optimal and a suboptimal output feedback controller, the latter based on 'minimum error excitation' of Kosut. Both the performances are found to be nearly the same, leading us to favor the latter technique because it entails only linear computations. Our final objective is to detect an instability due to truncated modes by representing them as a multiplicative and an additive perturbation in a nominal transfer function. In an example problem it is found that this procedure leads to a narrow range of permissible controller gains, and that it labels a wrong mode as a cause of instability. A free beam is used to illustrate the analysis in this work.

Comparative study of mobile Raman instrumentation for art analysis.

PubMed

Vandenabeele, P; Castro, K; Hargreaves, M; Moens, L; Madariaga, J M; Edwards, H G M

2007-04-04

In archaeometry, one of the main concerns is to extract information from an art object, without damaging it. Raman spectroscopy is being applied in this research field with recent developments in mobile instrumentation facilitating more routine analysis. This research paper evaluates the performances of five mobile Raman instruments (Renishaw RA100, Renishaw Portable Raman Analyser RX210, Ocean Optics RSL-1, Delta Nu Inspector Raman, Mobile Art Analyser--MArtA) in three different laboratories. A set of samples were collected, in order to obtain information on the spectral performances of the instruments including: spectral resolution, calibration, laser cut-off, the ability to record spectra of organic and inorganic pigments through varnish layers and on the possibilities to identify biomaterials. Spectra were recorded from predefined regions on a canvas painting to simulate the investigation of artworks and the capabilities to record spectra from hardly accessible areas was evaluated.

VHF command system study. [spectral analysis of GSFC VHF-PSK and VHF-FSK Command Systems

NASA Technical Reports Server (NTRS)

Gee, T. H.; Geist, J. M.

1973-01-01

Solutions are provided to specific problems arising in the GSFC VHF-PSK and VHF-FSK Command Systems in support of establishment and maintenance of Data Systems Standards. Signal structures which incorporate transmission on the uplink of a clock along with the PSK or FSK data are considered. Strategies are developed for allocating power between the clock and data, and spectral analyses are performed. Bit error probability and other probabilities pertinent to correct transmission of command messages are calculated. Biphase PCM/PM and PCM/FM are considered as candidate modulation techniques on the telemetry downlink, with application to command verification. Comparative performance of PCM/PM and PSK systems is given special attention, including implementation considerations. Gain in bit error performance due to coding is also considered.

Comparative Analysis of Normalised Difference Spectral Indices Derived from MODIS for Detecting Surface Water in Flooded Rice Cropping Systems

PubMed Central

Boschetti, Mirco; Nutini, Francesco; Manfron, Giacinto; Brivio, Pietro Alessandro; Nelson, Andrew

2014-01-01

Identifying managed flooding in paddy fields is commonly used in remote sensing to detect rice. Such flooding, followed by rapid vegetation growth, is a reliable indicator to discriminate rice. Spectral indices (SIs) are often used to perform this task. However, little work has been done on determining which spectral combination in the form of Normalised Difference Spectral Indices (NDSIs) is most appropriate for surface water detection or which thresholds are most robust to separate water from other surfaces in operational contexts. To address this, we conducted analyses on satellite and field spectral data from an agronomic experiment as well as on real farming situations with different soil and plant conditions. Firstly, we review and select NDSIs proposed in the literature, including a new combination of visible and shortwave infrared bands. Secondly, we analyse spectroradiometric field data and satellite data to evaluate mixed pixel effects. Thirdly, we analyse MODIS data and Landsat data at four sites in Europe and Asia to assess NDSI performance in real-world conditions. Finally, we test the performance of the NDSIs on MODIS temporal profiles in the four sites. We also compared the NDSIs against a combined index previously used for agronomic flood detection. Analyses suggest that NDSIs using MODIS bands 4 and 7, 1 and 7, 4 and 6 or 1 and 6 perform best. A common threshold for each NDSI across all sites was more appropriate than locally adaptive thresholds. In general, NDSIs that use band 7 have a negligible increase in Commission Error over those that use band 6 but are more sensitive to water presence in mixed land cover conditions typical of moderate spatial resolution analyses. The best performing NDSI is comparable to the combined index but with less variability in performance across sites, suggesting a more succinct and robust flood detection method. PMID:24586381

a Comparative Study of Alto Saxophone Reeds Through Spectral and Subjective Analyses.

NASA Astrophysics Data System (ADS)

Henderson, Caroline Blythe

The purpose of this study was to analyze six brands of cane reeds and five brands of synthetic reeds to determine the differences in tone quality produced by each. Spectral analysis was used to determine the individual reed which conformed most closely to the average profile of each brand. A panel of seven saxophone performers then presented their opinions of the each reed's tone quality upon hearing a live performance of an excerpt from Eugene Bozza's Aria for alto saxophone and piano performed on the reeds most representative of each brand. The evaluation form used by the judges included ten sets of bipolar adjectives: good-bad, harmonious-dissonant, clean-dirty, light-dark, pleasurable-painful, beautiful-ugly, strong-weak, complex -simple, masculine-feminine, and interesting-boring. The results indicated that the primary factors influencing the tone quality of a given reed were the strength of the overtones present regardless of their order and the dominance of either the fundamental or the first overtone. Although professional musicians normally hand-select their reeds for performance, this research based on both spectral and subjective analyses provides clear evidence for both musicians and music educators to refine and improve their reed selection process.

Development of a calibration equipment for spectrometer qualification

NASA Astrophysics Data System (ADS)

Michel, C.; Borguet, B.; Boueé, A.; Blain, P.; Deep, A.; Moreau, V.; François, M.; Maresi, L.; Myszkowiak, A.; Taccola, M.; Versluys, J.; Stockman, Y.

2017-09-01

With the development of new spectrometer concepts, it is required to adapt the calibration facilities to characterize correctly their performances. These spectro-imaging performances are mainly Modulation Transfer Function, spectral response, resolution and registration; polarization, straylight and radiometric calibration. The challenge of this calibration development is to achieve better performance than the item under test using mostly standard items. Because only the subsystem spectrometer needs to be calibrated, the calibration facility needs to simulate the geometrical "behaviours" of the imaging system. A trade-off study indicates that no commercial devices are able to fulfil completely all the requirements so that it was necessary to opt for an in home telecentric achromatic design. The proposed concept is based on an Offner design. This allows mainly to use simple spherical mirrors and to cover the spectral range. The spectral range is covered with a monochromator. Because of the large number of parameters to record the calibration facility is fully automatized. The performances of the calibration system have been verified by analysis and experimentally. Results achieved recently on a free-form grating Offner spectrometer demonstrate the capacities of this new calibration facility. In this paper, a full calibration facility is described, developed specifically for a new free-form spectro-imager.

New Methods of Spectral-Density Based Graph Construction and Their Application to Hyperspectral Image Analysis

NASA Astrophysics Data System (ADS)

Stevens, Jeffrey

The past decade has seen the emergence of many hyperspectral image (HSI) analysis algorithms based on graph theory and derived manifold-coordinates. Yet, despite the growing number of algorithms, there has been limited study of the graphs constructed from spectral data themselves. Which graphs are appropriate for various HSI analyses--and why? This research aims to begin addressing these questions as the performance of graph-based techniques is inextricably tied to the graphical model constructed from the spectral data. We begin with a literature review providing a survey of spectral graph construction techniques currently used by the hyperspectral community, starting with simple constructs demonstrating basic concepts and then incrementally adding components to derive more complex approaches. Throughout this development, we discuss algorithm advantages and disadvantages for different types of hyperspectral analysis. A focus is provided on techniques influenced by spectral density through which the concept of community structure arises. Through the use of simulated and real HSI data, we demonstrate density-based edge allocation produces more uniform nearest neighbor lists than non-density based techniques through increasing the number of intracluster edges, facilitating higher k-nearest neighbor (k-NN) classification performance. Imposing the common mutuality constraint to symmetrify adjacency matrices is demonstrated to be beneficial in most circumstances, especially in rural (less cluttered) scenes. Many complex adaptive edge-reweighting techniques are shown to slightly degrade nearest-neighbor list characteristics. Analysis suggests this condition is possibly attributable to the validity of characterizing spectral density by a single variable representing data scale for each pixel. Additionally, it is shown that imposing mutuality hurts the performance of adaptive edge-allocation techniques or any technique that aims to assign a low number of edges (<10) to any pixel. A simple k bias addresses this problem. Many of the adaptive edge-reweighting techniques are based on the concept of codensity, so we explore codensity properties as they relate to density-based edge reweighting. We find that codensity may not be the best estimator of local scale due to variations in cluster density, so we introduce and compare two inherently density-weighted graph construction techniques from the data mining literature: shared nearest neighbors (SNN) and mutual proximity (MP). MP and SNN are not reliant upon a codensity measure, hence are not susceptible to its shortcomings. Neither has been used for hyperspectral analyses, so this presents the first study of these techniques on HSI data. We demonstrate MP and SNN can offer better performance, but in general none of the reweighting techniques improve the quality of these spectral graphs in our neighborhood structure tests. As such, these complex adaptive edge-reweighting techniques may need to be modified to increase their effectiveness. During this investigation, we probe deeper into properties of high-dimensional data and introduce the concept of concentration of measure (CoM)--the degradation in the efficacy of many common distance measures with increasing dimensionality--as it relates to spectral graph construction. CoM exists in pairwise distances between HSI pixels, but not to the degree experienced in random data of the same extrinsic dimension; a characteristic we demonstrate is due to the rich correlation and cluster structure present in HSI data. CoM can lead to hubness--a condition wherein some nodes have short distances (high similarities) to an exceptionally large number of nodes. We study hub presence in 49 HSI datasets of varying resolutions, altitudes, and spectral bands to demonstrate hubness effects are negligible in a k-NN classification example (generalized counting scenarios), but we note its impact on methods that use edge weights to derive manifold coordinates or splitting clusters based on spectral graph theory requires more investigation. Many of these new graph-related quantities can be exploited to demonstrate new techniques for HSI classification and anomaly detection. We present an initial exploration into this relatively new and exciting field based on an enhanced Schroedinger Eigenmap classification example and compare results to the current state-of-the-art approach. We produce equivalent results, but demonstrate different types of misclassifications, opening the door to combine the best of both approaches to achieve truly superior performance. A separate less mature hubness-assisted anomaly detector (HAAD) is also presented.

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

PubMed

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

2017-10-20

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

Early prognostic value of an Algorithm based on spectral Variables of Ventricular fibrillAtion from the EKG of patients with suddEn cardiac death: A multicentre observational study (AWAKE).

PubMed

Palacios-Rubio, Julián; Marina-Breysse, Manuel; Quintanilla, Jorge G; Gil-Perdomo, José Miguel; Juárez-Fernández, Miriam; Garcia-Gonzalez, Inés; Rial-Bastón, Verónica; Corcobado, María Carmen; Espinosa, María Carmen; Ruiz, Francisco; Gómez-Mascaraque Pérez, Francisco; Bringas-Bollada, María; Lillo-Castellano, José María; Pérez-Castellano, Nicasio; Martínez-Sellés, Manuel; López de Sá, Esteban; Martín-Benítez, Juan Carlos; Perez-Villacastín, Julián; Filgueiras-Rama, David

2018-06-06

Ventricular fibrillation (VF)-related sudden cardiac death (SCD) is a leading cause of mortality and morbidity. Current biological and imaging parameters show significant limitations on predicting cerebral performance at hospital admission. The AWAKE study (NCT03248557) is a multicentre observational study to validate a model based on spectral ECG analysis to early predict cerebral performance and survival in resuscitated comatose survivors. Data from VF ECG tracings of patients resuscitated from SCD will be collected using an electronic Case Report Form. Patients can be either comatose (Glasgow Coma Scale - GCS - ≤8) survivors undergoing temperature control after return of spontaneous circulation (RoSC), or those who regain consciousness (GCS=15) after RoSC; all admitted to Intensive Cardiac Care Units in 4 major university hospitals. VF tracings prior to the first direct current shock will be digitized and analyzed to derive spectral data and feed a predictive model to estimate favorable neurological performance (FNP). The results of the model will be compared to the actual prognosis. The primary clinical outcome is FNP during hospitalization. Patients will be categorized into 4 subsets of neurological prognosis according to the risk score obtained from the predictive model. The secondary clinical outcomes are survival to hospital discharge, and FNP and survival after 6 months of follow-up. The model-derived categorisation will be also compared with clinical variables to assess model sensitivity, specificity, and accuracy. A model based on spectral analysis of VF tracings is a promising tool to obtain early prognostic data after SCD. Copyright © 2018 Instituto Nacional de Cardiología Ignacio Chávez. Publicado por Masson Doyma México S.A. All rights reserved.

Epsilon-Q: An Automated Analyzer Interface for Mass Spectral Library Search and Label-Free Protein Quantification.

PubMed

Cho, Jin-Young; Lee, Hyoung-Joo; Jeong, Seul-Ki; Paik, Young-Ki

2017-12-01

Mass spectrometry (MS) is a widely used proteome analysis tool for biomedical science. In an MS-based bottom-up proteomic approach to protein identification, sequence database (DB) searching has been routinely used because of its simplicity and convenience. However, searching a sequence DB with multiple variable modification options can increase processing time, false-positive errors in large and complicated MS data sets. Spectral library searching is an alternative solution, avoiding the limitations of sequence DB searching and allowing the detection of more peptides with high sensitivity. Unfortunately, this technique has less proteome coverage, resulting in limitations in the detection of novel and whole peptide sequences in biological samples. To solve these problems, we previously developed the "Combo-Spec Search" method, which uses manually multiple references and simulated spectral library searching to analyze whole proteomes in a biological sample. In this study, we have developed a new analytical interface tool called "Epsilon-Q" to enhance the functions of both the Combo-Spec Search method and label-free protein quantification. Epsilon-Q performs automatically multiple spectral library searching, class-specific false-discovery rate control, and result integration. It has a user-friendly graphical interface and demonstrates good performance in identifying and quantifying proteins by supporting standard MS data formats and spectrum-to-spectrum matching powered by SpectraST. Furthermore, when the Epsilon-Q interface is combined with the Combo-Spec search method, called the Epsilon-Q system, it shows a synergistic function by outperforming other sequence DB search engines for identifying and quantifying low-abundance proteins in biological samples. The Epsilon-Q system can be a versatile tool for comparative proteome analysis based on multiple spectral libraries and label-free quantification.

Analysis of spatial and temporal spectra of liquid film surface in annular gas-liquid flow

NASA Astrophysics Data System (ADS)

Alekseenko, Sergey; Cherdantsev, Andrey; Heinz, Oksana; Kharlamov, Sergey; Markovich, Dmitriy

2013-09-01

Wavy structure of liquid film in annular gas-liquid flow without liquid entrainment consists of fast long-living primary waves and slow short-living secondary waves. In present paper, results of spectral analysis of this wavy structure are presented. Application of high-speed LIF technique allowed us to perform such analysis in both spatial and temporal domains. Power spectra in both domains are characterized by one-humped shape with long exponential tail. Influence of gas velocity, liquid Reynolds number, liquid viscosity and pipe diameter on frequency of the waves is investigated. When gravity effect is much lesser than the shear stress, similarity of power spectra at different gas velocities is observed. Using combination of spectral analysis and identification of characteristic lines of primary waves, frequency of generation of secondary waves by primary waves is measured.

Multispectral signature analysis measurements of selected sniper rifles and small arms

NASA Astrophysics Data System (ADS)

Law, David B.; Carapezza, Edward M.; Csanadi, Christina J.; Edwards, Gerald D.; Hintz, Todd M.; Tong, Ronald M.

1997-02-01

During October 1995 - June 1996, the Naval Command, Control and Ocean Surveillance Center RDT&E Division (NRaD), under sponsorship from Defense Advanced Research Projects Agency (DARPA), conducted an intensive series of multi-spectral signature analyses of typical sniper weapons. Multi-spectral signatures of the muzzle flashes from rifles and pistols and some imagery of the bullets in flight were collected. Multi- spectral signatures of the muzzle flash were collected in the infrared (2.5 - 14.5 microns), visible -- near-IR (400 - 1200 nanometers), and the ultra-violet (185 - 400 nanometers) wavelength regions. These measurements consisted of high spectral resolution (0.0159 micron) measurements of the spectral radiance of the muzzle flash. A time history plot of the muzzle flash as it evolves just forward of the end of the muzzle is provided. These measurements were performed with a CI Systems Model SR5000 IR/Visible spectroradiometer and an Ocean Optics Model PC1000 UV spectroradiometer. Muzzle flash infrared imagery is provided to show the effect that specific muzzle breaks have on the resulting muzzle flash. The following set of sniper weapons were included in this test: AK-47, SKS, M16A2, M-14, FN-FAL, SMLE IIa, 03 Springfield, SVD Dragunov, 50 caliber McMillan, and a 45 caliber ACP pistol. The results of this signature analysis show that important measurable electro-optical differences do exist between all these weapons in terms of spectral radiance of the flash, spectral content of the gun powders, and spectral shapes/geometries of the muzzle flashes. These differences were sufficient such that, after a more complete data base is collected, it will be possible to develop a passive electro-optical weapon and ammunition identifier.

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

Spectral analysis methods for vehicle interior vibro-acoustics identification

NASA Astrophysics Data System (ADS)

Hosseini Fouladi, Mohammad; Nor, Mohd. Jailani Mohd.; Ariffin, Ahmad Kamal

2009-02-01

Noise has various effects on comfort, performance and health of human. Sound are analysed by human brain based on the frequencies and amplitudes. In a dynamic system, transmission of sound and vibrations depend on frequency and direction of the input motion and characteristics of the output. It is imperative that automotive manufacturers invest a lot of effort and money to improve and enhance the vibro-acoustics performance of their products. The enhancement effort may be very difficult and time-consuming if one relies only on 'trial and error' method without prior knowledge about the sources itself. Complex noise inside a vehicle cabin originated from various sources and travel through many pathways. First stage of sound quality refinement is to find the source. It is vital for automotive engineers to identify the dominant noise sources such as engine noise, exhaust noise and noise due to vibration transmission inside of vehicle. The purpose of this paper is to find the vibro-acoustical sources of noise in a passenger vehicle compartment. The implementation of spectral analysis method is much faster than the 'trial and error' methods in which, parts should be separated to measure the transfer functions. Also by using spectral analysis method, signals can be recorded in real operational conditions which conduce to more consistent results. A multi-channel analyser is utilised to measure and record the vibro-acoustical signals. Computational algorithms are also employed to identify contribution of various sources towards the measured interior signal. These achievements can be utilised to detect, control and optimise interior noise performance of road transport vehicles.

Multispectral colour analysis for quantitative evaluation of pseudoisochromatic color deficiency tests

NASA Astrophysics Data System (ADS)

Ozolinsh, Maris; Fomins, Sergejs

2010-11-01

Multispectral color analysis was used for spectral scanning of Ishihara and Rabkin color deficiency test book images. It was done using tunable liquid-crystal LC filters built in the Nuance II analyzer. Multispectral analysis keeps both, information on spatial content of tests and on spectral content. Images were taken in the range of 420-720nm with a 10nm step. We calculated retina neural activity charts taking into account cone sensitivity functions, and processed charts in order to find the visibility of latent symbols in color deficiency plates using cross-correlation technique. In such way the quantitative measure is found for each of diagnostics plate for three different color deficiency carrier types - protanopes, deutanopes and tritanopes. Multispectral color analysis allows to determine the CIE xyz color coordinates of pseudoisochromatic plate design elements and to perform statistical analysis of these data to compare the color quality of available color deficiency test books.

Evaluation of FTIR spectroscopy as diagnostic tool for colorectal cancer using spectral analysis

NASA Astrophysics Data System (ADS)

Dong, Liu; Sun, Xuejun; Chao, Zhang; Zhang, Shiyun; Zheng, Jianbao; Gurung, Rajendra; Du, Junkai; Shi, Jingsen; Xu, Yizhuang; Zhang, Yuanfu; Wu, Jinguang

2014-03-01

The aim of this study is to confirm FTIR spectroscopy as a diagnostic tool for colorectal cancer. 180 freshly removed colorectal samples were collected from 90 patients for spectrum analysis. The ratios of spectral intensity and relative intensity (/I1460) were calculated. Principal component analysis (PCA) and Fisher's discriminant analysis (FDA) were applied to distinguish the malignant from normal. The FTIR parameters of colorectal cancer and normal tissues were distinguished due to the contents or configurations of nucleic acids, proteins, lipids and carbohydrates. Related to nitrogen containing, water, protein and nucleic acid were increased significantly in the malignant group. Six parameters were selected as independent factors to perform discriminant functions. The sensitivity for FTIR in diagnosing colorectal cancer was 96.6% by discriminant analysis. Our study demonstrates that FTIR can be a useful technique for detection of colorectal cancer and may be applied in clinical colorectal cancer diagnosis.

Rapid analysis of pharmaceutical drugs using LIBS coupled with multivariate analysis.

PubMed

Tiwari, P K; Awasthi, S; Kumar, R; Anand, R K; Rai, P K; Rai, A K

2018-02-01

Type 2 diabetes drug tablets containing voglibose having dose strengths of 0.2 and 0.3 mg of various brands have been examined, using laser-induced breakdown spectroscopy (LIBS) technique. The statistical methods such as the principal component analysis (PCA) and the partial least square regression analysis (PLSR) have been employed on LIBS spectral data for classifying and developing the calibration models of drug samples. We have developed the ratio-based calibration model applying PLSR in which relative spectral intensity ratios H/C, H/N and O/N are used. Further, the developed model has been employed to predict the relative concentration of element in unknown drug samples. The experiment has been performed in air and argon atmosphere, respectively, and the obtained results have been compared. The present model provides rapid spectroscopic method for drug analysis with high statistical significance for online control and measurement process in a wide variety of pharmaceutical industrial applications.

Quantitative method to assess caries via fluorescence imaging from the perspective of autofluorescence spectral analysis

NASA Astrophysics Data System (ADS)

Chen, Q. G.; Zhu, H. H.; Xu, Y.; Lin, B.; Chen, H.

2015-08-01

A quantitative method to discriminate caries lesions for a fluorescence imaging system is proposed in this paper. The autofluorescence spectral investigation of 39 teeth samples classified by the International Caries Detection and Assessment System levels was performed at 405 nm excitation. The major differences in the different caries lesions focused on the relative spectral intensity range of 565-750 nm. The spectral parameter, defined as the ratio of wavebands at 565-750 nm to the whole spectral range, was calculated. The image component ratio R/(G + B) of color components was statistically computed by considering the spectral parameters (e.g. autofluorescence, optical filter, and spectral sensitivity) in our fluorescence color imaging system. Results showed that the spectral parameter and image component ratio presented a linear relation. Therefore, the image component ratio was graded as <0.66, 0.66-1.06, 1.06-1.62, and >1.62 to quantitatively classify sound, early decay, established decay, and severe decay tissues, respectively. Finally, the fluorescence images of caries were experimentally obtained, and the corresponding image component ratio distribution was compared with the classification result. A method to determine the numerical grades of caries using a fluorescence imaging system was proposed. This method can be applied to similar imaging systems.

Source characteristics of 2000 small earthquakes nucleating on the Alto Tiberina fault system (central Italy).

NASA Astrophysics Data System (ADS)

Munafo, I.; Malagnini, L.; Tinti, E.; Chiaraluce, L.; Di Stefano, R.; Valoroso, L.

2014-12-01

The Alto Tiberina Fault (ATF) is a 60 km long east-dipping low-angle normal fault, located in a sector of the Northern Apennines (Italy) undergoing active extension since the Quaternary. The ATF has been imaged by analyzing the active source seismic reflection profiles, and the instrumentally recorded persistent background seismicity. The present study is an attempt to separate the contributions of source, site, and crustal attenuation, in order to focus on the mechanics of the seismic sources on the ATF, as well on the synthetic and the antithetic structures within the ATF hanging-wall (i.e. Colfiorito fault, Gubbio fault and Umbria Valley fault). In order to compute source spectra, we perform a set of regressions over the seismograms of 2000 small earthquakes (-0.8 < ML< 4) recorded between 2010 and 2014 at 50 permanent seismic stations deployed in the framework of the Alto Tiberina Near Fault Observatory project (TABOO) and equipped with three-components seismometers, three of which located in shallow boreholes. Because we deal with some very small earthquakes, we maximize the signal to noise ratio (SNR) with a technique based on the analysis of peak values of bandpass-filtered time histories, in addition to the same processing performed on Fourier amplitudes. We rely on a tool called Random Vibration Theory (RVT) to completely switch from peak values in the time domain to Fourier spectral amplitudes. Low-frequency spectral plateau of the source terms are used to compute moment magnitudes (Mw) of all the events, whereas a source spectral ratio technique is used to estimate the corner frequencies (Brune spectral model) of a subset of events chosen over the analysis of the noise affecting the spectral ratios. So far, the described approach provides high accuracy over the spectral parameters of earthquakes of localized seismicity, and may be used to gain insights into the underlying mechanics of faulting and the earthquake processes.

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.

The Benard problem: A comparison of finite difference and spectral collocation eigen value solutions

NASA Technical Reports Server (NTRS)

Skarda, J. Raymond Lee; Mccaughan, Frances E.; Fitzmaurice, Nessan

1995-01-01

The application of spectral methods, using a Chebyshev collocation scheme, to solve hydrodynamic stability problems is demonstrated on the Benard problem. Implementation of the Chebyshev collocation formulation is described. The performance of the spectral scheme is compared with that of a 2nd order finite difference scheme. An exact solution to the Marangoni-Benard problem is used to evaluate the performance of both schemes. The error of the spectral scheme is at least seven orders of magnitude smaller than finite difference error for a grid resolution of N = 15 (number of points used). The performance of the spectral formulation far exceeded the performance of the finite difference formulation for this problem. The spectral scheme required only slightly more effort to set up than the 2nd order finite difference scheme. This suggests that the spectral scheme may actually be faster to implement than higher order finite difference schemes.

Spectral characterization and antibacterial activity of an isolated compound from Memecylon edule leaves.

PubMed

Srinivasan, R; Natarajan, D; Shivakumar, M S

2017-03-01

Memecylon edule Roxb. (Melastamataceae family) is a small evergreen tree reported as having ethnobotanical and pharmacological properties. The present study was aimed to investigate the spectral characterization and antibacterial activity of isolated pure compound (3β-hydroxyurs-12-en-28-oic acid (ursolic acid)) from Memecylon edule leaves by performing bioassay guided isolation method. The structure derivation of isolated compound was done by different spectral studies like UV, FT-IR, LC-MS, CHNS analysis, 1D ( 1 H, 13 C and DEPT-135) and 2D-NMR (HSQC and HMBC), respectively. About 99.29% purity of the compound was found in LC analysis. 1 H NMR spectrum results of compound shown 48 protons appear at different shielded region and most of the protons were present in aliphatic region. Whereas, 13 C NMR spectral data resulted seven methyl carbons (CH3), nine methylene carbons (CH2), seven methine carbons (CH) and six non-hydrogenated carbons (C) which are characteristic of pentacyclic triterpene. The isolated pure compound was tested for its antibacterial properties against targeted human pathogens by performing agar well diffusion, MIC and MBC assays and the result exhibits better growth inhibitory effects against S. epidermidis and S. pneumoniae, with the MIC values of 1.56 and 3.15μg/ml. The outcome of this study suggests that the bioactive compound is used for development of plant based drugs in pharmaceutical industry for combating microbial mediated diseases. Copyright © 2017 Elsevier B.V. All rights reserved.

Experiences with radiation portal detectors for international rail transport

NASA Astrophysics Data System (ADS)

Stromswold, D. C.; McCormick, K.; Todd, L.; Ashbaker, E. D.; Evans, J. C.

2006-08-01

Radiation detectors monitored trains at two international borders to evaluate the performance of NaI(Tl) and plastic (polyvinyltoluene: PVT) gamma-ray detectors to characterize rail cargo. The detectors included a prototype NaI(Tl) radiation-portal-monitor panel having four large detectors (10-cm × 10-cm × 41-cm) and a PVT panel with a 41 cm × 173 cm × 3.8-cm detector. Spectral data from the NaI(Tl) and PVT detectors were recorded. Of particular emphasis was the identification of naturally occurring radioactive material (NORM) and the resultant frequency of nuisance alarms. For rail monitoring, the difficulty in stopping trains to perform secondary inspection on alarming cars creates a need for reliable identification of NORM during initial screening. Approximately 30 trains were monitored, and the commodities in individual railcars were ascertained from manifest information. At one test site, the trains carried inter-modal containers that had been unloaded from ships, and at the other site, the trains contained bulk cargo in tanker cars and hopper cars or individual items in boxcars or flatbeds. NORM encountered included potash, liquefied petroleum gas, fireworks, televisions, and clay-based products (e.g., pottery). Analysis of the spectral data included the use of the template-fitting portion of the program GADRAS developed at Sandia National Laboratories. For most of the NORM, the NaI(Tl) data produced a correct identification of the radionuclides present in the railcars. The same analysis was also used for PVT data in which the spectral information (no peaks but only gradual spectral changes including Compton edges) was limited. However, the PVT analysis provided correct identification of 40K and 226Ra in many cases.

Experiences with radiation portal detectors for international rail transport

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

Stromswold, David C.; McCormick, Kathleen R.; Todd, Lindsay C.

Radiation detectors monitored trains at two international borders to evaluate the performance of NaI(Tl) and plastic (polyvinyltoluene: PVT) gamma-ray detectors to characterize rail cargo. The detectors included a prototype NaI(Tl) radiation-portal-monitor panel having four large detectors (10-cm × 10-cm × 41-cm) and a PVT panel with a 41 cm × 173 cm × 3.8-cm detector. Spectral data from the NaI(Tl) and PVT detectors were recorded. Of particular emphasis was the identification of naturally occurring radioactive material (NORM) and the resultant frequency of nuisance alarms. For rail monitoring, the difficulty in stopping trains to perform secondary inspection on alarming cars createsmore » a need for reliable identification of NORM during initial screening. Approximately 30 trains were monitored, and the commodities in individual railcars were ascertained from manifest information. At one test site the trains carried inter-modal containers that had been unloaded from ships, and at the other site the trains contained bulk cargo or individual items in boxcars or flatbeds. NORM encountered included potash, liquefied petroleum gas, fireworks, televisions, and clay-based products (e.g., pottery). Analysis of the spectral data included the use of the template-fitting program GADRAS/FitToDB from Sandia National Laboratories. For much of the NORM the NaI(Tl) data produced a correct identification of the radionuclides present in the railcars. The same analysis was also used for PVT data in which the spectral information (no peaks but only gradual spectral changes including Compton edges) was limited. However, the PVT analysis provided correct identification of 40K and 226Ra in many cases.« less

Spectral discrimination of macrophyte species during different seasons in a tropical wetland using in-situ hyperspectral remote sensing

NASA Astrophysics Data System (ADS)

Saluja, Ridhi; Garg, J. K.

2017-10-01

Wetlands, one of the most productive ecosystems on Earth, perform myriad ecological functions and provide a host of ecological services. Despite their ecological and economic values, wetlands have experienced significant degradation during the last century and the trend continues. Hyperspectral sensors provide opportunities to map and monitor macrophyte species within wetlands for their management and conservation. In this study, an attempt has been made to evaluate the potential of narrowband spectroradiometer data in discriminating wetland macrophytes during different seasons. main objectives of the research were (1) to determine whether macrophyte species could be discriminated based on in-situ hyperspectral reflectance collected over different seasons and at each measured waveband (400-950nm), (2) to compare the effectiveness of spectral reflectance and spectral indices in discriminating macrophyte species, and (3) to identify spectral wavelengths that are most sensitive in discriminating macrophyte species. Spectral characteristics of dominant wetland macrophyte species were collected seasonally using SVC GER 1500 portable spectroradiometer over the 400 to 1050nm spectral range at 1.5nm interval, at the Bhindawas wetland in the state of Haryana, India. Hyperspectral observations were pre-processed and subjected to statistical analysis, which involved a two-step approach including feature selection (ANOVA and KW test) and feature extraction (LDA and PCA). Statistical analysis revealed that the most influential wavelengths for discrimination were distributed along the spectral profile from visible to the near-infrared regions. The results suggest that hyperspectral data can be used discriminate wetland macrophyte species working as an effective tool for advanced mapping and monitoring of wetlands.

EEG resolutions in detecting and decoding finger movements from spectral analysis

PubMed Central

Xiao, Ran; Ding, Lei

2015-01-01

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

Broadband radio jet emission and variability of γ-ray blazars

NASA Astrophysics Data System (ADS)

Nestoras, Ioannis

2015-07-01

AGN (Active Galactic Nuclei) and in particular their subclass blazars, are among the most energetic objects observed in the universe, featuring extreme phenomenological characteristics such as rapid broadband flux density and polarization variability, fast super--luminal motion, high degree of polarization and a broadband, double-humped spectral energy distribution (SED). The details of the emission processes and violent variability of blazars are still poorly understood. Variability studies give important clues about the size, structure, physics and dynamics of the emitting region making AGN/blazar monitoring programs of uttermost importance in providing the necessary constraints for understanding the origin of energy production. In this framework the F-gamma program was initiated, monitoring monthly 60 fermi detected AGN/blazars at 12 frequencies between 2.6 and 345GHz since 2007. For the thesis in hand observations and data analysis were performed within the realms of the F-gamma program, using the Effelsberg (EB) 100m and Pico Veleta (PV) 30m telescopes at 10 frequency bands ranging from 2.64 to 142GHz. The cm to short-mm variability/spectral characteristics are monitored for a sample of 59 sources for a period of five years enabling for the first time a detailed study of the observed flaring activity in both the light curve and spectral domains for such a large number of sources and such high cadence. Also the observing systems and methods are introduced as well as the data reduction techniques. The thesis at hand is structured as follows: Chapter 3 presents the reduction methods and post measurement corrections applied to the data such as pointing offsets, gain--elevation and sensitivity corrections as well as specific corrections applied for each of the Effelsberg and Pico Veleta observing systems respectively. Chapter 4 presents the analysis tools and methods that were used such as: variability characteristics, flare amplitudes with a new method for estimating the intrinsic standard deviation, flare time scales using Structure Function analysis, spectral indices and spectral peak estimations. Chapter 5 presents the results of the analysis performed upon the five year light curves. The significance of variability through a x^2 test is estimated as well as the flare amplitudes using the intrinsic variability of the light curves along with a new proposed k--index. The introduction of the k--index enables the characterization of the observed variability amplitudes across frequency, thus permitting us to limit the parameter space of various physical models. Also flare time scales, brightness temperatures and Doppler factors are reported. Chapter 6 presents the corresponding analysis in the spectral domain, including results for spectral indices and an S_max - v_max analysis. By determining the spectral peak of every spectra for a selected number of sources, it is possible to track the evolution of the flaring activity in the S_max - v_max plane, enabling us to discriminate between different underlying physical mechanisms that are in action. Finally Chapter 7 includes the overall discussion and a summary of results obtained.

Introduction to basic solar cell measurements

NASA Technical Reports Server (NTRS)

Brandhorst, H. W., Jr.

1976-01-01

The basic approaches to solar cell performance and diagnostic measurements are described. The light sources, equipment for I-V curve measurement, and the test conditions and procedures for performance measurement are detailed. Solar cell diagnostic tools discussed include analysis of I-V curves, series resistance and reverse saturation current determination, spectral response/quantum yield measurement, and diffusion length/lifetime determination.

Application of MCR-ALS to reveal intermediate conformations in the thermally induced α-β transition of poly-L-lysine monitored by FT-IR spectroscopy

NASA Astrophysics Data System (ADS)

Alcaráz, Mirta R.; Schwaighofer, Andreas; Goicoechea, Héctor; Lendl, Bernhard

2017-10-01

Temperature-induced conformational transitions of poly-L-lysine were monitored with Fourier-transform infrared (FT-IR) spectroscopy between 10 °C and 70 °C. Chemometric analysis of dynamic IR spectra was performed by multivariate curve analysis-alternating least squares (MCR-ALS) of the amide I‧ and amide II‧ spectral region. With this approach, the pure spectral and concentration profiles of the conformational transition were obtained. Beside the initial α-helical, the intermediate random coil/extended helices and the final β-sheet structure, an additional intermediate PLL conformation was identified and attributed to a transient β-sheet structure.

Spectral atmospheric observations at Nantucket Island, May 7-14, 1981

NASA Technical Reports Server (NTRS)

Talay, T. A.; Poole, L. R.

1981-01-01

An experiment was conducted by the National Langley Research Center to measure atmospheric optical conditions using a 10-channel solar spectral photometer system. This experiment was part of a larger series of multidisciplinary experiments performed in the area of Nantucket Shoals aimed at studying the dynamics of phytoplankton production processes. Analysis of the collected atmospheric data yield total and aerosol optical depths, transmittances, normalized sky radiance distributions, and total and sky irradiances. Results of this analysis may aid in atmospheric corrections of remote sensor data obtained by several sensors overflying the Nantucket Shoals area. Recommendations are presented concerning future experiments using the described solar photometer system and calibration and operational deficiencies uncovered during the experiment.

SIGN SINGULARITY AND FLARES IN SOLAR ACTIVE REGION NOAA 11158

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

Sorriso-Valvo, L.; De Vita, G.; Kazachenko, M. D.

Solar Active Region NOAA 11158 has hosted a number of strong flares, including one X2.2 event. The complexity of current density and current helicity are studied through cancellation analysis of their sign-singular measure, which features power-law scaling. Spectral analysis is also performed, revealing the presence of two separate scaling ranges with different spectral index. The time evolution of parameters is discussed. Sudden changes of the cancellation exponents at the time of large flares and the presence of correlation with Extreme-Ultra-Violet and X-ray flux suggest that eruption of large flares can be linked to the small-scale properties of the current structures.

TU-CD-207-01: Characterization of Breast Tissue Composition Using Spectral Mammography

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

Ding, H; Cho, H; Kumar, N

Purpose: To investigate the feasibility of characterizing the chemical composition of breast tissue, in terms of water and lipid, by using spectral mammography in simulation and postmortem studies. Methods: Analytical simulations were performed to obtain low- and high-energy signals of breast tissue based on previously reported water, lipid, and protein contents. Dual-energy decomposition was used to characterize the simulated breast tissue into water and lipid basis materials and the measured water density was compared to the known value. In experimental studies, postmortem breasts were imaged with a spectral mammography system based on a scanning multi-slit Si strip photon-counting detector. Low-more » and high-energy images were acquired simultaneously from a single exposure by sorting the recorded photons into the corresponding energy bins. Dual-energy material decomposition of the low- and high-energy images yielded individual pixel measurements of breast tissue composition in terms of water and lipid thicknesses. After imaging, each postmortem breast was chemically decomposed into water, lipid and protein. The water density calculated from chemical analysis was used as the reference gold standard. Correlation of the water density measurements between spectral mammography and chemical analysis was analyzed using linear regression. Results: Both simulation and postmortem studies showed good linear correlation between the decomposed water thickness using spectral mammography and chemical analysis. The slope of the linear fitting function in the simulation and postmortem studies were 1.15 and 1.21, respectively. Conclusion: The results indicate that breast tissue composition, in terms of water and lipid, can be accurately measured using spectral mammography. Quantitative breast tissue composition can potentially be used to stratify patients according to their breast cancer risk.« less

[Analysis of the effect of detector's operating temperature on SNR in space-based remote sensor].

PubMed

Li, Zhan-feng; Wang, Shu-rong; Huang, Yu

2012-03-01

Limb viewing is a new viewing geometry for space-based atmospheric remote sensing, but the spectral radiance of atmosphere scattering reduces rapidly with limb height. So the signal-noise-ratio (SNR) is a key performance parameter of limb remote sensor. A SNR model varying with detector's temperature is proposed, based on analysis of spectral radiative transfer and noise' source in representative instruments. The SNR at limb height 70 km under space conditions was validated by simulation experiment on limb remote sensing spectrometer prototype. Theoretic analysis and experiment's results indicate congruously that when detector's temperature reduces to some extent, a maximum SNR will be reached. After considering the power consumption, thermal conductivity and other issues, optimal operating temperature of detector can be decided.

Time-Gated Raman Spectroscopy for Quantitative Determination of Solid-State Forms of Fluorescent Pharmaceuticals.

PubMed

Lipiäinen, Tiina; Pessi, Jenni; Movahedi, Parisa; Koivistoinen, Juha; Kurki, Lauri; Tenhunen, Mari; Yliruusi, Jouko; Juppo, Anne M; Heikkonen, Jukka; Pahikkala, Tapio; Strachan, Clare J

2018-04-03

Raman spectroscopy is widely used for quantitative pharmaceutical analysis, but a common obstacle to its use is sample fluorescence masking the Raman signal. Time-gating provides an instrument-based method for rejecting fluorescence through temporal resolution of the spectral signal and allows Raman spectra of fluorescent materials to be obtained. An additional practical advantage is that analysis is possible in ambient lighting. This study assesses the efficacy of time-gated Raman spectroscopy for the quantitative measurement of fluorescent pharmaceuticals. Time-gated Raman spectroscopy with a 128 × (2) × 4 CMOS SPAD detector was applied for quantitative analysis of ternary mixtures of solid-state forms of the model drug, piroxicam (PRX). Partial least-squares (PLS) regression allowed quantification, with Raman-active time domain selection (based on visual inspection) improving performance. Model performance was further improved by using kernel-based regularized least-squares (RLS) regression with greedy feature selection in which the data use in both the Raman shift and time dimensions was statistically optimized. Overall, time-gated Raman spectroscopy, especially with optimized data analysis in both the spectral and time dimensions, shows potential for sensitive and relatively routine quantitative analysis of photoluminescent pharmaceuticals during drug development and manufacturing.

Hyperspectral imaging coupled with chemometric analysis for non-invasive differentiation of black pens

NASA Astrophysics Data System (ADS)

Chlebda, Damian K.; Majda, Alicja; Łojewski, Tomasz; Łojewska, Joanna

2016-11-01

Differentiation of the written text can be performed with a non-invasive and non-contact tool that connects conventional imaging methods with spectroscopy. Hyperspectral imaging (HSI) is a relatively new and rapid analytical technique that can be applied in forensic science disciplines. It allows an image of the sample to be acquired, with full spectral information within every pixel. For this paper, HSI and three statistical methods (hierarchical cluster analysis, principal component analysis, and spectral angle mapper) were used to distinguish between traces of modern black gel pen inks. Non-invasiveness and high efficiency are among the unquestionable advantages of ink differentiation using HSI. It is also less time-consuming than traditional methods such as chromatography. In this study, a set of 45 modern gel pen ink marks deposited on a paper sheet were registered. The spectral characteristics embodied in every pixel were extracted from an image and analysed using statistical methods, externally and directly on the hypercube. As a result, different black gel inks deposited on paper can be distinguished and classified into several groups, in a non-invasive manner.

Comparative Analysis of Alternative Spectral Bands of CO2 and O2 for the Sensing of CO2 Mixing Ratios

NASA Technical Reports Server (NTRS)

Pliutau, Denis; Prasad, Narasimha S.

2013-01-01

We performed comparative studies to establish favorable spectral regions and measurement wavelength combinations in alternative bands of CO2 and O2, for the sensing of CO2 mixing ratios (XCO2) in missions such as ASCENDS. The analysis employed several simulation approaches including separate layers calculations based on pre-analyzed atmospheric data from the modern-era retrospective analysis for research and applications (MERRA), and the line-byline radiative transfer model (LBLRTM) to obtain achievable accuracy estimates as a function of altitude and for the total path over an annual span of variations in atmospheric parameters. Separate layer error estimates also allowed investigation of the uncertainties in the weighting functions at varying altitudes and atmospheric conditions. The parameters influencing the measurement accuracy were analyzed independently and included temperature sensitivity, water vapor interferences, selection of favorable weighting functions, excitations wavelength stabilities and other factors. The results were used to identify favorable spectral regions and combinations of on / off line wavelengths leading to reductions in interferences and the improved total accuracy.

Mass Spectral Library Quality Assurance by Inter-Library Comparison

NASA Astrophysics Data System (ADS)

Wallace, William E.; Ji, Weihua; Tchekhovskoi, Dmitrii V.; Phinney, Karen W.; Stein, Stephen E.

2017-04-01

A method to discover and correct errors in mass spectral libraries is described. Comparing across a set of highly curated reference libraries compounds that have the same chemical structure quickly identifies entries that are outliers. In cases where three or more entries for the same compound are compared, the outlier as determined by visual inspection was almost always found to contain the error. These errors were either in the spectrum itself or in the chemical descriptors that accompanied it. The method is demonstrated on finding errors in compounds of forensic interest in the NIST/EPA/NIH Mass Spectral Library. The target list of compounds checked was the Scientific Working Group for the Analysis of Seized Drugs (SWGDRUG) mass spectral library. Some examples of errors found are described. A checklist of errors that curators should look for when performing inter-library comparisons is provided.

PFS/Mars Express first results: water vapour and carbon monoxide global distribution

NASA Astrophysics Data System (ADS)

Ignatiev, N. I.; Titov, D. V.; Formisano, V.; Moroz, V. I.; Lellouch, E.; Encrenaz, Th.; Fouchet, T.; Grassi, D.; Giuranna, M.; Atreya, S.; Pfs Team

Planetary Fourier Spectrometer onboard Mars Express, with its wide spectral range (1.2--45 um) and high spectral resolution (1.4 cm-1), makes it possible to study in a self-consistent manner the Martian atmosphere by means of simultaneous analysis of spectral features in several spectral regions. As concerned small species, we observe 30--50, 6.3, 2.56, 1.87 and 1.38 μ m H2O bands, and 4.7 and 2.35 μ m CO bands. The most favourable, with respect to the instrument performance, 2.56 μ m H2O and 4.7 μ m CO bands, are used to study the variations of column abundance of water vapour and carbon monoxide on a global scale from pole to pole. All necessary atmospheric parameters, namely temperature profiles, surface pressure, and dust density are obtained from the same spectra, whenever possible.

Mass Spectral Library Quality Assurance by Inter-Library Comparison

PubMed Central

Wallace, W.E.; Ji, W.; Tchekhovskoi, D.V.; Phinney, K.W.; Stein, S.E.

2017-01-01

A method to discover and correct errors in mass spectral libraries is described. Comparing across a set of highly curated reference libraries compounds that have the same chemical structure quickly identifies entries that are outliers. In cases where three or more entries for the same compound are compared the outlier as determined by visual inspection was almost always found to contain the error. These errors were either in the spectrum itself or in the chemical descriptors that accompanied it. The method is demonstrated on finding errors in compounds of forensic interest in the NIST/EPA/NIH Mass Spectral Library. The target list of compounds checked was the Scientific Working Group for the Analysis of Seized Drugs (SWGDRUG) mass spectral library. Some examples of errors found are described. A checklist of errors that curators should look for when performing inter-library comparisons is provided. PMID:28127680

Sculpting narrowband Fano resonances inherent in the large-area mid-infrared photonic crystal microresonators for spectroscopic imaging

PubMed Central

Liu, Jui-Nung; Schulmerich, Matthew V.; Bhargava, Rohit; Cunningham, Brian T.

2014-01-01

Fourier transform infrared (FT-IR) imaging spectrometers are almost universally used to record microspectroscopic imaging data in the mid-infrared (mid-IR) spectral region. While the commercial standard, interferometry necessitates collection of large spectral regions, requires a large data handling overhead for microscopic imaging and is slow. Here we demonstrate an approach for mid-IR spectroscopic imaging at selected discrete wavelengths using narrowband resonant filtering of a broadband thermal source, enabled by high-performance guided-mode Fano resonances in one-layer, large-area mid-IR photonic crystals on a glass substrate. The microresonant devices enable discrete frequency IR (DF-IR), in which a limited number of wavelengths that are of interest are recorded using a mechanically robust instrument. This considerably simplifies instrumentation as well as overhead of data acquisition, storage and analysis for large format imaging with array detectors. To demonstrate the approach, we perform DF-IR spectral imaging of a polymer USAF resolution target and human tissue in the C−H stretching region (2600−3300 cm−1). DF-IR spectroscopy and imaging can be generalized to other IR spectral regions and can serve as an analytical tool for environmental and biomedical applications. PMID:25089433

Evaluation of 1H NMR metabolic profiling using biofluid mixture design.

PubMed

Athersuch, Toby J; Malik, Shahid; Weljie, Aalim; Newton, Jack; Keun, Hector C

2013-07-16

A strategy for evaluating the performance of quantitative spectral analysis tools in conditions that better approximate background variation in a metabonomics experiment is presented. Three different urine samples were mixed in known proportions according to a {3, 3} simplex lattice experimental design and analyzed in triplicate by 1D (1)H NMR spectroscopy. Fifty-four urinary metabolites were subsequently quantified from the sample spectra using two methods common in metabolic profiling studies: (1) targeted spectral fitting and (2) targeted spectral integration. Multivariate analysis using partial least-squares (PLS) regression showed the latent structure of the spectral set recapitulated the experimental mixture design. The goodness-of-prediction statistic (Q(2)) of each metabolite variable in a PLS model was calculated as a metric for the reliability of measurement, across the sample compositional space. Several metabolites were observed to have low Q(2) values, largely as a consequence of their spectral resonances having low s/n or strong overlap with other sample components. This strategy has the potential to allow evaluation of spectral features obtained from metabolic profiling platforms in the context of the compositional background found in real biological sample sets, which may be subject to considerable variation. We suggest that it be incorporated into metabolic profiling studies to improve the estimation of matrix effects that confound accurate metabolite measurement. This novel method provides a rational basis for exploiting information from several samples in an efficient manner and avoids the use of multiple spike-in authentic standards, which may be difficult to obtain.

Optimization of data analysis for the in vivo neutron activation analysis of aluminum in bone.

PubMed

Mohseni, H K; Matysiak, W; Chettle, D R; Byun, S H; Priest, N; Atanackovic, J; Prestwich, W V

2016-10-01

An existing system at McMaster University has been used for the in vivo measurement of aluminum in human bone. Precise and detailed analysis approaches are necessary to determine the aluminum concentration because of the low levels of aluminum found in the bone and the challenges associated with its detection. Phantoms resembling the composition of the human hand with varying concentrations of aluminum were made for testing the system prior to the application to human studies. A spectral decomposition model and a photopeak fitting model involving the inverse-variance weighted mean and a time-dependent analysis were explored to analyze the results and determine the model with the best performance and lowest minimum detection limit. The results showed that the spectral decomposition and the photopeak fitting model with the inverse-variance weighted mean both provided better results compared to the other methods tested. The spectral decomposition method resulted in a marginally lower detection limit (5μg Al/g Ca) compared to the inverse-variance weighted mean (5.2μg Al/g Ca), rendering both equally applicable to human measurements. Copyright © 2016 Elsevier Ltd. All rights reserved.

Voice gender identification by cochlear implant users: The role of spectral and temporal resolution

NASA Astrophysics Data System (ADS)

Fu, Qian-Jie; Chinchilla, Sherol; Nogaki, Geraldine; Galvin, John J.

2005-09-01

The present study explored the relative contributions of spectral and temporal information to voice gender identification by cochlear implant users and normal-hearing subjects. Cochlear implant listeners were tested using their everyday speech processors, while normal-hearing subjects were tested under speech processing conditions that simulated various degrees of spectral resolution, temporal resolution, and spectral mismatch. Voice gender identification was tested for two talker sets. In Talker Set 1, the mean fundamental frequency values of the male and female talkers differed by 100 Hz while in Talker Set 2, the mean values differed by 10 Hz. Cochlear implant listeners achieved higher levels of performance with Talker Set 1, while performance was significantly reduced for Talker Set 2. For normal-hearing listeners, performance was significantly affected by the spectral resolution, for both Talker Sets. With matched speech, temporal cues contributed to voice gender identification only for Talker Set 1 while spectral mismatch significantly reduced performance for both Talker Sets. The performance of cochlear implant listeners was similar to that of normal-hearing subjects listening to 4-8 spectral channels. The results suggest that, because of the reduced spectral resolution, cochlear implant patients may attend strongly to periodicity cues to distinguish voice gender.

Auditory spectral versus spatial temporal order judgment: Threshold distribution analysis.

PubMed

Fostick, Leah; Babkoff, Harvey

2017-05-01

Some researchers suggested that one central mechanism is responsible for temporal order judgments (TOJ), within and across sensory channels. This suggestion is supported by findings of similar TOJ thresholds in same modality and cross-modality TOJ tasks. In the present study, we challenge this idea by analyzing and comparing the threshold distributions of the spectral and spatial TOJ tasks. In spectral TOJ, the tones differ in their frequency ("high" and "low") and are delivered either binaurally or monaurally. In spatial (or dichotic) TOJ, the two tones are identical but are presented asynchronously to the two ears and thus differ with respect to which ear received the first tone and which ear received the second tone ("left"/"left"). Although both tasks are regarded as measures of auditory temporal processing, a review of data published in the literature suggests that they trigger different patterns of response. The aim of the current study was to systematically examine spectral and spatial TOJ threshold distributions across a large number of studies. Data are based on 388 participants in 13 spectral TOJ experiments, and 222 participants in 9 spatial TOJ experiments. None of the spatial TOJ distributions deviated significantly from the Gaussian; while all of the spectral TOJ threshold distributions were skewed to the right, with more than half of the participants accurately judging temporal order at very short interstimulus intervals (ISI). The data do not support the hypothesis that 1 central mechanism is responsible for all temporal order judgments. We suggest that different perceptual strategies are employed when performing spectral TOJ than when performing spatial TOJ. We posit that the spectral TOJ paradigm may provide the opportunity for two-tone masking or temporal integration, which is sensitive to the order of the tones and thus provides perceptual cues that may be used to judge temporal order. This possibility should be considered when interpreting spectral TOJ data, especially in the context of comparing different populations. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Silicon oxide nanoparticles doped PQ-PMMA for volume holographic imaging filters.

PubMed

Luo, Yuan; Russo, Juan M; Kostuk, Raymond K; Barbastathis, George

2010-04-15

Holographic imaging filters are required to have high Bragg selectivity, namely, narrow angular and spectral bandwidth, to obtain spatial-spectral information within a three-dimensional object. In this Letter, we present the design of holographic imaging filters formed using silicon oxide nanoparticles (nano-SiO(2)) in phenanthrenquinone-poly(methyl methacrylate) (PQ-PMMA) polymer recording material. This combination offers greater Bragg selectivity and increases the diffraction efficiency of holographic filters. The holographic filters with optimized ratio of nano-SiO(2) in PQ-PMMA can significantly improve the performance of Bragg selectivity and diffraction efficiency by 53% and 16%, respectively. We present experimental results and data analysis demonstrating this technique in use for holographic spatial-spectral imaging filters.

Field research on the spectral properties of crops and soils, volume 1. [Purdue Agronomy Farm

NASA Technical Reports Server (NTRS)

Bauer, M. E. (Principal Investigator); Biehl, L. L.; Robinson, B. F.

1980-01-01

The experiment design, data acquisition and preprocessing, data base management, analysis results and development of instrumentation for the AgRISTARS Supporting Research Project, Field Research task are described. Results of several investigations on the spectral reflectance of corn and soybean canopies as influenced by cultural practices, development stage and nitrogen nutrition are reported as well as results of analyses of the spectral properties of crop canopies as a function of canopy geometry, row orientation, sensor view angle and solar illumination angle are presented. The objectives, experiment designs and data acquired in 1980 for field research experiments are described. The development and performance characteristics of a prototype multiband radiometer, data logger, and aerial tower for field research are discussed.

Multi-Dimensional High Order Essentially Non-Oscillatory Finite Difference Methods in Generalized Coordinates

NASA Technical Reports Server (NTRS)

Shu, Chi-Wang

1998-01-01

This project is about the development of high order, non-oscillatory type schemes for computational fluid dynamics. Algorithm analysis, implementation, and applications are performed. Collaborations with NASA scientists have been carried out to ensure that the research is relevant to NASA objectives. The combination of ENO finite difference method with spectral method in two space dimension is considered, jointly with Cai [3]. The resulting scheme behaves nicely for the two dimensional test problems with or without shocks. Jointly with Cai and Gottlieb, we have also considered one-sided filters for spectral approximations to discontinuous functions [2]. We proved theoretically the existence of filters to recover spectral accuracy up to the discontinuity. We also constructed such filters for practical calculations.

A portable spectrometer for use from 5 to 15 micrometers

NASA Technical Reports Server (NTRS)

Hoover, G.; Kahle, A. B.

1986-01-01

A field portable spectrometer suitable for collecting data relevant to remote sensing applications in the 8 to 12 micrometer atmospheric window has been built at the Jet Propulsion Laboratory. The instrument employs a single cooled HgCdTe detector and a continuously variable filter wheel analyzer. The spectral range covered is 5 to 14.5 micrometers and the resolution is approximately 1.5 percent of the wavelength. A description of the hardware is followed by a discussion of the analysis of the spectral data leading to finished emissivity and radiance spectra. A section is devoted to the evaluation of the instrument performance with respect to spectral resolution, radiometric precision, and accuracy. Several examples of spectra acquired in the field are included.

Arc-Welding Spectroscopic Monitoring based on Feature Selection and Neural Networks.

PubMed

Garcia-Allende, P Beatriz; Mirapeix, Jesus; Conde, Olga M; Cobo, Adolfo; Lopez-Higuera, Jose M

2008-10-21

A new spectral processing technique designed for application in the on-line detection and classification of arc-welding defects is presented in this paper. A noninvasive fiber sensor embedded within a TIG torch collects the plasma radiation originated during the welding process. The spectral information is then processed in two consecutive stages. A compression algorithm is first applied to the data, allowing real-time analysis. The selected spectral bands are then used to feed a classification algorithm, which will be demonstrated to provide an efficient weld defect detection and classification. The results obtained with the proposed technique are compared to a similar processing scheme presented in previous works, giving rise to an improvement in the performance of the monitoring system.

Properties of magnetic photonic crystals in the visible spectral region and their performance limitations

NASA Astrophysics Data System (ADS)

Kotov, V. A.; Shavrov, V. G.; Vasiliev, M.; Alameh, K.; Nur-E-Alam, M.; Balabanov, D. E.

2018-02-01

We report on the results of computer modelling and performance analysis of the optical and magneto-optical (MO) characteristics of one-dimensional magnetic photonic crystals (MPC) of several classic design types (having either a single structure defect, or a number of these), designed for applications in the visible spectral region. The calculations are performed accounting for the real levels of optical absorption achievable in existing MO materials which currently demonstrate the best MO quality (bismuth-substituted ferrite garnets). We consider Bi2Dy1Fe4Ga1O12 as the base material for use within quarter-wave thick MO layers of MPC; silica is used for the non-magnetic transparent quarter-wave layers. The achieved results can be used to clarify the nature of the differences that exist between the expected practical potential of MPCs in integrated photonics, and the actual attained experimental results. Our results show that in MPCs optimized for light intensity modulation applications, in the red spectral region (near 650 nm), the achievable levels of optical transmission are limited to about 30%. This coincides spectrally with the peaks of Faraday rotation reaching their maxima at about 25°, with further transmission increases possible in the near-infrared region. Larger Faraday rotation angles are only achievable currently in structures or single film layers with reduced transmission.

Assessing Cd-induced stress from plant spectral response

NASA Astrophysics Data System (ADS)

Kancheva, Rumiana; Georgiev, Georgi

2014-10-01

Remote sensing plays a significant role in local, regional and global monitoring of land covers. Ecological concerns worldwide determine the importance of remote sensing applications for the assessment of soil conditions, vegetation health and identification of stress-induced changes. The extensive industrial growth and intensive agricultural land-use arise the serious ecological problem of environmental pollution associated with the increasing anthropogenic pressure on the environment. Soil contamination is a reason for degradation processes and temporary or permanent decrease of the productive capacity of land. Heavy metals are among the most dangerous pollutants because of their toxicity, persistent nature, easy up-take by plants and long biological half-life. This paper takes as its focus the study of crop species spectral response to Cd pollution. Ground-based experiments were performed, using alfalfa, spring barley and pea grown in Cd contaminated soils and in different hydroponic systems under varying concentrations of the heavy metal. Cd toxicity manifested itself by inhibition of plant growth and synthesis of photosynthetic pigments. Multispectral reflectance, absorbance and transmittance, as well as red and far red fluorescence were measured and examined for their suitability to detect differences in plant condition. Statistical analysis was performed and empirical relationships were established between Cd concentration, plant growth variables and spectral response Various spectral properties proved to be indicators of plant performance and quantitative estimators of the degree of the Cd-induced stress.

Assessing the biophysical naturalness of grassland in eastern North Dakota with hyperspectral imagery

NASA Astrophysics Data System (ADS)

Zhou, Qiang

Over the past two decades, non-native species within grassland communities have quickly developed due to human migration and commerce. Invasive species like Smooth Brome grass (Bromus inermis) and Kentucky Blue Grass (Poa pratensis), seriously threaten conservation of native grasslands. This study aims to discriminate between native grasslands and planted hayfields and conservation areas dominated by introduced grasses using hyperspectral imagery. Hyperspectral imageries from the Hyperion sensor on EO-1 were acquired in late spring and late summer on 2009 and 2010. Field spectra for widely distributed species as well as smooth brome grass and Kentucky blue grass were collected from the study sites throughout the growing season. Imagery was processed with an unmixing algorithm to estimate fractional cover of green and dry vegetation and bare soil. As the spectrum is significantly different through growing season, spectral libraries for the most common species are then built for both the early growing season and late growing season. After testing multiple methods, the Adaptive Coherence Estimator (ACE) was used for spectral matching analysis between the imagery and spectral libraries. Due in part to spectral similarity among key species, the results of spectral matching analysis were not definitive. Additional indexes, "Level of Dominance" and "Band variance", were calculated to measure the predominance of spectral signatures in any area. A Texture co-occurrence analysis was also performed on both "Level of Dominance" and "Band variance" indexes to extract spatial characteristics. The results suggest that compared with disturbed area, native prairie tend to have generally lower "Level of Dominance" and "Band variance" as well as lower spatial dissimilarity. A final decision tree model was created to predict presence of native or introduced grassland. The model was more effective for identification of Mixed Native Grassland than for grassland dominated by a single species. The discrimination of native and introduced grassland was limited by the similarity of spectral signatures between forb-dominated native grasslands and brome-grass stands. However, saline native grasslands were distinguishable from brome grass.

A Critical Examination of Figure of Merit (FOM). Assessing the Goodness-of-Fit in Gamma/X-ray Peak Analysis

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

Croft, S.; Favalli, Andrea; Weaver, Brian Phillip

2015-10-06

In this paper we develop and investigate several criteria for assessing how well a proposed spectral form fits observed spectra. We consider the classical improved figure of merit (FOM) along with several modifications, as well as criteria motivated by Poisson regression from the statistical literature. We also develop a new FOM that is based on the statistical idea of the bootstrap. A spectral simulator has been developed to assess the performance of these different criteria under multiple data configurations.

Variation of the transmittance spectrum of a polymer cladding optical fibre for the influence of hydrocarbons and changes in temperature

NASA Astrophysics Data System (ADS)

Santoyo, A. T.; Shlyagin, M. G.; Mendieta, F. J.; Spirin, V.; de Rivera, L. N.

2005-12-01

We develop an analysis of the behavior of an evanescent field fiber optic sensor under different conditions for its optimization. This paper presents results of an experimental study of the spectral characteristics of a polymer cladding optical fiber exposed to different analytes. The measurements were performed in the spectral interval from 1100 to 1800 nanometers in a temperature range from 5 to 50 degrees C. Influence of ambient temperature on the optical fiber transmittance was found to be strongly dependent on wavelength.

Asteroid taxonomy

NASA Technical Reports Server (NTRS)

Tholen, David J.; Barucci, M. Antonietta

1989-01-01

The spectral reflectivity of asteroid surfaces over the wavelength range of 0.3 to 1.1 micron can be used to classify these objects into several broad groups with similar spectral characteristics. The three most recently developed taxonomies group the asteroids into 9, 11, or 14 different clases, depending on the technique used to perform the analysis. The distribution of the taxonomic classes shows that darker and redder objects become more dominant at larger heliocentric distances, while the rare asteroid types are found more frequently among the small objects of the planet-crossing population.

Complementarity of UV and IR differential absorption lidar for global measurements of atmospheric species

NASA Technical Reports Server (NTRS)

Megie, G.; Menzies, R. T.

1980-01-01

An analysis of the potential capabilities of a spectrally diversified DIAL technique for monitoring atmospheric species is presented assuming operation from an earth-orbiting platform. Emphasis is given to the measurement accuracies and spatial and temporal resolutions required to meet present atmospheric science objectives. The discussion points out advantages of spectral diversity to perform comprehensive studies of the atmosphere; in general it is shown that IR systems have an advantage in lower atmospheric measurements, while UV systems are superior for middle and upper atmospheric measurements.

Novel selective TOCSY method enables NMR spectral elucidation of metabolomic mixtures

NASA Astrophysics Data System (ADS)

MacKinnon, Neil; While, Peter T.; Korvink, Jan G.

2016-11-01

Complex mixture analysis is routinely encountered in NMR-based investigations. With the aim of component identification, spectral complexity may be addressed chromatographically or spectroscopically, the latter being favored to reduce sample handling requirements. An attractive experiment is selective total correlation spectroscopy (sel-TOCSY), which is capable of providing tremendous spectral simplification and thereby enhancing assignment capability. Unfortunately, isolating a well resolved resonance is increasingly difficult as the complexity of the mixture increases and the assumption of single spin system excitation is no longer robust. We present TOCSY optimized mixture elucidation (TOOMIXED), a technique capable of performing spectral assignment particularly in the case where the assumption of single spin system excitation is relaxed. Key to the technique is the collection of a series of 1D sel-TOCSY experiments as a function of the isotropic mixing time (τm), resulting in a series of resonance intensities indicative of the underlying molecular structure. By comparing these τm -dependent intensity patterns with a library of pre-determined component spectra, one is able to regain assignment capability. After consideration of the technique's robustness, we tested TOOMIXED firstly on a model mixture. As a benchmark we were able to assign a molecule with high confidence in the case of selectively exciting an isolated resonance. Assignment confidence was not compromised when performing TOOMIXED on a resonance known to contain multiple overlapping signals, and in the worst case the method suggested a follow-up sel-TOCSY experiment to confirm an ambiguous assignment. TOOMIXED was then demonstrated on two realistic samples (whisky and urine), where under our conditions an approximate limit of detection of 0.6 mM was determined. Taking into account literature reports for the sel-TOCSY limit of detection, the technique should reach on the order of 10 μ M sensitivity. We anticipate this technique will be highly attractive to various analytical fields facing mixture analysis, including metabolomics, foodstuff analysis, pharmaceutical analysis, and forensics.

Multiband tissue classification for ultrasonic transmission tomography using spectral profile detection

NASA Astrophysics Data System (ADS)

Jeong, Jeong-Won; Kim, Tae-Seong; Shin, Dae-Chul; Do, Synho; Marmarelis, Vasilis Z.

2004-04-01

Recently it was shown that soft tissue can be differentiated with spectral unmixing and detection methods that utilize multi-band information obtained from a High-Resolution Ultrasonic Transmission Tomography (HUTT) system. In this study, we focus on tissue differentiation using the spectral target detection method based on Constrained Energy Minimization (CEM). We have developed a new tissue differentiation method called "CEM filter bank". Statistical inference on the output of each CEM filter of a filter bank is used to make a decision based on the maximum statistical significance rather than the magnitude of each CEM filter output. We validate this method through 3-D inter/intra-phantom soft tissue classification where target profiles obtained from an arbitrary single slice are used for differentiation in multiple tomographic slices. Also spectral coherence between target and object profiles of an identical tissue at different slices and phantoms is evaluated by conventional cross-correlation analysis. The performance of the proposed classifier is assessed using Receiver Operating Characteristic (ROC) analysis. Finally we apply our method to classify tiny structures inside a beef kidney such as Styrofoam balls (~1mm), chicken tissue (~5mm), and vessel-duct structures.

Color analysis and image rendering of woodblock prints with oil-based ink

NASA Astrophysics Data System (ADS)

Horiuchi, Takahiko; Tanimoto, Tetsushi; Tominaga, Shoji

2012-01-01

This paper proposes a method for analyzing the color characteristics of woodblock prints having oil-based ink and rendering realistic images based on camera data. The analysis results of woodblock prints show some characteristic features in comparison with oil paintings: 1) A woodblock print can be divided into several cluster areas, each with similar surface spectral reflectance; and 2) strong specular reflection from the influence of overlapping paints arises only in specific cluster areas. By considering these properties, we develop an effective rendering algorithm by modifying our previous algorithm for oil paintings. A set of surface spectral reflectances of a woodblock print is represented by using only a small number of average surface spectral reflectances and the registered scaling coefficients, whereas the previous algorithm for oil paintings required surface spectral reflectances of high dimension at all pixels. In the rendering process, in order to reproduce the strong specular reflection in specific cluster areas, we use two sets of parameters in the Torrance-Sparrow model for cluster areas with or without strong specular reflection. An experiment on a woodblock printing with oil-based ink was performed to demonstrate the feasibility of the proposed method.

Accurate palm vein recognition based on wavelet scattering and spectral regression kernel discriminant analysis

NASA Astrophysics Data System (ADS)

Elnasir, Selma; Shamsuddin, Siti Mariyam; Farokhi, Sajad

2015-01-01

Palm vein recognition (PVR) is a promising new biometric that has been applied successfully as a method of access control by many organizations, which has even further potential in the field of forensics. The palm vein pattern has highly discriminative features that are difficult to forge because of its subcutaneous position in the palm. Despite considerable progress and a few practical issues, providing accurate palm vein readings has remained an unsolved issue in biometrics. We propose a robust and more accurate PVR method based on the combination of wavelet scattering (WS) with spectral regression kernel discriminant analysis (SRKDA). As the dimension of WS generated features is quite large, SRKDA is required to reduce the extracted features to enhance the discrimination. The results based on two public databases-PolyU Hyper Spectral Palmprint public database and PolyU Multi Spectral Palmprint-show the high performance of the proposed scheme in comparison with state-of-the-art methods. The proposed approach scored a 99.44% identification rate and a 99.90% verification rate [equal error rate (EER)=0.1%] for the hyperspectral database and a 99.97% identification rate and a 99.98% verification rate (EER=0.019%) for the multispectral database.

Relationships Among Peripheral and Central Electrophysiological Measures of Spatial and Spectral Selectivity and Speech Perception in Cochlear Implant Users

PubMed Central

Scheperle, Rachel A.; Abbas, Paul J.

2014-01-01

Objectives The ability to perceive speech is related to the listener’s ability to differentiate among frequencies (i.e., spectral resolution). Cochlear implant (CI) users exhibit variable speech-perception and spectral-resolution abilities, which can be attributed in part to the extent of electrode interactions at the periphery (i.e., spatial selectivity). However, electrophysiological measures of peripheral spatial selectivity have not been found to correlate with speech perception. The purpose of this study was to evaluate auditory processing at the periphery and cortex using both simple and spectrally complex stimuli to better understand the stages of neural processing underlying speech perception. The hypotheses were that (1) by more completely characterizing peripheral excitation patterns than in previous studies, significant correlations with measures of spectral selectivity and speech perception would be observed, (2) adding information about processing at a level central to the auditory nerve would account for additional variability in speech perception, and (3) responses elicited with spectrally complex stimuli would be more strongly correlated with speech perception than responses elicited with spectrally simple stimuli. Design Eleven adult CI users participated. Three experimental processor programs (MAPs) were created to vary the likelihood of electrode interactions within each participant. For each MAP, a subset of 7 of 22 intracochlear electrodes was activated: adjacent (MAP 1), every-other (MAP 2), or every third (MAP 3). Peripheral spatial selectivity was assessed using the electrically evoked compound action potential (ECAP) to obtain channel-interaction functions for all activated electrodes (13 functions total). Central processing was assessed by eliciting the auditory change complex (ACC) with both spatial (electrode pairs) and spectral (rippled noise) stimulus changes. Speech-perception measures included vowel-discrimination and the Bamford-Kowal-Bench Sentence-in-Noise (BKB-SIN) test. Spatial and spectral selectivity and speech perception were expected to be poorest with MAP 1 (closest electrode spacing) and best with MAP 3 (widest electrode spacing). Relationships among the electrophysiological and speech-perception measures were evaluated using mixed-model and simple linear regression analyses. Results All electrophysiological measures were significantly correlated with each other and with speech perception for the mixed-model analysis, which takes into account multiple measures per person (i.e. experimental MAPs). The ECAP measures were the best predictor of speech perception. In the simple linear regression analysis on MAP 3 data, only the cortical measures were significantly correlated with speech; spectral ACC amplitude was the strongest predictor. Conclusions The results suggest that both peripheral and central electrophysiological measures of spatial and spectral selectivity provide valuable information about speech perception. Clinically, it is often desirable to optimize performance for individual CI users. These results suggest that ECAP measures may be the most useful for within-subject applications, when multiple measures are performed to make decisions about processor options. They also suggest that if the goal is to compare performance across individuals based on single measure, then processing central to the auditory nerve (specifically, cortical measures of discriminability) should be considered. PMID:25658746

A comparison of spectral decorrelation techniques and performance evaluation metrics for a wavelet-based, multispectral data compression algorithm

NASA Technical Reports Server (NTRS)

Matic, Roy M.; Mosley, Judith I.

1994-01-01

Future space-based, remote sensing systems will have data transmission requirements that exceed available downlinks necessitating the use of lossy compression techniques for multispectral data. In this paper, we describe several algorithms for lossy compression of multispectral data which combine spectral decorrelation techniques with an adaptive, wavelet-based, image compression algorithm to exploit both spectral and spatial correlation. We compare the performance of several different spectral decorrelation techniques including wavelet transformation in the spectral dimension. The performance of each technique is evaluated at compression ratios ranging from 4:1 to 16:1. Performance measures used are visual examination, conventional distortion measures, and multispectral classification results. We also introduce a family of distortion metrics that are designed to quantify and predict the effect of compression artifacts on multi spectral classification of the reconstructed data.

[Study on Application of NIR Spectral Information Screening in Identification of Maca Origin].

PubMed

Wang, Yuan-zhong; Zhao, Yan-li; Zhang, Ji; Jin, Hang

2016-02-01

Medicinal and edible plant Maca is rich in various nutrients and owns great medicinal value. Based on near infrared diffuse reflectance spectra, 139 Maca samples collected from Peru and Yunnan were used to identify their geographical origins. Multiplication signal correction (MSC) coupled with second derivative (SD) and Norris derivative filter (ND) was employed in spectral pretreatment. Spectrum range (7,500-4,061 cm⁻¹) was chosen by spectrum standard deviation. Combined with principal component analysis-mahalanobis distance (PCA-MD), the appropriate number of principal components was selected as 5. Based on the spectrum range and the number of principal components selected, two abnormal samples were eliminated by modular group iterative singular sample diagnosis method. Then, four methods were used to filter spectral variable information, competitive adaptive reweighted sampling (CARS), monte carlo-uninformative variable elimination (MC-UVE), genetic algorithm (GA) and subwindow permutation analysis (SPA). The spectral variable information filtered was evaluated by model population analysis (MPA). The results showed that RMSECV(SPA) > RMSECV(CARS) > RMSECV(MC-UVE) > RMSECV(GA), were 2. 14, 2. 05, 2. 02, and 1. 98, and the spectral variables were 250, 240, 250 and 70, respectively. According to the spectral variable filtered, partial least squares discriminant analysis (PLS-DA) was used to build the model, with random selection of 97 samples as training set, and the other 40 samples as validation set. The results showed that, R²: GA > MC-UVE > CARS > SPA, RMSEC and RMSEP: GA < MC-UVE < CARS

Large-scale automated image analysis for computational profiling of brain tissue surrounding implanted neuroprosthetic devices using Python.

PubMed

Rey-Villamizar, Nicolas; Somasundar, Vinay; Megjhani, Murad; Xu, Yan; Lu, Yanbin; Padmanabhan, Raghav; Trett, Kristen; Shain, William; Roysam, Badri

2014-01-01

In this article, we describe the use of Python for large-scale automated server-based bio-image analysis in FARSIGHT, a free and open-source toolkit of image analysis methods for quantitative studies of complex and dynamic tissue microenvironments imaged by modern optical microscopes, including confocal, multi-spectral, multi-photon, and time-lapse systems. The core FARSIGHT modules for image segmentation, feature extraction, tracking, and machine learning are written in C++, leveraging widely used libraries including ITK, VTK, Boost, and Qt. For solving complex image analysis tasks, these modules must be combined into scripts using Python. As a concrete example, we consider the problem of analyzing 3-D multi-spectral images of brain tissue surrounding implanted neuroprosthetic devices, acquired using high-throughput multi-spectral spinning disk step-and-repeat confocal microscopy. The resulting images typically contain 5 fluorescent channels. Each channel consists of 6000 × 10,000 × 500 voxels with 16 bits/voxel, implying image sizes exceeding 250 GB. These images must be mosaicked, pre-processed to overcome imaging artifacts, and segmented to enable cellular-scale feature extraction. The features are used to identify cell types, and perform large-scale analysis for identifying spatial distributions of specific cell types relative to the device. Python was used to build a server-based script (Dell 910 PowerEdge servers with 4 sockets/server with 10 cores each, 2 threads per core and 1TB of RAM running on Red Hat Enterprise Linux linked to a RAID 5 SAN) capable of routinely handling image datasets at this scale and performing all these processing steps in a collaborative multi-user multi-platform environment. Our Python script enables efficient data storage and movement between computers and storage servers, logs all the processing steps, and performs full multi-threaded execution of all codes, including open and closed-source third party libraries.

Monitoring Fatigue Status with HRV Measures in Elite Athletes: An Avenue Beyond RMSSD?

PubMed

Schmitt, Laurent; Regnard, Jacques; Millet, Grégoire P

2015-01-01

Among the tools proposed to assess the athlete's "fatigue," the analysis of heart rate variability (HRV) provides an indirect evaluation of the settings of autonomic control of heart activity. HRV analysis is performed through assessment of time-domain indices, the square root of the mean of the sum of the squares of differences between adjacent normal R-R intervals (RMSSD) measured during short (5 min) recordings in supine position upon awakening in the morning and particularly the logarithm of RMSSD (LnRMSSD) has been proposed as the most useful resting HRV indicator. However, if RMSSD can help the practitioner to identify a global "fatigue" level, it does not allow discriminating different types of fatigue. Recent results using spectral HRV analysis highlighted firstly that HRV profiles assessed in supine and standing positions are independent and complementary; and secondly that using these postural profiles allows the clustering of distinct sub-categories of "fatigue." Since, cardiovascular control settings are different in standing and lying posture, using the HRV figures of both postures to cluster fatigue state embeds information on the dynamics of control responses. Such, HRV spectral analysis appears more sensitive and enlightening than time-domain HRV indices. The wealthier information provided by this spectral analysis should improve the monitoring of the adaptive training-recovery process in athletes.

Evans hole and non linear optical activity in Bis(melaminium) sulphate dihydrate: A vibrational spectral study.

PubMed

Suresh Kumar, V R; Binoy, J; Dawn Dharma Roy, S; Marchewka, M K; Jayakumar, V S

2015-01-01

Bis(melaminium) sulphate dihydrate (BMSD), an interesting melaminium derivative for nonlinear optical activity, has been subjected to vibrational spectral analysis using FT IR and FT Raman spectra. The analysis has been aided by the Potential Energy Distribution (PED) of vibrational spectral bands, derived using density functional theory (DFT) at B3LYP/6-31G(d) level. The geometry is found to correlate well with the XRD structure and the band profiles for certain vibrations in the finger print region have been theoretically explained using Evans hole. The detailed Natural Bond Orbital (NBO) analysis of the hydrogen bonding in BMSD has also been carried out to understand the correlation between the stabilization energy of hyperconjugation of the lone pair of donor with the σ(∗) orbital of hydrogen-acceptor bond and the strength of hydrogen bond. The theoretical calculation shows that BMSD has NLO efficiency, 2.66 times that of urea. The frontier molecular orbital analysis points to a charge transfer, which contributes to NLO activity, through N-H…O intermolecular hydrogen bonding between the melaminium ring and the sulphate. The molecular electrostatic potential (MEP) mapping has also been performed for the detailed analysis of the mutual interactions between melaminium ring and sulphate ion. Copyright © 2015 Elsevier B.V. All rights reserved.

The hypoxia model in human psychopharmacology: neurophysiological and psychometric studies with aniracetam i.v.

PubMed

Saletu, B; Grünberger, J

1984-01-01

Changes in human brain function and mental performance under hypoxic hypoxidosis as well as after intravenous injection of aniracetam - a new potentially nootropic 2-pyrrolidinone derivative - were investigated in a double-blind placebo-controlled study utilizing computer-assisted spectral analysis of the EEG and psychometric tests. Hypoxic hypoxidosis was induced by a fixed gas combination of 11.2% O2 and 88.8% N2, which was inhaled under normobaric conditions by 10 male healthy volunteers. The following substances were injected intravenously at weekly intervals according to a latin square design: placebo, 10 mg and 100 mg aniracetam and the solvent under hypoxic conditions as well as placebo under normoxic conditions. Spectral analysis of the EEG recorded under hypoxia demonstrated neurophysiological alterations indicative of a deterioration in vigilance, which was also reflected by a deterioration in psychomotor activity and mnestic performance in the psychometric tests. Aniracetam i.v. attenuated the hypoxia-induced deterioration of brain function and mental performance, thus exhibiting protective properties against hypoxia in man. The usefulness of the hypoxia model in the screening of antihypoxidotic compounds is discussed.

SMV⊥: Simplex of maximal volume based upon the Gram-Schmidt process

NASA Astrophysics Data System (ADS)

Salazar-Vazquez, Jairo; Mendez-Vazquez, Andres

2015-10-01

In recent years, different algorithms for Hyperspectral Image (HI) analysis have been introduced. The high spectral resolution of these images allows to develop different algorithms for target detection, material mapping, and material identification for applications in Agriculture, Security and Defense, Industry, etc. Therefore, from the computer science's point of view, there is fertile field of research for improving and developing algorithms in HI analysis. In some applications, the spectral pixels of a HI can be classified using laboratory spectral signatures. Nevertheless, for many others, there is no enough available prior information or spectral signatures, making any analysis a difficult task. One of the most popular algorithms for the HI analysis is the N-FINDR because it is easy to understand and provides a way to unmix the original HI in the respective material compositions. The N-FINDR is computationally expensive and its performance depends on a random initialization process. This paper proposes a novel idea to reduce the complexity of the N-FINDR by implementing a bottom-up approach based in an observation from linear algebra and the use of the Gram-Schmidt process. Therefore, the Simplex of Maximal Volume Perpendicular (SMV⊥) algorithm is proposed for fast endmember extraction in hyperspectral imagery. This novel algorithm has complexity O(n) with respect to the number of pixels. In addition, the evidence shows that SMV⊥ calculates a bigger volume, and has lower computational time complexity than other poular algorithms on synthetic and real scenarios.

Laser Doppler velocimeter system simulation for sensing aircraft wake vortices. Part 2: Processing and analysis of LDV data (for runs 1023 and 2023)

NASA Technical Reports Server (NTRS)

Meng, J. C. S.; Thomson, J. A. L.

1975-01-01

A data analysis program constructed to assess LDV system performance, to validate the simulation model, and to test various vortex location algorithms is presented. Real or simulated Doppler spectra versus range and elevation is used and the spatial distributions of various spectral moments or other spectral characteristics are calculated and displayed. Each of the real or simulated scans can be processed by one of three different procedures: simple frequency or wavenumber filtering, matched filtering, and deconvolution filtering. The final output is displayed as contour plots in an x-y coordinate system, as well as in the form of vortex tracks deduced from the maxima of the processed data. A detailed analysis of run number 1023 and run number 2023 is presented to demonstrate the data analysis procedure. Vortex tracks and system range resolutions are compared with theoretical predictions.

Analysis of thematic mapper simulator data collected over eastern North Dakota

NASA Technical Reports Server (NTRS)

Anderson, J. E. (Principal Investigator)

1982-01-01

The results of the analysis of aircraft-acquired thematic mapper simulator (TMS) data, collected to investigate the utility of thematic mapper data in crop area and land cover estimates, are discussed. Results of the analysis indicate that the seven-channel TMS data are capable of delineating the 13 crop types included in the study to an overall pixel classification accuracy of 80.97% correct, with relative efficiencies for four crop types examined between 1.62 and 26.61. Both supervised and unsupervised spectral signature development techniques were evaluated. The unsupervised methods proved to be inferior (based on analysis of variance) for the majority of crop types considered. Given the ground truth data set used for spectral signature development as well as evaluation of performance, it is possible to demonstrate which signature development technique would produce the highest percent correct classification for each crop type.

Reformulation of Traditional Chamomile Oil: Quality Controls and Fingerprint Presentation Based on Cluster Analysis of Attenuated Total Reflectance–Infrared Spectral Data

PubMed Central

Sakhteman, Amirhossein; Faridi, Pouya; Daneshamouz, Saeid; Akbarizadeh, Amin Reza; Borhani-Haghighi, Afshin; Mohagheghzadeh, Abdolali

2017-01-01

Herbal oils have been widely used in Iran as medicinal compounds dating back to thousands of years in Iran. Chamomile oil is widely used as an example of traditional oil. We remade chamomile oils and tried to modify it with current knowledge and facilities. Six types of oil (traditional and modified) were prepared. Microbial limit tests and physicochemical tests were performed on them. Also, principal component analysis, hierarchical cluster analysis, and partial least squares discriminant analysis were done on the spectral data of attenuated total reflectance–infrared in order to obtain insight based on classification pattern of the samples. The results show that we can use modified versions of the chamomile oils (modified Clevenger-type apparatus method and microwave method) with the same content of traditional ones and with less microbial contaminations and better physicochemical properties. PMID:28585466

Reformulation of Traditional Chamomile Oil: Quality Controls and Fingerprint Presentation Based on Cluster Analysis of Attenuated Total Reflectance-Infrared Spectral Data.

PubMed

Zargaran, Arman; Sakhteman, Amirhossein; Faridi, Pouya; Daneshamouz, Saeid; Akbarizadeh, Amin Reza; Borhani-Haghighi, Afshin; Mohagheghzadeh, Abdolali

2017-10-01

Herbal oils have been widely used in Iran as medicinal compounds dating back to thousands of years in Iran. Chamomile oil is widely used as an example of traditional oil. We remade chamomile oils and tried to modify it with current knowledge and facilities. Six types of oil (traditional and modified) were prepared. Microbial limit tests and physicochemical tests were performed on them. Also, principal component analysis, hierarchical cluster analysis, and partial least squares discriminant analysis were done on the spectral data of attenuated total reflectance-infrared in order to obtain insight based on classification pattern of the samples. The results show that we can use modified versions of the chamomile oils (modified Clevenger-type apparatus method and microwave method) with the same content of traditional ones and with less microbial contaminations and better physicochemical properties.

A new approach for SSVEP detection using PARAFAC and canonical correlation analysis.

PubMed

Tello, Richard; Pouryazdian, Saeed; Ferreira, Andre; Beheshti, Soosan; Krishnan, Sridhar; Bastos, Teodiano

2015-01-01

This paper presents a new way for automatic detection of SSVEPs through correlation analysis between tensor models. 3-way EEG tensor of channel × frequency × time is decomposed into constituting factor matrices using PARAFAC model. PARAFAC analysis of EEG tensor enables us to decompose multichannel EEG into constituting temporal, spectral and spatial signatures. SSVEPs characterized with localized spectral and spatial signatures are then detected exploiting a correlation analysis between extracted signatures of the EEG tensor and the corresponding simulated signatures of all target SSVEP signals. The SSVEP that has the highest correlation is selected as the intended target. Two flickers blinking at 8 and 13 Hz were used as visual stimuli and the detection was performed based on data packets of 1 second without overlapping. Five subjects participated in the experiments and the highest classification rate of 83.34% was achieved, leading to the Information Transfer Rate (ITR) of 21.01 bits/min.

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.

[Research on symmetrical optical waveguide based surface plasmon resonance sensing with spectral interrogation].

PubMed

Zhang, Yi-long; Liu, Le; Guo, Jun; Zhang, Peng-fei; Guo, Ji-hua; Ma, Hui; He, Yong-hong

2015-02-01

Surface plasmon resonance (SPR) sensors with spectral interrogation can adopt fiber to transmit light signals, thus leaving the sensing part separated, which is very convenient for miniaturization, remote-sensing and on-site analysis. Symmetrical optical waveguide (SOW) SPR has the same refractive index of the-two buffer media layers adjacent to the metal film, resulting in longer propagation distance, deeper penetration depth and better performance compared to conventional SPR In the present paper, we developed a symmetrical optical, waveguide (SOW) SPR sensor with wavelength interrogation. In the system, MgF2-Au-MgF2 film was used as SOW module for glucose sensing, and a fiber based light source and detection was used in the spectral interrogation. In the experiment, a refractive index resolution of 2.8 x 10(-7) RIU in fluid protocol was acquired. This technique provides advantages of high resolution and could have potential use in compact design, on-site analysis and remote sensing.

Frequency characteristics of the heart rate variability produced by Cheyne-Stokes respiration during 24-hr ambulatory electrocardiographic monitoring.

PubMed

Ichimaru, Y; Yanaga, T

1989-06-01

Spectral analysis of heart rates during 24-hr ambulatory electrocardiographic monitoring has been carried out to characterize the heart rate spectral components of Cheyne-Stokes respiration (CSR) by using fast Fourier transformation (FFT). Eight patients with congestive heart failure were selected for the study. FFT analyses have been performed for 614.4 sec. Out of the power spectrum, five parameters were extracted to characterize the CSR. The low peak frequencies in eight subjects were between 0.0179 Hz (56 sec) and 0.0081 Hz (123 sec). The algorithms used to detect CSR are the followings: (i) if the LFPA/ULFA ratios were above the absolute value of 1.0, and (ii) the LFPP/MLFP ratios were above the absolute values of 4.0, then the power spectrum is suggestive of CSR. We conclude that the automatic detection of CSR by heart rate spectral analysis during ambulatory ECG monitoring may afford a tool for the evaluation of the patients with congestive heart failure.

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.

Power spectral analysis of R-R interval variability before and during the sinusoidal heart rate pattern in fetal lambs.

PubMed

Suzuki, T; Okamura, K; Kimura, Y; Watanabe, T; Yaegashi, N; Murotsuki, J; Uehara, S; Yajima, A

2000-05-01

The appearance of the sinusoidal heart rate pattern found on fetal cardiotocograms has not been fully explained, either physiologically or clinically. In this study we performed power spectral analysis on the sinusoidal heart rate pattern obtained by administration of arginine vasopressin and atropine sulfate to investigate its frequency components in fetal lambs with long-term instrument implantation. Eleven tests were performed in 4 fetal lambs at 120 to 130 days' gestation. An artificial sinusoidal heart rate pattern was obtained by administration of atropine sulfate and arginine vasopressin in 9 tests. An autoregression model was used to compare the spectral patterns before and during the sinusoidal heart rate pattern. Marked decreases in low-frequency (0.025-0.125 cycles/beat) and high-frequency (0.2-0.5 cycles/beat) areas were observed in the presence of the sinusoidal heart rate pattern. However, there were no significant changes in the very-low-frequency area (0.01-0.025 cycles/beat), which corresponds to the frequency of the sinusoidal heart rate pattern. The sinusoidal heart rate pattern may represent a very low-frequency component inherent in fetal heart rate variability that appears when low- and high-frequency components are reduced as a result of strongly suppressed autonomic nervous activity.

Flame analysis using image processing techniques

NASA Astrophysics Data System (ADS)

Her Jie, Albert Chang; Zamli, Ahmad Faizal Ahmad; Zulazlan Shah Zulkifli, Ahmad; Yee, Joanne Lim Mun; Lim, Mooktzeng

2018-04-01

This paper presents image processing techniques with the use of fuzzy logic and neural network approach to perform flame analysis. Flame diagnostic is important in the industry to extract relevant information from flame images. Experiment test is carried out in a model industrial burner with different flow rates. Flame features such as luminous and spectral parameters are extracted using image processing and Fast Fourier Transform (FFT). Flame images are acquired using FLIR infrared camera. Non-linearities such as thermal acoustic oscillations and background noise affect the stability of flame. Flame velocity is one of the important characteristics that determines stability of flame. In this paper, an image processing method is proposed to determine flame velocity. Power spectral density (PSD) graph is a good tool for vibration analysis where flame stability can be approximated. However, a more intelligent diagnostic system is needed to automatically determine flame stability. In this paper, flame features of different flow rates are compared and analyzed. The selected flame features are used as inputs to the proposed fuzzy inference system to determine flame stability. Neural network is used to test the performance of the fuzzy inference system.

Hyperspectral Biofilm Classification Analysis for Carrying Capacity of Migratory Birds in the South Bay Salt Ponds

NASA Technical Reports Server (NTRS)

Hsu, Wei-Chen; Kuss, Amber Jean; Ketron, Tyler; Nguyen, Andrew; Remar, Alex Covello; Newcomer, Michelle; Fleming, Erich; Debout, Leslie; Debout, Brad; Detweiler, Angela;

Delineating gas bearing reservoir by using spectral decomposition attribute: Case study of Steenkool formation, Bintuni Basin

NASA Astrophysics Data System (ADS)

Haris, A.; Pradana, G. S.; Riyanto, A.

2017-07-01

Tectonic setting of the Bird Head Papua Island becomes an important model for petroleum system in Eastern part of Indonesia. The current exploration has been started since the oil seepage finding in Bintuni and Salawati Basin. The biogenic gas in shallow layer turns out to become an interesting issue in the hydrocarbon exploration. The hydrocarbon accumulation appearance in a shallow layer with dry gas type, appeal biogenic gas for further research. This paper aims at delineating the sweet spot hydrocarbon potential in shallow layer by applying the spectral decomposition technique. The spectral decomposition is decomposing the seismic signal into an individual frequency, which has significant geological meaning. One of spectral decomposition methods is Continuous Wavelet Transform (CWT), which transforms the seismic signal into individual time and frequency simultaneously. This method is able to make easier time-frequency map analysis. When time resolution increases, the frequency resolution will be decreased, and vice versa. In this study, we perform low-frequency shadow zone analysis in which the amplitude anomaly at a low frequency of 15 Hz was observed and we then compare it to the amplitude at the mid (20 Hz) and the high-frequency (30 Hz). The appearance of the amplitude anomaly at a low frequency was disappeared at high frequency, this anomaly disappears. The spectral decomposition by using CWT algorithm has been successfully applied to delineate the sweet spot zone.

Development and Evaluation of a Spectral Analysis Method to Eliminate Organic Interference with Cavity Ring-Down Measurements of Water Isotope Ratios.

NASA Astrophysics Data System (ADS)

Lin, Z.; Kim-Hak, D.; Popp, B. N.; Wallsgrove, N.; Kagawa-Viviani, A.; Johnson, J.

2017-12-01

Cavity ring-down spectroscopy (CRDS) is a technology based on the spectral absorption of gas molecules of interest at specific spectral regions. The CRDS technique enables the analysis of hydrogen and oxygen stable isotope ratios of water by directly measuring individual isotopologue absorption peaks such as H16OH, H18OH, and D16OH. Early work demonstrated that the accuracy of isotope analysis by CRDS and other laser-based absorption techniques could be compromised by spectral interference from organic compounds, in particular methanol and ethanol, which can be prevalent in ecologically-derived waters. There have been several methods developed by various research groups including Picarro to address the organic interference challenge. Here, we describe an organic fitter and a post-processing algorithm designed to improve the accuracy of the isotopic analysis of the "organic contaminated" water specifically for Picarro models L2130-i and L2140-i. To create the organic fitter, the absorption features of methanol around 7200 cm-1 were characterized and incorporated into spectral analysis. Since there was residual interference remaining after applying the organic fitter, a statistical model was also developed for post-processing correction. To evaluate the performance of the organic fitter and the postprocessing correction, we conducted controlled experiments on the L2130-i for two water samples with different isotope ratios blended with varying amounts of methanol (0-0.5%) and ethanol (0-5%). When the original fitter was not used for spectral analysis, the addition of 0.5% methanol changed the apparent isotopic composition of the water samples by +62‰ for δ18O values and +97‰ for δ2H values, and the addition of 5% ethanol changed the apparent isotopic composition by -0.5‰ for δ18O values and -3‰ for δ2H values. When the organic fitter was used for spectral analysis, the maximum methanol-induced errors were reduced to +4‰ for δ18O values and +5‰ for δ2H values, and the maximum ethanol-induced errors were unchanged. When the organic fitter was combined with the post-processing correction, up to 99.8% of the total methanol-induced errors and 96% of the total ethanol-induced errors could be corrected. The applicability of the algorithm to natural samples such as plant and soil waters will be investigated.

3D tensor-based blind multispectral image decomposition for tumor demarcation

NASA Astrophysics Data System (ADS)

Kopriva, Ivica; Peršin, Antun

2010-03-01

Blind decomposition of multi-spectral fluorescent image for tumor demarcation is formulated exploiting tensorial structure of the image. First contribution of the paper is identification of the matrix of spectral responses and 3D tensor of spatial distributions of the materials present in the image from Tucker3 or PARAFAC models of 3D image tensor. Second contribution of the paper is clustering based estimation of the number of the materials present in the image as well as matrix of their spectral profiles. 3D tensor of the spatial distributions of the materials is recovered through 3-mode multiplication of the multi-spectral image tensor and inverse of the matrix of spectral profiles. Tensor representation of the multi-spectral image preserves its local spatial structure that is lost, due to vectorization process, when matrix factorization-based decomposition methods (such as non-negative matrix factorization and independent component analysis) are used. Superior performance of the tensor-based image decomposition over matrix factorization-based decompositions is demonstrated on experimental red-green-blue (RGB) image with known ground truth as well as on RGB fluorescent images of the skin tumor (basal cell carcinoma).

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

PubMed

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

2017-06-01

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

[Evaluation of a simplified index (spectral entropy) about sleep state of electrocardiogram recorded by a simplified polygraph, MemCalc-Makin2].

PubMed

Ohisa, Noriko; Ogawa, Hiromasa; Murayama, Nobuki; Yoshida, Katsumi

2010-02-01

Polysomnography (PSG) is the gold standard for the diagnosis of sleep apnea hypopnea syndrome (SAHS), but it takes time to analyze the PSG and PSG cannot be performed repeatedly because of efforts and costs. Therefore, simplified sleep respiratory disorder indices in which are reflected the PSG results are needed. The Memcalc method, which is a combination of the maximum entropy method for spectral analysis and the non-linear least squares method for fitting analysis (Makin2, Suwa Trust, Tokyo, Japan) has recently been developed. Spectral entropy which is derived by the Memcalc method might be useful to expressing the trend of time-series behavior. Spectral entropy of ECG which is calculated with the Memcalc method was evaluated by comparing to the PSG results. Obstructive SAS patients (n = 79) and control volanteer (n = 7) ECG was recorded using MemCalc-Makin2 (GMS) with PSG recording using Alice IV (Respironics) from 20:00 to 6:00. Spectral entropy of ECG, which was calculated every 2 seconds using the Memcalc method, was compared to sleep stages which were analyzed manually from PSG recordings. Spectral entropy value (-0.473 vs. -0.418, p < 0.05) were significantly increased in the OSAHS compared to the control. For the entropy cutoff level of -0.423, sensitivity and specificity for OSAHS were 86.1% and 71.4%, respectively, resulting in a receiver operating characteristic with an area under the curve of 0.837. The absolute value of entropy had inverse correlation with stage 3. Spectral entropy, which was calculated with Memcalc method, might be a possible index evaluating the quality of sleep.

Understanding the spatial distribution of eroded areas in the former rural homelands of South Africa: Comparative evidence from two new non-commercial multispectral sensors

NASA Astrophysics Data System (ADS)

Sepuru, Terrence Koena; Dube, Timothy

2018-07-01

In this study, we determine the most suitable multispectral sensor that can accurately detect and map eroded areas from other land cover types in Sekhukhune rural district, Limpopo Province, South Africa. Specifically, the study tested the ability of multi-date (wet and dry season) Landsat 8 OLI and Sentinel-2 MSI images in detecting and mapping eroded areas. The implementation was done, using a robust non-parametric classification ensemble: Discriminant Analysis (DA). Three sets of analysis were applied (Analysis 1: Spectral bands as independent dataset; Analysis 2: Spectral vegetation indices as independent and Analysis 3: Combined spectral bands and spectral vegetation indices). Overall classification accuracies ranging between 80% to 81.90% for MSI and 75.71%-80.95% for OLI were derived for the wet and dry season, respectively. The integration of spectral bands and spectral vegetation indices showed that Sentinel-2 (OA = 83, 81%), slightly performed better than Landsat 8, with 82, 86%. The use of bands and vegetation indices as independent dataset resulted in slightly weaker results for both sensors. Sentinel-2 MSI bands located in the NIR (0.785-0.900 μm), red edge (0.698-0.785 μm) and SWIR (1.565-2.280 μm) regions were selected as the most optimal for discriminating degraded soils from other land cover types. However, for Landsat 8OLI, only the SWIR (1.560-2.300 μm), NIR (0.845-0.885 μm) region were selected as the best regions. Of the eighteen spectral vegetation indices computed, NDVI and SAVI and SAVI and Global Environmental Monitoring Index (GEMI) were ranked selected as the most suitable for detecting and mapping soil erosion. Additionally, SRTM DEM derived information illustrates that for both sensors eroded areas occur on sites that are 600 m and 900 m of altitude with similar trends observed in both dry and wet season maps. Findings of this work emphasize the importance of free and readily available new generation sensors in continuous landscape-scale soil erosion monitoring. Besides, such information can help to identify hotspots and potentially vulnerable areas, as well as aid in developing possible control and mitigation measures.

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.

Effects of vibration and shock on the performance of gas-bearing space-power Brayton cycle turbomachinery. Part 3: Sinusoidal and random vibration data reduction and evaluation, and random vibration probability analysis

NASA Technical Reports Server (NTRS)

Tessarzik, J. M.; Chiang, T.; Badgley, R. H.

1973-01-01

The random vibration response of a gas bearing rotor support system has been experimentally and analytically investigated in the amplitude and frequency domains. The NASA Brayton Rotating Unit (BRU), a 36,000 rpm, 10 KWe turbogenerator had previously been subjected in the laboratory to external random vibrations, and the response data recorded on magnetic tape. This data has now been experimentally analyzed for amplitude distribution and magnetic tape. This data has now been experimentally analyzed for amplitude distribution and frequency content. The results of the power spectral density analysis indicate strong vibration responses for the major rotor-bearing system components at frequencies which correspond closely to their resonant frequencies obtained under periodic vibration testing. The results of amplitude analysis indicate an increasing shift towards non-Gaussian distributions as the input level of external vibrations is raised. Analysis of axial random vibration response of the BRU was performed by using a linear three-mass model. Power spectral densities, the root-mean-square value of the thrust bearing surface contact were calculated for specified input random excitation.

Spectral Unmixing Analysis of Time Series Landsat 8 Images

NASA Astrophysics Data System (ADS)

Zhuo, R.; Xu, L.; Peng, J.; Chen, Y.

2018-05-01

Temporal analysis of Landsat 8 images opens up new opportunities in the unmixing procedure. Although spectral analysis of time series Landsat imagery has its own advantage, it has rarely been studied. Nevertheless, using the temporal information can provide improved unmixing performance when compared to independent image analyses. Moreover, different land cover types may demonstrate different temporal patterns, which can aid the discrimination of different natures. Therefore, this letter presents time series K-P-Means, a new solution to the problem of unmixing time series Landsat imagery. The proposed approach is to obtain the "purified" pixels in order to achieve optimal unmixing performance. The vertex component analysis (VCA) is used to extract endmembers for endmember initialization. First, nonnegative least square (NNLS) is used to estimate abundance maps by using the endmember. Then, the estimated endmember is the mean value of "purified" pixels, which is the residual of the mixed pixel after excluding the contribution of all nondominant endmembers. Assembling two main steps (abundance estimation and endmember update) into the iterative optimization framework generates the complete algorithm. Experiments using both simulated and real Landsat 8 images show that the proposed "joint unmixing" approach provides more accurate endmember and abundance estimation results compared with "separate unmixing" approach.

Research progress in Asia on methods of processing laser-induced breakdown spectroscopy data

NASA Astrophysics Data System (ADS)

Guo, Yang-Min; Guo, Lian-Bo; Li, Jia-Ming; Liu, Hong-Di; Zhu, Zhi-Hao; Li, Xiang-You; Lu, Yong-Feng; Zeng, Xiao-Yan

2016-10-01

Laser-induced breakdown spectroscopy (LIBS) has attracted much attention in terms of both scientific research and industrial application. An important branch of LIBS research in Asia, the development of data processing methods for LIBS, is reviewed. First, the basic principle of LIBS and the characteristics of spectral data are briefly introduced. Next, two aspects of research on and problems with data processing methods are described: i) the basic principles of data preprocessing methods are elaborated in detail on the basis of the characteristics of spectral data; ii) the performance of data analysis methods in qualitative and quantitative analysis of LIBS is described. Finally, a direction for future development of data processing methods for LIBS is also proposed.

Thermo spectral analysis (TSA) of living human skin by FT-IR -Development of a diagnostic method for the early detection of chronic diseases

NASA Astrophysics Data System (ADS)

Folberth, W.; Heim, G.

1985-12-01

A Fourier spectrometer was used in order to measure the spectral emissivity E(k) of human skin in the FIR region k=190-420 cm-1. Three studies on patient groups with defined chronic diseases have been performed: patients with untreated bronchial carcinoma, patients with rheumatic arthritis and patients with chronic renal insufficiency. In comparison with a symptomfree control group all patient groups show significant differences in E(k). As result of a discriminant analysis a separation of 95.7% between carcinoma patients and control persons is possible. The separation quotes between the other groups indicate that patients with malignant neoplasms can be discriminated from other chronically ill persons.

Spatial compression algorithm for the analysis of very large multivariate images

DOEpatents

Keenan, Michael R [Albuquerque, NM

2008-07-15

A method for spatially compressing data sets enables the efficient analysis of very large multivariate images. The spatial compression algorithms use a wavelet transformation to map an image into a compressed image containing a smaller number of pixels that retain the original image's information content. Image analysis can then be performed on a compressed data matrix consisting of a reduced number of significant wavelet coefficients. Furthermore, a block algorithm can be used for performing common operations more efficiently. The spatial compression algorithms can be combined with spectral compression algorithms to provide further computational efficiencies.

Convolutional neural networks for vibrational spectroscopic data analysis.

PubMed

Acquarelli, Jacopo; van Laarhoven, Twan; Gerretzen, Jan; Tran, Thanh N; Buydens, Lutgarde M C; Marchiori, Elena

2017-02-15

In this work we show that convolutional neural networks (CNNs) can be efficiently used to classify vibrational spectroscopic data and identify important spectral regions. CNNs are the current state-of-the-art in image classification and speech recognition and can learn interpretable representations of the data. These characteristics make CNNs a good candidate for reducing the need for preprocessing and for highlighting important spectral regions, both of which are crucial steps in the analysis of vibrational spectroscopic data. Chemometric analysis of vibrational spectroscopic data often relies on preprocessing methods involving baseline correction, scatter correction and noise removal, which are applied to the spectra prior to model building. Preprocessing is a critical step because even in simple problems using 'reasonable' preprocessing methods may decrease the performance of the final model. We develop a new CNN based method and provide an accompanying publicly available software. It is based on a simple CNN architecture with a single convolutional layer (a so-called shallow CNN). Our method outperforms standard classification algorithms used in chemometrics (e.g. PLS) in terms of accuracy when applied to non-preprocessed test data (86% average accuracy compared to the 62% achieved by PLS), and it achieves better performance even on preprocessed test data (96% average accuracy compared to the 89% achieved by PLS). For interpretability purposes, our method includes a procedure for finding important spectral regions, thereby facilitating qualitative interpretation of results. Copyright © 2016 Elsevier B.V. All rights reserved.

MicrOmega: a VIS/NIR hyperspectral microscope for in situ analysis in space

NASA Astrophysics Data System (ADS)

Leroi, V.; Bibring, J. P.; Berthé, M.

2008-07-01

MicrOmega is an ultra miniaturized spectral microscope for in situ analysis of samples. It is composed of 2 microscopes: one with a spatial sampling of 5 μm, working in 4 color in the visible range and one NIR hyperspectral microscope in the spectral range 0.9-4 μm with a spatial sampling of 20 μm per pixel (described in this paper). MicrOmega/NIR illuminates and images samples a few mm in size and acquires the NIR spectrum of each resolved pixel in up to 600 contiguous spectral channels. The goal of this instrument is to analyse in situ the composition of collected samples at almost their grain size scale, in a non destructive way. It should be among the first set of instruments who will analyse the sample and enable other complementary analyses to be performed on it. With the spectral range and resolution chosen, a wide variety of constituents can be identified: minerals, such as pyroxene and olivine, ferric oxides, hydrated phyllosilicates, sulfates and carbonates; ices and organics. The composition of the various phases within a given sample is a critical record of its formation and evolution. Coupled to the mapping information, it provides unique clues to describe the history of the parent body. In particular, the capability to identify hydrated grains and to characterize their adjacent phases has a huge potential in the search for potential bio-relics. We will present the major instrumental principles and specifications of MicrOmega/NIR, and its expected performances in particular for the ESA/ExoMars Mission.

Time-frequency analysis of human motion during rhythmic exercises.

PubMed

Omkar, S N; Vyas, Khushi; Vikranth, H N

2011-01-01

Biomechanical signals due to human movements during exercise are represented in time-frequency domain using Wigner Distribution Function (WDF). Analysis based on WDF reveals instantaneous spectral and power changes during a rhythmic exercise. Investigations were carried out on 11 healthy subjects who performed 5 cycles of sun salutation, with a body-mounted Inertial Measurement Unit (IMU) as a motion sensor. Variance of Instantaneous Frequency (I.F) and Instantaneous Power (I.P) for performance analysis of the subject is estimated using one-way ANOVA model. Results reveal that joint Time-Frequency analysis of biomechanical signals during motion facilitates a better understanding of grace and consistency during rhythmic exercise.

Test plane uniformity analysis for the MSFC solar simulator lamp array

NASA Technical Reports Server (NTRS)

Griner, D. B.

1976-01-01

A preliminary analysis was made on the solar simulator lamp array. It is an array of 405 tungsten halogen lamps with Fresnel lenses to achieve the required spectral distribution and collimation. A computer program was developed to analyze lamp array performance at the test plane. Measurements were made on individual lamp lens combinations to obtain data for the computer analysis. The analysis indicated that the performance of the lamp array was about as expected, except for a need to position the test plane within 2.7 m of the lamp array to achieve the desired 7 percent uniformity of illumination tolerance.

An adaptive band selection method for dimension reduction of hyper-spectral remote sensing image

NASA Astrophysics Data System (ADS)

Yu, Zhijie; Yu, Hui; Wang, Chen-sheng

2014-11-01

Hyper-spectral remote sensing data can be acquired by imaging the same area with multiple wavelengths, and it normally consists of hundreds of band-images. Hyper-spectral images can not only provide spatial information but also high resolution spectral information, and it has been widely used in environment monitoring, mineral investigation and military reconnaissance. However, because of the corresponding large data volume, it is very difficult to transmit and store Hyper-spectral images. Hyper-spectral image dimensional reduction technique is desired to resolve this problem. Because of the High relation and high redundancy of the hyper-spectral bands, it is very feasible that applying the dimensional reduction method to compress the data volume. This paper proposed a novel band selection-based dimension reduction method which can adaptively select the bands which contain more information and details. The proposed method is based on the principal component analysis (PCA), and then computes the index corresponding to every band. The indexes obtained are then ranked in order of magnitude from large to small. Based on the threshold, system can adaptively and reasonably select the bands. The proposed method can overcome the shortcomings induced by transform-based dimension reduction method and prevent the original spectral information from being lost. The performance of the proposed method has been validated by implementing several experiments. The experimental results show that the proposed algorithm can reduce the dimensions of hyper-spectral image with little information loss by adaptively selecting the band images.

Diverse Power Iteration Embeddings and Its Applications

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

Huang H.; Yoo S.; Yu, D.

2014-12-14

Abstract—Spectral Embedding is one of the most effective dimension reduction algorithms in data mining. However, its computation complexity has to be mitigated in order to apply it for real-world large scale data analysis. Many researches have been focusing on developing approximate spectral embeddings which are more efficient, but meanwhile far less effective. This paper proposes Diverse Power Iteration Embeddings (DPIE), which not only retains the similar efficiency of power iteration methods but also produces a series of diverse and more effective embedding vectors. We test this novel method by applying it to various data mining applications (e.g. clustering, anomaly detectionmore » and feature selection) and evaluating their performance improvements. The experimental results show our proposed DPIE is more effective than popular spectral approximation methods, and obtains the similar quality of classic spectral embedding derived from eigen-decompositions. Moreover it is extremely fast on big data applications. For example in terms of clustering result, DPIE achieves as good as 95% of classic spectral clustering on the complex datasets but 4000+ times faster in limited memory environment.« less

Proceedings of the Third Airborne Imaging Spectrometer Data Analysis Workshop

NASA Technical Reports Server (NTRS)

Vane, Gregg (Editor)

1987-01-01

Summaries of 17 papers presented at the workshop are published. After an overview of the imaging spectrometer program, time was spent discussing AIS calibration, performance, information extraction techniques, and the application of high spectral resolution imagery to problems of geology and botany.

Grain size mapping in shallow rivers using spectral information: a lab spectroradiometry perspective

NASA Astrophysics Data System (ADS)

Niroumand-Jadidi, Milad; Vitti, Alfonso

2017-10-01

Every individual attribute of a riverine environment defines the overall spectral signature to be observed by an optical sensor. The spectral characteristic of riverbed is influenced not only by the type but also the roughness of substrates. Motivated by this assumption, potential of optical imagery for mapping grain size of shallow rivers (< 1 m deep) is examined in this research. The previous studies concerned with grain size mapping are all built upon the texture analysis of exposed bed material using very high resolution (i.e. cm resolution) imagery. However, the application of texturebased techniques is limited to very low altitude sensors (e.g. UAVs) to ensure the sufficient spatial resolution. Moreover, these techniques are applicable only in the presence of exposed substrates along the river channel. To address these drawbacks, this study examines the effectiveness of spectral information to make distinction among grain sizes for submerged substrates. Spectroscopic experiments are performed in controlled condition of a hydraulic lab. The spectra are collected over a water flume in a range of water depths and bottoms with several grain sizes. A spectral convolution is performed to match the spectra to WorldView-2 spectral bands. The material type of substrates is considered the same for all the experiments with only variable roughness/size of grains. The spectra observed over dry beds revealed that the brightness/reflectance increases with the grain size across all the spectral bands. Based on this finding, the above-water spectra over a river channel are simulated considering different grain sizes in the bottom. A water column correction method is then used to retrieve the bottom reflectances. Then the inferred bottom reflectances are clustered to segregate among grain sizes. The results indicate high potential of the spectral approach for clustering grain sizes (overall accuracy of 92%) which opens up some horizons for mapping this valuable attribute of rivers using remotely sensed data.

Assessing FRET using Spectral Techniques

PubMed Central

Leavesley, Silas J.; Britain, Andrea L.; Cichon, Lauren K.; Nikolaev, Viacheslav O.; Rich, Thomas C.

2015-01-01

Förster resonance energy transfer (FRET) techniques have proven invaluable for probing the complex nature of protein–protein interactions, protein folding, and intracellular signaling events. These techniques have traditionally been implemented with the use of one or more fluorescence band-pass filters, either as fluorescence microscopy filter cubes, or as dichroic mirrors and band-pass filters in flow cytometry. In addition, new approaches for measuring FRET, such as fluorescence lifetime and acceptor photobleaching, have been developed. Hyperspectral techniques for imaging and flow cytometry have also shown to be promising for performing FRET measurements. In this study, we have compared traditional (filter-based) FRET approaches to three spectral-based approaches: the ratio of acceptor-to-donor peak emission, linear spectral unmixing, and linear spectral unmixing with a correction for direct acceptor excitation. All methods are estimates of FRET efficiency, except for one-filter set and three-filter set FRET indices, which are included for consistency with prior literature. In the first part of this study, spectrofluorimetric data were collected from a CFP–Epac–YFP FRET probe that has been used for intracellular cAMP measurements. All comparisons were performed using the same spectrofluorimetric datasets as input data, to provide a relevant comparison. Linear spectral unmixing resulted in measurements with the lowest coefficient of variation (0.10) as well as accurate fits using the Hill equation. FRET efficiency methods produced coefficients of variation of less than 0.20, while FRET indices produced coefficients of variation greater than 8.00. These results demonstrate that spectral FRET measurements provide improved response over standard, filter-based measurements. Using spectral approaches, single-cell measurements were conducted through hyperspectral confocal microscopy, linear unmixing, and cell segmentation with quantitative image analysis. Results from these studies confirmed that spectral imaging is effective for measuring subcellular, time-dependent FRET dynamics and that additional fluorescent signals can be readily separated from FRET signals, enabling multilabel studies of molecular interactions. PMID:23929684

Assessing FRET using spectral techniques.

PubMed

Leavesley, Silas J; Britain, Andrea L; Cichon, Lauren K; Nikolaev, Viacheslav O; Rich, Thomas C

2013-10-01

Förster resonance energy transfer (FRET) techniques have proven invaluable for probing the complex nature of protein-protein interactions, protein folding, and intracellular signaling events. These techniques have traditionally been implemented with the use of one or more fluorescence band-pass filters, either as fluorescence microscopy filter cubes, or as dichroic mirrors and band-pass filters in flow cytometry. In addition, new approaches for measuring FRET, such as fluorescence lifetime and acceptor photobleaching, have been developed. Hyperspectral techniques for imaging and flow cytometry have also shown to be promising for performing FRET measurements. In this study, we have compared traditional (filter-based) FRET approaches to three spectral-based approaches: the ratio of acceptor-to-donor peak emission, linear spectral unmixing, and linear spectral unmixing with a correction for direct acceptor excitation. All methods are estimates of FRET efficiency, except for one-filter set and three-filter set FRET indices, which are included for consistency with prior literature. In the first part of this study, spectrofluorimetric data were collected from a CFP-Epac-YFP FRET probe that has been used for intracellular cAMP measurements. All comparisons were performed using the same spectrofluorimetric datasets as input data, to provide a relevant comparison. Linear spectral unmixing resulted in measurements with the lowest coefficient of variation (0.10) as well as accurate fits using the Hill equation. FRET efficiency methods produced coefficients of variation of less than 0.20, while FRET indices produced coefficients of variation greater than 8.00. These results demonstrate that spectral FRET measurements provide improved response over standard, filter-based measurements. Using spectral approaches, single-cell measurements were conducted through hyperspectral confocal microscopy, linear unmixing, and cell segmentation with quantitative image analysis. Results from these studies confirmed that spectral imaging is effective for measuring subcellular, time-dependent FRET dynamics and that additional fluorescent signals can be readily separated from FRET signals, enabling multilabel studies of molecular interactions. © 2013 International Society for Advancement of Cytometry. Copyright © 2013 International Society for Advancement of Cytometry.

Radiometric Comparison between Sentinel 2A (S2A) Multispectral Imager (MSI) and Landsat 8 (L8) Operational Land Imager (OLI)

NASA Astrophysics Data System (ADS)

Micijevic, E.; Haque, M. O.

2016-12-01

With its forty-four year continuous data record, the Landsat image archive provides an invaluable source of information for essential climate variables, global land change studies and a variety of other applications. The latest in the series, Landsat 8, carries the Operational Land Imager (OLI), the sensor with an improved design compared to its predecessors, but with similar radiometric, spatial and spectral characteristics, to provide image data continuity. Sentinel 2A (S2A), launched in June 2015, carries the Multispectral Imager (MSI) that has a number of bands with spectral and radiometric characteristics similar to L8 OLI. As such, it offers an opportunity to augment the Landsat data record through increased frequency of acquisitions, when combined with OLI. In this study, we compared Top-of-Atmosphere (TOA) reflectance of matching spectral bands in MSI and OLI products. Comparison between S2A MSI and L8 OLI sensors was performed using image data acquired near simultaneously primarily over Pseudo Invariant Calibration Site (PICS) Libya 4, but also over other calibration test sites. Spectral differences between the two sensors were accounted for using their spectral filter profiles and a spectral signature of the site derived from EO1 Hyperion hyperspectral imagery. Temporal stability was also assessed through temporal trending of Top-of-Atmosphere (TOA) reflectance measured by the two sensors over PICS. The performed analysis suggests good agreement between the two sensors, within 5% for the costal aerosol band and better than 3% for other matching bands. It is important to note that whenever data from different sensors are used together in a study, the special attention need to be paid to the spectral band differences between the sensors because the necessary spectral difference adjustment is target dependent and may vary a lot from target to target.

A Marker-Based Approach for the Automated Selection of a Single Segmentation from a Hierarchical Set of Image Segmentations

NASA Technical Reports Server (NTRS)

Tarabalka, Y.; Tilton, J. C.; Benediktsson, J. A.; Chanussot, J.

2012-01-01

The Hierarchical SEGmentation (HSEG) algorithm, which combines region object finding with region object clustering, has given good performances for multi- and hyperspectral image analysis. This technique produces at its output a hierarchical set of image segmentations. The automated selection of a single segmentation level is often necessary. We propose and investigate the use of automatically selected markers for this purpose. In this paper, a novel Marker-based HSEG (M-HSEG) method for spectral-spatial classification of hyperspectral images is proposed. Two classification-based approaches for automatic marker selection are adapted and compared for this purpose. Then, a novel constrained marker-based HSEG algorithm is applied, resulting in a spectral-spatial classification map. Three different implementations of the M-HSEG method are proposed and their performances in terms of classification accuracies are compared. The experimental results, presented for three hyperspectral airborne images, demonstrate that the proposed approach yields accurate segmentation and classification maps, and thus is attractive for remote sensing image analysis.

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.

Evaluating the utility of mid-infrared spectral subspaces for predicting soil properties.

PubMed

Sila, Andrew M; Shepherd, Keith D; Pokhariyal, Ganesh P

2016-04-15

We propose four methods for finding local subspaces in large spectral libraries. The proposed four methods include (a) cosine angle spectral matching; (b) hit quality index spectral matching; (c) self-organizing maps and (d) archetypal analysis methods. Then evaluate prediction accuracies for global and subspaces calibration models. These methods were tested on a mid-infrared spectral library containing 1907 soil samples collected from 19 different countries under the Africa Soil Information Service project. Calibration models for pH, Mehlich-3 Ca, Mehlich-3 Al, total carbon and clay soil properties were developed for the whole library and for the subspace. Root mean square error of prediction was used to evaluate predictive performance of subspace and global models. The root mean square error of prediction was computed using a one-third-holdout validation set. Effect of pretreating spectra with different methods was tested for 1st and 2nd derivative Savitzky-Golay algorithm, multiplicative scatter correction, standard normal variate and standard normal variate followed by detrending methods. In summary, the results show that global models outperformed the subspace models. We, therefore, conclude that global models are more accurate than the local models except in few cases. For instance, sand and clay root mean square error values from local models from archetypal analysis method were 50% poorer than the global models except for subspace models obtained using multiplicative scatter corrected spectra with which were 12% better. However, the subspace approach provides novel methods for discovering data pattern that may exist in large spectral libraries.

USGS Digital Spectral Library splib06a

USGS Publications Warehouse

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

2007-01-01

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

All-metal meta-surfaces for narrowband light absorption and high performance sensing

NASA Astrophysics Data System (ADS)

Liu, Zhengqi; Liu, Guiqiang; Fu, Guolan; Liu, Xiaoshan; Huang, Zhenping; Gu, Gang

2016-11-01

We report an experimental scheme for high performance sensing by an all-metal meta-surface (AMMS) platform. A dual-band resonant absorption spectrum with a bandwidth down to a single-digit nanometer level and an absorbance up to 89% is achieved due to the surface lattice resonances supported by the resonators array and their hybridization coupling with the particle plasmon resonances. The sensing application in the analysis of the sodium chloride solution has been demonstrated, where remarkable changes from a spectral ‘dark state’ to ‘bright state’ and vice versa are observed. Sensing performance factors of the figure of merit exceeding 50 and the spectral intensity change related FoM* up to 1075 are simultaneously achieved. The corresponding detection limit is as low as 8.849  ×  10-6 RIU. These features make such an AMMS-based sensor a promising route for efficient bio-chemical sensing, etc.

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

PubMed

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

2010-06-01

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

Score-moment combined linear discrimination analysis (SMC-LDA) as an improved discrimination method.

PubMed

Han, Jintae; Chung, Hoeil; Han, Sung-Hwan; Yoon, Moon-Young

2007-01-01

A new discrimination method called the score-moment combined linear discrimination analysis (SMC-LDA) has been developed and its performance has been evaluated using three practical spectroscopic datasets. The key concept of SMC-LDA was to use not only the score from principal component analysis (PCA), but also the moment of the spectrum, as inputs for LDA to improve discrimination. Along with conventional score, moment is used in spectroscopic fields as an effective alternative for spectral feature representation. Three different approaches were considered. Initially, the score generated from PCA was projected onto a two-dimensional feature space by maximizing Fisher's criterion function (conventional PCA-LDA). Next, the same procedure was performed using only moment. Finally, both score and moment were utilized simultaneously for LDA. To evaluate discrimination performances, three different spectroscopic datasets were employed: (1) infrared (IR) spectra of normal and malignant stomach tissue, (2) near-infrared (NIR) spectra of diesel and light gas oil (LGO) and (3) Raman spectra of Chinese and Korean ginseng. For each case, the best discrimination results were achieved when both score and moment were used for LDA (SMC-LDA). Since the spectral representation character of moment was different from that of score, inclusion of both score and moment for LDA provided more diversified and descriptive information.

Digital nonlinearity compensation in high-capacity optical communication systems considering signal spectral broadening effect.

PubMed

Xu, Tianhua; Karanov, Boris; Shevchenko, Nikita A; Lavery, Domaniç; Liga, Gabriele; Killey, Robert I; Bayvel, Polina

2017-10-11

Nyquist-spaced transmission and digital signal processing have proved effective in maximising the spectral efficiency and reach of optical communication systems. In these systems, Kerr nonlinearity determines the performance limits, and leads to spectral broadening of the signals propagating in the fibre. Although digital nonlinearity compensation was validated to be promising for mitigating Kerr nonlinearities, the impact of spectral broadening on nonlinearity compensation has never been quantified. In this paper, the performance of multi-channel digital back-propagation (MC-DBP) for compensating fibre nonlinearities in Nyquist-spaced optical communication systems is investigated, when the effect of signal spectral broadening is considered. It is found that accounting for the spectral broadening effect is crucial for achieving the best performance of DBP in both single-channel and multi-channel communication systems, independent of modulation formats used. For multi-channel systems, the degradation of DBP performance due to neglecting the spectral broadening effect in the compensation is more significant for outer channels. Our work also quantified the minimum bandwidths of optical receivers and signal processing devices to ensure the optimal compensation of deterministic nonlinear distortions.

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.

Bayesian statistics as a new tool for spectral analysis - I. Application for the determination of basic parameters of massive stars

NASA Astrophysics Data System (ADS)

Mugnes, J.-M.; Robert, C.

2015-11-01

Spectral analysis is a powerful tool to investigate stellar properties and it has been widely used for decades now. However, the methods considered to perform this kind of analysis are mostly based on iteration among a few diagnostic lines to determine the stellar parameters. While these methods are often simple and fast, they can lead to errors and large uncertainties due to the required assumptions. Here, we present a method based on Bayesian statistics to find simultaneously the best combination of effective temperature, surface gravity, projected rotational velocity, and microturbulence velocity, using all the available spectral lines. Different tests are discussed to demonstrate the strength of our method, which we apply to 54 mid-resolution spectra of field and cluster B stars obtained at the Observatoire du Mont-Mégantic. We compare our results with those found in the literature. Differences are seen which are well explained by the different methods used. We conclude that the B-star microturbulence velocities are often underestimated. We also confirm the trend that B stars in clusters are on average faster rotators than field B stars.

Frequency spectrum analysis of finger photoplethysmographic waveform variability during haemodialysis.

PubMed

Javed, Faizan; Middleton, Paul M; Malouf, Philip; Chan, Gregory S H; Savkin, Andrey V; Lovell, Nigel H; Steel, Elizabeth; Mackie, James

2010-09-01

This study investigates the peripheral circulatory and autonomic response to volume withdrawal in haemodialysis based on spectral analysis of photoplethysmographic waveform variability (PPGV). Frequency spectrum analysis was performed on the baseline and pulse amplitude variabilities of the finger infrared photoplethysmographic (PPG) waveform and on heart rate variability extracted from the ECG signal collected from 18 kidney failure patients undergoing haemodialysis. Spectral powers were calculated from the low frequency (LF, 0.04-0.145 Hz) and high frequency (HF, 0.145-0.45 Hz) bands. In eight stable fluid overloaded patients (fluid removal of >2 L) not on alpha blockers, progressive reduction in relative blood volume during haemodialysis resulted in significant increase in LF and HF powers of PPG baseline and amplitude variability (P < 0.01), when expressed in mean-scaled units. The augmentation of LF powers in PPGV during haemodialysis may indicate the recovery and possibly further enhancement of peripheral sympathetic vascular modulation subsequent to volume unloading, whilst the increase in respiratory HF power in PPGV is most likely a sign of preload reduction. Spectral analysis of finger PPGV may provide valuable information on the autonomic vascular response to blood volume reduction in haemodialysis, and can be potentially utilized as a non-invasive tool for assessing peripheral circulatory control during routine dialysis procedure.

Prior-knowledge-based spectral mixture analysis for impervious surface mapping

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

Zhang, Jinshui; He, Chunyang; Zhou, Yuyu

2014-01-03

In this study, we developed a prior-knowledge-based spectral mixture analysis (PKSMA) to map impervious surfaces by using endmembers derived separately for high- and low-density urban regions. First, an urban area was categorized into high- and low-density urban areas, using a multi-step classification method. Next, in high-density urban areas that were assumed to have only vegetation and impervious surfaces (ISs), the Vegetation-Impervious model (V-I) was used in a spectral mixture analysis (SMA) with three endmembers: vegetation, high albedo, and low albedo. In low-density urban areas, the Vegetation-Impervious-Soil model (V-I-S) was used in an SMA analysis with four endmembers: high albedo, lowmore » albedo, soil, and vegetation. The fraction of IS with high and low albedo in each pixel was combined to produce the final IS map. The root mean-square error (RMSE) of the IS map produced using PKSMA was about 11.0%, compared to 14.52% using four-endmember SMA. Particularly in high-density urban areas, PKSMA (RMSE = 6.47%) showed better performance than four-endmember (15.91%). The results indicate that PKSMA can improve IS mapping compared to traditional SMA by using appropriately selected endmembers and is particularly strong in high-density urban areas.« less

Non-Maxwellian Analysis of the Transition-region Line Profiles Observed by the Interface Region Imaging Spectrograph

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

Dudík, Jaroslav; Dzifčáková, Elena; Polito, Vanessa

2017-06-10

We investigate the nature of the spectral line profiles for transition-region (TR) ions observed with the Interface Region Imaging Spectrograph (IRIS) . In this context, we analyzed an active-region observation performed by IRIS in its 1400 Å spectral window. The TR lines are found to exhibit significant wings in their spectral profiles, which can be well fitted with a non-Maxwellian κ distribution. The fit with a κ distribution can perform better than a double-Gaussian fit, especially for the strongest line, Si iv 1402.8 Å. Typical values of κ found are about 2, occurring in a majority of spatial pixels wheremore » the TR lines are symmetric, i.e., the fit can be performed. Furthermore, all five spectral lines studied (from Si iv, O iv, and S iv) appear to have the same full-width at half-maximum irrespective of whether the line is an allowed or an intercombination transition. A similar value of κ is obtained for the electron distribution by the fitting of the line intensities relative to Si iv 1402.8 Å, if photospheric abundances are assumed. The κ distributions, however, do not remove the presence of non-thermal broadening. Instead, they actually increase the non-thermal width. This is because, for κ distributions, TR ions are formed at lower temperatures. The large observed non-thermal width lowers the opacity of the Si iv line sufficiently enough for this line to become optically thin.« less

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.

Observer model optimization of a spectral mammography system

NASA Astrophysics Data System (ADS)

Fredenberg, Erik; Åslund, Magnus; Cederström, Björn; Lundqvist, Mats; Danielsson, Mats

2010-04-01

Spectral imaging is a method in medical x-ray imaging to extract information about the object constituents by the material-specific energy dependence of x-ray attenuation. Contrast-enhanced spectral imaging has been thoroughly investigated, but unenhanced imaging may be more useful because it comes as a bonus to the conventional non-energy-resolved absorption image at screening; there is no additional radiation dose and no need for contrast medium. We have used a previously developed theoretical framework and system model that include quantum and anatomical noise to characterize the performance of a photon-counting spectral mammography system with two energy bins for unenhanced imaging. The theoretical framework was validated with synthesized images. Optimal combination of the energy-resolved images for detecting large unenhanced tumors corresponded closely, but not exactly, to minimization of the anatomical noise, which is commonly referred to as energy subtraction. In that case, an ideal-observer detectability index could be improved close to 50% compared to absorption imaging. Optimization with respect to the signal-to-quantum-noise ratio, commonly referred to as energy weighting, deteriorated detectability. For small microcalcifications or tumors on uniform backgrounds, however, energy subtraction was suboptimal whereas energy weighting provided a minute improvement. The performance was largely independent of beam quality, detector energy resolution, and bin count fraction. It is clear that inclusion of anatomical noise and imaging task in spectral optimization may yield completely different results than an analysis based solely on quantum noise.

Penalized discriminant analysis for the detection of wild-grown and cultivated Ganoderma lucidum using Fourier transform infrared spectroscopy

NASA Astrophysics Data System (ADS)

Zhu, Ying; Tan, Tuck Lee

2016-04-01

An effective and simple analytical method using Fourier transform infrared (FTIR) spectroscopy to distinguish wild-grown high-quality Ganoderma lucidum (G. lucidum) from cultivated one is of essential importance for its quality assurance and medicinal value estimation. Commonly used chemical and analytical methods using full spectrum are not so effective for the detection and interpretation due to the complex system of the herbal medicine. In this study, two penalized discriminant analysis models, penalized linear discriminant analysis (PLDA) and elastic net (Elnet),using FTIR spectroscopy have been explored for the purpose of discrimination and interpretation. The classification performances of the two penalized models have been compared with two widely used multivariate methods, principal component discriminant analysis (PCDA) and partial least squares discriminant analysis (PLSDA). The Elnet model involving a combination of L1 and L2 norm penalties enabled an automatic selection of a small number of informative spectral absorption bands and gave an excellent classification accuracy of 99% for discrimination between spectra of wild-grown and cultivated G. lucidum. Its classification performance was superior to that of the PLDA model in a pure L1 setting and outperformed the PCDA and PLSDA models using full wavelength. The well-performed selection of informative spectral features leads to substantial reduction in model complexity and improvement of classification accuracy, and it is particularly helpful for the quantitative interpretations of the major chemical constituents of G. lucidum regarding its anti-cancer effects.

RXTE spectra of the Galactic microquasar GRO J1655-40 during the 2005 outburst

NASA Astrophysics Data System (ADS)

Saito, Koji; Yamaoka, K.; Fukuyama, M.; Miyakawa, T. G.; Yoshida, A.; Homan, J.

We report on the results of a detailed spectral analysis of 389 RXTE observations of the Galac- tic microquasar GRO J1655-40, performed during its 2005 outburst. The maximum luminosity reached during this outburst was 1.4 times higher than in the previous (1996-1997) outburst. However, the spectral behavior during the two outbursts was very similar. In particular, L disk was 4 proportional to Tin up to the same critical luminosity and in both outbursts there were periods during which the energy spectra were very soft, but could not be fit with standard disk models.

Applications of remote sensing, volume 3

NASA Technical Reports Server (NTRS)

Landgrebe, D. A. (Principal Investigator)

1977-01-01

The author has identified the following significant results. Of the four change detection techniques (post classification comparison, delta data, spectral/temporal, and layered spectral temporal), the post classification comparison was selected for further development. This was based upon test performances of the four change detection method, straightforwardness of the procedures, and the output products desired. A standardized modified, supervised classification procedure for analyzing the Texas coastal zone data was compiled. This procedure was developed in order that all quadrangles in the study are would be classified using similar analysis techniques to allow for meaningful comparisons and evaluations of the classifications.

Absorption, fluorescence and second harmonic generation in Cr3+-doped BiB3O6 glasses

NASA Astrophysics Data System (ADS)

Kuznik, W.; Fuks-Janczarek, I.; Wojciechowski, A.; Kityk, I. V.; Kiisk, V.; Majchrowski, A.; Jaroszewicz, L. R.; Brik, M. G.; Nagy, G. U. L.

2015-06-01

Synthesis, spectral properties and photoinduced nonlinear optical effects of chromium-doped BiB3O6 glass are studied in the present paper. Absorption, excitation and time resolved luminescence spectra are presented and luminescence decay behavior is discussed. Detailed analysis of the obtained spectra (assignment of the most prominent spectral features in terms of the corresponding Cr3+ energy levels, crystal field strength Dq, Racah parameters B and C) was performed. A weak photostimulated second harmonic generation signal was found to increase drastically due to poling by proton implantation in the investigated sample.

Textural signatures for wetland vegetation

NASA Technical Reports Server (NTRS)

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

1973-01-01

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

Calibration of the Geostationary Imaging Fourier Transform Spectrometer (GIFTS)

NASA Technical Reports Server (NTRS)

Best, F. A.; Revercomb, H. E.; Bingham, G. E.; Knuteson, R. O.; Tobin, D. C.; LaPorte, D. D.; Smith, W. L.

2001-01-01

The NASA New Millennium Program's Geostationary Imaging Fourier Transform Spectrometer (GIFTS) requires highly accurate radiometric and spectral calibration in order to carry out its mission to provide water vapor, wind, temperature, and trace gas profiling from geostationary orbit. A calibration concept has been developed for the GIFTS Phase A instrument design. The in-flight calibration is performed using views of two on-board blackbody sources along with cold space. A radiometric calibration uncertainty analysis has been developed and used to show that the expected performance for GIFTS exceeds its top level requirement to measure brightness temperature to better than 1 K. For the Phase A GIFTS design, the spectral calibration is established by the highly stable diode laser used as the reference for interferogram sampling, and verified with comparisons to atmospheric calculations.

Identification and characterization of salmonella serotypes using DNA spectral characteristics by fourier transform infrared (FT-IR) spectroscopy

USDA-ARS?s Scientific Manuscript database

Analysis of DNA samples of Salmonella serotypes (Salmonella Typhimurium, Salmonella Enteritidis, Salmonella Infantis, Salmonella Heidelberg and Salmonella Kentucky) were performed using Fourier transform infrared spectroscopy (FT-IR) spectrometer by placing directly in contact with a diamond attenua...

Development of space-stable thermal control coatings for use on large space vehicles

NASA Technical Reports Server (NTRS)

Gilligan, J. E.; Harada, Y.

1976-01-01

The potential of zinc orthotitanate as a pigment for spacecraft thermal control was demonstrated. The properties and performance of pigments prepared by solid state, coprecipitation, and mixed oxalate methods were compared. Environmental tests and subsequent spectral analysis were given primary emphasis.

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

Software Defined Network Monitoring Scheme Using Spectral Graph Theory and Phantom Nodes

DTIC Science & Technology

2014-09-01

networks is the emergence of software - defined networking ( SDN ) [1]. SDN has existed for the...Chapter III for network monitoring. A. SOFTWARE DEFINED NETWORKS SDNs provide a new and innovative method to simplify network hardware by logically...and R. Giladi, “Performance analysis of software - defined networking ( SDN ),” in Proc. of IEEE 21st International Symposium on Modeling, Analysis

Feasibility study in the application of optical signal analysis to non-destructive testing of complex structures

NASA Technical Reports Server (NTRS)

Baker, B.; Brown, H.

1974-01-01

Advantages of the large time bandwidth product of optical processing are presented. Experiments were performed to study the feasibility of the use of optical spectral analysis for detection of flaws in structural elements excited by random noise. Photographic and electronic methods of comparison of complex spectra were developed. Limitations were explored, and suggestions for further work are offered.

Optimum thermal infrared bands for mapping general rock type and temperature from space

NASA Technical Reports Server (NTRS)

Holmes, Q. A.; Nueesch, D. R.; Vincent, R. K.

1980-01-01

A study was carried out to determine quantitatively the number and location of spectral bands required to perform general rock type discrimination from spaceborne imaging sensors using only thermal infrared measurements. Beginning with laboratory spectra collected under idealized conditions from relatively well-characterized homogeneous samples, a radiative transfer model was used to transform ground exitance values into the corresponding spectral radiance at the top of the atmosphere. Taking sensor noise into account, analysis of these data revealed that three 1 micron wide spectral bands would permit independent estimations of rock type and sample temperature from a satellite infrared multispectral scanner. This study, which ignores the mixing of terrain elements within the instantaneous field of view of a satellite scanner, indicates that the location of three spectral bands at 8.1-9.1, 9.5-10.5, and 11.0-12.0 microns, and the employment of appropriate preprocessing to minimize atmospheric effects makes it possible to predict general rock type and temperature for a variety of atmospheric states and temperatures.

Optimum thermal infrared bands for mapping general rock type and temperature from space

NASA Technical Reports Server (NTRS)

Holmes, Q. A.; Nuesch, D. R.

1978-01-01

A study was carried out to determine quantitatively the number and locations of spectral bands required to perform general rock-type discrimination from spaceborne imaging sensors using only thermal infrared measurements. Beginning with laboratory spectra collected under idealized conditions from relatively well characterized, homogeneous samples, a radiative transfer model was employed to transform ground exitance values into the corresponding spectral radiance at the top of the atmosphere. Taking sensor noise into account analysis of these data revealed that three 1 micrometer wide spectral bands would permit independent estimators of rock-type and sample temperature from a satellite infrared multispectral scanner. This study, indicates that the location of three spectral bands at 8.1-9.1 micrometers, 9.5-10.5 micrometers and 11.0-12.0 micrometers, and the employment of appropriate preprocessing to minimize atmospheric effects makes it possible to predict general rock-type and temperature for a variety of atmospheric states and temperatures.

Structural, vibrational, thermal and optical studies of organic single crystal: Benzotriazolium p-toluene sulfonate (BTPTS)

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

Kumar, R. Ramesh; Sathya, P.; Gopalakrishnan, R., E-mail: krgkrishnan@yahoo.com

Benzotriazolium p-toluene sulfonate (BTPTS) was grown by solution growth technique. The powder X-ray diffraction analysis was carried out to evaluate crystal system of the compound. LeBail Profile fitting analysis was performed to extract the individual peak intensities. FTIR spectrum analysis was recorded to study vibration frequencies of the prepared organic salt. Thermal studies were carried out using TG-DSC analysis. Optical absorption and energy band gap of the title compound was evaluated by UV-Vis spectral study.

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

Spectral density mapping at multiple magnetic fields suitable for 13C NMR relaxation studies

NASA Astrophysics Data System (ADS)

Kadeřávek, Pavel; Zapletal, Vojtěch; Fiala, Radovan; Srb, Pavel; Padrta, Petr; Přecechtělová, Jana Pavlíková; Šoltésová, Mária; Kowalewski, Jozef; Widmalm, Göran; Chmelík, Josef; Sklenář, Vladimír; Žídek, Lukáš

2016-05-01

Standard spectral density mapping protocols, well suited for the analysis of 15N relaxation rates, introduce significant systematic errors when applied to 13C relaxation data, especially if the dynamics is dominated by motions with short correlation times (small molecules, dynamic residues of macromolecules). A possibility to improve the accuracy by employing cross-correlated relaxation rates and on measurements taken at several magnetic fields has been examined. A suite of protocols for analyzing such data has been developed and their performance tested. Applicability of the proposed protocols is documented in two case studies, spectral density mapping of a uniformly labeled RNA hairpin and of a selectively labeled disaccharide exhibiting highly anisotropic tumbling. Combination of auto- and cross-correlated relaxation data acquired at three magnetic fields was applied in the former case in order to separate effects of fast motions and conformational or chemical exchange. An approach using auto-correlated relaxation rates acquired at five magnetic fields, applicable to anisotropically moving molecules, was used in the latter case. The results were compared with a more advanced analysis of data obtained by interpolation of auto-correlated relaxation rates measured at seven magnetic fields, and with the spectral density mapping of cross-correlated relaxation rates. The results showed that sufficiently accurate values of auto- and cross-correlated spectral density functions at zero and 13C frequencies can be obtained from data acquired at three magnetic fields for uniformly 13C -labeled molecules with a moderate anisotropy of the rotational diffusion tensor. Analysis of auto-correlated relaxation rates at five magnetic fields represents an alternative for molecules undergoing highly anisotropic motions.

Characterization and Analysis of InGaAsSb Detectors

NASA Technical Reports Server (NTRS)

Abedin, M. Nurul; Refaat, Tamer F.; Joshi, Ravindra P.; Sulima, Oleg V.; Mauk, Michael; Singh, Upendra N.

2003-01-01

Profiling of atmospheric CO2 at 2 micron wavelength using the LIDAR technique, has recently gained interest. Although several detectors might be suitable for this application, an ideal device would have high gain, low noise and narrow spectral response peaking around the wavelength of interest. This increases the detector signal-to-noise ratio and minimizes the background signal, thereby increasing the device sensitivity and dynamic range. Detectors meeting the above idealized criteria are commercially unavailable for this particular wavelength. In this paper, the characterization and analysis of Sb-based detectors for 2 micron lidar applications are presented. The detectors were manufactured by AstroPower, Inc., with an InGaAsSb absorbing layer and AlGaAsSb passivating layer. The characterization experiments included spectral response, current versus voltage and noise measurements. The effect of the detectors bias voltage and temperature on its performance, have been investigated as well. The detectors peak responsivity is located at the 2 micron wavelength. Comparing three detector samples, an optimization of the spectral response around the 2 micron wavelength, through a narrower spectral period was observed. Increasing the detector bias voltage enhances the device gain at the narrow spectral range, while cooling the device reduces the cut-off wavelength and lowers its noise. Noise-equivalent-power analysis results in a value as low as 4 x 10(exp -12) W/Hz(exp 1/2) corresponding to D* of 1 x 10(exp 10) cmHz(exp 1/2)/W, at -1 V and 20 C. Discussions also include device operational physics and optimization guidelines, taking into account peculiarity of the Type II heterointerface and transport mechanisms under these conditions.

Design and analysis of optical systems for the Stanford/MSFC Multi-Spectral Solar Telescope Array

NASA Astrophysics Data System (ADS)

Hadaway, James B.; Johnson, R. Barry; Hoover, Richard B.; Lindblom, Joakim F.; Walker, Arthur B. C., Jr.

1989-07-01

This paper reports on the design and the theoretical ray trace analysis of the optical systems which will comprise the primary imaging components for the Stanford/MSFC Multi-Spectral Solar Telescope Array (MSSTA). This instrument is being developed for ultra-high resolution investigations of the sun from a sounding rocket. Doubly reflecting systems of sphere-sphere, ellipsoid-sphere (Dall-Kirkham), paraboloid-hyperboloid (Cassegrain), and hyperboloid-hyperboloid (Ritchey-Chretien) configurations were analyzed. For these mirror systems, ray trace analysis was performed and through-focus spot diagrams, point spread function plots, and geometrical and diffraction MTFs were generated. The results of these studies are presented along with the parameters of the Ritchey-Chretien optical system selected for the MSSTA flight. The payload, which incorporates seven of these Ritchey-Chretien systems, is now being prepared for launch in late September 1989.

Design and analysis of optical systems for the Stanford/MSFC Multi-Spectral Solar Telescope Array

NASA Technical Reports Server (NTRS)

Hadaway, James B.; Johnson, R. Barry; Hoover, Richard B.; Lindblom, Joakim F.; Walker, Arthur B. C., Jr.

1989-01-01

This paper reports on the design and the theoretical ray trace analysis of the optical systems which will comprise the primary imaging components for the Stanford/MSFC Multi-Spectral Solar Telescope Array (MSSTA). This instrument is being developed for ultra-high resolution investigations of the sun from a sounding rocket. Doubly reflecting systems of sphere-sphere, ellipsoid-sphere (Dall-Kirkham), paraboloid-hyperboloid (Cassegrain), and hyperboloid-hyperboloid (Ritchey-Chretien) configurations were analyzed. For these mirror systems, ray trace analysis was performed and through-focus spot diagrams, point spread function plots, and geometrical and diffraction MTFs were generated. The results of these studies are presented along with the parameters of the Ritchey-Chretien optical system selected for the MSSTA flight. The payload, which incorporates seven of these Ritchey-Chretien systems, is now being prepared for launch in late September 1989.

Moments distributions of single dye molecule spectra in a low-temperature polymer: Analysis of system ergodicity

NASA Astrophysics Data System (ADS)

Anikushina, T. A.; Naumov, A. V.

2013-12-01

This article demonstrates the principal advantages of the technique for analysis of the long-term spectral evolution of single molecules (SM) in the study of the microscopic nature of the dynamic processes in low-temperature polymers. We performed the detailed analysis of the spectral trail of single tetra-tert-butylterrylene (TBT) molecule in an amorphous polyisobutylene matrix, measured over 5 hours at T = 7K. It has been shown that the slow temporal dynamics is in qualitative agreement with the standard model of two-level systems and stochastic sudden-jump model. At the same time the distributions of the first four moments (cumulants) of the spectra of the selected SM measured at different time points were found not consistent with the standard theory prediction. It was considered as evidence that in a given time interval the system is not ergodic

Spectral analysis of stellar light curves by means of neural networks

NASA Astrophysics Data System (ADS)

Tagliaferri, R.; Ciaramella, A.; Milano, L.; Barone, F.; Longo, G.

1999-06-01

Periodicity analysis of unevenly collected data is a relevant issue in several scientific fields. In astrophysics, for example, we have to find the fundamental period of light or radial velocity curves which are unevenly sampled observations of stars. Classical spectral analysis methods are unsatisfactory to solve the problem. In this paper we present a neural network based estimator system which performs well the frequency extraction in unevenly sampled signals. It uses an unsupervised Hebbian nonlinear neural algorithm to extract, from the interpolated signal, the principal components which, in turn, are used by the MUSIC frequency estimator algorithm to extract the frequencies. The neural network is tolerant to noise and works well also with few points in the sequence. We benchmark the system on synthetic and real signals with the Periodogram and with the Cramer-Rao lower bound. This work was been partially supported by IIASS, by MURST 40\\% and by the Italian Space Agency.

Evolution of miniature detectors and focal plane arrays for infrared sensors

NASA Astrophysics Data System (ADS)

Watts, Louis A.

1993-06-01

Sensors that are sensitive in the infrared spectral region have been under continuous development since the WW2 era. A quest for the military advantage of 'seeing in the dark' has pushed thermal imaging technology toward high spatial and temporal resolution for night vision equipment, fire control, search track, and seeker 'homing' guidance sensing devices. Similarly, scientific applications have pushed spectral resolution for chemical analysis, remote sensing of earth resources, and astronomical exploration applications. As a result of these developments, focal plane arrays (FPA) are now available with sufficient sensitivity for both high spatial and narrow bandwidth spectral resolution imaging over large fields of view. Such devices combined with emerging opto-electronic developments in integrated FPA data processing techniques can yield miniature sensors capable of imaging reflected sunlight in the near IR and emitted thermal energy in the Mid-wave (MWIR) and longwave (LWIR) IR spectral regions. Robotic space sensors equipped with advanced versions of these FPA's will provide high resolution 'pictures' of their surroundings, perform remote analysis of solid, liquid, and gas matter, or selectively look for 'signatures' of specific objects. Evolutionary trends and projections of future low power micro detector FPA developments for day/night operation or use in adverse viewing conditions are presented in the following test.

Near-infrared spectral image analysis of pork marbling based on Gabor filter and wide line detector techniques.

PubMed

Huang, Hui; Liu, Li; Ngadi, Michael O; Gariépy, Claude; Prasher, Shiv O

2014-01-01

Marbling is an important quality attribute of pork. Detection of pork marbling usually involves subjective scoring, which raises the efficiency costs to the processor. In this study, the ability to predict pork marbling using near-infrared (NIR) hyperspectral imaging (900-1700 nm) and the proper image processing techniques were studied. Near-infrared images were collected from pork after marbling evaluation according to current standard chart from the National Pork Producers Council. Image analysis techniques-Gabor filter, wide line detector, and spectral averaging-were applied to extract texture, line, and spectral features, respectively, from NIR images of pork. Samples were grouped into calibration and validation sets. Wavelength selection was performed on calibration set by stepwise regression procedure. Prediction models of pork marbling scores were built using multiple linear regressions based on derivatives of mean spectra and line features at key wavelengths. The results showed that the derivatives of both texture and spectral features produced good results, with correlation coefficients of validation of 0.90 and 0.86, respectively, using wavelengths of 961, 1186, and 1220 nm. The results revealed the great potential of the Gabor filter for analyzing NIR images of pork for the effective and efficient objective evaluation of pork marbling.

Spectral data compression using weighted principal component analysis with consideration of human visual system and light sources

NASA Astrophysics Data System (ADS)

Cao, Qian; Wan, Xiaoxia; Li, Junfeng; Liu, Qiang; Liang, Jingxing; Li, Chan

2016-10-01

This paper proposed two weight functions based on principal component analysis (PCA) to reserve more colorimetric information in spectral data compression process. One weight function consisted of the CIE XYZ color-matching functions representing the characteristic of the human visual system, while another was made up of the CIE XYZ color-matching functions of human visual system and relative spectral power distribution of the CIE standard illuminant D65. The improvement obtained from the proposed two methods were tested to compress and reconstruct the reflectance spectra of 1600 glossy Munsell color chips and 1950 Natural Color System color chips as well as six multispectral images. The performance was evaluated by the mean values of color difference under the CIE 1931 standard colorimetric observer and the CIE standard illuminant D65 and A. The mean values of root mean square errors between the original and reconstructed spectra were also calculated. The experimental results show that the proposed two methods significantly outperform the standard PCA and another two weighted PCA in the aspects of colorimetric reconstruction accuracy with very slight degradation in spectral reconstruction accuracy. In addition, weight functions with the CIE standard illuminant D65 can improve the colorimetric reconstruction accuracy compared to weight functions without the CIE standard illuminant D65.

High Energy Emission of V404 Cygni during 2015 outburst with INTEGRAL/SPI: Spectral analysis results, issues and solutions

NASA Astrophysics Data System (ADS)

Jourdain, Elisabeth; Roques, Jean-Pierre

2016-04-01

A strong outburst of the X-ray transient V404 Cygni (= GS2023-338) was observed in 2015 June/July up to a level of 50 Crab in the hard X-ray domain.We have used the INTEGRAL/SPI data to investigate the spectral behavior of the source between 20 and 1000 keV during its maximum of activity. We have found striking variability patterns at all timescales. For the 20-200 keV energy band, the huge signal to noise ratio allows us to scrutinize the source evolution on a never reached timescale (30 s). At higher energy, the spectral shape can be determined on a timescale < 1 h.However, we note that at this level of photon flux, instrument's behavior may be severely tested and that some instrumental artifacts could affect the data analysis. We have performed thorough checks to ensure a correct handling of the SPI data and present how to obtain reliable spectral results on the emission of V404 Cyg. We demonstrate that, with the correct configuration, the hard X-ray emission, up to the MeV region, is well described by a two component model (Comptonisation law + cutoff power law) as observed in Cyg X-1 and for V404 Cygni itself at lower flux levels.

Evolution of miniature detectors and focal plane arrays for infrared sensors

NASA Technical Reports Server (NTRS)

Watts, Louis A.

1993-01-01

Sensors that are sensitive in the infrared spectral region have been under continuous development since the WW2 era. A quest for the military advantage of 'seeing in the dark' has pushed thermal imaging technology toward high spatial and temporal resolution for night vision equipment, fire control, search track, and seeker 'homing' guidance sensing devices. Similarly, scientific applications have pushed spectral resolution for chemical analysis, remote sensing of earth resources, and astronomical exploration applications. As a result of these developments, focal plane arrays (FPA) are now available with sufficient sensitivity for both high spatial and narrow bandwidth spectral resolution imaging over large fields of view. Such devices combined with emerging opto-electronic developments in integrated FPA data processing techniques can yield miniature sensors capable of imaging reflected sunlight in the near IR and emitted thermal energy in the Mid-wave (MWIR) and longwave (LWIR) IR spectral regions. Robotic space sensors equipped with advanced versions of these FPA's will provide high resolution 'pictures' of their surroundings, perform remote analysis of solid, liquid, and gas matter, or selectively look for 'signatures' of specific objects. Evolutionary trends and projections of future low power micro detector FPA developments for day/night operation or use in adverse viewing conditions are presented in the following test.

Spectral energy distribution of M-subdwarfs: A study of their atmospheric properties

NASA Astrophysics Data System (ADS)

Rajpurohit, A. S.; Reylé, C.; Allard, F.; Homeier, D.; Bayo, A.; Mousis, O.; Rajpurohit, S.; Fernández-Trincado, J. G.

2016-11-01

Context. M-type subdwarfs are metal-poor low-mass stars and are probes for the old populations in our Galaxy. Accurate knowledge of their atmospheric parameters and especially their composition is essential for understanding the chemical history of our Galaxy. Aims: The purpose of this work is to perform a detailed study of M-subdwarf spectra covering the full wavelength range from the optical to the near-infrared. It allows us to perform a more detailed analysis of the atmospheric composition in order to determine the stellar parameters, and to constrain the atmospheric models. The study will allow us to further understand physical and chemical processes such as increasing condensation of gas into dust, to point out the missing continuum opacities, and to see how the main band features are reproduced by the models. The spectral resolution and the large wavelength coverage used is a unique combination that can constrain the processes that occur in a cool atmosphere. Methods: We obtained medium-resolution spectra (R = 5000-7000) over the wavelength range 0.3-2.5 μm of ten M-type subdwarfs with X-shooter at VLT. These data constitute a unique atlas of M-subdwarfs from optical to near-infrared. We performed a spectral synthesis analysis using a full grid of synthetic spectra computed from BT-Settl models and obtained consistent stellar parameters such as effective temperature, surface gravity, and metallicity. Results: We show that state-of the-art atmospheric models correctly represent the overall shape of their spectral energy distribution, as well as atomic and molecular line profiles both in the optical and near-infrared. We find that the actual fitted gravities of almost all our sample are consistent with old objects, except for LHS 73 where it is found to be surprisingly low. Based on observations made with the ESO Very Large Telescope at the Paranal Observatory under programme 092.D-0600(A).

Parametric mapping using spectral analysis for 11C-PBR28 PET reveals neuroinflammation in mild cognitive impairment subjects.

PubMed

Fan, Zhen; Dani, Melanie; Femminella, Grazia D; Wood, Melanie; Calsolaro, Valeria; Veronese, Mattia; Turkheimer, Federico; Gentleman, Steve; Brooks, David J; Hinz, Rainer; Edison, Paul

2018-07-01

Neuroinflammation and microglial activation play an important role in amnestic mild cognitive impairment (MCI) and Alzheimer's disease. In this study, we investigated the spatial distribution of neuroinflammation in MCI subjects, using spectral analysis (SA) to generate parametric maps and quantify 11 C-PBR28 PET, and compared these with compartmental and other kinetic models of quantification. Thirteen MCI and nine healthy controls were enrolled in this study. Subjects underwent 11 C-PBR28 PET scans with arterial cannulation. Spectral analysis with an arterial plasma input function was used to generate 11 C-PBR28 parametric maps. These maps were then compared with regional 11 C-PBR28 V T (volume of distribution) using a two-tissue compartment model and Logan graphic analysis. Amyloid load was also assessed with 18 F-Flutemetamol PET. With SA, three component peaks were identified in addition to blood volume. The 11 C-PBR28 impulse response function (IRF) at 90 min produced the lowest coefficient of variation. Single-subject analysis using this IRF demonstrated microglial activation in five out of seven amyloid-positive MCI subjects. IRF parametric maps of 11 C-PBR28 uptake revealed a group-wise significant increase in neuroinflammation in amyloid-positive MCI subjects versus HC in multiple cortical association areas, and particularly in the temporal lobe. Interestingly, compartmental analysis detected group-wise increase in 11 C-PBR28 binding in the thalamus of amyloid-positive MCI subjects, while Logan parametric maps did not perform well. This study demonstrates for the first time that spectral analysis can be used to generate parametric maps of 11 C-PBR28 uptake, and is able to detect microglial activation in amyloid-positive MCI subjects. IRF parametric maps of 11 C-PBR28 uptake allow voxel-wise single-subject analysis and could be used to evaluate microglial activation in individual subjects.

Monitoring Fatigue Status with HRV Measures in Elite Athletes: An Avenue Beyond RMSSD?

PubMed Central

Schmitt, Laurent; Regnard, Jacques; Millet, Grégoire P.

2015-01-01

Among the tools proposed to assess the athlete's “fatigue,” the analysis of heart rate variability (HRV) provides an indirect evaluation of the settings of autonomic control of heart activity. HRV analysis is performed through assessment of time-domain indices, the square root of the mean of the sum of the squares of differences between adjacent normal R-R intervals (RMSSD) measured during short (5 min) recordings in supine position upon awakening in the morning and particularly the logarithm of RMSSD (LnRMSSD) has been proposed as the most useful resting HRV indicator. However, if RMSSD can help the practitioner to identify a global “fatigue” level, it does not allow discriminating different types of fatigue. Recent results using spectral HRV analysis highlighted firstly that HRV profiles assessed in supine and standing positions are independent and complementary; and secondly that using these postural profiles allows the clustering of distinct sub-categories of “fatigue.” Since, cardiovascular control settings are different in standing and lying posture, using the HRV figures of both postures to cluster fatigue state embeds information on the dynamics of control responses. Such, HRV spectral analysis appears more sensitive and enlightening than time-domain HRV indices. The wealthier information provided by this spectral analysis should improve the monitoring of the adaptive training-recovery process in athletes. PMID:26635629

Analysis of Moisture Content in Beetroot using Fourier Transform Infrared Spectroscopy and by Principal Component Analysis.

PubMed

Nesakumar, Noel; Baskar, Chanthini; Kesavan, Srinivasan; Rayappan, John Bosco Balaguru; Alwarappan, Subbiah

2018-05-22

The moisture content of beetroot varies during long-term cold storage. In this work, we propose a strategy to identify the moisture content and age of beetroot using principal component analysis coupled Fourier transform infrared spectroscopy (FTIR). Frequent FTIR measurements were recorded directly from the beetroot sample surface over a period of 34 days for analysing its moisture content employing attenuated total reflectance in the spectral ranges of 2614-4000 and 1465-1853 cm -1 with a spectral resolution of 8 cm -1 . In order to estimate the transmittance peak height (T p ) and area under the transmittance curve [Formula: see text] over the spectral ranges of 2614-4000 and 1465-1853 cm -1 , Gaussian curve fitting algorithm was performed on FTIR data. Principal component and nonlinear regression analyses were utilized for FTIR data analysis. Score plot over the ranges of 2614-4000 and 1465-1853 cm -1 allowed beetroot quality discrimination. Beetroot quality predictive models were developed by employing biphasic dose response function. Validation experiment results confirmed that the accuracy of the beetroot quality predictive model reached 97.5%. This research work proves that FTIR spectroscopy in combination with principal component analysis and beetroot quality predictive models could serve as an effective tool for discriminating moisture content in fresh, half and completely spoiled stages of beetroot samples and for providing status alerts.

Spectacle and SpecViz: New Spectral Analysis and Visualization Tools

NASA Astrophysics Data System (ADS)

Earl, Nicholas; Peeples, Molly; JDADF Developers

2018-01-01

A new era of spectroscopic exploration of our universe is being ushered in with advances in instrumentation and next-generation space telescopes. The advent of new spectroscopic instruments has highlighted a pressing need for tools scientists can use to analyze and explore these new data. We have developed Spectacle, a software package for analyzing both synthetic spectra from hydrodynamic simulations as well as real COS data with an aim of characterizing the behavior of the circumgalactic medium. It allows easy reduction of spectral data and analytic line generation capabilities. Currently, the package is focused on automatic determination of absorption regions and line identification with custom line list support, simultaneous line fitting using Voigt profiles via least-squares or MCMC methods, and multi-component modeling of blended features. Non-parametric measurements, such as equivalent widths, delta v90, and full-width half-max are available. Spectacle also provides the ability to compose compound models used to generate synthetic spectra allowing the user to define various LSF kernels, uncertainties, and to specify sampling.We also present updates to the visualization tool SpecViz, developed in conjunction with the JWST data analysis tools development team, to aid in the exploration of spectral data. SpecViz is an open source, Python-based spectral 1-D interactive visualization and analysis application built around high-performance interactive plotting. It supports handling general and instrument-specific data and includes advanced tool-sets for filtering and detrending one-dimensional data, along with the ability to isolate absorption regions using slicing and manipulate spectral features via spectral arithmetic. Multi-component modeling is also possible using a flexible model fitting tool-set that supports custom models to be used with various fitting routines. It also features robust user extensions such as custom data loaders and support for user-created plugins that add new functionality.This work was supported in part by HST AR #13919, HST GO #14268, and HST AR #14560.

Columnar characteristics of aerosols by spectroradiometer measurements in the maritime area of the Cadiz Gulf (Spain)

NASA Astrophysics Data System (ADS)

Vergaz, Ricardo; Cachorro, Victoria E.; de Frutos, Ángel M.; Vilaplana, José M.; de La Morena, Benito A.

2005-11-01

Atmospheric aerosol characteristics represented by the spectral aerosol optical depth AOD) and the Ångström turbidity parameter were determined in the coastal area of the Gulf of Cádiz, (southwest of Spain). The columnar aerosol properties presented here correspond to the 1996-1999 period, and were obtained by solar direct irradiance measurements carried out by a Licor1800 spectroradiometer. The performance of this type of medium-spectral resolution radiometric system is analysed over the measured period. The detailed spectral information of these irradiance measurements enabled the use of selected non-absorption gases spectral windows to determine the columnar spectral AOD that was modelled by Ångström formula to obtain the coefficient. Temporal evolutions of instantaneous values together with a general statistical analysis represented by seasonal values, frequency distributions and some representative correlations for the AOD and the derived Ångström coefficient gave us the first insight of aerosol characteristics in this coastal area. Special attention was paid to the analysis of these aerosol properties at the nominal wavelengths of 440 nm, 670 nm, 870 nm and 1020 nm for the near-future comparisons with the Cimel sun-photometer data. However, taking the most representative aerosol wavelength of 500 nm, the variability of the AOD ranges from 0.005 to 0.53, with a mean of 0.12 (s.d = 0.07) and that of the parameter is given by a mean value of 0.93 (s.d. = 0.58) falling inside the range of marine aerosols. A quantitative discrimination of aerosol types was conducted on the basis of the spectral aerosol properties and air mass back trajectory analysis, which resulted in a mixed type because of the specificity of this area, given by very frequent desert dust episodes, continental and polluted local influences. This study represents the first extended data characterization about columnar properties of aerosols in Spain which has been continued by Cimel-AERONET data. Copyright

Spatial-temporal-spectral EEG patterns of BOLD functional network connectivity dynamics

NASA Astrophysics Data System (ADS)

Lamoš, Martin; Mareček, Radek; Slavíček, Tomáš; Mikl, Michal; Rektor, Ivan; Jan, Jiří

2018-06-01

Objective. Growing interest in the examination of large-scale brain network functional connectivity dynamics is accompanied by an effort to find the electrophysiological correlates. The commonly used constraints applied to spatial and spectral domains during electroencephalogram (EEG) data analysis may leave part of the neural activity unrecognized. We propose an approach that blindly reveals multimodal EEG spectral patterns that are related to the dynamics of the BOLD functional network connectivity. Approach. The blind decomposition of EEG spectrogram by parallel factor analysis has been shown to be a useful technique for uncovering patterns of neural activity. The simultaneously acquired BOLD fMRI data were decomposed by independent component analysis. Dynamic functional connectivity was computed on the component’s time series using a sliding window correlation, and between-network connectivity states were then defined based on the values of the correlation coefficients. ANOVA tests were performed to assess the relationships between the dynamics of between-network connectivity states and the fluctuations of EEG spectral patterns. Main results. We found three patterns related to the dynamics of between-network connectivity states. The first pattern has dominant peaks in the alpha, beta, and gamma bands and is related to the dynamics between the auditory, sensorimotor, and attentional networks. The second pattern, with dominant peaks in the theta and low alpha bands, is related to the visual and default mode network. The third pattern, also with peaks in the theta and low alpha bands, is related to the auditory and frontal network. Significance. Our previous findings revealed a relationship between EEG spectral pattern fluctuations and the hemodynamics of large-scale brain networks. In this study, we suggest that the relationship also exists at the level of functional connectivity dynamics among large-scale brain networks when no standard spatial and spectral constraints are applied on the EEG data.

Performance evaluation of the multiple-image optical compression and encryption method by increasing the number of target images

NASA Astrophysics Data System (ADS)

Aldossari, M.; Alfalou, A.; Brosseau, C.

2017-08-01

In an earlier study [Opt. Express 22, 22349-22368 (2014)], a compression and encryption method that simultaneous compress and encrypt closely resembling images was proposed and validated. This multiple-image optical compression and encryption (MIOCE) method is based on a special fusion of the different target images spectra in the spectral domain. Now for the purpose of assessing the capacity of the MIOCE method, we would like to evaluate and determine the influence of the number of target images. This analysis allows us to evaluate the performance limitation of this method. To achieve this goal, we use a criterion based on the root-mean-square (RMS) [Opt. Lett. 35, 1914-1916 (2010)] and compression ratio to determine the spectral plane area. Then, the different spectral areas are merged in a single spectrum plane. By choosing specific areas, we can compress together 38 images instead of 26 using the classical MIOCE method. The quality of the reconstructed image is evaluated by making use of the mean-square-error criterion (MSE).

Impacts of spectral nudging on the simulated surface air temperature in summer compared with the selection of shortwave radiation and land surface model physics parameterization in a high-resolution regional atmospheric model

NASA Astrophysics Data System (ADS)

Park, Jun; Hwang, Seung-On

2017-11-01

The impact of a spectral nudging technique for the dynamical downscaling of the summer surface air temperature in a high-resolution regional atmospheric model is assessed. The performance of this technique is measured by comparing 16 analysis-driven simulation sets of physical parameterization combinations of two shortwave radiation and four land surface model schemes of the model, which are known to be crucial for the simulation of the surface air temperature. It is found that the application of spectral nudging to the outermost domain has a greater impact on the regional climate than any combination of shortwave radiation and land surface model physics schemes. The optimal choice of two model physics parameterizations is helpful for obtaining more realistic spatiotemporal distributions of land surface variables such as the surface air temperature, precipitation, and surface fluxes. However, employing spectral nudging adds more value to the results; the improvement is greater than using sophisticated shortwave radiation and land surface model physical parameterizations. This result indicates that spectral nudging applied to the outermost domain provides a more accurate lateral boundary condition to the innermost domain when forced by analysis data by securing the consistency with large-scale forcing over a regional domain. This consequently indirectly helps two physical parameterizations to produce small-scale features closer to the observed values, leading to a better representation of the surface air temperature in a high-resolution downscaled climate.

Reflectance Prediction Modelling for Residual-Based Hyperspectral Image Coding

PubMed Central

Xiao, Rui; Gao, Junbin; Bossomaier, Terry

2016-01-01

A Hyperspectral (HS) image provides observational powers beyond human vision capability but represents more than 100 times the data compared to a traditional image. To transmit and store the huge volume of an HS image, we argue that a fundamental shift is required from the existing “original pixel intensity”-based coding approaches using traditional image coders (e.g., JPEG2000) to the “residual”-based approaches using a video coder for better compression performance. A modified video coder is required to exploit spatial-spectral redundancy using pixel-level reflectance modelling due to the different characteristics of HS images in their spectral and shape domain of panchromatic imagery compared to traditional videos. In this paper a novel coding framework using Reflectance Prediction Modelling (RPM) in the latest video coding standard High Efficiency Video Coding (HEVC) for HS images is proposed. An HS image presents a wealth of data where every pixel is considered a vector for different spectral bands. By quantitative comparison and analysis of pixel vector distribution along spectral bands, we conclude that modelling can predict the distribution and correlation of the pixel vectors for different bands. To exploit distribution of the known pixel vector, we estimate a predicted current spectral band from the previous bands using Gaussian mixture-based modelling. The predicted band is used as the additional reference band together with the immediate previous band when we apply the HEVC. Every spectral band of an HS image is treated like it is an individual frame of a video. In this paper, we compare the proposed method with mainstream encoders. The experimental results are fully justified by three types of HS dataset with different wavelength ranges. The proposed method outperforms the existing mainstream HS encoders in terms of rate-distortion performance of HS image compression. PMID:27695102

Spectral feature design in high dimensional multispectral data

NASA Technical Reports Server (NTRS)

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

1988-01-01

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

Stochastic model stationarization by eliminating the periodic term and its effect on time series prediction

NASA Astrophysics Data System (ADS)

Moeeni, Hamid; Bonakdari, Hossein; Fatemi, Seyed Ehsan

2017-04-01

Because time series stationarization has a key role in stochastic modeling results, three methods are analyzed in this study. The methods are seasonal differencing, seasonal standardization and spectral analysis to eliminate the periodic effect on time series stationarity. First, six time series including 4 streamflow series and 2 water temperature series are stationarized. The stochastic term for these series obtained with ARIMA is subsequently modeled. For the analysis, 9228 models are introduced. It is observed that seasonal standardization and spectral analysis eliminate the periodic term completely, while seasonal differencing maintains seasonal correlation structures. The obtained results indicate that all three methods present acceptable performance overall. However, model accuracy in monthly streamflow prediction is higher with seasonal differencing than with the other two methods. Another advantage of seasonal differencing over the other methods is that the monthly streamflow is never estimated as negative. Standardization is the best method for predicting monthly water temperature although it is quite similar to seasonal differencing, while spectral analysis performed the weakest in all cases. It is concluded that for each monthly seasonal series, seasonal differencing is the best stationarization method in terms of periodic effect elimination. Moreover, the monthly water temperature is predicted with more accuracy than monthly streamflow. The criteria of the average stochastic term divided by the amplitude of the periodic term obtained for monthly streamflow and monthly water temperature were 0.19 and 0.30, 0.21 and 0.13, and 0.07 and 0.04 respectively. As a result, the periodic term is more dominant than the stochastic term for water temperature in the monthly water temperature series compared to streamflow series.

Fast and Accurate Radiative Transfer Calculations Using Principal Component Analysis for (Exo-)Planetary Retrieval Models

NASA Astrophysics Data System (ADS)

Kopparla, P.; Natraj, V.; Shia, R. L.; Spurr, R. J. D.; Crisp, D.; Yung, Y. L.

2015-12-01

Radiative transfer (RT) computations form the engine of atmospheric retrieval codes. However, full treatment of RT processes is computationally expensive, prompting usage of two-stream approximations in current exoplanetary atmospheric retrieval codes [Line et al., 2013]. Natraj et al. [2005, 2010] and Spurr and Natraj [2013] demonstrated the ability of a technique using principal component analysis (PCA) to speed up RT computations. In the PCA method for RT performance enhancement, empirical orthogonal functions are developed for binned sets of inherent optical properties that possess some redundancy; costly multiple-scattering RT calculations are only done for those few optical states corresponding to the most important principal components, and correction factors are applied to approximate radiation fields. Kopparla et al. [2015, in preparation] extended the PCA method to a broadband spectral region from the ultraviolet to the shortwave infrared (0.3-3 micron), accounting for major gas absorptions in this region. Here, we apply the PCA method to a some typical (exo-)planetary retrieval problems. Comparisons between the new model, called Universal Principal Component Analysis Radiative Transfer (UPCART) model, two-stream models and line-by-line RT models are performed, for spectral radiances, spectral fluxes and broadband fluxes. Each of these are calculated at the top of the atmosphere for several scenarios with varying aerosol types, extinction and scattering optical depth profiles, and stellar and viewing geometries. We demonstrate that very accurate radiance and flux estimates can be obtained, with better than 1% accuracy in all spectral regions and better than 0.1% in most cases, as compared to a numerically exact line-by-line RT model. The accuracy is enhanced when the results are convolved to typical instrument resolutions. The operational speed and accuracy of UPCART can be further improved by optimizing binning schemes and parallelizing the codes, work on which is under way.

Sentence intelligibility during segmental interruption and masking by speech-modulated noise: Effects of age and hearing loss

PubMed Central

Fogerty, Daniel; Ahlstrom, Jayne B.; Bologna, William J.; Dubno, Judy R.

2015-01-01

This study investigated how single-talker modulated noise impacts consonant and vowel cues to sentence intelligibility. Younger normal-hearing, older normal-hearing, and older hearing-impaired listeners completed speech recognition tests. All listeners received spectrally shaped speech matched to their individual audiometric thresholds to ensure sufficient audibility with the exception of a second younger listener group who received spectral shaping that matched the mean audiogram of the hearing-impaired listeners. Results demonstrated minimal declines in intelligibility for older listeners with normal hearing and more evident declines for older hearing-impaired listeners, possibly related to impaired temporal processing. A correlational analysis suggests a common underlying ability to process information during vowels that is predictive of speech-in-modulated noise abilities. Whereas, the ability to use consonant cues appears specific to the particular characteristics of the noise and interruption. Performance declines for older listeners were mostly confined to consonant conditions. Spectral shaping accounted for the primary contributions of audibility. However, comparison with the young spectral controls who received identical spectral shaping suggests that this procedure may reduce wideband temporal modulation cues due to frequency-specific amplification that affected high-frequency consonants more than low-frequency vowels. These spectral changes may impact speech intelligibility in certain modulation masking conditions. PMID:26093436

An advanced scanning method for space-borne hyper-spectral imaging system

NASA Astrophysics Data System (ADS)

Wang, Yue-ming; Lang, Jun-Wei; Wang, Jian-Yu; Jiang, Zi-Qing

2011-08-01

Space-borne hyper-spectral imagery is an important means for the studies and applications of earth science. High cost efficiency could be acquired by optimized system design. In this paper, an advanced scanning method is proposed, which contributes to implement both high temporal and spatial resolution imaging system. Revisit frequency and effective working time of space-borne hyper-spectral imagers could be greatly improved by adopting two-axis scanning system if spatial resolution and radiometric accuracy are not harshly demanded. In order to avoid the quality degradation caused by image rotation, an idea of two-axis rotation has been presented based on the analysis and simulation of two-dimensional scanning motion path and features. Further improvement of the imagers' detection ability under the conditions of small solar altitude angle and low surface reflectance can be realized by the Ground Motion Compensation on pitch axis. The structure and control performance are also described. An intelligent integration technology of two-dimensional scanning and image motion compensation is elaborated in this paper. With this technology, sun-synchronous hyper-spectral imagers are able to pay quick visit to hot spots, acquiring both high spatial and temporal resolution hyper-spectral images, which enables rapid response of emergencies. The result has reference value for developing operational space-borne hyper-spectral imagers.

Spectral analysis of /s/ sound with changing angulation of the maxillary central incisors.

PubMed

Runte, Christoph; Tawana, Djafar; Dirksen, Dieter; Runte, Bettina; Lamprecht-Dinnesen, Antoinette; Bollmann, Friedhelm; Seifert, Eberhard; Danesh, Gholamreza

2002-01-01

The aim of the study was to measure the influence of the maxillary central incisors free from adaptation phenomena using spectral analysis. The maxillary dentures of 18 subjects were duplicated. The central incisors were fixed in a pivoting appliance so that their position could be changed from labial to palatal direction. A mechanical push/pull cable enabled the incisor section to be handled extraorally. Connected to the control was a sound generator producing a sinus wave whose frequency was related to the central incisor angulation. This acoustic signal was recorded on one channel of a digital tape recorder. After calibration of the unit, the denture duplicate was inserted into the subject's mouth, and the signal of the /s/ sounds subsequently produced by the subject was recorded on the second channel during alteration of the inclination angle simultaneously with the generator signal. Spectral analysis was performed using a Kay Speech-Lab 4300B. Labial displacement in particular produced significant changes in spectral characteristics, with the lower boundary frequency of the /s/ sound being raised and the upper boundary frequency being reduced. Maxillary incisor position influences /s/ sound production. Displacement of the maxillary incisors must be considered a cause of immediate changes in /s/ sound distortion. Therefore, denture teeth should be placed in the original tooth position as accurately as possible. Our results also indicate that neuromuscular reactions are more important for initial speech sound distortions than are aerodynamic changes in the anterior speech sound-producing areas.

Quantitative Hyperspectral Reflectance Imaging

PubMed Central

Klein, Marvin E.; Aalderink, Bernard J.; Padoan, Roberto; de Bruin, Gerrit; Steemers, Ted A.G.

2008-01-01

Hyperspectral imaging is a non-destructive optical analysis technique that can for instance be used to obtain information from cultural heritage objects unavailable with conventional colour or multi-spectral photography. This technique can be used to distinguish and recognize materials, to enhance the visibility of faint or obscured features, to detect signs of degradation and study the effect of environmental conditions on the object. We describe the basic concept, working principles, construction and performance of a laboratory instrument specifically developed for the analysis of historical documents. The instrument measures calibrated spectral reflectance images at 70 wavelengths ranging from 365 to 1100 nm (near-ultraviolet, visible and near-infrared). By using a wavelength tunable narrow-bandwidth light-source, the light energy used to illuminate the measured object is minimal, so that any light-induced degradation can be excluded. Basic analysis of the hyperspectral data includes a qualitative comparison of the spectral images and the extraction of quantitative data such as mean spectral reflectance curves and statistical information from user-defined regions-of-interest. More sophisticated mathematical feature extraction and classification techniques can be used to map areas on the document, where different types of ink had been applied or where one ink shows various degrees of degradation. The developed quantitative hyperspectral imager is currently in use by the Nationaal Archief (National Archives of The Netherlands) to study degradation effects of artificial samples and original documents, exposed in their permanent exhibition area or stored in their deposit rooms. PMID:27873831

Hyperspectral microscopic analysis of normal, benign and carcinoma microarray tissue sections

NASA Astrophysics Data System (ADS)

Maggioni, Mauro; Davis, Gustave L.; Warner, Frederick J.; Geshwind, Frank B.; Coppi, Andreas C.; DeVerse, Richard A.; Coifman, Ronald R.

2006-02-01

We apply a unique micro-optoelectromechanical tuned light source and new algorithms to the hyper-spectral microscopic analysis of human colon biopsies. The tuned light prototype (Plain Sight Systems Inc.) transmits any combination of light frequencies, range 440nm 700nm, trans-illuminating H and E stained tissue sections of normal (N), benign adenoma (B) and malignant carcinoma (M) colon biopsies, through a Nikon Biophot microscope. Hyper-spectral photomicrographs, randomly collected 400X magnication, are obtained with a CCD camera (Sensovation) from 59 different patient biopsies (20 N, 19 B, 20 M) mounted as a microarray on a single glass slide. The spectra of each pixel are normalized and analyzed to discriminate among tissue features: gland nuclei, gland cytoplasm and lamina propria/lumens. Spectral features permit the automatic extraction of 3298 nuclei with classification as N, B or M. When nuclei are extracted from each of the 59 biopsies the average classification among N, B and M nuclei is 97.1%; classification of the biopsies, based on the average nuclei classification, is 100%. However, when the nuclei are extracted from a subset of biopsies, and the prediction is made on nuclei in the remaining biopsies, there is a marked decrement in performance to 60% across the 3 classes. Similarly the biopsy classification drops to 54%. In spite of these classification differences, which we believe are due to instrument and biopsy normalization issues, hyper-spectral analysis has the potential to achieve diagnostic efficiency needed for objective microscopic diagnosis.

Analysis of multispectral scanner (MSS) and Thematic Mapper (TM) performance (pre-launch and post-launch)

NASA Technical Reports Server (NTRS)

Barker, J. L.

1983-01-01

Tables and graphs show the results of the spectral, radiometric, and geometric characterization of LANDSAT 4 sensors associated with imagery and of the imagery associated with sensors and processing. Specifications for the various parameters are compared with the photoflight and flight values.

Spectral Characterization of H2020/PTAL Mineral Samples: Implications for In Situ Martian Exploration and Mars Sample Selection

NASA Astrophysics Data System (ADS)

Lantz, C.; Pilorget, C.; Poulet, F.; Riu, L.; Dypvik, H.; Hellevang, H.; Rull Perez, F.; Veneranda, M.; Cousin, A.; Viennet, J.-C.; Werner, S. C.

2018-04-01

We present combined analysis performed in the framework of the Planetary Terrestrial Analogues Library (H2020 project). XRD, NIR, Raman, and LIBS spectroscopies are used to characterise samples to prepare ExoMars/ESA and Mars2020/NASA observations.

The use of MALDI-TOF ICMS as an alternative tool for Trichophyton rubrum identification and typing.

PubMed

Pereira, Leonel; Dias, Nicolina; Santos, Cledir; Lima, Nelson

2014-01-01

In this study, the potential of matrix-assisted laser desorption/ionization time-of-flight intact cell mass spectrometry (MALDI-TOF ICMS) was investigated for the identification of clinical isolates. The isolates were analyzed at the species and strain level. Spectral identification by MALDI-TOF ICMS was performed for all strains, and compared with the results of sequencing of the internal transcribed spacers (ITS1 and ITS2), and the 5.8S rDNA region. PCR fingerprinting analysis using primers M13, (GACA)4, and (AC)10 was performed in order to assess the intra-specific variability of Trichophyton rubrum strains. The identification of strains at species level by MALDI-TOF ICMS was in agreement with the previously performed morphological and biochemical analysis. Sequence data confirmed spectral mass identification at species level. Intra-specific variability was assessed. Within the T. rubrum cluster, strains were distributed into smaller highly related sub-groups with a similarity values above 85%. MALDI-TOF ICMS was shown to be a rapid, low-cost and accurate alternative tool for the identification and strain typing of T. rubrum. Copyright © 2012 Elsevier España, S.L. All rights reserved.

Exploiting spectral content for image segmentation in GPR data

NASA Astrophysics Data System (ADS)

Wang, Patrick K.; Morton, Kenneth D., Jr.; Collins, Leslie M.; Torrione, Peter A.

2011-06-01

Ground-penetrating radar (GPR) sensors provide an effective means for detecting changes in the sub-surface electrical properties of soils, such as changes indicative of landmines or other buried threats. However, most GPR-based pre-screening algorithms only localize target responses along the surface of the earth, and do not provide information regarding an object's position in depth. As a result, feature extraction algorithms are forced to process data from entire cubes of data around pre-screener alarms, which can reduce feature fidelity and hamper performance. In this work, spectral analysis is investigated as a method for locating subsurface anomalies in GPR data. In particular, a 2-D spatial/frequency decomposition is applied to pre-screener flagged GPR B-scans. Analysis of these spatial/frequency regions suggests that aspects (e.g. moments, maxima, mode) of the frequency distribution of GPR energy can be indicative of the presence of target responses. After translating a GPR image to a function of the spatial/frequency distributions at each pixel, several image segmentation approaches can be applied to perform segmentation in this new transformed feature space. To illustrate the efficacy of the approach, a performance comparison between feature processing with and without the image segmentation algorithm is provided.

Research in the application of spectral data to crop identification and assessment, volume 2

NASA Technical Reports Server (NTRS)

Daughtry, C. S. T. (Principal Investigator); Hixson, M. M.; Bauer, M. E.

1980-01-01

The development of spectrometry crop development stage models is discussed with emphasis on models for corn and soybeans. One photothermal and four thermal meteorological models are evaluated. Spectral data were investigated as a source of information for crop yield models. Intercepted solar radiation and soil productivity are identified as factors related to yield which can be estimated from spectral data. Several techniques for machine classification of remotely sensed data for crop inventory were evaluated. Early season estimation, training procedures, the relationship of scene characteristics to classification performance, and full frame classification methods were studied. The optimal level for combining area and yield estimates of corn and soybeans is assessed utilizing current technology: digital analysis of LANDSAT MSS data on sample segments to provide area estimates and regression models to provide yield estimates.

[A cloud detection algorithm for MODIS images combining Kmeans clustering and multi-spectral threshold method].

PubMed

Wang, Wei; Song, Wei-Guo; Liu, Shi-Xing; Zhang, Yong-Ming; Zheng, Hong-Yang; Tian, Wei

2011-04-01

An improved method for detecting cloud combining Kmeans clustering and the multi-spectral threshold approach is described. On the basis of landmark spectrum analysis, MODIS data is categorized into two major types initially by Kmeans method. The first class includes clouds, smoke and snow, and the second class includes vegetation, water and land. Then a multi-spectral threshold detection is applied to eliminate interference such as smoke and snow for the first class. The method is tested with MODIS data at different time under different underlying surface conditions. By visual method to test the performance of the algorithm, it was found that the algorithm can effectively detect smaller area of cloud pixels and exclude the interference of underlying surface, which provides a good foundation for the next fire detection approach.

An improved synthesis, spectroscopic (FT-IR, NMR) study and DFT computational analysis (IR, NMR, UV-Vis, MEP diagrams, NBO, NLO, FMO) of the 1,5-methanoazocino[4,3-b]indole core structure

NASA Astrophysics Data System (ADS)

Uludağ, Nesimi; Serdaroğlu, Goncagül

2018-03-01

This study examines the synthesis of azocino[4,3-b]indole structure, which constitutes the tetracyclic framework of uleine, dasycarpidoneand tubifolidineas well as ABDE substructure of the strychnosalkaloid family. It has been synthesized by Fischer indolization of 2 and through the cylization of 4 by 2,3-dichlor-5-6-dicyanobenzoquinone (DDQ). 1H and 1C NMR chemical shifts have been predicted with GIAO approach and the calculated chemical shifts show very good agreement with observed shifts. FT-IR spectroscopy is important for the analysis of functional groups of synthesized compounds and we also supported FT-IR vibrational analysis with computational IR analysis. The vibrational spectral analysis was performed at B3LYP level of the theory in both the gas and the water phases and it was compared with the observed IR values for the important functional groups. The DFT calculations have been conducted to determine the most stable structure of the 1,2,3,4,5,6,7-Hexahydro-1,5-methanoazocino [4,3-b] indole (5). The Frontier Molecular Orbital Analysis, quantum chemical parameters, physicochemical properties have been predicted by using the same theory of level in both gas phase and the water phase, at 631 + g** and 6311++g** basis sets. TD- DFT calculations have been performed to predict the UV- Vis spectral analysis for this synthesized molecule. The Natural Bond Orbital (NBO) analysis have been performed at B3LYP level of theory to elucidate the intra-molecular interactions such as electron delocalization and conjugative interactions. NLO calculations were conducted to obtain the electric dipole moment and polarizability of the title compound.

A decision support system for automatic sleep staging from EEG signals using tunable Q-factor wavelet transform and spectral features.

PubMed

Hassan, Ahnaf Rashik; Bhuiyan, Mohammed Imamul Hassan

2016-09-15

Automatic sleep scoring is essential owing to the fact that conventionally a large volume of data have to be analyzed visually by the physicians which is onerous, time-consuming and error-prone. Therefore, there is a dire need of an automated sleep staging scheme. In this work, we decompose sleep-EEG signal segments using tunable-Q factor wavelet transform (TQWT). Various spectral features are then computed from TQWT sub-bands. The performance of spectral features in the TQWT domain has been determined by intuitive and graphical analyses, statistical validation, and Fisher criteria. Random forest is used to perform classification. Optimal choices and the effects of TQWT and random forest parameters have been determined and expounded. Experimental outcomes manifest the efficacy of our feature generation scheme in terms of p-values of ANOVA analysis and Fisher criteria. The proposed scheme yields 90.38%, 91.50%, 92.11%, 94.80%, 97.50% for 6-stage to 2-stage classification of sleep states on the benchmark Sleep-EDF data-set. In addition, its performance on DREAMS Subjects Data-set is also promising. The performance of the proposed method is significantly better than the existing ones in terms of accuracy and Cohen's kappa coefficient. Additionally, the proposed scheme gives high detection accuracy for sleep stages non-REM 1 and REM. Spectral features in the TQWT domain can discriminate sleep-EEG signals corresponding to various sleep states efficaciously. The proposed scheme will alleviate the burden of the physicians, speed-up sleep disorder diagnosis, and expedite sleep research. Copyright © 2016 Elsevier B.V. All rights reserved.

SGR J1550-5418 Bursts Detected with the Fermi Gamma-Ray Burst Monitor during Its Most Prolific Activity

NASA Technical Reports Server (NTRS)

vanderHorst, A. J.; Kouveliotou, C.; Gorgone, N. M.; Kaneko, Y.; Baring, M. G.; Guiriec, S.; Gogus, E,; Granot, J.; Watts, A. L.; Lin, L.;

Frequency domain modeling and dynamic characteristics evaluation of existing wind turbine systems

NASA Astrophysics Data System (ADS)

Chiang, Chih-Hung; Yu, Chih-Peng

2016-04-01

It is quite well accepted that frequency domain procedures are suitable for the design and dynamic analysis of wind turbine structures, especially for floating offshore wind turbines, since random wind loads and wave induced motions are most likely simulated in the frequency domain. This paper presents specific applications of an effective frequency domain scheme to the linear analysis of wind turbine structures in which a 1-D spectral element was developed based on the axially-loaded member. The solution schemes are summarized for the spectral analyses of the tower, the blades, and the combined system with selected frequency-dependent coupling effect from foundation-structure interactions. Numerical examples demonstrate that the modal frequencies obtained using spectral-element models are in good agreement with those found in the literature. A 5-element mono-pile model results in less than 0.3% deviation from an existing 160-element model. It is preliminarily concluded that the proposed scheme is relatively efficient in performing quick verification for test data obtained from the on-site vibration measurement using the microwave interferometer.

Cloud-based processing of multi-spectral imaging data

NASA Astrophysics Data System (ADS)

Bernat, Amir S.; Bolton, Frank J.; Weiser, Reuven; Levitz, David

2017-03-01

Multispectral imaging holds great promise as a non-contact tool for the assessment of tissue composition. Performing multi - spectral imaging on a hand held mobile device would allow to bring this technology and with it knowledge to low resource settings to provide a state of the art classification of tissue health. This modality however produces considerably larger data sets than white light imaging and requires preliminary image analysis for it to be used. The data then needs to be analyzed and logged, while not requiring too much of the system resource or a long computation time and battery use by the end point device. Cloud environments were designed to allow offloading of those problems by allowing end point devices (smartphones) to offload computationally hard tasks. For this end we present a method where the a hand held device based around a smartphone captures a multi - spectral dataset in a movie file format (mp4) and compare it to other image format in size, noise and correctness. We present the cloud configuration used for segmenting images to frames where they can later be used for further analysis.

Quantifying Vocal Mimicry in the Greater Racket-Tailed Drongo: A Comparison of Automated Methods and Human Assessment

PubMed Central

Agnihotri, Samira; Sundeep, P. V. D. S.; Seelamantula, Chandra Sekhar; Balakrishnan, Rohini

2014-01-01

Objective identification and description of mimicked calls is a primary component of any study on avian vocal mimicry but few studies have adopted a quantitative approach. We used spectral feature representations commonly used in human speech analysis in combination with various distance metrics to distinguish between mimicked and non-mimicked calls of the greater racket-tailed drongo, Dicrurus paradiseus and cross-validated the results with human assessment of spectral similarity. We found that the automated method and human subjects performed similarly in terms of the overall number of correct matches of mimicked calls to putative model calls. However, the two methods also misclassified different subsets of calls and we achieved a maximum accuracy of ninety five per cent only when we combined the results of both the methods. This study is the first to use Mel-frequency Cepstral Coefficients and Relative Spectral Amplitude - filtered Linear Predictive Coding coefficients to quantify vocal mimicry. Our findings also suggest that in spite of several advances in automated methods of song analysis, corresponding cross-validation by humans remains essential. PMID:24603717

Hyperspectral microscopy and cluster analysis for oral cancer diagnosis

NASA Astrophysics Data System (ADS)

Jarman, Anneliese; Manickavasagam, Arunthathi; Hosny, Neveen; Festy, Frederic

2017-02-01

Oral cancer incidences have been increasing in recent years and late detection often leads to poor prognosis. Raman spectroscopy has been identified has a valuable diagnostic tool for cancer but its time consuming nature has prevented its clinical use. For Raman to become a realistic aid to histopathology, a rapid pre-screening technique is required to find small regions of interest on tissue sections [1]. The aim of this work is to investigate the feasibility of hyperspectral imaging in the visible spectral range as a fast imaging technique before Raman is performed. We have built a hyperspectral microscope which captures 300 focused and intensity corrected images with wavelength ranging from 450- 750 nm in around 30 minutes with sub-micron spatial resolution and around 10 nm spectral resolution. Hyperstacks of known absorbing samples, including fluorescent dyes and dried blood droplets, show excellent results with spectrally accurate transmission spectra and concentration-dependent intensity variations. We successfully showed the presence of different components from a non-absorbent saliva droplet sample. Data analysis is the greatest hurdle to the interpretation of more complex data such as unstained tissue sections.

Use of the TM tasseled cap transform for interpretation of spectral contrasts in an urban scene

NASA Technical Reports Server (NTRS)

Goward, S. N.; Wharton, S. W.

1984-01-01

Investigations are being conducted with the objective to develop automated numerical image analysis procedures. In this context, an examination is performed of physically-based multispectral data transforms as a means to incorporate a priori knowledge of land radiance properties in the analysis process. A physically-based transform of TM observations was developed. This transform extends the Landsat MSS Tasseled Cap transform reported by Kauth and Thomas (1976) to TM data observations. The present study has the aim to examine the utility of the TM Tasseled Cap transform as applied to TM data from an urban landscape. The analysis conducted is based on 512 x 512 subset of the Washington, DC November 2, 1982 TM scene, centered on Springfield, VA. It appears that the TM tasseled cap transformation provides a good means to explain land physical attributes of the Washington scene. This result provides a suggestion regarding a direction by which a priori knowledge of landscape spectral patterns may be incorporated into numerical image analysis.

The fundamental parameter method applied to X-ray fluorescence analysis with synchrotron radiation

NASA Astrophysics Data System (ADS)

Pantenburg, F. J.; Beier, T.; Hennrich, F.; Mommsen, H.

1992-05-01

Quantitative X-ray fluorescence analysis applying the fundamental parameter method is usually restricted to monochromatic excitation sources. It is shown here, that such analyses can be performed as well with a white synchrotron radiation spectrum. To determine absolute elemental concentration values it is necessary to know the spectral distribution of this spectrum. A newly designed and tested experimental setup, which uses the synchrotron radiation emitted from electrons in a bending magnet of ELSA (electron stretcher accelerator of the university of Bonn) is presented. The determination of the exciting spectrum, described by the given electron beam parameters, is limited due to uncertainties in the vertical electron beam size and divergence. We describe a method which allows us to determine the relative and absolute spectral distributions needed for accurate analysis. First test measurements of different alloys and standards of known composition demonstrate that it is possible to determine exact concentration values in bulk and trace element analysis.

Use of airborne hyperspectral data to estimate residual heavy metal contamination and acidification potential in the Guadiamar floodplain Andalusia, Spain after the Aznacollar mining accident

NASA Astrophysics Data System (ADS)

Kemper, Thomas; Sommer, Stefan

2004-10-01

Field and airborne hyperspectral data was used to map residual contamination after a mining accident, by applying spectral mixture modelling. Test case was the Aznalcollar Mine (Southern Spain) accident, where heavy metal bearing sludge from a tailings pond was distributed over large areas of the Guadiamar flood plain. Although the sludge and the contaminated topsoils have been removed mechanically in the whole affected area, still high abundance of pyritic material remained on the ground. During dedicated field campaigns in two subsequent years soil samples were collected for geochemical and spectral laboratory analysis and spectral field measurements were carried out in parallel to data acquisition with the HyMap sensor. A Variable Multiple Endmember Spectral Mixture Analysis (VMESMA) tool was used providing possibilities of multiple endmember unmixing, aiming to estimate the quantities and distribution of the remaining tailings material. A spectrally based zonal partition of the area was introduced to allow the application of different submodels to the selected areas. Based on an iterative feedback process, the unmixing performance could be improved in each stage until an optimum level was reached. The sludge abundances obtained by unmixing the hyperspectral spectral data were confirmed by the field observations and chemical measurements of samples taken in the area. The semi-quantitative sludge abundances of residual pyritic material could be transformed into quantitative information for an assessment of acidification risk and distribution of residual heavy metal contamination based on an artificial mixture experiment. The unmixing of the second year images allowed identification of secondary minerals of pyrite as indicators of pyrite oxidation and associated acidification.

Quantitative monitoring of sucrose, reducing sugar and total sugar dynamics for phenotyping of water-deficit stress tolerance in rice through spectroscopy and chemometrics

NASA Astrophysics Data System (ADS)

Das, Bappa; Sahoo, Rabi N.; Pargal, Sourabh; Krishna, Gopal; Verma, Rakesh; Chinnusamy, Viswanathan; Sehgal, Vinay K.; Gupta, Vinod K.; Dash, Sushanta K.; Swain, Padmini

2018-03-01

In the present investigation, the changes in sucrose, reducing and total sugar content due to water-deficit stress in rice leaves were modeled using visible, near infrared (VNIR) and shortwave infrared (SWIR) spectroscopy. The objectives of the study were to identify the best vegetation indices and suitable multivariate technique based on precise analysis of hyperspectral data (350 to 2500 nm) and sucrose, reducing sugar and total sugar content measured at different stress levels from 16 different rice genotypes. Spectral data analysis was done to identify suitable spectral indices and models for sucrose estimation. Novel spectral indices in near infrared (NIR) range viz. ratio spectral index (RSI) and normalised difference spectral indices (NDSI) sensitive to sucrose, reducing sugar and total sugar content were identified which were subsequently calibrated and validated. The RSI and NDSI models had R2 values of 0.65, 0.71 and 0.67; RPD values of 1.68, 1.95 and 1.66 for sucrose, reducing sugar and total sugar, respectively for validation dataset. Different multivariate spectral models such as artificial neural network (ANN), multivariate adaptive regression splines (MARS), multiple linear regression (MLR), partial least square regression (PLSR), random forest regression (RFR) and support vector machine regression (SVMR) were also evaluated. The best performing multivariate models for sucrose, reducing sugars and total sugars were found to be, MARS, ANN and MARS, respectively with respect to RPD values of 2.08, 2.44, and 1.93. Results indicated that VNIR and SWIR spectroscopy combined with multivariate calibration can be used as a reliable alternative to conventional methods for measurement of sucrose, reducing sugars and total sugars of rice under water-deficit stress as this technique is fast, economic, and noninvasive.

Periictal activity in cooled asphyxiated neonates with seizures.

PubMed

Major, Philippe; Lortie, Anne; Dehaes, Mathieu; Lodygensky, Gregory Anton; Gallagher, Anne; Carmant, Lionel; Birca, Ala

2017-04-01

Seizures are common in critically ill neonates. Both seizures and antiepileptic treatments may lead to short term complications and worsen the outcomes. Predicting the risks of seizure reoccurrence could enable individual treatment regimens and better outcomes. We aimed to identify EEG signatures of seizure reoccurrence by investigating periictal electrographic features and spectral power characteristics in hypothermic neonates with hypoxic-ischemic encephalopathy (HIE) with or without reoccurrence of seizures on rewarming. We recruited five consecutive HIE neonates, submitted to continuous EEG monitoring, with high seizure burden (>20% per hour) while undergoing therapeutic hypothermia. Two of them had reoccurrence of seizures on rewarming. We performed quantitative analysis of fifteen artifact-free consecutive seizures to appreciate spectral power changes between the interictal, preictal and ictal periods, separately for each patient. Visual analysis allowed description of electrographic features associated with ictal events. Every patient demonstrated a significant increase in overall spectral power from the interictal to preictal and ictal periods (p<0.01). Alpha power increase was more pronounced in the two patients with reoccurrence of seizures on rewarming and significant when comparing both interictal-to-preictal and interictal-to-ictal periods. This alpha activity increase could be also appreciated using visual analysis and distinguished neonates with and without seizure reoccurrence. This distinct alpha activity preceding ictal onset could represent a biomarker of propensity for seizure reoccurrence in neonates. Future studies should be performed to confirm whether quantitative periictal characteristics and electrographic features allow predicting the risks of seizure reoccurrence in HIE neonates and other critically ill patients. Copyright © 2017 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

Evaluation of the performance of a tandem mass spectral library with mass spectral data extracted from literature.

PubMed

Würtinger, Philipp; Oberacher, Herbert

2012-01-01

MSforID represents a database of tandem mass spectral data obtained from (quasi-)molecular ions produced by atmospheric pressure ionization methods. At the current stage of development the library contains 12 122 spectra of 1208 small (bio-)organic molecules. The present work was aimed to evaluate the performance of the MSforID library in terms of accuracy and transferability with a collection of fragment ion mass spectra from various compounds acquired on multiple instruments. A literature survey was conducted to collect the set of sample spectra. A total number of 554 spectra covering 291 compounds were extracted from 109 publications. The majority of spectra originated from publications on applications of LC/MS/MS in drug monitoring, pharmacokinetics, environmental analysis, forensic analysis as well as food analysis. Almost all types of tandem mass spectrometric instruments distributed by the five most important instrument vendors were included in the study. The overall sensitivity of library search was found to be 96.4%, which clearly proves that the MSforID library can successfully handle data from a huge variety of mass spectrometric instruments to allow accurate compound identification. Only for spectra containing three or more fragment ions, however, the rate of classified matches (= matches with a relative average match probability (ramp) score > 40.0) was 95%. Ambiguous or unclassified results were mainly obtained for searches with single precursor-to-fragment ion transitions due to the insufficient specificity of such a low amount of structural information to unequivocally define a single compound. Copyright © 2011 John Wiley & Sons, Ltd.

Absorption and Attenuation Coefficients Using the WET Labs ac-s in the Mid-Atlantic Bight: Field Measurements and Data Analysis

NASA Technical Reports Server (NTRS)

Ohi, Nobuaki; Makinen, Carla P.; Mitchell, Richard; Moisan, Tiffany A.

2008-01-01

Ocean color algorithms are based on the parameterization of apparent optical properties as a function of inherent optical properties. WET Labs underwater absorption and attenuation meters (ac-9 and ac-s) measure both the spectral beam attenuation [c (lambda)] and absorption coefficient [a (lambda)]. The ac-s reports in a continuous range of 390-750 nm with a band pass of 4 nm, totaling approximately 83 distinct wavelengths, while the ac-9 reports at 9 wavelengths. We performed the ac-s field measurements at nine stations in the Mid-Atlantic Bight from water calibrations to data analysis. Onboard the ship, the ac-s was calibrated daily using Milli Q-water. Corrections for the in situ temperature and salinity effects on optical properties of water were applied. Corrections for incomplete recovery of the scattered light in the ac-s absorption tube were performed. The fine scale of spectral and vertical distributions of c (lambda) and a (lambda) were described from the ac-s. The significant relationships between a (674) and that of spectrophotometric analysis and chlorophyll a concentration of discrete water samples were observed.

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.

Absolute Configuration of 3-METHYLCYCLOHEXANONE by Chiral Tag Rotational Spectroscopy and Vibrational Circular Dichroism

NASA Astrophysics Data System (ADS)

Evangelisti, Luca; Holdren, Martin S.; Mayer, Kevin J.; Smart, Taylor; West, Channing; Pate, Brooks

2017-06-01

The absolute configuration of 3-methylcyclohexanone was established by chiral tag rotational spectroscopy measurements using 3-butyn-2-ol as the tag partner. This molecule was chosen because it is a benchmark measurement for vibrational circular dichroism (VCD). A comparison of the analysis approaches of chiral tag rotational spectroscopy and VCD will be presented. One important issue in chiral analysis by both methods is the conformational flexibility of the molecule being analyzed. The analysis of conformational composition of samples will be illustrated. In this case, the high spectral resolution of molecular rotational spectroscopy and potential for spectral simplification by conformational cooling in the pulsed jet expansion are advantages for chiral tag spectroscopy. The computational chemistry requirements for the two methods will also be discussed. In this case, the need to perform conformer searches for weakly bound complexes and to perform reasonably high level quantum chemistry geometry optimizations on these complexes makes the computational time requirements less favorable for chiral tag rotational spectroscopy. Finally, the issue of reliability of the determination of the absolute configuration will be considered. In this case, rotational spectroscopy offers a "gold standard" analysis method through the determination of the ^{13}C-subsitution structure of the complex between 3-methylcyclohexanone and an enantiopure sample of the 3-butyn-2-ol tag.

Imaging of blood cells based on snapshot Hyper-Spectral Imaging systems

NASA Astrophysics Data System (ADS)

Robison, Christopher J.; Kolanko, Christopher; Bourlai, Thirimachos; Dawson, Jeremy M.

2015-05-01

Snapshot Hyper-Spectral imaging systems are capable of capturing several spectral bands simultaneously, offering coregistered images of a target. With appropriate optics, these systems are potentially able to image blood cells in vivo as they flow through a vessel, eliminating the need for a blood draw and sample staining. Our group has evaluated the capability of a commercial Snapshot Hyper-Spectral imaging system, the Arrow system from Rebellion Photonics, in differentiating between white and red blood cells on unstained blood smear slides. We evaluated the imaging capabilities of this hyperspectral camera; attached to a microscope at varying objective powers and illumination intensity. Hyperspectral data consisting of 25, 443x313 hyperspectral bands with ~3nm spacing were captured over the range of 419 to 494nm. Open-source hyper-spectral data cube analysis tools, used primarily in Geographic Information Systems (GIS) applications, indicate that white blood cells features are most prominent in the 428-442nm band for blood samples viewed under 20x and 50x magnification over a varying range of illumination intensities. These images could potentially be used in subsequent automated white blood cell segmentation and counting algorithms for performing in vivo white blood cell counting.

Resolution-enhanced Mapping Spectrometer

NASA Technical Reports Server (NTRS)

Kumer, J. B.; Aubrun, J. N.; Rosenberg, W. J.; Roche, A. E.

1993-01-01

A familiar mapping spectrometer implementation utilizes two dimensional detector arrays with spectral dispersion along one direction and spatial along the other. Spectral images are formed by spatially scanning across the scene (i.e., push-broom scanning). For imaging grating and prism spectrometers, the slit is perpendicular to the spatial scan direction. For spectrometers utilizing linearly variable focal-plane-mounted filters the spatial scan direction is perpendicular to the direction of spectral variation. These spectrometers share the common limitation that the number of spectral resolution elements is given by the number of pixels along the spectral (or dispersive) direction. Resolution enhancement by first passing the light input to the spectrometer through a scanned etalon or Michelson is discussed. Thus, while a detector element is scanned through a spatial resolution element of the scene, it is also temporally sampled. The analysis for all the pixels in the dispersive direction is addressed. Several specific examples are discussed. The alternate use of a Michelson for the same enhancement purpose is also discussed. Suitable for weight constrained deep space missions, hardware systems were developed including actuators, sensor, and electronics such that low-resolution etalons with performance required for implementation would weigh less than one pound.

Spectral discrimination of bleached and healthy submerged corals based on principal components analysis

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

Holden, H.; LeDrew, E.

1997-06-01

Remote discrimination of substrate types in relatively shallow coastal waters has been limited by the spatial and spectral resolution of available sensors. An additional limiting factor is the strong attenuating influence of the water column over the substrate. As a result, there have been limited attempts to map submerged ecosystems such as coral reefs based on spectral characteristics. Both healthy and bleached corals were measured at depth with a hand-held spectroradiometer, and their spectra compared. Two separate principal components analyses (PCA) were performed on two sets of spectral data. The PCA revealed that there is indeed a spectral difference basedmore » on health. In the first data set, the first component (healthy coral) explains 46.82%, while the second component (bleached coral) explains 46.35% of the variance. In the second data set, the first component (bleached coral) explained 46.99%; the second component (healthy coral) explained 36.55%; and the third component (healthy coral) explained 15.44 % of the total variance in the original data. These results are encouraging with respect to using an airborne spectroradiometer to identify areas of bleached corals thus enabling accurate monitoring over time.« less

Phototoxicity of bergamot oil assessed by in vitro techniques in combination with human patch tests.

PubMed

Kejlová, K; Jírová, D; Bendová, H; Kandárová, H; Weidenhoffer, Z; Kolárová, H; Liebsch, M

2007-10-01

The aim of this study was to clarify the differences in the phototoxicity of bergamot oil obtained from four different suppliers. Spectral and chemical analyses were performed to identify presence of photoactive compounds in the test samples. The phototoxicity was assessed in vitro by the 3T3 NRU phototoxicity test (PT) and subsequently in a phototoxicity test on reconstructed human skin model (H3D PT). Confirmatory photopatch tests in a group of volunteers were performed using the first non-phototoxic concentration determined in the H3D PT. The spectral and chemical analyses revealed, that two samples of bergamot oil exhibited a potential for photoactivation. These oils were subsequently classified as phototoxic in the 3T3 NRU PT, however, only on the basis of borderline results and depending on the solvent used. H3D PT revealed clear classifications, correlating well with the findings of spectral and chemical analysis. The test was, however, not yet capable of precise prediction of safe, non-phototoxic concentrations. Additional endpoints, e.g. interleukin determination might be employed to increase the sensitivity of the test. Although the study showed the usefulness of the tiered testing strategy, currently, the extrapolation of in vitro results to human situation may be performed only to a limited extent.

Stage call: Cardiovascular reactivity to audition stress in musicians

PubMed Central

Chanwimalueang, Theerasak; Aufegger, Lisa; Adjei, Tricia; Wasley, David; Cruder, Cinzia; Mandic, Danilo P.

2017-01-01

Auditioning is at the very center of educational and professional life in music and is associated with significant psychophysical demands. Knowledge of how these demands affect cardiovascular responses to psychosocial pressure is essential for developing strategies to both manage stress and understand optimal performance states. To this end, we recorded the electrocardiograms (ECGs) of 16 musicians (11 violinists and 5 flutists) before and during performances in both low- and high-stress conditions: with no audience and in front of an audition panel, respectively. The analysis consisted of the detection of R-peaks in the ECGs to extract heart rate variability (HRV) from the notoriously noisy real-world ECGs. Our data analysis approach spanned both standard (temporal and spectral) and advanced (structural complexity) techniques. The complexity science approaches—namely, multiscale sample entropy and multiscale fuzzy entropy—indicated a statistically significant decrease in structural complexity in HRV from the low- to the high-stress condition and an increase in structural complexity from the pre-performance to performance period, thus confirming the complexity loss theory and a loss in degrees of freedom due to stress. Results from the spectral analyses also suggest that the stress responses in the female participants were more parasympathetically driven than those of the male participants. In conclusion, our findings suggest that interventions to manage stress are best targeted at the sensitive pre-performance period, before an audition begins. PMID:28437466

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.

CALIBRATION AND VALIDATION OF CONFOCAL SPECTRAL IMAGING SYSTEMS

EPA Science Inventory

Confocal spectral imaging (CSI) microscope systems now on the market can perform spectral characterization of biological specimens containing fluorescent proteins, labels or dyes. Some CSI have been found to present inconsistent spectral characterizations within a particular syst...

Isotopic determination of uranium in soil by laser induced breakdown spectroscopy

DOE PAGES

Chan, George C. -Y.; Choi, Inhee; Mao, Xianglei; ...

2016-03-26

Laser-induced breakdown spectroscopy (LIBS) operated under ambient pressure has been evaluated for isotopic analysis of uranium in real-world samples such as soil, with U concentrations in the single digit percentage levels. The study addresses the requirements for spectral decomposition of 235U and 238U atomic emission peaks that are only partially resolved. Although non-linear least-square fitting algorithms are typically able to locate the optimal combination of fitting parameters that best describes the experimental spectrum even when all fitting parameters are treated as free independent variables, the analytical results of such an unconstrained free-parameter approach are ambiguous. In this work, five spectralmore » decomposition algorithms were examined, with different known physical properties (e.g., isotopic splitting, hyperfine structure) of the spectral lines sequentially incorporated into the candidate algorithms as constraints. It was found that incorporation of such spectral-line constraints into the decomposition algorithm is essential for the best isotopic analysis. The isotopic abundance of 235U was determined from a simple two-component Lorentzian fit on the U II 424.437 nm spectral profile. For six replicate measurements, each with only fifteen laser shots, on a soil sample with U concentration at 1.1% w/w, the determined 235U isotopic abundance was (64.6 ± 4.8)%, and agreed well with the certified value of 64.4%. Another studied U line - U I 682.691 nm possesses hyperfine structure that is comparatively broad and at a significant fraction as the isotopic shift. Thus, 235U isotopic analysis with this U I line was performed with spectral decomposition involving individual hyperfine components. For the soil sample with 1.1% w/w U, the determined 235U isotopic abundance was (60.9 ± 2.0)%, which exhibited a relative bias about 6% from the certified value. The bias was attributed to the spectral resolution of our measurement system - the measured line width for this U I line was larger than its isotopic splitting. In conclusion, although not the best emission line for isotopic analysis, this U I emission line is sensitive for element analysis with a detection limit of 500 ppm U in the soil matrix; the detection limit for the U II 424.437 nm line was 2000 ppm.« less

[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.

Recent progress of push-broom infrared hyper-spectral imager in SITP

NASA Astrophysics Data System (ADS)

Wang, Yueming; Hu, Weida; Shu, Rong; Li, Chunlai; Yuan, Liyin; Wang, Jianyu

2017-02-01

In the past decades, hyper-spectral imaging technologies were well developed in SITP, CAS. Many innovations for system design and key parts of hyper-spectral imager were finished. First airborne hyper-spectral imager operating from VNIR to TIR in the world was emerged in SITP. It is well known as OMIS(Operational Modular Imaging Spectrometer). Some new technologies were introduced to improve the performance of hyper-spectral imaging system in these years. A high spatial space-borne hyper-spectral imager aboard Tiangong-1 spacecraft was launched on Sep.29, 2011. Thanks for ground motion compensation and high optical efficiency prismatic spectrometer, a large amount of hyper-spectral imagery with high sensitivity and good quality were acquired in the past years. Some important phenomena were observed. To diminish spectral distortion and expand field of view, new type of prismatic imaging spectrometer based curved prism were proposed by SITP. A prototype of hyper-spectral imager based spherical fused silica prism were manufactured, which can operate from 400nm 2500nm. We also made progress in the development of LWIR hyper-spectral imaging technology. Compact and low F number LWIR imaging spectrometer was designed, manufactured and integrated. The spectrometer operated in a cryogenically-cooled vacuum box for background radiation restraint. The system performed well during flight experiment in an airborne platform. Thanks high sensitivity FPA and high performance optics, spatial resolution and spectral resolution and SNR of system are improved enormously. However, more work should be done for high radiometric accuracy in the future.

Trace gas detection in hyperspectral imagery using the wavelet packet subspace

NASA Astrophysics Data System (ADS)

Salvador, Mark A. Z.

This dissertation describes research into a new remote sensing method to detect trace gases in hyperspectral and ultra-spectral data. This new method is based on the wavelet packet transform. It attempts to improve both the computational tractability and the detection of trace gases in airborne and spaceborne spectral imagery. Atmospheric trace gas research supports various Earth science disciplines to include climatology, vulcanology, pollution monitoring, natural disasters, and intelligence and military applications. Hyperspectral and ultra-spectral data significantly increases the data glut of existing Earth science data sets. Spaceborne spectral data in particular significantly increases spectral resolution while performing daily global collections of the earth. Application of the wavelet packet transform to the spectral space of hyperspectral and ultra-spectral imagery data potentially improves remote sensing detection algorithms. It also facilities the parallelization of these methods for high performance computing. This research seeks two science goals, (1) developing a new spectral imagery detection algorithm, and (2) facilitating the parallelization of trace gas detection in spectral imagery data.

Multispectral Snapshot Imagers Onboard Small Satellite Formations for Multi-Angular Remote Sensing

NASA Technical Reports Server (NTRS)

Nag, Sreeja; Hewagama, Tilak; Georgiev, Georgi; Pasquale, Bert; Aslam, Shahid; Gatebe, Charles K.

2017-01-01

Multispectral snapshot imagers are capable of producing 2D spatial images with a single exposure at selected, numerous wavelengths using the same camera, therefore operate differently from push broom or whiskbroom imagers. They are payloads of choice in multi-angular, multi-spectral imaging missions that use small satellites flying in controlled formation, to retrieve Earth science measurements dependent on the targets Bidirectional Reflectance-Distribution Function (BRDF). Narrow fields of view are needed to capture images with moderate spatial resolution. This paper quantifies the dependencies of the imagers optical system, spectral elements and camera on the requirements of the formation mission and their impact on performance metrics such as spectral range, swath and signal to noise ratio (SNR). All variables and metrics have been generated from a comprehensive, payload design tool. The baseline optical parameters selected (diameter 7 cm, focal length 10.5 cm, pixel size 20 micron, field of view 1.15 deg) and snapshot imaging technologies are available. The spectral components shortlisted were waveguide spectrometers, acousto-optic tunable filters (AOTF), electronically actuated Fabry-Perot interferometers, and integral field spectrographs. Qualitative evaluation favored AOTFs because of their low weight, small size, and flight heritage. Quantitative analysis showed that waveguide spectrometers perform better in terms of achievable swath (10-90 km) and SNR (greater than 20) for 86 wavebands, but the data volume generated will need very high bandwidth communication to downlink. AOTFs meet the external data volume caps well as the minimum spectral (wavebands) and radiometric (SNR) requirements, therefore are found to be currently feasible in spite of lower swath and SNR.

An Example Crossover Experiment for Testing New Vicarious Calibration Techniques for Satellite Ocean Color Radiometry

NASA Technical Reports Server (NTRS)

Voss, Kenneth J.; McLean, Scott; Lewis, Marlon; Johnson, Carol; Flora, Stephanie; Feinholz, Michael; Yarbrough, Mark; Trees, Charles; Twardowski, Mike; Clark, Dennis

2010-01-01

Vicarious calibration of ocean color satellites involves the use of accurate surface measurements of water-leaving radiance to update and improve the system calibration of ocean color satellite sensors. An experiment was performed to compare a free-fall technique with the established MOBY measurement. We found in the laboratory that the radiance and irradiance instruments compared well within their estimated uncertainties for various spectral sources. The spectrally averaged differences between the NIST values for the sources and the instruments were less than 2.5% for the radiance sensors and less than 1.5% for the irradiance sensors. In the field, the sensors measuring the above-surface downwelling irradiance performed nearly as well as they had in the laboratory, with an average difference of less than 2%. While the water-leaving radiance, L(sub w) calculated from each instrument agreed in almost all cases within the combined instrument uncertainties (approximately 7%), there was a relative bias between the two instrument classes/techniques that varied spectrally. The spectrally averaged (400 nm to 600 nm) difference between the two instrument classes/techniques was 3.1 %. However the spectral variation resulted in the free fall instruments being 0.2% lower at 450 nm and 5.9% higher at 550 nm. Based on the analysis of one matchup, the bias in the L(sub w), was similar to that observed for L(sub u)(1 m) with both systems, indicating the difference did not come from propagating L(sub u)(1 m) to L(sub w).

Mid-IR Spectral Investigation of Normal and Malignant Breast and Cervical Tissue Samples Using a Quantum Cascade Laser-Based Microscope

NASA Astrophysics Data System (ADS)

Haugen, Paul

Mid-infrared (MIR) spectroscopy has been a tool used to identify specific features of normal and malignant tissue samples by utilizing MIR characteristics, specifically in the "fingerprint" region. The fingerprint region is a biologically significant spectral region typically identified between 1500 and 500 cm-1. MIR spectroscopy can be used to study molecular changes and variations occurring in samples, which can then be used to fingerprint specific spectral characteristics and biomarkers in order to categorize the specimens. The most common instruments currently used in this analysis are Fourier transform infrared (FTIR) spectrometers, although properties inherent in these instruments, such as slow data collection time and an inability to specify sample location for the spectral data collection, have placed a ceiling on the clinical practicality of their use for specimen classification and identification. In this thesis, we use a prototype of an infrared hyperspectral imaging microscopy platform based around tunable quantum cascade laser (QCL) technology that has a spectral coverage from 1800-900 cm-1. The quantum cascade lasers are coupled with a series of MIR refractive objectives and an uncooled microbolometer camera. The speed of spectral imaging improves to 30 frames per second, and the high magnification objective has a 1.34 microm pixel resolution with a 0.70 numerical aperture and 4.3 microm spatial resolution. We are able to specify data collection at specific discrete wavelengths as opposed to the full spectrum, which improves the data collection time and de-clutters the data for analysis expediency. Finally, we perform spectral imaging real-time, which aides in selecting precise regions of interest on the target sample. This thesis demonstrates the advantages of exploiting the capabilities of the QCL microscope to advance MIR spectroscopy in the identification of distinguishing traits of normal and malignant breast and cervical tissue samples.

Method and apparatus for simultaneously measuring a plurality of spectral wavelengths present in electromagnetic radiation

DOEpatents

Buican, Tudor N.; Martin, John C.

1990-01-01

An apparatus and method simultaneously measures a plurality of spectral wavelengths present in electromagnetic radiation. A modulatable birefringent optical element is employed to divide a polarized light beam into two components, thereby producing a phase difference in two resulting light beams such that the two beams can be made to interfere with one another when recombined, the interference pattern providing the wavelength information required for the analysis of the incident light. The interferometer thus created performs in a similar manner to a Michelson interferometer, but with no moving parts, and with a resolution dependent on the degree of phase shift introduced by the modulator.

Batse/Sax and Batse/RXTE-ASM Joint Spectral Studies of GRBs

NASA Technical Reports Server (NTRS)

Paciesas, William S.

2002-01-01

We proposed to make joint spectral analysis of gamma-ray bursts (GRBs) in the BATSE data base that are located within the fields of view of either the BeppoSAX wide field cameras (WFCs) or the RXTE all-sky monitor (ASM). The very broad-band coverage obtained in this way would facilitate various studies of GRB spectra that are difficult to perform with BATSE data alone. Unfortunately, the termination of the CGRO mission in June 2000 was not anticipated at the time of the proposal, and the sample of common events turned out to be smaller than we would have liked.

Hyperspectral imaging using the single-pixel Fourier transform technique

NASA Astrophysics Data System (ADS)

Jin, Senlin; Hui, Wangwei; Wang, Yunlong; Huang, Kaicheng; Shi, Qiushuai; Ying, Cuifeng; Liu, Dongqi; Ye, Qing; Zhou, Wenyuan; Tian, Jianguo

2017-03-01

Hyperspectral imaging technology is playing an increasingly important role in the fields of food analysis, medicine and biotechnology. To improve the speed of operation and increase the light throughput in a compact equipment structure, a Fourier transform hyperspectral imaging system based on a single-pixel technique is proposed in this study. Compared with current imaging spectrometry approaches, the proposed system has a wider spectral range (400-1100 nm), a better spectral resolution (1 nm) and requires fewer measurement data (a sample rate of 6.25%). The performance of this system was verified by its application to the non-destructive testing of potatoes.

WAVELENGTH AND ALIGNMENT TESTS FOR CONFOCAL SPECTRAL IMAGING SYSTEMS

EPA Science Inventory

Confocal spectral imaging (CSI) microscope systems now on the market delineate multiple fluorescent proteins, labels, or dyes within biological specimens by performing spectral characterizations. However, we find that some CSI present inconsistent spectral profiles of reference s...

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.

Analysis of protein glycation in human fingernail clippings with near-infrared (NIR) spectroscopy as an alternative technique for the diagnosis of diabetes mellitus.

PubMed

Monteyne, Tinne; Coopman, Renaat; Kishabongo, Antoine S; Himpe, Jonas; Lapauw, Bruno; Shadid, Samyah; Van Aken, Elisabeth H; Berenson, Darja; Speeckaert, Marijn M; De Beer, Thomas; Delanghe, Joris R

2018-05-11

Glycated keratin allows the monitoring of average tissue glucose exposure over previous weeks. In the present study, we wanted to explore if near-infrared (NIR) spectroscopy could be used as a non-invasive diagnostic tool for assessing glycation in diabetes mellitus. A total of 52 patients with diabetes mellitus and 107 healthy subjects were enrolled in this study. A limited number (n=21) of nails of healthy subjects were glycated in vitro with 0.278 mol/L, 0.556 mol/L and 0.833 mol/L glucose solution to study the effect of glucose on the nail spectrum. Consequently, the nail clippings of the patients were analyzed using a Thermo Fisher Antaris II Near-IR Analyzer Spectrometer and near infrared (NIR) chemical imaging. Spectral classification (patients with diabetes mellitus vs. healthy subjects) was performed using partial least square discriminant analysis (PLS-DA). In vitro glycation resulted in peak sharpening between 4300 and 4400 cm-1 and spectral variations at 5270 cm-1 and between 6600 and 7500 cm-1. Similar regions encountered spectral deviations during analysis of the patients' nails. Optimization of the spectral collection parameters was necessary in order to distinguish a large dataset. Spectra had to be collected at 16 cm-1, 128 scans, region 4000-7500 cm-1. Using standard normal variate, Savitsky-Golay smoothing (7 points) and first derivative preprocessing allowed for the prediction of the test set with 100% correct assignments utilizing a PLS-DA model. Analysis of protein glycation in human fingernail clippings with NIR spectroscopy could be an alternative affordable technique for the diagnosis of diabetes mellitus.

Novel Spectral Representations and Sparsity-Driven Algorithms for Shape Modeling and Analysis

NASA Astrophysics Data System (ADS)

Zhong, Ming

In this dissertation, we focus on extending classical spectral shape analysis by incorporating spectral graph wavelets and sparsity-seeking algorithms. Defined with the graph Laplacian eigenbasis, the spectral graph wavelets are localized both in the vertex domain and graph spectral domain, and thus are very effective in describing local geometry. With a rich dictionary of elementary vectors and forcing certain sparsity constraints, a real life signal can often be well approximated by a very sparse coefficient representation. The many successful applications of sparse signal representation in computer vision and image processing inspire us to explore the idea of employing sparse modeling techniques with dictionary of spectral basis to solve various shape modeling problems. Conventional spectral mesh compression uses the eigenfunctions of mesh Laplacian as shape bases, which are highly inefficient in representing local geometry. To ameliorate, we advocate an innovative approach to 3D mesh compression using spectral graph wavelets as dictionary to encode mesh geometry. The spectral graph wavelets are locally defined at individual vertices and can better capture local shape information than Laplacian eigenbasis. The multi-scale SGWs form a redundant dictionary as shape basis, so we formulate the compression of 3D shape as a sparse approximation problem that can be readily handled by greedy pursuit algorithms. Surface inpainting refers to the completion or recovery of missing shape geometry based on the shape information that is currently available. We devise a new surface inpainting algorithm founded upon the theory and techniques of sparse signal recovery. Instead of estimating the missing geometry directly, our novel method is to find this low-dimensional representation which describes the entire original shape. More specifically, we find that, for many shapes, the vertex coordinate function can be well approximated by a very sparse coefficient representation with respect to the dictionary comprising its Laplacian eigenbasis, and it is then possible to recover this sparse representation from partial measurements of the original shape. Taking advantage of the sparsity cue, we advocate a novel variational approach for surface inpainting, integrating data fidelity constraints on the shape domain with coefficient sparsity constraints on the transformed domain. Because of the powerful properties of Laplacian eigenbasis, the inpainting results of our method tend to be globally coherent with the remaining shape. Informative and discriminative feature descriptors are vital in qualitative and quantitative shape analysis for a large variety of graphics applications. We advocate novel strategies to define generalized, user-specified features on shapes. Our new region descriptors are primarily built upon the coefficients of spectral graph wavelets that are both multi-scale and multi-level in nature, consisting of both local and global information. Based on our novel spectral feature descriptor, we developed a user-specified feature detection framework and a tensor-based shape matching algorithm. Through various experiments, we demonstrate the competitive performance of our proposed methods and the great potential of spectral basis and sparsity-driven methods for shape modeling.

Penalized discriminant analysis for the detection of wild-grown and cultivated Ganoderma lucidum using Fourier transform infrared spectroscopy.

PubMed

Zhu, Ying; Tan, Tuck Lee

2016-04-15

An effective and simple analytical method using Fourier transform infrared (FTIR) spectroscopy to distinguish wild-grown high-quality Ganoderma lucidum (G. lucidum) from cultivated one is of essential importance for its quality assurance and medicinal value estimation. Commonly used chemical and analytical methods using full spectrum are not so effective for the detection and interpretation due to the complex system of the herbal medicine. In this study, two penalized discriminant analysis models, penalized linear discriminant analysis (PLDA) and elastic net (Elnet),using FTIR spectroscopy have been explored for the purpose of discrimination and interpretation. The classification performances of the two penalized models have been compared with two widely used multivariate methods, principal component discriminant analysis (PCDA) and partial least squares discriminant analysis (PLSDA). The Elnet model involving a combination of L1 and L2 norm penalties enabled an automatic selection of a small number of informative spectral absorption bands and gave an excellent classification accuracy of 99% for discrimination between spectra of wild-grown and cultivated G. lucidum. Its classification performance was superior to that of the PLDA model in a pure L1 setting and outperformed the PCDA and PLSDA models using full wavelength. The well-performed selection of informative spectral features leads to substantial reduction in model complexity and improvement of classification accuracy, and it is particularly helpful for the quantitative interpretations of the major chemical constituents of G. lucidum regarding its anti-cancer effects. Copyright © 2016 Elsevier B.V. All rights reserved.

Blind source separation of ex-vivo aorta tissue multispectral images

PubMed Central

Galeano, July; Perez, Sandra; Montoya, Yonatan; Botina, Deivid; Garzón, Johnson

2015-01-01

Blind Source Separation methods (BSS) aim for the decomposition of a given signal in its main components or source signals. Those techniques have been widely used in the literature for the analysis of biomedical images, in order to extract the main components of an organ or tissue under study. The analysis of skin images for the extraction of melanin and hemoglobin is an example of the use of BSS. This paper presents a proof of concept of the use of source separation of ex-vivo aorta tissue multispectral Images. The images are acquired with an interference filter-based imaging system. The images are processed by means of two algorithms: Independent Components analysis and Non-negative Matrix Factorization. In both cases, it is possible to obtain maps that quantify the concentration of the main chromophores present in aortic tissue. Also, the algorithms allow for spectral absorbance of the main tissue components. Those spectral signatures were compared against the theoretical ones by using correlation coefficients. Those coefficients report values close to 0.9, which is a good estimator of the method’s performance. Also, correlation coefficients lead to the identification of the concentration maps according to the evaluated chromophore. The results suggest that Multi/hyper-spectral systems together with image processing techniques is a potential tool for the analysis of cardiovascular tissue. PMID:26137366

Performance comparison of single and dual-excitation-wavelength resonance-Raman explosives detectors

NASA Astrophysics Data System (ADS)

Yellampalle, Balakishore; Martin, Robert; Witt, Kenneth; McCormick, William; Wu, Hai-Shan; Sluch, Mikhail; Ice, Robert; Lemoff, Brian

2017-05-01

Deep-ultraviolet Raman spectroscopy is a very useful approach for standoff detection of explosive traces. Using two simultaneous excitation wavelengths improves the specificity and sensitivity to standoff explosive detection. The High Technology Foundation developed a highly compact prototype of resonance Raman explosives detector. In this work, we discuss the relative performance of a dual-excitation sensor compared to a single-excitation sensor. We present trade space analysis comparing three representative Raman systems with similar size, weight, and power. The analysis takes into account, cost, spectral resolution, detection/identification time and the overall system benefit.

Using HPLC-Mass Spectrometry to Teach Proteomics Concepts with Problem-Based Techniques

ERIC Educational Resources Information Center

Short, Michael; Short, Anne; Vankempen, Rachel; Seymour, Michael; Burnatowska-Hledin, Maria

2010-01-01

Practical instruction of proteomics concepts was provided using high-performance liquid chromatography coupled with a mass selective detection system (HPLC-MS) for the analysis of simulated protein digests. The samples were prepared from selected dipeptides in order to facilitate the mass spectral identification. As part of the prelaboratory…

Neutron spectral measurements in the upper atmosphere

NASA Technical Reports Server (NTRS)

Zobel, W.; Love, T. A.; Delorenzo, J. T.; Mcnew, C. O.

1972-01-01

An experiment to measure neutrons in the upper atmosphere was performed on a balloon flight from Palestine, Texas, at an altitude of about 32 km. The experimental arrangement is discussed briefly, and results of a preliminary analysis of the data for neutrons in the energy range 3 to 30 MeV are given.

Guided filter and principal component analysis hybrid method for hyperspectral pansharpening

NASA Astrophysics Data System (ADS)

Qu, Jiahui; Li, Yunsong; Dong, Wenqian

2018-01-01

Hyperspectral (HS) pansharpening aims to generate a fused HS image with high spectral and spatial resolution through integrating an HS image with a panchromatic (PAN) image. A guided filter (GF) and principal component analysis (PCA) hybrid HS pansharpening method is proposed. First, the HS image is interpolated and the PCA transformation is performed on the interpolated HS image. The first principal component (PC1) channel concentrates on the spatial information of the HS image. Different from the traditional PCA method, the proposed method sharpens the PAN image and utilizes the GF to obtain the spatial information difference between the HS image and the enhanced PAN image. Then, in order to reduce spectral and spatial distortion, an appropriate tradeoff parameter is defined and the spatial information difference is injected into the PC1 channel through multiplying by this tradeoff parameter. Once the new PC1 channel is obtained, the fused image is finally generated by the inverse PCA transformation. Experiments performed on both synthetic and real datasets show that the proposed method outperforms other several state-of-the-art HS pansharpening methods in both subjective and objective evaluations.

Traffic contribution to air pollution in urban street canyons: Integrated application of the OSPM, moss biomonitoring and spectral analysis

NASA Astrophysics Data System (ADS)

Lazić, Lazar; Urošević, Mira Aničić; Mijić, Zoran; Vuković, Gordana; Ilić, Luka

2016-09-01

To investigate the air pollutant distribution within the ambient of urban street canyon, Operational Street Pollution Model (OSPM) was used to predict hourly content of NOX, NO, NO2, O3, CO, BNZ and PM10. The study was performed in five street canyons in Belgrade (Serbia) during 10-week summer period. The model receptors were located on each side of street canyons at 4 m, 8 m and 16 m height. To monitor airborne trace element content, the moss bag biomonitors were simultaneously exposed with the model receptors at two heights-4 m and 16 m. The results of both methods, modelling and biomonitoring, showed significantly decreasing trend of the air pollutants with height. The results indirectly demonstrate that biomonitoring, i.e., moss bag technique could be a valuable tool to verify model performance. In addition, spectral analysis was applied to investigate weekly variation of the daily background and modelled data set. Typical periodicities and weekend effect, caused by anthropogenic influences, have been identified.

Robust vortex lines, vortex rings, and hopfions in three-dimensional Bose-Einstein condensates

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

Bisset, R. N.; Wang, Wenlong; Ticknor, Christopher

Performing a systematic Bogoliubov–de Gennes spectral analysis, we illustrate that stationary vortex lines, vortex rings, and more exotic states, such as hopfions, are robust in three-dimensional atomic Bose-Einstein condensates, for large parameter intervals. Importantly, we find that the hopfion can be stabilized in a simple parabolic trap, without the need for trap rotation or inhomogeneous interactions. We supplement our spectral analysis by studying the dynamics of such stationary states; we find them to be robust against significant perturbations of the initial state. In the unstable regimes, we not only identify the unstable mode, such as a quadrupolar or hexapolar mode,more » but we also observe the corresponding instability dynamics. Moreover, deep in the Thomas-Fermi regime, we investigate the particlelike behavior of vortex rings and hopfions.« less

Robust vortex lines, vortex rings, and hopfions in three-dimensional Bose-Einstein condensates

DOE PAGES

Bisset, R. N.; Wang, Wenlong; Ticknor, Christopher; ...

2015-12-07

Performing a systematic Bogoliubov–de Gennes spectral analysis, we illustrate that stationary vortex lines, vortex rings, and more exotic states, such as hopfions, are robust in three-dimensional atomic Bose-Einstein condensates, for large parameter intervals. Importantly, we find that the hopfion can be stabilized in a simple parabolic trap, without the need for trap rotation or inhomogeneous interactions. We supplement our spectral analysis by studying the dynamics of such stationary states; we find them to be robust against significant perturbations of the initial state. In the unstable regimes, we not only identify the unstable mode, such as a quadrupolar or hexapolar mode,more » but we also observe the corresponding instability dynamics. Moreover, deep in the Thomas-Fermi regime, we investigate the particlelike behavior of vortex rings and hopfions.« less

On-chip wavelength multiplexed detection of cancer DNA biomarkers in blood

PubMed Central

Cai, H.; Stott, M. A.; Ozcelik, D.; Parks, J. W.; Hawkins, A. R.; Schmidt, H.

2016-01-01

We have developed an optofluidic analysis system that processes biomolecular samples starting from whole blood and then analyzes and identifies multiple targets on a silicon-based molecular detection platform. We demonstrate blood filtration, sample extraction, target enrichment, and fluorescent labeling using programmable microfluidic circuits. We detect and identify multiple targets using a spectral multiplexing technique based on wavelength-dependent multi-spot excitation on an antiresonant reflecting optical waveguide chip. Specifically, we extract two types of melanoma biomarkers, mutated cell-free nucleic acids —BRAFV600E and NRAS, from whole blood. We detect and identify these two targets simultaneously using the spectral multiplexing approach with up to a 96% success rate. These results point the way toward a full front-to-back chip-based optofluidic compact system for high-performance analysis of complex biological samples. PMID:28058082

Psychoacoustic and cognitive aspects of auditory roughness: definitions, models, and applications

NASA Astrophysics Data System (ADS)

Vassilakis, Pantelis N.; Kendall, Roger A.

2010-02-01

The term "auditory roughness" was first introduced in the 19th century to describe the buzzing, rattling auditory sensation accompanying narrow harmonic intervals (i.e. two tones with frequency difference in the range of ~15-150Hz, presented simultaneously). A broader definition and an overview of the psychoacoustic correlates of the auditory roughness sensation, also referred to as sensory dissonance, is followed by an examination of efforts to quantify it over the past one hundred and fifty years and leads to the introduction of a new roughness calculation model and an application that automates spectral and roughness analysis of sound signals. Implementation of spectral and roughness analysis is briefly discussed in the context of two pilot perceptual experiments, designed to assess the relationship among cultural background, music performance practice, and aesthetic attitudes towards the auditory roughness sensation.

Spectral-timing analysis of the low-B magnetar SWIFT J1822.3-1606: testing our understanding of the magnetar behavior

NASA Astrophysics Data System (ADS)

Perna, Rosalba

2014-09-01

AXPs and SGRs are young neutron stars (NSs) characterized by high X-ray quiescent luminosities, outbursts, and sporadic giant flares (the SGRs). They are believed to be powered by ultra-strong B fields. However, the observation of outbursts from 'low-B' NSs has been a long-standing puzzle. Theoretical work by our group has shown that a) outbursts from a 'low-B' NS can be produced if the NS has a very strong internal toroidal field; b) a strong internal toroidal field can be revealed by spectral and timing analysis of the NS pulse profile. Here we propose to perform a detailed modeling of the spectra and pulse profile of the low-B magnetar SWIFT J1822.3-1606 with the aim of inferring its magnetic field topology and viewing geometry.

Spectral reflectance of surface soils - A statistical analysis

NASA Technical Reports Server (NTRS)

Crouse, K. R.; Henninger, D. L.; Thompson, D. R.

1983-01-01

The relationship of the physical and chemical properties of soils to their spectral reflectance as measured at six wavebands of Thematic Mapper (TM) aboard NASA's Landsat-4 satellite was examined. The results of performing regressions of over 20 soil properties on the six TM bands indicated that organic matter, water, clay, cation exchange capacity, and calcium were the properties most readily predicted from TM data. The middle infrared bands, bands 5 and 7, were the best bands for predicting soil properties, and the near infrared band, band 4, was nearly as good. Clustering 234 soil samples on the TM bands and characterizing the clusters on the basis of soil properties revealed several clear relationships between properties and reflectance. Discriminant analysis found organic matter, fine sand, base saturation, sand, extractable acidity, and water to be significant in discriminating among clusters.

Spectral identification of minerals using imaging spectrometry data: Evaluating the effects of signal to noise and spectral resolution using the tricorder algorithm

NASA Technical Reports Server (NTRS)

Swayze, Gregg A.; Clark, Roger N.

1995-01-01

The rapid development of sophisticated imaging spectrometers and resulting flood of imaging spectrometry data has prompted a rapid parallel development of spectral-information extraction technology. Even though these extraction techniques have evolved along different lines (band-shape fitting, endmember unmixing, near-infrared analysis, neural-network fitting, and expert systems to name a few), all are limited by the spectrometer's signal to noise (S/N) and spectral resolution in producing useful information. This study grew from a need to quantitatively determine what effects these parameters have on our ability to differentiate between mineral absorption features using a band-shape fitting algorithm. We chose to evaluate the AVIRIS, HYDICE, MIVIS, GERIS, VIMS, NIMS, and ASTER instruments because they collect data over wide S/N and spectral-resolution ranges. The study evaluates the performance of the Tricorder algorithm, in differentiating between mineral spectra in the 0.4-2.5 micrometer spectral region. The strength of the Tricorder algorithm is in its ability to produce an easily understood comparison of band shape that can concentrate on small relevant portions of the spectra, giving it an advantage over most unmixing schemes, and in that it need not spend large amounts of time reoptimizing each time a new mineral component is added to its reference library, as is the case with neural-network schemes. We believe the flexibility of the Tricorder algorithm is unparalleled among spectral-extraction techniques and that the results from this study, although dealing with minerals, will have direct applications to spectral identification in other disciplines.

Retrieval of high-spectral-resolution lidar for atmospheric aerosol optical properties profiling

NASA Astrophysics Data System (ADS)

Liu, Dong; Luo, Jing; Yang, Yongying; Cheng, Zhongtao; Zhang, Yupeng; Zhou, Yudi; Duan, Lulin; Su, Lin

2015-10-01

High-spectral-resolution lidars (HSRLs) are increasingly being developed for atmospheric aerosol remote sensing applications due to the straightforward and independent retrieval of aerosol optical properties without reliance on assumptions about lidar ratio. In HSRL technique, spectral discrimination between scattering from molecules and aerosol particles is one of the most critical processes, which needs to be accomplished by means of a narrowband spectroscopic filter. To ensure a high retrieval accuracy of an HSRL system, the high-quality design of its spectral discrimination filter should be made. This paper reviews the available algorithms that were proposed for HSRLs and makes a general accuracy analysis of the HSRL technique focused on the spectral discrimination, in order to provide heuristic guidelines for the reasonable design of the spectral discrimination filter. We introduce a theoretical model for retrieval error evaluation of an HSRL instrument with general three-channel configuration. Monte Carlo (MC) simulations are performed to validate the correctness of the theoretical model. Results from both the model and MC simulations agree very well, and they illustrate one important, although not well realized fact: a large molecular transmittance and a large spectral discrimination ratio (SDR, i.e., ratio of the molecular transmittance to the aerosol transmittance) are beneficial t o promote the retrieval accuracy. The application of the conclusions obtained in this paper in the designing of a new type of spectroscopic filter, that is, the field-widened Michelson interferometer, is illustrated in detail. These works are with certain universality and expected to be useful guidelines for HSRL community, especially when choosing or designing the spectral discrimination filter.

Improvements in Virtual Sensors: Using Spatial Information to Estimate Remote Sensing Spectra

NASA Technical Reports Server (NTRS)

Oza, Nikunj C.; Srivastava, Ashok N.; Stroeve, Julienne

2005-01-01

Various instruments are used to create images of the Earth and other objects in the universe in a diverse set of wavelength bands with the aim of understanding natural phenomena. Sometimes these instruments are built in a phased approach, with additional measurement capabilities added in later phases. In other cases, technology may mature to the point that the instrument offers new measurement capabilities that were not planned in the original design of the instrument. In still other cases, high resolution spectral measurements may be too costly to perform on a large sample and therefore lower resolution spectral instruments are used to take the majority of measurements. Many applied science questions that are relevant to the earth science remote sensing community require analysis of enormous amounts of data that were generated by instruments with disparate measurement capabilities. In past work [1], we addressed this problem using Virtual Sensors: a method that uses models trained on spectrally rich (high spectral resolution) data to "fill in" unmeasured spectral channels in spectrally poor (low spectral resolution) data. We demonstrated this method by using models trained on the high spectral resolution Terra MODIS instrument to estimate what the equivalent of the MODIS 1.6 micron channel would be for the NOAA AVHRR2 instrument. The scientific motivation for the simulation of the 1.6 micron channel is to improve the ability of the AVHRR2 sensor to detect clouds over snow and ice. This work contains preliminary experiments demonstrating that the use of spatial information can improve our ability to estimate these spectra.

MetaboID: a graphical user interface package for assignment of 1H NMR spectra of bodyfluids and tissues.

PubMed

MacKinnon, Neil; Somashekar, Bagganahalli S; Tripathi, Pratima; Ge, Wencheng; Rajendiran, Thekkelnaycke M; Chinnaiyan, Arul M; Ramamoorthy, Ayyalusamy

2013-01-01

Nuclear magnetic resonance based measurements of small molecule mixtures continues to be confronted with the challenge of spectral assignment. While multi-dimensional experiments are capable of addressing this challenge, the imposed time constraint becomes prohibitive, particularly with the large sample sets commonly encountered in metabolomic studies. Thus, one-dimensional spectral assignment is routinely performed, guided by two-dimensional experiments on a selected sample subset; however, a publicly available graphical interface for aiding in this process is currently unavailable. We have collected spectral information for 360 unique compounds from publicly available databases including chemical shift lists and authentic full resolution spectra, supplemented with spectral information for 25 compounds collected in-house at a proton NMR frequency of 900 MHz. This library serves as the basis for MetaboID, a Matlab-based user interface designed to aid in the one-dimensional spectral assignment process. The tools of MetaboID were built to guide resonance assignment in order of increasing confidence, starting from cursory compound searches based on chemical shift positions to analysis of authentic spike experiments. Together, these tools streamline the often repetitive task of spectral assignment. The overarching goal of the integrated toolbox of MetaboID is to centralize the one dimensional spectral assignment process, from providing access to large chemical shift libraries to providing a straightforward, intuitive means of spectral comparison. Such a toolbox is expected to be attractive to both experienced and new metabolomic researchers as well as general complex mixture analysts. Copyright © 2012 Elsevier Inc. All rights reserved.

Beyond the double banana: improved recognition of temporal lobe seizures in long-term EEG.

PubMed

Rosenzweig, Ivana; Fogarasi, András; Johnsen, Birger; Alving, Jørgen; Fabricius, Martin Ejler; Scherg, Michael; Neufeld, Miri Y; Pressler, Ronit; Kjaer, Troels W; van Emde Boas, Walter; Beniczky, Sándor

2014-02-01

To investigate whether extending the 10-20 array with 6 electrodes in the inferior temporal chain and constructing computed montages increases the diagnostic value of ictal EEG activity originating in the temporal lobe. In addition, the accuracy of computer-assisted spectral source analysis was investigated. Forty EEG samples were reviewed by 7 EEG experts in various montages (longitudinal and transversal bipolar, common average, source derivation, source montage, current source density, and reference-free montages) using 2 electrode arrays (10-20 and the extended one). Spectral source analysis used source montage to calculate density spectral array, defining the earliest oscillatory onset. From this, phase maps were calculated for localization. The reference standard was the decision of the multidisciplinary epilepsy surgery team on the seizure onset zone. Clinical performance was compared with the double banana (longitudinal bipolar montage, 10-20 array). Adding the inferior temporal electrode chain, computed montages (reference free, common average, and source derivation), and voltage maps significantly increased the sensitivity. Phase maps had the highest sensitivity and identified ictal activity at earlier time-point than visual inspection. There was no significant difference concerning specificity. The findings advocate for the use of these digital EEG technology-derived analysis methods in clinical practice.

The physical origin of the X-ray emission from SN 1987A

NASA Astrophysics Data System (ADS)

Miceli, M.; Orlando, S.; Petruk, O.

2017-10-01

We revisit the spectral analysis of the set of archive XMM-Newton observations of SN 1987A through our 3-D hydrodynamic model describing the whole evolution from the onset of the supernova to the full remnant development. For the first time the spectral analysis accounts for the single observations and for the evolution of the system self-consistently. We adopt a forward modeling approach which allows us to directly synthesize, from the model, X-ray spectra and images in different energy bands. We fold the synthetic observables through the XMM-Newton instrumental response and directly compare models and actual data. We find that our simulation provides an excellent fit to the data, by reproducing simultaneously X-ray fluxes, spectral features, and morphology of SN 1987A at all evolutionary stages. Our analysis enables us to obtain a deep insight on the physical origin of the observed multi-thermal emission, by revealing the contribution of shocked surrounding medium, dense clumps of the circumstellar ring, and ejecta to the total emission. We finally provide predictions for future observations (to be performed with XMM-Newton in the next future and with the forthcoming Athena X-ray telescope in approximately 10 years), showing the growing contribution of the ejecta X-ray emission.

Hyperspectral analysis of soil organic matter in coal mining regions using wavelets, correlations, and partial least squares regression.

PubMed

Lin, Lixin; Wang, Yunjia; Teng, Jiyao; Wang, Xuchen

2016-02-01

Hyperspectral estimation of soil organic matter (SOM) in coal mining regions is an important tool for enhancing fertilization in soil restoration programs. The correlation--partial least squares regression (PLSR) method effectively solves the information loss problem of correlation--multiple linear stepwise regression, but results of the correlation analysis must be optimized to improve precision. This study considers the relationship between spectral reflectance and SOM based on spectral reflectance curves of soil samples collected from coal mining regions. Based on the major absorption troughs in the 400-1006 nm spectral range, PLSR analysis was performed using 289 independent bands of the second derivative (SDR) with three levels and measured SOM values. A wavelet-correlation-PLSR (W-C-PLSR) model was then constructed. By amplifying useful information that was previously obscured by noise, the W-C-PLSR model was optimal for estimating SOM content, with smaller prediction errors in both calibration (R(2) = 0.970, root mean square error (RMSEC) = 3.10, and mean relative error (MREC) = 8.75) and validation (RMSEV = 5.85 and MREV = 14.32) analyses, as compared with other models. Results indicate that W-C-PLSR has great potential to estimate SOM in coal mining regions.

Detection of artificially ripened mango using spectrometric analysis

NASA Astrophysics Data System (ADS)

Mithun, B. S.; Mondal, Milton; Vishwakarma, Harsh; Shinde, Sujit; Kimbahune, Sanjay

2017-05-01

Hyperspectral sensing has been proven to be useful to determine the quality of food in general. It has also been used to distinguish naturally and artificially ripened mangoes by analyzing the spectral signature. However the focus has been on improving the accuracy of classification after performing dimensionality reduction, optimum feature selection and using suitable learning algorithm on the complete visible and NIR spectrum range data, namely 350nm to 1050nm. In this paper we focus on, (i) the use of low wavelength resolution and low cost multispectral sensor to reliably identify artificially ripened mango by selectively using the spectral information so that classification accuracy is not hampered at the cost of low resolution spectral data and (ii) use of visible spectrum i.e. 390nm to 700 nm data to accurately discriminate artificially ripened mangoes. Our results show that on a low resolution spectral data, the use of logistic regression produces an accuracy of 98.83% and outperforms other methods like classification tree, random forest significantly. And this is achieved by analyzing only 36 spectral reflectance data points instead of the complete 216 data points available in visual and NIR range. Another interesting experimental observation is that we are able to achieve more than 98% classification accuracy by selecting only 15 irradiance values in the visible spectrum. Even the number of data needs to be collected using hyper-spectral or multi-spectral sensor can be reduced by a factor of 24 for classification with high degree of confidence

Contrast enhancement of subcutaneous blood vessel images by means of visible and near-infrared hyper-spectral imaging

NASA Astrophysics Data System (ADS)

Katrašnik, Jaka; Bürmen, Miran; Pernuš, Franjo; Likar, Boštjan

2009-02-01

Visualization of subcutaneous veins is very difficult with the naked eye, but important for diagnosis of medical conditions and different medical procedures such as catheter insertion and blood withdrawal. Moreover, recent studies showed that the images of subcutaneous veins could be used for biometric identification. The majority of methods used for enhancing the contrast between the subcutaneous veins and surrounding tissue are based on simple imaging systems utilizing CMOS or CCD cameras with LED illumination capable of acquiring images from the near infrared spectral region, usually near 900 nm. However, such simplified imaging methods cannot exploit the full potential of the spectral information. In this paper, a new highly versatile method for enhancing the contrast of subcutaneous veins based on state-of-the-art high-resolution hyper-spectral imaging system utilizing the spectral region from 550 to 1700 nm is presented. First, a detailed analysis of the contrast between the subcutaneous veins and the surrounding tissue as a function of wavelength, for several different positions on the human arm, was performed in order to extract the spectral regions with the highest contrast. The highest contrast images were acquired at 1100 nm, however, combining the individual images from the extracted spectral regions by the proposed contrast enhancement method resulted in a single image with up to ten-fold better contrast. Therefore, the proposed method has proved to be a useful tool for visualization of subcutaneous veins.

Time-resolved multispectral imaging of combustion reactions

NASA Astrophysics Data System (ADS)

Huot, Alexandrine; Gagnon, Marc-André; Jahjah, Karl-Alexandre; Tremblay, Pierre; Savary, Simon; Farley, Vincent; Lagueux, Philippe; Guyot, Éric; Chamberland, Martin; Marcotte, Frédérick

2015-10-01

Thermal infrared imaging is a field of science that evolves rapidly. Scientists have used for years the simplest tool: thermal broadband cameras. These allow to perform target characterization in both the longwave (LWIR) and midwave (MWIR) infrared spectral range. Infrared thermal imaging is used for a wide range of applications, especially in the combustion domain. For example, it can be used to follow combustion reactions, in order to characterize the injection and the ignition in a combustion chamber or even to observe gases produced by a flare or smokestack. Most combustion gases, such as carbon dioxide (CO2), selectively absorb/emit infrared radiation at discrete energies, i.e. over a very narrow spectral range. Therefore, temperatures derived from broadband imaging are not reliable without prior knowledge of spectral emissivity. This information is not directly available from broadband images. However, spectral information is available using spectral filters. In this work, combustion analysis was carried out using a Telops MS-IR MW camera, which allows multispectral imaging at a high frame rate. A motorized filter wheel allowing synchronized acquisitions on eight (8) different channels was used to provide time-resolved multispectral imaging of combustion products of a candle in which black powder has been burnt to create a burst. It was then possible to estimate the temperature by modeling spectral profiles derived from information obtained with the different spectral filters. Comparison with temperatures obtained using conventional broadband imaging illustrates the benefits of time-resolved multispectral imaging for the characterization of combustion processes.

Time-resolved multispectral imaging of combustion reaction

NASA Astrophysics Data System (ADS)

Huot, Alexandrine; Gagnon, Marc-André; Jahjah, Karl-Alexandre; Tremblay, Pierre; Savary, Simon; Farley, Vincent; Lagueux, Philippe; Guyot, Éric; Chamberland, Martin; Marcotte, Fréderick

2015-05-01

Thermal infrared imaging is a field of science that evolves rapidly. Scientists have used for years the simplest tool: thermal broadband cameras. This allows to perform target characterization in both the longwave (LWIR) and midwave (MWIR) infrared spectral range. Infrared thermal imaging is used for a wide range of applications, especially in the combustion domain. For example, it can be used to follow combustion reactions, in order to characterize the injection and the ignition in a combustion chamber or even to observe gases produced by a flare or smokestack. Most combustion gases such as carbon dioxide (CO2) selectively absorb/emit infrared radiation at discrete energies, i.e. over a very narrow spectral range. Therefore, temperatures derived from broadband imaging are not reliable without prior knowledge about spectral emissivity. This information is not directly available from broadband images. However, spectral information is available using spectral filters. In this work, combustion analysis was carried out using Telops MS-IR MW camera which allows multispectral imaging at a high frame rate. A motorized filter wheel allowing synchronized acquisitions on eight (8) different channels was used to provide time-resolved multispectral imaging of combustion products of a candle in which black powder has been burnt to create a burst. It was then possible to estimate the temperature by modeling spectral profile derived from information obtained with the different spectral filters. Comparison with temperatures obtained using conventional broadband imaging illustrates the benefits of time-resolved multispectral imaging for the characterization of combustion processes.

Study of sensor spectral responses and data processing algorithms and architectures for onboard feature identification

NASA Technical Reports Server (NTRS)

Huck, F. O.; Davis, R. E.; Fales, C. L.; Aherron, R. M.

1982-01-01

A computational model of the deterministic and stochastic processes involved in remote sensing is used to study spectral feature identification techniques for real-time onboard processing of data acquired with advanced earth-resources sensors. Preliminary results indicate that: Narrow spectral responses are advantageous; signal normalization improves mean-square distance (MSD) classification accuracy but tends to degrade maximum-likelihood (MLH) classification accuracy; and MSD classification of normalized signals performs better than the computationally more complex MLH classification when imaging conditions change appreciably from those conditions during which reference data were acquired. The results also indicate that autonomous categorization of TM signals into vegetation, bare land, water, snow and clouds can be accomplished with adequate reliability for many applications over a reasonably wide range of imaging conditions. However, further analysis is required to develop computationally efficient boundary approximation algorithms for such categorization.

Preliminary Analysis of the Performance of the Landsat 8/OLI Land Surface Reflectance Product

NASA Technical Reports Server (NTRS)

Vermote, Eric; Justice, Chris; Claverie, Martin; Franch, Belen

2016-01-01

The surface reflectance, i.e., satellite derived top of atmosphere (TOA) reflectance corrected for the temporally, spatially and spectrally varying scattering and absorbing effects of atmospheric gases and aerosols, is needed to monitor the land surface reliably. For this reason, the surface reflectance, and not TOA reflectance, is used to generate the greater majority of global land products, for example, from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) sensors. Even if atmospheric effects are minimized by sensor design, atmospheric effects are still challenging to correct. In particular, the strong impact of aerosols in the visible and near infrared spectral range can be difficult to correct, because they can be highly discrete in space and time (e.g., smoke plumes) and because of the complex scattering and absorbing properties of aerosols that vary spectrally and with aerosol size, shape, chemistry and density.

Using digital images to measure and discriminate small particles in cotton

NASA Astrophysics Data System (ADS)

Taylor, Robert A.; Godbey, Luther C.

1991-02-01

Inages from conventional video systems are being digitized in coraputers for the analysis of small trash particles in cotton. The method has been developed to automate particle counting and area measurements for bales of cotton prepared for market. Because the video output is linearly proportional to the amount of light reflected the best spectral band for optimum particle discrimination should be centered at the wavelength of maximum difference between particles and their surroundings. However due to the spectral distribution of the illumination energy and the detector sensitivity peak image performance bands were altered. Reflectance from seven mechanically cleaned cotton lint samples and trash removed were examined for spectral contrast in the wavelength range of camera sensitivity. Pixel intensity histograms from the video systent are reported for simulated trashmeter area reference samples (painted dots on panels) and for cotton containing trash to demonstrate the particle discrimination mechanism. 2.

Novel full‐spectral flow cytometry with multiple spectrally‐adjacent fluorescent proteins and fluorochromes and visualization of in vivo cellular movement

PubMed Central

Futamura, Koji; Sekino, Masashi; Hata, Akihiro; Ikebuchi, Ryoyo; Nakanishi, Yasutaka; Egawa, Gyohei; Kabashima, Kenji; Watanabe, Takeshi; Furuki, Motohiro

2015-01-01

Abstract Flow cytometric analysis with multicolor fluoroprobes is an essential method for detecting biological signatures of cells. Here, we present a new full‐spectral flow cytometer (spectral‐FCM). Unlike conventional flow cytometer, this spectral‐FCM acquires the emitted fluorescence for all probes across the full‐spectrum from each cell with 32 channels sequential PMT unit after dispersion with prism, and extracts the signals of each fluoroprobe based on the spectral shape of each fluoroprobe using unique algorithm in high speed, high sensitive, accurate, automatic and real‐time. The spectral‐FCM detects the continuous changes in emission spectra from green to red of the photoconvertible protein, KikGR with high‐spectral resolution and separates spectrally‐adjacent fluoroprobes, such as FITC (Emission peak (Em) 519 nm) and EGFP (Em 507 nm). Moreover, the spectral‐FCM can measure and subtract autofluorescence of each cell providing increased signal‐to‐noise ratios and improved resolution of dim samples, which leads to a transformative technology for investigation of single cell state and function. These advances make it possible to perform 11‐color fluorescence analysis to visualize movement of multilinage immune cells by using KikGR‐expressing mice. Thus, the novel spectral flow cytometry improves the combinational use of spectrally‐adjacent various FPs and multicolor fluorochromes in metabolically active cell for the investigation of not only the immune system but also other research and clinical fields of use. © 2015 The Authors. Cytometry Part A Published by Wiley Periodicals, Inc. on behalf of ISAC PMID:26217952

Multispectral imaging of absorption and scattering properties of in vivo exposed rat brain using a digital red-green-blue camera.

PubMed

Yoshida, Keiichiro; Nishidate, Izumi; Ishizuka, Tomohiro; Kawauchi, Satoko; Sato, Shunichi; Sato, Manabu

2015-05-01

In order to estimate multispectral images of the absorption and scattering properties in the cerebral cortex of in vivo rat brain, we investigated spectral reflectance images estimated by the Wiener estimation method using a digital RGB camera. A Monte Carlo simulation-based multiple regression analysis for the corresponding spectral absorbance images at nine wavelengths (500, 520, 540, 560, 570, 580, 600, 730, and 760 nm) was then used to specify the absorption and scattering parameters of brain tissue. In this analysis, the concentrations of oxygenated hemoglobin and that of deoxygenated hemoglobin were estimated as the absorption parameters, whereas the coefficient a and the exponent b of the reduced scattering coefficient spectrum approximated by a power law function were estimated as the scattering parameters. The spectra of absorption and reduced scattering coefficients were reconstructed from the absorption and scattering parameters, and the spectral images of absorption and reduced scattering coefficients were then estimated. In order to confirm the feasibility of this method, we performed in vivo experiments on exposed rat brain. The estimated images of the absorption coefficients were dominated by the spectral characteristics of hemoglobin. The estimated spectral images of the reduced scattering coefficients had a broad scattering spectrum, exhibiting a larger magnitude at shorter wavelengths, corresponding to the typical spectrum of brain tissue published in the literature. The changes in the estimated absorption and scattering parameters during normoxia, hyperoxia, and anoxia indicate the potential applicability of the method by which to evaluate the pathophysiological conditions of in vivo brain due to the loss of tissue viability.

Influence of the spectral distribution of light on the characteristics of photovoltaic panel. Comparison between simulation and experimental

NASA Astrophysics Data System (ADS)

Chadel, Meriem; Bouzaki, Mohammed Moustafa; Chadel, Asma; Petit, Pierre; Sawicki, Jean-Paul; Aillerie, Michel; Benyoucef, Boumediene

2017-02-01

We present and analyze experimental results obtained with a laboratory setup based on a hardware and smart instrumentation for the complete study of performance of PV panels using for illumination an artificial radiation source (Halogen lamps). Associated to an accurate analysis, this global experimental procedure allows the determination of effective performance under standard conditions thanks to a simulation process originally developed under Matlab software environment. The uniformity of the irradiated surface was checked by simulation of the light field. We studied the response of standard commercial photovoltaic panels under enlightenment measured by a spectrometer with different spectra for two sources, halogen lamps and sunlight. Then, we bring a special attention to the influence of the spectral distribution of light on the characteristics of photovoltaic panel, that we have performed as a function of temperature and for different illuminations with dedicated measurements and studies of the open circuit voltage and short-circuit current.

Impact of Positive Emotions Enhancement on Physiological Processes and Psychological Functioning in Military Pilots

DTIC Science & Technology

2009-10-01

8 weeks. The experimental procedure consisted in collecting (i) psychological data (resilience, well-being, anxiety ), (ii) 12h-night urines to assess...was performed during 6 to 8 weeks. The experimental procedure consisted in collecting (i) psychological data (resilience, well-being, anxiety ), (ii...cardio- vascular regulation, the spectral analysis of heart rate variability ( HRV ) analysis is usually proposed as a method to assess vagal tone [7,2,8

Analysis of seismic stability of large-sized tank VST-20000 with software package ANSYS

NASA Astrophysics Data System (ADS)

Tarasenko, A. A.; Chepur, P. V.; Gruchenkova, A. A.

2018-05-01

The work is devoted to the study of seismic stability of vertical steel tank VST-20000 with due consideration of the system response “foundation-tank-liquid”, conducted on the basis of the finite element method, modal analysis and linear spectral theory. The calculations are performed for the tank model with a high degree of detailing of metallic structures: shells, a fixed roof, a bottom, a reinforcing ring.

Hyperspectral Fluorescence and Reflectance Imaging Instrument

NASA Technical Reports Server (NTRS)

Ryan, Robert E.; O'Neal, S. Duane; Lanoue, Mark; Russell, Jeffrey

2008-01-01

The system is a single hyperspectral imaging instrument that has the unique capability to acquire both fluorescence and reflectance high-spatial-resolution data that is inherently spatially and spectrally registered. Potential uses of this instrument include plant stress monitoring, counterfeit document detection, biomedical imaging, forensic imaging, and general materials identification. Until now, reflectance and fluorescence spectral imaging have been performed by separate instruments. Neither a reflectance spectral image nor a fluorescence spectral image alone yields as much information about a target surface as does a combination of the two modalities. Before this system was developed, to benefit from this combination, analysts needed to perform time-consuming post-processing efforts to co-register the reflective and fluorescence information. With this instrument, the inherent spatial and spectral registration of the reflectance and fluorescence images minimizes the need for this post-processing step. The main challenge for this technology is to detect the fluorescence signal in the presence of a much stronger reflectance signal. To meet this challenge, the instrument modulates artificial light sources from ultraviolet through the visible to the near-infrared part of the spectrum; in this way, both the reflective and fluorescence signals can be measured through differencing processes to optimize fluorescence and reflectance spectra as needed. The main functional components of the instrument are a hyperspectral imager, an illumination system, and an image-plane scanner. The hyperspectral imager is a one-dimensional (line) imaging spectrometer that includes a spectrally dispersive element and a two-dimensional focal plane detector array. The spectral range of the current imaging spectrometer is between 400 to 1,000 nm, and the wavelength resolution is approximately 3 nm. The illumination system consists of narrowband blue, ultraviolet, and other discrete wavelength light-emitting-diode (LED) sources and white-light LED sources designed to produce consistently spatially stable light. White LEDs provide illumination for the measurement of reflectance spectra, while narrowband blue and UV LEDs are used to excite fluorescence. Each spectral type of LED can be turned on or off depending on the specific remote-sensing process being performed. Uniformity of illumination is achieved by using an array of LEDs and/or an integrating sphere or other diffusing surface. The image plane scanner uses a fore optic with a field of view large enough to provide an entire scan line on the image plane. It builds up a two-dimensional image in pushbroom fashion as the target is scanned across the image plane either by moving the object or moving the fore optic. For fluorescence detection, spectral filtering of a narrowband light illumination source is sometimes necessary to minimize the interference of the source spectrum wings with the fluorescence signal. Spectral filtering is achieved with optical interference filters and absorption glasses. This dual spectral imaging capability will enable the optimization of reflective, fluorescence, and fused datasets as well as a cost-effective design for multispectral imaging solutions. This system has been used in plant stress detection studies and in currency analysis.

A spectral power analysis of driving behavior changes during the transition from nondistraction to distraction.

PubMed

Wang, Yuan; Bao, Shan; Du, Wenjun; Ye, Zhirui; Sayer, James R

2017-11-17

This article investigated and compared frequency domain and time domain characteristics of drivers' behaviors before and after the start of distracted driving. Data from an existing naturalistic driving study were used. Fast Fourier transform (FFT) was applied for the frequency domain analysis to explore drivers' behavior pattern changes between nondistracted (prestarting of visual-manual task) and distracted (poststarting of visual-manual task) driving periods. Average relative spectral power in a low frequency range (0-0.5 Hz) and the standard deviation in a 10-s time window of vehicle control variables (i.e., lane offset, yaw rate, and acceleration) were calculated and further compared. Sensitivity analyses were also applied to examine the reliability of the time and frequency domain analyses. Results of the mixed model analyses from the time and frequency domain analyses all showed significant degradation in lateral control performance after engaging in visual-manual tasks while driving. Results of the sensitivity analyses suggested that the frequency domain analysis was less sensitive to the frequency bandwidth, whereas the time domain analysis was more sensitive to the time intervals selected for variation calculations. Different time interval selections can result in significantly different standard deviation values, whereas average spectral power analysis on yaw rate in both low and high frequency bandwidths showed consistent results, that higher variation values were observed during distracted driving when compared to nondistracted driving. This study suggests that driver state detection needs to consider the behavior changes during the prestarting periods, instead of only focusing on periods with physical presence of distraction, such as cell phone use. Lateral control measures can be a better indicator of distraction detection than longitudinal controls. In addition, frequency domain analyses proved to be a more robust and consistent method in assessing driving performance compared to time domain analyses.

Preliminary results of the comparative study between EO-1/Hyperion and ALOS/PALSAR

NASA Astrophysics Data System (ADS)

Koizumi, E.; Furuta, R.; Yamamoto, A.

2011-12-01

[Introduction]Hyper-spectral remote sensing images have been used for land-cover classification due to their high spectral resolutions. Synthetic Aperture Radar (SAR) remote sensing data are also useful to probe surface condition because radar image reflects surface geometry, although there are not so many reports about the land-cover detection with combination use of both hyper-spectral data and SAR data. Among SAR sensors, L-band SAR is thought to be useful tool to find physical properties because its comparatively long wave length can through small objects on surface. We are comparing the result of land cover classification and/or physical values from hyper-spectral and L-band SAR data to find the relationship between these two quite different sensors and to confirm the possibility of the combined analysis of hyper-spectral and L-band SAR data, and in this presentation we will report the preliminary result of this study. There are only few sources of both hyper-spectral and L-band SAR data from the space in this time, however, several space organizations plan to launch new satellites on which hyper-spectral or L-band SAR equipments are mounted in next few years. So, the importance of the combined analysis will increase more than ever. [Target Area]We are performing and planning analyses on the following areas in this study. (a)South of Cairo, Nile river area, Egypt, for sand, sandstone, limestone, river, crops. (b)Mount Sakurajima, Japan, for igneous rock and other related geological property. [Methods and Results]EO-1 Hyperion data are analyzed in this study as hyper-spectral data. The Hyperion equipment has 242 channels but some of them include full noise or have no data. We selected channels for analysis by checking each channel, and select about 150 channels (depend on the area). Before analysis, the atmospheric correction of ATCOR-3 was applied for the selected channels. The corrected data were analyzed by unsupervised classification or principal component analysis (PCA). We also did the unsupervised classification with the several components from PCA. According to the analysis results, several classifications can be extracted for each category (vegetation, sand and rocks, and water). One of the interesting results is that there are a few classes for sand as those of other categories, and these classes seem to reflect artificial and natural surface changes that are some result of excavation or scratching. ALOS PALSAR data are analyzed as L-band SAR data. We selected the Dual Polarization data for each target area. The data were converted to backscattered images, and then calculated some image statistic values. The topographic information also calculates with SAR interferometry technique as reference. Comparing the Hyperion classification results with the result of the calculation of statistic values from PALSAR, there are some areas where relativities seem to be confirmed. To confirm the combined analysis between hyper-spectral and L-band SAR data to detect and classify the surface material, further studies are still required. We will continue to investigate more efficient analytic methods and to examine other functions like the adopted channels, the number of class in classification, the kind of statistic information, and so on, to refine the method.

Double Fourier analysis for Emotion Identification in Voiced Speech

NASA Astrophysics Data System (ADS)

Sierra-Sosa, D.; Bastidas, M.; Ortiz P., D.; Quintero, O. L.

2016-04-01

We propose a novel analysis alternative, based on two Fourier Transforms for emotion recognition from speech. Fourier analysis allows for display and synthesizes different signals, in terms of power spectral density distributions. A spectrogram of the voice signal is obtained performing a short time Fourier Transform with Gaussian windows, this spectrogram portraits frequency related features, such as vocal tract resonances and quasi-periodic excitations during voiced sounds. Emotions induce such characteristics in speech, which become apparent in spectrogram time-frequency distributions. Later, the signal time-frequency representation from spectrogram is considered an image, and processed through a 2-dimensional Fourier Transform in order to perform the spatial Fourier analysis from it. Finally features related with emotions in voiced speech are extracted and presented.

[Study of near infrared spectral preprocessing and wavelength selection methods for endometrial cancer tissue].

PubMed

Zhao, Li-Ting; Xiang, Yu-Hong; Dai, Yin-Mei; Zhang, Zhuo-Yong

2010-04-01

Near infrared spectroscopy was applied to measure the tissue slice of endometrial tissues for collecting the spectra. A total of 154 spectra were obtained from 154 samples. The number of normal, hyperplasia, and malignant samples was 36, 60, and 58, respectively. Original near infrared spectra are composed of many variables, for example, interference information including instrument errors and physical effects such as particle size and light scatter. In order to reduce these influences, original spectra data should be performed with different spectral preprocessing methods to compress variables and extract useful information. So the methods of spectral preprocessing and wavelength selection have played an important role in near infrared spectroscopy technique. In the present paper the raw spectra were processed using various preprocessing methods including first derivative, multiplication scatter correction, Savitzky-Golay first derivative algorithm, standard normal variate, smoothing, and moving-window median. Standard deviation was used to select the optimal spectral region of 4 000-6 000 cm(-1). Then principal component analysis was used for classification. Principal component analysis results showed that three types of samples could be discriminated completely and the accuracy almost achieved 100%. This study demonstrated that near infrared spectroscopy technology and chemometrics method could be a fast, efficient, and novel means to diagnose cancer. The proposed methods would be a promising and significant diagnosis technique of early stage cancer.

8-13 Hz fluctuations in rectal pressure are an objective marker of clitorally-induced orgasm in women.

PubMed

van Netten, Jaap J; Georgiadis, Janniko R; Nieuwenburg, Arie; Kortekaas, Rudie

2008-04-01

Orgasm is a subjective experience accompanied by involuntary muscle contractions. We hypothesized that orgasm in women would be distinguishable by frequency analysis of a perineal muscle-derived signal. Rectal pressure, an index of perineal muscle activity, was measured continuously in 23 healthy women during different sexual tasks: receiving clitoral stimulation, imitation of orgasm, and attempt to reach orgasm, in which case the women were asked to report whether orgasm had been reached ("orgasm") or not ("failed orgasm attempt"). We performed spectral analysis on the rectal pressure data and calculated the spectral power in the frequency bands delta (0.5-4 Hz), theta (4-8 Hz), alpha (8-13 Hz), and beta (13-25 Hz). The most significant and most important difference in spectral power between orgasm and both control motor tasks (imitation of orgasm and failed orgasm attempt) was found in the alpha band. An objective rule based on spectral power in the alpha band recognized 94% (29/31) of orgasms and correctly labeled 69% (44/64) of all orgasm attempts as either successful or failed. Because outbursts of alpha fluctuations in rectal pressure only occurred during orgasm and not during voluntary imitation of orgasm or failed attempts, we propose that they represent involuntary contractions of muscles in the rectal vicinity. This is the first objective and quantitative measure that has a strong correspondence with the subjective experience of orgasm.

Detection of Spectral Evolution in the Bursts Emitted During the 2008-2009 Active Episode of SGR J1550 - 5418

NASA Technical Reports Server (NTRS)

von Kienlin, Andreas; Gruber, David; Kouveliotou, Chryssa; Granot, Jonathan; Baring, Matthew G.; Gogus, Ersin; Huppenkothen, Daniela; Kaneko, Yuki; Lin, Lin; Watts, Anna L.;

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.

Hyperspectral Image Classification via Multitask Joint Sparse Representation and Stepwise MRF Optimization.

PubMed

Yuan, Yuan; Lin, Jianzhe; Wang, Qi

2016-12-01

Hyperspectral image (HSI) classification is a crucial issue in remote sensing. Accurate classification benefits a large number of applications such as land use analysis and marine resource utilization. But high data correlation brings difficulty to reliable classification, especially for HSI with abundant spectral information. Furthermore, the traditional methods often fail to well consider the spatial coherency of HSI that also limits the classification performance. To address these inherent obstacles, a novel spectral-spatial classification scheme is proposed in this paper. The proposed method mainly focuses on multitask joint sparse representation (MJSR) and a stepwise Markov random filed framework, which are claimed to be two main contributions in this procedure. First, the MJSR not only reduces the spectral redundancy, but also retains necessary correlation in spectral field during classification. Second, the stepwise optimization further explores the spatial correlation that significantly enhances the classification accuracy and robustness. As far as several universal quality evaluation indexes are concerned, the experimental results on Indian Pines and Pavia University demonstrate the superiority of our method compared with the state-of-the-art competitors.

A target detection multi-layer matched filter for color and hyperspectral cameras

NASA Astrophysics Data System (ADS)

Miyanishi, Tomoya; Preece, Bradley L.; Reynolds, Joseph P.

2018-05-01

In this article, a method for applying matched filters to a 3-dimentional hyperspectral data cube is discussed. In many applications, color visible cameras or hyperspectral cameras are used for target detection where the color or spectral optical properties of the imaged materials are partially known in advance. Therefore, the use of matched filtering with spectral data along with shape data is an effective method for detecting certain targets. Since many methods for 2D image filtering have been researched, we propose a multi-layer filter where ordinary spatially matched filters are used before the spectral filters. We discuss a way to layer the spectral filters for a 3D hyperspectral data cube, accompanied by a detectability metric for calculating the SNR of the filter. This method is appropriate for visible color cameras and hyperspectral cameras. We also demonstrate an analysis using the Night Vision Integrated Performance Model (NV-IPM) and a Monte Carlo simulation in order to confirm the effectiveness of the filtering in providing a higher output SNR and a lower false alarm rate.

Emotion to emotion speech conversion in phoneme level

NASA Astrophysics Data System (ADS)

Bulut, Murtaza; Yildirim, Serdar; Busso, Carlos; Lee, Chul Min; Kazemzadeh, Ebrahim; Lee, Sungbok; Narayanan, Shrikanth

2004-10-01

Having an ability to synthesize emotional speech can make human-machine interaction more natural in spoken dialogue management. This study investigates the effectiveness of prosodic and spectral modification in phoneme level on emotion-to-emotion speech conversion. The prosody modification is performed with the TD-PSOLA algorithm (Moulines and Charpentier, 1990). We also transform the spectral envelopes of source phonemes to match those of target phonemes using LPC-based spectral transformation approach (Kain, 2001). Prosodic speech parameters (F0, duration, and energy) for target phonemes are estimated from the statistics obtained from the analysis of an emotional speech database of happy, angry, sad, and neutral utterances collected from actors. Listening experiments conducted with native American English speakers indicate that the modification of prosody only or spectrum only is not sufficient to elicit targeted emotions. The simultaneous modification of both prosody and spectrum results in higher acceptance rates of target emotions, suggesting that not only modeling speech prosody but also modeling spectral patterns that reflect underlying speech articulations are equally important to synthesize emotional speech with good quality. We are investigating suprasegmental level modifications for further improvement in speech quality and expressiveness.

An initial model for estimating soybean development stages from spectral data

NASA Technical Reports Server (NTRS)

Henderson, K. E.; Badhwar, G. D.

1982-01-01

A model, utilizing a direct relationship between remotely sensed spectral data and soybean development stage, has been proposed. The model is based upon transforming the spectral data in Landsat bands to greenness values over time and relating the area of this curve to soybean development stage. Soybean development stages were estimated from data acquired in 1978 from research plots at the Purdue University Agronomy Farm as well as Landsat data acquired over sample areas of the U.S. Corn Belt in 1978 and 1979. Analysis of spectral data from research plots revealed that the model works well with reasonable variation in planting date, row spacing, and soil background. The R-squared of calculated U.S. observed development stage exceeded 0.91 for all treatment variables. Using Landsat data the calculated U.S. observed development stage gave an R-squared of 0.89 in 1978 and 0.87 in 1979. No difference in the models performance could be detected between early and late planted fields, small and large fields, or high and low yielding fields.