Measurement of high-temperature spectral emissivity using integral blackbody approach

NASA Astrophysics Data System (ADS)

Pan, Yijie; Dong, Wei; Lin, Hong; Yuan, Zundong; Bloembergen, Pieter

2016-11-01

Spectral emissivity is one of the most critical thermophysical properties of a material for heat design and analysis. Especially in the traditional radiation thermometry, normal spectral emissivity is very important. We developed a prototype instrument based upon an integral blackbody method to measure material's spectral emissivity at elevated temperatures. An optimized commercial variable-high-temperature blackbody, a high speed linear actuator, a linear pyrometer, and an in-house designed synchronization circuit was used to implemented the system. A sample was placed in a crucible at the bottom of the blackbody furnace, by which the sample and the tube formed a simulated reference blackbody which had an effective total emissivity greater than 0.985. During the measurement, a pneumatic cylinder pushed a graphite rode and then the sample crucible to the cold opening within hundreds of microseconds. The linear pyrometer was used to monitor the brightness temperature of the sample surface, and the corresponding opto-converted voltage was fed and recorded by a digital multimeter. To evaluate the temperature drop of the sample along the pushing process, a physical model was proposed. The tube was discretized into several isothermal cylindrical rings, and the temperature of each ring was measurement. View factors between sample and rings were utilized. Then, the actual surface temperature of the sample at the end opening was obtained. Taking advantages of the above measured voltage signal and the calculated actual temperature, normal spectral emissivity under the that temperature point was obtained. Graphite sample at 1300°C was measured to prove the validity of the method.

Future VIIRS enhancements for the integrated polar-orbiting environmental satellite system

NASA Astrophysics Data System (ADS)

Puschell, Jeffery J.; Silny, John; Cook, Lacy; Kim, Eugene

2010-08-01

The Visible/Infrared Imager Radiometer Suite (VIIRS) is the next-generation imaging spectroradiometer for the future operational polar-orbiting environmental satellite system. A successful Flight Unit 1 has been delivered and integrated onto the NPP spacecraft. The flexible VIIRS architecture can be adapted and enhanced to respond to a wide range of requirements and to incorporate new technology as it becomes available. This paper reports on recent design studies to evaluate building a MW-VLWIR dispersive hyperspectral module with active cooling into the existing VIIRS architecture. Performance of a two-grating VIIRS hyperspectral module was studied across a broad trade space defined primarily by spatial sampling, spectral range, spectral sampling interval, along-track field of view and integration time. The hyperspectral module studied here provides contiguous coverage across 3.9 - 15.5 μm with a spectral sampling interval of 10 nm or better, thereby extending VIIRS spectral range to the shortwave side of the 15.5 μm CO2 band and encompassing the 6.7 μm H2O band. Spatial sampling occurs at VIIRS I-band (~0.4 km at nadir) spatial resolution with aggregation to M-band (~0.8 km) and larger pixel sizes to improve sensitivity. Radiometric sensitivity (NEdT) at a spatial resolution of ~4 km is ~0.1 K or better for a 250 K scene across a wavelength range of 4.5 μm to 15.5 μm. The large number of high spectral and spatial resolution FOVs in this instrument improves chances for retrievals of information on the physical state and composition of the atmosphere all the way to the surface in cloudy regions relative to current systems. Spectral aggregation of spatial resolution measurements to MODIS and VIIRS multispectral bands would continue legacy measurements with better sensitivity in nearly all bands. Additional work is needed to optimize spatial sampling, spectral range and spectral sampling approaches for the hyperspectral module and to further refine this powerful imager concept.

Baseline Correction of Diffuse Reflection Near-Infrared Spectra Using Searching Region Standard Normal Variate (SRSNV).

PubMed

Genkawa, Takuma; Shinzawa, Hideyuki; Kato, Hideaki; Ishikawa, Daitaro; Murayama, Kodai; Komiyama, Makoto; Ozaki, Yukihiro

2015-12-01

An alternative baseline correction method for diffuse reflection near-infrared (NIR) spectra, searching region standard normal variate (SRSNV), was proposed. Standard normal variate (SNV) is an effective pretreatment method for baseline correction of diffuse reflection NIR spectra of powder and granular samples; however, its baseline correction performance depends on the NIR region used for SNV calculation. To search for an optimal NIR region for baseline correction using SNV, SRSNV employs moving window partial least squares regression (MWPLSR), and an optimal NIR region is identified based on the root mean square error (RMSE) of cross-validation of the partial least squares regression (PLSR) models with the first latent variable (LV). The performance of SRSNV was evaluated using diffuse reflection NIR spectra of mixture samples consisting of wheat flour and granular glucose (0-100% glucose at 5% intervals). From the obtained NIR spectra of the mixture in the 10 000-4000 cm(-1) region at 4 cm intervals (1501 spectral channels), a series of spectral windows consisting of 80 spectral channels was constructed, and then SNV spectra were calculated for each spectral window. Using these SNV spectra, a series of PLSR models with the first LV for glucose concentration was built. A plot of RMSE versus the spectral window position obtained using the PLSR models revealed that the 8680–8364 cm(-1) region was optimal for baseline correction using SNV. In the SNV spectra calculated using the 8680–8364 cm(-1) region (SRSNV spectra), a remarkable relative intensity change between a band due to wheat flour at 8500 cm(-1) and that due to glucose at 8364 cm(-1) was observed owing to successful baseline correction using SNV. A PLSR model with the first LV based on the SRSNV spectra yielded a determination coefficient (R2) of 0.999 and an RMSE of 0.70%, while a PLSR model with three LVs based on SNV spectra calculated in the full spectral region gave an R2 of 0.995 and an RMSE of 2.29%. Additional evaluation of SRSNV was carried out using diffuse reflection NIR spectra of marzipan and corn samples, and PLSR models based on SRSNV spectra showed good prediction results. These evaluation results indicate that SRSNV is effective in baseline correction of diffuse reflection NIR spectra and provides regression models with good prediction accuracy.

Utility of BRDF Models for Estimating Optimal View Angles in Classification of Remotely Sensed Images

NASA Technical Reports Server (NTRS)

Valdez, P. F.; Donohoe, G. W.

1997-01-01

Statistical classification of remotely sensed images attempts to discriminate between surface cover types on the basis of the spectral response recorded by a sensor. It is well known that surfaces reflect incident radiation as a function of wavelength producing a spectral signature specific to the material under investigation. Multispectral and hyperspectral sensors sample the spectral response over tens and even hundreds of wavelength bands to capture the variation of spectral response with wavelength. Classification algorithms then exploit these differences in spectral response to distinguish between materials of interest. Sensors of this type, however, collect detailed spectral information from one direction (usually nadir); consequently, do not consider the directional nature of reflectance potentially detectable at different sensor view angles. Improvements in sensor technology have resulted in remote sensing platforms capable of detecting reflected energy across wavelengths (spectral signatures) and from multiple view angles (angular signatures) in the fore and aft directions. Sensors of this type include: the moderate resolution imaging spectroradiometer (MODIS), the multiangle imaging spectroradiometer (MISR), and the airborne solid-state array spectroradiometer (ASAS). A goal of this paper, then, is to explore the utility of Bidirectional Reflectance Distribution Function (BRDF) models in the selection of optimal view angles for the classification of remotely sensed images by employing a strategy of searching for the maximum difference between surface BRDFs. After a brief discussion of directional reflect ante in Section 2, attention is directed to the Beard-Maxwell BRDF model and its use in predicting the bidirectional reflectance of a surface. The selection of optimal viewing angles is addressed in Section 3, followed by conclusions and future work in Section 4.

JURASSIC Retrieval Processing

NASA Astrophysics Data System (ADS)

Blank, J.; Ungermann, J.; Guggenmoser, T.; Kaufmann, M.; Riese, M.

2012-04-01

The Gimballed Limb Observer for Radiance Imaging in the Atmosphere (GLORIA) is an aircraft based infrared limb-sounder. This presentation will give an overview of the retrieval techniques used for the analysis of data produced by the GLORIA instrument. For data processing, the JUelich RApid Spectral SImulation Code 2 (JURASSIC2) was developed. It consists of a set of programs to retrieve atmospheric profiles from GLORIA measurements. The GLORIA Michelson interferometer can run with a wide range of parameters. In the dynamics mode, spectra are generate with a medium spectral and a very high temporal and spatial resolution. Each sample can contain thousands of spectral lines for each contributing trace gas. In the JURASSIC retrieval code this is handled by using a radiative transport model based on the Emissivity Growth Approximation. Deciding which samples should be included in the retrieval is a non-trivial task and requires specific domain knowledge. To ease this problem we developed an automatic selection program by analysing the Shannon information content. By taking into account data for all relevant trace gases and instrument effects, optimal integrated spectral windows are computed. This includes considerations for cross-influence of trace gases, which has non-obvious consequence for the contribution of spectral samples. We developed methods to assess the influence of spectral windows on the retrieval. While we can not exhaustively search the whole range of possible spectral sample combinations, it is possible to optimize information content using a genetic algorithm. The GLORIA instrument is mounted with a viewing direction perpendicular to the flight direction. A gimbal frame makes it possible to move the instrument 45° to both direction. By flying on a circular path, it is possible to generate images of an area of interest from a wide range of angles. These can be analyzed in a 3D-tomographic fashion, which yields superior spatial resolution along line of site. Usually limb instruments have a resolution of several hundred kilometers. In studies we have shown to get a resolution of 35km in all horizontal directions. Even when only linear flight patterns can be realized, resolutions of ≈70km can be obtained. This technique can be used to observe features of the Upper Troposphere Lower Stratosphere (UTLS), where important mixing processes take place. Especially tropopause folds are difficult to image, as their main features need to be along line of flight when using common 1D approach.

High temperature spectral emissivity measurement using integral blackbody method

NASA Astrophysics Data System (ADS)

Pan, Yijie; Dong, Wei; Lin, Hong; Yuan, Zundong; Bloembergen, Pieter

2016-10-01

Spectral emissivity is a critical material's thermos-physical property for heat design and radiation thermometry. A prototype instrument based upon an integral blackbody method was developed to measure material's spectral emissivity above 1000 °. The system was implemented with an optimized commercial variable-high-temperature blackbody, a high speed linear actuator, a linear pyrometer, and an in-house designed synchronization circuit. A sample was placed in a crucible at the bottom of the blackbody furnace, by which the sample and the tube formed a simulated blackbody which had an effective total emissivity greater than 0.985. During the measurement, the sample was pushed to the end opening of the tube by a graphite rod which was actuated through a pneumatic cylinder. A linear pyrometer was used to monitor the brightness temperature of the sample surface through the measurement. The corresponding opto-converted voltage signal was fed and recorded by a digital multi-meter. A physical model was proposed to numerically evaluate the temperature drop along the process. Tube was discretized as several isothermal cylindrical rings, and the temperature profile of the tube was measurement. View factors between sample and rings were calculated and updated along the whole pushing process. The actual surface temperature of the sample at the end opening was obtained. Taking advantages of the above measured voltage profile and the calculated true temperature, spectral emissivity under this temperature point was calculated.

Spectral Estimation Model Construction of Heavy Metals in Mining Reclamation Areas

PubMed Central

Dong, Jihong; Dai, Wenting; Xu, Jiren; Li, Songnian

2016-01-01

The study reported here examined, as the research subject, surface soils in the Liuxin mining area of Xuzhou, and explored the heavy metal content and spectral data by establishing quantitative models with Multivariable Linear Regression (MLR), Generalized Regression Neural Network (GRNN) and Sequential Minimal Optimization for Support Vector Machine (SMO-SVM) methods. The study results are as follows: (1) the estimations of the spectral inversion models established based on MLR, GRNN and SMO-SVM are satisfactory, and the MLR model provides the worst estimation, with R2 of more than 0.46. This result suggests that the stress sensitive bands of heavy metal pollution contain enough effective spectral information; (2) the GRNN model can simulate the data from small samples more effectively than the MLR model, and the R2 between the contents of the five heavy metals estimated by the GRNN model and the measured values are approximately 0.7; (3) the stability and accuracy of the spectral estimation using the SMO-SVM model are obviously better than that of the GRNN and MLR models. Among all five types of heavy metals, the estimation for cadmium (Cd) is the best when using the SMO-SVM model, and its R2 value reaches 0.8628; (4) using the optimal model to invert the Cd content in wheat that are planted on mine reclamation soil, the R2 and RMSE between the measured and the estimated values are 0.6683 and 0.0489, respectively. This result suggests that the method using the SMO-SVM model to estimate the contents of heavy metals in wheat samples is feasible. PMID:27367708

Spectral Estimation Model Construction of Heavy Metals in Mining Reclamation Areas.

PubMed

Dong, Jihong; Dai, Wenting; Xu, Jiren; Li, Songnian

2016-06-28

The study reported here examined, as the research subject, surface soils in the Liuxin mining area of Xuzhou, and explored the heavy metal content and spectral data by establishing quantitative models with Multivariable Linear Regression (MLR), Generalized Regression Neural Network (GRNN) and Sequential Minimal Optimization for Support Vector Machine (SMO-SVM) methods. The study results are as follows: (1) the estimations of the spectral inversion models established based on MLR, GRNN and SMO-SVM are satisfactory, and the MLR model provides the worst estimation, with R² of more than 0.46. This result suggests that the stress sensitive bands of heavy metal pollution contain enough effective spectral information; (2) the GRNN model can simulate the data from small samples more effectively than the MLR model, and the R² between the contents of the five heavy metals estimated by the GRNN model and the measured values are approximately 0.7; (3) the stability and accuracy of the spectral estimation using the SMO-SVM model are obviously better than that of the GRNN and MLR models. Among all five types of heavy metals, the estimation for cadmium (Cd) is the best when using the SMO-SVM model, and its R² value reaches 0.8628; (4) using the optimal model to invert the Cd content in wheat that are planted on mine reclamation soil, the R² and RMSE between the measured and the estimated values are 0.6683 and 0.0489, respectively. This result suggests that the method using the SMO-SVM model to estimate the contents of heavy metals in wheat samples is feasible.

Detection of chlorine with concentration of 0.18 kg/m{sup 3} in concrete by laser-induced breakdown spectroscopy

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

Sugiyama, K.; Fujii, T.; Matsumura, T.

2010-05-01

The chlorine concentration in concrete samples was measured by laser-induced breakdown spectroscopy (LIBS). One or two pulsed second harmonic Nd:YAG lasers ({lambda}=532 nm) were used for the generation of laser-induced breakdown, and an intensified CCD camera, spectrometer, and optical bundle fiber were used for spectral measurement. To maximize the spectral intensity of the chlorine fluorescence line at a wavelength of 837.59 nm, the time delay between laser irradiation and spectral measurement, the time delay between the two laser pulses in double-pulse measurement, and the gate width of the spectral measurement were optimized. The linear relationship between the spectral intensity ofmore » the chlorine fluorescence line and the chlorine concentration was verified for pressed samples with chlorine concentrations from 0.18 to 5.4 kg/m{sup 3}. The signal-to-noise ratio was higher than 2 for the sample with a chlorine concentration of 0.18 kg/m{sup 3} (0.008 wt. %). Thus, a chlorine concentration of 0.6 kg/m{sup 3}, at which the reinforcing bars in concrete structures start to corrode, can be detected. These results show that LIBS is effective for the quantitative measurement of chlorine concentration in concrete with high sensitivity.« less

[Variable selection methods combined with local linear embedding theory used for optimization of near infrared spectral quantitative models].

PubMed

Hao, Yong; Sun, Xu-Dong; Yang, Qiang

2012-12-01

Variables selection strategy combined with local linear embedding (LLE) was introduced for the analysis of complex samples by using near infrared spectroscopy (NIRS). Three methods include Monte Carlo uninformation variable elimination (MCUVE), successive projections algorithm (SPA) and MCUVE connected with SPA were used for eliminating redundancy spectral variables. Partial least squares regression (PLSR) and LLE-PLSR were used for modeling complex samples. The results shown that MCUVE can both extract effective informative variables and improve the precision of models. Compared with PLSR models, LLE-PLSR models can achieve more accurate analysis results. MCUVE combined with LLE-PLSR is an effective modeling method for NIRS quantitative analysis.

GAME: GAlaxy Machine learning for Emission lines

NASA Astrophysics Data System (ADS)

Ucci, G.; Ferrara, A.; Pallottini, A.; Gallerani, S.

2018-06-01

We present an updated, optimized version of GAME (GAlaxy Machine learning for Emission lines), a code designed to infer key interstellar medium physical properties from emission line intensities of ultraviolet /optical/far-infrared galaxy spectra. The improvements concern (a) an enlarged spectral library including Pop III stars, (b) the inclusion of spectral noise in the training procedure, and (c) an accurate evaluation of uncertainties. We extensively validate the optimized code and compare its performance against empirical methods and other available emission line codes (PYQZ and HII-CHI-MISTRY) on a sample of 62 SDSS stacked galaxy spectra and 75 observed HII regions. Very good agreement is found for metallicity. However, ionization parameters derived by GAME tend to be higher. We show that this is due to the use of too limited libraries in the other codes. The main advantages of GAME are the simultaneous use of all the measured spectral lines and the extremely short computational times. We finally discuss the code potential and limitations.

Optimized Multi-Spectral Filter Array Based Imaging of Natural Scenes.

PubMed

Li, Yuqi; Majumder, Aditi; Zhang, Hao; Gopi, M

2018-04-12

Multi-spectral imaging using a camera with more than three channels is an efficient method to acquire and reconstruct spectral data and is used extensively in tasks like object recognition, relighted rendering, and color constancy. Recently developed methods are used to only guide content-dependent filter selection where the set of spectral reflectances to be recovered are known a priori. We present the first content-independent spectral imaging pipeline that allows optimal selection of multiple channels. We also present algorithms for optimal placement of the channels in the color filter array yielding an efficient demosaicing order resulting in accurate spectral recovery of natural reflectance functions. These reflectance functions have the property that their power spectrum statistically exhibits a power-law behavior. Using this property, we propose power-law based error descriptors that are minimized to optimize the imaging pipeline. We extensively verify our models and optimizations using large sets of commercially available wide-band filters to demonstrate the greater accuracy and efficiency of our multi-spectral imaging pipeline over existing methods.

Optimized Multi-Spectral Filter Array Based Imaging of Natural Scenes

PubMed Central

Li, Yuqi; Majumder, Aditi; Zhang, Hao; Gopi, M.

2018-01-01

Multi-spectral imaging using a camera with more than three channels is an efficient method to acquire and reconstruct spectral data and is used extensively in tasks like object recognition, relighted rendering, and color constancy. Recently developed methods are used to only guide content-dependent filter selection where the set of spectral reflectances to be recovered are known a priori. We present the first content-independent spectral imaging pipeline that allows optimal selection of multiple channels. We also present algorithms for optimal placement of the channels in the color filter array yielding an efficient demosaicing order resulting in accurate spectral recovery of natural reflectance functions. These reflectance functions have the property that their power spectrum statistically exhibits a power-law behavior. Using this property, we propose power-law based error descriptors that are minimized to optimize the imaging pipeline. We extensively verify our models and optimizations using large sets of commercially available wide-band filters to demonstrate the greater accuracy and efficiency of our multi-spectral imaging pipeline over existing methods. PMID:29649114

Optical spectroscopic characterization of human meniscus biomechanical properties

NASA Astrophysics Data System (ADS)

Ala-Myllymäki, Juho; Danso, Elvis K.; Honkanen, Juuso T. J.; Korhonen, Rami K.; Töyräs, Juha; Afara, Isaac O.

2017-12-01

This study investigates the capacity of optical spectroscopy in the visible (VIS) and near-infrared (NIR) spectral ranges for estimating the biomechanical properties of human meniscus. Seventy-two samples obtained from the anterior, central, and posterior locations of the medial and lateral menisci of 12 human cadaver joints were used. The samples were subjected to mechanical indentation, then traditional biomechanical parameters (equilibrium and dynamic moduli) were calculated. In addition, strain-dependent fibril network modulus and permeability strain-dependency coefficient were determined via finite-element modeling. Subsequently, absorption spectra were acquired from each location in the VIS (400 to 750 nm) and NIR (750 to 1100 nm) spectral ranges. Partial least squares regression, combined with spectral preprocessing and transformation, was then used to investigate the relationship between the biomechanical properties and spectral response. The NIR spectral region was observed to be optimal for model development (83.0%≤R2≤90.8%). The percentage error of the models are: Eeq (7.1%), Edyn (9.6%), Eɛ (8.4%), and Mk (8.9%). Thus, we conclude that optical spectroscopy in the NIR range is a potential method for rapid and nondestructive evaluation of human meniscus functional integrity and health in real time during arthroscopic surgery.

Influence of Laser Radiation Power Density on the Intensity of Spectral Lines for Main Components in a Clay Laser-Induced Plasma

NASA Astrophysics Data System (ADS)

Anufrik, S. S.; Kurian, N. N.; Znosko, K. F.; Belkov, M. V.

2018-05-01

We have studied the intensity of the spectral lines for the main components in clay: Al I 309.4 nm, Al II 358.7 nm, Mg II 279.6 nm, Ti II 323.6 nm vs. the position of the object relative to the focus of the optical system when the samples are exposed to single laser pulses from a YAG:Nd3+ laser. We have determined the permissible ranges for positioning the object relative to the focus of the optical system (positive and negative defocusing) for which there is practically no change in the reproducibility of the intensity for the spectral lines for red and white clay samples. We show that the position of the object relative to the focus of the optical system should be within the range ΔZ ±1.5 mm for optimal laser pulse energies for the analyte spectral lines. We have calculated the radiation flux density for different laser pulse energies and different distances from the focus to the object. We have shown experimentally that reducing the radiation flux density leads to a decrease in the intensity of the analyte spectral lines.

Optimization of Decision-Making for Spatial Sampling in the North China Plain, Based on Remote-Sensing a Priori Knowledge

NASA Astrophysics Data System (ADS)

Feng, J.; Bai, L.; Liu, S.; Su, X.; Hu, H.

2012-07-01

In this paper, the MODIS remote sensing data, featured with low-cost, high-timely and moderate/low spatial resolutions, in the North China Plain (NCP) as a study region were firstly used to carry out mixed-pixel spectral decomposition to extract an useful regionalized indicator parameter (RIP) (i.e., an available ratio, that is, fraction/percentage, of winter wheat planting area in each pixel as a regionalized indicator variable (RIV) of spatial sampling) from the initial selected indicators. Then, the RIV values were spatially analyzed, and the spatial structure characteristics (i.e., spatial correlation and variation) of the NCP were achieved, which were further processed to obtain the scalefitting, valid a priori knowledge or information of spatial sampling. Subsequently, founded upon an idea of rationally integrating probability-based and model-based sampling techniques and effectively utilizing the obtained a priori knowledge or information, the spatial sampling models and design schemes and their optimization and optimal selection were developed, as is a scientific basis of improving and optimizing the existing spatial sampling schemes of large-scale cropland remote sensing monitoring. Additionally, by the adaptive analysis and decision strategy the optimal local spatial prediction and gridded system of extrapolation results were able to excellently implement an adaptive report pattern of spatial sampling in accordance with report-covering units in order to satisfy the actual needs of sampling surveys.

Hyper-spectral imaging in scanning-confocal-fluorescence microscopy using a novel broadband diffractive optic

NASA Astrophysics Data System (ADS)

Wang, Peng; Ebeling, Carl G.; Gerton, Jordan; Menon, Rajesh

In this paper, we demonstrate hyper-spectral imaging of fluorescent microspheres in a scanning-confocal-fluorescence microscope by spatially dispersing the spectra using a novel broadband diffractive optic, and applying a nonlinear optimization technique to extract the full-incident spectra. This broadband diffractive optic has a designed optical efficiency of over 90% across the entire visible spectrum. We used this technique to create two-color images of two fluorophores and also extracted their emission spectra with good fidelity. This method can be extended to image both spatially and spectrally overlapping fluorescent samples. Full control in the number of emission spectra and the feasibility of enhanced imaging speed are demonstrated as well.

Discriminative illumination: per-pixel classification of raw materials based on optimal projections of spectral BRDF.

PubMed

Liu, Chao; Gu, Jinwei

2014-01-01

Classifying raw, unpainted materials--metal, plastic, ceramic, fabric, and so on--is an important yet challenging task for computer vision. Previous works measure subsets of surface spectral reflectance as features for classification. However, acquiring the full spectral reflectance is time consuming and error-prone. In this paper, we propose to use coded illumination to directly measure discriminative features for material classification. Optimal illumination patterns--which we call "discriminative illumination"--are learned from training samples, after projecting to which the spectral reflectance of different materials are maximally separated. This projection is automatically realized by the integration of incident light for surface reflection. While a single discriminative illumination is capable of linear, two-class classification, we show that multiple discriminative illuminations can be used for nonlinear and multiclass classification. We also show theoretically that the proposed method has higher signal-to-noise ratio than previous methods due to light multiplexing. Finally, we construct an LED-based multispectral dome and use the discriminative illumination method for classifying a variety of raw materials, including metal (aluminum, alloy, steel, stainless steel, brass, and copper), plastic, ceramic, fabric, and wood. Experimental results demonstrate its effectiveness.

Distortion Representation of Forecast Errors for Model Skill Assessment and Objective Analysis

NASA Technical Reports Server (NTRS)

Hoffman, Ross N.

2001-01-01

We completed the formulation of the smoothness penalty functional this past quarter. We used a simplified procedure for estimating the statistics of the FCA solution spectral coefficients from the results of the unconstrained, low-truncation FCA (stopping criterion) solutions. During the current reporting period we have completed the calculation of GEOS-2 model-equivalent brightness temperatures for the 6.7 micron and 11 micron window channels used in the GOES imagery for all 10 cases from August 1999. These were simulated using the AER-developed Optimal Spectral Sampling (OSS) model.

Statistical analysis of latent generalized correlation matrix estimation in transelliptical distribution.

PubMed

Han, Fang; Liu, Han

2017-02-01

Correlation matrix plays a key role in many multivariate methods (e.g., graphical model estimation and factor analysis). The current state-of-the-art in estimating large correlation matrices focuses on the use of Pearson's sample correlation matrix. Although Pearson's sample correlation matrix enjoys various good properties under Gaussian models, its not an effective estimator when facing heavy-tail distributions with possible outliers. As a robust alternative, Han and Liu (2013b) advocated the use of a transformed version of the Kendall's tau sample correlation matrix in estimating high dimensional latent generalized correlation matrix under the transelliptical distribution family (or elliptical copula). The transelliptical family assumes that after unspecified marginal monotone transformations, the data follow an elliptical distribution. In this paper, we study the theoretical properties of the Kendall's tau sample correlation matrix and its transformed version proposed in Han and Liu (2013b) for estimating the population Kendall's tau correlation matrix and the latent Pearson's correlation matrix under both spectral and restricted spectral norms. With regard to the spectral norm, we highlight the role of "effective rank" in quantifying the rate of convergence. With regard to the restricted spectral norm, we for the first time present a "sign subgaussian condition" which is sufficient to guarantee that the rank-based correlation matrix estimator attains the optimal rate of convergence. In both cases, we do not need any moment condition.

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

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

Biologically-inspired data decorrelation for hyper-spectral imaging

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

SU-D-218-05: Material Quantification in Spectral X-Ray Imaging: Optimization and Validation.

PubMed

Nik, S J; Thing, R S; Watts, R; Meyer, J

2012-06-01

To develop and validate a multivariate statistical method to optimize scanning parameters for material quantification in spectral x-rayimaging. An optimization metric was constructed by extensively sampling the thickness space for the expected number of counts for m (two or three) materials. This resulted in an m-dimensional confidence region ofmaterial quantities, e.g. thicknesses. Minimization of the ellipsoidal confidence region leads to the optimization of energy bins. For the given spectrum, the minimum counts required for effective material separation can be determined by predicting the signal-to-noise ratio (SNR) of the quantification. A Monte Carlo (MC) simulation framework using BEAM was developed to validate the metric. Projection data of the m-materials was generated and material decomposition was performed for combinations of iodine, calcium and water by minimizing the z-score between the expected spectrum and binned measurements. The mean square error (MSE) and variance were calculated to measure the accuracy and precision of this approach, respectively. The minimum MSE corresponds to the optimal energy bins in the BEAM simulations. In the optimization metric, this is equivalent to the smallest confidence region. The SNR of the simulated images was also compared to the predictions from the metric. TheMSE was dominated by the variance for the given material combinations,which demonstrates accurate material quantifications. The BEAMsimulations revealed that the optimization of energy bins was accurate to within 1keV. The SNRs predicted by the optimization metric yielded satisfactory agreement but were expectedly higher for the BEAM simulations due to the inclusion of scattered radiation. The validation showed that the multivariate statistical method provides accurate material quantification, correct location of optimal energy bins and adequateprediction of image SNR. The BEAM code system is suitable for generating spectral x- ray imaging simulations. © 2012 American Association of Physicists in Medicine.

Quantification of calcium using localized normalization on laser-induced breakdown spectroscopy data

NASA Astrophysics Data System (ADS)

Sabri, Nursalwanie Mohd; Haider, Zuhaib; Tufail, Kashif; Aziz, Safwan; Ali, Jalil; Wahab, Zaidan Abdul; Abbas, Zulkifly

2017-03-01

This paper focuses on localized normalization for improved calibration curves in laser-induced breakdown spectroscopy (LIBS) measurements. The calibration curves have been obtained using five samples consisting of different concentrations of calcium (Ca) in potassium bromide (KBr) matrix. The work has utilized Q-switched Nd:YAG laser installed in LIBS2500plus system with fundamental wavelength and laser energy of 650 mJ. Optimization of gate delay can be obtained from signal-to-background ratio (SBR) of Ca II 315.9 and 317.9 nm. The optimum conditions are determined in which having high spectral intensity and SBR. The highest spectral lines of ionic and emission lines of Ca at gate delay of 0.83 µs. From SBR, the optimized gate delay is at 5.42 µs for both Ca II spectral lines. Calibration curves consist of three parts; original intensity from LIBS experimentation, normalization and localized normalization of the spectral line intensity. The R2 values of the calibration curves plotted using locally normalized intensities of Ca I 610.3, 612.2 and 616.2 nm spectral lines are 0.96329, 0.97042, and 0.96131, respectively. The enhancement from calibration curves using the regression coefficient allows more accurate analysis in LIBS. At the request of all authors of the paper, and with the agreement of the Proceedings Editor, an updated version of this article was published on 24 May 2017.

[Main Components of Xinjiang Lavender Essential Oil Determined by Partial Least Squares and Near Infrared Spectroscopy].

PubMed

Liao, Xiang; Wang, Qing; Fu, Ji-hong; Tang, Jun

2015-09-01

This work was undertaken to establish a quantitative analysis model which can rapid determinate the content of linalool, linalyl acetate of Xinjiang lavender essential oil. Totally 165 lavender essential oil samples were measured by using near infrared absorption spectrum (NIR), after analyzing the near infrared spectral absorption peaks of all samples, lavender essential oil have abundant chemical information and the interference of random noise may be relatively low on the spectral intervals of 7100~4500 cm(-1). Thus, the PLS models was constructed by using this interval for further analysis. 8 abnormal samples were eliminated. Through the clustering method, 157 lavender essential oil samples were divided into 105 calibration set samples and 52 validation set samples. Gas chromatography mass spectrometry (GC-MS) was used as a tool to determine the content of linalool and linalyl acetate in lavender essential oil. Then the matrix was established with the GC-MS raw data of two compounds in combination with the original NIR data. In order to optimize the model, different pretreatment methods were used to preprocess the raw NIR spectral to contrast the spectral filtering effect, after analysizing the quantitative model results of linalool and linalyl acetate, the root mean square error prediction (RMSEP) of orthogonal signal transformation (OSC) was 0.226, 0.558, spectrally, it was the optimum pretreatment method. In addition, forward interval partial least squares (FiPLS) method was used to exclude the wavelength points which has nothing to do with determination composition or present nonlinear correlation, finally 8 spectral intervals totally 160 wavelength points were obtained as the dataset. Combining the data sets which have optimized by OSC-FiPLS with partial least squares (PLS) to establish a rapid quantitative analysis model for determining the content of linalool and linalyl acetate in Xinjiang lavender essential oil, numbers of hidden variables of two components were 8 in the model. The performance of the model was evaluated according to root mean square error of cross-validation (RMSECV), root mean square error of prediction (RMSEP). In the model, RESECV of linalool and linalyl acetate were 0.170 and 0.416, respectively; RM-SEP were 0.188 and 0.364. The results indicated that raw data was pretreated by OSC and FiPLS, the NIR-PLS quantitative analysis model with good robustness, high measurement precision; it could quickly determine the content of linalool and linalyl acetate in lavender essential oil. In addition, the model has a favorable prediction ability. The study also provide a new effective method which could rapid quantitative analysis the major components of Xinjiang lavender essential oil.

Martian Radiative Transfer Modeling Using the Optimal Spectral Sampling Method

NASA Technical Reports Server (NTRS)

Eluszkiewicz, J.; Cady-Pereira, K.; Uymin, G.; Moncet, J.-L.

2005-01-01

The large volume of existing and planned infrared observations of Mars have prompted the development of a new martian radiative transfer model that could be used in the retrievals of atmospheric and surface properties. The model is based on the Optimal Spectral Sampling (OSS) method [1]. The method is a fast and accurate monochromatic technique applicable to a wide range of remote sensing platforms (from microwave to UV) and was originally developed for the real-time processing of infrared and microwave data acquired by instruments aboard the satellites forming part of the next-generation global weather satellite system NPOESS (National Polarorbiting Operational Satellite System) [2]. As part of our on-going research related to the radiative properties of the martian polar caps, we have begun the development of a martian OSS model with the goal of using it to perform self-consistent atmospheric corrections necessary to retrieve caps emissivity from the Thermal Emission Spectrometer (TES) spectra. While the caps will provide the initial focus area for applying the new model, it is hoped that the model will be of interest to the wider Mars remote sensing community.

A novel baseline correction method using convex optimization framework in laser-induced breakdown spectroscopy quantitative analysis

NASA Astrophysics Data System (ADS)

Yi, Cancan; Lv, Yong; Xiao, Han; Ke, Ke; Yu, Xun

2017-12-01

For laser-induced breakdown spectroscopy (LIBS) quantitative analysis technique, baseline correction is an essential part for the LIBS data preprocessing. As the widely existing cases, the phenomenon of baseline drift is generated by the fluctuation of laser energy, inhomogeneity of sample surfaces and the background noise, which has aroused the interest of many researchers. Most of the prevalent algorithms usually need to preset some key parameters, such as the suitable spline function and the fitting order, thus do not have adaptability. Based on the characteristics of LIBS, such as the sparsity of spectral peaks and the low-pass filtered feature of baseline, a novel baseline correction and spectral data denoising method is studied in this paper. The improved technology utilizes convex optimization scheme to form a non-parametric baseline correction model. Meanwhile, asymmetric punish function is conducted to enhance signal-noise ratio (SNR) of the LIBS signal and improve reconstruction precision. Furthermore, an efficient iterative algorithm is applied to the optimization process, so as to ensure the convergence of this algorithm. To validate the proposed method, the concentration analysis of Chromium (Cr),Manganese (Mn) and Nickel (Ni) contained in 23 certified high alloy steel samples is assessed by using quantitative models with Partial Least Squares (PLS) and Support Vector Machine (SVM). Because there is no prior knowledge of sample composition and mathematical hypothesis, compared with other methods, the method proposed in this paper has better accuracy in quantitative analysis, and fully reflects its adaptive ability.

Spectral imaging using consumer-level devices and kernel-based regression.

PubMed

Heikkinen, Ville; Cámara, Clara; Hirvonen, Tapani; Penttinen, Niko

2016-06-01

Hyperspectral reflectance factor image estimations were performed in the 400-700 nm wavelength range using a portable consumer-level laptop display as an adjustable light source for a trichromatic camera. Targets of interest were ColorChecker Classic samples, Munsell Matte samples, geometrically challenging tempera icon paintings from the turn of the 20th century, and human hands. Measurements and simulations were performed using Nikon D80 RGB camera and Dell Vostro 2520 laptop screen as a light source. Estimations were performed without spectral characteristics of the devices and by emphasizing simplicity for training sets and estimation model optimization. Spectral and color error images are shown for the estimations using line-scanned hyperspectral images as the ground truth. Estimations were performed using kernel-based regression models via a first-degree inhomogeneous polynomial kernel and a Matérn kernel, where in the latter case the median heuristic approach for model optimization and link function for bounded estimation were evaluated. Results suggest modest requirements for a training set and show that all estimation models have markedly improved accuracy with respect to the DE00 color distance (up to 99% for paintings and hands) and the Pearson distance (up to 98% for paintings and 99% for hands) from a weak training set (Digital ColorChecker SG) case when small representative training data were used in the estimation.

Origin and Correction of Magnetic Field Inhomogeneity at the Interface in Biphasic NMR Samples

PubMed Central

Martin, Bryan T.; Chingas, G. C.

2012-01-01

The use of susceptibility matching to minimize spectral distortion of biphasic samples layered in a standard 5 mm NMR tube is described. The approach uses magic angle spinning (MAS) to first extract chemical shift differences by suppressing bulk magnetization. Then, using biphasic coaxial samples, magnetic susceptibilities are matched by titration with a paramagnetic salt. The matched phases are then layered in a standard NMR tube where they can be shimmed and examined. Line widths of two distinct spectral lines, selected to characterize homogeneity in each phase, are simultaneously optimized. Two-dimensional distortion-free, slice-resolved spectra of an octanol/water system illustrate the method. These data are obtained using a 2D stepped-gradient pulse sequence devised for this application. Advantages of this sequence over slice-selective methods are that acquisition efficiency is increased and processing requires only conventional software. PMID:22459062

Theoretical and Monte Carlo optimization of a stacked three-layer flat-panel x-ray imager for applications in multi-spectral diagnostic medical imaging

NASA Astrophysics Data System (ADS)

Lopez Maurino, Sebastian; Badano, Aldo; Cunningham, Ian A.; Karim, Karim S.

2016-03-01

We propose a new design of a stacked three-layer flat-panel x-ray detector for dual-energy (DE) imaging. Each layer consists of its own scintillator of individual thickness and an underlying thin-film-transistor-based flat-panel. Three images are obtained simultaneously in the detector during the same x-ray exposure, thereby eliminating any motion artifacts. The detector operation is two-fold: a conventional radiography image can be obtained by combining all three layers' images, while a DE subtraction image can be obtained from the front and back layers' images, where the middle layer acts as a mid-filter that helps achieve spectral separation. We proceed to optimize the detector parameters for two sample imaging tasks that could particularly benefit from this new detector by obtaining the best possible signal to noise ratio per root entrance exposure using well-established theoretical models adapted to fit our new design. These results are compared to a conventional DE temporal subtraction detector and a single-shot DE subtraction detector with a copper mid-filter, both of which underwent the same theoretical optimization. The findings are then validated using advanced Monte Carlo simulations for all optimized detector setups. Given the performance expected from initial results and the recent decrease in price for digital x-ray detectors, the simplicity of the three-layer stacked imager approach appears promising to usher in a new generation of multi-spectral digital x-ray diagnostics.

Complementary shifts in photoreceptor spectral tuning unlock the full adaptive potential of ultraviolet vision in birds.

PubMed

Toomey, Matthew B; Lind, Olle; Frederiksen, Rikard; Curley, Robert W; Riedl, Ken M; Wilby, David; Schwartz, Steven J; Witt, Christopher C; Harrison, Earl H; Roberts, Nicholas W; Vorobyev, Misha; McGraw, Kevin J; Cornwall, M Carter; Kelber, Almut; Corbo, Joseph C

2016-07-12

Color vision in birds is mediated by four types of cone photoreceptors whose maximal sensitivities (λmax) are evenly spaced across the light spectrum. In the course of avian evolution, the λmax of the most shortwave-sensitive cone, SWS1, has switched between violet (λmax > 400 nm) and ultraviolet (λmax < 380 nm) multiple times. This shift of the SWS1 opsin is accompanied by a corresponding short-wavelength shift in the spectrally adjacent SWS2 cone. Here, we show that SWS2 cone spectral tuning is mediated by modulating the ratio of two apocarotenoids, galloxanthin and 11’,12’-dihydrogalloxanthin, which act as intracellular spectral filters in this cell type. We propose an enzymatic pathway that mediates the differential production of these apocarotenoids in the avian retina, and we use color vision modeling to demonstrate how correlated evolution of spectral tuning is necessary to achieve even sampling of the light spectrum and thereby maintain near-optimal color discrimination.

Persistence of uranium emission in laser-produced plasmas

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

LaHaye, N. L.; Harilal, S. S., E-mail: hari@purdue.edu; Diwakar, P. K.

2014-04-28

Detection of uranium and other nuclear materials is of the utmost importance for nuclear safeguards and security. Optical emission spectroscopy of laser-ablated U plasmas has been presented as a stand-off, portable analytical method that can yield accurate qualitative and quantitative elemental analysis of a variety of samples. In this study, optimal laser ablation and ambient conditions are explored, as well as the spatio-temporal evolution of the plasma for spectral analysis of excited U species in a glass matrix. Various Ar pressures were explored to investigate the role that plasma collisional effects and confinement have on spectral line emission enhancement andmore » persistence. The plasma-ambient gas interaction was also investigated using spatially resolved spectra and optical time-of-flight measurements. The results indicate that ambient conditions play a very important role in spectral emission intensity as well as the persistence of excited neutral U emission lines, influencing the appropriate spectral acquisition conditions.« less

Optimizing of MALDI-ToF-based low-molecular-weight serum proteome pattern analysis in detection of breast cancer patients; the effect of albumin removal on classification performance.

PubMed

Pietrowska, M; Marczak, L; Polanska, J; Nowicka, E; Behrent, K; Tarnawski, R; Stobiecki, M; Polanski, A; Widlak, P

2010-01-01

Mass spectrometry-based analysis of the serum proteome allows identifying multi-peptide patterns/signatures specific for blood of cancer patients, thus having high potential value for cancer diagnostics. However, because of problems with optimization and standardization of experimental and computational design, none of identified proteome patterns/signatures was approved for diagnostics in clinical practice as yet. Here we compared two methods of serum sample preparation for mass spectrometry-based proteome pattern analysis aimed to identify biomarkers that could be used in early detection of breast cancer patients. Blood samples were collected in a group of 92 patients diagnosed at early (I and II) stages of the disease before the start of therapy, and in a group of age-matched healthy controls (104 women). Serum specimens were purified and analyzed using MALDI-ToF spectrometry, either directly or after membrane filtration (50 kDa cut-off) to remove albumin and other large serum proteins. Mass spectra of the low-molecular-weight fraction (2-10 kDa) of the serum proteome were resolved using the Gaussian mixture decomposition, and identified spectral components were used to build classifiers that differentiated samples from breast cancer patients and healthy persons. Mass spectra of complete serum and membrane-filtered albumin-depleted samples have apparently different structure and peaks specific for both types of samples could be identified. The optimal classifier built for the complete serum specimens consisted of 8 spectral components, and had 81% specificity and 72% sensitivity, while that built for the membrane-filtered samples consisted of 4 components, and had 80% specificity and 81% sensitivity. We concluded that pre-processing of samples to remove albumin might be recommended before MALDI-ToF mass spectrometric analysis of the low-molecular-weight components of human serum Keywords: albumin removal; breast cancer; clinical proteomics; mass spectrometry; pattern analysis; serum proteome.

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

NASA Astrophysics Data System (ADS)

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

2003-12-01

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

The effect of spectral filters on visual search in stroke patients.

PubMed

Beasley, Ian G; Davies, Leon N

2013-01-01

Visual search impairment can occur following stroke. The utility of optimal spectral filters on visual search in stroke patients has not been considered to date. The present study measured the effect of optimal spectral filters on visual search response time and accuracy, using a task requiring serial processing. A stroke and control cohort undertook the task three times: (i) using an optimally selected spectral filter; (ii) the subjects were randomly assigned to two groups with group 1 using an optimal filter for two weeks, whereas group 2 used a grey filter for two weeks; (iii) the groups were crossed over with group 1 using a grey filter for a further two weeks and group 2 given an optimal filter, before undertaking the task for the final time. Initial use of an optimal spectral filter improved visual search response time but not error scores in the stroke cohort. Prolonged use of neither an optimal nor a grey filter improved response time or reduced error scores. In fact, response times increased with the filter, regardless of its type, for stroke and control subjects; this outcome may be due to contrast reduction or a reflection of task design, given that significant practice effects were noted.

Statistical analysis of latent generalized correlation matrix estimation in transelliptical distribution

PubMed Central

Han, Fang; Liu, Han

2016-01-01

Correlation matrix plays a key role in many multivariate methods (e.g., graphical model estimation and factor analysis). The current state-of-the-art in estimating large correlation matrices focuses on the use of Pearson’s sample correlation matrix. Although Pearson’s sample correlation matrix enjoys various good properties under Gaussian models, its not an effective estimator when facing heavy-tail distributions with possible outliers. As a robust alternative, Han and Liu (2013b) advocated the use of a transformed version of the Kendall’s tau sample correlation matrix in estimating high dimensional latent generalized correlation matrix under the transelliptical distribution family (or elliptical copula). The transelliptical family assumes that after unspecified marginal monotone transformations, the data follow an elliptical distribution. In this paper, we study the theoretical properties of the Kendall’s tau sample correlation matrix and its transformed version proposed in Han and Liu (2013b) for estimating the population Kendall’s tau correlation matrix and the latent Pearson’s correlation matrix under both spectral and restricted spectral norms. With regard to the spectral norm, we highlight the role of “effective rank” in quantifying the rate of convergence. With regard to the restricted spectral norm, we for the first time present a “sign subgaussian condition” which is sufficient to guarantee that the rank-based correlation matrix estimator attains the optimal rate of convergence. In both cases, we do not need any moment condition. PMID:28337068

Time and frequency constrained sonar signal design for optimal detection of elastic objects.

PubMed

Hamschin, Brandon; Loughlin, Patrick J

2013-04-01

In this paper, the task of model-based transmit signal design for optimizing detection is considered. Building on past work that designs the spectral magnitude for optimizing detection, two methods for synthesizing minimum duration signals with this spectral magnitude are developed. The methods are applied to the design of signals that are optimal for detecting elastic objects in the presence of additive noise and self-noise. Elastic objects are modeled as linear time-invariant systems with known impulse responses, while additive noise (e.g., ocean noise or receiver noise) and acoustic self-noise (e.g., reverberation or clutter) are modeled as stationary Gaussian random processes with known power spectral densities. The first approach finds the waveform that preserves the optimal spectral magnitude while achieving the minimum temporal duration. The second approach yields a finite-length time-domain sequence by maximizing temporal energy concentration, subject to the constraint that the spectral magnitude is close (in a least-squares sense) to the optimal spectral magnitude. The two approaches are then connected analytically, showing the former is a limiting case of the latter. Simulation examples that illustrate the theory are accompanied by discussions that address practical applicability and how one might satisfy the need for target and environmental models in the real-world.

Application of surface enhanced Raman scattering and competitive adaptive reweighted sampling on detecting furfural dissolved in transformer oil

NASA Astrophysics Data System (ADS)

Chen, Weigen; Zou, Jingxin; Wan, Fu; Fan, Zhou; Yang, Dingkun

2018-03-01

Detecting the dissolving furfural in mineral oil is an essential technical method to evaluate the ageing condition of oil-paper insulation and the degradation of mechanical properties. Compared with the traditional detection method, Raman spectroscopy is obviously convenient and timesaving in operation. This study explored the method of applying surface enhanced Raman scattering (SERS) on quantitative analysis of the furfural dissolved in oil. Oil solution with different concentration of furfural were prepared and calibrated by high-performance liquid chromatography. Confocal laser Raman spectroscopy (CLRS) and SERS technology were employed to acquire Raman spectral data. Monte Carlo cross validation (MCCV) was used to eliminate the outliers in sample set, then competitive adaptive reweighted sampling (CARS) was developed to select an optimal combination of informative variables that most reflect the chemical properties of concern. Based on selected Raman spectral features, support vector machine (SVM) combined with particle swarm algorithm (PSO) was used to set up a furfural quantitative analysis model. Finally, the generalization ability and prediction precision of the established method were verified by the samples made in lab. In summary, a new spectral method is proposed to quickly detect furfural in oil, which lays a foundation for evaluating the ageing of oil-paper insulation in oil immersed electrical equipment.

Resampling algorithm for the Spatial Infrared Imaging Telescope (SPIRIT III) Fourier transform spectrometer

NASA Astrophysics Data System (ADS)

Sargent, Steven D.; Greenman, Mark E.; Hansen, Scott M.

1998-11-01

The Spatial Infrared Imaging Telescope (SPIRIT III) is the primary sensor aboard the Midcourse Space Experiment (MSX), which was launched 24 April 1996. SPIRIT III included a Fourier transform spectrometer that collected terrestrial and celestial background phenomenology data for the Ballistic Missile Defense Organization (BMDO). This spectrometer used a helium-neon reference laser to measure the optical path difference (OPD) in the spectrometer and to command the analog-to-digital conversion of the infrared detector signals, thereby ensuring the data were sampled at precise increments of OPD. Spectrometer data must be sampled at accurate increments of OPD to optimize the spectral resolution and spectral position of the transformed spectra. Unfortunately, a failure in the power supply preregulator at the MSX spacecraft/SPIRIT III interface early in the mission forced the spectrometer to be operated without the reference laser until a failure investigation was completed. During this time data were collected in a backup mode that used an electronic clock to sample the data. These data were sampled evenly in time, and because the scan velocity varied, at nonuniform increments of OPD. The scan velocity profile depended on scan direction and scan length, and varied over time, greatly degrading the spectral resolution and spectral and radiometric accuracy of the measurements. The Convert software used to process the SPIRIT III data was modified to resample the clock-sampled data at even increments of OPD, using scan velocity profiles determined from ground and on-orbit data, greatly improving the quality of the clock-sampled data. This paper presents the resampling algorithm, the characterization of the scan velocity profiles, and the results of applying the resampling algorithm to on-orbit data.

[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.

Setting the magic angle for fast magic-angle spinning probes.

PubMed

Penzel, Susanne; Smith, Albert A; Ernst, Matthias; Meier, Beat H

2018-06-15

Fast magic-angle spinning, coupled with 1 H detection is a powerful method to improve spectral resolution and signal to noise in solid-state NMR spectra. Commercial probes now provide spinning frequencies in excess of 100 kHz. Then, one has sufficient resolution in the 1 H dimension to directly detect protons, which have a gyromagnetic ratio approximately four times larger than 13 C spins. However, the gains in sensitivity can quickly be lost if the rotation angle is not set precisely. The most common method of magic-angle calibration is to optimize the number of rotary echoes, or sideband intensity, observed on a sample of KBr. However, this typically uses relatively low spinning frequencies, where the spinning of fast-MAS probes is often unstable, and detection on the 13 C channel, for which fast-MAS probes are typically not optimized. Therefore, we compare the KBr-based optimization of the magic angle with two alternative approaches: optimization of the splitting observed in 13 C-labeled glycine-ethylester on the carbonyl due to the Cα-C' J-coupling, or optimization of the H-N J-coupling spin echo in the protein sample itself. The latter method has the particular advantage that no separate sample is necessary for the magic-angle optimization. Copyright © 2018. Published by Elsevier Inc.

Optimization of LC-Orbitrap-HRMS acquisition and MZmine 2 data processing for nontarget screening of environmental samples using design of experiments.

PubMed

Hu, Meng; Krauss, Martin; Brack, Werner; Schulze, Tobias

2016-11-01

Liquid chromatography-high resolution mass spectrometry (LC-HRMS) is a well-established technique for nontarget screening of contaminants in complex environmental samples. Automatic peak detection is essential, but its performance has only rarely been assessed and optimized so far. With the aim to fill this gap, we used pristine water extracts spiked with 78 contaminants as a test case to evaluate and optimize chromatogram and spectral data processing. To assess whether data acquisition strategies have a significant impact on peak detection, three values of MS cycle time (CT) of an LTQ Orbitrap instrument were tested. Furthermore, the key parameter settings of the data processing software MZmine 2 were optimized to detect the maximum number of target peaks from the samples by the design of experiments (DoE) approach and compared to a manual evaluation. The results indicate that short CT significantly improves the quality of automatic peak detection, which means that full scan acquisition without additional MS 2 experiments is suggested for nontarget screening. MZmine 2 detected 75-100 % of the peaks compared to manual peak detection at an intensity level of 10 5 in a validation dataset on both spiked and real water samples under optimal parameter settings. Finally, we provide an optimization workflow of MZmine 2 for LC-HRMS data processing that is applicable for environmental samples for nontarget screening. The results also show that the DoE approach is useful and effort-saving for optimizing data processing parameters. Graphical Abstract ᅟ.

Optimization of data retrieval process for spectroscopic CO2 isotopologue ratio measurements

NASA Astrophysics Data System (ADS)

Hovorka, J.; Čermák, P.; Veis, P.

2017-05-01

In this work, a numerical model was developed for critical evaluation of the 13CO2/12CO2 ratio retrievals ( Δ δ value) from laser absorption spectra. The goal of the analysis was to determine the dependency of the absolute error of δ on different experimental parameters, in order to find the optimal conditions for isotopic ratio retrievals without using calibrated reference samples. In our study, the target precision for Δ δ was set at a level of ≤slant 1 %. The analysis was performed in the spectral range of the {ν1}+{ν3} CO2 band at 1.6 μm, with the theoretical data originating from the HITRAN database. The proposed fitting algorithm allowed efficient compensation of the interference from weak transitions which are not well recognizable in a single spectrum. This effect was found to make a dominant contribution to the Δ δ value. Next, the optimal conditions for such an experiment regarding the pressure, spectral range and spectrum noise were found and discussed from the perspective of widely tunable laser applications.

Study of 3-Ethylamino-but-2-enoic acid phenylamide as a new ligand for preconcentration of lanthanides from aqueous media by liquid-liquid extraction prior to ICP-MS analysis.

PubMed

Varbanova, Evelina K; Angelov, Plamen A; Stefanova, Violeta M

2016-11-01

In the present work the potential of a new ligand 3-Ethylamino-but-2-enoic acid phenylamide (representing the class of enaminones) for selective preconcentration of lanthanides (La, Ce, Eu, Gd and Er) from aqueous medium is examined. Liquid-liquid extraction parameters, such as pH of the water phase, type and volume of organic solvent, quantity of ligand and reaction time are optimized on model solutions. Recovery of lanthanides by re-extraction with nitric acid makes the LLE procedure compatible with Inductively Coupled Plasma Mass Spectrometry. Spectral and non-spectral interferences are studied. Two isotopes per element are measured (with exception of La) for dynamic evaluation of the potential risk of spectral interference in variable real samples. The selectivity of complex formation reaction towards concomitant alkali and alkali-earth elements eliminates the interferences from sample matrix. Subjecting the standards to the optimized extraction procedure in combination with Re as internal standard is recommended as calibration strategy. The accuracy of developed method is approved by analysis of CRM Bush branches and leaves (NCS DC 73348) and recovery of spiked water and plant samples. The method's limits of detection for both studied objects are in the ranges from 0.2 ((158)Gd) to 3.7 ((139)La) ngl(-1) and 0.02 ((158)Gd) to 0.37((139)La) ngg(-1) for waters and plants respectively. The studied compound is an effective new ligand for preconcentration/separation of lanthanides from aqueous medium by LLE and subsequent determination by ICP-MS. Copyright © 2016 Elsevier B.V. All rights reserved.

Optimization of laser energy deposition for single-shot high aspect-ratio microstructuring of thick BK7 glass

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

Garzillo, Valerio; Grigutis, Robertas; Jukna, Vytautas

We investigate the generation of high aspect ratio microstructures across 0.7 mm thick glass by means of single shot Bessel beam laser direct writing. We study the effect on the photoinscription of the cone angle, as well as of the energy and duration of the ultrashort laser pulse. The aim of the study is to optimize the parameters for the writing of a regular microstructure due to index modification along the whole sample thickness. By using a spectrally resolved single pulse transmission diagnostics at the output surface of the glass, we correlate the single shot material modification with observations of themore » absorption in different portions of the retrieved spectra, and with the absence or presence of spectral modulation. Numerical simulations of the evolution of the Bessel pulse intensity and of the energy deposition inside the sample help us interpret the experimental results that suggest to use picosecond pulses for an efficient and more regular energy deposition. Picosecond pulses take advantage of nonlinear plasma absorption and avoid temporal dynamics effects which can compromise the stationarity of the Bessel beam propagation.« less

Femtosecond pump/supercontinuum-probe spectroscopy: optimized setup and signal analysis for single-shot spectral referencing.

PubMed

Dobryakov, A L; Kovalenko, S A; Weigel, A; Pérez-Lustres, J L; Lange, J; Müller, A; Ernsting, N P

2010-11-01

A setup for pump/supercontinuum-probe spectroscopy is described which (i) is optimized to cancel fluctuations of the probe light by single-shot referencing, and (ii) extends the probe range into the near-uv (1000-270 nm). Reflective optics allow 50 μm spot size in the sample and upon entry into two separate spectrographs. The correlation γ(same) between sample and reference readings of probe light level at every pixel exceeds 0.99, compared to γ(consec)<0.92 reported for consecutive referencing. Statistical analysis provides the confidence interval of the induced optical density, ΔOD. For demonstration we first examine a dye (Hoechst 33258) bound in the minor groove of double-stranded DNA. A weak 1.1 ps spectral oscillation in the fluorescence region, assigned to DNA breathing, is shown to be significant. A second example concerns the weak vibrational structure around t=0 which reflects stimulated Raman processes. With 1% fluctuations of probe power, baseline noise for a transient absorption spectrum becomes 25 μOD rms in 1 s at 1 kHz, allowing to record resonance Raman spectra of flavine adenine dinucleotide in the S(0) and S(1) state.

Dynamic terahertz spectroscopy of gas molecules mixed with unwanted aerosol under atmospheric pressure using fibre-based asynchronous-optical-sampling terahertz time-domain spectroscopy

PubMed Central

Hsieh, Yi-Da; Nakamura, Shota; Abdelsalam, Dahi Ghareab; Minamikawa, Takeo; Mizutani, Yasuhiro; Yamamoto, Hirotsugu; Iwata, Tetsuo; Hindle, Francis; Yasui, Takeshi

2016-01-01

Terahertz (THz) spectroscopy is a promising method for analysing polar gas molecules mixed with unwanted aerosols due to its ability to obtain spectral fingerprints of rotational transition and immunity to aerosol scattering. In this article, dynamic THz spectroscopy of acetonitrile (CH3CN) gas was performed in the presence of smoke under the atmospheric pressure using a fibre-based, asynchronous-optical-sampling THz time-domain spectrometer. To match THz spectral signatures of gas molecules at atmospheric pressure, the spectral resolution was optimized to 1 GHz with a measurement rate of 1 Hz. The spectral overlapping of closely packed absorption lines significantly boosted the detection limit to 200 ppm when considering all the spectral contributions of the numerous absorption lines from 0.2 THz to 1 THz. Temporal changes of the CH3CN gas concentration were monitored under the smoky condition at the atmospheric pressure during volatilization of CH3CN droplets and the following diffusion of the volatilized CH3CN gas without the influence of scattering or absorption by the smoke. This system will be a powerful tool for real-time monitoring of target gases in practical applications of gas analysis in the atmospheric pressure, such as combustion processes or fire accident. PMID:27301319

Dynamic terahertz spectroscopy of gas molecules mixed with unwanted aerosol under atmospheric pressure using fibre-based asynchronous-optical-sampling terahertz time-domain spectroscopy

NASA Astrophysics Data System (ADS)

Hsieh, Yi-Da; Nakamura, Shota; Abdelsalam, Dahi Ghareab; Minamikawa, Takeo; Mizutani, Yasuhiro; Yamamoto, Hirotsugu; Iwata, Tetsuo; Hindle, Francis; Yasui, Takeshi

2016-06-01

Terahertz (THz) spectroscopy is a promising method for analysing polar gas molecules mixed with unwanted aerosols due to its ability to obtain spectral fingerprints of rotational transition and immunity to aerosol scattering. In this article, dynamic THz spectroscopy of acetonitrile (CH3CN) gas was performed in the presence of smoke under the atmospheric pressure using a fibre-based, asynchronous-optical-sampling THz time-domain spectrometer. To match THz spectral signatures of gas molecules at atmospheric pressure, the spectral resolution was optimized to 1 GHz with a measurement rate of 1 Hz. The spectral overlapping of closely packed absorption lines significantly boosted the detection limit to 200 ppm when considering all the spectral contributions of the numerous absorption lines from 0.2 THz to 1 THz. Temporal changes of the CH3CN gas concentration were monitored under the smoky condition at the atmospheric pressure during volatilization of CH3CN droplets and the following diffusion of the volatilized CH3CN gas without the influence of scattering or absorption by the smoke. This system will be a powerful tool for real-time monitoring of target gases in practical applications of gas analysis in the atmospheric pressure, such as combustion processes or fire accident.

Dynamic terahertz spectroscopy of gas molecules mixed with unwanted aerosol under atmospheric pressure using fibre-based asynchronous-optical-sampling terahertz time-domain spectroscopy.

PubMed

Hsieh, Yi-Da; Nakamura, Shota; Abdelsalam, Dahi Ghareab; Minamikawa, Takeo; Mizutani, Yasuhiro; Yamamoto, Hirotsugu; Iwata, Tetsuo; Hindle, Francis; Yasui, Takeshi

2016-06-15

Terahertz (THz) spectroscopy is a promising method for analysing polar gas molecules mixed with unwanted aerosols due to its ability to obtain spectral fingerprints of rotational transition and immunity to aerosol scattering. In this article, dynamic THz spectroscopy of acetonitrile (CH3CN) gas was performed in the presence of smoke under the atmospheric pressure using a fibre-based, asynchronous-optical-sampling THz time-domain spectrometer. To match THz spectral signatures of gas molecules at atmospheric pressure, the spectral resolution was optimized to 1 GHz with a measurement rate of 1 Hz. The spectral overlapping of closely packed absorption lines significantly boosted the detection limit to 200 ppm when considering all the spectral contributions of the numerous absorption lines from 0.2 THz to 1 THz. Temporal changes of the CH3CN gas concentration were monitored under the smoky condition at the atmospheric pressure during volatilization of CH3CN droplets and the following diffusion of the volatilized CH3CN gas without the influence of scattering or absorption by the smoke. This system will be a powerful tool for real-time monitoring of target gases in practical applications of gas analysis in the atmospheric pressure, such as combustion processes or fire accident.

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

PubMed

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

2014-04-01

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

A novel built-up spectral index developed by using multiobjective particle-swarm-optimization technique

NASA Astrophysics Data System (ADS)

Sameen, Maher Ibrahim; Pradhan, Biswajeet

2016-06-01

In this study, we propose a novel built-up spectral index which was developed by using particle-swarm-optimization (PSO) technique for Worldview-2 images. PSO was used to select the relevant bands from the eight (8) spectral bands of Worldview-2 image and then were used for index development. Multiobiective optimization was used to minimize the number of selected spectral bands and to maximize the classification accuracy. The results showed that the most important and relevant spectral bands among the eight (8) bands for built-up area extraction are band4 (yellow) and band7 (NIR1). Using those relevant spectral bands, the final spectral index was form ulated by developing a normalized band ratio. The validation of the classification result using the proposed spectral index showed that our novel spectral index performs well compared to the existing WV -BI index. The accuracy assessment showed that the new proposed spectral index could extract built-up areas from Worldview-2 image with an area under curve (AUC) of (0.76) indicating the effectiveness of the developed spectral index. Further improvement could be done by using several datasets during the index development process to ensure the transferability of the index to other datasets and study areas.

[Non-destructive detection research for hollow heart of potato based on semi-transmission hyperspectral imaging and SVM].

PubMed

Huang, Tao; Li, Xiao-yu; Xu, Meng-ling; Jin, Rui; Ku, Jing; Xu, Sen-miao; Wu, Zhen-zhong

2015-01-01

The quality of potato is directly related to their edible value and industrial value. Hollow heart of potato, as a physiological disease occurred inside the tuber, is difficult to be detected. This paper put forward a non-destructive detection method by using semi-transmission hyperspectral imaging with support vector machine (SVM) to detect hollow heart of potato. Compared to reflection and transmission hyperspectral image, semi-transmission hyperspectral image can get clearer image which contains the internal quality information of agricultural products. In this study, 224 potato samples (149 normal samples and 75 hollow samples) were selected as the research object, and semi-transmission hyperspectral image acquisition system was constructed to acquire the hyperspectral images (390-1 040 nn) of the potato samples, and then the average spectrum of region of interest were extracted for spectral characteristics analysis. Normalize was used to preprocess the original spectrum, and prediction model were developed based on SVM using all wave bands, the accurate recognition rate of test set is only 87. 5%. In order to simplify the model competitive.adaptive reweighed sampling algorithm (CARS) and successive projection algorithm (SPA) were utilized to select important variables from the all 520 spectral variables and 8 variables were selected (454, 601, 639, 664, 748, 827, 874 and 936 nm). 94. 64% of the accurate recognition rate of test set was obtained by using the 8 variables to develop SVM model. Parameter optimization algorithms, including artificial fish swarm algorithm (AFSA), genetic algorithm (GA) and grid search algorithm, were used to optimize the SVM model parameters: penalty parameter c and kernel parameter g. After comparative analysis, AFSA, a new bionic optimization algorithm based on the foraging behavior of fish swarm, was proved to get the optimal model parameter (c=10. 659 1, g=0. 349 7), and the recognition accuracy of 10% were obtained for the AFSA-SVM model. The results indicate that combining the semi-transmission hyperspectral imaging technology with CARS-SPA and AFSA-SVM can accurately detect hollow heart of potato, and also provide technical support for rapid non-destructive detecting of hollow heart of potato.

Spectral risk measures: the risk quadrangle and optimal approximation

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

Kouri, Drew P.

We develop a general risk quadrangle that gives rise to a large class of spectral risk measures. The statistic of this new risk quadrangle is the average value-at-risk at a specific confidence level. As such, this risk quadrangle generates a continuum of error measures that can be used for superquantile regression. For risk-averse optimization, we introduce an optimal approximation of spectral risk measures using quadrature. Lastly, we prove the consistency of this approximation and demonstrate our results through numerical examples.

Spectral risk measures: the risk quadrangle and optimal approximation

DOE PAGES

Kouri, Drew P.

2018-05-24

We develop a general risk quadrangle that gives rise to a large class of spectral risk measures. The statistic of this new risk quadrangle is the average value-at-risk at a specific confidence level. As such, this risk quadrangle generates a continuum of error measures that can be used for superquantile regression. For risk-averse optimization, we introduce an optimal approximation of spectral risk measures using quadrature. Lastly, we prove the consistency of this approximation and demonstrate our results through numerical examples.

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.

Complementary shifts in photoreceptor spectral tuning unlock the full adaptive potential of ultraviolet vision in birds

PubMed Central

Toomey, Matthew B; Lind, Olle; Frederiksen, Rikard; Curley, Robert W; Riedl, Ken M; Wilby, David; Schwartz, Steven J; Witt, Christopher C; Harrison, Earl H; Roberts, Nicholas W; Vorobyev, Misha; McGraw, Kevin J; Cornwall, M Carter; Kelber, Almut; Corbo, Joseph C

2016-01-01

Color vision in birds is mediated by four types of cone photoreceptors whose maximal sensitivities (λmax) are evenly spaced across the light spectrum. In the course of avian evolution, the λmax of the most shortwave-sensitive cone, SWS1, has switched between violet (λmax > 400 nm) and ultraviolet (λmax < 380 nm) multiple times. This shift of the SWS1 opsin is accompanied by a corresponding short-wavelength shift in the spectrally adjacent SWS2 cone. Here, we show that SWS2 cone spectral tuning is mediated by modulating the ratio of two apocarotenoids, galloxanthin and 11’,12’-dihydrogalloxanthin, which act as intracellular spectral filters in this cell type. We propose an enzymatic pathway that mediates the differential production of these apocarotenoids in the avian retina, and we use color vision modeling to demonstrate how correlated evolution of spectral tuning is necessary to achieve even sampling of the light spectrum and thereby maintain near-optimal color discrimination. DOI: http://dx.doi.org/10.7554/eLife.15675.001 PMID:27402384

Effects of Spectral Overlays on Reading Performance of Brazilian Elementary School Children.

PubMed

Garcia, Ana Carla Oliveira; Momensohn-Santos, Teresa Maria; Vilhena, Douglas de Araújo

2018-03-20

To investigate the effects of spectral overlays on reading performance of Brazilian elementary school children. Sixty-eight children (aged 9-12 years) enrolled in the 5th and 6th grade were included in the study. The Rate of Reading Test (RRT - Brazilian Portuguese version) was used to evaluate reading speed and the Irlen Reading Perceptual Scale was used to allocate the sample according to reading difficulty/discomfort symptoms and to define the optimal spectral overlays. A total of 13% of the children presented an improvement of at least 15% in reading speed with the use of spectral overlays. Pupils with severe reading difficulties tended to have more improvement in RRT with spectral overlays. Children with severe reading discomfort obtained the highest gains in RRT, with an average of 9.6% improvement with intervention, compared to a decrease of -8.2% in the control group. Participants with severe discomfort had an odds ratio of 3.36 to improve reading speed with intervention compared to the control group. The use of spectral overlays can improve reading performance, particularly in those children with severe visual discomfort. © 2018 S. Karger AG, Basel.

Spectral anomaly methods for aerial detection using KUT nuisance rejection

NASA Astrophysics Data System (ADS)

Detwiler, R. S.; Pfund, D. M.; Myjak, M. J.; Kulisek, J. A.; Seifert, C. E.

2015-06-01

This work discusses the application and optimization of a spectral anomaly method for the real-time detection of gamma radiation sources from an aerial helicopter platform. Aerial detection presents several key challenges over ground-based detection. For one, larger and more rapid background fluctuations are typical due to higher speeds, larger field of view, and geographically induced background changes. As well, the possible large altitude or stand-off distance variations cause significant steps in background count rate as well as spectral changes due to increased gamma-ray scatter with detection at higher altitudes. The work here details the adaptation and optimization of the PNNL-developed algorithm Nuisance-Rejecting Spectral Comparison Ratios for Anomaly Detection (NSCRAD), a spectral anomaly method previously developed for ground-based applications, for an aerial platform. The algorithm has been optimized for two multi-detector systems; a NaI(Tl)-detector-based system and a CsI detector array. The optimization here details the adaptation of the spectral windows for a particular set of target sources to aerial detection and the tailoring for the specific detectors. As well, the methodology and results for background rejection methods optimized for the aerial gamma-ray detection using Potassium, Uranium and Thorium (KUT) nuisance rejection are shown. Results indicate that use of a realistic KUT nuisance rejection may eliminate metric rises due to background magnitude and spectral steps encountered in aerial detection due to altitude changes and geographically induced steps such as at land-water interfaces.

Pick a Color MARIA: Adaptive Sampling Enables the Rapid Identification of Complex Perovskite Nanocrystal Compositions with Defined Emission Characteristics.

PubMed

Bezinge, Leonard; Maceiczyk, Richard M; Lignos, Ioannis; Kovalenko, Maksym V; deMello, Andrew J

2018-06-06

Recent advances in the development of hybrid organic-inorganic lead halide perovskite (LHP) nanocrystals (NCs) have demonstrated their versatility and potential application in photovoltaics and as light sources through compositional tuning of optical properties. That said, due to their compositional complexity, the targeted synthesis of mixed-cation and/or mixed-halide LHP NCs still represents an immense challenge for traditional batch-scale chemistry. To address this limitation, we herein report the integration of a high-throughput segmented-flow microfluidic reactor and a self-optimizing algorithm for the synthesis of NCs with defined emission properties. The algorithm, named Multiparametric Automated Regression Kriging Interpolation and Adaptive Sampling (MARIA), iteratively computes optimal sampling points at each stage of an experimental sequence to reach a target emission peak wavelength based on spectroscopic measurements. We demonstrate the efficacy of the method through the synthesis of multinary LHP NCs, (Cs/FA)Pb(I/Br) 3 (FA = formamidinium) and (Rb/Cs/FA)Pb(I/Br) 3 NCs, using MARIA to rapidly identify reagent concentrations that yield user-defined photoluminescence peak wavelengths in the green-red spectral region. The procedure returns a robust model around a target output in far fewer measurements than systematic screening of parametric space and additionally enables the prediction of other spectral properties, such as, full-width at half-maximum and intensity, for conditions yielding NCs with similar emission peak wavelength.

Thermal Infrared Spectral Imager for Airborne Science Applications

NASA Technical Reports Server (NTRS)

Johnson, William R.; Hook, Simon J.; Mouroulis, Pantazis; Wilson, Daniel W.; Gunapala, Sarath D.; Hill, Cory J.; Mumolo, Jason M.; Eng, Bjorn T.

2009-01-01

An airborne thermal hyperspectral imager is under development which utilizes the compact Dyson optical configuration and quantum well infrared photo detector (QWIP) focal plane array. The Dyson configuration uses a single monolithic prism-like grating design which allows for a high throughput instrument (F/1.6) with minimal ghosting, stray-light and large swath width. The configuration has the potential to be the optimal imaging spectroscopy solution for lighter-than-air (LTA) vehicles and unmanned aerial vehicles (UAV) due to its small form factor and relatively low power requirements. The planned instrument specifications are discussed as well as design trade-offs. Calibration testing results (noise equivalent temperature difference, spectral linearity and spectral bandwidth) and laboratory emissivity plots from samples are shown using an operational testbed unit which has similar specifications as the final airborne system. Field testing of the testbed unit was performed to acquire plots of apparent emissivity for various known standard minerals (such as quartz). A comparison is made using data from the ASTER spectral library.

[Spectral scatter correction of coal samples based on quasi-linear local weighted method].

PubMed

Lei, Meng; Li, Ming; Ma, Xiao-Ping; Miao, Yan-Zi; Wang, Jian-Sheng

2014-07-01

The present paper puts forth a new spectral correction method based on quasi-linear expression and local weighted function. The first stage of the method is to search 3 quasi-linear expressions to replace the original linear expression in MSC method, such as quadratic, cubic and growth curve expression. Then the local weighted function is constructed by introducing 4 kernel functions, such as Gaussian, Epanechnikov, Biweight and Triweight kernel function. After adding the function in the basic estimation equation, the dependency between the original and ideal spectra is described more accurately and meticulously at each wavelength point. Furthermore, two analytical models were established respectively based on PLS and PCA-BP neural network method, which can be used for estimating the accuracy of corrected spectra. At last, the optimal correction mode was determined by the analytical results with different combination of quasi-linear expression and local weighted function. The spectra of the same coal sample have different noise ratios while the coal sample was prepared under different particle sizes. To validate the effectiveness of this method, the experiment analyzed the correction results of 3 spectral data sets with the particle sizes of 0.2, 1 and 3 mm. The results show that the proposed method can eliminate the scattering influence, and also can enhance the information of spectral peaks. This paper proves a more efficient way to enhance the correlation between corrected spectra and coal qualities significantly, and improve the accuracy and stability of the analytical model substantially.

A reconstruction algorithm for three-dimensional object-space data using spatial-spectral multiplexing

NASA Astrophysics Data System (ADS)

Wu, Zhejun; Kudenov, Michael W.

2017-05-01

This paper presents a reconstruction algorithm for the Spatial-Spectral Multiplexing (SSM) optical system. The goal of this algorithm is to recover the three-dimensional spatial and spectral information of a scene, given that a one-dimensional spectrometer array is used to sample the pupil of the spatial-spectral modulator. The challenge of the reconstruction is that the non-parametric representation of the three-dimensional spatial and spectral object requires a large number of variables, thus leading to an underdetermined linear system that is hard to uniquely recover. We propose to reparameterize the spectrum using B-spline functions to reduce the number of unknown variables. Our reconstruction algorithm then solves the improved linear system via a least- square optimization of such B-spline coefficients with additional spatial smoothness regularization. The ground truth object and the optical model for the measurement matrix are simulated with both spatial and spectral assumptions according to a realistic field of view. In order to test the robustness of the algorithm, we add Poisson noise to the measurement and test on both two-dimensional and three-dimensional spatial and spectral scenes. Our analysis shows that the root mean square error of the recovered results can be achieved within 5.15%.

Eigenvalue-eigenvector decomposition (EED) analysis of dissimilarity and covariance matrix obtained from total synchronous fluorescence spectral (TSFS) data sets of herbal preparations: Optimizing the classification approach

NASA Astrophysics Data System (ADS)

Tarai, Madhumita; Kumar, Keshav; Divya, O.; Bairi, Partha; Mishra, Kishor Kumar; Mishra, Ashok Kumar

2017-09-01

The present work compares the dissimilarity and covariance based unsupervised chemometric classification approaches by taking the total synchronous fluorescence spectroscopy data sets acquired for the cumin and non-cumin based herbal preparations. The conventional decomposition method involves eigenvalue-eigenvector analysis of the covariance of the data set and finds the factors that can explain the overall major sources of variation present in the data set. The conventional approach does this irrespective of the fact that the samples belong to intrinsically different groups and hence leads to poor class separation. The present work shows that classification of such samples can be optimized by performing the eigenvalue-eigenvector decomposition on the pair-wise dissimilarity matrix.

All-optical on-chip sensor for high refractive index sensing

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

Liu, Yazhao; Kavli Institute of Nanoscience, Delft University of Technology, Lorentzweg 1, 2628 CJ, Delft; Salemink, H. W. M., E-mail: H.Salemink@science.ru.nl

2015-01-19

A highly sensitive sensor design based on two-dimensional photonic crystal cavity is demonstrated. The geometric structure of the cavity is modified to gain a high quality factor, which enables a sensitive refractive index sensing. A group of slots with optimized parameters is created in the cavity. The existence of the slots enhances the light-matter interactions between confined photons and analytes. The interactions result in large wavelength shifts in the transmission spectra and are denoted by high sensitivities. Experiments show that a change in refractive index of Δn ∼ 0.12 between water and oil sample 1 causes a spectral shift of 23.5 nm, andmore » the spectral shift between two oil samples is 5.1 nm for Δn ∼ 0.039. These results are in good agreement with simulations, which are 21.3 and 7.39 nm for the same index changes.« less

Point to point multispectral light projection applied to cultural heritage

NASA Astrophysics Data System (ADS)

Vázquez, D.; Alvarez, A.; Canabal, H.; Garcia, A.; Mayorga, S.; Muro, C.; Galan, T.

2017-09-01

Use of new of light sources based on LED technology should allow the develop of systems that combine conservation and exhibition requirements and allow to make these art goods available to the next generations according to sustainability principles. The goal of this work is to develop light systems and sources with an optimized spectral distribution for each specific point of the art piece. This optimization process implies to maximize the color fidelity reproduction and the same time to minimize the photochemical damage. Perceived color under these sources will be similar (metameric) to technical requirements given by the restoration team uncharged of the conservation and exhibition of the goods of art. Depending of the fragility of the exposed art objects (i.e. spectral responsivity of the material) the irradiance must be kept under a critical level. Therefore, it is necessary to develop a mathematical model that simulates with enough accuracy both the visual effect of the illumination and the photochemical impact of the radiation. Spectral reflectance of a reference painting The mathematical model is based on a merit function that optimized the individual intensity of the LED-light sources taking into account the damage function of the material and color space coordinates. Moreover the algorithm used weights for damage and color fidelity in order to adapt the model to a specific museal application. In this work we show a sample of this technology applied to a picture of Sorolla (1863-1923) an important Spanish painter title "woman walking at the beach".

Optimization of light quality from color mixing light-emitting diode systems for general lighting

NASA Astrophysics Data System (ADS)

Thorseth, Anders

2012-03-01

Given the problem of metamerisms inherent in color mixing in light-emitting diode (LED) systems with more than three distinct colors, a method for optimizing the spectral output of multicolor LED system with regards to standardized light quality parameters has been developed. The composite spectral power distribution from the LEDs are simulated using spectral radiometric measurements of single commercially available LEDs for varying input power, to account for the efficiency droop and other non-linear effects in electrical power vs. light output. The method uses electrical input powers as input parameters in a randomized steepest decent optimization. The resulting spectral power distributions are evaluated with regard to the light quality using the standard characteristics: CIE color rendering index, correlated color temperature and chromaticity distance. The results indicate Pareto optimal boundaries for each system, mapping the capabilities of the simulated lighting systems with regard to the light quality characteristics.

Determining the Optimal Spectral Sampling Frequency and Uncertainty Thresholds for Hyperspectral Remote Sensing of Ocean Color

NASA Technical Reports Server (NTRS)

Vandermeulen, Ryan A.; Mannino, Antonio; Neeley, Aimee; Werdell, Jeremy; Arnone, Robert

2017-01-01

Using a modified geostatistical technique, empirical variograms were constructed from the first derivative of several diverse remote sensing reflectance and phytoplankton absorbance spectra to describe how data points are correlated with distance across the spectra. The maximum rate of information gain is measured as a function of the kurtosis associated with the Gaussian structure of the output, and is determined for discrete segments of spectra obtained from a variety of water types (turbid river filaments, coastal waters, shelf waters, a dense Microcystis bloom, and oligotrophic waters), as well as individual and mixed phytoplankton functional types (PFTs; diatoms, chlorophytes, cyanobacteria, coccolithophores). Results show that a continuous spectrum of 5 to 7 nm spectral resolution is optimal to resolve the variability across mixed reflectance and absorbance spectra. In addition, the impact of uncertainty on subsequent derivative analysis is assessed, showing that a limit of 3 Gaussian noise (SNR 66) is tolerated without smoothing the spectrum, and 13 (SNR 15) noise is tolerated with smoothing.

Optimized LWIR enhancement of nanosecond and femtosecond LIBS uranium emission

NASA Astrophysics Data System (ADS)

Akpovo, Codjo A.; Ford, Alan; Johnson, Lewis

2016-05-01

A carbon dioxide (CO2) transverse electrical breakdown in atmosphere (TEA), pulsed laser was used to enhance the laser-induced breakdown spectroscopy (LIBS) spectral signatures of uranium under nanosecond (ns) and femtosecond (fs) ablation. The peak areas of both ionic and neutral species increased by one order of magnitude for ns-ablation and two orders of magnitude for fs-ablation over LIBS when the CO2 TEA laser was used with samples of dried solutions of uranyl nitrate hexahydrate (UO2(NO3)2·6H2O) on silicon wafers. Electron temperature and density measurements show that the spectral emission improvement from using the TEA laser comes from plasma reheating.

Development of techniques for advanced optical contamination measurement with internal reflection spectroscopy, phase 1, volume 1

NASA Technical Reports Server (NTRS)

Hayes, J. D.

1972-01-01

The feasibility of monitoring volatile contaminants in a large space simulation chamber using techniques of internal reflection spectroscopy was demonstrated analytically and experimentally. The infrared spectral region was selected as the operational spectral range in order to provide unique identification of the contaminants along with sufficient sensitivity to detect trace contaminant concentrations. It was determined theoretically that a monolayer of the contaminants could be detected and identified using optimized experimental procedures. This ability was verified experimentally. Procedures were developed to correct the attenuated total reflectance spectra for thick sample distortion. However, by using two different element designs the need for such correction can be avoided.

Hyperspectral light sheet microscopy

NASA Astrophysics Data System (ADS)

Jahr, Wiebke; Schmid, Benjamin; Schmied, Christopher; Fahrbach, Florian O.; Huisken, Jan

2015-09-01

To study the development and interactions of cells and tissues, multiple fluorescent markers need to be imaged efficiently in a single living organism. Instead of acquiring individual colours sequentially with filters, we created a platform based on line-scanning light sheet microscopy to record the entire spectrum for each pixel in a three-dimensional volume. We evaluated data sets with varying spectral sampling and determined the optimal channel width to be around 5 nm. With the help of these data sets, we show that our setup outperforms filter-based approaches with regard to image quality and discrimination of fluorophores. By spectral unmixing we resolved overlapping fluorophores with up to nanometre resolution and removed autofluorescence in zebrafish and fruit fly embryos.

Hyperspectral light sheet microscopy.

PubMed

Jahr, Wiebke; Schmid, Benjamin; Schmied, Christopher; Fahrbach, Florian O; Huisken, Jan

2015-09-02

To study the development and interactions of cells and tissues, multiple fluorescent markers need to be imaged efficiently in a single living organism. Instead of acquiring individual colours sequentially with filters, we created a platform based on line-scanning light sheet microscopy to record the entire spectrum for each pixel in a three-dimensional volume. We evaluated data sets with varying spectral sampling and determined the optimal channel width to be around 5 nm. With the help of these data sets, we show that our setup outperforms filter-based approaches with regard to image quality and discrimination of fluorophores. By spectral unmixing we resolved overlapping fluorophores with up to nanometre resolution and removed autofluorescence in zebrafish and fruit fly embryos.

Optimal and robust control of quantum state transfer by shaping the spectral phase of ultrafast laser pulses.

PubMed

Guo, Yu; Dong, Daoyi; Shu, Chuan-Cun

2018-04-04

Achieving fast and efficient quantum state transfer is a fundamental task in physics, chemistry and quantum information science. However, the successful implementation of the perfect quantum state transfer also requires robustness under practically inevitable perturbative defects. Here, we demonstrate how an optimal and robust quantum state transfer can be achieved by shaping the spectral phase of an ultrafast laser pulse in the framework of frequency domain quantum optimal control theory. Our numerical simulations of the single dibenzoterrylene molecule as well as in atomic rubidium show that optimal and robust quantum state transfer via spectral phase modulated laser pulses can be achieved by incorporating a filtering function of the frequency into the optimization algorithm, which in turn has potential applications for ultrafast robust control of photochemical reactions.

Optimal trading strategies—a time series approach

NASA Astrophysics Data System (ADS)

Bebbington, Peter A.; Kühn, Reimer

2016-05-01

Motivated by recent advances in the spectral theory of auto-covariance matrices, we are led to revisit a reformulation of Markowitz’ mean-variance portfolio optimization approach in the time domain. In its simplest incarnation it applies to a single traded asset and allows an optimal trading strategy to be found which—for a given return—is minimally exposed to market price fluctuations. The model is initially investigated for a range of synthetic price processes, taken to be either second order stationary, or to exhibit second order stationary increments. Attention is paid to consequences of estimating auto-covariance matrices from small finite samples, and auto-covariance matrix cleaning strategies to mitigate against these are investigated. Finally we apply our framework to real world data.

Optimizing indoor illumination quality and energy efficiency using a spectrally tunable lighting system to augment natural daylight.

PubMed

Hertog, W; Llenas, A; Carreras, J

2015-11-30

This article demonstrates the benefits of complementing a daylight-lit environment with a spectrally tunable illumination system. The spectral components of daylight present in the room are measured by a low-cost miniature spectrophotometer and processed through a number of optimization algorithms, carefully trading color fidelity for energy efficiency. Spectrally-tunable luminaires provide only those wavelengths that ensure that either the final illumination spectrum inside the room is kept constant or carefully follows the dynamic spectral pattern of natural daylight. Analyzing the measured data proves that such a hybrid illumination system brings both unprecendented illumination quality and significant energy savings.

Photonic Jets for Strained-Layer Superlattice Infrared Photodetector Enhancement

DTIC Science & Technology

2014-06-25

top of a 40 µm photodetector fixed into position using a silicone rubber . As illustrated in Fig. 2, the spectral response was characterized before and...midwave-infrared spectral band (3-5 ?m). We optimized the design of these structures and experimentally demonstrated the increased sensitivity compared to...midwave-infrared spectral band (3-5 ?m). We optimized the design of these structures and experimentally demonstrated the increased sensitivity

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.

Optimal Wavelength Selection on Hyperspectral Data with Fused Lasso for Biomass Estimation of Tropical Rain Forest

NASA Astrophysics Data System (ADS)

Takayama, T.; Iwasaki, A.

2016-06-01

Above-ground biomass prediction of tropical rain forest using remote sensing data is of paramount importance to continuous large-area forest monitoring. Hyperspectral data can provide rich spectral information for the biomass prediction; however, the prediction accuracy is affected by a small-sample-size problem, which widely exists as overfitting in using high dimensional data where the number of training samples is smaller than the dimensionality of the samples due to limitation of require time, cost, and human resources for field surveys. A common approach to addressing this problem is reducing the dimensionality of dataset. Also, acquired hyperspectral data usually have low signal-to-noise ratio due to a narrow bandwidth and local or global shifts of peaks due to instrumental instability or small differences in considering practical measurement conditions. In this work, we propose a methodology based on fused lasso regression that select optimal bands for the biomass prediction model with encouraging sparsity and grouping, which solves the small-sample-size problem by the dimensionality reduction from the sparsity and the noise and peak shift problem by the grouping. The prediction model provided higher accuracy with root-mean-square error (RMSE) of 66.16 t/ha in the cross-validation than other methods; multiple linear analysis, partial least squares regression, and lasso regression. Furthermore, fusion of spectral and spatial information derived from texture index increased the prediction accuracy with RMSE of 62.62 t/ha. This analysis proves efficiency of fused lasso and image texture in biomass estimation of tropical forests.

Contrast-enhanced spectral mammography with a photon-counting detector.

PubMed

Fredenberg, Erik; Hemmendorff, Magnus; Cederström, Björn; Aslund, Magnus; Danielsson, Mats

2010-05-01

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. The authors have investigated a photon-counting spectral imaging system with two energy bins for contrast-enhanced mammography. System optimization and the potential benefit compared to conventional non-energy-resolved absorption imaging was studied. A framework for system characterization was set up that included quantum and anatomical noise and a theoretical model of the system was benchmarked to phantom measurements. Optimal combination of the energy-resolved images corresponded approximately 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 in the phantom study. Optimization with respect to the signal-to-quantum-noise ratio, commonly referred to as energy weighting, yielded only a minute improvement. In a simulation of a clinically more realistic case, spectral imaging was predicted to perform approximately 30% better than absorption imaging for an average glandularity breast with an average level of anatomical noise. For dense breast tissue and a high level of anatomical noise, however, a rise in detectability by a factor of 6 was predicted. Another approximately 70%-90% improvement was found to be within reach for an optimized system. Contrast-enhanced spectral mammography is feasible and beneficial with the current system, and there is room for additional improvements. Inclusion of anatomical noise is essential for optimizing spectral imaging systems.

Acquisition and visualization techniques for narrow spectral color imaging.

PubMed

Neumann, László; García, Rafael; Basa, János; Hegedüs, Ramón

2013-06-01

This paper introduces a new approach in narrow-band imaging (NBI). Existing NBI techniques generate images by selecting discrete bands over the full visible spectrum or an even wider spectral range. In contrast, here we perform the sampling with filters covering a tight spectral window. This image acquisition method, named narrow spectral imaging, can be particularly useful when optical information is only available within a narrow spectral window, such as in the case of deep-water transmittance, which constitutes the principal motivation of this work. In this study we demonstrate the potential of the proposed photographic technique on nonunderwater scenes recorded under controlled conditions. To this end three multilayer narrow bandpass filters were employed, which transmit at 440, 456, and 470 nm bluish wavelengths, respectively. Since the differences among the images captured in such a narrow spectral window can be extremely small, both image acquisition and visualization require a novel approach. First, high-bit-depth images were acquired with multilayer narrow-band filters either placed in front of the illumination or mounted on the camera lens. Second, a color-mapping method is proposed, using which the input data can be transformed onto the entire display color gamut with a continuous and perceptually nearly uniform mapping, while ensuring optimally high information content for human perception.

Breath analysis with broadly tunable quantum cascade lasers.

PubMed

Wörle, Katharina; Seichter, Felicia; Wilk, Andreas; Armacost, Chris; Day, Tim; Godejohann, Matthias; Wachter, Ulrich; Vogt, Josef; Radermacher, Peter; Mizaikoff, Boris

2013-03-05

With the availability of broadly tunable external cavity quantum cascade lasers (EC-QCLs), particularly bright mid-infrared (MIR; 3-20 μm) light sources are available offering high spectral brightness along with an analytically relevant spectral tuning range of >2 μm. Accurate isotope ratio determination of (12)CO2 and (13)CO2 in exhaled breath is of critical importance in the field of breath analysis, which may be addressed via measurements in the MIR spectral regime. Here, we combine for the first time an EC-QCL tunable across the (12)CO2/(13)CO2 spectral band with a miniaturized hollow waveguide gas cell for quantitatively determining the (12)CO2/(13)CO2 ratio within the exhaled breath of mice. Due to partially overlapping spectral features, these studies are augmented by appropriate multivariate data evaluation and calibration techniques based on partial least-squares regression along with optimized data preprocessing. Highly accurate determinations of the isotope ratio within breath samples collected from a mouse intensive care unit validated via hyphenated gas chromatography-mass spectrometry confirm the viability of IR-HWG-EC-QCL sensing techniques for isotope-selective exhaled breath analysis.

Compressive hyperspectral and multispectral imaging fusion

NASA Astrophysics Data System (ADS)

Espitia, Óscar; Castillo, Sergio; Arguello, Henry

2016-05-01

Image fusion is a valuable framework which combines two or more images of the same scene from one or multiple sensors, allowing to improve the resolution of the images and increase the interpretable content. In remote sensing a common fusion problem consists of merging hyperspectral (HS) and multispectral (MS) images that involve large amount of redundant data, which ignores the highly correlated structure of the datacube along the spatial and spectral dimensions. Compressive HS and MS systems compress the spectral data in the acquisition step allowing to reduce the data redundancy by using different sampling patterns. This work presents a compressed HS and MS image fusion approach, which uses a high dimensional joint sparse model. The joint sparse model is formulated by combining HS and MS compressive acquisition models. The high spectral and spatial resolution image is reconstructed by using sparse optimization algorithms. Different fusion spectral image scenarios are used to explore the performance of the proposed scheme. Several simulations with synthetic and real datacubes show promising results as the reliable reconstruction of a high spectral and spatial resolution image can be achieved by using as few as just the 50% of the datacube.

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.

Eigenvalue-eigenvector decomposition (EED) analysis of dissimilarity and covariance matrix obtained from total synchronous fluorescence spectral (TSFS) data sets of herbal preparations: Optimizing the classification approach.

PubMed

Tarai, Madhumita; Kumar, Keshav; Divya, O; Bairi, Partha; Mishra, Kishor Kumar; Mishra, Ashok Kumar

2017-09-05

The present work compares the dissimilarity and covariance based unsupervised chemometric classification approaches by taking the total synchronous fluorescence spectroscopy data sets acquired for the cumin and non-cumin based herbal preparations. The conventional decomposition method involves eigenvalue-eigenvector analysis of the covariance of the data set and finds the factors that can explain the overall major sources of variation present in the data set. The conventional approach does this irrespective of the fact that the samples belong to intrinsically different groups and hence leads to poor class separation. The present work shows that classification of such samples can be optimized by performing the eigenvalue-eigenvector decomposition on the pair-wise dissimilarity matrix. Copyright © 2017 Elsevier B.V. All rights reserved.

Optimal network modification for spectral radius dependent phase transitions

NASA Astrophysics Data System (ADS)

Rosen, Yonatan; Kirsch, Lior; Louzoun, Yoram

2016-09-01

The dynamics of contact processes on networks is often determined by the spectral radius of the networks adjacency matrices. A decrease of the spectral radius can prevent the outbreak of an epidemic, or impact the synchronization among systems of coupled oscillators. The spectral radius is thus tightly linked to network dynamics and function. As such, finding the minimal change in network structure necessary to reach the intended spectral radius is important theoretically and practically. Given contemporary big data resources such as large scale communication or social networks, this problem should be solved with a low runtime complexity. We introduce a novel method for the minimal decrease in weights of edges required to reach a given spectral radius. The problem is formulated as a convex optimization problem, where a global optimum is guaranteed. The method can be easily adjusted to an efficient discrete removal of edges. We introduce a variant of the method which finds optimal decrease with a focus on weights of vertices. The proposed algorithm is exceptionally scalable, solving the problem for real networks of tens of millions of edges in a short time.

Arbitrary-order Hilbert Spectral Analysis and Intermittency in Solar Wind Density Fluctuations

NASA Astrophysics Data System (ADS)

Carbone, Francesco; Sorriso-Valvo, Luca; Alberti, Tommaso; Lepreti, Fabio; Chen, Christopher H. K.; Němeček, Zdenek; Šafránková, Jana

2018-05-01

The properties of inertial- and kinetic-range solar wind turbulence have been investigated with the arbitrary-order Hilbert spectral analysis method, applied to high-resolution density measurements. Due to the small sample size and to the presence of strong nonstationary behavior and large-scale structures, the classical analysis in terms of structure functions may prove to be unsuccessful in detecting the power-law behavior in the inertial range, and may underestimate the scaling exponents. However, the Hilbert spectral method provides an optimal estimation of the scaling exponents, which have been found to be close to those for velocity fluctuations in fully developed hydrodynamic turbulence. At smaller scales, below the proton gyroscale, the system loses its intermittent multiscaling properties and converges to a monofractal process. The resulting scaling exponents, obtained at small scales, are in good agreement with those of classical fractional Brownian motion, indicating a long-term memory in the process, and the absence of correlations around the spectral-break scale. These results provide important constraints on models of kinetic-range turbulence in the solar wind.

Mid-infrared spectroscopy combined with chemometrics to detect Sclerotinia stem rot on oilseed rape (Brassica napus L.) leaves.

PubMed

Zhang, Chu; Feng, Xuping; Wang, Jian; Liu, Fei; He, Yong; Zhou, Weijun

2017-01-01

Detection of plant diseases in a fast and simple way is crucial for timely disease control. Conventionally, plant diseases are accurately identified by DNA, RNA or serology based methods which are time consuming, complex and expensive. Mid-infrared spectroscopy is a promising technique that simplifies the detection procedure for the disease. Mid-infrared spectroscopy was used to identify the spectral differences between healthy and infected oilseed rape leaves. Two different sample sets from two experiments were used to explore and validate the feasibility of using mid-infrared spectroscopy in detecting Sclerotinia stem rot (SSR) on oilseed rape leaves. The average mid-infrared spectra showed differences between healthy and infected leaves, and the differences varied among different sample sets. Optimal wavenumbers for the 2 sample sets selected by the second derivative spectra were similar, indicating the efficacy of selecting optimal wavenumbers. Chemometric methods were further used to quantitatively detect the oilseed rape leaves infected by SSR, including the partial least squares-discriminant analysis, support vector machine and extreme learning machine. The discriminant models using the full spectra and the optimal wavenumbers of the 2 sample sets were effective for classification accuracies over 80%. The discriminant results for the 2 sample sets varied due to variations in the samples. The use of two sample sets proved and validated the feasibility of using mid-infrared spectroscopy and chemometric methods for detecting SSR on oilseed rape leaves. The similarities among the selected optimal wavenumbers in different sample sets made it feasible to simplify the models and build practical models. Mid-infrared spectroscopy is a reliable and promising technique for SSR control. This study helps in developing practical application of using mid-infrared spectroscopy combined with chemometrics to detect plant disease.

Spectropolarimetry of blood plasma in optimal molecular targeted therapy

NASA Astrophysics Data System (ADS)

Voloshynska, Katerina; Ilashchuk, Tetjana; Yermolenko, Sergey

2015-02-01

The aim of the study was to establish objective parameters of the field of laser and incoherent radiation of different spectral ranges (UV, visible, IR) as a non-invasive optical method of interaction with different samples of biological tissues and fluids of patients to determine the dynamics of metabolic syndrome and choosing the best personal treatment. As diagnostic methods have been used ultraviolet spectrometry samples of blood plasma in the liquid state, infrared spectroscopy middle range (2,5 - 25 microns) dry residue of plasma polarization and laser diagnostic technique of thin histological sections of biological tissues.

High Definition Confocal Imaging Modalities for the Characterization of Tissue-Engineered Substitutes.

PubMed

Mayrand, Dominique; Fradette, Julie

2018-01-01

Optimal imaging methods are necessary in order to perform a detailed characterization of thick tissue samples from either native or engineered tissues. Tissue-engineered substitutes are featuring increasing complexity including multiple cell types and capillary-like networks. Therefore, technical approaches allowing the visualization of the inner structural organization and cellular composition of tissues are needed. This chapter describes an optical clearing technique which facilitates the detailed characterization of whole-mount samples from skin and adipose tissues (ex vivo tissues and in vitro tissue-engineered substitutes) when combined with spectral confocal microscopy and quantitative analysis on image renderings.

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

PubMed

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

2016-08-15

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

Versatile, ultra-low sample volume gas analyzer using a rapid, broad-tuning ECQCL and a hollow fiber gas cell

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

Kriesel, Jason M.; Makarem, Camille N.; Phillips, Mark C.

We describe a versatile mid-infrared (Mid-IR) spectroscopy system developed to measure the concentration of a wide range of gases with an ultra-low sample size. The system combines a rapidly-swept external cavity quantum cascade laser (ECQCL) with a hollow fiber gas cell. The ECQCL has sufficient spectral resolution and reproducibility to measure gases with narrow features (e.g., water, methane, ammonia, etc.), and also the spectral tuning range needed to measure volatile organic compounds (VOCs), (e.g., aldehydes, ketones, hydrocarbons), sulfur compounds, chlorine compounds, etc. The hollow fiber is a capillary tube having an internal reflective coating optimized for transmitting the Mid-IR lasermore » beam to a detector. Sample gas introduced into the fiber (e.g., internal volume = 0.6 ml) interacts strongly with the laser beam, and despite relatively modest path lengths (e.g., L ~ 3 m), the requisite quantity of sample needed for sensitive measurements can be significantly less than what is required using conventional IR laser spectroscopy systems. Example measurements are presented including quantification of VOCs relevant for human breath analysis with a sensitivity of ~2 picomoles at a 1 Hz data rate.« less

Versatile, ultra-low sample volume gas analyzer using a rapid, broad-tuning ECQCL and a hollow fiber gas cell

NASA Astrophysics Data System (ADS)

Kriesel, Jason M.; Makarem, Camille N.; Phillips, Mark C.; Moran, James J.; Coleman, Max L.; Christensen, Lance E.; Kelly, James F.

2017-05-01

We describe a versatile mid-infrared (Mid-IR) spectroscopy system developed to measure the concentration of a wide range of gases with an ultra-low sample size. The system combines a rapidly-swept external cavity quantum cascade laser (ECQCL) with a hollow fiber gas cell. The ECQCL has sufficient spectral resolution and reproducibility to measure gases with narrow features (e.g., water, methane, ammonia, etc.), and also the spectral tuning range needed to measure volatile organic compounds (VOCs), (e.g., aldehydes, ketones, hydrocarbons), sulfur compounds, chlorine compounds, etc. The hollow fiber is a capillary tube having an internal reflective coating optimized for transmitting the Mid-IR laser beam to a detector. Sample gas introduced into the fiber (e.g., internal volume = 0.6 ml) interacts strongly with the laser beam, and despite relatively modest path lengths (e.g., L 3 m), the requisite quantity of sample needed for sensitive measurements can be significantly less than what is required using conventional IR laser spectroscopy systems. Example measurements are presented including quantification of VOCs relevant for human breath analysis with a sensitivity of 2 picomoles at a 1 Hz data rate.

Subsurface water parameters: optimization approach to their determination from remotely sensed water color data.

PubMed

Jain, S C; Miller, J R

1976-04-01

A method, using an optimization scheme, has been developed for the interpretation of spectral albedo (or spectral reflectance) curves obtained from remotely sensed water color data. This method used a two-flow model of the radiation flow and solves for the albedo. Optimization fitting of predicted to observed reflectance data is performed by a quadratic interpolation method for the variables chlorophyll concentration and scattering coefficient. The technique is applied to airborne water color data obtained from Kawartha Lakes, Sargasso Sea, and Nova Scotia coast. The modeled spectral albedo curves are compared to those obtained experimentally, and the computed optimum water parameters are compared to ground truth values. It is shown that the backscattered spectral signal contains information that can be interpreted to give quantitative estimates of the chlorophyll concentration and turbidity in the waters studied.

Hyperspectral Vehicle BRDF Learning: An Exploration of Vehicle Reflectance Variation and Optimal Measures of Spectral Similarity for Vehicle Reacquisition and Tracking Algorithms

NASA Astrophysics Data System (ADS)

Svejkosky, Joseph

The spectral signatures of vehicles in hyperspectral imagery exhibit temporal variations due to the preponderance of surfaces with material properties that display non-Lambertian bi-directional reflectance distribution functions (BRDFs). These temporal variations are caused by changing illumination conditions, changing sun-target-sensor geometry, changing road surface properties, and changing vehicle orientations. To quantify these variations and determine their relative importance in a sub-pixel vehicle reacquisition and tracking scenario, a hyperspectral vehicle BRDF sampling experiment was conducted in which four vehicles were rotated at different orientations and imaged over a six-hour period. The hyperspectral imagery was calibrated using novel in-scene methods and converted to reflectance imagery. The resulting BRDF sampled time-series imagery showed a strong vehicle level BRDF dependence on vehicle shape in off-nadir imaging scenarios and a strong dependence on vehicle color in simulated nadir imaging scenarios. The imagery also exhibited spectral features characteristic of sampling the BRDF of non-Lambertian targets, which were subsequently verified with simulations. In addition, the imagery demonstrated that the illumination contribution from vehicle adjacent horizontal surfaces significantly altered the shape and magnitude of the vehicle reflectance spectrum. The results of the BRDF sampling experiment illustrate the need for a target vehicle BRDF model and detection scheme that incorporates non-Lambertian BRDFs. A new detection algorithm called Eigenvector Loading Regression (ELR) is proposed that learns a hyperspectral vehicle BRDF from a series of BRDF measurements using regression in a lower dimensional space and then applies the learned BRDF to make test spectrum predictions. In cases of non-Lambertian vehicle BRDF, this detection methodology performs favorably when compared to subspace detections algorithms and graph-based detection algorithms that do not account for the target BRDF. The algorithms are compared using a test environment in which observed spectral reflectance signatures from the BRDF sampling experiment are implanted into aerial hyperspectral imagery that contain large quantities of vehicles.

Investigation of the Carbon Arc Source as an AM0 Solar Simulator for Use in Characterizing Multi-Junction Solar Cells

NASA Technical Reports Server (NTRS)

Xu, Jianzeng; Woodyward, James R.

2005-01-01

The operation of multi-junction solar cells used for production of space power is critically dependent on the spectral irradiance of the illuminating light source. Unlike single-junction cells where the spectral irradiance of the simulator and computational techniques may be used to optimized cell designs, optimization of multi-junction solar cell designs requires a solar simulator with a spectral irradiance that closely matches AM0.

Evaluation of SDS depletion using an affinity spin column and IMS-MS detection

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

Hengel, Shawna M.; Floyd, Erica A.; Baker, Erin Shammel

2012-11-01

While the use of detergents is necessary for a variety of protein isolation preparation protocols, often prior to mass spectral (MS) analysis, they are not compatible with MS analysis due to ion suppression and adduct formation. This manuscript describes optimization of detergent removal, using commercially available SDS depletion spin columns containing an affinity resin, providing for both increased protein recovery and thorough SDS removal. Ion mobility spectrometry coupled with mass spectrometry (IMS-MS) allowed for a concurrent analysis of both analyte and detergent. In the case of both proteins and peptides, higher detergent concentrations than previously reported provided an increase ofmore » sample recovery; however there was a limit as SDS was detected by IMS-MS at higher levels of SDS indicating incomplete detergent depletion. The results also suggest optimal conditions for SDS removal are dependent on the sample concentration. Overall, this study provides a useful guide for proteomic studies where SDS is required for efficient sample preparation.« less

A well-posed optimal spectral element approximation for the Stokes problem

NASA Technical Reports Server (NTRS)

Maday, Y.; Patera, A. T.; Ronquist, E. M.

1987-01-01

A method is proposed for the spectral element simulation of incompressible flow. This method constitutes in a well-posed optimal approximation of the steady Stokes problem with no spurious modes in the pressure. The resulting method is analyzed, and numerical results are presented for a model problem.

Radiometric calibration of hyper-spectral imaging spectrometer based on optimizing multi-spectral band selection

NASA Astrophysics Data System (ADS)

Sun, Li-wei; Ye, Xin; Fang, Wei; He, Zhen-lei; Yi, Xiao-long; Wang, Yu-peng

2017-11-01

Hyper-spectral imaging spectrometer has high spatial and spectral resolution. Its radiometric calibration needs the knowledge of the sources used with high spectral resolution. In order to satisfy the requirement of source, an on-orbit radiometric calibration method is designed in this paper. This chain is based on the spectral inversion accuracy of the calibration light source. We compile the genetic algorithm progress which is used to optimize the channel design of the transfer radiometer and consider the degradation of the halogen lamp, thus realizing the high accuracy inversion of spectral curve in the whole working time. The experimental results show the average root mean squared error is 0.396%, the maximum root mean squared error is 0.448%, and the relative errors at all wavelengths are within 1% in the spectral range from 500 nm to 900 nm during 100 h operating time. The design lays a foundation for the high accuracy calibration of imaging spectrometer.

Large-Scale Optimization for Bayesian Inference in Complex Systems

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

Willcox, Karen; Marzouk, Youssef

2013-11-12

The SAGUARO (Scalable Algorithms for Groundwater Uncertainty Analysis and Robust Optimization) Project focused on the development of scalable numerical algorithms for large-scale Bayesian inversion in complex systems that capitalize on advances in large-scale simulation-based optimization and inversion methods. The project was a collaborative effort among MIT, the University of Texas at Austin, Georgia Institute of Technology, and Sandia National Laboratories. The research was directed in three complementary areas: efficient approximations of the Hessian operator, reductions in complexity of forward simulations via stochastic spectral approximations and model reduction, and employing large-scale optimization concepts to accelerate sampling. The MIT--Sandia component of themore » SAGUARO Project addressed the intractability of conventional sampling methods for large-scale statistical inverse problems by devising reduced-order models that are faithful to the full-order model over a wide range of parameter values; sampling then employs the reduced model rather than the full model, resulting in very large computational savings. Results indicate little effect on the computed posterior distribution. On the other hand, in the Texas--Georgia Tech component of the project, we retain the full-order model, but exploit inverse problem structure (adjoint-based gradients and partial Hessian information of the parameter-to-observation map) to implicitly extract lower dimensional information on the posterior distribution; this greatly speeds up sampling methods, so that fewer sampling points are needed. We can think of these two approaches as ``reduce then sample'' and ``sample then reduce.'' In fact, these two approaches are complementary, and can be used in conjunction with each other. Moreover, they both exploit deterministic inverse problem structure, in the form of adjoint-based gradient and Hessian information of the underlying parameter-to-observation map, to achieve their speedups.« less

Sensitive Dual Color in vivo Bioluminescence Imaging Using a New Red Codon Optimized Firefly Luciferase and a Green Click Beetle Luciferase

DTIC Science & Technology

2011-04-01

Sensitive Dual Color In Vivo Bioluminescence Imaging Using a New Red Codon Optimized Firefly Luciferase and a Green Click Beetle Luciferase Laura...20 nm). Spectral unmixing algorithms were applied to the images where good separation of signals was observed. Furthermore, HEK293 cells that...spectral emissions using a suitable spectral unmixing algorithm . This new D-luciferin-dependent reporter gene couplet opens up the possibility in the future

Wavelet-domain de-noising technique for THz pulsed spectroscopy

NASA Astrophysics Data System (ADS)

Chernomyrdin, Nikita V.; Zaytsev, Kirill I.; Gavdush, Arsenii A.; Fokina, Irina N.; Karasik, Valeriy E.; Reshetov, Igor V.; Kudrin, Konstantin G.; Nosov, Pavel A.; Yurchenko, Stanislav O.

2014-09-01

De-noising of terahertz (THz) pulsed spectroscopy (TPS) data is an essential problem, since a noise in the TPS system data prevents correct reconstruction of the sample spectral dielectric properties and to perform the sample internal structure studying. There are certain regions in TPS signal Fourier spectrum, where Fourier-domain signal-to-noise ratio is relatively small. Effective de-noising might potentially expand the range of spectrometer spectral sensitivity and reduce the time of waveform registration, which is an essential problem for biomedical applications of TPS. In this work, it is shown how the recent progress in signal processing in wavelet-domain could be used for TPS waveforms de-noising. It demonstrates the ability to perform effective de-noising of TPS data using the algorithm of the Fast Wavelet Transform (FWT). The results of the optimal wavelet basis selection and wavelet-domain thresholding technique selection are reported. Developed technique is implemented for reconstruction of in vivo healthy and deseased skin samplesspectral characteristics at THz frequency range.

Comparison of Benchtop Fourier-Transform (FT) and Portable Grating Scanning Spectrometers for Determination of Total Soluble Solid Contents in Single Grape Berry (Vitis vinifera L.) and Calibration Transfer.

PubMed

Xiao, Hui; Sun, Ke; Sun, Ye; Wei, Kangli; Tu, Kang; Pan, Leiqing

2017-11-22

Near-infrared (NIR) spectroscopy was applied for the determination of total soluble solid contents (SSC) of single Ruby Seedless grape berries using both benchtop Fourier transform (VECTOR 22/N) and portable grating scanning (SupNIR-1500) spectrometers in this study. The results showed that the best SSC prediction was obtained by VECTOR 22/N in the range of 12,000 to 4000 cm -1 (833-2500 nm) for Ruby Seedless with determination coefficient of prediction (R p ²) of 0.918, root mean squares error of prediction (RMSEP) of 0.758% based on least squares support vector machine (LS-SVM). Calibration transfer was conducted on the same spectral range of two instruments (1000-1800 nm) based on the LS-SVM model. By conducting Kennard-Stone (KS) to divide sample sets, selecting the optimal number of standardization samples and applying Passing-Bablok regression to choose the optimal instrument as the master instrument, a modified calibration transfer method between two spectrometers was developed. When 45 samples were selected for the standardization set, the linear interpolation-piecewise direct standardization (linear interpolation-PDS) performed well for calibration transfer with R p ² of 0.857 and RMSEP of 1.099% in the spectral region of 1000-1800 nm. And it was proved that re-calculating the standardization samples into master model could improve the performance of calibration transfer in this study. This work indicated that NIR could be used as a rapid and non-destructive method for SSC prediction, and provided a feasibility to solve the transfer difficulty between totally different NIR spectrometers.

A Spectral Reconstruction Algorithm of Miniature Spectrometer Based on Sparse Optimization and Dictionary Learning.

PubMed

Zhang, Shang; Dong, Yuhan; Fu, Hongyan; Huang, Shao-Lun; Zhang, Lin

2018-02-22

The miniaturization of spectrometer can broaden the application area of spectrometry, which has huge academic and industrial value. Among various miniaturization approaches, filter-based miniaturization is a promising implementation by utilizing broadband filters with distinct transmission functions. Mathematically, filter-based spectral reconstruction can be modeled as solving a system of linear equations. In this paper, we propose an algorithm of spectral reconstruction based on sparse optimization and dictionary learning. To verify the feasibility of the reconstruction algorithm, we design and implement a simple prototype of a filter-based miniature spectrometer. The experimental results demonstrate that sparse optimization is well applicable to spectral reconstruction whether the spectra are directly sparse or not. As for the non-directly sparse spectra, their sparsity can be enhanced by dictionary learning. In conclusion, the proposed approach has a bright application prospect in fabricating a practical miniature spectrometer.

A Spectral Reconstruction Algorithm of Miniature Spectrometer Based on Sparse Optimization and Dictionary Learning

PubMed Central

Zhang, Shang; Fu, Hongyan; Huang, Shao-Lun; Zhang, Lin

2018-01-01

The miniaturization of spectrometer can broaden the application area of spectrometry, which has huge academic and industrial value. Among various miniaturization approaches, filter-based miniaturization is a promising implementation by utilizing broadband filters with distinct transmission functions. Mathematically, filter-based spectral reconstruction can be modeled as solving a system of linear equations. In this paper, we propose an algorithm of spectral reconstruction based on sparse optimization and dictionary learning. To verify the feasibility of the reconstruction algorithm, we design and implement a simple prototype of a filter-based miniature spectrometer. The experimental results demonstrate that sparse optimization is well applicable to spectral reconstruction whether the spectra are directly sparse or not. As for the non-directly sparse spectra, their sparsity can be enhanced by dictionary learning. In conclusion, the proposed approach has a bright application prospect in fabricating a practical miniature spectrometer. PMID:29470406

Investigations of calcium spectral lines in laser-induced breakdown spectroscopy

NASA Astrophysics Data System (ADS)

Ching, Sim Yit; Tariq, Usman; Haider, Zuhaib; Tufail, Kashif; Sabri, Salwanie; Imran, Muhammad; Ali, Jalil

2017-03-01

Laser-induced breakdown spectroscopy (LIBS) is a direct and versatile analytical technique that performs the elemental composition analysis based on optical emission produced by laser induced-plasma, with a little or no sample preparation. The performance of the LIBS technique relies on the choice of experimental conditions which must be thoroughly explored and optimized for each application. The main parameters affecting the LIBS performance are the laser energy, laser wavelength, pulse duration, gate delay, geometrical set-up of the focusing and collecting optics. In LIBS quantitative analysis, the gate delay and laser energy are very important parameters that have pronounced impact on the accuracy of the elemental composition information of the materials. The determination of calcium elements in the pelletized samples was investigated and served for the purpose of optimizing the gate delay and laser energy by studying and analyzing the results from emission intensities collected and signal to background ratio (S/B) for the specified wavelengths.

Fast Infrared Chemical Imaging with a Quantum Cascade Laser

PubMed Central

2015-01-01

Infrared (IR) spectroscopic imaging systems are a powerful tool for visualizing molecular microstructure of a sample without the need for dyes or stains. Table-top Fourier transform infrared (FT-IR) imaging spectrometers, the current established technology, can record broadband spectral data efficiently but requires scanning the entire spectrum with a low throughput source. The advent of high-intensity, broadly tunable quantum cascade lasers (QCL) has now accelerated IR imaging but results in a fundamentally different type of instrument and approach, namely, discrete frequency IR (DF-IR) spectral imaging. While the higher intensity of the source provides a higher signal per channel, the absence of spectral multiplexing also provides new opportunities and challenges. Here, we couple a rapidly tunable QCL with a high performance microscope equipped with a cooled focal plane array (FPA) detector. Our optical system is conceptualized to provide optimal performance based on recent theory and design rules for high-definition (HD) IR imaging. Multiple QCL units are multiplexed together to provide spectral coverage across the fingerprint region (776.9 to 1904.4 cm–1) in our DF-IR microscope capable of broad spectral coverage, wide-field detection, and diffraction-limited spectral imaging. We demonstrate that the spectral and spatial fidelity of this system is at least as good as the best FT-IR imaging systems. Our configuration provides a speedup for equivalent spectral signal-to-noise ratio (SNR) compared to the best spectral quality from a high-performance linear array system that has 10-fold larger pixels. Compared to the fastest available HD FT-IR imaging system, we demonstrate scanning of large tissue microarrays (TMA) in 3-orders of magnitude smaller time per essential spectral frequency. These advances offer new opportunities for high throughput IR chemical imaging, especially for the measurement of cells and tissues. PMID:25474546

Fast infrared chemical imaging with a quantum cascade laser.

PubMed

Yeh, Kevin; Kenkel, Seth; Liu, Jui-Nung; Bhargava, Rohit

2015-01-06

Infrared (IR) spectroscopic imaging systems are a powerful tool for visualizing molecular microstructure of a sample without the need for dyes or stains. Table-top Fourier transform infrared (FT-IR) imaging spectrometers, the current established technology, can record broadband spectral data efficiently but requires scanning the entire spectrum with a low throughput source. The advent of high-intensity, broadly tunable quantum cascade lasers (QCL) has now accelerated IR imaging but results in a fundamentally different type of instrument and approach, namely, discrete frequency IR (DF-IR) spectral imaging. While the higher intensity of the source provides a higher signal per channel, the absence of spectral multiplexing also provides new opportunities and challenges. Here, we couple a rapidly tunable QCL with a high performance microscope equipped with a cooled focal plane array (FPA) detector. Our optical system is conceptualized to provide optimal performance based on recent theory and design rules for high-definition (HD) IR imaging. Multiple QCL units are multiplexed together to provide spectral coverage across the fingerprint region (776.9 to 1904.4 cm(-1)) in our DF-IR microscope capable of broad spectral coverage, wide-field detection, and diffraction-limited spectral imaging. We demonstrate that the spectral and spatial fidelity of this system is at least as good as the best FT-IR imaging systems. Our configuration provides a speedup for equivalent spectral signal-to-noise ratio (SNR) compared to the best spectral quality from a high-performance linear array system that has 10-fold larger pixels. Compared to the fastest available HD FT-IR imaging system, we demonstrate scanning of large tissue microarrays (TMA) in 3-orders of magnitude smaller time per essential spectral frequency. These advances offer new opportunities for high throughput IR chemical imaging, especially for the measurement of cells and tissues.

Optimizing inhomogeneous spin ensembles for quantum memory

NASA Astrophysics Data System (ADS)

Bensky, Guy; Petrosyan, David; Majer, Johannes; Schmiedmayer, Jörg; Kurizki, Gershon

2012-07-01

We propose a method to maximize the fidelity of quantum memory implemented by a spectrally inhomogeneous spin ensemble. The method is based on preselecting the optimal spectral portion of the ensemble by judiciously designed pulses. This leads to significant improvement of the transfer and storage of quantum information encoded in the microwave or optical field.

Optimizing spectral CT parameters for material classification tasks

NASA Astrophysics Data System (ADS)

Rigie, D. S.; La Rivière, P. J.

2016-06-01

In this work, we propose a framework for optimizing spectral CT imaging parameters and hardware design with regard to material classification tasks. Compared with conventional CT, many more parameters must be considered when designing spectral CT systems and protocols. These choices will impact material classification performance in a non-obvious, task-dependent way with direct implications for radiation dose reduction. In light of this, we adapt Hotelling Observer formalisms typically applied to signal detection tasks to the spectral CT, material-classification problem. The result is a rapidly computable metric that makes it possible to sweep out many system configurations, generating parameter optimization curves (POC’s) that can be used to select optimal settings. The proposed model avoids restrictive assumptions about the basis-material decomposition (e.g. linearity) and incorporates signal uncertainty with a stochastic object model. This technique is demonstrated on dual-kVp and photon-counting systems for two different, clinically motivated material classification tasks (kidney stone classification and plaque removal). We show that the POC’s predicted with the proposed analytic model agree well with those derived from computationally intensive numerical simulation studies.

Optimizing Spectral CT Parameters for Material Classification Tasks

PubMed Central

Rigie, D. S.; La Rivière, P. J.

2017-01-01

In this work, we propose a framework for optimizing spectral CT imaging parameters and hardware design with regard to material classification tasks. Compared with conventional CT, many more parameters must be considered when designing spectral CT systems and protocols. These choices will impact material classification performance in a non-obvious, task-dependent way with direct implications for radiation dose reduction. In light of this, we adapt Hotelling Observer formalisms typically applied to signal detection tasks to the spectral CT, material-classification problem. The result is a rapidly computable metric that makes it possible to sweep out many system configurations, generating parameter optimization curves (POC’s) that can be used to select optimal settings. The proposed model avoids restrictive assumptions about the basis-material decomposition (e.g. linearity) and incorporates signal uncertainty with a stochastic object model. This technique is demonstrated on dual-kVp and photon-counting systems for two different, clinically motivated material classification tasks (kidney stone classification and plaque removal). We show that the POC’s predicted with the proposed analytic model agree well with those derived from computationally intensive numerical simulation studies. PMID:27227430

Improvements In The Calculation Of White Light Modulation Transfer Function (MTF) In Japan Optical Engineering Research Association (JOERA)

NASA Astrophysics Data System (ADS)

Minami, Setsuo; Ogawa, Ryota

1980-09-01

Consequences of the working project formed in JOERA (JAPAN OPTICAL ENGINEERING RESEARCH ASSOCIATION) from 1976 to 1978 are to be reported. The question, "What is the most reasonable number of mesh divides of entrance pupil to get monochromatic OTF and the most economical sampling method of spectral wavelengths to calculate White Light MTF?" is important in the actual stage of designing to optimize the conflict relationship between numerical accuracy and computing time. We have examined the spectral characteristics of OTF using some typical lenses such as photographic telephoto lens and wide angled retrofocus lens, cleared the structure of the White Light MTF, and found some techniques to get the reasonable numerical results. As a result of trial experiments to get coincidence between measurements and calculat-ions, the standard filter, which should be added to the MTF lens tester and whose spectral transmittance should be installed in the calculation, are proposed.

Combining the Hanning windowed interpolated FFT in both directions

NASA Astrophysics Data System (ADS)

Chen, Kui Fu; Li, Yan Feng

2008-06-01

The interpolated fast Fourier transform (IFFT) has been proposed as a way to eliminate the picket fence effect (PFE) of the fast Fourier transform. The modulus based IFFT, cited in most relevant references, makes use of only the 1st and 2nd highest spectral lines. An approach using three principal spectral lines is proposed. This new approach combines both directions of the complex spectrum based IFFT with the Hanning window. The optimal weight to minimize the estimation variance is established on the first order Taylor series expansion of noise interference. A numerical simulation is carried out, and the results are compared with the Cramer-Rao bound. It is demonstrated that the proposed approach has a lower estimation variance than the two-spectral-line approach. The improvement depends on the extent of sampling deviating from the coherent condition, and the best is decreasing variance by 2/7. However, it is also shown that the estimation variance of the windowed IFFT with the Hanning is significantly higher than that of without windowing.

Spectral analysis method and sample generation for real time visualization of speech

NASA Astrophysics Data System (ADS)

Hobohm, Klaus

A method for translating speech signals into optical models, characterized by high sound discrimination and learnability and designed to provide to deaf persons a feedback towards control of their way of speaking, is presented. Important properties of speech production and perception processes and organs involved in these mechanisms are recalled in order to define requirements for speech visualization. It is established that the spectral representation of time, frequency and amplitude resolution of hearing must be fair and continuous variations of acoustic parameters of speech signal must be depicted by a continuous variation of images. A color table was developed for dynamic illustration and sonograms were generated with five spectral analysis methods such as Fourier transformations and linear prediction coding. For evaluating sonogram quality, test persons had to recognize consonant/vocal/consonant words and an optimized analysis method was achieved with a fast Fourier transformation and a postprocessor. A hardware concept of a real time speech visualization system, based on multiprocessor technology in a personal computer, is presented.

Dereplication of Natural Products Using GC-TOF Mass Spectrometry: Improved Metabolite Identification by Spectral Deconvolution Ratio Analysis.

PubMed

Carnevale Neto, Fausto; Pilon, Alan C; Selegato, Denise M; Freire, Rafael T; Gu, Haiwei; Raftery, Daniel; Lopes, Norberto P; Castro-Gamboa, Ian

2016-01-01

Dereplication based on hyphenated techniques has been extensively applied in plant metabolomics, thereby avoiding re-isolation of known natural products. However, due to the complex nature of biological samples and their large concentration range, dereplication requires the use of chemometric tools to comprehensively extract information from the acquired data. In this work we developed a reliable GC-MS-based method for the identification of non-targeted plant metabolites by combining the Ratio Analysis of Mass Spectrometry deconvolution tool (RAMSY) with Automated Mass Spectral Deconvolution and Identification System software (AMDIS). Plants species from Solanaceae, Chrysobalanaceae and Euphorbiaceae were selected as model systems due to their molecular diversity, ethnopharmacological potential, and economical value. The samples were analyzed by GC-MS after methoximation and silylation reactions. Dereplication was initiated with the use of a factorial design of experiments to determine the best AMDIS configuration for each sample, considering linear retention indices and mass spectral data. A heuristic factor (CDF, compound detection factor) was developed and applied to the AMDIS results in order to decrease the false-positive rates. Despite the enhancement in deconvolution and peak identification, the empirical AMDIS method was not able to fully deconvolute all GC-peaks, leading to low MF values and/or missing metabolites. RAMSY was applied as a complementary deconvolution method to AMDIS to peaks exhibiting substantial overlap, resulting in recovery of low-intensity co-eluted ions. The results from this combination of optimized AMDIS with RAMSY attested to the ability of this approach as an improved dereplication method for complex biological samples such as plant extracts.

Dereplication of Natural Products Using GC-TOF Mass Spectrometry: Improved Metabolite Identification by Spectral Deconvolution Ratio Analysis

PubMed Central

Carnevale Neto, Fausto; Pilon, Alan C.; Selegato, Denise M.; Freire, Rafael T.; Gu, Haiwei; Raftery, Daniel; Lopes, Norberto P.; Castro-Gamboa, Ian

2016-01-01

Dereplication based on hyphenated techniques has been extensively applied in plant metabolomics, thereby avoiding re-isolation of known natural products. However, due to the complex nature of biological samples and their large concentration range, dereplication requires the use of chemometric tools to comprehensively extract information from the acquired data. In this work we developed a reliable GC-MS-based method for the identification of non-targeted plant metabolites by combining the Ratio Analysis of Mass Spectrometry deconvolution tool (RAMSY) with Automated Mass Spectral Deconvolution and Identification System software (AMDIS). Plants species from Solanaceae, Chrysobalanaceae and Euphorbiaceae were selected as model systems due to their molecular diversity, ethnopharmacological potential, and economical value. The samples were analyzed by GC-MS after methoximation and silylation reactions. Dereplication was initiated with the use of a factorial design of experiments to determine the best AMDIS configuration for each sample, considering linear retention indices and mass spectral data. A heuristic factor (CDF, compound detection factor) was developed and applied to the AMDIS results in order to decrease the false-positive rates. Despite the enhancement in deconvolution and peak identification, the empirical AMDIS method was not able to fully deconvolute all GC-peaks, leading to low MF values and/or missing metabolites. RAMSY was applied as a complementary deconvolution method to AMDIS to peaks exhibiting substantial overlap, resulting in recovery of low-intensity co-eluted ions. The results from this combination of optimized AMDIS with RAMSY attested to the ability of this approach as an improved dereplication method for complex biological samples such as plant extracts. PMID:27747213

Neutron optics concept for the materials engineering diffractometer at the ESS

NASA Astrophysics Data System (ADS)

Šaroun, J.; Fenske, J.; Rouijaa, M.; Beran, P.; Navrátil, J.; Lukáš, P.; Schreyer, A.; Strobl, M.

2016-09-01

The Beamline for European Materials Engineering Research (BEER) has been recently proposed to be built at the European Spallation Source (ESS). The presented concept of neutron delivery optics for this instrument addresses the problems of bi-spectral beam extraction from a small moderator, optimization of neutron guides profile for long-range neutron transport and focusing at the sample under various constraints. They include free space before and after the guides, a narrow guide section with gaps for choppers, closing of direct line of sight and cost reduction by optimization of the guides cross-section and coating. A system of slits and exchangeable focusing optics is proposed in order to match various wavelength resolution options provided by the pulse shaping and modulation choppers, which permits to efficiently trade resolution for intensity in a wide range. Simulated performance characteristics such as brilliance transfer ratio are complemented by the analysis of the histories of “useful” neutrons obtained by back tracing neutrons hitting the sample, which helps to optimize some of the neutron guide parameters such as supermirror coating.

A comparison between Gauss-Newton and Markov chain Monte Carlo basedmethods for inverting spectral induced polarization data for Cole-Coleparameters

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

Chen, Jinsong; Kemna, Andreas; Hubbard, Susan S.

2008-05-15

We develop a Bayesian model to invert spectral induced polarization (SIP) data for Cole-Cole parameters using Markov chain Monte Carlo (MCMC) sampling methods. We compare the performance of the MCMC based stochastic method with an iterative Gauss-Newton based deterministic method for Cole-Cole parameter estimation through inversion of synthetic and laboratory SIP data. The Gauss-Newton based method can provide an optimal solution for given objective functions under constraints, but the obtained optimal solution generally depends on the choice of initial values and the estimated uncertainty information is often inaccurate or insufficient. In contrast, the MCMC based inversion method provides extensive globalmore » information on unknown parameters, such as the marginal probability distribution functions, from which we can obtain better estimates and tighter uncertainty bounds of the parameters than with the deterministic method. Additionally, the results obtained with the MCMC method are independent of the choice of initial values. Because the MCMC based method does not explicitly offer single optimal solution for given objective functions, the deterministic and stochastic methods can complement each other. For example, the stochastic method can first be used to obtain the means of the unknown parameters by starting from an arbitrary set of initial values and the deterministic method can then be initiated using the means as starting values to obtain the optimal estimates of the Cole-Cole parameters.« less

The use of single-date MODIS imagery for estimating large-scale urban impervious surface fraction with spectral mixture analysis and machine learning techniques

NASA Astrophysics Data System (ADS)

Deng, Chengbin; Wu, Changshan

2013-12-01

Urban impervious surface information is essential for urban and environmental applications at the regional/national scales. As a popular image processing technique, spectral mixture analysis (SMA) has rarely been applied to coarse-resolution imagery due to the difficulty of deriving endmember spectra using traditional endmember selection methods, particularly within heterogeneous urban environments. To address this problem, we derived endmember signatures through a least squares solution (LSS) technique with known abundances of sample pixels, and integrated these endmember signatures into SMA for mapping large-scale impervious surface fraction. In addition, with the same sample set, we carried out objective comparative analyses among SMA (i.e. fully constrained and unconstrained SMA) and machine learning (i.e. Cubist regression tree and Random Forests) techniques. Analysis of results suggests three major conclusions. First, with the extrapolated endmember spectra from stratified random training samples, the SMA approaches performed relatively well, as indicated by small MAE values. Second, Random Forests yields more reliable results than Cubist regression tree, and its accuracy is improved with increased sample sizes. Finally, comparative analyses suggest a tentative guide for selecting an optimal approach for large-scale fractional imperviousness estimation: unconstrained SMA might be a favorable option with a small number of samples, while Random Forests might be preferred if a large number of samples are available.

A rigorous analysis of digital pre-emphasis and DAC resolution for interleaved DAC Nyquist-WDM signal generation in high-speed coherent optical transmission systems

NASA Astrophysics Data System (ADS)

Weng, Yi; Wang, Junyi; He, Xuan; Pan, Zhongqi

2018-02-01

The Nyquist spectral shaping techniques facilitate a promising solution to enhance spectral efficiency (SE) and further reduce the cost-per-bit in high-speed wavelength-division multiplexing (WDM) transmission systems. Hypothetically, any Nyquist WDM signals with arbitrary shapes can be generated by the use of the digital signal processing (DSP) based electrical filters (E-filter). Nonetheless, in actual 100G/ 200G coherent systems, the performance as well as DSP complexity are increasingly restricted by cost and power consumption. Henceforward it is indispensable to optimize DSP to accomplish the preferred performance at the least complexity. In this paper, we systematically investigated the minimum requirements and challenges of Nyquist WDM signal generation, particularly for higher-order modulation formats, including 16 quadrature amplitude modulation (QAM) or 64QAM. A variety of interrelated parameters, such as channel spacing and roll-off factor, have been evaluated to optimize the requirements of the digital-to-analog converter (DAC) resolution and transmitter E-filter bandwidth. The impact of spectral pre-emphasis has been predominantly enhanced via the proposed interleaved DAC architecture by at least 4%, and hence reducing the required optical signal to noise ratio (OSNR) at a bit error rate (BER) of 10-3 by over 0.45 dB at a channel spacing of 1.05 symbol rate and an optimized roll-off factor of 0.1. Furthermore, the requirements of sampling rate for different types of super-Gaussian E-filters are discussed for 64QAM Nyquist WDM transmission systems. Finally, the impact of the non-50% duty cycle error between sub-DACs upon the quality of the generated signals for the interleaved DAC structure has been analyzed.

Design of wide-angle solar-selective absorbers using aperiodic metal-dielectric stacks.

PubMed

Sergeant, Nicholas P; Pincon, Olivier; Agrawal, Mukul; Peumans, Peter

2009-12-07

Spectral control of the emissivity of surfaces is essential in applications such as solar thermal and thermophotovoltaic energy conversion in order to achieve the highest conversion efficiencies possible. We investigated the spectral performance of planar aperiodic metal-dielectric multilayer coatings for these applications. The response of the coatings was optimized for a target operational temperature using needle-optimization based on a transfer matrix approach. Excellent spectral selectivity was achieved over a wide angular range. These aperiodic metal-dielectric stacks have the potential to significantly increase the efficiency of thermophotovoltaic and solar thermal conversion systems. Optimal coatings for concentrated solar thermal conversion were modeled to have a thermal emissivity <7% at 720K while absorbing >94% of the incident light. In addition, optimized coatings for solar thermophotovoltaic applications were modeled to have thermal emissivity <16% at 1750K while absorbing >85% of the concentrated solar radiation.

Fluorescence Spectroscopy for the Monitoring of Food Processes.

PubMed

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

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

Method for optimizing output in ultrashort-pulse multipass laser amplifiers with selective use of a spectral filter

DOEpatents

Backus, Sterling J [Erie, CO; Kapteyn, Henry C [Boulder, CO

2007-07-10

A method for optimizing multipass laser amplifier output utilizes a spectral filter in early passes but not in later passes. The pulses shift position slightly for each pass through the amplifier, and the filter is placed such that early passes intersect the filter while later passes bypass it. The filter position may be adjust offline in order to adjust the number of passes in each category. The filter may be optimized for use in a cryogenic amplifier.

Identification of coffee bean varieties using hyperspectral imaging: influence of preprocessing methods and pixel-wise spectra analysis.

PubMed

Zhang, Chu; Liu, Fei; He, Yong

2018-02-01

Hyperspectral imaging was used to identify and to visualize the coffee bean varieties. Spectral preprocessing of pixel-wise spectra was conducted by different methods, including moving average smoothing (MA), wavelet transform (WT) and empirical mode decomposition (EMD). Meanwhile, spatial preprocessing of the gray-scale image at each wavelength was conducted by median filter (MF). Support vector machine (SVM) models using full sample average spectra and pixel-wise spectra, and the selected optimal wavelengths by second derivative spectra all achieved classification accuracy over 80%. Primarily, the SVM models using pixel-wise spectra were used to predict the sample average spectra, and these models obtained over 80% of the classification accuracy. Secondly, the SVM models using sample average spectra were used to predict pixel-wise spectra, but achieved with lower than 50% of classification accuracy. The results indicated that WT and EMD were suitable for pixel-wise spectra preprocessing. The use of pixel-wise spectra could extend the calibration set, and resulted in the good prediction results for pixel-wise spectra and sample average spectra. The overall results indicated the effectiveness of using spectral preprocessing and the adoption of pixel-wise spectra. The results provided an alternative way of data processing for applications of hyperspectral imaging in food industry.

Selection of optimal spectral sensitivity functions for color filter arrays.

PubMed

Parmar, Manu; Reeves, Stanley J

2010-12-01

A color image meant for human consumption can be appropriately displayed only if at least three distinct color channels are present. Typical digital cameras acquire three-color images with only one sensor. A color filter array (CFA) is placed on the sensor such that only one color is sampled at a particular spatial location. This sparsely sampled signal is then reconstructed to form a color image with information about all three colors at each location. In this paper, we show that the wavelength sensitivity functions of the CFA color filters affect both the color reproduction ability and the spatial reconstruction quality of recovered images. We present a method to select perceptually optimal color filter sensitivity functions based upon a unified spatial-chromatic sampling framework. A cost function independent of particular scenes is defined that expresses the error between a scene viewed by the human visual system and the reconstructed image that represents the scene. A constrained minimization of the cost function is used to obtain optimal values of color-filter sensitivity functions for several periodic CFAs. The sensitivity functions are shown to perform better than typical RGB and CMY color filters in terms of both the s-CIELAB ∆E error metric and a qualitative assessment.

Variable selection based cotton bollworm odor spectroscopic detection

NASA Astrophysics Data System (ADS)

Lü, Chengxu; Gai, Shasha; Luo, Min; Zhao, Bo

2016-10-01

Aiming at rapid automatic pest detection based efficient and targeting pesticide application and shooting the trouble of reflectance spectral signal covered and attenuated by the solid plant, the possibility of near infrared spectroscopy (NIRS) detection on cotton bollworm odor is studied. Three cotton bollworm odor samples and 3 blank air gas samples were prepared. Different concentrations of cotton bollworm odor were prepared by mixing the above gas samples, resulting a calibration group of 62 samples and a validation group of 31 samples. Spectral collection system includes light source, optical fiber, sample chamber, spectrometer. Spectra were pretreated by baseline correction, modeled with partial least squares (PLS), and optimized by genetic algorithm (GA) and competitive adaptive reweighted sampling (CARS). Minor counts differences are found among spectra of different cotton bollworm odor concentrations. PLS model of all the variables was built presenting RMSEV of 14 and RV2 of 0.89, its theory basis is insect volatilizes specific odor, including pheromone and allelochemics, which are used for intra-specific and inter-specific communication and could be detected by NIR spectroscopy. 28 sensitive variables are selected by GA, presenting the model performance of RMSEV of 14 and RV2 of 0.90. Comparably, 8 sensitive variables are selected by CARS, presenting the model performance of RMSEV of 13 and RV2 of 0.92. CARS model employs only 1.5% variables presenting smaller error than that of all variable. Odor gas based NIR technique shows the potential for cotton bollworm detection.

Broadband and tunable optical parametric generator for remote detection of gas molecules in the short and mid-infrared.

PubMed

Lambert-Girard, Simon; Allard, Martin; Piché, Michel; Babin, François

2015-04-01

The development of a novel broadband and tunable optical parametric generator (OPG) is presented. The OPG properties are studied numerically and experimentally in order to optimize the generator's use in a broadband spectroscopic LIDAR operating in the short and mid-infrared. This paper discusses trade-offs to be made on the properties of the pump, crystal, and seeding signal in order to optimize the pulse spectral density and divergence while enabling energy scaling. A seed with a large spectral bandwidth is shown to enhance the pulse-to-pulse stability and optimize the pulse spectral density. A numerical model shows excellent agreement with output power measurements; the model predicts that a pump having a large number of longitudinal modes improves conversion efficiency and pulse stability.

Application of Hyperspectral Imaging to Detect Sclerotinia sclerotiorum on Oilseed Rape Stems

PubMed Central

Kong, Wenwen; Zhang, Chu; Huang, Weihao

2018-01-01

Hyperspectral imaging covering the spectral range of 384–1034 nm combined with chemometric methods was used to detect Sclerotinia sclerotiorum (SS) on oilseed rape stems by two sample sets (60 healthy and 60 infected stems for each set). Second derivative spectra and PCA loadings were used to select the optimal wavelengths. Discriminant models were built and compared to detect SS on oilseed rape stems, including partial least squares-discriminant analysis, radial basis function neural network, support vector machine and extreme learning machine. The discriminant models using full spectra and optimal wavelengths showed good performance with classification accuracies of over 80% for the calibration and prediction set. Comparing all developed models, the optimal classification accuracies of the calibration and prediction set were over 90%. The similarity of selected optimal wavelengths also indicated the feasibility of using hyperspectral imaging to detect SS on oilseed rape stems. The results indicated that hyperspectral imaging could be used as a fast, non-destructive and reliable technique to detect plant diseases on stems. PMID:29300315

Influence of temperature on the spectral characteristics of semiconductor lasers in the visible range

NASA Astrophysics Data System (ADS)

Adamov, A. A.; Baranov, M. S.; Khramov, V. N.

2018-04-01

The results of studies on the effect of temperature on the output spectral characteristics of continuous semiconductor lasers of the visible range are presented. The paper presents the results of studying the spectral-optical radiation parameters of semiconductor lasers, their coherence lengths, and the dependence of the position of the spectral peak of the wavelength on temperature. This is necessary for the selection of the most optimal laser in order to use it for medical ophthalmologic diagnosis. The experiment was carried out using semiconductor laser modules based on a laser diode. The spectra were recorded by using a two-channel automated spectral complex based on the MDR-23 monochromator. Spectral dependences on the temperature of semiconductor lasers are obtained, in the range from 300 to 370 K. The possibility of determining the internal damage to the stabilization of laser modules without opening the case is shown, but only with the use of their spectral characteristics. The obtained data allow taking into account temperature characteristics and further optimization of parameters of such lasers when used in medical practice, in particular, in ophthalmologic diagnostics.

Autopilot for frequency-modulation atomic force microscopy.

PubMed

Kuchuk, Kfir; Schlesinger, Itai; Sivan, Uri

2015-10-01

One of the most challenging aspects of operating an atomic force microscope (AFM) is finding optimal feedback parameters. This statement applies particularly to frequency-modulation AFM (FM-AFM), which utilizes three feedback loops to control the cantilever excitation amplitude, cantilever excitation frequency, and z-piezo extension. These loops are regulated by a set of feedback parameters, tuned by the user to optimize stability, sensitivity, and noise in the imaging process. Optimization of these parameters is difficult due to the coupling between the frequency and z-piezo feedback loops by the non-linear tip-sample interaction. Four proportional-integral (PI) parameters and two lock-in parameters regulating these loops require simultaneous optimization in the presence of a varying unknown tip-sample coupling. Presently, this optimization is done manually in a tedious process of trial and error. Here, we report on the development and implementation of an algorithm that computes the control parameters automatically. The algorithm reads the unperturbed cantilever resonance frequency, its quality factor, and the z-piezo driving signal power spectral density. It analyzes the poles and zeros of the total closed loop transfer function, extracts the unknown tip-sample transfer function, and finds four PI parameters and two lock-in parameters for the frequency and z-piezo control loops that optimize the bandwidth and step response of the total system. Implementation of the algorithm in a home-built AFM shows that the calculated parameters are consistently excellent and rarely require further tweaking by the user. The new algorithm saves the precious time of experienced users, facilitates utilization of FM-AFM by casual users, and removes the main hurdle on the way to fully automated FM-AFM.

Autopilot for frequency-modulation atomic force microscopy

NASA Astrophysics Data System (ADS)

Kuchuk, Kfir; Schlesinger, Itai; Sivan, Uri

2015-10-01

One of the most challenging aspects of operating an atomic force microscope (AFM) is finding optimal feedback parameters. This statement applies particularly to frequency-modulation AFM (FM-AFM), which utilizes three feedback loops to control the cantilever excitation amplitude, cantilever excitation frequency, and z-piezo extension. These loops are regulated by a set of feedback parameters, tuned by the user to optimize stability, sensitivity, and noise in the imaging process. Optimization of these parameters is difficult due to the coupling between the frequency and z-piezo feedback loops by the non-linear tip-sample interaction. Four proportional-integral (PI) parameters and two lock-in parameters regulating these loops require simultaneous optimization in the presence of a varying unknown tip-sample coupling. Presently, this optimization is done manually in a tedious process of trial and error. Here, we report on the development and implementation of an algorithm that computes the control parameters automatically. The algorithm reads the unperturbed cantilever resonance frequency, its quality factor, and the z-piezo driving signal power spectral density. It analyzes the poles and zeros of the total closed loop transfer function, extracts the unknown tip-sample transfer function, and finds four PI parameters and two lock-in parameters for the frequency and z-piezo control loops that optimize the bandwidth and step response of the total system. Implementation of the algorithm in a home-built AFM shows that the calculated parameters are consistently excellent and rarely require further tweaking by the user. The new algorithm saves the precious time of experienced users, facilitates utilization of FM-AFM by casual users, and removes the main hurdle on the way to fully automated FM-AFM.

Autopilot for frequency-modulation atomic force microscopy

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

Kuchuk, Kfir; Schlesinger, Itai; Sivan, Uri, E-mail: phsivan@tx.technion.ac.il

2015-10-15

One of the most challenging aspects of operating an atomic force microscope (AFM) is finding optimal feedback parameters. This statement applies particularly to frequency-modulation AFM (FM-AFM), which utilizes three feedback loops to control the cantilever excitation amplitude, cantilever excitation frequency, and z-piezo extension. These loops are regulated by a set of feedback parameters, tuned by the user to optimize stability, sensitivity, and noise in the imaging process. Optimization of these parameters is difficult due to the coupling between the frequency and z-piezo feedback loops by the non-linear tip-sample interaction. Four proportional-integral (PI) parameters and two lock-in parameters regulating these loopsmore » require simultaneous optimization in the presence of a varying unknown tip-sample coupling. Presently, this optimization is done manually in a tedious process of trial and error. Here, we report on the development and implementation of an algorithm that computes the control parameters automatically. The algorithm reads the unperturbed cantilever resonance frequency, its quality factor, and the z-piezo driving signal power spectral density. It analyzes the poles and zeros of the total closed loop transfer function, extracts the unknown tip-sample transfer function, and finds four PI parameters and two lock-in parameters for the frequency and z-piezo control loops that optimize the bandwidth and step response of the total system. Implementation of the algorithm in a home-built AFM shows that the calculated parameters are consistently excellent and rarely require further tweaking by the user. The new algorithm saves the precious time of experienced users, facilitates utilization of FM-AFM by casual users, and removes the main hurdle on the way to fully automated FM-AFM.« less

Numerical simulation and optimal design of Segmented Planar Imaging Detector for Electro-Optical Reconnaissance

NASA Astrophysics Data System (ADS)

Chu, Qiuhui; Shen, Yijie; Yuan, Meng; Gong, Mali

2017-12-01

Segmented Planar Imaging Detector for Electro-Optical Reconnaissance (SPIDER) is a cutting-edge electro-optical imaging technology to realize miniaturization and complanation of imaging systems. In this paper, the principle of SPIDER has been numerically demonstrated based on the partially coherent light theory, and a novel concept of adjustable baseline pairing SPIDER system has further been proposed. Based on the results of simulation, it is verified that the imaging quality could be effectively improved by adjusting the Nyquist sampling density, optimizing the baseline pairing method and increasing the spectral channel of demultiplexer. Therefore, an adjustable baseline pairing algorithm is established for further enhancing the image quality, and the optimal design procedure in SPIDER for arbitrary targets is also summarized. The SPIDER system with adjustable baseline pairing method can broaden its application and reduce cost under the same imaging quality.

Improvement of LOD in Fluorescence Detection with Spectrally Nonuniform Background by Optimization of Emission Filtering.

PubMed

Galievsky, Victor A; Stasheuski, Alexander S; Krylov, Sergey N

2017-10-17

The limit-of-detection (LOD) in analytical instruments with fluorescence detection can be improved by reducing noise of optical background. Efficiently reducing optical background noise in systems with spectrally nonuniform background requires complex optimization of an emission filter-the main element of spectral filtration. Here, we introduce a filter-optimization method, which utilizes an expression for the signal-to-noise ratio (SNR) as a function of (i) all noise components (dark, shot, and flicker), (ii) emission spectrum of the analyte, (iii) emission spectrum of the optical background, and (iv) transmittance spectrum of the emission filter. In essence, the noise components and the emission spectra are determined experimentally and substituted into the expression. This leaves a single variable-the transmittance spectrum of the filter-which is optimized numerically by maximizing SNR. Maximizing SNR provides an accurate way of filter optimization, while a previously used approach based on maximizing a signal-to-background ratio (SBR) is the approximation that can lead to much poorer LOD specifically in detection of fluorescently labeled biomolecules. The proposed filter-optimization method will be an indispensable tool for developing new and improving existing fluorescence-detection systems aiming at ultimately low LOD.

Prediction of soil organic carbon with different parent materials development using visible-near infrared spectroscopy.

PubMed

Liu, Jinbao; Han, Jichang; Zhang, Yang; Wang, Huanyuan; Kong, Hui; Shi, Lei

2018-06-05

The storage of soil organic carbon (SOC) should improve soil fertility. Conventional determination of SOC is expensive and tedious. Visible-near infrared reflectance spectroscopy is a practical and cost-effective approach that has been successfully used SOC concentration. Soil spectral inversion model could quickly and efficiently determine SOC content. This paper presents a study dealing with SOC estimation through the combination of soil spectroscopy and stepwise multiple linear regression (SMLR), partial least squares regression (PLSR), principal component regression (PCR). Spectral measurements for 106 soil samples were acquired using an ASD FieldSpec 4 standard-res spectroradiometer (350-2500 nm). Six types of transformations and three regression methods were applied to build for the quantification of different parent materials development soil. The results show that (1)the basaltic volcanic clastics development of SOC spectral response bands located in 500 nm, 800 nm; Trachyte spectral response of the soil quality, and the volcanic clastics development at 405 nm, 465 nm, 575 nm, 1105 nm. (2) Basaltic volcanic debris soil development, first deviation of maximum correlation coefficient is 0.8898; thick surface soil of the development of rocky volcanic debris from bottom reflectivity logarithm of first deviation of maximum correlation coefficient is 0.9029. (3) Soil organic matter content of basaltic volcanic clastics development optimal prediction model based on spectral reflectance inverse logarithms of first deviation of SMLR. Independent variable number is 7, Rv 2  = 0.9720, RMSEP = 2.0590, sig = 0.003. Trachyte qualitative volcanic clastics developed soil organic matter content of the optimal prediction model based on spectral reflectance inverse logarithms of first deviation of PLSR. Model number of the independent variables Pc = 5, Rc = 0.9872, Rc 2  = 0.9745, RMSEC = 0.4821, SEC = 0.4906, forecasts determine coefficient Rv 2  = 0.9702, RMSEP = 0.9563, SEP = 0.9711, Bias = 0.0637. Copyright © 2018 Elsevier B.V. All rights reserved.

Autopiquer - a Robust and Reliable Peak Detection Algorithm for Mass Spectrometry

NASA Astrophysics Data System (ADS)

Kilgour, David P. A.; Hughes, Sam; Kilgour, Samantha L.; Mackay, C. Logan; Palmblad, Magnus; Tran, Bao Quoc; Goo, Young Ah; Ernst, Robert K.; Clarke, David J.; Goodlett, David R.

2017-02-01

We present a simple algorithm for robust and unsupervised peak detection by determining a noise threshold in isotopically resolved mass spectrometry data. Solving this problem will greatly reduce the subjective and time-consuming manual picking of mass spectral peaks and so will prove beneficial in many research applications. The Autopiquer approach uses autocorrelation to test for the presence of (isotopic) structure in overlapping windows across the spectrum. Within each window, a noise threshold is optimized to remove the most unstructured data, whilst keeping as much of the (isotopic) structure as possible. This algorithm has been successfully demonstrated for both peak detection and spectral compression on data from many different classes of mass spectrometer and for different sample types, and this approach should also be extendible to other types of data that contain regularly spaced discrete peaks.

Autopiquer - a Robust and Reliable Peak Detection Algorithm for Mass Spectrometry.

PubMed

Kilgour, David P A; Hughes, Sam; Kilgour, Samantha L; Mackay, C Logan; Palmblad, Magnus; Tran, Bao Quoc; Goo, Young Ah; Ernst, Robert K; Clarke, David J; Goodlett, David R

2017-02-01

We present a simple algorithm for robust and unsupervised peak detection by determining a noise threshold in isotopically resolved mass spectrometry data. Solving this problem will greatly reduce the subjective and time-consuming manual picking of mass spectral peaks and so will prove beneficial in many research applications. The Autopiquer approach uses autocorrelation to test for the presence of (isotopic) structure in overlapping windows across the spectrum. Within each window, a noise threshold is optimized to remove the most unstructured data, whilst keeping as much of the (isotopic) structure as possible. This algorithm has been successfully demonstrated for both peak detection and spectral compression on data from many different classes of mass spectrometer and for different sample types, and this approach should also be extendible to other types of data that contain regularly spaced discrete peaks. Graphical Abstract ᅟ.

Statistically Optimized Inversion Algorithm for Enhanced Retrieval of Aerosol Properties from Spectral Multi-Angle Polarimetric Satellite Observations

NASA Technical Reports Server (NTRS)

Dubovik, O; Herman, M.; Holdak, A.; Lapyonok, T.; Taure, D.; Deuze, J. L.; Ducos, F.; Sinyuk, A.

2011-01-01

The proposed development is an attempt to enhance aerosol retrieval by emphasizing statistical optimization in inversion of advanced satellite observations. This optimization concept improves retrieval accuracy relying on the knowledge of measurement error distribution. Efficient application of such optimization requires pronounced data redundancy (excess of the measurements number over number of unknowns) that is not common in satellite observations. The POLDER imager on board the PARASOL microsatellite registers spectral polarimetric characteristics of the reflected atmospheric radiation at up to 16 viewing directions over each observed pixel. The completeness of such observations is notably higher than for most currently operating passive satellite aerosol sensors. This provides an opportunity for profound utilization of statistical optimization principles in satellite data inversion. The proposed retrieval scheme is designed as statistically optimized multi-variable fitting of all available angular observations obtained by the POLDER sensor in the window spectral channels where absorption by gas is minimal. The total number of such observations by PARASOL always exceeds a hundred over each pixel and the statistical optimization concept promises to be efficient even if the algorithm retrieves several tens of aerosol parameters. Based on this idea, the proposed algorithm uses a large number of unknowns and is aimed at retrieval of extended set of parameters affecting measured radiation.

Experimental geometry for simultaneous beam characterization and sample imaging allowing for pink beam Fourier transform holography or coherent diffractive imaging

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

Flewett, Samuel; Eisebitt, Stefan

2011-02-20

One consequence of the self-amplified stimulated emission process used to generate x rays in free electron lasers (FELs) is the intrinsic shot-to-shot variance in the wavelength and temporal coherence. In order to optimize the results from diffractive imaging experiments at FEL sources, it will be advantageous to acquire a means of collecting coherence and spectral information simultaneously with the diffraction pattern from the sample we wish to study. We present a holographic mask geometry, including a grating structure, which can be used to extract both temporal and spatial coherence information alongside the sample scatter from each individual FEL shot andmore » also allows for the real space reconstruction of the sample using either Fourier transform holography or iterative phase retrieval.« less

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.

Accuracy assessment and characterization of x-ray coded aperture coherent scatter spectral imaging for breast cancer classification

PubMed Central

Lakshmanan, Manu N.; Greenberg, Joel A.; Samei, Ehsan; Kapadia, Anuj J.

2017-01-01

Abstract. Although transmission-based x-ray imaging is the most commonly used imaging approach for breast cancer detection, it exhibits false negative rates higher than 15%. To improve cancer detection accuracy, x-ray coherent scatter computed tomography (CSCT) has been explored to potentially detect cancer with greater consistency. However, the 10-min scan duration of CSCT limits its possible clinical applications. The coded aperture coherent scatter spectral imaging (CACSSI) technique has been shown to reduce scan time through enabling single-angle imaging while providing high detection accuracy. Here, we use Monte Carlo simulations to test analytical optimization studies of the CACSSI technique, specifically for detecting cancer in ex vivo breast samples. An anthropomorphic breast tissue phantom was modeled, a CACSSI imaging system was virtually simulated to image the phantom, a diagnostic voxel classification algorithm was applied to all reconstructed voxels in the phantom, and receiver-operator characteristics analysis of the voxel classification was used to evaluate and characterize the imaging system for a range of parameters that have been optimized in a prior analytical study. The results indicate that CACSSI is able to identify the distribution of cancerous and healthy tissues (i.e., fibroglandular, adipose, or a mix of the two) in tissue samples with a cancerous voxel identification area-under-the-curve of 0.94 through a scan lasting less than 10 s per slice. These results show that coded aperture scatter imaging has the potential to provide scatter images that automatically differentiate cancerous and healthy tissue within ex vivo samples. Furthermore, the results indicate potential CACSSI imaging system configurations for implementation in subsequent imaging development studies. PMID:28331884

Studies on the origin and transformation of selenium and its chemical species along the process of petroleum refining

NASA Astrophysics Data System (ADS)

Stivanin de Almeida, Cibele M.; Ribeiro, Anderson S.; Saint'Pierre, Tatiana D.; Miekeley, Norbert

2009-06-01

Inductively coupled plasma optical emission spectrometry and mass spectrometry (ICPMS), the latter hyphenated to flow injection hydride generation, electrothermal vaporization or ion chromatography, have been applied to the chemical characterization of crude oil, aqueous process stream samples and wastewaters from a petroleum refinery, in order to get information on the behavior of selenium and its chemical species along effluent generation and treatment. Multielemental characterization of these effluents by ICPMS revealed a complex composition of most of them, with high salinity and potential spectral and non-spectral interferents present. For this reason, a critical re-assessment of the analytical techniques for the determination of total selenium and its species was performed. Methane was employed as gas in dynamic reaction cell ICPMS and cell parameters were optimized for a simulated brine matrix and for diluted aqueous solutions to match the expected process and treated wastewaters samples. The signal-to-background ratios for 78Se and 80Se were used as criteria in optimization, the first isotope resulting in better detection limits for the simulated brine matrix ( 78Se: 0.07 μg L - 1 , 80Se: 0.31 μg L - 1 ). A large variability in the concentration of selenium (from < 10 μg kg - 1 up to 960 μg kg - 1 ) was observed in 16 of the most frequently processed crude oil samples in the refinery here investigated, which may explain the pronounced concentrations changes of this element measured in aqueous process stream and wastewater samples. Highest concentrations of total selenium were analyzed in samples from the hydrotreater (up to about 1800 μg L - 1 ). The predominance of selenocyanate (SeCN -) was observed in most of the wastewaters so far investigated, but also other species were detected with retention times different from Se(IV), Se(VI) and SeCN -. Colloidal selenium (Se 0) was the only Se-species observed in samples from the atmospheric distillation unit, but was also identified in other samples, most probably formed by the decomposition of SeCN - or other unstable species.

The establishment and external validation of NIR qualitative analysis model for waste polyester-cotton blend fabrics.

PubMed

Li, Feng; Li, Wen-Xia; Zhao, Guo-Liang; Tang, Shi-Jun; Li, Xue-Jiao; Wu, Hong-Mei

2014-10-01

A series of 354 polyester-cotton blend fabrics were studied by the near-infrared spectra (NIRS) technology, and a NIR qualitative analysis model for different spectral characteristics was established by partial least squares (PLS) method combined with qualitative identification coefficient. There were two types of spectrum for dying polyester-cotton blend fabrics: normal spectrum and slash spectrum. The slash spectrum loses its spectral characteristics, which are effected by the samples' dyes, pigments, matting agents and other chemical additives. It was in low recognition rate when the model was established by the total sample set, so the samples were divided into two types of sets: normal spectrum sample set and slash spectrum sample set, and two NIR qualitative analysis models were established respectively. After the of models were established the model's spectral region, pretreatment methods and factors were optimized based on the validation results, and the robustness and reliability of the model can be improved lately. The results showed that the model recognition rate was improved greatly when they were established respectively, the recognition rate reached up to 99% when the two models were verified by the internal validation. RC (relation coefficient of calibration) values of the normal spectrum model and slash spectrum model were 0.991 and 0.991 respectively, RP (relation coefficient of prediction) values of them were 0.983 and 0.984 respectively, SEC (standard error of calibration) values of them were 0.887 and 0.453 respectively, SEP (standard error of prediction) values of them were 1.131 and 0.573 respectively. A series of 150 bounds samples reached used to verify the normal spectrum model and slash spectrum model and the recognition rate reached up to 91.33% and 88.00% respectively. It showed that the NIR qualitative analysis model can be used for identification in the recycle site for the polyester-cotton blend fabrics.

Land ECVs from QA4ECV using an optimal estimation framework

NASA Astrophysics Data System (ADS)

Muller, Jan-Peter; Kharbouche, Said; Lewis, Philip; Danne, Olaf; Blessing, Simon; Giering, Ralf; Gobron, Nadine; Lanconelli, Christian; Govaerts, Yves; Schulz, Joerg; Doutriaux-Boucher, Marie; Lattanzio, Alessio; Aoun, Youva

2017-04-01

In the ESA-DUE GlobAlbedo project (http://www.GlobAlbedo.org), a 15 year record of land surface albedo was generated from the European VEGETATION & MERIS sensors using optimal estimation. This was based on 3 broadbands (0.4-0.7, 0.7-3, 0.4-3µm) and fused data at level-2 after converting from spectral narrowband to these 3 broadbands with surface BRFs. A 10 year long record of land surface albedo climatology was generated from Collection 5 of the MODIS BRDF product for these same broadbands. This was employed as an a priori estimate for an optimal estimation based retrieval of land surface albedo when there were insufficient samples from the European sensors. This so-called MODIS prior was derived at 1km from the 500m MOD43A1,2 BRDF inputs every 8 days using the QA bits and the method described in the GlobAlbedo ATBD which is available from the website (http://www.globalbedo.org/docs/GlobAlbedo_Albedo_ATBD_V4.12.pdf). In the ESA-STSE WACMOS-ET project, FastOpt generated fapar & LAI based on this GlobAlbedo BRDF with associated per pixel uncertainty using the TIP framework. In the successor EU-FP7-QA4ECV* project, we have developed a 33 year record (1981-2014) of Earth surface spectral and broadband albedo (i.e. including the ocean and sea-ice) using optimal estimation for the land and where available, relevant sensors for "instantaneous" retrievals over the poles (Kharbouche & Muller, this conference). This requires the longest possible land surface spectral and broadband BRDF record that can only be supplied by a 16 year of MODIS Collection 6 BRDFs at 500m but produced on a daily basis. The CEMS Big Data computer at RAL was used to generate 7 spectral bands and 3 broadband BRDF with and without snow and snow_only. We will discuss the progress made since the start of the QA4ECV project on the production of a new fused land surface BRDF/albedo spectral and broadband CDR product based on four European sensors: MERIS, (A)ATSR(2), VEGETATION, PROBA-V and two US sensors: MISR & MODIS. For the European sensors, an uniform atmospheric correction scheme has been employed to generate spectral BRF products and these have all been mapped into MODIS spectral bands whilst the US sensors have employed their own level-2 BRF retrieval schemes with associated uncertainty information. Progress is also demonstrated on the use of TIP for fapar/LAI retrieval from the broadband BRDFs as well as fapar from AVHRR based on retrievals from MERIS and OLCI. In parallel, work has taken place at two of our partners on the production of a new geostationary broadband BRF and associated albedo and their fusion with AVHRR-LTDR for a 33 year record. QA4ECV has received funding from the European Union's Seventh Framework Programme (FP7/2007-2013) under grant agreement no. 607405

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.

Optimization of spectral bands for hyperspectral remote sensing of forest vegetation

NASA Astrophysics Data System (ADS)

Dmitriev, Egor V.; Kozoderov, Vladimir V.

2013-10-01

Optimization principles of accounting for the most informative spectral channels in hyperspectral remote sensing data processing serve to enhance the efficiency of the employed high-productive computers. The problem of pattern recognition of the remotely sensed land surface objects with the accent on the forests is outlined from the point of view of the spectral channels optimization on the processed hyperspectral images. The relevant computational procedures are tested using the images obtained by the produced in Russia hyperspectral camera that was installed on a gyro-stabilized platform to conduct the airborne flight campaigns. The Bayesian classifier is used for the pattern recognition of the forests with different tree species and age. The probabilistically optimal algorithm constructed on the basis of the maximum likelihood principle is described to minimize the probability of misclassification given by this classifier. The classification error is the major category to estimate the accuracy of the applied algorithm by the known holdout cross-validation method. Details of the related techniques are presented. Results are shown of selecting the spectral channels of the camera while processing the images having in mind radiometric distortions that diminish the classification accuracy. The spectral channels are selected of the obtained subclasses extracted from the proposed validation techniques and the confusion matrices are constructed that characterize the age composition of the classified pine species as well as the broad age-class recognition for the pine and birch species with the fully illuminated parts of their crowns.

Project STOP (Spectral Thermal Optimization Program)

NASA Technical Reports Server (NTRS)

Goldhammer, L. J.; Opjorden, R. W.; Goodelle, G. S.; Powe, J. S.

1977-01-01

The spectral thermal optimization of solar cell configurations for various solar panel applications is considered. The method of optimization depends upon varying the solar cell configuration's optical characteristics to minimize panel temperatures, maximize power output and decrease the power delta from beginning of life to end of life. Four areas of primary investigation are: (1) testing and evaluation of ultraviolet resistant coverslide adhesives, primarily FEP as an adhesive; (2) examination of solar cell absolute spectral response and corresponding cell manufacturing processes that affect it; (3) experimental work with solar cell manufacturing processes that vary cell reflectance (solar absorptance); and (4) experimental and theoretical studies with various coverslide filter designs, mainly a red rejection filter. The Hughes' solar array prediction program has been modified to aid in evaluating the effect of each of the above four areas on the output of a solar panel in orbit.

Solid sampling determination of magnesium in lithium niobate crystals by graphite furnace atomic absorption spectrometry

NASA Astrophysics Data System (ADS)

Dravecz, Gabriella; Laczai, Nikoletta; Hajdara, Ivett; Bencs, László

2016-12-01

The vaporization/atomization processes of Mg in high-resolution continuum source graphite furnace atomic absorption spectrometry (HR-CS-GFAAS) were investigated by evaporating solid (powder) samples of lithium niobate (LiNbO3) optical single crystals doped with various amounts of Mg in a transversally heated graphite atomizer (THGA). Optimal analytical conditions were attained by using the Mg I 215.4353 nm secondary spectral line. An optimal pyrolysis temperature of 1500 °C was found for Mg, while the compromise atomization temperature in THGAs (2400 °C) was applied for analyte vaporization. The calibration was performed against solid (powered) lithium niobate crystal standards. The standards were prepared with exactly known Mg content via solid state fusion of the oxide components of the matrix and analyte. The correlation coefficient (R value) of the linear calibration was not worse than 0.9992. The calibration curves were linear in the dopant concentration range of interest (0.74-7.25 mg/g Mg), when dosing 3-10 mg of the powder samples into the graphite sample insertion boats. The Mg content of the studied 19 samples was in the range of 1.69-4.13 mg/g. The precision of the method was better than 6.3%. The accuracy of the results was verified by means of flame atomic absorption spectrometry with solution sample introduction after digestion of several crystal samples.

Determination of yolk contamination in liquid egg white using Raman spectroscopy.

PubMed

Cluff, K; Konda Naganathan, G; Jonnalagada, D; Mortensen, I; Wehling, R; Subbiah, J

2016-07-01

Purified egg white is an important ingredient in a number of baked and confectionary foods because of its foaming properties. However, yolk contamination in amounts as low as 0.01% can impede the foaming ability of egg white. In this study, we used Raman spectroscopy to evaluate the hypothesis that yolk contamination in egg white could be detected based on its molecular optical properties. Yolk contaminated egg white samples (n = 115) with contamination levels ranging from 0% to 0.25% (on weight basis) were prepared. The samples were excited with a 785 nm laser and Raman spectra from 250 to 3,200 cm(-1) were recorded. The Raman spectra were baseline corrected using an optimized piecewise cubic interpolation on each spectrum and then normalized with a standard normal variate transformation. Samples were randomly divided into calibration (n = 77) and validation (n = 38) data sets. A partial least squares regression (PLSR) model was developed to predict yolk contamination levels, based on the Raman spectral fingerprint. Raman spectral peaks, in the spectral region of 1,080 and 1,666 cm(-1), had the largest influence on detecting yolk contamination in egg white. The PLSR model was able to correctly predict yolk contamination levels with an R(2) = 0.90 in the validation data set. These results demonstrate the capability of Raman spectroscopy for detection of yolk contamination at very low levels in egg white and present a strong case for development of an on-line system to be deployed in egg processing plants. © 2016 Poultry Science Association Inc.

Temporal measurement and analysis of high-resolution spectral signatures of plants and relationships to biophysical characteristics

NASA Astrophysics Data System (ADS)

Bostater, Charles R., Jr.; Rebbman, Jan; Hall, Carlton; Provancha, Mark; Vieglais, David

1995-11-01

Measurements of temporal reflectance signatures as a function of growing season for sand live oak (Quercus geminata), myrtle oak (Q. myrtifolia, and saw palmetto (Serenoa repens) were collected during a two year study period. Canopy level spectral reflectance signatures, as a function of 252 channels between 368 and 1115 nm, were collected using near nadir viewing geometry and a consistent sun illumination angle. Leaf level reflectance measurements were made in the laboratory using a halogen light source and an environmental optics chamber with a barium sulfate reflectance coating. Spectral measurements were related to several biophysical measurements utilizing optimal passive ambient correlation spectroscopy (OPACS) technique. Biophysical parameters included percent moisture, water potential (MPa), total chlorophyll, and total Kjeldahl nitrogen. Quantitative data processing techniques were used to determine optimal bands based on the utilization of a second order derivative or inflection estimator. An optical cleanup procedure was then employed that computes the double inflection ratio (DIR) spectra for all possible three band combinations normalized to the previously computed optimal bands. These results demonstrate a unique approach to the analysis of high spectral resolution reflectance signatures for estimation of several biophysical measures of plants at the leaf and canopy level from optimally selected bands or bandwidths.

Optimal design of waveform digitisers for both energy resolution and pulse shape discrimination

NASA Astrophysics Data System (ADS)

Cang, Jirong; Xue, Tao; Zeng, Ming; Zeng, Zhi; Ma, Hao; Cheng, Jianping; Liu, Yinong

2018-04-01

Fast digitisers and digital pulse processing have been widely used for spectral application and pulse shape discrimination (PSD) owing to their advantages in terms of compactness, higher trigger rates, offline analysis, etc. Meanwhile, the noise of readout electronics is usually trivial for organic, plastic, or liquid scintillator with PSD ability because of their poor intrinsic energy resolution. However, LaBr3(Ce) has been widely used for its excellent energy resolution and has been proven to have PSD ability for alpha/gamma particles. Therefore, designing a digital acquisition system for such scintillators as LaBr3(Ce) with both optimal energy resolution and promising PSD ability is worthwhile. Several experimental research studies about the choice of digitiser properties for liquid scintillators have already been conducted in terms of the sampling rate and vertical resolution. Quantitative analysis on the influence of waveform digitisers, that is, fast amplifier (optional), sampling rates, and vertical resolution, on both applications is still lacking. The present paper provides quantitative analysis of these factors and, hence, general rules about the optimal design of digitisers for both energy resolution and PSD application according to the noise analysis of time-variant gated charge integration.

Optimizing interconnections to maximize the spectral radius of interdependent networks

NASA Astrophysics Data System (ADS)

Chen, Huashan; Zhao, Xiuyan; Liu, Feng; Xu, Shouhuai; Lu, Wenlian

2017-03-01

The spectral radius (i.e., the largest eigenvalue) of the adjacency matrices of complex networks is an important quantity that governs the behavior of many dynamic processes on the networks, such as synchronization and epidemics. Studies in the literature focused on bounding this quantity. In this paper, we investigate how to maximize the spectral radius of interdependent networks by optimally linking k internetwork connections (or interconnections for short). We derive formulas for the estimation of the spectral radius of interdependent networks and employ these results to develop a suite of algorithms that are applicable to different parameter regimes. In particular, a simple algorithm is to link the k nodes with the largest k eigenvector centralities in one network to the node in the other network with a certain property related to both networks. We demonstrate the applicability of our algorithms via extensive simulations. We discuss the physical implications of the results, including how the optimal interconnections can more effectively decrease the threshold of epidemic spreading in the susceptible-infected-susceptible model and the threshold of synchronization of coupled Kuramoto oscillators.

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

Optimization of analytical and pre-analytical conditions for MALDI-TOF-MS human urine protein profiles.

PubMed

Calvano, C D; Aresta, A; Iacovone, M; De Benedetto, G E; Zambonin, C G; Battaglia, M; Ditonno, P; Rutigliano, M; Bettocchi, C

2010-03-11

Protein analysis in biological fluids, such as urine, by means of mass spectrometry (MS) still suffers for insufficient standardization in protocols for sample collection, storage and preparation. In this work, the influence of these variables on healthy donors human urine protein profiling performed by matrix assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS) was studied. A screening of various urine sample pre-treatment procedures and different sample deposition approaches on the MALDI target was performed. The influence of urine samples storage time and temperature on spectral profiles was evaluated by means of principal component analysis (PCA). The whole optimized procedure was eventually applied to the MALDI-TOF-MS analysis of human urine samples taken from prostate cancer patients. The best results in terms of detected ions number and abundance in the MS spectra were obtained by using home-made microcolumns packed with hydrophilic-lipophilic balance (HLB) resin as sample pre-treatment method; this procedure was also less expensive and suitable for high throughput analyses. Afterwards, the spin coating approach for sample deposition on the MALDI target plate was optimized, obtaining homogenous and reproducible spots. Then, PCA indicated that low storage temperatures of acidified and centrifuged samples, together with short handling time, allowed to obtain reproducible profiles without artifacts contribution due to experimental conditions. Finally, interesting differences were found by comparing the MALDI-TOF-MS protein profiles of pooled urine samples of healthy donors and prostate cancer patients. The results showed that analytical and pre-analytical variables are crucial for the success of urine analysis, to obtain meaningful and reproducible data, even if the intra-patient variability is very difficult to avoid. It has been proven how pooled urine samples can be an interesting way to make easier the comparison between healthy and pathological samples and to individuate possible differences in the protein expression between the two sets of samples. Copyright 2009 Elsevier B.V. All rights reserved.

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

Inversion of Robin coefficient by a spectral stochastic finite element approach

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

Jin Bangti; Zou Jun

2008-03-01

This paper investigates a variational approach to the nonlinear stochastic inverse problem of probabilistically calibrating the Robin coefficient from boundary measurements for the steady-state heat conduction. The problem is formulated into an optimization problem, and mathematical properties relevant to its numerical computations are investigated. The spectral stochastic finite element method using polynomial chaos is utilized for the discretization of the optimization problem, and its convergence is analyzed. The nonlinear conjugate gradient method is derived for the optimization system. Numerical results for several two-dimensional problems are presented to illustrate the accuracy and efficiency of the stochastic finite element method.

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.

Pseudo-spectral control of a novel oscillating surge wave energy converter in regular waves for power optimization including load reduction

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

Tom, Nathan M.; Yu, Yi -Hsiang; Wright, Alan D.

The aim of this study is to describe a procedure to maximize the power-to-load ratio of a novel wave energy converter (WEC) that combines an oscillating surge wave energy converter with variable structural components. The control of the power-take-off torque will be on a wave-to-wave timescale, whereas the structure will be controlled statically such that the geometry remains the same throughout the wave period. Linear hydrodynamic theory is used to calculate the upper and lower bounds for the time-averaged absorbed power and surge foundation loads while assuming that the WEC motion remains sinusoidal. Previous work using pseudo-spectral techniques to solvemore » the optimal control problem focused solely on maximizing absorbed energy. This work extends the optimal control problem to include a measure of the surge foundation force in the optimization. The objective function includes two competing terms that force the optimizer to maximize power capture while minimizing structural loads. A penalty weight was included with the surge foundation force that allows control of the optimizer performance based on whether emphasis should be placed on power absorption or load shedding. Results from pseudo-spectral optimal control indicate that a unit reduction in time-averaged power can be accompanied by a greater reduction in surge-foundation force.« less

Pseudo-spectral control of a novel oscillating surge wave energy converter in regular waves for power optimization including load reduction

DOE PAGES

Tom, Nathan M.; Yu, Yi -Hsiang; Wright, Alan D.; ...

2017-04-18

The aim of this study is to describe a procedure to maximize the power-to-load ratio of a novel wave energy converter (WEC) that combines an oscillating surge wave energy converter with variable structural components. The control of the power-take-off torque will be on a wave-to-wave timescale, whereas the structure will be controlled statically such that the geometry remains the same throughout the wave period. Linear hydrodynamic theory is used to calculate the upper and lower bounds for the time-averaged absorbed power and surge foundation loads while assuming that the WEC motion remains sinusoidal. Previous work using pseudo-spectral techniques to solvemore » the optimal control problem focused solely on maximizing absorbed energy. This work extends the optimal control problem to include a measure of the surge foundation force in the optimization. The objective function includes two competing terms that force the optimizer to maximize power capture while minimizing structural loads. A penalty weight was included with the surge foundation force that allows control of the optimizer performance based on whether emphasis should be placed on power absorption or load shedding. Results from pseudo-spectral optimal control indicate that a unit reduction in time-averaged power can be accompanied by a greater reduction in surge-foundation force.« less

Inverse Analysis of Irradiated NuclearMaterial Gamma Spectra via Nonlinear Optimization

NASA Astrophysics Data System (ADS)

Dean, Garrett James

Nuclear forensics is the collection of technical methods used to identify the provenance of nuclear material interdicted outside of regulatory control. Techniques employed in nuclear forensics include optical microscopy, gas chromatography, mass spectrometry, and alpha, beta, and gamma spectrometry. This dissertation focuses on the application of inverse analysis to gamma spectroscopy to estimate the history of pulse irradiated nuclear material. Previous work in this area has (1) utilized destructive analysis techniques to supplement the nondestructive gamma measurements, and (2) been applied to samples composed of spent nuclear fuel with long irradiation and cooling times. Previous analyses have employed local nonlinear solvers, simple empirical models of gamma spectral features, and simple detector models of gamma spectral features. The algorithm described in this dissertation uses a forward model of the irradiation and measurement process within a global nonlinear optimizer to estimate the unknown irradiation history of pulse irradiated nuclear material. The forward model includes a detector response function for photopeaks only. The algorithm uses a novel hybrid global and local search algorithm to quickly estimate the irradiation parameters, including neutron fluence, cooling time and original composition. Sequential, time correlated series of measurements are used to reduce the uncertainty in the estimated irradiation parameters. This algorithm allows for in situ measurements of interdicted irradiated material. The increase in analysis speed comes with a decrease in information that can be determined, but the sample fluence, cooling time, and composition can be determined within minutes of a measurement. Furthermore, pulse irradiated nuclear material has a characteristic feature that irradiation time and flux cannot be independently estimated. The algorithm has been tested against pulse irradiated samples of pure special nuclear material with cooling times of four minutes to seven hours. The algorithm described is capable of determining the cooling time and fluence the sample was exposed to within 10% as well as roughly estimating the relative concentrations of nuclides present in the original composition.

Blue light hazard optimization for white light-emitting diode sources with high luminous efficacy of radiation and high color rendering index

NASA Astrophysics Data System (ADS)

Zhang, Jingjing; Guo, Weihong; Xie, Bin; Yu, Xingjian; Luo, Xiaobing; Zhang, Tao; Yu, Zhihua; Wang, Hong; Jin, Xing

2017-09-01

Blue light hazard of white light-emitting diodes (LED) is a hidden risk for human's photobiological safety. Recent spectral optimization methods focus on maximizing luminous efficacy and improving color performances of LEDs, but few of them take blue hazard into account. Therefore, for healthy lighting, it's urgent to propose a spectral optimization method for white LED source to exhibit low blue light hazard, high luminous efficacy of radiation (LER) and high color performances. In this study, a genetic algorithm with penalty functions was proposed for realizing white spectra with low blue hazard, maximal LER and high color rendering index (CRI) values. By simulations, white spectra from LEDs with low blue hazard, high LER (≥297 lm/W) and high CRI (≥90) were achieved at different correlated color temperatures (CCTs) from 2013 K to 7845 K. Thus, the spectral optimization method can be used for guiding the fabrication of LED sources in line with photobiological safety. It is also found that the maximum permissible exposure duration of the optimized spectra increases by 14.9% than that of bichromatic phosphor-converted LEDs with equal CCT.

Spectral optimization simulation of white light based on the photopic eye-sensitivity curve

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

Dai, Qi, E-mail: qidai@tongji.edu.cn; Institute for Advanced Study, Tongji University, 1239 Siping Road, Shanghai 200092; Key Laboratory of Ecology and Energy-saving Study of Dense Habitat

Spectral optimization simulation of white light is studied to boost maximum attainable luminous efficacy of radiation at high color-rendering index (CRI) and various color temperatures. The photopic eye-sensitivity curve V(λ) is utilized as the dominant portion of white light spectra. Emission spectra of a blue InGaN light-emitting diode (LED) and a red AlInGaP LED are added to the spectrum of V(λ) to match white color coordinates. It is demonstrated that at the condition of color temperature from 2500 K to 6500 K and CRI above 90, such white sources can achieve spectral efficacy of 330–390 lm/W, which is higher than the previously reportedmore » theoretical maximum values. We show that this eye-sensitivity-based approach also has advantages on component energy conversion efficiency compared with previously reported optimization solutions.« less

Selective enhancement of carbohydrate ion abundances by diamond nanoparticles for mass spectrometric analysis.

PubMed

Wu, Chieh-Lin; Wang, Chia-Chen; Lai, Yin-Hung; Lee, Hsun; Lin, Jia-Der; Lee, Yuan Tseh; Wang, Yi-Sheng

2013-04-16

Diamond nanoparticles (DNPs) were incorporated into matrix-assisted laser desorption/ionization (MALDI) samples to enhance the sensitivity of the mass spectrometer to carbohydrates. The DNPs optimize the MALDI sample morphology and thermalize the samples for thermally labile compounds because they have a high thermal conductivity, a low extinction coefficient in UV-vis spectral range, and stable chemical properties. The best enhancement effect was achieved when matrix, DNP, and carbohydrate solutions were deposited and vacuum-dried consecutively to form a trilayer sample morphology. It allows the direct identification of underivatized carbohydrates mixed with equal amount of proteins because no increase in the ion abundance of proteins was achieved. For dextran with an average molecular weight of 1500, the trilayer method typically improves the sensitivity by 79- and 7-fold in comparison to the conventional dried-droplet and thin-layer methods, respectively.

Contraction Options and Optimal Multiple-Stopping in Spectrally Negative Lévy Models

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

Yamazaki, Kazutoshi, E-mail: kyamazak@kansai-u.ac.jp

This paper studies the optimal multiple-stopping problem arising in the context of the timing option to withdraw from a project in stages. The profits are driven by a general spectrally negative Lévy process. This allows the model to incorporate sudden declines of the project values, generalizing greatly the classical geometric Brownian motion model. We solve the one-stage case as well as the extension to the multiple-stage case. The optimal stopping times are of threshold-type and the value function admits an expression in terms of the scale function. A series of numerical experiments are conducted to verify the optimality and tomore » evaluate the efficiency of the algorithm.« less

Optimization of neural network architecture for classification of radar jamming FM signals

NASA Astrophysics Data System (ADS)

Soto, Alberto; Mendoza, Ariadna; Flores, Benjamin C.

2017-05-01

The purpose of this study is to investigate several artificial Neural Network (NN) architectures in order to design a cognitive radar system capable of optimally distinguishing linear Frequency-Modulated (FM) signals from bandlimited Additive White Gaussian Noise (AWGN). The goal is to create a theoretical framework to determine an optimal NN architecture to achieve a Probability of Detection (PD) of 95% or higher and a Probability of False Alarm (PFA) of 1.5% or lower at 5 dB Signal to Noise Ratio (SNR). Literature research reveals that the frequency-domain power spectral densities characterize a signal more efficiently than its time-domain counterparts. Therefore, the input data is preprocessed by calculating the magnitude square of the Discrete Fourier Transform of the digitally sampled bandlimited AWGN and linear FM signals to populate a matrix containing N number of samples and M number of spectra. This matrix is used as input for the NN, and the spectra are divided as follows: 70% for training, 15% for validation, and 15% for testing. The study begins by experimentally deducing the optimal number of hidden neurons (1-40 neurons), then the optimal number of hidden layers (1-5 layers), and lastly, the most efficient learning algorithm. The training algorithms examined are: Resilient Backpropagation, Scaled Conjugate Gradient, Conjugate Gradient with Powell/Beale Restarts, Polak-Ribiére Conjugate Gradient, and Variable Learning Rate Backpropagation. We determine that an architecture with ten hidden neurons (or higher), one hidden layer, and a Scaled Conjugate Gradient for training algorithm encapsulates an optimal architecture for our application.

Optimality of the barrier strategy in de Finetti's dividend problem for spectrally negative Lévy processes: An alternative approach

NASA Astrophysics Data System (ADS)

Yin, Chuancun; Wang, Chunwei

2009-11-01

The optimal dividend problem proposed in de Finetti [1] is to find the dividend-payment strategy that maximizes the expected discounted value of dividends which are paid to the shareholders until the company is ruined. Avram et al. [9] studied the case when the risk process is modelled by a general spectrally negative Lévy process and Loeffen [10] gave sufficient conditions under which the optimal strategy is of the barrier type. Recently Kyprianou et al. [11] strengthened the result of Loeffen [10] which established a larger class of Lévy processes for which the barrier strategy is optimal among all admissible ones. In this paper we use an analytical argument to re-investigate the optimality of barrier dividend strategies considered in the three recent papers.

Resolution and throughput optimized intraoperative spectrally encoded coherence tomography and reflectometry (iSECTR) for multimodal imaging during ophthalmic microsurgery

NASA Astrophysics Data System (ADS)

Malone, Joseph D.; El-Haddad, Mohamed T.; Leeburg, Kelsey C.; Terrones, Benjamin D.; Tao, Yuankai K.

2018-02-01

Limited visualization of semi-transparent structures in the eye remains a critical barrier to improving clinical outcomes and developing novel surgical techniques. While increases in imaging speed has enabled intraoperative optical coherence tomography (iOCT) imaging of surgical dynamics, several critical barriers to clinical adoption remain. Specifically, these include (1) static field-of-views (FOVs) requiring manual instrument-tracking; (2) high frame-rates require sparse sampling, which limits FOV; and (3) small iOCT FOV also limits the ability to co-register data with surgical microscopy. We previously addressed these limitations in image-guided ophthalmic microsurgery by developing microscope-integrated multimodal intraoperative swept-source spectrally encoded scanning laser ophthalmoscopy and optical coherence tomography. Complementary en face images enabled orientation and coregistration with the widefield surgical microscope view while OCT imaging enabled depth-resolved visualization of surgical instrument positions relative to anatomic structures-of-interest. In addition, we demonstrated novel integrated segmentation overlays for augmented-reality surgical guidance. Unfortunately, our previous system lacked the resolution and optical throughput for in vivo retinal imaging and necessitated removal of cornea and lens. These limitations were predominately a result of optical aberrations from imaging through a shared surgical microscope objective lens, which was modeled as a paraxial surface. Here, we present an optimized intraoperative spectrally encoded coherence tomography and reflectometry (iSECTR) system. We use a novel lens characterization method to develop an accurate model of surgical microscope objective performance and balance out inherent aberrations using iSECTR relay optics. Using this system, we demonstrate in vivo multimodal ophthalmic imaging through a surgical microscope

Seasonal trends in separability of leaf reflectance spectra for Ailanthus altissima and four other tree species

NASA Astrophysics Data System (ADS)

Burkholder, Aaron

This project investigated the spectral separability of the invasive species Ailanthus altissima, commonly called tree of heaven, and four other native species. Leaves were collected from Ailanthus and four native tree species from May 13 through August 24, 2008, and spectral reflectance factor measurements were gathered for each tree using an ASD (Boulder, Colorado) FieldSpec Pro full-range spectroradiometer. The original data covered the range from 350-2500 nm, with one reflectance measurement collected per one nm wavelength. To reduce dimensionality, the measurements were resampled to the actual resolution of the spectrometer's sensors, and regions of atmospheric absorption were removed. Continuum removal was performed on the reflectance data, resulting in a second dataset. For both the reflectance and continuum removed datasets, least angle regression (LARS) and random forest classification were used to identify a single set of optimal wavelengths across all sampled dates, a set of optimal wavelengths for each date, and the dates for which Ailanthus is most separable from other species. It was found that classification accuracy varies both with dates and bands used. Contrary to expectations that early spring would provide the best separability, the lowest classification error was observed on July 22 for the reflectance data, and on May 13, July 11 and August 1 for the continuum removed data. This suggests that July and August are also potentially good months for species differentiation. Applying continuum removal in many cases reduced classification error, although not consistently. Band selection seems to be more important for reflectance data in that it results in greater improvement in classification accuracy, and LARS appears to be an effective band selection tool. The optimal spectral bands were selected from across the spectrum, often with bands from the blue (401-431 nm), NIR (1115 nm) and SWIR (1985-1995 nm), suggesting that hyperspectral sensors with broad wavelength sensitivity are important for mapping and identification of Ailanthus.

Optimizing spectral wave estimates with adjoint-based sensitivity maps

NASA Astrophysics Data System (ADS)

Orzech, Mark; Veeramony, Jay; Flampouris, Stylianos

2014-04-01

A discrete numerical adjoint has recently been developed for the stochastic wave model SWAN. In the present study, this adjoint code is used to construct spectral sensitivity maps for two nearshore domains. The maps display the correlations of spectral energy levels throughout the domain with the observed energy levels at a selected location or region of interest (LOI/ROI), providing a full spectrum of values at all locations in the domain. We investigate the effectiveness of sensitivity maps based on significant wave height ( H s ) in determining alternate offshore instrument deployment sites when a chosen nearshore location or region is inaccessible. Wave and bathymetry datasets are employed from one shallower, small-scale domain (Duck, NC) and one deeper, larger-scale domain (San Diego, CA). The effects of seasonal changes in wave climate, errors in bathymetry, and multiple assimilation points on sensitivity map shapes and model performance are investigated. Model accuracy is evaluated by comparing spectral statistics as well as with an RMS skill score, which estimates a mean model-data error across all spectral bins. Results indicate that data assimilation from identified high-sensitivity alternate locations consistently improves model performance at nearshore LOIs, while assimilation from low-sensitivity locations results in lesser or no improvement. Use of sub-sampled or alongshore-averaged bathymetry has a domain-specific effect on model performance when assimilating from a high-sensitivity alternate location. When multiple alternate assimilation locations are used from areas of lower sensitivity, model performance may be worse than with a single, high-sensitivity assimilation point.

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

NASA Astrophysics Data System (ADS)

Bittel, Amy M.; Saldivar, Isaac S.; Nan, Xiaolin; Gibbs, Summer L.

2016-02-01

Single-molecule localization microscopy (SMLM) utilizes photoswitchable fluorophores to detect biological entities with 10-20 nm resolution. Multispectral superresolution microscopy (MSSRM) extends SMLM functionality by improving its spectral resolution up to 5 fold facilitating imaging of multicomponent cellular structures or signaling pathways. Current commercial fluorophores are not ideal for MSSRM as they are not designed to photoswitch and do not adequately cover the visible and far-red spectral regions required for MSSRM imaging. To obtain optimal MSSRM spatial and spectral resolution, fluorophores with narrow emission spectra and controllable photoswitching properties are necessary. Herein, a library of BODIPY-based fluorophores was synthesized and characterized to create optimal photoswitchable fluorophores for MSSRM. BODIPY was chosen as the core structure as it is photostable, has high quantum yield, and controllable photoswitching. The BODIPY core was modified through the addition of various aromatic moieties, resulting in a spectrally diverse library. Photoswitching properties were characterized using a novel polyvinyl alcohol (PVA) based film methodology to isolate single molecules. The PVA film methodology enabled photoswitching assessment without the need for protein conjugation, greatly improving screening efficiency of the BODIPY library. Additionally, image buffer conditions were optimized for the BODIPY-based fluorophores through systematic testing of oxygen scavenger systems, redox components, and additives. Through screening the photoswitching properties of BODIPY-based compounds in PVA films with optimized imaging buffer we identified novel fluorophores well suited for SMLM and MSSRM.

A consensus least squares support vector regression (LS-SVR) for analysis of near-infrared spectra of plant samples.

PubMed

Li, Yankun; Shao, Xueguang; Cai, Wensheng

2007-04-15

Consensus modeling of combining the results of multiple independent models to produce a single prediction avoids the instability of single model. Based on the principle of consensus modeling, a consensus least squares support vector regression (LS-SVR) method for calibrating the near-infrared (NIR) spectra was proposed. In the proposed approach, NIR spectra of plant samples were firstly preprocessed using discrete wavelet transform (DWT) for filtering the spectral background and noise, then, consensus LS-SVR technique was used for building the calibration model. With an optimization of the parameters involved in the modeling, a satisfied model was achieved for predicting the content of reducing sugar in plant samples. The predicted results show that consensus LS-SVR model is more robust and reliable than the conventional partial least squares (PLS) and LS-SVR methods.

Retrievability of atmospheric water vapour, temperature and vertical windspeed profiles from proposed sub-millimetre instrument ORTIS.

NASA Astrophysics Data System (ADS)

Hurley, Jane; Irwin, Patrick; Teanby, Nicholas; de Kok, Remco; Calcutt, Simon; Irshad, Ranah; Ellison, Brian

2010-05-01

The sub-millimetre range of the spectrum has been exploited in the field of Earth observation by many instruments over the years and has provided a plethora of information on atmospheric chemistry and dynamics - however, this spectral range has not been fully explored in planetary science. To this end, a sub-millimetre instrument, the Orbiter Terahertz Infrared Spectrometer (ORTIS), is jointly proposed by the University of Oxford and the Rutherford Appleton Laboratory, to meet the requirements of the European Space Agency's Cosmic Visions Europa Jupiter System Mission (EJSM). ORTIS will consist of an infrared and a sub-millimetre component; however in this study only the sub-millimetre component will be explored. The sub-millimetre component of ORTIS is projected to measure a narrow band of frequencies centred at approximately 2.2 THz, with a spectral resolution varying between approximately 1 kHz and 1 MHz, and having an expected noise magnitude of 2 nW/cm2 sr cm-1. In this spectral region, there are strong water and methane emission lines at most altitudes on Jupiter. The sub-millimetre component of ORTIS is designed to measure the abundance of atmospheric water vapour and atmospheric temperature, as well as vertical windspeed profiles from Doppler-shifted emission lines, measured at high spectral resolution. This study will test to see if, in practice, these science objectives may be met from the planned design, as applied to Jupiter. In order to test the retrievability of atmospheric water vapour, temperature and windspeed with the proposed ORTIS design, it is necessary to have a set of "measurements' for which the input parameters (such as species' concentrations, atmospheric temperature, pressure - and windspeed) are known. This is accomplished by generating a set of radiative transfer simulations using radiative transfer model RadTrans in the spectral range sampled by ORTIS, whereby the atmospheric data pertaining to Jupiter have provided by Cassini-CIRS. These simulations are then convolved with the ORTIS field-of-view response function, yielding "measurements' of Jupiter as would be registered by ORTIS about which all atmospheric parameters are known. A standard optimal estimation retrieval code, the Non-Linear Optimal Estimator for Multivariate Spectral Analysis (NEMESIS), shall be used to retrieve atmospheric water vapour and temperature from such nadir "measurements' taken by ORTIS. The vertical windspeed profiles, as determined from Doppler-shifted emission lines taken at extremely high spectral resolution from limb (or near-limb, 80° emission angle) ORTIS "measurements', shall be determined using an implementation of standard optimal estimation theory. Preliminary analysis indicates that ORTIS should be able to retrieve atmospheric water vapour and temperature, as well as Doppler windspeed profiles on Jupiter to a high degree of accuracy over a large range of altitudes using single nadir or limb/near-limb measurements, respectively.

Spectrophotometric determination of gold(III) in forensic and pharmaceutical samples and results complemented with ICP AES and EDXRF analysis

NASA Astrophysics Data System (ADS)

Nagaraja, Vani; Kumar, M. Kiran; Giddappa, Nagendrappa

2017-02-01

Spectrophotometric method with three systems were developed here for the determination of gold(III) using o-dianisidine, aniline sulphate and catechol. Gold(III),in the system 1 it oxidizes o-dianisidine, in the system 2 it oxidizes catechol followed by its coupling with o-dianisidine, in the system 3 it oxidizes catechol followed by its coupling with aniline sulphate forming dye products with respective λmax 446 nm, 540 nm, and 505 nm. All the three systems were optimized and analytical parameters were calculated. The molar absorptivity values were 9.27 × 104, 1.97 × 104 and 1.62 × 104 respectively for the systems 1, 2 and 3 with the corresponding Sandell sensitivity values (μg cm- 2), 0.0021, 0.0096 and 0.011. The optimized systems were used for the determination of gold present in some forensic jewellery and pharmaceutical samples and the results obtained were compared with the results of all samples determined by Inductively Coupled Plasma - Atomic Emission Spectrometric method and a few of them were also complemented by Energy Dispersive X-Ray Fluorescent spectral analysis.

Spectrophotometric determination of gold(III) in forensic and pharmaceutical samples and results complemented with ICP AES and EDXRF analysis.

PubMed

Nagaraja, Vani; Kumar, M Kiran; Giddappa, Nagendrappa

2017-02-15

Spectrophotometric method with three systems were developed here for the determination of gold(III) using o-dianisidine, aniline sulphate and catechol. Gold(III),in the system 1 it oxidizes o-dianisidine, in the system 2 it oxidizes catechol followed by its coupling with o-dianisidine, in the system 3 it oxidizes catechol followed by its coupling with aniline sulphate forming dye products with respective λ max 446nm, 540nm, and 505nm. All the three systems were optimized and analytical parameters were calculated. The molar absorptivity values were 9.27×10 4 , 1.97×10 4 and 1.62×10 4 respectively for the systems 1, 2 and 3 with the corresponding Sandell sensitivity values (μgcm -2 ), 0.0021, 0.0096 and 0.011. The optimized systems were used for the determination of gold present in some forensic jewellery and pharmaceutical samples and the results obtained were compared with the results of all samples determined by Inductively Coupled Plasma - Atomic Emission Spectrometric method and a few of them were also complemented by Energy Dispersive X-Ray Fluorescent spectral analysis. Copyright © 2016 Elsevier B.V. All rights reserved.

Adaptive optimization of reference intensity for optical coherence imaging using galvanometric mirror tilting method

NASA Astrophysics Data System (ADS)

Kim, Ji-hyun; Han, Jae-Ho; Jeong, Jichai

2015-09-01

Integration time and reference intensity are important factors for achieving high signal-to-noise ratio (SNR) and sensitivity in optical coherence tomography (OCT). In this context, we present an adaptive optimization method of reference intensity for OCT setup. The reference intensity is automatically controlled by tilting a beam position using a Galvanometric scanning mirror system. Before sample scanning, the OCT system acquires two dimensional intensity map with normalized intensity and variables in color spaces using false-color mapping. Then, the system increases or decreases reference intensity following the map data for optimization with a given algorithm. In our experiments, the proposed method successfully corrected the reference intensity with maintaining spectral shape, enabled to change integration time without manual calibration of the reference intensity, and prevented image degradation due to over-saturation and insufficient reference intensity. Also, SNR and sensitivity could be improved by increasing integration time with automatic adjustment of the reference intensity. We believe that our findings can significantly aid in the optimization of SNR and sensitivity for optical coherence tomography systems.

A fundamental study of laser-induced breakdown spectroscopy using fiber optics for remote measurements of trace metals. Interim progress report

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

Goode, S.R.; Angel, S.M.

1997-01-01

'The long-term goal of this project is to develop a system to measure the elemental composition of unprepared samples using laser-induced breakdown spectroscopy, LIBS, with a fiber-optic probe. From images shown in this report it is evident that the temporal and spatial behavior of laser-induced plasmas IS a complex process. However, through the use of spectral imaging, optimal conditions can be determined for collecting the atomic emission signal in these plasmas. By tailoring signal collection to the regions of the plasma that contain the highest emission signal with the least amount of background interference both the detection limits and themore » precision of LIBS measurements could be improved. The optimal regions for both gated and possibly non-gated LIBS measurements have been shown to correspond to the inner regions and outer regions, respectively, in an axial plasma. By using this data fiber-optic LIBS probe designs can be optimized for collecting plasma emission at the optimal regions for improved detection limits and precision in a LIBS measurement.'« less

Effects of spectrometer band pass, sampling, and signal-to-noise ratio on spectral identification using the Tetracorder algorithm

USGS Publications Warehouse

Swayze, G.A.; Clark, R.N.; Goetz, A.F.H.; Chrien, T.H.; Gorelick, N.S.

2003-01-01

Estimates of spectrometer band pass, sampling interval, and signal-to-noise ratio required for identification of pure minerals and plants were derived using reflectance spectra convolved to AVIRIS, HYDICE, MIVIS, VIMS, and other imaging spectrometers. For each spectral simulation, various levels of random noise were added to the reflectance spectra after convolution, and then each was analyzed with the Tetracorder spectra identification algorithm [Clark et al., 2003]. The outcome of each identification attempt was tabulated to provide an estimate of the signal-to-noise ratio at which a given percentage of the noisy spectra were identified correctly. Results show that spectral identification is most sensitive to the signal-to-noise ratio at narrow sampling interval values but is more sensitive to the sampling interval itself at broad sampling interval values because of spectral aliasing, a condition when absorption features of different materials can resemble one another. The band pass is less critical to spectral identification than the sampling interval or signal-to-noise ratio because broadening the band pass does not induce spectral aliasing. These conclusions are empirically corroborated by analysis of mineral maps of AVIRIS data collected at Cuprite, Nevada, between 1990 and 1995, a period during which the sensor signal-to-noise ratio increased up to sixfold. There are values of spectrometer sampling and band pass beyond which spectral identification of materials will require an abrupt increase in sensor signal-to-noise ratio due to the effects of spectral aliasing. Factors that control this threshold are the uniqueness of a material's diagnostic absorptions in terms of shape and wavelength isolation, and the spectral diversity of the materials found in nature and in the spectral library used for comparison. Array spectrometers provide the best data for identification when they critically sample spectra. The sampling interval should not be broadened to increase the signal-to-noise ratio in a photon-noise-limited system when high levels of accuracy are desired. It is possible, using this simulation method, to select optimum combinations of band-pass, sampling interval, and signal-to-noise ratio values for a particular application that maximize identification accuracy and minimize the volume of imaging data.

Legendre spectral-collocation method for solving some types of fractional optimal control problems

PubMed Central

Sweilam, Nasser H.; Al-Ajami, Tamer M.

2014-01-01

In this paper, the Legendre spectral-collocation method was applied to obtain approximate solutions for some types of fractional optimal control problems (FOCPs). The fractional derivative was described in the Caputo sense. Two different approaches were presented, in the first approach, necessary optimality conditions in terms of the associated Hamiltonian were approximated. In the second approach, the state equation was discretized first using the trapezoidal rule for the numerical integration followed by the Rayleigh–Ritz method to evaluate both the state and control variables. Illustrative examples were included to demonstrate the validity and applicability of the proposed techniques. PMID:26257937

Optimal-adaptive filters for modelling spectral shape, site amplification, and source scaling

USGS Publications Warehouse

Safak, Erdal

1989-01-01

This paper introduces some applications of optimal filtering techniques to earthquake engineering by using the so-called ARMAX models. Three applications are presented: (a) spectral modelling of ground accelerations, (b) site amplification (i.e., the relationship between two records obtained at different sites during an earthquake), and (c) source scaling (i.e., the relationship between two records obtained at a site during two different earthquakes). A numerical example for each application is presented by using recorded ground motions. The results show that the optimal filtering techniques provide elegant solutions to above problems, and can be a useful tool in earthquake engineering.

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.

A TV-constrained decomposition method for spectral CT

NASA Astrophysics Data System (ADS)

Guo, Xiaoyue; Zhang, Li; Xing, Yuxiang

2017-03-01

Spectral CT is attracting more and more attention in medicine, industrial nondestructive testing and security inspection field. Material decomposition is an important issue to a spectral CT to discriminate materials. Because of the spectrum overlap of energy channels, as well as the correlation of basis functions, it is well acknowledged that decomposition step in spectral CT imaging causes noise amplification and artifacts in component coefficient images. In this work, we propose materials decomposition via an optimization method to improve the quality of decomposed coefficient images. On the basis of general optimization problem, total variance minimization is constrained on coefficient images in our overall objective function with adjustable weights. We solve this constrained optimization problem under the framework of ADMM. Validation on both a numerical dental phantom in simulation and a real phantom of pig leg on a practical CT system using dual-energy imaging is executed. Both numerical and physical experiments give visually obvious better reconstructions than a general direct inverse method. SNR and SSIM are adopted to quantitatively evaluate the image quality of decomposed component coefficients. All results demonstrate that the TV-constrained decomposition method performs well in reducing noise without losing spatial resolution so that improving the image quality. The method can be easily incorporated into different types of spectral imaging modalities, as well as for cases with energy channels more than two.

Research on the principle and experimentation of optical compressive spectral imaging

NASA Astrophysics Data System (ADS)

Chen, Yuheng; Chen, Xinhua; Zhou, Jiankang; Ji, Yiqun; Shen, Weimin

2013-12-01

The optical compressive spectral imaging method is a novel spectral imaging technique that draws in the inspiration of compressed sensing, which takes on the advantages such as reducing acquisition data amount, realizing snapshot imaging, increasing signal to noise ratio and so on. Considering the influence of the sampling quality on the ultimate imaging quality, researchers match the sampling interval with the modulation interval in former reported imaging system, while the depressed sampling rate leads to the loss on the original spectral resolution. To overcome that technical defect, the demand for the matching between the sampling interval and the modulation interval is disposed of and the spectral channel number of the designed experimental device increases more than threefold comparing to that of the previous method. Imaging experiment is carried out by use of the experiment installation and the spectral data cube of the shooting target is reconstructed with the acquired compressed image by use of the two-step iterative shrinkage/thresholding algorithms. The experimental result indicates that the spectral channel number increases effectively and the reconstructed data stays high-fidelity. The images and spectral curves are able to accurately reflect the spatial and spectral character of the target.

Apparatus and system for multivariate spectral analysis

DOEpatents

Keenan, Michael R.; Kotula, Paul G.

2003-06-24

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

Highly Sensitive Refractive Index Sensors with Plasmonic Nanoantennas-Utilization of Optimal Spectral Detuning of Fano Resonances.

PubMed

Mesch, Martin; Weiss, Thomas; Schäferling, Martin; Hentschel, Mario; Hegde, Ravi S; Giessen, Harald

2018-05-25

We analyze and optimize the performance of coupled plasmonic nanoantennas for refractive index sensing. The investigated structure supports a sub- and super-radiant mode that originates from the weak coupling of a dipolar and quadrupolar mode, resulting in a Fano-type spectral line shape. In our study, we vary the near-field coupling of the two modes and particularly examine the influence of the spectral detuning between them on the sensing performance. Surprisingly, the case of matched resonance frequencies does not provide the best sensor. Instead, we find that the right amount of coupling strength and spectral detuning allows for achieving the ideal combination of narrow line width and sufficient excitation strength of the subradiant mode, and therefore results in optimized sensor performance. Our findings are confirmed by experimental results and first-order perturbation theory. The latter is based on the resonant state expansion and provides direct access to resonance frequency shifts and line width changes as well as the excitation strength of the modes. Based on these parameters, we define a figure of merit that can be easily calculated for different sensing geometries and agrees well with the numerical and experimental results.

Research on the shortwave infrared hyperspectral imaging technology based on Integrated Stepwise filter

NASA Astrophysics Data System (ADS)

Wei, Liqing; Xiao, Xizhong; Wang, Yueming; Zhuang, Xiaoqiong; Wang, Jianyu

2017-11-01

Space-borne hyperspectral imagery is an important tool for earth sciences and industrial applications. Higher spatial and spectral resolutions have been sought persistently, although this results in more power, larger volume and weight during a space-borne spectral imager design. For miniaturization of hyperspectral imager and optimization of spectral splitting methods, several methods are compared in this paper. Spectral time delay integration (TDI) method with high transmittance Integrated Stepwise Filter (ISF) is proposed.With the method, an ISF imaging spectrometer with TDI could achieve higher system sensitivity than the traditional prism/grating imaging spectrometer. In addition, the ISF imaging spectrometer performs well in suppressing infrared background radiation produced by instrument. A compact shortwave infrared (SWIR) hyperspectral imager prototype based on HgCdTe covering the spectral range of 2.0-2.5 μm with 6 TDI stages was designed and integrated. To investigate the performance of ISF spectrometer, a method to derive the optimal blocking band curve of the ISF is introduced, along with known error characteristics. To assess spectral performance of the ISF system, a new spectral calibration based on blackbody radiation with temperature scanning is proposed. The results of the imaging experiment showed the merits of ISF. ISF has great application prospects in the field of high sensitivity and high resolution space-borne hyperspectral imagery.

CARMENES input catalogue of M dwarfs. I. Low-resolution spectroscopy with CAFOS

NASA Astrophysics Data System (ADS)

Alonso-Floriano, F. J.; Morales, J. C.; Caballero, J. A.; Montes, D.; Klutsch, A.; Mundt, R.; Cortés-Contreras, M.; Ribas, I.; Reiners, A.; Amado, P. J.; Quirrenbach, A.; Jeffers, S. V.

2015-05-01

Context. CARMENES is a stabilised, high-resolution, double-channel spectrograph at the 3.5 m Calar Alto telescope. It is optimally designed for radial-velocity surveys of M dwarfs with potentially habitable Earth-mass planets. Aims: We prepare a list of the brightest, single M dwarfs in each spectral subtype observable from the northern hemisphere, from which we will select the best planet-hunting targets for CARMENES. Methods: In this first paper on the preparation of our input catalogue, we compiled a large amount of public data and collected low-resolution optical spectroscopy with CAFOS at the 2.2 m Calar Alto telescope for 753 stars. We derived accurate spectral types using a dense grid of standard stars, a double least-squares minimisation technique, and 31 spectral indices previously defined by other authors. Additionally, we quantified surface gravity, metallicity, and chromospheric activity for all the stars in our sample. Results: We calculated spectral types for all 753 stars, of which 305 are new and 448 are revised. We measured pseudo-equivalent widths of Hα for all the stars in our sample, concluded that chromospheric activity does not affect spectral typing from our indices, and tabulated 49 stars that had been reported to be young stars in open clusters, moving groups, and stellar associations. Of the 753 stars, two are new subdwarf candidates, three are T Tauri stars, 25 are giants, 44 are K dwarfs, and 679 are M dwarfs. Many of the 261 investigated dwarfs in the range M4.0-8.0 V are among the brightest stars known in their spectral subtype. Conclusions: This collection of low-resolution spectroscopic data serves as a candidate target list for the CARMENES survey and can be highly valuable for other radial-velocity surveys of M dwarfs and for studies of cool dwarfs in the solar neighbourhood. Full Tables A.1, A.2, and A.3 are only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (ftp://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/577/A128

MO-F-CAMPUS-I-04: Characterization of Fan Beam Coded Aperture Coherent Scatter Spectral Imaging Methods for Differentiation of Normal and Neoplastic Breast Structures

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

Morris, R; Albanese, K; Lakshmanan, M

Purpose: This study intends to characterize the spectral and spatial resolution limits of various fan beam geometries for differentiation of normal and neoplastic breast structures via coded aperture coherent scatter spectral imaging techniques. In previous studies, pencil beam raster scanning methods using coherent scatter computed tomography and selected volume tomography have yielded excellent results for tumor discrimination. However, these methods don’t readily conform to clinical constraints; primarily prolonged scan times and excessive dose to the patient. Here, we refine a fan beam coded aperture coherent scatter imaging system to characterize the tradeoffs between dose, scan time and image quality formore » breast tumor discrimination. Methods: An X-ray tube (125kVp, 400mAs) illuminated the sample with collimated fan beams of varying widths (3mm to 25mm). Scatter data was collected via two linear-array energy-sensitive detectors oriented parallel and perpendicular to the beam plane. An iterative reconstruction algorithm yields images of the sample’s spatial distribution and respective spectral data for each location. To model in-vivo tumor analysis, surgically resected breast tumor samples were used in conjunction with lard, which has a form factor comparable to adipose (fat). Results: Quantitative analysis with current setup geometry indicated optimal performance for beams up to 10mm wide, with wider beams producing poorer spatial resolution. Scan time for a fixed volume was reduced by a factor of 6 when scanned with a 10mm fan beam compared to a 1.5mm pencil beam. Conclusion: The study demonstrates the utility of fan beam coherent scatter spectral imaging for differentiation of normal and neoplastic breast tissues has successfully reduced dose and scan times whilst sufficiently preserving spectral and spatial resolution. Future work to alter the coded aperture and detector geometries could potentially allow the use of even wider fans, thereby making coded aperture coherent scatter imaging a clinically viable method for breast cancer detection. United States Department of Homeland Security; Duke University Medical Center - Department of Radiology; Carl E Ravin Advanced Imaging Laboratories; Duke University Medical Physics Graduate Program.« less

Optimization of the coherence function estimation for multi-core central processing unit

NASA Astrophysics Data System (ADS)

Cheremnov, A. G.; Faerman, V. A.; Avramchuk, V. S.

2017-02-01

The paper considers use of parallel processing on multi-core central processing unit for optimization of the coherence function evaluation arising in digital signal processing. Coherence function along with other methods of spectral analysis is commonly used for vibration diagnosis of rotating machinery and its particular nodes. An algorithm is given for the function evaluation for signals represented with digital samples. The algorithm is analyzed for its software implementation and computational problems. Optimization measures are described, including algorithmic, architecture and compiler optimization, their results are assessed for multi-core processors from different manufacturers. Thus, speeding-up of the parallel execution with respect to sequential execution was studied and results are presented for Intel Core i7-4720HQ и AMD FX-9590 processors. The results show comparatively high efficiency of the optimization measures taken. In particular, acceleration indicators and average CPU utilization have been significantly improved, showing high degree of parallelism of the constructed calculating functions. The developed software underwent state registration and will be used as a part of a software and hardware solution for rotating machinery fault diagnosis and pipeline leak location with acoustic correlation method.

Hyperspectral Analysis of Soil Total Nitrogen in Subsided Land Using the Local Correlation Maximization-Complementary Superiority (LCMCS) Method.

PubMed

Lin, Lixin; Wang, Yunjia; Teng, Jiyao; Xi, Xiuxiu

2015-07-23

The measurement of soil total nitrogen (TN) by hyperspectral remote sensing provides an important tool for soil restoration programs in areas with subsided land caused by the extraction of natural resources. This study used the local correlation maximization-complementary superiority method (LCMCS) to establish TN prediction models by considering the relationship between spectral reflectance (measured by an ASD FieldSpec 3 spectroradiometer) and TN based on spectral reflectance curves of soil samples collected from subsided land which is determined by synthetic aperture radar interferometry (InSAR) technology. Based on the 1655 selected effective bands of the optimal spectrum (OSP) of the first derivate differential of reciprocal logarithm ([log{1/R}]'), (correlation coefficients, p < 0.01), the optimal model of LCMCS method was obtained to determine the final model, which produced lower prediction errors (root mean square error of validation [RMSEV] = 0.89, mean relative error of validation [MREV] = 5.93%) when compared with models built by the local correlation maximization (LCM), complementary superiority (CS) and partial least squares regression (PLS) methods. The predictive effect of LCMCS model was optional in Cangzhou, Renqiu and Fengfeng District. Results indicate that the LCMCS method has great potential to monitor TN in subsided lands caused by the extraction of natural resources including groundwater, oil and coal.

Second-order data obtained by beta-cyclodextrin complexes: a novel approach for multicomponent analysis with three-way multivariate calibration methods.

PubMed

Khani, Rouhollah; Ghasemi, Jahan B; Shemirani, Farzaneh

2014-10-01

This research reports the first application of β-cyclodextrin (β-CD) complexes as a new method for generation of three way data, combined with second-order calibration methods for quantification of a binary mixture of caffeic (CA) and vanillic (VA) acids, as model compounds in fruit juices samples. At first, the basic experimental parameters affecting the formation of inclusion complexes between target analytes and β-CD were investigated and optimized. Then under the optimum conditions, parallel factor analysis (PARAFAC) and bilinear least squares/residual bilinearization (BLLS/RBL) were applied for deconvolution of trilinear data to get spectral and concentration profiles of CA and VA as a function of β-CD concentrations. Due to severe concentration profile overlapping between CA and VA in β-CD concentration dimension, PARAFAC could not be successfully applied to the studied samples. So, BLLS/RBL performed better than PARAFAC. The resolution of the model compounds was possible due to differences in the spectral absorbance changes of the β-CD complexes signals of the investigated analytes, opening a new approach for second-order data generation. The proposed method was validated by comparison with a reference method based on high-performance liquid chromatography photodiode array detection (HPLC-PDA), and no significant differences were found between the reference values and the ones obtained with the proposed method. Such a chemometrics-based protocol may be a very promising tool for more analytical applications in real samples monitoring, due to its advantages of simplicity, rapidity, accuracy, sufficient spectral resolution and concentration prediction even in the presence of unknown interferents. Copyright © 2014 Elsevier B.V. All rights reserved.

Development of Enabling Scientific Tools to Characterize the Geologic Subsurface at Hanford

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

Kenna, Timothy C.; Herron, Michael M.

2014-07-08

This final report to the Department of Energy provides a summary of activities conducted under our exploratory grant, funded through U.S. DOE Subsurface Biogeochemical Research Program in the category of enabling scientific tools, which covers the period from July 15, 2010 to July 14, 2013. The main goal of this exploratory project is to determine the parameters necessary to translate existing borehole log data into reservoir properties following scientifically sound petrophysical relationships. For this study, we focused on samples and Ge-based spectral gamma logging system (SGLS) data collected from wells located in the Hanford 300 Area. The main activities consistedmore » of 1) the analysis of available core samples for a variety of mineralogical, chemical and physical; 2) evaluation of selected spectral gamma logs, environmental corrections, and calibration; 3) development of algorithms and a proposed workflow that permits translation of log responses into useful reservoir properties such as lithology, matrix density, porosity, and permeability. These techniques have been successfully employed in the petroleum industry; however, the approach is relatively new when applied to subsurface remediation. This exploratory project has been successful in meeting its stated objectives. We have demonstrated that our approach can lead to an improved interpretation of existing well log data. The algorithms we developed can utilize available log data, in particular gamma, and spectral gamma logs, and continued optimization will improve their application to ERSP goals of understanding subsurface properties.« less

Rapid Sequential in Situ Multiplexing with DNA Exchange Imaging in Neuronal Cells and Tissues.

PubMed

Wang, Yu; Woehrstein, Johannes B; Donoghue, Noah; Dai, Mingjie; Avendaño, Maier S; Schackmann, Ron C J; Zoeller, Jason J; Wang, Shan Shan H; Tillberg, Paul W; Park, Demian; Lapan, Sylvain W; Boyden, Edward S; Brugge, Joan S; Kaeser, Pascal S; Church, George M; Agasti, Sarit S; Jungmann, Ralf; Yin, Peng

2017-10-11

To decipher the molecular mechanisms of biological function, it is critical to map the molecular composition of individual cells or even more importantly tissue samples in the context of their biological environment in situ. Immunofluorescence (IF) provides specific labeling for molecular profiling. However, conventional IF methods have finite multiplexing capabilities due to spectral overlap of the fluorophores. Various sequential imaging methods have been developed to circumvent this spectral limit but are not widely adopted due to the common limitation of requiring multirounds of slow (typically over 2 h at room temperature to overnight at 4 °C in practice) immunostaining. We present here a practical and robust method, which we call DNA Exchange Imaging (DEI), for rapid in situ spectrally unlimited multiplexing. This technique overcomes speed restrictions by allowing for single-round immunostaining with DNA-barcoded antibodies, followed by rapid (less than 10 min) buffer exchange of fluorophore-bearing DNA imager strands. The programmability of DEI allows us to apply it to diverse microscopy platforms (with Exchange Confocal, Exchange-SIM, Exchange-STED, and Exchange-PAINT demonstrated here) at multiple desired resolution scales (from ∼300 nm down to sub-20 nm). We optimized and validated the use of DEI in complex biological samples, including primary neuron cultures and tissue sections. These results collectively suggest DNA exchange as a versatile, practical platform for rapid, highly multiplexed in situ imaging, potentially enabling new applications ranging from basic science, to drug discovery, and to clinical pathology.

Efficient Wideband Spectrum Sensing with Maximal Spectral Efficiency for LEO Mobile Satellite Systems

PubMed Central

Li, Feilong; Li, Zhiqiang; Li, Guangxia; Dong, Feihong; Zhang, Wei

2017-01-01

The usable satellite spectrum is becoming scarce due to static spectrum allocation policies. Cognitive radio approaches have already demonstrated their potential towards spectral efficiency for providing more spectrum access opportunities to secondary user (SU) with sufficient protection to licensed primary user (PU). Hence, recent scientific literature has been focused on the tradeoff between spectrum reuse and PU protection within narrowband spectrum sensing (SS) in terrestrial wireless sensing networks. However, those narrowband SS techniques investigated in the context of terrestrial CR may not be applicable for detecting wideband satellite signals. In this paper, we mainly investigate the problem of joint designing sensing time and hard fusion scheme to maximize SU spectral efficiency in the scenario of low earth orbit (LEO) mobile satellite services based on wideband spectrum sensing. Compressed detection model is established to prove that there indeed exists one optimal sensing time achieving maximal spectral efficiency. Moreover, we propose novel wideband cooperative spectrum sensing (CSS) framework where each SU reporting duration can be utilized for its following SU sensing. The sensing performance benefits from the novel CSS framework because the equivalent sensing time is extended by making full use of reporting slot. Furthermore, in respect of time-varying channel, the spatiotemporal CSS (ST-CSS) is presented to attain space and time diversity gain simultaneously under hard decision fusion rule. Computer simulations show that the optimal sensing settings algorithm of joint optimization of sensing time, hard fusion rule and scheduling strategy achieves significant improvement in spectral efficiency. Additionally, the novel ST-CSS scheme performs much higher spectral efficiency than that of general CSS framework. PMID:28117712

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

PubMed

Aldossari, M; Alfalou, A; Brosseau, C

2014-09-22

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

Approaching Terahertz Range with 3-color Broadband Coherent Raman Micro Spectroscopy

NASA Astrophysics Data System (ADS)

Ujj, Laszlo; Olson, Trevor; Amos, James

The presentation reports the recent progress made on reliable signal recording and processing using 3-color broadband coherent Raman scattering (3C-BCRS). Signals are generated either from nanoparticle structures on surfaces or from bulk samples in transmission and in epi-detected mode. Spectra are recorded with a narrowband (at 532 nm) and a broadband radiation produced by a newly optimized optical parametric oscillator using the signal or idler beams. Vibrational and librational bands are measured over the 0.15-15 THz spectral range from solution and crystalline samples. Volumetric Brag-filter approach is introduced for recording 3C-BCRS spectra at the first time. The technical limitations and advantages of the narrowband filtering relative to the Notch-filter technic is clarified. The signal is proportional to the spectral autocorrelation of the broadband radiation therefore the present scheme gives a better signal-to-noise ratio relative to the traditional multiplex CRS methods. This makes the automation of non-model dependent signal processing more reliable to extract vibrational information which is very crucial in coherent Raman microscopy. Financial support from the Hal Marcus College of Science and Engineering is greatly appreciated.

Combining near infrared spectra of feces and geostatistics to generate forage nutritional quality maps across landscapes

NASA Astrophysics Data System (ADS)

Jean, Pierre-Olivier; Bradley, Robert; Tremblay, Jean-Pierre

2015-04-01

An important asset for the management of wild ungulates is the ability to recognize the spatial distribution of forage quality across heterogeneous landscapes. To do so typically requires knowledge of which plant species are eaten, in what abundance they are eaten, and what their nutritional quality might be. Acquiring such data may be, however, difficult and time consuming. Here, we are proposing a rapid and cost-effective forage quality monitoring tool that combines near infrared (NIR) spectra of fecal samples and easily obtained data on plant community composition. Our approach rests on the premise that NIR spectra of fecal samples collected within low population density exclosures reflect the optimal forage quality of a given landscape. Forage quality can thus be based on the Mahalanobis distance of fecal spectral scans across the landscape relative to fecal spectral scans inside exclosures (referred to as DISTEX). The Gi* spatial autocorrelation statistic can then be applied among neighbouring DISTEX values to detect and map 'hot-spots' and 'cold-spots' of nutritional quality over the landscape. We tested our approach in a heterogeneous boreal landscape on Anticosti Island (Qu

A Novel Calibration-Minimum Method for Prediction of Mole Fraction in Non-Ideal Mixture.

PubMed

Shibayama, Shojiro; Kaneko, Hiromasa; Funatsu, Kimito

2017-04-01

This article proposes a novel concentration prediction model that requires little training data and is useful for rapid process understanding. Process analytical technology is currently popular, especially in the pharmaceutical industry, for enhancement of process understanding and process control. A calibration-free method, iterative optimization technology (IOT), was proposed to predict pure component concentrations, because calibration methods such as partial least squares, require a large number of training samples, leading to high costs. However, IOT cannot be applied to concentration prediction in non-ideal mixtures because its basic equation is derived from the Beer-Lambert law, which cannot be applied to non-ideal mixtures. We proposed a novel method that realizes prediction of pure component concentrations in mixtures from a small number of training samples, assuming that spectral changes arising from molecular interactions can be expressed as a function of concentration. The proposed method is named IOT with virtual molecular interaction spectra (IOT-VIS) because the method takes spectral change as a virtual spectrum x nonlin,i into account. It was confirmed through the two case studies that the predictive accuracy of IOT-VIS was the highest among existing IOT methods.

Modeling soil parameters using hyperspectral image reflectance in subtropical coastal wetlands

NASA Astrophysics Data System (ADS)

Anne, Naveen J. P.; Abd-Elrahman, Amr H.; Lewis, David B.; Hewitt, Nicole A.

2014-12-01

Developing spectral models of soil properties is an important frontier in remote sensing and soil science. Several studies have focused on modeling soil properties such as total pools of soil organic matter and carbon in bare soils. We extended this effort to model soil parameters in areas densely covered with coastal vegetation. Moreover, we investigated soil properties indicative of soil functions such as nutrient and organic matter turnover and storage. These properties include the partitioning of mineral and organic soil between particulate (>53 μm) and fine size classes, and the partitioning of soil carbon and nitrogen pools between stable and labile fractions. Soil samples were obtained from Avicennia germinans mangrove forest and Juncus roemerianus salt marsh plots on the west coast of central Florida. Spectra corresponding to field plot locations from Hyperion hyperspectral image were extracted and analyzed. The spectral information was regressed against the soil variables to determine the best single bands and optimal band combinations for the simple ratio (SR) and normalized difference index (NDI) indices. The regression analysis yielded levels of correlation for soil variables with R2 values ranging from 0.21 to 0.47 for best individual bands, 0.28 to 0.81 for two-band indices, and 0.53 to 0.96 for partial least-squares (PLS) regressions for the Hyperion image data. Spectral models using Hyperion data adequately (RPD > 1.4) predicted particulate organic matter (POM), silt + clay, labile carbon (C), and labile nitrogen (N) (where RPD = ratio of standard deviation to root mean square error of cross-validation [RMSECV]). The SR (0.53 μm, 2.11 μm) model of labile N with R2 = 0.81, RMSECV= 0.28, and RPD = 1.94 produced the best results in this study. Our results provide optimism that remote-sensing spectral models can successfully predict soil properties indicative of ecosystem nutrient and organic matter turnover and storage, and do so in areas with dense canopy cover.

Effects of Moisture and Particle Size on Quantitative Determination of Total Organic Carbon (TOC) in Soils Using Near-Infrared Spectroscopy.

PubMed

Tamburini, Elena; Vincenzi, Fabio; Costa, Stefania; Mantovi, Paolo; Pedrini, Paola; Castaldelli, Giuseppe

2017-10-17

Near-Infrared Spectroscopy is a cost-effective and environmentally friendly technique that could represent an alternative to conventional soil analysis methods, including total organic carbon (TOC). Soil fertility and quality are usually measured by traditional methods that involve the use of hazardous and strong chemicals. The effects of physical soil characteristics, such as moisture content and particle size, on spectral signals could be of great interest in order to understand and optimize prediction capability and set up a robust and reliable calibration model, with the future perspective of being applied in the field. Spectra of 46 soil samples were collected. Soil samples were divided into three data sets: unprocessed, only dried and dried, ground and sieved, in order to evaluate the effects of moisture and particle size on spectral signals. Both separate and combined normalization methods including standard normal variate (SNV), multiplicative scatter correction (MSC) and normalization by closure (NCL), as well as smoothing using first and second derivatives (DV1 and DV2), were applied to a total of seven cases. Pretreatments for model optimization were designed and compared for each data set. The best combination of pretreatments was achieved by applying SNV and DV2 on partial least squares (PLS) modelling. There were no significant differences between the predictions using the three different data sets ( p < 0.05). Finally, a unique database including all three data sets was built to include all the sources of sample variability that were tested and used for final prediction. External validation of TOC was carried out on 16 unknown soil samples to evaluate the predictive ability of the final combined calibration model. Hence, we demonstrate that sample preprocessing has minor influence on the quality of near infrared spectroscopy (NIR) predictions, laying the ground for a direct and fast in situ application of the method. Data can be acquired outside the laboratory since the method is simple and does not need more than a simple band ratio of the spectra.

Method of multivariate spectral analysis

DOEpatents

Keenan, Michael R.; Kotula, Paul G.

2004-01-06

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

Enhanced Characterization of Niobium Surface Topography

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

Chen Xu, Hui Tian, Charles Reece, Michael Kelley

2011-12-01

Surface topography characterization is a continuing issue for the Superconducting Radio Frequency (SRF) particle accelerator community. Efforts are underway to both to improve surface topography, and its characterization and analysis using various techniques. In measurement of topography, Power Spectral Density (PSD) is a promising method to quantify typical surface parameters and develop scale-specific interpretations. PSD can also be used to indicate how chemical processes modifiesy the roughnesstopography at different scales. However, generating an accurate and meaningful topographic PSD of an SRF surface requires careful analysis and optimization. In this report, polycrystalline surfaces with different process histories are sampled with AFMmore » and stylus/white light interferometer profilometryers and analyzed to indicate trace topography evolution at different scales. evolving during etching or polishing. Moreover, Aan optimized PSD analysis protocol will be offered to serve the SRF surface characterization needs is presented.« less

Using FT-NIR spectroscopy technique to determine arginine content in fermented Cordyceps sinensis mycelium.

PubMed

Xie, Chuanqi; Xu, Ning; Shao, Yongni; He, Yong

2015-01-01

This research investigated the feasibility of using Fourier transform near-infrared (FT-NIR) spectral technique for determining arginine content in fermented Cordyceps sinensis (C. sinensis) mycelium. Three different models were carried out to predict the arginine content. Wavenumber selection methods such as competitive adaptive reweighted sampling (CARS) and successive projections algorithm (SPA) were used to identify the most important wavenumbers and reduce the high dimensionality of the raw spectral data. Only a few wavenumbers were selected by CARS and CARS-SPA as the optimal wavenumbers, respectively. Among the prediction models, CARS-least squares-support vector machine (CARS-LS-SVM) model performed best with the highest values of the coefficient of determination of prediction (Rp(2)=0.8370) and residual predictive deviation (RPD=2.4741), the lowest value of root mean square error of prediction (RMSEP=0.0841). Moreover, the number of the input variables was forty-five, which only accounts for 2.04% of that of the full wavenumbers. The results showed that FT-NIR spectral technique has the potential to be an objective and non-destructive method to detect arginine content in fermented C. sinensis mycelium. Copyright © 2015 Elsevier B.V. All rights reserved.

Laser-induced fluorescence fiber optic probe measurement of oil dilution by fuel

DOEpatents

Parks, II, James E [Knoxville, TN; Partridge, Jr., William P [Oak Ridge, TN

2010-11-23

Apparatus for detecting fuel in oil includes an excitation light source in optical communication with an oil sample for exposing the oil sample to excitation light in order to excite the oil sample from a non-excited state to an excited state and a spectrally selective device in optical communication with the oil sample for detecting light emitted from the oil sample as the oil sample returns from the excited state to a non-excited state to produce spectral indicia that can be analyzed to determine the presence of fuel in the oil sample. A method of detecting fuel in oil includes the steps of exposing a oil sample to excitation light in order to excite the oil sample from a non-excited state to an excited state, as the oil sample returns from the excited state to a non-excited state, detecting light emitted from the oil sample to produce spectral indicia; and analyzing the spectral indicia to determine the presence of fuel in the oil sample.

Modeling of frequency-domain scalar wave equation with the average-derivative optimal scheme based on a multigrid-preconditioned iterative solver

NASA Astrophysics Data System (ADS)

Cao, Jian; Chen, Jing-Bo; Dai, Meng-Xue

2018-01-01

An efficient finite-difference frequency-domain modeling of seismic wave propagation relies on the discrete schemes and appropriate solving methods. The average-derivative optimal scheme for the scalar wave modeling is advantageous in terms of the storage saving for the system of linear equations and the flexibility for arbitrary directional sampling intervals. However, using a LU-decomposition-based direct solver to solve its resulting system of linear equations is very costly for both memory and computational requirements. To address this issue, we consider establishing a multigrid-preconditioned BI-CGSTAB iterative solver fit for the average-derivative optimal scheme. The choice of preconditioning matrix and its corresponding multigrid components is made with the help of Fourier spectral analysis and local mode analysis, respectively, which is important for the convergence. Furthermore, we find that for the computation with unequal directional sampling interval, the anisotropic smoothing in the multigrid precondition may affect the convergence rate of this iterative solver. Successful numerical applications of this iterative solver for the homogenous and heterogeneous models in 2D and 3D are presented where the significant reduction of computer memory and the improvement of computational efficiency are demonstrated by comparison with the direct solver. In the numerical experiments, we also show that the unequal directional sampling interval will weaken the advantage of this multigrid-preconditioned iterative solver in the computing speed or, even worse, could reduce its accuracy in some cases, which implies the need for a reasonable control of directional sampling interval in the discretization.

Novel plasma source for safe beryllium spectral line studies in the presence of beryllium dust

NASA Astrophysics Data System (ADS)

Stankov, B. D.; Vinić, M.; Gavrilović Božović, M. R.; Ivković, M.

2018-05-01

Plasma source for beryllium spectral line studies in the presence of beryllium dust particles was realised. The guideline during construction was to prevent exposure to formed dust, considering the toxicity of beryllium. Plasma source characterization through determination of optimal working conditions is described. The necessary conditions for Be spectral line appearance and optimal conditions for line shape measurements are found. It is proven experimentally that under these conditions dust appears coincidently with the second current maximum. The electron density measured after discharge current maximum is determined from the peak separation of the hydrogen Balmer beta spectral line, and the electron temperature is determined from the ratios of the relative intensities of Be spectral lines emitted from successive ionized stages of atoms. Maximum values of electron density and temperature are measured to be 9.3 × 1022 m-3 and 16 800 K, respectively. Construction details and testing of the BeO discharge tube in comparison with SiO2 and Al2O3 discharge tubes are also presented in this paper.

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.

Spectrally optimal illuminations for diabetic retinopathy detection in retinal imaging

NASA Astrophysics Data System (ADS)

Bartczak, Piotr; Fält, Pauli; Penttinen, Niko; Ylitepsa, Pasi; Laaksonen, Lauri; Lensu, Lasse; Hauta-Kasari, Markku; Uusitalo, Hannu

2017-04-01

Retinal photography is a standard method for recording retinal diseases for subsequent analysis and diagnosis. However, the currently used white light or red-free retinal imaging does not necessarily provide the best possible visibility of different types of retinal lesions, important when developing diagnostic tools for handheld devices, such as smartphones. Using specifically designed illumination, the visibility and contrast of retinal lesions could be improved. In this study, spectrally optimal illuminations for diabetic retinopathy lesion visualization are implemented using a spectrally tunable light source based on digital micromirror device. The applicability of this method was tested in vivo by taking retinal monochrome images from the eyes of five diabetic volunteers and two non-diabetic control subjects. For comparison to existing methods, we evaluated the contrast of retinal images taken with our method and red-free illumination. The preliminary results show that the use of optimal illuminations improved the contrast of diabetic lesions in retinal images by 30-70%, compared to the traditional red-free illumination imaging.

AlGaN Nanostructures with Extremely High Room-Temperature Internal Quantum Efficiency of Emission Below 300 nm

NASA Astrophysics Data System (ADS)

Toropov, A. A.; Shevchenko, E. A.; Shubina, T. V.; Jmerik, V. N.; Nechaev, D. V.; Evropeytsev, E. A.; Kaibyshev, V. Kh.; Pozina, G.; Rouvimov, S.; Ivanov, S. V.

2017-07-01

We present theoretical optimization of the design of a quantum well (QW) heterostructure based on AlGaN alloys, aimed at achievement of the maximum possible internal quantum efficiency of emission in the mid-ultraviolet spectral range below 300 nm at room temperature. A sample with optimized parameters was fabricated by plasma-assisted molecular beam epitaxy using the submonolayer digital alloying technique for QW formation. High-angle annular dark-field scanning transmission electron microscopy confirmed strong compositional disordering of the thus-fabricated QW, which presumably facilitates lateral localization of charge carriers in the QW plane. Stress evolution in the heterostructure was monitored in real time during growth using a multibeam optical stress sensor intended for measurements of substrate curvature. Time-resolved photoluminescence spectroscopy confirmed that radiative recombination in the fabricated sample dominated in the whole temperature range up to 300 K. This leads to record weak temperature-induced quenching of the QW emission intensity, which at 300 K does not exceed 20% of the low-temperature value.

Vibration and acoustic frequency spectra for industrial process modeling using selective fusion multi-condition samples and multi-source features

NASA Astrophysics Data System (ADS)

Tang, Jian; Qiao, Junfei; Wu, ZhiWei; Chai, Tianyou; Zhang, Jian; Yu, Wen

2018-01-01

Frequency spectral data of mechanical vibration and acoustic signals relate to difficult-to-measure production quality and quantity parameters of complex industrial processes. A selective ensemble (SEN) algorithm can be used to build a soft sensor model of these process parameters by fusing valued information selectively from different perspectives. However, a combination of several optimized ensemble sub-models with SEN cannot guarantee the best prediction model. In this study, we use several techniques to construct mechanical vibration and acoustic frequency spectra of a data-driven industrial process parameter model based on selective fusion multi-condition samples and multi-source features. Multi-layer SEN (MLSEN) strategy is used to simulate the domain expert cognitive process. Genetic algorithm and kernel partial least squares are used to construct the inside-layer SEN sub-model based on each mechanical vibration and acoustic frequency spectral feature subset. Branch-and-bound and adaptive weighted fusion algorithms are integrated to select and combine outputs of the inside-layer SEN sub-models. Then, the outside-layer SEN is constructed. Thus, "sub-sampling training examples"-based and "manipulating input features"-based ensemble construction methods are integrated, thereby realizing the selective information fusion process based on multi-condition history samples and multi-source input features. This novel approach is applied to a laboratory-scale ball mill grinding process. A comparison with other methods indicates that the proposed MLSEN approach effectively models mechanical vibration and acoustic signals.

Extension of the Time-Spectral Approach to Overset Solvers for Arbitrary Motion

NASA Technical Reports Server (NTRS)

Leffell, Joshua Isaac; Murman, Scott M.; Pulliam, Thomas H.

2012-01-01

Forced periodic flows arise in a broad range of aerodynamic applications such as rotorcraft, turbomachinery, and flapping wing configurations. Standard practice involves solving the unsteady flow equations forward in time until the initial transient exits the domain and a statistically stationary flow is achieved. It is often required to simulate through several periods to remove the initial transient making unsteady design optimization prohibitively expensive for most realistic problems. An effort to reduce the computational cost of these calculations led to the development of the Harmonic Balance method [1, 2] which capitalizes on the periodic nature of the solution. The approach exploits the fact that forced temporally periodic flow, while varying in the time domain, is invariant in the frequency domain. Expanding the temporal variation at each spatial node into a Fourier series transforms the unsteady governing equations into a steady set of equations in integer harmonics that can be tackled with the acceleration techniques afforded to steady-state flow solvers. Other similar approaches, such as the Nonlinear Frequency Domain [3,4,5], Reduced Frequency [6] and Time-Spectral [7, 8, 9] methods, were developed shortly thereafter. Additionally, adjoint-based optimization techniques can be applied [10, 11] as well as frequency-adaptive methods [12, 13, 14] to provide even more flexibility to the method. The Fourier temporal basis functions imply spectral convergence as the number of harmonic modes, and correspondingly number of time samples, N, is increased. Some elect to solve the equations in the frequency domain directly, while others choose to transform the equations back into the time domain to simplify the process of adding this capability to existing solvers, but each harnesses the underlying steady solution in the frequency domain. These temporal projection methods will herein be collectively referred to as Time-Spectral methods. Time-Spectral methods have demonstrated marked success in reducing the computational costs associated with simulating periodic forced flows, but have yet to be fully applied to overset or Cartesian solvers for arbitrary motion with dynamic hole-cutting. Overset and Cartesian grid methodologies are versatile techniques capable of handling complex geometry configurations in practical engineering applications, and the combination of the Time-Spectral approach with this general capability potentially provides an enabling new design and analysis tool. In an arbitrary moving-body scenario for these approaches, a Lagrangian body moves through a fixed Eulerian mesh and mesh points in the Eulerian mesh interior to the solid body are removed (cut or blanked), leaving a hole in the Eulerian mesh. During the dynamic motion some gridpoints in the domain are blanked and do not have a complete set of time-samples preventing a direct implementation of the Time-Spectral method. Murman[6] demonstrated the Time-Spectral approach for a Cartesian solver with a rigid domain motion, wherein the hole cutting remains constant. Similarly, Custer et al. [15, 16] used the NASA overset OVERFLOW solver and limited the amount of relative motion to ensure static hole-cutting and interpolation. Recently, Mavriplis and Mundis[17] demonstrated a qualitative method for applying the Time-Spectral approach to an unstructured overset solver for arbitrary motion. The goal of the current work is to develop a robust and general method for handling arbitrary motion with the Time-Spectral approach within an overset or Cartesian mesh method, while still approaching the spectral convergence rate of the original Time-Spectral approach. The viscous OVERFLOW solver will be augmented with the new Time-Spectral algorithm and the capability of the method for benchmark problems in rotorcraft and turbomachinery will be demonstrated. This abstract begins with a brief synopsis of the Time-Spectral approach for overset grids and provides details of e current approach to allow for arbitrary motion. Model problem results in one and two dimensions are included to demonstrate the viability of the method and the convergence properties. Section IV briefly outlines the implementation into the OVERFLOW solver, and the abstract closes with a description of the benchmark test cases which will be included in the final paper.

Rapid microscopy measurement of very large spectral images.

PubMed

Lindner, Moshe; Shotan, Zav; Garini, Yuval

2016-05-02

The spectral content of a sample provides important information that cannot be detected by the human eye or by using an ordinary RGB camera. The spectrum is typically a fingerprint of the chemical compound, its environmental conditions, phase and geometry. Thus measuring the spectrum at each point of a sample is important for a large range of applications from art preservation through forensics to pathological analysis of a tissue section. To date, however, there is no system that can measure the spectral image of a large sample in a reasonable time. Here we present a novel method for scanning very large spectral images of microscopy samples even if they cannot be viewed in a single field of view of the camera. The system is based on capturing information while the sample is being scanned continuously 'on the fly'. Spectral separation implements Fourier spectroscopy by using an interferometer mounted along the optical axis. High spectral resolution of ~5 nm at 500 nm could be achieved with a diffraction-limited spatial resolution. The acquisition time is fairly high and takes 6-8 minutes for a sample size of 10mm x 10mm measured under a bright-field microscope using a 20X magnification.

Dual THz comb spectroscopy

NASA Astrophysics Data System (ADS)

Yasui, Takeshi

2017-08-01

Optical frequency combs are innovative tools for broadband spectroscopy because a series of comb modes can serve as frequency markers that are traceable to a microwave frequency standard. However, a mode distribution that is too discrete limits the spectral sampling interval to the mode frequency spacing even though individual mode linewidth is sufficiently narrow. Here, using a combination of a spectral interleaving and dual-comb spectroscopy in the terahertz (THz) region, we achieved a spectral sampling interval equal to the mode linewidth rather than the mode spacing. The spectrally interleaved THz comb was realized by sweeping the laser repetition frequency and interleaving additional frequency marks. In low-pressure gas spectroscopy, we achieved an improved spectral sampling density of 2.5 MHz and enhanced spectral accuracy of 8.39 × 10-7 in the THz region. The proposed method is a powerful tool for simultaneously achieving high resolution, high accuracy, and broad spectral coverage in THz spectroscopy.

Spectrally interleaved, comb-mode-resolved spectroscopy using swept dual terahertz combs

PubMed Central

Hsieh, Yi-Da; Iyonaga, Yuki; Sakaguchi, Yoshiyuki; Yokoyama, Shuko; Inaba, Hajime; Minoshima, Kaoru; Hindle, Francis; Araki, Tsutomu; Yasui, Takeshi

2014-01-01

Optical frequency combs are innovative tools for broadband spectroscopy because a series of comb modes can serve as frequency markers that are traceable to a microwave frequency standard. However, a mode distribution that is too discrete limits the spectral sampling interval to the mode frequency spacing even though individual mode linewidth is sufficiently narrow. Here, using a combination of a spectral interleaving and dual-comb spectroscopy in the terahertz (THz) region, we achieved a spectral sampling interval equal to the mode linewidth rather than the mode spacing. The spectrally interleaved THz comb was realized by sweeping the laser repetition frequency and interleaving additional frequency marks. In low-pressure gas spectroscopy, we achieved an improved spectral sampling density of 2.5 MHz and enhanced spectral accuracy of 8.39 × 10−7 in the THz region. The proposed method is a powerful tool for simultaneously achieving high resolution, high accuracy, and broad spectral coverage in THz spectroscopy. PMID:24448604

Effect of non-Poisson samples on turbulence spectra from laser velocimetry

NASA Technical Reports Server (NTRS)

Sree, Dave; Kjelgaard, Scott O.; Sellers, William L., III

1994-01-01

Spectral analysis of laser velocimetry (LV) data plays an important role in characterizing a turbulent flow and in estimating the associated turbulence scales, which can be helpful in validating theoretical and numerical turbulence models. The determination of turbulence scales is critically dependent on the accuracy of the spectral estimates. Spectral estimations from 'individual realization' laser velocimetry data are typically based on the assumption of a Poisson sampling process. What this Note has demonstrated is that the sampling distribution must be considered before spectral estimates are used to infer turbulence scales.

Researches of fruit quality prediction model based on near infrared spectrum

NASA Astrophysics Data System (ADS)

Shen, Yulin; Li, Lian

2018-04-01

With the improvement in standards for food quality and safety, people pay more attention to the internal quality of fruits, therefore the measurement of fruit internal quality is increasingly imperative. In general, nondestructive soluble solid content (SSC) and total acid content (TAC) analysis of fruits is vital and effective for quality measurement in global fresh produce markets, so in this paper, we aim at establishing a novel fruit internal quality prediction model based on SSC and TAC for Near Infrared Spectrum. Firstly, the model of fruit quality prediction based on PCA + BP neural network, PCA + GRNN network, PCA + BP adaboost strong classifier, PCA + ELM and PCA + LS_SVM classifier are designed and implemented respectively; then, in the NSCT domain, the median filter and the SavitzkyGolay filter are used to preprocess the spectral signal, Kennard-Stone algorithm is used to automatically select the training samples and test samples; thirdly, we achieve the optimal models by comparing 15 kinds of prediction model based on the theory of multi-classifier competition mechanism, specifically, the non-parametric estimation is introduced to measure the effectiveness of proposed model, the reliability and variance of nonparametric estimation evaluation of each prediction model to evaluate the prediction result, while the estimated value and confidence interval regard as a reference, the experimental results demonstrate that this model can better achieve the optimal evaluation of the internal quality of fruit; finally, we employ cat swarm optimization to optimize two optimal models above obtained from nonparametric estimation, empirical testing indicates that the proposed method can provide more accurate and effective results than other forecasting methods.

Development of gradient descent adaptive algorithms to remove common mode artifact for improvement of cardiovascular signal quality.

PubMed

Ciaccio, Edward J; Micheli-Tzanakou, Evangelia

2007-07-01

Common-mode noise degrades cardiovascular signal quality and diminishes measurement accuracy. Filtering to remove noise components in the frequency domain often distorts the signal. Two adaptive noise canceling (ANC) algorithms were tested to adjust weighted reference signals for optimal subtraction from a primary signal. Update of weight w was based upon the gradient term of the steepest descent equation: [see text], where the error epsilon is the difference between primary and weighted reference signals. nabla was estimated from Deltaepsilon(2) and Deltaw without using a variable Deltaw in the denominator which can cause instability. The Parallel Comparison (PC) algorithm computed Deltaepsilon(2) using fixed finite differences +/- Deltaw in parallel during each discrete time k. The ALOPEX algorithm computed Deltaepsilon(2)x Deltaw from time k to k + 1 to estimate nabla, with a random number added to account for Deltaepsilon(2) . Deltaw--> 0 near the optimal weighting. Using simulated data, both algorithms stably converged to the optimal weighting within 50-2000 discrete sample points k even with a SNR = 1:8 and weights which were initialized far from the optimal. Using a sharply pulsatile cardiac electrogram signal with added noise so that the SNR = 1:5, both algorithms exhibited stable convergence within 100 ms (100 sample points). Fourier spectral analysis revealed minimal distortion when comparing the signal without added noise to the ANC restored signal. ANC algorithms based upon difference calculations can rapidly and stably converge to the optimal weighting in simulated and real cardiovascular data. Signal quality is restored with minimal distortion, increasing the accuracy of biophysical measurement.

Space-time interpolation of satellite winds in the tropics

NASA Astrophysics Data System (ADS)

Patoux, Jérôme; Levy, Gad

2013-09-01

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

Estimation of Saxophone Control Parameters by Convex Optimization.

PubMed

Wang, Cheng-I; Smyth, Tamara; Lipton, Zachary C

2014-12-01

In this work, an approach to jointly estimating the tone hole configuration (fingering) and reed model parameters of a saxophone is presented. The problem isn't one of merely estimating pitch as one applied fingering can be used to produce several different pitches by bugling or overblowing. Nor can a fingering be estimated solely by the spectral envelope of the produced sound (as it might for estimation of vocal tract shape in speech) since one fingering can produce markedly different spectral envelopes depending on the player's embouchure and control of the reed. The problem is therefore addressed by jointly estimating both the reed (source) parameters and the fingering (filter) of a saxophone model using convex optimization and 1) a bank of filter frequency responses derived from measurement of the saxophone configured with all possible fingerings and 2) sample recordings of notes produced using all possible fingerings, played with different overblowing, dynamics and timbre. The saxophone model couples one of several possible frequency response pairs (corresponding to the applied fingering), and a quasi-static reed model generating input pressure at the mouthpiece, with control parameters being blowing pressure and reed stiffness. Applied fingering and reed parameters are estimated for a given recording by formalizing a minimization problem, where the cost function is the error between the recording and the synthesized sound produced by the model having incremental parameter values for blowing pressure and reed stiffness. The minimization problem is nonlinear and not differentiable and is made solvable using convex optimization. The performance of the fingering identification is evaluated with better accuracy than previous reported value.

Optimal Monochromatic Energy Levels in Spectral CT Pulmonary Angiography for the Evaluation of Pulmonary Embolism

PubMed Central

Wu, Huawei; Zhang, Qing; Hua, Jia; Hua, Xiaolan; Xu, Jianrong

2013-01-01

Background The aim of this study was to determine the optimal monochromatic spectral CT pulmonary angiography (sCTPA) levels to obtain the highest image quality and diagnostic confidence for pulmonary embolism detection. Methods The Institutional Review Board of the Shanghai Jiao Tong University School of Medicine approved this study, and written informed consent was obtained from all participating patients. Seventy-two patients with pulmonary embolism were scanned with spectral CT mode in the arterial phase. One hundred and one sets of virtual monochromatic spectral (VMS) images were generated ranging from 40 keV to 140 keV. Image noise, clot diameter and clot to artery contrast-to-noise ratio (CNR) from seven sets of VMS images at selected monochromatic levels in sCTPA were measured and compared. Subjective image quality and diagnostic confidence for these images were also assessed and compared. Data were analyzed by paired t test and Wilcoxon rank sum test. Results The lowest noise and the highest image quality score for the VMS images were obtained at 65 keV. The VMS images at 65 keV also had the second highest CNR value behind that of 50 keV VMS images. There was no difference in the mean noise and CNR between the 65 keV and 70 keV VMS images. The apparent clot diameter correlated with the keV levels. Conclusions The optimal energy level for detecting pulmonary embolism using dual-energy spectral CT pulmonary angiography was 65–70 keV. Virtual monochromatic spectral images at approximately 65–70 keV yielded the lowest image noise, high CNR and highest diagnostic confidence for the detection of pulmonary embolism. PMID:23667583

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.

Optical Sensing of Ecosystem Carbon Fluxes Combining Spectral Reflectance Indices with Solar Induced Fluorescence

NASA Astrophysics Data System (ADS)

Huemmrich, K. F.; Middleton, E.; Corp, L. A.; Campbell, P. K.; Kustas, W. P.

2014-12-01

Optical sampling of spectral reflectance and solar induced fluorescence provide information on the physiological status of vegetation that can be used to infer stress responses and estimates of production. Multiple repeated observations are required to observe the effects of changing environmental conditions on vegetation. This study examines the use of optical signals to determine inputs to a light use efficiency (LUE) model describing productivity of a cornfield where repeated observations of carbon flux, spectral reflectance and fluorescence were collected. Data were collected at the Optimizing Production Inputs for Economic and Environmental Enhancement (OPE3) fields (39.03°N, 76.85°W) at USDA Beltsville Agricultural Research Center. Agricultural Research Service researchers measured CO2 fluxes using eddy covariance methods throughout the growing season. Optical measurements were made from the nearby tower supporting the NASA FUSION sensors. The sensor system consists of two dual channel, upward and downward looking, spectrometers used to simultaneously collect high spectral resolution measurements of reflected and fluoresced light from vegetation canopies. Estimates of chlorophyll fluorescence, combined with measures of vegetation pigment content and the Photosynthetic Reflectance Index (PRI) derived from the spectral reflectance are compared with CO2 fluxes over diurnal periods for multiple days. PRI detects changes in Xanthophyll cycle pigments using reflectance at 531 nm compared to a reference band at 570 nm. The relationships among the different optical measurements indicate that they are providing different types of information on the vegetation and that combinations of these measurements provide improved retrievals of CO2 fluxes than any index alone.

Optical Sensing of Ecosystem Carbon Fluxes Combining Spectral Reflectance Indices with Solar Induced Fluorescence

NASA Astrophysics Data System (ADS)

Huemmrich, K. F.; Corp, L.; Campbell, P. K.; Cook, B. D.; Middleton, E.; Cheng, Y.; Zhang, Q.; Russ, A.; Kustas, W. P.

2013-12-01

Optical sampling of spectral reflectance and solar induced fluorescence provide information on the physiological status of vegetation that can be used to infer stress responses and estimates of production. Multiple repeated observations can observe the effects of changing environmental conditions on vegetation. This study examines the use of optical signals to determine inputs to a light use efficiency (LUE) model describing productivity of a cornfield where repeated observations of carbon flux, spectral reflectance and fluorescence were collected. Data were collected at the Optimizing Production Inputs for Economic and Environmental Enhancement (OPE3) fields (39.03°N, 76.85°W) at USDA Beltsville Agricultural Research Center. Agricultural Research Service researchers measured CO2 fluxes using eddy covariance methods throughout the growing season. Optical measurements were made from the nearby tower supporting the NASA FUSION sensors. This sensor system consists of two dual channel, upward and downward looking, spectrometers used to simultaneously collect high spectral resolution measurements of reflected and fluoresced light from vegetation canopies. Estimates of chlorophyll fluorescence, combined with measures of vegetation pigment content and the Photosynthetic Reflectance Index (PRI) derived from the spectral reflectance are compared with CO2 fluxes over diurnal periods for multiple days. PRI detects changes in Xanthophyll cycle pigments using reflectance at 531 nm compared to a reference band at 570 nm. The relationships among the different optical measurements indicate that they are providing different types of information on the vegetation and that combinations of these measurements provide improved retrievals of CO2 fluxes than any index alone.

USGS Digital Spectral Library splib05a

USGS Publications Warehouse

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

2003-01-01

We have assembled a digital reflectance spectral library of spectra that covers wavelengths from the ultraviolet to near-infrared along with sample documentation. The library includes samples of minerals, rocks, soils, physically constructed as well as mathematically computed mixtures, vegetation, microorganisms, and man-made materials. The samples and spectra collected were assembled for the purpose of using spectral features for the remote detection of these and similar materials.

Optimizing Spectral Wave Estimates with Adjoint-Based Sensitivity Maps

DTIC Science & Technology

2014-02-18

J, Orzech MD, Ngodock HE (2013) Validation of a wave data assimilation system based on SWAN. Geophys Res Abst, (15), EGU2013-5951-1, EGU General ...surface wave spectra. Sensitivity maps are generally constructed for a selected system indicator (e.g., vorticity) by computing the differential of...spectral action balance Eq. 2, generally initialized at the off- shore boundary with spectral wave and other outputs from regional models such as

Evaluation of multispectral plenoptic camera

NASA Astrophysics Data System (ADS)

Meng, Lingfei; Sun, Ting; Kosoglow, Rich; Berkner, Kathrin

2013-01-01

Plenoptic cameras enable capture of a 4D lightfield, allowing digital refocusing and depth estimation from data captured with a compact portable camera. Whereas most of the work on plenoptic camera design has been based a simplistic geometric-optics-based characterization of the optical path only, little work has been done of optimizing end-to-end system performance for a specific application. Such design optimization requires design tools that need to include careful parameterization of main lens elements, as well as microlens array and sensor characteristics. In this paper we are interested in evaluating the performance of a multispectral plenoptic camera, i.e. a camera with spectral filters inserted into the aperture plane of the main lens. Such a camera enables single-snapshot spectral data acquisition.1-3 We first describe in detail an end-to-end imaging system model for a spectrally coded plenoptic camera that we briefly introduced in.4 Different performance metrics are defined to evaluate the spectral reconstruction quality. We then present a prototype which is developed based on a modified DSLR camera containing a lenslet array on the sensor and a filter array in the main lens. Finally we evaluate the spectral reconstruction performance of a spectral plenoptic camera based on both simulation and measurements obtained from the prototype.

Optimization of Immunolabeled Plasmonic Nanoparticles for Cell Surface Receptor Analysis

PubMed Central

Seekell, Kevin; Price, Hillel; Marinakos, Stella; Wax, Adam

2011-01-01

Noble metal nanoparticles hold great potential as optical contrast agents due to a unique feature, known as the plasmon resonance, which produces enhanced scattering and absorption at specific frequencies. The plasmon resonance also provides a spectral tunability that is not often found in organic fluorophores or other labeling methods. The ability to functionalize these nanoparticles with antibodies has led to their development as contrast agents for molecular optical imaging. In this review article, we present methods for optimizing the spectral agility of these labels. We discuss synthesis of gold nanorods, a plasmonic nanoparticle in which the plasmonic resonance can be tuned during synthesis to provide imaging within the spectral window commonly utilized in biomedical applications. We describe recent advances in our group to functionalize gold and silver nanoparticles using distinct antibodies, including EGFR, HER-2 and IGF-1, selected for their relevance to tumor imaging. Finally, we present characterization of these nanoparticle labels to verify their spectral properties and molecular specificity. PMID:21911063

Spectral Range Optimization to Enhance the Effectiveness of Phototherapy for Neonatal Hyperbilirubinemia

NASA Astrophysics Data System (ADS)

Plavskii, V. Yu.; Mikulich, A. V.; Leusenko, I. A.; Tretyakova, A. I.; Plavskaya, L. G.; Serdyuchenko, N. S.; Gao, J.; Xiong, D.; Wu, X.

2017-03-01

The effectiveness of phototherapy for hyperbilirubinemia of newborns using narrowband LED sources was found to depend not only on the position of the LED emission spectrum peak within the absorption band of bilirubin but also on the width of the incident radiation spectrum. Extension of the spectral range of radiation by adding a green component with λmax ≈ 505 nm to the blue light band with λmax ≈ 462 nm (provided equal integrated power density) gives a more efficient decrease in the total bilirubin level in the blood of newborns. This effect was attributed to heterogeneity of the spectral characteristics of bilirubin in different microenvironments as well as dependence of the optimal wavelength for photoisomerization of the pigment on the depth of the blood vessels where the bilirubin phototransformation reactions occur. Moreover, extension of the spectral range of the incident radiation by adding a green component increases the irradiated volumes of blood where the photoisomerization reactions with a high lumirubin quantum yield underlying this phototherapy are initiated.

Smooth Upgrade of Existing Passive Optical Networks With Spectral-Shaping Line-Coding Service Overlay

NASA Astrophysics Data System (ADS)

Hsueh, Yu-Li; Rogge, Matthew S.; Shaw, Wei-Tao; Kim, Jaedon; Yamamoto, Shu; Kazovsky, Leonid G.

2005-09-01

A simple and cost-effective upgrade of existing passive optical networks (PONs) is proposed, which realizes service overlay by novel spectral-shaping line codes. A hierarchical coding procedure allows processing simplicity and achieves desired long-term spectral properties. Different code rates are supported, and the spectral shape can be properly tailored to adapt to different systems. The computation can be simplified by quantization of trigonometric functions. DC balance is achieved by passing the dc residual between processing windows. The proposed line codes tend to introduce bit transitions to avoid long consecutive identical bits and facilitate receiver clock recovery. Experiments demonstrate and compare several different optimized line codes. For a specific tolerable interference level, the optimal line code can easily be determined, which maximizes the data throughput. The service overlay using the line-coding technique leaves existing services and field-deployed fibers untouched but fully functional, providing a very flexible and economic way to upgrade existing PONs.

Saliency-Guided Change Detection of Remotely Sensed Images Using Random Forest

NASA Astrophysics Data System (ADS)

Feng, W.; Sui, H.; Chen, X.

2018-04-01

Studies based on object-based image analysis (OBIA) representing the paradigm shift in change detection (CD) have achieved remarkable progress in the last decade. Their aim has been developing more intelligent interpretation analysis methods in the future. The prediction effect and performance stability of random forest (RF), as a new kind of machine learning algorithm, are better than many single predictors and integrated forecasting method. In this paper, we present a novel CD approach for high-resolution remote sensing images, which incorporates visual saliency and RF. First, highly homogeneous and compact image super-pixels are generated using super-pixel segmentation, and the optimal segmentation result is obtained through image superimposition and principal component analysis (PCA). Second, saliency detection is used to guide the search of interest regions in the initial difference image obtained via the improved robust change vector analysis (RCVA) algorithm. The salient regions within the difference image that correspond to the binarized saliency map are extracted, and the regions are subject to the fuzzy c-means (FCM) clustering to obtain the pixel-level pre-classification result, which can be used as a prerequisite for superpixel-based analysis. Third, on the basis of the optimal segmentation and pixel-level pre-classification results, different super-pixel change possibilities are calculated. Furthermore, the changed and unchanged super-pixels that serve as the training samples are automatically selected. The spectral features and Gabor features of each super-pixel are extracted. Finally, superpixel-based CD is implemented by applying RF based on these samples. Experimental results on Ziyuan 3 (ZY3) multi-spectral images show that the proposed method outperforms the compared methods in the accuracy of CD, and also confirm the feasibility and effectiveness of the proposed approach.

Standardized cell samples for midIR technology development

NASA Astrophysics Data System (ADS)

Kastl, Lena; Rommel, Christina E.; Kemper, Björn; Schnekenburger, Jürgen

2015-03-01

The application of midIR spectroscopy towards human cell and tissue samples is impaired by the need for technical solutions and lacking sample standards for technology development. We here present the standardization of stable test samples for the continuous development and testing of novel optical system components. We have selected cell lines representing the major cellular skin constituents keratinocytes and fibroblasts (NIH-3T3, HaCaT). In addition, two skin cancer cell types (A-375 and SK-MEL-28 cells) were analyzed. Cells were seeded on CaF2 substrates and measured dried and under aqueous medium as well as fixated and unfixated. Several independent cell preparations were analyzed with an FTIR spectrometer in the wave number range from 1000 - 4000 cm-1. The obtained data demonstrate that fixed and dehydrated cells on CaF2 can be stored in pure ethanol for several weeks without significant losses in quality of the spectral properties. The established protocol of cell seeding on CaF2 substrates, chemical fixation, dehydration, storage under ethanol and air-drying is suitable for the production of reliable midIR standards. The retrieved spectra demonstrate that fixed cells on CaF2 can be prepared reproducibly; with stable midIR spectral properties over several weeks and properties mimicking reliable unfixed cells. Moreover, the fixated samples on CaF2 show clear differences in the cell type specific spectra that can be identified by principle component analysis. In summary, the standardized cell culture samples on CaF2 substrates are suitable for the development of a midIR device and the optimization of the specific midIR spectra.

Raman fiber-optical method for colon cancer detection: Cross-validation and outlier identification approach

NASA Astrophysics Data System (ADS)

Petersen, D.; Naveed, P.; Ragheb, A.; Niedieker, D.; El-Mashtoly, S. F.; Brechmann, T.; Kötting, C.; Schmiegel, W. H.; Freier, E.; Pox, C.; Gerwert, K.

2017-06-01

Endoscopy plays a major role in early recognition of cancer which is not externally accessible and therewith in increasing the survival rate. Raman spectroscopic fiber-optical approaches can help to decrease the impact on the patient, increase objectivity in tissue characterization, reduce expenses and provide a significant time advantage in endoscopy. In gastroenterology an early recognition of malign and precursor lesions is relevant. Instantaneous and precise differentiation between adenomas as precursor lesions for cancer and hyperplastic polyps on the one hand and between high and low-risk alterations on the other hand is important. Raman fiber-optical measurements of colon biopsy samples taken during colonoscopy were carried out during a clinical study, and samples of adenocarcinoma (22), tubular adenomas (141), hyperplastic polyps (79) and normal tissue (101) from 151 patients were analyzed. This allows us to focus on the bioinformatic analysis and to set stage for Raman endoscopic measurements. Since spectral differences between normal and cancerous biopsy samples are small, special care has to be taken in data analysis. Using a leave-one-patient-out cross-validation scheme, three different outlier identification methods were investigated to decrease the influence of systematic errors, like a residual risk in misplacement of the sample and spectral dilution of marker bands (esp. cancerous tissue) and therewith optimize the experimental design. Furthermore other validations methods like leave-one-sample-out and leave-one-spectrum-out cross-validation schemes were compared with leave-one-patient-out cross-validation. High-risk lesions were differentiated from low-risk lesions with a sensitivity of 79%, specificity of 74% and an accuracy of 77%, cancer and normal tissue with a sensitivity of 79%, specificity of 83% and an accuracy of 81%. Additionally applied outlier identification enabled us to improve the recognition of neoplastic biopsy samples.

On Pythagoras Theorem for Products of Spectral Triples

NASA Astrophysics Data System (ADS)

D'Andrea, Francesco; Martinetti, Pierre

2013-05-01

We discuss a version of Pythagoras theorem in noncommutative geometry. Usual Pythagoras theorem can be formulated in terms of Connes' distance, between pure states, in the product of commutative spectral triples. We investigate the generalization to both non-pure states and arbitrary spectral triples. We show that Pythagoras theorem is replaced by some Pythagoras inequalities, that we prove for the product of arbitrary (i.e. non-necessarily commutative) spectral triples, assuming only some unitality condition. We show that these inequalities are optimal, and we provide non-unital counter-examples inspired by K-homology.

Structure of the sulfur K x-ray emission spectrum: influence of the oxidation state

NASA Astrophysics Data System (ADS)

Pérez, P. D.; Carreras, A. C.; Trincavelli, J. C.

2012-01-01

The sulfur K x-ray emission was studied in pure sulfur, anhydrite (CaSO4) and sphalerite (ZnS) samples. The ionizations were induced by electron impact and the spectra were recorded with a wavelength dispersive spectrometer. The spectral processing was performed through a methodology based on the optimization of atomic and experimental parameters. Energies and intensities of diagram and satellite lines were determined for a set of transitions in the Kα and Kβ groups. The lines studied include Kα22, Kα2, Kα1, Kα‧, Kα3, Kα4, Kα5, Kα6, Kβ1,3, Kβ-RAE, KβIII, KβIV, Kβx, Kβ‧ and Kβ″. The main spectral differences between the three oxidation states were analysed, considering the influence of the ligand atoms. The results were compared with data published by other authors and the origin of certain lines was discussed on the basis of data available in the literature.

The History and Legacy of BATSE

NASA Technical Reports Server (NTRS)

Fishman, Gerald J.

2012-01-01

The BATSE experiment on the Compton Gamma-ray Observatory was the first large detector system specifically designed for the study of gamma-ray bursts. The eight large-area detectors allowed full-sky coverage and were optimized to operate in the energy region of the peak emission of most GRBs. BATSE provided detailed observations of the temporal and spectral characteristics of large samples of GRBs, and it was the first experiment to provide rapid notifications of the coarse location of many them. It also provided strong evidence for the cosmological distances to GRBs through the observation of the sky distribution and intensity distribution of numerous GRBs. The large number of GRBs observed with the high- sensitivity BATSE detectors continues to provide a database of GRB spectral and temporal properties in the primary energy range of GRB emission that will likely not be exceeded for at least another decade. The origin and development of the BATSE experiment, some highlights from the mission and its continuing legacy are described in this paper.

Spectrally-engineered solar thermal photovoltaic devices

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

Lenert, Andrej; Bierman, David; Chan, Walker

A solar thermal photovoltaic device, and method of forming same, includes a solar absorber and a spectrally selective emitter formed on either side of a thermally conductive substrate. The solar absorber is configured to absorb incident solar radiation. The solar absorber and the spectrally selective emitter are configured with an optimized emitter-to-absorber area ratio. The solar thermal photovoltaic device also includes a photovoltaic cell in thermal communication with the spectrally selective emitter. The spectrally selective emitter is configured to permit high emittance for energies above a bandgap of the photovoltaic cell and configured to permit low emittance for energies belowmore » the bandgap.« less

Determination of tailored filter sets to create rayfiles including spatial and angular resolved spectral information.

PubMed

Rotscholl, Ingo; Trampert, Klaus; Krüger, Udo; Perner, Martin; Schmidt, Franz; Neumann, Cornelius

2015-11-16

To simulate and optimize optical designs regarding perceived color and homogeneity in commercial ray tracing software, realistic light source models are needed. Spectral rayfiles provide angular and spatial varying spectral information. We propose a spectral reconstruction method with a minimum of time consuming goniophotometric near field measurements with optical filters for the purpose of creating spectral rayfiles. Our discussion focuses on the selection of the ideal optical filter combination for any arbitrary spectrum out of a given filter set by considering measurement uncertainties with Monte Carlo simulations. We minimize the simulation time by a preselection of all filter combinations, which bases on factorial design.

The ARIEL mission reference sample

NASA Astrophysics Data System (ADS)

Zingales, Tiziano; Tinetti, Giovanna; Pillitteri, Ignazio; Leconte, Jérémy; Micela, Giuseppina; Sarkar, Subhajit

2018-02-01

The ARIEL (Atmospheric Remote-sensing Exoplanet Large-survey) mission concept is one of the three M4 mission candidates selected by the European Space Agency (ESA) for a Phase A study, competing for a launch in 2026. ARIEL has been designed to study the physical and chemical properties of a large and diverse sample of exoplanets and, through those, understand how planets form and evolve in our galaxy. Here we describe the assumptions made to estimate an optimal sample of exoplanets - including already known exoplanets and expected ones yet to be discovered - observable by ARIEL and define a realistic mission scenario. To achieve the mission objectives, the sample should include gaseous and rocky planets with a range of temperatures around stars of different spectral type and metallicity. The current ARIEL design enables the observation of ˜1000 planets, covering a broad range of planetary and stellar parameters, during its four year mission lifetime. This nominal list of planets is expected to evolve over the years depending on the new exoplanet discoveries.

Three-way spectrofluorimetric-assisted multivariate determination of nonylphenol ethoxylate and 2-naphtalene sulfonate in wastewater samples and optimization approach for their photocatalytic degradation by CoTiO3 nanostructure.

PubMed

Mohsenikia, Atefeh; Gholami, Ali; Masoum, Saeed; Abbasi, Saleheh

2017-09-01

This study presents a new strategy for the simultaneous quantification of two industrial contaminants. The excitation-emission fluorescence data matrix combined with a three-way chemometric method, such as parallel factor analysis, was used for the determination of nonylphenol ethoxylate (NPE-9) as a nonionic surfactant and 2-naphthalene sulfonate (2-NS) in waste water samples. It is noticeable that this method can resolve overlapping signal into spectral and relative concentration profiles. By spiking the known concentrations of these compounds in the wastewater samples, the accuracy of the proposed methods was validated and recoveries of the spiked values were calculated. High recoveries (i.e. 90-110%) obtained for the waste water samples indicate the present method can be used successfully to determine the analytes concentration in the environmental contaminations. The photocatalytic degradation of NPE-9 and 2-NS in aqueous solution was studied using the CoTiO 3 nanoparticles catalyst. It was synthesized by the sol-gel technique. The catalytic activity of the prepared nanoparticles was measured in a batch photoreactor containing appropriate solutions of these compounds with UV irradiation. The photodegradation process of these compounds was optimized by using the central composite design. The CoTiO 3 showed high activity for UV-photocatalytic degradation of NPE-9 and 2-NS.

Adaptive detection of noise signal according to Neumann-Pearson criterion

NASA Astrophysics Data System (ADS)

Padiryakov, Y. A.

1985-03-01

Optimum detection according to the Neumann-Pearson criterion is considered in the case of a random Gaussian noise signal, stationary during measurement, and a stationary random Gaussian background interference. Detection is based on two samples, their statistics characterized by estimates of their spectral densities, it being a priori known that sample A from the signal channel is either the sum of signal and interference or interference alone and sample B from the reference interference channel is an interference with the same spectral density as that of the interference in sample A for both hypotheses. The probability of correct detection is maximized on the average, first in the 2N-dimensional space of signal spectral density and interference spectral density readings, by fixing the probability of false alarm at each point so as to stabilize it at a constant level against variation of the interference spectral density. Deterministic decision rules are established. The algorithm is then reduced to equivalent detection in the N-dimensional space of the ratio of sample A readings to sample B readings.

A statistical evaluation of spectral fingerprinting methods using analysis of variance and principal component analysis

USDA-ARS?s Scientific Manuscript database

Six methods were compared with respect to spectral fingerprinting of a well-characterized series of broccoli samples. Spectral fingerprints were acquired for finely-powdered solid samples using Fourier transform-infrared (IR) and Fourier transform-near infrared (NIR) spectrometry and for aqueous met...

Extracting Optical Fiber Background from Surface-Enhanced Raman Spectroscopy Spectra Based on Bi-Objective Optimization Modeling.

PubMed

Huang, Jie; Shi, Tielin; Tang, Zirong; Zhu, Wei; Liao, Guanglan; Li, Xiaoping; Gong, Bo; Zhou, Tengyuan

2017-08-01

We propose a bi-objective optimization model for extracting optical fiber background from the measured surface-enhanced Raman spectroscopy (SERS) spectrum of the target sample in the application of fiber optic SERS. The model is built using curve fitting to resolve the SERS spectrum into several individual bands, and simultaneously matching some resolved bands with the measured background spectrum. The Pearson correlation coefficient is selected as the similarity index and its maximum value is pursued during the spectral matching process. An algorithm is proposed, programmed, and demonstrated successfully in extracting optical fiber background or fluorescence background from the measured SERS spectra of rhodamine 6G (R6G) and crystal violet (CV). The proposed model not only can be applied to remove optical fiber background or fluorescence background for SERS spectra, but also can be transferred to conventional Raman spectra recorded using fiber optic instrumentation.

Weld defect identification in friction stir welding using power spectral density

NASA Astrophysics Data System (ADS)

Das, Bipul; Pal, Sukhomay; Bag, Swarup

2018-04-01

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

High-Definition Infrared Spectroscopic Imaging

PubMed Central

Reddy, Rohith K.; Walsh, Michael J.; Schulmerich, Matthew V.; Carney, P. Scott; Bhargava, Rohit

2013-01-01

The quality of images from an infrared (IR) microscope has traditionally been limited by considerations of throughput and signal-to-noise ratio (SNR). An understanding of the achievable quality as a function of instrument parameters, from first principals is needed for improved instrument design. Here, we first present a model for light propagation through an IR spectroscopic imaging system based on scalar wave theory. The model analytically describes the propagation of light along the entire beam path from the source to the detector. The effect of various optical elements and the sample in the microscope is understood in terms of the accessible spatial frequencies by using a Fourier optics approach and simulations are conducted to gain insights into spectroscopic image formation. The optimal pixel size at the sample plane is calculated and shown much smaller than that in current mid-IR microscopy systems. A commercial imaging system is modified, and experimental data are presented to demonstrate the validity of the developed model. Building on this validated theoretical foundation, an optimal sampling configuration is set up. Acquired data were of high spatial quality but, as expected, of poorer SNR. Signal processing approaches were implemented to improve the spectral SNR. The resulting data demonstrated the ability to perform high-definition IR imaging in the laboratory by using minimally-modified commercial instruments. PMID:23317676

High-definition infrared spectroscopic imaging.

PubMed

Reddy, Rohith K; Walsh, Michael J; Schulmerich, Matthew V; Carney, P Scott; Bhargava, Rohit

2013-01-01

The quality of images from an infrared (IR) microscope has traditionally been limited by considerations of throughput and signal-to-noise ratio (SNR). An understanding of the achievable quality as a function of instrument parameters, from first principals is needed for improved instrument design. Here, we first present a model for light propagation through an IR spectroscopic imaging system based on scalar wave theory. The model analytically describes the propagation of light along the entire beam path from the source to the detector. The effect of various optical elements and the sample in the microscope is understood in terms of the accessible spatial frequencies by using a Fourier optics approach and simulations are conducted to gain insights into spectroscopic image formation. The optimal pixel size at the sample plane is calculated and shown much smaller than that in current mid-IR microscopy systems. A commercial imaging system is modified, and experimental data are presented to demonstrate the validity of the developed model. Building on this validated theoretical foundation, an optimal sampling configuration is set up. Acquired data were of high spatial quality but, as expected, of poorer SNR. Signal processing approaches were implemented to improve the spectral SNR. The resulting data demonstrated the ability to perform high-definition IR imaging in the laboratory by using minimally-modified commercial instruments.

Identification of Highly Pathogenic Microorganisms by Matrix-Assisted Laser Desorption Ionization–Time of Flight Mass Spectrometry: Results of an Interlaboratory Ring Trial

PubMed Central

Lasch, Peter; Wahab, Tara; Weil, Sandra; Pályi, Bernadett; Tomaso, Herbert; Zange, Sabine; Kiland Granerud, Beathe; Drevinek, Michal; Kokotovic, Branko; Wittwer, Matthias; Pflüger, Valentin; Di Caro, Antonino; Stämmler, Maren; Grunow, Roland

2015-01-01

In the case of a release of highly pathogenic bacteria (HPB), there is an urgent need for rapid, accurate, and reliable diagnostics. MALDI-TOF mass spectrometry is a rapid, accurate, and relatively inexpensive technique that is becoming increasingly important in microbiological diagnostics to complement classical microbiology, PCR, and genotyping of HPB. In the present study, the results of a joint exercise with 11 partner institutions from nine European countries are presented. In this exercise, 10 distinct microbial samples, among them five HPB, Bacillus anthracis, Brucella canis, Burkholderia mallei, Burkholderia pseudomallei, and Yersinia pestis, were characterized under blinded conditions. Microbial strains were inactivated by high-dose gamma irradiation before shipment. Preparatory investigations ensured that this type of inactivation induced only subtle spectral changes with negligible influence on the quality of the diagnosis. Furthermore, pilot tests on nonpathogenic strains were systematically conducted to ensure the suitability of sample preparation and to optimize and standardize the workflow for microbial identification. The analysis of the microbial mass spectra was carried out by the individual laboratories on the basis of spectral libraries available on site. All mass spectra were also tested against an in-house HPB library at the Robert Koch Institute (RKI). The averaged identification accuracy was 77% in the first case and improved to >93% when the spectral diagnoses were obtained on the basis of the RKI library. The compilation of complete and comprehensive databases with spectra from a broad strain collection is therefore considered of paramount importance for accurate microbial identification. PMID:26063856

Raman spectroscopy application in frozen carrot cooked in different ways and the relationship with carotenoids.

PubMed

Camorani, Paolo; Chiavaro, Emma; Cristofolini, Luigi; Paciulli, Maria; Zaupa, Maria; Visconti, Attilio; Fogliano, Vincenzo; Pellegrini, Nicoletta

2015-08-30

Raman spectroscopy, in its confocal micro-Raman variation, has been recently proposed as a spatially resolved method to identify carotenoids in various food matrices, being faster, non-destructive, and avoiding sample extraction, but no data are present in the literature concerning its application to the evaluation of carotenoid pattern changes after thermal treatment of carrots. The effect of three cooking methods (i.e. boiling, steaming and microwaving) was evaluated on frozen carrot, comparing changes on carotenoid profiles measured by means of Raman spectroscopy with their high-performance liquid chromatographic determination and colour. A more pronounced detrimental effect on carotenoids was detected in steamed carrots, in accordance with colour data. Conversely, boiling and, to a lesser extent, microwaving caused an increase in carotenoid concentration. Cooking procedures affected the Raman spectral features of carotenoids, causing a shift of vibration frequencies towards a higher energy, increase in the spectral baseline and peak intensities as well as a broadening of their width, probably in relation to the thermal degradation of longer carotenoids (i.e. the all-trans form) and the isomerization process. In particular, steamed samples showed a significantly higher increase of centre frequency, in accordance with a more pronounced isomerization and changes in colour parameters. This work showed that the evolution of Raman spectral parameters could provide information on carotenoid bioaccessibility for carrots cooked using various methods. This paves the way for a future use of this technique to monitor and optimize cooking processes aimed at maximizing carotenoid bioaccessibility and bioavailability. © 2014 Society of Chemical Industry.

Establishing a method to measure bone structure using spectral CT

NASA Astrophysics Data System (ADS)

Ramyar, M.; Leary, C.; Raja, A.; Butler, A. P. H.; Woodfield, T. B. F.; Anderson, N. G.

2017-03-01

Combining bone structure and density measurement in 3D is required to assess site-specific fracture risk. Spectral molecular imaging can measure bone structure in relation to bone density by measuring macro and microstructure of bone in 3D. This study aimed to optimize spectral CT methodology to measure bone structure in excised bone samples. MARS CT with CdTe Medipix3RX detector was used in multiple energy bins to calibrate bone structure measurements. To calibrate thickness measurement, eight different thicknesses of Aluminium (Al) sheets were scanned one in air and the other around a falcon tube and then analysed. To test if trabecular thickness measurements differed depending on scan plane, a bone sample from sheep proximal tibia was scanned in two orthogonal directions. To assess the effect of air on thickness measurement, two parts of the same human femoral head were scanned in two conditions (in the air and in PBS). The results showed that the MARS scanner (with 90μm voxel size) is able to accurately measure the Al (in air) thicknesses over 200μm but it underestimates the thicknesses below 200μm because of partial volume effect in Al-air interface. The Al thickness measured in the highest energy bin is overestimated at Al-falcon tube interface. Bone scanning in two orthogonal directions gives the same trabecular thickness and air in the bone structure reduced measurement accuracy. We have established a bone structure assessment protocol on MARS scanner. The next step is to combine this with bone densitometry to assess bone strength.

[Quantitative analysis of Cu in water by collinear DP-LIBS].

PubMed

Zheng, Mei-Lan; Yao, Ming-Yin; Chen, Tian-Bing; Lin, Yong-Zeng; Li, Wen-Bing; Liu, Mu-Hua

2014-07-01

The purpose of this research is to study the influence of double pulse laser induced breakdown spectroscopy (DP-LIBS) on the sensitivity of Cu in water. The water solution of Cu was tested by collinear DP-LIBS in this article. The results show that spectral intensity of Cu can be enhanced obviously by DP-LIBS, compared with single pulse laser induced breakdown spectroscopy (SP-LIBS). Besides, the experimental results were significantly impacted by delay time between laser pulse and spectrometer acquisition, delay time of double laser pulse and energy of laser pulse and so on. The paper determined the best conditions for DP-LIBS detecting Cu in water. The optimal acquisition delay time was 1 380 ns. The best laser pulse delay time was 25 ns. The most appropriate energy of double laser pulse was 100 mJ. Characteristic analysis of spectra of Cu at 324.7 and 327.4 nm was done for quantitative analysis. The detection limit was 3.5 microg x mL(-1) at 324.7 nm, and the detection limit was 4.84 microg x mL(-1) at 327.4 nm. The relative standard deviation of the two characteristic spectral lines was within 10%. The calibration curve of characteristic spectral line, established by 327.4 nm, was verified with 500 microg x mL(-1) sample. Concentration of the sample was 446 microg x mL(-1) calculated by the calibration curve. This research shows that the detection sensitivity of Cu in water can be improved by DP-LIBS. At the same time, it had high stability.

Integrated fluorescence analysis system

DOEpatents

Buican, Tudor N.; Yoshida, Thomas M.

1992-01-01

An integrated fluorescence analysis system enables a component part of a sample to be virtually sorted within a sample volume after a spectrum of the component part has been identified from a fluorescence spectrum of the entire sample in a flow cytometer. Birefringent optics enables the entire spectrum to be resolved into a set of numbers representing the intensity of spectral components of the spectrum. One or more spectral components are selected to program a scanning laser microscope, preferably a confocal microscope, whereby the spectrum from individual pixels or voxels in the sample can be compared. Individual pixels or voxels containing the selected spectral components are identified and an image may be formed to show the morphology of the sample with respect to only those components having the selected spectral components. There is no need for any physical sorting of the sample components to obtain the morphological information.

Feasibility of spectral CT imaging for the detection of liver lesions with gold-based contrast agents - A simulation study.

PubMed

Müllner, Marie; Schlattl, Helmut; Hoeschen, Christoph; Dietrich, Olaf

2015-12-01

To demonstrate the feasibility of gold-specific spectral CT imaging for the detection of liver lesions in humans at low concentrations of gold as targeted contrast agent. A Monte Carlo simulation study of spectral CT imaging with a photon-counting and energy-resolving detector (with 6 energy bins) was performed in a realistic phantom of the human abdomen. The detector energy thresholds were optimized for the detection of gold. The simulation results were reconstructed with the K-edge imaging algorithm; the reconstructed gold-specific images were filtered and evaluated with respect to signal-to-noise ratio and contrast-to-noise ratio (CNR). The simulations demonstrate the feasibility of spectral CT with CNRs of the specific gold signal between 2.7 and 4.8 after bilateral filtering. Using the optimized bin thresholds increases the CNRs of the lesions by up to 23% compared to bin thresholds described in former studies. Gold is a promising new CT contrast agent for spectral CT in humans; minimum tissue mass fractions of 0.2 wt% of gold are required for sufficient image contrast. Copyright © 2015 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

[Research on improving spectrum resolution of optimized Wollaston prism array].

PubMed

Zhang, Peng; Wang, Jian-Rong; Zhang, Guo-Chen; Hou, Wen

2011-11-01

In order to not affect the image quality of interference fringes on the basis of the structure by increasing the structure angle of Wollaston prism to improve spectrum resolution, the authors optimized the structure of Wollaston prism. Calculating the function of the splitting angle and the structure angle, analysis indicated that taking the isosceles triangle prism with the same nature of the second wedge-shaped prism after the Wollaston prism, which makes the o and e light parallel to the optical axis, and alpha=0 degrees, the imaging interference fringes are no longer affected by changes in the splitting angle. Several optimized Wollaston prisms were made as an array to improve the spectral resolution. Experiments used traditional and optimized Wollaston prism array to detect the spectrum of the 980 nm laser. Experimental data showed that using optimized Wollaston prism array gets a clearer contrast of interference fringes, and the spectral data with Fourier transform are more accurate with DSP.

A random optimization approach for inherent optic properties of nearshore waters

NASA Astrophysics Data System (ADS)

Zhou, Aijun; Hao, Yongshuai; Xu, Kuo; Zhou, Heng

2016-10-01

Traditional method of water quality sampling is time-consuming and highly cost. It can not meet the needs of social development. Hyperspectral remote sensing technology has well time resolution, spatial coverage and more general segment information on spectrum. It has a good potential in water quality supervision. Via the method of semi-analytical, remote sensing information can be related with the water quality. The inherent optical properties are used to quantify the water quality, and an optical model inside the water is established to analysis the features of water. By stochastic optimization algorithm Threshold Acceptance, a global optimization of the unknown model parameters can be determined to obtain the distribution of chlorophyll, organic solution and suspended particles in water. Via the improvement of the optimization algorithm in the search step, the processing time will be obviously reduced, and it will create more opportunity for the increasing the number of parameter. For the innovation definition of the optimization steps and standard, the whole inversion process become more targeted, thus improving the accuracy of inversion. According to the application result for simulated data given by IOCCG and field date provided by NASA, the approach model get continuous improvement and enhancement. Finally, a low-cost, effective retrieval model of water quality from hyper-spectral remote sensing can be achieved.

Spectral splitting for thermal management in photovoltaic cells

NASA Astrophysics Data System (ADS)

Apostoleris, Harry; Chiou, Yu-Cheng; Chiesa, Matteo; Almansouri, Ibraheem

2017-09-01

Spectral splitting is widely employed as a way to divide light between different solar cells or processes to optimize energy conversion. Well-understood but less explored is the use of spectrum splitting or filtering to combat solar cell heating. This has impacts both on cell performance and on the surrounding environment. In this manuscript we explore the design of spectral filtering systems that can improve the thermal and power-conversion performance of commercial PV modules.

Spectral variability of sea surface skylight reflectance and its effect on ocean color.

PubMed

Cui, Ting-Wei; Song, Qing-Jun; Tang, Jun-Wu; Zhang, Jie

2013-10-21

In this study, sea surface skylight spectral reflectance ρ(λ) was retrieved by means of the non-linear spectral optimization method and a bio-optical model. The spectral variability of ρ(λ) was found to be mainly influenced by the uniformity of the incident skylight, and a model is proposed to predict the ρ(λ) spectral dependency based on skylight reflectance at 750 nm. It is demonstrated that using the spectrally variable ρ(λ), rather than a constant, yields an improved agreement between the above-water remote sensing reflectance R(rs)(λ) estimates and concurrent profiling ones. The findings of this study highlight the necessity to re-process the relevant historical above-water data and update ocean color retrieval algorithms accordingly.

Decision Tree Repository and Rule Set Based Mingjiang River Estuarine Wetlands Classifaction

NASA Astrophysics Data System (ADS)

Zhang, W.; Li, X.; Xiao, W.

2018-05-01

The increasing urbanization and industrialization have led to wetland losses in estuarine area of Mingjiang River over past three decades. There has been increasing attention given to produce wetland inventories using remote sensing and GIS technology. Due to inconsistency training site and training sample, traditionally pixel-based image classification methods can't achieve a comparable result within different organizations. Meanwhile, object-oriented image classification technique shows grate potential to solve this problem and Landsat moderate resolution remote sensing images are widely used to fulfill this requirement. Firstly, the standardized atmospheric correct, spectrally high fidelity texture feature enhancement was conducted before implementing the object-oriented wetland classification method in eCognition. Secondly, we performed the multi-scale segmentation procedure, taking the scale, hue, shape, compactness and smoothness of the image into account to get the appropriate parameters, using the top and down region merge algorithm from single pixel level, the optimal texture segmentation scale for different types of features is confirmed. Then, the segmented object is used as the classification unit to calculate the spectral information such as Mean value, Maximum value, Minimum value, Brightness value and the Normalized value. The Area, length, Tightness and the Shape rule of the image object Spatial features and texture features such as Mean, Variance and Entropy of image objects are used as classification features of training samples. Based on the reference images and the sampling points of on-the-spot investigation, typical training samples are selected uniformly and randomly for each type of ground objects. The spectral, texture and spatial characteristics of each type of feature in each feature layer corresponding to the range of values are used to create the decision tree repository. Finally, with the help of high resolution reference images, the random sampling method is used to conduct the field investigation, achieve an overall accuracy of 90.31 %, and the Kappa coefficient is 0.88. The classification method based on decision tree threshold values and rule set developed by the repository, outperforms the results obtained from the traditional methodology. Our decision tree repository and rule set based object-oriented classification technique was an effective method for producing comparable and consistency wetlands data set.

Kepler and K2 Light Curves of Active Galaxies: Optical Time Domain Windows into the Central Engine

NASA Astrophysics Data System (ADS)

Smith, Krista Lynne; Mushotzky, Richard; Boyd, Patricia T.; Howell, Steve B.; Gehrels, Neil; Gelino, Dawn M.

2017-01-01

We have used the Kepler spacecraft, the most precise photometer ever built, to measure aperiodic variability in active galactic nuclei. Kepler's high cadence and even sampling make it an exquisite instrument for astrophysics far beyond exoplanets, especially in the study of active galactic nuclei, which have long been known for their strong optical variability. Because of the very small size of accretion disks, this variability provides the only direct probe of their interior physics. In order to find AGN for study with the Kepler and K2 missions, we have conducted an X-ray survey of the Kepler and K2 fields of view with the Swift XRT, locating hundreds of new AGN that sample a wide parameter space in black hole mass and accretion rate. This survey also yielded an abundant sample of X-ray bright variable stellar targets. We then built a custom pipeline to handle Kepler light curves of extended objects (the AGN host galaxies) with stochastic variability. This was necessary, since the default Kepler pipeline was not optimized for such objects. Power spectral density (PSD) analysis of the AGN light curves exhibit characteristic timescales on the order of 2.5 days to 80 days, consistent with the physical timescales believed to be important in the disk. Optical spectral follow-up of the full sample enables comparison with physical parameters such as black hole mass, Eddington ratio and bolometric luminosity. The black hole mass relationship with characteristic timescale is consistent with an extrapolation of the relationship seen in stellar mass black holes, implying accretion similarities across many orders of magnitude. One object hosts a strong candidate for an optical quasi-periodic oscillation (QPO), the characteristic frequency of which correctly predicts the measured single-epoch black hole mass. The sample also contains bimodal flux distributions, which may indicate accretion states. Many of the high-frequency power spectral density (PSD) slopes are generally consistent with damped random walk models, but these fail to describe the full range of variability observed. The light curves continue to provide a fertile testing bed for the various predictions of accretion disk simulations.

Hyperspectral estimation of soil heavy metals in Guanzhong area, Shaanxi province

NASA Astrophysics Data System (ADS)

Liu, Jinbao; Cheng, Jie; Wang, Huanyuan; Tong, Wei; Ma, Zenghui

2017-10-01

In this study, the contents of Cr, Mn, Ni, Cu, and Zn, As, Cd, Hg and Pub in 44 soil samples were collected from Fufeng County, Yangling County and Wugong County, Shaanxi Province and were used as data sources. ASD Field Spec HR (350 ˜ 2500 nm), and then the NOR, MSC and SNV of the reflectance were pretreated, the first deviation, second deviation and reflectance reciprocal logarithmic transformation were carried out. The optimal hyper spectral estimation model of nine heavy metal elements of Cr, Mn, Ni, Cu, and Zn, As, Cd, Hg and Pb was established by regression method. Comparing the reflection characteristics of different heavy metal contents and the effect of different pretreatment methods on the establishment of soil heavy metal spectral inversion model. The results show that: (1) the reflectance spectrum improves the signal-to-noise ratio of the reflectance spectrum after the transformation of NOR, MSC and SNV. Combining differential transformation can improve the information of heavy metal elements in the soil, and use the correlation band energy significantly improve the stability and predictability of the model. (2) The modeling accuracy of the optimal model of nine heavy metal spectra of Cr, Mn, Ni, Cu, and Zn, As, Cd, Hg and Pb by PLSR method were 0.7002, 0.7852, 0.687, 0.8036, 0.8619, 0.5765, 0.5451, 0.9912, and 0.6182.

Hyperspectral Analysis of Soil Total Nitrogen in Subsided Land Using the Local Correlation Maximization-Complementary Superiority (LCMCS) Method

PubMed Central

Lin, Lixin; Wang, Yunjia; Teng, Jiyao; Xi, Xiuxiu

2015-01-01

The measurement of soil total nitrogen (TN) by hyperspectral remote sensing provides an important tool for soil restoration programs in areas with subsided land caused by the extraction of natural resources. This study used the local correlation maximization-complementary superiority method (LCMCS) to establish TN prediction models by considering the relationship between spectral reflectance (measured by an ASD FieldSpec 3 spectroradiometer) and TN based on spectral reflectance curves of soil samples collected from subsided land which is determined by synthetic aperture radar interferometry (InSAR) technology. Based on the 1655 selected effective bands of the optimal spectrum (OSP) of the first derivate differential of reciprocal logarithm ([log{1/R}]′), (correlation coefficients, p < 0.01), the optimal model of LCMCS method was obtained to determine the final model, which produced lower prediction errors (root mean square error of validation [RMSEV] = 0.89, mean relative error of validation [MREV] = 5.93%) when compared with models built by the local correlation maximization (LCM), complementary superiority (CS) and partial least squares regression (PLS) methods. The predictive effect of LCMCS model was optional in Cangzhou, Renqiu and Fengfeng District. Results indicate that the LCMCS method has great potential to monitor TN in subsided lands caused by the extraction of natural resources including groundwater, oil and coal. PMID:26213935

Optimal Fisher Discriminant Ratio for an Arbitrary Spatial Light Modulator

NASA Technical Reports Server (NTRS)

Juday, Richard D.

1999-01-01

Optimizing the Fisher ratio is well established in statistical pattern recognition as a means of discriminating between classes. I show how to optimize that ratio for optical correlation intensity by choice of filter on an arbitrary spatial light modulator (SLM). I include the case of additive noise of known power spectral density.

Spectral pattern recognition of controlled substances in street samples using artificial neural network system

NASA Astrophysics Data System (ADS)

Poryvkina, Larisa; Aleksejev, Valeri; Babichenko, Sergey M.; Ivkina, Tatjana

2011-04-01

The NarTest fluorescent technique is aimed at the detection of analyte of interest in street samples by recognition of its specific spectral patterns in 3-dimentional Spectral Fluorescent Signatures (SFS) measured with NTX2000 analyzer without chromatographic or other separation of controlled substances from a mixture with cutting agents. The illicit drugs have their own characteristic SFS features which can be used for detection and identification of narcotics, however typical street sample consists of a mixture with cutting agents: adulterants and diluents. Many of them interfere the spectral shape of SFS. The expert system based on Artificial Neural Networks (ANNs) has been developed and applied for such pattern recognition in SFS of street samples of illicit drugs.

Optimal colour quality of LED clusters based on memory colours.

PubMed

Smet, Kevin; Ryckaert, Wouter R; Pointer, Michael R; Deconinck, Geert; Hanselaer, Peter

2011-03-28

The spectral power distributions of tri- and tetrachromatic clusters of Light-Emitting-Diodes, composed of simulated and commercially available LEDs, were optimized with a genetic algorithm to maximize the luminous efficacy of radiation and the colour quality as assessed by the memory colour quality metric developed by the authors. The trade-off of the colour quality as assessed by the memory colour metric and the luminous efficacy of radiation was investigated by calculating the Pareto optimal front using the NSGA-II genetic algorithm. Optimal peak wavelengths and spectral widths of the LEDs were derived, and over half of them were found to be close to Thornton's prime colours. The Pareto optimal fronts of real LED clusters were always found to be smaller than those of the simulated clusters. The effect of binning on designing a real LED cluster was investigated and was found to be quite large. Finally, a real LED cluster of commercially available AlGaInP, InGaN and phosphor white LEDs was optimized to obtain a higher score on memory colour quality scale than its corresponding CIE reference illuminant.

Multi-objective based spectral unmixing for hyperspectral images

NASA Astrophysics Data System (ADS)

Xu, Xia; Shi, Zhenwei

2017-02-01

Sparse hyperspectral unmixing assumes that each observed pixel can be expressed by a linear combination of several pure spectra in a priori library. Sparse unmixing is challenging, since it is usually transformed to a NP-hard l0 norm based optimization problem. Existing methods usually utilize a relaxation to the original l0 norm. However, the relaxation may bring in sensitive weighted parameters and additional calculation error. In this paper, we propose a novel multi-objective based algorithm to solve the sparse unmixing problem without any relaxation. We transform sparse unmixing to a multi-objective optimization problem, which contains two correlative objectives: minimizing the reconstruction error and controlling the endmember sparsity. To improve the efficiency of multi-objective optimization, a population-based randomly flipping strategy is designed. Moreover, we theoretically prove that the proposed method is able to recover a guaranteed approximate solution from the spectral library within limited iterations. The proposed method can directly deal with l0 norm via binary coding for the spectral signatures in the library. Experiments on both synthetic and real hyperspectral datasets demonstrate the effectiveness of the proposed method.

Some Insights of Spectral Optimization in Ocean Color Inversion

NASA Technical Reports Server (NTRS)

Lee, Zhongping; Franz, Bryan; Shang, Shaoling; Dong, Qiang; Arnone, Robert

2011-01-01

In the past decades various algorithms have been developed for the retrieval of water constituents from the measurement of ocean color radiometry, and one of the approaches is spectral optimization. This approach defines an error target (or error function) between the input remote sensing reflectance and the output remote sensing reflectance, with the latter modeled with a few variables that represent the optically active properties (such as the absorption coefficient of phytoplankton and the backscattering coefficient of particles). The values of the variables when the error reach a minimum (optimization is achieved) are considered the properties that form the input remote sensing reflectance; or in other words, the equations are solved numerically. The applications of this approach implicitly assume that the error is a monotonic function of the various variables. Here, with data from numerical simulation and field measurements, we show the shape of the error surface, in a way to justify the possibility of finding a solution of the various variables. In addition, because the spectral properties could be modeled differently, impacts of such differences on the error surface as well as on the retrievals are also presented.

Spectral optimized asymmetric segmented phase-only correlation filter.

PubMed

Leonard, I; Alfalou, A; Brosseau, C

2012-05-10

We suggest a new type of optimized composite filter, i.e., the asymmetric segmented phase-only filter (ASPOF), for improving the effectiveness of a VanderLugt correlator (VLC) when used for face identification. Basically, it consists in merging several reference images after application of a specific spectral optimization method. After segmentation of the spectral filter plane to several areas, each area is assigned to a single winner reference according to a new optimized criterion. The point of the paper is to show that this method offers a significant performance improvement on standard composite filters for face identification. We first briefly revisit composite filters [adapted, phase-only, inverse, compromise optimal, segmented, minimum average correlation energy, optimal trade-off maximum average correlation, and amplitude-modulated phase-only (AMPOF)], which are tools of choice for face recognition based on correlation techniques, and compare their performances with those of the ASPOF. We illustrate some of the drawbacks of current filters for several binary and grayscale image identifications. Next, we describe the optimization steps and introduce the ASPOF that can overcome these technical issues to improve the quality and the reliability of the correlation-based decision. We derive performance measures, i.e., PCE values and receiver operating characteristic curves, to confirm consistency of the results. We numerically find that this filter increases the recognition rate and decreases the false alarm rate. The results show that the discrimination of the ASPOF is comparable to that of the AMPOF, but the ASPOF is more robust than the trade-off maximum average correlation height against rotation and various types of noise sources. Our method has several features that make it amenable to experimental implementation using a VLC.

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

USDA-ARS?s Scientific Manuscript database

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

Parallel detecting, spectroscopic ellipsometers/polarimeters

DOEpatents

Furtak, Thomas E.

2002-01-01

The parallel detecting spectroscopic ellipsometer/polarimeter sensor has no moving parts and operates in real-time for in-situ monitoring of the thin film surface properties of a sample within a processing chamber. It includes a multi-spectral source of radiation for producing a collimated beam of radiation directed towards the surface of the sample through a polarizer. The thus polarized collimated beam of radiation impacts and is reflected from the surface of the sample, thereby changing its polarization state due to the intrinsic material properties of the sample. The light reflected from the sample is separated into four separate polarized filtered beams, each having individual spectral intensities. Data about said four individual spectral intensities is collected within the processing chamber, and is transmitted into one or more spectrometers. The data of all four individual spectral intensities is then analyzed using transformation algorithms, in real-time.

Simulation of time-dispersion spectral device with sample spectra accumulation

NASA Astrophysics Data System (ADS)

Zhdanov, Arseny; Khansuvarov, Ruslan; Korol, Georgy

2014-09-01

This research is conducted in order to design a spectral device for light sources power spectrum analysis. The spectral device should process radiation from sources, direct contact with radiation of which is either impossible or undesirable. Such sources include jet blast of an aircraft, optical radiation in metallurgy and textile industry. In proposed spectral device optical radiation is guided out of unfavorable environment via a piece of optical fiber with high dispersion. It is necessary for analysis to make samples of analyzed radiation as short pulses. Dispersion properties of such optical fiber cause spectral decomposition of input optical pulses. The faster time of group delay vary the stronger the spectral decomposition effect. This effect allows using optical fiber with high dispersion as a major element of proposed spectral device. Duration of sample must be much shorter than group delay time difference of a dispersive system. In the given frequency range this characteristic has to be linear. The frequency range is 400 … 500 THz for typical optical fiber. Using photonic-crystal fiber (PCF) gives much wider spectral range for analysis. In this paper we propose simulation of single pulse transmission through dispersive system with linear dispersion characteristic and quadratic-detected output responses accumulation. During simulation we propose studying influence of optical fiber dispersion characteristic angle on spectral measurement results. We also consider pulse duration and group delay time difference impact on output pulse shape and duration. Results show the most suitable dispersion characteristic that allow choosing the structure of PCF - major element of time-dispersion spectral analysis method and required number of samples for reliable assessment of measured spectrum.

A 1064 nm dispersive Raman spectral imaging system for food safety and quality evaluation

USDA-ARS?s Scientific Manuscript database

Raman spectral imaging is an effective method to analyze and evaluate chemical composition and structure of a sample, and has many applications for food safety and quality research. This study developed a 1064 nm Raman spectral imaging system for surface and subsurface analysis of food samples. A 10...

Optimal spectral structure for simultaneous Stimulated Brillouin Scattering suppression and coherent property preservation in high power coherent beam combination system

NASA Astrophysics Data System (ADS)

Han, Kai; Xu, Xiaojun; Liu, Zejin

2013-05-01

Based on the spectral manipulation technique, the Stimulated Brillouin Scattering (SBS) suppression effect and the coherent beam combination (CBC) effect in multi-tone CBC system are researched theoretically and experimentally. To get satisfactory SBS suppression, the frequency interval of the multi-tone seed laser should be large enough, at least larger than the SBS gain bandwidth. In order to attain excellent CBC effect, the spectra of the multi-tone seed laser need to be matched with the optical path differences among the amplifier chains. Hence, a sufficiently separated matching spectrum is capable at both SBS mitigation and coherent property preservation. By comparing the SBS suppression effect and the CBC effect at various spectra, the optimal spectral structure for simultaneous SBS suppression and excellent CBC effect is found.

A method for simultaneous echo planar imaging of hyperpolarized 13C pyruvate and 13C lactate

NASA Astrophysics Data System (ADS)

Reed, Galen D.; Larson, Peder E. Z.; von Morze, Cornelius; Bok, Robert; Lustig, Michael; Kerr, Adam B.; Pauly, John M.; Kurhanewicz, John; Vigneron, Daniel B.

2012-04-01

A rapid echo planar imaging sequence for dynamic imaging of [1-13C] lactate and [1-13C] pyruvate simultaneously was developed. Frequency-based separation of these metabolites was achieved by spatial shifting in the phase-encoded direction with the appropriate choice of echo spacing. Suppression of the pyruvate-hydrate and alanine resonances is achieved through an optimized spectral-spatial RF waveform. Signal sampling efficiency as a function of pyruvate and lactate excitation angle was simulated using two site exchange models. Dynamic imaging is demonstrated in a transgenic mouse model, and phantom validations of the RF pulse frequency selectivity were performed.

Utilizing a Tower Based System for Optical Sensing of Ecosystem Carbon Fluxes

NASA Astrophysics Data System (ADS)

Huemmrich, K. F.; Corp, L. A.; Middleton, E.; Campbell, P. K. E.; Landis, D.; Kustas, W. P.

2015-12-01

Optical sampling of spectral reflectance and solar induced fluorescence provide information on the physiological status of vegetation that can be used to infer stress responses and estimates of production. Multiple repeated observations are required to observe the effects of changing environmental conditions on vegetation. This study examines the use of optical signals to determine inputs to a light use efficiency (LUE) model describing productivity of a cornfield where repeated observations of carbon flux, spectral reflectance and fluorescence were collected. Data were collected at the Optimizing Production Inputs for Economic and Environmental Enhancement (OPE3) fields (39.03°N, 76.85°W) at USDA Beltsville Agricultural Research Center. Agricultural Research Service researchers measured CO2 fluxes using eddy covariance methods throughout the growing season. Optical measurements were made from the nearby tower supporting the NASA FUSION sensors. The sensor system consists of two dual channel, upward and downward looking, spectrometers used to simultaneously collect high spectral resolution measurements of reflected and fluoresced light from vegetation canopies at multiple view angles. Estimates of chlorophyll fluorescence, combined with measures of vegetation pigment content and the Photosynthetic Reflectance Index (PRI) derived from the spectral reflectance are compared with CO2 fluxes over diurnal periods for multiple days. The relationships among the different optical measurements indicate that they are providing different types of information on the vegetation and that combinations of these measurements provide improved retrievals of CO2 fluxes than any index alone

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.

Studies on spectral analysis of randomly sampled signals: Application to laser velocimetry data

NASA Technical Reports Server (NTRS)

Sree, David

1992-01-01

Spectral analysis is very useful in determining the frequency characteristics of many turbulent flows, for example, vortex flows, tail buffeting, and other pulsating flows. It is also used for obtaining turbulence spectra from which the time and length scales associated with the turbulence structure can be estimated. These estimates, in turn, can be helpful for validation of theoretical/numerical flow turbulence models. Laser velocimetry (LV) is being extensively used in the experimental investigation of different types of flows, because of its inherent advantages; nonintrusive probing, high frequency response, no calibration requirements, etc. Typically, the output of an individual realization laser velocimeter is a set of randomly sampled velocity data. Spectral analysis of such data requires special techniques to obtain reliable estimates of correlation and power spectral density functions that describe the flow characteristics. FORTRAN codes for obtaining the autocorrelation and power spectral density estimates using the correlation-based slotting technique were developed. Extensive studies have been conducted on simulated first-order spectrum and sine signals to improve the spectral estimates. A first-order spectrum was chosen because it represents the characteristics of a typical one-dimensional turbulence spectrum. Digital prefiltering techniques, to improve the spectral estimates from randomly sampled data were applied. Studies show that the spectral estimates can be increased up to about five times the mean sampling rate.

Structure, isomerism, and vibrational assignment of aluminumtrifluoroacetylacetonate. An experimental and theoretical study

NASA Astrophysics Data System (ADS)

Afzali, R.; Vakili, M.; Boluri, E.; Tayyari, S. F.; Nekoei, A.-R.; Hakimi-Tabar, M.; Darugar, V.

2018-02-01

An interpretation of the experimental IR and Raman spectra of Aluminum (III) trifluoroacetylacetonate (Al(TFAA)3) complex, which were synthesized by us, is first reported here. The charge distribution, isomerism, strength of metal-oxygen binding and vibrational spectral properties for this complex structure were theoretically investigated through population analysis, geometry optimization and harmonic frequency calculations, performed at B3LYP/6-311G* level of theory. In the population analysis, two different approaches reffered to as ;Atoms in molecules (AIM);, and ;Natural Bond Orbital (NBO); were used. According to the calculation resuls, the energy difference between the cis and trans isomers of Al(TFAA)3 is very small and indicates that both isomers coexist in the sample in comparable proportions. Comparison of the calculated frequency and intensity data with the observed IR and Raman spectra of the complex has supported this conclusion. On the other hand, comparison of the structural and vibrational spectral data of Al(TFAA)3, which were experimentally measured and calculated at B3LYP/6-311G* level, with the corresponding data of Aluminum acetylacetonate (Al(AA)3) has revealed the effects of CF3 substitution on the structural and vibrational spectral data associated with the CH3 groups in the complex structure.

Ultra-high-resolution inelastic X-ray scattering at high-repetition-rate self-seeded X-ray free-electron lasers

PubMed Central

Chubar, Oleg; Geloni, Gianluca; Kocharyan, Vitali; Madsen, Anders; Saldin, Evgeni; Serkez, Svitozar; Shvyd’ko, Yuri; Sutter, John

2016-01-01

Inelastic X-ray scattering (IXS) is an important tool for studies of equilibrium dynamics in condensed matter. A new spectrometer recently proposed for ultra-high-resolution IXS (UHRIX) has achieved 0.6 meV and 0.25 nm−1 spectral and momentum-transfer resolutions, respectively. However, further improvements down to 0.1 meV and 0.02 nm−1 are required to close the gap in energy–momentum space between high- and low-frequency probes. It is shown that this goal can be achieved by further optimizing the X-ray optics and by increasing the spectral flux of the incident X-ray pulses. UHRIX performs best at energies from 5 to 10 keV, where a combination of self-seeding and undulator tapering at the SASE-2 beamline of the European XFEL promises up to a 100-fold increase in average spectral flux compared with nominal SASE pulses at saturation, or three orders of magnitude more than what is possible with storage-ring-based radiation sources. Wave-optics calculations show that about 7 × 1012 photons s−1 in a 90 µeV bandwidth can be achieved on the sample. This will provide unique new possibilities for dynamics studies by IXS. PMID:26917127

Liquid chromatography with diode array detection combined with spectral deconvolution for the analysis of some diterpene esters in Arabica coffee brew.

PubMed

Erny, Guillaume L; Moeenfard, Marzieh; Alves, Arminda

2015-02-01

In this manuscript, the separation of kahweol and cafestol esters from Arabica coffee brews was investigated using liquid chromatography with a diode array detector. When detected in conjunction, cafestol, and kahweol esters were eluted together, but, after optimization, the kahweol esters could be selectively detected by setting the wavelength at 290 nm to allow their quantification. Such an approach was not possible for the cafestol esters, and spectral deconvolution was used to obtain deconvoluted chromatograms. In each of those chromatograms, the four esters were baseline separated allowing for the quantification of the eight targeted compounds. Because kahweol esters could be quantified either using the chromatogram obtained by setting the wavelength at 290 nm or using the deconvoluted chromatogram, those compounds were used to compare the analytical performances. Slightly better limits of detection were obtained using the deconvoluted chromatogram. Identical concentrations were found in a real sample with both approaches. The peak areas in the deconvoluted chromatograms were repeatable (intraday repeatability of 0.8%, interday repeatability of 1.0%). This work demonstrates the accuracy of spectral deconvolution when using liquid chromatography to mathematically separate coeluting compounds using the full spectra recorded by a diode array detector. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Optical Sensing of Ecosystem Carbon Fluxes from Tower-mounted Spectrometers

NASA Astrophysics Data System (ADS)

Huemmrich, K. F.; Corp, L. A.; Middleton, E.; Cook, B.; Campbell, P. K. E.; Zhang, Q.; Hom, M.; Russ, A.; Kustas, W. P.

2016-12-01

Optical sampling of spectral reflectance and solar induced fluorescence provide information on the physiological status of vegetation that can be used to infer stress responses and estimates of production. To fully understand these measurements requires descriptions of temporal and bidirectional variability. The NASA FUSION tower-mounted system consists of two dual channel, upward and downward looking, spectrometers used to simultaneously collect high spectral resolution measurements of reflected and fluoresced light from vegetation canopies at multiple view angles. This comprehensive tower measurement dataset can provide insights into interpretation of satellite or aircraft observations. Data were collected in the Optimizing Production Inputs for Economic and Environmental Enhancement (OPE3) cornfields (39.03°N, 76.85°W) at USDA Beltsville Agricultural Research Center in conjunction with CO2 eddy covariance fluxes throughout the growing season. Estimates of chlorophyll fluorescence, combined with measures of vegetation pigment content and the Photosynthetic Reflectance Index (PRI) derived from the spectral reflectance are compared with CO2 fluxes over diurnal periods for multiple days. We find significant bidirectional effects. The relationships among the different optical measurements indicate that they are providing different types of information on the vegetation and that combinations of these measurements provide improved retrievals of CO2 fluxes than any index alone.

Evaluation of wavelet spectral features in pathological detection and discrimination of yellow rust and powdery mildew in winter wheat with hyperspectral reflectance data

NASA Astrophysics Data System (ADS)

Shi, Yue; Huang, Wenjiang; Zhou, Xianfeng

2017-04-01

Hyperspectral absorption features are important indicators of characterizing plant biophysical variables for the automatic diagnosis of crop diseases. Continuous wavelet analysis has proven to be an advanced hyperspectral analysis technique for extracting absorption features; however, specific wavelet features (WFs) and their relationship with pathological characteristics induced by different infestations have rarely been summarized. The aim of this research is to determine the most sensitive WFs for identifying specific pathological lesions from yellow rust and powdery mildew in winter wheat, based on 314 hyperspectral samples measured in field experiments in China in 2002, 2003, 2005, and 2012. The resultant WFs could be used as proxies to capture the major spectral absorption features caused by infestation of yellow rust or powdery mildew. Multivariate regression analysis based on these WFs outperformed conventional spectral features in disease detection; meanwhile, a Fisher discrimination model exhibited considerable potential for generating separable clusters for each infestation. Optimal classification returned an overall accuracy of 91.9% with a Kappa of 0.89. This paper also emphasizes the WFs and their relationship with pathological characteristics in order to provide a foundation for the further application of this approach in monitoring winter wheat diseases at the regional scale.

Ultra-high-resolution inelastic X-ray scattering at high-repetition-rate self-seeded X-ray free-electron lasers

DOE PAGES

Chubar, Oleg; Geloni, Gianluca; Kocharyan, Vitali; ...

2016-03-01

Inelastic X-ray scattering (IXS) is an important tool for studies of equilibrium dynamics in condensed matter. A new spectrometer recently proposed for ultra-high-resolution IXS (UHRIX) has achieved 0.6 meV and 0.25 nm ₋1spectral and momentum-transfer resolutions, respectively. However, further improvements down to 0.1 meV and 0.02 nm ₋1are required to close the gap in energy–momentum space between high- and low-frequency probes. It is shown that this goal can be achieved by further optimizing the X-ray optics and by increasing the spectral flux of the incident X-ray pulses. UHRIX performs best at energies from 5 to 10 keV, where a combinationmore » of self-seeding and undulator tapering at the SASE-2 beamline of the European XFEL promises up to a 100-fold increase in average spectral flux compared with nominal SASE pulses at saturation, or three orders of magnitude more than what is possible with storage-ring-based radiation sources. Wave-optics calculations show that about 7 × 10 12 photons s ₋1in a 90 µeV bandwidth can be achieved on the sample. Ultimately, this will provide unique new possibilities for dynamics studies by IXS.« less

Optimal positions and parameters of translational and rotational mass dampers in beams subjected to random excitation

NASA Astrophysics Data System (ADS)

Łatas, Waldemar

2018-01-01

The problem of vibrations of the beam with the attached system of translational and rotational dynamic mass dampers subjected to random excitations with peaked power spectral densities, is presented in the hereby paper. The Euler-Bernoulli beam model is applied, while for solving the equation of motion the Galerkin method and the Laplace time transform are used. The obtained transfer functions allow to determine power spectral densities of the beam deflection and other dependent variables. Numerical examples present simple optimization problems of mass dampers parameters for local and global objective functions.

Formulation procedure and spectral data for a coatings system optimally employing the high intrinsic reflectance of barium sulphate

NASA Technical Reports Server (NTRS)

Schutt, J. B.; Stromberg, E.; Shai, C. M.; Arens, J. F.

1972-01-01

The use of polyvinyl alcohol as a binder for barium sulphate does not allow the intrinsically high reflectance of this material in the near vacuum ultraviolet to be optimally employed. In an effort to better utilize this property, completely inorganic coatings systems are described, where from the intrinsically high reflectance of barium sulphate in this spectral region can be gotten. Potassium sulphate turns out to be the preferred binder. Compositions, formulating procedures, and application techniques are included. For completeness, absolute and relative reflectance data are included for intra- and intersystem comparisons.

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.

Spectrally-Temporally Adapted Spectrally Modulated Spectrally Encoded (SMSE) Waveform Design for Coexistent CR-Based SDR Applications

DTIC Science & Technology

2010-03-01

uses all available resources in some optimized manner. By further exploiting the design flexibility and computational efficiency of Orthogonal Frequency...in the following sections. 3.2.1 Estimation of PU Signal Statistics. The Estimate PU Signal Statis- tics function of Fig 3.4 is used to compute the...consecutive PU transmissions, and 4) the probability of transitioning from one transmission state to another. These statistics are then used to compute the

Synthetic Hounsfield units from spectral CT data

NASA Astrophysics Data System (ADS)

Bornefalk, Hans

2012-04-01

Beam-hardening-free synthetic images with absolute CT numbers that radiologists are used to can be constructed from spectral CT data by forming ‘dichromatic’ images after basis decomposition. The CT numbers are accurate for all tissues and the method does not require additional reconstruction. This method prevents radiologists from having to relearn new rules-of-thumb regarding absolute CT numbers for various organs and conditions as conventional CT is replaced by spectral CT. Displaying the synthetic Hounsfield unit images side-by-side with images reconstructed for optimal detectability for a certain task can ease the transition from conventional to spectral CT.

Frequency locking of a field-widened Michelson interferometer based on optimal multi-harmonics heterodyning.

PubMed

Cheng, Zhongtao; Liu, Dong; Zhou, Yudi; Yang, Yongying; Luo, Jing; Zhang, Yupeng; Shen, Yibing; Liu, Chong; Bai, Jian; Wang, Kaiwei; Su, Lin; Yang, Liming

2016-09-01

A general resonant frequency locking scheme for a field-widened Michelson interferometer (FWMI), which is intended as a spectral discriminator in a high-spectral-resolution lidar, is proposed based on optimal multi-harmonics heterodyning. By transferring the energy of a reference laser to multi-harmonics of different orders generated by optimal electro-optic phase modulation, the heterodyne signal of these multi-harmonics through the FWMI can reveal the resonant frequency drift of the interferometer very sensitively within a large frequency range. This approach can overcome the locking difficulty induced by the low finesse of the FWMI, thus contributing to excellent locking accuracy and lock acquisition range without any constraint on the interferometer itself. The theoretical and experimental results are presented to verify the performance of this scheme.

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.

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.

Effect of non-Poisson samples on turbulence spectra from laser velocimetry

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

Sree, D.; Kjelgaard, S.O.; Sellers, W.L. III

1994-12-01

Spectral estimations from LV data are typically based on the assumption of a Poisson sampling process. It is demonstrated here that the sampling distribution must be considered before spectral estimates are used to infer turbulence scales. A non-Poisson sampling process can occur if there is nonhomogeneous distribution of particles in the flow. Based on the study of a simulated first-order spectrum, it has been shown that a non-Poisson sampling process causes the estimated spectrum to deviate from the true spectrum. Also, in this case the prefiltering techniques do not improve the spectral estimates at higher frequencies. 4 refs.

Methods for spectral image analysis by exploiting spatial simplicity

DOEpatents

Keenan, Michael R.

2010-05-25

Several full-spectrum imaging techniques have been introduced in recent years that promise to provide rapid and comprehensive chemical characterization of complex samples. One of the remaining obstacles to adopting these techniques for routine use is the difficulty of reducing the vast quantities of raw spectral data to meaningful chemical information. Multivariate factor analysis techniques, such as Principal Component Analysis and Alternating Least Squares-based Multivariate Curve Resolution, have proven effective for extracting the essential chemical information from high dimensional spectral image data sets into a limited number of components that describe the spectral characteristics and spatial distributions of the chemical species comprising the sample. There are many cases, however, in which those constraints are not effective and where alternative approaches may provide new analytical insights. For many cases of practical importance, imaged samples are "simple" in the sense that they consist of relatively discrete chemical phases. That is, at any given location, only one or a few of the chemical species comprising the entire sample have non-zero concentrations. The methods of spectral image analysis of the present invention exploit this simplicity in the spatial domain to make the resulting factor models more realistic. Therefore, more physically accurate and interpretable spectral and abundance components can be extracted from spectral images that have spatially simple structure.

Methods for spectral image analysis by exploiting spatial simplicity

DOEpatents

Keenan, Michael R.

2010-11-23

Several full-spectrum imaging techniques have been introduced in recent years that promise to provide rapid and comprehensive chemical characterization of complex samples. One of the remaining obstacles to adopting these techniques for routine use is the difficulty of reducing the vast quantities of raw spectral data to meaningful chemical information. Multivariate factor analysis techniques, such as Principal Component Analysis and Alternating Least Squares-based Multivariate Curve Resolution, have proven effective for extracting the essential chemical information from high dimensional spectral image data sets into a limited number of components that describe the spectral characteristics and spatial distributions of the chemical species comprising the sample. There are many cases, however, in which those constraints are not effective and where alternative approaches may provide new analytical insights. For many cases of practical importance, imaged samples are "simple" in the sense that they consist of relatively discrete chemical phases. That is, at any given location, only one or a few of the chemical species comprising the entire sample have non-zero concentrations. The methods of spectral image analysis of the present invention exploit this simplicity in the spatial domain to make the resulting factor models more realistic. Therefore, more physically accurate and interpretable spectral and abundance components can be extracted from spectral images that have spatially simple structure.

The spatial sensitivity of the spectral diversity-biodiversity relationship: an experimental test in a prairie grassland.

PubMed

Wang, Ran; Gamon, John A; Cavender-Bares, Jeannine; Townsend, Philip A; Zygielbaum, Arthur I

2018-03-01

Remote sensing has been used to detect plant biodiversity in a range of ecosystems based on the varying spectral properties of different species or functional groups. However, the most appropriate spatial resolution necessary to detect diversity remains unclear. At coarse resolution, differences among spectral patterns may be too weak to detect. In contrast, at fine resolution, redundant information may be introduced. To explore the effect of spatial resolution, we studied the scale dependence of spectral diversity in a prairie ecosystem experiment at Cedar Creek Ecosystem Science Reserve, Minnesota, USA. Our study involved a scaling exercise comparing synthetic pixels resampled from high-resolution images within manipulated diversity treatments. Hyperspectral data were collected using several instruments on both ground and airborne platforms. We used the coefficient of variation (CV) of spectral reflectance in space as the indicator of spectral diversity and then compared CV at different scales ranging from 1 mm 2 to 1 m 2 to conventional biodiversity metrics, including species richness, Shannon's index, Simpson's index, phylogenetic species variation, and phylogenetic species evenness. In this study, higher species richness plots generally had higher CV. CV showed higher correlations with Shannon's index and Simpson's index than did species richness alone, indicating evenness contributed to the spectral diversity. Correlations with species richness and Simpson's index were generally higher than with phylogenetic species variation and evenness measured at comparable spatial scales, indicating weaker relationships between spectral diversity and phylogenetic diversity metrics than with species diversity metrics. High resolution imaging spectrometer data (1 mm 2 pixels) showed the highest sensitivity to diversity level. With decreasing spatial resolution, the difference in CV between diversity levels decreased and greatly reduced the optical detectability of biodiversity. The optimal pixel size for distinguishing α diversity in these prairie plots appeared to be around 1 mm to 10 cm, a spatial scale similar to the size of an individual herbaceous plant. These results indicate a strong scale-dependence of the spectral diversity-biodiversity relationships, with spectral diversity best able to detect a combination of species richness and evenness, and more weakly detecting phylogenetic diversity. These findings can be used to guide airborne studies of biodiversity and develop more effective large-scale biodiversity sampling methods. ©2018 The Authors Ecological Applications published by Wiley Periodicals, Inc. on behalf of Ecological Society of America.

The analytical design of spectral measurements for multispectral remote sensor systems

NASA Technical Reports Server (NTRS)

Wiersma, D. J.; Landgrebe, D. A. (Principal Investigator)

1979-01-01

The author has identified the following significant results. In order to choose a design which will be optimal for the largest class of remote sensing problems, a method was developed which attempted to represent the spectral response function from a scene as accurately as possible. The performance of the overall recognition system was studied relative to the accuracy of the spectral representation. The spectral representation was only one of a set of five interrelated parameter categories which also included the spatial representation parameter, the signal to noise ratio, ancillary data, and information classes. The spectral response functions observed from a stratum were modeled as a stochastic process with a Gaussian probability measure. The criterion for spectral representation was defined by the minimum expected mean-square error.

Slitless Solar Spectroscopy

NASA Technical Reports Server (NTRS)

Davila, Joseph M.; Jones, Sahela

2011-01-01

Spectrographs have traditionally suffered from the inability to obtain line intensities, widths, and Doppler shifts over large spatial regions of the Sun quickly because of the narrow instantaneous field of view. This has limited the spectroscopic analysis of rapidly varying solar features like, flares, CME eruptions, coronal jets, and reconnection regions. Imagers have provided high time resolution images of the full Sun with limited spectral resolution. In this paper we present recent advances in deconvolving spectrally dispersed images obtained through broad slits. We use this new theoretical formulation to examine the effectiveness of various potential observing scenarios, spatial and spectral resolutions, signal to noise ratio, and other instrument characteristics. This information will lay the foundation for a new generation of spectral imagers optimized for slitless spectral operation, while retaining the ability to obtain spectral information in transient solar events.

An End-to-End simulator for the development of atmospheric corrections and temperature - emissivity separation algorithms in the TIR spectral domain

NASA Astrophysics Data System (ADS)

Rock, Gilles; Fischer, Kim; Schlerf, Martin; Gerhards, Max; Udelhoven, Thomas

2017-04-01

The development and optimization of image processing algorithms requires the availability of datasets depicting every step from earth surface to the sensor's detector. The lack of ground truth data obliges to develop algorithms on simulated data. The simulation of hyperspectral remote sensing data is a useful tool for a variety of tasks such as the design of systems, the understanding of the image formation process, and the development and validation of data processing algorithms. An end-to-end simulator has been set up consisting of a forward simulator, a backward simulator and a validation module. The forward simulator derives radiance datasets based on laboratory sample spectra, applies atmospheric contributions using radiative transfer equations, and simulates the instrument response using configurable sensor models. This is followed by the backward simulation branch, consisting of an atmospheric correction (AC), a temperature and emissivity separation (TES) or a hybrid AC and TES algorithm. An independent validation module allows the comparison between input and output dataset and the benchmarking of different processing algorithms. In this study, hyperspectral thermal infrared scenes of a variety of surfaces have been simulated to analyze existing AC and TES algorithms. The ARTEMISS algorithm was optimized and benchmarked against the original implementations. The errors in TES were found to be related to incorrect water vapor retrieval. The atmospheric characterization could be optimized resulting in increasing accuracies in temperature and emissivity retrieval. Airborne datasets of different spectral resolutions were simulated from terrestrial HyperCam-LW measurements. The simulated airborne radiance spectra were subjected to atmospheric correction and TES and further used for a plant species classification study analyzing effects related to noise and mixed pixels.

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.

Higher-order triangular spectral element method with optimized cubature points for seismic wavefield modeling

NASA Astrophysics Data System (ADS)

Liu, Youshan; Teng, Jiwen; Xu, Tao; Badal, José

2017-05-01

The mass-lumped method avoids the cost of inverting the mass matrix and simultaneously maintains spatial accuracy by adopting additional interior integration points, known as cubature points. To date, such points are only known analytically in tensor domains, such as quadrilateral or hexahedral elements. Thus, the diagonal-mass-matrix spectral element method (SEM) in non-tensor domains always relies on numerically computed interpolation points or quadrature points. However, only the cubature points for degrees 1 to 6 are known, which is the reason that we have developed a p-norm-based optimization algorithm to obtain higher-order cubature points. In this way, we obtain and tabulate new cubature points with all positive integration weights for degrees 7 to 9. The dispersion analysis illustrates that the dispersion relation determined from the new optimized cubature points is comparable to that of the mass and stiffness matrices obtained by exact integration. Simultaneously, the Lebesgue constant for the new optimized cubature points indicates its surprisingly good interpolation properties. As a result, such points provide both good interpolation properties and integration accuracy. The Courant-Friedrichs-Lewy (CFL) numbers are tabulated for the conventional Fekete-based triangular spectral element (TSEM), the TSEM with exact integration, and the optimized cubature-based TSEM (OTSEM). A complementary study demonstrates the spectral convergence of the OTSEM. A numerical example conducted on a half-space model demonstrates that the OTSEM improves the accuracy by approximately one order of magnitude compared to the conventional Fekete-based TSEM. In particular, the accuracy of the 7th-order OTSEM is even higher than that of the 14th-order Fekete-based TSEM. Furthermore, the OTSEM produces a result that can compete in accuracy with the quadrilateral SEM (QSEM). The high accuracy of the OTSEM is also tested with a non-flat topography model. In terms of computational efficiency, the OTSEM is more efficient than the Fekete-based TSEM, although it is slightly costlier than the QSEM when a comparable numerical accuracy is required.

A tutorial in displaying mass spectrometry-based proteomic data using heat maps.

PubMed

Key, Melissa

2012-01-01

Data visualization plays a critical role in interpreting experimental results of proteomic experiments. Heat maps are particularly useful for this task, as they allow us to find quantitative patterns across proteins and biological samples simultaneously. The quality of a heat map can be vastly improved by understanding the options available to display and organize the data in the heat map. This tutorial illustrates how to optimize heat maps for proteomics data by incorporating known characteristics of the data into the image. First, the concepts used to guide the creating of heat maps are demonstrated. Then, these concepts are applied to two types of analysis: visualizing spectral features across biological samples, and presenting the results of tests of statistical significance. For all examples we provide details of computer code in the open-source statistical programming language R, which can be used for biologists and clinicians with little statistical background. Heat maps are a useful tool for presenting quantitative proteomic data organized in a matrix format. Understanding and optimizing the parameters used to create the heat map can vastly improve both the appearance and the interoperation of heat map data.

Elemental composition of edible nuts: fast optimization and validation procedure of an ICP-OES method.

PubMed

Tošić, Snežana B; Mitić, Snežana S; Velimirović, Dragan S; Stojanović, Gordana S; Pavlović, Aleksandra N; Pecev-Marinković, Emilija T

2015-08-30

An inductively coupled plasma-optical emission spectrometry method for the speedy simultaneous detection of 19 elements in edible nuts (walnuts: Juglans nigra; almonds: Prunus dulcis; hazelnuts: Corylus avellana; Brazil nuts: Bertholletia excelsa; cashews: Anacardium occidentalle; pistachios: Pistacia vera; and peanuts: Arachis hypogaea) available on the Serbian markets, was optimized and validated through the selection of instrumental parameters and analytical lines free from spectral interference and with the lowest matrix effects. The analysed macro-elements were present in the following descending order: Na > Mg > Ca > K. Of all the trace elements, the tested samples showed the highest content of Fe. The micro-element Se was detected in all the samples of nuts. The toxic elements As, Cd and Pb were either not detected or the contents were below the limit of detection. One-way analysis of variance, Student's t-test, Tukey's HSD post hoc test and hierarchical agglomerative cluster analysis were applied in the statistical analysis of the results. Based on the detected content of analysed elements it can be concluded that nuts may be a good additional source of minerals as micronutrients. © 2014 Society of Chemical Industry.

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

PubMed

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

2015-02-01

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

Influence of spectral resolution, spectral range and signal-to-noise ratio of Fourier transform infra-red spectra on identification of high explosive substances

NASA Astrophysics Data System (ADS)

Banas, Krzysztof; Banas, Agnieszka M.; Heussler, Sascha P.; Breese, Mark B. H.

2018-01-01

In the contemporary spectroscopy there is a trend to record spectra with the highest possible spectral resolution. This is clearly justified if the spectral features in the spectrum are very narrow (for example infra-red spectra of gas samples). However there is a plethora of samples (in the liquid and especially in the solid form) where there is a natural spectral peak broadening due to collisions and proximity predominately. Additionally there is a number of portable devices (spectrometers) with inherently restricted spectral resolution, spectral range or both, which are extremely useful in some field applications (archaeology, agriculture, food industry, cultural heritage, forensic science). In this paper the investigation of the influence of spectral resolution, spectral range and signal-to-noise ratio on the identification of high explosive substances by applying multivariate statistical methods on the Fourier transform infra-red spectral data sets is studied. All mathematical procedures on spectral data for dimension reduction, clustering and validation were implemented within R open source environment.

Optimization design of spectral discriminator for high-spectral-resolution lidar based on error analysis.

PubMed

Di, Huige; Zhang, Zhanfei; Hua, Hangbo; Zhang, Jiaqi; Hua, Dengxin; Wang, Yufeng; He, Tingyao

2017-03-06

Accurate aerosol optical properties could be obtained via the high spectral resolution lidar (HSRL) technique, which employs a narrow spectral filter to suppress the Rayleigh or Mie scattering in lidar return signals. The ability of the filter to suppress Rayleigh or Mie scattering is critical for HSRL. Meanwhile, it is impossible to increase the rejection of the filter without limitation. How to optimize the spectral discriminator and select the appropriate suppression rate of the signal is important to us. The HSRL technology was thoroughly studied based on error propagation. Error analyses and sensitivity studies were carried out on the transmittance characteristics of the spectral discriminator. Moreover, ratwo different spectroscopic methods for HSRL were described and compared: one is to suppress the Mie scattering; the other is to suppress the Rayleigh scattering. The corresponding HSRLs were simulated and analyzed. The results show that excessive suppression of Rayleigh scattering or Mie scattering in a high-spectral channel is not necessary if the transmittance of the spectral filter for molecular and aerosol scattering signals can be well characterized. When the ratio of transmittance of the spectral filter for aerosol scattering and molecular scattering is less than 0.1 or greater than 10, the detection error does not change much with its value. This conclusion implies that we have more choices for the high-spectral discriminator in HSRL. Moreover, the detection errors of HSRL regarding the two spectroscopic methods vary greatly with the atmospheric backscattering ratio. To reduce the detection error, it is necessary to choose a reasonable spectroscopic method. The detection method of suppressing the Rayleigh signal and extracting the Mie signal can achieve less error in a clear atmosphere, while the method of suppressing the Mie signal and extracting the Rayleigh signal can achieve less error in a polluted atmosphere.

Prediction of meat spectral patterns based on optical properties and concentrations of the major constituents.

PubMed

ElMasry, Gamal; Nakauchi, Shigeki

2016-03-01

A simulation method for approximating spectral signatures of minced meat samples was developed depending on concentrations and optical properties of the major chemical constituents. Minced beef samples of different compositions scanned on a near-infrared spectroscopy and on a hyperspectral imaging system were examined. Chemical composition determined heuristically and optical properties collected from authenticated references were simulated to approximate samples' spectral signatures. In short-wave infrared range, the resulting spectrum equals the sum of the absorption of three individual absorbers, that is, water, protein, and fat. By assuming homogeneous distributions of the main chromophores in the mince samples, the obtained absorption spectra are found to be a linear combination of the absorption spectra of the major chromophores present in the sample. Results revealed that developed models were good enough to derive spectral signatures of minced meat samples with a reasonable level of robustness of a high agreement index value more than 0.90 and ratio of performance to deviation more than 1.4.

Investigation of spectral analysis techniques for randomly sampled velocimetry data

NASA Technical Reports Server (NTRS)

Sree, Dave

1993-01-01

It is well known that velocimetry (LV) generates individual realization velocity data that are randomly or unevenly sampled in time. Spectral analysis of such data to obtain the turbulence spectra, and hence turbulence scales information, requires special techniques. The 'slotting' technique of Mayo et al, also described by Roberts and Ajmani, and the 'Direct Transform' method of Gaster and Roberts are well known in the LV community. The slotting technique is faster than the direct transform method in computation. There are practical limitations, however, as to how a high frequency and accurate estimate can be made for a given mean sampling rate. These high frequency estimates are important in obtaining the microscale information of turbulence structure. It was found from previous studies that reliable spectral estimates can be made up to about the mean sampling frequency (mean data rate) or less. If the data were evenly samples, the frequency range would be half the sampling frequency (i.e. up to Nyquist frequency); otherwise, aliasing problem would occur. The mean data rate and the sample size (total number of points) basically limit the frequency range. Also, there are large variabilities or errors associated with the high frequency estimates from randomly sampled signals. Roberts and Ajmani proposed certain pre-filtering techniques to reduce these variabilities, but at the cost of low frequency estimates. The prefiltering acts as a high-pass filter. Further, Shapiro and Silverman showed theoretically that, for Poisson sampled signals, it is possible to obtain alias-free spectral estimates far beyond the mean sampling frequency. But the question is, how far? During his tenure under 1993 NASA-ASEE Summer Faculty Fellowship Program, the author investigated from his studies on the spectral analysis techniques for randomly sampled signals that the spectral estimates can be enhanced or improved up to about 4-5 times the mean sampling frequency by using a suitable prefiltering technique. But, this increased bandwidth comes at the cost of the lower frequency estimates. The studies further showed that large data sets of the order of 100,000 points, or more, high data rates, and Poisson sampling are very crucial for obtaining reliable spectral estimates from randomly sampled data, such as LV data. Some of the results of the current study are presented.

Coupling detergent lysis/clean-up methodology with intact protein fractionation for enhanced proteome characterization

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

Sharma, Ritin; Dill, Brian; Chourey, Karuna

2012-01-01

The expanding use of surfactants for proteome sample preparations has prompted the need to systematically optimize the application and removal of these MS-deleterious agents prior to proteome measurements. Here we compare four different detergent clean-up methods (Trichloroacetic acid (TCA) precipitation, Chloroform/Methanol/Water (CMW) extraction, commercial detergent removal spin column method (DRS) and filter-aided sample preparation(FASP)) with respect to varying amounts of protein biomass in the samples, and provide efficiency benchmarks with respect to protein, peptide, and spectral identifications for each method. Our results show that for protein limited samples, FASP outperforms the other three clean-up methods, while at high protein amountmore » all the methods are comparable. This information was used in a dual strategy of comparing molecular weight based fractionated and unfractionated lysates from three increasingly complex samples (Escherichia coli, a five microbial isolate mixture, and a natural microbial community groundwater sample), which were all lysed with SDS and cleaned up using FASP. The two approaches complemented each other by enhancing the number of protein identifications by 8%-25% across the three samples and provided broad pathway coverage.« less

Spectral Band Selection for Urban Material Classification Using Hyperspectral Libraries

NASA Astrophysics Data System (ADS)

Le Bris, A.; Chehata, N.; Briottet, X.; Paparoditis, N.

2016-06-01

In urban areas, information concerning very high resolution land cover and especially material maps are necessary for several city modelling or monitoring applications. That is to say, knowledge concerning the roofing materials or the different kinds of ground areas is required. Airborne remote sensing techniques appear to be convenient for providing such information at a large scale. However, results obtained using most traditional processing methods based on usual red-green-blue-near infrared multispectral images remain limited for such applications. A possible way to improve classification results is to enhance the imagery spectral resolution using superspectral or hyperspectral sensors. In this study, it is intended to design a superspectral sensor dedicated to urban materials classification and this work particularly focused on the selection of the optimal spectral band subsets for such sensor. First, reflectance spectral signatures of urban materials were collected from 7 spectral libraires. Then, spectral optimization was performed using this data set. The band selection workflow included two steps, optimising first the number of spectral bands using an incremental method and then examining several possible optimised band subsets using a stochastic algorithm. The same wrapper relevance criterion relying on a confidence measure of Random Forests classifier was used at both steps. To cope with the limited number of available spectra for several classes, additional synthetic spectra were generated from the collection of reference spectra: intra-class variability was simulated by multiplying reference spectra by a random coefficient. At the end, selected band subsets were evaluated considering the classification quality reached using a rbf svm classifier. It was confirmed that a limited band subset was sufficient to classify common urban materials. The important contribution of bands from the Short Wave Infra-Red (SWIR) spectral domain (1000-2400 nm) to material classification was also shown.

Three-Dimensional Reconstruction from Single Image Base on Combination of CNN and Multi-Spectral Photometric Stereo.

PubMed

Lu, Liang; Qi, Lin; Luo, Yisong; Jiao, Hengchao; Dong, Junyu

2018-03-02

Multi-spectral photometric stereo can recover pixel-wise surface normal from a single RGB image. The difficulty lies in that the intensity in each channel is the tangle of illumination, albedo and camera response; thus, an initial estimate of the normal is required in optimization-based solutions. In this paper, we propose to make a rough depth estimation using the deep convolutional neural network (CNN) instead of using depth sensors or binocular stereo devices. Since high-resolution ground-truth data is expensive to obtain, we designed a network and trained it with rendered images of synthetic 3D objects. We use the model to predict initial normal of real-world objects and iteratively optimize the fine-scale geometry in the multi-spectral photometric stereo framework. The experimental results illustrate the improvement of the proposed method compared with existing methods.

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.

Three-Dimensional Reconstruction from Single Image Base on Combination of CNN and Multi-Spectral Photometric Stereo

PubMed Central

Lu, Liang; Qi, Lin; Luo, Yisong; Jiao, Hengchao; Dong, Junyu

2018-01-01

Multi-spectral photometric stereo can recover pixel-wise surface normal from a single RGB image. The difficulty lies in that the intensity in each channel is the tangle of illumination, albedo and camera response; thus, an initial estimate of the normal is required in optimization-based solutions. In this paper, we propose to make a rough depth estimation using the deep convolutional neural network (CNN) instead of using depth sensors or binocular stereo devices. Since high-resolution ground-truth data is expensive to obtain, we designed a network and trained it with rendered images of synthetic 3D objects. We use the model to predict initial normal of real-world objects and iteratively optimize the fine-scale geometry in the multi-spectral photometric stereo framework. The experimental results illustrate the improvement of the proposed method compared with existing methods. PMID:29498703

[Estimation of rice LAI by using NDVI at different spectral bandwidths].

PubMed

Wang, Fu-min; Huang, Jing-feng; Tang, Yan-lin; Wang, Xiu-zhen

2007-11-01

The canopy hyperspectral reflectance data of rice at its different development stages were collected from field measurement, and the corresponding NDVIs as well as the correlation coefficients of NDVIs and LAI were computed at extending bandwidth of TM red and near-infrared (NIR) spectra. According to the variation characteristics of best fitted R2 with spectral bandwidth, the optimal bandwidth was determined. The results showed that the correlation coefficients of LAI and ND-VI and the maximum R2 of the best fitted functions at different spectral bandwidths had the same variation trend, i.e., decreased with increasing bandwidth when the bandwidth was less than 60 nm. However, when the bandwidth was beyond 60 nm, the maximum R2 somewhat fluctuated due to the effect of NIR. The analysis of R2 variation with bandwidth indicated that 15 nm was the optimal bandwidth for the estimation of rice LAI by using NDVI.

Radioastronomic signal processing cores for the SKA radio telescope

NASA Astrophysics Data System (ADS)

Comorett, G.; Chiarucc, S.; Belli, C.

Modern radio telescopes require the processing of wideband signals, with sample rates from tens of MHz to tens of GHz, and are composed from hundreds up to a million of individual antennas. Digital signal processing of these signals include digital receivers (the digital equivalent of the heterodyne receiver), beamformers, channelizers, spectrometers. FPGAs present the advantage of providing a relatively low power consumption, relative to GPUs or dedicated computers, a wide signal data path, and high interconnectivity. Efficient algorithms have been developed for these applications. Here we will review some of the signal processing cores developed for the SKA telescope. The LFAA beamformer/channelizer architecture is based on an oversampling channelizer, where the channelizer output sampling rate and channel spacing can be set independently. This is useful where an overlap between adjacent channels is required to provide an uniform spectral coverage. The architecture allows for an efficient and distributed channelization scheme, with a final resolution corresponding to a million of spectral channels, minimum leakage and high out-of-band rejection. An optimized filter design procedure is used to provide an equiripple response with a very large number of spectral channels. A wideband digital receiver has been designed in order to select the processed bandwidth of the SKA Mid receiver. The receiver extracts a 2.5 MHz bandwidth form a 14 GHz input bandwidth. The design allows for non-integer ratios between the input and output sampling rates, with a resource usage comparable to that of a conventional decimating digital receiver. Finally, some considerations on quantization of radioastronomic signals are presented. Due to the stochastic nature of the signal, quantization using few data bits is possible. Good accuracies and dynamic range are possible even with 2-3 bits, but the nonlinearity in the correlation process must be corrected in post-processing. With at least 6 bits it is possible to have a very linear response of the instrument, with nonlinear terms below 80 dB, providing the signal amplitude is kept within bounds.

Spectral discrimination of giant reed (Arundo donax L.): A seasonal study in riparian areas

NASA Astrophysics Data System (ADS)

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

2013-06-01

The giant reed (Arundo donax L.) is amongst the one hundred worst invasive alien species of the world, and it is responsible for biodiversity loss and failure of ecosystem functions in riparian habitats. In this work, field spectroradiometry was used to assess the spectral separability of the giant reed from the adjacent vegetation and from the common reed, a native similar species. The study was conducted at different phenological periods and also for the giant reed stands regenerated after mechanical cutting (giant reed_RAC). A hierarchical procedure using Kruskal-Wallis test followed by Classification and Regression Trees (CART) was used to select the minimum number of optimal bands that discriminate the giant reed from the adjacent vegetation. A new approach was used to identify sets of wavelengths - wavezones - that maximize the spectral separability beyond the minimum number of optimal bands. Jeffries Matusita and Bhattacharya distance were used to evaluate the spectral separability using the minimum optimal bands and in three simulated satellite images, namely Landsat, IKONOS and SPOT. Giant reed was spectrally separable from the adjacent vegetation, both at the vegetative and the senescent period, exception made to the common reed at the vegetative period. The red edge region was repeatedly selected, although the visible region was also important to separate the giant reed from the herbaceous vegetation and the mid infrared region to the discrimination from the woody vegetation. The highest separability was obtained for the giant reed_RAC stands, due to its highly homogeneous, dense and dark-green stands. Results are discussed by relating the phenological, morphological and structural features of the giant reed stands and the adjacent vegetation with their optical traits. Weaknesses and strengths of the giant reed spectral discrimination are highlighted and implications of imagery selection for mapping purposes are argued based on present results.

Improved observations of turbulence dissipation rates from wind profiling radars

DOE PAGES

McCaffrey, Katherine; Bianco, Laura; Wilczak, James M.

2017-07-20

Observations of turbulence dissipation rates in the planetary boundary layer are crucial for validation of parameterizations in numerical weather prediction models. However, because dissipation rates are difficult to obtain, they are infrequently measured through the depth of the boundary layer. For this reason, demonstrating the ability of commonly used wind profiling radars (WPRs) to estimate this quantity would be greatly beneficial. During the XPIA field campaign at the Boulder Atmospheric Observatory, two WPRs operated in an optimized configuration, using high spectral resolution for increased accuracy of Doppler spectral width, specifically chosen to estimate turbulence from a vertically pointing beam. Multiplemore » post-processing techniques, including different numbers of spectral averages and peak processing algorithms for calculating spectral moments, were evaluated to determine the most accurate procedures for estimating turbulence dissipation rates using the information contained in the Doppler spectral width, using sonic anemometers mounted on a 300 m tower for validation. Furthermore, the optimal settings were determined, producing a low bias, which was later corrected. Resulting estimations of turbulence dissipation rates correlated well ( R 2 = 0.54 and 0.41) with the sonic anemometers, and profiles up to 2 km from the 449 MHz WPR and 1 km from the 915 MHz WPR were observed.« less

Improved observations of turbulence dissipation rates from wind profiling radars

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

McCaffrey, Katherine; Bianco, Laura; Wilczak, James M.

Observations of turbulence dissipation rates in the planetary boundary layer are crucial for validation of parameterizations in numerical weather prediction models. However, because dissipation rates are difficult to obtain, they are infrequently measured through the depth of the boundary layer. For this reason, demonstrating the ability of commonly used wind profiling radars (WPRs) to estimate this quantity would be greatly beneficial. During the XPIA field campaign at the Boulder Atmospheric Observatory, two WPRs operated in an optimized configuration, using high spectral resolution for increased accuracy of Doppler spectral width, specifically chosen to estimate turbulence from a vertically pointing beam. Multiplemore » post-processing techniques, including different numbers of spectral averages and peak processing algorithms for calculating spectral moments, were evaluated to determine the most accurate procedures for estimating turbulence dissipation rates using the information contained in the Doppler spectral width, using sonic anemometers mounted on a 300 m tower for validation. Furthermore, the optimal settings were determined, producing a low bias, which was later corrected. Resulting estimations of turbulence dissipation rates correlated well ( R 2 = 0.54 and 0.41) with the sonic anemometers, and profiles up to 2 km from the 449 MHz WPR and 1 km from the 915 MHz WPR were observed.« less

Novel hyperspectral prediction method and apparatus

NASA Astrophysics Data System (ADS)

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

2009-05-01

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

Method using in vivo quantitative spectroscopy to guide design and optimization of low-cost, compact clinical imaging devices: emulation and evaluation of multispectral imaging systems

NASA Astrophysics Data System (ADS)

Saager, Rolf B.; Baldado, Melissa L.; Rowland, Rebecca A.; Kelly, Kristen M.; Durkin, Anthony J.

2018-04-01

With recent proliferation in compact and/or low-cost clinical multispectral imaging approaches and commercially available components, questions remain whether they adequately capture the requisite spectral content of their applications. We present a method to emulate the spectral range and resolution of a variety of multispectral imagers, based on in-vivo data acquired from spatial frequency domain spectroscopy (SFDS). This approach simulates spectral responses over 400 to 1100 nm. Comparing emulated data with full SFDS spectra of in-vivo tissue affords the opportunity to evaluate whether the sparse spectral content of these imagers can (1) account for all sources of optical contrast present (completeness) and (2) robustly separate and quantify sources of optical contrast (crosstalk). We validate the approach over a range of tissue-simulating phantoms, comparing the SFDS-based emulated spectra against measurements from an independently characterized multispectral imager. Emulated results match the imager across all phantoms (<3 % absorption, <1 % reduced scattering). In-vivo test cases (burn wounds and photoaging) illustrate how SFDS can be used to evaluate different multispectral imagers. This approach provides an in-vivo measurement method to evaluate the performance of multispectral imagers specific to their targeted clinical applications and can assist in the design and optimization of new spectral imaging devices.

Emergent spectral properties of river network topology: an optimal channel network approach.

PubMed

Abed-Elmdoust, Armaghan; Singh, Arvind; Yang, Zong-Liang

2017-09-13

Characterization of river drainage networks has been a subject of research for many years. However, most previous studies have been limited to quantities which are loosely connected to the topological properties of these networks. In this work, through a graph-theoretic formulation of drainage river networks, we investigate the eigenvalue spectra of their adjacency matrix. First, we introduce a graph theory model for river networks and explore the properties of the network through its adjacency matrix. Next, we show that the eigenvalue spectra of such complex networks follow distinct patterns and exhibit striking features including a spectral gap in which no eigenvalue exists as well as a finite number of zero eigenvalues. We show that such spectral features are closely related to the branching topology of the associated river networks. In this regard, we find an empirical relation for the spectral gap and nullity in terms of the energy dissipation exponent of the drainage networks. In addition, the eigenvalue distribution is found to follow a finite-width probability density function with certain skewness which is related to the drainage pattern. Our results are based on optimal channel network simulations and validated through examples obtained from physical experiments on landscape evolution. These results suggest the potential of the spectral graph techniques in characterizing and modeling river networks.

Determination of zinc oxide content of mineral medicine calamine using near-infrared spectroscopy based on MIV and BP-ANN algorithm

NASA Astrophysics Data System (ADS)

Zhang, Xiaodong; Chen, Long; Sun, Yangbo; Bai, Yu; Huang, Bisheng; Chen, Keli

2018-03-01

Near-infrared (NIR) spectroscopy has been widely used in the analysis fields of traditional Chinese medicine. It has the advantages of fast analysis, no damage to samples and no pollution. In this research, a fast quantitative model for zinc oxide (ZnO) content in mineral medicine calamine was explored based on NIR spectroscopy. NIR spectra of 57 batches of calamine samples were collected and the first derivative (FD) method was adopted for conducting spectral pretreatment. The content of ZnO in calamine sample was determined using ethylenediaminetetraacetic acid (EDTA) titration and taken as reference value of NIR spectroscopy. 57 batches of calamine samples were categorized into calibration and prediction set using the Kennard-Stone (K-S) algorithm. Firstly, in the calibration set, to calculate the correlation coefficient (r) between the absorbance value and the ZnO content of corresponding samples at each wave number. Next, according to the square correlation coefficient (r2) value to obtain the top 50 wave numbers to compose the characteristic spectral bands (4081.8-4096.3, 4188.9-4274.7, 4335.4, 4763.6,4794.4-4802.1, 4809.9, 4817.6-4875.4 cm- 1), which were used to establish the quantitative model of ZnO content using back propagation artificial neural network (BP-ANN) algorithm. Then, the 50 wave numbers were operated by the mean impact value (MIV) algorithm to choose wave numbers whose absolute value of MIV greater than or equal to 25, to obtain the optimal characteristic spectral bands (4875.4-4836.9, 4223.6-4080.9 cm- 1). And then, both internal cross and external validation were used to screen the number of hidden layer nodes of BP-ANN. Finally, the number 4 of hidden layer nodes was chosen as the best. At last, the BP-ANN model was found to enjoy a high accuracy and strong forecasting capacity for analyzing ZnO content in calamine samples ranging within 42.05-69.98%, with relative mean square error of cross validation (RMSECV) of 1.66% and coefficient of determination (R2) of 95.75% in internal cross and relative mean square error of prediction (RMSEP) of 1.98%, R2 of 97.94% and ratio of performance to deviation (RPD) of 6.11 in external validation.

Improving the Curie depth estimation through optimizing the spectral block dimensions of the aeromagnetic data in the Sabalan geothermal field

NASA Astrophysics Data System (ADS)

Akbar, Somaieh; Fathianpour, Nader

2016-12-01

The Curie point depth is of great importance in characterizing geothermal resources. In this study, the Curie iso-depth map was provided using the well-known method of dividing the aeromagnetic dataset into overlapping blocks and analyzing the power spectral density of each block separately. Determining the optimum block dimension is vital in improving the resolution and accuracy of estimating Curie point depth. To investigate the relation between the optimal block size and power spectral density, a forward magnetic modeling was implemented on an artificial prismatic body with specified characteristics. The top, centroid, and bottom depths of the body were estimated by the spectral analysis method for different block dimensions. The result showed that the optimal block size could be considered as the smallest possible block size whose corresponding power spectrum represents an absolute maximum in small wavenumbers. The Curie depth map of the Sabalan geothermal field and its surrounding areas, in the northwestern Iran, was produced using a grid of 37 blocks with different dimensions from 10 × 10 to 50 × 50 km2, which showed at least 50% overlapping with adjacent blocks. The Curie point depth was estimated in the range of 5 to 21 km. The promising areas with the Curie point depths less than 8.5 km are located around Mountain Sabalan encompassing more than 90% of known geothermal resources in the study area. Moreover, the Curie point depth estimated by the improved spectral analysis is in good agreement with the depth calculated from the thermal gradient data measured in one of the exploratory wells in the region.

Final Report: Large-Scale Optimization for Bayesian Inference in Complex Systems

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

Ghattas, Omar

2013-10-15

The SAGUARO (Scalable Algorithms for Groundwater Uncertainty Analysis and Robust Optimiza- tion) Project focuses on the development of scalable numerical algorithms for large-scale Bayesian inversion in complex systems that capitalize on advances in large-scale simulation-based optimiza- tion and inversion methods. Our research is directed in three complementary areas: efficient approximations of the Hessian operator, reductions in complexity of forward simulations via stochastic spectral approximations and model reduction, and employing large-scale optimization concepts to accelerate sampling. Our efforts are integrated in the context of a challenging testbed problem that considers subsurface reacting flow and transport. The MIT component of the SAGUAROmore » Project addresses the intractability of conventional sampling methods for large-scale statistical inverse problems by devising reduced-order models that are faithful to the full-order model over a wide range of parameter values; sampling then employs the reduced model rather than the full model, resulting in very large computational savings. Results indicate little effect on the computed posterior distribution. On the other hand, in the Texas-Georgia Tech component of the project, we retain the full-order model, but exploit inverse problem structure (adjoint-based gradients and partial Hessian information of the parameter-to- observation map) to implicitly extract lower dimensional information on the posterior distribution; this greatly speeds up sampling methods, so that fewer sampling points are needed. We can think of these two approaches as "reduce then sample" and "sample then reduce." In fact, these two approaches are complementary, and can be used in conjunction with each other. Moreover, they both exploit deterministic inverse problem structure, in the form of adjoint-based gradient and Hessian information of the underlying parameter-to-observation map, to achieve their speedups.« less

Extragalactic Peaked-spectrum Radio Sources at Low Frequencies

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

Callingham, J. R.; Gaensler, B. M.; Sadler, E. M.

We present a sample of 1483 sources that display spectral peaks between 72 MHz and 1.4 GHz, selected from the GaLactic and Extragalactic All-sky Murchison Widefield Array (GLEAM) survey. The GLEAM survey is the widest fractional bandwidth all-sky survey to date, ideal for identifying peaked-spectrum sources at low radio frequencies. Our peaked-spectrum sources are the low-frequency analogs of gigahertz-peaked spectrum (GPS) and compact-steep spectrum (CSS) sources, which have been hypothesized to be the precursors to massive radio galaxies. Our sample more than doubles the number of known peaked-spectrum candidates, and 95% of our sample have a newly characterized spectral peak.more » We highlight that some GPS sources peaking above 5 GHz have had multiple epochs of nuclear activity, and we demonstrate the possibility of identifying high-redshift ( z > 2) galaxies via steep optically thin spectral indices and low observed peak frequencies. The distribution of the optically thick spectral indices of our sample is consistent with past GPS/CSS samples but with a large dispersion, suggesting that the spectral peak is a product of an inhomogeneous environment that is individualistic. We find no dependence of observed peak frequency with redshift, consistent with the peaked-spectrum sample comprising both local CSS sources and high-redshift GPS sources. The 5 GHz luminosity distribution lacks the brightest GPS and CSS sources of previous samples, implying that a convolution of source evolution and redshift influences the type of peaked-spectrum sources identified below 1 GHz. Finally, we discuss sources with optically thick spectral indices that exceed the synchrotron self-absorption limit.« less

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.

Hyperspectral sensing of heavy metals in soil and vegetation: Feasibility and challenges

NASA Astrophysics Data System (ADS)

Wang, Fenghe; Gao, Jay; Zha, Yong

2018-02-01

Remote sensing of heavy metal contamination of soils has been widely studied. These studies concentrate heavily on the hyperspectral reflectance of typical metals in soils and in plants measured either in situ or in the laboratory. The most used wavebands lie within the visible-near infrared portion of the spectrum, especially the red edge. In comparison, mid- and far-infrared wavelengths are used far less frequently. Hyperspectral data are optimized to suppress noises and enhance the signal of the targeted metals through spectral derivatives and vegetation indexing. It is found that only subtle disparity exists in spectral responses for some metals at a sufficiently high content level. Not all metals have their own unique spectral response. Their detection has to rely on their co-variation with the spectrally responsive metals or organic matter in the soils. The closeness of the correlation dictates the accuracy of prediction. Without any theoretical grounding, this correlation is site-specific. Various analytical methods, including stepwise multi-linear regression, partial least squares regression, and neural networks have been used to model metal content level from the identified spectrally sensitive bands and/or their transformed indices. Both the model and the explanatory variables vary with the metal under detection and the area from which in situ samples are collected. Despite the amply demonstrated feasibility of estimating several metals by a large number of authors, only a few have succeeded in mapping the spatial distribution of metals from HyMAP, HJ-1A and Hyperion images to a satisfactory accuracy using complex algorithms and after taking environmental variables into account. The large number of reported failures testifies the difficulty in the detection of heavy metals in soils and plants, especially when their concentration level is low. The reasons or factors responsible for the success or failure have not been systematically analyzed, including the minimal spectral resolution required.

Selection of optimal multispectral imaging system parameters for small joint arthritis detection

NASA Astrophysics Data System (ADS)

Dolenec, Rok; Laistler, Elmar; Stergar, Jost; Milanic, Matija

2018-02-01

Early detection and treatment of arthritis is essential for a successful outcome of the treatment, but it has proven to be very challenging with existing diagnostic methods. Novel methods based on the optical imaging of the affected joints are becoming an attractive alternative. A non-contact multispectral imaging (MSI) system for imaging of small joints of human hands and feet is being developed. In this work, a numerical simulation of the MSI system is presented. The purpose of the simulation is to determine the optimal design parameters. Inflamed and unaffected human joint models were constructed with a realistic geometry and tissue distributions, based on a MRI scan of a human finger with a spatial resolution of 0.2 mm. The light transport simulation is based on a weighted-photon 3D Monte Carlo method utilizing CUDA GPU acceleration. An uniform illumination of the finger within the 400-1100 nm spectral range was simulated and the photons exiting the joint were recorded using different acceptance angles. From the obtained reflectance and transmittance images the spectral and spatial features most indicative of inflammation were identified. Optimal acceptance angle and spectral bands were determined. This study demonstrates that proper selection of MSI system parameters critically affects ability of a MSI system to discriminate the unaffected and inflamed joints. The presented system design optimization approach could be applied to other pathologies.

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.

Joint analyses by laser-induced breakdown spectroscopy (LIBS) and Raman spectroscopy at stand-off distances.

PubMed

Wiens, Roger C; Sharma, Shiv K; Thompson, Justin; Misra, Anupam; Lucey, Paul G

2005-08-01

Raman spectroscopy and laser-induced breakdown spectroscopy (LIBS) of solid samples have both been shown to be feasible with sample-to-instrument distances of many meters. The two techniques are very useful together, as the combination of elemental compositions from LIBS and molecular vibrational information from Raman spectroscopy strongly complement each other. Remote LIBS and Raman spectroscopy spectra were taken together on a number of mineral samples including sulfates, carbonates and silicates at a distance of 8.3 m. The complementary nature of these spectra is highlighted and discussed. A factor of approximately 20 difference in intensity was observed between the brightest Raman line of calcite, at optimal laser power, and the brighter Ca I LIBS emission line measured with 55 mJ/pulse laser power. LIBS and Raman spectroscopy have several obstacles to devising a single instrument capable of both techniques. These include the differing spectral ranges and required detection sensitivity. The current state of technology in these areas is discussed.

Study on nondestructive discrimination of genuine and counterfeit wild ginsengs using NIRS

NASA Astrophysics Data System (ADS)

Lu, Q.; Fan, Y.; Peng, Z.; Ding, H.; Gao, H.

2012-07-01

A new approach for the nondestructive discrimination between genuine wild ginsengs and the counterfeit ones by near infrared spectroscopy (NIRS) was developed. Both discriminant analysis and back propagation artificial neural network (BP-ANN) were applied to the model establishment for discrimination. Optimal modeling wavelengths were determined based on the anomalous spectral information of counterfeit samples. Through principal component analysis (PCA) of various wild ginseng samples, genuine and counterfeit, the cumulative percentages of variance of the principal components were obtained, serving as a reference for principal component (PC) factor determination. Discriminant analysis achieved an identification ratio of 88.46%. With sample' truth values as its outputs, a three-layer BP-ANN model was built, which yielded a higher discrimination accuracy of 100%. The overall results sufficiently demonstrate that NIRS combined with BP-ANN classification algorithm performs better on ginseng discrimination than discriminant analysis, and can be used as a rapid and nondestructive method for the detection of counterfeit wild ginsengs in food and pharmaceutical industry.

Application of hyperspectral imaging for characterization of intramuscular fat distribution in beef

USDA-ARS?s Scientific Manuscript database

In this study, a hyperspectral imaging system in the spectral region of 400–1000 nm was used for visualization and determination of intramuscular fat concentration in beef samples. Hyperspectral images were acquired for beef samples, and spectral information was then extracted from each single sampl...

Semi-automated scoring of triple-probe FISH in human sperm using confocal microscopy.

PubMed

Branch, Francesca; Nguyen, GiaLinh; Porter, Nicholas; Young, Heather A; Martenies, Sheena E; McCray, Nathan; Deloid, Glen; Popratiloff, Anastas; Perry, Melissa J

2017-09-01

Structural and numerical sperm chromosomal aberrations result from abnormal meiosis and are directly linked to infertility. Any live births that arise from aneuploid conceptuses can result in syndromes such as Kleinfelter, Turners, XYY and Edwards. Multi-probe fluorescence in situ hybridization (FISH) is commonly used to study sperm aneuploidy, however manual FISH scoring in sperm samples is labor-intensive and introduces errors. Automated scoring methods are continuously evolving. One challenging aspect for optimizing automated sperm FISH scoring has been the overlap in excitation and emission of the fluorescent probes used to enumerate the chromosomes of interest. Our objective was to demonstrate the feasibility of combining confocal microscopy and spectral imaging with high-throughput methods for accurately measuring sperm aneuploidy. Our approach used confocal microscopy to analyze numerical chromosomal abnormalities in human sperm using enhanced slide preparation and rigorous semi-automated scoring methods. FISH for chromosomes X, Y, and 18 was conducted to determine sex chromosome disomy in sperm nuclei. Application of online spectral linear unmixing was used for effective separation of four fluorochromes while decreasing data acquisition time. Semi-automated image processing, segmentation, classification, and scoring were performed on 10 slides using custom image processing and analysis software and results were compared with manual methods. No significant differences in disomy frequencies were seen between the semi automated and manual methods. Samples treated with pepsin were observed to have reduced background autofluorescence and more uniform distribution of cells. These results demonstrate that semi-automated methods using spectral imaging on a confocal platform are a feasible approach for analyzing numerical chromosomal aberrations in sperm, and are comparable to manual methods. © 2017 International Society for Advancement of Cytometry. © 2017 International Society for Advancement of Cytometry.

EXhype: A tool for mineral classification using hyperspectral data

NASA Astrophysics Data System (ADS)

Adep, Ramesh Nityanand; shetty, Amba; Ramesh, H.

2017-02-01

Various supervised classification algorithms have been developed to classify earth surface features using hyperspectral data. Each algorithm is modelled based on different human expertises. However, the performance of conventional algorithms is not satisfactory to map especially the minerals in view of their typical spectral responses. This study introduces a new expert system named 'EXhype (Expert system for hyperspectral data classification)' to map minerals. The system incorporates human expertise at several stages of it's implementation: (i) to deal with intra-class variation; (ii) to identify absorption features; (iii) to discriminate spectra by considering absorption features, non-absorption features and by full spectra comparison; and (iv) finally takes a decision based on learning and by emphasizing most important features. It is developed using a knowledge base consisting of an Optimal Spectral Library, Segmented Upper Hull method, Spectral Angle Mapper (SAM) and Artificial Neural Network. The performance of the EXhype is compared with a traditional, most commonly used SAM algorithm using Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data acquired over Cuprite, Nevada, USA. A virtual verification method is used to collect samples information for accuracy assessment. Further, a modified accuracy assessment method is used to get a real users accuracies in cases where only limited or desired classes are considered for classification. With the modified accuracy assessment method, SAM and EXhype yields an overall accuracy of 60.35% and 90.75% and the kappa coefficient of 0.51 and 0.89 respectively. It was also found that the virtual verification method allows to use most desired stratified random sampling method and eliminates all the difficulties associated with it. The experimental results show that EXhype is not only producing better accuracy compared to traditional SAM but, can also rightly classify the minerals. It is proficient in avoiding misclassification between target classes when applied on minerals.

Fast detection and visualization of minced lamb meat adulteration using NIR hyperspectral imaging and multivariate image analysis.

PubMed

Kamruzzaman, Mohammed; Sun, Da-Wen; ElMasry, Gamal; Allen, Paul

2013-01-15

Many studies have been carried out in developing non-destructive technologies for predicting meat adulteration, but there is still no endeavor for non-destructive detection and quantification of adulteration in minced lamb meat. The main goal of this study was to develop and optimize a rapid analytical technique based on near-infrared (NIR) hyperspectral imaging to detect the level of adulteration in minced lamb. Initial investigation was carried out using principal component analysis (PCA) to identify the most potential adulterate in minced lamb. Minced lamb meat samples were then adulterated with minced pork in the range 2-40% (w/w) at approximately 2% increments. Spectral data were used to develop a partial least squares regression (PLSR) model to predict the level of adulteration in minced lamb. Good prediction model was obtained using the whole spectral range (910-1700 nm) with a coefficient of determination (R(2)(cv)) of 0.99 and root-mean-square errors estimated by cross validation (RMSECV) of 1.37%. Four important wavelengths (940, 1067, 1144 and 1217 nm) were selected using weighted regression coefficients (Bw) and a multiple linear regression (MLR) model was then established using these important wavelengths to predict adulteration. The MLR model resulted in a coefficient of determination (R(2)(cv)) of 0.98 and RMSECV of 1.45%. The developed MLR model was then applied to each pixel in the image to obtain prediction maps to visualize the distribution of adulteration of the tested samples. The results demonstrated that the laborious and time-consuming tradition analytical techniques could be replaced by spectral data in order to provide rapid, low cost and non-destructive testing technique for adulterate detection in minced lamb meat. Copyright © 2012 Elsevier B.V. All rights reserved.

SRS modeling in high power CW fiber lasers for component optimization

NASA Astrophysics Data System (ADS)

Brochu, G.; Villeneuve, A.; Faucher, M.; Morin, M.; Trépanier, F.; Dionne, R.

2017-02-01

A CW kilowatt fiber laser numerical model has been developed taking into account intracavity stimulated Raman scattering (SRS). It uses the split-step Fourier method which is applied iteratively over several cavity round trips. The gain distribution is re-evaluated after each iteration with a standard CW model using an effective FBG reflectivity that quantifies the non-linear spectral leakage. This model explains why spectrally narrow output couplers produce more SRS than wider FBGs, as recently reported by other authors, and constitute a powerful tool to design optimized and innovative fiber components to push back the onset of SRS for a given fiber core diameter.

The SED Machine: A Robotic Spectrograph for Fast Transient Classification

NASA Astrophysics Data System (ADS)

Blagorodnova, Nadejda; Neill, James D.; Walters, Richard; Kulkarni, Shrinivas R.; Fremling, Christoffer; Ben-Ami, Sagi; Dekany, Richard G.; Fucik, Jason R.; Konidaris, Nick; Nash, Reston; Ngeow, Chow-Choong; Ofek, Eran O.; O’ Sullivan, Donal; Quimby, Robert; Ritter, Andreas; Vyhmeister, Karl E.

2018-03-01

Current time domain facilities are finding several hundreds of transient astronomical events a year. The discovery rate is expected to increase in the future as soon as new surveys such as the Zwicky Transient Facility (ZTF) and the Large Synoptic Sky Survey (LSST) come online. Presently, the rate at which transients are classified is approximately one order or magnitude lower than the discovery rate, leading to an increasing “follow-up drought”. Existing telescopes with moderate aperture can help address this deficit when equipped with spectrographs optimized for spectral classification. Here, we provide an overview of the design, operations and first results of the Spectral Energy Distribution Machine (SEDM), operating on the Palomar 60-inch telescope (P60). The instrument is optimized for classification and high observing efficiency. It combines a low-resolution (R ∼ 100) integral field unit (IFU) spectrograph with “Rainbow Camera” (RC), a multi-band field acquisition camera which also serves as multi-band (ugri) photometer. The SEDM was commissioned during the operation of the intermediate Palomar Transient Factory (iPTF) and has already lived up to its promise. The success of the SEDM demonstrates the value of spectrographs optimized for spectral classification.

How to Collect National Institute of Standards and Technology (NIST) Traceable Fluorescence Excitation and Emission Spectra.

PubMed

Gilmore, Adam Matthew

2014-01-01

Contemporary spectrofluorimeters comprise exciting light sources, excitation and emission monochromators, and detectors that without correction yield data not conforming to an ideal spectral response. The correction of the spectral properties of the exciting and emission light paths first requires calibration of the wavelength and spectral accuracy. The exciting beam path can be corrected up to the sample position using a spectrally corrected reference detection system. The corrected reference response accounts for both the spectral intensity and drift of the exciting light source relative to emission and/or transmission detector responses. The emission detection path must also be corrected for the combined spectral bias of the sample compartment optics, emission monochromator, and detector. There are several crucial issues associated with both excitation and emission correction including the requirement to account for spectral band-pass and resolution, optical band-pass or neutral density filters, and the position and direction of polarizing elements in the light paths. In addition, secondary correction factors are described including (1) subtraction of the solvent's fluorescence background, (2) removal of Rayleigh and Raman scattering lines, as well as (3) correcting for sample concentration-dependent inner-filter effects. The importance of the National Institute of Standards and Technology (NIST) traceable calibration and correction protocols is explained in light of valid intra- and interlaboratory studies and effective spectral qualitative and quantitative analyses including multivariate spectral modeling.

Numerical model of tapered fiber Bragg gratings for comprehensive analysis and optimization of their sensing and strain-induced tunable dispersion properties.

PubMed

Osuch, Tomasz; Markowski, Konrad; Jędrzejewski, Kazimierz

2015-06-10

A versatile numerical model for spectral transmission/reflection, group delay characteristic analysis, and design of tapered fiber Bragg gratings (TFBGs) is presented. This approach ensures flexibility with defining both distribution of refractive index change of the gratings (including apodization) and shape of the taper profile. Additionally, sensing and tunable dispersion properties of the TFBGs were fully examined, considering strain-induced effects. The presented numerical approach, together with Pareto optimization, were also used to design the best tanh apodization profiles of the TFBG in terms of maximizing its spectral width with simultaneous minimization of the group delay oscillations. Experimental verification of the model confirms its correctness. The combination of model versatility and possibility to define the other objective functions of Pareto optimization creates a universal tool for TFBG analysis and design.

Augmented classical least squares multivariate spectral analysis

DOEpatents

Haaland, David M.; Melgaard, David K.

2004-02-03

A method of multivariate spectral analysis, termed augmented classical least squares (ACLS), provides an improved CLS calibration model when unmodeled sources of spectral variation are contained in a calibration sample set. The ACLS methods use information derived from component or spectral residuals during the CLS calibration to provide an improved calibration-augmented CLS model. The ACLS methods are based on CLS so that they retain the qualitative benefits of CLS, yet they have the flexibility of PLS and other hybrid techniques in that they can define a prediction model even with unmodeled sources of spectral variation that are not explicitly included in the calibration model. The unmodeled sources of spectral variation may be unknown constituents, constituents with unknown concentrations, nonlinear responses, non-uniform and correlated errors, or other sources of spectral variation that are present in the calibration sample spectra. Also, since the various ACLS methods are based on CLS, they can incorporate the new prediction-augmented CLS (PACLS) method of updating the prediction model for new sources of spectral variation contained in the prediction sample set without having to return to the calibration process. The ACLS methods can also be applied to alternating least squares models. The ACLS methods can be applied to all types of multivariate data.

Augmented Classical Least Squares Multivariate Spectral Analysis

DOEpatents

Haaland, David M.; Melgaard, David K.

2005-07-26

A method of multivariate spectral analysis, termed augmented classical least squares (ACLS), provides an improved CLS calibration model when unmodeled sources of spectral variation are contained in a calibration sample set. The ACLS methods use information derived from component or spectral residuals during the CLS calibration to provide an improved calibration-augmented CLS model. The ACLS methods are based on CLS so that they retain the qualitative benefits of CLS, yet they have the flexibility of PLS and other hybrid techniques in that they can define a prediction model even with unmodeled sources of spectral variation that are not explicitly included in the calibration model. The unmodeled sources of spectral variation may be unknown constituents, constituents with unknown concentrations, nonlinear responses, non-uniform and correlated errors, or other sources of spectral variation that are present in the calibration sample spectra. Also, since the various ACLS methods are based on CLS, they can incorporate the new prediction-augmented CLS (PACLS) method of updating the prediction model for new sources of spectral variation contained in the prediction sample set without having to return to the calibration process. The ACLS methods can also be applied to alternating least squares models. The ACLS methods can be applied to all types of multivariate data.

Augmented Classical Least Squares Multivariate Spectral Analysis

DOEpatents

Haaland, David M.; Melgaard, David K.

2005-01-11

A method of multivariate spectral analysis, termed augmented classical least squares (ACLS), provides an improved CLS calibration model when unmodeled sources of spectral variation are contained in a calibration sample set. The ACLS methods use information derived from component or spectral residuals during the CLS calibration to provide an improved calibration-augmented CLS model. The ACLS methods are based on CLS so that they retain the qualitative benefits of CLS, yet they have the flexibility of PLS and other hybrid techniques in that they can define a prediction model even with unmodeled sources of spectral variation that are not explicitly included in the calibration model. The unmodeled sources of spectral variation may be unknown constituents, constituents with unknown concentrations, nonlinear responses, non-uniform and correlated errors, or other sources of spectral variation that are present in the calibration sample spectra. Also, since the various ACLS methods are based on CLS, they can incorporate the new prediction-augmented CLS (PACLS) method of updating the prediction model for new sources of spectral variation contained in the prediction sample set without having to return to the calibration process. The ACLS methods can also be applied to alternating least squares models. The ACLS methods can be applied to all types of multivariate data.

Spectral sensitivity characteristics simulation for silicon p-i-n photodiode

NASA Astrophysics Data System (ADS)

Urchuk, S. U.; Legotin, S. A.; Osipov, U. V.; Elnikov, D. S.; Didenko, S. I.; Astahov, V. P.; Rabinovich, O. I.; Yaromskiy, V. P.; Kuzmina, K. A.

2015-11-01

In this paper the simulation results of the spectral sensitivity characteristics of silicon p-i-n-photodiodes are presented. The analysis of the characteristics of the semiconductor material (the doping level, lifetime, surface recombination velocity), the construction and operation modes on the characteristics of photosensitive structures in order to optimize them was carried out.

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.

Micromega/IR: Design and status of a near-infrared spectral microscope for in situ analysis of Mars samples

NASA Astrophysics Data System (ADS)

Leroi, Vaitua; Bibring, Jean-Pierre; Berthe, Michel

2009-07-01

MicrOmega is an ultra miniaturized spectral microscope for in situ analysis of samples. It is composed of 2 microscopes; one with a spatial sampling less or equal to 4 μm, working in 4 colors in the visible range: MicrOmega/VIS, and a NIR hyperspectral microscope working in the spectral range 0.9-4 μm with a spatial sampling of 20 μm per pixel: MicrOmega/IR (described in this paper). MicrOmega/IR illuminates and images samples a few mm in size and acquires the NIR spectrum of each resolved pixel in up to 320 contiguous spectral channels. The goal of this instrument is to analyze in situ the composition of collected samples at almost their grain size scale, in a non-destructive way. With the chosen spectral range and resolution, a wide variety of constituents can be identified: minerals, such as pyroxene and olivine, ferric oxides, hydrated phyllosilicates, sulfates and carbonates and 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 (planet, satellite and small body). In particular, the capability to identify hydrated grains and to characterize their adjacent phases has a huge potential in the search for possible bio-relics.

Quantifying Foliar Pigment Concentrations of Temperate Forest Species Using Digital Photography and Hyperspectral Reflectance Indices

NASA Astrophysics Data System (ADS)

Gagnon, M. T.; Rock, B. N.; Jahnke, L. S.; Lee, T. D.

2008-12-01

Determination of leaf chlorophyll content is a common and important procedure for plant scientists. There are many multispectral techniques for non destructive in-vivo, estimation of chlorophyll in foliage. Although much has been done to explore the estimation of foliar pigments using remote sensing, very little work has been done exploring the potential that basic, affordable, digital cameras may have for such analysis. This study utilizes a combination of digital photography, hyperspectral laboratory remote sensing, and chlorophyll extractions to determine if digital photographs can be used to accurately predict foliar chlorophyll concentrations as well to compare this digital approach with several common spectral indices used for estimating foliar chlorophyll content. Foliar materials for this study come from three sources. A large collection of samples were collected (60) from 9 common temperate forest species in July and late September over a 1 kilometer area at the Bartlett Experimental Forest in northern New Hampshire. Secondly, 15 trees were selected in a forested setting near the University of New Hampshire for more intensive phenological analysis. These samples consist of 5 white pine (Pinus strobus), 5 black oak (Quercus velutina) and 5 sugar maple (Acer saccharum). Finally, dozens of samples of white pine utilized in Forest Watch, a successful K-12 science outreach which assesses the impact of tropospheric ozone on forest health in New England, were also analyzed for this study. For all samples in this study, chlorophyll extractions were conducted to determine chlorophyll a, chlorophyll b, and total chlorophyll concentrations. Laboratory spectral analysis was performed using a GER 2600 Spectroradiometer to determine hyperspectral estimates of chlorophyll content using a Red Edge Inflection Point (REIP) approach, as well as a Transformed Chlorophyll Absorption Reflectance Index/Optimized Soil Adjusted Vegetation Index (TCARI/OSAVI) approach. These measures of chlorophyll estimation were utilized to determine whether red, green and blue spectral data from digital images taken with a Kodak C713 model camera could be used to estimate foliar chlorophyll concentrations in forest foliage. Preliminary results of this study will be presented.

Spectral CT metal artifact reduction with an optimization-based reconstruction algorithm

NASA Astrophysics Data System (ADS)

Gilat Schmidt, Taly; Barber, Rina F.; Sidky, Emil Y.

2017-03-01

Metal objects cause artifacts in computed tomography (CT) images. This work investigated the feasibility of a spectral CT method to reduce metal artifacts. Spectral CT acquisition combined with optimization-based reconstruction is proposed to reduce artifacts by modeling the physical effects that cause metal artifacts and by providing the flexibility to selectively remove corrupted spectral measurements in the spectral-sinogram space. The proposed Constrained `One-Step' Spectral CT Image Reconstruction (cOSSCIR) algorithm directly estimates the basis material maps while enforcing convex constraints. The incorporation of constraints on the reconstructed basis material maps is expected to mitigate undersampling effects that occur when corrupted data is excluded from reconstruction. The feasibility of the cOSSCIR algorithm to reduce metal artifacts was investigated through simulations of a pelvis phantom. The cOSSCIR algorithm was investigated with and without the use of a third basis material representing metal. The effects of excluding data corrupted by metal were also investigated. The results demonstrated that the proposed cOSSCIR algorithm reduced metal artifacts and improved CT number accuracy. For example, CT number error in a bright shading artifact region was reduced from 403 HU in the reference filtered backprojection reconstruction to 33 HU using the proposed algorithm in simulation. In the dark shading regions, the error was reduced from 1141 HU to 25 HU. Of the investigated approaches, decomposing the data into three basis material maps and excluding the corrupted data demonstrated the greatest reduction in metal artifacts.

Optimized laser-induced breakdown spectroscopy for determination of xenobiotic silver in monosodium glutamate and its verification using ICP-AES.

PubMed

Rehan, I; Gondal, M A; Rehan, K

2018-04-20

Laser-induced breakdown spectroscopy (LIBS) was applied as a potential tool for the determination of xenobiotic metal in monosodium glutamate (MSG). In order to achieve a high-sensitivity LIBS system required to determine trace amounts of metallic silver in MSG and to attain the best detection limit, the parameters used in our experiment (impact of focusing laser energy on the intensity of LIBS emission signals, the influence of focusing lens distance on the intensity of LIBS signals, and time responses of the plasma emissions) were optimized. The spectra of MSG were obtained in air using a suitable detector with an optical resolution of 0.06 nm, covering a spectral region from 220 to 720 nm. Along with the detection of xenobiotic silver, other elements such as Ca, Mg, S, and Na were also detected in MSG. To determine the concentration of xenobiotic silver in MSG, the calibration curve was plotted by preparing standard samples having different silver abundances in an MSG matrix. The LIBS results of each sample were cross-verified by analyzing with a standard analytical technique such as inductively coupled plasma-atomic emission spectroscopy (ICP-AES). Both (LIBS and ICP-AES) results were in mutual agreement. The limit of detection of the LIBS setup was found to be 0.57 ppm for silver present in MSG samples.

Blocking reduction of Landsat Thematic Mapper JPEG browse images using optimal PSNR estimated spectra adaptive postfiltering

NASA Technical Reports Server (NTRS)

Linares, Irving; Mersereau, Russell M.; Smith, Mark J. T.

1994-01-01

Two representative sample images of Band 4 of the Landsat Thematic Mapper are compressed with the JPEG algorithm at 8:1, 16:1 and 24:1 Compression Ratios for experimental browsing purposes. We then apply the Optimal PSNR Estimated Spectra Adaptive Postfiltering (ESAP) algorithm to reduce the DCT blocking distortion. ESAP reduces the blocking distortion while preserving most of the image's edge information by adaptively postfiltering the decoded image using the block's spectral information already obtainable from each block's DCT coefficients. The algorithm iteratively applied a one dimensional log-sigmoid weighting function to the separable interpolated local block estimated spectra of the decoded image until it converges to the optimal PSNR with respect to the original using a 2-D steepest ascent search. Convergence is obtained in a few iterations for integer parameters. The optimal logsig parameters are transmitted to the decoder as a negligible byte of overhead data. A unique maxima is guaranteed due to the 2-D asymptotic exponential overshoot shape of the surface generated by the algorithm. ESAP is based on a DFT analysis of the DCT basis functions. It is implemented with pixel-by-pixel spatially adaptive separable FIR postfilters. PSNR objective improvements between 0.4 to 0.8 dB are shown together with their corresponding optimal PSNR adaptive postfiltered images.

Research on marine and freshwater fish identification model based on hyper-spectral imaging technology

NASA Astrophysics Data System (ADS)

Fu, Yan; Guo, Pei-yuan; Xiang, Ling-zi; Bao, Man; Chen, Xing-hai

2013-08-01

With the gradually mature of hyper spectral image technology, the application of the meat nondestructive detection and recognition has become one of the current research focuses. This paper for the study of marine and freshwater fish by the pre-processing and feature extraction of the collected spectral curve data, combined with BP network structure and LVQ network structure, a predictive model of hyper spectral image data of marine and freshwater fish has been initially established and finally realized the qualitative analysis and identification of marine and freshwater fish quality. The results of this study show that hyper spectral imaging technology combined with the BP and LVQ Artificial Neural Network Model can be used for the identification of marine and freshwater fish detection. Hyper-spectral data acquisition can be carried out without any pretreatment of the samples, thus hyper-spectral imaging technique is the lossless, high- accuracy and rapid detection method for quality of fish. In this study, only 30 samples are used for the exploratory qualitative identification of research, although the ideal study results are achieved, we will further increase the sample capacity to take the analysis of quantitative identification and verify the feasibility of this theory.

Using an optimal CC-PLSR-RBFNN model and NIR spectroscopy for the starch content determination in corn

NASA Astrophysics Data System (ADS)

Jiang, Hao; Lu, Jiangang

2018-05-01

Corn starch is an important material which has been traditionally used in the fields of food and chemical industry. In order to enhance the rapidness and reliability of the determination for starch content in corn, a methodology is proposed in this work, using an optimal CC-PLSR-RBFNN calibration model and near-infrared (NIR) spectroscopy. The proposed model was developed based on the optimal selection of crucial parameters and the combination of correlation coefficient method (CC), partial least squares regression (PLSR) and radial basis function neural network (RBFNN). To test the performance of the model, a standard NIR spectroscopy data set was introduced, containing spectral information and chemical reference measurements of 80 corn samples. For comparison, several other models based on the identical data set were also briefly discussed. In this process, the root mean square error of prediction (RMSEP) and coefficient of determination (Rp2) in the prediction set were used to make evaluations. As a result, the proposed model presented the best predictive performance with the smallest RMSEP (0.0497%) and the highest Rp2 (0.9968). Therefore, the proposed method combining NIR spectroscopy with the optimal CC-PLSR-RBFNN model can be helpful to determine starch content in corn.

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

PubMed

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

2007-11-01

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

A rapid quantification method for the screening indicator for β-thalassemia with near-infrared spectroscopy

NASA Astrophysics Data System (ADS)

Chen, Jiemei; Peng, Lijun; Han, Yun; Yao, Lijun; Zhang, Jing; Pan, Tao

2018-03-01

Near-infrared (NIR) spectroscopy combined with chemometrics was applied to rapidly analyse haemoglobin A2 (HbA2) for β-thalassemia screening in human haemolysate samples. The relative content indicator HbA2 was indirectly quantified by simultaneous analysis of two absolute content indicators (Hb and Hb • HbA2). According to the comprehensive prediction effect of the multiple partitioning of calibration and prediction sets, the parameters were optimized to achieve modelling stability, and the preferred models were validated using the samples not involved in modelling. Savitzky-Golay smoothing was firstly used for the spectral pretreatment. The absorbance optimization partial least squares (AO-PLS) was used to eliminate high-absorption wave-bands appropriately. The equidistant combination PLS (EC-PLS) was further used to optimize wavelength models. The selected optimal models were I = 856 nm, N = 16, G = 1 and F = 6 for Hb and I = 988 nm, N = 12, G = 2 and F = 5 for Hb • HbA2. Through independent validation, the root-mean-square errors and correlation coefficients for prediction (RMSEP, RP) were 3.50 g L- 1 and 0.977 for Hb and 0.38 g L- 1 and 0.917 for Hb • HbA2, respectively. The predicted values of relative percentage HbA2 were further calculated, and the calculated RMSEP and RP were 0.31% and 0.965, respectively. The sensitivity and specificity for β-thalassemia both reached 100%. Therefore, the prediction of HbA2 achieved high accuracy for distinguishing β-thalassemia. The local optimal models for single parameter and the optimal equivalent model sets were proposed, providing more models to match possible constraints in practical applications. The NIR analysis method for the screening indicator of β-thalassemia was successfully established. The proposed method was rapid, simple and promising for thalassemia screening in a large population.

Optical diffuse reflectance accessory for measurements of skin tissue by near-infrared spectroscopy

NASA Astrophysics Data System (ADS)

Marbach, R.; Heise, H. M.

1995-02-01

An optimized accessory for measuring the diffuse reflectance spectra of human skin tissue in the near-infrared spectral range is presented. The device includes an on-axis ellipsoidal collecting mirror with efficient illumination optics for small sampling areas of bulky body specimens. The optical design is supported by the results of a Monte Carlo simulation study of the reflectance characteristics of skin tissue. Because the results evolved from efforts to measure blood glucose noninvasively, the main emphasis is placed on the long-wavelength near-infrared range where sufficient penetration depth for radiation into tissue is still available. The accessory is applied for in vivo diffuse reflectance measurements.

On-line identification of 3,4-methylenedioxymethamphetamine in human urine by non-aqueous capillary electrophoresis-fluorescence spectroscopy at 77 K.

PubMed

Chung, Y L; Liu, J T; Lin, C H

2001-08-15

The analytical profiles for 3,4-methylenedioxymethamphetamine (3,4-MDMA) and related amphetamines in urine samples are described for non-aqueous capillary electrophoresis-fluorescence spectroscopy. 3,4-MDMA was detected and identified on-line, using a cryogenic molecular fluorescence technique at 77 K. Under optimized conditions, baseline separation of the selected compounds was achieved in less than 12 min. Precision was evaluated by measuring the repeatability and intermediate precision of the migration times and corrected peak areas. The non-aqueous CE separation conditions and the spectral characteristics of 3,4-MDMA with respect to solvent and temperature effects are also discussed.

Effective hard x-ray spectrum of a tabletop Mather-type plasma focus optimized for flash radiography of metallic objects

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

Raspa, V.; Moreno, C.; Sigaut, L.

The effective spectrum of the hard x-ray output of a Mather-type tabletop plasma focus device was determined from attenuation data on metallic samples using commercial radiographic film coupled to a Gd{sub 2}O{sub 2}S:Tb phosphor intensifier screen. It was found that the radiation has relevant spectral components in the 40-150 keV range, with a single maximum around 60-80 keV. The radiation output allows for 50 ns resolution, good contrast, and introspective imaging of metallic objects even through metallic walls. A numerical estimation of the induced voltage on the focus during the compressional stage is briefly discussed.

Measuring the Redshift Dependence of The Cosmic Microwave Background Monopole Temperature With Planck Data

NASA Technical Reports Server (NTRS)

De Martino, I.; Atrio-Barandela, F.; Da Silva, A.; Ebling, H.; Kashlinsky, A.; Kocevski, D.; Martins, C. J. A. P.

2012-01-01

We study the capability of Planck data to constrain deviations of the cosmic microwave background (CMB) blackbody temperature from adiabatic evolution using the thermal Sunyaev-Zeldovich anisotropy induced by clusters of galaxies. We consider two types of data sets depending on how the cosmological signal is removed: using a CMB template or using the 217 GHz map. We apply two different statistical estimators, based on the ratio of temperature anisotropies at two different frequencies and on a fit to the spectral variation of the cluster signal with frequency. The ratio method is biased if CMB residuals with amplitude approximately 1 microK or larger are present in the data, while residuals are not so critical for the fit method. To test for systematics, we construct a template from clusters drawn from a hydro-simulation included in the pre-launch Planck Sky Model. We demonstrate that, using a proprietary catalog of X-ray-selected clusters with measured redshifts, electron densities, and X-ray temperatures, we can constrain deviations of adiabatic evolution, measured by the parameter a in the redshift scaling T (z) = T0(1 + z)(sup 1-alpha), with an accuracy of sigma(sub alpha) = 0.011 in the most optimal case and with sigma alpha = 0.018 for a less optimal case. These results represent a factor of 2-3 improvement over similar measurements carried out using quasar spectral lines and a factor 6-20 with respect to earlier results using smaller cluster samples.

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

Use of polarized radiation for increasing the sensitivity of multielement x-ray fluorescence analysis

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

Ter-Saakov, A.A.; Glebov, M.V.

1985-10-01

An experimental x-ray fluorescence analysis facility has been developed using polarized radiation. A modernized small-sized REIS-I emitter is used as the x-ray genertor. Its characteristics are: a straight-through drift tube with a copper, molybdenum, or silver anode; and a controlled working voltage from 0 to 45 kV. The thickness of the inlet beryllium window is 100 um. Experiments were carried out on the facility on the optimization of fluorescence excitation conditions of biological samples. The investigations conducted of the dosimetric and spectral characteristics of the BS-1, BS-3, and BKh-7 x-ray tubes with copper, silver, and molybdenum anodes have shown thatmore » for the analysis in samples of biogenic elements, it is most efficient to use the BKh-7 and BS-1 tubes with a copper anode.« less

Targeted Modification of Neutron Energy Spectra for National Security Applications

NASA Astrophysics Data System (ADS)

Bevins, James Edward

At its core, research represents an attempt to break from the "this is the way we have always done it" paradigm. This idea is evidenced from the start in this research effort by the problem formulation to develop a new way to generate synthetic debris that mimics the samples that would be collected for forensics purposes following a nuclear weapon attack on the U.S. or its allies. The philosophy is also demonstrated by the design methodology used to solve the synthetic debris problem, using methods not commonly applied to nuclear engineering problems. Through this research, the bounds of what is deemed possible in neutron spectral shaping are moved ever so slightly. A capability for the production of synthetic debris and fission products was developed for the National Ignition Facility (NIF). Synthetic debris has historically been made in a limited fashion using sample doping techniques since the cessation of nuclear weapons testing, but a more robust alternative approach using neutron spectral shaping was proposed and developed by the University of California-Berkeley and Lawrence Livermore National Laboratory (LLNL). Using NIF as a starting source spectrum, the energy tuning assembly (ETA) developed in this work can irradiate samples with a combined thermonuclear and prompt fission neutron spectrum (TN+PFNS). When used with fissile foils, this irradiation will produce a synthetic fission product distribution that is realistic across all mass chains. To design the ETA, traditional parametric point design approaches were discarded in favor of formal optimization techniques. Finding a lack of suitable algorithms in the literature, a metaheuristic-based optimization algorithm, Gnowee, was developed for rapid convergence to nearly globally optimum solutions for complex, constrained engineering problems with mixed-integer and combinatorial design vectors and high-cost, noisy, discontinuous, black box objective function evaluations. Comparisons between Gnowee and several well-established metaheuristic algorithms are made for a set of continuous, mixed-integer, and combinatorial benchmarks. These results demonstrated Gnoweee to have superior flexibility and convergence characteristics over a wide range of design spaces. The Gnowee algorithm was implemented in Coeus, a new piece of software, to perform optimization of design problems requiring radiation transport for the evaluation of their objective functions. Currently, Coeus solves ETA optimization problems using hybrid radiation transport (ADVANTG and MCNP) to assess design permutations developed by Gnowee. Future enhancements of Coeus will look to expand the geometries and objective functions considered to those beyond ETA design. Coeus was used to generate an ETA design for the TN+PFNS application on NIF. The design achieved a reasonable match with the objective TN+PFNS and associated fission product distributions within the size and weight constraints imposed by the NIF facility. The ETA design was built by American Elements, and initial validation tests were conducted at the Lawrence Berkeley National Laboratory's 88-Inch Cyclotron. These experiments used foil activation and pulse height spectroscopy to measure the ETA-modified spectrum. Additionally, pulse height spectroscopy measurements were taken as the ETA was built-up component-by-component to measure the impact of nuclear data on the ability to model the ETA performance. Some initial analysis of these results is included here. Finally, an integral validation experiment on NIF was proposed using the Coeus generated ETA design. A scoping study conducted by LLNL determined the proposed experiment and ETA design are within NIF facility limitations and current radio-chemistry capabilities. The study found that the proposed ETA experiment was "low risk," has "no show stoppers," and has a "reasonable cost." All that is needed is a sponsor to close the last funding gap and bring the experiment to fruition. This research broke with the current sample doping approach and applied neutron spectral shaping to design an ETA that can create realistic synthetic fission and activation products and improve technical nuclear forensics outcomes. However, the ETA presented in this research represents more than a stand alone point design with a limited scope and application. It is proof of a concept and the product of a unique capability that has a wide range of potential applications. This research demonstrates that the concept of neutron spectral shaping can be used to engineer complex neutron spectra within the confines of physics. There are many possible applications that could benefit from the ability to generate custom energy neutron spectra that fall outside of current sources and methods. The ETA is the product of a general-purpose optimization algorithm, Gnowee, and design framework, Coeus, which enables the use of Gnowee for complex nuclear design problems. Through Gnowee and Coeus, new ETA neutronics designs can be generated in days, not months or years, with a drastic reduction in the research effort required to do so. (Abstract shortened by ProQuest.).

Early pest detection in soy plantations from hyperspectral measurements: a case study for caterpillar detection

NASA Astrophysics Data System (ADS)

Tailanián, Matías; Castiglioni, Enrique; Musé, Pablo; Fernández Flores, Germán.; Lema, Gabriel; Mastrángelo, Pedro; Almansa, Mónica; Fernández Liñares, Ignacio; Fernández Liñares, Germán.

2015-10-01

Soybean producers suffer from caterpillar damage in many areas of the world. Estimated average economic losses are annually 500 million USD in Brazil, Argentina, Paraguay and Uruguay. Designing efficient pest control management using selective and targeted pesticide applications is extremely important both from economic and environmental perspectives. With that in mind, we conducted a research program during the 2013-2014 and 2014-2015 planting seasons in a 4,000 ha soybean farm, seeking to achieve early pest detection. Nowadays pest presence is evaluated using manual, labor-intensive counting methods based on sampling strategies which are time consuming and imprecise. The experiment was conducted as follows. Using manual counting methods as ground-truth, a spectrometer capturing reflectance from 400 to 1100 nm was used to measure the reflectance of soy plants. A first conclusion, resulting from measuring the spectral response at leaves level, showed that stress was a property of plants since different leaves with different levels of damage yielded the same spectral response. Then, to assess the applicability of unsupervised classification of plants as healthy, biotic-stressed or abiotic-stressed, feature extraction and selection from leaves spectral signatures, combined with a Supported Vector Machine classifier was designed. Optimization of SVM parameters using grid search with cross-validation, along with classification evaluation by ten-folds cross-validation showed a correct classification rate of 95%, consistently on both seasons. Controlled experiments using cages with different numbers of caterpillars--including caterpillar-free plants--were also conducted to evaluate consistency in trends of the spectral response as well as the extracted features.

Optimization of lamp spectrum for vegetable growth

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

Prikupets, L.B.; Tikhomirov, A.A.

1994-12-31

Commmercial light sources were evaluated as to the optimum conditions for the production of tomatoes and cucumbers. Data is presented which corresponds to the maximum productivity and optimal spectral ratios. It is suggested that the commercial light sources evaluated were not efficient for the growing of the vegetables.

Spectral embedding finds meaningful (relevant) structure in image and microarray data

PubMed Central

Higgs, Brandon W; Weller, Jennifer; Solka, Jeffrey L

2006-01-01

Background Accurate methods for extraction of meaningful patterns in high dimensional data have become increasingly important with the recent generation of data types containing measurements across thousands of variables. Principal components analysis (PCA) is a linear dimensionality reduction (DR) method that is unsupervised in that it relies only on the data; projections are calculated in Euclidean or a similar linear space and do not use tuning parameters for optimizing the fit to the data. However, relationships within sets of nonlinear data types, such as biological networks or images, are frequently mis-rendered into a low dimensional space by linear methods. Nonlinear methods, in contrast, attempt to model important aspects of the underlying data structure, often requiring parameter(s) fitting to the data type of interest. In many cases, the optimal parameter values vary when different classification algorithms are applied on the same rendered subspace, making the results of such methods highly dependent upon the type of classifier implemented. Results We present the results of applying the spectral method of Lafon, a nonlinear DR method based on the weighted graph Laplacian, that minimizes the requirements for such parameter optimization for two biological data types. We demonstrate that it is successful in determining implicit ordering of brain slice image data and in classifying separate species in microarray data, as compared to two conventional linear methods and three nonlinear methods (one of which is an alternative spectral method). This spectral implementation is shown to provide more meaningful information, by preserving important relationships, than the methods of DR presented for comparison. Tuning parameter fitting is simple and is a general, rather than data type or experiment specific approach, for the two datasets analyzed here. Tuning parameter optimization is minimized in the DR step to each subsequent classification method, enabling the possibility of valid cross-experiment comparisons. Conclusion Results from the spectral method presented here exhibit the desirable properties of preserving meaningful nonlinear relationships in lower dimensional space and requiring minimal parameter fitting, providing a useful algorithm for purposes of visualization and classification across diverse datasets, a common challenge in systems biology. PMID:16483359

Stability-Constrained Aerodynamic Shape Optimization with Applications to Flying Wings

NASA Astrophysics Data System (ADS)

Mader, Charles Alexander

A set of techniques is developed that allows the incorporation of flight dynamics metrics as an additional discipline in a high-fidelity aerodynamic optimization. Specifically, techniques for including static stability constraints and handling qualities constraints in a high-fidelity aerodynamic optimization are demonstrated. These constraints are developed from stability derivative information calculated using high-fidelity computational fluid dynamics (CFD). Two techniques are explored for computing the stability derivatives from CFD. One technique uses an automatic differentiation adjoint technique (ADjoint) to efficiently and accurately compute a full set of static and dynamic stability derivatives from a single steady solution. The other technique uses a linear regression method to compute the stability derivatives from a quasi-unsteady time-spectral CFD solution, allowing for the computation of static, dynamic and transient stability derivatives. Based on the characteristics of the two methods, the time-spectral technique is selected for further development, incorporated into an optimization framework, and used to conduct stability-constrained aerodynamic optimization. This stability-constrained optimization framework is then used to conduct an optimization study of a flying wing configuration. This study shows that stability constraints have a significant impact on the optimal design of flying wings and that, while static stability constraints can often be satisfied by modifying the airfoil profiles of the wing, dynamic stability constraints can require a significant change in the planform of the aircraft in order for the constraints to be satisfied.

Determination of copper and mercury in phosphate fertilizers employing direct solid sampling analysis and high resolution continuum source graphite furnace atomic absorption spectrometry

NASA Astrophysics Data System (ADS)

de Oliveira Souza, Sidnei; François, Luciane Luiza; Borges, Aline Rocha; Vale, Maria Goreti Rodrigues; Araujo, Rennan Geovanny Oliveira

2015-12-01

The present study proposes the determination of copper and mercury in phosphate fertilizers by direct solid sampling analysis (SS) employing high resolution continuum source graphite furnace atomic absorption spectrometry (HR-CS GF AAS). For Cu determination, two analytical lines were used: 327.3960 nm and 249.2146 nm. Hg determination was carried out on the line 253.6521 nm and 100 μg KMnO4 was used as chemical modifier. The optimal pyrolysis temperature for Cu determination was 1300 °C. Atomization temperatures for Cu and Hg were 2400 and 1100 °C, respectively. External calibration with aqueous standard solutions was adopted for both elements. The limits of quantification (LoQs) and characteristic mass (m0) obtained for Cu determination were 0.4 μg g- 1 and 1.12 ng, respectively, on line 249.2146 nm, and 64 μg g- 1 and 25 pg on 327.3960 nm. For mercury, LoQ and m0 were 4.8 ng g- 1 and 39 pg, respectively. The accuracy of the proposed methods was confirmed by the analysis of standard reference material (SRM) of Trace Elements in Multi-Nutrient Fertilizer (SRM NIST 695). The precision expressed as relative standard deviation (RSD), was better than 8.2% for Hg and 7.7% for the Cu (n = 5), considered satisfactory for microanalysis in solid sample. Four fertilizer samples acquired in commercial establishments in the city of Salvador, Bahia, Brazil, were analyzed. The optimized analytical methods were simple, fast, accurate, precise and free of spectral interferences for the determination of Cu and Hg in phosphate fertilizer samples by SS-HR-CS GF AAS, avoiding the dissolution of the sample, the use of harmful reagents and the generation of residues.

Timing Is Important: Unmanned Aircraft vs. Satellite Imagery in Plant Invasion Monitoring

PubMed Central

Müllerová, Jana; Brůna, Josef; Bartaloš, Tomáš; Dvořák, Petr; Vítková, Michaela; Pyšek, Petr

2017-01-01

The rapid spread of invasive plants makes their management increasingly difficult. Remote sensing offers a means of fast and efficient monitoring, but still the optimal methodologies remain to be defined. The seasonal dynamics and spectral characteristics of the target invasive species are important factors, since, at certain time of the vegetation season (e.g., at flowering or senescing), plants are often more distinct (or more visible beneath the canopy). Our aim was to establish fast, repeatable and a cost-efficient, computer-assisted method applicable over larger areas, to reduce the costs of extensive field campaigns. To achieve this goal, we examined how the timing of monitoring affects the detection of noxious plant invaders in Central Europe, using two model herbaceous species with markedly different phenological, structural, and spectral characteristics. They are giant hogweed (Heracleum mantegazzianum), a species with very distinct flowering phase, and the less distinct knotweeds (Fallopia japonica, F. sachalinensis, and their hybrid F. × bohemica). The variety of data generated, such as imagery from purposely-designed, unmanned aircraft vehicle (UAV), and VHR satellite, and aerial color orthophotos enabled us to assess the effects of spectral, spatial, and temporal resolution (i.e., the target species' phenological state) for successful recognition. The demands for both spatial and spectral resolution depended largely on the target plant species. In the case that a species was sampled at the most distinct phenological phase, high accuracy was achieved even with lower spectral resolution of our low-cost UAV. This demonstrates that proper timing can to some extent compensate for the lower spectral resolution. The results of our study could serve as a basis for identifying priorities for management, targeted at localities with the greatest risk of invasive species' spread and, once eradicated, to monitor over time any return. The best mapping strategy should reflect morphological and structural features of the target plant and choose appropriate spatial, spectral, and temporal resolution. The UAV enables flexible data acquisition for required time periods at low cost and is, therefore, well-suited for targeted monitoring; while satellite imagery provides the best solution for larger areas. Nonetheless, users must be aware of their limits. PMID:28620399

A new COmpact hyperSpectral Imaging system (COSI) for UAS

NASA Astrophysics Data System (ADS)

Sima, Aleksandra; Baeck, Pieter-Jan; Delalieux, Stephanie; Livens, Stefan; Blommaert, Joris; Delauré, Bavo; Boonen, Miet

2016-04-01

This presentation gives an overview of the new COmpact hyperSpectral Imaging (COSI) system recently developed at the Flemish Institute for Technological Research (VITO, Belgium) and suitable for multirotor Remotely Piloted Aircraft Systems (RPAS) platforms. The camera is compact and lightweight, with a total mass of less than 500g including: an embedded computer, storage and power distribution unit. Such device miniaturization was possible thanks to the application of linear variable filters technology, in which image lines in the across flight direction correspond to different spectral bands as well as a different location on the ground (frame camera). The scanning motion is required to retrieve the complete spectrum for every point on the ground. The COSI camera captures data in 72 narrow (FWHM: 5nm to 10 nm) bands in the spectral range of 600-900 nm. Such spectral information is highly favourable for vegetation studies, since the main chlorophyll absorption feature centred around 680 nm is measured, as well as, the red-edge region (680 nm to 730 nm) which is often linked to plant stress. The NIR region furthermore reflects the internal plant structure, and is often linked to leaf area index and plant biomass. Next to the high spectral resolution, the COSI imager also provides a very high spatial data resolution i.e. images captured with a 9mm lens at 40m altitude cover a swath of ~40m with a ~2cm ground sampling distance. A dedicated data processing chain transforms the raw images into various information and action maps representing the status of the vegetation health and thus allowing for optimization of the management decisions within agricultural fields. In a number of test flights, hyperspectral COSI imager data were acquired covering diverse environments, e.g.: strawberry fields, natural grassland or pear orchards. Next to the COSI system overview, examples of collected data will be presented together with the results of the spectral data analysis. Lessons learned and an outlook on further improvements will be also shared with the audience.

Laboratory Thermal Infrared and Visible to Near-Infrared Spectral Analysis of Chert

NASA Astrophysics Data System (ADS)

McDowell, M. L.; Hamilton, V. E.

2007-12-01

Though basaltic materials dominate the composition of the Martian surface, a material with a relatively high silica component in an area of Eos Chasma was reported by [1] from thermal infrared (TIR) data. The spectrum of the silica phase resembles quartz or chert, but with the existing information it is difficult to tell which phase best fits the observations. Though quartz, chert, and amorphous silica are chemically identical (SiO2), their physical differences (e.g., microstructures) result in different TIR spectral characteristics. Previous studies have analyzed a limited number of chert samples using emission infrared spectroscopy [2] and transmission infrared spectroscopy [3]. We continue these preliminary studies with an investigation aiming to more completely understand and document the variation in spectral character of cherts. This knowledge may help to identify the silica phase in Eos Chasma and any future discoveries. Our study includes a more extensive sampling of geologic chert in hand sample (>15 samples) with various sources, methods of formation, surface textures, and crystallinities. We analyzed their visible to near-infrared (VNIR) reflectance spectra, as well as spectral features in TIR emission spectra. We measured multiple locations on each sample to determine spectral homogeneity across the sample and between various orientations. Where possible, natural, cut, and recently fractured surfaces were measured. We compared the collected TIR spectra for similarities and differences in shape and spectral contrast within each sample and between samples that may relate to variations in the samples' structure (e.g. crystallinity, and surface texture). VNIR measurements show features indicative of non-silica phases and water that may be present in the cherts. [1] Hamilton, V.E. (2005) Eos Trans. AGU, Fall Meeting Suppl., Abstract P24A-08. [2] Michalski, J.R. (2005) PhD Diss., ASU, Tempe. [3] Long, D. G. et al. (2001) Canadian Archaeological Assoc., 33rd Meeting.

Design and fabrication of a 900-1700 nm hyper-spectral imaging spectrometer

NASA Astrophysics Data System (ADS)

Kim, Tae Hyoung; Kong, Hong Jin; Kim, Tae Hoon; Shin, Jae Sung

2010-02-01

This paper presents a 900-1700 nm hyper-spectral imaging spectrometer which offers low distortions, a low F-number, a compact size, an easily-fabricated design and a low cost (is presented in this paper). The starting point for its optical design is discussed according to the geometrical aberration theory and Rowland circle condition. It is shown that these methods are useful in designing a push-broom hyper-spectral imaging spectrometer that has an aperture of f/2.4, modulation transfer functions of less than 0.8 at 25 cycles/mm, and spot sizes less than 10 μm. A prototype of the optimized hyper-spectral imaging spectrometer has been fabricated using a high precision machine and the experimental demonstration with the fabricated hyper-spectral imaging spectrometer is presented.

Improving alpine-region spectral unmixing with optimal-fit snow endmembers

NASA Technical Reports Server (NTRS)

Painter, Thomas H.; Roberts, Dar A.; Green, Robert O.; Dozier, Jeff

1995-01-01

Surface albedo and snow-covered-area (SCA) are crucial inputs to the hydrologic and climatologic modeling of alpine and seasonally snow-covered areas. Because the spectral albedo and thermal regime of pure snow depend on grain size, areal distribution of snow grain size is required. Remote sensing has been shown to be an effective (and necessary) means of deriving maps of grain size distribution and snow-covered-area. Developed here is a technique whereby maps of grain size distribution improve estimates of SCA from spectral mixture analysis with AVIRIS data.

Spectral dependence of the main parameters of ITE silicon avalanche photodiodes

NASA Astrophysics Data System (ADS)

Wegrzecka, Iwona; Grynglas, Maria; Wegrzecki, Maciej

2001-08-01

New applications for avalanche photodiodes (APDs) as in systems using visible radiation, have prompted the need for the evaluation of detection properties of ITE APDs in the 400 divided by 700 nm spectral range. The paper presents the method and result of studies on the spectral dependence of the gain, dark and noise currents, sensitivity and excess noise factor of ITE APDs. The studies have shown that ITE APDs optimized for the near IR radiation can be effectively applied in the detection of radiation above the 500 nm wavelength.

Spectral matching technology for light-emitting diode-based jaundice photodynamic therapy device

NASA Astrophysics Data System (ADS)

Gan, Ru-ting; Guo, Zhen-ning; Lin, Jie-ben

2015-02-01

The objective of this paper is to obtain the spectrum of light-emitting diode (LED)-based jaundice photodynamic therapy device (JPTD), the bilirubin absorption spectrum in vivo was regarded as target spectrum. According to the spectral constructing theory, a simple genetic algorithm as the spectral matching algorithm was first proposed in this study. The optimal combination ratios of LEDs were obtained, and the required LEDs number was then calculated. Meanwhile, the algorithm was compared with the existing spectral matching algorithms. The results show that this algorithm runs faster with higher efficiency, the switching time consumed is 2.06 s, and the fitting spectrum is very similar to the target spectrum with 98.15% matching degree. Thus, blue LED-based JPTD can replace traditional blue fluorescent tube, the spectral matching technology that has been put forward can be applied to the light source spectral matching for jaundice photodynamic therapy and other medical phototherapy.

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

David, Aurelien; Fini, Paul T.; Houser, Kevin W.

We have developed a two-measure system for evaluating light sources’ color rendition that builds upon conceptual progress of numerous researchers over the last two decades. The system quantifies the color fidelity and color gamut (change in object chroma) of a light source in comparison to a reference illuminant. The calculations are based on a newly developed set of reflectance data from real samples uniformly distributed in color space (thereby fairly representing all colors) and in wavelength space (thereby precluding artificial optimization of the color rendition scores by spectral engineering). The color fidelity score R f is an improved version ofmore » the CIE color rendering index. The color gamut score R g is an improved version of the Gamut Area Index. In combination, they provide two complementary assessments to guide the optimization of future light sources. This method summarizes the findings of the Color Metric Task Group of the Illuminating Engineering Society of North America (IES). It is adopted in the upcoming IES TM-30-2015, and is proposed for consideration with the International Commission on Illumination (CIE).« less

Magnetic fluctuations and quasi-static magnetism in optimally doped FeSe0.4Te0.6

NASA Astrophysics Data System (ADS)

Thampy, Vivek; Bao, Wei; Savici, A. T.; Qiu, Y.; Hu, Jin; Liu, Tijiang; Mao, Z. Q.; Broholm, Collin

2010-03-01

Magnetic Fluctuations in the optimally doped 11-type iron superconductor FeSe0.4Te0.6 were examined using inelastic neutron scattering on the MACS instrument at NIST. In the normal state at T=25K we find strong low energy fluctuations through an extended area of the (hk0) zone that includes and connects the high symmetry (1/2,0,0) and (1/2,1/2,0) points. In the superconducting state intensity at the (1/2,1/2,0) location is depleted for φ = 1.5 meV as spectral weight is transferred to the 6.5 meV resonance. Low energy and quasi-elastic scattering however remains at (1/2,0,0). In the (HHL) zone we observed striped features indicating shorter range correlations along c. While glassy magnetism and superconductivity coexist in our samples, they are associated with distinct parts of momentum space. Work at JHU was supported by DoE through DE-FG02-08ER46544.

The X-IFU end-to-end simulations performed for the TES array optimization exercise

NASA Astrophysics Data System (ADS)

Peille, Philippe; Wilms, J.; Brand, T.; Cobo, B.; Ceballos, M. T.; Dauser, T.; Smith, S. J.; Barret, D.; den Herder, J. W.; Piro, L.; Barcons, X.; Pointecouteau, E.; Bandler, S.; den Hartog, R.; de Plaa, J.

2015-09-01

The focal plane assembly of the Athena X-ray Integral Field Unit (X-IFU) includes as the baseline an array of ~4000 single size calorimeters based on Transition Edge Sensors (TES). Other sensor array configurations could however be considered, combining TES of different properties (e.g. size). In attempting to improve the X-IFU performance in terms of field of view, count rate performance, and even spectral resolution, two alternative TES array configurations to the baseline have been simulated, each combining a small and a large pixel array. With the X-IFU end-to-end simulator, a sub-sample of the Athena core science goals, selected by the X-IFU science team as potentially driving the optimal TES array configuration, has been simulated for the results to be scientifically assessed and compared. In this contribution, we will describe the simulation set-up for the various array configurations, and highlight some of the results of the test cases simulated.

Evaluating an image-fusion algorithm with synthetic-image-generation tools

NASA Astrophysics Data System (ADS)

Gross, Harry N.; Schott, John R.

1996-06-01

An algorithm that combines spectral mixing and nonlinear optimization is used to fuse multiresolution images. Image fusion merges images of different spatial and spectral resolutions to create a high spatial resolution multispectral combination. High spectral resolution allows identification of materials in the scene, while high spatial resolution locates those materials. In this algorithm, conventional spectral mixing estimates the percentage of each material (called endmembers) within each low resolution pixel. Three spectral mixing models are compared; unconstrained, partially constrained, and fully constrained. In the partially constrained application, the endmember fractions are required to sum to one. In the fully constrained application, all fractions are additionally required to lie between zero and one. While negative fractions seem inappropriate, they can arise from random spectral realizations of the materials. In the second part of the algorithm, the low resolution fractions are used as inputs to a constrained nonlinear optimization that calculates the endmember fractions for the high resolution pixels. The constraints mirror the low resolution constraints and maintain consistency with the low resolution fraction results. The algorithm can use one or more higher resolution sharpening images to locate the endmembers to high spatial accuracy. The algorithm was evaluated with synthetic image generation (SIG) tools. A SIG developed image can be used to control the various error sources that are likely to impair the algorithm performance. These error sources include atmospheric effects, mismodeled spectral endmembers, and variability in topography and illumination. By controlling the introduction of these errors, the robustness of the algorithm can be studied and improved upon. The motivation for this research is to take advantage of the next generation of multi/hyperspectral sensors. Although the hyperspectral images will be of modest to low resolution, fusing them with high resolution sharpening images will produce a higher spatial resolution land cover or material map.

Generalized assorted pixel camera: postcapture control of resolution, dynamic range, and spectrum.

PubMed

Yasuma, Fumihito; Mitsunaga, Tomoo; Iso, Daisuke; Nayar, Shree K

2010-09-01

We propose the concept of a generalized assorted pixel (GAP) camera, which enables the user to capture a single image of a scene and, after the fact, control the tradeoff between spatial resolution, dynamic range and spectral detail. The GAP camera uses a complex array (or mosaic) of color filters. A major problem with using such an array is that the captured image is severely under-sampled for at least some of the filter types. This leads to reconstructed images with strong aliasing. We make four contributions in this paper: 1) we present a comprehensive optimization method to arrive at the spatial and spectral layout of the color filter array of a GAP camera. 2) We develop a novel algorithm for reconstructing the under-sampled channels of the image while minimizing aliasing artifacts. 3) We demonstrate how the user can capture a single image and then control the tradeoff of spatial resolution to generate a variety of images, including monochrome, high dynamic range (HDR) monochrome, RGB, HDR RGB, and multispectral images. 4) Finally, the performance of our GAP camera has been verified using extensive simulations that use multispectral images of real world scenes. A large database of these multispectral images has been made available at http://www1.cs.columbia.edu/CAVE/projects/gap_camera/ for use by the research community.

Optimization-based limiters for the spectral element method

NASA Astrophysics Data System (ADS)

Guba, Oksana; Taylor, Mark; St-Cyr, Amik

2014-06-01

We introduce a new family of optimization based limiters for the h-p spectral element method. The native spectral element advection operator is oscillatory, but due to its mimetic properties it is locally conservative and has a monotone property with respect to element averages. We exploit this property to construct locally conservative quasimonotone and sign-preserving limiters. The quasimonotone limiter prevents all overshoots and undershoots at the element level, but is not strictly non-oscillatory. It also maintains quasimonotonicity even with the addition of a dissipation term such as viscosity or hyperviscosity. The limiters are based on a least-squares formulation with equality and inequality constraints and are local to each element. We evaluate the new limiters using a deformational flow test case for advection on the surface of the sphere. We focus on mesh refinement for moderate (p=3) and high order (p=6) elements. As expected, the spectral element method obtains its formal order of accuracy for smooth problems without limiters. For advection of fields with cusps and discontinuities, the high order convergence is lost, but in all cases, p=6 outperforms p=3 for the same degrees of freedom.

Learning from Past Classification Errors: Exploring Methods for Improving the Performance of a Deep Learning-based Building Extraction Model through Quantitative Analysis of Commission Errors for Optimal Sample Selection

NASA Astrophysics Data System (ADS)

Swan, B.; Laverdiere, M.; Yang, L.

2017-12-01

In the past five years, deep Convolutional Neural Networks (CNN) have been increasingly favored for computer vision applications due to their high accuracy and ability to generalize well in very complex problems; however, details of how they function and in turn how they may be optimized are still imperfectly understood. In particular, their complex and highly nonlinear network architecture, including many hidden layers and self-learned parameters, as well as their mathematical implications, presents open questions about how to effectively select training data. Without knowledge of the exact ways the model processes and transforms its inputs, intuition alone may fail as a guide to selecting highly relevant training samples. Working in the context of improving a CNN-based building extraction model used for the LandScan USA gridded population dataset, we have approached this problem by developing a semi-supervised, highly-scalable approach to select training samples from a dataset of identified commission errors. Due to the large scope this project, tens of thousands of potential samples could be derived from identified commission errors. To efficiently trim those samples down to a manageable and effective set for creating additional training sample, we statistically summarized the spectral characteristics of areas with rates of commission errors at the image tile level and grouped these tiles using affinity propagation. Highly representative members of each commission error cluster were then used to select sites for training sample creation. The model will be incrementally re-trained with the new training data to allow for an assessment of how the addition of different types of samples affects the model performance, such as precision and recall rates. By using quantitative analysis and data clustering techniques to select highly relevant training samples, we hope to improve model performance in a manner that is resource efficient, both in terms of training process and in sample creation.

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

NASA Astrophysics Data System (ADS)

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

2015-01-01

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

Selective excitation for spectral editing and assignment in separated local field experiments of oriented membrane proteins

NASA Astrophysics Data System (ADS)

Koroloff, Sophie N.; Nevzorov, Alexander A.

2017-01-01

Spectroscopic assignment of NMR spectra for oriented uniformly labeled membrane proteins embedded in their native-like bilayer environment is essential for their structure determination. However, sequence-specific assignment in oriented-sample (OS) NMR is often complicated by insufficient resolution and spectral crowding. Therefore, the assignment process is usually done by a laborious and expensive "shotgun" method involving multiple selective labeling of amino acid residues. Presented here is a strategy to overcome poor spectral resolution in crowded regions of 2D spectra by selecting resolved "seed" residues via soft Gaussian pulses inserted into spin-exchange separated local-field experiments. The Gaussian pulse places the selected polarization along the z-axis while dephasing the other signals before the evolution of the 1H-15N dipolar couplings. The transfer of magnetization is accomplished via mismatched Hartmann-Hahn conditions to the nearest-neighbor peaks via the proton bath. By optimizing the length and amplitude of the Gaussian pulse, one can also achieve a phase inversion of the closest peaks, thus providing an additional phase contrast. From the superposition of the selective spin-exchanged SAMPI4 onto the fully excited SAMPI4 spectrum, the 15N sites that are directly adjacent to the selectively excited residues can be easily identified, thereby providing a straightforward method for initiating the assignment process in oriented membrane proteins.

High-Throughput Field Phenotyping of Leaves, Leaf Sheaths, Culms and Ears of Spring Barley Cultivars at Anthesis and Dough Ripeness.

PubMed

Barmeier, Gero; Schmidhalter, Urs

2017-01-01

To optimize plant architecture (e.g., photosynthetic active leaf area, leaf-stem ratio), plant physiologists and plant breeders rely on destructively and tediously harvested biomass samples. A fast and non-destructive method for obtaining information about different plant organs could be vehicle-based spectral proximal sensing. In this 3-year study, the mobile phenotyping platform PhenoTrac 4 was used to compare the measurements from active and passive spectral proximal sensors of leaves, leaf sheaths, culms and ears of 34 spring barley cultivars at anthesis and dough ripeness. Published vegetation indices (VI), partial least square regression (PLSR) models and contour map analysis were compared to assess these traits. Contour maps are matrices consisting of coefficients of determination for all of the binary combinations of wavelengths and the biomass parameters. The PLSR models of leaves, leaf sheaths and culms showed strong correlations ( R 2 = 0.61-0.76). Published vegetation indices depicted similar coefficients of determination; however, their RMSEs were higher. No wavelength combination could be found by the contour map analysis to improve the results of the PLSR or published VIs. The best results were obtained for the dry weight and N uptake of leaves and culms. The PLSR models yielded satisfactory relationships for leaf sheaths at anthesis ( R 2 = 0.69), whereas only a low performance for all of sensors and methods was observed at dough ripeness. No relationships with ears were observed. Active and passive sensors performed comparably, with slight advantages observed for the passive spectrometer. The results indicate that tractor-based proximal sensing in combination with optimized spectral indices or PLSR models may represent a suitable tool for plant breeders to assess relevant morphological traits, allowing for a better understanding of plant architecture, which is closely linked to the physiological performance. Further validation of PLSR models is required in independent studies. Organ specific phenotyping represents a first step toward breeding by design.

High-Throughput Field Phenotyping of Leaves, Leaf Sheaths, Culms and Ears of Spring Barley Cultivars at Anthesis and Dough Ripeness

PubMed Central

Barmeier, Gero; Schmidhalter, Urs

2017-01-01

To optimize plant architecture (e.g., photosynthetic active leaf area, leaf-stem ratio), plant physiologists and plant breeders rely on destructively and tediously harvested biomass samples. A fast and non-destructive method for obtaining information about different plant organs could be vehicle-based spectral proximal sensing. In this 3-year study, the mobile phenotyping platform PhenoTrac 4 was used to compare the measurements from active and passive spectral proximal sensors of leaves, leaf sheaths, culms and ears of 34 spring barley cultivars at anthesis and dough ripeness. Published vegetation indices (VI), partial least square regression (PLSR) models and contour map analysis were compared to assess these traits. Contour maps are matrices consisting of coefficients of determination for all of the binary combinations of wavelengths and the biomass parameters. The PLSR models of leaves, leaf sheaths and culms showed strong correlations (R2 = 0.61–0.76). Published vegetation indices depicted similar coefficients of determination; however, their RMSEs were higher. No wavelength combination could be found by the contour map analysis to improve the results of the PLSR or published VIs. The best results were obtained for the dry weight and N uptake of leaves and culms. The PLSR models yielded satisfactory relationships for leaf sheaths at anthesis (R2 = 0.69), whereas only a low performance for all of sensors and methods was observed at dough ripeness. No relationships with ears were observed. Active and passive sensors performed comparably, with slight advantages observed for the passive spectrometer. The results indicate that tractor-based proximal sensing in combination with optimized spectral indices or PLSR models may represent a suitable tool for plant breeders to assess relevant morphological traits, allowing for a better understanding of plant architecture, which is closely linked to the physiological performance. Further validation of PLSR models is required in independent studies. Organ specific phenotyping represents a first step toward breeding by design. PMID:29163629

Optimal Spectral Regions For Laser Excited Fluorescence Diagnostics For Point Of Care Application

NASA Astrophysics Data System (ADS)

Vaitkuviene, A.; Gėgžna, V.; Varanius, D.; Vaitkus, J.

2011-09-01

The tissue fluorescence gives the response of light emitting molecule signature, and characterizes the cell composition and peculiarities of metabolism. Both are useful for the biomedical diagnostics, as reported in previous our and others works. The present work demonstrates the results of application of laser excited autofluorescence for diagnostics of pathology in genital tissues, and the feasibility for the bedside at "point of care—off lab" application. A portable device using the USB spectrophotometer, micro laser (355 nm Nd:YAG, 0,5 ns pulse, repetition rate 10 kHz, output power 15 mW), three channel optical fiber and computer with diagnostic program was designed and ready for clinical trial to be used for cytology and biopsy specimen on site diagnostics, and for the endoscopy/puncture procedures. The biopsy and cytology samples, as well as intervertebral disc specimen were evaluated by pathology experts and the fluorescence spectra were investigated in the fresh and preserved specimens. The spectra were recorded in the spectral range 350-900 nm. At the initial stage the Gaussian components of spectra were found and the Mann-Whitney test was used for the groups' differentiation and the spectral regions for optimal diagnostics purpose were found. Then a formal dividing of spectra in the components or the definite width bands, where the main difference of the different group spectra was observed, was used to compare these groups. The ROC analysis based diagnostic algorithms were created for medical prognosis. The positive prognostic values and negative prediction values were determined for cervical Liquid PAP smear supernatant sediment diagnosis of being Cervicitis and Norma versus CIN2+. In a case of intervertebral disc the analysis allows to get the additional information about the disc degeneration status. All these results demonstrated an efficiency of the proposed procedure and the designed device could be tested at the point-of-care site or for intervertebral disc operations.

Optimal fluorescence waveband determination for detecting defect cherry tomatoes using fluorescence excitation-emission matrix

USDA-ARS?s Scientific Manuscript database

A multi-spectral fluorescence imaging technique was used to detect defect cherry tomatoes. The fluorescence excitation and emission matrix was used to measure for defects, sound surface, and stem areas to determine the optimal fluorescence excitation and emission wavelengths for discrimination. Two-...

A Canonical Ensemble Correlation Prediction Model for Seasonal Precipitation Anomaly

NASA Technical Reports Server (NTRS)

Shen, Samuel S. P.; Lau, William K. M.; Kim, Kyu-Myong; Li, Guilong

2001-01-01

This report describes an optimal ensemble forecasting model for seasonal precipitation and its error estimation. Each individual forecast is based on the canonical correlation analysis (CCA) in the spectral spaces whose bases are empirical orthogonal functions (EOF). The optimal weights in the ensemble forecasting crucially depend on the mean square error of each individual forecast. An estimate of the mean square error of a CCA prediction is made also using the spectral method. The error is decomposed onto EOFs of the predictand and decreases linearly according to the correlation between the predictor and predictand. This new CCA model includes the following features: (1) the use of area-factor, (2) the estimation of prediction error, and (3) the optimal ensemble of multiple forecasts. The new CCA model is applied to the seasonal forecasting of the United States precipitation field. The predictor is the sea surface temperature.

A Framework for Cloudy Model Optimization and Database Storage

NASA Astrophysics Data System (ADS)

Calvén, Emilia; Helton, Andrew; Sankrit, Ravi

2018-01-01

We present a framework for producing Cloudy photoionization models of the nebular emission from novae ejecta and storing a subset of the results in SQL database format for later usage. The database can be searched for models best fitting observed spectral line ratios. Additionally, the framework includes an optimization feature that can be used in tandem with the database to search for and improve on models by creating new Cloudy models while, varying the parameters. The database search and optimization can be used to explore the structures of nebulae by deriving their properties from the best-fit models. The goal is to provide the community with a large database of Cloudy photoionization models, generated from parameters reflecting conditions within novae ejecta, that can be easily fitted to observed spectral lines; either by directly accessing the database using the framework code or by usage of a website specifically made for this purpose.

Development of stable, narrow spectral line-width, fiber delivered laser source for spin exchange optical pumping

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

Liu, Bo; Tong, Xin; Jiang, Chenyang

2015-06-05

In this study, we developed a stable, narrow spectral line-width, fiber delivered laser source for spin exchange optical pumping. An optimized external cavity equipped with an off-the-shelf volume holographic grating narrowed the spectral line-width of a 100 W high-power diode laser and stabilized the laser spectrum. The laser spectrum showed a high side mode suppression ratio of >30 dB and good long-term stability (center wavelength drifting within ±0.002 nm during 220 h of operation). Finally, our laser is delivered by a multimode fiber with power ~70 W, center wavelength of 794.77 nm, and spectral bandwidth of ~0.12 nm.

Interactive Spectral Analysis and Computation (ISAAC)

NASA Technical Reports Server (NTRS)

Lytle, D. M.

1992-01-01

Isaac is a task in the NSO external package for IRAF. A descendant of a FORTRAN program written to analyze data from a Fourier transform spectrometer, the current implementation has been generalized sufficiently to make it useful for general spectral analysis and other one dimensional data analysis tasks. The user interface for Isaac is implemented as an interpreted mini-language containing a powerful, programmable vector calculator. Built-in commands provide much of the functionality needed to produce accurate line lists from input spectra. These built-in functions include automated spectral line finding, least squares fitting of Voigt profiles to spectral lines including equality constraints, various filters including an optimal filter construction tool, continuum fitting, and various I/O functions.

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.

Spectral Characterization of Analog Samples in Anticipation of OSIRIS-REx's Arrival at Bennu

NASA Technical Reports Server (NTRS)

Donaldson Hanna, K. L.; Schrader, D. L.; Bowles, N. E.; Clark, B. E.; Cloutis, E. A.; Connolly, H. C., Jr.; Hamilton, V. E.; Keller, L. P.; Lauretta, D. S.; Lim, L. F.;

On-line measurement of lignin in wood pulp by color shift of fluorescence

DOEpatents

Jeffers, Larry A.; Malito, Michael L.

1996-01-01

Lignin concentrations from wood pulp samples are measured by applying an excitation light at a selected wavelength to the samples in order to cause the lignin to emit fluorescence. A spectral distribution of the fluorescence emission is then determined. The lignin concentration is then calculated based on the spectral distribution signal. The spectral distribution is quantified by either a wavelength centroid method or a band ratio method.

On-line measurement of lignin in wood pulp by color shift of fluorescence

DOEpatents

Jeffers, L.A.; Malito, M.L.

1996-01-23

Lignin concentrations from wood pulp samples are measured by applying an excitation light at a selected wavelength to the samples in order to cause the lignin to emit fluorescence. A spectral distribution of the fluorescence emission is then determined. The lignin concentration is then calculated based on the spectral distribution signal. The spectral distribution is quantified by either a wavelength centroid method or a band ratio method. 6 figs.

Variation of surface water spectral response as a function of in situ sampling technique

NASA Technical Reports Server (NTRS)

Davis, Bruce A.; Hodgson, Michael E.

1988-01-01

Tests were carried out to determine the spectral variation contributed by a particular sampling technique. A portable radiometer was used to measure the surface water spectral response. Variation due to the reflectance of objects near the radiometer (i.e., the boat side) during data acquisition was studied. Consideration was also given to the variation due to the temporal nature of the phenomena (i.e., wave activity).

Variable selection based near infrared spectroscopy quantitative and qualitative analysis on wheat wet gluten

NASA Astrophysics Data System (ADS)

Lü, Chengxu; Jiang, Xunpeng; Zhou, Xingfan; Zhang, Yinqiao; Zhang, Naiqian; Wei, Chongfeng; Mao, Wenhua

2017-10-01

Wet gluten is a useful quality indicator for wheat, and short wave near infrared spectroscopy (NIRS) is a high performance technique with the advantage of economic rapid and nondestructive test. To study the feasibility of short wave NIRS analyzing wet gluten directly from wheat seed, 54 representative wheat seed samples were collected and scanned by spectrometer. 8 spectral pretreatment method and genetic algorithm (GA) variable selection method were used to optimize analysis. Both quantitative and qualitative model of wet gluten were built by partial least squares regression and discriminate analysis. For quantitative analysis, normalization is the optimized pretreatment method, 17 wet gluten sensitive variables are selected by GA, and GA model performs a better result than that of all variable model, with R2V=0.88, and RMSEV=1.47. For qualitative analysis, automatic weighted least squares baseline is the optimized pretreatment method, all variable models perform better results than those of GA models. The correct classification rates of 3 class of <24%, 24-30%, >30% wet gluten content are 95.45, 84.52, and 90.00%, respectively. The short wave NIRS technique shows potential for both quantitative and qualitative analysis of wet gluten for wheat seed.

Optimization of bicelle lipid composition and temperature for EPR spectroscopy of aligned membranes.

PubMed

McCaffrey, Jesse E; James, Zachary M; Thomas, David D

2015-01-01

We have optimized the magnetic alignment of phospholipid bilayered micelles (bicelles) for EPR spectroscopy, by varying lipid composition and temperature. Bicelles have been extensively used in NMR spectroscopy for several decades, in order to obtain aligned samples in a near-native membrane environment and take advantage of the intrinsic sensitivity of magnetic resonance to molecular orientation. Recently, bicelles have also seen increasing use in EPR, which offers superior sensitivity and orientational resolution. However, the low magnetic field strength (less than 1 T) of most conventional EPR spectrometers results in homogeneously oriented bicelles only at a temperature well above physiological. To optimize bicelle composition for magnetic alignment at reduced temperature, we prepared bicelles containing varying ratios of saturated (DMPC) and unsaturated (POPC) phospholipids, using EPR spectra of a spin-labeled fatty acid to assess alignment as a function of lipid composition and temperature. Spectral analysis showed that bicelles containing an equimolar mixture of DMPC and POPC homogeneously align at 298 K, 20 K lower than conventional DMPC-only bicelles. It is now possible to perform EPR studies of membrane protein structure and dynamics in well-aligned bicelles at physiological temperatures and below. Copyright © 2014 Elsevier Inc. All rights reserved.

Aminoquinolines as fluorescent labels for hydrophilic interaction liquid chromatography of oligosaccharides.

PubMed

Struwe, Weston B; Rudd, Pauline M

2012-08-01

In this study, we investigated the potential of four different aminoquinoline (AQ) compounds as fluorescent labels for glycan analysis using hydrophilic interaction liquid chromatography (HILIC) and fluorescence detection (FLD). We confirmed the optimal excitation and emission wavelengths of 3-AQ and 6-AQ conjugated to glycan standards using three-dimensional fluorescent spectral scanning. The optimal excitation and emission wavelengths for 6-AQ were confirmed at λ(ex)=355 nm and λ(em)=440 nm. We concluded that the optimal wavelengths for 3-AQ were λ(ex)=355 nm and λ(em)=420 nm, which differed considerably from the wavelengths applied in previous reports. HILIC-FLD chromatograms using experimentally determined wavelengths were similar to 2-aminobenzamide controls, but the peak capacity and resolution differed significantly when published 3-AQ λ(ex/em) values were applied. Furthermore, we found that 5-AQ and 8-AQ labeled maltohexaose did not display any fluorescent properties when used as a carbohydrate tag for HPLC analysis. Finally, we applied experimentally determined wavelengths to 3-AQ labeled N-glycans released from human IgG to illustrate changes in retention time as well as to demonstrate that AQ labeling is applicable to complex sample analysis via exoglycosidase sequencing.

Detection of Fungus Infection on Petals of Rapeseed (Brassica napus L.) Using NIR Hyperspectral Imaging

NASA Astrophysics Data System (ADS)

Zhao, Yan-Ru; Yu, Ke-Qiang; Li, Xiaoli; He, Yong

2016-12-01

Infected petals are often regarded as the source for the spread of fungi Sclerotinia sclerotiorum in all growing process of rapeseed (Brassica napus L.) plants. This research aimed to detect fungal infection of rapeseed petals by applying hyperspectral imaging in the spectral region of 874-1734 nm coupled with chemometrics. Reflectance was extracted from regions of interest (ROIs) in the hyperspectral image of each sample. Firstly, principal component analysis (PCA) was applied to conduct a cluster analysis with the first several principal components (PCs). Then, two methods including X-loadings of PCA and random frog (RF) algorithm were used and compared for optimizing wavebands selection. Least squares-support vector machine (LS-SVM) methodology was employed to establish discriminative models based on the optimal and full wavebands. Finally, area under the receiver operating characteristics curve (AUC) was utilized to evaluate classification performance of these LS-SVM models. It was found that LS-SVM based on the combination of all optimal wavebands had the best performance with AUC of 0.929. These results were promising and demonstrated the potential of applying hyperspectral imaging in fungus infection detection on rapeseed petals.

Optimized linear motor and digital PID controller setup used in Mössbauer spectrometer

NASA Astrophysics Data System (ADS)

Kohout, Pavel; Kouřil, Lukáš; Navařík, Jakub; Novák, Petr; Pechoušek, Jiří

2014-10-01

Optimization of a linear motor and digital PID controller setup used in a Mössbauer spectrometer is presented. Velocity driving system with a digital PID feedback subsystem was developed in the LabVIEW graphical environment and deployed on the sbRIO real-time hardware device (National Instruments). The most important data acquisition processes are performed as real-time deterministic tasks on an FPGA chip. Velocity transducer of a double loudspeaker type with a power amplifier circuit is driven by the system. Series of calibration measurements were proceeded to find the optimal setup of the P, I, D parameters together with velocity error signal analysis. The shape and given signal characteristics of the velocity error signal are analyzed in details. Remote applications for controlling and monitoring the PID system from computer or smart phone, respectively, were also developed. The best setup and P, I, D parameters were set and calibration spectrum of α-Fe sample with an average nonlinearity of the velocity scale below 0.08% was collected. Furthermore, the width of the spectral line below 0.30 mm/s was observed. Powerful and complex velocity driving system was designed.

Theoretical and experimental analysis of injection seeding a Q-switched alexandrite laser

NASA Technical Reports Server (NTRS)

Prasad, C. R.; Lee, H. S.; Glesne, T. R.; Monosmith, B.; Schwemmer, G. K.

1991-01-01

Injection seeding is a method for achieving linewidths of less than 500 MHz in the output of broadband, tunable, solid state lasers. Dye lasers, CW and pulsed diode lasers, and other solid state lasers have been used as injection seeders. By optimizing the fundamental laser parameters of pump energy, Q-switched pulse build-up time, injection seed power and mode matching, one can achieve significant improvements in the spectral purity of the Q-switched output. These parameters are incorporated into a simple model for analyzing spectral purity and pulse build-up processes in a Q-switched, injection-seeded laser. Experiments to optimize the relevant parameters of an alexandrite laser show good agreement.

Design and resolution analysis of parabolic mirror spectrometer

NASA Astrophysics Data System (ADS)

Wu, Su; Wang, Guodong; Xia, Guo; Sun, Yanchao; Hu, Mingyong

2017-10-01

In order to further eliminate aberration and improve resolution, the paper employs parabolic mirror as the collimating mirror and the focusing mirror to design "Z" configuration and "U" configuration optical structure of parabolic spectrometer with the F number 2.5 and the spectral range varying from 250 nm to 850 nm. We conduct experiments on ZEMAX to simulate and optimize the initial parameters of two structures with the root-mean-square (RMS) radius of spots along Y axis as the optimization goal. Through analyzing the spot diagram and the root-mean-square (RMS) of Y axis, we can see that the "U" configuration spectrometers can achieve much better spectral resolution than the "Z" configuration.

Breast composition measurement with a cadmium-zinc-telluride based spectral computed tomography system

PubMed Central

Ding, Huanjun; Ducote, Justin L.; Molloi, Sabee

2012-01-01

Purpose: To investigate the feasibility of breast tissue composition in terms of water, lipid, and protein with a cadmium-zinc-telluride (CZT) based computed tomography (CT) system to help better characterize suspicious lesions. Methods: Simulations and experimental studies were performed using a spectral CT system equipped with a CZT-based photon-counting detector with energy resolution. Simulations of the figure-of-merit (FOM), the signal-to-noise ratio (SNR) of the dual energy image with respect to the square root of mean glandular dose (MGD), were performed to find the optimal configuration of the experimental acquisition parameters. A calibration phantom 3.175 cm in diameter was constructed from polyoxymethylene plastic with cylindrical holes that were filled with water and oil. Similarly, sized samples of pure adipose and pure lean bovine tissues were used for the three-material decomposition. Tissue composition results computed from the images were compared to the chemical analysis data of the tissue samples. Results: The beam energy was selected to be 100 kVp with a splitting energy of 40 keV. The tissue samples were successfully decomposed into water, lipid, and protein contents. The RMS error of the volumetric percentage for the three-material decomposition, as compared to data from the chemical analysis, was estimated to be approximately 5.7%. Conclusions: The results of this study suggest that the CZT-based photon-counting detector may be employed in the CT system to quantify the water, lipid, and protein mass densities in tissue with a relatively good agreement. PMID:22380361

Improved LIBS limit of detection of Be, Mg, Si, Mn, Fe and Cu in aluminum alloy samples using a portable Echelle spectrometer with ICCD camera

NASA Astrophysics Data System (ADS)

Mohamed, Walid Tawfik Y.

2008-02-01

Laser-induced breakdown spectroscopy (LIBS) is a laser-based technique that can provide non-intrusive, qualitative and quantitative measurement of metals in various environments. LIBS uses the plasma generated by a high-energy laser beam to prepare and excite the sample in one step. In the present work, LIBS has been applied to perform elemental analysis of six trace elements simultaneously in aluminum alloy targets. The plasma is generated by focusing a pulsed Nd:YAG laser on the target in air at atmospheric pressure. LIBS limit of detection (LOD) is affected by many experimental parameters such as interferences, self-absorption, spectral overlap and matrix effect. We aimed to improve the LIBS LOD by optimizing these experimental parameters as possible. In doing so, a portable Echelle spectrometer with intensified CCD camera was used to detect the LIBS plasma emission. This advanced Echelle spectrometer provides a constant spectral resolution (CSR) of 7500 corresponding to 4 pixels FWHM over a wavelength range 200-1000 nm displayable in a single spectrum. Then, the calibration curves for iron, beryllium, magnesium, silicon, manganese and copper as minor elements were achieved with linear regression coefficients between 98-99% on average in aluminum standard sample alloys. New LOD values were achieved in the ppm range with high precision (RSD 3-8%). From the application view point, improving LIBS LOD is very important in the on-line industrial process control to follow-up multi-elements for the correct alloying in metals.

Raman microspectrometer combined with scattering microscopy and lensless imaging for bacteria identification

NASA Astrophysics Data System (ADS)

Strola, S. A.; Schultz, E.; Allier, C. P.; DesRoches, B.; Lemmonier, J.; Dinten, J.-M.

2013-03-01

In this paper, we report on a compact prototype capable both of lensfree imaging, Raman spectrometry and scattering microscopy from bacteria samples. This instrument allows high-throughput real-time characterization without the need of markers, making it potentially suitable to field label-free biomedical and environmental applications. Samples are illuminated from above with a focused-collimated 532nm laser beam and can be x-y-z scanned. The bacteria detection is based on emerging lensfree imaging technology able to localize cells of interest over a large field-of-view of 24mm2. Raman signal and scattered light are then collected by separate measurement arms simultaneously. In the first arm the emission light is fed by a fiber into a prototype spectrometer, developed by Tornado Spectral System based on Tornado's High Throughput Virtual Slit (HTVS) novel technology. The enhanced light throughput in the spectral region of interest (500-1800 cm-1) reduces Raman acquisition time down to few seconds, thus facilitating experimental protocols and avoiding the bacteria deterioration induced by laser thermal heating. Scattered light impinging in the second arm is collected onto a charge-coupled-device. The reconstructed image allows studying the single bacteria diffraction pattern and their specific structural features. The characterization and identification of different bacteria have been performed to validate and optimize the acquisition system and the component setup. The results obtained demonstrate the benefits of these three techniques combination by providing the precise bacteria localization, their chemical composition and a morphology description. The procedure for a rapid identification of particular pathogen bacteria in a sample is illustrated.

Spatially offset Raman spectroscopy for photon migration investigations in long bone

NASA Astrophysics Data System (ADS)

Sowoidnich, Kay; Churchwell, John H.; Buckley, Kevin; Kerns, Jemma G.; Goodship, Allen E.; Parker, Anthony W.; Matousek, Pavel

2015-07-01

Raman Spectroscopy has become an important technique for assessing the composition of excised sections of bone, and is currently being developed as an in vivo tool for transcutaneous detection of bone disease using spatially offset Raman spectroscopy (SORS). The sampling volume of the Raman technique (and thus the amount of bone material interrogated by SORS) depends on the nature of the photon scattering in the probed tissue. Bone is a complex hierarchical material and to date little is known regarding its diffuse scattering properties which are important for the development and optimization of SORS as a diagnostic tool for characterizing bone disease in vivo. SORS measurements at 830 nm excitation wavelength are carried out on stratified samples to determine the depth from which the Raman signal originates within bone tissue. The measurements are made using a 0.38 mm thin Teflon slice, to give a pronounced and defined spectral signature, inserted in between layers of stacked 0.60 mm thin equine bone slices. Comparing the stack of bone slices with and without underlying bone section below the Teflon slice illustrated that thin sections of bone can lose appreciable number of photons through the unilluminated back surface. The results show that larger SORS offsets lead to progressively larger penetration depth into the sample; different Raman spectral signatures could be retrieved through up to 3.9 mm of overlying bone material with a 7 mm offset. These findings have direct impact on potential diagnostic medical applications; for instance on the detection of bone tumors or areas of infected bone.

[Effect of Characteristic Variable Extraction on Accuracy of Cu in Navel Orange Peel by LIBS].

PubMed

Li, Wen-bing; Yao, Ming-yin; Huang, Lin; Chen, Tian-bing; Zheng, Jian-hong; Fan, Shi-quan; Liu Mu-hua HE, Mu-hua; Lin, Jin-long; Ouyang, Jing-yi

2015-07-01

Heavy metals pollution in foodstuffs is more and more serious. It is impossible to satisfy the modern agricultural development by conventional chemical analysis. Laser induced breakdown spectroscopy (LIBS) is an emerging technology with the characteristic of rapid and nondestructive detection. But LIBS' s repeatability, sensitivity and accuracy has much room to improve. In this work, heavy metal Cu in Gannan Navel Orange which is the Jiangxi specialty fruit will be predicted by LIBS. Firstly, the navel orange samples were contaminated in our lab. The spectra of samples were collected by irradiating the peel by optimized LIBS parameters. The laser energy was set as 20 mJ, delay time of Spectral Data Gathering was set as 1.2 micros, the integration time of Spectral data gathering was set as 2 ms. The real concentration in samples was obtained by AAS (atom absorption spectroscopy). The characteristic variables Cu I 324.7 and Cu I 327.4 were extracted. And the calibration model was constructed between LIBS spectra and real concentration about Cu. The results show that relative error of the predicted concentrations of three relational model were 7.01% or less, reached a minimum of 0.02%, 0.01% and 0.02% respectively. The average relative errors were 2.33%, 3.10% and 26.3%. Tests showed that different characteristic variables decided different accuracy. It is very important to choose suitable characteristic variable. At the same time, this work is helpful to explore the distribution of heavy metals between pulp and peel.

Remote sensing imagery classification using multi-objective gravitational search algorithm

NASA Astrophysics Data System (ADS)

Zhang, Aizhu; Sun, Genyun; Wang, Zhenjie

2016-10-01

Simultaneous optimization of different validity measures can capture different data characteristics of remote sensing imagery (RSI) and thereby achieving high quality classification results. In this paper, two conflicting cluster validity indices, the Xie-Beni (XB) index and the fuzzy C-means (FCM) (Jm) measure, are integrated with a diversity-enhanced and memory-based multi-objective gravitational search algorithm (DMMOGSA) to present a novel multi-objective optimization based RSI classification method. In this method, the Gabor filter method is firstly implemented to extract texture features of RSI. Then, the texture features are syncretized with the spectral features to construct the spatial-spectral feature space/set of the RSI. Afterwards, cluster of the spectral-spatial feature set is carried out on the basis of the proposed method. To be specific, cluster centers are randomly generated initially. After that, the cluster centers are updated and optimized adaptively by employing the DMMOGSA. Accordingly, a set of non-dominated cluster centers are obtained. Therefore, numbers of image classification results of RSI are produced and users can pick up the most promising one according to their problem requirements. To quantitatively and qualitatively validate the effectiveness of the proposed method, the proposed classification method was applied to classifier two aerial high-resolution remote sensing imageries. The obtained classification results are compared with that produced by two single cluster validity index based and two state-of-the-art multi-objective optimization algorithms based classification results. Comparison results show that the proposed method can achieve more accurate RSI classification.

Identification of mineral compositions in some renal calculi by FT Raman and IR spectral analysis

NASA Astrophysics Data System (ADS)

Tonannavar, J.; Deshpande, Gouri; Yenagi, Jayashree; Patil, Siddanagouda B.; Patil, Nikhil A.; Mulimani, B. G.

2016-02-01

We present in this paper accurate and reliable Raman and IR spectral identification of mineral constituents in nine samples of renal calculi (kidney stones) removed from patients suffering from nephrolithiasis. The identified mineral components include Calcium Oxalate Monohydrate (COM, whewellite), Calcium Oxalate Dihydrate (COD, weddellite), Magnesium Ammonium Phosphate Hexahydrate (MAPH, struvite), Calcium Hydrogen Phosphate Dihydrate (CHPD, brushite), Pentacalcium Hydroxy Triphosphate (PCHT, hydroxyapatite) and Uric Acid (UA). The identification is based on a satisfactory assignment of all the observed IR and Raman bands (3500-400 cm- 1) to chemical functional groups of mineral components in the samples, aided by spectral analysis of pure materials of COM, MAPH, CHPD and UA. It is found that the eight samples are composed of COM as the common component, the other mineral species as common components are: MAPH in five samples, PCHT in three samples, COD in three samples, UA in three samples and CHPD in two samples. One sample is wholly composed of UA as a single component; this inference is supported by the good agreement between ab initio density functional theoretical spectra and experimental spectral measurements of both sample and pure material. A combined application of Raman and IR techniques has shown that, where the IR is ambiguous, the Raman analysis can differentiate COD from COM and PCHT from MAPH.

Identification of mineral compositions in some renal calculi by FT Raman and IR spectral analysis.

PubMed

Tonannavar, J; Deshpande, Gouri; Yenagi, Jayashree; Patil, Siddanagouda B; Patil, Nikhil A; Mulimani, B G

2016-02-05

We present in this paper accurate and reliable Raman and IR spectral identification of mineral constituents in nine samples of renal calculi (kidney stones) removed from patients suffering from nephrolithiasis. The identified mineral components include Calcium Oxalate Monohydrate (COM, whewellite), Calcium Oxalate Dihydrate (COD, weddellite), Magnesium Ammonium Phosphate Hexahydrate (MAPH, struvite), Calcium Hydrogen Phosphate Dihydrate (CHPD, brushite), Pentacalcium Hydroxy Triphosphate (PCHT, hydroxyapatite) and Uric Acid (UA). The identification is based on a satisfactory assignment of all the observed IR and Raman bands (3500-400c m(-1)) to chemical functional groups of mineral components in the samples, aided by spectral analysis of pure materials of COM, MAPH, CHPD and UA. It is found that the eight samples are composed of COM as the common component, the other mineral species as common components are: MAPH in five samples, PCHT in three samples, COD in three samples, UA in three samples and CHPD in two samples. One sample is wholly composed of UA as a single component; this inference is supported by the good agreement between ab initio density functional theoretical spectra and experimental spectral measurements of both sample and pure material. A combined application of Raman and IR techniques has shown that, where the IR is ambiguous, the Raman analysis can differentiate COD from COM and PCHT from MAPH. Copyright © 2015 Elsevier B.V. All rights reserved.

Relation of laboratory and remotely sensed spectral signatures of ocean-dumped acid waste

NASA Technical Reports Server (NTRS)

Lewis, B. W.

1978-01-01

Results of laboratory transmission and remotely sensed ocean upwelled spectral signatures of acid waste ocean water solutions are presented. The studies were performed to establish ocean-dumped acid waste spectral signatures and to relate them to chemical and physical interactions occurring in the dump plume. The remotely sensed field measurements and the laboratory measurements were made using the same rapid-scanning spectrometer viewing a dump plume and with actual acid waste and ocean water samples, respectively. Laboratory studies showed that the signatures were produced by soluble ferric iron being precipitated in situ as ferric hydroxide upon dilution with ocean water. Sea-truth water samples were taken and analyzed for pertinent major components of the acid waste. Relationships were developed between the field and laboratory data both for spectral signatures and color changes with concentration. The relationships allow for the estimation of concentration of the indicator iron from remotely sensed spectral data and the laboratory transmission concentration data without sea-truth samples.

GEOS-2 C-band radar system project. Spectral analysis as related to C-band radar data analysis

NASA Technical Reports Server (NTRS)

1972-01-01

Work performed on spectral analysis of data from the C-band radars tracking GEOS-2 and on the development of a data compaction method for the GEOS-2 C-band radar data is described. The purposes of the spectral analysis study were to determine the optimum data recording and sampling rates for C-band radar data and to determine the optimum method of filtering and smoothing the data. The optimum data recording and sampling rate is defined as the rate which includes an optimum compromise between serial correlation and the effects of frequency folding. The goal in development of a data compaction method was to reduce to a minimum the amount of data stored, while maintaining all of the statistical information content of the non-compacted data. A digital computer program for computing estimates of the power spectral density function of sampled data was used to perform the spectral analysis study.

Identification of spilled oils by NIR spectroscopy technology based on KPCA and LSSVM

NASA Astrophysics Data System (ADS)

Tan, Ailing; Bi, Weihong

2011-08-01

Oil spills on the sea surface are seen relatively often with the development of the petroleum exploitation and transportation of the sea. Oil spills are great threat to the marine environment and the ecosystem, thus the oil pollution in the ocean becomes an urgent topic in the environmental protection. To develop the oil spill accident treatment program and track the source of the spilled oils, a novel qualitative identification method combined Kernel Principal Component Analysis (KPCA) and Least Square Support Vector Machine (LSSVM) was proposed. The proposed method adapt Fourier transform NIR spectrophotometer to collect the NIR spectral data of simulated gasoline, diesel fuel and kerosene oil spills samples and do some pretreatments to the original spectrum. We use the KPCA algorithm which is an extension of Principal Component Analysis (PCA) using techniques of kernel methods to extract nonlinear features of the preprocessed spectrum. Support Vector Machines (SVM) is a powerful methodology for solving spectral classification tasks in chemometrics. LSSVM are reformulations to the standard SVMs which lead to solving a system of linear equations. So a LSSVM multiclass classification model was designed which using Error Correcting Output Code (ECOC) method borrowing the idea of error correcting codes used for correcting bit errors in transmission channels. The most common and reliable approach to parameter selection is to decide on parameter ranges, and to then do a grid search over the parameter space to find the optimal model parameters. To test the proposed method, 375 spilled oil samples of unknown type were selected to study. The optimal model has the best identification capabilities with the accuracy of 97.8%. Experimental results show that the proposed KPCA plus LSSVM qualitative analysis method of near infrared spectroscopy has good recognition result, which could work as a new method for rapid identification of spilled oils.

Wavelength Scanning with a Tilting Interference Filter for Glow-Discharge Elemental Imaging.

PubMed

Storey, Andrew P; Ray, Steven J; Hoffmann, Volker; Voronov, Maxim; Engelhard, Carsten; Buscher, Wolfgang; Hieftje, Gary M

2017-06-01

Glow discharges have long been used for depth profiling and bulk analysis of solid samples. In addition, over the past decade, several methods of obtaining lateral surface elemental distributions have been introduced, each with its own strengths and weaknesses. Challenges for each of these techniques are acceptable optical throughput and added instrumental complexity. Here, these problems are addressed with a tilting-filter instrument. A pulsed glow discharge is coupled to an optical system comprising an adjustable-angle tilting filter, collimating and imaging lenses, and a gated, intensified charge-coupled device (CCD) camera, which together provide surface elemental mapping of solid samples. The tilting-filter spectrometer is instrumentally simpler, produces less image distortion, and achieves higher optical throughput than a monochromator-based instrument, but has a much more limited tunable spectral range and poorer spectral resolution. As a result, the tilting-filter spectrometer is limited to single-element or two-element determinations, and only when the target spectral lines fall within an appropriate spectral range and can be spectrally discerned. Spectral interferences that result from heterogeneous impurities can be flagged and overcome by observing the spatially resolved signal response across the available tunable spectral range. The instrument has been characterized and evaluated for the spatially resolved analysis of glow-discharge emission from selected but representative samples.

[Local Regression Algorithm Based on Net Analyte Signal and Its Application in Near Infrared Spectral Analysis].

PubMed

Zhang, Hong-guang; Lu, Jian-gang

2016-02-01

Abstract To overcome the problems of significant difference among samples and nonlinearity between the property and spectra of samples in spectral quantitative analysis, a local regression algorithm is proposed in this paper. In this algorithm, net signal analysis method(NAS) was firstly used to obtain the net analyte signal of the calibration samples and unknown samples, then the Euclidean distance between net analyte signal of the sample and net analyte signal of calibration samples was calculated and utilized as similarity index. According to the defined similarity index, the local calibration sets were individually selected for each unknown sample. Finally, a local PLS regression model was built on each local calibration sets for each unknown sample. The proposed method was applied to a set of near infrared spectra of meat samples. The results demonstrate that the prediction precision and model complexity of the proposed method are superior to global PLS regression method and conventional local regression algorithm based on spectral Euclidean distance.

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.

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.

Spectral characterization of near-infrared acousto-optic tunable filter (AOTF) hyperspectral imaging systems using standard calibration materials.

PubMed

Bürmen, Miran; Pernuš, Franjo; Likar, Boštjan

2011-04-01

In this study, we propose and evaluate a method for spectral characterization of acousto-optic tunable filter (AOTF) hyperspectral imaging systems in the near-infrared (NIR) spectral region from 900 nm to 1700 nm. The proposed spectral characterization method is based on the SRM-2035 standard reference material, exhibiting distinct spectral features, which enables robust non-rigid matching of the acquired and reference spectra. The matching is performed by simultaneously optimizing the parameters of the AOTF tuning curve, spectral resolution, baseline, and multiplicative effects. In this way, the tuning curve (frequency-wavelength characteristics) and the corresponding spectral resolution of the AOTF hyperspectral imaging system can be characterized simultaneously. Also, the method enables simple spectral characterization of the entire imaging plane of hyperspectral imaging systems. The results indicate that the method is accurate and efficient and can easily be integrated with systems operating in diffuse reflection or transmission modes. Therefore, the proposed method is suitable for characterization, calibration, or validation of AOTF hyperspectral imaging systems. © 2011 Society for Applied Spectroscopy

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

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

Radiative characteristics of a thin solid fuel at discrete levels of pyrolysis: Angular, spectral, and thermal dependencies

NASA Astrophysics Data System (ADS)

Pettegrew, Richard Dale

Numerical models of solid fuel combustion rely on accurate radiative property values to properly account for radiative heat transfer to and from the surface. The spectral properties can change significantly over the temperature range from ambient to burnout temperature. The variations of these properties are due to mass loss (as the sample pyrolyzes), chemical changes, and surface finish changes. In addition, band-integrated properties can vary due to the shift in the peak of the Planck curve as the temperature increases, which results in differing weightings of the spectral values. These effects were quantified for a thin cellulosic fuel commonly used in microgravity combustion studies (KimWipesRTM). Pyrolytic effects were simulated by heat-treating the samples in a constant temperature oven for varying times. Spectral data was acquired using a Fourier Transform Infrared (FTIR) spectrometer, along with an integrating sphere. Data was acquired at different incidence angles by mounting the samples at different angles inside the sphere. Comparisons of samples of similar area density created using different heat-treatment regimens showed that thermal history of the samples was irrelevant in virtually all spectral regions, with overall results correlating well with changes in area density. Spectral, angular, and thermal dependencies were determined for a representative data set, showing that the spectral absorptance decreases as the temperature increases, and decreases as the incidence angle varies from normal. Changes in absorptance are primarily offset by corresponding changes in transmittances, with reflectance values shown to be low over the tested spectral region of 2.50 mum to 24.93 mum. Band-integrated values were calculated as a function of temperature for the entire tested spectral region, as well as limited bands relevant for thermal imaging applications. This data was used to demonstrate the significant error that is likely if incorrect emittance values are used in heat transfer calculations. The pyrolyzed samples were also used to determine the activation energy and pre-exponential factor needed in the zeroth-order Arrhenius reaction, sometimes used to model the mass loss from the surface in numerical models. The values determined were used to calculate an estimated peak surface temperature, which agrees well with experimentally determined values.

SPECTRAL SMILE CORRECTION IN CRISM HYPERSPECTRAL IMAGES

NASA Astrophysics Data System (ADS)

Ceamanos, X.; Doute, S.

2009-12-01

The Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) is affected by a common artifact in "push-broom" sensors, the so-called "spectral smile". As a consequence, both central wavelength and spectral width of the spectral response vary along the across-track dimension, thus giving rise to a shifting and smoothing of spectra (see Fig. 1 (left)). In fact, both effects are greater for spectra on the edges, while they are minimum for data acquired by central detectors, the so-called "sweet spot". The prior artifacts become particularly critical for Martian observations which contain steep spectra such as CO2 ice-rich polar images. Fig. 1 (right) shows the horizontal brightness gradient which appears in every band corresponding to a steep portion of spectra. The correction of CRISM spectral smile is addressed using a two-step method which aims at modifying data sensibly in order to mimic the optimal CRISM response. First, all spectra, which are previously interpolated by cubic splines, are resampled to the "sweet spot" wavelengths in order to overcome the spectra shift. Secondly, the non-uniform spectral width is overcome by mimicking an increase of spectral resolution thanks to a spectral sharpening. In order to minimize noise, only bands particularly suffering from smile are selected. First, bands corresponding to the outliers of the Minimum Noise Transformation (MNF) eigenvector, which corresponds to the MNF band related to smile (MNF-smile), are selected. Then, a spectral neighborhood Θi, which takes into account the local spectral convexity or concavity, is defined for every selected band in order to maximize spectral shape preservation. The proposed sharpening technique takes into account both the instrument parameters and the observed spectra. First, every reflectance value belonging to a Θi is reevaluated by a sharpening which depends on a ratio of the spectral width of the current detector and the "sweet spot" one. Then, the optimal degree of sharpening for every Θi is determined thanks to a loop of sharpening procedures, which is assessed by the examination of an estimation of the smile energy (the MNF-smile eigenvalue). As a matter of fact, a higher sharpening is performed on Θi as long as the smile energy decreases. Experiments on CRISM data show remarkable results regarding the decrease of smile energy (up to 80%) and the spectral shape preservation. In fact, initial smile-affected spectra do no longer show shifting nor smoothing (see Fig. 2). Line-averaged spectra and band 155 of FRT5AE3_07 showing spectral smile effects Line-averaged spectra and band 155 of smile-corrected FRT5AE3_07

Comparative Analysis of Mass Spectral Similarity Measures on Peak Alignment for Comprehensive Two-Dimensional Gas Chromatography Mass Spectrometry

PubMed Central

2013-01-01

Peak alignment is a critical procedure in mass spectrometry-based biomarker discovery in metabolomics. One of peak alignment approaches to comprehensive two-dimensional gas chromatography mass spectrometry (GC×GC-MS) data is peak matching-based alignment. A key to the peak matching-based alignment is the calculation of mass spectral similarity scores. Various mass spectral similarity measures have been developed mainly for compound identification, but the effect of these spectral similarity measures on the performance of peak matching-based alignment still remains unknown. Therefore, we selected five mass spectral similarity measures, cosine correlation, Pearson's correlation, Spearman's correlation, partial correlation, and part correlation, and examined their effects on peak alignment using two sets of experimental GC×GC-MS data. The results show that the spectral similarity measure does not affect the alignment accuracy significantly in analysis of data from less complex samples, while the partial correlation performs much better than other spectral similarity measures when analyzing experimental data acquired from complex biological samples. PMID:24151524

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

USGS Publications Warehouse

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

2006-01-01

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

Compressive Spectral Method for the Simulation of the Nonlinear Gravity Waves

PubMed Central

Bayındır, Cihan

2016-01-01

In this paper an approach for decreasing the computational effort required for the spectral simulations of the fully nonlinear ocean waves is introduced. The proposed approach utilizes the compressive sampling algorithm and depends on the idea of using a smaller number of spectral components compared to the classical spectral method. After performing the time integration with a smaller number of spectral components and using the compressive sampling technique, it is shown that the ocean wave field can be reconstructed with a significantly better efficiency compared to the classical spectral method. For the sparse ocean wave model in the frequency domain the fully nonlinear ocean waves with Jonswap spectrum is considered. By implementation of a high-order spectral method it is shown that the proposed methodology can simulate the linear and the fully nonlinear ocean waves with negligible difference in the accuracy and with a great efficiency by reducing the computation time significantly especially for large time evolutions. PMID:26911357

Technical note: optimization for improved tube-loading efficiency in the dual-energy computed tomography coupled with balanced filter method.

PubMed

Saito, Masatoshi

2010-08-01

This article describes the spectral optimization of dual-energy computed tomography using balanced filters (bf-DECT) to reduce the tube loadings and dose by dedicating to the acquisition of electron density information, which is essential for treatment planning in radiotherapy. For the spectral optimization of bf-DECT, the author calculated the beam-hardening error and air kerma required to achieve a desired noise level in an electron density image of a 50-cm-diameter cylindrical water phantom. The calculation enables the selection of beam parameters such as tube voltage, balanced filter material, and its thickness. The optimal combination of tube voltages was 80 kV/140 kV in conjunction with Tb/Hf and Bi/Mo filter pairs; this combination agrees with that obtained in a previous study [M. Saito, "Spectral optimization for measuring electron density by the dual-energy computed tomography coupled with balanced filter method," Med. Phys. 36, 3631-3642 (2009)], although the thicknesses of the filters that yielded a minimum tube output were slightly different from those obtained in the previous study. The resultant tube loading of a low-energy scan of the present bf-DECT significantly decreased from 57.5 to 4.5 times that of a high-energy scan for conventional DECT. Furthermore, the air kerma of bf-DECT could be reduced to less than that of conventional DECT, while obtaining the same figure of merit for the measurement of electron density and effective atomic number. The tube-loading and dose efficiencies of bf-DECT were considerably improved by sacrificing the quality of the noise level in the images of effective atomic number.

Spectrally-encoded color imaging

PubMed Central

Kang, DongKyun; Yelin, Dvir; Bouma, Brett E.; Tearney, Guillermo J.

2010-01-01

Spectrally-encoded endoscopy (SEE) is a technique for ultraminiature endoscopy that encodes each spatial location on the sample with a different wavelength. One limitation of previous incarnations of SEE is that it inherently creates monochromatic images, since the spectral bandwidth is expended in the spatial encoding process. Here we present a spectrally-encoded imaging system that has color imaging capability. The new imaging system utilizes three distinct red, green, and blue spectral bands that are configured to illuminate the grating at different incident angles. By careful selection of the incident angles, the three spectral bands can be made to overlap on the sample. To demonstrate the method, a bench-top system was built, comprising a 2400-lpmm grating illuminated by three 525-μm-diameter beams with three different spectral bands. Each spectral band had a bandwidth of 75 nm, producing 189 resolvable points. A resolution target, color phantoms, and excised swine small intestine were imaged to validate the system's performance. The color SEE system showed qualitatively and quantitatively similar color imaging performance to that of a conventional digital camera. PMID:19688002

Hyperspectral analysis of clay minerals

NASA Astrophysics Data System (ADS)

Janaki Rama Suresh, G.; Sreenivas, K.; Sivasamy, R.

2014-11-01

A study was carried out by collecting soil samples from parts of Gwalior and Shivpuri district, Madhya Pradesh in order to assess the dominant clay mineral of these soils using hyperspectral data, as 0.4 to 2.5 μm spectral range provides abundant and unique information about many important earth-surface minerals. Understanding the spectral response along with the soil chemical properties can provide important clues for retrieval of mineralogical soil properties. The soil samples were collected based on stratified random sampling approach and dominant clay minerals were identified through XRD analysis. The absorption feature parameters like depth, width, area and asymmetry of the absorption peaks were derived from spectral profile of soil samples through DISPEC tool. The derived absorption feature parameters were used as inputs for modelling the dominant soil clay mineral present in the unknown samples using Random forest approach which resulted in kappa accuracy of 0.795. Besides, an attempt was made to classify the Hyperion data using Spectral Angle Mapper (SAM) algorithm with an overall accuracy of 68.43 %. Results showed that kaolinite was the dominant mineral present in the soils followed by montmorillonite in the study area.

Computerized EEG analysis for studying the effect of drugs on the central nervous system.

PubMed

Rosadini, G; Cavazza, B; Rodriguez, G; Sannita, W G; Siccardi, A

1977-11-01

Samples of our experience in quantitative pharmaco-EEG are reviewed to discuss and define its applicability and limits. Simple processing systems, such as the computation of Hjorth's descriptors, are useful for on-line monitoring of drug-induced EEG modifications which are evident also at the visual visual analysis. Power spectral analysis is suitable to identify and quantify EEG effects not evident at the visual inspection. It demonstrated how the EEG effects of compounds in a long-acting formulation vary according to the sampling time and the explored cerebral area. EEG modifications not detected by power spectral analysis can be defined by comparing statistically (F test) the spectral values of the EEG from a single lead at the different samples (longitudinal comparison), or the spectral values from different leads at any sample (intrahemispheric comparison). The presently available procedures of quantitative pharmaco-EEG are effective when applied to the study of mutltilead EEG recordings in a statistically significant sample of population. They do not seem reliable in the monitoring of directing of neuropyschiatric therapies in single patients, due to individual variability of drug effects.

The US Geological Survey, digital spectral reflectance library: version 1: 0.2 to 3.0 microns

NASA Technical Reports Server (NTRS)

Clark, Roger N.; Swayze, Gregg A.; King, Trude V. V.; Gallagher, Andrea J.; Calvin, Wendy M.

1993-01-01

We have developed a digital reflectance spectral library, with management and spectral analysis software. The library includes 500 spectra of 447 samples (some samples include a series of grain sizes) measured from approximately 0.2 to 3.0 microns. The spectral resolution (Full Width Half Maximum) of the reflectance data is less than or equal to 4 nm in the visible (0.2-0.8 microns) and less than or equal 10 nm in the NIR (0.8-2.35 microns). All spectra were corrected to absolute reflectance using an NBS Halon standard. Library management software lets users search on parameters (e.g. chemical formulae, chemical analyses, purity of samples, mineral groups, etc.) as well as spectral features. Minerals from sulfide, oxide, hydroxide, halide, carbonate, nitrate, borate, phosphate, and silicate groups are represented. X-ray and chemical analyses are tabulated for many of the entries, and all samples have been evaluated for spectral purity. The library also contains end and intermediate members for the olivine, garnet, scapolite, montmorillonite, muscovite, jarosite, and alunite solid-solution series. We have included representative spectra of H2O ice, kerogen, ammonium-bearing minerals, rare-earth oxides, desert varnish coatings, kaolinite crystallinity series, kaolinite-smectite series, zeolite series, and an extensive evaporite series. Because of the importance of vegetation to climate-change studies we have include 17 spectra of tree leaves, bushes, and grasses.

A Multi-Channel Method for Retrieving Surface Temperature for High-Emissivity Surfaces from Hyperspectral Thermal Infrared Images

PubMed Central

Zhong, Xinke; Labed, Jelila; Zhou, Guoqing; Shao, Kun; Li, Zhao-Liang

2015-01-01

The surface temperature (ST) of high-emissivity surfaces is an important parameter in climate systems. The empirical methods for retrieving ST for high-emissivity surfaces from hyperspectral thermal infrared (HypTIR) images require spectrally continuous channel data. This paper aims to develop a multi-channel method for retrieving ST for high-emissivity surfaces from space-borne HypTIR data. With an assumption of land surface emissivity (LSE) of 1, ST is proposed as a function of 10 brightness temperatures measured at the top of atmosphere by a radiometer having a spectral interval of 800–1200 cm−1 and a spectral sampling frequency of 0.25 cm−1. We have analyzed the sensitivity of the proposed method to spectral sampling frequency and instrumental noise, and evaluated the proposed method using satellite data. The results indicated that the parameters in the developed function are dependent on the spectral sampling frequency and that ST of high-emissivity surfaces can be accurately retrieved by the proposed method if appropriate values are used for each spectral sampling frequency. The results also showed that the accuracy of the retrieved ST is of the order of magnitude of the instrumental noise and that the root mean square error (RMSE) of the ST retrieved from satellite data is 0.43 K in comparison with the AVHRR SST product. PMID:26061199

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

NASA Astrophysics Data System (ADS)

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

2014-10-01

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

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

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

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

Spectral reflectance properties of carbon-bearing materials

NASA Technical Reports Server (NTRS)

Cloutis, Edward A.; Gaffey, Michael J.; Moslow, Thomas F.

1994-01-01

The 0.3-2.6 micrometers spectral reflectance properties of carbon polymorphs (graphite, carbon black, diamond), carbides (silicon carbide, cementite), and macromolecular organic-bearing materials (coal, coal tar extract, oil sand, oil shale) are found to vary from sample to sample and among groups. The carbon polymorphs are readily distinguishable on the basis of their visible-near infrared spectral slopes and shapes. The spectra of macromolecular organic-bearing materials show increases in reflectance toward longer wavelengths, exceeding the reflectance rise of more carbon-rich materials. Reflectance spectra of carbonaceous materials are affected by the crystal structure, composition, and degree of order/disorder of the samples. The characteristic spectral properties can potentially be exploited to identify individual carbonaceous grains in meteorites (as separates or in situ) or to conduct remote sensing geothermometry and identification of carbonaceous phases on asteroids.

Refractive index measurements in absorbing media with white light spectral interferometry.

PubMed

Arosa, Yago; Lago, Elena López; de la Fuente, Raúl

2018-03-19

White light spectral interferometry is applied to measure the refractive index in absorbing liquids in the spectral range of 400-1000 nm. We analyze the influence of absorption on the visibility of interferometric fringes and, accordingly, on the measurement of the refractive index. Further, we show that the refractive index in the absorption band can be retrieved by a two-step process. The procedure requires the use of two samples of different thickness, the thicker one to retrieve the refractive index in the transparent region and the thinnest to obtain the data in the absorption region. First, the refractive index values are retrieved with good accuracy in the transparent region of the material for 1-mm-thick samples. Second, these refractive index values serve also to precisely calculate the thickness of a thinner sample (~150 µm) since the accuracy of the methods depends strongly on the thickness of the sample. Finally, the refractive index is recovered for the entire spectral range.

Lessons Learned from Preparing OSIRIS-REx Spectral Analog Samples for Bennu

NASA Technical Reports Server (NTRS)

Schrader, D. L.; McCoy, T. J.; Cody, G. D.; King, A. J.; Schofield, P. F.; Russell, S. S.; Connolly, H. C., Jr.; Keller, L. P.; Donaldson Hanna, K.; Bowles, N.;

Semi-automatic engineering and tailoring of high-efficiency Bragg-reflection waveguide samples for quantum photonic applications

NASA Astrophysics Data System (ADS)

Pressl, B.; Laiho, K.; Chen, H.; Günthner, T.; Schlager, A.; Auchter, S.; Suchomel, H.; Kamp, M.; Höfling, S.; Schneider, C.; Weihs, G.

2018-04-01

Semiconductor alloys of aluminum gallium arsenide (AlGaAs) exhibit strong second-order optical nonlinearities. This makes them prime candidates for the integration of devices for classical nonlinear optical frequency conversion or photon-pair production, for example, through the parametric down-conversion (PDC) process. Within this material system, Bragg-reflection waveguides (BRW) are a promising platform, but the specifics of the fabrication process and the peculiar optical properties of the alloys require careful engineering. Previously, BRW samples have been mostly derived analytically from design equations using a fixed set of aluminum concentrations. This approach limits the variety and flexibility of the device design. Here, we present a comprehensive guide to the design and analysis of advanced BRW samples and show how to automatize these tasks. Then, nonlinear optimization techniques are employed to tailor the BRW epitaxial structure towards a specific design goal. As a demonstration of our approach, we search for the optimal effective nonlinearity and mode overlap which indicate an improved conversion efficiency or PDC pair production rate. However, the methodology itself is much more versatile as any parameter related to the optical properties of the waveguide, for example the phasematching wavelength or modal dispersion, may be incorporated as design goals. Further, we use the developed tools to gain a reliable insight in the fabrication tolerances and challenges of real-world sample imperfections. One such example is the common thickness gradient along the wafer, which strongly influences the photon-pair rate and spectral properties of the PDC process. Detailed models and a better understanding of the optical properties of a realistic BRW structure are not only useful for investigating current samples, but also provide important feedback for the design and fabrication of potential future turn-key devices.

Sensitive dual color in vivo bioluminescence imaging using a new red codon optimized firefly luciferase and a green click beetle luciferase.

PubMed

Mezzanotte, Laura; Que, Ivo; Kaijzel, Eric; Branchini, Bruce; Roda, Aldo; Löwik, Clemens

2011-04-22

Despite a plethora of bioluminescent reporter genes being cloned and used for cell assays and molecular imaging purposes, the simultaneous monitoring of multiple events in small animals is still challenging. This is partly attributable to the lack of optimization of cell reporter gene expression as well as too much spectral overlap of the color-coupled reporter genes. A new red emitting codon-optimized luciferase reporter gene mutant of Photinus pyralis, Ppy RE8, has been developed and used in combination with the green click beetle luciferase, CBG99. Human embryonic kidney cells (HEK293) were transfected with vectors that expressed red Ppy RE8 and green CBG99 luciferases. Populations of red and green emitting cells were mixed in different ratios. After addition of the shared single substrate, D-luciferin, bioluminescent (BL) signals were imaged with an ultrasensitive cooled CCD camera using a series of band pass filters (20 nm). Spectral unmixing algorithms were applied to the images where good separation of signals was observed. Furthermore, HEK293 cells that expressed the two luciferases were injected at different depth in the animals. Spectrally-separate images and quantification of the dual BL signals in a mixed population of cells was achieved when cells were either injected subcutaneously or directly into the prostate. We report here the re-engineering of different luciferase genes for in vitro and in vivo dual color imaging applications to address the technical issues of using dual luciferases for imaging. In respect to previously used dual assays, our study demonstrated enhanced sensitivity combined with spatially separate BL spectral emissions using a suitable spectral unmixing algorithm. This new D-luciferin-dependent reporter gene couplet opens up the possibility in the future for more accurate quantitative gene expression studies in vivo by simultaneously monitoring two events in real time.

Sensitive Dual Color In Vivo Bioluminescence Imaging Using a New Red Codon Optimized Firefly Luciferase and a Green Click Beetle Luciferase

PubMed Central

Mezzanotte, Laura; Que, Ivo; Kaijzel, Eric; Branchini, Bruce; Roda, Aldo; Löwik, Clemens

2011-01-01

Background Despite a plethora of bioluminescent reporter genes being cloned and used for cell assays and molecular imaging purposes, the simultaneous monitoring of multiple events in small animals is still challenging. This is partly attributable to the lack of optimization of cell reporter gene expression as well as too much spectral overlap of the color-coupled reporter genes. A new red emitting codon-optimized luciferase reporter gene mutant of Photinus pyralis, Ppy RE8, has been developed and used in combination with the green click beetle luciferase, CBG99. Principal Findings Human embryonic kidney cells (HEK293) were transfected with vectors that expressed red Ppy RE8 and green CBG99 luciferases. Populations of red and green emitting cells were mixed in different ratios. After addition of the shared single substrate, D-luciferin, bioluminescent (BL) signals were imaged with an ultrasensitive cooled CCD camera using a series of band pass filters (20 nm). Spectral unmixing algorithms were applied to the images where good separation of signals was observed. Furthermore, HEK293 cells that expressed the two luciferases were injected at different depth in the animals. Spectrally-separate images and quantification of the dual BL signals in a mixed population of cells was achieved when cells were either injected subcutaneously or directly into the prostate. Significance We report here the re-engineering of different luciferase genes for in vitro and in vivo dual color imaging applications to address the technical issues of using dual luciferases for imaging. In respect to previously used dual assays, our study demonstrated enhanced sensitivity combined with spatially separate BL spectral emissions using a suitable spectral unmixing algorithm. This new D-luciferin-dependent reporter gene couplet opens up the possibility in the future for more accurate quantitative gene expression studies in vivo by simultaneously monitoring two events in real time. PMID:21544210

Rainbow correlation imaging with macroscopic twin beam

NASA Astrophysics Data System (ADS)

Allevi, Alessia; Bondani, Maria

2017-06-01

We present the implementation of a correlation-imaging protocol that exploits both the spatial and spectral correlations of macroscopic twin-beam states generated by parametric downconversion. In particular, the spectral resolution of an imaging spectrometer coupled to an EMCCD camera is used in a proof-of-principle experiment to encrypt and decrypt a simple code to be transmitted between two parties. In order to optimize the trade-off between visibility and resolution, we provide the characterization of the correlation images as a function of the spatio-spectral properties of twin beams generated at different pump power values.

Adaptive mesh strategies for the spectral element method

NASA Technical Reports Server (NTRS)

Mavriplis, Catherine

1992-01-01

An adaptive spectral method was developed for the efficient solution of time dependent partial differential equations. Adaptive mesh strategies that include resolution refinement and coarsening by three different methods are illustrated on solutions to the 1-D viscous Burger equation and the 2-D Navier-Stokes equations for driven flow in a cavity. Sharp gradients, singularities, and regions of poor resolution are resolved optimally as they develop in time using error estimators which indicate the choice of refinement to be used. The adaptive formulation presents significant increases in efficiency, flexibility, and general capabilities for high order spectral methods.

Lunar UV-visible-IR mapping interferometric spectrometer

NASA Technical Reports Server (NTRS)

Smith, W. Hayden; Haskin, L.; Korotev, R.; Arvidson, R.; Mckinnon, W.; Hapke, B.; Larson, S.; Lucey, P.

1992-01-01

Ultraviolet-visible-infrared mapping digital array scanned interferometers for lunar compositional surveys was developed. The research has defined a no-moving-parts, low-weight and low-power, high-throughput, and electronically adaptable digital array scanned interferometer that achieves measurement objectives encompassing and improving upon all the requirements defined by the LEXSWIG for lunar mineralogical investigation. In addition, LUMIS provides a new, important, ultraviolet spectral mapping, high-spatial-resolution line scan camera, and multispectral camera capabilities. An instrument configuration optimized for spectral mapping and imaging of the lunar surface and provide spectral results in support of the instrument design are described.

A simple integrated ratiometric wavelength monitor based on multimode interference structure

NASA Astrophysics Data System (ADS)

Hatta, Agus Muhamad; Farrell, Gerald; Wang, Qian

2008-09-01

Wavelength measurement or monitoring can be implemented using a ratiometric power measurement technique. A ratiometric wavelength monitor normally consists of a Y-branch splitter with two arms: an edge filter arm with a well defined spectral response and a reference arm or alternatively, two edge filters arms with opposite slope spectral responses. In this paper, a simple configuration for an integrated ratiometric wavelength monitor based on a single multimode interference structure is proposed. By optimizing the length of the MMI and the two output port positions, opposite spectral responses for the two output ports can be achieved. The designed structure demonstrates a spectral response suitable for wavelength measurement with potentially a 10 pm resolution over a 100 nm wavelength range.

Superscattering of light optimized by a genetic algorithm

NASA Astrophysics Data System (ADS)

Mirzaei, Ali; Miroshnichenko, Andrey E.; Shadrivov, Ilya V.; Kivshar, Yuri S.

2014-07-01

We analyse scattering of light from multi-layer plasmonic nanowires and employ a genetic algorithm for optimizing the scattering cross section. We apply the mode-expansion method using experimental data for material parameters to demonstrate that our genetic algorithm allows designing realistic core-shell nanostructures with the superscattering effect achieved at any desired wavelength. This approach can be employed for optimizing both superscattering and cloaking at different wavelengths in the visible spectral range.

Atmospheric turbulence power spectral measurements to long wavelengths for several meteorological conditions

NASA Technical Reports Server (NTRS)

Rhyne, R. H.; Murrow, H. N.; Sidwell, K.

1976-01-01

Use of power spectral design techniques for supersonic transports requires accurate definition of atmospheric turbulence in the long wavelength region below the knee of the power spectral density function curve. Examples are given of data obtained from a current turbulence flight sampling program. These samples are categorized as (1) convective, (2) wind shear, (3) rotor, and (4) mountain-wave turbulence. Time histories, altitudes, root-mean-square values, statistical degrees of freedom, power spectra, and integral scale values are shown and discussed.

Laboratory spectroscopy of meteorite samples at UV-vis-NIR wavelengths: Analysis and discrimination by principal components analysis

NASA Astrophysics Data System (ADS)

Penttilä, Antti; Martikainen, Julia; Gritsevich, Maria; Muinonen, Karri

2018-02-01

Meteorite samples are measured with the University of Helsinki integrating-sphere UV-vis-NIR spectrometer. The resulting spectra of 30 meteorites are compared with selected spectra from the NASA Planetary Data System meteorite spectra database. The spectral measurements are transformed with the principal component analysis, and it is shown that different meteorite types can be distinguished from the transformed data. The motivation is to improve the link between asteroid spectral observations and meteorite spectral measurements.

Meteorite-asteroid spectral comparison - The effects of comminution, melting, and recrystallization

NASA Technical Reports Server (NTRS)

Clark, Beth E.; Fanale, Fraser P.; Salisbury, John W.

1992-01-01

The present laboratory simulation of possible spectral-alteration effects on the optical surface of ordinary chondrite parent bodies duplicated regolith processes through comminution of the samples to finer rain sizes. After reflectance spectra characterization, the comminuted samples were melted, crystallized, recomminuted, and again characterized. While individual spectral characteristics could be significantly changed by these processes, no combination of the alteration procedures appeared capable of affecting all relevant parameters in a way that improved the match between chondritic meteorites and S-class asteroids.

Transforming reflectance spectra into Munsell color space by using prime colors.

PubMed

Romney, A Kimball; Fulton, James T

2006-10-17

Independent researchers have proved mathematically that, given a set of color-matching functions, there exists a unique set of three monochromatic spectral lights that optimizes luminous efficiency and color gamut. These lights are called prime colors. We present a method for transforming reflectance spectra into Munsell color space by using hypothetical absorbance curves based on Gaussian approximations of the prime colors and a simplified version of opponent process theory. The derived color appearance system is represented as a 3D color system that is qualitatively similar to a conceptual representation of the Munsell color system. We illustrate the application of the model and compare it with existing models by using reflectance spectra obtained from 1,269 Munsell color samples.

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

NASA Technical Reports Server (NTRS)

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

2016-01-01

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

Quantitative estimation of soil salinity by means of different modeling methods and visible-near infrared (VIS–NIR) spectroscopy, Ebinur Lake Wetland, Northwest China

PubMed Central

Wang, Jingzhe; Abulimiti, Aerzuna; Cai, Lianghong

2018-01-01

Soil salinization is one of the most common forms of land degradation. The detection and assessment of soil salinity is critical for the prevention of environmental deterioration especially in arid and semi-arid areas. This study introduced the fractional derivative in the pretreatment of visible and near infrared (VIS–NIR) spectroscopy. The soil samples (n = 400) collected from the Ebinur Lake Wetland, Xinjiang Uyghur Autonomous Region (XUAR), China, were used as the dataset. After measuring the spectral reflectance and salinity in the laboratory, the raw spectral reflectance was preprocessed by means of the absorbance and the fractional derivative order in the range of 0.0–2.0 order with an interval of 0.1. Two different modeling methods, namely, partial least squares regression (PLSR) and random forest (RF) with preprocessed reflectance were used for quantifying soil salinity. The results showed that more spectral characteristics were refined for the spectrum reflectance treated via fractional derivative. The validation accuracies showed that RF models performed better than those of PLSR. The most effective model was established based on RF with the 1.5 order derivative of absorbance with the optimal values of R2 (0.93), RMSE (4.57 dS m−1), and RPD (2.78 ≥ 2.50). The developed RF model was stable and accurate in the application of spectral reflectance for determining the soil salinity of the Ebinur Lake wetland. The pretreatment of fractional derivative could be useful for monitoring multiple soil parameters with higher accuracy, which could effectively help to analyze the soil salinity. PMID:29736341

Quantitative estimation of soil salinity by means of different modeling methods and visible-near infrared (VIS-NIR) spectroscopy, Ebinur Lake Wetland, Northwest China.

PubMed

Wang, Jingzhe; Ding, Jianli; Abulimiti, Aerzuna; Cai, Lianghong

2018-01-01

Soil salinization is one of the most common forms of land degradation. The detection and assessment of soil salinity is critical for the prevention of environmental deterioration especially in arid and semi-arid areas. This study introduced the fractional derivative in the pretreatment of visible and near infrared (VIS-NIR) spectroscopy. The soil samples ( n  = 400) collected from the Ebinur Lake Wetland, Xinjiang Uyghur Autonomous Region (XUAR), China, were used as the dataset. After measuring the spectral reflectance and salinity in the laboratory, the raw spectral reflectance was preprocessed by means of the absorbance and the fractional derivative order in the range of 0.0-2.0 order with an interval of 0.1. Two different modeling methods, namely, partial least squares regression (PLSR) and random forest (RF) with preprocessed reflectance were used for quantifying soil salinity. The results showed that more spectral characteristics were refined for the spectrum reflectance treated via fractional derivative. The validation accuracies showed that RF models performed better than those of PLSR. The most effective model was established based on RF with the 1.5 order derivative of absorbance with the optimal values of R 2 (0.93), RMSE (4.57 dS m -1 ), and RPD (2.78 ≥ 2.50). The developed RF model was stable and accurate in the application of spectral reflectance for determining the soil salinity of the Ebinur Lake wetland. The pretreatment of fractional derivative could be useful for monitoring multiple soil parameters with higher accuracy, which could effectively help to analyze the soil salinity.

Comparison of SP-LIBS and DP-LIBS on metal and non-metal testing based on LIBS

NASA Astrophysics Data System (ADS)

Lin, Xiaomei; Sun, Haoran; Lin, Jingjun

2017-10-01

Laser-induced breakdown spectroscopy (LIBS) technology for metal and nonmetallic detection accuracy is the key technology to be solved in LIBS measurement, Due to metal elements and non-metallic elements in the lively, atomic structure and the degree of excitation of the laser are totally different, so the laser induced plasma evolution and spectral intensity are absolutely different. Among the many factors that affect measurement accuracy, the single and double pulse of the laser has a great influence on the measurement accuracy of metal and non-metal, they both have their own advantages, but also have their own shortcomings. In order to compare the effect of SP-LIBS and DP-LIBS on the measurement results of different elements, in this experiment, we put the metal element aluminum and non-metallic element carbon as the sample, the laser energy as a variable, using the high-speed camera shooting SP- LIBS and DP- LIBS plasma images. Using the spectral analyzer to record the spectral intensity of the elements, by calculating the relative RSD of the signal intensity and comparing the spectral intensity and the signal stability for different elements, develop an optimized experimental program. The experimental results show that under the same energy condition, the metal aluminum ion image under the DP- LIBS and the non-metallic carbon ion image under the SP- LIBS are the most suitable images. By considering the stability of the line intensity and the signal stability, we find that the sensitivity and stability of the signal strength of the metal elements under the double pulse are better than that of the single pulse, and for the non-metallic element, the single pulse laser is better than the double pulse.

Using a non-invasive technique in nutrition: synchrotron radiation infrared microspectroscopy spectroscopic characterization of oil seeds treated with different processing conditions on molecular spectral factors influencing nutrient delivery.

PubMed

Zhang, Xuewei; Yu, Peiqiang

2014-07-02

Non-invasive techniques are a key to study nutrition and structure interaction. Fourier transform infrared microspectroscopy coupled with a synchrotron radiation source (SR-IMS) is a rapid, non-invasive, and non-destructive bioanalytical technique. To understand internal structure changes in relation to nutrient availability in oil seed processing is vital to find optimal processing conditions. The objective of this study was to use a synchrotron-based bioanalytical technique SR-IMS as a non-invasive and non-destructive tool to study the effects of heat-processing methods and oil seed canola type on modeled protein structure based on spectral data within intact tissue that were randomly selected and quantify the relationship between the modeled protein structure and protein nutrient supply to ruminants. The results showed that the moisture heat-related processing significantly changed (p<0.05) modeled protein structures compared to the raw canola (control) and those processing by dry heating. The moisture heating increased (p<0.05) spectral intensities of amide I, amide II, α-helices, and β-sheets but decreased (p<0.05) the ratio of modeled α-helices to β-sheet spectral intensity. There was no difference (p>0.05) in the protein spectral profile between the raw and dry-heated canola tissue and between yellow- and brown-type canola tissue. The results indicated that different heat processing methods have different impacts on the protein inherent structure. The protein intrinsic structure in canola seed tissue was more sensitive and more response to the moisture heating in comparison to the dry heating. These changes are expected to be related to the nutritive value. However, the current study is based on limited samples, and more large-scale studies are needed to confirm our findings.

The HYDICE instrument design and its application to planetary instruments

NASA Technical Reports Server (NTRS)

Basedow, R.; Silverglate, P.; Rappoport, W.; Rockwell, R.; Rosenberg, D.; Shu, K.; Whittlesey, R.; Zalewski, E.

1993-01-01

The Hyperspectral Digital Imagery Collection Experiment (HYDICE) instrument represents a significant advance in the state of the art in hyperspectral sensors. It combines a higher signal-to-noise ratio (SNR) and significantly better spatial and spectral resolution and radio metric accuracy than systems flying on aircraft today. The need for 'clean' data, i.e., data free of sampling artifacts and excessive spatial or spectral noise, is a key driver behind the difficult combination of performance requirements laid out for HYDICE. Most of these involve the sensor optics and detector. This paper presents an optimized approach to those requirements, one that comprises push broom scanning, a single, mechanically cooled focal plane, a double-pass prism spectrometer, and an easily fabricated yet wide-field telescope. Central to the approach is a detector array that covers the entire spectrum from 0.4 to 2.5 microns. Among the major benefits conferred by such a design are optical and mechanical simplicity, low polarization sensitivity, and coverage of the entire spectrum without suffering the spectral gaps caused by beam splitters. The overall system minimizes interfaces to the C-141 aircraft on which it will be flown, can be calibrated on the ground and in flight to accuracies better than those required, and is designed for simple, push-button operation. Only unprocessed data are recorded during flight. A ground data processing station provides quick-look, calibration correction, and archiving capabilities, with a throughput better than the requirements. Overall performance of the system is expected to provide the solid database required to evaluate the potential of hyperspectral imagery in a wide variety of applications. HYDICE can be regarded as a test bed for future planetary instruments. The ability to spectrally image a wide field of view over multiple spectral octaves offers obvious advantages and is expected to maximize science return for the required cost and weight.

Optimization of a direct analysis in real time/time-of-flight mass spectrometry method for rapid serum metabolomic fingerprinting.

PubMed

Zhou, Manshui; McDonald, John F; Fernández, Facundo M

2010-01-01

Metabolomic fingerprinting of bodily fluids can reveal the underlying causes of metabolic disorders associated with many diseases, and has thus been recognized as a potential tool for disease diagnosis and prognosis following therapy. Here we report a rapid approach in which direct analysis in real time (DART) coupled with time-of-flight (TOF) mass spectrometry (MS) and hybrid quadrupole TOF (Q-TOF) MS is used as a means for metabolomic fingerprinting of human serum. In this approach, serum samples are first treated to precipitate proteins, and the volatility of the remaining metabolites increased by derivatization, followed by DART MS analysis. Maximum DART MS performance was obtained by optimizing instrumental parameters such as ionizing gas temperature and flow rate for the analysis of identical aliquots of a healthy human serum samples. These variables were observed to have a significant effect on the overall mass range of the metabolites detected as well as the signal-to-noise ratios in DART mass spectra. Each DART run requires only 1.2 min, during which more than 1500 different spectral features are observed in a time-dependent fashion. A repeatability of 4.1% to 4.5% was obtained for the total ion signal using a manual sampling arm. With the appealing features of high-throughput, lack of memory effects, and simplicity, DART MS has shown potential to become an invaluable tool for metabolomic fingerprinting. 2010 American Society for Mass Spectrometry. Published by Elsevier Inc. All rights reserved.

Exploring Geographical Differentiation of the Hoelen Medicinal Mushroom, Wolfiporia extensa (Agaricomycetes), Using Fourier-Transform Infrared Spectroscopy Combined with Multivariate Analysis.

PubMed

Li, Yan; Zhang, Ji; Zhao, Yanli; Liu, Honggao; Wang, Yuanzhong; Jin, Hang

2016-01-01

In this study the geographical differentiation of dried sclerotia of the medicinal mushroom Wolfiporia extensa, obtained from different regions in Yunnan Province, China, was explored using Fourier-transform infrared (FT-IR) spectroscopy coupled with multivariate data analysis. The FT-IR spectra of 97 samples were obtained for wave numbers ranging from 4000 to 400 cm-1. Then, the fingerprint region of 1800-600 cm-1 of the FT-IR spectrum, rather than the full spectrum, was analyzed. Different pretreatments were applied on the spectra, and a discriminant analysis model based on the Mahalanobis distance was developed to select an optimal pretreatment combination. Two unsupervised pattern recognition procedures- principal component analysis and hierarchical cluster analysis-were applied to enhance the authenticity of discrimination of the specimens. The results showed that excellent classification could be obtained after optimizing spectral pretreatment. The tested samples were successfully discriminated according to their geographical locations. The chemical properties of dried sclerotia of W. extensa were clearly dependent on the mushroom's geographical origins. Furthermore, an interesting finding implied that the elevations of collection areas may have effects on the chemical components of wild W. extensa sclerotia. Overall, this study highlights the feasibility of FT-IR spectroscopy combined with multivariate data analysis in particular for exploring the distinction of different regional W. extensa sclerotia samples. This research could also serve as a basis for the exploitation and utilization of medicinal mushrooms.

Comparing auditory filter bandwidths, spectral ripple modulation detection, spectral ripple discrimination, and speech recognition: Normal and impaired hearinga)

PubMed Central

Davies-Venn, Evelyn; Nelson, Peggy; Souza, Pamela

2015-01-01

Some listeners with hearing loss show poor speech recognition scores in spite of using amplification that optimizes audibility. Beyond audibility, studies have suggested that suprathreshold abilities such as spectral and temporal processing may explain differences in amplified speech recognition scores. A variety of different methods has been used to measure spectral processing. However, the relationship between spectral processing and speech recognition is still inconclusive. This study evaluated the relationship between spectral processing and speech recognition in listeners with normal hearing and with hearing loss. Narrowband spectral resolution was assessed using auditory filter bandwidths estimated from simultaneous notched-noise masking. Broadband spectral processing was measured using the spectral ripple discrimination (SRD) task and the spectral ripple depth detection (SMD) task. Three different measures were used to assess unamplified and amplified speech recognition in quiet and noise. Stepwise multiple linear regression revealed that SMD at 2.0 cycles per octave (cpo) significantly predicted speech scores for amplified and unamplified speech in quiet and noise. Commonality analyses revealed that SMD at 2.0 cpo combined with SRD and equivalent rectangular bandwidth measures to explain most of the variance captured by the regression model. Results suggest that SMD and SRD may be promising clinical tools for diagnostic evaluation and predicting amplification outcomes. PMID:26233047

Comparing auditory filter bandwidths, spectral ripple modulation detection, spectral ripple discrimination, and speech recognition: Normal and impaired hearing.

PubMed

Davies-Venn, Evelyn; Nelson, Peggy; Souza, Pamela

2015-07-01

Some listeners with hearing loss show poor speech recognition scores in spite of using amplification that optimizes audibility. Beyond audibility, studies have suggested that suprathreshold abilities such as spectral and temporal processing may explain differences in amplified speech recognition scores. A variety of different methods has been used to measure spectral processing. However, the relationship between spectral processing and speech recognition is still inconclusive. This study evaluated the relationship between spectral processing and speech recognition in listeners with normal hearing and with hearing loss. Narrowband spectral resolution was assessed using auditory filter bandwidths estimated from simultaneous notched-noise masking. Broadband spectral processing was measured using the spectral ripple discrimination (SRD) task and the spectral ripple depth detection (SMD) task. Three different measures were used to assess unamplified and amplified speech recognition in quiet and noise. Stepwise multiple linear regression revealed that SMD at 2.0 cycles per octave (cpo) significantly predicted speech scores for amplified and unamplified speech in quiet and noise. Commonality analyses revealed that SMD at 2.0 cpo combined with SRD and equivalent rectangular bandwidth measures to explain most of the variance captured by the regression model. Results suggest that SMD and SRD may be promising clinical tools for diagnostic evaluation and predicting amplification outcomes.

[Application of infrared spectroscopy technique to protein content fast measurement in milk powder based on support vector machines].

PubMed

Wu, Di; Cao, Fang; Feng, Shui-Juan; He, Yong

2008-05-01

In the present study, the JASCO Model FTIR-4 000 fourier transform infrared spectrometer (Japan) was used, with a valid range of 7 800-350 cm(-1). Seven brands of milk powder were bought in a local supermarket. Milk powder was compressed into a uniform tablet with a diameter of 5 mm and a thickness of 2 mm, and then scanned by the spectrometer. Each sample was scanned 40 times and the data were averaged. About 60 samples were measured for each brand, and data for 409 samples were obtained. NIRS analysis was based on the range of 4 000 to 6 666 cm(-1), while MIRS analysis was between 400 and 4 000 cm(-1). The protein content was determined by kjeldahl method and the factor 6.38 was used to convert the nitrogen values to protein. The protein content value is the weight of protein per 100 g of milk powder. The NIR data of the milk powder exhibited slight differences. Univariate analysis was not really appropriate for analyzing the data sets. From NIRS region, it could be observed that the trend of different curves is similar. The one around 4 312 cm(-1) embodies the vibration of protein. From MIRS region, it could be determined that there are many differences between transmission value curves. Two troughs around 1 545 and 1 656 cm(-1) stand for the vibration of amide I and II bands of protein. The smoothing way of Savitzky-Golay with 3 segments and zero polynomials and multiplicative scatter correction (MSC) were applied for denoising. First 8 important principle components (PCs), which were obtained from principle component analysis (PCA), were the optimal input feature subset. Least-squares support vector machines was applied to build the protein prediction model based on infrared spectral transmission value. The prediction result was better than that of traditional PLS regression model as the determination coefficient for prediction (R(p)2) is 0.951 7 and root mean square error for prediction (RMSEP) is 0.520 201. These indicate that LS-SVM is a powerful tool for spectral analysis. Moreover, the study compared the prediction results based on near infrared spectral data and mid-infrared spectral data. The results showed that the performance of the model with mid-infrared spectral data was better than the one with near infrared spectra data. It was concluded that infrared spectroscopy technique can do the quantification of protein content in milk powder fast and non-destructively and the process was simple and easy to operate. The results of this study can be used for the design of a simple and non-destructive spectra sensor for the quantitative of protein content in milk powder.

Spectral-Spatial Classification of Hyperspectral Images Using Hierarchical Optimization

NASA Technical Reports Server (NTRS)

Tarabalka, Yuliya; Tilton, James C.

2011-01-01

A new spectral-spatial method for hyperspectral data classification is proposed. For a given hyperspectral image, probabilistic pixelwise classification is first applied. Then, hierarchical step-wise optimization algorithm is performed, by iteratively merging neighboring regions with the smallest Dissimilarity Criterion (DC) and recomputing class labels for new regions. The DC is computed by comparing region mean vectors, class labels and a number of pixels in the two regions under consideration. The algorithm is converged when all the pixels get involved in the region merging procedure. Experimental results are presented on two remote sensing hyperspectral images acquired by the AVIRIS and ROSIS sensors. The proposed approach improves classification accuracies and provides maps with more homogeneous regions, when compared to previously proposed classification techniques.

Development of a Nonequilibrium Radiative Heating Prediction Method for Coupled Flowfield Solutions

NASA Technical Reports Server (NTRS)

Hartung, Lin C.

1991-01-01

A method for predicting radiative heating and coupling effects in nonequilibrium flow-fields has been developed. The method resolves atomic lines with a minimum number of spectral points, and treats molecular radiation using the smeared band approximation. To further minimize computational time, the calculation is performed on an optimized spectrum, which is computed for each flow condition to enhance spectral resolution. Additional time savings are obtained by performing the radiation calculation on a subgrid optimally selected for accuracy. Representative results from the new method are compared to previous work to demonstrate that the speedup does not cause a loss of accuracy and is sufficient to make coupled solutions practical. The method is found to be a useful tool for studies of nonequilibrium flows.

Optimization of pectin extraction and antioxidant activities from Jerusalem artichoke

NASA Astrophysics Data System (ADS)

Liu, Shengyi; Shi, Xuejie; Xu, Lanlan; Yi, Yuetao

2016-03-01

Jerusalem artichoke is an economic crop widely planted in saline-alkaline soil. The use of Jerusalem artichoke is of great significance. In this study, the response surface method was employed to optimize the effects of processing variables (extraction temperature, pH, extraction time, and liquid-to-solid ratio) on the yield of Jerusalem artichoke pectin. Under the optimal extraction conditions: pH 1.52, 63.62 min, 100°C and a liquid-to-solid ratio of 44.4 mL/g, the maximum pectin yield was predicted to be 18.76%. Experiments were conducted under these optimal conditions and a pectin yield of 18.52±0.90% was obtained, which validated the model prediction. The effects of diff erent drying methods (freeze drying, spray drying and vacuum drying) on the properties of Jerusalem artichoke pectin were evaluated and they were compared with apple pectin. FTIR spectral analysis showed no major structural diff erences in Jerusalem artichoke pectin samples produced by various drying treatments. The antioxidant activities of pectin dried by diff erent methods were investigated using in vitro hydroxyl and DPPH radical scavenging systems. The results revealed that the activities of spray dried pectin (SDP) and apple pectin (AP) were stronger than those of vacuum oven dried pectin (ODP) and vacuum freeze dried pectin (FDP). Therefore compared with the other two drying methods, the spray drying method was the best.

Convergence Analysis of the Graph Allen-Cahn Scheme

DTIC Science & Technology

2016-02-01

CONVERGENCE ANALYSIS OF THE GRAPH ALLEN-CAHN SCHEME ∗ XIYANG LUO† AND ANDREA L. BERTOZZI† Abstract. Graph partitioning problems have a wide range of...optimization, convergence and monotonicity are shown for a class of schemes under a graph-independent timestep restriction. We also analyze the effects of...spectral truncation, a common technique used to save computational cost. Convergence of the scheme with spectral truncation is also proved under a

Infrared reflectance spectra (4-12 micron) of lunar samples

NASA Technical Reports Server (NTRS)

Nash, Douglas B.

1991-01-01

Presented here are infrared reflectance spectra of a typical set of Apollo samples to illustrate spectral character in the mid-infrared (4 to 12 microns) of lunar materials and how the spectra varies among three main forms: soil, breccia, and igneous rocks. Reflectance data, to a close approximation, are the inverse of emission spectra; thus, for a given material the spectral reflectance (R) at any given wavelength is related to emission (E) by 1 - R equals E. Therefore, one can use reflectance spectra of lunar samples to predict how emission spectra of material on the lunar surface will appear to spectrometers on orbiting spacecraft or earthbound telescopes. Spectra were measured in the lab in dry air using a Fourier Transform Infrared spectrometer. Shown here is only the key portion (4 to 12 microns) of each spectrum relating to the principal spectral emission region for sunlit lunar materials and to where the most diagnostic spectral features occur.

Recursive Hierarchical Image Segmentation by Region Growing and Constrained Spectral Clustering

NASA Technical Reports Server (NTRS)

Tilton, James C.

2002-01-01

This paper describes an algorithm for hierarchical image segmentation (referred to as HSEG) and its recursive formulation (referred to as RHSEG). The HSEG algorithm is a hybrid of region growing and constrained spectral clustering that produces a hierarchical set of image segmentations based on detected convergence points. In the main, HSEG employs the hierarchical stepwise optimization (HS WO) approach to region growing, which seeks to produce segmentations that are more optimized than those produced by more classic approaches to region growing. In addition, HSEG optionally interjects between HSWO region growing iterations merges between spatially non-adjacent regions (i.e., spectrally based merging or clustering) constrained by a threshold derived from the previous HSWO region growing iteration. While the addition of constrained spectral clustering improves the segmentation results, especially for larger images, it also significantly increases HSEG's computational requirements. To counteract this, a computationally efficient recursive, divide-and-conquer, implementation of HSEG (RHSEG) has been devised and is described herein. Included in this description is special code that is required to avoid processing artifacts caused by RHSEG s recursive subdivision of the image data. Implementations for single processor and for multiple processor computer systems are described. Results with Landsat TM data are included comparing HSEG with classic region growing. Finally, an application to image information mining and knowledge discovery is discussed.

Reflectance analysis of porosity gradient in nanostructured silicon layers

NASA Astrophysics Data System (ADS)

Jurečka, Stanislav; Imamura, Kentaro; Matsumoto, Taketoshi; Kobayashi, Hikaru

2017-12-01

In this work we study optical properties of nanostructured layers formed on silicon surface. Nanostructured layers on Si are formed in order to reach high suppression of the light reflectance. Low spectral reflectance is important for improvement of the conversion efficiency of solar cells and for other optoelectronic applications. Effective method of forming nanostructured layers with ultralow reflectance in a broad interval of wavelengths is in our approach based on metal assisted etching of Si. Si surface immersed in HF and H2O2 solution is etched in contact with the Pt mesh roller and the structure of the mesh is transferred on the etched surface. During this etching procedure the layer density evolves gradually and the spectral reflectance decreases exponentially with the depth in porous layer. We analyzed properties of the layer porosity by incorporating the porosity gradient into construction of the layer spectral reflectance theoretical model. Analyzed layer is splitted into 20 sublayers in our approach. Complex dielectric function in each sublayer is computed by using Bruggeman effective media theory and the theoretical spectral reflectance of modelled multilayer system is computed by using Abeles matrix formalism. Porosity gradient is extracted from the theoretical reflectance model optimized in comparison to the experimental values. Resulting values of the structure porosity development provide important information for optimization of the technological treatment operations.

The Ultracool Typing Kit - An Open-Source, Qualitative Spectral Typing GUI for L Dwarfs

NASA Astrophysics Data System (ADS)

Schwab, Ellianna; Cruz, Kelle; Núñez, Alejandro; Burgasser, Adam J.; Rice, Emily; Reid, Neill; Faherty, Jacqueline K.; BDNYC

2018-01-01

The Ultracool Typing Kit (UTK) is an open-source graphical user interface for classifying the NIR spectral types of L dwarfs, including field and low-gravity dwarfs spanning L0-L9. The user is able to input an NIR spectrum and qualitatively compare the input spectrum to a full suite of spectral templates, including low-gravity beta and gamma templates. The user can choose to view the input spectrum as both a band-by-band comparison with the templates and a full bandwidth comparison with NIR spectral standards. Once an optimal qualitative comparison is selected, the user can save their spectral type selection both graphically and to a database. Using UTK to classify 78 previously typed L dwarfs, we show that a band-by-band classification method more accurately agrees with optical spectral typing systems than previous L dwarf NIR classification schemes. UTK is written in python, released on Zenodo with a BSD-3 clause license and publicly available on the BDNYC Github page.

High-frequency modulation of the four states of polarization of light with a single phase modulator

NASA Astrophysics Data System (ADS)

Compain, Eric; Drevillon, Bernard

1998-04-01

A method for light polarization modulation is described. It allows us to independently modulate, at a high frequency, the four components of the Stokes vector of light using a single phase modulator. It works in a double-pass configuration: the polarization of light is modulated a first time by the phase modulator, and is then modified by a coupling object before being modulated a second time by the same modulator. The coupling object consists of multiple glass plates, oriented at the Brewster angle, acting as a partial polarizer and in a right angle prism acting as a phase shifter and back reflector. Its polarimetric properties are obtained from refractive index contrast effects, which provides optimized and constant properties over a wide spectral range. The phase modulator can be either an electro-optic modulator providing a very high-frequency capability (up to 100 MHz) or a photoelastic modulator providing a wide spectral range capability. It is robust because there is no moving part and simple to implement because of the presence of one modulation. It displays a high level of sensitivity because all the components are high-frequency modulated. Two applications using this modulator in a polarimeter or in a polarization states generator are described. The four modulations, having the same fundamental frequency, are easily demodulated by numerical data processing. Optimized demodulation processing, adapted to the different kind of phase modulator is described. Its adaptation taking into account the bandwidth limitation and the variation of the sampling phase, are finally presented in the case of a photoelastic modulator.

Software algorithm and hardware design for real-time implementation of new spectral estimator

PubMed Central

2014-01-01

Background Real-time spectral analyzers can be difficult to implement for PC computer-based systems because of the potential for high computational cost, and algorithm complexity. In this work a new spectral estimator (NSE) is developed for real-time analysis, and compared with the discrete Fourier transform (DFT). Method Clinical data in the form of 216 fractionated atrial electrogram sequences were used as inputs. The sample rate for acquisition was 977 Hz, or approximately 1 millisecond between digital samples. Real-time NSE power spectra were generated for 16,384 consecutive data points. The same data sequences were used for spectral calculation using a radix-2 implementation of the DFT. The NSE algorithm was also developed for implementation as a real-time spectral analyzer electronic circuit board. Results The average interval for a single real-time spectral calculation in software was 3.29 μs for NSE versus 504.5 μs for DFT. Thus for real-time spectral analysis, the NSE algorithm is approximately 150× faster than the DFT. Over a 1 millisecond sampling period, the NSE algorithm had the capability to spectrally analyze a maximum of 303 data channels, while the DFT algorithm could only analyze a single channel. Moreover, for the 8 second sequences, the NSE spectral resolution in the 3-12 Hz range was 0.037 Hz while the DFT spectral resolution was only 0.122 Hz. The NSE was also found to be implementable as a standalone spectral analyzer board using approximately 26 integrated circuits at a cost of approximately $500. The software files used for analysis are included as a supplement, please see the Additional files 1 and 2. Conclusions The NSE real-time algorithm has low computational cost and complexity, and is implementable in both software and hardware for 1 millisecond updates of multichannel spectra. The algorithm may be helpful to guide radiofrequency catheter ablation in real time. PMID:24886214

Compressive Coded-Aperture Multimodal Imaging Systems

NASA Astrophysics Data System (ADS)

Rueda-Chacon, Hoover F.

Multimodal imaging refers to the framework of capturing images that span different physical domains such as space, spectrum, depth, time, polarization, and others. For instance, spectral images are modeled as 3D cubes with two spatial and one spectral coordinate. Three-dimensional cubes spanning just the space domain, are referred as depth volumes. Imaging cubes varying in time, spectra or depth, are referred as 4D-images. Nature itself spans different physical domains, thus imaging our real world demands capturing information in at least 6 different domains simultaneously, giving turn to 3D-spatial+spectral+polarized dynamic sequences. Conventional imaging devices, however, can capture dynamic sequences with up-to 3 spectral channels, in real-time, by the use of color sensors. Capturing multiple spectral channels require scanning methodologies, which demand long time. In general, to-date multimodal imaging requires a sequence of different imaging sensors, placed in tandem, to simultaneously capture the different physical properties of a scene. Then, different fusion techniques are employed to mix all the individual information into a single image. Therefore, new ways to efficiently capture more than 3 spectral channels of 3D time-varying spatial information, in a single or few sensors, are of high interest. Compressive spectral imaging (CSI) is an imaging framework that seeks to optimally capture spectral imagery (tens of spectral channels of 2D spatial information), using fewer measurements than that required by traditional sensing procedures which follows the Shannon-Nyquist sampling. Instead of capturing direct one-to-one representations of natural scenes, CSI systems acquire linear random projections of the scene and then solve an optimization algorithm to estimate the 3D spatio-spectral data cube by exploiting the theory of compressive sensing (CS). To date, the coding procedure in CSI has been realized through the use of ``block-unblock" coded apertures, commonly implemented as chrome-on-quartz photomasks. These apertures block or permit to pass the entire spectrum from the scene at given spatial locations, thus modulating the spatial characteristics of the scene. In the first part, this thesis aims to expand the framework of CSI by replacing the traditional block-unblock coded apertures by patterned optical filter arrays, referred as ``color" coded apertures. These apertures are formed by tiny pixelated optical filters, which in turn, allow the input image to be modulated not only spatially but spectrally as well, entailing more powerful coding strategies. The proposed colored coded apertures are either synthesized through linear combinations of low-pass, high-pass and band-pass filters, paired with binary pattern ensembles realized by a digital-micromirror-device (DMD), or experimentally realized through thin-film color-patterned filter arrays. The optical forward model of the proposed CSI architectures will be presented along with the design and proof-of-concept implementations, which achieve noticeable improvements in the quality of the reconstructions compared with conventional block-unblock coded aperture-based CSI architectures. On another front, due to the rich information contained in the infrared spectrum as well as the depth domain, this thesis aims to explore multimodal imaging by extending the range sensitivity of current CSI systems to a dual-band visible+near-infrared spectral domain, and also, it proposes, for the first time, a new imaging device that captures simultaneously 4D data cubes (2D spatial+1D spectral+depth imaging) with as few as a single snapshot. Due to the snapshot advantage of this camera, video sequences are possible, thus enabling the joint capture of 5D imagery. It aims to create super-human sensing that will enable the perception of our world in new and exciting ways. With this, we intend to advance in the state of the art in compressive sensing systems to extract depth while accurately capturing spatial and spectral material properties. The applications of such a sensor are self-evident in fields such as computer/robotic vision because they would allow an artificial intelligence to make informed decisions about not only the location of objects within a scene but also their material properties.

Geospatial compilation of results from field sample collection in support of mineral resource investigations, Western Alaska Range, Alaska, July 2013

USGS Publications Warehouse

Johnson, Michaela R.; Graham, Garth E.; Hubbard, Bernard E.; Benzel, William M.

2015-07-16

This Data Series summarizes results from July 2013 sampling in the western Alaska Range near Mount Estelle, Alaska. The fieldwork combined in situ and camp-based spectral measurements of talus/soil and rock samples. Five rock and 48 soil samples were submitted for quantitative geochemi­cal analysis (for 55 major and trace elements), and the 48 soils samples were also analyzed by x-ray diffraction to establish mineralogy and geochemistry. The results and sample photo­graphs are presented in a geodatabase that accompanies this report. The spectral, mineralogical, and geochemical charac­terization of these samples and the sites that they represent can be used to validate existing remote-sensing datasets (for example, ASTER) and future hyperspectral studies. Empiri­cal evidence of jarosite (as identified by x-ray diffraction and spectral analysis) corresponding with gold concentrations in excess of 50 parts per billion in soil samples suggests that surficial mapping of jarosite in regional surveys may be use­ful for targeting areas of prospective gold occurrences in this sampling area.

Using GIS servers and interactive maps in spectral data sharing and administration: Case study of Ahvaz Spectral Geodatabase Platform (ASGP)

NASA Astrophysics Data System (ADS)

Karami, Mojtaba; Rangzan, Kazem; Saberi, Azim

2013-10-01

With emergence of air-borne and space-borne hyperspectral sensors, spectroscopic measurements are gaining more importance in remote sensing. Therefore, the number of available spectral reference data is constantly increasing. This rapid increase often exhibits a poor data management, which leads to ultimate isolation of data on disk storages. Spectral data without precise description of the target, methods, environment, and sampling geometry cannot be used by other researchers. Moreover, existing spectral data (in case it accompanied with good documentation) become virtually invisible or unreachable for researchers. Providing documentation and a data-sharing framework for spectral data, in which researchers are able to search for or share spectral data and documentation, would definitely improve the data lifetime. Relational Database Management Systems (RDBMS) are main candidates for spectral data management and their efficiency is proven by many studies and applications to date. In this study, a new approach to spectral data administration is presented based on spatial identity of spectral samples. This method benefits from scalability and performance of RDBMS for storage of spectral data, but uses GIS servers to provide users with interactive maps as an interface to the system. The spectral files, photographs and descriptive data are considered as belongings of a geospatial object. A spectral processing unit is responsible for evaluation of metadata quality and performing routine spectral processing tasks for newly-added data. As a result, by using internet browser software the users would be able to visually examine availability of data and/or search for data based on descriptive attributes associated to it. The proposed system is scalable and besides giving the users good sense of what data are available in the database, it facilitates participation of spectral reference data in producing geoinformation.

Automated acoustic matrix deposition for MALDI sample preparation.

PubMed

Aerni, Hans-Rudolf; Cornett, Dale S; Caprioli, Richard M

2006-02-01

Novel high-throughput sample preparation strategies for MALDI imaging mass spectrometry (IMS) and profiling are presented. An acoustic reagent multispotter was developed to provide improved reproducibility for depositing matrix onto a sample surface, for example, such as a tissue section. The unique design of the acoustic droplet ejector and its optimization for depositing matrix solution are discussed. Since it does not contain a capillary or nozzle for fluid ejection, issues with clogging of these orifices are avoided. Automated matrix deposition provides better control of conditions affecting protein extraction and matrix crystallization with the ability to deposit matrix accurately onto small surface features. For tissue sections, matrix spots of 180-200 microm in diameter were obtained and a procedure is described for generating coordinate files readable by a mass spectrometer to permit automated profile acquisition. Mass spectral quality and reproducibility was found to be better than that obtained with manual pipet spotting. The instrument can also deposit matrix spots in a dense array pattern so that, after analysis in a mass spectrometer, two-dimensional ion images may be constructed. Example ion images from a mouse brain are presented.

Investigations of gain redshift in high peak power Ti:sapphire laser systems

NASA Astrophysics Data System (ADS)

Wu, Fenxiang; Yu, Linpeng; Zhang, Zongxin; Li, Wenkai; Yang, Xiaojun; Wu, Yuanfeng; Li, Shuai; Wang, Cheng; Liu, Yanqi; Lu, Xiaoming; Xu, Yi; Leng, Yuxin

2018-07-01

Gain redshift in high peak power Ti:sapphire laser systems can result in narrowband spectral output and hence lengthen the compressed pulse duration. In order to realize broadband spectral output in 10 PW-class Ti:sapphire lasers, the influence on gain redshift induced by spectral pre-shaping, gain distribution of cascaded amplifiers and Extraction During Pumping (EDP) technique have been investigated. The theoretical and experimental results show that the redshift of output spectrum is sensitive to the spectral pre-shaping and the gain distribution of cascaded amplifiers, while insensitive to the pumping scheme with or without EDP. Moreover, the output spectrum from our future 10 PW Ti:sapphire laser is theoretically analyzed based on the investigations above, which indicates that a Fourier-transform limited (FTL) pulse duration of 21 fs can be achieved just by optimizing the spectral pre-shaping and gain distribution in 10 PW-class Ti:sapphire lasers.

Low-Loss Coupling of Quantum Cascade Lasers into Hollow-Core Waveguides with Single-Mode Output in the 3.7-7.6 μm Spectral Range.

PubMed

Patimisco, Pietro; Sampaolo, Angelo; Mihai, Laura; Giglio, Marilena; Kriesel, Jason; Sporea, Dan; Scamarcio, Gaetano; Tittel, Frank K; Spagnolo, Vincenzo

2016-04-13

We demonstrated low-loss and single-mode laser beam delivery through hollow-core waveguides (HCWs) operating in the 3.7-7.6 μm spectral range. The employed HCWs have a circular cross section with a bore diameter of 200 μm and metallic/dielectric internal coatings deposited inside a glass capillary tube. The internal coatings have been produced to enhance the spectral response of the HCWs in the range 3.5-12 µm. We demonstrated Gaussian-like outputs throughout the 4.5-7.6 µm spectral range. A quasi single-mode output beam with only small beam distortions was achieved when the wavelength was reduced to 3.7 μm. With a 15-cm-long HCW and optimized coupling conditions, we measured coupling efficiencies of >88% and transmission losses of <1 dB in the investigated infrared spectral range.

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.

Spectral characterization of natural backgrounds

NASA Astrophysics Data System (ADS)

Winkelmann, Max

2017-10-01

As the distribution and use of hyperspectral sensors is constantly increasing, the exploitation of spectral features is a threat for camouflaged objects. To improve camouflage materials at first the spectral behavior of backgrounds has to be known to adjust and optimize the spectral reflectance of camouflage materials. In an international effort, the NATO CSO working group SCI-295 "Development of Methods for Measurements and Evaluation of Natural Background EO Signatures" is developing a method how this characterization of backgrounds has to be done. It is obvious that the spectral characterization of a background will be quite an effort. To compare and exchange data internationally the measurements will have to be done in a similar way. To test and further improve this method an international field trial has been performed in Storkow, Germany. In the following we present first impressions and lessons learned from this field campaign and describe the data that has been measured.

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.

Single-source dual-energy spectral multidetector CT of pancreatic adenocarcinoma: optimization of energy level viewing significantly increases lesion contrast.

PubMed

Patel, B N; Thomas, J V; Lockhart, M E; Berland, L L; Morgan, D E

2013-02-01

To evaluate lesion contrast in pancreatic adenocarcinoma patients using spectral multidetector computed tomography (MDCT) analysis. The present institutional review board-approved, Health Insurance Portability and Accountability Act of 1996 (HIPAA)-compliant retrospective study evaluated 64 consecutive adults with pancreatic adenocarcinoma examined using a standardized, multiphasic protocol on a single-source, dual-energy MDCT system. Pancreatic phase images (35 s) were acquired in dual-energy mode; unenhanced and portal venous phases used standard MDCT. Lesion contrast was evaluated on an independent workstation using dual-energy analysis software, comparing tumour to non-tumoural pancreas attenuation (HU) differences and tumour diameter at three energy levels: 70 keV; individual subject-optimized viewing energy level (based on the maximum contrast-to-noise ratio, CNR); and 45 keV. The image noise was measured for the same three energies. Differences in lesion contrast, diameter, and noise between the different energy levels were analysed using analysis of variance (ANOVA). Quantitative differences in contrast gain between 70 keV and CNR-optimized viewing energies, and between CNR-optimized and 45 keV were compared using the paired t-test. Thirty-four women and 30 men (mean age 68 years) had a mean tumour diameter of 3.6 cm. The median optimized energy level was 50 keV (range 40-77). The mean ± SD lesion contrast values (non-tumoural pancreas - tumour attenuation) were: 57 ± 29, 115 ± 70, and 146 ± 74 HU (p = 0.0005); the lengths of the tumours were: 3.6, 3.3, and 3.1 cm, respectively (p = 0.026); and the contrast to noise ratios were: 24 ± 7, 39 ± 12, and 59 ± 17 (p = 0.0005) for 70 keV, the optimized energy level, and 45 keV, respectively. For individuals, the mean ± SD contrast gain from 70 keV to the optimized energy level was 59 ± 45 HU; and the mean ± SD contrast gain from the optimized energy level to 45 keV was 31 ± 25 HU (p = 0.007). Significantly increased pancreatic lesion contrast was noted at lower viewing energies using spectral MDCT. Individual patient CNR-optimized energy level images have the potential to improve lesion conspicuity. Copyright © 2012 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

Visible and shortwave infrared focal planes for remote sensing instruments

NASA Astrophysics Data System (ADS)

Tower, J. R.; McCarthy, B. M.; Pellon, L. E.; Strong, R. T.; Elabd, H.

1984-01-01

The development of solid-state sensor technology for multispectral linear array (MLA) instruments is described. A buttable four-spectral-band linear-format CCD and a buttable two-spectral band linear-format short-wave IR CCD have been designed, and first samples have been demonstrated. In addition, first-sample four-band interference filters have been fabricated, and hybrid packaging technology is being developed. Based on this development work, the design and construction of focal planes for a Shuttle sortie MLA instrument have begun. This work involves a visible and near-IR focal plane with 2048 pixels x 4 spectral bands and a short-wave IR focal plane with 1024 pixels x 2 spectral bands.

The on-ground calibration performances of the hyperspectral microscope MicrOmega for the Hayabusa-2 mission

NASA Astrophysics Data System (ADS)

Riu, Lucie; Bibring, Jean-Pierre; Pilorget, Cédric; Poulet, François; Hamm, Vincent

2018-03-01

The miniaturized near-infrared hyperspectral microscope MicrOmega, on board the MASCOT lander for Hayabusa-2 mission, is designed to perform in situ measurements at the grain scale of the C-type asteroid 1999 JU3 RYUGU. MicrOmega will observe samples with a field of view of a few millimeters with a spatial sampling of 25 μm and acquire near-infrared spectra by illuminating the sample sequentially with different wavelengths from 0.99 to 3.55 μm over two spectral channels with a typical spectral sampling of 20 cm-1. The on-ground calibration of MicrOmega requires a full characterization of the nominal range of operation of the instrument, both spectral (0.99-3.55 μm) and thermal (-40 °C to +40 °C) to derive the radiometric and spectral responses combined into a 4D transfer function to convert raw signal to calibrated reflectance. This specific 4D radiometric reference gives the instrument response according to the pixel location (x,y), the wavelength and the instrument temperature. This paper reports the complex computation of the 4D radiometric reference for the 0.9-2.5 μm channel. In this spectral range, the composition of the grains of a wide variety of minerals with relevance to solar system bodies can be identified through diagnostic spectral features: mafic (pyroxene, olivine…) as well as hydrated and altered minerals that are key phases for the solar system bodies' exploration.

Preliminary study on the diagnostic value of single-source dual-energy CT in diagnosing cervical lymph node metastasis of thyroid carcinoma

PubMed Central

Zhao, Yanfeng; Li, Xiaolu; Wang, Xiaoyi; Lin, Meng; Zhao, Xinming; Luo, Dehong; Li, Jianying

2017-01-01

Background To investigate the value of single-source dual-energy spectral CT imaging in improving the accuracy of preoperative diagnosis of lymph node metastasis of thyroid carcinoma. Methods Thirty-four thyroid carcinoma patients were enrolled and received spectral CT scanning before thyroidectomy and cervical lymph node dissection surgery. Iodine-based material decomposition (MD) images and 101 sets of monochromatic images from 40 to 140 keV were reconstructed after CT scans. The iodine concentrations (IC) of lymph nodes were measured on the MD images and was normalized to that of common carotid artery to obtain the normalized iodine concentration (NIC). The CT number of lymph nodes as function of photon energy was measured on the 101 sets of images to generate a spectral HU curve and to calculate its slope λHU. The measurements between the metastatic and non-metastatic lymph nodes were statistically compared and receiver operating characteristic (ROC) curves were used to determine the optimal thresholds of these measurements for diagnosing lymph nodes metastasis. Results There were 136 lymph nodes that were pathologically confirmed. Among them, 102 (75%) were metastatic and 34 (25%) were non-metastatic. The IC, NIC and the slope λHU of the metastatic lymph nodes were 3.93±1.58 mg/mL, 0.70±0.55 and 4.63±1.91, respectively. These values were statistically higher than the respective values of 1.77±0.71 mg/mL, 0.29±0.16 and 2.19±0.91 for the non-metastatic lymph nodes (all P<0.001). ROC analysis determined the optimal diagnostic threshold for IC as 2.56 mg/mL, with the sensitivity, specificity and accuracy of 83.3%, 91.2% and 85.3%, respectively. The optimal threshold for NIC was 0.289, with the sensitivity, specificity and accuracy of 96.1%, 76.5% and 91.2%, respectively. The optimal threshold for the spectral curve slope λHU was 2.692, with the sensitivity, specificity and accuracy of 88.2%, 82.4% and 86.8%, respectively. Conclusions The measurements obtained in dual-energy spectral CT improve the sensitivity and accuracy for preoperatively diagnosing lymph node metastasis in thyroid carcinoma. PMID:29268547

Near-earth orbital guidance and remote sensing

NASA Technical Reports Server (NTRS)

Powers, W. F.

1972-01-01

The curriculum of a short course in remote sensing and parameter optimization is presented. The subjects discussed are: (1) basics of remote sensing and the user community, (2) multivariant spectral analysis, (3) advanced mathematics and physics of remote sensing, (4) the atmospheric environment, (5) imaging sensing, and (6)nonimaging sensing. Mathematical models of optimization techniques are developed.

Design and evaluation of a THz time domain imaging system using standard optical design software.

PubMed

Brückner, Claudia; Pradarutti, Boris; Müller, Ralf; Riehemann, Stefan; Notni, Gunther; Tünnermann, Andreas

2008-09-20

A terahertz (THz) time domain imaging system is analyzed and optimized with standard optical design software (ZEMAX). Special requirements to the illumination optics and imaging optics are presented. In the optimized system, off-axis parabolic mirrors and lenses are combined. The system has a numerical aperture of 0.4 and is diffraction limited for field points up to 4 mm and wavelengths down to 750 microm. ZEONEX is used as the lens material. Higher aspherical coefficients are used for correction of spherical aberration and reduction of lens thickness. The lenses were manufactured by ultraprecision machining. For optimization of the system, ray tracing and wave-optical methods were combined. We show how the ZEMAX Gaussian beam analysis tool can be used to evaluate illumination optics. The resolution of the THz system was tested with a wire and a slit target, line gratings of different period, and a Siemens star. The behavior of the temporal line spread function can be modeled with the polychromatic coherent line spread function feature in ZEMAX. The spectral and temporal resolutions of the line gratings are compared with the respective modulation transfer function of ZEMAX. For maximum resolution, the system has to be diffraction limited down to the smallest wavelength of the spectrum of the THz pulse. Then, the resolution on time domain analysis of the pulse maximum can be estimated with the spectral resolution of the center of gravity wavelength. The system resolution near the optical axis on time domain analysis of the pulse maximum is 1 line pair/mm with an intensity contrast of 0.22. The Siemens star is used for estimation of the resolution of the whole system. An eight channel electro-optic sampling system was used for detection. The resolution on time domain analysis of the pulse maximum of all eight channels could be determined with the Siemens star to be 0.7 line pairs/mm.

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.

Matched spectral filter based on reflection holograms for analyte identification.

PubMed

Cao, Liangcai; Gu, Claire

2009-12-20

A matched spectral filter set that provides automatic preliminary analyte identification is proposed and analyzed. Each matched spectral filter in the set containing the multiple spectral peaks corresponding to the Raman spectrum of a substance is capable of collecting the specified spectrum into the detector simultaneously. The filter set is implemented by multiplexed volume holographic reflection gratings. The fabrication of a matched spectral filter in an Fe:LiNbO(3) crystal is demonstrated to match the Raman spectrum of the sample Rhodamine 6G (R6G). An interference alignment method is proposed and used in the fabrication to ensure that the multiplexed gratings are in the same direction at a high angular accuracy of 0.0025 degrees . Diffused recording beams are used to control the bandwidth of the spectral peaks. The reflection spectrum of the filter is characterized using a modified Raman spectrometer. The result of the filter's reflection spectrum matches that of the sample R6G. A library of such matched spectral filters will facilitate a fast detection with a higher sensitivity and provide a capability for preliminary molecule identification.

Radiometric calibration of optical microscopy and microspectroscopy apparata over a broad spectral range using a special thin-film luminescence standard

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

Valenta, J., E-mail: jan.valenta@mff.cuni.cz; Greben, M.

2015-04-15

Application capabilities of optical microscopes and microspectroscopes can be considerably enhanced by a proper calibration of their spectral sensitivity. We propose and demonstrate a method of relative and absolute calibration of a microspectroscope over an extraordinary broad spectral range covered by two (parallel) detection branches in visible and near-infrared spectral regions. The key point of the absolute calibration of a relative spectral sensitivity is application of the standard sample formed by a thin layer of Si nanocrystals with stable and efficient photoluminescence. The spectral PL quantum yield and the PL spatial distribution of the standard sample must be characterized bymore » separate experiments. The absolutely calibrated microspectroscope enables to characterize spectral photon emittance of a studied object or even its luminescence quantum yield (QY) if additional knowledge about spatial distribution of emission and about excitance is available. Capabilities of the calibrated microspectroscope are demonstrated by measuring external QY of electroluminescence from a standard poly-Si solar-cell and of photoluminescence of Er-doped Si nanocrystals.« less

Calibration Transfer in LIBS and Raman Spectroscopy for Planetary Applications

NASA Astrophysics Data System (ADS)

Dyar, M. D.; Thomas, B. F.; Parente, M.; Gemp, I.; Mullen, T. H.

2017-12-01

Planetary scientists rely on spectral libraries and instrument reproducibility to interpret results from missions. Major investments have been made into assembling libraries, but they often naively assume that spectra of single crystals versus powders and from varying instruments will be the same. Calibration transfer (CT) seeks to algorithmically resolve discrepancies among datasets from different instruments or conditions. It offers the ability to align suites of spectra with a small number of common samples, allowing better models to be built with combined data sets. LIBS and Raman data present different challenges for CT. Quantitative geochemical analyses by LIBS spectroscopy are limited by lack of consistency among repeated laser shots and across instruments. Many different factors affect the presence/absence of emission lines and their intensities, such as laser power/plasma temperature, angle of incidence, detector sensitivity/resolution. To overcome these, models in which disparate datasets are projected into a joint low-dimensional subspace where all data can be aligned before quantitative analysis, such as Correlation Analysis for Domain Adaptation (CADA), have proven very effective. They require some overlap between the populations of spectra to be aligned. For example, prediction of SiO2 on 80 samples from two different LIBS labs show errors of ±16-29 wt.% when the training and test sets have no overlap, and ±4.94 wt% SiO2 when CADA is used. Uncorrected Earth-Mars spectral differences are likely to cause errors with the same order of magnitude. As with other types of reflectance spectroscopy, Raman data are plagued by differences among single crystal/powder samples and laser wavelength that affect peak intensities, and by spectral offsets from instruments with varying resolution and wavenumber alignment schemes. These problems persist even within the archetypal RRUFF database. Pre-processing transformation functions such as optimized baseline removal, normalization, squashing, and smoothing improve mineral matching accuracy. Alignment methods can record shifts between corresponding peaks from the same mineral from pairs of instruments. By considering many pairs of minerals, corrections at each energy increment can be determined, creating a transfer function to align the data.

[Estimation and Visualization of Nitrogen Content in Citrus Canopy Based on Two Band Vegetation Index (TBVI)].

PubMed

Wang, Qiao-nan; Ye, Xu-jun; Li, Jin-meng; Xiao, Yu-zhao; He, Yong

2015-03-01

Nitrogen is a necessary and important element for the growth and development of fruit orchards. Timely, accurate and nondestructive monitoring of nitrogen status in fruit orchards would help maintain the fruit quality and efficient production of the orchard, and mitigate the pollution of water resources caused by excessive nitrogen fertilization. This study investigated the capability of hyperspectral imagery for estimating and visualizing the nitrogen content in citrus canopy. Hyperspectral images were obtained for leaf samples in laboratory as well as for the whole canopy in the field with ImSpector V10E (Spectral Imaging Ltd., Oulu, Finland). The spectral datas for each leaf sample were represented by the average spectral data extracted from the selected region of interest (ROI) in the hyperspectral images with the aid of ENVI software. The nitrogen content in each leaf sample was measured by the Dumas combustion method with the rapid N cube (Elementar Analytical, Germany). Simple correlation analysis and the two band vegetation index (TBVI) were then used to develop the spectra data-based nitrogen content prediction models. Results obtained through the formula calculation indicated that the model with the two band vegetation index (TBVI) based on the wavelengths 811 and 856 nm achieved the optimal estimation of nitrogen content in citrus leaves (R2 = 0.607 1). Furthermore, the canopy image for the identified TBVI was calculated, and the nitrogen content of the canopy was visualized by incorporating the model into the TBVI image. The tender leaves, middle-aged leaves and elder leaves showed distinct nitrogen status from highto low-levels in the canopy image. The results suggested the potential of hyperspectral imagery for the nondestructive detection and diagnosis of nitrogen status in citrus canopy in real time. Different from previous studies focused on nitrogen content prediction at leaf level, this study succeeded in predicting and visualizing the nutrient content of fruit trees at canopy level. This would provide valuable information for the implementation of individual tree-based fertilization schemes in precision orchard management practices.