Cardiovascular response to acute stress in freely moving rats: time-frequency analysis.

PubMed

Loncar-Turukalo, Tatjana; Bajic, Dragana; Japundzic-Zigon, Nina

2008-01-01

Spectral analysis of cardiovascular series is an important tool for assessing the features of the autonomic control of the cardiovascular system. In this experiment Wistar rats ecquiped with intraarterial catheter for blood pressure (BP) recording were exposed to stress induced by blowing air. The problem of non stationary data was overcomed applying the Smoothed Pseudo Wigner Villle (SPWV) time-frequency distribution. Spectral analysis was done before stress, during stress, immediately after stress and later in recovery. The spectral indices were calculated for both systolic blood pressure (SBP) and pulse interval (PI) series. The time evolution of spectral indices showed perturbed sympathovagal balance.

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

Fu, Li; Zhang, Yun; Wei, Zhehao

We report in this work detailed measurements on the chiral and achiral sum-frequency vibrational spectra in the C-H stretching vibration region (2800-3050cm-1) of the air/liquid interfaces of R-limonene and S-limonene, using the recently developed high-resolution broadband sum-frequency generation vibrational spectroscopy (HR-BB-SFG-VS). The achiral SFG spectra of R-limonene and S-limonene, as well as the equal amount (50/50) racemic mixture show that the enantiomers are with the same interfacial orientations. The interference chiral SFG spectra of the limonene enantiomers exhibit spectral signature from chiral response of the Cα-H stretching mode, and spectral signature from prochiral response of the CH2 asymmetric stretching mode,more » respectively. The chiral spectral feature of the Cα-H stretching mode changes sign from R-limonene to S-limonene, and disappears for the 50/50 racemic mixture. While the prochiral spectral feature of the CH2 asymmetric stretching mode is the same for R-limonene and S-limonene, and also surprisingly remains the same for the 50/50 racemic mixture. These results provided detail information in understanding the structure and chirality of molecular interfaces, and demonstrated the sensitivity and potential of SFG-VS as unique spectroscopic tool for chirality characterization and chiral recognition at the molecular interface.« less

Scaling within the spectral function approach

NASA Astrophysics Data System (ADS)

Sobczyk, J. E.; Rocco, N.; Lovato, A.; Nieves, J.

2018-03-01

Scaling features of the nuclear electromagnetic response functions unveil aspects of nuclear dynamics that are crucial for interpreting neutrino- and electron-scattering data. In the large momentum-transfer regime, the nucleon-density response function defines a universal scaling function, which is independent of the nature of the probe. In this work, we analyze the nucleon-density response function of 12C, neglecting collective excitations. We employ particle and hole spectral functions obtained within two distinct many-body methods, both widely used to describe electroweak reactions in nuclei. We show that the two approaches provide compatible nucleon-density scaling functions that for large momentum transfers satisfy first-kind scaling. Both methods yield scaling functions characterized by an asymmetric shape, although less pronounced than that of experimental scaling functions. This asymmetry, only mildly affected by final state interactions, is mostly due to nucleon-nucleon correlations, encoded in the continuum component of the hole spectral function.

Infrared responsivity of a pyroelectric detector with a single-wall carbon nanotube coating.

PubMed

Theocharous, E; Engtrakul, C; Dillon, A C; Lehman, J

2008-08-01

The performance of a 10 mm diameter pyroelectric detector coated with a single-wall carbon nanotube (SWCNT) was evaluated in the 0.8 to 20 microm wavelength range. The relative spectral responsivity of this detector exhibits significant fluctuations over the wavelength range examined. This is consistent with independent absorbance measurements, which show that SWCNTs exhibit selective absorption bands in the visible and near-infrared. The performance of the detector in terms of noise equivalent power and detectivity in wavelength regions of high coating absorptivity was comparable with gold-black-coated pyroelectric detectors based on 50 microm thick LiTaO(3) crystals. The response of this detector was shown to be nonlinear for DC equivalent photocurrents >10(-9) A, and its spatial uniformity of response was comparable with other pyroelectric detectors utilizing gold-black coatings. The nonuniform spectral responsivity exhibited by the SWCNT-coated detector is expected to severely restrict the use of SWCNTs as black coatings for thermal detectors. However, the deposition of SWCNT coatings on a pyroelectric crystal followed by the study of the prominence of the spectral features in the relative spectral responsivity of the resultant pyroelectric detectors is shown to provide an effective method for quantifying the impurity content in SWCNT samples.

Exploiting spectral content for image segmentation in GPR data

NASA Astrophysics Data System (ADS)

Wang, Patrick K.; Morton, Kenneth D., Jr.; Collins, Leslie M.; Torrione, Peter A.

2011-06-01

Ground-penetrating radar (GPR) sensors provide an effective means for detecting changes in the sub-surface electrical properties of soils, such as changes indicative of landmines or other buried threats. However, most GPR-based pre-screening algorithms only localize target responses along the surface of the earth, and do not provide information regarding an object's position in depth. As a result, feature extraction algorithms are forced to process data from entire cubes of data around pre-screener alarms, which can reduce feature fidelity and hamper performance. In this work, spectral analysis is investigated as a method for locating subsurface anomalies in GPR data. In particular, a 2-D spatial/frequency decomposition is applied to pre-screener flagged GPR B-scans. Analysis of these spatial/frequency regions suggests that aspects (e.g. moments, maxima, mode) of the frequency distribution of GPR energy can be indicative of the presence of target responses. After translating a GPR image to a function of the spatial/frequency distributions at each pixel, several image segmentation approaches can be applied to perform segmentation in this new transformed feature space. To illustrate the efficacy of the approach, a performance comparison between feature processing with and without the image segmentation algorithm is provided.

Multivariable passive RFID vapor sensors: roll-to-roll fabrication on a flexible substrate.

PubMed

Potyrailo, Radislav A; Burns, Andrew; Surman, Cheryl; Lee, D J; McGinniss, Edward

2012-06-21

We demonstrate roll-to-roll (R2R) fabrication of highly selective, battery-free radio frequency identification (RFID) sensors on a flexible polyethylene terephthalate (PET) polymeric substrate. Selectivity of our developed RFID sensors is provided by measurements of their resonance impedance spectra, followed by the multivariate analysis of spectral features, and correlation of these spectral features to the concentrations of vapors of interest. The multivariate analysis of spectral features also provides the ability for the rejection of ambient interferences. As a demonstration of our R2R fabrication process, we employed polyetherurethane (PEUT) as a "classic" sensing material, extruded this sensing material as 25, 75, and 125-μm thick films, and thermally laminated the films onto RFID inlays, rapidly producing approximately 5000 vapor sensors. We further tested these RFID vapor sensors for their response selectivity toward several model vapors such as toluene, acetone, and ethanol as well as water vapor as an abundant interferent. Our RFID sensing concept features 16-bit resolution provided by the sensor reader, granting a highly desired independence from costly proprietary RFID memory chips with a low-resolution analog input. Future steps are being planned for field-testing of these sensors in numerous conditions.

Spectral-Spatial Scale Invariant Feature Transform for Hyperspectral Images.

PubMed

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

2018-02-01

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

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

PubMed

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

2018-01-01

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

NIR small arms muzzle flash

NASA Astrophysics Data System (ADS)

Montoya, Joseph; Kennerly, Stephen; Rede, Edward

2010-04-01

Utilization of Near-Infrared (NIR) spectral features in a muzzle flash will allow for small arms detection using low cost silicon (Si)-based imagers. Detection of a small arms muzzle flash in a particular wavelength region is dependent on the intensity of that emission, the efficiency of source emission transmission through the atmosphere, and the relative intensity of the background scene. The NIR muzzle flash signature exists in the relatively large Si spectral response wavelength region of 300 nm-1100 nm, which allows for use of commercial-off-the-shelf (COTS) Si-based detectors. The alkali metal origin of the NIR spectral features in the 7.62 × 39-mm round muzzle flash is discussed, and the basis for the spectral bandwidth is examined, using a calculated Voigt profile. This report will introduce a model of the 7.62 × 39-mm NIR muzzle flash signature based on predicted source characteristics. Atmospheric limitations based on NIR spectral regions are investigated in relation to the NIR muzzle flash signature. A simple signal-to-clutter ratio (SCR) metric is used to predict sensor performance based on a model of radiance for the source and solar background and pixel registered image subtraction.

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.

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

NASA Astrophysics Data System (ADS)

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

2013-05-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

Ultrafast spectral dynamics of dual-color-soliton intracavity collision in a mode-locked fiber laser

NASA Astrophysics Data System (ADS)

Wei, Yuan; Li, Bowen; Wei, Xiaoming; Yu, Ying; Wong, Kenneth K. Y.

2018-02-01

The single-shot spectral dynamics of dual-color-soliton collisions inside a mode-locked laser is experimentally and numerically investigated. By using the all-optically dispersive Fourier transform, we spectrally unveil the collision-induced soliton self-reshaping process, which features dynamic spectral fringes over the soliton main lobe, and the rebuilding of Kelly sidebands with wavelength drifting. Meanwhile, the numerical simulations validate the experimental observation and provide additional insights into the physical mechanism of the collision-induced spectral dynamics from the temporal domain perspective. It is verified that the dynamic interference between the soliton and the dispersive waves is responsible for the observed collision-induced spectral evolution. These dynamic phenomena not only demonstrate the role of dispersive waves in the sophisticated soliton interaction inside the laser cavity, but also facilitate a deeper understanding of the soliton's inherent stability.

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.

Multivariate Analysis of Mixed Lipid Aggregate Phase Transitions Monitored Using Raman Spectroscopy.

PubMed

Neal, Sharon L

2018-01-01

The phase behavior of aqueous 1,2-dimyristoyl-sn-glycero-3-phosphorylcholine (DMPC)/1,2-dihexanoyl-sn-glycero-3-phosphocholine (DHPC) mixtures between 8.0 ℃ and 41.0 ℃ were monitored using Raman spectroscopy. Temperature-dependent Raman matrices were assembled from series of spectra and subjected to multivariate analysis. The consensus of pseudo-rank estimation results is that seven to eight components account for the temperature-dependent changes observed in the spectra. The spectra and temperature response profiles of the mixture components were resolved by applying a variant of the non-negative matrix factorization (NMF) algorithm described by Lee and Seung (1999). The rotational ambiguity of the data matrix was reduced by augmenting the original temperature-dependent spectral matrix with its cumulative counterpart, i.e., the matrix formed by successive integration of the spectra across the temperature index (columns). Successive rounds of constrained NMF were used to isolate component spectra from a significant fluorescence background. Five major components exhibiting varying degrees of gel and liquid crystalline lipid character were resolved. Hydrogen-bonded water networks exhibiting varying degrees of organization are associated with the lipid components. Spectral parameters were computed to compare the chain conformation, packing, and hydration indicated by the resolved spectra. Based on spectral features and relative amounts of the components observed, four components reflect long chain lipid response. The fifth component could reflect the response of the short chain lipid, DHPC, but there were no definitive spectral features confirming this assignment. A minor component of uncertain assignment that exhibits a striking response to the DMPC pre-transition and chain melting transition also was recovered. While none of the spectra resolved exhibit features unequivocally attributable to a specific aggregate morphology or step in the gelation process, the results are consistent with the evolution of mixed phase bicelles (nanodisks) and small amounts of worm-like DMPC/DHPC aggregates, and perhaps DHPC micelles, at low temperature to suspensions of branched and entangled worm-like aggregates above the DMPC gel phase transition and perforated multi-lamellar aggregates at high temperature.

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

NASA Astrophysics Data System (ADS)

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

2014-01-01

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

Data compressive paradigm for multispectral sensing using tunable DWELL mid-infrared detectors.

PubMed

Jang, Woo-Yong; Hayat, Majeed M; Godoy, Sebastián E; Bender, Steven C; Zarkesh-Ha, Payman; Krishna, Sanjay

2011-09-26

While quantum dots-in-a-well (DWELL) infrared photodetectors have the feature that their spectral responses can be shifted continuously by varying the applied bias, the width of the spectral response at any applied bias is not sufficiently narrow for use in multispectral sensing without the aid of spectral filters. To achieve higher spectral resolutions without using physical spectral filters, algorithms have been developed for post-processing the DWELL's bias-dependent photocurrents resulting from probing an object of interest repeatedly over a wide range of applied biases. At the heart of these algorithms is the ability to approximate an arbitrary spectral filter, which we desire the DWELL-algorithm combination to mimic, by forming a weighted superposition of the DWELL's non-orthogonal spectral responses over a range of applied biases. However, these algorithms assume availability of abundant DWELL data over a large number of applied biases (>30), leading to large overall acquisition times in proportion with the number of biases. This paper reports a new multispectral sensing algorithm to substantially compress the number of necessary bias values subject to a prescribed performance level across multiple sensing applications. The algorithm identifies a minimal set of biases to be used in sensing only the relevant spectral information for remote-sensing applications of interest. Experimental results on target spectrometry and classification demonstrate a reduction in the number of required biases by a factor of 7 (e.g., from 30 to 4). The tradeoff between performance and bias compression is thoroughly investigated. © 2011 Optical Society of America

Results from the calibration of the Extreme Ultraviolet Explorer instruments

NASA Technical Reports Server (NTRS)

Welsh, Barry Y.; Jelinsky, Pat; Vedder, Peter W.; Vallerga, John V.; Finley, David S.; Malina, Roger F.

1991-01-01

The paper describes the main features and selected results of the calibration of the scientific instruments to be flown on the Extreme Ultraviolet Explorer in 1991. The instrument payload includes three grazing incidence scanning telescopes and an EUV spectrometer/deep survey instrument covering the spectral region 70-800 A. The measured imaging characteristics, the effective areas, and the details of spectral responses of the instruments are presented. Diagrams of the cross-sectional views of the scanning telescope and the deep-survey/spectrometer telescope are included.

M.S.L.A.P. Modular Spectral Line Analysis Program documentation

NASA Technical Reports Server (NTRS)

Joseph, Charles L.; Jenkins, Edward B.

1991-01-01

MSLAP is a software for analyzing spectra, providing the basic structure to identify spectral features, to make quantitative measurements of this features, and to store the measurements for convenient access. MSLAP can be used to measure not only the zeroth moment (equivalent width) of a profile, but also the first and second moments. Optical depths and the corresponding column densities across the profile can be measured as well for sufficiently high resolution data. The software was developed for an interactive, graphical analysis where the computer carries most of the computational and data organizational burden and the investigator is responsible only for all judgement decisions. It employs sophisticated statistical techniques for determining the best polynomial fit to the continuum and for calculating the uncertainties.

[Features of adaptive responses in right-handers and left-handers, and their relationship to the functional activity of the brain].

PubMed

Barkar, A A; Markina, L D

2014-01-01

In the article there is considered the relationship between adaptation state of the organism and features of bioelectric activity of the brain in right-handers and left-handers. Practically healthy persons of both genders, 23-45 years of age, with the chronic stress disorder were examined. Adaptation status was evaluated with a computer software "Anti-stress", features of bioelectric brain activity were detected by means of spectral and coherent EEG analysis, also the character of motor and sensory asymmetries was determined. The obtained data showed that the response of the organism to excitators of varying strength is a system one and manifested at different levels; adaptation status and bioelectrical activity in right-handers and left-handers have features.

[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.

Characterizing the marsh dieback spectral response at the plant and canopy level with hyperspectral and temporal remote sensing data

USGS Publications Warehouse

Ramsey, E.; Rangoonwala, A.

2008-01-01

We describe newly developed remote sensing tools to map the localized occurrences and regional distribution of the marsh dieback in coastal Louisiana (Fig. 1). As a final goal of our research and development, we identified what spectral features accompanied the onset of dieback and could be directly linked to the optical signal measured at the satellite. In order to accomplish our research goal, we carried out two interlinked objectives. First, we determined the spectral features within the hyperspectral spectra of the impacted plant that could be linked to the spectral return. This was accomplished by measuring the differences in leaf optical properties of impacted and non impacted marsh plants in such a way that the measured differences could be linked to the dieback onset and progression. The spectral analyses were constrained to selected wavelengths (bands of reflectance data) historically associated with changes in leaf composition and structure caused by changes in the plant biophysical environment. Second, we determined what changes in the canopy reflectance (canopy signal sensed at the satellite) could be linked to dieback onset and progression. Third, we transformed a suite of six Landsat Thematic Mapper images collected before, during, and in the final stages of dieback to maps of dieback occurrences. ??2008 IEEE.

Model reductions using a projection formulation

NASA Technical Reports Server (NTRS)

De Villemagne, Christian; Skelton, Robert E.

1987-01-01

A new methodology for model reduction of MIMO systems exploits the notion of an oblique projection. A reduced model is uniquely defined by a projector whose range space and orthogonal to the null space are chosen among the ranges of generalized controllability and observability matrices. The reduced order models match various combinations (chosen by the designer) of four types of parameters of the full order system associated with (1) low frequency response, (2) high frequency response, (3) low frequency power spectral density, and (4) high frequency power spectral density. Thus, the proposed method is a computationally simple substitute for many existing methods, has an extreme flexibility to embrace combinations of existing methods and offers some new features.

Comparison of two feature selection methods for the separability analysis of intertidal sediments with spectrometric datasets in the German Wadden Sea

NASA Astrophysics Data System (ADS)

Jung, Richard; Ehlers, Manfred

2016-10-01

The spectral features of intertidal sediments are all influenced by the same biophysical properties, such as water, salinity, grain size or vegetation and therefore they are hard to separate by using only multispectral sensors. This could be shown by a previous study of Jung et al. (2015). A more detailed analysis of their characteristic spectral feature has to be carried out to understand the differences and similarities. Spectrometry data (i.e., hyperspectral sensors), for instance, have the opportunity to measure the reflection of the landscape as a continuous spectral pattern for each pixel of an image built from dozen to hundreds of narrow spectral bands. This reveals a high potential to measure unique spectral responses of different ecological conditions (Hennig et al., 2007). In this context, this study uses spectrometric datasets to distinguish between 14 different sediment classes obtained from a study area in the German Wadden Sea. A new feature selection method is proposed (Jeffries-Matusita distance bases feature selection; JMDFS), which uses the Euclidean distance to eliminate the wavelengths with the most similar reflectance values in an iterative process. Subsequent to each iteration, the separation capability is estimated by the Jeffries-Matusita distance (JMD). Two classes can be separated if the JMD is greater than 1.9 and if less than four wavelengths remain, no separation can be assumed. The results of the JMDFS are compared with a state-of-the-art feature selection method called ReliefF. Both methods showed the ability to improve the separation by achieving overall accuracies greater than 82%. The accuracies are 4%-13% better than the results with all wavelengths applied. The number of remaining wavelengths is very diverse and ranges from 14 to 213 of 703. The advantage of JMDFS compared with ReliefF is clearly the processing time. ReliefF needs 30 min for one temporary result. It is necessary to repeat the process several times and to average all temporary results to achieve a final result. In this study 50 iterations were carried out, which makes four days of processing. In contrast, JMDFS needs only 30 min for a final result.

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

PubMed

Liu, Da; Li, Jianxun

2016-12-16

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

Can Infrared Spectroscopy Be Used to Measure Change in Potassium Nitrate Concentration as a Proxy for Soil Particle Movement?

PubMed Central

Luleva, Mila Ivanova; van der Werff, Harald; Jetten, Victor; van der Meer, Freek

2011-01-01

Displacement of soil particles caused by erosion influences soil condition and fertility. To date, the cesium 137 isotope (137Cs) technique is most commonly used for soil particle tracing. However when large areas are considered, the expensive soil sampling and analysis present an obstacle. Infrared spectral measurements would provide a solution, however the small concentrations of the isotope do not influence the spectral signal sufficiently. Potassium (K) has similar electrical, chemical and physical properties as Cs. Our hypothesis is that it can be used as possible replacement in soil particle tracing. Soils differing in texture were sampled for the study. Laboratory soil chemical analyses and spectral sensitivity analyses were carried out to identify the wavelength range related to K concentration. Different concentrations of K fertilizer were added to soils with varying texture properties in order to establish spectral characteristics of the absorption feature associated with the element. Changes in position of absorption feature center were observed at wavelengths between 2,450 and 2,470 nm, depending on the amount of fertilizer applied. Other absorption feature parameters (absorption band depth, width and area) were also found to change with K concentration with coefficient of determination between 0.85 and 0.99. Tracing soil particles using K fertilizer and infrared spectral response is considered suitable for soils with sandy and sandy silt texture. It is a new approach that can potentially grow to a technique for rapid monitoring of soil particle movement over large areas. PMID:22163843

Prediction of spectral acceleration response ordinates based on PGA attenuation

USGS Publications Warehouse

Graizer, V.; Kalkan, E.

2009-01-01

Developed herein is a new peak ground acceleration (PGA)-based predictive model for 5% damped pseudospectral acceleration (SA) ordinates of free-field horizontal component of ground motion from shallow-crustal earthquakes. The predictive model of ground motion spectral shape (i.e., normalized spectrum) is generated as a continuous function of few parameters. The proposed model eliminates the classical exhausted matrix of estimator coefficients, and provides significant ease in its implementation. It is structured on the Next Generation Attenuation (NGA) database with a number of additions from recent Californian events including 2003 San Simeon and 2004 Parkfield earthquakes. A unique feature of the model is its new functional form explicitly integrating PGA as a scaling factor. The spectral shape model is parameterized within an approximation function using moment magnitude, closest distance to the fault (fault distance) and VS30 (average shear-wave velocity in the upper 30 m) as independent variables. Mean values of its estimator coefficients were computed by fitting an approximation function to spectral shape of each record using robust nonlinear optimization. Proposed spectral shape model is independent of the PGA attenuation, allowing utilization of various PGA attenuation relations to estimate the response spectrum of earthquake recordings.

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

PubMed Central

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

2013-01-01

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

T-ray relevant frequencies for osteosarcoma classification

NASA Astrophysics Data System (ADS)

Withayachumnankul, W.; Ferguson, B.; Rainsford, T.; Findlay, D.; Mickan, S. P.; Abbott, D.

2006-01-01

We investigate the classification of the T-ray response of normal human bone cells and human osteosarcoma cells, grown in culture. Given the magnitude and phase responses within a reliable spectral range as features for input vectors, a trained support vector machine can correctly classify the two cell types to some extent. Performance of the support vector machine is deteriorated by the curse of dimensionality, resulting from the comparatively large number of features in the input vectors. Feature subset selection methods are used to select only an optimal number of relevant features for inputs. As a result, an improvement in generalization performance is attainable, and the selected frequencies can be used for further describing different mechanisms of the cells, responding to T-rays. We demonstrate a consistent classification accuracy of 89.6%, while the only one fifth of the original features are retained in the data set.

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

NASA Technical Reports Server (NTRS)

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

1990-01-01

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

Using Whispering-Gallery-Mode Resonators for Refractometry

NASA Technical Reports Server (NTRS)

Matsko, Andrey; Savchenkov, Anatoliy; Strekalov, Dmitry; Iltchenko, Vladimir; Maleki, Lute

2010-01-01

A method of determining the refractive and absorptive properties of optically transparent materials involves a combination of theoretical and experimental analysis of electromagnetic responses of whispering-gallery-mode (WGM) resonator disks made of those materials. The method was conceived especially for use in studying transparent photorefractive materials, for which purpose this method affords unprecedented levels of sensitivity and accuracy. The method is expected to be particularly useful for measuring temporally varying refractive and absorptive properties of photorefractive materials at infrared wavelengths. Still more particularly, the method is expected to be useful for measuring drifts in these properties that are so slow that, heretofore, the properties were assumed to be constant. The basic idea of the method is to attempt to infer values of the photorefractive properties of a material by seeking to match (1) theoretical predictions of the spectral responses (or selected features thereof) of a WGM of known dimensions made of the material with (2) the actual spectral responses (or selected features thereof). Spectral features that are useful for this purpose include resonance frequencies, free spectral ranges (differences between resonance frequencies of adjacently numbered modes), and resonance quality factors (Q values). The method has been demonstrated in several experiments, one of which was performed on a WGM resonator made from a disk of LiNbO3 doped with 5 percent of MgO. The free spectral range of the resonator was approximately equal to 3.42 GHz at wavelengths in the vicinity of 780 nm, the smallest full width at half maximum of a mode was approximately equal to 50 MHz, and the thickness of the resonator in the area of mode localization was 30 microns. In the experiment, laser power of 9 mW was coupled into the resonator with an efficiency of 75 percent, and the laser was scanned over a frequency band 9 GHz wide at a nominal wavelength of approximately equal to 780 nm. Resonance frequencies were measured as functions of time during several hours of exposure to the laser light. The results of these measurements, plotted in the figure, show a pronounced collective frequency drift of the resonator modes. The size of the drift has been estimated to correspond to a change of 8.5 x 10(exp -5) in the effective ordinary index of refraction of the resonator material.

Effects of spectral and temporal disruption on cortical encoding of gerbil vocalizations

PubMed Central

Ter-Mikaelian, Maria; Semple, Malcolm N.

2013-01-01

Animal communication sounds contain spectrotemporal fluctuations that provide powerful cues for detection and discrimination. Human perception of speech is influenced both by spectral and temporal acoustic features but is most critically dependent on envelope information. To investigate the neural coding principles underlying the perception of communication sounds, we explored the effect of disrupting the spectral or temporal content of five different gerbil call types on neural responses in the awake gerbil's primary auditory cortex (AI). The vocalizations were impoverished spectrally by reduction to 4 or 16 channels of band-passed noise. For this acoustic manipulation, an average firing rate of the neuron did not carry sufficient information to distinguish between call types. In contrast, the discharge patterns of individual AI neurons reliably categorized vocalizations composed of only four spectral bands with the appropriate natural token. The pooled responses of small populations of AI cells classified spectrally disrupted and natural calls with an accuracy that paralleled human performance on an analogous speech task. To assess whether discharge pattern was robust to temporal perturbations of an individual call, vocalizations were disrupted by time-reversing segments of variable duration. For this acoustic manipulation, cortical neurons were relatively insensitive to short reversal lengths. Consistent with human perception of speech, these results indicate that the stable representation of communication sounds in AI is more dependent on sensitivity to slow temporal envelopes than on spectral detail. PMID:23761696

Angle-dependent modulated spectral peaks of proton beams generated in ultrashort intense laser-solid interactions

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

Su, L. N.; Hu, Z. D.; Zheng, Y.

2014-09-15

Proton acceleration from 4 μm thick aluminum foils irradiated by 30-TW Ti:sapphire laser pulses is investigated using an angle-resolved proton energy spectrometer. We find that a modulated spectral peak at ∼0.82 MeV is presented at 2.5° off the target normal direction. The divergence angle of the modulated zone is 3.8°. Two-dimensional particle-in-cell simulations reveal that self-generated toroidal magnetic field at the rear surface of the target foil is responsible for the modulated spectral feature. The field deflects the low energy protons, resulting in the modulated energy spectrum with certain peaks.

Enhanced Vertical Perception through Head-Related Impulse Response Customization Based on Pinna Response Tuning in the Median Plane

NASA Astrophysics Data System (ADS)

Shin, Ki Hoon; Park, Youngjin

Human's ability to perceive elevation of a sound and distinguish whether a sound is coming from the front or rear strongly depends on the monaural spectral features of the pinnae. In order to realize an effective virtual auditory display by HRTF (head-related transfer function) customization, the pinna responses were isolated from the median HRIRs (head-related impulse responses) of 45 individual HRIRs in the CIPIC HRTF database and modeled as linear combinations of 4 or 5 basic temporal shapes (basis functions) per each elevation on the median plane by PCA (principal components analysis) in the time domain. By tuning the weight of each basis function computed for a specific height to replace the pinna response in the KEMAR HRIR at the same height with the resulting customized pinna response and listening to the filtered stimuli over headphones, 4 individuals with normal hearing sensitivity were able to create a set of HRIRs that outperformed the KEMAR HRIRs in producing vertical effects with reduced front/back ambiguity in the median plane. Since the monaural spectral features of the pinnae are almost independent of azimuthal variation of the source direction, similar vertical effects could also be generated at different azimuthal directions simply by varying the ITD (interaural time difference) according to the direction as well as the size of each individual's own head.

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

NASA Technical Reports Server (NTRS)

Clark, Roger N.; Swayze, Gregg A.

1995-01-01

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

Spectral and Spatial Analysis of Volatile Deposits in Io's Loki Patera

NASA Astrophysics Data System (ADS)

Landis, C. E.; Howell, R. R.

2012-12-01

Loki Patera is an active volcanic feature approximately 200 km in diameter on Jupiter's moon Io. The goals of this research are to better understand the nature of volatile distribution in and around the Loki region. Images taken by Voyager I show a number of bright features distributed across the patera surface. These features, referred to as "bergs," may be fumaroles which allow sulfur gases from the lava beneath the hardened crust to escape onto the surface. By examining the spatial distribution of the bergs and the spectral signatures of bergs and other features around Loki Patera, we can better understand their role in the volcanic activity observed at Loki, and perhaps elsewhere on Io. Spectral data from the Voyager and Galileo missions were examined using ISIS3, a program suite developed by the USGS. Photometric corrections were applied to the images to adjust for changes in lighting geometry. The spatial distribution of the bergs was examined using ArcMap. Initial results indicate that the bergs seldom occur near the inner and outer edges of the patera, which are known to be hotter than other parts of the patera. The lack of bergs in this area suggests that thermal properties of the crust may control the distribution of the bergs. The spacing of the bergs, which on average are about 6 km from each other, and other distribution statistics are used to test whether there is some maximum area of crust in which one berg can accommodate the escaping gases. The spectral signatures of the bergs themselves are compared to other surface features in and around the patera. Further study of the bergs and other features will continue to shed light on the underlying geologic and volcanic processes responsible for the activity at Loki. This work was supported in part by NASA JDAP grant NNX09AE06G.

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

PubMed

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

2017-06-01

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

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

NASA Astrophysics Data System (ADS)

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

2015-11-01

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

Enhancement of color saturation and color gamut enabled by a dual-band color filter exhibiting an adjustable spectral response.

PubMed

Shrestha, Vivek Raj; Park, Chul-Soon; Lee, Sang-Shin

2014-02-10

The enhancement of color saturation and color gamut has been demonstrated, by taking advantage of a dual-band color filter based on a subwavelength rectangular metal-dielectric resonant grating, which exhibits an adjustable spectral response with respect to its relative transmittances at the two bands of green and red, thereby producing any color in between green and red, through the adjustment of incoming light polarization. Also, the prominent features of the spectral response of the filter, namely the bandwidth and resonant wavelength, can be readily adjusted by varying the dielectric layer thickness and the grating pitch, respectively. The dependence of chromaticity coordinates of the filter in the CIE (International Commission on Illumination) 1931 chromaticity diagram upon the parameters of the spectral response, including the center wavelength, spectral bandwidth and sideband level, has been rigorously examined, and their influence on the color gamut and the excitation purity, which is a colorimetric measure of saturation, has been analytically explored at the same time, in order to optimize the color performance of the filters. In particular, a device with wider spectral bandwidth was observed to efficiently extend the color gamut and enhance the color saturation, i.e. the excitation purity for a given sideband level. Two dual-band green-red filters, exhibiting different bandwidths of about 17 and 36 nm, were specifically designed and fabricated. As compared with the case with narrower bandwidth, the device with wider bandwidth was observed to provide both higher excitation purity leading to better color saturation and greater separation of the chromaticity coordinates for the filter output for different incident polarizations, which provides extended color gamut. The proposed device structure may permit the color tuning span to encompass all primary color bands, by adjusting the grating pitch.

Satellite and airborne oil spill remote sensing: State of the art and application to the BP DeepWater Horizon oil spill

USGS Publications Warehouse

Leifer, I.; Clark, R.; Jones, C.; Holt, B.; Svejkovsky, J.; Swayze, G.

2011-01-01

The vast, persistent, and unconstrained oil release from the DeepWater Horizon (DWH) challenged the spill response, which required accurate quantitative oil assessment at synoptic and operational scales. Experienced observers are the mainstay of oil spill response. Key limitations are weather, scene illumination geometry, and few trained observers, leading to potential observer bias. Aiding the response was extensive passive and active satellite and airborne remote sensing, including intelligent system augmentation, reviewed herein. Oil slick appearance strongly depends on many factors like emulsion composition and scene geometry, yielding false positives and great thickness uncertainty. Oil thicknesses and the oil to water ratios for thick slicks were derived quantitatively with a new spectral library approach based on the shape and depth of spectral features related to C-H vibration bands. The approach used near infrared, imaging spectroscopy data from the AVIRIS (Airborne Visual/InfraRed Imaging Spectrometer) instrument on the NASA ER-2 stratospheric airplane. Extrapolation to the total slick used MODIS satellite visual-spectrum broadband data, which observes sunglint reflection from surface slicks; i.e., indicates the presence of oil and/or surfactant slicks. Oil slick emissivity is less than seawater's allowing MODIS thermal infrared (TIR) nighttime identification; however, water temperature variations can cause false positives. Some strong emissivity features near 6.7 and 9.7 ??m could be analyzed as for the AVIRIS short wave infrared features, but require high spectral resolution data. TIR spectral trends can allow fresh/weathered oil discrimination. Satellite Synthetic Aperture Radar (SSAR) provided synoptic data under all-sky conditions by observing oil dampening of capillary waves; however, SSAR typically cannot discriminate thick from thin oil slicks. Airborne UAVSAR's significantly greater signal-to-noise ratio and fine spatial resolution allowed successful mapping of oil slick thickness-related patterns. Laser induced fluorescence (LIF) can quantify oil thicknesses by Raman scattering line distortions, but saturates for >20-??m thick oil and depends on oil optical characteristics and sea state. Combined with laser bathymetry LIF can provide submerged oil remote sensing.

Processing of Presolar Grains around Post-Asymptotic Giant Branch Stars: Silicon Carbide as the Carrier of the 21 Micron Feature

NASA Astrophysics Data System (ADS)

Speck, Angela K.; Hofmeister, Anne M.

2004-01-01

Some proto-planetary nebulae (PPNs) exhibit an enigmatic feature in their infrared spectra at ~21 μm. This feature is not seen in the spectra of either the precursors to PPNs, the asymptotic giant branch (AGB) stars, or the successors of PPNs, ``normal'' planetary nebulae (PNs). However, the 21 μm feature has been seen in the spectra of PNs with Wolf-Rayet central stars. Therefore, the carrier of this feature is unlikely to be a transient species that only exists in the PPN phase. This feature has been attributed to various molecular and solid-state species, none of which satisfy all constraints, although titanium carbide (TiC) and polycyclic aromatic hydrocarbons (PAHs) have seemed the most viable. We present new laboratory data for silicon carbide (SiC) and show that it has a spectral feature that is a good candidate for the carrier of the 21 μm feature. The SiC spectral feature appears at approximately the same wavelength (depending on the polytype/grain size) and has the same asymmetric profile as the observed astronomical feature. We suggest that processing and cooling of the SiC grains known to exist around carbon-rich AGB stars are responsible for the emergence of the enigmatic 21 μm feature. The emergence of this feature in the spectra of post-AGB stars demonstrates the processing of dust due to the changing physical environments around evolving stars.

Simulating charge transport to understand the spectral response of Swept Charge Devices

NASA Astrophysics Data System (ADS)

Athiray, P. S.; Sreekumar, P.; Narendranath, S.; Gow, J. P. D.

2015-11-01

Context. Swept Charge Devices (SCD) are novel X-ray detectors optimized for improved spectral performance without any demand for active cooling. The Chandrayaan-1 X-ray Spectrometer (C1XS) experiment onboard the Chandrayaan-1 spacecraft used an array of SCDs to map the global surface elemental abundances on the Moon using the X-ray fluorescence (XRF) technique. The successful demonstration of SCDs in C1XS spurred an enhanced version of the spectrometer on Chandrayaan-2 using the next-generation SCD sensors. Aims: The objective of this paper is to demonstrate validation of a physical model developed to simulate X-ray photon interaction and charge transportation in a SCD. The model helps to understand and identify the origin of individual components that collectively contribute to the energy-dependent spectral response of the SCD. Furthermore, the model provides completeness to various calibration tasks, such as generating spectral matrices (RMFs - redistribution matrix files), estimating efficiency, optimizing event selection logic, and maximizing event recovery to improve photon-collection efficiency in SCDs. Methods: Charge generation and transportation in the SCD at different layers related to channel stops, field zones, and field-free zones due to photon interaction were computed using standard drift and diffusion equations. Charge collected in the buried channel due to photon interaction in different volumes of the detector was computed by assuming a Gaussian radial profile of the charge cloud. The collected charge was processed further to simulate both diagonal clocking read-out, which is a novel design exclusive for SCDs, and event selection logic to construct the energy spectrum. Results: We compare simulation results of the SCD CCD54 with measurements obtained during the ground calibration of C1XS and clearly demonstrate that our model reproduces all the major spectral features seen in calibration data. We also describe our understanding of interactions at different layers of SCD that contribute to the observed spectrum. Using simulation results, we identify the origin of different spectral features and quantify their contributions.

Polycyclic aromatic hydrocarbon molecules in astrophysics

NASA Astrophysics Data System (ADS)

Rastogi, Shantanu; Pathak, Amit; Maurya, Anju

2013-06-01

Polycyclic aromatic hydrocarbon (PAH) molecules are responsible for the mid-infrared emission features. Their ubiquitous presence in almost all types of astrophysical environments and related variations in their spectral profilesmake them an important tool to understand the physics and chemistry of the interstellar medium. The observed spectrum is generally a composite superposition of all different types of PAHs possible in the region. In the era of space telescopes the spectral richness of the emission features has enhanced their importance as probe and also the need to understand the variations with respect to PAH size, type and ionic state. Quantum computational studies of PAHs have proved useful in elucidating the profile variations and put constraints on the possible types of PAHs in different environments. The study of PAHs has also significantly contributed to the problems of diffuse interstellar bands (DIBs), UV extinction and understanding the chemistry of the formation of complex organics in space. The review highlights the results of various computational models for the understanding of infrared emission features, the PAH-DIB relation, formation of prebiotics and possible impact in the understanding of far-infrared features.

Radiometric responsivity determination for Feature Identification and Location Experiment (FILE) flown on space shuttle mission

NASA Technical Reports Server (NTRS)

Wilson, R. G.; Davis, R. E.; Wright, R. E., Jr.; Sivertson, W. E., Jr.; Bullock, G. F.

1986-01-01

A procedure was developed to obtain the radiometric (radiance) responsivity of the Feature Identification and Local Experiment (FILE) instrument in preparation for its flight on Space Shuttle Mission 41-G (November 1984). This instrument was designed to obtain Earth feature radiance data in spectral bands centered at 0.65 and 0.85 microns, along with corroborative color and color-infrared photographs, and to collect data to evaluate a technique for in-orbit autonomous classification of the Earth's primary features. The calibration process incorporated both solar radiance measurements and radiative transfer model predictions in estimating expected radiance inputs to the FILE on the Shuttle. The measured data are compared with the model predictions, and the differences observed are discussed. Application of the calibration procedure to the FILE over an 18-month period indicated a constant responsivity characteristic. This report documents the calibration procedure and the associated radiometric measurements and predictions that were part of the instrument preparation for flight.

Fatigue crack detection by nonlinear spectral correlation with a wideband input

NASA Astrophysics Data System (ADS)

Liu, Peipei; Sohn, Hoon

2017-04-01

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

Documentation of procedures for textural/spatial pattern recognition techniques

NASA Technical Reports Server (NTRS)

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

1976-01-01

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

Understanding reconstructed Dante spectra using high resolution spectroscopy

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

May, M. J., E-mail: may13@llnl.gov; Widmann, K.; Kemp, G. E.

2016-11-15

The Dante is an 18 channel filtered diode array used at the National Ignition Facility (NIF) to measure the spectrally and temporally resolved radiation flux between 50 eV and 20 keV from various targets. The absolute flux is determined from the radiometric calibration of the x-ray diodes, filters, and mirrors and a reconstruction algorithm applied to the recorded voltages from each channel. The reconstructed spectra are very low resolution with features consistent with the instrument response and are not necessarily consistent with the spectral emission features from the plasma. Errors may exist between the reconstructed spectra and the actual emissionmore » features due to assumptions in the algorithm. Recently, a high resolution convex crystal spectrometer, VIRGIL, has been installed at NIF with the same line of sight as the Dante. Spectra from L-shell Ag and Xe have been recorded by both VIRGIL and Dante. Comparisons of these two spectroscopic measurements yield insights into the accuracy of the Dante reconstructions.« less

Hyperspectral data discrimination methods

NASA Astrophysics Data System (ADS)

Casasent, David P.; Chen, Xuewen

2000-12-01

Hyperspectral data provides spectral response information that provides detailed chemical, moisture, and other description of constituent parts of an item. These new sensor data are useful in USDA product inspection. However, such data introduce problems such as the curse of dimensionality, the need to reduce the number of features used to accommodate realistic small training set sizes, and the need to employ discriminatory features and still achieve good generalization (comparable training and test set performance). Several two-step methods are compared to a new and preferable single-step spectral decomposition algorithm. Initial results on hyperspectral data for good/bad almonds and for good/bad (aflatoxin infested) corn kernels are presented. The hyperspectral application addressed differs greatly from prior USDA work (PLS) in which the level of a specific channel constituent in food was estimated. A validation set (separate from the test set) is used in selecting algorithm parameters. Threshold parameters are varied to select the best Pc operating point. Initial results show that nonlinear features yield improved performance.

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

NASA Astrophysics Data System (ADS)

Yang, Jianping; Li, Jun

2018-02-01

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

A theoretical investigation of soliton induced supercontinuum generation in liquid core photonic crystal fiber and dual core optical fiber

NASA Astrophysics Data System (ADS)

Porsezian, K.; Nithyanandan, K.; Vasantha Jayakantha Raja, R.; Ganapathy, R.

2013-07-01

The supercontinuum generation (SCG) in liquid core photonic crystal fiber (LCPCF) with versatile nonlinear response and the spectral broadening in dual core optical fiber is presented. The analysis is presented in two phase, phase I deals with the SCG in LCPCF with the effect of saturable nonlinearity and re-orientational nonlinearity. We identify and discuss the generic nature of the saturable nonlinearity and reorientational nonlinearity in the SCG, using suitable model. For the physical explanation, modulational instability and soliton fission techniques is implemented to investigate the impact of saturable nonlinear response and slow nonlinear response, respectively. It is observed that the saturable nonlinearity inevitably suppresses the MI and the subsequent SCG. On the other hand, the re-orientational nonlinearity contributes to the slow nonlinear response in addition to the conventional fast response due to the electronic contribution. The phase II features the exclusive investigation of the spectral broadening in the dual core optical fiber.

Calculation of Electronic and Optical Properties of AgGaO2 Polymorphs Using Many-Body Approaches

NASA Astrophysics Data System (ADS)

Dadsetani, Mehrdad; Nejatipour, Reihan

2018-02-01

Ab initio calculations based on many-body perturbation theory have been used to study the electronic and optical properties of AgGaO2 in rhombohedral, hexagonal, and orthorhombic phases. GW calculations showed that AgGaO2 is an indirect-bandgap semiconductor in all three phases with energy bandgap of 2.35 eV, 2.23 eV, and 2.07 eV, in good agreement with available experimental values. By solving the Bethe-Salpeter equation (BSE) using the full potential linearized augmented plane wave basis, optical properties of the AgGaO2 polymorphs were calculated and compared with those obtained using the GW-corrected random phase approximation (RPA) and with existing experimental data. Strong anisotropy in the optical absorption spectra was observed, and the excitonic structures which were absent in the RPA calculations were reproduced in GWBSE calculations, in good agreement with the optical absorption spectrum of the rhombohedral phase. While modifying peak positions and intensities of the absorption spectra, the GWBSE gave rise to the redistribution of oscillator strengths. In comparison with the z-polarized response, excitonic effects in the x-polarized response were dominant. In the x- (and y-) polarized responses of r- and h-AgGaO2, spectral features and excitonic effects occur at the lower energies, but in the case of o-AgGaO2, the spectral structures of the z-polarized response occur at lower energies. In addition, the low-energy loss functions of AgGaO2 were calculated and compared using the GWBSE approach. Spectral features in the energy loss function components near the bandgap region were attributed to corresponding excitonic structures in the imaginary part of the dielectric function.

Hybridization and electron-phonon coupling in ferroelectric BaTiO3 probed by resonant inelastic x-ray scattering

NASA Astrophysics Data System (ADS)

Fatale, S.; Moser, S.; Miyawaki, J.; Harada, Y.; Grioni, M.

2016-11-01

We investigated the ferroelectric perovskite material BaTiO3 by resonant inelastic x-ray scattering (RIXS) at the Ti L3 edge. We observe with decreasing temperature a transfer of spectral weight from the elastic to the charge-transfer spectral features, indicative of increasing Ti 3 d -O 2 p hybridization. When the incident photon energy selects transitions to the Ti 3 d eg manifold, the quasielastic RIXS response exhibits a tail indicative of phonon excitations. A fit of the spectral line shape by a theoretical model allows us to estimate the electron-phonon coupling strength M ˜0.25 eV, which places BaTiO3 in the intermediate coupling regime.

[Spectral features analysis of sea ice in the Arctic Ocean].

PubMed

Ke, Chang-qing; Xie, Hong-jie; Lei, Rui-bo; Li, Qun; Sun, Bo

2012-04-01

Sea ice in the Arctic Ocean plays an important role in the global climate change, and its quick change and impact are the scientists' focus all over the world. The spectra of different kinds of sea ice were measured with portable ASD FieldSpec 3 spectrometer during the long-term ice station of the 4th Chinese national Arctic Expedition in 2010, and the spectral features were analyzed systematically. The results indicated that the reflectance of sea ice covered by snow is the highest one, naked sea ice the second, and melted sea ice the lowest. Peak and valley characteristics of spectrum curves of sea ice covered by thick snow, thin snow, wet snow and snow crystal are very significant, and the reflectance basically decreases with the wavelength increasing. The rules of reflectance change with wavelength of natural sea ice, white ice and blue ice are basically same, the reflectance of them is medium, and that of grey ice is far lower than natural sea ice, white ice and blue ice. It is very significant for scientific research to analyze the spectral features of sea ice in the Arctic Ocean and to implement the quantitative remote sensing of sea ice, and to further analyze its response to the global warming.

Humor drawings evoked temporal and spectral EEG processes

PubMed Central

Kuo, Hsien-Chu; Chuang, Shang-Wen

2017-01-01

Abstract The study aimed to explore the humor processing elicited through the manipulation of artistic drawings. Using the Comprehension–Elaboration Theory of humor as the main research background, the experiment manipulated the head portraits of celebrities based on the independent variables of facial deformation (large/small) and addition of affective features (positive/negative). A 64-channel electroencephalography was recorded in 30 participants while viewing the incongruous drawings of celebrities. The electroencephalography temporal and spectral responses were measured during the three stages of humor which included incongruity detection, incongruity comprehension and elaboration of humor. Analysis of event-related potentials indicated that for humorous vs non-humorous drawings, facial deformation and the addition of affective features significantly affected the degree of humor elicited, specifically: large > small deformation; negative > positive affective features. The N170, N270, N400, N600-800 and N900-1200 components showed significant differences, particularly in the right prefrontal and frontal regions. Analysis of event-related spectral perturbation showed significant differences in the theta band evoked in the anterior cingulate cortex, parietal region and posterior cingulate cortex; and in the alpha and beta bands in the motor areas. These regions are involved in emotional processing, memory retrieval, and laughter and feelings of amusement induced by elaboration of the situation. PMID:28402573

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

PubMed

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

2015-01-01

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

Dual-band plasmonic resonator based on Jerusalem cross-shaped nanoapertures

NASA Astrophysics Data System (ADS)

Cetin, Arif E.; Kaya, Sabri; Mertiri, Alket; Aslan, Ekin; Erramilli, Shyamsunder; Altug, Hatice; Turkmen, Mustafa

2015-06-01

In this paper, we both experimentally and numerically introduce a dual-resonant metamaterial based on subwavelength Jerusalem cross-shaped apertures. We numerically investigate the physical origin of the dual-resonant behavior, originating from the constituting aperture elements, through finite difference time domain calculations. Our numerical calculations show that at the dual-resonances, the aperture system supports large and easily accessible local electromagnetic fields. In order to experimentally realize the aperture system, we utilize a high-precision and lift-off free fabrication method based on electron-beam lithography. We also introduce a fine-tuning mechanism for controlling the dual-resonant spectral response through geometrical device parameters. Finally, we show the aperture system's highly advantageous far- and near-field characteristics through numerical calculations on refractive index sensitivity. The quantitative analyses on the availability of the local fields supported by the aperture system are employed to explain the grounds behind the sensitivity of each spectral feature within the dual-resonant behavior. Possessing dual-resonances with large and accessible electromagnetic fields, Jerusalem cross-shaped apertures can be highly advantageous for wide range of applications demanding multiple spectral features with strong nearfield characteristics.

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

PubMed Central

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

2015-01-01

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

The growing population of dark objects that have high emissivity contrast

NASA Astrophysics Data System (ADS)

Sunshine, Jessica M.; Kelley, Michael S. P.; McAdam, Margaret M.

2017-10-01

At visible and near-infrared wavelengths dark asteroids, Trojan asteroids, and cometary nuclei are largely featureless and are thus characterized and compared primarily based on differences in their spectral slopes. In contrast, in the mid-infrared a series of telescopic observations (e.g., ISO, Spitzer, SOFIA) have revealed subtle but clear silicate emissions in the 9-11 µm region. For the most part, these features are very low in spectral contrast (~5%). However, Emery et al. (2006) showed that Spitzer spectra of Trojan asteroids can have much larger spectral contrast (~10-15%) akin to cometary comae and dust in planetary disks. Similar high-contrast silicate features were found by Kelley et al. (2017) in Spitzer spectra of bare cometary nuclei. Together these results suggest the presence of fine grained and likely highly porous surfaces (Emery et al., 2006; Vernazza et al., 2012). Here we report on archival spectroscopy with the Spitzer Space Telescope that shows two mainbelt asteroids 267 Tirza (D-type; 55 km diameter) and 1284 Lativa (T/L-type; 40 km diameter) also have strong 10 µm silicate emission features. Moreover, the shapes of their silicate features match those of the other Trojan D-types; the best agreement is with 1172 Aneas. If high porosity is responsible for the enhanced spectra contrast in these objects, that porosity must now be explained for objects over an extended range of heliocentric distances, sizes, and that likely have different accretionary and impact histories.

The Growing Population of Dark Objects Inferred to Have High Surface Porosity

NASA Astrophysics Data System (ADS)

Sunshine, J. M.; Kelley, M. S. P.; McAdam, M. M.

2017-12-01

At visible and near-infrared wavelengths dark asteroids, Trojan asteroids, and cometary nuclei are largely featureless and are thus characterized and compared primarily based on differences in their spectral slopes. In contrast, in the mid-infrared a series of telescopic observations (e.g., ISO, Spitzer, SOFIA) have revealed subtle but clear silicate emissions in the 9-11 µm region. These features are mostly very low in spectral contrast ( 5%). However, Emery et al. (2006) showed that Spitzer spectra of Trojan asteroids can have much larger spectral contrast ( 10-15%) akin to cometary comae and dust in planetary disks. Similar high-contrast silicate features were found by Kelley et al. (2017) in Spitzer spectra of bare cometary nuclei. Together these results suggest the presence of fine grained and likely highly porous surfaces (Emery et al., 2006; Vernazza et al., 2012). Here we report on archival spectroscopy with the Spitzer Space Telescope that shows two mainbelt asteroids 267 Tirza (D-type; 55 km diameter) and 1284 Lativa (T/L-type; 40 km diameter) also have strong 10 µm silicate emission features. Moreover, the shapes of their silicate features match those of the other Trojan D-types. The best agreement is with 1172 Aneas. If high porosity is responsible for the enhanced spectra contrast in these objects, that porosity must now be explained for objects over an extended range of heliocentric distances, sizes, and that likely have different accretionary and impact histories.

Detecting Proxima b’s Atmosphere with JWST Targeting CO2 at 15 μm Using a High-pass Spectral Filtering Technique

NASA Astrophysics Data System (ADS)

Snellen, I. A. G.; Désert, J.-M.; Waters, L. B. F. M.; Robinson, T.; Meadows, V.; van Dishoeck, E. F.; Brandl, B. R.; Henning, T.; Bouwman, J.; Lahuis, F.; Min, M.; Lovis, C.; Dominik, C.; Van Eylen, V.; Sing, D.; Anglada-Escudé, G.; Birkby, J. L.; Brogi, M.

2017-08-01

Exoplanet Proxima b will be an important laboratory for the search for extraterrestrial life for the decades ahead. Here, we discuss the prospects of detecting carbon dioxide at 15 μm using a spectral filtering technique with the Medium Resolution Spectrograph (MRS) mode of the Mid-Infrared Instrument (MIRI) on the James Webb Space Telescope (JWST). At superior conjunction, the planet is expected to show a contrast of up to 100 ppm with respect to the star. At a spectral resolving power of R = 1790-2640, about 100 spectral CO2 features are visible within the 13.2-15.8 μm (3B) band, which can be combined to boost the planet atmospheric signal by a factor of 3-4, depending on the atmospheric temperature structure and CO2 abundance. If atmospheric conditions are favorable (assuming an Earth-like atmosphere), with this new application to the cross-correlation technique, carbon dioxide can be detected within a few days of JWST observations. However, this can only be achieved if both the instrumental spectral response and the stellar spectrum can be determined to a relative precision of ≤1 × 10-4 between adjacent spectral channels. Absolute flux calibration is not required, and the method is insensitive to the strong broadband variability of the host star. Precise calibration of the spectral features of the host star may only be attainable by obtaining deep observations of the system during inferior conjunction that serve as a reference. The high-pass filter spectroscopic technique with the MIRI MRS can be tested on warm Jupiters, Neptunes, and super-Earths with significantly higher planet/star contrast ratios than the Proxima system.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

IMF and [Na/Fe] abundance ratios from optical and NIR spectral features in early-type galaxies

NASA Astrophysics Data System (ADS)

La Barbera, F.; Vazdekis, A.; Ferreras, I.; Pasquali, A.; Allende Prieto, C.; Röck, B.; Aguado, D. S.; Peletier, R. F.

2017-01-01

We present a joint analysis of the four most prominent sodium-sensitive features (Na D, Na I λ8190Å, Na I λ1.14 μm, and Na I λ2.21 μm), in the optical and near-infrared spectral ranges, of two nearby, massive (σ ˜ 300 km s-1), early-type galaxies (named XSG1 and XSG2). Our analysis relies on deep Very Large Telescope/X-Shooter long-slit spectra, along with newly developed stellar population models, allowing for [Na/Fe] variations, up to ˜1.2 dex, over a wide range of age, total metallicity, and initial mass function (IMF) slope. The new models show that the response of the Na-dependent spectral indices to [Na/Fe] is stronger when the IMF is bottom heavier. For the first time, we are able to match all four Na features in the central regions of massive early-type galaxies finding an overabundance of [Na/Fe] in the range 0.5-0.7 dex and a bottom-heavy IMF. Therefore, individual abundance variations cannot be fully responsible for the trends of gravity-sensitive indices, strengthening the case towards a non-universal IMF. Given current limitations of theoretical atmosphere models, our [Na/Fe] estimates should be taken as upper limits. For XSG1, where line strengths are measured out to ˜0.8 Re, the radial trend of [Na/Fe] is similar to [α/Fe] and [C/Fe], being constant out to ˜0.5 Re, and decreasing by ˜0.2-0.3 dex at ˜0.8 Re, without any clear correlation with local metallicity. Such a result seems to be in contrast to the predicted increase of Na nucleosynthetic yields from asymptotic giant branch stars and Type II supernovae. For XSG1, the Na-inferred IMF radial profile is consistent, within the errors, with that derived from TiO features and the Wing-Ford band presented in a recent paper.

Monochromatic Measurements of the JPSS-1 VIIRS Polarization Sensitivity

NASA Technical Reports Server (NTRS)

McIntire, Jeff; Moyer, David; Brown, Steven W.; Lykke, Keith R.; Waluschka, Eugene; Oudrari, Hassan; Xiong, Xiaoxiong

2016-01-01

Polarization sensitivity is a critical property that must be characterized for spaceborne remote sensing instruments designed to measure reflected solar radiation. Broadband testing of the first Joint Polar-orbiting Satellite System (JPSS-1) Visible Infrared Imaging Radiometer Suite (VIIRS) showed unexpectedly large polarization sensitivities for the bluest bands on VIIRS (centered between 400 and 600 nm). Subsequent ray trace modeling indicated that large diattenuation on the edges of the bandpass for these spectral bands was the driver behind these large sensitivities. Additional testing using the National Institute of Standards and Technologies Traveling Spectral Irradiance and Radiance Responsivity Calibrations Using Uniform Sources was added to the test program to verify and enhance the model. The testing was limited in scope to two spectral bands at two scan angles; nonetheless, this additional testing provided valuable insight into the polarization sensitivity. Analysis has shown that the derived diattenuation agreed with the broadband measurements to within an absolute difference of about0.4 and that the ray trace model reproduced the general features of the measured data. Additionally, by deriving the spectral responsivity, the linear diattenuation is shown to be explicitly dependent on the changes in bandwidth with polarization state.

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

NASA Astrophysics Data System (ADS)

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

2000-10-01

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

Voyager planetary radio astronomy studies

NASA Technical Reports Server (NTRS)

Staelin, David H.; Eikenberry, Stephen S.

1993-01-01

Analysis of nonthermal radio emission data obtained by the Planetary Radio Astronomy (PRA) spectrometers on the Voyager 1 and 2 spacecraft was performed. This PRA data provided unique insights into the radio emission characteristics of the outer planets because of PRA's unique spectral response below the terrestrial ionospheric plasma frequency and its unprecedented proximity to the source. Of those results which were documented or published, this final report surveys only the highlights and cites references for more complete discussions. Unpublished results for Uranus, Neptune, and theoretical Ionian current distributions are presented at greater length. The most important conclusion to be drawn from these observations is that banded spectral emission is common to the radio emission below 1-2 MHz observed from all four Jovian planets. In every case multiple spectral features evolve on time scales of seconds to minutes. To the extent these features drift in frequency, they appear never to cross one another. The Neptunian spectral features appear to drift little or not at all, their evolution consisting principally of waxing and waning. Since other evidence strongly suggests that most or all of this radio emission is occurring near the local magnetospheric electron cyclotron frequency, this implies that this emission preferentially occurs at certain continually changing planetary radii. It remains unknown why certain radii might be favored, unless radial electric field components or other means serve to differentiate radially the magnetospheric plasma density, particle energy vectors, or particle coherence. Calculation of the spatial distribution and intensity of the Io-generated magnetospheric currents are also presented; these currents may be limited principally by wave impedance and local field strengths.

Intercomparison of Carbonate Deposits on Mars: VNIR Spectral Character and Geologic Context

NASA Astrophysics Data System (ADS)

Wiseman, S.; Mustard, J. F.; Ehlmann, B. L.

2012-12-01

Carbonate-bearing deposits were identified on Mars at multiple locations using CRISM VNIR spectral data [1,2,3,4,5]. Carbonates exhibit distinctive C-O related absorption features near 2300, 2500, 3400 and 3900nm that can be used to identify specific carbonate phases (e.g., Mg-carbonates have band minima at 2300/2500nm and Fe-carbonates have minima at 2330/2530nm [6]). The features at 2300 and 2500nm are the focus of most CRISM analyses because this part of the spectral range is well calibrated, lacks strong contributions from thermal emission, and is not impacted by strong water-related absorptions near 3000nm (e.g., in Fe/Mg phyllosilicates). However, multiple other phases also exhibit features near 2300 and 2500nm.For carbonates, the depth of the 2500nm feature is stronger than at 2300nm as opposed to most Fe/Mg phyllosilicates. Mixing of the carbonate with other phases in CRISM pixels impacts the band centers and strengths of the 2300 and 2500nm features and therefore complicates identification of the carbonate phase(s) responsible for observed CRISM spectral features. In this study we analyze CRISM data fully corrected for the atmosphere using DISORT radiative transfer modeling [7,8] to evaluate CRISM spectra of multiple carbonate-bearing deposits. Rigorous intercomparison of CRISM spectra extracted from different images is affected by variable aerosol, CO2 and water vapor features left by the standard volcano scan empirical atmospheric correction [9]. While residual gas absorptions are commonly suppressed by ratioing, the appearance of spectral features in ratio spectra is impacted by spectral features in the dominator spectrum compromising detailed assessments of ratio spectra derived from different images. Atmospheric correction is particularly important for interpreting carbonate deposits because the 2500nm carbonate feature overlaps with atmospheric water vapor absorptions. In Nili Fossae, carbonates occur in association with olivine, smectite, serpentine [1,10], and possibly talc [11].These carbonates are hypothesized to have formed via alteration of olivine and/or serpentine under surface or low temperature hydrothermal conditions [1,11,12] Laboratory spectra of Mg carbonates (magnesite/hydromagnesite) are the closest matches to the Nili Fossae carbonates [1]. CRISM spectra of carbonates in and around Huygens basin are interpreted to be Fe and/or Ca carbonates [3], similar to carbonate spectra described by [2]. However, the CRISM carbonate-bearing spectra are mixed with Fe/Mg phyllosilicates [1,2,3], making a one to one comparison among Martian and laboratory carbonate spectra challenging. [1] Ehlmann et al. (2008), Sci., 322, 1828-1831, [2] Michalski and. Niles (2010), Nat. Geo., 3, 751-55, [3] Wray et al. (2011), LPSC, #2635, [4] Bishop et al. (2012), LPSC, #2330, [5] Carter and Poulet (2012), Icarus, [6] Gaffey (1987), JGR, 92, 1429-1440, [7] Stamnes et al. (1999), Appl. Opt., 27, 2502-2509, [8] Wolff et al. (2009), JGR, 11, [9] Wiseman et al., 2010, LPSC , #2461, [10] Ehlmann et al. (2010), GRL, 37, [11] Brown et al. (2010), EPSL, 297, 174-182. [12] Ehlmann et al. (2009), JGR, 114.

Airborne spectroradiometry: The application of AIS data to detecting subtle mineral absorption features

NASA Technical Reports Server (NTRS)

Cocks, T. D.; Green, A. A.

1986-01-01

Analysis of Airborne Imaging Spectrometer (AIS) data acquired in Australia has revealed a number of operational problems. Horizontal striping in AIS imagery and spectral distortions due to order overlap were investigated. Horizontal striping, caused by grating position errors can be removed with little or no effect on spectral details. Order overlap remains a problem that seriously compromises identification of subtle mineral absorption features within AIS spectra. A spectrometric model of the AIS was developed to assist in identifying spurious spectral features, and will be used in efforts to restore the spectral integrity of the data.

Microstructure Analysis of Bismuth Absorbers for Transition-Edge Sensor X-ray Microcalorimeters

NASA Astrophysics Data System (ADS)

Yan, Daikang; Divan, Ralu; Gades, Lisa M.; Kenesei, Peter; Madden, Timothy J.; Miceli, Antonino; Park, Jun-Sang; Patel, Umeshkumar M.; Quaranta, Orlando; Sharma, Hemant; Bennett, Douglas A.; Doriese, William B.; Fowler, Joseph W.; Gard, Johnathon D.; Hays-Wehle, James P.; Morgan, Kelsey M.; Schmidt, Daniel R.; Swetz, Daniel S.; Ullom, Joel N.

2018-03-01

Given its large X-ray stopping power and low specific heat capacity, bismuth (Bi) is a promising absorber material for X-ray microcalorimeters and has been used with transition-edge sensors (TESs) in the past. However, distinct X-ray spectral features have been observed in TESs with Bi absorbers deposited with different techniques. Evaporated Bi absorbers are widely reported to have non-Gaussian low-energy tails, while electroplated ones do not show this feature. In this study, we fabricated Bi absorbers with these two methods and performed microstructure analysis using scanning electron microscopy and X-ray diffraction microscopy. The two types of material showed the same crystallographic structure, but the grain size of the electroplated Bi was about 40 times larger than that of the evaporated Bi. This distinction in grain size is likely to be the cause of their different spectral responses.

Response comment: Carbon sequestration on Mars

USGS Publications Warehouse

Edwards, Christopher; Ehlmann, Bethany L.

2016-01-01

Martian atmospheric pressure has important implications for the past and present habitability of the planet, including the timing and causes of environmental change. The ancient Martian surface is strewn with evidence for early water bound in minerals (e.g., Ehlmann and Edwards, 2014) and recorded in surface features such as large catastrophically created outflow channels (e.g., Carr, 1979), valley networks (Hynek et al., 2010; Irwin et al., 2005), and crater lakes (e.g., Fassett and Head, 2008). Using orbital spectral data sets coupled with geologic maps and a set of numerical spectral analysis models, Edwards and Ehlmann (2015) constrained the amount of atmospheric sequestration in early Martian rocks and found that the majority of this sequestration occurred prior to the formation of the early Hesperian/late Noachian valley networks (Fassett and Head, 2011; Hynek et al., 2010), thus implying the atmosphere was already thin by the time these surface-water-related features were formed.

IMAGE 100: The interactive multispectral image processing system

NASA Technical Reports Server (NTRS)

Schaller, E. S.; Towles, R. W.

1975-01-01

The need for rapid, cost-effective extraction of useful information from vast quantities of multispectral imagery available from aircraft or spacecraft has resulted in the design, implementation and application of a state-of-the-art processing system known as IMAGE 100. Operating on the general principle that all objects or materials possess unique spectral characteristics or signatures, the system uses this signature uniqueness to identify similar features in an image by simultaneously analyzing signatures in multiple frequency bands. Pseudo-colors, or themes, are assigned to features having identical spectral characteristics. These themes are displayed on a color CRT, and may be recorded on tape, film, or other media. The system was designed to incorporate key features such as interactive operation, user-oriented displays and controls, and rapid-response machine processing. Owing to these features, the user can readily control and/or modify the analysis process based on his knowledge of the input imagery. Effective use can be made of conventional photographic interpretation skills and state-of-the-art machine analysis techniques in the extraction of useful information from multispectral imagery. This approach results in highly accurate multitheme classification of imagery in seconds or minutes rather than the hours often involved in processing using other means.

Intrinsic chirality and prochirality at Air/R-(+)- and S-(-)-limonene interfaces: spectral signatures with interference chiral sum-frequency generation vibrational spectroscopy.

PubMed

Fu, Li; Zhang, Yun; Wei, Zhe-Hao; Wang, Hong-Fei

2014-09-01

We report in this work detailed measurements of the chiral and achiral sum-frequency vibrational spectra in the C-H stretching vibration region (2800-3050 cm(-1)) of the air/liquid interfaces of R-(+)-limonene and S-(-)-limonene, using the recently developed high-resolution broadband sum-frequency generation vibrational spectroscopy (HR-BB-SFG-VS). The achiral SFG spectra of R-limonene and S-limonene, as well as the RS racemic mixture (50/50 equal amount mixture), show that the corresponding molecular groups of the R and S enantiomers are with the same interfacial orientations. The interference chiral SFG spectra of the limonene enantiomers exhibit a spectral signature from the chiral response of the Cα-H stretching mode, and a spectral signature from the prochiral response of the CH(2) asymmetric stretching mode, respectively. The chiral spectral feature of the Cα-H stretching mode changes sign from R-(+)-limonene to S-(-)-limonene surfaces, and disappears for the RS racemic mixture surface. While the prochiral spectral feature of the CH(2) asymmetric stretching mode is the same for R-(+)-limonene and S-(-)-limonene surfaces, and also surprisingly remains the same for the RS racemic mixture surface. Therefore, the structures of the R-(+)-limonene and the S-(-)-limonene at the liquid interfaces are nevertheless not mirror images to each other, even though the corresponding groups have the same tilt angle from the interfacial normal, i.e., the R-(+)-limonene and the S-(-)-limonene at the surface are diastereomeric instead of enantiomeric. These results provide detailed information in understanding the structure and chirality of molecular interfaces and demonstrate the sensitivity and potential of SFG-VS as a unique spectroscopic tool for chirality characterization and chiral recognition at the molecular interface. © 2014 Wiley Periodicals, Inc.

[A Method to Reconstruct Surface Reflectance Spectrum from Multispectral Image Based on Canopy Radiation Transfer Model].

PubMed

Zhao, Yong-guang; Ma, Ling-ling; Li, Chuan-rong; Zhu, Xiao-hua; Tang, Ling-li

2015-07-01

Due to the lack of enough spectral bands for multi-spectral sensor, it is difficult to reconstruct surface retlectance spectrum from finite spectral information acquired by multi-spectral instrument. Here, taking into full account of the heterogeneity of pixel from remote sensing image, a method is proposed to simulate hyperspectral data from multispectral data based on canopy radiation transfer model. This method first assumes the mixed pixels contain two types of land cover, i.e., vegetation and soil. The sensitive parameters of Soil-Leaf-Canopy (SLC) model and a soil ratio factor were retrieved from multi-spectral data based on Look-Up Table (LUT) technology. Then, by combined with a soil ratio factor, all the parameters were input into the SLC model to simulate the surface reflectance spectrum from 400 to 2 400 nm. Taking Landsat Enhanced Thematic Mapper Plus (ETM+) image as reference image, the surface reflectance spectrum was simulated. The simulated reflectance spectrum revealed different feature information of different surface types. To test the performance of this method, the simulated reflectance spectrum was convolved with the Landsat ETM + spectral response curves and Moderate Resolution Imaging Spectrometer (MODIS) spectral response curves to obtain the simulated Landsat ETM+ and MODIS image. Finally, the simulated Landsat ETM+ and MODIS images were compared with the observed Landsat ETM+ and MODIS images. The results generally showed high correction coefficients (Landsat: 0.90-0.99, MODIS: 0.74-0.85) between most simulated bands and observed bands and indicated that the simulated reflectance spectrum was well simulated and reliable.

Forest tree species clssification based on airborne hyper-spectral imagery

NASA Astrophysics Data System (ADS)

Dian, Yuanyong; Li, Zengyuan; Pang, Yong

2013-10-01

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

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.

INTEGRAL/SPI γ-ray line spectroscopy. Response and background characteristics

NASA Astrophysics Data System (ADS)

Diehl, Roland; Siegert, Thomas; Greiner, Jochen; Krause, Martin; Kretschmer, Karsten; Lang, Michael; Pleintinger, Moritz; Strong, Andrew W.; Weinberger, Christoph; Zhang, Xiaoling

2018-03-01

Context. The space based γ-ray observatory INTEGRAL of the European Space Agency (ESA) includes the spectrometer instrument "SPI". This is a coded mask telescope featuring a 19-element Germanium detector array for high-resolution γ-ray spectroscopy, encapsulated in a scintillation detector assembly that provides a veto for background from charged particles. In space, cosmic rays irradiate spacecraft and instruments, which, in spite of the vetoing detectors, results in a large instrumental background from activation of those materials, and leads to deterioration of the charge collection properties of the Ge detectors. Aim. We aim to determine the measurement characteristics of our detectors and their evolution with time, that is, their spectral response and instrumental background. These incur systematic variations in the SPI signal from celestial photons, hence their determination from a broad empirical database enables a reduction of underlying systematics in data analysis. For this, we explore compromises balancing temporal and spectral resolution within statistical limitations. Our goal is to enable modelling of background applicable to spectroscopic studies of the sky, accounting separately for changes of the spectral response and of instrumental background. Methods: We use 13.5 years of INTEGRAL/SPI data, which consist of spectra for each detector and for each pointing of the satellite. Spectral fits to each such spectrum, with independent but coherent treatment of continuum and line backgrounds, provides us with details about separated background components. From the strongest background lines, we first determine how the spectral response changes with time. Applying symmetry and long-term stability tests, we eliminate degeneracies and reduce statistical fluctuations of background parameters, with the aim of providing a self-consistent description of the spectral response for each individual detector. Accounting for this, we then determine how the instrumental background components change in intensities and other characteristics, most-importantly their relative distribution among detectors. Results: Spectral resolution of Ge detectors in space degrades with time, up to 15% within half a year, consistently for all detectors, and across the SPI energy range. Semi-annual annealing operations recover these losses, yet there is a small long-term degradation. The intensity of instrumental background varies anti-correlated to solar activity, in general. There are significant differences among different lines and with respect to continuum. Background lines are found to have a characteristic, well-defined and long-term consistent intensity ratio among detectors. We use this to categorise lines in groups of similar behaviour. The dataset of spectral-response and background parameters as fitted across the INTEGRAL mission allows studies of SPI spectral response and background behaviour in a broad perspective, and efficiently supports precision modelling of instrumental background.

Smile effect detection for dispersive hypersepctral imager based on the doped reflectance panel

NASA Astrophysics Data System (ADS)

Zhou, Jiankang; Liu, Xiaoli; Ji, Yiqun; Chen, Yuheng; Shen, Weimin

2012-11-01

Hyperspectral imager is now widely used in many regions, such as resource development, environmental monitoring and so on. The reliability of spectral data is based on the instrument calibration. The smile, wavelengths at the center pixels of imaging spectrometer detector array are different from the marginal pixels, is a main factor in the spectral calibration because it can deteriorate the spectral data accuracy. When the spectral resolution is high, little smile can result in obvious signal deviation near weak atmospheric absorption peak. The traditional method of detecting smile is monochromator wavelength scanning which is time consuming and complex and can not be used in the field or at the flying platform. We present a new smile detection method based on the holmium oxide panel which has the rich of absorbed spectral features. The higher spectral resolution spectrometer and the under-test imaging spectrometer acquired the optical signal from the Spectralon panel and the holmium oxide panel respectively. The wavelength absorption peak positions of column pixels are determined by curve fitting method which includes spectral response function sequence model and spectral resampling. The iteration strategy and Pearson coefficient together are used to confirm the correlation between the measured and modeled spectral curve. The present smile detection method is posed on our designed imaging spectrometer and the result shows that it can satisfy precise smile detection requirement of high spectral resolution imaging spectrometer.

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.

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

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

Spectral feature measurements and analyses of the East Lake

NASA Astrophysics Data System (ADS)

Fang, Shenghui; Zhou, Yuan; Zhu, Wu

2005-10-01

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

Effect of toxicity of Ag nanoparticles on SERS spectral variance of bacteria

NASA Astrophysics Data System (ADS)

Cui, Li; Chen, Shaode; Zhang, Kaisong

2015-02-01

Ag nanoparticles (NPs) have been extensively utilized in surface-enhanced Raman scattering (SERS) spectroscopy for bacterial identification. However, Ag NPs are toxic to bacteria. Whether such toxicity can affect SERS features of bacteria and interfere with bacterial identification is still unknown and needed to explore. Here, by carrying out a comparative study on non-toxic Au NPs with that on toxic Ag NPs, we investigated the influence of nanoparticle concentration and incubation time on bacterial SERS spectral variance, both of which were demonstrated to be closely related to the toxicity of Ag NPs. Sensitive spectral alterations were observed on Ag NPs with increase of NPs concentration or incubation time, accompanied with an obvious decrease in number of viable bacteria. In contrast, SERS spectra and viable bacterial number on Au NPs were rather constant under the same conditions. A further analysis on spectral changes demonstrated that it was cell response (i.e. metabolic activity or death) to the toxicity of Ag NPs causing spectral variance. However, biochemical responses to the toxicity of Ag were very different in different bacteria, indicating the complex toxic mechanism of Ag NPs. Ag NPs are toxic to a great variety of organisms, including bacteria, fungi, algae, protozoa etc., therefore, this work will be helpful in guiding the future application of SERS technique in various complex biological systems.

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

NASA Astrophysics Data System (ADS)

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

2013-08-01

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

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

NASA Astrophysics Data System (ADS)

Pan, Zhuokun; Huang, Jingfeng; Wang, Fumin

2013-12-01

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

A TALE OF TWO MYSTERIES IN INTERSTELLAR ASTROPHYSICS: THE 2175 A EXTINCTION BUMP AND DIFFUSE INTERSTELLAR BANDS

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

Xiang, F. Y.; Zhong, J. X.; Li Aigen, E-mail: jxzhong@xtu.edu.cn, E-mail: lia@missouri.edu

2011-06-01

The diffuse interstellar bands (DIBs) are ubiquitous absorption spectral features arising from the tenuous material in the space between stars-the interstellar medium (ISM). Since their first detection nearly nine decades ago, over 400 DIBs have been observed in the visible and near-infrared wavelength range in both the Milky Way and external galaxies, both nearby and distant. However, the identity of the species responsible for these bands remains as one of the most enigmatic mysteries in astrophysics. An equally mysterious interstellar spectral signature is the 2175 A extinction bump, the strongest absorption feature observed in the ISM. Its carrier also remainsmore » unclear since its first detection 46 years ago. Polycyclic aromatic hydrocarbon (PAH) molecules have long been proposed as a candidate for DIBs as their electronic transitions occur in the wavelength range where DIBs are often found. In recent years, the 2175 A extinction bump is also often attributed to the {pi}-{pi}* transition in PAHs. If PAHs are indeed responsible for both the 2175 A extinction feature and DIBs, their strengths may correlate. We perform an extensive literature search for lines of sight for which both the 2175 A extinction feature and DIBs have been measured. Unfortunately, we found no correlation between the strength of the 2175 A feature and the equivalent widths of the strongest DIBs. A possible explanation might be that DIBs are produced by small free gas-phase PAH molecules and ions, while the 2175 A bump is mainly from large PAHs or PAH clusters in condensed phase so that there is no tight correlation between DIBs and the 2175 A bump.« less

Thermal Infrared Spectral Band Detection Limits for Unidentified Surface Materials

NASA Technical Reports Server (NTRS)

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

2001-01-01

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

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

PubMed

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

2011-03-28

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

Observation of an emergent coherent state in the iron-based superconductor KFe 2 As 2

DOE PAGES

Yang, Run; Yin, Zhiping; Wang, Yilin; ...

2017-11-14

The ab-plane optical properties of KFe 2As 2 single crystals have been measured over a wide temperature and frequency range. Below T*≃155 K, where this material undergoes an incoherentcoherent crossover, a new coherent response emerges in the optical conductivity. A spectral weight analysis suggests that this new feature originates from high-energy bound states. Below about ≃75 K the scattering rate for this new feature is quadratic in temperature, indicating a Fermiliquid response. Theoretical calculations suggest this crossover is dominated by the d xy orbital. Our results indicate Kondo-type screening is the likely mechanism for the incoherent-coherent crossover in hole-overdoped KFemore » 2As 2.« less

BLAZAR ANTI-SEQUENCE OF SPECTRAL VARIATION WITHIN INDIVIDUAL BLAZARS: CASES FOR MRK 501 AND 3C 279

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

Zhang, Jin; Zhang, Shuang-Nan; Liang, En-Wei, E-mail: zhang.jin@hotmail.com

2013-04-10

The jet properties of Mrk 501 and 3C 279 are derived by fitting broadband spectral energy distributions (SEDs) with lepton models. The derived {gamma}{sub b} (the break Lorenz factor of the electron distribution) is 10{sup 4}-10{sup 6} for Mrk 501 and 200 {approx} 600 for 3C 279. The magnetic field strength (B) of Mrk 501 is usually one order of magnitude lower than that of 3C 279, but their Doppler factors ({delta}) are comparable. A spectral variation feature where the peak luminosity is correlated with the peak frequency, which is opposite from the blazar sequence, is observed in the twomore » sources. We find that (1) the peak luminosities of the two bumps in the SEDs for Mrk 501 depend on {gamma}{sub b} in both the observer and co-moving frames, but they are not correlated with B and {delta} and (2) the luminosity variation of 3C 279 is dominated by the external Compton (EC) peak and its peak luminosity is correlated with {gamma}{sub b} and {delta}, but anti-correlated with B. These results suggest that {gamma}{sub b} may govern the spectral variation of Mrk 501 and {delta} and B would be responsible for the spectral variation of 3C 279. The narrow distribution of {gamma}{sub b} and the correlation of {gamma}{sub b} and B in 3C 279 would be due to the cooling from the EC process and the strong magnetic field. Based on our brief discussion, we propose that this spectral variation feature may originate from the instability of the corona but not from the variation of the accretion rate as does the blazar sequence.« less

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.

Hierarchical Processing of Auditory Objects in Humans

PubMed Central

Kumar, Sukhbinder; Stephan, Klaas E; Warren, Jason D; Friston, Karl J; Griffiths, Timothy D

2007-01-01

This work examines the computational architecture used by the brain during the analysis of the spectral envelope of sounds, an important acoustic feature for defining auditory objects. Dynamic causal modelling and Bayesian model selection were used to evaluate a family of 16 network models explaining functional magnetic resonance imaging responses in the right temporal lobe during spectral envelope analysis. The models encode different hypotheses about the effective connectivity between Heschl's Gyrus (HG), containing the primary auditory cortex, planum temporale (PT), and superior temporal sulcus (STS), and the modulation of that coupling during spectral envelope analysis. In particular, we aimed to determine whether information processing during spectral envelope analysis takes place in a serial or parallel fashion. The analysis provides strong support for a serial architecture with connections from HG to PT and from PT to STS and an increase of the HG to PT connection during spectral envelope analysis. The work supports a computational model of auditory object processing, based on the abstraction of spectro-temporal “templates” in the PT before further analysis of the abstracted form in anterior temporal lobe areas. PMID:17542641

Different event-related patterns of gamma-band power in brain waves of fast- and slow-reacting subjects.

PubMed Central

Jokeit, H; Makeig, S

1994-01-01

Fast- and slow-reacting subjects exhibit different patterns of gamma-band electroencephalogram (EEG) activity when responding as quickly as possible to auditory stimuli. This result appears to confirm long-standing speculations of Wundt that fast- and slow-reacting subjects produce speeded reactions in different ways and demonstrates that analysis of event-related changes in the amplitude of EEG activity recorded from the human scalp can reveal information about event-related brain processes unavailable using event-related potential measures. Time-varying spectral power in a selected (35- to 43-Hz) gamma frequency band was averaged across trials in two experimental conditions: passive listening and speeded reacting to binaural clicks, forming 40-Hz event-related spectral responses. Factor analysis of between-subject event-related spectral response differences split subjects into two near-equal groups composed of faster- and slower-reacting subjects. In faster-reacting subjects, 40-Hz power peaked near 200 ms and 400 ms poststimulus in the react condition, whereas in slower-reacting subjects, 40-Hz power just before stimulus delivery was larger in the react condition. These group differences were preserved in separate averages of relatively long and short reaction-time epochs for each group. gamma-band (20-60 Hz)-filtered event-related potential response averages did not differ between the two groups or conditions. Because of this and because gamma-band power in the auditory event-related potential is small compared with the EEG, the observed event-related spectral response features must represent gamma-band EEG activity reliably induced by, but not phase-locked to, experimental stimuli or events. PMID:8022783

High-Resolution Broadband Spectral Interferometry

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

Erskine, D J; Edelstein, J

2002-08-09

We demonstrate solar spectra from a novel interferometric method for compact broadband high-resolution spectroscopy. The spectral interferometer (SI) is a hybrid instrument that uses a spectrometer to externally disperse the output of a fixed-delay interferometer. It also has been called an externally dispersed interferometer (EDI). The interferometer can be used with linear spectrometers for imaging spectroscopy or with echelle spectrometers for very broad-band coverage. EDI's heterodyning technique enhances the spectrometer's response to high spectral-density features, increasing the effective resolution by factors of several while retaining its bandwidth. The method is extremely robust to instrumental insults such as focal spot sizemore » or displacement. The EDI uses no moving parts, such as purely interferometric FTS spectrometers, and can cover a much wider simultaneous bandpass than other internally dispersed interferometers (e.g. HHS or SHS).« less

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

NASA Technical Reports Server (NTRS)

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

1992-01-01

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

Frequency organization and responses to complex sounds in the medial geniculate body of the mustached bat.

PubMed

Wenstrup, J J

1999-11-01

The auditory cortex of the mustached bat (Pteronotus parnellii) displays some of the most highly developed physiological and organizational features described in mammalian auditory cortex. This study examines response properties and organization in the medial geniculate body (MGB) that may contribute to these features of auditory cortex. About 25% of 427 auditory responses had simple frequency tuning with single excitatory tuning curves. The remainder displayed more complex frequency tuning using two-tone or noise stimuli. Most of these were combination-sensitive, responsive to combinations of different frequency bands within sonar or social vocalizations. They included FM-FM neurons, responsive to different harmonic elements of the frequency modulated (FM) sweep in the sonar signal, and H1-CF neurons, responsive to combinations of the bat's first sonar harmonic (H1) and a higher harmonic of the constant frequency (CF) sonar signal. Most combination-sensitive neurons (86%) showed facilitatory interactions. Neurons tuned to frequencies outside the biosonar range also displayed combination-sensitive responses, perhaps related to analyses of social vocalizations. Complex spectral responses were distributed throughout dorsal and ventral divisions of the MGB, forming a major feature of this bat's analysis of complex sounds. The auditory sector of the thalamic reticular nucleus also was dominated by complex spectral responses to sounds. The ventral division was organized tonotopically, based on best frequencies of singly tuned neurons and higher best frequencies of combination-sensitive neurons. Best frequencies were lowest ventrolaterally, increasing dorsally and then ventromedially. However, representations of frequencies associated with higher harmonics of the FM sonar signal were reduced greatly. Frequency organization in the dorsal division was not tonotopic; within the middle one-third of MGB, combination-sensitive responses to second and third harmonic CF sonar signals (60-63 and 90-94 kHz) occurred in adjacent regions. In the rostral one-third, combination-sensitive responses to second, third, and fourth harmonic FM frequency bands predominated. These FM-FM neurons, thought to be selective for delay between an emitted pulse and echo, showed some organization of delay selectivity. The organization of frequency sensitivity in the MGB suggests a major rewiring of the output of the central nucleus of the inferior colliculus, by which collicular neurons tuned to the bat's FM sonar signals mostly project to the dorsal, not the ventral, division. Because physiological differences between collicular and MGB neurons are minor, a major role of the tecto-thalamic projection in the mustached bat may be the reorganization of responses to provide for cortical representations of sonar target features.

Wheat signature modeling and analysis for improved training statistics

NASA Technical Reports Server (NTRS)

Nalepka, R. F. (Principal Investigator); Malila, W. A.; Cicone, R. C.; Gleason, J. M.

1976-01-01

The author has identified the following significant results. The spectral, spatial, and temporal characteristics of wheat and other signatures in LANDSAT multispectral scanner data were examined through empirical analysis and simulation. Irrigation patterns varied widely within Kansas; 88 percent of wheat acreage in Finney was irrigated and 24 percent in Morton, as opposed to less than 3 percent for western 2/3's of the State. The irrigation practice was definitely correlated with the observed spectral response; wheat variety differences produced observable spectral differences due to leaf coloration and different dates of maturation. Between-field differences were generally greater than within-field differences, and boundary pixels produced spectral features distinct from those within field centers. Multiclass boundary pixels contributed much of the observed bias in proportion estimates. The variability between signatures obtained by different draws of training data decreased as the sample size became larger; also, the resulting signatures became more robust and the particular decision threshold value became less important.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Hyper-Spectral Image Analysis With Partially Latent Regression and Spatial Markov Dependencies

NASA Astrophysics Data System (ADS)

Deleforge, Antoine; Forbes, Florence; Ba, Sileye; Horaud, Radu

2015-09-01

Hyper-spectral data can be analyzed to recover physical properties at large planetary scales. This involves resolving inverse problems which can be addressed within machine learning, with the advantage that, once a relationship between physical parameters and spectra has been established in a data-driven fashion, the learned relationship can be used to estimate physical parameters for new hyper-spectral observations. Within this framework, we propose a spatially-constrained and partially-latent regression method which maps high-dimensional inputs (hyper-spectral images) onto low-dimensional responses (physical parameters such as the local chemical composition of the soil). The proposed regression model comprises two key features. Firstly, it combines a Gaussian mixture of locally-linear mappings (GLLiM) with a partially-latent response model. While the former makes high-dimensional regression tractable, the latter enables to deal with physical parameters that cannot be observed or, more generally, with data contaminated by experimental artifacts that cannot be explained with noise models. Secondly, spatial constraints are introduced in the model through a Markov random field (MRF) prior which provides a spatial structure to the Gaussian-mixture hidden variables. Experiments conducted on a database composed of remotely sensed observations collected from the Mars planet by the Mars Express orbiter demonstrate the effectiveness of the proposed model.

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

NASA Astrophysics Data System (ADS)

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

2010-08-01

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

Sequencing the Cortical Processing of Pitch-Evoking Stimuli using EEG Analysis and Source Estimation

PubMed Central

Butler, Blake E.; Trainor, Laurel J.

2012-01-01

Cues to pitch include spectral cues that arise from tonotopic organization and temporal cues that arise from firing patterns of auditory neurons. fMRI studies suggest a common pitch center is located just beyond primary auditory cortex along the lateral aspect of Heschl’s gyrus, but little work has examined the stages of processing for the integration of pitch cues. Using electroencephalography, we recorded cortical responses to high-pass filtered iterated rippled noise (IRN) and high-pass filtered complex harmonic stimuli, which differ in temporal and spectral content. The two stimulus types were matched for pitch saliency, and a mismatch negativity (MMN) response was elicited by infrequent pitch changes. The P1 and N1 components of event-related potentials (ERPs) are thought to arise from primary and secondary auditory areas, respectively, and to result from simple feature extraction. MMN is generated in secondary auditory cortex and is thought to act on feature-integrated auditory objects. We found that peak latencies of both P1 and N1 occur later in response to IRN stimuli than to complex harmonic stimuli, but found no latency differences between stimulus types for MMN. The location of each ERP component was estimated based on iterative fitting of regional sources in the auditory cortices. The sources of both the P1 and N1 components elicited by IRN stimuli were located dorsal to those elicited by complex harmonic stimuli, whereas no differences were observed for MMN sources across stimuli. Furthermore, the MMN component was located between the P1 and N1 components, consistent with fMRI studies indicating a common pitch region in lateral Heschl’s gyrus. These results suggest that while the spectral and temporal processing of different pitch-evoking stimuli involves different cortical areas during early processing, by the time the object-related MMN response is formed, these cues have been integrated into a common representation of pitch. PMID:22740836

Estimating Achievable Accuracy for Global Imaging Spectroscopy Measurement of Non-Photosynthetic Vegetation Cover

NASA Astrophysics Data System (ADS)

Dennison, P. E.; Kokaly, R. F.; Daughtry, C. S. T.; Roberts, D. A.; Thompson, D. R.; Chambers, J. Q.; Nagler, P. L.; Okin, G. S.; Scarth, P.

2016-12-01

Terrestrial vegetation is dynamic, expressing seasonal, annual, and long-term changes in response to climate and disturbance. Phenology and disturbance (e.g. drought, insect attack, and wildfire) can result in a transition from photosynthesizing "green" vegetation to non-photosynthetic vegetation (NPV). NPV cover can include dead and senescent vegetation, plant litter, agricultural residues, and non-photosynthesizing stem tissue. NPV cover is poorly captured by conventional remote sensing vegetation indices, but it is readily separable from substrate cover based on spectral absorption features in the shortwave infrared. We will present past research motivating the need for global NPV measurements, establishing that mapping seasonal NPV cover is critical for improving our understanding of ecosystem function and carbon dynamics. We will also present new research that helps determine a best achievable accuracy for NPV cover estimation. To test the sensitivity of different NPV cover estimation methods, we simulated satellite imaging spectrometer data using field spectra collected over mixtures of NPV, green vegetation, and soil substrate. We incorporated atmospheric transmittance and modeled sensor noise to create simulated spectra with spectral resolutions ranging from 10 to 30 nm. We applied multiple methods of NPV estimation to the simulated spectra, including spectral indices, spectral feature analysis, multiple endmember spectral mixture analysis, and partial least squares regression, and compared the accuracy and bias of each method. These results prescribe sensor characteristics for an imaging spectrometer mission with NPV measurement capabilities, as well as a "Quantified Earth Science Objective" for global measurement of NPV cover. Copyright 2016, all rights reserved.

A novel approach to pharmaco-EEG for investigating analgesics: assessment of spectral indices in single-sweep evoked brain potentials.

PubMed

Gram, Mikkel; Graversen, Carina; Nielsen, Anders K; Arendt-Nielsen, Thomas; Mørch, Carsten D; Andresen, Trine; Drewes, Asbjørn M

2013-12-01

To compare results from analysis of averaged and single-sweep evoked brain potentials (EPs) by visual inspection and spectral analysis in order to identify an objective measure for the analgesic effect of buprenorphine and fentanyl. Twenty-two healthy males were included in a randomized study to assess the changes in EPs after 110 sweeps of painful electrical stimulation to the median nerve following treatment with buprenorphine, fentanyl or placebo patches. Bone pressure, cutaneous heat and electrical pain ratings were assessed. EPs and pain assessments were obtained before drug administration, 24, 48, 72 and 144 h after beginning of treatment. Features from EPs were extracted by three different approaches: (i) visual inspection of amplitude and latency of the main peaks in the average EPs, (ii) spectral distribution of the average EPs and (iii) spectral distribution of the EPs from single-sweeps. Visual inspection revealed no difference between active treatments and placebo (all P > 0.05). Spectral distribution of the averaged potentials showed a decrease in the beta (12-32 Hz) band for fentanyl (P = 0.036), which however did not correlate with pain ratings. Spectral distribution in the single-sweep EPs revealed significant increases in the theta, alpha and beta bands for buprenorphine (all P < 0.05) as well as theta band increase for fentanyl (P = 0.05). For buprenorphine, beta band activity correlated with bone pressure and cutaneous heat pain (both P = 0.04, r = 0.90). In conclusion single-sweep spectral band analysis increases the information on the response of the brain to opioids and may be used to identify the response to analgesics. © 2013 The Authors. British Journal of Clinical Pharmacology © 2013 The British Pharmacological Society.

Application-Dedicated Selection of Filters (ADSF) using covariance maximization and orthogonal projection.

PubMed

Hadoux, Xavier; Kumar, Dinesh Kant; Sarossy, Marc G; Roger, Jean-Michel; Gorretta, Nathalie

2016-05-19

Visible and near-infrared (Vis-NIR) spectra are generated by the combination of numerous low resolution features. Spectral variables are thus highly correlated, which can cause problems for selecting the most appropriate ones for a given application. Some decomposition bases such as Fourier or wavelet generally help highlighting spectral features that are important, but are by nature constraint to have both positive and negative components. Thus, in addition to complicating the selected features interpretability, it impedes their use for application-dedicated sensors. In this paper we have proposed a new method for feature selection: Application-Dedicated Selection of Filters (ADSF). This method relaxes the shape constraint by enabling the selection of any type of user defined custom features. By considering only relevant features, based on the underlying nature of the data, high regularization of the final model can be obtained, even in the small sample size context often encountered in spectroscopic applications. For larger scale deployment of application-dedicated sensors, these predefined feature constraints can lead to application specific optical filters, e.g., lowpass, highpass, bandpass or bandstop filters with positive only coefficients. In a similar fashion to Partial Least Squares, ADSF successively selects features using covariance maximization and deflates their influences using orthogonal projection in order to optimally tune the selection to the data with limited redundancy. ADSF is well suited for spectroscopic data as it can deal with large numbers of highly correlated variables in supervised learning, even with many correlated responses. Copyright © 2016 Elsevier B.V. All rights reserved.

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

PubMed

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

2010-09-01

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

Comparing Features for Classification of MEG Responses to Motor Imagery.

PubMed

Halme, Hanna-Leena; Parkkonen, Lauri

2016-01-01

Motor imagery (MI) with real-time neurofeedback could be a viable approach, e.g., in rehabilitation of cerebral stroke. Magnetoencephalography (MEG) noninvasively measures electric brain activity at high temporal resolution and is well-suited for recording oscillatory brain signals. MI is known to modulate 10- and 20-Hz oscillations in the somatomotor system. In order to provide accurate feedback to the subject, the most relevant MI-related features should be extracted from MEG data. In this study, we evaluated several MEG signal features for discriminating between left- and right-hand MI and between MI and rest. MEG was measured from nine healthy participants imagining either left- or right-hand finger tapping according to visual cues. Data preprocessing, feature extraction and classification were performed offline. The evaluated MI-related features were power spectral density (PSD), Morlet wavelets, short-time Fourier transform (STFT), common spatial patterns (CSP), filter-bank common spatial patterns (FBCSP), spatio-spectral decomposition (SSD), and combined SSD+CSP, CSP+PSD, CSP+Morlet, and CSP+STFT. We also compared four classifiers applied to single trials using 5-fold cross-validation for evaluating the classification accuracy and its possible dependence on the classification algorithm. In addition, we estimated the inter-session left-vs-right accuracy for each subject. The SSD+CSP combination yielded the best accuracy in both left-vs-right (mean 73.7%) and MI-vs-rest (mean 81.3%) classification. CSP+Morlet yielded the best mean accuracy in inter-session left-vs-right classification (mean 69.1%). There were large inter-subject differences in classification accuracy, and the level of the 20-Hz suppression correlated significantly with the subjective MI-vs-rest accuracy. Selection of the classification algorithm had only a minor effect on the results. We obtained good accuracy in sensor-level decoding of MI from single-trial MEG data. Feature extraction methods utilizing both the spatial and spectral profile of MI-related signals provided the best classification results, suggesting good performance of these methods in an online MEG neurofeedback system.

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

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

NASA Technical Reports Server (NTRS)

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

1974-01-01

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

Wide-bandwidth high-resolution search for extraterrestrial intelligence

NASA Technical Reports Server (NTRS)

Horowitz, Paul

1995-01-01

Research was accomplished during the third year of the grant on: BETA architecture, an FFT array, a feature extractor, the Pentium array and workstation, and a radio astronomy spectrometer. The BETA (this SETI project) system architecture has been evolving generally in the direction of greater robustness against terrestrial interference. The new design adds a powerful state-memory feature, multiple simultaneous thresholds, and the ability to integrate multiple spectra in a flexible state-machine architecture. The FFT array is reported with regards to its hardware verification, array production, and control. The feature extractor is responsible for maintaining a moving baseline, recognizing large spectral peaks, following the progress of previously identified interesting spectral regions, and blocking signals from regions previously identified as containing interference. The Pentium array consists of 21 Pentium-based PC motherboards, each with 16 MByte of RAM and an Ethernet interface. Each motherboard receives and processes the data from a feature extractor/correlator board set, passing on the results of a first analysis to the central Unix workstation (through which each is also booted). The radio astronomy spectrometer is a technological spinoff from SETI work. It is proposed to be a combined spectrometer and power-accumulator, for use at Arecibo Observatory to search for neutral hydrogen emission from condensations of neutral hydrogen at high redshift (z = 5).

Low complexity feature extraction for classification of harmonic signals

NASA Astrophysics Data System (ADS)

William, Peter E.

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

Active listening: task-dependent plasticity of spectrotemporal receptive fields in primary auditory cortex.

PubMed

Fritz, Jonathan; Elhilali, Mounya; Shamma, Shihab

2005-08-01

Listening is an active process in which attentive focus on salient acoustic features in auditory tasks can influence receptive field properties of cortical neurons. Recent studies showing rapid task-related changes in neuronal spectrotemporal receptive fields (STRFs) in primary auditory cortex of the behaving ferret are reviewed in the context of current research on cortical plasticity. Ferrets were trained on spectral tasks, including tone detection and two-tone discrimination, and on temporal tasks, including gap detection and click-rate discrimination. STRF changes could be measured on-line during task performance and occurred within minutes of task onset. During spectral tasks, there were specific spectral changes (enhanced response to tonal target frequency in tone detection and discrimination, suppressed response to tonal reference frequency in tone discrimination). However, only in the temporal tasks, the STRF was changed along the temporal dimension by sharpening temporal dynamics. In ferrets trained on multiple tasks, distinctive and task-specific STRF changes could be observed in the same cortical neurons in successive behavioral sessions. These results suggest that rapid task-related plasticity is an ongoing process that occurs at a network and single unit level as the animal switches between different tasks and dynamically adapts cortical STRFs in response to changing acoustic demands.

Radio-nuclide mixture identification using medium energy resolution detectors

DOEpatents

Nelson, Karl Einar

2013-09-17

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

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Spectral characterization of the LANDSAT thematic mapper sensors

NASA Technical Reports Server (NTRS)

Markham, B. L.; Barker, J. L.

1983-01-01

Data collected on the spectral characteristics of the LANDSAT-4 and LANDSAT-4 backup thematic mapper instruments, the protoflight (TM/PF) and flight (TM/F) models, respectively, are presented and analyzed. Tests were conducted on the instruments and their components to determine compliance with two sets of spectral specifications: band-by-band spectral coverage and channel-by-channel within-band spectral matching. Spectral coverage specifications were placed on: (1) band edges--points at 50% of peak response, (2) band edge slopes--steepness of rise and fall-off of response, (3) spectral flatness--evenness of response between edges, and (4) spurious system response--ratio of out-of-band response to in-band response. Compliance with the spectral coverage specifications was determined by analysis of spectral measurements on the individual components contributing to the overall spectral response: filters, detectors, and optical surfaces.

Detecting Proxima b’s Atmosphere with JWST Targeting CO{sub 2} at 15 μ m Using a High-pass Spectral Filtering Technique

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

Snellen, I. A. G.; Van Dishoeck, E. F.; Brandl, B. R.

Exoplanet Proxima b will be an important laboratory for the search for extraterrestrial life for the decades ahead. Here, we discuss the prospects of detecting carbon dioxide at 15 μ m using a spectral filtering technique with the Medium Resolution Spectrograph (MRS) mode of the Mid-Infrared Instrument (MIRI) on the James Webb Space Telescope ( JWST ). At superior conjunction, the planet is expected to show a contrast of up to 100 ppm with respect to the star. At a spectral resolving power of R  = 1790–2640, about 100 spectral CO{sub 2} features are visible within the 13.2–15.8 μ m (3B)more » band, which can be combined to boost the planet atmospheric signal by a factor of 3–4, depending on the atmospheric temperature structure and CO{sub 2} abundance. If atmospheric conditions are favorable (assuming an Earth-like atmosphere), with this new application to the cross-correlation technique, carbon dioxide can be detected within a few days of JWST observations. However, this can only be achieved if both the instrumental spectral response and the stellar spectrum can be determined to a relative precision of ≤1 × 10{sup −4} between adjacent spectral channels. Absolute flux calibration is not required, and the method is insensitive to the strong broadband variability of the host star. Precise calibration of the spectral features of the host star may only be attainable by obtaining deep observations of the system during inferior conjunction that serve as a reference. The high-pass filter spectroscopic technique with the MIRI MRS can be tested on warm Jupiters, Neptunes, and super-Earths with significantly higher planet/star contrast ratios than the Proxima system.« less

Hyperspectral remote sensing of the responses of vegetation ecosystems to physical and biological changes of the environment

NASA Astrophysics Data System (ADS)

Krezhova, Dora; Krezhov, Kiril; Maneva, Svetla; Moskova, Irina; Petrov, Nikolay

2016-07-01

Hyperspectral remote sensing technique, based on reflectance measurements acquired in a high number of contiguous spectral bands in the visible and near infrared spectral ranges, was used to detect the influence of some environmental changes to vegetation ecosystems. Adverse physical and biological conditions give rise to morphological, physiological, and biochemical changes in the plants that affect the manner in which they interact with the light. All green vegetation species have unique spectral features, mainly because of the chlorophyll and carotenoid, and other pigments, and water content. Because spectral reflectance is a function of the illumination conditions, tissue optical properties and biochemical content of the plants it may be used to collect information on several important biophysical parameters such as color and the spectral signature of features, vegetation chlorophyll absorption characteristics, vegetation moisture content, etc. Remotely sensed data collected by means of a portable fiber-optics spectrometer in the spectral range 350-1100 nm were used to extract information on the influence of some environmental changes. Stress factors such as enhanced UV-radiation, salinity, viral infections, were applied to some young plants species (potato, tomato, plums). The test data were subjected to different digital image processing techniques. This included statistical (Student's t-criterion), first derivative and cluster analyses and some vegetation indices. Statistical analyses were carried out in four most informative for the investigated species regions: green (520-580 nm), red (640-680 nm), red edge (680-720 nm) and near infrared (720-780 nm). The strong relationship, which was found between the results from the remote sensing technique and some biochemical and serological analyses (stress markers, DAS-ELISA), indicates the importance of hyperspectral reflectance data for conducting, easily and without damage, rapid assessments of plant biophysical variables. Emphasis is put on current capability and future potential of remote sensing for assessment of the plant health and on the optimum spectral regions and vegetation indices for sensing these biophysical variables.

Differential coding of conspecific vocalizations in the ventral auditory cortical stream.

PubMed

Fukushima, Makoto; Saunders, Richard C; Leopold, David A; Mishkin, Mortimer; Averbeck, Bruno B

2014-03-26

The mammalian auditory cortex integrates spectral and temporal acoustic features to support the perception of complex sounds, including conspecific vocalizations. Here we investigate coding of vocal stimuli in different subfields in macaque auditory cortex. We simultaneously measured auditory evoked potentials over a large swath of primary and higher order auditory cortex along the supratemporal plane in three animals chronically using high-density microelectrocorticographic arrays. To evaluate the capacity of neural activity to discriminate individual stimuli in these high-dimensional datasets, we applied a regularized multivariate classifier to evoked potentials to conspecific vocalizations. We found a gradual decrease in the level of overall classification performance along the caudal to rostral axis. Furthermore, the performance in the caudal sectors was similar across individual stimuli, whereas the performance in the rostral sectors significantly differed for different stimuli. Moreover, the information about vocalizations in the caudal sectors was similar to the information about synthetic stimuli that contained only the spectral or temporal features of the original vocalizations. In the rostral sectors, however, the classification for vocalizations was significantly better than that for the synthetic stimuli, suggesting that conjoined spectral and temporal features were necessary to explain differential coding of vocalizations in the rostral areas. We also found that this coding in the rostral sector was carried primarily in the theta frequency band of the response. These findings illustrate a progression in neural coding of conspecific vocalizations along the ventral auditory pathway.

Differential Coding of Conspecific Vocalizations in the Ventral Auditory Cortical Stream

PubMed Central

Saunders, Richard C.; Leopold, David A.; Mishkin, Mortimer; Averbeck, Bruno B.

2014-01-01

The mammalian auditory cortex integrates spectral and temporal acoustic features to support the perception of complex sounds, including conspecific vocalizations. Here we investigate coding of vocal stimuli in different subfields in macaque auditory cortex. We simultaneously measured auditory evoked potentials over a large swath of primary and higher order auditory cortex along the supratemporal plane in three animals chronically using high-density microelectrocorticographic arrays. To evaluate the capacity of neural activity to discriminate individual stimuli in these high-dimensional datasets, we applied a regularized multivariate classifier to evoked potentials to conspecific vocalizations. We found a gradual decrease in the level of overall classification performance along the caudal to rostral axis. Furthermore, the performance in the caudal sectors was similar across individual stimuli, whereas the performance in the rostral sectors significantly differed for different stimuli. Moreover, the information about vocalizations in the caudal sectors was similar to the information about synthetic stimuli that contained only the spectral or temporal features of the original vocalizations. In the rostral sectors, however, the classification for vocalizations was significantly better than that for the synthetic stimuli, suggesting that conjoined spectral and temporal features were necessary to explain differential coding of vocalizations in the rostral areas. We also found that this coding in the rostral sector was carried primarily in the theta frequency band of the response. These findings illustrate a progression in neural coding of conspecific vocalizations along the ventral auditory pathway. PMID:24672012

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

NASA Astrophysics Data System (ADS)

Chockalingam, Letchumanan

2005-01-01

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

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

ERIC Educational Resources Information Center

De Lorenzi Pezzolo, Alessandra

2013-01-01

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

Deep Learning Based Binaural Speech Separation in Reverberant Environments.

PubMed

Zhang, Xueliang; Wang, DeLiang

2017-05-01

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

Universal properties of materials with the Dirac dispersion relation of low-energy excitations

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

Protogenov, A. P., E-mail: alprot@appl.sci-nnov.ru; Chulkov, E. V.

2015-12-15

The N-terminal scheme is considered for studying the contribution of edge states to the response of a two-dimensional topological insulator. A universal distribution of the nonlocal resistance between terminals is determined in the ballistic transport approach. The calculated responses are identical to experimentally observed values. The spectral properties of surface electronic states in Weyl semimetals are also studied. The density of surface states is accurately determined. The universal behavior of these characteristics is a distinctive feature of the considered Dirac materials which can be used in practical applications.

Psychoacoustic cues to emotion in speech prosody and music.

PubMed

Coutinho, Eduardo; Dibben, Nicola

2013-01-01

There is strong evidence of shared acoustic profiles common to the expression of emotions in music and speech, yet relatively limited understanding of the specific psychoacoustic features involved. This study combined a controlled experiment and computational modelling to investigate the perceptual codes associated with the expression of emotion in the acoustic domain. The empirical stage of the study provided continuous human ratings of emotions perceived in excerpts of film music and natural speech samples. The computational stage created a computer model that retrieves the relevant information from the acoustic stimuli and makes predictions about the emotional expressiveness of speech and music close to the responses of human subjects. We show that a significant part of the listeners' second-by-second reported emotions to music and speech prosody can be predicted from a set of seven psychoacoustic features: loudness, tempo/speech rate, melody/prosody contour, spectral centroid, spectral flux, sharpness, and roughness. The implications of these results are discussed in the context of cross-modal similarities in the communication of emotion in the acoustic domain.

System-independent characterization of materials using dual-energy computed tomography

DOE PAGES

Azevedo, Stephen G.; Martz, Jr., Harry E.; Aufderheide, III, Maurice B.; ...

2016-02-01

In this study, we present a new decomposition approach for dual-energy computed tomography (DECT) called SIRZ that provides precise and accurate material description, independent of the scanner, over diagnostic energy ranges (30 to 200 keV). System independence is achieved by explicitly including a scanner-specific spectral description in the decomposition method, and a new X-ray-relevant feature space. The feature space consists of electron density, ρ e, and a new effective atomic number, Z e, which is based on published X-ray cross sections. Reference materials are used in conjunction with the system spectral response so that additional beam-hardening correction is not necessary.more » The technique is tested against other methods on DECT data of known specimens scanned by diverse spectra and systems. Uncertainties in accuracy and precision are less than 3% and 2% respectively for the (ρ e, Z e) results compared to prior methods that are inaccurate and imprecise (over 9%).« less

Operating organic light-emitting diodes imaged by super-resolution spectroscopy

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

King, John T.; Granick, Steve

Super-resolution stimulated emission depletion (STED) microscopy is adapted here for materials characterization that would not otherwise be possible. With the example of organic light-emitting diodes (OLEDs), spectral imaging with pixel-by-pixel wavelength discrimination allows us to resolve local-chain environment encoded in the spectral response of the semi-conducting polymer, and correlate chain packing with local electroluminescence by using externally applied current as the excitation source. We observe nanoscopic defects that would be unresolvable by traditional microscopy. They are revealed in electroluminescence maps in operating OLEDs with 50 nm spatial resolution. We find that brightest emission comes from regions with more densely packedmore » chains. Conventional microscopy of an operating OLED would lack the resolution needed to discriminate these features, while traditional methods to resolve nanoscale features generally cannot be performed when the device is operating. As a result, this points the way towards real-time analysis of materials design principles in devices as they actually operate.« less

Classification of ion mobility spectra by functional groups using neural networks

NASA Technical Reports Server (NTRS)

Bell, S.; Nazarov, E.; Wang, Y. F.; Eiceman, G. A.

1999-01-01

Neural networks were trained using whole ion mobility spectra from a standardized database of 3137 spectra for 204 chemicals at various concentrations. Performance of the network was measured by the success of classification into ten chemical classes. Eleven stages for evaluation of spectra and of spectral pre-processing were employed and minimums established for response thresholds and spectral purity. After optimization of the database, network, and pre-processing routines, the fraction of successful classifications by functional group was 0.91 throughout a range of concentrations. Network classification relied on a combination of features, including drift times, number of peaks, relative intensities, and other factors apparently including peak shape. The network was opportunistic, exploiting different features within different chemical classes. Application of neural networks in a two-tier design where chemicals were first identified by class and then individually eliminated all but one false positive out of 161 test spectra. These findings establish that ion mobility spectra, even with low resolution instrumentation, contain sufficient detail to permit the development of automated identification systems.

Operating organic light-emitting diodes imaged by super-resolution spectroscopy

DOE PAGES

King, John T.; Granick, Steve

2016-06-21

Super-resolution stimulated emission depletion (STED) microscopy is adapted here for materials characterization that would not otherwise be possible. With the example of organic light-emitting diodes (OLEDs), spectral imaging with pixel-by-pixel wavelength discrimination allows us to resolve local-chain environment encoded in the spectral response of the semi-conducting polymer, and correlate chain packing with local electroluminescence by using externally applied current as the excitation source. We observe nanoscopic defects that would be unresolvable by traditional microscopy. They are revealed in electroluminescence maps in operating OLEDs with 50 nm spatial resolution. We find that brightest emission comes from regions with more densely packedmore » chains. Conventional microscopy of an operating OLED would lack the resolution needed to discriminate these features, while traditional methods to resolve nanoscale features generally cannot be performed when the device is operating. As a result, this points the way towards real-time analysis of materials design principles in devices as they actually operate.« less

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

PubMed

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

2017-03-22

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

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

NASA Astrophysics Data System (ADS)

Zhao, Bei; Zhong, Yanfei; Zhang, Liangpei

2016-06-01

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

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

NASA Technical Reports Server (NTRS)

Bowyer, Stuart; Malina, Roger F.

1986-01-01

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

A calibration method for the measurement of IR detector spectral responses using a FTIR spectrometer equipped with a DTGS reference cell

NASA Astrophysics Data System (ADS)

Gravrand, Olivier; Wlassow, J.; Bonnefond, L.

2014-07-01

Various high performance IR detectors are today available on the market from QWIPs to narrow gap semiconductor photodiodes, which exhibit various spectral features. In the astrophysics community, the knowledge of the detector spectral shape is of first importance. This quantity (spectral QE or response) is usually measured by means of a monochromator followed by an integrating sphere and compared to a calibrated reference detector. This approach is usually very efficient in the visible range, where all optical elements are very well known, particularly the reference detector. This setup is also widely used in the near IR (up to 3μm) but as the wavelength increases, it becomes less efficient. For instance, the internal emittance of integrating spheres in the IR, and the bad knowledge of reference detectors for longer wavelengths tend to degrade the measurement reliability. Another approach may therefore be considered, using a Fourier transform IR spectrometer (FTIR). In this case, as opposed to the monochromator, the tested detector is not in low flux condition, the incident light containing a mix of different wavelengths. Therefore, the reference detector has to be to be sensitive (and known) in the whole spectral band of interest, because it will sense all those wavelengths at the same time. A popular detector used in this case is a Deuterated Triglycine Sulfate thermal detector (DTGS). Being a pyro detetector, the spectral response of such a detector is very flat, mainly limited by its window. However, the response of such a detector is very slow, highly depending on the temporal frequency of the input signal. Moreover, being a differential detector, it doesn't work in DC. In commercial FTIR spectrometers, the source luminance is usually continuously modulated by the moving interferometer, and the result is that the interferogram mixes optical spectral information (optical path difference) and temporal variations (temporal frequency) so that the temporal transfert function of the DTGS has to be qualified and taken into account. The usual way is to measure it directly by means of an optical shopper and a locking amplifier for different shopping frequencies. We present here an alternative method to estimate this DTGS transfer function, based on the fact that a FTIR continuous scan interfergram contains the different spectral frequencies of interest. Such a calibration method doesn't need a specific setup as it can be performed in standard configuration, playing only with spectrometer parameters. It allows for the precise estimation of detector spectral shapes. However, this measurement is not absolute and the peak response needs therefore to be estimated using a calibrated black body cavity. The method, its results and limits is presented and discussed for a set of different DTGS cells.

Spectral feature variations in x-ray diffraction imaging systems

NASA Astrophysics Data System (ADS)

Wolter, Scott D.; Greenberg, Joel A.

2016-05-01

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

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

PubMed

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

2015-10-01

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

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

NASA Technical Reports Server (NTRS)

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

1973-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2000-10-01

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

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

PubMed Central

Singha, Mrinal; Wu, Bingfang; Zhang, Miao

2016-01-01

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

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

PubMed

Singha, Mrinal; Wu, Bingfang; Zhang, Miao

2016-12-22

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

Preliminary results from an investigation of AIS-1 data over an area of epithermal alteration: Plateau, Northern Queensland, Australia

NASA Technical Reports Server (NTRS)

Mackin, Steve; Munday, Tim; Hook, Simon

1987-01-01

Airborne Imaging Spectrometer-1 (AIS-1) data were flown over undifferentiated sequences of acid to intermediate volcanics and intrusives; meta-sediments; and a series of partially lateritized sedimentary rocks. The area exhibits a considerable spectral variability, after the suppression of striping effects. Log residual, and Internal Average Relative Reflectance (IARR) analytical techniques were used to enhance mineralogically related spectral features. Both methods produce similar results, but did not visually highlight mineral absorption features due to processing artifacts in areas of significant vegetation cover. The enhancement of mineral related absorption features was achieved using a hybrid processing approach based on the relative reflectance differences between vegetated and non-vegetated surfaces at 1.2 and 2.1 micron. The result is an image with little overall contrast, but which enhances the more subtle spectral features believed to be associated with clays and epidote. The AIS data was subject to interactive analysis using SPAM. Clear separation of clay and epidote related absorption features was apparent, and the identification of kaolinite was possible despite detrimental spectral effects.

An advanced scanning method for space-borne hyper-spectral imaging system

NASA Astrophysics Data System (ADS)

Wang, Yue-ming; Lang, Jun-Wei; Wang, Jian-Yu; Jiang, Zi-Qing

2011-08-01

Space-borne hyper-spectral imagery is an important means for the studies and applications of earth science. High cost efficiency could be acquired by optimized system design. In this paper, an advanced scanning method is proposed, which contributes to implement both high temporal and spatial resolution imaging system. Revisit frequency and effective working time of space-borne hyper-spectral imagers could be greatly improved by adopting two-axis scanning system if spatial resolution and radiometric accuracy are not harshly demanded. In order to avoid the quality degradation caused by image rotation, an idea of two-axis rotation has been presented based on the analysis and simulation of two-dimensional scanning motion path and features. Further improvement of the imagers' detection ability under the conditions of small solar altitude angle and low surface reflectance can be realized by the Ground Motion Compensation on pitch axis. The structure and control performance are also described. An intelligent integration technology of two-dimensional scanning and image motion compensation is elaborated in this paper. With this technology, sun-synchronous hyper-spectral imagers are able to pay quick visit to hot spots, acquiring both high spatial and temporal resolution hyper-spectral images, which enables rapid response of emergencies. The result has reference value for developing operational space-borne hyper-spectral imagers.

[The new method monitoring crop water content based on NIR-Red spectrum feature space].

PubMed

Cheng, Xiao-juan; Xu, Xin-gang; Chen, Tian-en; Yang, Gui-jun; Li, Zhen-hai

2014-06-01

Moisture content is an important index of crop water stress condition, timely and effective monitoring of crop water content is of great significance for evaluating crop water deficit balance and guiding agriculture irrigation. The present paper was trying to build a new crop water index for winter wheat vegetation water content based on NIR-Red spectral space. Firstly, canopy spectrums of winter wheat with narrow-band were resampled according to relative spectral response function of HJ-CCD and ZY-3. Then, a new index (PWI) was set up to estimate vegetation water content of winter wheat by improveing PDI (perpendicular drought index) and PVI (perpendicular vegetation index) based on NIR-Red spectral feature space. The results showed that the relationship between PWI and VWC (vegetation water content) was stable based on simulation of wide-band multispectral data HJ-CCD and ZY-3 with R2 being 0.684 and 0.683, respectively. And then VWC was estimated by using PWI with the R2 and RMSE being 0.764 and 0.764, 3.837% and 3.840%, respectively. The results indicated that PWI has certain feasibility to estimate crop water content. At the same time, it provides a new method for monitoring crop water content using remote sensing data HJ-CCD and ZY-3.

Multi scales based sparse matrix spectral clustering image segmentation

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Spectral reflectance and emissivity features of broad leaf plants: Prospects for remote sensing in the thermal infrared (8.0-14.0 μm)

USGS Publications Warehouse

Ribeiro da Luz, Beatriz; Crowley, James K.

2007-01-01

In contrast to visible and short-wave infrared data, thermal infrared spectra of broad leaf plants show considerable spectral diversity, suggesting that such data eventually could be utilized to map vegetation composition. However, remotely measuring the subtle emissivity features of leaves still presents major challenges. To be successful, sensors operating in the 8–14 μm atmospheric window must have high signal-to-noise and a small enough instantaneous field of view to allow measurements of only a few leaf surfaces. Methods for atmospheric compensation, temperature–emissivity separation, and spectral feature analysis also will need to be refined to allow the recognition, and perhaps, exploitation of leaf thermal infrared spectral properties.

Multi-Color QWIP FPAs for Hyperspectral Thermal Emission Instruments

NASA Technical Reports Server (NTRS)

Soibel, Alexander; Luong, Ed; Mumolo, Jason M.; Liu, John; Rafol, Sir B.; Keo, Sam A.; Johnson, William; Willson, Dan; Hill, Cory J.; Ting, David Z.-Y.;

Earth Observing-1 Advanced Land Imager: Radiometric Response Calibration

NASA Technical Reports Server (NTRS)

Mendenhall, J. A.; Lencioni, D. E.; Evans, J. B.

2000-01-01

The Advanced Land Imager (ALI) is one of three instruments to be flown on the first Earth Observing mission (EO-1) under NASA's New Millennium Program (NMP). ALI contains a number of innovative features, including a wide field of view optical design, compact multispectral focal plane arrays, non-cryogenic HgCdTe detectors for the short wave infrared bands, and silicon carbide optics. This document outlines the techniques adopted during ground calibration of the radiometric response of the Advanced Land Imager. Results from system level measurements of the instrument response, signal-to-noise ratio, saturation radiance, and dynamic range for all detectors of every spectral band are also presented.

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

USGS Publications Warehouse

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

2011-01-01

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

The detection of 'virtual' objects using echoes by humans: Spectral cues.

PubMed

Rowan, Daniel; Papadopoulos, Timos; Archer, Lauren; Goodhew, Amanda; Cozens, Hayley; Lopez, Ricardo Guzman; Edwards, David; Holmes, Hannah; Allen, Robert

2017-07-01

Some blind people use echoes to detect discrete, silent objects to support their spatial orientation/navigation, independence, safety and wellbeing. The acoustical features that people use for this are not well understood. Listening to changes in spectral shape due to the presence of an object could be important for object detection and avoidance, especially at short range, although it is currently not known whether it is possible with echolocation-related sounds. Bands of noise were convolved with recordings of binaural impulse responses of objects in an anechoic chamber to create 'virtual objects', which were analysed and played to sighted and blind listeners inexperienced in echolocation. The sounds were also manipulated to remove cues unrelated to spectral shape. Most listeners could accurately detect hard flat objects using changes in spectral shape. The useful spectral changes for object detection occurred above approximately 3 kHz, as with object localisation. However, energy in the sounds below 3 kHz was required to exploit changes in spectral shape for object detection, whereas energy below 3 kHz impaired object localisation. Further recordings showed that the spectral changes were diminished by room reverberation. While good high-frequency hearing is generally important for echolocation, the optimal echo-generating stimulus will probably depend on the task. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Nanophotonics-enabled smart windows, buildings and wearables

NASA Astrophysics Data System (ADS)

Smith, Geoff; Gentle, Angus; Arnold, Matthew; Cortie, Michael

2016-06-01

Design and production of spectrally smart windows, walls, roofs and fabrics has a long history, which includes early examples of applied nanophotonics. Evolving nanoscience has a special role to play as it provides the means to improve the functionality of these everyday materials. Improvement in the quality of human experience in any location at any time of year is the goal. Energy savings, thermal and visual comfort indoors and outdoors, visual experience, air quality and better health are all made possible by materials, whose "smartness" is aimed at designed responses to environmental energy flows. The spectral and angle of incidence responses of these nanomaterials must thus take account of the spectral and directional aspects of solar energy and of atmospheric thermal radiation plus the visible and color sensitivity of the human eye. The structures required may use resonant absorption, multilayer stacks, optical anisotropy and scattering to achieve their functionality. These structures are, in turn, constructed out of particles, columns, ultrathin layers, voids, wires, pure and doped oxides, metals, polymers or transparent conductors (TCs). The need to cater for wavelengths stretching from 0.3 to 35 μm including ultraviolet-visible, near-infrared (IR) and thermal or Planck radiation, with a spectrally and directionally complex atmosphere, and both being dynamic, means that hierarchical and graded nanostructures often feature. Nature has evolved to deal with the same energy flows, so biomimicry is sometimes a useful guide.

Algorithms for Spectral Decomposition with Applications to Optical Plume Anomaly Detection

NASA Technical Reports Server (NTRS)

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

2008-01-01

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

Processing of presolar grains around post-AGB stars: SiC as the carrier of the ``21''μ m feature

NASA Astrophysics Data System (ADS)

Hofmeister, A. M.; Speck, A. K.

2003-12-01

Intermediate mass stars (0.8-8.0 Msolar) eventually evolve on the H-R diagram, up the asymptotic giant branch (AGB). The intensive mass loss which characterizes the AGB produces a circumstellar shell of dust and neutral gas. At the end of the AGB, mass loss virtually stops and the circumstellar shell begins to drift away from the star. At the same time the central star begins to shrink and heat up. This is the proto-planetary nebula (PPN) phase. Some PPNe exhibit an enigmatic feature in their infrared (IR) spectra at ˜21μ m. This feature is not seen in the spectra of either the precursors to PPNe, the AGB stars, or the successors of PPNe, ``normal'' planetary nebulae (PNe). However the ``21''μ m feature has been seen in the spectra of PNe with Wolf-Rayet central stars. Therefore the carrier of this feature is unlikely to be a transient species that only exists in the PPNe phase. This feature has been attributed to various molecular and solid state species, none of which satisfy all constraints, although titanium carbide (TiC) and polycyclic aromatic hydrocarbons (PAHs) have seemed the most viable. We present new laboratory data for silicon carbide (SiC) and show that it has a spectral feature which is a good candidate for the carrier of the 21μ m feature. The SiC spectral feature appears at approximately the same wavelength (depending on polytype/grain size) and has the same asymmetric profile as the observed astronomical feature. We suggest that processing and cooling of the SiC grains known to exist around carbon-rich AGB stars are responsible for the emergence of the enigmatic 21μ m feature. The emergence of this feature in the spectra of post-AGB stars demonstrates the processing of dust due to the changing physical environments around evolving stars.

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

PubMed

Schädler, Marc René; Kollmeier, Birger

2015-04-01

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

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

NASA Astrophysics Data System (ADS)

Kohno, Masanori

2018-05-01

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

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

PubMed

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

2010-01-01

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

An interactive tool for semi-automatic feature extraction of hyperspectral data

NASA Astrophysics Data System (ADS)

Kovács, Zoltán; Szabó, Szilárd

2016-09-01

The spectral reflectance of the surface provides valuable information about the environment, which can be used to identify objects (e.g. land cover classification) or to estimate quantities of substances (e.g. biomass). We aimed to develop an MS Excel add-in - Hyperspectral Data Analyst (HypDA) - for a multipurpose quantitative analysis of spectral data in VBA programming language. HypDA was designed to calculate spectral indices from spectral data with user defined formulas (in all possible combinations involving a maximum of 4 bands) and to find the best correlations between the quantitative attribute data of the same object. Different types of regression models reveal the relationships, and the best results are saved in a worksheet. Qualitative variables can also be involved in the analysis carried out with separability and hypothesis testing; i.e. to find the wavelengths responsible for separating data into predefined groups. HypDA can be used both with hyperspectral imagery and spectrometer measurements. This bivariate approach requires significantly fewer observations than popular multivariate methods; it can therefore be applied to a wide range of research areas.

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

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

USDA-ARS?s Scientific Manuscript database

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

Interpreting Quasi-Thermal Effects in Ultrafast Spectroscopy of Hydrogen-Bonded Systems.

PubMed

Stingel, Ashley M; Petersen, Poul B

2018-03-15

Vibrational excitation of molecules in the condensed phase relaxes through vibrational modes of decreasing energy to ultimately generate an equilibrium state in which the energy is distributed among low-frequency modes. In ultrafast vibrational spectroscopy, changes in the vibrational features of hydrogen-bonded NH and OH stretch modes are typically observed to persist long after these high-frequency vibrations have relaxed. Due to the resemblance to the spectral changes caused by heating the sample, these features are typically described as arising from a hot ground state. However, these spectral features appear on ultrafast time scales that are much too fast to result from a true thermal state, and significant differences between the thermal difference spectrum and the induced quasi-thermal changes in ultrafast spectroscopy are often observed. Here, we examine and directly compare the thermal and quasi-thermal responses of the hydrogen-bonded homodimer of 7-azaindole with temperature-dependent FTIR spectroscopy and ultrafast mid-IR continuum spectroscopy. We find that the thermal difference spectra contain contributions from both dissociation of the hydrogen bonds and from frequency shifts due to changes in the thermal population of low-frequency modes. The transient spectra in ultrafast vibrational spectroscopy are also found to contain two contributions: initial frequency shifts over 2.3 ± 0.11 ps associated with equilibration of the initial excitation, and frequency shifts associated with the excitation of several fingerprint modes, which decay over 21.8 ± 0.11 ps, giving rise to a quasi-thermal response caused by a distribution of fingerprint modes being excited within the sample ensemble. This resembles the thermal frequency shifts due to population changes of low-frequency modes, but not the overall thermal spectrum, which is dominated by features caused by dimer dissociation. These findings provide insight into the changes in the vibrational spectrum from different origins and are important for assigning, analyzing, and comparing features in thermal and ultrafast vibrational spectroscopy of hydrogen-bonded complexes.

The properties of electromagnetic responses and optical modulation in terahertz metamaterials

NASA Astrophysics Data System (ADS)

Chen, Wei; Shi, Yulei; Wang, Wei; Zhou, Qingli; Zhang, Cunlin

2016-11-01

Metamaterials with subwavelength structural features show unique electromagnetic responses that are unattainable with natural materials. Recently, the research on these artificial materials has been pushed forward to the terahertz (THz) region because of potential applications in biological fingerprinting, security imaging, and high frequency magnetic and electric resonant devices. Furthermore, active control of their properties could further facilitate and open up new applications in terms of modulation and switching. In our work, we will first present our studies of dipole arrays at terahertz frequencies. Then in experimental and theoretical studies of terahertz subwavelength L-shaped structure, we proposed an unusual-mode current resonance responsible for low-frequency characteristic dip in transmission spectra. Comparing spectral properties of our designed simplified structures with that of split-ring resonators, we attribute this unusual mode to the resonance coupling and splitting under the broken symmetry of the structure. Finally, we use optical pump-terahertz probe method to investigate the spectral and dynamic behaviour of optical modulation in the split-ring resonators. We have observed the blue-shift and band broadening in the spectral changes of transmission under optical excitation at different delay times. The calculated surface currents using finite difference time domain simulation are presented to characterize these resonances, and the blue-shift can be explained by the changed refractive index and conductivity in the photoexcited semiconductor substrate.

Hyperspectral feature mapping classification based on mathematical morphology

NASA Astrophysics Data System (ADS)

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

2016-03-01

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

O2 on ganymede: Spectral characteristics and plasma formation mechanisms

USGS Publications Warehouse

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

1996-01-01

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

An Extended Spectral-Spatial Classification Approach for Hyperspectral Data

NASA Astrophysics Data System (ADS)

Akbari, D.

2017-11-01

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

Functional Topography of Human Auditory Cortex

PubMed Central

Rauschecker, Josef P.

2016-01-01

Functional and anatomical studies have clearly demonstrated that auditory cortex is populated by multiple subfields. However, functional characterization of those fields has been largely the domain of animal electrophysiology, limiting the extent to which human and animal research can inform each other. In this study, we used high-resolution functional magnetic resonance imaging to characterize human auditory cortical subfields using a variety of low-level acoustic features in the spectral and temporal domains. Specifically, we show that topographic gradients of frequency preference, or tonotopy, extend along two axes in human auditory cortex, thus reconciling historical accounts of a tonotopic axis oriented medial to lateral along Heschl's gyrus and more recent findings emphasizing tonotopic organization along the anterior–posterior axis. Contradictory findings regarding topographic organization according to temporal modulation rate in acoustic stimuli, or “periodotopy,” are also addressed. Although isolated subregions show a preference for high rates of amplitude-modulated white noise (AMWN) in our data, large-scale “periodotopic” organization was not found. Organization by AM rate was correlated with dominant pitch percepts in AMWN in many regions. In short, our data expose early auditory cortex chiefly as a frequency analyzer, and spectral frequency, as imposed by the sensory receptor surface in the cochlea, seems to be the dominant feature governing large-scale topographic organization across human auditory cortex. SIGNIFICANCE STATEMENT In this study, we examine the nature of topographic organization in human auditory cortex with fMRI. Topographic organization by spectral frequency (tonotopy) extended in two directions: medial to lateral, consistent with early neuroimaging studies, and anterior to posterior, consistent with more recent reports. Large-scale organization by rates of temporal modulation (periodotopy) was correlated with confounding spectral content of amplitude-modulated white-noise stimuli. Together, our results suggest that the organization of human auditory cortex is driven primarily by its response to spectral acoustic features, and large-scale periodotopy spanning across multiple regions is not supported. This fundamental information regarding the functional organization of early auditory cortex will inform our growing understanding of speech perception and the processing of other complex sounds. PMID:26818527

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

USDA-ARS?s Scientific Manuscript database

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

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

NASA Astrophysics Data System (ADS)

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

2012-11-01

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

EEG resolutions in detecting and decoding finger movements from spectral analysis

PubMed Central

Xiao, Ran; Ding, Lei

2015-01-01

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

Lithologic mapping of the Mordor, NT, Australia ultramafic complex by using the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER)

USGS Publications Warehouse

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

2005-01-01

Spectral measurements made in the Mordor Pound, NT, Australia study area using the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), in the laboratory and in situ show dominantly Al-OH and ferric-iron VNIR-SWIR absorption features in felsic rock spectra and ferrous-iron and Fe,Mg-OH features in the mafic-ultramafic rock spectra. ASTER ratio images, matched-filter, and spectral-angle mapper processing (SAM) were evaluated for mapping the lithologies. Matched-filter processing in which VNIR + SWIR image spectra were used for reference resulted in 4 felsic classes and 4 mafic-ultramafic classes based on Al-OH or Fe,Mg-OH absorption features and, in some, subtle reflectance differences related to differential weathering and vegetation. These results were similar to those obtained by match-filter analysis of HyMap data from a previous study, but the units were more clearly demarcated in the HyMap image. ASTER TIR spectral emittance data and laboratory emissivity measurements document a wide wavelength range of Si-O spectral features, which reflect the lithological diversity of the Mordor ultramafic complex and adjacent rocks. SAM processing of the spectral emittance data distinguished 2 classes representing the mafic-ultramafic rocks and 4 classes comprising the quartzose to intermediate composition rocks. Utilization of the complementary attributes of the spectral reflectance and spectral emittance data resulted in discrimination of 4 mafic-ultramafic categories; 3 categories of alluvial-colluvial deposits; and a significantly more completely mapped quartzite unit than could be accomplished by using either data set alone. ?? 2005 Elsevier Inc. All rights reserved.

Comparing Features for Classification of MEG Responses to Motor Imagery

PubMed Central

Halme, Hanna-Leena; Parkkonen, Lauri

2016-01-01

Background Motor imagery (MI) with real-time neurofeedback could be a viable approach, e.g., in rehabilitation of cerebral stroke. Magnetoencephalography (MEG) noninvasively measures electric brain activity at high temporal resolution and is well-suited for recording oscillatory brain signals. MI is known to modulate 10- and 20-Hz oscillations in the somatomotor system. In order to provide accurate feedback to the subject, the most relevant MI-related features should be extracted from MEG data. In this study, we evaluated several MEG signal features for discriminating between left- and right-hand MI and between MI and rest. Methods MEG was measured from nine healthy participants imagining either left- or right-hand finger tapping according to visual cues. Data preprocessing, feature extraction and classification were performed offline. The evaluated MI-related features were power spectral density (PSD), Morlet wavelets, short-time Fourier transform (STFT), common spatial patterns (CSP), filter-bank common spatial patterns (FBCSP), spatio—spectral decomposition (SSD), and combined SSD+CSP, CSP+PSD, CSP+Morlet, and CSP+STFT. We also compared four classifiers applied to single trials using 5-fold cross-validation for evaluating the classification accuracy and its possible dependence on the classification algorithm. In addition, we estimated the inter-session left-vs-right accuracy for each subject. Results The SSD+CSP combination yielded the best accuracy in both left-vs-right (mean 73.7%) and MI-vs-rest (mean 81.3%) classification. CSP+Morlet yielded the best mean accuracy in inter-session left-vs-right classification (mean 69.1%). There were large inter-subject differences in classification accuracy, and the level of the 20-Hz suppression correlated significantly with the subjective MI-vs-rest accuracy. Selection of the classification algorithm had only a minor effect on the results. Conclusions We obtained good accuracy in sensor-level decoding of MI from single-trial MEG data. Feature extraction methods utilizing both the spatial and spectral profile of MI-related signals provided the best classification results, suggesting good performance of these methods in an online MEG neurofeedback system. PMID:27992574

Bipolar gas outflow from the nova V458 Vul

NASA Astrophysics Data System (ADS)

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

2010-06-01

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

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

USGS Publications Warehouse

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

2012-01-01

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

Spectra of Particulate Backscattering in Natural Waters

NASA Technical Reports Server (NTRS)

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

2009-01-01

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

On the Relationship between Fourier and Response Spectra: Implications for the Adjustment of Empirical Ground-Motion Prediction Equations (GMPEs)

NASA Astrophysics Data System (ADS)

Bora, Sanjay; Scherbaum, Frank; Kuehn, Nicolas; Stafford, Peter

2016-04-01

Often, scaling of response spectral amplitudes, (e.g., spectral acceleration) obtained from empirical ground motion prediction equations (GMPEs), with respect to commonly used seismological parameters such as magnitude, distance and site condition is assumed/referred to be representing a similar scaling of Fourier spectral amplitudes. For instance, the distance scaling of response spectral amplitudes is related with the geometrical spreading of seismic waves. Such comparison of scaling of response spectral amplitudes with that of corresponding Fourier spectral amplitudes is motivated by that, the functional forms of response spectral GMPEs are often derived using the concepts borrowed from Fourier spectral modeling of ground motion. As these GMPEs are subsequently calibrated with empirical observations, this may not appear to pose any major problems in the prediction of ground motion for a particular earthquake scenario. However, the assumption that the Fourier spectral concepts persist for response spectra can lead to undesirable consequences when it comes to the adjustment of response spectral GMPEs to represent conditions not covered in the original empirical data set. In this context, a couple of important questions arise, e.g., what are the distinctions and/or similarities between Fourier and response spectra of ground-motions? And, if they are different, then what is the mechanism responsible for such differences and how do adjustments that are made to FAS manifest in response spectra? We explore the relationship between the Fourier and response spectrum of ground motion by using random vibration theory (RVT). With a simple Brune (1970, 1971) source model, RVT-generated acceleration spectra for a fixed magnitude and distance scenario are used. The RVT analyses reveal that the scaling of low oscillator-frequency response spectral ordinates can be treated as being equivalent to the scaling of the corresponding Fourier spectral ordinates. However, the high oscillator-frequency response spectral ordinates are controlled by a rather wide-band of Fourier spectral ordinates. In fact, the peak ground acceleration (PGA), counter to the popular perception that it is a reflection of the high-frequency characteristics of ground motion, is controlled by the entire Fourier spectrum of ground-motion. Finally, it is demonstrated, how an adjustment made in Fourier spectral amplitudes is different or similar to the same adjustment made in the response spectral amplitudes. For this purpose, two cases: adjustments to the stress parameter (Δσ) (source term) and to attributes reflecting site response (V s-κ0) are considered.

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

DTIC Science & Technology

2005-04-01

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

IRAS Low Resolution Spectra of Asteroids

NASA Technical Reports Server (NTRS)

Cohen, Martin; Walker, Russell G.

2002-01-01

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

Probing collective oscillation of d-orbital electrons at the nanoscale

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

Effect of gold photocathode contamination on a flat spectral response X-ray diode

NASA Astrophysics Data System (ADS)

Wang, Kun-lun; Zhang, Si-qun; Zhou, Shao-tong; Huang, Xian-bin; Ren, Xiao-dong; Dan, Jia-kun; Xu, Qiang

2018-03-01

A detector with an approximately flat spectral response is important for diagnosing intense thermal X-ray flux. A flat-spectral-response X-ray diode (FSR-XRD) utilizes a gold photocathode X-ray diode and a specially configured gold filter to give rise to a nearly flat spectral response in the photon energy range of 100-4000 eV. It has been observed that the spectral responses of several FSR-XRDs changed after a few shots of z-pinch experiments on the Primary Test Stand facility. This paper presents an analysis of the changes by fitting the spectral responses of the gold photocathodes using a model with a free parameter which characterizes the thickness of the contamination. The spectral responses of FSR-XRDs were calibrated with synchrotron radiation, and several cleaning methods were tested with the calibration. Considering the results of model and cleaning, it may be anticipated that contamination was the major reason of the response changing. Contamination worsened the flatness of the spectral response of the FSR-XRD and decreased the averaged response, hence it is important to avoid contamination. Current results indicate a requirement of further study of the contamination.

Modification of spectral features by nonhuman primates

PubMed Central

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

2017-01-01

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

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

NASA Technical Reports Server (NTRS)

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

1986-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-02-01

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

Identification of Fourier transform infrared photoacoustic spectral features for detection of Aspergillus flavus infection in corn.

PubMed

Gordon, S H; Schudy, R B; Wheeler, B C; Wicklow, D T; Greene, R V

1997-04-01

Aspergillus flavus and other pathogenic fungi display typical infrared spectra which differ significantly from spectra of substrate materials such as corn. On this basis, specific spectral features have been identified which permit detection of fungal infection on the surface of corn kernels by photoacoustic infrared spectroscopy. In a blind study, ten corn kernels showing bright greenish yellow fluorescence (BGYF) in the germ or endosperm and ten BGYF-negative kernels were correctly classified as infected or not infected by Fourier transform infrared photoacoustic spectroscopy. Earlier studies have shown that BGYF-positive kernels contain the bulk of the aflatoxin contaminating grain at harvest. Ten major spectral features, identified by visual inspection of the photoacoustic spectra of A. flavus mycelium grown in culture versus uninfected corn, were interpreted and assigned by theoretical comparisons of the relative chemical compositions of fungi and corn. The spectral features can be built into either empirical or knowledge-based computer models (expert systems) for automatic infrared detection and segregation of grains or kernels containing aflatoxin from the food and feed supply.

Thermally generated metals for plasmonic coloring and surface-enhanced Raman sensing

NASA Astrophysics Data System (ADS)

Huang, Zhenping; Chen, Jian; Liu, Guiqiang; Wang, Yan; Liu, Yi; Tang, Li; Liu, Zhengqi

2018-03-01

Spectral coloring glass and its application on the surface-enhanced Raman scattering are demonstrated experimentally via a simple and moderate heat-treating of the top ultrathin gold film to create discrete nanoparticles, which can produce localized surface plasmon resonances and strong plasmonic near-field coupling effects. Ultrathin metal films with a wide range of thicknesses are investigated by different heat-treatment processes. The annealed metal films have been demonstrated with a series of spectral coloring responses. Moreover, the microscopy images of the metal film structures confirm the formation of distinct geometry features in these operation procedures. Densely packed nanoparticles are observed for the ultrathin metal film with the single-digit level of thickness. With increasing the film thickness over 10 nm, metallic clusters and porous morphologies can be obtained. Importantly, the metallic resonators can provide enhanced Raman scattering with the detection limit down to 10 - 7 molL - 1 of Rhodamine 6G molecules due to the excitation of plasmon resonances and strong near-field coupling effects. These features hold great potential for large-scale and low-cost production of colored glass and Raman substrate.

The correction for spectral mismatch effects on the calibration of a solar cell when using a solar simulator

NASA Technical Reports Server (NTRS)

Seaman, C. H.

1981-01-01

A general expression was derived to enable calculation of the calibration error. The information required includes the relative spectral response of the reference cell, the relative spectral response of the cell under test, and the relative spectral irradiance of the simulator (over the spectral range defined by cell response). The spectral irradiance of the solar AMX is assumed to be known.

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

NASA Technical Reports Server (NTRS)

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

2000-01-01

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

Solar UV Variations During the Decline of Cycle 23

NASA Technical Reports Server (NTRS)

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

2011-01-01

Characterization of temporal and spectral variations in solar ultraviolet irradiance over a solar cycle is essential for understanding the forcing of Earth's atmosphere and climate. Satellite measurements of solar UV variability for solar cycles 21, 22, and 23 show consistent solar cycle irradiance changes at key wavelengths (e.g. 205 nm, 250 nm) within instrumental uncertainties. All historical data sets also show the same relative spectral dependence for both short-term (rotational) and long-term (solar cycle) variations. Empirical solar irradiance models also produce long-term solar UV variations that agree well with observational data. Recent UV irradiance data from the Solar Radiation and Climate Experiment (SORCE) Spectral Irradiance Monitor (SIM) and Solar Stellar Irradiance Comparison Experiment (SOLSTICE) instruments covering the declining phase of Cycle 23 present a different picture oflong-term solar variations from previous results. Time series of SIM and SOLSTICE spectral irradiance data between 2003 and 2007 show solar variations that greatly exceed both previous measurements and predicted irradiance changes over this period, and the spectral dependence of the SIM and SOLSTICE variations during these years do not show features expected from solar physics theory. The use of SORCE irradiance variations in atmospheric models yields substantially different middle atmosphere ozone responses in both magnitude and vertical structure. However, short-term solar variability derived from SIM and SOLSTICE UV irradiance data is consistent with concurrent solar UV measurements from other instruments, as well as previous results, suggesting no change in solar physics. Our analysis of short-term solar variability is much less sensitive to residual instrument response changes than the observations of long-term variations. The SORCE long-term UV results can be explained by under-correction of instrument response changes during the first few years of measurements, rather than requiring an unexpected change in the physical behavior of the Sun.

Constraints on the Compositions of Phobos and Deimos from Mineral Absorptions

NASA Technical Reports Server (NTRS)

Fraeman, A. A.; Murchie, S. L.; Arvidson, R. E.; Rivkin, A. S.; Morris, R. V.

2013-01-01

The compositions of Phobos and Deimos have remained controversial despite multiple Earth- and space-based observations acquired during the last 40 years. Phobos is composed of at least two spectral units that are both dark yet distinct at visible to near infrared wavelenghts; a spectrally red-sloped "red" unit covers most of the moon and a less red-sloped "blue" unit is present in the ejecta of the approximately 9-km diameter impact crater Stickney [1,2]. Deimos is similar spectrally to Phobos' "red" unit [2]. Here we report results from mapping mineral absorptions on Phobos and Deimos using visible/near infrared observations from the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM). We find evidence for an absorption feature at 0.65 m in the Phobos red unit and Deimos that is reproducible in observations from other instruments. The phase responsible is uncertain but may be a Fe-bearing phyllosilicate and/or graphite, consistent with the notion that Phobos and Deimos have compositions similar to CM carbonaceous chondrites [3].

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

NASA Astrophysics Data System (ADS)

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

2017-07-01

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

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

PubMed Central

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

2014-01-01

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

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

USGS Publications Warehouse

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

2006-01-01

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

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

NASA Astrophysics Data System (ADS)

An, G. Q.

2018-04-01

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

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

PubMed

Liu, Xue-Hua; Wu, Yan

2012-12-01

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

Effects of band selection on endmember extraction for forestry applications

NASA Astrophysics Data System (ADS)

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

2014-10-01

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

Constraining Cometary Crystal Shapes from IR Spectral Features

NASA Technical Reports Server (NTRS)

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

2013-01-01

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

Artifacts reduction in VIR/Dawn data.

PubMed

Carrozzo, F G; Raponi, A; De Sanctis, M C; Ammannito, E; Giardino, M; D'Aversa, E; Fonte, S; Tosi, F

2016-12-01

Remote sensing images are generally affected by different types of noise that degrade the quality of the spectral data (i.e., stripes and spikes). Hyperspectral images returned by a Visible and InfraRed (VIR) spectrometer onboard the NASA Dawn mission exhibit residual systematic artifacts. VIR is an imaging spectrometer coupling high spectral and spatial resolutions in the visible and infrared spectral domain (0.25-5.0 μm). VIR data present one type of noise that may mask or distort real features (i.e., spikes and stripes), which may lead to misinterpretation of the surface composition. This paper presents a technique for the minimization of artifacts in VIR data that include a new instrument response function combining ground and in-flight radiometric measurements, correction of spectral spikes, odd-even band effects, systematic vertical stripes, high-frequency noise, and comparison with ground telescopic spectra of Vesta and Ceres. We developed a correction of artifacts in a two steps process: creation of the artifacts matrix and application of the same matrix to the VIR dataset. In the approach presented here, a polynomial function is used to fit the high frequency variations. After applying these corrections, the resulting spectra show improvements of the quality of the data. The new calibrated data enhance the significance of results from the spectral analysis of Vesta and Ceres.

Research on oral test modeling based on multi-feature fusion

NASA Astrophysics Data System (ADS)

Shi, Yuliang; Tao, Yiyue; Lei, Jun

2018-04-01

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

Contamination of the 5394 Å spectral region by telluric lines

NASA Astrophysics Data System (ADS)

Vince, I.; Vince, O.

2010-11-01

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

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

NASA Astrophysics Data System (ADS)

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

2010-10-01

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

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

NASA Astrophysics Data System (ADS)

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

2014-08-01

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

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

PubMed

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

2014-08-14

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

Light-hole quantization in the optical response of ultra-wide GaAs/Al(x)Ga(1-x)As quantum wells.

PubMed

Solovyev, V V; Bunakov, V A; Schmult, S; Kukushkin, I V

2013-01-16

Temperature-dependent reflectivity and photoluminescence spectra are studied for undoped ultra-wide 150 and 250 nm GaAs quantum wells. It is shown that spectral features previously attributed to a size quantization of the exciton motion in the z-direction coincide well with energies of quantized levels for light holes. Furthermore, optical spectra reveal very similar properties at temperatures above the exciton dissociation point.

Ultrafast transient absorption revisited: Phase-flips, spectral fingers, and other dynamical features

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

Cina, Jeffrey A., E-mail: cina@uoregon.edu; Kovac, Philip A.; Jumper, Chanelle C.

We rebuild the theory of ultrafast transient-absorption/transmission spectroscopy starting from the optical response of an individual molecule to incident femtosecond pump and probe pulses. The resulting description makes use of pulse propagators and free molecular evolution operators to arrive at compact expressions for the several contributions to a transient-absorption signal. In this alternative description, which is physically equivalent to the conventional response-function formalism, these signal contributions are conveniently expressed as quantum mechanical overlaps between nuclear wave packets that have undergone different sequences of pulse-driven optical transitions and time-evolution on different electronic potential-energy surfaces. Using this setup in application to amore » simple, multimode model of the light-harvesting chromophores of PC577, we develop wave-packet pictures of certain generic features of ultrafast transient-absorption signals related to the probed-frequency dependence of vibrational quantum beats. These include a Stokes-shifting node at the time-evolving peak emission frequency, antiphasing between vibrational oscillations on opposite sides (i.e., to the red or blue) of this node, and spectral fingering due to vibrational overtones and combinations. Our calculations make a vibrationally abrupt approximation for the incident pump and probe pulses, but properly account for temporal pulse overlap and signal turn-on, rather than neglecting pulse overlap or assuming delta-function excitations, as are sometimes done.« less

DFT/TD-DFT study of solvent effect as well the substituents influence on the different features of TPP derivatives for PDT application

NASA Astrophysics Data System (ADS)

Dulski, Mateusz; Kempa, Marta; Kozub, Patrycja; Wójcik, Justyna; Rojkiewicz, Marcin; Kuś, Piotr; Szurko, Agnieszka; Ratuszna, Alicja; Wrzalik, Roman

2013-03-01

Spectral characteristics study of meso-tetraphenylporphyrin derivatives (TPP1 and TPP2) used as photosensitizers for utilization in photodynamic therapy (PDT) has been performed by density functional theory (DFT) and time dependent DFT (TD-DFT) calculations at B3LYP/6-31G(d) level of theory using PCM solvation model. The geometrical parameters of porphyrins have been studied for ground and excited-state geometry to deduce the influence of various substituents as well as solvent effect on the deformation of porphyrin ring. Two theoretical approaches - linear response (LR) and external iteration (EI) - have been performed to replicate absorption and fluorescence emission spectra. Experimental and theoretical investigations have shown that EI method reproduces the absorption energies very well for both singlet-singlet and triplet-triplet transitions, whereas the LR approach is more coherent with experimental fluorescence emission spectra. Spectral features and HOMO-LUMO band gap analysis have shown that TPP1 can be more useful in PDT. Calculations have revealed that two the highest occupied and two the lowest unoccupied molecular orbitals are responsible for the Q-band absorption and are located mainly on the porphyrin ring. In order to verify the substituent effect on the activity of tested compounds in their ground and excited states, the molecular electrostatic potential surfaces have been analyzed.

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

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

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

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

Physical and Hydrological Meaning of the Spectral Information from Hydrodynamic Signals at Karst Springs

NASA Astrophysics Data System (ADS)

Dufoyer, A.; Lecoq, N.; Massei, N.; Marechal, J. C.

2017-12-01

Physics-based modeling of karst systems remains almost impossible without enough accurate information about the inner physical characteristics. Usually, the only available hydrodynamic information is the flow rate at the karst outlet. Numerous works in the past decades have used and proven the usefulness of time-series analysis and spectral techniques applied to spring flow, precipitations or even physico-chemical parameters, for interpreting karst hydrological functioning. However, identifying or interpreting the karst systems physical features that control statistical or spectral characteristics of spring flow variations is still challenging, not to say sometimes controversial. The main objective of this work is to determine how the statistical and spectral characteristics of the hydrodynamic signal at karst springs can be related to inner physical and hydraulic properties. In order to address this issue, we undertake an empirical approach based on the use of both distributed and physics-based models, and on synthetic systems responses. The first step of the research is to conduct a sensitivity analysis of time-series/spectral methods to karst hydraulic and physical properties. For this purpose, forward modeling of flow through several simple, constrained and synthetic cases in response to precipitations is undertaken. It allows us to quantify how the statistical and spectral characteristics of flow at the outlet are sensitive to changes (i) in conduit geometries, and (ii) in hydraulic parameters of the system (matrix/conduit exchange rate, matrix hydraulic conductivity and storativity). The flow differential equations resolved by MARTHE, a computer code developed by the BRGM, allows karst conduits modeling. From signal processing on simulated spring responses, we hope to determine if specific frequencies are always modified, thanks to Fourier series and multi-resolution analysis. We also hope to quantify which parameters are the most variable with auto-correlation analysis: first results seem to show higher variations due to conduit conductivity than the ones due to matrix/conduit exchange rate. Future steps will be using another computer code, based on double-continuum approach and allowing turbulent conduit flow, and modeling a natural system.

Plant phenolics and absorption features in vegetation reflectance spectra near 1.66 μm

NASA Astrophysics Data System (ADS)

Kokaly, Raymond F.; Skidmore, Andrew K.

2015-12-01

Past laboratory and field studies have quantified phenolic substances in vegetative matter from reflectance measurements for understanding plant response to herbivores and insect predation. Past remote sensing studies on phenolics have evaluated crop quality and vegetation patterns caused by bedrock geology and associated variations in soil geochemistry. We examined spectra of pure phenolic compounds, common plant biochemical constituents, dry leaves, fresh leaves, and plant canopies for direct evidence of absorption features attributable to plant phenolics. Using spectral feature analysis with continuum removal, we observed that a narrow feature at 1.66 μm is persistent in spectra of manzanita, sumac, red maple, sugar maple, tea, and other species. This feature was consistent with absorption caused by aromatic Csbnd H bonds in the chemical structure of phenolic compounds and non-hydroxylated aromatics. Because of overlapping absorption by water, the feature was weaker in fresh leaf and canopy spectra compared to dry leaf measurements. Simple linear regressions of feature depth and feature area with polyphenol concentration in tea resulted in high correlations and low errors (% phenol by dry weight) at the dry leaf (r2 = 0.95, RMSE = 1.0%, n = 56), fresh leaf (r2 = 0.79, RMSE = 2.1%, n = 56), and canopy (r2 = 0.78, RMSE = 1.0%, n = 13) levels of measurement. Spectra of leaves, needles, and canopies of big sagebrush and evergreens exhibited a weak absorption feature centered near 1.63 μm, short ward of the phenolic compounds, possibly consistent with terpenes. This study demonstrates that subtle variation in vegetation spectra in the shortwave infrared can directly indicate biochemical constituents and be used to quantify them. Phenolics are of lesser abundance compared to the major plant constituents but, nonetheless, have important plant functions and ecological significance. Additional research is needed to advance our understanding of the spectral influences of plant phenolics and terpenes relative to dominant leaf biochemistry (water, chlorophyll, protein/nitrogen, cellulose, and lignin).

The Mysterious 6565 Å Absorption Feature of the Galactic Halo

NASA Astrophysics Data System (ADS)

Sethi, Shiv K.; Shchekinov, Yuri; Nath, Biman B.

2017-12-01

We consider various possible scenarios to explain the recent observation of what has been called a broad Hα absorption in our Galactic halo, with peak optical depth τ ≃ 0.01 and equivalent width W≃ 0.17 \\mathringA . We show that the absorbed feature cannot arise from the circumgalactic and ISM Hα absorption. As the observed absorption feature is quite broad ({{Δ }}λ ≃ 30 \\mathringA ), we also consider CNO lines that lie close to Hα as possible alternatives to explain the feature. We show that such lines could also not account for the observed feature. Instead, we suggest that it could arise from diffuse interstellar bands (DIBs) carriers or polyaromatic hydrocarbons (PAHs) absorption. While we identify several such lines close to the Hα transition, we are unable to determine the molecule responsible for the observed feature, partly because of selection effects that prevent us from identifying DIBs/PAHs features close to Hα using local observations. Deep integration of a few extragalactic sources with high spectral resolution might allow us to distinguish between different possible explanations.

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

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

DTIC Science & Technology

2012-12-17

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

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

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

NASA Astrophysics Data System (ADS)

Hajda, John Michael

1999-06-01

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

Utilization of a balanced steady state free precession signal model for improved fat/water decomposition.

PubMed

Henze Bancroft, Leah C; Strigel, Roberta M; Hernando, Diego; Johnson, Kevin M; Kelcz, Frederick; Kijowski, Richard; Block, Walter F

2016-03-01

Chemical shift based fat/water decomposition methods such as IDEAL are frequently used in challenging imaging environments with large B0 inhomogeneity. However, they do not account for the signal modulations introduced by a balanced steady state free precession (bSSFP) acquisition. Here we demonstrate improved performance when the bSSFP frequency response is properly incorporated into the multipeak spectral fat model used in the decomposition process. Balanced SSFP allows for rapid imaging but also introduces a characteristic frequency response featuring periodic nulls and pass bands. Fat spectral components in adjacent pass bands will experience bulk phase offsets and magnitude modulations that change the expected constructive and destructive interference between the fat spectral components. A bSSFP signal model was incorporated into the fat/water decomposition process and used to generate images of a fat phantom, and bilateral breast and knee images in four normal volunteers at 1.5 Tesla. Incorporation of the bSSFP signal model into the decomposition process improved the performance of the fat/water decomposition. Incorporation of this model allows rapid bSSFP imaging sequences to use robust fat/water decomposition methods such as IDEAL. While only one set of imaging parameters were presented, the method is compatible with any field strength or repetition time. © 2015 Wiley Periodicals, Inc.

Multiwavelength Spectral Variability of Mkn 501 in Outburst

NASA Astrophysics Data System (ADS)

Hempfling, Christina

2012-10-01

We propose simultaneous multiwavelength observations of the blazar Mrk501 in flaring state with XMM-Newton, FACT and Swift. Bright TeV gamma-ray flares have been detected repeatedly from Mrk501. Leptonic blazar models predict an simultaneous increase in the gamma-ray and X-ray bands. However, Mrk 501 also showed so-called orphan flares, as well as flares featuring time lags that are hard to explain by current models. Available data lack detailed light curves and hence are not sufficient to make strong statements on the nature of the responsible processes. These observations of a flare of Mrk501 in the gamma-ray and X-ray band with high spectral sensitivity and time resolution will yield a big contribution to the comprehension of blazar emission processes.

Composition and structure of fresh ammonia clouds on Jupiter based on quantitative analysis of Galileo/NIMS and New Horizons/LEISA spectra

NASA Astrophysics Data System (ADS)

Sromovsky, L. A.; Fry, P. M.

2018-06-01

Ammonia gas has long been assumed to be the main source of condensables for the upper cloud layer on Jupiter, but distinctive spectral features associated with ammonia have been seen only rarely. Since both ammonia and NH4SH absorb in the 3 μm region, and widespread absorption in the 3 μm region was present (Sromovsky and Fry, 2010), identification of the 2 μm absorption feature of NH3 provided an opportunity to clearly establish its presence in Jovian clouds. Baines et al. (2002) succeeded in finding in Near Infrared Mapping Spectrometer (NIMS) observations one feature that had both 2 μm and 3 μm absorption, and many which were known to have absorption at 2.73 μm. They named these Spectrally Identifiable Ammonia Clouds (SIACs). They also argued that these were fresh ammonia clouds that would eventually succumb to some process that would obscure their absorption features. Detection of many more of the 2 μm features was later achieved by New Horizon's Linear Etalon Imaging Spectral Array (LEISA) instrument, which provided both the spatial and spectral resolution needed to identify these features. Here we report on the first quantitative modeling that uses NIMS spectra over a broad (1-5.2 μm) spectral range and LEISA spectra over a much narrower (1.25-2.5 μm) spectral range to constrain the cloud structure and composition of these rare cloud features and compare them to background clouds. We find that the absorption signature at 2 μm, which is well characterized in LEISA spectra, is relatively subtle and easily matched by model clouds containing spherical particles of ammonia ice with radii of 2-4 μm. The NIMS spectra, which cover both reflected sunlight as well as thermal emission regions are more difficult to model with cloud materials plausibly present in Jupiter's atmosphere. The best signal/noise spectra obtained from NIMS provide a relatively sparse sampling of the spectrum, which does not establish the detailed shape of the 3 μm absorption region. NIMS SIAC spectra with much denser spectral sampling are limited by much higher noise levels that degrade the features that are key to identifying cloud composition. The structure which best matches the wide range NIMS SIAC spectra contains two overlapping NH3 clouds with a bi-modal size distribution over an optically thick NH4SH cloud. The bi-modal distribution may be a result of modeling non-spherical, possibly fractal aggregate, particles with spheres.

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

NASA Technical Reports Server (NTRS)

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

1992-01-01

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

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

NASA Technical Reports Server (NTRS)

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

1990-01-01

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

Characterization of various Si-photodiode junction combinations and layout specialities in 0.18µm CMOS and HV-CMOS technologies

NASA Astrophysics Data System (ADS)

Jonak-Auer, I.; Synooka, O.; Kraxner, A.; Roger, F.

2017-12-01

With the ongoing miniaturization of CMOS technologies the need for integrated optical sensors on smaller scale CMOS nodes arises. In this paper we report on the development and implementation of different optical sensor concepts in high performance 0.18µm CMOS and high voltage (HV) CMOS technologies on three different substrate materials. The integration process is such that complete modularity of the CMOS processes remains untouched and no additional masks or ion implantation steps are necessary for the sensor integration. The investigated processes support 1.8V and 3V standard CMOS functionality as well as HV transistors capable of operating voltages of 20V and 50V. These processes intrinsically offer a wide variety of junction combinations, which can be exploited for optical sensing purposes. The availability of junction depths from submicron to several microns enables the selection of spectral range from blue to infrared wavelengths. By appropriate layout the contributions of photo-generated carriers outside the target spectral range can be kept to a minimum. Furthermore by making use of other features intrinsically available in 0.18µm CMOS and HV-CMOS processes dark current rates of optoelectronic devices can be minimized. We present TCAD simulations as well as spectral responsivity, dark current and capacitance data measured for various photodiode layouts and the influence of different EPI and Bulk substrate materials thereon. We show examples of spectral responsivity of junction combinations optimized for peak sensitivity in the ranges of 400-500nm, 550-650nm and 700-900nm. Appropriate junction combination enables good spectral resolution for colour sensing applications even without any additional filter implementation. We also show that by appropriate use of shallow trenches dark current values of photodiodes can further be reduced.

Progressively expanded neural network for automatic material identification in hyperspectral imagery

NASA Astrophysics Data System (ADS)

Paheding, Sidike

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

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

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

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

2016-02-20

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

Probing collective oscillation of d -orbital electrons at the nanoscale

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

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

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

Climate variability related to the 11 year solar cycle as represented in different spectral solar irradiance reconstructions

NASA Astrophysics Data System (ADS)

Kruschke, Tim; Kunze, Markus; Misios, Stergios; Matthes, Katja; Langematz, Ulrike; Tourpali, Kleareti

2016-04-01

Advanced spectral solar irradiance (SSI) reconstructions differ significantly from each other in terms of the mean solar spectrum, that is the spectral distribution of energy, and solar cycle variability. Largest uncertainties - relative to mean irradiance - are found for the ultraviolet range of the spectrum, a spectral region highly important for radiative heating and chemistry in the stratosphere and troposphere. This study systematically analyzes the effects of employing different SSI reconstructions in long-term (40 years) chemistry-climate model (CCM) simulations to estimate related uncertainties of the atmospheric response. These analyses are highly relevant for the next round of CCM studies as well as climate models within the CMIP6 exercise. The simulations are conducted by means of two state-of-the-art CCMs - CESM1(WACCM) and EMAC - run in "atmosphere-only"-mode. These models are quite different with respect to the complexity of the implemented radiation and chemistry schemes. CESM1(WACCM) features a chemistry module with considerably higher spectral resolution of the photolysis scheme while EMAC employs a radiation code with notably higher spectral resolution. For all simulations, concentrations of greenhouse gases and ozone depleting substances, as well as observed sea surface temperatures (SST) are set to average conditions representative for the year 2000 (for SSTs: mean of decade centered over year 2000) to exclude anthropogenic influences and differences due to variable SST forcing. Only the SSI forcing differs for the various simulations. Four different forcing datasets are used: NRLSSI1 (used as a reference in all previous climate modeling intercomparisons, i.e. CMIP5, CCMVal, CCMI), NRLSSI2, SATIRE-S, and the SSI forcing dataset recommended for the CMIP6 exercise. For each dataset, a solar maximum and minimum timeslice is integrated, respectively. The results of these simulations - eight in total - are compared to each other with respect to their shortwave heating rate differences (additionally collated with line-by-line calculations using libradtran), differences in the photolysis rates, as well as atmospheric circulation features (temperature, zonal wind, geopotential height, etc.). It is shown that atmospheric responses to the different SSI datasets differ significantly from each other. This is a result from direct radiative effects as well as indirect effects induced by ozone feedbacks. Differences originating from using different SSI datasets for the same level of solar activity are in the same order of magnitude as those associated with the 11 year solar cycle within a specific dataset. However, the climate signals related to the solar cycle are quite comparable across datasets.

Thermal Effects of Lunar Surface Roughness: Application for the 2008 LRO Diviner Lunar Radiometer Experiment

NASA Astrophysics Data System (ADS)

Greenhagen, B.; Paige, D. A.

2007-12-01

It is well known that surface roughness affects spectral slope in the infrared. For the first time, we applied a three-dimensional thermal model to a high resolution lunar topography map to study the effects of surface roughness on lunar thermal emission spectra. We applied a numerical instrument model of the upcoming Diviner Lunar Radiometer Experiment (DLRE) to simulate the expected instrument response to surface roughness variations. The Diviner Lunar Radiometer Experiment (DLRE) will launch in late 2008 onboard the Lunar Reconnaissance Orbiter (LRO). DLRE is a nine-channel radiometer designed to study the thermal and petrologic properties of the lunar surface. DLRE has two solar channels (0.3-3.0 μm high/low sensitivity), three mid-infrared petrology channels (7.55-8.05, 8.10-8.40 8.40-8.70 μm), and four thermal infrared channels (12.5-25, 25-50, 50-100, and 100-200 μm). The topographic data we used was selected from a USGS Hadley Rille DEM (from Apollo 15 Panoramic Camera data) with 10 m resolution (M. Rosiek; personal communication). To remove large scale topographic features, we applied a 200 x 200 pixel boxcar high-pass filter to a relatively flat portion of the DEM. This "flattened" surface roughness map served as the basis for much of this study. We also examined the unaltered topography. Surface temperatures were calculated using a three-dimensional ray tracing thermal model. We created temperature maps at numerous solar incidence angles with nadir viewing geometry. A DLRE instrument model, which includes filter spectral responses and detector fields of view, was applied to the high resolution temperature maps. We studied both the thermal and petrologic effects of surface roughness. For the thermal study, the output of the optics model is a filter specific temperature, scaled to a DLRE footprint of < 500 m. For the petrologic study, we examined the effect of the surface roughness induced spectral slope on the DLRE's ability to locate the Christiansen Feature, which is a good compositional indicator. With multiple thermal infrared channels over a wide spectral range, DLRE will be well suited to measure temperature variations due to surface roughness. Any necessary compensation (e.g. correction for spectral slope) to the mid-infrared petrology data will be performed.

Network Receptive Field Modeling Reveals Extensive Integration and Multi-feature Selectivity in Auditory Cortical Neurons.

PubMed

Harper, Nicol S; Schoppe, Oliver; Willmore, Ben D B; Cui, Zhanfeng; Schnupp, Jan W H; King, Andrew J

2016-11-01

Cortical sensory neurons are commonly characterized using the receptive field, the linear dependence of their response on the stimulus. In primary auditory cortex neurons can be characterized by their spectrotemporal receptive fields, the spectral and temporal features of a sound that linearly drive a neuron. However, receptive fields do not capture the fact that the response of a cortical neuron results from the complex nonlinear network in which it is embedded. By fitting a nonlinear feedforward network model (a network receptive field) to cortical responses to natural sounds, we reveal that primary auditory cortical neurons are sensitive over a substantially larger spectrotemporal domain than is seen in their standard spectrotemporal receptive fields. Furthermore, the network receptive field, a parsimonious network consisting of 1-7 sub-receptive fields that interact nonlinearly, consistently better predicts neural responses to auditory stimuli than the standard receptive fields. The network receptive field reveals separate excitatory and inhibitory sub-fields with different nonlinear properties, and interaction of the sub-fields gives rise to important operations such as gain control and conjunctive feature detection. The conjunctive effects, where neurons respond only if several specific features are present together, enable increased selectivity for particular complex spectrotemporal structures, and may constitute an important stage in sound recognition. In conclusion, we demonstrate that fitting auditory cortical neural responses with feedforward network models expands on simple linear receptive field models in a manner that yields substantially improved predictive power and reveals key nonlinear aspects of cortical processing, while remaining easy to interpret in a physiological context.

Network Receptive Field Modeling Reveals Extensive Integration and Multi-feature Selectivity in Auditory Cortical Neurons

PubMed Central

Willmore, Ben D. B.; Cui, Zhanfeng; Schnupp, Jan W. H.; King, Andrew J.

2016-01-01

Cortical sensory neurons are commonly characterized using the receptive field, the linear dependence of their response on the stimulus. In primary auditory cortex neurons can be characterized by their spectrotemporal receptive fields, the spectral and temporal features of a sound that linearly drive a neuron. However, receptive fields do not capture the fact that the response of a cortical neuron results from the complex nonlinear network in which it is embedded. By fitting a nonlinear feedforward network model (a network receptive field) to cortical responses to natural sounds, we reveal that primary auditory cortical neurons are sensitive over a substantially larger spectrotemporal domain than is seen in their standard spectrotemporal receptive fields. Furthermore, the network receptive field, a parsimonious network consisting of 1–7 sub-receptive fields that interact nonlinearly, consistently better predicts neural responses to auditory stimuli than the standard receptive fields. The network receptive field reveals separate excitatory and inhibitory sub-fields with different nonlinear properties, and interaction of the sub-fields gives rise to important operations such as gain control and conjunctive feature detection. The conjunctive effects, where neurons respond only if several specific features are present together, enable increased selectivity for particular complex spectrotemporal structures, and may constitute an important stage in sound recognition. In conclusion, we demonstrate that fitting auditory cortical neural responses with feedforward network models expands on simple linear receptive field models in a manner that yields substantially improved predictive power and reveals key nonlinear aspects of cortical processing, while remaining easy to interpret in a physiological context. PMID:27835647

Planck 2013 results. IX. HFI spectral response

NASA Astrophysics Data System (ADS)

Planck Collaboration; Ade, P. A. R.; Aghanim, N.; Armitage-Caplan, C.; Arnaud, M.; Ashdown, M.; Atrio-Barandela, F.; Aumont, J.; Baccigalupi, C.; Banday, A. J.; Barreiro, R. B.; Battaner, E.; Benabed, K.; Benoît, A.; Benoit-Lévy, A.; Bernard, J.-P.; Bersanelli, M.; Bielewicz, P.; Bobin, J.; Bock, J. J.; Bond, J. R.; Borrill, J.; Bouchet, F. R.; Boulanger, F.; Bridges, M.; Bucher, M.; Burigana, C.; Cardoso, J.-F.; Catalano, A.; Challinor, A.; Chamballu, A.; Chary, R.-R.; Chen, X.; Chiang, H. C.; Chiang, L.-Y.; Christensen, P. R.; Church, S.; Clements, D. L.; Colombi, S.; Colombo, L. P. L.; Combet, C.; Comis, B.; Couchot, F.; Coulais, A.; Crill, B. P.; Curto, A.; Cuttaia, F.; Danese, L.; Davies, R. D.; de Bernardis, P.; de Rosa, A.; de Zotti, G.; Delabrouille, J.; Delouis, J.-M.; Désert, F.-X.; Dickinson, C.; Diego, J. M.; Dole, H.; Donzelli, S.; Doré, O.; Douspis, M.; Dupac, X.; Efstathiou, G.; Enßlin, T. A.; Eriksen, H. K.; Falgarone, E.; Finelli, F.; Forni, O.; Frailis, M.; Franceschi, E.; Galeotta, S.; Ganga, K.; Giard, M.; Giraud-Héraud, Y.; González-Nuevo, J.; Górski, K. M.; Gratton, S.; Gregorio, A.; Gruppuso, A.; Hansen, F. K.; Hanson, D.; Harrison, D.; Henrot-Versillé, S.; Hernández-Monteagudo, C.; Herranz, D.; Hildebrandt, S. R.; Hivon, E.; Hobson, M.; Holmes, W. A.; Hornstrup, A.; Hovest, W.; Huffenberger, K. M.; Hurier, G.; Jaffe, A. H.; Jaffe, T. R.; Jones, W. C.; Juvela, M.; Keihänen, E.; Keskitalo, R.; Kisner, T. S.; Kneissl, R.; Knoche, J.; Knox, L.; Kunz, M.; Kurki-Suonio, H.; Lagache, G.; Lamarre, J.-M.; Lasenby, A.; Laureijs, R. J.; Lawrence, C. R.; Leahy, J. P.; Leonardi, R.; Leroy, C.; Lesgourgues, J.; Liguori, M.; Lilje, P. B.; Linden-Vørnle, M.; López-Caniego, M.; Lubin, P. M.; Macías-Pérez, J. F.; Maffei, B.; Mandolesi, N.; Maris, M.; Marshall, D. J.; Martin, P. G.; Martínez-González, E.; Masi, S.; Massardi, M.; Matarrese, S.; Matthai, F.; Mazzotta, P.; McGehee, P.; Melchiorri, A.; Mendes, L.; Mennella, A.; Migliaccio, M.; Mitra, S.; Miville-Deschênes, M.-A.; Moneti, A.; Montier, L.; Morgante, G.; Mortlock, D.; Munshi, D.; Murphy, J. A.; Naselsky, P.; Nati, F.; Natoli, P.; Netterfield, C. B.; Nørgaard-Nielsen, H. U.; North, C.; Noviello, F.; Novikov, D.; Novikov, I.; Osborne, S.; Oxborrow, C. A.; Paci, F.; Pagano, L.; Pajot, F.; Paoletti, D.; Pasian, F.; Patanchon, G.; Perdereau, O.; Perotto, L.; Perrotta, F.; Piacentini, F.; Piat, M.; Pierpaoli, E.; Pietrobon, D.; Plaszczynski, S.; Pointecouteau, E.; Polenta, G.; Ponthieu, N.; Popa, L.; Poutanen, T.; Pratt, G. W.; Prézeau, G.; Prunet, S.; Puget, J.-L.; Rachen, J. P.; Reinecke, M.; Remazeilles, M.; Renault, C.; Ricciardi, S.; Riller, T.; Ristorcelli, I.; Rocha, G.; Rosset, C.; Roudier, G.; Rusholme, B.; Santos, D.; Savini, G.; Scott, D.; Shellard, E. P. S.; Spencer, L. D.; Starck, J.-L.; Stolyarov, V.; Stompor, R.; Sudiwala, R.; Sureau, F.; Sutton, D.; Suur-Uski, A.-S.; Sygnet, J.-F.; Tauber, J. A.; Tavagnacco, D.; Terenzi, L.; Tomasi, M.; Tristram, M.; Tucci, M.; Umana, G.; Valenziano, L.; Valiviita, J.; Van Tent, B.; Vielva, P.; Villa, F.; Vittorio, N.; Wade, L. A.; Wandelt, B. D.; Yvon, D.; Zacchei, A.; Zonca, A.

2014-11-01

The Planck High Frequency Instrument (HFI) spectral response was determined through a series of ground based tests conducted with the HFI focal plane in a cryogenic environment prior to launch. The main goal of the spectral transmission tests was to measure the relative spectral response (includingthe level of out-of-band signal rejection) of all HFI detectors to a known source of electromagnetic radiation individually. This was determined by measuring the interferometric output of a continuously scanned Fourier transform spectrometer with all HFI detectors. As there is no on-board spectrometer within HFI, the ground-based spectral response experiments provide the definitive data set for the relative spectral calibration of the HFI. Knowledge of the relative variations in the spectral response between HFI detectors allows for a more thorough analysis of the HFI data. The spectral response of the HFI is used in Planck data analysis and component separation, this includes extraction of CO emission observed within Planck bands, dust emission, Sunyaev-Zeldovich sources, and intensity to polarization leakage. The HFI spectral response data have also been used to provide unit conversion and colour correction analysis tools. While previous papers describe the pre-flight experiments conducted on the Planck HFI, this paper focusses on the analysis of the pre-flight spectral response measurements and the derivation of data products, e.g. band-average spectra, unit conversion coefficients, and colour correction coefficients, all with related uncertainties. Verifications of the HFI spectral response data are provided through comparisons with photometric HFI flight data. This validation includes use of HFI zodiacal emission observations to demonstrate out-of-band spectral signal rejection better than 108. The accuracy of the HFI relative spectral response data is verified through comparison with complementary flight-data based unit conversion coefficients and colour correction coefficients. These coefficients include those based upon HFI observations of CO, dust, and Sunyaev-Zeldovich emission. General agreement is observed between the ground-based spectral characterization of HFI and corresponding in-flight observations, within the quoted uncertainty of each; explanations are provided for any discrepancies.

Surface Composition of Trojan Asteroids from Thermal-Infrared Spectroscopy

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Supervised non-negative tensor factorization for automatic hyperspectral feature extraction and target discrimination

NASA Astrophysics Data System (ADS)

Anderson, Dylan; Bapst, Aleksander; Coon, Joshua; Pung, Aaron; Kudenov, Michael

2017-05-01

Hyperspectral imaging provides a highly discriminative and powerful signature for target detection and discrimination. Recent literature has shown that considering additional target characteristics, such as spatial or temporal profiles, simultaneously with spectral content can greatly increase classifier performance. Considering these additional characteristics in a traditional discriminative algorithm requires a feature extraction step be performed first. An example of such a pipeline is computing a filter bank response to extract spatial features followed by a support vector machine (SVM) to discriminate between targets. This decoupling between feature extraction and target discrimination yields features that are suboptimal for discrimination, reducing performance. This performance reduction is especially pronounced when the number of features or available data is limited. In this paper, we propose the use of Supervised Nonnegative Tensor Factorization (SNTF) to jointly perform feature extraction and target discrimination over hyperspectral data products. SNTF learns a tensor factorization and a classification boundary from labeled training data simultaneously. This ensures that the features learned via tensor factorization are optimal for both summarizing the input data and separating the targets of interest. Practical considerations for applying SNTF to hyperspectral data are presented, and results from this framework are compared to decoupled feature extraction/target discrimination pipelines.

Standardization of UV LED measurements

NASA Astrophysics Data System (ADS)

Eppeldauer, G. P.; Larason, T. C.; Yoon, H. W.

2015-09-01

Traditionally used source spectral-distribution or detector spectral-response based standards cannot be applied for accurate UV LED measurements. Since the CIE standardized rectangular-shape spectral response function for UV measurements cannot be realized with small spectral mismatch when using filtered detectors, the UV measurement errors can be several times ten percent or larger. The UV LEDs produce broadband radiation and both their peaks or spectral bandwidths can change significantly. The detectors used for the measurement of these LEDs also have different spectral bandwidths. In the discussed example, where LEDs with 365 nm peak are applied for fluorescent crack-recognition using liquid penetrant (non-destructive) inspection, the broadband radiometric LED (signal) measurement procedure is standardized. A UV LED irradiance-source was calibrated against an FEL lamp standard to determine its spectral irradiance. The spectral irradiance responsivity of a reference UV meter was also calibrated. The output signal of the reference UV meter was calculated from the spectral irradiance of the UV source and the spectral irradiance responsivity of the reference UV meter. From the output signal, both the integrated irradiance (in the reference plane of the reference meter) and the integrated responsivity of the reference meter were determined. Test UV meters calibrated for integrated responsivity against the reference UV meter, can be used to determine the integrated irradiance from a field UV source. The obtained 5 % (k=2) measurement uncertainty can be decreased when meters with spectral response close to a constant value are selected.

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

PubMed

Speier, William; Fried, Itzhak; Pouratian, Nader

2013-07-01

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

Behavioral state classification in epileptic brain using intracranial electrophysiology

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Factorization-based texture segmentation

DOE PAGES

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

2015-06-17

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

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

PubMed

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

2009-04-30

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

A new approach for the calculation of response spectral density of a linear stationary random multidegree of freedom system

NASA Astrophysics Data System (ADS)

Sharan, A. M.; Sankar, S.; Sankar, T. S.

1982-08-01

A new approach for the calculation of response spectral density for a linear stationary random multidegree of freedom system is presented. The method is based on modifying the stochastic dynamic equations of the system by using a set of auxiliary variables. The response spectral density matrix obtained by using this new approach contains the spectral densities and the cross-spectral densities of the system generalized displacements and velocities. The new method requires significantly less computation time as compared to the conventional method for calculating response spectral densities. Two numerical examples are presented to compare quantitatively the computation time.

Spectroscopic remote sensing of the distribution and persistence of oil from the Deepwater Horizon spill in Barataria Bay marshes

USGS Publications Warehouse

Kokaly, Raymond F.; Couvillion, Brady; Holloway, JoAnn M.; Roberts, Dar A.; Ustin, Susan L.; Peterson, Seth H.; Khanna, Shruti; Piazza, Sarai C.

2013-01-01

We applied a spectroscopic analysis to Airborne Visible/InfraRed Imaging Spectrometer (AVIRIS) data collected from low and medium altitudes during and after the Deepwater Horizon oil spill to delineate the distribution of oil-damaged canopies in the marshes of Barataria Bay, Louisiana. Spectral feature analysis compared the AVIRIS data to reference spectra of oiled marsh by using absorption features centered near 1.7 and 2.3 μm, which arise from CH bonds in oil. AVIRIS-derived maps of oiled shorelines from the individual dates of July 31, September 14, and October 4, 2010, were 89.3%, 89.8%, and 90.6% accurate, respectively. A composite map at 3.5 m grid spacing, accumulated from the three dates, was 93.4% accurate in detecting oiled shorelines. The composite map had 100% accuracy for detecting damaged plant canopy in oiled areas that extended more than 1.2 m into the marsh. Spatial resampling of the AVIRIS data to 30 m reduced the accuracy to 73.6% overall. However, detection accuracy remained high for oiled canopies that extended more than 4 m into the marsh (23 of 28 field reference points with oil were detected). Spectral resampling of the 3.5 m AVIRIS data to Landsat Enhanced Thematic Mapper (ETM) spectral response greatly reduced the detection of oil spectral signatures. With spatial resampling of simulated Landsat ETM data to 30 m, oil signatures were not detected. Overall, ~ 40 km of coastline, marsh comprised mainly of Spartina alterniflora and Juncus roemerianus, were found to be oiled in narrow zones at the shorelines. Zones of oiled canopies reached on average 11 m into the marsh, with a maximum reach of 21 m. The field and airborne data showed that, in many areas, weathered oil persisted in the marsh from the first field survey, July 10, to the latest airborne survey, October 4, 2010. The results demonstrate the applicability of high spatial resolution imaging spectrometer data to identifying contaminants in the environment for use in evaluating ecosystem disturbance and response.

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

PubMed

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

2012-08-01

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

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

ERIC Educational Resources Information Center

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

1998-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2014-01-01

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

Ultrafast optical modulation of magneto-optical terahertz effects occurring in a graphene-loaded resonant metasurface

NASA Astrophysics Data System (ADS)

Zanotto, S.; Lange, C.; Maag, T.; Pitanti, A.; Miseikis, V.; Coletti, C.; Degl'Innocenti, R.; Baldacci, L.; Huber, R.; Tredicucci, A.

2016-09-01

In this paper we investigate the effect of a static magnetic field and of optical pumping on the transmittance of a hybrid graphene-split ring resonator metasurface. A significant modulation of the transmitted spectra is obtained, both by optical pumping, and by a combination of optical pumping and magnetostatic biasing. The transmittance modulation features spectral fingerprints that are characteristic of a non-trivial interplay between the bare graphene response and the split ring resonance.

Coherent Optical Transients and Spectral Line Narrowing Phenomena in Four Wave Mixing Spectroscopies: Theoretical and Experimental Studies.

NASA Astrophysics Data System (ADS)

Dugan, Mark Allen

1990-08-01

The theoretical basis for new signal transients and spectral features generated in field correlated four wave mixing (4WM) spectroscopies is developed. Special attention is given to those signal responses that are sensitive to phase/amplitude correlation among the input driving fields and not simply their intensity correlation. Thus, the cases of incoherent broadband excitation and of coherent short pulsed excitation will be discussed and compared. Applications to the coherent Raman spectroscopies, both electronically nonresonant and fully resonant, are analyzed. Novel interferometric oscillatory behavior is exposed in terms of field-matter detuning beats and matter-matter bi-level and tri-level quantum beats. In addition new detuning resonances are found that have sub-material linewidths and lock onto the mode frequency of the driven chromophore. These spectral features are a member of a class of bichromophore resonant lineshapes arising from nonlinear mixing with correlated driving fields. The origin of such bichromophore resonances can be based on a coupling between two field-matter superposition states driven by correlated fields on separate chromophores. Analytic results are presented and modelled to anticipate the experimental results presented in a following chapter. The onset of resolvable homogeneous electronic memory is reported in room temperature solutions of dye molecules. A narrowing of the homogeneous linewidths with increasing concentration of these dye solutions is observed in sub-picosecond photon echo experiments. This effect is attributed to aggregation which results in a delocalization of the electronic states over several molecules. Ultra -fast spectral diffusion in these dye aggregates is observed in stimulated photon echo measurements. Aggregate bands, seen in the linear absorption spectrum only at high concentrations, can be probed in more dilute solutions with nonlinear four wave mixing.

Microscopic and macroscopic spectral peculiarities of cutaneous tumours

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Spectral lags in different episodes of gamma-ray bursts

NASA Astrophysics Data System (ADS)

Jia, LanWei; Yi, TingFeng; Liang, EnWei

2013-08-01

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

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

NASA Technical Reports Server (NTRS)

Singer, R. B.

1981-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

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

NASA Technical Reports Server (NTRS)

Key, J.

1990-01-01

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

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

PubMed

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

2014-05-06

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

Biologically-inspired data decorrelation for hyper-spectral imaging

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

Going Deeper With Contextual CNN for Hyperspectral Image Classification.

PubMed

Lee, Hyungtae; Kwon, Heesung

2017-10-01

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

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

NASA Astrophysics Data System (ADS)

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

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

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

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

NASA Astrophysics Data System (ADS)

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

2015-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

Overview of Sentinel-2

NASA Astrophysics Data System (ADS)

Fernandez, Valerie; Martimort, Philippe; Spoto, Francois; Sy, Omar; Laberinti, Paolo

2013-10-01

GMES is a joint initiative of the European Commission (EC) and the European Space Agency (ESA), designed to establish a European capacity for the provision and use of operational monitoring information for environment and security applications. ESA's role in GMES is to provide the definition and the development of the space- and ground-related system elements. GMES Sentinel-2 mission provides continuity to services relying on multi-spectral highresolution optical observations over global terrestrial surfaces. The key mission objectives for Sentinel-2 are: (1) to provide systematic global acquisitions of high-resolution multi-spectral imagery with a high revisit frequency, (2) to provide enhanced continuity of multi-spectral imagery provided by the SPOT series of satellites, and (3) to provide observations for the next generation of operational products such as landcover maps, land change detection maps, and geophysical variables. Consequently, Sentinel-2 will directly contribute to the Land Monitoring, Emergency Response, and Security services. The corresponding user requirements have driven the design towards a dependable multi-spectral Earthobservation system featuring the MSI with 13 spectral bands spanning from the visible and the near infrared to the short wave infrared. The spatial resolution varies from 10 m to 60 m depending on the spectral band with a 290 km field of view. This unique combination of high spatial resolution, wide field of view and large spectral coverage will represent a major step forward compared to current multi-spectral missions. The mission foresees a series of satellites, each having a 7.25-year lifetime (extendable to 12 years) over a 20-year period starting with the launch of Sentinel-2A foreseen by mid-2014. During full operations two identical satellites will be maintained in the same sun synchronous orbit with a phase delay of 180° providing a revisit time of five days at the equator.

Empirical calibration of the near-infrared CaII triplet - IV. The stellar population synthesis models

NASA Astrophysics Data System (ADS)

Vazdekis, A.; Cenarro, A. J.; Gorgas, J.; Cardiel, N.; Peletier, R. F.

2003-04-01

We present a new evolutionary stellar population synthesis model, which predicts spectral energy distributions for single-age single-metallicity stellar populations (SSPs) at resolution 1.5 Å (FWHM) in the spectral region of the near-infrared CaII triplet feature. The main ingredient of the model is a new extensive empirical stellar spectral library that has been recently presented by Cenarro et al., which is composed of more than 600 stars with an unprecedented coverage of the stellar atmospheric parameters. Two main products of interest for stellar population analysis are presented. The first is a spectral library for SSPs with metallicities -1.7 < [Fe/H] < +0.2, a large range of ages (0.1-18 Gyr) and initial mass function (IMF) types. They are well suited to modelling galaxy data, since the SSP spectra, with flux-calibrated response curves, can be smoothed to the resolution of the observational data, taking into account the internal velocity dispersion of the galaxy, allowing the user to analyse the observed spectrum in its own system. We also produce integrated absorption-line indices (namely CaT*, CaT and PaT) for the same SSPs in the form of equivalent widths. We find the following behaviour for the CaII triplet feature in old-aged SSPs: (i) the strength of the CaT* index does not change much with time for all metallicities for ages larger than ~3 Gyr; (ii) this index shows a strong dependence on metallicity for values below [M/H]~-0.5 and (iii) for larger metallicities this feature does not show a significant dependence either on age or on the metallicity, being more sensitive to changes in the slope of power-like IMF shapes. The SSP spectra have been calibrated with measurements for globular clusters by Armandroff & Zinn, which are well reproduced, probing the validity of using the integrated CaII triplet feature for determining the metallicities of these systems. Fitting the models to two early-type galaxies of different luminosities (NGC 4478 and 4365), we find that the CaII triplet measurements cannot be fitted unless a very dwarf-dominated IMF is imposed, or if the Ca abundance is even lower than the Fe abundance. More details can be found in work by Cenarro et al.

Feature Selection Methods for Zero-Shot Learning of Neural Activity.

PubMed

Caceres, Carlos A; Roos, Matthew J; Rupp, Kyle M; Milsap, Griffin; Crone, Nathan E; Wolmetz, Michael E; Ratto, Christopher R

2017-01-01

Dimensionality poses a serious challenge when making predictions from human neuroimaging data. Across imaging modalities, large pools of potential neural features (e.g., responses from particular voxels, electrodes, and temporal windows) have to be related to typically limited sets of stimuli and samples. In recent years, zero-shot prediction models have been introduced for mapping between neural signals and semantic attributes, which allows for classification of stimulus classes not explicitly included in the training set. While choices about feature selection can have a substantial impact when closed-set accuracy, open-set robustness, and runtime are competing design objectives, no systematic study of feature selection for these models has been reported. Instead, a relatively straightforward feature stability approach has been adopted and successfully applied across models and imaging modalities. To characterize the tradeoffs in feature selection for zero-shot learning, we compared correlation-based stability to several other feature selection techniques on comparable data sets from two distinct imaging modalities: functional Magnetic Resonance Imaging and Electrocorticography. While most of the feature selection methods resulted in similar zero-shot prediction accuracies and spatial/spectral patterns of selected features, there was one exception; A novel feature/attribute correlation approach was able to achieve those accuracies with far fewer features, suggesting the potential for simpler prediction models that yield high zero-shot classification accuracy.

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

NASA Astrophysics Data System (ADS)

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

2004-09-01

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

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

NASA Technical Reports Server (NTRS)

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

1992-01-01

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

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

USGS Publications Warehouse

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

2004-01-01

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

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).

Spectral Measurements of Geosynchronous Satellites During Glint Season

DTIC Science & Technology

2015-01-01

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

Spectral-structural characteristics of the extremely scarce silver arsenic sulfosalts, proustite, smithite, trechmannite and xanthoconite: μ-Raman spectroscopy evidence

NASA Astrophysics Data System (ADS)

Kharbish, S.

2017-04-01

The spectral - structural features of the rare silver arsenic (Ag-As) sulfosalts, proustite, Ag3AsS3, and the extremely scarce smithite, AgAsS2, trechmannite, AgAsS2 and xanthoconite, Ag3AsS3, were studied by the μ-Raman technique. Stretching - bending vibrations of the pyramidal isolated and interconnected AsS3 groups were responsible for the Raman spectra of the studied sulfosalts. The symmetric and asymmetric stretching modes appear between 380 and 350 cm- 1, whereas those of bending (Ssbnd Assbnd S) vibrations between 335 and 280 cm- 1. The Assbnd S longer bond lengths absolutely demonstrate the red shift (i.e. decrease in energy) from xanthoconite to trechmannite, smithite and proustite and the lowering in FWHM in comparable vibrational modes.

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

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

USDA-ARS?s Scientific Manuscript database

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

Could near-infrared Raman spectroscopy be correlated with the METAVIR scores in liver lesions induced by hepatitis C virus?

NASA Astrophysics Data System (ADS)

Gaggini, Marcio Cesar Reino; Navarro, Ricardo Scarparo; Stefanini, Aline Reis; Sano, Rubens Sato; Silveira, Landulfo

2013-03-01

The liver is responsible for several basic functions in human body how the syntheses of the most main proteins and degradation process of toxins, drugs and alcohols. In present days, the viral hepatitis C is one of the highest causes of chronic hepatic illness worldwide, affecting around 3% of the world population. The liver biopsy is considered the gold standard for diagnosing hepatic fibrosis; however, the biopsies may be questioned because of potential sampling error, morbidity, possible mortality and relatively high costs. Spectroscopy techniques such as Raman spectroscopy have been used for diagnosis of human tissues, with favorable results. Raman spectroscopy has been employed to distinguish normal from hepatic lesions through spectral features mainly of proteins, nucleic acids and lipids. In this study, eleven patients with diagnoses of chronic hepatitis C underwent hepatic biopsies having two hepatic fragments collected: one was scored through METAVIR system and the other one was submitted to near-infrared Raman spectroscopy using a dispersive spectrometer (830 nm wavelength, 300 mW laser power and 20 s exposure time). Five spectra were collected in each fragment and submitted to Principal Components Analysis (PCA). Results showed a good correlation between the Raman spectroscopy features and the stage of hepatic fibrosis and inflammation. PCA showed that samples with higher degree of fibrosis presented higher amount of protein features (collagen), whereas samples of higher degree of inflammation presented higher features of hemoglobin, in accordance to the expected evolution of the chronic hepatitis. It has been found an important biomarker for the beginning of hepatic lesion (quinone) with a spectral feature at 1595 cm-1.

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

USGS Publications Warehouse

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

2004-01-01

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

Using high spectral resolution spectrophotometry to study broad mineral absorption features on Mars

NASA Technical Reports Server (NTRS)

Blaney, D. L.; Crisp, D.

1993-01-01

Traditionally telescopic measurements of mineralogic absorption features have been made using relatively low to moderate (R=30-300) spectral resolution. Mineralogic absorption features tend to be broad so high resolution spectroscopy (R greater than 10,000) does not provide significant additional compositional information. Low to moderate resolution spectroscopy allows an observer to obtain data over a wide wavelength range (hundreds to thousands of wavenumbers) compared to the several wavenumber intervals that are collected using high resolution spectrometers. However, spectrophotometry at high resolution has major advantages over lower resolution spectroscopy in situations that are applicable to studies of the Martian surface, i.e., at wavelengths where relatively weak surface absorption features and atmospheric gas absorption features both occur.

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

USGS Publications Warehouse

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

2003-01-01

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

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

NASA Technical Reports Server (NTRS)

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

2004-01-01

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

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

USGS Publications Warehouse

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

2004-01-01

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

Characterizing multivariate decoding models based on correlated EEG spectral features

PubMed Central

McFarland, Dennis J.

2013-01-01

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

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

PubMed

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

2010-06-01

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

Intraseasonal variability and tides in Makassar Strait

NASA Astrophysics Data System (ADS)

Susanto, R. Dwi; Gordon, Arnold L.; Sprintall, Janet; Herunadi, Bambang

2000-05-01

Intraseasonal variability and tides along the Makassar Strait, the major route of Indonesian throughflow, are investigated using spectral and time-frequency analyses which are applied to sea level, wind and mooring data. Semidiurnal and diurnal tides are dominant features, with higher (lower) semidiurnal (diurnal) energy in the north compared to the south. Sea levels and mooring data display intraseasonal variability which are probably a response to remotely forced Kelvin waves from the Indian Ocean through Lombok Strait and to Rossby waves from the Pacific Ocean. Sea levels in Tarakan and Balikpapan and Makassar mooring velocities reveal intraseasonal features with periods of 48-62 days associated with Rossby waves from the Sulawesi Sea. Kelvin wave features with periods of 67-100 days are seen in Bali (Lombok Strait), at the mooring sites and in Balikpapan, however, they are not seen in Tarakan, which implies that these waves diminish after passing through the Makassar Strait.

Tunable plasmonic toroidal terahertz metamodulator

NASA Astrophysics Data System (ADS)

Gerislioglu, Burak; Ahmadivand, Arash; Pala, Nezih

2018-04-01

Optical modulators are essential and strategic parts of micro- and nanophotonic circuits to encode electro-optical signals in the optical domain. Here, by using arrays of multipixel toroidal plasmonic terahertz (THz) metamolecules, we developed a functional plasmonic metamodulator with high efficiency and tunability. Technically, the dynamic toroidal dipole induces nonradiating charge-current arrangements leading to have an exquisite role in defining the inherent spectral features of various materials. By categorizing in a different family of multipoles far from the traditional electromagnetic multipoles, the toroidal dipole corresponds to poloidal currents flowing on the surface of a closed-loop torus. Utilizing the sensitivity of the optically driven toroidal momentum to the incident THz beam power and by employing both numerical tools and experimental analysis, we systematically studied the spectral response of the proposed THz plasmonic metadevice. In this Rapid Communication, we uncover a correlation between the existence and the excitation of the toroidal response and the incident beam power. This mechanism is employed to develop THz toroidal metamodulators with a strong potential to be employed for practical advanced and next-generation communication, filtering, and routing applications.

Spectral Irradiance Calibration in the Infrared. 7. 5-14 microns Spectroscopy of the Asteroids Ceres, Vesta, and Pallas

NASA Technical Reports Server (NTRS)

Cohen, Martin; Witteborn, Fred C.; Roush, Ted; Bregman, Jesse; Wooden, Diane

1996-01-01

We describe our efforts to seek "closure" in our infrared absolute calibration scheme by comparing spectra of asteroids, absolutely calibrated through reference stars, with "Standard Thermal Models" and "Thermophysical Models" for these bodies. Our use of continuous 5-14 microns airborne spectra provides complete sampling of the rise to, and peak, of the infrared spectral energy distribution and constrains these models. Such models currently support the absolute calibration of ISO-PHOT at far-infrared wave- lengths (as far as 300 microns), and contribute to that of the Mid-Infrared Spectrometer on the "Infrared Telescope in Space" in the 6-12 microns region. The best match to our observed spectra of Ceres and Vesta is a, standard thermal model using a beaming factor of unity. We also report the presence of three emissivity features in Ceres which may complicate the traditional model extrapolation to the far-infrared from contemporaneous ground-based N-band photometry that is used to support calibration of, for example, ISO-PHOT. While identification of specific materials that cause these features is not made, we discuss families of minerals that may be responsible.

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

NASA Astrophysics Data System (ADS)

Xin, Hangshu; Yu, Peiqiang

2013-10-01

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

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

PubMed

Xin, Hangshu; Yu, Peiqiang

2013-10-01

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

Joint Bayesian Component Separation and CMB Power Spectrum Estimation

NASA Technical Reports Server (NTRS)

Eriksen, H. K.; Jewell, J. B.; Dickinson, C.; Banday, A. J.; Gorski, K. M.; Lawrence, C. R.

2008-01-01

We describe and implement an exact, flexible, and computationally efficient algorithm for joint component separation and CMB power spectrum estimation, building on a Gibbs sampling framework. Two essential new features are (1) conditional sampling of foreground spectral parameters and (2) joint sampling of all amplitude-type degrees of freedom (e.g., CMB, foreground pixel amplitudes, and global template amplitudes) given spectral parameters. Given a parametric model of the foreground signals, we estimate efficiently and accurately the exact joint foreground- CMB posterior distribution and, therefore, all marginal distributions such as the CMB power spectrum or foreground spectral index posteriors. The main limitation of the current implementation is the requirement of identical beam responses at all frequencies, which restricts the analysis to the lowest resolution of a given experiment. We outline a future generalization to multiresolution observations. To verify the method, we analyze simple models and compare the results to analytical predictions. We then analyze a realistic simulation with properties similar to the 3 yr WMAP data, downgraded to a common resolution of 3 deg FWHM. The results from the actual 3 yr WMAP temperature analysis are presented in a companion Letter.

Dual-Pitch Processing Mechanisms in Primate Auditory Cortex

PubMed Central

Bendor, Daniel; Osmanski, Michael S.

2012-01-01

Pitch, our perception of how high or low a sound is on a musical scale, is a fundamental perceptual attribute of sounds and is important for both music and speech. After more than a century of research, the exact mechanisms used by the auditory system to extract pitch are still being debated. Theoretically, pitch can be computed using either spectral or temporal acoustic features of a sound. We have investigated how cues derived from the temporal envelope and spectrum of an acoustic signal are used for pitch extraction in the common marmoset (Callithrix jacchus), a vocal primate species, by measuring pitch discrimination behaviorally and examining pitch-selective neuronal responses in auditory cortex. We find that pitch is extracted by marmosets using temporal envelope cues for lower pitch sounds composed of higher-order harmonics, whereas spectral cues are used for higher pitch sounds with lower-order harmonics. Our data support dual-pitch processing mechanisms, originally proposed by psychophysicists based on human studies, whereby pitch is extracted using a combination of temporal envelope and spectral cues. PMID:23152599

Digital filtering implementations for the detection of broad spectral features by direct analysis of passive Fourier transform infrared interferograms.

PubMed

Tarumi, Toshiyasu; Small, Gary W; Combs, Roger J; Kroutil, Robert T

2004-04-01

Finite impulse response (FIR) filters and finite impulse response matrix (FIRM) filters are evaluated for use in the detection of volatile organic compounds with wide spectral bands by direct analysis of interferogram data obtained from passive Fourier transform infrared (FT-IR) measurements. Short segments of filtered interferogram points are classified by support vector machines (SVMs) to implement the automated detection of heated plumes of the target analyte, ethanol. The interferograms employed in this study were acquired with a downward-looking passive FT-IR spectrometer mounted on a fixed-wing aircraft. Classifiers are trained with data collected on the ground and subsequently used for the airborne detection. The success of the automated detection depends on the effective removal of background contributions from the interferogram segments. Removing the background signature is complicated when the analyte spectral bands are broad because there is significant overlap between the interferogram representations of the analyte and background. Methods to implement the FIR and FIRM filters while excluding background contributions are explored in this work. When properly optimized, both filtering procedures provide satisfactory classification results for the airborne data. Missed detection rates of 8% or smaller for ethanol and false positive rates of at most 0.8% are realized. The optimization of filter design parameters, the starting interferogram point for filtering, and the length of the interferogram segments used in the pattern recognition is discussed.

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

PubMed

Sousa, Daniel; Small, Christopher

2018-02-14

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

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

PubMed Central

Small, Christopher

2018-01-01

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

Monolithic CMOS imaging x-ray spectrometers

NASA Astrophysics Data System (ADS)

Kenter, Almus; Kraft, Ralph; Gauron, Thomas; Murray, Stephen S.

2014-07-01

The Smithsonian Astrophysical Observatory (SAO) in collaboration with SRI/Sarnoff is developing monolithic CMOS detectors optimized for x-ray astronomy. The goal of this multi-year program is to produce CMOS x-ray imaging spectrometers that are Fano noise limited over the 0.1-10keV energy band while incorporating the many benefits of CMOS technology. These benefits include: low power consumption, radiation "hardness", high levels of integration, and very high read rates. Small format test devices from a previous wafer fabrication run (2011-2012) have recently been back-thinned and tested for response below 1keV. These devices perform as expected in regards to dark current, read noise, spectral response and Quantum Efficiency (QE). We demonstrate that running these devices at rates ~> 1Mpix/second eliminates the need for cooling as shot noise from any dark current is greatly mitigated. The test devices were fabricated on 15μm, high resistivity custom (~30kΩ-cm) epitaxial silicon and have a 16 by 192 pixel format. They incorporate 16μm pitch, 6 Transistor Pinned Photo Diode (6TPPD) pixels which have ~40μV/electron sensitivity and a highly parallel analog CDS signal chain. Newer, improved, lower noise detectors have just been fabricated (October 2013). These new detectors are fabricated on 9μm epitaxial silicon and have a 1k by 1k format. They incorporate similar 16μm pitch, 6TPPD pixels but have ~ 50% higher sensitivity and much (3×) lower read noise. These new detectors have undergone preliminary testing for functionality in Front Illuminated (FI) form and are presently being prepared for back thinning and packaging. Monolithic CMOS devices such as these, would be ideal candidate detectors for the focal planes of Solar, planetary and other space-borne x-ray astronomy missions. The high through-put, low noise and excellent low energy response, provide high dynamic range and good time resolution; bright, time varying x-ray features could be temporally and spectrally resolved without saturation. We present details of our camera design and device performance with particular emphasis on those aspects of interest to single photon counting x-ray astronomy. These features include read noise, x-ray spectral response and quantum efficiency. Funding for this work has been provided in large part by NASA Grant NNX09AE86G and a grant from the Betty and Gordon Moore Foundation.

Optimum ArFi laser bandwidth for 10nm node logic imaging performance

NASA Astrophysics Data System (ADS)

Alagna, Paolo; Zurita, Omar; Timoshkov, Vadim; Wong, Patrick; Rechtsteiner, Gregory; Baselmans, Jan; Mailfert, Julien

2015-03-01

Lithography process window (PW) and CD uniformity (CDU) requirements are being challenged with scaling across all device types. Aggressive PW and yield specifications put tight requirements on scanner performance, especially on focus budgets resulting in complicated systems for focus control. In this study, an imec N10 Logic-type test vehicle was used to investigate the E95 bandwidth impact on six different Metal 1 Logic features. The imaging metrics that track the impact of light source E95 bandwidth on performance of hot spots are: process window (PW), line width roughness (LWR), and local critical dimension uniformity (LCDU). In the first section of this study, the impact of increasing E95 bandwidth was investigated to observe the lithographic process control response of the specified logic features. In the second section, a preliminary assessment of the impact of lower E95 bandwidth was performed. The impact of lower E95 bandwidth on local intensity variability was monitored through the CDU of line end features and the LWR power spectral density (PSD) of line/space patterns. The investigation found that the imec N10 test vehicle (with OPC optimized for standard E95 bandwidth of300fm) features exposed at 200fm showed pattern specific responses, suggesting areas of potential interest for further investigation.

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

NASA Astrophysics Data System (ADS)

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

2012-01-01

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

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

PubMed

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

2015-10-01

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

Search for Feo and Pyroxene on MERCURY?S Surface

NASA Astrophysics Data System (ADS)

Sprague, Ann L.; Emery, Joshua P.

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

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

PubMed

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

1995-07-01

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

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

PubMed

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

2017-10-20

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

Reverberation effects on directionality and response of stationary monopole and dipole sources in a wind tunnel

NASA Technical Reports Server (NTRS)

Baumeister, K. J.

1985-01-01

Analytical solutions for the three dimensional inhomogeneous wave equation with flow in a hardwall rectangular wind tunnel and in the free field are presented for a stationary monopole noise source. Dipole noise sources are calculated by combining two monopoles 180 deg out of phase. Numerical calculations for the modal content, spectral response and directivity for both monopole and dipole sources are presented. In addition, the effect of tunnel alterations, such as the addition of a mounting plate, on the tunnels reverberant response are considered. In the frequency range of practical importance for the turboprop response, important features of the free field directivity can be approximated in a hardwall wind tunnel with flow if the major lobe of the noise source is not directed upstream. However, for an omnidirectional source, such as a monopole, the hardwall wind tunnel and free field response are not comparable.

An evaluation of supervised classifiers for indirectly detecting salt-affected areas at irrigation scheme level

NASA Astrophysics Data System (ADS)

Muller, Sybrand Jacobus; van Niekerk, Adriaan

2016-07-01

Soil salinity often leads to reduced crop yield and quality and can render soils barren. Irrigated areas are particularly at risk due to intensive cultivation and secondary salinization caused by waterlogging. Regular monitoring of salt accumulation in irrigation schemes is needed to keep its negative effects under control. The dynamic spatial and temporal characteristics of remote sensing can provide a cost-effective solution for monitoring salt accumulation at irrigation scheme level. This study evaluated a range of pan-fused SPOT-5 derived features (spectral bands, vegetation indices, image textures and image transformations) for classifying salt-affected areas in two distinctly different irrigation schemes in South Africa, namely Vaalharts and Breede River. The relationship between the input features and electro conductivity measurements were investigated using regression modelling (stepwise linear regression, partial least squares regression, curve fit regression modelling) and supervised classification (maximum likelihood, nearest neighbour, decision tree analysis, support vector machine and random forests). Classification and regression trees and random forest were used to select the most important features for differentiating salt-affected and unaffected areas. The results showed that the regression analyses produced weak models (<0.4 R squared). Better results were achieved using the supervised classifiers, but the algorithms tend to over-estimate salt-affected areas. A key finding was that none of the feature sets or classification algorithms stood out as being superior for monitoring salt accumulation at irrigation scheme level. This was attributed to the large variations in the spectral responses of different crops types at different growing stages, coupled with their individual tolerances to saline conditions.

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

NASA Technical Reports Server (NTRS)

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

1989-01-01

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

Feature Selection for Ridge Regression with Provable Guarantees.

PubMed

Paul, Saurabh; Drineas, Petros

2016-04-01

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

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

NASA Technical Reports Server (NTRS)

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

1995-01-01

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

Adaptation to spectrally-rotated speech.

PubMed

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

2013-08-01

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

Using spectral information in forensic imaging.

PubMed

Miskelly, Gordon M; Wagner, John H

2005-12-20

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

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

PubMed

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

2006-05-01

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

Multitaper scan-free spectrum estimation using a rotational shear interferometer

NASA Astrophysics Data System (ADS)

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

2006-05-01

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

Relative spectral response calibration using Ti plasma lines

NASA Astrophysics Data System (ADS)

Teng, FEI; Congyuan, PAN; Qiang, ZENG; Qiuping, WANG; Xuewei, DU

2018-04-01

This work introduces the branching ratio (BR) method for determining relative spectral responses, which are needed routinely in laser induced breakdown spectroscopy (LIBS). Neutral and singly ionized Ti lines in the 250–498 nm spectral range are investigated by measuring laser-induced micro plasma near a Ti plate and used to calculate the relative spectral response of an entire LIBS detection system. The results are compared with those of the conventional relative spectral response calibration method using a tungsten halogen lamp, and certain lines available for the BR method are selected. The study supports the common manner of using BRs to calibrate the detection system in LIBS setups.

Hyperspectral Imaging Sensors and the Marine Coastal Zone

NASA Technical Reports Server (NTRS)

Richardson, Laurie L.

2000-01-01

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

Determination of Primary Spectral Bands for Remote Sensing of Aquatic Environments

DTIC Science & Technology

2007-12-20

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

Onboard spectral imager data processor

NASA Astrophysics Data System (ADS)

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

1999-10-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-09-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-10-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Textural signatures for wetland vegetation

NASA Technical Reports Server (NTRS)

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

1973-01-01

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

Plant phenolics and absorption features in vegetation reflectance spectra near 1.66 μm

USGS Publications Warehouse

Kokaly, Raymond F.; Skidmore, Andrew K

2015-01-01

Past laboratory and field studies have quantified phenolic substances in vegetative matter from reflectance measurements for understanding plant response to herbivores and insect predation. Past remote sensing studies on phenolics have evaluated crop quality and vegetation patterns caused by bedrock geology and associated variations in soil geochemistry. We examined spectra of pure phenolic compounds, common plant biochemical constituents, dry leaves, fresh leaves, and plant canopies for direct evidence of absorption features attributable to plant phenolics. Using spectral feature analysis with continuum removal, we observed that a narrow feature at 1.66 μm is persistent in spectra of manzanita, sumac, red maple, sugar maple, tea, and other species. This feature was consistent with absorption caused by aromatic C-H bonds in the chemical structure of phenolic compounds and non-hydroxylated aromatics. Because of overlapping absorption by water, the feature was weaker in fresh leaf and canopy spectra compared to dry leaf measurements. Simple linear regressions of feature depth and feature area with polyphenol concentration in tea resulted in high correlations and low errors (% phenol by dry weight) at the dry leaf (r2 = 0.95, RMSE = 1.0%, n = 56), fresh leaf (r2 = 0.79, RMSE = 2.1%, n = 56), and canopy (r2 = 0.78, RMSE = 1.0%, n = 13) levels of measurement. Spectra of leaves, needles, and canopies of big sagebrush and evergreens exhibited a weak absorption feature centered near 1.63 μm, short ward of the phenolic compounds, possibly consistent with terpenes. This study demonstrates that subtle variation in vegetation spectra in the shortwave infrared can directly indicate biochemical constituents and be used to quantify them. Phenolics are of lesser abundance compared to the major plant constituents but, nonetheless, have important plant functions and ecological significance. Additional research is needed to advance our understanding of the spectral influences of plant phenolics and terpenes relative to dominant leaf biochemistry (water, chlorophyll, protein/nitrogen, cellulose, and lignin).

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

NASA Technical Reports Server (NTRS)

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

2011-01-01

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

Examination of the spectral features of vegetation in 1987 AVIRIS data

NASA Technical Reports Server (NTRS)

Elvidge, Christopher D.

1988-01-01

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

Spectral features of solar plasma flows

NASA Astrophysics Data System (ADS)

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

2014-11-01

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

The design and application of a multi-band IR imager

NASA Astrophysics Data System (ADS)

Li, Lijuan

2018-02-01

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

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

PubMed

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

2015-08-19

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

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

PubMed Central

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

2015-01-01

Despite its intrinsic advantages, translation of laser induced breakdown spectroscopy for material identification has been often impeded by the lack of robustness of developed classification models, often due to the presence of spurious correlations. While a number of classifiers exhibiting high discriminatory power have been reported, efforts in establishing the subset of relevant spectral features that enable a fundamental interpretation of the segmentation capability and avoid the ‘curse of dimensionality’ have been lacking. Using LIBS data acquired from a set of secondary explosives, we investigate judicious feature selection approaches and architect two different chemometrics classifiers –based on feature selection through prerequisite knowledge of the sample composition and genetic algorithm, respectively. While the full spectral input results in classification rate of ca.92%, selection of only carbon to hydrogen spectral window results in near identical performance. Importantly, the genetic algorithm-derived classifier shows a statistically significant improvement to ca. 94% accuracy for prospective classification, even though the number of features used is an order of magnitude smaller. Our findings demonstrate the impact of rigorous feature selection in LIBS and also hint at the feasibility of using a discrete filter based detector thereby enabling a cheaper and compact system more amenable to field operations. PMID:26286630

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

NASA Astrophysics Data System (ADS)

Shi, Yue; Huang, Wenjiang; Zhou, Xianfeng

2017-04-01

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

Fusion of LBP and SWLD using spatio-spectral information for hyperspectral face recognition

NASA Astrophysics Data System (ADS)

Xie, Zhihua; Jiang, Peng; Zhang, Shuai; Xiong, Jinquan

2018-01-01

Hyperspectral imaging, recording intrinsic spectral information of the skin cross different spectral bands, become an important issue for robust face recognition. However, the main challenges for hyperspectral face recognition are high data dimensionality, low signal to noise ratio and inter band misalignment. In this paper, hyperspectral face recognition based on LBP (Local binary pattern) and SWLD (Simplified Weber local descriptor) is proposed to extract discriminative local features from spatio-spectral fusion information. Firstly, the spatio-spectral fusion strategy based on statistical information is used to attain discriminative features of hyperspectral face images. Secondly, LBP is applied to extract the orientation of the fusion face edges. Thirdly, SWLD is proposed to encode the intensity information in hyperspectral images. Finally, we adopt a symmetric Kullback-Leibler distance to compute the encoded face images. The hyperspectral face recognition is tested on Hong Kong Polytechnic University Hyperspectral Face database (PolyUHSFD). Experimental results show that the proposed method has higher recognition rate (92.8%) than the state of the art hyperspectral face recognition algorithms.

Insight into resolution enhancement in generalized two-dimensional correlation spectroscopy.

PubMed

Ma, Lu; Sikirzhytski, Vitali; Hong, Zhenmin; Lednev, Igor K; Asher, Sanford A

2013-03-01

Generalized two-dimensional correlation spectroscopy (2D-COS) can be used to enhance spectral resolution in order to help differentiate highly overlapped spectral bands. Despite the numerous extensive 2D-COS investigations, the origin of the 2D spectral resolution enhancement mechanism(s) is not completely understood. In the work here, we studied the 2D-COS of simulated spectra in order to develop new insights into the dependence of 2D-COS spectral features on the overlapping band separations, their intensities and bandwidths, and their band intensity change rates. We found that the features in the 2D-COS maps that are derived from overlapping bands were determined by the spectral normalized half-intensities and the total intensity changes of the correlated bands. We identified the conditions required to resolve overlapping bands. In particular, 2D-COS peak resolution requires that the normalized half-intensities of a correlating band have amplitudes between the maxima and minima of the normalized half-intensities of the overlapping bands.

Insight into Resolution Enhancement in Generalized Two-Dimensional Correlation Spectroscopy

PubMed Central

Ma, Lu; Sikirzhytski, Vitali; Hong, Zhenmin; Lednev, Igor K.; Asher, Sanford A.

2014-01-01

Generalized two-dimensional correlation spectroscopy (2D COS) can be used to enhance spectral resolution in order to help differentiate highly overlapped spectral bands. Despite the numerous extensive 2D COS investigations, the origin of the 2D spectral resolution enhancement mechanism(s) are not completely understood. In the work here we studied the 2D COS of simulated spectra in order to develop new insights into the dependence of the 2D COS spectral features on the overlapping band separations, their intensities and bandwidths, and their band intensity change rates. We find that the features in the 2D COS maps that derive from overlapping bands are determined by the spectral normalized half-intensities and the total intensity changes of the correlated bands. We identify the conditions required to resolve overlapping bands. In particular, 2D COS peak resolution requires that the normalized half-intensities of a correlating band have amplitudes between the maxima and minima of the normalized half-intensities of the overlapping bands. PMID:23452492

High-Energy Density science at the Linac Coherent Light Source

NASA Astrophysics Data System (ADS)

Glenzer, S. H.; Fletcher, L. B.; Hastings, J. B.

2016-03-01

The Matter in Extreme Conditions end station at the Linac Coherent Light Source holds great promise for novel pump-probe experiments to make new discoveries in high- energy density science. In recent experiments we have demonstrated the first spectrally- resolved measurements of plasmons using a seeded 8-keV x-ray laser beam. Forward x-ray Thomson scattering spectra from isochorically heated solid aluminum show a well-resolved plasmon feature that is down-shifted in energy by 19 eV from the incident 8 keV elastic scattering feature. In this spectral range, the simultaneously measured backscatter spectrum shows no spectral features indicating observation of collective plasmon oscillations on a scattering length comparable to the screening length. This technique is a prerequisite for Thomson scattering measurements in compressed matter where the plasmon shift is a sensitive function of the free electron density and where the plasmon intensity provides information on temperature.

High-Energy Density science at the Linac Coherent Light Source

DOE PAGES

Glenzer, S. H.; Fletcher, L. B.; Hastings, J. B.

2016-04-01

The Matter in Extreme Conditions end station at the Linac Coherent Light Source holds great promise for novel pump-probe experiments to make new discoveries in high- energy density science. Recently, our experiments have demonstrated the first spectrally- resolved measurements of plasmons using a seeded 8-keV x-ray laser beam. Forward x-ray Thomson scattering spectra from isochorically heated solid aluminum show a well-resolved plasmon feature that is down-shifted in energy by 19 eV from the incident 8 keV elastic scattering feature. In this spectral range, the simultaneously measured backscatter spectrum shows no spectral features indicating observation of collective plasmon oscillations on amore » scattering length comparable to the screening length. Moreover, this technique is a prerequisite for Thomson scattering measurements in compressed matter where the plasmon shift is a sensitive function of the free electron density and where the plasmon intensity provides information on temperature.« less

A Comparison of the Near-Infrared Spectral Features of Early-Type Galaxies in the Virgo and Coma Clusters

NASA Astrophysics Data System (ADS)

Houdashelt, M. L.

1992-05-01

Initial results are presented from an examination of near-infrared spectra (6800 - 9200 Angstroms) of 34 early-type galaxies - 17 in the Virgo cluster, 10 in the Coma cluster and seven field members. It has previously been speculated that E/S0 galaxies of similar luminosity in the Virgo and Coma clusters have different red stellar populations. To explore this possibility, pseudo-equivalent widths of a number of near-IR spectral features have been measured. The important features studied include the TiO bands near 7100, 7890, 8197, 8500 and 8950 Angstroms, which are mainly produced by the late-type stars whose flux contributes only about 10-20\\ the near-IR. The strengths of the Ca triplet (8498, 8542, 8662 Angstroms) and Na I doublet (8183, 8195 Angstroms) are also measured, since these features are affected by the relative contribution of dwarf stars to the red light. Although the main focus of this work is the search for spectral differences among the Coma, Virgo and field E/S0 populations, each subgroup of galaxies (and the sample as a whole) are also examined for correlations among the feature strengths, galaxy color and luminosity.

Spectrum Analyzers Incorporating Tunable WGM Resonators

NASA Technical Reports Server (NTRS)

Savchenkov, Anatoliy; Matsko, Andrey; Strekalov, Dmitry; Maleki, Lute

2009-01-01

A photonic instrument is proposed to boost the resolution for ultraviolet/ optical/infrared spectral analysis and spectral imaging allowing the detection of narrow (0.00007-to-0.07-picometer wavelength resolution range) optical spectral signatures of chemical elements in space and planetary atmospheres. The idea underlying the proposal is to exploit the advantageous spectral characteristics of whispering-gallery-mode (WGM) resonators to obtain spectral resolutions at least three orders of magnitude greater than those of optical spectrum analyzers now in use. Such high resolutions would enable measurement of spectral features that could not be resolved by prior instruments.

Spectral analysis for nonstationary and nonlinear systems: a discrete-time-model-based approach.

PubMed

He, Fei; Billings, Stephen A; Wei, Hua-Liang; Sarrigiannis, Ptolemaios G; Zhao, Yifan

2013-08-01

A new frequency-domain analysis framework for nonlinear time-varying systems is introduced based on parametric time-varying nonlinear autoregressive with exogenous input models. It is shown how the time-varying effects can be mapped to the generalized frequency response functions (FRFs) to track nonlinear features in frequency, such as intermodulation and energy transfer effects. A new mapping to the nonlinear output FRF is also introduced. A simulated example and the application to intracranial electroencephalogram data are used to illustrate the theoretical results.

The Spitzer Atlas of Stellar Spectra (SASS)

NASA Astrophysics Data System (ADS)

Ardila, D. R.; van Dyk, S. D., Makowiecki, W.; Stauffer, J.; Song, I.; Ro, J.; Fajardo-Acosta, S.; Hoard, D. W.; Wachter, S.

2011-11-01

We present the Spitzer Atlas of Stellar Spectra (SASS), which includes 159 stellar spectra (5 to 32 micron; R about 100) taken with the Infrared Spectrograph on the Spitzer Space Telescope. This Atlas gathers representative spectra of a broad section of the Hertzsprung-Russell diagram, intended to serve as a general stellar spectral reference in the mid-infrared. It includes stars from all luminosity classes, as well as Wolf-Rayet (WR) objects. Furthermore, it includes some objects of intrinsic interest, like blue stragglers and certain pulsating variables. All the spectra have been uniformly reduced, and all are available online. For dwarfs and giants, the spectra of early-type objects are relatively featureless, dominated by Hydrogen lines around A spectral types. Besides these, the most noticeable photospheric features correspond to water vapor and silicon monoxide in late-type objects and methane and ammonia features at the latest spectral types. Most supergiant spectra in the Atlas present evidence of circumstellar gas. The sample includes five M supergiant spectra, which show strong dust excesses and in some cases PAH features. Sequences of WR stars present the well-known pattern of lines of He I and He II, as well as forbidden lines of ionized metals. The characteristic flat-top shape of the [Ne III] line is evident even at these low spectral resolutions. Several Luminous Blue Variables and other transition stars are present in the Atlas and show very diverse spectra, dominated by circumstellar gas and dust features. We show that the [8]-[24] Spitzer colors (IRAC and MIPS) are poor predictors of spectral type for most luminosity classes.

Surface materials map of Afghanistan: iron-bearing minerals and other materials

USGS Publications Warehouse

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

2012-01-01

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

Field measurements of the spectral response of natural waters

NASA Technical Reports Server (NTRS)

Bartolucci, L. A.; Robinson, B. F.; Silva, L. F.

1977-01-01

The spectral response (air-water interface reflectance and water-volume scattering) of turbid river water (99 mg/liter suspended solids) and relatively clear lake water (10 mg/liter suspended solids) was measured in situ with a field spectroradiometer. The influence of the river bottom on the spectral response of the water also was determined by using a modified Secchi disc approach. The results indicated that turbid river water had a higher spectral response than clear lake water (about 6 percent) in the red (0.6-0.7 micron) and near-infrared (0.7-0.9 micron) portions of the spectrum. Also, the reflectance characteristics of the river bottom did not influence the spectral response of the turbid river water when the water was deeper than 30 cm

RESPONSE OF GRANULATION TO SMALL-SCALE BRIGHT FEATURES IN THE QUIET SUN

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

Andic, A.; Chae, J.; Goode, P. R.

2011-04-10

We detected 2.8 bright points (BPs) per Mm{sup 2} in the quiet Sun with the New Solar Telescope at Big Bear Solar Observatory, using the TiO 705.68 nm spectral line at an angular resolution {approx}0.''1 to obtain a 30 minute data sequence. Some BPs formed knots that were stable in time and influenced the properties of the granulation pattern around them. The observed granulation pattern within {approx}3'' of knots presents smaller granules than those observed in a normal granulation pattern, i.e., around the knots a suppressed convection is detected. Observed BPs covered {approx}5% of the solar surface and were notmore » homogeneously distributed. BPs had an average size of 0.''22, they were detectable for 4.28 minutes on average, and had an averaged contrast of 0.1% in the deep red TiO spectral line.« less

Spectral Domain RF Fingerprinting for 802.11 Wireless Devices

DTIC Science & Technology

2010-03-01

induce unintentional modulation effects . If these effects (features) are sufficiently unique, it becomes possible to identify a device us- ing its...Previous AFIT research has demonstrated the effectiveness of RF Fin- gerprinting using 802.11A signals with 1) spectral correlation on Power Spectral...32 4.5. SD Intra-manufacturer Classification: Effects of Burst Location Error

Feature Selection Methods for Zero-Shot Learning of Neural Activity

PubMed Central

Caceres, Carlos A.; Roos, Matthew J.; Rupp, Kyle M.; Milsap, Griffin; Crone, Nathan E.; Wolmetz, Michael E.; Ratto, Christopher R.

2017-01-01

Dimensionality poses a serious challenge when making predictions from human neuroimaging data. Across imaging modalities, large pools of potential neural features (e.g., responses from particular voxels, electrodes, and temporal windows) have to be related to typically limited sets of stimuli and samples. In recent years, zero-shot prediction models have been introduced for mapping between neural signals and semantic attributes, which allows for classification of stimulus classes not explicitly included in the training set. While choices about feature selection can have a substantial impact when closed-set accuracy, open-set robustness, and runtime are competing design objectives, no systematic study of feature selection for these models has been reported. Instead, a relatively straightforward feature stability approach has been adopted and successfully applied across models and imaging modalities. To characterize the tradeoffs in feature selection for zero-shot learning, we compared correlation-based stability to several other feature selection techniques on comparable data sets from two distinct imaging modalities: functional Magnetic Resonance Imaging and Electrocorticography. While most of the feature selection methods resulted in similar zero-shot prediction accuracies and spatial/spectral patterns of selected features, there was one exception; A novel feature/attribute correlation approach was able to achieve those accuracies with far fewer features, suggesting the potential for simpler prediction models that yield high zero-shot classification accuracy. PMID:28690513

Improved classification accuracy of powdery mildew infection levels of wine grapes by spatial-spectral analysis of hyperspectral images.

PubMed

Knauer, Uwe; Matros, Andrea; Petrovic, Tijana; Zanker, Timothy; Scott, Eileen S; Seiffert, Udo

2017-01-01

Hyperspectral imaging is an emerging means of assessing plant vitality, stress parameters, nutrition status, and diseases. Extraction of target values from the high-dimensional datasets either relies on pixel-wise processing of the full spectral information, appropriate selection of individual bands, or calculation of spectral indices. Limitations of such approaches are reduced classification accuracy, reduced robustness due to spatial variation of the spectral information across the surface of the objects measured as well as a loss of information intrinsic to band selection and use of spectral indices. In this paper we present an improved spatial-spectral segmentation approach for the analysis of hyperspectral imaging data and its application for the prediction of powdery mildew infection levels (disease severity) of intact Chardonnay grape bunches shortly before veraison. Instead of calculating texture features (spatial features) for the huge number of spectral bands independently, dimensionality reduction by means of Linear Discriminant Analysis (LDA) was applied first to derive a few descriptive image bands. Subsequent classification was based on modified Random Forest classifiers and selective extraction of texture parameters from the integral image representation of the image bands generated. Dimensionality reduction, integral images, and the selective feature extraction led to improved classification accuracies of up to [Formula: see text] for detached berries used as a reference sample (training dataset). Our approach was validated by predicting infection levels for a sample of 30 intact bunches. Classification accuracy improved with the number of decision trees of the Random Forest classifier. These results corresponded with qPCR results. An accuracy of 0.87 was achieved in classification of healthy, infected, and severely diseased bunches. However, discrimination between visually healthy and infected bunches proved to be challenging for a few samples, perhaps due to colonized berries or sparse mycelia hidden within the bunch or airborne conidia on the berries that were detected by qPCR. An advanced approach to hyperspectral image classification based on combined spatial and spectral image features, potentially applicable to many available hyperspectral sensor technologies, has been developed and validated to improve the detection of powdery mildew infection levels of Chardonnay grape bunches. The spatial-spectral approach improved especially the detection of light infection levels compared with pixel-wise spectral data analysis. This approach is expected to improve the speed and accuracy of disease detection once the thresholds for fungal biomass detected by hyperspectral imaging are established; it can also facilitate monitoring in plant phenotyping of grapevine and additional crops.

Comparative study of icy patches on comet nuclei

NASA Astrophysics Data System (ADS)

Oklay, Nilda; Pommerol, Antoine; Barucci, Maria Antonietta; Sunshine, Jessica; Sierks, Holger; Pajola, Maurizio

2016-07-01

Cometary missions Deep Impact, EPOXI and Rosetta investigated the nuclei of comets 9P/Tempel 1, 103P/Hartley 2 and 67P/Churyumov-Gerasimenko respectively. Bright patches were observed on the surfaces of each of these three comets [1-5]. Of these, the surface of 67P is mapped at the highest spatial resolution via narrow angle camera (NAC) of the Optical, Spectroscopic, and Infrared Remote Imaging System (OSIRIS, [6]) on board the Rosetta spacecraft. OSIRIS NAC is equipped with twelve filters covering the wavelength range of 250 nm to 1000 nm. Various filters combinations are used during surface mapping. With high spatial resolution data of comet 67P, three types of bright features were detected on the comet surface: Clustered, isolated and bright boulders [2]. In the visible spectral range, clustered bright features on comet 67P display bluer spectral slopes than the average surface [2, 4] while isolated bright features on comet 67P have flat spectra [4]. Icy patches observed on the surface of comets 9P and 103P display bluer spectral slopes than the average surface [1, 5]. Clustered and isolated bright features are blue in the RGB composites generated by using the images taken in NIR, visible and NUV wavelengths [2, 4]. This is valid for the icy patches observed on comets 9P and 103P [1, 5]. Spectroscopic observations of bright patches on comets 9P and 103P confirmed the existence of water [1, 5]. There were more than a hundred of bright features detected on the northern hemisphere of comet 67P [2]. Analysis of those features from both multispectral data and spectroscopic data is an ongoing work. Water ice is detected in eight of the bright features so far [7]. Additionally, spectroscopic observations of two clustered bright features on the surface of comet 67P revealed the existence of water ice [3]. The spectral properties of one of the icy patches were studied by [4] using OSIRIS NAC images and compared with the spectral properties of the active regions observed on comet 67P. Additionally jets rising from the same clustered bright feature were detected visually [4]. We analyzed bright patches on the surface of comets 9P, 103P and 67P using multispectral data obtained by the high-resolution instrument (HRI), medium- resolution instrument (MRI) and OSIRIS NAC using various spectral analysis techniques. Clustered bright features on comet 67P have similar visible spectra to the bright patches on comets 9P and 103P. The comparison of the bright patches includes the published results of the IR spectra. References: [1] Sunshine et al., 2006, Science, 311, 1453 [2] Pommerol et al., 2015, A&A, 583, A25 [3] Filacchione et al., 2016, Nature, 529, 368-372 [4] Oklay et al., 2016, A&A, 586, A80 [5] Sunshine et al. 2012, ACM [6] Keller et al., 2007, Space Sci. Rev., 128, 433 [7] Barucci et al., 2016, COSPAR, B04

National-scale cropland mapping based on spectral-temporal features and outdated land cover information.

PubMed

Waldner, François; Hansen, Matthew C; Potapov, Peter V; Löw, Fabian; Newby, Terence; Ferreira, Stefanus; Defourny, Pierre

2017-01-01

The lack of sufficient ground truth data has always constrained supervised learning, thereby hindering the generation of up-to-date satellite-derived thematic maps. This is all the more true for those applications requiring frequent updates over large areas such as cropland mapping. Therefore, we present a method enabling the automated production of spatially consistent cropland maps at the national scale, based on spectral-temporal features and outdated land cover information. Following an unsupervised approach, this method extracts reliable calibration pixels based on their labels in the outdated map and their spectral signatures. To ensure spatial consistency and coherence in the map, we first propose to generate seamless input images by normalizing the time series and deriving spectral-temporal features that target salient cropland characteristics. Second, we reduce the spatial variability of the class signatures by stratifying the country and by classifying each stratum independently. Finally, we remove speckle with a weighted majority filter accounting for per-pixel classification confidence. Capitalizing on a wall-to-wall validation data set, the method was tested in South Africa using a 16-year old land cover map and multi-sensor Landsat time series. The overall accuracy of the resulting cropland map reached 92%. A spatially explicit validation revealed large variations across the country and suggests that intensive grain-growing areas were better characterized than smallholder farming systems. Informative features in the classification process vary from one stratum to another but features targeting the minimum of vegetation as well as short-wave infrared features were consistently important throughout the country. Overall, the approach showed potential for routinely delivering consistent cropland maps over large areas as required for operational crop monitoring.

National-scale cropland mapping based on spectral-temporal features and outdated land cover information

PubMed Central

Hansen, Matthew C.; Potapov, Peter V.; Löw, Fabian; Newby, Terence; Ferreira, Stefanus; Defourny, Pierre

2017-01-01

The lack of sufficient ground truth data has always constrained supervised learning, thereby hindering the generation of up-to-date satellite-derived thematic maps. This is all the more true for those applications requiring frequent updates over large areas such as cropland mapping. Therefore, we present a method enabling the automated production of spatially consistent cropland maps at the national scale, based on spectral-temporal features and outdated land cover information. Following an unsupervised approach, this method extracts reliable calibration pixels based on their labels in the outdated map and their spectral signatures. To ensure spatial consistency and coherence in the map, we first propose to generate seamless input images by normalizing the time series and deriving spectral-temporal features that target salient cropland characteristics. Second, we reduce the spatial variability of the class signatures by stratifying the country and by classifying each stratum independently. Finally, we remove speckle with a weighted majority filter accounting for per-pixel classification confidence. Capitalizing on a wall-to-wall validation data set, the method was tested in South Africa using a 16-year old land cover map and multi-sensor Landsat time series. The overall accuracy of the resulting cropland map reached 92%. A spatially explicit validation revealed large variations across the country and suggests that intensive grain-growing areas were better characterized than smallholder farming systems. Informative features in the classification process vary from one stratum to another but features targeting the minimum of vegetation as well as short-wave infrared features were consistently important throughout the country. Overall, the approach showed potential for routinely delivering consistent cropland maps over large areas as required for operational crop monitoring. PMID:28817618

Inspection of baked carbon anodes using a combination of multi-spectral acousto-ultrasonic techniques and principal component analysis.

PubMed

Boubaker, Moez Ben; Picard, Donald; Duchesne, Carl; Tessier, Jayson; Alamdari, Houshang; Fafard, Mario

2018-05-17

This paper reports on the application of an acousto-ultrasonic (AU) scheme for the inspection of industrial-size carbon anode blocks used in the production of primary aluminium by the Hall-Héroult process. A frequency-modulated wave is used to excite the anode blocks at multiple points. The collected attenuated AU signals are decomposed using the Discrete Wavelet Transform (DTW) after which vectors of features are calculated. Principal Component Analysis (PCA) is utilized to cluster the AU responses of the anodes. The approach allows locating cracks in the blocks and the AU features were found sensitive to crack severity. The results are validated using images collected after cutting some anodes. Copyright © 2018 Elsevier B.V. All rights reserved.

Raman spectral signatures as conformational probes of gas phase flexible molecules

NASA Astrophysics Data System (ADS)

Golan, Amir; Mayorkas, Nitzan; Rosenwaks, Salman; Bar, Ilana

2009-07-01

A novel application of ionization-loss stimulated Raman spectroscopy (ILSRS) for monitoring the spectral features of four conformers of a gas phase flexible molecule is reported. The Raman spectral signatures of four conformers of 2-phenylethylamine are well matched by the results of density functional theory calculations, showing bands uniquely identifying the structures. The measurement of spectral signatures by ILSRS in an extended spectral range, with a conventional laser source, is instrumental in facilitating the unraveling of intra- and intermolecular interactions that are significant in biological structure and activity.

[Cross comparison of ASTER and Landsat ETM+ multispectral measurements for NDVI and SAVI vegetation indices].

PubMed

Xu, Han-qiu; Zhang, Tie-jun

2011-07-01

The present paper investigates the quantitative relationship between the NDVI and SAVI vegetation indices of Landsat and ASTER sensors based on three tandem image pairs. The study examines how well ASTER sensor vegetation observations replicate ETM+ vegetation observations, and more importantly, the difference in the vegetation observations between the two sensors. The DN values of the three image pairs were first converted to at-sensor reflectance to reduce radiometric differences between two sensors, images. The NDVI and SAVI vegetation indices of the two sensors were then calculated using the converted reflectance. The quantitative relationship was revealed through regression analysis on the scatter plots of the vegetation index values of the two sensors. The models for the conversion between the two sensors, vegetation indices were also obtained from the regression. The results show that the difference does exist between the two sensors, vegetation indices though they have a very strong positive linear relationship. The study found that the red and near infrared measurements differ between the two sensors, with ASTER generally producing higher reflectance in the red band and lower reflectance in the near infrared band than the ETM+ sensor. This results in the ASTER sensor producing lower spectral vegetation index measurements, for the same target, than ETM+. The relative spectral response function differences in the red and near infrared bands between the two sensors are believed to be the main factor contributing to their differences in vegetation index measurements, because the red and near infrared relative spectral response features of the ASTER sensor overlap the vegetation "red edge" spectral region. The obtained conversion models have high accuracy with a RMSE less than 0.04 for both sensors' inter-conversion between corresponding vegetation indices.

The pre-launch characterization of SIMBIO-SYS/VIHI imaging spectrometer for the BepiColombo mission to Mercury. II. Spectral calibrations.

PubMed

Altieri, F; Filacchione, G; Capaccioni, F; Carli, C; Dami, M; Tommasi, L; Aroldi, G; Borrelli, D; Barbis, A; Baroni, M; Pastorini, G; Ficai Veltroni, I; Mugnuolo, R

2017-09-01

The Visible and near Infrared Hyperspectral Imager (VIHI) is the VIS-IR spectrometer with imaging capabilities aboard the ESA BepiColombo mission to Mercury. In this second paper, we report the instrument spectral characterization derived by the calibration campaign carried out before spacecraft integration. Complementary measurements concerning radiometric and linearity responses, as well as geometric performances, are described in Paper I [G. Filacchione et al., Rev. Sci. Instrum. 88, 094502 (2017)]. We have verified the VIHI spectral range, spectral dispersion, spectral response function, and spectral uniformity along the whole slit. Instrumental defects and optical aberrations due to smiling and keystone effects have been evaluated, and they are lower than the design requirement (<1/3 pixel). The instrumental response is uniform along the whole slit, while spectral dispersion is well represented by a second order curve, rather than to be constant along the spectral dimension.

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

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

Dion, Michael; Eiden, Greg; Farmer, Orville

2016-07-22

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

X-Ray Spectra from MHD Simulations of Accreting Black Holes

NASA Technical Reports Server (NTRS)

Schnittman, Jeremy D.; Noble, Scott C.; Krolik, Julian H.

2011-01-01

We present new global calculations of X-ray spectra from fully relativistic magneto-hydrodynamic (MHO) simulations of black hole (BH) accretion disks. With a self consistent radiative transfer code including Compton scattering and returning radiation, we can reproduce the predominant spectral features seen in decades of X-ray observations of stellar-mass BHs: a broad thermal peak around 1 keV, power-law continuum up to >100 keV, and a relativistically broadened iron fluorescent line. By varying the mass accretion rate, different spectral states naturally emerge: thermal-dominant, steep power-law, and low/hard. In addition to the spectral features, we briefly discuss applications to X-ray timing and polarization.

Near-infrared spectra of the Martian surface: Reading between the lines

NASA Technical Reports Server (NTRS)

Crisp, D.; Bell, J. F., III

1993-01-01

Moderate-resolution near-infrared (NIR) spectra of Mars have been widely used in studies of the Martian surface because many candidate surface materials have distinctive absorption features at these wavelengths. Recent advances in NIR detector technology and instrumentation have also encouraged studies in this spectral region. The use of moderate spectral resolution has often been justified for NIR surface observations because the spectral features produced by most surface materials are relatively broad, and easily discriminated at this resolution. In spite of this, NIR spectra of Mars are usually very difficult to interpret quantitatively. One problem is that NIR surface absorption features are often only a few percent deep, requiring observations with great signal-to-noise ratios. A more significant problem is that gases in the Martian atmosphere contribute numerous absorption features at these wavelengths. Ground-based observers must also contend with variable absorption by several gases in the Earth's atmosphere (H2O, CO2, O3, N2O, CH4, O2). The strong CO2 bands near 1.4, 1.6, 2.0, 2.7, 4.3, and 4.8 micrometers largely preclude the analysis of surface spectral features at these wavelengths. Martian atmospheric water vapor also contributes significant absorption near 1.33, 1.88, and 2.7 micrometers, but water vapor in the Earth's atmosphere poses a much larger problem to ground-based studies of these spectral regions. The third most important NIR absorber in the Martian atmosphere is CO. This gas absorbs most strongly in the relatively-transparent spectral windows near 4.6 and 2.3 micrometers. It also produces 1-10 percent absorption in the solar spectrum at these NIR wavelengths. This solar CO absorption cannot be adequately removed by dividing the Martian spectrum by that of a star, as is commonly done to calibrate ground-based spectroscopic observations, because most stars do not have identical amounts of CO absorption in their spectra. Here, we describe tow effective methods for eliminating contamination of Martian surface spectra by absorption in the solar, terrestrial, and Martian atmospheres. Both methods involve the use of very-high-resolution spectra that completely resolve the narrow atmospheric absorption lines.

Altered cerebral blood flow velocity features in fibromyalgia patients in resting-state conditions

PubMed Central

Rodríguez, Alejandro; Tembl, José; Mesa-Gresa, Patricia; Muñoz, Miguel Ángel; Montoya, Pedro

2017-01-01

The aim of this study is to characterize in resting-state conditions the cerebral blood flow velocity (CBFV) signals of fibromyalgia patients. The anterior and middle cerebral arteries of both hemispheres from 15 women with fibromyalgia and 15 healthy women were monitored using Transcranial Doppler (TCD) during a 5-minute eyes-closed resting period. Several signal processing methods based on time, information theory, frequency and time-frequency analyses were used in order to extract different features to characterize the CBFV signals in the different vessels. Main results indicated that, in comparison with control subjects, fibromyalgia patients showed a higher complexity of the envelope CBFV and a different distribution of the power spectral density. In addition, it has been observed that complexity and spectral features show correlations with clinical pain parameters and emotional factors. The characterization features were used in a lineal model to discriminate between fibromyalgia patients and healthy controls, providing a high accuracy. These findings indicate that CBFV signals, specifically their complexity and spectral characteristics, contain information that may be relevant for the assessment of fibromyalgia patients in resting-state conditions. PMID:28700720

Musical ability and non-native speech-sound processing are linked through sensitivity to pitch and spectral information.

PubMed

Kempe, Vera; Bublitz, Dennis; Brooks, Patricia J

2015-05-01

Is the observed link between musical ability and non-native speech-sound processing due to enhanced sensitivity to acoustic features underlying both musical and linguistic processing? To address this question, native English speakers (N = 118) discriminated Norwegian tonal contrasts and Norwegian vowels. Short tones differing in temporal, pitch, and spectral characteristics were used to measure sensitivity to the various acoustic features implicated in musical and speech processing. Musical ability was measured using Gordon's Advanced Measures of Musical Audiation. Results showed that sensitivity to specific acoustic features played a role in non-native speech-sound processing: Controlling for non-verbal intelligence, prior foreign language-learning experience, and sex, sensitivity to pitch and spectral information partially mediated the link between musical ability and discrimination of non-native vowels and lexical tones. The findings suggest that while sensitivity to certain acoustic features partially mediates the relationship between musical ability and non-native speech-sound processing, complex tests of musical ability also tap into other shared mechanisms. © 2014 The British Psychological Society.

Characterizing multivariate decoding models based on correlated EEG spectral features.

PubMed

McFarland, Dennis J

2013-07-01

Multivariate decoding methods are popular techniques for analysis of neurophysiological data. The present study explored potential interpretative problems with these techniques when predictors are correlated. Data from sensorimotor rhythm-based cursor control experiments was analyzed offline with linear univariate and multivariate models. Features were derived from autoregressive (AR) spectral analysis of varying model order which produced predictors that varied in their degree of correlation (i.e., multicollinearity). The use of multivariate regression models resulted in much better prediction of target position as compared to univariate regression models. However, with lower order AR features interpretation of the spectral patterns of the weights was difficult. This is likely to be due to the high degree of multicollinearity present with lower order AR features. Care should be exercised when interpreting the pattern of weights of multivariate models with correlated predictors. Comparison with univariate statistics is advisable. While multivariate decoding algorithms are very useful for prediction their utility for interpretation may be limited when predictors are correlated. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Fourier transform infrared spectroscopy microscopic imaging classification based on spatial-spectral features

NASA Astrophysics Data System (ADS)

Liu, Lian; Yang, Xiukun; Zhong, Mingliang; Liu, Yao; Jing, Xiaojun; Yang, Qin

2018-04-01

The discrete fractional Brownian incremental random (DFBIR) field is used to describe the irregular, random, and highly complex shapes of natural objects such as coastlines and biological tissues, for which traditional Euclidean geometry cannot be used. In this paper, an anisotropic variable window (AVW) directional operator based on the DFBIR field model is proposed for extracting spatial characteristics of Fourier transform infrared spectroscopy (FTIR) microscopic imaging. Probabilistic principal component analysis first extracts spectral features, and then the spatial features of the proposed AVW directional operator are combined with the former to construct a spatial-spectral structure, which increases feature-related information and helps a support vector machine classifier to obtain more efficient distribution-related information. Compared to Haralick’s grey-level co-occurrence matrix, Gabor filters, and local binary patterns (e.g. uniform LBPs, rotation-invariant LBPs, uniform rotation-invariant LBPs), experiments on three FTIR spectroscopy microscopic imaging datasets show that the proposed AVW directional operator is more advantageous in terms of classification accuracy, particularly for low-dimensional spaces of spatial characteristics.

Altered cerebral blood flow velocity features in fibromyalgia patients in resting-state conditions.

PubMed

Rodríguez, Alejandro; Tembl, José; Mesa-Gresa, Patricia; Muñoz, Miguel Ángel; Montoya, Pedro; Rey, Beatriz

2017-01-01

The aim of this study is to characterize in resting-state conditions the cerebral blood flow velocity (CBFV) signals of fibromyalgia patients. The anterior and middle cerebral arteries of both hemispheres from 15 women with fibromyalgia and 15 healthy women were monitored using Transcranial Doppler (TCD) during a 5-minute eyes-closed resting period. Several signal processing methods based on time, information theory, frequency and time-frequency analyses were used in order to extract different features to characterize the CBFV signals in the different vessels. Main results indicated that, in comparison with control subjects, fibromyalgia patients showed a higher complexity of the envelope CBFV and a different distribution of the power spectral density. In addition, it has been observed that complexity and spectral features show correlations with clinical pain parameters and emotional factors. The characterization features were used in a lineal model to discriminate between fibromyalgia patients and healthy controls, providing a high accuracy. These findings indicate that CBFV signals, specifically their complexity and spectral characteristics, contain information that may be relevant for the assessment of fibromyalgia patients in resting-state conditions.

Fluorescent marker-based and marker-free discrimination between healthy and cancerous human tissues using hyper-spectral imaging

NASA Astrophysics Data System (ADS)

Arnold, Thomas; De Biasio, Martin; Leitner, Raimund

2015-06-01

Two problems are addressed in this paper (i) the fluorescent marker-based and the (ii) marker-free discrimination between healthy and cancerous human tissues. For both applications the performance of hyper-spectral methods are quantified. Fluorescent marker-based tissue classification uses a number of fluorescent markers to dye specific parts of a human cell. The challenge is that the emission spectra of the fluorescent dyes overlap considerably. They are, furthermore disturbed by the inherent auto-fluorescence of human tissue. This results in ambiguities and decreased image contrast causing difficulties for the treatment decision. The higher spectral resolution introduced by tunable-filter-based spectral imaging in combination with spectral unmixing techniques results in an improvement of the image contrast and therefore more reliable information for the physician to choose the treatment decision. Marker-free tissue classification is based solely on the subtle spectral features of human tissue without the use of artificial markers. The challenge in this case is that the spectral differences between healthy and cancerous tissues are subtle and embedded in intra- and inter-patient variations of these features. The contributions of this paper are (i) the evaluation of hyper-spectral imaging in combination with spectral unmixing techniques for fluorescence marker-based tissue classification, (ii) the evaluation of spectral imaging for marker-free intra surgery tissue classification. Within this paper, we consider real hyper-spectral fluorescence and endoscopy data sets to emphasize the practical capability of the proposed methods. It is shown that the combination of spectral imaging with multivariate statistical methods can improve the sensitivity and specificity of the detection and the staging of cancerous tissues compared to standard procedures.

Standardization of Broadband UV Measurements for 365 nm LED Sources

PubMed Central

Eppeldauer, George P.

2012-01-01

Broadband UV measurements are evaluated when UV-A irradiance meters measure optical radiation from 365 nm UV sources. The CIE standardized rectangular-shape UV-A function can be realized only with large spectral mismatch errors. The spectral power-distribution of the 365 nm excitation source is not standardized. Accordingly, the readings made with different types of UV meters, even if they measure the same UV source, can be very different. Available UV detectors and UV meters were measured and evaluated for spectral responsivity. The spectral product of the source-distribution and the meter’s spectral-responsivity were calculated for different combinations to estimate broad-band signal-measurement errors. Standardization of both the UV source-distribution and the meter spectral-responsivity is recommended here to perform uniform broad-band measurements with low uncertainty. It is shown what spectral responsivity function(s) is needed for new and existing UV irradiance meters to perform low-uncertainty broadband 365 nm measurements. PMID:26900516

A fully-coupled discontinuous Galerkin spectral element method for two-phase flow in petroleum reservoirs

NASA Astrophysics Data System (ADS)

Taneja, Ankur; Higdon, Jonathan

2018-01-01

A high-order spectral element discontinuous Galerkin method is presented for simulating immiscible two-phase flow in petroleum reservoirs. The governing equations involve a coupled system of strongly nonlinear partial differential equations for the pressure and fluid saturation in the reservoir. A fully implicit method is used with a high-order accurate time integration using an implicit Rosenbrock method. Numerical tests give the first demonstration of high order hp spatial convergence results for multiphase flow in petroleum reservoirs with industry standard relative permeability models. High order convergence is shown formally for spectral elements with up to 8th order polynomials for both homogeneous and heterogeneous permeability fields. Numerical results are presented for multiphase fluid flow in heterogeneous reservoirs with complex geometric or geologic features using up to 11th order polynomials. Robust, stable simulations are presented for heterogeneous geologic features, including globally heterogeneous permeability fields, anisotropic permeability tensors, broad regions of low-permeability, high-permeability channels, thin shale barriers and thin high-permeability fractures. A major result of this paper is the demonstration that the resolution of the high order spectral element method may be exploited to achieve accurate results utilizing a simple cartesian mesh for non-conforming geological features. Eliminating the need to mesh to the boundaries of geological features greatly simplifies the workflow for petroleum engineers testing multiple scenarios in the face of uncertainty in the subsurface geology.

Spectral gamuts and spectral gamut mapping

NASA Astrophysics Data System (ADS)

Rosen, Mitchell R.; Derhak, Maxim W.

2006-01-01

All imaging devices have two gamuts: the stimulus gamut and the response gamut. The response gamut of a print engine is typically described in CIE colorimetry units, a system derived to quantify human color response. More fundamental than colorimetric gamuts are spectral gamuts, based on radiance, reflectance or transmittance units. Spectral gamuts depend on the physics of light or on how materials interact with light and do not involve the human's photoreceptor integration or brain processing. Methods for visualizing a spectral gamut raise challenges as do considerations of how to utilize such a data-set for producing superior color reproductions. Recent work has described a transformation of spectra reduced to 6-dimensions called LabPQR. LabPQR was designed as a hybrid space with three explicit colorimetric axes and three additional spectral reconstruction axes. In this paper spectral gamuts are discussed making use of LabPQR. Also, spectral gamut mapping is considered in light of the colorimetric-spectral duality of the LabPQR space.

Optical spectral singularities as threshold resonances

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

Mostafazadeh, Ali

2011-04-15

Spectral singularities are among generic mathematical features of complex scattering potentials. Physically they correspond to scattering states that behave like zero-width resonances. For a simple optical system, we show that a spectral singularity appears whenever the gain coefficient coincides with its threshold value and other parameters of the system are selected properly. We explore a concrete realization of spectral singularities for a typical semiconductor gain medium and propose a method of constructing a tunable laser that operates at threshold gain.

High-resolution CASSINI-VIMS mosaics of Titan and the icy Saturnian satellites

USGS Publications Warehouse

Jaumann, R.; Stephan, K.; Brown, R.H.; Buratti, B.J.; Clark, R.N.; McCord, T.B.; Coradini, A.; Capaccioni, F.; Filacchione, G.; Cerroni, P.; Baines, K.H.; Bellucci, G.; Bibring, J.-P.; Combes, M.; Cruikshank, D.P.; Drossart, P.; Formisano, V.; Langevin, Y.; Matson, D.L.; Nelson, R.M.; Nicholson, P.D.; Sicardy, B.; Sotin, Christophe; Soderbloom, L.A.; Griffith, C.; Matz, K.-D.; Roatsch, Th.; Scholten, F.; Porco, C.C.

2006-01-01

The Visual Infrared Mapping Spectrometer (VIMS) onboard the CASSINI spacecraft obtained new spectral data of the icy satellites of Saturn after its arrival at Saturn in June 2004. VIMS operates in a spectral range from 0.35 to 5.2 ??m, generating image cubes in which each pixel represents a spectrum consisting of 352 contiguous wavebands. As an imaging spectrometer VIMS combines the characteristics of both a spectrometer and an imaging instrument. This makes it possible to analyze the spectrum of each pixel separately and to map the spectral characteristics spatially, which is important to study the relationships between spectral information and geological and geomorphologic surface features. The spatial analysis of the spectral data requires the determination of the exact geographic position of each pixel on the specific surface and that all 352 spectral elements of each pixel show the same region of the target. We developed a method to reproject each pixel geometrically and to convert the spectral data into map projected image cubes. This method can also be applied to mosaic different VIMS observations. Based on these mosaics, maps of the spectral properties for each Saturnian satellite can be derived and attributed to geographic positions as well as to geological and geomorphologic surface features. These map-projected mosaics are the basis for all further investigations. ?? 2006 Elsevier Ltd. All rights reserved.

An optimized index of human cardiovascular adaptation to simulated weightlessness

NASA Technical Reports Server (NTRS)

Wang, M.; Hassebrook, L.; Evans, J.; Varghese, T.; Knapp, C.

1996-01-01

Prolonged exposure to weightlessness is known to produce a variety of cardiovascular changes, some of which may influence the astronaut's performance during a mission. In order to find a reliable indicator of cardiovascular adaptation to weightlessness, we analyzed data from nine male subjects after a 24-hour period of normal activity and after a period of simulated weightlessness produced by two hours in a launch position followed by 20 hours of 6 degrees head-down tilt plus pharmacologically induced diuresis (furosemide). Heart rate, arterial pressure, thoracic fluid index, and radial flow were analyzed. Autoregressive spectral estimation and decomposition were used to obtain the spectral components of each variable from the subjects in the supine position during pre- and post-simulated weightlessness. We found a significant decrease in heart rate power and an increase in thoracic fluid index power in the high frequency region (0.2-0.45 Hz) and significant increases in radial flow and arterial pressure powers in the low frequency region (<0.2 Hz) in response to simulated weightlessness. However, due to the variability among subjects, any single variable appeared limited as a dependable index of cardiovascular adaptation to weightlessness. The backward elimination algorithm was then used to select the best discriminatory features from these spectral components. Fisher's linear discriminant and Bayes' quadratic discriminant were used to combine the selected features to obtain an optimal index of adaptation to simulated weightlessness. Results showed that both techniques provided improved discriminant performance over any single variable and thus have the potential for use as an index to track adaptation and prescribe countermeasures to the effects of weightlessness.

Retrieval of spheroid particle size distribution from spectral extinction data in the independent mode using PCA approach

NASA Astrophysics Data System (ADS)

Tang, Hong; Lin, Jian-Zhong

2013-01-01

An improved anomalous diffraction approximation (ADA) method is presented for calculating the extinction efficiency of spheroids firstly. In this approach, the extinction efficiency of spheroid particles can be calculated with good accuracy and high efficiency in a wider size range by combining the Latimer method and the ADA theory, and this method can present a more general expression for calculating the extinction efficiency of spheroid particles with various complex refractive indices and aspect ratios. Meanwhile, the visible spectral extinction with varied spheroid particle size distributions and complex refractive indices is surveyed. Furthermore, a selection principle about the spectral extinction data is developed based on PCA (principle component analysis) of first derivative spectral extinction. By calculating the contribution rate of first derivative spectral extinction, the spectral extinction with more significant features can be selected as the input data, and those with less features is removed from the inversion data. In addition, we propose an improved Tikhonov iteration method to retrieve the spheroid particle size distributions in the independent mode. Simulation experiments indicate that the spheroid particle size distributions obtained with the proposed method coincide fairly well with the given distributions, and this inversion method provides a simple, reliable and efficient method to retrieve the spheroid particle size distributions from the spectral extinction data.

IMAGING SPECTROSCOPY FOR DETERMINING RANGELAND STRESSORS TO WESTERN WATERSHEDS

EPA Science Inventory

The Environmental Protection Agency is developing rangeland ecological indicators in twelve western states using advanced remote sensing techniques. Fine spectral resolution (hyperspectral) sensors, or imaging spectrometers, can detect the subtle spectral features that make veget...

IMAGING SPECTROSCOPY FOR DETERMINING RANGELAND STRESSORS TO WESTERN WATERSHEDS

EPA Science Inventory

The Environmental Protection Agency is developing rangeland ecological indicators in eleven western states using advanced remote sensing systems. Fine spectral resolution (hyperspemal) sensors, or imaging spectrometers, can detect the subtle spectral features that makes vegetatio...

Spectral characteristics and feature selection of satellite remote sensing data for climate and anthropogenic changes assessment in Bucharest area

NASA Astrophysics Data System (ADS)

Zoran, Maria; Savastru, Roxana; Savastru, Dan; Tautan, Marina; Miclos, Sorin; Cristescu, Luminita; Carstea, Elfrida; Baschir, Laurentiu

2010-05-01

Urban systems play a vital role in social and economic development in all countries. Their environmental changes can be investigated on different spatial and temporal scales. Urban and peri-urban environment dynamics is of great interest for future planning and decision making as well as in frame of local and regional changes. Changes in urban land cover include changes in biotic diversity, actual and potential primary productivity, soil quality, runoff, and sedimentation rates, and cannot be well understood without the knowledge of land use change that drives them. The study focuses on the assessment of environmental features changes for Bucharest metropolitan area, Romania by satellite remote sensing and in-situ monitoring data. Rational feature selection from the varieties of spectral channels in the optical wavelengths of electromagnetic spectrum (VIS and NIR) is very important for effective analysis and information extraction of remote sensing data. Based on comprehensively analyses of the spectral characteristics of remote sensing data is possibly to derive environmental changes in urban areas. The information quantity contained in a band is an important parameter in evaluating the band. The deviation and entropy are often used to show information amount. Feature selection is one of the most important steps in recognition and classification of remote sensing images. Therefore, it is necessary to select features before classification. The optimal features are those that can be used to distinguish objects easily and correctly. Three factors—the information quantity of bands, the correlation between bands and the spectral characteristic (e.g. absorption specialty) of classified objects in test area Bucharest have been considered in our study. As, the spectral characteristic of an object is influenced by many factors, being difficult to define optimal feature parameters to distinguish all the objects in a whole area, a method of multi-level feature selection was suggested. On the basis of analyzing the information quantity of bands, correlation between different bands, spectral absorption characteristics of objects and object separability in bands, a fundamental method of optimum band selection and feature extraction from remote sensing data was discussed. Spectral signatures of different terrain features have been used to extract structural patterns aiming to separate surface units and to classify the general categories. The synergetic analysis and interpretation of the different satellite images (LANDSAT: TM, ETM; MODIS, IKONOS) acquired over a period of more than 20 years reveals significant aspects regarding impacts of climate and anthropogenic changes on urban/periurban environment. It was delimited residential zones of industrial zones which are very often a source of pollution. An important role has urban green cover assessment. Have been emphasized the particularities of the functional zones from different points of view: architectural, streets and urban surface traffic, some components of urban infrastructure as well as habitat quality. The growth of Bucharest urban area in Romania has been a result of a rapid process of industrialization, and also of the increase of urban population. Information on the spatial pattern and temporal dynamics of land cover and land use of urban areas is critical to address a wide range of practical problems relating to urban regeneration, urban sustainability and rational planning policy.

Multi-Centrality Graph Spectral Decompositions and Their Application to Cyber Intrusion Detection

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

Chen, Pin-Yu; Choudhury, Sutanay; Hero, Alfred

Many modern datasets can be represented as graphs and hence spectral decompositions such as graph principal component analysis (PCA) can be useful. Distinct from previous graph decomposition approaches based on subspace projection of a single topological feature, e.g., the centered graph adjacency matrix (graph Laplacian), we propose spectral decomposition approaches to graph PCA and graph dictionary learning that integrate multiple features, including graph walk statistics, centrality measures and graph distances to reference nodes. In this paper we propose a new PCA method for single graph analysis, called multi-centrality graph PCA (MC-GPCA), and a new dictionary learning method for ensembles ofmore » graphs, called multi-centrality graph dictionary learning (MC-GDL), both based on spectral decomposition of multi-centrality matrices. As an application to cyber intrusion detection, MC-GPCA can be an effective indicator of anomalous connectivity pattern and MC-GDL can provide discriminative basis for attack classification.« less

Analysis of cosmetic residues on a single human hair by ATR FT-IR microspectroscopy

NASA Astrophysics Data System (ADS)

Pienpinijtham, Prompong; Thammacharoen, Chuchaat; Naranitad, Suwimol; Ekgasit, Sanong

2018-05-01

In this work, ATR FT-IR spectra of single human hair and cosmetic residues on hair surface are successfully collected using a homemade dome-shaped Ge μIRE accessary installed on an infrared microscope. By collecting ATR spectra of hairs from the same person, the spectral patterns are identical and superimposed while different spectral features are observed from ATR spectra of hairs collected from different persons. The spectral differences depend on individual hair characteristics, chemical treatments, and cosmetics on hair surface. The "Contact-and-Collect" technique that transfers remarkable materials on the hair surface to the tip of the Ge μIRE enables an identification of cosmetics on a single hair. Moreover, the differences between un-split and split hairs are also studied in this report. These highly specific spectral features can be employed for unique identification or for differentiation of hairs based on the molecular structures of hairs and cosmetics on hairs.

Formation of spectral lines in planetary atmospheres. I - Theory for cloudy atmospheres: Application to Venus.

NASA Technical Reports Server (NTRS)

Hunt, G. E.

1972-01-01

The theory of the formation of spectral lines in a cloudy planetary atmosphere is studied in detail. It is shown that models based upon homogeneous, isotropically scattering atmospheres cannot be used to reproduce observed spectroscopic features of phase effect and the shape of spectral lines for weak and strong bands. The theory must, therefore, be developed using an inhomogeneous (gravitational) model of a planetary atmosphere, accurately incorporating all the physical processes of radiative transfer. Such a model of the lower Venus atmosphere, consistent with our present knowledge, is constructed. The results discussed in this article demonstrate the effects of the parameters that describe the atmospheric model on the spectroscopic features of spectral line profile and phase effect, at visible and near infrared wavelengths. This information enables us to develop a comprehensive theory of line formation in a Venus atmosphere.

a Novel Deep Convolutional Neural Network for Spectral-Spatial Classification of Hyperspectral Data

NASA Astrophysics Data System (ADS)

Li, N.; Wang, C.; Zhao, H.; Gong, X.; Wang, D.

2018-04-01

Spatial and spectral information are obtained simultaneously by hyperspectral remote sensing. Joint extraction of these information of hyperspectral image is one of most import methods for hyperspectral image classification. In this paper, a novel deep convolutional neural network (CNN) is proposed, which extracts spectral-spatial information of hyperspectral images correctly. The proposed model not only learns sufficient knowledge from the limited number of samples, but also has powerful generalization ability. The proposed framework based on three-dimensional convolution can extract spectral-spatial features of labeled samples effectively. Though CNN has shown its robustness to distortion, it cannot extract features of different scales through the traditional pooling layer that only have one size of pooling window. Hence, spatial pyramid pooling (SPP) is introduced into three-dimensional local convolutional filters for hyperspectral classification. Experimental results with a widely used hyperspectral remote sensing dataset show that the proposed model provides competitive performance.

The basal ganglia is necessary for learning spectral, but not temporal features of birdsong

PubMed Central

Ali, Farhan; Fantana, Antoniu L.; Burak, Yoram; Ölveczky, Bence P.

2013-01-01

Executing a motor skill requires the brain to control which muscles to activate at what times. How these aspects of control - motor implementation and timing - are acquired, and whether the learning processes underlying them differ, is not well understood. To address this we used a reinforcement learning paradigm to independently manipulate both spectral and temporal features of birdsong, a complex learned motor sequence, while recording and perturbing activity in underlying circuits. Our results uncovered a striking dissociation in how neural circuits underlie learning in the two domains. The basal ganglia was required for modifying spectral, but not temporal structure. This functional dissociation extended to the descending motor pathway, where recordings from a premotor cortex analogue nucleus reflected changes to temporal, but not spectral structure. Our results reveal a strategy in which the nervous system employs different and largely independent circuits to learn distinct aspects of a motor skill. PMID:24075977

On- and off-axis spectral emission features from laser-produced gas breakdown plasmas

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

Harilal, S. S.; Skrodzki, P. J.; Miloshevsky, A.

Laser-heated gas breakdown plasmas or sparks emit profoundly in the ultraviolet and visible region of the electromagnetic spectrum with contributions from ionic, atomic, and molecular species. Laser created kernels expand into a cold ambient with high velocities during its early lifetime followed by confinement of the plasma kernel and eventually collapse. However, the plasma kernels produced during laser breakdown of gases are also capable of exciting and ionizing the surrounding ambient medium. Two mechanisms can be responsible for excitation and ionization of surrounding ambient: viz. photoexcitation and ionization by intense ultraviolet emission from the sparks produced during the early timesmore » of its creation and/or heating by strong shocks generated by the kernel during its expansion into the ambient. In this study, an investigation is made on the spectral features of on- and off-axis emission features of laser-induced plasma breakdown kernels generated in atmospheric pressure conditions with an aim to elucidate the mechanisms leading to ambient excitation and emission. Pulses from an Nd:YAG laser emitting at 1064 nm with 6 ns pulse duration are used to generate plasma kernels. Laser sparks were generated in air, argon, and helium gases to provide different physical properties of expansion dynamics and plasma chemistry considering the differences in laser absorption properties, mass density and speciation. Point shadowgraphy and time-resolved imaging were used to evaluate the shock wave and spark self-emission morphology at early and late times while space and time resolved spectroscopy is used for evaluating the emission features as well as for inferring plasma fundaments at on- and off-axis. Structure and dynamics of the plasma kernel obtained using imaging techniques are also compared to numerical simulations using computational fluid dynamics code. The emission from the kernel showed that spectral features from ions, atoms and molecules are separated in time with an early time temperatures and densities in excess of 35000 K and 4×10 18 /cm 3 with an existence of thermal equilibrium. However, the emission from the off-kernel positions from the breakdown plasmas showed enhanced ultraviolet radiation with the presence of N 2 bands and represented by non-LTE conditions. Finally, our results also highlight that the ultraviolet radiation emitted during early time of spark evolution is the predominant source of the photo-excitation of the surrounding medium.« less

On- and off-axis spectral emission features from laser-produced gas breakdown plasmas

DOE PAGES

Harilal, S. S.; Skrodzki, P. J.; Miloshevsky, A.; ...

2017-06-01

Laser-heated gas breakdown plasmas or sparks emit profoundly in the ultraviolet and visible region of the electromagnetic spectrum with contributions from ionic, atomic, and molecular species. Laser created kernels expand into a cold ambient with high velocities during its early lifetime followed by confinement of the plasma kernel and eventually collapse. However, the plasma kernels produced during laser breakdown of gases are also capable of exciting and ionizing the surrounding ambient medium. Two mechanisms can be responsible for excitation and ionization of surrounding ambient: viz. photoexcitation and ionization by intense ultraviolet emission from the sparks produced during the early timesmore » of its creation and/or heating by strong shocks generated by the kernel during its expansion into the ambient. In this study, an investigation is made on the spectral features of on- and off-axis emission features of laser-induced plasma breakdown kernels generated in atmospheric pressure conditions with an aim to elucidate the mechanisms leading to ambient excitation and emission. Pulses from an Nd:YAG laser emitting at 1064 nm with 6 ns pulse duration are used to generate plasma kernels. Laser sparks were generated in air, argon, and helium gases to provide different physical properties of expansion dynamics and plasma chemistry considering the differences in laser absorption properties, mass density and speciation. Point shadowgraphy and time-resolved imaging were used to evaluate the shock wave and spark self-emission morphology at early and late times while space and time resolved spectroscopy is used for evaluating the emission features as well as for inferring plasma fundaments at on- and off-axis. Structure and dynamics of the plasma kernel obtained using imaging techniques are also compared to numerical simulations using computational fluid dynamics code. The emission from the kernel showed that spectral features from ions, atoms and molecules are separated in time with an early time temperatures and densities in excess of 35000 K and 4×1018 /cm3 with an existence of thermal equilibrium. However, the emission from the off-kernel positions from the breakdown plasmas showed enhanced ultraviolet radiation with the presence of N2 bands and represented by non-LTE conditions. Our results also highlight that the ultraviolet radiation emitted during early time of spark evolution is the predominant source of the photo-excitation of the surrounding medium.« less

Automated processing of label-free Raman microscope images of macrophage cells with standardized regression for high-throughput analysis.

PubMed

Milewski, Robert J; Kumagai, Yutaro; Fujita, Katsumasa; Standley, Daron M; Smith, Nicholas I

2010-11-19

Macrophages represent the front lines of our immune system; they recognize and engulf pathogens or foreign particles thus initiating the immune response. Imaging macrophages presents unique challenges, as most optical techniques require labeling or staining of the cellular compartments in order to resolve organelles, and such stains or labels have the potential to perturb the cell, particularly in cases where incomplete information exists regarding the precise cellular reaction under observation. Label-free imaging techniques such as Raman microscopy are thus valuable tools for studying the transformations that occur in immune cells upon activation, both on the molecular and organelle levels. Due to extremely low signal levels, however, Raman microscopy requires sophisticated image processing techniques for noise reduction and signal extraction. To date, efficient, automated algorithms for resolving sub-cellular features in noisy, multi-dimensional image sets have not been explored extensively. We show that hybrid z-score normalization and standard regression (Z-LSR) can highlight the spectral differences within the cell and provide image contrast dependent on spectral content. In contrast to typical Raman imaging processing methods using multivariate analysis, such as single value decomposition (SVD), our implementation of the Z-LSR method can operate nearly in real-time. In spite of its computational simplicity, Z-LSR can automatically remove background and bias in the signal, improve the resolution of spatially distributed spectral differences and enable sub-cellular features to be resolved in Raman microscopy images of mouse macrophage cells. Significantly, the Z-LSR processed images automatically exhibited subcellular architectures whereas SVD, in general, requires human assistance in selecting the components of interest. The computational efficiency of Z-LSR enables automated resolution of sub-cellular features in large Raman microscopy data sets without compromise in image quality or information loss in associated spectra. These results motivate further use of label free microscopy techniques in real-time imaging of live immune cells.

Discrimination of poorly exposed lithologies in AVIRIS data

NASA Technical Reports Server (NTRS)

Farrand, William H.; Harsanyi, Joseph C.

1993-01-01

One of the advantages afforded by imaging spectrometers such as AVIRIS is the capability to detect target materials at a sub-pixel scale. This paper presents several examples of the identification of poorly exposed geologic materials - materials which are either subpixel in scale or which, while having some surface expression over several pixels, are partially covered by vegetation or other materials. Sabol et al. (1992) noted that a primary factor in the ability to distinguish sub-pixel targets is the spectral contrast between the target and its surroundings. In most cases, this contrast is best expressed as an absorption feature or features present in the target but absent in the surroundings. Under such circumstances, techniques such as band depth mapping (Clark et al., 1992) are feasible. However, the only difference between a target material and its surroundings is often expressed solely in the continuum. We define the 'continuum' as the reflectance or radiance spanning spectral space between spectral features. Differences in continuum slope and shape can only be determined by reduction techniques which considers the entire spectral range; i.e., techniques such as spectral mixture analysis (Adams et al., 1989) and recently developed techniques which utilize an orthogonal subspace projection operator (Harsanyi, 1993). Two of the three examples considered herein deal with cases where the target material differs from its surroundings only by such a subtle continuum change.

Automated method for the systematic interpretation of resonance peaks in spectrum data

DOEpatents

Damiano, B.; Wood, R.T.

1997-04-22

A method is described for spectral signature interpretation. The method includes the creation of a mathematical model of a system or process. A neural network training set is then developed based upon the mathematical model. The neural network training set is developed by using the mathematical model to generate measurable phenomena of the system or process based upon model input parameter that correspond to the physical condition of the system or process. The neural network training set is then used to adjust internal parameters of a neural network. The physical condition of an actual system or process represented by the mathematical model is then monitored by extracting spectral features from measured spectra of the actual process or system. The spectral features are then input into said neural network to determine the physical condition of the system or process represented by the mathematical model. More specifically, the neural network correlates the spectral features (i.e. measurable phenomena) of the actual process or system with the corresponding model input parameters. The model input parameters relate to specific components of the system or process, and, consequently, correspond to the physical condition of the process or system. 1 fig.

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

NASA Astrophysics Data System (ADS)

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

2015-01-01

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

Automated method for the systematic interpretation of resonance peaks in spectrum data

DOEpatents

Damiano, Brian; Wood, Richard T.

1997-01-01

A method for spectral signature interpretation. The method includes the creation of a mathematical model of a system or process. A neural network training set is then developed based upon the mathematical model. The neural network training set is developed by using the mathematical model to generate measurable phenomena of the system or process based upon model input parameter that correspond to the physical condition of the system or process. The neural network training set is then used to adjust internal parameters of a neural network. The physical condition of an actual system or process represented by the mathematical model is then monitored by extracting spectral features from measured spectra of the actual process or system. The spectral features are then input into said neural network to determine the physical condition of the system or process represented by the mathematical. More specifically, the neural network correlates the spectral features (i.e. measurable phenomena) of the actual process or system with the corresponding model input parameters. The model input parameters relate to specific components of the system or process, and, consequently, correspond to the physical condition of the process or system.

Real-time evaluation of polyphenol oxidase (PPO) activity in lychee pericarp based on weighted combination of spectral data and image features as determined by fuzzy neural network.

PubMed

Yang, Yi-Chao; Sun, Da-Wen; Wang, Nan-Nan; Xie, Anguo

2015-07-01

A novel method of using hyperspectral imaging technique with the weighted combination of spectral data and image features by fuzzy neural network (FNN) was proposed for real-time prediction of polyphenol oxidase (PPO) activity in lychee pericarp. Lychee images were obtained by a hyperspectral reflectance imaging system operating in the range of 400-1000nm. A support vector machine-recursive feature elimination (SVM-RFE) algorithm was applied to eliminating variables with no or little information for the prediction from all bands, resulting in a reduced set of optimal wavelengths. Spectral information at the optimal wavelengths and image color features were then used respectively to develop calibration models for the prediction of PPO in pericarp during storage, and the results of two models were compared. In order to improve the prediction accuracy, a decision strategy was developed based on weighted combination of spectral data and image features, in which the weights were determined by FNN for a better estimation of PPO activity. The results showed that the combined decision model was the best among all of the calibration models, with high R(2) values of 0.9117 and 0.9072 and low RMSEs of 0.45% and 0.459% for calibration and prediction, respectively. These results demonstrate that the proposed weighted combined decision method has great potential for improving model performance. The proposed technique could be used for a better prediction of other internal and external quality attributes of fruits. Copyright © 2015 Elsevier B.V. All rights reserved.

Absorption Efficiencies of Forsterite. I: DDA Explorations in Grain Shape and Size

NASA Technical Reports Server (NTRS)

Lindsay, Sean S.; Wooden, Diane; Harker, David E.; Kelley, Michael S.; Woodward, Charles E.; Murphy, Jim R.

2013-01-01

We compute the absorption efficiency (Q(sub abs)) of forsterite using the discrete dipole approximation (DDA) in order to identify and describe what characteristics of crystal grain shape and size are important to the shape, peak location, and relative strength of spectral features in the 8 - 40 micron wavelength range. Using the DDSCAT code, we compute Q(sub abs) for non-spherical polyhedral grain shapes with a(sub eff) = 0.1 micron. The shape characteristics identified are: 1) elongation/reduction along one of three crystallographic axes; 2) asymmetry, such that all three crystallographic axes are of different lengths; and 3) the presence of crystalline faces that are not parallel to a specific crystallographic axis, e.g., non-rectangular prisms and (di)pyramids. Elongation/reduction dominates the locations and shapes of spectral features near 10, 11, 16, 23.5, 27, and 33.5 micron, while asymmetry and tips are secondary shape effects. Increasing grain sizes (0.1 - 1.0 micron) shifts the 10, 11 micron features systematically towards longer wavelengths and relative to the 11 micron feature increases the strengths and slightly broadens the longer wavelength features. Seven spectral shape classes are established for crystallographic a-, b-, and c-axes and include columnar and platelet shapes plus non-elongated or equant grain shapes. The spectral shape classes and the effects of grain size have practical application in identifying or excluding columnar, platelet or equant forsterite grain shapes in astrophysical environs. Identification of the shape characteristics of forsterite from 8 - 40 micron spectra provides a potential means to probe the temperatures at which forsterite formed.

An electron spin resonance study of gamma-irradiated grapes

NASA Astrophysics Data System (ADS)

Tabner, Brian J.; Tabner, Vivienne A.

The ESR spectra of the seeds, skins and stalks of unirradiated and γ-irradiated Cape black grapes have been obtained. In the spectra of all parts of the grape a single line (g ca. 2.004) is observed both before and after irradiation. New spectral features are observed after irradiation with doses of between 2 and 10 kGy. Some of these features decline in intensity over a period of several days. However, in the case of stalks, new spectral features are readily observed over the shelf-life of the fruit and in samples irradiated to a dose of only 2kGy.

The Copernicus ultraviolet spectral atlas of Sirius

NASA Technical Reports Server (NTRS)

Rogerson, John B., Jr.

1987-01-01

A near-ultraviolet spectral atlas for the A1 V star Alpha CMa (Sirius) has been prepared from data taken by the Princeton spectrometer aboard the Copernicus satellite. The spectral region from 1649 to 3170 A has been scanned with a resolution of 0.1 A. The atlas is presented in graphs, and line identifications for the absorption features have been tabulated.

Spectral response of fiber-coupled Fabry-Perot etalons.

PubMed

Ionov, Pavel

2014-03-01

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

Feature selection methods for object-based classification of sub-decimeter resolution digital aerial imagery

USDA-ARS?s Scientific Manuscript database

Due to the availability of numerous spectral, spatial, and contextual features, the determination of optimal features and class separabilities can be a time consuming process in object-based image analysis (OBIA). While several feature selection methods have been developed to assist OBIA, a robust c...

Development of a new approach based on midwave infrared spectroscopy for post-consumer black plastic waste sorting in the recycling industry.

PubMed

Rozenstein, Offer; Puckrin, Eldon; Adamowski, Jan

2017-10-01

Waste sorting is key to the process of waste recycling. Exact identification of plastic resin and wood products using Near Infrared (NIR, 1-1.7µm) sensing is currently in use. Yet, dark targets characterized by low reflectance, such as black plastics, are hard to identify by this method. Following the recent success of Midwave Infrared (MWIR, 3-12µm) measurements to identify coloured plastic polymers, the aim of this study was to assess whether this technique is applicable to sorting black plastic polymers and wood products. We performed infrared reflectance contact measurements of 234 plastic samples and 29 samples of wood and paper products. Plastic samples included black, coloured and transparent Polyethylene Terephthalate (PET), Polyethylene (PE), Polyvinyl Chloride (PVC), Polypropylene (PP), Polylactic acid (PLA) and Polystyrene (PS). The spectral signatures of the black and coloured plastic samples were compared with clear plastic samples and signatures documented in the literature to identify the polymer spectral features in the presence of coloured material. This information was used to determine the spectral bands that best suit the sorting of black plastic polymers. The main NIR-MWIR absorption features of wood, cardboard and paper were identified as well according to the spectral measurements. Good agreement was found between our measurements and the absorption features documented in the literature. The new approach using MWIR spectral features appears to be useful for black plastics as it overcomes some of the limitations in the NIR region to identify them. The main limitation of this technique for industrial applications is the trade-off between the signal-to-noise ratio of the sensor operating in standoff mode and the speed at which waste is moved under the sensor. This limitation can be resolved by reducing the system's spectral resolution to 16cm -1 , which allows for faster spectra acquisition while maintaining a reasonable signal-to-noise ratio. Copyright © 2017 Elsevier Ltd. All rights reserved.

INSTRUMENTS AND METHODS OF INVESTIGATION: Spectral and spectral-frequency methods of investigating atmosphereless bodies of the Solar system

NASA Astrophysics Data System (ADS)

Busarev, Vladimir V.; Prokof'eva-Mikhailovskaya, Valentina V.; Bochkov, Valerii V.

2007-06-01

A method of reflectance spectrophotometry of atmosphereless bodies of the Solar system, its specificity, and the means of eliminating basic spectral noise are considered. As a development, joining the method of reflectance spectrophotometry with the frequency analysis of observational data series is proposed. The combined spectral-frequency method allows identification of formations with distinctive spectral features, and estimations of their sizes and distribution on the surface of atmospherelss celestial bodies. As applied to investigations of asteroids 21 Lutetia and 4 Vesta, the spectral frequency method has given us the possibility of obtaining fundamentally new information about minor planets.

SpecViz: Interactive Spectral Data Analysis

NASA Astrophysics Data System (ADS)

Earl, Nicholas Michael; STScI

2016-06-01

The astronomical community is about to enter a new generation of scientific enterprise. With next-generation instrumentation and advanced capabilities, the need has arisen to equip astronomers with the necessary tools to deal with large, multi-faceted data. The Space Telescope Science Institute has initiated a data analysis forum for the creation, development, and maintenance of software tools for the interpretation of these new data sets. SpecViz is a spectral 1-D interactive visualization and analysis application built with Python in an open source development environment. A user-friendly GUI allows for a fast, interactive approach to spectral analysis. SpecViz supports handling of unique and instrument-specific data, incorporation of advanced spectral unit handling and conversions in a flexible, high-performance interactive plotting environment. Active spectral feature analysis is possible through interactive measurement and statistical tools. It can be used to build wide-band SEDs, with the capability of combining or overplotting data products from various instruments. SpecViz sports advanced toolsets for filtering and detrending spectral lines; identifying, isolating, and manipulating spectral features; as well as utilizing spectral templates for renormalizing data in an interactive way. SpecViz also includes a flexible model fitting toolset that allows for multi-component models, as well as custom models, to be used with various fitting and decomposition routines. SpecViz also features robust extension via custom data loaders and connection to the central communication system underneath the interface for more advanced control. Incorporation with Jupyter notebooks via connection with the active iPython kernel allows for SpecViz to be used in addition to a user’s normal workflow without demanding the user drastically alter their method of data analysis. In addition, SpecViz allows the interactive analysis of multi-object spectroscopy in the same straight-forward, consistent way. Through the development of such tools, STScI hopes to unify astronomical data analysis software for JWST and other instruments, allowing for efficient, reliable, and consistent scientific results.

Mars analog minerals' spectral reflectance characteristics under Martian surface conditions

NASA Astrophysics Data System (ADS)

Poitras, J. T.; Cloutis, E. A.; Salvatore, M. R.; Mertzman, S. A.; Applin, D. M.; Mann, P.

2018-05-01

We investigated the spectral reflectance properties of minerals under a simulated Martian environment. Twenty-eight different hydrated or hydroxylated phases of carbonates, sulfates, and silica minerals were selected based on past detection on Mars through spectral remote sensing data. Samples were ground and dry sieved to <45 μm grain size and characterized by XRD before and after 133 days inside a simulated Martian surface environment (pressure 5 Torr and CO2 fed). Reflectance spectra from 0.35 to 4 μm were taken periodically through a sapphire (0.35-2.5 μm) and zinc selenide (2.5-4 μm) window over a 133-day period. Mineral stability on the Martian surface was assessed through changes in spectral characteristics. Results indicate that the hydrated carbonates studied would be stable on the surface of Mars, only losing adsorbed H2O while maintaining their diagnostic spectral features. Sulfates were less stable, often with shifts in the band position of the SO, Fe, and OH absorption features. Silicas displayed spectral shifts related to SiOH and hydration state of the mineral surface, while diagnostic bands for quartz were stable. Previous detection of carbonate minerals based on 2.3-2.5 μm and 3.4-3.9 μm features appears to be consistent with our results. Sulfate mineral detection is more questionable since there can be shifts in band position related to SO4. The loss of the 0.43 μm Fe3+ band in many of the sulfates indicate that there are fewer potential candidates for Fe3+ sulfates to permanently exist on the Martian surface based on this band. The gypsum sample changed phase to basanite during desiccation as demonstrated by both reflectance and XRD. Silica on Mars has been detected using band depth ratio at 1.91 and 1.96 μm and band minimum position of the 1.4 μm feature, and the properties are also used to determine their age. This technique continues to be useful for positive silica identifications, however, silica age appears to be less consistent with our laboratory data. These results will be useful in spectral libraries for characterizing Martian remote sensed data.

3-µm Spectroscopy of Asteroid 16 Psyche

NASA Astrophysics Data System (ADS)

Takir, Driss; Reddy, Vishnu; Sanchez, Juan; Shepard, Michael K.

2016-10-01

Asteroid 16 Psyche, an M-type asteroid, is thought to be one of the most massive exposed iron metal object in the asteroid belt. The high radar albedos of Psyche suggest that this differentiated asteroid is dominantly composed of metal. Psyche was previously found to be featureless in the 3-µm spectral region. However, in our study we found that this asteroid exhibits a 3-µm absorption feature, possibly indicating the presence of hydrated silicates.We have observed Psyche in the 3-µm spectral region, using the long-wavelength cross-dispersed (LXD:1.9-4.2 µm) mode of the SpeX spectrograph/imager at the NASA Infrared Telescope Facility (IRTF). For data reduction, we used the IDL (Interactive Data Language)-based spectral reduction tool Spextool (v4.1). Psyche was observed over the course of three nights with an apparent visual magnitude of ~9.50: 8 December 2015 (3 sets), 9 December 2015 (1 set), and 10 March 2016 (1 set). These observations have revealed that Psyche may exhibit a 3-µm absorption feature, similar to the sharp group in the 2.9-3.3-µm spectral range. Psyche also exhibits an absorption feature similar to the one in Ceres and Ceres-like group in the spectral 3.3-4.0-µm range. These 3-µm observational results revealed that Psyche may not be as featureless as once thought in the 3-µm spectral region.Evidence for the 3-µm band was found on the surfaces of many M-type asteroids and a number of plausible alternative interpretations for the presence of this 3-µm band were previously suggested. These interpretations include the presence of anhydrous silicates containing structural OH, the presence of fluid inclusions, the presence of xenolithic hydrous meteorite components on asteroid surfaces from impacts, solar wind-implanted H, or the presence of troilite. The detection of the Ceres-like feature in the 3.3-4.0-µm spectral range, however, would rule out some of these alternative interpretations, especially the solar wind-implanted H.

Solar-Cycle Variability of Magnetosheath Fluctuations at Earth and Venus

NASA Astrophysics Data System (ADS)

Dwivedi, N. K.; Narita, Y.; Kovacs, P.

2014-12-01

The magnetosheath is a region between the bow-shock and magnetopause and the magnetosheath plasma is mostly in the turbulent state. In the present investigation we put an effort to closely examine the magnetosheath fluctuations dependency on the solar-cycles (solar-maximum and solar minimum) at the magnetized planetary body (Earth) and their comparison with the un-magnetized planetary body (Venus) for the solar minimum. We use the CLUSTER FGM data for the solar-maximum (2001-2002), solar-minimum (2006-2008) and Venus fluxgate magnetometer data for the solar-minimum (2006-2008) to perform a comparative statistical study on the energy spectra and probability density function (PDF) and asses the spectral features of the magnetic fluctuations of the both planetary bodies. In the comparison we study the relation between the inertial ranges of the spectra and the temporal scales of non-Gaussian magnetic fluctuations derived from PDF analyses. The first can refer to turbulent cascade dynamics, while the latter may indicate intermittency. We first transformed the magnetic field data into mean field aligned coordinate system with respect to the large-scale magnetic field direction and then after we compute the power spectral density with the help of Welch algorithm. The computed energy spectra of Earth's magnetosheath show a moderate variability with the solar-cycles and have a broader inertial range. However the estimated energy spectra for the solar-minimum at Venus give the clear evidence of the existence of the break point in the vicinity of the ion gyroradius. After the break-point the energy spectra become steeper and show a distinctive spectral scales which is interpreted as the realization of the begging of the energy cascade. We also briefly address the influence of turbulence on the plasma transport and wave dynamics responsible for the spectral break and predict spectral features of the energy spectra for the solar-maximum at Venus based on the results obtained for the solar-minimum. The research leading to these results has received funding from the European Community's Seventh Framework Programme ([FP7/2007-2013]) under grant agreement number 313038/STORM.

Recent Observations and Modeling of Narrowband Stimulated Electromagnetic Emissions SEEs at HAARP and EISCAT

NASA Astrophysics Data System (ADS)

Scales, W.; Mahmoudian, A.; Fu, H.; Bordikar, M. R.; Samimi, A.; Bernhardt, P. A.; Briczinski, S. J., Jr.; Kosch, M. J.; Senior, A.; Isham, B.

2014-12-01

There has been significant interest in so-called narrowband Stimulated Electromagnetic Emission SEE over the past several years due to recent discoveries at the High Frequency Active Auroral Research Program HAARP facility near Gakone, Alaska. Narrowband SEE (NSEE) has been defined as spectral features in the SEE spectrum typically within 1 kHz of the transmitter (or pump) frequency. SEE is due to nonlinear processes leading to re-radiation at frequencies other than the pump wave frequency during heating the ionospheric plasma with high power HF radio waves. Although NSEE exhibits a richly complex structure, it has now been shown after a substantial number of observations at HAARP, that NSEE can be grouped into two basic classes. The first are those spectral features, associated with Stimulated Brillouin Scatter SBS, which typically occur when the pump frequency is not close to electron gyro-harmonic frequencies. Typically, these spectral features are within roughly 50 Hz of the pump wave frequency where it is to be noted that the O+ ion gyro-frequency is roughly 50 Hz. The second class of spectral features corresponds to the case when the pump wave frequency is typically within roughly 10 kHz of electron gyro-harmonic frequencies. In this case, spectral features ordered by harmonics of ion gyro-frequencies are typically observed, and termed Stimulated Ion Bernstein Scatter SIBS. This presentation will first provide an overview of the recent NSEE experimental observations at HAARP. Both Stimulated Brillouin Scatter SBS and Stimulated Ion Bernstein Scatter SIBS observations will be discussed as well as their relationship to each other. Possible theoretical formulation in terms of parametric decay instabilities and computational modeling will be provided. Possible applications of NSEE will be pointed out including triggering diagnostics for artificial ionization layer formation, proton precipitation event diagnostics, electron temperature measurements in the heated volume and detection of heavy ion species. Finally potential for observing such SEE at the European Incoherent Scatter EISCAT facility will be discussed.

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

NASA Astrophysics Data System (ADS)

Liu, Wanjun; Liang, Xuejian; Qu, Haicheng

2017-11-01

Hyperspectral image (HSI) classification is one of the most popular topics in remote sensing community. Traditional and deep learning-based classification methods were proposed constantly in recent years. In order to improve the classification accuracy and robustness, a dimensionality-varied convolutional neural network (DVCNN) was proposed in this paper. DVCNN was a novel deep architecture based on convolutional neural network (CNN). The input of DVCNN was a set of 3D patches selected from HSI which contained spectral-spatial joint information. In the following feature extraction process, each patch was transformed into some different 1D vectors by 3D convolution kernels, which were able to extract features from spectral-spatial data. The rest of DVCNN was about the same as general CNN and processed 2D matrix which was constituted by by all 1D data. So that the DVCNN could not only extract more accurate and rich features than CNN, but also fused spectral-spatial information to improve classification accuracy. Moreover, the robustness of network on water-absorption bands was enhanced in the process of spectral-spatial fusion by 3D convolution, and the calculation was simplified by dimensionality varied convolution. Experiments were performed on both Indian Pines and Pavia University scene datasets, and the results showed that the classification accuracy of DVCNN improved by 32.87% on Indian Pines and 19.63% on Pavia University scene than spectral-only CNN. The maximum accuracy improvement of DVCNN achievement was 13.72% compared with other state-of-the-art HSI classification methods, and the robustness of DVCNN on water-absorption bands noise was demonstrated.

Immunodominant role of CCHA subunit of Concholepas hemocyanin is associated with unique biochemical properties.

PubMed

Becker, María Inés; Fuentes, Alejandra; Del Campo, Miguel; Manubens, Augusto; Nova, Esteban; Oliva, Harold; Faunes, Fernando; Valenzuela, María Antonieta; Campos-Vallette, Marcelo; Aliaga, Alvaro; Ferreira, Jorge; De Ioannes, Alfredo E; De Ioannes, Pablo; Moltedo, Bruno

2009-03-01

Hemocyanin, the oxygen transporter metallo-glycoprotein from mollusks, shows strong relationship between its notable structural features and intrinsic immunomodulatory effects. Here we investigated the individual contribution of CCHA and CCHB subunits from Concholepas hemocyanin (CCH) to in vivo humoral immune response and their pre-clinical evaluation as immunotherapeutic agent in a mice bladder cancer model, in relation to their biochemical properties. To this end, subunits were purified and well characterized. Homogeneous subunits were obtained by anionic exchange chromatography, and its purity assessed by electrophoretic and immunochemical methods. While each CCH subunit contains eight functional units showing partial cross reaction, the vibrational spectral analysis showed several spectral differences, suggesting structural differences between them. In addition, we demonstrated differences in the carbohydrate content: CCHA had a 3.6% w/w sugar with both N- and O-linked moieties. In turn, CCHB had a 2.5% w/w sugar with N-linked, while O-linked moieties were nearly absent. Considering these differences, it was not possible to predict a priori whether the immunogenic and immunotherapeutic properties of subunits might be similar. Surprisingly, both subunits by itself induced a humoral response, and showed an antitumor effect in the bladder carcinoma cell line MBT-2. However, when immunologic parameters were analyzed, CCHA showed better efficiency than CCHB. No allergic reactions or any toxic effects were observed in mice treated with CCHA, sustaining its potential therapeutic use. Our study supports that CCHA subunit accounts for the most important features involved in the immunogenicity of CCH, such as better hydrophilicity and higher content of carbohydrates.

Shift-variant linear system modeling for multispectral scanners

NASA Astrophysics Data System (ADS)

Amini, Abolfazl M.; Ioup, George E.; Ioup, Juliette W.

1995-07-01

Multispectral scanner data are affected both by the spatial impulse response of the sensor and the spectral response of each channel. To achieve a realistic representation for the output data for a given scene spectral input, both of these effects must be incorporated into a forward model. Each channel can have a different spatial response and each has its characteristic spectral response. A forward model is built which includes the shift invariant spatial broadening of the input for the channels and the shift variant spectral response across channels. The model is applied to the calibrated airborne multispectral scanner as well as the airborne terrestrial applications sensor developed at NASA Stennis Space Center.

Adaptive infrared-reflecting systems inspired by cephalopods

NASA Astrophysics Data System (ADS)

Xu, Chengyi; Stiubianu, George T.; Gorodetsky, Alon A.

2018-03-01

Materials and systems that statically reflect radiation in the infrared region of the electromagnetic spectrum underpin the performance of many entrenched technologies, including building insulation, energy-conserving windows, spacecraft components, electronics shielding, container packaging, protective clothing, and camouflage platforms. The development of their adaptive variants, in which the infrared-reflecting properties dynamically change in response to external stimuli, has emerged as an important unmet scientific challenge. By drawing inspiration from cephalopod skin, we developed adaptive infrared-reflecting platforms that feature a simple actuation mechanism, low working temperature, tunable spectral range, weak angular dependence, fast response, stability to repeated cycling, amenability to patterning and multiplexing, autonomous operation, robust mechanical properties, and straightforward manufacturability. Our findings may open opportunities for infrared camouflage and other technologies that regulate infrared radiation.

Distribution of hydrothermally altered rocks in the Reko Diq, Pakistan mineralized area based on spectral analysis of ASTER data

USGS Publications Warehouse

Rowan, L.C.; Schmidt, R.G.; Mars, J.C.

2006-01-01

The Reko Diq, Pakistan mineralized study area, approximately 10??km in diameter, is underlain by a central zone of hydrothermally altered rocks associated with Cu-Au mineralization. The surrounding country rocks are a variable mixture of unaltered volcanic rocks, fluvial deposits, and eolian quartz sand. Analysis of 15-band Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data of the study area, aided by laboratory spectral reflectance and spectral emittance measurements of field samples, shows that phyllically altered rocks are laterally extensive, and contain localized areas of argillically altered rocks. In the visible through shortwave-infrared (VNIR + SWIR) phyllically altered rocks are characterized by Al-OH absorption in ASTER band 6 because of molecular vibrations in muscovite, whereas argillically altered rocks have an absorption feature in band 5 resulting from alunite. Propylitically altered rocks form a peripheral zone and are present in scattered exposures within the main altered area. Chlorite and muscovite cause distinctive absorption features at 2.33 and 2.20????m, respectively, although less intense 2.33????m absorption is also present in image spectra of country rocks. Important complementary lithologic information was derived by analysis of the spectral emittance data in the 5 thermal-infrared (TIR) bands. Silicified rocks were not distinguished in the 9 VNIR + SWIR bands because of the lack of diagnostic spectral absorption features in quartz in this wavelength region. Quartz-bearing surficial deposits, as well as hydrothermally silicified rocks, were mapped in the TIR bands by using a band 13/band 12 ratio image, which is sensitive to the intensity of the quartz reststrahlen feature. Improved distinction between the quartzose surficial deposits and silicified bedrock was achieved by using matched-filter processing with TIR image spectra for reference. ?? 2006 Elsevier Inc. All rights reserved.

Ultraviolet spectral reflectance of carbonaceous materials

NASA Astrophysics Data System (ADS)

Applin, Daniel M.; Izawa, Matthew R. M.; Cloutis, Edward A.; Gillis-Davis, Jeffrey J.; Pitman, Karly M.; Roush, Ted L.; Hendrix, Amanda R.; Lucey, Paul G.

2018-06-01

A number of planetary spacecraft missions have carried instruments with sensors covering the ultraviolet (UV) wavelength range. However, there exists a general lack of relevant UV reflectance laboratory data to compare against these planetary surface remote sensing observations in order to make confident material identifications. To address this need, we have systematically analyzed reflectance spectra of carbonaceous materials in the 200-500 nm spectral range, and found spectral-compositional-structural relationships that suggest this wavelength region could distinguish between otherwise difficult-to-identify carbon phases. In particular (and by analogy with the infrared spectral region), large changes over short wavelength intervals in the refractive indices associated with the trigonal sp2π-π* transition of carbon can lead to Fresnel peaks and Christiansen-like features in reflectance. Previous studies extending to shorter wavelengths also show that anomalous dispersion caused by the σ-σ* transition associated with both the trigonal sp2 and tetrahedral sp3 sites causes these features below λ = 200 nm. The peak wavelength positions and shapes of π-π* and σ-σ* features contain information on sp3/sp2, structure, crystallinity, and powder grain size. A brief comparison with existing observational data indicates that the carbon fraction of the surface of Mercury is likely amorphous and submicroscopic, as is that on the surface of the martian satellites Phobos and Deimos, and possibly comet 67P/Churyumov-Gerasimenko, while further coordinated observations and laboratory experiments should refine these feature assignments and compositional hypotheses. The new laboratory diffuse reflectance data reported here provide an important new resource for interpreting UV reflectance measurements from planetary surfaces throughout the solar system, and confirm that the UV can be rich in important spectral information.

THE SPITZER ATLAS OF STELLAR SPECTRA (SASS)

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

Ardila, David R.; Van Dyk, Schuyler D.; Makowiecki, Wojciech

2010-12-15

We present the Spitzer Atlas of Stellar Spectra, which includes 159 stellar spectra (5-32 {mu}m; R {approx} 100) taken with the Infrared Spectrograph on the Spitzer Space Telescope. This Atlas gathers representative spectra of a broad section of the Hertzsprung-Russell diagram, intended to serve as a general stellar spectral reference in the mid-infrared. It includes stars from all luminosity classes, as well as Wolf-Rayet (WR) objects. Furthermore, it includes some objects of intrinsic interest, such as blue stragglers and certain pulsating variables. All of the spectra have been uniformly reduced, and all are available online. For dwarfs and giants, themore » spectra of early-type objects are relatively featureless, characterized by the presence of hydrogen lines in A spectral types. Besides these, the most noticeable photospheric features correspond to water vapor and silicon monoxide in late-type objects and methane and ammonia features at the latest spectral types. Most supergiant spectra in the Atlas present evidence of circumstellar gas and/or dust. The sample includes five M supergiant spectra, which show strong dust excesses and in some cases polycyclic aromatic hydrocarbon features. Sequences of WR stars present the well-known pattern of lines of He I and He II, as well as forbidden lines of ionized metals. The characteristic flat-top shape of the [Ne III] line is evident even at these low spectral resolutions. Several Luminous Blue Variables and other transition stars are present in the Atlas and show very diverse spectra, dominated by circumstellar gas and dust features. We show that the [8]-[24] Spitzer colors (IRAC and MIPS) are poor predictors of spectral type for most luminosity classes.« less

The Spitzer Atlas of Stellar Spectra (SASS)

NASA Astrophysics Data System (ADS)

Ardila, David R.; Van Dyk, Schuyler D.; Makowiecki, Wojciech; Stauffer, John; Song, Inseok; Rho, Jeonghee; Fajardo-Acosta, Sergio; Hoard, D. W.; Wachter, Stefanie

2010-12-01

We present the Spitzer Atlas of Stellar Spectra, which includes 159 stellar spectra (5-32 μm R ~ 100) taken with the Infrared Spectrograph on the Spitzer Space Telescope. This Atlas gathers representative spectra of a broad section of the Hertzsprung-Russell diagram, intended to serve as a general stellar spectral reference in the mid-infrared. It includes stars from all luminosity classes, as well as Wolf-Rayet (WR) objects. Furthermore, it includes some objects of intrinsic interest, such as blue stragglers and certain pulsating variables. All of the spectra have been uniformly reduced, and all are available online. For dwarfs and giants, the spectra of early-type objects are relatively featureless, characterized by the presence of hydrogen lines in A spectral types. Besides these, the most noticeable photospheric features correspond to water vapor and silicon monoxide in late-type objects and methane and ammonia features at the latest spectral types. Most supergiant spectra in the Atlas present evidence of circumstellar gas and/or dust. The sample includes five M supergiant spectra, which show strong dust excesses and in some cases polycyclic aromatic hydrocarbon features. Sequences of WR stars present the well-known pattern of lines of He I and He II, as well as forbidden lines of ionized metals. The characteristic flat-top shape of the [Ne III] line is evident even at these low spectral resolutions. Several Luminous Blue Variables and other transition stars are present in the Atlas and show very diverse spectra, dominated by circumstellar gas and dust features. We show that the [8]-[24] Spitzer colors (IRAC and MIPS) are poor predictors of spectral type for most luminosity classes.

Berkeley SuperNova Ia Program (BSNIP): Initial Spectral Analysis

NASA Astrophysics Data System (ADS)

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

2011-01-01

The Berkeley SuperNova Ia Program (BSNIP) has been observing nearby (z < 0.1) Type Ia supernovae (SNe Ia) both photometrically and spectroscopically for over two decades. Using telescopes at both Lick and Keck Observatories, we have amassed an extensive collection of well-sampled optical light curves with complementary spectra covering, on average, 3400-10,000 Å. In total, we have obtained nearly 600 spectra of over 200 SNe Ia with densely sampled multi-color light curves. The initial analysis of this dataset consists of accurately and robustly measuring the strength and position of various spectral features near maximum brightness. We determine the endpoints, pseudo-continuum, expansion velocity, equivalent width, and depth of each major feature observed in our wavelength range. For objects with multiple spectra near maximum brightness we investigate how these values change with time. From these measurements we also calculate velocity gradients and various flux ratios within a given spectrum which will allow us to explore correlations between spectral and photometric observables. Some possible correlations have been studied previously, but our dataset is unique in how self-consistent the data reduction and spectral feature measurements have been, and it is a factor of a few larger than most earlier studies. We will briefly summarize the contents of the full dataset as an introduction to our initial analysis. Some of our measurements of SN Ia spectral features, along with a few initial results from those measurements, will be presented. Finally, we will comment on our current progress and planned future work. We gratefully acknowledge the financial support of NSF grant AST-0908886, the TABASGO Foundation, and the Marc J. Staley Graduate Fellowship in Astronomy.

Signature Optical Cues: Emerging Technologies for Monitoring Plant Health

PubMed Central

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

2008-01-01

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

Interactions between pre-processing and classification methods for event-related-potential classification: best-practice guidelines for brain-computer interfacing.

PubMed

Farquhar, J; Hill, N J

2013-04-01

Detecting event related potentials (ERPs) from single trials is critical to the operation of many stimulus-driven brain computer interface (BCI) systems. The low strength of the ERP signal compared to the noise (due to artifacts and BCI irrelevant brain processes) makes this a challenging signal detection problem. Previous work has tended to focus on how best to detect a single ERP type (such as the visual oddball response). However, the underlying ERP detection problem is essentially the same regardless of stimulus modality (e.g., visual or tactile), ERP component (e.g., P300 oddball response, or the error-potential), measurement system or electrode layout. To investigate whether a single ERP detection method might work for a wider range of ERP BCIs we compare detection performance over a large corpus of more than 50 ERP BCI datasets whilst systematically varying the electrode montage, spectral filter, spatial filter and classifier training methods. We identify an interesting interaction between spatial whitening and regularised classification which made detection performance independent of the choice of spectral filter low-pass frequency. Our results show that pipeline consisting of spectral filtering, spatial whitening, and regularised classification gives near maximal performance in all cases. Importantly, this pipeline is simple to implement and completely automatic with no expert feature selection or parameter tuning required. Thus, we recommend this combination as a "best-practice" method for ERP detection problems.

CCD reflectance spectra of selected asteroids. I - Presentation and data analysis considerations

NASA Technical Reports Server (NTRS)

Vilas, Faith; Mcfadden, Lucy A.

1992-01-01

Narrowband reflectance spectra have been acquired which contribute to the library of asteroid data in the visible and near-IR spectral regions. The spectra support the existence of aqueous alteration products on asteroids located in the outer part of the main asteroid belt out to at least 4 AU. No evidence for features similar to the spectral features of ordinary chondrite meteorites was found in the spectra of asteroids located near the 3:1 Kirkwood Gap chaotic zone.

Evaluation and Improvement of Spectral Features for the Detection of Buried Explosive Hazards Using Forward-Looking Ground-Penetrating Radar

DTIC Science & Technology

2012-07-01

cross track direction is calculated. This is accomplished by taking a 101 point horizontal slice of pixels centered on the alarm. Then, a 101 point...Hamming window, is the 101 -length row vector of FLGPR image pixels surrounding alarm A. We then store the first 50 frequency values (excluding the...Figure 3. Illustration of spectral features in the cross track direction and the difference between actual targets and FAs. Eleven rows of 101

Thermal infrared spectral character of Hawaiian basaltic glasses

NASA Technical Reports Server (NTRS)

Crisp, Joy; Kahle, Anne B.; Abbott, Elsa A.

1990-01-01

Thermal IR reflectance spectra of exposed surfaces of Hawaiian basalt samples from Mauna Loa and Kilauea show systematic changes with age. Spectra of fresh glass collected from active lava flows showed evidence of a strong degree of disorder. After a few weeks of exposure to the laboratory environment, spectra of the top surfaces of these samples began to exhibit spectral features suggestive of ordering into silicate chainlike ansd sheetlike units. With progressive aging, features of apparent sheetlike structures became the preferred mode.

Novel Spectral Representations and Sparsity-Driven Algorithms for Shape Modeling and Analysis

NASA Astrophysics Data System (ADS)

Zhong, Ming

In this dissertation, we focus on extending classical spectral shape analysis by incorporating spectral graph wavelets and sparsity-seeking algorithms. Defined with the graph Laplacian eigenbasis, the spectral graph wavelets are localized both in the vertex domain and graph spectral domain, and thus are very effective in describing local geometry. With a rich dictionary of elementary vectors and forcing certain sparsity constraints, a real life signal can often be well approximated by a very sparse coefficient representation. The many successful applications of sparse signal representation in computer vision and image processing inspire us to explore the idea of employing sparse modeling techniques with dictionary of spectral basis to solve various shape modeling problems. Conventional spectral mesh compression uses the eigenfunctions of mesh Laplacian as shape bases, which are highly inefficient in representing local geometry. To ameliorate, we advocate an innovative approach to 3D mesh compression using spectral graph wavelets as dictionary to encode mesh geometry. The spectral graph wavelets are locally defined at individual vertices and can better capture local shape information than Laplacian eigenbasis. The multi-scale SGWs form a redundant dictionary as shape basis, so we formulate the compression of 3D shape as a sparse approximation problem that can be readily handled by greedy pursuit algorithms. Surface inpainting refers to the completion or recovery of missing shape geometry based on the shape information that is currently available. We devise a new surface inpainting algorithm founded upon the theory and techniques of sparse signal recovery. Instead of estimating the missing geometry directly, our novel method is to find this low-dimensional representation which describes the entire original shape. More specifically, we find that, for many shapes, the vertex coordinate function can be well approximated by a very sparse coefficient representation with respect to the dictionary comprising its Laplacian eigenbasis, and it is then possible to recover this sparse representation from partial measurements of the original shape. Taking advantage of the sparsity cue, we advocate a novel variational approach for surface inpainting, integrating data fidelity constraints on the shape domain with coefficient sparsity constraints on the transformed domain. Because of the powerful properties of Laplacian eigenbasis, the inpainting results of our method tend to be globally coherent with the remaining shape. Informative and discriminative feature descriptors are vital in qualitative and quantitative shape analysis for a large variety of graphics applications. We advocate novel strategies to define generalized, user-specified features on shapes. Our new region descriptors are primarily built upon the coefficients of spectral graph wavelets that are both multi-scale and multi-level in nature, consisting of both local and global information. Based on our novel spectral feature descriptor, we developed a user-specified feature detection framework and a tensor-based shape matching algorithm. Through various experiments, we demonstrate the competitive performance of our proposed methods and the great potential of spectral basis and sparsity-driven methods for shape modeling.

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

NASA Astrophysics Data System (ADS)

Leviner, Marom; Maltz, Masha

2009-03-01

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

THE VIEWING ANGLES OF BROAD ABSORPTION LINE VERSUS UNABSORBED QUASARS

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

DiPompeo, M. A.; Brotherton, M. S.; De Breuck, C.

2012-06-10

It was recently shown that there is a significant difference in the radio spectral index distributions of broad absorption line (BAL) quasars and unabsorbed quasars, with an overabundance of BAL quasars with steeper radio spectra. This result suggests that source orientation does play into the presence or absence of BAL features. In this paper, we provide more quantitative analysis of this result based on Monte Carlo simulations. While the relationship between viewing angle and spectral index does indeed contain a lot of scatter, the spectral index distributions are different enough to overcome that intrinsic variation. Utilizing two different models ofmore » the relationship between spectral index and viewing angle, the simulations indicate that the difference in spectral index distributions can be explained by allowing BAL quasar viewing angles to extend about 10 Degree-Sign farther from the radio jet axis than non-BAL sources, though both can be seen at small angles. These results show that orientation cannot be the only factor determining whether BAL features are present, but it does play a role.« less

A Developed Spectral Identification Tree for Mineral Mapping using Hyperspectral Data

NASA Astrophysics Data System (ADS)

Gan, Fuping; Wang, Runsheng; Yan, Bokun; Shang, Kun

2016-04-01

The relationship between the spectral features and the composition of minerals are the basis of mineral identification using hyperspectral data. The reflectance spectrum of minerals results from the systematic combination of several modes of interaction between electromagnetic energy and mineral particles in the form of reflection and absorption. Minerals tend to have absorbing features at specific wavelengths with a characteristic shape, which can be used as diagnostic indicators for identification. The spectral identification tree (SIT) method for mineral identification is developed in our research to map minerals accurately and applied in some typical mineral deposits in China. The SIT method is based on the diagnostic absorption features of minerals through comparing and statistically analyzing characteristic spectral data of minerals. We establish several levels of identification rules for the type, group and species of minerals using IF-THEN rule according to the spectral identification criteria so that the developed SIT can be further used to map minerals at different levels of detail from mineral type to mineral species. Identifiable minerals can be grouped into six types: Fe2+-bearing, Fe3+-bearing, Mn2+-bearing, Al-OH-bearing, Mg-OH-bearing and carbonate minerals. Each type can be further divided into several mineral groups. Each group contains several mineral species or specific minerals. A mineral spectral series, therefore, can be constructed as "type-group-species-specific mineral (mineral variety)" for mineral spectral identification. It is noted that the mineral classification is based mainly on spectral reflectance characteristics of minerals which may not be consistent with the classification in mineralogy. We applied the developed SIT method to the datasets acquired at the Eastern Tianshan Mountains of Xinjiang (HyMap data) and the Qulong district of Xizang (Hyperion data). In Xinjiang, the two major classes of Al-OH and Mg-OH minerals were mapped firstly. Then montmorillonite, kaolinite and muscovite were identified in the area of the Al-OH bearing minerals, and chlorite and epidote were identified in the area of the Mg-OH bearing minerals. Muscovite of rich Al and poor Al were further identified in the area of muscovite. In Xizang, Al-rich and Al-poor muscovite, kaolinite, chlorite and malachite were identified using SIT method. In all, the developed SIT method can further reduce the effect of other materials and focus on targeted minerals. In particular, the discrimination accuracy will be improved when the most diagnostic absorption spectral features are used in the developed SIT method.

The correlated k-distribution technique as applied to the AVHRR channels

NASA Technical Reports Server (NTRS)

Kratz, David P.

1995-01-01

Correlated k-distributions have been created to account for the molecular absorption found in the spectral ranges of the five Advanced Very High Resolution Radiometer (AVHRR) satellite channels. The production of the k-distributions was based upon an exponential-sum fitting of transmissions (ESFT) technique which was applied to reference line-by-line absorptance calculations. To account for the overlap of spectral features from different molecular species, the present routines made use of the multiplication transmissivity property which allows for considerable flexibility, especially when altering relative mixing ratios of the various molecular species. To determine the accuracy of the correlated k-distribution technique as compared to the line-by-line procedure, atmospheric flux and heating rate calculations were run for a wide variety of atmospheric conditions. For the atmospheric conditions taken into consideration, the correlated k-distribution technique has yielded results within about 0.5% for both the cases where the satellite spectral response functions were applied and where they were not. The correlated k-distribution's principal advantages is that it can be incorporated directly into multiple scattering routines that consider scattering as well as absorption by clouds and aerosol particles.

Vanadium supersaturated silicon system: a theoretical and experimental approach

NASA Astrophysics Data System (ADS)

Garcia-Hemme, Eric; García, Gregorio; Palacios, Pablo; Montero, Daniel; García-Hernansanz, Rodrigo; Gonzalez-Diaz, Germán; Wahnon, Perla

2017-12-01

The effect of high dose vanadium ion implantation and pulsed laser annealing on the crystal structure and sub-bandgap optical absorption features of V-supersaturated silicon samples has been studied through the combination of experimental and theoretical approaches. Interest in V-supersaturated Si focusses on its potential as a material having a new band within the Si bandgap. Rutherford backscattering spectrometry measurements and formation energies computed through quantum calculations provide evidence that V atoms are mainly located at interstitial positions. The response of sub-bandgap spectral photoconductance is extended far into the infrared region of the spectrum. Theoretical simulations (based on density functional theory and many-body perturbation in GW approximation) bring to light that, in addition to V atoms at interstitial positions, Si defects should also be taken into account in explaining the experimental profile of the spectral photoconductance. The combination of experimental and theoretical methods provides evidence that the improved spectral photoconductance up to 6.2 µm (0.2 eV) is due to new sub-bandgap transitions, for which the new band due to V atoms within the Si bandgap plays an essential role. This enables the use of V-supersaturated silicon in the third generation of photovoltaic devices.

Spectral evolution of active galactic nuclei: A unified description of the X-ray and gamma

NASA Technical Reports Server (NTRS)

Leiter, D.; Boldt, E.

1982-01-01

A model for spectral evolution is presented whereby active galactic nuclei (AGN) of the type observed individually emerge from an earlier stage at z approx = 4 in which they are the thermal X-ray sources responsible for most of the cosmic X-ray background (CXB). The conjecture is pursued that these precursor objects are initially supermassive Schwarzschild black holes with accretion disks radiating near the Eddington luminosity limit. It is noted that after approx. 10 to the 8th power years these central black holes are spun-up to a canonical Kerr equilibrium state (A/M = 0.998; Thorne 1974) and shown how they then can lead to spectral evolution involving non-thermal emission extending to gamma rays, at the expense of reduced thermal disk radiation. That major portion of the CXB remaining after the contribution of usual AGN are considered, while a superposition of AGN sources at z 1 can account for the gamma ray background. Extensive X-ray measurements carried out with the HEAO 1 and 2 missions as well as gamma ray and optical data are shown to compare favorably with principal features of this model.

Novel micro-Raman setup with tunable laser excitation for time-efficient resonance Raman microscopy and imaging.

PubMed

Stürzl, Ninette; Lebedkin, Sergei; Klumpp, Stefanie; Hennrich, Frank; Kappes, Manfred M

2013-05-07

We describe a micro-Raman setup allowing for efficient resonance Raman spectroscopy (RRS), i.e., mapping of Raman spectra as a function of tunable laser excitation wavelength. The instrument employs angle-tunable bandpass optical filters which are integrated into software-controlled Raman and laser cleanup filter devices. These automatically follow the excitation laser wavelength and combine tunability with high bandpass transmission as well as high off-band blocking of light. Whereas the spectral intervals which can be simultaneously acquired are bandpass limited to ~350 cm(-1), they can be tuned across the spectrum of interest to access all characteristic Raman features. As an illustration of performance, we present Raman mapping of single-walled carbon nanotubes (SWNTs): (i) in a small volume of water-surfactant dispersion as well as (ii) after deposition onto a substrate. A significant improvement in the acquisition time (and efficiency) is demonstrated compared to previous RRS implementations. These results may help to establish (micro) Raman spectral mapping as a routine tool for characterization of SWNTs as well as other materials with a pronounced resonance Raman response in the visible-near-infrared spectral region.

Study and simulation results for video landmark acquisition and tracking technology (Vilat-2)

NASA Technical Reports Server (NTRS)

Lowrie, J. W.; Tietz, J. C.; Thomas, H. M.; Gremban, K. D.; Hughes, C.; Chang, C. Y.

1983-01-01

The results of several investigations and hardware developments which supported new technology for Earth feature recognition and classification are described. Data analysis techniques and procedures were developed for processing the Feature Identification and Location Experiment (FILE) data. This experiment was flown in November 1981, on the second Shuttle flight and a second instrument, designed for aircraft flights, was flown over the United States in 1981. Ground tests were performed to provide the basis for designing a more advanced version (four spectral bands) of the FILE which would be capable of classifying clouds and snow (and possibly ice) as distinct features, in addition to the features classified in the Shuttle experiment (two spectral bands). The Shuttle instrument classifies water, bare land, vegetation, and clouds/snow/ice (grouped).

Spectral Optical Readout of Rectangular–Miniature Hollow Glass Tubing for Refractive Index Sensing

PubMed Central

Rigamonti, Giulia; Bello, Valentina

2018-01-01

For answering the growing demand of innovative micro-fluidic devices able to measure the refractive index of samples in extremely low volumes, this paper presents an overview of the performances of a micro-opto-fluidic sensing platform that employs rectangular, miniature hollow glass tubings. The operating principle is described by showing the analytical model of the tubing, obtained as superposition of different optical cavities, and the optical readout method based on spectral reflectivity detection. We have analyzed, in particular, the theoretical and experimental optical features of rectangular tubings with asymmetrical geometry, thus with channel depth larger than the thickness of the glass walls, though all of them in the range of a few tens of micrometers. The origins of the complex line-shape of the spectral response in reflection, due to the different cavities formed by the tubing flat walls and channel, have been investigated using a Fourier transform analysis. The implemented instrumental configuration, based on standard telecom fiberoptic components and a semiconductor broadband optical source emitting in the near infrared wavelength region centered at 1.55 µm, has allowed acquisition of reflectivity spectra for experimental verification of the expected theoretical behavior. We have achieved detection of refractive index variations related to the change of concentration of glucose-water solutions flowing through the tubing by monitoring the spectral shift of the optical resonances. PMID:29462907

Spectral Optical Readout of Rectangular-Miniature Hollow Glass Tubing for Refractive Index Sensing.

PubMed

Rigamonti, Giulia; Bello, Valentina; Merlo, Sabina

2018-02-16

For answering the growing demand of innovative micro-fluidic devices able to measure the refractive index of samples in extremely low volumes, this paper presents an overview of the performances of a micro-opto-fluidic sensing platform that employs rectangular, miniature hollow glass tubings. The operating principle is described by showing the analytical model of the tubing, obtained as superposition of different optical cavities, and the optical readout method based on spectral reflectivity detection. We have analyzed, in particular, the theoretical and experimental optical features of rectangular tubings with asymmetrical geometry, thus with channel depth larger than the thickness of the glass walls, though all of them in the range of a few tens of micrometers. The origins of the complex line-shape of the spectral response in reflection, due to the different cavities formed by the tubing flat walls and channel, have been investigated using a Fourier transform analysis. The implemented instrumental configuration, based on standard telecom fiberoptic components and a semiconductor broadband optical source emitting in the near infrared wavelength region centered at 1.55 µm, has allowed acquisition of reflectivity spectra for experimental verification of the expected theoretical behavior. We have achieved detection of refractive index variations related to the change of concentration of glucose-water solutions flowing through the tubing by monitoring the spectral shift of the optical resonances.

USGS Digital Spectral Library splib05a

USGS Publications Warehouse

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

2003-01-01

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

Cloud classification in polar regions using AVHRR textural and spectral signatures

NASA Technical Reports Server (NTRS)

Welch, R. M.; Sengupta, S. K.; Weger, R. C.; Christopher, S. A.; Kuo, K. S.; Carsey, F. D.

1990-01-01

Arctic clouds and ice-covered surfaces are classified on the basis of textural and spectral features obtained with AVHRR 1.1-km spatial resolution imagery over the Beaufort Sea during May-October, 1989. Scenes were acquired about every 5 days, for a total of 38 cases. A list comprising 20 arctic-surface and cloud classes is compiled using spectral measures defined by Garand (1988).

The Copernicus ultraviolet spectral atlas of Vega

NASA Technical Reports Server (NTRS)

Rogerson, John B., Jr.

1989-01-01

A near-ultraviolet spectral atlas for the A0 V star Alpha Lyr (Vega) has been prepared from data taken by the Princeton spectrometer aboard the Copernicus satellite. The spectral region from 2000 to 3187 A has been scanned with a resolution of 0.1 A. The atlas is presented in graphs with a normalized continuum, and an identification table for the absorption features has been prepared.

Indirect searches of dark matter via polynomial spectral features

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

Garcia-Cely, Camilo; Heeck, Julian

2016-08-11

We derive the spectra arising from non-relativistic dark matter annihilations or decays into intermediary particles with arbitrary spin, which subsequently produce neutrinos or photons via two-body decays. Our approach is model independent and predicts spectral features restricted to a kinematic box. The overall shape within that box is a polynomial determined by the polarization of the decaying particle. We illustrate our findings with two examples. First, with the neutrino spectra arising from dark matter annihilations into the massive Standard Model gauge bosons. Second, with the gamma-ray and neutrino spectra generated by dark matter annihilations into hypothetical massive spin-2 particles. Ourmore » results are in particular applicable to the 750 GeV diphoton excess observed at the LHC if interpreted as a spin-0 or spin-2 particle coupled to dark matter. We also derive limits on the dark matter annihilation cross section into this resonance from the non-observation of the associated gamma-ray spectral features by the H.E.S.S. telescope.« less

Spectrally queued feature selection for robotic visual odometery

NASA Astrophysics Data System (ADS)

Pirozzo, David M.; Frederick, Philip A.; Hunt, Shawn; Theisen, Bernard; Del Rose, Mike

2011-01-01

Over the last two decades, research in Unmanned Vehicles (UV) has rapidly progressed and become more influenced by the field of biological sciences. Researchers have been investigating mechanical aspects of varying species to improve UV air and ground intrinsic mobility, they have been exploring the computational aspects of the brain for the development of pattern recognition and decision algorithms and they have been exploring perception capabilities of numerous animals and insects. This paper describes a 3 month exploratory applied research effort performed at the US ARMY Research, Development and Engineering Command's (RDECOM) Tank Automotive Research, Development and Engineering Center (TARDEC) in the area of biologically inspired spectrally augmented feature selection for robotic visual odometry. The motivation for this applied research was to develop a feasibility analysis on multi-spectrally queued feature selection, with improved temporal stability, for the purposes of visual odometry. The intended application is future semi-autonomous Unmanned Ground Vehicle (UGV) control as the richness of data sets required to enable human like behavior in these systems has yet to be defined.

A comparison of three feature selection methods for object-based classification of sub-decimeter resolution UltraCam-L imagery

USDA-ARS?s Scientific Manuscript database

The availability of numerous spectral, spatial, and contextual features with object-based image analysis (OBIA) renders the selection of optimal features a time consuming and subjective process. While several feature election methods have been used in conjunction with OBIA, a robust comparison of th...

Discriminating Induced-Microearthquakes Using New Seismic Features

NASA Astrophysics Data System (ADS)

Mousavi, S. M.; Horton, S.

2016-12-01

We studied characteristics of induced-microearthquakes on the basis of the waveforms recorded on a limited number of surface receivers using machine-learning techniques. Forty features in the time, frequency, and time-frequency domains were measured on each waveform, and several techniques such as correlation-based feature selection, Artificial Neural Networks (ANNs), Logistic Regression (LR) and X-mean were used as research tools to explore the relationship between these seismic features and source parameters. The results show that spectral features have the highest correlation to source depth. Two new measurements developed as seismic features for this study, spectral centroids and 2D cross-correlations in the time-frequency domain, performed better than the common seismic measurements. These features can be used by machine learning techniques for efficient automatic classification of low energy signals recorded at one or more seismic stations. We applied the technique to 440 microearthquakes-1.7Reference: Mousavi, S.M., S.P. Horton, C. A. Langston, B. Samei, (2016) Seismic features and automatic discrimination of deep and shallow induced-microearthquakes using neural network and logistic regression, Geophys. J. Int. doi: 10.1093/gji/ggw258.

Spitzer-IRS Spectroscopic Studies of Oxygen-Rich Asymptotic Giant Branch Star and Red Supergiant Star Dust Properties

NASA Astrophysics Data System (ADS)

Sargent, Benjamin A.; Srinivasan, Sundar; Speck, Angela; Volk, Kevin; Kemper, Ciska; Reach, William T.; Lagadec, Eric; Bernard, Jean-Philippe; McDonald, Iain; Meixner, Margaret

2015-01-01

We analyze the dust emission features seen in Spitzer Space Telescope Infrared Spectrograph (IRS) spectra of Oxygen-rich (O-rich) asymptotic giant branch (AGB) and red supergiant (RSG) stars. The spectra come from the Spitzer Legacy program SAGE-Spectroscopy (PI: F. Kemper) and other archival Spitzer-IRS programs. The broad 10 and 20 micron emission features attributed to amorphous dust of silicate composition seen in the spectra show evidence for systematic differences in the centroid of both emission features between O-rich AGB and RSG populations. Radiative transfer modeling using the GRAMS grid of models of AGB and RSG stars suggests that the centroid differences are due to differences in dust properties. We present an update of our investigation of differences in dust composition, size, shape, etc that might be responsible for these spectral differences. We explore how these differences may arise from the different circumstellar environments around RSG and O-rich AGB stars. BAS acknowledges funding from NASA ADAP grant NNX13AD54G.

Spitzer-IRS Spectroscopic Studies of the Properties of Dust from Oxygen-Rich Asymptotic Giant Branch and Red Supergiant Stars

NASA Astrophysics Data System (ADS)

Sargent, Benjamin A.; Speck, A.; Volk, K.; Kemper, C.; Reach, W. T.; Lagadec, E.; Bernard, J.; McDonald, I.; Meixner, M.; Srinivasan, S.

2014-01-01

We analyze the dust emission features seen in Spitzer Space Telescope Infrared Spectrograph (IRS) spectra of Oxygen-rich (O-rich) asymptotic giant branch (AGB) and red supergiant (RSG) stars. The spectra come from the Spitzer Legacy program SAGE-Spectroscopy (PI: F. Kemper) and other archival Spitzer-IRS programs. The broad 10 and 20 micron emission features attributed to amorphous dust of silicate composition seen in the spectra show evidence for systematic differences in the centroid of both emission features between O-rich AGB and RSG populations. Radiative transfer modeling using the GRAMS grid of models of AGB and RSG stars suggests that the centroid differences are due to differences in dust properties. We investigate differences in dust composition, size, shape, etc that might be responsible for these spectral differences. We explore how these differences may arise from the different circumstellar environments around RSG and O-rich AGB stars. BAS acknowledges funding from NASA ADAP grant NNX13AD54G.

Linking Spectral Features with Composition, Crystallinity, and Roughness Properties of Silica and Implications for Candidate Hydrothermal Systems on Mars

NASA Astrophysics Data System (ADS)

Hamilton, V. E.; McDowell, M. L.; Berger, J. A.; Cady, S. L.; Knauth, L. P.

2011-12-01

We have collected visible to near infrared reflectance (VNIR, ~0.4 - 2.5 um), thermal infrared emissivity (TIR, ~5 - 45 um), SEM, XRD, surface roughness, and petrographic data for 18 silica samples. These rocks (e.g., replacement chert, geyserite, opal-A/-CT) represent a variety of geologic formation environments, including hydrothermal, and have XRD-determined crystallinities ranging from <1 to >10 according to the quartz crystallinity index. Our findings are relevant to the interpretation of orbital and in situ spectral observations of crystalline or amorphous silica on the Martian surface, some of which may have formed in hydrothermal systems. Almost all of our samples' VNIR spectra contain discernible bands. The most common features are related to hydration (H2O and/or OH) of silica (e.g., at ~1.4, 1.9, and 2.2 um). The visibility and strength of these bands is not always constant between spectra from different areas of a sample. Other features include those of carbonate, phyllosilicate, and iron oxide impurities. All of our amorphous silica samples have hydration features in the VNIR, but we note that the absorptions around ~2.2 um can be very weak in amorphous samples relative to features at other wavelengths and relative to ~2.2-um features observed in Martian data, suggesting that some amorphous silica on Mars could go undetected. Deposits containing significant anhydrous, crystalline silica (chert) may be assumed to lack features in the VNIR, but many of our cherts have spectral features and could be misidentified as materials dominated by what is a minor contaminant. Thermal infrared spectra of chert and opaline silica differ from each other as a result of the loss of long-range Si-O order in increasingly amorphous samples. Our samples display a clear trend in TIR band shapes where features attributable to crystalline quartz and amorphous silica are blended in samples with intermediate crystallinities. Most diagnostic TIR spectral features observable in laboratory data typically are recognizable in hyperspectral remote sensing data. These features are more difficult to distinguish (or are not included) at multispectral resolutions, but in nearly all uncontaminated samples, the positions of Si-O emissivity minima shift towards longer wavelengths with decreasing crystallinity. Contaminating phases with strong VNIR spectral features are observed in some of the TIR spectra but have a negligible effect in others, suggesting that TIR spectroscopy helps constrain the abundances of these phases. In addition to compositional and crystallinity information, our laboratory data demonstrate that TIR spectra can be used to deduce important information on silica phases' texture and orientation. If used in combination, VNIR and TIR spectroscopy can detect and characterize silica phases, allowing us to estimate conditions of silica formation, e.g., high- or low-temperature aqueous systems.

Use of field reflectance data for crop mapping using airborne hyperspectral image

NASA Astrophysics Data System (ADS)

Nidamanuri, Rama Rao; Zbell, Bernd

2011-09-01

Recent developments in hyperspectral remote sensing technologies enable acquisition of image with high spectral resolution, which is typical to the laboratory or in situ reflectance measurements. There has been an increasing interest in the utilization of in situ reference reflectance spectra for rapid and repeated mapping of various surface features. Here we examined the prospect of classifying airborne hyperspectral image using field reflectance spectra as the training data for crop mapping. Canopy level field reflectance measurements of some important agricultural crops, i.e. alfalfa, winter barley, winter rape, winter rye, and winter wheat collected during four consecutive growing seasons are used for the classification of a HyMAP image acquired for a separate location by (1) mixture tuned matched filtering (MTMF), (2) spectral feature fitting (SFF), and (3) spectral angle mapper (SAM) methods. In order to answer a general research question "what is the prospect of using independent reference reflectance spectra for image classification", while focussing on the crop classification, the results indicate distinct aspects. On the one hand, field reflectance spectra of winter rape and alfalfa demonstrate excellent crop discrimination and spectral matching with the image across the growing seasons. On the other hand, significant spectral confusion detected among the winter barley, winter rye, and winter wheat rule out the possibility of existence of a meaningful spectral matching between field reflectance spectra and image. While supporting the current notion of "non-existence of characteristic reflectance spectral signatures for vegetation", results indicate that there exist some crops whose spectral signatures are similar to characteristic spectral signatures with possibility of using them in image classification.

Processing of spectral and amplitude envelope of animal vocalizations in the human auditory cortex.

PubMed

Altmann, Christian F; Gomes de Oliveira Júnior, Cícero; Heinemann, Linda; Kaiser, Jochen

2010-08-01

In daily life, we usually identify sounds effortlessly and efficiently. Two properties are particularly salient and of importance for sound identification: the sound's overall spectral envelope and its temporal amplitude envelope. In this study, we aimed at investigating the representation of these two features in the human auditory cortex by using a functional magnetic resonance imaging adaptation paradigm. We presented pairs of sound stimuli derived from animal vocalizations that preserved the time-averaged frequency spectrum of the animal vocalizations and the amplitude envelope. We presented the pairs in four different conditions: (a) pairs with the same amplitude envelope and mean spectral envelope, (b) same amplitude envelope, but different mean spectral envelope, (c) different amplitude envelope, but same mean spectral envelope and (d) both different amplitude envelope and mean spectral envelope. We found fMRI adaptation effects for both the mean spectral envelope and the amplitude envelope of animal vocalizations in overlapping cortical areas in the bilateral superior temporal gyrus posterior to Heschl's gyrus. Areas sensitive to the amplitude envelope extended further anteriorly along the lateral superior temporal gyrus in the left hemisphere, while areas sensitive to the spectral envelope extended further anteriorly along the right lateral superior temporal gyrus. Posterior tonotopic areas within the left superior temporal lobe displayed sensitivity for the mean spectrum. Our findings suggest involvement of primary auditory areas in the representation of spectral cues and encoding of general spectro-temporal features of natural sounds in non-primary posterior and lateral superior temporal cortex. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Characterization of Cryptosporidium parvum by Matrix-Assisted Laser Desorption Ionization–Time of Flight Mass Spectrometry

PubMed Central

Magnuson, Matthew L.; Owens, James H.; Kelty, Catherine A.

2000-01-01

Matrix-assisted laser desorption ionization–time of flight mass spectrometry (MALDI-TOF MS) was used to investigate whole and freeze-thawed Cryptosporidium parvum oocysts. Whole oocysts revealed some mass spectral features. Reproducible patterns of spectral markers and increased sensitivity were obtained after the oocysts were lysed with a freeze-thaw procedure. Spectral-marker patterns for C. parvum were distinguishable from those obtained for Cryptosporidium muris. One spectral marker appears specific for the genus, while others appear specific at the species level. Three different C. parvum lots were investigated, and similar spectral markers were observed in each. Disinfection of the oocysts reduced and/or eliminated the patterns of spectral markers. PMID:11055915

Demonstration of spectral correlation control in a source of polarization-entangled photon pairs at telecom wavelength.

PubMed

Lutz, Thomas; Kolenderski, Piotr; Jennewein, Thomas

2014-03-15

Spectrally correlated photon pairs can be used to improve the performance of long-range fiber-based quantum communication protocols. We present a source based on spontaneous parametric downconversion, which allows one to control spectral correlations within the entangled photon pair without spectral filtering by changing the pump-pulse duration or the characteristics of the coupled spatial modes. The spectral correlations and polarization entanglement are characterized. We find that the generated photon pairs can feature both positive spectral correlations, decorrelation, or negative correlations at the same time as polarization entanglement with a high fidelity of 0.97 (no background subtraction) with the expected Bell state.

A TALE OF THREE MYSTERIOUS SPECTRAL FEATURES IN CARBON-RICH EVOLVED STARS: THE 21 μm, 30 μm, AND “UNIDENTIFIED INFRARED” EMISSION FEATURES

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

Mishra, Ajay; Li, Aigen; Jiang, B. W., E-mail: amishra@mail.missouri.edu, E-mail: lia@missouri.edu, E-mail: bjiang@bnu.edu.cn

2015-03-20

The mysterious “21 μm” emission feature seen almost exclusively in the short-lived protoplanetary nebula (PPN) phase of stellar evolution remains unidentified since its discovery two decades ago. This feature is always accompanied by the equally mysterious, unidentified “30 μm” feature and the so-called “unidentified infrared” (UIR) features at 3.3, 6.2, 7.7, 8.6, and 11.3 μm which are generally attributed to polycyclic aromatic hydrocarbon (PAH) molecules. The 30 μm feature is commonly observed in all stages of stellar evolution from the asymptotic giant branch through PPN to the planetary nebula phase. We explore the interrelations among the mysterious 21, 30 μm,more » and UIR features of the 21 μm sources. We derive the fluxes emitted in the observed UIR, 21, and 30 μm features from published Infrared Space Observatory or Spitzer/IRS spectra. We find that none of these spectral features correlate with each other. This argues against a common carrier (e.g., thiourea) for both the 21 μm feature and the 30 μm feature. This also does not support large PAH clusters as a possible carrier for the 21 μm feature.« less

Simulation of the hyperspectral data from multispectral data using Python programming language

NASA Astrophysics Data System (ADS)

Tiwari, Varun; Kumar, Vinay; Pandey, Kamal; Ranade, Rigved; Agarwal, Shefali

2016-04-01

Multispectral remote sensing (MRS) sensors have proved their potential in acquiring and retrieving information of Land Use Land (LULC) Cover features in the past few decades. These MRS sensor generally acquire data within limited broad spectral bands i.e. ranging from 3 to 10 number of bands. The limited number of bands and broad spectral bandwidth in MRS sensors becomes a limitation in detailed LULC studies as it is not capable of distinguishing spectrally similar LULC features. On the counterpart, fascinating detailed information available in hyperspectral (HRS) data is spectrally over determined and able to distinguish spectrally similar material of the earth surface. But presently the availability of HRS sensors is limited. This is because of the requirement of sensitive detectors and large storage capability, which makes the acquisition and processing cumbersome and exorbitant. So, there arises a need to utilize the available MRS data for detailed LULC studies. Spectral reconstruction approach is one of the technique used for simulating hyperspectral data from available multispectral data. In the present study, spectral reconstruction approach is utilized for the simulation of hyperspectral data using EO-1 ALI multispectral data. The technique is implemented using python programming language which is open source in nature and possess support for advanced imaging processing libraries and utilities. Over all 70 bands have been simulated and validated using visual interpretation, statistical and classification approach.

Laboratory Spectroscopy of Astrophysically-Relevant Materials: Developing Dust as a Diagnostic

NASA Technical Reports Server (NTRS)

Rinehart, Stephen A.

2010-01-01

Over forty years ago, observations in the new field of infrared astronomy showed a broad spectral feature at 10 microns; the feature was quickly associated with the presence of silicate-rich dust. Since that time, improvements in infrared astronomy have led to the discovery of a plethora of additional spectral features attributable to dust. By combining these observations with spectroscopic data acquired in the laboratory, astronomers have a diagnostic tool that can be used to explore underlying astronomical phenomena. As the laboratory data improves, so does our ability to interpret the astronomical observations. Here, we discuss some recent progress in laboratory spectroscopy and attempt to identify future research directions.

Color heterogeneity of the surface of Phobos - Relationships to geologic features and comparison to meteorite analogs

NASA Technical Reports Server (NTRS)

Murchie, Scott L.; Britt, Daniel T.; Head, James W.; Pratt, Stephen F.; Fisher, Paul C.

1991-01-01

Color ratio images created from multispectral observations of Phobos are analyzed in order to characterize the spectral properties of Phobos' surface, to assess their spatial distributions and relationships with geologic features, and to compare Phobos' surface materials with possible meteorite analogs. Data calibration and processing is briefly discussed, and the observed spectral properties of Phobos and their lateral variations are examined. Attention is then given to the color properties of different types of impact craters, the origin of lateral variations in surface color, the relation between the spatial distribution of color properties and independently identifiable geologic features, and the relevance of color variation spatial distribution to the origin of the grooves.

Laboratory experiments on carbonaceous material as a source for the red rectangle visual emissions

NASA Technical Reports Server (NTRS)

Wdowiak, Thomas J.; Donn, Bertram; Nuth, Joseph A.; Chappelle, Emmett; Moore, Marla

1989-01-01

The authors subjected mixtures of CO, Ar, N2, H2O, and CH4 with 42 percent and 8 percent argon to an electrical discharge, froze out the reaction products at T about 20 K, and subsequently warmed the sample to room temperature. This resulted in a stable residue having broad-band fluorescence. It is suggested tht interstellar grains in the Red Rectangle/HD 44179 are coated with a residue of generally similar composition that is responsible for the broad emission feature in the 5400-7500 A spectral region.

Origin of Vibrational Spectroscopic Response at Ice Surface.

PubMed

Ishiyama, Tatsuya; Takahashi, Hideaki; Morita, Akihiro

2012-10-18

Since the basal plane surface of ice was first observed by sum frequency generation, an extraordinarily intense band for the hydrogen(H)-bonded OH stretching vibration has been a matter of debate. We elucidate the remarkable spectral feature of the ice surface by quantum mechanics/molecular mechanics calculations. The intense H-bonded band is originated mostly from the "bilayer-stitching" modes of a few surface bilayers, through significant intermolecular charge transfer. The mechanism of enhanced signal is sensitive to the order of the tetrahedral ice structure, as the charge transfer is coupled to the vibrational delocalization.

Preliminary results on an H-alpha map of the Gum nebula obtained with the D-z-A satellite

NASA Technical Reports Server (NTRS)

Blamont, J. E.; Levasseur, A. C.

1971-01-01

Hydrogen emissions, including telluric H alpha, in the terrestrial atmosphere were studied. The H alpha experiment was designed to use a monochromatic photometer that would provide measurements of weak H alpha emission originating at altitudes of a few hundred or thousand km, free of contamination by other telluric emissions. The Gum nebula was recorded by the instrument as a much more intense feature than the geocoronal emission. The spacecraft employed and the optical onboard equipment are described. Field of view, spectral response, absolute calibration, linearity, and inflight performance are discussed.

First-Order Parametric Model of Reflectance Spectra for Dyed Fabrics

DTIC Science & Technology

2016-02-19

Unclassified Unlimited 31 Daniel Aiken (202) 279-5293 Parametric modeling Inverse /direct analysis This report describes a first-order parametric model of...Appendix: Dielectric Response Functions for Dyes Obtained by Inverse Analysis ……………………………...…………………………………………………….19 1 First-Order Parametric...which provides for both their inverse and direct modeling1. The dyes considered contain spectral features that are of interest to the U.S. Navy for

Self-injection-locking linewidth narrowing in a semiconductor laser coupled to an external fiber-optic ring resonator

NASA Astrophysics Data System (ADS)

Korobko, Dmitry A.; Zolotovskii, Igor O.; Panajotov, Krassimir; Spirin, Vasily V.; Fotiadi, Andrei A.

2017-12-01

We develop a theoretical framework for modeling of semiconductor laser coupled to an external fiber-optic ring resonator. The developed approach has shown good qualitative agreement between theoretical predictions and experimental results for particular configuration of a self-injection locked DFB laser delivering narrow-band radiation. The model is capable of describing the main features of the experimentally measured laser outputs such as laser line narrowing, spectral shape of generated radiation, mode-hoping instabilities and makes possible exploring the key physical mechanisms responsible for the laser operation stability.

UV Spectroscopy of Lucy Mission Targets

NASA Astrophysics Data System (ADS)

Thomas, Cristina

2017-08-01

The Trojan asteroids are a significant population of primitive bodies trapped in Jupiter's stable L4 and L5 Lagrange regions. Their physical properties and existence in these particular orbits constrain the chemical and dynamical processes in our early Solar System. NASA's recently selected Lucy mission will perform the first reconnaissance of these asteroids and will answer many fundamental questions about the population. The compositions of the Trojans are not well understood. Spectroscopy and spectrophotometry in visible and near-infrared wavelengths show red slopes (spectra with reflectivity increasing towards the long wavelength end of the spectrum) and no diagnostic spectral absorption features. However, past spectral and photometric observations suggest there are unobserved features in ultraviolet wavelengths. We propose to obtain ultraviolet spectroscopy with WFC3 of four Trojan asteroids that are targets of the Lucy mission. Lucy will not have the capability to obtain ultraviolet spectra. The proposed observations can only be made using Hubble. We will determine if there are UV spectral features, as suggested by visible wavelength observations, and connect these features to candidate compositional components. These observations will enable connections between the compositions of Trojans and dynamical models of the early Solar System.

Can the bump in the composite spectrum of GRB 910503 be an emission line feature of gamma-ray bursts?

NASA Astrophysics Data System (ADS)

Qin, Yi-Ping; Zhang, Fu-Wen

2005-12-01

Appearing in the composite spectral data of BATSE, EGRET and COMPTEL for GRB 910503, there is a bump at around 1600 keV. We perform a statistical analysis on the spectral data, trying to find out if the bump could be accounted for by a blue-shifted and significantly broadened rest frame line due to the Doppler effect of an expanding fireball surface. We made an F-test and adopted previously proposed criteria. The study reveals that the criteria are well satisfied and the feature can be interpreted as the blue shifted 6.4 keV line. From the fit with this line taken into account, we find the Lorentz factor of this source to be Γ = 116+9-9 (at the 68% confident level, triangleχ2 = 1) and the rest frame spectral peak energy to be E0,p = 2.96+0.24-0.18 keV. Although the existence of the emission line feature requires other independent tests to confirm, the analysis suggests that it is feasible to detect emission line features in the high energy range of GRB spectra when taking into account the Doppler effect of fireball expansion.

CHARACTERIZATION OF CRYPTOSPORIDIUM PARVUM BY MATRIX-ASSISTED LASER DESORPTION -- IONIZATION TIME OF FLIGHT MASS SPECTROMETRY

EPA Science Inventory

Matrix assisted laser desorption/ionization (MALDI) mass spectrometry was used to investigate whole and freeze thawed Cryptosporidium parvum oocysts. Whole oocysts revealed some mass spectral features. Reproducible patterns of spectral markers and increased sensitivity were obtai...

The U. S. Geological Survey, Digital Spectral Library: Version 1 (0.2 to 3.0um)

USGS Publications Warehouse

Clark, Roger N.; Swayze, Gregg A.; Gallagher, Andrea J.; King, Trude V.V.; Calvin, Wendy M.

1993-01-01

We have developed a digital reflectance spectral library, with management and spectral analysis software. The library includes 498 spectra of 444 samples (some samples include a series of grain sizes) measured from approximately 0.2 to 3.0 um . The spectral resolution (Full Width Half Maximum) of the reflectance data is <= 4 nm in the visible (0.2-0.8 um) and <= 10 nm in the NIR (0.8-2.35 um). All spectra were corrected to absolute reflectance using an NIST Halon standard. Library management software lets users search on parameters (e.g. chemical formulae, chemical analyses, purity of samples, mineral groups, etc.) as well as spectral features. Minerals from borate, carbonate, chloride, element, halide, hydroxide, nitrate, oxide, phosphate, sulfate, sulfide, sulfosalt, and the silicate (cyclosilicate, inosilicate, nesosilicate, phyllosilicate, sorosilicate, and tectosilicate) classes are represented. X-Ray and chemical analyses are tabulated for many of the entries, and all samples have been evaluated for spectral purity. The library also contains end and intermediate members for the olivine, garnet, scapolite, montmorillonite, muscovite, jarosite, and alunite solid-solution series. We have included representative spectra of H2O ice, kerogen, ammonium-bearing minerals, rare-earth oxides, desert varnish coatings, kaolinite crystallinity series, kaolinite-smectite series, zeolite series, and an extensive evaporite series. Because of the importance of vegetation to climate-change studies we have include 17 spectra of tree leaves, bushes, and grasses. The library and software are available as a series of U.S.G.S. Open File reports. PC user software is available to convert the binary data to ascii files (a separate U.S.G.S. open file report). Additionally, a binary data files are on line at the U.S.G.S. in Denver for anonymous ftp to users on the Internet. The library search software enables a user to search on documentation parameters as well as spectral features. The analysis system includes general spectral analysis routines, plotting packages, radiative transfer software for computing intimate mixtures, routines to derive optical constants from reflectance spectra, tools to analyze spectral features, and the capability to access imaging spectrometer data cubes for spectral analysis. Users may build customized libraries (at specific wavelengths and spectral resolution) for their own instruments using the library software. We are currently extending spectral coverage to 150 um. The libraries (original and convolved) will be made available in the future on a CD-ROM.

Emotion Recognition from Single-Trial EEG Based on Kernel Fisher's Emotion Pattern and Imbalanced Quasiconformal Kernel Support Vector Machine

PubMed Central

Liu, Yi-Hung; Wu, Chien-Te; Cheng, Wei-Teng; Hsiao, Yu-Tsung; Chen, Po-Ming; Teng, Jyh-Tong

2014-01-01

Electroencephalogram-based emotion recognition (EEG-ER) has received increasing attention in the fields of health care, affective computing, and brain-computer interface (BCI). However, satisfactory ER performance within a bi-dimensional and non-discrete emotional space using single-trial EEG data remains a challenging task. To address this issue, we propose a three-layer scheme for single-trial EEG-ER. In the first layer, a set of spectral powers of different EEG frequency bands are extracted from multi-channel single-trial EEG signals. In the second layer, the kernel Fisher's discriminant analysis method is applied to further extract features with better discrimination ability from the EEG spectral powers. The feature vector produced by layer 2 is called a kernel Fisher's emotion pattern (KFEP), and is sent into layer 3 for further classification where the proposed imbalanced quasiconformal kernel support vector machine (IQK-SVM) serves as the emotion classifier. The outputs of the three layer EEG-ER system include labels of emotional valence and arousal. Furthermore, to collect effective training and testing datasets for the current EEG-ER system, we also use an emotion-induction paradigm in which a set of pictures selected from the International Affective Picture System (IAPS) are employed as emotion induction stimuli. The performance of the proposed three-layer solution is compared with that of other EEG spectral power-based features and emotion classifiers. Results on 10 healthy participants indicate that the proposed KFEP feature performs better than other spectral power features, and IQK-SVM outperforms traditional SVM in terms of the EEG-ER accuracy. Our findings also show that the proposed EEG-ER scheme achieves the highest classification accuracies of valence (82.68%) and arousal (84.79%) among all testing methods. PMID:25061837

A decision support system for automatic sleep staging from EEG signals using tunable Q-factor wavelet transform and spectral features.

PubMed

Hassan, Ahnaf Rashik; Bhuiyan, Mohammed Imamul Hassan

2016-09-15

Automatic sleep scoring is essential owing to the fact that conventionally a large volume of data have to be analyzed visually by the physicians which is onerous, time-consuming and error-prone. Therefore, there is a dire need of an automated sleep staging scheme. In this work, we decompose sleep-EEG signal segments using tunable-Q factor wavelet transform (TQWT). Various spectral features are then computed from TQWT sub-bands. The performance of spectral features in the TQWT domain has been determined by intuitive and graphical analyses, statistical validation, and Fisher criteria. Random forest is used to perform classification. Optimal choices and the effects of TQWT and random forest parameters have been determined and expounded. Experimental outcomes manifest the efficacy of our feature generation scheme in terms of p-values of ANOVA analysis and Fisher criteria. The proposed scheme yields 90.38%, 91.50%, 92.11%, 94.80%, 97.50% for 6-stage to 2-stage classification of sleep states on the benchmark Sleep-EDF data-set. In addition, its performance on DREAMS Subjects Data-set is also promising. The performance of the proposed method is significantly better than the existing ones in terms of accuracy and Cohen's kappa coefficient. Additionally, the proposed scheme gives high detection accuracy for sleep stages non-REM 1 and REM. Spectral features in the TQWT domain can discriminate sleep-EEG signals corresponding to various sleep states efficaciously. The proposed scheme will alleviate the burden of the physicians, speed-up sleep disorder diagnosis, and expedite sleep research. Copyright © 2016 Elsevier B.V. All rights reserved.

Emotion recognition from single-trial EEG based on kernel Fisher's emotion pattern and imbalanced quasiconformal kernel support vector machine.

PubMed

Liu, Yi-Hung; Wu, Chien-Te; Cheng, Wei-Teng; Hsiao, Yu-Tsung; Chen, Po-Ming; Teng, Jyh-Tong

2014-07-24

Electroencephalogram-based emotion recognition (EEG-ER) has received increasing attention in the fields of health care, affective computing, and brain-computer interface (BCI). However, satisfactory ER performance within a bi-dimensional and non-discrete emotional space using single-trial EEG data remains a challenging task. To address this issue, we propose a three-layer scheme for single-trial EEG-ER. In the first layer, a set of spectral powers of different EEG frequency bands are extracted from multi-channel single-trial EEG signals. In the second layer, the kernel Fisher's discriminant analysis method is applied to further extract features with better discrimination ability from the EEG spectral powers. The feature vector produced by layer 2 is called a kernel Fisher's emotion pattern (KFEP), and is sent into layer 3 for further classification where the proposed imbalanced quasiconformal kernel support vector machine (IQK-SVM) serves as the emotion classifier. The outputs of the three layer EEG-ER system include labels of emotional valence and arousal. Furthermore, to collect effective training and testing datasets for the current EEG-ER system, we also use an emotion-induction paradigm in which a set of pictures selected from the International Affective Picture System (IAPS) are employed as emotion induction stimuli. The performance of the proposed three-layer solution is compared with that of other EEG spectral power-based features and emotion classifiers. Results on 10 healthy participants indicate that the proposed KFEP feature performs better than other spectral power features, and IQK-SVM outperforms traditional SVM in terms of the EEG-ER accuracy. Our findings also show that the proposed EEG-ER scheme achieves the highest classification accuracies of valence (82.68%) and arousal (84.79%) among all testing methods.

Quantitative characterization of crude oils and fuels in mineral substrates using reflectance spectroscopy: Implications for remote sensing

NASA Astrophysics Data System (ADS)

Scafutto, Rebecca Del'Papa Moreira; Souza Filho, Carlos Roberto de

2016-08-01

The near and shortwave infrared spectral reflectance properties of several mineral substrates impregnated with crude oils (°APIs 19.2, 27.5 and 43.2), diesel, gasoline and ethanol were measured and assembled in a spectral library. These data were examined using Principal Component Analysis (PCA) and Partial Least Squares (PLS) Regression. Unique and characteristic absorption features were identified in the mixtures, besides variations of the spectral signatures related to the compositional difference of the crude oils and fuels. These features were used for qualitative and quantitative determination of the contaminant impregnated in the substrates. Specific wavelengths, where key absorption bands occur, were used for the individual characterization of oils and fuels. The intensity of these features can be correlated to the abundance of the contaminant in the mixtures. Grain size and composition of the impregnated substrate directly influence the variation of the spectral signatures. PCA models applied to the spectral library proved able to differentiate the type and density of the hydrocarbons. The calibration models generated by PLS are robust, of high quality and can also be used to predict the concentration of oils and fuels in mixtures with mineral substrates. Such data and models are employable as a reference for classifying unknown samples of contaminated substrates. The results of this study have important implications for onshore exploration and environmental monitoring of oil and fuels leaks using proximal and far range multispectral, hyperspectral and ultraespectral remote sensing.

Infrared (2.08-14 micron) spectra of powered stony meteorites

NASA Technical Reports Server (NTRS)

Salisbury, J. W.; Daria, D. M.; Jarosewich, E.

1991-01-01

Infrared biconical reflectance spectra of 60 powdered meteorite samples, representing 50 different stony meteorites, were measured as analogues of asteroidal regolith. Representative samples were measured in directional hemispherical reflectance to assure that Kirchhoff's Law can be used to predict relative emissivity from the reflectance spectra. These spectral data confirm that the O-H fundamental absorption band near 2.9 microns is an extremely sensitive indicator of incipient alteration, which often has taken place in powdered meteorite samples exposed only to water vapor in the air. Such non-carbonaceous samples typically contain less than 1 percent water by weight. Likewise, the C-H fundamental absorption bands near 3.4 and 3.5 microns are equally sensitive indicators of contamination with volatile hydrocarbons, which can also be absorbed from the air. The heavy, macromolecular hydrocarbons native to chondrites do not display such heavy bands, making detection of these bands in remote sensing of asteroids unlikely. Despite the spectral artifacts introduced by alteration and hydrocarbon contamination, powdered stony meteorites display a wide variety of real spectral features that can be used for their identification, including residual reststrahlen bands, absorption bands, and the Christiansen feature. Researchers found that the wavelengths of the peaks or troughs of each of these spectral features can be used independently to infer meteorite composition, but the best results are obtained when the entire spectral curve is used, or at least the portion of it encompassed by the 8 to 14 micron atmospheric window, in a digital search library.

Critical Seismic Vector Random Excitations for Multiply Supported Structures

NASA Astrophysics Data System (ADS)

Sarkar, A.; Manohar, C. S.

1998-05-01

A method for determining critical power spectral density matrix models for earthquake excitations which maximize steady response variance of linear multiply supported extended structures and which also satisfy constraints on input variance, zero crossing rates, frequency content and transmission time lag has been developed. The optimization problem is shown to be non-linear in nature and solutions are obtained by using an iterative technique which is based on linear programming method. A constraint on entropy rate as a measure of uncertainty which can be expected in realistic earthquake ground motions is proposed which makes the critical excitations more realistic. Two special cases are also considered. Firstly, when knowledge of autospectral densities is available, the critical response is shown to be produced by fully coherent excitations which are neither in-phase nor out-of-phase. The critical phase between the excitation components depends on structural parameters, but independent of the auto-spectral densities of the excitations. Secondly, when the knowledge of autospectral densities and phase spectrum of the excitations is available, the critical response is shown to be produced by a system dependent coherence function representing neither fully coherent nor fully incoherent ground motions. The applications of these special cases are discussed in the context of land-based extended structures and secondary systems such as nuclear piping assembly. Illustrative examples on critical inputs and response of sdof and a long-span suspended cable which demonstrated the various features of the approach developed are presented.

Mapped minerals at Questa, New Mexico, using airborne visible-infrared imaging spectrometer (AVIRIS) data -- Preliminary report

USGS Publications Warehouse

Livo, K. Eric; Clark, Roger N.

2002-01-01

This preliminary study for the First Quarterly Report has spectrally mapped hydrothermally altered minerals useful in assisting in assessment of water quality of the Red River. Airborne Visible-Infrared Imaging Spectrometer (AVIRIS) data was analyzed to characterize mined and unmined ground at Questa, New Mexico. AVIRIS data covers the Red River drainage north of the river, from between the town of Questa on the west, to east of the town of Red River. The data was calibrated and analyzed using U.S. Geological Survey custom software and spectral mineral library. AVIRIS data was tested for spectral features that matched similar features in the spectral mineral library. Goodness-of-fit and band-depth were calculated for each comparison of spectral features and used to identify surface mineralogy. Mineral distribution, mineral associations, and AVIRIS pixel spectra were examined. Mineral maps show the distribution of iron hydroxides, iron sulfates, clays, micas, carbonates, and other minerals. Initial results show a system of alteration suites that overprint each other. Quartz-sericite-pyrite (QSP) alteration grading out to propylitic alteration (epidote and calcite) was identified at the Questa Mine (molybdenum porphyry) and a similar alteration pattern was mapped at the landslide (?scar?) areas. Supergene weathering overprints the altered rock, as shown by jarosite, kaolinite, and gypsum. In the spectral analysis, hydrothermally altered ground appears to be more extensive at the unmined Goat Hill Gulch and the mined ground, than the ?scars? to the east. Though the ?scars? have similar overall altered mineral suites, there are differences between the ?scars? in sericite, kaolinite, jarosite, gypsum, and calcite abundance. Fieldwork has verified the results at the central unmined ?scar? areas.

Identification of spectral phenotypes in age-related macular degeneration patients

NASA Astrophysics Data System (ADS)

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

2007-02-01

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

Controller design and consonantal contrast coding using a multi-finger tactual display1

PubMed Central

Israr, Ali; Meckl, Peter H.; Reed, Charlotte M.; Tan, Hong Z.

2009-01-01

This paper presents the design and evaluation of a new controller for a multi-finger tactual display in speech communication. A two-degree-of-freedom controller consisting of a feedback controller and a prefilter and its application in a consonant contrasting experiment are presented. The feedback controller provides stable, fast, and robust response of the fingerpad interface and the prefilter shapes the frequency-response of the closed-loop system to match with the human detection-threshold function. The controller is subsequently used in a speech communication system that extracts spectral features from recorded speech signals and presents them as vibrational-motional waveforms to three digits on a receiver’s left hand. Performance from a consonantal contrast test suggests that participants are able to identify tactual cues necessary for discriminating consonants in the initial position of consonant-vowel-consonant (CVC) segments. The average sensitivity indices for contrasting voicing, place, and manner features are 3.5, 2.7, and 3.4, respectively. The results show that the consonantal features can be successfully transmitted by utilizing a broad range of the kinesthetic-cutaneous sensory system. The present study also demonstrates the validity of designing controllers that take into account not only the electromechanical properties of the hardware, but the sensory characteristics of the human user. PMID:19507975

Arrhythmia Mechanism and Scaling Effect on the Spectral Properties of Electroanatomical Maps With Manifold Harmonics.

PubMed

Sanroman-Junquera, Margarita; Mora-Jimenez, Inmaculada; Garcia-Alberola, Arcadio; Caamano, Antonio J; Trenor, Beatriz; Rojo-Alvarez, Jose L

2018-04-01

Spatial and temporal processing of intracardiac electrograms provides relevant information to support the arrhythmia ablation during electrophysiological studies. Current cardiac navigation systems (CNS) and electrocardiographic imaging (ECGI) build detailed 3-D electroanatomical maps (EAM), which represent the spatial anatomical distribution of bioelectrical features, such as activation time or voltage. We present a principled methodology for spectral analysis of both EAM geometry and bioelectrical feature in CNS or ECGI, including their spectral representation, cutoff frequency, or spatial sampling rate (SSR). Existing manifold harmonic techniques for spectral mesh analysis are adapted to account for a fourth dimension, corresponding to the EAM bioelectrical feature. Appropriate scaling is required to address different magnitudes and units. With our approach, simulated and real EAM showed strong SSR dependence on both the arrhythmia mechanism and the cardiac anatomical shape. For instance, high frequencies increased significantly the SSR because of the "early-meets-late" in flutter EAM, compared with the sinus rhythm. Besides, higher frequency components were obtained for the left atrium (more complex anatomy) than for the right atrium in sinus rhythm. The proposed manifold harmonics methodology opens the field toward new signal processing tools for principled EAM spatiofeature analysis in CNS and ECGI, and to an improved knowledge on arrhythmia mechanisms.

Fluorescence and reflectance properties of hemoglobin-pigmented skin disorders

NASA Astrophysics Data System (ADS)

Troyanova, P.; Borisova, E.; Avramov, L.

2007-06-01

There has been growing interest in clinical application of laser-induced autofluorescence (LIAF) and reflectance spectroscopy (RS) to differentiate disease from normal surrounding tissue, including skin pathologies. Pigmented cutaneous lesions diagnosis plays important role in clinical practice, as malignant melanoma, which is characterized with greatest mortality from all skin cancer types, must be carefully discriminated form other colorized pathologies. The goals of this work were investigation of cutaneous hemoglobin-pigmented lesions (heamangioma, angiokeratoma, and fibroma) by the methods of LIAFS and RS. Spectra from healthy skin areas near to the lesion were detected to be used posteriori in analysis. Fluorescence and reflectance of cutaneous hemoglobin-pigmented lesions are used to develop criterion for differentiation from other pigmented pathologies. Origins of the spectral features obtained are discussed and determination of lesion types is achieved using selected spectral features. The spectral results, obtained were used to develop multispectral diagnostic algorithms based on the most prominent spectral features from the fluorescence and reflectance spectra of the lesions investigated. In comparison between normal skin and different cutaneous lesion types and between lesion types themselves sensitivities and specificities higher than 90 % were achieved. These results show a perspective possibility to differentiate hemoglobin-pigmented lesions from other pigmented pathologies using non-invasive and real time discrimination procedure.

Near-infrared spectral image analysis of pork marbling based on Gabor filter and wide line detector techniques.

PubMed

Huang, Hui; Liu, Li; Ngadi, Michael O; Gariépy, Claude; Prasher, Shiv O

2014-01-01

Marbling is an important quality attribute of pork. Detection of pork marbling usually involves subjective scoring, which raises the efficiency costs to the processor. In this study, the ability to predict pork marbling using near-infrared (NIR) hyperspectral imaging (900-1700 nm) and the proper image processing techniques were studied. Near-infrared images were collected from pork after marbling evaluation according to current standard chart from the National Pork Producers Council. Image analysis techniques-Gabor filter, wide line detector, and spectral averaging-were applied to extract texture, line, and spectral features, respectively, from NIR images of pork. Samples were grouped into calibration and validation sets. Wavelength selection was performed on calibration set by stepwise regression procedure. Prediction models of pork marbling scores were built using multiple linear regressions based on derivatives of mean spectra and line features at key wavelengths. The results showed that the derivatives of both texture and spectral features produced good results, with correlation coefficients of validation of 0.90 and 0.86, respectively, using wavelengths of 961, 1186, and 1220 nm. The results revealed the great potential of the Gabor filter for analyzing NIR images of pork for the effective and efficient objective evaluation of pork marbling.

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

[Bare Soil Moisture Inversion Model Based on Visible-Shortwave Infrared Reflectance].

PubMed

Zheng, Xiao-po; Sun, Yue-jun; Qin, Qi-ming; Ren, Hua-zhong; Gao, Zhong-ling; Wu, Ling; Meng, Qing-ye; Wang, Jin-liang; Wang, Jian-hua

2015-08-01

Soil is the loose solum of land surface that can support plants. It consists of minerals, organics, atmosphere, moisture, microbes, et al. Among its complex compositions, soil moisture varies greatly. Therefore, the fast and accurate inversion of soil moisture by using remote sensing is very crucial. In order to reduce the influence of soil type on the retrieval of soil moisture, this paper proposed a normalized spectral slope and absorption index named NSSAI to estimate soil moisture. The modeling of the new index contains several key steps: Firstly, soil samples with different moisture level were artificially prepared, and soil reflectance spectra was consequently measured using spectroradiometer produced by ASD Company. Secondly, the moisture absorption spectral feature located at shortwave wavelengths and the spectral slope of visible wavelengths were calculated after analyzing the regular spectral feature change patterns of different soil at different moisture conditions. Then advantages of the two features at reducing soil types' effects was synthesized to build the NSSAI. Thirdly, a linear relationship between NSSAI and soil moisture was established. The result showed that NSSAI worked better (correlation coefficient is 0.93) than most of other traditional methods in soil moisture extraction. It can weaken the influences caused by soil types at different moisture levels and improve the bare soil moisture inversion accuracy.

Pulsed eddy current differential probe to detect the defects in a stainless steel pipe

NASA Astrophysics Data System (ADS)

Angani, C. S.; Park, D. G.; Kim, C. G.; Leela, P.; Kishore, M.; Cheong, Y. M.

2011-04-01

Pulsed eddy current (PEC) is an electromagnetic nondestructive technique widely used to detect and quantify the flaws in conducting materials. In the present study a differential Hall-sensor probe which is used in the PEC system has been fabricated for the detection of defects in stainless steel pipelines. The differential probe has an exciting coil with two Hall-sensors. A stainless steel test sample with electrical discharge machining (EDM) notches under different depths of 1-5 mm was made and the sample was laminated by plastic insulation having uniform thickness to simulate the pipelines in nuclear power plants (NPPs). The driving coil in the probe is excited by a rectangular current pulse and the resultant response, which is the difference of the two Hall-sensors, has been detected as the PEC probe signal. The discriminating time domain features of the detected pulse such as peak value and time to zero are used to interpret the experimental results with the defects in the test sample. A feature extraction technique such as spectral power density has been devised to infer the PEC response.

Investigations of vibrational spectra and bioactivity of novel anticancer drug N-(6-ferrocenyl-2-naphthoyl)-gamma-amino butyric acid ethyl ester

NASA Astrophysics Data System (ADS)

Sudhi, Geethu; Rajina, S. R.; Praveen, S. G.; Xavier, T. S.; Kenny, Peter T. M.; Jaiswal-Nagar, D.; Binoy, J.

2017-10-01

The bioactivity of compounds is mainly dependent on molecular structure and the present work aims to explore the bonding features responsible for biological activity of novel anticancer drug N-(6-ferrocenyl-2-naphthoyl)-gamma-amino butyric acid ethyl ester (FNGABEE). In the present study, we investigate the molecular structural properties of newly synthesized title compound through experimental and quantum chemical studies. The detailed vibrational analysis has been performed using FT IR and FT Raman spectrum, aided by DFT computed geometry, vibrational spectrum, Eigen vector distribution and PED, at B3LYP/6-311 ++G(d,p) level. The resonance structure of naphthalene, different from that of benzene, revealed by molecular structure has been investigated using Csbnd C and Cdbnd C stretching modes. The proton transfer in amide has been analyzed to obtain spectral distinction between different carbonyl and Csbnd N groups which point to the reactive sites responsible for binding with DNA and bovine serum albumin (BSA). The spectral distinction between eclipsed and staggered form of ferrocene has been analyzed. The molecular docking of FNGABEE with BSA and DNA has been performed to find the strength of binding and the moieties responsible for the interactions. The experimental binding studies of FNGABEE with BSA and DNA has been performed using UV absorption spectroscopy and fluorometric assay, to find the nature and strength of binding.

Spectral response of healthy and damaged leaves of tropical seagrass Enhalus acoroides, Thalassia hemprichii, and Cymodocea rotundata

NASA Astrophysics Data System (ADS)

Wicaksono, Pramaditya; Kamal, Muhammad

2017-10-01

Characterization of seagrass spectral reflectance response is important to understand seagrass condition and for the possibility of mapping activities using remote sensing data, which is important for the management, monitoring, and evaluation of seagrass ecosystem. This paper presents the spectral reflectance response of several tropical seagrass species. These species are Enhalus acoroides (Ea), Thalassia hemprichii (Th) and Cymodocea rotundata (Cr). Spectral reflectance response of healthy seagrass, epiphyte-covered seagrass, and damaged seagrass leaves for each species were measured using Jaz EL-350 field spectrometer ranged from 350 - 1100 nm. Repeated measurements were performed above water on harvested seagrass leaves. The results indicate that there is a change in spectral reflectance response of damaged or epiphyte-covered seagrass leaves compared to the healthy leaves. The results show similar pattern for the three species, where the peak reflectance in visible wavelengths shifted toward longer wavelengths on damaged seagrass leaves. The results of this research open up a possibility of mapping seagrass health condition using remote sensing image.

Raman Spectral Signatures as Conformational Probes of Biomolecules

NASA Astrophysics Data System (ADS)

Golan, Amir; Mayorkas, Nitzan; Rosenwaks, Salman; Bar, Ilana

2009-06-01

A first application of ionization-loss stimulated Raman spectroscopy (ILSRS) for monitoring the spectral features of four conformers of a gas phase neurotransmitter (2-phenylethylamine) is reported. The Raman spectra of the conformers show bands that uniquely identify the conformational structure of the molecule and are well matched by density functional theory calculations. The measurement of spectral signatures by ILSRS in an extended spectral range, with a relatively convenient laser source, is extremely important, allowing enhanced accessibility to intra- and inter-molecular forces, which are significant in biological structure and activity.

Raman Spectral Signatures as Conformational Probes of Biomolecules

NASA Astrophysics Data System (ADS)

Bar, Ilana; Golan, Amir; Mayorkas, Nitzan; Rosenwaks, Salman

2009-03-01

A first application of ionization-loss stimulated Raman spectroscopy (ILSRS) monitoring the spectral features of four conformers of a gas phase neurotransmitter (2-phenylethylamine) is reported. The Raman spectra of the conformers show bands that uniquely identify the conformational structure of the molecule and are well matched by density functional theory calculations. The measurement of spectral signatures by ILSRS in an extended spectral range, with a relatively convenient laser source, is extremely important, allowing enhanced accessibility to intra- and inter-molecular forces, which are significant in biological structure and activity.

SDP_mharwit_1: Demonstration of HIFI Linear Polarization Analysis of Spectral Features

NASA Astrophysics Data System (ADS)

Harwit, M.

2010-03-01

We propose to observe the polarization of the 621 GHz water vapor maser in VY Canis Majoris to demonstrate the capability of HIFI to make polarization observations of Far-Infrared/Submillimeter spectral lines. The proposed Demonstration Phase would: - Show that HIFI is capable of interesting linear polarization measurements of spectral lines; - Test out the highest spectral resolving power to sort out closely spaced Doppler components; - Determine whether the relative intensities predicted by Neufeld and Melnick are correct; - Record the degree and direction of linear polarization for the closely-Doppler shifted peaks.

Observational aspects of outbursting black hole sources: Evolution of spectro-temporal features and X-ray variability

NASA Astrophysics Data System (ADS)

Sreehari, H.; Nandi, Anuj; Radhika, D.; Iyer, Nirmal; Mandal, Samir

2018-02-01

We report on our attempt to understand the outbursting profile of Galactic Black Hole sources, keeping in mind the evolution of temporal and spectral features during the outburst. We present results of evolution of quasi-periodic oscillations, spectral states and possible connection with jet ejections during the outburst phase. Further, we attempt to connect the observed X-ray variabilities (i.e., `class'/`structured' variabilities, similar to GRS 1915+105) with spectral states of black hole sources. Towards these studies, we consider three black hole sources that have undergone single (XTE J1859+226), a few (IGR J17091-3624) and many (GX 339-4) outbursts since the start of RXTE era. Finally, we model the broadband energy spectra (3-150 keV) of different spectral states using RXTE and NuSTAR observations. Results are discussed in the context of two-component advective flow model, while constraining the mass of the three black hole sources.

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

NASA Astrophysics Data System (ADS)

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

2016-10-01

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

A Comparison of Raman Spectral Features of Frozen and Deparaffinized Tissues in Neuroblastoma and Ganglioneuroma

NASA Astrophysics Data System (ADS)

Devpura, Suneetha; Thakur, Jagdish S.; Poulik, Janet M.; Rabah, Raja; Naik, Vaman M.; Naik, Ratna

2012-02-01

We have investigated the cellular regions in neuroblastoma and ganglioneuroma using Raman spectroscopy and compared their spectral characteristics with those of normal adrenal gland. Thin sections from both frozen and deparaffinized tissues, obtained from the same tissue specimen, were studied in conjunction with the pathological examination of the tissues. We found a significant difference in the spectral features of frozen sections of normal adrenal gland, neuroblastoma, and ganglioneuroma when compared to deparaffinized tissues. The quantitative analysis of the Raman data using chemometric methods of principal component analysis and discriminant function analysis obtained from the frozen tissues show a sensitivity and specificity of 100% each. The biochemical identification based on the spectral differences shows that the normal adrenal gland tissues have higher levels of carotenoids, lipids, and cholesterol compared to the neuroblastoma and ganglioneuroma frozen tissues. However, deparaffinized tissues show complete removal of these biochemicals in adrenal tissues. This study demonstrates that Raman spectroscopy combined with chemometric methods can successfully distinguish neuroblastoma and ganglioneuroma at cellular level.

Influence of magnetism and correlation on the spectral properties of doped Mott insulators

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

Wang, Yao; Moritz, Brian; Chen, Cheng-Chien

Unraveling the nature of the doping-induced transition between a Mott insulator and a weakly correlated metal is crucial to understanding novel emergent phases in strongly correlated materials. Here, for this purpose, we study the evolution of spectral properties upon doping Mott insulating states by utilizing the cluster perturbation theory on the Hubbard and t – J -like models. Specifically, a quasifree dispersion crossing the Fermi level develops with small doping, and it eventually evolves into the most dominant feature at high doping levels. Although this dispersion is related to the free-electron hopping, our study shows that this spectral feature is,more » in fact, influenced inherently by both electron-electron correlation and spin-exchange interaction: the correlation destroys coherence, while the coupling between spin and mobile charge restores it in the photoemission spectrum. Due to the persistent impact of correlations and spin physics, the onset of gaps or the high-energy anomaly in the spectral functions can be expected in doped Mott insulators.« less

Influence of magnetism and correlation on the spectral properties of doped Mott insulators

DOE PAGES

Wang, Yao; Moritz, Brian; Chen, Cheng-Chien; ...

2018-03-01

Unraveling the nature of the doping-induced transition between a Mott insulator and a weakly correlated metal is crucial to understanding novel emergent phases in strongly correlated materials. Here, for this purpose, we study the evolution of spectral properties upon doping Mott insulating states by utilizing the cluster perturbation theory on the Hubbard and t – J -like models. Specifically, a quasifree dispersion crossing the Fermi level develops with small doping, and it eventually evolves into the most dominant feature at high doping levels. Although this dispersion is related to the free-electron hopping, our study shows that this spectral feature is,more » in fact, influenced inherently by both electron-electron correlation and spin-exchange interaction: the correlation destroys coherence, while the coupling between spin and mobile charge restores it in the photoemission spectrum. Due to the persistent impact of correlations and spin physics, the onset of gaps or the high-energy anomaly in the spectral functions can be expected in doped Mott insulators.« less

The outburst decay of the low magnetic field magnetar SWIFT J1822.3-1606: phase-resolved analysis and evidence for a variable cyclotron feature

NASA Astrophysics Data System (ADS)

Rodríguez Castillo, Guillermo A.; Israel, Gian Luca; Tiengo, Andrea; Salvetti, David; Turolla, Roberto; Zane, Silvia; Rea, Nanda; Esposito, Paolo; Mereghetti, Sandro; Perna, Rosalba; Stella, Luigi; Pons, José A.; Campana, Sergio; Götz, Diego; Motta, Sara

2016-03-01

We study the timing and spectral properties of the low-magnetic field, transient magnetar SWIFT J1822.3-1606 as it approached quiescence. We coherently phase-connect the observations over a time-span of ˜500 d since the discovery of SWIFT J1822.3-1606 following the Swift-Burst Alert Telescope (BAT) trigger on 2011 July 14, and carried out a detailed pulse phase spectroscopy along the outburst decay. We follow the spectral evolution of different pulse phase intervals and find a phase and energy-variable spectral feature, which we interpret as proton cyclotron resonant scattering of soft photon from currents circulating in a strong (≳1014 G) small-scale component of the magnetic field near the neutron star surface, superimposed to the much weaker (˜3 × 1013 G) magnetic field. We discuss also the implications of the pulse-resolved spectral analysis for the emission regions on the surface of the cooling magnetar.

M dwarf spectra from 0.6 to 1.5 micron - A spectral sequence, model atmosphere fitting, and the temperature scale

NASA Technical Reports Server (NTRS)

Kirkpatrick, J. D.; Kelly, Douglas M.; Rieke, George H.; Liebert, James; Allard, France; Wehrse, Rainer

1993-01-01

Red/infrared (0.6-1.5 micron) spectra are presented for a sequence of well-studied M dwarfs ranging from M2 through M9. A variety of temperature-sensitive features useful for spectral classification are identified. Using these features, the spectral data are compared to recent theoretical models, from which a temperature scale is assigned. The red portion of the model spectra provide reasonably good fits for dwarfs earlier than M6. For layer types, the infrared region provides a more reliable fit to the observations. In each case, the wavelength region used includes the broad peak of the energy distribution. For a given spectral type, the derived temperature sequence assigns higher temperatures than have earlier studies - the difference becoming more pronounced at lower luminosities. The positions of M dwarfs on the H-R diagram are, as a result, in closer agreement with theoretical tracks of the lower main sequence.

Spectral Regression Based Fault Feature Extraction for Bearing Accelerometer Sensor Signals

PubMed Central

Xia, Zhanguo; Xia, Shixiong; Wan, Ling; Cai, Shiyu

2012-01-01

Bearings are not only the most important element but also a common source of failures in rotary machinery. Bearing fault prognosis technology has been receiving more and more attention recently, in particular because it plays an increasingly important role in avoiding the occurrence of accidents. Therein, fault feature extraction (FFE) of bearing accelerometer sensor signals is essential to highlight representative features of bearing conditions for machinery fault diagnosis and prognosis. This paper proposes a spectral regression (SR)-based approach for fault feature extraction from original features including time, frequency and time-frequency domain features of bearing accelerometer sensor signals. SR is a novel regression framework for efficient regularized subspace learning and feature extraction technology, and it uses the least squares method to obtain the best projection direction, rather than computing the density matrix of features, so it also has the advantage in dimensionality reduction. The effectiveness of the SR-based method is validated experimentally by applying the acquired vibration signals data to bearings. The experimental results indicate that SR can reduce the computation cost and preserve more structure information about different bearing faults and severities, and it is demonstrated that the proposed feature extraction scheme has an advantage over other similar approaches. PMID:23202017

Time Resolved Spectroscopy, High Sensitivity Power Spectrum & a Search for the X-Ray QPO in NGC 5548

NASA Astrophysics Data System (ADS)

Yaqoob, Tahir

1999-09-01

Controversy surrounds the EXOSAT discovery of a QPO (period ~500 s) in NGC 5548 due to the data being plagued by high background and instrumental systematics. If the NGC 5548 QPO is real, the implications for the physics of the X-ray emission mechanism and inner-most disk/black-hole system are enormous. AXAF provides the first opportunity to settle the issue, capable of yielding power spectra with unprecedented sensitivity, pushing the limit on finding new features. Using HETG/ACIS we will also perform time-resolved spectroscopy of the ionized absorption features and Fe-K emission line, search for energy-dependent time lags in the continuum, between the continuum and spectral features, and between the spectral features. These data will provide powerful constraints on models of AGN.

Angle-resolved Auger electron spectra induced by neon ion impact on aluminum

NASA Technical Reports Server (NTRS)

Pepper, S. V.; Aron, P. R.

1986-01-01

Auger electron emission from aluminum bombarded with 1 to 5 keV neon ions was studied by angle-resolved electron spectroscopy. The position and shape of the spectral features depended on the incident ion energy, angle of ion incidence, and electron take-off angle with respect to the aluminum surface. These spectral dependencies were interpreted in terms of the Doppler shift given to the Auger electron velocity by the excited atom ejected into the vacuum. For oblique ion incidence it is concluded that a flux of high energy atoms are ejected in a direction close to the projection of the ion beam on the target surface. In addition, a new spectral feature was found and identified as due to Auger emission from excited neon in the aluminum matrix.

Acousto-optic infrared spectral imager for Pluto fast flyby

NASA Technical Reports Server (NTRS)

Glenar, D. A.; Hillman, J. J.

1993-01-01

Acousto-optic tunable filters (AOTF's) enable the design of compact, two-dimensional imaging spectrometers with high spectral and spatial resolution and with no moving parts. Tellurium dioxide AOTF's operate from about 400 nm to nearly 5 microns, and a single device will tune continuously over one octave by changing the RF acoustic frequency applied to the device. An infrared (1.2-2.5 micron) Acousto-Optic Imaging Spectrometer (AImS) was designed that closely conforms to the surface composition mapping objectives of the Pluto Fast Flyby. It features a 75-cm focal length telescope, infrared AOTF, and 256 x 256 NICMOS-3 focal plane array for acquiring narrowband images with a spectral resolving power (lambda/delta(lambda)) exceeding 250. We summarize the instrument design features and its expected performance at the Pluto-Charon encounter.

hyperspectral characterization of tissue simulating phantoms using a supercontinuum laser in a spatial frequency domain imaging instrument

NASA Astrophysics Data System (ADS)

Torabzadeh, Mohammad; Stockton, Patrick; Kennedy, Gordon T.; Saager, Rolf B.; Durkin, Anthony J.; Bartels, Randy A.; Tromberg, Bruce J.

2018-02-01

Hyperspectral Imaging (HSI) is a growing field in tissue optics due to its ability to collect continuous spectral features of a sample without a contact probe. Spatial Frequency Domain Imaging (SFDI) is a non-contact wide-field spectral imaging technique that is used to quantitatively characterize tissue structure and chromophore concentration. In this study, we designed a Hyperspectral SFDI (H-SFDI) instrument which integrated a supercontinuum laser source to a wavelength tuning optical configuration and a sCMOS camera to extract spatial (Field of View: 2cm×2cm) and broadband spectral features (580nm-950nm). A preliminary experiment was also performed to integrate the hyperspectral projection unit to a compressed single pixel camera and Light Labeling (LiLa) technique.

Wavelet Based Characterization of Low Radio Frequency Solar Emissions

NASA Astrophysics Data System (ADS)

Suresh, A.; Sharma, R.; Das, S. B.; Oberoi, D.; Pankratius, V.; Lonsdale, C.

2016-12-01

Low-frequency solar radio observations with the Murchison Widefield Array (MWA) have revealed the presence of numerous short-lived, narrow-band weak radio features, even during quiet solar conditions. In their appearance in in the frequency-time plane, they come closest to the solar type III bursts, but with much shorter spectral spans and flux densities, so much so that they are not detectable with the usual swept frequency radio spectrographs. These features occur at rates of many thousand features per hour in the 30.72 MHz MWA bandwidth, and hence necessarily require an automated approach to determine robust statistical estimates of their properties, e.g., distributions of spectral widths, temporal spans, flux densities, slopes in the time-frequency plane and distribution over frequency. To achieve this, a wavelet decomposition approach has been developed for feature recognition and subsequent parameter extraction from the MWA dynamic spectrum. This work builds on earlier work by the members of this team to achieve a reliable flux calibration in a computationally efficient manner. Preliminary results show that the distribution of spectral span of these features peaks around 3 MHz, most of them last for less than two seconds and are characterized by flux densities of about 60% of the background solar emission. In analogy with the solar type III bursts, this non-thermal emission is envisaged to arise via coherent emission processes. There is also an exciting possibility that these features might correspond to radio signatures of nanoflares, hypothesized (Gold, 1964; Parker, 1972) to explain coronal heating.

Probing the 9.7 μm Interstellar Silicate Extinction Profile through the Spitzer/IRS Spectroscopy of OB Stars

NASA Astrophysics Data System (ADS)

Shao, Zhenzhen; Jiang, B. W.; Li, Aigen; Gao, Jian; Lv, Zhangpan; Yao, Jiawen

2018-05-01

The 9.7 μm interstellar spectral feature, arising from the Si-O stretch of amorphous silicate dust, is the strongest extinction feature in the infrared (IR). In principle, the spectral profile of this feature could allow one to diagnose the mineralogical composition of interstellar silicate material. However, observationally, the 9.7 μm interstellar silicate extinction profile is not well determined. Here we utilize the Spitzer/IRS spectra of five early-type (one O- and four B-type) stars and compare them with that of unreddened stars of the same spectral type to probe the interstellar extinction of silicate dust around 9.7 μm. We find that, while the silicate extinction profiles all peak at ˜ 9.7 μm, two stars exhibit a narrow feature of FWHM ˜ 2.0 μm and three stars display a broad feature of FWHM ˜ 3.0 μm. We also find that the width of the 9.7 μm extinction feature does not show any environmental dependence. With a FWHM of ˜ 2.2 μm, the mean 9.7 μm extinction profile, obtained by averaging over our five stars, closely resembles that of the prototypical diffuse interstellar medium along the lines of sight toward Cyg OB2 No. 12 and WR 98a. Finally, an analytical formula is presented to parameterize the interstellar extinction in the IR at 0.9 μm ≲ λ ≲ 15 μm.

Estimation of canopy carotenoid content of winter wheat using multi-angle hyperspectral data

NASA Astrophysics Data System (ADS)

Kong, Weiping; Huang, Wenjiang; Liu, Jiangui; Chen, Pengfei; Qin, Qiming; Ye, Huichun; Peng, Dailiang; Dong, Yingying; Mortimer, A. Hugh

2017-11-01

Precise estimation of carotenoid (Car) content in crops, using remote sensing data, could be helpful for agricultural resources management. Conventional methods for Car content estimation were mostly based on reflectance data acquired from nadir direction. However, reflectance acquired at this direction is highly influenced by canopy structure and soil background reflectance. Off-nadir observation is less impacted, and multi-angle viewing data are proven to contain additional information rarely exploited for crop Car content estimation. The objective of this study was to explore the potential of multi-angle observation data for winter wheat canopy Car content estimation. Canopy spectral reflectance was measured from nadir as well as from a series of off-nadir directions during different growing stages of winter wheat, with concurrent canopy Car content measurements. Correlation analyses were performed between Car content and the original and continuum removed spectral reflectance. Spectral features and previously published indices were derived from data obtained at different viewing angles and were tested for Car content estimation. Results showed that spectral features and indices obtained from backscattering directions between 20° and 40° view zenith angle had a stronger correlation with Car content than that from the nadir direction, and the strongest correlation was observed from about 30° backscattering direction. Spectral absorption depth at 500 nm derived from spectral data obtained from 30° backscattering direction was found to reduce the difference induced by plant cultivars greatly. It was the most suitable for winter wheat canopy Car estimation, with a coefficient of determination 0.79 and a root mean square error of 19.03 mg/m2. This work indicates the importance of taking viewing geometry effect into account when using spectral features/indices and provides new insight in the application of multi-angle remote sensing for the estimation of crop physiology.

Type II Supernova Spectral Diversity. I. Observations, Sample Characterization, and Spectral Line Evolution

NASA Astrophysics Data System (ADS)

Gutiérrez, Claudia P.; Anderson, Joseph P.; Hamuy, Mario; Morrell, Nidia; González-Gaitan, Santiago; Stritzinger, Maximilian D.; Phillips, Mark M.; Galbany, Lluis; Folatelli, Gastón; Dessart, Luc; Contreras, Carlos; Della Valle, Massimo; Freedman, Wendy L.; Hsiao, Eric Y.; Krisciunas, Kevin; Madore, Barry F.; Maza, José; Suntzeff, Nicholas B.; Prieto, Jose Luis; González, Luis; Cappellaro, Enrico; Navarrete, Mauricio; Pizzella, Alessandro; Ruiz, Maria T.; Smith, R. Chris; Turatto, Massimo

2017-11-01

We present 888 visual-wavelength spectra of 122 nearby type II supernovae (SNe II) obtained between 1986 and 2009, and ranging between 3 and 363 days post-explosion. In this first paper, we outline our observations and data reduction techniques, together with a characterization based on the spectral diversity of SNe II. A statistical analysis of the spectral matching technique is discussed as an alternative to nondetection constraints for estimating SN explosion epochs. The time evolution of spectral lines is presented and analyzed in terms of how this differs for SNe of different photometric, spectral, and environmental properties: velocities, pseudo-equivalent widths, decline rates, magnitudes, time durations, and environment metallicity. Our sample displays a large range in ejecta expansion velocities, from ˜9600 to ˜1500 km s-1 at 50 days post-explosion with a median {{{H}}}α value of 7300 km s-1. This is most likely explained through differing explosion energies. Significant diversity is also observed in the absolute strength of spectral lines, characterized through their pseudo-equivalent widths. This implies significant diversity in both temperature evolution (linked to progenitor radius) and progenitor metallicity between different SNe II. Around 60% of our sample shows an extra absorption component on the blue side of the {{{H}}}α P-Cygni profile (“Cachito” feature) between 7 and 120 days since explosion. Studying the nature of Cachito, we conclude that these features at early times (before ˜35 days) are associated with Si II λ 6355, while past the middle of the plateau phase they are related to high velocity (HV) features of hydrogen lines. This paper includes data gathered with the 6.5 m Magellan Telescopes located at Las Campanas Observatory, Chile; and the Gemini Observatory, Cerro Pachon, Chile (Gemini Program GS-2008B-Q-56). Based on observations collected at the European Organisation for Astronomical Research in the Southern Hemisphere, Chile (ESO Programs 076.A-0156, 078.D-0048, 080.A-0516, and 082.A-0526).

Single-hole spectral function and spin-charge separation in the t-J model

NASA Astrophysics Data System (ADS)

Mishchenko, A. S.; Prokof'ev, N. V.; Svistunov, B. V.

2001-07-01

Worm algorithm Monte Carlo simulations of the hole Green function with subsequent spectral analysis were performed for 0.1<=J/t<=0.4 on lattices with up to L×L=32×32 sites at a temperature as low as T=J/40, and present, apparently, the hole spectral function in the thermodynamic limit. Spectral analysis reveals a δ-function-sharp quasiparticle peak at the lower edge of the spectrum that is incompatible with the power-law singularity and thus rules out the possibility of spin-charge separation in this parameter range. Spectral continuum features two peaks separated by a gap ~4÷5 t.

Ground-truthing AVIRIS mineral mapping at Cuprite, Nevada

NASA Technical Reports Server (NTRS)

Swayze, Gregg; Clark, Roger N.; Kruse, Fred; Sutley, Steve; Gallagher, Andrea

1992-01-01

Mineral abundance maps of 18 minerals were made of the Cuprite Mining District using 1990 AVIRIS data and the Multiple Spectral Feature Mapping Algorithm (MSFMA) as discussed in Clark et al. This technique uses least-squares fitting between a scaled laboratory reference spectrum and ground calibrated AVIRIS data for each pixel. Multiple spectral features can be fitted for each mineral and an unlimited number of minerals can be mapped simultaneously. Quality of fit and depth from continuum numbers for each mineral are calculated for each pixel and the results displayed as a multicolor image.

Urban, Forest, and Agricultural AIS Data: Fine Spectral Structure

NASA Technical Reports Server (NTRS)

Vanderbilt, V. C.

1985-01-01

Spectra acquired by the Airborne Imaging Spectrometer (AIS) near Lafayette, IN, Ely, MN, and over the Stanford University campus, CA were analyzed for fine spectral structure using two techniques: the ratio of radiance of a ground target to the radiance of a standard and also the correlation coefficient of radiances at adjacent wavelengths. The results show ramp like features in the ratios. These features are due to the biochemical composition of the leaf and to the optical scattering properties of its cuticle. The size and shape of the ramps vary with ground cover.

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

NASA Technical Reports Server (NTRS)

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

1989-01-01

We have discovered a new IR emission feature at 1905 cm-1 (5.25 microns) in the spectrum of BD +30 degrees 3639. This feature joins the family of well-known IR emission features at 3040, 2940, 1750, 1610, "1310," 1160, and 890 cm-1 (3.3, 3.4, 5.7, 6.2, "7.7," 8.6, and 11.2 microns). The origin of this new feature is discussed and it is assigned to an overtone or combination band involving C-H bending modes of polycyclic aromatic hydrocarbons (PAHs). Laboratory work suggests that spectral studies of the 2000-1650 cm-1 (5.0-6.1 microns) region may be very useful in elucidating the molecular structure of interstellar PAHs. The new feature, in conjunction with other recently discovered spectral structure, suggests that the narrow IR emission features originate in PAH molecules rather than large carbon grains. Larger species are likely to be the source of the broad underlying "plateaus" seen in many of the spectra.

EEG-based recognition of video-induced emotions: selecting subject-independent feature set.

PubMed

Kortelainen, Jukka; Seppänen, Tapio

2013-01-01

Emotions are fundamental for everyday life affecting our communication, learning, perception, and decision making. Including emotions into the human-computer interaction (HCI) could be seen as a significant step forward offering a great potential for developing advanced future technologies. While the electrical activity of the brain is affected by emotions, offers electroencephalogram (EEG) an interesting channel to improve the HCI. In this paper, the selection of subject-independent feature set for EEG-based emotion recognition is studied. We investigate the effect of different feature sets in classifying person's arousal and valence while watching videos with emotional content. The classification performance is optimized by applying a sequential forward floating search algorithm for feature selection. The best classification rate (65.1% for arousal and 63.0% for valence) is obtained with a feature set containing power spectral features from the frequency band of 1-32 Hz. The proposed approach substantially improves the classification rate reported in the literature. In future, further analysis of the video-induced EEG changes including the topographical differences in the spectral features is needed.

A minimum drives automatic target definition procedure for multi-axis random control testing

NASA Astrophysics Data System (ADS)

Musella, Umberto; D'Elia, Giacomo; Carrella, Alex; Peeters, Bart; Mucchi, Emiliano; Marulo, Francesco; Guillaume, Patrick

2018-07-01

Multiple-Input Multiple-Output (MIMO) vibration control tests are able to closely replicate, via shakers excitation, the vibration environment that a structure needs to withstand during its operational life. This feature is fundamental to accurately verify the experienced stress state, and ultimately the fatigue life, of the tested structure. In case of MIMO random tests, the control target is a full reference Spectral Density Matrix in the frequency band of interest. The diagonal terms are the Power Spectral Densities (PSDs), representative for the acceleration operational levels, and the off-diagonal terms are the Cross Spectral Densities (CSDs). The specifications of random vibration tests are however often given in terms of PSDs only, coming from a legacy of single axis testing. Information about the CSDs is often missing. An accurate definition of the CSD profiles can further enhance the MIMO random testing practice, as these terms influence both the responses and the shaker's voltages (the so-called drives). The challenges are linked to the algebraic constraint that the full reference matrix must be positive semi-definite in the entire bandwidth, with no flexibility in modifying the given PSDs. This paper proposes a newly developed method that automatically provides the full reference matrix without modifying the PSDs, considered as test specifications. The innovative feature is the capability of minimizing the drives required to match the reference PSDs and, at the same time, to directly guarantee that the obtained full matrix is positive semi-definite. The drives minimization aims on one hand to reach the fixed test specifications without stressing the delicate excitation system; on the other hand it potentially allows to further increase the test levels. The detailed analytic derivation and implementation steps of the proposed method are followed by real-life testing considering different scenarios.

A Massive Shell of Supernova-Formed Dust in SNR G54.1+0.3

NASA Technical Reports Server (NTRS)

Temim, Tea; Dwek, Eli; Arendt, Richard G.; Borkowski, Kazimiera J.; Reynolds, Stephen P.; Slane, Patrick; Gelfand, Joseph D.; Raymond, John C.

2017-01-01

While theoretical models of dust condensation predict that most refractory elements produced in core-collapsesupernovae (SNe) efficiently condense into dust, a large quantity of dust has so far only been observed inSN1987A. We present an analysis of observations from the Spitzer Space Telescope, Herschel SpaceObservatory, Stratospheric Observatory for Infrared Astronomy, and AKARI of the infrared shell surrounding thepulsar wind nebula in the supernova remnant G54.1+0.3. We attribute a distinctive spectral feature at 21 m to amagnesium silicate grain species that has been invoked in modeling the ejecta-condensed dust in Cas A, whichexhibits the same spectral signature. If this species is responsible for producing the observed spectral feature andaccounts for a significant fraction of the observed infrared continuum, we find that it would be the dominantconstituent of the dust in G54.1+0.3, with possible secondary contributions from other compositions, such ascarbon, silicate, or alumina grains. The total mass of SN-formed dust required by this model is at least 0.3Me. Wediscuss how these results may be affected by varying dust grain properties and self-consistent grain heating models.The spatial distribution of the dust mass and temperature in G54.1+0.3 confirms the scenario in which the SNformeddust has not yet been processed by the SN reverse shock and is being heated by stars belonging to a clusterin which the SN progenitor exploded. The dust mass and composition suggest a progenitor mass of 1627Me andimply a high dust condensation efficiency, similar to that found for Cas A and SN1987A. The study providesanother example of significant dust formation in a Type IIP SN explosion and sheds light on the properties ofpristine SN-condensed dust.

The MetOp second generation 3MI instrument

NASA Astrophysics Data System (ADS)

Manolis, Ilias; Grabarnik, Semen; Caron, Jérôme; Bézy, Jean-Loup; Loiselet, Marc; Betto, Maurizio; Barré, Hubert; Mason, Graeme; Meynart, Roland

2013-10-01

The MetOp-SG programme is a joint Programme of EUMETSAT and ESA. ESA develops the prototype MetOp-SG satellites (including associated instruments) and procures, on behalf of EUMETSAT, the recurrent satellites (and associated instruments). Two parallel, competitive phase A/B1 studies for MetOp Second Generation (MetOp-SG) have been concluded in May 2013. The implementation phases (B2/C/D/E) are planned to start the first quarter of 2014. ESA is responsible for instrument design of six missions, namely Microwave Sounding Mission (MWS), Scatterometer mission (SCA), Radio Occultation mission (RO), Microwave Imaging mission (MWI), Ice Cloud Imager (ICI) and Multi-viewing, Multi-channel, Multi-polarisation imaging mission (3MI). The paper will present the main performances of the 3MI instrument and will highlight the performance improvements with respect to its heritage derived by the POLDER instrument, such as number of spectral channels and spectral range coverage, swath and ground spatial resolution. The engineering of some key performance requirements (multi-viewing, polarisation sensitivity, straylight etc.) will also be discussed. The results of the feasibility studies will be presented together with the programmatics for the instrument development. Several pre-development activities have been initiated to retire highest risks and to demonstrate the ultimate performances of the 3MI optics. The scope, objectives and current status of those activities will be presented. Key technologies involved in the 3MI instrument design and implementation are considered to be: the optical design featuring aspheric optics, the implementation of broadband Anti Reflection coatings featuring low polarisation and low de-phasing properties, the development and qualification of polarisers with acceptable performances as well as spectral filters with good uniformities over a large clear aperture.

Calibration of the ROSAT HRI Spectral Response

NASA Technical Reports Server (NTRS)

Prestwich, Andrea H.; Silverman, John; McDowell, Jonathan; Callanan, Paul; Snowden, Steve

2000-01-01

The ROSAT High Resolution Imager has a limited (2-band) spectral response. This spectral capability can give X-ray hardness ratios on spatial scales of 5 arcseconds. The spectral response of the center of the detector was calibrated before the launch of ROSAT, but the gain decreases with time and also is a function of position on the detector. To complicate matters further, the satellite is 'wobbled', possibly moving a source across several spatial gain states. These difficulties have prevented the spectral response of the ROSAT High Resolution Imager (HRI) from being used for scientific measurements. We have used Bright Earth data and in-flight calibration sources to map the spatial and temporal gain changes, and written software which will allow ROSAT users to generate a calibrated XSPEC (an x ray spectral fitting package) response matrix and hence determine a calibrated hardness ratio. In this report, we describe the calibration procedure and show how to obtain a response matrix. In Section 2 we give an overview of the calibration procedure, in Section 3 we give a summary of HRI spatial and temporal gain variations. Section 4 describes the routines used to determine the gain distribution of a source. In Sections 5 and 6, we describe in detail how, the Bright Earth database and calibration sources are used to derive a corrected response matrix for a given observation. Finally, Section 7 describes how to use the software.

Extension of laboratory-measured soil spectra to field conditions

NASA Technical Reports Server (NTRS)

Stoner, E. R.; Baumgardner, M. F.; Weismiller, R. A.; Biehl, L. L.; Robinson, B. F.

1982-01-01

Spectral responses of two glaciated soils, Chalmers silty clay loam and Fincastle silt loam, formed under prairie grass and forest vegetation, respectively, were measured in the laboratory under controlled moisture equilibria using an Exotech Model 20C spectroradiometer to obtain spectral data in the laboratory under artificial illumination. The same spectroradiometer was used outdoors under solar illumination to obtain spectral response from dry and moistened field plots with and without corn residue cover, representing the two different soils. Results indicate that laboratory-measured spectra of moist soil are directly proportional to the spectral response of that same field-measured moist bare soil over the 0.52 micrometer to 1.75 micrometer wavelength range. The magnitudes of difference in spectral response between identically treated Chalmers and Fincastle soils are greatest in the 0.6 micrometers to 0.8 micrometer transition region between the visible and near infrared, regardless of field condition or laboratory preparation studied.

Extracting scene feature vectors through modeling, volume 3

NASA Technical Reports Server (NTRS)

Berry, J. K.; Smith, J. A.

1976-01-01

The remote estimation of the leaf area index of winter wheat at Finney County, Kansas was studied. The procedure developed consists of three activities: (1) field measurements; (2) model simulations; and (3) response classifications. The first activity is designed to identify model input parameters and develop a model evaluation data set. A stochastic plant canopy reflectance model is employed to simulate reflectance in the LANDSAT bands as a function of leaf area index for two phenological stages. An atmospheric model is used to translate these surface reflectances into simulated satellite radiance. A divergence classifier determines the relative similarity between model derived spectral responses and those of areas with unknown leaf area index. The unknown areas are assigned the index associated with the closest model response. This research demonstrated that the SRVC canopy reflectance model is appropriate for wheat scenes and that broad categories of leaf area index can be inferred from the procedure developed.

EEG oscillations entrain their phase to high-level features of speech sound.

PubMed

Zoefel, Benedikt; VanRullen, Rufin

2016-01-01

Phase entrainment of neural oscillations, the brain's adjustment to rhythmic stimulation, is a central component in recent theories of speech comprehension: the alignment between brain oscillations and speech sound improves speech intelligibility. However, phase entrainment to everyday speech sound could also be explained by oscillations passively following the low-level periodicities (e.g., in sound amplitude and spectral content) of auditory stimulation-and not by an adjustment to the speech rhythm per se. Recently, using novel speech/noise mixture stimuli, we have shown that behavioral performance can entrain to speech sound even when high-level features (including phonetic information) are not accompanied by fluctuations in sound amplitude and spectral content. In the present study, we report that neural phase entrainment might underlie our behavioral findings. We observed phase-locking between electroencephalogram (EEG) and speech sound in response not only to original (unprocessed) speech but also to our constructed "high-level" speech/noise mixture stimuli. Phase entrainment to original speech and speech/noise sound did not differ in the degree of entrainment, but rather in the actual phase difference between EEG signal and sound. Phase entrainment was not abolished when speech/noise stimuli were presented in reverse (which disrupts semantic processing), indicating that acoustic (rather than linguistic) high-level features play a major role in the observed neural entrainment. Our results provide further evidence for phase entrainment as a potential mechanism underlying speech processing and segmentation, and for the involvement of high-level processes in the adjustment to the rhythm of speech. Copyright © 2015 Elsevier Inc. All rights reserved.

Development of Response Spectral Ground Motion Prediction Equations from Empirical Models for Fourier Spectra and Duration of Ground Motion

NASA Astrophysics Data System (ADS)

Bora, S. S.; Scherbaum, F.; Kuehn, N. M.; Stafford, P.; Edwards, B.

2014-12-01

In a probabilistic seismic hazard assessment (PSHA) framework, it still remains a challenge to adjust ground motion prediction equations (GMPEs) for application in different seismological environments. In this context, this study presents a complete framework for the development of a response spectral GMPE easily adjustable to different seismological conditions; and which does not suffer from the technical problems associated with the adjustment in response spectral domain. Essentially, the approach consists of an empirical FAS (Fourier Amplitude Spectrum) model and a duration model for ground motion which are combined within the random vibration theory (RVT) framework to obtain the full response spectral ordinates. Additionally, FAS corresponding to individual acceleration records are extrapolated beyond the frequency range defined by the data using the stochastic FAS model, obtained by inversion as described in Edwards & Faeh, (2013). To that end, an empirical model for a duration, which is tuned to optimize the fit between RVT based and observed response spectral ordinate, at each oscillator frequency is derived. Although, the main motive of the presented approach was to address the adjustability issues of response spectral GMPEs; comparison, of median predicted response spectra with the other regional models indicate that presented approach can also be used as a stand-alone model. Besides that, a significantly lower aleatory variability (σ<0.5 in log units) in comparison to other regional models, at shorter periods brands it to a potentially viable alternative to the classical regression (on response spectral ordinates) based GMPEs for seismic hazard studies in the near future. The dataset used for the presented analysis is a subset of the recently compiled database RESORCE-2012 across Europe, Middle East and the Mediterranean region.

Tunable Fano resonance using weak-value amplification with asymmetric spectral response as a natural pointer

NASA Astrophysics Data System (ADS)

Singh, Ankit K.; Ray, Subir K.; Chandel, Shubham; Pal, Semanti; Gupta, Angad; Mitra, P.; Ghosh, N.

2018-05-01

Weak measurement enables faithful amplification and high-precision measurement of small physical parameters and is under intensive investigation as an effective tool in metrology and for addressing foundational questions in quantum mechanics. Here we demonstrate weak-value amplification using the asymmetric spectral response of Fano resonance as the pointer arising naturally in precisely designed metamaterials, namely, waveguided plasmonic crystals. The weak coupling between the polarization degree of freedom and the spectral response of Fano resonance arises due to a tiny shift in the asymmetric spectral response between two orthogonal linear polarizations. By choosing the preselected and postselected polarization states to be nearly mutually orthogonal, we observe both real and imaginary weak-value amplifications manifested as a spectacular shift of the Fano-resonance peak and narrowing (or broadening) of the resonance linewidth, respectively. The remarkable control and tunability of Fano resonance in a single device enabled by weak-value amplification may enhance active Fano-resonance-based applications in the nano-optical domain. In general, weak measurements using Fano-type spectral response broadens the domain of applicability of weak measurements using natural spectral line shapes as a pointer in a wide range of physical systems.

FPA-FTIR Microspectroscopy for Monitoring Chemotherapy Efficacy in Triple-Negative Breast Cancer

NASA Astrophysics Data System (ADS)

Zawlik, Izabela; Kaznowska, Ewa; Cebulski, Jozef; Kolodziej, Magdalena; Depciuch, Joanna; Vongsvivut, Jitraporn; Cholewa, Marian

2016-11-01

Triple-negative breast cancer is the most aggressive breast cancer subtype with limited treatment options and a poor prognosis. Approximately 70% of triple-negative breast cancer patients fail to achieve a pathologic complete response (pCR) after chemotherapy due to the lack of targeted therapies for this subtype. We report here the development of a focal-plane-array Fourier transform infrared (FPA-FTIR) microspectroscopic technique combined with principal component analysis (PCA) for monitoring chemotherapy effects in triple-negative breast cancer patients. The PCA results obtained using the FPA-FTIR spectral data collected from the same patients before and after the chemotherapy revealed discriminatory features that were consistent with the pathologic and clinical responses to chemotherapy, indicating the potential of the technique as a monitoring tool for observing chemotherapy efficacy.

Pattern recognition and image processing for environmental monitoring

NASA Astrophysics Data System (ADS)

Siddiqui, Khalid J.; Eastwood, DeLyle

1999-12-01

Pattern recognition (PR) and signal/image processing methods are among the most powerful tools currently available for noninvasively examining spectroscopic and other chemical data for environmental monitoring. Using spectral data, these systems have found a variety of applications employing analytical techniques for chemometrics such as gas chromatography, fluorescence spectroscopy, etc. An advantage of PR approaches is that they make no a prior assumption regarding the structure of the patterns. However, a majority of these systems rely on human judgment for parameter selection and classification. A PR problem is considered as a composite of four subproblems: pattern acquisition, feature extraction, feature selection, and pattern classification. One of the basic issues in PR approaches is to determine and measure the features useful for successful classification. Selection of features that contain the most discriminatory information is important because the cost of pattern classification is directly related to the number of features used in the decision rules. The state of the spectral techniques as applied to environmental monitoring is reviewed. A spectral pattern classification system combining the above components and automatic decision-theoretic approaches for classification is developed. It is shown how such a system can be used for analysis of large data sets, warehousing, and interpretation. In a preliminary test, the classifier was used to classify synchronous UV-vis fluorescence spectra of relatively similar petroleum oils with reasonable success.

Land use and land cover classification for rural residential areas in China using soft-probability cascading of multifeatures

NASA Astrophysics Data System (ADS)

Zhang, Bin; Liu, Yueyan; Zhang, Zuyu; Shen, Yonglin

2017-10-01

A multifeature soft-probability cascading scheme to solve the problem of land use and land cover (LULC) classification using high-spatial-resolution images to map rural residential areas in China is proposed. The proposed method is used to build midlevel LULC features. Local features are frequently considered as low-level feature descriptors in a midlevel feature learning method. However, spectral and textural features, which are very effective low-level features, are neglected. The acquisition of the dictionary of sparse coding is unsupervised, and this phenomenon reduces the discriminative power of the midlevel feature. Thus, we propose to learn supervised features based on sparse coding, a support vector machine (SVM) classifier, and a conditional random field (CRF) model to utilize the different effective low-level features and improve the discriminability of midlevel feature descriptors. First, three kinds of typical low-level features, namely, dense scale-invariant feature transform, gray-level co-occurrence matrix, and spectral features, are extracted separately. Second, combined with sparse coding and the SVM classifier, the probabilities of the different LULC classes are inferred to build supervised feature descriptors. Finally, the CRF model, which consists of two parts: unary potential and pairwise potential, is employed to construct an LULC classification map. Experimental results show that the proposed classification scheme can achieve impressive performance when the total accuracy reached about 87%.

Models and methods to characterize site amplification from a pair of records

USGS Publications Warehouse

Safak, E.

1997-01-01

The paper presents a tutorial review of the models and methods that are used to characterize site amplification from the pairs of rock- and soil-site records, and introduces some new techniques with better theoretical foundations. The models and methods discussed include spectral and cross-spectral ratios, spectral ratios for downhole records, response spectral ratios, constant amplification factors, parametric models, physical models, and time-varying filters. An extensive analytical and numerical error analysis of spectral and cross-spectral ratios shows that probabilistically cross-spectral ratios give more reliable estimates of site amplification. Spectral ratios should not be used to determine site amplification from downhole-surface recording pairs because of the feedback in the downhole sensor. Response spectral ratios are appropriate for low frequencies, but overestimate the amplification at high frequencies. The best method to be used depends on how much precision is required in the estimates.

Imaging spectroscopy: Earth and planetary remote sensing with the USGS Tetracorder and expert systems

USGS Publications Warehouse

Clark, Roger N.; Swayze, Gregg A.; Livo, K. Eric; Kokaly, Raymond F.; Sutley, Steve J.; Dalton, J. Brad; McDougal, Robert R.; Gent, Carol A.

2003-01-01

Imaging spectroscopy is a tool that can be used to spectrally identify and spatially map materials based on their specific chemical bonds. Spectroscopic analysis requires significantly more sophistication than has been employed in conventional broadband remote sensing analysis. We describe a new system that is effective at material identification and mapping: a set of algorithms within an expert system decision‐making framework that we call Tetracorder. The expertise in the system has been derived from scientific knowledge of spectral identification. The expert system rules are implemented in a decision tree where multiple algorithms are applied to spectral analysis, additional expert rules and algorithms can be applied based on initial results, and more decisions are made until spectral analysis is complete. Because certain spectral features are indicative of specific chemical bonds in materials, the system can accurately identify and map those materials. In this paper we describe the framework of the decision making process used for spectral identification, describe specific spectral feature analysis algorithms, and give examples of what analyses and types of maps are possible with imaging spectroscopy data. We also present the expert system rules that describe which diagnostic spectral features are used in the decision making process for a set of spectra of minerals and other common materials. We demonstrate the applications of Tetracorder to identify and map surface minerals, to detect sources of acid rock drainage, and to map vegetation species, ice, melting snow, water, and water pollution, all with one set of expert system rules. Mineral mapping can aid in geologic mapping and fault detection and can provide a better understanding of weathering, mineralization, hydrothermal alteration, and other geologic processes. Environmental site assessment, such as mapping source areas of acid mine drainage, has resulted in the acceleration of site cleanup, saving millions of dollars and years in cleanup time. Imaging spectroscopy data and Tetracorder analysis can be used to study both terrestrial and planetary science problems. Imaging spectroscopy can be used to probe planetary systems, including their atmospheres, oceans, and land surfaces.

[Spectral features analysis of Pinus massoniana with pest of Dendrolimus punctatus Walker and levels detection].

PubMed

Xu, Zhang-Hua; Liu, Jian; Yu, Kun-Yong; Gong, Cong-Hong; Xie, Wan-Jun; Tang, Meng-Ya; Lai, Ri-Wen; Li, Zeng-Lu

2013-02-01

Taking 51 field measured hyperspectral data with different pest levels in Yanping, Fujian Province as objects, the spectral reflectance and first derivative features of 4 levels of healthy, mild, moderate and severe insect pest were analyzed. On the basis of 7 detecting parameters construction, the pest level detecting models were built. The results showed that (1) the spectral reflectance of Pinus massoniana with pests were significantly lower than that of healthy state, and the higher the pest level, the lower the reflectance; (2) with the increase in pest level, the spectral reflectance curves' "green peak" and "red valley" of Pinus massoniana gradually disappeared, and the red edge was leveleds (3) the pest led to spectral "green peak" red shift, red edge position blue shift, but the changes in "red valley" and near-infrared position were complicated; (4) CARI, RES, REA and REDVI were highly relevant to pest levels, and the correlations between REP, RERVI, RENDVI and pest level were weak; (5) the multiple linear regression model with the variables of the 7 detection parameters could effectively detect the pest levels of Dendrolimus punctatus Walker, with both the estimation rate and accuracy above 0.85.