UNTANGLING THE NEAR-IR SPECTRAL FEATURES IN THE PROTOPLANETARY ENVIRONMENT OF KH 15D

Energy Technology Data Exchange (ETDEWEB)

Arulanantham, Nicole A.; Herbst, William; Gilmore, Martha S.; Cauley, P. Wilson [Astronomy Department, Wesleyan University, Middletown, CT 06459 (United States); Leggett, S. K., E-mail: nicole.arulanantham@colorado.edu [Gemini Observatory (North), Hilo, HI 96720 (United States)

2017-01-10

We report on Gemini/GNIRS observations of the binary T Tauri system V582 Mon (KH 15D) at three orbital phases. These spectra allow us to untangle five components of the system: the photosphere and magnetosphere of star B, the jet, scattering properties of the ring material, and excess near-infrared (near-IR) radiation previously attributed to a possible self-luminous planet. We confirm an early-K subgiant classification for star B and show that the magnetospheric He i emission line is variable, possibly indicating increased mass accretion at certain times. As expected, the H{sub 2} emission features associated with the inner part of the jet show no variation with orbital phase. We show that the reflectance spectrum for the scattered light has a distinctive blue slope and spectral features consistent with scattering and absorption by a mixture of water and methane ice grains in the 1–50 μ m size range. This suggests that the methane frost line is closer than ∼5 au in this system, requiring that the grains be shielded from direct radiation. After correcting for features from the scattered light, jet, magnetosphere, and photosphere, we confirm the presence of leftover near-IR light from an additional source, detectable near minimum brightness. A spectral emission feature matching the model spectrum of a 10 M {sub J}, 1 Myr old planet is found in the excess flux, but other expected features from this model are not seen. Our observations, therefore, tentatively support the picture that a luminous planet is present within the system, although they cannot yet be considered definitive.

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

Science.gov (United States)

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.

Smoothing of Fused Spectral Consistent Satellite Images with TV-based Edge Detection

DEFF Research Database (Denmark)

Sveinsson, Johannes; Aanæs, Henrik; Benediktsson, Jon Atli

2007-01-01

based on satellite data. Additionally, most conventional methods are loosely connected to the image forming physics of the satellite image, giving these methods an ad hoc feel. Vesteinsson et al. [1] proposed a method of fusion of satellite images that is based on the properties of imaging physics...... in a statistically meaningful way and was called spectral consistent panshapening (SCP). In this paper we improve this framework for satellite image fusion by introducing a better image prior, via data-dependent image smoothing. The dependency is obtained via total variation edge detection method.......Several widely used methods have been proposed for fusing high resolution panchromatic data and lower resolution multi-channel data. However, many of these methods fail to maintain the spectral consistency of the fused high resolution image, which is of high importance to many of the applications...

Negative running of the spectral index, hemispherical asymmetry and the consistency of Planck with large r

International Nuclear Information System (INIS)

McDonald, John

2014-01-01

Planck favours a negative running of the spectral index, with the likelihood being dominated by low multipoles l ∼< 50 and no preference for running at higher l. A negative spectral index is also necessary for the 2- Planck upper bound on the tensor-to-scalar ratio r to be consistent with values significantly larger than 0.1. Planck has also observed a hemispherical asymmetry of the CMB power spectrum, again mostly at low multipoles. Here we consider whether the physics responsible for the hemispherical asymmetry could also account for the negative running of the spectral index and the consistency of Planck with a large value of r. A negative running of the spectral index can be generated if the hemispherical asymmetry is due to a scale- and space-dependent modulation which suppresses the CMB power spectrum at low multipoles. We show that the observed hemispherical asymmetry at low l can be generated while satisfying constraints on the asymmetry at higher l and generating a negative spectral index of the right magnitude to account for the Planck observation and to allow Planck to be consistent with a large value of r

Camouflaged target detection based on polarized spectral features

Science.gov (United States)

Tan, Jian; Zhang, Junping; Zou, Bin

2016-05-01

The polarized hyperspectral images (PHSI) include polarization, spectral, spatial and radiant features, which provide more information about objects and scenes than traditional intensity or spectrum ones. And polarization can suppress the background and highlight the object, leading to the high potential to improve camouflaged target detection. So polarized hyperspectral imaging technique has aroused extensive concern in the last few years. Nowadays, the detection methods are still not very mature, most of which are rooted in the detection of hyperspectral image. And before using these algorithms, Stokes vector is used to process the original four-dimensional polarized hyperspectral data firstly. However, when the data is large and complex, the amount of calculation and error will increase. In this paper, tensor is applied to reconstruct the original four-dimensional data into new three-dimensional data, then, the constraint energy minimization (CEM) is used to process the new data, which adds the polarization information to construct the polarized spectral filter operator and takes full advantages of spectral and polarized information. This way deals with the original data without extracting the Stokes vector, so as to reduce the computation and error greatly. The experimental results also show that the proposed method in this paper is more suitable for the target detection of the PHSI.

Digital mammography: Mixed feature neural network with spectral entropy decision for detection of microcalcifications

Energy Technology Data Exchange (ETDEWEB)

Zheng, B. [Univ. of South Florida, Tampa, FL (United States)]|[Nanjing Univ. of Posts and Telecommunications (China). Dept. of Telecommunication Engineering; Qian, W.; Clarke, L.P. [Univ. of South Florida, Tampa, FL (United States)

1996-10-01

A computationally efficient mixed feature based neural network (MFNN) is proposed for the detection of microcalcification clusters (MCC`s) in digitized mammograms. The MFNN employs features computed in both the spatial and spectral domain and uses spectral entropy as a decision parameter. Backpropagation with Kalman Filtering (KF) is employed to allow more efficient network training as required for evaluation of different features, input images, and related error analysis. A previously reported, wavelet-based image-enhancement method is also employed to enhance microcalcification clusters for improved detection. The relative performance of the MFNN for both the raw and enhanced images is evaluated using a common image database of 30 digitized mammograms, with 20 images containing 21 biopsy proven MCC`s and ten normal cases. The computed sensitivity (true positive (TP) detection rate) was 90.1% with an average low false positive (FP) detection of 0.71 MCCs/image for the enhanced images using a modified k-fold validation error estimation technique. The corresponding computed sensitivity for the raw images was reduced to 81.4% and with 0.59 FP`s MCCs/image. A relative comparison to an earlier neural network (NN) design, using only spatially related features, suggests the importance of the addition of spectral domain features when the raw image data are analyzed.

Digital mammography: Mixed feature neural network with spectral entropy decision for detection of microcalcifications

International Nuclear Information System (INIS)

Zheng, B.

1996-01-01

A computationally efficient mixed feature based neural network (MFNN) is proposed for the detection of microcalcification clusters (MCC's) in digitized mammograms. The MFNN employs features computed in both the spatial and spectral domain and uses spectral entropy as a decision parameter. Backpropagation with Kalman Filtering (KF) is employed to allow more efficient network training as required for evaluation of different features, input images, and related error analysis. A previously reported, wavelet-based image-enhancement method is also employed to enhance microcalcification clusters for improved detection. The relative performance of the MFNN for both the raw and enhanced images is evaluated using a common image database of 30 digitized mammograms, with 20 images containing 21 biopsy proven MCC's and ten normal cases. The computed sensitivity (true positive (TP) detection rate) was 90.1% with an average low false positive (FP) detection of 0.71 MCCs/image for the enhanced images using a modified k-fold validation error estimation technique. The corresponding computed sensitivity for the raw images was reduced to 81.4% and with 0.59 FP's MCCs/image. A relative comparison to an earlier neural network (NN) design, using only spatially related features, suggests the importance of the addition of spectral domain features when the raw image data are analyzed

Spectral Polarimetric Features Analysis of Wind Turbine Clutter in Weather Radar

NARCIS (Netherlands)

Yin, J.; Krasnov, O.A.; Unal, C.M.H.; Medagli, S.; Russchenberg, H.W.J.

2017-01-01

Wind turbine clutter has gradually become a concern for the radar community for its increasing size and quantity worldwide. Based on the S-band polarimetric Doppler PARSAX radar measurements, this paper demonstrates the micro-Doppler features and spectral-polarimetric characteristic of wind turbine

Poly(A) motif prediction using spectral latent features from human DNA sequences

KAUST Repository

Xie, Bo; Jankovic, Boris R.; Bajic, Vladimir B.; Song, Le; Gao, Xin

2013-01-01

Motivation: Polyadenylation is the addition of a poly(A) tail to an RNA molecule. Identifying DNA sequence motifs that signal the addition of poly(A) tails is essential to improved genome annotation and better understanding of the regulatory mechanisms and stability of mRNA.Existing poly(A) motif predictors demonstrate that information extracted from the surrounding nucleotide sequences of candidate poly(A) motifs can differentiate true motifs from the false ones to a great extent. A variety of sophisticated features has been explored, including sequential, structural, statistical, thermodynamic and evolutionary properties. However, most of these methods involve extensive manual feature engineering, which can be time-consuming and can require in-depth domain knowledge.Results: We propose a novel machine-learning method for poly(A) motif prediction by marrying generative learning (hidden Markov models) and discriminative learning (support vector machines). Generative learning provides a rich palette on which the uncertainty and diversity of sequence information can be handled, while discriminative learning allows the performance of the classification task to be directly optimized. Here, we used hidden Markov models for fitting the DNA sequence dynamics, and developed an efficient spectral algorithm for extracting latent variable information from these models. These spectral latent features were then fed into support vector machines to fine-tune the classification performance.We evaluated our proposed method on a comprehensive human poly(A) dataset that consists of 14 740 samples from 12 of the most abundant variants of human poly(A) motifs. Compared with one of the previous state-of-the-art methods in the literature (the random forest model with expert-crafted features), our method reduces the average error rate, false-negative rate and false-positive rate by 26, 15 and 35%, respectively. Meanwhile, our method makes ?30% fewer error predictions relative to the other

Poly(A) motif prediction using spectral latent features from human DNA sequences

KAUST Repository

Xie, Bo

2013-06-21

Motivation: Polyadenylation is the addition of a poly(A) tail to an RNA molecule. Identifying DNA sequence motifs that signal the addition of poly(A) tails is essential to improved genome annotation and better understanding of the regulatory mechanisms and stability of mRNA.Existing poly(A) motif predictors demonstrate that information extracted from the surrounding nucleotide sequences of candidate poly(A) motifs can differentiate true motifs from the false ones to a great extent. A variety of sophisticated features has been explored, including sequential, structural, statistical, thermodynamic and evolutionary properties. However, most of these methods involve extensive manual feature engineering, which can be time-consuming and can require in-depth domain knowledge.Results: We propose a novel machine-learning method for poly(A) motif prediction by marrying generative learning (hidden Markov models) and discriminative learning (support vector machines). Generative learning provides a rich palette on which the uncertainty and diversity of sequence information can be handled, while discriminative learning allows the performance of the classification task to be directly optimized. Here, we used hidden Markov models for fitting the DNA sequence dynamics, and developed an efficient spectral algorithm for extracting latent variable information from these models. These spectral latent features were then fed into support vector machines to fine-tune the classification performance.We evaluated our proposed method on a comprehensive human poly(A) dataset that consists of 14 740 samples from 12 of the most abundant variants of human poly(A) motifs. Compared with one of the previous state-of-the-art methods in the literature (the random forest model with expert-crafted features), our method reduces the average error rate, false-negative rate and false-positive rate by 26, 15 and 35%, respectively. Meanwhile, our method makes ?30% fewer error predictions relative to the other

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

Science.gov (United States)

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.

On the relevance of spectral features for instrument classification

DEFF Research Database (Denmark)

Nielsen, Andreas Brinch; Sigurdsson, Sigurdur; Hansen, Lars Kai

2007-01-01

Automatic knowledge extraction from music signals is a key component for most music organization and music information retrieval systems. In this paper, we consider the problem of instrument modelling and instrument classification from the rough audio data. Existing systems for automatic instrument...... classification operate normally on a relatively large number of features, from which those related to the spectrum of the audio signal are particularly relevant. In this paper, we confront two different models about the spectral characterization of musical instruments. The first assumes a constant envelope...

Resolving fine spectral features in lattice vibrational modes using femtosecond coherent spectroscopy

Directory of Open Access Journals (Sweden)

A. Card

2016-02-01

Full Text Available We show resolution of fine spectral features within several Raman active vibrational modes in potassium titanyl phosphate (KTP crystal. Measurements are performed using a femtosecond time-domain coherent anti-Stokes Raman scattering spectroscopy technique that is capable of delivering equivalent spectral resolution of 0.1 cm−1. The Raman spectra retrieved from our measurements show several spectral components corresponding to vibrations of different symmetry with distinctly different damping rates. In particular, linewidths for unassigned optical phonon mode triplet centered at around 820 cm−1 are found to be 7.5 ± 0.2 cm−1, 9.1 ± 0.3 cm−1, and 11.2 ± 0.3 cm−1. Results of our experiments will ultimately help to design an all-solid-state source for sub-optical-wavelength waveform generation that is based on stimulated Raman scattering.

Berkeley SuperNova Ia Program (BSNIP): Initial Spectral Analysis

Science.gov (United States)

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 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.

Analysis of Spectral Features of Seawaterbiooptical Components Fluorescence from the Excitation-emission Matrix

Science.gov (United States)

Salyuk, P. A.; Nagorny, I. G.

The paper presents the method for processing of excitation-emission matrix of sea water and the allocation of the spectral characteristics of different types of colored dissolved organic matter (CDOM) and phytoplankton cells in seawater. The method consists of identification of regularly observed fluorescence peaks of CDOM in marine waters of different type and definition of the spectral ranges, where the predominant influence of these peaks are observed.

Land Cover Classification Using Integrated Spectral, Temporal, and Spatial Features Derived from Remotely Sensed Images

Directory of Open Access Journals (Sweden)

Yongguang Zhai

2018-03-01

Full Text Available Obtaining accurate and timely land cover information is an important topic in many remote sensing applications. Using satellite image time series data should achieve high-accuracy land cover classification. However, most satellite image time-series classification methods do not fully exploit the available data for mining the effective features to identify different land cover types. Therefore, a classification method that can take full advantage of the rich information provided by time-series data to improve the accuracy of land cover classification is needed. In this paper, a novel method for time-series land cover classification using spectral, temporal, and spatial information at an annual scale was introduced. Based on all the available data from time-series remote sensing images, a refined nonlinear dimensionality reduction method was used to extract the spectral and temporal features, and a modified graph segmentation method was used to extract the spatial features. The proposed classification method was applied in three study areas with land cover complexity, including Illinois, South Dakota, and Texas. All the Landsat time series data in 2014 were used, and different study areas have different amounts of invalid data. A series of comparative experiments were conducted on the annual time-series images using training data generated from Cropland Data Layer. The results demonstrated higher overall and per-class classification accuracies and kappa index values using the proposed spectral-temporal-spatial method compared to spectral-temporal classification methods. We also discuss the implications of this study and possibilities for future applications and developments of the method.

Atmospheric-water absorption features near 2.2 micrometers and their importance in high spectral resolution remote sensing

Science.gov (United States)

Kruse, F. A.; Clark, R. N.

1986-01-01

Selective absorption of electromagnetic radiation by atmospheric gases and water vapor is an accepted fact in terrestrial remote sensing. Until recently, only a general knowledge of atmospheric effects was required for analysis of remote sensing data; however, with the advent of high spectral resolution imaging devices, detailed knowledge of atmospheric absorption bands has become increasingly important for accurate analysis. Detailed study of high spectral resolution aircraft data at the U.S. Geological Survey has disclosed narrow absorption features centered at approximately 2.17 and 2.20 micrometers not caused by surface mineralogy. Published atmospheric transmission spectra and atmospheric spectra derived using the LOWTRAN-5 computer model indicate that these absorption features are probably water vapor. Spectral modeling indicates that the effects of atmospheric absorption in this region are most pronounced in spectrally flat materials with only weak absorption bands. Without correction and detailed knowledge of the atmospheric effects, accurate mapping of surface mineralogy (particularly at low mineral concentrations) is not possible.

A comparison of random forest and its Gini importance with standard chemometric methods for the feature selection and classification of spectral data

Directory of Open Access Journals (Sweden)

Himmelreich Uwe

2009-07-01

Full Text Available Abstract Background Regularized regression methods such as principal component or partial least squares regression perform well in learning tasks on high dimensional spectral data, but cannot explicitly eliminate irrelevant features. The random forest classifier with its associated Gini feature importance, on the other hand, allows for an explicit feature elimination, but may not be optimally adapted to spectral data due to the topology of its constituent classification trees which are based on orthogonal splits in feature space. Results We propose to combine the best of both approaches, and evaluated the joint use of a feature selection based on a recursive feature elimination using the Gini importance of random forests' together with regularized classification methods on spectral data sets from medical diagnostics, chemotaxonomy, biomedical analytics, food science, and synthetically modified spectral data. Here, a feature selection using the Gini feature importance with a regularized classification by discriminant partial least squares regression performed as well as or better than a filtering according to different univariate statistical tests, or using regression coefficients in a backward feature elimination. It outperformed the direct application of the random forest classifier, or the direct application of the regularized classifiers on the full set of features. Conclusion The Gini importance of the random forest provided superior means for measuring feature relevance on spectral data, but – on an optimal subset of features – the regularized classifiers might be preferable over the random forest classifier, in spite of their limitation to model linear dependencies only. A feature selection based on Gini importance, however, may precede a regularized linear classification to identify this optimal subset of features, and to earn a double benefit of both dimensionality reduction and the elimination of noise from the classification task.

Beyond intensity: Spectral features effectively predict music-induced subjective arousal.

Science.gov (United States)

Gingras, Bruno; Marin, Manuela M; Fitch, W Tecumseh

2014-01-01

Emotions in music are conveyed by a variety of acoustic cues. Notably, the positive association between sound intensity and arousal has particular biological relevance. However, although amplitude normalization is a common procedure used to control for intensity in music psychology research, direct comparisons between emotional ratings of original and amplitude-normalized musical excerpts are lacking. In this study, 30 nonmusicians retrospectively rated the subjective arousal and pleasantness induced by 84 six-second classical music excerpts, and an additional 30 nonmusicians rated the same excerpts normalized for amplitude. Following the cue-redundancy and Brunswik lens models of acoustic communication, we hypothesized that arousal and pleasantness ratings would be similar for both versions of the excerpts, and that arousal could be predicted effectively by other acoustic cues besides intensity. Although the difference in mean arousal and pleasantness ratings between original and amplitude-normalized excerpts correlated significantly with the amplitude adjustment, ratings for both sets of excerpts were highly correlated and shared a similar range of values, thus validating the use of amplitude normalization in music emotion research. Two acoustic parameters, spectral flux and spectral entropy, accounted for 65% of the variance in arousal ratings for both sets, indicating that spectral features can effectively predict arousal. Additionally, we confirmed that amplitude-normalized excerpts were adequately matched for loudness. Overall, the results corroborate our hypotheses and support the cue-redundancy and Brunswik lens models.

Spectral features of nasals in Standard Latvian

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Jana Taperte

2015-12-01

Full Text Available In the article, the acoustic features of nasals in Standard Latvian are investigated. The aim of the study is to examine whether some of the spectral properties of nasal murmur (namely anti-formant frequency, as well as frequency and bandwidth of the first nasal formant can be considered as efficient cues for distinguishing between nasal places of articulation.Speech recordings from 10 native speakers of Standard Latvian, five male and five female, aged 19–39, without any disorders or dialectal traces in their pronunciation, were used for the analysis. Prevocalic nasals [m; n; ɲ] were analyzed in isolated CVC syllables, where C is one of the nasals and V is one of the vowels [i(ː; e(ː; æ(ː; ɑ(ː; ɔ(ː; u(ː]. The velar [ŋ] — the allophone of the phoneme /n/ — was recorded in postvocalic position in [k]V[ŋks] structure units. 1260 items were analyzed in total.According to the results, the nasals of Standard Latvian can be distinguished by anti-formant frequencies rather efficiently, and the results generally agree with those obtained in previous research of Latvian as well as data reported for other languages. The frequencies and the bandwidths of the first nasal formant are less informative regarding nasal place of articulation and can be used only for distinguishing between [ŋ] and [m; n; ɲ]. Conducting perception tests to assess the auditory relevance of these acoustic features is necessary.

Spectral feature characterization methods for blood stain detection in crime scene backgrounds

Science.gov (United States)

Yang, Jie; Mathew, Jobin J.; Dube, Roger R.; Messinger, David W.

2016-05-01

Blood stains are one of the most important types of evidence for forensic investigation. They contain valuable DNA information, and the pattern of the stains can suggest specifics about the nature of the violence that transpired at the scene. Blood spectral signatures containing unique reflectance or absorption features are important both for forensic on-site investigation and laboratory testing. They can be used for target detection and identification applied to crime scene hyperspectral imagery, and also be utilized to analyze the spectral variation of blood on various backgrounds. Non-blood stains often mislead the detection and can generate false alarms at a real crime scene, especially for dark and red backgrounds. This paper measured the reflectance of liquid blood and 9 kinds of non-blood samples in the range of 350 nm - 2500 nm in various crime scene backgrounds, such as pure samples contained in petri dish with various thicknesses, mixed samples with different colors and materials of fabrics, and mixed samples with wood, all of which are examined to provide sub-visual evidence for detecting and recognizing blood from non-blood samples in a realistic crime scene. The spectral difference between blood and non-blood samples are examined and spectral features such as "peaks" and "depths" of reflectance are selected. Two blood stain detection methods are proposed in this paper. The first method uses index to denote the ratio of "depth" minus "peak" over"depth" add"peak" within a wavelength range of the reflectance spectrum. The second method uses relative band depth of the selected wavelength ranges of the reflectance spectrum. Results show that the index method is able to discriminate blood from non-blood samples in most tested crime scene backgrounds, but is not able to detect it from black felt. Whereas the relative band depth method is able to discriminate blood from non-blood samples on all of the tested background material types and colors.

Analysis of wheezes using wavelet higher order spectral features.

Science.gov (United States)

Taplidou, Styliani A; Hadjileontiadis, Leontios J

2010-07-01

. This paves the way for the use of the wavelet higher order spectral features as an input vector to an efficient classifier. Apparently, this would integrate the intrinsic characteristics of wheezes within computerized diagnostic tools toward their more efficient evaluation.

Application of self-organizing feature maps to analyze the relationships between ignitable liquids and selected mass spectral ions.

Science.gov (United States)

Frisch-Daiello, Jessica L; Williams, Mary R; Waddell, Erin E; Sigman, Michael E

2014-03-01

The unsupervised artificial neural networks method of self-organizing feature maps (SOFMs) is applied to spectral data of ignitable liquids to visualize the grouping of similar ignitable liquids with respect to their American Society for Testing and Materials (ASTM) class designations and to determine the ions associated with each group. The spectral data consists of extracted ion spectra (EIS), defined as the time-averaged mass spectrum across the chromatographic profile for select ions, where the selected ions are a subset of ions from Table 2 of the ASTM standard E1618-11. Utilization of the EIS allows for inter-laboratory comparisons without the concern of retention time shifts. The trained SOFM demonstrates clustering of the ignitable liquid samples according to designated ASTM classes. The EIS of select samples designated as miscellaneous or oxygenated as well as ignitable liquid residues from fire debris samples are projected onto the SOFM. The results indicate the similarities and differences between the variables of the newly projected data compared to those of the data used to train the SOFM. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Integration of Absorption Feature Information from Visible to Longwave Infrared Spectral Ranges for Mineral Mapping

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Veronika Kopačková

2017-09-01

Full Text Available Merging hyperspectral data from optical and thermal ranges allows a wider variety of minerals to be mapped and thus allows lithology to be mapped in a more complex way. In contrast, in most of the studies that have taken advantage of the data from the visible (VIS, near-infrared (NIR, shortwave infrared (SWIR and longwave infrared (LWIR spectral ranges, these different spectral ranges were analysed and interpreted separately. This limits the complexity of the final interpretation. In this study a presentation is made of how multiple absorption features, which are directly linked to the mineral composition and are present throughout the VIS, NIR, SWIR and LWIR ranges, can be automatically derived and, moreover, how these new datasets can be successfully used for mineral/lithology mapping. The biggest advantage of this approach is that it overcomes the issue of prior definition of endmembers, which is a requested routine employed in all widely used spectral mapping techniques. In this study, two different airborne image datasets were analysed, HyMap (VIS/NIR/SWIR image data and Airborne Hyperspectral Scanner (AHS, LWIR image data. Both datasets were acquired over the Sokolov lignite open-cast mines in the Czech Republic. It is further demonstrated that even in this case, when the absorption feature information derived from multispectral LWIR data is integrated with the absorption feature information derived from hyperspectral VIS/NIR/SWIR data, an important improvement in terms of more complex mineral mapping is achieved.

A Closer Look at Deep Learning Neural Networks with Low-level Spectral Periodicity Features

DEFF Research Database (Denmark)

Sturm, Bob L.; Kereliuk, Corey; Pikrakis, Aggelos

2014-01-01

Systems built using deep learning neural networks trained on low-level spectral periodicity features (DeSPerF) reproduced the most “ground truth” of the systems submitted to the MIREX 2013 task, “Audio Latin Genre Classification.” To answer why this was the case, we take a closer look...

Quasiparticle self-consistent GW method for the spectral properties of complex materials.

Science.gov (United States)

Bruneval, Fabien; Gatti, Matteo

2014-01-01

The GW approximation to the formally exact many-body perturbation theory has been applied successfully to materials for several decades. Since the practical calculations are extremely cumbersome, the GW self-energy is most commonly evaluated using a first-order perturbative approach: This is the so-called G 0 W 0 scheme. However, the G 0 W 0 approximation depends heavily on the mean-field theory that is employed as a basis for the perturbation theory. Recently, a procedure to reach a kind of self-consistency within the GW framework has been proposed. The quasiparticle self-consistent GW (QSGW) approximation retains some positive aspects of a self-consistent approach, but circumvents the intricacies of the complete GW theory, which is inconveniently based on a non-Hermitian and dynamical self-energy. This new scheme allows one to surmount most of the flaws of the usual G 0 W 0 at a moderate calculation cost and at a reasonable implementation burden. In particular, the issues of small band gap semiconductors, of large band gap insulators, and of some transition metal oxides are then cured. The QSGW method broadens the range of materials for which the spectral properties can be predicted with confidence.

Self-consistent spectral function for non-degenerate Coulomb systems and analytic scaling behaviour

International Nuclear Information System (INIS)

Fortmann, Carsten

2008-01-01

Novel results for the self-consistent single-particle spectral function and self-energy are presented for non-degenerate one-component Coulomb systems at various densities and temperatures. The GW (0) -method for the dynamical self-energy is used to include many-particle correlations beyond the quasi-particle approximation. The self-energy is analysed over a broad range of densities and temperatures (n = 10 17 cm -3 -10 27 cm -3 , T = 10 2 eV/k B -10 4 eV/k B ). The spectral function shows a systematic behaviour, which is determined by collective plasma modes at small wavenumbers and converges towards a quasi-particle resonance at higher wavenumbers. In the low density limit, the numerical results comply with an analytic scaling law that is presented for the first time. It predicts a power-law behaviour of the imaginary part of the self-energy, ImΣ ∼ -n 1/4 . This resolves a long time problem of the quasi-particle approximation which yields a finite self-energy at vanishing density

Isotopically varying spectral features of silicon-vacancy in diamond

International Nuclear Information System (INIS)

Dietrich, Andreas; Jahnke, Kay D; Binder, Jan M; Rogers, Lachlan J; Jelezko, Fedor; Teraji, Tokuyuki; Isoya, Junichi

2014-01-01

The silicon-vacancy centre (SiV − ) in diamond has exceptional spectral properties for single-emitter quantum information applications. Most of the fluorescence is concentrated in a strong zero phonon line (ZPL), with a weak phonon sideband extending for 100 nm that contains several clear features. We demonstrate that the ZPL position can be used to reliably identify the silicon isotope present in a single SiV − centre. This is of interest for quantum information applications since only the 29 Si isotope has nuclear spin. In addition, we show that the sharp 64 meV phonon peak is due to a local vibrational mode of the silicon atom. The presence of a local mode suggests a plausible origin of the measured isotopic shift of the ZPL. (paper)

Thermal Infrared Spectra of Microcrystalline Sedimentary Phases: Effects of Natural Surface Roughness on Spectral Feature Shape

Science.gov (United States)

Hardgrove, C.; Rogers, A. D.

2012-03-01

Thermal infrared spectral features of common microcrystalline phases (chert, alabaster, micrite) are presented. Spectra are sensitive to mineralogy and micron-scale (~1-25 µm) surface roughness. Roughness is on the scale of the average crystal size.

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

Science.gov (United States)

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

2017-10-01

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

Acoustic Event Detection in Multichannel Audio Using Gated Recurrent Neural Networks with High‐Resolution Spectral Features

Directory of Open Access Journals (Sweden)

Hyoung‐Gook Kim

2017-12-01

Full Text Available Recently, deep recurrent neural networks have achieved great success in various machine learning tasks, and have also been applied for sound event detection. The detection of temporally overlapping sound events in realistic environments is much more challenging than in monophonic detection problems. In this paper, we present an approach to improve the accuracy of polyphonic sound event detection in multichannel audio based on gated recurrent neural networks in combination with auditory spectral features. In the proposed method, human hearing perception‐based spatial and spectral‐domain noise‐reduced harmonic features are extracted from multichannel audio and used as high‐resolution spectral inputs to train gated recurrent neural networks. This provides a fast and stable convergence rate compared to long short‐term memory recurrent neural networks. Our evaluation reveals that the proposed method outperforms the conventional approaches.

Spectral Decomposition Algorithm (SDA)

Data.gov (United States)

National Aeronautics and Space Administration — Spectral Decomposition Algorithm (SDA) is an unsupervised feature extraction technique similar to PCA that was developed to better distinguish spectral features in...

Spectral characteristics and feature selection of satellite remote sensing data for climate and anthropogenic changes assessment in Bucharest area

Science.gov (United States)

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

Temperature profile retrieval in axisymmetric combustion plumes using multilayer perceptron modeling and spectral feature selection in the infrared CO2 emission band.

Science.gov (United States)

García-Cuesta, Esteban; de Castro, Antonio J; Galván, Inés M; López, Fernando

2014-01-01

In this work, a methodology based on the combined use of a multilayer perceptron model fed using selected spectral information is presented to invert the radiative transfer equation (RTE) and to recover the spatial temperature profile inside an axisymmetric flame. The spectral information is provided by the measurement of the infrared CO2 emission band in the 3-5 μm spectral region. A guided spectral feature selection was carried out using a joint criterion of principal component analysis and a priori physical knowledge of the radiative problem. After applying this guided feature selection, a subset of 17 wavenumbers was selected. The proposed methodology was applied over synthetic scenarios. Also, an experimental validation was carried out by measuring the spectral emission of the exhaust hot gas plume in a microjet engine with a Fourier transform-based spectroradiometer. Temperatures retrieved using the proposed methodology were compared with classical thermocouple measurements, showing a good agreement between them. Results obtained using the proposed methodology are very promising and can encourage the use of sensor systems based on the spectral measurement of the CO2 emission band in the 3-5 μm spectral window to monitor combustion processes in a nonintrusive way.

[Spectral features analysis of Pinus massoniana with pest of Dendrolimus punctatus Walker and levels detection].

Science.gov (United States)

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.

USGS Digital Spectral Library splib06a

Science.gov (United States)

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

2007-01-01

), 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

Consistent Feature Extraction From Vector Fields: Combinatorial Representations and Analysis Under Local Reference Frames

Energy Technology Data Exchange (ETDEWEB)

Bhatia, Harsh [Univ. of Utah, Salt Lake City, UT (United States)

2015-05-01

This dissertation presents research on addressing some of the contemporary challenges in the analysis of vector fields—an important type of scientific data useful for representing a multitude of physical phenomena, such as wind flow and ocean currents. In particular, new theories and computational frameworks to enable consistent feature extraction from vector fields are presented. One of the most fundamental challenges in the analysis of vector fields is that their features are defined with respect to reference frames. Unfortunately, there is no single “correct” reference frame for analysis, and an unsuitable frame may cause features of interest to remain undetected, thus creating serious physical consequences. This work develops new reference frames that enable extraction of localized features that other techniques and frames fail to detect. As a result, these reference frames objectify the notion of “correctness” of features for certain goals by revealing the phenomena of importance from the underlying data. An important consequence of using these local frames is that the analysis of unsteady (time-varying) vector fields can be reduced to the analysis of sequences of steady (timeindependent) vector fields, which can be performed using simpler and scalable techniques that allow better data management by accessing the data on a per-time-step basis. Nevertheless, the state-of-the-art analysis of steady vector fields is not robust, as most techniques are numerical in nature. The residing numerical errors can violate consistency with the underlying theory by breaching important fundamental laws, which may lead to serious physical consequences. This dissertation considers consistency as the most fundamental characteristic of computational analysis that must always be preserved, and presents a new discrete theory that uses combinatorial representations and algorithms to provide consistency guarantees during vector field analysis along with the uncertainty

Linking Spectral Features with Composition, Crystallinity, and Roughness Properties of Silica and Implications for Candidate Hydrothermal Systems on Mars

Science.gov (United States)

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 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

Novel spectral features of nanoelectromechanical systems

KAUST Repository

Tahir, M.; MacKinnon, A.; Schwingenschlö gl, Udo

2014-01-01

of freedom. We tune the electronic level of the quantum dot by a gate voltage, where the leads are kept at zero temperature. Due to the nonequilibrium distribution of the electrons in the quantum dot, the spectral function becomes a function of the gate

STATISTICS OF FLARING LOOPS OBSERVED BY NOBEYAMA RADIOHELIOGRAPH. II. SPECTRAL EVOLUTION

International Nuclear Information System (INIS)

Huang Guangli; Nakajima, Hiroshi

2009-01-01

The spectral evolution of solar microwave bursts is studied in 10 impulsive events with loop-like structures, which are selected in the flare list of Nobeyama Radioheliograph. Most events have a brighter and harder looptop (LT) with maximum time later than at least one of its two footpoints (FPs), and have a common feature of the spectral evolution in the LT and the two FPs. There are five simple impulsive bursts with a well known pattern of soft-hard-soft or soft-hard-harder (SHH). It is first found that the other five events have multiple subpeaks in their impulsive phase, and mostly have a new feature of hard-soft-hard (HSH) in each subpeak, but, the well known tendency of SHH is still maintained in the total spectral evolution of these events. All of these features in the spectral evolution of the 10 selected events are consistent with the full Sun observations of Nobeyama Radio Polarimeters in these events. The new feature of HSH may be explained by the thermal free-free emission before, during, and after these bursts, together with multiple injections of nonthermal electrons, while the SHH pattern in the total duration may be directly caused by the trapping effect.

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

Science.gov (United States)

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.

Spectral Feature Analysis of Minerals and Planetary Surfaces in an Introductory Planetary Science Course

Science.gov (United States)

Urban, Michael J.

2013-01-01

Using an ALTA II reflectance spectrometer, the USGS digital spectral library, graphs of planetary spectra, and a few mineral hand samples, one can teach how light can be used to study planets and moons. The author created the hands-on, inquiry-based activity for an undergraduate planetary science course consisting of freshman to senior level…

Mars analog minerals' spectral reflectance characteristics under Martian surface conditions

Science.gov (United States)

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

Multiple intelligence: ethical leadership feature consistent financial institutions.

Directory of Open Access Journals (Sweden)

Diamela Nava

2015-03-01

Full Text Available This study aims to make a theoretical underpinning contrast analysis on the multiple intelligences: consistent feature of Ethical Leadership in Financial Institutions. However, this research was conducted under a qualitative approach, a descriptive, using document analysis, which eventually might be considered that would support multiple intelligences to implement certain capabilities, to achieve the objectives with the purpose and from the rational point of view, to know how to establish significant changes in some ways it is, the way to assess the cognitive abilities of integrating human talent in organizations. Therefore, the role of the leader is to guide and support the development of human potential in their group as a community of interest in order to achieve the aspirations of the organization using intelligence as a strategic tool in different ways to not limit your imagination, judgment, and cooperative action.  

Influence of semantic consistency and perceptual features on visual attention during scene viewing in toddlers.

Science.gov (United States)

Helo, Andrea; van Ommen, Sandrien; Pannasch, Sebastian; Danteny-Dordoigne, Lucile; Rämä, Pia

2017-11-01

Conceptual representations of everyday scenes are built in interaction with visual environment and these representations guide our visual attention. Perceptual features and object-scene semantic consistency have been found to attract our attention during scene exploration. The present study examined how visual attention in 24-month-old toddlers is attracted by semantic violations and how perceptual features (i. e. saliency, centre distance, clutter and object size) and linguistic properties (i. e. object label frequency and label length) affect gaze distribution. We compared eye movements of 24-month-old toddlers and adults while exploring everyday scenes which either contained an inconsistent (e.g., soap on a breakfast table) or consistent (e.g., soap in a bathroom) object. Perceptual features such as saliency, centre distance and clutter of the scene affected looking times in the toddler group during the whole viewing time whereas looking times in adults were affected only by centre distance during the early viewing time. Adults looked longer to inconsistent than consistent objects either if the objects had a high or a low saliency. In contrast, toddlers presented semantic consistency effect only when objects were highly salient. Additionally, toddlers with lower vocabulary skills looked longer to inconsistent objects while toddlers with higher vocabulary skills look equally long to both consistent and inconsistent objects. Our results indicate that 24-month-old children use scene context to guide visual attention when exploring the visual environment. However, perceptual features have a stronger influence in eye movement guidance in toddlers than in adults. Our results also indicate that language skills influence cognitive but not perceptual guidance of eye movements during scene perception in toddlers. Copyright © 2017 Elsevier Inc. All rights reserved.

Unified picture of the photoexcitations in phenylene-based conjugated polymers: Universal spectral and dynamical features in subpicosecond transient absorption

International Nuclear Information System (INIS)

Kraabel, B.; Klimov, V. I.; Kohlman, R.; Xu, S.; Wang, H-L.; McBranch, D. W.

2000-01-01

Using subpicosecond transient absorption spectroscopy, we investigate the primary photoexcitations in thin films and solutions of several phenylene-based conjugated polymers and an oligomer. We identify several features in the transient absorption spectra and dynamics that are common to all of the materials which we studied from this family. The first spectral feature is a photoinduced absorption (PA) band peaking near 1 eV that has intensity-dependent dynamics that match the stimulated emission dynamics exactly over two orders of magnitude in excitation density. This band is associated with singlet intrachain excitons. The second spectral feature (observed only in thin films and aggregated solutions) is a PA band peaking near 1.8 eV, that is longer lived than the 1 eV exciton PA band, and that has dynamics that are independent (or weakly dependent) on excitation density. This feature is attributed to polarons, generated through a mechanism that is sample dependent. In pristine samples, polarons are generated via a mechanism that is quadratic in exciton density, whereas in photodegraded samples or samples doped with electron acceptors, the generation mechanism becomes linear in exciton density. (c) 2000 The American Physical Society

M DWARF LUMINOSITY, RADIUS, AND α-ENRICHMENT FROM I-BAND SPECTRAL FEATURES

Energy Technology Data Exchange (ETDEWEB)

Terrien, Ryan C.; Mahadevan, Suvrath; Bender, Chad F.; Deshpande, Rohit; Robertson, Paul, E-mail: rct151@psu.edu [Department of Astronomy and Astrophysics, The Pennsylvania State University, 525 Davey Laboratory, University Park, PA 16802 (United States)

2015-03-20

Despite the ubiquity of M dwarfs and their growing importance to studies of exoplanets, Galactic evolution, and stellar structure, methods for precisely measuring their fundamental stellar properties remain elusive. Existing techniques for measuring M dwarf luminosity, mass, radius, or composition are calibrated over a limited range of stellar parameters or require expensive observations. We find a strong correlation between the K{sub S}-band luminosity (M{sub K}), the observed strength of the I-band sodium doublet absorption feature, and [Fe/H] in M dwarfs without strong Hα emission. We show that the strength of this feature, coupled with [Fe/H] and spectral type, can be used to derive M dwarf M{sub K} and radius without requiring parallax. Additionally, we find promising evidence that the strengths of the I-band sodium doublet and the nearby I-band calcium triplet may jointly indicate α-element enrichment. The use of these I-band features requires only moderate-resolution near-infrared spectroscopy to provide valuable information about the potential habitability of exoplanets around M dwarfs, and surface gravity and distance for M dwarfs throughout the Galaxy. This technique has immediate applicability for both target selection and candidate planet–host system characterization for exoplanet missions such as TESS and K2.

M DWARF LUMINOSITY, RADIUS, AND α-ENRICHMENT FROM I-BAND SPECTRAL FEATURES

International Nuclear Information System (INIS)

Terrien, Ryan C.; Mahadevan, Suvrath; Bender, Chad F.; Deshpande, Rohit; Robertson, Paul

2015-01-01

Despite the ubiquity of M dwarfs and their growing importance to studies of exoplanets, Galactic evolution, and stellar structure, methods for precisely measuring their fundamental stellar properties remain elusive. Existing techniques for measuring M dwarf luminosity, mass, radius, or composition are calibrated over a limited range of stellar parameters or require expensive observations. We find a strong correlation between the K S -band luminosity (M K ), the observed strength of the I-band sodium doublet absorption feature, and [Fe/H] in M dwarfs without strong Hα emission. We show that the strength of this feature, coupled with [Fe/H] and spectral type, can be used to derive M dwarf M K and radius without requiring parallax. Additionally, we find promising evidence that the strengths of the I-band sodium doublet and the nearby I-band calcium triplet may jointly indicate α-element enrichment. The use of these I-band features requires only moderate-resolution near-infrared spectroscopy to provide valuable information about the potential habitability of exoplanets around M dwarfs, and surface gravity and distance for M dwarfs throughout the Galaxy. This technique has immediate applicability for both target selection and candidate planet–host system characterization for exoplanet missions such as TESS and K2

Developement of the method for realization of spectral irradiance scale featuring system of spectral comparisons

International Nuclear Information System (INIS)

Skerovic, V; Zarubica, V; Aleksic, M; Zekovic, L; Belca, I

2010-01-01

Realization of the scale of spectral responsivity of the detectors in the Directorate of Measures and Precious Metals (DMDM) is based on silicon detectors traceable to LNE-INM. In order to realize the unit of spectral irradiance in the laboratory for photometry and radiometry of the Bureau of Measures and Precious Metals, the new method based on the calibration of the spectroradiometer by comparison with standard detector has been established. The development of the method included realization of the System of Spectral Comparisons (SSC), together with the detector spectral responsivity calibrations by means of a primary spectrophotometric system. The linearity testing and stray light analysis were preformed to characterize the spectroradiometer. Measurement of aperture diameter and calibration of transimpedance amplifier were part of the overall experiment. In this paper, the developed method is presented and measurement results with the associated measurement uncertainty budget are shown.

Developement of the method for realization of spectral irradiance scale featuring system of spectral comparisons

Energy Technology Data Exchange (ETDEWEB)

Skerovic, V; Zarubica, V; Aleksic, M [Directorate of measures and precious metals, Optical radiation Metrology department, Mike Alasa 14, 11000 Belgrade (Serbia); Zekovic, L; Belca, I, E-mail: vladanskerovic@dmdm.r [Faculty of Physics, Department for Applied physics and metrology, Studentski trg 12-16, 11000 Belgrade (Serbia)

2010-10-15

Realization of the scale of spectral responsivity of the detectors in the Directorate of Measures and Precious Metals (DMDM) is based on silicon detectors traceable to LNE-INM. In order to realize the unit of spectral irradiance in the laboratory for photometry and radiometry of the Bureau of Measures and Precious Metals, the new method based on the calibration of the spectroradiometer by comparison with standard detector has been established. The development of the method included realization of the System of Spectral Comparisons (SSC), together with the detector spectral responsivity calibrations by means of a primary spectrophotometric system. The linearity testing and stray light analysis were preformed to characterize the spectroradiometer. Measurement of aperture diameter and calibration of transimpedance amplifier were part of the overall experiment. In this paper, the developed method is presented and measurement results with the associated measurement uncertainty budget are shown.

A TALE OF THREE MYSTERIOUS SPECTRAL FEATURES IN CARBON-RICH EVOLVED STARS: THE 21 μm, 30 μm, AND “UNIDENTIFIED INFRARED” EMISSION FEATURES

Energy Technology Data Exchange (ETDEWEB)

Mishra, Ajay; Li, Aigen [Department of Physics and Astronomy, University of Missouri, Columbia, MO 65211 (United States); Jiang, B. W., E-mail: amishra@mail.missouri.edu, E-mail: lia@missouri.edu, E-mail: bjiang@bnu.edu.cn [Department of Astronomy, Beijing Normal University, Beijing 100875 (China)

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, 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.

Radiometric Normalization of Temporal Images Combining Automatic Detection of Pseudo-Invariant Features from the Distance and Similarity Spectral Measures, Density Scatterplot Analysis, and Robust Regression

Directory of Open Access Journals (Sweden)

Ana Paula Ferreira de Carvalho

2013-05-01

Full Text Available Radiometric precision is difficult to maintain in orbital images due to several factors (atmospheric conditions, Earth-sun distance, detector calibration, illumination, and viewing angles. These unwanted effects must be removed for radiometric consistency among temporal images, leaving only land-leaving radiances, for optimum change detection. A variety of relative radiometric correction techniques were developed for the correction or rectification of images, of the same area, through use of reference targets whose reflectance do not change significantly with time, i.e., pseudo-invariant features (PIFs. This paper proposes a new technique for radiometric normalization, which uses three sequential methods for an accurate PIFs selection: spectral measures of temporal data (spectral distance and similarity, density scatter plot analysis (ridge method, and robust regression. The spectral measures used are the spectral angle (Spectral Angle Mapper, SAM, spectral correlation (Spectral Correlation Mapper, SCM, and Euclidean distance. The spectral measures between the spectra at times t1 and t2 and are calculated for each pixel. After classification using threshold values, it is possible to define points with the same spectral behavior, including PIFs. The distance and similarity measures are complementary and can be calculated together. The ridge method uses a density plot generated from images acquired on different dates for the selection of PIFs. In a density plot, the invariant pixels, together, form a high-density ridge, while variant pixels (clouds and land cover changes are spread, having low density, facilitating its exclusion. Finally, the selected PIFs are subjected to a robust regression (M-estimate between pairs of temporal bands for the detection and elimination of outliers, and to obtain the optimal linear equation for a given set of target points. The robust regression is insensitive to outliers, i.e., observation that appears to deviate

On- and off-axis spectral emission features from laser-produced gas breakdown plasmas

Energy Technology Data Exchange (ETDEWEB)

Harilal, S. S.; Skrodzki, P. J.; Miloshevsky, A.; Brumfield, B. E.; Phillips, M. C.; Miloshevsky, G.

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 times 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

Evaluation of Spectral and Prosodic Features of Speech Affected by Orthodontic Appliances Using the Gmm Classifier

Science.gov (United States)

Přibil, Jiří; Přibilová, Anna; Ďuračkoá, Daniela

2014-01-01

The paper describes our experiment with using the Gaussian mixture models (GMM) for classification of speech uttered by a person wearing orthodontic appliances. For the GMM classification, the input feature vectors comprise the basic and the complementary spectral properties as well as the supra-segmental parameters. Dependence of classification correctness on the number of the parameters in the input feature vector and on the computation complexity is also evaluated. In addition, an influence of the initial setting of the parameters for GMM training process was analyzed. Obtained recognition results are compared visually in the form of graphs as well as numerically in the form of tables and confusion matrices for tested sentences uttered using three configurations of orthodontic appliances.

An unsupervised technique for optimal feature selection in attribute profiles for spectral-spatial classification of hyperspectral images

Science.gov (United States)

Bhardwaj, Kaushal; Patra, Swarnajyoti

2018-04-01

Inclusion of spatial information along with spectral features play a significant role in classification of remote sensing images. Attribute profiles have already proved their ability to represent spatial information. In order to incorporate proper spatial information, multiple attributes are required and for each attribute large profiles need to be constructed by varying the filter parameter values within a wide range. Thus, the constructed profiles that represent spectral-spatial information of an hyperspectral image have huge dimension which leads to Hughes phenomenon and increases computational burden. To mitigate these problems, this work presents an unsupervised feature selection technique that selects a subset of filtered image from the constructed high dimensional multi-attribute profile which are sufficiently informative to discriminate well among classes. In this regard the proposed technique exploits genetic algorithms (GAs). The fitness function of GAs are defined in an unsupervised way with the help of mutual information. The effectiveness of the proposed technique is assessed using one-against-all support vector machine classifier. The experiments conducted on three hyperspectral data sets show the robustness of the proposed method in terms of computation time and classification accuracy.

Performance Evaluation of Downscaling Sentinel-2 Imagery for Land Use and Land Cover Classification by Spectral-Spatial Features

Directory of Open Access Journals (Sweden)

Hongrui Zheng

2017-12-01

Full Text Available Land Use and Land Cover (LULC classification is vital for environmental and ecological applications. Sentinel-2 is a new generation land monitoring satellite with the advantages of novel spectral capabilities, wide coverage and fine spatial and temporal resolutions. The effects of different spatial resolution unification schemes and methods on LULC classification have been scarcely investigated for Sentinel-2. This paper bridged this gap by comparing the differences between upscaling and downscaling as well as different downscaling algorithms from the point of view of LULC classification accuracy. The studied downscaling algorithms include nearest neighbor resampling and five popular pansharpening methods, namely, Gram-Schmidt (GS, nearest neighbor diffusion (NNDiffusion, PANSHARP algorithm proposed by Y. Zhang, wavelet transformation fusion (WTF and high-pass filter fusion (HPF. Two spatial features, textural metrics derived from Grey-Level-Co-occurrence Matrix (GLCM and extended attribute profiles (EAPs, are investigated to make up for the shortcoming of pixel-based spectral classification. Random forest (RF is adopted as the classifier. The experiment was conducted in Xitiaoxi watershed, China. The results demonstrated that downscaling obviously outperforms upscaling in terms of classification accuracy. For downscaling, image sharpening has no obvious advantages than spatial interpolation. Different image sharpening algorithms have distinct effects. Two multiresolution analysis (MRA-based methods, i.e., WTF and HFP, achieve the best performance. GS achieved a similar accuracy with NNDiffusion and PANSHARP. Compared to image sharpening, the introduction of spatial features, both GLCM and EAPs can greatly improve the classification accuracy for Sentinel-2 imagery. Their effects on overall accuracy are similar but differ significantly to specific classes. In general, using the spectral bands downscaled by nearest neighbor interpolation can meet

Consistency relations for sharp inflationary non-Gaussian features

Energy Technology Data Exchange (ETDEWEB)

Mooij, Sander; Palma, Gonzalo A.; Panotopoulos, Grigoris [Departamento de Física, Facultad de Ciencias Físicas y Matemáticas, Universidad de Chile, Blanco Encalada 2008, Santiago (Chile); Soto, Alex, E-mail: sander.mooij@ing.uchile.cl, E-mail: gpalmaquilod@ing.uchile.cl, E-mail: gpanotop@ing.uchile.cl, E-mail: gatogeno@gmail.com [Departamento de Física, Facultad de Ciencias, Universidad de Chile, Las Palmeras 3425, Ñuñoa, Santiago (Chile)

2016-09-01

If cosmic inflation suffered tiny time-dependent deviations from the slow-roll regime, these would induce the existence of small scale-dependent features imprinted in the primordial spectra, with their shapes and sizes revealing information about the physics that produced them. Small sharp features could be suppressed at the level of the two-point correlation function, making them undetectable in the power spectrum, but could be amplified at the level of the three-point correlation function, offering us a window of opportunity to uncover them in the non-Gaussian bispectrum. In this article, we show that sharp features may be analyzed using only data coming from the three point correlation function parametrizing primordial non-Gaussianity. More precisely, we show that if features appear in a particular non-Gaussian triangle configuration (e.g. equilateral, folded, squeezed), these must reappear in every other configuration according to a specific relation allowing us to correlate features across the non-Gaussian bispectrum. As a result, we offer a method to study scale-dependent features generated during inflation that depends only on data coming from measurements of non-Gaussianity, allowing us to omit data from the power spectrum.

Consistency relations for sharp inflationary non-Gaussian features

International Nuclear Information System (INIS)

Mooij, Sander; Palma, Gonzalo A.; Panotopoulos, Grigoris; Soto, Alex

2016-01-01

If cosmic inflation suffered tiny time-dependent deviations from the slow-roll regime, these would induce the existence of small scale-dependent features imprinted in the primordial spectra, with their shapes and sizes revealing information about the physics that produced them. Small sharp features could be suppressed at the level of the two-point correlation function, making them undetectable in the power spectrum, but could be amplified at the level of the three-point correlation function, offering us a window of opportunity to uncover them in the non-Gaussian bispectrum. In this article, we show that sharp features may be analyzed using only data coming from the three point correlation function parametrizing primordial non-Gaussianity. More precisely, we show that if features appear in a particular non-Gaussian triangle configuration (e.g. equilateral, folded, squeezed), these must reappear in every other configuration according to a specific relation allowing us to correlate features across the non-Gaussian bispectrum. As a result, we offer a method to study scale-dependent features generated during inflation that depends only on data coming from measurements of non-Gaussianity, allowing us to omit data from the power spectrum.

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

Science.gov (United States)

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 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.

Fault feature extraction of planet gear in wind turbine gearbox based on spectral kurtosis and time wavelet energy spectrum

Science.gov (United States)

Kong, Yun; Wang, Tianyang; Li, Zheng; Chu, Fulei

2017-09-01

Planetary transmission plays a vital role in wind turbine drivetrains, and its fault diagnosis has been an important and challenging issue. Owing to the complicated and coupled vibration source, time-variant vibration transfer path, and heavy background noise masking effect, the vibration signal of planet gear in wind turbine gearboxes exhibits several unique characteristics: Complex frequency components, low signal-to-noise ratio, and weak fault feature. In this sense, the periodic impulsive components induced by a localized defect are hard to extract, and the fault detection of planet gear in wind turbines remains to be a challenging research work. Aiming to extract the fault feature of planet gear effectively, we propose a novel feature extraction method based on spectral kurtosis and time wavelet energy spectrum (SK-TWES) in the paper. Firstly, the spectral kurtosis (SK) and kurtogram of raw vibration signals are computed and exploited to select the optimal filtering parameter for the subsequent band-pass filtering. Then, the band-pass filtering is applied to extrude periodic transient impulses using the optimal frequency band in which the corresponding SK value is maximal. Finally, the time wavelet energy spectrum analysis is performed on the filtered signal, selecting Morlet wavelet as the mother wavelet which possesses a high similarity to the impulsive components. The experimental signals collected from the wind turbine gearbox test rig demonstrate that the proposed method is effective at the feature extraction and fault diagnosis for the planet gear with a localized defect.

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

Science.gov (United States)

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.

Interpretation of archaeological small-scale features in spectral images

DEFF Research Database (Denmark)

Grøn, Ole; Palmer, Susanna; Stylegar, Frans-Arne

2011-01-01

The paper's focus is the use of spectral images for the distinction of small archaeological anomalies on the basis of the authors work. Special attention is given to the ground-truthing perspective in the discussion of a number of cases from Norway. Different approaches to pattern-recognition are......The paper's focus is the use of spectral images for the distinction of small archaeological anomalies on the basis of the authors work. Special attention is given to the ground-truthing perspective in the discussion of a number of cases from Norway. Different approaches to pattern...

Consistency with synchrotron emission in the bright GRB 160625B observed by Fermi

Science.gov (United States)

Ravasio, M. E.; Oganesyan, G.; Ghirlanda, G.; Nava, L.; Ghisellini, G.; Pescalli, A.; Celotti, A.

2018-05-01

We present time-resolved spectral analysis of prompt emission from GRB 160625B, one of the brightest bursts ever detected by Fermi in its nine years of operations. Standard empirical functions fail to provide an acceptable fit to the GBM spectral data, which instead require the addition of a low-energy break to the fitting function. We introduce a new fitting function, called 2SBPL, consisting of three smoothly connected power laws. Fitting this model to the data, the goodness of the fits significantly improves and the spectral parameters are well constrained. We also test a spectral model that combines non-thermal and thermal (black body) components, but find that the 2SBPL model is systematically favoured. The spectral evolution shows that the spectral break is located around Ebreak 100 keV, while the usual νFν peak energy feature Epeak evolves in the 0.5-6 MeV energy range. The slopes below and above Ebreak are consistent with the values -0.67 and -1.5, respectively, expected from synchrotron emission produced by a relativistic electron population with a low-energy cut-off. If Ebreak is interpreted as the synchrotron cooling frequency, the implied magnetic field in the emitting region is 10 Gauss, i.e. orders of magnitudes smaller than the value expected for a dissipation region located at 1013-14 cm from the central engine. The low ratio between Epeak and Ebreak implies that the radiative cooling is incomplete, contrary to what is expected in strongly magnetized and compact emitting regions.

Registration of 3D spectral OCT volumes using 3D SIFT feature point matching

Science.gov (United States)

Niemeijer, Meindert; Garvin, Mona K.; Lee, Kyungmoo; van Ginneken, Bram; Abràmoff, Michael D.; Sonka, Milan

2009-02-01

The recent introduction of next generation spectral OCT scanners has enabled routine acquisition of high resolution, 3D cross-sectional volumetric images of the retina. 3D OCT is used in the detection and management of serious eye diseases such as glaucoma and age-related macular degeneration. For follow-up studies, image registration is a vital tool to enable more precise, quantitative comparison of disease states. This work presents a registration method based on a recently introduced extension of the 2D Scale-Invariant Feature Transform (SIFT) framework1 to 3D.2 The SIFT feature extractor locates minima and maxima in the difference of Gaussian scale space to find salient feature points. It then uses histograms of the local gradient directions around each found extremum in 3D to characterize them in a 4096 element feature vector. Matching points are found by comparing the distance between feature vectors. We apply this method to the rigid registration of optic nerve head- (ONH) and macula-centered 3D OCT scans of the same patient that have only limited overlap. Three OCT data set pairs with known deformation were used for quantitative assessment of the method's robustness and accuracy when deformations of rotation and scaling were considered. Three-dimensional registration accuracy of 2.0+/-3.3 voxels was observed. The accuracy was assessed as average voxel distance error in N=1572 matched locations. The registration method was applied to 12 3D OCT scans (200 x 200 x 1024 voxels) of 6 normal eyes imaged in vivo to demonstrate the clinical utility and robustness of the method in a real-world environment.

Categorical templates are more useful when features are consistent: Evidence from eye movements during search for societally important vehicles.

Science.gov (United States)

Hout, Michael C; Robbins, Arryn; Godwin, Hayward J; Fitzsimmons, Gemma; Scarince, Collin

2017-08-01

Unlike in laboratory visual search tasks-wherein participants are typically presented with a pictorial representation of the item they are asked to seek out-in real-world searches, the observer rarely has veridical knowledge of the visual features that define their target. During categorical search, observers look for any instance of a categorically defined target (e.g., helping a family member look for their mobile phone). In these circumstances, people may not have information about noncritical features (e.g., the phone's color), and must instead create a broad mental representation using the features that define (or are typical of) the category of objects they are seeking out (e.g., modern phones are typically rectangular and thin). In the current investigation (Experiment 1), using a categorical visual search task, we add to the body of evidence suggesting that categorical templates are effective enough to conduct efficient visual searches. When color information was available (Experiment 1a), attentional guidance, attention restriction, and object identification were enhanced when participants looked for categories with consistent features (e.g., ambulances) relative to categories with more variable features (e.g., sedans). When color information was removed (Experiment 1b), attention benefits disappeared, but object recognition was still better for feature-consistent target categories. In Experiment 2, we empirically validated the relative homogeneity of our societally important vehicle stimuli. Taken together, our results are in line with a category-consistent view of categorical target templates (Yu, Maxfield, & Zelinsky in, Psychological Science, 2016. doi: 10.1177/0956797616640237 ), and suggest that when features of a category are consistent and predictable, searchers can create mental representations that allow for the efficient guidance and restriction of attention as well as swift object identification.

Changes in the Spectral Features of Zinc Phthalocyanine Induced by Nitrogen Dioxide Gas in Solution and in Solid Polymer Nanofiber Media.

Science.gov (United States)

Zugle, Ruphino; Tetteh, Samuel

2017-03-01

The changes in the spectral features of zinc phthalocyanine in the visible domain as a result of its interaction with nitrogen dioxide gas were assessed in this work. This was done both in solution and when the phthalocyanine was incorporated into a solid polystyrene polymer nanofiber matrix. The spectral changes were found to be spontaneous and marked in both cases suggesting a rapid response criterion for the detection of the gas. In particular, the functionalised nano-fabric material could serve as a practical fire alarm system as it rapidly detects the nitrogen dioxide gas generated during burning.

Microscopic nucleon spectral function for finite nuclei featuring two- and three-nucleon short-range correlations: The model versus ab initio calculations for three-nucleon systems

Science.gov (United States)

Ciofi degli Atti, Claudio; Mezzetti, Chiara Benedetta; Morita, Hiko

2017-04-01

Background: Two-nucleon (2 N ) short-range correlations (SRC) in nuclei have been recently thoroughly investigated, both theoretically and experimentally and the study of three-nucleon (3 N ) SRC, which could provide important information on short-range hadronic structure, is underway. Novel theoretical ideas concerning 2 N and 3 N SRC are put forward in the present paper. Purpose: The general features of a microscopic one-nucleon spectral function which includes the effects of both 2 N and 3 N SRC and its comparison with ab initio spectral functions of the three-nucleon systems are illustrated. Methods: A microscopic and parameter-free one-nucleon spectral function expressed in terms of a convolution integral involving ab initio relative and center-of-mass (c.m.) momentum distributions of a 2 N pair and aimed at describing two- and three-nucleon short-range correlations, is obtained by using: (i) the two-nucleon momentum distributions obtained within ab initio approaches based upon nucleon-nucleon interactions of the Argonne family; (ii) the exact relation between one- and two-nucleon momentum distributions; (iii) the fundamental property of factorization of the nuclear wave function at short internucleon ranges. Results: The comparison between the ab initio spectral function of 3He and the one based upon the convolution integral shows that when the latter contains only two-nucleon short-range correlations the removal energy location of the peaks and the region around them exhibited by the ab initio spectral function are correctly predicted, unlike the case of the high and low removal energy tails; the inclusion of the effects of three-nucleon correlations brings the convolution model spectral function in much better agreement with the ab initio one; it is also found that whereas the three-nucleon short-range correlations dominate the high energy removal energy tail of the spectral function, their effects on the one-nucleon momentum distribution are almost one

Spectral and spectral-frequency methods of investigating atmosphereless bodies of the Solar system

International Nuclear Information System (INIS)

Busarev, Vladimir V; Prokof'eva-Mikhailovskaya, Valentina V; Bochkov, Valerii V

2007-01-01

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. (instruments and methods of investigation)

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

Science.gov (United States)

Spectral nudging – a scale-selective interior constraint technique – is commonly used in regional climate models to maintain consistency with large-scale forcing while permitting mesoscale features to develop in the downscaled simulations. Several studies have demonst...

Spectral singularities, biorthonormal systems and a two-parameter family of complex point interactions

Energy Technology Data Exchange (ETDEWEB)

Mostafazadeh, Ali [Department of Mathematics, Koc University, Rumelifeneri Yolu, 34450 Sariyer, Istanbul (Turkey); Mehri-Dehnavi, Hossein [Department of Physics, Institute for Advanced Studies in Basic Sciences, Zanjan 45195-1159 (Iran, Islamic Republic of)], E-mail: amostafazadeh@ku.edu.tr, E-mail: mehrideh@iasbs.ac.ir

2009-03-27

A curious feature of complex scattering potentials v(x) is the appearance of spectral singularities. We offer a quantitative description of spectral singularities that identifies them with an obstruction to the existence of a complete biorthonormal system consisting of the eigenfunctions of the Hamiltonian operator and its adjoint. We establish the equivalence of this description with the mathematicians' definition of spectral singularities for the potential v(x) = z{sub -}{delta}(x + a) + z{sub +}{delta}(x - a), where z{sub {+-}} and a are respectively complex and real parameters and {delta}(x) is the Dirac delta function. We offer a through analysis of the spectral properties of this potential and determine the regions in the space of the coupling constants z{sub {+-}} where it admits bound states and spectral singularities. In particular, we find an explicit bound on the size of certain regions in which the Hamiltonian is quasi-Hermitian and examine the consequences of imposing PT-symmetry.

Spectral singularities, biorthonormal systems and a two-parameter family of complex point interactions

International Nuclear Information System (INIS)

Mostafazadeh, Ali; Mehri-Dehnavi, Hossein

2009-01-01

A curious feature of complex scattering potentials v(x) is the appearance of spectral singularities. We offer a quantitative description of spectral singularities that identifies them with an obstruction to the existence of a complete biorthonormal system consisting of the eigenfunctions of the Hamiltonian operator and its adjoint. We establish the equivalence of this description with the mathematicians' definition of spectral singularities for the potential v(x) = z - δ(x + a) + z + δ(x - a), where z ± and a are respectively complex and real parameters and δ(x) is the Dirac delta function. We offer a through analysis of the spectral properties of this potential and determine the regions in the space of the coupling constants z ± where it admits bound states and spectral singularities. In particular, we find an explicit bound on the size of certain regions in which the Hamiltonian is quasi-Hermitian and examine the consequences of imposing PT-symmetry

Onboard spectral imager data processor

Science.gov (United States)

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.

Novel acoustic features for speech emotion recognition

Institute of Scientific and Technical Information of China (English)

ROH; Yong-Wan; KIM; Dong-Ju; LEE; Woo-Seok; HONG; Kwang-Seok

2009-01-01

This paper focuses on acoustic features that effectively improve the recognition of emotion in human speech.The novel features in this paper are based on spectral-based entropy parameters such as fast Fourier transform(FFT) spectral entropy,delta FFT spectral entropy,Mel-frequency filter bank(MFB) spectral entropy,and Delta MFB spectral entropy.Spectral-based entropy features are simple.They reflect frequency characteristic and changing characteristic in frequency of speech.We implement an emotion rejection module using the probability distribution of recognized-scores and rejected-scores.This reduces the false recognition rate to improve overall performance.Recognized-scores and rejected-scores refer to probabilities of recognized and rejected emotion recognition results,respectively.These scores are first obtained from a pattern recognition procedure.The pattern recognition phase uses the Gaussian mixture model(GMM).We classify the four emotional states as anger,sadness,happiness and neutrality.The proposed method is evaluated using 45 sentences in each emotion for 30 subjects,15 males and 15 females.Experimental results show that the proposed method is superior to the existing emotion recognition methods based on GMM using energy,Zero Crossing Rate(ZCR),linear prediction coefficient(LPC),and pitch parameters.We demonstrate the effectiveness of the proposed approach.One of the proposed features,combined MFB and delta MFB spectral entropy improves performance approximately 10% compared to the existing feature parameters for speech emotion recognition methods.We demonstrate a 4% performance improvement in the applied emotion rejection with low confidence score.

Novel acoustic features for speech emotion recognition

Institute of Scientific and Technical Information of China (English)

ROH Yong-Wan; KIM Dong-Ju; LEE Woo-Seok; HONG Kwang-Seok

2009-01-01

This paper focuses on acoustic features that effectively improve the recognition of emotion in human speech. The novel features in this paper are based on spectral-based entropy parameters such as fast Fourier transform (FFT) spectral entropy, delta FFT spectral entropy, Mel-frequency filter bank (MFB)spectral entropy, and Delta MFB spectral entropy. Spectral-based entropy features are simple. They reflect frequency characteristic and changing characteristic in frequency of speech. We implement an emotion rejection module using the probability distribution of recognized-scores and rejected-scores.This reduces the false recognition rate to improve overall performance. Recognized-scores and rejected-scores refer to probabilities of recognized and rejected emotion recognition results, respectively.These scores are first obtained from a pattern recognition procedure. The pattern recognition phase uses the Gaussian mixture model (GMM). We classify the four emotional states as anger, sadness,happiness and neutrality. The proposed method is evaluated using 45 sentences in each emotion for 30 subjects, 15 males and 15 females. Experimental results show that the proposed method is superior to the existing emotion recognition methods based on GMM using energy, Zero Crossing Rate (ZCR),linear prediction coefficient (LPC), and pitch parameters. We demonstrate the effectiveness of the proposed approach. One of the proposed features, combined MFB and delta MFB spectral entropy improves performance approximately 10% compared to the existing feature parameters for speech emotion recognition methods. We demonstrate a 4% performance improvement in the applied emotion rejection with low confidence score.

Fitting Analysis using Differential evolution Optimization (FADO):. Spectral population synthesis through genetic optimization under self-consistency boundary conditions

Science.gov (United States)

Gomes, J. M.; Papaderos, P.

2017-07-01

The goal of population spectral synthesis (pss; also referred to as inverse, semi-empirical evolutionary- or fossil record approach) is to decipher from the spectrum of a galaxy the mass, age and metallicity of its constituent stellar populations. This technique, which is the reverse of but complementary to evolutionary synthesis, has been established as fundamental tool in extragalactic research. It has been extensively applied to large spectroscopic data sets, notably the SDSS, leading to important insights into the galaxy assembly history. However, despite significant improvements over the past decade, all current pss codes suffer from two major deficiencies that inhibit us from gaining sharp insights into the star-formation history (SFH) of galaxies and potentially introduce substantial biases in studies of their physical properties (e.g., stellar mass, mass-weighted stellar age and specific star formation rate). These are I) the neglect of nebular emission in spectral fits, consequently; II) the lack of a mechanism that ensures consistency between the best-fitting SFH and the observed nebular emission characteristics of a star-forming (SF) galaxy (e.g., hydrogen Balmer-line luminosities and equivalent widths-EWs, shape of the continuum in the region around the Balmer and Paschen jump). In this article, we present fado (Fitting Analysis using Differential evolution Optimization) - a conceptually novel, publicly available pss tool with the distinctive capability of permitting identification of the SFH that reproduces the observed nebular characteristics of a SF galaxy. This so-far unique self-consistency concept allows us to significantly alleviate degeneracies in current spectral synthesis, thereby opening a new avenue to the exploration of the assembly history of galaxies. The innovative character of fado is further augmented by its mathematical foundation: fado is the first pss code employing genetic differential evolution optimization. This, in conjunction

Spectral features of tidal disruption candidates and alternative origins for such transient flares

Science.gov (United States)

Saxton, Curtis J.; Perets, Hagai B.; Baskin, Alexei

2018-03-01

UV and optically selected candidates for stellar tidal disruption events (TDEs) often exhibit broad spectral features (He II emission, H α emission, or absorption lines) on a blackbody-like continuum (104 K≲ T≲ 105 K). The lines presumably emit from TDE debris or circumnuclear clouds photoionized by the flare. Line velocities however are much lower than expected from a stellar disruption by supermassive black hole (SMBH), and are somewhat faster than expected for the broad line region (BLR) clouds of a persistently active galactic nucleus (AGN). The distinctive spectral states are not strongly related to observed luminosity and velocity, nor to SMBH mass estimates. We use exhaustive photoionization modelling to map the domain of fluxes and cloud properties that yield (e.g.) an He-overbright state where a large He II(4686 Å)/H α line ratio creates an illusion of helium enrichment. Although observed line ratios occur in a plausible minority of cases, AGN-like illumination cannot reproduce the observed equivalent widths. We therefore propose to explain these properties by a light-echo photoionization model: the initial flash of a hot blackbody (detonation) excites BLR clouds, which are then seen superimposed on continuum from a later, expanded, cooled stage of the luminous source. The implied cloud mass is substellar, which may be inconsistent with a TDE. Given these and other inconsistencies with TDE models (e.g. host-galaxies distribution) we suggest to also consider alternative origins for these nuclear flares, which we briefly discuss (e.g. nuclear supernovae and starved/subluminous AGNs).

Spectral reflectance properties of carbonaceous chondrites: 1. CI chondrites

Science.gov (United States)

Cloutis, E. A.; Hiroi, T.; Gaffey, M. J.; Alexander, C. M. O.'D.; Mann, P.

2011-03-01

Existing reflectance spectra of CI chondrites (18 spectra of 3 CIs) have been augmented with new (18 spectra of 2 CIs) reflectance spectra to ascertain the spectral variability of this meteorite class and provide insights into their spectral properties as a function of grain size, composition, particle packing, and viewing geometry. Particle packing and viewing geometry effects have not previously been examined for CI chondrites. The current analysis is focused on the 0.3-2.5 μm interval, as this region is available for the largest number of CI spectra. Reflectance spectra of powdered CI1 chondrites are uniformly dark (IOM), as no other CI opaque phase appears able to produce concurrent darkening and bluing. Magnetite can also explain the presence of an absorption feature near 1 μm in some CI spectra. The most blue-sloped spectra are generally associated with the larger grain size samples. For incidence and emission angles <60°, increasing phase angle results in darker and redder spectra, particularly below ∼1 μm. At high incidence angles (60°), increasing emission angle results in brighter and redder spectra. More densely packed samples and underdense (fluffed) samples show lower overall reflectance than normally packed and flat-surface powdered samples. Some B-class asteroids exhibit selected spectral properties consistent with CI chondrites, although perfect spectral matches have not been found. Because many CI chondrite spectra exhibit absorption features that can be related to specific mineral phases, the search for CI parent bodies can fruitfully be conducted using such parameters.

SDP_mharwit_1: Demonstration of HIFI Linear Polarization Analysis of Spectral Features

Science.gov (United States)

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.

A multimodal spectral approach to characterize rhythm in natural speech.

Science.gov (United States)

Alexandrou, Anna Maria; Saarinen, Timo; Kujala, Jan; Salmelin, Riitta

2016-01-01

Human utterances demonstrate temporal patterning, also referred to as rhythm. While simple oromotor behaviors (e.g., chewing) feature a salient periodical structure, conversational speech displays a time-varying quasi-rhythmic pattern. Quantification of periodicity in speech is challenging. Unimodal spectral approaches have highlighted rhythmic aspects of speech. However, speech is a complex multimodal phenomenon that arises from the interplay of articulatory, respiratory, and vocal systems. The present study addressed the question of whether a multimodal spectral approach, in the form of coherence analysis between electromyographic (EMG) and acoustic signals, would allow one to characterize rhythm in natural speech more efficiently than a unimodal analysis. The main experimental task consisted of speech production at three speaking rates; a simple oromotor task served as control. The EMG-acoustic coherence emerged as a sensitive means of tracking speech rhythm, whereas spectral analysis of either EMG or acoustic amplitude envelope alone was less informative. Coherence metrics seem to distinguish and highlight rhythmic structure in natural speech.

Mid-Infrared Spectral Properties of IR QSOs

International Nuclear Information System (INIS)

Xia, X. Y.; Cao, C.; Mao, S.; Deng, Z. G.

2008-01-01

We analyse mid-infrared (MIR) spectroscopic properties for 19 ultra-luminous infrared quasars (IR QSOs) in the local universe based on the spectra from the Infrared Spectrograph on board the Spitzer Space Telescope. The MIR properties of IR QSOs are compared with those of optically-selected Palomar-Green QSOs (PG QSOs) and ultra-luminous infrared galaxies (ULIRGs). The average MIR spectral features from ∼5 to 30 μm, including the spectral slopes, 6.2 μm PAH emission strengths and [NeII] 12.81 μm luminosities of IR QSOs, differ from those of PG QSOs. In contrast, IR QSOs and ULIRGs have comparable PAH and [NeII] luminosities. These results are consistent with IR QSOs being at a transitional stage from ULIRGs to classical QSOs. We also find the correlation between the EW (PAH 6.2 μm) and outflow velocities suggests that star formation activities are suppressed by feedback from AGNs and/or supernovae.

A Statistical study of the Doppler spectral width of high-latitude ionospheric F-region echoes recorded with SuperDARN coherent HF radars

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J.-P. Villain

2002-11-01

Full Text Available The HF radars of the Super Dual Auroral Radar Network (SuperDARN provide measurements of the E × B drift of ionospheric plasma over extended regions of the high-latitude ionosphere. We have conducted a statistical study of the associated Doppler spectral width of ionospheric F-region echoes. The study has been conducted with all available radars from the Northern Hemisphere for 2 specific periods of time. Period 1 corresponds to the winter months of 1994, while period 2 covers October 1996 to March 1997. The distributions of data points and average spectral width are presented as a function of Magnetic Latitude and Magnetic Local Time. The databases are very consistent and exhibit the same features. The most stringent features are: a region of very high spectral width, collocated with the ionospheric LLBL/cusp/mantle region; an oval shaped region of high spectral width, whose equator-ward boundary matches the poleward limit of the Holzworth and Meng auroral oval. A simulation has been conducted to evaluate the geometrical and instrumental effects on the spectral width. It shows that these effects cannot account for the observed spectral features. It is then concluded that these specific spectral width characteristics are the signature of ionospheric/magnetospheric coupling phenomena.Key words. Ionosphere (auroral ionosphere; ionosphere-magnetosphere interactions; ionospheric irregularities

A Statistical study of the Doppler spectral width of high-latitude ionospheric F-region echoes recorded with SuperDARN coherent HF radars

Directory of Open Access Journals (Sweden)

J.-P. Villain

Full Text Available The HF radars of the Super Dual Auroral Radar Network (SuperDARN provide measurements of the E × B drift of ionospheric plasma over extended regions of the high-latitude ionosphere. We have conducted a statistical study of the associated Doppler spectral width of ionospheric F-region echoes. The study has been conducted with all available radars from the Northern Hemisphere for 2 specific periods of time. Period 1 corresponds to the winter months of 1994, while period 2 covers October 1996 to March 1997. The distributions of data points and average spectral width are presented as a function of Magnetic Latitude and Magnetic Local Time. The databases are very consistent and exhibit the same features. The most stringent features are: a region of very high spectral width, collocated with the ionospheric LLBL/cusp/mantle region; an oval shaped region of high spectral width, whose equator-ward boundary matches the poleward limit of the Holzworth and Meng auroral oval. A simulation has been conducted to evaluate the geometrical and instrumental effects on the spectral width. It shows that these effects cannot account for the observed spectral features. It is then concluded that these specific spectral width characteristics are the signature of ionospheric/magnetospheric coupling phenomena.

Key words. Ionosphere (auroral ionosphere; ionosphere-magnetosphere interactions; ionospheric irregularities

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

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Daniel Sousa

2018-02-01

Full Text Available 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.

Calibrating spectral images using penalized likelihood

NARCIS (Netherlands)

Heijden, van der G.W.A.M.; Glasbey, C.

2003-01-01

A new method is presented for automatic correction of distortions and for spectral calibration (which band corresponds to which wavelength) of spectral images recorded by means of a spectrograph. The method consists of recording a bar-like pattern with an illumination source with spectral bands

Multi-view 3D echocardiography compounding based on feature consistency

Science.gov (United States)

Yao, Cheng; Simpson, John M.; Schaeffter, Tobias; Penney, Graeme P.

2011-09-01

Echocardiography (echo) is a widely available method to obtain images of the heart; however, echo can suffer due to the presence of artefacts, high noise and a restricted field of view. One method to overcome these limitations is to use multiple images, using the 'best' parts from each image to produce a higher quality 'compounded' image. This paper describes our compounding algorithm which specifically aims to reduce the effect of echo artefacts as well as improving the signal-to-noise ratio, contrast and extending the field of view. Our method weights image information based on a local feature coherence/consistency between all the overlapping images. Validation has been carried out using phantom, volunteer and patient datasets consisting of up to ten multi-view 3D images. Multiple sets of phantom images were acquired, some directly from the phantom surface, and others by imaging through hard and soft tissue mimicking material to degrade the image quality. Our compounding method is compared to the original, uncompounded echocardiography images, and to two basic statistical compounding methods (mean and maximum). Results show that our method is able to take a set of ten images, degraded by soft and hard tissue artefacts, and produce a compounded image of equivalent quality to images acquired directly from the phantom. Our method on phantom, volunteer and patient data achieves almost the same signal-to-noise improvement as the mean method, while simultaneously almost achieving the same contrast improvement as the maximum method. We show a statistically significant improvement in image quality by using an increased number of images (ten compared to five), and visual inspection studies by three clinicians showed very strong preference for our compounded volumes in terms of overall high image quality, large field of view, high endocardial border definition and low cavity noise.

Multi-view 3D echocardiography compounding based on feature consistency

International Nuclear Information System (INIS)

Yao Cheng; Schaeffter, Tobias; Penney, Graeme P; Simpson, John M

2011-01-01

Echocardiography (echo) is a widely available method to obtain images of the heart; however, echo can suffer due to the presence of artefacts, high noise and a restricted field of view. One method to overcome these limitations is to use multiple images, using the 'best' parts from each image to produce a higher quality 'compounded' image. This paper describes our compounding algorithm which specifically aims to reduce the effect of echo artefacts as well as improving the signal-to-noise ratio, contrast and extending the field of view. Our method weights image information based on a local feature coherence/consistency between all the overlapping images. Validation has been carried out using phantom, volunteer and patient datasets consisting of up to ten multi-view 3D images. Multiple sets of phantom images were acquired, some directly from the phantom surface, and others by imaging through hard and soft tissue mimicking material to degrade the image quality. Our compounding method is compared to the original, uncompounded echocardiography images, and to two basic statistical compounding methods (mean and maximum). Results show that our method is able to take a set of ten images, degraded by soft and hard tissue artefacts, and produce a compounded image of equivalent quality to images acquired directly from the phantom. Our method on phantom, volunteer and patient data achieves almost the same signal-to-noise improvement as the mean method, while simultaneously almost achieving the same contrast improvement as the maximum method. We show a statistically significant improvement in image quality by using an increased number of images (ten compared to five), and visual inspection studies by three clinicians showed very strong preference for our compounded volumes in terms of overall high image quality, large field of view, high endocardial border definition and low cavity noise.

Consistently violating the non-Gaussian consistency relation

International Nuclear Information System (INIS)

Mooij, Sander; Palma, Gonzalo A.

2015-01-01

Non-attractor models of inflation are characterized by the super-horizon evolution of curvature perturbations, introducing a violation of the non-Gaussian consistency relation between the bispectrum's squeezed limit and the power spectrum's spectral index. In this work we show that the bispectrum's squeezed limit of non-attractor models continues to respect a relation dictated by the evolution of the background. We show how to derive this relation using only symmetry arguments, without ever needing to solve the equations of motion for the perturbations

Finite-temperature gluon spectral functions from N{sub f} = 2+1+1 lattice QCD

Energy Technology Data Exchange (ETDEWEB)

Ilgenfritz, Ernst-Michael; Trunin, Anton [Joint Institute for Nuclear Research, Bogoliubov Laboratory of Theoretical Physics, Dubna (Russian Federation); Pawlowski, Jan M. [Universitaet Heidelberg, Institut fuer Theoretische Physik, Heidelberg (Germany); ExtreMe Matter Institute EMMI, GSI Helmholtzzentrum fuer Schwerionenforschung mbH, Darmstadt (Germany); Rothkopf, Alexander [Universitaet Heidelberg, Institut fuer Theoretische Physik, Heidelberg (Germany)

2018-02-15

We investigate gluon correlation functions and spectral functions at finite temperature in Landau gauge on lattice QCD ensembles with N{sub f} = 2+1+1 dynamical twisted-mass quarks flavors, generated by the tmfT collaboration. They cover a temperature range from 0.8 ≤ T/T{sub C} ≤ 4 using the fixed-scale approach. Our study of spectral properties is based on a novel Bayesian approach for the extraction of non-positive-definite spectral functions. For each binned spatial momentum we take into account the gluon correlation functions at all available discrete imaginary frequencies. Clear indications for the existence of a well defined quasi-particle peak are obtained. Due to a relatively small number of imaginary frequencies available, we focus on the momentum and temperature dependence of the position of this spectral feature. The corresponding dispersion relation reveals different in-medium masses for longitudinal and transversal gluons at high temperatures, qualitatively consistent with weak coupling expectations. (orig.)

Multi scales based sparse matrix spectral clustering image segmentation

Science.gov (United States)

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.

Multilayer Photonic Crystal for Spectral Narrowing of Emission

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Zhanfang LIU

2017-08-01

Full Text Available Multilayer colloidal crystal has been prepared by the layer-by-layer deposition of silica microspheres on a glass slide. Each layer is a slab consisting of a fcc close-packed colloidal arrays. By properly choosing the sizes of spheres, the whole spectral feature of multilayer colloidal crystal can be tuned. Here, we engineered a multilayer superlattice structure with an effective passband between two stop bands. This gives a strong narrowing effect on emission spectrum. With the stop bands at the shortwave and longwave edges of emission spectrum, the passband in the central wavelength region can be regarded as a strong decrease of suppression effect and enhancement of a narrow wavelength region of emission. The spectral narrowing modification effect of suitably engineered colloidal crystals shows up their importance in potential application as optical filters and lasing devices.DOI: http://dx.doi.org/10.5755/j01.ms.23.3.16320

SPECTRAL CHARACTERISTICS OF SELECTED HERMATYPIC CORALS FROM GULF OF KACHCHH, INDIA

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N. Ray Chaudhury

2012-07-01

Full Text Available Hermatypic, scleractinian corals are the most important benthic substrates in a coral reef ecosystem. The existing, high (spatial resolution, broad-band, multi-spectral, space-borne sensors have limited capability to spatially detect and spectrally discriminate coral substrates. In situ hyperspectral signatures of eight coral targets were collected with the help of Analytical Spectral Devices FieldSpec spectroradiometer from Paga and Laku Point reefs of Gulf of Kachchh, India to study the spectral behaviour of corals. The eight coral targets consisted of seven live corals representing four distinct colony morphologies and one bleached coral target. The coral spectra were studied over a continuous range of 350 to 1350 nm. The corals strongly reflected in the NIR and MIR regions with regional central maximas located at 820 and 1070 nm respectively. In the visible region the live coral spectra conformed to "brown mode" of coral reflectance with triple-peaked pattern at 575, 600 and 650 nm. All coral spectra are characterized with two distinct absorption features: chlorophyll absorption at 675 nm and water absorption at 975 nm. The live and the bleached corals get distinguished in the visible region over 400 to 600 nm region. Water column over the targets modifies the spectral shape and magnitude. First and second-order derivatives help in identifying spectral windows to distinguish live and bleached corals.

THE RESEARCH OF SPECTRAL RECONSTRUCTION FOR LARGE APERTURE STATIC IMAGING SPECTROMETER

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H. Lv

2018-04-01

Full Text Available Imaging spectrometer obtains or indirectly obtains the spectral information of the ground surface feature while obtaining the target image, which makes the imaging spectroscopy has a prominent advantage in fine characterization of terrain features, and is of great significance for the study of geoscience and other related disciplines. Since the interference data obtained by interferometric imaging spectrometer is intermediate data, which must be reconstructed to achieve the high quality spectral data and finally used by users. The difficulty to restrict the application of interferometric imaging spectroscopy is to reconstruct the spectrum accurately. Based on the original image acquired by Large Aperture Static Imaging Spectrometer as the input, this experiment selected the pixel that is identified as crop by artificial recognition, extract and preprocess the interferogram to recovery the corresponding spectrum of this pixel. The result shows that the restructured spectrum formed a small crest near the wavelength of 0.55 μm with obvious troughs on both sides. The relative reflection intensity of the restructured spectrum rises abruptly at the wavelength around 0.7 μm, forming a steep slope. All these characteristics are similar with the spectral reflection curve of healthy green plants. It can be concluded that the experimental result is consistent with the visual interpretation results, thus validating the effectiveness of the scheme for interferometric imaging spectrum reconstruction proposed in this paper.

Running spectral index from large-field inflation with modulations revisited

Energy Technology Data Exchange (ETDEWEB)

Czerny, Michael, E-mail: mczerny@tuhep.phys.tohoku.ac.jp [Department of Physics, Tohoku University, Sendai 980-8578 (Japan); Kobayashi, Takeshi, E-mail: takeshi@cita.utoronto.ca [Canadian Institute for Theoretical Astrophysics, University of Toronto, 60 St. George Street, Toronto, Ontario M5S 3H8 (Canada); Perimeter Institute for Theoretical Physics, 31 Caroline Street North, Waterloo, Ontario N2L 2Y5 (Canada); Takahashi, Fuminobu, E-mail: fumi@tuhep.phys.tohoku.ac.jp [Department of Physics, Tohoku University, Sendai 980-8578 (Japan); Kavli IPMU, TODIAS, University of Tokyo, Kashiwa 277-8583 (Japan)

2014-07-30

We revisit large field inflation models with modulations in light of the recent discovery of the primordial B-mode polarization by the BICEP2 experiment, which, when combined with the Planck+WP+highL data, gives a strong hint for additional suppression of the CMB temperature fluctuations at small scales. Such a suppression can be explained by a running spectral index. In fact, it was pointed out by two of the present authors (TK and FT) that the existence of both tensor mode perturbations and a sizable running of the spectral index is a natural outcome of large inflation models with modulations such as axion monodromy inflation. We find that this holds also in the recently proposed multi-natural inflation, in which the inflaton potential consists of multiple sinusoidal functions and therefore the modulations are a built-in feature.

Spectral characterization of surface emissivities in the thermal infrared

Science.gov (United States)

Niclòs, Raquel; Mira, Maria; Valor, Enric; Caselles, Diego; García-Santos, Vicente; Caselles, Vicente; Sánchez, Juan M.

2015-04-01

Thermal infrared (TIR) remote sensing trends to hyperspectral sensors on board satellites in the last decades, e.g., the current EOS-MODIS and EOS-ASTER and future missions like HyspIRI, ECOSTRESS, THIRSTY and MISTIGRI. This study aims to characterize spectrally the emissive properties of several surfaces, mostly soils. A spectrometer ranging from 2 to 16 μm, D&P Model 102, has been used to measure samples with singular spectral features, e.g. a sandy soil rich in gypsum sampled in White Sands (New Mexico, USA), salt samples, powdered quartz, and powdered calcite. These samples were chosen for their role in the assessment of thermal emissivity of soils, e.g., the calcite and quartz contents are key variables for modeling TIR emissivities of bare soils, along with soil moisture and organic matter. Additionally, the existence of large areas in the world with abundance of these materials, some of them used for calibration/validation activities of satellite sensors and products, makes the chosen samples interesting. White Sands is the world's largest gypsum dune field encompassing 400 km^2; the salt samples characterize the Salar of Uyuni (Bolivia), the largest salt flat in the world (up to 10,000 km^2), as well as the Jordanian and Israeli salt evaporation ponds at the south end of the Dead Sea, or the evaporation lagoons in Aigües-Mortes (France); and quartz is omnipresent in most of the arid regions of the world such as the Algodones Dunes or Kelso Dunes (California, USA), with areas around 700 km2 and 120 km^2, respectively. Measurements of target leaving radiance, hemispherical radiance reflected by a diffuse reflectance panel, and the radiance from a black body at different temperatures were taken to obtain thermal spectra with the D&P spectrometer. The good consistency observed between our measurements and laboratory spectra of similar samples (ASTER and MODIS spectral libraries) indicated the validity of the measurement protocol. Further, our study showed the

Spectral features based tea garden extraction from digital orthophoto maps

Science.gov (United States)

Jamil, Akhtar; Bayram, Bulent; Kucuk, Turgay; Zafer Seker, Dursun

2018-05-01

The advancements in the photogrammetry and remote sensing technologies has made it possible to extract useful tangible information from data which plays a pivotal role in various application such as management and monitoring of forests and agricultural lands etc. This study aimed to evaluate the effectiveness of spectral signatures for extraction of tea gardens from 1 : 5000 scaled digital orthophoto maps obtained from Rize city in Turkey. First, the normalized difference vegetation index (NDVI) was derived from the input images to suppress the non-vegetation areas. NDVI values less than zero were discarded and the output images was normalized in the range 0-255. Individual pixels were then mapped into meaningful objects using global region growing technique. The resulting image was filtered and smoothed to reduce the impact of noise. Furthermore, geometrical constraints were applied to remove small objects (less than 500 pixels) followed by morphological opening operator to enhance the results. These objects served as building blocks for further image analysis. Finally, for the classification stage, a range of spectral values were empirically calculated for each band and applied on candidate objects to extract tea gardens. For accuracy assessment, we employed an area based similarity metric by overlapping obtained tea garden boundaries with the manually digitized tea garden boundaries created by experts of photogrammetry. The overall accuracy of the proposed method scored 89 % for tea gardens from 10 sample orthophoto maps. We concluded that exploiting the spectral signatures using object based analysis is an effective technique for extraction of dominant tree species from digital orthophoto maps.

Spectral split in a prompt supernova neutrino burst: Analytic three-flavor treatment

International Nuclear Information System (INIS)

Dasgupta, Basudeb; Dighe, Amol; Mirizzi, Alessandro; Raffelt, Georg G.

2008-01-01

The prompt ν e burst from a core-collapse supernova is subject to both matter-induced flavor conversions and strong neutrino-neutrino refractive effects. For the lowest-mass progenitors, leading to O-Ne-Mg core supernovae, the matter density profile can be so steep that the usual Mikheyev-Smirnov-Wolfenstein matter effects occur within the dense-neutrino region close to the neutrino sphere. In this case a ''split'' occurs in the emerging spectrum, i.e., the ν e flavor survival probability shows a steplike feature. We explain this feature analytically as a spectral split prepared by the Mikheyev-Smirnov-Wolfenstein effect. In a three-flavor treatment, the steplike feature actually consists of two narrowly spaced splits. They are determined by two combinations of flavor-lepton numbers that are conserved under collective oscillations

Spectral split in a prompt supernova neutrino burst: Analytic three-flavor treatment

Science.gov (United States)

Dasgupta, Basudeb; Dighe, Amol; Mirizzi, Alessandro; Raffelt, Georg G.

2008-06-01

The prompt νe burst from a core-collapse supernova is subject to both matter-induced flavor conversions and strong neutrino-neutrino refractive effects. For the lowest-mass progenitors, leading to O-Ne-Mg core supernovae, the matter density profile can be so steep that the usual Mikheyev-Smirnov-Wolfenstein matter effects occur within the dense-neutrino region close to the neutrino sphere. In this case a “split” occurs in the emerging spectrum, i.e., the νe flavor survival probability shows a steplike feature. We explain this feature analytically as a spectral split prepared by the Mikheyev-Smirnov-Wolfenstein effect. In a three-flavor treatment, the steplike feature actually consists of two narrowly spaced splits. They are determined by two combinations of flavor-lepton numbers that are conserved under collective oscillations.

Biologically-inspired data decorrelation for hyper-spectral imaging

Directory of Open Access Journals (Sweden)

Ghita Ovidiu

2011-01-01

Full Text Available Abstract 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

Spectral synchronicity in brain signals

KAUST Repository

de Jesus Euan Campos, Carolina; Ombao, Hernando; Ortega, Joaquí n

2018-01-01

This paper addresses the problem of identifying brain regions with similar oscillatory patterns detected from electroencephalograms. We introduce the hierarchical spectral merger (HSM) clustering method where the feature of interest is the spectral curve and the similarity metric used is the total variance distance. The HSM method is compared with clustering using features derived from independent-component analysis. Moreover, the HSM method is applied to 2 different electroencephalogram datasets. The first was recorded at resting state where the participant was not engaged in any cognitive task; the second was recorded during a spontaneous epileptic seizure. The results of the analyses using the HSM method demonstrate that clustering could evolve over the duration of the resting state and during epileptic seizure.

Spectral synchronicity in brain signals

KAUST Repository

de Jesus Euan Campos, Carolina

2018-05-04

This paper addresses the problem of identifying brain regions with similar oscillatory patterns detected from electroencephalograms. We introduce the hierarchical spectral merger (HSM) clustering method where the feature of interest is the spectral curve and the similarity metric used is the total variance distance. The HSM method is compared with clustering using features derived from independent-component analysis. Moreover, the HSM method is applied to 2 different electroencephalogram datasets. The first was recorded at resting state where the participant was not engaged in any cognitive task; the second was recorded during a spontaneous epileptic seizure. The results of the analyses using the HSM method demonstrate that clustering could evolve over the duration of the resting state and during epileptic seizure.

Guilt by Association: The 13 micron Dust Feature in Circumstellar Shells and Related Spectral Features

Science.gov (United States)

Sloan, G. C.; Kraemer, K. E.; Goebel, J. H.; Price, S. D.

A study of spectra from the SWS on ISO of optically thin oxygen-rich dust shells shows that the strength of the 13 micron dust emission feature is correlated with the CO2 bands (13--17 microns) and dust emission features at 19.8 and 28.1 microns. SRb variables tend to show stronger 13 micron features than Mira variables, suggesting that the presence of the 13 micron and related features depends on pulsation mode and mass-loss rate. The absence of any correlation to dust emission features at 16.8 and 32 microns makes spinel an unlikely carrier. The most plausible carrier of the 13 micron feature remains crystalline alumina, and we suggest that the related dust features may be crystalline silicates. When dust forms in regions of low density, it may condense into crystalline grain structures.

[Review of digital ground object spectral library].

Science.gov (United States)

Zhou, Xiao-Hu; Zhou, Ding-Wu

2009-06-01

A higher spectral resolution is the main direction of developing remote sensing technology, and it is quite important to set up the digital ground object reflectance spectral database library, one of fundamental research fields in remote sensing application. Remote sensing application has been increasingly relying on ground object spectral characteristics, and quantitative analysis has been developed to a new stage. The present article summarized and systematically introduced the research status quo and development trend of digital ground object reflectance spectral libraries at home and in the world in recent years. Introducing the spectral libraries has been established, including desertification spectral database library, plants spectral database library, geological spectral database library, soil spectral database library, minerals spectral database library, cloud spectral database library, snow spectral database library, the atmosphere spectral database library, rocks spectral database library, water spectral database library, meteorites spectral database library, moon rock spectral database library, and man-made materials spectral database library, mixture spectral database library, volatile compounds spectral database library, and liquids spectral database library. In the process of establishing spectral database libraries, there have been some problems, such as the lack of uniform national spectral database standard and uniform standards for the ground object features as well as the comparability between different databases. In addition, data sharing mechanism can not be carried out, etc. This article also put forward some suggestions on those problems.

Comprehensive spectral and instrumental approaches for the easy monitoring of features and purity of different carbon nanostructures for nanocomposite applications

International Nuclear Information System (INIS)

Boccaleri, Enrico; Arrais, Aldo; Frache, Alberto; Gianelli, Walter; Fino, Paolo; Camino, Giovanni

2006-01-01

A wide series of carbon nanostructures (ranging from fullerenes, through carbon nanotubes, up to carbon nanofibers) promise to change several fields in material science, but a real industrial implementation depends on their availability at reasonable prices with affordable and reproducible degrees of purity. In this study we propose simple instrumental approaches to efficiently characterize different commercial samples, particularly for qualitative evaluation of impurities, the discrimination of their respective spectral features and, when possible, for quantitative determination. We critically discuss information that researchers in the field of nanocomposite technology can achieve in this aim by spectral techniques such as Raman and FT-IR spectroscopy, thermo-gravimetrical analysis, mass spectrometry-hyphenated thermogravimetry, X-ray diffraction and energy dispersive spectroscopy. All these can be helpful, in applied research on material science, for a fast reliable monitoring of the actual purity of carbon products in both commercial and laboratory-produced samples as well as in composite materials

PHROG: A Multimodal Feature for Place Recognition

Directory of Open Access Journals (Sweden)

Fabien Bonardi

2017-05-01

Full Text Available Long-term place recognition in outdoor environments remains a challenge due to high appearance changes in the environment. The problem becomes even more difficult when the matching between two scenes has to be made with information coming from different visual sources, particularly with different spectral ranges. For instance, an infrared camera is helpful for night vision in combination with a visible camera. In this paper, we emphasize our work on testing usual feature point extractors under both constraints: repeatability across spectral ranges and long-term appearance. We develop a new feature extraction method dedicated to improve the repeatability across spectral ranges. We conduct an evaluation of feature robustness on long-term datasets coming from different imaging sources (optics, sensors size and spectral ranges with a Bag-of-Words approach. The tests we perform demonstrate that our method brings a significant improvement on the image retrieval issue in a visual place recognition context, particularly when there is a need to associate images from various spectral ranges such as infrared and visible: we have evaluated our approach using visible, Near InfraRed (NIR, Short Wavelength InfraRed (SWIR and Long Wavelength InfraRed (LWIR.

SPATIAL-SPECTRAL CLASSIFICATION BASED ON THE UNSUPERVISED CONVOLUTIONAL SPARSE AUTO-ENCODER FOR HYPERSPECTRAL REMOTE SENSING IMAGERY

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X. Han

2016-06-01

Full Text Available Current hyperspectral remote sensing imagery spatial-spectral classification methods mainly consider concatenating the spectral information vectors and spatial information vectors together. However, the combined spatial-spectral information vectors may cause information loss and concatenation deficiency for the classification task. To efficiently represent the spatial-spectral feature information around the central pixel within a neighbourhood window, the unsupervised convolutional sparse auto-encoder (UCSAE with window-in-window selection strategy is proposed in this paper. Window-in-window selection strategy selects the sub-window spatial-spectral information for the spatial-spectral feature learning and extraction with the sparse auto-encoder (SAE. Convolution mechanism is applied after the SAE feature extraction stage with the SAE features upon the larger outer window. The UCSAE algorithm was validated by two common hyperspectral imagery (HSI datasets – Pavia University dataset and the Kennedy Space Centre (KSC dataset, which shows an improvement over the traditional hyperspectral spatial-spectral classification methods.

A Spectral Unmixing Model for the Integration of Multi-Sensor Imagery: A Tool to Generate Consistent Time Series Data

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Georgia Doxani

2015-10-01

Full Text Available The Sentinel missions have been designed to support the operational services of the Copernicus program, ensuring long-term availability of data for a wide range of spectral, spatial and temporal resolutions. In particular, Sentinel-2 (S-2 data with improved high spatial resolution and higher revisit frequency (five days with the pair of satellites in operation will play a fundamental role in recording land cover types and monitoring land cover changes at regular intervals. Nevertheless, cloud coverage usually hinders the time series availability and consequently the continuous land surface monitoring. In an attempt to alleviate this limitation, the synergistic use of instruments with different features is investigated, aiming at the future synergy of the S-2 MultiSpectral Instrument (MSI and Sentinel-3 (S-3 Ocean and Land Colour Instrument (OLCI. To that end, an unmixing model is proposed with the intention of integrating the benefits of the two Sentinel missions, when both in orbit, in one composite image. The main goal is to fill the data gaps in the S-2 record, based on the more frequent information of the S-3 time series. The proposed fusion model has been applied on MODIS (MOD09GA L2G and SPOT4 (Take 5 data and the experimental results have demonstrated that the approach has high potential. However, the different acquisition characteristics of the sensors, i.e. illumination and viewing geometry, should be taken into consideration and bidirectional effects correction has to be performed in order to reduce noise in the reflectance time series.

Ultraviolet spectral reflectance of carbonaceous materials

Science.gov (United States)

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.

Consistency-dependent optical properties of lubricating grease studied by terahertz spectroscopy

International Nuclear Information System (INIS)

Tian Lu; Zhao Kun; Zhou Qing-Li; Shi Yu-Lei; Zhao Dong-Mei; Zhang Cun-Lin; Zhao Song-Qing; Zhao Hui; Bao Ri-Ma; Zhu Shou-Ming; Miao Qing

2011-01-01

The optical properties of four kinds of lubricating greases (urea, lithium, extreme pressure lithium, molybdenum disulfide lithium greases) with different NLGL (National Lubricant Grease Institute of America) numbers were investigated using terahertz time-domain spectroscopy. Greases with different NLGL grades have unique spectral features in the terahertz range. Comparison of the experimental data with predictions based on Lorentz—Lorenz theory exhibited that the refractive indices of each kind of lubricating grease were dependent on the their consistency. In addition, molybdenum disulfide (MoS 2 ) as a libricant additive shows strong absorption from 0.2 to 1.4 THz, leading to higher absorption of MoS 2 -lithium grease than that of lithium grease. (general)

Accurate X-Ray Spectral Predictions: An Advanced Self-Consistent-Field Approach Inspired by Many-Body Perturbation Theory.

Science.gov (United States)

Liang, Yufeng; Vinson, John; Pemmaraju, Sri; Drisdell, Walter S; Shirley, Eric L; Prendergast, David

2017-03-03

Constrained-occupancy delta-self-consistent-field (ΔSCF) methods and many-body perturbation theories (MBPT) are two strategies for obtaining electronic excitations from first principles. Using the two distinct approaches, we study the O 1s core excitations that have become increasingly important for characterizing transition-metal oxides and understanding strong electronic correlation. The ΔSCF approach, in its current single-particle form, systematically underestimates the pre-edge intensity for chosen oxides, despite its success in weakly correlated systems. By contrast, the Bethe-Salpeter equation within MBPT predicts much better line shapes. This motivates one to reexamine the many-electron dynamics of x-ray excitations. We find that the single-particle ΔSCF approach can be rectified by explicitly calculating many-electron transition amplitudes, producing x-ray spectra in excellent agreement with experiments. This study paves the way to accurately predict x-ray near-edge spectral fingerprints for physics and materials science beyond the Bethe-Salpether equation.

Diagnostic spectral characteristics of damouritization in granite type uranium deposit

International Nuclear Information System (INIS)

He Jianguo; Mao Yuxian; Li Jianzhong; Wang Changliang; Feng Mingyue; Rong Jiashu; Zhu Minqiang; Rao Minghui

2008-01-01

Spectral characteristics of different alteration type in uranium deposit are the prerequisite of selecting remote sensing spectral bands for uranium reconnaissance and exploration. It is also a basis for mapping alteration zone using imaging spectral data. Taking the No. 201 uranium deposit as example, the paper is focused on the spectral characteristics researching of damouritization in granite type uranium deposite. Through extracting diagnostic spectral feature of damourite and analyzing the reason causing absorption valley, it was found that spectral characteristics of damouritization in Chinese uranium deposit is different from that of illite in the spectral library published abroad. (authors)

Diagnostic spectral characteristics of damouritization in granite type uranium deposit

Energy Technology Data Exchange (ETDEWEB)

Jianguo, He; Yuxian, Mao; Jianzhong, Li; Changliang, Wang; Mingyue, Feng; Jiashu, Rong [Beijing Research Inst. of Uranium Geology, Beijing (China); Minqiang, Zhu; Minghui, Rao [East China Univ. of Technology, Fuzhou (China)

2008-07-15

Spectral characteristics of different alteration type in uranium deposit are the prerequisite of selecting remote sensing spectral bands for uranium reconnaissance and exploration. It is also a basis for mapping alteration zone using imaging spectral data. Taking the No. 201 uranium deposit as example, the paper is focused on the spectral characteristics researching of damouritization in granite type uranium deposite. Through extracting diagnostic spectral feature of damourite and analyzing the reason causing absorption valley, it was found that spectral characteristics of damouritization in Chinese uranium deposit is different from that of illite in the spectral library published abroad. (authors)

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

Energy Technology Data Exchange (ETDEWEB)

Cina, Jeffrey A., E-mail: cina@uoregon.edu; Kovac, Philip A. [Department of Chemistry and Biochemistry, and Oregon Center for Optical, Molecular, and Quantum Science, University of Oregon, Eugene, Oregon 97403 (United States); Jumper, Chanelle C. [Department of Chemistry, University of Toronto, Toronto, Ontario M5S 3H6 (Canada); Dean, Jacob C.; Scholes, Gregory D., E-mail: gscholes@princeton.edu [Department of Chemistry, Princeton University, Princeton, New Jersey 08544 (United States)

2016-05-07

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 a 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.

Evaluation of EEG Features in Decoding Individual Finger Movements from One Hand

Directory of Open Access Journals (Sweden)

Ran Xiao

2013-01-01

Full Text Available With the advancements in modern signal processing techniques, the field of brain-computer interface (BCI is progressing fast towards noninvasiveness. One challenge still impeding these developments is the limited number of features, especially movement-related features, available to generate control signals for noninvasive BCIs. A few recent studies investigated several movement-related features, such as spectral features in electrocorticography (ECoG data obtained through a spectral principal component analysis (PCA and direct use of EEG temporal data, and demonstrated the decoding of individual fingers. The present paper evaluated multiple movement-related features under the same task, that is, discriminating individual fingers from one hand using noninvasive EEG. The present results demonstrate the existence of a broadband feature in EEG to discriminate individual fingers, which has only been identified previously in ECoG. It further shows that multiple spectral features obtained from the spectral PCA yield an average decoding accuracy of 45.2%, which is significantly higher than the guess level (P<0.05 and other features investigated (P<0.05, including EEG spectral power changes in alpha and beta bands and EEG temporal data. The decoding of individual fingers using noninvasive EEG is promising to improve number of features for control, which can facilitate the development of noninvasive BCI applications with rich complexity.

Manifold learning based feature extraction for classification of hyper-spectral data

CSIR Research Space (South Africa)

Lunga, D

2013-08-01

Full Text Available Advances in hyperspectral sensing provide new capability for characterizing spectral signatures in a wide range of physical and biological systems, while inspiring new methods for extracting information from these data. Hyperspectral image data...

Algorithms for Spectral Decomposition with Applications

Data.gov (United States)

National Aeronautics and Space Administration — The analysis of spectral signals for features that represent physical phenomenon is ubiquitous in the science and engineering communities. There are two main...

Spectral Properties, Generation Order Parameters, and Luminosities for Spin-powered X-Ray Pulsars

Science.gov (United States)

Wang, Wei; Zhao, Yongheng

2004-02-01

We show the spectral properties of 15 spin-powered X-ray pulsars, and the correlation between the average power-law photon index and spin-down rate. Generation order parameters (GOPs) based on polar cap models are introduced to characterize the X-ray pulsars. We calculate three definitions of generation order parameters arising from the different effects of magnetic and electric fields on photon absorption during cascade processes, and study the relations between the GOPs and spectral properties of X-ray pulsars. There exists a possible correlation between the photon index and GOP in our pulsar sample. Furthermore, we present a method stemming from the concept of GOPs to estimate the nonthermal X-ray luminosity for spin-powered pulsars. Then X-ray luminosity is calculated in the context of our polar cap accelerator model, which is consistent with most observed X-ray pulsar data. The ratio between the X-ray luminosity estimated by our method and the pulsar's spin-down power is consistent with the LX~10-3Lsd feature.

A consistency-based feature selection method allied with linear SVMs for HIV-1 protease cleavage site prediction.

Directory of Open Access Journals (Sweden)

Orkun Oztürk

Full Text Available BACKGROUND: Predicting type-1 Human Immunodeficiency Virus (HIV-1 protease cleavage site in protein molecules and determining its specificity is an important task which has attracted considerable attention in the research community. Achievements in this area are expected to result in effective drug design (especially for HIV-1 protease inhibitors against this life-threatening virus. However, some drawbacks (like the shortage of the available training data and the high dimensionality of the feature space turn this task into a difficult classification problem. Thus, various machine learning techniques, and specifically several classification methods have been proposed in order to increase the accuracy of the classification model. In addition, for several classification problems, which are characterized by having few samples and many features, selecting the most relevant features is a major factor for increasing classification accuracy. RESULTS: We propose for HIV-1 data a consistency-based feature selection approach in conjunction with recursive feature elimination of support vector machines (SVMs. We used various classifiers for evaluating the results obtained from the feature selection process. We further demonstrated the effectiveness of our proposed method by comparing it with a state-of-the-art feature selection method applied on HIV-1 data, and we evaluated the reported results based on attributes which have been selected from different combinations. CONCLUSION: Applying feature selection on training data before realizing the classification task seems to be a reasonable data-mining process when working with types of data similar to HIV-1. On HIV-1 data, some feature selection or extraction operations in conjunction with different classifiers have been tested and noteworthy outcomes have been reported. These facts motivate for the work presented in this paper. SOFTWARE AVAILABILITY: The software is available at http

An Extended Spectral-Spatial Classification Approach for Hyperspectral Data

Science.gov (United States)

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.

Reconfiguration of spectral absorption features using a frequency-chirped laser pulse.

Science.gov (United States)

Tian, Mingzhen; Chang, Tiejun; Merkel, Kristian D; Babbitt, W Randall

2011-12-20

A technique is proposed to manipulate atomic population in an inhomogeneously broadened medium, which can set an arbitrary absorption spectrum to a uniform transparency (erasure) or to a nearly complete inversion. These reconfigurations of atomic spectral distribution are achieved through excitation of electronic transitions using a laser pulse with chirped frequency, which precisely affects selected spectral regions while leaving the rest of the spectrum unperturbed. An erasure operation sets the final atomic population inversion to zero and the inversion operation flips the population between the ground and the excited states, regardless of the previously existing population distribution. This technique finds important applications both in optical signal processing, where fast, recursive processing and high dynamic range are desirable and in quantum memory and quantum computing, which both require high efficiency and high fidelity in quantum state preparation of atomic ensembles. Proof-of-concept demonstrations were performed in a rare-earth doped crystal.

Speech recognition using articulatory and excitation source features

CERN Document Server

Rao, K Sreenivasa

2017-01-01

This book discusses the contribution of articulatory and excitation source information in discriminating sound units. The authors focus on excitation source component of speech -- and the dynamics of various articulators during speech production -- for enhancement of speech recognition (SR) performance. Speech recognition is analyzed for read, extempore, and conversation modes of speech. Five groups of articulatory features (AFs) are explored for speech recognition, in addition to conventional spectral features. Each chapter provides the motivation for exploring the specific feature for SR task, discusses the methods to extract those features, and finally suggests appropriate models to capture the sound unit specific knowledge from the proposed features. The authors close by discussing various combinations of spectral, articulatory and source features, and the desired models to enhance the performance of SR systems.

Visible Near-infrared Spectral Evolution of Irradiated Mixed Ices and Application to Kuiper Belt Objects and Jupiter Trojans

Science.gov (United States)

Poston, Michael J.; Mahjoub, Ahmed; Ehlmann, Bethany L.; Blacksberg, Jordana; Brown, Michael E.; Carlson, Robert W.; Eiler, John M.; Hand, Kevin P.; Hodyss, Robert; Wong, Ian

2018-04-01

Understanding the history of Kuiper Belt Objects and Jupiter Trojans will help to constrain models of solar system formation and dynamical evolution. Laboratory simulations of a possible thermal and irradiation history of these bodies were conducted on ice mixtures while monitoring their spectral properties. These simulations tested the hypothesis that the presence or absence of sulfur explains the two distinct visible near-infrared spectral groups observed in each population and that Trojans and KBOs share a common formation location. Mixed ices consisting of water, methanol, and ammonia, in mixtures both with and without hydrogen sulfide, were deposited and irradiated with 10 keV electrons. Deposition and initial irradiation were performed at 50 K to simulate formation at 20 au in the early solar system, then heated to Trojan-like temperatures and irradiated further. Finally, irradiation was concluded and resulting samples were observed during heating to room temperature. Results indicated that the presence of sulfur resulted in steeper spectral slopes. Heating through the 140–200 K range decreased the slopes and total reflectance for both mixtures. In addition, absorption features at 410, 620, and 900 nm appeared under irradiation, but only in the H2S-containing mixture. These features were lost with heating once irradiation was concluded. While the results reported here are consistent with the hypothesis, additional work is needed to address uncertainties and to simulate conditions not included in the present work.

Spectral characterization of natural backgrounds

Science.gov (United States)

Winkelmann, Max

2017-10-01

As the distribution and use of hyperspectral sensors is constantly increasing, the exploitation of spectral features is a threat for camouflaged objects. To improve camouflage materials at first the spectral behavior of backgrounds has to be known to adjust and optimize the spectral reflectance of camouflage materials. In an international effort, the NATO CSO working group SCI-295 "Development of Methods for Measurements and Evaluation of Natural Background EO Signatures" is developing a method how this characterization of backgrounds has to be done. It is obvious that the spectral characterization of a background will be quite an effort. To compare and exchange data internationally the measurements will have to be done in a similar way. To test and further improve this method an international field trial has been performed in Storkow, Germany. In the following we present first impressions and lessons learned from this field campaign and describe the data that has been measured.

Significance of Joint Features Derived from the Modified Group Delay Function in Speech Processing

Directory of Open Access Journals (Sweden)

Murthy Hema A

2007-01-01

Full Text Available This paper investigates the significance of combining cepstral features derived from the modified group delay function and from the short-time spectral magnitude like the MFCC. The conventional group delay function fails to capture the resonant structure and the dynamic range of the speech spectrum primarily due to pitch periodicity effects. The group delay function is modified to suppress these spikes and to restore the dynamic range of the speech spectrum. Cepstral features are derived from the modified group delay function, which are called the modified group delay feature (MODGDF. The complementarity and robustness of the MODGDF when compared to the MFCC are also analyzed using spectral reconstruction techniques. Combination of several spectral magnitude-based features and the MODGDF using feature fusion and likelihood combination is described. These features are then used for three speech processing tasks, namely, syllable, speaker, and language recognition. Results indicate that combining MODGDF with MFCC at the feature level gives significant improvements for speech recognition tasks in noise. Combining the MODGDF and the spectral magnitude-based features gives a significant increase in recognition performance of 11% at best, while combining any two features derived from the spectral magnitude does not give any significant improvement.

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

Science.gov (United States)

Paul, Subir; Nagesh Kumar, D.

2018-04-01

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

Chebyshev super spectral viscosity method for water hammer analysis

Directory of Open Access Journals (Sweden)

Hongyu Chen

2013-09-01

Full Text Available In this paper, a new fast and efficient algorithm, Chebyshev super spectral viscosity (SSV method, is introduced to solve the water hammer equations. Compared with standard spectral method, the method's advantage essentially consists in adding a super spectral viscosity to the equations for the high wave numbers of the numerical solution. It can stabilize the numerical oscillation (Gibbs phenomenon and improve the computational efficiency while discontinuities appear in the solution. Results obtained from the Chebyshev super spectral viscosity method exhibit greater consistency with conventional water hammer calculations. It shows that this new numerical method offers an alternative way to investigate the behavior of the water hammer in propellant pipelines.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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 identification of plant communities for mapping of semi-natural grasslands

DEFF Research Database (Denmark)

Jacobsen, Anne; Nielsen, Allan Aasbjerg; Ejrnæs, Rasmus

2000-01-01

identification of plant communities was based on a hierarchical approach relating the test sites to i) management (Ma) and ii) flora (Fl) using spectral consistency and separability as the main criteria. Evaluation of spectral consistency was based on unsupervised clustering of test sites of Ma classes 1 to 7...... as a measure of plant community heterogeneity within management classes. The spectral analysis as well as the maximum likelihood classification indicated that the source of spectral variation within management classes might be related to vegetation composition....

X-ray spectral components observed in the afterglow of GRB 130925A

DEFF Research Database (Denmark)

Bellm, Eric C.; Barrière, Nicolas M.; Bhalerao, Varun

2014-01-01

We have identified spectral features in the late-time X-ray afterglow of the unusually long, slow-decaying GRB 130925A using NuSTAR, Swift/X-Ray Telescope, and Chandra. A spectral component in addition to an absorbed power law is required at >4σ significance, and its spectral shape varies between...... two observation epochs at 2 × 105 and 106 s after the burst. Several models can fit this additional component, each with very different physical implications. A broad, resolved Gaussian absorption feature of several keV width improves the fit, but it is poorly constrained in the second epoch...

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

Science.gov (United States)

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.

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

Science.gov (United States)

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

2018-01-01

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

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

Science.gov (United States)

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

The Spectral Properties of Gamma-ray Bursts: a Review of Recent Development

Science.gov (United States)

Teegarden, B. J.

1983-01-01

Developments in the spectroscopy of gamma ray bursts (GRB) are reviewed. The general question of the validity of the spectral results, particularly with regard to features in the spectrum, is discussed. Confirmations of these spectral features are summarized. Results from the KONUS experiments on Venera 13 and 14 are reviewed. The status of models of the continuum spectrum is summarized. A number of different radiation mechanisms appear capable of fitting the data. These include thermal bremsstrahlung, thermal synchrotron and inverse Compton. Rapid variability of the spectra shape on time scales 76] 0.25 sec. was reported. The characteristic energy of the spectrum was observed to vary over nearly an order of magnitude during individual events. A strong correlation between spectral hardness and luminosity was found. Low-energy (50 keV) absorption features and high-energy (400 keV) emission features continue to appear in GRB spectra. Understanding the origin of these lines in the context of the existing continuum models remains a difficult problem.

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

Science.gov (United States)

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.

Evolving spectral transformations for multitemporal information extraction using evolutionary computation

Science.gov (United States)

Momm, Henrique; Easson, Greg

2011-01-01

Remote sensing plays an important role in assessing temporal changes in land features. The challenge often resides in the conversion of large quantities of raw data into actionable information in a timely and cost-effective fashion. To address this issue, research was undertaken to develop an innovative methodology integrating biologically-inspired algorithms with standard image classification algorithms to improve information extraction from multitemporal imagery. Genetic programming was used as the optimization engine to evolve feature-specific candidate solutions in the form of nonlinear mathematical expressions of the image spectral channels (spectral indices). The temporal generalization capability of the proposed system was evaluated by addressing the task of building rooftop identification from a set of images acquired at different dates in a cross-validation approach. The proposed system generates robust solutions (kappa values > 0.75 for stage 1 and > 0.4 for stage 2) despite the statistical differences between the scenes caused by land use and land cover changes coupled with variable environmental conditions, and the lack of radiometric calibration between images. Based on our results, the use of nonlinear spectral indices enhanced the spectral differences between features improving the clustering capability of standard classifiers and providing an alternative solution for multitemporal information extraction.

Feature level fusion for enhanced geological mapping of ophiolile complex using ASTER and Landsat TM data

International Nuclear Information System (INIS)

Pournamdari, M; Hashim, M

2014-01-01

Chromite ore deposit occurrence is related to ophiolite complexes as a part of the oceanic crust and provides a good opportunity for lithological mapping using remote sensing data. The main contribution of this paper is a novel approaches to discriminate different rock units associated with ophiolite complex using the Feature Level Fusion technique on ASTER and Landsat TM satellite data at regional scale. In addition this study has applied spectral transform approaches, consisting of Spectral Angle Mapper (SAM) to distinguish the concentration of high-potential areas of chromite and also for determining the boundary between different rock units. Results indicated both approaches show superior outputs compared to other methods and can produce a geological map for ophiolite complex rock units in the arid and the semi-arid region. The novel technique including feature level fusion and Spectral Angle Mapper (SAM) discriminated ophiolitic rock units and produced detailed geological maps of the study area. As a case study, Sikhoran ophiolite complex located in SE, Iran has been selected for image processing techniques. In conclusion, a suitable approach for lithological mapping of ophiolite complexes is demonstrated, this technique contributes meaningfully towards economic geology in terms of identifying new prospects

Aftereffects of Spectrally Similar and Dissimilar Spectral Motion Adaptors in the Tritone Paradox

Directory of Open Access Journals (Sweden)

Stephanie Malek

2018-05-01

Full Text Available Shepard tones consist of octave-spaced components, whose amplitudes are generated under a fixed bell-shaped spectral envelope. They are well defined in pitch chroma, but generate octave confusions that in turn can produce ambiguities in the perceived relative pitch heights when their chromas are exactly a tritone apart (the tritone paradox. This study examined the effects of tonal context on relative pitch height judgments using adaptor sequences followed by target sequences (pairs of Shepard tones of different chromas separated by a tritone. Listeners judged whether the second target Shepard tone was higher or lower than the first. Adaptor sequences consisted of rising or falling scales (43 s at the beginning of each block, 4 s before each target sequence. Two sets of Shepard tones were used for adaptors and targets that were generated under spectral envelopes centered at either A3 (220 Hz and C6 (1,046 Hz. Pitch direction judgments (rising vs. falling to spectrally consistent (A3–A3, C6–C6 and inconsistent (A3–C6, C6–A3 adaptor-target combinations were studied. Large significant contrastive aftereffects (0.08–0.21 change in fraction of pitch direction responses were only found for the Shepard tones that were judged as higher in the control condition (judgments about the target sequences without adaptor sequences for the consistent adaptor-target conditions (A3–A3, C6–C6. The experiments rule out explanations based on non-sensory decision making processes. Possible explanations in terms of perceptual aftereffects caused by adaptation in central auditory frequency-motion detectors are discussed.

Tree species mapping in tropical forests using multi-temporal imaging spectroscopy: Wavelength adaptive spectral mixture analysis

Science.gov (United States)

Somers, B.; Asner, G. P.

2014-09-01

The use of imaging spectroscopy for florisic mapping of forests is complicated by the spectral similarity among co-existing species. Here we evaluated an alternative spectral unmixing strategy combining a time series of EO-1 Hyperion images and an automated feature selection in Multiple Endmember Spectral Mixture Analysis (MESMA). The temporal analysis provided a way to incorporate species phenology while feature selection indicated the best phenological time and best spectral feature set to optimize the separability between tree species. Instead of using the same set of spectral bands throughout the image which is the standard approach in MESMA, our modified Wavelength Adaptive Spectral Mixture Analysis (WASMA) approach allowed the spectral subsets to vary on a per pixel basis. As such we were able to optimize the spectral separability between the tree species present in each pixel. The potential of the new approach for floristic mapping of tree species in Hawaiian rainforests was quantitatively assessed using both simulated and actual hyperspectral image time-series. With a Cohen's Kappa coefficient of 0.65, WASMA provided a more accurate tree species map compared to conventional MESMA (Kappa = 0.54; p-value < 0.05. The flexible or adaptive use of band sets in WASMA provides an interesting avenue to address spectral similarities in complex vegetation canopies.

An inverse spectral problem related to the Geng-Xue two-component peakon equation

CERN Document Server

Lundmark, Hans

2016-01-01

The authors solve a spectral and an inverse spectral problem arising in the computation of peakon solutions to the two-component PDE derived by Geng and Xue as a generalization of the Novikov and Degasperisâe"Procesi equations. Like the spectral problems for those equations, this one is of a âeoediscrete cubic stringâe typeâe"a nonselfadjoint generalization of a classical inhomogeneous stringâe"but presents some interesting novel features: there are two Lax pairs, both of which contribute to the correct complete spectral data, and the solution to the inverse problem can be expressed using quantities related to Cauchy biorthogonal polynomials with two different spectral measures. The latter extends the range of previous applications of Cauchy biorthogonal polynomials to peakons, which featured either two identical, or two closely related, measures. The method used to solve the spectral problem hinges on the hidden presence of oscillatory kernels of Gantmacherâe"Krein type, implying that the spectrum of...

Amplified emission and modified spectral features in an opal hetero-structure mediated by passive defect mode localization

Science.gov (United States)

Rout, Dipak; Kumar, Govind; Vijaya, R.

2018-01-01

A photonic crystal hetero-structure consisting of a passive planar defect of SiO2 thin film sandwiched between two identical opals grown by inward growing self-assembly method using Rhodamine-B dye-doped polystyrene microspheres is studied for the characteristics of dye emission. The optical properties and the defect mode characteristics of the hetero-structure are studied from the reflection and transmission measurements. Laser-induced fluorescence from the hetero-structure showed amplified and spectrally narrowed emission compared to the photonic crystal emphasizing the role of the defect mode and distributed feedback. The enhanced emission is also complemented by the reduction in fluorescence decay time in the case of the hetero-structure in comparison to the 3D photonic crystals.

Speech recognition from spectral dynamics

Indian Academy of Sciences (India)

Some of the history of gradual infusion of the modulation spectrum concept into Automatic recognition of speech (ASR) comes next, pointing to the relationship of modulation spectrum processing to wellaccepted ASR techniques such as dynamic speech features or RelAtive SpecTrAl (RASTA) filtering. Next, the frequency ...

IDENTIFYING PLANETARY BIOSIGNATURE IMPOSTORS: SPECTRAL FEATURES OF CO AND O{sub 4} RESULTING FROM ABIOTIC O{sub 2}/O{sub 3} PRODUCTION

Energy Technology Data Exchange (ETDEWEB)

Schwieterman, Edward W.; Meadows, Victoria S.; Arney, Giada N.; Luger, Rodrigo; Misra, Amit; Barnes, Rory [Astronomy Department, University of Washington, Box 351580, Seattle, WA 98195 (United States); Domagal-Goldman, Shawn D.; Deming, Drake; Harman, Chester E., E-mail: eschwiet@uw.edu [NASA Astrobiology Institute’s Virtual Planetary Laboratory, Seattle, WA 981195 (United States)

2016-03-01

O{sub 2} and O{sub 3} have been long considered the most robust individual biosignature gases in a planetary atmosphere, yet multiple mechanisms that may produce them in the absence of life have been described. However, these abiotic planetary mechanisms modify the environment in potentially identifiable ways. Here we briefly discuss two of the most detectable spectral discriminants for abiotic O{sub 2}/O{sub 3}: CO and O{sub 4}. We produce the first explicit self-consistent simulations of these spectral discriminants as they may be seen by James Webb Space Telescope (JWST). If JWST-NIRISS and/or NIRSpec observe CO (2.35, 4.6 μm) in conjunction with CO{sub 2} (1.6, 2.0, 4.3 μm) in the transmission spectrum of a terrestrial planet it could indicate robust CO{sub 2} photolysis and suggest that a future detection of O{sub 2} or O{sub 3} might not be biogenic. Strong O{sub 4} bands seen in transmission at 1.06 and 1.27 μm could be diagnostic of a post-runaway O{sub 2}-dominated atmosphere from massive H-escape. We find that for these false positive scenarios, CO at 2.35 μm, CO{sub 2} at 2.0 and 4.3 μm, and O{sub 4} at 1.27 μm are all stronger features in transmission than O{sub 2}/O{sub 3} and could be detected with S/Ns ≳ 3 for an Earth-size planet orbiting a nearby M dwarf star with as few as 10 transits, assuming photon-limited noise. O{sub 4} bands could also be sought in UV/VIS/NIR reflected light (at 0.345, 0.36, 0.38, 0.445, 0.475, 0.53, 0.57, 0.63, 1.06, and 1.27 μm) by a next generation direct-imaging telescope such as LUVOIR/HDST or HabEx and would indicate an oxygen atmosphere too massive to be biologically produced.

Spectral evolution of galaxies: current views

International Nuclear Information System (INIS)

Bruzual, A.G.

1985-01-01

A summary of current views on the interpretation of the various evolutionary tests aimed at detecting spectral evolution in galaxies is presented. It is concluded that the evolution taking place in known galaxy samples is a slow process (perhaps consistent with no evolution at all), and that the early phases of rapid spectral evolution in early-type galaxies have not yet been detected. (author)

GBTIDL: Reduction and Analysis of GBT Spectral Line Data

Science.gov (United States)

Marganian, P.; Garwood, R. W.; Braatz, J. A.; Radziwill, N. M.; Maddalena, R. J.

2013-03-01

GBTIDL is an interactive package for reduction and analysis of spectral line data taken with the Robert C. Byrd Green Bank Telescope (GBT). The package, written entirely in IDL, consists of straightforward yet flexible calibration, averaging, and analysis procedures (the "GUIDE layer") modeled after the UniPOPS and CLASS data reduction philosophies, a customized plotter with many built-in visualization features, and Data I/O and toolbox functionality that can be used for more advanced tasks. GBTIDL makes use of data structures which can also be used to store intermediate results. The package consumes and produces data in GBT SDFITS format. GBTIDL can be run online and have access to the most recent data coming off the telescope, or can be run offline on preprocessed SDFITS files.

Research on oral test modeling based on multi-feature fusion

Science.gov (United States)

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.

Cobalt-related features of spectral and magnetic properties of RNi4Co (R=Ho, Er)

International Nuclear Information System (INIS)

Lukoyanov, A.V.; Knyazev, Yu.V.; Kuz‘min, Yu.I.; Kuchin, A.G.

2014-01-01

In this paper we investigate spectral and magnetic properties of RNi 4 Co (R=Ho, Er) intermetallics to reveal the features associated with the presence of Co substituting ion in comparison with the parent HoNi 5 and ErNi 5 compounds. Our ab initio LSDA+U calculations show that in the electronic structure Co states are strongly manifested near the Fermi energy for the case of Co in 2c position, while Co in 3g position results only in weak changes of the total DOS curve. Theoretical optical conductivity calculated assuming Co equally redistributed among 2c or 3g positions agrees well with the experimental optical conductivity. Cobalt ion in RNi 4 Co (R=Ho, Er) is characterized by magnetic moment of 1μ B that increases exchange interaction in the 3d sublattice by several times that contributes to the growth of Curie temperature in comparison with the parent compounds. - Highlights: • Electronic structure of RNi4Co (R=Ho, Er) is calculated in LSDA+U. • Cobalt ion is considered in 2c or 3g position and compared. • Experimental optical conductivity is interpreted based on the calculated one

Phase coherence and Rabi frequency induced ultranarrow spectral line

International Nuclear Information System (INIS)

Dutta, Bibhas Kumar; Panchadhyayee, Pradipta; Mahapatra, Prasanta Kumar

2012-01-01

A scheme is proposed to achieve ultranarrow spectral line in the fluorescence spectrum of a lifetime broadened multilevel phase-coherent atom. It is shown that for weak-field coupling, ultranarrow spectral feature in the fluorescence spectrum can be generated by controlling the values of the Rabi frequencies involved in the coherent mechanism of the system. For fixed values of the Rabi frequencies in the weak-field limit, ultranarrow feature appears in the spectrum through the adjustment of the relative phase of the coherent fields. The results highlight that, larger the values of the decay rates associated with the field-driven channels, more pronounced is the phenomenon of narrowing in the spectrum.

Discriminating Induced-Microearthquakes Using New Seismic Features

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Assessment of damage in composite laminates through dynamic, full-spectral interrogation of fiber Bragg grating sensors

International Nuclear Information System (INIS)

Propst, A; Peters, K; Zikry, M A; Schultz, S; Kunzler, W; Zhu, Z; Wirthlin, M; Selfridge, R

2010-01-01

In this study, we demonstrate the full-spectral interrogation of a fiber Bragg grating (FBG) sensor at 535 Hz. The sensor is embedded in a woven, graphite fiber–epoxy composite laminate subjected to multiple low-velocity impacts. The measurement of unique, time dependent spectral features from the FBG sensor permits classification of the laminate lifetime into five regimes. These damage regimes compare well with previous analysis of the same material system using combined global and local FBG sensor information. Observed transient spectral features include peak splitting, wide spectral broadening and a strong single peak at the end of the impact event. Such features could not be measured through peak wavelength interrogation of the FBG sensor. Cross-correlation of the measured spectra with the original embedded FBG spectrum permitted rapid visualization of average strains and the presence of transverse compressive strain on the optical fiber, but smeared out the details of the spectral profile

Spectral characteristics of seismic noise using data of Kazakhstan monitoring stations

International Nuclear Information System (INIS)

Mikhajlova, N.N.; Komarov, I.I.

2006-01-01

Spectral specifications of seismic noise research for PS23-Makanchi, Karatau, Akbulak, AS057-Borovoye and new three-component station AS059-Aktyubinsk was done. Spectral noise density models were obtained for day and night time and spectral density values variation. Noise close to low-level universal noise model is peculiar for all stations, which provides their high efficiency while seismic monitoring. Noise parameters dependence on seismic receivers installation conditions was investigated separately. Based on three stations (Makanchi, Borovoye, and Aktyubinsk), spectral density change features are shown after borehole equipment installation. (author)

Determination of Primary Spectral Bands for Remote Sensing of Aquatic Environments

Science.gov (United States)

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

Transient spectral hole burning observed on the single-molecule level in terrylene-doped biphenyl

International Nuclear Information System (INIS)

Pärs, M.; Palm, V.; Kikas, J.

2014-01-01

We use the method of fluorescence correlation spectroscopy to analyze the single-molecule (SM) spectroscopy data earlier recorded for a special type of terrylene SM impurity center (referred as “spectrally confined unstable molecule”, SCM) in an incommensurate single crystal of biphenyl. The SCM's SM line seems to be chaotically jumping around within a broad “spectral envelope” and was first considered being subject to a peculiar spectral diffusion behavior. However, our correlation analysis reveals that all the features observed for SCM at 1.8 K are consistent with an assumption that this SM center participates in a process of reversible (transient) spectral hole burning (THB) earlier observed for terrylene-doped polycrystalline biphenyl. No observations of THB processes on SM level have been so far reported for this impurity system, partially due to a low concentration of relevant impurity centers. Another reason making searching for such centers experimentally challenging is an unusual SM line behavior: the photoinduced transition to a metastable “dark state” leads to the SM line saturational broadening, which is much stronger than the triplet broadening. Hence required prolonged observation is often prevented by an SM act of persistent spectral hole burning. - Highlights: • SCM—special type of terrylene single-molecule center in incommensurate biphenyl. • An unusually stable SCM was investigated during several hours at T=1.8 K. • SCM undergoes photoinduced transitions to an unknown metastable “dark state” (DS). • The long DS lifetime causes strong saturational broadening of SCM spectral line. • SCM participates in an earlier observed process of transient hole burning

Examining the consistency relations describing the three-point functions involving tensors

International Nuclear Information System (INIS)

Sreenath, V.; Sriramkumar, L.

2014-01-01

It is well known that the non-Gaussianity parameter f NL characterizing the scalar bi-spectrum can be expressed in terms of the scalar spectral index in the squeezed limit, a property that is referred to as the consistency relation. In contrast to the scalar bi-spectrum, the three-point cross-correlations involving scalars and tensors and the tensor bi-spectrum have not received adequate attention, which can be largely attributed to the fact that the tensors had remained undetected at the level of the power spectrum until very recently. The detection of the imprints of the primordial tensor perturbations by BICEP2 and its indication of a rather high tensor-to-scalar ratio, if confirmed, can open up a new window for understanding the tensor perturbations, not only at the level of the power spectrum, but also in the realm of non-Gaussianities. In this work, we consider the consistency relations associated with the three-point cross-correlations involving scalars and tensors as well as the tensor bi-spectrum in inflationary models driven by a single, canonical, scalar field. Characterizing the cross-correlations in terms of the dimensionless non-Gaussianity parameters C NL R and C NL γ that we had introduced earlier, we express the consistency relations governing the cross-correlations as relations between these non-Gaussianity parameters and the scalar or tensor spectral indices, in a fashion similar to that of the purely scalar case. We also discuss the corresponding relation for the non-Gaussianity parameter h NL used to describe the tensor bi-spectrum. We analytically establish these consistency relations explicitly in the following two situations: a simple example involving a specific case of power law inflation and a non-trivial scenario in the so-called Starobinsky model that is governed by a linear potential with a sharp change in its slope. We also numerically verify the consistency relations in three types of inflationary models that permit deviations from

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

Science.gov (United States)

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.

All-optical OFDM demultiplexing by spectral magnification and band-pass filtering

DEFF Research Database (Denmark)

Palushani, Evarist; Mulvad, Hans Christian Hansen; Kong, Deming

2014-01-01

We propose a simple OFDM receiver allowing for the use of standard WDM receivers to receive spectrally advanced OFDM signals. We propose to spectrally magnify the optical-OFDM super-channels using a spectral telescope consisting of two time-lenses, which enables reduced inter-carrier-interference...

Spectrally resolved measurement of the ion feature in the scattered spectrum of a hydrogen plasma obtained with a periodically pulsed Nd3+: YAG-laser

International Nuclear Information System (INIS)

Kasparek, W.

Ion temperature and density in a magnetically stabilized hydrogen arc were determined with laser scattering from collective electron density fluctuations. A 90 0 -scattering experiment was set up using a periodically pulsed Nd 3+ : YAG-laser, an IR-photomultiplier and synchronous signal detection. A spectral resolution of 0.3 Angstroem was achieved by narrowing the laser line width and by using a Fabry-Perot-interferometer in combination with a monochromator as spectrometer. The data obtained from the scattered spectra (Tsub(i) = 1,1 ... 1,8 eV, nsub(e) = 2 ... 6 x 10 21 m -3 ) agree well with those obtained by other methods. The achieved high resolution also allowed to measure separately the ion features of two ion species with different mass, which are spectrally distinguished from each other. The results confirm the theoretical model of Evans. Demixing effects in a H 2 /A mixture as well as a temperature difference between the ion sorts are deduced. (orig.) 891 HT/orig. 892 HIS

Fourier spectral of PalmCode as descriptor for palmprint recognition

NARCIS (Netherlands)

Ruan, Qiuqi; Spreeuwers, Lieuwe Jan; Veldhuis, Raymond N.J.; Mu, Meiru

Study on automatic person recognition by palmprint is currently a hot topic. In this paper, we propose a novel palmprint recognition method by transforming the typical palmprint phase code feature into its Fourier frequency domain. The resulting real-valued Fourier spectral features are further

Spectral quality requirements for effluent identification

Science.gov (United States)

Czerwinski, R. N.; Seeley, J. A.; Wack, E. C.

2005-11-01

We consider the problem of remotely identifying gaseous materials using passive sensing of long-wave infrared (LWIR) spectral features at hyperspectral resolution. Gaseous materials are distinguishable in the LWIR because of their unique spectral fingerprints. A sensor degraded in capability by noise or limited spectral resolution, however, may be unable to positively identify contaminants, especially if they are present in low concentrations or if the spectral library used for comparisons includes materials with similar spectral signatures. This paper will quantify the relative importance of these parameters and express the relationships between them in a functional form which can be used as a rule of thumb in sensor design or in assessing sensor capability for a specific task. This paper describes the simulation of remote sensing datacontaining a gas cloud.In each simulation, the spectra are degraded in spectral resolution and through the addition of noise to simulate spectra collected by sensors of varying design and capability. We form a trade space by systematically varying the number of sensor spectral channels and signal-to-noise ratio over a range of values. For each scenario, we evaluate the capability of the sensor for gas identification by computing the ratio of the F-statistic for the truth gas tothe same statistic computed over the rest of the library.The effect of the scope of the library is investigated as well, by computing statistics on the variability of the identification capability as the library composition is varied randomly.

Substitution dynamical systems spectral analysis

CERN Document Server

Queffélec, Martine

2010-01-01

This volume mainly deals with the dynamics of finitely valued sequences, and more specifically, of sequences generated by substitutions and automata. Those sequences demonstrate fairly simple combinatorical and arithmetical properties and naturally appear in various domains. As the title suggests, the aim of the initial version of this book was the spectral study of the associated dynamical systems: the first chapters consisted in a detailed introduction to the mathematical notions involved, and the description of the spectral invariants followed in the closing chapters. This approach, combined with new material added to the new edition, results in a nearly self-contained book on the subject. New tools - which have also proven helpful in other contexts - had to be developed for this study. Moreover, its findings can be concretely applied, the method providing an algorithm to exhibit the spectral measures and the spectral multiplicity, as is demonstrated in several examples. Beyond this advanced analysis, many...

Spectral Classification of Galaxies at 0.5 <= z <= 1 in the CDFS: The Artificial Neural Network Approach

Science.gov (United States)

Teimoorinia, H.

2012-12-01

The aim of this work is to combine spectral energy distribution (SED) fitting with artificial neural network techniques to assign spectral characteristics to a sample of galaxies at 0.5 MUSIC catalog covering bands between ~0.4 and 24 μm in 10-13 filters. We use the CIGALE code to fit photometric data to Maraston's synthesis spectra to derive mass, specific star formation rate, and age, as well as the best SED of the galaxies. We use the spectral models presented by Kinney et al. as targets in the wavelength interval ~1200-7500 Å. Then a series of neural networks are trained, with average performance ~90%, to classify the best SED in a supervised manner. We consider the effects of the prominent features of the best SED on the performance of the trained networks and also test networks on the galaxy spectra of Coleman et al., which have a lower resolution than the target models. In this way, we conclude that the trained networks take into account all the features of the spectra simultaneously. Using the method, 105 out of 142 galaxies of the sample are classified with high significance. The locus of the classified galaxies in the three graphs of the physical parameters of mass, age, and specific star formation rate appears consistent with the morphological characteristics of the galaxies.

On the causes of spectral enhancements in solar wind power spectra

Science.gov (United States)

Unti, T.; Russell, C. T.

1976-01-01

Enhancements in power spectra of the solar-wind ion flux in the frequency neighborhood of 0.5 Hz had been noted by Unti et al. (1973). It was speculated that these were due to convected small-scale density irregularities. In this paper, 54 flux spectra calculated from OGO 5 data are examined. It is seen that the few prominent spectral peaks which occur were not generated by density irregularities, but were due to several different causes, including convected discontinuities and propagating transverse waves. A superposition of many spectra, however, reveals a moderate enhancement at a frequency corresponding to convected features with a correlation length of a proton gyroradius, consistent with the results of Neugebauer (1975).

SPECTRAL FILTRATION OF IMAGES BY MEANS OF DISPERSIVE SYSTEMS

Directory of Open Access Journals (Sweden)

I. M. Gulis

2016-01-01

Full Text Available Instruments for spectral filtration of images are an important element of the systems used in remote sensing, medical diagnostics, in-process measurements. The aim of this study is analysis of the functional features and characteristics of the proposed two image monochromator versions which are based on dispersive spectral filtering. The first is based on the use of a dispersive monochromator, where collimating and camera lenses form a telescopic system, the dispersive element of which is within the intermediate image plane. The second version is based on an imaging double monochromator with dispersion subtraction by back propagation. For the telescopic system version, the spectral and spatial resolutions are estimated, the latter being limited by aberrations and diffraction from the entrance slit. The device has been numerically simulated and prototyped. It is shown that for the spectral bandwidth 10 nm (visible spectral range, the aberration-limited spot size is from 10–20 μm at the image center to about 30 μm at the image periphery for the image size 23–27 mm. The monochromator with dispersion subtraction enables one to vary the spectral resolution (up to 1 nm and higher by changing the intermediate slit width. But the distinctive feature is a significant change in the selected central wavelength over the image field. The considered designs of dispersive image monochromators look very promising due to the particular advantages over the systems based on tunable filters as regards the spectral resolution, fast tuning, and the spectral contrast. The monochromator based on a telescopic system has a simple design and a rather large image field but it also has a limited light throughput due to small aperture size. The monochromator with dispersion subtraction has higher light throughput, can provide high spectral resolution when recording a full data cube in a series of measuring acts for different dispersive element positions. 

Upconversion based spectral imaging in 6 to 8 μm spectral regime

DEFF Research Database (Denmark)

Junaid, Saher; Tidemand-Lichtenberg, Peter; Pedersen, Christian

2017-01-01

Spectral imaging in the 6 to 8μm range has great potential for medical diagnostics. Here a novel technique based on frequency upconversion of the infrared images to the near visible for subsequent acquisition using a Si-CCD camera is investigated. The upconversion unit consists of an AgGaS2 crystal...

Time-resolved spectral analysis of prompt emission from long gamma-ray bursts with GeV emission

International Nuclear Information System (INIS)

Rao Arikkala Raghurama; Basak Rupal; Bhattacharya Jishnu; Chandra Sarthak; Maheshwari Nikunj; Choudhury Manojendu; Misra Ranjeev

2014-01-01

We performed detailed time-resolved spectroscopy of bright long gamma-ray bursts (GRBs) which show significant GeV emissions (GRB 080916C, GRB 090902B and GRB 090926A). In addition to the standard Band model, we also use a model consisting of a black body and a power law to fit the spectra. We find that for the latter model there are indications of an additional soft component in the spectra. While previous studies have shown that such models are required for GRB 090902B, here we find that a composite spectral model consisting of two blackbodies and a power law adequately fits the data of all the three bright GRBs. We investigate the evolution of the spectral parameters and find several interesting features that appear in all three GRBs, like (a) temperatures of the blackbodies are strongly correlated with each other, (b) fluxes in the black body components are strongly correlated with each other, (c) the temperatures of the black body trace the profile of the individual pulses of the GRBs, and (d) the characteristics of power law components like the spectral index and the delayed onset bear a close similarity to the emission characteristics in the GeV regions. We discuss the implications of these results and the possibility of identifying the radiation mechanisms during the prompt emission of GRBs. (research papers)

Ultra-Widefield Steering-Based Spectral-Domain Optical Coherence Tomography Imaging of the Retinal Periphery.

Science.gov (United States)

Choudhry, Netan; Golding, John; Manry, Matthew W; Rao, Rajesh C

2016-06-01

To describe the spectral-domain optical coherence tomography (SD OCT) features of peripheral retinal findings using an ultra-widefield (UWF) steering technique to image the retinal periphery. Observational study. A total of 68 patients (68 eyes) with 19 peripheral retinal features. Spectral-domain OCT-based structural features. Nineteen peripheral retinal features, including vortex vein, congenital hypertrophy of the retinal pigment epithelium, pars plana, ora serrata pearl, typical cystoid degeneration (TCD), cystic retinal tuft, meridional fold, lattice and cobblestone degeneration, retinal hole, retinal tear, rhegmatogenous retinal detachment, typical degenerative senile retinoschisis, peripheral laser coagulation scars, ora tooth, cryopexy scars (retinal tear and treated retinoblastoma scar), bone spicules, white without pressure, and peripheral drusen, were identified by peripheral clinical examination. Near-infrared scanning laser ophthalmoscopy images and SD OCT of these entities were registered to UWF color photographs. Spectral-domain OCT resolved structural features of all peripheral findings. Dilated hyporeflective tubular structures within the choroid were observed in the vortex vein. Loss of retinal lamination, neural retinal attenuation, retinal pigment epithelium loss, or hypertrophy was seen in several entities, including congenital hypertrophy of the retinal pigment epithelium, ora serrata pearl, TCD, cystic retinal tuft, meridional fold, lattice, and cobblestone degenerations. Hyporeflective intraretinal spaces, indicating cystoid or schitic fluid, were seen in ora serrata pearl, ora tooth, TCD, cystic retinal tuft, meridional fold, retinal hole, and typical degenerative senile retinoschisis. The vitreoretinal interface, which often consisted of lamellae-like structures of the condensed cortical vitreous near or adherent to the neural retina, appeared clearly in most peripheral findings, confirming its association with many low-risk and vision

Extracting attosecond delays from spectrally overlapping interferograms

Science.gov (United States)

Jordan, Inga; Wörner, Hans Jakob

2018-02-01

Attosecond interferometry is becoming an increasingly popular technique for measuring the dynamics of photoionization in real time. Whereas early measurements focused on atomic systems with very simple photoelectron spectra, the technique is now being applied to more complex systems including isolated molecules and solids. The increase in complexity translates into an augmented spectral congestion, unavoidably resulting in spectral overlap in attosecond interferograms. Here, we discuss currently used methods for phase retrieval and introduce two new approaches for determining attosecond photoemission delays from spectrally overlapping photoelectron spectra. We show that the previously used technique, consisting in the spectral integration of the areas of interest, does in general not provide reliable results. Our methods resolve this problem, thereby opening the technique of attosecond interferometry to complex systems and fully exploiting its specific advantages in terms of spectral resolution compared to attosecond streaking.

Reducing the spectral index in supernatural inflation

International Nuclear Information System (INIS)

Lin, C.-M.; Cheung, Kingman

2009-01-01

Supernatural inflation is an attractive model based on just a flat direction with soft supersymmetry breaking mass terms in the framework of supersymmetry. The beauty of the model is that it needs no fine-tuning. However, the prediction of the spectral index is n s > or approx. 1, in contrast to experimental data. In this paper, we discuss supernatural inflation with the spectral index reduced to n s =0.96 without any fine-tuning, considering the general feature that a flat direction is lifted by a nonrenormalizable term with an A-term.

Reducing the spectral index in supernatural inflation

Science.gov (United States)

Lin, Chia-Min; Cheung, Kingman

2009-04-01

Supernatural inflation is an attractive model based on just a flat direction with soft supersymmetry breaking mass terms in the framework of supersymmetry. The beauty of the model is that it needs no fine-tuning. However, the prediction of the spectral index is ns≳1, in contrast to experimental data. In this paper, we discuss supernatural inflation with the spectral index reduced to ns=0.96 without any fine-tuning, considering the general feature that a flat direction is lifted by a nonrenormalizable term with an A-term.

Spectral Theory of Operators on Hilbert Spaces

CERN Document Server

Kubrusly, Carlos S

2012-01-01

This work is a concise introduction to spectral theory of Hilbert space operators. Its emphasis is on recent aspects of theory and detailed proofs, with the primary goal of offering a modern introductory textbook for a first graduate course in the subject. The coverage of topics is thorough, as the book explores various delicate points and hidden features often left untreated. Spectral Theory of Operators on Hilbert Space is addressed to an interdisciplinary audience of graduate students in mathematics, statistics, economics, engineering, and physics. It will also be useful to working mathemat

Spectral confocal reflection microscopy using a white light source

Science.gov (United States)

Booth, M.; Juškaitis, R.; Wilson, T.

2008-08-01

We present a reflection confocal microscope incorporating a white light supercontinuum source and spectral detection. The microscope provides images resolved spatially in three-dimensions, in addition to spectral resolution covering the wavelength range 450-650nm. Images and reflection spectra of artificial and natural specimens are presented, showing features that are not normally revealed in conventional microscopes or confocal microscopes using discrete line lasers. The specimens include thin film structures on semiconductor chips, iridescent structures in Papilio blumei butterfly scales, nacre from abalone shells and opal gemstones. Quantitative size and refractive index measurements of transparent beads are derived from spectral interference bands.

X-ray grating spectrometer for opacity measurements in the 50 eV to 250 eV spectral range at the LULI 2000 laser facility.

Science.gov (United States)

Reverdin, Charles; Thais, Frédéric; Loisel, Guillaume; Busquet, M; Bastiani-Ceccotti, S; Blenski, T; Caillaud, T; Ducret, J E; Foelsner, W; Gilles, D; Gilleron, F; Pain, J C; Poirier, M; Serres, F; Silvert, V; Soullie, G; Turck-Chieze, S; Villette, B

2012-10-01

An x-ray grating spectrometer was built in order to measure opacities in the 50 eV to 250 eV spectral range with an average spectral resolution ∼ 50. It has been used at the LULI-2000 laser facility at École Polytechnique (France) to measure the Δn = 0, n = 3 transitions of several elements with neighboring atomic number: Cr, Fe, Ni, and Cu in the same experimental conditions. Hence a spectrometer with a wide spectral range is required. This spectrometer features one line of sight looking through a heated sample at backlighter emission. It is outfitted with one toroidal condensing mirror and several flat mirrors cutting off higher energy photons. The spectral dispersion is obtained with a flatfield grating. Detection consists of a streak camera sensitive to soft x-ray radiation. Some experimental results showing the performance of this spectrometer are presented.

X-ray grating spectrometer for opacity measurements in the 50 eV to 250 eV spectral range at the LULI 2000 laser facility

International Nuclear Information System (INIS)

Reverdin, Charles; Caillaud, T.; Gilleron, F.; Pain, J. C.; Silvert, V.; Soullie, G.; Villette, B.; Thais, Frédéric; Loisel, Guillaume; Blenski, T.; Poirier, M.; Busquet, M.; Bastiani-Ceccotti, S.; Serres, F.; Ducret, J. E.; Foelsner, W.; Gilles, D.; Turck-Chieze, S.

2012-01-01

An x-ray grating spectrometer was built in order to measure opacities in the 50 eV to 250 eV spectral range with an average spectral resolution ∼ 50. It has been used at the LULI-2000 laser facility at École Polytechnique (France) to measure the Δn = 0, n = 3 transitions of several elements with neighboring atomic number: Cr, Fe, Ni, and Cu in the same experimental conditions. Hence a spectrometer with a wide spectral range is required. This spectrometer features one line of sight looking through a heated sample at backlighter emission. It is outfitted with one toroidal condensing mirror and several flat mirrors cutting off higher energy photons. The spectral dispersion is obtained with a flatfield grating. Detection consists of a streak camera sensitive to soft x-ray radiation. Some experimental results showing the performance of this spectrometer are presented.

X-ray grating spectrometer for opacity measurements in the 50 eV to 250 eV spectral range at the LULI 2000 laser facility

Energy Technology Data Exchange (ETDEWEB)

Reverdin, Charles; Caillaud, T.; Gilleron, F.; Pain, J. C.; Silvert, V.; Soullie, G.; Villette, B. [CEA, DAM, DIF, 91297 Arpajon (France); Thais, Frederic; Loisel, Guillaume; Blenski, T.; Poirier, M. [CEA, DSM, IRAMIS, Service Photons, Atomes et Molecules, 91191 Gif-sur-Yvette (France); Busquet, M. [ARTEP Inc, Ellicott City, Maryland 21042 (United States); Bastiani-Ceccotti, S.; Serres, F. [LULI, Ecole Polytechnique, CNRS, CEA, UPMC, route de Saclay, 91128 Palaiseau (France); Ducret, J. E. [CELIA, UMR5107, CEA, CNRS, Universite de Bordeaux, 33400 Talence (France); Foelsner, W. [Max Planck Instituet fuer Quantum Optik, 85748 Garching (Germany); Gilles, D.; Turck-Chieze, S. [CEA, DSM, IRFU, Service d' astrophysique, 91191 Gif-sur-Yvette (France)

2012-10-15

An x-ray grating spectrometer was built in order to measure opacities in the 50 eV to 250 eV spectral range with an average spectral resolution {approx} 50. It has been used at the LULI-2000 laser facility at Ecole Polytechnique (France) to measure the {Delta}n = 0, n = 3 transitions of several elements with neighboring atomic number: Cr, Fe, Ni, and Cu in the same experimental conditions. Hence a spectrometer with a wide spectral range is required. This spectrometer features one line of sight looking through a heated sample at backlighter emission. It is outfitted with one toroidal condensing mirror and several flat mirrors cutting off higher energy photons. The spectral dispersion is obtained with a flatfield grating. Detection consists of a streak camera sensitive to soft x-ray radiation. Some experimental results showing the performance of this spectrometer are presented.

Coupled Dyson-Schwinger equations and effects of self-consistency

International Nuclear Information System (INIS)

Wu, S.S.; Zhang, H.X.; Yao, Y.J.

2001-01-01

Using the σ-ω model as an effective tool, the effects of self-consistency are studied in some detail. A coupled set of Dyson-Schwinger equations for the renormalized baryon and meson propagators in the σ-ω model is solved self-consistently according to the dressed Hartree-Fock scheme, where the hadron propagators in both the baryon and meson self-energies are required to also satisfy this coupled set of equations. It is found that the self-consistency affects the baryon spectral function noticeably, if only the interaction with σ mesons is considered. However, there is a cancellation between the effects due to the σ and ω mesons and the additional contribution of ω mesons makes the above effect insignificant. In both the σ and σ-ω cases the effects of self-consistency on meson spectral function are perceptible, but they can nevertheless be taken account of without a self-consistent calculation. Our study indicates that to include the meson propagators in the self-consistency requirement is unnecessary and one can stop at an early step of an iteration procedure to obtain a good approximation to the fully self-consistent results of all the hadron propagators in the model, if an appropriate initial input is chosen. Vertex corrections and their effects on ghost poles are also studied

Evaluating Surgical Margins with Optical Spectroscopy and Spectral Imaging Following Breast Cancer Resection

Science.gov (United States)

2009-08-01

Raman spectral features of hydroxyapatite crystals (found in breast calcifications) through overlying lean chicken breast tissue [18]. Thus, the...Raman signature of bone through several mm of soft tissue [3-5]. It has also been used to detect the Ram an spectral features of hydroxyapatite ...all f eaturing in- line f iltering at the ir tips (Em vision). All seve n f ibers we re bin ned a fter a sing le 3 se cond acquisition, and these

Radial measurements of IMF-sensitive absorption features in two massive ETGs

Science.gov (United States)

Vaughan, Sam P.; Davies, Roger L.; Zieleniewski, Simon; Houghton, Ryan C. W.

2018-03-01

We make radial measurements of stellar initial mass function (IMF) sensitive absorption features in the two massive early-type galaxies NGC 1277 and IC 843. Using the Oxford Short Wavelength Integral Field specTrogaph (SWIFT), we obtain resolved measurements of the Na I 0.82 and FeH 0.99 indices, amongst others, finding both galaxies show strong gradients in Na I absorption combined with flat FeH profiles at ˜0.4 Å. We find these measurements may be explained by radial gradients in the IMF, appropriate abundance gradients in [Na/Fe] and [Fe/H], or a combination of the two, and our data are unable to break this degeneracy. We also use full spectral fitting to infer global properties from an integrated spectrum of each object, deriving a unimodal IMF slope consistent with Salpeter in IC 843 (x = 2.27 ± 0.17) but steeper than Salpeter in NGC 1277 (x = 2.69 ± 0.11), despite their similar FeH equivalent widths. Independently, we fit the strength of the FeH feature and compare to the E-MILES and CvD12 stellar population libraries, finding agreement between the models. The IMF values derived in this way are in close agreement with those from spectral fitting in NGC 1277 (x_{CvD}=2.59^{+0.25}_{-0.48}, x_{E-MILES}=2.77± 0.31), but are less consistent in IC 843, with the IMF derived from FeH alone leading to steeper slopes than when fitting the full spectrum (x_{CvD}=2.57^{+0.30}_{-0.41}, x_{E-MILES}=2.72± 0.25). This work highlights the importance of a large wavelength coverage for breaking the degeneracy between abundance and IMF variations, and may bring into doubt the use of the Wing-Ford band as an IMF index if used without other spectral information.

Preliminary report on NTS spectral gamma logging and calibration models

International Nuclear Information System (INIS)

Mathews, M.A.; Warren, R.G.; Garcia, S.R.; Lavelle, M.J.

1985-01-01

Facilities are now available at the Nevada Test Site (NTS) in Building 2201 to calibrate spectral gamma logging equipment in environments of low radioactivity. Such environments are routinely encountered during logging of holes at the NTS. Four calibration models were delivered to Building 2201 in January 1985. Each model, or test pit, consists of a stone block with a 12-inch diameter cored borehole. Preliminary radioelement values from the core for the test pits range from 0.58 to 3.83% potassium (K), 0.48 to 29.11 ppm thorium (Th), and 0.62 to 40.42 ppm uranium (U). Two satellite holes, U19ab number2 and U19ab number3, were logged during the winter of 1984-1985. The response of these logs correlates with contents of the naturally radioactive elements K. Th. and U determined in samples from petrologic zones that occur within these holes. Based on these comparisons, the spectral gamma log aids in the recognition and mapping of subsurface stratigraphic units and alteration features associated with unusual concentration of these radioactive elements, such as clay-rich zones

Spectral properties of 441 radio pulsars

Science.gov (United States)

Jankowski, F.; van Straten, W.; Keane, E. F.; Bailes, M.; Barr, E. D.; Johnston, S.; Kerr, M.

2018-02-01

We present a study of the spectral properties of 441 pulsars observed with the Parkes radio telescope near the centre frequencies of 728, 1382 and 3100 MHz. The observations at 728 and 3100 MHz were conducted simultaneously using the dual-band 10-50 cm receiver. These high-sensitivity, multifrequency observations provide a systematic and uniform sample of pulsar flux densities. We combine our measurements with spectral data from the literature in order to derive the spectral properties of these pulsars. Using techniques from robust regression and information theory, we classify the observed spectra in an objective, robust and unbiased way into five morphological classes: simple or broken power law, power law with either low- or high-frequency cut-off and log-parabolic spectrum. While about 79 per cent of the pulsars that could be classified have simple power-law spectra, we find significant deviations in 73 pulsars, 35 of which have curved spectra, 25 with a spectral break and 10 with a low-frequency turn-over. We identify 11 gigahertz-peaked spectrum (GPS) pulsars, with 3 newly identified in this work and 8 confirmations of known GPS pulsars; 3 others show tentative evidence of GPS, but require further low-frequency measurements to support this classification. The weighted mean spectral index of all pulsars with simple power-law spectra is -1.60 ± 0.03. The observed spectral indices are well described by a shifted log-normal distribution. The strongest correlations of spectral index are with spin-down luminosity, magnetic field at the light-cylinder and spin-down rate. We also investigate the physical origin of the observed spectral features and determine emission altitudes for three pulsars.

Spectral dependence of backscattering coefficient of mixed phase clouds over West Africa measured with two-wavelength Raman polarization lidar: Features attributed to ice-crystals corner reflection

Science.gov (United States)

Veselovskii, I.; Goloub, P.; Podvin, T.; Tanre, D.; Ansmann, A.; Korenskiy, M.; Borovoi, A.; Hu, Q.; Whiteman, D. N.

2017-11-01

The existing models predict that corner reflection (CR) of laser radiation by simple ice crystals of perfect shape, such as hexagonal columns or plates, can provide a significant contribution to the ice cloud backscattering. However in real clouds the CR effect may be suppressed due to crystal deformation and surface roughness. In contrast to the extinction coefficient, which is spectrally independent, consideration of diffraction associated with CR results in a spectral dependence of the backscattering coefficient. Thus measuring the spectral dependence of the cloud backscattering coefficient, the contribution of CR can be identified. The paper presents the results of profiling of backscattering coefficient (β) and particle depolarization ratio (δ) of ice and mixed-phase clouds over West Africa by means of a two-wavelength polarization Mie-Raman lidar operated at 355 nm and 532 nm during the SHADOW field campaign. The lidar observations were performed at a slant angle of 43 degree off zenith, thus CR from both randomly oriented crystals and oriented plates could be analyzed. For the most of the observations the cloud backscatter color ratio β355/β532 was close to 1.0, and no spectral features that might indicate the presence of CR of randomly oriented crystals were revealed. Still, in two measurement sessions we observed an increase of backscatter color ratio to a value of nearly 1.3 simultaneously with a decrease of the spectral depolarization ratio δ355/δ532 ratio from 1.0 to 0.8 inside the layers containing precipitating ice crystals. We attribute these changes in optical properties to corner reflections by horizontally oriented ice plates.

Selection/extraction of spectral regions for autofluorescence spectra measured in the oral cavity

NARCIS (Netherlands)

Skurichina, M; Paclik, P; Duin, RPW; de Veld, D; Sterenborg, HJCM; Witjes, MJH; Roodenburg, JLN; Fred, A; Caelli, T; Duin, RPW; Campilho, A; DeRidder, D

2004-01-01

Recently a number of successful algorithms to select/extract discriminative spectral regions was introduced. These methods may be more beneficial than the standard feature selection/extraction methods for spectral classification. In this paper, on the example of autofluorescence spectra measured in

Assessment of Landsat multispectral scanner spectral indexes for monitoring arid rangeland

Science.gov (United States)

Musick, H. B.

1984-01-01

Correlations between spectral indices and vegetation parameters in south-central New Mexico were used to determine the utility of Landsat Multispectral Scanner (MSS) spectral indices in arid rangeland monitoring. In addition, spectral index change for 1976-1980 was calculated from retrospective MSS data and compared with qualitative ground truth in order to evaluate vegetation change detection by means of spectral indices. Brightness index change consistently differentiated between cover increase and decrease, but index change appears to have been offset from true cover change; this may at least partly be attributed to the failure of the methods used to standardize MSS scenes for differences in sensor response. Green vegetation indices, by contrast to brightness indices, failed to consistently differentiate between cover increase and decrease.

Prominent spectral features of Sm3+ ion in disordered zinc tellurite glass

Directory of Open Access Journals (Sweden)

Y.A. Tanko

Full Text Available Trivalent rare earth doped glasses with modified spectroscopic features are essential for solid state lasers and diverse photonic applications. Glass composition optimisation may fulfil such demand. Stimulating the spectral properties of samarium (Sm3+ ions in tellurite glass host with desired enhancement is the key issue. Glasses with composition (80 − xTeO2–20ZnO–(xSm2O3, where 0 ⩽ x ⩽ 1.5 mol% are prepared using melt quenching method. The role of varying Sm3+ contents to improving the absorption and emission properties of the prepared glasses are determined. XRD pattern verifies amorphous nature of synthesised glasses. FTIR spectroscopy has been used to observe the structural modification of (TeO4 trigonal bipyramid structural units. DTA traces display prominent transition peaks for glass transition, crystallisation and melting temperature. Samples are discerned to be stable with desired Hruby parameter and superior glass forming ability. The UV–Vis–NIR absorption spectra reveals nine peaks centred at 470, 548, 947, 1085, 1238, 1385, 1492, 1550 and 1589 nm. These bands arise due to 6H5/2 → 4I11/2, 4G5/2, 6F11/2, 6F9/2, 6F7/2, 6F5/2, 6F3/2, 6H15/2 and 6F1/2 transitions, respectively. The direct, indirect band gap and Urbach energy calculated from the absorption edge of UV–Vis–NIR spectra are found to appear within (2.75–3.18 eV, (3.22–3.40 eV, and (0.20–0.31 eV, respectively. The observed increase in refractive index from 2.45 to 2.47 is ascribed to the generation of non-bridging oxygen atoms via the conversion of TeO4 into TeO3 units. Conversely the decrease in refractive index to 2.39 is attributed to the lower ionic radii (1.079 Å of Sm3+. PL spectra under the excitation of 452 nm display four emission bands centred at 563, 600, 644 and 705 nm corresponding to 4G5/2 → 6H5/2, 6H7/2, 6H9/2 and 6H11/2 transitions of samarium ions. Excellent features of the results nominate these compositions

Characterization of the titanium Kβ spectral profile

International Nuclear Information System (INIS)

Chantler, C T; Smale, L F; Kinnane, M N; Illig, A J; Kimpton, J A; Crosby, D N

2013-01-01

Transition metals have Kα and Kβ characteristic radiation possessing complex asymmetric spectral profiles. Instrumental broadening normally encountered in x-ray experiments shifts features of profiles used for calibration, such as peak energy, by many times the quoted accuracies. We measure and characterize the titanium Kβ spectral profile. The peak energy of the titanium Kβ spectral profile is found to be 4931.966 ± 0.022 eV prior to instrumental broadening. This 4.5 ppm result decreases the uncertainty over the past literature by a factor of 2.6 and is 2.4 standard deviations from the previous standard. The spectrum is analysed and the resolution-free lineshape is extracted and listed for use in other experiments. We also incorporate improvement in analysis applied to earlier results for V Kβ. (paper)

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

Science.gov (United States)

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.

Spectral feature extraction of EEG signals and pattern recognition during mental tasks of 2-D cursor movements for BCI using SVM and ANN.

Science.gov (United States)

Bascil, M Serdar; Tesneli, Ahmet Y; Temurtas, Feyzullah

2016-09-01

Brain computer interface (BCI) is a new communication way between man and machine. It identifies mental task patterns stored in electroencephalogram (EEG). So, it extracts brain electrical activities recorded by EEG and transforms them machine control commands. The main goal of BCI is to make available assistive environmental devices for paralyzed people such as computers and makes their life easier. This study deals with feature extraction and mental task pattern recognition on 2-D cursor control from EEG as offline analysis approach. The hemispherical power density changes are computed and compared on alpha-beta frequency bands with only mental imagination of cursor movements. First of all, power spectral density (PSD) features of EEG signals are extracted and high dimensional data reduced by principle component analysis (PCA) and independent component analysis (ICA) which are statistical algorithms. In the last stage, all features are classified with two types of support vector machine (SVM) which are linear and least squares (LS-SVM) and three different artificial neural network (ANN) structures which are learning vector quantization (LVQ), multilayer neural network (MLNN) and probabilistic neural network (PNN) and mental task patterns are successfully identified via k-fold cross validation technique.

Spectral asymmetry for bag boundary conditions

International Nuclear Information System (INIS)

Beneventano, C G; Santangelo, E M; Wipf, A

2002-01-01

We give an expression, in terms of boundary spectral functions, for the spectral asymmetry of the Euclidean Dirac operator in two dimensions, when its domain is determined by local boundary conditions and the manifold is of product type. As an application, we explicitly evaluate the asymmetry in the case of a finite-length cylinder and check that the outcome is consistent with our general result. Finally, we study the asymmetry in a disc, which is a non-product case, and propose an interpretation

FIVE YEARS OF SYNTHESIS OF SOLAR SPECTRAL IRRADIANCE FROM SDID/SISA AND SDO /AIA IMAGES

Energy Technology Data Exchange (ETDEWEB)

Fontenla, J. M. [NorthWest Research Associates, Boulder, CO 80301 (United States); Codrescu, M. [Space Weather Prediction Center, National Oceanic and Atmospheric Administration, Boulder, CO 80305 (United States); Fedrizzi, M.; Fuller-Rowell, T. [Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, CO 80309 (United States); Hill, F. [National Solar Observatory, Boulder, CO 80303 (United States); Landi, E. [Department of Climate and Space Science and Engineering, University of Michigan, Ann Arbor, MI 48109 (United States); Woods, T., E-mail: johnf@digidyna.com [Laboratory for Atmospheric and Space Physics, University of Colorado Boulder, Boulder, CO 80303 (United States)

2017-01-01

In this paper we describe the synthetic solar spectral irradiance (SSI) calculated from 2010 to 2015 using data from the Atmospheric Imaging Assembly (AIA) instrument, on board the Solar Dynamics Observatory spacecraft. We used the algorithms for solar disk image decomposition (SDID) and the spectral irradiance synthesis algorithm (SISA) that we had developed over several years. The SDID algorithm decomposes the images of the solar disk into areas occupied by nine types of chromospheric and 5 types of coronal physical structures. With this decomposition and a set of pre-computed angle-dependent spectra for each of the features, the SISA algorithm is used to calculate the SSI. We discuss the application of the basic SDID/SISA algorithm to a subset of the AIA images and the observed variation occurring in the 2010–2015 period of the relative areas of the solar disk covered by the various solar surface features. Our results consist of the SSI and total solar irradiance variations over the 2010–2015 period. The SSI results include soft X-ray, ultraviolet, visible, infrared, and far-infrared observations and can be used for studies of the solar radiative forcing of the Earth’s atmosphere. These SSI estimates were used to drive a thermosphere–ionosphere physical simulation model. Predictions of neutral mass density at low Earth orbit altitudes in the thermosphere and peak plasma densities at mid-latitudes are in reasonable agreement with the observations. The correlation between the simulation results and the observations was consistently better when fluxes computed by SDID/SISA procedures were used.

Digital staining for histopathology multispectral images by the combined application of spectral enhancement and spectral transformation.

Science.gov (United States)

Bautista, Pinky A; Yagi, Yukako

2011-01-01

In this paper we introduced a digital staining method for histopathology images captured with an n-band multispectral camera. The method consisted of two major processes: enhancement of the original spectral transmittance and the transformation of the enhanced transmittance to its target spectral configuration. Enhancement is accomplished by shifting the original transmittance with the scaled difference between the original transmittance and the transmittance estimated with m dominant principal component (PC) vectors;the m-PC vectors were determined from the transmittance samples of the background image. Transformation of the enhanced transmittance to the target spectral configuration was done using an nxn transformation matrix, which was derived by applying a least square method to the enhanced and target spectral training data samples of the different tissue components. Experimental results on the digital conversion of a hematoxylin and eosin (H&E) stained multispectral image to its Masson's trichrome stained (MT) equivalent shows the viability of the method.

An Interferometric Spectral-Line and Imaging Survey of VY Canis Majoris in the 345 GHz Band

OpenAIRE

Kaminski, T.; Gottlieb, C. A.; Young, K. H.; Menten, K. M.; Patel, N. A.

2013-01-01

A spectral line survey of the oxygen-rich red supergiant VY Canis Majoris was made between 279 and 355 GHz with the Submillimeter Array. Two hundred twenty three spectral features from 19 molecules (not counting isotopic species of some of them) were observed, including the rotational spectra of TiO, TiO2, and AlCl for the first time in this source. The parameters and an atlas of all spectral features is presented. Observations of each line with a synthesized beam of ~0.9 arcsec, reveal the c...

An efficient quantum algorithm for spectral estimation

Science.gov (United States)

Steffens, Adrian; Rebentrost, Patrick; Marvian, Iman; Eisert, Jens; Lloyd, Seth

2017-03-01

We develop an efficient quantum implementation of an important signal processing algorithm for line spectral estimation: the matrix pencil method, which determines the frequencies and damping factors of signals consisting of finite sums of exponentially damped sinusoids. Our algorithm provides a quantum speedup in a natural regime where the sampling rate is much higher than the number of sinusoid components. Along the way, we develop techniques that are expected to be useful for other quantum algorithms as well—consecutive phase estimations to efficiently make products of asymmetric low rank matrices classically accessible and an alternative method to efficiently exponentiate non-Hermitian matrices. Our algorithm features an efficient quantum-classical division of labor: the time-critical steps are implemented in quantum superposition, while an interjacent step, requiring much fewer parameters, can operate classically. We show that frequencies and damping factors can be obtained in time logarithmic in the number of sampling points, exponentially faster than known classical algorithms.

EOG feature relevance determination for microsleep detection

Directory of Open Access Journals (Sweden)

Golz Martin

2017-09-01

Full Text Available Automatic relevance determination (ARD was applied to two-channel EOG recordings for microsleep event (MSE recognition. 10 s immediately before MSE and also before counterexamples of fatigued, but attentive driving were analysed. Two type of signal features were extracted: the maximum cross correlation (MaxCC and logarithmic power spectral densities (PSD averaged in spectral bands of 0.5 Hz width ranging between 0 and 8 Hz. Generalised learn-ing vector quantisation (GRLVQ was used as ARD method to show the potential of feature reduction. This is compared to support-vector machines (SVM, in which the feature reduction plays a much smaller role. Cross validation yielded mean normalised relevancies of PSD features in the range of 1.6 – 4.9 % and 1.9 – 10.4 % for horizontal and vertical EOG, respectively. MaxCC relevancies were 0.002 – 0.006 % and 0.002 – 0.06 %, respectively. This shows that PSD features of vertical EOG are indispensable, whereas MaxCC can be neglected. Mean classification accuracies were estimated at 86.6±b 1.3 % and 92.3±b 0.2 % for GRLVQ and SVM, respectively. GRLVQ permits objective feature reduction by inclusion of all processing stages, but is not as accurate as SVM.

EOG feature relevance determination for microsleep detection

Directory of Open Access Journals (Sweden)

Golz Martin

2017-09-01

Full Text Available Automatic relevance determination (ARD was applied to two-channel EOG recordings for microsleep event (MSE recognition. 10 s immediately before MSE and also before counterexamples of fatigued, but attentive driving were analysed. Two type of signal features were extracted: the maximum cross correlation (MaxCC and logarithmic power spectral densities (PSD averaged in spectral bands of 0.5 Hz width ranging between 0 and 8 Hz. Generalised learn-ing vector quantisation (GRLVQ was used as ARD method to show the potential of feature reduction. This is compared to support-vector machines (SVM, in which the feature reduction plays a much smaller role. Cross validation yielded mean normalised relevancies of PSD features in the range of 1.6 - 4.9 % and 1.9 - 10.4 % for horizontal and vertical EOG, respectively. MaxCC relevancies were 0.002 - 0.006 % and 0.002 - 0.06 %, respectively. This shows that PSD features of vertical EOG are indispensable, whereas MaxCC can be neglected. Mean classification accuracies were estimated at 86.6±b 1.3 % and 92.3±b 0.2 % for GRLVQ and SVM, respec-tively. GRLVQ permits objective feature reduction by inclu-sion of all processing stages, but is not as accurate as SVM.

M3 spectral analysis of lunar swirls and the link between optical maturation and surface hydroxyl formation at magnetic anomalies

Science.gov (United States)

Kramer, G.Y.; Besse, S.; Dhingra, D.; Nettles, J.; Klima, R.; Garrick-Bethell, I.; Clark, Roger N.; Combe, J.-P.; Head, J. W.; Taylor, L.A.; Pieters, C.M.; Boardman, J.; McCord, T.B.

2011-01-01

We examined the lunar swirls using data from the Moon Mineralogy Mapper (M3). The improved spectral and spatial resolution of M3 over previous spectral imaging data facilitates distinction of subtle spectral differences, and provides new information about the nature of these enigmatic features. We characterized spectral features of the swirls, interswirl regions (dark lanes), and surrounding terrain for each of three focus regions: Reiner Gamma, Gerasimovich, and Mare Ingenii. We used Principle Component Analysis to identify spectrally distinct surfaces at each focus region, and characterize the spectral features that distinguish them. We compared spectra from small, recent impact craters with the mature soils into which they penetrated to examine differences in maturation trends on- and off-swirl. Fresh, on-swirl crater spectra are higher albedo, exhibit a wider range in albedos and have well-preserved mafic absorption features compared with fresh off-swirl craters. Albedoand mafic absorptions are still evident in undisturbed, on-swirl surface soils, suggesting the maturation process is retarded. The spectral continuum is more concave compared with off-swirl spectra; a result of the limited spectral reddening being mostly constrained to wavelengths less than ∼1500 nm. Off-swirl spectra show very little reddening or change in continuum shape across the entire M3 spectral range. Off-swirl spectra are dark, have attenuated absorption features, and the narrow range in off-swirl albedos suggests off-swirl regions mature rapidly. Spectral parameter maps depicting the relative OH surface abundance for each of our three swirl focus regions were created using the depth of the hydroxyl absorption feature at 2.82 μm. For each of the studied regions, the 2.82 μm absorption feature is significantly weaker on-swirl than off-swirl, indicating the swirls are depleted in OH relative to their surroundings. The spectral characteristics of the swirls and adjacent terrains

[Progress in the spectral library based protein identification strategy].

Science.gov (United States)

Yu, Derui; Ma, Jie; Xie, Zengyan; Bai, Mingze; Zhu, Yunping; Shu, Kunxian

2018-04-25

Exponential growth of the mass spectrometry (MS) data is exhibited when the mass spectrometry-based proteomics has been developing rapidly. It is a great challenge to develop some quick, accurate and repeatable methods to identify peptides and proteins. Nowadays, the spectral library searching has become a mature strategy for tandem mass spectra based proteins identification in proteomics, which searches the experiment spectra against a collection of confidently identified MS/MS spectra that have been observed previously, and fully utilizes the abundance in the spectrum, peaks from non-canonical fragment ions, and other features. This review provides an overview of the implement of spectral library search strategy, and two key steps, spectral library construction and spectral library searching comprehensively, and discusses the progress and challenge of the library search strategy.

All-optical OFDM demultiplexing by spectral magnification and band-pass filtering.

Science.gov (United States)

Palushani, E; Mulvad, H C Hansen; Kong, D; Guan, P; Galili, M; Oxenløwe, L K

2014-01-13

We propose a simple OFDM receiver allowing for the use of standard WDM receivers to receive spectrally advanced OFDM signals. We propose to spectrally magnify the optical-OFDM super-channels using a spectral telescope consisting of two time-lenses, which enables reduced inter-carrier-interference in subcarrier detection by simple band-pass filtering. A demonstration on an emulated 100 Gbit/s DPSK optical-OFDM channel shows improved sensitivities after 4-times spectral magnification.

Stellar Spectral Classification with Minimum Within-Class and ...

Indian Academy of Sciences (India)

spectral classification methods, and it is widely used in practice. But its ... Digital Sky Survey (SDSS) show that MMSVM performs better than. SVM. Key words. ... to feature extraction, and then the traditional classifier SVM is used to classify the.

Synthetic spectral analysis of a kinetic model for slow-magnetosonic waves in solar corona

Energy Technology Data Exchange (ETDEWEB)

Ruan, Wenzhi; He, Jiansen; Tu, Chuanyi; Wang, Linghua [School of Earth and Space Sciences, Peking University, Beijing, 100871, China, E-mail: jshept@gmail.com (China); Zhang, Lei [State Key Laboratory of Space Weather, Chinese Academy of Sciences, Beijing 100190 (China); Vocks, Christian [Leibniz-Institut für Astrophysik Potsdam, 14482, Potsdam (Germany); Marsch, Eckart [Institute for Experimental and Applied Physics, Christian-Albrechts-Universität zu Kiel, 24118 Kiel (Germany); Peter, Hardi [Max Plank Institut für Sonnensystemforschung, Justus-von-Liebig-Weg 3, 37077 Göttingen (Germany)

2016-03-25

We propose a kinetic model of slow-magnetosonic waves to explain various observational features associated with the propagating intensity disturbances (PIDs) occurring in the solar corona. The characteristics of slow mode waves, e.g, inphase oscillations of density, velocity, and thermal speed, are reproduced in this kinetic model. Moreover, the red-blue (R-B) asymmetry of the velocity distribution as self-consistently generated in the model is found to be contributed from the beam component, as a result of the competition between Landau resonance and Coulomb collisions. Furthermore, we synthesize the spectral lines and make the spectral analysis, based on the kinetic simulation data of the flux tube plasmas and the hypothesis of the surrounding background plasmas. It is found that the fluctuations of parameters of the synthetic spectral lines are basically consistent with the observations: (1) the line intensity, Doppler shift, and line width are fluctuating in phase; (2) the R-B asymmetry usually oscillate out of phase with the former three parameters; (3) the blueward asymmetry is more evident than the redward asymmetry in the R-B fluctuations. The oscillations of line parameters become weakened for the case with denser surrounding background plasmas. Similar to the observations, there is no doubled-frequency oscillation of the line width for the case with flux-tube plasmas flowing bulkly upward among the static background plasmas. Therefore, we suggest that the “wave + beam flow” kinetic model may be a viable interpretation for the PIDs observed in the solar corona.

Raman spectral feature selection using ant colony optimization for breast cancer diagnosis.

Science.gov (United States)

Fallahzadeh, Omid; Dehghani-Bidgoli, Zohreh; Assarian, Mohammad

2018-06-04

Pathology as a common diagnostic test of cancer is an invasive, time-consuming, and partially subjective method. Therefore, optical techniques, especially Raman spectroscopy, have attracted the attention of cancer diagnosis researchers. However, as Raman spectra contain numerous peaks involved in molecular bounds of the sample, finding the best features related to cancerous changes can improve the accuracy of diagnosis in this method. The present research attempted to improve the power of Raman-based cancer diagnosis by finding the best Raman features using the ACO algorithm. In the present research, 49 spectra were measured from normal, benign, and cancerous breast tissue samples using a 785-nm micro-Raman system. After preprocessing for removal of noise and background fluorescence, the intensity of 12 important Raman bands of the biological samples was extracted as features of each spectrum. Then, the ACO algorithm was applied to find the optimum features for diagnosis. As the results demonstrated, by selecting five features, the classification accuracy of the normal, benign, and cancerous groups increased by 14% and reached 87.7%. ACO feature selection can improve the diagnostic accuracy of Raman-based diagnostic models. In the present study, features corresponding to ν(C-C) αhelix proline, valine (910-940), νs(C-C) skeletal lipids (1110-1130), and δ(CH2)/δ(CH3) proteins (1445-1460) were selected as the best features in cancer diagnosis.

Understanding the features in the ultrafast transient absorption spectra of CdSe quantum dots

Energy Technology Data Exchange (ETDEWEB)

Zhang, Cheng; Do, Thanh Nhut [Division of Chemistry and Biological Chemistry, School of Physical and Mathematical Sciences, Nanyang Technological University, 21 Nanyang Link, Singapore 637371 (Singapore); Ong, Xuanwei [Department of Chemistry, National University of Singapore, 3 Science Drive 3, Singapore 117543 (Singapore); Chan, Yinthai [Department of Chemistry, National University of Singapore, 3 Science Drive 3, Singapore 117543 (Singapore); Institute of Materials Research & Engineering, A*STAR, 2 Fusionopolis Way, Innovis, Singapore 138634 (Singapore); Tan, Howe-Siang, E-mail: howesiang@ntu.edu.sg [Division of Chemistry and Biological Chemistry, School of Physical and Mathematical Sciences, Nanyang Technological University, 21 Nanyang Link, Singapore 637371 (Singapore)

2016-12-20

We describe a model to explain the features of the ultrafast transient absorption (TA) spectra of CdSe core type quantum dots (QDs). The measured TA spectrum consists of contributions by the ground state bleach (GSB), stimulated emission (SE) and excited state absorption (ESA) processes associated with the three lowest energy transition of the QDs. We model the shapes of the GSB, SE and ESA spectral components after fits to the linear absorption. The spectral positions of the ESA components take into account the biexcitonic binding energy. In order to obtain the correct weightage of the GSB, SE and ESA components to the TA spectrum, we enumerate the set of coherence transfer pathways associated with these processes. From our fits of the experimental TA spectra of 65 Å diameter QDs, biexcitonic binding energies for the three lowest energy transitions are obtained.

Predicting borderline personality disorder features from personality traits, identity orientation, and attachment styles in Italian nonclinical adults: issues of consistency across age ranges.

Science.gov (United States)

Fossati, Andrea; Borroni, Serena; Feeney, Judith; Maffei, Cesare

2012-04-01

The aims of this study were to assess whether Borderline Personality Disorder (BPD) features could be predicted by Big Five traits, impulsivity, identity orientation, and adult attachment patterns in a sample of 1,192 adult nonclinical participants, and to evaluate the consistency of these regression models across four age groups (49 years, and >50 years, respectively). In the full sample, measures of neuroticism (N), impulsivity, and anxious insecure attachment were substantial predictors of BPD features (adjusted R(2) = .38, p personality traits and disturbed attachment patterns.

On the spectral dependence of the critical temperature of superconductors

International Nuclear Information System (INIS)

Combescot, R.

1989-01-01

The authors have solved analytically the linearized Eliashberg equations for T c in the weak coupling limit. The corrections to their result go to zero in this limit. Their calculation is valid for any spectral shape. They find a smooth dependence of T c on the spectral shape. Only the gross features of the spectrum are relevant. The authors propose for T c an interpolation formula valid for any coupling strength and any spectral shape. This formula is in good agreement with known numerical results. It agrees with all the qualitative behavior obtained from computer work

Spectral zone selection methodology for pebble bed reactors

International Nuclear Information System (INIS)

Mphahlele, Ramatsemela; Ougouag, Abderrafi M.; Ivanov, Kostadin N.; Gougar, Hans D.

2011-01-01

A methodology is developed for determining boundaries of spectral zones for pebble bed reactors. A spectral zone is defined as a region made up of a number of nodes whose characteristics are collectively similar and that are assigned the same few-group diffusion constants. The spectral zones are selected in such a manner that the difference (error) between the reference transport solution and the diffusion code solution takes a minimum value. This is achieved by choosing spectral zones through optimally minimizing this error. The objective function for the optimization algorithm is the total reaction rate error, which is defined as the sum of the leakage, absorption and fission reaction rates errors in each zone. The selection of these spectral zones is such that the core calculation results based on diffusion theory are within an acceptable tolerance as compared to a proper transport reference solution. Through this work, a consistent approach for identifying spectral zones that yield more accurate diffusion results is introduced.

Spectral gamuts and spectral gamut mapping

Science.gov (United States)

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.

Quantum gravity boundary terms from the spectral action of noncommutative space.

Science.gov (United States)

Chamseddine, Ali H; Connes, Alain

2007-08-17

We study the boundary terms of the spectral action of the noncommutative space, defined by the spectral triple dictated by the physical spectrum of the standard model, unifying gravity with all other fundamental interactions. We prove that the spectral action predicts uniquely the gravitational boundary term required for consistency of quantum gravity with the correct sign and coefficient. This is a remarkable result given the lack of freedom in the spectral action to tune this term.

Color features for quality control in ceramic tile industry

Science.gov (United States)

Kukkonen, Saku; Kaelviaeinen, Heikki; Parkkinen, Jussi P.

2001-02-01

We study visual quality control in the ceramics industry. In the manufacturing, it is important that in each set of tiles, every single tile looks similar. Currently, the estimation is usually done by human vision. Our goal is to design a machine vision system that can estimate the sufficient similarity, or same appearance, to the human eye. Our main approach is to use accurate spectral representation of color, and compare spectral features to the RGB color features. A laboratory system for color measurements is built. Experimentations with five classes of brown tiles are presented and discussed. In addition to the k-nearest neighbor (k-NN) classifier, a neural network called the self-organizing map (SOM) is used to provide understanding of the spectral features. Every single spectrum in each tile of a training set is used as input to a 2D SOM. The SOM is analyzed to understand how spectra are clustered. As a result, tiles are classified using a trained 2D SOM. It is also of interest to know whether the order of spectral colors can be determined. In our approach, all spectra are clustered in a 1D SOM, and each pixel spectrum) is presented by pseudocolors according to the trained nodes. Finally, the results are compared to experiments with human vision.

Spectral evidence for amorphous silicates in least-processed CO meteorites and their parent bodies

Science.gov (United States)

McAdam, Margaret M.; Sunshine, Jessica M.; Howard, Kieren T.; Alexander, Conel M.; McCoy, Timothy J.; Bus, Schelte J.

2018-05-01

Least-processed carbonaceous chondrites (carbonaceous chondrites that have experienced minimal aqueous alteration and thermal metamorphism) are characterized by their predominately amorphous iron-rich silicate interchondrule matrices and chondrule rims. This material is highly susceptible to destruction by the parent body processes of thermal metamorphism or aqueous alteration. The presence of abundant amorphous material in a meteorite indicates that the parent body, or at least a region of the parent body, experienced minimal processing since the time of accretion. The CO chemical group of carbonaceous chondrites has a significant number of these least-processed samples. We present visible/near-infrared and mid-infrared spectra of eight least-processed CO meteorites (petrologic type 3.0-3.1). In the visible/near-infrared, these COs are characterized by a broad weak feature that was first observed by Cloutis et al. (2012) to be at 1.3-μm and attributed to iron-rich amorphous silicate matrix materials. This feature is observed to be centered at 1.4-μm for terrestrially unweathered, least-processed CO meteorites. At mid-infrared wavelengths, a 21-μm feature, consistent with Si-O vibrations of amorphous materials and glasses, is also present. The spectral features of iron-rich amorphous silicate matrix are absent in both the near- and mid-infrared spectra of higher metamorphic grade COs because this material has recrystallized as crystalline olivine. Furthermore, spectra of least-processed primitive meteorites from other chemical groups (CRs, MET 00426 and QUE 99177, and C2-ungrouped Acfer 094), also exhibit a 21-μm feature. Thus, we conclude that the 1.4- and 21-μm features are characteristic of primitive least-processed meteorites from all chemical groups of carbonaceous chondrites. Finally, we present an IRTF + SPeX observation of asteroid (93) Minerva that has spectral similarities in the visible/near-infrared to the least-processed CO carbonaceous chondrites

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

Science.gov (United States)

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

2014-10-01

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

Widespread distribution of OH/H2O on the lunar surface inferred from spectral data.

Science.gov (United States)

Bandfield, Joshua L; Poston, Michael J; Klima, Rachel L; Edwards, Christopher S

2018-01-01

Remote sensing data from lunar orbiters have revealed spectral features consistent with the presence of OH or H 2 O on the lunar surface. Analyses of data from the Moon Mineralogy Mapper spectrometer onboard the Chandryaan-1 spacecraft have suggested that OH/H 2 O is recycled on diurnal timescales and persists only at high latitudes. However, the spatial distribution and temporal variability of the OH/H 2 O, as well as its source, remain uncertain. Here we incorporate a physics-based thermal correction into analysis of reflectance spectra from the Moon Mineralogy Mapper and find that prominent absorption features consistent with OH/H 2 O can be present at all latitudes, local times, and surface types examined. This suggests the widespread presence of OH/H 2 O on the lunar surface without significant diurnal migration. We suggest that the spectra are consistent with the production of OH in space weathered materials by the solar wind implantation of H + and formation of OH at crystal defect sites, as opposed to H 2 O sourced from the lunar interior. Regardless of the specific composition or formation mechanism, we conclude that OH/H 2 O can be present on the Moon under thermal conditions more wide-ranging than previously recognized.

A SELF-CONSISTENT MODEL OF THE CIRCUMSTELLAR DEBRIS CREATED BY A GIANT HYPERVELOCITY IMPACT IN THE HD 172555 SYSTEM

International Nuclear Information System (INIS)

Johnson, B. C.; Melosh, H. J.; Lisse, C. M.; Chen, C. H.; Wyatt, M. C.; Thebault, P.; Henning, W. G.; Gaidos, E.; Elkins-Tanton, L. T.; Bridges, J. C.; Morlok, A.

2012-01-01

Spectral modeling of the large infrared excess in the Spitzer IRS spectra of HD 172555 suggests that there is more than 10 19 kg of submicron dust in the system. Using physical arguments and constraints from observations, we rule out the possibility of the infrared excess being created by a magma ocean planet or a circumplanetary disk or torus. We show that the infrared excess is consistent with a circumstellar debris disk or torus, located at ∼6 AU, that was created by a planetary scale hypervelocity impact. We find that radiation pressure should remove submicron dust from the debris disk in less than one year. However, the system's mid-infrared photometric flux, dominated by submicron grains, has been stable within 4% over the last 27 years, from the Infrared Astronomical Satellite (1983) to WISE (2010). Our new spectral modeling work and calculations of the radiation pressure on fine dust in HD 172555 provide a self-consistent explanation for this apparent contradiction. We also explore the unconfirmed claim that ∼10 47 molecules of SiO vapor are needed to explain an emission feature at ∼8 μm in the Spitzer IRS spectrum of HD 172555. We find that unless there are ∼10 48 atoms or 0.05 M ⊕ of atomic Si and O vapor in the system, SiO vapor should be destroyed by photo-dissociation in less than 0.2 years. We argue that a second plausible explanation for the ∼8 μm feature can be emission from solid SiO, which naturally occurs in submicron silicate ''smokes'' created by quickly condensing vaporized silicate.

Spectral Lag Evolution among γ-Ray Burst Pulses Lan-Wei Jia1 ...

Indian Academy of Sciences (India)

pulses with observations by CGRO/BATSE. No universal spectral lag evolution feature and pulse luminosity-lag relation within a GRB is observed. ... Key words. γ-rays: bursts—spectral lag—GRB pulse. 1. Introduction. It is found that soft photons lag behind the hard photons and is usually seen in long. GRBs (e.g., Norris et ...

Semiconductor Laser Multi-Spectral Sensing and Imaging

Directory of Open Access Journals (Sweden)

Han Q. Le

2010-01-01

Full Text Available Multi-spectral laser imaging is a technique that can offer a combination of the laser capability of accurate spectral sensing with the desirable features of passive multispectral imaging. The technique can be used for detection, discrimination, and identification of objects by their spectral signature. This article describes and reviews the development and evaluation of semiconductor multi-spectral laser imaging systems. Although the method is certainly not specific to any laser technology, the use of semiconductor lasers is significant with respect to practicality and affordability. More relevantly, semiconductor lasers have their own characteristics; they offer excellent wavelength diversity but usually with modest power. Thus, system design and engineering issues are analyzed for approaches and trade-offs that can make the best use of semiconductor laser capabilities in multispectral imaging. A few systems were developed and the technique was tested and evaluated on a variety of natural and man-made objects. It was shown capable of high spectral resolution imaging which, unlike non-imaging point sensing, allows detecting and discriminating objects of interest even without a priori spectroscopic knowledge of the targets. Examples include material and chemical discrimination. It was also shown capable of dealing with the complexity of interpreting diffuse scattered spectral images and produced results that could otherwise be ambiguous with conventional imaging. Examples with glucose and spectral imaging of drug pills were discussed. Lastly, the technique was shown with conventional laser spectroscopy such as wavelength modulation spectroscopy to image a gas (CO. These results suggest the versatility and power of multi-spectral laser imaging, which can be practical with the use of semiconductor lasers.

Semiconductor laser multi-spectral sensing and imaging.

Science.gov (United States)

Le, Han Q; Wang, Yang

2010-01-01

Multi-spectral laser imaging is a technique that can offer a combination of the laser capability of accurate spectral sensing with the desirable features of passive multispectral imaging. The technique can be used for detection, discrimination, and identification of objects by their spectral signature. This article describes and reviews the development and evaluation of semiconductor multi-spectral laser imaging systems. Although the method is certainly not specific to any laser technology, the use of semiconductor lasers is significant with respect to practicality and affordability. More relevantly, semiconductor lasers have their own characteristics; they offer excellent wavelength diversity but usually with modest power. Thus, system design and engineering issues are analyzed for approaches and trade-offs that can make the best use of semiconductor laser capabilities in multispectral imaging. A few systems were developed and the technique was tested and evaluated on a variety of natural and man-made objects. It was shown capable of high spectral resolution imaging which, unlike non-imaging point sensing, allows detecting and discriminating objects of interest even without a priori spectroscopic knowledge of the targets. Examples include material and chemical discrimination. It was also shown capable of dealing with the complexity of interpreting diffuse scattered spectral images and produced results that could otherwise be ambiguous with conventional imaging. Examples with glucose and spectral imaging of drug pills were discussed. Lastly, the technique was shown with conventional laser spectroscopy such as wavelength modulation spectroscopy to image a gas (CO). These results suggest the versatility and power of multi-spectral laser imaging, which can be practical with the use of semiconductor lasers.

Cobalt-related features of spectral and magnetic properties of RNi{sub 4}Co (R=Ho, Er)

Energy Technology Data Exchange (ETDEWEB)

Lukoyanov, A.V., E-mail: lukoyanov@imp.uran.ru [Institute of Metal Physics, Russian Academy of Sciences–Ural Branch, 620990 Yekaterinburg (Russian Federation); Ural Federal University, 620002 Yekaterinburg (Russian Federation); Knyazev, Yu.V.; Kuz‘min, Yu.I.; Kuchin, A.G. [Institute of Metal Physics, Russian Academy of Sciences–Ural Branch, 620990 Yekaterinburg (Russian Federation)

2014-11-15

In this paper we investigate spectral and magnetic properties of RNi{sub 4}Co (R=Ho, Er) intermetallics to reveal the features associated with the presence of Co substituting ion in comparison with the parent HoNi{sub 5} and ErNi{sub 5} compounds. Our ab initio LSDA+U calculations show that in the electronic structure Co states are strongly manifested near the Fermi energy for the case of Co in 2c position, while Co in 3g position results only in weak changes of the total DOS curve. Theoretical optical conductivity calculated assuming Co equally redistributed among 2c or 3g positions agrees well with the experimental optical conductivity. Cobalt ion in RNi{sub 4}Co (R=Ho, Er) is characterized by magnetic moment of 1μ{sub B} that increases exchange interaction in the 3d sublattice by several times that contributes to the growth of Curie temperature in comparison with the parent compounds. - Highlights: • Electronic structure of RNi4Co (R=Ho, Er) is calculated in LSDA+U. • Cobalt ion is considered in 2c or 3g position and compared. • Experimental optical conductivity is interpreted based on the calculated one.

A Spectral-Texture Kernel-Based Classification Method for Hyperspectral Images

Directory of Open Access Journals (Sweden)

Yi Wang

2016-11-01

Full Text Available Classification of hyperspectral images always suffers from high dimensionality and very limited labeled samples. Recently, the spectral-spatial classification has attracted considerable attention and can achieve higher classification accuracy and smoother classification maps. In this paper, a novel spectral-spatial classification method for hyperspectral images by using kernel methods is investigated. For a given hyperspectral image, the principle component analysis (PCA transform is first performed. Then, the first principle component of the input image is segmented into non-overlapping homogeneous regions by using the entropy rate superpixel (ERS algorithm. Next, the local spectral histogram model is applied to each homogeneous region to obtain the corresponding texture features. Because this step is performed within each homogenous region, instead of within a fixed-size image window, the obtained local texture features in the image are more accurate, which can effectively benefit the improvement of classification accuracy. In the following step, a contextual spectral-texture kernel is constructed by combining spectral information in the image and the extracted texture information using the linearity property of the kernel methods. Finally, the classification map is achieved by the support vector machines (SVM classifier using the proposed spectral-texture kernel. Experiments on two benchmark airborne hyperspectral datasets demonstrate that our method can effectively improve classification accuracies, even though only a very limited training sample is available. Specifically, our method can achieve from 8.26% to 15.1% higher in terms of overall accuracy than the traditional SVM classifier. The performance of our method was further compared to several state-of-the-art classification methods of hyperspectral images using objective quantitative measures and a visual qualitative evaluation.

Optimized feature subsets for epileptic seizure prediction studies.

Science.gov (United States)

Direito, Bruno; Ventura, Francisco; Teixeira, César; Dourado, António

2011-01-01

The reduction of the number of EEG features to give as inputs to epilepsy seizure predictors is a needed step towards the development of a transportable device for real-time warning. This paper presents a comparative study of three feature selection methods, based on Support Vector Machines. Minimum-Redundancy Maximum-Relevance, Recursive Feature Elimination, Genetic Algorithms, show that, for three patients of the European Database on Epilepsy, the most important univariate features are related to spectral information and statistical moments.

EOG feature relevance determination for microsleep detection

OpenAIRE

Golz Martin; Wollner Sebastian; Sommer David; Schnieder Sebastian

2017-01-01

Automatic relevance determination (ARD) was applied to two-channel EOG recordings for microsleep event (MSE) recognition. 10 s immediately before MSE and also before counterexamples of fatigued, but attentive driving were analysed. Two type of signal features were extracted: the maximum cross correlation (MaxCC) and logarithmic power spectral densities (PSD) averaged in spectral bands of 0.5 Hz width ranging between 0 and 8 Hz. Generalised learn-ing vector quantisation (GRLVQ) was used as ARD...

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

Science.gov (United States)

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. ...

Detecting Molecular Features of Spectra Mainly Associated with Structural and Non-Structural Carbohydrates in Co-Products from BioEthanol Production Using DRIFT with Uni- and Multivariate Molecular Spectral Analyses

Science.gov (United States)

Yu, Peiqiang; Damiran, Daalkhaijav; Azarfar, Arash; Niu, Zhiyuan

2011-01-01

The objective of this study was to use DRIFT spectroscopy with uni- and multivariate molecular spectral analyses as a novel approach to detect molecular features of spectra mainly associated with carbohydrate in the co-products (wheat DDGS, corn DDGS, blend DDGS) from bioethanol processing in comparison with original feedstock (wheat (Triticum), corn (Zea mays)). The carbohydrates related molecular spectral bands included: A_Cell (structural carbohydrates, peaks area region and baseline: ca. 1485–1188 cm−1), A_1240 (structural carbohydrates, peak area centered at ca. 1240 cm−1 with region and baseline: ca. 1292–1198 cm−1), A_CHO (total carbohydrates, peaks region and baseline: ca. 1187–950 cm−1), A_928 (non-structural carbohydrates, peak area centered at ca. 928 cm−1 with region and baseline: ca. 952–910 cm−1), A_860 (non-structural carbohydrates, peak area centered at ca. 860 cm−1 with region and baseline: ca. 880–827 cm−1), H_1415 (structural carbohydrate, peak height centered at ca. 1415 cm−1 with baseline: ca. 1485–1188 cm−1), H_1370 (structural carbohydrate, peak height at ca. 1370 cm−1 with a baseline: ca. 1485–1188 cm−1). The study shows that the grains had lower spectral intensity (KM Unit) of the cellulosic compounds of A_1240 (8.5 vs. 36.6, P carbohydrate of A_928 (17.3 vs. 2.0) and A_860 (20.7 vs. 7.6) than their co-products from bioethanol processing. There were no differences (P > 0.05) in the peak area intensities of A_Cell (structural CHO) at 1292–1198 cm−1 and A_CHO (total CHO) at 1187–950 cm−1 with average molecular infrared intensity KM unit of 226.8 and 508.1, respectively. There were no differences (P > 0.05) in the peak height intensities of H_1415 and H_1370 (structural CHOs) with average intensities 1.35 and 1.15, respectively. The multivariate molecular spectral analyses were able to discriminate and classify between the corn and corn DDGS molecular spectra, but not wheat and wheat DDGS. This

SPAM- SPECTRAL ANALYSIS MANAGER (UNIX VERSION)

Science.gov (United States)

Solomon, J. E.

1994-01-01

The Spectral Analysis Manager (SPAM) was developed to allow easy qualitative analysis of multi-dimensional imaging spectrometer data. Imaging spectrometers provide sufficient spectral sampling to define unique spectral signatures on a per pixel basis. Thus direct material identification becomes possible for geologic studies. SPAM provides a variety of capabilities for carrying out interactive analysis of the massive and complex datasets associated with multispectral remote sensing observations. In addition to normal image processing functions, SPAM provides multiple levels of on-line help, a flexible command interpretation, graceful error recovery, and a program structure which can be implemented in a variety of environments. SPAM was designed to be visually oriented and user friendly with the liberal employment of graphics for rapid and efficient exploratory analysis of imaging spectrometry data. SPAM provides functions to enable arithmetic manipulations of the data, such as normalization, linear mixing, band ratio discrimination, and low-pass filtering. SPAM can be used to examine the spectra of an individual pixel or the average spectra over a number of pixels. SPAM also supports image segmentation, fast spectral signature matching, spectral library usage, mixture analysis, and feature extraction. High speed spectral signature matching is performed by using a binary spectral encoding algorithm to separate and identify mineral components present in the scene. The same binary encoding allows automatic spectral clustering. Spectral data may be entered from a digitizing tablet, stored in a user library, compared to the master library containing mineral standards, and then displayed as a timesequence spectral movie. The output plots, histograms, and stretched histograms produced by SPAM can be sent to a lineprinter, stored as separate RGB disk files, or sent to a Quick Color Recorder. SPAM is written in C for interactive execution and is available for two different

Spectral Cauchy Characteristic Extraction: Gravitational Waves and Gauge Free News

Science.gov (United States)

Handmer, Casey; Szilagyi, Bela; Winicour, Jeff

2015-04-01

We present a fast, accurate spectral algorithm for the characteristic evolution of the full non-linear vacuum Einstein field equations in the Bondi framework. Developed within the Spectral Einstein Code (SpEC), we demonstrate how spectral Cauchy characteristic extraction produces gravitational News without confounding gauge effects. We explain several numerical innovations and demonstrate speed, stability, accuracy, exponential convergence, and consistency with existing methods. We highlight its capability to deliver physical insights in the study of black hole binaries.

Is a step in the primordial spectral index favoured by CMB data?

International Nuclear Information System (INIS)

Joy, Minu; Shafieloo, Arman; Sahni, Varun; Starobinsky, Alexei A.

2009-01-01

A sudden small change in the second derivative of the inflaton potential can result in a universal local feature in the spectrum of primordial perturbations generated during inflation. The exact solution describing this feature \\cite(minu) is characterized by a step in the spectral index modulated by characteristic oscillations and results in a large running of the spectral index localized over a few e-folds of scale. In this paper we confront this step-like feature with the 5 year WMAP results and demonstrate that it provides a better fit to this data than a featureless initial spectrum. If such a feature exists at all, then it should lie at sufficiently large scales k 0 ∼ −1 corresponding to l ∼ s localized near this scale. This feature could arise as a result of a 'mini-waterfall'-type fast second order phase transition experienced by an auxiliary heavy field during inflation, in a model similar to hybrid inflation (though for a different choice of parameters). If this is the case, then the auxiliary field should be positively coupled to the inflaton

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

Science.gov (United States)

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.

On the Use of Memory Models in Audio Features

DEFF Research Database (Denmark)

Jensen, Karl Kristoffer

2011-01-01

Audio feature estimation is potentially improved by including higher- level models. One such model is the Short Term Memory (STM) model. A new paradigm of audio feature estimation is obtained by adding the influence of notes in the STM. These notes are identified when the perceptual spectral flux...

Multispectral atmospheric mapping sensor of mesoscale water vapor features

Science.gov (United States)

Menzel, P.; Jedlovec, G.; Wilson, G.; Atkinson, R.; Smith, W.

1985-01-01

The Multispectral atmospheric mapping sensor was checked out for specified spectral response and detector noise performance in the eight visible and three infrared (6.7, 11.2, 12.7 micron) spectral bands. A calibration algorithm was implemented for the infrared detectors. Engineering checkout flights on board the ER-2 produced imagery at 50 m resolution in which water vapor features in the 6.7 micron spectral band are most striking. These images were analyzed on the Man computer Interactive Data Access System (McIDAS). Ground truth and ancillary data was accessed to verify the calibration.

Martian spectral units derived from ISM imaging spectrometer data

Science.gov (United States)

Murchie, S.; Mustard, J.; Saylor, R.

1993-01-01

Based on results of the Viking mission, the soil layer of Mars has been thought to be fairly homogeneous and to consist of a mixture of as few as two components, a 'dark gray' basaltic material and a 'bright red' altered material. However, near-infrared reflectance spectra measured recently both telescopically and from spacecraft indicate compositional heterogeneity beyond what can be explained by just two components. In particular, data from the ISM imaging spectrometer, which observed much of the equatorial region at a spatial resolution of approximately 22 km, indicate spatial differences in the presence and abundance of Fe-containing phases, hydroxylated silicates, and H2O. The ISM data was used to define, characterize, and map soil 'units' based on their spectral properties. The spatial distribution of these 'units' were compared to morphologic, visible color, and thermal inertia features recognized in Viking data.

Plasmonic spectral tunability of conductive ternary nitrides

Energy Technology Data Exchange (ETDEWEB)

Kassavetis, S.; Patsalas, P., E-mail: ppats@physics.auth.gr [Department of Physics, Aristotle University of Thessaloniki, GR-54124 Thessaloniki (Greece); Bellas, D. V.; Lidorikis, E. [Department of Materials Science and Engineering, University of Ioannina, GR-45110 Ioannina (Greece); Abadias, G. [Institut Pprime, Département Physique et Mécanique des Matériaux, Université de Poitiers-CNRS-ENSMA, 86962 Chasseneuil-Futuroscope (France)

2016-06-27

Conductive binary transition metal nitrides, such as TiN and ZrN, have emerged as a category of promising alternative plasmonic materials. In this work, we show that ternary transition metal nitrides such as Ti{sub x}Ta{sub 1−x}N, Ti{sub x}Zr{sub 1−x}N, Ti{sub x}Al{sub 1−x}N, and Zr{sub x}Ta{sub 1−x}N share the important plasmonic features with their binary counterparts, while having the additional asset of the exceptional spectral tunability in the entire visible (400–700 nm) and UVA (315–400 nm) spectral ranges depending on their net valence electrons. In particular, we demonstrate that such ternary nitrides can exhibit maximum field enhancement factors comparable with gold in the aforementioned broadband range. We also critically evaluate the structural features that affect the quality factor of the plasmon resonance and we provide rules of thumb for the selection and growth of materials for nitride plasmonics.

Accuracy in mineral identification: image spectral and spatial resolutions and mineral spectral properties

Directory of Open Access Journals (Sweden)

L. Pompilio

2006-06-01

Full Text Available Problems related to airborne hyperspectral image data are reviewed and the requirements for data analysis applied to mineralogical (rocks and soils interpretation are discussed. The variability of mineral spectral features, including absorption position, shape and depth is considered and interpreted as due to chemical composition, grain size effects and mineral association. It is also shown how this variability can be related to well defined geologic processes. The influence of sensor noise and diffuse atmospheric radiance in classification accuracy is also analyzed.

Integrated Spectral Energy Distributions and Absorption Feature Indices of Single Stellar Populations

OpenAIRE

Zhang, Fenghui; Han, Zhanwen; Li, Lifang; Hurley, Jarrod R.

2004-01-01

Using evolutionary population synthesis, we present integrated spectral energy distributions and absorption-line indices defined by the Lick Observatory image dissector scanner (referred to as Lick/IDS) system, for an extensive set of instantaneous burst single stellar populations (SSPs). The ages of the SSPs are in the range 1-19 Gyr and the metallicities [Fe/H] are in the range -2.3 - 0.2. Our models use the rapid single stellar evolution algorithm of Hurley, Pols and Tout for the stellar e...

Spectacle and SpecViz: New Spectral Analysis and Visualization Tools

Science.gov (United States)

Earl, Nicholas; Peeples, Molly; JDADF Developers

2018-01-01

A new era of spectroscopic exploration of our universe is being ushered in with advances in instrumentation and next-generation space telescopes. The advent of new spectroscopic instruments has highlighted a pressing need for tools scientists can use to analyze and explore these new data. We have developed Spectacle, a software package for analyzing both synthetic spectra from hydrodynamic simulations as well as real COS data with an aim of characterizing the behavior of the circumgalactic medium. It allows easy reduction of spectral data and analytic line generation capabilities. Currently, the package is focused on automatic determination of absorption regions and line identification with custom line list support, simultaneous line fitting using Voigt profiles via least-squares or MCMC methods, and multi-component modeling of blended features. Non-parametric measurements, such as equivalent widths, delta v90, and full-width half-max are available. Spectacle also provides the ability to compose compound models used to generate synthetic spectra allowing the user to define various LSF kernels, uncertainties, and to specify sampling.We also present updates to the visualization tool SpecViz, developed in conjunction with the JWST data analysis tools development team, to aid in the exploration of spectral data. SpecViz is an open source, Python-based spectral 1-D interactive visualization and analysis application built around high-performance interactive plotting. It supports handling general and instrument-specific data and includes advanced tool-sets for filtering and detrending one-dimensional data, along with the ability to isolate absorption regions using slicing and manipulate spectral features via spectral arithmetic. Multi-component modeling is also possible using a flexible model fitting tool-set that supports custom models to be used with various fitting routines. It also features robust user extensions such as custom data loaders and support for user

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

Science.gov (United States)

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.

Self consistent solution of the tJ model in the overdoped regime

Science.gov (United States)

Shastry, B. Sriram; Hansen, Daniel

2013-03-01

Detailed results from a recent microscopic theory of extremely correlated Fermi liquids, applied to the t-J model in two dimensions, are presented. The theory is to second order in a parameter λ, and is valid in the overdoped regime of the tJ model. The solution reported here is from Ref, where relevant equations given in Ref are self consistently solved for the square lattice. Thermodynamic variables and the resistivity are displayed at various densities and T for two sets of band parameters. The momentum distribution function and the renormalized electronic dispersion, its width and asymmetry are reported along principal directions of the zone. The optical conductivity is calculated. The electronic spectral function A (k , ω) probed in ARPES, is detailed with different elastic scattering parameters to account for the distinction between LASER and synchrotron ARPES. A high (binding) energy waterfall feature, sensitively dependent on the band hopping parameter t' is noted. This work was supported by DOE under Grant No. FG02-06ER46319.

SPECTRAL CLASSIFICATION OF GALAXIES AT 0.5 {<=} z {<=} 1 IN THE CDFS: THE ARTIFICIAL NEURAL NETWORK APPROACH

Energy Technology Data Exchange (ETDEWEB)

Teimoorinia, H., E-mail: hteimoo@uvic.ca [Department of Physics and Astronomy, University of Victoria, Victoria, British Columbia, V8P 1A1 (Canada)

2012-12-01

The aim of this work is to combine spectral energy distribution (SED) fitting with artificial neural network techniques to assign spectral characteristics to a sample of galaxies at 0.5 < z < 1. The sample is selected from the spectroscopic campaign of the ESO/GOODS-South field, with 142 sources having photometric data from the GOODS-MUSIC catalog covering bands between {approx}0.4 and 24 {mu}m in 10-13 filters. We use the CIGALE code to fit photometric data to Maraston's synthesis spectra to derive mass, specific star formation rate, and age, as well as the best SED of the galaxies. We use the spectral models presented by Kinney et al. as targets in the wavelength interval {approx}1200-7500 A. Then a series of neural networks are trained, with average performance {approx}90%, to classify the best SED in a supervised manner. We consider the effects of the prominent features of the best SED on the performance of the trained networks and also test networks on the galaxy spectra of Coleman et al., which have a lower resolution than the target models. In this way, we conclude that the trained networks take into account all the features of the spectra simultaneously. Using the method, 105 out of 142 galaxies of the sample are classified with high significance. The locus of the classified galaxies in the three graphs of the physical parameters of mass, age, and specific star formation rate appears consistent with the morphological characteristics of the galaxies.

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

Science.gov (United States)

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.

Feature study of hysterical blindness EEG based on FastICA with combined-channel information.

Science.gov (United States)

Qin, Xuying; Wang, Wei; Hu, Lintao; Wang, Xu; Yuan, Xiaojie

2015-01-01

An appropriate feature study of hysteria electroencephalograms (EEG) would provide new insights into neural mechanisms of the disease, and also make improvements in patient diagnosis and management. The objective of this paper is to provide an explanation for what causes a particular visual loss, by associating the features of hysterical blindness EEG with brain function. An idea for the novel feature extraction for hysterical blindness EEG, utilizing combined-channel information, was applied in this paper. After channels had been combined, the sliding-window-FastICA was applied to process the combined normal EEG and hysteria EEG, respectively. Kurtosis features were calculated from the processed signals. As the comparison feature, the power spectral density of normal and hysteria EEG were computed. According to the feature analysis results, a region of brain dysfunction was located at the occipital lobe, O1 and O2. Furthermore, new abnormality was found at the parietal lobe, C3, C4, P3, and P4, that provided us with a new perspective for understanding hysterical blindness. Indicated by the kurtosis results which were consistent with brain function and the clinical diagnosis, our method was found to be a useful tool to capture features in hysterical blindness EEG.

Tomographic spectral imaging: microanalysis in 3D

International Nuclear Information System (INIS)

Kotula, P.G.; Keenan, M.R.; Michael, J.R.

2003-01-01

Full text: Spectral imaging, where a series of complete x-ray spectra are typically collected from a 2D area, holds great promise for comprehensive near-surface microanalysis. There are however numerous microanalysis problems where 3D chemical information is needed as well. In the SEM, some sort of sectioning (either mechanical or with a focused ion beam (FIB) tool) followed by x-ray mapping has, in the past, been utilized in an attempt to perform 3D microanalysis. Reliance on simple mapping has the potential to miss important chemical features as well as misidentify others. In this paper we will describe the acquisition of serial-section tomographic spectral images (TSI) with a dual-beam FIB/SEM equipped with an EDS system. We will also describe the application of a modified version of our multivariate statistical analysis algorithms to TSIs. Serial sectioning was performed with a FEI DB-235 FIB/SEM. Firstly, the specimen normal was tilted to the optic axis of the FIB column and a trench was milled into the surface of the specimen. A second trench was then milled perpendicular to the first to provide visibility of the entire analysis surface to the x-ray detector. In addition, several fiducial markers were milled into the surface to allow for alignment from slice to slice. The electron column is at an angle of 52 deg to the ion column so the electron beam can 'see' the analysis surface milled by the FIB with no additional specimen tilting or rotation. Likewise the x-ray detector is at a radial angle of 45 deg to the plane of the electron and ion columns (about the electron column) and a take-off-angle of 35 deg with respect to an untilted specimen so it can 'see' the analysis surface as well with no additional sample tilting or rotation. Spectral images were acquired from regions 40 μm wide and 20μm deep for each slice. Approximately 1μm/slice was milled and 10-12 total slices were cut. Spectral images were acquired with a Thermo NORAN Vantage (Digital imaging

A SELF-CONSISTENT MODEL OF THE CIRCUMSTELLAR DEBRIS CREATED BY A GIANT HYPERVELOCITY IMPACT IN THE HD 172555 SYSTEM

Energy Technology Data Exchange (ETDEWEB)

Johnson, B. C.; Melosh, H. J. [Department of Physics, Purdue University, 525 Northwestern Avenue, West Lafayette, IN 47907 (United States); Lisse, C. M. [JHU-APL, 11100 Johns Hopkins Road, Laurel, MD 20723 (United States); Chen, C. H. [STScI, 3700 San Martin Drive, Baltimore, MD 21218 (United States); Wyatt, M. C. [Institute of Astronomy, University of Cambridge, Madingley Road, Cambridge CB3 0HA (United Kingdom); Thebault, P. [LESIA, Observatoire de Paris, F-92195 Meudon Principal Cedex (France); Henning, W. G. [NASA Goddard Space Flight Center, 8800 Greenbelt Road, Greenbelt, MD 20771 (United States); Gaidos, E. [Department of Geology and Geophysics, University of Hawaii at Manoa, Honolulu, HI 96822 (United States); Elkins-Tanton, L. T. [Department of Terrestrial Magnetism, Carnegie Institution for Science, Washington, DC 20015 (United States); Bridges, J. C. [Department of Physics and Astronomy, University of Leicester, Leicester LE1 7RH (United Kingdom); Morlok, A., E-mail: johns477@purdue.edu [Department of Physical Sciences, Open University, Walton Hall, Milton Keynes MK7 6AA (United Kingdom)

2012-12-10

Spectral modeling of the large infrared excess in the Spitzer IRS spectra of HD 172555 suggests that there is more than 10{sup 19} kg of submicron dust in the system. Using physical arguments and constraints from observations, we rule out the possibility of the infrared excess being created by a magma ocean planet or a circumplanetary disk or torus. We show that the infrared excess is consistent with a circumstellar debris disk or torus, located at {approx}6 AU, that was created by a planetary scale hypervelocity impact. We find that radiation pressure should remove submicron dust from the debris disk in less than one year. However, the system's mid-infrared photometric flux, dominated by submicron grains, has been stable within 4% over the last 27 years, from the Infrared Astronomical Satellite (1983) to WISE (2010). Our new spectral modeling work and calculations of the radiation pressure on fine dust in HD 172555 provide a self-consistent explanation for this apparent contradiction. We also explore the unconfirmed claim that {approx}10{sup 47} molecules of SiO vapor are needed to explain an emission feature at {approx}8 {mu}m in the Spitzer IRS spectrum of HD 172555. We find that unless there are {approx}10{sup 48} atoms or 0.05 M{sub Circled-Plus} of atomic Si and O vapor in the system, SiO vapor should be destroyed by photo-dissociation in less than 0.2 years. We argue that a second plausible explanation for the {approx}8 {mu}m feature can be emission from solid SiO, which naturally occurs in submicron silicate ''smokes'' created by quickly condensing vaporized silicate.

a Novel Deep Convolutional Neural Network for Spectral-Spatial Classification of Hyperspectral Data

Science.gov (United States)

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.

Luminosity and Redshift dependence of quasar spectral properties

Energy Technology Data Exchange (ETDEWEB)

Daniel E. Vanden Berk et al.

2004-03-09

Using a large sample of quasar spectra from the SDSS, we examine the composite spectral trends of quasars as functions of both redshift and luminosity, independently of one another. Aside from the well known Baldwin effect (BE)--the decrease of line equivalent width with luminosity--the average spectral properties are remarkably similar. Host galaxy contamination and the BE are the primary causes for apparent changes in the average spectral slope of the quasars. The BE is detected for most emission lines, including the Balmer lines, but with several exceptions including NV1240A. Emission line shifts of several lines are associated with the BE. The BE is mainly a function of luminosity, but also partly a function of redshift in that line equivalent widths become stronger with redshift. Some of the complex iron features change with redshift, particularly near the small blue bump region.

Classical diffusion, Anderson localization, and spectral statistics in billiard chains

International Nuclear Information System (INIS)

Dittrich, T.; Doron, E.; Smilansky, U.

1993-03-01

We study spectral properties of quasi one-dimensional extended systems that show deterministic diffusion on the classical level and Anderson localization in the quantal description. Using semiclassical arguments, we relate to universal aspects of the spectral fluctuations to features of the set of classical periodic orbits, expressed in terms of probability to perform periodic motion, that are likewise universal. This allows to derive an analytical expression for the spectral form factor which reflects the diffusive nature of the corresponding classical dynamics. It defines a novel spectral universality class which covers the transition between GOE statistics in the limit of a small ratio of the system size to the localization length, corresponding to the metallic regime of disordered systems, to Poissonian level fluctuations in the opposite limit. Our semiclassical predictions are illustrated and confirmed by a numerical investigation of aperiodic chains of chaotic billiards. (authors)

Consistent measurements comparing the drift features of noble gas mixtures

CERN Document Server

Becker, U; Fortunato, E M; Kirchner, J; Rosera, K; Uchida, Y

1999-01-01

We present a consistent set of measurements of electron drift velocities and Lorentz deflection angles for all noble gases with methane and ethane as quenchers in magnetic fields up to 0.8 T. Empirical descriptions are also presented. Details on the World Wide Web allow for guided design and optimization of future detectors.

Evaluating automatic laughter segmentation in meetings using acoustic and acoustic-phonetic features

NARCIS (Netherlands)

Truong, K.P.; Leeuwen, D.A. van

2007-01-01

In this study, we investigated automatic laughter segmentation in meetings. We first performed laughterspeech discrimination experiments with traditional spectral features and subsequently used acousticphonetic features. In segmentation, we used Gaussian Mixture Models that were trained with

Spectral features of the tunneling-induced transparency and the Autler-Townes doublet and triplet in a triple quantum dot.

Science.gov (United States)

Luo, Xiao-Qing; Li, Zeng-Zhao; Jing, Jun; Xiong, Wei; Li, Tie-Fu; Yu, Ting

2018-02-15

We theoretically investigate the spectral features of tunneling-induced transparency (TIT) and Autler-Townes (AT) doublet and triplet in a triple-quantum-dot system. By analyzing the eigenenergy spectrum of the system Hamiltonian, we can discriminate TIT and double TIT from AT doublet and triplet, respectively. For the resonant case, the presence of the TIT does not exhibit distinguishable anticrossing in the eigenenergy spectrum in the weak-tunneling regime, while the occurrence of double anticrossings in the strong-tunneling regime shows that the TIT evolves to the AT doublet. For the off-resonance case, the appearance of a new detuning-dependent dip in the absorption spectrum leads to double TIT behavior in the weak-tunneling regime due to no distinguished anticrossing occurring in the eigenenergy spectrum. However, in the strong-tunneling regime, a new detuning-dependent dip in the absorption spectrum results in AT triplet owing to the presence of triple anticrossings in the eigenenergy spectrum. Our results can be applied to quantum measurement and quantum-optics devices in solid systems.

Spectral curves of surface reflectance in some Antarctic regions

International Nuclear Information System (INIS)

Lupi, A.; Tomasi, C.; Orsini, A.; Cacciari, A.; Vitale, V.; Georgiadis, T.; Casacchia, R.; Salvatori, R.; Salvi, S.

2001-01-01

Four surface reflectance models of solar radiation were determined by examining several sets of field measurements taken for clear-sky conditions at various sites in Antarctica. Each model consists of the mean spectral curve of surface reflectance in the 0.25-2.7 μm wavelength range and of the dependence curve of total abedo on the solar elevation angle h, within the range from 5 0 to 55 0 . The TNB (Terra Nova Bay) model refers to a rocky terrain where granites are predominant; the NIS (Nansen Ice Sheet) model to a glacier surface made uneven by sastrugi and streaked by irregular fractures; the HAP (High Altitude Plateau) model to a flat ice surface covered by fresh snow and scored by light sastrugi; and the RIS (Ross Ice Shelf) model to an area covered by the sea ice pack presenting many discontinuities in the reflectance features, due to melt water lakes, puddles, refrozen ice and snow pots. The reflectance curve obtained for the TNB model presents gradually increasing values as wavelength increases through the visible spectral range and almost constant values at infrared wavelengths, giving a total albedo value equal to 0.264 at = 30 0 , which increases by about 80% through the lower range of h and decreases by 12% through the upper range. The reflectance curves of the NIS, HAP and RIS models are all peaked at visible wavelengths and exhibit decreasing values throughout the infrared spectral range, giving values of total albedo equal to 0.464, 0.738 and 0.426 at h 30 0 , respectively. These values were estimated to increase by 8-14% as h decreases from 30 0 to 5 0 and to decrease by 2-4% only as h increases from 30 0 to 55 0

Classification of Hyperspectral Images by SVM Using a Composite Kernel by Employing Spectral, Spatial and Hierarchical Structure Information

Directory of Open Access Journals (Sweden)

Yi Wang

2018-03-01

Full Text Available In this paper, we introduce a novel classification framework for hyperspectral images (HSIs by jointly employing spectral, spatial, and hierarchical structure information. In this framework, the three types of information are integrated into the SVM classifier in a way of multiple kernels. Specifically, the spectral kernel is constructed through each pixel’s vector value in the original HSI, and the spatial kernel is modeled by using the extended morphological profile method due to its simplicity and effectiveness. To accurately characterize hierarchical structure features, the techniques of Fish-Markov selector (FMS, marker-based hierarchical segmentation (MHSEG and algebraic multigrid (AMG are combined. First, the FMS algorithm is used on the original HSI for feature selection to produce its spectral subset. Then, the multigrid structure of this subset is constructed using the AMG method. Subsequently, the MHSEG algorithm is exploited to obtain a hierarchy consist of a series of segmentation maps. Finally, the hierarchical structure information is represented by using these segmentation maps. The main contributions of this work is to present an effective composite kernel for HSI classification by utilizing spatial structure information in multiple scales. Experiments were conducted on two hyperspectral remote sensing images to validate that the proposed framework can achieve better classification results than several popular kernel-based classification methods in terms of both qualitative and quantitative analysis. Specifically, the proposed classification framework can achieve 13.46–15.61% in average higher than the standard SVM classifier under different training sets in the terms of overall accuracy.

Environmental Temperature Effect on the Far-Infrared Absorption Features of Aromatic-Based Titan's Aerosol Analogs

Science.gov (United States)

Gautier, Thomas; Trainer, Melissa G.; Loeffler, Mark J.; Sebree, Joshua A.; Anderson, Carrie M.

2016-01-01

Benzene detection has been reported in Titans atmosphere both in the stratosphere at ppb levels by remote sensing and in the thermosphere at ppm levels by the Cassini's Ion and Neutral Mass Spectrometer. This detection supports the idea that aromatic and heteroaromatic reaction pathways may play an important role in Titans atmospheric chemistry, especially in the formation of aerosols. Indeed, aromatic molecules are easily dissociated by ultraviolet radiation and can therefore contribute significantly to aerosol formation. It has been shown recently that aerosol analogs produced from a gas mixture containing a low concentration of aromatic and/or heteroaromatic molecules (benzene, naphthalene, pyridine, quinoline and isoquinoline) have spectral signatures below 500/cm, a first step towards reproducing the aerosol spectral features observed by Cassini's Composite InfraRed Spectrometer (CIRS) in the far infrared. In this work we investigate the influence of environmental temperature on the absorption spectra of such aerosol samples, simulating the temperature range to which aerosols, once formed, are exposed during their transport through Titans stratosphere. Our results show that environmental temperature does not have any major effect on the spectral shape of these aerosol analogs in the far-infrared, which is consistent with the CIRS observations.

Automated classification and visualization of healthy and pathological dental tissues based on near-infrared hyper-spectral imaging

Science.gov (United States)

Usenik, Peter; Bürmen, Miran; Vrtovec, Tomaž; Fidler, Aleš; Pernuš, Franjo; Likar, Boštjan

2011-03-01

Despite major improvements in dental healthcare and technology, dental caries remains one of the most prevalent chronic diseases of modern society. The initial stages of dental caries are characterized by demineralization of enamel crystals, commonly known as white spots which are difficult to diagnose. If detected early enough, such demineralization can be arrested and reversed by non-surgical means through well established dental treatments (fluoride therapy, anti-bacterial therapy, low intensity laser irradiation). Near-infrared (NIR) hyper-spectral imaging is a new promising technique for early detection of demineralization based on distinct spectral features of healthy and pathological dental tissues. In this study, we apply NIR hyper-spectral imaging to classify and visualize healthy and pathological dental tissues including enamel, dentin, calculus, dentin caries, enamel caries and demineralized areas. For this purpose, a standardized teeth database was constructed consisting of 12 extracted human teeth with different degrees of natural dental lesions imaged by NIR hyper-spectral system, X-ray and digital color camera. The color and X-ray images of teeth were presented to a clinical expert for localization and classification of the dental tissues, thereby obtaining the gold standard. Principal component analysis was used for multivariate local modeling of healthy and pathological dental tissues. Finally, the dental tissues were classified by employing multiple discriminant analysis. High agreement was observed between the resulting classification and the gold standard with the classification sensitivity and specificity exceeding 85 % and 97 %, respectively. This study demonstrates that NIR hyper-spectral imaging has considerable diagnostic potential for imaging hard dental tissues.

Ion spectral structures observed by the Van Allen Probes

Science.gov (United States)

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

2015-12-01

During the last decades several missions have recorded the presence of dynamic spectral features of energetic ions in the inner magnetosphere. Previous studies have reported single "nose-like" structures occurring alone and simultaneous nose-like structures (up to three). These ion structures are named after the characteristic shapes of energy bands or gaps in the energy-time spectrograms of in situ measured ion fluxes. They constitute the observational signatures of ion acceleration, transport, and loss in the global magnetosphere. The HOPE mass spectrometer onboard the Van Allen Probes measures energetic hydrogen, helium, and oxygen ions near the inner edge of the plasma sheet, where these ion structures are observed. We present a statistical study of nose-like structures, using 2-years measurements from the HOPE instrument. The results provide important details about the spatial distribution (dependence on geocentric distance), spectral features of the structures (differences among species), and geomagnetic conditions under which these structures occur.

Combining Spectral Data and a DSM from UAS-Images for Improved Classification of Non-Submerged Aquatic Vegetation

Directory of Open Access Journals (Sweden)

Eva Husson

2017-03-01

Full Text Available Monitoring of aquatic vegetation is an important component in the assessment of freshwater ecosystems. Remote sensing with unmanned aircraft systems (UASs can provide sub-decimetre-resolution aerial images and is a useful tool for detailed vegetation mapping. In a previous study, non-submerged aquatic vegetation was successfully mapped using automated classification of spectral and textural features from a true-colour UAS-orthoimage with 5-cm pixels. In the present study, height data from a digital surface model (DSM created from overlapping UAS-images has been incorporated together with the spectral and textural features from the UAS-orthoimage to test if classification accuracy can be improved further. We studied two levels of thematic detail: (a Growth forms including the classes of water, nymphaeid, and helophyte; and (b dominant taxa including seven vegetation classes. We hypothesized that the incorporation of height data together with spectral and textural features would increase classification accuracy as compared to using spectral and textural features alone, at both levels of thematic detail. We tested our hypothesis at five test sites (100 m × 100 m each with varying vegetation complexity and image quality using automated object-based image analysis in combination with Random Forest classification. Overall accuracy at each of the five test sites ranged from 78% to 87% at the growth-form level and from 66% to 85% at the dominant-taxon level. In comparison to using spectral and textural features alone, the inclusion of height data increased the overall accuracy significantly by 4%–21% for growth-forms and 3%–30% for dominant taxa. The biggest improvement gained by adding height data was observed at the test site with the most complex vegetation. Height data derived from UAS-images has a large potential to efficiently increase the accuracy of automated classification of non-submerged aquatic vegetation, indicating good possibilities

Color Shift Failure Prediction for Phosphor-Converted White LEDs by Modeling Features of Spectral Power Distribution with a Nonlinear Filter Approach

Directory of Open Access Journals (Sweden)

Jiajie Fan

2017-07-01

Full Text Available With the expanding application of light-emitting diodes (LEDs, the color quality of white LEDs has attracted much attention in several color-sensitive application fields, such as museum lighting, healthcare lighting and displays. Reliability concerns for white LEDs are changing from the luminous efficiency to color quality. However, most of the current available research on the reliability of LEDs is still focused on luminous flux depreciation rather than color shift failure. The spectral power distribution (SPD, defined as the radiant power distribution emitted by a light source at a range of visible wavelength, contains the most fundamental luminescence mechanisms of a light source. SPD is used as the quantitative inference of an LED’s optical characteristics, including color coordinates that are widely used to represent the color shift process. Thus, to model the color shift failure of white LEDs during aging, this paper first extracts the features of an SPD, representing the characteristics of blue LED chips and phosphors, by multi-peak curve-fitting and modeling them with statistical functions. Then, because the shift processes of extracted features in aged LEDs are always nonlinear, a nonlinear state-space model is then developed to predict the color shift failure time within a self-adaptive particle filter framework. The results show that: (1 the failure mechanisms of LEDs can be identified by analyzing the extracted features of SPD with statistical curve-fitting and (2 the developed method can dynamically and accurately predict the color coordinates, correlated color temperatures (CCTs, and color rendering indexes (CRIs of phosphor-converted (pc-white LEDs, and also can estimate the residual color life.

Color Shift Failure Prediction for Phosphor-Converted White LEDs by Modeling Features of Spectral Power Distribution with a Nonlinear Filter Approach.

Science.gov (United States)

Fan, Jiajie; Mohamed, Moumouni Guero; Qian, Cheng; Fan, Xuejun; Zhang, Guoqi; Pecht, Michael

2017-07-18

With the expanding application of light-emitting diodes (LEDs), the color quality of white LEDs has attracted much attention in several color-sensitive application fields, such as museum lighting, healthcare lighting and displays. Reliability concerns for white LEDs are changing from the luminous efficiency to color quality. However, most of the current available research on the reliability of LEDs is still focused on luminous flux depreciation rather than color shift failure. The spectral power distribution (SPD), defined as the radiant power distribution emitted by a light source at a range of visible wavelength, contains the most fundamental luminescence mechanisms of a light source. SPD is used as the quantitative inference of an LED's optical characteristics, including color coordinates that are widely used to represent the color shift process. Thus, to model the color shift failure of white LEDs during aging, this paper first extracts the features of an SPD, representing the characteristics of blue LED chips and phosphors, by multi-peak curve-fitting and modeling them with statistical functions. Then, because the shift processes of extracted features in aged LEDs are always nonlinear, a nonlinear state-space model is then developed to predict the color shift failure time within a self-adaptive particle filter framework. The results show that: (1) the failure mechanisms of LEDs can be identified by analyzing the extracted features of SPD with statistical curve-fitting and (2) the developed method can dynamically and accurately predict the color coordinates, correlated color temperatures (CCTs), and color rendering indexes (CRIs) of phosphor-converted (pc)-white LEDs, and also can estimate the residual color life.

Spectral theory and nonlinear functional analysis

CERN Document Server

Lopez-Gomez, Julian

2001-01-01

This Research Note addresses several pivotal problems in spectral theory and nonlinear functional analysis in connection with the analysis of the structure of the set of zeroes of a general class of nonlinear operators. It features the construction of an optimal algebraic/analytic invariant for calculating the Leray-Schauder degree, new methods for solving nonlinear equations in Banach spaces, and general properties of components of solutions sets presented with minimal use of topological tools. The author also gives several applications of the abstract theory to reaction diffusion equations and systems.The results presented cover a thirty-year period and include recent, unpublished findings of the author and his coworkers. Appealing to a broad audience, Spectral Theory and Nonlinear Functional Analysis contains many important contributions to linear algebra, linear and nonlinear functional analysis, and topology and opens the door for further advances.

Language identification using excitation source features

CERN Document Server

Rao, K Sreenivasa

2015-01-01

This book discusses the contribution of excitation source information in discriminating language. The authors focus on the excitation source component of speech for enhancement of language identification (LID) performance. Language specific features are extracted using two different modes: (i) Implicit processing of linear prediction (LP) residual and (ii) Explicit parameterization of linear prediction residual. The book discusses how in implicit processing approach, excitation source features are derived from LP residual, Hilbert envelope (magnitude) of LP residual and Phase of LP residual; and in explicit parameterization approach, LP residual signal is processed in spectral domain to extract the relevant language specific features. The authors further extract source features from these modes, which are combined for enhancing the performance of LID systems. The proposed excitation source features are also investigated for LID in background noisy environments. Each chapter of this book provides the motivatio...

Particulate characterization by PIXE multivariate spectral analysis

International Nuclear Information System (INIS)

Antolak, Arlyn J.; Morse, Daniel H.; Grant, Patrick G.; Kotula, Paul G.; Doyle, Barney L.; Richardson, Charles B.

2007-01-01

Obtaining particulate compositional maps from scanned PIXE (proton-induced X-ray emission) measurements is extremely difficult due to the complexity of analyzing spectroscopic data collected with low signal-to-noise at each scan point (pixel). Multivariate spectral analysis has the potential to analyze such data sets by reducing the PIXE data to a limited number of physically realizable and easily interpretable components (that include both spectral and image information). We have adapted the AXSIA (automated expert spectral image analysis) program, originally developed by Sandia National Laboratories to quantify electron-excited X-ray spectroscopy data, for this purpose. Samples consisting of particulates with known compositions and sizes were loaded onto Mylar and paper filter substrates and analyzed by scanned micro-PIXE. The data sets were processed by AXSIA and the associated principal component spectral data were quantified by converting the weighting images into concentration maps. The results indicate automated, nonbiased, multivariate statistical analysis is useful for converting very large amounts of data into a smaller, more manageable number of compositional components needed for locating individual particles-of-interest on large area collection media

Wavelength feature mapping as a proxy to mineral chemistry for investigating geologic systems: An example from the Rodalquilar epithermal system

Science.gov (United States)

van der Meer, Freek; Kopačková, Veronika; Koucká, Lucie; van der Werff, Harald M. A.; van Ruitenbeek, Frank J. A.; Bakker, Wim H.

2018-02-01

The final product of a geologic remote sensing data analysis using multi spectral and hyperspectral images is a mineral (abundance) map. Multispectral data, such as ASTER, Landsat, SPOT, Sentinel-2, typically allow to determine qualitative estimates of what minerals are in a pixel, while hyperspectral data allow to quantify this. As input to most image classification or spectral processing approach, endmembers are required. An alternative approach to classification is to derive absorption feature characteristics such as the wavelength position of the deepest absorption, depth of the absorption and symmetry of the absorption feature from hyperspectral data. Two approaches are presented, tested and compared in this paper: the 'Wavelength Mapper' and the 'QuanTools'. Although these algorithms use a different mathematical solution to derive absorption feature wavelength and depth, and use different image post-processing, the results are consistent, comparable and reproducible. The wavelength images can be directly linked to mineral type and abundance, but more importantly also to mineral chemical composition and subtle changes thereof. This in turn allows to interpret hyperspectral data in terms of mineral chemistry changes which is a proxy to pressure-temperature of formation of minerals. We show the case of the Rodalquilar epithermal system of the southern Spanish Gabo de Gata volcanic area using HyMAP airborne hyperspectral images.

Election Districts and Precincts, PrecinctPoly-The data set is a polygon feature consisting of 220 segments representing voter precinct boundaries., Published in 1991, Davis County Government.

Data.gov (United States)

NSGIC Local Govt | GIS Inventory — Election Districts and Precincts dataset current as of 1991. PrecinctPoly-The data set is a polygon feature consisting of 220 segments representing voter precinct...

Spectral-element simulation of two-dimensional elastic wave propagation in fully heterogeneous media on a GPU cluster

Science.gov (United States)

Rudianto, Indra; Sudarmaji

2018-04-01

We present an implementation of the spectral-element method for simulation of two-dimensional elastic wave propagation in fully heterogeneous media. We have incorporated most of realistic geological features in the model, including surface topography, curved layer interfaces, and 2-D wave-speed heterogeneity. To accommodate such complexity, we use an unstructured quadrilateral meshing technique. Simulation was performed on a GPU cluster, which consists of 24 core processors Intel Xeon CPU and 4 NVIDIA Quadro graphics cards using CUDA and MPI implementation. We speed up the computation by a factor of about 5 compared to MPI only, and by a factor of about 40 compared to Serial implementation.

Extracting structural features of rat sciatic nerve using polarization-sensitive spectral domain optical coherence tomography

NARCIS (Netherlands)

Islam, M.S.; Oliveira, M.C.; Wang, Y.; Henry, F.P.; Randolph, M.A.; Park, B. H.; de Boer, J.F.

2012-01-01

We present spectral domain polarization-sensitive optical coherence tomography (SD PS-OCT) imaging of peripheral nerves. Structural and polarization-sensitive OCT imaging of uninjured rat sciatic nerves was evaluated both qualitatively and quantitatively. OCT and its functional extension, PS-OCT,

Spectral dimension of elastic Sierpinski gaskets with general elastic forces

International Nuclear Information System (INIS)

Liu, S.H.; Liu, A.J.

1985-01-01

The spectral dimension is calculated for a Sierpinski gasket with the most general elastic restoring forces allowed by symmetry. The elastic forces consist of bond-stretching and angle-bending components. The spectral dimension is the same as that for the bond-stretching-force (central-force) model. This demonstrates that on the Sierpinski gasket the two types of forces belong to the same universality class

Characterisation and geostatistical analysis of clay rocks in underground facilities using hyper-spectral images

International Nuclear Information System (INIS)

Becker, J.K.; Marschall, P.; Brunner, P.; Cholet, C.; Renard, P.; Buckley, S.; Kurz, T.

2012-01-01

covering a wider area. This, although with very tight limitations, can be seen as an approach to t est the ability of 'up-scaling' the information contained in the classified images. 3. A third step consists of correlating the classified values with relevant petrophysical properties for each of these phases. This may help to relate petrophysical properties based on the mineralogy obtained from the classified hyper-spectral images. 4. The final step is the analysis of the connectivity of the different phases in two dimensions. The work flow briefly described above can of course be extended to the third dimension if scans and/or additional data at suitable positions exist. We present here an attempt to characterize different clay facies utilizing their reflection features in an underground setting. The first characterization is solely based on the 'visual' information obtained from classified hyper-spectral images and their comparison with lab measurements and geological maps. The second part extends this characterization to a more rigorous geostatistical analysis

Order and correlations in genomic DNA sequences. The spectral approach

International Nuclear Information System (INIS)

Lobzin, Vasilii V; Chechetkin, Vladimir R

2000-01-01

The structural analysis of genomic DNA sequences is discussed in the framework of the spectral approach, which is sufficiently universal due to the reciprocal correspondence and mutual complementarity of Fourier transform length scales. The spectral characteristics of random sequences of the same nucleotide composition possess the property of self-averaging for relatively short sequences of length M≥100-300. Comparison with the characteristics of random sequences determines the statistical significance of the structural features observed. Apart from traditional applications to the search for hidden periodicities, spectral methods are also efficient in studying mutual correlations in DNA sequences. By combining spectra for structure factors and correlation functions, not only integral correlations can be estimated but also their origin identified. Using the structural spectral entropy approach, the regularity of a sequence can be quantitatively assessed. A brief introduction to the problem is also presented and other major methods of DNA sequence analysis described. (reviews of topical problems)

Longwave thermal infrared spectral variability in individual rocks

Energy Technology Data Exchange (ETDEWEB)

Balick, Lee K [Los Alamos National Laboratory; Gillespie, Alan [UN. WASHINGTON; French, Andrew [USDA-ARS; Danilina, Iryna [UN. WASHINGTON

2008-01-01

A hyperspectral imaging spectrometer measuring in the longwave thermal infrared (7.6-11.6 {micro}m) with a spatial resolution less than 4 mm was used in the field to observe the variability of emissivity spectra within individual rocks. The rocks were obtained commercially, were on the order of 20 cm in size and were selected to have distinct spectral features: they include alabaster (gypsum), soapstone (steatite with talc), obsidian (volcanic glass), norite (plagioclase and orthopyroxene), and 'jasper' (silica with iron oxides). The advantages of using an imaging spectrometer to spectrally characterize these rocks are apparent. Large spectral variations were observed within individual rocks that may be attributed to roughness, surface geometry, and compositional variation. Non-imaging spectrometers would normally miss these variations as would small samples used in laboratory measurements, spatially averaged spectra can miss the optimum spectra for identification materials and spatially localized components of the rock can be obscured.

Holonomy loops, spectral triples and quantum gravity

DEFF Research Database (Denmark)

Johannes, Aastrup; Grimstrup, Jesper Møller; Nest, Ryszard

2009-01-01

We review the motivation, construction and physical interpretation of a semi-finite spectral triple obtained through a rearrangement of central elements of loop quantum gravity. The triple is based on a countable set of oriented graphs and the algebra consists of generalized holonomy loops...

DCTNet and PCANet for acoustic signal feature extraction

OpenAIRE

Xian, Yin; Thompson, Andrew; Sun, Xiaobai; Nowacek, Douglas; Nolte, Loren

2016-01-01

We introduce the use of DCTNet, an efficient approximation and alternative to PCANet, for acoustic signal classification. In PCANet, the eigenfunctions of the local sample covariance matrix (PCA) are used as filterbanks for convolution and feature extraction. When the eigenfunctions are well approximated by the Discrete Cosine Transform (DCT) functions, each layer of of PCANet and DCTNet is essentially a time-frequency representation. We relate DCTNet to spectral feature representation method...

Deep CNNs Along the Time Axis With Intermap Pooling for Robustness to Spectral Variations

Science.gov (United States)

Lee, Hwaran; Kim, Geonmin; Kim, Ho-Gyeong; Oh, Sang-Hoon; Lee, Soo-Young

2016-10-01

Convolutional neural networks (CNNs) with convolutional and pooling operations along the frequency axis have been proposed to attain invariance to frequency shifts of features. However, this is inappropriate with regard to the fact that acoustic features vary in frequency. In this paper, we contend that convolution along the time axis is more effective. We also propose the addition of an intermap pooling (IMP) layer to deep CNNs. In this layer, filters in each group extract common but spectrally variant features, then the layer pools the feature maps of each group. As a result, the proposed IMP CNN can achieve insensitivity to spectral variations characteristic of different speakers and utterances. The effectiveness of the IMP CNN architecture is demonstrated on several LVCSR tasks. Even without speaker adaptation techniques, the architecture achieved a WER of 12.7% on the SWB part of the Hub5'2000 evaluation test set, which is competitive with other state-of-the-art methods.

SPECTRAL CLASSIFICATION OF GALAXIES AT 0.5 ≤ z ≤ 1 IN THE CDFS: THE ARTIFICIAL NEURAL NETWORK APPROACH

International Nuclear Information System (INIS)

Teimoorinia, H.

2012-01-01

The aim of this work is to combine spectral energy distribution (SED) fitting with artificial neural network techniques to assign spectral characteristics to a sample of galaxies at 0.5 < z < 1. The sample is selected from the spectroscopic campaign of the ESO/GOODS-South field, with 142 sources having photometric data from the GOODS-MUSIC catalog covering bands between ∼0.4 and 24 μm in 10-13 filters. We use the CIGALE code to fit photometric data to Maraston's synthesis spectra to derive mass, specific star formation rate, and age, as well as the best SED of the galaxies. We use the spectral models presented by Kinney et al. as targets in the wavelength interval ∼1200-7500 Å. Then a series of neural networks are trained, with average performance ∼90%, to classify the best SED in a supervised manner. We consider the effects of the prominent features of the best SED on the performance of the trained networks and also test networks on the galaxy spectra of Coleman et al., which have a lower resolution than the target models. In this way, we conclude that the trained networks take into account all the features of the spectra simultaneously. Using the method, 105 out of 142 galaxies of the sample are classified with high significance. The locus of the classified galaxies in the three graphs of the physical parameters of mass, age, and specific star formation rate appears consistent with the morphological characteristics of the galaxies.

EEG-based recognition of video-induced emotions: selecting subject-independent feature set.

Science.gov (United States)

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.

Feature-Based Retinal Image Registration Using D-Saddle Feature

Directory of Open Access Journals (Sweden)

Roziana Ramli

2017-01-01

Full Text Available Retinal image registration is important to assist diagnosis and monitor retinal diseases, such as diabetic retinopathy and glaucoma. However, registering retinal images for various registration applications requires the detection and distribution of feature points on the low-quality region that consists of vessels of varying contrast and sizes. A recent feature detector known as Saddle detects feature points on vessels that are poorly distributed and densely positioned on strong contrast vessels. Therefore, we propose a multiresolution difference of Gaussian pyramid with Saddle detector (D-Saddle to detect feature points on the low-quality region that consists of vessels with varying contrast and sizes. D-Saddle is tested on Fundus Image Registration (FIRE Dataset that consists of 134 retinal image pairs. Experimental results show that D-Saddle successfully registered 43% of retinal image pairs with average registration accuracy of 2.329 pixels while a lower success rate is observed in other four state-of-the-art retinal image registration methods GDB-ICP (28%, Harris-PIIFD (4%, H-M (16%, and Saddle (16%. Furthermore, the registration accuracy of D-Saddle has the weakest correlation (Spearman with the intensity uniformity metric among all methods. Finally, the paired t-test shows that D-Saddle significantly improved the overall registration accuracy of the original Saddle.

Relative spectral absorption of solar radiation by water vapor and cloud droplets

Science.gov (United States)

Davies, R.; Ridgway, W. L.

1983-01-01

A moderate (20/cm) spectral resolution model which accounts for both the highly variable spectral transmission of solar radiation through water vapor within and above cloud, as well as the more slowly varying features of absorption and anisotropic multiple scattering by the cloud droplets, is presented. Results from this model as applied to the case of a typical 1 km thick stratus cloud in a standard atmosphere, with cloud top altitude of 2 km and overhead sun, are discussed, showing the relative importance of water vapor above the cloud, water vapor within the cloud, and cloud droplets on the spectral absorption of solar radiation.

Humor drawings evoked temporal and spectral EEG processes

Science.gov (United States)

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

Humor drawings evoked temporal and spectral EEG processes.

Science.gov (United States)

Wang, Regina W Y; Kuo, Hsien-Chu; Chuang, Shang-Wen

2017-08-01

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. © The Author (2017). Published by Oxford University Press.

Estimation of spectral distribution of sky radiance using a commercial digital camera.

Science.gov (United States)

Saito, Masanori; Iwabuchi, Hironobu; Murata, Isao

2016-01-10

Methods for estimating spectral distribution of sky radiance from images captured by a digital camera and for accurately estimating spectral responses of the camera are proposed. Spectral distribution of sky radiance is represented as a polynomial of the wavelength, with coefficients obtained from digital RGB counts by linear transformation. The spectral distribution of radiance as measured is consistent with that obtained by spectrometer and radiative transfer simulation for wavelengths of 430-680 nm, with standard deviation below 1%. Preliminary applications suggest this method is useful for detecting clouds and studying the relation between irradiance at the ground and cloud distribution.

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

Science.gov (United States)

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.

On some spectral properties of billiards and nuclei. Similarities and differences

International Nuclear Information System (INIS)

Richter, A.

2005-01-01

Generic and non-generic features of billiards and nuclei which show up in certain spectral properties are discussed by way of selected examples. First, the short and long range correlations of levels belonging to the magnetic dipole Scissors Mode in heavy deformed nuclei at an excitation energy of about 3 MeV prove that this mode is indeed caused by an ordered or regular collective motion. Second, the fine structure distribution of the so called electric Pygmy Dipole Resonance around 6 to 7 MeV excitation energy seems to indicate a situation where the spectral properties are governed by mixed dynamics, i.e. by regular and chaotic features. However, in nuclei quantitative conclusions are always severely hampered by missing levels due to limited experimental resolution and detector efficiency. Third, it is shown that this situation can be largely overcome by studying spectral properties in superconducting microwave billards considered as nuclear analogs. As an example resonance strength distributions in billards of mixed and fully chaotic dynamics are considered. Finally it is demonstrated how symmetry breaking effects in nuclei - e.g. isospin symmetry breaking - can be studied through those resonance strength distributions by modelling the nuclear problem with coupled billards. (orig.)

On some spectral properties of billiards and nuclei. Similarities and differences

Energy Technology Data Exchange (ETDEWEB)

Richter, A.

2005-07-01

Generic and non-generic features of billiards and nuclei which show up in certain spectral properties are discussed by way of selected examples. First, the short and long range correlations of levels belonging to the magnetic dipole Scissors Mode in heavy deformed nuclei at an excitation energy of about 3 MeV prove that this mode is indeed caused by an ordered or regular collective motion. Second, the fine structure distribution of the so called electric Pygmy Dipole Resonance around 6 to 7 MeV excitation energy seems to indicate a situation where the spectral properties are governed by mixed dynamics, i.e. by regular and chaotic features. However, in nuclei quantitative conclusions are always severely hampered by missing levels due to limited experimental resolution and detector efficiency. Third, it is shown that this situation can be largely overcome by studying spectral properties in superconducting microwave billards considered as nuclear analogs. As an example resonance strength distributions in billards of mixed and fully chaotic dynamics are considered. Finally it is demonstrated how symmetry breaking effects in nuclei - e.g. isospin symmetry breaking - can be studied through those resonance strength distributions by modelling the nuclear problem with coupled billards. (orig.)

Automated road network extraction from high spatial resolution multi-spectral imagery

Science.gov (United States)

Zhang, Qiaoping

For the last three decades, the Geomatics Engineering and Computer Science communities have considered automated road network extraction from remotely-sensed imagery to be a challenging and important research topic. The main objective of this research is to investigate the theory and methodology of automated feature extraction for image-based road database creation, refinement or updating, and to develop a series of algorithms for road network extraction from high resolution multi-spectral imagery. The proposed framework for road network extraction from multi-spectral imagery begins with an image segmentation using the k-means algorithm. This step mainly concerns the exploitation of the spectral information for feature extraction. The road cluster is automatically identified using a fuzzy classifier based on a set of predefined road surface membership functions. These membership functions are established based on the general spectral signature of road pavement materials and the corresponding normalized digital numbers on each multi-spectral band. Shape descriptors of the Angular Texture Signature are defined and used to reduce the misclassifications between roads and other spectrally similar objects (e.g., crop fields, parking lots, and buildings). An iterative and localized Radon transform is developed for the extraction of road centerlines from the classified images. The purpose of the transform is to accurately and completely detect the road centerlines. It is able to find short, long, and even curvilinear lines. The input image is partitioned into a set of subset images called road component images. An iterative Radon transform is locally applied to each road component image. At each iteration, road centerline segments are detected based on an accurate estimation of the line parameters and line widths. Three localization approaches are implemented and compared using qualitative and quantitative methods. Finally, the road centerline segments are grouped into a

Is a step in the primordial spectral index favoured by CMB data?

Energy Technology Data Exchange (ETDEWEB)

Joy, Minu; Shafieloo, Arman; Sahni, Varun [Inter-University Centre for Astronomy and Astrophysics, Pune 411 007 (India); Starobinsky, Alexei A., E-mail: minujoy@alphonsacollege.ac.in, E-mail: a.shafieloo1@physics.ox.ac.uk, E-mail: varun@iucaa.ernet.in, E-mail: alstar@landau.ac.ru [Landau Institute for Theoretical Physics, 119334 Moscow (Russian Federation)

2009-06-01

A sudden small change in the second derivative of the inflaton potential can result in a universal local feature in the spectrum of primordial perturbations generated during inflation. The exact solution describing this feature \\cite(minu) is characterized by a step in the spectral index modulated by characteristic oscillations and results in a large running of the spectral index localized over a few e-folds of scale. In this paper we confront this step-like feature with the 5 year WMAP results and demonstrate that it provides a better fit to this data than a featureless initial spectrum. If such a feature exists at all, then it should lie at sufficiently large scales k{sub 0} ∼< 0.003 Mpc{sup −1} corresponding to l ∼< 40. The sign of the effect is shown to correspond to the negative running of n{sub s} localized near this scale. This feature could arise as a result of a 'mini-waterfall'-type fast second order phase transition experienced by an auxiliary heavy field during inflation, in a model similar to hybrid inflation (though for a different choice of parameters). If this is the case, then the auxiliary field should be positively coupled to the inflaton.

Composite spectral functions for solving Volterra's population model

International Nuclear Information System (INIS)

Ramezani, M.; Razzaghi, M.; Dehghan, M.

2007-01-01

An approximate method for solving Volterra's population model for population growth of a species in a closed system is proposed. Volterra's model is a nonlinear integro-differential equation, where the integral term represents the effect of toxin. The approach is based upon composite spectral functions approximations. The properties of composite spectral functions consisting of few terms of orthogonal functions are presented and are utilized to reduce the solution of the Volterra's model to the solution of a system of algebraic equations. The method is easy to implement and yields very accurate result

Multi-spectral confocal microendoscope for in-vivo imaging

Science.gov (United States)

Rouse, Andrew Robert

The concept of in-vivo multi-spectral confocal microscopy is introduced. A slit-scanning multi-spectral confocal microendoscope (MCME) was built to demonstrate the technique. The MCME employs a flexible fiber-optic catheter coupled to a custom built slit-scan confocal microscope fitted with a custom built imaging spectrometer. The catheter consists of a fiber-optic imaging bundle linked to a miniature objective and focus assembly. The design and performance of the miniature objective and focus assembly are discussed. The 3mm diameter catheter may be used on its own or routed though the instrument channel of a commercial endoscope. The confocal nature of the system provides optical sectioning with 3mum lateral resolution and 30mum axial resolution. The prism based multi-spectral detection assembly is typically configured to collect 30 spectral samples over the visible chromatic range. The spectral sampling rate varies from 4nm/pixel at 490nm to 8nm/pixel at 660nm and the minimum resolvable wavelength difference varies from 7nm to 18nm over the same spectral range. Each of these characteristics are primarily dictated by the dispersive power of the prism. The MCME is designed to examine cellular structures during optical biopsy and to exploit the diagnostic information contained within the spectral domain. The primary applications for the system include diagnosis of disease in the gastro-intestinal tract and female reproductive system. Recent data from the grayscale imaging mode are presented. Preliminary multi-spectral results from phantoms, cell cultures, and excised human tissue are presented to demonstrate the potential of in-vivo multi-spectral imaging.

Spatial and spectral effects in subcritical system pulsed experiments

International Nuclear Information System (INIS)

Dulla, S.; Nervo, M.; Ravetto, P.; Carta, M.

2013-01-01

Accurate neutronic models are needed for the interpretation of pulsed experiments in subcritical systems. In this work, the extent of spatial and spectral effects in the pulse propagation phenomena is investigated and the analysis is applied to the GUINEVERE experiment. The multigroup cross section data is generated by the Monte Carlo SERPENT code and the neutronic evolution following the source pulse is simulated by a kinetic diffusion code. The results presented show that important spatial and spectral aspects need to be properly accounted for and that a detailed energy approach may be needed to adequately capture the physical features of the system to the pulse injection. (authors)

Spectral functions from anisotropic lattice QCD

Energy Technology Data Exchange (ETDEWEB)

Aarts, G.; Allton, C. [Department of Physics, Swansea University, Swansea SA2 8PP, Wales (United Kingdom); Amato, A. [Helsinki Institute of Physics and University of Helsinki, Helsinki (Finland); Evans, W. [Albert Einstein Center for Fundamental Physics, Institute for Theoretical Physics Universitat Bern, Sidlerstrasse 5, CH-3012 Bern (Switzerland); Giudice, P. [Institut für Theoretische Physik, Universität Münster, D–48149 Münster (Germany); Harris, T. [School of Mathematics, Trinity College, Dublin 2 (Ireland); Kelly, A. [Department of Mathematical Physics, Maynooth University, Maynooth, Co Kildare (Ireland); Kim, S.Y. [Department of Physics, Sejong University, Seoul 143-747 (Korea, Republic of); Lombardo, M.P. [INFN–Laboratori Nazionali di Frascati, I–00044 Frascati (RM) (Italy); Praki, K. [Department of Physics, Swansea University, Swansea SA2 8PP, Wales (United Kingdom); Ryan, S.M. [School of Mathematics, Trinity College, Dublin 2 (Ireland); Skullerud, J.-I. [Department of Mathematical Physics, Maynooth University, Maynooth, Co Kildare (Ireland)

2016-12-15

The FASTSUM collaboration has been carrying out lattice simulations of QCD for temperatures ranging from one third to twice the crossover temperature, investigating the transition region, as well as the properties of the Quark Gluon Plasma. In this contribution we concentrate on quarkonium correlators and spectral functions. We work in a fixed scale scheme and use anisotropic lattices which help achieving the desirable fine resolution in the temporal direction, thus facilitating the (ill posed) integral transform from imaginary time to frequency space. We contrast and compare results for the correlators obtained with different methods, and different temporal spacings. We observe robust features of the results, confirming the sequential dissociation scenario, but also quantitative differences indicating that the methods' systematic errors are not yet under full control. We briefly outline future steps towards accurate results for the spectral functions and their associated statistical and systematic errors.

Understanding Soliton Spectral Tunneling as a Spectral Coupling Effect

DEFF Research Database (Denmark)

Guo, Hairun; Wang, Shaofei; Zeng, Xianglong

2013-01-01

Soliton eigenstate is found corresponding to a dispersive phase profile under which the soliton phase changes induced by the dispersion and nonlinearity are instantaneously counterbalanced. Much like a waveguide coupler relying on a spatial refractive index profile that supports mode coupling...... between channels, here we suggest that the soliton spectral tunneling effect can be understood supported by a spectral phase coupler. The dispersive wave number in the spectral domain must have a coupler-like symmetric profile for soliton spectral tunneling to occur. We show that such a spectral coupler...

HYPERSPECTRAL HYPERION IMAGERY ANALYSIS AND ITS APPLICATION USING SPECTRAL ANALYSIS

Directory of Open Access Journals (Sweden)

W. Pervez

2015-03-01

Full Text Available Rapid advancement in remote sensing open new avenues to explore the hyperspectral Hyperion imagery pre-processing techniques, analysis and application for land use mapping. The hyperspectral data consists of 242 bands out of which 196 calibrated/useful bands are available for hyperspectral applications. Atmospheric correction applied to the hyperspectral calibrated bands make the data more useful for its further processing/ application. Principal component (PC analysis applied to the hyperspectral calibrated bands reduced the dimensionality of the data and it is found that 99% of the data is held in first 10 PCs. Feature extraction is one of the important application by using vegetation delineation and normalized difference vegetation index. The machine learning classifiers uses the technique to identify the pixels having significant difference in the spectral signature which is very useful for classification of an image. Supervised machine learning classifier technique has been used for classification of hyperspectral image which resulted in overall efficiency of 86.6703 and Kappa co-efficient of 0.7998.

Thermal infrared spectral analysis of compacted fine-grained mineral mixtures: implications for spectral interpretation of lithified sedimentary materials on Mars

Science.gov (United States)

Pan, C.; Rogers, D.

2012-12-01

Characterizing the thermal infrared (TIR) spectral mixing behavior of compacted fine-grained mineral assemblages is necessary for facilitating quantitative mineralogy of sedimentary surfaces from spectral measurements. Previous researchers have demonstrated that TIR spectra from igneous and metamorphic rocks as well as coarse-grained (>63 micron) sand mixtures combine in proportion to their volume abundance. However, the spectral mixing behavior of compacted, fine-grained mineral mixtures that would be characteristic of sedimentary depositional environments has received little attention. Here we characterize the spectral properties of pressed pellet samples of pestle and centrifuged to obtain less than 10 micron size. Pure phases and mixtures of two, three and four components were made in varying proportions by volume. All of the samples were pressed into pellets at 15000PSI to minimize volume scattering. Thermal infrared spectra of pellets were measured in the Vibrational Spectroscopy Laboratory at Stony Brook University with a Thermo Fisher Nicolet 6700 Fourier transform infrared Michelson interferometer from ~225 to 2000 cm-1. Our preliminary results indicate that some pelletized samples have contributions from volume scattering, which leads to non-linear spectral combinations. It is not clear if the transparency features (which arise from multiple surface reflections of incident photons) are due to minor clinging fines on an otherwise specular pellet surface or to partially transmitted energy through optically thin grains in the compacted mixture. Inclusion of loose powder (analysis of TES and Mini-TES data of lithified sedimentary deposits.

International Conference on Spectral and High-Order Methods

CERN Document Server

Dumont, Ney; Hesthaven, Jan

2017-01-01

This book features a selection of high-quality papers chosen from the best presentations at the International Conference on Spectral and High-Order Methods (2016), offering an overview of the depth and breadth of the activities within this important research area. The carefully reviewed papers provide a snapshot of the state of the art, while the extensive bibliography helps initiate new research directions.

Spectral changes in conifers subjected to air pollution and water stress: Experimental studies

Science.gov (United States)

Westman, Walter E.; Price, Curtis V.

1988-01-01

The roles of leaf anatomy, moisture and pigment content, and number of leaf layers on spectral reflectance in healthy, pollution-stressed, and water-stressed conifer needles were examined experimentally. Jeffrey pine (Pinus jeffreyi) and giant sequoia (Sequoiadendron gigantea) were exposed to ozone and acid mist treatments in fumigation chambers; red pine (Pinus resinosa) needles were artificially dried. Infrared reflectance from stacked needles rose with free water loss. In an air-drying experiment, cell volume reductions induced by loss of turgor caused near-infrared reflectance (TM band 4) to drop after most free water was lost. Under acid mist fumigation, stunting of tissue development similarly reduced band 4 reflectance. Both artificial drying and pollutant fumigation caused a blue shift of the red edge of spectral reflectance curves in conifers, attributable to chlorophyll denaturation. Thematic mapper band ratio 4/3 fell and 5/4 rose with increasing pollution stress on artificial drying. Loss of water by air-drying, freeze-drying, or oven-drying enhanced spectral features, due in part to greater scattering and reduced water absorption. Grinding of the leaf tissue further enhanced the spectral features by increasing reflecting surfaces and path length. In a leaf-stacking experiment, an asymptote in visible and infrared reflectance was reached at 7-8 needle layers of red pine.

Assessing and monitoring of urban vegetation using multiple endmember spectral mixture analysis

Science.gov (United States)

Zoran, M. A.; Savastru, R. S.; Savastru, D. M.

2013-08-01

During last years urban vegetation with significant health, biological and economical values had experienced dramatic changes due to urbanization and human activities in the metropolitan area of Bucharest in Romania. We investigated the utility of remote sensing approaches of multiple endmember spectral mixture analysis (MESMA) applied to IKONOS and Landsat TM/ETM satellite data for estimating fractional cover of urban/periurban forest, parks, agricultural vegetation areas. Because of the spectral heterogeneity of same physical features of urban vegetation increases with the increase of image resolution, the traditional spectral information-based statistical method may not be useful to classify land cover dynamics from high resolution imageries like IKONOS. So we used hierarchy tree classification method in classification and MESMA for vegetation land cover dynamics assessment based on available IKONOS high-resolution imagery of Bucharest town. This study employs thirty two endmembers and six hundred and sixty spectral models to identify all Earth's features (vegetation, water, soil, impervious) and shade in the Bucharest area. The mean RMS error for the selected vegetation land cover classes range from 0.0027 to 0.018. The Pearson correlation between the fraction outputs from MESMA and reference data from all IKONOS images 1m panchromatic resolution data for urban/periurban vegetation were ranging in the domain 0.7048 - 0.8287. The framework in this study can be applied to other urban vegetation areas in Romania.

CONNJUR Workflow Builder: a software integration environment for spectral reconstruction.

Science.gov (United States)

Fenwick, Matthew; Weatherby, Gerard; Vyas, Jay; Sesanker, Colbert; Martyn, Timothy O; Ellis, Heidi J C; Gryk, Michael R

2015-07-01

CONNJUR Workflow Builder (WB) is an open-source software integration environment that leverages existing spectral reconstruction tools to create a synergistic, coherent platform for converting biomolecular NMR data from the time domain to the frequency domain. WB provides data integration of primary data and metadata using a relational database, and includes a library of pre-built workflows for processing time domain data. WB simplifies maximum entropy reconstruction, facilitating the processing of non-uniformly sampled time domain data. As will be shown in the paper, the unique features of WB provide it with novel abilities to enhance the quality, accuracy, and fidelity of the spectral reconstruction process. WB also provides features which promote collaboration, education, parameterization, and non-uniform data sets along with processing integrated with the Rowland NMR Toolkit (RNMRTK) and NMRPipe software packages. WB is available free of charge in perpetuity, dual-licensed under the MIT and GPL open source licenses.

CONNJUR Workflow Builder: a software integration environment for spectral reconstruction

Energy Technology Data Exchange (ETDEWEB)

Fenwick, Matthew; Weatherby, Gerard; Vyas, Jay; Sesanker, Colbert [UConn Health, Department of Molecular Biology and Biophysics (United States); Martyn, Timothy O. [Rensselaer at Hartford, Department of Engineering and Science (United States); Ellis, Heidi J. C. [Western New England College, Department of Computer Science and Information Technology (United States); Gryk, Michael R., E-mail: gryk@uchc.edu [UConn Health, Department of Molecular Biology and Biophysics (United States)

2015-07-15

CONNJUR Workflow Builder (WB) is an open-source software integration environment that leverages existing spectral reconstruction tools to create a synergistic, coherent platform for converting biomolecular NMR data from the time domain to the frequency domain. WB provides data integration of primary data and metadata using a relational database, and includes a library of pre-built workflows for processing time domain data. WB simplifies maximum entropy reconstruction, facilitating the processing of non-uniformly sampled time domain data. As will be shown in the paper, the unique features of WB provide it with novel abilities to enhance the quality, accuracy, and fidelity of the spectral reconstruction process. WB also provides features which promote collaboration, education, parameterization, and non-uniform data sets along with processing integrated with the Rowland NMR Toolkit (RNMRTK) and NMRPipe software packages. WB is available free of charge in perpetuity, dual-licensed under the MIT and GPL open source licenses.

Differences between downscaling with spectral and grid nudging using WRF

Directory of Open Access Journals (Sweden)

P. Liu

2012-04-01

Full Text Available Dynamical downscaling has been extensively used to study regional climate forced by large-scale global climate models. During the downscaling process, however, the simulation of regional climate models (RCMs tends to drift away from the driving fields. Developing a solution that addresses this issue, by retaining the large scale features (from the large-scale fields and the small-scale features (from the RCMs has led to the development of "nudging" techniques. Here, we examine the performance of two nudging techniques, grid and spectral nudging, in the downscaling of NCEP/NCAR data with the Weather Research and Forecasting (WRF Model. The simulations are compared against the results with North America Regional Reanalysis (NARR data set at different scales of interest using the concept of similarity. We show that with the appropriate choice of wave numbers, spectral nudging outperforms grid nudging in the capacity of balancing the performance of simulation at the large and small scales.

CONNJUR Workflow Builder: a software integration environment for spectral reconstruction

International Nuclear Information System (INIS)

Fenwick, Matthew; Weatherby, Gerard; Vyas, Jay; Sesanker, Colbert; Martyn, Timothy O.; Ellis, Heidi J. C.; Gryk, Michael R.

2015-01-01

CONNJUR Workflow Builder (WB) is an open-source software integration environment that leverages existing spectral reconstruction tools to create a synergistic, coherent platform for converting biomolecular NMR data from the time domain to the frequency domain. WB provides data integration of primary data and metadata using a relational database, and includes a library of pre-built workflows for processing time domain data. WB simplifies maximum entropy reconstruction, facilitating the processing of non-uniformly sampled time domain data. As will be shown in the paper, the unique features of WB provide it with novel abilities to enhance the quality, accuracy, and fidelity of the spectral reconstruction process. WB also provides features which promote collaboration, education, parameterization, and non-uniform data sets along with processing integrated with the Rowland NMR Toolkit (RNMRTK) and NMRPipe software packages. WB is available free of charge in perpetuity, dual-licensed under the MIT and GPL open source licenses

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

Science.gov (United States)

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.

Spectral properties of nuclear matter

International Nuclear Information System (INIS)

Bozek, P

2006-01-01

We review self-consistent spectral methods for nuclear matter calculations. The in-medium T-matrix approach is conserving and thermodynamically consistent. It gives both the global and the single-particle properties the system. The T-matrix approximation allows to address the pairing phenomenon in cold nuclear matter. A generalization of nuclear matter calculations to the super.uid phase is discussed and numerical results are presented for this case. The linear response of a correlated system going beyond the Hartree-Fock+ Random-Phase-Approximation (RPA) scheme is studied. The polarization is obtained by solving a consistent Bethe-Salpeter (BS) equation for the coupling of dressed nucleons to an external field. We find that multipair contributions are important for the spin(isospin) response when the interaction is spin(isospin) dependent

SPAM- SPECTRAL ANALYSIS MANAGER (DEC VAX/VMS VERSION)

Science.gov (United States)

Solomon, J. E.

1994-01-01

The Spectral Analysis Manager (SPAM) was developed to allow easy qualitative analysis of multi-dimensional imaging spectrometer data. Imaging spectrometers provide sufficient spectral sampling to define unique spectral signatures on a per pixel basis. Thus direct material identification becomes possible for geologic studies. SPAM provides a variety of capabilities for carrying out interactive analysis of the massive and complex datasets associated with multispectral remote sensing observations. In addition to normal image processing functions, SPAM provides multiple levels of on-line help, a flexible command interpretation, graceful error recovery, and a program structure which can be implemented in a variety of environments. SPAM was designed to be visually oriented and user friendly with the liberal employment of graphics for rapid and efficient exploratory analysis of imaging spectrometry data. SPAM provides functions to enable arithmetic manipulations of the data, such as normalization, linear mixing, band ratio discrimination, and low-pass filtering. SPAM can be used to examine the spectra of an individual pixel or the average spectra over a number of pixels. SPAM also supports image segmentation, fast spectral signature matching, spectral library usage, mixture analysis, and feature extraction. High speed spectral signature matching is performed by using a binary spectral encoding algorithm to separate and identify mineral components present in the scene. The same binary encoding allows automatic spectral clustering. Spectral data may be entered from a digitizing tablet, stored in a user library, compared to the master library containing mineral standards, and then displayed as a timesequence spectral movie. The output plots, histograms, and stretched histograms produced by SPAM can be sent to a lineprinter, stored as separate RGB disk files, or sent to a Quick Color Recorder. SPAM is written in C for interactive execution and is available for two different

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

Science.gov (United States)

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

2007-07-01

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

Piecewise spectrally band-pass for compressive coded aperture spectral imaging

International Nuclear Information System (INIS)

Qian Lu-Lu; Lü Qun-Bo; Huang Min; Xiang Li-Bin

2015-01-01

Coded aperture snapshot spectral imaging (CASSI) has been discussed in recent years. It has the remarkable advantages of high optical throughput, snapshot imaging, etc. The entire spatial-spectral data-cube can be reconstructed with just a single two-dimensional (2D) compressive sensing measurement. On the other hand, for less spectrally sparse scenes, the insufficiency of sparse sampling and aliasing in spatial-spectral images reduce the accuracy of reconstructed three-dimensional (3D) spectral cube. To solve this problem, this paper extends the improved CASSI. A band-pass filter array is mounted on the coded mask, and then the first image plane is divided into some continuous spectral sub-band areas. The entire 3D spectral cube could be captured by the relative movement between the object and the instrument. The principle analysis and imaging simulation are presented. Compared with peak signal-to-noise ratio (PSNR) and the information entropy of the reconstructed images at different numbers of spectral sub-band areas, the reconstructed 3D spectral cube reveals an observable improvement in the reconstruction fidelity, with an increase in the number of the sub-bands and a simultaneous decrease in the number of spectral channels of each sub-band. (paper)

Feature Selection for Audio Surveillance in Urban Environment

Directory of Open Access Journals (Sweden)

KIKTOVA Eva

2014-05-01

Full Text Available This paper presents the work leading to the acoustic event detection system, which is designed to recognize two types of acoustic events (shot and breaking glass in urban environment. For this purpose, a huge front-end processing was performed for the effective parametric representation of an input sound. MFCC features and features computed during their extraction (MELSPEC and FBANK, then MPEG-7 audio descriptors and other temporal and spectral characteristics were extracted. High dimensional feature sets were created and in the next phase reduced by the mutual information based selection algorithms. Hidden Markov Model based classifier was applied and evaluated by the Viterbi decoding algorithm. Thus very effective feature sets were identified and also the less important features were found.

3D registration method for assessing the gastrointestinal motility using spectral reflectance estimation

Science.gov (United States)

Nobe, Kazuki; Yoshimoto, Kayo; Yamada, Kenji; Takahashi, Hideya

2018-02-01

Functional gastrointestinal disorders (FGID) are the most common gastrointestinal disorders. The term "functional" is generally applied to disorders where there are no structural abnormalities. One of the major factors for FGID is abnormal gastrointestinal motility. We have proposed a system for assessing the function of gastric motility using a 3D endoscope. In this previous study, we established a method for estimating characteristics of contraction wave extracted from a 3D shape include contraction wave obtained from stereo endoscope. Because it is difficult to fix the tip position of the endoscope during the examination, estimation of the 3D position between the endoscope and the gastric wall is necessary for the accurate assessment. Then, we have proposed a motion compensation method using 3D scene flow. However, since mucosa has few feature points, it is difficult to obtain 3D scene flow from RGB images. So, we focused on spectral imaging that can enhance visualization of mucosal structure. Spectral image can be obtained without switching optical filters by using technique to estimate spectral reflectance by image processing. In this paper, we propose registration method of measured 3D shape in time series using estimated spectral image. The spectral image is estimated from the RGB image for each frame. 3D scene flow of feature points, that is, enhanced mucosal structure calculated by spectral images in a time series. The position change between the endoscope and gastric wall is estimated by 3D scene flow. We experimented to confirm the validity of the proposed method using papers with a grid of colors close to the background color.

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

Science.gov (United States)

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

Detecting gallbladders in chicken livers using spectral analysis

DEFF Research Database (Denmark)

Jørgensen, Anders; Mølvig Jensen, Eigil; Moeslund, Thomas B.

2015-01-01

This paper presents a method for detecting gallbladders attached to chicken livers using spectral imaging. Gallbladders can contaminate good livers, making them unfit for human consumption. A data set consisting of chicken livers with and without gallbladders, has been captured using 33 wavelengths...

[Spectral navigation technology and its application in positioning the fruits of fruit trees].

Science.gov (United States)

Yu, Xiao-Lei; Zhao, Zhi-Min

2010-03-01

An innovative technology of spectral navigation is presented in the present paper. This new method adopts reflectance spectra of fruits, leaves and branches as one of the key navigation parameters and positions the fruits of fruit trees relying on the diversity of spectral characteristics. The research results show that the distinct smoothness as effect is available in the spectrum of leaves of fruit trees. On the other hand, gradual increasing as the trend is an important feature in the spectrum of branches of fruit trees while the spectrum of fruit fluctuates. In addition, the peak diversity of reflectance rate between fruits and leaves of fruit trees is reached at 850 nm of wavelength. So the limit value can be designed at this wavelength in order to distinguish fruits and leaves. The method introduced here can not only quickly distinguish fruits, leaves and branches, but also avoid the effects of surroundings. Compared with the traditional navigation systems based on machine vision, there are still some special and unique features in the field of positioning the fruits of fruit trees using spectral navigation technology.

ULTRAVIOLET RAMAN SPECTRAL SIGNATURE ACQUISITION: UV RAMAN SPECTRAL FINGERPRINTS.

Energy Technology Data Exchange (ETDEWEB)

SEDLACEK,III, A.J.FINFROCK,C.

2002-09-01

As a member of the science-support part of the ITT-lead LISA development program, BNL is tasked with the acquisition of UV Raman spectral fingerprints and associated scattering cross-sections for those chemicals-of-interest to the program's sponsor. In support of this role, the present report contains the first installment of UV Raman spectral fingerprint data on the initial subset of chemicals. Because of the unique nature associated with the acquisition of spectral fingerprints for use in spectral pattern matching algorithms (i.e., CLS, PLS, ANN) great care has been undertaken to maximize the signal-to-noise and to minimize unnecessary spectral subtractions, in an effort to provide the highest quality spectral fingerprints. This report is divided into 4 sections. The first is an Experimental section that outlines how the Raman spectra are performed. This is then followed by a section on Sample Handling. Following this, the spectral fingerprints are presented in the Results section where the data reduction process is outlined. Finally, a Photographs section is included.

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

Science.gov (United States)

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.

Single Trial Decoding of Belief Decision Making from EEG and fMRI Data Using ICA Features

Directory of Open Access Journals (Sweden)

Pamela eDouglas

2013-07-01

Full Text Available The complex task of assessing the veracity of a statement is thought to activate uniquely distributed brain regions based on whether a subject believes or disbelieves a given assertion. In the current work, we present parallel machine learning methods for predicting a subject’s decision response to a given propositional statement based on independent component (IC features derived from EEG and fMRI data. Our results demonstrate that IC features outperformed features derived from event related spectral perturbations derived from any single spectral band, yet were similar to accuracy across all spectral bands combined. We compared our diagnostic IC spatial maps with our conventional general linear model (GLM results, and found that informative ICs had significant spatial overlap with our GLM results, yet also revealed unique regions like amygdala that were not statistically significant in GLM analyses. Overall, these results suggest that ICs may yield a parsimonious feature set that can be used along with a decision tree structure for interpretation of features used in classifying complex cognitive processes such as belief and disbelief across both fMRI and EEG neuroimaging modalities.

Spectral classifying base on color of live corals and dead corals covered with algae

Science.gov (United States)

Nurdin, Nurjannah; Komatsu, Teruhisa; Barille, Laurent; Akbar, A. S. M.; Sawayama, Shuhei; Fitrah, Muh. Nur; Prasyad, Hermansyah

2016-05-01

Pigments in the host tissues of corals can make a significant contribution to their spectral signature and can affect their apparent color as perceived by a human observer. The aim of this study is classifying the spectral reflectance of corals base on different color. It is expected that they can be used as references in discriminating between live corals, dead coral covered with algae Spectral reflectance data was collected in three small islands, Spermonde Archipelago, Indonesia by using a hyperspectral radiometer underwater. First and second derivative analysis resolved the wavelength locations of dominant features contributing to reflectance in corals and support the distinct differences in spectra among colour existed. Spectral derivative analysis was used to determine the specific wavelength regions ideal for remote identification of substrate type. The analysis results shown that yellow, green, brown and violet live corals are spectrally separable from each other, but they are similar with dead coral covered with algae spectral.

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

Science.gov (United States)

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.

BATSE gamma-ray burst line search. 2: Bayesian consistency methodology

Science.gov (United States)

Band, D. L.; Ford, L. A.; Matteson, J. L.; Briggs, M.; Paciesas, W.; Pendleton, G.; Preece, R.; Palmer, D.; Teegarden, B.; Schaefer, B.

1994-01-01

We describe a Bayesian methodology to evaluate the consistency between the reported Ginga and Burst and Transient Source Experiment (BATSE) detections of absorption features in gamma-ray burst spectra. Currently no features have been detected by BATSE, but this methodology will still be applicable if and when such features are discovered. The Bayesian methodology permits the comparison of hypotheses regarding the two detectors' observations and makes explicit the subjective aspects of our analysis (e.g., the quantification of our confidence in detector performance). We also present non-Bayesian consistency statistics. Based on preliminary calculations of line detectability, we find that both the Bayesian and non-Bayesian techniques show that the BATSE and Ginga observations are consistent given our understanding of these detectors.

A spectral algorithm for the seriation problem

Energy Technology Data Exchange (ETDEWEB)

Atkins, J.E. [Michigan Univ., Ann Arbor, MI (United States). Dept. of Mathematics; Boman, E.G. [Stanford Univ., CA (United States). Dept. of Computer Science; Hendrickson, B. [Sandia National Labs., Albuquerque, NM (United States)

1994-11-01

Given a set of objects and a correlation function f reflecting the desire for two items to be near each other, find all sequences {pi} of the items so that correlation preferences are preserved; that is if {pi}(i) < {pi}(j) < {pi}(k) then f(i,j) {ge} f(i,k) and f(j,k) {ge} f(i,k). This seriation problem has numerous applications, for instance, solving it yields a solution to the consecutive ones problem. We present a spectral algorithm for this problem that has a number of interesting features. Whereas most previous applications of spectral techniques provided bounds or heuristics, our result is an algorithm for a nontrivial combinatorial problem. Our analysis introduces powerful tools from matrix theory to the theoretical computer science community. Also, spectral methods are being applied as heuristics for a variety of sequencing problems and our result helps explain and justify these applications. Although the worst case running time for our approach is not competitive with that of existing methods for well posed problem instances, unlike combinatorial approaches our algorithm remains a credible heuristic for the important cases where there are errors in the data.

Hybrid spectral CT reconstruction.

Directory of Open Access Journals (Sweden)

Darin P Clark

Full Text Available Current photon counting x-ray detector (PCD technology faces limitations associated with spectral fidelity and photon starvation. One strategy for addressing these limitations is to supplement PCD data with high-resolution, low-noise data acquired with an energy-integrating detector (EID. In this work, we propose an iterative, hybrid reconstruction technique which combines the spectral properties of PCD data with the resolution and signal-to-noise characteristics of EID data. Our hybrid reconstruction technique is based on an algebraic model of data fidelity which substitutes the EID data into the data fidelity term associated with the PCD reconstruction, resulting in a joint reconstruction problem. Within the split Bregman framework, these data fidelity constraints are minimized subject to additional constraints on spectral rank and on joint intensity-gradient sparsity measured between the reconstructions of the EID and PCD data. Following a derivation of the proposed technique, we apply it to the reconstruction of a digital phantom which contains realistic concentrations of iodine, barium, and calcium encountered in small-animal micro-CT. The results of this experiment suggest reliable separation and detection of iodine at concentrations ≥ 5 mg/ml and barium at concentrations ≥ 10 mg/ml in 2-mm features for EID and PCD data reconstructed with inherent spatial resolutions of 176 μm and 254 μm, respectively (point spread function, FWHM. Furthermore, hybrid reconstruction is demonstrated to enhance spatial resolution within material decomposition results and to improve low-contrast detectability by as much as 2.6 times relative to reconstruction with PCD data only. The parameters of the simulation experiment are based on an in vivo micro-CT experiment conducted in a mouse model of soft-tissue sarcoma. Material decomposition results produced from this in vivo data demonstrate the feasibility of distinguishing two K-edge contrast agents with

Hybrid spectral CT reconstruction

Science.gov (United States)

Clark, Darin P.

2017-01-01

Current photon counting x-ray detector (PCD) technology faces limitations associated with spectral fidelity and photon starvation. One strategy for addressing these limitations is to supplement PCD data with high-resolution, low-noise data acquired with an energy-integrating detector (EID). In this work, we propose an iterative, hybrid reconstruction technique which combines the spectral properties of PCD data with the resolution and signal-to-noise characteristics of EID data. Our hybrid reconstruction technique is based on an algebraic model of data fidelity which substitutes the EID data into the data fidelity term associated with the PCD reconstruction, resulting in a joint reconstruction problem. Within the split Bregman framework, these data fidelity constraints are minimized subject to additional constraints on spectral rank and on joint intensity-gradient sparsity measured between the reconstructions of the EID and PCD data. Following a derivation of the proposed technique, we apply it to the reconstruction of a digital phantom which contains realistic concentrations of iodine, barium, and calcium encountered in small-animal micro-CT. The results of this experiment suggest reliable separation and detection of iodine at concentrations ≥ 5 mg/ml and barium at concentrations ≥ 10 mg/ml in 2-mm features for EID and PCD data reconstructed with inherent spatial resolutions of 176 μm and 254 μm, respectively (point spread function, FWHM). Furthermore, hybrid reconstruction is demonstrated to enhance spatial resolution within material decomposition results and to improve low-contrast detectability by as much as 2.6 times relative to reconstruction with PCD data only. The parameters of the simulation experiment are based on an in vivo micro-CT experiment conducted in a mouse model of soft-tissue sarcoma. Material decomposition results produced from this in vivo data demonstrate the feasibility of distinguishing two K-edge contrast agents with a spectral

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

Science.gov (United States)

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.

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

Science.gov (United States)

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

SPECTRAL VARIABILITY FROM THE PATCHY ATMOSPHERES OF T AND Y DWARFS

International Nuclear Information System (INIS)

Morley, Caroline V.; Fortney, Jonathan J.; Marley, Mark S.; Lupu, Roxana

2014-01-01

Brown dwarfs of a variety of spectral types have been observed to be photometrically variable. Previous studies have focused on objects at the L/T transition, where the iron and silicate clouds in L dwarfs break up or dissipate. However, objects outside of this transitional effective temperature regime also exhibit variability. Here, we present models for mid-late T dwarfs and Y dwarfs. We present models that include patchy salt and sulfide clouds as well as water clouds for the Y dwarfs. We find that for objects over 375 K, patchy cloud opacity would generate the largest amplitude variability within near-infrared spectral windows. For objects under 375 K, water clouds also become important and generate larger amplitude variability in the mid-infrared. We also present models in which we perturb the temperature structure at different pressure levels of the atmosphere to simulate hot spots. These models show the most variability in the absorption features between spectral windows. The variability is strongest at wavelengths that probe pressure levels at which the heating is the strongest. The most illustrative types of observations for understanding the physical processes underlying brown dwarf variability are simultaneous, multi-wavelength observations that probe both inside and outside of molecular absorption features

Detection of the 3.4 micron emission feature in Comets P/Brorsen-Metcalf and Okazaki-Levy-Rudenko (1989r) and an observational summary

International Nuclear Information System (INIS)

Brooke, T.Y.; Tokunaga, A.T.; Knacke, R.F.

1991-01-01

The 3.4 micron emission feature due to cometary organics was detected in Comets P/Brorsen-Metcalf and Okazaki-Levy-Rudenko (1989r). Features-to-continuum ratios in these two comets were higher than those expected from the trend seen in other comets to date. Three micron spectra of eight comets are reviewed. The 3.4 micron band flux is better correlated with the water production rate than with the dust production rate in this sample of comets. High feature-to-continuum ratios in P/Brorsen-Metcalf and Okazaki-Levy-Rudenko can be explained by the low dust-to-gas ratios of these two comets. The observations to date are consistent with cometary organics being present in all comets (even those for which no 3.4 micron feature was evident) at comparable abundances with respect to water. The emission mechanism and absolute abundance of the organics are not well determined; either gas-phase fluorescence or thermal emission from hot grains is consistent with the heliocentric distance dependence of the 3.4 micron band flux. There is an overall similarity in the spectral profiles of the 3.4 micron feature in comets; however, there are some potentially significant differences in the details of the spectra. 30 refs

Identification of spectral units on Phoebe

Science.gov (United States)

Coradini, A.; Tosi, F.; Gavrishin, A.I.; Capaccioni, F.; Cerroni, P.; Filacchione, G.; Adriani, A.; Brown, R.H.; Bellucci, G.; Formisano, V.; D'Aversa, E.; Lunine, J.I.; Baines, K.H.; Bibring, J.-P.; Buratti, B.J.; Clark, R.N.; Cruikshank, D.P.; Combes, M.; Drossart, P.; Jaumann, R.; Langevin, Y.; Matson, D.L.; McCord, T.B.; Mennella, V.; Nelson, R.M.; Nicholson, P.D.; Sicardy, B.; Sotin, Christophe; Hedman, M.M.; Hansen, G.B.; Hibbitts, C.A.; Showalter, M.; Griffith, C.; Strazzulla, G.

2008-01-01

We apply a multivariate statistical method to the Phoebe spectra collected by the VIMS experiment onboard the Cassini spacecraft during the flyby of June 2004. The G-mode clustering method, which permits identification of the most important features in a spectrum, is used on a small subset of data, characterized by medium and high spatial resolution, to perform a raw spectral classification of the surface of Phoebe. The combination of statistics and comparative analysis of the different areas using both the VIMS and ISS data is explored in order to highlight possible correlations with the surface geology. In general, the results by Clark et al. [Clark, R.N., Brown, R.H., Jaumann, R., Cruikshank, D.P., Nelson, R.M., Buratti, B.J., McCord, T.B., Lunine, J., Hoefen, T., Curchin, J.M., Hansen, G., Hibbitts, K., Matz, K.-D., Baines, K.H., Bellucci, G., Bibring, J.-P., Capaccioni, F., Cerroni, P., Coradini, A., Formisano, V., Langevin, Y., Matson, D.L., Mennella, V., Nicholson, P.D., Sicardy, B., Sotin, C., 2005. Nature 435, 66-69] are confirmed; but we also identify new signatures not reported before, such as the aliphatic CH stretch at 3.53 ??m and the ???4.4 ??m feature possibly related to cyanide compounds. On the basis of the band strengths computed for several absorption features and for the homogeneous spectral types isolated by the G-mode, a strong correlation of CO2 and aromatic hydrocarbons with exposed water ice, where the uniform layer covering Phoebe has been removed, is established. On the other hand, an anti-correlation of cyanide compounds with CO2 is suggested at a medium resolution scale. ?? 2007 Elsevier Inc. All rights reserved.

Evaluating variations of physiology-based hyperspectral features along a soil water gradient in Eucalyptus grandis plantation

CSIR Research Space (South Africa)

Cho, Moses A

2010-04-01

Full Text Available a raised platform. Foliar macronutrient concentrations for N, P, K, S, Ca, Mg and Na and their corresponding spectral features were also evaluated. The spectral signals for leaf water-normalized difference water index (NDWI), water band index (WBI...

Pervasive randomness in physics: an introduction to its modelling and spectral characterisation

Science.gov (United States)

Howard, Roy

2017-10-01

An introduction to the modelling and spectral characterisation of random phenomena is detailed at a level consistent with a first exposure to the subject at an undergraduate level. A signal framework for defining a random process is provided and this underpins an introduction to common random processes including the Poisson point process, the random walk, the random telegraph signal, shot noise, information signalling random processes, jittered pulse trains, birth-death random processes and Markov chains. An introduction to the spectral characterisation of signals and random processes, via either an energy spectral density or a power spectral density, is detailed. The important case of defining a white noise random process concludes the paper.

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

Science.gov (United States)

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.

Spectral Characteristics of Salinized Soils during Microbial Remediation Processes.

Science.gov (United States)

Ma, Chuang; Shen, Guang-rong; Zhi, Yue-e; Wang, Zi-jun; Zhu, Yun; Li, Xian-hua

2015-09-01

In this study, the spectral reflectance of saline soils, the associated soil salt content (SSC) and the concentrations of salt ions were measured and analysed by tracing the container microbial remediation experiments for saline soil (main salt is sodium chloride) of Dongying City, Shandong Province. The sensitive spectral reflectance bands of saline soils to SSC, Cl- and Na+ in the process of microbial remediation were analysed. The average-dimension reduction of these bands was conducted by using a combination of correlation coefficient and decision coefficient, and by gradually narrowing the sampling interval method. Results showed that the tendency and magnitude of the average spectral reflectance in all bands of saline soils during the total remediation processes were nearly consistent with SSC and with Cl- coocentration, respectively. The degree of salinity of the soil, including SSC and salt ion concentrations, had a significant positive correlation with the spectral reflectance of all bands, particularly in the near-infrared band. The optimal spectral bands of SSC were 1370 to 1445 nm and 1447 to 1608 nm, whereas the optimal spectral bands of Cl- and Na+ were 1336 to 1461 nm and 1471 to 1561 nm, respectively. The relationship model among SSC, soil salt ion concentrations (Cl- and Na+) and soil spectral reflectance of the corresponding optimal spectral band was established. The largest R2 of relationship model between SSC and the average reflectance of associated optimal band reached to 0.95, and RMSEC and RMSEP were 1.076 and 0.591, respectively. Significant statistical analysis of salt factors and soil reflectance for different microbial remediation processes indicated that the spectral response characteristics and sensitivity of SSC to soil reflectance, which implied the feasibility of high spectrum test on soil microbial remediation monitoring, also provided the basis for quick nondestructive monitoring soil bioremediation process by soil spectral

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

Energy Technology Data Exchange (ETDEWEB)

Oklopčić, Antonija [California Institute of Technology, 1200 East California Boulevard, MC 249-17, Pasadena, CA 91125 (United States); Hirata, Christopher M. [Center for Cosmology and Astroparticle Physics, Ohio State University, 191 West Woodruff Avenue, Columbus, OH 43210 (United States); Heng, Kevin, E-mail: oklopcic@astro.caltech.edu [Center for Space and Habitability, University of Bern, Sidlerstrasse 5, CH-3012, Bern (Switzerland)

2017-09-10

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, depend 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.

Nonlocal low-rank and sparse matrix decomposition for spectral CT reconstruction

Science.gov (United States)

Niu, Shanzhou; Yu, Gaohang; Ma, Jianhua; Wang, Jing

2018-02-01

Spectral computed tomography (CT) has been a promising technique in research and clinics because of its ability to produce improved energy resolution images with narrow energy bins. However, the narrow energy bin image is often affected by serious quantum noise because of the limited number of photons used in the corresponding energy bin. To address this problem, we present an iterative reconstruction method for spectral CT using nonlocal low-rank and sparse matrix decomposition (NLSMD), which exploits the self-similarity of patches that are collected in multi-energy images. Specifically, each set of patches can be decomposed into a low-rank component and a sparse component, and the low-rank component represents the stationary background over different energy bins, while the sparse component represents the rest of the different spectral features in individual energy bins. Subsequently, an effective alternating optimization algorithm was developed to minimize the associated objective function. To validate and evaluate the NLSMD method, qualitative and quantitative studies were conducted by using simulated and real spectral CT data. Experimental results show that the NLSMD method improves spectral CT images in terms of noise reduction, artifact suppression and resolution preservation.

Theory of atomic spectral emission intensity

Science.gov (United States)

Yngström, Sten

1994-07-01

The theoretical derivation of a new spectral line intensity formula for atomic radiative emission is presented. The theory is based on first principles of quantum physics, electrodynamics, and statistical physics. Quantum rules lead to revision of the conventional principle of local thermal equilibrium of matter and radiation. Study of electrodynamics suggests absence of spectral emission from fractions of the numbers of atoms and ions in a plasma due to radiative inhibition caused by electromagnetic force fields. Statistical probability methods are extended by the statement: A macroscopic physical system develops in the most probable of all conceivable ways consistent with the constraining conditions for the system. The crucial role of statistical physics in transforming quantum logic into common sense logic is stressed. The theory is strongly supported by experimental evidence.

Some properties of spectral binary stars

International Nuclear Information System (INIS)

Krajcheva, Z.T.; Popova, E.I.; Tutukov, A.V.; Yungel'son, L.R.; AN SSSR, Moscow. Astronomicheskij Sovet)

1978-01-01

Statistical investigations of spectra binary stars are carried out. Binary systems consisting of main sequence stars are considered. For 826 binary stars masses of components, ratios of component masses, semiaxes of orbits and orbital angular momenta are calculated. The distributions of these parameters and their correlations are analyzed. The dependences of statistical properties of spectral binary stars on their origin and evolution are discussed

Mid-IR Reflectance (DRIFT) Spectral Variations in Basaltic Mineralogy with Direction of Impact at Lonar Crater, India

Science.gov (United States)

Basavaiah, N.; Chavan, R. S.; Arif, M.

2012-12-01

shock metamorphism in contrast to eastern sector. This is consistent with the structural degradation of unshocked basaltic mineralogy comprising mainly Plagioclase Feldspar, which agrees with our previous rock-magnetic work. Similarly, the 550-600 cm-1 band which is attributed to Si-O bending or deformation, is noticed to get weakened in the western sector relative to eastern sector. Also, a slight change in depth of feature in 600-650cm-1 with direction of impactor is observed. The results show that there is relative loss of spectral features in western sector compared to eastern sector as a result of increased shock wave and subsequent disordering of mineralogy. In all, the spectral changes of Lonar basalts reflect the distribution of post impact shock processes and thus resulting mineralogical changes. The OMNIC-present mineral distribution maps around the Lonar crater are represented by pie-charts prepared from the identification of the first 10 minerals on the recorded rock powder spectra, revealing an abundance of primary and secondary minerals. Also, the combined results of our ongoing ATR, XRD and SEM analyses of primary and secondary basaltic mineralogy at Lonar will be presented, which may have implications in understanding overall impact-, alteration- and weathering-processes occurring on other planetary bodies such as Mars.

Automics: an integrated platform for NMR-based metabonomics spectral processing and data analysis

Directory of Open Access Journals (Sweden)

Qu Lijia

2009-03-01

Full Text Available Abstract Background Spectral processing and post-experimental data analysis are the major tasks in NMR-based metabonomics studies. While there are commercial and free licensed software tools available to assist these tasks, researchers usually have to use multiple software packages for their studies because software packages generally focus on specific tasks. It would be beneficial to have a highly integrated platform, in which these tasks can be completed within one package. Moreover, with open source architecture, newly proposed algorithms or methods for spectral processing and data analysis can be implemented much more easily and accessed freely by the public. Results In this paper, we report an open source software tool, Automics, which is specifically designed for NMR-based metabonomics studies. Automics is a highly integrated platform that provides functions covering almost all the stages of NMR-based metabonomics studies. Automics provides high throughput automatic modules with most recently proposed algorithms and powerful manual modules for 1D NMR spectral processing. In addition to spectral processing functions, powerful features for data organization, data pre-processing, and data analysis have been implemented. Nine statistical methods can be applied to analyses including: feature selection (Fisher's criterion, data reduction (PCA, LDA, ULDA, unsupervised clustering (K-Mean and supervised regression and classification (PLS/PLS-DA, KNN, SIMCA, SVM. Moreover, Automics has a user-friendly graphical interface for visualizing NMR spectra and data analysis results. The functional ability of Automics is demonstrated with an analysis of a type 2 diabetes metabolic profile. Conclusion Automics facilitates high throughput 1D NMR spectral processing and high dimensional data analysis for NMR-based metabonomics applications. Using Automics, users can complete spectral processing and data analysis within one software package in most cases

Automics: an integrated platform for NMR-based metabonomics spectral processing and data analysis.

Science.gov (United States)

Wang, Tao; Shao, Kang; Chu, Qinying; Ren, Yanfei; Mu, Yiming; Qu, Lijia; He, Jie; Jin, Changwen; Xia, Bin

2009-03-16

Spectral processing and post-experimental data analysis are the major tasks in NMR-based metabonomics studies. While there are commercial and free licensed software tools available to assist these tasks, researchers usually have to use multiple software packages for their studies because software packages generally focus on specific tasks. It would be beneficial to have a highly integrated platform, in which these tasks can be completed within one package. Moreover, with open source architecture, newly proposed algorithms or methods for spectral processing and data analysis can be implemented much more easily and accessed freely by the public. In this paper, we report an open source software tool, Automics, which is specifically designed for NMR-based metabonomics studies. Automics is a highly integrated platform that provides functions covering almost all the stages of NMR-based metabonomics studies. Automics provides high throughput automatic modules with most recently proposed algorithms and powerful manual modules for 1D NMR spectral processing. In addition to spectral processing functions, powerful features for data organization, data pre-processing, and data analysis have been implemented. Nine statistical methods can be applied to analyses including: feature selection (Fisher's criterion), data reduction (PCA, LDA, ULDA), unsupervised clustering (K-Mean) and supervised regression and classification (PLS/PLS-DA, KNN, SIMCA, SVM). Moreover, Automics has a user-friendly graphical interface for visualizing NMR spectra and data analysis results. The functional ability of Automics is demonstrated with an analysis of a type 2 diabetes metabolic profile. Automics facilitates high throughput 1D NMR spectral processing and high dimensional data analysis for NMR-based metabonomics applications. Using Automics, users can complete spectral processing and data analysis within one software package in most cases. Moreover, with its open source architecture, interested

The gravitational wave background from massive black hole binaries in Illustris: spectral features and time to detection with pulsar timing arrays

Science.gov (United States)

Kelley, Luke Zoltan; Blecha, Laura; Hernquist, Lars; Sesana, Alberto; Taylor, Stephen R.

2017-11-01

Pulsar timing arrays (PTAs) around the world are using the incredible consistency of millisecond pulsars to measure low-frequency gravitational waves from (super)massive black hole (MBH) binaries. We use comprehensive MBH merger models based on cosmological hydrodynamic simulations to predict the spectrum of the stochastic gravitational wave background (GWB). We use real time-of-arrival specifications from the European, NANOGrav, Parkes, and International PTA (IPTA) to calculate realistic times to detection of the GWB across a wide range of model parameters. In addition to exploring the parameter space of environmental hardening processes (in particular: stellar scattering efficiencies), we have expanded our models to include eccentric binary evolution which can have a strong effect on the GWB spectrum. Our models show that strong stellar scattering and high characteristic eccentricities enhance the GWB strain amplitude near the PTA-sensitive `sweet-spot' (near the frequency f = 1 yr-1), slightly improving detection prospects in these cases. While the GWB amplitude is degenerate between cosmological and environmental parameters, the location of a spectral turnover at low frequencies (f ≲ 0.1 yr-1) is strongly indicative of environmental coupling. At high frequencies (f ≳ 1 yr-1), the GWB spectral index can be used to infer the number density of sources and possibly their eccentricity distribution. Even with merger models that use pessimistic environmental and eccentricity parameters, if the current rate of PTA expansion continues, we find that the IPTA is highly likely to make a detection within about 10 yr.

Spectral dynamics of square pulses in passively mode-locked fiber lasers

Science.gov (United States)

Semaan, Georges; Komarov, Andrey; Niang, Alioune; Salhi, Mohamed; Sanchez, François

2018-02-01

We investigate experimentally and numerically the spectral dynamics of square pulses generated in passively mode-locked fiber lasers under the dissipative soliton resonance. The features of the transition from the single-peak spectral profile to the doublet spectrum with increasing pump power are studied. The used master equation takes into account the gain saturation, the quadratic frequency dispersion of the gain and the refractive index, and the cubic-quintic nonlinearity of the losses and refractive index. Experimental data are obtained for an Er:Yb-doped fiber ring laser. The theoretical and experimental results are in good agreement with each other.

Feature ranking and rank aggregation for automatic sleep stage classification: a comparative study.

Science.gov (United States)

Najdi, Shirin; Gharbali, Ali Abdollahi; Fonseca, José Manuel

2017-08-18

Nowadays, sleep quality is one of the most important measures of healthy life, especially considering the huge number of sleep-related disorders. Identifying sleep stages using polysomnographic (PSG) signals is the traditional way of assessing sleep quality. However, the manual process of sleep stage classification is time-consuming, subjective and costly. Therefore, in order to improve the accuracy and efficiency of the sleep stage classification, researchers have been trying to develop automatic classification algorithms. Automatic sleep stage classification mainly consists of three steps: pre-processing, feature extraction and classification. Since classification accuracy is deeply affected by the extracted features, a poor feature vector will adversely affect the classifier and eventually lead to low classification accuracy. Therefore, special attention should be given to the feature extraction and selection process. In this paper the performance of seven feature selection methods, as well as two feature rank aggregation methods, were compared. Pz-Oz EEG, horizontal EOG and submental chin EMG recordings of 22 healthy males and females were used. A comprehensive feature set including 49 features was extracted from these recordings. The extracted features are among the most common and effective features used in sleep stage classification from temporal, spectral, entropy-based and nonlinear categories. The feature selection methods were evaluated and compared using three criteria: classification accuracy, stability, and similarity. Simulation results show that MRMR-MID achieves the highest classification performance while Fisher method provides the most stable ranking. In our simulations, the performance of the aggregation methods was in the average level, although they are known to generate more stable results and better accuracy. The Borda and RRA rank aggregation methods could not outperform significantly the conventional feature ranking methods. Among

SPECTRAL EVOLUTION OF THE 2010 SEPTEMBER GAMMA-RAY FLARE FROM THE CRAB NEBULA

International Nuclear Information System (INIS)

Vittorini, V.; Tavani, M.; Donnarumma, I.; Trois, A.; Del Monte, E.; Evangelista, Y.; Lazzarotto, F.; Pacciani, L.; Pucella, G.; Striani, E.; Caraveo, P.; Giuliani, A.; Mereghetti, S.; Pellizzoni, A.; Ferrari, A.; Barbiellini, G.; Bulgarelli, A.; Cattaneo, P. W.; Colafrancesco, S.; Pilia, M.

2011-01-01

Strong gamma-ray flares from the Crab Nebula have been recently discovered by AGILE and confirmed by Fermi-LAT. We study here the spectral evolution in the gamma-ray energy range above 50 MeV of the 2010 September flare that was simultaneously detected by AGILE and Fermi-LAT. We revisit the AGILE spectral data and present an emission model based on rapid (within 1 day) acceleration followed by synchrotron cooling. We show that this model successfully explains both the published AGILE and Fermi-LAT spectral data showing a rapid rise and a decay within 2 and 3 days. Our analysis constrains the acceleration timescale and mechanism, the properties of the particle distribution function, and the local magnetic field. The combination of very rapid acceleration, emission well above 100 MeV, and the spectral evolution consistent with synchrotron cooling contradicts the idealized scenario predicting an exponential cutoff at photon energies above 100 MeV. We also consider a variation of our model based on even shorter acceleration and decay timescales, which can be consistent with the published averaged properties.

Interferometric and nonlinear-optical spectral-imaging techniques for outer space and live cells

Science.gov (United States)

Itoh, Kazuyoshi

2015-12-01

Multidimensional signals such as the spectral images allow us to have deeper insights into the natures of objects. In this paper the spectral imaging techniques that are based on optical interferometry and nonlinear optics are presented. The interferometric imaging technique is based on the unified theory of Van Cittert-Zernike and Wiener-Khintchine theorems and allows us to retrieve a spectral image of an object in the far zone from the 3D spatial coherence function. The retrieval principle is explained using a very simple object. The promising applications to space interferometers for astronomy that are currently in progress will also be briefly touched on. An interesting extension of interferometric spectral imaging is a 3D and spectral imaging technique that records 4D information of objects where the 3D and spectral information is retrieved from the cross-spectral density function of optical field. The 3D imaging is realized via the numerical inverse propagation of the cross-spectral density. A few techniques suggested recently are introduced. The nonlinear optical technique that utilizes stimulated Raman scattering (SRS) for spectral imaging of biomedical targets is presented lastly. The strong signals of SRS permit us to get vibrational information of molecules in the live cell or tissue in real time. The vibrational information of unstained or unlabeled molecules is crucial especially for medical applications. The 3D information due to the optical nonlinearity is also the attractive feature of SRS spectral microscopy.

Introduction to Hilbert space and the theory of spectral multiplicity

CERN Document Server

Halmos, Paul R

2017-01-01

Concise introductory treatment consists of three chapters: The Geometry of Hilbert Space, The Algebra of Operators, and The Analysis of Spectral Measures. A background in measure theory is the sole prerequisite. 1957 edition.

Spectral functions and transport coefficients from the functional renormalization group

Energy Technology Data Exchange (ETDEWEB)

Tripolt, Ralf-Arno

2015-06-03

In this thesis we present a new method to obtain real-time quantities like spectral functions and transport coefficients at finite temperature and density using the Functional Renormalization Group approach. Our non-perturbative method is thermodynamically consistent, symmetry preserving and based on an analytic continuation from imaginary to real time on the level of the flow equations. We demonstrate the applicability of this method by calculating mesonic spectral functions as well as the shear viscosity for the quark-meson model. In particular, results are presented for the pion and sigma spectral function at finite temperature and chemical potential, with a focus on the regime near the critical endpoint in the phase diagram of the quark-meson model. Moreover, the different time-like and space-like processes, which give rise to a complex structure of the spectral functions, are discussed. Finally, based on the momentum dependence of the spectral functions, we calculate the shear viscosity and the shear viscosity to entropy density ratio using the corresponding Green-Kubo formula.

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

Science.gov (United States)

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.

Terrain Extraction by Integrating Terrestrial Laser Scanner Data and Spectral Information

Science.gov (United States)

Lau, C. L.; Halim, S.; Zulkepli, M.; Azwan, A. M.; Tang, W. L.; Chong, A. K.

2015-10-01

The extraction of true terrain points from unstructured laser point cloud data is an important process in order to produce an accurate digital terrain model (DTM). However, most of these spatial filtering methods just utilizing the geometrical data to discriminate the terrain points from nonterrain points. The point cloud filtering method also can be improved by using the spectral information available with some scanners. Therefore, the objective of this study is to investigate the effectiveness of using the three-channel (red, green and blue) of the colour image captured from built-in digital camera which is available in some Terrestrial Laser Scanner (TLS) for terrain extraction. In this study, the data acquisition was conducted at a mini replica landscape in Universiti Teknologi Malaysia (UTM), Skudai campus using Leica ScanStation C10. The spectral information of the coloured point clouds from selected sample classes are extracted for spectral analysis. The coloured point clouds which within the corresponding preset spectral threshold are identified as that specific feature point from the dataset. This process of terrain extraction is done through using developed Matlab coding. Result demonstrates that a higher spectral resolution passive image is required in order to improve the output. This is because low quality of the colour images captured by the sensor contributes to the low separability in spectral reflectance. In conclusion, this study shows that, spectral information is capable to be used as a parameter for terrain extraction.

Arrhythmia Mechanism and Scaling Effect on the Spectral Properties of Electroanatomical Maps With Manifold Harmonics.

Science.gov (United States)

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.

Spectral evolution of GRBs with negative spectral lag using Fermi GBM observations

Science.gov (United States)

Chakrabarti, Arundhati; Chaudhury, Kishor; Sarkar, Samir K.; Bhadra, Arunava

2018-06-01

The positive spectral lag of Gamma Ray Bursts (GRBs) is often explained in terms of hard-to-soft spectral evolution of GRB pulses. While positive lags of GRBs is very common, there are few GRB pulses that exhibits negative spectral lags. In the present work we examine whether negative lags of GRBs also can be interpreted in terms of spectral evolution of GRB pulses or not. Using Fermi-GBM data, we identify two GRBs, GRB 090426C and GRB 150213A, with clean pulses that exhibit negative spectral lag. An indication of soft to hard transition has been noticed for the negative spectral lag events from the spectral evolution study. The implication of the present findings on the models of GRB spectral lags are discussed.

A stabilised nodal spectral element method for fully nonlinear water waves

DEFF Research Database (Denmark)

Engsig-Karup, Allan Peter; Eskilsson, C.; Bigoni, Daniele

2016-01-01

can cause severe aliasing problems and consequently numerical instability for marginally resolved or very steep waves. We show how the scheme can be stabilised through a combination of over-integration of the Galerkin projections and a mild spectral filtering on a per element basis. This effectively......We present an arbitrary-order spectral element method for general-purpose simulation of non-overturning water waves, described by fully nonlinear potential theory. The method can be viewed as a high-order extension of the classical finite element method proposed by Cai et al. (1998) [5], although...... the numerical implementation differs greatly. Features of the proposed spectral element method include: nodal Lagrange basis functions, a general quadrature-free approach and gradient recovery using global L2 projections. The quartic nonlinear terms present in the Zakharov form of the free surface conditions...

Comprehensive spectral analysis of Cyg X-1 using RXTE data

International Nuclear Information System (INIS)

Shahid, Rizwan; Jaaffrey, S. N. A.; Misra, Ranjeev

2012-01-01

We analyze a large number (> 500) of pointed Rossi X-Ray Timing Explorer (RXTE) observations of Cyg X-1 and model the spectrum of each one. A subset of the observations for which there is a simultaneous reliable measure of the hardness ratio by the All Sky Monitor shows that the sample covers nearly all the spectral shapes of Cyg X-1. Each observation is fitted with a generic empirical model consisting of a disk black body spectrum, a Comptonized component whose input photon shape is the same as the disk emission, a Gaussian to represent the iron line and a reflection feature. The relative strength, width of the iron line and the reflection parameter are in general correlated with the high energy photon spectral index Γ. This is broadly consistent with a geometry where for the hard state (low Γ ∼ 1.7) there is a hot inner Comptonizing region surrounded by a truncated cold disk. The inner edge of the disk moves inwards as the source becomes softer till finally in the soft state (high Γ > 2.2) the disk fills the inner region and active regions above the disk produce the Comptonized component. However, the reflection parameter shows non-monotonic behavior near the transition region (Γ ∼ 2), which suggests a more complex geometry or physical state of the reflector. In addition, the inner disk temperature, during the hard state, is on average higher than in the soft one, albeit with large scatter. These inconsistencies could be due to limitations in the data and the empirical model used to fit them. The flux of each spectral component is well correlated with Γ, which shows that unlike some other black hole systems, Cyg X-1 does not show any hysteresis behavior. In the soft state, the flux of the Comptonized component is always similar to the disk one, which confirms that the ultra-soft state (seen in other brighter black hole systems) is not exhibited by Cyg X-1. The rapid variation of the Compton amplification factor with Γ naturally explains the absence of

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

Science.gov (United States)

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.

Prediction of spectral acceleration response ordinates based on PGA attenuation

Science.gov (United States)

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.

Laboratory Thermal Infrared and Visible to Near-Infrared Spectral Analysis of Chert

Science.gov (United States)

McDowell, M. L.; Hamilton, V. E.

2007-12-01

Though basaltic materials dominate the composition of the Martian surface, a material with a relatively high silica component in an area of Eos Chasma was reported by [1] from thermal infrared (TIR) data. The spectrum of the silica phase resembles quartz or chert, but with the existing information it is difficult to tell which phase best fits the observations. Though quartz, chert, and amorphous silica are chemically identical (SiO2), their physical differences (e.g., microstructures) result in different TIR spectral characteristics. Previous studies have analyzed a limited number of chert samples using emission infrared spectroscopy [2] and transmission infrared spectroscopy [3]. We continue these preliminary studies with an investigation aiming to more completely understand and document the variation in spectral character of cherts. This knowledge may help to identify the silica phase in Eos Chasma and any future discoveries. Our study includes a more extensive sampling of geologic chert in hand sample (>15 samples) with various sources, methods of formation, surface textures, and crystallinities. We analyzed their visible to near-infrared (VNIR) reflectance spectra, as well as spectral features in TIR emission spectra. We measured multiple locations on each sample to determine spectral homogeneity across the sample and between various orientations. Where possible, natural, cut, and recently fractured surfaces were measured. We compared the collected TIR spectra for similarities and differences in shape and spectral contrast within each sample and between samples that may relate to variations in the samples' structure (e.g. crystallinity, and surface texture). VNIR measurements show features indicative of non-silica phases and water that may be present in the cherts. [1] Hamilton, V.E. (2005) Eos Trans. AGU, Fall Meeting Suppl., Abstract P24A-08. [2] Michalski, J.R. (2005) PhD Diss., ASU, Tempe. [3] Long, D. G. et al. (2001) Canadian Archaeological Assoc., 33rd

Retrieval of spheroid particle size distribution from spectral extinction data in the independent mode using PCA approach

International Nuclear Information System (INIS)

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. -- Highlights: ► Improved ADA is presented for calculating the extinction efficiency of spheroids. ► Selection principle about spectral extinction data is developed based on PCA. ► Improved Tikhonov iteration method is proposed to retrieve the spheroid PSD.

Consistency relation in power law G-inflation

International Nuclear Information System (INIS)

Unnikrishnan, Sanil; Shankaranarayanan, S.

2014-01-01

In the standard inflationary scenario based on a minimally coupled scalar field, canonical or non-canonical, the subluminal propagation of speed of scalar perturbations ensures the following consistency relation: r ≤ −8n T , where r is the tensor-to-scalar-ratio and n T is the spectral index for tensor perturbations. However, recently, it has been demonstrated that this consistency relation could be violated in Galilean inflation models even in the absence of superluminal propagation of scalar perturbations. It is therefore interesting to investigate whether the subluminal propagation of scalar field perturbations impose any bound on the ratio r/|n T | in G-inflation models. In this paper, we derive the consistency relation for a class of G-inflation models that lead to power law inflation. Within these class of models, it turns out that one can have r > −8n T or r ≤ −8n T depending on the model parameters. However, the subluminal propagation of speed of scalar field perturbations, as required by causality, restricts r ≤ −(32/3) n T

From spectral holeburning memory to spatial-spectral microwave signal processing

International Nuclear Information System (INIS)

Babbitt, Wm Randall; Barber, Zeb W; Harrington, Calvin; Mohan, R Krishna; Sharpe, Tia; Bekker, Scott H; Chase, Michael D; Merkel, Kristian D; Stiffler, Colton R; Traxinger, Aaron S; Woidtke, Alex J

2014-01-01

Many storage and processing systems based on spectral holeburning have been proposed that access the broad bandwidth and high dynamic range of spatial-spectral materials, but only recently have practical systems been developed that exceed the performance and functional capabilities of electronic devices. This paper reviews the history of the proposed applications of spectral holeburning and spatial-spectral materials, from frequency domain optical memory to microwave photonic signal processing systems. The recent results of a 20 GHz bandwidth high performance spectrum monitoring system with the additional capability of broadband direction finding demonstrates the potential for spatial-spectral systems to be the practical choice for solving demanding signal processing problems in the near future. (paper)

ANALYSIS OF SPECTRAL CHARACTERISTICS AMONG DIFFERENT SENSORS BY USE OF SIMULATED RS IMAGES

Institute of Scientific and Technical Information of China (English)

无

2000-01-01

This research, by use of RS image-simulating method, simulated apparent reflectance images at sensor level and ground-reflectance images of SPOT-HRV,CBERS-CCD,Landsat-TM and NOAA14-AVHRR' s corresponding bands. These images were used to analyze sensor's differences caused by spectral sensitivity and atmospheric impacts. The differences were analyzed on Normalized Difference Vegetation Index(NDVI). The results showed that the differences of sensors' spectral characteristics cause changes of their NDVI and reflectance. When multiple sensors' data are applied to digital analysis, the error should be taken into account. Atmospheric effect makes NDVI smaller, and atn~pheric correction has the tendency of increasing NDVI values. The reflectance and their NDVIs of different sensors can be used to analyze the differences among sensor' s features. The spectral analysis method based on RS simulated images can provide a new way to design the spectral characteristics of new sensors.

[Research on Spectral Polarization Imaging System Based on Static Modulation].

Science.gov (United States)

Zhao, Hai-bo; Li, Huan; Lin, Xu-ling; Wang, Zheng

2015-04-01

The main disadvantages of traditional spectral polarization imaging system are: complex structure, with moving parts, low throughput. A novel method of spectral polarization imaging system is discussed, which is based on static polarization intensity modulation combined with Savart polariscope interference imaging. The imaging system can obtain real-time information of spectral and four Stokes polarization messages. Compared with the conventional methods, the advantages of the imaging system are compactness, low mass and no moving parts, no electrical control, no slit and big throughput. The system structure and the basic theory are introduced. The experimental system is established in the laboratory. The experimental system consists of reimaging optics, polarization intensity module, interference imaging module, and CCD data collecting and processing module. The spectral range is visible and near-infrared (480-950 nm). The white board and the plane toy are imaged by using the experimental system. The ability of obtaining spectral polarization imaging information is verified. The calibration system of static polarization modulation is set up. The statistical error of polarization degree detection is less than 5%. The validity and feasibility of the basic principle is proved by the experimental result. The spectral polarization data captured by the system can be applied to object identification, object classification and remote sensing detection.

Image enhancement by spectral-error correction for dual-energy computed tomography.

Science.gov (United States)

Park, Kyung-Kook; Oh, Chang-Hyun; Akay, Metin

2011-01-01

Dual-energy CT (DECT) was reintroduced recently to use the additional spectral information of X-ray attenuation and aims for accurate density measurement and material differentiation. However, the spectral information lies in the difference between low and high energy images or measurements, so that it is difficult to acquire accurate spectral information due to amplification of high pixel noise in the resulting difference image. In this work, an image enhancement technique for DECT is proposed, based on the fact that the attenuation of a higher density material decreases more rapidly as X-ray energy increases. We define as spectral error the case when a pixel pair of low and high energy images deviates far from the expected attenuation trend. After analyzing the spectral-error sources of DECT images, we propose a DECT image enhancement method, which consists of three steps: water-reference offset correction, spectral-error correction, and anti-correlated noise reduction. It is the main idea of this work that makes spectral errors distributed like random noise over the true attenuation and suppressed by the well-known anti-correlated noise reduction. The proposed method suppressed noise of liver lesions and improved contrast between liver lesions and liver parenchyma in DECT contrast-enhanced abdominal images and their two-material decomposition.

Spectral feature of 31 December 1981 γ-ray burst not confirmed

International Nuclear Information System (INIS)

Nolan, P.L.; Share, G.H.; Chupp, E.L.; Forrest, D.J.; Matz, S.M.

1984-01-01

The authors compare measurements of a γ-ray burst at 01:37 UT on 31 December 1981, using the Solar Maximum Mission (SMM) γ-ray spectrometer with those made by the Konus instruments on Veneras 11-14. The SMM spectra exhibit no evidence for the presence of emission features reported by the Konus group. (author)

SURFACE ALBEDO AND SPECTRAL VARIABILITY OF CERES

Energy Technology Data Exchange (ETDEWEB)

Li, Jian-Yang; Reddy, Vishnu; Corre, Lucille Le; Sykes, Mark V.; Prettyman, Thomas H. [Planetary Science Institute, 1700 E. Ft. Lowell Road, Suite 106, Tucson, AZ 85719 (United States); Nathues, Andreas; Hoffmann, Martin; Schaefer, Michael [Max Planck Institute for Solar System Research, Göttingen (Germany); Izawa, Matthew R. M.; Cloutis, Edward A. [University of Winnipeg, Winnipeg, Manitoba (Canada); Carsenty, Uri; Jaumann, Ralf; Krohn, Katrin; Mottola, Stefano; Schröder, Stefan E. [German Aerospace Center (DLR), Institute of Planetary Research, Berlin (Germany); Castillo-Rogez, Julie C. [Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109 (United States); Schenk, Paul [Lunar and Planetary Institute, Houston, TX 77058 (United States); Williams, David A. [School of Earth and Space Exploration, Arizona State University, Tempe, AZ 85287 (United States); Smith, David E. [Solar System Exploration Division, NASA Goddard Space Flight Center, Greenbelt, MD 20771 (United States); Zuber, Maria T. [Department of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139 (United States); and others

2016-02-01

Previous observations suggested that Ceres has active, but possibly sporadic, water outgassing as well as possibly varying spectral characteristics over a timescale of months. We used all available data of Ceres collected in the past three decades from the ground and the Hubble Space Telescope, as well as the newly acquired images by the Dawn  Framing Camera, to search for spectral and albedo variability on Ceres, on both a global scale and in local regions, particularly the bright spots inside the Occator crater, over timescales of a few months to decades. Our analysis has placed an upper limit on the possible temporal albedo variation on Ceres. Sporadic water vapor venting, or any possibly ongoing activity on Ceres, is not significant enough to change the albedo or the area of the bright features in the Occator crater by >15%, or the global albedo by >3% over the various timescales that we searched. Recently reported spectral slope variations can be explained by changing Sun–Ceres–Earth geometry. The active area on Ceres is less than 1 km{sup 2}, too small to cause global albedo and spectral variations detectable in our data. Impact ejecta due to impacting projectiles of tens of meters in size like those known to cause observable changes to the surface albedo on Asteroid Scheila cannot cause detectable albedo change on Ceres due to its relatively large size and strong gravity. The water vapor activity on Ceres is independent of Ceres’ heliocentric distance, ruling out the possibility of the comet-like sublimation process as a possible mechanism driving the activity.

Modelling Perception of Structure and Affect in Music: Spectral Centroid and Wishart's Red Bird

Directory of Open Access Journals (Sweden)

Roger T. Dean

2011-12-01

Full Text Available Pearce (2011 provides a positive and interesting response to our article on time series analysis of the influences of acoustic properties on real-time perception of structure and affect in a section of Trevor Wishart’s Red Bird (Dean & Bailes, 2010. We address the following topics raised in the response and our paper. First, we analyse in depth the possible influence of spectral centroid, a timbral feature of the acoustic stream distinct from the high level general parameter we used initially, spectral flatness. We find that spectral centroid, like spectral flatness, is not a powerful predictor of real-time responses, though it does show some features that encourage its continued consideration. Second, we discuss further the issue of studying both individual responses, and as in our paper, group averaged responses. We show that a multivariate Vector Autoregression model handles the grand average series quite similarly to those of individual members of our participant groups, and we analyse this in greater detail with a wide range of approaches in work which is in press and continuing. Lastly, we discuss the nature and intent of computational modelling of cognition using acoustic and music- or information theoretic data streams as predictors, and how the music- or information theoretic approaches may be applied to electroacoustic music, which is ‘sound-based’ rather than note-centred like Western classical music.

Consistent Regulation of Infrastructure Businesses: Some Economic Issues

OpenAIRE

Flavio M. Menezes

2008-01-01

This paper examines some important economic aspects associated with the notion that consistency in the regulation of infrastructure businesses is a desirable feature. It makes two important points. First, it is not easy to measure consistency. In particular, one cannot simply point to different regulatory parameters as evidence of inconsistent regulatory policy. Second, even if one does observe consistency emerging from decisions made by different regulators, it does not necessarily mean that...

Nonparametric Collective Spectral Density Estimation and Clustering

KAUST Repository

Maadooliat, Mehdi; Sun, Ying; Chen, Tianbo

2017-01-01

In this paper, we develop a method for the simultaneous estimation of spectral density functions (SDFs) for a collection of stationary time series that share some common features. Due to the similarities among the SDFs, the log-SDF can be represented using a common set of basis functions. The basis shared by the collection of the log-SDFs is estimated as a low-dimensional manifold of a large space spanned by a pre-specified rich basis. A collective estimation approach pools information and borrows strength across the SDFs to achieve better estimation efficiency. Also, each estimated spectral density has a concise representation using the coefficients of the basis expansion, and these coefficients can be used for visualization, clustering, and classification purposes. The Whittle pseudo-maximum likelihood approach is used to fit the model and an alternating blockwise Newton-type algorithm is developed for the computation. A web-based shiny App found at

Nonparametric Collective Spectral Density Estimation and Clustering

KAUST Repository

Maadooliat, Mehdi

2017-04-12

In this paper, we develop a method for the simultaneous estimation of spectral density functions (SDFs) for a collection of stationary time series that share some common features. Due to the similarities among the SDFs, the log-SDF can be represented using a common set of basis functions. The basis shared by the collection of the log-SDFs is estimated as a low-dimensional manifold of a large space spanned by a pre-specified rich basis. A collective estimation approach pools information and borrows strength across the SDFs to achieve better estimation efficiency. Also, each estimated spectral density has a concise representation using the coefficients of the basis expansion, and these coefficients can be used for visualization, clustering, and classification purposes. The Whittle pseudo-maximum likelihood approach is used to fit the model and an alternating blockwise Newton-type algorithm is developed for the computation. A web-based shiny App found at

Site Features

Data.gov (United States)

U.S. Environmental Protection Agency — This dataset consists of various site features from multiple Superfund sites in U.S. EPA Region 8. These data were acquired from multiple sources at different times...

Archiving Spectral Libraries in the Planetary Data System

Science.gov (United States)

Slavney, S.; Guinness, E. A.; Scholes, D.; Zastrow, A.

2017-12-01

Spectral libraries are becoming popular candidates for archiving in PDS. With the increase in the number of individual investigators funded by programs such as NASA's PDART, the PDS Geosciences Node is receiving many requests for support from proposers wishing to archive various forms of laboratory spectra. To accommodate the need for a standardized approach to archiving spectra, the Geosciences Node has designed the PDS Spectral Library Data Dictionary, which contains PDS4 classes and attributes specifically for labeling spectral data, including a classification scheme for samples. The Reflectance Experiment Laboratory (RELAB) at Brown University, which has long been a provider of spectroscopy equipment and services to the science community, has provided expert input into the design of the dictionary. Together the Geosciences Node and RELAB are preparing the whole of the RELAB Spectral Library, consisting of many thousands of spectra collected over the years, to be archived in PDS. An online interface for searching, displaying, and downloading selected spectra is planned, using the Spectral Library metadata recorded in the PDS labels. The data dictionary and online interface will be extended to include spectral libraries submitted by other data providers. The Spectral Library Data Dictionary is now available from PDS at https://pds.nasa.gov/pds4/schema/released/. It can be used in PDS4 labels for reflectance spectra as well as for Raman, XRF, XRD, LIBS, and other types of spectra. Ancillary data such as images, chemistry, and abundance data are also supported. To help generate PDS4-compliant labels for spectra, the Geosciences Node provides a label generation program called MakeLabels (http://pds-geosciences.wustl.edu/tools/makelabels.html) which creates labels from a template, and which can be used for any kind of PDS4 label. For information, contact the Geosciences Node at geosci@wunder.wustl.edu.

Visible/near-infrared spectral diversity from in situ observations of the Bagnold Dune Field sands in Gale Crater, Mars

Science.gov (United States)

Johnson, Jeffrey R.; Achilles, Cherie; Bell, James F.; Bender, Steve; Cloutis, Edward; Ehlmann, Bethany; Fraeman, Abigail; Gasnault, Olivier; Hamilton, Victoria E.; Le Mouélic, Stéphane; Maurice, Sylvestre; Pinet, Patrick; Thompson, Lucy; Wellington, Danika; Wiens, Roger C.

2017-12-01

As part of the Bagnold Dune campaign conducted by Mars Science Laboratory rover Curiosity, visible/near-infrared reflectance spectra of dune sands were acquired using Mast Camera (Mastcam) multispectral imaging (445-1013 nm) and Chemistry and Camera (ChemCam) passive point spectroscopy (400-840 nm). By comparing spectra from pristine and rover-disturbed ripple crests and troughs within the dune field, and through analysis of sieved grain size fractions, constraints on mineral segregation from grain sorting could be determined. In general, the dune areas exhibited low relative reflectance, a weak 530 nm absorption band, an absorption band near 620 nm, and a spectral downturn after 685 nm consistent with olivine-bearing sands. The finest grain size fractions occurred within ripple troughs and in the subsurface and typically exhibited the strongest 530 nm bands, highest relative reflectances, and weakest red/near-infrared ratios, consistent with a combination of crystalline and amorphous ferric materials. Coarser-grained samples were the darkest and bluest and exhibited weaker 530 nm bands, lower relative reflectances, and stronger downturns in the near-infrared, consistent with greater proportions of mafic minerals such as olivine and pyroxene. These grains were typically segregated along ripple crests and among the upper surfaces of grain flows in disturbed sands. Sieved dune sands exhibited progressive decreases in reflectance with increasing grain size, as observed in laboratory spectra of olivine size separates. The continuum of spectral features observed between the coarse- and fine-grained dune sands suggests that mafic grains, ferric materials, and air fall dust mix in variable proportions depending on aeolian activity and grain sorting.

The spectral theorem for quaternionic unbounded normal operators based on the S-spectrum

Energy Technology Data Exchange (ETDEWEB)

Alpay, Daniel, E-mail: dany@math.bgu.ac.il; Kimsey, David P., E-mail: dpkimsey@gmail.com [Department of Mathematics, Ben-Gurion University of the Negev, Beer-Sheva 84105 (Israel); Colombo, Fabrizio, E-mail: fabrizio.colombo@polimi.it [Politecnico di Milano, Dipartimento di Matematica, Via E. Bonardi, 9, 20133 Milano (Italy)

2016-02-15

In this paper we prove the spectral theorem for quaternionic unbounded normal operators using the notion of S-spectrum. The proof technique consists of first establishing a spectral theorem for quaternionic bounded normal operators and then using a transformation which maps a quaternionic unbounded normal operator to a quaternionic bounded normal operator. With this paper we complete the foundation of spectral analysis of quaternionic operators. The S-spectrum has been introduced to define the quaternionic functional calculus but it turns out to be the correct object also for the spectral theorem for quaternionic normal operators. The lack of a suitable notion of spectrum was a major obstruction to fully understand the spectral theorem for quaternionic normal operators. A prime motivation for studying the spectral theorem for quaternionic unbounded normal operators is given by the subclass of unbounded anti-self adjoint quaternionic operators which play a crucial role in the quaternionic quantum mechanics.

A spectral profile multiplexed FBG sensor network with application to strain measurement in a Kevlar woven fabric

Science.gov (United States)

Guo, Guodong; Hackney, Drew; Pankow, Mark; Peters, Kara

2017-04-01

A spectral profile division multiplexed fiber Bragg grating (FBG) sensor network is described in this paper. The unique spectral profile of each sensor in the network is identified as a distinct feature to be interrogated. Spectrum overlap is allowed under working conditions. Thus, a specific wavelength window does not need to be allocated to each sensor as in a wavelength division multiplexed (WDM) network. When the sensors are serially connected in the network, the spectrum output is expressed through a truncated series. To track the wavelength shift of each sensor, the identification problem is transformed to a nonlinear optimization problem, which is then solved by a modified dynamic multi-swarm particle swarm optimizer (DMS-PSO). To demonstrate the application of the developed network, a network consisting of four FBGs was integrated into a Kevlar woven fabric, which was under a quasi-static load imposed by an impactor head. Due to the substantial radial strain in the fabric, the spectrums of different FBGs were found to overlap during the loading process. With the developed interrogating method, the overlapped spectrum would be distinguished thus the wavelength shift of each sensor can be monitored.

A novel and compact spectral imaging system based on two curved prisms

Science.gov (United States)

Nie, Yunfeng; Bin, Xiangli; Zhou, Jinsong; Li, Yang

2013-09-01

As a novel detection approach which simultaneously acquires two-dimensional visual picture and one-dimensional spectral information, spectral imaging offers promising applications on biomedical imaging, conservation and identification of artworks, surveillance of food safety, and so forth. A novel moderate-resolution spectral imaging system consisting of merely two optical elements is illustrated in this paper. It can realize the function of a relay imaging system as well as a 10nm spectral resolution spectroscopy. Compared to conventional prismatic imaging spectrometers, this design is compact and concise with only two special curved prisms by utilizing two reflective surfaces. In contrast to spectral imagers based on diffractive grating, the usage of compound-prism possesses characteristics of higher energy utilization and wider free spectral range. The seidel aberration theory and dispersive principle of this special prism are analyzed at first. According to the results, the optical system of this design is simulated, and the performance evaluation including spot diagram, MTF and distortion, is presented. In the end, considering the difficulty and particularity of manufacture and alignment, an available method for fabrication and measurement is proposed.

Spectral Imaging by Upconversion

DEFF Research Database (Denmark)

Dam, Jeppe Seidelin; Pedersen, Christian; Tidemand-Lichtenberg, Peter

2011-01-01

We present a method to obtain spectrally resolved images using upconversion. By this method an image is spectrally shifted from one spectral region to another wavelength. Since the process is spectrally sensitive it allows for a tailored spectral response. We believe this will allow standard...... silicon based cameras designed for visible/near infrared radiation to be used for spectral images in the mid infrared. This can lead to much lower costs for such imaging devices, and a better performance....

Lesion characterization in spectral photon-counting tomosynthesis

Science.gov (United States)

Cederström, Björn; Fredenberg, Erik; Berggren, Karl; Erhard, Klaus; Danielsson, Mats; Wallis, Matthew

2017-03-01

It has previously been shown that 2D spectral mammography can be used to discriminate between (likely benign) cystic and (potentially malignant) solid lesions in order to reduce unnecessary recalls in mammography. One limitation of the technique is, however, that the composition of overlapping tissue needs to be interpolated from a region surrounding the lesion. The purpose of this investigation was to demonstrate that lesion characterization can be done with spectral tomosynthesis, and to investigate whether the 3D information available in tomosynthesis can reduce the uncertainty from the interpolation of surrounding tissue. A phantom experiment was designed to simulate a cyst and a tumor, where the tumor was overlaid with a structure that made it mimic a cyst. In 2D, the two targets appeared similar in composition, whereas spectral tomosynthesis revealed the exact compositional difference. However, the loss of discrimination signal due to spread from the plane of interest was of the same strength as the reduction of anatomical noise. Results from a preliminary investigation on clinical tomosynthesis images of solid lesions yielded results that were consistent with the phantom experiments, but were still to some extent inconclusive. We conclude that lesion characterization is feasible in spectral tomosynthesis, but more data, as well as refinement of the calibration and discrimination algorithms, are needed to draw final conclusions about the benefit compared to 2D.

Multitaper spectral analysis of atmospheric radar signals

Directory of Open Access Journals (Sweden)

V. K. Anandan

2004-11-01

Full Text Available Multitaper spectral analysis using sinusoidal taper has been carried out on the backscattered signals received from the troposphere and lower stratosphere by the Gadanki Mesosphere-Stratosphere-Troposphere (MST radar under various conditions of the signal-to-noise ratio. Comparison of study is made with sinusoidal taper of the order of three and single tapers of Hanning and rectangular tapers, to understand the relative merits of processing under the scheme. Power spectra plots show that echoes are better identified in the case of multitaper estimation, especially in the region of a weak signal-to-noise ratio. Further analysis is carried out to obtain three lower order moments from three estimation techniques. The results show that multitaper analysis gives a better signal-to-noise ratio or higher detectability. The spectral analysis through multitaper and single tapers is subjected to study of consistency in measurements. Results show that the multitaper estimate is better consistent in Doppler measurements compared to single taper estimates. Doppler width measurements with different approaches were studied and the results show that the estimation was better in the multitaper technique in terms of temporal resolution and estimation accuracy.

Boosted dark matter and its implications for the features in IceCube HESE data

Energy Technology Data Exchange (ETDEWEB)

Bhattacharya, Atri [Space sciences, Technologies and Astrophysics Research (STAR) Institute, Université de Liège, Bât. B5a, 4000 Liège (Belgium); Gandhi, Raj; Gupta, Aritra [Harish-Chandra Research Institute, Chhatnag Road, Jhunsi, Allahabad-211019 (India); Mukhopadhyay, Satyanarayan, E-mail: A.Bhattacharya@ulg.ac.be, E-mail: raj@hri.res.in, E-mail: aritra@hri.res.in, E-mail: satya@pitt.edu [PITT-PACC, Department of Physics and Astronomy, University of Pittsburgh, PA 15260 (United States)

2017-05-01

We study the implications of the premise that any new, relativistic, highly energetic neutral particle that interacts with quarks and gluons would create cascade-like events in the IceCube (IC) detector. Such events would be observationally indistinguishable from neutral current deep-inelastic (DIS) scattering events due to neutrinos. Consequently, one reason for deviations, breaks or excesses in the expected astrophysical power-law neutrino spectrum could be the flux of such a particle. Motivated by features in the recent 1347-day IceCube high energy starting event (HESE) data, we focus on particular boosted dark matter (χ) related realizations of this premise. Here, χ is assumed to be much lighter than, and the result of, the slow decay of a massive scalar (φ ) which constitutes a major fraction of the Universe's dark matter (DM) . We show that this hypothesis, coupled with a standard power-law astrophysical neutrino flux is capable of providing very good fits to the present data, along with a possible explanation of other features in the HESE sample. These features include a) the paucity of events beyond ∼ 2 PeV b) a spectral feature resembling a dip or a spectral change in the 400 TeV–1 PeV region and c) an excess in the 50−100 TeV region. We consider two different boosted DM scenarios, and determine the allowed mass ranges and couplings for four different types of mediators (scalar, pseudoscalar, vector and axial-vector) which could connect the standard and dark sectors.We consider constraints from gamma-ray observations and collider searches. We find that the gamma-ray observations provide the most restrictive constraints, disfavouring the 1σ allowed parameter space from IC fits, while still being consistent with the 3σ allowed region. We also test our proposal and its implications against the (statistically independent) sample of six year through-going muon track data recently released by IceCube.

Comparing Features for Classification of MEG Responses to Motor Imagery.

Directory of Open Access Journals (Sweden)

Hanna-Leena Halme

Full Text Available 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

Effectiveness of a consistently formulated diffusion-synthetic acceleration differencing approach

International Nuclear Information System (INIS)

Khalil, H.

1988-01-01

A consistently formulated differencing approach is applied to the diffusion-synthetic acceleration of discrete ordinates calculations based on various spatial differencing schemes. The diffusion ''coupling'' equations derived for each scheme are contrasted to conventional coupling relations and are shown to permit derivation of either point- or box-centered diffusion difference equations. The resulting difference equations are shown to be mathematically equivalent, in slab geometry, to equations derived by applying Larsen's four-step procedure to the S/sub 2/ equations. Fourier stability analysis of the acceleration method applied to slab model problems is used to demonstrate that, for any S/sub n/ differencing scheme (a) the upper bound on the spectral radius of the method occurs in the fine-mesh limit and equals that of the spatially continuous case (0.22466), and (b) the spectral radius decreases with increasing mesh size to an asymptotic value <0.13135. This model problem performance is somewhat superior to that of Larsen's approach, for which the spectral radius is bounded by 0.25 in the wide-mesh limit. Numerical results of multidimensional, heterogeneous, scattering-dominated problems are also presented to demonstrate the rapid convergence of accelerated discrete ordinates calculations using various spatial differencing schemes

A Method of Road Extraction from High-resolution Remote Sensing Images Based on Shape Features

Directory of Open Access Journals (Sweden)

LEI Xiaoqi

2016-02-01

Full Text Available Road extraction from high-resolution remote sensing image is an important and difficult task.Since remote sensing images include complicated information,the methods that extract roads by spectral,texture and linear features have certain limitations.Also,many methods need human-intervention to get the road seeds(semi-automatic extraction,which have the great human-dependence and low efficiency.The road-extraction method,which uses the image segmentation based on principle of local gray consistency and integration shape features,is proposed in this paper.Firstly,the image is segmented,and then the linear and curve roads are obtained by using several object shape features,so the method that just only extract linear roads are rectified.Secondly,the step of road extraction is carried out based on the region growth,the road seeds are automatic selected and the road network is extracted.Finally,the extracted roads are regulated by combining the edge information.In experiments,the images that including the better gray uniform of road and the worse illuminated of road surface were chosen,and the results prove that the method of this study is promising.

[Analysis of spectral features based on water content of desert vegetation].

Science.gov (United States)

Zhao, Zhao; Li, Xia; Yin, Ye-biao; Tang, Jin; Zhou, Sheng-bin

2010-09-01

By using HR-768 field-portable spectroradiometer made by the Spectra Vista Corporation (SVC) of America, the hyper-spectral data of nine types of desert plants were measured, and the water content of corresponding vegetation was determined by roasting in lab. The continuum of measured hyperspectral data was removed by using ENVI, and the relationship between the water content of vegetation and the reflectance spectrum was analyzed by using correlation coefficient method. The result shows that the correlation between the bands from 978 to 1030 nm and water content of vegetation is weak while it is better for the bands from 1133 to 1266 nm. The bands from 1374 to 1534 nm are the characteristic bands because of the correlation between them and water content is the best. By using cluster analysis and according to the water content, the vegetation could be marked off into three grades: high (>70%), medium (50%-70%) and low (<50%). The research reveals the relationship between water content of desert vegetation and hyperspectral data, and provides basis for the analysis of area in desert and the monitoring of desert vegetation by using remote sensing data.

Tissues segmentation based on multi spectral medical images

Science.gov (United States)

Li, Ya; Wang, Ying

2017-11-01

Each band image contains the most obvious tissue feature according to the optical characteristics of different tissues in different specific bands for multispectral medical images. In this paper, the tissues were segmented by their spectral information at each multispectral medical images. Four Local Binary Patter descriptors were constructed to extract blood vessels based on the gray difference between the blood vessels and their neighbors. The segmented tissue in each band image was merged to a clear image.

[Compressive-spectral analysis of EEG in patients with panic attacks in the context of different psychiatric diseases].

Science.gov (United States)

Tuter, N V; Gnezditskiĭ, V V

2008-01-01

Panic disorders (PD) which develop in the context of different psychiatric diseases (neurotic, personality disorder and schizotypal disorders) have their own clinical and neurophysiological features. The results of compressive-spectral analysis of EEG (CSA EEG) in patients with panic attack were different depending on the specifics of initial psychiatric status. EEG parameters in patients differed from those in controls. The common feature for all PD patients was the lower spectral density of theta-, alpha- and beta-bands as well as total spectral density without any alterations of region distribution. The decrease of electrical activity of activation systems was found in the groups with neurotic and schizotypal disorders and that of inhibition systems - in the group with schizotypal disorders. The EEG results did not suggest any depression of activation systems in patients with specific personality disorders. The data obtained with CSA EEG mirror the integrative brain activity which determinad of the appearance of PA as well as of nosology of psychiatre disease.

Changes of fluorescent spectral features after successive rare earth doping of gadolinium oxide powders

Energy Technology Data Exchange (ETDEWEB)

Kuznik, W. [Chemical Department, Silesian University of Technology, Gliwice (Poland); Institute of Physics, University of Tartu, Riia 142, Tartu 51014 (Estonia); Brik, M.G. [Institute of Physics, University of Tartu, Riia 142, Tartu 51014 (Estonia); Cieslik, I.; Majchrowski, A.; Jaroszewicz, L. [Institute of Applied Physics, Military University of Technology, Kaliskiego 2, 00-908 Warsaw (Poland); AlZayed, N.S. [Physics and Astronomy Dept., College of Science, P.O. Box 2455, King Saud University, Riyadh 11451 (Saudi Arabia); El-Naggar, A.M. [Physics and Astronomy Dept., College of Science, P.O. Box 2455, King Saud University, Riyadh 11451 (Saudi Arabia); Permanent address: Physics department, Faculty of Science, Ain Shams University, Abassia, Cairo 11566 (Egypt); Sildos, I.; Lange, S.; Kiisk, V. [Institute of Physics, University of Tartu, Riia 142, Tartu 51014 (Estonia); Kityk, I.V., E-mail: ikityk@el.pcz.czest.pl [Electrical Engineering Department, Czestochowa University of Technology, Armii Krajowej 17, Czestochowa (Poland); Physics and Astronomy Dept., College of Science, P.O. Box 2455, King Saud University, Riyadh 11451 (Saudi Arabia)

2012-01-15

Highlights: > Principally new phosphors based on rare earth moped Gd{sub 2}O{sub 3} are obtained. > The time-resolved fluorescent spectra show drastic changes with the doping. > Temperature measurements were done. - Abstract: We present a complex fluorescence study of a series of gadolinium oxide polycrystalline powders singly, doubly and triply doped with trivalent rare earth ions (Er{sup 3+}, Tb{sup 3+}, and Dy{sup 3+}), to explore a possibility of their use as materials for white light emitting diodes. The excitation and luminescence spectra along with the decay kinetics were measured in the temperature range from 6 to 300 K. The luminescence efficiency was studied within the visible spectral range, i.e. -400 nm to 750 nm under excitation by 355 nm third harmonic Nd:YAG laser pulses. Singly doped Er{sup 3+} sample gave stronger luminescence signals, but others showed significantly larger decay lifetimes. The successive rare earths doping leads to substantial changes of the spectral positions due to the up-conversion processes. In the singly (Er{sup 3+}) doped sample, following the time resolved spectrum and decay curves, there are two different types of emissions: at 660 nm and at shorter wavelengths (below 640 nm) the red emission's lifetime is ten times longer than at shorter wavelengths. The singly doped sample shows unclear temperature-dependence of luminescence with lifetime at 550 nm (the longest at 100 K, similarly at 6 K and 300 K) and achieved luminous efficacy 73.5 lm/W.

Spectral and temporal cues for perception of material and action categories in impacted sound sources

DEFF Research Database (Denmark)

Hjortkjær, Jens; McAdams, Stephen

2016-01-01

In two experiments, similarity ratings and categorization performance with recorded impact sounds representing three material categories (wood, metal, glass) being manipulated by three different categories of action (drop, strike, rattle) were examined. Previous research focusing on single impact...... correlated with the pattern of confusion in categorization judgments. Listeners tended to confuse materials with similar spectral centroids, and actions with similar temporal centroids and onset densities. To confirm the influence of these different features, spectral cues were removed by applying...

TU-A-12A-04: Quantitative Texture Features Calculated in Lung Tissue From CT Scans Demonstrate Consistency Between Two Databases From Different Institutions

International Nuclear Information System (INIS)

Cunliffe, A; Armato, S; Castillo, R; Pham, N; Guerrero, T; Al-Hallaq, H

2014-01-01

Purpose: To evaluate the consistency of computed tomography (CT) scan texture features, previously identified as stable in a healthy patient cohort, in esophageal cancer patient CT scans. Methods: 116 patients receiving radiation therapy (median dose: 50.4Gy) for esophageal cancer were retrospectively identified. For each patient, diagnostic-quality pre-therapy (0-183 days) and post-therapy (5-120 days) scans (mean voxel size: 0.8mm×0.8mm×2.5mm) and a treatment planning scan and associated dose map were collected. An average of 501 32x32-pixel ROIs were placed randomly in the lungs of each pre-therapy scan. ROI centers were mapped to corresponding locations in post-therapy and planning scans using the displacement vector field output by demons deformable registration. Only ROIs with mean dose <5Gy were analyzed, as these were expected to contain minimal post-treatment damage. 140 texture features were calculated in pre-therapy and post-therapy scan ROIs and compared using Bland-Altman analysis. For each feature, the mean feature value change and the distance spanned by the 95% limits of agreement were normalized to the mean feature value, yielding normalized range of agreement (nRoA) and normalized bias (nBias). Using Wilcoxon signed rank tests, nRoA and nBias were compared with values computed previously in 27 healthy patient scans (mean voxel size: 0.67mm×0.67mm×1mm) acquired at a different institution. Results: nRoA was significantly (p<0.001) larger in cancer patients than healthy patients. Differences in nBias were not significant (p=0.23). The 20 features identified previously as having nRoA<20% for healthy patients had the lowest nRoA values in the current database, with an average increase of 5.6%. Conclusion: Despite differences in CT scanner type, scan resolution, and patient health status, the same 20 features remained stable (i.e., low variability and bias) in the absence of disease changes for databases from two institutions. Identification of

Evolutionary Computing Methods for Spectral Retrieval

Science.gov (United States)

Terrile, Richard; Fink, Wolfgang; Huntsberger, Terrance; Lee, Seugwon; Tisdale, Edwin; VonAllmen, Paul; Tinetti, Geivanna

2009-01-01

A methodology for processing spectral images to retrieve information on underlying physical, chemical, and/or biological phenomena is based on evolutionary and related computational methods implemented in software. In a typical case, the solution (the information that one seeks to retrieve) consists of parameters of a mathematical model that represents one or more of the phenomena of interest. The methodology was developed for the initial purpose of retrieving the desired information from spectral image data acquired by remote-sensing instruments aimed at planets (including the Earth). Examples of information desired in such applications include trace gas concentrations, temperature profiles, surface types, day/night fractions, cloud/aerosol fractions, seasons, and viewing angles. The methodology is also potentially useful for retrieving information on chemical and/or biological hazards in terrestrial settings. In this methodology, one utilizes an iterative process that minimizes a fitness function indicative of the degree of dissimilarity between observed and synthetic spectral and angular data. The evolutionary computing methods that lie at the heart of this process yield a population of solutions (sets of the desired parameters) within an accuracy represented by a fitness-function value specified by the user. The evolutionary computing methods (ECM) used in this methodology are Genetic Algorithms and Simulated Annealing, both of which are well-established optimization techniques and have also been described in previous NASA Tech Briefs articles. These are embedded in a conceptual framework, represented in the architecture of the implementing software, that enables automatic retrieval of spectral and angular data and analysis of the retrieved solutions for uniqueness.

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

Science.gov (United States)

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

2013-08-01

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

Spectral properties of doped bilayer cuprates at finite temperatures

Indian Academy of Sciences (India)

teresting results. For the overdoped samples, these results show a splitting of electronic states near ... self-consistent perturbation approach is used to calculate the electronic spectral function for differ- ent values of hole .... Council for Scientific and Industrial Research (CSIR), Government of India, for financial support via ...

Alexnet Feature Extraction and Multi-Kernel Learning for Objectoriented Classification

Science.gov (United States)

Ding, L.; Li, H.; Hu, C.; Zhang, W.; Wang, S.

2018-04-01

In view of the fact that the deep convolutional neural network has stronger ability of feature learning and feature expression, an exploratory research is done on feature extraction and classification for high resolution remote sensing images. Taking the Google image with 0.3 meter spatial resolution in Ludian area of Yunnan Province as an example, the image segmentation object was taken as the basic unit, and the pre-trained AlexNet deep convolution neural network model was used for feature extraction. And the spectral features, AlexNet features and GLCM texture features are combined with multi-kernel learning and SVM classifier, finally the classification results were compared and analyzed. The results show that the deep convolution neural network can extract more accurate remote sensing image features, and significantly improve the overall accuracy of classification, and provide a reference value for earthquake disaster investigation and remote sensing disaster evaluation.

ALEXNET FEATURE EXTRACTION AND MULTI-KERNEL LEARNING FOR OBJECTORIENTED CLASSIFICATION

Directory of Open Access Journals (Sweden)

L. Ding

2018-04-01

Full Text Available In view of the fact that the deep convolutional neural network has stronger ability of feature learning and feature expression, an exploratory research is done on feature extraction and classification for high resolution remote sensing images. Taking the Google image with 0.3 meter spatial resolution in Ludian area of Yunnan Province as an example, the image segmentation object was taken as the basic unit, and the pre-trained AlexNet deep convolution neural network model was used for feature extraction. And the spectral features, AlexNet features and GLCM texture features are combined with multi-kernel learning and SVM classifier, finally the classification results were compared and analyzed. The results show that the deep convolution neural network can extract more accurate remote sensing image features, and significantly improve the overall accuracy of classification, and provide a reference value for earthquake disaster investigation and remote sensing disaster evaluation.

Examination of Spectral Transformations on Spectral Mixture Analysis

Science.gov (United States)

Deng, Y.; Wu, C.

2018-04-01

While many spectral transformation techniques have been applied on spectral mixture analysis (SMA), few study examined their necessity and applicability. This paper focused on exploring the difference between spectrally transformed schemes and untransformed scheme to find out which transformed scheme performed better in SMA. In particular, nine spectrally transformed schemes as well as untransformed scheme were examined in two study areas. Each transformed scheme was tested 100 times using different endmember classes' spectra under the endmember model of vegetation- high albedo impervious surface area-low albedo impervious surface area-soil (V-ISAh-ISAl-S). Performance of each scheme was assessed based on mean absolute error (MAE). Statistical analysis technique, Paired-Samples T test, was applied to test the significance of mean MAEs' difference between transformed and untransformed schemes. Results demonstrated that only NSMA could exceed the untransformed scheme in all study areas. Some transformed schemes showed unstable performance since they outperformed the untransformed scheme in one area but weakened the SMA result in another region.

High spectral resolution infrared observations of V1057 Cygni

International Nuclear Information System (INIS)

Hartmann, L.; Kenyon, S.J.

1987-01-01

High-resolution near-infrared spectra of V1057 Cygni obtained in 1986 with the KPNO 4-m Fourier transform spectrometer provide support for a previously proposed accretion disk model. The model predicts that the observed rotational broadening of spectral lines should be smaller in the infrared than in the optical. The present observations show that V1057 Cyg rotates more slowly at 2.3 microns than at 6000 A by an amount quantitatively consistent with the simple disk models. The absence of any radial velocity variations in either the infrared or optical spectral regions supports the suggestion that the accreted material arises from a remnant disk of protostellar material. 19 references

Simplification of gamma-ray spectral data by using Fourier transform

International Nuclear Information System (INIS)

Tominaga, Shoji; Nagata, Shojiro; Nayatani, Yoshinobu; Ueda, Isamu; Sasaki, Satoshi.

1977-01-01

A method is proposed to represent γ-ray response spectra by Fourier series for the purpose of compressing spectral data. The usefulness of the method was confirmed by applying it to a spectral library of a NaI detector. In the method, a response spectrum as a wave is described by superposition of sine (cosine) waves with low frequencies, whose coefficient parameters can be obtained by a Fast Fourier Transform program. The relation between the number of parameters and the fitting error is discussed, and as the result, it is shown that the number of parameters can be reduced to about a half. The merits and features are presented in practical application of the method to the analysis of γ-ray spectra. (auth.)

Use of fast Fourier transform in gamma-ray spectral analysis

International Nuclear Information System (INIS)

Tominaga, Shoji; Nayatani, Yoshinobu; Nagata, Shojiro; Sasaki, Takashi; Ueda, Isamu.

1978-01-01

In order to simplify the mass data processing in a response matrix method for γ-ray spectral analysis, a method using a Fast Fourier Transform has been devised. The validity of the method has been confirmed by computer simulation for spectra of a NaI detector. First, it is shown that spectral data can be represented by Fourier series with a reduced number of terms. Then the estimation of intensities of γ-ray components is performed by a matrix operation using the compressed data of an observation spectrum and standard spectra in Fourier coefficients. The identification of γ-ray energies is also easy. Several features of the method and a general problem to be solved in relation to a response matrix method are described. (author)

The Pale Orange Dot: Spectral Effects of a Hazy Early Earth

Science.gov (United States)

Arney, G. N.; Meadows, V. S.; Domagal-Goldman, S. D.; Claire, M.; Schwieterman, E.

2014-12-01

Increasing evidence suggests Archean Earth had a photochemical hydrocarbon haze similar to Titan's (Zerkle et al. 2012), with important climate implications (Pavlov et al. 2001, Trainer et al. 2006, Haqq-Misra et al. 2008, Domagal-Goldman et al. 2008, Wolf and Toon 2012). Observations also suggest hazy exoplanets are common (Sing et al. 2011, Kreidberg et al 2014), so hazy planet spectra will be relevant to future exoplanet spectral characterization missions. Here, we consider the implications of hydrocarbon aerosols on the spectrum of Archean Earth, examining the effect of a haze layer on the detectability of spectral features from putative biosignatures and the Rayleigh scattering slope. We also examine haze's impact on the spectral energy distribution at the planetary surface, which may be important to the co-evolution of life with its environment. Because the atmospheric pressure and haze particle composition of the Archean Earth are poorly constrained, we test the impact of atmospheric pressure and particle density on haze formation. Our study uses a modified version of the 1-D photochemical code developed originally by Kasting et al. (1979) to generate a fractal haze in the model Archean atmosphere. The 1-D line-by-line fully multiple scattering Spectral Mapping Atmospheric Radiative Transfer Model (SMART) (Meadows and Crisp 1996) is then used to generate synthetic spectra of early Earth with haze. We find (Fig 1) that haze scattering significantly depletes the radiation at short wavelengths, strongly affecting the spectral region of the Rayleigh slope, a broadband change in spectral shape detectable at low spectral resolution. At the surface, the spectral energy distribution is shifted towards longer wavelengths, which may be important to photosynthetic life. Thus, the haze may have significant effects on biology, which in turn produces the methane that leads to haze formation, creating feedback loops between biology and the planet.

Temporal Evolution of Ion Spectral Structures During a Geomagnetic Storm: Observations and Modeling

Science.gov (United States)

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

2018-01-01

Using the Van Allen Probes/Helium, Oxygen, Proton, and Electron mass spectrometer, we perform a case study of the temporal evolution of ion spectral structures observed in the energy range of 1 to 50 keV throughout the geomagnetic storm of 2 October 2013. The ion spectral features are observed near the inner edge of the plasma sheet and are signatures of fresh transport from the plasma sheet into the inner magnetosphere. We find that the characteristics of the ion structures are determined by the intensity of the convection electric field. Prior to the beginning of the storm, the plasma sheet inner edge exhibits narrow nose spectral structures that vary little in energy across L values. Ion access to the inner magnetosphere during these times is limited to the nose energy bands. As convection is enhanced and large amounts of plasma are injected from the plasma sheet during the main phase of the storm, ion access occurs at a wide energy range, as no nose structures are observed. As the magnetosphere recovers from the storm, single noses and then multiple noses are observed once again. We use a model of ion drift and losses due to charge exchange to simulate the ion spectra and gain insight into the main observed features.

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

Energy Technology Data Exchange (ETDEWEB)

Shetrone, M. [University of Texas at Austin, McDonald Observatory (United States); Bizyaev, D.; Chojnowski, D. [Apache Point Observatory and New Mexico State University, P.O. Box 59, Sunspot, NM, 88349-0059 (United States); Lawler, J. E. [Department of Physics, University of Wisconsin-Madison, 1150 University Avenue, Madison, WI 53706 (United States); Prieto, C. Allende; Zamora, O.; García-Hernández, D. A.; Souto, D. [Instituto de Astrofísica de Canarias, Calle Vía Lactea s/n, E-38205 La Laguna, Tenerife (Spain); Johnson, J. A. [Department of Astronomy, The Ohio State University, Columbus, OH 43210 (United States); Smith, V. V. [National Optical Astronomy Observatory, 950 North Cherry Avenue, Tucson, AZ 85719 (United States); Cunha, K. [Observatório Nacional, Rua General Jose Cristino, 77, 20921-400 São Cristóvão, Rio de Janeiro, RJ (Brazil); Holtzman, J. [Department of Astronomy, New Mexico State University, Las Cruces, NM 88003 (United States); Pérez, A. E. García; Sobeck, J.; Majewski, S. [Department of Astronomy, University of Virginia, P.O. Box 400325, Charlottesville, VA 22904-4325 (United States); Mészáros, Sz. [ELTE Gothard Astrophysical Observatory, H-9704 Szombathely, Szent Imre herceg st. 112 (Hungary); Koesterke, L. [The University of Texas at Austin, Texas Advanced Computing Center (United States); Zasowski, G. [Department of Physics and Astronomy, Johns Hopkins University, Baltimore, MD 21218 (United States)

2015-12-15

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

Twisted entire cyclic cohomology, J-L-O cocycles and equivariant spectral triples

International Nuclear Information System (INIS)

Goswami, D.

2002-07-01

We study the 'quantized calculus' corresponding to the algebraic ideas related to 'twisted cyclic cohomology'. With very similar definitions and techniques, we define and study 'twisted entire cyclic cohomology' and the 'twisted Chern character' associated with an appropriate operator theoretic data called 'twisted spectral data', which consists of a spectral triple in the conventional sense of noncommutative geometry and an additional positive operator having some specified properties. Furthermore, it is shown that given a spectral triple (in the conventional sense) which is equivariant under the action of a compact matrix pseudogroup, it is possible to obtain a canonical twisted spectral data and hence the corresponding (twisted) Chern character, which will be invariant under the action of the pseudogroup, in contrast to the fact that the Chern character coming from the conventional noncommutative geometry need not be invariant under the above action. (author)

Trojan Asteroids: Spectral Groups, Volatiles, and Rotational Variation

Science.gov (United States)

Emery, J. P.; Takir, D.; Stamper, N. G.; Lucas, M. P.

2017-12-01

Trojan asteroids comprise a substantial population of primitive bodies confined to Jupiter's stable Lagrange regions. ecause they likely became trapped in these orbits at the end of the initial phase of planetary formation and subsequent migration, the compositions of Trojans provide unique perspectives on chemical and dynamical processes that shaped the Solar System. Ices and organics are of particular interest for understanding Trojan histories. Published near-infrared (0.7 to 4.0 mm) spectra of Trojans show no absorption bands due to H2O or organics. However, if the Trojan asteroids formed at or beyond their present heliocentric distance of 5.2 AU and never spent significant amounts of time closer to the Sun, they should contain H2O ice. Two VNIR spectral groups exist within the Trojans: 2/3 of large Trojans form a cluster with very red (D-type-like) spectral slopes, while the other 1/3 cluster around less-red (P-type-like) slopes. Visible colors of smaller Trojans suggest that the ratio of red to less-red Trojans decreases with decreasing size, from which Wong and Brown (2015; AJ 150:174) suggest that the interiors of all Trojans are represented by the less-red spectral group. In order to further test the hypothesis that Trojans contain H­2O ice and complex organics and to test the result from visible colors that the spectral group ratio changes with size, we have measured near-infrared (0.8 - 2.5 μm) spectra of small ( 35 to 75 km) Trojans from both swarms using the SpeX spectrograph at the NASA Infrared Telescope Facility (IRTF). We have also measured 2 - 4 μm spectra of several Trojans to search for spectral signatures of H2O and organics. We confirm that the two spectral groups persist to smaller sizes, and we still detect no absorption features that would be diagnostic of composition. The spectrum of two large Trojans show evidence of spectral slope variations with rotation, but spectra of several others do not. We will present the new spectra and

USGS Spectral Library Version 7

Science.gov (United States)

Kokaly, Raymond F.; Clark, Roger N.; Swayze, Gregg A.; Livo, K. Eric; Hoefen, Todd M.; Pearson, Neil C.; Wise, Richard A.; Benzel, William M.; Lowers, Heather A.; Driscoll, Rhonda L.; Klein, Anna J.

2017-04-10

We have assembled a library of spectra measured with laboratory, field, and airborne spectrometers. The instruments used cover wavelengths from the ultraviolet to the far infrared (0.2 to 200 microns [μm]). Laboratory samples of specific minerals, plants, chemical compounds, and manmade materials were measured. In many cases, samples were purified, so that unique spectral features of a material can be related to its chemical structure. These spectro-chemical links are important for interpreting remotely sensed data collected in the field or from an aircraft or spacecraft. This library also contains physically constructed as well as mathematically computed mixtures. Four different spectrometer types were used to measure spectra in the library: (1) Beckman™ 5270 covering the spectral range 0.2 to 3 µm, (2) standard, high resolution (hi-res), and high-resolution Next Generation (hi-resNG) models of Analytical Spectral Devices (ASD) field portable spectrometers covering the range from 0.35 to 2.5 µm, (3) Nicolet™ Fourier Transform Infra-Red (FTIR) interferometer spectrometers covering the range from about 1.12 to 216 µm, and (4) the NASA Airborne Visible/Infra-Red Imaging Spectrometer AVIRIS, covering the range 0.37 to 2.5 µm. Measurements of rocks, soils, and natural mixtures of minerals were made in laboratory and field settings. Spectra of plant components and vegetation plots, comprising many plant types and species with varying backgrounds, are also in this library. Measurements by airborne spectrometers are included for forested vegetation plots, in which the trees are too tall for measurement by a field spectrometer. This report describes the instruments used, the organization of materials into chapters, metadata descriptions of spectra and samples, and possible artifacts in the spectral measurements. To facilitate greater application of the spectra, the library has also been convolved to selected spectrometer and imaging spectrometers sampling and

Leds used as spectral selective light detectors in remote sensing techniques

International Nuclear Information System (INIS)

Weber, C; Tocho, J O; Rodriguez, E J; Acciaresi, H A

2011-01-01

Remote sensing has been commonly considered as an effective technique in developing precision agriculture tools. Ground based and satellite spectral sensors have wide uses to retrieve remotely quantitative biophysical and biochemical characteristics of vegetation canopies as well as vegetation ground cover. Usually in-field remote sensing technologies use either a combination of interferential filters and photodiodes or different compact spectrometers to separate the spectral regions of interest. In this paper we present a new development of a sensor with LEDs used as spectrally selective photodetectors. Its performance was compared with a photodiode-filter sensor used in agronomic applications. Subsequent measurements of weed cover degree were performed and compared with other methodologies. Results show that the new LEDs based sensor has similar features that conventional ones to determining the weed soil cover degree; while LEDs based sensor has comparative advantages related its very low manufacturing cost and its robustness compatible with agricultural field applications.

Neutrino mass hierarchy and three-flavor spectral splits of supernova neutrinos

International Nuclear Information System (INIS)

Dasgupta, Basudeb; Mirizzi, Alessandro; Tomas, Ricard; Tamborra, Irene

2010-01-01

It was recently realized that three-flavor effects could peculiarly modify the development of spectral splits induced by collective oscillations, for supernova neutrinos emitted during the cooling phase of a protoneutron star. We systematically explore this case, explaining how the impact of these three-flavor effects depends on the ordering of the neutrino masses. In inverted mass hierarchy, the solar mass splitting gives rise to instabilities in regions of the (anti)neutrino energy spectra that were otherwise stable under the leading two-flavor evolution governed by the atmospheric mass splitting and by the 1-3 mixing angle. As a consequence, the high-energy spectral splits found in the electron (anti)neutrino spectra disappear, and are transferred to other flavors. Imperfect adiabaticity leads to smearing of spectral swap features. In normal mass hierarchy, the three-flavor and the two-flavor instabilities act in the same region of the neutrino energy spectrum, leading to only minor departures from the two-flavor treatment.

Group sparse multiview patch alignment framework with view consistency for image classification.

Science.gov (United States)

Gui, Jie; Tao, Dacheng; Sun, Zhenan; Luo, Yong; You, Xinge; Tang, Yuan Yan

2014-07-01

No single feature can satisfactorily characterize the semantic concepts of an image. Multiview learning aims to unify different kinds of features to produce a consensual and efficient representation. This paper redefines part optimization in the patch alignment framework (PAF) and develops a group sparse multiview patch alignment framework (GSM-PAF). The new part optimization considers not only the complementary properties of different views, but also view consistency. In particular, view consistency models the correlations between all possible combinations of any two kinds of view. In contrast to conventional dimensionality reduction algorithms that perform feature extraction and feature selection independently, GSM-PAF enjoys joint feature extraction and feature selection by exploiting l(2,1)-norm on the projection matrix to achieve row sparsity, which leads to the simultaneous selection of relevant features and learning transformation, and thus makes the algorithm more discriminative. Experiments on two real-world image data sets demonstrate the effectiveness of GSM-PAF for image classification.

Epileptic seizure prediction based on a bivariate spectral power methodology.

Science.gov (United States)

Bandarabadi, Mojtaba; Teixeira, Cesar A; Direito, Bruno; Dourado, Antonio

2012-01-01

The spectral power of 5 frequently considered frequency bands (Alpha, Beta, Gamma, Theta and Delta) for 6 EEG channels is computed and then all the possible pairwise combinations among the 30 features set, are used to create a 435 dimensional feature space. Two new feature selection methods are introduced to choose the best candidate features among those and to reduce the dimensionality of this feature space. The selected features are then fed to Support Vector Machines (SVMs) that classify the cerebral state in preictal and non-preictal classes. The outputs of the SVM are regularized using a method that accounts for the classification dynamics of the preictal class, also known as "Firing Power" method. The results obtained using our feature selection approaches are compared with the ones obtained using minimum Redundancy Maximum Relevance (mRMR) feature selection method. The results in a group of 12 patients of the EPILEPSIAE database, containing 46 seizures and 787 hours multichannel recording for out-of-sample data, indicate the efficiency of the bivariate approach as well as the two new feature selection methods. The best results presented sensitivity of 76.09% (35 of 46 seizures predicted) and a false prediction rate of 0.15(-1).

A Study of Various Feature Extraction Methods on a Motor Imagery Based Brain Computer Interface System

Directory of Open Access Journals (Sweden)

Seyed Navid Resalat

2016-01-01

Discussion: These features were selected for the designed real-time navigation. The corresponding results revealed the subject-specific nature of the MI-based BCI system however, the Power Spectral Density (PSD based &alpha-BP feature had the highest averaged accuracy.

A spectral radioluminescence study for dating and dosimetry

International Nuclear Information System (INIS)

Krbetschek, M.R.; Trautmann, T.

2000-01-01

The spectral distribution of radioluminescence (RL) and its dose dependence was investigated on various substances to get information about the applicability in dosimetry and dating. The list comprises archaeometallurgical slag components (quartz relicts, glassy fraction), bone, cooking salt, corals, egg shell, flint, mussel shell, natural gypsum, natural halite, quartz (sediments, vein quartz) and sugar. The different emission wave-bands and basic features of their RL-dose-characteristics are reported for 18 different samples. Furthermore results of some materials are discussed in more detail

Phase extracting algorithms analysis in the white-light spectral interferometry

Science.gov (United States)

Guo, Tong; Li, Bingtong; Li, Minghui; Chen, Jinping; Fu, Xing; Hu, Xiaotang

2018-01-01

As an optical testing method, white-light spectral interferometry has the characteristics of non-contact, high precision. The phase information can be obtained by analyzing the spectral interference signal of the tested sample, and then the absolute distance is calculated. Fourier transform method, temporal phase-shifting method, spatial phase-shifting method and envelope method can be used to extract the phase information of the spectral interference signal. In this paper, the performance of four methods to extract phase information is simulated and analyzed by using the ideal spectral interference signal. It turns out that temporal phase-shifting method has the performance of high precision, the results of Fourier transform method and envelop method are distorted at the edge of the signal, and spatial phase-shifting method has the worst precision. Adding different levels of white noise to the ideal signal, temporal phase-shifting method is most accurate, while Fourier transform method and envelope method are relatively poor. Finally, the absolute distance measurement experiment is carried out on the constructed test system, and the results are consistent with the simulation ones.

Spectral boundary conditions and solitonic solutions in a classical Sellmeier dielectric

Energy Technology Data Exchange (ETDEWEB)

Belgiorno, F. [Politecnico di Milano, Dipartimento di Matematica, Milan (Italy); INdAM-GNFM, Rome (Italy); INFN, Milan (Italy); Cacciatori, S.L. [Universita dell' Insubria, Department of Science and High Technology, Como (Italy); INFN, Milan (Italy); Vigano, A. [Universita degli Studi di Milano, Dipartimento di Fisica, Milan (Italy)

2017-06-15

Electromagnetic field interactions in a dielectric medium represent a longstanding field of investigation, both at the classical level and at the quantum one. We propose a 1+1 dimensional toy-model which consists of an half-line filling dielectric medium, with the aim to set up a simplified situation where technicalities related to gauge invariance and, as a consequence, physics of constrained systems are avoided, and still interesting features appear. In particular, we simulate the electromagnetic field and the polarization field by means of two coupled scalar fields φ, ψ, respectively, in a Hopfield-like model. We find that, in order to obtain a physically meaningful behavior for the model, one has to introduce spectral boundary conditions depending on the particle spectrum one is dealing with. This is the first interesting achievement of our analysis. The second relevant achievement is that, by introducing a nonlinear contribution in the polarization field ψ, with the aim of mimicking a third order nonlinearity in a nonlinear dielectric, we obtain solitonic solutions in the Hopfield model framework, whose classical behavior is analyzed too. (orig.)

Comparison of perceptual properties of auditory streaming between spectral and amplitude modulation domains.

Science.gov (United States)

Yamagishi, Shimpei; Otsuka, Sho; Furukawa, Shigeto; Kashino, Makio

2017-07-01

The two-tone sequence (ABA_), which comprises two different sounds (A and B) and a silent gap, has been used to investigate how the auditory system organizes sequential sounds depending on various stimulus conditions or brain states. Auditory streaming can be evoked by differences not only in the tone frequency ("spectral cue": ΔF TONE , TONE condition) but also in the amplitude modulation rate ("AM cue": ΔF AM , AM condition). The aim of the present study was to explore the relationship between the perceptual properties of auditory streaming for the TONE and AM conditions. A sequence with a long duration (400 repetitions of ABA_) was used to examine the property of the bistability of streaming. The ratio of feature differences that evoked an equivalent probability of the segregated percept was close to the ratio of the Q-values of the auditory and modulation filters, consistent with a "channeling theory" of auditory streaming. On the other hand, for values of ΔF AM and ΔF TONE evoking equal probabilities of the segregated percept, the number of perceptual switches was larger for the TONE condition than for the AM condition, indicating that the mechanism(s) that determine the bistability of auditory streaming are different between or sensitive to the two domains. Nevertheless, the number of switches for individual listeners was positively correlated between the spectral and AM domains. The results suggest a possibility that the neural substrates for spectral and AM processes share a common switching mechanism but differ in location and/or in the properties of neural activity or the strength of internal noise at each level. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Relationship between channel interaction and spectral-ripple discrimination in cochlear implant users.

Science.gov (United States)

Jones, Gary L; Won, Jong Ho; Drennan, Ward R; Rubinstein, Jay T

2013-01-01

Cochlear implant (CI) users can achieve remarkable speech understanding, but there is great variability in outcomes that is only partially accounted for by age, residual hearing, and duration of deafness. Results might be improved with the use of psychophysical tests to predict which sound processing strategies offer the best potential outcomes. In particular, the spectral-ripple discrimination test offers a time-efficient, nonlinguistic measure that is correlated with perception of both speech and music by CI users. Features that make this "one-point" test time-efficient, and thus potentially clinically useful, are also connected to controversy within the CI field about what the test measures. The current work examined the relationship between thresholds in the one-point spectral-ripple test, in which stimuli are presented acoustically, and interaction indices measured under the controlled conditions afforded by direct stimulation with a research processor. Results of these studies include the following: (1) within individual subjects there were large variations in the interaction index along the electrode array, (2) interaction indices generally decreased with increasing electrode separation, and (3) spectral-ripple discrimination improved with decreasing mean interaction index at electrode separations of one, three, and five electrodes. These results indicate that spectral-ripple discrimination thresholds can provide a useful metric of the spectral resolution of CI users.

Accurate powder patterns and new spectral shape in orthorrombic symmetry

International Nuclear Information System (INIS)

Gonzalez-Tovany, L.

1991-01-01

The shape of the powder pattern of the center resonance line (M= 1/2 ↔ -1/2) for electron paramagnetic resonance (EPR) in orthorhombic symmetry, or nuclear magnetic resonance (NMR) with quadrupole interaction, is determined for all values of the crystal field symmetry parameter N by means of a general analytical method developed by Beltran-Lopez and Castro-Tello. Analytical functions in terms of elliptical integrals are obtained which are good approximations to the true powder pattern except in a narrow region around the field value corresponding to E=-2n 2 /3. numerical gaussian quadrature of the powder pattern from the single-variable integral arising in the analytical method is shown to be a very efficient semianalytical method of calculation for computer work, being much smoother and requiring only a few seconds of CPU time versus the several minutes needed with the grid of the Monte Carlo methods. The semianalytical powder patterns reveal the existence of a previous unknown EPR spectral feature in orthorhombic symmetry resembling a divergence. This feature which should appear at E=-2n 2 /3 for asymmetry parameter values near N=√ of 2/3, is hidden in the experimental spectra by the broadening effect of the linewidth of the individual crystallites. Comparison of experimental and simulated spectra obtained by convoluting powder patterns with first-derivate lorentzian lineshapes of convenient width are also shown. Semianalytical spectra are much smoother than Monte Carlo simulated spectra, revealing finer spectral features. (Author)

High-Speed Target Identification System Based on the Plume’s Spectral Distribution

Directory of Open Access Journals (Sweden)

Wenjie Lang

2015-01-01

Full Text Available In order to recognize the target of high speed quickly and accurately, an identification system was designed based on analysis of the distribution characteristics of the plume spectrum. In the system, the target was aligned with visible light tracking module, and the spectral analysis of the target’s plume radiation was achieved by interference module. The distinguishing factor recognition algorithm was designed on basis of ratio of multifeature band peaks and valley mean values. Effective recognition of the high speed moving target could be achieved after partition of the active region and the influence of target motion on spectral acquisition was analyzed. In the experiment the small rocket combustion was used as the target. The spectral detection experiment was conducted at different speeds 2.0 km away from the detection system. Experimental results showed that spectral distribution had significant spectral offset in the same sampling period for the target with different speeds, but the spectral distribution was basically consistent. Through calculation of the inclusion relationship between distinguishing factor and distinction interval of the peak value and the valley value at the corresponding wave-bands, effective identification of target could be achieved.

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

Science.gov (United States)

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.

Spectral autofluorescence imaging of the retina for drusen detection

Science.gov (United States)

Foubister, James J.; Gorman, Alistair; Harvey, Andy; Hemert, Jano van

2018-02-01

The presence and characteristics of drusen in retinal images, namely their size, location, and distribution, can be used to aid in the diagnosis and monitoring of Age Related Macular Degeneration (AMD); one of the leading causes for blindness in the elderly population. Current imaging techniques are effective at determining the presence and number of drusen, but fail when it comes to classifying their size and form. These distinctions are important for correctly characterising the disease, especially in the early stages where the development of just one larger drusen can indicate progression. Another challenge for automated detection is in distinguishing them from other retinal features, such as cotton wool spots. We describe the development of a multi-spectral scanning-laser ophthalmoscope that records images of retinal autofluorescence (AF) in four spectral bands. This will offer the potential to detect drusen with improved contrast based on spectral discrimination for automated classification. The resulting improved specificity and sensitivity for their detection offers more reliable characterisation of AMD. We present proof of principle images prior to further system optimisation and clinical trials for assessment of enhanced detection of drusen.

Explanation of the Knee-like Feature in the DAMPE Cosmic {e}^{-}+{e}^{+} Energy Spectrum

Science.gov (United States)

Fang, Kun; Bi, Xiao-Jun; Yin, Peng-Fei

2018-02-01

The DArk Matter Particle Explorer, a space-based high precision cosmic-ray detector, has just reported the new measurement of the total electron plus positron energy spectrum up to 4.6 TeV. A notable feature in the spectrum is the spectral break at ∼0.9 TeV, with the spectral index softening from ‑3.1 to ‑3.9. Such a feature is very similar to the knee at the cosmic nuclei energy spectrum. In this work, we propose that the knee-like feature can be explained naturally by assuming that the electrons are accelerated at the supernova remnants (SNRs) and released when the SNRs die out with lifetimes around 105 years. The cut-off energy of those electrons have already decreased to several TeV due to radiative cooling, which may induce the observed TeV spectral break. Another possibility is that the break is induced by a single nearby old SNR. Such a scenario may bring a large electron flux anisotropy that may be observable by the future detectors. We also show that a minor part of electrons escaping during the acceleration in young and nearby SNRs is able to contribute to a several TeV or higher energy region of the spectrum.

Analysis of a cryolava flow-like feature on Titan

Science.gov (United States)

Le, Corre L.; Le, Mouelic S.; Sotin, Christophe; Combe, J.-P.; Rodriguez, S.; Barnes, J.W.; Brown, R.H.; Buratti, B.J.; Jaumann, R.; Soderblom, J.; Soderblom, L.A.; Clark, R.; Baines, K.H.; Nicholson, P.D.

2009-01-01

This paper reports on the analysis of the highest spatial resolution hyperspectral images acquired by the Visual and Infrared Mapping Spectrometer (VIMS) onboard the Cassini spacecraft during its prime mission. A bright area matches a flow-like feature coming out of a caldera-like feature observed in Synthetic Aperture Radar (SAR) data recorded by the Cassini radar experiment [Lopes et al., 2007. Cryovolcanic features on Titan's surface as revealed by the Cassini Titan Radar Mapper. Icarus 186, 395-412, doi:10.1016/j.icarus.2006.09.006]. In this SAR image, the flow extends about 160 km east of the caldera. The contrast in brightness between the flow and the surroundings progressively vanishes, suggesting alteration or evolution of the composition of the cryolava during the lifetime of the eruptions. Dunes seem to cover part of this flow on its eastern end. We analyze the different terrains using the Spectral Mixing Analysis (SMA) approach of the Multiple-Endmember Linear Unmixing Model (MELSUM, Combe et al., 2008). The study area can be fully modeled by using only two types of terrains. Then, the VIMS spectra are compared with laboratory spectra of known materials in the relevant atmospheric windows (from 1 to 2.78 ??m). We considered simple molecules that could be produced during cryovolcanic events, including H2O, CO2 (using two different grain sizes), CH4 and NH3. We find that the mean spectrum of the cryoflow-like feature is not consistent with pure water ice. It can be best fitted by linear combinations of spectra of the candidate materials, showing that its composition is compatible with a mixture of H2O, CH4 and CO2.. ?? 2009 Elsevier Ltd.

Spectral stability of shifted states on star graphs

Science.gov (United States)

Kairzhan, Adilbek; Pelinovsky, Dmitry E.

2018-03-01

We consider the nonlinear Schrödinger (NLS) equation with the subcritical power nonlinearity on a star graph consisting of N edges and a single vertex under generalized Kirchhoff boundary conditions. The stationary NLS equation may admit a family of solitary waves parameterized by a translational parameter, which we call the shifted states. The two main examples include (i) the star graph with even N under the classical Kirchhoff boundary conditions and (ii) the star graph with one incoming edge and N  -  1 outgoing edges under a single constraint on coefficients of the generalized Kirchhoff boundary conditions. We obtain the general counting results on the Morse index of the shifted states and apply them to the two examples. In the case of (i), we prove that the shifted states with even N ≥slant 4 are saddle points of the action functional which are spectrally unstable under the NLS flow. In the case of (ii), we prove that the shifted states with the monotone profiles in the N  -  1 edges are spectrally stable, whereas the shifted states with non-monotone profiles in the N  -  1 edges are spectrally unstable, the two families intersect at the half-soliton states which are spectrally stable but nonlinearly unstable under the NLS flow. Since the NLS equation on a star graph with shifted states can be reduced to the homogeneous NLS equation on an infinite line, the spectral instability of shifted states is due to the perturbations breaking this reduction. We give a simple argument suggesting that the spectrally stable shifted states in the case of (ii) are nonlinearly unstable under the NLS flow due to the perturbations breaking the reduction to the homogeneous NLS equation.

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

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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

Spectral zeta function and non-perturbative effects in ABJM Fermi-gas

International Nuclear Information System (INIS)

Hatsuda, Yasuyuki

2015-03-01

The exact partition function in ABJM theory on three-sphere can be regarded as a canonical partition function of a non-interacting Fermi-gas with an unconventional Hamiltonian. All the information on the partition function is encoded in the discrete spectrum of this Hamiltonian. We explain how (quantum mechanical) non-perturbative corrections in the Fermi-gas system appear from a spectral consideration. Basic tools in our analysis are a Mellin-Barnes type integral representation and a spectral zeta function. From a consistency with known results, we conjecture that the spectral zeta function in the ABJM Fermi-gas has an infinite number of ''non-perturbative'' poles, which are invisible in the semi-classical expansion of the Planck constant. We observe that these poles indeed appear after summing up perturbative corrections. As a consequence, the perturbative resummation of the spectral zeta function causes non-perturbative corrections to the grand canonical partition function. We also present another example associated with a spectral problem in topological string theory. A conjectured non-perturbative free energy on the resolved conifold is successfully reproduced in this framework.

A spectral analysis of ablating meteors

Science.gov (United States)

Bloxam, K.; Campbell-Brown, M.

2017-09-01

Meteor ablation features in the spectral lines occurring at 394, 436, 520, and 589 nm were observed using a four-camera spectral system between September and December 2015. In conjunction with this multi-camera system the Canadian Automated Meteor Observatory was used to observe the orbital parameters and fragmentation of these meteors. In total, 95 light curves with complete data in the 520 and 589 nm filters were analyzed; some also had partial or complete data in the 394 nm filter, but no usable data was collected with the 436 nm filter. Of the 95 events, 70 exhibited some degree of differential ablation, and in all except 3 of these 70 events the 589 nm filter started or ended sooner compared with the 520 nm filter, indicating early ablation at the 589 nm wavelength. In the majority of cases the meteor showed evidence of fragmentation regardless of the type of ablation (differential or uniform). A surprising result was the lack of correlation found concerning the KB parameter, linked to meteoroid strength, and differential ablation. In addition, 22 shower-associated meteors were observed; Geminids showed mainly slight differential ablation, while Taurids were more likely to ablate uniformly.

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

Science.gov (United States)

Liu, Chao; Gu, Jinwei

2014-01-01

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

Classification of high resolution imagery based on fusion of multiscale texture features

International Nuclear Information System (INIS)

Liu, Jinxiu; Liu, Huiping; Lv, Ying; Xue, Xiaojuan

2014-01-01

In high resolution data classification process, combining texture features with spectral bands can effectively improve the classification accuracy. However, the window size which is difficult to choose is regarded as an important factor influencing overall classification accuracy in textural classification and current approaches to image texture analysis only depend on a single moving window which ignores different scale features of various land cover types. In this paper, we propose a new method based on the fusion of multiscale texture features to overcome these problems. The main steps in new method include the classification of fixed window size spectral/textural images from 3×3 to 15×15 and comparison of all the posterior possibility values for every pixel, as a result the biggest probability value is given to the pixel and the pixel belongs to a certain land cover type automatically. The proposed approach is tested on University of Pavia ROSIS data. The results indicate that the new method improve the classification accuracy compared to results of methods based on fixed window size textural classification

Providing Consistent (A)ATSR Solar Channel Radiometry for Climate Studies

Science.gov (United States)

Smith, D.; Latter, B. G.; Poulsen, C.

2012-04-01

Data from the solar reflectance channels of the Along Track Scanning Radiometer (ATSR) series of instruments are being used in applications for monitoring trends in clouds and aerosols. In order to provide quantitative information, the radiometric calibrations of the sensors must be consistent, stable and ideally traced to international standards. This paper describes the methods used to monitor the calibrations of the ATSR instruments to provide consistent Level 1b radiometric data sets. Comparisons of the in-orbit calibrations are made by reference to data from quasi stable sites such as DOME-C in Antarctica or Saharan Desert sites. Comparisons are performed either by time coincident match-ups of the radiometric data for sensors having similar spectral bands and view/solar geometry and overpass times as for AATSR and MERIS; or via a reference BRDF model derived from averages of measurements over the site from a reference sensor where there is limited or no temporal overlap (e.g. MODIS-Aqua, ATSR-1 and ATSR-2). The results of the intercomparisons provide values of the long term calibration drift and systematic biases between the sensors. Look-up tables based on smoothed averages of the drift measurements are used to provide the corrections to Level 1b data. The uncertainty budgets for the comparisons are provided. It is also possible to perform comparisons of measurements against high spectral resolution instruments that are co-located on the same platform, i.e. AATSR/SCIA on ENVISAT and ATSR-2/GOME on ERS-2. The comparisons are performed by averaging the spectrometer data to the spectral response of the filter radiometer, and averaging the radiometer data to the spatial resolution of the spectrometer. In this paper, the authors present the results of the inter-comparisons to achieve a consistent calibration for the solar channels of the complete ATSR dataset. An assessment of the uncertainties associated with the techniques will be discussed. The impacts of the

The spectral changes of deforestation in the Brazilian tropical savanna.

Science.gov (United States)

Trancoso, Ralph; Sano, Edson E; Meneses, Paulo R

2015-01-01

The Cerrado is a biome in Brazil that is experiencing the most rapid loss in natural vegetation. The objective of this study was to analyze the changes in the spectral response in the red, near infrared (NIR), middle infrared (MIR), and normalized difference vegetation index (NDVI) when native vegetation in the Cerrado is deforested. The test sites were regions of the Cerrado located in the states of Bahia, Minas Gerais, and Mato Grosso. For each region, a pair of Landsat Thematic Mapper (TM) scenes from 2008 (before deforestation) and 2009 (after deforestation) was compared. A set of 1,380 samples of deforested polygons and an equal number of samples of native vegetation have their spectral properties statistically analyzed. The accuracy of deforestation detections was also evaluated using high spatial resolution imagery. Results showed that the spectral data of deforested areas and their corresponding native vegetation were statistically different. The red band showed the highest difference between the reflectance data from deforested areas and native vegetation, while the NIR band showed the lowest difference. A consistent pattern of spectral change when native vegetation in the Cerrado is deforested was identified regardless of the location in the biome. The overall accuracy of deforestation detections was 97.75%. Considering both the marked pattern of spectral changes and the high deforestation detection accuracy, this study suggests that deforestation in Cerrado can be accurately monitored, but a strong seasonal and spatial variability of spectral changes might be expected.

Topological vertex, string amplitudes and spectral functions of hyperbolic geometry

Energy Technology Data Exchange (ETDEWEB)

Guimaraes, M.E.X.; Rosa, T.O. [Universidade Federal Fluminense, Instituto de Fisica, Av. Gal. Milton Tavares de Souza, s/n, CEP 24210-346, Niteroi, RJ (Brazil); Luna, R.M. [Universidade Estadual de Londrina, Departamento de Fisica, Caixa Postal 6001, Londrina, Parana (Brazil)

2014-05-15

We discuss the homological aspects of the connection between quantum string generating function and the formal power series associated to the dimensions of chains and homologies of suitable Lie algebras. Our analysis can be considered as a new straightforward application of the machinery of modular forms and spectral functions (with values in the congruence subgroup of SL(2,Z)) to the partition functions of Lagrangian branes, refined vertex and open string partition functions, represented by means of formal power series that encode Lie algebra properties. The common feature in our examples lies in the modular properties of the characters of certain representations of the pertinent affine Lie algebras and in the role of Selberg-type spectral functions of a hyperbolic three-geometry associated with q-series in the computation of the string amplitudes. (orig.)

Spectral image reconstruction using an edge preserving spatio-spectral Wiener estimation.

Science.gov (United States)

Urban, Philipp; Rosen, Mitchell R; Berns, Roy S

2009-08-01

Reconstruction of spectral images from camera responses is investigated using an edge preserving spatio-spectral Wiener estimation. A Wiener denoising filter and a spectral reconstruction Wiener filter are combined into a single spatio-spectral filter using local propagation of the noise covariance matrix. To preserve edges the local mean and covariance matrix of camera responses is estimated by bilateral weighting of neighboring pixels. We derive the edge-preserving spatio-spectral Wiener estimation by means of Bayesian inference and show that it fades into the standard Wiener reflectance estimation shifted by a constant reflectance in case of vanishing noise. Simulation experiments conducted on a six-channel camera system and on multispectral test images show the performance of the filter, especially for edge regions. A test implementation of the method is provided as a MATLAB script at the first author's website.

Integration of heterogeneous features for remote sensing scene classification

Science.gov (United States)

Wang, Xin; Xiong, Xingnan; Ning, Chen; Shi, Aiye; Lv, Guofang

2018-01-01

Scene classification is one of the most important issues in remote sensing (RS) image processing. We find that features from different channels (shape, spectral, texture, etc.), levels (low-level and middle-level), or perspectives (local and global) could provide various properties for RS images, and then propose a heterogeneous feature framework to extract and integrate heterogeneous features with different types for RS scene classification. The proposed method is composed of three modules (1) heterogeneous features extraction, where three heterogeneous feature types, called DS-SURF-LLC, mean-Std-LLC, and MS-CLBP, are calculated, (2) heterogeneous features fusion, where the multiple kernel learning (MKL) is utilized to integrate the heterogeneous features, and (3) an MKL support vector machine classifier for RS scene classification. The proposed method is extensively evaluated on three challenging benchmark datasets (a 6-class dataset, a 12-class dataset, and a 21-class dataset), and the experimental results show that the proposed method leads to good classification performance. It produces good informative features to describe the RS image scenes. Moreover, the integration of heterogeneous features outperforms some state-of-the-art features on RS scene classification tasks.

Research on Remote Sensing Image Classification Based on Feature Level Fusion

Science.gov (United States)

Yuan, L.; Zhu, G.

2018-04-01

Remote sensing image classification, as an important direction of remote sensing image processing and application, has been widely studied. However, in the process of existing classification algorithms, there still exists the phenomenon of misclassification and missing points, which leads to the final classification accuracy is not high. In this paper, we selected Sentinel-1A and Landsat8 OLI images as data sources, and propose a classification method based on feature level fusion. Compare three kind of feature level fusion algorithms (i.e., Gram-Schmidt spectral sharpening, Principal Component Analysis transform and Brovey transform), and then select the best fused image for the classification experimental. In the classification process, we choose four kinds of image classification algorithms (i.e. Minimum distance, Mahalanobis distance, Support Vector Machine and ISODATA) to do contrast experiment. We use overall classification precision and Kappa coefficient as the classification accuracy evaluation criteria, and the four classification results of fused image are analysed. The experimental results show that the fusion effect of Gram-Schmidt spectral sharpening is better than other methods. In four kinds of classification algorithms, the fused image has the best applicability to Support Vector Machine classification, the overall classification precision is 94.01 % and the Kappa coefficients is 0.91. The fused image with Sentinel-1A and Landsat8 OLI is not only have more spatial information and spectral texture characteristics, but also enhances the distinguishing features of the images. The proposed method is beneficial to improve the accuracy and stability of remote sensing image classification.

A comparison of EEG spectral entropy with conventional quantitative ...

African Journals Online (AJOL)

Adele

and decrease with increasing depth of anaesthesia. Spectral en- tropy yields two scales: Response Entropy (RE), ranging between. 0 to100, is an amalgam of EEG and frontal muscle activity while. State Entropy (SE), consisting mainly of EEG activity in a lower frequency band, ranges from 0 to 91.2 Initial reports have pro-.

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

Science.gov (United States)

Saluja, Ridhi; Garg, J. K.

2017-10-01

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

Automatic parquet block sorting using real-time spectral classification

Science.gov (United States)

Astrom, Anders; Astrand, Erik; Johansson, Magnus

1999-03-01

This paper presents a real-time spectral classification system based on the PGP spectrograph and a smart image sensor. The PGP is a spectrograph which extracts the spectral information from a scene and projects the information on an image sensor, which is a method often referred to as Imaging Spectroscopy. The classification is based on linear models and categorizes a number of pixels along a line. Previous systems adopting this method have used standard sensors, which often resulted in poor performance. The new system, however, is based on a patented near-sensor classification method, which exploits analogue features on the smart image sensor. The method reduces the enormous amount of data to be processed at an early stage, thus making true real-time spectral classification possible. The system has been evaluated on hardwood parquet boards showing very good results. The color defects considered in the experiments were blue stain, white sapwood, yellow decay and red decay. In addition to these four defect classes, a reference class was used to indicate correct surface color. The system calculates a statistical measure for each parquet block, giving the pixel defect percentage. The patented method makes it possible to run at very high speeds with a high spectral discrimination ability. Using a powerful illuminator, the system can run with a line frequency exceeding 2000 line/s. This opens up the possibility to maintain high production speed and still measure with good resolution.

Detection and quantification of flow consistency in business process models.

Science.gov (United States)

Burattin, Andrea; Bernstein, Vered; Neurauter, Manuel; Soffer, Pnina; Weber, Barbara

2018-01-01

Business process models abstract complex business processes by representing them as graphical models. Their layout, as determined by the modeler, may have an effect when these models are used. However, this effect is currently not fully understood. In order to systematically study this effect, a basic set of measurable key visual features is proposed, depicting the layout properties that are meaningful to the human user. The aim of this research is thus twofold: first, to empirically identify key visual features of business process models which are perceived as meaningful to the user and second, to show how such features can be quantified into computational metrics, which are applicable to business process models. We focus on one particular feature, consistency of flow direction, and show the challenges that arise when transforming it into a precise metric. We propose three different metrics addressing these challenges, each following a different view of flow consistency. We then report the results of an empirical evaluation, which indicates which metric is more effective in predicting the human perception of this feature. Moreover, two other automatic evaluations describing the performance and the computational capabilities of our metrics are reported as well.

Spectroscopy of the 3.3 ad 3.4 micron dust emission features

International Nuclear Information System (INIS)

Geballe, T.R.

1984-01-01

Various unidentified infrared features which have been observed in the interstellar grain medium are thought to be emitted or absorbed by molecules within dust grains. In order to correctly identify these molecules accurate high spectral resolution measurements of the features must be obtained. In order to obtain more accurate profiles, the 3.3 and 3.4 micron features have been observed in the planetary nebula NGC 7027 and in the HII region S106, during June and July 1983, using UKIRT and its 7-channel cooled grating spectrometer. (author)

Spectral Mixing in Nervous Systems: Experimental Evidenceand Biologically Plausible Circuits

Science.gov (United States)

Kleinfeld, D.; Mehta, S. B.

The ability to compute the difference frequency for two periodic signals depends on a nonlinear operation that mixes those signals. Behavioral and psychophysical evidence suggest that such mixing is likely to occur in the vertebrate nervous system as a means to compare rhythmic sensory signals, such as occurs in human audition, and as a means to lock an intrinsic rhythm to a sensory input. Electrophysiological data from electroreceptors in the immobilized electric fish and somatosensory cortex in the anesthetized rat yield direct evidence for such mixing, providing a neurological substrate for the modulation and demodulation of rhythmic neuronal signals. We consider an analytical model of spectral mixing that makes use of the threshold characteristics of neuronal firing and which has features consistent with the experimental observations. This model serves as a guide for constructing circuits that isolate given mixture components. In particular, such circuits can generate nearly pure difference tones from sinusoidal inputs without the use of band-pass filters, in analogy to an image-reject mixer in communications engineering. We speculate that such computations may play a role in coding of sensory input and feedback stabilization of motor output in nervous systems.

Optical spectral weight anomalies and strong correlation

International Nuclear Information System (INIS)

Toschi, A.; Capone, M.; Ortolani, M.; Calvani, P.; Lupi, S.; Castellani, C.

2007-01-01

The anomalous behavior observed in the optical spectral weight (W) of the cuprates provides valuable information about the physics of these compounds. Both the doping and the temperature dependences of W are hardly explained through conventional estimates based on the f-sum rule. By computing the optical conductivity of the doped Hubbard model with the Dynamical Mean Field Theory, we point out that the strong correlation plays a key role in determining the basic features of the observed anomalies: the proximity to a Mott insulating phase accounts simultaneously for the strong temperature dependence of W and for its zero temperature value

Spectral-spatial classification of hyperspectral image using three-dimensional convolution network