Sample records for identify spectral features

  1. Constraining Cometary Crystal Shapes from IR Spectral Features

    NASA Technical Reports Server (NTRS)

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

    2013-01-01

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

  2. Spectral-Spatial Scale Invariant Feature Transform for Hyperspectral Images.

    PubMed

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

    2018-02-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-11-01

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

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

    PubMed

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

    2018-01-01

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

  5. Spectral feature design in high dimensional multispectral data

    NASA Technical Reports Server (NTRS)

    Chen, Chih-Chien Thomas; Landgrebe, David A.

    1988-01-01

    The High resolution Imaging Spectrometer (HIRIS) is designed to acquire images simultaneously in 192 spectral bands in the 0.4 to 2.5 micrometers wavelength region. It will make possible the collection of essentially continuous reflectance spectra at a spectral resolution sufficient to extract significantly enhanced amounts of information from return signals as compared to existing systems. The advantages of such high dimensional data come at a cost of increased system and data complexity. For example, since the finer the spectral resolution, the higher the data rate, it becomes impractical to design the sensor to be operated continuously. It is essential to find new ways to preprocess the data which reduce the data rate while at the same time maintaining the information content of the high dimensional signal produced. Four spectral feature design techniques are developed from the Weighted Karhunen-Loeve Transforms: (1) non-overlapping band feature selection algorithm; (2) overlapping band feature selection algorithm; (3) Walsh function approach; and (4) infinite clipped optimal function approach. The infinite clipped optimal function approach is chosen since the features are easiest to find and their classification performance is the best. After the preprocessed data has been received at the ground station, canonical analysis is further used to find the best set of features under the criterion that maximal class separability is achieved. Both 100 dimensional vegetation data and 200 dimensional soil data were used to test the spectral feature design system. It was shown that the infinite clipped versions of the first 16 optimal features had excellent classification performance. The overall probability of correct classification is over 90 percent while providing for a reduced downlink data rate by a factor of 10.

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

    NASA Astrophysics Data System (ADS)

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

    2017-03-01

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

  7. Spectral feature measurements and analyses of the East Lake

    NASA Astrophysics Data System (ADS)

    Fang, Shenghui; Zhou, Yuan; Zhu, Wu

    2005-10-01

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

  8. Constraining Cometary Crystal Shapes from IR Spectral Features

    NASA Astrophysics Data System (ADS)

    Wooden, D. H.; Lindsay, S.; Harker, D. E.; Kelley, M. S.; Woodward, C. E.; Murphy, J. R.

    2013-12-01

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

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

    NASA Astrophysics Data System (ADS)

    Pan, Zhuokun; Huang, Jingfeng; Wang, Fumin

    2013-12-01

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

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

    PubMed

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

    2017-06-01

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

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

    PubMed

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

    1997-04-01

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

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

    PubMed

    Liu, Da; Li, Jianxun

    2016-12-16

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

  13. Spectral features of solar plasma flows

    NASA Astrophysics Data System (ADS)

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

    2014-11-01

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

  14. Spectral feature variations in x-ray diffraction imaging systems

    NASA Astrophysics Data System (ADS)

    Wolter, Scott D.; Greenberg, Joel A.

    2016-05-01

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

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

    PubMed Central

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

    2013-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-05-01

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

  17. Modeling photoacoustic spectral features of micron-sized particles

    NASA Astrophysics Data System (ADS)

    Strohm, Eric M.; Gorelikov, Ivan; Matsuura, Naomi; Kolios, Michael C.

    2014-10-01

    The photoacoustic signal generated from particles when irradiated by light is determined by attributes of the particle such as the size, speed of sound, morphology and the optical absorption coefficient. Unique features such as periodically varying minima and maxima are observed throughout the photoacoustic signal power spectrum, where the periodicity depends on these physical attributes. The frequency content of the photoacoustic signals can be used to obtain the physical attributes of unknown particles by comparison to analytical solutions of homogeneous symmetric geometric structures, such as spheres. However, analytical solutions do not exist for irregularly shaped particles, inhomogeneous particles or particles near structures. A finite element model (FEM) was used to simulate photoacoustic wave propagation from four different particle configurations: a homogeneous particle suspended in water, a homogeneous particle on a reflecting boundary, an inhomogeneous particle with an absorbing shell and non-absorbing core, and an irregularly shaped particle such as a red blood cell. Biocompatible perfluorocarbon droplets, 3-5 μm in diameter containing optically absorbing nanoparticles were used as the representative ideal particles, as they are spherical, homogeneous, optically translucent, and have known physical properties. The photoacoustic spectrum of micron-sized single droplets in suspension and on a reflecting boundary were measured over the frequency range of 100-500 MHz and compared directly to analytical models and the FEM. Good agreement between the analytical model, FEM and measured values were observed for a droplet in suspension, where the spectral minima agreed to within a 3.3 MHz standard deviation. For a droplet on a reflecting boundary, spectral features were correctly reproduced using the FEM but not the analytical model. The photoacoustic spectra from other common particle configurations such as particle with an absorbing shell and a

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

    NASA Technical Reports Server (NTRS)

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

    1973-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Yang, Jianping; Li, Jun

    2018-02-01

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

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

    NASA Technical Reports Server (NTRS)

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

    1990-01-01

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

  1. Modification of spectral features by nonhuman primates

    PubMed Central

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

    2017-01-01

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

  2. Spectral Archives: Extending Spectral Libraries to Analyze both Identified and Unidentified Spectra

    PubMed Central

    Frank, Ari M.; Monroe, Matthew E.; Shah, Anuj R.; Carver, Jeremy J.; Bandeira, Nuno F.; Moore, Ronald J.; Anderson, Gordon A.; Smith, Richard D.; Pevzner, Pavel A.

    2011-01-01

    MS/MS experiments generate multiple, nearly identical spectra of the same peptide in various laboratories, but proteomics researchers typically do not leverage the unidentified spectra produced in other labs to decode spectra generated in their own labs. We propose a spectral archives approach that clusters MS/MS datasets, representing similar spectra by a single consensus spectrum. Spectral archives extend spectral libraries by analyzing both identified and unidentified spectra in the same way and maintaining information about spectra of peptides shared across species and conditions. Thus archives offer both traditional library spectrum similarity-based search capabilities along with novel ways to analyze the data. By developing a clustering tool, MS-Cluster, we generated a spectral archive from ~1.18 billion spectra that greatly exceeds the size of existing spectral repositories. We advocate that publicly available data should be organized into spectral archives, rather than be analyzed as disparate datasets, as is mostly the case today. PMID:21572408

  3. Spectral EEG Features of a Short Psycho-physiological Relaxation

    NASA Astrophysics Data System (ADS)

    Teplan, Michal; Krakovská, Anna; Špajdel, Marián

    2014-08-01

    Short-lasting psycho-physiological relaxation was investigated through an analysis of its bipolar electroencephalographic (EEG) characteristics. In 8 subjects, 6-channel EEG data of 3-minute duration were recorded during 88 relaxation sessions. Time course of spectral EEG features was examined. Alpha powers were decreasing during resting conditions of 3-minute sessions in lying position with eyes closed. This was followed by a decrease of total power in centro-parietal cortex regions and an increase of beta power in fronto-central areas. Represented by EEG coherences the interhemispheric communication between the parieto-occipital regions was enhanced within a frequency range of 2-10 Hz. In order to discern between higher and lower levels of relaxation distinguished according to self-rated satisfaction, EEG features were assessed and discriminating parameters were identified. Successful relaxation was determined mainly by the presence of decreased delta-1 power across the cortex. Potential applications for these findings include the clinical, pharmacological, and stress management fields.

  4. Identifying significant environmental features using feature recognition.

    DOT National Transportation Integrated Search

    2015-10-01

    The Department of Environmental Analysis at the Kentucky Transportation Cabinet has expressed an interest in feature-recognition capability because it may help analysts identify environmentally sensitive features in the landscape, : including those r...

  5. Spectrally queued feature selection for robotic visual odometery

    NASA Astrophysics Data System (ADS)

    Pirozzo, David M.; Frederick, Philip A.; Hunt, Shawn; Theisen, Bernard; Del Rose, Mike

    2011-01-01

    Over the last two decades, research in Unmanned Vehicles (UV) has rapidly progressed and become more influenced by the field of biological sciences. Researchers have been investigating mechanical aspects of varying species to improve UV air and ground intrinsic mobility, they have been exploring the computational aspects of the brain for the development of pattern recognition and decision algorithms and they have been exploring perception capabilities of numerous animals and insects. This paper describes a 3 month exploratory applied research effort performed at the US ARMY Research, Development and Engineering Command's (RDECOM) Tank Automotive Research, Development and Engineering Center (TARDEC) in the area of biologically inspired spectrally augmented feature selection for robotic visual odometry. The motivation for this applied research was to develop a feasibility analysis on multi-spectrally queued feature selection, with improved temporal stability, for the purposes of visual odometry. The intended application is future semi-autonomous Unmanned Ground Vehicle (UGV) control as the richness of data sets required to enable human like behavior in these systems has yet to be defined.

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

    NASA Astrophysics Data System (ADS)

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

    2000-10-01

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

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

    PubMed

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

    2015-02-01

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

  8. Characterizing multivariate decoding models based on correlated EEG spectral features.

    PubMed

    McFarland, Dennis J

    2013-07-01

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

  9. Characterizing multivariate decoding models based on correlated EEG spectral features

    PubMed Central

    McFarland, Dennis J.

    2013-01-01

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

  10. Identifying Planetary Biosignature Impostors: Spectral Features of CO and O4 Resulting from Abiotic O2/O3 Production

    NASA Astrophysics Data System (ADS)

    Schwieterman, Edward W.; Meadows, Victoria S.; Domagal-Goldman, Shawn D.; Deming, Drake; Arney, Giada N.; Luger, Rodrigo; Harman, Chester E.; Misra, Amit; Barnes, Rory

    2016-03-01

    O2 and O3 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 O2/O3: CO and O4. 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 CO2 (1.6, 2.0, 4.3 μm) in the transmission spectrum of a terrestrial planet it could indicate robust CO2 photolysis and suggest that a future detection of O2 or O3 might not be biogenic. Strong O4 bands seen in transmission at 1.06 and 1.27 μm could be diagnostic of a post-runaway O2-dominated atmosphere from massive H-escape. We find that for these false positive scenarios, CO at 2.35 μm, CO2 at 2.0 and 4.3 μm, and O4 at 1.27 μm are all stronger features in transmission than O2/O3 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. O4 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.

  11. Identifying Planetary Biosignature Impostors: Spectral Features of CO and O4 Resulting from Abiotic O2/O3 Production

    NASA Technical Reports Server (NTRS)

    Schwieterman, Edward W.; Meadows, Victoria S.; Domagal-Goldman, Shawn D.; Deming, Drake; Arney, Giada N.; Luger, Rodrigo; Harman, Chester E.; Misra, Amit; Barnes, Rory

    2016-01-01

    O2 and O3 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 O2/O3: CO and O4. 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 (Near InfraRed Imager and Slitless Spectrograph) and/or NIRSpec (Near InfraRed Spectograph) observe CO (2.35, 4.6 micrometers) in conjunction with CO2 (1.6, 2.0, 4.3 micrometers) in the transmission spectrum of a terrestrial planet it could indicate robust CO2 photolysis and suggest that a future detection of O2 or O3 might not be biogenic. Strong O4 bands seen in transmission at 1.06 and 1.27 micrometers could be diagnostic of a post-runaway O2-dominated atmosphere from massive H-escape. We find that for these false positive scenarios, CO at 2.35 micrometers, CO2 at 2.0 and 4.3 micrometers, and O4 at 1.27 micrometers are all stronger features in transmission than O2/O3 and could be detected with sigal to noise ratios greater than or approximately 3 for an Earth-size planet orbiting a nearby M dwarf star with as few as 10 transits, assuming photon-limited noise. O4 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 micrometers) by a next generation direct imaging telescope such as LUVOIR (Large Ultraviolet Visible Infrared)/HDST (High-Definition Space Telescope) or HabEx (Habitable-Exoplanet Imaging Mission) and would indicate an oxygen atmosphere too massive to be biologically produced.

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

    NASA Astrophysics Data System (ADS)

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

    2014-08-01

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

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

    PubMed

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

    2014-08-14

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

  14. Unique Spectral Features Search In The 20 - 35 Micron Range of Mgs Tes Data

    NASA Astrophysics Data System (ADS)

    Altieri, F.; Bellucci, G.

    TES is the Thermal Emission Spectrometer aboard the NASA mission Mars Global Surveyor (MGS) orbiting around Mars since September 1997. It is collecting 6 - 50 micron thermal emission spectra and one of its principal purposes is to determine and map the Mars surface composition. Spectral features directly ascribable to sur- face minerals have been identified in the 20 - 35 micron spectral range: deposits of crystalline gray hematite have been localized in three regions, Sinus Meridiani, Aram Chaos and Valles Marineris [1, 2], and outcrops of olivines have been individuated in Nili Fossae [3]. The crystalline gray hematite areas have been interpreted to be formed by aqueous mineralization, indicating that liquid water was stable near the Mars sur- face for a long period of time in some limited regions. On the other hand there is no evidence in TES data for large scale occurrences (< 10 km) of moderate-grained (> 50 micron) carbonates exposed at the surface at a detection limit of 10 % [2]. Mars thermal emission spectra show, in general, significant variance between 20 and 35 mi- cron. This variance is not directly attributable to surface mineralogical components for the difficulty of discriminating the contribute of atmospheric components: CO2 and water vapour gas, dust and water ice aerosols. Moreover, the dust layer deposited on the soil has a spectral masking effect, obscuring superficial signature related to smaller mineral deposit and making difficult their identification. In this study we report some examples of single TES spectra with typical hematite and olivine bands and spectra with other unique features in the 20 - 35 micron range likely related to superficial components. For some of them we have analysed how the spectral features change in two different Mars seasons. These single TES pixels could be best investigated by instruments with an higher spatial resolution, as THEMIS and OMEGA. References: [1] Christensen P. R., et al., JGR, 105, 9623-9642, 2000

  15. Indirect searches of dark matter via polynomial spectral features

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

    Garcia-Cely, Camilo; Heeck, Julian

    2016-08-11

    We derive the spectra arising from non-relativistic dark matter annihilations or decays into intermediary particles with arbitrary spin, which subsequently produce neutrinos or photons via two-body decays. Our approach is model independent and predicts spectral features restricted to a kinematic box. The overall shape within that box is a polynomial determined by the polarization of the decaying particle. We illustrate our findings with two examples. First, with the neutrino spectra arising from dark matter annihilations into the massive Standard Model gauge bosons. Second, with the gamma-ray and neutrino spectra generated by dark matter annihilations into hypothetical massive spin-2 particles. Ourmore » results are in particular applicable to the 750 GeV diphoton excess observed at the LHC if interpreted as a spin-0 or spin-2 particle coupled to dark matter. We also derive limits on the dark matter annihilation cross section into this resonance from the non-observation of the associated gamma-ray spectral features by the H.E.S.S. telescope.« less

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

    PubMed

    Speier, William; Fried, Itzhak; Pouratian, Nader

    2013-07-01

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

  17. Camouflaged target detection based on polarized spectral features

    NASA Astrophysics Data System (ADS)

    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.

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

    NASA Astrophysics Data System (ADS)

    Zhao, Bei; Zhong, Yanfei; Zhang, Liangpei

    2016-06-01

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

  19. Identifying Potential Collapse Features Under Highways

    DOT National Transportation Integrated Search

    2003-01-01

    In 1994, subsidence features were identified on Interstate 70 in eastern Ohio. These : features were caused by collapse of old mine workings beneath the highway. An attempt : was made to delineate these features using geophysical methods with no avai...

  20. Identifying potential collapse features under highways.

    DOT National Transportation Integrated Search

    2003-03-01

    In 1994, subsidence features were identified on Interstate 70 in eastern Ohio. These features were caused by collapse of old mine workings beneath the highway. An attempt was made to delineate these features using geophysical methods with no avail. T...

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

    USGS Publications Warehouse

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

    2003-01-01

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

  2. Utilization of spectral-spatial characteristics in shortwave infrared hyperspectral images to classify and identify fungi-contaminated peanuts.

    PubMed

    Qiao, Xiaojun; Jiang, Jinbao; Qi, Xiaotong; Guo, Haiqiang; Yuan, Deshuai

    2017-04-01

    It's well-known fungi-contaminated peanuts contain potent carcinogen. Efficiently identifying and separating the contaminated can help prevent aflatoxin entering in food chain. In this study, shortwave infrared (SWIR) hyperspectral images for identifying the prepared contaminated kernels. Feature selection method of analysis of variance (ANOVA) and feature extraction method of nonparametric weighted feature extraction (NWFE) were used to concentrate spectral information into a subspace where contaminated and healthy peanuts can have favorable separability. Then, peanut pixels were classified using SVM. Moreover, image segmentation method of region growing was applied to segment the image as kernel-scale patches and meanwhile to number the kernels. The result shows that pixel-wise classification accuracies are 99.13% for breed A, 96.72% for B and 99.73% for C in learning images, and are 96.32%, 94.2% and 97.51% in validation images. Contaminated peanuts were correctly marked as aberrant kernels in both learning images and validation images. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

    NASA Technical Reports Server (NTRS)

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

    1974-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2017-11-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2018-04-01

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

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

    PubMed

    Liu, Xue-Hua; Wu, Yan

    2012-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-01-01

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

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

    USDA-ARS?s Scientific Manuscript database

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

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

    PubMed

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

    2012-04-01

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

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

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

    Schwieterman, Edward W.; Meadows, Victoria S.; Arney, Giada N.

    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 withmore » 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.« less

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

    PubMed

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

    2017-01-01

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

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

    PubMed Central

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

    2017-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Leviner, Marom; Maltz, Masha

    2009-03-01

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

  14. Towards limb position invariant myoelectric pattern recognition using time-dependent spectral features.

    PubMed

    Khushaba, Rami N; Takruri, Maen; Miro, Jaime Valls; Kodagoda, Sarath

    2014-07-01

    Recent studies in Electromyogram (EMG) pattern recognition reveal a gap between research findings and a viable clinical implementation of myoelectric control strategies. One of the important factors contributing to the limited performance of such controllers in practice is the variation in the limb position associated with normal use as it results in different EMG patterns for the same movements when carried out at different positions. However, the end goal of the myoelectric control scheme is to allow amputees to control their prosthetics in an intuitive and accurate manner regardless of the limb position at which the movement is initiated. In an attempt to reduce the impact of limb position on EMG pattern recognition, this paper proposes a new feature extraction method that extracts a set of power spectrum characteristics directly from the time-domain. The end goal is to form a set of features invariant to limb position. Specifically, the proposed method estimates the spectral moments, spectral sparsity, spectral flux, irregularity factor, and signals power spectrum correlation. This is achieved through using Fourier transform properties to form invariants to amplification, translation and signal scaling, providing an efficient and accurate representation of the underlying EMG activity. Additionally, due to the inherent temporal structure of the EMG signal, the proposed method is applied on the global segments of EMG data as well as the sliced segments using multiple overlapped windows. The performance of the proposed features is tested on EMG data collected from eleven subjects, while implementing eight classes of movements, each at five different limb positions. Practical results indicate that the proposed feature set can achieve significant reduction in classification error rates, in comparison to other methods, with ≈8% error on average across all subjects and limb positions. A real-time implementation and demonstration is also provided and made available

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

    NASA Astrophysics Data System (ADS)

    Shi, Yue; Huang, Wenjiang; Zhou, Xianfeng

    2017-04-01

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

  16. Spectral Regression Based Fault Feature Extraction for Bearing Accelerometer Sensor Signals

    PubMed Central

    Xia, Zhanguo; Xia, Shixiong; Wan, Ling; Cai, Shiyu

    2012-01-01

    Bearings are not only the most important element but also a common source of failures in rotary machinery. Bearing fault prognosis technology has been receiving more and more attention recently, in particular because it plays an increasingly important role in avoiding the occurrence of accidents. Therein, fault feature extraction (FFE) of bearing accelerometer sensor signals is essential to highlight representative features of bearing conditions for machinery fault diagnosis and prognosis. This paper proposes a spectral regression (SR)-based approach for fault feature extraction from original features including time, frequency and time-frequency domain features of bearing accelerometer sensor signals. SR is a novel regression framework for efficient regularized subspace learning and feature extraction technology, and it uses the least squares method to obtain the best projection direction, rather than computing the density matrix of features, so it also has the advantage in dimensionality reduction. The effectiveness of the SR-based method is validated experimentally by applying the acquired vibration signals data to bearings. The experimental results indicate that SR can reduce the computation cost and preserve more structure information about different bearing faults and severities, and it is demonstrated that the proposed feature extraction scheme has an advantage over other similar approaches. PMID:23202017

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

    NASA Technical Reports Server (NTRS)

    Blaney, D. L.; Crisp, D.

    1993-01-01

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

  18. Identifying Potential Collapse Features Under Highways : Executive Summary

    DOT National Transportation Integrated Search

    2003-03-01

    In 1994, subsidence features were identified on Interstate 70 in eastern Ohio. These : features were caused by collapse of old mine workings beneath the highway. An attempt : was made to delineate these features using geophysical methods with no avai...

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

    PubMed

    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.

  20. Efficient integration of spectral features for vehicle tracking utilizing an adaptive sensor

    NASA Astrophysics Data System (ADS)

    Uzkent, Burak; Hoffman, Matthew J.; Vodacek, Anthony

    2015-03-01

    Object tracking in urban environments is an important and challenging problem that is traditionally tackled using visible and near infrared wavelengths. By inserting extended data such as spectral features of the objects one can improve the reliability of the identification process. However, huge increase in data created by hyperspectral imaging is usually prohibitive. To overcome the complexity problem, we propose a persistent air-to-ground target tracking system inspired by a state-of-the-art, adaptive, multi-modal sensor. The adaptive sensor is capable of providing panchromatic images as well as the spectra of desired pixels. This addresses the data challenge of hyperspectral tracking by only recording spectral data as needed. Spectral likelihoods are integrated into a data association algorithm in a Bayesian fashion to minimize the likelihood of misidentification. A framework for controlling spectral data collection is developed by incorporating motion segmentation information and prior information from a Gaussian Sum filter (GSF) movement predictions from a multi-model forecasting set. An intersection mask of the surveillance area is extracted from OpenStreetMap source and incorporated into the tracking algorithm to perform online refinement of multiple model set. The proposed system is tested using challenging and realistic scenarios generated in an adverse environment.

  1. Individual Human Brain Areas Can Be Identified from Their Characteristic Spectral Activation Fingerprints

    PubMed Central

    Keitel, Anne; Gross, Joachim

    2016-01-01

    The human brain can be parcellated into diverse anatomical areas. We investigated whether rhythmic brain activity in these areas is characteristic and can be used for automatic classification. To this end, resting-state MEG data of 22 healthy adults was analysed. Power spectra of 1-s long data segments for atlas-defined brain areas were clustered into spectral profiles (“fingerprints”), using k-means and Gaussian mixture (GM) modelling. We demonstrate that individual areas can be identified from these spectral profiles with high accuracy. Our results suggest that each brain area engages in different spectral modes that are characteristic for individual areas. Clustering of brain areas according to similarity of spectral profiles reveals well-known brain networks. Furthermore, we demonstrate task-specific modulations of auditory spectral profiles during auditory processing. These findings have important implications for the classification of regional spectral activity and allow for novel approaches in neuroimaging and neurostimulation in health and disease. PMID:27355236

  2. Individual Human Brain Areas Can Be Identified from Their Characteristic Spectral Activation Fingerprints.

    PubMed

    Keitel, Anne; Gross, Joachim

    2016-06-01

    The human brain can be parcellated into diverse anatomical areas. We investigated whether rhythmic brain activity in these areas is characteristic and can be used for automatic classification. To this end, resting-state MEG data of 22 healthy adults was analysed. Power spectra of 1-s long data segments for atlas-defined brain areas were clustered into spectral profiles ("fingerprints"), using k-means and Gaussian mixture (GM) modelling. We demonstrate that individual areas can be identified from these spectral profiles with high accuracy. Our results suggest that each brain area engages in different spectral modes that are characteristic for individual areas. Clustering of brain areas according to similarity of spectral profiles reveals well-known brain networks. Furthermore, we demonstrate task-specific modulations of auditory spectral profiles during auditory processing. These findings have important implications for the classification of regional spectral activity and allow for novel approaches in neuroimaging and neurostimulation in health and disease.

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

    USDA-ARS?s Scientific Manuscript database

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

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

    NASA Astrophysics Data System (ADS)

    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.

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

    NASA Technical Reports Server (NTRS)

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

    2000-01-01

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

  6. Analysis of wheezes using wavelet higher order spectral features.

    PubMed

    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.

  7. Computerized macular pathology diagnosis in spectral domain optical coherence tomography scans based on multiscale texture and shape features.

    PubMed

    Liu, Yu-Ying; Ishikawa, Hiroshi; Chen, Mei; Wollstein, Gadi; Duker, Jay S; Fujimoto, James G; Schuman, Joel S; Rehg, James M

    2011-10-21

    To develop an automated method to identify the normal macula and three macular pathologies (macular hole [MH], macular edema [ME], and age-related macular degeneration [AMD]) from the fovea-centered cross sections in three-dimensional (3D) spectral-domain optical coherence tomography (SD-OCT) images. A sample of SD-OCT macular scans (macular cube 200 × 200 or 512 × 128 scan protocol; Cirrus HD-OCT; Carl Zeiss Meditec, Inc., Dublin, CA) was obtained from healthy subjects and subjects with MH, ME, and/or AMD (dataset for development: 326 scans from 136 subjects [193 eyes], and dataset for testing: 131 scans from 37 subjects [58 eyes]). A fovea-centered cross-sectional slice for each of the SD-OCT images was encoded using spatially distributed multiscale texture and shape features. Three ophthalmologists labeled each fovea-centered slice independently, and the majority opinion for each pathology was used as the ground truth. Machine learning algorithms were used to identify the discriminative features automatically. Two-class support vector machine classifiers were trained to identify the presence of normal macula and each of the three pathologies separately. The area under the receiver operating characteristic curve (AUC) was calculated to assess the performance. The cross-validation AUC result on the development dataset was 0.976, 0.931, 0939, and 0.938, and the AUC result on the holdout testing set was 0.978, 0.969, 0.941, and 0.975, for identifying normal macula, MH, ME, and AMD, respectively. The proposed automated data-driven method successfully identified various macular pathologies (all AUC > 0.94). This method may effectively identify the discriminative features without relying on a potentially error-prone segmentation module.

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

    NASA Astrophysics Data System (ADS)

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

    2017-10-01

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

  9. Spectral lags in different episodes of gamma-ray bursts

    NASA Astrophysics Data System (ADS)

    Jia, LanWei; Yi, TingFeng; Liang, EnWei

    2013-08-01

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

  10. Contamination of the 5394 Å spectral region by telluric lines

    NASA Astrophysics Data System (ADS)

    Vince, I.; Vince, O.

    2010-11-01

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

  11. Computerized Macular Pathology Diagnosis in Spectral Domain Optical Coherence Tomography Scans Based on Multiscale Texture and Shape Features

    PubMed Central

    Liu, Yu-Ying; Chen, Mei; Wollstein, Gadi; Duker, Jay S.; Fujimoto, James G.; Schuman, Joel S.; Rehg, James M.

    2011-01-01

    Purpose. To develop an automated method to identify the normal macula and three macular pathologies (macular hole [MH], macular edema [ME], and age-related macular degeneration [AMD]) from the fovea-centered cross sections in three-dimensional (3D) spectral-domain optical coherence tomography (SD-OCT) images. Methods. A sample of SD-OCT macular scans (macular cube 200 × 200 or 512 × 128 scan protocol; Cirrus HD-OCT; Carl Zeiss Meditec, Inc., Dublin, CA) was obtained from healthy subjects and subjects with MH, ME, and/or AMD (dataset for development: 326 scans from 136 subjects [193 eyes], and dataset for testing: 131 scans from 37 subjects [58 eyes]). A fovea-centered cross-sectional slice for each of the SD-OCT images was encoded using spatially distributed multiscale texture and shape features. Three ophthalmologists labeled each fovea-centered slice independently, and the majority opinion for each pathology was used as the ground truth. Machine learning algorithms were used to identify the discriminative features automatically. Two-class support vector machine classifiers were trained to identify the presence of normal macula and each of the three pathologies separately. The area under the receiver operating characteristic curve (AUC) was calculated to assess the performance. Results. The cross-validation AUC result on the development dataset was 0.976, 0.931, 0939, and 0.938, and the AUC result on the holdout testing set was 0.978, 0.969, 0.941, and 0.975, for identifying normal macula, MH, ME, and AMD, respectively. Conclusions. The proposed automated data-driven method successfully identified various macular pathologies (all AUC > 0.94). This method may effectively identify the discriminative features without relying on a potentially error-prone segmentation module. PMID:21911579

  12. The basal ganglia is necessary for learning spectral, but not temporal features of birdsong

    PubMed Central

    Ali, Farhan; Fantana, Antoniu L.; Burak, Yoram; Ölveczky, Bence P.

    2013-01-01

    Executing a motor skill requires the brain to control which muscles to activate at what times. How these aspects of control - motor implementation and timing - are acquired, and whether the learning processes underlying them differ, is not well understood. To address this we used a reinforcement learning paradigm to independently manipulate both spectral and temporal features of birdsong, a complex learned motor sequence, while recording and perturbing activity in underlying circuits. Our results uncovered a striking dissociation in how neural circuits underlie learning in the two domains. The basal ganglia was required for modifying spectral, but not temporal structure. This functional dissociation extended to the descending motor pathway, where recordings from a premotor cortex analogue nucleus reflected changes to temporal, but not spectral structure. Our results reveal a strategy in which the nervous system employs different and largely independent circuits to learn distinct aspects of a motor skill. PMID:24075977

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

    NASA Technical Reports Server (NTRS)

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

    1986-01-01

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

  14. Collective feature selection to identify crucial epistatic variants.

    PubMed

    Verma, Shefali S; Lucas, Anastasia; Zhang, Xinyuan; Veturi, Yogasudha; Dudek, Scott; Li, Binglan; Li, Ruowang; Urbanowicz, Ryan; Moore, Jason H; Kim, Dokyoon; Ritchie, Marylyn D

    2018-01-01

    Machine learning methods have gained popularity and practicality in identifying linear and non-linear effects of variants associated with complex disease/traits. Detection of epistatic interactions still remains a challenge due to the large number of features and relatively small sample size as input, thus leading to the so-called "short fat data" problem. The efficiency of machine learning methods can be increased by limiting the number of input features. Thus, it is very important to perform variable selection before searching for epistasis. Many methods have been evaluated and proposed to perform feature selection, but no single method works best in all scenarios. We demonstrate this by conducting two separate simulation analyses to evaluate the proposed collective feature selection approach. Through our simulation study we propose a collective feature selection approach to select features that are in the "union" of the best performing methods. We explored various parametric, non-parametric, and data mining approaches to perform feature selection. We choose our top performing methods to select the union of the resulting variables based on a user-defined percentage of variants selected from each method to take to downstream analysis. Our simulation analysis shows that non-parametric data mining approaches, such as MDR, may work best under one simulation criteria for the high effect size (penetrance) datasets, while non-parametric methods designed for feature selection, such as Ranger and Gradient boosting, work best under other simulation criteria. Thus, using a collective approach proves to be more beneficial for selecting variables with epistatic effects also in low effect size datasets and different genetic architectures. Following this, we applied our proposed collective feature selection approach to select the top 1% of variables to identify potential interacting variables associated with Body Mass Index (BMI) in ~ 44,000 samples obtained from Geisinger

  15. X-ray signatures: New time scales and spectral features

    NASA Technical Reports Server (NTRS)

    Boldt, E. A.

    1977-01-01

    The millisecond bursts from Cyg X-1 are investigated and the overall chaotic variability for the bulk of the Cyg X-1 emission is compared to that of Sco X-1, showing that the essential character is remarkably similar (i.e. shot noise) although the fundamental time scales involved differ widely, from a fraction of a second (for Cyg X-1) to a fraction of a day (for Sco X-1). Recent OSO-8 observations of spectra features attributable to iron are reviewed. In particular, line emission is discussed within the context of a model for thermal radiation by a hot evolved gas in systems as different as supernova remnants and clusters of galaxies. Newly observed spectral structure in the emission from the X-ray pulsar Her X-1 is reported.

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

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

    Arulanantham, Nicole A.; Herbst, William; Gilmore, Martha S.

    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 jetmore » 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.« less

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

    NASA Astrophysics Data System (ADS)

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

    2017-10-01

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

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

    ERIC Educational Resources Information Center

    De Lorenzi Pezzolo, Alessandra

    2013-01-01

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

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

    USDA-ARS?s Scientific Manuscript database

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

  20. Thermal Infrared Spectral Band Detection Limits for Unidentified Surface Materials

    NASA Technical Reports Server (NTRS)

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

    2001-01-01

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

  1. A Developed Spectral Identification Tree for Mineral Mapping using Hyperspectral Data

    NASA Astrophysics Data System (ADS)

    Gan, Fuping; Wang, Runsheng; Yan, Bokun; Shang, Kun

    2016-04-01

    The relationship between the spectral features and the composition of minerals are the basis of mineral identification using hyperspectral data. The reflectance spectrum of minerals results from the systematic combination of several modes of interaction between electromagnetic energy and mineral particles in the form of reflection and absorption. Minerals tend to have absorbing features at specific wavelengths with a characteristic shape, which can be used as diagnostic indicators for identification. The spectral identification tree (SIT) method for mineral identification is developed in our research to map minerals accurately and applied in some typical mineral deposits in China. The SIT method is based on the diagnostic absorption features of minerals through comparing and statistically analyzing characteristic spectral data of minerals. We establish several levels of identification rules for the type, group and species of minerals using IF-THEN rule according to the spectral identification criteria so that the developed SIT can be further used to map minerals at different levels of detail from mineral type to mineral species. Identifiable minerals can be grouped into six types: Fe2+-bearing, Fe3+-bearing, Mn2+-bearing, Al-OH-bearing, Mg-OH-bearing and carbonate minerals. Each type can be further divided into several mineral groups. Each group contains several mineral species or specific minerals. A mineral spectral series, therefore, can be constructed as "type-group-species-specific mineral (mineral variety)" for mineral spectral identification. It is noted that the mineral classification is based mainly on spectral reflectance characteristics of minerals which may not be consistent with the classification in mineralogy. We applied the developed SIT method to the datasets acquired at the Eastern Tianshan Mountains of Xinjiang (HyMap data) and the Qulong district of Xizang (Hyperion data). In Xinjiang, the two major classes of Al-OH and Mg-OH minerals were

  2. Spectral Domain RF Fingerprinting for 802.11 Wireless Devices

    DTIC Science & Technology

    2010-03-01

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

  3. EEG resolutions in detecting and decoding finger movements from spectral analysis

    PubMed Central

    Xiao, Ran; Ding, Lei

    2015-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Zoran, Maria; Savastru, Roxana; Savastru, Dan; Tautan, Marina; Miclos, Sorin; Cristescu, Luminita; Carstea, Elfrida; Baschir, Laurentiu

    2010-05-01

    Urban systems play a vital role in social and economic development in all countries. Their environmental changes can be investigated on different spatial and temporal scales. Urban and peri-urban environment dynamics is of great interest for future planning and decision making as well as in frame of local and regional changes. Changes in urban land cover include changes in biotic diversity, actual and potential primary productivity, soil quality, runoff, and sedimentation rates, and cannot be well understood without the knowledge of land use change that drives them. The study focuses on the assessment of environmental features changes for Bucharest metropolitan area, Romania by satellite remote sensing and in-situ monitoring data. Rational feature selection from the varieties of spectral channels in the optical wavelengths of electromagnetic spectrum (VIS and NIR) is very important for effective analysis and information extraction of remote sensing data. Based on comprehensively analyses of the spectral characteristics of remote sensing data is possibly to derive environmental changes in urban areas. The information quantity contained in a band is an important parameter in evaluating the band. The deviation and entropy are often used to show information amount. Feature selection is one of the most important steps in recognition and classification of remote sensing images. Therefore, it is necessary to select features before classification. The optimal features are those that can be used to distinguish objects easily and correctly. Three factors—the information quantity of bands, the correlation between bands and the spectral characteristic (e.g. absorption specialty) of classified objects in test area Bucharest have been considered in our study. As, the spectral characteristic of an object is influenced by many factors, being difficult to define optimal feature parameters to distinguish all the objects in a whole area, a method of multi-level feature selection

  5. [Analysis of software for identifying spectral line of laser-induced breakdown spectroscopy based on LabVIEW].

    PubMed

    Hu, Zhi-yu; Zhang, Lei; Ma, Wei-guang; Yan, Xiao-juan; Li, Zhi-xin; Zhang, Yong-zhi; Wang, Le; Dong, Lei; Yin, Wang-bao; Jia, Suo-tang

    2012-03-01

    Self-designed identifying software for LIBS spectral line was introduced. Being integrated with LabVIEW, the soft ware can smooth spectral lines and pick peaks. The second difference and threshold methods were employed. Characteristic spectrum of several elements matches the NIST database, and realizes automatic spectral line identification and qualitative analysis of the basic composition of sample. This software can analyze spectrum handily and rapidly. It will be a useful tool for LIBS.

  6. Raman Spectral Signatures as Conformational Probes of Biomolecules

    NASA Astrophysics Data System (ADS)

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

    2009-06-01

    A first application of ionization-loss stimulated Raman spectroscopy (ILSRS) for monitoring the spectral features of four conformers of a gas phase neurotransmitter (2-phenylethylamine) is reported. The Raman spectra of the conformers show bands that uniquely identify the conformational structure of the molecule and are well matched by density functional theory calculations. The measurement of spectral signatures by ILSRS in an extended spectral range, with a relatively convenient laser source, is extremely important, allowing enhanced accessibility to intra- and inter-molecular forces, which are significant in biological structure and activity.

  7. Raman Spectral Signatures as Conformational Probes of Biomolecules

    NASA Astrophysics Data System (ADS)

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

    2009-03-01

    A first application of ionization-loss stimulated Raman spectroscopy (ILSRS) monitoring the spectral features of four conformers of a gas phase neurotransmitter (2-phenylethylamine) is reported. The Raman spectra of the conformers show bands that uniquely identify the conformational structure of the molecule and are well matched by density functional theory calculations. The measurement of spectral signatures by ILSRS in an extended spectral range, with a relatively convenient laser source, is extremely important, allowing enhanced accessibility to intra- and inter-molecular forces, which are significant in biological structure and activity.

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

    PubMed

    Xu, Zhang-Hua; Liu, Jian; Yu, Kun-Yong; Gong, Cong-Hong; Xie, Wan-Jun; Tang, Meng-Ya; Lai, Ri-Wen; Li, Zeng-Lu

    2013-02-01

    Taking 51 field measured hyperspectral data with different pest levels in Yanping, Fujian Province as objects, the spectral reflectance and first derivative features of 4 levels of healthy, mild, moderate and severe insect pest were analyzed. On the basis of 7 detecting parameters construction, the pest level detecting models were built. The results showed that (1) the spectral reflectance of Pinus massoniana with pests were significantly lower than that of healthy state, and the higher the pest level, the lower the reflectance; (2) with the increase in pest level, the spectral reflectance curves' "green peak" and "red valley" of Pinus massoniana gradually disappeared, and the red edge was leveleds (3) the pest led to spectral "green peak" red shift, red edge position blue shift, but the changes in "red valley" and near-infrared position were complicated; (4) CARI, RES, REA and REDVI were highly relevant to pest levels, and the correlations between REP, RERVI, RENDVI and pest level were weak; (5) the multiple linear regression model with the variables of the 7 detection parameters could effectively detect the pest levels of Dendrolimus punctatus Walker, with both the estimation rate and accuracy above 0.85.

  9. A Comparison of Raman Spectral Features of Frozen and Deparaffinized Tissues in Neuroblastoma and Ganglioneuroma

    NASA Astrophysics Data System (ADS)

    Devpura, Suneetha; Thakur, Jagdish S.; Poulik, Janet M.; Rabah, Raja; Naik, Vaman M.; Naik, Ratna

    2012-02-01

    We have investigated the cellular regions in neuroblastoma and ganglioneuroma using Raman spectroscopy and compared their spectral characteristics with those of normal adrenal gland. Thin sections from both frozen and deparaffinized tissues, obtained from the same tissue specimen, were studied in conjunction with the pathological examination of the tissues. We found a significant difference in the spectral features of frozen sections of normal adrenal gland, neuroblastoma, and ganglioneuroma when compared to deparaffinized tissues. The quantitative analysis of the Raman data using chemometric methods of principal component analysis and discriminant function analysis obtained from the frozen tissues show a sensitivity and specificity of 100% each. The biochemical identification based on the spectral differences shows that the normal adrenal gland tissues have higher levels of carotenoids, lipids, and cholesterol compared to the neuroblastoma and ganglioneuroma frozen tissues. However, deparaffinized tissues show complete removal of these biochemicals in adrenal tissues. This study demonstrates that Raman spectroscopy combined with chemometric methods can successfully distinguish neuroblastoma and ganglioneuroma at cellular level.

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

    PubMed

    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.

  11. Identifying Planar Deformation Features Using EBSD and FIB

    NASA Astrophysics Data System (ADS)

    Pickersgill, A. E.; Lee, M. R.

    2015-09-01

    Planar deformation features in quartz grains from the Gow Lake impact structure have been successfully identified and indexed using electron backscatter diffraction in combination with focused ion beam milling.

  12. VNIR spectral features observed by the Mars Exploration Rover Opportunity in hematite-bearing materials at Meridiani Planum

    NASA Astrophysics Data System (ADS)

    Farrand, W. H.; Bell, J. F.; Morris, R. V.; Joliff, B. L.; Squyres, S. W.; Souza, P. A.

    2004-12-01

    The Mars Exploration Rover Opportunity was sent to Meridiani Planum based largely on MGS TES spectroscopic evidence of a large surface exposure of coarse grained gray hematite. The presence of hematite at Meridiani Planum has been confirmed through thermal infrared spectroscopy by the rover's Mini-TES instrument and by in-situ measurements by its Moessbauer (MB) spectrometer. Several types of hematite, as expressed by differences in MB spectral parameters, have been associated with various rocks and soils examined in Eagle crater and on the surrounding plains. The host materials include the small spherules (informally known as "blueberries") littering the floor of Eagle crater and the plains of Meridiani, the outcrop rock itself, specific types of soils, and two measurements on unique rocks in the Shoemaker's Patio area of Eagle crater. At the visible to near infrared (VNIR) wavelengths covered by the rover's multispectral Panoramic camera (Pancam), gray hematite is spectrally neutral. However, multispectral observations by Pancam of some of these hematite-bearing materials show discernable spectral features. Specifically, portions of the outcrop visible in the walls of Eagle crater display a strong 535 nm absorption feature. This feature resembles a similar feature in laboratory spectra of red hematite, but the characteristic 860 nm absorption of red hematite is either absent or is instead replaced by a longer wavelength absorption centered on Pancam's 900 nm channel. The blueberries display a deep and broad absorption centered on 900 nm and as well as an increase in reflectance in the 1009 nm band. The shape of the absorption feature in the blueberries is consistent with that seen in red hematite, but again the band minimum is displaced to a longer wavelength than would be expected for red hematite. The blueberries also lack the prominent absorption at the shortest wavelengths that would be expected of red hematite. The unique hematite-bearing (or coated) rocks

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

    NASA Astrophysics Data System (ADS)

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

    2012-11-01

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

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

    NASA Astrophysics Data System (ADS)

    Hamilton, V. E.; McDowell, M. L.; Berger, J. A.; Cady, S. L.; Knauth, L. P.

    2011-12-01

    We have collected visible to near infrared reflectance (VNIR, ~0.4 - 2.5 um), thermal infrared emissivity (TIR, ~5 - 45 um), SEM, XRD, surface roughness, and petrographic data for 18 silica samples. These rocks (e.g., replacement chert, geyserite, opal-A/-CT) represent a variety of geologic formation environments, including hydrothermal, and have XRD-determined crystallinities ranging from <1 to >10 according to the quartz crystallinity index. Our findings are relevant to the interpretation of orbital and in situ spectral observations of crystalline or amorphous silica on the Martian surface, some of which may have formed in hydrothermal systems. Almost all of our samples' VNIR spectra contain discernible bands. The most common features are related to hydration (H2O and/or OH) of silica (e.g., at ~1.4, 1.9, and 2.2 um). The visibility and strength of these bands is not always constant between spectra from different areas of a sample. Other features include those of carbonate, phyllosilicate, and iron oxide impurities. All of our amorphous silica samples have hydration features in the VNIR, but we note that the absorptions around ~2.2 um can be very weak in amorphous samples relative to features at other wavelengths and relative to ~2.2-um features observed in Martian data, suggesting that some amorphous silica on Mars could go undetected. Deposits containing significant anhydrous, crystalline silica (chert) may be assumed to lack features in the VNIR, but many of our cherts have spectral features and could be misidentified as materials dominated by what is a minor contaminant. Thermal infrared spectra of chert and opaline silica differ from each other as a result of the loss of long-range Si-O order in increasingly amorphous samples. Our samples display a clear trend in TIR band shapes where features attributable to crystalline quartz and amorphous silica are blended in samples with intermediate crystallinities. Most diagnostic TIR spectral features observable in

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

    NASA Astrophysics Data System (ADS)

    Houdashelt, M. L.

    1992-05-01

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

  16. Terahertz spectral unmixing based method for identifying gastric cancer

    NASA Astrophysics Data System (ADS)

    Cao, Yuqi; Huang, Pingjie; Li, Xian; Ge, Weiting; Hou, Dibo; Zhang, Guangxin

    2018-02-01

    At present, many researchers are exploring biological tissue inspection using terahertz time-domain spectroscopy (THz-TDS) techniques. In this study, based on a modified hard modeling factor analysis method, terahertz spectral unmixing was applied to investigate the relationships between the absorption spectra in THz-TDS and certain biomarkers of gastric cancer in order to systematically identify gastric cancer. A probability distribution and box plot were used to extract the distinctive peaks that indicate carcinogenesis, and the corresponding weight distributions were used to discriminate the tissue types. The results of this work indicate that terahertz techniques have the potential to detect different levels of cancer, including benign tumors and polyps.

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

    NASA Technical Reports Server (NTRS)

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

    1986-01-01

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

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

    ERIC Educational Resources Information Center

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

    1998-01-01

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

  19. USGS Digital Spectral Library splib06a

    USGS Publications Warehouse

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

    2007-01-01

    Introduction We have assembled a digital reflectance spectral library that covers the wavelength range from the ultraviolet to far infrared along with sample documentation. The library includes samples of minerals, rocks, soils, physically constructed as well as mathematically computed mixtures, plants, vegetation communities, microorganisms, and man-made materials. The samples and spectra collected were assembled for the purpose of using spectral features for the remote detection of these and similar materials. Analysis of spectroscopic data from laboratory, aircraft, and spacecraft instrumentation requires a knowledge base. The spectral library discussed here forms a knowledge base for the spectroscopy of minerals and related materials of importance to a variety of research programs being conducted at the U.S. Geological Survey. Much of this library grew out of the need for spectra to support imaging spectroscopy studies of the Earth and planets. Imaging spectrometers, such as the National Aeronautics and Space Administration (NASA) Airborne Visible/Infra Red Imaging Spectrometer (AVIRIS) or the NASA Cassini Visual and Infrared Mapping Spectrometer (VIMS) which is currently orbiting Saturn, have narrow bandwidths in many contiguous spectral channels that permit accurate definition of absorption features in spectra from a variety of materials. Identification of materials from such data requires a comprehensive spectral library of minerals, vegetation, man-made materials, and other subjects in the scene. Our research involves the use of the spectral library to identify the components in a spectrum of an unknown. Therefore, the quality of the library must be very good. However, the quality required in a spectral library to successfully perform an investigation depends on the scientific questions to be answered and the type of algorithms to be used. For example, to map a mineral using imaging spectroscopy and the mapping algorithm of Clark and others (1990a, 2003b

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

    PubMed

    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.

  1. Raman spectral signatures as conformational probes of gas phase flexible molecules

    NASA Astrophysics Data System (ADS)

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

    2009-07-01

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

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

    USGS Publications Warehouse

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

    2004-01-01

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

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

    USGS Publications Warehouse

    Ribeiro da Luz, Beatriz; Crowley, James K.

    2007-01-01

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

  4. Spectral quality requirements for effluent identification

    NASA Astrophysics Data System (ADS)

    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.

  5. Spectral features of biogenic calcium carbonates and implications for astrobiology

    NASA Astrophysics Data System (ADS)

    Berg, B. L.; Ronholm, J.; Applin, D. M.; Mann, P.; Izawa, M.; Cloutis, E. A.; Whyte, L. G.

    2014-09-01

    The ability to discriminate biogenic from abiogenic calcium carbonate (CaCO3) would be useful in the search for extant or extinct life, since CaCO3 can be produced by both biotic and abiotic processes on Earth. Bioprecipitated CaCO3 material was produced during the growth of heterotrophic microbial isolates on medium enriched with calcium acetate or calcium citrate. These biologically produced CaCO3, along with natural and synthetic non-biologically produced CaCO3 samples, were analysed by reflectance spectroscopy (0.35-2.5 μm), Raman spectroscopy (532 and 785 nm), and laser-induced fluorescence spectroscopy (365 and 405 nm excitation). Optimal instruments for the discrimination of biogenic from abiogenic CaCO3 were determined to be reflectance spectroscopy, and laser-induced fluorescence spectroscopy. Multiple absorption features in the visible light region occurred in reflectance spectra for most biogenic CaCO3 samples, which are likely due to organic pigments. Multiple fluorescence peaks occurred in emission spectra (405 nm excitation) of biogenic CaCO3 samples, which also are best attributed to the presence of organic compounds; however, further analyses must be performed in order to better determine the cause of these features to establish criteria for confirming the origin of a given CaCO3 sample. Raman spectroscopy was not useful for discrimination since any potential Raman peaks in spectra of biogenic carbonates collected by both the 532 and 785 nm lasers were overwhelmed by fluorescence. However, this also suggests that biogenic carbonates may be identified by the presence of this organic-associated fluorescence. No reliable spectroscopic differences in terms of parameters such as positions or widths of carbonate-associated absorption bands were found between the biogenic and abiogenic carbonate samples. These results indicate that the presence or absence of organic matter intimately associated with carbonate minerals is the only potentially useful

  6. Study on identifying deciduous forest by the method of feature space transformation

    NASA Astrophysics Data System (ADS)

    Zhang, Xuexia; Wu, Pengfei

    2009-10-01

    The thematic remotely sensed information extraction is always one of puzzling nuts which the remote sensing science faces, so many remote sensing scientists devotes diligently to this domain research. The methods of thematic information extraction include two kinds of the visual interpretation and the computer interpretation, the developing direction of which is intellectualization and comprehensive modularization. The paper tries to develop the intelligent extraction method of feature space transformation for the deciduous forest thematic information extraction in Changping district of Beijing city. The whole Chinese-Brazil resources satellite images received in 2005 are used to extract the deciduous forest coverage area by feature space transformation method and linear spectral decomposing method, and the result from remote sensing is similar to woodland resource census data by Chinese forestry bureau in 2004.

  7. Mineralogical and spectral analysis of Vesta's Gegania and Lucaria quadrangles and comparative analysis of their key features

    NASA Astrophysics Data System (ADS)

    Longobardo, Andrea; Palomba, Ernesto; De Sanctis, Maria Cristina; Zinzi, Angelo; Scully, Jennifer E. C.; Capaccioni, Fabrizio; Tosi, Federico; Zambon, Francesca; Ammannito, Eleonora; Combe, Jean-Philippe; Raymond, Carol A.; Russell, Cristopher T.

    2015-10-01

    This work is aimed at developing and interpreting infrared albedo, pyroxene and OH band depths, and pyroxene band center maps of Vesta's Gegania and Lucaria quadrangles, obtained from data provided by the Visible and InfraRed (VIR) mapper spectrometer on board NASA's Dawn spacecraft. The Gegania and Lucaria quadrangles span latitudes from 22°S to 22°N and longitudes from 0°E to 144°E. The mineralogical and spectral maps identify two large-scale units on this area of Vesta, which extend eastwards and westward of about 60°E, respectively. The two regions are not associated to large-scale geological units, which have a latitudinal distribution rather than longitudinal, but are defined by different contents of carbonaceous chondrites (CC): the eastern region, poor in CCs, is brighter and OH-depleted, whereas the western one, rich in CCs, is darker and OH-enriched. A detailed analysis of the small-scale units in these quadrangles is also performed. Almost all the units show the typical correspondence between high albedo, deep pyroxene bands, short band centers and absence of OH and vice versa. Only a few exceptions occur, such as the ejecta from the Aelia crater, where dark and bright materials are intimately mixed. The most characteristic features of these quadrangles are the equatorial troughs and the Lucaria tholus. The equatorial troughs consist of graben, i.e. a depression limited by two conjugate faults. The graben do not present their own spectral signatures, but spectral parameters similar to their surroundings, in agreement to their structural origin. This is observed also in graben outside the Gegania and Lucaria quadrangles. However, it is possible to observe other structural features, such as tectonic grooves, characterized by a changing composition and hence an albedo variation. This result is confirmed not only by mineralogical maps of Vesta, but also by analyzing the VIRTIS-Rosetta observations of Lutetia. The albedo change is instead a typical

  8. SpecViz: Interactive Spectral Data Analysis

    NASA Astrophysics Data System (ADS)

    Earl, Nicholas Michael; STScI

    2016-06-01

    The astronomical community is about to enter a new generation of scientific enterprise. With next-generation instrumentation and advanced capabilities, the need has arisen to equip astronomers with the necessary tools to deal with large, multi-faceted data. The Space Telescope Science Institute has initiated a data analysis forum for the creation, development, and maintenance of software tools for the interpretation of these new data sets. SpecViz is a spectral 1-D interactive visualization and analysis application built with Python in an open source development environment. A user-friendly GUI allows for a fast, interactive approach to spectral analysis. SpecViz supports handling of unique and instrument-specific data, incorporation of advanced spectral unit handling and conversions in a flexible, high-performance interactive plotting environment. Active spectral feature analysis is possible through interactive measurement and statistical tools. It can be used to build wide-band SEDs, with the capability of combining or overplotting data products from various instruments. SpecViz sports advanced toolsets for filtering and detrending spectral lines; identifying, isolating, and manipulating spectral features; as well as utilizing spectral templates for renormalizing data in an interactive way. SpecViz also includes a flexible model fitting toolset that allows for multi-component models, as well as custom models, to be used with various fitting and decomposition routines. SpecViz also features robust extension via custom data loaders and connection to the central communication system underneath the interface for more advanced control. Incorporation with Jupyter notebooks via connection with the active iPython kernel allows for SpecViz to be used in addition to a user’s normal workflow without demanding the user drastically alter their method of data analysis. In addition, SpecViz allows the interactive analysis of multi-object spectroscopy in the same straight

  9. Techniques for identifying dust devils in mars pathfinder images

    USGS Publications Warehouse

    Metzger, S.M.; Carr, J.R.; Johnson, J. R.; Parker, T.J.; Lemmon, M.T.

    2000-01-01

    Image processing methods used to identify and enhance dust devil features imaged by IMP (Imager for Mars Pathfinder) are reviewed. Spectral differences, visible red minus visible blue, were used for initial dust devil searches, driven by the observation that Martian dust has high red and low blue reflectance. The Martian sky proved to be more heavily dust-laden than pre-Pathfinder predictions, based on analysis of images from the Hubble Space Telescope. As a result, these initial spectral difference methods failed to contrast dust devils with background dust haze. Imager artifacts (dust motes on the camera lens, flat-field effects caused by imperfections in the CCD, and projection onto a flat sensor plane by a convex lens) further impeded the ability to resolve subtle dust devil features. Consequently, reference images containing sky with a minimal horizon were first subtracted from each spectral filter image to remove camera artifacts and reduce the background dust haze signal. Once the sky-flat preprocessing step was completed, the red-minus-blue spectral difference scheme was attempted again. Dust devils then were successfully identified as bright plumes. False-color ratios using calibrated IMP images were found useful for visualizing dust plumes, verifying initial discoveries as vortex-like features. Enhancement of monochromatic (especially blue filter) images revealed dust devils as silhouettes against brighter background sky. Experiments with principal components transformation identified dust devils in raw, uncalibrated IMP images and further showed relative movement of dust devils across the Martian surface. A variety of methods therefore served qualitative and quantitative goals for dust plume identification and analysis in an environment where such features are obscure.

  10. Io's Thermal Regions and Non-SO2 Spectral Features

    NASA Technical Reports Server (NTRS)

    Smythe, W. D.; Soderblom, L. A.; Lopes, R. M. C.

    2003-01-01

    Several absorptions have been identified in the Galileo NIMS spectra of Io that are not related to SO2. [1,2]. These absorptions have band centers at 2.97, 3.15, 3.85, and 3.91 microns. There are also broad absorptions in the regions 1-1.3 and 3- 3.4 microns. Patterning noise in wavelength registration, arising from the pushbroom imaging and grating motion of the NIMS instrument have previously inhibited reliable mapping of weak absorptions. Recent improvements in techniques to remove the coherent pattern noise from the NIMS dataset have been made by Soderblom. This greatly improves the signal to noise ratio and enables mapping of weak spectral signatures such as the 3.15 micron absorption on Io.

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

    NASA Astrophysics Data System (ADS)

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

    2017-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2010-08-01

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

  13. Identifying Creativity during Problem Solving Using Linguistic Features

    ERIC Educational Resources Information Center

    Skalicky, Stephen; Crossley, Scott A.; McNamara, Danielle S.; Muldner, Kasia

    2017-01-01

    Creativity is commonly assessed using divergent thinking tasks, which measure the fluency, flexibility, originality, and elaboration of participant output on a variety of different tasks. This study assesses the degree to which creativity can be identified based on linguistic features of participants' language while completing collaborative…

  14. Ultraviolet spectral reflectance of carbonaceous materials

    NASA Astrophysics Data System (ADS)

    Applin, Daniel M.; Izawa, Matthew R. M.; Cloutis, Edward A.; Gillis-Davis, Jeffrey J.; Pitman, Karly M.; Roush, Ted L.; Hendrix, Amanda R.; Lucey, Paul G.

    2018-06-01

    A number of planetary spacecraft missions have carried instruments with sensors covering the ultraviolet (UV) wavelength range. However, there exists a general lack of relevant UV reflectance laboratory data to compare against these planetary surface remote sensing observations in order to make confident material identifications. To address this need, we have systematically analyzed reflectance spectra of carbonaceous materials in the 200-500 nm spectral range, and found spectral-compositional-structural relationships that suggest this wavelength region could distinguish between otherwise difficult-to-identify carbon phases. In particular (and by analogy with the infrared spectral region), large changes over short wavelength intervals in the refractive indices associated with the trigonal sp2π-π* transition of carbon can lead to Fresnel peaks and Christiansen-like features in reflectance. Previous studies extending to shorter wavelengths also show that anomalous dispersion caused by the σ-σ* transition associated with both the trigonal sp2 and tetrahedral sp3 sites causes these features below λ = 200 nm. The peak wavelength positions and shapes of π-π* and σ-σ* features contain information on sp3/sp2, structure, crystallinity, and powder grain size. A brief comparison with existing observational data indicates that the carbon fraction of the surface of Mercury is likely amorphous and submicroscopic, as is that on the surface of the martian satellites Phobos and Deimos, and possibly comet 67P/Churyumov-Gerasimenko, while further coordinated observations and laboratory experiments should refine these feature assignments and compositional hypotheses. The new laboratory diffuse reflectance data reported here provide an important new resource for interpreting UV reflectance measurements from planetary surfaces throughout the solar system, and confirm that the UV can be rich in important spectral information.

  15. Study of sensor spectral responses and data processing algorithms and architectures for onboard feature identification

    NASA Technical Reports Server (NTRS)

    Huck, F. O.; Davis, R. E.; Fales, C. L.; Aherron, R. M.

    1982-01-01

    A computational model of the deterministic and stochastic processes involved in remote sensing is used to study spectral feature identification techniques for real-time onboard processing of data acquired with advanced earth-resources sensors. Preliminary results indicate that: Narrow spectral responses are advantageous; signal normalization improves mean-square distance (MSD) classification accuracy but tends to degrade maximum-likelihood (MLH) classification accuracy; and MSD classification of normalized signals performs better than the computationally more complex MLH classification when imaging conditions change appreciably from those conditions during which reference data were acquired. The results also indicate that autonomous categorization of TM signals into vegetation, bare land, water, snow and clouds can be accomplished with adequate reliability for many applications over a reasonably wide range of imaging conditions. However, further analysis is required to develop computationally efficient boundary approximation algorithms for such categorization.

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

    NASA Technical Reports Server (NTRS)

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

    1992-01-01

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

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

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

    Mishra, Ajay; Li, Aigen; Jiang, B. W., E-mail: amishra@mail.missouri.edu, E-mail: lia@missouri.edu, E-mail: bjiang@bnu.edu.cn

    2015-03-20

    The mysterious “21 μm” emission feature seen almost exclusively in the short-lived protoplanetary nebula (PPN) phase of stellar evolution remains unidentified since its discovery two decades ago. This feature is always accompanied by the equally mysterious, unidentified “30 μm” feature and the so-called “unidentified infrared” (UIR) features at 3.3, 6.2, 7.7, 8.6, and 11.3 μm which are generally attributed to polycyclic aromatic hydrocarbon (PAH) molecules. The 30 μm feature is commonly observed in all stages of stellar evolution from the asymptotic giant branch through PPN to the planetary nebula phase. We explore the interrelations among the mysterious 21, 30 μm,more » and UIR features of the 21 μm sources. We derive the fluxes emitted in the observed UIR, 21, and 30 μm features from published Infrared Space Observatory or Spitzer/IRS spectra. We find that none of these spectral features correlate with each other. This argues against a common carrier (e.g., thiourea) for both the 21 μm feature and the 30 μm feature. This also does not support large PAH clusters as a possible carrier for the 21 μm feature.« less

  18. A decision support system for automatic sleep staging from EEG signals using tunable Q-factor wavelet transform and spectral features.

    PubMed

    Hassan, Ahnaf Rashik; Bhuiyan, Mohammed Imamul Hassan

    2016-09-15

    Automatic sleep scoring is essential owing to the fact that conventionally a large volume of data have to be analyzed visually by the physicians which is onerous, time-consuming and error-prone. Therefore, there is a dire need of an automated sleep staging scheme. In this work, we decompose sleep-EEG signal segments using tunable-Q factor wavelet transform (TQWT). Various spectral features are then computed from TQWT sub-bands. The performance of spectral features in the TQWT domain has been determined by intuitive and graphical analyses, statistical validation, and Fisher criteria. Random forest is used to perform classification. Optimal choices and the effects of TQWT and random forest parameters have been determined and expounded. Experimental outcomes manifest the efficacy of our feature generation scheme in terms of p-values of ANOVA analysis and Fisher criteria. The proposed scheme yields 90.38%, 91.50%, 92.11%, 94.80%, 97.50% for 6-stage to 2-stage classification of sleep states on the benchmark Sleep-EDF data-set. In addition, its performance on DREAMS Subjects Data-set is also promising. The performance of the proposed method is significantly better than the existing ones in terms of accuracy and Cohen's kappa coefficient. Additionally, the proposed scheme gives high detection accuracy for sleep stages non-REM 1 and REM. Spectral features in the TQWT domain can discriminate sleep-EEG signals corresponding to various sleep states efficaciously. The proposed scheme will alleviate the burden of the physicians, speed-up sleep disorder diagnosis, and expedite sleep research. Copyright © 2016 Elsevier B.V. All rights reserved.

  19. Spectral properties of 441 radio pulsars

    NASA Astrophysics Data System (ADS)

    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.

  20. Spectral Knowledge (SK-UTALCA): Software for Exploratory Analysis of High-Resolution Spectral Reflectance Data on Plant Breeding.

    PubMed

    Lobos, Gustavo A; Poblete-Echeverría, Carlos

    2016-01-01

    This article describes public, free software that provides efficient exploratory analysis of high-resolution spectral reflectance data. Spectral reflectance data can suffer from problems such as poor signal to noise ratios in various wavebands or invalid measurements due to changes in incoming solar radiation or operator fatigue leading to poor orientation of sensors. Thus, exploratory data analysis is essential to identify appropriate data for further analyses. This software overcomes the problem that analysis tools such as Excel are cumbersome to use for the high number of wavelengths and samples typically acquired in these studies. The software, Spectral Knowledge (SK-UTALCA), was initially developed for plant breeding, but it is also suitable for other studies such as precision agriculture, crop protection, ecophysiology plant nutrition, and soil fertility. Various spectral reflectance indices (SRIs) are often used to relate crop characteristics to spectral data and the software is loaded with 255 SRIs which can be applied quickly to the data. This article describes the architecture and functions of SK-UTALCA and the features of the data that led to the development of each of its modules.

  1. A simulation of remote sensor systems and data processing algorithms for spectral feature classification

    NASA Technical Reports Server (NTRS)

    Arduini, R. F.; Aherron, R. M.; Samms, R. W.

    1984-01-01

    A computational model of the deterministic and stochastic processes involved in multispectral remote sensing was designed to evaluate the performance of sensor systems and data processing algorithms for spectral feature classification. Accuracy in distinguishing between categories of surfaces or between specific types is developed as a means to compare sensor systems and data processing algorithms. The model allows studies to be made of the effects of variability of the atmosphere and of surface reflectance, as well as the effects of channel selection and sensor noise. Examples of these effects are shown.

  2. Spectral features of the body fluids of patients with benign and malignant prostate tumours

    NASA Astrophysics Data System (ADS)

    Atif, M.; Devanesan, S.; Farhat, K.; Rabah, D.; AlSalhi, M. S.; Masilamani, V.

    2013-05-01

    In this study, we present the results of fluorescence spectra of blood and urine to detect and discriminate between samples drawn from benign and malignant prostate patients and we find a very good demarcation in terms of spectral features. This preliminary study was carried out as a proof of concept, with limited samples of blood and urine from known cases of patients of BPH and CaP. In the near future it is expected that a detailed clinical validation will be done to establish it as a reliable cancer diagnosis protocol.

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

    PubMed

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

    2011-03-28

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

  4. Using electroretinograms and multi-model inference to identify spectral classes of photoreceptors and relative opsin expression levels

    PubMed Central

    2017-01-01

    Understanding how individual photoreceptor cells factor in the spectral sensitivity of a visual system is essential to explain how they contribute to the visual ecology of the animal in question. Existing methods that model the absorption of visual pigments use templates which correspond closely to data from thin cross-sections of photoreceptor cells. However, few modeling approaches use a single framework to incorporate physical parameters of real photoreceptors, which can be fused, and can form vertical tiers. Akaike’s information criterion (AICc) was used here to select absorptance models of multiple classes of photoreceptor cells that maximize information, given visual system spectral sensitivity data obtained using extracellular electroretinograms and structural parameters obtained by histological methods. This framework was first used to select among alternative hypotheses of photoreceptor number. It identified spectral classes from a range of dark-adapted visual systems which have between one and four spectral photoreceptor classes. These were the velvet worm, Principapillatus hitoyensis, the branchiopod water flea, Daphnia magna, normal humans, and humans with enhanced S-cone syndrome, a condition in which S-cone frequency is increased due to mutations in a transcription factor that controls photoreceptor expression. Data from the Asian swallowtail, Papilio xuthus, which has at least five main spectral photoreceptor classes in its compound eyes, were included to illustrate potential effects of model over-simplification on multi-model inference. The multi-model framework was then used with parameters of spectral photoreceptor classes and the structural photoreceptor array kept constant. The goal was to map relative opsin expression to visual pigment concentration. It identified relative opsin expression differences for two populations of the bluefin killifish, Lucania goodei. The modeling approach presented here will be useful in selecting the most likely

  5. Using electroretinograms and multi-model inference to identify spectral classes of photoreceptors and relative opsin expression levels.

    PubMed

    Lessios, Nicolas

    2017-01-01

    Understanding how individual photoreceptor cells factor in the spectral sensitivity of a visual system is essential to explain how they contribute to the visual ecology of the animal in question. Existing methods that model the absorption of visual pigments use templates which correspond closely to data from thin cross-sections of photoreceptor cells. However, few modeling approaches use a single framework to incorporate physical parameters of real photoreceptors, which can be fused, and can form vertical tiers. Akaike's information criterion (AIC c ) was used here to select absorptance models of multiple classes of photoreceptor cells that maximize information, given visual system spectral sensitivity data obtained using extracellular electroretinograms and structural parameters obtained by histological methods. This framework was first used to select among alternative hypotheses of photoreceptor number. It identified spectral classes from a range of dark-adapted visual systems which have between one and four spectral photoreceptor classes. These were the velvet worm, Principapillatus hitoyensis , the branchiopod water flea, Daphnia magna , normal humans, and humans with enhanced S-cone syndrome, a condition in which S-cone frequency is increased due to mutations in a transcription factor that controls photoreceptor expression. Data from the Asian swallowtail, Papilio xuthus , which has at least five main spectral photoreceptor classes in its compound eyes, were included to illustrate potential effects of model over-simplification on multi-model inference. The multi-model framework was then used with parameters of spectral photoreceptor classes and the structural photoreceptor array kept constant. The goal was to map relative opsin expression to visual pigment concentration. It identified relative opsin expression differences for two populations of the bluefin killifish, Lucania goodei . The modeling approach presented here will be useful in selecting the most

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

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

    Harilal, S. S.; Skrodzki, P. J.; Miloshevsky, A.

    Laser-heated gas breakdown plasmas or sparks emit profoundly in the ultraviolet and visible region of the electromagnetic spectrum with contributions from ionic, atomic, and molecular species. Laser created kernels expand into a cold ambient with high velocities during its early lifetime followed by confinement of the plasma kernel and eventually collapse. However, the plasma kernels produced during laser breakdown of gases are also capable of exciting and ionizing the surrounding ambient medium. Two mechanisms can be responsible for excitation and ionization of surrounding ambient: viz. photoexcitation and ionization by intense ultraviolet emission from the sparks produced during the early timesmore » of its creation and/or heating by strong shocks generated by the kernel during its expansion into the ambient. In this study, an investigation is made on the spectral features of on- and off-axis emission features of laser-induced plasma breakdown kernels generated in atmospheric pressure conditions with an aim to elucidate the mechanisms leading to ambient excitation and emission. Pulses from an Nd:YAG laser emitting at 1064 nm with 6 ns pulse duration are used to generate plasma kernels. Laser sparks were generated in air, argon, and helium gases to provide different physical properties of expansion dynamics and plasma chemistry considering the differences in laser absorption properties, mass density and speciation. Point shadowgraphy and time-resolved imaging were used to evaluate the shock wave and spark self-emission morphology at early and late times while space and time resolved spectroscopy is used for evaluating the emission features as well as for inferring plasma fundaments at on- and off-axis. Structure and dynamics of the plasma kernel obtained using imaging techniques are also compared to numerical simulations using computational fluid dynamics code. The emission from the kernel showed that spectral features from ions, atoms and molecules are

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

    DOE PAGES

    Harilal, S. S.; Skrodzki, P. J.; Miloshevsky, A.; ...

    2017-06-01

    Laser-heated gas breakdown plasmas or sparks emit profoundly in the ultraviolet and visible region of the electromagnetic spectrum with contributions from ionic, atomic, and molecular species. Laser created kernels expand into a cold ambient with high velocities during its early lifetime followed by confinement of the plasma kernel and eventually collapse. However, the plasma kernels produced during laser breakdown of gases are also capable of exciting and ionizing the surrounding ambient medium. Two mechanisms can be responsible for excitation and ionization of surrounding ambient: viz. photoexcitation and ionization by intense ultraviolet emission from the sparks produced during the early timesmore » of its creation and/or heating by strong shocks generated by the kernel during its expansion into the ambient. In this study, an investigation is made on the spectral features of on- and off-axis emission features of laser-induced plasma breakdown kernels generated in atmospheric pressure conditions with an aim to elucidate the mechanisms leading to ambient excitation and emission. Pulses from an Nd:YAG laser emitting at 1064 nm with 6 ns pulse duration are used to generate plasma kernels. Laser sparks were generated in air, argon, and helium gases to provide different physical properties of expansion dynamics and plasma chemistry considering the differences in laser absorption properties, mass density and speciation. Point shadowgraphy and time-resolved imaging were used to evaluate the shock wave and spark self-emission morphology at early and late times while space and time resolved spectroscopy is used for evaluating the emission features as well as for inferring plasma fundaments at on- and off-axis. Structure and dynamics of the plasma kernel obtained using imaging techniques are also compared to numerical simulations using computational fluid dynamics code. The emission from the kernel showed that spectral features from ions, atoms and molecules are

  8. Using a Weak CN Spectral Feature as a Marker for Massive AGB Stars in the Andromeda Galaxy

    NASA Astrophysics Data System (ADS)

    Guhathakurta, Puragra; Kamath, Anika; Sales, Alyssa; Sarukkai, Atmika; Hays, Jon; PHAT Collaboration; SPLASH Collaboration

    2017-01-01

    The Panchromatic Hubble Andromeda Treasury (PHAT) survey has produced six-filter photometry at near-ultraviolet, optical and nearly infrared wavelengths (F275W, F336W, F475W, F814W, F110W and F160W) for over 100 million stars in the disk of the of the Andromeda galaxy (M31). As part of the Spectroscopic and Photometric Landscape of Andromeda's Stellar Halo (SPLASH) survey, medium resolution (R ~ 2000) spectra covering the wavelength range 4500-9500A were obtained for over 5000 relatively bright stars from the PHAT source catalog using the Keck II 10-meter telescope and DEIMOS spectrograph. While searching for carbon stars in the spectroscopic data set, we discovered a rare population of stars that show a weak CN spectral absorption feature at ~7900A (much weaker than the CN feature in typical carbon stars) along with other spectral absorption features like TiO and the Ca triplet that are generally not present/visible in carbon star spectra but that are typical for normal stars with oxygen rich atmospheres. These 150 or so "weak CN" stars appear to be fairly localized in six-filter space (i.e., in various color-color and color-magnitude diagrams) but are generally offset from carbon stars. Comparison to PARSEC model stellar tracks indicates that these weak CN stars are probably massive (5-10 Msun) asymptotic giant branch (AGB) stars in a relatively short-lived core helium burning phase of their evolution. Careful spectroscopic analysis indicates that the details of the CN spectral feature are about 3-4x weaker in weak CN stars than in carbon stars. The kinematics of weak CN stars are similar to those of other young stars (e.g., massive main sequence stars) and reflect the well ordered rotation of M31's disk.This research project is funded in part by NASA/STScI and the National Science Foundation. Much of this work was carried out by high school students and undergraduates under the auspices of the Science Internship Program and LAMAT program at the University of

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

    NASA Astrophysics Data System (ADS)

    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.

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

    NASA Astrophysics Data System (ADS)

    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.

  11. Robust Joint Graph Sparse Coding for Unsupervised Spectral Feature Selection.

    PubMed

    Zhu, Xiaofeng; Li, Xuelong; Zhang, Shichao; Ju, Chunhua; Wu, Xindong

    2017-06-01

    In this paper, we propose a new unsupervised spectral feature selection model by embedding a graph regularizer into the framework of joint sparse regression for preserving the local structures of data. To do this, we first extract the bases of training data by previous dictionary learning methods and, then, map original data into the basis space to generate their new representations, by proposing a novel joint graph sparse coding (JGSC) model. In JGSC, we first formulate its objective function by simultaneously taking subspace learning and joint sparse regression into account, then, design a new optimization solution to solve the resulting objective function, and further prove the convergence of the proposed solution. Furthermore, we extend JGSC to a robust JGSC (RJGSC) via replacing the least square loss function with a robust loss function, for achieving the same goals and also avoiding the impact of outliers. Finally, experimental results on real data sets showed that both JGSC and RJGSC outperformed the state-of-the-art algorithms in terms of k -nearest neighbor classification performance.

  12. Spectral Knowledge (SK-UTALCA): Software for Exploratory Analysis of High-Resolution Spectral Reflectance Data on Plant Breeding

    PubMed Central

    Lobos, Gustavo A.; Poblete-Echeverría, Carlos

    2017-01-01

    This article describes public, free software that provides efficient exploratory analysis of high-resolution spectral reflectance data. Spectral reflectance data can suffer from problems such as poor signal to noise ratios in various wavebands or invalid measurements due to changes in incoming solar radiation or operator fatigue leading to poor orientation of sensors. Thus, exploratory data analysis is essential to identify appropriate data for further analyses. This software overcomes the problem that analysis tools such as Excel are cumbersome to use for the high number of wavelengths and samples typically acquired in these studies. The software, Spectral Knowledge (SK-UTALCA), was initially developed for plant breeding, but it is also suitable for other studies such as precision agriculture, crop protection, ecophysiology plant nutrition, and soil fertility. Various spectral reflectance indices (SRIs) are often used to relate crop characteristics to spectral data and the software is loaded with 255 SRIs which can be applied quickly to the data. This article describes the architecture and functions of SK-UTALCA and the features of the data that led to the development of each of its modules. PMID:28119705

  13. A Novel Feature Extraction Method with Feature Selection to Identify Golgi-Resident Protein Types from Imbalanced Data

    PubMed Central

    Yang, Runtao; Zhang, Chengjin; Gao, Rui; Zhang, Lina

    2016-01-01

    The Golgi Apparatus (GA) is a major collection and dispatch station for numerous proteins destined for secretion, plasma membranes and lysosomes. The dysfunction of GA proteins can result in neurodegenerative diseases. Therefore, accurate identification of protein subGolgi localizations may assist in drug development and understanding the mechanisms of the GA involved in various cellular processes. In this paper, a new computational method is proposed for identifying cis-Golgi proteins from trans-Golgi proteins. Based on the concept of Common Spatial Patterns (CSP), a novel feature extraction technique is developed to extract evolutionary information from protein sequences. To deal with the imbalanced benchmark dataset, the Synthetic Minority Over-sampling Technique (SMOTE) is adopted. A feature selection method called Random Forest-Recursive Feature Elimination (RF-RFE) is employed to search the optimal features from the CSP based features and g-gap dipeptide composition. Based on the optimal features, a Random Forest (RF) module is used to distinguish cis-Golgi proteins from trans-Golgi proteins. Through the jackknife cross-validation, the proposed method achieves a promising performance with a sensitivity of 0.889, a specificity of 0.880, an accuracy of 0.885, and a Matthew’s Correlation Coefficient (MCC) of 0.765, which remarkably outperforms previous methods. Moreover, when tested on a common independent dataset, our method also achieves a significantly improved performance. These results highlight the promising performance of the proposed method to identify Golgi-resident protein types. Furthermore, the CSP based feature extraction method may provide guidelines for protein function predictions. PMID:26861308

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

    NASA Astrophysics Data System (ADS)

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

    2004-09-01

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

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

    NASA Astrophysics Data System (ADS)

    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.

  16. Identifying scales of pattern in ecological data: a comparison of lacunarity, spectral and wavelet analyses

    Treesearch

    Sari C. Saunders; Jiquan Chen; Thomas D. Drummer; Eric J. Gustafson; Kimberley D. Brosofske

    2005-01-01

    Identifying scales of pattern in ecological systems and coupling patterns to processes that create them are ongoing challenges. We examined the utility of three techniques (lacunarity, spectral, and wavelet analysis) for detecting scales of pattern of ecological data. We compared the information obtained using these methods for four datasets, including: surface...

  17. Connecting infrared spectra with plant traits to identify species

    NASA Astrophysics Data System (ADS)

    Buitrago, Maria F.; Skidmore, Andrew K.; Groen, Thomas A.; Hecker, Christoph A.

    2018-05-01

    Plant traits are used to define species, but also to evaluate the health status of forests, plantations and crops. Conventional methods of measuring plant traits (e.g. wet chemistry), although accurate, are inefficient and costly when applied over large areas or with intensive sampling. Spectroscopic methods, as used in the food industry and mineralogy, are nowadays applied to identify plant traits, however, most studies analysed visible to near infrared, while infrared spectra of longer wavelengths have been little used for identifying the spectral differences between plant species. This study measured the infrared spectra (1.4-16.0 μm) on individual, fresh leaves of 19 species (from herbaceous to woody species), as well as 14 leaf traits for each leaf. The results describe at which wavelengths in the infrared the leaves' spectra can differentiate most effectively between these plant species. A Quadratic Discrimination Analysis (QDA) shows that using five bands in the SWIR or the LWIR is enough to accurately differentiate these species (Kappa: 0.93, 0.94 respectively), while the MWIR has a lower classification accuracy (Kappa: 0.84). This study also shows that in the infrared spectra of fresh leaves, the identified species-specific features are correlated with leaf traits as well as changes in their values. Spectral features in the SWIR (1.66, 1.89 and 2.00 μm) are common to all species and match the main features of pure cellulose and lignin spectra. The depth of these features varies with changes of cellulose and leaf water content and can be used to differentiate species in this region. In the MWIR and LWIR, the absorption spectra of leaves are formed by key species-specific traits including lignin, cellulose, water, nitrogen and leaf thickness. The connection found in this study between leaf traits, features and spectral signatures are novel tools to assist when identifying plant species by spectroscopy and remote sensing.

  18. Hyperspectral Features of Oil-Polluted Sea Ice and the Response to the Contamination Area Fraction

    PubMed Central

    Li, Ying; Liu, Chengyu; Xie, Feng

    2018-01-01

    Researchers have studied oil spills in open waters using remote sensors, but few have focused on extracting reflectance features of oil pollution on sea ice. An experiment was conducted on natural sea ice in Bohai Bay, China, to obtain the spectral reflectance of oil-contaminated sea ice. The spectral absorption index (SAI), spectral peak height (SPH), and wavelet detail coefficient (DWT d5) were calculated using stepwise multiple linear regression. The reflectances of some false targets were measured and analysed. The simulated false targets were sediment, iron ore fines, coal dust, and the melt pool. The measured reflectances were resampled using five common sensors (GF-2, Landsat8-OLI, Sentinel3-OLCI, MODIS, and AVIRIS). Some significant spectral features could discriminate between oil-polluted and clean sea ice. The indices correlated well with the oil area fractions. All of the adjusted R2 values exceeded 0.9. The SPH model1, based on spectral features at 507–670 and 1627–1746 nm, displayed the best fitting. The resampled data indicated that these multi-spectral and hyper-spectral sensors could be used to detect crude oil on the sea ice if the effect of noise and spatial resolution are neglected. The spectral features and their identified changes may provide reference on sensor design and band selection. PMID:29342945

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

    NASA Astrophysics Data System (ADS)

    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 their 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 the surrounding ambient: photoexcitation and ionization by intense ultraviolet emission from the sparks produced during the early times of their 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 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 a pulse duration of 6 ns 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 and for inferring plasma physical conditions at on- and off-axis positions. The structure and dynamics of the plasma kernel obtained using imaging techniques are also compared to numerical simulations using the computational fluid dynamics code. The emission from the kernel showed that spectral features from ions, atoms, and

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

    USGS Publications Warehouse

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

    2004-01-01

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

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

    NASA Astrophysics Data System (ADS)

    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.

  2. Identifying Trajectories of Borderline Personality Features in Adolescence

    PubMed Central

    Haltigan, John D.

    2016-01-01

    Objective: To examine trajectories of adolescent borderline personality (BP) features in a normative-risk cohort (n = 566) of Canadian children assessed at ages 13, 14, 15, and 16 and childhood predictors of trajectory group membership assessed at ages 8, 10, 11, and 12. Method: Data were drawn from the McMaster Teen Study, an on-going study examining relations among bullying, mental health, and academic achievement. Participants and their parents completed a battery of mental health and peer relations questionnaires at each wave of the study. Academic competence was assessed at age 8 (Grade 3). Latent class growth analysis, analysis of variance, and logistic regression were used to analyze the data. Results: Three distinct BP features trajectory groups were identified: elevated or rising, intermediate or stable, and low or stable. Parent- and child-reported mental health symptoms, peer relations risk factors, and intra-individual risk factors were significant predictors of elevated or rising and intermediate or stable trajectory groups. Child-reported attention-deficit hyperactivity disorder (ADHD) and somatization symptoms uniquely predicted elevated or rising trajectory group membership, whereas parent-reported anxiety and child-reported ADHD symptoms uniquely predicted intermediate or stable trajectory group membership. Child-reported somatization symptoms was the only predictor to differentiate the intermediate or stable and elevated or rising trajectory groups (OR 1.15, 95% CI 1.04 to 1.28). Associations between child-reported reactive temperament and elevated BP features trajectory group membership were 10.23 times higher among children who were bullied, supporting a diathesis–stress pathway in the development of BP features for these youth. Conclusions: Findings demonstrate the heterogeneous course of BP features in early adolescence and shed light on the potential prodromal course of later borderline personality disorder. PMID:27254092

  3. Identification of spectral phenotypes in age-related macular degeneration patients

    NASA Astrophysics Data System (ADS)

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

    2007-02-01

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

  4. Identifying sports videos using replay, text, and camera motion features

    NASA Astrophysics Data System (ADS)

    Kobla, Vikrant; DeMenthon, Daniel; Doermann, David S.

    1999-12-01

    Automated classification of digital video is emerging as an important piece of the puzzle in the design of content management systems for digital libraries. The ability to classify videos into various classes such as sports, news, movies, or documentaries, increases the efficiency of indexing, browsing, and retrieval of video in large databases. In this paper, we discuss the extraction of features that enable identification of sports videos directly from the compressed domain of MPEG video. These features include detecting the presence of action replays, determining the amount of scene text in vide, and calculating various statistics on camera and/or object motion. The features are derived from the macroblock, motion,and bit-rate information that is readily accessible from MPEG video with very minimal decoding, leading to substantial gains in processing speeds. Full-decoding of selective frames is required only for text analysis. A decision tree classifier built using these features is able to identify sports clips with an accuracy of about 93 percent.

  5. A Moderate Resolution NIR Spectral Library of Weak-Lined T Tauri Stars

    NASA Astrophysics Data System (ADS)

    Cooper, Rachel; Covey, K. R.

    2013-01-01

    We present a spectral library of high-quality moderate resolution (R ~ 3500) NIR spectra for 44 weak-lined T Tauri Stars (WTTS) in the Taurus-Auriga Molecular Cloud. These spectra, obtained with the TripleSpec spectrograph on the Astrophysical Research Consortium (ARC) 3.5 meter telescope, provide full coverage of the J, H, and K near-infrared bands in a single epoch. Analyzing these spectra, along with those of dwarf and giant spectral type standards from the SpeX Spectral Library, we have identified several elemental and molecular absorption lines that vary in strength with respect to each star's spectral type and luminosity class. Calibrating each of these features as a spectral type indicator, we provide a detailed characterization for each of the WTTSs in our sample, identifying each star's NIR spectral type and line-of-sight extinction, estimated both from the shape of the overall continuum and from the fluxes of the Paschen beta and Brackett gamma emission lines. In addition to improving our understanding of the properties of these WTTSs, this well characterized spectral library will be a valuable resource for analyses of the NIR continuum veiling and line emission present in the spectra of accreting classical T Tauri stars. This research was made possible by NSF Grant AST-1004107.

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

    PubMed

    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.

  7. Identifying DNA Methylation Features that Underlie Prostate Cancer Disparities

    DTIC Science & Technology

    2016-10-01

    Report We will continue to recruit African American patients and bank their prostate tissue . We will continue dissecting tumor samples into tumor...in prostate tumors and adjacent normal tissue derived from both AA and EA individuals. We will determine if DNA methylation patterns in prostate... tissue (both cancerous and normal tissue ) differ between AA and EA individuals. We will also identify methylation features that differ between tumor

  8. 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

    NASA Astrophysics Data System (ADS)

    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.

  9. Spectral imaging of histological and cytological specimens

    NASA Astrophysics Data System (ADS)

    Rothmann, Chana; Malik, Zvi

    1999-05-01

    Evaluation of cell morphology by bright field microscopy is the pillar of histopathological diagnosis. The need for quantitative and objective parameters for diagnosis has given rise to the development of morphometric methods. The development of spectral imaging for biological and medical applications introduced both fields to large amounts of information extracted from a single image. Spectroscopic analysis is based on the ability of a stained histological specimen to absorb, reflect, or emit photons in ways characteristic to its interactions with specific dyes. Spectral information obtained from a histological specimen is stored in a cube whose appellate signifies the two spatial dimensions of a flat sample (x and y) and the third dimension, the spectrum, representing the light intensity for every wavelength. The spectral information stored in the cube can be further processed by morphometric analysis and quantitative procedures. Such a procedure is spectral-similarity mapping (SSM), which enables the demarcation of areas occupied by the same type of material. SSM constructs new images of the specimen, revealing areas with similar stain-macromolecule characteristics and enhancing subcellular features. Spectral imaging combined with SSM reveals nuclear organization through the differentiation stages as well as in apoptotic and necrotic conditions and identifies specifically the nucleoli domains.

  10. Benefits of Red-Edge Spectral Band and Texture Features for the Object-based Classification using RapidEye sSatellite Image data

    NASA Astrophysics Data System (ADS)

    Kim, H. O.; Yeom, J. M.

    2014-12-01

    Space-based remote sensing in agriculture is particularly relevant to issues such as global climate change, food security, and precision agriculture. Recent satellite missions have opened up new perspectives by offering high spatial resolution, various spectral properties, and fast revisit rates to the same regions. Here, we examine the utility of broadband red-edge spectral information in multispectral satellite image data for classifying paddy rice crops in South Korea. Additionally, we examine how object-based spectral features affect the classification of paddy rice growth stages. For the analysis, two seasons of RapidEye satellite image data were used. The results showed that the broadband red-edge information slightly improved the classification accuracy of the crop condition in heterogeneous paddy rice crop environments, particularly when single-season image data were used. This positive effect appeared to be offset by the multi-temporal image data. Additional texture information brought only a minor improvement or a slight decline, although it is well known to be advantageous for object-based classification in general. We conclude that broadband red-edge information derived from conventional multispectral satellite data has the potential to improve space-based crop monitoring. Because the positive or negative effects of texture features for object-based crop classification could barely be interpreted, the relationships between the textual properties and paddy rice crop parameters at the field scale should be further examined in depth.

  11. Adaptation to spectrally-rotated speech.

    PubMed

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

    2013-08-01

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

  12. Method of identifying features in indexed data

    DOEpatents

    Jarman, Kristin H [Richland, WA; Daly, Don Simone [Richland, WA; Anderson, Kevin K [Richland, WA; Wahl, Karen L [Richland, WA

    2001-06-26

    The present invention is a method of identifying features in indexed data, especially useful for distinguishing signal from noise in data provided as a plurality of ordered pairs. Each of the plurality of ordered pairs has an index and a response. The method has the steps of: (a) providing an index window having a first window end located on a first index and extending across a plurality of indices to a second window end; (b) selecting responses corresponding to the plurality of indices within the index window and computing a measure of dispersion of the responses; and (c) comparing the measure of dispersion to a dispersion critical value. Advantages of the present invention include minimizing signal to noise ratio, signal drift, varying baseline signal and combinations thereof.

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

    NASA Astrophysics Data System (ADS)

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

    2017-01-01

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

  14. An Optimal Mean Based Block Robust Feature Extraction Method to Identify Colorectal Cancer Genes with Integrated Data.

    PubMed

    Liu, Jian; Cheng, Yuhu; Wang, Xuesong; Zhang, Lin; Liu, Hui

    2017-08-17

    It is urgent to diagnose colorectal cancer in the early stage. Some feature genes which are important to colorectal cancer development have been identified. However, for the early stage of colorectal cancer, less is known about the identity of specific cancer genes that are associated with advanced clinical stage. In this paper, we conducted a feature extraction method named Optimal Mean based Block Robust Feature Extraction method (OMBRFE) to identify feature genes associated with advanced colorectal cancer in clinical stage by using the integrated colorectal cancer data. Firstly, based on the optimal mean and L 2,1 -norm, a novel feature extraction method called Optimal Mean based Robust Feature Extraction method (OMRFE) is proposed to identify feature genes. Then the OMBRFE method which introduces the block ideology into OMRFE method is put forward to process the colorectal cancer integrated data which includes multiple genomic data: copy number alterations, somatic mutations, methylation expression alteration, as well as gene expression changes. Experimental results demonstrate that the OMBRFE is more effective than previous methods in identifying the feature genes. Moreover, genes identified by OMBRFE are verified to be closely associated with advanced colorectal cancer in clinical stage.

  15. Onboard spectral imager data processor

    NASA Astrophysics Data System (ADS)

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

    1999-10-01

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

  16. Key clinical features to identify girls with CDKL5 mutations.

    PubMed

    Bahi-Buisson, Nadia; Nectoux, Juliette; Rosas-Vargas, Haydeé; Milh, Mathieu; Boddaert, Nathalie; Girard, Benoit; Cances, Claude; Ville, Dorothée; Afenjar, Alexandra; Rio, Marlène; Héron, Delphine; N'guyen Morel, Marie Ange; Arzimanoglou, Alexis; Philippe, Christophe; Jonveaux, Philippe; Chelly, Jamel; Bienvenu, Thierry

    2008-10-01

    Mutations in the human X-linked cyclin-dependent kinase-like 5 (CDKL5) gene have been shown to cause infantile spasms as well as Rett syndrome (RTT)-like phenotype. To date, less than 25 different mutations have been reported. So far, there are still little data on the key clinical diagnosis criteria and on the natural history of CDKL5-associated encephalopathy. We screened the entire coding region of CDKL5 for mutations in 183 females with encephalopathy with early seizures by denaturing high liquid performance chromatography and direct sequencing, and we identified in 20 unrelated girls, 18 different mutations including 7 novel mutations. These mutations were identified in eight patients with encephalopathy with RTT-like features, five with infantile spasms and seven with encephalopathy with refractory epilepsy. Early epilepsy with normal interictal EEG and severe hypotonia are the key clinical features in identifying patients likely to have CDKL5 mutations. Our study also indicates that these patients clearly exhibit some RTT features such as deceleration of head growth, stereotypies and hand apraxia and that these RTT features become more evident in older and ambulatory patients. However, some RTT signs are clearly absent such as the so called RTT disease profile (period of nearly normal development followed by regression with loss of acquired fine finger skill in early childhood and characteristic intensive eye communication) and the characteristic evolution of the RTT electroencephalogram. Interestingly, in addition to the overall stereotypical symptomatology (age of onset and evolution of the disease) resulting from CDKL5 mutations, atypical forms of CDKL5-related conditions have also been observed. Our data suggest that phenotypic heterogeneity does not correlate with the nature or the position of the mutations or with the pattern of X-chromosome inactivation, but most probably with the functional transcriptional and/or translational consequences of CDKL5

  17. Fatigue crack detection by nonlinear spectral correlation with a wideband input

    NASA Astrophysics Data System (ADS)

    Liu, Peipei; Sohn, Hoon

    2017-04-01

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

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

    NASA Astrophysics Data System (ADS)

    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).

  19. Forest tree species clssification based on airborne hyper-spectral imagery

    NASA Astrophysics Data System (ADS)

    Dian, Yuanyong; Li, Zengyuan; Pang, Yong

    2013-10-01

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

  20. SDP_mharwit_1: Demonstration of HIFI Linear Polarization Analysis of Spectral Features

    NASA Astrophysics Data System (ADS)

    Harwit, M.

    2010-03-01

    We propose to observe the polarization of the 621 GHz water vapor maser in VY Canis Majoris to demonstrate the capability of HIFI to make polarization observations of Far-Infrared/Submillimeter spectral lines. The proposed Demonstration Phase would: - Show that HIFI is capable of interesting linear polarization measurements of spectral lines; - Test out the highest spectral resolving power to sort out closely spaced Doppler components; - Determine whether the relative intensities predicted by Neufeld and Melnick are correct; - Record the degree and direction of linear polarization for the closely-Doppler shifted peaks.

  1. Evaluation and Improvement of Spectral Features for the Detection of Buried Explosive Hazards Using Forward-Looking Ground-Penetrating Radar

    DTIC Science & Technology

    2012-07-01

    cross track direction is calculated. This is accomplished by taking a 101 point horizontal slice of pixels centered on the alarm. Then, a 101 point...Hamming window, is the 101 -length row vector of FLGPR image pixels surrounding alarm A. We then store the first 50 frequency values (excluding the...Figure 3. Illustration of spectral features in the cross track direction and the difference between actual targets and FAs. Eleven rows of 101

  2. Photoelectron energy loss and spectral features deduced by the plasma line technique. [in topside F region

    NASA Technical Reports Server (NTRS)

    Abreu, V. J.; Carlson, H. C.

    1977-01-01

    Plasma line data gathered at the Arecibo Observatory are used to examine relative variations in topside F region differential photoelectron fluxes in the 5- to 20-eV range. A spectral feature not found in present theoretically calculated spectra is noted near 15 eV. A new approach to the interpretation of the measured spectra is taken, which allows a qualitative estimate of the relative importance of different energy loss mechanisms. The altitude variation of the observed photoelectron flux energy spectra at the higher altitudes (above 350 km) and the lower energies (less than 10 eV) agrees quantitatively with the expected variation of the spectrum.

  3. Computation and evaluation of features of surface electromyogram to identify the force of muscle contraction and muscle fatigue.

    PubMed

    Arjunan, Sridhar P; Kumar, Dinesh K; Naik, Ganesh

    2014-01-01

    The relationship between force of muscle contraction and muscle fatigue with six different features of surface electromyogram (sEMG) was determined by conducting experiments on thirty-five volunteers. The participants performed isometric contractions at 50%, 75%, and 100% of their maximum voluntary contraction (MVC). Six features were considered in this study: normalised spectral index (NSM5), median frequency, root mean square, waveform length, normalised root mean square (NRMS), and increase in synchronization (IIS) index. Analysis of variance (ANOVA) and linear regression analysis were performed to determine the significance of the feature with respect to the three factors: muscle force, muscle fatigue, and subject. The results show that IIS index of sEMG had the highest correlation with muscle fatigue and the relationship was statistically significant (P < 0.01), while NSM5 associated best with level of muscle contraction (%MVC) (P < 0.01). Both of these features were not affected by the intersubject variations (P > 0.05).

  4. Computation and Evaluation of Features of Surface Electromyogram to Identify the Force of Muscle Contraction and Muscle Fatigue

    PubMed Central

    Arjunan, Sridhar P.; Kumar, Dinesh K.; Naik, Ganesh

    2014-01-01

    The relationship between force of muscle contraction and muscle fatigue with six different features of surface electromyogram (sEMG) was determined by conducting experiments on thirty-five volunteers. The participants performed isometric contractions at 50%, 75%, and 100% of their maximum voluntary contraction (MVC). Six features were considered in this study: normalised spectral index (NSM5), median frequency, root mean square, waveform length, normalised root mean square (NRMS), and increase in synchronization (IIS) index. Analysis of variance (ANOVA) and linear regression analysis were performed to determine the significance of the feature with respect to the three factors: muscle force, muscle fatigue, and subject. The results show that IIS index of sEMG had the highest correlation with muscle fatigue and the relationship was statistically significant (P < 0.01), while NSM5 associated best with level of muscle contraction (%MVC) (P < 0.01). Both of these features were not affected by the intersubject variations (P > 0.05). PMID:24995275

  5. Spatio-temporal Spectral Variability in Cas A

    NASA Astrophysics Data System (ADS)

    Nambiar, Yamini; Kashyap, V.; Patnaude, D.

    2014-01-01

    We have analyzed Chandra archival data of Cas A Supernova Remnant to identify regions with large spectral abnormalities and variability over the last decade. We use 8 ACIS-S observations spanning the years 2000 to 2012. We compute spectral hardness ratios in the soft/medium and medium/hard CSC bands over spatial scales corresponding to binning by 4, 8, 16, 32, and 64. We reduce the data and apply the latest calibration using the CIAO tool chandra_repro. We account for exposure variations using exposure maps and compute photon fluxes using the CIAO tool fluximage. We then renormalize the color light curves at each pixel and flag large departures from the norm by comparing with the observed spread in the renormalized color light curves. This allows regions with different intrinsic spectral properties to be compared. We flag deviations of >3σ from the renormalized mean at each epoch, and combine all such pixels to form a map of interesting regions in the remnant. We also identify pixels which have intrinsically abnormal hardness ratios at each epoch. We show that there exist many sites on Cas A where abnormal variations in the spectrum exist. Specifically, we find that many of the identified regions coincide with prominent features of the SNR, such as the edge of the remnant, the central compact object, and numerous knots. In addition, we find various other locations 1000) where there is indication of an atypical spectral signature. The full region lists, along with analysis scripts and the figures and tables shown in this poster, are stored on the Harvard Dataverse Network, at http://dx.doi.org/10.7910/DVN1/22634 YN thanks ABRHS and Young Einsteins Science Club for support and guidance. VK and DP acknowledge support during this project from the Chandra X-Ray Center.

  6. Spectral Feature Analysis for Quantitative Estimation of Cyanobacteria Chlorophyll-A

    NASA Astrophysics Data System (ADS)

    Lin, Yi; Ye, Zhanglin; Zhang, Yugan; Yu, Jie

    2016-06-01

    In recent years, lake eutrophication caused a large of Cyanobacteria bloom which not only brought serious ecological disaster but also restricted the sustainable development of regional economy in our country. Chlorophyll-a is a very important environmental factor to monitor water quality, especially for lake eutrophication. Remote sensed technique has been widely utilized in estimating the concentration of chlorophyll-a by different kind of vegetation indices and monitoring its distribution in lakes, rivers or along coastline. For each vegetation index, its quantitative estimation accuracy for different satellite data might change since there might be a discrepancy of spectral resolution and channel center between different satellites. The purpose this paper is to analyze the spectral feature of chlorophyll-a with hyperspectral data (totally 651 bands) and use the result to choose the optimal band combination for different satellites. The analysis method developed here in this study could be useful to recognize and monitor cyanobacteria bloom automatically and accrately. In our experiment, the reflectance (from 350nm to 1000nm) of wild cyanobacteria in different consistency (from 0 to 1362.11ug/L) and the corresponding chlorophyll-a concentration were measured simultaneously. Two kinds of hyperspectral vegetation indices were applied in this study: simple ratio (SR) and narrow band normalized difference vegetation index (NDVI), both of which consists of any two bands in the entire 651 narrow bands. Then multivariate statistical analysis was used to construct the linear, power and exponential models. After analyzing the correlation between chlorophyll-a and single band reflectance, SR, NDVI respetively, the optimal spectral index for quantitative estimation of cyanobacteria chlorophyll-a, as well corresponding central wavelength and band width were extracted. Results show that: Under the condition of water disturbance, SR and NDVI are both suitable for quantitative

  7. Novel histopathologic feature identified through image analysis augments stage II colorectal cancer clinical reporting

    PubMed Central

    Caie, Peter D.; Zhou, Ying; Turnbull, Arran K.; Oniscu, Anca; Harrison, David J.

    2016-01-01

    A number of candidate histopathologic factors show promise in identifying stage II colorectal cancer (CRC) patients at a high risk of disease-specific death, however they can suffer from low reproducibility and none have replaced classical pathologic staging. We developed an image analysis algorithm which standardized the quantification of specific histopathologic features and exported a multi-parametric feature-set captured without bias. The image analysis algorithm was executed across a training set (n = 50) and the resultant big data was distilled through decision tree modelling to identify the most informative parameters to sub-categorize stage II CRC patients. The most significant, and novel, parameter identified was the ‘sum area of poorly differentiated clusters’ (AreaPDC). This feature was validated across a second cohort of stage II CRC patients (n = 134) (HR = 4; 95% CI, 1.5– 11). Finally, the AreaPDC was integrated with the significant features within the clinical pathology report, pT stage and differentiation, into a novel prognostic index (HR = 7.5; 95% CI, 3–18.5) which improved upon current clinical staging (HR = 4.26; 95% CI, 1.7– 10.3). The identification of poorly differentiated clusters as being highly significant in disease progression presents evidence to suggest that these features could be the source of novel targets to decrease the risk of disease specific death. PMID:27322148

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

    Carbonate-bearing deposits were identified on Mars at multiple locations using CRISM VNIR spectral data [1,2,3,4,5]. Carbonates exhibit distinctive C-O related absorption features near 2300, 2500, 3400 and 3900nm that can be used to identify specific carbonate phases (e.g., Mg-carbonates have band minima at 2300/2500nm and Fe-carbonates have minima at 2330/2530nm [6]). The features at 2300 and 2500nm are the focus of most CRISM analyses because this part of the spectral range is well calibrated, lacks strong contributions from thermal emission, and is not impacted by strong water-related absorptions near 3000nm (e.g., in Fe/Mg phyllosilicates). However, multiple other phases also exhibit features near 2300 and 2500nm.For carbonates, the depth of the 2500nm feature is stronger than at 2300nm as opposed to most Fe/Mg phyllosilicates. Mixing of the carbonate with other phases in CRISM pixels impacts the band centers and strengths of the 2300 and 2500nm features and therefore complicates identification of the carbonate phase(s) responsible for observed CRISM spectral features. In this study we analyze CRISM data fully corrected for the atmosphere using DISORT radiative transfer modeling [7,8] to evaluate CRISM spectra of multiple carbonate-bearing deposits. Rigorous intercomparison of CRISM spectra extracted from different images is affected by variable aerosol, CO2 and water vapor features left by the standard volcano scan empirical atmospheric correction [9]. While residual gas absorptions are commonly suppressed by ratioing, the appearance of spectral features in ratio spectra is impacted by spectral features in the dominator spectrum compromising detailed assessments of ratio spectra derived from different images. Atmospheric correction is particularly important for interpreting carbonate deposits because the 2500nm carbonate feature overlaps with atmospheric water vapor absorptions. In Nili Fossae, carbonates occur in association with olivine, smectite, serpentine

  9. Correlations of Power-law Spectral and QPO Features In Black Hole Candidate Sources

    NASA Technical Reports Server (NTRS)

    Fiorito, Ralph; Titarchuk, Lev

    2004-01-01

    Recent studies have shown that strong correlations are observed between low frequency QPO s and the spectral power law index for a number of black hole candidate sources (BHCs), when these sources exhibit quasi-steady hard x-ray emission states. The dominant long standing interpretation of QPO's is that they are produced in and are the signature of the thermal accretion disk. Paradoxically, strong QPO's are present even in the cases where the thermal component is negligible. We present a model which identifies the origin of the QPO's and relates them directly to the properties of a compact coronal region which is bounded by the adjustment from Kepleriaa to sub-Kelperian inflow into the BH, and is primarily responsible for the observed power law spectrum. The model also predicts the relationship between high and low frequency QPO's and shows how BH's can be unique identified from observations of the soft states of NS's and BHC's.

  10. Determining local and contextual features describing appearance of difficult to identify mitotic figures

    NASA Astrophysics Data System (ADS)

    Gandomkar, Ziba; Brennan, Patrick C.; Mello-Thoms, Claudia

    2017-03-01

    Mitotic count is helpful in determining the aggressiveness of breast cancer. In previous studies, it was shown that the agreement among pathologists for grading mitotic index is fairly modest, as mitoses have a large variety of appearances and they could be mistaken for other similar objects. In this study, we determined local and contextual features that differ significantly between easily identifiable mitoses and challenging ones. The images were obtained from the Mitosis-Atypia 2014 challenge. In total, the dataset contained 453 mitotic figures. Two pathologists annotated each mitotic figure. In case of disagreement, an opinion from a third pathologist was requested. The mitoses were grouped into three categories, those recognized as "a true mitosis" by both pathologists ,those labelled as "a true mitosis" by only one of the first two readers and also the third pathologist, and those annotated as "probably a mitosis" by all readers or the majority of them. After color unmixing, the mitoses were segmented from H channel. Shape-based features along with intensity-based and textural features were extracted from H-channel, blue ratio channel and five different color spaces. Holistic features describing each image were also considered. The Kruskal-Wallis H test was used to identify significantly different features. Multiple comparisons were done using the rank-based version of Tukey-Kramer test. The results indicated that there are local and global features which differ significantly among different groups. In addition, variations between mitoses in different groups were captured in the features from HSL and LCH color space more than other ones.

  11. The Transit Light Source Effect: False Spectral Features and Incorrect Densities for M-dwarf Transiting Planets

    NASA Astrophysics Data System (ADS)

    Rackham, Benjamin V.; Apai, Dániel; Giampapa, Mark S.

    2018-02-01

    Transmission spectra are differential measurements that utilize stellar illumination to probe transiting exoplanet atmospheres. Any spectral difference between the illuminating light source and the disk-integrated stellar spectrum due to starspots and faculae will be imprinted in the observed transmission spectrum. However, few constraints exist for the extent of photospheric heterogeneities in M dwarfs. Here we model spot and faculae covering fractions consistent with observed photometric variabilities for M dwarfs and the associated 0.3–5.5 μm stellar contamination spectra. We find that large ranges of spot and faculae covering fractions are consistent with observations and corrections assuming a linear relation between variability amplitude, and covering fractions generally underestimate the stellar contamination. Using realistic estimates for spot and faculae covering fractions, we find that stellar contamination can be more than 10× larger than the transit depth changes expected for atmospheric features in rocky exoplanets. We also find that stellar spectral contamination can lead to systematic errors in radius and therefore the derived density of small planets. In the case of the TRAPPIST-1 system, we show that TRAPPIST-1's rotational variability is consistent with spot covering fractions {f}{spot}={8}-7+18 % and faculae covering fractions {f}{fac}={54}-46+16 % . The associated stellar contamination signals alter the transit depths of the TRAPPIST-1 planets at wavelengths of interest for planetary atmospheric species by roughly 1–15× the strength of planetary features, significantly complicating JWST follow-up observations of this system. Similarly, we find that stellar contamination can lead to underestimates of the bulk densities of the TRAPPIST-1 planets of {{Δ }}(ρ )=-{8}-20+7 % , thus leading to overestimates of their volatile contents.

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

    NASA Astrophysics Data System (ADS)

    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.

  13. Identifying sources of tick blood meals using unidentified tandem mass spectral libraries.

    PubMed

    Önder, Özlem; Shao, Wenguang; Kemps, Brian D; Lam, Henry; Brisson, Dustin

    2013-01-01

    Rapid and reliable identification of the vertebrate species on which a disease vector previously parasitized is imperative to study ecological factors that affect pathogen distribution and can aid the development of public health programs. Here we describe a proteome profiling technique designed to identify the source of blood meals of haematophagous arthropods. This method employs direct spectral matching and thus does not require a priori knowledge of any genetic or protein sequence information. Using this technology, we detect remnants of blood in blacklegged ticks (Ixodes scapularis) and correctly determine the vertebrate species from which the blood was derived, even 6 months after the tick had fed. This biological fingerprinting methodology is sensitive, fast, cost-effective and can potentially be adapted for other biological and medical applications when existing genome-based methods are impractical or ineffective.

  14. Processing of spectral and amplitude envelope of animal vocalizations in the human auditory cortex.

    PubMed

    Altmann, Christian F; Gomes de Oliveira Júnior, Cícero; Heinemann, Linda; Kaiser, Jochen

    2010-08-01

    In daily life, we usually identify sounds effortlessly and efficiently. Two properties are particularly salient and of importance for sound identification: the sound's overall spectral envelope and its temporal amplitude envelope. In this study, we aimed at investigating the representation of these two features in the human auditory cortex by using a functional magnetic resonance imaging adaptation paradigm. We presented pairs of sound stimuli derived from animal vocalizations that preserved the time-averaged frequency spectrum of the animal vocalizations and the amplitude envelope. We presented the pairs in four different conditions: (a) pairs with the same amplitude envelope and mean spectral envelope, (b) same amplitude envelope, but different mean spectral envelope, (c) different amplitude envelope, but same mean spectral envelope and (d) both different amplitude envelope and mean spectral envelope. We found fMRI adaptation effects for both the mean spectral envelope and the amplitude envelope of animal vocalizations in overlapping cortical areas in the bilateral superior temporal gyrus posterior to Heschl's gyrus. Areas sensitive to the amplitude envelope extended further anteriorly along the lateral superior temporal gyrus in the left hemisphere, while areas sensitive to the spectral envelope extended further anteriorly along the right lateral superior temporal gyrus. Posterior tonotopic areas within the left superior temporal lobe displayed sensitivity for the mean spectrum. Our findings suggest involvement of primary auditory areas in the representation of spectral cues and encoding of general spectro-temporal features of natural sounds in non-primary posterior and lateral superior temporal cortex. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

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

    PubMed

    Schädler, Marc René; Kollmeier, Birger

    2015-04-01

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

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

    USGS Publications Warehouse

    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

  17. Spectral properties of identified polarized-light sensitive interneurons in the brain of the desert locust Schistocerca gregaria.

    PubMed

    Kinoshita, Michiyo; Pfeiffer, Keram; Homberg, Uwe

    2007-04-01

    Many migrating animals employ a celestial compass mechanism for spatial navigation. Behavioral experiments in bees and ants have shown that sun compass navigation may rely on the spectral gradient in the sky as well as on the pattern of sky polarization. While polarized-light sensitive interneurons (POL neurons) have been identified in the brain of several insect species, there are at present no data on the neural basis of coding the spectral gradient of the sky. In the present study we have analyzed the chromatic properties of two identified POL neurons in the brain of the desert locust. Both neurons, termed TuTu1 and LoTu1, arborize in the anterior optic tubercle and respond to unpolarized light as well as to polarized light. We show here that the polarized-light response of both types of neuron relies on blue-sensitive photoreceptors. Responses to unpolarized light depended on stimulus position and wavelength. Dorsal unpolarized blue light inhibited the neurons, while stimulation from the ipsilateral side resulted in opponent responses to UV light and green light. While LoTu1 was inhibited by UV light and was excited by green light, one subtype of TuTu1 was excited by UV and inhibited by green light. In LoTu1 the sensitivity to polarized light was at least 2 log units higher than the response to unpolarized light stimuli. Taken together, the spatial and chromatic properties of the neurons may be suited to signal azimuthal directions based on a combination of the spectral gradient and the polarization pattern of the sky.

  18. Identifying the features of an exercise addiction: A Delphi study

    PubMed Central

    Macfarlane, Lucy; Owens, Glynn; Cruz, Borja del Pozo

    2016-01-01

    Objectives There remains limited consensus regarding the definition and conceptual basis of exercise addiction. An understanding of the factors motivating maintenance of addictive exercise behavior is important for appropriately targeting intervention. The aims of this study were twofold: first, to establish consensus on features of an exercise addiction using Delphi methodology and second, to identify whether these features are congruous with a conceptual model of exercise addiction adapted from the Work Craving Model. Methods A three-round Delphi process explored the views of participants regarding the features of an exercise addiction. The participants were selected from sport and exercise relevant domains, including physicians, physiotherapists, coaches, trainers, and athletes. Suggestions meeting consensus were considered with regard to the proposed conceptual model. Results and discussion Sixty-three items reached consensus. There was concordance of opinion that exercising excessively is an addiction, and therefore it was appropriate to consider the suggestions in light of the addiction-based conceptual model. Statements reaching consensus were consistent with all three components of the model: learned (negative perfectionism), behavioral (obsessive–compulsive drive), and hedonic (self-worth compensation and reduction of negative affect and withdrawal). Conclusions Delphi methodology allowed consensus to be reached regarding the features of an exercise addiction, and these features were consistent with our hypothesized conceptual model of exercise addiction. This study is the first to have applied Delphi methodology to the exercise addiction field, and therefore introduces a novel approach to exercise addiction research that can be used as a template to stimulate future examination using this technique. PMID:27554504

  19. A practical approach to spectral calibration of short wavelength infrared hyper-spectral imaging systems

    NASA Astrophysics Data System (ADS)

    Bürmen, Miran; Pernuš, Franjo; Likar, Boštjan

    2010-02-01

    Near-infrared spectroscopy is a promising, rapidly developing, reliable and noninvasive technique, used extensively in the biomedicine and in pharmaceutical industry. With the introduction of acousto-optic tunable filters (AOTF) and highly sensitive InGaAs focal plane sensor arrays, real-time high resolution hyper-spectral imaging has become feasible for a number of new biomedical in vivo applications. However, due to the specificity of the AOTF technology and lack of spectral calibration standardization, maintaining long-term stability and compatibility of the acquired hyper-spectral images across different systems is still a challenging problem. Efficiently solving both is essential as the majority of methods for analysis of hyper-spectral images relay on a priori knowledge extracted from large spectral databases, serving as the basis for reliable qualitative or quantitative analysis of various biological samples. In this study, we propose and evaluate fast and reliable spectral calibration of hyper-spectral imaging systems in the short wavelength infrared spectral region. The proposed spectral calibration method is based on light sources or materials, exhibiting distinct spectral features, which enable robust non-rigid registration of the acquired spectra. The calibration accounts for all of the components of a typical hyper-spectral imaging system such as AOTF, light source, lens and optical fibers. The obtained results indicated that practical, fast and reliable spectral calibration of hyper-spectral imaging systems is possible, thereby assuring long-term stability and inter-system compatibility of the acquired hyper-spectral images.

  20. SPAM- SPECTRAL ANALYSIS MANAGER (UNIX VERSION)

    NASA Technical Reports Server (NTRS)

    Solomon, J. E.

    1994-01-01

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

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

    PubMed

    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.

  2. An expert botanical feature extraction technique based on phenetic features for identifying plant species.

    PubMed

    Kolivand, Hoshang; Fern, Bong Mei; Rahim, Mohd Shafry Mohd; Sulong, Ghazali; Baker, Thar; Tully, David

    2018-01-01

    In this paper, we present a new method to recognise the leaf type and identify plant species using phenetic parts of the leaf; lobes, apex and base detection. Most of the research in this area focuses on the popular features such as the shape, colour, vein, and texture, which consumes large amounts of computational processing and are not efficient, especially in the Acer database with a high complexity structure of the leaves. This paper is focused on phenetic parts of the leaf which increases accuracy. Detecting the local maxima and local minima are done based on Centroid Contour Distance for Every Boundary Point, using north and south region to recognise the apex and base. Digital morphology is used to measure the leaf shape and the leaf margin. Centroid Contour Gradient is presented to extract the curvature of leaf apex and base. We analyse 32 leaf images of tropical plants and evaluated with two different datasets, Flavia, and Acer. The best accuracy obtained is 94.76% and 82.6% respectively. Experimental results show the effectiveness of the proposed technique without considering the commonly used features with high computational cost.

  3. An expert botanical feature extraction technique based on phenetic features for identifying plant species

    PubMed Central

    Fern, Bong Mei; Rahim, Mohd Shafry Mohd; Sulong, Ghazali; Baker, Thar; Tully, David

    2018-01-01

    In this paper, we present a new method to recognise the leaf type and identify plant species using phenetic parts of the leaf; lobes, apex and base detection. Most of the research in this area focuses on the popular features such as the shape, colour, vein, and texture, which consumes large amounts of computational processing and are not efficient, especially in the Acer database with a high complexity structure of the leaves. This paper is focused on phenetic parts of the leaf which increases accuracy. Detecting the local maxima and local minima are done based on Centroid Contour Distance for Every Boundary Point, using north and south region to recognise the apex and base. Digital morphology is used to measure the leaf shape and the leaf margin. Centroid Contour Gradient is presented to extract the curvature of leaf apex and base. We analyse 32 leaf images of tropical plants and evaluated with two different datasets, Flavia, and Acer. The best accuracy obtained is 94.76% and 82.6% respectively. Experimental results show the effectiveness of the proposed technique without considering the commonly used features with high computational cost. PMID:29420568

  4. Multi scales based sparse matrix spectral clustering image segmentation

    NASA Astrophysics Data System (ADS)

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

    2018-04-01

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

  5. Real-time evaluation of polyphenol oxidase (PPO) activity in lychee pericarp based on weighted combination of spectral data and image features as determined by fuzzy neural network.

    PubMed

    Yang, Yi-Chao; Sun, Da-Wen; Wang, Nan-Nan; Xie, Anguo

    2015-07-01

    A novel method of using hyperspectral imaging technique with the weighted combination of spectral data and image features by fuzzy neural network (FNN) was proposed for real-time prediction of polyphenol oxidase (PPO) activity in lychee pericarp. Lychee images were obtained by a hyperspectral reflectance imaging system operating in the range of 400-1000nm. A support vector machine-recursive feature elimination (SVM-RFE) algorithm was applied to eliminating variables with no or little information for the prediction from all bands, resulting in a reduced set of optimal wavelengths. Spectral information at the optimal wavelengths and image color features were then used respectively to develop calibration models for the prediction of PPO in pericarp during storage, and the results of two models were compared. In order to improve the prediction accuracy, a decision strategy was developed based on weighted combination of spectral data and image features, in which the weights were determined by FNN for a better estimation of PPO activity. The results showed that the combined decision model was the best among all of the calibration models, with high R(2) values of 0.9117 and 0.9072 and low RMSEs of 0.45% and 0.459% for calibration and prediction, respectively. These results demonstrate that the proposed weighted combined decision method has great potential for improving model performance. The proposed technique could be used for a better prediction of other internal and external quality attributes of fruits. Copyright © 2015 Elsevier B.V. All rights reserved.

  6. Type II Supernova Spectral Diversity. I. Observations, Sample Characterization, and Spectral Line Evolution

    NASA Astrophysics Data System (ADS)

    Gutiérrez, Claudia P.; Anderson, Joseph P.; Hamuy, Mario; Morrell, Nidia; González-Gaitan, Santiago; Stritzinger, Maximilian D.; Phillips, Mark M.; Galbany, Lluis; Folatelli, Gastón; Dessart, Luc; Contreras, Carlos; Della Valle, Massimo; Freedman, Wendy L.; Hsiao, Eric Y.; Krisciunas, Kevin; Madore, Barry F.; Maza, José; Suntzeff, Nicholas B.; Prieto, Jose Luis; González, Luis; Cappellaro, Enrico; Navarrete, Mauricio; Pizzella, Alessandro; Ruiz, Maria T.; Smith, R. Chris; Turatto, Massimo

    2017-11-01

    We present 888 visual-wavelength spectra of 122 nearby type II supernovae (SNe II) obtained between 1986 and 2009, and ranging between 3 and 363 days post-explosion. In this first paper, we outline our observations and data reduction techniques, together with a characterization based on the spectral diversity of SNe II. A statistical analysis of the spectral matching technique is discussed as an alternative to nondetection constraints for estimating SN explosion epochs. The time evolution of spectral lines is presented and analyzed in terms of how this differs for SNe of different photometric, spectral, and environmental properties: velocities, pseudo-equivalent widths, decline rates, magnitudes, time durations, and environment metallicity. Our sample displays a large range in ejecta expansion velocities, from ˜9600 to ˜1500 km s-1 at 50 days post-explosion with a median {{{H}}}α value of 7300 km s-1. This is most likely explained through differing explosion energies. Significant diversity is also observed in the absolute strength of spectral lines, characterized through their pseudo-equivalent widths. This implies significant diversity in both temperature evolution (linked to progenitor radius) and progenitor metallicity between different SNe II. Around 60% of our sample shows an extra absorption component on the blue side of the {{{H}}}α P-Cygni profile (“Cachito” feature) between 7 and 120 days since explosion. Studying the nature of Cachito, we conclude that these features at early times (before ˜35 days) are associated with Si II λ 6355, while past the middle of the plateau phase they are related to high velocity (HV) features of hydrogen lines. This paper includes data gathered with the 6.5 m Magellan Telescopes located at Las Campanas Observatory, Chile; and the Gemini Observatory, Cerro Pachon, Chile (Gemini Program GS-2008B-Q-56). Based on observations collected at the European Organisation for Astronomical Research in the Southern Hemisphere

  7. Infrared micro-spectral imaging: distinction of tissue types in axillary lymph node histology

    PubMed Central

    Bird, Benjamin; Miljkovic, Milos; Romeo, Melissa J; Smith, Jennifer; Stone, Nicholas; George, Michael W; Diem, Max

    2008-01-01

    Background Histopathologic evaluation of surgical specimens is a well established technique for disease identification, and has remained relatively unchanged since its clinical introduction. Although it is essential for clinical investigation, histopathologic identification of tissues remains a time consuming and subjective technique, with unsatisfactory levels of inter- and intra-observer discrepancy. A novel approach for histological recognition is to use Fourier Transform Infrared (FT-IR) micro-spectroscopy. This non-destructive optical technique can provide a rapid measurement of sample biochemistry and identify variations that occur between healthy and diseased tissues. The advantage of this method is that it is objective and provides reproducible diagnosis, independent of fatigue, experience and inter-observer variability. Methods We report a method for analysing excised lymph nodes that is based on spectral pathology. In spectral pathology, an unstained (fixed or snap frozen) tissue section is interrogated by a beam of infrared light that samples pixels of 25 μm × 25 μm in size. This beam is rastered over the sample, and up to 100,000 complete infrared spectra are acquired for a given tissue sample. These spectra are subsequently analysed by a diagnostic computer algorithm that is trained by correlating spectral and histopathological features. Results We illustrate the ability of infrared micro-spectral imaging, coupled with completely unsupervised methods of multivariate statistical analysis, to accurately reproduce the histological architecture of axillary lymph nodes. By correlating spectral and histopathological features, a diagnostic algorithm was trained that allowed both accurate and rapid classification of benign and malignant tissues composed within different lymph nodes. This approach was successfully applied to both deparaffinised and frozen tissues and indicates that both intra-operative and more conventional surgical specimens can be

  8. Optical spectral singularities as threshold resonances

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

    Mostafazadeh, Ali

    2011-04-15

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

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

    PubMed Central

    Mohamed, Moumouni Guero; Fan, Xuejun; Zhang, Guoqi; Pecht, Michael

    2017-01-01

    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. PMID:28773176

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

    PubMed

    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.

  11. Learning from patients: Identifying design features of medicines that cause medication use problems.

    PubMed

    Notenboom, Kim; Leufkens, Hubert Gm; Vromans, Herman; Bouvy, Marcel L

    2017-01-30

    Usability is a key factor in ensuring safe and efficacious use of medicines. However, several studies showed that people experience a variety of problems using their medicines. The purpose of this study was to identify design features of oral medicines that cause use problems among older patients in daily practice. A qualitative study with semi-structured interviews on the experiences of older people with the use of their medicines was performed (n=59). Information on practical problems, strategies to overcome these problems and the medicines' design features that caused these problems were collected. The practical problems and management strategies were categorised into 'use difficulties' and 'use errors'. A total of 158 use problems were identified, of which 45 were categorized as use difficulties and 113 as use error. Design features that contributed the most to the occurrence of use difficulties were the dimensions and surface texture of the dosage form (29.6% and 18.5%, respectively). Design features that contributed the most to the occurrence of use errors were the push-through force of blisters (22.1%) and tamper evident packaging (12.1%). These findings will help developers of medicinal products to proactively address potential usability issues with their medicines. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

  12. Newborn human brain identifies repeated auditory feature conjunctions of low sequential probability.

    PubMed

    Ruusuvirta, Timo; Huotilainen, Minna; Fellman, Vineta; Näätänen, Risto

    2004-11-01

    Natural environments are usually composed of multiple sources for sounds. The sounds might physically differ from one another only as feature conjunctions, and several of them might occur repeatedly in the short term. Nevertheless, the detection of rare sounds requires the identification of the repeated ones. Adults have some limited ability to effortlessly identify repeated sounds in such acoustically complex environments, but the developmental onset of this finite ability is unknown. Sleeping newborn infants were presented with a repeated tone carrying six frequent (P = 0.15 each) and six rare (P approximately 0.017 each) conjunctions of its frequency, intensity and duration. Event-related potentials recorded from the infants' scalp were found to shift in amplitude towards positive polarity selectively in response to rare conjunctions. This finding suggests that humans are relatively hard-wired to preattentively identify repeated auditory feature conjunctions even when such conjunctions occur rarely among other similar ones.

  13. Spectral features of LO phonon sidebands in luminescence of free excitons in GaN

    NASA Astrophysics Data System (ADS)

    Xu, S. J.; Li, G. Q.; Xiong, S.-J.; Tong, S. Y.; Che, C. M.; Liu, W.; Li, M. F.

    2005-06-01

    In the paper a combined experimental and theoretical investigation of the longitudinal optical phonon sidebands (PSBs) in the luminescence of free excitons in GaN at moderately high temperatures was reported. The spectral features, including line broadening, shift, and asymmetry of the one- and two-phonon PSBs, were revealed both experimentally and theoretically. It is found that the linewidth of the one-phonon PSB is surprisingly always larger than that of the two-phonon PSB in the interested temperature range. Moreover, the thermal broadening rates of the one- and two-phonon PSBs are considerably different. We adopted the Segall-Mahan theory [B. Segall and G. D. Mahan, Phys. Rev. 171, 935 (1968)] to compute the PSB spectra of the free excitons in GaN. Only one adjustable parameter, the effective mass of the holes, was used in the calculations. For the one-phonon PSB, an excellent agreement between theory and experiment is achieved when an adequate effective mass of the holes was used.

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

    NASA Astrophysics Data System (ADS)

    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.

  15. Microbiota fingerprints lose individually identifying features over time.

    PubMed

    Wilkins, David; Leung, Marcus H Y; Lee, Patrick K H

    2017-01-09

    Humans host individually unique skin microbiota, suggesting that microbiota traces transferred from skin to surfaces could serve as forensic markers analogous to fingerprints. While it is known that individuals leave identifiable microbiota traces on surfaces, it is not clear for how long these traces persist. Moreover, as skin and surface microbiota change with time, even persistent traces may lose their forensic potential as they would cease to resemble the microbiota of the person who left them. We followed skin and surface microbiota within households for four seasons to determine whether accurate microbiota-based matching of individuals to their households could be achieved across long time delays. While household surface microbiota traces could be matched to the correct occupant or occupants with 67% accuracy, accuracy decreased substantially when skin and surface samples were collected in different seasons, and particularly when surface samples were collected long after skin samples. Most OTUs persisted on skin or surfaces for less than one season, indicating that OTU loss was the major cause of decreased matching accuracy. OTUs that were more useful for individual identification persisted for less time and were less likely to be deposited from skin to surface, suggesting a trade-off between the longevity and identifying value of microbiota traces. While microbiota traces have potential forensic value, unlike fingerprints they are not static and may degrade in a way that preferentially erases features useful in identifying individuals.

  16. Application of musical timbre discrimination features to active sonar classification

    NASA Astrophysics Data System (ADS)

    Young, Victor W.; Hines, Paul C.; Pecknold, Sean

    2005-04-01

    In musical acoustics significant effort has been devoted to uncovering the physical basis of timbre perception. Most investigations into timbre rely on multidimensional scaling (MDS), in which different musical sounds are arranged as points in multidimensional space. The Euclidean distance between points corresponds to the perceptual distance between sounds and the multidimensional axes are linked to measurable properties of the sounds. MDS has identified numerous temporal and spectral features believed to be important to timbre perception. There is reason to believe that some of these features may have wider application in the disparate field of underwater acoustics, since anecdotal evidence suggests active sonar returns from metallic objects sound different than natural clutter returns when auralized by human operators. This is particularly encouraging since attempts to develop robust automatic classifiers capable of target-clutter discrimination over a wide range of operational conditions have met with limited success. Spectral features relevant to target-clutter discrimination are believed to include click-pitch and envelope irregularity; relevant temporal features are believed to include duration, sub-band attack/decay time, and time separation pitch. Preliminary results from an investigation into the role of these timbre features in target-clutter discrimination will be presented. [Work supported by NSERC and GDC.

  17. The Mysterious 6565 Å Absorption Feature of the Galactic Halo

    NASA Astrophysics Data System (ADS)

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

    2017-12-01

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

  18. Raman spectroscopy identifies radiation response in human non-small cell lung cancer xenografts

    NASA Astrophysics Data System (ADS)

    Harder, Samantha J.; Isabelle, Martin; Devorkin, Lindsay; Smazynski, Julian; Beckham, Wayne; Brolo, Alexandre G.; Lum, Julian J.; Jirasek, Andrew

    2016-02-01

    External beam radiation therapy is a standard form of treatment for numerous cancers. Despite this, there are no approved methods to account for patient specific radiation sensitivity. In this report, Raman spectroscopy (RS) was used to identify radiation-induced biochemical changes in human non-small cell lung cancer xenografts. Chemometric analysis revealed unique radiation-related Raman signatures that were specific to nucleic acid, lipid, protein and carbohydrate spectral features. Among these changes was a dramatic shift in the accumulation of glycogen spectral bands for doses of 5 or 15 Gy when compared to unirradiated tumours. When spatial mapping was applied in this analysis there was considerable variability as we found substantial intra- and inter-tumour heterogeneity in the distribution of glycogen and other RS spectral features. Collectively, these data provide unique insight into the biochemical response of tumours, irradiated in vivo, and demonstrate the utility of RS for detecting distinct radiobiological responses in human tumour xenografts.

  19. INSTRUMENTS AND METHODS OF INVESTIGATION: Spectral and spectral-frequency methods of investigating atmosphereless bodies of the Solar system

    NASA Astrophysics Data System (ADS)

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

    2007-06-01

    A method of reflectance spectrophotometry of atmosphereless bodies of the Solar system, its specificity, and the means of eliminating basic spectral noise are considered. As a development, joining the method of reflectance spectrophotometry with the frequency analysis of observational data series is proposed. The combined spectral-frequency method allows identification of formations with distinctive spectral features, and estimations of their sizes and distribution on the surface of atmospherelss celestial bodies. As applied to investigations of asteroids 21 Lutetia and 4 Vesta, the spectral frequency method has given us the possibility of obtaining fundamentally new information about minor planets.

  20. Using spectral information in forensic imaging.

    PubMed

    Miskelly, Gordon M; Wagner, John H

    2005-12-20

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

  1. Spectral features based tea garden extraction from digital orthophoto maps

    NASA Astrophysics Data System (ADS)

    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.

  2. Color heterogeneity of the surface of Phobos - Relationships to geologic features and comparison to meteorite analogs

    NASA Technical Reports Server (NTRS)

    Murchie, Scott L.; Britt, Daniel T.; Head, James W.; Pratt, Stephen F.; Fisher, Paul C.

    1991-01-01

    Color ratio images created from multispectral observations of Phobos are analyzed in order to characterize the spectral properties of Phobos' surface, to assess their spatial distributions and relationships with geologic features, and to compare Phobos' surface materials with possible meteorite analogs. Data calibration and processing is briefly discussed, and the observed spectral properties of Phobos and their lateral variations are examined. Attention is then given to the color properties of different types of impact craters, the origin of lateral variations in surface color, the relation between the spatial distribution of color properties and independently identifiable geologic features, and the relevance of color variation spatial distribution to the origin of the grooves.

  3. Biologically-inspired data decorrelation for hyper-spectral imaging

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

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

  4. Low complexity feature extraction for classification of harmonic signals

    NASA Astrophysics Data System (ADS)

    William, Peter E.

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

  5. Combining random forest and 2D correlation analysis to identify serum spectral signatures for neuro-oncology.

    PubMed

    Smith, Benjamin R; Ashton, Katherine M; Brodbelt, Andrew; Dawson, Timothy; Jenkinson, Michael D; Hunt, Neil T; Palmer, David S; Baker, Matthew J

    2016-06-07

    Fourier transform infrared (FTIR) spectroscopy has long been established as an analytical technique for the measurement of vibrational modes of molecular systems. More recently, FTIR has been used for the analysis of biofluids with the aim of becoming a tool to aid diagnosis. For the clinician, this represents a convenient, fast, non-subjective option for the study of biofluids and the diagnosis of disease states. The patient also benefits from this method, as the procedure for the collection of serum is much less invasive and stressful than traditional biopsy. This is especially true of patients in whom brain cancer is suspected. A brain biopsy is very unpleasant for the patient, potentially dangerous and can occasionally be inconclusive. We therefore present a method for the diagnosis of brain cancer from serum samples using FTIR and machine learning techniques. The scope of the study involved 433 patients from whom were collected 9 spectra each in the range 600-4000 cm(-1). To begin the development of the novel method, various pre-processing steps were investigated and ranked in terms of final accuracy of the diagnosis. Random forest machine learning was utilised as a classifier to separate patients into cancer or non-cancer categories based upon the intensities of wavenumbers present in their spectra. Generalised 2D correlational analysis was then employed to further augment the machine learning, and also to establish spectral features important for the distinction between cancer and non-cancer serum samples. Using these methods, sensitivities of up to 92.8% and specificities of up to 91.5% were possible. Furthermore, ratiometrics were also investigated in order to establish any correlations present in the dataset. We show a rapid, computationally light, accurate, statistically robust methodology for the identification of spectral features present in differing disease states. With current advances in IR technology, such as the development of rapid discrete

  6. a UV Spectral Library of Metal-Poor Massive Stars

    NASA Astrophysics Data System (ADS)

    Robert, Carmelle

    1994-01-01

    We propose to use the FOS to build a snapshot library of UV spectra of a sample of about 50 metal-poor massive stars located in the Magellanic Clouds. The majority of libraries already existing contains spectra of hot stars with chemical abundances close to solar. The high spectral resolution achieves with the FOS will be a major factor for the uniqueness of this new library. UV spectral libraries represent fundamental tools for the study of the massive star populations of young star-forming regions. Massive stars, which are impossible to identify directly in the optical-IR part of a composite spectrum, display on the other hand key signatures in the UV region. These signatures are mainly broad, metallicity dependent spectral features formed in the hot star winds. They require a high spectral resolution (of the order of 200-300 km/s) for an adequate study. A spectral library of metal-poor massive stars represents also a unique source of data for a stellar atmosphere analysis. Within less then 10 min we will obtain a high signal-to-noise ratio of at least 30. Finally, since short exposure times are possible, this proposal makes extremely good use of the capabilities of HST. We designed an observing strategy which yields a maximum scientific return at a minimum cost of spacecraft time.

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

    NASA Astrophysics Data System (ADS)

    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.

  8. [Review of digital ground object spectral library].

    PubMed

    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.

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

    NASA Astrophysics Data System (ADS)

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

    2015-11-01

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

  10. Adventitious sounds identification and extraction using temporal-spectral dominance-based features.

    PubMed

    Jin, Feng; Krishnan, Sridhar Sri; Sattar, Farook

    2011-11-01

    Respiratory sound (RS) signals carry significant information about the underlying functioning of the pulmonary system by the presence of adventitious sounds (ASs). Although many studies have addressed the problem of pathological RS classification, only a limited number of scientific works have focused on the analysis of the evolution of symptom-related signal components in joint time-frequency (TF) plane. This paper proposes a new signal identification and extraction method for various ASs based on instantaneous frequency (IF) analysis. The presented TF decomposition method produces a noise-resistant high definition TF representation of RS signals as compared to the conventional linear TF analysis methods, yet preserving the low computational complexity as compared to those quadratic TF analysis methods. The discarded phase information in conventional spectrogram has been adopted for the estimation of IF and group delay, and a temporal-spectral dominance spectrogram has subsequently been constructed by investigating the TF spreads of the computed time-corrected IF components. The proposed dominance measure enables the extraction of signal components correspond to ASs from noisy RS signal at high noise level. A new set of TF features has also been proposed to quantify the shapes of the obtained TF contours, and therefore strongly, enhances the identification of multicomponents signals such as polyphonic wheezes. An overall accuracy of 92.4±2.9% for the classification of real RS recordings shows the promising performance of the presented method.

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

    PubMed Central

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

    2015-01-01

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

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

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

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

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

  13. Spectral imaging: principles and applications.

    PubMed

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

    2006-08-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-12-01

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

  15. Single-sweep spectral analysis of contact heat evoked potentials: a novel approach to identify altered cortical processing after morphine treatment

    PubMed Central

    Hansen, Tine M; Graversen, Carina; Frøkjær, Jens B; Olesen, Anne E; Valeriani, Massimiliano; Drewes, Asbjørn M

    2015-01-01

    Aims The cortical response to nociceptive thermal stimuli recorded as contact heat evoked potentials (CHEPs) may be altered by morphine. However, previous studies have averaged CHEPs over multiple stimuli, which are confounded by jitter between sweeps. Thus, the aim was to assess single-sweep characteristics to identify alterations induced by morphine. Methods In a crossover study 15 single-sweep CHEPs were analyzed from 62 electroencephalography electrodes in 26 healthy volunteers before and after administration of morphine or placebo. Each sweep was decomposed by a continuous wavelet transform to obtain normalized spectral indices in the delta (0.5–4 Hz), theta (4–8 Hz), alpha (8–12 Hz), beta (12–32 Hz) and gamma (32–80 Hz) bands. The average distribution over all sweeps and channels was calculated for the four recordings for each volunteer, and the two recordings before treatments were assessed for reproducibility. Baseline corrected spectral indices after morphine and placebo treatments were compared to identify alterations induced by morphine. Results Reproducibility between baseline CHEPs was demonstrated. As compared with placebo, morphine decreased the spectral indices in the delta and theta bands by 13% (P = 0.04) and 9% (P = 0.007), while the beta and gamma bands were increased by 10% (P = 0.006) and 24% (P = 0.04). Conclusion The decreases in the delta and theta band are suggested to represent a decrease in the pain specific morphology of the CHEPs, which indicates a diminished pain response after morphine administration. Hence, assessment of spectral indices in single-sweep CHEPs can be used to study cortical mechanisms induced by morphine treatment. PMID:25556985

  16. Examination of the spectral features of vegetation in 1987 AVIRIS data

    NASA Technical Reports Server (NTRS)

    Elvidge, Christopher D.

    1988-01-01

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

  17. Microscopic and macroscopic spectral peculiarities of cutaneous tumours

    NASA Astrophysics Data System (ADS)

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

    2017-12-01

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

  18. Observational Signatures of Black Holes: Spectral and Temporal Features of XTE J1550-564

    NASA Technical Reports Server (NTRS)

    Titarchuk, Lev; Shrader, C. R.; White, Nicholas E. (Technical Monitor)

    2002-01-01

    The theoretical predictions of the converging inflow, or Bulk-Motion Comptonization model are discussed and some predictions are compared to X- and gamma-ray observations of the high-soft state of Galactic black hole candidate XTE J1550+564. The approx. 10(exp 2)-Hz QPO phenomenon tends to be detected in the high-state at times when the bolometric luminosity surges and the hard-powerlaw spectral component is dominant. Furthermore, the power in these features increases with energy. We offer interpretation of this phenomenon, as oscillations of the innermost part of the accretion disk, which in turn supplies the seed photons for the converging inflow where the hard power-law is formed through Bulk Motion Comptonization (BMC). We further argue that the noted lack of coherence between intensity variations of the high-soft-state low and high energy bands is a natural consequence of our model, and that a natural explanation for the observed hard and soft lag phenomenon is offered. In addition, we address some criticisms of the BMC model supporting our claims with observational results.

  19. Spectral-clustering approach to Lagrangian vortex detection.

    PubMed

    Hadjighasem, Alireza; Karrasch, Daniel; Teramoto, Hiroshi; Haller, George

    2016-06-01

    One of the ubiquitous features of real-life turbulent flows is the existence and persistence of coherent vortices. Here we show that such coherent vortices can be extracted as clusters of Lagrangian trajectories. We carry out the clustering on a weighted graph, with the weights measuring pairwise distances of fluid trajectories in the extended phase space of positions and time. We then extract coherent vortices from the graph using tools from spectral graph theory. Our method locates all coherent vortices in the flow simultaneously, thereby showing high potential for automated vortex tracking. We illustrate the performance of this technique by identifying coherent Lagrangian vortices in several two- and three-dimensional flows.

  20. Terrain Extraction by Integrating Terrestrial Laser Scanner Data and Spectral Information

    NASA Astrophysics Data System (ADS)

    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.

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

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

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

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

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

    NASA Astrophysics Data System (ADS)

    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.

  3. The Research of Spectral Reconstruction for Large Aperture Static Imaging Spectrometer

    NASA Astrophysics Data System (ADS)

    Lv, H.; Lee, Y.; Liu, R.; Fan, C.; Huang, Y.

    2018-04-01

    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.

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

    NASA Astrophysics Data System (ADS)

    Zhang, Qiaoping

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

  5. Spectral Data Reduction via Wavelet Decomposition

    NASA Technical Reports Server (NTRS)

    Kaewpijit, S.; LeMoigne, J.; El-Ghazawi, T.; Rood, Richard (Technical Monitor)

    2002-01-01

    The greatest advantage gained from hyperspectral imagery is that narrow spectral features can be used to give more information about materials than was previously possible with broad-band multispectral imagery. For many applications, the new larger data volumes from such hyperspectral sensors, however, present a challenge for traditional processing techniques. For example, the actual identification of each ground surface pixel by its corresponding reflecting spectral signature is still one of the most difficult challenges in the exploitation of this advanced technology, because of the immense volume of data collected. Therefore, conventional classification methods require a preprocessing step of dimension reduction to conquer the so-called "curse of dimensionality." Spectral data reduction using wavelet decomposition could be useful, as it does not only reduce the data volume, but also preserves the distinctions between spectral signatures. This characteristic is related to the intrinsic property of wavelet transforms that preserves high- and low-frequency features during the signal decomposition, therefore preserving peaks and valleys found in typical spectra. When comparing to the most widespread dimension reduction technique, the Principal Component Analysis (PCA), and looking at the same level of compression rate, we show that Wavelet Reduction yields better classification accuracy, for hyperspectral data processed with a conventional supervised classification such as a maximum likelihood method.

  6. The Copernicus ultraviolet spectral atlas of Sirius

    NASA Technical Reports Server (NTRS)

    Rogerson, John B., Jr.

    1987-01-01

    A near-ultraviolet spectral atlas for the A1 V star Alpha CMa (Sirius) has been prepared from data taken by the Princeton spectrometer aboard the Copernicus satellite. The spectral region from 1649 to 3170 A has been scanned with a resolution of 0.1 A. The atlas is presented in graphs, and line identifications for the absorption features have been tabulated.

  7. Identification of spectral units on Phoebe

    USGS Publications Warehouse

    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.

  8. M dwarf spectra from 0.6 to 1.5 micron - A spectral sequence, model atmosphere fitting, and the temperature scale

    NASA Technical Reports Server (NTRS)

    Kirkpatrick, J. D.; Kelly, Douglas M.; Rieke, George H.; Liebert, James; Allard, France; Wehrse, Rainer

    1993-01-01

    Red/infrared (0.6-1.5 micron) spectra are presented for a sequence of well-studied M dwarfs ranging from M2 through M9. A variety of temperature-sensitive features useful for spectral classification are identified. Using these features, the spectral data are compared to recent theoretical models, from which a temperature scale is assigned. The red portion of the model spectra provide reasonably good fits for dwarfs earlier than M6. For layer types, the infrared region provides a more reliable fit to the observations. In each case, the wavelength region used includes the broad peak of the energy distribution. For a given spectral type, the derived temperature sequence assigns higher temperatures than have earlier studies - the difference becoming more pronounced at lower luminosities. The positions of M dwarfs on the H-R diagram are, as a result, in closer agreement with theoretical tracks of the lower main sequence.

  9. Detailed Spectral Analysis of the 260 ks XMM-Newton Data of 1E 1207.4-5209 and Significance of a 2.1 keV Absorption Feature

    NASA Astrophysics Data System (ADS)

    Mori, Kaya; Chonko, James C.; Hailey, Charles J.

    2005-10-01

    We have reanalyzed the 260 ks XMM-Newton observation of 1E 1207.4-5209. There are several significant improvements over previous work. First, a much broader range of physically plausible spectral models was used. Second, we have used a more rigorous statistical analysis. The standard F-distribution was not employed, but rather the exact finite statistics F-distribution was determined by Monte Carlo simulations. This approach was motivated by the recent work of Protassov and coworkers and Freeman and coworkers. They demonstrated that the standard F-distribution is not even asymptotically correct when applied to assess the significance of additional absorption features in a spectrum. With our improved analysis we do not find a third and fourth spectral feature in 1E 1207.4-5209 but only the two broad absorption features previously reported. Two additional statistical tests, one line model dependent and the other line model independent, confirmed our modified F-test analysis. For all physically plausible continuum models in which the weak residuals are strong enough to fit, the residuals occur at the instrument Au M edge. As a sanity check we confirmed that the residuals are consistent in strength and position with the instrument Au M residuals observed in 3C 273.

  10. Multiscale Feature Analysis of Salivary Gland Branching Morphogenesis

    PubMed Central

    Baydil, Banu; Daley, William P.; Larsen, Melinda; Yener, Bülent

    2012-01-01

    Pattern formation in developing tissues involves dynamic spatio-temporal changes in cellular organization and subsequent evolution of functional adult structures. Branching morphogenesis is a developmental mechanism by which patterns are generated in many developing organs, which is controlled by underlying molecular pathways. Understanding the relationship between molecular signaling, cellular behavior and resulting morphological change requires quantification and categorization of the cellular behavior. In this study, tissue-level and cellular changes in developing salivary gland in response to disruption of ROCK-mediated signaling by are modeled by building cell-graphs to compute mathematical features capturing structural properties at multiple scales. These features were used to generate multiscale cell-graph signatures of untreated and ROCK signaling disrupted salivary gland organ explants. From confocal images of mouse submandibular salivary gland organ explants in which epithelial and mesenchymal nuclei were marked, a multiscale feature set capturing global structural properties, local structural properties, spectral, and morphological properties of the tissues was derived. Six feature selection algorithms and multiway modeling of the data was performed to identify distinct subsets of cell graph features that can uniquely classify and differentiate between different cell populations. Multiscale cell-graph analysis was most effective in classification of the tissue state. Cellular and tissue organization, as defined by a multiscale subset of cell-graph features, are both quantitatively distinct in epithelial and mesenchymal cell types both in the presence and absence of ROCK inhibitors. Whereas tensor analysis demonstrate that epithelial tissue was affected the most by inhibition of ROCK signaling, significant multiscale changes in mesenchymal tissue organization were identified with this analysis that were not identified in previous biological studies. We

  11. Hyperspectral feature mapping classification based on mathematical morphology

    NASA Astrophysics Data System (ADS)

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

    2016-03-01

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

  12. Algorithms for Spectral Decomposition with Applications to Optical Plume Anomaly Detection

    NASA Technical Reports Server (NTRS)

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

    2008-01-01

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

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

    NASA Technical Reports Server (NTRS)

    Solomon, J. E.

    1994-01-01

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

  14. Spectral identification/elimination of molecular species in spacecraft glow

    NASA Technical Reports Server (NTRS)

    Green, B. D.; Marinelli, W. J.; Rawlins, W. T.

    1985-01-01

    Computer models of molecular electronic and vibrational emission intensities were developed. Known radiative emission rates (Einstein coefficients) permit the determination of relative excited state densities from spectral intensities. These codes were applied to the published spectra of glow above shuttle surface and to the Spacelab 1 results of Torr and Torr. The theoretical high-resolution spectra were convolved with the appropriate instrumental slit functions to allow accurate comparison with data. The published spacelab spectrum is complex but N2+ Meinel emission can be clearly identified in the ram spectrum. M2 First Positive emission does not correlate well with observed features, nor does the CN Red System. Spectral overlay comparisons are presented. The spectrum of glow above shuttle surfaces, in contrast to the ISO data, is not highly structured. Diatomic molecular emission was matched to the observed spectral shape. Source excitation mechanisms such as (oxygen atom)-(surface species) reaction product chemiluminescence, surface recombination, or resonance fluorescent re-emission will be discussed for each tentative assignment. These assignments are the necessary first analytical step toward mechanism identification. Different glow mechanisms will occur above surfaces under different orbital conditions.

  15. A P-Norm Robust Feature Extraction Method for Identifying Differentially Expressed Genes

    PubMed Central

    Liu, Jian; Liu, Jin-Xing; Gao, Ying-Lian; Kong, Xiang-Zhen; Wang, Xue-Song; Wang, Dong

    2015-01-01

    In current molecular biology, it becomes more and more important to identify differentially expressed genes closely correlated with a key biological process from gene expression data. In this paper, based on the Schatten p-norm and Lp-norm, a novel p-norm robust feature extraction method is proposed to identify the differentially expressed genes. In our method, the Schatten p-norm is used as the regularization function to obtain a low-rank matrix and the Lp-norm is taken as the error function to improve the robustness to outliers in the gene expression data. The results on simulation data show that our method can obtain higher identification accuracies than the competitive methods. Numerous experiments on real gene expression data sets demonstrate that our method can identify more differentially expressed genes than the others. Moreover, we confirmed that the identified genes are closely correlated with the corresponding gene expression data. PMID:26201006

  16. A P-Norm Robust Feature Extraction Method for Identifying Differentially Expressed Genes.

    PubMed

    Liu, Jian; Liu, Jin-Xing; Gao, Ying-Lian; Kong, Xiang-Zhen; Wang, Xue-Song; Wang, Dong

    2015-01-01

    In current molecular biology, it becomes more and more important to identify differentially expressed genes closely correlated with a key biological process from gene expression data. In this paper, based on the Schatten p-norm and Lp-norm, a novel p-norm robust feature extraction method is proposed to identify the differentially expressed genes. In our method, the Schatten p-norm is used as the regularization function to obtain a low-rank matrix and the Lp-norm is taken as the error function to improve the robustness to outliers in the gene expression data. The results on simulation data show that our method can obtain higher identification accuracies than the competitive methods. Numerous experiments on real gene expression data sets demonstrate that our method can identify more differentially expressed genes than the others. Moreover, we confirmed that the identified genes are closely correlated with the corresponding gene expression data.

  17. Classification method, spectral diversity, band combination and accuracy assessment evaluation for urban feature detection

    NASA Astrophysics Data System (ADS)

    Erener, A.

    2013-04-01

    Automatic extraction of urban features from high resolution satellite images is one of the main applications in remote sensing. It is useful for wide scale applications, namely: urban planning, urban mapping, disaster management, GIS (geographic information systems) updating, and military target detection. One common approach to detecting urban features from high resolution images is to use automatic classification methods. This paper has four main objectives with respect to detecting buildings. The first objective is to compare the performance of the most notable supervised classification algorithms, including the maximum likelihood classifier (MLC) and the support vector machine (SVM). In this experiment the primary consideration is the impact of kernel configuration on the performance of the SVM. The second objective of the study is to explore the suitability of integrating additional bands, namely first principal component (1st PC) and the intensity image, for original data for multi classification approaches. The performance evaluation of classification results is done using two different accuracy assessment methods: pixel based and object based approaches, which reflect the third aim of the study. The objective here is to demonstrate the differences in the evaluation of accuracies of classification methods. Considering consistency, the same set of ground truth data which is produced by labeling the building boundaries in the GIS environment is used for accuracy assessment. Lastly, the fourth aim is to experimentally evaluate variation in the accuracy of classifiers for six different real situations in order to identify the impact of spatial and spectral diversity on results. The method is applied to Quickbird images for various urban complexity levels, extending from simple to complex urban patterns. The simple surface type includes a regular urban area with low density and systematic buildings with brick rooftops. The complex surface type involves almost all

  18. An Extended Spectral-Spatial Classification Approach for Hyperspectral Data

    NASA Astrophysics Data System (ADS)

    Akbari, D.

    2017-11-01

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

  19. Using fragmentation trees and mass spectral trees for identifying unknown compounds in metabolomics.

    PubMed

    Vaniya, Arpana; Fiehn, Oliver

    2015-06-01

    Identification of unknown metabolites is the bottleneck in advancing metabolomics, leaving interpretation of metabolomics results ambiguous. The chemical diversity of metabolism is vast, making structure identification arduous and time consuming. Currently, comprehensive analysis of mass spectra in metabolomics is limited to library matching, but tandem mass spectral libraries are small compared to the large number of compounds found in the biosphere, including xenobiotics. Resolving this bottleneck requires richer data acquisition and better computational tools. Multi-stage mass spectrometry (MSn) trees show promise to aid in this regard. Fragmentation trees explore the fragmentation process, generate fragmentation rules and aid in sub-structure identification, while mass spectral trees delineate the dependencies in multi-stage MS of collision-induced dissociations. This review covers advancements over the past 10 years as a tool for metabolite identification, including algorithms, software and databases used to build and to implement fragmentation trees and mass spectral annotations.

  20. Identifying marker genes in transcription profiling data using a mixture of feature relevance experts.

    PubMed

    Chow, M L; Moler, E J; Mian, I S

    2001-03-08

    Transcription profiling experiments permit the expression levels of many genes to be measured simultaneously. Given profiling data from two types of samples, genes that most distinguish the samples (marker genes) are good candidates for subsequent in-depth experimental studies and developing decision support systems for diagnosis, prognosis, and monitoring. This work proposes a mixture of feature relevance experts as a method for identifying marker genes and illustrates the idea using published data from samples labeled as acute lymphoblastic and myeloid leukemia (ALL, AML). A feature relevance expert implements an algorithm that calculates how well a gene distinguishes samples, reorders genes according to this relevance measure, and uses a supervised learning method [here, support vector machines (SVMs)] to determine the generalization performances of different nested gene subsets. The mixture of three feature relevance experts examined implement two existing and one novel feature relevance measures. For each expert, a gene subset consisting of the top 50 genes distinguished ALL from AML samples as completely as all 7,070 genes. The 125 genes at the union of the top 50s are plausible markers for a prototype decision support system. Chromosomal aberration and other data support the prediction that the three genes at the intersection of the top 50s, cystatin C, azurocidin, and adipsin, are good targets for investigating the basic biology of ALL/AML. The same data were employed to identify markers that distinguish samples based on their labels of T cell/B cell, peripheral blood/bone marrow, and male/female. Selenoprotein W may discriminate T cells from B cells. Results from analysis of transcription profiling data from tumor/nontumor colon adenocarcinoma samples support the general utility of the aforementioned approach. Theoretical issues such as choosing SVM kernels and their parameters, training and evaluating feature relevance experts, and the impact of

  1. The value of anthropometric indices for identifying women with features of metabolic syndrome

    USDA-ARS?s Scientific Manuscript database

    BMI is a widely used anthropometric measure for identifying CVD and metabolic syndrome (MetS) risk. Two new anthropometric indices are A Body Shape Index (ABSI) and Body Roundness Index (BRI) that may provide better correlations to features of MetS. Methods: Subject data were obtained from 91 over...

  2. The Copernicus ultraviolet spectral atlas of Vega

    NASA Technical Reports Server (NTRS)

    Rogerson, John B., Jr.

    1989-01-01

    A near-ultraviolet spectral atlas for the A0 V star Alpha Lyr (Vega) has been prepared from data taken by the Princeton spectrometer aboard the Copernicus satellite. The spectral region from 2000 to 3187 A has been scanned with a resolution of 0.1 A. The atlas is presented in graphs with a normalized continuum, and an identification table for the absorption features has been prepared.

  3. New Infrared Emission Features and Spectral Variations in Ngc 7023

    NASA Technical Reports Server (NTRS)

    Werner, M. W.; Uchida, K. I.; Sellgren, K.; Marengo, M.; Gordon, K. D.; Morris, P. W.; Houck, J. R.; Stansberry, J. A.

    2004-01-01

    We observed the reflection nebula NGC 7023, with the Short-High module and the long-slit Short-Low and Long-Low modules of the Infrared Spectrograph on the Spitzer Space Telescope. We also present Infrared Array Camera (IRAC) and Multiband Imaging Photometer for Spitzer (MIPS) images of NGC 7023 at 3.6, 4.5, 8.0, and 24 m. We observe the aromatic emission features (AEFs) at 6.2, 7.7, 8.6, 11.3, and 12.7 m, plus a wealth of weaker features. We find new unidentified interstellar emission features at 6.7, 10.1, 15.8, 17.4, and 19.0 m. Possible identifications include aromatic hydrocarbons or nanoparticles of unknown mineralogy. We see variations in relative feature strengths, central wavelengths, and feature widths, in the AEFs and weaker emission features, depending on both distance from the star and nebular position (southeast vs. northwest).

  4. Spectral characterization of natural backgrounds

    NASA Astrophysics Data System (ADS)

    Winkelmann, Max

    2017-10-01

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

  5. Combination of Multiple Spectral Libraries Improves the Current Search Methods Used to Identify Missing Proteins in the Chromosome-Centric Human Proteome Project.

    PubMed

    Cho, Jin-Young; Lee, Hyoung-Joo; Jeong, Seul-Ki; Kim, Kwang-Youl; Kwon, Kyung-Hoon; Yoo, Jong Shin; Omenn, Gilbert S; Baker, Mark S; Hancock, William S; Paik, Young-Ki

    2015-12-04

    Approximately 2.9 billion long base-pair human reference genome sequences are known to encode some 20 000 representative proteins. However, 3000 proteins, that is, ~15% of all proteins, have no or very weak proteomic evidence and are still missing. Missing proteins may be present in rare samples in very low abundance or be only temporarily expressed, causing problems in their detection and protein profiling. In particular, some technical limitations cause missing proteins to remain unassigned. For example, current mass spectrometry techniques have high limits and error rates for the detection of complex biological samples. An insufficient proteome coverage in a reference sequence database and spectral library also raises major issues. Thus, the development of a better strategy that results in greater sensitivity and accuracy in the search for missing proteins is necessary. To this end, we used a new strategy, which combines a reference spectral library search and a simulated spectral library search, to identify missing proteins. We built the human iRefSPL, which contains the original human reference spectral library and additional peptide sequence-spectrum match entries from other species. We also constructed the human simSPL, which contains the simulated spectra of 173 907 human tryptic peptides determined by MassAnalyzer (version 2.3.1). To prove the enhanced analytical performance of the combination of the human iRefSPL and simSPL methods for the identification of missing proteins, we attempted to reanalyze the placental tissue data set (PXD000754). The data from each experiment were analyzed using PeptideProphet, and the results were combined using iProphet. For the quality control, we applied the class-specific false-discovery rate filtering method. All of the results were filtered at a false-discovery rate of <1% at the peptide and protein levels. The quality-controlled results were then cross-checked with the neXtProt DB (2014-09-19 release). The two

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

    PubMed Central

    Chen, Hongtao; Digman, Michelle A.

    2015-01-01

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

  7. On the Spectral Variance of MGS TES Spectra in the 300-500 cm-1 Range

    NASA Astrophysics Data System (ADS)

    Altieri, F.; Bellucci, G.

    2001-11-01

    The Thermal Emission Spectrometer (TES) aboard NASA mission Mars Global Surveyor (MGS) is collecting 200 - 1600 cm-1 thermal emission spectra since September 1997. The principal purpose of TES is to determine and map the Mars surface composition. Spectral features directly ascribable to surface minerals have been identified in the 300 - 500 cm-1 spectral range. Outcrops of hematite have been localized in Sinus Meridiani, Aram Chaos and Valles Marineris [1, 2] and areas with olivine have been individuated in Nili Fossae and in other limited regions [3]. On the other hand, TES spectra show, in general, significant variance between 300 and 500 cm-1; this variance is not directly attributable to surface mineralogical components. In this study we report some examples of spectra with typical hematite and olivine bands and spectra with a different spectral contrast. The spectral masking effect of a dust layer is suggested to explain this behaviour. Spectra characterized by hematite features have been localized also inside a crater near Baldet Crater. The MOC narrow-angle image M02-0039 acquired on the same area shows dark layers at the crater bottom. References: [1] Christensen P. R., et al., JGR, 105, 9623-9642, 2000. [2] Christensen P. R., et al., JGR, in press., 2001. [3] Hoefen T. M. and Clark R. N., LPS XXXII, 2049, 2001.

  8. Identifying Features of Bodily Expression As Indicators of Emotional Experience during Multimedia Learning

    PubMed Central

    Riemer, Valentin; Frommel, Julian; Layher, Georg; Neumann, Heiko; Schrader, Claudia

    2017-01-01

    The importance of emotions experienced by learners during their interaction with multimedia learning systems, such as serious games, underscores the need to identify sources of information that allow the recognition of learners’ emotional experience without interrupting the learning process. Bodily expression is gaining in attention as one of these sources of information. However, to date, the question of how bodily expression can convey different emotions has largely been addressed in research relying on acted emotion displays. Following a more contextualized approach, the present study aims to identify features of bodily expression (i.e., posture and activity of the upper body and the head) that relate to genuine emotional experience during interaction with a serious game. In a multimethod approach, 70 undergraduates played a serious game relating to financial education while their bodily expression was captured using an off-the-shelf depth-image sensor (Microsoft Kinect). In addition, self-reports of experienced enjoyment, boredom, and frustration were collected repeatedly during gameplay, to address the dynamic changes in emotions occurring in educational tasks. Results showed that, firstly, the intensities of all emotions indeed changed significantly over the course of the game. Secondly, by using generalized estimating equations, distinct features of bodily expression could be identified as significant indicators for each emotion under investigation. A participant keeping their head more turned to the right was positively related to frustration being experienced, whereas keeping their head more turned to the left was positively related to enjoyment. Furthermore, having their upper body positioned more closely to the gaming screen was also positively related to frustration. Finally, increased activity of a participant’s head emerged as a significant indicator of boredom being experienced. These results confirm the value of bodily expression as an indicator

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2007-12-01

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

  11. The Problem of Spectral Mimicry of Supergiants

    NASA Astrophysics Data System (ADS)

    Klochkova, V. G.; Chentsov, E. L.

    2018-01-01

    The phenomenon of spectral mimicry refers to the fact that hypergiants and post-AGB supergiants—stars of different masses in fundamentally different stages of their evolution—have similar optical spectra, and also share certain other characteristics (unstable extended atmospheres, expanding dust-gas envelopes, high IR excesses). As a consequence, it is not always possible to distinguish post-AGB stars from hypergiants based on individual spectral observations in the optical. Examples of spectral mimicry are analyzed using uniform, high-quality spectral material obtained on the 6-m telescope of the Special Astrophysical Observatory in the course of long-term monitoring of high-luminosity stars. It is shown that unambiguously resolving the mimicry problem for individual stars requires the determination of a whole set of parameters: luminosity, wind parameters, spectral energy distribution, spectral features, velocity field in the atmosphere and circumstellar medium, behavior of the parameters with time, and the chemical composition of the atmosphere.

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

    NASA Astrophysics Data System (ADS)

    Paul, Subir; Nagesh Kumar, D.

    2018-04-01

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

  13. USGS Digital Spectral Library splib05a

    USGS Publications Warehouse

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

    2003-01-01

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

  14. Feature genes in metastatic breast cancer identified by MetaDE and SVM classifier methods.

    PubMed

    Tuo, Youlin; An, Ning; Zhang, Ming

    2018-03-01

    The aim of the present study was to investigate the feature genes in metastatic breast cancer samples. A total of 5 expression profiles of metastatic breast cancer samples were downloaded from the Gene Expression Omnibus database, which were then analyzed using the MetaQC and MetaDE packages in R language. The feature genes between metastasis and non‑metastasis samples were screened under the threshold of P<0.05. Based on the protein‑protein interactions (PPIs) in the Biological General Repository for Interaction Datasets, Human Protein Reference Database and Biomolecular Interaction Network Database, the PPI network of the feature genes was constructed. The feature genes identified by topological characteristics were then used for support vector machine (SVM) classifier training and verification. The accuracy of the SVM classifier was then evaluated using another independent dataset from The Cancer Genome Atlas database. Finally, function and pathway enrichment analyses for genes in the SVM classifier were performed. A total of 541 feature genes were identified between metastatic and non‑metastatic samples. The top 10 genes with the highest betweenness centrality values in the PPI network of feature genes were Nuclear RNA Export Factor 1, cyclin‑dependent kinase 2 (CDK2), myelocytomatosis proto‑oncogene protein (MYC), Cullin 5, SHC Adaptor Protein 1, Clathrin heavy chain, Nucleolin, WD repeat domain 1, proteasome 26S subunit non‑ATPase 2 and telomeric repeat binding factor 2. The cyclin‑dependent kinase inhibitor 1A (CDKN1A), E2F transcription factor 1 (E2F1), and MYC interacted with CDK2. The SVM classifier constructed by the top 30 feature genes was able to distinguish metastatic samples from non‑metastatic samples [correct rate, specificity, positive predictive value and negative predictive value >0.89; sensitivity >0.84; area under the receiver operating characteristic curve (AUROC) >0.96]. The verification of the SVM classifier in an

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

    PubMed

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

    2015-10-01

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

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

    NASA Technical Reports Server (NTRS)

    Joseph, Charles L.; Jenkins, Edward B.

    1991-01-01

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

  17. New Dust Features Observed with ISO

    NASA Technical Reports Server (NTRS)

    Tielens, Alexander G. G. M.; Young, Richard E. (Technical Monitor)

    1997-01-01

    This paper will review our current knowledge of circumstellar and interstellar dust with the emphasis on infrared spectroscopy with ISO. Objects embedded in or located behind molecular clouds show a wealth of absorption features due to simple molecules in an icy mantle. The SWS on ISO has provided us, for the first time, with complete 3-45 um spectra which allow an inventory of interstellar ice. Among the species identified are H2O, CH3OH, CH4, CO2, CO, and OCS. These species are formed through simple reactions among gas phase species accreted on grain surfaces, possibly modified by FUV photolysis and warm-up (ie., outgassing). The implications of the observations for our understanding of these processes will be reviewed. The IR spectra of many UV bright objects are dominated by strong emission features at 3.3, 6.2, 7.7, and 11.3 micrometers. These are generally attributed to Polycyclic Aromatic Hydrocarbons (PAHs) molecules. The observational evidence will be reviewed. The emphasis will be on recent data which show widespread spectral variations, particularly among protoplanetary and planetary nebulae, and their implications. One of the most exciting, recent discoveries on interstellar and circumstellar dust has been the detection of spectral structure due to crystalline olivine and enstatite in a variety of objects surrounded by circumstellar silicates. These spectra will be reviewed and circumstellar silicate mineralogy will be discussed.

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

    NASA Astrophysics Data System (ADS)

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

    2017-10-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2018-01-01

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

  20. Analysis of spectrally resolved autofluorescence images by support vector machines

    NASA Astrophysics Data System (ADS)

    Mateasik, A.; Chorvat, D.; Chorvatova, A.

    2013-02-01

    Spectral analysis of the autofluorescence images of isolated cardiac cells was performed to evaluate and to classify the metabolic state of the cells in respect to the responses to metabolic modulators. The classification was done using machine learning approach based on support vector machine with the set of the automatically calculated features from recorded spectral profile of spectral autofluorescence images. This classification method was compared with the classical approach where the individual spectral components contributing to cell autofluorescence were estimated by spectral analysis, namely by blind source separation using non-negative matrix factorization. Comparison of both methods showed that machine learning can effectively classify the spectrally resolved autofluorescence images without the need of detailed knowledge about the sources of autofluorescence and their spectral properties.

  1. Covariance propagation in spectral indices

    DOE PAGES

    Griffin, P. J.

    2015-01-09

    In this study, the dosimetry community has a history of using spectral indices to support neutron spectrum characterization and cross section validation efforts. An important aspect to this type of analysis is the proper consideration of the contribution of the spectrum uncertainty to the total uncertainty in calculated spectral indices (SIs). This study identifies deficiencies in the traditional treatment of the SI uncertainty, provides simple bounds to the spectral component in the SI uncertainty estimates, verifies that these estimates are reflected in actual applications, details a methodology that rigorously captures the spectral contribution to the uncertainty in the SI, andmore » provides quantified examples that demonstrate the importance of the proper treatment the spectral contribution to the uncertainty in the SI.« less

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

    PubMed

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

    2010-06-01

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

  3. O2 on ganymede: Spectral characteristics and plasma formation mechanisms

    USGS Publications Warehouse

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

    1996-01-01

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

  4. X-ray diffraction, crystal structure, and spectral features of the optical susceptibilities of single crystals of the ternary borate oxide lead bismuth tetraoxide, PbBiBO4.

    PubMed

    Reshak, Ali Hussain; Kityk, I V; Auluck, S; Chen, Xuean

    2009-05-14

    The all-electron full-potential linearized augmented plane-wave method has been used for an ab initio theoretical study of the band structure, the spectral features of the optical susceptibilities, the density of states, and the electron charge density for PbBiBO4. Our calculations show that the valence-band maximum (VBM) and conduction-band minimum (CBM) are located at the center of the Brillouin zone, resulting in a direct energy gap of about 3.2 eV. We have synthesized the PbBiBO4 crystal by employing a conventional solid-state reaction method. The theoretical calculations in this work are based on the structure built from our measured atomic parameters. We should emphasize that the observed experimental X-ray diffraction (XRD) pattern is in good agreement with the theoretical one, confirming that our structural model is valid. Our calculated bond lengths show excellent agreement with the experimental data. This agreement is attributed to our use of full-potential calculations. The spectral features of the optical susceptibilities show a small positive uniaxial anisotropy.

  5. Feature Selection for Ridge Regression with Provable Guarantees.

    PubMed

    Paul, Saurabh; Drineas, Petros

    2016-04-01

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

  6. System and method employing a self-organizing map load feature database to identify electric load types of different electric loads

    DOEpatents

    Lu, Bin; Harley, Ronald G.; Du, Liang; Yang, Yi; Sharma, Santosh K.; Zambare, Prachi; Madane, Mayura A.

    2014-06-17

    A method identifies electric load types of a plurality of different electric loads. The method includes providing a self-organizing map load feature database of a plurality of different electric load types and a plurality of neurons, each of the load types corresponding to a number of the neurons; employing a weight vector for each of the neurons; sensing a voltage signal and a current signal for each of the loads; determining a load feature vector including at least four different load features from the sensed voltage signal and the sensed current signal for a corresponding one of the loads; and identifying by a processor one of the load types by relating the load feature vector to the neurons of the database by identifying the weight vector of one of the neurons corresponding to the one of the load types that is a minimal distance to the load feature vector.

  7. Spectral-Domain Optical Coherence Tomography Staging and Autofluorescence Imaging in Achromatopsia

    PubMed Central

    Greenberg, Jonathan P.; Sherman, Jerome; Zweifel, Sandrine A.; Chen, Royce W. S.; Duncker, Tobias; Kohl, Susanne; Baumann, Britta; Wissinger, Bernd; Yannuzzi, Lawrence A.; Tsang, Stephen H.

    2015-01-01

    Importance Evidence is mounting that achromatopsia is a progressive retinal degeneration, and treatments for this condition are on the horizon. Objectives To categorize achromatopsia into clinically identifiable stages using spectral-domain optical coherence tomography and to describe fundus autofluorescence imaging in this condition. Design, Setting, and Participants A prospective observational study was performed between 2010 and 2012 at the Edward S. Harkness Eye Institute, New York-Presbyterian Hospital. Participants included 17 patients (aged 10-62 years) with full-field electroretinography-confirmed achromatopsia. Main outcomes and Measures Spectral-domain optical coherence tomography features and staging system, fundus autofluorescence and near-infrared reflectance features and their correlation to optical coherence tomography, and genetic mutations served as the outcomes and measures. Results Achromatopsia was categorized into 5 stages on spectral-domain optical coherence tomography: stage 1 (2 patients [12%]), intact outer retina; stage 2 (2 patients [12%]), inner segment ellipsoid line disruption; stage 3 (5 patients [29%]), presence of an optically empty space; stage 4 (5 patients [29%]), optically empty space with partial retinal pigment epithelium disruption; and stage 5 (3 patients [18%]), complete retinal pigment epithelium disruption and/or loss of the outer nuclear layer. Stage 1 patients showed isolated hyperreflectivity of the external limiting membrane in the fovea, and the external limiting membrane was hyperreflective above each optically empty space. On near infrared reflectance imaging, the fovea was normal, hyporeflective, or showed both hyporeflective and hyperreflective features. All patients demonstrated autofluorescence abnormalities in the fovea and/or parafovea: 9 participants (53%) had reduced or absent autofluorescence surrounded by increased autofluorescence, 4 individuals (24%) showed only reduced or absent autofluorescence, 3

  8. Spectral-domain optical coherence tomography staging and autofluorescence imaging in achromatopsia.

    PubMed

    Greenberg, Jonathan P; Sherman, Jerome; Zweifel, Sandrine A; Chen, Royce W S; Duncker, Tobias; Kohl, Susanne; Baumann, Britta; Wissinger, Bernd; Yannuzzi, Lawrence A; Tsang, Stephen H

    2014-04-01

    IMPORTANCE Evidence is mounting that achromatopsia is a progressive retinal degeneration, and treatments for this condition are on the horizon. OBJECTIVES To categorize achromatopsia into clinically identifiable stages using spectral-domain optical coherence tomography and to describe fundus autofluorescence imaging in this condition. DESIGN, SETTING, AND PARTICIPANTS A prospective observational study was performed between 2010 and 2012 at the Edward S. Harkness Eye Institute, New York-Presbyterian Hospital. Participants included 17 patients (aged 10-62 years) with full-field electroretinography-confirmed achromatopsia. MAIN OUTCOMES AND MEASURES Spectral-domain optical coherence tomography features and staging system, fundus autofluorescence and near-infrared reflectance features and their correlation to optical coherence tomography, and genetic mutations served as the outcomes and measures. RESULTS Achromatopsia was categorized into 5 stages on spectral-domain optical coherence tomography: stage 1 (2 patients [12%]), intact outer retina; stage 2 (2 patients [12%]), inner segment ellipsoid line disruption; stage 3 (5 patients [29%]), presence of an optically empty space; stage 4 (5 patients [29%]), optically empty space with partial retinal pigment epithelium disruption; and stage 5 (3 patients [18%]), complete retinal pigment epithelium disruption and/or loss of the outer nuclear layer. Stage 1 patients showed isolated hyperreflectivity of the external limiting membrane in the fovea, and the external limiting membrane was hyperreflective above each optically empty space. On near infrared reflectance imaging, the fovea was normal, hyporeflective, or showed both hyporeflective and hyperreflective features. All patients demonstrated autofluorescence abnormalities in the fovea and/or parafovea: 9 participants (53%) had reduced or absent autofluorescence surrounded by increased autofluorescence, 4 individuals (24%) showed only reduced or absent autofluorescence, 3

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

    NASA Astrophysics Data System (ADS)

    Chockalingam, Letchumanan

    2005-01-01

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

  10. Investigating the high-frequency spectral features of SNRs Tycho, W44 and IC443 with the Sardinia Radio Telescope

    NASA Astrophysics Data System (ADS)

    Loru, S.; Pellizzoni, A.; Egron, E.; Righini, S.; Iacolina, M. N.; Mulas, S.; Cardillo, M.; Marongiu, M.; Ricci, R.; Bachetti, M.; Pilia, M.; Trois, A.; Ingallinera, A.; Petruk, O.; Murtas, G.; Serra, G.; Concu, F. Buffa R.; Gaudiomonte, F.; Melis, A.; Navarrini, A.; Perrodin, D.; Valente, G.

    2018-05-01

    The main characteristics in the radio continuum spectra of Supernova Remnants (SNRs) result from simple synchrotron emission. In addition, electron acceleration mechanisms can shape the spectra in specific ways, especially at high radio frequencies. These features are connected to the age and the peculiar conditions of the local interstellar medium interacting with the SNR. Whereas the bulk radio emission is expected at up to 20 - 50 GHz, sensitive high-resolution images of SNRs above 10 GHz are lacking and are not easily achievable, especially in the confused regions of the Galactic Plane. In the framework of the early science observations with the Sardinia Radio Telescope in February-March 2016, we obtained high-resolution images of SNRs Tycho, W44 and IC443 that provided accurate integrated flux density measurements at 21.4 GHz: 8.8 ± 0.9 Jy for Tycho, 25 ± 3 Jy for W44 and 66 ± 7 Jy for IC443. We coupled the SRT measurements with radio data available in the literature in order to characterise the integrated and spatially-resolved spectra of these SNRs, and to find significant frequency- and region-dependent spectral slope variations. For the first time, we provide direct evidence of a spectral break in the radio spectral energy distribution of W44 at an exponential cutoff frequency of 15 ± 2 GHz. This result constrains the maximum energy of the accelerated electrons in the range 6 - 13 GeV, in agreement with predictions indirectly derived from AGILE and Fermi-LAT gamma-ray observations. With regard to IC443, our results confirm the noticeable presence of a bump in the integrated spectrum around 20 - 70 GHz that could result from a spinning dust emission mechanism.

  11. A spectral reflectance estimation technique using multispectral data from the Viking lander camera

    NASA Technical Reports Server (NTRS)

    Park, S. K.; Huck, F. O.

    1976-01-01

    A technique is formulated for constructing spectral reflectance curve estimates from multispectral data obtained with the Viking lander camera. The multispectral data are limited to six spectral channels in the wavelength range from 0.4 to 1.1 micrometers and most of these channels exhibit appreciable out-of-band response. The output of each channel is expressed as a linear (integral) function of the (known) solar irradiance, atmospheric transmittance, and camera spectral responsivity and the (unknown) spectral responsivity and the (unknown) spectral reflectance. This produces six equations which are used to determine the coefficients in a representation of the spectral reflectance as a linear combination of known basis functions. Natural cubic spline reflectance estimates are produced for a variety of materials that can be reasonably expected to occur on Mars. In each case the dominant reflectance features are accurately reproduced, but small period features are lost due to the limited number of channels. This technique may be a valuable aid in selecting the number of spectral channels and their responsivity shapes when designing a multispectral imaging system.

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

    NASA Astrophysics Data System (ADS)

    Saluja, Ridhi; Garg, J. K.

    2017-10-01

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

  13. Hungaria Asteroid Region Telescopic Spectral Survey (HARTSS) II: Spectral Homogeneity Among Hungaria Family Asteroids

    NASA Astrophysics Data System (ADS)

    Lucas, Michael P.; Emery, Joshua; Pinilla-Alonso, Noemi; Lindsay, Sean S.; MacLennan, Eric M.; Cartwright, Richard; Reddy, Vishnu; Sanchez, Juan A.; Thomas, Cristina A.; Lorenzi, Vania

    2017-10-01

    Spectral observations of asteroid family members provide valuable information regarding parent body interiors, the source regions of near-Earth asteroids, and the link between meteorites and their parent bodies. Hungaria family asteroids constitute the closest samples to the Earth from a collisional family (~1.94 AU), permitting observations of smaller fragments than accessible for Main Belt families. We have carried out a ground-based observational campaign - Hungaria Asteroid Region Telescopic Spectral Survey (HARTSS) - to record reflectance spectra of these preserved samples from the inner-most primordial asteroid belt. During HARTSS phase one (Lucas et al. [2017]. Icarus 291, 268-287) we found that ~80% of the background population is comprised of stony S-complex asteroids that exhibit considerable spectral and mineralogical diversity. In HARTSS phase two, we turn our attention to family members and hypothesize that the Hungaria collisional family is homogeneous. We test this hypothesis through taxonomic classification, albedo estimates, and spectral properties.During phase two of HARTSS we acquired near-infrared (NIR) spectra of 50 new Hungarias (19 family; 31 background) with SpeX/IRTF and NICS/TNG. We analyzed X-type family spectra for NIR color indices (0.85-J J-K), and a subtle ~0.9 µm absorption feature that may be attributed to Fe-poor orthopyroxene. Surviving fragments of an asteroid collisional family typically exhibit similar taxonomies, albedos, and spectral properties. Spectral analysis of X-type Hungaria family members and independently calculated WISE albedo determinations for 428 Hungaria asteroids is consistent with this scenario. Furthermore, ~1/4 of the background population exhibit similar spectral properties and albedos to family X-types.Spectral observations of 92 Hungaria region asteroids acquired during both phases of HARTSS uncover a compositionally heterogeneous background and spectral homogeneity down to ~2 km for collisional family

  14. Berkeley SuperNova Ia Program (BSNIP): Initial Spectral Analysis

    NASA Astrophysics Data System (ADS)

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

    2011-01-01

    The Berkeley SuperNova Ia Program (BSNIP) has been observing nearby (z < 0.1) Type Ia supernovae (SNe Ia) both photometrically and spectroscopically for over two decades. Using telescopes at both Lick and Keck Observatories, we have amassed an extensive collection of well-sampled optical light curves with complementary spectra covering, on average, 3400-10,000 Å. In total, we have obtained nearly 600 spectra of over 200 SNe Ia with densely sampled multi-color light curves. The initial analysis of this dataset consists of accurately and robustly measuring the strength and position of various spectral features near maximum brightness. We determine the endpoints, pseudo-continuum, expansion velocity, equivalent width, and depth of each major feature observed in our wavelength range. For objects with multiple spectra near maximum brightness we investigate how these values change with time. From these measurements we also calculate velocity gradients and various flux ratios within a given spectrum which will allow us to explore correlations between spectral and photometric observables. Some possible correlations have been studied previously, but our dataset is unique in how self-consistent the data reduction and spectral feature measurements have been, and it is a factor of a few larger than most earlier studies. We will briefly summarize the contents of the full dataset as an introduction to our initial analysis. Some of our measurements of SN Ia spectral features, along with a few initial results from those measurements, will be presented. Finally, we will comment on our current progress and planned future work. We gratefully acknowledge the financial support of NSF grant AST-0908886, the TABASGO Foundation, and the Marc J. Staley Graduate Fellowship in Astronomy.

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

    USGS Publications Warehouse

    Ramsey, E.; Rangoonwala, A.

    2008-01-01

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

  16. The Physical Nature of the Sharp Spectral Feature at 7 keV Detected in 1H0707-495

    NASA Technical Reports Server (NTRS)

    Brandt, Niel

    2005-01-01

    XMM-Newton acquired data on the accepted target, 1H0707-495, on 2002 October 13 during revolution 0521. The observation was successful, with only about 5% data loss due to background flaring. We compared the data from this observation with earlier data taken on this Narrow-Line Seyfert 1 about two years before, performing interpretation studies in the context of the partial-covering model. Our second longer observation once again displays a sharp (< 200 eV) spectral drop above 7 keV. However, in comparison to the first observation, the edge depth and energy have changed significantly. In addition to changes in the edge parameters, the high-energy spectrum appears steeper. The changes in the high-energy spectrum can be adequately explained in terms of a partial-covering absorber out-flowing from the central region. The low-energy spectrum also shows significant long-term spectral variability, including (1) a substantial increase in the disk temperature, (2) detection of an approx. 0.9 keV emission feature, and (3) the presence of ionized absorption that was detected during the ASCA mission. The large increase in disk temperature, and the more modest rise in luminosity, can be understood if we consider a slim-disk model for 1H0707-495. In addition, the higher disk luminosity could be the driving force behind the outflow and the re-appearance of an ionized medium during the second XMM-Newton observation.

  17. Mineralogy of dark asteroids: Detection of phyllosilicate features in the mid-infrared

    NASA Astrophysics Data System (ADS)

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

    2014-11-01

    Dark asteroids (C- and related types) have been shown to have phyllosilicates on their surfaces by the presence of the 0.7-µm charge transfer band in the visible/near-infrared (VIS/NIR) spectral region (e.g. [1], [2]). Observations of asteroids in the 2.5-5-µm have also indicated the presence of water [3, 4] and phyllosilicates [5, 6]. Phyllosilicates also have spectral features in the 8-30-µm [7]. The results of a coordinated spectral-mineralogical study of aqueously altered meteorites [8] can be used to both remotely identify the presence of aqueous alteration and determine the degree of alteration on asteroids. Two main regions have strong features related to the mineralogy and degree of alteration: the 10-13-µm and the 16-25-µm region. Alteration features change continuously in these regions between less 60%) and highly 90%) altered meteorites. These features have been identified in the spectra of some dark asteroids [8, 9, 10]. Additionally, no trends are found between 0.7-µm charge transfer band and degree of alteration. While all meteorites with a 0.7-µm band have phyllosilicates, the absence of a 0.7-µm band is not indicative of the absence of alteration. Altered meteorites always exhibit MIR features that are directly related to their degree of alteration whether or not they have a 0.7-µm band. Here, we present preliminary results of a survey of archived Spitzer Space Telescope data of asteroids in the 10-13-µm region and the 16-25-µm region (where data is available) including comparisons to published VIS/NIR spectra of the same dark asteroids without VIS/NIR features. Possible effects in comparing laboratory measurements of meteorite powders under ambient conditions to telescopic spectra of asteroid regoliths are considered. [1] Vilas and Gaffey, (1989) Nature, 246, 790-792. [2] Barucci et al (1998) Icarus, 132, 388-396. [3] Campins et al., (2010), Nature Letters, 464, 1320-1321. [4] Rivkin & Emery (2010) Nature Letters, 464, 1322-1323. [5

  18. Research on oral test modeling based on multi-feature fusion

    NASA Astrophysics Data System (ADS)

    Shi, Yuliang; Tao, Yiyue; Lei, Jun

    2018-04-01

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

  19. Defining and Detecting Complex Peak Relationships in Mass Spectral Data: The Mz.unity Algorithm.

    PubMed

    Mahieu, Nathaniel G; Spalding, Jonathan L; Gelman, Susan J; Patti, Gary J

    2016-09-20

    Analysis of a single analyte by mass spectrometry can result in the detection of more than 100 degenerate peaks. These degenerate peaks complicate spectral interpretation and are challenging to annotate. In mass spectrometry-based metabolomics, this degeneracy leads to inflated false discovery rates, data sets containing an order of magnitude more features than analytes, and an inefficient use of resources during data analysis. Although software has been introduced to annotate spectral degeneracy, current approaches are unable to represent several important classes of peak relationships. These include heterodimers and higher complex adducts, distal fragments, relationships between peaks in different polarities, and complex adducts between features and background peaks. Here we outline sources of peak degeneracy in mass spectra that are not annotated by current approaches and introduce a software package called mz.unity to detect these relationships in accurate mass data. Using mz.unity, we find that data sets contain many more complex relationships than we anticipated. Examples include the adduct of glutamate and nicotinamide adenine dinucleotide (NAD), fragments of NAD detected in the same or opposite polarities, and the adduct of glutamate and a background peak. Further, the complex relationships we identify show that several assumptions commonly made when interpreting mass spectral degeneracy do not hold in general. These contributions provide new tools and insight to aid in the annotation of complex spectral relationships and provide a foundation for improved data set identification. Mz.unity is an R package and is freely available at https://github.com/nathaniel-mahieu/mz.unity as well as our laboratory Web site http://pattilab.wustl.edu/software/ .

  20. Identifying predictive features in drug response using machine learning: opportunities and challenges.

    PubMed

    Vidyasagar, Mathukumalli

    2015-01-01

    This article reviews several techniques from machine learning that can be used to study the problem of identifying a small number of features, from among tens of thousands of measured features, that can accurately predict a drug response. Prediction problems are divided into two categories: sparse classification and sparse regression. In classification, the clinical parameter to be predicted is binary, whereas in regression, the parameter is a real number. Well-known methods for both classes of problems are briefly discussed. These include the SVM (support vector machine) for classification and various algorithms such as ridge regression, LASSO (least absolute shrinkage and selection operator), and EN (elastic net) for regression. In addition, several well-established methods that do not directly fall into machine learning theory are also reviewed, including neural networks, PAM (pattern analysis for microarrays), SAM (significance analysis for microarrays), GSEA (gene set enrichment analysis), and k-means clustering. Several references indicative of the application of these methods to cancer biology are discussed.

  1. Discriminating Induced-Microearthquakes Using New Seismic Features

    NASA Astrophysics Data System (ADS)

    Mousavi, S. M.; Horton, S.

    2016-12-01

    We studied characteristics of induced-microearthquakes on the basis of the waveforms recorded on a limited number of surface receivers using machine-learning techniques. Forty features in the time, frequency, and time-frequency domains were measured on each waveform, and several techniques such as correlation-based feature selection, Artificial Neural Networks (ANNs), Logistic Regression (LR) and X-mean were used as research tools to explore the relationship between these seismic features and source parameters. The results show that spectral features have the highest correlation to source depth. Two new measurements developed as seismic features for this study, spectral centroids and 2D cross-correlations in the time-frequency domain, performed better than the common seismic measurements. These features can be used by machine learning techniques for efficient automatic classification of low energy signals recorded at one or more seismic stations. We applied the technique to 440 microearthquakes-1.7Reference: Mousavi, S.M., S.P. Horton, C. A. Langston, B. Samei, (2016) Seismic features and automatic discrimination of deep and shallow induced-microearthquakes using neural network and logistic regression, Geophys. J. Int. doi: 10.1093/gji/ggw258.

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

    NASA Astrophysics Data System (ADS)

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

    2018-02-01

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

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

    NASA Astrophysics Data System (ADS)

    Tanko, Y. A.; Sahar, M. R.; Ghoshal, S. K.

    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 - x)TeO2-20ZnO-(x)Sm2O3, 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 towards prospective applications.

  4. System and method employing a minimum distance and a load feature database to identify electric load types of different electric loads

    DOEpatents

    Lu, Bin; Yang, Yi; Sharma, Santosh K; Zambare, Prachi; Madane, Mayura A

    2014-12-23

    A method identifies electric load types of a plurality of different electric loads. The method includes providing a load feature database of a plurality of different electric load types, each of the different electric load types including a first load feature vector having at least four different load features; sensing a voltage signal and a current signal for each of the different electric loads; determining a second load feature vector comprising at least four different load features from the sensed voltage signal and the sensed current signal for a corresponding one of the different electric loads; and identifying by a processor one of the different electric load types by determining a minimum distance of the second load feature vector to the first load feature vector of the different electric load types of the load feature database.

  5. Spectral Characteristics of Young Stars Associated with the Sh2-296 Nebula

    NASA Astrophysics Data System (ADS)

    Fernandes, Beatriz; Gregorio-Hetem, Jane

    Aiming to contribute to the understanding of star formation and evolution in the Canis Major (CMa R1) Molecular Clouds Complex, we analyze the spectral characteristics of a population of young stars associated with the arc-shaped nebula Sh2-296. Our XMM/Newton observations detected 109 X-ray sources in the region and optical spectroscopy was performed with Gemini telescope for 85 optical counterparts. We identified and characterized 51 objects that present features typically found in young objects, such as Hα emission and strong absorption on the Li I line.

  6. Exploring the limits of identifying sub-pixel thermal features using ASTER TIR data

    USGS Publications Warehouse

    Vaughan, R.G.; Keszthelyi, L.P.; Davies, A.G.; Schneider, D.J.; Jaworowski, C.; Heasler, H.

    2010-01-01

    Understanding the characteristics of volcanic thermal emissions and how they change with time is important for forecasting and monitoring volcanic activity and potential hazards. Satellite instruments view volcanic thermal features across the globe at various temporal and spatial resolutions. Thermal features that may be a precursor to a major eruption, or indicative of important changes in an on-going eruption can be subtle, making them challenging to reliably identify with satellite instruments. The goal of this study was to explore the limits of the types and magnitudes of thermal anomalies that could be detected using satellite thermal infrared (TIR) data. Specifically, the characterization of sub-pixel thermal features with a wide range of temperatures is considered using ASTER multispectral TIR data. First, theoretical calculations were made to define a "thermal mixing detection threshold" for ASTER, which quantifies the limits of ASTER's ability to resolve sub-pixel thermal mixing over a range of hot target temperatures and % pixel areas. Then, ASTER TIR data were used to model sub-pixel thermal features at the Yellowstone National Park geothermal area (hot spring pools with temperatures from 40 to 90 ??C) and at Mount Erebus Volcano, Antarctica (an active lava lake with temperatures from 200 to 800 ??C). Finally, various sources of uncertainty in sub-pixel thermal calculations were quantified for these empirical measurements, including pixel resampling, atmospheric correction, and background temperature and emissivity assumptions.

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

    A spectral line survey of the oxygen-rich red supergiant VY Canis Majoris was made between 279 and 355 GHz with the Submillimeter Array (SMA). 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 are presented. Observations of each line with a synthesized beam of ~0.''9, reveal the complex kinematics and morphology of the nebula surrounding VY CMa. Many of the molecules are observed in high-lying rotational levels or in excited vibrational levels. From these, it was established that the main source of the submillimeter-wave continuum (dust) and the high-excitation molecular gas (the star) are separated by about 0.''15. Apparent coincidences between the molecular gas observed with the SMA, and some of the arcs and knots observed at infrared wavelengths and in the optical scattered light by the Hubble Space Telescope are identified. The observations presented here provide important constraints on the molecular chemistry in oxygen-dominated circumstellar environments and a deeper picture of the complex circumstellar environment of VY CMa.

  8. Principal component analysis of three-dimensional face shape: Identifying shape features that change with age.

    PubMed

    Kurosumi, M; Mizukoshi, K

    2018-05-01

    The types of shape feature that constitutes a face have not been comprehensively established, and most previous studies of age-related changes in facial shape have focused on individual characteristics, such as wrinkle, sagging skin, etc. In this study, we quantitatively measured differences in face shape between individuals and investigated how shape features changed with age. We analyzed three-dimensionally the faces of 280 Japanese women aged 20-69 years and used principal component analysis to establish the shape features that characterized individual differences. We also evaluated the relationships between each feature and age, clarifying the shape features characteristic of different age groups. Changes in facial shape in middle age were a decreased volume of the upper face and increased volume of the whole cheeks and around the chin. Changes in older people were an increased volume of the lower cheeks and around the chin, sagging skin, and jaw distortion. Principal component analysis was effective for identifying facial shape features that represent individual and age-related differences. This method allowed straightforward measurements, such as the increase or decrease in cheeks caused by soft tissue changes or skeletal-based changes to the forehead or jaw, simply by acquiring three-dimensional facial images. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  9. Determination of Primary Spectral Bands for Remote Sensing of Aquatic Environments

    DTIC Science & Technology

    2007-12-20

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

  10. The mid-IR spectral effects of darkening agents and porosity on the silicate surface features of airless bodies

    NASA Astrophysics Data System (ADS)

    Young, C. L.; Wray, J. J.; Poston, M.; Hand, K. P.; Carlson, R. W.

    2017-12-01

    The surfaces of airless bodies present opportunities to investigate the physical processes acting on planetary systems over time, without the need to account for surface-atmosphere interactions. Silicate surfaces mixed with fine-grained optically dark material with varying degrees of porosity are ubiquitous on many airless bodies (e.g., Earth's Moon, Deimos, Phobos, asteroids, meteorites, and moons of the outer solar system). Although the mid-IR is rich in emissivity features of important minerals and molecular groups, including organics [e.g., 1], it is less studied for airless conditions and presents challenges in signal-to-noise ratio, especially for the colder outer solar system bodies with fined-grained surfaces [2, 3]. We systematically measured the mid-IR spectra of different mixtures of three silicates (antigorite, lizardite, and pure silica) with varying porosities and amounts of darkening agent (iron oxide and carbon). Serpentines, such as antigorite and lizardite, are common to airless surfaces, and their mid-IR spectra in the presence of darkening agents and different surface porosities would be typical for those measured by spacecraft. Although pure silica has only been measured in the plumes of Enceladus, it presents exciting possibilities for other Saturn-system surfaces due to long range transport [4], and it is therefore important to investigate how its spectral signature would be manifested in the mid-IR. Overall, this work provides a library of mineral mixtures to facilitate dealing with current and future mid-IR datasets of airless bodies. These results are also applicable to the development of future missions to airless bodies, and our continuing efforts will help determine if mid-IR spectrometry is worthwhile for surface compositional studies of icy bodies. The mixtures presented here could be useful for testing future mid-IR instruments by confirming detectability of spectral features for typical materials on the surfaces of interest. [1

  11. Studies on Ammonia Spectral Signatures Relevant to Jupiter's Clouds

    NASA Astrophysics Data System (ADS)

    Kalogerakis, Konstantinos S.; Oza, A. U.; Marschall, J.; Wong, M. H.

    2006-09-01

    Observational evidence and thermochemical models indicate an abundance of ammonia ice clouds in Jupiter's atmosphere. However, spectrally identifiable ammonia ice clouds are found covering less than 1% of Jupiter's atmosphere, notably in turbulent areas [1,2]. Current literature suggests two possible explanations: coating by a hydrocarbon haze and/or photochemical processing ("tanning") [2,3]. We are pursuing a research program investigating the above hypotheses. In the experiments, thin films of ammonia ices are deposited in a cryogenic apparatus, coated with hydrocarbons, and characterized by infrared spectroscopy. The ice films can be irradiated by ultraviolet light to study their photochemistry. The spectroscopic measurements aim to identify the processes that control the optical properties of the ice mixtures and quantify their dependence on the identity of the coating, the temperature, and the ice composition. We have observed a consistent suppression of the ammonia absorption feature at 3 μm with coverage by thin layers of hydrocarbons. Modeling calculations of the multi-layer thin films assist in the interpretation of the experimental results and reveal the role of optical interference in masking the aforementioned ammonia spectral feature. The implications of these results for Jupiter's atmosphere will be discussed. Funding from the NSF Planetary Astronomy Program under grant AST-0206270 and from the NASA Outer Planets Research Program under grant NNG06GF37G is gratefully acknowledged. The participation of Anand Oza (Princeton University) was made possible by the NSF Research Experiences for Undergraduates Program under grant PHY-0353745. 1. S. K. Atreya, A.-S. Wong, K. H. Baines, M. H. Wong, T. C. Owen, Planet. Space Science 53, 498 (2005). 2. K. H. Baines, R. W. Carlson, and L. W. Kamp, Icarus 159, 74 (2002). 3. A.-S. Wong, Y. L. Yung, and A. J. Friedson, Geophys. Res. Lett. 30, 1447 (2003).

  12. Studies on Ammonia Spectral Signatures Relevant to Jupiter's Clouds

    NASA Astrophysics Data System (ADS)

    Oza, A. U.; Marschall, J.; Wong, M. H.; Kalogerakis, K. S.

    2006-12-01

    Observational evidence and thermochemical models indicate an abundance of ammonia ice clouds in Jupiter's atmosphere. However, spectrally identifiable ammonia ice clouds are found covering less than 1% of Jupiter's atmosphere, notably in turbulent areas [1,2]. Current literature suggests two possible explanations: coating by a hydrocarbon haze and/or photochemical processing ("tanning")[2,3]. We are pursuing a research program investigating the above hypotheses. In the experiments, thin films of ammonia ices are deposited in a cryogenic apparatus, coated with hydrocarbons, and characterized by infrared spectroscopy. The ice films can be irradiated by ultraviolet light to study their photochemistry. The spectroscopic measurements aim to identify the processes that control the optical properties of the ice mixtures and quantify their dependence on the identity of the coating, the temperature, and the ice composition. We have observed a consistent suppression of the ammonia absorption feature at 3 μm with coverage by thin layers of hydrocarbons. Modeling calculations of the multi-layer thin films assist in the interpretation of the experimental results and reveal the role of optical interference in masking the aforementioned ammonia spectral feature. The implications of these results for Jupiter's atmosphere will be discussed. Funding from the NSF Planetary Astronomy Program under grant AST-0206270 and from the NASA Outer Planets Research Program under grant NNG06GF37G is gratefully acknowledged. The participation of Anand Oza (Princeton University) was made possible by the NSF Research Experiences for Undergraduates Program under grant PHY-0353745. 1. S. K. Atreya, A.-S. Wong, K. H. Baines, M. H. Wong, T. C. Owen, Planet. Space Science 53, 498 (2005). 2. K. H. Baines, R. W. Carlson, and L. W. Kamp, Icarus 159, 74 (2002). 3. A.-S. Wong, Y. L. Yung, and A. J. Friedson, Geophys. Res. Lett. 30, 1447 (2003).

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

    NASA Astrophysics Data System (ADS)

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

    2018-04-01

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

  14. Spectral methods to detect surface mines

    NASA Astrophysics Data System (ADS)

    Winter, Edwin M.; Schatten Silvious, Miranda

    2008-04-01

    Over the past five years, advances have been made in the spectral detection of surface mines under minefield detection programs at the U. S. Army RDECOM CERDEC Night Vision and Electronic Sensors Directorate (NVESD). The problem of detecting surface land mines ranges from the relatively simple, the detection of large anti-vehicle mines on bare soil, to the very difficult, the detection of anti-personnel mines in thick vegetation. While spatial and spectral approaches can be applied to the detection of surface mines, spatial-only detection requires many pixels-on-target such that the mine is actually imaged and shape-based features can be exploited. This method is unreliable in vegetated areas because only part of the mine may be exposed, while spectral detection is possible without the mine being resolved. At NVESD, hyperspectral and multi-spectral sensors throughout the reflection and thermal spectral regimes have been applied to the mine detection problem. Data has been collected on mines in forest and desert regions and algorithms have been developed both to detect the mines as anomalies and to detect the mines based on their spectral signature. In addition to the detection of individual mines, algorithms have been developed to exploit the similarities of mines in a minefield to improve their detection probability. In this paper, the types of spectral data collected over the past five years will be summarized along with the advances in algorithm development.

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

    NASA Astrophysics Data System (ADS)

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

    2000-10-01

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

  16. Spectral Dimensionality and Scale of Urban Radiance

    NASA Technical Reports Server (NTRS)

    Small, Christopher

    2001-01-01

    Characterization of urban radiance and reflectance is important for understanding the effects of solar energy flux on the urban environment as well as for satellite mapping of urban settlement patterns. Spectral mixture analyses of Landsat and Ikonos imagery suggest that the urban radiance field can very often be described with combinations of three or four spectral endmembers. Dimensionality estimates of Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) radiance measurements of urban areas reveal the existence of 30 to 60 spectral dimensions. The extent to which broadband imagery collected by operational satellites can represent the higher dimensional mixing space is a function of both the spatial and spectral resolution of the sensor. AVIRIS imagery offers the spatial and spectral resolution necessary to investigate the scale dependence of the spectral dimensionality. Dimensionality estimates derived from Minimum Noise Fraction (MNF) eigenvalue distributions show a distinct scale dependence for AVIRIS radiance measurements of Milpitas, California. Apparent dimensionality diminishes from almost 40 to less than 10 spectral dimensions between scales of 8000 m and 300 m. The 10 to 30 m scale of most features in urban mosaics results in substantial spectral mixing at the 20 m scale of high altitude AVIRIS pixels. Much of the variance at pixel scales is therefore likely to result from actual differences in surface reflectance at pixel scales. Spatial smoothing and spectral subsampling of AVIRIS spectra both result in substantial loss of information and reduction of apparent dimensionality, but the primary spectral endmembers in all cases are analogous to those found in global analyses of Landsat and Ikonos imagery of other urban areas.

  17. Identifying potential collapse features under highways : research implementation plan.

    DOT National Transportation Integrated Search

    2005-09-01

    There are many unmapped features under the states roadways that threaten them with major localized : collapse. The most common of these features are abandoned underground mines in the eastern part of : the state and sinkholes in portions of limest...

  18. Infrared Spectral Signatures for Io's Dark and Green Spots

    NASA Technical Reports Server (NTRS)

    Granahan, J. C.; Fanale, F. P.; Carlson, R.; Smythe, W. D.

    2001-01-01

    This spectral study of Io identifies the infrared components of the visible spectral units (green and dark) as identified by Galileo. The green units possess sulfur dioxide and the dark units are associated with infrared thermal signatures. Additional information is contained in the original extended abstract.

  19. Mars analog minerals' spectral reflectance characteristics under Martian surface conditions

    NASA Astrophysics Data System (ADS)

    Poitras, J. T.; Cloutis, E. A.; Salvatore, M. R.; Mertzman, S. A.; Applin, D. M.; Mann, P.

    2018-05-01

    We investigated the spectral reflectance properties of minerals under a simulated Martian environment. Twenty-eight different hydrated or hydroxylated phases of carbonates, sulfates, and silica minerals were selected based on past detection on Mars through spectral remote sensing data. Samples were ground and dry sieved to <45 μm grain size and characterized by XRD before and after 133 days inside a simulated Martian surface environment (pressure 5 Torr and CO2 fed). Reflectance spectra from 0.35 to 4 μm were taken periodically through a sapphire (0.35-2.5 μm) and zinc selenide (2.5-4 μm) window over a 133-day period. Mineral stability on the Martian surface was assessed through changes in spectral characteristics. Results indicate that the hydrated carbonates studied would be stable on the surface of Mars, only losing adsorbed H2O while maintaining their diagnostic spectral features. Sulfates were less stable, often with shifts in the band position of the SO, Fe, and OH absorption features. Silicas displayed spectral shifts related to SiOH and hydration state of the mineral surface, while diagnostic bands for quartz were stable. Previous detection of carbonate minerals based on 2.3-2.5 μm and 3.4-3.9 μm features appears to be consistent with our results. Sulfate mineral detection is more questionable since there can be shifts in band position related to SO4. The loss of the 0.43 μm Fe3+ band in many of the sulfates indicate that there are fewer potential candidates for Fe3+ sulfates to permanently exist on the Martian surface based on this band. The gypsum sample changed phase to basanite during desiccation as demonstrated by both reflectance and XRD. Silica on Mars has been detected using band depth ratio at 1.91 and 1.96 μm and band minimum position of the 1.4 μm feature, and the properties are also used to determine their age. This technique continues to be useful for positive silica identifications, however, silica age appears to be less consistent

  20. Application of a simplified calculation for full-wave microtremor H/ V spectral ratio based on the diffuse field approximation to identify underground velocity structures

    NASA Astrophysics Data System (ADS)

    Wu, Hao; Masaki, Kazuaki; Irikura, Kojiro; Sánchez-Sesma, Francisco José

    2017-12-01

    Under the diffuse field approximation, the full-wave (FW) microtremor H/ V spectral ratio ( H/ V) is modeled as the square root of the ratio of the sum of imaginary parts of the Green's function of the horizontal components to that of the vertical one. For a given layered medium, the FW H/ V can be well approximated with only surface waves (SW) H/ V of the "cap-layered" medium which consists of the given layered medium and a new larger velocity half-space (cap layer) at large depth. Because the contribution of surface waves can be simply obtained by the residue theorem, the computation of SW H/ V of cap-layered medium is faster than that of FW H/ V evaluated by discrete wavenumber method and contour integration method. The simplified computation of SW H/ V was then applied to identify the underground velocity structures at six KiK-net strong-motion stations. The inverted underground velocity structures were used to evaluate FW H/ Vs which were consistent with the SW H/ Vs of corresponding cap-layered media. The previous study on surface waves H/ Vs proposed with the distributed surface sources assumption and a fixed Rayleigh-to-Love waves amplitude ratio for horizontal motions showed a good agreement with the SW H/ Vs of our study. The consistency between observed and theoretical spectral ratios, such as the earthquake motions of H/ V spectral ratio and spectral ratio of horizontal motions between surface and bottom of borehole, indicated that the underground velocity structures identified from SW H/ V of cap-layered medium were well resolved by the new method.[Figure not available: see fulltext.

  1. Reducing the spectral index in supernatural inflation

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

    Lin, C.-M.; Cheung, Kingman; Division of Quantum Phases and Devices, School of Physics, Konkuk University, Seoul 143-701

    2009-04-15

    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{sub s} > or approx. 1, in contrast to experimental data. In this paper, we discuss supernatural inflation with the spectral index reduced to n{sub 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.

  2. Reducing the spectral index in supernatural inflation

    NASA Astrophysics Data System (ADS)

    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.

  3. Hyperspectral retinal imaging with a spectrally tunable light source

    NASA Astrophysics Data System (ADS)

    Francis, Robert P.; Zuzak, Karel J.; Ufret-Vincenty, Rafael

    2011-03-01

    Hyperspectral retinal imaging can measure oxygenation and identify areas of ischemia in human patients, but the devices used by current researchers are inflexible in spatial and spectral resolution. We have developed a flexible research prototype consisting of a DLP®-based spectrally tunable light source coupled to a fundus camera to quickly explore the effects of spatial resolution, spectral resolution, and spectral range on hyperspectral imaging of the retina. The goal of this prototype is to (1) identify spectral and spatial regions of interest for early diagnosis of diseases such as glaucoma, age-related macular degeneration (AMD), and diabetic retinopathy (DR); and (2) define required specifications for commercial products. In this paper, we describe the challenges and advantages of using a spectrally tunable light source for hyperspectral retinal imaging, present clinical results of initial imaging sessions, and describe how this research can be leveraged into specifying a commercial product.

  4. Spectral confocal reflection microscopy using a white light source

    NASA Astrophysics Data System (ADS)

    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.

  5. A delphi exercise to identify characteristic features of gout - opinions from patients and physicians, the first stage in developing new classification criteria.

    PubMed

    Prowse, Rebecca L; Dalbeth, Nicola; Kavanaugh, Arthur; Adebajo, Adewale O; Gaffo, Angelo L; Terkeltaub, Robert; Mandell, Brian F; Suryana, Bagus P P; Goldenstein-Schainberg, Claudia; Diaz-Torne, Cèsar; Khanna, Dinesh; Lioté, Frederic; Mccarthy, Geraldine; Kerr, Gail S; Yamanaka, Hisashi; Janssens, Hein; Baraf, Herbert F; Chen, Jiunn-Horng; Vazquez-Mellado, Janitzia; Harrold, Leslie R; Stamp, Lisa K; Van De Laar, Mart A; Janssen, Matthijs; Doherty, Michael; Boers, Maarten; Edwards, N Lawrence; Gow, Peter; Chapman, Peter; Khanna, Puja; Helliwell, Philip S; Grainger, Rebecca; Schumacher, H Ralph; Neogi, Tuhina; Jansen, Tim L; Louthrenoo, Worawit; Sivera, Francisca; Taylor, William J; Alten, Rieke

    2013-04-01

    To identify a comprehensive list of features that might discriminate between gout and other rheumatic musculoskeletal conditions, to be used subsequently for a case-control study to develop and test new classification criteria for gout. Two Delphi exercises were conducted using Web-based questionnaires: one with physicians from several countries who had an interest in gout and one with patients from New Zealand who had gout. Physicians rated a list of potentially discriminating features that were identified by literature review and expert opinion, and patients rated a list of features that they generated themselves. Agreement was defined by the RAND/UCLA disagreement index. Forty-four experienced physicians and 9 patients responded to all iterations. For physicians, 71 items were identified by literature review and 15 more were suggested by physicians. The physician survey showed agreement for 26 discriminatory features and 15 as not discriminatory. The patients identified 46 features of gout, for which there was agreement on 25 items as being discriminatory and 7 items as not discriminatory. Patients and physicians agreed upon several key features of gout. Physicians emphasized objective findings, imaging, and patterns of symptoms, whereas patients emphasized severity, functional results, and idiographic perception of symptoms.

  6. A DETAILED FAR-ULTRAVIOLET SPECTRAL ATLAS OF MAIN-SEQUENCE B STARS

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

    Smith, Myron A.

    2010-02-01

    We have constructed a detailed spectral atlas covering the wavelength region 930-1225 A for 10 sharp-lined B0-B9 stars near the main sequence. Most of the spectra we assembled are from the archives of the Far Ultraviolet Spectroscopic Explorer satellite, but for nine stars, wavelength coverage above 1188 A was taken from high-resolution International Ultraviolet Explorer or echelle Hubble Space Telescope/Space Telescope Imaging Spectrograph spectra. To represent the tenth star at type B0.2 V, we used the Copernicus atlas of {tau} Sco. We made extensive line identifications in the region 949-1225 A of all atomic features having published oscillator strengths atmore » types B0, B2, and B8. These are provided as a supplementary data product-hence the term detailed atlas. Our list of found features totals 2288, 1612, and 2469 lines, respectively. We were able to identify 92%, 98%, and 98% of these features with known atomic transitions with varying degrees of certainty in these spectra. The remaining lines do not have published oscillator strengths. Photospheric lines account for 94%, 87%, and 91%, respectively, of all our identifications, with the remainder being due to interstellar (usually molecular H{sub 2}) lines. We also discuss the numbers of lines with respect to the distributions of various ions for these three most studied spectral subtypes. A table is also given of 162 least blended lines that can be used as possible diagnostics of physical conditions in B star atmospheres.« less

  7. Spectral Measurements of Geosynchronous Satellites During Glint Season

    DTIC Science & Technology

    2015-01-01

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

  8. Identifying Medication Management Smartphone App Features Suitable for Young Adults With Developmental Disabilities: Delphi Consensus Study

    PubMed Central

    Salgado, Teresa M; Fedrigon, Alexa; Riccio Omichinski, Donna; Meade, Michelle A

    2018-01-01

    Background Smartphone apps can be a tool to facilitate independent medication management among persons with developmental disabilities. At present, multiple medication management apps exist in the market, but only 1 has been specifically designed for persons with developmental disabilities. Before initiating further app development targeting this population, input from stakeholders including persons with developmental disabilities, caregivers, and professionals regarding the most preferred features should be obtained. Objective The aim of this study was to identify medication management app features that are suitable to promote independence in the medication management process by young adults with developmental disabilities using a Delphi consensus method. Methods A compilation of medication management app features was performed by searching the iTunes App Store, United States, in February 2016, using the following terms: adherence, medication, medication management, medication list, and medication reminder. After identifying features within the retrieved apps, a final list of 42 features grouped into 4 modules (medication list, medication reminder, medication administration record, and additional features) was included in a questionnaire for expert consensus rating. A total of 52 experts in developmental disabilities, including persons with developmental disabilities, caregivers, and professionals, were invited to participate in a 3-round Delphi technique. The purpose was to obtain consensus on features that are preferred and suitable to promote independence in the medication management process among persons with developmental disabilities. Consensus for the first, second, and third rounds was defined as ≥90%, ≥80%, and ≥75% agreement, respectively. Results A total of 75 responses were received over the 3 Delphi rounds—30 in the first round, 24 in the second round, and 21 in the third round. At the end of the third round, cumulative consensus was achieved

  9. Plasmonic spectral tunability of conductive ternary nitrides

    NASA Astrophysics Data System (ADS)

    Kassavetis, S.; Bellas, D. V.; Abadias, G.; Lidorikis, E.; Patsalas, P.

    2016-06-01

    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 TixTa1-xN, TixZr1-xN, TixAl1-xN, and ZrxTa1-xN 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.

  10. Spectral and spread-spectral teleportation

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

    Humble, Travis S.

    2010-06-15

    We report how quantum information encoded into the spectral degree of freedom of a single-photon state may be teleported using a finite spectrally entangled biphoton state. We further demonstrate how the bandwidth of the teleported wave form can be controllably and coherently dilated using a spread-spectral variant of teleportation. We calculate analytical expressions for the fidelities of spectral and spread-spectral teleportation when complex-valued Gaussian states are transferred using a proposed experimental approach. Finally, we discuss the utility of these techniques for integrating broad-bandwidth photonic qubits with narrow-bandwidth receivers in quantum communication systems.

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

    NASA Astrophysics Data System (ADS)

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

    2016-02-01

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

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

    NASA Astrophysics Data System (ADS)

    Pournamdari, M.; Hashim, M.

    2014-02-01

    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.

  13. Identifying 5-methylcytosine sites in RNA sequence using composite encoding feature into Chou's PseKNC.

    PubMed

    Sabooh, M Fazli; Iqbal, Nadeem; Khan, Mukhtaj; Khan, Muslim; Maqbool, H F

    2018-05-01

    This study examines accurate and efficient computational method for identification of 5-methylcytosine sites in RNA modification. The occurrence of 5-methylcytosine (m 5 C) plays a vital role in a number of biological processes. For better comprehension of the biological functions and mechanism it is necessary to recognize m 5 C sites in RNA precisely. The laboratory techniques and procedures are available to identify m 5 C sites in RNA, but these procedures require a lot of time and resources. This study develops a new computational method for extracting the features of RNA sequence. In this method, first the RNA sequence is encoded via composite feature vector, then, for the selection of discriminate features, the minimum-redundancy-maximum-relevance algorithm was used. Secondly, the classification method used has been based on a support vector machine by using jackknife cross validation test. The suggested method efficiently identifies m 5 C sites from non- m 5 C sites and the outcome of the suggested algorithm is 93.33% with sensitivity of 90.0 and specificity of 96.66 on bench mark datasets. The result exhibits that proposed algorithm shown significant identification performance compared to the existing computational techniques. This study extends the knowledge about the occurrence sites of RNA modification which paves the way for better comprehension of the biological uses and mechanism. Copyright © 2018 Elsevier Ltd. All rights reserved.

  14. Identifying Trajectories of Borderline Personality Features in Adolescence: Antecedent and Interactive Risk Factors.

    PubMed

    Haltigan, John D; Vaillancourt, Tracy

    2016-03-01

    To examine trajectories of adolescent borderline personality (BP) features in a normative-risk cohort (n = 566) of Canadian children assessed at ages 13, 14, 15, and 16 and childhood predictors of trajectory group membership assessed at ages 8, 10, 11, and 12. Data were drawn from the McMaster Teen Study, an on-going study examining relations among bullying, mental health, and academic achievement. Participants and their parents completed a battery of mental health and peer relations questionnaires at each wave of the study. Academic competence was assessed at age 8 (Grade 3). Latent class growth analysis, analysis of variance, and logistic regression were used to analyze the data. Three distinct BP features trajectory groups were identified: elevated or rising, intermediate or stable, and low or stable. Parent- and child-reported mental health symptoms, peer relations risk factors, and intra-individual risk factors were significant predictors of elevated or rising and intermediate or stable trajectory groups. Child-reported attention-deficit hyperactivity disorder (ADHD) and somatization symptoms uniquely predicted elevated or rising trajectory group membership, whereas parent-reported anxiety and child-reported ADHD symptoms uniquely predicted intermediate or stable trajectory group membership. Child-reported somatization symptoms was the only predictor to differentiate the intermediate or stable and elevated or rising trajectory groups (OR 1.15, 95% CI 1.04 to 1.28). Associations between child-reported reactive temperament and elevated BP features trajectory group membership were 10.23 times higher among children who were bullied, supporting a diathesis-stress pathway in the development of BP features for these youth. Findings demonstrate the heterogeneous course of BP features in early adolescence and shed light on the potential prodromal course of later borderline personality disorder. © The Author(s) 2015.

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

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

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

    2016-02-20

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

  16. Silica-rich deposits and hydrated minerals at Gusev Crater, Mars: Vis-NIR spectral characterization and regional mapping

    USGS Publications Warehouse

    Rice, M.S.; Bell, J.F.; Cloutis, E.A.; Wang, A.; Ruff, S.W.; Craig, M.A.; Bailey, D.T.; Johnson, J. R.; De Souza, P.A.; Farrand, W. H.

    2010-01-01

    The Mars Exploration Rover (MER) Spirit has discovered surprisingly high concentrations of amorphous silica in soil and nodular outcrops in the Inner Basin of the Columbia Hills. In Pancam multispectral observations, we find that an absorption feature at the longest Pancam wavelength (1009 nm) appears to be characteristic of these silica-rich materials; however, spectral analyses of amorphous silica suggest that the ???1009 nm spectral feature is not a direct reflection of their silica-rich nature. Based on comparisons with spectral databases, we hypothesize that the presence of H2O or OH, either free (as water ice), adsorbed or bound in a mineral structure, is responsible for the spectral feature observed by Pancam. The Gertrude Weise soil, which is nearly pure opaline silica, may have adsorbed water cold-trapped on mineral grains. The origin of the ???1009 nm Pancam feature observed in the silica-rich nodular outcrops may result from the presence of additional hydrated minerals (specific sulfates, halides, chlorides, sodium silicates, carbonates or borates). Using the ???1009 nm feature with other spectral parameters as a "hydration signature" we have mapped the occurrence of hydrated materials along the extent of Spirit's traverse across the Columbia Hills from West Spur to Home Plate (sols 155-1696). We have also mapped this hydration signature across large panoramic images to understand the regional distribution of materials that are spectrally similar to the silica-rich soil and nodular outcrops. Our results suggest that hydrated materials are common in the Columbia Hills. ?? 2009 Elsevier Inc.

  17. Identifying Novel Transcriptional and Epigenetic Features of Nuclear Lamina-associated Genes.

    PubMed

    Wu, Feinan; Yao, Jie

    2017-03-07

    Because a large portion of the mammalian genome is associated with the nuclear lamina (NL), it is interesting to study how native genes resided there are transcribed and regulated. In this study, we report unique transcriptional and epigenetic features of nearly 3,500 NL-associated genes (NL genes). Promoter regions of active NL genes are often excluded from NL-association, suggesting that NL-promoter interactions may repress transcription. Active NL genes with higher RNA polymerase II (Pol II) recruitment levels tend to display Pol II promoter-proximal pausing, while Pol II recruitment and Pol II pausing are not correlated among non-NL genes. At the genome-wide scale, NL-association and H3K27me3 distinguishes two large gene classes with low transcriptional activities. Notably, NL-association is anti-correlated with both transcription and active histone mark levels among genes not significantly enriched with H3K9me3 or H3K27me3, suggesting that NL-association may represent a novel gene repression pathway. Interestingly, an NL gene subgroup is not significantly enriched with H3K9me3 or H3K27me3 and is transcribed at higher levels than the rest of NL genes. Furthermore, we identified distal enhancers associated with active NL genes and reported their epigenetic features.

  18. Using local correlation tracking to recover solar spectral information from a slitless spectrograph

    NASA Astrophysics Data System (ADS)

    Courrier, Hans T.; Kankelborg, Charles C.

    2018-01-01

    The Multi-Order Solar EUV Spectrograph (MOSES) is a sounding rocket instrument that utilizes a concave spherical diffraction grating to form simultaneous images in the diffraction orders m=0, +1, and -1. MOSES is designed to capture high-resolution cotemporal spectral and spatial information of solar features over a large two-dimensional field of view. Our goal is to estimate the Doppler shift as a function of position for every MOSES exposure. Since the instrument is designed to operate without an entrance slit, this requires disentangling overlapping spectral and spatial information in the m=±1 images. Dispersion in these images leads to a field-dependent displacement that is proportional to Doppler shift. We identify these Doppler shift-induced displacements for the single bright emission line in the instrument passband by comparing images from each spectral order. We demonstrate the use of local correlation tracking as a means to quantify these differences between a pair of cotemporal image orders. The resulting vector displacement field is interpreted as a measurement of the Doppler shift. Since three image orders are available, we generate three Doppler maps from each exposure. These may be compared to produce an error estimate.

  19. Spectral filtering for plant production

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

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

    1994-12-31

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

  20. A Detailed Far-ultraviolet Spectral Atlas of O-type Stars

    NASA Astrophysics Data System (ADS)

    Smith, Myron A.

    2012-10-01

    In this paper, we present a spectral atlas covering the wavelength interval 930-1188 Å for O2-O9.5 stars using Far-Ultraviolet Spectroscopic Explorer archival data. The stars selected for the atlas were drawn from three populations: Galactic main-sequence (classes III-V) stars, supergiants, and main-sequence stars in the Magellanic Clouds, which have low metallicities. For several of these stars, we have prepared FITS files comprised of pairs of merged spectra for user access via the Multimission Archive at Space Telescope (MAST). We chose spectra from the first population with spectral types O4, O5, O6, O7, O8, and O9.5 and used them to compile tables and figures with identifications of all possible atmospheric and interstellar medium lines in the region 949-1188 Å. Our identified line totals for these six representative spectra are 821 (500), 992 (663), 1077 (749), 1178 (847), 1359 (1001), and 1798 (1392) lines, respectively, where the numbers in parentheses are the totals of lines formed in the atmospheres, according to spectral synthesis models. The total number of unique atmospheric identifications for the six main-sequence O-star template spectra is 1792, whereas the number of atmospheric lines in common to these spectra is 300. The number of identified lines decreases toward earlier types (increasing effective temperature), while the percentages of "missed" features (unknown lines not predicted from our spectral syntheses) drop from a high of 8% at type B0.2, from our recently published B-star far-UV atlas, to 1%-3% for type O spectra. The percentages of overpredicted lines are similar, despite their being much higher for B-star spectra. We discuss the statistics of line populations among the various elemental ionization states. Also, as an aid to users we list those isolated lines that can be used to determine stellar temperatures and the presence of possible chemical anomalies. Finally, we have prepared FITS files that give pairs of merged spectra for

  1. Classification by diagnosing all absorption features (CDAF) for the most abundant minerals in airborne hyperspectral images

    NASA Astrophysics Data System (ADS)

    Mobasheri, Mohammad Reza; Ghamary-Asl, Mohsen

    2011-12-01

    Imaging through hyperspectral technology is a powerful tool that can be used to spectrally identify and spatially map materials based on their specific absorption characteristics in electromagnetic spectrum. A robust method called Tetracorder has shown its effectiveness at material identification and mapping, using a set of algorithms within an expert system decision-making framework. In this study, using some stages of Tetracorder, a technique called classification by diagnosing all absorption features (CDAF) is introduced. This technique enables one to assign a class to the most abundant mineral in each pixel with high accuracy. The technique is based on the derivation of information from reflectance spectra of the image. This can be done through extraction of spectral absorption features of any minerals from their respected laboratory-measured reflectance spectra, and comparing it with those extracted from the pixels in the image. The CDAF technique has been executed on the AVIRIS image where the results show an overall accuracy of better than 96%.

  2. Spectral Emissivity (6 - 38 µm) of Jupiter's Trojan Asteroids

    NASA Astrophysics Data System (ADS)

    Martin, Audrey; Emery, Joshua P.; Lindsay, Sean S.

    2016-10-01

    Jovian Trojan asteroids, located in Jupiter's stable Lagrange points, are an extensive population of primitive bodies in the Solar System. Previous work in the visible and NIR shows Trojans have featureless, red-sloped spectra and low albedos, making mineralogical characterization difficult. However, it has been shown that three Trojans exhibit silicate emissivity features in the thermal IR (6 - 38 μm Emery et al. 2006, Icarus 182). The detected features indicate the presence of fine-grained (micron-sized) silicate dust on the surfaces, and closely resemble spectral features measured of cometary comae. We hypothesize that Trojan surface mineralogy is fairly uniform and is similar to comet dust. The principal goal of this work is, therefore, to derive primary surface mineralogy from thermal emission spectra. We present thermal IR spectra of 12 Trojans observed with NASA's Spitzer space telescope, using the InfraRed Spectrograph (IRS) in Staring Mode from June 2006 to June 2007. Eight objects were observed over the 5.2 - 38 µm spectral range, and four objects over the 7.5 - 38 µm range. Using the NEATM thermal model, we have computed size, albedo, and beaming parameter for the 12 Trojans. Results for these physical parameters are comparable to those derived from WISE data (Grav et al. 2011, ApJ 742 (1); Grav et al. 2012, ApJ 759 (49)). There are, however, some discrepancies, especially with 2797 Teucer. The emissivity spectra fall into groups that directly correlate with the red and less-red spectral slope groupings described in Emery et al. (2011, ApJ, 141(1)). Strong 10 µm emission features appear in each object, suggesting the presence of fine-grained silicates. Features found between 12-13 µm, and 18-19 µm are also observed in all spectra. We will present these new Trojan asteroid data with mineralogical estimates derived from the emissivity spectra.

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

    PubMed

    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.

  4. Discrete Wavelet Transform-Based Whole-Spectral and Subspectral Analysis for Improved Brain Tumor Clustering Using Single Voxel MR Spectroscopy.

    PubMed

    Yang, Guang; Nawaz, Tahir; Barrick, Thomas R; Howe, Franklyn A; Slabaugh, Greg

    2015-12-01

    Many approaches have been considered for automatic grading of brain tumors by means of pattern recognition with magnetic resonance spectroscopy (MRS). Providing an improved technique which can assist clinicians in accurately identifying brain tumor grades is our main objective. The proposed technique, which is based on the discrete wavelet transform (DWT) of whole-spectral or subspectral information of key metabolites, combined with unsupervised learning, inspects the separability of the extracted wavelet features from the MRS signal to aid the clustering. In total, we included 134 short echo time single voxel MRS spectra (SV MRS) in our study that cover normal controls, low grade and high grade tumors. The combination of DWT-based whole-spectral or subspectral analysis and unsupervised clustering achieved an overall clustering accuracy of 94.8% and a balanced error rate of 7.8%. To the best of our knowledge, it is the first study using DWT combined with unsupervised learning to cluster brain SV MRS. Instead of dimensionality reduction on SV MRS or feature selection using model fitting, our study provides an alternative method of extracting features to obtain promising clustering results.

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

    NASA Astrophysics Data System (ADS)

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

    2014-01-01

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

  6. Intelligent multi-spectral IR image segmentation

    NASA Astrophysics Data System (ADS)

    Lu, Thomas; Luong, Andrew; Heim, Stephen; Patel, Maharshi; Chen, Kang; Chao, Tien-Hsin; Chow, Edward; Torres, Gilbert

    2017-05-01

    This article presents a neural network based multi-spectral image segmentation method. A neural network is trained on the selected features of both the objects and background in the longwave (LW) Infrared (IR) images. Multiple iterations of training are performed until the accuracy of the segmentation reaches satisfactory level. The segmentation boundary of the LW image is used to segment the midwave (MW) and shortwave (SW) IR images. A second neural network detects the local discontinuities and refines the accuracy of the local boundaries. This article compares the neural network based segmentation method to the Wavelet-threshold and Grab-Cut methods. Test results have shown increased accuracy and robustness of this segmentation scheme for multi-spectral IR images.

  7. kmer-SVM: a web server for identifying predictive regulatory sequence features in genomic data sets.

    PubMed

    Fletez-Brant, Christopher; Lee, Dongwon; McCallion, Andrew S; Beer, Michael A

    2013-07-01

    Massively parallel sequencing technologies have made the generation of genomic data sets a routine component of many biological investigations. For example, Chromatin immunoprecipitation followed by sequence assays detect genomic regions bound (directly or indirectly) by specific factors, and DNase-seq identifies regions of open chromatin. A major bottleneck in the interpretation of these data is the identification of the underlying DNA sequence code that defines, and ultimately facilitates prediction of, these transcription factor (TF) bound or open chromatin regions. We have recently developed a novel computational methodology, which uses a support vector machine (SVM) with kmer sequence features (kmer-SVM) to identify predictive combinations of short transcription factor-binding sites, which determine the tissue specificity of these genomic assays (Lee, Karchin and Beer, Discriminative prediction of mammalian enhancers from DNA sequence. Genome Res. 2011; 21:2167-80). This regulatory information can (i) give confidence in genomic experiments by recovering previously known binding sites, and (ii) reveal novel sequence features for subsequent experimental testing of cooperative mechanisms. Here, we describe the development and implementation of a web server to allow the broader research community to independently apply our kmer-SVM to analyze and interpret their genomic datasets. We analyze five recently published data sets and demonstrate how this tool identifies accessory factors and repressive sequence elements. kmer-SVM is available at http://kmersvm.beerlab.org.

  8. kmer-SVM: a web server for identifying predictive regulatory sequence features in genomic data sets

    PubMed Central

    Fletez-Brant, Christopher; Lee, Dongwon; McCallion, Andrew S.; Beer, Michael A.

    2013-01-01

    Massively parallel sequencing technologies have made the generation of genomic data sets a routine component of many biological investigations. For example, Chromatin immunoprecipitation followed by sequence assays detect genomic regions bound (directly or indirectly) by specific factors, and DNase-seq identifies regions of open chromatin. A major bottleneck in the interpretation of these data is the identification of the underlying DNA sequence code that defines, and ultimately facilitates prediction of, these transcription factor (TF) bound or open chromatin regions. We have recently developed a novel computational methodology, which uses a support vector machine (SVM) with kmer sequence features (kmer-SVM) to identify predictive combinations of short transcription factor-binding sites, which determine the tissue specificity of these genomic assays (Lee, Karchin and Beer, Discriminative prediction of mammalian enhancers from DNA sequence. Genome Res. 2011; 21:2167–80). This regulatory information can (i) give confidence in genomic experiments by recovering previously known binding sites, and (ii) reveal novel sequence features for subsequent experimental testing of cooperative mechanisms. Here, we describe the development and implementation of a web server to allow the broader research community to independently apply our kmer-SVM to analyze and interpret their genomic datasets. We analyze five recently published data sets and demonstrate how this tool identifies accessory factors and repressive sequence elements. kmer-SVM is available at http://kmersvm.beerlab.org. PMID:23771147

  9. Properties of Spectral Shapes of Whistler-Mode Emissions

    NASA Astrophysics Data System (ADS)

    Macusova, E.; Santolik, O.; Pickett, J. S.; Gurnett, D. A.; Cornilleau-Wehrlin, N.

    2014-12-01

    Whistler-mode emissions play an important role in wave-particle interactions occurring in the radiation belt region. Whistler mode chorus emissions consist of discrete wave packets which exhibit different spectral shapes. Rising tones (events with positive value of the frequency sweep rate) are frequently observed. Other categories of chorus spectral shapes, such as falling tones, hooks, broadband patterns, are also known. Whistler-mode emissions can additionally occur as hiss or combinations of hiss with discrete patterns. In this study, we have analyzed more than 11 years of high-time resolution measurements provided by the Wideband Data (WBD) instrument onboard four Cluster spacecraft to identify different spectral shapes of whistler mode emissions. We determine the distribution of individual groups of chorus spectral shapes in the Earth's magnetosphere and the effect of the different geomagnetic conditions on their occurrence. We focus on average polarization and propagation properties of the different types of spectral shapes, obtained during visually identified time intervals from multicomponent measurements of the STAFF-SA instrument recorded with a time resolution of 4 seconds.

  10. Ordinary Chondrite Spectral Signatures in the 243 Ida Asteroid System

    NASA Astrophysics Data System (ADS)

    Granahan, J. C.

    2012-12-01

    The NASA Galileo spacecraft observed asteroid 243 Ida and satellite Dactyl on August 28, 1993, with the Near Infrared Mapping Spectrometer (NIMS) at wavelengths ranging from 0.7 to 5.2 micrometers[Carlson et al., 1994]. Work is being conducted to produce radiance-calibrated spectral images of 243 Ida consisting of 17-channel, 299 meters per pixel files and a 102-channel, 3.2 kilometer per pixel NIMS observations of 243 Ida for the NASA Planetary Data System (PDS). These data are currently archived in PDS as uncalibrated data number counts. Radiometric calibrated 17-channel and 102-channel NIMS spectral data files of Dactyl and light curve 243 Ida observations are also being prepared. Analysis of this infrared asteroid data has confirmed that both 243 Ida and Dactyl are S-type asteroid objects and found that their olivine and pyroxene mineral abundances are consistent with that of ordinary chondrite meteorites. Tholen [1989] identified 243 Ida and Chapman et al. [1995] identified Dactyl as S-type asteroids on the basis of spectral data ranging from 0.4 to 1.0 micrometers. S-type are described [Tholen, 1989] as asteroids with a moderate albedos, a moderate to strong absorption feature shortward of 0.7 micrometers, and moderate to nonexistent absorption features longward of 0.7 micrometers. DeMeo et al. [2009] found 243 Ida to be a Sw asteroid based on Earth-based spectral observations 0.4 to 2.5 micrometers in range. Sw is a subclass of S-type asteroids that has a space weathering spectral component [DeMeo et al., 2009]. The NIMS data 243 Ida and Dactyl processed in this study exhibit signatures consistent with the Sw designation of DeMeo et al. [2009]. Measurements of olivine and pyroxene spectral bands were also conducted for the NIMS radiance data of 243 Ida and Dactyl. Band depth and band center measurements have been used to compare S-type asteroids with those of meteorites [Dunn et al., 2010; Gaffey et al., 1993]. The 243 Ida spectra were found to be consistent

  11. Spectral gamuts and spectral gamut mapping

    NASA Astrophysics Data System (ADS)

    Rosen, Mitchell R.; Derhak, Maxim W.

    2006-01-01

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

  12. Characterizing mammographic images by using generic texture features

    PubMed Central

    2012-01-01

    Introduction Although mammographic density is an established risk factor for breast cancer, its use is limited in clinical practice because of a lack of automated and standardized measurement methods. The aims of this study were to evaluate a variety of automated texture features in mammograms as risk factors for breast cancer and to compare them with the percentage mammographic density (PMD) by using a case-control study design. Methods A case-control study including 864 cases and 418 controls was analyzed automatically. Four hundred seventy features were explored as possible risk factors for breast cancer. These included statistical features, moment-based features, spectral-energy features, and form-based features. An elaborate variable selection process using logistic regression analyses was performed to identify those features that were associated with case-control status. In addition, PMD was assessed and included in the regression model. Results Of the 470 image-analysis features explored, 46 remained in the final logistic regression model. An area under the curve of 0.79, with an odds ratio per standard deviation change of 2.88 (95% CI, 2.28 to 3.65), was obtained with validation data. Adding the PMD did not improve the final model. Conclusions Using texture features to predict the risk of breast cancer appears feasible. PMD did not show any additional value in this study. With regard to the features assessed, most of the analysis tools appeared to reflect mammographic density, although some features did not correlate with PMD. It remains to be investigated in larger case-control studies whether these features can contribute to increased prediction accuracy. PMID:22490545

  13. Acousto-optic infrared spectral imager for Pluto fast flyby

    NASA Technical Reports Server (NTRS)

    Glenar, D. A.; Hillman, J. J.

    1993-01-01

    Acousto-optic tunable filters (AOTF's) enable the design of compact, two-dimensional imaging spectrometers with high spectral and spatial resolution and with no moving parts. Tellurium dioxide AOTF's operate from about 400 nm to nearly 5 microns, and a single device will tune continuously over one octave by changing the RF acoustic frequency applied to the device. An infrared (1.2-2.5 micron) Acousto-Optic Imaging Spectrometer (AImS) was designed that closely conforms to the surface composition mapping objectives of the Pluto Fast Flyby. It features a 75-cm focal length telescope, infrared AOTF, and 256 x 256 NICMOS-3 focal plane array for acquiring narrowband images with a spectral resolving power (lambda/delta(lambda)) exceeding 250. We summarize the instrument design features and its expected performance at the Pluto-Charon encounter.

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

    PubMed

    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

  15. Spectral Characteristics of the Unitary Critical Almost-Mathieu Operator

    NASA Astrophysics Data System (ADS)

    Fillman, Jake; Ong, Darren C.; Zhang, Zhenghe

    2017-04-01

    We discuss spectral characteristics of a one-dimensional quantum walk whose coins are distributed quasi-periodically. The unitary update rule of this quantum walk shares many spectral characteristics with the critical Almost-Mathieu Operator; however, it possesses a feature not present in the Almost-Mathieu Operator, namely singularity of the associated cocycles (this feature is, however, present in the so-called Extended Harper's Model). We show that this operator has empty absolutely continuous spectrum and that the Lyapunov exponent vanishes on the spectrum; hence, this model exhibits Cantor spectrum of zero Lebesgue measure for all irrational frequencies and arbitrary phase, which in physics is known as Hofstadter's butterfly. In fact, we will show something stronger, namely, that all spectral parameters in the spectrum are of critical type, in the language of Avila's global theory of analytic quasiperiodic cocycles. We further prove that it has empty point spectrum for each irrational frequency and away from a frequency-dependent set of phases having Lebesgue measure zero. The key ingredients in our proofs are an adaptation of Avila's Global Theory to the present setting, self-duality via the Fourier transform, and a Johnson-type theorem for singular dynamically defined CMV matrices which characterizes their spectra as the set of spectral parameters at which the associated cocycles fail to admit a dominated splitting.

  16. Spectral Observations and Analyses of Low-Redshift Type Ia Supernovae

    NASA Astrophysics Data System (ADS)

    Silverman, Jeffrey Michael

    The explosive deaths of stars, known as a supernovae (SNe), have been critical to our understanding of the Universe for centuries. An introduction to SNe, their importance in astronomy, and how we observe them is given in Chapter 1. In the second Chapter, I present the full BSNIP sample which consists of 1298 low-redshift (z ≤ 0.2) optical spectra of 582 SNe Ia observed from 1989 through the end of 2008. I describe our spectral classification scheme (using the SuperNova IDentification code, SNID; Blondin & Tonry 2007), utilizing my newly constructed set of SNID spectral templates. These templates allow me to accurately spectroscopically classify the entire BSNIP dataset, and by doing so I am able to reclassify a handful of objects as bona fide SNe Ia and a few other objects as members of some of the peculiar SN Ia subtypes. In fact, the BSNIP dataset includes spectra of nearly 90 spectroscopically peculiar SNe Ia. I also present spectroscopic host-galaxy redshifts of some SNe Ia where these values were previously unknown. I present measurements of spectral features of 432 low-redshift ( z < 0.1) optical spectra within 20 d of maximum brightness of 261 SNe Ia from the BSNIP sample in the third Chapter. I describe in detail my method of automated, robust spectral feature definition and measurement which expands upon similar previous studies. Using this procedure, I attempt to measure expansion velocities, (pseudo-)equivalent widths (pEWs), spectral feature depths, and fluxes at the center and endpoints of each of nine major spectral feature complexes. A sanity check of the consistency of the measurements is performed using the BSNIP data (as well as a separate spectral dataset). I investigate how velocity and pEW evolve with time and how they correlate with each other. Various spectral classification schemes are employed and quantitative spectral differences among the subclasses are investigated. Several ratios of pEW values are calculated and studied. Furthermore

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

    NASA Technical Reports Server (NTRS)

    Singer, R. B.

    1981-01-01

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

  18. Novel Spectral Representations and Sparsity-Driven Algorithms for Shape Modeling and Analysis

    NASA Astrophysics Data System (ADS)

    Zhong, Ming

    respect to the dictionary comprising its Laplacian eigenbasis, and it is then possible to recover this sparse representation from partial measurements of the original shape. Taking advantage of the sparsity cue, we advocate a novel variational approach for surface inpainting, integrating data fidelity constraints on the shape domain with coefficient sparsity constraints on the transformed domain. Because of the powerful properties of Laplacian eigenbasis, the inpainting results of our method tend to be globally coherent with the remaining shape. Informative and discriminative feature descriptors are vital in qualitative and quantitative shape analysis for a large variety of graphics applications. We advocate novel strategies to define generalized, user-specified features on shapes. Our new region descriptors are primarily built upon the coefficients of spectral graph wavelets that are both multi-scale and multi-level in nature, consisting of both local and global information. Based on our novel spectral feature descriptor, we developed a user-specified feature detection framework and a tensor-based shape matching algorithm. Through various experiments, we demonstrate the competitive performance of our proposed methods and the great potential of spectral basis and sparsity-driven methods for shape modeling.

  19. Eclipsing and density effects on the spectral behavior of Beta Lyrae binary system in the UV

    NASA Astrophysics Data System (ADS)

    Sanad, M. R.

    2010-01-01

    We analyze both long and short high resolution ultraviolet spectrum of Beta Lyrae eclipsing binary system observed with the International Ultraviolet Explorer (IUE) between 1980 and 1989. The main spectral features are P Cygni profiles originating from different environments of Beta Lyrae. A set of 23 Mg II k&h spectral lines at 2800 Å, originating from the extended envelope [Hack, M., 1980. IAUS, 88, 271H], have been identified and measured to determine their fluxes and widths. We found that there is spectral variability for these physical parameters with phase, similar to that found for the light curve [Kondo, Y., McCluskey, G.E., Jeffery, M.M.S., Ronald, S.P., Carolina, P.S. McCluskey, Joel, A.E., 1994. ApJ, 421, 787], which we attribute to the eclipse effects [Ak, H., Chadima, P., Harmanec, P., Demircan, O., Yang, S., Koubský, P., Škoda, P., Šlechta, M., Wolf, M., Božić, H., 2007. A&A, 463, 233], in addition to the changes of density and temperature of the region from which these lines are coming, as a result of the variability of mass loss from the primary star to the secondary [Hoffman, J.L., Nordsieck, K.H., Fox, G.K., 1998. AJ, 115, 1576; Linnell, A.P., Hubeny, I., Harmanec, P., 1998. ApJ, 509, 379]. Also we present a study of Fe II spectral line at 2600 Å, originating from the atmosphere of the primary star [Hack, M., 1980. IAUS, 88, 271H]. We found spectral variability of line fluxes and line widths with phase similar to that found for Mg II k&h lines. Finally we present a study of Si IV spectral line at 1394 Å, originating from the extended envelope [Hack, M., 1980. IAUS, 88, 271H]. A set of 52 Si IV spectral line at 1394 Å have been identified and measured to determine their fluxes and widths. Also we found spectral variability of these physical parameters with phase similar to that found for Mg II k&h and Fe II spectral lines.

  20. A Tape Method for Fast Characterization and Identification of Active Pharmaceutical Ingredients in the 2-18 THz Spectral Range

    NASA Astrophysics Data System (ADS)

    Kissi, Eric Ofosu; Bawuah, Prince; Silfsten, Pertti; Peiponen, Kai-Erik

    2015-03-01

    In order to find counterfeit drugs quickly and reliably, we have developed `tape method' a transmission spectroscopic terahertz (THz) measurement technique and compared it with a standard attenuated total reflection (ATR) THz spectroscopic measurement. We used well-known training samples, which include commercial paracetamol and aspirin tablets to check the validity of these two measurement techniques. In this study, the spectral features of some active pharmaceutical ingredients (APIs), such as aspirin and paracetamol are characterized for identification purpose. This work covers a wide THz spectral range namely, 2-18 THz. This proposed simple but novel technique, the tape method, was used for characterizing API and identifying their presence in their dosage forms. By comparing the spectra of the APIs to their dosage forms (powder samples), all distinct fingerprints present in the APIs are also present in their respective dosage forms. The positions of the spectral features obtained with the ATR techniques were akin to that obtained from the tape method. The ATR and the tape method therefore, complement each other. The presence of distinct fingerprints in this spectral range has highlighted the possibility of developing fast THz sensors for the screening of pharmaceuticals. It is worth noting that, the ATR method is applicable to flat faced tablets whereas the tape method is suitable for powders in general (e.g. curved surface tablets that require milling before measurement). Finally, we have demonstrated that ATR techniques can be used to screen counterfeit antimalarial tablets.

  1. EXOPLANETARY DETECTION BY MULTIFRACTAL SPECTRAL ANALYSIS

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

    Agarwal, Sahil; Wettlaufer, John S.; Sordo, Fabio Del

    2017-01-01

    Owing to technological advances, the number of exoplanets discovered has risen dramatically in the last few years. However, when trying to observe Earth analogs, it is often difficult to test the veracity of detection. We have developed a new approach to the analysis of exoplanetary spectral observations based on temporal multifractality, which identifies timescales that characterize planetary orbital motion around the host star and those that arise from stellar features such as spots. Without fitting stellar models to spectral data, we show how the planetary signal can be robustly detected from noisy data using noise amplitude as a source ofmore » information. For observation of transiting planets, combining this method with simple geometry allows us to relate the timescales obtained to primary and secondary eclipse of the exoplanets. Making use of data obtained with ground-based and space-based observations we have tested our approach on HD 189733b. Moreover, we have investigated the use of this technique in measuring planetary orbital motion via Doppler shift detection. Finally, we have analyzed synthetic spectra obtained using the SOAP 2.0 tool, which simulates a stellar spectrum and the influence of the presence of a planet or a spot on that spectrum over one orbital period. We have demonstrated that, so long as the signal-to-noise-ratio ≥ 75, our approach reconstructs the planetary orbital period, as well as the rotation period of a spot on the stellar surface.« less

  2. Automatic Detection and Recognition of Craters Based on the Spectral Features of Lunar Rocks and Minerals

    NASA Astrophysics Data System (ADS)

    Ye, L.; Xu, X.; Luan, D.; Jiang, W.; Kang, Z.

    2017-07-01

    Crater-detection approaches can be divided into four categories: manual recognition, shape-profile fitting algorithms, machine-learning methods and geological information-based analysis using terrain and spectral data. The mainstream method is Shape-profile fitting algorithms. Many scholars throughout the world use the illumination gradient information to fit standard circles by least square method. Although this method has achieved good results, it is difficult to identify the craters with poor "visibility", complex structure and composition. Moreover, the accuracy of recognition is difficult to be improved due to the multiple solutions and noise interference. Aiming at the problem, we propose a method for the automatic extraction of impact craters based on spectral characteristics of the moon rocks and minerals: 1) Under the condition of sunlight, the impact craters are extracted from MI by condition matching and the positions as well as diameters of the craters are obtained. 2) Regolith is spilled while lunar is impacted and one of the elements of lunar regolith is iron. Therefore, incorrectly extracted impact craters can be removed by judging whether the crater contains "non iron" element. 3) Craters which are extracted correctly, are divided into two types: simple type and complex type according to their diameters. 4) Get the information of titanium and match the titanium distribution of the complex craters with normal distribution curve, then calculate the goodness of fit and set the threshold. The complex craters can be divided into two types: normal distribution curve type of titanium and non normal distribution curve type of titanium. We validated our proposed method with MI acquired by SELENE. Experimental results demonstrate that the proposed method has good performance in the test area.

  3. Comparative evaluation of features and techniques for identifying activity type and estimating energy cost from accelerometer data

    PubMed Central

    Kate, Rohit J.; Swartz, Ann M.; Welch, Whitney A.; Strath, Scott J.

    2016-01-01

    Wearable accelerometers can be used to objectively assess physical activity. However, the accuracy of this assessment depends on the underlying method used to process the time series data obtained from accelerometers. Several methods have been proposed that use this data to identify the type of physical activity and estimate its energy cost. Most of the newer methods employ some machine learning technique along with suitable features to represent the time series data. This paper experimentally compares several of these techniques and features on a large dataset of 146 subjects doing eight different physical activities wearing an accelerometer on the hip. Besides features based on statistics, distance based features and simple discrete features straight from the time series were also evaluated. On the physical activity type identification task, the results show that using more features significantly improve results. Choice of machine learning technique was also found to be important. However, on the energy cost estimation task, choice of features and machine learning technique were found to be less influential. On that task, separate energy cost estimation models trained specifically for each type of physical activity were found to be more accurate than a single model trained for all types of physical activities. PMID:26862679

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

    USGS Publications Warehouse

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

    2011-01-01

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

  5. Semiconductor Laser Multi-Spectral Sensing and Imaging

    PubMed Central

    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. PMID:22315555

  6. Semiconductor laser multi-spectral sensing and imaging.

    PubMed

    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.

  7. Spectral Unmixing With Multiple Dictionaries

    NASA Astrophysics Data System (ADS)

    Cohen, Jeremy E.; Gillis, Nicolas

    2018-02-01

    Spectral unmixing aims at recovering the spectral signatures of materials, called endmembers, mixed in a hyperspectral or multispectral image, along with their abundances. A typical assumption is that the image contains one pure pixel per endmember, in which case spectral unmixing reduces to identifying these pixels. Many fully automated methods have been proposed in recent years, but little work has been done to allow users to select areas where pure pixels are present manually or using a segmentation algorithm. Additionally, in a non-blind approach, several spectral libraries may be available rather than a single one, with a fixed number (or an upper or lower bound) of endmembers to chose from each. In this paper, we propose a multiple-dictionary constrained low-rank matrix approximation model that address these two problems. We propose an algorithm to compute this model, dubbed M2PALS, and its performance is discussed on both synthetic and real hyperspectral images.

  8. Cloud classification in polar regions using AVHRR textural and spectral signatures

    NASA Technical Reports Server (NTRS)

    Welch, R. M.; Sengupta, S. K.; Weger, R. C.; Christopher, S. A.; Kuo, K. S.; Carsey, F. D.

    1990-01-01

    Arctic clouds and ice-covered surfaces are classified on the basis of textural and spectral features obtained with AVHRR 1.1-km spatial resolution imagery over the Beaufort Sea during May-October, 1989. Scenes were acquired about every 5 days, for a total of 38 cases. A list comprising 20 arctic-surface and cloud classes is compiled using spectral measures defined by Garand (1988).

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

    NASA Astrophysics Data System (ADS)

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

    2016-10-01

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

  10. Multidomain spectral solution of shock-turbulence interactions

    NASA Technical Reports Server (NTRS)

    Kopriva, David A.; Hussaini, M. Yousuff

    1989-01-01

    The use of a fitted-shock multidomain spectral method for solving the time-dependent Euler equations of gasdynamics is described. The multidomain method allows short spatial scale features near the shock to be resolved throughout the calculation. Examples presented are of a shock-plane wave, shock-hot spot and shock-vortex street interaction.

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  12. Spectral Learning for Supervised Topic Models.

    PubMed

    Ren, Yong; Wang, Yining; Zhu, Jun

    2018-03-01

    Supervised topic models simultaneously model the latent topic structure of large collections of documents and a response variable associated with each document. Existing inference methods are based on variational approximation or Monte Carlo sampling, which often suffers from the local minimum defect. Spectral methods have been applied to learn unsupervised topic models, such as latent Dirichlet allocation (LDA), with provable guarantees. This paper investigates the possibility of applying spectral methods to recover the parameters of supervised LDA (sLDA). We first present a two-stage spectral method, which recovers the parameters of LDA followed by a power update method to recover the regression model parameters. Then, we further present a single-phase spectral algorithm to jointly recover the topic distribution matrix as well as the regression weights. Our spectral algorithms are provably correct and computationally efficient. We prove a sample complexity bound for each algorithm and subsequently derive a sufficient condition for the identifiability of sLDA. Thorough experiments on synthetic and real-world datasets verify the theory and demonstrate the practical effectiveness of the spectral algorithms. In fact, our results on a large-scale review rating dataset demonstrate that our single-phase spectral algorithm alone gets comparable or even better performance than state-of-the-art methods, while previous work on spectral methods has rarely reported such promising performance.

  13. 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.

    PubMed

    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 < 0.05), higher (P < 0.05) intensities of the non-structural 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

  14. Featured Image: Identifying Weird Galaxies

    NASA Astrophysics Data System (ADS)

    Kohler, Susanna

    2017-08-01

    Hoags Object, an example of a ring galaxy. [NASA/Hubble Heritage Team/Ray A. Lucas (STScI/AURA)]The above image (click for the full view) shows PanSTARRSobservationsof some of the 185 galaxies identified in a recent study as ring galaxies bizarre and rare irregular galaxies that exhibit stars and gas in a ring around a central nucleus. Ring galaxies could be formed in a number of ways; one theory is that some might form in a galaxy collision when a smaller galaxy punches through the center of a larger one, triggering star formation around the center. In a recent study, Ian Timmis and Lior Shamir of Lawrence Technological University in Michigan explore ways that we may be able to identify ring galaxies in the overwhelming number of images expected from large upcoming surveys. They develop a computer analysis method that automatically finds ring galaxy candidates based on their visual appearance, and they test their approach on the 3 million galaxy images from the first PanSTARRS data release. To see more of the remarkable galaxies the authors found and to learn more about their identification method, check out the paper below.CitationIan Timmis and Lior Shamir 2017 ApJS 231 2. doi:10.3847/1538-4365/aa78a3

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

    NASA Astrophysics Data System (ADS)

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

    2017-10-01

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

  16. An integrated condition-monitoring method for a milling process using reduced decomposition features

    NASA Astrophysics Data System (ADS)

    Liu, Jie; Wu, Bo; Wang, Yan; Hu, Youmin

    2017-08-01

    Complex and non-stationary cutting chatter affects productivity and quality in the milling process. Developing an effective condition-monitoring approach is critical to accurately identify cutting chatter. In this paper, an integrated condition-monitoring method is proposed, where reduced features are used to efficiently recognize and classify machine states in the milling process. In the proposed method, vibration signals are decomposed into multiple modes with variational mode decomposition, and Shannon power spectral entropy is calculated to extract features from the decomposed signals. Principal component analysis is adopted to reduce feature size and computational cost. With the extracted feature information, the probabilistic neural network model is used to recognize and classify the machine states, including stable, transition, and chatter states. Experimental studies are conducted, and results show that the proposed method can effectively detect cutting chatter during different milling operation conditions. This monitoring method is also efficient enough to satisfy fast machine state recognition and classification.

  17. Identifying the relevant features of the National Digital Cadastral Database (NDCDB) for spatial analysis by using the Delphi Technique

    NASA Astrophysics Data System (ADS)

    Halim, N. Z. A.; Sulaiman, S. A.; Talib, K.; Ng, E. G.

    2018-02-01

    This paper explains the process carried out in identifying the relevant features of the National Digital Cadastral Database (NDCDB) for spatial analysis. The research was initially a part of a larger research exercise to identify the significance of NDCDB from the legal, technical, role and land-based analysis perspectives. The research methodology of applying the Delphi technique is substantially discussed in this paper. A heterogeneous panel of 14 experts was created to determine the importance of NDCDB from the technical relevance standpoint. Three statements describing the relevant features of NDCDB for spatial analysis were established after three rounds of consensus building. It highlighted the NDCDB’s characteristics such as its spatial accuracy, functions, and criteria as a facilitating tool for spatial analysis. By recognising the relevant features of NDCDB for spatial analysis in this study, practical application of NDCDB for various analysis and purpose can be widely implemented.

  18. Spectrotemporal Processing in Spectral Tuning Modules of Cat Primary Auditory Cortex

    PubMed Central

    Atencio, Craig A.; Schreiner, Christoph E.

    2012-01-01

    Spectral integration properties show topographical order in cat primary auditory cortex (AI). Along the iso-frequency domain, regions with predominantly narrowly tuned (NT) neurons are segregated from regions with more broadly tuned (BT) neurons, forming distinct processing modules. Despite their prominent spatial segregation, spectrotemporal processing has not been compared for these regions. We identified these NT and BT regions with broad-band ripple stimuli and characterized processing differences between them using both spectrotemporal receptive fields (STRFs) and nonlinear stimulus/firing rate transformations. The durations of STRF excitatory and inhibitory subfields were shorter and the best temporal modulation frequencies were higher for BT neurons than for NT neurons. For NT neurons, the bandwidth of excitatory and inhibitory subfields was matched, whereas for BT neurons it was not. Phase locking and feature selectivity were higher for NT neurons. Properties of the nonlinearities showed only slight differences across the bandwidth modules. These results indicate fundamental differences in spectrotemporal preferences - and thus distinct physiological functions - for neurons in BT and NT spectral integration modules. However, some global processing aspects, such as spectrotemporal interactions and nonlinear input/output behavior, appear to be similar for both neuronal subgroups. The findings suggest that spectral integration modules in AI differ in what specific stimulus aspects are processed, but they are similar in the manner in which stimulus information is processed. PMID:22384036

  19. Spectral Clustering of Hermean craters hollows

    NASA Astrophysics Data System (ADS)

    Lucchetti, Alice; Pajola, Maurizio; Cremonese, Gabriele; Carli, Cristian; Marzo, Giuseppe; Roush, Ted

    2017-04-01

    The Mercury Dual Imaging System (MDIS, Hawkins et al., 2007) onboard NASA MESSENGER (MErcury Surface, Space ENvironment, GEochemistry, and Ranging) spacecraft, provided high-resolution images of "hollows", i.e. shallow, irregular, rimless, flat-floored depressions with bright interiors and halos, often found on crater walls, rims, floors and central peaks (Blewett et al., 2011, 2013). The formation mechanism of these features was suggested to be related to the depletion of subsurface volatiles (Blewett et al., 2011, Vaughan et al., 2012). To understand the hollows' mineralogical composition, which can provide new insights on Mercury's surface characterization, we applied a spectral clustering method to different craters where hollows are present. We chose, as first test case, the 20 km wide Dominici crater due to previous multiple spectral detection (Vilas et al., 2016). We used the MDIS WAC dataset covering Dominici crater with a scale of 935 m/pixel through eight filters, ranging from 0.433 to 0.996 μm. First, the images have been photometrically corrected using the Hapke parameters (Hapke et al., 2002) derived in Domingue et al. (2015). We then applied a statistical clustering over the entire dataset based on a K-means partitioning algorithm (Marzo et al., 2006). This approach was developed and evaluated by Marzo et al. (2006, 2008, 2009) and makes use of the Calinski and Harabasz criterion (Calinski, T., Harabasz, J., 1974) to identify the intrinsically natural number of clusters, making the process unsupervised. The natural number of ten clusters was identified and spectrally separates the Dominici surrounding terrains from its interior, as well as the two hollows from their edges. The units located on the brightest part of the south wall/rim of Dominici crater clearly present a wide absorption band between 0.558 and 0.828 μm. Hollows surrounding terrains typically present a red slope in the VNIR with a possible weak absorption band centered at 0.748

  20. Hubble Space Telescope studies of low-redshift Type Ia supernovae: evolution with redshift and ultraviolet spectral trends

    NASA Astrophysics Data System (ADS)

    Maguire, K.; Sullivan, M.; Ellis, R. S.; Nugent, P. E.; Howell, D. A.; Gal-Yam, A.; Cooke, J.; Mazzali, P.; Pan, Y.-C.; Dilday, B.; Thomas, R. C.; Arcavi, I.; Ben-Ami, S.; Bersier, D.; Bianco, F. B.; Fulton, B. J.; Hook, I.; Horesh, A.; Hsiao, E.; James, P. A.; Podsiadlowski, P.; Walker, E. S.; Yaron, O.; Kasliwal, M. M.; Laher, R. R.; Law, N. M.; Ofek, E. O.; Poznanski, D.; Surace, J.

    2012-11-01

    We present an analysis of the maximum light, near-ultraviolet (NUV; 2900 < λ < 5500 Å) spectra of 32 low-redshift (0.001 < z < 0.08) Type Ia supernovae (SNe Ia), obtained with the Hubble Space Telescope (HST) using the Space Telescope Imaging Spectrograph. We combine this spectroscopic sample with high-quality gri light curves obtained with robotic telescopes to measure SN Ia photometric parameters, such as stretch (light-curve width), optical colour and brightness (Hubble residual). By comparing our new data to a comparable sample of SNe Ia at intermediate redshift (0.4 < z < 0.9), we detect modest spectral evolution (3σ), in the sense that our mean low-redshift NUV spectrum has a depressed flux compared to its intermediate-redshift counterpart. We also see a strongly increased dispersion about the mean with decreasing wavelength, confirming the results of earlier surveys. We show that these trends are consistent with changes in metallicity as predicted by contemporary SN Ia spectral models. We also examine the properties of various NUV spectral diagnostics in the individual SN spectra. We find a general correlation between SN stretch and the velocity (or position) of many NUV spectral features. In particular, we observe that higher stretch SNe have larger Ca II H&K velocities, which also correlate with host galaxy stellar mass. This latter trend is probably driven by the well-established correlation between stretch and host galaxy stellar mass. We find no significant trends between UV spectral features and optical colour. Mean spectra constructed according to whether the SN has a positive or negative Hubble residual show very little difference at NUV wavelengths, indicating that the NUV evolution and variation we identify does not directly correlate with Hubble diagram residuals. Our work confirms and strengthens earlier conclusions regarding the complex behaviour of SNe Ia in the NUV spectral region, but suggests the correlations we find are more useful in

  1. High-Resolution Broadband Spectral Interferometry

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

    Erskine, D J; Edelstein, J

    2002-08-09

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

  2. Asymmetric lasing at spectral singularities

    NASA Astrophysics Data System (ADS)

    Jin, L.

    2018-03-01

    Scattering coefficients can diverge at spectral singularities. In such situation, the stationary solution becomes a laser solution with outgoing waves only. We explore a parity-time (PT )-symmetric non-Hermitian two-arm Aharonov-Bohm interferometer consisting of three coupled resonators enclosing synthetic magnetic flux. The synthetic magnetic flux does not break the PT symmetry, which protects the symmetric transmission. The features and conditions of symmetric, asymmetric, and unidirectional lasing at spectral singularities are discussed. We elucidate that lasing affected by the interference is asymmetric; asymmetric lasing is induced by the interplay between the synthetic magnetic flux and the system's non-Hermiticity. The product of the left and right transmissions is equal to that of the reflections. Our findings reveal that the synthetic magnetic flux affects light propagation, and the results can be applied in the design of lasing devices.

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

    NASA Astrophysics Data System (ADS)

    Liu, Wanjun; Liang, Xuejian; Qu, Haicheng

    2017-11-01

    Hyperspectral image (HSI) classification is one of the most popular topics in remote sensing community. Traditional and deep learning-based classification methods were proposed constantly in recent years. In order to improve the classification accuracy and robustness, a dimensionality-varied convolutional neural network (DVCNN) was proposed in this paper. DVCNN was a novel deep architecture based on convolutional neural network (CNN). The input of DVCNN was a set of 3D patches selected from HSI which contained spectral-spatial joint information. In the following feature extraction process, each patch was transformed into some different 1D vectors by 3D convolution kernels, which were able to extract features from spectral-spatial data. The rest of DVCNN was about the same as general CNN and processed 2D matrix which was constituted by by all 1D data. So that the DVCNN could not only extract more accurate and rich features than CNN, but also fused spectral-spatial information to improve classification accuracy. Moreover, the robustness of network on water-absorption bands was enhanced in the process of spectral-spatial fusion by 3D convolution, and the calculation was simplified by dimensionality varied convolution. Experiments were performed on both Indian Pines and Pavia University scene datasets, and the results showed that the classification accuracy of DVCNN improved by 32.87% on Indian Pines and 19.63% on Pavia University scene than spectral-only CNN. The maximum accuracy improvement of DVCNN achievement was 13.72% compared with other state-of-the-art HSI classification methods, and the robustness of DVCNN on water-absorption bands noise was demonstrated.

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

    NASA Technical Reports Server (NTRS)

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

    1992-01-01

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

  5. [Accuracy improvement of spectral classification of crop using microwave backscatter data].

    PubMed

    Jia, Kun; Li, Qiang-Zi; Tian, Yi-Chen; Wu, Bing-Fang; Zhang, Fei-Fei; Meng, Ji-Hua

    2011-02-01

    In the present study, VV polarization microwave backscatter data used for improving accuracies of spectral classification of crop is investigated. Classification accuracy using different classifiers based on the fusion data of HJ satellite multi-spectral and Envisat ASAR VV backscatter data are compared. The results indicate that fusion data can take full advantage of spectral information of HJ multi-spectral data and the structure sensitivity feature of ASAR VV polarization data. The fusion data enlarges the spectral difference among different classifications and improves crop classification accuracy. The classification accuracy using fusion data can be increased by 5 percent compared to the single HJ data. Furthermore, ASAR VV polarization data is sensitive to non-agrarian area of planted field, and VV polarization data joined classification can effectively distinguish the field border. VV polarization data associating with multi-spectral data used in crop classification enlarges the application of satellite data and has the potential of spread in the domain of agriculture.

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

    NASA Astrophysics Data System (ADS)

    Kohno, Masanori

    2018-05-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

  8. Multispectral atmospheric mapping sensor of mesoscale water vapor features

    NASA Technical Reports Server (NTRS)

    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.

  9. The Spectral Shift Function and Spectral Flow

    NASA Astrophysics Data System (ADS)

    Azamov, N. A.; Carey, A. L.; Sukochev, F. A.

    2007-11-01

    At the 1974 International Congress, I. M. Singer proposed that eta invariants and hence spectral flow should be thought of as the integral of a one form. In the intervening years this idea has lead to many interesting developments in the study of both eta invariants and spectral flow. Using ideas of [24] Singer’s proposal was brought to an advanced level in [16] where a very general formula for spectral flow as the integral of a one form was produced in the framework of noncommutative geometry. This formula can be used for computing spectral flow in a general semifinite von Neumann algebra as described and reviewed in [5]. In the present paper we take the analytic approach to spectral flow much further by giving a large family of formulae for spectral flow between a pair of unbounded self-adjoint operators D and D + V with D having compact resolvent belonging to a general semifinite von Neumann algebra {mathcal{N}} and the perturbation V in {mathcal{N}} . In noncommutative geometry terms we remove summability hypotheses. This level of generality is made possible by introducing a new idea from [3]. There it was observed that M. G. Krein’s spectral shift function (in certain restricted cases with V trace class) computes spectral flow. The present paper extends Krein’s theory to the setting of semifinite spectral triples where D has compact resolvent belonging to {mathcal{N}} and V is any bounded self-adjoint operator in {mathcal{N}} . We give a definition of the spectral shift function under these hypotheses and show that it computes spectral flow. This is made possible by the understanding discovered in the present paper of the interplay between spectral shift function theory and the analytic theory of spectral flow. It is this interplay that enables us to take Singer’s idea much further to create a large class of one forms whose integrals calculate spectral flow. These advances depend critically on a new approach to the calculus of functions of non

  10. Plasmonic spectral tunability of conductive ternary nitrides

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

    Kassavetis, S.; Patsalas, P., E-mail: ppats@physics.auth.gr; Bellas, D. V.

    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 aforementionedmore » 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.« less

  11. New features of the Moon revealed and identified by CLTM-s01

    NASA Astrophysics Data System (ADS)

    Huang, Qian; Ping, Jinsong; Su, Xiaoli; Shu, Rong; Tang, Geshi

    2009-12-01

    Previous analyses showed a clear asymmetry in the topography, geological material distribution, and crustal thickness between the nearside and farside of the Moon. Lunar detecting data, such as topography and gravity, have made it possible to interpret this hemisphere dichotomy. The high-resolution lunar topographic model CLTM-s01 has revealed that there still exist four unknown features, namely, quasi-impact basin Sternfeld-Lewis (20°S, 232°E), confirmed impact basin Fitzgerald-Jackson (25°N, 191°E), crater Wugang (13°N, 189°E) and volcanic deposited highland Yutu (14°N, 308°E). Furthermore, we analyzed and identified about eleven large-scale impact basins that have been proposed since 1994, and classified them according to their circular characteristics.

  12. Spectral Mapping at Asteroid 101955 Bennu

    NASA Astrophysics Data System (ADS)

    Clark, Beth Ellen; Hamilton, Victoria E.; Emery, Joshua P.; Hawley, C. Luke; Howell, Ellen S.; Lauretta, Dante; Simon, Amy A.; Christensen, Philip R.; Reuter, Dennis

    2017-10-01

    The OSIRIS-REx Asteroid Sample Return mission was launched in September 2016. The main science surveys of asteroid 101955 Bennu start in March 2019. Science instruments include a Visible-InfraRed Spectrometer (OVIRS) and a Thermal Emission Spectrometer (OTES) that will produce observations that will be co-registered to the tessellated shape model of Bennu (the fundamental unit of which is a triangular facet). One task of the science team is to synthesize the results in real time during proximity operations to contribute to selection of the sampling site. Hence, we will be focused on quickly producing spectral maps for: (1) mineral abundances; (2) band strengths of minerals and chemicals (including a search for the subtle ~5% absorption feature produced by organics in meteorites); and (3) temperature and thermal inertia values. In sum, we will be producing on the order of ~60 spectral maps of Bennu’s surface composition and thermophysical properties. Due to overlapping surface spots, simulations of our spectral maps show there may be an opportunity to perform spectral super-resolution. We have a large parameter space of choices available in creating spectral maps of Bennu, including: (a) mean facet size (shape model resolution), (b) percentage of overlap between subsequent spot measurements, (c) the number of spectral spots measured per facet, and (d) the mathematical algorithm used to combine the overlapping spots (or bin them on a per-facet basis). Projection effects -- caused by irregular sampling of an irregularly shaped object with circular spectrometer fields-of-view and then mapping these circles onto triangular facets -- can be intense. To prepare for prox ops, we are simulating multiple mineralogical “truth worlds” of Bennu to study the projection effects that result from our planned methods of spectral mapping. This presentation addresses: Can we combine the three planned global surveys of the asteroid (to be obtained at different phase angles) to

  13. Thermal infrared spectral character of Hawaiian basaltic glasses

    NASA Technical Reports Server (NTRS)

    Crisp, Joy; Kahle, Anne B.; Abbott, Elsa A.

    1990-01-01

    Thermal IR reflectance spectra of exposed surfaces of Hawaiian basalt samples from Mauna Loa and Kilauea show systematic changes with age. Spectra of fresh glass collected from active lava flows showed evidence of a strong degree of disorder. After a few weeks of exposure to the laboratory environment, spectra of the top surfaces of these samples began to exhibit spectral features suggestive of ordering into silicate chainlike ansd sheetlike units. With progressive aging, features of apparent sheetlike structures became the preferred mode.

  14. Spectacle and SpecViz: New Spectral Analysis and Visualization Tools

    NASA Astrophysics Data System (ADS)

    Earl, Nicholas; Peeples, Molly; JDADF Developers

    2018-01-01

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

  15. Spectral analysis of time series of categorical variables in earth sciences

    NASA Astrophysics Data System (ADS)

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

    2016-10-01

    Time series of categorical variables often appear in Earth Science disciplines and there is considerable interest in studying their cyclic behavior. This is true, for example, when the type of facies, petrofabric features, ichnofabrics, fossil assemblages or mineral compositions are measured continuously over a core or throughout a stratigraphic succession. Here we deal with the problem of applying spectral analysis to such sequences. A full indicator approach is proposed to complement the spectral envelope often used in other disciplines. Additionally, a stand-alone computer program is provided for calculating the spectral envelope, in this case implementing the permutation test to assess the statistical significance of the spectral peaks. We studied simulated sequences as well as real data in order to illustrate the methodology.

  16. Multi-species Identification of Polymorphic Peptide Variants via Propagation in Spectral Networks

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

    Na, Seungjin; Payne, Samuel H.; Bandeira, Nuno

    The spectral networks approach enables the detection of pairs of spectra from related peptides and thus allows for the propagation of annotations from identified peptides to unidentified spectra. Beyond allowing for unbiased discovery of unexpected post-translational modifications, spectral networks are also applicable to multi-species comparative proteomics or metaproteomics to identify numerous orthologous versions of a protein. We present algorithmic and statistical advances in spectral networks that have made it possible to rigorously assess the statistical significance of spectral pairs and accurately estimate the error rate of identifications via propagation. In the analysis of three related Cyanothece species, a model organismmore » for biohydrogen production, spectral networks identified peptides with highly divergent sequences with up to dozens of variants per peptide, including many novel peptides in species that lack a sequenced genome. Furthermore, spectral networks strongly suggested the presence of novel peptides even in genomically characterized species (i.e. missing from databases) in that a significant portion of unidentified multi-species networks included at least two polymorphic peptide variants.« less

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

    PubMed

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

    2017-10-20

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

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

    NASA Astrophysics Data System (ADS)

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

    2018-01-01

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

  19. Faceting for direction-dependent spectral deconvolution

    NASA Astrophysics Data System (ADS)

    Tasse, C.; Hugo, B.; Mirmont, M.; Smirnov, O.; Atemkeng, M.; Bester, L.; Hardcastle, M. J.; Lakhoo, R.; Perkins, S.; Shimwell, T.

    2018-04-01

    The new generation of radio interferometers is characterized by high sensitivity, wide fields of view and large fractional bandwidth. To synthesize the deepest images enabled by the high dynamic range of these instruments requires us to take into account the direction-dependent Jones matrices, while estimating the spectral properties of the sky in the imaging and deconvolution algorithms. In this paper we discuss and implement a wideband wide-field spectral deconvolution framework (DDFacet) based on image plane faceting, that takes into account generic direction-dependent effects. Specifically, we present a wide-field co-planar faceting scheme, and discuss the various effects that need to be taken into account to solve for the deconvolution problem (image plane normalization, position-dependent Point Spread Function, etc). We discuss two wideband spectral deconvolution algorithms based on hybrid matching pursuit and sub-space optimisation respectively. A few interesting technical features incorporated in our imager are discussed, including baseline dependent averaging, which has the effect of improving computing efficiency. The version of DDFacet presented here can account for any externally defined Jones matrices and/or beam patterns.

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

    DTIC Science & Technology

    2005-04-01

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

  1. Revealing the ultrafast outflow in IRAS 13224-3809 through spectral variability

    NASA Astrophysics Data System (ADS)

    Parker, M. L.; Alston, W. N.; Buisson, D. J. K.; Fabian, A. C.; Jiang, J.; Kara, E.; Lohfink, A.; Pinto, C.; Reynolds, C. S.

    2017-08-01

    We present an analysis of the long-term X-ray variability of the extreme narrow-line Seyfert 1 galaxy IRAS 13224-3809 using principal component analysis (PCA) and fractional excess variability (Fvar) spectra to identify model-independent spectral components. We identify a series of variability peaks in both the first PCA component and Fvar spectrum which correspond to the strongest predicted absorption lines from the ultrafast outflow (UFO) discovered by Parker et al. (2017). We also find higher order PCA components, which correspond to variability of the soft excess and reflection features. The subtle differences between RMS and PCA results argue that the observed flux-dependence of the absorption is due to increased ionization of the gas, rather than changes in column density or covering fraction. This result demonstrates that we can detect outflows from variability alone and that variability studies of UFOs are an extremely promising avenue for future research.

  2. Identifying Patients with Atrioventricular Septal Defect in Down Syndrome Populations by Using Self-Normalizing Neural Networks and Feature Selection.

    PubMed

    Pan, Xiaoyong; Hu, Xiaohua; Zhang, Yu Hang; Feng, Kaiyan; Wang, Shao Peng; Chen, Lei; Huang, Tao; Cai, Yu Dong

    2018-04-12

    Atrioventricular septal defect (AVSD) is a clinically significant subtype of congenital heart disease (CHD) that severely influences the health of babies during birth and is associated with Down syndrome (DS). Thus, exploring the differences in functional genes in DS samples with and without AVSD is a critical way to investigate the complex association between AVSD and DS. In this study, we present a computational method to distinguish DS patients with AVSD from those without AVSD using the newly proposed self-normalizing neural network (SNN). First, each patient was encoded by using the copy number of probes on chromosome 21. The encoded features were ranked by the reliable Monte Carlo feature selection (MCFS) method to obtain a ranked feature list. Based on this feature list, we used a two-stage incremental feature selection to construct two series of feature subsets and applied SNNs to build classifiers to identify optimal features. Results show that 2737 optimal features were obtained, and the corresponding optimal SNN classifier constructed on optimal features yielded a Matthew's correlation coefficient (MCC) value of 0.748. For comparison, random forest was also used to build classifiers and uncover optimal features. This method received an optimal MCC value of 0.582 when top 132 features were utilized. Finally, we analyzed some key features derived from the optimal features in SNNs found in literature support to further reveal their essential roles.

  3. Application of partial least squares near-infrared spectral classification in diabetic identification

    NASA Astrophysics Data System (ADS)

    Yan, Wen-juan; Yang, Ming; He, Guo-quan; Qin, Lin; Li, Gang

    2014-11-01

    In order to identify the diabetic patients by using tongue near-infrared (NIR) spectrum - a spectral classification model of the NIR reflectivity of the tongue tip is proposed, based on the partial least square (PLS) method. 39sample data of tongue tip's NIR spectra are harvested from healthy people and diabetic patients , respectively. After pretreatment of the reflectivity, the spectral data are set as the independent variable matrix, and information of classification as the dependent variables matrix, Samples were divided into two groups - i.e. 53 samples as calibration set and 25 as prediction set - then the PLS is used to build the classification model The constructed modelfrom the 53 samples has the correlation of 0.9614 and the root mean square error of cross-validation (RMSECV) of 0.1387.The predictions for the 25 samples have the correlation of 0.9146 and the RMSECV of 0.2122.The experimental result shows that the PLS method can achieve good classification on features of healthy people and diabetic patients.

  4. Utilizing Hierarchical Clustering to improve Efficiency of Self-Organizing Feature Map to Identify Hydrological Homogeneous Regions

    NASA Astrophysics Data System (ADS)

    Farsadnia, Farhad; Ghahreman, Bijan

    2016-04-01

    Hydrologic homogeneous group identification is considered both fundamental and applied research in hydrology. Clustering methods are among conventional methods to assess the hydrological homogeneous regions. Recently, Self-Organizing feature Map (SOM) method has been applied in some studies. However, the main problem of this method is the interpretation on the output map of this approach. Therefore, SOM is used as input to other clustering algorithms. The aim of this study is to apply a two-level Self-Organizing feature map and Ward hierarchical clustering method to determine the hydrologic homogenous regions in North and Razavi Khorasan provinces. At first by principal component analysis, we reduced SOM input matrix dimension, then the SOM was used to form a two-dimensional features map. To determine homogeneous regions for flood frequency analysis, SOM output nodes were used as input into the Ward method. Generally, the regions identified by the clustering algorithms are not statistically homogeneous. Consequently, they have to be adjusted to improve their homogeneity. After adjustment of the homogeneity regions by L-moment tests, five hydrologic homogeneous regions were identified. Finally, adjusted regions were created by a two-level SOM and then the best regional distribution function and associated parameters were selected by the L-moment approach. The results showed that the combination of self-organizing maps and Ward hierarchical clustering by principal components as input is more effective than the hierarchical method, by principal components or standardized inputs to achieve hydrologic homogeneous regions.

  5. Spectral negentropy based sidebands and demodulation analysis for planet bearing fault diagnosis

    NASA Astrophysics Data System (ADS)

    Feng, Zhipeng; Ma, Haoqun; Zuo, Ming J.

    2017-12-01

    Planet bearing vibration signals are highly complex due to intricate kinematics (involving both revolution and spinning) and strong multiple modulations (including not only the fault induced amplitude modulation and frequency modulation, but also additional amplitude modulations due to load zone passing, time-varying vibration transfer path, and time-varying angle between the gear pair mesh lines of action and fault impact force vector), leading to difficulty in fault feature extraction. Rolling element bearing fault diagnosis essentially relies on detection of fault induced repetitive impulses carried by resonance vibration, but they are usually contaminated by noise and therefor are hard to be detected. This further adds complexity to planet bearing diagnostics. Spectral negentropy is able to reveal the frequency distribution of repetitive transients, thus providing an approach to identify the optimal frequency band of a filter for separating repetitive impulses. In this paper, we find the informative frequency band (including the center frequency and bandwidth) of bearing fault induced repetitive impulses using the spectral negentropy based infogram. In Fourier spectrum, we identify planet bearing faults according to sideband characteristics around the center frequency. For demodulation analysis, we filter out the sensitive component based on the informative frequency band revealed by the infogram. In amplitude demodulated spectrum (squared envelope spectrum) of the sensitive component, we diagnose planet bearing faults by matching the present peaks with the theoretical fault characteristic frequencies. We further decompose the sensitive component into mono-component intrinsic mode functions (IMFs) to estimate their instantaneous frequencies, and select a sensitive IMF with an instantaneous frequency fluctuating around the center frequency for frequency demodulation analysis. In the frequency demodulated spectrum (Fourier spectrum of instantaneous frequency) of

  6. Multi-Centrality Graph Spectral Decompositions and Their Application to Cyber Intrusion Detection

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

    Chen, Pin-Yu; Choudhury, Sutanay; Hero, Alfred

    Many modern datasets can be represented as graphs and hence spectral decompositions such as graph principal component analysis (PCA) can be useful. Distinct from previous graph decomposition approaches based on subspace projection of a single topological feature, e.g., the centered graph adjacency matrix (graph Laplacian), we propose spectral decomposition approaches to graph PCA and graph dictionary learning that integrate multiple features, including graph walk statistics, centrality measures and graph distances to reference nodes. In this paper we propose a new PCA method for single graph analysis, called multi-centrality graph PCA (MC-GPCA), and a new dictionary learning method for ensembles ofmore » graphs, called multi-centrality graph dictionary learning (MC-GDL), both based on spectral decomposition of multi-centrality matrices. As an application to cyber intrusion detection, MC-GPCA can be an effective indicator of anomalous connectivity pattern and MC-GDL can provide discriminative basis for attack classification.« less

  7. Applicability of spectral indices on thickness identification of oil slick

    NASA Astrophysics Data System (ADS)

    Niu, Yanfei; Shen, Yonglin; Chen, Qihao; Liu, Xiuguo

    2016-10-01

    Hyperspectral remote sensing technology has played a vital role in the identification and monitoring of oil spill events, and amount of spectral indices have been developed. In this paper, the applicability of six frequently-used indices is analyzed, and a combination of spectral indices in aids of support vector machine (SVM) algorithm is used to identify the oil slicks and corresponding thickness. The six spectral indices are spectral rotation (SR), spectral absorption depth (HI), band ratio of blue and green (BG), band ratio of BG and shortwave infrared index (BGN), 555nm and 645nm normalized by the blue band index (NB) and spectral slope (ND). The experimental study is conducted in the Gulf of Mexico oil spill zone, with Airborne Visible Infrared Imaging Spectrometer (AVIRIS) hyperspectral imagery captured in May 17, 2010. The results show that SR index is the best in all six indices, which can effectively distinguish the thickness of the oil slick and identify it from seawater; HI index and ND index can obviously distinguish oil slick thickness; BG, BGN and NB are more suitable to identify oil slick from seawater. With the comparison among different kernel functions of SVM, the classify accuracy show that the polynomial and RBF kernel functions have the best effect on the separation of oil slick thickness and the relatively pure seawater. The applicability of spectral indices of oil slick and the method of oil film thickness identification will in aids of oil/gas exploration and oil spill monitoring.

  8. Single-hole spectral function and spin-charge separation in the t-J model

    NASA Astrophysics Data System (ADS)

    Mishchenko, A. S.; Prokof'ev, N. V.; Svistunov, B. V.

    2001-07-01

    Worm algorithm Monte Carlo simulations of the hole Green function with subsequent spectral analysis were performed for 0.1<=J/t<=0.4 on lattices with up to L×L=32×32 sites at a temperature as low as T=J/40, and present, apparently, the hole spectral function in the thermodynamic limit. Spectral analysis reveals a δ-function-sharp quasiparticle peak at the lower edge of the spectrum that is incompatible with the power-law singularity and thus rules out the possibility of spin-charge separation in this parameter range. Spectral continuum features two peaks separated by a gap ~4÷5 t.

  9. Spectral characterization of surface emissivities in the thermal infrared

    NASA Astrophysics Data System (ADS)

    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

  10. Advances in Spectral-Spatial Classification of Hyperspectral Images

    NASA Technical Reports Server (NTRS)

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

    2012-01-01

    Recent advances in spectral-spatial classification of hyperspectral images are presented in this paper. Several techniques are investigated for combining both spatial and spectral information. Spatial information is extracted at the object (set of pixels) level rather than at the conventional pixel level. Mathematical morphology is first used to derive the morphological profile of the image, which includes characteristics about the size, orientation and contrast of the spatial structures present in the image. Then the morphological neighborhood is defined and used to derive additional features for classification. Classification is performed with support vector machines using the available spectral information and the extracted spatial information. Spatial post-processing is next investigated to build more homogeneous and spatially consistent thematic maps. To that end, three presegmentation techniques are applied to define regions that are used to regularize the preliminary pixel-wise thematic map. Finally, a multiple classifier system is defined to produce relevant markers that are exploited to segment the hyperspectral image with the minimum spanning forest algorithm. Experimental results conducted on three real hyperspectral images with different spatial and spectral resolutions and corresponding to various contexts are presented. They highlight the importance of spectral-spatial strategies for the accurate classification of hyperspectral images and validate the proposed methods.

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

    NASA Astrophysics Data System (ADS)

    Li, N.; Wang, C.; Zhao, H.; Gong, X.; Wang, D.

    2018-04-01

    Spatial and spectral information are obtained simultaneously by hyperspectral remote sensing. Joint extraction of these information of hyperspectral image is one of most import methods for hyperspectral image classification. In this paper, a novel deep convolutional neural network (CNN) is proposed, which extracts spectral-spatial information of hyperspectral images correctly. The proposed model not only learns sufficient knowledge from the limited number of samples, but also has powerful generalization ability. The proposed framework based on three-dimensional convolution can extract spectral-spatial features of labeled samples effectively. Though CNN has shown its robustness to distortion, it cannot extract features of different scales through the traditional pooling layer that only have one size of pooling window. Hence, spatial pyramid pooling (SPP) is introduced into three-dimensional local convolutional filters for hyperspectral classification. Experimental results with a widely used hyperspectral remote sensing dataset show that the proposed model provides competitive performance.

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

    PubMed

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

    2013-12-01

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

  13. 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

    PubMed Central

    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 < 0.05), higher (P < 0.05) intensities of the non-structural 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

  14. Spectral function of a hole in the t - J model

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

    Liu, Z.; Manousakis, E.

    1991-08-01

    We give numerical solutions, on finite but large-size square lattices, of the equation for the single-hole Green's function obtained by the self-consistent approach of Schmitt-Rink {ital et} {ital al}. and Kane {ital et} {ital al}. The spectral function of the hole in a quantum antiferromagnet shows that most features describing the hole motion are in close agreement with the results of the exact diagonalization on the 4{sup 2} lattice in the region of {ital J}/{ital t}{le}0.2. Our results obtained on sufficiently large-size lattices suggest that certain important features of the spectral function survive in the thermodynamic limit while others changemore » due to finite-size effects. We find that the leading nonzero vertex correction is given by a two-loop diagram, which has a small contribution.« less

  15. Tandem mass spectrometry spectral libraries and library searching.

    PubMed

    Deutsch, Eric W

    2011-01-01

    Spectral library searching in the field of proteomics has been gaining visibility and use in the last few years, primarily due to the expansion of public proteomics data repositories and the large spectral libraries that can be generated from them. Spectral library searching has several advantages over conventional sequence searching: it is generally much faster, and has higher specificity and sensitivity. The speed increase is primarily, due to having a smaller, fully indexable search space of real spectra that are known to be observable. The increase in specificity and sensitivity is primarily due to the ability of a search engine to utilize the known intensities of the fragment ions, rather than just comparing with theoretical spectra as is done with sequence searching. The main disadvantage of spectral library searching is that one can only identify peptide ions that have been seen before and are stored in the spectral library. In this chapter, an overview of spectral library searching and the libraries currently available are presented.

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

    PubMed

    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.

  17. Eigensolution analysis of spectral/hp continuous Galerkin approximations to advection-diffusion problems: Insights into spectral vanishing viscosity

    NASA Astrophysics Data System (ADS)

    Moura, R. C.; Sherwin, S. J.; Peiró, J.

    2016-02-01

    This study addresses linear dispersion-diffusion analysis for the spectral/hp continuous Galerkin (CG) formulation in one dimension. First, numerical dispersion and diffusion curves are obtained for the advection-diffusion problem and the role of multiple eigencurves peculiar to spectral/hp methods is discussed. From the eigencurves' behaviour, we observe that CG might feature potentially undesirable non-smooth dispersion/diffusion characteristics for under-resolved simulations of problems strongly dominated by either convection or diffusion. Subsequently, the linear advection equation augmented with spectral vanishing viscosity (SVV) is analysed. Dispersion and diffusion characteristics of CG with SVV-based stabilization are verified to display similar non-smooth features in flow regions where convection is much stronger than dissipation or vice-versa, owing to a dependency of the standard SVV operator on a local Péclet number. First a modification is proposed to the traditional SVV scaling that enforces a globally constant Péclet number so as to avoid the previous issues. In addition, a new SVV kernel function is suggested and shown to provide a more regular behaviour for the eigencurves along with a consistent increase in resolution power for higher-order discretizations, as measured by the extent of the wavenumber range where numerical errors are negligible. The dissipation characteristics of CG with the SVV modifications suggested are then verified to be broadly equivalent to those obtained through upwinding in the discontinuous Galerkin (DG) scheme. Nevertheless, for the kernel function proposed, the full upwind DG scheme is found to have a slightly higher resolution power for the same dissipation levels. These results show that improved CG-SVV characteristics can be pursued via different kernel functions with the aid of optimization algorithms.

  18. Preliminary measurements of spectral signatures of tropical and temperate plants in the thermal infrared

    NASA Technical Reports Server (NTRS)

    Salisbury, John W.; Milton, N. M.

    1987-01-01

    Spectral reflectance measurements of seven tropical species and six deciduous species were carried out in thermal infrared to establish the species-dependent spectral characteristics and to investigate the effect on spectral signatures of environmental variables, such as leaf maturity, drought, and metal stress. Seasonal variations of spectral signatures occurred between spring and summer leaves, but such variations were minimal during summer and early fall. Overall reflectance of senescent leaves was higher than that of young leaves, as was the reflectance of leaves from trees growing in metal-enriched soils, as compared with leaves from the control area. However, the characteristic spectral features were not changed in either case. It was also found that water stress did not have any effect on the infrared signatures: trees grown during a drought season maintained their characteristic spectral signatures.

  19. sEMG feature evaluation for identification of elbow angle resolution in graded arm movement.

    PubMed

    Castro, Maria Claudia F; Colombini, Esther L; Aquino, Plinio T; Arjunan, Sridhar P; Kumar, Dinesh K

    2014-11-25

    Automatic and accurate identification of elbow angle from surface electromyogram (sEMG) is essential for myoelectric controlled upper limb exoskeleton systems. This requires appropriate selection of sEMG features, and identifying the limitations of such a system.This study has demonstrated that it is possible to identify three discrete positions of the elbow; full extension, right angle, and mid-way point, with window size of only 200 milliseconds. It was seen that while most features were suitable for this purpose, Power Spectral Density Averages (PSD-Av) performed best. The system correctly classified the sEMG against the elbow angle for 100% cases when only two discrete positions (full extension and elbow at right angle) were considered, while correct classification was 89% when there were three discrete positions. However, sEMG was unable to accurately determine the elbow position when five discrete angles were considered. It was also observed that there was no difference for extension or flexion phases.

  20. Spectral Features and Charge Dynamics of Lead Halide Perovskites: Origins and Interpretations.

    PubMed

    Sum, Tze Chien; Mathews, Nripan; Xing, Guichuan; Lim, Swee Sien; Chong, Wee Kiang; Giovanni, David; Dewi, Herlina Arianita

    2016-02-16

    to the spectral features of halide perovskites and their origins. In the process, we emphasize some key findings of seminal photophysical studies and draw attention to the interpretations that remain divergent and the open questions. This is followed by a general description into how we prepare and conduct the TAS characterization of CH3NH3PbI3 thin films in our laboratory with specific discussions into the potential pitfalls and the influence of thin film processing on the kinetics. Lastly, we conclude with our views on the challenges and opportunities from the photophysical perspective for the field and our expectations for systems beyond lead halide perovskites.

  1. A multimodal image sensor system for identifying water stress in grapevines

    NASA Astrophysics Data System (ADS)

    Zhao, Yong; Zhang, Qin; Li, Minzan; Shao, Yongni; Zhou, Jianfeng; Sun, Hong

    2012-11-01

    Water stress is one of the most common limitations of fruit growth. Water is the most limiting resource for crop growth. In grapevines, as well as in other fruit crops, fruit quality benefits from a certain level of water deficit which facilitates to balance vegetative and reproductive growth and the flow of carbohydrates to reproductive structures. A multi-modal sensor system was designed to measure the reflectance signature of grape plant surfaces and identify different water stress levels in this paper. The multi-modal sensor system was equipped with one 3CCD camera (three channels in R, G, and IR). The multi-modal sensor can capture and analyze grape canopy from its reflectance features, and identify the different water stress levels. This research aims at solving the aforementioned problems. The core technology of this multi-modal sensor system could further be used as a decision support system that combines multi-modal sensory data to improve plant stress detection and identify the causes of stress. The images were taken by multi-modal sensor which could output images in spectral bands of near-infrared, green and red channel. Based on the analysis of the acquired images, color features based on color space and reflectance features based on image process method were calculated. The results showed that these parameters had the potential as water stress indicators. More experiments and analysis are needed to validate the conclusion.

  2. Human body as a set of biometric features identified by means of optoelectronics

    NASA Astrophysics Data System (ADS)

    Podbielska, Halina; Bauer, Joanna

    2005-09-01

    Human body posses many unique, singular features that are impossible to copy or forge. Nowadays, to establish and to ensure the public security requires specially designed devices and systems. Biometrics is a field of science and technology, exploiting human body characteristics for people recognition. It identifies the most characteristic and unique ones in order to design and construct systems capable to recognize people. In this paper some overview is given, presenting the achievements in biometrics. The verification and identification process is explained, along with the way of evaluation of biometric recognition systems. The most frequently human biometrics used in practice are shortly presented, including fingerprints, facial imaging (including thermal characteristic), hand geometry and iris patterns.

  3. Ion spectral structures observed by the Van Allen Probes

    NASA Astrophysics Data System (ADS)

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

    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.

  4. Carbon stars in the X-Shooter Spectral Library

    NASA Astrophysics Data System (ADS)

    Gonneau, A.; Lançon, A.; Trager, S. C.; Aringer, B.; Lyubenova, M.; Nowotny, W.; Peletier, R. F.; Prugniel, P.; Chen, Y.-P.; Dries, M.; Choudhury, O. S.; Falcón-Barroso, J.; Koleva, M.; Meneses-Goytia, S.; Sánchez-Blázquez, P.; Vazdekis, A.

    2016-05-01

    We provide a new collection of spectra of 35 carbon stars obtained with the ESO/VLT X-Shooter instrument as part of the X-Shooter Spectral Library project. The spectra extend from 0.3 μm to 2.4 μm with a resolving power above ~8000. The sample contains stars with a broad range of (J - K) color and pulsation properties located in the Milky Way and the Magellanic Clouds. We show that the distribution of spectral properties of carbon stars at a given (J - K) color becomes bimodal (in our sample) when (J - K) is larger than about 1.5. We describe the two families of spectra that emerge, characterized by the presence or absence of the absorption feature at 1.53 μm, generally associated with HCN and C2H2. This feature appears essentially only in large-amplitude variables, though not in all observations. Associated spectral signatures that we interpret as the result of veiling by circumstellar matter, indicate that the 1.53 μm feature might point to episodes of dust production in carbon-rich Miras. Based on observations collected at the European Southern Observatory, Paranal, Chile, Prog. ID 084.B-0869(A/B), 085.B-0751(A/B), 189.B-0925(A/B/C/D).Tables 1, B.1, E.1, E.2 are also available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (ftp://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/589/A36The reduced spectra are only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (ftp://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/589/A36

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  6. Spectral Confusion for Cosmological Surveys of Redshifted C II Emission

    NASA Technical Reports Server (NTRS)

    Kogut, A.; Dwek, E.; Moseley, S. H.

    2015-01-01

    Far-infrared cooling lines are ubiquitous features in the spectra of star-forming galaxies. Surveys of redshifted fine-structure lines provide a promising new tool to study structure formation and galactic evolution at redshifts including the epoch of reionization as well as the peak of star formation. Unlike neutral hydrogen surveys, where the 21 cm line is the only bright line, surveys of redshifted fine-structure lines suffer from confusion generated by line broadening, spectral overlap of different lines, and the crowding of sources with redshift. We use simulations to investigate the resulting spectral confusion and derive observing parameters to minimize these effects in pencilbeam surveys of redshifted far-IR line emission. We generate simulated spectra of the 17 brightest far-IR lines in galaxies, covering the 150-1300 µm wavelength region corresponding to redshifts 0 < z < 7, and develop a simple iterative algorithm that successfully identifies the 158 µm [C II] line and other lines. Although the [C II] line is a principal coolant for the interstellar medium, the assumption that the brightest observed lines in a given line of sight are always [C II] lines is a poor approximation to the simulated spectra once other lines are included. Blind line identification requires detection of fainter companion lines from the same host galaxies, driving survey sensitivity requirements. The observations require moderate spectral resolution 700 < R < 4000 with angular resolution between 20? and 10', sufficiently narrow to minimize confusion yet sufficiently large to include a statistically meaningful number of sources.

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

    ERIC Educational Resources Information Center

    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…

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

    PubMed

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

    2017-08-08

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

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

    PubMed Central

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

    2017-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2010-10-01

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

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

    NASA Technical Reports Server (NTRS)

    Key, J.

    1990-01-01

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

  12. High-resolution 3-μm spectra of Jupiter: Latitudinal spectral variations influenced by molecules, clouds, and haze

    NASA Astrophysics Data System (ADS)

    Kim, Sang J.; Geballe, T. R.; Kim, J. H.; Jung, A.; Seo, H. J.; Minh, Y. C.

    2010-08-01

    We present latitudinally-resolved high-resolution ( R = 37,000) pole-to-pole spectra of Jupiter in various narrow longitudinal ranges, in spectral intervals covering roughly half of the spectral range 2.86-3.53 μm. We have analyzed the data with the aid of synthetic spectra generated from a model jovian atmosphere that included lines of CH 4, CH 3D, NH 3, C 2H 2, C 2H 6, PH 3, and HCN, as well as clouds and haze. Numerous spectral features of many of these molecular species are present and are individually identified for the first time, as are many lines of H3+ and a few unidentified spectral features. In both polar regions the 2.86-3.10-μm continuum is more than 10 times weaker than in spectra at lower latitudes, implying that in this wavelength range the single-scattering albedos of polar haze particles are very low. In contrast, the 3.24-3.53 μm the weak polar and equatorial continua are of comparable intensity. We derive vertical distributions of NH 3, C 2H 2 and C 2H 6, and find that the mixing ratios of NH 3 and C 2H 6 show little variation between equatorial and polar regions. However, the mixing ratios of C 2H 2 in the northern and southern polar regions are ˜6 and ˜3 times, respectively, less than those in the equatorial regions. The derived mixing ratio curves of C 2H 2 and C 2H 6 extend up to the 10 -6 bar level, a significantly higher altitude than most previous results in the literature. Further ground-based observations covering other longitudes are needed to test if these mixing ratios are representative values for the equatorial and polar regions.

  13. Mid-IR Spectral Investigation of Normal and Malignant Breast and Cervical Tissue Samples Using a Quantum Cascade Laser-Based Microscope

    NASA Astrophysics Data System (ADS)

    Haugen, Paul

    Mid-infrared (MIR) spectroscopy has been a tool used to identify specific features of normal and malignant tissue samples by utilizing MIR characteristics, specifically in the "fingerprint" region. The fingerprint region is a biologically significant spectral region typically identified between 1500 and 500 cm-1. MIR spectroscopy can be used to study molecular changes and variations occurring in samples, which can then be used to fingerprint specific spectral characteristics and biomarkers in order to categorize the specimens. The most common instruments currently used in this analysis are Fourier transform infrared (FTIR) spectrometers, although properties inherent in these instruments, such as slow data collection time and an inability to specify sample location for the spectral data collection, have placed a ceiling on the clinical practicality of their use for specimen classification and identification. In this thesis, we use a prototype of an infrared hyperspectral imaging microscopy platform based around tunable quantum cascade laser (QCL) technology that has a spectral coverage from 1800-900 cm-1. The quantum cascade lasers are coupled with a series of MIR refractive objectives and an uncooled microbolometer camera. The speed of spectral imaging improves to 30 frames per second, and the high magnification objective has a 1.34 microm pixel resolution with a 0.70 numerical aperture and 4.3 microm spatial resolution. We are able to specify data collection at specific discrete wavelengths as opposed to the full spectrum, which improves the data collection time and de-clutters the data for analysis expediency. Finally, we perform spectral imaging real-time, which aides in selecting precise regions of interest on the target sample. This thesis demonstrates the advantages of exploiting the capabilities of the QCL microscope to advance MIR spectroscopy in the identification of distinguishing traits of normal and malignant breast and cervical tissue samples.

  14. VizieR Online Data Catalog: Far-UV spectral atlas of O-type stars (Smith, 2012)

    NASA Astrophysics Data System (ADS)

    Smith, M. A.

    2012-10-01

    In this paper, we present a spectral atlas covering the wavelength interval 930-1188Å for O2-O9.5 stars using Far-Ultraviolet Spectroscopic Explorer archival data. The stars selected for the atlas were drawn from three populations: Galactic main-sequence (classes III-V) stars, supergiants, and main-sequence stars in the Magellanic Clouds, which have low metallicities. For several of these stars, we have prepared FITS files comprised of pairs of merged spectra for user access via the Multimission Archive at Space Telescope (MAST). We chose spectra from the first population with spectral types O4, O5, O6, O7, O8, and O9.5 and used them to compile tables and figures with identifications of all possible atmospheric and interstellar medium lines in the region 949-1188Å. Our identified line totals for these six representative spectra are 821 (500), 992 (663), 1077 (749), 1178 (847), 1359 (1001), and 1798 (1392) lines, respectively, where the numbers in parentheses are the totals of lines formed in the atmospheres, according to spectral synthesis models. The total number of unique atmospheric identifications for the six main-sequence O-star template spectra is 1792, whereas the number of atmospheric lines in common to these spectra is 300. The number of identified lines decreases toward earlier types (increasing effective temperature), while the percentages of "missed" features (unknown lines not predicted from our spectral syntheses) drop from a high of 8% at type B0.2, from our recently published B-star far-UV atlas (Cat. J/ApJS/186/175), to 1%-3% for type O spectra. The percentages of overpredicted lines are similar, despite their being much higher for B-star spectra. (4 data files).

  15. Interpretation of AIS Images of Cuprite, Nevada Using Constraints of Spectral Mixtures

    NASA Technical Reports Server (NTRS)

    Smith, M. O.; Adams, J. B.

    1985-01-01

    A technique is outlined that tests the hypothesis Airborne Imaging Spectrometer (AIS) image spectra are produced by mixtures of surface materials. This technique allows separation of AIS images into concentration images of spectral endmembers (e.g., surface materials causing spectral variation). Using a spectral reference library it was possible to uniquely identify these spectral endmembers with respect to the reference library and to calibrate the AIS images.

  16. Using Combination of Planar and Height Features for Detecting Built-Up Areas from High-Resolution Stereo Imagery

    NASA Astrophysics Data System (ADS)

    Peng, F.; Cai, X.; Tan, W.

    2017-09-01

    Within-class spectral variation and between-class spectral confusion in remotely sensed imagery degrades the performance of built-up area detection when using planar texture, shape, and spectral features. Terrain slope and building height are often used to optimize the results, but extracted from auxiliary data (e.g. LIDAR data, DSM). Moreover, the auxiliary data must be acquired around the same time as image acquisition. Otherwise, built-up area detection accuracy is affected. Stereo imagery incorporates both planar and height information unlike single remotely sensed images. Stereo imagery acquired by many satellites (e.g. Worldview-4, Pleiades-HR, ALOS-PRISM, and ZY-3) can be used as data source of identifying built-up areas. A new method of identifying high-accuracy built-up areas from stereo imagery is achieved by using a combination of planar and height features. The digital surface model (DSM) and digital orthophoto map (DOM) are first generated from stereo images. Then, height values of above-ground objects (e.g. buildings) are calculated from the DSM, and used to obtain raw built-up areas. Other raw built-up areas are obtained from the DOM using Pantex and Gabor, respectively. Final high-accuracy built-up area results are achieved from these raw built-up areas using the decision level fusion. Experimental results show that accurate built-up areas can be achieved from stereo imagery. The height information used in the proposed method is derived from stereo imagery itself, with no need to require auxiliary height data (e.g. LIDAR data). The proposed method is suitable for spaceborne and airborne stereo pairs and triplets.

  17. Spectral monitoring of AB Aur

    NASA Astrophysics Data System (ADS)

    Rodríguez Díaz, L. F.; Oostra, B.

    2017-07-01

    The Astronomical Observatory of the Universidad de los Andes in Bogotá, Colombia, did a spectral monitoring during 2014 and 2015 to AB Aurigae, the brightest Herbig Ae/be star in the northern hemisphere. The aim of this project is applying spectral techniques, in order to identify specific features that could help us not only to understand how this star is forming, but also to establish a pattern to explain general star formation processes. We have recorded 19 legible spectra with a resolving power of R = 11,0000, using a 40 cm Meade telescope with an eShel spectrograph, coupled by a 50-micron optical fiber. We looked for the prominent absorption lines, the Sodium doublet at 5890Å and 5896Å, respectively and Magnesium II at 4481Å; to measure radial velocities of the star, but, we did not find a constant value. Instead, it ranges from 15 km/s to 32 km/s. This variability could be explained by means of an oscillation or pulsation of the external layers of the star. Other variabilities are observed in some emission lines: Hα, Hβ, He I at 5876Å and Fe II at 5018Å. It seems this phenomenon could be typical in stars that are forming and have a circumstellar disk around themselves. This variability is associated with the nonhomogeneous surface of the star and the interaction that it has with its disk. Results of this interaction could be seen also in the stellar wind ejected by the star. More data are required in order to look for a possible period in the changes of radial velocity of the star, the same for the variability of He I and Fe II, and phenomena present in Hα. We plan to take new data in January of 2017.

  18. Effects of spectral smearing on performance of the spectral ripple and spectro-temporal ripple tests.

    PubMed

    Narne, Vijaya Kumar; Sharma, Mridula; Van Dun, Bram; Bansal, Shalini; Prabhu, Latika; Moore, Brian C J

    2016-12-01

    The main aim of this study was to use spectral smearing to evaluate the efficacy of a spectral ripple test (SRt) using stationary sounds and a recent variant with gliding ripples called the spectro-temporal ripple test (STRt) in measuring reduced spectral resolution. In experiment 1 the highest detectable ripple density was measured using four amounts of spectral smearing (unsmeared, mild, moderate, and severe). The thresholds worsened with increasing smearing and were similar for the SRt and the STRt across the three conditions with smearing. For unsmeared stimuli, thresholds were significantly higher (better) for the STRt than for the SRt. An amplitude fluctuation at the outputs of simulated (gammatone) auditory filters centered above 6400 Hz was identified as providing a potential detection cue for the STRt stimuli. Experiment 2 used notched noise with energy below and above the passband of the SRt and STRt stimuli to reduce confounding cues in the STRt. Thresholds were almost identical for the STRt and SRt for both unsmeared and smeared stimuli, indicating that the confounding cue for the STRt was eliminated by the notched noise. Thresholds obtained with notched noise present could be predicted reasonably accurately using an excitation-pattern model.

  19. Spectral Reconstruction for Obtaining Virtual Hyperspectral Images

    NASA Astrophysics Data System (ADS)

    Perez, G. J. P.; Castro, E. C.

    2016-12-01

    Hyperspectral sensors demonstrated its capabalities in identifying materials and detecting processes in a satellite scene. However, availability of hyperspectral images are limited due to the high development cost of these sensors. Currently, most of the readily available data are from multi-spectral instruments. Spectral reconstruction is an alternative method to address the need for hyperspectral information. The spectral reconstruction technique has been shown to provide a quick and accurate detection of defects in an integrated circuit, recovers damaged parts of frescoes, and it also aids in converting a microscope into an imaging spectrometer. By using several spectral bands together with a spectral library, a spectrum acquired by a sensor can be expressed as a linear superposition of elementary signals. In this study, spectral reconstruction is used to estimate the spectra of different surfaces imaged by Landsat 8. Four atmospherically corrected surface reflectance from three visible bands (499 nm, 585 nm, 670 nm) and one near-infrared band (872 nm) of Landsat 8, and a spectral library of ground elements acquired from the United States Geological Survey (USGS) are used. The spectral library is limited to 420-1020 nm spectral range, and is interpolated at one nanometer resolution. Singular Value Decomposition (SVD) is used to calculate the basis spectra, which are then applied to reconstruct the spectrum. The spectral reconstruction is applied for test cases within the library consisting of vegetation communities. This technique was successful in reconstructing a hyperspectral signal with error of less than 12% for most of the test cases. Hence, this study demonstrated the potential of simulating information at any desired wavelength, creating a virtual hyperspectral sensor without the need for additional satellite bands.

  20. Hyperspectral analysis for qualitative and quantitative features related to acid mine drainage at a remediated open-pit mine

    NASA Astrophysics Data System (ADS)

    Davies, G.; Calvin, W. M.

    2015-12-01

    The exposure of pyrite to oxygen and water in mine waste environments is known to generate acidity and the accumulation of secondary iron minerals. Sulfates and secondary iron minerals associated with acid mine drainage (AMD) exhibit diverse spectral properties in the ultraviolet, visible and near-infrared regions of the electromagnetic spectrum. The use of hyperspectral imagery for identification of AMD mineralogy and contamination has been well studied. Fewer studies have examined the impacts of hydrologic variations on mapping AMD or the unique spectral signatures of mine waters. Open-pit mine lakes are an additional environmental hazard which have not been widely studied using imaging spectroscopy. A better understanding of AMD variation related to climate fluctuations and the spectral signatures of contaminated surface waters will aid future assessments of environmental contamination. This study examined the ability of multi-season airborne hyperspectral data to identify the geochemical evolution of substances and contaminant patterns at the Leviathan Mine Superfund site. The mine is located 24 miles southeast of Lake Tahoe and contains remnant tailings piles and several AMD collection ponds. The objectives were to 1) distinguish temporal changes in mineralogy at a the remediated open-pit sulfur mine, 2) identify the absorption features of mine affected waters, and 3) quantitatively link water spectra to known dissolved iron concentrations. Images from NASA's AVIRIS instrument were collected in the spring, summer, and fall seasons for two consecutive years at Leviathan (HyspIRI campaign). Images had a spatial resolution of 15 meters at nadir. Ground-based surveys using the ASD FieldSpecPro spectrometer and laboratory spectral and chemical analysis complemented the remote sensing data. Temporal changes in surface mineralogy were difficult to distinguish. However, seasonal changes in pond water quality were identified. Dissolved ferric iron and chlorophyll

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

    PubMed

    Kortelainen, Jukka; Seppänen, Tapio

    2013-01-01

    Emotions are fundamental for everyday life affecting our communication, learning, perception, and decision making. Including emotions into the human-computer interaction (HCI) could be seen as a significant step forward offering a great potential for developing advanced future technologies. While the electrical activity of the brain is affected by emotions, offers electroencephalogram (EEG) an interesting channel to improve the HCI. In this paper, the selection of subject-independent feature set for EEG-based emotion recognition is studied. We investigate the effect of different feature sets in classifying person's arousal and valence while watching videos with emotional content. The classification performance is optimized by applying a sequential forward floating search algorithm for feature selection. The best classification rate (65.1% for arousal and 63.0% for valence) is obtained with a feature set containing power spectral features from the frequency band of 1-32 Hz. The proposed approach substantially improves the classification rate reported in the literature. In future, further analysis of the video-induced EEG changes including the topographical differences in the spectral features is needed.

  2. Diagnostic accuracy of clinical examination features for identifying large rotator cuff tears in primary health care

    PubMed Central

    Cadogan, Angela; McNair, Peter; Laslett, Mark; Hing, Wayne; Taylor, Stephen

    2013-01-01

    Objectives: Rotator cuff tears are a common and disabling complaint. The early diagnosis of medium and large size rotator cuff tears can enhance the prognosis of the patient. The aim of this study was to identify clinical features with the strongest ability to accurately predict the presence of a medium, large or multitendon (MLM) rotator cuff tear in a primary care cohort. Methods: Participants were consecutively recruited from primary health care practices (n = 203). All participants underwent a standardized history and physical examination, followed by a standardized X-ray series and diagnostic ultrasound scan. Clinical features associated with the presence of a MLM rotator cuff tear were identified (P<0.200), a logistic multiple regression model was derived for identifying a MLM rotator cuff tear and thereafter diagnostic accuracy was calculated. Results: A MLM rotator cuff tear was identified in 24 participants (11.8%). Constant pain and a painful arc in abduction were the strongest predictors of a MLM tear (adjusted odds ratio 3.04 and 13.97 respectively). Combinations of ten history and physical examination variables demonstrated highest levels of sensitivity when five or fewer were positive [100%, 95% confidence interval (CI): 0.86–1.00; negative likelihood ratio: 0.00, 95% CI: 0.00–0.28], and highest specificity when eight or more were positive (0.91, 95% CI: 0.86–0.95; positive likelihood ratio 4.66, 95% CI: 2.34–8.74). Discussion: Combinations of patient history and physical examination findings were able to accurately detect the presence of a MLM rotator cuff tear. These findings may aid the primary care clinician in more efficient and accurate identification of rotator cuff tears that may require further investigation or orthopedic consultation. PMID:24421626

  3. High spectral resolution remote sensing of canopy chemistry

    NASA Technical Reports Server (NTRS)

    Aber, John D.; Martin, Mary E.

    1995-01-01

    Near infrared laboratory spectra have been used for many years to determine nitrogen and lignin concentrations in plant materials. In recent years, similar high spectral resolution visible and infrared data have been available via airborne remote sensing instruments. Using data from NASA's Airborne visible/Infrared Imaging Spectrometer (AVIRIS) we attempt to identify spectral regions correlated with foliar chemistry at the canopy level in temperate forests.

  4. Automated feature extraction and classification from image sources

    USGS Publications Warehouse

    ,

    1995-01-01

    The U.S. Department of the Interior, U.S. Geological Survey (USGS), and Unisys Corporation have completed a cooperative research and development agreement (CRADA) to explore automated feature extraction and classification from image sources. The CRADA helped the USGS define the spectral and spatial resolution characteristics of airborne and satellite imaging sensors necessary to meet base cartographic and land use and land cover feature classification requirements and help develop future automated geographic and cartographic data production capabilities. The USGS is seeking a new commercial partner to continue automated feature extraction and classification research and development.

  5. Humor drawings evoked temporal and spectral EEG processes

    PubMed Central

    Kuo, Hsien-Chu; Chuang, Shang-Wen

    2017-01-01

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

  6. Demonstration of spectral correlation control in a source of polarization-entangled photon pairs at telecom wavelength.

    PubMed

    Lutz, Thomas; Kolenderski, Piotr; Jennewein, Thomas

    2014-03-15

    Spectrally correlated photon pairs can be used to improve the performance of long-range fiber-based quantum communication protocols. We present a source based on spontaneous parametric downconversion, which allows one to control spectral correlations within the entangled photon pair without spectral filtering by changing the pump-pulse duration or the characteristics of the coupled spatial modes. The spectral correlations and polarization entanglement are characterized. We find that the generated photon pairs can feature both positive spectral correlations, decorrelation, or negative correlations at the same time as polarization entanglement with a high fidelity of 0.97 (no background subtraction) with the expected Bell state.

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

    PubMed

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

    2015-10-01

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

  8. Identifying persistent and characteristic features in firearm tool marks on cartridge cases

    NASA Astrophysics Data System (ADS)

    Ott, Daniel; Soons, Johannes; Thompson, Robert; Song, John

    2017-12-01

    Recent concerns about subjectivity in forensic firearm identification have motivated the development of algorithms to compare firearm tool marks that are imparted on ammunition and to generate quantitative measures of similarity. In this paper, we describe an algorithm that identifies impressed tool marks on a cartridge case that are both consistent between firings and contribute strongly to a surface similarity metric. The result is a representation of the tool mark topography that emphasizes both significant and persistent features across firings. This characteristic surface map is useful for understanding the variability and persistence of the tool marks created by a firearm and can provide improved discrimination between the comparison scores of samples fired from the same firearm and the scores of samples fired from different firearms. The algorithm also provides a convenient method for visualizing areas of similarity that may be useful in providing quantitative support for visual comparisons by trained examiners.

  9. The True Ultracool Binary Fraction Using Spectral Binaries

    NASA Astrophysics Data System (ADS)

    Bardalez Gagliuffi, Daniella; Burgasser, Adam J.; Schmidt, Sarah J.; Gagné, Jonathan; Faherty, Jacqueline K.; Cruz, Kelle; Gelino, Chris

    2018-01-01

    Brown dwarfs bridge the gap between stars and giant planets. While the essential mechanisms governing their formation are not well constrained, binary statistics are a direct outcome of the formation process, and thus provide a means to test formation theories. Observational constraints on the brown dwarf binary fraction place it at 10 ‑ 20%, dominated by imaging studies (85% of systems) with the most common separation at 4 AU. This coincides with the resolution limit of state-of-the-art imaging techniques, suggesting that the binary fraction is underestimated. We have developed a separation-independent method to identify and characterize tightly-separated (< 5 AU) binary systems of brown dwarfs as spectral binaries by identifying traces of methane in the spectra of late-M and early-L dwarfs. Imaging follow-up of 17 spectral binaries yielded 3 (18%) resolved systems, corroborating the observed binary fraction, but 5 (29%) known binaries were missed, reinforcing the hypothesis that the short-separation systems are undercounted. In order to find the true binary fraction of brown dwarfs, we have compiled a volume-limited, spectroscopic sample of M7-L5 dwarfs and searched for T dwarf companions. In the 25 pc volume, 4 candidates were found, three of which are already confirmed, leading to a spectral binary fraction of 0.95 ± 0.50%, albeit for a specific combination of spectral types. To extract the true binary fraction and determine the biases of the spectral binary method, we have produced a binary population simulation based on different assumptions of the mass function, age distribution, evolutionary models and mass ratio distribution. Applying the correction fraction resulting from this method to the observed spectral binary fraction yields a true binary fraction of 27 ± 4%, which is roughly within 1σ of the binary fraction obtained from high resolution imaging studies, radial velocity and astrometric monitoring. This method can be extended to identify giant

  10. Formation of spectral lines in planetary atmospheres. I - Theory for cloudy atmospheres: Application to Venus.

    NASA Technical Reports Server (NTRS)

    Hunt, G. E.

    1972-01-01

    The theory of the formation of spectral lines in a cloudy planetary atmosphere is studied in detail. It is shown that models based upon homogeneous, isotropically scattering atmospheres cannot be used to reproduce observed spectroscopic features of phase effect and the shape of spectral lines for weak and strong bands. The theory must, therefore, be developed using an inhomogeneous (gravitational) model of a planetary atmosphere, accurately incorporating all the physical processes of radiative transfer. Such a model of the lower Venus atmosphere, consistent with our present knowledge, is constructed. The results discussed in this article demonstrate the effects of the parameters that describe the atmospheric model on the spectroscopic features of spectral line profile and phase effect, at visible and near infrared wavelengths. This information enables us to develop a comprehensive theory of line formation in a Venus atmosphere.

  11. High-throughput spectral and lifetime-based FRET screening in living cells to identify small-molecule effectors of SERCA

    PubMed Central

    Schaaf, Tory M.; Peterson, Kurt C.; Grant, Benjamin D.; Bawaskar, Prachi; Yuen, Samantha; Li, Ji; Muretta, Joseph M.; Gillispie, Gregory D.; Thomas, David D.

    2017-01-01

    A robust high-throughput screening (HTS) strategy has been developed to discover small-molecule effectors targeting the sarco/endoplasmic reticulum calcium ATPase (SERCA), based on a fluorescence microplate reader that records both the nanosecond decay waveform (lifetime mode) and the complete emission spectrum (spectral mode), with high precision and speed. This spectral unmixing plate reader (SUPR) was used to screen libraries of small molecules with a fluorescence resonance energy transfer (FRET) biosensor expressed in living cells. Ligand binding was detected by FRET associated with structural rearrangements of green (GFP, donor) and red (RFP, acceptor) fluorescent proteins fused to the cardiac-specific SERCA2a isoform. The results demonstrate accurate quantitation of FRET along with high precision of hit identification. Fluorescence lifetime analysis resolved SERCA’s distinct structural states, providing a method to classify small-molecule chemotypes on the basis of their structural effect on the target. The spectral analysis was also applied to flag interference by fluorescent compounds. FRET hits were further evaluated for functional effects on SERCA’s ATPase activity via both a coupled-enzyme assay and a FRET-based calcium sensor. Concentration-response curves indicated excellent correlation between FRET and function. These complementary spectral and lifetime FRET detection methods offer an attractive combination of precision, speed, and resolution for HTS. PMID:27899691

  12. Pattern recognition in volcano seismology - Reducing spectral dimensionality

    NASA Astrophysics Data System (ADS)

    Unglert, K.; Radic, V.; Jellinek, M.

    2015-12-01

    Variations in the spectral content of volcano seismicity can relate to changes in volcanic activity. Low-frequency seismic signals often precede or accompany volcanic eruptions. However, they are commonly manually identified in spectra or spectrograms, and their definition in spectral space differs from one volcanic setting to the next. Increasingly long time series of monitoring data at volcano observatories require automated tools to facilitate rapid processing and aid with pattern identification related to impending eruptions. Furthermore, knowledge transfer between volcanic settings is difficult if the methods to identify and analyze the characteristics of seismic signals differ. To address these challenges we evaluate whether a machine learning technique called Self-Organizing Maps (SOMs) can be used to characterize the dominant spectral components of volcano seismicity without the need for any a priori knowledge of different signal classes. This could reduce the dimensions of the spectral space typically analyzed by orders of magnitude, and enable rapid processing and visualization. Preliminary results suggest that the temporal evolution of volcano seismicity at Kilauea Volcano, Hawai`i, can be reduced to as few as 2 spectral components by using a combination of SOMs and cluster analysis. We will further refine our methodology with several datasets from Hawai`i and Alaska, among others, and compare it to other techniques.

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

    NASA Astrophysics Data System (ADS)

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

    2015-06-01

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

  14. [Changes of Forest Canopy Spectral Reflectance with Seasons in Lang Ya Mountains].

    PubMed

    Li, Wei-tao; Peng, Dao-li; Zhang, Yan; Wu, Jian; Chen, Tai-sheng

    2015-08-01

    The physiological mechanism and ecological structure of forest trees can change with the changes of years. In a certain extent, the changes were expressed through the canopy spectral features. The mastery of changing rules about spectral characteristics of trees over the years is benefit to remote sensing interpretation and provide scientific basis for the classification of different trees. The study adopted high-resolution spectrometer to measure the canopy spectral characteristics for seven major deciduous trees and seven evergreen trees to gain the spectrum curve of four different ages and calculate the first derivative curve. The analysis of changing rules about spectral characteristics of different deciduous trees and evergreen trees and the comparison of changes about spectrum of various trees in the visible and infrared band could find the best year and best band for identification of trees. The results showed that the canopy spectral reflectance of deciduous and evergreen trees increases with the increase of age. And the spectral changes of two species were most obvious in the near infrared band.

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

    DTIC Science & Technology

    2009-08-01

    Raman spectral features of hydroxyapatite crystals (found in breast calcifications) through overlying lean chicken breast tissue [18]. Thus, the...form o f spectral imaging to examine entire margins in a single acquisition . 23 1. INTRODUCTION Of the approxim ately 180,000 patien ts each...ination sources into a single, 10-mm-core liquid light guide, which delivered the illumination light to the sample. 2.3 Data acquisition For lum

  16. Feature selection methods for object-based classification of sub-decimeter resolution digital aerial imagery

    USDA-ARS?s Scientific Manuscript database

    Due to the availability of numerous spectral, spatial, and contextual features, the determination of optimal features and class separabilities can be a time consuming process in object-based image analysis (OBIA). While several feature selection methods have been developed to assist OBIA, a robust c...

  17. The U. S. Geological Survey, Digital Spectral Library: Version 1 (0.2 to 3.0um)

    USGS Publications Warehouse

    Clark, Roger N.; Swayze, Gregg A.; Gallagher, Andrea J.; King, Trude V.V.; Calvin, Wendy M.

    1993-01-01

    We have developed a digital reflectance spectral library, with management and spectral analysis software. The library includes 498 spectra of 444 samples (some samples include a series of grain sizes) measured from approximately 0.2 to 3.0 um . The spectral resolution (Full Width Half Maximum) of the reflectance data is <= 4 nm in the visible (0.2-0.8 um) and <= 10 nm in the NIR (0.8-2.35 um). All spectra were corrected to absolute reflectance using an NIST Halon standard. Library management software lets users search on parameters (e.g. chemical formulae, chemical analyses, purity of samples, mineral groups, etc.) as well as spectral features. Minerals from borate, carbonate, chloride, element, halide, hydroxide, nitrate, oxide, phosphate, sulfate, sulfide, sulfosalt, and the silicate (cyclosilicate, inosilicate, nesosilicate, phyllosilicate, sorosilicate, and tectosilicate) classes are represented. X-Ray and chemical analyses are tabulated for many of the entries, and all samples have been evaluated for spectral purity. The library also contains end and intermediate members for the olivine, garnet, scapolite, montmorillonite, muscovite, jarosite, and alunite solid-solution series. We have included representative spectra of H2O ice, kerogen, ammonium-bearing minerals, rare-earth oxides, desert varnish coatings, kaolinite crystallinity series, kaolinite-smectite series, zeolite series, and an extensive evaporite series. Because of the importance of vegetation to climate-change studies we have include 17 spectra of tree leaves, bushes, and grasses. The library and software are available as a series of U.S.G.S. Open File reports. PC user software is available to convert the binary data to ascii files (a separate U.S.G.S. open file report). Additionally, a binary data files are on line at the U.S.G.S. in Denver for anonymous ftp to users on the Internet. The library search software enables a user to search on documentation parameters as well as spectral features. The

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

    PubMed

    Sousa, Daniel; Small, Christopher

    2018-02-14

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

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

    PubMed Central

    Small, Christopher

    2018-01-01

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

  20. Automatic classification of spectral units in the Aristarchus plateau

    NASA Astrophysics Data System (ADS)

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

    1999-09-01

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

  1. Speech recognition features for EEG signal description in detection of neonatal seizures.

    PubMed

    Temko, A; Boylan, G; Marnane, W; Lightbody, G

    2010-01-01

    In this work, features which are usually employed in automatic speech recognition (ASR) are used for the detection of neonatal seizures in newborn EEG. Three conventional ASR feature sets are compared to the feature set which has been previously developed for this task. The results indicate that the thoroughly-studied spectral envelope based ASR features perform reasonably well on their own. Additionally, the SVM Recursive Feature Elimination routine is applied to all extracted features pooled together. It is shown that ASR features consistently appear among the top-rank features.

  2. "Ersatz" and "hybrid" NMR spectral estimates using the filter diagonalization method.

    PubMed

    Ridge, Clark D; Shaka, A J

    2009-03-12

    The filter diagonalization method (FDM) is an efficient and elegant way to make a spectral estimate purely in terms of Lorentzian peaks. As NMR spectral peaks of liquids conform quite well to this model, the FDM spectral estimate can be accurate with far fewer time domain points than conventional discrete Fourier transform (DFT) processing. However, noise is not efficiently characterized by a finite number of Lorentzian peaks, or by any other analytical form, for that matter. As a result, noise can affect the FDM spectrum in different ways than it does the DFT spectrum, and the effect depends on the dimensionality of the spectrum. Regularization to suppress (or control) the influence of noise to give an "ersatz", or EFDM, spectrum is shown to sometimes miss weak features, prompting a more conservative implementation of filter diagonalization. The spectra obtained, called "hybrid" or HFDM spectra, are acquired by using regularized FDM to obtain an "infinite time" spectral estimate and then adding to it the difference between the DFT of the data and the finite time FDM estimate, over the same time interval. HFDM has a number of advantages compared to the EFDM spectra, where all features must be Lorentzian. They also show better resolution than DFT spectra. The HFDM spectrum is a reliable and robust way to try to extract more information from noisy, truncated data records and is less sensitive to the choice of regularization parameter. In multidimensional NMR of liquids, HFDM is a conservative way to handle the problems of noise, truncation, and spectral peaks that depart significantly from the model of a multidimensional Lorentzian peak.

  3. A Novel Feature-Map Based ICA Model for Identifying the Individual, Intra/Inter-Group Brain Networks across Multiple fMRI Datasets.

    PubMed

    Wang, Nizhuan; Chang, Chunqi; Zeng, Weiming; Shi, Yuhu; Yan, Hongjie

    2017-01-01

    Independent component analysis (ICA) has been widely used in functional magnetic resonance imaging (fMRI) data analysis to evaluate functional connectivity of the brain; however, there are still some limitations on ICA simultaneously handling neuroimaging datasets with diverse acquisition parameters, e.g., different repetition time, different scanner, etc. Therefore, it is difficult for the traditional ICA framework to effectively handle ever-increasingly big neuroimaging datasets. In this research, a novel feature-map based ICA framework (FMICA) was proposed to address the aforementioned deficiencies, which aimed at exploring brain functional networks (BFNs) at different scales, e.g., the first level (individual subject level), second level (intragroup level of subjects within a certain dataset) and third level (intergroup level of subjects across different datasets), based only on the feature maps extracted from the fMRI datasets. The FMICA was presented as a hierarchical framework, which effectively made ICA and constrained ICA as a whole to identify the BFNs from the feature maps. The simulated and real experimental results demonstrated that FMICA had the excellent ability to identify the intergroup BFNs and to characterize subject-specific and group-specific difference of BFNs from the independent component feature maps, which sharply reduced the size of fMRI datasets. Compared with traditional ICAs, FMICA as a more generalized framework could efficiently and simultaneously identify the variant BFNs at the subject-specific, intragroup, intragroup-specific and intergroup levels, implying that FMICA was able to handle big neuroimaging datasets in neuroscience research.

  4. Urban, Forest, and Agricultural AIS Data: Fine Spectral Structure

    NASA Technical Reports Server (NTRS)

    Vanderbilt, V. C.

    1985-01-01

    Spectra acquired by the Airborne Imaging Spectrometer (AIS) near Lafayette, IN, Ely, MN, and over the Stanford University campus, CA were analyzed for fine spectral structure using two techniques: the ratio of radiance of a ground target to the radiance of a standard and also the correlation coefficient of radiances at adjacent wavelengths. The results show ramp like features in the ratios. These features are due to the biochemical composition of the leaf and to the optical scattering properties of its cuticle. The size and shape of the ramps vary with ground cover.

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

    NASA Technical Reports Server (NTRS)

    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.

  6. Application of IRS-1D data in water erosion features detection (case study: Nour roud catchment, Iran).

    PubMed

    Solaimani, K; Amri, M A Hadian

    2008-08-01

    The aim of this study was capability of Indian Remote Sensing (IRS) data of 1D to detecting erosion features which were created from run-off. In this study, ability of PAN digital data of IRS-1D satellite was evaluated for extraction of erosion features in Nour-roud catchment located in Mazandaran province, Iran, using GIS techniques. Research method has based on supervised digital classification, using MLC algorithm and also visual interpretation, using PMU analysis and then these were evaluated and compared. Results indicated that opposite of digital classification, with overall accuracy 40.02% and kappa coefficient 31.35%, due to low spectral resolution; visual interpretation and classification, due to high spatial resolution (5.8 m), prepared classifying erosion features from this data, so that these features corresponded with the lithology, slope and hydrograph lines using GIS, so closely that one can consider their boundaries overlapped. Also field control showed that this data is relatively fit for using this method in investigation of erosion features and specially, can be applied to identify large erosion features.

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

    PubMed

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

    2017-09-13

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

  8. CONNJUR Workflow Builder: A software integration environment for spectral reconstruction

    PubMed Central

    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. PMID:26066803

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

    PubMed

    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.

  10. Spectral Anonymization of Data

    PubMed Central

    Lasko, Thomas A.; Vinterbo, Staal A.

    2011-01-01

    The goal of data anonymization is to allow the release of scientifically useful data in a form that protects the privacy of its subjects. This requires more than simply removing personal identifiers from the data, because an attacker can still use auxiliary information to infer sensitive individual information. Additional perturbation is necessary to prevent these inferences, and the challenge is to perturb the data in a way that preserves its analytic utility. No existing anonymization algorithm provides both perfect privacy protection and perfect analytic utility. We make the new observation that anonymization algorithms are not required to operate in the original vector-space basis of the data, and many algorithms can be improved by operating in a judiciously chosen alternate basis. A spectral basis derived from the data’s eigenvectors is one that can provide substantial improvement. We introduce the term spectral anonymization to refer to an algorithm that uses a spectral basis for anonymization, and we give two illustrative examples. We also propose new measures of privacy protection that are more general and more informative than existing measures, and a principled reference standard with which to define adequate privacy protection. PMID:21373375

  11. Low-energy spectral features of supernova (anti)neutrinos in inverted hierarchy

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

    Fogli, G. L.; Marrone, A.; Tamborra, I.

    2008-11-01

    In the dense supernova core, self-interactions may align the flavor polarization vectors of {nu} and {nu} and induce collective flavor transformations. Different alignment Ansaetze are known to describe approximately the phenomena of synchronized or bipolar oscillations and the split of {nu} energy spectra. We discuss another phenomenon observed in some numerical experiments in inverted hierarchy, showing features akin to a low-energy split of {nu} spectra. The phenomenon appears to be approximately described by another alignment Ansatz which, in the considered scenario, reduces the (nonadiabatic) dynamics of all energy modes to only two {nu} plus two {nu} modes. The associated spectralmore » features, however, appear to be fragile when passing from single to multiangle simulations.« less

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

    PubMed

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

    2017-01-01

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

  13. Single trial decoding of belief decision making from EEG and fMRI data using independent components features

    PubMed Central

    Douglas, Pamela K.; Lau, Edward; Anderson, Ariana; Head, Austin; Kerr, Wesley; Wollner, Margalit; Moyer, Daniel; Li, Wei; Durnhofer, Mike; Bramen, Jennifer; Cohen, Mark S.

    2013-01-01

    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. PMID:23914164

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

    NASA Astrophysics Data System (ADS)

    Tang, Hong; Lin, Jian-Zhong

    2013-01-01

    An improved anomalous diffraction approximation (ADA) method is presented for calculating the extinction efficiency of spheroids firstly. In this approach, the extinction efficiency of spheroid particles can be calculated with good accuracy and high efficiency in a wider size range by combining the Latimer method and the ADA theory, and this method can present a more general expression for calculating the extinction efficiency of spheroid particles with various complex refractive indices and aspect ratios. Meanwhile, the visible spectral extinction with varied spheroid particle size distributions and complex refractive indices is surveyed. Furthermore, a selection principle about the spectral extinction data is developed based on PCA (principle component analysis) of first derivative spectral extinction. By calculating the contribution rate of first derivative spectral extinction, the spectral extinction with more significant features can be selected as the input data, and those with less features is removed from the inversion data. In addition, we propose an improved Tikhonov iteration method to retrieve the spheroid particle size distributions in the independent mode. Simulation experiments indicate that the spheroid particle size distributions obtained with the proposed method coincide fairly well with the given distributions, and this inversion method provides a simple, reliable and efficient method to retrieve the spheroid particle size distributions from the spectral extinction data.

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

    NASA Astrophysics Data System (ADS)

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

    2007-07-01

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

  16. [The study of M dwarf spectral classification].

    PubMed

    Yi, Zhen-Ping; Pan, Jing-Chang; Luo, A-Li

    2013-08-01

    As the most common stars in the galaxy, M dwarfs can be used to trace the structure and evolution of the Milky Way. Besides, investigating M dwarfs is important for searching for habitability of extrasolar planets orbiting M dwarfs. Spectral classification of M dwarfs is a fundamental work. The authors used DR7 M dwarf sample of SLOAN to extract important features from the range of 600-900 nm by random forest method. Compared to the features used in Hammer Code, the authors added three new indices. Our test showed that the improved Hammer with new indices is more accurate. Our method has been applied to classify M dwarf spectra of LAMOST.

  17. Pulse shaping in mode-locked fiber lasers by in-cavity spectral filter.

    PubMed

    Boscolo, Sonia; Finot, Christophe; Karakuzu, Huseyin; Petropoulos, Periklis

    2014-02-01

    We numerically show the possibility of pulse shaping in a passively mode-locked fiber laser by inclusion of a spectral filter into the laser cavity. Depending on the amplitude transfer function of the filter, we are able to achieve various regimes of advanced temporal waveform generation, including ones featuring bright and dark parabolic-, flat-top-, triangular- and saw-tooth-profiled pulses. The results demonstrate the strong potential of an in-cavity spectral pulse shaper for controlling the dynamics of mode-locked fiber lasers.

  18. Spectral-domain optical coherence tomography for endoscopic imaging

    NASA Astrophysics Data System (ADS)

    Chen, Xiaodong; Li, Qiao; Li, Wanhui; Wang, Yi; Yu, Daoyin

    2007-02-01

    Optical coherence tomography (OCT) is an emerging cross-sectional imaging technology. It uses broadband light sources to achieve axial image resolutions on the few micron scale. OCT is widely applied to medical imaging, it can get cross-sectional image of bio-tissue (transparent and turbid) with non-invasion and non-touch. In this paper, the principle of OCT is presented and the crucial parameters of the system are discussed in theory. With analysis of different methods and medical endoscopic system's feature, a design which combines the spectral domain OCT (SDOCT) technique and endoscopy is put forward. SDOCT provides direct access to the spectrum of the optical signal. It is shown to provide higher imaging speed when compared to time domain OCT. At the meantime, a novel OCT probe which uses advanced micromotor to drive reflecting prism is designed according to alimentary tract endoscopic feature. A simple optical coherence tomography system has been developed based on a fiber-based Michelson interferometer and spectrometer. An experiment which uses motor to drive prism to realize rotating imaging is done. Images obtained with this spectral interferometer are presented. The results verify the feasibility of endoscopic optical coherence tomography system with rotating scan.

  19. Advances in Spectral-Spatial Classification of Hyperspectral Images

    NASA Technical Reports Server (NTRS)

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

    2012-01-01

    Recent advances in spectral-spatial classification of hyperspectral images are presented in this paper. Several techniques are investigated for combining both spatial and spectral information. Spatial information is extracted at the object (set of pixels) level rather than at the conventional pixel level. Mathematical morphology is first used to derive the morphological profile of the image, which includes characteristics about the size, orientation, and contrast of the spatial structures present in the image. Then, the morphological neighborhood is defined and used to derive additional features for classification. Classification is performed with support vector machines (SVMs) using the available spectral information and the extracted spatial information. Spatial postprocessing is next investigated to build more homogeneous and spatially consistent thematic maps. To that end, three presegmentation techniques are applied to define regions that are used to regularize the preliminary pixel-wise thematic map. Finally, a multiple-classifier (MC) system is defined to produce relevant markers that are exploited to segment the hyperspectral image with the minimum spanning forest algorithm. Experimental results conducted on three real hyperspectral images with different spatial and spectral resolutions and corresponding to various contexts are presented. They highlight the importance of spectral–spatial strategies for the accurate classification of hyperspectral images and validate the proposed methods.

  20. A comparison of the near-infrared spectral features of early-type galaxies in the Coma Cluster, the Virgo cluster and the field

    NASA Technical Reports Server (NTRS)

    Houdashelt, Mark L.; Frogel, Jay A.

    1993-01-01

    Earlier researchers derived the relative distance between the Coma and Virgo clusters from color-magnitude relations of the early-type galaxies in each cluster. They found that the derived distance was color-dependent and concluded that the galaxies of similar luminosity in the two clusters differ in their red stellar populations. More recently, the color-dependence of the Coma-Virgo distance modulus has been called into question. However, because these two clusters differ so dramatically in their morphologies and kinematics, it is plausible that the star formation histories of the member galaxies also differed. If the conclusions of earlier researchers are indeed correct, then some signature of the resulting stellar population differences should appear in the near-infrared and/or infrared light of the respective galaxies. We have collected near-infrared spectra of 17 Virgo and 10 Coma early-type galaxies; this sample spans about four magnitudes in luminosity in each cluster. Seven field E/S0 galaxies have been observed for comparison. Pseudo-equivalent widths have been measured for all of the field galaxies, all but one of the Virgo members, and five of the Coma galaxies. The features examined are sensitive to the temperature, metallicity, and surface gravity of the reddest stars. A preliminary analysis of these spectral features has been performed, and, with a few notable exceptions, the measured pseudo-equivalent widths agree well with previously published values.

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

    PubMed

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

    2017-01-01

    Hyperspectral imaging is an emerging means of assessing plant vitality, stress parameters, nutrition status, and diseases. Extraction of target values from the high-dimensional datasets either relies on pixel-wise processing of the full spectral information, appropriate selection of individual bands, or calculation of spectral indices. Limitations of such approaches are reduced classification accuracy, reduced robustness due to spatial variation of the spectral information across the surface of the objects measured as well as a loss of information intrinsic to band selection and use of spectral indices. In this paper we present an improved spatial-spectral segmentation approach for the analysis of hyperspectral imaging data and its application for the prediction of powdery mildew infection levels (disease severity) of intact Chardonnay grape bunches shortly before veraison. Instead of calculating texture features (spatial features) for the huge number of spectral bands independently, dimensionality reduction by means of Linear Discriminant Analysis (LDA) was applied first to derive a few descriptive image bands. Subsequent classification was based on modified Random Forest classifiers and selective extraction of texture parameters from the integral image representation of the image bands generated. Dimensionality reduction, integral images, and the selective feature extraction led to improved classification accuracies of up to [Formula: see text] for detached berries used as a reference sample (training dataset). Our approach was validated by predicting infection levels for a sample of 30 intact bunches. Classification accuracy improved with the number of decision trees of the Random Forest classifier. These results corresponded with qPCR results. An accuracy of 0.87 was achieved in classification of healthy, infected, and severely diseased bunches. However, discrimination between visually healthy and infected bunches proved to be challenging for a few samples

  2. [Building Mass Spectrometry Spectral Libraries of Human Cancer Cell Lines].

    PubMed

    Faktor, J; Bouchal, P

    Cancer research often focuses on protein quantification in model cancer cell lines and cancer tissues. SWATH (sequential windowed acquisition of all theoretical fragment ion spectra), the state of the art method, enables the quantification of all proteins included in spectral library. Spectral library contains fragmentation patterns of each detectable protein in a sample. Thorough spectral library preparation will improve quantitation of low abundant proteins which usually play an important role in cancer. Our research is focused on the optimization of spectral library preparation aimed at maximizing the number of identified proteins in MCF-7 breast cancer cell line. First, we optimized the sample preparation prior entering the mass spectrometer. We examined the effects of lysis buffer composition, peptide dissolution protocol and the material of sample vial on the number of proteins identified in spectral library. Next, we optimized mass spectrometry (MS) method for spectral library data acquisition. Our thorough optimized protocol for spectral library building enabled the identification of 1,653 proteins (FDR < 1%) in 1 µg of MCF-7 lysate. This work contributed to the enhancement of protein coverage in SWATH digital biobanks which enable quantification of arbitrary protein from physically unavailable samples. In future, high quality spectral libraries could play a key role in preparing of patient proteome digital fingerprints.Key words: biomarker - mass spectrometry - proteomics - digital biobanking - SWATH - protein quantificationThis work was supported by the project MEYS - NPS I - LO1413.The authors declare they have no potential conflicts of interest concerning drugs, products, or services used in the study.The Editorial Board declares that the manuscript met the ICMJE recommendation for biomedical papers.Submitted: 7. 5. 2016Accepted: 9. 6. 2016.

  3. Characterizing Cyclostationary Features of Digital Modulated Signals with Empirical Measurements using Spectral Correlation Function

    DTIC Science & Technology

    2011-06-01

    USING SPECTRAL CORRELATION FUNCTION THESIS Mujun Song, Captain, ROKA AFIT/GCE/ENG/11-09 DEPARTMENT OF THE AIR FORCE AIR UNIVERSITY AIR...Management Air Force Institute of Technology Air University Air Education and Training Command In Partial Fulfillment of the Requirements for the...generator, Agilent E4438C, ESG Vector Signal Generator. Universal Software Radio Peripheral 2 (USRP2), which is a Software Defined Radio (SDR), is used

  4. A Genetic-Based Feature Selection Approach in the Identification of Left/Right Hand Motor Imagery for a Brain-Computer Interface

    PubMed Central

    Yaacoub, Charles; Mhanna, Georges; Rihana, Sandy

    2017-01-01

    Electroencephalography is a non-invasive measure of the brain electrical activity generated by millions of neurons. Feature extraction in electroencephalography analysis is a core issue that may lead to accurate brain mental state classification. This paper presents a new feature selection method that improves left/right hand movement identification of a motor imagery brain-computer interface, based on genetic algorithms and artificial neural networks used as classifiers. Raw electroencephalography signals are first preprocessed using appropriate filtering. Feature extraction is carried out afterwards, based on spectral and temporal signal components, and thus a feature vector is constructed. As various features might be inaccurate and mislead the classifier, thus degrading the overall system performance, the proposed approach identifies a subset of features from a large feature space, such that the classifier error rate is reduced. Experimental results show that the proposed method is able to reduce the number of features to as low as 0.5% (i.e., the number of ignored features can reach 99.5%) while improving the accuracy, sensitivity, specificity, and precision of the classifier. PMID:28124985

  5. A Genetic-Based Feature Selection Approach in the Identification of Left/Right Hand Motor Imagery for a Brain-Computer Interface.

    PubMed

    Yaacoub, Charles; Mhanna, Georges; Rihana, Sandy

    2017-01-23

    Electroencephalography is a non-invasive measure of the brain electrical activity generated by millions of neurons. Feature extraction in electroencephalography analysis is a core issue that may lead to accurate brain mental state classification. This paper presents a new feature selection method that improves left/right hand movement identification of a motor imagery brain-computer interface, based on genetic algorithms and artificial neural networks used as classifiers. Raw electroencephalography signals are first preprocessed using appropriate filtering. Feature extraction is carried out afterwards, based on spectral and temporal signal components, and thus a feature vector is constructed. As various features might be inaccurate and mislead the classifier, thus degrading the overall system performance, the proposed approach identifies a subset of features from a large feature space, such that the classifier error rate is reduced. Experimental results show that the proposed method is able to reduce the number of features to as low as 0.5% (i.e., the number of ignored features can reach 99.5%) while improving the accuracy, sensitivity, specificity, and precision of the classifier.

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

    NASA Astrophysics Data System (ADS)

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

    2013-06-01

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

  7. Influence of magnetism and correlation on the spectral properties of doped Mott insulators

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

    Wang, Yao; Moritz, Brian; Chen, Cheng-Chien

    Unraveling the nature of the doping-induced transition between a Mott insulator and a weakly correlated metal is crucial to understanding novel emergent phases in strongly correlated materials. Here, for this purpose, we study the evolution of spectral properties upon doping Mott insulating states by utilizing the cluster perturbation theory on the Hubbard and t – J -like models. Specifically, a quasifree dispersion crossing the Fermi level develops with small doping, and it eventually evolves into the most dominant feature at high doping levels. Although this dispersion is related to the free-electron hopping, our study shows that this spectral feature is,more » in fact, influenced inherently by both electron-electron correlation and spin-exchange interaction: the correlation destroys coherence, while the coupling between spin and mobile charge restores it in the photoemission spectrum. Due to the persistent impact of correlations and spin physics, the onset of gaps or the high-energy anomaly in the spectral functions can be expected in doped Mott insulators.« less

  8. Influence of magnetism and correlation on the spectral properties of doped Mott insulators

    DOE PAGES

    Wang, Yao; Moritz, Brian; Chen, Cheng-Chien; ...

    2018-03-01

    Unraveling the nature of the doping-induced transition between a Mott insulator and a weakly correlated metal is crucial to understanding novel emergent phases in strongly correlated materials. Here, for this purpose, we study the evolution of spectral properties upon doping Mott insulating states by utilizing the cluster perturbation theory on the Hubbard and t – J -like models. Specifically, a quasifree dispersion crossing the Fermi level develops with small doping, and it eventually evolves into the most dominant feature at high doping levels. Although this dispersion is related to the free-electron hopping, our study shows that this spectral feature is,more » in fact, influenced inherently by both electron-electron correlation and spin-exchange interaction: the correlation destroys coherence, while the coupling between spin and mobile charge restores it in the photoemission spectrum. Due to the persistent impact of correlations and spin physics, the onset of gaps or the high-energy anomaly in the spectral functions can be expected in doped Mott insulators.« less

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

    PubMed

    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.

  10. Spectral analysis using CCDs

    NASA Technical Reports Server (NTRS)

    Hewes, C. R.; Brodersen, R. W.; De Wit, M.; Buss, D. D.

    1976-01-01

    Charge-coupled devices (CCDs) are ideally suited for performing sampled-data transversal filtering operations in the analog domain. Two algorithms have been identified for performing spectral analysis in which the bulk of the computation can be performed in a CCD transversal filter; the chirp z-transform and the prime transform. CCD implementation of both these transform algorithms is presented together with performance data and applications.

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

    NASA Astrophysics Data System (ADS)

    Taneja, Ankur; Higdon, Jonathan

    2018-01-01

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

  12. Detection of spectral line curvature in imaging spectrometer data

    NASA Astrophysics Data System (ADS)

    Neville, Robert A.; Sun, Lixin; Staenz, Karl

    2003-09-01

    A procedure has been developed to measure the band-centers and bandwidths for imaging spectrometers using data acquired by the sensor in flight. This is done for each across-track pixel, thus allowing the measurement of the instrument's slit curvature or spectral 'smile'. The procedure uses spectral features present in the at-sensor radiance which are common to all pixels in the scene. These are principally atmospheric absorption lines. The band-center and bandwidth determinations are made by correlating the sensor measured radiance with a modelled radiance, the latter calculated using MODTRAN 4.2. Measurements have been made for a number of instruments including Airborne Visible and Infra-Red Imaging Spectrometer (AVIRIS), SWIR Full Spectrum Imager (SFSI), and Hyperion. The measurements on AVIRIS data were performed as a test of the procedure; since AVIRIS is a whisk-broom scanner it is expected to be free of spectral smile. SFSI is an airborne pushbroom instrument with considerable spectral smile. Hyperion is a satellite pushbroom sensor with a relatively small degree of smile. Measurements of Hyperion were made using three different data sets to check for temporal variations.

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

    NASA Astrophysics Data System (ADS)

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

    2016-05-01

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

  14. Spectral characterization of volcanic rocks in the VIS-NIR for martian exploration

    NASA Astrophysics Data System (ADS)

    De Angelis, Simone; Carli, Cristian; Manzari, Paola; De Sanctis, Maria Cristina; Capaccioni, Fabrizio

    2016-10-01

    Igneous effusive rocks cover much of the surface of Mars [1,2,3]. Initially only two types of lithologies were thought to constitute the Martian crust, i.e. a basaltic one and a more andesitic one [1,2], while more evolved lithologies were ruled out.Nevertheless a more complex situation is appearing in the last years. Recently several observations have highlighted the presence of evolved, acidic rocks. High-silica dacite units were identified in Syrtis Major caldera by thermal IR data [4]. Outcrops in Noachis Terra were interpreted as constituted of felsic (i.e. feldspar-rich) rocks essentially by the observation of a 1.3-µm spectral feature in CRISM data, attributed to Fe2+ in feldspars [5]. However different interpretations exist, invoking plagioclase-enriched basalts [6] rather than felsic products.The increasing of high-resolution and in-situ rover-based observations datasets and the changing of the initial paradigm justify a new systematic spectral study of igneous effusive rocks. In this work we focus on the spectral characterization of volcanic effusive rocks in the 0.35-2.5-µm range. We are carrying out measurements and spectral analyses on a wide ensemble of effusive samples, from mafic to sialic, with variable alkali contents, following the classification in the Total-Alkali-Silica diagram, and discussing the influence on spectral characteristics of different mineral assemblages and/or texture ([7], [8]). [1] Bandfield J.L., et al., Science, 287, 1626, 2000; [2] Christensen P.R., et al., J. Geophys. Res., 105, N.E4, 9609-9621, 2000; [3] Ehlmann B.L. & Edwards C.S., Annu. Rev. Earth Planet. Sci., 42, 291-315, 2014; [4] Christensen P.R., et al., Nature, 436, 504-509, 2005; [5] Wray J.J., et al., 44th LPSC, abs. n.3065, 2013; [6] Rogers A.D. & Nekvasil H., Geophys. Res. Lett., 42, 2619-2626, 2015; [7] Carli C. and Sgavetti M.,Icarus, 211, 1034-1048, 2011; [7] Carli C. et al., SGL, doi 10.1144/SP401.19, 2015.

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

    NASA Astrophysics Data System (ADS)

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

    2015-01-01

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

  16. Imaging Characteristics of Pathologically Proven Thymic Hyperplasia: Identifying Features That Can Differentiate True From Lymphoid Hyperplasia

    PubMed Central

    Araki, Tetsuro; Sholl, Lynette M.; Gerbaudo, Victor H.; Hatabu, Hiroto; Nishino, Mizuki

    2014-01-01

    OBJECTIVE The purpose of this article is to investigate the imaging characteristics of pathologically proven thymic hyperplasia and to identify features that can differentiate true hyperplasia from lymphoid hyperplasia. MATERIALS AND METHODS Thirty-one patients (nine men and 22 women; age range, 20–68 years) with pathologically confirmed thymic hyperplasia (18 true and 13 lymphoid) who underwent preoperative CT (n = 27), PET/CT (n = 5), or MRI (n = 6) were studied. The length and thickness of each thymic lobe and the transverse and anterior-posterior diameters and attenuation of the thymus were measured on CT. Thymic morphologic features and heterogeneity on CT and chemical shift on MRI were evaluated. Maximum standardized uptake values were measured on PET. Imaging features between true and lymphoid hyperplasia were compared. RESULTS No significant differences were observed between true and lymphoid hyperplasia in terms of thymic length, thickness, diameters, morphologic features, and other qualitative features (p > 0.16). The length, thickness, and diameters of thymic hyperplasia were significantly larger than the mean values of normal glands in the corresponding age group (p < 0.001). CT attenuation of lymphoid hyperplasia was significantly higher than that of true hyperplasia among 15 patients with contrast-enhanced CT (median, 47.9 vs 31.4 HU; Wilcoxon p = 0.03). The receiver operating characteristic analysis yielded greater than 41.2 HU as the optimal threshold for differentiating lymphoid hyperplasia from true hyperplasia, with 83% sensitivity and 89% specificity. A decrease of signal intensity on opposed-phase images was present in all four cases with in- and opposed-phase imaging. The mean maximum standardized uptake value was 2.66. CONCLUSION CT attenuation of the thymus was significantly higher in lymphoid hyperplasia than in true hyperplasia, with an optimal threshold of greater than 41.2 HU in this cohort of patients with pathologically confirmed

  17. Spectral identification of minerals using imaging spectrometry data: Evaluating the effects of signal to noise and spectral resolution using the tricorder algorithm

    NASA Technical Reports Server (NTRS)

    Swayze, Gregg A.; Clark, Roger N.

    1995-01-01

    The rapid development of sophisticated imaging spectrometers and resulting flood of imaging spectrometry data has prompted a rapid parallel development of spectral-information extraction technology. Even though these extraction techniques have evolved along different lines (band-shape fitting, endmember unmixing, near-infrared analysis, neural-network fitting, and expert systems to name a few), all are limited by the spectrometer's signal to noise (S/N) and spectral resolution in producing useful information. This study grew from a need to quantitatively determine what effects these parameters have on our ability to differentiate between mineral absorption features using a band-shape fitting algorithm. We chose to evaluate the AVIRIS, HYDICE, MIVIS, GERIS, VIMS, NIMS, and ASTER instruments because they collect data over wide S/N and spectral-resolution ranges. The study evaluates the performance of the Tricorder algorithm, in differentiating between mineral spectra in the 0.4-2.5 micrometer spectral region. The strength of the Tricorder algorithm is in its ability to produce an easily understood comparison of band shape that can concentrate on small relevant portions of the spectra, giving it an advantage over most unmixing schemes, and in that it need not spend large amounts of time reoptimizing each time a new mineral component is added to its reference library, as is the case with neural-network schemes. We believe the flexibility of the Tricorder algorithm is unparalleled among spectral-extraction techniques and that the results from this study, although dealing with minerals, will have direct applications to spectral identification in other disciplines.

  18. Spatial variation analyses of Thematic Mapper data for the identification of linear features in agricultural landscapes

    NASA Technical Reports Server (NTRS)

    Pelletier, R. E.

    1984-01-01

    A need exists for digitized information pertaining to linear features such as roads, streams, water bodies and agricultural field boundaries as component parts of a data base. For many areas where this data may not yet exist or is in need of updating, these features may be extracted from remotely sensed digital data. This paper examines two approaches for identifying linear features, one utilizing raw data and the other classified data. Each approach uses a series of data enhancement procedures including derivation of standard deviation values, principal component analysis and filtering procedures using a high-pass window matrix. Just as certain bands better classify different land covers, so too do these bands exhibit high spectral contrast by which boundaries between land covers can be delineated. A few applications for this kind of data are briefly discussed, including its potential in a Universal Soil Loss Equation Model.

  19. Scaling within the spectral function approach

    NASA Astrophysics Data System (ADS)

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

    2018-03-01

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

  20. Hybrid spectral CT reconstruction

    PubMed Central

    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

  1. The Open Spectral Database: an open platform for sharing and searching spectral data.

    PubMed

    Chalk, Stuart J

    2016-01-01

    A number of websites make available spectral data for download (typically as JCAMP-DX text files) and one (ChemSpider) that also allows users to contribute spectral files. As a result, searching and retrieving such spectral data can be time consuming, and difficult to reuse if the data is compressed in the JCAMP-DX file. What is needed is a single resource that allows submission of JCAMP-DX files, export of the raw data in multiple formats, searching based on multiple chemical identifiers, and is open in terms of license and access. To address these issues a new online resource called the Open Spectral Database (OSDB) http://osdb.info/ has been developed and is now available. Built using open source tools, using open code (hosted on GitHub), providing open data, and open to community input about design and functionality, the OSDB is available for anyone to submit spectral data, making it searchable and available to the scientific community. This paper details the concept and coding, internal architecture, export formats, Representational State Transfer (REST) Application Programming Interface and options for submission of data. The OSDB website went live in November 2015. Concurrently, the GitHub repository was made available at https://github.com/stuchalk/OSDB/, and is open for collaborators to join the project, submit issues, and contribute code. The combination of a scripting environment (PHPStorm), a PHP Framework (CakePHP), a relational database (MySQL) and a code repository (GitHub) provides all the capabilities to easily develop REST based websites for ingestion, curation and exposure of open chemical data to the community at all levels. It is hoped this software stack (or equivalent ones in other scripting languages) will be leveraged to make more chemical data available for both humans and computers.

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

    NASA Astrophysics Data System (ADS)

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

    2018-01-01

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

  3. A semi-Lagrangian advection scheme for radioactive tracers in a regional spectral model

    NASA Astrophysics Data System (ADS)

    Chang, E.-C.; Yoshimura, K.

    2015-06-01

    In this study, the non-iteration dimensional-split semi-Lagrangian (NDSL) advection scheme is applied to the National Centers for Environmental Prediction (NCEP) regional spectral model (RSM) to alleviate the Gibbs phenomenon. The Gibbs phenomenon is a problem wherein negative values of positive-definite quantities (e.g., moisture and tracers) are generated by the spectral space transformation in a spectral model system. To solve this problem, the spectral prognostic specific humidity and radioactive tracer advection scheme is replaced by the NDSL advection scheme, which considers advection of tracers in a grid system without spectral space transformations. A regional version of the NDSL is developed in this study and is applied to the RSM. Idealized experiments show that the regional version of the NDSL is successful. The model runs for an actual case study suggest that the NDSL can successfully advect radioactive tracers (iodine-131 and cesium-137) without noise from the Gibbs phenomenon. The NDSL can also remove negative specific humidity values produced in spectral calculations without losing detailed features.

  4. Carbon Stars Identified from LAMOST DR4 Using Machine Learning

    NASA Astrophysics Data System (ADS)

    Li, Yin-Bi; Luo, A.-Li; Du, Chang-De; Zuo, Fang; Wang, Meng-Xin; Zhao, Gang; Jiang, Bi-Wei; Zhang, Hua-Wei; Liu, Chao; Qin, Li; Wang, Rui; Du, Bing; Guo, Yan-Xin; Wang, Bo; Han, Zhan-Wen; Xiang, Mao-Sheng; Huang, Yang; Chen, Bing-Qiu; Chen, Jian-Jun; Kong, Xiao; Hou, Wen; Song, Yi-Han; Wang, You-Fen; Wu, Ke-Fei; Zhang, Jian-Nan; Zhang, Yong; Wang, Yue-Fei; Cao, Zi-Huang; Hou, Yong-Hui; Zhao, Yong-Heng

    2018-02-01

    In this work, we present a catalog of 2651 carbon stars from the fourth Data Release (DR4) of the Large Sky Area Multi-Object Fiber Spectroscopy Telescope (LAMOST). Using an efficient machine-learning algorithm, we find these stars from more than 7 million spectra. As a by-product, 17 carbon-enhanced metal-poor turnoff star candidates are also reported in this paper, and they are preliminarily identified by their atmospheric parameters. Except for 176 stars that could not be given spectral types, we classify the other 2475 carbon stars into five subtypes: 864 C-H, 226 C-R, 400 C-J, 266 C-N, and 719 barium stars based on a series of spectral features. Furthermore, we divide the C-J stars into three subtypes, C-J(H), C-J(R), and C-J(N), and about 90% of them are cool N-type stars as expected from previous literature. Besides spectroscopic classification, we also match these carbon stars to multiple broadband photometries. Using ultraviolet photometry data, we find that 25 carbon stars have FUV detections and that they are likely to be in binary systems with compact white dwarf companions.

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

    PubMed

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

    2015-08-19

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

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

    PubMed Central

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

    2015-01-01

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

  7. DoE Phase II SBIR: Spectrally-Assisted Vehicle Tracking

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

    Villeneuve, Pierre V.

    2013-02-28

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

  8. Normalized spectral damage of a linear system over different spectral loading patterns

    NASA Astrophysics Data System (ADS)

    Kim, Chan-Jung

    2017-08-01

    Spectral fatigue damage is affected by different loading patterns; the damage may be accumulated in a different manner because the spectral pattern has an influence on stresses or strains. The normalization of spectral damage with respect to spectral loading acceleration is a novel solution to compare the accumulated fatigue damage over different spectral loading patterns. To evaluate the sensitivity of fatigue damage over different spectral loading cases, a simple notched specimen is used to conduct a uniaxial vibration test for two representative spectral patterns-random and harmonic-between 30 and 3000 Hz. The fatigue damage to the simple specimen is analyzed for different spectral loading cases using the normalized spectral damage from the measured response data for both acceleration and strain. The influence of spectral loading patterns is discussed based on these analyses.

  9. Comparative analyses of Legionella species identifies genetic features of strains causing Legionnaires' disease.

    PubMed

    Gomez-Valero, Laura; Rusniok, Christophe; Rolando, Monica; Neou, Mario; Dervins-Ravault, Delphine; Demirtas, Jasmin; Rouy, Zoe; Moore, Robert J; Chen, Honglei; Petty, Nicola K; Jarraud, Sophie; Etienne, Jerome; Steinert, Michael; Heuner, Klaus; Gribaldo, Simonetta; Médigue, Claudine; Glöckner, Gernot; Hartland, Elizabeth L; Buchrieser, Carmen

    2014-01-01

    The genus Legionella comprises over 60 species. However, L. pneumophila and L. longbeachae alone cause over 95% of Legionnaires’ disease. To identify the genetic bases underlying the different capacities to cause disease we sequenced and compared the genomes of L. micdadei, L. hackeliae and L. fallonii (LLAP10), which are all rarely isolated from humans. We show that these Legionella species possess different virulence capacities in amoeba and macrophages, correlating with their occurrence in humans. Our comparative analysis of 11 Legionella genomes belonging to five species reveals highly heterogeneous genome content with over 60% representing species-specific genes; these comprise a complete prophage in L. micdadei, the first ever identified in a Legionella genome. Mobile elements are abundant in Legionella genomes; many encode type IV secretion systems for conjugative transfer, pointing to their importance for adaptation of the genus. The Dot/Icm secretion system is conserved, although the core set of substrates is small, as only 24 out of over 300 described Dot/Icm effector genes are present in all Legionella species. We also identified new eukaryotic motifs including thaumatin, synaptobrevin or clathrin/coatomer adaptine like domains. Legionella genomes are highly dynamic due to a large mobilome mainly comprising type IV secretion systems, while a minority of core substrates is shared among the diverse species. Eukaryotic like proteins and motifs remain a hallmark of the genus Legionella. Key factors such as proteins involved in oxygen binding, iron storage, host membrane transport and certain Dot/Icm substrates are specific features of disease-related strains.

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

    PubMed

    Harris, A Thomas

    2006-08-01

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

  11. Higher-Order Spectral Analysis of F-18 Flight Flutter Data

    NASA Technical Reports Server (NTRS)

    Silva, Walter A.; Dunn, Shane

    2005-01-01

    Royal Australian Air Force (RAAF) F/A-18 flight flutter test data is presented and analyzed using various techniques. The data includes high-quality measurements of forced responses and limit cycle oscillation (LCO) phenomena. Standard correlation and power spectral density (PSD) techniques are applied to the data and presented. Novel applications of experimentally-identified impulse responses and higher-order spectral techniques are also applied to the data and presented. The goal of this research is to develop methods that can identify the onset of nonlinear aeroelastic phenomena, such as LCO, during flutter testing.

  12. Monitoring Geothermal Features in Yellowstone National Park with ATLAS Multispectral Imagery

    NASA Technical Reports Server (NTRS)

    Spruce, Joseph; Berglund, Judith

    2000-01-01

    The National Park Service (NPS) must produce an Environmental Impact Statement for each proposed development in the vicinity of known geothermal resource areas (KGRAs) in Yellowstone National Park. In addition, the NPS monitors indicator KGRAs for environmental quality and is still in the process of mapping many geothermal areas. The NPS currently maps geothermal features with field survey techniques. High resolution aerial multispectral remote sensing in the visible, NIR, SWIR, and thermal spectral regions could enable YNP geothermal features to be mapped more quickly and in greater detail In response, Yellowstone Ecosystems Studies, in partnership with NASA's Commercial Remote Sensing Program, is conducting a study on the use of Airborne Terrestrial Applications Sensor (ATLAS) multispectral data for monitoring geothermal features in the Upper Geyser Basin. ATLAS data were acquired at 2.5 meter resolution on August 17, 2000. These data were processed into land cover classifications and relative temperature maps. For sufficiently large features, the ATLAS data can map geothermal areas in terms of geyser pools and hot springs, plus multiple categories of geothermal runoff that are apparently indicative of temperature gradients and microbial matting communities. In addition, the ATLAS maps clearly identify geyserite areas. The thermal bands contributed to classification success and to the computation of relative temperature. With masking techniques, one can assess the influence of geothermal features on the Firehole River. Preliminary results appear to confirm ATLAS data utility for mapping and monitoring geothermal features. Future work will include classification refinement and additional validation.

  13. An energy ratio feature extraction method for optical fiber vibration signal

    NASA Astrophysics Data System (ADS)

    Sheng, Zhiyong; Zhang, Xinyan; Wang, Yanping; Hou, Weiming; Yang, Dan

    2018-03-01

    The intrusion events in the optical fiber pre-warning system (OFPS) are divided into two types which are harmful intrusion event and harmless interference event. At present, the signal feature extraction methods of these two types of events are usually designed from the view of the time domain. However, the differences of time-domain characteristics for different harmful intrusion events are not obvious, which cannot reflect the diversity of them in detail. We find that the spectrum distribution of different intrusion signals has obvious differences. For this reason, the intrusion signal is transformed into the frequency domain. In this paper, an energy ratio feature extraction method of harmful intrusion event is drawn on. Firstly, the intrusion signals are pre-processed and the power spectral density (PSD) is calculated. Then, the energy ratio of different frequency bands is calculated, and the corresponding feature vector of each type of intrusion event is further formed. The linear discriminant analysis (LDA) classifier is used to identify the harmful intrusion events in the paper. Experimental results show that the algorithm improves the recognition rate of the intrusion signal, and further verifies the feasibility and validity of the algorithm.

  14. Mapping the Spectral and Biochemical Characteristics of Riparian Vegetation and Soils

    NASA Astrophysics Data System (ADS)

    Balaji Bhaskar, M. S.

    2016-12-01

    Salt cedar (Tamarix ramosissima), an invasive plant species, has successfully invaded large extents of several riparian zones along the western United States and northern Mexico. Mapping the distribution and abundance of Tamarix over these large areas through a, multi-seasonal, cost-effective monitoring approach using satellite remote sensing is very essential. Hence, the objectives of this study are: 1) to identify the spectral characteristics of the major riparian, agricultural vegetation types and soils in the Lower Colorado River (LCR) region; and 2) to determine the biochemical characteristics of the vegetation and soils. Ground truth surveys were conducted at 79 locations where the spectral reflectance measurements of vegetation, type of plant species, plant heights, soil samples and GPS co-ordinates were recorded. All the sampling was designed to coincide with the satellite overpass period. From the LANDSAT TM image, dark-object-subtracted (DOS) digital number (DN) values of six LANDSAT single bands (1-5 and 7) were extracted and all the spectral ratios and vegetative indices were calculated. The NDVI, R1,5 and R1,7 were identified as the best ratios to distinguish the major vegetation types. The LANDSAT TM color-composite spectral ratio image (NDVI, R1,5 and R1,7 as GBR) can clearly identify and map the areas infested with Tamarix. The salt cedar infested riparian soils showed high concentrations of Ca, Mg and Na concentrations compared to other soils and the spectral reflectance of soils with high Na concentrations were significantly higher in the 350-2500 nm spectral range compared to other soils. The Leaf Area Index (LAI) data shows that the salt cedar has higher LAI compared to other riparian vegetation. The spectral and satellite image analysis shows that the selected spectral ratios can be applied to multiple satellite overpasses for monitoring the seasonal progression of the riparian growth over time. Extending the image analysis over wider areas of

  15. The HIFI spectral survey of AFGL 2591 (CHESS). II. Summary of the survey

    NASA Astrophysics Data System (ADS)

    Kaźmierczak-Barthel, M.; van der Tak, F. F. S.; Helmich, F. P.; Chavarría, L.; Wang, K.-S.; Ceccarelli, C.

    2014-07-01

    Aims: This paper presents the richness of submillimeter spectral features in the high-mass star forming region AFGL 2591. Methods: As part of the Chemical Herschel Survey of Star Forming Regions (CHESS) key programme, AFGL 2591 was observed by the Herschel (HIFI) instrument. The spectral survey covered a frequency range from 480 to 1240 GHz as well as single lines from 1267 to 1901 GHz (i.e. CO, HCl, NH3, OH, and [CII]). Rotational and population diagram methods were used to calculate column densities, excitation temperatures, and the emission extents of the observed molecules associated with AFGL 2591. The analysis was supplemented with several lines from ground-based JCMT spectra. Results: From the HIFI spectral survey analysis a total of 32 species were identified (including isotopologues). Although the lines are mostly quite weak (∫TmbdV ~ few K km s-1), 268 emission and 16 absorption lines were found (excluding blends). Molecular column densities range from 6 × 1011 to 1 × 1019 cm-2 and excitation temperatures from 19 to 175 K. Cold (e.g. HCN, H2S, and NH3 with temperatures below 70 K) and warm species (e.g. CH3OH, SO2) in the protostellar envelope can be distinguished. Herschel is an ESA space observatory with science instruments provided by European-led Principal Investigator consortia and with important participation from NASA.Appendix A is available in electronic form at http://www.aanda.org

  16. Spectral measurements of cosmic gamma-ray bursts with the Konus-Wind and Konus-A instruments

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

    Golenetskii, S. V.; Aptekar, R. L.; Frederiks, D. D.

    1998-05-16

    The Konus gamma-ray burst instrumentation on board the US GGS-Wind spacecraft and the near-Earth Russian satellite Kosmos-2326 makes it possible to make spectral measurements and comparisons between 12 keV to 10 MeV. Since November 1994, over 370 bursts have been observed in the triggered mode, for which detailed spectral measurements are available. Incident photon spectra are derived from the count rate spectra of a number of bright bursts for which the celestial source position or the angle relative to the sensor axis is known. The spectral evolution of these bursts and the possible existence of spectral features in both themore » soft and hard energy bands are discussed.« less

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

    PubMed Central

    Singha, Mrinal; Wu, Bingfang; Zhang, Miao

    2016-01-01

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

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

    PubMed

    Singha, Mrinal; Wu, Bingfang; Zhang, Miao

    2016-12-22

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

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

    NASA Astrophysics Data System (ADS)

    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.

  20. Automated Image Registration Using Morphological Region of Interest Feature Extraction

    NASA Technical Reports Server (NTRS)

    Plaza, Antonio; LeMoigne, Jacqueline; Netanyahu, Nathan S.

    2005-01-01

    With the recent explosion in the amount of remotely sensed imagery and the corresponding interest in temporal change detection and modeling, image registration has become increasingly important as a necessary first step in the integration of multi-temporal and multi-sensor data for applications such as the analysis of seasonal and annual global climate changes, as well as land use/cover changes. The task of image registration can be divided into two major components: (1) the extraction of control points or features from images; and (2) the search among the extracted features for the matching pairs that represent the same feature in the images to be matched. Manual control feature extraction can be subjective and extremely time consuming, and often results in few usable points. Automated feature extraction is a solution to this problem, where desired target features are invariant, and represent evenly distributed landmarks such as edges, corners and line intersections. In this paper, we develop a novel automated registration approach based on the following steps. First, a mathematical morphology (MM)-based method is used to obtain a scale-orientation morphological profile at each image pixel. Next, a spectral dissimilarity metric such as the spectral information divergence is applied for automated extraction of landmark chips, followed by an initial approximate matching. This initial condition is then refined using a hierarchical robust feature matching (RFM) procedure. Experimental results reveal that the proposed registration technique offers a robust solution in the presence of seasonal changes and other interfering factors. Keywords-Automated image registration, multi-temporal imagery, mathematical morphology, robust feature matching.

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