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Sample records for undertake spectral classifications

  1. Stellar Spectral Classification with Locality Preserving Projections ...

    Indian Academy of Sciences (India)

    With the help of computer tools and algorithms, automatic stellar spectral classification has become an area of current interest. The process of stellar spectral classification mainly includes two steps: dimension reduction and classification. As a popular dimensionality reduction technique, Principal Component Analysis (PCA) ...

  2. Spectral Classification of Asteroids by Random Forest

    Science.gov (United States)

    Huang, C.; Ma, Y. H.; Zhao, H. B.; Lu, X. P.

    2016-09-01

    With the increasing asteroid spectral and photometric data, a variety of classification methods for asteroids have been proposed. This paper classifies asteroids based on the observations of Sloan Digital Sky Survey (SDSS) Moving Object Catalogue (MOC) by using the random forest algorithm. With the training data derived from the taxonomies of Tholen, Bus, Lazzaro, DeMeo, and Principal Component Analysis, we classify 48642 asteroids according to g, r, i, and z SDSS magnitudes. In this way, asteroids are divided into 8 spectral classes (C, X, S, B, D, K, L, and V).

  3. Spectral Classification of Asteroids by Random Forest

    Science.gov (United States)

    Huang, Chao; Ma, Yue-hua; Zhao, Hai-bin; Lu, Xiao-ping

    2017-10-01

    With the increasing spectral and photometric data of asteroids, a variety of classification methods for asteroids have been proposed. This paper classifies asteroids based on the observations in the Sloan Digital Sky Survey (SDSS) Moving Object Catalogue (MOC) by using the random forest algorithm. In combination with the present taxonomies of Tholen, Bus, Lazzaro, and DeMeo, and the principal component analysis, we have classified 48642 asteroids according to their SDSS magnitudes at the g, r, i, and z wavebands. In this way, these asteroids are divided into 8 (C, X, S, B, D, K, L, and V) classes.

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

    Indian Academy of Sciences (India)

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

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

    Indian Academy of Sciences (India)

    Support Vector Machine (SVM) is one of the important stellar spectral classification methods, and it is widely used in practice. But its classification efficiencies cannot be greatly improved because it does not take the class distribution into consideration. In view of this, a modified SVM-named Minimum within-class and ...

  6. Spectral band selection for classification of soil organic matter content

    Science.gov (United States)

    Henderson, Tracey L.; Szilagyi, Andrea; Baumgardner, Marion F.; Chen, Chih-Chien Thomas; Landgrebe, David A.

    1989-01-01

    This paper describes the spectral-band-selection (SBS) algorithm of Chen and Landgrebe (1987, 1988, and 1989) and uses the algorithm to classify the organic matter content in the earth's surface soil. The effectiveness of the algorithm was evaluated comparing the results of classification of the soil organic matter using SBS bands with those obtained using Landsat MSS bands and TM bands, showing that the algorithm was successful in finding important spectral bands for classification of organic matter content. Using the calculated bands, the probabilities of correct classification for climate-stratified data were found to range from 0.910 to 0.980.

  7. Spectral classification of emission-line galaxies

    International Nuclear Information System (INIS)

    Veilleux, S.; Osterbrock, D.E.

    1987-01-01

    A revised method of classification of narrow-line active galaxies and H II region-like galaxies is proposed. It involves the line ratios which take full advantage of the physical distinction between the two types of objects and minimize the effects of reddening correction and errors in the flux calibration. Large sets of internally consistent data are used, including new, previously unpublished measurements. Predictions of recent photoionization models by power-law spectra and by hot stars are compared with the observations. The classification is based on the observational data interpreted on the basis of these models. 63 references

  8. A computer method for spectral classification

    International Nuclear Information System (INIS)

    Appenzeller, I.; Zekl, H.

    1978-01-01

    The authors describe the start of an attempt to improve the accuracy of spectroscopic parallaxes by evaluating spectroscopic temperature and luminosity criteria such as those of the MK classification spectrograms which were analyzed automatically by means of a suitable computer program. (Auth.)

  9. Soil classification basing on the spectral characteristics of topsoil samples

    Science.gov (United States)

    Liu, Huanjun; Zhang, Xiaokang; Zhang, Xinle

    2016-04-01

    Soil taxonomy plays an important role in soil utility and management, but China has only course soil map created based on 1980s data. New technology, e.g. spectroscopy, could simplify soil classification. The study try to classify soils basing on the spectral characteristics of topsoil samples. 148 topsoil samples of typical soils, including Black soil, Chernozem, Blown soil and Meadow soil, were collected from Songnen plain, Northeast China, and the room spectral reflectance in the visible and near infrared region (400-2500 nm) were processed with weighted moving average, resampling technique, and continuum removal. Spectral indices were extracted from soil spectral characteristics, including the second absorption positions of spectral curve, the first absorption vale's area, and slope of spectral curve at 500-600 nm and 1340-1360 nm. Then K-means clustering and decision tree were used respectively to build soil classification model. The results indicated that 1) the second absorption positions of Black soil and Chernozem were located at 610 nm and 650 nm respectively; 2) the spectral curve of the meadow is similar to its adjacent soil, which could be due to soil erosion; 3) decision tree model showed higher classification accuracy, and accuracy of Black soil, Chernozem, Blown soil and Meadow are 100%, 88%, 97%, 50% respectively, and the accuracy of Blown soil could be increased to 100% by adding one more spectral index (the first two vole's area) to the model, which showed that the model could be used for soil classification and soil map in near future.

  10. Classification of breast microcalcifications using spectral mammography

    Science.gov (United States)

    Ghammraoui, B.; Glick, S. J.

    2017-03-01

    Purpose: To investigate the potential of spectral mammography to distinguish between type I calcifications, consisting of calcium oxalate dihydrate or weddellite compounds that are more often associated with benign lesions, and type II calcifications containing hydroxyapatite which are predominantly associated with malignant tumors. Methods: Using a ray tracing algorithm, we simulated the total number of x-ray photons recorded by the detector at one pixel from a single pencil-beam projection through a breast of 50/50 (adipose/glandular) tissues with inserted microcalcifications of different types and sizes. Material decomposition using two energy bins was then applied to characterize the simulated calcifications into hydroxyapatite and weddellite using maximumlikelihood estimation, taking into account the polychromatic source, the detector response function and the energy dependent attenuation. Results: Simulation tests were carried out for different doses and calcification sizes for multiple realizations. The results were summarized using receiver operating characteristic (ROC) analysis with the area under the curve (AUC) taken as an overall indicator of discrimination performance and showing high AUC values up to 0.99. Conclusion: Our simulation results obtained for a uniform breast imaging phantom indicate that spectral mammography using two energy bins has the potential to be used as a non-invasive method for discrimination between type I and type II microcalcifications to improve early breast cancer diagnosis and reduce the number of unnecessary breast biopsies.

  11. Stellar spectral classification with locality preserving projections and ...

    Indian Academy of Sciences (India)

    63

    Manuscript Number: JOAA-D-16-00002R3. Full Title: Stellar Spectral Classification with Locality Preserving Projections and Support Vector. Machine. Article Type: Original Study. Corresponding Author: zhongbao liu. North University of China. CHINA. Corresponding Author Secondary. Information: Corresponding Author's ...

  12. Automatic parquet block sorting using real-time spectral classification

    Science.gov (United States)

    Astrom, Anders; Astrand, Erik; Johansson, Magnus

    1999-03-01

    This paper presents a real-time spectral classification system based on the PGP spectrograph and a smart image sensor. The PGP is a spectrograph which extracts the spectral information from a scene and projects the information on an image sensor, which is a method often referred to as Imaging Spectroscopy. The classification is based on linear models and categorizes a number of pixels along a line. Previous systems adopting this method have used standard sensors, which often resulted in poor performance. The new system, however, is based on a patented near-sensor classification method, which exploits analogue features on the smart image sensor. The method reduces the enormous amount of data to be processed at an early stage, thus making true real-time spectral classification possible. The system has been evaluated on hardwood parquet boards showing very good results. The color defects considered in the experiments were blue stain, white sapwood, yellow decay and red decay. In addition to these four defect classes, a reference class was used to indicate correct surface color. The system calculates a statistical measure for each parquet block, giving the pixel defect percentage. The patented method makes it possible to run at very high speeds with a high spectral discrimination ability. Using a powerful illuminator, the system can run with a line frequency exceeding 2000 line/s. This opens up the possibility to maintain high production speed and still measure with good resolution.

  13. Vulnerable land ecosystems classification using spatial context and spectral indices

    Science.gov (United States)

    Ibarrola-Ulzurrun, Edurne; Gonzalo-Martín, Consuelo; Marcello, Javier

    2017-10-01

    Natural habitats are exposed to growing pressure due to intensification of land use and tourism development. Thus, obtaining information on the vegetation is necessary for conservation and management projects. In this context, remote sensing is an important tool for monitoring and managing habitats, being classification a crucial stage. The majority of image classifications techniques are based upon the pixel-based approach. An alternative is the object-based (OBIA) approach, in which a previous segmentation step merges image pixels to create objects that are then classified. Besides, improved results may be gained by incorporating additional spatial information and specific spectral indices into the classification process. The main goal of this work was to implement and assess object-based classification techniques on very-high resolution imagery incorporating spectral indices and contextual spatial information in the classification models. The study area was Teide National Park in Canary Islands (Spain) using Worldview-2 orthoready imagery. In the classification model, two common indices were selected Normalized Difference Vegetation Index (NDVI) and Optimized Soil Adjusted Vegetation Index (OSAVI), as well as two specific Worldview-2 sensor indices, Worldview Vegetation Index and Worldview Soil Index. To include the contextual information, Grey Level Co-occurrence Matrices (GLCM) were used. The classification was performed training a Support Vector Machine with sufficient and representative number of vegetation samples (Spartocytisus supranubius, Pterocephalus lasiospermus, Descurainia bourgaeana and Pinus canariensis) as well as urban, road and bare soil classes. Confusion Matrices were computed to evaluate the results from each classification model obtaining the highest overall accuracy (90.07%) combining both Worldview indices with the GLCM-dissimilarity.

  14. On the relevance of spectral features for instrument classification

    DEFF Research Database (Denmark)

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

    2007-01-01

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

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

    Science.gov (United States)

    Akbari, D.

    2017-11-01

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

  16. Spectral classification by the near infrared photometric parameters

    International Nuclear Information System (INIS)

    Tignanelli, H.L.; Feinstein, A.

    1985-01-01

    From the analysis of the measurements of KM-type stars done in the near infrared (1 to 3.5 microns: the JHKL bands of Johnsons's system), with an 83 cm reflector and a PbS detector at La Plata Observatory, we try to establish a new photometric classification system that discriminates luminosity class by means of certain parameters defined by infrared colours and infrared magnitudes. Data compiled and homogenized by J.Koornneef of southern bright stars in those bands were also included. The results give us information about the spectral types and reddening of those stars. We also indicate how to calculate the radiation excess that those stars could have. (author)

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

    Science.gov (United States)

    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.

  18. Central stars of planetary nebulae: New spectral classifications and catalogue

    Science.gov (United States)

    Weidmann, W. A.; Gamen, R.

    2011-02-01

    Context. There are more than 3000 confirmed and probable known Galactic planetary nebulae (PNe), but central star spectroscopic information is available for only 13% of them. Aims: We undertook a spectroscopic survey of central stars of PNe at low resolution and compiled a large list of central stars for which information was dispersed in the literature. Methods: We observed 45 PNs using the 2.15 m telescope at Casleo, Argentina. Results: We present a catalogue of 492 confirmed and probable CSPN and provide a preliminary spectral classification for 45 central star of PNe. This revises previous values of the proportion of CSPN with atmospheres poor in hydrogen in at least 30% of cases and provide statistical information that allows us to infer the origin of H-poor stars. Based on data collected at the Complejo Astronómico El Leoncito (CASLEO), which is operated under agreement between the Consejo Nacional de Investigaciones Científicas y Técnicas de la República Argentina y Universidades Nacionales de La Plata, Córdoba y San Juan, Argentina.

  19. Spectral Classification of Similar Materials using the Tetracorder Algorithm: The Calcite-Epidote-Chlorite Problem

    Science.gov (United States)

    Dalton, J. Brad; Bove, Dana; Mladinich, Carol; Clark, Roger; Rockwell, Barnaby; Swayze, Gregg; King, Trude; Church, Stanley

    2001-01-01

    Recent work on automated spectral classification algorithms has sought to distinguish ever-more similar materials. From modest beginnings separating shade, soil, rock and vegetation to ambitious attempts to discriminate mineral types and specific plant species, the trend seems to be toward using increasingly subtle spectral differences to perform the classification. Rule-based expert systems exploiting the underlying physics of spectroscopy such as the US Geological Society Tetracorder system are now taking advantage of the high spectral resolution and dimensionality of current imaging spectrometer designs to discriminate spectrally similar materials. The current paper details recent efforts to discriminate three minerals having absorptions centered at the same wavelength, with encouraging results.

  20. Multi Angle Imaging With Spectral Remote Sensing for Scene Classification

    National Research Council Canada - National Science Library

    Prasert, Sunyaruk

    2005-01-01

    .... This study analyses the BRDF (Bidirectional Reflectance Distribution Function) impact and effectiveness of texture analysis on terrain classification within Fresno County area in state of California...

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

    Science.gov (United States)

    Paul, Subir; Nagesh Kumar, D.

    2018-04-01

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

  2. Hyper-spectral frequency selection for the classification of vegetation diseases

    OpenAIRE

    Dijkstra, Klaas; van de Loosdrecht, Jaap; Schomaker, Lambert; Wiering, Marco

    2017-01-01

    Reducing the use of pesticides by early visual detection of diseases in precision agriculture is important. Because of the color similarity between potato-plant diseases, narrow band hyper-spectral imaging is required. Payload constraints on unmanned aerial vehicles require reduc- tion of spectral bands. Therefore, we present a methodology for per-patch classification combined with hyper-spectral band selection. In controlled experiments performed on a set of individual leaves, we measure the...

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

    Directory of Open Access Journals (Sweden)

    Yi Wang

    2016-11-01

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

  4. Hyperspectral Image Classification Based on the Combination of Spatial-spectral Feature and Sparse Representation

    Directory of Open Access Journals (Sweden)

    YANG Zhaoxia

    2015-07-01

    Full Text Available In order to avoid the problem of being over-dependent on high-dimensional spectral feature in the traditional hyperspectral image classification, a novel approach based on the combination of spatial-spectral feature and sparse representation is proposed in this paper. Firstly, we extract the spatial-spectral feature by reorganizing the local image patch with the first d principal components(PCs into a vector representation, followed by a sorting scheme to make the vector invariant to local image rotation. Secondly, we learn the dictionary through a supervised method, and use it to code the features from test samples afterwards. Finally, we embed the resulting sparse feature coding into the support vector machine(SVM for hyperspectral image classification. Experiments using three hyperspectral data show that the proposed method can effectively improve the classification accuracy comparing with traditional classification methods.

  5. Multi-spectral Image Analysis for Astaxanthin Coating Classification

    DEFF Research Database (Denmark)

    Ljungqvist, Martin Georg; Ersbøll, Bjarne Kjær; Nielsen, Michael Engelbrecht

    2011-01-01

    Industrial quality inspection using image analysis on astaxanthin coating in aquaculture feed pellets is of great importance for automatic production control. In this study multi-spectral image analysis of pellets was performed using LDA, QDA, SNV and PCA on pixel level and mean value of pixels...

  6. Public Undertakings and Imputability

    DEFF Research Database (Denmark)

    Ølykke, Grith Skovgaard

    2013-01-01

    In this article, the issue of impuability to the State of public undertakings’ decision-making is analysed and discussed in the context of the DSBFirst case. DSBFirst is owned by the independent public undertaking DSB and the private undertaking FirstGroup plc and won the contracts in the 2008...... Oeresund tender for the provision of passenger transport by railway. From the start, the services were provided at a loss, and in the end a part of DSBFirst was wound up. In order to frame the problems illustrated by this case, the jurisprudence-based imputability requirement in the definition of State aid...... in Article 107(1) TFEU is analysed. It is concluded that where the public undertaking transgresses the control system put in place by the State, conditions for imputability are not fulfilled, and it is argued that in the current state of law, there is no conditional link between the level of control...

  7. Spatial and Spectral Hybrid Image Classification for Rice Lodging Assessment through UAV Imagery

    Directory of Open Access Journals (Sweden)

    Ming-Der Yang

    2017-06-01

    Full Text Available Rice lodging identification relies on manual in situ assessment and often leads to a compensation dispute in agricultural disaster assessment. Therefore, this study proposes a comprehensive and efficient classification technique for agricultural lands that entails using unmanned aerial vehicle (UAV imagery. In addition to spectral information, digital surface model (DSM and texture information of the images was obtained through image-based modeling and texture analysis. Moreover, single feature probability (SFP values were computed to evaluate the contribution of spectral and spatial hybrid image information to classification accuracy. The SFP results revealed that texture information was beneficial for the classification of rice and water, DSM information was valuable for lodging and tree classification, and the combination of texture and DSM information was helpful in distinguishing between artificial surface and bare land. Furthermore, a decision tree classification model incorporating SFP values yielded optimal results, with an accuracy of 96.17% and a Kappa value of 0.941, compared with that of a maximum likelihood classification model (90.76%. The rice lodging ratio in paddies at the study site was successfully identified, with three paddies being eligible for disaster relief. The study demonstrated that the proposed spatial and spectral hybrid image classification technology is a promising tool for rice lodging assessment.

  8. JET Joint Undertaking

    International Nuclear Information System (INIS)

    Keen, B.E.

    1987-03-01

    The paper presents the progress report of the Joint European Torus (JET) Joint Undertaking, 1986. The report contains a survey of the scientific and technical achievements on JET during 1986; the more important articles referred to in this survey are reproduced as appendices to this Report. The last section discusses developments which might improve the overall performance of the machine. (U.K.)

  9. LAMOST OBSERVATIONS IN THE KEPLER FIELD: SPECTRAL CLASSIFICATION WITH THE MKCLASS CODE

    Energy Technology Data Exchange (ETDEWEB)

    Gray, R. O. [Department of Physics and Astronomy, Appalachian State University, Boone, NC 28608 (United States); Corbally, C. J. [Vatican Observatory Research Group, Steward Observatory, Tucson, AZ 85721-0065 (United States); Cat, P. De [Royal Observatory of Belgium, Ringlaan 3, B-1180 Brussel (Belgium); Fu, J. N.; Ren, A. B. [Department of Astronomy, Beijing Normal University, 19 Avenue Xinjiekouwai, Beijing 100875 (China); Shi, J. R.; Luo, A. L.; Zhang, H. T.; Wu, Y.; Cao, Z.; Li, G. [Key Laboratory for Optical Astronomy, National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012 (China); Zhang, Y.; Hou, Y.; Wang, Y. [Nanjing Institute of Astronomical Optics and Technology, National Astronomical Observatories, Chinese Academy of Sciences, Nanjing 210042 (China)

    2016-01-15

    The LAMOST-Kepler project was designed to obtain high-quality, low-resolution spectra of many of the stars in the Kepler field with the Large Sky Area Multi Object Fiber Spectroscopic Telescope (LAMOST) spectroscopic telescope. To date 101,086 spectra of 80,447 objects over the entire Kepler field have been acquired. Physical parameters, radial velocities, and rotational velocities of these stars will be reported in other papers. In this paper we present MK spectral classifications for these spectra determined with the automatic classification code MKCLASS. We discuss the quality and reliability of the spectral types and present histograms showing the frequency of the spectral types in the main table organized according to luminosity class. Finally, as examples of the use of this spectral database, we compute the proportion of A-type stars that are Am stars, and identify 32 new barium dwarf candidates.

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

    Directory of Open Access Journals (Sweden)

    Yongguang Zhai

    2018-03-01

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

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

    Science.gov (United States)

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

    2018-01-01

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

  12. Parallel exploitation of a spatial-spectral classification approach for hyperspectral images on RVC-CAL

    Science.gov (United States)

    Lazcano, R.; Madroñal, D.; Fabelo, H.; Ortega, S.; Salvador, R.; Callicó, G. M.; Juárez, E.; Sanz, C.

    2017-10-01

    Hyperspectral Imaging (HI) assembles high resolution spectral information from hundreds of narrow bands across the electromagnetic spectrum, thus generating 3D data cubes in which each pixel gathers the spectral information of the reflectance of every spatial pixel. As a result, each image is composed of large volumes of data, which turns its processing into a challenge, as performance requirements have been continuously tightened. For instance, new HI applications demand real-time responses. Hence, parallel processing becomes a necessity to achieve this requirement, so the intrinsic parallelism of the algorithms must be exploited. In this paper, a spatial-spectral classification approach has been implemented using a dataflow language known as RVCCAL. This language represents a system as a set of functional units, and its main advantage is that it simplifies the parallelization process by mapping the different blocks over different processing units. The spatial-spectral classification approach aims at refining the classification results previously obtained by using a K-Nearest Neighbors (KNN) filtering process, in which both the pixel spectral value and the spatial coordinates are considered. To do so, KNN needs two inputs: a one-band representation of the hyperspectral image and the classification results provided by a pixel-wise classifier. Thus, spatial-spectral classification algorithm is divided into three different stages: a Principal Component Analysis (PCA) algorithm for computing the one-band representation of the image, a Support Vector Machine (SVM) classifier, and the KNN-based filtering algorithm. The parallelization of these algorithms shows promising results in terms of computational time, as the mapping of them over different cores presents a speedup of 2.69x when using 3 cores. Consequently, experimental results demonstrate that real-time processing of hyperspectral images is achievable.

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

    Science.gov (United States)

    Liu, Wanjun; Liang, Xuejian; Qu, Haicheng

    2017-11-01

    Hyperspectral image (HSI) classification is one of the most popular topics in remote sensing community. Traditional and deep learning-based classification methods were proposed constantly in recent years. In order to improve the classification accuracy and robustness, a dimensionality-varied convolutional neural network (DVCNN) was proposed in this paper. DVCNN was a novel deep architecture based on convolutional neural network (CNN). The input of DVCNN was a set of 3D patches selected from HSI which contained spectral-spatial joint information. In the following feature extraction process, each patch was transformed into some different 1D vectors by 3D convolution kernels, which were able to extract features from spectral-spatial data. The rest of DVCNN was about the same as general CNN and processed 2D matrix which was constituted by by all 1D data. So that the DVCNN could not only extract more accurate and rich features than CNN, but also fused spectral-spatial information to improve classification accuracy. Moreover, the robustness of network on water-absorption bands was enhanced in the process of spectral-spatial fusion by 3D convolution, and the calculation was simplified by dimensionality varied convolution. Experiments were performed on both Indian Pines and Pavia University scene datasets, and the results showed that the classification accuracy of DVCNN improved by 32.87% on Indian Pines and 19.63% on Pavia University scene than spectral-only CNN. The maximum accuracy improvement of DVCNN achievement was 13.72% compared with other state-of-the-art HSI classification methods, and the robustness of DVCNN on water-absorption bands noise was demonstrated.

  14. Jet Joint Undertaking

    International Nuclear Information System (INIS)

    Keen, B.E.; O'Hara, G.W.; Pollard, I.E.

    1988-07-01

    The paper presents the Jet Joint Undertaking annual report 1987. A description is given of the JET and Euratom and International Fusion Programmes. The technical status of JET is outlined, including the development and improvements made to the system in 1987. The results of JET Operation in 1987 are described within the areas of: density effects, temperature improvements, energy confinement studies and other material effects. The contents also contain a summary of the future programme of JET. (U.K.)

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

    Science.gov (United States)

    Li, N.; Wang, C.; Zhao, H.; Gong, X.; Wang, D.

    2018-04-01

    Spatial and spectral information are obtained simultaneously by hyperspectral remote sensing. Joint extraction of these information of hyperspectral image is one of most import methods for hyperspectral image classification. In this paper, a novel deep convolutional neural network (CNN) is proposed, which extracts spectral-spatial information of hyperspectral images correctly. The proposed model not only learns sufficient knowledge from the limited number of samples, but also has powerful generalization ability. The proposed framework based on three-dimensional convolution can extract spectral-spatial features of labeled samples effectively. Though CNN has shown its robustness to distortion, it cannot extract features of different scales through the traditional pooling layer that only have one size of pooling window. Hence, spatial pyramid pooling (SPP) is introduced into three-dimensional local convolutional filters for hyperspectral classification. Experimental results with a widely used hyperspectral remote sensing dataset show that the proposed model provides competitive performance.

  16. Dichotomous classification of black-colored metal using spectral analysis

    Directory of Open Access Journals (Sweden)

    Abramovich A.O.

    2017-05-01

    Full Text Available The task of detecting metal objects in different environments has always been important. To solve it metal detectors are used. They are designed to detect and identify objects that in their electric or magnetic properties different from the environment in which they are located. The most common among them are the metal detectors of the «detection of very low frequency» type (Very Low Frequency (VLF detectors. They use eddy current testing for detecting metal targets, which solves the problem of dichotomous distinction, that is a problem of splitting (or set into two parts (subsets: black or colored target. The target distinction is performed by a threshold level of the received signal. However, this approach does not allow to identify the type of target, if two samples of different metals are nearby. To overcome the above described limitations we propose another way of distinction based on the use of spectral analysis, which occurs in the metal detector antenna by Foucault current. We show that the problem of dichotomous distinction can be solved in just a measurement of width and area by the envelope of amplitude spectrum (hereinafter spectrum of the received signal. In this regard the laboratory model using eddy current metal detector will combat withdrawal from two samples – steel and copper, located along and calculate its range. The task of distinguishing between metal targets reduced to determining the hit spectra of reference samples obtained spectrum. The ratio between the areas is measured and reference spectra indicates the percentage of specific metals (e.g. two identical samples of different metals lying side by side. Signal processing is performed by specially designed program that compares two spectra along posted samples of black and colored metals with base.

  17. An expert computer program for classifying stars on the MK spectral classification system

    International Nuclear Information System (INIS)

    Gray, R. O.; Corbally, C. J.

    2014-01-01

    This paper describes an expert computer program (MKCLASS) designed to classify stellar spectra on the MK Spectral Classification system in a way similar to humans—by direct comparison with the MK classification standards. Like an expert human classifier, the program first comes up with a rough spectral type, and then refines that spectral type by direct comparison with MK standards drawn from a standards library. A number of spectral peculiarities, including barium stars, Ap and Am stars, λ Bootis stars, carbon-rich giants, etc., can be detected and classified by the program. The program also evaluates the quality of the delivered spectral type. The program currently is capable of classifying spectra in the violet-green region in either the rectified or flux-calibrated format, although the accuracy of the flux calibration is not important. We report on tests of MKCLASS on spectra classified by human classifiers; those tests suggest that over the entire HR diagram, MKCLASS will classify in the temperature dimension with a precision of 0.6 spectral subclass, and in the luminosity dimension with a precision of about one half of a luminosity class. These results compare well with human classifiers.

  18. An expert computer program for classifying stars on the MK spectral classification system

    Energy Technology Data Exchange (ETDEWEB)

    Gray, R. O. [Department of Physics and Astronomy, Appalachian State University, Boone, NC 26808 (United States); Corbally, C. J. [Vatican Observatory Research Group, Tucson, AZ 85721-0065 (United States)

    2014-04-01

    This paper describes an expert computer program (MKCLASS) designed to classify stellar spectra on the MK Spectral Classification system in a way similar to humans—by direct comparison with the MK classification standards. Like an expert human classifier, the program first comes up with a rough spectral type, and then refines that spectral type by direct comparison with MK standards drawn from a standards library. A number of spectral peculiarities, including barium stars, Ap and Am stars, λ Bootis stars, carbon-rich giants, etc., can be detected and classified by the program. The program also evaluates the quality of the delivered spectral type. The program currently is capable of classifying spectra in the violet-green region in either the rectified or flux-calibrated format, although the accuracy of the flux calibration is not important. We report on tests of MKCLASS on spectra classified by human classifiers; those tests suggest that over the entire HR diagram, MKCLASS will classify in the temperature dimension with a precision of 0.6 spectral subclass, and in the luminosity dimension with a precision of about one half of a luminosity class. These results compare well with human classifiers.

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

    Science.gov (United States)

    Liu, Chao; Gu, Jinwei

    2014-01-01

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

  20. JET Joint Undertaking

    International Nuclear Information System (INIS)

    Keen, B.E.; Lallia, P.; O'Hara, G.W.; Pollard, I.E.

    1987-06-01

    The paper presents the annual report of the Joint European Torus (JET) Joint Undertaking, 1986. The report is divided into two parts: a part on the scientific and technical programme of the project, and a part setting out the administration and organisation of the Project. The first part includes: a summary of the main features of the JET apparatus, the JET experimental programme, the position of the Project in the overall Euratom programme, and how JET relates to other large fusion devices throughout the world. In addition, the technical status of JET is described, as well as the results of the JET operations in 1986. The final section of the first part outlines the proposed future programme of JET. (U.K.)

  1. On the classification of the spectrally stable standing waves of the Hartree problem

    Science.gov (United States)

    Georgiev, Vladimir; Stefanov, Atanas

    2018-05-01

    We consider the fractional Hartree model, with general power non-linearity and arbitrary spatial dimension. We construct variationally the "normalized" solutions for the corresponding Choquard-Pekar model-in particular a number of key properties, like smoothness and bell-shapedness are established. As a consequence of the construction, we show that these solitons are spectrally stable as solutions to the time-dependent Hartree model. In addition, we analyze the spectral stability of the Moroz-Van Schaftingen solitons of the classical Hartree problem, in any dimensions and power non-linearity. A full classification is obtained, the main conclusion of which is that only and exactly the "normalized" solutions (which exist only in a portion of the range) are spectrally stable.

  2. Bidirectional-Convolutional LSTM Based Spectral-Spatial Feature Learning for Hyperspectral Image Classification

    Directory of Open Access Journals (Sweden)

    Qingshan Liu

    2017-12-01

    Full Text Available This paper proposes a novel deep learning framework named bidirectional-convolutional long short term memory (Bi-CLSTM network to automatically learn the spectral-spatial features from hyperspectral images (HSIs. In the network, the issue of spectral feature extraction is considered as a sequence learning problem, and a recurrent connection operator across the spectral domain is used to address it. Meanwhile, inspired from the widely used convolutional neural network (CNN, a convolution operator across the spatial domain is incorporated into the network to extract the spatial feature. In addition, to sufficiently capture the spectral information, a bidirectional recurrent connection is proposed. In the classification phase, the learned features are concatenated into a vector and fed to a Softmax classifier via a fully-connected operator. To validate the effectiveness of the proposed Bi-CLSTM framework, we compare it with six state-of-the-art methods, including the popular 3D-CNN model, on three widely used HSIs (i.e., Indian Pines, Pavia University, and Kennedy Space Center. The obtained results show that Bi-CLSTM can improve the classification performance by almost 1.5 % as compared to 3D-CNN.

  3. Application of partial least squares near-infrared spectral classification in diabetic identification

    Science.gov (United States)

    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. On the construction of a new stellar classification template library for the LAMOST spectral analysis pipeline

    Energy Technology Data Exchange (ETDEWEB)

    Wei, Peng; Luo, Ali; Li, Yinbi; Tu, Liangping; Wang, Fengfei; Zhang, Jiannan; Chen, Xiaoyan; Hou, Wen; Kong, Xiao; Wu, Yue; Zuo, Fang; Yi, Zhenping; Zhao, Yongheng; Chen, Jianjun; Du, Bing; Guo, Yanxin; Ren, Juanjuan [Key Laboratory of Optical Astronomy, National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012 (China); Pan, Jingchang; Jiang, Bin; Liu, Jie, E-mail: lal@nao.cas.cn, E-mail: weipeng@nao.cas.cn [School of Mechanical, Electrical, and Information Engineering, Shandong University, Weihai 264209 (China); and others

    2014-05-01

    The LAMOST spectral analysis pipeline, called the 1D pipeline, aims to classify and measure the spectra observed in the LAMOST survey. Through this pipeline, the observed stellar spectra are classified into different subclasses by matching with template spectra. Consequently, the performance of the stellar classification greatly depends on the quality of the template spectra. In this paper, we construct a new LAMOST stellar spectral classification template library, which is supposed to improve the precision and credibility of the present LAMOST stellar classification. About one million spectra are selected from LAMOST Data Release One to construct the new stellar templates, and they are gathered in 233 groups by two criteria: (1) pseudo g – r colors obtained by convolving the LAMOST spectra with the Sloan Digital Sky Survey ugriz filter response curve, and (2) the stellar subclass given by the LAMOST pipeline. In each group, the template spectra are constructed using three steps. (1) Outliers are excluded using the Local Outlier Probabilities algorithm, and then the principal component analysis method is applied to the remaining spectra of each group. About 5% of the one million spectra are ruled out as outliers. (2) All remaining spectra are reconstructed using the first principal components of each group. (3) The weighted average spectrum is used as the template spectrum in each group. Using the previous 3 steps, we initially obtain 216 stellar template spectra. We visually inspect all template spectra, and 29 spectra are abandoned due to low spectral quality. Furthermore, the MK classification for the remaining 187 template spectra is manually determined by comparing with 3 template libraries. Meanwhile, 10 template spectra whose subclass is difficult to determine are abandoned. Finally, we obtain a new template library containing 183 LAMOST template spectra with 61 different MK classes by combining it with the current library.

  5. A Method of Particle Swarm Optimized SVM Hyper-spectral Remote Sensing Image Classification

    International Nuclear Information System (INIS)

    Liu, Q J; Jing, L H; Wang, L M; Lin, Q Z

    2014-01-01

    Support Vector Machine (SVM) has been proved to be suitable for classification of remote sensing image and proposed to overcome the Hughes phenomenon. Hyper-spectral sensors are intrinsically designed to discriminate among a broad range of land cover classes which may lead to high computational time in SVM mutil-class algorithms. Model selection for SVM involving kernel and the margin parameter values selection which is usually time-consuming, impacts training efficiency of SVM model and final classification accuracies of SVM hyper-spectral remote sensing image classifier greatly. Firstly, based on combinatorial optimization theory and cross-validation method, particle swarm algorithm is introduced to the optimal selection of SVM (PSSVM) kernel parameter σ and margin parameter C to improve the modelling efficiency of SVM model. Then an experiment of classifying AVIRIS in India Pine site of USA was performed for evaluating the novel PSSVM, as well as traditional SVM classifier with general Grid-Search cross-validation method (GSSVM). And then, evaluation indexes including SVM model training time, classification Overall Accuracy (OA) and Kappa index of both PSSVM and GSSVM are all analyzed quantitatively. It is demonstrated that OA of PSSVM on test samples and whole image are 85% and 82%, the differences with that of GSSVM are both within 0.08% respectively. And Kappa indexes reach 0.82 and 0.77, the differences with that of GSSVM are both within 0.001. While the modelling time of PSSVM can be only 1/10 of that of GSSVM, and the modelling. Therefore, PSSVM is an fast and accurate algorithm for hyper-spectral image classification and is superior to GSSVM

  6. Improving Spectral Image Classification through Band-Ratio Optimization and Pixel Clustering

    Science.gov (United States)

    O'Neill, M.; Burt, C.; McKenna, I.; Kimblin, C.

    2017-12-01

    The Underground Nuclear Explosion Signatures Experiment (UNESE) seeks to characterize non-prompt observables from underground nuclear explosions (UNE). As part of this effort, we evaluated the ability of DigitalGlobe's WorldView-3 (WV3) to detect and map UNE signatures. WV3 is the current state-of-the-art, commercial, multispectral imaging satellite; however, it has relatively limited spectral and spatial resolutions. These limitations impede image classifiers from detecting targets that are spatially small and lack distinct spectral features. In order to improve classification results, we developed custom algorithms to reduce false positive rates while increasing true positive rates via a band-ratio optimization and pixel clustering front-end. The clusters resulting from these algorithms were processed with standard spectral image classifiers such as Mixture-Tuned Matched Filter (MTMF) and Adaptive Coherence Estimator (ACE). WV3 and AVIRIS data of Cuprite, Nevada, were used as a validation data set. These data were processed with a standard classification approach using MTMF and ACE algorithms. They were also processed using the custom front-end prior to the standard approach. A comparison of the results shows that the custom front-end significantly increases the true positive rate and decreases the false positive rate.This work was done by National Security Technologies, LLC, under Contract No. DE-AC52-06NA25946 with the U.S. Department of Energy. DOE/NV/25946-3283.

  7. Spectral-spatial classification of hyperspectral image using three-dimensional convolution network

    Science.gov (United States)

    Liu, Bing; Yu, Xuchu; Zhang, Pengqiang; Tan, Xiong; Wang, Ruirui; Zhi, Lu

    2018-01-01

    Recently, hyperspectral image (HSI) classification has become a focus of research. However, the complex structure of an HSI makes feature extraction difficult to achieve. Most current methods build classifiers based on complex handcrafted features computed from the raw inputs. The design of an improved 3-D convolutional neural network (3D-CNN) model for HSI classification is described. This model extracts features from both the spectral and spatial dimensions through the application of 3-D convolutions, thereby capturing the important discrimination information encoded in multiple adjacent bands. The designed model views the HSI cube data altogether without relying on any pre- or postprocessing. In addition, the model is trained in an end-to-end fashion without any handcrafted features. The designed model was applied to three widely used HSI datasets. The experimental results demonstrate that the 3D-CNN-based method outperforms conventional methods even with limited labeled training samples.

  8. Image-Based Airborne Sensors: A Combined Approach for Spectral Signatures Classification through Deterministic Simulated Annealing

    Science.gov (United States)

    Guijarro, María; Pajares, Gonzalo; Herrera, P. Javier

    2009-01-01

    The increasing technology of high-resolution image airborne sensors, including those on board Unmanned Aerial Vehicles, demands automatic solutions for processing, either on-line or off-line, the huge amountds of image data sensed during the flights. The classification of natural spectral signatures in images is one potential application. The actual tendency in classification is oriented towards the combination of simple classifiers. In this paper we propose a combined strategy based on the Deterministic Simulated Annealing (DSA) framework. The simple classifiers used are the well tested supervised parametric Bayesian estimator and the Fuzzy Clustering. The DSA is an optimization approach, which minimizes an energy function. The main contribution of DSA is its ability to avoid local minima during the optimization process thanks to the annealing scheme. It outperforms simple classifiers used for the combination and some combined strategies, including a scheme based on the fuzzy cognitive maps and an optimization approach based on the Hopfield neural network paradigm. PMID:22399989

  9. Classification of Error-Diffused Halftone Images Based on Spectral Regression Kernel Discriminant Analysis

    Directory of Open Access Journals (Sweden)

    Zhigao Zeng

    2016-01-01

    Full Text Available This paper proposes a novel algorithm to solve the challenging problem of classifying error-diffused halftone images. We firstly design the class feature matrices, after extracting the image patches according to their statistics characteristics, to classify the error-diffused halftone images. Then, the spectral regression kernel discriminant analysis is used for feature dimension reduction. The error-diffused halftone images are finally classified using an idea similar to the nearest centroids classifier. As demonstrated by the experimental results, our method is fast and can achieve a high classification accuracy rate with an added benefit of robustness in tackling noise.

  10. Classification of Hyperspectral or Trichromatic Measurements of Ocean Color Data into Spectral Classes

    Directory of Open Access Journals (Sweden)

    Dilip K. Prasad

    2016-03-01

    Full Text Available We propose a method for classifying radiometric oceanic color data measured by hyperspectral satellite sensors into known spectral classes, irrespective of the downwelling irradiance of the particular day, i.e., the illumination conditions. The focus is not on retrieving the inherent optical properties but to classify the pixels according to the known spectral classes of the reflectances from the ocean. The method compensates for the unknown downwelling irradiance by white balancing the radiometric data at the ocean pixels using the radiometric data of bright pixels (typically from clouds. The white-balanced data is compared with the entries in a pre-calibrated lookup table in which each entry represents the spectral properties of one class. The proposed approach is tested on two datasets of in situ measurements and 26 different daylight illumination spectra for medium resolution imaging spectrometer (MERIS, moderate-resolution imaging spectroradiometer (MODIS, sea-viewing wide field-of-view sensor (SeaWiFS, coastal zone color scanner (CZCS, ocean and land colour instrument (OLCI, and visible infrared imaging radiometer suite (VIIRS sensors. Results are also shown for CIMEL’s SeaPRISM sun photometer sensor used on-board field trips. Accuracy of more than 92% is observed on the validation dataset and more than 86% is observed on the other dataset for all satellite sensors. The potential of applying the algorithms to non-satellite and non-multi-spectral sensors mountable on airborne systems is demonstrated by showing classification results for two consumer cameras. Classification on actual MERIS data is also shown. Additional results comparing the spectra of remote sensing reflectance with level 2 MERIS data and chlorophyll concentration estimates of the data are included.

  11. A COMPARISON STUDY OF DIFFERENT MARKER SELECTION METHODS FOR SPECTRAL-SPATIAL CLASSIFICATION OF HYPERSPECTRAL IMAGES

    Directory of Open Access Journals (Sweden)

    D. Akbari

    2015-12-01

    Full Text Available An effective approach based on the Minimum Spanning Forest (MSF, grown from automatically selected markers using Support Vector Machines (SVM, has been proposed for spectral-spatial classification of hyperspectral images by Tarabalka et al. This paper aims at improving this approach by using image segmentation to integrate the spatial information into marker selection process. In this study, the markers are extracted from the classification maps, obtained by both SVM and segmentation algorithms, and then are used to build the MSF. The segmentation algorithms are the watershed, expectation maximization (EM and hierarchical clustering. These algorithms are used in parallel and independently to segment the image. Moreover, the pixels of each class, with the largest population in the classification map, are kept for each region of the segmentation map. Lastly, the most reliable classified pixels are chosen from among the exiting pixels as markers. Two benchmark urban hyperspectral datasets are used for evaluation: Washington DC Mall and Berlin. The results of our experiments indicate that, compared to the original MSF approach, the marker selection using segmentation algorithms leads in more accurate classification maps.

  12. The Galah Survey: Classification and Diagnostics with t-SNE Reduction of Spectral Information

    Energy Technology Data Exchange (ETDEWEB)

    Traven, G.; Zwitter, T.; Žerjal, M. [Faculty of Mathematics and Physics, University of Ljubljana, Jadranska 19, 1000 Ljubljana (Slovenia); Matijevič, G. [Leibniz-Institut für Astrophysik Potsdam (AIP), An der Sternwarte 16, D-14482 Potsdam (Germany); Kos, J.; Bland-Hawthorn, J.; De Silva, G.; Sharma, S. [Sydney Institute for Astronomy, School of Physics, A28, The University of Sydney, NSW 2006 (Australia); Asplund, M.; Freeman, K.; Lin, J.; Da Costa, G.; Duong, L. [Research School of Astronomy and Astrophysics, Australian National University, Canberra, ACT 2611 (Australia); Casey, A. R. [Institute of Astronomy, University of Cambridge, Madingley Road, Cambridge CB3 0HA (United Kingdom); Martell, S. L. [School of Physics, University of New South Wales, Sydney, NSW 2052 (Australia); Schlesinger, K. J. [Research School of Astronomy and Astrophysics, Mount Stromlo Observatory, Cotter Road, Weston Creek, ACT 2611 (Australia); Simpson, J. D. [Australian Astronomical Observatory, North Ryde, NSW 2113 (Australia); Zucker, D. B. [Australian Astronomical Observatory, P.O. Box 915, North Ryde, NSW 1670 (Australia); Anguiano, B. [Department of Physics and Astronomy, Macquarie University, North Ryde, NSW 2109 (Australia); Horner, J., E-mail: gregor.traven@fmf.uni-lj.si [Computational Engineering and Science Research Centre, University of Southern Queensland, Towoomba QLD 4350 (Australia); and others

    2017-02-01

    Galah is an ongoing high-resolution spectroscopic survey with the goal of disentangling the formation history of the Milky Way using the fossil remnants of disrupted star formation sites that are now dispersed around the Galaxy. It is targeting a randomly selected magnitude-limited ( V ≤ 14) sample of stars, with the goal of observing one million objects. To date, 300,000 spectra have been obtained. Not all of them are correctly processed by parameter estimation pipelines, and we need to know about them. We present a semi-automated classification scheme that identifies different types of peculiar spectral morphologies in an effort to discover and flag potentially problematic spectra and thus help to preserve the integrity of the survey results. To this end, we employ the recently developed dimensionality reduction technique t-SNE ( t -distributed stochastic neighbor embedding), which enables us to represent the complex spectral morphology in a two-dimensional projection map while still preserving the properties of the local neighborhoods of spectra. We find that the majority (178,483) of the 209,533 Galah spectra considered in this study represents normal single stars, whereas 31,050 peculiar and problematic spectra with very diverse spectral features pertaining to 28,579 stars are distributed into 10 classification categories: hot stars, cool metal-poor giants, molecular absorption bands, binary stars, H α /H β emission, H α /H β emission superimposed on absorption, H α /H β P-Cygni, H α /H β inverted P-Cygni, lithium absorption, and problematic. Classified spectra with supplementary information are presented in the catalog, indicating candidates for follow-up observations and population studies of the short-lived phases of stellar evolution.

  13. Spectral reflectance of carbonate sediments and application to remote sensing classification of benthic habitats

    Science.gov (United States)

    Louchard, Eric Michael

    Remote sensing is a valuable tool in marine research that has advanced to the point that images from shallow waters can be used to identify different seafloor types and create maps of benthic habitats. A major goal of this dissertation is to examine differences in spectral reflectance and create new methods of analyzing shallow water remote sensing data to identify different seafloor types quickly and accurately. Carbonate sediments were used as a model system as they presented a relatively uniform, smooth surface for measurement and are a major bottom type in tropical coral reef systems. Experimental results found that sediment reflectance varied in shape and magnitude depending on pigment content, but only varied in magnitude with variations in grain size and shape. Derivative analysis of the reflectance spectra identified wavelength regions that correlate to chlorophyll a and chlorophyllide a as well as accessory pigments, indicating differences in microbial community structure. Derivative peak height also correlated to pigment content in the sediments. In remote sensing data, chlorophyll a, chlorophyllide a, and some xanthophylls were identified in derivative spectra and could be quantified from second derivative peak height. Most accessory pigments were attenuated by the water column, however, and could not be used to quantify pigments in sediments from remote sensing images. Radiative transfer modeling of remote sensing reflectance showed that there was sufficient spectral variation to separate major sediment types, such as ooid shoals and sediment with microbial layers, from different densities of seagrass and pavement bottom communities. Both supervised classification with a spectral library and unsupervised classification with principal component analysis were used to create maps of seafloor type. The results of the experiments were promising; classified seafloor types correlated with ground truth observations taken from underwater video and were

  14. A Framework for Coxeter Spectral Classification of Finite Posets and Their Mesh Geometries of Roots

    Directory of Open Access Journals (Sweden)

    Daniel Simson

    2013-01-01

    Full Text Available Following our paper [Linear Algebra Appl. 433(2010, 699–717], we present a framework and computational tools for the Coxeter spectral classification of finite posets J≡(J,⪯. One of the main motivations for the study is an application of matrix representations of posets in representation theory explained by Drozd [Funct. Anal. Appl. 8(1974, 219–225]. We are mainly interested in a Coxeter spectral classification of posets J such that the symmetric Gram matrix GJ:=(1/2[CJ+CJtr]∈J(ℚ is positive semidefinite, where CJ∈J(ℤ is the incidence matrix of J. Following the idea of Drozd mentioned earlier, we associate to J its Coxeter matrix CoxJ:=-CJ·CJ-tr, its Coxeter spectrum speccJ, a Coxeter polynomial coxJ(t∈ℤ[t], and a Coxeter number  cJ. In case GJ is positive semi-definite, we also associate to J a reduced Coxeter number   čJ, and the defect homomorphism ∂J:ℤJ→ℤ. In this case, the Coxeter spectrum speccJ is a subset of the unit circle and consists of roots of unity. In case GJ is positive semi-definite of corank one, we relate the Coxeter spectral properties of the posets J with the Coxeter spectral properties of a simply laced Euclidean diagram DJ∈{̃n,̃6,̃7,̃8} associated with J. Our aim of the Coxeter spectral analysis of such posets J is to answer the question when the Coxeter type CtypeJ:=(speccJ,cJ,  čJ of J determines its incidence matrix CJ (and, hence, the poset J uniquely, up to a ℤ-congruency. In connection with this question, we also discuss the problem studied by Horn and Sergeichuk [Linear Algebra Appl. 389(2004, 347–353], if for any ℤ-invertible matrix A∈n(ℤ, there is B∈n(ℤ such that Atr=Btr·A·B and B2=E is the identity matrix.

  15. PARALLEL IMPLEMENTATION OF MORPHOLOGICAL PROFILE BASED SPECTRAL-SPATIAL CLASSIFICATION SCHEME FOR HYPERSPECTRAL IMAGERY

    Directory of Open Access Journals (Sweden)

    B. Kumar

    2016-06-01

    Full Text Available Extended morphological profile (EMP is a good technique for extracting spectral-spatial information from the images but large size of hyperspectral images is an important concern for creating EMPs. However, with the availability of modern multi-core processors and commodity parallel processing systems like graphics processing units (GPUs at desktop level, parallel computing provides a viable option to significantly accelerate execution of such computations. In this paper, parallel implementation of an EMP based spectralspatial classification method for hyperspectral imagery is presented. The parallel implementation is done both on multi-core CPU and GPU. The impact of parallelization on speed up and classification accuracy is analyzed. For GPU, the implementation is done in compute unified device architecture (CUDA C. The experiments are carried out on two well-known hyperspectral images. It is observed from the experimental results that GPU implementation provides a speed up of about 7 times, while parallel implementation on multi-core CPU resulted in speed up of about 3 times. It is also observed that parallel implementation has no adverse impact on the classification accuracy.

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

    Directory of Open Access Journals (Sweden)

    X. Han

    2016-06-01

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

  17. Data preprocessing methods of FT-NIR spectral data for the classification cooking oil

    Science.gov (United States)

    Ruah, Mas Ezatul Nadia Mohd; Rasaruddin, Nor Fazila; Fong, Sim Siong; Jaafar, Mohd Zuli

    2014-12-01

    This recent work describes the data pre-processing method of FT-NIR spectroscopy datasets of cooking oil and its quality parameters with chemometrics method. Pre-processing of near-infrared (NIR) spectral data has become an integral part of chemometrics modelling. Hence, this work is dedicated to investigate the utility and effectiveness of pre-processing algorithms namely row scaling, column scaling and single scaling process with Standard Normal Variate (SNV). The combinations of these scaling methods have impact on exploratory analysis and classification via Principle Component Analysis plot (PCA). The samples were divided into palm oil and non-palm cooking oil. The classification model was build using FT-NIR cooking oil spectra datasets in absorbance mode at the range of 4000cm-1-14000cm-1. Savitzky Golay derivative was applied before developing the classification model. Then, the data was separated into two sets which were training set and test set by using Duplex method. The number of each class was kept equal to 2/3 of the class that has the minimum number of sample. Then, the sample was employed t-statistic as variable selection method in order to select which variable is significant towards the classification models. The evaluation of data pre-processing were looking at value of modified silhouette width (mSW), PCA and also Percentage Correctly Classified (%CC). The results show that different data processing strategies resulting to substantial amount of model performances quality. The effects of several data pre-processing i.e. row scaling, column standardisation and single scaling process with Standard Normal Variate indicated by mSW and %CC. At two PCs model, all five classifier gave high %CC except Quadratic Distance Analysis.

  18. VizieR Online Data Catalog: Catalogue of Stellar Spectral Classifications (Skiff, 2009-2016)

    Science.gov (United States)

    Skiff, B. A.

    2014-10-01

    This file contains spectral classifications for stars collected from the literature, serving as a continuation of the compilations produced by the Jascheks, by Kennedy, and by Buscombe. The source of each spectral type is indicated by a standard 19-digit bibcode citation. These papers of course should be cited in publication, not this compilation. The stars are identified either by the name used in each publication or by a valid SIMBAD identifier. Some effort has been made to determine accurate (~1" or better) coordinates for equinox J2000 (and epoch 2000 if possible), and these serve as a secondary identifier. To the extent possible with current astrometric sources, the components of double stars and stars with composite spectra are shown as separate entries. Magnitudes are provided as an indication of brightness, but these data are not necessarily accurate, as they often derive from photographic photometry or rough estimates. The file includes only spectral types determined from spectra (viz. line and band strengths or ratios), omitting those determined from photometry (e.g. DDO, Vilnius) or inferred from broadband colors or spectral energy distributions. The classifications include MK types as well as types not strictly on the MK system (white dwarfs, Wolf-Rayet, etc), and in addition simple HD-style temperature types. Luminosity classes in the early Mount Wilson style (e.g. 'd' for dwarf, 'g' for giant) and other similar schemes have been converted to modern notation. Since a citation is provided for each entry, the source paper should be consulted for details about classification schemes, spectral dispersion, and instrumentation used. System-defining primary MK standard stars are included from the last lists by Morgan and Keenan, and are flagged by a + sign in column 83. The early-type standards comprise the 1973 "dagger standards" (1973ARA&A..11...29M) and stars from the Morgan, Abt, and Tapscott atlas (1978rmsa.book.....M). Standards from Table I of the

  19. VizieR Online Data Catalog: Catalogue of Stellar Spectral Classifications (Skiff, 2009-2012)

    Science.gov (United States)

    Skiff, B. A.

    2010-11-01

    This file contains spectral classifications for stars collected from the literature, serving as a continuation of the compilations produced by the Jascheks, by Kennedy, and by Buscombe. The source of each spectral type is indicated by a standard 19-digit bibcode citation. These papers of course should be cited in publication, not this compilation. The stars are identified either by the name used in each publication or by a valid SIMBAD identifier. Some effort has been made to determine accurate (~1" or better) coordinates for equinox J2000 (and epoch 2000 if possible), and these serve as a secondary identifier. To the extent possible with current astrometric sources, the components of double stars and stars with composite spectra are shown as separate entries. Magnitudes are provided as an indication of brightness, but these data are not necessarily accurate, as they often derive from photographic photometry or rough estimates. The file includes only spectral types determined from spectra (viz. line and band strengths or ratios), omitting those determined from photometry (e.g. DDO, Vilnius) or inferred from broadband colors or spectral energy distributions. The classifications include MK types as well as types not strictly on the MK system (white dwarfs, Wolf-Rayet, etc), and in addition simple HD-style temperature types. Luminosity classes in the early Mount Wilson style (e.g. 'd' for dwarf, 'g' for giant) and other similar schemes have been converted to modern notation. Since a citation is provided for each entry, the source paper should be consulted for details about classification schemes, spectral dispersion, and instrumentation used. System-defining primary MK standard stars are included from the last lists by Morgan and Keenan, and are flagged by a + sign in column 83. The early-type standards comprise the 1973 "dagger standards" (1973ARA&A..11...29M) and stars from the Morgan, Abt, and Tapscott atlas (1978rmsa.book.....M). Standards from Table I of the

  20. VizieR Online Data Catalog: Catalogue of Stellar Spectral Classifications (Skiff, 2009-2014)

    Science.gov (United States)

    Skiff, B. A.

    2014-10-01

    This file contains spectral classifications for stars collected from the literature, serving as a continuation of the compilations produced by the Jascheks, by Kennedy, and by Buscombe. The source of each spectral type is indicated by a standard 19-digit bibcode citation. These papers of course should be cited in publication, not this compilation. The stars are identified either by the name used in each publication or by a valid SIMBAD identifier. Some effort has been made to determine accurate (~1" or better) coordinates for equinox J2000 (and epoch 2000 if possible), and these serve as a secondary identifier. To the extent possible with current astrometric sources, the components of double stars and stars with composite spectra are shown as separate entries. Magnitudes are provided as an indication of brightness, but these data are not necessarily accurate, as they often derive from photographic photometry or rough estimates. The file includes only spectral types determined from spectra (viz. line and band strengths or ratios), omitting those determined from photometry (e.g. DDO, Vilnius) or inferred from broadband colors or spectral energy distributions. The classifications include MK types as well as types not strictly on the MK system (white dwarfs, Wolf-Rayet, etc), and in addition simple HD-style temperature types. Luminosity classes in the early Mount Wilson style (e.g. 'd' for dwarf, 'g' for giant) and other similar schemes have been converted to modern notation. Since a citation is provided for each entry, the source paper should be consulted for details about classification schemes, spectral dispersion, and instrumentation used. System-defining primary MK standard stars are included from the last lists by Morgan and Keenan, and are flagged by a + sign in column 83. The early-type standards comprise the 1973 "dagger standards" (1973ARA&A..11...29M) and stars from the Morgan, Abt, and Tapscott atlas (1978rmsa.book.....M). Standards from Table I of the

  1. VizieR Online Data Catalog: Catalogue of Stellar Spectral Classifications (Skiff, 2010)

    Science.gov (United States)

    Skiff, B. A.

    2009-02-01

    This file contains spectral classifications for stars collected from the literature, serving as a continuation of the compilations produced by the Jascheks, by Kennedy, and by Buscombe. The source of each spectral type is indicated by a standard 19-digit bibcode citation. These papers of course should be cited in publication, not this compilation. The stars are identified either by the name used in each publication or by a valid SIMBAD identifier. Some effort has been made to determine accurate (~1" or better) coordinates for equinox J2000 (and epoch 2000 if possible), and these serve as a secondary identifier. To the extent possible with current astrometric sources, the components of double stars and stars with composite spectra are shown as separate entries. Magnitudes are provided as an indication of brightness, but these data are not necessarily accurate, as they often derive from photographic photometry or rough estimates. The file includes only spectral types determined from spectra (viz. line and band strengths or ratios), omitting those determined from photometry (e.g. DDO, Vilnius) or inferred from broadband colors or spectral energy distributions. The classifications include MK types as well as types not strictly on the MK system (white dwarfs, Wolf-Rayet, etc), and in addition simple HD-style temperature types. Luminosity classes in the early Mount Wilson style (e.g. 'd' for dwarf, 'g' for giant) and other similar schemes have been converted to modern notation. Since a citation is provided for each entry, the source paper should be consulted for details about classification schemes, spectral dispersion, and instrumentation used. System-defining primary MK standard stars are included from the last lists by Morgan and Keenan, and are flagged by a + sign in column 83. The early-type standards comprise the 1973 "dagger standards" (1973ARA&A..11...29M) and stars from the Morgan, Abt, and Tapscott atlas (1978rmsa.book.....M). Standards from Table I of the

  2. VizieR Online Data Catalog: Catalogue of Stellar Spectral Classifications (Skiff, 2009-2013)

    Science.gov (United States)

    Skiff, B. A.

    2013-05-01

    This file contains spectral classifications for stars collected from the literature, serving as a continuation of the compilations produced by the Jascheks, by Kennedy, and by Buscombe. The source of each spectral type is indicated by a standard 19-digit bibcode citation. These papers of course should be cited in publication, not this compilation. The stars are identified either by the name used in each publication or by a valid SIMBAD identifier. Some effort has been made to determine accurate (~1" or better) coordinates for equinox J2000 (and epoch 2000 if possible), and these serve as a secondary identifier. To the extent possible with current astrometric sources, the components of double stars and stars with composite spectra are shown as separate entries. Magnitudes are provided as an indication of brightness, but these data are not necessarily accurate, as they often derive from photographic photometry or rough estimates. The file includes only spectral types determined from spectra (viz. line and band strengths or ratios), omitting those determined from photometry (e.g. DDO, Vilnius) or inferred from broadband colors or spectral energy distributions. The classifications include MK types as well as types not strictly on the MK system (white dwarfs, Wolf-Rayet, etc), and in addition simple HD-style temperature types. Luminosity classes in the early Mount Wilson style (e.g. 'd' for dwarf, 'g' for giant) and other similar schemes have been converted to modern notation. Since a citation is provided for each entry, the source paper should be consulted for details about classification schemes, spectral dispersion, and instrumentation used. System-defining primary MK standard stars are included from the last lists by Morgan and Keenan, and are flagged by a + sign in column 83. The early-type standards comprise the 1973 "dagger standards" (1973ARA&A..11...29M) and stars from the Morgan, Abt, and Tapscott atlas (1978rmsa.book.....M). Standards from Table I of the

  3. SPECTRAL CLASSIFICATION AND PROPERTIES OF THE O Vz STARS IN THE GALACTIC O-STAR SPECTROSCOPIC SURVEY (GOSSS)

    Energy Technology Data Exchange (ETDEWEB)

    Arias, Julia I.; Barbá, Rodolfo H.; Sabín-Sanjulián, Carolina [Departamento de Física y Astronomía, Universidad de La Serena, Av. Cisternas 1200 Norte, La Serena (Chile); Walborn, Nolan R. [Space Telescope Science Institute, 3700 San Martin Drive, MD 21218, Baltimore (United States); Díaz, Sergio Simón [Instituto de Astrofísica de Canarias, E-38200, Departamento de Astrofísica, Universidad de La Laguna, E-38205, La Laguna, Tenerife (Spain); Apellániz, Jesús Maíz [Centro de Astrobiología, CSIC-INTA, campus ESAC, Camino Bajo del Castillo s/n, E-28 692 Madrid (Spain); Gamen, Roberto C. [Instituto de Astrofísica de La Plata (CONICET, UNLP), Facultad de Ciencias Astronómicas y Geofísicas, Universidad Nacional de La Plata, Paseo del Bosque s/n, 1900 La Plata (Argentina); Morrell, Nidia I. [Las Campanas Observatory, Carnegie Observatories, Casilla 601, La Serena (Chile); Sota, Alfredo [Instituto de Astrofísica de Andalucía-CSIC, Glorieta de la Astronomía s/n, E-18 008 Granada (Spain); Marco, Amparo; Negueruela, Ignacio, E-mail: jarias@userena.cl [Departamento de Física, Ingeniería de Sistemas y Teoría de la Señal, Escuela Politécnica Superior, Universidad de Alicante, Carretera San Vicente del Raspeig s/n, E03690, San Vicente del Raspeig (Spain); and others

    2016-08-01

    On the basis of the Galactic O Star Spectroscopic Survey (GOSSS), we present a detailed systematic investigation of the O Vz stars. The currently used spectral classification criteria are rediscussed, and the Vz phenomenon is recalibrated through the addition of a quantitative criterion based on the equivalent widths of the He i λ 4471, He ii λ 4542, and He ii λ 4686 spectral lines. The GOSSS O Vz and O V populations resulting from the newly adopted spectral classification criteria are comparatively analyzed. The locations of the O Vz stars are probed, showing a concentration of the most extreme cases toward the youngest star-forming regions. The occurrence of the Vz spectral peculiarity in a solar-metallicity environment, as predicted by the fastwind code, is also investigated, confirming the importance of taking into account several processes for the correct interpretation of the phenomenon.

  4. SPECTRAL CLASSIFICATION AND PROPERTIES OF THE O Vz STARS IN THE GALACTIC O-STAR SPECTROSCOPIC SURVEY (GOSSS)

    International Nuclear Information System (INIS)

    Arias, Julia I.; Barbá, Rodolfo H.; Sabín-Sanjulián, Carolina; Walborn, Nolan R.; Díaz, Sergio Simón; Apellániz, Jesús Maíz; Gamen, Roberto C.; Morrell, Nidia I.; Sota, Alfredo; Marco, Amparo; Negueruela, Ignacio

    2016-01-01

    On the basis of the Galactic O Star Spectroscopic Survey (GOSSS), we present a detailed systematic investigation of the O Vz stars. The currently used spectral classification criteria are rediscussed, and the Vz phenomenon is recalibrated through the addition of a quantitative criterion based on the equivalent widths of the He i λ 4471, He ii λ 4542, and He ii λ 4686 spectral lines. The GOSSS O Vz and O V populations resulting from the newly adopted spectral classification criteria are comparatively analyzed. The locations of the O Vz stars are probed, showing a concentration of the most extreme cases toward the youngest star-forming regions. The occurrence of the Vz spectral peculiarity in a solar-metallicity environment, as predicted by the fastwind code, is also investigated, confirming the importance of taking into account several processes for the correct interpretation of the phenomenon.

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

    Science.gov (United States)

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

    2018-04-01

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

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

    Science.gov (United States)

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

    2017-01-01

    Hyperspectral imaging is an emerging means of assessing plant vitality, stress parameters, nutrition status, and diseases. Extraction of target values from the high-dimensional datasets either relies on pixel-wise processing of the full spectral information, appropriate selection of individual bands, or calculation of spectral indices. Limitations of such approaches are reduced classification accuracy, reduced robustness due to spatial variation of the spectral information across the surface of the objects measured as well as a loss of information intrinsic to band selection and use of spectral indices. In this paper we present an improved spatial-spectral segmentation approach for the analysis of hyperspectral imaging data and its application for the prediction of powdery mildew infection levels (disease severity) of intact Chardonnay grape bunches shortly before veraison. Instead of calculating texture features (spatial features) for the huge number of spectral bands independently, dimensionality reduction by means of Linear Discriminant Analysis (LDA) was applied first to derive a few descriptive image bands. Subsequent classification was based on modified Random Forest classifiers and selective extraction of texture parameters from the integral image representation of the image bands generated. Dimensionality reduction, integral images, and the selective feature extraction led to improved classification accuracies of up to [Formula: see text] for detached berries used as a reference sample (training dataset). Our approach was validated by predicting infection levels for a sample of 30 intact bunches. Classification accuracy improved with the number of decision trees of the Random Forest classifier. These results corresponded with qPCR results. An accuracy of 0.87 was achieved in classification of healthy, infected, and severely diseased bunches. However, discrimination between visually healthy and infected bunches proved to be challenging for a few samples

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

    Directory of Open Access Journals (Sweden)

    Eva Husson

    2017-03-01

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

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

    Directory of Open Access Journals (Sweden)

    Hongrui Zheng

    2017-12-01

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

  9. Assessing the Impact of Spectral Resolution on Classification of Lowland Native Grassland Communities Based on Field Spectroscopy in Tasmania, Australia

    Directory of Open Access Journals (Sweden)

    Bethany Melville

    2018-02-01

    Full Text Available This paper presents a case study for the analysis of endangered lowland native grassland communities in the Tasmanian Midlands region using field spectroscopy and spectral convolution techniques. The aim of the study was to determine whether there was significant improvement in classification accuracy for lowland native grasslands and other vegetation communities based on hyperspectral resolution datasets over multispectral equivalents. A spectral dataset was collected using an ASD Handheld-2 spectroradiometer at Tunbridge Township Lagoon. The study then employed a k-fold cross-validation approach for repeated classification of a full hyperspectral dataset, a reduced hyperspectral dataset, and two convoluted multispectral datasets. Classification was performed on each of the four datasets a total of 30 times, based on two different class configurations. The classes analysed were Themeda triandra grassland, Danthonia/Poa grassland, Wilsonia rotundifolia/Selliera radicans, saltpan, and a simplified C3 vegetation class. The results of the classifications were then tested for statistically significant differences using ANOVA and Tukey’s post-hoc comparisons. The results of the study indicated that hyperspectral resolution provides small but statistically significant increases in classification accuracy for Themeda and Danthonia grasslands. For other classes, differences in classification accuracy for all datasets were not statistically significant. The results obtained here indicate that there is some potential for enhanced detection of major lowland native grassland community types using hyperspectral resolution datasets, and that future analysis should prioritise good performance in these classes over others. This study presents a method for identification of optimal spectral resolution across multiple datasets, and constitutes an important case study for lowland native grassland mapping in Tasmania.

  10. Jet Joint Undertaking. Vol. 2

    International Nuclear Information System (INIS)

    1989-06-01

    The scientific, technical, experimental and theoretical investigations related to JET tokamak are presented. The JET Joint Undertaking, Volume 2, includes papers presented at: the 15th European Conference on controlled fusion and plasma heating, the 15th Symposium on fusion technology, the 12th IAEA Conference on plasma physics and controlled nuclear fusion research, the 8th Topical Meeting on technology of fusion. Moreover, the following topics, concerning JET, are discussed: experience with wall materials, plasma performance, high power ion cyclotron resonance heating, plasma boundary, results and prospects for fusion, preparation for D-T operation, active gas handling system and remote handling equipment

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

    Science.gov (United States)

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

    2011-03-01

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

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

    Directory of Open Access Journals (Sweden)

    Yi Wang

    2018-03-01

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

  13. A k-mer-based barcode DNA classification methodology based on spectral representation and a neural gas network.

    Science.gov (United States)

    Fiannaca, Antonino; La Rosa, Massimo; Rizzo, Riccardo; Urso, Alfonso

    2015-07-01

    In this paper, an alignment-free method for DNA barcode classification that is based on both a spectral representation and a neural gas network for unsupervised clustering is proposed. In the proposed methodology, distinctive words are identified from a spectral representation of DNA sequences. A taxonomic classification of the DNA sequence is then performed using the sequence signature, i.e., the smallest set of k-mers that can assign a DNA sequence to its proper taxonomic category. Experiments were then performed to compare our method with other supervised machine learning classification algorithms, such as support vector machine, random forest, ripper, naïve Bayes, ridor, and classification tree, which also consider short DNA sequence fragments of 200 and 300 base pairs (bp). The experimental tests were conducted over 10 real barcode datasets belonging to different animal species, which were provided by the on-line resource "Barcode of Life Database". The experimental results showed that our k-mer-based approach is directly comparable, in terms of accuracy, recall and precision metrics, with the other classifiers when considering full-length sequences. In addition, we demonstrate the robustness of our method when a classification is performed task with a set of short DNA sequences that were randomly extracted from the original data. For example, the proposed method can reach the accuracy of 64.8% at the species level with 200-bp fragments. Under the same conditions, the best other classifier (random forest) reaches the accuracy of 20.9%. Our results indicate that we obtained a clear improvement over the other classifiers for the study of short DNA barcode sequence fragments. Copyright © 2015 Elsevier B.V. All rights reserved.

  14. A classification of spectral populations observed in HF radar backscatter from the E region auroral electrojets

    Directory of Open Access Journals (Sweden)

    S. E. Milan

    2001-02-01

    Full Text Available Observations of HF radar backscatter from the auroral electrojet E region indicate the presence of five major spectral populations, as opposed to the two predominant spectral populations, types I and II, observed in the VHF regime. The Doppler shift, spectral width, backscatter power, and flow angle dependencies of these five populations are investigated and described. Two of these populations are identified with type I and type II spectral classes, and hence, are thought to be generated by the two-stream and gradient drift instabilities, respectively. The remaining three populations occur over a range of velocities which can greatly exceed the ion acoustic speed, the usual limiting velocity in VHF radar observations of the E region. The generation of these spectral populations is discussed in terms of electron density gradients in the electrojet region and recent non-linear theories of E region irregularity generation.Key words. Ionosphere (ionospheric irregularities

  15. A classification of spectral populations observed in HF radar backscatter from the E region auroral electrojets

    Directory of Open Access Journals (Sweden)

    S. E. Milan

    Full Text Available Observations of HF radar backscatter from the auroral electrojet E region indicate the presence of five major spectral populations, as opposed to the two predominant spectral populations, types I and II, observed in the VHF regime. The Doppler shift, spectral width, backscatter power, and flow angle dependencies of these five populations are investigated and described. Two of these populations are identified with type I and type II spectral classes, and hence, are thought to be generated by the two-stream and gradient drift instabilities, respectively. The remaining three populations occur over a range of velocities which can greatly exceed the ion acoustic speed, the usual limiting velocity in VHF radar observations of the E region. The generation of these spectral populations is discussed in terms of electron density gradients in the electrojet region and recent non-linear theories of E region irregularity generation.

    Key words. Ionosphere (ionospheric irregularities

  16. COMPARISON BETWEEN SPECTRAL, SPATIAL AND POLARIMETRIC CLASSIFICATION OF URBAN AND PERIURBAN LANDCOVER USING TEMPORAL SENTINEL – 1 IMAGES

    Directory of Open Access Journals (Sweden)

    K. Roychowdhury

    2016-06-01

    Full Text Available Landcover is the easiest detectable indicator of human interventions on land. Urban and peri-urban areas present a complex combination of landcover, which makes classification challenging. This paper assesses the different methods of classifying landcover using dual polarimetric Sentinel-1 data collected during monsoon (July and winter (December months of 2015. Four broad landcover classes such as built up areas, water bodies and wetlands, vegetation and open spaces of Kolkata and its surrounding regions were identified. Polarimetric analyses were conducted on Single Look Complex (SLC data of the region while ground range detected (GRD data were used for spectral and spatial classification. Unsupervised classification by means of K-Means clustering used backscatter values and was able to identify homogenous landcovers over the study area. The results produced an overall accuracy of less than 50% for both the seasons. Higher classification accuracy (around 70% was achieved by adding texture variables as inputs along with the backscatter values. However, the accuracy of classification increased significantly with polarimetric analyses. The overall accuracy was around 80% in Wishart H-A-Alpha unsupervised classification. The method was useful in identifying urban areas due to their double-bounce scattering and vegetated areas, which have more random scattering. Normalized Difference Built-up index (NDBI and Normalized Difference Vegetation Index (NDVI obtained from Landsat 8 data over the study area were used to verify vegetation and urban classes. The study compares the accuracies of different methods of classifying landcover using medium resolution SAR data in a complex urban area and suggests that polarimetric analyses present the most accurate results for urban and suburban areas.

  17. Comparison Between Spectral, Spatial and Polarimetric Classification of Urban and Periurban Landcover Using Temporal Sentinel - 1 Images

    Science.gov (United States)

    Roychowdhury, K.

    2016-06-01

    Landcover is the easiest detectable indicator of human interventions on land. Urban and peri-urban areas present a complex combination of landcover, which makes classification challenging. This paper assesses the different methods of classifying landcover using dual polarimetric Sentinel-1 data collected during monsoon (July) and winter (December) months of 2015. Four broad landcover classes such as built up areas, water bodies and wetlands, vegetation and open spaces of Kolkata and its surrounding regions were identified. Polarimetric analyses were conducted on Single Look Complex (SLC) data of the region while ground range detected (GRD) data were used for spectral and spatial classification. Unsupervised classification by means of K-Means clustering used backscatter values and was able to identify homogenous landcovers over the study area. The results produced an overall accuracy of less than 50% for both the seasons. Higher classification accuracy (around 70%) was achieved by adding texture variables as inputs along with the backscatter values. However, the accuracy of classification increased significantly with polarimetric analyses. The overall accuracy was around 80% in Wishart H-A-Alpha unsupervised classification. The method was useful in identifying urban areas due to their double-bounce scattering and vegetated areas, which have more random scattering. Normalized Difference Built-up index (NDBI) and Normalized Difference Vegetation Index (NDVI) obtained from Landsat 8 data over the study area were used to verify vegetation and urban classes. The study compares the accuracies of different methods of classifying landcover using medium resolution SAR data in a complex urban area and suggests that polarimetric analyses present the most accurate results for urban and suburban areas.

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

    CSIR Research Space (South Africa)

    Lunga, D

    2013-08-01

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

  19. CLASSIFICATION AND QUANTITATIVE ANALYSIS OF GEOGRAPHIC ATROPHY JUNCTIONAL ZONE USING SPECTRAL DOMAIN OPTICAL COHERENCE TOMOGRAPHY.

    Science.gov (United States)

    Qu, Jinfeng; Velaga, Swetha Bindu; Hariri, Amir H; Nittala, Muneeswar Gupta; Sadda, Srinivas

    2017-08-22

    The junctional zone at the border of areas of geographic atrophy (GA) in eyes with nonneovascular age-related macular degeneration is an important target region for future therapeutic strategies. The goal of this study was to perform a detailed classification and quantitative characterization of the junctional zone using spectral domain optical coherence tomography. Spectral domain optical coherence tomography volume cube scans (Spectralis OCT, 1024 × 37, Automatic Real Time > 9) were obtained from 15 eyes of 11 patients with GA because of nonneovascular age-related macular degeneration. Volume optical coherence tomography data were imported into previously described validated grading software (3D-OCTOR), and manual segmentation of the retinal pigment epithelium (RPE) and photoreceptor layers was performed on all B-scans (total of 555). Retinal pigment epithelium and photoreceptor defect maps were produced for each case. The borders of the photoreceptor defect area and RPE defect area were delineated individually on separate annotation layers. The two outlines were then superimposed to compare the areas of overlap and nonoverlap. The perimeter of the RPE defect area was calculated by the software in pixels. The superimposed outline of the photoreceptor defect area and the RPE defect area was scrutinized to classify the overlap configuration of the junctional zone into one of three categories: Type 0, exact correspondence between the edge of the RPE defect and photoreceptor defect; Type 1, loss of photoreceptors outside and beyond the edge of the RPE defect; Type 2, preservation of photoreceptors beyond the edge of the RPE defect. The relative proportion of the various border configurations was expressed as a percentage of the perimeter of the RPE defect. Each configuration was then classified into four subgroups according to irregularity of the RPE band and the presence of debris. Fifteen eyes of 11 patients (mean age: 79.3 ± 4.3 years; range: 79-94 years) were

  20. Object-Based Land Use Classification of Agricultural Land by Coupling Multi-Temporal Spectral Characteristics and Phenological Events in Germany

    Science.gov (United States)

    Knoefel, Patrick; Loew, Fabian; Conrad, Christopher

    2015-04-01

    Crop maps based on classification of remotely sensed data are of increased attendance in agricultural management. This induces a more detailed knowledge about the reliability of such spatial information. However, classification of agricultural land use is often limited by high spectral similarities of the studied crop types. More, spatially and temporally varying agro-ecological conditions can introduce confusion in crop mapping. Classification errors in crop maps in turn may have influence on model outputs, like agricultural production monitoring. One major goal of the PhenoS project ("Phenological structuring to determine optimal acquisition dates for Sentinel-2 data for field crop classification"), is the detection of optimal phenological time windows for land cover classification purposes. Since many crop species are spectrally highly similar, accurate classification requires the right selection of satellite images for a certain classification task. In the course of one growing season, phenological phases exist where crops are separable with higher accuracies. For this purpose, coupling of multi-temporal spectral characteristics and phenological events is promising. The focus of this study is set on the separation of spectrally similar cereal crops like winter wheat, barley, and rye of two test sites in Germany called "Harz/Central German Lowland" and "Demmin". However, this study uses object based random forest (RF) classification to investigate the impact of image acquisition frequency and timing on crop classification uncertainty by permuting all possible combinations of available RapidEye time series recorded on the test sites between 2010 and 2014. The permutations were applied to different segmentation parameters. Then, classification uncertainty was assessed and analysed, based on the probabilistic soft-output from the RF algorithm at the per-field basis. From this soft output, entropy was calculated as a spatial measure of classification uncertainty

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

    Science.gov (United States)

    Bhardwaj, Kaushal; Patra, Swarnajyoti

    2018-04-01

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

  2. Comparison of Aerosol Classification From Airborne High Spectral Resolution Lidar and the CALIPSO Vertical Feature Mask

    Science.gov (United States)

    Burton, Sharon P.; Ferrare, Rich A.; Omar, Ali H.; Vaughan, Mark A.; Rogers, Raymond R.; Hostetler, Chris a.; Hair, Johnathan W.; Obland, Michael D.; Butler, Carolyn F.; Cook, Anthony L.; hide

    2012-01-01

    Knowledge of aerosol composition and vertical distribution is crucial for assessing the impact of aerosols on climate. In addition, aerosol classification is a key input to CALIOP aerosol retrievals, since CALIOP requires an inference of the lidar ratio in order to estimate the effects of aerosol extinction and backscattering. In contrast, the NASA airborne HSRL-1 directly measures both aerosol extinction and backscatter, and therefore the lidar ratio (extinction-to-backscatter ratio). Four aerosol intensive properties from HSRL-1 are combined to infer aerosol type. Aerosol classification results from HSRL-1 are used here to validate the CALIOP aerosol type inferences.

  3. Classification of Clean and Dirty Pighouse Surfaces Based on Spectral Reflectance

    DEFF Research Database (Denmark)

    Blanke, Mogens; Braithwaite, Ian David; Zhang, Guo-Qiang

    2004-01-01

    of designing a vision based system to locate dirty areas and subsequently direct a cleaning robot to remove dirt. Novel results include the characterisation of the spectral reflectance of real surfaces and dirt in a pig house and the design of illumination to obtain discrimination of clean from dirty areas...

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

    Science.gov (United States)

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

    2018-06-01

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

  5. Urban Classification Techniques Using the Fusion of LiDAR and Spectral Data

    Science.gov (United States)

    2012-09-01

    37 D. MASK CREATION .......................................................................................39 viii 1. LiDAR-based Masks...in Quick Terrain Modeler 2. WorldView-2 The image used in this project was collected by WorldView-2 on November 8, 2011 at Zulu time 19:34:42...OBSERVATIONS A. PROCESS OVERVIEW The focus of this thesis was to create a robust technique for fusing LiDAR and spectral imagery for creation of a

  6. Machine learning in APOGEE. Unsupervised spectral classification with K-means

    Science.gov (United States)

    Garcia-Dias, Rafael; Allende Prieto, Carlos; Sánchez Almeida, Jorge; Ordovás-Pascual, Ignacio

    2018-05-01

    Context. The volume of data generated by astronomical surveys is growing rapidly. Traditional analysis techniques in spectroscopy either demand intensive human interaction or are computationally expensive. In this scenario, machine learning, and unsupervised clustering algorithms in particular, offer interesting alternatives. The Apache Point Observatory Galactic Evolution Experiment (APOGEE) offers a vast data set of near-infrared stellar spectra, which is perfect for testing such alternatives. Aims: Our research applies an unsupervised classification scheme based on K-means to the massive APOGEE data set. We explore whether the data are amenable to classification into discrete classes. Methods: We apply the K-means algorithm to 153 847 high resolution spectra (R ≈ 22 500). We discuss the main virtues and weaknesses of the algorithm, as well as our choice of parameters. Results: We show that a classification based on normalised spectra captures the variations in stellar atmospheric parameters, chemical abundances, and rotational velocity, among other factors. The algorithm is able to separate the bulge and halo populations, and distinguish dwarfs, sub-giants, RC, and RGB stars. However, a discrete classification in flux space does not result in a neat organisation in the parameters' space. Furthermore, the lack of obvious groups in flux space causes the results to be fairly sensitive to the initialisation, and disrupts the efficiency of commonly-used methods to select the optimal number of clusters. Our classification is publicly available, including extensive online material associated with the APOGEE Data Release 12 (DR12). Conclusions: Our description of the APOGEE database can help greatly with the identification of specific types of targets for various applications. We find a lack of obvious groups in flux space, and identify limitations of the K-means algorithm in dealing with this kind of data. Full Tables B.1-B.4 are only available at the CDS via

  7. Classification of Astaxanthin Colouration of Salmonid Fish using Spectral Imaging and Tricolour Measurement

    DEFF Research Database (Denmark)

    Ljungqvist, Martin Georg; Dissing, Bjørn Skovlund; Nielsen, Michael Engelbrecht

    capturing, tricolour CIELAB measurement, and manual SalmoFan inspection. Furthermore it was tested whether the best predictions come from measurements of the steak or the fillet of the fish. Methods used for classication were linear discriminant analysis (LDA), quadratic discriminant analysis (QDA......The goal of this study was to investigate if it is possible to differentiate between rainbow trout (Oncorhynchus mykiss) having been fed with natural or synthetic astaxanthin. Three different techniques were used for visual inspection of the surface colour of the fish meat: multi-spectral image...

  8. Object Classification Based on Analysis of Spectral Characteristics of Seismic Signal Envelopes

    Science.gov (United States)

    Morozov, Yu. V.; Spektor, A. A.

    2017-11-01

    A method for classifying moving objects having a seismic effect on the ground surface is proposed which is based on statistical analysis of the envelopes of received signals. The values of the components of the amplitude spectrum of the envelopes obtained applying Hilbert and Fourier transforms are used as classification criteria. Examples illustrating the statistical properties of spectra and the operation of the seismic classifier are given for an ensemble of objects of four classes (person, group of people, large animal, vehicle). It is shown that the computational procedures for processing seismic signals are quite simple and can therefore be used in real-time systems with modest requirements for computational resources.

  9. Investigating the Potential of Using the Spatial and Spectral Information of Multispectral LiDAR for Object Classification

    Directory of Open Access Journals (Sweden)

    Wei Gong

    2015-09-01

    Full Text Available The abilities of multispectral LiDAR (MSL as a new high-potential active instrument for remote sensing have not been fully revealed. This study demonstrates the potential of using the spectral and spatial features derived from a novel MSL to discriminate surface objects. Data acquired with the MSL include distance information and the intensities of four wavelengths at 556, 670, 700, and 780 nm channels. A support vector machine was used to classify diverse objects in the experimental scene into seven types: wall, ceramic pots, Cactaceae, carton, plastic foam block, and healthy and dead leaves of E. aureum. Different features were used during classification to compare the performance of different detection systems. The spectral backscattered reflectance of one wavelength and distance represented the features from an equivalent single-wavelength LiDAR system; reflectance of the four wavelengths represented the features from an equivalent multispectral image with four bands. Results showed that the overall accuracy of using MSL data was as high as 88.7%, this value was 9.8%–39.2% higher than those obtained using a single-wavelength LiDAR, and 4.2% higher than for multispectral image.

  10. Classification

    Science.gov (United States)

    Clary, Renee; Wandersee, James

    2013-01-01

    In this article, Renee Clary and James Wandersee describe the beginnings of "Classification," which lies at the very heart of science and depends upon pattern recognition. Clary and Wandersee approach patterns by first telling the story of the "Linnaean classification system," introduced by Carl Linnacus (1707-1778), who is…

  11. Spectral classification of medium-scale high-latitude F region plasma density irregularities

    International Nuclear Information System (INIS)

    Singh, M.; Rodriguez, P.; Szuszczewicz, E.P.; Sachs Freeman Associates, Bowie, MD)

    1985-01-01

    The high-latitude ionosphere represents a highly structured plasma. Rodriguez and Szuszczewicz (1984) reported a wide range of plasma density irregularities (150 km to 75 m) at high latitudes near 200 km. They have shown that the small-scale irregularities (7.5 km to 75 m) populated the dayside oval more often than the other phenomenological regions. It was suggested that in the lower F region the chemical recombination is fast enough to remove small-scale irregularities before convection can transport them large distances, leaving structured particle precipitation as the dominant source term for irregularities. The present paper provides the results of spectral analyses of pulsed plasma probe data collected in situ aboard the STP/S3-4 satellite during the period March-September 1978. A quantitative description of irregularity spectra in the high-latitude lower F region plasma density is given. 22 references

  12. Application of higher order spectral features and support vector machines for bearing faults classification.

    Science.gov (United States)

    Saidi, Lotfi; Ben Ali, Jaouher; Fnaiech, Farhat

    2015-01-01

    Condition monitoring and fault diagnosis of rolling element bearings timely and accurately are very important to ensure the reliability of rotating machinery. This paper presents a novel pattern classification approach for bearings diagnostics, which combines the higher order spectra analysis features and support vector machine classifier. The use of non-linear features motivated by the higher order spectra has been reported to be a promising approach to analyze the non-linear and non-Gaussian characteristics of the mechanical vibration signals. The vibration bi-spectrum (third order spectrum) patterns are extracted as the feature vectors presenting different bearing faults. The extracted bi-spectrum features are subjected to principal component analysis for dimensionality reduction. These principal components were fed to support vector machine to distinguish four kinds of bearing faults covering different levels of severity for each fault type, which were measured in the experimental test bench running under different working conditions. In order to find the optimal parameters for the multi-class support vector machine model, a grid-search method in combination with 10-fold cross-validation has been used. Based on the correct classification of bearing patterns in the test set, in each fold the performance measures are computed. The average of these performance measures is computed to report the overall performance of the support vector machine classifier. In addition, in fault detection problems, the performance of a detection algorithm usually depends on the trade-off between robustness and sensitivity. The sensitivity and robustness of the proposed method are explored by running a series of experiments. A receiver operating characteristic (ROC) curve made the results more convincing. The results indicated that the proposed method can reliably identify different fault patterns of rolling element bearings based on vibration signals. Copyright © 2014 ISA

  13. Classification

    DEFF Research Database (Denmark)

    Hjørland, Birger

    2017-01-01

    This article presents and discusses definitions of the term “classification” and the related concepts “Concept/conceptualization,”“categorization,” “ordering,” “taxonomy” and “typology.” It further presents and discusses theories of classification including the influences of Aristotle...... and Wittgenstein. It presents different views on forming classes, including logical division, numerical taxonomy, historical classification, hermeneutical and pragmatic/critical views. Finally, issues related to artificial versus natural classification and taxonomic monism versus taxonomic pluralism are briefly...

  14. A Contribution for the Automatic Sleep Classification Based on the Itakura-Saito Spectral Distance

    Science.gov (United States)

    Cardoso, Eduardo; Batista, Arnaldo; Rodrigues, Rui; Ortigueira, Manuel; Bárbara, Cristina; Martinho, Cristina; Rato, Raul

    Sleep staging is a crucial step before the scoring the sleep apnoea, in subjects that are tested for this condition. These patients undergo a whole night polysomnography recording that includes EEG, EOG, ECG, EMG and respiratory signals. Sleep staging refers to the quantification of its depth. Despite the commercial sleep software being able to stage the sleep, there is a general lack of confidence amongst health practitioners of these machine results. Generally the sleep scoring is done over the visual inspection of the overnight patient EEG recording, which takes the attention of an expert medical practitioner over a couple of hours. This contributes to a waiting list of two years for patients of the Portuguese Health Service. In this work we have used a spectral comparison method called Itakura distance to be able to make a distinction between sleepy and awake epochs in a night EEG recording, therefore automatically doing the staging. We have used the data from 20 patients of Hospital Pulido Valente, which had been previously visually expert scored. Our technique results were promising, in a way that Itakura distance can, by itself, distinguish with a good degree of certainty the N2, N3 and awake states. Pre-processing stages for artefact reduction and baseline removal using Wavelets were applied.

  15. Ontology-based classification of remote sensing images using spectral rules

    Science.gov (United States)

    Andrés, Samuel; Arvor, Damien; Mougenot, Isabelle; Libourel, Thérèse; Durieux, Laurent

    2017-05-01

    Earth Observation data is of great interest for a wide spectrum of scientific domain applications. An enhanced access to remote sensing images for "domain" experts thus represents a great advance since it allows users to interpret remote sensing images based on their domain expert knowledge. However, such an advantage can also turn into a major limitation if this knowledge is not formalized, and thus is difficult for it to be shared with and understood by other users. In this context, knowledge representation techniques such as ontologies should play a major role in the future of remote sensing applications. We implemented an ontology-based prototype to automatically classify Landsat images based on explicit spectral rules. The ontology is designed in a very modular way in order to achieve a generic and versatile representation of concepts we think of utmost importance in remote sensing. The prototype was tested on four subsets of Landsat images and the results confirmed the potential of ontologies to formalize expert knowledge and classify remote sensing images.

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

    Directory of Open Access Journals (Sweden)

    Himmelreich Uwe

    2009-07-01

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

  17. Price Undertakings, VERs, and Foreign Direct Investment

    OpenAIRE

    Ishikawa, Jota; Miyagiwa, Kaz

    2006-01-01

    We compare the relative effect of a voluntary export restraint (VER) and a price undertaking on foreign firms' incentive to engage in FDI. We emphasize foreign rivalry as a determinant of FDI. We show, in a model that has two foreign firms competing with a home firm in the home country, that a price undertaking induces more FDI than a VER. The home country government, operating under the constraint to protect the home firm, is generally better off settling an antidumping case with a VER than ...

  18. JET joint undertaking. Annual report 1978

    International Nuclear Information System (INIS)

    1979-02-01

    This document is intended for information only and should not be used as a technical reference. After an introductive part on the controlled nuclear fusion research and an historical survey of the JET project, are presented: the JET joint undertaking (members of council and committee...) with its administration (finance, personnel, external relations), and the scientific and technical department with its divisions for systems (experimental, magnet, plasma, assembly, power supplies, control and data acquisition, and site and building). In appendix is described the Euratom fusion research programme

  19. Spectral analysis and classification of igneous and metamorphic rocks of Hamedan region for remote sensing studies; using laboratory reflectance spectra (350-2500 nm)

    International Nuclear Information System (INIS)

    Rangzan, K.; Saki, A.; Hassanshahi, H.; Mojaradi, B.

    2012-01-01

    Reflectance spectrometry techniques with the integration of remote sensing data help us in identifying and mapping the phenomena on the earth. Using these techniques to discriminate the petrologic units independently and without knowing the spectral behavior of rocks along the electromagnetic wavelengths can not be so much useful. For the purposes of this study, 65 samples of igneous and metamorphic rocks from Hamedan region were collected and their spectra were measured using Fieldspec3 device in laboratory. The spectra were analyzed on the basis of absorption, position and shape. Petrographic analyses were used to interpret the absorption patterns as well. Then the spectra were classified according to spectral patterns. This measurement was done on both freshly cut and exposed surfaces of the samples and except a few samples, the two sets of spectra did not differ significantly. Finally, to evaluate the possibility of recognition of these targets, the responses of two hyper spectral and multispectral sensors were simulated from spectra representative of the spectral classes, showing that significant identification and classification of well exposed rocks are potentially possible using remote instruments providing high quality spectra. Also Aster simulation showed that a preliminary gross discrimination of rocks was however possible.

  20. Improving classification accuracy of spectrally similar tree species: a complex case study in the Kruger National Park

    CSIR Research Space (South Africa)

    Debba, Pravesh

    2009-07-01

    Full Text Available , sugar beet, sunflower, alfalfa. Digital Imaging Spectrometer – DAIS-7915 – 79 channel hyperspectral image. Spectral range from visible (0.4 µm) to thermal infrared (12.3 µm). Spatial resolution 3–20 m depending on the carrier aircraft altitude...

  1. Detection and classification of salmonella serotypes using spectral signatures collected by fourier transform infrared (FT-IR) spectroscopy

    Science.gov (United States)

    Spectral signatures of Salmonella serotypes namely Salmonella Typhimurium, Salmonella Enteritidis, Salmonella Infantis, Salmonella Heidelberg and Salmonella Kentucky were collected using Fourier transform infrared spectroscopy (FT-IR). About 5-10 µL of Salmonella suspensions with concentrations of 1...

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

    Science.gov (United States)

    Teimoorinia, H.

    2012-12-01

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

  3. Site classification for National Strong Motion Observation Network System (NSMONS) stations in China using an empirical H/V spectral ratio method

    Science.gov (United States)

    Ji, Kun; Ren, Yefei; Wen, Ruizhi

    2017-10-01

    Reliable site classification of the stations of the China National Strong Motion Observation Network System (NSMONS) has not yet been assigned because of lacking borehole data. This study used an empirical horizontal-to-vertical (H/V) spectral ratio (hereafter, HVSR) site classification method to overcome this problem. First, according to their borehole data, stations selected from KiK-net in Japan were individually assigned a site class (CL-I, CL-II, or CL-III), which is defined in the Chinese seismic code. Then, the mean HVSR curve for each site class was computed using strong motion recordings captured during the period 1996-2012. These curves were compared with those proposed by Zhao et al. (2006a) for four types of site classes (SC-I, SC-II, SC-III, and SC-IV) defined in the Japanese seismic code (JRA, 1980). It was found that an approximate range of the predominant period Tg could be identified by the predominant peak of the HVSR curve for the CL-I and SC-I sites, CL-II and SC-II sites, and CL-III and SC-III + SC-IV sites. Second, an empirical site classification method was proposed based on comprehensive consideration of peak period, amplitude, and shape of the HVSR curve. The selected stations from KiK-net were classified using the proposed method. The results showed that the success rates of the proposed method in identifying CL-I, CL-II, and CL-III sites were 63%, 64%, and 58% respectively. Finally, the HVSRs of 178 NSMONS stations were computed based on recordings from 2007 to 2015 and the sites classified using the proposed method. The mean HVSR curves were re-calculated for three site classes and compared with those from KiK-net data. It was found that both the peak period and the amplitude were similar for the mean HVSR curves derived from NSMONS classification results and KiK-net borehole data, implying the effectiveness of the proposed method in identifying different site classes. The classification results have good agreement with site classes

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2012-12-01

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

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

    International Nuclear Information System (INIS)

    Teimoorinia, H.

    2012-01-01

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

  6. Classification of real farm conditions Iberian pigs according to the feeding regime with multivariate models developed by using fatty acids composition or NIR spectral data

    Directory of Open Access Journals (Sweden)

    De Pedro, Emiliano

    2009-07-01

    Full Text Available Multivariate Classification models to classify real farm conditions Iberian pigs, according to the feeding regime were developed by using fatty acids composition or NIR spectral data of liquid fat samples. A total of 121 subcutaneous fat samples were taken from Iberian pigs carcasses belonging to 5 batches reared under different feeding systems. Once the liquid sample was extracted from each subcutaneous fat sample, it was determined the percentage of 11 fatty acids (C14:0, C16:0, C16:1, C17:0, C17:1, C18:0, C18:1, C18:2, C18:3, C20:0 and C20:1. At the same time, Near Infrared (NIR spectrum of each liquid sample was obtained. Linear Discriminant Analysis (LDA was considered as pattern recognition method to develop the multivariate models. Classification errors of the LDA models generated by using NIR spectral data were 0.0% and 1.7% for the model generated by using fatty acids composition. Results confirm the possibility to discriminate Iberian pig liquid samples from animals reared under different feeding regimes on real farm conditions by using NIR spectral data or fatty acids composition. Classification error obtained using models generated from NIR spectral data were lower than those obtained in models based on fatty acids composition.Se han desarrollado modelos multivariantes, generados a partir de la composición en ácidos grasos o datos espectrales NIR, para clasificar según el régimen alimenticio cerdos Ibéricos producidos bajo condiciones no experimentales. Se han empleado 121 muestras de grasa líquida procedentes de grasa subcutánea de canales de cerdos Ibéricos pertenecientes a 5 partidas con regímenes alimenticios diferentes. A dichas muestras líquidas se les determinó el contenido en 11 ácidos grasos (C14:0, C16:0, C16:1, C17:0, C17:1, C18:0, C18:1, C18:2, C18:3, C20:0 and C20:1 y se obtuvo su espectro NIR. Los modelos de clasificación multivariantes se desarrollaron mediante Análisis Discriminante Lineal. Dichos

  7. High throughput assessment of cells and tissues: Bayesian classification of spectral metrics from infrared vibrational spectroscopic imaging data.

    Science.gov (United States)

    Bhargava, Rohit; Fernandez, Daniel C; Hewitt, Stephen M; Levin, Ira W

    2006-07-01

    Vibrational spectroscopy allows a visualization of tissue constituents based on intrinsic chemical composition and provides a potential route to obtaining diagnostic markers of diseases. Characterizations utilizing infrared vibrational spectroscopy, in particular, are conventionally low throughput in data acquisition, generally lacking in spatial resolution with the resulting data requiring intensive numerical computations to extract information. These factors impair the ability of infrared spectroscopic measurements to represent accurately the spatial heterogeneity in tissue, to incorporate robustly the diversity introduced by patient cohorts or preparative artifacts and to validate developed protocols in large population studies. In this manuscript, we demonstrate a combination of Fourier transform infrared (FTIR) spectroscopic imaging, tissue microarrays (TMAs) and fast numerical analysis as a paradigm for the rapid analysis, development and validation of high throughput spectroscopic characterization protocols. We provide an extended description of the data treatment algorithm and a discussion of various factors that may influence decision-making using this approach. Finally, a number of prostate tissue biopsies, arranged in an array modality, are employed to examine the efficacy of this approach in histologic recognition of epithelial cell polarization in patients displaying a variety of normal, malignant and hyperplastic conditions. An index of epithelial cell polarization, derived from a combined spectral and morphological analysis, is determined to be a potentially useful diagnostic marker.

  8. The Application of Spectral Analysis of Surface Wave (SASW) Method as a New Rock Mass Classification Technique in Engineering Geology

    International Nuclear Information System (INIS)

    Abdul Rahim Samsuddin; Abdul Ghani Rafek; Umar Hamzah; Suharsono; Khairul Anuar Mohd Nayan

    2008-01-01

    Spectral analysis of surface waves (SASW) is a seismic method that uses the dispersive characteristics of Rayleigh waves propagating through layered material to evaluate S-wave velocity profile. The SASW is an in situ non intrusive method for geotechnical site characterization which is cost effective as compared to the conventional drilling method. In this study, a total of 20 stations from 13 sites were selected. A software (WINSASW 2.0) was used for the inversion process to produce S-wave velocity versus depth profiles. These profiles were then separately analyzed in relation to several engineering rock mass geological parameters such as stiffness, rock quality designation (RQD), anisotropy and the excavability properties. The analysis of the SASW data was based on the assumption that the rock mass is an isotropic homogeneous material with various intensity of discontinuity which influenced the velocity of surface wave propagation within the rock mass. Measurement of dynamic soil properties was carried out employing the shear wave velocities and the N values of the Standard Penetration Test (N SPT ) from borehole data. A new linear equation V s = 4.44 N SPT + 213.84 which relates S-wave and N SPT was deduced. An empirical equation is also proposed to calculate Rock Quality Designation (RQD) values based on S-wave velocity derived from SASW and that of ultrasonic tests. The result of this equation was found to be less than 10% in comparison to the RQD obtained from actual borehole data. An isotropic analysis of the rock mass was carried out using S-wave velocities derived from SASW measurements in four directions. The plots of S-wave - ultrasonic velocity ratio versus ultrasonic velocity were used to evaluate the excavability properties of rock mass. Five classes of rock mass excavability curves were finally proposed in relation to easy digging, easy ripping, hard ripping, hydraulic breaking and blasting. (author)

  9. Students Collaborating to Undertake Tracking Efforts for Sturgeon(SCUTES)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Students Collaborating to Undertake Tracking Efforts for Sturgeon (SCUTES) is a collaboration between NOAA Fisheries, sturgeon researchers, and teachers/educators in...

  10. The IACOB project. V. Spectroscopic parameters of the O-type stars in the modern grid of standards for spectral classification

    Science.gov (United States)

    Holgado, G.; Simón-Díaz, S.; Barbá, R. H.; Puls, J.; Herrero, A.; Castro, N.; Garcia, M.; Maíz Apellániz, J.; Negueruela, I.; Sabín-Sanjulián, C.

    2018-06-01

    Context. The IACOB and OWN surveys are two ambitious, complementary observational projects which have made available a large multi-epoch spectroscopic database of optical high resolution spectra of Galactic massive O-type stars. Aims: Our aim is to study the full sample of (more than 350) O stars surveyed by the IACOB and OWN projects. As a first step towards this aim, we have performed the quantitative spectroscopic analysis of a subsample of 128 stars included in the modern grid of O-type standards for spectral classification. The sample comprises stars with spectral types in the range O3-O9.7 and covers all luminosity classes. Methods: We used the semi-automatized IACOB-BROAD and IACOB-GBAT/FASTWIND tools to determine the complete set of spectroscopic parameters that can be obtained from the optical spectrum of O-type stars. A quality flag was assigned to the outcome of the IACOB-GBAT/FASTWIND analysis for each star, based on a visual evaluation of how the synthetic spectrum of the best fitting FASTWIND model reproduces the observed spectrum. We also benefitted from the multi-epoch character of the IACOB and OWN surveys to perform a spectroscopic variability study of the complete sample, providing two different flags for each star accounting for spectroscopic binarity as well as variability of the main wind diagnostic lines. Results: We obtain - for the first time in a homogeneous and complete manner - the full set of spectroscopic parameters of the "anchors" of the spectral classification system in the O star domain. We provide a general overview of the stellar and wind parameters of this reference sample, as well as updated recipes for the SpT-Teff and SpT-log g calibrations for Galactic O-type stars. We also propose a distance-independent test for the wind-momentum luminosity relationship. We evaluate the reliability of our semi-automatized analysis strategy using a subsample of 40 stars extensively studied in the literature, and find a fairly good agreement

  11. 31 CFR 248.4 - Undertaking of indemnity.

    Science.gov (United States)

    2010-07-01

    ... 31 Money and Finance: Treasury 2 2010-07-01 2010-07-01 false Undertaking of indemnity. 248.4 Section 248.4 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued) FISCAL... in the circumstances set forth below, a corporate surety authorized by the Secretary of the Treasury...

  12. Using an undertaker's data to assess changing patterns of mortality ...

    African Journals Online (AJOL)

    Key informant interviews were done to support the undertaker's data and determine how families bear the burden of burying deceased relatives. Despite a disproportionate increase in deaths in certain age categories and evidence of worsening poverty, funerals remain large and elaborate affairs. Keywords: AIDS, burial ...

  13. Spectral matching techniques (SMTs) and automated cropland classification algorithms (ACCAs) for mapping croplands of Australia using MODIS 250-m time-series (2000–2015) data

    Science.gov (United States)

    Teluguntla, Pardhasaradhi G.; Thenkabail, Prasad S.; Xiong, Jun N.; Gumma, Murali Krishna; Congalton, Russell G.; Oliphant, Adam; Poehnelt, Justin; Yadav, Kamini; Rao, Mahesh N.; Massey, Richard

    2017-01-01

    Mapping croplands, including fallow areas, are an important measure to determine the quantity of food that is produced, where they are produced, and when they are produced (e.g. seasonality). Furthermore, croplands are known as water guzzlers by consuming anywhere between 70% and 90% of all human water use globally. Given these facts and the increase in global population to nearly 10 billion by the year 2050, the need for routine, rapid, and automated cropland mapping year-after-year and/or season-after-season is of great importance. The overarching goal of this study was to generate standard and routine cropland products, year-after-year, over very large areas through the use of two novel methods: (a) quantitative spectral matching techniques (QSMTs) applied at continental level and (b) rule-based Automated Cropland Classification Algorithm (ACCA) with the ability to hind-cast, now-cast, and future-cast. Australia was chosen for the study given its extensive croplands, rich history of agriculture, and yet nonexistent routine yearly generated cropland products using multi-temporal remote sensing. This research produced three distinct cropland products using Moderate Resolution Imaging Spectroradiometer (MODIS) 250-m normalized difference vegetation index 16-day composite time-series data for 16 years: 2000 through 2015. The products consisted of: (1) cropland extent/areas versus cropland fallow areas, (2) irrigated versus rainfed croplands, and (3) cropping intensities: single, double, and continuous cropping. An accurate reference cropland product (RCP) for the year 2014 (RCP2014) produced using QSMT was used as a knowledge base to train and develop the ACCA algorithm that was then applied to the MODIS time-series data for the years 2000–2015. A comparison between the ACCA-derived cropland products (ACPs) for the year 2014 (ACP2014) versus RCP2014 provided an overall agreement of 89.4% (kappa = 0.814) with six classes: (a) producer’s accuracies varying

  14. Non-financial reporting, CSR frameworks and groups of undertakings

    DEFF Research Database (Denmark)

    Szabó, Dániel Gergely; Sørensen, Karsten Engsig

    2017-01-01

    The recently adopted Directive on non-financial reporting (Directive 2014/95/EU) and several CSR frameworks are based on the assumption that groups of undertakings adopt, report and implement one group policy. This is a very important but also rather unique approach to groups. This article first...... shows how the Directive as well as a few CSR frameworks intend to be implemented in groups and next it discusses potential barriers to do so. Even though company law does not always facilitate the adoption, communication and implementation of a group CSR policy, it may not in practice be a problem to do...... so. However, it is shown that doing so may have unforeseen consequences for the parent undertaking. To avoid them, it is recommended to make adjustments to the implementation of the group policy....

  15. Original article Personality determinants of motivation to undertake vocational training

    Directory of Open Access Journals (Sweden)

    Dorota Godlewska-Werner

    2014-05-01

    Full Text Available Background Recently, at a time of frequent changes in the economic and socio-economic circumstances, knowledge acquired in the course of formal education is insufficient. Especially, the education system is still criticized for a lack of flexibility and strong resistance to change. Therefore, regular participation in various forms of training is required. Employee education and training are becoming an optimal answer to complex business challenges. The aim of this study was to determine which personality traits are responsible for the strength of motivation to undertake vocational training and other educational forms. Participants and procedure The study included 104 staff members of Polish companies (60 women and 44 men. The study used Cattell’s 16 PF Questionnaire and the scales of readiness to undertake training and further education as a measure of the strength of motivation (Kawecka, Łaguna & Tabor, 2010. Results The study showed that openness to change and tension (primary traits had the greatest impact on the intention and planning to take vocational training. Additionally, the intention and planning to take vocational training were found to be associated with mindedness, independence, self-control, and anxiety (secondary traits. Such traits as rule-consciousness [G], social-boldness [H], abstractedness [M], and apprehension [O] (primary traits, were important in some aspects, which could constitute a background for further research and discussion of the results. Conclusions The obtained results lead to the conclusion that some of the individual differences in personality determine the motivation to undertake vocational training.

  16. Organization of multinational undertakings in the nuclear field

    International Nuclear Information System (INIS)

    Yajima, Masayuki

    1982-01-01

    Various proposals have been put forward to establish multinational undertakings for enrichment, fuel fabrication, reprocessing, spent fuel storage and waste management. The purpose of this paper is to investigate the legal, institutional framework aspects of multinational undertakings in the field of nuclear fuel cycle. The selection of the appropriate bodies representing the interest of participating countries would largely depend on the object or role of multinational undertakings. Regarding the principle of formation, URENCO is a much informative model of formation, which distinguishes the equity participation at national level and multinational level. The allocation of service between equity participants and non-equity participants depends on the objective of establishing business. Some priority in service allocation should be given to equity participants, and the participants having non-proliferation objective may require service allocation to avoid proliferation risk. The degree of achieving non-proliferation goal is related to the scope of participation. The experience in the field of nuclear energy seems to suggest that the concept of two-tiered decisionmaking structure is generally accepted. Various legal instruments appropriate to constitute multinational fuel cycle arrangement were examined, referring to the precedents and experience. (Kako, I.)

  17. Changes in the functions of undertakings in electricity supply

    International Nuclear Information System (INIS)

    Oberlack, H.W.

    1976-01-01

    For the electricity supply industry also it is necessary, by means of more intensive publicity work, to achieve the general realisation that neither new laws nor intervention of the state are required for dealing in the interests of the consumer with the problems arising, from great changes in all fields of business enterprise. It is more important for the electricity supply undertakings (EVU), by means of executive power and the administration of justice, to be put a position to carry out in the most efficient manner the functions entrusted to them by the Federal Government under the Power Supply Law and the energy programme. (orig.) [de

  18. A multi-tier higher order Conditional Random Field for land cover classification of multi-temporal multi-spectral Landsat imagery

    CSIR Research Space (South Africa)

    Salmon, BP

    2015-07-01

    Full Text Available In this paper the authors present a 2-tier higher order Conditional Random Field which is used for land cover classification. The Conditional Random Field is based on probabilistic messages being passed along a graph to compute efficiently...

  19. An undertaking planning game for the electricity supply industry

    International Nuclear Information System (INIS)

    Troescher, H.

    1977-01-01

    Planning games have been found satisfactory in many field in political and economic life. In particular the more convenient access to electronic calculators has made a contrinution to their wider use. It is therefore surprising that the first planning game which has become known for the electricity supply industry was first published in the year 1975. This is the planning game for the Bernischen Kraftwerke AG, which is based on a simplified model of a small electricity supply undertaking (EVU). This planning game was adapted in the RWE to the conditions in larger EVU and a few additional model components were added. Besides the general points of view on planning games for EVU the author deals with the extended planning game which is termed in the article PEW. (orig.) [de

  20. Supporting students undertaking the Specialist Practitioner Qualification in District Nursing.

    Science.gov (United States)

    Ginger, Tracey; Ritchie, Georgina

    2017-11-02

    The ever-evolving role of the Specialist Practitioner Qualified District Nurse (SPQDN) presents an increasing number of challenges for Practice Teachers and mentors in preparing SPQDN students for the elevated level clinical and transformational leadership necessary to ensure high-quality patient care. The daily challenges of clinical practice within the community nursing setting in addition to undertaking educational interventions in the clinical arena demand that a structured approach to supervision and mentorship is crucial. Employing learning plans to assess individual students learning needs, prepare plans for educational developments and interventions and evaluate a student's progress can be a helpful tool in aiding the learning journey for both the SPQDN student and Practice Teacher or mentor. This article examines how and why a structured learning plan may be used in supporting learning and competency in achieving the necessary level of practice to meet the requirements of the SPQDN.

  1. Absorption spectroscopy and multi-angle scattering measurements in the visible spectral range for the geographic classification of Italian exravirgin olive oils

    Science.gov (United States)

    Mignani, Anna G.; Ciaccheri, Leonardo; Cimato, Antonio; Sani, Graziano; Smith, Peter R.

    2004-03-01

    Absorption spectroscopy and multi-angle scattering measurements in the visible spectral range are innovately used to analyze samples of extra virgin olive oils coming from selected areas of Tuscany, a famous Italian region for the production of extra virgin olive oil. The measured spectra are processed by means of the Principal Component Analysis method, so as to create a 3D map capable of clustering the Tuscan oils within the wider area of Italian extra virgin olive oils.

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

    Science.gov (United States)

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

    2017-09-01

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

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

    Science.gov (United States)

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

    2017-09-05

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

  4. Combination of support vector machine, artificial neural network and random forest for improving the classification of convective and stratiform rain using spectral features of SEVIRI data

    Science.gov (United States)

    Lazri, Mourad; Ameur, Soltane

    2018-05-01

    A model combining three classifiers, namely Support vector machine, Artificial neural network and Random forest (SAR) is designed for improving the classification of convective and stratiform rain. This model (SAR model) has been trained and then tested on a datasets derived from MSG-SEVIRI (Meteosat Second Generation-Spinning Enhanced Visible and Infrared Imager). Well-classified, mid-classified and misclassified pixels are determined from the combination of three classifiers. Mid-classified and misclassified pixels that are considered unreliable pixels are reclassified by using a novel training of the developed scheme. In this novel training, only the input data corresponding to the pixels in question to are used. This whole process is repeated a second time and applied to mid-classified and misclassified pixels separately. Learning and validation of the developed scheme are realized against co-located data observed by ground radar. The developed scheme outperformed different classifiers used separately and reached 97.40% of overall accuracy of classification.

  5. Undertaking qualitative health research in social virtual worlds.

    Science.gov (United States)

    McElhinney, Evelyn; Cheater, Francine M; Kidd, Lisa

    2014-06-01

    This paper discusses the methodological challenges of using the 3D social virtual world Second Life for research and offers some solutions on a range of research issues including research ethics committee approval, gaining consent, recruitment of sample, data collection and engagement with 'in - world culture'. The attraction of social virtual worlds to researchers is their ability to mimic the physical world, as they, are seen as 'places' where people have a feeling of presence (being there) and social presence (being there with others) through the use of a 'customisable' avatar (digital self-representation). Emerging research demonstrating the persuasive nature of avatars on health behaviours through virtual worlds, online games and the 3D web has increased the use of and interest in these areas for delivering health information, advice and support. However, conducting research can be challenging in a 3D world where people are represented as anonymous avatars in an environment unlike any other online media. 25 semi-structured interviews were conducted in Second Life from September 2011-June 2012. Nurses wishing to undertake research in social virtual worlds should spend time in-world to acquire technical skills and gain an understanding of the culture of the world. Our experience of an interview-based study in virtual worlds indicates that researchers require several virtual world technical skills to create innovative tools to recruit, gain consent and collect data and an understanding of in-world culture, language and social norms to increase the chances of successful research. © 2013 John Wiley & Sons Ltd.

  6. Adinkras, Dessins, Origami, and Supersymmetry Spectral Triples

    OpenAIRE

    Marcolli, Matilde; Zolman, Nick

    2016-01-01

    We investigate the spectral geometry and spectral action functionals associated to 1D Supersymmetry Algebras, using the classification of these superalgebras in terms of Adinkra graphs and the construction of associated dessin d'enfant and origami curves. The resulting spectral action functionals are computed in terms of the Selberg (super) trace formula.

  7. Temporal-Spectral Characterization and Classification of Marine Mammal Vocalizations and Diesel-Electric Ships Radiated Sound over Continental Shelf Scale Regions with Coherent Hydrophone Array Measurements

    Science.gov (United States)

    Huang, Wei

    The passive ocean acoustic waveguide remote sensing (POAWRS) technology is capable of monitoring a large variety of underwater sound sources over instantaneous wide areas spanning continental-shelf scale regions. POAWRS uses a large-aperture densely-sampled coherent hydrophone array to significantly enhance the signal-to-noise ratio via beamforming, enabling detection of sound sources roughly two-orders of magnitude more distant in range than that possible with a single hydrophone. The sound sources detected by POAWRS include ocean biology, geophysical processes, and man-made activities. POAWRS provides detection, bearing-time estimation, localization, and classification of underwater sound sources. The volume of underwater sounds detected by POAWRS is immense, typically exceeding a million unique signal detections per day, in the 10-4000 Hz frequency range, making it a tremendously challenging task to distinguish and categorize the various sound sources present in a given region. Here we develop various approaches for characterizing and clustering the signal detections for various subsets of data acquired using the POAWRS technology. The approaches include pitch tracking of the dominant signal detections, time-frequency feature extraction, clustering and categorization methods. These approaches are essential for automatic processing and enhancing the efficiency and accuracy of POAWRS data analysis. The results of the signal detection, clustering and classification analysis are required for further POAWRS processing, including localization and tracking of a large number of oceanic sound sources. Here the POAWRS detection, localization and clustering approaches are applied to analyze and elucidate the vocalization behavior of humpback, sperm and fin whales in the New England continental shelf and slope, including the Gulf of Maine from data acquired using coherent hydrophone arrays. The POAWRS technology can also be applied for monitoring ocean vehicles. Here the

  8. The exclusion of 'public undertakings' from the re-use of public sector information regime

    NARCIS (Netherlands)

    Ricolfi, M.; Drexl, J.; van Eechoud, M.; Salmeron, M.; Sappa, C.; Tziavos, P.; Valero, J.; Pavoni, F.; Patrito, P.

    2011-01-01

    Should public undertakings be covered by the PSI Directive? The definitions of public sector bodies and bodies governed by public law, to which the PSI Directive applies, are currently taken from the public procurement Directives and public undertakings are not covered by these definitions. Should

  9. 12 CFR 980.2 - Limitation on Bank authority to undertake new business activities.

    Science.gov (United States)

    2010-01-01

    ... business activities. 980.2 Section 980.2 Banks and Banking FEDERAL HOUSING FINANCE BOARD NEW FEDERAL HOME LOAN BANK ACTIVITIES NEW BUSINESS ACTIVITIES § 980.2 Limitation on Bank authority to undertake new business activities. No Bank shall undertake any new business activity except in accordance with the...

  10. 20 CFR 703.304 - Filing of Agreement and Undertaking; deposit of security.

    Science.gov (United States)

    2010-04-01

    ... the amount fixed by the Office, or deposit negotiable securities under §§ 703.306 and 703.307 in that... 20 Employees' Benefits 3 2010-04-01 2010-04-01 false Filing of Agreement and Undertaking; deposit... REGULATIONS Authorization of Self-Insurers § 703.304 Filing of Agreement and Undertaking; deposit of security...

  11. Classifying Classifications

    DEFF Research Database (Denmark)

    Debus, Michael S.

    2017-01-01

    This paper critically analyzes seventeen game classifications. The classifications were chosen on the basis of diversity, ranging from pre-digital classification (e.g. Murray 1952), over game studies classifications (e.g. Elverdam & Aarseth 2007) to classifications of drinking games (e.g. LaBrie et...... al. 2013). The analysis aims at three goals: The classifications’ internal consistency, the abstraction of classification criteria and the identification of differences in classification across fields and/or time. Especially the abstraction of classification criteria can be used in future endeavors...... into the topic of game classifications....

  12. Stellar Spectral Classification with Locality Preserving Projections ...

    Indian Academy of Sciences (India)

    School of Computer and Control Engineering, North University of China,. Taiyuan 030051 ... (2013) was used to mine the association rules of a stellar ... of the graph, we then compute a transformation matrix which maps the data points to.

  13. Spectral stratigraphy

    Science.gov (United States)

    Lang, Harold R.

    1991-01-01

    A new approach to stratigraphic analysis is described which uses photogeologic and spectral interpretation of multispectral remote sensing data combined with topographic information to determine the attitude, thickness, and lithology of strata exposed at the surface. The new stratigraphic procedure is illustrated by examples in the literature. The published results demonstrate the potential of spectral stratigraphy for mapping strata, determining dip and strike, measuring and correlating stratigraphic sequences, defining lithofacies, mapping biofacies, and interpreting geological structures.

  14. Land Cover Classification in a Complex Urban-Rural Landscape with Quickbird Imagery

    OpenAIRE

    Moran, Emilio Federico.

    2010-01-01

    High spatial resolution images have been increasingly used for urban land use/cover classification, but the high spectral variation within the same land cover, the spectral confusion among different land covers, and the shadow problem often lead to poor classification performance based on the traditional per-pixel spectral-based classification methods. This paper explores approaches to improve urban land cover classification with Quickbird imagery. Traditional per-pixel spectral-based supervi...

  15. CONSIDERATIONS ON THE RULES ON COMPETITION GOVERNING UNDERTAKINGS IN THE EUROPEAN UNION

    Directory of Open Access Journals (Sweden)

    Vlad – Teodor Florea

    2014-11-01

    Full Text Available This study concerns the general rules on competition between undertakings in the EU. The author paid attention primarly to matters on the prohibition of agreements that aim to distort or impair competition on the internal market. Moreover, he examined in detail the matter concerning the regulation and interdiction of the abuse of a dominant position. The work also reviews doctrinal opinions, as well as the jurisprudential solutions in the area. The author’s concern to summarize and develop the conditions for the implementation of each of the two legal mechanisms is worth noting: the prohibition of agreements between undertakings and the abuse of a dominant position. The essential considerations taken into account by the Court of Justice of the European Union in settling a case whose subject consisted of assessing the manner in which an undertaking reflected on competition on the internal market were selected at the end of the work.

  16. Metallicity and the spectral energy distribution and spectral types of dwarf O-stars

    NARCIS (Netherlands)

    Mokiem, MR; Martin-Hernandez, NL; Lenorzer, A; de Koter, A; Tielens, AGGA

    We present a systematic study of the effect of metallicity on the stellar spectral energy distribution (SED) of 0 main sequence (dwarf) stars, focussing on the hydrogen and helium ionizing continua, and on the optical and near-IR lines used for spectral classification. The spectra are based on

  17. Metallicity and the spectral energy distribution and spectral types of dwarf O-stars

    NARCIS (Netherlands)

    Mokiem, M.R.; Martín-Hernández, N.L.; Lenorzer, A.; de Koter, A.; Tielens, A.G.G.M.

    2004-01-01

    We present a systematic study of the effect of metallicity on the stellar spectral energy distribution (SED) of O main sequence (dwarf) stars, focussing on the hydrogen and helium ionizing continua, and on the optical and near-IR lines used for spectral classification. The spectra are based on

  18. Assisted reproductive technologies in Ghana : Transnational undertakings, local practices and ‘more affordable’ IVF

    NARCIS (Netherlands)

    Gerrits, T.

    The article sketches the origins and development of IVF in Ghana as a highly transnational undertaking. Movements are from and to Africa, involving human beings (providers and users), and also refer to other entities such as technologies, skills and knowledge. None of these movements are paid for

  19. The Costs and Benefits of Undertaking Adult Education Courses from the Perspective of the Individual

    Science.gov (United States)

    AONTAS The National Adult Learning Organisation, 2009

    2009-01-01

    The aim of this study is to examine the costs and benefits of undertaking adult education courses from the perspective of the individual, using three different case studies. This will give a snapshot of the benefits and the types of costs incurred by three adult learners. Three individuals were contacted by Aontas and were asked if they would be…

  20. 20 CFR 703.205 - Filing of Agreement and Undertaking; deposit of security.

    Science.gov (United States)

    2010-04-01

    ...— (1) Deposit with the Branch indemnity bonds or letters of credit in the amount fixed by the Office... and payable from the proceeds of the deposited security; (b) Give security in the amount fixed in the... 20 Employees' Benefits 3 2010-04-01 2010-04-01 false Filing of Agreement and Undertaking; deposit...

  1. Accuracy assessment between different image classification ...

    African Journals Online (AJOL)

    What image classification does is to assign pixel to a particular land cover and land use type that has the most similar spectral signature. However, there are possibilities that different methods or algorithms of image classification of the same data set could produce appreciable variant results in the sizes, shapes and areas of ...

  2. The qualitative interview and challenges for clinicians undertaking research: a personal reflection.

    Science.gov (United States)

    Fisher, Karin

    2011-01-01

    Drawing on my doctoral experience the aim of this article is to present my transition from practitioner to novice researcher and the challenges I encountered when undertaking qualitative in-depth interviews. The contents of my research diary were coded for words, sentences and paragraphs and were then grouped into themes and subsequently organised into concepts and categories. The analysis identified one core category: 'changing states: learning to become a researcher'. The related categories included 'guessing responses', 'confusing boundaries' and 'revealing hidden concepts'. These concepts provide a description of how I learnt to become a researcher and became a changed state. The paper provides practitioners with practical examples of my transition from practitioner to novice researcher. I offer some tips for practitioners who wish to undertake research in their clinical role.

  3. [Environmental licensing of major undertakings: possible connection between health and environment].

    Science.gov (United States)

    Silveira, Missifany; Araújo Neto, Mário Diniz de

    2014-09-01

    The prospect of multidisciplinary assessment that considers the environmental impacts on the health of the population during the implementation of potentially polluting projects is incipient in Brazil. Considering the scenario of major undertakings in the country, broadening the outlook on the health and environment relationship based on social and economic development processes striving for environmentally sustainable projects is a key strategy. This article examines the debate on the relationship between the current development model, the risks, the environment and health and discusses the importance of the participation of the health sector in the environmental licensing procedures, which is the instrument of the Environmental Impact Assessment (EIA). Seeking to create more environmentally and socially sustainable territories, the health sector has been looking for opportunities to participate in the licensing processes of major undertakings from the EIA standpoint. Results of research conducted by the Ministry of Health have demonstrated the form of participation in these processes, highlighting the strengths and weaknesses that favor or hinder the increase of preventive actions in public health in the implementation of major undertakings in Brazil.

  4. Landsat sattelite multi-spectral image classification of land cover and land use changes for GIS-based urbanization analysis in irrigation districts of lower Rio Grande Valley of Texas

    Science.gov (United States)

    The Lower Rio Grande Valley in the south of Texas is experiencing rapid increase of population to bring up urban growth that continues influencing on the irrigation districts in the region. This study evaluated the Landsat satellite multi-spectral imagery to provide information for GIS-based urbaniz...

  5. EU program fuel cells in 2012 - FCH JU Fuel Cell and Hydrogen Joint Undertaking; EU-program braensleceller 2012 - FCH JU Fuel Cell and Hydrogen Joint Undertaking

    Energy Technology Data Exchange (ETDEWEB)

    Ridell, Bengt

    2013-03-15

    An EU activity in fuel cell and hydrogen field are gathered since 2008 in a so called JU, Joint Undertaking, or as it is also referred to as JTI Joint Technology Initiative. The program will run 2008 - 2013 and covers in total 940 MEUR of which the EU Commission is funding 470 MEUR. The activities of the FCH JU are governed by a Governing Board which has 12 members, five from the Commission, one of the research group and 5 from the Industrial Group. The current agreement for the FCH JU / JTI is coming to an end, and the sixth and final call was released in January 2013 with the deadline of 22 May 2013. Funding from the Commission is made through the Seventh Framework Programme FP7, which ends in 2013. Next the Eighth Framework Programme called Horizon 2020 shall continue for the years 2014 - 2020. Five of the six calls are completed. From the four first calls there are 61 projects started which 6 have been completed. From the fifth announcement is further 27 projects selected for negotiation with the Commission and they will start soon. It is now working intensively to plan Horizon 2020. There are plans to continue the new FCH JU but nothing is decided either for this or for the budget for Horizon 2020. If the FCH Joint Undertaking shall continue in its present form as a Joint Undertaking it will require clear long-term commitments from the private sector and also from the Member States. Another issue is that the long-term research should also get space it has not been the case in the present FCH JU. There are several Swedish participants in the projects and in the working groups of the program. There are Swedish participants in 11 of the 68 projects launched so far. It is in the areas of Stationary systems, Transportation and Early Markets. Project manager for the project FCGEN is Volvo Technology AB. FCH JU has its own website, www.fch-ju.eu, which opened in 2010 when the organization of the program was taken over from the Commission to permanent organisation

  6. Classification of IRAS asteroids

    International Nuclear Information System (INIS)

    Tedesco, E.F.; Matson, D.L.; Veeder, G.J.

    1989-01-01

    Albedos and spectral reflectances are essential for classifying asteroids. For example, classes E, M and P are indistinguishable without albedo data. Colorometric data are available for about 1000 asteroids but, prior to IRAS, albedo data was available for only about 200. IRAS broke this bottleneck by providing albedo data on nearly 2000 asteroids. Hence, excepting absolute magnitudes, the albedo and size are now the most common asteroid physical parameters known. In this chapter the authors present the results of analyses of IRAS-derived asteroid albedos, discuss their application to asteroid classification, and mention several studies which might be done to exploit further this data set

  7. Potential of Spectral Reflectance as Postharvest Classification Tool for Flower Development of Calla Lily (Zantedeschia aethiopica (L. Spreng. Potencial de la Reflectancia Espectral como Herramienta para la Clasificación Poscosecha del Desarrollo Floral en Cala (Zantedeschia aethiopica (L. Spreng.

    Directory of Open Access Journals (Sweden)

    Antonio J . Steidle Neto

    2009-12-01

    Full Text Available Unsuitable postharvest management is one of the most serious problems that floriculture has to face. An option for reducing postharvest losses is to use automatic systems for flower sorting and classification, which yield consistent results, reduce costs and speed up these tasks. The objective of this work was show the potential of spectral reflectance to distinguish different postharvest development stages of calla lily flowers, Zantedeschia aethiopica (L. Spreng., aiming the use of this technology within automatic systems for flower classification. The measuring equipment was a spectrometer connected to a portable computer and configured for reflectance data acquisition in the 400 to 1000 nm range. Based on the results, it was verified a differentiation between the spectral reflectance curves of calla lily flowers, with gradual decreases on the measured values according to the increase of the senescence stages. Thus, the spectral reflectance has potential to be used in the development of automatic systems for postharvest classification of calla lily flowers.El manejo poscosecha inadecuado es uno de los problemas más serios que la floricultura tiene que enfrentar. Una opción para reducir las pérdidas poscosecha es emplear sistemas automáticos para ordenar y clasificar las flores, los cuales permiten resultados consistentes, reducen gastos y aceleran estas tareas. El objetivo de este trabajo fue demostrar el potencial de la reflectancia espectral para discriminar las diferentes fases de desarrollo poscosecha de flores de cala (Zantedeschia aethiopica [L.] Spreng., visando el uso de esta tecnología en sistemas automáticos para la clasificación de flores. El equipo de medición fue un espectrómetro conectado a un computador portátil y configurado para la adquisición de datos de reflectancia comprendidos en la región espectral de 400 a 1000 nm. Con base en los resultados, se constató una diferencia entre las curvas de reflectancia

  8. Who should be undertaking population-based surveys in humanitarian emergencies?

    Directory of Open Access Journals (Sweden)

    Spiegel Paul B

    2007-06-01

    Full Text Available Abstract Background Timely and accurate data are necessary to prioritise and effectively respond to humanitarian emergencies. 30-by-30 cluster surveys are commonly used in humanitarian emergencies because of their purported simplicity and reasonable validity and precision. Agencies have increasingly used 30-by-30 cluster surveys to undertake measurements beyond immunisation coverage and nutritional status. Methodological errors in cluster surveys have likely occurred for decades in humanitarian emergencies, often with unknown or unevaluated consequences. Discussion Most surveys in humanitarian emergencies are done by non-governmental organisations (NGOs. Some undertake good quality surveys while others have an already overburdened staff with limited epidemiological skills. Manuals explaining cluster survey methodology are available and in use. However, it is debatable as to whether using standardised, 'cookbook' survey methodologies are appropriate. Coordination of surveys is often lacking. If a coordinating body is established, as recommended, it is questionable whether it should have sole authority to release surveys due to insufficient independence. Donors should provide sufficient funding for personnel, training, and survey implementation, and not solely for direct programme implementation. Summary A dedicated corps of trained epidemiologists needs to be identified and made available to undertake surveys in humanitarian emergencies. NGOs in the field may need to form an alliance with certain specialised agencies or pool technically capable personnel. If NGOs continue to do surveys by themselves, a simple training manual with sample survey questionnaires, methodology, standardised files for data entry and analysis, and manual for interpretation should be developed and modified locally for each situation. At the beginning of an emergency, a central coordinating body should be established that has sufficient authority to set survey standards

  9. An investigation of nurse educator's perceptions and experiences of undertaking clinical practice.

    Science.gov (United States)

    Williams, Angela; Taylor, Cathy

    2008-11-01

    Educational policy (DOH, 1999. Making a difference: strengthening the nursing, midwifery and health visiting contribution to health and healthcare. Department of Health, London; UKCC, 1999. Fitness for Practice. United Kingdom Central Council for Nursing, Midwifery and Health Visiting, London; Nursing and Midwifery Council, 2006. Standards to support learning and assessment in practice. Nursing and Midwifery Council, London) and current nursing literature (Griscti, O., Jacono, B., Jacono, J., 2005. The nurse educator's clinical role. Journal of Advanced Nursing 50 (1), 84-92; Owen, S., Ferguson, K., Baguley, I., 2005. The clinical activity of mental health nurse lecturers. Journal of Psychiatric and Mental Health Nursing 12, 310-316), place increasing emphasis on nurse educators undertaking clinical practice to facilitate their clinical confidence and competence. This study investigated nurse educators' perceptions and experiences of undertaking clinical practice. A qualitative design and descriptive, exploratory approach were used. A purposive sample of 11 nurse educators in one nursing department, took part in two focus group interviews, one with 5 and the other with 6 respondents, to identify and discuss their perceptions and experiences of undertaking clinical practice. A process of thematic content analysis revealed three broad themes relating to the meaning and importance of clinical practice, perceived benefits and barriers which are examined and discussed. The paper concludes that despite policy recommendations, barriers highlighted in this study such as insufficient time, heavy workload and a lack of valuing of the clinical role have been raised over the past few decades. The effect of undertaking clinical practice, particularly on the quality of teaching is argued to be valuable armoury in the battle to secure sufficient resources to support engagement in clinical practice. Financial and organisational commitment; valuing of clinical practice and research

  10. Undertaking and writing research that is important, targeted, and the best you can do.

    Science.gov (United States)

    McLeod, Sharynne

    2014-04-01

    Conducting and writing research is a privilege. It is a privilege because researchers can change lives through their findings and can influence public knowledge and debate. It is also a privilege because researchers are reliant on the time and goodwill of participants (and colleagues), and research is often underpinned by funding raised by the public, either through taxes or philanthropic donations. This privilege comes with responsibility. Researchers have a responsibility to undertake research that is important, targeted, and of high quality. This editorial aims to inspire, challenge, and bolster the research efforts of individuals and teams.

  11. Training staff to empower people with long-term conditions to undertake self care activities.

    Science.gov (United States)

    Bowler, Mandy

    Self care can help people with long-term conditions take control of their lives. However, their interest and ability to engage with it may fluctuate over the course of an illness and many need support to undertake self care activities. A team of community matrons in NHS South of Tyne and Wear helped to develop and pilot an e-learning tool for staff, to remind them of the importance of self care and give advice on ways to support patients. The tool has since been rolled out to all staff groups.

  12. The development of power generation by electricity supply undertakings and industries in Western Europe

    International Nuclear Information System (INIS)

    Cura, H.

    1998-01-01

    Following the events of recent years - the opening up of the east, efforts to stimulate international competition - the Western European electricity industry is strongly on the move. In spite of the non-uniformity of the electricity supply structures in the individual countries, the trend towards liberalization of the electricity market is characterized by different forms of expression. Against this background, this paper provides a review of the status and prospects of electricity demand developments and of primary energy supply. It considers the consequences which thereby arise for the power plant inventory of electricity supply undertakings and industries. (orig.) [de

  13. Spectral Imaging by Upconversion

    DEFF Research Database (Denmark)

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

    2011-01-01

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

  14. Co-founding ant queens prevent disease by performing prophylactic undertaking behaviour.

    Science.gov (United States)

    Pull, Christopher D; Cremer, Sylvia

    2017-10-13

    Social insects form densely crowded societies in environments with high pathogen loads, but have evolved collective defences that mitigate the impact of disease. However, colony-founding queens lack this protection and suffer high rates of mortality. The impact of pathogens may be exacerbated in species where queens found colonies together, as healthy individuals may contract pathogens from infectious co-founders. Therefore, we tested whether ant queens avoid founding colonies with pathogen-exposed conspecifics and how they might limit disease transmission from infectious individuals. Using Lasius niger queens and a naturally infecting fungal pathogen Metarhizium brunneum, we observed that queens were equally likely to found colonies with another pathogen-exposed or sham-treated queen. However, when one queen died, the surviving individual performed biting, burial and removal of the corpse. These undertaking behaviours were performed prophylactically, i.e. targeted equally towards non-infected and infected corpses, as well as carried out before infected corpses became infectious. Biting and burial reduced the risk of the queens contracting and dying from disease from an infectious corpse of a dead co-foundress. We show that co-founding ant queens express undertaking behaviours that, in mature colonies, are performed exclusively by workers. Such infection avoidance behaviours act before the queens can contract the disease and will therefore improve the overall chance of colony founding success in ant queens.

  15. Reasons why specialist doctors undertake rural outreach services: an Australian cross-sectional study.

    Science.gov (United States)

    O'Sullivan, Belinda G; McGrail, Matthew R; Stoelwinder, Johannes U

    2017-01-07

    The purpose of the study is to explore the reasons why specialist doctors travel to provide regular rural outreach services, and whether reasons relate to (1) salaried or private fee-for-service practice and (2) providing rural outreach services in more remote locations. A national cross-sectional study of specialist doctors from the Medicine in Australia: Balancing Employment and Life (MABEL) survey in 2014 was implemented. Specialists providing rural outreach services self-reported on a 5-point scale their level of agreement with five reasons for participating. Chi-squared analysis tested association between agreement and variables of interest. Of 567 specialists undertaking rural outreach services, reasons for participating include to grow the practice (54%), maintain a regional connection (26%), provide complex healthcare (18%), healthcare for disadvantaged people (12%) and support rural staff (6%). Salaried specialists more commonly participated to grow the practice compared with specialists in fee-for-service practice (68 vs 49%). This reason was also related to travelling further and providing outreach services in outer regional/remote locations. Private fee-for-service specialists more commonly undertook outreach services to provide complex healthcare (22 vs 14%). Specialist doctors undertake rural outreach services for a range of reasons, mainly to complement the growth and diversity of their main practice or maintain a regional connection. Structuring rural outreach around the specialist's main practice is likely to support participation and improve service distribution.

  16. Spectral Decomposition Algorithm (SDA)

    Data.gov (United States)

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

  17. Orthogonal feature selection method. [For preprocessing of man spectral data

    Energy Technology Data Exchange (ETDEWEB)

    Kowalski, B R [Univ. of Washington, Seattle; Bender, C F

    1976-01-01

    A new method of preprocessing spectral data for extraction of molecular structural information is desired. This SELECT method generates orthogonal features that are important for classification purposes and that also retain their identity to the original measurements. A brief introduction to chemical pattern recognition is presented. A brief description of the method and an application to mass spectral data analysis follow. (BLM)

  18. Spectrally based mapping of riverbed composition

    Science.gov (United States)

    Legleiter, Carl; Stegman, Tobin K.; Overstreet, Brandon T.

    2016-01-01

    Remote sensing methods provide an efficient means of characterizing fluvial systems. This study evaluated the potential to map riverbed composition based on in situ and/or remote measurements of reflectance. Field spectra and substrate photos from the Snake River, Wyoming, USA, were used to identify different sediment facies and degrees of algal development and to quantify their optical characteristics. We hypothesized that accounting for the effects of depth and water column attenuation to isolate the reflectance of the streambed would enhance distinctions among bottom types and facilitate substrate classification. A bottom reflectance retrieval algorithm adapted from coastal research yielded realistic spectra for the 450 to 700 nm range; but bottom reflectance-based substrate classifications, generated using a random forest technique, were no more accurate than classifications derived from above-water field spectra. Additional hypothesis testing indicated that a combination of reflectance magnitude (brightness) and indices of spectral shape provided the most accurate riverbed classifications. Convolving field spectra to the response functions of a multispectral satellite and a hyperspectral imaging system did not reduce classification accuracies, implying that high spectral resolution was not essential. Supervised classifications of algal density produced from hyperspectral data and an inferred bottom reflectance image were not highly accurate, but unsupervised classification of the bottom reflectance image revealed distinct spectrally based clusters, suggesting that such an image could provide additional river information. We attribute the failure of bottom reflectance retrieval to yield more reliable substrate maps to a latent correlation between depth and bottom type. Accounting for the effects of depth might have eliminated a key distinction among substrates and thus reduced discriminatory power. Although further, more systematic study across a broader

  19. Building confidence: an exploration of nurses undertaking a postgraduate biological science course.

    Science.gov (United States)

    Van Wissen, Kim; McBride-Henry, Karen

    2010-01-01

    This study aimed to explore the impact of studying biological science at a postgraduate level and how this impacted on nursing practice. The term biological sciences in this research encompasses elements of physiology, genetics, biochemistry and pathophysiology. A qualitative research study was designed, that involved the dissemination of a pre- and post-course semi-structured questionnaire for a biological science course, as part of a Master of Nursing programme at a New Zealand University, thus exploring the impact of undertaking a postgraduate biological sciences course. The responses were analysed into themes, based on interpretive concepts. The primary themes revealed improvement in confidence as: confidence in communication, confidence in linking nursing theoretical knowledge to practice and confidence in clinical nursing knowledge. This study highlights the need to privilege clinically-derived nursing knowledge, and that confidence in this nursing knowledge and clinical practice can be instilled through employing the model of theory-guided practice.

  20. Undertaking cause-specific mortality measurement in an unregistered population: an example from Tigray Region, Ethiopia

    Directory of Open Access Journals (Sweden)

    Hagos Godefay

    2014-09-01

    Full Text Available Background: The lack of adequate documentation of deaths, and particularly their cause, is often noted in African and Asian settings, but practical solutions for addressing the problem are not always clear. Verbal autopsy methods (interviewing witnesses after a death have developed rapidly, but there remains a lack of clarity as to how these methods can be effectively applied to large unregistered populations. This paper sets out practical details for undertaking a representative survey of cause-specific mortality in a population of several million, taking Tigray Region in Ethiopia as a prototype. Sampling: Sampling was designed around an expected level of maternal mortality ratio of 400 per 100,000 live births, which needed measuring within a 95% confidence interval of approximately ±100. Taking a stratified cluster sample within the region at the district level for logistic reasons, and allowing for a design effect of 2, this required a population of around 900,000 people, equating to six typical districts. Since the region is administered in six geographic zones, one district per zone was randomly selected. Implementation: The survey was implemented as a two-stage process: first, to trace deaths that occurred in the sampled districts within the preceding year, and second to follow them up with verbal autopsy interviews. The field work for both stages was undertaken by health extension workers, working in their normally assigned areas. Most of the work was associated with tracing the deaths, rather than undertaking the verbal autopsy interviews. Discussion: This approach to measuring cause-specific mortality in an unregistered Ethiopian population proved to be feasible and effective. Although it falls short of the ideal situation of continuous civil registration and vital statistics, a survey-based strategy of this kind may prove to be a useful intermediate step on the road towards full civil registration and vital statistics implementation.

  1. Tissue Classification

    DEFF Research Database (Denmark)

    Van Leemput, Koen; Puonti, Oula

    2015-01-01

    Computational methods for automatically segmenting magnetic resonance images of the brain have seen tremendous advances in recent years. So-called tissue classification techniques, aimed at extracting the three main brain tissue classes (white matter, gray matter, and cerebrospinal fluid), are now...... well established. In their simplest form, these methods classify voxels independently based on their intensity alone, although much more sophisticated models are typically used in practice. This article aims to give an overview of often-used computational techniques for brain tissue classification...

  2. Aspiring to Spectral Ignorance in Earth Observation

    Science.gov (United States)

    Oliver, S. A.

    2016-12-01

    Enabling robust, defensible and integrated decision making in the Era of Big Earth Data requires the fusion of data from multiple and diverse sensor platforms and networks. While the application of standardised global grid systems provides a common spatial analytics framework that facilitates the computationally efficient and statistically valid integration and analysis of these various data sources across multiple scales, there remains the challenge of sensor equivalency; particularly when combining data from different earth observation satellite sensors (e.g. combining Landsat and Sentinel-2 observations). To realise the vision of a sensor ignorant analytics platform for earth observation we require automation of spectral matching across the available sensors. Ultimately, the aim is to remove the requirement for the user to possess any sensor knowledge in order to undertake analysis. This paper introduces the concept of spectral equivalence and proposes a methodology through which equivalent bands may be sourced from a set of potential target sensors through application of equivalence metrics and thresholds. A number of parameters can be used to determine whether a pair of spectra are equivalent for the purposes of analysis. A baseline set of thresholds for these parameters and how to apply them systematically to enable relation of spectral bands amongst numerous different sensors is proposed. The base unit for comparison in this work is the relative spectral response. From this input, determination of a what may constitute equivalence can be related by a user, based on their own conceptualisation of equivalence.

  3. Improving discrimination of savanna tree species through a multiple endmember spectral-angle-mapper (SAM) approach: canopy level analysis

    CSIR Research Space (South Africa)

    Cho, Moses A

    2010-11-01

    Full Text Available sensing. The objectives of this paper were to (i) evaluate the classification performance of a multiple-endmember spectral angle mapper (SAM) classification approach (conventionally known as the nearest neighbour) in discriminating ten common African...

  4. Transporter Classification Database (TCDB)

    Data.gov (United States)

    U.S. Department of Health & Human Services — The Transporter Classification Database details a comprehensive classification system for membrane transport proteins known as the Transporter Classification (TC)...

  5. [Modeling and Simulation of Spectral Polarimetric BRDF].

    Science.gov (United States)

    Ling, Jin-jiang; Li, Gang; Zhang, Ren-bin; Tang, Qian; Ye, Qiu

    2016-01-01

    Under the conditions of the polarized light, The reflective surface of the object is affected by many factors, refractive index, surface roughness, and so the angle of incidence. For the rough surface in the different wavelengths of light exhibit different reflection characteristics of polarization, a spectral polarimetric BRDF based on Kirchhof theory is proposee. The spectral model of complex refraction index is combined with refraction index and extinction coefficient spectral model which were got by using the known complex refraction index at different value. Then get the spectral model of surface roughness derived from the classical surface roughness measuring method combined with the Fresnel reflection function. Take the spectral model of refraction index and roughness into the BRDF model, then the spectral polarimetirc BRDF model is proposed. Compare the simulation results of the refractive index varies with wavelength, roughness is constant, the refraction index and roughness both vary with wavelength and origin model with other papers, it shows that, the spectral polarimetric BRDF model can show the polarization characteristics of the surface accurately, and can provide a reliable basis for the application of polarization remote sensing, and other aspects of the classification of substances.

  6. Does undertaking an intercalated BSc influence first clinical year exam results at a London medical school?

    Directory of Open Access Journals (Sweden)

    Jones Melvyn

    2011-02-01

    Full Text Available Abstract Background Intercalated BScs (iBScs are an optional part of the medical school curriculum in many Universities. Does undertaking an iBSc influence subsequent student performance? Previous studies addressing this question have been flawed by iBSc students being highly selected. This study looks at data from medical students where there is a compulsory iBSc for non-graduates. Our aim was to see whether there was any difference in performance between students who took an iBSc before or after their third year (first clinical year exams. Methods A multivariable analysis was performed to compare the third year results of students at one London medical school who had or had not completed their iBSc by the start of this year (n = 276. A general linear model was applied to adjust for differences between the two groups in terms of potential confounders (age, sex, nationality and baseline performance. Results The results of third year summative exams for 276 students were analysed (184 students with an iBSc and 92 without. Unadjusted analysis showed students who took an iBSc before their third year achieved significantly higher end of year marks than those who did not with a mean score difference of 4.4 (0.9 to 7.9 95% CI, p = 0.01. (overall mean score 238.4 "completed iBSc" students versus 234.0 "not completed", range 145.2 - 272.3 out of 300. There was however a significant difference between the two groups in their prior second year exam marks with those choosing to intercalate before their third year having higher marks. Adjusting for this, the difference in overall exam scores was no longer significant with a mean score difference of 1.4 (-4.9 to +7.7 95% CI, p = 0.66. (overall mean score 238.0 " completed iBSc" students versus 236.5 "not completed". Conclusions Once possible confounders are controlled for (age, sex, previous academic performance undertaking an iBSc does not influence third year exam results. One explanation for this

  7. Decision tree approach for classification of remotely sensed satellite

    Indian Academy of Sciences (India)

    DTC) algorithm for classification of remotely sensed satellite data (Landsat TM) using open source support. The decision tree is constructed by recursively partitioning the spectral distribution of the training dataset using WEKA, open source ...

  8. The home as an appropriate setting for women undertaking cervical ripening before the induction of labour.

    Science.gov (United States)

    Reid, Margaret; Lorimer, Karen; Norman, Jane E; Bollapragada, Shrikant S; Norrie, John

    2011-02-01

    to explore women's experiences of cervical ripening using isosorbide mononitrate (IMN) in the home as part of the main randomised controlled trial. qualitative study with semi-structured interviews carried out at three weeks post partum. Interview transcripts were analysed to identify recurrent themes, focusing on why women became involved in the study, their views about both the self-medication and the home setting, and whether they would repeat the experience. the home. twenty women enrolled in the main randomised controlled trial. the study is part of a double-blind randomised controlled trial with 350 patients investigating whether a nitric oxide donor (IMN) used in cervical ripening improves the process of induction of labour. women liked the opportunity to remain at home during the cervical ripening process. Timing and setting were central issues; women hoped that it would hasten labour, while the home was seen as a setting offering freedom, security and reassurance, as opposed to the hospital, seen as constraining. Two women reported problems with IMN but the remainder reported that they would repeat the experience. women were very positive about the opportunity to undertake cervical ripening at home. It is important to explore this setting further for appropriate interventions. Copyright © 2009 Elsevier Ltd. All rights reserved.

  9. The lived experiences of flemish midwifery students undertaking an internship in Suriname: A phenomenological study.

    Science.gov (United States)

    Hilde, Curinckx; Marion, Welsh; Marianne, Nieuwenhuijze

    2018-05-01

    The aim of this study is to explore the lived experience of Flemish midwifery students undertaking an internship in Suriname. Hermeneutic phenomenological method as described by van Manen. Seven midwifery students from one University College were selected purposefully for an in-depth interview during their internship abroad within the period October-November 2014. All interviews were audio-taped, transcribed verbatim and analysed thematically. The study revealed five overarching themes: (1) A time to reconsider the time, (2) a time of connection and disconnection, (3) spatiality for thought and rethinking, (4) a body to undergo or a body to respond and (5) the other(s) among the others. The experience of an internship in Suriname presents itself in each individual as: 'A process of awareness from the self with a main focus on the professional'. Meaning that it was a process of 'disconnection' from their own culture towards 'connection' with another culture. Both, the 'rethinking' of their role as a midwife, as well as, balancing between guarding one's own authenticity by 'responding' or being the friendly stranger through 'undergoing', was noticeably striking. Copyright © 2018 Elsevier Ltd. All rights reserved.

  10. Spectral gamuts and spectral gamut mapping

    Science.gov (United States)

    Rosen, Mitchell R.; Derhak, Maxim W.

    2006-01-01

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

  11. Multispectral Image classification using the theories of neural networks

    International Nuclear Information System (INIS)

    Ardisasmita, M.S.; Subki, M.I.R.

    1997-01-01

    Image classification is the one of the important part of digital image analysis. the objective of image classification is to identify and regroup the features occurring in an image into one or several classes in terms of the object. basic to the understanding of multispectral classification is the concept of the spectral response of an object as a function of the electromagnetic radiation and the wavelength of the spectrum. new approaches to classification has been developed to improve the result of analysis, these state-of-the-art classifiers are based upon the theories of neural networks. Neural network classifiers are algorithmes which mimic the computational abilities of the human brain. Artificial neurons are simple emulation's of biological neurons; they take in information from sensors or other artificial neurons, perform very simple operations on this data, and pass the result to other recognize the spectral signature of each image pixel. Neural network image classification has been divided into supervised and unsupervised training procedures. In the supervised approach, examples of each cover type can be located and the computer can compute spectral signatures to categorize all pixels in a digital image into several land cover classes. In supervised classification, spectral signatures are generated by mathematically grouping and it does not require analyst-specified training data. Thus, in the supervised approach we define useful information categories and then examine their spectral reparability; in the unsupervised approach the computer determines spectrally sapable classes and then we define thei information value

  12. Spectral signature selection for mapping unvegetated soils

    Science.gov (United States)

    May, G. A.; Petersen, G. W.

    1975-01-01

    Airborne multispectral scanner data covering the wavelength interval from 0.40-2.60 microns were collected at an altitude of 1000 m above the terrain in southeastern Pennsylvania. Uniform training areas were selected within three sites from this flightline. Soil samples were collected from each site and a procedure developed to allow assignment of scan line and element number from the multispectral scanner data to each sampling location. These soil samples were analyzed on a spectrophotometer and laboratory spectral signatures were derived. After correcting for solar radiation and atmospheric attenuation, the laboratory signatures were compared to the spectral signatures derived from these same soils using multispectral scanner data. Both signatures were used in supervised and unsupervised classification routines. Computer-generated maps using the laboratory and multispectral scanner derived signatures resulted in maps that were similar to maps resulting from field surveys. Approximately 90% agreement was obtained between classification maps produced using multispectral scanner derived signatures and laboratory derived signatures.

  13. Assisted reproductive technologies in Ghana: transnational undertakings, local practices and ‘more affordable’ IVF

    Directory of Open Access Journals (Sweden)

    Trudie Gerrits

    2016-06-01

    Full Text Available The article sketches the origins and development of IVF in Ghana as a highly transnational undertaking. Movements are from and to Africa, involving human beings (providers and users, and also refer to other entities such as technologies, skills and knowledge. None of these movements are paid for using public money, neither are they subsidized by international health organizations. Currently, ‘more affordable’ IVF is being introduced into Ghana, on initiative of the first Association of Childless Couples of Ghana (ACCOG, in collaboration with the Belgium based non-profit organization the Walking Egg (tWE, representing another form of transnational networking. The article underlines the scarcity of well-trained embryologists in Ghana, which turns the embryologists’ expertise and skills into a scarce and precious commodity and guarantees this expertise becomes a major challenge for the directors of the private clinics. Next to local Ghanaian couples, the clinics also attend to transnational reproductive travellers, including women and men from neighbouring countries and Ghanaians in the diaspora returning to their country of origin. Their manifold motivations to cross borders and visit the IVF clinics in Ghana provide insight into the structural conditions impeding or facilitating the use of assisted reproductive technologies at different local sites. Transnational movements also include the flow of new procreation practices (such as surrogacy and the use of donor material, which (re-shape existing cultural and societal notions regarding kinship and the importance of blood/genetic ties. Finally, the article lists a number of thematic and theoretical issues which require further exploration and studies.

  14. Factors associated with quality of life in elderly undertaking literacy programs

    Directory of Open Access Journals (Sweden)

    Bruna Rodrigues dos Santos

    Full Text Available ABSTRACT Increased life expectancy has led to a significant number of elderly enrolling on Youth and Adult Education programs (YAE. These individuals leave inactivity and negative aspects of aging in search of opportunities for social inclusion. Objective: To evaluate the influence of sociodemographic factors and depressive and cognitive symptoms on quality of life (QL of elderly attending the YAE of São Carlos city in São Paulo state. Methods: A descriptive and quantitative study approved by the Research Ethics Committee of São Carlos Federal University was conducted. The sample comprised all elderly undertaking the YAE literacy program in 2012. The instruments used were the Mini-Mental State Examination (MMSE, Geriatric Depression Scale (GDS, WHOQOL-bref and WHOQOL-old, and a sociodemographic instrument. Results: We interviewed 23 elderly, predominantly females (91.3% in the early stages of old age (69.6%. The number of years of YAE study showed no correlation with cognition scores obtained on the MMSE or with QL domains. However, scores on the GDS had a moderate inverse relationship with total scores for the Physical (p<0.01, Sensory Functioning (p<0.05, Independence (p<0.01, Past, Present and Future Activities (p<0.05, Social Participation (p<0.01, and Intimacy (p<0.05 QV domains, and a strong inversely proportional relationship with the Social Relationships QV domain (p<0.01. Scores attained on the MMSE showed a moderate and direct relationship with total scores on the Independence QL domain (p=0.001. Conclusion: Elderly on literacy programs have average quality of life scores. Several QL domains are influenced by depression and cognitive symptoms.

  15. A method to incorporate uncertainty in the classification of remote sensing images

    OpenAIRE

    Gonçalves, Luísa M. S.; Fonte, Cidália C.; Júlio, Eduardo N. B. S.; Caetano, Mario

    2009-01-01

    The aim of this paper is to investigate if the incorporation of the uncertainty associated with the classification of surface elements into the classification of landscape units (LUs) increases the results accuracy. To this end, a hybrid classification method is developed, including uncertainty information in the classification of very high spatial resolution multi-spectral satellite images, to obtain a map of LUs. The developed classification methodology includes the following...

  16. Classification and mapping of rangeland vegetation physiognomic ...

    African Journals Online (AJOL)

    Plot vegetation species growth form, cover and height data were collected from 450 sampling sites based on eight spectral strata generated using unsupervised image classification. Field data were grouped at four levels of seven, six, three and two vegetation physiognomic classes which were subjected to both ML and ...

  17. Importance of spatial and spectral data reduction in the detection of internal defects in food products.

    Science.gov (United States)

    Zhang, Xuechen; Nansen, Christian; Aryamanesh, Nader; Yan, Guijun; Boussaid, Farid

    2015-04-01

    Despite the importance of data reduction as part of the processing of reflection-based classifications, this study represents one of the first in which the effects of both spatial and spectral data reductions on classification accuracies are quantified. Furthermore, the effects of approaches to data reduction were quantified for two separate classification methods, linear discriminant analysis (LDA) and support vector machine (SVM). As the model dataset, reflection data were acquired using a hyperspectral camera in 230 spectral channels from 401 to 879 nm (spectral resolution of 2.1 nm) from field pea (Pisum sativum) samples with and without internal pea weevil (Bruchus pisorum) infestation. We deployed five levels of spatial data reduction (binning) and eight levels of spectral data reduction (40 datasets). Forward stepwise LDA was used to select and include only spectral channels contributing the most to the separation of pixels from non-infested and infested field peas. Classification accuracies obtained with LDA and SVM were based on the classification of independent validation datasets. Overall, SVMs had significantly higher classification accuracies than LDAs (P food products with internal defects, and it highlights that spatial and spectral data reductions can (1) improve classification accuracies, (2) vastly decrease computer constraints, and (3) reduce analytical concerns associated with classifications of large and high-dimensional datasets.

  18. The capabilities and scope-of-practice requirements of advanced life support practitioners undertaking critical care transfers: A Delphi study

    Directory of Open Access Journals (Sweden)

    Monique Venter

    2016-11-01

    Full Text Available Background. Critical care transfers (CCT refer to the high level of care given during transport (via ambulance, helicopter or fixed-wing aircraft of patients who are of high acuity. In South Africa (SA, advanced life support (ALS paramedics undertake CCTs. The scope of ALS in SA has no extended protocol regarding procedures or medications in terms of dealing with these CCTs. Aim. The aim of this study was to obtain the opinions of several experts in fields pertaining to critical care and transport and to gain consensus on the skills and scope-of-practice requirements of paramedics undertaking CCTs in the SA setting. Methods. A modified Delphi study consisting of three rounds was undertaken using an online survey platform. A heterogeneous sample (n=7, consisting of specialists in the fields of anaesthesiology, emergency medicine, internal medicine, critical care, critical care transport and paediatrics, was asked to indicate whether, in their opinion, selected procedures and medications were needed within the scope of practice of paramedics undertaking CCTs. Results. After three rounds, consensus was obtained in 70% (57/81 of procedures and medications. Many of these items are not currently within the scope of paramedics’ training. The panel felt that paramedics undertaking these transfers should have additional postgraduate training that is specific to critical care. Conclusion. Major discrepancies exist between the current scope of paramedic practice and the suggested required scope of practice for CCTs. An extended scope of practice and additional training should be considered for these practitioners.

  19. Farmers prone to drought risk : why some farmers undertake farm-level risk-reduction measures while others not?

    NARCIS (Netherlands)

    Gidey, T.G.; van der Veen, A.

    2015-01-01

    This research investigates farmers’ cognitive perceptions of risk and the behavioral intentions to undertake farm-level risk-reduction measures. It has been observed that people who are susceptible to natural hazards often fail to act, or do very little, to protect their assets or lives. To answer

  20. A Phytase Enzyme-Based Biochemistry Practical Particularly Suited to Students Undertaking Courses in Biotechnology and Environmental Science

    Science.gov (United States)

    Boyce, Angela; Casey, Anne; Walsh, Gary

    2004-01-01

    Courses in introductory biochemistry invariably encompass basic principles of enzymology, with reinforcement of lecture-based material in appropriate laboratory practicals. Students undertaking practical classes are more enthusiastic, and generally display improved performance, when the specific experiments undertaken show direct relevance to…

  1. Classification of Pansharpened Urban Satellite Images

    DEFF Research Database (Denmark)

    Palsson, Frosti; Sveinsson, Johannes R.; Benediktsson, Jon Atli

    2012-01-01

    The classification of high resolution urban remote sensing imagery is addressed with the focus on classification of imagery that has been pansharpened by a number of different pansharpening methods. The pansharpening process introduces some spectral and spatial distortions in the resulting fused...... multispectral image, the amount of which highly varies depending on which pansharpening technique is used. In the majority of the pansharpening techniques that have been proposed, there is a compromise between the spatial enhancement and the spectral consistency. Here we study the effects of the spectral...... information from the panchromatic data. Random Forests (RF) and Support Vector Machines (SVM) will be used as classifiers. Experiments are done for three different datasets that have been obtained by two different imaging sensors, IKONOS and QuickBird. These sensors deliver multispectral images that have four...

  2. Spectral properties of 441 radio pulsars

    Science.gov (United States)

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

    2018-02-01

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

  3. Adaptive Spectral Doppler Estimation

    DEFF Research Database (Denmark)

    Gran, Fredrik; Jakobsson, Andreas; Jensen, Jørgen Arendt

    2009-01-01

    . The methods can also provide better quality of the estimated power spectral density (PSD) of the blood signal. Adaptive spectral estimation techniques are known to pro- vide good spectral resolution and contrast even when the ob- servation window is very short. The 2 adaptive techniques are tested......In this paper, 2 adaptive spectral estimation techniques are analyzed for spectral Doppler ultrasound. The purpose is to minimize the observation window needed to estimate the spectrogram to provide a better temporal resolution and gain more flexibility when designing the data acquisition sequence...... and compared with the averaged periodogram (Welch’s method). The blood power spectral capon (BPC) method is based on a standard minimum variance technique adapted to account for both averaging over slow-time and depth. The blood amplitude and phase estimation technique (BAPES) is based on finding a set...

  4. Non proliferation regimes undertakings: Benefits and limits of synergies in verification technologies and procedures

    International Nuclear Information System (INIS)

    Richard, M.

    2001-01-01

    Full text: Thirty years ago the NPT was entering into force. Therewith, when a State became party to the NPT, it had, in accordance with article III.1 of the Treaty, an undertaking to conclude a Comprehensive Safeguards agreement with the IAEA and accept safeguards verification on source or special fissionable material in all peaceful nuclear activities within its territories in order to verify that such material is not diverted. This multilateral instrument was the foundation stone of the non-proliferation regime and marked the actual birth of internationally accepted measures to verily compliance with politically stringent agreements. Since that time several important multilateral or bilateral instruments on non-proliferation and disarmament have been negotiated and adopted to curb the development and the acquisition of Weapons of Mass Destruction (WMD) most of them since the middle of the eighties and the collapse of the Soviet Union. Amongst the multilateral instruments are the Convention on the Prohibition of Bacteriological Weapon and Toxin Weapons (1972), the Convention on the Prohibition of Chemical Weapons (1993), the Comprehensive Test Ban Treaty (1996), the Strengthening of the IAEA Safeguards and the Additional Protocol (1997), with some still in negotiation like the Protocol of the Convention on the Prohibition of Bacteriological and Toxin Weapons, and some on which negotiation is still a wish like the Fissile Material Cut-off Treaty. Bilateral disarmament agreements between the United States of America and the Russian Federation such as the INF Treaty, START I and II, the agreements on the elimination of excess defence nuclear material as well as the Trilateral Initiative with the IAEA pave the way to nuclear disarmament with the reduction of both the number of nuclear weapons arsenal and the fissile material inventories. The politically stringent undertakings of States that have become parties to those agreements would not be possible without the

  5. Introduction to spectral theory

    CERN Document Server

    Levitan, B M

    1975-01-01

    This monograph is devoted to the spectral theory of the Sturm- Liouville operator and to the spectral theory of the Dirac system. In addition, some results are given for nth order ordinary differential operators. Those parts of this book which concern nth order operators can serve as simply an introduction to this domain, which at the present time has already had time to become very broad. For the convenience of the reader who is not familar with abstract spectral theory, the authors have inserted a chapter (Chapter 13) in which they discuss this theory, concisely and in the main without proofs, and indicate various connections with the spectral theory of differential operators.

  6. Classification in context

    DEFF Research Database (Denmark)

    Mai, Jens Erik

    2004-01-01

    This paper surveys classification research literature, discusses various classification theories, and shows that the focus has traditionally been on establishing a scientific foundation for classification research. This paper argues that a shift has taken place, and suggests that contemporary...... classification research focus on contextual information as the guide for the design and construction of classification schemes....

  7. Classification of the web

    DEFF Research Database (Denmark)

    Mai, Jens Erik

    2004-01-01

    This paper discusses the challenges faced by investigations into the classification of the Web and outlines inquiries that are needed to use principles for bibliographic classification to construct classifications of the Web. This paper suggests that the classification of the Web meets challenges...... that call for inquiries into the theoretical foundation of bibliographic classification theory....

  8. Virtual Satellite Construction and Application for Image Classification

    International Nuclear Information System (INIS)

    Su, W G; Su, F Z; Zhou, C H

    2014-01-01

    Nowadays, most remote sensing image classification uses single satellite remote sensing data, so the number of bands and band spectral width is consistent. In addition, observed phenomenon such as land cover have the same spectral signature, which causes the classification accuracy to decrease as different data have unique characteristic. Therefore, this paper analyzes different optical remote sensing satellites, comparing the spectral differences and proposes the ideas and methods to build a virtual satellite. This article illustrates the research on the TM, HJ-1 and MODIS data. We obtained the virtual band X 0 through these satellites' bands combined it with the 4 bands of a TM image to build a virtual satellite with five bands. Based on this, we used these data for image classification. The experimental results showed that the virtual satellite classification results of building land and water information were superior to the HJ-1 and TM data respectively

  9. Classification of natural formations based on their optical characteristics using small volumes of samples

    Science.gov (United States)

    Abramovich, N. S.; Kovalev, A. A.; Plyuta, V. Y.

    1986-02-01

    A computer algorithm has been developed to classify the spectral bands of natural scenes on Earth according to their optical characteristics. The algorithm is written in FORTRAN-IV and can be used in spectral data processing programs requiring small data loads. The spectral classifications of some different types of green vegetable canopies are given in order to illustrate the effectiveness of the algorithm.

  10. Verifying compliance with nuclear non-proliferation undertakings: IAEA safeguards agreements and additional protocols

    International Nuclear Information System (INIS)

    2008-06-01

    This report provides background information on safeguards and explains procedures for States to conclude Additional Protocols to comprehensive Safeguards Agreements with the IAEA. Since the IAEA was founded in 1957, its safeguards system has been an indispensable component of the nuclear non-proliferation regime and has facilitated peaceful nuclear cooperation. In recognition of this, the Treaty on the Non-Proliferation of Nuclear Weapons (NPT) makes it mandatory for all non-nuclear-weapon States (NNWS) party to the Treaty to conclude comprehensive safeguards agreements with the IAEA, and thus allow for the application of safeguards to all their nuclear material. Under Article III of the NPT, all NNWS undertake to accept safeguards, as set forth in agreements to be negotiated and concluded with the IAEA, for the exclusive purpose of verification of the fulfilment of the States' obligations under the NPT. In May 1997, the IAEA Board of Governors approved the Model Additional Protocol to Safeguards Agreements (reproduced in INFCIRC/540(Corr.)) which provided for an additional legal authority. In States that have both a comprehensive safeguards agreement and an additional protocol in force, the IAEA is able to optimize the implementation of all safeguards measures available. In order to simplify certain procedures under comprehensive safeguards agreements for States with little or no nuclear material and no nuclear material in a facility, the IAEA began making available, in 1971, a 'small quantities protocol' (SQP), which held in abeyance the implementation of most of the detailed provisions of comprehensive safeguards agreements for so long as the State concerned satisfied these criteria. The safeguards system aims at detecting and deterring the diversion of nuclear material. Such material includes enriched uranium, plutonium and uranium-233, which could be used directly in nuclear weapons. It also includes natural uranium and depleted uranium, the latter of which is

  11. Verifying compliance with nuclear non-proliferation undertakings: IAEA safeguards agreements and additional protocols

    International Nuclear Information System (INIS)

    2008-04-01

    This report provides background information on safeguards and explains procedures for States to conclude Additional Protocols to comprehensive Safeguards Agreements with the IAEA. Since the IAEA was founded in 1957, its safeguards system has been an indispensable component of the nuclear non-proliferation regime and has facilitated peaceful nuclear cooperation. In recognition of this, the Treaty on the Non-Proliferation of Nuclear Weapons (NPT) makes it mandatory for all non-nuclear-weapon States (NNWS) party to the Treaty to conclude comprehensive safeguards agreements with the IAEA, and thus allow for the application of safeguards to all their nuclear material. Under Article III of the NPT, all NNWS undertake to accept safeguards, as set forth in agreements to be negotiated and concluded with the IAEA, for the exclusive purpose of verification of the fulfilment of the States' obligations under the NPT. In May 1997, the IAEA Board of Governors approved the Model Additional Protocol to Safeguards Agreements (reproduced in INFCIRC/540(Corr.)) which provided for an additional legal authority. In States that have both a comprehensive safeguards agreement and an additional protocol in force, the IAEA is able to optimize the implementation of all safeguards measures available. In order to simplify certain procedures under comprehensive safeguards agreements for States with little or no nuclear material and no nuclear material in a facility, the IAEA began making available, in 1971, a 'small quantities protocol' (SQP), which held in abeyance the implementation of most of the detailed provisions of comprehensive safeguards agreements for so long as the State concerned satisfied these criteria. The safeguards system aims at detecting and deterring the diversion of nuclear material. Such material includes enriched uranium, plutonium and uranium-233, which could be used directly in nuclear weapons. It also includes natural uranium and depleted uranium, the latter of which is

  12. Hazard classification methodology

    International Nuclear Information System (INIS)

    Brereton, S.J.

    1996-01-01

    This document outlines the hazard classification methodology used to determine the hazard classification of the NIF LTAB, OAB, and the support facilities on the basis of radionuclides and chemicals. The hazard classification determines the safety analysis requirements for a facility

  13. On Longitudinal Spectral Coherence

    DEFF Research Database (Denmark)

    Kristensen, Leif

    1979-01-01

    It is demonstrated that the longitudinal spectral coherence differs significantly from the transversal spectral coherence in its dependence on displacement and frequency. An expression for the longitudinal coherence is derived and it is shown how the scale of turbulence, the displacement between ...... observation sites and the turbulence intensity influence the results. The limitations of the theory are discussed....

  14. Superfícies de resposta espectro-temporal de imagens do sensor MODIS para classificação de área de soja no Estado do Rio Grande do Sul Spectral-temporal response surface of MODIS sensor images for soybean area classification in Rio Grande do Sul State

    Directory of Open Access Journals (Sweden)

    Conrado de Moraes Rudorff

    2007-02-01

    Full Text Available Este trabalho objetivou avaliar o potencial e as limitações das imagens MODIS para classificação e estimativa de área de soja por meio do método de superfície de resposta espectro-temporal (Spectral-Temporal Response Surface - STRS. Um mapa temático das áreas com soja, oriundo da classificação de imagens Landsat do Estado do Rio Grande do Sul, foi utilizado como referência para auxiliar na orientação da amostragem dos pixels de treinamento e para a comparação dos resultados. Seis imagens compostas do sensor MODIS foram utilizadas para a classificação supervisionada da área de soja por meio do algoritmo de máxima verossimilhança (MAXVER adaptado ao método STRS. Os resultados foram avaliados pelo coeficiente Kappa para a totalidade da área em estudo e também para uma região de latifúndios e outra de minifúndios. O método STRS subestimou em 6,6% a área de soja para toda a região estudada, sendo que a estatística Kappa foi de 0,503. Para as regiões de latifúndios e minifúndios, a área de soja foi superestimada em 8% (Kappa=0,424 e subestimada em 43,4% (Kappa=0,358, respectivamente. As imagens MODIS, por meio do método STRS, demonstraram ter potencial para classificar a área de soja, principalmente em regiões de latifúndios. Em regiões de minifúndios, a correta identificação e classificação das áreas de soja mostrou-se pouco eficiente em razão da baixa resolução espacial das imagens MODIS.This paper was aimed at evaluating the potential and the limitations of MODIS images for soybean classification and area estimation through a Spectral-Temporal Response Surface (STRS method. A soybean thematic map from Rio Grande do Sul State, Brazil, derived from Landsat images was used as reference data to assist both sample training and results comparison. Six 16-day composite MODIS images were classified through a supervised maximum likelihood algorithm (MAXVER adapted to the STRS method. The results were

  15. Farmers Prone to Drought Risk: Why Some Farmers Undertake Farm-Level Risk-Reduction Measures While Others Not?

    Science.gov (United States)

    Gebrehiwot, Tagel; van der Veen, Anne

    2015-03-01

    This research investigates farmers' cognitive perceptions of risk and the behavioral intentions to undertake farm-level risk-reduction measures. It has been observed that people who are susceptible to natural hazards often fail to act, or do very little, to protect their assets or lives. To answer the question of why some people show adaptive behavior while others do not, a socio-psychological model of precautionary adaptation based on protection motivation theory and trans-theoretical stage model has been applied for the first time to areas of drought risk in the developing countries cultural context. The applicability of the integrated model is explored by means of a representative sample survey of smallholder farmers in northern Ethiopia. The result of the study showed that there is a statistically significant association between farmer's behavioral intention to undertake farm-level risk-reduction measures and the main important protection motivation model variables. High perceived vulnerability, severity of consequences, self-efficacy, and response efficacy lead to higher levels of behavioral intentions to undertake farm-level risk-reduction measures. For farmers in the action stage, self-efficacy and response efficacy were the main motivators of behavioral intention. For farmers in the contemplative stage, self-efficacy and cost appear to be the main motivators for them to act upon risk reduction, while perceived severity of consequences and cost of response actions were found to be important for farmers in the pre-contemplative stage.

  16. Ultracool Dwarf Stars: Surveys, Properties, and Spectral Classification

    Science.gov (United States)

    Steele, Iain A.; Jones, Hugh R. A.

    2001-03-01

    Conference was held in Manchester, England, United Kingdom, in 2000 August. The Proceedings will be edited by H. R. A. Jones and I. A. Steele and published in the Lecture Notes in Physics Series by Springer-Verlag.

  17. Spectral Classification of PSN J15381795+2544173

    Science.gov (United States)

    Silverman, J. M.; Cohen, D. P.; Filippenko, A. V.

    2012-06-01

    We report that inspection of a noisy CCD spectrum (range 340-1000 nm), obtained on June 27.3 UT with the Shane 3-m reflector (+ Kast spectrograph) at Lick Observatory, shows that PSN J15381795+2544173 (ATEL 4200) is a Type Ia supernova (SN Ia). After removal of the host-galaxy recession velocity of 26,952 km/s (Sloan Digital Sky Survey Data Release 6), we find the absorption minimum of the Si II 635.5-nm line to be blueshifted by about 11,700 km/s.

  18. Spectral Classification of MASTER J221505.32+101812.6

    Science.gov (United States)

    Silverman, J. M.; Cohen, D. P.; Filippenko, A. V.

    2012-06-01

    We report that inspection of a CCD spectrum (range 340-1000 nm), obtained on June 27.4 UT with the Shane 3-m reflector (+ Kast spectrograph) at Lick Observatory, shows that MASTER J221505.32+101812.6 (ATel #4213) is a Type Ia supernova (SN Ia). Cross-correlation with a library of SN spectra using the "SuperNova IDentification" code (SNID; Blondin & Tonry 2007, Ap.J. 666, 1024) indicates that the object is a normal SN Ia near maximum brightness at a redshift of 0.090.

  19. Spectral Classification of MASTER J174041.78+272632.4

    Science.gov (United States)

    Silverman, J. M.; Cohen, D. P.; Filippenko, A. V.

    2012-06-01

    We report that inspection of a CCD spectrum (range 340-1000 nm), obtained on June 27.4 UT with the Shane 3-m reflector (+ Kast spectrograph) at Lick Observatory, shows that MASTER J174041.78+272632.4 (ATel #4213) is a Galactic variable star. Hydrogen Balmer absorption superposed with weak, narrow emission is detected at redshift 0. The spectrum roughly resembles that of a B[e] star.

  20. Classification Accuracy Increase Using Multisensor Data Fusion

    Science.gov (United States)

    Makarau, A.; Palubinskas, G.; Reinartz, P.

    2011-09-01

    The practical use of very high resolution visible and near-infrared (VNIR) data is still growing (IKONOS, Quickbird, GeoEye-1, etc.) but for classification purposes the number of bands is limited in comparison to full spectral imaging. These limitations may lead to the confusion of materials such as different roofs, pavements, roads, etc. and therefore may provide wrong interpretation and use of classification products. Employment of hyperspectral data is another solution, but their low spatial resolution (comparing to multispectral data) restrict their usage for many applications. Another improvement can be achieved by fusion approaches of multisensory data since this may increase the quality of scene classification. Integration of Synthetic Aperture Radar (SAR) and optical data is widely performed for automatic classification, interpretation, and change detection. In this paper we present an approach for very high resolution SAR and multispectral data fusion for automatic classification in urban areas. Single polarization TerraSAR-X (SpotLight mode) and multispectral data are integrated using the INFOFUSE framework, consisting of feature extraction (information fission), unsupervised clustering (data representation on a finite domain and dimensionality reduction), and data aggregation (Bayesian or neural network). This framework allows a relevant way of multisource data combination following consensus theory. The classification is not influenced by the limitations of dimensionality, and the calculation complexity primarily depends on the step of dimensionality reduction. Fusion of single polarization TerraSAR-X, WorldView-2 (VNIR or full set), and Digital Surface Model (DSM) data allow for different types of urban objects to be classified into predefined classes of interest with increased accuracy. The comparison to classification results of WorldView-2 multispectral data (8 spectral bands) is provided and the numerical evaluation of the method in comparison to

  1. Estimation of spectral kurtosis

    Science.gov (United States)

    Sutawanir

    2017-03-01

    Rolling bearings are the most important elements in rotating machinery. Bearing frequently fall out of service for various reasons: heavy loads, unsuitable lubrications, ineffective sealing. Bearing faults may cause a decrease in performance. Analysis of bearing vibration signals has attracted attention in the field of monitoring and fault diagnosis. Bearing vibration signals give rich information for early detection of bearing failures. Spectral kurtosis, SK, is a parameter in frequency domain indicating how the impulsiveness of a signal varies with frequency. Faults in rolling bearings give rise to a series of short impulse responses as the rolling elements strike faults, SK potentially useful for determining frequency bands dominated by bearing fault signals. SK can provide a measure of the distance of the analyzed bearings from a healthy one. SK provides additional information given by the power spectral density (psd). This paper aims to explore the estimation of spectral kurtosis using short time Fourier transform known as spectrogram. The estimation of SK is similar to the estimation of psd. The estimation falls in model-free estimation and plug-in estimator. Some numerical studies using simulations are discussed to support the methodology. Spectral kurtosis of some stationary signals are analytically obtained and used in simulation study. Kurtosis of time domain has been a popular tool for detecting non-normality. Spectral kurtosis is an extension of kurtosis in frequency domain. The relationship between time domain and frequency domain analysis is establish through power spectrum-autocovariance Fourier transform. Fourier transform is the main tool for estimation in frequency domain. The power spectral density is estimated through periodogram. In this paper, the short time Fourier transform of the spectral kurtosis is reviewed, a bearing fault (inner ring and outer ring) is simulated. The bearing response, power spectrum, and spectral kurtosis are plotted to

  2. Spectrally accurate contour dynamics

    International Nuclear Information System (INIS)

    Van Buskirk, R.D.; Marcus, P.S.

    1994-01-01

    We present an exponentially accurate boundary integral method for calculation the equilibria and dynamics of piece-wise constant distributions of potential vorticity. The method represents contours of potential vorticity as a spectral sum and solves the Biot-Savart equation for the velocity by spectrally evaluating a desingularized contour integral. We use the technique in both an initial-value code and a newton continuation method. Our methods are tested by comparing the numerical solutions with known analytic results, and it is shown that for the same amount of computational work our spectral methods are more accurate than other contour dynamics methods currently in use

  3. Spectral radius of graphs

    CERN Document Server

    Stevanovic, Dragan

    2015-01-01

    Spectral Radius of Graphs provides a thorough overview of important results on the spectral radius of adjacency matrix of graphs that have appeared in the literature in the preceding ten years, most of them with proofs, and including some previously unpublished results of the author. The primer begins with a brief classical review, in order to provide the reader with a foundation for the subsequent chapters. Topics covered include spectral decomposition, the Perron-Frobenius theorem, the Rayleigh quotient, the Weyl inequalities, and the Interlacing theorem. From this introduction, the

  4. Spectral unmixing: estimating partial abundances

    CSIR Research Space (South Africa)

    Debba, Pravesh

    2009-01-01

    Full Text Available techniques is complicated when considering very similar spectral signatures. Iron-bearing oxide/hydroxide/sulfate minerals have similar spectral signatures. The study focuses on how could estimates of abundances of spectrally similar iron-bearing oxide...

  5. The Effect of Epidermal Structures on Leaf Spectral Signatures of Ice Plants (Aizoaceae

    Directory of Open Access Journals (Sweden)

    René Hans-Jürgen Heim

    2015-12-01

    Full Text Available Epidermal structures (ES of leaves are known to affect the functional properties and spectral responses. Spectral studies focused mostly on the effect of hairs or wax layers only. We studied a wider range of different ES and their impact on spectral properties. Additionally, we identified spectral regions that allow distinguishing different ES. We used a field spectrometer to measure ex situ leaf spectral responses from 350 nm–2500 nm. A spectral library for 25 species of the succulent family Aizoaceae was assembled. Five functional types were defined based on ES: flat epidermal cell surface, convex to papillary epidermal cell surface, bladder cells, hairs and wax cover. We tested the separability of ES using partial least squares discriminant analysis (PLS-DA based on the spectral data. Subsequently, variable importance (VIP was calculated to identify spectral regions relevant for discriminating our functional types (classes. Classification performance was high, with a kappa value of 0.9 indicating well-separable spectral classes. VIP calculations identified six spectral regions of increased importance for the classification. We confirmed and extended previous findings regarding the visible-near-infrared spectral region. Our experiments also confirmed that epidermal leaf traits can be classified due to clearly distinguishable spectral signatures across species and genera within the Aizoaceae.

  6. Rectangular spectral collocation

    KAUST Repository

    Driscoll, Tobin A.; Hale, Nicholas

    2015-01-01

    Boundary conditions in spectral collocation methods are typically imposed by removing some rows of the discretized differential operator and replacing them with others that enforce the required conditions at the boundary. A new approach based upon

  7. Vowel Inherent Spectral Change

    CERN Document Server

    Assmann, Peter

    2013-01-01

    It has been traditional in phonetic research to characterize monophthongs using a set of static formant frequencies, i.e., formant frequencies taken from a single time-point in the vowel or averaged over the time-course of the vowel. However, over the last twenty years a growing body of research has demonstrated that, at least for a number of dialects of North American English, vowels which are traditionally described as monophthongs often have substantial spectral change. Vowel Inherent Spectral Change has been observed in speakers’ productions, and has also been found to have a substantial effect on listeners’ perception. In terms of acoustics, the traditional categorical distinction between monophthongs and diphthongs can be replaced by a gradient description of dynamic spectral patterns. This book includes chapters addressing various aspects of vowel inherent spectral change (VISC), including theoretical and experimental studies of the perceptually relevant aspects of VISC, the relationship between ar...

  8. Hyperspectral image classifier based on beach spectral feature

    International Nuclear Information System (INIS)

    Liang, Zhang; Lianru, Gao; Bing, Zhang

    2014-01-01

    The seashore, especially coral bank, is sensitive to human activities and environmental changes. A multispectral image, with coarse spectral resolution, is inadaptable for identify subtle spectral distinctions between various beaches. To the contrary, hyperspectral image with narrow and consecutive channels increases our capability to retrieve minor spectral features which is suit for identification and classification of surface materials on the shore. Herein, this paper used airborne hyperspectral data, in addition to ground spectral data to study the beaches in Qingdao. The image data first went through image pretreatment to deal with the disturbance of noise, radiation inconsistence and distortion. In succession, the reflection spectrum, the derivative spectrum and the spectral absorption features of the beach surface were inspected in search of diagnostic features. Hence, spectra indices specific for the unique environment of seashore were developed. According to expert decisions based on image spectrums, the beaches are ultimately classified into sand beach, rock beach, vegetation beach, mud beach, bare land and water. In situ surveying reflection spectrum from GER1500 field spectrometer validated the classification production. In conclusion, the classification approach under expert decision based on feature spectrum is proved to be feasible for beaches

  9. Spectrally selective glazings

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1998-08-01

    Spectrally selective glazing is window glass that permits some portions of the solar spectrum to enter a building while blocking others. This high-performance glazing admits as much daylight as possible while preventing transmission of as much solar heat as possible. By controlling solar heat gains in summer, preventing loss of interior heat in winter, and allowing occupants to reduce electric lighting use by making maximum use of daylight, spectrally selective glazing significantly reduces building energy consumption and peak demand. Because new spectrally selective glazings can have a virtually clear appearance, they admit more daylight and permit much brighter, more open views to the outside while still providing the solar control of the dark, reflective energy-efficient glass of the past. This Federal Technology Alert provides detailed information and procedures for Federal energy managers to consider spectrally selective glazings. The principle of spectrally selective glazings is explained. Benefits related to energy efficiency and other architectural criteria are delineated. Guidelines are provided for appropriate application of spectrally selective glazing, and step-by-step instructions are given for estimating energy savings. Case studies are also presented to illustrate actual costs and energy savings. Current manufacturers, technology users, and references for further reading are included for users who have questions not fully addressed here.

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

    NARCIS (Netherlands)

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

    2004-01-01

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

  11. Nonparametric Collective Spectral Density Estimation and Clustering

    KAUST Repository

    Maadooliat, Mehdi

    2017-04-12

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

  12. Nonparametric Collective Spectral Density Estimation and Clustering

    KAUST Repository

    Maadooliat, Mehdi; Sun, Ying; Chen, Tianbo

    2017-01-01

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

  13. Decree No. 67/77 of 6 May establishing a National Uranium Undertaking as a public body

    International Nuclear Information System (INIS)

    1977-01-01

    This Decree, promulgated on 29 March 1977, sets up a National Uranium Undertaking (ENU). The ENU Statute which is attached to the Decree lays down that its main purpose is to prospect for and inventory uranium deposits, to explore known deposits, to set up facilities for recovery and treatment of uranium ores, and finally, to market the products obtained. The ENU has taken over the work which, until now, had been carried out in that field by the Junta de Energia Nuclear and it is placed under the authority of the Minister of Industry and Technology. (NEA) [fr

  14. Multiple endmember spectral-angle-mapper (SAM) analysis improves discrimination of Savanna tree species

    CSIR Research Space (South Africa)

    Cho, Moses A

    2009-08-01

    Full Text Available of this paper was to evaluate the classification performance of a multiple-endmember spectral angle mapper (SAM) classification approach in discriminating seven common African savanna tree species and to compare the results with the traditional SAM classifier...

  15. SAW Classification Algorithm for Chinese Text Classification

    OpenAIRE

    Xiaoli Guo; Huiyu Sun; Tiehua Zhou; Ling Wang; Zhaoyang Qu; Jiannan Zang

    2015-01-01

    Considering the explosive growth of data, the increased amount of text data’s effect on the performance of text categorization forward the need for higher requirements, such that the existing classification method cannot be satisfied. Based on the study of existing text classification technology and semantics, this paper puts forward a kind of Chinese text classification oriented SAW (Structural Auxiliary Word) algorithm. The algorithm uses the special space effect of Chinese text where words...

  16. Parallel computation for blood cell classification in medical hyperspectral imagery

    International Nuclear Information System (INIS)

    Li, Wei; Wu, Lucheng; Qiu, Xianbo; Ran, Qiong; Xie, Xiaoming

    2016-01-01

    With the advantage of fine spectral resolution, hyperspectral imagery provides great potential for cell classification. This paper provides a promising classification system including the following three stages: (1) band selection for a subset of spectral bands with distinctive and informative features, (2) spectral-spatial feature extraction, such as local binary patterns (LBP), and (3) followed by an effective classifier. Moreover, these three steps are further implemented on graphics processing units (GPU) respectively, which makes the system real-time and more practical. The GPU parallel implementation is compared with the serial implementation on central processing units (CPU). Experimental results based on real medical hyperspectral data demonstrate that the proposed system is able to offer high accuracy and fast speed, which are appealing for cell classification in medical hyperspectral imagery. (paper)

  17. Classification in Astronomy: Past and Present

    Science.gov (United States)

    Feigelson, Eric

    2012-03-01

    Astronomers have always classified celestial objects. The ancient Greeks distinguished between asteros, the fixed stars, and planetos, the roving stars. The latter were associated with the Gods and, starting with Plato in his dialog Timaeus, provided the first mathematical models of celestial phenomena. Giovanni Hodierna classified nebulous objects, seen with a Galilean refractor telescope in the mid-seventeenth century into three classes: "Luminosae," "Nebulosae," and "Occultae." A century later, Charles Messier compiled a larger list of nebulae, star clusters and galaxies, but did not attempt a classification. Classification of comets was a significant enterprise in the 19th century: Alexander (1850) considered two groups based on orbit sizes, Lardner (1853) proposed three groups of orbits, and Barnard (1891) divided them into two classes based on morphology. Aside from the segmentation of the bright stars into constellations, most stellar classifications were based on colors and spectral properties. During the 1860s, the pioneering spectroscopist Angelo Secchi classified stars into five classes: white, yellow, orange, carbon stars, and emission line stars. After many debates, the stellar spectral sequence was refined by the group at Harvard into the familiar OBAFGKM spectral types, later found to be a sequence on surface temperature (Cannon 1926). The spectral classification is still being extended with recent additions of O2 hot stars (Walborn et al. 2002) and L and T brown dwarfs (Kirkpatrick 2005). Townley (1913) reviews 30 years of variable star classification, emerging with six classes with five subclasses. The modern classification of variable stars has about 80 (sub)classes, and is still under debate (Samus 2009). Shortly after his confirmation that some nebulae are external galaxies, Edwin Hubble (1926) proposed his famous bifurcated classification of galaxy morphologies with three classes: ellipticals, spirals, and irregulars. These classes are still

  18. Hyperspectral image classification using Support Vector Machine

    International Nuclear Information System (INIS)

    Moughal, T A

    2013-01-01

    Classification of land cover hyperspectral images is a very challenging task due to the unfavourable ratio between the number of spectral bands and the number of training samples. The focus in many applications is to investigate an effective classifier in terms of accuracy. The conventional multiclass classifiers have the ability to map the class of interest but the considerable efforts and large training sets are required to fully describe the classes spectrally. Support Vector Machine (SVM) is suggested in this paper to deal with the multiclass problem of hyperspectral imagery. The attraction to this method is that it locates the optimal hyper plane between the class of interest and the rest of the classes to separate them in a new high-dimensional feature space by taking into account only the training samples that lie on the edge of the class distributions known as support vectors and the use of the kernel functions made the classifier more flexible by making it robust against the outliers. A comparative study has undertaken to find an effective classifier by comparing Support Vector Machine (SVM) to the other two well known classifiers i.e. Maximum likelihood (ML) and Spectral Angle Mapper (SAM). At first, the Minimum Noise Fraction (MNF) was applied to extract the best possible features form the hyperspectral imagery and then the resulting subset of the features was applied to the classifiers. Experimental results illustrate that the integration of MNF and SVM technique significantly reduced the classification complexity and improves the classification accuracy.

  19. APPLICATION OF FUSION WITH SAR AND OPTICAL IMAGES IN LAND USE CLASSIFICATION BASED ON SVM

    Directory of Open Access Journals (Sweden)

    C. Bao

    2012-07-01

    Full Text Available As the increment of remote sensing data with multi-space resolution, multi-spectral resolution and multi-source, data fusion technologies have been widely used in geological fields. Synthetic Aperture Radar (SAR and optical camera are two most common sensors presently. The multi-spectral optical images express spectral features of ground objects, while SAR images express backscatter information. Accuracy of the image classification could be effectively improved fusing the two kinds of images. In this paper, Terra SAR-X images and ALOS multi-spectral images were fused for land use classification. After preprocess such as geometric rectification, radiometric rectification noise suppression and so on, the two kind images were fused, and then SVM model identification method was used for land use classification. Two different fusion methods were used, one is joining SAR image into multi-spectral images as one band, and the other is direct fusing the two kind images. The former one can raise the resolution and reserve the texture information, and the latter can reserve spectral feature information and improve capability of identifying different features. The experiment results showed that accuracy of classification using fused images is better than only using multi-spectral images. Accuracy of classification about roads, habitation and water bodies was significantly improved. Compared to traditional classification method, the method of this paper for fused images with SVM classifier could achieve better results in identifying complicated land use classes, especially for small pieces ground features.

  20. CRISS power spectral density

    International Nuclear Information System (INIS)

    Vaeth, W.

    1979-04-01

    The correlation of signal components at different frequencies like higher harmonics cannot be detected by a normal power spectral density measurement, since this technique correlates only components at the same frequency. This paper describes a special method for measuring the correlation of two signal components at different frequencies: the CRISS power spectral density. From this new function in frequency analysis, the correlation of two components can be determined quantitatively either they stem from one signal or from two diverse signals. The principle of the method, suitable for the higher harmonics of a signal as well as for any other frequency combinations is shown for the digital frequency analysis technique. Two examples of CRISS power spectral densities demonstrates the operation of the new method. (orig.) [de

  1. Parametric Explosion Spectral Model

    Energy Technology Data Exchange (ETDEWEB)

    Ford, S R; Walter, W R

    2012-01-19

    Small underground nuclear explosions need to be confidently detected, identified, and characterized in regions of the world where they have never before occurred. We develop a parametric model of the nuclear explosion seismic source spectrum derived from regional phases that is compatible with earthquake-based geometrical spreading and attenuation. Earthquake spectra are fit with a generalized version of the Brune spectrum, which is a three-parameter model that describes the long-period level, corner-frequency, and spectral slope at high-frequencies. Explosion spectra can be fit with similar spectral models whose parameters are then correlated with near-source geology and containment conditions. We observe a correlation of high gas-porosity (low-strength) with increased spectral slope. The relationship between the parametric equations and the geologic and containment conditions will assist in our physical understanding of the nuclear explosion source.

  2. Photovoltaic spectral responsivity measurements

    Energy Technology Data Exchange (ETDEWEB)

    Emery, K.; Dunlavy, D.; Field, H.; Moriarty, T. [National Renewable Energy Lab., Golden, CO (United States)

    1998-09-01

    This paper discusses the various elemental random and nonrandom error sources in typical spectral responsivity measurement systems. The authors focus specifically on the filter and grating monochrometer-based spectral responsivity measurement systems used by the Photovoltaic (PV) performance characterization team at NREL. A variety of subtle measurement errors can occur that arise from a finite photo-current response time, bandwidth of the monochromatic light, waveform of the monochromatic light, and spatial uniformity of the monochromatic and bias lights; the errors depend on the light source, PV technology, and measurement system. The quantum efficiency can be a function of he voltage bias, light bias level, and, for some structures, the spectral content of the bias light or location on the PV device. This paper compares the advantages and problems associated with semiconductor-detector-based calibrations and pyroelectric-detector-based calibrations. Different current-to-voltage conversion and ac photo-current detection strategies employed at NREL are compared and contrasted.

  3. Spectral analysis by correlation

    International Nuclear Information System (INIS)

    Fauque, J.M.; Berthier, D.; Max, J.; Bonnet, G.

    1969-01-01

    The spectral density of a signal, which represents its power distribution along the frequency axis, is a function which is of great importance, finding many uses in all fields concerned with the processing of the signal (process identification, vibrational analysis, etc...). Amongst all the possible methods for calculating this function, the correlation method (correlation function calculation + Fourier transformation) is the most promising, mainly because of its simplicity and of the results it yields. The study carried out here will lead to the construction of an apparatus which, coupled with a correlator, will constitute a set of equipment for spectral analysis in real time covering the frequency range 0 to 5 MHz. (author) [fr

  4. Spectral backward radiation profile

    International Nuclear Information System (INIS)

    Kwon, Sung Duck; Lee, Keun Hyun; Kim, Bo Ra; Yoon, Suk Soo

    2004-01-01

    Ultrasonic backward radiation profile is frequency-dependent when incident region has deptional gradient of acoustical properties or multi-layers. Until now, we have measured the profiles of principal frequencies of used transducers so that it was not easy to understand the change of the frequency component and spectrum of backward radiation from the profile. We tried to measure the spectral backward radiation profiles using DFP(digital filer package) Lecroy DSO. The very big changes in the shape and pattern of spectral backward radiation profiles leads to the conclusion that this new try could be very effective tool to evaluate frequency dependent surface area.

  5. Asteroid taxonomic classifications

    International Nuclear Information System (INIS)

    Tholen, D.J.

    1989-01-01

    This paper reports on three taxonomic classification schemes developed and applied to the body of available color and albedo data. Asteroid taxonomic classifications according to two of these schemes are reproduced

  6. Topographic gradient based site characterization in India complemented by strong ground-motion spectral attributes

    KAUST Repository

    Nath, Sankar Kumar; Thingbaijam, Kiran Kumar; Adhikari, M. D.; Nayak, Avinash; Devaraj, N.; Ghosh, Soumalya K.; Mahajan, Arun K.

    2013-01-01

    We appraise topographic-gradient approach for site classification that employs correlations between 30. m column averaged shear-wave velocity and topographic gradients. Assessments based on site classifications reported from cities across India indicate that the approach is reasonably viable at regional level. Additionally, we experiment three techniques for site classification based on strong ground-motion recordings, namely Horizontal-to-Vertical Spectral Ratio (HVSR), Response Spectra Shape (RSS), and Horizontal-to-Vertical Response Spectral Ratio (HVRSR) at the strong motion stations located across the Himalayas and northeast India. Statistical tests on the results indicate that these three techniques broadly differentiate soil and rock sites while RSS and HVRSR yield better signatures. The results also support the implemented site classification in the light of strong ground-motion spectral attributes observed in different parts of the globe. © 2013 Elsevier Ltd.

  7. Topographic gradient based site characterization in India complemented by strong ground-motion spectral attributes

    KAUST Repository

    Nath, Sankar Kumar

    2013-12-01

    We appraise topographic-gradient approach for site classification that employs correlations between 30. m column averaged shear-wave velocity and topographic gradients. Assessments based on site classifications reported from cities across India indicate that the approach is reasonably viable at regional level. Additionally, we experiment three techniques for site classification based on strong ground-motion recordings, namely Horizontal-to-Vertical Spectral Ratio (HVSR), Response Spectra Shape (RSS), and Horizontal-to-Vertical Response Spectral Ratio (HVRSR) at the strong motion stations located across the Himalayas and northeast India. Statistical tests on the results indicate that these three techniques broadly differentiate soil and rock sites while RSS and HVRSR yield better signatures. The results also support the implemented site classification in the light of strong ground-motion spectral attributes observed in different parts of the globe. © 2013 Elsevier Ltd.

  8. What factors influence community-dwelling older people’s intent to undertake multifactorial fall prevention programs?

    Directory of Open Access Journals (Sweden)

    Hill KD

    2014-11-01

    Full Text Available Keith D Hill,1,2 Lesley Day,3 Terry P Haines4,5 1School of Physiotherapy and Exercise Science, Faculty of Health Sciences, Curtin University, Perth, WA, Australia; 2National Ageing Research Institute, Royal Melbourne Hospital, Parkville, VIC, Australia; 3Falls Prevention Research Unit, Monash Injury Research Institute, Monash University, VIC, Australia; 4Allied Health Research Unit, Southern Health, Cheltenham, VIC, Australia; 5Physiotherapy Department, Faculty of Medicine, Nursing, and Health Sciences, Monash University, VIC, Australia Purpose: To investigate previous, current, or planned participation in, and perceptions toward, multifactorial fall prevention programs such as those delivered through a falls clinic in the community setting, and to identify factors influencing older people’s intent to undertake these interventions.Design and methods: Community-dwelling people aged >70 years completed a telephone survey. Participants were randomly selected from an electronic residential telephone listing, but purposeful sampling was used to include equal numbers with and without common chronic health conditions associated with fall-related hospitalization. The survey included scenarios for fall prevention interventions, including assessment/multifactorial interventions, such as those delivered through a falls clinic. Participants were asked about previous exposure to, or intent to participate in, the interventions. A path model analysis was used to identify factors associated with intent to participate in assessment/multifactorial interventions.Results: Thirty of 376 participants (8.0% reported exposure to a multifactorial falls clinic-type intervention in the past 5 years, and 16.0% expressed intention to undertake this intervention. Of the 132 participants who reported one or more falls in the past 12 months, over one-third were undecided or disagreed that a falls clinic type of intervention would be of benefit to them. Four elements

  9. Hand eczema classification

    DEFF Research Database (Denmark)

    Diepgen, T L; Andersen, Klaus Ejner; Brandao, F M

    2008-01-01

    of the disease is rarely evidence based, and a classification system for different subdiagnoses of hand eczema is not agreed upon. Randomized controlled trials investigating the treatment of hand eczema are called for. For this, as well as for clinical purposes, a generally accepted classification system...... A classification system for hand eczema is proposed. Conclusions It is suggested that this classification be used in clinical work and in clinical trials....

  10. River floodplain vegetation classification using multi-temporal high-resolution colour infrared UAV imagery.

    NARCIS (Netherlands)

    van Iersel, W.K.; Straatsma, M.W.; Addink, E.A.; Middelkoop, H.

    2016-01-01

    To evaluate floodplain functioning, monitoring of its vegetation is essential. Although airborne imagery is widely applied for this purpose, classification accuracy (CA) remains low for grassland (< 88%) and herbaceous vegetation (<57%) due to the spectral and structural similarity of these

  11. An Object-Oriented Classification Method on High Resolution Satellite Data

    National Research Council Canada - National Science Library

    Xiaoxia, Sun; Jixian, Zhang; Zhengjun, Liu

    2004-01-01

    .... Thereby only the spectral information is used for the classification. High spatial resolution sensors involves a general increase of spatial information and the accuracy of results may decrease on a per-pixel basis...

  12. Classifications of PSN J03034759+0024146 and CSS141123:091002+521856

    Science.gov (United States)

    Shivvers, I.; Filippenko, A. V.

    2014-11-01

    We report the spectral classification of two optical transients. Spectra of these objects (range 330-1000 nm) were obtained on November 26 UT with the 3-m Shane reflector (+ Kast) at Lick Observatory.

  13. Spectral Ensemble Kalman Filters

    Czech Academy of Sciences Publication Activity Database

    Mandel, Jan; Kasanický, Ivan; Vejmelka, Martin; Fuglík, Viktor; Turčičová, Marie; Eben, Kryštof; Resler, Jaroslav; Juruš, Pavel

    2014-01-01

    Roč. 11, - (2014), EMS2014-446 [EMS Annual Meeting /14./ & European Conference on Applied Climatology (ECAC) /10./. 06.10.2014-10.10.2014, Prague] R&D Projects: GA ČR GA13-34856S Grant - others:NSF DMS-1216481 Institutional support: RVO:67985807 Keywords : data assimilation * spectral filter Subject RIV: DG - Athmosphere Sciences, Meteorology

  14. Mechanical spectral shift reactor

    International Nuclear Information System (INIS)

    Sherwood, D.G.; Wilson, J.F.; Salton, R.B.; Fensterer, H.F.

    1981-01-01

    A mechanical spectral shift reactor comprises apparatus for inserting and withdrawing water displacer elements from the reactor core for selectively changing the water-moderator volume in the core thereby changing the reactivity of the core. The apparatus includes drivemechanisms for moving the displacer elements relative to the core and guide mechanisms for guiding the displayer rods through the reactor vessel

  15. Mechanical spectral shift reactor

    International Nuclear Information System (INIS)

    Sherwood, D.G.; Wilson, J.F.; Salton, R.B.; Fensterer, H.F.

    1982-01-01

    A mechanical spectral shift reactor comprises apparatus for inserting and withdrawing water displacer elements from the reactor core for selectively changing the water-moderator volume in the core thereby changing the reactivity of the core. The apparatus includes drive mechanisms for moving the displacer elements relative to the core and guide mechanisms for guiding the displacer rods through the reactor vessel. (author)

  16. AUTOMATIC APPROACH TO VHR SATELLITE IMAGE CLASSIFICATION

    Directory of Open Access Journals (Sweden)

    P. Kupidura

    2016-06-01

    Full Text Available In this paper, we present a proposition of a fully automatic classification of VHR satellite images. Unlike the most widespread approaches: supervised classification, which requires prior defining of class signatures, or unsupervised classification, which must be followed by an interpretation of its results, the proposed method requires no human intervention except for the setting of the initial parameters. The presented approach bases on both spectral and textural analysis of the image and consists of 3 steps. The first step, the analysis of spectral data, relies on NDVI values. Its purpose is to distinguish between basic classes, such as water, vegetation and non-vegetation, which all differ significantly spectrally, thus they can be easily extracted basing on spectral analysis. The second step relies on granulometric maps. These are the product of local granulometric analysis of an image and present information on the texture of each pixel neighbourhood, depending on the texture grain. The purpose of texture analysis is to distinguish between different classes, spectrally similar, but yet of different texture, e.g. bare soil from a built-up area, or low vegetation from a wooded area. Due to the use of granulometric analysis, based on mathematical morphology opening and closing, the results are resistant to the border effect (qualifying borders of objects in an image as spaces of high texture, which affect other methods of texture analysis like GLCM statistics or fractal analysis. Therefore, the effectiveness of the analysis is relatively high. Several indices based on values of different granulometric maps have been developed to simplify the extraction of classes of different texture. The third and final step of the process relies on a vegetation index, based on near infrared and blue bands. Its purpose is to correct partially misclassified pixels. All the indices used in the classification model developed relate to reflectance values, so the

  17. Classification with support hyperplanes

    NARCIS (Netherlands)

    G.I. Nalbantov (Georgi); J.C. Bioch (Cor); P.J.F. Groenen (Patrick)

    2006-01-01

    textabstractA new classification method is proposed, called Support Hy- perplanes (SHs). To solve the binary classification task, SHs consider the set of all hyperplanes that do not make classification mistakes, referred to as semi-consistent hyperplanes. A test object is classified using

  18. Standard classification: Physics

    International Nuclear Information System (INIS)

    1977-01-01

    This is a draft standard classification of physics. The conception is based on the physics part of the systematic catalogue of the Bayerische Staatsbibliothek and on the classification given in standard textbooks. The ICSU-AB classification now used worldwide by physics information services was not taken into account. (BJ) [de

  19. Image Classification Workflow Using Machine Learning Methods

    Science.gov (United States)

    Christoffersen, M. S.; Roser, M.; Valadez-Vergara, R.; Fernández-Vega, J. A.; Pierce, S. A.; Arora, R.

    2016-12-01

    Recent increases in the availability and quality of remote sensing datasets have fueled an increasing number of scientifically significant discoveries based on land use classification and land use change analysis. However, much of the software made to work with remote sensing data products, specifically multispectral images, is commercial and often prohibitively expensive. The free to use solutions that are currently available come bundled up as small parts of much larger programs that are very susceptible to bugs and difficult to install and configure. What is needed is a compact, easy to use set of tools to perform land use analysis on multispectral images. To address this need, we have developed software using the Python programming language with the sole function of land use classification and land use change analysis. We chose Python to develop our software because it is relatively readable, has a large body of relevant third party libraries such as GDAL and Spectral Python, and is free to install and use on Windows, Linux, and Macintosh operating systems. In order to test our classification software, we performed a K-means unsupervised classification, Gaussian Maximum Likelihood supervised classification, and a Mahalanobis Distance based supervised classification. The images used for testing were three Landsat rasters of Austin, Texas with a spatial resolution of 60 meters for the years of 1984 and 1999, and 30 meters for the year 2015. The testing dataset was easily downloaded using the Earth Explorer application produced by the USGS. The software should be able to perform classification based on any set of multispectral rasters with little to no modification. Our software makes the ease of land use classification using commercial software available without an expensive license.

  20. A Simple Spectral Observer

    Directory of Open Access Journals (Sweden)

    Lizeth Torres

    2018-05-01

    Full Text Available The principal aim of a spectral observer is twofold: the reconstruction of a signal of time via state estimation and the decomposition of such a signal into the frequencies that make it up. A spectral observer can be catalogued as an online algorithm for time-frequency analysis because is a method that can compute on the fly the Fourier transform (FT of a signal, without having the entire signal available from the start. In this regard, this paper presents a novel spectral observer with an adjustable constant gain for reconstructing a given signal by means of the recursive identification of the coefficients of a Fourier series. The reconstruction or estimation of a signal in the context of this work means to find the coefficients of a linear combination of sines a cosines that fits a signal such that it can be reproduced. The design procedure of the spectral observer is presented along with the following applications: (1 the reconstruction of a simple periodical signal, (2 the approximation of both a square and a triangular signal, (3 the edge detection in signals by using the Fourier coefficients, (4 the fitting of the historical Bitcoin market data from 1 December 2014 to 8 January 2018 and (5 the estimation of a input force acting upon a Duffing oscillator. To round out this paper, we present a detailed discussion about the results of the applications as well as a comparative analysis of the proposed spectral observer vis-à-vis the Short Time Fourier Transform (STFT, which is a well-known method for time-frequency analysis.

  1. Identification of Preferred Sources of Information for Undertaking Studies in the Faculty of Engineering Management at Poznan University of Technology

    Directory of Open Access Journals (Sweden)

    Magdalena Wyrwicka

    2015-06-01

    Full Text Available Since 2010 a survey has been conducted among first-year students about sources of information which influence the decision of undertaking field studies in Safety Engineering, Management Engineering and Logistics in the Faculty of Engineering Management at Poznan University of Technology. The goal of these analyses is both to assess the effectiveness of promotion and also show trends in the use of diverse channels of information transfer of studies. The results of the investigation show that internet promotion via university and faculty website plays the dominant role but also direct promotion, such as opinion of older friends, is crucial. Furthermore, from year to year the analyses indicate the significant increase of official media and reveal that the prospective students rely on a few sources of information simultaneously.

  2. Verification of pharmacogenetics-based warfarin dosing algorithms in Han-Chinese patients undertaking mechanic heart valve replacement.

    Science.gov (United States)

    Zhao, Li; Chen, Chunxia; Li, Bei; Dong, Li; Guo, Yingqiang; Xiao, Xijun; Zhang, Eryong; Qin, Li

    2014-01-01

    To study the performance of pharmacogenetics-based warfarin dosing algorithms in the initial and the stable warfarin treatment phases in a cohort of Han-Chinese patients undertaking mechanic heart valve replacement. We searched PubMed, Chinese National Knowledge Infrastructure and Wanfang databases for selecting pharmacogenetics-based warfarin dosing models. Patients with mechanic heart valve replacement were consecutively recruited between March 2012 and July 2012. The predicted warfarin dose of each patient was calculated and compared with the observed initial and stable warfarin doses. The percentage of patients whose predicted dose fell within 20% of their actual therapeutic dose (percentage within 20%), and the mean absolute error (MAE) were utilized to evaluate the predictive accuracy of all the selected algorithms. A total of 8 algorithms including Du, Huang, Miao, Wei, Zhang, Lou, Gage, and International Warfarin Pharmacogenetics Consortium (IWPC) model, were tested in 181 patients. The MAE of the Gage, IWPC and 6 Han-Chinese pharmacogenetics-based warfarin dosing algorithms was less than 0.6 mg/day in accuracy and the percentage within 20% exceeded 45% in all of the selected models in both the initial and the stable treatment stages. When patients were stratified according to the warfarin dose range, all of the equations demonstrated better performance in the ideal-dose range (1.88-4.38 mg/day) than the low-dose range (pharmacogenetics-based warfarin dosing regimens performed similarly in our cohort. However, the algorithms of Wei, Huang, and Miao showed a better potential for warfarin prediction in the initial and the stable treatment phases in Han-Chinese patients undertaking mechanic heart valve replacement.

  3. Verification of Pharmacogenetics-Based Warfarin Dosing Algorithms in Han-Chinese Patients Undertaking Mechanic Heart Valve Replacement

    Science.gov (United States)

    Zhao, Li; Chen, Chunxia; Li, Bei; Dong, Li; Guo, Yingqiang; Xiao, Xijun; Zhang, Eryong; Qin, Li

    2014-01-01

    Objective To study the performance of pharmacogenetics-based warfarin dosing algorithms in the initial and the stable warfarin treatment phases in a cohort of Han-Chinese patients undertaking mechanic heart valve replacement. Methods We searched PubMed, Chinese National Knowledge Infrastructure and Wanfang databases for selecting pharmacogenetics-based warfarin dosing models. Patients with mechanic heart valve replacement were consecutively recruited between March 2012 and July 2012. The predicted warfarin dose of each patient was calculated and compared with the observed initial and stable warfarin doses. The percentage of patients whose predicted dose fell within 20% of their actual therapeutic dose (percentage within 20%), and the mean absolute error (MAE) were utilized to evaluate the predictive accuracy of all the selected algorithms. Results A total of 8 algorithms including Du, Huang, Miao, Wei, Zhang, Lou, Gage, and International Warfarin Pharmacogenetics Consortium (IWPC) model, were tested in 181 patients. The MAE of the Gage, IWPC and 6 Han-Chinese pharmacogenetics-based warfarin dosing algorithms was less than 0.6 mg/day in accuracy and the percentage within 20% exceeded 45% in all of the selected models in both the initial and the stable treatment stages. When patients were stratified according to the warfarin dose range, all of the equations demonstrated better performance in the ideal-dose range (1.88–4.38 mg/day) than the low-dose range (warfarin dose prediction and in the low-dose and the ideal-dose ranges. Conclusions All of the selected pharmacogenetics-based warfarin dosing regimens performed similarly in our cohort. However, the algorithms of Wei, Huang, and Miao showed a better potential for warfarin prediction in the initial and the stable treatment phases in Han-Chinese patients undertaking mechanic heart valve replacement. PMID:24728385

  4. Classification of refrigerants; Classification des fluides frigorigenes

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2001-07-01

    This document was made from the US standard ANSI/ASHRAE 34 published in 2001 and entitled 'designation and safety classification of refrigerants'. This classification allows to clearly organize in an international way the overall refrigerants used in the world thanks to a codification of the refrigerants in correspondence with their chemical composition. This note explains this codification: prefix, suffixes (hydrocarbons and derived fluids, azeotropic and non-azeotropic mixtures, various organic compounds, non-organic compounds), safety classification (toxicity, flammability, case of mixtures). (J.S.)

  5. On the Use of Complementary Spectral Features for Speaker Recognition

    Directory of Open Access Journals (Sweden)

    Sridhar Krishnan

    2007-12-01

    Full Text Available The most popular features for speaker recognition are Mel frequency cepstral coefficients (MFCCs and linear prediction cepstral coefficients (LPCCs. These features are used extensively because they characterize the vocal tract configuration which is known to be highly speaker-dependent. In this work, several features are introduced that can characterize the vocal system in order to complement the traditional features and produce better speaker recognition models. The spectral centroid (SC, spectral bandwidth (SBW, spectral band energy (SBE, spectral crest factor (SCF, spectral flatness measure (SFM, Shannon entropy (SE, and Renyi entropy (RE were utilized for this purpose. This work demonstrates that these features are robust in noisy conditions by simulating some common distortions that are found in the speakers' environment and a typical telephone channel. Babble noise, additive white Gaussian noise (AWGN, and a bandpass channel with 1 dB of ripple were used to simulate these noisy conditions. The results show significant improvements in classification performance for all noise conditions when these features were used to complement the MFCC and ΔMFCC features. In particular, the SC and SCF improved performance in almost all noise conditions within the examined SNR range (10–40 dB. For example, in cases where there was only one source of distortion, classification improvements of up to 8% and 10% were achieved under babble noise and AWGN, respectively, using the SCF feature.

  6. Behavioral state classification in epileptic brain using intracranial electrophysiology

    Science.gov (United States)

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

    2017-04-01

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

  7. Experimental study on multi-sub-classifier for land cover classification: a case study in Shangri-La, China

    Science.gov (United States)

    Wang, Yan-ying; Wang, Jin-liang; Wang, Ping; Hu, Wen-yin; Su, Shao-hua

    2015-12-01

    High accuracy remote sensed image classification technology is a long-term and continuous pursuit goal of remote sensing applications. In order to evaluate single classification algorithm accuracy, take Landsat TM image as data source, Northwest Yunnan as study area, seven types of land cover classification like Maximum Likelihood Classification has been tested, the results show that: (1)the overall classification accuracy of Maximum Likelihood Classification(MLC), Artificial Neural Network Classification(ANN), Minimum Distance Classification(MinDC) is higher, which is 82.81% and 82.26% and 66.41% respectively; the overall classification accuracy of Parallel Hexahedron Classification(Para), Spectral Information Divergence Classification(SID), Spectral Angle Classification(SAM) is low, which is 37.29%, 38.37, 53.73%, respectively. (2) from each category classification accuracy: although the overall accuracy of the Para is the lowest, it is much higher on grasslands, wetlands, forests, airport land, which is 89.59%, 94.14%, and 89.04%, respectively; the SAM, SID are good at forests classification with higher overall classification accuracy, which is 89.8% and 87.98%, respectively. Although the overall classification accuracy of ANN is very high, the classification accuracy of road, rural residential land and airport land is very low, which is 10.59%, 11% and 11.59% respectively. Other classification methods have their advantages and disadvantages. These results show that, under the same conditions, the same images with different classification methods to classify, there will be a classifier to some features has higher classification accuracy, a classifier to other objects has high classification accuracy, and therefore, we may select multi sub-classifier integration to improve the classification accuracy.

  8. Classification, disease, and diagnosis.

    Science.gov (United States)

    Jutel, Annemarie

    2011-01-01

    Classification shapes medicine and guides its practice. Understanding classification must be part of the quest to better understand the social context and implications of diagnosis. Classifications are part of the human work that provides a foundation for the recognition and study of illness: deciding how the vast expanse of nature can be partitioned into meaningful chunks, stabilizing and structuring what is otherwise disordered. This article explores the aims of classification, their embodiment in medical diagnosis, and the historical traditions of medical classification. It provides a brief overview of the aims and principles of classification and their relevance to contemporary medicine. It also demonstrates how classifications operate as social framing devices that enable and disable communication, assert and refute authority, and are important items for sociological study.

  9. JET joint undertaking

    International Nuclear Information System (INIS)

    1984-06-01

    JET began operations on 25 June 1983. This annual report contains administrative information and a general review of scientific and technical developments. Among them are vacuum systems, toroidal and poloidal field systems, power supplies, neutral beam heating, radiofrequency heating, remote handling, tritium handling, control and data acquisition systems and diagnostic systems

  10. JET Joint Undertaking

    International Nuclear Information System (INIS)

    Keen, B.E.; Kupschus, P.

    1984-09-01

    The report is in sections, as follows. (1) Introduction and summary. (2) A brief description of the origins of the JET Project within the EURATOM fusion programme and the objectives and aims of the device. The basic JET design and the overall philosophy of operation are explained and the first six months of operation of the machine are summarised. The Project Team Structure adopted for the Operation Phase is set out. Finally, in order to set JET's progress in context, other large tokamaks throughout the world and their achievements are briefly described. (3) The activities and progress within the Operation and Development Department are set out; particularly relating to its responsibilities for the operation and maintenance of the tokamak and for developing the necessary engineering equipment to enhance the machine to full performance. (4) The activities and progress within the Scientific Department are described; particularly relating to the specification, procurement and operation of diagnostic equipment; definition and execution of the programme; and the interpretation of experimental results. (5) JET's programme plans for the immediate future and a broad outline of the JET Development Plan to 1990 are given. (author)

  11. JET Joint Undertaking

    International Nuclear Information System (INIS)

    Keen, B.E.

    1986-03-01

    This is an overview summary of the scientific and technical advances at JET during the year 1985, supplemented by appendices of detailed contributions (in preprint form) of eight of the more important JET articles produced during that year. It is aimed not only at specialists and experts but also at a more general scientific community. Thus there is a brief summary of the background to the project, a description of the basic objectives of JET and the principle design features of the machine. The new structure of the Project Team is also explained. Developments and future plans are included. Improvements considered are those which are designed to overcome certain limitations encountered generally on Tokamaks, particularly those concerned with density limits, with plasma MHD behaviour, with impurities and with plasma transport. There is also a complete list of articles, reports and conference papers published in 1985 - there are 167 such items listed. (UK)

  12. JET Joint Undertaking

    International Nuclear Information System (INIS)

    Keen, B.E.

    1988-03-01

    The paper is a JET progress report 1987, and covers the fourth full year of JET's operation. The report contains an overview summary of the scientific and technical advances during the year, and is supplemented by appendices of detailed contributions of the more important JET articles published during 1987. The document is aimed at specialists and experts engaged in nuclear fusion and plasma physics, as well as the general scientific community. (U.K.)

  13. Spectral identification of plant communities for mapping of semi-natural grasslands

    DEFF Research Database (Denmark)

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

    2000-01-01

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

  14. Hybrid spectral CT reconstruction.

    Directory of Open Access Journals (Sweden)

    Darin P Clark

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

  15. Hybrid spectral CT reconstruction

    Science.gov (United States)

    Clark, Darin P.

    2017-01-01

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

  16. Noncommutativity from spectral flow

    Energy Technology Data Exchange (ETDEWEB)

    Heinzl, Thomas; Ilderton, Anton [School of Mathematics and Statistics, University of Plymouth, Drake Circus, Plymouth PL4 8AA (United Kingdom)

    2007-07-27

    We investigate the transition from second- to first-order systems. Quantum mechanically, this transforms configuration space into phase space and hence introduces noncommutativity in the former. This transition may be described in terms of spectral flow. Gaps in the energy or mass spectrum may become large which effectively truncates the available state space. Using both operator and path integral languages we explicitly discuss examples in quantum mechanics (light-front) quantum field theory and string theory.

  17. Mechanical spectral shift reactor

    International Nuclear Information System (INIS)

    Wilson, J.F.; Sherwood, D.G.

    1982-01-01

    A mechanical spectral shift reactor comprises a reactive core having fuel assemblies accommodating both water displacer elements and neutron absorbing control rods for selectively changing the volume of water-moderator in the core. The fuel assemblies with displacer and control rods are arranged in alternating fashion so that one displacer element drive mechanism may move displacer elements in more than one fuel assembly without interfering with the movement of control rods of a corresponding control rod drive mechanisms. (author)

  18. Speech recognition from spectral dynamics

    Indian Academy of Sciences (India)

    Carrier nature of speech; modulation spectrum; spectral dynamics ... the relationships between phonetic values of sounds and their short-term spectral envelopes .... the number of free parameters that need to be estimated from training data.

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

    Directory of Open Access Journals (Sweden)

    L. Pompilio

    2006-06-01

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

  20. Security classification of information

    Energy Technology Data Exchange (ETDEWEB)

    Quist, A.S.

    1993-04-01

    This document is the second of a planned four-volume work that comprehensively discusses the security classification of information. The main focus of Volume 2 is on the principles for classification of information. Included herein are descriptions of the two major types of information that governments classify for national security reasons (subjective and objective information), guidance to use when determining whether information under consideration for classification is controlled by the government (a necessary requirement for classification to be effective), information disclosure risks and benefits (the benefits and costs of classification), standards to use when balancing information disclosure risks and benefits, guidance for assigning classification levels (Top Secret, Secret, or Confidential) to classified information, guidance for determining how long information should be classified (classification duration), classification of associations of information, classification of compilations of information, and principles for declassifying and downgrading information. Rules or principles of certain areas of our legal system (e.g., trade secret law) are sometimes mentioned to .provide added support to some of those classification principles.

  1. Comparing and optimizing land use classification in a Himalayan area using parametric and non parametric approaches

    NARCIS (Netherlands)

    Sterk, G.; Sameer Saran,; Raju, P.L.N.; Amit, Bharti

    2007-01-01

    Supervised classification is one of important tasks in remote sensing image interpretation, in which the image pixels are classified to various predefined land use/land cover classes based on the spectral reflectance values in different bands. In reality some classes may have very close spectral

  2. Understanding Soliton Spectral Tunneling as a Spectral Coupling Effect

    DEFF Research Database (Denmark)

    Guo, Hairun; Wang, Shaofei; Zeng, Xianglong

    2013-01-01

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

  3. METHODS OF ANALYSIS AND CLASSIFICATION OF THE COMPONENTS OF GRAIN MIXTURES BASED ON MEASURING THE REFLECTION AND TRANSMISSION SPECTRA

    Directory of Open Access Journals (Sweden)

    Artem O. Donskikh*

    2017-10-01

    Full Text Available The paper considers methods of classification of grain mixture components based on spectral analysis in visible and near-infrared wavelength ranges using various measurement approaches - reflection, transmission and combined spectrum methods. It also describes the experimental measuring units used and suggests the prototype of a multispectral grain mixture analyzer. The results of the spectral measurement were processed using neural network based classification algorithms. The probabilities of incorrect recognition for various numbers of spectral parts and combinations of spectral methods were estimated. The paper demonstrates that combined usage of two spectral analysis methods leads to higher classification accuracy and allows for reducing the number of the analyzed spectral parts. A detailed description of the proposed measurement device for high-performance real-time multispectral analysis of the components of grain mixtures is given.

  4. Texture classification of vegetation cover in high altitude wetlands zone

    International Nuclear Information System (INIS)

    Wentao, Zou; Bingfang, Wu; Hongbo, Ju; Hua, Liu

    2014-01-01

    The aim of this study was to investigate the utility of datasets composed of texture measures and other features for the classification of vegetation cover, specifically wetlands. QUEST decision tree classifier was applied to a SPOT-5 image sub-scene covering the typical wetlands area in Three River Sources region in Qinghai province, China. The dataset used for the classification comprised of: (1) spectral data and the components of principal component analysis; (2) texture measures derived from pixel basis; (3) DEM and other ancillary data covering the research area. Image textures is an important characteristic of remote sensing images; it can represent spatial variations with spectral brightness in digital numbers. When the spectral information is not enough to separate the different land covers, the texture information can be used to increase the classification accuracy. The texture measures used in this study were calculated from GLCM (Gray level Co-occurrence Matrix); eight frequently used measures were chosen to conduct the classification procedure. The results showed that variance, mean and entropy calculated by GLCM with a 9*9 size window were effective in distinguishing different vegetation types in wetlands zone. The overall accuracy of this method was 84.19% and the Kappa coefficient was 0.8261. The result indicated that the introduction of texture measures can improve the overall accuracy by 12.05% and the overall kappa coefficient by 0.1407 compared with the result using spectral and ancillary data

  5. Preliminary Research on Grassland Fine-classification Based on MODIS

    International Nuclear Information System (INIS)

    Hu, Z W; Zhang, S; Yu, X Y; Wang, X S

    2014-01-01

    Grassland ecosystem is important for climatic regulation, maintaining the soil and water. Research on the grassland monitoring method could provide effective reference for grassland resource investigation. In this study, we used the vegetation index method for grassland classification. There are several types of climate in China. Therefore, we need to use China's Main Climate Zone Maps and divide the study region into four climate zones. Based on grassland classification system of the first nation-wide grass resource survey in China, we established a new grassland classification system which is only suitable for this research. We used MODIS images as the basic data resources, and use the expert classifier method to perform grassland classification. Based on the 1:1,000,000 Grassland Resource Map of China, we obtained the basic distribution of all the grassland types and selected 20 samples evenly distributed in each type, then used NDVI/EVI product to summarize different spectral features of different grassland types. Finally, we introduced other classification auxiliary data, such as elevation, accumulate temperature (AT), humidity index (HI) and rainfall. China's nation-wide grassland classification map is resulted by merging the grassland in different climate zone. The overall classification accuracy is 60.4%. The result indicated that expert classifier is proper for national wide grassland classification, but the classification accuracy need to be improved

  6. SNSEDextend: SuperNova Spectral Energy Distributions extrapolation toolkit

    Science.gov (United States)

    Pierel, Justin D. R.; Rodney, Steven A.; Avelino, Arturo; Bianco, Federica; Foley, Ryan J.; Friedman, Andrew; Hicken, Malcolm; Hounsell, Rebekah; Jha, Saurabh W.; Kessler, Richard; Kirshner, Robert; Mandel, Kaisey; Narayan, Gautham; Filippenko, Alexei V.; Scolnic, Daniel; Strolger, Louis-Gregory

    2018-05-01

    SNSEDextend extrapolates core-collapse and Type Ia Spectral Energy Distributions (SEDs) into the UV and IR for use in simulations and photometric classifications. The user provides a library of existing SED templates (such as those in the authors' SN SED Repository) along with new photometric constraints in the UV and/or NIR wavelength ranges. The software then extends the existing template SEDs so their colors match the input data at all phases. SNSEDextend can also extend the SALT2 spectral time-series model for Type Ia SN for a "first-order" extrapolation of the SALT2 model components, suitable for use in survey simulations and photometric classification tools; as the code does not do a rigorous re-training of the SALT2 model, the results should not be relied on for precision applications such as light curve fitting for cosmology.

  7. Classification of Flotation Frothers

    Directory of Open Access Journals (Sweden)

    Jan Drzymala

    2018-02-01

    Full Text Available In this paper, a scheme of flotation frothers classification is presented. The scheme first indicates the physical system in which a frother is present and four of them i.e., pure state, aqueous solution, aqueous solution/gas system and aqueous solution/gas/solid system are distinguished. As a result, there are numerous classifications of flotation frothers. The classifications can be organized into a scheme described in detail in this paper. The frother can be present in one of four physical systems, that is pure state, aqueous solution, aqueous solution/gas and aqueous solution/gas/solid system. It results from the paper that a meaningful classification of frothers relies on choosing the physical system and next feature, trend, parameter or parameters according to which the classification is performed. The proposed classification can play a useful role in characterizing and evaluation of flotation frothers.

  8. Classification of Hyperspectral Images Using Kernel Fully Constrained Least Squares

    Directory of Open Access Journals (Sweden)

    Jianjun Liu

    2017-11-01

    Full Text Available As a widely used classifier, sparse representation classification (SRC has shown its good performance for hyperspectral image classification. Recent works have highlighted that it is the collaborative representation mechanism under SRC that makes SRC a highly effective technique for classification purposes. If the dimensionality and the discrimination capacity of a test pixel is high, other norms (e.g., ℓ 2 -norm can be used to regularize the coding coefficients, except for the sparsity ℓ 1 -norm. In this paper, we show that in the kernel space the nonnegative constraint can also play the same role, and thus suggest the investigation of kernel fully constrained least squares (KFCLS for hyperspectral image classification. Furthermore, in order to improve the classification performance of KFCLS by incorporating spatial-spectral information, we investigate two kinds of spatial-spectral methods using two regularization strategies: (1 the coefficient-level regularization strategy, and (2 the class-level regularization strategy. Experimental results conducted on four real hyperspectral images demonstrate the effectiveness of the proposed KFCLS, and show which way to incorporate spatial-spectral information efficiently in the regularization framework.

  9. Research on Remote Sensing Image Classification Based on Feature Level Fusion

    Science.gov (United States)

    Yuan, L.; Zhu, G.

    2018-04-01

    Remote sensing image classification, as an important direction of remote sensing image processing and application, has been widely studied. However, in the process of existing classification algorithms, there still exists the phenomenon of misclassification and missing points, which leads to the final classification accuracy is not high. In this paper, we selected Sentinel-1A and Landsat8 OLI images as data sources, and propose a classification method based on feature level fusion. Compare three kind of feature level fusion algorithms (i.e., Gram-Schmidt spectral sharpening, Principal Component Analysis transform and Brovey transform), and then select the best fused image for the classification experimental. In the classification process, we choose four kinds of image classification algorithms (i.e. Minimum distance, Mahalanobis distance, Support Vector Machine and ISODATA) to do contrast experiment. We use overall classification precision and Kappa coefficient as the classification accuracy evaluation criteria, and the four classification results of fused image are analysed. The experimental results show that the fusion effect of Gram-Schmidt spectral sharpening is better than other methods. In four kinds of classification algorithms, the fused image has the best applicability to Support Vector Machine classification, the overall classification precision is 94.01 % and the Kappa coefficients is 0.91. The fused image with Sentinel-1A and Landsat8 OLI is not only have more spatial information and spectral texture characteristics, but also enhances the distinguishing features of the images. The proposed method is beneficial to improve the accuracy and stability of remote sensing image classification.

  10. Ontologies vs. Classification Systems

    DEFF Research Database (Denmark)

    Madsen, Bodil Nistrup; Erdman Thomsen, Hanne

    2009-01-01

    What is an ontology compared to a classification system? Is a taxonomy a kind of classification system or a kind of ontology? These are questions that we meet when working with people from industry and public authorities, who need methods and tools for concept clarification, for developing meta...... data sets or for obtaining advanced search facilities. In this paper we will present an attempt at answering these questions. We will give a presentation of various types of ontologies and briefly introduce terminological ontologies. Furthermore we will argue that classification systems, e.g. product...... classification systems and meta data taxonomies, should be based on ontologies....

  11. Bio-based Industries Joint Undertaking: The catalyst for sustainable bio-based economic growth in Europe.

    Science.gov (United States)

    Mengal, Philippe; Wubbolts, Marcel; Zika, Eleni; Ruiz, Ana; Brigitta, Dieter; Pieniadz, Agata; Black, Sarah

    2018-01-25

    This article discusses the preparation, structure and objectives of the Bio-based Industries Joint Undertaking (BBI JU). BBI JU is a public-private partnership (PPP) between the European Commission (EC) and the Bio-based Industries Consortium (BIC), the industry-led private not-for-profit organisation representing the private sectors across the bio-based industries. The model of the public-private partnership has been successful as a new approach to supporting research and innovation and de-risking investment in Europe. The BBI JU became a reality in 2014 and represents the largest industrial and economic cooperation endeavour financially ever undertaken in Europe in the area of industrial biotechnologies. It is considered to be one of the most forward-looking initiatives under Horizon 2020 and demonstrates the circular economy in action. The BBI JU will be the catalyst for this strategy to mobilise actors across Europe including large industry, small and medium-sized enterprises (SMEs), all types of research organisations, networks and universities. It will support regions and in doing so, the European Union Member States and associated countries in the implementation of their bioeconomy strategies. Copyright © 2017 Elsevier B.V. All rights reserved.

  12. DETERMINATION OF THE URGENCY OF UNDERTAKING LAND CONSOLIDATION WORKS IN THE VILLAGES OF THE SŁAWNO MUNICIPALITY

    Directory of Open Access Journals (Sweden)

    Przemysław Leń

    2016-09-01

    Full Text Available The object of the paper is to analyze the spatial structure of land and identification of the needs of consolidation works and exchange of land in the villages of the Sławno municipality, lying in the district of Opoczno, in the Łódzkie Voivodship. The authors use the method of zero unitarisation for the purposes of determining the order of undertaking consolidation works and exchange of land in the area of research. The basis for calculation is the database of 19 factors (x1–x19 characteristic for the listed five groups of issues, describing each of the following villages. The obtained results, in a form of synthetic meter for each village, allowed creating the hierarchy of the urgency of carrying out consolidation works. The problem of excessive fragmentation of farms, constituting the collections of a certain number of parcels, in a broader sense, is one of the elements that prevent the acceleration of reforms by conversion of the Land and Buildings Register (EGiB in a full valuable real estate cadastre in Poland. The importance of the problem is highlighted by the fact that there are ecological grounds in the study area, significant from the point of view of environmental protection.

  13. The Level of Anxiety and Depression in Dialysis Patients Undertaking Regular Physical Exercise Training - a Preliminary Study

    Directory of Open Access Journals (Sweden)

    Wioletta Dziubek

    2016-02-01

    Full Text Available Background/Aims: The aim of the study was to evaluate the effects of a six-month physical training undertaken by haemodialysis (HD patients, on the depression and anxiety. Methods: Patients with end stage renal disease (ESRD were recruited from the dialysis station at the Department of Nephrology and Transplantation Medicine in Wroclaw. Physical training took place at the beginning of the first 4-hours of dialysis, three times a week for six months. A personal questionnaire, Beck Depression Inventory (BDI and State-Trait Anxiety Inventory (STAI were used in the study. Results: A total of 28 patients completed the study: 20 were randomised to endurance training and 8 were randomised to resistance training. Statistical analysis of depression and anxiety at the initial (t1 and final examination (t2 indicated a significant reduction in depression and anxiety, particularly anxiety as a trait (X2 in the whole study group. The change in anxiety as a state correlated with the disease duration, duration of dialysis and the initial level of anxiety as a state (t1X1. The change in anxiety as a trait significantly correlated with age and the initial level of anxiety (t1X2. Conclusions: Undertaking physical training during dialysis by patients with ESRD is beneficial in reducing their levels of anxiety and depression. Both resistance and endurance training improves mood, but only endurance training additionally results in anxiety reduction.

  14. Barriers for domestic surrogacy and challenges of transnational surrogacy in the context of Australians undertaking surrogacy in India.

    Science.gov (United States)

    Johnson, Louise; Blyth, Eric; Hammarberg, Karin

    2014-09-01

    The ethical, social, psychological, legal and financial complexities associated with cross-border travel for reproductive services are gaining attention internationally. Travel abroad for surrogacy, and the transfer of gametes or embryos between countries for use in a surrogacy arrangement, can create conflict in relation to the rights of the parties involved: commissioning parents, surrogates and their families, gamete and embryo donors, and children born as a result of the arrangement. Australian surrogacy laws are restrictive and limit access to domestic surrogacy. Despite the introduction of laws in some Australian jurisdictions that penalise residents entering into international commercial surrogacy arrangements, hundreds of Australians resort to surrogacy arrangements in India and other countries each year. This article discusses legislation, policy and practice as they relate to Australians' use of surrogacy in India. It reviews current surrogacy-related legislation and regulation in Australia and India and existing evidence about the challenges posed by transnational surrogacy, and considers how restrictive Australian legislation may contribute to the number of Australians undertaking surrogacy in India.

  15. Exploring the role of social interactions and supports in overcoming accessibility barriers while undertaking health tours in India.

    Science.gov (United States)

    Jana, Arnab; Harata, Noboru; Kiyoshi, Takami; Ohmori, Nobuaki

    2014-01-01

    This article explores the phenomenon of companionship as an adaptation strategy to counter the existing barriers to health care access in developing nations. Companionship is argued to be an outcome of "inter" and "intra" household collaboration to offer diverse supports in addition to altruism. The analysis of the household survey conducted in West Bengal, India, exhibited different patterns of health care tours and the associated dependencies. In addition to support in terms of mobility while traveling and companionship while waiting for the opportunity, support in terms of refuge is also found to be essential, especially for the poor while they undertake regional tours. Causal models focusing on aggregated general health tours and specific regional tours were estimated separately to comprehend the implicit social interactions and their effects on the patient as well as the companions. The research demonstrated that accessibility barriers affect not only the ill, but also those associated with them and at times adversely. Segregation of regional tours illustrated the gaps, which instigated such tours and also might aid in health infrastructure planning as a whole.

  16. The Level of Anxiety and Depression in Dialysis Patients Undertaking Regular Physical Exercise Training--a Preliminary Study.

    Science.gov (United States)

    Dziubek, Wioletta; Kowalska, Joanna; Kusztal, Mariusz; Rogowski, Łukasz; Gołębiowski, Tomasz; Nikifur, Małgorzata; Szczepańska-Gieracha, Joanna; Zembroń-Łacny, Agnieszka; Klinger, Marian; Woźniewski, Marek

    2016-01-01

    The aim of the study was to evaluate the effects of a six-month physical training undertaken by haemodialysis (HD) patients, on the depression and anxiety. Patients with end stage renal disease (ESRD) were recruited from the dialysis station at the Department of Nephrology and Transplantation Medicine in Wroclaw. Physical training took place at the beginning of the first 4-hours of dialysis, three times a week for six months. A personal questionnaire, Beck Depression Inventory (BDI) and State-Trait Anxiety Inventory (STAI) were used in the study. A total of 28 patients completed the study: 20 were randomised to endurance training and 8 were randomised to resistance training. Statistical analysis of depression and anxiety at the initial (t1) and final examination (t2) indicated a significant reduction in depression and anxiety, particularly anxiety as a trait (X2) in the whole study group. The change in anxiety as a state correlated with the disease duration, duration of dialysis and the initial level of anxiety as a state (t1X1). The change in anxiety as a trait significantly correlated with age and the initial level of anxiety (t1X2). Undertaking physical training during dialysis by patients with ESRD is beneficial in reducing their levels of anxiety and depression. Both resistance and endurance training improves mood, but only endurance training additionally results in anxiety reduction. © 2016 S. Karger AG, Basel.

  17. Chinese Anti-Cancer Association as a non-governmental organization undertakes systematic cancer prevention work in China

    Science.gov (United States)

    2015-01-01

    Cancer has become the first leading cause of death in the world, particularly in low- and middle-income countries. Facing the increasing trend of cancer incidence and mortality, China issued and implemented “three-early (early prevention, early diagnosis and early treatment)” national cancer prevention plan. As the main body and dependence of social governance, non-governmental organizations (NGOs) take over the role of government in the field of cancer prevention and treatment. American Cancer Society (ACS) made a research on cancer NGOs and civil society in cancer control and found that cancer NGOs in developing countries mobilize civil society to work together and advocate governments in their countries to develop policies to address the growing cancer burden. Union for International Cancer Control (UICC), Cancer Council Australia (CCA), and Malaysian cancer NGOs are the representatives of cancer NGOs in promoting cancer control. Selecting Chinese Anti-Cancer Association (CACA) as an example in China, this article is to investigate how NGOs undertake systematic cancer prevention work in China. By conducting real case study, we found that, as a NGO, CACA plays a significant role in intensifying the leading role of government in cancer control, optimizing cancer outcomes, decreasing cancer incidence and mortality rates and improving public health. PMID:26361412

  18. Comparison between Possibilistic c-Means (PCM and Artificial Neural Network (ANN Classification Algorithms in Land use/ Land cover Classification

    Directory of Open Access Journals (Sweden)

    Ganchimeg Ganbold

    2017-03-01

    Full Text Available There are several statistical classification algorithms available for landuse/land cover classification. However, each has a certain bias orcompromise. Some methods like the parallel piped approach in supervisedclassification, cannot classify continuous regions within a feature. Onthe other hand, while unsupervised classification method takes maximumadvantage of spectral variability in an image, the maximally separableclusters in spectral space may not do much for our perception of importantclasses in a given study area. In this research, the output of an ANNalgorithm was compared with the Possibilistic c-Means an improvementof the fuzzy c-Means on both moderate resolutions Landsat8 and a highresolution Formosat 2 images. The Formosat 2 image comes with an8m spectral resolution on the multispectral data. This multispectral imagedata was resampled to 10m in order to maintain a uniform ratio of1:3 against Landsat 8 image. Six classes were chosen for analysis including:Dense forest, eucalyptus, water, grassland, wheat and riverine sand. Using a standard false color composite (FCC, the six features reflecteddifferently in the infrared region with wheat producing the brightestpixel values. Signature collection per class was therefore easily obtainedfor all classifications. The output of both ANN and FCM, were analyzedseparately for accuracy and an error matrix generated to assess the qualityand accuracy of the classification algorithms. When you compare theresults of the two methods on a per-class-basis, ANN had a crisperoutput compared to PCM which yielded clusters with pixels especiallyon the moderate resolution Landsat 8 imagery.

  19. On spectral pollution

    International Nuclear Information System (INIS)

    Llobet, X.; Appert, K.; Bondeson, A.; Vaclavik, J.

    1990-01-01

    Finite difference and finite element approximations of eigenvalue problems, under certain circumstances exhibit spectral pollution, i.e. the appearance of eigenvalues that do not converge to the correct value when the mesh density is increased. In the present paper this phenomenon is investigated in a homogeneous case by means of discrete dispersion relations: the polluting modes belong to a branch of the dispersion relation that is strongly distorted by the discretization method employed, or to a new, spurious branch. The analysis is applied to finite difference methods and to finite element methods, and some indications about how to avoiding polluting schemes are given. (author) 5 figs., 10 refs

  20. Mechanical spectral shift reactor

    International Nuclear Information System (INIS)

    Doshi, P.K.; George, R.A.; Dollard, W.J.

    1982-01-01

    A mechanical spectral shift arrangement for controlling a nuclear reactor includes a plurality of reactor coolant displacer members which are inserted into a reactor core at the beginning of the core life to reduce the volume of reactor coolant-moderator in the core at start-up. However, as the reactivity of the core declines with fuel depletion, selected displacer members are withdrawn from the core at selected time intervals to increase core moderation at a time when fuel reactivity is declining. (author)

  1. Spectral signatures of chirality

    DEFF Research Database (Denmark)

    Pedersen, Jesper Goor; Mortensen, Asger

    2009-01-01

    We present a new way of measuring chirality, via the spectral shift of photonic band gaps in one-dimensional structures. We derive an explicit mapping of the problem of oblique incidence of circularly polarized light on a chiral one-dimensional photonic crystal with negligible index contrast...... to the formally equivalent problem of linearly polarized light incident on-axis on a non-chiral structure with index contrast. We derive analytical expressions for the first-order shifts of the band gaps for negligible index contrast. These are modified to give good approximations to the band gap shifts also...

  2. Spectral shift reactor

    International Nuclear Information System (INIS)

    Carlson, W.R.; Piplica, E.J.

    1982-01-01

    A spectral shift pressurized water reactor comprising apparatus for inserting and withdrawing water displacer elements having differing neutron absorbing capabilities for selectively changing the water-moderator volume in the core thereby changing the reactivity of the core. The displacer elements comprise substantially hollow cylindrical low neutron absorbing rods and substantially hollow cylindrical thick walled stainless rods. Since the stainless steel displacer rods have greater neutron absorbing capability, they can effect greater reactivity change per rod. However, by arranging fewer stainless steel displacer rods in a cluster, the reactivity worth of the stainless steel displacer rod cluster can be less than a low neutron absorbing displacer rod cluster. (author)

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

    Science.gov (United States)

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

    2015-04-01

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

  4. Is spectral reflectance of the face a reliable biometric?

    Science.gov (United States)

    Uzair, Muhammad; Mahmood, Arif; Shafait, Faisal; Nansen, Christian; Mian, Ajmal

    2015-06-15

    Over a decade ago, Pan et al. [IEEE TPAMI 25, 1552 (2003)] performed face recognition using only the spectral reflectance of the face at six points and reported around 95% recognition rate. Since their database is private, no one has been able to replicate these results. Moreover, due to the unavailability of public datasets, there has been no detailed study in the literature on the viability of facial spectral reflectance for person identification. In this study, we introduce a new public database of facial spectral reflectance profiles measured with a high precision spectrometer. For each of the 40 subjects, spectral reflectance was measured at the same six points as Pan et al. [IEEE TPAMI 25, 1552 (2003)] in multiple sessions and with time lapse. Furthermore, we sample the facial spectral reflectance from two public hyperspectral face image datasets and analyzed the data using state of the art face classification techniques. The best performing classifier achieved the maximum rank-1 identification rate of 53.8%. We conclude that facial spectral reflectance alone is not a reliable biometric for unconstrained face recognition.

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

    Directory of Open Access Journals (Sweden)

    Ghita Ovidiu

    2011-01-01

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

  6. Active-passive data fusion algorithms for seafloor imaging and classification from CZMIL data

    Science.gov (United States)

    Park, Joong Yong; Ramnath, Vinod; Feygels, Viktor; Kim, Minsu; Mathur, Abhinav; Aitken, Jennifer; Tuell, Grady

    2010-04-01

    CZMIL will simultaneously acquire lidar and passive spectral data. These data will be fused to produce enhanced seafloor reflectance images from each sensor, and combined at a higher level to achieve seafloor classification. In the DPS software, the lidar data will first be processed to solve for depth, attenuation, and reflectance. The depth measurements will then be used to constrain the spectral optimization of the passive spectral data, and the resulting water column estimates will be used recursively to improve the estimates of seafloor reflectance from the lidar. Finally, the resulting seafloor reflectance cube will be combined with texture metrics estimated from the seafloor topography to produce classifications of the seafloor.

  7. Intensity Conserving Spectral Fitting

    Science.gov (United States)

    Klimchuk, J. A.; Patsourakos, S.; Tripathi, D.

    2015-01-01

    The detailed shapes of spectral line profiles provide valuable information about the emitting plasma, especially when the plasma contains an unresolved mixture of velocities, temperatures, and densities. As a result of finite spectral resolution, the intensity measured by a spectrometer is the average intensity across a wavelength bin of non-zero size. It is assigned to the wavelength position at the center of the bin. However, the actual intensity at that discrete position will be different if the profile is curved, as it invariably is. Standard fitting routines (spline, Gaussian, etc.) do not account for this difference, and this can result in significant errors when making sensitive measurements. Detection of asymmetries in solar coronal emission lines is one example. Removal of line blends is another. We have developed an iterative procedure that corrects for this effect. It can be used with any fitting function, but we employ a cubic spline in a new analysis routine called Intensity Conserving Spline Interpolation (ICSI). As the name implies, it conserves the observed intensity within each wavelength bin, which ordinary fits do not. Given the rapid convergence, speed of computation, and ease of use, we suggest that ICSI be made a standard component of the processing pipeline for spectroscopic data.

  8. Knowledge Discovery in Spectral Data by Means of Complex Networks

    Directory of Open Access Journals (Sweden)

    Stefano Boccaletti

    2013-03-01

    Full Text Available In the last decade, complex networks have widely been applied to the study of many natural and man-made systems, and to the extraction of meaningful information from the interaction structures created by genes and proteins. Nevertheless, less attention has been devoted to metabonomics, due to the lack of a natural network representation of spectral data. Here we define a technique for reconstructing networks from spectral data sets, where nodes represent spectral bins, and pairs of them are connected when their intensities follow a pattern associated with a disease. The structural analysis of the resulting network can then be used to feed standard data-mining algorithms, for instance for the classification of new (unlabeled subjects. Furthermore, we show how the structure of the network is resilient to the presence of external additive noise, and how it can be used to extract relevant knowledge about the development of the disease.

  9. [Automatic Classification of Dry Cough and Wet Cough Based on Improved Reverse Mel Frequency Cepstrum Coefficients].

    Science.gov (United States)

    Zhu, Chunmei; Liu, Baojun; Li, Ping; Mo, Hongqiang; Zheng, Zeguang

    2016-04-01

    Automatic classification of different types of cough plays an important role in clinical.In the previous research of cough classification or cough recognition,traditional Mel frequency cepstrum coefficients(MFCC)which extracts feature mainly from low frequency band is usually used as feature expression.In this paper,by analyzing the distributions of spectral energy of dry/wet cough,it is found that spectral difference of two types of cough exits mainly in middle frequency band and high frequency band.To better reflect the spectral difference of dry cough and wet cough,an improved method of extracting reverse MFCC is proposed.In this method,reverse Mel filter-bank in which filters are allocated in reverse Mel scale is adopted and is improved by placing filters only in the frequency band with high spectral energy.As a result,features are mainly extracted from the frequency band where two types of cough show both high spectral energy and distinguished difference.Detailed process of accessing improved reverse MFCC was introduced and hidden Markov models trained by 60 dry cough and 60 wet cough were used as cough classification model.Classification experiment results for 120 dry cough and 85 wet cough showed that,compared to traditional MFCC,better classification performance was achieved by the proposed method and the total classification accuracy was raised from 89.76%to 93.66%.

  10. Classification of radiological procedures

    International Nuclear Information System (INIS)

    1989-01-01

    A classification for departments in Danish hospitals which use radiological procedures. The classification codes consist of 4 digits, where the first 2 are the codes for the main groups. The first digit represents the procedure's topographical object and the second the techniques. The last 2 digits describe individual procedures. (CLS)

  11. Colombia: Territorial classification

    International Nuclear Information System (INIS)

    Mendoza Morales, Alberto

    1998-01-01

    The article is about the approaches of territorial classification, thematic axes, handling principles and territorial occupation, politician and administrative units and administration regions among other topics. Understanding as Territorial Classification the space distribution on the territory of the country, of the geographical configurations, the human communities, the political-administrative units and the uses of the soil, urban and rural, existent and proposed

  12. Munitions Classification Library

    Science.gov (United States)

    2016-04-04

    members of the community to make their own additions to any, or all, of the classification libraries . The next phase entailed data collection over less......Include area code) 04/04/2016 Final Report August 2014 - August 2015 MUNITIONS CLASSIFICATION LIBRARY Mr. Craig Murray, Parsons Dr. Thomas H. Bell, Leidos

  13. Recursive automatic classification algorithms

    Energy Technology Data Exchange (ETDEWEB)

    Bauman, E V; Dorofeyuk, A A

    1982-03-01

    A variational statement of the automatic classification problem is given. The dependence of the form of the optimal partition surface on the form of the classification objective functional is investigated. A recursive algorithm is proposed for maximising a functional of reasonably general form. The convergence problem is analysed in connection with the proposed algorithm. 8 references.

  14. Library Classification 2020

    Science.gov (United States)

    Harris, Christopher

    2013-01-01

    In this article the author explores how a new library classification system might be designed using some aspects of the Dewey Decimal Classification (DDC) and ideas from other systems to create something that works for school libraries in the year 2020. By examining what works well with the Dewey Decimal System, what features should be carried…

  15. Spectroscopic classification of transients

    DEFF Research Database (Denmark)

    Stritzinger, M. D.; Fraser, M.; Hummelmose, N. N.

    2017-01-01

    We report the spectroscopic classification of several transients based on observations taken with the Nordic Optical Telescope (NOT) equipped with ALFOSC, over the nights 23-25 August 2017.......We report the spectroscopic classification of several transients based on observations taken with the Nordic Optical Telescope (NOT) equipped with ALFOSC, over the nights 23-25 August 2017....

  16. Astrophysical Information from Objective Prism Digitized Images: Classification with an Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Bratsolis Emmanuel

    2005-01-01

    Full Text Available Stellar spectral classification is not only a tool for labeling individual stars but is also useful in studies of stellar population synthesis. Extracting the physical quantities from the digitized spectral plates involves three main stages: detection, extraction, and classification of spectra. Low-dispersion objective prism images have been used and automated methods have been developed. The detection and extraction problems have been presented in previous works. In this paper, we present a classification method based on an artificial neural network (ANN. We make a brief presentation of the entire automated system and we compare the new classification method with the previously used method of maximum correlation coefficient (MCC. Digitized photographic material has been used here. The method can also be used on CCD spectral images.

  17. DOE LLW classification rationale

    International Nuclear Information System (INIS)

    Flores, A.Y.

    1991-01-01

    This report was about the rationale which the US Department of Energy had with low-level radioactive waste (LLW) classification. It is based on the Nuclear Regulatory Commission's classification system. DOE site operators met to review the qualifications and characteristics of the classification systems. They evaluated performance objectives, developed waste classification tables, and compiled dose limits on the waste. A goal of the LLW classification system was to allow each disposal site the freedom to develop limits to radionuclide inventories and concentrations according to its own site-specific characteristics. This goal was achieved with the adoption of a performance objectives system based on a performance assessment, with site-specific environmental conditions and engineered disposal systems

  18. Constructing criticality by classification

    DEFF Research Database (Denmark)

    Machacek, Erika

    2017-01-01

    " in the bureaucratic practice of classification: Experts construct material criticality in assessments as they allot information on the materials to the parameters of the assessment framework. In so doing, they ascribe a new set of connotations to the materials, namely supply risk, and their importance to clean energy......, legitimizing a criticality discourse.Specifically, the paper introduces a typology delineating the inferences made by the experts from their produced recommendations in the classification of rare earth element criticality. The paper argues that the classification is a specific process of constructing risk....... It proposes that the expert bureaucratic practice of classification legitimizes (i) the valorisation that was made in the drafting of the assessment framework for the classification, and (ii) political operationalization when enacted that might have (non-)distributive implications for the allocation of public...

  19. Modified DCTNet for audio signals classification

    Science.gov (United States)

    Xian, Yin; Pu, Yunchen; Gan, Zhe; Lu, Liang; Thompson, Andrew

    2016-10-01

    In this paper, we investigate DCTNet for audio signal classification. Its output feature is related to Cohen's class of time-frequency distributions. We introduce the use of adaptive DCTNet (A-DCTNet) for audio signals feature extraction. The A-DCTNet applies the idea of constant-Q transform, with its center frequencies of filterbanks geometrically spaced. The A-DCTNet is adaptive to different acoustic scales, and it can better capture low frequency acoustic information that is sensitive to human audio perception than features such as Mel-frequency spectral coefficients (MFSC). We use features extracted by the A-DCTNet as input for classifiers. Experimental results show that the A-DCTNet and Recurrent Neural Networks (RNN) achieve state-of-the-art performance in bird song classification rate, and improve artist identification accuracy in music data. They demonstrate A-DCTNet's applicability to signal processing problems.

  20. Classifications of objects on hyperspectral images

    DEFF Research Database (Denmark)

    Kucheryavskiy, Sergey

    . In the present work a classification method that combines classic image classification approach and MIA is proposed. The basic idea is to group all pixels and calculate spectral properties of the pixel group to be used further as a vector of predictors for calibration and class prediction. The grouping can...... be done with mathematical morphology methods applied to a score image where objects are well separated. In the case of small overlapping a watershed transformation can be applied to disjoint the objects. The method has been tested on several simulated and real cases and showed good results and significant...... improvements in comparison with a standard MIA approach. The results as well as method details will be reported....

  1. Resumption of menstruation and pituitary response to gonadotropin-releasing hormone in functional hypothalamic amenorrhea subjects undertaking estrogen replacement therapy.

    Science.gov (United States)

    Shen, Z Q; Xu, J J; Lin, J F

    2013-11-01

    Functional hypothalamic amenorrhea (FHA) refers to a functional menstrual disorder with various causes and presentations. Recovery of menstrual cyclicity is common in long-term follow-up but the affecting factors remain unknown. To explore factors affecting the menstrual resumption and to evaluate the pituitary response to gonadotropin-releasing hormone (GnRH) in FHA. Thirty cases with FHA were recruited. All subjects were put on continuous 1 mg/day estradiol valerate orally and followed up monthly. Recovery was defined as the occurrence of at least three consecutive regular cycles. Responder referred to those who recovered within two years of therapy. Gonadotropin response to the 50 μg GnRH challenge was tested every three months. Nineteen (63.3%) subjects recovered with a mean time to recovery of 26.8 months. Time to recovery was negatively correlated with body mass index (BMI) before and by amenorrhea. Twentyone cases had undertaken therapy for more than two years and 10 of them recovered. BMI before and by amenorrhea were negatively correlated with the recovery. Significant increase of serum luteinizing hormone (LH) and LH response to GnRH were noted after recovery. Menstrual resumption was common in FHA undertaking estrogen replacement therapy (ERT). The likelihood of recovery was affected by their BMI before and by amenorrhea but not by the weight gain during therapy. Low serum LH and attenuated LH response to GnRH were the main features of pituitary deficiency in FHA. The menstrual resumption in FHA was accompanied by the recovery of serum LH and the LH response to GnRH.

  2. Building capacity to use and undertake research in health organisations: a survey of training needs and priorities among staff.

    Science.gov (United States)

    Barratt, Helen; Fulop, Naomi J

    2016-12-07

    Efforts to improve healthcare and population health depend partly on the ability of health organisations to use research knowledge and participate in its production. We report the findings of a survey conducted to prioritise training needs among healthcare and public health staff, in relation to the production and implementation of research, across an applied health research collaboration. A questionnaire survey using a validated tool, the Hennessy-Hicks Training Needs Assessment Questionnaire. Participants rated 25 tasks on a five-point scale with regard to both their confidence in performing the task, and its importance to their role. A questionnaire weblink was distributed to a convenience sample of 35 healthcare and public health organisations in London and South East England, with a request that they cascade the information to relevant staff. 203 individuals responded, from 20 healthcare and public health organisations. None. Training needs were identified by comparing median importance and performance scores for each task. Individuals were also invited to describe up to three priority areas in which they require training. Across the study sample, evaluation; teaching; making do with limited resources; coping with change and managing competing demands were identified as key tasks. Assessing the relevance of research and learning about new developments were the most relevant research-related tasks. Participants' training priorities included evaluation; finding, appraising and applying research evidence; and data analysis. Key barriers to involvement included time and resources, as well as a lack of institutional support for undertaking research. We identify areas in which healthcare and public health professionals may benefit from support to facilitate their involvement in and use of applied health research. We also describe barriers to participation and differing perceptions of research between professional groups. Published by the BMJ Publishing Group Limited

  3. VizieR Online Data Catalog: Spectral properties of 441 radio pulsars (Jankowski+, 2018)

    Science.gov (United States)

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

    2018-03-01

    We present spectral parameters for 441 radio pulsars. These were obtained from observations centred at 728, 1382 and 3100MHz using the 10-50cm and the 20cm multibeam receiver at the Parkes radio telescope. In particular, we list the pulsar names (J2000), the calibrated, band-integrated flux densities at 728, 1382 and 3100MHz, the spectral classifications, the frequency ranges the spectral classifications were performed over, the spectral indices for pulsars with simple power-law spectra and the robust modulation indices at all three centre frequencies for pulsars of which we have at least six measurement epochs. The flux density uncertainties include scintillation and a systematic contribution, in addition to the statistical uncertainty. Upper limits are reported at the 3σ level and all other uncertainties at the 1σ level. (1 data file).

  4. Use of UAV-Borne Spectrometer for Land Cover Classification

    Directory of Open Access Journals (Sweden)

    Sowmya Natesan

    2018-04-01

    Full Text Available Unmanned aerial vehicles (UAV are being used for low altitude remote sensing for thematic land classification using visible light and multi-spectral sensors. The objective of this work was to investigate the use of UAV equipped with a compact spectrometer for land cover classification. The UAV platform used was a DJI Flamewheel F550 hexacopter equipped with GPS and Inertial Measurement Unit (IMU navigation sensors, and a Raspberry Pi processor and camera module. The spectrometer used was the FLAME-NIR, a near-infrared spectrometer for hyperspectral measurements. RGB images and spectrometer data were captured simultaneously. As spectrometer data do not provide continuous terrain coverage, the locations of their ground elliptical footprints were determined from the bundle adjustment solution of the captured images. For each of the spectrometer ground ellipses, the land cover signature at the footprint location was determined to enable the characterization, identification, and classification of land cover elements. To attain a continuous land cover classification map, spatial interpolation was carried out from the irregularly distributed labeled spectrometer points. The accuracy of the classification was assessed using spatial intersection with the object-based image classification performed using the RGB images. Results show that in homogeneous land cover, like water, the accuracy of classification is 78% and in mixed classes, like grass, trees and manmade features, the average accuracy is 50%, thus, indicating the contribution of hyperspectral measurements of low altitude UAV-borne spectrometers to improve land cover classification.

  5. Applying aerial digital photography as a spectral remote sensing technique for macrophytic cover assessment in small rural streams

    Science.gov (United States)

    Anker, Y.; Hershkovitz, Y.; Gasith, A.; Ben-Dor, E.

    2011-12-01

    Although remote sensing of fluvial ecosystems is well developed, the tradeoff between spectral and spatial resolutions prevents its application in small streams (habitat scales classifications, acquisition of aerial digital RGB datasets. B. For section scale classification, hyperspectral (HSR) dataset acquisition. C. For calibration, HSR reflectance measurements of specific ground targets, in close proximity to each dataset acquisition swath. D. For habitat scale classification, manual, in-stream flora grid transects classification. The digital RGB datasets were converted to reflectance units by spectral calibration against colored reference plates. These red, green, blue, white, and black EVA foam reference plates were measured by an ASD field spectrometer and each was given a spectral value. Each spectral value was later applied to the spectral calibration and radiometric correction of spectral RGB (SRGB) cube. Spectral calibration of the HSR dataset was done using the empirical line method, based on reference values of progressive grey scale targets. Differentiation between the vegetation species was done by supervised classification both for the HSR and for the SRGB datasets. This procedure was done using the Spectral Angle Mapper function with the spectral pattern of each vegetation species as a spectral end member. Comparison between the two remote sensing techniques and between the SRGB classification and the in-situ transects indicates that: A. Stream vegetation classification resolution is about 4 cm by the SRGB method compared to about 1 m by HSR. Moreover, this resolution is also higher than of the manual grid transect classification. B. The SRGB method is by far the most cost-efficient. The combination of spectral information (rather than the cognitive color) and high spatial resolution of aerial photography provides noise filtration and better sub-water detection capabilities than the HSR technique. C. Only the SRGB method applies for habitat and

  6. Rectangular spectral collocation

    KAUST Repository

    Driscoll, Tobin A.

    2015-02-06

    Boundary conditions in spectral collocation methods are typically imposed by removing some rows of the discretized differential operator and replacing them with others that enforce the required conditions at the boundary. A new approach based upon resampling differentiated polynomials into a lower-degree subspace makes differentiation matrices, and operators built from them, rectangular without any row deletions. Then, boundary and interface conditions can be adjoined to yield a square system. The resulting method is both flexible and robust, and avoids ambiguities that arise when applying the classical row deletion method outside of two-point scalar boundary-value problems. The new method is the basis for ordinary differential equation solutions in Chebfun software, and is demonstrated for a variety of boundary-value, eigenvalue and time-dependent problems.

  7. Spectral evolution of galaxies

    International Nuclear Information System (INIS)

    Rocca-Volmerange, B.

    1989-01-01

    A recent striking event in Observational Cosmology is the discovery of a large population of galaxies at extreme cosmological distances (extended from spectral redshifts ≅ 1 to ≥ 3) corresponding to a lookback time of 80% of the Universe's age. However when galaxies are observed at such remote epochs, their appearances are affected by at least two simultaneous effects which are respectively a cosmological effect and the intrinsic evolution of their stellar populations which appear younger than in our nearby galaxies. The fundamental problem is first to disentangle the respective contributions of these two effects to apparent magnitudes and colors of distant galaxies. Other effects which are likely to modify the appearance of galaxies are amplification by gravitational lensing and interaction with environment will also be considered. (author)

  8. Spectral Line Shapes. Proceedings

    International Nuclear Information System (INIS)

    Zoppi, M.; Ulivi, L.

    1997-01-01

    These proceedings represent papers presented at the 13th International Conference on Spectral Line Shapes which was held in Firenze,Italy from June 16-21, 1996. The topics covered a wide range of subjects emphasizing the physical processes associated with the formation of line profiles: high and low density plasma; atoms and molecules in strong laser fields, Dopple-free and ultra-fine spectroscopy; the line shapes generated by the interaction of neutrals, atoms and molecules, where the relavant quantities are single particle properties, and the interaction-induced spectroscopy. There were 131 papers presented at the conference, out of these, 6 have been abstracted for the Energy Science and Technology database

  9. Ministerial Decree of 15 February 1974 establishing the inventory of qualified experts and physicians authorized to undertake the health physics and medical supervision of protection against ionizing radiations

    International Nuclear Information System (INIS)

    1974-01-01

    This Decree was made in implementation of DPR No. 185 of 13 February 1964 and provides for the legal and administrative acknowledgment of experts and physicians who are required to undertake supervision of protection against the hazards of ionizing radiations. (NEA) [fr

  10. ATR neutron spectral characterization

    Energy Technology Data Exchange (ETDEWEB)

    Rogers, J.W.; Anderl, R.A.

    1995-11-01

    The Advanced Test Reactor (ATR) at INEL provides intense neutron fields for irradiation-effects testing of reactor material samples, for production of radionuclides used in industrial and medical applications, and for scientific research. Characterization of the neutron environments in the irradiation locations of the ATR has been done by means of neutronics calculations and by means of neutron dosimetry based on the use of neutron activation monitors that are placed in the various irradiation locations. The primary purpose of this report is to present the results of an extensive characterization of several ATR irradiation locations based on neutron dosimetry measurements and on least-squares-adjustment analyses that utilize both neutron dosimetry measurements and neutronics calculations. This report builds upon the previous publications, especially the reference 4 paper. Section 2 provides a brief description of the ATR and it tabulates neutron spectral information for typical irradiation locations, as derived from the more historical neutron dosimetry measurements. Relevant details that pertain to the multigroup neutron spectral characterization are covered in section 3. This discussion includes a presentation on the dosimeter irradiation and analyses and a development of the least-squares adjustment methodology, along with a summary of the results of these analyses. Spectrum-averaged cross sections for neutron monitoring and for displacement-damage prediction in Fe, Cr, and Ni are given in section 4. In addition, section4 includes estimates of damage generation rates for these materials in selected ATR irradiation locations. In section 5, the authors present a brief discussion of the most significant conclusions of this work and comment on its relevance to the present ATR core configuration. Finally, detailed numerical and graphical results for the spectrum-characterization analyses in each irradiation location are provided in the Appendix.

  11. Spectral Target Detection using Schroedinger Eigenmaps

    Science.gov (United States)

    Dorado-Munoz, Leidy P.

    Applications of optical remote sensing processes include environmental monitoring, military monitoring, meteorology, mapping, surveillance, etc. Many of these tasks include the detection of specific objects or materials, usually few or small, which are surrounded by other materials that clutter the scene and hide the relevant information. This target detection process has been boosted lately by the use of hyperspectral imagery (HSI) since its high spectral dimension provides more detailed spectral information that is desirable in data exploitation. Typical spectral target detectors rely on statistical or geometric models to characterize the spectral variability of the data. However, in many cases these parametric models do not fit well HSI data that impacts the detection performance. On the other hand, non-linear transformation methods, mainly based on manifold learning algorithms, have shown a potential use in HSI transformation, dimensionality reduction and classification. In target detection, non-linear transformation algorithms are used as preprocessing techniques that transform the data to a more suitable lower dimensional space, where the statistical or geometric detectors are applied. One of these non-linear manifold methods is the Schroedinger Eigenmaps (SE) algorithm that has been introduced as a technique for semi-supervised classification. The core tool of the SE algorithm is the Schroedinger operator that includes a potential term that encodes prior information about the materials present in a scene, and enables the embedding to be steered in some convenient directions in order to cluster similar pixels together. A completely novel target detection methodology based on SE algorithm is proposed for the first time in this thesis. The proposed methodology does not just include the transformation of the data to a lower dimensional space but also includes the definition of a detector that capitalizes on the theory behind SE. The fact that target pixels and

  12. Spectral Theory of Chemical Bonding

    National Research Council Canada - National Science Library

    Langhoff, P. W; Boatz, J. A; Hinde, R. J; Sheehy, J. A

    2004-01-01

    .... Wave function antisymmetry in the aggregate atomic spectral-product basis is enforced by unitary transformation performed subsequent to formation of the Hamiltonian matrix, greatly simplifying its construction...

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

    Science.gov (United States)

    Zhou, Xiao-Hu; Zhou, Ding-Wu

    2009-06-01

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

  14. Oro-facial pain and temporomandibular disorders classification systems: A critical appraisal and future directions.

    Science.gov (United States)

    Klasser, G D; Manfredini, D; Goulet, J-P; De Laat, A

    2018-03-01

    It is a difficult undertaking to design a classification system for any disease entity, let alone for oro-facial pain (OFP) and more specifically for temporomandibular disorders (TMD). A further complication of this task is that both physical and psychosocial variables must be included. To augment this process, a two-step systematic review, adhering to PRISMA guidelines, of the classification systems published during the last 20 years for OFP and TMD was performed. The first search step identified 190 potential citations which ultimately resulted in only 17 articles being included for in-depth analysis and review. The second step resulted in only 5 articles being selected for inclusion in this review. Five additional articles and four classification guidelines/criteria were also included due to expansion of the search criteria. Thus, in total, 14 documents comprising articles and guidelines/criteria (8 proposals of classification systems for OFP; 6 for TMD) were selected for inclusion in the systematic review. For each, a discussion as to their advantages, strengths and limitations was provided. Suggestions regarding the future direction for improving the classification process with the use of ontological principles rather than taxonomy are discussed. Furthermore, the potential for expanding the scope of axes included in existing classification systems, to include genetic, epigenetic and neurobiological variables, is explored. It is therefore recommended that future classification system proposals be based on combined approaches aiming to provide archetypal treatment-oriented classifications. © 2017 John Wiley & Sons Ltd.

  15. Land-Use and Land-Cover Mapping Using a Gradable Classification Method

    Directory of Open Access Journals (Sweden)

    Keigo Kitada

    2012-05-01

    Full Text Available Conventional spectral-based classification methods have significant limitations in the digital classification of urban land-use and land-cover classes from high-resolution remotely sensed data because of the lack of consideration given to the spatial properties of images. To recognize the complex distribution of urban features in high-resolution image data, texture information consisting of a group of pixels should be considered. Lacunarity is an index used to characterize different texture appearances. It is often reported that the land-use and land-cover in urban areas can be effectively classified using the lacunarity index with high-resolution images. However, the applicability of the maximum-likelihood approach for hybrid analysis has not been reported. A more effective approach that employs the original spectral data and lacunarity index can be expected to improve the accuracy of the classification. A new classification procedure referred to as “gradable classification method” is proposed in this study. This method improves the classification accuracy in incremental steps. The proposed classification approach integrates several classification maps created from original images and lacunarity maps, which consist of lacnarity values, to create a new classification map. The results of this study confirm the suitability of the gradable classification approach, which produced a higher overall accuracy (68% and kappa coefficient (0.64 than those (65% and 0.60, respectively obtained with the maximum-likelihood approach.

  16. Land Cover Classification Using ALOS Imagery For Penang, Malaysia

    International Nuclear Information System (INIS)

    Sim, C K; Abdullah, K; MatJafri, M Z; Lim, H S

    2014-01-01

    This paper presents the potential of integrating optical and radar remote sensing data to improve automatic land cover mapping. The analysis involved standard image processing, and consists of spectral signature extraction and application of a statistical decision rule to identify land cover categories. A maximum likelihood classifier is utilized to determine different land cover categories. Ground reference data from sites throughout the study area are collected for training and validation. The land cover information was extracted from the digital data using PCI Geomatica 10.3.2 software package. The variations in classification accuracy due to a number of radar imaging processing techniques are studied. The relationship between the processing window and the land classification is also investigated. The classification accuracies from the optical and radar feature combinations are studied. Our research finds that fusion of radar and optical significantly improved classification accuracies. This study indicates that the land cover/use can be mapped accurately by using this approach

  17. Signal classification using global dynamical models, Part I: Theory

    International Nuclear Information System (INIS)

    Kadtke, J.; Kremliovsky, M.

    1996-01-01

    Detection and classification of signals is one of the principal areas of signal processing, and the utilization of nonlinear information has long been considered as a way of improving performance beyond standard linear (e.g. spectral) techniques. Here, we develop a method for using global models of chaotic dynamical systems theory to define a signal classification processing chain, which is sensitive to nonlinear correlations in the data. We use it to demonstrate classification in high noise regimes (negative SNR), and argue that classification probabilities can be directly computed from ensemble statistics in the model coefficient space. We also develop a modification for non-stationary signals (i.e. transients) using non-autonomous ODEs. In Part II of this paper, we demonstrate the analysis on actual open ocean acoustic data from marine biologics. copyright 1996 American Institute of Physics

  18. Classification of movement disorders.

    Science.gov (United States)

    Fahn, Stanley

    2011-05-01

    The classification of movement disorders has evolved. Even the terminology has shifted, from an anatomical one of extrapyramidal disorders to a phenomenological one of movement disorders. The history of how this shift came about is described. The history of both the definitions and the classifications of the various neurologic conditions is then reviewed. First is a review of movement disorders as a group; then, the evolving classifications for 3 of them--parkinsonism, dystonia, and tremor--are covered in detail. Copyright © 2011 Movement Disorder Society.

  19. A Study of Spectral Integration and Normalization in NMR-based Metabonomic Analyses

    Energy Technology Data Exchange (ETDEWEB)

    Webb-Robertson, Bobbie-Jo M.; Lowry, David F.; Jarman, Kristin H.; Harbo, Sam J.; Meng, Quanxin; Fuciarelli, Alfred F.; Pounds, Joel G.; Lee, Monica T.

    2005-09-15

    Metabonomics involves the quantitation of the dynamic multivariate metabolic response of an organism to a pathological event or genetic modification (Nicholson, Lindon and Holmes, 1999). The analysis of these data involves the use of appropriate multivariate statistical methods. Exploratory Data Analysis (EDA) linear projection methods, primarily Principal Component Analysis (PCA), have been documented as a valuable pattern recognition technique for 1H NMR spectral data (Brindle et al., 2002, Potts et al., 2001, Robertson et al., 2000, Robosky et al., 2002). Prior to PCA the raw data is typically processed through four steps; (1) baseline correction, (2) endogenous peak removal, (3) integration over spectral regions to reduce the number of variables, and (4) normalization. The effect of the size of spectral integration regions and normalization has not been well studied. We assess the variability structure and classification accuracy on two distinctly different datasets via PCA and a leave-one-out cross-validation approach under two normalization approaches and an array of spectral integration regions. This study indicates that independent of the normalization method the classification accuracy achieved from metabonomic studies is not highly sensitive to the size of the spectral integration region. Additionally, both datasets scaled to mean zero and unity variance (auto-scaled) has higher variability within classification accuracy over spectral integration window widths than data scaled to the total intensity of the spectrum.

  20. Classification of Complex Sounds.

    Science.gov (United States)

    1992-10-31

    spectral weights may be useful in developing signal enhancement techniques based on psychological aspects of the listener (providing a complement to...Journals) Green, D.M., and Berg, B.G. (1991). Spectral weights and the profile bowl. Quarterly Journal of Experimental Psychology , 43A, 449-458. Dai, H...Macmillan and C.D. Creelman . Cambridge/NY: Cambridge Universi- ty Press, 1991.) J. Math. Psych., in press. Training Currently, there are two graduate

  1. Update on diabetes classification.

    Science.gov (United States)

    Thomas, Celeste C; Philipson, Louis H

    2015-01-01

    This article highlights the difficulties in creating a definitive classification of diabetes mellitus in the absence of a complete understanding of the pathogenesis of the major forms. This brief review shows the evolving nature of the classification of diabetes mellitus. No classification scheme is ideal, and all have some overlap and inconsistencies. The only diabetes in which it is possible to accurately diagnose by DNA sequencing, monogenic diabetes, remains undiagnosed in more than 90% of the individuals who have diabetes caused by one of the known gene mutations. The point of classification, or taxonomy, of disease, should be to give insight into both pathogenesis and treatment. It remains a source of frustration that all schemes of diabetes mellitus continue to fall short of this goal. Copyright © 2015 Elsevier Inc. All rights reserved.

  2. Learning Apache Mahout classification

    CERN Document Server

    Gupta, Ashish

    2015-01-01

    If you are a data scientist who has some experience with the Hadoop ecosystem and machine learning methods and want to try out classification on large datasets using Mahout, this book is ideal for you. Knowledge of Java is essential.

  3. CLASSIFICATION OF VIRUSES

    Indian Academy of Sciences (India)

    First page Back Continue Last page Overview Graphics. CLASSIFICATION OF VIRUSES. On basis of morphology. On basis of chemical composition. On basis of structure of genome. On basis of mode of replication. Notes:

  4. Pitch Based Sound Classification

    DEFF Research Database (Denmark)

    Nielsen, Andreas Brinch; Hansen, Lars Kai; Kjems, U

    2006-01-01

    A sound classification model is presented that can classify signals into music, noise and speech. The model extracts the pitch of the signal using the harmonic product spectrum. Based on the pitch estimate and a pitch error measure, features are created and used in a probabilistic model with soft......-max output function. Both linear and quadratic inputs are used. The model is trained on 2 hours of sound and tested on publicly available data. A test classification error below 0.05 with 1 s classification windows is achieved. Further more it is shown that linear input performs as well as a quadratic......, and that even though classification gets marginally better, not much is achieved by increasing the window size beyond 1 s....

  5. SPECTRAL ANALYSIS OF EXCHANGE RATES

    Directory of Open Access Journals (Sweden)

    ALEŠA LOTRIČ DOLINAR

    2013-06-01

    Full Text Available Using spectral analysis is very common in technical areas but rather unusual in economics and finance, where ARIMA and GARCH modeling are much more in use. To show that spectral analysis can be useful in determining hidden periodic components for high-frequency finance data as well, we use the example of foreign exchange rates

  6. Towards secondary fingerprint classification

    CSIR Research Space (South Africa)

    Msiza, IS

    2011-07-01

    Full Text Available an accuracy figure of 76.8%. This small difference between the two figures is indicative of the validity of the proposed secondary classification module. Keywords?fingerprint core; fingerprint delta; primary classifi- cation; secondary classification I..., namely, the fingerprint core and the fingerprint delta. Forensically, a fingerprint core is defined as the innermost turning point where the fingerprint ridges form a loop, while the fingerprint delta is defined as the point where these ridges form a...

  7. Expected Classification Accuracy

    Directory of Open Access Journals (Sweden)

    Lawrence M. Rudner

    2005-08-01

    Full Text Available Every time we make a classification based on a test score, we should expect some number..of misclassifications. Some examinees whose true ability is within a score range will have..observed scores outside of that range. A procedure for providing a classification table of..true and expected scores is developed for polytomously scored items under item response..theory and applied to state assessment data. A simplified procedure for estimating the..table entries is also presented.

  8. Latent classification models

    DEFF Research Database (Denmark)

    Langseth, Helge; Nielsen, Thomas Dyhre

    2005-01-01

    parametric family ofdistributions.  In this paper we propose a new set of models forclassification in continuous domains, termed latent classificationmodels. The latent classification model can roughly be seen ascombining the \\NB model with a mixture of factor analyzers,thereby relaxing the assumptions...... classification model, and wedemonstrate empirically that the accuracy of the proposed model issignificantly higher than the accuracy of other probabilisticclassifiers....

  9. 78 FR 68983 - Cotton Futures Classification: Optional Classification Procedure

    Science.gov (United States)

    2013-11-18

    ...-AD33 Cotton Futures Classification: Optional Classification Procedure AGENCY: Agricultural Marketing... regulations to allow for the addition of an optional cotton futures classification procedure--identified and... response to requests from the U.S. cotton industry and ICE, AMS will offer a futures classification option...

  10. EEG BASED COGNITIVE WORKLOAD CLASSIFICATION DURING NASA MATB-II MULTITASKING

    Directory of Open Access Journals (Sweden)

    Sushil Chandra

    2015-06-01

    Full Text Available The objective of this experiment was to determine the best possible input EEG feature for classification of the workload while designing load balancing logic for an automated operator. The input features compared in this study consisted of spectral features of Electroencephalography, objective scoring and subjective scoring. Method utilizes to identify best EEG feature as an input in Neural Network Classifiers for workload classification, to identify channels which could provide classification with the highest accuracy and for identification of EEG feature which could give discrimination among workload level without adding any classifiers. The result had shown Engagement Index is the best feature for neural network classification.

  11. Supernova Photometric Lightcurve Classification

    Science.gov (United States)

    Zaidi, Tayeb; Narayan, Gautham

    2016-01-01

    This is a preliminary report on photometric supernova classification. We first explore the properties of supernova light curves, and attempt to restructure the unevenly sampled and sparse data from assorted datasets to allow for processing and classification. The data was primarily drawn from the Dark Energy Survey (DES) simulated data, created for the Supernova Photometric Classification Challenge. This poster shows a method for producing a non-parametric representation of the light curve data, and applying a Random Forest classifier algorithm to distinguish between supernovae types. We examine the impact of Principal Component Analysis to reduce the dimensionality of the dataset, for future classification work. The classification code will be used in a stage of the ANTARES pipeline, created for use on the Large Synoptic Survey Telescope alert data and other wide-field surveys. The final figure-of-merit for the DES data in the r band was 60% for binary classification (Type I vs II).Zaidi was supported by the NOAO/KPNO Research Experiences for Undergraduates (REU) Program which is funded by the National Science Foundation Research Experiences for Undergraduates Program (AST-1262829).

  12. ULTRAVIOLET RAMAN SPECTRAL SIGNATURE ACQUISITION: UV RAMAN SPECTRAL FINGERPRINTS.

    Energy Technology Data Exchange (ETDEWEB)

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

    2002-09-01

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

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

    Science.gov (United States)

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

    2011-01-01

    Tidal marshes are highly productive ecosystems that support migratory birds as roosting and over-wintering habitats on the Pacific Flyway. Microphytobenthos, or more commonly 'biofilms' contribute significantly to the primary productivity of wetland ecosystems, and provide a substantial food source for macroinvertebrates and avian communities. In this study, biofilms were characterized based on taxonomic classification, density differences, and spectral signatures. These techniques were then applied to remotely sensed images to map biofilm densities and distributions in the South Bay Salt Ponds and predict the carrying capacity of these newly restored ponds for migratory birds. The GER-1500 spectroradiometer was used to obtain in situ spectral signatures for each density-class of biofilm. The spectral variation and taxonomic classification between high, medium, and low density biofilm cover types was mapped using in-situ spectral measurements and classification of EO-1 Hyperion and Landsat TM 5 images. Biofilm samples were also collected in the field to perform laboratory analyses including chlorophyll-a, taxonomic classification, and energy content. Comparison of the spectral signatures between the three density groups shows distinct variations useful for classification. Also, analysis of chlorophyll-a concentrations show statistically significant differences between each density group, using the Tukey-Kramer test at an alpha level of 0.05. The potential carrying capacity in South Bay Salt Ponds is estimated to be 250,000 birds.

  14. Archiving Spectral Libraries in the Planetary Data System

    Science.gov (United States)

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

    2017-12-01

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

  15. APPLICATION OF SENSOR FUSION TO IMPROVE UAV IMAGE CLASSIFICATION

    Directory of Open Access Journals (Sweden)

    S. Jabari

    2017-08-01

    Full Text Available Image classification is one of the most important tasks of remote sensing projects including the ones that are based on using UAV images. Improving the quality of UAV images directly affects the classification results and can save a huge amount of time and effort in this area. In this study, we show that sensor fusion can improve image quality which results in increasing the accuracy of image classification. Here, we tested two sensor fusion configurations by using a Panchromatic (Pan camera along with either a colour camera or a four-band multi-spectral (MS camera. We use the Pan camera to benefit from its higher sensitivity and the colour or MS camera to benefit from its spectral properties. The resulting images are then compared to the ones acquired by a high resolution single Bayer-pattern colour camera (here referred to as HRC. We assessed the quality of the output images by performing image classification tests. The outputs prove that the proposed sensor fusion configurations can achieve higher accuracies compared to the images of the single Bayer-pattern colour camera. Therefore, incorporating a Pan camera on-board in the UAV missions and performing image fusion can help achieving higher quality images and accordingly higher accuracy classification results.

  16. Application of Sensor Fusion to Improve Uav Image Classification

    Science.gov (United States)

    Jabari, S.; Fathollahi, F.; Zhang, Y.

    2017-08-01

    Image classification is one of the most important tasks of remote sensing projects including the ones that are based on using UAV images. Improving the quality of UAV images directly affects the classification results and can save a huge amount of time and effort in this area. In this study, we show that sensor fusion can improve image quality which results in increasing the accuracy of image classification. Here, we tested two sensor fusion configurations by using a Panchromatic (Pan) camera along with either a colour camera or a four-band multi-spectral (MS) camera. We use the Pan camera to benefit from its higher sensitivity and the colour or MS camera to benefit from its spectral properties. The resulting images are then compared to the ones acquired by a high resolution single Bayer-pattern colour camera (here referred to as HRC). We assessed the quality of the output images by performing image classification tests. The outputs prove that the proposed sensor fusion configurations can achieve higher accuracies compared to the images of the single Bayer-pattern colour camera. Therefore, incorporating a Pan camera on-board in the UAV missions and performing image fusion can help achieving higher quality images and accordingly higher accuracy classification results.

  17. A New Classification Approach Based on Multiple Classification Rules

    OpenAIRE

    Zhongmei Zhou

    2014-01-01

    A good classifier can correctly predict new data for which the class label is unknown, so it is important to construct a high accuracy classifier. Hence, classification techniques are much useful in ubiquitous computing. Associative classification achieves higher classification accuracy than some traditional rule-based classification approaches. However, the approach also has two major deficiencies. First, it generates a very large number of association classification rules, especially when t...

  18. Deep learning for tumor classification in imaging mass spectrometry.

    Science.gov (United States)

    Behrmann, Jens; Etmann, Christian; Boskamp, Tobias; Casadonte, Rita; Kriegsmann, Jörg; Maaß, Peter

    2018-04-01

    Tumor classification using imaging mass spectrometry (IMS) data has a high potential for future applications in pathology. Due to the complexity and size of the data, automated feature extraction and classification steps are required to fully process the data. Since mass spectra exhibit certain structural similarities to image data, deep learning may offer a promising strategy for classification of IMS data as it has been successfully applied to image classification. Methodologically, we propose an adapted architecture based on deep convolutional networks to handle the characteristics of mass spectrometry data, as well as a strategy to interpret the learned model in the spectral domain based on a sensitivity analysis. The proposed methods are evaluated on two algorithmically challenging tumor classification tasks and compared to a baseline approach. Competitiveness of the proposed methods is shown on both tasks by studying the performance via cross-validation. Moreover, the learned models are analyzed by the proposed sensitivity analysis revealing biologically plausible effects as well as confounding factors of the considered tasks. Thus, this study may serve as a starting point for further development of deep learning approaches in IMS classification tasks. https://gitlab.informatik.uni-bremen.de/digipath/Deep_Learning_for_Tumor_Classification_in_IMS. jbehrmann@uni-bremen.de or christianetmann@uni-bremen.de. Supplementary data are available at Bioinformatics online.

  19. A comparison of autonomous techniques for multispectral image analysis and classification

    Science.gov (United States)

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

    2012-10-01

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

  20. DETAILED CLASSIFICATION OF SWIFT 'S GAMMA-RAY BURSTS

    International Nuclear Information System (INIS)

    Horvath, I.; Veres, P.; Bagoly, Z.; Balazs, L. G.; De Ugarte Postigo, A.; Meszaros, A.

    2010-01-01

    Earlier classification analyses found three types of gamma-ray bursts (short, long, and intermediate in duration) in the BATSE sample. Recent works have shown that these three groups are also present in the RHESSI and BeppoSAX databases. The duration distribution analysis of the bursts observed by the Swift satellite also favors the three-component model. In this paper, we extend the analysis of the Swift data with spectral information. We show, using the spectral hardness and duration simultaneously, that the maximum likelihood method favors the three-component against the two-component model. The likelihood also shows that a fourth component is not needed.

  1. Land-cover classification in a moist tropical region of Brazil with Landsat TM imagery.

    Science.gov (United States)

    Li, Guiying; Lu, Dengsheng; Moran, Emilio; Hetrick, Scott

    2011-01-01

    This research aims to improve land-cover classification accuracy in a moist tropical region in Brazil by examining the use of different remote sensing-derived variables and classification algorithms. Different scenarios based on Landsat Thematic Mapper (TM) spectral data and derived vegetation indices and textural images, and different classification algorithms - maximum likelihood classification (MLC), artificial neural network (ANN), classification tree analysis (CTA), and object-based classification (OBC), were explored. The results indicated that a combination of vegetation indices as extra bands into Landsat TM multispectral bands did not improve the overall classification performance, but the combination of textural images was valuable for improving vegetation classification accuracy. In particular, the combination of both vegetation indices and textural images into TM multispectral bands improved overall classification accuracy by 5.6% and kappa coefficient by 6.25%. Comparison of the different classification algorithms indicated that CTA and ANN have poor classification performance in this research, but OBC improved primary forest and pasture classification accuracies. This research indicates that use of textural images or use of OBC are especially valuable for improving the vegetation classes such as upland and liana forest classes having complex stand structures and having relatively large patch sizes.

  2. Cancer patients undertaking bone scans in a department of Nuclear Medicine have significant stress related to the examination

    International Nuclear Information System (INIS)

    Sioka, C.; Manetou, M.; Dimakopoulos, N.; Christidi, S.; Kouraklis, G.

    2005-01-01

    Bone scanning is a standard screening procedure for evaluation of metastases in cancer patient. In addition to the staging procedures, bone scan is a valuable test for deciding palliative therapeutic options in selected patients. The aim of this study was to investigate if patients with cancer who were undertaking routine bone scans had any stress related to the test. We asked 83 consecutive patients with various types of cancer if they had anxiety just prior to undergoing the test. Overall, we found that 53 (64%) patients had increased anxiety related to the examination and 30 (36%) patients did not. Among the 53 patients who were anxious about the bone scan, 32 were concerned about the results of the examination, 13 worried about the effects of the radiation, 4 were anxious for both results/radiation, and 4 patients had stress but could not specify the reason. Among the 32 patients who were concerned about the results of the examination, 15 were having their first bone scans, while 17 had already undergone the procedure before. Among the 13 patients who were mainly concerned about the risks of the radiation exposure during the test, 9 were having bone scans for the first time. Out of the 4 patients who feared both the results and radiation, 3 were having bone scans for the first time and 1 had it for several times. Finally, out of the 4 patients who had anxiety about the test but could not identify the reason, 3 were having bone scans for the first time and one had the test before but was claustrophobic. Our findings indicate that most patients (64%) with cancer who underwent a routine bone scan to check for metastatic disease had intense stress related either to the results or the side effects of the examination. However, there were more patients who were concerned about the results of the test rather than the effects of radiation. Among the patients who feared the effects of radioactivity most were having the test for the first time. A previous study in a

  3. Ministerial Decree of 12 May 1980 authorising Agip Nucleare S.p.a. in Rome to undertake health physics and medical supervision of protection against ionizing radiation

    International Nuclear Information System (INIS)

    1980-01-01

    Section 83 of Decree No. 185 of 13 February 1964 on protection against ionizing radiation provides that institutions previously authorised by the Minister of Labour and Social Security may, on condition that they are adequately equipped for such services, be authorised to undertake health physics and medical supervision of personnel. This Decree accordingly authorises the Agip Nucleare Company to carry out this work. (NEA) [fr

  4. Graph-Based Semi-Supervised Hyperspectral Image Classification Using Spatial Information

    Science.gov (United States)

    Jamshidpour, N.; Homayouni, S.; Safari, A.

    2017-09-01

    Hyperspectral image classification has been one of the most popular research areas in the remote sensing community in the past decades. However, there are still some problems that need specific attentions. For example, the lack of enough labeled samples and the high dimensionality problem are two most important issues which degrade the performance of supervised classification dramatically. The main idea of semi-supervised learning is to overcome these issues by the contribution of unlabeled samples, which are available in an enormous amount. In this paper, we propose a graph-based semi-supervised classification method, which uses both spectral and spatial information for hyperspectral image classification. More specifically, two graphs were designed and constructed in order to exploit the relationship among pixels in spectral and spatial spaces respectively. Then, the Laplacians of both graphs were merged to form a weighted joint graph. The experiments were carried out on two different benchmark hyperspectral data sets. The proposed method performed significantly better than the well-known supervised classification methods, such as SVM. The assessments consisted of both accuracy and homogeneity analyses of the produced classification maps. The proposed spectral-spatial SSL method considerably increased the classification accuracy when the labeled training data set is too scarce.When there were only five labeled samples for each class, the performance improved 5.92% and 10.76% compared to spatial graph-based SSL, for AVIRIS Indian Pine and Pavia University data sets respectively.

  5. GRAPH-BASED SEMI-SUPERVISED HYPERSPECTRAL IMAGE CLASSIFICATION USING SPATIAL INFORMATION

    Directory of Open Access Journals (Sweden)

    N. Jamshidpour

    2017-09-01

    Full Text Available Hyperspectral image classification has been one of the most popular research areas in the remote sensing community in the past decades. However, there are still some problems that need specific attentions. For example, the lack of enough labeled samples and the high dimensionality problem are two most important issues which degrade the performance of supervised classification dramatically. The main idea of semi-supervised learning is to overcome these issues by the contribution of unlabeled samples, which are available in an enormous amount. In this paper, we propose a graph-based semi-supervised classification method, which uses both spectral and spatial information for hyperspectral image classification. More specifically, two graphs were designed and constructed in order to exploit the relationship among pixels in spectral and spatial spaces respectively. Then, the Laplacians of both graphs were merged to form a weighted joint graph. The experiments were carried out on two different benchmark hyperspectral data sets. The proposed method performed significantly better than the well-known supervised classification methods, such as SVM. The assessments consisted of both accuracy and homogeneity analyses of the produced classification maps. The proposed spectral-spatial SSL method considerably increased the classification accuracy when the labeled training data set is too scarce.When there were only five labeled samples for each class, the performance improved 5.92% and 10.76% compared to spatial graph-based SSL, for AVIRIS Indian Pine and Pavia University data sets respectively.

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

    DEFF Research Database (Denmark)

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

    2014-01-01

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

  7. Land-cover classification with an expert classification algorithm using digital aerial photographs

    Directory of Open Access Journals (Sweden)

    José L. de la Cruz

    2010-05-01

    Full Text Available The purpose of this study was to evaluate the usefulness of the spectral information of digital aerial sensors in determining land-cover classification using new digital techniques. The land covers that have been evaluated are the following, (1 bare soil, (2 cereals, including maize (Zea mays L., oats (Avena sativa L., rye (Secale cereale L., wheat (Triticum aestivum L. and barley (Hordeun vulgare L., (3 high protein crops, such as peas (Pisum sativum L. and beans (Vicia faba L., (4 alfalfa (Medicago sativa L., (5 woodlands and scrublands, including holly oak (Quercus ilex L. and common retama (Retama sphaerocarpa L., (6 urban soil, (7 olive groves (Olea europaea L. and (8 burnt crop stubble. The best result was obtained using an expert classification algorithm, achieving a reliability rate of 95%. This result showed that the images of digital airborne sensors hold considerable promise for the future in the field of digital classifications because these images contain valuable information that takes advantage of the geometric viewpoint. Moreover, new classification techniques reduce problems encountered using high-resolution images; while reliabilities are achieved that are better than those achieved with traditional methods.

  8. Spectral and correlation analysis of soft X-ray signals from the Joint European Torus tokamak

    International Nuclear Information System (INIS)

    Karlsson, J.; Pazsit, I.

    1997-01-01

    Tomographic methods applied to soft X-rays emitted from a fusion plasma have long been used to diagnose and interpret magnetohydrodynamic and other plasma activities. However, fluctuation analysis has recently been proposed as a complementary method to tomography. The novelty of the suggested method is that the various modes can be determined without tomographic inversion. This paper reports on the results of correlation and spectral analysis of soft X-ray data. The seven measurements analyzed were made by the Joint European Torus (JET) Joint Undertaking using their old soft X-ray measurement system. Auto power spectral densities and phase relations were evaluated from the measured signals as functions of the lines of sight. The fundamental mode m=n=1 was identified in several measurements. The corresponding frequency and toroidal rotation velocity were determined. Higher order modes were also observed and identified. Furthermore, simple model calculations were performed and the results compared with evaluated auto-spectra. (orig.)

  9. Cellular image classification

    CERN Document Server

    Xu, Xiang; Lin, Feng

    2017-01-01

    This book introduces new techniques for cellular image feature extraction, pattern recognition and classification. The authors use the antinuclear antibodies (ANAs) in patient serum as the subjects and the Indirect Immunofluorescence (IIF) technique as the imaging protocol to illustrate the applications of the described methods. Throughout the book, the authors provide evaluations for the proposed methods on two publicly available human epithelial (HEp-2) cell datasets: ICPR2012 dataset from the ICPR'12 HEp-2 cell classification contest and ICIP2013 training dataset from the ICIP'13 Competition on cells classification by fluorescent image analysis. First, the reading of imaging results is significantly influenced by one’s qualification and reading systems, causing high intra- and inter-laboratory variance. The authors present a low-order LP21 fiber mode for optical single cell manipulation and imaging staining patterns of HEp-2 cells. A focused four-lobed mode distribution is stable and effective in optical...

  10. Bosniak classification system

    DEFF Research Database (Denmark)

    Graumann, Ole; Osther, Susanne Sloth; Karstoft, Jens

    2016-01-01

    BACKGROUND: The Bosniak classification was originally based on computed tomographic (CT) findings. Magnetic resonance (MR) and contrast-enhanced ultrasonography (CEUS) imaging may demonstrate findings that are not depicted at CT, and there may not always be a clear correlation between the findings...... at MR and CEUS imaging and those at CT. PURPOSE: To compare diagnostic accuracy of MR, CEUS, and CT when categorizing complex renal cystic masses according to the Bosniak classification. MATERIAL AND METHODS: From February 2011 to June 2012, 46 complex renal cysts were prospectively evaluated by three...... readers. Each mass was categorized according to the Bosniak classification and CT was chosen as gold standard. Kappa was calculated for diagnostic accuracy and data was compared with pathological results. RESULTS: CT images found 27 BII, six BIIF, seven BIII, and six BIV. Forty-three cysts could...

  11. Bosniak Classification system

    DEFF Research Database (Denmark)

    Graumann, Ole; Osther, Susanne Sloth; Karstoft, Jens

    2014-01-01

    Background: The Bosniak classification is a diagnostic tool for the differentiation of cystic changes in the kidney. The process of categorizing renal cysts may be challenging, involving a series of decisions that may affect the final diagnosis and clinical outcome such as surgical management....... Purpose: To investigate the inter- and intra-observer agreement among experienced uroradiologists when categorizing complex renal cysts according to the Bosniak classification. Material and Methods: The original categories of 100 cystic renal masses were chosen as “Gold Standard” (GS), established...... to the calculated weighted κ all readers performed “very good” for both inter-observer and intra-observer variation. Most variation was seen in cysts catagorized as Bosniak II, IIF, and III. These results show that radiologists who evaluate complex renal cysts routinely may apply the Bosniak classification...

  12. Substitution dynamical systems spectral analysis

    CERN Document Server

    Queffélec, Martine

    2010-01-01

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

  13. Spectral characterization of natural backgrounds

    Science.gov (United States)

    Winkelmann, Max

    2017-10-01

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

  14. Classification of objects on hyperspectral images — further developments

    DEFF Research Database (Denmark)

    Kucheryavskiy, Sergey V.; Williams, Paul

    Classification of objects (such as tablets, cereals, fruits, etc.) is one of the very important applications of hyperspectral imaging and image analysis. Quite often, a hyperspectral image is represented and analyzed just as a bunch of spectra without taking into account spatial information about...... the pixels, which makes classification objects inefficient. Recently, several methods, which combine spectral and spatial information, has been also developed and this approach becomes more and more wide-spread. The methods use local rank, topology, spectral features calculated for separate objects and other...... spatial characteristics. In this work we would like to show several improvements to the classification method, which utilizes spectral features calculated for individual objects [1]. The features are based (in general) on descriptors of spatial patterns of individual object’s pixels in a common principal...

  15. Improved land use classification from Landsat and Seasat satellite imagery registered to a common map base

    Science.gov (United States)

    Clark, J.

    1981-01-01

    In the case of Landsat Multispectral Scanner System (MSS) data, ambiguities in spectral signature can arise in urban areas. A study was initiated in the belief that Seasat digital SAR could help provide the spectral separability needed for a more accurate urban land use classification. A description is presented of the results of land use classifications performed on Landsat and preprocessed Seasat imagery that were registered to a common map base. The process of registering imagery and training site boundary coordinates to a common map has been reported by Clark (1980). It is found that preprocessed Seasat imagery provides signatures for urban land uses which are spectrally separable from Landsat signatures. This development appears to significantly improve land use classifications in an urban setting for class 12 (Commercial and Services), class 13 (Industrial), and class 14 (Transportation, Communications, and Utilities).

  16. Adiabatic theorem and spectral concentration

    International Nuclear Information System (INIS)

    Nenciu, G.

    1981-01-01

    The spectral concentration of arbitrary order, for the Stark effect is proved to exist for a large class of Hamiltonians appearing in nonrelativistic and relativistic quantum mechanics. The results are consequences of an abstract theorem about the spectral concentration for self-ad oint operators. A general form of the adiabatic theorem of quantum mechanics, generalizing an earlier result of the author as well as some results of Lenard, is also proved [ru

  17. Acoustic classification of dwellings

    DEFF Research Database (Denmark)

    Berardi, Umberto; Rasmussen, Birgit

    2014-01-01

    insulation performance, national schemes for sound classification of dwellings have been developed in several European countries. These schemes define acoustic classes according to different levels of sound insulation. Due to the lack of coordination among countries, a significant diversity in terms...... exchanging experiences about constructions fulfilling different classes, reducing trade barriers, and finally increasing the sound insulation of dwellings.......Schemes for the classification of dwellings according to different building performances have been proposed in the last years worldwide. The general idea behind these schemes relates to the positive impact a higher label, and thus a better performance, should have. In particular, focusing on sound...

  18. Minimum Error Entropy Classification

    CERN Document Server

    Marques de Sá, Joaquim P; Santos, Jorge M F; Alexandre, Luís A

    2013-01-01

    This book explains the minimum error entropy (MEE) concept applied to data classification machines. Theoretical results on the inner workings of the MEE concept, in its application to solving a variety of classification problems, are presented in the wider realm of risk functionals. Researchers and practitioners also find in the book a detailed presentation of practical data classifiers using MEE. These include multi‐layer perceptrons, recurrent neural networks, complexvalued neural networks, modular neural networks, and decision trees. A clustering algorithm using a MEE‐like concept is also presented. Examples, tests, evaluation experiments and comparison with similar machines using classic approaches, complement the descriptions.

  19. Classification of iconic images

    OpenAIRE

    Zrianina, Mariia; Kopf, Stephan

    2016-01-01

    Iconic images represent an abstract topic and use a presentation that is intuitively understood within a certain cultural context. For example, the abstract topic “global warming” may be represented by a polar bear standing alone on an ice floe. Such images are widely used in media and their automatic classification can help to identify high-level semantic concepts. This paper presents a system for the classification of iconic images. It uses a variation of the Bag of Visual Words approach wi...

  20. Casemix classification systems.

    Science.gov (United States)

    Fetter, R B

    1999-01-01

    The idea of using casemix classification to manage hospital services is not new, but has been limited by available technology. It was not until after the introduction of Medicare in the United States in 1965 that serious attempts were made to measure hospital production in order to contain spiralling costs. This resulted in a system of casemix classification known as diagnosis related groups (DRGs). This paper traces the development of DRGs and their evolution from the initial version to the All Patient Refined DRGs developed in 1991.

  1. Information gathering for CLP classification

    Directory of Open Access Journals (Sweden)

    Ida Marcello

    2011-01-01

    Full Text Available Regulation 1272/2008 includes provisions for two types of classification: harmonised classification and self-classification. The harmonised classification of substances is decided at Community level and a list of harmonised classifications is included in the Annex VI of the classification, labelling and packaging Regulation (CLP. If a chemical substance is not included in the harmonised classification list it must be self-classified, based on available information, according to the requirements of Annex I of the CLP Regulation. CLP appoints that the harmonised classification will be performed for carcinogenic, mutagenic or toxic to reproduction substances (CMR substances and for respiratory sensitisers category 1 and for other hazard classes on a case-by-case basis. The first step of classification is the gathering of available and relevant information. This paper presents the procedure for gathering information and to obtain data. The data quality is also discussed.

  2. The paradox of atheoretical classification

    DEFF Research Database (Denmark)

    Hjørland, Birger

    2016-01-01

    A distinction can be made between “artificial classifications” and “natural classifications,” where artificial classifications may adequately serve some limited purposes, but natural classifications are overall most fruitful by allowing inference and thus many different purposes. There is strong...... support for the view that a natural classification should be based on a theory (and, of course, that the most fruitful theory provides the most fruitful classification). Nevertheless, atheoretical (or “descriptive”) classifications are often produced. Paradoxically, atheoretical classifications may...... be very successful. The best example of a successful “atheoretical” classification is probably the prestigious Diagnostic and Statistical Manual of Mental Disorders (DSM) since its third edition from 1980. Based on such successes one may ask: Should the claim that classifications ideally are natural...

  3. Tree Classification with Fused Mobile Laser Scanning and Hyperspectral Data

    Science.gov (United States)

    Puttonen, Eetu; Jaakkola, Anttoni; Litkey, Paula; Hyyppä, Juha

    2011-01-01

    Mobile Laser Scanning data were collected simultaneously with hyperspectral data using the Finnish Geodetic Institute Sensei system. The data were tested for tree species classification. The test area was an urban garden in the City of Espoo, Finland. Point clouds representing 168 individual tree specimens of 23 tree species were determined manually. The classification of the trees was done using first only the spatial data from point clouds, then with only the spectral data obtained with a spectrometer, and finally with the combined spatial and hyperspectral data from both sensors. Two classification tests were performed: the separation of coniferous and deciduous trees, and the identification of individual tree species. All determined tree specimens were used in distinguishing coniferous and deciduous trees. A subset of 133 trees and 10 tree species was used in the tree species classification. The best classification results for the fused data were 95.8% for the separation of the coniferous and deciduous classes. The best overall tree species classification succeeded with 83.5% accuracy for the best tested fused data feature combination. The respective results for paired structural features derived from the laser point cloud were 90.5% for the separation of the coniferous and deciduous classes and 65.4% for the species classification. Classification accuracies with paired hyperspectral reflectance value data were 90.5% for the separation of coniferous and deciduous classes and 62.4% for different species. The results are among the first of their kind and they show that mobile collected fused data outperformed single-sensor data in both classification tests and by a significant margin. PMID:22163894

  4. Identification of spectral units on Phoebe

    Science.gov (United States)

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

    2008-01-01

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

  5. Optimisation of material discrimination using spectral CT

    International Nuclear Information System (INIS)

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

    2010-01-01

    Full text: Spectral computed tomography (CT) using novel X-ray photon counting detectors (PCDs) with energy resolving capabilities is capable of providing energy-selective images. This extra energy information may allow materials such as iodine and calcium, or water and fat to be distinguished. PCDs have energy thresholds, enabling the classification of photons into multiple energy bins. The inform tion content of spectral CT images depends on how the photons are grouped together. [n this work, a method is presented to optimise energy windows for maximum material discrimination. Given a combination of thicknesses, the reference number of expected photons in each energy bin is computed using the Bee Lambert equation. A similar calculation is performed for an exhaustive range of thicknesses and the number of photons in each case is com pared to the reference, allowing a statistical map of the uncertainty in thickness parameters to be constructed. The 63%-confidence region in the two-dimensional thickness space is a representation of how optimal the bins are for material separation. The model is demonstrated with 0.1 mm of iodine and 2.2 mm of calcium using two adjacent bins encompassing the entire energy range. Bins bordering at the iodine k-edge of 33.2 keY are found to be optimal. When compared to two abutted energy bins with equal incident counts as used in the literature (bordering at 54 keY), the thickness uncertainties are reduced from approximately 4% to less than I % (see Figure). This approach has been developed for two materials and is expandable to an arbitrary number of materials and bins.

  6. Silence–breathing–snore classification from snore-related sounds

    International Nuclear Information System (INIS)

    Karunajeewa, Asela S; Abeyratne, Udantha R; Hukins, Craig

    2008-01-01

    Obstructive sleep apnea (OSA) is a highly prevalent disease in which upper airways are collapsed during sleep, leading to serious consequences. Snoring is the earliest symptom of OSA, but its potential in clinical diagnosis is not fully recognized yet. The first task in the automatic analysis of snore-related sounds (SRS) is to segment the SRS data as accurately as possible into three main classes: snoring (voiced non-silence), breathing (unvoiced non-silence) and silence. SRS data are generally contaminated with background noise. In this paper, we present classification performance of a new segmentation algorithm based on pattern recognition. We considered four features derived from SRS to classify samples of SRS into three classes. The features—number of zero crossings, energy of the signal, normalized autocorrelation coefficient at 1 ms delay and the first predictor coefficient of linear predictive coding (LPC) analysis—in combination were able to achieve a classification accuracy of 90.74% in classifying a set of test data. We also investigated the performance of the algorithm when three commonly used noise reduction (NR) techniques in speech processing—amplitude spectral subtraction (ASS), power spectral subtraction (PSS) and short time spectral amplitude (STSA) estimation—are used for noise reduction. We found that noise reduction together with a proper choice of features could improve the classification accuracy to 96.78%, making the automated analysis a possibility

  7. Time Series of Images to Improve Tree Species Classification

    Science.gov (United States)

    Miyoshi, G. T.; Imai, N. N.; de Moraes, M. V. A.; Tommaselli, A. M. G.; Näsi, R.

    2017-10-01

    Tree species classification provides valuable information to forest monitoring and management. The high floristic variation of the tree species appears as a challenging issue in the tree species classification because the vegetation characteristics changes according to the season. To help to monitor this complex environment, the imaging spectroscopy has been largely applied since the development of miniaturized sensors attached to Unmanned Aerial Vehicles (UAV). Considering the seasonal changes in forests and the higher spectral and spatial resolution acquired with sensors attached to UAV, we present the use of time series of images to classify four tree species. The study area is an Atlantic Forest area located in the western part of São Paulo State. Images were acquired in August 2015 and August 2016, generating three data sets of images: only with the image spectra of 2015; only with the image spectra of 2016; with the layer stacking of images from 2015 and 2016. Four tree species were classified using Spectral angle mapper (SAM), Spectral information divergence (SID) and Random Forest (RF). The results showed that SAM and SID caused an overfitting of the data whereas RF showed better results and the use of the layer stacking improved the classification achieving a kappa coefficient of 18.26 %.

  8. A classification model of Hyperion image base on SAM combined decision tree

    Science.gov (United States)

    Wang, Zhenghai; Hu, Guangdao; Zhou, YongZhang; Liu, Xin

    2009-10-01

    Monitoring the Earth using imaging spectrometers has necessitated more accurate analyses and new applications to remote sensing. A very high dimensional input space requires an exponentially large amount of data to adequately and reliably represent the classes in that space. On the other hand, with increase in the input dimensionality the hypothesis space grows exponentially, which makes the classification performance highly unreliable. Traditional classification algorithms Classification of hyperspectral images is challenging. New algorithms have to be developed for hyperspectral data classification. The Spectral Angle Mapper (SAM) is a physically-based spectral classification that uses an ndimensional angle to match pixels to reference spectra. The algorithm determines the spectral similarity between two spectra by calculating the angle between the spectra, treating them as vectors in a space with dimensionality equal to the number of bands. The key and difficulty is that we should artificial defining the threshold of SAM. The classification precision depends on the rationality of the threshold of SAM. In order to resolve this problem, this paper proposes a new automatic classification model of remote sensing image using SAM combined with decision tree. It can automatic choose the appropriate threshold of SAM and improve the classify precision of SAM base on the analyze of field spectrum. The test area located in Heqing Yunnan was imaged by EO_1 Hyperion imaging spectrometer using 224 bands in visual and near infrared. The area included limestone areas, rock fields, soil and forests. The area was classified into four different vegetation and soil types. The results show that this method choose the appropriate threshold of SAM and eliminates the disturbance and influence of unwanted objects effectively, so as to improve the classification precision. Compared with the likelihood classification by field survey data, the classification precision of this model

  9. Evolving spectral transformations for multitemporal information extraction using evolutionary computation

    Science.gov (United States)

    Momm, Henrique; Easson, Greg

    2011-01-01

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

  10. THE INFRARED TELESCOPE FACILITY (IRTF) SPECTRAL LIBRARY: COOL STARS

    International Nuclear Information System (INIS)

    Rayner, John T.; Cushing, Michael C.; Vacca, William D.

    2009-01-01

    We present a 0.8-5 μm spectral library of 210 cool stars observed at a resolving power of R ≡ λ/Δλ ∼ 2000 with the medium-resolution infrared spectrograph, SpeX, at the 3.0 m NASA Infrared Telescope Facility (IRTF) on Mauna Kea, Hawaii. The stars have well-established MK spectral classifications and are mostly restricted to near-solar metallicities. The sample not only contains the F, G, K, and M spectral types with luminosity classes between I and V, but also includes some AGB, carbon, and S stars. In contrast to some other spectral libraries, the continuum shape of the spectra is measured and preserved in the data reduction process. The spectra are absolutely flux calibrated using the Two Micron All Sky Survey photometry. Potential uses of the library include studying the physics of cool stars, classifying and studying embedded young clusters and optically obscured regions of the Galaxy, evolutionary population synthesis to study unresolved stellar populations in optically obscured regions of galaxies and synthetic photometry. The library is available in digital form from the IRTF Web site.

  11. The Infrared Telescope Facility (IRTF) Spectral Library: Cool Stars

    Science.gov (United States)

    Rayner, John T.; Cushing, Michael C.; Vacca, William D.

    2009-12-01

    We present a 0.8-5 μm spectral library of 210 cool stars observed at a resolving power of R ≡ λ/Δλ ~ 2000 with the medium-resolution infrared spectrograph, SpeX, at the 3.0 m NASA Infrared Telescope Facility (IRTF) on Mauna Kea, Hawaii. The stars have well-established MK spectral classifications and are mostly restricted to near-solar metallicities. The sample not only contains the F, G, K, and M spectral types with luminosity classes between I and V, but also includes some AGB, carbon, and S stars. In contrast to some other spectral libraries, the continuum shape of the spectra is measured and preserved in the data reduction process. The spectra are absolutely flux calibrated using the Two Micron All Sky Survey photometry. Potential uses of the library include studying the physics of cool stars, classifying and studying embedded young clusters and optically obscured regions of the Galaxy, evolutionary population synthesis to study unresolved stellar populations in optically obscured regions of galaxies and synthetic photometry. The library is available in digital form from the IRTF Web site.

  12. Characterizing CDOM Spectral Variability Across Diverse Regions and Spectral Ranges

    Science.gov (United States)

    Grunert, Brice K.; Mouw, Colleen B.; Ciochetto, Audrey B.

    2018-01-01

    Satellite remote sensing of colored dissolved organic matter (CDOM) has focused on CDOM absorption (aCDOM) at a reference wavelength, as its magnitude provides insight into the underwater light field and large-scale biogeochemical processes. CDOM spectral slope, SCDOM, has been treated as a constant or semiconstant parameter in satellite retrievals of aCDOM despite significant regional and temporal variabilities. SCDOM and other optical metrics provide insights into CDOM composition, processing, food web dynamics, and carbon cycling. To date, much of this work relies on fluorescence techniques or aCDOM in spectral ranges unavailable to current and planned satellite sensors (e.g., global variability in SCDOM and fit deviations in the aCDOM spectra using the recently proposed Gaussian decomposition method. From this, we investigate if global variability in retrieved SCDOM and Gaussian components is significant and regionally distinct. We iteratively decreased the spectral range considered and analyzed the number, location, and magnitude of fitted Gaussian components to understand if a reduced spectral range impacts information obtained within a common spectral window. We compared the fitted slope from the Gaussian decomposition method to absorption-based indices that indicate CDOM composition to determine the ability of satellite-derived slope to inform the analysis and modeling of large-scale biogeochemical processes. Finally, we present implications of the observed variability for remote sensing of CDOM characteristics via SCDOM.

  13. Land Cover and Land Use Classification with TWOPAC: towards Automated Processing for Pixel- and Object-Based Image Classification

    Directory of Open Access Journals (Sweden)

    Stefan Dech

    2012-09-01

    Full Text Available We present a novel and innovative automated processing environment for the derivation of land cover (LC and land use (LU information. This processing framework named TWOPAC (TWinned Object and Pixel based Automated classification Chain enables the standardized, independent, user-friendly, and comparable derivation of LC and LU information, with minimized manual classification labor. TWOPAC allows classification of multi-spectral and multi-temporal remote sensing imagery from different sensor types. TWOPAC enables not only pixel-based classification, but also allows classification based on object-based characteristics. Classification is based on a Decision Tree approach (DT for which the well-known C5.0 code has been implemented, which builds decision trees based on the concept of information entropy. TWOPAC enables automatic generation of the decision tree classifier based on a C5.0-retrieved ascii-file, as well as fully automatic validation of the classification output via sample based accuracy assessment.Envisaging the automated generation of standardized land cover products, as well as area-wide classification of large amounts of data in preferably a short processing time, standardized interfaces for process control, Web Processing Services (WPS, as introduced by the Open Geospatial Consortium (OGC, are utilized. TWOPAC’s functionality to process geospatial raster or vector data via web resources (server, network enables TWOPAC’s usability independent of any commercial client or desktop software and allows for large scale data processing on servers. Furthermore, the components of TWOPAC were built-up using open source code components and are implemented as a plug-in for Quantum GIS software for easy handling of the classification process from the user’s perspective.

  14. Ecosystem classification, Chapter 2

    Science.gov (United States)

    M.J. Robin-Abbott; L.H. Pardo

    2011-01-01

    The ecosystem classification in this report is based on the ecoregions developed through the Commission for Environmental Cooperation (CEC) for North America (CEC 1997). Only ecosystems that occur in the United States are included. CEC ecoregions are described, with slight modifications, below (CEC 1997) and shown in Figures 2.1 and 2.2. We chose this ecosystem...

  15. The classification of phocomelia.

    Science.gov (United States)

    Tytherleigh-Strong, G; Hooper, G

    2003-06-01

    We studied 24 patients with 44 phocomelic upper limbs. Only 11 limbs could be grouped in the classification system of Frantz and O' Rahilly. The non-classifiable limbs were further studied and their characteristics identified. It is confirmed that phocomelia is not an intercalary defect.

  16. Principles for ecological classification

    Science.gov (United States)

    Dennis H. Grossman; Patrick Bourgeron; Wolf-Dieter N. Busch; David T. Cleland; William Platts; G. Ray; C. Robins; Gary Roloff

    1999-01-01

    The principal purpose of any classification is to relate common properties among different entities to facilitate understanding of evolutionary and adaptive processes. In the context of this volume, it is to facilitate ecosystem stewardship, i.e., to help support ecosystem conservation and management objectives.

  17. Mimicking human texture classification

    NARCIS (Netherlands)

    Rogowitz, B.E.; van Rikxoort, Eva M.; van den Broek, Egon; Pappas, T.N.; Schouten, Theo E.; Daly, S.J.

    2005-01-01

    In an attempt to mimic human (colorful) texture classification by a clustering algorithm three lines of research have been encountered, in which as test set 180 texture images (both their color and gray-scale equivalent) were drawn from the OuTex and VisTex databases. First, a k-means algorithm was

  18. Classification, confusion and misclassification

    African Journals Online (AJOL)

    The classification of objects and phenomena in science and nature has fascinated academics since Carl Linnaeus, the Swedish botanist and zoologist, created his binomial description of living things in the 1700s and probably long before in accounts of others in textbooks long since gone. It must have concerned human ...

  19. Classifications in popular music

    NARCIS (Netherlands)

    van Venrooij, A.; Schmutz, V.; Wright, J.D.

    2015-01-01

    The categorical system of popular music, such as genre categories, is a highly differentiated and dynamic classification system. In this article we present work that studies different aspects of these categorical systems in popular music. Following the work of Paul DiMaggio, we focus on four

  20. Shark Teeth Classification

    Science.gov (United States)

    Brown, Tom; Creel, Sally; Lee, Velda

    2009-01-01

    On a recent autumn afternoon at Harmony Leland Elementary in Mableton, Georgia, students in a fifth-grade science class investigated the essential process of classification--the act of putting things into groups according to some common characteristics or attributes. While they may have honed these skills earlier in the week by grouping their own…

  1. Text document classification

    Czech Academy of Sciences Publication Activity Database

    Novovičová, Jana

    č. 62 (2005), s. 53-54 ISSN 0926-4981 R&D Projects: GA AV ČR IAA2075302; GA AV ČR KSK1019101; GA MŠk 1M0572 Institutional research plan: CEZ:AV0Z10750506 Keywords : document representation * categorization * classification Subject RIV: BD - Theory of Information

  2. Classification in Medical Imaging

    DEFF Research Database (Denmark)

    Chen, Chen

    Classification is extensively used in the context of medical image analysis for the purpose of diagnosis or prognosis. In order to classify image content correctly, one needs to extract efficient features with discriminative properties and build classifiers based on these features. In addition...... on characterizing human faces and emphysema disease in lung CT images....

  3. Improving Student Question Classification

    Science.gov (United States)

    Heiner, Cecily; Zachary, Joseph L.

    2009-01-01

    Students in introductory programming classes often articulate their questions and information needs incompletely. Consequently, the automatic classification of student questions to provide automated tutorial responses is a challenging problem. This paper analyzes 411 questions from an introductory Java programming course by reducing the natural…

  4. NOUN CLASSIFICATION IN ESAHIE

    African Journals Online (AJOL)

    The present work deals with noun classification in Esahie (Kwa, Niger ... phonological information influences the noun (form) class system of Esahie. ... between noun classes and (grammatical) Gender is interrogated (in the light of ..... the (A) argument6 precedes the verb and the (P) argument7 follows the verb in a simple.

  5. Dynamic Latent Classification Model

    DEFF Research Database (Denmark)

    Zhong, Shengtong; Martínez, Ana M.; Nielsen, Thomas Dyhre

    as possible. Motivated by this problem setting, we propose a generative model for dynamic classification in continuous domains. At each time point the model can be seen as combining a naive Bayes model with a mixture of factor analyzers (FA). The latent variables of the FA are used to capture the dynamics...

  6. Classification of myocardial infarction

    DEFF Research Database (Denmark)

    Saaby, Lotte; Poulsen, Tina Svenstrup; Hosbond, Susanne Elisabeth

    2013-01-01

    The classification of myocardial infarction into 5 types was introduced in 2007 as an important component of the universal definition. In contrast to the plaque rupture-related type 1 myocardial infarction, type 2 myocardial infarction is considered to be caused by an imbalance between demand...

  7. Event Classification using Concepts

    NARCIS (Netherlands)

    Boer, M.H.T. de; Schutte, K.; Kraaij, W.

    2013-01-01

    The semantic gap is one of the challenges in the GOOSE project. In this paper a Semantic Event Classification (SEC) system is proposed as an initial step in tackling the semantic gap challenge in the GOOSE project. This system uses semantic text analysis, multiple feature detectors using the BoW

  8. IRIS COLOUR CLASSIFICATION SCALES--THEN AND NOW.

    Science.gov (United States)

    Grigore, Mariana; Avram, Alina

    2015-01-01

    Eye colour is one of the most obvious phenotypic traits of an individual. Since the first documented classification scale developed in 1843, there have been numerous attempts to classify the iris colour. In the past centuries, iris colour classification scales has had various colour categories and mostly relied on comparison of an individual's eye with painted glass eyes. Once photography techniques were refined, standard iris photographs replaced painted eyes, but this did not solve the problem of painted/ printed colour variability in time. Early clinical scales were easy to use, but lacked objectivity and were not standardised or statistically tested for reproducibility. The era of automated iris colour classification systems came with the technological development. Spectrophotometry, digital analysis of high-resolution iris images, hyper spectral analysis of the human real iris and the dedicated iris colour analysis software, all accomplished an objective, accurate iris colour classification, but are quite expensive and limited in use to research environment. Iris colour classification systems evolved continuously due to their use in a wide range of studies, especially in the fields of anthropology, epidemiology and genetics. Despite the wide range of the existing scales, up until present there has been no generally accepted iris colour classification scale.

  9. IRIS COLOUR CLASSIFICATION SCALES – THEN AND NOW

    Science.gov (United States)

    Grigore, Mariana; Avram, Alina

    2015-01-01

    Eye colour is one of the most obvious phenotypic traits of an individual. Since the first documented classification scale developed in 1843, there have been numerous attempts to classify the iris colour. In the past centuries, iris colour classification scales has had various colour categories and mostly relied on comparison of an individual’s eye with painted glass eyes. Once photography techniques were refined, standard iris photographs replaced painted eyes, but this did not solve the problem of painted/ printed colour variability in time. Early clinical scales were easy to use, but lacked objectivity and were not standardised or statistically tested for reproducibility. The era of automated iris colour classification systems came with the technological development. Spectrophotometry, digital analysis of high-resolution iris images, hyper spectral analysis of the human real iris and the dedicated iris colour analysis software, all accomplished an objective, accurate iris colour classification, but are quite expensive and limited in use to research environment. Iris colour classification systems evolved continuously due to their use in a wide range of studies, especially in the fields of anthropology, epidemiology and genetics. Despite the wide range of the existing scales, up until present there has been no generally accepted iris colour classification scale. PMID:27373112

  10. NEW CLASSIFICATION OF ECOPOLICES

    Directory of Open Access Journals (Sweden)

    VOROBYOV V. V.

    2016-09-01

    Full Text Available Problem statement. Ecopolices are the newest stage of the urban planning. They have to be consideredsuchas material and energy informational structures, included to the dynamic-evolutionary matrix netsofex change processes in the ecosystems. However, there are not made the ecopolice classifications, developing on suchapproaches basis. And this determined the topicality of the article. Analysis of publications on theoretical and applied aspects of the ecopolices formation showed, that the work on them is managed mainly in the context of the latest scientific and technological achievements in the various knowledge fields. These settlements are technocratic. They are connected with the morphology of space, network structures of regional and local natural ecosystems, without independent stability, can not exist without continuous man support. Another words, they do not work in with an ecopolices idea. It is come to a head for objective, symbiotic searching of ecopolices concept with the development of their classifications. Purpose statement is to develop the objective evidence for ecopolices and to propose their new classification. Conclusion. On the base of the ecopolices classification have to lie an elements correlation idea of their general plans and men activity type according with natural mechanism of accepting, reworking and transmission of material, energy and information between geo-ecosystems, planet, man, ecopolices material part and Cosmos. New ecopolices classification should be based on the principles of multi-dimensional, time-spaced symbiotic clarity with exchange ecosystem networks. The ecopolice function with this approach comes not from the subjective anthropocentric economy but from the holistic objective of Genesis paradigm. Or, otherwise - not from the Consequence, but from the Cause.

  11. Efficient Fingercode Classification

    Science.gov (United States)

    Sun, Hong-Wei; Law, Kwok-Yan; Gollmann, Dieter; Chung, Siu-Leung; Li, Jian-Bin; Sun, Jia-Guang

    In this paper, we present an efficient fingerprint classification algorithm which is an essential component in many critical security application systems e. g. systems in the e-government and e-finance domains. Fingerprint identification is one of the most important security requirements in homeland security systems such as personnel screening and anti-money laundering. The problem of fingerprint identification involves searching (matching) the fingerprint of a person against each of the fingerprints of all registered persons. To enhance performance and reliability, a common approach is to reduce the search space by firstly classifying the fingerprints and then performing the search in the respective class. Jain et al. proposed a fingerprint classification algorithm based on a two-stage classifier, which uses a K-nearest neighbor classifier in its first stage. The fingerprint classification algorithm is based on the fingercode representation which is an encoding of fingerprints that has been demonstrated to be an effective fingerprint biometric scheme because of its ability to capture both local and global details in a fingerprint image. We enhance this approach by improving the efficiency of the K-nearest neighbor classifier for fingercode-based fingerprint classification. Our research firstly investigates the various fast search algorithms in vector quantization (VQ) and the potential application in fingerprint classification, and then proposes two efficient algorithms based on the pyramid-based search algorithms in VQ. Experimental results on DB1 of FVC 2004 demonstrate that our algorithms can outperform the full search algorithm and the original pyramid-based search algorithms in terms of computational efficiency without sacrificing accuracy.

  12. Differential Classification of Dementia

    Directory of Open Access Journals (Sweden)

    E. Mohr

    1995-01-01

    Full Text Available In the absence of biological markers, dementia classification remains complex both in terms of characterization as well as early detection of the presence or absence of dementing symptoms, particularly in diseases with possible secondary dementia. An empirical, statistical approach using neuropsychological measures was therefore developed to distinguish demented from non-demented patients and to identify differential patterns of cognitive dysfunction in neurodegenerative disease. Age-scaled neurobehavioral test results (Wechsler Adult Intelligence Scale—Revised and Wechsler Memory Scale from Alzheimer's (AD and Huntington's (HD patients, matched for intellectual disability, as well as normal controls were used to derive a classification formula. Stepwise discriminant analysis accurately (99% correct distinguished controls from demented patients, and separated the two patient groups (79% correct. Variables discriminating between HD and AD patient groups consisted of complex psychomotor tasks, visuospatial function, attention and memory. The reliability of the classification formula was demonstrated with a new, independent sample of AD and HD patients which yielded virtually identical results (classification accuracy for dementia: 96%; AD versus HD: 78%. To validate the formula, the discriminant function was applied to Parkinson's (PD patients, 38% of whom were classified as demented. The validity of the classification was demonstrated by significant PD subgroup differences on measures of dementia not included in the discriminant function. Moreover, a majority of demented PD patients (65% were classified as having an HD-like pattern of cognitive deficits, in line with previous reports of the subcortical nature of PD dementia. This approach may thus be useful in classifying presence or absence of dementia and in discriminating between dementia subtypes in cases of secondary or coincidental dementia.

  13. Analysis of Landsat-4 Thematic Mapper data for classification of forest stands in Baldwin County, Alabama

    Science.gov (United States)

    Hill, C. L.

    1984-01-01

    A computer-implemented classification has been derived from Landsat-4 Thematic Mapper data acquired over Baldwin County, Alabama on January 15, 1983. One set of spectral signatures was developed from the data by utilizing a 3x3 pixel sliding window approach. An analysis of the classification produced from this technique identified forested areas. Additional information regarding only the forested areas. Additional information regarding only the forested areas was extracted by employing a pixel-by-pixel signature development program which derived spectral statistics only for pixels within the forested land covers. The spectral statistics from both approaches were integrated and the data classified. This classification was evaluated by comparing the spectral classes produced from the data against corresponding ground verification polygons. This iterative data analysis technique resulted in an overall classification accuracy of 88.4 percent correct for slash pine, young pine, loblolly pine, natural pine, and mixed hardwood-pine. An accuracy assessment matrix has been produced for the classification.

  14. An Active Learning Framework for Hyperspectral Image Classification Using Hierarchical Segmentation

    Science.gov (United States)

    Zhang, Zhou; Pasolli, Edoardo; Crawford, Melba M.; Tilton, James C.

    2015-01-01

    Augmenting spectral data with spatial information for image classification has recently gained significant attention, as classification accuracy can often be improved by extracting spatial information from neighboring pixels. In this paper, we propose a new framework in which active learning (AL) and hierarchical segmentation (HSeg) are combined for spectral-spatial classification of hyperspectral images. The spatial information is extracted from a best segmentation obtained by pruning the HSeg tree using a new supervised strategy. The best segmentation is updated at each iteration of the AL process, thus taking advantage of informative labeled samples provided by the user. The proposed strategy incorporates spatial information in two ways: 1) concatenating the extracted spatial features and the original spectral features into a stacked vector and 2) extending the training set using a self-learning-based semi-supervised learning (SSL) approach. Finally, the two strategies are combined within an AL framework. The proposed framework is validated with two benchmark hyperspectral datasets. Higher classification accuracies are obtained by the proposed framework with respect to five other state-of-the-art spectral-spatial classification approaches. Moreover, the effectiveness of the proposed pruning strategy is also demonstrated relative to the approaches based on a fixed segmentation.

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

    Science.gov (United States)

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

    2007-07-01

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

  16. Morphological Interpretation of Reflectance Spectrum (MIRS using libraries looking towards soil classification

    Directory of Open Access Journals (Sweden)

    José Alexandre Melo Demattê

    2014-12-01

    Full Text Available The search for tools to perform soil surveying faster and cheaper has led to the development of technological innovations such as remote sensing (RS and the so-called spectral libraries in recent years. However, there are no studies which collate all the RS background to demonstrate how to use this technology for soil classification. The present study aims to describe a simple method of how to classify soils by the morphology of spectra associated with a quantitative view (400-2,500 nm. For this, we constructed three spectral libraries: (i one for quantitative model performance; (ii a second to function as the spectral patterns; and (iii a third to serve as a validation stage. All samples had their chemical and granulometric attributes determined by laboratory analysis and prediction models were created based on soil spectra. The system is based on seven steps summarized as follows: i interpretation of the spectral curve intensity; ii observation of the general shape of curves; iii evaluation of absorption features; iv comparison of spectral curves between the same profile horizons; v quantification of soil attributes by spectral library models; vi comparison of a pre-existent spectral library with unknown profile spectra; vii most probable soil classification. A soil cannot be classified from one spectral curve alone. The behavior between the horizons of a profile, however, was correlated with its classification. In fact, the validation showed 85 % accuracy between the Morphological Interpretation of Reflectance Spectrum (MIRS method and the traditional classification, showing the importance and potential of a combination of descriptive and quantitative evaluations.

  17. Comparing Features for Classification of MEG Responses to Motor Imagery.

    Directory of Open Access Journals (Sweden)

    Hanna-Leena Halme

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

  18. Acoustic and spectral characteristics of young children's fricative productions: A developmental perspective

    Science.gov (United States)

    Nissen, Shawn L.; Fox, Robert Allen

    2005-10-01

    Scientists have made great strides toward understanding the mechanisms of speech production and perception. However, the complex relationships between the acoustic structures of speech and the resulting psychological percepts have yet to be fully and adequately explained, especially in speech produced by younger children. Thus, this study examined the acoustic structure of voiceless fricatives (/f, θ, s, /sh/) produced by adults and typically developing children from 3 to 6 years of age in terms of multiple acoustic parameters (durations, normalized amplitude, spectral slope, and spectral moments). It was found that the acoustic parameters of spectral slope and variance (commonly excluded from previous studies of child speech) were important acoustic parameters in the differentiation and classification of the voiceless fricatives, with spectral variance being the only measure to separate all four places of articulation. It was further shown that the sibilant contrast between /s/ and /sh/ was less distinguished in children than adults, characterized by a dramatic change in several spectral parameters at approximately five years of age. Discriminant analysis revealed evidence that classification models based on adult data were sensitive to these spectral differences in the five-year-old age group.

  19. 78 FR 54970 - Cotton Futures Classification: Optional Classification Procedure

    Science.gov (United States)

    2013-09-09

    ... Service 7 CFR Part 27 [AMS-CN-13-0043] RIN 0581-AD33 Cotton Futures Classification: Optional Classification Procedure AGENCY: Agricultural Marketing Service, USDA. ACTION: Proposed rule. SUMMARY: The... optional cotton futures classification procedure--identified and known as ``registration'' by the U.S...

  20. a Hyperspectral Image Classification Method Using Isomap and Rvm

    Science.gov (United States)

    Chang, H.; Wang, T.; Fang, H.; Su, Y.

    2018-04-01

    Classification is one of the most significant applications of hyperspectral image processing and even remote sensing. Though various algorithms have been proposed to implement and improve this application, there are still drawbacks in traditional classification methods. Thus further investigations on some aspects, such as dimension reduction, data mining, and rational use of spatial information, should be developed. In this paper, we used a widely utilized global manifold learning approach, isometric feature mapping (ISOMAP), to address the intrinsic nonlinearities of hyperspectral image for dimension reduction. Considering the impropriety of Euclidean distance in spectral measurement, we applied spectral angle (SA) for substitute when constructed the neighbourhood graph. Then, relevance vector machines (RVM) was introduced to implement classification instead of support vector machines (SVM) for simplicity, generalization and sparsity. Therefore, a probability result could be obtained rather than a less convincing binary result. Moreover, taking into account the spatial information of the hyperspectral image, we employ a spatial vector formed by different classes' ratios around the pixel. At last, we combined the probability results and spatial factors with a criterion to decide the final classification result. To verify the proposed method, we have implemented multiple experiments with standard hyperspectral images compared with some other methods. The results and different evaluation indexes illustrated the effectiveness of our method.

  1. Using ecological zones to increase the detail of Landsat classifications

    Science.gov (United States)

    Fox, L., III; Mayer, K. E.

    1981-01-01

    Changes in classification detail of forest species descriptions were made for Landsat data on 2.2 million acres in northwestern California. Because basic forest canopy structures may exhibit very similar E-M energy reflectance patterns in different environmental regions, classification labels based on Landsat spectral signatures alone become very generalized when mapping large heterogeneous ecological regions. By adding a seven ecological zone stratification, a 167% improvement in classification detail was made over the results achieved without it. The seven zone stratification is a less costly alternative to the inclusion of complex collateral information, such as terrain data and soil type, into the Landsat data base when making inventories of areas greater than 500,000 acres.

  2. Support Vector Machines for Hyperspectral Remote Sensing Classification

    Science.gov (United States)

    Gualtieri, J. Anthony; Cromp, R. F.

    1998-01-01

    The Support Vector Machine provides a new way to design classification algorithms which learn from examples (supervised learning) and generalize when applied to new data. We demonstrate its success on a difficult classification problem from hyperspectral remote sensing, where we obtain performances of 96%, and 87% correct for a 4 class problem, and a 16 class problem respectively. These results are somewhat better than other recent results on the same data. A key feature of this classifier is its ability to use high-dimensional data without the usual recourse to a feature selection step to reduce the dimensionality of the data. For this application, this is important, as hyperspectral data consists of several hundred contiguous spectral channels for each exemplar. We provide an introduction to this new approach, and demonstrate its application to classification of an agriculture scene.

  3. Hyperspectral image classification based on local binary patterns and PCANet

    Science.gov (United States)

    Yang, Huizhen; Gao, Feng; Dong, Junyu; Yang, Yang

    2018-04-01

    Hyperspectral image classification has been well acknowledged as one of the challenging tasks of hyperspectral data processing. In this paper, we propose a novel hyperspectral image classification framework based on local binary pattern (LBP) features and PCANet. In the proposed method, linear prediction error (LPE) is first employed to select a subset of informative bands, and LBP is utilized to extract texture features. Then, spectral and texture features are stacked into a high dimensional vectors. Next, the extracted features of a specified position are transformed to a 2-D image. The obtained images of all pixels are fed into PCANet for classification. Experimental results on real hyperspectral dataset demonstrate the effectiveness of the proposed method.

  4. 32 CFR 2700.22 - Classification guides.

    Science.gov (United States)

    2010-07-01

    ... SECURITY INFORMATION REGULATIONS Derivative Classification § 2700.22 Classification guides. OMSN shall... direct derivative classification, shall identify the information to be protected in specific and uniform...

  5. Onboard spectral imager data processor

    Science.gov (United States)

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

    1999-10-01

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

  6. Intersection numbers of spectral curves

    CERN Document Server

    Eynard, B.

    2011-01-01

    We compute the symplectic invariants of an arbitrary spectral curve with only 1 branchpoint in terms of integrals of characteristic classes in the moduli space of curves. Our formula associates to any spectral curve, a characteristic class, which is determined by the laplace transform of the spectral curve. This is a hint to the key role of Laplace transform in mirror symmetry. When the spectral curve is y=\\sqrt{x}, the formula gives Kontsevich--Witten intersection numbers, when the spectral curve is chosen to be the Lambert function \\exp{x}=y\\exp{-y}, the formula gives the ELSV formula for Hurwitz numbers, and when one chooses the mirror of C^3 with framing f, i.e. \\exp{-x}=\\exp{-yf}(1-\\exp{-y}), the formula gives the Marino-Vafa formula, i.e. the generating function of Gromov-Witten invariants of C^3. In some sense this formula generalizes ELSV, Marino-Vafa formula, and Mumford formula.

  7. Spectral filtering for plant production

    Energy Technology Data Exchange (ETDEWEB)

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

    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 and 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.

  8. Spectral dimension of quantum geometries

    International Nuclear Information System (INIS)

    Calcagni, Gianluca; Oriti, Daniele; Thürigen, Johannes

    2014-01-01

    The spectral dimension is an indicator of geometry and topology of spacetime and a tool to compare the description of quantum geometry in various approaches to quantum gravity. This is possible because it can be defined not only on smooth geometries but also on discrete (e.g., simplicial) ones. In this paper, we consider the spectral dimension of quantum states of spatial geometry defined on combinatorial complexes endowed with additional algebraic data: the kinematical quantum states of loop quantum gravity (LQG). Preliminarily, the effects of topology and discreteness of classical discrete geometries are studied in a systematic manner. We look for states reproducing the spectral dimension of a classical space in the appropriate regime. We also test the hypothesis that in LQG, as in other approaches, there is a scale dependence of the spectral dimension, which runs from the topological dimension at large scales to a smaller one at short distances. While our results do not give any strong support to this hypothesis, we can however pinpoint when the topological dimension is reproduced by LQG quantum states. Overall, by exploring the interplay of combinatorial, topological and geometrical effects, and by considering various kinds of quantum states such as coherent states and their superpositions, we find that the spectral dimension of discrete quantum geometries is more sensitive to the underlying combinatorial structures than to the details of the additional data associated with them. (paper)

  9. Spectral Imaging of Portolan Charts

    Science.gov (United States)

    France, Fenella G.; Wilson, Meghan A.; Ghez, Anita

    2018-05-01

    Spectral imaging of Portolan Charts, early nautical charts, provided extensive new information about their construction and creation. The origins of the portolan chart style have been a continual source of perplexity to numerous generations of cartographic historians. The spectral imaging system utilized incorporates a 50 megapixel mono-chrome camera with light emitting diode (LED) illumination panels that cover the range from 365 nm to 1050 nm to capture visible and non-visible information. There is little known about how portolan charts evolved, and what influenced their creation. These early nautical charts began as working navigational tools of medieval mariners, initially made in the 1300s in Italy, Portugal and Spain; however the origin and development of the portolan chart remained shrouded in mystery. Questions about these early navigational charts included whether colorants were commensurate with the time period and geographical location, and if different, did that give insight into trade routes, or possible later additions to the charts? For example; spectral data showed the red pigment on both the 1320 portolan chart and the 1565 Galapagos Islands matched vermillion, an opaque red pigment used since antiquity. The construction of these charts was also of great interest. Spectral imaging with a range of illumination modes revealed the presence of a "hidden circle" often referred to in relation to their construction. This paper will present in-depth analysis of how spectral imaging of the Portolans revealed similarities and differences, new hidden information and shed new light on construction and composition.

  10. A spectral atlas of λ Bootis stars

    Directory of Open Access Journals (Sweden)

    Paunzen E.

    2014-01-01

    Full Text Available Since the discovery of λ Bootis stars, a permanent confusion about their classification can be found in literature. This group of non-magnetic, Population I, metal-poor A to F-type stars, has often been used as some sort of trash can for "exotic" and spectroscopically dubious objects. Some attempts have been made to establish a homogeneous group of stars which share the same common properties. Unfortunately, the flood of "new" information (e.g. UV and IR data led again to a whole zoo of objects classified as λ Bootis stars, which, however, are apparent non-members. To overcome this unsatisfying situation, a spectral atlas of well established λ Bootis stars for the classical optical domain was compiled. It includes intermediate dispersion (40 and 120Å mm-1 spectra of three λ Bootis, as well as appropriate MK standard stars. Furthermore, "suspicious" objects, such as shell and Field Horizontal Branch stars, have been considered in order to provide to classifiers a homogeneous reference. As a further step, a high resolution (8Å mm-1 spectrum of one "classical" λ Bootis star in the same wavelength region (3800-4600Å is presented. In total, 55 lines can be used for this particular star to derive detailed abundances for nine heavy elements (Mg, Ca, Sc, Ti, Cr, Mn, Fe, Sr and Ba.

  11. IAEA Classification of Uranium Deposits

    International Nuclear Information System (INIS)

    Bruneton, Patrice

    2014-01-01

    Classifications of uranium deposits follow two general approaches, focusing on: • descriptive features such as the geotectonic position, the host rock type, the orebody morphology, …… : « geologic classification »; • or on genetic aspects: « genetic classification »

  12. Classification of Osteogenesis Imperfecta revisited

    NARCIS (Netherlands)

    van Dijk, F. S.; Pals, G.; van Rijn, R. R.; Nikkels, P. G. J.; Cobben, J. M.

    2010-01-01

    In 1979 Sillence proposed a classification of Osteogenesis Imperfecta (OI) in OI types I, II, III and IV. In 2004 and 2007 this classification was expanded with OI types V-VIII because of distinct clinical features and/or different causative gene mutations. We propose a revised classification of OI

  13. The future of general classification

    DEFF Research Database (Denmark)

    Mai, Jens Erik

    2013-01-01

    Discusses problems related to accessing multiple collections using a single retrieval language. Surveys the concepts of interoperability and switching language. Finds that mapping between more indexing languages always will be an approximation. Surveys the issues related to general classification...... and contrasts that to special classifications. Argues for the use of general classifications to provide access to collections nationally and internationally....

  14. The process of undertaking a quantitative dissertation for a taught M.Sc: Personal insights gained from supporting and examining students in the UK and Ireland

    International Nuclear Information System (INIS)

    Marshall, Gill; Brennan, Patrick

    2008-01-01

    Purpose: This article discusses the roles of the student and the supervisor in the process of undertaking and writing a dissertation, a potentially daunting process. Results: The authors have supervised and examined students within 20 institutions and the personal insights gained result in the guidance provided within this article. Conclusion: The authors conclude that much can be done by students working with their supervisors, to improve progress in both performing and writing up the dissertation. Taking account of these factors will ease the dissertation process and move students progressively towards the production of a well-written dissertation

  15. Examination of Spectral Transformations on Spectral Mixture Analysis

    Science.gov (United States)

    Deng, Y.; Wu, C.

    2018-04-01

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

  16. Assessing therapeutic relevance of biologically interesting, ampholytic substances based on their physicochemical and spectral characteristics with chemometric tools

    Science.gov (United States)

    Judycka, U.; Jagiello, K.; Bober, L.; Błażejowski, J.; Puzyn, T.

    2018-06-01

    Chemometric tools were applied to investigate the biological behaviour of ampholytic substances in relation to their physicochemical and spectral properties. Results of the Principal Component Analysis suggest that size of molecules and their electronic and spectral characteristics are the key properties required to predict therapeutic relevance of the compounds examined. These properties were used for developing the structure-activity classification model. The classification model allows assessing the therapeutic behaviour of ampholytic substances on the basis of solely values of descriptors that can be obtained computationally. Thus, the prediction is possible without necessity of carrying out time-consuming and expensive laboratory tests, which is its main advantage.

  17. Berlin Reflectance Spectral Library (BRSL)

    Science.gov (United States)

    Henckel, D.; Arnold, G.; Kappel, D.; Moroz, L. V.; Markus, K.

    2017-09-01

    The Berlin Reflectance Spectral Library (BRSL) provides a collection of reflectance spectra between 0.3 and 17 µm. It was originally dedicated to support space missions to small solar system bodies. Meanwhile the library includes selections of biconical reflectance spectra for spectral data analysis of other planetary bodies as well. The library provides reference spectra of well-characterized terrestrial analogue materials and meteorites for interpretation of remote sensing reflectance spectra of planetary surfaces. We introduce the BRSL, summarize the data available, and access to use them for further relevant applications.

  18. Spectral ellipsometry of nanodiamond composite

    International Nuclear Information System (INIS)

    Yastrebov, S.G.; Ivanov-Omskij, V.I.; Gordeev, S.K.; Garriga, M.; Alonso, I.A.

    2006-01-01

    Methods of spectral ellipsometry were applied for analysis of optical properties of nanodiamond based composite in spectral region 1.4-5 eV. The nanocomposite was synthesized by molding of ultradispersed nanodiamond powder in the course of heterogeneous chemical reaction of decomposition of methane, forming pyrocarbon interconnecting nanodiamond grains. The energy of σ + π plasmon of pyrocarbon component of nanodiamond composite was restored which proves to be ∼ 24 eV; using this value, an estimation was done of pyrocarbon matrix density, which occurs to be 2 g/cm 3 [ru

  19. [Headache: classification and diagnosis].

    Science.gov (United States)

    Carbaat, P A T; Couturier, E G M

    2016-11-01

    There are many types of headache and, moreover, many people have different types of headache at the same time. Adequate treatment is possible only on the basis of the correct diagnosis. Technically and in terms of content the current diagnostics process for headache is based on the 'International Classification of Headache Disorders' (ICHD-3-beta) that was produced under the auspices of the International Headache Society. This classification is based on a distinction between primary and secondary headaches. The most common primary headache types are the tension type headache, migraine and the cluster headache. Application of uniform diagnostic concepts is essential to come to the most appropriate treatment of the various types of headache.

  20. Classification of hand eczema

    DEFF Research Database (Denmark)

    Agner, T; Aalto-Korte, K; Andersen, K E

    2015-01-01

    BACKGROUND: Classification of hand eczema (HE) is mandatory in epidemiological and clinical studies, and also important in clinical work. OBJECTIVES: The aim was to test a recently proposed classification system of HE in clinical practice in a prospective multicentre study. METHODS: Patients were...... recruited from nine different tertiary referral centres. All patients underwent examination by specialists in dermatology and were checked using relevant allergy testing. Patients were classified into one of the six diagnostic subgroups of HE: allergic contact dermatitis, irritant contact dermatitis, atopic...... system investigated in the present study was useful, being able to give an appropriate main diagnosis for 89% of HE patients, and for another 7% when using two main diagnoses. The fact that more than half of the patients had one or more additional diagnoses illustrates that HE is a multifactorial disease....

  1. Sound classification of dwellings

    DEFF Research Database (Denmark)

    Rasmussen, Birgit

    2012-01-01

    National schemes for sound classification of dwellings exist in more than ten countries in Europe, typically published as national standards. The schemes define quality classes reflecting different levels of acoustical comfort. Main criteria concern airborne and impact sound insulation between...... dwellings, facade sound insulation and installation noise. The schemes have been developed, implemented and revised gradually since the early 1990s. However, due to lack of coordination between countries, there are significant discrepancies, and new standards and revisions continue to increase the diversity...... is needed, and a European COST Action TU0901 "Integrating and Harmonizing Sound Insulation Aspects in Sustainable Urban Housing Constructions", has been established and runs 2009-2013, one of the main objectives being to prepare a proposal for a European sound classification scheme with a number of quality...

  2. Piroxicam derivatives THz classification

    Science.gov (United States)

    Sterczewski, Lukasz A.; Grzelczak, Michal P.; Nowak, Kacper; Szlachetko, Bogusław; Plinska, Stanislawa; Szczesniak-Siega, Berenika; Malinka, Wieslaw; Plinski, Edward F.

    2016-02-01

    In this paper we report a new approach to linking the terahertz spectral shapes of drug candidates having a similar molecular structure to their chemical and physical parameters. We examined 27 newly-synthesized derivatives of a well-known nonsteroidal anti-inflammatory drug Piroxicam used for treatment of inflammatory arthritis and chemoprevention of colon cancer. The testing was carried out by means of terahertz pulsed spectroscopy (TPS). Using chemometric techniques we evaluated their spectral similarity in the terahertz range and attempted to link the position on the principal component analysis (PCA) score map to the similarity of molecular descriptors. A simplified spectral model preserved 75% and 85.1% of the variance in 2 and 3 dimensions respectively, compared to the input 1137. We have found that in 85% of the investigated samples a similarity of the physical and chemical parameters corresponds to a similarity in the terahertz spectra. The effects of data preprocessing on the generated maps are also discussed. The technique presented can support the choice of the most promising drug candidates for clinical trials in pharmacological research.

  3. Granular loess classification based

    International Nuclear Information System (INIS)

    Browzin, B.S.

    1985-01-01

    This paper discusses how loess might be identified by two index properties: the granulometric composition and the dry unit weight. These two indices are necessary but not always sufficient for identification of loess. On the basis of analyses of samples from three continents, it was concluded that the 0.01-0.5-mm fraction deserves the name loessial fraction. Based on the loessial fraction concept, a granulometric classification of loess is proposed. A triangular chart is used to classify loess

  4. Classification and regression trees

    CERN Document Server

    Breiman, Leo; Olshen, Richard A; Stone, Charles J

    1984-01-01

    The methodology used to construct tree structured rules is the focus of this monograph. Unlike many other statistical procedures, which moved from pencil and paper to calculators, this text's use of trees was unthinkable before computers. Both the practical and theoretical sides have been developed in the authors' study of tree methods. Classification and Regression Trees reflects these two sides, covering the use of trees as a data analysis method, and in a more mathematical framework, proving some of their fundamental properties.

  5. CLASSIFICATION OF CRIMINAL GROUPS

    OpenAIRE

    Natalia Romanova

    2013-01-01

    New types of criminal groups are emerging in modern society.  These types have their special criminal subculture. The research objective is to develop new parameters of classification of modern criminal groups, create a new typology of criminal groups and identify some features of their subculture. Research methodology is based on the system approach that includes using the method of analysis of documentary sources (materials of a criminal case), method of conversations with themembers of the...

  6. Decimal Classification Editions

    Directory of Open Access Journals (Sweden)

    Zenovia Niculescu

    2009-01-01

    Full Text Available The study approaches the evolution of Dewey Decimal Classification editions from the perspective of updating the terminology, reallocating and expanding the main and auxilary structure of Dewey indexing language. The comparative analysis of DDC editions emphasizes the efficiency of Dewey scheme from the point of view of improving the informational offer, through basic index terms, revised and developed, as well as valuing the auxilary notations.

  7. Decimal Classification Editions

    OpenAIRE

    Zenovia Niculescu

    2009-01-01

    The study approaches the evolution of Dewey Decimal Classification editions from the perspective of updating the terminology, reallocating and expanding the main and auxilary structure of Dewey indexing language. The comparative analysis of DDC editions emphasizes the efficiency of Dewey scheme from the point of view of improving the informational offer, through basic index terms, revised and developed, as well as valuing the auxilary notations.

  8. Classifications of track structures

    International Nuclear Information System (INIS)

    Paretzke, H.G.

    1984-01-01

    When ionizing particles interact with matter they produce random topological structures of primary activations which represent the initial boundary conditions for all subsequent physical, chemical and/or biological reactions. There are two important aspects of research on such track structures, namely their experimental or theoretical determination on one hand and the quantitative classification of these complex structures which is a basic pre-requisite for the understanding of mechanisms of radiation actions. This paper deals only with the latter topic, i.e. the problems encountered in and possible approaches to quantitative ordering and grouping of these multidimensional objects by their degrees of similarity with respect to their efficiency in producing certain final radiation effects, i.e. to their ''radiation quality.'' Various attempts of taxonometric classification with respect to radiation efficiency have been made in basic and applied radiation research including macro- and microdosimetric concepts as well as track entities and stopping power based theories. In this paper no review of those well-known approaches is given but rather an outline and discussion of alternative methods new to this field of radiation research which have some very promising features and which could possibly solve at least some major classification problems

  9. Neuromuscular disease classification system

    Science.gov (United States)

    Sáez, Aurora; Acha, Begoña; Montero-Sánchez, Adoración; Rivas, Eloy; Escudero, Luis M.; Serrano, Carmen

    2013-06-01

    Diagnosis of neuromuscular diseases is based on subjective visual assessment of biopsies from patients by the pathologist specialist. A system for objective analysis and classification of muscular dystrophies and neurogenic atrophies through muscle biopsy images of fluorescence microscopy is presented. The procedure starts with an accurate segmentation of the muscle fibers using mathematical morphology and a watershed transform. A feature extraction step is carried out in two parts: 24 features that pathologists take into account to diagnose the diseases and 58 structural features that the human eye cannot see, based on the assumption that the biopsy is considered as a graph, where the nodes are represented by each fiber, and two nodes are connected if two fibers are adjacent. A feature selection using sequential forward selection and sequential backward selection methods, a classification using a Fuzzy ARTMAP neural network, and a study of grading the severity are performed on these two sets of features. A database consisting of 91 images was used: 71 images for the training step and 20 as the test. A classification error of 0% was obtained. It is concluded that the addition of features undetectable by the human visual inspection improves the categorization of atrophic patterns.

  10. An automated cirrus classification

    Science.gov (United States)

    Gryspeerdt, Edward; Quaas, Johannes; Goren, Tom; Klocke, Daniel; Brueck, Matthias

    2018-05-01

    Cirrus clouds play an important role in determining the radiation budget of the earth, but many of their properties remain uncertain, particularly their response to aerosol variations and to warming. Part of the reason for this uncertainty is the dependence of cirrus cloud properties on the cloud formation mechanism, which itself is strongly dependent on the local meteorological conditions. In this work, a classification system (Identification and Classification of Cirrus or IC-CIR) is introduced to identify cirrus clouds by the cloud formation mechanism. Using reanalysis and satellite data, cirrus clouds are separated into four main types: orographic, frontal, convective and synoptic. Through a comparison to convection-permitting model simulations and back-trajectory-based analysis, it is shown that these observation-based regimes can provide extra information on the cloud-scale updraughts and the frequency of occurrence of liquid-origin ice, with the convective regime having higher updraughts and a greater occurrence of liquid-origin ice compared to the synoptic regimes. Despite having different cloud formation mechanisms, the radiative properties of the regimes are not distinct, indicating that retrieved cloud properties alone are insufficient to completely describe them. This classification is designed to be easily implemented in GCMs, helping improve future model-observation comparisons and leading to improved parametrisations of cirrus cloud processes.

  11. Hyperspectral imaging of polymer banknotes for building and analysis of spectral library

    Science.gov (United States)

    Lim, Hoong-Ta; Murukeshan, Vadakke Matham

    2017-11-01

    The use of counterfeit banknotes increases crime rates and cripples the economy. New countermeasures are required to stop counterfeiters who use advancing technologies with criminal intent. Many countries started adopting polymer banknotes to replace paper notes, as polymer notes are more durable and have better quality. The research on authenticating such banknotes is of much interest to the forensic investigators. Hyperspectral imaging can be employed to build a spectral library of polymer notes, which can then be used for classification to authenticate these notes. This is however not widely reported and has become a research interest in forensic identification. This paper focuses on the use of hyperspectral imaging on polymer notes to build spectral libraries, using a pushbroom hyperspectral imager which has been previously reported. As an initial study, a spectral library will be built from three arbitrarily chosen regions of interest of five circulated genuine polymer notes. Principal component analysis is used for dimension reduction and to convert the information in the spectral library to principal components. A 99% confidence ellipse is formed around the cluster of principal component scores of each class and then used as classification criteria. The potential of the adopted methodology is demonstrated by the classification of the imaged regions as training samples.

  12. Maximum mutual information regularized classification

    KAUST Repository

    Wang, Jim Jing-Yan

    2014-09-07

    In this paper, a novel pattern classification approach is proposed by regularizing the classifier learning to maximize mutual information between the classification response and the true class label. We argue that, with the learned classifier, the uncertainty of the true class label of a data sample should be reduced by knowing its classification response as much as possible. The reduced uncertainty is measured by the mutual information between the classification response and the true class label. To this end, when learning a linear classifier, we propose to maximize the mutual information between classification responses and true class labels of training samples, besides minimizing the classification error and reducing the classifier complexity. An objective function is constructed by modeling mutual information with entropy estimation, and it is optimized by a gradient descend method in an iterative algorithm. Experiments on two real world pattern classification problems show the significant improvements achieved by maximum mutual information regularization.

  13. Maximum mutual information regularized classification

    KAUST Repository

    Wang, Jim Jing-Yan; Wang, Yi; Zhao, Shiguang; Gao, Xin

    2014-01-01

    In this paper, a novel pattern classification approach is proposed by regularizing the classifier learning to maximize mutual information between the classification response and the true class label. We argue that, with the learned classifier, the uncertainty of the true class label of a data sample should be reduced by knowing its classification response as much as possible. The reduced uncertainty is measured by the mutual information between the classification response and the true class label. To this end, when learning a linear classifier, we propose to maximize the mutual information between classification responses and true class labels of training samples, besides minimizing the classification error and reducing the classifier complexity. An objective function is constructed by modeling mutual information with entropy estimation, and it is optimized by a gradient descend method in an iterative algorithm. Experiments on two real world pattern classification problems show the significant improvements achieved by maximum mutual information regularization.

  14. Optimized extreme learning machine for urban land cover classification using hyperspectral imagery

    Science.gov (United States)

    Su, Hongjun; Tian, Shufang; Cai, Yue; Sheng, Yehua; Chen, Chen; Najafian, Maryam

    2017-12-01

    This work presents a new urban land cover classification framework using the firefly algorithm (FA) optimized extreme learning machine (ELM). FA is adopted to optimize the regularization coefficient C and Gaussian kernel σ for kernel ELM. Additionally, effectiveness of spectral features derived from an FA-based band selection algorithm is studied for the proposed classification task. Three sets of hyperspectral databases were recorded using different sensors, namely HYDICE, HyMap, and AVIRIS. Our study shows that the proposed method outperforms traditional classification algorithms such as SVM and reduces computational cost significantly.

  15. Observed spectral features of dust

    International Nuclear Information System (INIS)

    Willner, S.P.

    1984-01-01

    The author concentrates on the observed properties of dust spectral features. Identifications, based on laboratory data, are given whenever plausible ones exist. There are a very large number of papers in the literature of even such a young field as infrared spectroscopy, and therefore the author refers only to the most recent paper on a topic or to another review. (Auth.)

  16. Rayleigh imaging in spectral mammography

    Science.gov (United States)

    Berggren, Karl; Danielsson, Mats; Fredenberg, Erik

    2016-03-01

    Spectral imaging is the acquisition of multiple images of an object at different energy spectra. In mammography, dual-energy imaging (spectral imaging with two energy levels) has been investigated for several applications, in particular material decomposition, which allows for quantitative analysis of breast composition and quantitative contrast-enhanced imaging. Material decomposition with dual-energy imaging is based on the assumption that there are two dominant photon interaction effects that determine linear attenuation: the photoelectric effect and Compton scattering. This assumption limits the number of basis materials, i.e. the number of materials that are possible to differentiate between, to two. However, Rayleigh scattering may account for more than 10% of the linear attenuation in the mammography energy range. In this work, we show that a modified version of a scanning multi-slit spectral photon-counting mammography system is able to acquire three images at different spectra and can be used for triple-energy imaging. We further show that triple-energy imaging in combination with the efficient scatter rejection of the system enables measurement of Rayleigh scattering, which adds an additional energy dependency to the linear attenuation and enables material decomposition with three basis materials. Three available basis materials have the potential to improve virtually all applications of spectral imaging.

  17. Speech recognition from spectral dynamics

    Indian Academy of Sciences (India)

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

  18. Spectral ansatz in quantum electrodynamics

    International Nuclear Information System (INIS)

    Atkinson, D.; Slim, H.A.

    1979-01-01

    An ansatz of Delbourgo and Salam for the spectral representation of the vertex function in quantum electrodynamics. The Ward-Takahashi identity is respected, and the electron propagator does not have a ghost. The infra-red and ultraviolet behaviours of the electron propagator in this theory are considered, and a rigorous existence theorem for the propagator in the Yennie gauge is presented

  19. Spectral Diagonal Ensemble Kalman Filters

    Czech Academy of Sciences Publication Activity Database

    Kasanický, Ivan; Mandel, Jan; Vejmelka, Martin

    2015-01-01

    Roč. 22, č. 4 (2015), s. 485-497 ISSN 1023-5809 R&D Projects: GA ČR GA13-34856S Grant - others:NSF(US) DMS-1216481 Institutional support: RVO:67985807 Keywords : data assimilation * ensemble Kalman filter * spectral representation Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 1.321, year: 2015

  20. Biomarkers and Biological Spectral Imaging

    Science.gov (United States)

    2001-01-23

    G. Sowa, H. H. Mantsch, National Research Council Canada; S. L. Zhang, Unilever Research (USA) 85 Brain tissue charcterization using spectral imaging...image registration and of the expert staff of Hill Top Research in Winnipeg for hosting the hydration study. Financial assistance from Unilever Research

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

    International Nuclear Information System (INIS)

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

    2014-01-01

    In high resolution data classification process, combining texture features with spectral bands can effectively improve the classification accuracy. However, the window size which is difficult to choose is regarded as an important factor influencing overall classification accuracy in textural classification and current approaches to image texture analysis only depend on a single moving window which ignores different scale features of various land cover types. In this paper, we propose a new method based on the fusion of multiscale texture features to overcome these problems. The main steps in new method include the classification of fixed window size spectral/textural images from 3×3 to 15×15 and comparison of all the posterior possibility values for every pixel, as a result the biggest probability value is given to the pixel and the pixel belongs to a certain land cover type automatically. The proposed approach is tested on University of Pavia ROSIS data. The results indicate that the new method improve the classification accuracy compared to results of methods based on fixed window size textural classification

  2. Integration of heterogeneous features for remote sensing scene classification

    Science.gov (United States)

    Wang, Xin; Xiong, Xingnan; Ning, Chen; Shi, Aiye; Lv, Guofang

    2018-01-01

    Scene classification is one of the most important issues in remote sensing (RS) image processing. We find that features from different channels (shape, spectral, texture, etc.), levels (low-level and middle-level), or perspectives (local and global) could provide various properties for RS images, and then propose a heterogeneous feature framework to extract and integrate heterogeneous features with different types for RS scene classification. The proposed method is composed of three modules (1) heterogeneous features extraction, where three heterogeneous feature types, called DS-SURF-LLC, mean-Std-LLC, and MS-CLBP, are calculated, (2) heterogeneous features fusion, where the multiple kernel learning (MKL) is utilized to integrate the heterogeneous features, and (3) an MKL support vector machine classifier for RS scene classification. The proposed method is extensively evaluated on three challenging benchmark datasets (a 6-class dataset, a 12-class dataset, and a 21-class dataset), and the experimental results show that the proposed method leads to good classification performance. It produces good informative features to describe the RS image scenes. Moreover, the integration of heterogeneous features outperforms some state-of-the-art features on RS scene classification tasks.

  3. Hyperspectral small animal fluorescence imaging: spectral selection imaging

    Science.gov (United States)

    Leavesley, Silas; Jiang, Yanan; Patsekin, Valery; Hall, Heidi; Vizard, Douglas; Robinson, J. Paul

    2008-02-01

    Molecular imaging is a rapidly growing area of research, fueled by needs in pharmaceutical drug-development for methods for high-throughput screening, pre-clinical and clinical screening for visualizing tumor growth and drug targeting, and a growing number of applications in the molecular biology fields. Small animal fluorescence imaging employs fluorescent probes to target molecular events in vivo, with a large number of molecular targeting probes readily available. The ease at which new targeting compounds can be developed, the short acquisition times, and the low cost (compared to microCT, MRI, or PET) makes fluorescence imaging attractive. However, small animal fluorescence imaging suffers from high optical scattering, absorption, and autofluorescence. Much of these problems can be overcome through multispectral imaging techniques, which collect images at different fluorescence emission wavelengths, followed by analysis, classification, and spectral deconvolution methods to isolate signals from fluorescence emission. We present an alternative to the current method, using hyperspectral excitation scanning (spectral selection imaging), a technique that allows excitation at any wavelength in the visible and near-infrared wavelength range. In many cases, excitation imaging may be more effective at identifying specific fluorescence signals because of the higher complexity of the fluorophore excitation spectrum. Because the excitation is filtered and not the emission, the resolution limit and image shift imposed by acousto-optic tunable filters have no effect on imager performance. We will discuss design of the imager, optimizing the imager for use in small animal fluorescence imaging, and application of spectral analysis and classification methods for identifying specific fluorescence signals.

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

    International Nuclear Information System (INIS)

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

    2015-01-01

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

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

    Science.gov (United States)

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

    2015-08-01

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

  6. The Ultracool Typing Kit - An Open-Source, Qualitative Spectral Typing GUI for L Dwarfs

    Science.gov (United States)

    Schwab, Ellianna; Cruz, Kelle; Núñez, Alejandro; Burgasser, Adam J.; Rice, Emily; Reid, Neill; Faherty, Jacqueline K.; BDNYC

    2018-01-01

    The Ultracool Typing Kit (UTK) is an open-source graphical user interface for classifying the NIR spectral types of L dwarfs, including field and low-gravity dwarfs spanning L0-L9. The user is able to input an NIR spectrum and qualitatively compare the input spectrum to a full suite of spectral templates, including low-gravity beta and gamma templates. The user can choose to view the input spectrum as both a band-by-band comparison with the templates and a full bandwidth comparison with NIR spectral standards. Once an optimal qualitative comparison is selected, the user can save their spectral type selection both graphically and to a database. Using UTK to classify 78 previously typed L dwarfs, we show that a band-by-band classification method more accurately agrees with optical spectral typing systems than previous L dwarf NIR classification schemes. UTK is written in python, released on Zenodo with a BSD-3 clause license and publicly available on the BDNYC Github page.

  7. SPORT FOOD ADDITIVE CLASSIFICATION

    Directory of Open Access Journals (Sweden)

    I. P. Prokopenko

    2015-01-01

    Full Text Available Correctly organized nutritive and pharmacological support is an important component of an athlete's preparation for competitions, an optimal shape maintenance, fast recovery and rehabilitation after traumas and defatigation. Special products of enhanced biological value (BAS for athletes nutrition are used with this purpose. Easy-to-use energy sources are administered into athlete's organism, yielded materials and biologically active substances which regulate and activate exchange reactions which proceed with difficulties during certain physical trainings. The article presents sport supplements classification which can be used before warm-up and trainings, after trainings and in competitions breaks.

  8. Radioactive facilities classification criteria

    International Nuclear Information System (INIS)

    Briso C, H.A.; Riesle W, J.

    1992-01-01

    Appropriate classification of radioactive facilities into groups of comparable risk constitutes one of the problems faced by most Regulatory Bodies. Regarding the radiological risk, the main facts to be considered are the radioactive inventory and the processes to which these radionuclides are subjected. Normally, operations are ruled by strict safety procedures. Thus, the total activity of the radionuclides existing in a given facility is the varying feature that defines its risk. In order to rely on a quantitative criterion and, considering that the Annual Limits of Intake are widely accepted references, an index based on these limits, to support decisions related to radioactive facilities, is proposed. (author)

  9. Spectral autofluorescence imaging of the retina for drusen detection

    Science.gov (United States)

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

    2018-02-01

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

  10. Obstacles to researching the researchers: a case study of the ethical challenges of undertaking methodological research investigating the reporting of randomised controlled trials.

    Science.gov (United States)

    McKenzie, Joanne E; Herbison, G Peter; Roth, Paul; Paul, Charlotte

    2010-03-21

    Recent cohort studies of randomised controlled trials have provided evidence of within-study selective reporting bias; where statistically significant outcomes are more likely to be more completely reported compared to non-significant outcomes. Bias resulting from selective reporting can impact on meta-analyses, influencing the conclusions of systematic reviews, and in turn, evidence based clinical practice guidelines.In 2006 we received funding to investigate if there was evidence of within-study selective reporting in a cohort of RCTs submitted to New Zealand Regional Ethics Committees in 1998/99. This research involved accessing ethics applications, their amendments and annual reports, and comparing these with corresponding publications. We did not plan to obtain informed consent from trialists to view their ethics applications for practical and scientific reasons. In November 2006 we sought ethical approval to undertake the research from our institutional ethics committee. The Committee declined our application on the grounds that we were not obtaining informed consent from the trialists to view their ethics application. This initiated a seventeen month process to obtain ethical approval. This publication outlines what we planned to do, the issues we encountered, discusses the legal and ethical issues, and presents some potential solutions. Methodological research such as this has the potential for public benefit and there is little or no harm for the participants (trialists) in undertaking it. Further, in New Zealand, there is freedom of information legislation, which in this circumstance, unambiguously provided rights of access and use of the information in the ethics applications. The decision of our institutional ethics committee defeated this right and did not recognise the nature of this observational research. Methodological research, such as this, can be used to develop processes to improve quality in research reporting. Recognition of the potential

  11. Supply chain planning classification

    Science.gov (United States)

    Hvolby, Hans-Henrik; Trienekens, Jacques; Bonde, Hans

    2001-10-01

    Industry experience a need to shift in focus from internal production planning towards planning in the supply network. In this respect customer oriented thinking becomes almost a common good amongst companies in the supply network. An increase in the use of information technology is needed to enable companies to better tune their production planning with customers and suppliers. Information technology opportunities and supply chain planning systems facilitate companies to monitor and control their supplier network. In spite if these developments, most links in today's supply chains make individual plans, because the real demand information is not available throughout the chain. The current systems and processes of the supply chains are not designed to meet the requirements now placed upon them. For long term relationships with suppliers and customers, an integrated decision-making process is needed in order to obtain a satisfactory result for all parties. Especially when customized production and short lead-time is in focus. An effective value chain makes inventory available and visible among the value chain members, minimizes response time and optimizes total inventory value held throughout the chain. In this paper a supply chain planning classification grid is presented based current manufacturing classifications and supply chain planning initiatives.

  12. Waste classification sampling plan

    International Nuclear Information System (INIS)

    Landsman, S.D.

    1998-01-01

    The purpose of this sampling is to explain the method used to collect and analyze data necessary to verify and/or determine the radionuclide content of the B-Cell decontamination and decommissioning waste stream so that the correct waste classification for the waste stream can be made, and to collect samples for studies of decontamination methods that could be used to remove fixed contamination present on the waste. The scope of this plan is to establish the technical basis for collecting samples and compiling quantitative data on the radioactive constituents present in waste generated during deactivation activities in B-Cell. Sampling and radioisotopic analysis will be performed on the fixed layers of contamination present on structural material and internal surfaces of process piping and tanks. In addition, dose rate measurements on existing waste material will be performed to determine the fraction of dose rate attributable to both removable and fixed contamination. Samples will also be collected to support studies of decontamination methods that are effective in removing the fixed contamination present on the waste. Sampling performed under this plan will meet criteria established in BNF-2596, Data Quality Objectives for the B-Cell Waste Stream Classification Sampling, J. M. Barnett, May 1998

  13. Cluster Based Text Classification Model

    DEFF Research Database (Denmark)

    Nizamani, Sarwat; Memon, Nasrullah; Wiil, Uffe Kock

    2011-01-01

    We propose a cluster based classification model for suspicious email detection and other text classification tasks. The text classification tasks comprise many training examples that require a complex classification model. Using clusters for classification makes the model simpler and increases...... the accuracy at the same time. The test example is classified using simpler and smaller model. The training examples in a particular cluster share the common vocabulary. At the time of clustering, we do not take into account the labels of the training examples. After the clusters have been created......, the classifier is trained on each cluster having reduced dimensionality and less number of examples. The experimental results show that the proposed model outperforms the existing classification models for the task of suspicious email detection and topic categorization on the Reuters-21578 and 20 Newsgroups...

  14. Classification of smooth Fano polytopes

    DEFF Research Database (Denmark)

    Øbro, Mikkel

    A simplicial lattice polytope containing the origin in the interior is called a smooth Fano polytope, if the vertices of every facet is a basis of the lattice. The study of smooth Fano polytopes is motivated by their connection to toric varieties. The thesis concerns the classification of smooth...... Fano polytopes up to isomorphism. A smooth Fano -polytope can have at most vertices. In case of vertices an explicit classification is known. The thesis contains the classification in case of vertices. Classifications of smooth Fano -polytopes for fixed exist only for . In the thesis an algorithm...... for the classification of smooth Fano -polytopes for any given is presented. The algorithm has been implemented and used to obtain the complete classification for ....

  15. Small-scale classification schemes

    DEFF Research Database (Denmark)

    Hertzum, Morten

    2004-01-01

    Small-scale classification schemes are used extensively in the coordination of cooperative work. This study investigates the creation and use of a classification scheme for handling the system requirements during the redevelopment of a nation-wide information system. This requirements...... classification inherited a lot of its structure from the existing system and rendered requirements that transcended the framework laid out by the existing system almost invisible. As a result, the requirements classification became a defining element of the requirements-engineering process, though its main...... effects remained largely implicit. The requirements classification contributed to constraining the requirements-engineering process by supporting the software engineers in maintaining some level of control over the process. This way, the requirements classification provided the software engineers...

  16. Spectral synchronicity in brain signals

    KAUST Repository

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

    2018-01-01

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

  17. Spectral synchronicity in brain signals

    KAUST Repository

    de Jesus Euan Campos, Carolina

    2018-05-04

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

  18. Spectral computations for bounded operators

    CERN Document Server

    Ahues, Mario; Limaye, Balmohan

    2001-01-01

    Exact eigenvalues, eigenvectors, and principal vectors of operators with infinite dimensional ranges can rarely be found. Therefore, one must approximate such operators by finite rank operators, then solve the original eigenvalue problem approximately. Serving as both an outstanding text for graduate students and as a source of current results for research scientists, Spectral Computations for Bounded Operators addresses the issue of solving eigenvalue problems for operators on infinite dimensional spaces. From a review of classical spectral theory through concrete approximation techniques to finite dimensional situations that can be implemented on a computer, this volume illustrates the marriage of pure and applied mathematics. It contains a variety of recent developments, including a new type of approximation that encompasses a variety of approximation methods but is simple to verify in practice. It also suggests a new stopping criterion for the QR Method and outlines advances in both the iterative refineme...

  19. Utility of multispectral imaging for nuclear classification of routine clinical histopathology imagery

    Directory of Open Access Journals (Sweden)

    Harvey Neal R

    2007-07-01

    Full Text Available Abstract Background We present an analysis of the utility of multispectral versus standard RGB imagery for routine H&E stained histopathology images, in particular for pixel-level classification of nuclei. Our multispectral imagery has 29 spectral bands, spaced 10 nm within the visual range of 420–700 nm. It has been hypothesized that the additional spectral bands contain further information useful for classification as compared to the 3 standard bands of RGB imagery. We present analyses of our data designed to test this hypothesis. Results For classification using all available image bands, we find the best performance (equal tradeoff between detection rate and false alarm rate is obtained from either the multispectral or our "ccd" RGB imagery, with an overall increase in performance of 0.79% compared to the next best performing image type. For classification using single image bands, the single best multispectral band (in the red portion of the spectrum gave a performance increase of 0.57%, compared to performance of the single best RGB band (red. Additionally, red bands had the highest coefficients/preference in our classifiers. Principal components analysis of the multispectral imagery indicates only two significant image bands, which is not surprising given the presence of two stains. Conclusion Our results indicate that multispectral imagery for routine H&E stained histopathology provides minimal additional spectral information for a pixel-level nuclear classification task than would standard RGB imagery.

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

    International Nuclear Information System (INIS)

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

    2010-01-01

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

  1. AN EXTENDED SPECTRAL–SPATIAL CLASSIFICATION APPROACH FOR HYPERSPECTRAL DATA

    Directory of Open Access Journals (Sweden)

    D. Akbari

    2017-11-01

    Full Text Available 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.

  2. CLASSIFICATION AND RECOGNITION OF TOMB INFORMATION IN HYPERSPECTRAL IMAGE

    Directory of Open Access Journals (Sweden)

    M. Gu

    2018-04-01

    Full Text Available There are a large number of materials with important historical information in ancient tombs. However, in many cases, these substances could become obscure and indistinguishable by human naked eye or true colour camera. In order to classify and identify materials in ancient tomb effectively, this paper applied hyperspectral imaging technology to archaeological research of ancient tomb in Shanxi province. Firstly, the feature bands including the main information at the bottom of the ancient tomb are selected by the Principal Component Analysis (PCA transformation to realize the data dimension. Then, the image classification was performed using Support Vector Machine (SVM based on feature bands. Finally, the material at the bottom of ancient tomb is identified by spectral analysis and spectral matching. The results show that SVM based on feature bands can not only ensure the classification accuracy, but also shorten the data processing time and improve the classification efficiency. In the material identification, it is found that the same matter identified in the visible light is actually two different substances. This research result provides a new reference and research idea for archaeological work.

  3. Object Classification Using Airborne Multispectral LiDAR Data

    Directory of Open Access Journals (Sweden)

    PAN Suoyan

    2018-02-01

    Full Text Available Airborne multispectral LiDAR system,which obtains surface geometry and spectral data of objects,simultaneously,has become a fast effective,large-scale spatial data acquisition method.Multispectral LiDAR data are characteristics of completeness and consistency of spectrum and spatial geometric information.Support vector machine (SVM,a machine learning method,is capable of classifying objects based on small samples.Therefore,by means of SVM,this paper performs land cover classification using multispectral LiDAR data. First,all independent point cloud with different wavelengths are merged into a single point cloud,where each pixel contains the three-wavelength spectral information.Next,the merged point cloud is converted into range and intensity images.Finally,land-cover classification is performed by means of SVM.All experiments were conducted on the Optech Titan multispectral LiDAR data,containing three individual point cloud collected by 532 nm,1024 nm,and 1550 nm laser beams.Experimental results demonstrate that ①compared to traditional single-wavelength LiDAR data,multispectral LiDAR data provide a promising solution to land use and land cover applications;②SVM is a feasible method for land cover classification of multispectral LiDAR data.

  4. Classification and Recognition of Tomb Information in Hyperspectral Image

    Science.gov (United States)

    Gu, M.; Lyu, S.; Hou, M.; Ma, S.; Gao, Z.; Bai, S.; Zhou, P.

    2018-04-01

    There are a large number of materials with important historical information in ancient tombs. However, in many cases, these substances could become obscure and indistinguishable by human naked eye or true colour camera. In order to classify and identify materials in ancient tomb effectively, this paper applied hyperspectral imaging technology to archaeological research of ancient tomb in Shanxi province. Firstly, the feature bands including the main information at the bottom of the ancient tomb are selected by the Principal Component Analysis (PCA) transformation to realize the data dimension. Then, the image classification was performed using Support Vector Machine (SVM) based on feature bands. Finally, the material at the bottom of ancient tomb is identified by spectral analysis and spectral matching. The results show that SVM based on feature bands can not only ensure the classification accuracy, but also shorten the data processing time and improve the classification efficiency. In the material identification, it is found that the same matter identified in the visible light is actually two different substances. This research result provides a new reference and research idea for archaeological work.

  5. Modal planes are spectral triples

    International Nuclear Information System (INIS)

    Gayral, Victor; Iochum, Bruno; Schuecker, Thomas; Gracia-Bondia, Jose M.; Varilly, Joseph C.

    2003-09-01

    Axioms for nonunital spectral triples, extending those introduced in the unital case by Connes, are proposed. As a guide, and for the sake of their importance in noncommutative quantum field theory, the spaces R 2N endowed with Moyal products are intensively investigated. Some physical applications, such as the construction of noncommutative Wick monomials and the computation of the Connes-Lott functional action, are given for these noncommutative hyperplanes. (author)

  6. Chebyshev and Fourier spectral methods

    CERN Document Server

    Boyd, John P

    2001-01-01

    Completely revised text focuses on use of spectral methods to solve boundary value, eigenvalue, and time-dependent problems, but also covers Hermite, Laguerre, rational Chebyshev, sinc, and spherical harmonic functions, as well as cardinal functions, linear eigenvalue problems, matrix-solving methods, coordinate transformations, methods for unbounded intervals, spherical and cylindrical geometry, and much more. 7 Appendices. Glossary. Bibliography. Index. Over 160 text figures.

  7. Active Learning for Text Classification

    OpenAIRE

    Hu, Rong

    2011-01-01

    Text classification approaches are used extensively to solve real-world challenges. The success or failure of text classification systems hangs on the datasets used to train them, without a good dataset it is impossible to build a quality system. This thesis examines the applicability of active learning in text classification for the rapid and economical creation of labelled training data. Four main contributions are made in this thesis. First, we present two novel selection strategies to cho...

  8. Unsupervised Classification Using Immune Algorithm

    OpenAIRE

    Al-Muallim, M. T.; El-Kouatly, R.

    2012-01-01

    Unsupervised classification algorithm based on clonal selection principle named Unsupervised Clonal Selection Classification (UCSC) is proposed in this paper. The new proposed algorithm is data driven and self-adaptive, it adjusts its parameters to the data to make the classification operation as fast as possible. The performance of UCSC is evaluated by comparing it with the well known K-means algorithm using several artificial and real-life data sets. The experiments show that the proposed U...

  9. Abundance estimation of spectrally similar minerals

    CSIR Research Space (South Africa)

    Debba, Pravesh

    2009-07-01

    Full Text Available This paper evaluates a spectral unmixing method for estimating the partial abundance of spectrally similar minerals in complex mixtures. The method requires formulation of a linear function of individual spectra of individual minerals. The first...

  10. Hybrid image classification technique for land-cover mapping in the Arctic tundra, North Slope, Alaska

    Science.gov (United States)

    Chaudhuri, Debasish

    Remotely sensed image classification techniques are very useful to understand vegetation patterns and species combination in the vast and mostly inaccessible arctic region. Previous researches that were done for mapping of land cover and vegetation in the remote areas of northern Alaska have considerably low accuracies compared to other biomes. The unique arctic tundra environment with short growing season length, cloud cover, low sun angles, snow and ice cover hinders the effectiveness of remote sensing studies. The majority of image classification research done in this area as reported in the literature used traditional unsupervised clustering technique with Landsat MSS data. It was also emphasized by previous researchers that SPOT/HRV-XS data lacked the spectral resolution to identify the small arctic tundra vegetation parcels. Thus, there is a motivation and research need to apply a new classification technique to develop an updated, detailed and accurate vegetation map at a higher spatial resolution i.e. SPOT-5 data. Traditional classification techniques in remotely sensed image interpretation are based on spectral reflectance values with an assumption of the training data being normally distributed. Hence it is difficult to add ancillary data in classification procedures to improve accuracy. The purpose of this dissertation was to develop a hybrid image classification approach that effectively integrates ancillary information into the classification process and combines ISODATA clustering, rule-based classifier and the Multilayer Perceptron (MLP) classifier which uses artificial neural network (ANN). The main goal was to find out the best possible combination or sequence of classifiers for typically classifying tundra type vegetation that yields higher accuracy than the existing classified vegetation map from SPOT data. Unsupervised ISODATA clustering and rule-based classification techniques were combined to produce an intermediate classified map which was

  11. Using Social Cognitive Theory to Explain the Intention of Final-year Pharmacy Students to Undertake a Higher Degree in Pharmacy Practice Research.

    Science.gov (United States)

    Carter, Stephen R; Moles, Rebekah J; Krass, Ines; Kritikos, Vicki S

    2016-08-25

    Objective. To develop and test a conceptual model that hypothesized student intention to undertake a higher degree in pharmacy practice research (PPR) would be increased by self-efficacy, outcome expectancy, and the social influence of faculty members. Methods. Cross-sectional surveys were completed by 387 final-year pharmacy undergraduates enrolled in 2012 and 2013. Structural equation modeling was used to explore relationships between variables and intention. Results. Fit indices were good. The model explained 55% of the variation in intention. As hypothesized, faculty social influence increased self-efficacy and indirectly increased outcome expectancy and intention. Conclusion. To increase pharmacy students' orientation towards a career in PPR, faculty members could use their social influence by highlighting PPR in their teaching.

  12. Reliability of Oronasal Fistula Classification.

    Science.gov (United States)

    Sitzman, Thomas J; Allori, Alexander C; Matic, Damir B; Beals, Stephen P; Fisher, David M; Samson, Thomas D; Marcus, Jeffrey R; Tse, Raymond W

    2018-01-01

    Objective Oronasal fistula is an important complication of cleft palate repair that is frequently used to evaluate surgical quality, yet reliability of fistula classification has never been examined. The objective of this study was to determine the reliability of oronasal fistula classification both within individual surgeons and between multiple surgeons. Design Using intraoral photographs of children with repaired cleft palate, surgeons rated the location of palatal fistulae using the Pittsburgh Fistula Classification System. Intrarater and interrater reliability scores were calculated for each region of the palate. Participants Eight cleft surgeons rated photographs obtained from 29 children. Results Within individual surgeons reliability for each region of the Pittsburgh classification ranged from moderate to almost perfect (κ = .60-.96). By contrast, reliability between surgeons was lower, ranging from fair to substantial (κ = .23-.70). Between-surgeon reliability was lowest for the junction of the soft and hard palates (κ = .23). Within-surgeon and between-surgeon reliability were almost perfect for the more general classification of fistula in the secondary palate (κ = .95 and κ = .83, respectively). Conclusions This is the first reliability study of fistula classification. We show that the Pittsburgh Fistula Classification System is reliable when used by an individual surgeon, but less reliable when used among multiple surgeons. Comparisons of fistula occurrence among surgeons may be subject to less bias if they use the more general classification of "presence or absence of fistula of the secondary palate" rather than the Pittsburgh Fistula Classification System.

  13. Calibration with near-continuous spectral measurements

    DEFF Research Database (Denmark)

    Nielsen, Henrik Aalborg; Rasmussen, Michael; Madsen, Henrik

    2001-01-01

    In chemometrics traditional calibration in case of spectral measurements express a quantity of interest (e.g. a concentration) as a linear combination of the spectral measurements at a number of wavelengths. Often the spectral measurements are performed at a large number of wavelengths and in thi...... by an example in which the octane number of gasoline is related to near infrared spectral measurements. The performance is found to be much better that for the traditional calibration methods....

  14. Improving urban land use and land cover classification from high-spatial-resolution hyperspectral imagery using contextual information

    Science.gov (United States)

    Yang, He; Ma, Ben; Du, Qian; Yang, Chenghai

    2010-08-01

    In this paper, we propose approaches to improve the pixel-based support vector machine (SVM) classification for urban land use and land cover (LULC) mapping from airborne hyperspectral imagery with high spatial resolution. Class spatial neighborhood relationship is used to correct the misclassified class pairs, such as roof and trail, road and roof. These classes may be difficult to be separated because they may have similar spectral signatures and their spatial features are not distinct enough to help their discrimination. In addition, misclassification incurred from within-class trivial spectral variation can be corrected by using pixel connectivity information in a local window so that spectrally homogeneous regions can be well preserved. Our experimental results demonstrate the efficiency of the proposed approaches in classification accuracy improvement. The overall performance is competitive to the object-based SVM classification.

  15. USGS Spectral Library Version 7

    Science.gov (United States)

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

    2017-04-10

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

  16. Spectral properties of generalized eigenparameter dependent ...

    African Journals Online (AJOL)

    Jost function, spectrum, the spectral singularities, and the properties of the principal vectors corresponding to the spectral singularities of L, if. ∞Σn=1 n(∣1 - an∣ + ∣bnl) < ∞. Mathematics Subject Classication (2010): 34L05, 34L40, 39A70, 47A10, 47A75. Key words: Discrete equations, eigenparameter, spectral analysis, ...

  17. Calibrating spectral images using penalized likelihood

    NARCIS (Netherlands)

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

    2003-01-01

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

  18. Fluorescence-based classification of Caribbean coral reef organisms and substrates

    Science.gov (United States)

    Zawada, David G.; Mazel, Charles H.

    2014-01-01

    A diverse group of coral reef organisms, representing several phyla, possess fluorescent pigments. We investigated the potential of using the characteristic fluorescence emission spectra of these pigments to enable unsupervised, optical classification of coral reef habitats. We compiled a library of characteristic fluorescence spectra through in situ and laboratory measurements from a variety of specimens throughout the Caribbean. Because fluorescent pigments are not species-specific, the spectral library is organized in terms of 15 functional groups. We investigated the spectral separability of the functional groups in terms of the number of wavebands required to distinguish between them, using the similarity measures Spectral Angle Mapper (SAM), Spectral Information Divergence (SID), SID-SAM mixed measure, and Mahalanobis distance. This set of measures represents geometric, stochastic, joint geometric-stochastic, and statistical approaches to classifying spectra. Our hyperspectral fluorescence data were used to generate sets of 4-, 6-, and 8-waveband spectra, including random variations in relative signal amplitude, spectral peak shifts, and water-column attenuation. Each set consisted of 2 different band definitions: ‘optimally-picked’ and ‘evenly-spaced.’ The optimally-picked wavebands were chosen to coincide with as many peaks as possible in the functional group spectra. Reference libraries were formed from half of the spectra in each set and used for training purposes. Average classification accuracies ranged from 76.3% for SAM with 4 evenly-spaced wavebands to 93.8% for Mahalanobis distance with 8 evenly-spaced wavebands. The Mahalanobis distance consistently outperformed the other measures. In a second test, empirically-measured spectra were classified using the same reference libraries and the Mahalanobis distance for just the 8 evenly-spaced waveband case. Average classification accuracies were 84% and 87%, corresponding to the extremes in modeled

  19. Classification of radioactive waste

    International Nuclear Information System (INIS)

    1994-01-01

    Radioactive wastes are generated in a number of different kinds of facilities and arise in a wide range of concentrations of radioactive materials and in a variety of physical and chemical forms. To simplify their management, a number of schemes have evolved for classifying radioactive waste according to the physical, chemical and radiological properties of significance to those facilities managing this waste. These schemes have led to a variety of terminologies, differing from country to country and even between facilities in the same country. This situation makes it difficult for those concerned to communicate with one another regarding waste management practices. This document revises and updates earlier IAEA references on radioactive waste classification systems given in IAEA Technical Reports Series and Safety Series. Guidance regarding exemption of materials from regulatory control is consistent with IAEA Safety Series and the RADWASS documents published under IAEA Safety Series. 11 refs, 2 figs, 2 tab

  20. Nonlinear estimation and classification

    CERN Document Server

    Hansen, Mark; Holmes, Christopher; Mallick, Bani; Yu, Bin

    2003-01-01

    Researchers in many disciplines face the formidable task of analyzing massive amounts of high-dimensional and highly-structured data This is due in part to recent advances in data collection and computing technologies As a result, fundamental statistical research is being undertaken in a variety of different fields Driven by the complexity of these new problems, and fueled by the explosion of available computer power, highly adaptive, non-linear procedures are now essential components of modern "data analysis," a term that we liberally interpret to include speech and pattern recognition, classification, data compression and signal processing The development of new, flexible methods combines advances from many sources, including approximation theory, numerical analysis, machine learning, signal processing and statistics The proposed workshop intends to bring together eminent experts from these fields in order to exchange ideas and forge directions for the future

  1. Automatic diabetic retinopathy classification

    Science.gov (United States)

    Bravo, María. A.; Arbeláez, Pablo A.

    2017-11-01

    Diabetic retinopathy (DR) is a disease in which the retina is damaged due to augmentation in the blood pressure of small vessels. DR is the major cause of blindness for diabetics. It has been shown that early diagnosis can play a major role in prevention of visual loss and blindness. This work proposes a computer based approach for the detection of DR in back-of-the-eye images based on the use of convolutional neural networks (CNNs). Our CNN uses deep architectures to classify Back-of-the-eye Retinal Photographs (BRP) in 5 stages of DR. Our method combines several preprocessing images of BRP to obtain an ACA score of 50.5%. Furthermore, we explore subproblems by training a larger CNN of our main classification task.

  2. Spectral multitude and spectral dynamics reflect changing conjugation length in single molecules of oligophenylenevinylenes

    KAUST Repository

    Kobayashi, Hiroyuki; Tsuchiya, Kousuke; Ogino, Kenji; Vacha, Martin

    2012-01-01

    Single-molecule study of phenylenevinylene oligomers revealed distinct spectral forms due to different conjugation lengths which are determined by torsional defects. Large spectral jumps between different spectral forms were ascribed to torsional flips of a single phenylene ring. These spectral changes reflect the dynamic nature of electron delocalization in oligophenylenevinylenes and enable estimation of the phenylene torsional barriers. © 2012 The Owner Societies.

  3. Conditions and Motivations to Undertake

    Directory of Open Access Journals (Sweden)

    Flor Ángela Marulanda Valencia

    2017-02-01

    Full Text Available This study aims at deepening in the analysis of motivations shown by a group of entrepreneurs in Medellin, Antioquia. It also describes the different perceptions about the enablers and obstacles for the development of entrepreneurship in appropriate environments to promote it. It was found that independence was the principal motivation for entrepreneurship and that the city offered the most favourable environment to foster it. Additionally, it was found that the most important obstacle to develop it was the difficulties to access a bank credit.

  4. Spectral methods. Fundamentals in single domains

    International Nuclear Information System (INIS)

    Canuto, C.

    2006-01-01

    Since the publication of ''Spectral Methods in Fluid Dynamics'' 1988, spectral methods have become firmly established as a mainstream tool for scientific and engineering computation. The authors of that book have incorporated into this new edition the many improvements in the algorithms and the theory of spectral methods that have been made since then. This latest book retains the tight integration between the theoretical and practical aspects of spectral methods, and the chapters are enhanced with material on the Galerkin with numerical integration version of spectral methods. The discussion of direct and iterative solution methods is also greatly expanded. (orig.)

  5. A Biologically Inspired Approach to Frequency Domain Feature Extraction for EEG Classification

    Directory of Open Access Journals (Sweden)

    Nurhan Gursel Ozmen

    2018-01-01

    Full Text Available Classification of electroencephalogram (EEG signal is important in mental decoding for brain-computer interfaces (BCI. We introduced a feature extraction approach based on frequency domain analysis to improve the classification performance on different mental tasks using single-channel EEG. This biologically inspired method extracts the most discriminative spectral features from power spectral densities (PSDs of the EEG signals. We applied our method on a dataset of six subjects who performed five different imagination tasks: (i resting state, (ii mental arithmetic, (iii imagination of left hand movement, (iv imagination of right hand movement, and (v imagination of letter “A.” Pairwise and multiclass classifications were performed in single EEG channel using Linear Discriminant Analysis and Support Vector Machines. Our method produced results (mean classification accuracy of 83.06% for binary classification and 91.85% for multiclassification that are on par with the state-of-the-art methods, using single-channel EEG with low computational cost. Among all task pairs, mental arithmetic versus letter imagination yielded the best result (mean classification accuracy of 90.29%, indicating that this task pair could be the most suitable pair for a binary class BCI. This study contributes to the development of single-channel BCI, as well as finding the best task pair for user defined applications.

  6. Hazard classification or risk assessment

    DEFF Research Database (Denmark)

    Hass, Ulla

    2013-01-01

    The EU classification of substances for e.g. reproductive toxicants is hazard based and does not to address the risk suchsubstances may pose through normal, or extreme, use. Such hazard classification complies with the consumer's right to know. It is also an incentive to careful use and storage...

  7. Seismic texture classification. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Vinther, R.

    1997-12-31

    The seismic texture classification method, is a seismic attribute that can both recognize the general reflectivity styles and locate variations from these. The seismic texture classification performs a statistic analysis for the seismic section (or volume) aiming at describing the reflectivity. Based on a set of reference reflectivities the seismic textures are classified. The result of the seismic texture classification is a display of seismic texture categories showing both the styles of reflectivity from the reference set and interpolations and extrapolations from these. The display is interpreted as statistical variations in the seismic data. The seismic texture classification is applied to seismic sections and volumes from the Danish North Sea representing both horizontal stratifications and salt diapers. The attribute succeeded in recognizing both general structure of successions and variations from these. Also, the seismic texture classification is not only able to display variations in prospective areas (1-7 sec. TWT) but can also be applied to deep seismic sections. The seismic texture classification is tested on a deep reflection seismic section (13-18 sec. TWT) from the Baltic Sea. Applied to this section the seismic texture classification succeeded in locating the Moho, which could not be located using conventional interpretation tools. The seismic texture classification is a seismic attribute which can display general reflectivity styles and deviations from these and enhance variations not found by conventional interpretation tools. (LN)

  8. Efficient AUC optimization for classification

    NARCIS (Netherlands)

    Calders, T.; Jaroszewicz, S.; Kok, J.N.; Koronacki, J.; Lopez de Mantaras, R.; Matwin, S.; Mladenic, D.; Skowron, A.

    2007-01-01

    In this paper we show an efficient method for inducing classifiers that directly optimize the area under the ROC curve. Recently, AUC gained importance in the classification community as a mean to compare the performance of classifiers. Because most classification methods do not optimize this

  9. Dewey Decimal Classification: A Quagmire.

    Science.gov (United States)

    Gamaluddin, Ahmad Fouad

    1980-01-01

    A survey of 660 Pennsylvania school librarians indicates that, though there is limited professional interest in the Library of Congress Classification system, Dewey Decimal Classification (DDC) appears to be firmly entrenched. This article also discusses the relative merits of DDC, the need for a uniform system, librarianship preparation, and…

  10. Latent class models for classification

    NARCIS (Netherlands)

    Vermunt, J.K.; Magidson, J.

    2003-01-01

    An overview is provided of recent developments in the use of latent class (LC) and other types of finite mixture models for classification purposes. Several extensions of existing models are presented. Two basic types of LC models for classification are defined: supervised and unsupervised

  11. 45 CFR 601.5 - Derivative classification.

    Science.gov (United States)

    2010-10-01

    ... CLASSIFICATION AND DECLASSIFICATION OF NATIONAL SECURITY INFORMATION § 601.5 Derivative classification. Distinct... 45 Public Welfare 3 2010-10-01 2010-10-01 false Derivative classification. 601.5 Section 601.5... classification guide, need not possess original classification authority. (a) If a person who applies derivative...

  12. 12 CFR 403.4 - Derivative classification.

    Science.gov (United States)

    2010-01-01

    ... SAFEGUARDING OF NATIONAL SECURITY INFORMATION § 403.4 Derivative classification. (a) Use of derivative classification. (1) Unlike original classification which is an initial determination, derivative classification... 12 Banks and Banking 4 2010-01-01 2010-01-01 false Derivative classification. 403.4 Section 403.4...

  13. 32 CFR 2001.15 - Classification guides.

    Science.gov (United States)

    2010-07-01

    ... 32 National Defense 6 2010-07-01 2010-07-01 false Classification guides. 2001.15 Section 2001.15..., NATIONAL ARCHIVES AND RECORDS ADMINISTRATION CLASSIFIED NATIONAL SECURITY INFORMATION Classification § 2001.15 Classification guides. (a) Preparation of classification guides. Originators of classification...

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

    Science.gov (United States)

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

    1997-01-01

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

  15. Vietnamese Document Representation and Classification

    Science.gov (United States)

    Nguyen, Giang-Son; Gao, Xiaoying; Andreae, Peter

    Vietnamese is very different from English and little research has been done on Vietnamese document classification, or indeed, on any kind of Vietnamese language processing, and only a few small corpora are available for research. We created a large Vietnamese text corpus with about 18000 documents, and manually classified them based on different criteria such as topics and styles, giving several classification tasks of different difficulty levels. This paper introduces a new syllable-based document representation at the morphological level of the language for efficient classification. We tested the representation on our corpus with different classification tasks using six classification algorithms and two feature selection techniques. Our experiments show that the new representation is effective for Vietnamese categorization, and suggest that best performance can be achieved using syllable-pair document representation, an SVM with a polynomial kernel as the learning algorithm, and using Information gain and an external dictionary for feature selection.

  16. Planck 2013 results. IX. HFI spectral response

    CERN Document Server

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

    2014-01-01

    The Planck High Frequency Instrument (HFI) spectral response was determined through a series of ground based tests conducted with the HFI focal plane in a cryogenic environment prior to launch. The main goal of the spectral transmission tests was to measure the relative spectral response (including out-of-band signal rejection) of all HFI detectors. This was determined by measuring the output of a continuously scanned Fourier transform spectrometer coupled with all HFI detectors. As there is no on-board spectrometer within HFI, the ground-based spectral response experiments provide the definitive data set for the relative spectral calibration of the HFI. The spectral response of the HFI is used in Planck data analysis and component separation, this includes extraction of CO emission observed within Planck bands, dust emission, Sunyaev-Zeldovich sources, and intensity to polarization leakage. The HFI spectral response data have also been used to provide unit conversion and colour correction analysis tools. Ver...

  17. Spectral representation in stochastic quantization

    International Nuclear Information System (INIS)

    Nakazato, Hiromichi.

    1988-10-01

    A spectral representation of stationary 2-point functions is investigated based on the operator formalism in stochastic quantization. Assuming the existence of asymptotic non-interacting fields, we can diagonalize the total Hamiltonian in terms of asymptotic fields and show that the correlation length along the fictious time is proportional to the physical mass expected in the usual field theory. A relation between renormalization factors in the operator formalism is derived as a byproduct and its validity is checked with the perturbative results calculated in this formalism. (orig.)

  18. Spectral Tensor-Train Decomposition

    DEFF Research Database (Denmark)

    Bigoni, Daniele; Engsig-Karup, Allan Peter; Marzouk, Youssef M.

    2016-01-01

    The accurate approximation of high-dimensional functions is an essential task in uncertainty quantification and many other fields. We propose a new function approximation scheme based on a spectral extension of the tensor-train (TT) decomposition. We first define a functional version of the TT...... adaptive Smolyak approach. The method is also used to approximate the solution of an elliptic PDE with random input data. The open source software and examples presented in this work are available online (http://pypi.python.org/pypi/TensorToolbox/)....

  19. T-ray relevant frequencies for osteosarcoma classification

    Science.gov (United States)

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

    2006-01-01

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

  20. On a classification of irreducible almost-commutative geometries IV

    International Nuclear Information System (INIS)

    Jureit, Jan-Hendrik; Stephan, Christoph A.

    2008-01-01

    In this paper, we will classify the finite spectral triples with KO-dimension 6, following the classification found in Iochum, B., Schuecker, T., and Stephan, C. A., J. Math. Phys. 45, 5003 (2004); Jureit, J.-H. and Stephan, C. A., J. Math. Phys. 46, 043512 (2005); Schuecker, T. (unpublished); Jureit, J.-H., Schuecker, T., and Stephan, C. A., J. Math. Phys. 46, 072302 (2005). with up to four summands in the matrix algebra. Again, heavy use is made of Krajewski diagrams [Krajewski, T., J. Geom. Phys. 28, 1 (1998).] This work has been inspired by the recent paper by Connes (unpublished) and Barrett (unpublished). In the classification, we find that the standard model of particle physics in its minimal version fits the axioms of noncommutative geometry in the case of KO-dimension 6. By minimal version, it is meant that at least one neutrino has to be massless and mass-terms mixing particles and antiparticles are prohibited