Digital spectral analysis parametric, non-parametric and advanced methods
Castanié, Francis
2013-01-01
Digital Spectral Analysis provides a single source that offers complete coverage of the spectral analysis domain. This self-contained work includes details on advanced topics that are usually presented in scattered sources throughout the literature.The theoretical principles necessary for the understanding of spectral analysis are discussed in the first four chapters: fundamentals, digital signal processing, estimation in spectral analysis, and time-series models.An entire chapter is devoted to the non-parametric methods most widely used in industry.High resolution methods a
Bayesian nonparametric data analysis
Müller, Peter; Jara, Alejandro; Hanson, Tim
2015-01-01
This book reviews nonparametric Bayesian methods and models that have proven useful in the context of data analysis. Rather than providing an encyclopedic review of probability models, the book’s structure follows a data analysis perspective. As such, the chapters are organized by traditional data analysis problems. In selecting specific nonparametric models, simpler and more traditional models are favored over specialized ones. The discussed methods are illustrated with a wealth of examples, including applications ranging from stylized examples to case studies from recent literature. The book also includes an extensive discussion of computational methods and details on their implementation. R code for many examples is included in on-line software pages.
Nonparametric Collective Spectral Density Estimation and Clustering
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
Nonparametric Collective Spectral Density Estimation and Clustering
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
Bayesian Nonparametric Longitudinal Data Analysis.
Quintana, Fernando A; Johnson, Wesley O; Waetjen, Elaine; Gold, Ellen
2016-01-01
Practical Bayesian nonparametric methods have been developed across a wide variety of contexts. Here, we develop a novel statistical model that generalizes standard mixed models for longitudinal data that include flexible mean functions as well as combined compound symmetry (CS) and autoregressive (AR) covariance structures. AR structure is often specified through the use of a Gaussian process (GP) with covariance functions that allow longitudinal data to be more correlated if they are observed closer in time than if they are observed farther apart. We allow for AR structure by considering a broader class of models that incorporates a Dirichlet Process Mixture (DPM) over the covariance parameters of the GP. We are able to take advantage of modern Bayesian statistical methods in making full predictive inferences and about characteristics of longitudinal profiles and their differences across covariate combinations. We also take advantage of the generality of our model, which provides for estimation of a variety of covariance structures. We observe that models that fail to incorporate CS or AR structure can result in very poor estimation of a covariance or correlation matrix. In our illustration using hormone data observed on women through the menopausal transition, biology dictates the use of a generalized family of sigmoid functions as a model for time trends across subpopulation categories.
Nonparametric factor analysis of time series
Rodríguez-Poo, Juan M.; Linton, Oliver Bruce
1998-01-01
We introduce a nonparametric smoothing procedure for nonparametric factor analaysis of multivariate time series. The asymptotic properties of the proposed procedures are derived. We present an application based on the residuals from the Fair macromodel.
Nonparametric analysis of blocked ordered categories data: some examples revisited
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O. Thas
2006-08-01
Full Text Available Nonparametric analysis for general block designs can be given by using the Cochran-Mantel-Haenszel (CMH statistics. We demonstrate this with four examples and note that several well-known nonparametric statistics are special cases of CMH statistics.
A Bayesian Nonparametric Approach to Factor Analysis
DEFF Research Database (Denmark)
Piatek, Rémi; Papaspiliopoulos, Omiros
2018-01-01
This paper introduces a new approach for the inference of non-Gaussian factor models based on Bayesian nonparametric methods. It relaxes the usual normality assumption on the latent factors, widely used in practice, which is too restrictive in many settings. Our approach, on the contrary, does no...
Weak Disposability in Nonparametric Production Analysis with Undesirable Outputs
Kuosmanen, T.K.
2005-01-01
Environmental Economics and Natural Resources Group at Wageningen University in The Netherlands Weak disposability of outputs means that firms can abate harmful emissions by decreasing the activity level. Modeling weak disposability in nonparametric production analysis has caused some confusion.
Non-parametric analysis of production efficiency of poultry egg ...
African Journals Online (AJOL)
Non-parametric analysis of production efficiency of poultry egg farmers in Delta ... analysis of factors affecting the output of poultry farmers showed that stock ... should be put in place for farmers to learn the best farm practices carried out on the ...
A Bayesian Nonparametric Meta-Analysis Model
Karabatsos, George; Talbott, Elizabeth; Walker, Stephen G.
2015-01-01
In a meta-analysis, it is important to specify a model that adequately describes the effect-size distribution of the underlying population of studies. The conventional normal fixed-effect and normal random-effects models assume a normal effect-size population distribution, conditionally on parameters and covariates. For estimating the mean overall…
Martinez Manzanera, Octavio; Elting, Jan Willem; van der Hoeven, Johannes H.; Maurits, Natasha M.
2016-01-01
In the clinic, tremor is diagnosed during a time-limited process in which patients are observed and the characteristics of tremor are visually assessed. For some tremor disorders, a more detailed analysis of these characteristics is needed. Accelerometry and electromyography can be used to obtain a better insight into tremor. Typically, routine clinical assessment of accelerometry and electromyography data involves visual inspection by clinicians and occasionally computational analysis to obtain objective characteristics of tremor. However, for some tremor disorders these characteristics may be different during daily activity. This variability in presentation between the clinic and daily life makes a differential diagnosis more difficult. A long-term recording of tremor by accelerometry and/or electromyography in the home environment could help to give a better insight into the tremor disorder. However, an evaluation of such recordings using routine clinical standards would take too much time. We evaluated a range of techniques that automatically detect tremor segments in accelerometer data, as accelerometer data is more easily obtained in the home environment than electromyography data. Time can be saved if clinicians only have to evaluate the tremor characteristics of segments that have been automatically detected in longer daily activity recordings. We tested four non-parametric methods and five parametric methods on clinical accelerometer data from 14 patients with different tremor disorders. The consensus between two clinicians regarding the presence or absence of tremor on 3943 segments of accelerometer data was employed as reference. The nine methods were tested against this reference to identify their optimal parameters. Non-parametric methods generally performed better than parametric methods on our dataset when optimal parameters were used. However, one parametric method, employing the high frequency content of the tremor bandwidth under consideration
Using non-parametric methods in econometric production analysis
DEFF Research Database (Denmark)
Czekaj, Tomasz Gerard; Henningsen, Arne
2012-01-01
by investigating the relationship between the elasticity of scale and the farm size. We use a balanced panel data set of 371~specialised crop farms for the years 2004-2007. A non-parametric specification test shows that neither the Cobb-Douglas function nor the Translog function are consistent with the "true......Econometric estimation of production functions is one of the most common methods in applied economic production analysis. These studies usually apply parametric estimation techniques, which obligate the researcher to specify a functional form of the production function of which the Cobb...... parameter estimates, but also in biased measures which are derived from the parameters, such as elasticities. Therefore, we propose to use non-parametric econometric methods. First, these can be applied to verify the functional form used in parametric production analysis. Second, they can be directly used...
Using non-parametric methods in econometric production analysis
DEFF Research Database (Denmark)
Czekaj, Tomasz Gerard; Henningsen, Arne
Econometric estimation of production functions is one of the most common methods in applied economic production analysis. These studies usually apply parametric estimation techniques, which obligate the researcher to specify the functional form of the production function. Most often, the Cobb...... results—including measures that are of interest of applied economists, such as elasticities. Therefore, we propose to use nonparametric econometric methods. First, they can be applied to verify the functional form used in parametric estimations of production functions. Second, they can be directly used...
STATCAT, Statistical Analysis of Parametric and Non-Parametric Data
International Nuclear Information System (INIS)
David, Hugh
1990-01-01
1 - Description of program or function: A suite of 26 programs designed to facilitate the appropriate statistical analysis and data handling of parametric and non-parametric data, using classical and modern univariate and multivariate methods. 2 - Method of solution: Data is read entry by entry, using a choice of input formats, and the resultant data bank is checked for out-of- range, rare, extreme or missing data. The completed STATCAT data bank can be treated by a variety of descriptive and inferential statistical methods, and modified, using other standard programs as required
Wesselink, Christiaan; Heeg, Govert P.; Jansonius, Nomdo M.
Objective: To compare prospectively 2 perimetric progression detection algorithms for glaucoma, the Early Manifest Glaucoma Trial algorithm (glaucoma progression analysis [GPA]) and a nonparametric algorithm applied to the mean deviation (MD) (nonparametric progression analysis [NPA]). Methods:
Multi-Directional Non-Parametric Analysis of Agricultural Efficiency
DEFF Research Database (Denmark)
Balezentis, Tomas
This thesis seeks to develop methodologies for assessment of agricultural efficiency and employ them to Lithuanian family farms. In particular, we focus on three particular objectives throughout the research: (i) to perform a fully non-parametric analysis of efficiency effects, (ii) to extend...... to the Multi-Directional Efficiency Analysis approach when the proposed models were employed to analyse empirical data of Lithuanian family farm performance, we saw substantial differences in efficiencies associated with different inputs. In particular, assets appeared to be the least efficiently used input...... relative to labour, intermediate consumption and land (in some cases land was not treated as a discretionary input). These findings call for further research on relationships among financial structure, investment decisions, and efficiency in Lithuanian family farms. Application of different techniques...
CADDIS Volume 4. Data Analysis: PECBO Appendix - R Scripts for Non-Parametric Regressions
Script for computing nonparametric regression analysis. Overview of using scripts to infer environmental conditions from biological observations, statistically estimating species-environment relationships, statistical scripts.
Discrete non-parametric kernel estimation for global sensitivity analysis
International Nuclear Information System (INIS)
Senga Kiessé, Tristan; Ventura, Anne
2016-01-01
This work investigates the discrete kernel approach for evaluating the contribution of the variance of discrete input variables to the variance of model output, via analysis of variance (ANOVA) decomposition. Until recently only the continuous kernel approach has been applied as a metamodeling approach within sensitivity analysis framework, for both discrete and continuous input variables. Now the discrete kernel estimation is known to be suitable for smoothing discrete functions. We present a discrete non-parametric kernel estimator of ANOVA decomposition of a given model. An estimator of sensitivity indices is also presented with its asymtotic convergence rate. Some simulations on a test function analysis and a real case study from agricultural have shown that the discrete kernel approach outperforms the continuous kernel one for evaluating the contribution of moderate or most influential discrete parameters to the model output. - Highlights: • We study a discrete kernel estimation for sensitivity analysis of a model. • A discrete kernel estimator of ANOVA decomposition of the model is presented. • Sensitivity indices are calculated for discrete input parameters. • An estimator of sensitivity indices is also presented with its convergence rate. • An application is realized for improving the reliability of environmental models.
Bayesian nonparametric meta-analysis using Polya tree mixture models.
Branscum, Adam J; Hanson, Timothy E
2008-09-01
Summary. A common goal in meta-analysis is estimation of a single effect measure using data from several studies that are each designed to address the same scientific inquiry. Because studies are typically conducted in geographically disperse locations, recent developments in the statistical analysis of meta-analytic data involve the use of random effects models that account for study-to-study variability attributable to differences in environments, demographics, genetics, and other sources that lead to heterogeneity in populations. Stemming from asymptotic theory, study-specific summary statistics are modeled according to normal distributions with means representing latent true effect measures. A parametric approach subsequently models these latent measures using a normal distribution, which is strictly a convenient modeling assumption absent of theoretical justification. To eliminate the influence of overly restrictive parametric models on inferences, we consider a broader class of random effects distributions. We develop a novel hierarchical Bayesian nonparametric Polya tree mixture (PTM) model. We present methodology for testing the PTM versus a normal random effects model. These methods provide researchers a straightforward approach for conducting a sensitivity analysis of the normality assumption for random effects. An application involving meta-analysis of epidemiologic studies designed to characterize the association between alcohol consumption and breast cancer is presented, which together with results from simulated data highlight the performance of PTMs in the presence of nonnormality of effect measures in the source population.
International Nuclear Information System (INIS)
McIntee, Erin; Viglino, Emilie; Rinke, Caitlin; Kumor, Stephanie; Ni Liqiang; Sigman, Michael E.
2010-01-01
Laser-induced breakdown spectroscopy (LIBS) has been investigated for the discrimination of automobile paint samples. Paint samples from automobiles of different makes, models, and years were collected and separated into sets based on the color, presence or absence of effect pigments and the number of paint layers. Twelve LIBS spectra were obtained for each paint sample, each an average of a five single shot 'drill down' spectra from consecutive laser ablations in the same spot on the sample. Analyses by a nonparametric permutation test and a parametric Wald test were performed to determine the extent of discrimination within each set of paint samples. The discrimination power and Type I error were assessed for each data analysis method. Conversion of the spectral intensity to a log-scale (base 10) resulted in a higher overall discrimination power while observing the same significance level. Working on the log-scale, the nonparametric permutation tests gave an overall 89.83% discrimination power with a size of Type I error being 4.44% at the nominal significance level of 5%. White paint samples, as a group, were the most difficult to differentiate with the power being only 86.56% followed by 95.83% for black paint samples. Parametric analysis of the data set produced lower discrimination (85.17%) with 3.33% Type I errors, which is not recommended for both theoretical and practical considerations. The nonparametric testing method is applicable across many analytical comparisons, with the specific application described here being the pairwise comparison of automotive paint samples.
The Use of Nonparametric Kernel Regression Methods in Econometric Production Analysis
DEFF Research Database (Denmark)
Czekaj, Tomasz Gerard
and nonparametric estimations of production functions in order to evaluate the optimal firm size. The second paper discusses the use of parametric and nonparametric regression methods to estimate panel data regression models. The third paper analyses production risk, price uncertainty, and farmers' risk preferences...... within a nonparametric panel data regression framework. The fourth paper analyses the technical efficiency of dairy farms with environmental output using nonparametric kernel regression in a semiparametric stochastic frontier analysis. The results provided in this PhD thesis show that nonparametric......This PhD thesis addresses one of the fundamental problems in applied econometric analysis, namely the econometric estimation of regression functions. The conventional approach to regression analysis is the parametric approach, which requires the researcher to specify the form of the regression...
Non-Parametric Analysis of Rating Transition and Default Data
DEFF Research Database (Denmark)
Fledelius, Peter; Lando, David; Perch Nielsen, Jens
2004-01-01
We demonstrate the use of non-parametric intensity estimation - including construction of pointwise confidence sets - for analyzing rating transition data. We find that transition intensities away from the class studied here for illustration strongly depend on the direction of the previous move b...
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
Dwivedi, Alok Kumar; Mallawaarachchi, Indika; Alvarado, Luis A
2017-06-30
Experimental studies in biomedical research frequently pose analytical problems related to small sample size. In such studies, there are conflicting findings regarding the choice of parametric and nonparametric analysis, especially with non-normal data. In such instances, some methodologists questioned the validity of parametric tests and suggested nonparametric tests. In contrast, other methodologists found nonparametric tests to be too conservative and less powerful and thus preferred using parametric tests. Some researchers have recommended using a bootstrap test; however, this method also has small sample size limitation. We used a pooled method in nonparametric bootstrap test that may overcome the problem related with small samples in hypothesis testing. The present study compared nonparametric bootstrap test with pooled resampling method corresponding to parametric, nonparametric, and permutation tests through extensive simulations under various conditions and using real data examples. The nonparametric pooled bootstrap t-test provided equal or greater power for comparing two means as compared with unpaired t-test, Welch t-test, Wilcoxon rank sum test, and permutation test while maintaining type I error probability for any conditions except for Cauchy and extreme variable lognormal distributions. In such cases, we suggest using an exact Wilcoxon rank sum test. Nonparametric bootstrap paired t-test also provided better performance than other alternatives. Nonparametric bootstrap test provided benefit over exact Kruskal-Wallis test. We suggest using nonparametric bootstrap test with pooled resampling method for comparing paired or unpaired means and for validating the one way analysis of variance test results for non-normal data in small sample size studies. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.
Categorical and nonparametric data analysis choosing the best statistical technique
Nussbaum, E Michael
2014-01-01
Featuring in-depth coverage of categorical and nonparametric statistics, this book provides a conceptual framework for choosing the most appropriate type of test in various research scenarios. Class tested at the University of Nevada, the book's clear explanations of the underlying assumptions, computer simulations, and Exploring the Concept boxes help reduce reader anxiety. Problems inspired by actual studies provide meaningful illustrations of the techniques. The underlying assumptions of each test and the factors that impact validity and statistical power are reviewed so readers can explain
Martinez Manzanera, Octavio; Elting, Jan Willem; van der Hoeven, Johannes H; Maurits, Natasha M
2016-01-01
In the clinic, tremor is diagnosed during a time-limited process in which patients are observed and the characteristics of tremor are visually assessed. For some tremor disorders, a more detailed analysis of these characteristics is needed. Accelerometry and electromyography can be used to obtain a
Feng, Jinchao; Lansford, Joshua; Mironenko, Alexander; Pourkargar, Davood Babaei; Vlachos, Dionisios G.; Katsoulakis, Markos A.
2018-03-01
We propose non-parametric methods for both local and global sensitivity analysis of chemical reaction models with correlated parameter dependencies. The developed mathematical and statistical tools are applied to a benchmark Langmuir competitive adsorption model on a close packed platinum surface, whose parameters, estimated from quantum-scale computations, are correlated and are limited in size (small data). The proposed mathematical methodology employs gradient-based methods to compute sensitivity indices. We observe that ranking influential parameters depends critically on whether or not correlations between parameters are taken into account. The impact of uncertainty in the correlation and the necessity of the proposed non-parametric perspective are demonstrated.
Directory of Open Access Journals (Sweden)
Jinchao Feng
2018-03-01
Full Text Available We propose non-parametric methods for both local and global sensitivity analysis of chemical reaction models with correlated parameter dependencies. The developed mathematical and statistical tools are applied to a benchmark Langmuir competitive adsorption model on a close packed platinum surface, whose parameters, estimated from quantum-scale computations, are correlated and are limited in size (small data. The proposed mathematical methodology employs gradient-based methods to compute sensitivity indices. We observe that ranking influential parameters depends critically on whether or not correlations between parameters are taken into account. The impact of uncertainty in the correlation and the necessity of the proposed non-parametric perspective are demonstrated.
Non-parametric production analysis of pesticides use in the Netherlands
Oude Lansink, A.G.J.M.; Silva, E.
2004-01-01
Many previous empirical studies on the productivity of pesticides suggest that pesticides are under-utilized in agriculture despite the general held believe that these inputs are substantially over-utilized. This paper uses data envelopment analysis (DEA) to calculate non-parametric measures of the
Mittag, Kathleen Cage
Most researchers using factor analysis extract factors from a matrix of Pearson product-moment correlation coefficients. A method is presented for extracting factors in a non-parametric way, by extracting factors from a matrix of Spearman rho (rank correlation) coefficients. It is possible to factor analyze a matrix of association such that…
Data analysis with small samples and non-normal data nonparametrics and other strategies
Siebert, Carl F
2017-01-01
Written in everyday language for non-statisticians, this book provides all the information needed to successfully conduct nonparametric analyses. This ideal reference book provides step-by-step instructions to lead the reader through each analysis, screenshots of the software and output, and case scenarios to illustrate of all the analytic techniques.
Nonparametric inference in nonlinear principal components analysis : exploration and beyond
Linting, Mariëlle
2007-01-01
In the social and behavioral sciences, data sets often do not meet the assumptions of traditional analysis methods. Therefore, nonlinear alternatives to traditional methods have been developed. This thesis starts with a didactic discussion of nonlinear principal components analysis (NLPCA),
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
Multilevel Latent Class Analysis: Parametric and Nonparametric Models
Finch, W. Holmes; French, Brian F.
2014-01-01
Latent class analysis is an analytic technique often used in educational and psychological research to identify meaningful groups of individuals within a larger heterogeneous population based on a set of variables. This technique is flexible, encompassing not only a static set of variables but also longitudinal data in the form of growth mixture…
Driving Style Analysis Using Primitive Driving Patterns With Bayesian Nonparametric Approaches
Wang, Wenshuo; Xi, Junqiang; Zhao, Ding
2017-01-01
Analysis and recognition of driving styles are profoundly important to intelligent transportation and vehicle calibration. This paper presents a novel driving style analysis framework using the primitive driving patterns learned from naturalistic driving data. In order to achieve this, first, a Bayesian nonparametric learning method based on a hidden semi-Markov model (HSMM) is introduced to extract primitive driving patterns from time series driving data without prior knowledge of the number...
Generalized Correlation Coefficient for Non-Parametric Analysis of Microarray Time-Course Data
DEFF Research Database (Denmark)
Tan, Qihua; Thomassen, Mads; Burton, Mark
2017-01-01
the heterogeneous time-course gene expression patterns. Application of the method identified nonlinear time-course patterns in high agreement with parametric analysis. We conclude that the non-parametric nature in the generalized correlation analysis could be an useful and efficient tool for analyzing microarray...... time-course data and for exploring the complex relationships in the omics data for studying their association with disease and health....
Nonparametric Bounds and Sensitivity Analysis of Treatment Effects
Richardson, Amy; Hudgens, Michael G.; Gilbert, Peter B.; Fine, Jason P.
2015-01-01
This paper considers conducting inference about the effect of a treatment (or exposure) on an outcome of interest. In the ideal setting where treatment is assigned randomly, under certain assumptions the treatment effect is identifiable from the observable data and inference is straightforward. However, in other settings such as observational studies or randomized trials with noncompliance, the treatment effect is no longer identifiable without relying on untestable assumptions. Nonetheless, the observable data often do provide some information about the effect of treatment, that is, the parameter of interest is partially identifiable. Two approaches are often employed in this setting: (i) bounds are derived for the treatment effect under minimal assumptions, or (ii) additional untestable assumptions are invoked that render the treatment effect identifiable and then sensitivity analysis is conducted to assess how inference about the treatment effect changes as the untestable assumptions are varied. Approaches (i) and (ii) are considered in various settings, including assessing principal strata effects, direct and indirect effects and effects of time-varying exposures. Methods for drawing formal inference about partially identified parameters are also discussed. PMID:25663743
Bornkamp, Björn; Ickstadt, Katja
2009-03-01
In this article, we consider monotone nonparametric regression in a Bayesian framework. The monotone function is modeled as a mixture of shifted and scaled parametric probability distribution functions, and a general random probability measure is assumed as the prior for the mixing distribution. We investigate the choice of the underlying parametric distribution function and find that the two-sided power distribution function is well suited both from a computational and mathematical point of view. The model is motivated by traditional nonlinear models for dose-response analysis, and provides possibilities to elicitate informative prior distributions on different aspects of the curve. The method is compared with other recent approaches to monotone nonparametric regression in a simulation study and is illustrated on a data set from dose-response analysis.
Substitution dynamical systems spectral analysis
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...
Generalized Correlation Coefficient for Non-Parametric Analysis of Microarray Time-Course Data.
Tan, Qihua; Thomassen, Mads; Burton, Mark; Mose, Kristian Fredløv; Andersen, Klaus Ejner; Hjelmborg, Jacob; Kruse, Torben
2017-06-06
Modeling complex time-course patterns is a challenging issue in microarray study due to complex gene expression patterns in response to the time-course experiment. We introduce the generalized correlation coefficient and propose a combinatory approach for detecting, testing and clustering the heterogeneous time-course gene expression patterns. Application of the method identified nonlinear time-course patterns in high agreement with parametric analysis. We conclude that the non-parametric nature in the generalized correlation analysis could be an useful and efficient tool for analyzing microarray time-course data and for exploring the complex relationships in the omics data for studying their association with disease and health.
Curceac, S.; Ternynck, C.; Ouarda, T.
2015-12-01
Over the past decades, a substantial amount of research has been conducted to model and forecast climatic variables. In this study, Nonparametric Functional Data Analysis (NPFDA) methods are applied to forecast air temperature and wind speed time series in Abu Dhabi, UAE. The dataset consists of hourly measurements recorded for a period of 29 years, 1982-2010. The novelty of the Functional Data Analysis approach is in expressing the data as curves. In the present work, the focus is on daily forecasting and the functional observations (curves) express the daily measurements of the above mentioned variables. We apply a non-linear regression model with a functional non-parametric kernel estimator. The computation of the estimator is performed using an asymmetrical quadratic kernel function for local weighting based on the bandwidth obtained by a cross validation procedure. The proximities between functional objects are calculated by families of semi-metrics based on derivatives and Functional Principal Component Analysis (FPCA). Additionally, functional conditional mode and functional conditional median estimators are applied and the advantages of combining their results are analysed. A different approach employs a SARIMA model selected according to the minimum Akaike (AIC) and Bayessian (BIC) Information Criteria and based on the residuals of the model. The performance of the models is assessed by calculating error indices such as the root mean square error (RMSE), relative RMSE, BIAS and relative BIAS. The results indicate that the NPFDA models provide more accurate forecasts than the SARIMA models. Key words: Nonparametric functional data analysis, SARIMA, time series forecast, air temperature, wind speed
Nonparametric bootstrap analysis with applications to demographic effects in demand functions.
Gozalo, P L
1997-12-01
"A new bootstrap proposal, labeled smooth conditional moment (SCM) bootstrap, is introduced for independent but not necessarily identically distributed data, where the classical bootstrap procedure fails.... A good example of the benefits of using nonparametric and bootstrap methods is the area of empirical demand analysis. In particular, we will be concerned with their application to the study of two important topics: what are the most relevant effects of household demographic variables on demand behavior, and to what extent present parametric specifications capture these effects." excerpt
International Nuclear Information System (INIS)
Peterson, James R.; Haas, Timothy C.; Lee, Danny C.
2000-01-01
Natural resource professionals are increasingly required to develop rigorous statistical models that relate environmental data to categorical responses data. Recent advances in the statistical and computing sciences have led to the development of sophisticated methods for parametric and nonparametric analysis of data with categorical responses. The statistical software package CATDAT was designed to make some of these relatively new and powerful techniques available to scientists. The CATDAT statistical package includes 4 analytical techniques: generalized logit modeling; binary classification tree; extended K-nearest neighbor classification; and modular neural network
Trend Analysis of Pahang River Using Non-Parametric Analysis: Mann Kendalls Trend Test
International Nuclear Information System (INIS)
Nur Hishaam Sulaiman; Mohd Khairul Amri Kamarudin; Mohd Khairul Amri Kamarudin; Ahmad Dasuki Mustafa; Muhammad Azizi Amran; Fazureen Azaman; Ismail Zainal Abidin; Norsyuhada Hairoma
2015-01-01
Flood is common in Pahang especially during northeast monsoon season from November to February. Three river cross station: Lubuk Paku, Sg. Yap and Temerloh were selected as area of this study. The stream flow and water level data were gathered from DID record. Data set for this study were analysed by using non-parametric analysis, Mann-Kendall Trend Test. The results that obtained from stream flow and water level analysis indicate that there are positively significant trend for Lubuk Paku (0.001) and Sg. Yap (<0.0001) from 1972-2011 with the p-value < 0.05. Temerloh (0.178) data from 1963-2011 recorded no trend for stream flow parameter but negative trend for water level parameter. Hydrological pattern and trend are extremely affected by outside factors such as north east monsoon season that occurred in South China Sea and affected Pahang during November to March. There are other factors such as development and management of the areas which can be considered as factors affected the data and results. Hydrological Pattern is important to indicate the river trend such as stream flow and water level. It can be used as flood mitigation by local authorities. (author)
Ryu, Duchwan
2010-09-28
We consider nonparametric regression analysis in a generalized linear model (GLM) framework for data with covariates that are the subject-specific random effects of longitudinal measurements. The usual assumption that the effects of the longitudinal covariate processes are linear in the GLM may be unrealistic and if this happens it can cast doubt on the inference of observed covariate effects. Allowing the regression functions to be unknown, we propose to apply Bayesian nonparametric methods including cubic smoothing splines or P-splines for the possible nonlinearity and use an additive model in this complex setting. To improve computational efficiency, we propose the use of data-augmentation schemes. The approach allows flexible covariance structures for the random effects and within-subject measurement errors of the longitudinal processes. The posterior model space is explored through a Markov chain Monte Carlo (MCMC) sampler. The proposed methods are illustrated and compared to other approaches, the "naive" approach and the regression calibration, via simulations and by an application that investigates the relationship between obesity in adulthood and childhood growth curves. © 2010, The International Biometric Society.
Genomic outlier profile analysis: mixture models, null hypotheses, and nonparametric estimation.
Ghosh, Debashis; Chinnaiyan, Arul M
2009-01-01
In most analyses of large-scale genomic data sets, differential expression analysis is typically assessed by testing for differences in the mean of the distributions between 2 groups. A recent finding by Tomlins and others (2005) is of a different type of pattern of differential expression in which a fraction of samples in one group have overexpression relative to samples in the other group. In this work, we describe a general mixture model framework for the assessment of this type of expression, called outlier profile analysis. We start by considering the single-gene situation and establishing results on identifiability. We propose 2 nonparametric estimation procedures that have natural links to familiar multiple testing procedures. We then develop multivariate extensions of this methodology to handle genome-wide measurements. The proposed methodologies are compared using simulation studies as well as data from a prostate cancer gene expression study.
Energy Technology Data Exchange (ETDEWEB)
Takamizawa, Hisashi, E-mail: takamizawa.hisashi@jaea.go.jp; Itoh, Hiroto, E-mail: ito.hiroto@jaea.go.jp; Nishiyama, Yutaka, E-mail: nishiyama.yutaka93@jaea.go.jp
2016-10-15
In order to understand neutron irradiation embrittlement in high fluence regions, statistical analysis using the Bayesian nonparametric (BNP) method was performed for the Japanese surveillance and material test reactor irradiation database. The BNP method is essentially expressed as an infinite summation of normal distributions, with input data being subdivided into clusters with identical statistical parameters, such as mean and standard deviation, for each cluster to estimate shifts in ductile-to-brittle transition temperature (DBTT). The clusters typically depend on chemical compositions, irradiation conditions, and the irradiation embrittlement. Specific variables contributing to the irradiation embrittlement include the content of Cu, Ni, P, Si, and Mn in the pressure vessel steels, neutron flux, neutron fluence, and irradiation temperatures. It was found that the measured shifts of DBTT correlated well with the calculated ones. Data associated with the same materials were subdivided into the same clusters even if neutron fluences were increased.
Directory of Open Access Journals (Sweden)
J. Bohlin
2012-07-01
Full Text Available The recent development in software for automatic photogrammetric processing of multispectral aerial imagery, and the growing nation-wide availability of Digital Elevation Model (DEM data, are about to revolutionize data capture for forest management planning in Scandinavia. Using only already available aerial imagery and ALS-assessed DEM data, raster estimates of the forest variables mean tree height, basal area, total stem volume, and species-specific stem volumes were produced and evaluated. The study was conducted at a coniferous hemi-boreal test site in southern Sweden (lat. 58° N, long. 13° E. Digital aerial images from the Zeiss/Intergraph Digital Mapping Camera system were used to produce 3D point-cloud data with spectral information. Metrics were calculated for 696 field plots (10 m radius from point-cloud data and used in k-MSN to estimate forest variables. For these stands, the tree height ranged from 1.4 to 33.0 m (18.1 m mean, stem volume from 0 to 829 m3 ha-1 (249 m3 ha-1 mean and basal area from 0 to 62.2 m2 ha-1 (26.1 m2 ha-1 mean, with mean stand size of 2.8 ha. Estimates made using digital aerial images corresponding to the standard acquisition of the Swedish National Land Survey (Lantmäteriet showed RMSEs (in percent of the surveyed stand mean of 7.5% for tree height, 11.4% for basal area, 13.2% for total stem volume, 90.6% for pine stem volume, 26.4 for spruce stem volume, and 72.6% for deciduous stem volume. The results imply that photogrammetric matching of digital aerial images has significant potential for operational use in forestry.
Performances of non-parametric statistics in sensitivity analysis and parameter ranking
International Nuclear Information System (INIS)
Saltelli, A.
1987-01-01
Twelve parametric and non-parametric sensitivity analysis techniques are compared in the case of non-linear model responses. The test models used are taken from the long-term risk analysis for the disposal of high level radioactive waste in a geological formation. They describe the transport of radionuclides through a set of engineered and natural barriers from the repository to the biosphere and to man. The output data from these models are the dose rates affecting the maximum exposed individual of a critical group at a given point in time. All the techniques are applied to the output from the same Monte Carlo simulations, where a modified version of Latin Hypercube method is used for the sample selection. Hypothesis testing is systematically applied to quantify the degree of confidence in the results given by the various sensitivity estimators. The estimators are ranked according to their robustness and stability, on the basis of two test cases. The conclusions are that no estimator can be considered the best from all points of view and recommend the use of more than just one estimator in sensitivity analysis
Single molecule force spectroscopy at high data acquisition: A Bayesian nonparametric analysis
Sgouralis, Ioannis; Whitmore, Miles; Lapidus, Lisa; Comstock, Matthew J.; Pressé, Steve
2018-03-01
Bayesian nonparametrics (BNPs) are poised to have a deep impact in the analysis of single molecule data as they provide posterior probabilities over entire models consistent with the supplied data, not just model parameters of one preferred model. Thus they provide an elegant and rigorous solution to the difficult problem encountered when selecting an appropriate candidate model. Nevertheless, BNPs' flexibility to learn models and their associated parameters from experimental data is a double-edged sword. Most importantly, BNPs are prone to increasing the complexity of the estimated models due to artifactual features present in time traces. Thus, because of experimental challenges unique to single molecule methods, naive application of available BNP tools is not possible. Here we consider traces with time correlations and, as a specific example, we deal with force spectroscopy traces collected at high acquisition rates. While high acquisition rates are required in order to capture dwells in short-lived molecular states, in this setup, a slow response of the optical trap instrumentation (i.e., trapped beads, ambient fluid, and tethering handles) distorts the molecular signals introducing time correlations into the data that may be misinterpreted as true states by naive BNPs. Our adaptation of BNP tools explicitly takes into consideration these response dynamics, in addition to drift and noise, and makes unsupervised time series analysis of correlated single molecule force spectroscopy measurements possible, even at acquisition rates similar to or below the trap's response times.
International Nuclear Information System (INIS)
Behringer, K.; Spiekerman, G.
1984-01-01
Piety (1977) proposed an automated signature analysis of power spectral density data. Eight statistical decision discriminants are introduced. For nearly all the discriminants, improved confidence statements can be made. The statistical characteristics of the last three discriminants, which are applications of non-parametric tests, are considered. (author)
Spectral analysis of bedform dynamics
DEFF Research Database (Denmark)
Winter, Christian; Ernstsen, Verner Brandbyge; Noormets, Riko
Successive multibeam echo sounder surveys in tidal channels off Esbjerg (Denmark) on the North Sea coast reveal the dynamics of subaquatic compound dunes. Mainly driven by tidal currents, dune structures show complex migration patterns in all temporal and spatial scales. Common methods for the an....... The proposed method overcomes the above mentioned problems of common descriptive analysis as it is an objective and straightforward mathematical process. The spectral decomposition of superimposed dunes allows a detailed description and analysis of dune patterns and migration.......Successive multibeam echo sounder surveys in tidal channels off Esbjerg (Denmark) on the North Sea coast reveal the dynamics of subaquatic compound dunes. Mainly driven by tidal currents, dune structures show complex migration patterns in all temporal and spatial scales. Common methods...... allows the application of a procedure, which has been a standard for the analysis of water waves for long times: The bathymetric signal of a cross-section of subaquatic compound dunes is approximated by the sum of a set of harmonic functions, derived by Fourier transformation. If the wavelength...
Nonparametric Bayesian inference for mean residual life functions in survival analysis.
Poynor, Valerie; Kottas, Athanasios
2018-01-19
Modeling and inference for survival analysis problems typically revolves around different functions related to the survival distribution. Here, we focus on the mean residual life (MRL) function, which provides the expected remaining lifetime given that a subject has survived (i.e. is event-free) up to a particular time. This function is of direct interest in reliability, medical, and actuarial fields. In addition to its practical interpretation, the MRL function characterizes the survival distribution. We develop general Bayesian nonparametric inference for MRL functions built from a Dirichlet process mixture model for the associated survival distribution. The resulting model for the MRL function admits a representation as a mixture of the kernel MRL functions with time-dependent mixture weights. This model structure allows for a wide range of shapes for the MRL function. Particular emphasis is placed on the selection of the mixture kernel, taken to be a gamma distribution, to obtain desirable properties for the MRL function arising from the mixture model. The inference method is illustrated with a data set of two experimental groups and a data set involving right censoring. The supplementary material available at Biostatistics online provides further results on empirical performance of the model, using simulated data examples. © The Author 2018. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Ramajo, Julián; Cordero, José Manuel; Márquez, Miguel Ángel
2017-10-01
This paper analyses region-level technical efficiency in nine European countries over the 1995-2007 period. We propose the application of a nonparametric conditional frontier approach to account for the presence of heterogeneous conditions in the form of geographical externalities. Such environmental factors are beyond the control of regional authorities, but may affect the production function. Therefore, they need to be considered in the frontier estimation. Specifically, a spatial autoregressive term is included as an external conditioning factor in a robust order- m model. Thus we can test the hypothesis of non-separability (the external factor impacts both the input-output space and the distribution of efficiencies), demonstrating the existence of significant global interregional spillovers into the production process. Our findings show that geographical externalities affect both the frontier level and the probability of being more or less efficient. Specifically, the results support the fact that the spatial lag variable has an inverted U-shaped non-linear impact on the performance of regions. This finding can be interpreted as a differential effect of interregional spillovers depending on the size of the neighboring economies: positive externalities for small values, possibly related to agglomeration economies, and negative externalities for high values, indicating the possibility of production congestion. Additionally, evidence of the existence of a strong geographic pattern of European regional efficiency is reported and the levels of technical efficiency are acknowledged to have converged during the period under analysis.
A Bayesian approach to the analysis of quantal bioassay studies using nonparametric mixture models.
Fronczyk, Kassandra; Kottas, Athanasios
2014-03-01
We develop a Bayesian nonparametric mixture modeling framework for quantal bioassay settings. The approach is built upon modeling dose-dependent response distributions. We adopt a structured nonparametric prior mixture model, which induces a monotonicity restriction for the dose-response curve. Particular emphasis is placed on the key risk assessment goal of calibration for the dose level that corresponds to a specified response. The proposed methodology yields flexible inference for the dose-response relationship as well as for other inferential objectives, as illustrated with two data sets from the literature. © 2013, The International Biometric Society.
Examination of Spectral Transformations on Spectral Mixture Analysis
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.
Basic Functional Analysis Puzzles of Spectral Flow
DEFF Research Database (Denmark)
Booss-Bavnbek, Bernhelm
2011-01-01
We explain an array of basic functional analysis puzzles on the way to general spectral flow formulae and indicate a direction of future topological research for dealing with these puzzles.......We explain an array of basic functional analysis puzzles on the way to general spectral flow formulae and indicate a direction of future topological research for dealing with these puzzles....
Does Private Tutoring Work? The Effectiveness of Private Tutoring: A Nonparametric Bounds Analysis
Hof, Stefanie
2014-01-01
Private tutoring has become popular throughout the world. However, evidence for the effect of private tutoring on students' academic outcome is inconclusive; therefore, this paper presents an alternative framework: a nonparametric bounds method. The present examination uses, for the first time, a large representative data-set in a European setting…
Non-Parametric Kinetic (NPK Analysis of Thermal Oxidation of Carbon Aerogels
Directory of Open Access Journals (Sweden)
Azadeh Seifi
2017-05-01
Full Text Available In recent years, much attention has been paid to aerogel materials (especially carbon aerogels due to their potential uses in energy-related applications, such as thermal energy storage and thermal protection systems. These open cell carbon-based porous materials (carbon aerogels can strongly react with oxygen at relatively low temperatures (~ 400°C. Therefore, it is necessary to evaluate the thermal performance of carbon aerogels in view of their energy-related applications at high temperatures and under thermal oxidation conditions. The objective of this paper is to study theoretically and experimentally the oxidation reaction kinetics of carbon aerogel using the non-parametric kinetic (NPK as a powerful method. For this purpose, a non-isothermal thermogravimetric analysis, at three different heating rates, was performed on three samples each with its specific pore structure, density and specific surface area. The most significant feature of this method, in comparison with the model-free isoconversional methods, is its ability to separate the functionality of the reaction rate with the degree of conversion and temperature by the direct use of thermogravimetric data. Using this method, it was observed that the Nomen-Sempere model could provide the best fit to the data, while the temperature dependence of the rate constant was best explained by a Vogel-Fulcher relationship, where the reference temperature was the onset temperature of oxidation. Moreover, it was found from the results of this work that the assumption of the Arrhenius relation for the temperature dependence of the rate constant led to over-estimation of the apparent activation energy (up to 160 kJ/mol that was considerably different from the values (up to 3.5 kJ/mol predicted by the Vogel-Fulcher relationship in isoconversional methods
International Nuclear Information System (INIS)
Janurová, Kateřina; Briš, Radim
2014-01-01
Medical survival right-censored data of about 850 patients are evaluated to analyze the uncertainty related to the risk of mortality on one hand and compare two basic surgery techniques in the context of risk of mortality on the other hand. Colorectal data come from patients who underwent colectomy in the University Hospital of Ostrava. Two basic surgery operating techniques are used for the colectomy: either traditional (open) or minimally invasive (laparoscopic). Basic question arising at the colectomy operation is, which type of operation to choose to guarantee longer overall survival time. Two non-parametric approaches have been used to quantify probability of mortality with uncertainties. In fact, complement of the probability to one, i.e. survival function with corresponding confidence levels is calculated and evaluated. First approach considers standard nonparametric estimators resulting from both the Kaplan–Meier estimator of survival function in connection with Greenwood's formula and the Nelson–Aalen estimator of cumulative hazard function including confidence interval for survival function as well. The second innovative approach, represented by Nonparametric Predictive Inference (NPI), uses lower and upper probabilities for quantifying uncertainty and provides a model of predictive survival function instead of the population survival function. The traditional log-rank test on one hand and the nonparametric predictive comparison of two groups of lifetime data on the other hand have been compared to evaluate risk of mortality in the context of mentioned surgery techniques. The size of the difference between two groups of lifetime data has been considered and analyzed as well. Both nonparametric approaches led to the same conclusion, that the minimally invasive operating technique guarantees the patient significantly longer survival time in comparison with the traditional operating technique
International Nuclear Information System (INIS)
Khoshroo, Alireza; Mulwa, Richard; Emrouznejad, Ali; Arabi, Behrouz
2013-01-01
Grape is one of the world's largest fruit crops with approximately 67.5 million tonnes produced each year and energy is an important element in modern grape productions as it heavily depends on fossil and other energy resources. Efficient use of these energies is a necessary step toward reducing environmental hazards, preventing destruction of natural resources and ensuring agricultural sustainability. Hence, identifying excessive use of energy as well as reducing energy resources is the main focus of this paper to optimize energy consumption in grape production. In this study we use a two-stage methodology to find the association of energy efficiency and performance explained by farmers' specific characteristics. In the first stage a non-parametric Data Envelopment Analysis is used to model efficiencies as an explicit function of human labor, machinery, chemicals, FYM (farmyard manure), diesel fuel, electricity and water for irrigation energies. In the second step, farm specific variables such as farmers' age, gender, level of education and agricultural experience are used in a Tobit regression framework to explain how these factors influence efficiency of grape farming. The result of the first stage shows substantial inefficiency between the grape producers in the studied area while the second stage shows that the main difference between efficient and inefficient farmers was in the use of chemicals, diesel fuel and water for irrigation. The use of chemicals such as insecticides, herbicides and fungicides were considerably less than inefficient ones. The results revealed that the more educated farmers are more energy efficient in comparison with their less educated counterparts. - Highlights: • The focus of this paper is to identify excessive use of energy and optimize energy consumption in grape production. • We measure the efficiency as a function of labor/machinery/chemicals/farmyard manure/diesel-fuel/electricity/water. • Data were obtained from 41 grape
von Hirschhausen, Christian R.; Cullmann, Astrid
2005-01-01
Abstract This paper applies parametric and non-parametric and parametric tests to assess the efficiency of electricity distribution companies in Germany. We address traditional issues in electricity sector benchmarking, such as the role of scale effects and optimal utility size, as well as new evidence specific to the situation in Germany. We use labour, capital, and peak load capacity as inputs, and units sold and the number of customers as output. The data cover 307 (out of 553) ...
Directory of Open Access Journals (Sweden)
Vangelis Sakkalis
2008-01-01
Full Text Available There is an important evidence of differences in the EEG frequency spectrum of control subjects as compared to epileptic subjects. In particular, the study of children presents difficulties due to the early stages of brain development and the various forms of epilepsy indications. In this study, we consider children that developed epileptic crises in the past but without any other clinical, psychological, or visible neurophysiological findings. The aim of the paper is to develop reliable techniques for testing if such controlled epilepsy induces related spectral differences in the EEG. Spectral features extracted by using nonparametric, signal representation techniques (Fourier and wavelet transform and a parametric, signal modeling technique (ARMA are compared and their effect on the classification of the two groups is analyzed. The subjects performed two different tasks: a control (rest task and a relatively difficult math task. The results show that spectral features extracted by modeling the EEG signals recorded from individual channels by an ARMA model give a higher discrimination between the two subject groups for the control task, where classification scores of up to 100% were obtained with a linear discriminant classifier.
Tang, Niansheng; Chow, Sy-Miin; Ibrahim, Joseph G; Zhu, Hongtu
2017-12-01
Many psychological concepts are unobserved and usually represented as latent factors apprehended through multiple observed indicators. When multiple-subject multivariate time series data are available, dynamic factor analysis models with random effects offer one way of modeling patterns of within- and between-person variations by combining factor analysis and time series analysis at the factor level. Using the Dirichlet process (DP) as a nonparametric prior for individual-specific time series parameters further allows the distributional forms of these parameters to deviate from commonly imposed (e.g., normal or other symmetric) functional forms, arising as a result of these parameters' restricted ranges. Given the complexity of such models, a thorough sensitivity analysis is critical but computationally prohibitive. We propose a Bayesian local influence method that allows for simultaneous sensitivity analysis of multiple modeling components within a single fitting of the model of choice. Five illustrations and an empirical example are provided to demonstrate the utility of the proposed approach in facilitating the detection of outlying cases and common sources of misspecification in dynamic factor analysis models, as well as identification of modeling components that are sensitive to changes in the DP prior specification.
Robust non-parametric one-sample tests for the analysis of recurrent events.
Rebora, Paola; Galimberti, Stefania; Valsecchi, Maria Grazia
2010-12-30
One-sample non-parametric tests are proposed here for inference on recurring events. The focus is on the marginal mean function of events and the basis for inference is the standardized distance between the observed and the expected number of events under a specified reference rate. Different weights are considered in order to account for various types of alternative hypotheses on the mean function of the recurrent events process. A robust version and a stratified version of the test are also proposed. The performance of these tests was investigated through simulation studies under various underlying event generation processes, such as homogeneous and nonhomogeneous Poisson processes, autoregressive and renewal processes, with and without frailty effects. The robust versions of the test have been shown to be suitable in a wide variety of event generating processes. The motivating context is a study on gene therapy in a very rare immunodeficiency in children, where a major end-point is the recurrence of severe infections. Robust non-parametric one-sample tests for recurrent events can be useful to assess efficacy and especially safety in non-randomized studies or in epidemiological studies for comparison with a standard population. Copyright © 2010 John Wiley & Sons, Ltd.
SPAM- SPECTRAL ANALYSIS MANAGER (UNIX VERSION)
Solomon, J. E.
1994-01-01
The Spectral Analysis Manager (SPAM) was developed to allow easy qualitative analysis of multi-dimensional imaging spectrometer data. Imaging spectrometers provide sufficient spectral sampling to define unique spectral signatures on a per pixel basis. Thus direct material identification becomes possible for geologic studies. SPAM provides a variety of capabilities for carrying out interactive analysis of the massive and complex datasets associated with multispectral remote sensing observations. In addition to normal image processing functions, SPAM provides multiple levels of on-line help, a flexible command interpretation, graceful error recovery, and a program structure which can be implemented in a variety of environments. SPAM was designed to be visually oriented and user friendly with the liberal employment of graphics for rapid and efficient exploratory analysis of imaging spectrometry data. SPAM provides functions to enable arithmetic manipulations of the data, such as normalization, linear mixing, band ratio discrimination, and low-pass filtering. SPAM can be used to examine the spectra of an individual pixel or the average spectra over a number of pixels. SPAM also supports image segmentation, fast spectral signature matching, spectral library usage, mixture analysis, and feature extraction. High speed spectral signature matching is performed by using a binary spectral encoding algorithm to separate and identify mineral components present in the scene. The same binary encoding allows automatic spectral clustering. Spectral data may be entered from a digitizing tablet, stored in a user library, compared to the master library containing mineral standards, and then displayed as a timesequence spectral movie. The output plots, histograms, and stretched histograms produced by SPAM can be sent to a lineprinter, stored as separate RGB disk files, or sent to a Quick Color Recorder. SPAM is written in C for interactive execution and is available for two different
NParCov3: A SAS/IML Macro for Nonparametric Randomization-Based Analysis of Covariance
Directory of Open Access Journals (Sweden)
Richard C. Zink
2012-07-01
Full Text Available Analysis of covariance serves two important purposes in a randomized clinical trial. First, there is a reduction of variance for the treatment effect which provides more powerful statistical tests and more precise confidence intervals. Second, it provides estimates of the treatment effect which are adjusted for random imbalances of covariates between the treatment groups. The nonparametric analysis of covariance method of Koch, Tangen, Jung, and Amara (1998 defines a very general methodology using weighted least-squares to generate covariate-adjusted treatment effects with minimal assumptions. This methodology is general in its applicability to a variety of outcomes, whether continuous, binary, ordinal, incidence density or time-to-event. Further, its use has been illustrated in many clinical trial settings, such as multi-center, dose-response and non-inferiority trials.NParCov3 is a SAS/IML macro written to conduct the nonparametric randomization-based covariance analyses of Koch et al. (1998. The software can analyze a variety of outcomes and can account for stratification. Data from multiple clinical trials will be used for illustration.
Nonparametric statistical inference
Gibbons, Jean Dickinson
2014-01-01
Thoroughly revised and reorganized, the fourth edition presents in-depth coverage of the theory and methods of the most widely used nonparametric procedures in statistical analysis and offers example applications appropriate for all areas of the social, behavioral, and life sciences. The book presents new material on the quantiles, the calculation of exact and simulated power, multiple comparisons, additional goodness-of-fit tests, methods of analysis of count data, and modern computer applications using MINITAB, SAS, and STATXACT. It includes tabular guides for simplified applications of tests and finding P values and confidence interval estimates.
Karabatsos, George
2017-02-01
Most of applied statistics involves regression analysis of data. In practice, it is important to specify a regression model that has minimal assumptions which are not violated by data, to ensure that statistical inferences from the model are informative and not misleading. This paper presents a stand-alone and menu-driven software package, Bayesian Regression: Nonparametric and Parametric Models, constructed from MATLAB Compiler. Currently, this package gives the user a choice from 83 Bayesian models for data analysis. They include 47 Bayesian nonparametric (BNP) infinite-mixture regression models; 5 BNP infinite-mixture models for density estimation; and 31 normal random effects models (HLMs), including normal linear models. Each of the 78 regression models handles either a continuous, binary, or ordinal dependent variable, and can handle multi-level (grouped) data. All 83 Bayesian models can handle the analysis of weighted observations (e.g., for meta-analysis), and the analysis of left-censored, right-censored, and/or interval-censored data. Each BNP infinite-mixture model has a mixture distribution assigned one of various BNP prior distributions, including priors defined by either the Dirichlet process, Pitman-Yor process (including the normalized stable process), beta (two-parameter) process, normalized inverse-Gaussian process, geometric weights prior, dependent Dirichlet process, or the dependent infinite-probits prior. The software user can mouse-click to select a Bayesian model and perform data analysis via Markov chain Monte Carlo (MCMC) sampling. After the sampling completes, the software automatically opens text output that reports MCMC-based estimates of the model's posterior distribution and model predictive fit to the data. Additional text and/or graphical output can be generated by mouse-clicking other menu options. This includes output of MCMC convergence analyses, and estimates of the model's posterior predictive distribution, for selected
Functional analysis, spectral theory, and applications
Einsiedler, Manfred
2017-01-01
This textbook provides a careful treatment of functional analysis and some of its applications in analysis, number theory, and ergodic theory. In addition to discussing core material in functional analysis, the authors cover more recent and advanced topics, including Weyl’s law for eigenfunctions of the Laplace operator, amenability and property (T), the measurable functional calculus, spectral theory for unbounded operators, and an account of Tao’s approach to the prime number theorem using Banach algebras. The book further contains numerous examples and exercises, making it suitable for both lecture courses and self-study. Functional Analysis, Spectral Theory, and Applications is aimed at postgraduate and advanced undergraduate students with some background in analysis and algebra, but will also appeal to everyone with an interest in seeing how functional analysis can be applied to other parts of mathematics.
Rodríguez-Álvarez, María Xosé; Roca-Pardiñas, Javier; Cadarso-Suárez, Carmen; Tahoces, Pablo G
2018-03-01
Prior to using a diagnostic test in a routine clinical setting, the rigorous evaluation of its diagnostic accuracy is essential. The receiver-operating characteristic curve is the measure of accuracy most widely used for continuous diagnostic tests. However, the possible impact of extra information about the patient (or even the environment) on diagnostic accuracy also needs to be assessed. In this paper, we focus on an estimator for the covariate-specific receiver-operating characteristic curve based on direct regression modelling and nonparametric smoothing techniques. This approach defines the class of generalised additive models for the receiver-operating characteristic curve. The main aim of the paper is to offer new inferential procedures for testing the effect of covariates on the conditional receiver-operating characteristic curve within the above-mentioned class. Specifically, two different bootstrap-based tests are suggested to check (a) the possible effect of continuous covariates on the receiver-operating characteristic curve and (b) the presence of factor-by-curve interaction terms. The validity of the proposed bootstrap-based procedures is supported by simulations. To facilitate the application of these new procedures in practice, an R-package, known as npROCRegression, is provided and briefly described. Finally, data derived from a computer-aided diagnostic system for the automatic detection of tumour masses in breast cancer is analysed.
Particulate characterization by PIXE multivariate spectral analysis
International Nuclear Information System (INIS)
Antolak, Arlyn J.; Morse, Daniel H.; Grant, Patrick G.; Kotula, Paul G.; Doyle, Barney L.; Richardson, Charles B.
2007-01-01
Obtaining particulate compositional maps from scanned PIXE (proton-induced X-ray emission) measurements is extremely difficult due to the complexity of analyzing spectroscopic data collected with low signal-to-noise at each scan point (pixel). Multivariate spectral analysis has the potential to analyze such data sets by reducing the PIXE data to a limited number of physically realizable and easily interpretable components (that include both spectral and image information). We have adapted the AXSIA (automated expert spectral image analysis) program, originally developed by Sandia National Laboratories to quantify electron-excited X-ray spectroscopy data, for this purpose. Samples consisting of particulates with known compositions and sizes were loaded onto Mylar and paper filter substrates and analyzed by scanned micro-PIXE. The data sets were processed by AXSIA and the associated principal component spectral data were quantified by converting the weighting images into concentration maps. The results indicate automated, nonbiased, multivariate statistical analysis is useful for converting very large amounts of data into a smaller, more manageable number of compositional components needed for locating individual particles-of-interest on large area collection media
Spectral theory and nonlinear functional analysis
Lopez-Gomez, Julian
2001-01-01
This Research Note addresses several pivotal problems in spectral theory and nonlinear functional analysis in connection with the analysis of the structure of the set of zeroes of a general class of nonlinear operators. It features the construction of an optimal algebraic/analytic invariant for calculating the Leray-Schauder degree, new methods for solving nonlinear equations in Banach spaces, and general properties of components of solutions sets presented with minimal use of topological tools. The author also gives several applications of the abstract theory to reaction diffusion equations and systems.The results presented cover a thirty-year period and include recent, unpublished findings of the author and his coworkers. Appealing to a broad audience, Spectral Theory and Nonlinear Functional Analysis contains many important contributions to linear algebra, linear and nonlinear functional analysis, and topology and opens the door for further advances.
Yau, C; Papaspiliopoulos, O; Roberts, G O; Holmes, C
2011-01-01
We consider the development of Bayesian Nonparametric methods for product partition models such as Hidden Markov Models and change point models. Our approach uses a Mixture of Dirichlet Process (MDP) model for the unknown sampling distribution (likelihood) for the observations arising in each state and a computationally efficient data augmentation scheme to aid inference. The method uses novel MCMC methodology which combines recent retrospective sampling methods with the use of slice sampler variables. The methodology is computationally efficient, both in terms of MCMC mixing properties, and robustness to the length of the time series being investigated. Moreover, the method is easy to implement requiring little or no user-interaction. We apply our methodology to the analysis of genomic copy number variation.
Nonparametric statistics for social and behavioral sciences
Kraska-MIller, M
2013-01-01
Introduction to Research in Social and Behavioral SciencesBasic Principles of ResearchPlanning for ResearchTypes of Research Designs Sampling ProceduresValidity and Reliability of Measurement InstrumentsSteps of the Research Process Introduction to Nonparametric StatisticsData AnalysisOverview of Nonparametric Statistics and Parametric Statistics Overview of Parametric Statistics Overview of Nonparametric StatisticsImportance of Nonparametric MethodsMeasurement InstrumentsAnalysis of Data to Determine Association and Agreement Pearson Chi-Square Test of Association and IndependenceContingency
Nonparametric correlation models for portfolio allocation
DEFF Research Database (Denmark)
Aslanidis, Nektarios; Casas, Isabel
2013-01-01
This article proposes time-varying nonparametric and semiparametric estimators of the conditional cross-correlation matrix in the context of portfolio allocation. Simulations results show that the nonparametric and semiparametric models are best in DGPs with substantial variability or structural ...... currencies. Results show the nonparametric model generally dominates the others when evaluating in-sample. However, the semiparametric model is best for out-of-sample analysis....
Terahertz Josephson spectral analysis and its applications
Snezhko, A. V.; Gundareva, I. I.; Lyatti, M. V.; Volkov, O. Y.; Pavlovskiy, V. V.; Poppe, U.; Divin, Y. Y.
2017-04-01
Principles of Hilbert-transform spectral analysis (HTSA) are presented and advantages of the technique in the terahertz (THz) frequency range are discussed. THz HTSA requires Josephson junctions with high values of characteristic voltages I c R n and dynamics described by a simple resistively shunted junction (RSJ) model. To meet these requirements, [001]- and [100]-tilt YBa2Cu3O7-x bicrystal junctions with deviations from the RSJ model less than 1% have been developed. Demonstrators of Hilbert-transform spectrum analyzers with various cryogenic environments, including integration into Stirling coolers, are described. Spectrum analyzers have been characterized in the spectral range from 50 GHz to 3 THz. Inside a power dynamic range of five orders, an instrumental function of the analyzers has been found to have a Lorentz form around a single frequency of 1.48 THz with a spectral resolution as low as 0.9 GHz. Spectra of THz radiation from optically pumped gas lasers and semiconductor frequency multipliers have been studied with these spectrum analyzers and the regimes of these radiation sources were optimized for a single-frequency operation. Future applications of HTSA will be related with quick and precise spectral characterization of new radiation sources and identification of substances in the THz frequency range.
Spectral analysis of Floating Car Data
Gössel, F.; Michler, E.; Wrase, B.
2003-01-01
Floating Car Data (FCD) are one important data source in traffic telematic systems. The original variable in these systems is the vehicle velocity. The paper analyses the measured value “vehicle velocity" by methods of information technology. Consequences for processing, transmission and storage of FCD under condition of limited resources are discussed. Starting point of the investigation is the analysis of spectral characteristics of velocity-time-profiles. The spectra are determined by...
Decision support using nonparametric statistics
Beatty, Warren
2018-01-01
This concise volume covers nonparametric statistics topics that most are most likely to be seen and used from a practical decision support perspective. While many degree programs require a course in parametric statistics, these methods are often inadequate for real-world decision making in business environments. Much of the data collected today by business executives (for example, customer satisfaction opinions) requires nonparametric statistics for valid analysis, and this book provides the reader with a set of tools that can be used to validly analyze all data, regardless of type. Through numerous examples and exercises, this book explains why nonparametric statistics will lead to better decisions and how they are used to reach a decision, with a wide array of business applications. Online resources include exercise data, spreadsheets, and solutions.
Nonparametric statistical inference
Gibbons, Jean Dickinson
2010-01-01
Overall, this remains a very fine book suitable for a graduate-level course in nonparametric statistics. I recommend it for all people interested in learning the basic ideas of nonparametric statistical inference.-Eugenia Stoimenova, Journal of Applied Statistics, June 2012… one of the best books available for a graduate (or advanced undergraduate) text for a theory course on nonparametric statistics. … a very well-written and organized book on nonparametric statistics, especially useful and recommended for teachers and graduate students.-Biometrics, 67, September 2011This excellently presente
Multitaper spectral analysis of atmospheric radar signals
Directory of Open Access Journals (Sweden)
V. K. Anandan
2004-11-01
Full Text Available Multitaper spectral analysis using sinusoidal taper has been carried out on the backscattered signals received from the troposphere and lower stratosphere by the Gadanki Mesosphere-Stratosphere-Troposphere (MST radar under various conditions of the signal-to-noise ratio. Comparison of study is made with sinusoidal taper of the order of three and single tapers of Hanning and rectangular tapers, to understand the relative merits of processing under the scheme. Power spectra plots show that echoes are better identified in the case of multitaper estimation, especially in the region of a weak signal-to-noise ratio. Further analysis is carried out to obtain three lower order moments from three estimation techniques. The results show that multitaper analysis gives a better signal-to-noise ratio or higher detectability. The spectral analysis through multitaper and single tapers is subjected to study of consistency in measurements. Results show that the multitaper estimate is better consistent in Doppler measurements compared to single taper estimates. Doppler width measurements with different approaches were studied and the results show that the estimation was better in the multitaper technique in terms of temporal resolution and estimation accuracy.
Semiclassical analysis spectral correlations in mesoscopic systems
International Nuclear Information System (INIS)
Argaman, N.; Imry, Y.; Smilansky, U.
1991-07-01
We consider the recently developed semiclassical analysis of the quantum mechanical spectral form factor, which may be expressed in terms of classically defiable properties. When applied to electrons whose classical behaviour is diffusive, the results of earlier quantum mechanical perturbative derivations, which were developed under a different set of assumptions, are reproduced. The comparison between the two derivations shows that the results depends not on their specific details, but to a large extent on the principle of quantum coherent superposition, and on the generality of the notion of diffusion. The connection with classical properties facilitates application to many physical situations. (author)
Spectral analysis of allogeneic hydroxyapatite powders
Timchenko, P. E.; Timchenko, E. V.; Pisareva, E. V.; Vlasov, M. Yu; Red'kin, N. A.; Frolov, O. O.
2017-01-01
In this paper we discuss the application of Raman spectroscopy to the in vitro analysis of the hydroxyapatite powder samples produced from different types of animal bone tissue during demineralization process at various acid concentrations and exposure durations. The derivation of the Raman spectrum of hydroxyapatite is attempted by the analysis of the pure powders of its known constituents. Were experimentally found spectral features of hydroxyapatite, based on analysis of the line amplitude at wave numbers 950-965 cm-1 ((PO4)3- (ν1) vibration) and 1065-1075 cm-1 ((CO3)2-(ν1) B-type replacement). Control of physicochemical properties of hydroxyapatite was carried out by Raman spectroscopy. Research results are compared with an infrared Fourier spectroscopy.
Spectral analysis of allogeneic hydroxyapatite powders
International Nuclear Information System (INIS)
Timchenko, P E; Timchenko, E V; Pisareva, E V; Vlasov, M Yu; Red’kin, N A; Frolov, O O
2017-01-01
In this paper we discuss the application of Raman spectroscopy to the in vitro analysis of the hydroxyapatite powder samples produced from different types of animal bone tissue during demineralization process at various acid concentrations and exposure durations. The derivation of the Raman spectrum of hydroxyapatite is attempted by the analysis of the pure powders of its known constituents. Were experimentally found spectral features of hydroxyapatite, based on analysis of the line amplitude at wave numbers 950-965 cm -1 ((PO 4 ) 3- (ν 1 ) vibration) and 1065-1075 cm -1 ((CO 3 ) 2- (ν 1 ) B-type replacement). Control of physicochemical properties of hydroxyapatite was carried out by Raman spectroscopy. Research results are compared with an infrared Fourier spectroscopy. (paper)
International Nuclear Information System (INIS)
Storlie, Curtis B.; Swiler, Laura P.; Helton, Jon C.; Sallaberry, Cedric J.
2009-01-01
The analysis of many physical and engineering problems involves running complex computational models (simulation models, computer codes). With problems of this type, it is important to understand the relationships between the input variables (whose values are often imprecisely known) and the output. The goal of sensitivity analysis (SA) is to study this relationship and identify the most significant factors or variables affecting the results of the model. In this presentation, an improvement on existing methods for SA of complex computer models is described for use when the model is too computationally expensive for a standard Monte-Carlo analysis. In these situations, a meta-model or surrogate model can be used to estimate the necessary sensitivity index for each input. A sensitivity index is a measure of the variance in the response that is due to the uncertainty in an input. Most existing approaches to this problem either do not work well with a large number of input variables and/or they ignore the error involved in estimating a sensitivity index. Here, a new approach to sensitivity index estimation using meta-models and bootstrap confidence intervals is described that provides solutions to these drawbacks. Further, an efficient yet effective approach to incorporate this methodology into an actual SA is presented. Several simulated and real examples illustrate the utility of this approach. This framework can be extended to uncertainty analysis as well.
Czech Academy of Sciences Publication Activity Database
Brázdik, František
-, č. 286 (2006), s. 1-45 ISSN 1211-3298 R&D Projects: GA MŠk LC542 Institutional research plan: CEZ:AV0Z70850503 Keywords : rice farms * data envelopment analysis Subject RIV: AH - Economics http://www.cerge-ei.cz/pdf/wp/Wp286.pdf
Pataky, Todd C; Vanrenterghem, Jos; Robinson, Mark A
2015-05-01
Biomechanical processes are often manifested as one-dimensional (1D) trajectories. It has been shown that 1D confidence intervals (CIs) are biased when based on 0D statistical procedures, and the non-parametric 1D bootstrap CI has emerged in the Biomechanics literature as a viable solution. The primary purpose of this paper was to clarify that, for 1D biomechanics datasets, the distinction between 0D and 1D methods is much more important than the distinction between parametric and non-parametric procedures. A secondary purpose was to demonstrate that a parametric equivalent to the 1D bootstrap exists in the form of a random field theory (RFT) correction for multiple comparisons. To emphasize these points we analyzed six datasets consisting of force and kinematic trajectories in one-sample, paired, two-sample and regression designs. Results showed, first, that the 1D bootstrap and other 1D non-parametric CIs were qualitatively identical to RFT CIs, and all were very different from 0D CIs. Second, 1D parametric and 1D non-parametric hypothesis testing results were qualitatively identical for all six datasets. Last, we highlight the limitations of 1D CIs by demonstrating that they are complex, design-dependent, and thus non-generalizable. These results suggest that (i) analyses of 1D data based on 0D models of randomness are generally biased unless one explicitly identifies 0D variables before the experiment, and (ii) parametric and non-parametric 1D hypothesis testing provide an unambiguous framework for analysis when one׳s hypothesis explicitly or implicitly pertains to whole 1D trajectories. Copyright © 2015 Elsevier Ltd. All rights reserved.
Wang, Su-Chen; Tsai, Chi-Cheng; Huang, Shun-Te; Hong, Yu-Jue
2002-12-01
Data envelopment analysis (DEA), a cross-sectional study design based on secondary data analysis, was used to evaluate the relative operational efficiency of 16 dental departments in medical centers in Taiwan in 1999. The results indicated that 68.7% of all dental departments in medical centers had poor performance in terms of overall efficiency and scale efficiency. All relatively efficient dental departments were in private medical centers. Half of these dental departments were unable to fully utilize available medical resources. 75.0% of public medical centers did not take full advantage of medical resources at their disposal. In the returns to scale, 56.3% of dental departments in medical centers exhibited increasing returns to scale, due to the insufficient scale influencing overall hospital operational efficiency. Public medical centers accounted for 77.8% of the institutions affected. The scale of dental departments in private medical centers was more appropriate than those in public medical centers. In the sensitivity analysis, the numbers of residents, interns, and published papers were used to assess teaching and research. Greater emphasis on teaching and research in medical centers has a large effect on the relative inefficiency of hospital operation. Dental departments in private medical centers had a higher mean overall efficiency score than those in public medical centers, and the overall efficiency of dental departments in non-university hospitals was greater than those in university hospitals. There was no information to evaluate the long-term efficiency of each dental department in all hospitals. A different combination of input and output variables, using common multipliers for efficiency value measurements in DEA, may help establish different pioneering dental departments in hospitals.
Non-parametric trend analysis of the aridity index for three large arid and semi-arid basins in Iran
Ahani, Hossien; Kherad, Mehrzad; Kousari, Mohammad Reza; van Roosmalen, Lieke; Aryanfar, Ramin; Hosseini, Seyyed Mashaallah
2013-05-01
Currently, an important scientific challenge that researchers are facing is to gain a better understanding of climate change at the regional scale, which can be especially challenging in an area with low and highly variable precipitation amounts such as Iran. Trend analysis of the medium-term change using ground station observations of meteorological variables can enhance our knowledge of the dominant processes in an area and contribute to the analysis of future climate projections. Generally, studies focus on the long-term variability of temperature and precipitation and to a lesser extent on other important parameters such as moisture indices. In this study the recent 50-year trends (1955-2005) of precipitation (P), potential evapotranspiration (PET), and aridity index (AI) in monthly time scale were studied over 14 synoptic stations in three large Iran basins using the Mann-Kendall non-parametric test. Additionally, an analysis of the monthly, seasonal and annual trend of each parameter was performed. Results showed no significant trends in the monthly time series. However, PET showed significant, mostly decreasing trends, for the seasonal values, which resulted in a significant negative trend in annual PET at five stations. Significant negative trends in seasonal P values were only found at a number of stations in spring and summer and no station showed significant negative trends in annual P. Due to the varied positive and negative trends in annual P and to a lesser extent PET, almost as many stations with negative as positive trends in annual AI were found, indicating that both drying and wetting trends occurred in Iran. Overall, the northern part of the study area showed an increasing trend in annual AI which meant that the region became wetter, while the south showed decreasing trends in AI.
A spectral analysis of rice grains
International Nuclear Information System (INIS)
McIlvaine, M.S.; Cua, F.T.; Navarro, E.F.
1976-06-01
With the advent of extensive nuclear testing and the development and use of highly potent pesticides and fertilizers, the hazardous threats of radioactive contamination due to fallout and to the absorption of pesticide residues have been given due consideration. Among the many forms of life exposed to these threats are food crops and among these is rice. Several rice grain samples - Japanese rice samples ''A'' and ''B'' submitted by the National Grains Authority (NGA) for analysis, random samples of rice being sold to the public at local markets, and ''black rice'' which were picked from along the shores of a Mindoro town were subjected to spectral analysis. Results revealed the presence of trace elements normally found in plants, such as; K-42, I-124, Cl-38, Na-24, Br-82, and Mn-56. No mercury was detected in the sample specimen analyzed
Spectral analysis of major heart tones
Lejkowski, W.; Dobrowolski, A. P.; Majka, K.; Olszewski, R.
2018-04-01
The World Health Organization (WHO) figures clearly indicate that cardiovascular disease is the most common cause of death and disability in the world. Early detection of cardiovascular pathologies may contribute to reducing such a high mortality rate. Auscultatory examination is one of the first and most important step in cardiologic diagnostics. Unfortunately, proper diagnosis is closely related to long-term practice and medical experience. The article presents the author's system of recording phonocardiograms and the way of saving data, as well as the outline of the analysis algorithm, which will allow to assign a case to a patient with heart failure or healthy voluntaries' with a certain high probability. The results of a pilot study of phonocardiographic signals were also presented as an introduction to further research aimed at the development of an efficient diagnostic algorithm based on spectral analysis of the heart tone.
Directory of Open Access Journals (Sweden)
Ignacio Santamaría
2008-04-01
Full Text Available This paper treats the identification of nonlinear systems that consist of a cascade of a linear channel and a nonlinearity, such as the well-known Wiener and Hammerstein systems. In particular, we follow a supervised identification approach that simultaneously identifies both parts of the nonlinear system. Given the correct restrictions on the identification problem, we show how kernel canonical correlation analysis (KCCA emerges as the logical solution to this problem. We then extend the proposed identification algorithm to an adaptive version allowing to deal with time-varying systems. In order to avoid overfitting problems, we discuss and compare three possible regularization techniques for both the batch and the adaptive versions of the proposed algorithm. Simulations are included to demonstrate the effectiveness of the presented algorithm.
Directory of Open Access Journals (Sweden)
Shanshan eLi
2016-01-01
Full Text Available Independent Component analysis (ICA is a widely used technique for separating signals that have been mixed together. In this manuscript, we propose a novel ICA algorithm using density estimation and maximum likelihood, where the densities of the signals are estimated via p-spline based histogram smoothing and the mixing matrix is simultaneously estimated using an optimization algorithm. The algorithm is exceedingly simple, easy to implement and blind to the underlying distributions of the source signals. To relax the identically distributed assumption in the density function, a modified algorithm is proposed to allow for different density functions on different regions. The performance of the proposed algorithm is evaluated in different simulation settings. For illustration, the algorithm is applied to a research investigation with a large collection of resting state fMRI datasets. The results show that the algorithm successfully recovers the established brain networks.
Spectral Analysis Methods of Social Networks
Directory of Open Access Journals (Sweden)
P. G. Klyucharev
2017-01-01
Full Text Available Online social networks (such as Facebook, Twitter, VKontakte, etc. being an important channel for disseminating information are often used to arrange an impact on the social consciousness for various purposes - from advertising products or services to the full-scale information war thereby making them to be a very relevant object of research. The paper reviewed the analysis methods of social networks (primarily, online, based on the spectral theory of graphs. Such methods use the spectrum of the social graph, i.e. a set of eigenvalues of its adjacency matrix, and also the eigenvectors of the adjacency matrix.Described measures of centrality (in particular, centrality based on the eigenvector and PageRank, which reflect a degree of impact one or another user of the social network has. A very popular PageRank measure uses, as a measure of centrality, the graph vertices, the final probabilities of the Markov chain, whose matrix of transition probabilities is calculated on the basis of the adjacency matrix of the social graph. The vector of final probabilities is an eigenvector of the matrix of transition probabilities.Presented a method of dividing the graph vertices into two groups. It is based on maximizing the network modularity by computing the eigenvector of the modularity matrix.Considered a method for detecting bots based on the non-randomness measure of a graph to be computed using the spectral coordinates of vertices - sets of eigenvector components of the adjacency matrix of a social graph.In general, there are a number of algorithms to analyse social networks based on the spectral theory of graphs. These algorithms show very good results, but their disadvantage is the relatively high (albeit polynomial computational complexity for large graphs.At the same time it is obvious that the practical application capacity of the spectral graph theory methods is still underestimated, and it may be used as a basis to develop new methods.The work
EXOPLANETARY DETECTION BY MULTIFRACTAL SPECTRAL ANALYSIS
Energy Technology Data Exchange (ETDEWEB)
Agarwal, Sahil; Wettlaufer, John S. [Program in Applied Mathematics, Yale University, New Haven, CT (United States); Sordo, Fabio Del [Department of Astronomy, Yale University, New Haven, CT (United States)
2017-01-01
Owing to technological advances, the number of exoplanets discovered has risen dramatically in the last few years. However, when trying to observe Earth analogs, it is often difficult to test the veracity of detection. We have developed a new approach to the analysis of exoplanetary spectral observations based on temporal multifractality, which identifies timescales that characterize planetary orbital motion around the host star and those that arise from stellar features such as spots. Without fitting stellar models to spectral data, we show how the planetary signal can be robustly detected from noisy data using noise amplitude as a source of information. For observation of transiting planets, combining this method with simple geometry allows us to relate the timescales obtained to primary and secondary eclipse of the exoplanets. Making use of data obtained with ground-based and space-based observations we have tested our approach on HD 189733b. Moreover, we have investigated the use of this technique in measuring planetary orbital motion via Doppler shift detection. Finally, we have analyzed synthetic spectra obtained using the SOAP 2.0 tool, which simulates a stellar spectrum and the influence of the presence of a planet or a spot on that spectrum over one orbital period. We have demonstrated that, so long as the signal-to-noise-ratio ≥ 75, our approach reconstructs the planetary orbital period, as well as the rotation period of a spot on the stellar surface.
A critique of non-parametric efficiency analysis in energy economics studies
International Nuclear Information System (INIS)
Chen, Chien-Ming
2013-01-01
The paper reexamines non-additive environmental efficiency models with weakly-disposable undesirable outputs appeared in the literature of energy economics. These efficiency models are used in numerous studies published in this journal and other energy-related outlets. Recent studies, however, have found key limitations of the weak-disposability assumption in its application to environmental efficiency analysis. It is found that efficiency scores obtained from non-additive efficiency models can be non-monotonic in pollution quantities under the weak-disposability assumption — which is against common intuition and the principle of environmental economics. In this paper, I present taxonomy of efficiency models found in the energy economics literature and illustrate the above limitations and discuss implications of monotonicity from a practical viewpoint. Finally, I review the formulations for a variable returns-to-scale technology with weakly-disposable undesirable outputs, which has been misused in a number of papers in the energy economics literature. An application to evaluating the energy efficiencies of 23 European Union states is presented to illustrate the problem. - Highlights: • Review different environmental efficiency model used in energy economics studies • Highlight limitations of these environmental efficiency models • These limitations have not been recognized in the existing energy economics literature. • Data from 23 European Union states are used to illustrate the methodological consequences
Industrial energy efficiency with CO2 emissions in China: A nonparametric analysis
International Nuclear Information System (INIS)
Wu, F.; Fan, L.W.; Zhou, P.; Zhou, D.Q.
2012-01-01
Global awareness on energy security and climate change has created much interest in assessing economy-wide energy efficiency performance. A number of previous studies have contributed to evaluate energy efficiency performance using different analytical techniques among which data envelopment analysis (DEA) has recently received increasing attention. Most of DEA-related energy efficiency studies do not consider undesirable outputs such as CO 2 emissions in their modeling framework, which may lead to biased energy efficiency values. Within a joint production framework of desirable and undesirable outputs, in this paper we construct both static and dynamic energy efficiency performance indexes for measuring industrial energy efficiency performance by using several environmental DEA models with CO 2 emissions. The dynamic energy efficiency performance indexes have further been decomposed into two contributing components. We finally apply the indexes proposed to assess the industrial energy efficiency performance of different provinces in China over time. Our empirical study shows that the energy efficiency improvement in China's industrial sector was mainly driven by technological improvement. - Highlights: ► China's industrial energy efficiency is evaluated by DEA models with CO 2 emissions. ► China's industrial energy efficiency improved by 5.6% annually since 1997. ► Industrial energy efficiency improvement in China was mainly driven by technological improvement.
Energy Technology Data Exchange (ETDEWEB)
Ford, Eric B.; /Florida U.; Fabrycky, Daniel C.; /Lick Observ.; Steffen, Jason H.; /Fermilab; Carter, Joshua A.; /Harvard-Smithsonian Ctr. Astrophys.; Fressin, Francois; /Harvard-Smithsonian Ctr. Astrophys.; Holman, Matthew J.; /Harvard-Smithsonian Ctr. Astrophys.; Lissauer, Jack J.; /NASA, Ames; Moorhead, Althea V.; /Florida U.; Morehead, Robert C.; /Florida U.; Ragozzine, Darin; /Harvard-Smithsonian Ctr. Astrophys.; Rowe, Jason F.; /NASA, Ames /SETI Inst., Mtn. View /San Diego State U., Astron. Dept.
2012-01-01
We present a new method for confirming transiting planets based on the combination of transit timing variations (TTVs) and dynamical stability. Correlated TTVs provide evidence that the pair of bodies are in the same physical system. Orbital stability provides upper limits for the masses of the transiting companions that are in the planetary regime. This paper describes a non-parametric technique for quantifying the statistical significance of TTVs based on the correlation of two TTV data sets. We apply this method to an analysis of the transit timing variations of two stars with multiple transiting planet candidates identified by Kepler. We confirm four transiting planets in two multiple planet systems based on their TTVs and the constraints imposed by dynamical stability. An additional three candidates in these same systems are not confirmed as planets, but are likely to be validated as real planets once further observations and analyses are possible. If all were confirmed, these systems would be near 4:6:9 and 2:4:6:9 period commensurabilities. Our results demonstrate that TTVs provide a powerful tool for confirming transiting planets, including low-mass planets and planets around faint stars for which Doppler follow-up is not practical with existing facilities. Continued Kepler observations will dramatically improve the constraints on the planet masses and orbits and provide sensitivity for detecting additional non-transiting planets. If Kepler observations were extended to eight years, then a similar analysis could likely confirm systems with multiple closely spaced, small transiting planets in or near the habitable zone of solar-type stars.
International Nuclear Information System (INIS)
Ford, Eric B.; Moorhead, Althea V.; Morehead, Robert C.; Fabrycky, Daniel C.; Steffen, Jason H.; Carter, Joshua A.; Fressin, Francois; Holman, Matthew J.; Ragozzine, Darin; Charbonneau, David; Lissauer, Jack J.; Rowe, Jason F.; Borucki, William J.; Bryson, Stephen T.; Burke, Christopher J.; Caldwell, Douglas A.; Welsh, William F.; Allen, Christopher; Batalha, Natalie M.; Buchhave, Lars A.
2012-01-01
We present a new method for confirming transiting planets based on the combination of transit timing variations (TTVs) and dynamical stability. Correlated TTVs provide evidence that the pair of bodies is in the same physical system. Orbital stability provides upper limits for the masses of the transiting companions that are in the planetary regime. This paper describes a non-parametric technique for quantifying the statistical significance of TTVs based on the correlation of two TTV data sets. We apply this method to an analysis of the TTVs of two stars with multiple transiting planet candidates identified by Kepler. We confirm four transiting planets in two multiple-planet systems based on their TTVs and the constraints imposed by dynamical stability. An additional three candidates in these same systems are not confirmed as planets, but are likely to be validated as real planets once further observations and analyses are possible. If all were confirmed, these systems would be near 4:6:9 and 2:4:6:9 period commensurabilities. Our results demonstrate that TTVs provide a powerful tool for confirming transiting planets, including low-mass planets and planets around faint stars for which Doppler follow-up is not practical with existing facilities. Continued Kepler observations will dramatically improve the constraints on the planet masses and orbits and provide sensitivity for detecting additional non-transiting planets. If Kepler observations were extended to eight years, then a similar analysis could likely confirm systems with multiple closely spaced, small transiting planets in or near the habitable zone of solar-type stars.
Energy Technology Data Exchange (ETDEWEB)
Ford, Eric B.; Moorhead, Althea V.; Morehead, Robert C. [Astronomy Department, University of Florida, 211 Bryant Space Sciences Center, Gainesville, FL 32611 (United States); Fabrycky, Daniel C. [UCO/Lick Observatory, University of California, Santa Cruz, CA 95064 (United States); Steffen, Jason H. [Fermilab Center for Particle Astrophysics, P.O. Box 500, MS 127, Batavia, IL 60510 (United States); Carter, Joshua A.; Fressin, Francois; Holman, Matthew J.; Ragozzine, Darin; Charbonneau, David [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States); Lissauer, Jack J.; Rowe, Jason F.; Borucki, William J.; Bryson, Stephen T.; Burke, Christopher J.; Caldwell, Douglas A. [NASA Ames Research Center, Moffett Field, CA 94035 (United States); Welsh, William F. [Astronomy Department, San Diego State University, San Diego, CA 92182-1221 (United States); Allen, Christopher [Orbital Sciences Corporation/NASA Ames Research Center, Moffett Field, CA 94035 (United States); Batalha, Natalie M. [Department of Physics and Astronomy, San Jose State University, San Jose, CA 95192 (United States); Buchhave, Lars A., E-mail: eford@astro.ufl.edu [Niels Bohr Institute, Copenhagen University, DK-2100 Copenhagen (Denmark); Collaboration: Kepler Science Team; and others
2012-05-10
We present a new method for confirming transiting planets based on the combination of transit timing variations (TTVs) and dynamical stability. Correlated TTVs provide evidence that the pair of bodies is in the same physical system. Orbital stability provides upper limits for the masses of the transiting companions that are in the planetary regime. This paper describes a non-parametric technique for quantifying the statistical significance of TTVs based on the correlation of two TTV data sets. We apply this method to an analysis of the TTVs of two stars with multiple transiting planet candidates identified by Kepler. We confirm four transiting planets in two multiple-planet systems based on their TTVs and the constraints imposed by dynamical stability. An additional three candidates in these same systems are not confirmed as planets, but are likely to be validated as real planets once further observations and analyses are possible. If all were confirmed, these systems would be near 4:6:9 and 2:4:6:9 period commensurabilities. Our results demonstrate that TTVs provide a powerful tool for confirming transiting planets, including low-mass planets and planets around faint stars for which Doppler follow-up is not practical with existing facilities. Continued Kepler observations will dramatically improve the constraints on the planet masses and orbits and provide sensitivity for detecting additional non-transiting planets. If Kepler observations were extended to eight years, then a similar analysis could likely confirm systems with multiple closely spaced, small transiting planets in or near the habitable zone of solar-type stars.
Directory of Open Access Journals (Sweden)
Navid Haghighat
2017-12-01
Full Text Available This paper focuses on evaluating airline service quality from the perspective of passengers' view. Until now a lot of researches has been performed in airline service quality evaluation in the world but a little research has been conducted in Iran, yet. In this study, a framework for measuring airline service quality in Iran is proposed. After reviewing airline service quality criteria, SSQAI model was selected because of its comprehensiveness in covering airline service quality dimensions. SSQAI questionnaire items were redesigned to adopt with Iranian airlines requirements and environmental circumstances in the Iran's economic and cultural context. This study includes fuzzy decision-making theory, considering the possible fuzzy subjective judgment of the evaluators during airline service quality evaluation. Fuzzy TOPSIS have been applied for ranking airlines service quality performances. Three major Iranian airlines which have the most passenger transfer volumes in domestic and foreign flights were chosen for evaluation in this research. Results demonstrated Mahan airline has got the best service quality performance rank in gaining passengers' satisfaction with delivery of high-quality services to its passengers, among the three major Iranian airlines. IranAir and Aseman airlines placed in the second and third rank, respectively, according to passenger's evaluation. Statistical analysis has been used in analyzing passenger responses. Due to the abnormality of data, Non-parametric tests were applied. To demonstrate airline ranks in every criterion separately, Friedman test was performed. Variance analysis and Tukey test were applied to study the influence of increasing in age and educational level of passengers on degree of their satisfaction from airline's service quality. Results showed that age has no significant relation to passenger satisfaction of airlines, however, increasing in educational level demonstrated a negative impact on
On Cooper's Nonparametric Test.
Schmeidler, James
1978-01-01
The basic assumption of Cooper's nonparametric test for trend (EJ 125 069) is questioned. It is contended that the proper assumption alters the distribution of the statistic and reduces its usefulness. (JKS)
Spectral analysis and filter theory in applied geophysics
Buttkus, Burkhard
2000-01-01
This book is intended to be an introduction to the fundamentals and methods of spectral analysis and filter theory and their appli cations in geophysics. The principles and theoretical basis of the various methods are described, their efficiency and effectiveness eval uated, and instructions provided for their practical application. Be sides the conventional methods, newer methods arediscussed, such as the spectral analysis ofrandom processes by fitting models to the ob served data, maximum-entropy spectral analysis and maximum-like lihood spectral analysis, the Wiener and Kalman filtering methods, homomorphic deconvolution, and adaptive methods for nonstation ary processes. Multidimensional spectral analysis and filtering, as well as multichannel filters, are given extensive treatment. The book provides a survey of the state-of-the-art of spectral analysis and fil ter theory. The importance and possibilities ofspectral analysis and filter theory in geophysics for data acquisition, processing an...
DEFF Research Database (Denmark)
Tan, Qihua; Zhao, J H; Iachine, I
2004-01-01
This report investigates the power issue in applying the non-parametric linkage analysis of affected sib-pairs (ASP) [Kruglyak and Lander, 1995: Am J Hum Genet 57:439-454] to localize genes that contribute to human longevity using long-lived sib-pairs. Data were simulated by introducing a recently...... developed statistical model for measuring marker-longevity associations [Yashin et al., 1999: Am J Hum Genet 65:1178-1193], enabling direct power comparison between linkage and association approaches. The non-parametric linkage (NPL) scores estimated in the region harboring the causal allele are evaluated...... in case of a dominant effect. Although the power issue may depend heavily on the true genetic nature in maintaining survival, our study suggests that results from small-scale sib-pair investigations should be referred with caution, given the complexity of human longevity....
Davies, Patrick Laurie
2014-01-01
Introduction IntroductionApproximate Models Notation Two Modes of Statistical AnalysisTowards One Mode of Analysis Approximation, Randomness, Chaos, Determinism ApproximationA Concept of Approximation Approximation Approximating a Data Set by a Model Approximation Regions Functionals and EquivarianceRegularization and Optimality Metrics and DiscrepanciesStrong and Weak Topologies On Being (almost) Honest Simulations and Tables Degree of Approximation and p-values ScalesStability of Analysis The Choice of En(α, P) Independence Procedures, Approximation and VaguenessDiscrete Models The Empirical Density Metrics and Discrepancies The Total Variation Metric The Kullback-Leibler and Chi-Squared Discrepancies The Po(λ) ModelThe b(k, p) and nb(k, p) Models The Flying Bomb Data The Student Study Times Data OutliersOutliers, Data Analysis and Models Breakdown Points and Equivariance Identifying Outliers and Breakdown Outliers in Multivariate Data Outliers in Linear Regression Outliers in Structured Data The Location...
Directory of Open Access Journals (Sweden)
Archer Kellie J
2008-02-01
Full Text Available Abstract Background With the popularity of DNA microarray technology, multiple groups of researchers have studied the gene expression of similar biological conditions. Different methods have been developed to integrate the results from various microarray studies, though most of them rely on distributional assumptions, such as the t-statistic based, mixed-effects model, or Bayesian model methods. However, often the sample size for each individual microarray experiment is small. Therefore, in this paper we present a non-parametric meta-analysis approach for combining data from independent microarray studies, and illustrate its application on two independent Affymetrix GeneChip studies that compared the gene expression of biopsies from kidney transplant recipients with chronic allograft nephropathy (CAN to those with normal functioning allograft. Results The simulation study comparing the non-parametric meta-analysis approach to a commonly used t-statistic based approach shows that the non-parametric approach has better sensitivity and specificity. For the application on the two CAN studies, we identified 309 distinct genes that expressed differently in CAN. By applying Fisher's exact test to identify enriched KEGG pathways among those genes called differentially expressed, we found 6 KEGG pathways to be over-represented among the identified genes. We used the expression measurements of the identified genes as predictors to predict the class labels for 6 additional biopsy samples, and the predicted results all conformed to their pathologist diagnosed class labels. Conclusion We present a new approach for combining data from multiple independent microarray studies. This approach is non-parametric and does not rely on any distributional assumptions. The rationale behind the approach is logically intuitive and can be easily understood by researchers not having advanced training in statistics. Some of the identified genes and pathways have been
Introduction to nonparametric statistics for the biological sciences using R
MacFarland, Thomas W
2016-01-01
This book contains a rich set of tools for nonparametric analyses, and the purpose of this supplemental text is to provide guidance to students and professional researchers on how R is used for nonparametric data analysis in the biological sciences: To introduce when nonparametric approaches to data analysis are appropriate To introduce the leading nonparametric tests commonly used in biostatistics and how R is used to generate appropriate statistics for each test To introduce common figures typically associated with nonparametric data analysis and how R is used to generate appropriate figures in support of each data set The book focuses on how R is used to distinguish between data that could be classified as nonparametric as opposed to data that could be classified as parametric, with both approaches to data classification covered extensively. Following an introductory lesson on nonparametric statistics for the biological sciences, the book is organized into eight self-contained lessons on various analyses a...
Lu, Tao
2016-01-01
The gene regulation network (GRN) evaluates the interactions between genes and look for models to describe the gene expression behavior. These models have many applications; for instance, by characterizing the gene expression mechanisms that cause certain disorders, it would be possible to target those genes to block the progress of the disease. Many biological processes are driven by nonlinear dynamic GRN. In this article, we propose a nonparametric differential equation (ODE) to model the nonlinear dynamic GRN. Specially, we address following questions simultaneously: (i) extract information from noisy time course gene expression data; (ii) model the nonlinear ODE through a nonparametric smoothing function; (iii) identify the important regulatory gene(s) through a group smoothly clipped absolute deviation (SCAD) approach; (iv) test the robustness of the model against possible shortening of experimental duration. We illustrate the usefulness of the model and associated statistical methods through a simulation and a real application examples.
Spectral analysis of noisy nonlinear maps
International Nuclear Information System (INIS)
Hirshman, S.P.; Whitson, J.C.
1982-01-01
A path integral equation formalism is developed to obtain the frequency spectrum of nonlinear mappings exhibiting chaotic behavior. The one-dimensional map, x/sub n+1/ = f(x/sub n/), where f is nonlinear and n is a discrete time variable, is analyzed in detail. This map is introduced as a paradigm of systems whose exact behavior is exceedingly complex, and therefore irretrievable, but which nevertheless possess smooth, well-behaved solutions in the presence of small sources of external noise. A Boltzmann integral equation is derived for the probability distribution function p(x,n). This equation is linear and is therefore amenable to spectral analysis. The nonlinear dynamics in f(x) appear as transition probability matrix elements, and the presence of noise appears simply as an overall multiplicative scattering amplitude. This formalism is used to investigate the band structure of the logistic equation and to analyze the effects of external noise on both the invariant measure and the frequency spectrum of x/sub n/ for several values of lambda epsilon [0,1
Nonparametric Transfer Function Models
Liu, Jun M.; Chen, Rong; Yao, Qiwei
2009-01-01
In this paper a class of nonparametric transfer function models is proposed to model nonlinear relationships between ‘input’ and ‘output’ time series. The transfer function is smooth with unknown functional forms, and the noise is assumed to be a stationary autoregressive-moving average (ARMA) process. The nonparametric transfer function is estimated jointly with the ARMA parameters. By modeling the correlation in the noise, the transfer function can be estimated more efficiently. The parsimonious ARMA structure improves the estimation efficiency in finite samples. The asymptotic properties of the estimators are investigated. The finite-sample properties are illustrated through simulations and one empirical example. PMID:20628584
Dickhaus, Thorsten
2018-01-01
This textbook provides a self-contained presentation of the main concepts and methods of nonparametric statistical testing, with a particular focus on the theoretical foundations of goodness-of-fit tests, rank tests, resampling tests, and projection tests. The substitution principle is employed as a unified approach to the nonparametric test problems discussed. In addition to mathematical theory, it also includes numerous examples and computer implementations. The book is intended for advanced undergraduate, graduate, and postdoc students as well as young researchers. Readers should be familiar with the basic concepts of mathematical statistics typically covered in introductory statistics courses.
Spectral signature verification using statistical analysis and text mining
DeCoster, Mallory E.; Firpi, Alexe H.; Jacobs, Samantha K.; Cone, Shelli R.; Tzeng, Nigel H.; Rodriguez, Benjamin M.
2016-05-01
In the spectral science community, numerous spectral signatures are stored in databases representative of many sample materials collected from a variety of spectrometers and spectroscopists. Due to the variety and variability of the spectra that comprise many spectral databases, it is necessary to establish a metric for validating the quality of spectral signatures. This has been an area of great discussion and debate in the spectral science community. This paper discusses a method that independently validates two different aspects of a spectral signature to arrive at a final qualitative assessment; the textual meta-data and numerical spectral data. Results associated with the spectral data stored in the Signature Database1 (SigDB) are proposed. The numerical data comprising a sample material's spectrum is validated based on statistical properties derived from an ideal population set. The quality of the test spectrum is ranked based on a spectral angle mapper (SAM) comparison to the mean spectrum derived from the population set. Additionally, the contextual data of a test spectrum is qualitatively analyzed using lexical analysis text mining. This technique analyzes to understand the syntax of the meta-data to provide local learning patterns and trends within the spectral data, indicative of the test spectrum's quality. Text mining applications have successfully been implemented for security2 (text encryption/decryption), biomedical3 , and marketing4 applications. The text mining lexical analysis algorithm is trained on the meta-data patterns of a subset of high and low quality spectra, in order to have a model to apply to the entire SigDB data set. The statistical and textual methods combine to assess the quality of a test spectrum existing in a database without the need of an expert user. This method has been compared to other validation methods accepted by the spectral science community, and has provided promising results when a baseline spectral signature is
Nonparametric Mixture of Regression Models.
Huang, Mian; Li, Runze; Wang, Shaoli
2013-07-01
Motivated by an analysis of US house price index data, we propose nonparametric finite mixture of regression models. We study the identifiability issue of the proposed models, and develop an estimation procedure by employing kernel regression. We further systematically study the sampling properties of the proposed estimators, and establish their asymptotic normality. A modified EM algorithm is proposed to carry out the estimation procedure. We show that our algorithm preserves the ascent property of the EM algorithm in an asymptotic sense. Monte Carlo simulations are conducted to examine the finite sample performance of the proposed estimation procedure. An empirical analysis of the US house price index data is illustrated for the proposed methodology.
Pardo-Igúzquiza, Eulogio; Rodríguez-Tovar, Francisco J.
2012-12-01
Many spectral analysis techniques have been designed assuming sequences taken with a constant sampling interval. However, there are empirical time series in the geosciences (sediment cores, fossil abundance data, isotope analysis, …) that do not follow regular sampling because of missing data, gapped data, random sampling or incomplete sequences, among other reasons. In general, interpolating an uneven series in order to obtain a succession with a constant sampling interval alters the spectral content of the series. In such cases it is preferable to follow an approach that works with the uneven data directly, avoiding the need for an explicit interpolation step. The Lomb-Scargle periodogram is a popular choice in such circumstances, as there are programs available in the public domain for its computation. One new computer program for spectral analysis improves the standard Lomb-Scargle periodogram approach in two ways: (1) It explicitly adjusts the statistical significance to any bias introduced by variance reduction smoothing, and (2) it uses a permutation test to evaluate confidence levels, which is better suited than parametric methods when neighbouring frequencies are highly correlated. Another novel program for cross-spectral analysis offers the advantage of estimating the Lomb-Scargle cross-periodogram of two uneven time series defined on the same interval, and it evaluates the confidence levels of the estimated cross-spectra by a non-parametric computer intensive permutation test. Thus, the cross-spectrum, the squared coherence spectrum, the phase spectrum, and the Monte Carlo statistical significance of the cross-spectrum and the squared-coherence spectrum can be obtained. Both of the programs are written in ANSI Fortran 77, in view of its simplicity and compatibility. The program code is of public domain, provided on the website of the journal (http://www.iamg.org/index.php/publisher/articleview/frmArticleID/112/). Different examples (with simulated and
Energy Technology Data Exchange (ETDEWEB)
Peterson, James T.
1999-12-01
Natural resource professionals are increasingly required to develop rigorous statistical models that relate environmental data to categorical responses data. Recent advances in the statistical and computing sciences have led to the development of sophisticated methods for parametric and nonparametric analysis of data with categorical responses. The statistical software package CATDAT was designed to make some of these relatively new and powerful techniques available to scientists. The CATDAT statistical package includes 4 analytical techniques: generalized logit modeling; binary classification tree; extended K-nearest neighbor classification; and modular neural network.
Spectral Analysis of Large Particle Systems
DEFF Research Database (Denmark)
Dahlbæk, Jonas
2017-01-01
that Schur complements, Feshbach maps and Grushin problems are three sides of the same coin, it seems to be a new observation that the smooth Feshbach method can also be formulated as a Grushin problem. Based on this, an abstract account of the spectral renormalization group is given....
Lee, L.; Helsel, D.
2007-01-01
Analysis of low concentrations of trace contaminants in environmental media often results in left-censored data that are below some limit of analytical precision. Interpretation of values becomes complicated when there are multiple detection limits in the data-perhaps as a result of changing analytical precision over time. Parametric and semi-parametric methods, such as maximum likelihood estimation and robust regression on order statistics, can be employed to model distributions of multiply censored data and provide estimates of summary statistics. However, these methods are based on assumptions about the underlying distribution of data. Nonparametric methods provide an alternative that does not require such assumptions. A standard nonparametric method for estimating summary statistics of multiply-censored data is the Kaplan-Meier (K-M) method. This method has seen widespread usage in the medical sciences within a general framework termed "survival analysis" where it is employed with right-censored time-to-failure data. However, K-M methods are equally valid for the left-censored data common in the geosciences. Our S-language software provides an analytical framework based on K-M methods that is tailored to the needs of the earth and environmental sciences community. This includes routines for the generation of empirical cumulative distribution functions, prediction or exceedance probabilities, and related confidence limits computation. Additionally, our software contains K-M-based routines for nonparametric hypothesis testing among an unlimited number of grouping variables. A primary characteristic of K-M methods is that they do not perform extrapolation and interpolation. Thus, these routines cannot be used to model statistics beyond the observed data range or when linear interpolation is desired. For such applications, the aforementioned parametric and semi-parametric methods must be used.
Spectral Analysis of Rich Network Topology in Social Networks
Wu, Leting
2013-01-01
Social networks have received much attention these days. Researchers have developed different methods to study the structure and characteristics of the network topology. Our focus is on spectral analysis of the adjacency matrix of the underlying network. Recent work showed good properties in the adjacency spectral space but there are few…
Nonlinear physical systems spectral analysis, stability and bifurcations
Kirillov, Oleg N
2013-01-01
Bringing together 18 chapters written by leading experts in dynamical systems, operator theory, partial differential equations, and solid and fluid mechanics, this book presents state-of-the-art approaches to a wide spectrum of new and challenging stability problems.Nonlinear Physical Systems: Spectral Analysis, Stability and Bifurcations focuses on problems of spectral analysis, stability and bifurcations arising in the nonlinear partial differential equations of modern physics. Bifurcations and stability of solitary waves, geometrical optics stability analysis in hydro- and magnetohydrodynam
SpectralNET – an application for spectral graph analysis and visualization
Directory of Open Access Journals (Sweden)
Schreiber Stuart L
2005-10-01
Full Text Available Abstract Background Graph theory provides a computational framework for modeling a variety of datasets including those emerging from genomics, proteomics, and chemical genetics. Networks of genes, proteins, small molecules, or other objects of study can be represented as graphs of nodes (vertices and interactions (edges that can carry different weights. SpectralNET is a flexible application for analyzing and visualizing these biological and chemical networks. Results Available both as a standalone .NET executable and as an ASP.NET web application, SpectralNET was designed specifically with the analysis of graph-theoretic metrics in mind, a computational task not easily accessible using currently available applications. Users can choose either to upload a network for analysis using a variety of input formats, or to have SpectralNET generate an idealized random network for comparison to a real-world dataset. Whichever graph-generation method is used, SpectralNET displays detailed information about each connected component of the graph, including graphs of degree distribution, clustering coefficient by degree, and average distance by degree. In addition, extensive information about the selected vertex is shown, including degree, clustering coefficient, various distance metrics, and the corresponding components of the adjacency, Laplacian, and normalized Laplacian eigenvectors. SpectralNET also displays several graph visualizations, including a linear dimensionality reduction for uploaded datasets (Principal Components Analysis and a non-linear dimensionality reduction that provides an elegant view of global graph structure (Laplacian eigenvectors. Conclusion SpectralNET provides an easily accessible means of analyzing graph-theoretic metrics for data modeling and dimensionality reduction. SpectralNET is publicly available as both a .NET application and an ASP.NET web application from http://chembank.broad.harvard.edu/resources/. Source code is
Bayesian nonparametric hierarchical modeling.
Dunson, David B
2009-04-01
In biomedical research, hierarchical models are very widely used to accommodate dependence in multivariate and longitudinal data and for borrowing of information across data from different sources. A primary concern in hierarchical modeling is sensitivity to parametric assumptions, such as linearity and normality of the random effects. Parametric assumptions on latent variable distributions can be challenging to check and are typically unwarranted, given available prior knowledge. This article reviews some recent developments in Bayesian nonparametric methods motivated by complex, multivariate and functional data collected in biomedical studies. The author provides a brief review of flexible parametric approaches relying on finite mixtures and latent class modeling. Dirichlet process mixture models are motivated by the need to generalize these approaches to avoid assuming a fixed finite number of classes. Focusing on an epidemiology application, the author illustrates the practical utility and potential of nonparametric Bayes methods.
Quantal Response: Nonparametric Modeling
2017-01-01
capture the behavior of observed phenomena. Higher-order polynomial and finite-dimensional spline basis models allow for more complicated responses as the...flexibility as these are nonparametric (not constrained to any particular functional form). These should be useful in identifying nonstandard behavior via... deviance ∆ = −2 log(Lreduced/Lfull) is defined in terms of the likelihood function L. For normal error, Lfull = 1, and based on Eq. A-2, we have log
Spectral Analysis of Vector Magnetic Field Profiles
Parker, Robert L.; OBrien, Michael S.
1997-01-01
We investigate the power spectra and cross spectra derived from the three components of the vector magnetic field measured on a straight horizontal path above a statistically stationary source. All of these spectra, which can be estimated from the recorded time series, are related to a single two-dimensional power spectral density via integrals that run in the across-track direction in the wavenumber domain. Thus the measured spectra must obey a number of strong constraints: for example, the sum of the two power spectral densities of the two horizontal field components equals the power spectral density of the vertical component at every wavenumber and the phase spectrum between the vertical and along-track components is always pi/2. These constraints provide powerful checks on the quality of the measured data; if they are violated, measurement or environmental noise should be suspected. The noise due to errors of orientation has a clear characteristic; both the power and phase spectra of the components differ from those of crustal signals, which makes orientation noise easy to detect and to quantify. The spectra of the crustal signals can be inverted to obtain information about the cross-track structure of the field. We illustrate these ideas using a high-altitude Project Magnet profile flown in the southeastern Pacific Ocean.
Evaluation of Fourier integral. Spectral analysis of seismic events
International Nuclear Information System (INIS)
Chitaru, Cristian; Enescu, Dumitru
2003-01-01
Spectral analysis of seismic events represents a method for great earthquake prediction. The seismic signal is not a sinusoidal signal; for this, it is necessary to find a method for best approximation of real signal with a sinusoidal signal. The 'Quanterra' broadband station allows the data access in numerical and/or graphical forms. With the numerical form we can easily make a computer program (MSOFFICE-EXCEL) for spectral analysis. (authors)
Alpha spectral analysis via artificial neural networks
International Nuclear Information System (INIS)
Kangas, L.J.; Hashem, S.; Keller, P.E.; Kouzes, R.T.; Troyer, G.L.
1994-10-01
An artificial neural network system that assigns quality factors to alpha particle energy spectra is discussed. The alpha energy spectra are used to detect plutonium contamination in the work environment. The quality factors represent the levels of spectral degradation caused by miscalibration and foreign matter affecting the instruments. A set of spectra was labeled with a quality factor by an expert and used in training the artificial neural network expert system. The investigation shows that the expert knowledge of alpha spectra quality factors can be transferred to an ANN system
Spectral response analysis of PVDF capacitive sensors
Reyes-Ramírez, B.; García-Segundo, C.; García-Valenzuela, A.
2013-06-01
We investigate the spectral response to ultrasound waves in water of low-noise capacitive sensors based on PVDF polymer piezoelectric films. First, we analyze theoretically the mechanical-to-electrical transduction as a function of the frequency of ultrasonic signals and derive an analytic expression of the sensor's transfer function. Then we present experimental results of the frequency response of a home-made PDVF in water to test signals from 1 to 20 MHz induced by a commercial hydrophone powered by a signal generator and compare with our theoretical model.
Emissivity compensated spectral pyrometry—algorithm and sensitivity analysis
International Nuclear Information System (INIS)
Hagqvist, Petter; Sikström, Fredrik; Christiansson, Anna-Karin; Lennartson, Bengt
2014-01-01
In order to solve the problem of non-contact temperature measurements on an object with varying emissivity, a new method is herein described and evaluated. The method uses spectral radiance measurements and converts them to temperature readings. It proves to be resilient towards changes in spectral emissivity and tolerates noisy spectral measurements. It is based on an assumption of smooth changes in emissivity and uses historical values of spectral emissivity and temperature for estimating current spectral emissivity. The algorithm, its constituent steps and accompanying parameters are described and discussed. A thorough sensitivity analysis of the method is carried out through simulations. No rigorous instrument calibration is needed for the presented method and it is therefore industrially tractable. (paper)
A spectral analysis of ablating meteors
Bloxam, K.; Campbell-Brown, M.
2017-09-01
Meteor ablation features in the spectral lines occurring at 394, 436, 520, and 589 nm were observed using a four-camera spectral system between September and December 2015. In conjunction with this multi-camera system the Canadian Automated Meteor Observatory was used to observe the orbital parameters and fragmentation of these meteors. In total, 95 light curves with complete data in the 520 and 589 nm filters were analyzed; some also had partial or complete data in the 394 nm filter, but no usable data was collected with the 436 nm filter. Of the 95 events, 70 exhibited some degree of differential ablation, and in all except 3 of these 70 events the 589 nm filter started or ended sooner compared with the 520 nm filter, indicating early ablation at the 589 nm wavelength. In the majority of cases the meteor showed evidence of fragmentation regardless of the type of ablation (differential or uniform). A surprising result was the lack of correlation found concerning the KB parameter, linked to meteoroid strength, and differential ablation. In addition, 22 shower-associated meteors were observed; Geminids showed mainly slight differential ablation, while Taurids were more likely to ablate uniformly.
Afshinpour, Babak; Hossein-Zadeh, Gholam-Ali; Soltanian-Zadeh, Hamid
2008-06-30
Unknown low frequency fluctuations called "trend" are observed in noisy time-series measured for different applications. In some disciplines, they carry primary information while in other fields such as functional magnetic resonance imaging (fMRI) they carry nuisance effects. In all cases, however, it is necessary to estimate them accurately. In this paper, a method for estimating trend in the presence of fractal noise is proposed and applied to fMRI time-series. To this end, a partly linear model (PLM) is fitted to each time-series. The parametric and nonparametric parts of PLM are considered as contributions of hemodynamic response and trend, respectively. Using the whitening property of wavelet transform, the unknown components of the model are estimated in the wavelet domain. The results of the proposed method are compared to those of other parametric trend-removal approaches such as spline and polynomial models. It is shown that the proposed method improves activation detection and decreases variance of the estimated parameters relative to the other methods.
Directory of Open Access Journals (Sweden)
Lars Ängquist
2008-01-01
Full Text Available In this article we try to discuss nonparametric linkage (NPL score functions within a broad and quite general framework. The main focus of the paper is the structure, derivation principles and interpretations of the score function entity itself. We define and discuss several families of one-locus score function definitions, i.e. the implicit, explicit and optimal ones. Some generalizations and comments to the two-locus, unconditional and conditional, cases are included as well. Although this article mainly aims at serving as an overview, where the concept of score functions are put into a covering context, we generalize the noncentrality parameter (NCP optimal score functions in Ängquist et al. (2007 to facilitate—through weighting—for incorporation of several plausible distinct genetic models. Since the genetic model itself most oftenly is to some extent unknown this facilitates weaker prior assumptions with respect to plausible true disease models without loosing the property of NCP-optimality. Moreover, we discuss general assumptions and properties of score functions in the above sense. For instance, the concept of identical by descent (IBD sharing structures and score function equivalence are discussed in some detail.
Antepartum Fetal Monitoring and Spectral Analysis of Preterm Birth Risk
Păsăricără, Alexandru; Nemescu, Dragoş; Arotăriţei, Dragoş; Rotariu, Cristian
2017-11-01
The monitoring and analysis of antepartum fetal and maternal recordings is a research area of notable interest due to the relatively high value of preterm birth. The interest stems from the improvement of devices used for monitoring. The current paper presents the spectral analysis of antepartum heart rate recordings conducted during a study in Romania at the Cuza Voda Obstetrics and Gynecology Clinical Hospital from Iasi between 2010 and 2014. The study focuses on normal and preterm birth risk subjects in order to determine differences between these two types or recordings in terms of spectral analysis.
International Nuclear Information System (INIS)
Wei, Chu; Löschel, Andreas; Liu, Bing
2015-01-01
In the context of soaring demand for electricity, mitigating and controlling greenhouse gas emissions is a great challenge for China's power sector. Increasing attention has been placed on the evaluation of energy efficiency and CO 2 abatement potential in the power sector. However, studies at the micro-level are relatively rare due to serious data limitations. This study uses the 2004 and 2008 Census data of Zhejiang province to construct a non-parametric frontier in order to assess the abatement space of energy and associated CO 2 emission from China's coal-fired power enterprises. A Weighted Russell Directional Distance Function (WRDDF) is applied to construct an energy-saving potential index and a CO 2 emission-abatement potential index. Both indicators depict the inefficiency level in terms of energy utilization and CO 2 emissions of electric power plants. Our results show a substantial variation of energy-saving potential and CO 2 abatement potential among enterprises. We find that large power enterprises are less efficient in 2004, but become more efficient than smaller enterprises in 2008. State-owned enterprises (SOE) are not significantly different in 2008 from 2004, but perform better than their non-SOE counterparts in 2008. This change in performance for large enterprises and SOE might be driven by the “top-1000 Enterprise Energy Conservation Action” that was implemented in 2006. - Highlights: • Energy-saving potential and CO 2 abatement-potential for Chinese power enterprise are evaluated. • The potential to curb energy and emission shows great variation and dynamic changes. • Large enterprise is less efficient than small enterprise in 2004, but more efficient in 2008. • The state-owned enterprise performs better than non-state-owned enterprise in 2008
Directory of Open Access Journals (Sweden)
Fernandez Ana
2010-05-01
Full Text Available Abstract Background Previous studies have analyzed the psychometric properties of the World Health Organization Disability Assessment Schedule II (WHO-DAS II using classical omnibus measures of scale quality. These analyses are sample dependent and do not model item responses as a function of the underlying trait level. The main objective of this study was to examine the effectiveness of the WHO-DAS II items and their options in discriminating between changes in the underlying disability level by means of item response analyses. We also explored differential item functioning (DIF in men and women. Methods The participants were 3615 adult general practice patients from 17 regions of Spain, with a first diagnosed major depressive episode. The 12-item WHO-DAS II was administered by the general practitioners during the consultation. We used a non-parametric item response method (Kernel-Smoothing implemented with the TestGraf software to examine the effectiveness of each item (item characteristic curves and their options (option characteristic curves in discriminating between changes in the underliying disability level. We examined composite DIF to know whether women had a higher probability than men of endorsing each item. Results Item response analyses indicated that the twelve items forming the WHO-DAS II perform very well. All items were determined to provide good discrimination across varying standardized levels of the trait. The items also had option characteristic curves that showed good discrimination, given that each increasing option became more likely than the previous as a function of increasing trait level. No gender-related DIF was found on any of the items. Conclusions All WHO-DAS II items were very good at assessing overall disability. Our results supported the appropriateness of the weights assigned to response option categories and showed an absence of gender differences in item functioning.
Hydrogen quasienergies from spectral analysis of wavepackets
International Nuclear Information System (INIS)
Dondera, M.; Muller, H.G.; Gavrila, M.
2002-01-01
Quasienergies (qe) are calculated traditionally by solving the time-independent Floquet system of differential equations. A number of such calculations have been carried out successfully in the past for atomic hydrogen, albeit not at the frequencies of operation of current super intense lasers. We now present a method for calculating qe based on the evolution of a wave packet of the Schroedinger equation with a time-periodic Hamiltonian, that is an extension of the well known 'spectral method' for obtaining (real) eigenenergies of a time-independent Hamiltonian. The present method is based on propagating a wave packet Ψ(t) with an appropriately chosen initial condition Ψ(0) in a periodic field of constant amplitude, and then Fourier analyzing the autocorrelation function A(t) = . The Fourier transform of the autocorrelation function displays a set of lines, whose location and widths are related to the complex qe of the Floquet states present in the expansion of the wave packet. When these lines are non-overlapping, standard fitting techniques allow the extraction of the real and imaginary parts of the qe. For the case of overlapping lines, we apply the more elaborate technique of 'filter diagonalization'. Our method was tested by comparison with qe obtained from other sources, e.g., the solution of the system of differential equations. We apply the method to 3D hydrogen in a laser field of linear polarization, at the frequently used photon energy ω = 1.55 eV (wavelength 800 nm). We consider Floquet states belonging to several symmetry manifolds m. The field amplitude is varied from zero to several a.u. We thus obtain a 'Floquet map' for the real part of the qe of the lower states, and separately, the imaginary parts (widths) of the qe. The Floquet map displays interesting pseudo-crossings. We interpret the results in terms of avoided crossings of trajectories of the qe in the complex energy plane, and discuss their physical significance. (authors)
SPAM- SPECTRAL ANALYSIS MANAGER (DEC VAX/VMS VERSION)
Solomon, J. E.
1994-01-01
The Spectral Analysis Manager (SPAM) was developed to allow easy qualitative analysis of multi-dimensional imaging spectrometer data. Imaging spectrometers provide sufficient spectral sampling to define unique spectral signatures on a per pixel basis. Thus direct material identification becomes possible for geologic studies. SPAM provides a variety of capabilities for carrying out interactive analysis of the massive and complex datasets associated with multispectral remote sensing observations. In addition to normal image processing functions, SPAM provides multiple levels of on-line help, a flexible command interpretation, graceful error recovery, and a program structure which can be implemented in a variety of environments. SPAM was designed to be visually oriented and user friendly with the liberal employment of graphics for rapid and efficient exploratory analysis of imaging spectrometry data. SPAM provides functions to enable arithmetic manipulations of the data, such as normalization, linear mixing, band ratio discrimination, and low-pass filtering. SPAM can be used to examine the spectra of an individual pixel or the average spectra over a number of pixels. SPAM also supports image segmentation, fast spectral signature matching, spectral library usage, mixture analysis, and feature extraction. High speed spectral signature matching is performed by using a binary spectral encoding algorithm to separate and identify mineral components present in the scene. The same binary encoding allows automatic spectral clustering. Spectral data may be entered from a digitizing tablet, stored in a user library, compared to the master library containing mineral standards, and then displayed as a timesequence spectral movie. The output plots, histograms, and stretched histograms produced by SPAM can be sent to a lineprinter, stored as separate RGB disk files, or sent to a Quick Color Recorder. SPAM is written in C for interactive execution and is available for two different
Spectacle and SpecViz: New Spectral Analysis and Visualization Tools
Earl, Nicholas; Peeples, Molly; JDADF Developers
2018-01-01
A new era of spectroscopic exploration of our universe is being ushered in with advances in instrumentation and next-generation space telescopes. The advent of new spectroscopic instruments has highlighted a pressing need for tools scientists can use to analyze and explore these new data. We have developed Spectacle, a software package for analyzing both synthetic spectra from hydrodynamic simulations as well as real COS data with an aim of characterizing the behavior of the circumgalactic medium. It allows easy reduction of spectral data and analytic line generation capabilities. Currently, the package is focused on automatic determination of absorption regions and line identification with custom line list support, simultaneous line fitting using Voigt profiles via least-squares or MCMC methods, and multi-component modeling of blended features. Non-parametric measurements, such as equivalent widths, delta v90, and full-width half-max are available. Spectacle also provides the ability to compose compound models used to generate synthetic spectra allowing the user to define various LSF kernels, uncertainties, and to specify sampling.We also present updates to the visualization tool SpecViz, developed in conjunction with the JWST data analysis tools development team, to aid in the exploration of spectral data. SpecViz is an open source, Python-based spectral 1-D interactive visualization and analysis application built around high-performance interactive plotting. It supports handling general and instrument-specific data and includes advanced tool-sets for filtering and detrending one-dimensional data, along with the ability to isolate absorption regions using slicing and manipulate spectral features via spectral arithmetic. Multi-component modeling is also possible using a flexible model fitting tool-set that supports custom models to be used with various fitting routines. It also features robust user extensions such as custom data loaders and support for user
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...
Spectral analysis of the structure of ultradispersed diamonds
Uglov, V. V.; Shimanski, V. I.; Rusalsky, D. P.; Samtsov, M. P.
2008-07-01
The structure of ultradispersed diamonds (UDD) is studied by spectral methods. The presence of diamond crystal phase in the UDD is found based on x-ray analysis and Raman spectra. The Raman spectra also show sp2-and sp3-hybridized carbon. Analysis of IR absorption spectra suggests that the composition of functional groups present in the particles changes during the treatment.
Analysis of spectral methods for the homogeneous Boltzmann equation
Filbet, Francis
2011-04-01
The development of accurate and fast algorithms for the Boltzmann collision integral and their analysis represent a challenging problem in scientific computing and numerical analysis. Recently, several works were devoted to the derivation of spectrally accurate schemes for the Boltzmann equation, but very few of them were concerned with the stability analysis of the method. In particular there was no result of stability except when the method was modified in order to enforce the positivity preservation, which destroys the spectral accuracy. In this paper we propose a new method to study the stability of homogeneous Boltzmann equations perturbed by smoothed balanced operators which do not preserve positivity of the distribution. This method takes advantage of the "spreading" property of the collision, together with estimates on regularity and entropy production. As an application we prove stability and convergence of spectral methods for the Boltzmann equation, when the discretization parameter is large enough (with explicit bound). © 2010 American Mathematical Society.
Analysis of spectral methods for the homogeneous Boltzmann equation
Filbet, Francis; Mouhot, Clé ment
2011-01-01
The development of accurate and fast algorithms for the Boltzmann collision integral and their analysis represent a challenging problem in scientific computing and numerical analysis. Recently, several works were devoted to the derivation of spectrally accurate schemes for the Boltzmann equation, but very few of them were concerned with the stability analysis of the method. In particular there was no result of stability except when the method was modified in order to enforce the positivity preservation, which destroys the spectral accuracy. In this paper we propose a new method to study the stability of homogeneous Boltzmann equations perturbed by smoothed balanced operators which do not preserve positivity of the distribution. This method takes advantage of the "spreading" property of the collision, together with estimates on regularity and entropy production. As an application we prove stability and convergence of spectral methods for the Boltzmann equation, when the discretization parameter is large enough (with explicit bound). © 2010 American Mathematical Society.
Nonparametric combinatorial sequence models.
Wauthier, Fabian L; Jordan, Michael I; Jojic, Nebojsa
2011-11-01
This work considers biological sequences that exhibit combinatorial structures in their composition: groups of positions of the aligned sequences are "linked" and covary as one unit across sequences. If multiple such groups exist, complex interactions can emerge between them. Sequences of this kind arise frequently in biology but methodologies for analyzing them are still being developed. This article presents a nonparametric prior on sequences which allows combinatorial structures to emerge and which induces a posterior distribution over factorized sequence representations. We carry out experiments on three biological sequence families which indicate that combinatorial structures are indeed present and that combinatorial sequence models can more succinctly describe them than simpler mixture models. We conclude with an application to MHC binding prediction which highlights the utility of the posterior distribution over sequence representations induced by the prior. By integrating out the posterior, our method compares favorably to leading binding predictors.
A Structural Labor Supply Model with Nonparametric Preferences
van Soest, A.H.O.; Das, J.W.M.; Gong, X.
2000-01-01
Nonparametric techniques are usually seen as a statistic device for data description and exploration, and not as a tool for estimating models with a richer economic structure, which are often required for policy analysis.This paper presents an example where nonparametric flexibility can be attained
Spectral Analysis of Moderately Charged Rare-Gas Atoms
Directory of Open Access Journals (Sweden)
Jorge Reyna Almandos
2017-03-01
Full Text Available This article presents a review concerning the spectral analysis of several ions of neon, argon, krypton and xenon, with impact on laser studies and astrophysics that were mainly carried out in our collaborative groups between Argentina and Brazil during many years. The spectra were recorded from the vacuum ultraviolet to infrared regions using pulsed discharges. Semi-empirical approaches with relativistic Hartree–Fock and Dirac-Fock calculations were also included in these investigations. The spectral analysis produced new classified lines and energy levels. Lifetimes and oscillator strengths were also calculated.
Spectral theory and nonlinear analysis with applications to spatial ecology
Cano-Casanova, S; Mora-Corral , C
2005-01-01
This volume details some of the latest advances in spectral theory and nonlinear analysis through various cutting-edge theories on algebraic multiplicities, global bifurcation theory, non-linear Schrödinger equations, non-linear boundary value problems, large solutions, metasolutions, dynamical systems, and applications to spatial ecology. The main scope of the book is bringing together a series of topics that have evolved separately during the last decades around the common denominator of spectral theory and nonlinear analysis - from the most abstract developments up to the most concrete applications to population dynamics and socio-biology - in an effort to fill the existing gaps between these fields.
Nonparametric Bayesian inference in biostatistics
Müller, Peter
2015-01-01
As chapters in this book demonstrate, BNP has important uses in clinical sciences and inference for issues like unknown partitions in genomics. Nonparametric Bayesian approaches (BNP) play an ever expanding role in biostatistical inference from use in proteomics to clinical trials. Many research problems involve an abundance of data and require flexible and complex probability models beyond the traditional parametric approaches. As this book's expert contributors show, BNP approaches can be the answer. Survival Analysis, in particular survival regression, has traditionally used BNP, but BNP's potential is now very broad. This applies to important tasks like arrangement of patients into clinically meaningful subpopulations and segmenting the genome into functionally distinct regions. This book is designed to both review and introduce application areas for BNP. While existing books provide theoretical foundations, this book connects theory to practice through engaging examples and research questions. Chapters c...
Nonparametric tests for censored data
Bagdonavicus, Vilijandas; Nikulin, Mikhail
2013-01-01
This book concerns testing hypotheses in non-parametric models. Generalizations of many non-parametric tests to the case of censored and truncated data are considered. Most of the test results are proved and real applications are illustrated using examples. Theories and exercises are provided. The incorrect use of many tests applying most statistical software is highlighted and discussed.
HYPERSPECTRAL HYPERION IMAGERY ANALYSIS AND ITS APPLICATION USING SPECTRAL ANALYSIS
Directory of Open Access Journals (Sweden)
W. Pervez
2015-03-01
Full Text Available Rapid advancement in remote sensing open new avenues to explore the hyperspectral Hyperion imagery pre-processing techniques, analysis and application for land use mapping. The hyperspectral data consists of 242 bands out of which 196 calibrated/useful bands are available for hyperspectral applications. Atmospheric correction applied to the hyperspectral calibrated bands make the data more useful for its further processing/ application. Principal component (PC analysis applied to the hyperspectral calibrated bands reduced the dimensionality of the data and it is found that 99% of the data is held in first 10 PCs. Feature extraction is one of the important application by using vegetation delineation and normalized difference vegetation index. The machine learning classifiers uses the technique to identify the pixels having significant difference in the spectral signature which is very useful for classification of an image. Supervised machine learning classifier technique has been used for classification of hyperspectral image which resulted in overall efficiency of 86.6703 and Kappa co-efficient of 0.7998.
Automated spectral and timing analysis of AGNs
Munz, F.; Karas, V.; Guainazzi, M.
2006-12-01
% We have developed an autonomous script that helps the user to automate the XMM-Newton data analysis for the purposes of extensive statistical investigations. We test this approach by examining X-ray spectra of bright AGNs pre-selected from the public database. The event lists extracted in this process were studied further by constructing their energy-resolved Fourier power-spectrum density. This analysis combines energy distributions, light-curves, and their power-spectra and it proves useful to assess the variability patterns present is the data. As another example, an automated search was based on the XSPEC package to reveal the emission features in 2-8 keV range.
[Infrared spectral analysis for calcined borax].
Zhao, Cui; Ren, Li-Li; Wang, Dong; Zhou, Ping; Zhang, Qian; Wang, Bo-Tao
2011-08-01
To valuate the quality of calcined borax which is sold in the market, 18 samples of calcined borax were studied using the Fourier transform infrared, and samples with different water content were selected and analyzed. Then, the results of analysis were used to evaluate the quality of calcined borax. Results show that the infrared spectra of calcined borax include OH vibration, BO3(-3) vibration and BO4(5-) vibration absorption bands. The position and width of OH vibration absorption band depend on the level of water content, and the more the water content, the wider the absorption band. The number of BO3(3-) vibration and BO4(5-) vibration bands also depend on the level of water content, and the more the water content, and the stronger the hydrogen bond and the lower the symmetry of B atoms, the more the number of infrared absorption peaks. It was concluded that because the quality of calcined borax has direct correlation with water content, the infrared spectroscopy is an express and objective approach to quality analysis and evaluation of calcined borax.
Nonparametric statistics with applications to science and engineering
Kvam, Paul H
2007-01-01
A thorough and definitive book that fully addresses traditional and modern-day topics of nonparametric statistics This book presents a practical approach to nonparametric statistical analysis and provides comprehensive coverage of both established and newly developed methods. With the use of MATLAB, the authors present information on theorems and rank tests in an applied fashion, with an emphasis on modern methods in regression and curve fitting, bootstrap confidence intervals, splines, wavelets, empirical likelihood, and goodness-of-fit testing. Nonparametric Statistics with Applications to Science and Engineering begins with succinct coverage of basic results for order statistics, methods of categorical data analysis, nonparametric regression, and curve fitting methods. The authors then focus on nonparametric procedures that are becoming more relevant to engineering researchers and practitioners. The important fundamental materials needed to effectively learn and apply the discussed methods are also provide...
PCLOOK: an interactive code for spectral analysis
International Nuclear Information System (INIS)
Macchiavelli, A.O.; Tomasi, D.
1993-01-01
The present work describes an interactive programme for the analysis of spectra developed to run in a PC platform. PCLOOK has a graphic interface that allows the user to get access to different functions using the mouse or directly typing commands. In this way one can switch to a suitable required environment to manage the histograms reassembling in this way a spectrum calculator.The PCLOOK programme was mainly developed to use in nuclear physics applications, but it is also possible to modify it with relative little effort to adapt it to other applications. It was written in Microsoft's BASIC 7.1 installed in a 33MHz 486 Everex PC. For a proper operation an ordinary VGA display and mouse are needed. The memory requirements depend on the size and number of the user defined spectra; for instance, for twenty 2048 channels spectra the available memory space must be 320 KBytes. (author). 5 figs
Nonparametric e-Mixture Estimation.
Takano, Ken; Hino, Hideitsu; Akaho, Shotaro; Murata, Noboru
2016-12-01
This study considers the common situation in data analysis when there are few observations of the distribution of interest or the target distribution, while abundant observations are available from auxiliary distributions. In this situation, it is natural to compensate for the lack of data from the target distribution by using data sets from these auxiliary distributions-in other words, approximating the target distribution in a subspace spanned by a set of auxiliary distributions. Mixture modeling is one of the simplest ways to integrate information from the target and auxiliary distributions in order to express the target distribution as accurately as possible. There are two typical mixtures in the context of information geometry: the [Formula: see text]- and [Formula: see text]-mixtures. The [Formula: see text]-mixture is applied in a variety of research fields because of the presence of the well-known expectation-maximazation algorithm for parameter estimation, whereas the [Formula: see text]-mixture is rarely used because of its difficulty of estimation, particularly for nonparametric models. The [Formula: see text]-mixture, however, is a well-tempered distribution that satisfies the principle of maximum entropy. To model a target distribution with scarce observations accurately, this letter proposes a novel framework for a nonparametric modeling of the [Formula: see text]-mixture and a geometrically inspired estimation algorithm. As numerical examples of the proposed framework, a transfer learning setup is considered. The experimental results show that this framework works well for three types of synthetic data sets, as well as an EEG real-world data set.
PIXE-quantified AXSIA: Elemental mapping by multivariate spectral analysis
International Nuclear Information System (INIS)
Doyle, B.L.; Provencio, P.P.; Kotula, P.G.; Antolak, A.J.; Ryan, C.G.; Campbell, J.L.; Barrett, K.
2006-01-01
Automated, nonbiased, multivariate statistical analysis techniques are useful for converting very large amounts of data into a smaller, more manageable number of chemical components (spectra and images) that are needed to describe the measurement. We report the first use of the multivariate spectral analysis program AXSIA (Automated eXpert Spectral Image Analysis) developed at Sandia National Laboratories to quantitatively analyze micro-PIXE data maps. AXSIA implements a multivariate curve resolution technique that reduces the spectral image data sets into a limited number of physically realizable and easily interpretable components (including both spectra and images). We show that the principal component spectra can be further analyzed using conventional PIXE programs to convert the weighting images into quantitative concentration maps. A common elemental data set has been analyzed using three different PIXE analysis codes and the results compared to the cases when each of these codes is used to separately analyze the associated AXSIA principal component spectral data. We find that these comparisons are in good quantitative agreement with each other
Euler deconvolution and spectral analysis of regional aeromagnetic ...
African Journals Online (AJOL)
Existing regional aeromagnetic data from the south-central Zimbabwe craton has been analysed using 3D Euler deconvolution and spectral analysis to obtain quantitative information on the geological units and structures for depth constraints on the geotectonic interpretation of the region. The Euler solution maps confirm ...
Spectral Depth Analysis of some Segments of the Bida Basin ...
African Journals Online (AJOL)
ADOWIE PERE
2017-12-16
Dec 16, 2017 ... ABSTRACT: Spectral depth analysis was carried out on ten (10) of the 2009 total magnetic field intensity data sheets covering some segments of the Bida basin, to determine the depth to magnetic basement within the basin. The data was ... groundwater lie concealed beneath the earth surface and the ...
Tomato sorting using independent component analysis on spectral images
Polder, G.; Heijden, van der G.W.A.M.; Young, I.T.
2003-01-01
Independent Component Analysis is one of the most widely used methods for blind source separation. In this paper we use this technique to estimate the most important compounds which play a role in the ripening of tomatoes. Spectral images of tomatoes were analyzed. Two main independent components
Curie depth and geothermal gradient from spectral analysis of ...
African Journals Online (AJOL)
The resent (2009) aeromagnetic data covering lower part of Benue and upper part of Anambra basins was subjected to one dimensional spectral analysis with the aim of estimating the curie depth and subsequently evaluating both the geothermal gradient and heat flow for the area. Curie point depth estimate obtained were ...
Estimation and analysis of spectral solar radiation over Cairo
International Nuclear Information System (INIS)
Abdel Wahab, M.M.; Omran, M.
1994-05-01
This work presents a methodology to estimate spectral diffuse and global radiation on horizontal surface. This method is validated by comparing with measured direct and global spectral radiation in four bands. The results show a good performance in cloudless conditions. The analysis of the ratio of surface values to extraterrestrial ones revealed an over-all depletion in the summer months. Also there was no evidence for any tendency for conversion of radiational components through different bands. The model presents excellent agreement with the measured values for (UV/G) ratio. (author). 7 refs, 4 figs, 3 tabs
MEM spectral analysis for predicting influenza epidemics in Japan.
Sumi, Ayako; Kamo, Ken-ichi
2012-03-01
The prediction of influenza epidemics has long been the focus of attention in epidemiology and mathematical biology. In this study, we tested whether time series analysis was useful for predicting the incidence of influenza in Japan. The method of time series analysis we used consists of spectral analysis based on the maximum entropy method (MEM) in the frequency domain and the nonlinear least squares method in the time domain. Using this time series analysis, we analyzed the incidence data of influenza in Japan from January 1948 to December 1998; these data are unique in that they covered the periods of pandemics in Japan in 1957, 1968, and 1977. On the basis of the MEM spectral analysis, we identified the periodic modes explaining the underlying variations of the incidence data. The optimum least squares fitting (LSF) curve calculated with the periodic modes reproduced the underlying variation of the incidence data. An extension of the LSF curve could be used to predict the incidence of influenza quantitatively. Our study suggested that MEM spectral analysis would allow us to model temporal variations of influenza epidemics with multiple periodic modes much more effectively than by using the method of conventional time series analysis, which has been used previously to investigate the behavior of temporal variations in influenza data.
2nd Conference of the International Society for Nonparametric Statistics
Manteiga, Wenceslao; Romo, Juan
2016-01-01
This volume collects selected, peer-reviewed contributions from the 2nd Conference of the International Society for Nonparametric Statistics (ISNPS), held in Cádiz (Spain) between June 11–16 2014, and sponsored by the American Statistical Association, the Institute of Mathematical Statistics, the Bernoulli Society for Mathematical Statistics and Probability, the Journal of Nonparametric Statistics and Universidad Carlos III de Madrid. The 15 articles are a representative sample of the 336 contributed papers presented at the conference. They cover topics such as high-dimensional data modelling, inference for stochastic processes and for dependent data, nonparametric and goodness-of-fit testing, nonparametric curve estimation, object-oriented data analysis, and semiparametric inference. The aim of the ISNPS 2014 conference was to bring together recent advances and trends in several areas of nonparametric statistics in order to facilitate the exchange of research ideas, promote collaboration among researchers...
An introduction to random vibrations, spectral & wavelet analysis
Newland, D E
2005-01-01
One of the first engineering books to cover wavelet analysis, this classic text describes and illustrates basic theory, with a detailed explanation of the workings of discrete wavelet transforms. Computer algorithms are explained and supported by examples and a set of problems, and an appendix lists ten computer programs for calculating and displaying wavelet transforms.Starting with an introduction to probability distributions and averages, the text examines joint probability distributions, ensemble averages, and correlation; Fourier analysis; spectral density and excitation response relation
Berkeley SuperNova Ia Program (BSNIP): Initial Spectral Analysis
Silverman, Jeffrey; Kong, J.; Ganeshalingam, M.; Li, W.; Filippenko, A. V.
2011-01-01
The Berkeley SuperNova Ia Program (BSNIP) has been observing nearby (z analysis of this dataset consists of accurately and robustly measuring the strength and position of various spectral features near maximum brightness. We determine the endpoints, pseudo-continuum, expansion velocity, equivalent width, and depth of each major feature observed in our wavelength range. For objects with multiple spectra near maximum brightness we investigate how these values change with time. From these measurements we also calculate velocity gradients and various flux ratios within a given spectrum which will allow us to explore correlations between spectral and photometric observables. Some possible correlations have been studied previously, but our dataset is unique in how self-consistent the data reduction and spectral feature measurements have been, and it is a factor of a few larger than most earlier studies. We will briefly summarize the contents of the full dataset as an introduction to our initial analysis. Some of our measurements of SN Ia spectral features, along with a few initial results from those measurements, will be presented. Finally, we will comment on our current progress and planned future work. We gratefully acknowledge the financial support of NSF grant AST-0908886, the TABASGO Foundation, and the Marc J. Staley Graduate Fellowship in Astronomy.
Power spectral analysis of heart rate in hyperthyroidism.
Cacciatori, V; Bellavere, F; Pezzarossa, A; Dellera, A; Gemma, M L; Thomaseth, K; Castello, R; Moghetti, P; Muggeo, M
1996-08-01
The aim of the present study was to evaluate the impact of hyperthyroidism on the cardiovascular system by separately analyzing the sympathetic and parasympathetic influences on heart rate. Heart rate variability was evaluated by autoregressive power spectral analysis. This method allows a reliable quantification of the low frequency (LF) and high frequency (HF) components of the heart rate power spectral density; these are considered to be under mainly sympathetic and pure parasympathetic control, respectively. In 10 newly diagnosed untreated hyperthyroid patients with Graves' disease, we analyzed power spectral density of heart rate cyclic variations at rest, while lying, and while standing. In addition, heart rate variations during deep breathing, lying and standing, and Valsalva's maneuver were analyzed. The results were compared to those obtained from 10 age-, sex-, and body mass index-matched control subjects. In 8 hyperthyroid patients, the same evaluation was repeated after the induction of stable euthyroidism by methimazole. Heart rate power spectral analysis showed a sharp reduction of HF components in hyperthyroid subjects compared to controls [lying, 13.3 +/- 4.1 vs. 32.0 +/- 5.6 normalized units (NU; P hyperthyroid subjects while both lying (11.3 +/- 4.5 vs. 3.5 +/- 1.1; P hyperthyroid patients than in controls (1.12 +/- 0.03 vs. 1.31 +/- 0.04; P activity and, thus, a relative hypersympathetic tone.
Varabyova, Yauheniya; Schreyögg, Jonas
2013-09-01
There is a growing interest in the cross-country comparisons of the performance of national health care systems. The present work provides a comparison of the technical efficiency of the hospital sector using unbalanced panel data from OECD countries over the period 2000-2009. The estimation of the technical efficiency of the hospital sector is performed using nonparametric data envelopment analysis (DEA) and parametric stochastic frontier analysis (SFA). Internal and external validity of findings is assessed by estimating the Spearman rank correlations between the results obtained in different model specifications. The panel-data analyses using two-step DEA and one-stage SFA show that countries, which have higher health care expenditure per capita, tend to have a more technically efficient hospital sector. Whether the expenditure is financed through private or public sources is not related to the technical efficiency of the hospital sector. On the other hand, the hospital sector in countries with higher income inequality and longer average hospital length of stay is less technically efficient. Copyright © 2013 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.
Nonparametric identification of copula structures
Li, Bo; Genton, Marc G.
2013-01-01
We propose a unified framework for testing a variety of assumptions commonly made about the structure of copulas, including symmetry, radial symmetry, joint symmetry, associativity and Archimedeanity, and max-stability. Our test is nonparametric
Huang, Norden E.; Hu, Kun; Yang, Albert C. C.; Chang, Hsing-Chih; Jia, Deng; Liang, Wei-Kuang; Yeh, Jia Rong; Kao, Chu-Lan; Juan, Chi-Hung; Peng, Chung Kang; Meijer, Johanna H.; Wang, Yung-Hung; Long, Steven R.; Wu, Zhauhua
2016-01-01
The Holo-Hilbert spectral analysis (HHSA) method is introduced to cure the deficiencies of traditional spectral analysis and to give a full informational representation of nonlinear and non-stationary data. It uses a nested empirical mode decomposition and Hilbert–Huang transform (HHT) approach to identify intrinsic amplitude and frequency modulations often present in nonlinear systems. Comparisons are first made with traditional spectrum analysis, which usually achieved its results through c...
International Nuclear Information System (INIS)
Lam, G.K.
1989-01-01
The combined effects of mixed radiations can be examined using a system of simple isoeffect relations which are derived from a recent analysis of in vitro results obtained for a variety of radiation mixtures. Similar isoeffect analysis methods have been used for over two decades in studies of the combined action of toxic agents such as drugs and antibiotics. Because of the isoeffect approach, the method is particularly useful for the analysis of ordinal data for which conventional models that are based on parametric dose-effect relations may not be suitable. This is illustrated by applying the method to the analysis of a set of recently published in vivo data using the mouse foot skin reaction system for mixtures of neutrons and X rays. The good agreement between this method and the ordinal data also helps to provide further experimental support for the existence of a class of radiobiological data for which the simple isoeffect relations are valid
Spectral analysis of full field digital mammography data
International Nuclear Information System (INIS)
Heine, John J.; Velthuizen, Robert P.
2002-01-01
The spectral content of mammograms acquired from using a full field digital mammography (FFDM) system are analyzed. Fourier methods are used to show that the FFDM image power spectra obey an inverse power law; in an average sense, the images may be considered as 1/f fields. Two data representations are analyzed and compared (1) the raw data, and (2) the logarithm of the raw data. Two methods are employed to analyze the power spectra (1) a technique based on integrating the Fourier plane with octave ring sectioning developed previously, and (2) an approach based on integrating the Fourier plane using rings of constant width developed for this work. Both methods allow theoretical modeling. Numerical analysis indicates that the effects due to the transformation influence the power spectra measurements in a statistically significant manner in the high frequency range. However, this effect has little influence on the inverse power law estimation for a given image regardless of the data representation or the theoretical analysis approach. The analysis is presented from two points of view (1) each image is treated independently with the results presented as distributions, and (2) for a given representation, the entire image collection is treated as an ensemble with the results presented as expected values. In general, the constant ring width analysis forms the foundation for a spectral comparison method for finding spectral differences, from an image distribution sense, after applying a nonlinear transformation to the data. The work also shows that power law estimation may be influenced due to the presence of noise in the higher frequency range, which is consistent with the known attributes of the detector efficiency. The spectral modeling and inverse power law determinations obtained here are in agreement with that obtained from the analysis of digitized film-screen images presented previously. The form of the power spectrum for a given image is approximately 1/f 2
Multivariate spectral-analysis of movement-related EEG data
International Nuclear Information System (INIS)
Andrew, C. M.
1997-01-01
The univariate method of event-related desynchronization (ERD) analysis, which quantifies the temporal evolution of power within specific frequency bands from electroencephalographic (EEG) data recorded during a task or event, is extended to an event related multivariate spectral analysis method. With this method, time courses of cross-spectra, phase spectra, coherence spectra, band-averaged coherence values (event-related coherence, ERCoh), partial power spectra and partial coherence spectra are estimated from an ensemble of multivariate event-related EEG trials. This provides a means of investigating relationships between EEG signals recorded over different scalp areas during the performance of a task or the occurrence of an event. The multivariate spectral analysis method is applied to EEG data recorded during three different movement-related studies involving discrete right index finger movements. The first study investigates the impact of the EEG derivation type on the temporal evolution of interhemispheric coherence between activity recorded at electrodes overlying the left and right sensorimotor hand areas during cued finger movement. The question results whether changes in coherence necessarily reflect changes in functional coupling of the cortical structures underlying the recording electrodes. The method is applied to data recorded during voluntary finger movement and a hypothesis, based on an existing global/local model of neocortical dynamics, is formulated to explain the coherence results. The third study applies partial spectral analysis too, and investigates phase relationships of, movement-related data recorded from a full head montage, thereby providing further results strengthening the global/local hypothesis. (author)
Spectral map-analysis: a method to analyze gene expression data
Bijnens, Luc J.M.; Lewi, Paul J.; Göhlmann, Hinrich W.; Molenberghs, Geert; Wouters, Luc
2004-01-01
bioinformatics; biplot; correspondence factor analysis; data mining; data visualization; gene expression data; microarray data; multivariate exploratory data analysis; principal component analysis; Spectral map analysis
Effective approach to spectroscopy and spectral analysis techniques using Matlab
Li, Xiang; Lv, Yong
2017-08-01
With the development of electronic information, computer and network, modern education technology has entered new era, which would give a great impact on teaching process. Spectroscopy and spectral analysis is an elective course for Optoelectronic Information Science and engineering. The teaching objective of this course is to master the basic concepts and principles of spectroscopy, spectral analysis and testing of basic technical means. Then, let the students learn the principle and technology of the spectrum to study the structure and state of the material and the developing process of the technology. MATLAB (matrix laboratory) is a multi-paradigm numerical computing environment and fourth-generation programming language. A proprietary programming language developed by MathWorks, MATLAB allows matrix manipulations, plotting of functions and data, Based on the teaching practice, this paper summarizes the new situation of applying Matlab to the teaching of spectroscopy. This would be suitable for most of the current school multimedia assisted teaching
Leak detection in pipelines through spectral analysis of pressure signals
Directory of Open Access Journals (Sweden)
Souza A.L.
2000-01-01
Full Text Available The development and test of a technique for leak detection in pipelines is presented. The technique is based on the spectral analysis of pressure signals measured in pipeline sections where the formation of stationary waves is favoured, allowing leakage detection during the start/stop of pumps. Experimental tests were performed in a 1250 m long pipeline for various operational conditions of the pipeline (liquid flow rate and leakage configuration. Pressure transients were obtained by four transducers connected to a PC computer. The obtained results show that the spectral analysis of pressure transients, together with the knowledge of reflection points provide a simple and efficient way of identifying leaks during the start/stop of pumps in pipelines.
Outlier Detection with Space Transformation and Spectral Analysis
DEFF Research Database (Denmark)
Dang, Xuan-Hong; Micenková, Barbora; Assent, Ira
2013-01-01
which rely on notions of distances or densities, this approach introduces a novel concept based on local quadratic entropy for evaluating the similarity of a data object with its neighbors. This information theoretic quantity is used to regularize the closeness amongst data instances and subsequently......Detecting a small number of outliers from a set of data observations is always challenging. In this paper, we present an approach that exploits space transformation and uses spectral analysis in the newly transformed space for outlier detection. Unlike most existing techniques in the literature...... benefits the process of mapping data into a usually lower dimensional space. Outliers are then identified by spectral analysis of the eigenspace spanned by the set of leading eigenvectors derived from the mapping procedure. The proposed technique is purely data-driven and imposes no assumptions regarding...
Fast analysis of spectral data using neural networks
International Nuclear Information System (INIS)
Roach, C.M.
1992-01-01
Fast analysis techniques are highly desirable in experiments where measurements are recorded at high rates. In fusion experiments the processing required to obtain plasma parameters is usually orders of magnitude slower than the data acquisition. Spectroscopic diagnostics suffer greatly from this problem. The extraction of plasma parameters from a measured spectrum typically corresponds to a nonlinear mapping between distinct multi-dimensional spaces. Where no analytic expression for the mapping exists, conventional analysis methods (e.g. least squares) are usually iterative and therefore slow. With this concern in mind a fast spectral analysis method involving neural networks has been investigated. (author) 6 refs., 3 figs
Qin, Xian-Lin; Zhu, Xi; Yang, Fei; Zhao, Kai-Rui; Pang, Yong; Li, Zeng-Yuan; Li, Xu-Zhi; Zhang, Jiu-Xing
2013-07-01
To obtain the sensitive spectral bands for detection of information on 4 kinds of burning status, i. e. flaming, smoldering, smoke, and fire scar, with satellite data, analysis was conducted to identify suitable satellite spectral bands for detection of information on these 4 kinds of burning status by using hyper-spectrum images of Tiangong-01 (TG-01) and employing a method combining statistics and spectral analysis. The results show that: in the hyper-spectral images of TG-01, the spectral bands differ obviously for detection of these 4 kinds of burning status; in all hyper-spectral short-wave infrared channels, the reflectance of flaming is higher than that of all other 3 kinds of burning status, and the reflectance of smoke is the lowest; the reflectance of smoke is higher than that of all other 3 kinds of burning status in the channels corresponding to hyper-spectral visible near-infrared and panchromatic sensors. For spectral band selection, more suitable spectral bands for flaming detection are 1 000.0-1 956.0 and 2 020.0-2 400.0 nm; the suitable spectral bands for identifying smoldering are 930.0-1 000.0 and 1 084.0-2 400.0 nm; the suitable spectral bands for smoke detection is in 400.0-920.0 nm; for fire scar detection, it is suitable to select bands with central wavelengths of 900.0-930.0 and 1 300.0-2 400.0 nm, and then to combine them to construct a detection model.
Spectral Envelopes and Additive + Residual Analysis/Synthesis
Rodet, Xavier; Schwarz, Diemo
The subject of this chapter is the estimation, representation, modification, and use of spectral envelopes in the context of sinusoidal-additive-plus-residual analysis/synthesis. A spectral envelope is an amplitude-vs-frequency function, which may be obtained from the envelope of a short-time spectrum (Rodet et al., 1987; Schwarz, 1998). [Precise definitions of such an envelope and short-time spectrum (STS) are given in Section 2.] The additive-plus-residual analysis/synthesis method is based on a representation of signals in terms of a sum of time-varying sinusoids and of a non-sinusoidal residual signal [e.g., see Serra (1989), Laroche et al. (1993), McAulay and Quatieri (1995), and Ding and Qian (1997)]. Many musical sound signals may be described as a combination of a nearly periodic waveform and colored noise. The nearly periodic part of the signal can be viewed as a sum of sinusoidal components, called partials, with time-varying frequency and amplitude. Such sinusoidal components are easily observed on a spectral analysis display (Fig. 5.1) as obtained, for instance, from a discrete Fourier transform.
Parametric image reconstruction using spectral analysis of PET projection data
International Nuclear Information System (INIS)
Meikle, Steven R.; Matthews, Julian C.; Cunningham, Vincent J.; Bailey, Dale L.; Livieratos, Lefteris; Jones, Terry; Price, Pat
1998-01-01
Spectral analysis is a general modelling approach that enables calculation of parametric images from reconstructed tracer kinetic data independent of an assumed compartmental structure. We investigated the validity of applying spectral analysis directly to projection data motivated by the advantages that: (i) the number of reconstructions is reduced by an order of magnitude and (ii) iterative reconstruction becomes practical which may improve signal-to-noise ratio (SNR). A dynamic software phantom with typical 2-[ 11 C]thymidine kinetics was used to compare projection-based and image-based methods and to assess bias-variance trade-offs using iterative expectation maximization (EM) reconstruction. We found that the two approaches are not exactly equivalent due to properties of the non-negative least-squares algorithm. However, the differences are small ( 1 and, to a lesser extent, VD). The optimal number of EM iterations was 15-30 with up to a two-fold improvement in SNR over filtered back projection. We conclude that projection-based spectral analysis with EM reconstruction yields accurate parametric images with high SNR and has potential application to a wide range of positron emission tomography ligands. (author)
Noise analysis role in reactor safety, Spectral analysis (PSD)
International Nuclear Information System (INIS)
Jovanovic, S.; Velickovic, Lj.
1967-11-01
Spectral power density of a zero power reactor is frequency dependent and related to transfer function of the reactor and to spectral density of the input disturbance. Measurement of spectral power density of a critical system is used to obtain the ratio (β/l), β is the effective yield of delayed neutrons, and l is the effective mean neutron lifetime. When reactor is subcritical, if the effective yie ald of delayed neutrons, the effective mean neutron lifetime are known, the shutdown margin can be determined by relation α = (1 - k (1- β0)/l, k is the effective multiplication factor. Output neutron spectrum at the RB reactor in Vinca was measured for a few reactor core configurations and for a few levels of heavy water at subcritical state. Measured values were satisfactory when the reactor was critical, but the reactor noise of subcritical system was covered by the white noise of the detector and electronic equipment. The Ra-Be source was under the reactor vessel when measurements of subcritical system were done. More efficient detector or external random stimulus for increasing the intensity of neutron fluctuations would be needed to obtain results for subcritical system
Directory of Open Access Journals (Sweden)
Dermody James J
2004-11-01
Full Text Available Abstract Background A major goal of cancer research is to identify discrete biomarkers that specifically characterize a given malignancy. These markers are useful in diagnosis, may identify potential targets for drug development, and can aid in evaluating treatment efficacy and predicting patient outcome. Microarray technology has enabled marker discovery from human cells by permitting measurement of steady-state mRNA levels derived from thousands of genes. However many challenging and unresolved issues regarding the acquisition and analysis of microarray data remain, such as accounting for both experimental and biological noise, transcripts whose expression profiles are not normally distributed, guidelines for statistical assessment of false positive/negative rates and comparing data derived from different research groups. This study addresses these issues using Affymetrix HG-U95A and HG-U133 GeneChip data derived from different research groups. Results We present here a simple non parametric approach coupled with noise filtering to identify sets of genes differentially expressed between the normal and cancer states in oral, breast, lung, prostate and ovarian tumors. An important feature of this study is the ability to integrate data from different laboratories, improving the analytical power of the individual results. One of the most interesting findings is the down regulation of genes involved in tissue differentiation. Conclusions This study presents the development and application of a noise model that suppresses noise, limits false positives in the results, and allows integration of results from individual studies derived from different research groups.
Analyzing availability using transfer function models and cross spectral analysis
International Nuclear Information System (INIS)
Singpurwalla, N.D.
1980-01-01
The paper shows how the methods of multivariate time series analysis can be used in a novel way to investigate the interrelationships between a series of operating (running) times and a series of maintenance (down) times of a complex system. Specifically, the techniques of cross spectral analysis are used to help obtain a Box-Jenkins type transfer function model for the running times and the down times of a nuclear reactor. A knowledge of the interrelationships between the running times and the down times is useful for an evaluation of maintenance policies, for replacement policy decisions, and for evaluating the availability and the readiness of complex systems
Spectral Analysis Of Business Cycles In The Visegrad Group Countries
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Kijek Arkadiusz
2017-06-01
Full Text Available This paper examines the business cycle properties of Visegrad group countries. The main objective is to identify business cycles in these countries and to study the relationships between them. The author applies a modification of the Fourier analysis to estimate cycle amplitudes and frequencies. This allows for a more precise estimation of cycle characteristics than the traditional approach. The cross-spectral analysis of GDP cyclical components for the Czech Republic, Hungary, Poland and Slovakia makes it possible to assess the degree of business cycle synchronization between the countries.
Directory of Open Access Journals (Sweden)
César Merino Soto
2009-05-01
Full Text Available Resumen:La presente investigación hace un estudio psicométrico de un nuevo sistema de calificación de la Prueba Gestáltica del Bendermodificada para niños, que es el Sistema de Calificación Cualitativa (Brannigan y Brunner, 2002, en un muestra de 244 niñosingresantes a primer grado de primaria en cuatro colegios públicos, ubicados en Lima. El enfoque usado es un análisis noparamétrico de ítems mediante el programa Testgraf (Ramsay, 1991. Los resultados indican niveles apropiados deconsistencia interna, identificándose la unidimensionalidad, y el buen nivel discriminativo de las categorías de calificación deeste Sistema Cualitativo. No se hallaron diferencias demográficas respecto al género ni la edad. Se discuten los presenteshallazgos en el contexto del potencial uso del Sistema de Calificación Cualitativa y del análisis no paramétrico de ítems en lainvestigación psicométrica.AbstracThis research designs a psychometric study of a new scoring system of the Bender Gestalt test modified to children: it is theQualitative Scoring System (Brannigan & Brunner, 2002, in a sample of 244 first grade children of primary level, in four public school of Lima. The approach aplied is the nonparametric item analysis using The test graft computer program (Ramsay, 1991. Our findings point to good levels of internal consistency, unidimensionality and good discriminative level ofthe categories of scoring from the Qualitative Scoring System. There are not demographic differences between gender or age.We discuss our findings within the context of the potential use of the Qualitative Scoring System and of the nonparametricitem analysis approach in the psychometric research.
International Nuclear Information System (INIS)
Chen, Chin-Wei; Cote, Patrick; Ferrarese, Laura; West, Andrew A.; Peng, Eric W.
2010-01-01
We present photometric and structural parameters for 100 ACS Virgo Cluster Survey (ACSVCS) galaxies based on homogeneous, multi-wavelength (ugriz), wide-field SDSS (DR5) imaging. These early-type galaxies, which trace out the red sequence in the Virgo Cluster, span a factor of nearly ∼10 3 in g-band luminosity. We describe an automated pipeline that generates background-subtracted mosaic images, masks field sources and measures mean shapes, total magnitudes, effective radii, and effective surface brightnesses using a model-independent approach. A parametric analysis of the surface brightness profiles is also carried out to obtain Sersic-based structural parameters and mean galaxy colors. We compare the galaxy parameters to those in the literature, including those from the ACSVCS, finding good agreement in most cases, although the sizes of the brightest, and most extended, galaxies are found to be most uncertain and model dependent. Our photometry provides an external measurement of the random errors on total magnitudes from the widely used Virgo Cluster Catalog, which we estimate to be σ(B T )∼ 0.13 mag for the brightest galaxies, rising to ∼ 0.3 mag for galaxies at the faint end of our sample (B T ∼ 16). The distribution of axial ratios of low-mass ( d warf ) galaxies bears a strong resemblance to the one observed for the higher-mass ( g iant ) galaxies. The global structural parameters for the full galaxy sample-profile shape, effective radius, and mean surface brightness-are found to vary smoothly and systematically as a function of luminosity, with unmistakable evidence for changes in structural homology along the red sequence. As noted in previous studies, the ugriz galaxy colors show a nonlinear but smooth variation over a ∼7 mag range in absolute magnitude, with an enhanced scatter for the faintest systems that is likely the signature of their more diverse star formation histories.
[Applications of spectral analysis technique to monitoring grasshoppers].
Lu, Hui; Han, Jian-guo; Zhang, Lu-da
2008-12-01
Grasshopper monitoring is of great significance in protecting environment and reducing economic loss. However, how to predict grasshoppers accurately and effectively is a difficult problem for a long time. In the present paper, the importance of forecasting grasshoppers and its habitat is expounded, and the development in monitoring grasshopper populations and the common arithmetic of spectral analysis technique are illustrated. Meanwhile, the traditional methods are compared with the spectral technology. Remote sensing has been applied in monitoring the living, growing and breeding habitats of grasshopper population, and can be used to develop a forecast model combined with GIS. The NDVI values can be analyzed throughout the remote sensing data and be used in grasshopper forecasting. Hyper-spectra remote sensing technique which can be used to monitor grasshoppers more exactly has advantages in measuring the damage degree and classifying damage areas of grasshoppers, so it can be adopted to monitor the spatial distribution dynamic of rangeland grasshopper population. Differentialsmoothing can be used to reflect the relations between the characteristic parameters of hyper-spectra and leaf area index (LAI), and indicate the intensity of grasshopper damage. The technology of near infrared reflectance spectroscopy has been employed in judging grasshopper species, examining species occurrences and monitoring hatching places by measuring humidity and nutrient of soil, and can be used to investigate and observe grasshoppers in sample research. According to this paper, it is concluded that the spectral analysis technique could be used as a quick and exact tool in monitoring and forecasting the infestation of grasshoppers, and will become an important means in such kind of research for their advantages in determining spatial orientation, information extracting and processing. With the rapid development of spectral analysis methodology, the goal of sustainable monitoring
The role of the computer in automated spectral analysis
International Nuclear Information System (INIS)
Rasmussen, S.E.
This report describes how a computer can be an extremely valuable tool for routine analysis of spectra, which is a time consuming process. A number of general-purpose algorithms that are available for the various phases of the analysis can be implemented, if these algorithms are designed to cope with all the variations that may occur. Since this is basically impossible, one must find a compromise between obscure error and program complexity. This is usually possible with human interaction at critical points. In spectral analysis this is possible if the user scans the data on an interactive graphics terminal, makes the necessary changes and then returns control to the computer for completion of the analysis
Monitoring urban greenness dynamics using multiple endmember spectral mixture analysis.
Directory of Open Access Journals (Sweden)
Muye Gan
Full Text Available Urban greenness is increasingly recognized as an essential constituent of the urban environment and can provide a range of services and enhance residents' quality of life. Understanding the pattern of urban greenness and exploring its spatiotemporal dynamics would contribute valuable information for urban planning. In this paper, we investigated the pattern of urban greenness in Hangzhou, China, over the past two decades using time series Landsat-5 TM data obtained in 1990, 2002, and 2010. Multiple endmember spectral mixture analysis was used to derive vegetation cover fractions at the subpixel level. An RGB-vegetation fraction model, change intensity analysis and the concentric technique were integrated to reveal the detailed, spatial characteristics and the overall pattern of change in the vegetation cover fraction. Our results demonstrated the ability of multiple endmember spectral mixture analysis to accurately model the vegetation cover fraction in pixels despite the complex spectral confusion of different land cover types. The integration of multiple techniques revealed various changing patterns in urban greenness in this region. The overall vegetation cover has exhibited a drastic decrease over the past two decades, while no significant change occurred in the scenic spots that were studied. Meanwhile, a remarkable recovery of greenness was observed in the existing urban area. The increasing coverage of small green patches has played a vital role in the recovery of urban greenness. These changing patterns were more obvious during the period from 2002 to 2010 than from 1990 to 2002, and they revealed the combined effects of rapid urbanization and greening policies. This work demonstrates the usefulness of time series of vegetation cover fractions for conducting accurate and in-depth studies of the long-term trajectories of urban greenness to obtain meaningful information for sustainable urban development.
Spectral analysis in thin tubes with axial heterogeneities
Ferreira, Rita; Mascarenhas, M. Luí sa; Piatnitski, Andrey
2015-01-01
In this paper, we present the 3D-1D asymptotic analysis of the Dirichlet spectral problem associated with an elliptic operator with axial periodic heterogeneities. We extend to the 3D-1D case previous 3D-2D results (see [10]) and we analyze the special case where the scale of thickness is much smaller than the scale of the heterogeneities and the planar coefficient has a unique global minimum in the periodic cell. These results are of great relevance in the comprehension of the wave propagation in nanowires showing axial heterogeneities (see [17]).
On asymptotic analysis of spectral problems in elasticity
Directory of Open Access Journals (Sweden)
S.A. Nazarov
Full Text Available The three-dimensional spectral elasticity problem is studied in an anisotropic and inhomogeneous solid with small defects, i.e., inclusions, voids, and microcracks. Asymptotics of eigenfrequencies and the corresponding elastic eigenmodes are constructed and justified. New technicalities of the asymptotic analysis are related to variable coefficients of differential operators, vectorial setting of the problem, and usage of intrinsic integral characteristics of defects. The asymptotic formulae are developed in a form convenient for application in shape optimization and inverse problems.
A nonparametric mixture model for cure rate estimation.
Peng, Y; Dear, K B
2000-03-01
Nonparametric methods have attracted less attention than their parametric counterparts for cure rate analysis. In this paper, we study a general nonparametric mixture model. The proportional hazards assumption is employed in modeling the effect of covariates on the failure time of patients who are not cured. The EM algorithm, the marginal likelihood approach, and multiple imputations are employed to estimate parameters of interest in the model. This model extends models and improves estimation methods proposed by other researchers. It also extends Cox's proportional hazards regression model by allowing a proportion of event-free patients and investigating covariate effects on that proportion. The model and its estimation method are investigated by simulations. An application to breast cancer data, including comparisons with previous analyses using a parametric model and an existing nonparametric model by other researchers, confirms the conclusions from the parametric model but not those from the existing nonparametric model.
Directory of Open Access Journals (Sweden)
Stochl Jan
2012-06-01
Full Text Available Abstract Background Mokken scaling techniques are a useful tool for researchers who wish to construct unidimensional tests or use questionnaires that comprise multiple binary or polytomous items. The stochastic cumulative scaling model offered by this approach is ideally suited when the intention is to score an underlying latent trait by simple addition of the item response values. In our experience, the Mokken model appears to be less well-known than for example the (related Rasch model, but is seeing increasing use in contemporary clinical research and public health. Mokken's method is a generalisation of Guttman scaling that can assist in the determination of the dimensionality of tests or scales, and enables consideration of reliability, without reliance on Cronbach's alpha. This paper provides a practical guide to the application and interpretation of this non-parametric item response theory method in empirical research with health and well-being questionnaires. Methods Scalability of data from 1 a cross-sectional health survey (the Scottish Health Education Population Survey and 2 a general population birth cohort study (the National Child Development Study illustrate the method and modeling steps for dichotomous and polytomous items respectively. The questionnaire data analyzed comprise responses to the 12 item General Health Questionnaire, under the binary recoding recommended for screening applications, and the ordinal/polytomous responses to the Warwick-Edinburgh Mental Well-being Scale. Results and conclusions After an initial analysis example in which we select items by phrasing (six positive versus six negatively worded items we show that all items from the 12-item General Health Questionnaire (GHQ-12 – when binary scored – were scalable according to the double monotonicity model, in two short scales comprising six items each (Bech’s “well-being” and “distress” clinical scales. An illustration of ordinal item analysis
Stochl, Jan; Jones, Peter B; Croudace, Tim J
2012-06-11
Mokken scaling techniques are a useful tool for researchers who wish to construct unidimensional tests or use questionnaires that comprise multiple binary or polytomous items. The stochastic cumulative scaling model offered by this approach is ideally suited when the intention is to score an underlying latent trait by simple addition of the item response values. In our experience, the Mokken model appears to be less well-known than for example the (related) Rasch model, but is seeing increasing use in contemporary clinical research and public health. Mokken's method is a generalisation of Guttman scaling that can assist in the determination of the dimensionality of tests or scales, and enables consideration of reliability, without reliance on Cronbach's alpha. This paper provides a practical guide to the application and interpretation of this non-parametric item response theory method in empirical research with health and well-being questionnaires. Scalability of data from 1) a cross-sectional health survey (the Scottish Health Education Population Survey) and 2) a general population birth cohort study (the National Child Development Study) illustrate the method and modeling steps for dichotomous and polytomous items respectively. The questionnaire data analyzed comprise responses to the 12 item General Health Questionnaire, under the binary recoding recommended for screening applications, and the ordinal/polytomous responses to the Warwick-Edinburgh Mental Well-being Scale. After an initial analysis example in which we select items by phrasing (six positive versus six negatively worded items) we show that all items from the 12-item General Health Questionnaire (GHQ-12)--when binary scored--were scalable according to the double monotonicity model, in two short scales comprising six items each (Bech's "well-being" and "distress" clinical scales). An illustration of ordinal item analysis confirmed that all 14 positively worded items of the Warwick-Edinburgh Mental
Testing discontinuities in nonparametric regression
Dai, Wenlin
2017-01-19
In nonparametric regression, it is often needed to detect whether there are jump discontinuities in the mean function. In this paper, we revisit the difference-based method in [13 H.-G. Müller and U. Stadtmüller, Discontinuous versus smooth regression, Ann. Stat. 27 (1999), pp. 299–337. doi: 10.1214/aos/1018031100
Testing discontinuities in nonparametric regression
Dai, Wenlin; Zhou, Yuejin; Tong, Tiejun
2017-01-01
In nonparametric regression, it is often needed to detect whether there are jump discontinuities in the mean function. In this paper, we revisit the difference-based method in [13 H.-G. Müller and U. Stadtmüller, Discontinuous versus smooth regression, Ann. Stat. 27 (1999), pp. 299–337. doi: 10.1214/aos/1018031100
Overlapping communities detection based on spectral analysis of line graphs
Gui, Chun; Zhang, Ruisheng; Hu, Rongjing; Huang, Guoming; Wei, Jiaxuan
2018-05-01
Community in networks are often overlapping where one vertex belongs to several clusters. Meanwhile, many networks show hierarchical structure such that community is recursively grouped into hierarchical organization. In order to obtain overlapping communities from a global hierarchy of vertices, a new algorithm (named SAoLG) is proposed to build the hierarchical organization along with detecting the overlap of community structure. SAoLG applies the spectral analysis into line graphs to unify the overlap and hierarchical structure of the communities. In order to avoid the limitation of absolute distance such as Euclidean distance, SAoLG employs Angular distance to compute the similarity between vertices. Furthermore, we make a micro-improvement partition density to evaluate the quality of community structure and use it to obtain the more reasonable and sensible community numbers. The proposed SAoLG algorithm achieves a balance between overlap and hierarchy by applying spectral analysis to edge community detection. The experimental results on one standard network and six real-world networks show that the SAoLG algorithm achieves higher modularity and reasonable community number values than those generated by Ahn's algorithm, the classical CPM and GN ones.
Spectral analysis of underwater explosions in the Dead Sea
Gitterman, Y.; Ben-Avraham, Z.; Ginzburg, A.
1998-08-01
The present study utilizes the Israel Seismic Network (ISN) as a spatially distributed multichannel system for the discrimination of low-magnitude events (ML UWEs) and 16 earthquakes in the magnitude range ML = 1.6-2.8, within distances of 10-150 km, recorded by the ISN, were selected for the analysis. The analysis is based on a smoothed (0.5 Hz window) Fourier spectrum of the whole signal (defined by the signal-to-noise criterion), without picking separate wave phases. It was found that the classical discriminant of the seismic energy ratio between the relatively low-frequency (1-6 Hz) and high-frequency (6-11 Hz) bands, averaged over an ISN subnetwork, showed an overlap between UWEs and earthquakes and cannot itself provide reliable identification. We developed and tested a new multistation discriminant based on the low- frequency spectral modulation (LFSM) method. In our case the LFSM is associated with the bubbling effect in underwater explosions. The method demonstrates a distinct azimuth-invariant coherency of spectral shapes in the low-frequency range (1-12 Hz) of short-period seismometer systems. The coherency of the modulated spectra for different ISN stations was measured by semblance statistics commonly used in seismic prospecting for phase correlation in the time domain. The modified statistics provided an almost complete separation between earthquakes and underwater explosions.
Spectral analysis of mammographic images using a multitaper method
International Nuclear Information System (INIS)
Wu Gang; Mainprize, James G.; Yaffe, Martin J.
2012-01-01
Purpose: Power spectral analysis in radiographic images is conventionally performed using a windowed overlapping averaging periodogram. This study describes an alternative approach using a multitaper technique and compares its performance with that of the standard method. This tool will be valuable in power spectrum estimation of images, whose content deviates significantly from uniform white noise. The performance of the multitaper approach will be evaluated in terms of spectral stability, variance reduction, bias, and frequency precision. The ultimate goal is the development of a useful tool for image quality assurance. Methods: A multitaper approach uses successive data windows of increasing order. This mitigates spectral leakage allowing one to calculate a reduced-variance power spectrum. The multitaper approach will be compared with the conventional power spectrum method in several typical situations, including the noise power spectra (NPS) measurements of simulated projection images of a uniform phantom, NPS measurement of real detector images of a uniform phantom for two clinical digital mammography systems, and the estimation of the anatomic noise in mammographic images (simulated images and clinical mammograms). Results: Examination of spectrum variance versus frequency resolution and bias indicates that the multitaper approach is superior to the conventional single taper methods in the prevention of spectrum leakage and variance reduction. More than four times finer frequency precision can be achieved with equivalent or less variance and bias. Conclusions: Without any shortening of the image data length, the bias is smaller and the frequency resolution is higher with the multitaper method, and the need to compromise in the choice of regions of interest size to balance between the reduction of variance and the loss of frequency resolution is largely eliminated.
GBTIDL: Reduction and Analysis of GBT Spectral Line Data
Marganian, P.; Garwood, R. W.; Braatz, J. A.; Radziwill, N. M.; Maddalena, R. J.
2013-03-01
GBTIDL is an interactive package for reduction and analysis of spectral line data taken with the Robert C. Byrd Green Bank Telescope (GBT). The package, written entirely in IDL, consists of straightforward yet flexible calibration, averaging, and analysis procedures (the "GUIDE layer") modeled after the UniPOPS and CLASS data reduction philosophies, a customized plotter with many built-in visualization features, and Data I/O and toolbox functionality that can be used for more advanced tasks. GBTIDL makes use of data structures which can also be used to store intermediate results. The package consumes and produces data in GBT SDFITS format. GBTIDL can be run online and have access to the most recent data coming off the telescope, or can be run offline on preprocessed SDFITS files.
ANALYSIS OF CAMOUFLAGE COVER SPECTRAL CHARACTERISTICS BY IMAGING SPECTROMETER
Directory of Open Access Journals (Sweden)
A. Y. Kouznetsov
2016-03-01
Full Text Available Subject of Research.The paper deals with the problems of detection and identification of objects in hyperspectral imagery. The possibility of object type determination by statistical methods is demonstrated. The possibility of spectral image application for its data type identification is considered. Method. Researching was done by means of videospectral equipment for objects detection at "Fregat" substrate. The postprocessing of hyperspectral information was done with the use of math model of pattern recognition system. The vegetation indexes TCHVI (Three-Channel Vegetation Index and NDVI (Normalized Difference Vegetation Index were applied for quality control of object recognition. Neumann-Pearson criterion was offered as a tool for determination of objects differences. Main Results. We have carried out analysis of the spectral characteristics of summer-typecamouflage cover (Germany. We have calculated the density distribution of vegetation indexes. We have obtained statistical characteristics needed for creation of mathematical model for pattern recognition system. We have shown the applicability of vegetation indices for detection of summer camouflage cover on averdure background. We have presented mathematical model of object recognition based on Neumann-Pearson criterion. Practical Relevance. The results may be useful for specialists in the field of hyperspectral data processing for surface state monitoring.
Spatially explicit spectral analysis of point clouds and geospatial data
Buscombe, Daniel D.
2015-01-01
The increasing use of spatially explicit analyses of high-resolution spatially distributed data (imagery and point clouds) for the purposes of characterising spatial heterogeneity in geophysical phenomena necessitates the development of custom analytical and computational tools. In recent years, such analyses have become the basis of, for example, automated texture characterisation and segmentation, roughness and grain size calculation, and feature detection and classification, from a variety of data types. In this work, much use has been made of statistical descriptors of localised spatial variations in amplitude variance (roughness), however the horizontal scale (wavelength) and spacing of roughness elements is rarely considered. This is despite the fact that the ratio of characteristic vertical to horizontal scales is not constant and can yield important information about physical scaling relationships. Spectral analysis is a hitherto under-utilised but powerful means to acquire statistical information about relevant amplitude and wavelength scales, simultaneously and with computational efficiency. Further, quantifying spatially distributed data in the frequency domain lends itself to the development of stochastic models for probing the underlying mechanisms which govern the spatial distribution of geological and geophysical phenomena. The software packagePySESA (Python program for Spatially Explicit Spectral Analysis) has been developed for generic analyses of spatially distributed data in both the spatial and frequency domains. Developed predominantly in Python, it accesses libraries written in Cython and C++ for efficiency. It is open source and modular, therefore readily incorporated into, and combined with, other data analysis tools and frameworks with particular utility for supporting research in the fields of geomorphology, geophysics, hydrography, photogrammetry and remote sensing. The analytical and computational structure of the toolbox is
Spatially explicit spectral analysis of point clouds and geospatial data
Buscombe, Daniel
2016-01-01
The increasing use of spatially explicit analyses of high-resolution spatially distributed data (imagery and point clouds) for the purposes of characterising spatial heterogeneity in geophysical phenomena necessitates the development of custom analytical and computational tools. In recent years, such analyses have become the basis of, for example, automated texture characterisation and segmentation, roughness and grain size calculation, and feature detection and classification, from a variety of data types. In this work, much use has been made of statistical descriptors of localised spatial variations in amplitude variance (roughness), however the horizontal scale (wavelength) and spacing of roughness elements is rarely considered. This is despite the fact that the ratio of characteristic vertical to horizontal scales is not constant and can yield important information about physical scaling relationships. Spectral analysis is a hitherto under-utilised but powerful means to acquire statistical information about relevant amplitude and wavelength scales, simultaneously and with computational efficiency. Further, quantifying spatially distributed data in the frequency domain lends itself to the development of stochastic models for probing the underlying mechanisms which govern the spatial distribution of geological and geophysical phenomena. The software package PySESA (Python program for Spatially Explicit Spectral Analysis) has been developed for generic analyses of spatially distributed data in both the spatial and frequency domains. Developed predominantly in Python, it accesses libraries written in Cython and C++ for efficiency. It is open source and modular, therefore readily incorporated into, and combined with, other data analysis tools and frameworks with particular utility for supporting research in the fields of geomorphology, geophysics, hydrography, photogrammetry and remote sensing. The analytical and computational structure of the toolbox is described
Directory of Open Access Journals (Sweden)
Haiyan Huang
2016-10-01
Full Text Available Biomass burning is a global phenomenon and systematic burned area mapping is of increasing importance for science and applications. With high spatial resolution and novelty in band design, the recently launched Sentinel-2A satellite provides a new opportunity for moderate spatial resolution burned area mapping. This study examines the performance of the Sentinel-2A Multi Spectral Instrument (MSI bands and derived spectral indices to differentiate between unburned and burned areas. For this purpose, five pairs of pre-fire and post-fire top of atmosphere (TOA reflectance and atmospherically corrected (surface reflectance images were studied. The pixel values of locations that were unburned in the first image and burned in the second image, as well as the values of locations that were unburned in both images which served as a control, were compared and the discrimination of individual bands and spectral indices were evaluated using parametric (transformed divergence and non-parametric (decision tree approaches. Based on the results, the most suitable MSI bands to detect burned areas are the 20 m near-infrared, short wave infrared and red-edge bands, while the performance of the spectral indices varied with location. The atmospheric correction only significantly influenced the separability of the visible wavelength bands. The results provide insights that are useful for developing Sentinel-2 burned area mapping algorithms.
Joint Spectral Analysis for Early Bright X-ray Flares of γ-Ray Bursts ...
Indian Academy of Sciences (India)
Abstract. A joint spectral analysis for early bright X-ray flares that were simultaneously observed with Swift BAT and XRT are present. Both BAT and XRT lightcurves of these flares are correlated. Our joint spectral anal- ysis shows that the radiations in the two energy bands are from the same spectral component, which can ...
IR spectral analysis for the diagnostics of crust earthquake precursors
Directory of Open Access Journals (Sweden)
R. M. Umarkhodgaev
2012-11-01
Full Text Available Some possible physical processes are analysed that cause, under the condition of additional ionisation in a pre-breakdown electric field, emissions in the infrared (IR interval. The atmospheric transparency region of the IR spectrum at wavelengths of 7–15 μm is taken into account. This transparency region corresponds to spectral lines of small atmospheric constituents like CH_{4}, CO_{2}, N_{2}O, NO_{2}, NO, and O_{3}. The possible intensities of the IR emissions observable in laboratories and in nature are estimated. The acceleration process of the electrons in the pre-breakdown electrical field before its adhesion to the molecules is analyzed. For daytime conditions, modifications of the adsorption spectra of the scattered solar emissions are studied; for nighttime, variations of emission spectra may be used for the analysis.
Nonparametric Inference for Periodic Sequences
Sun, Ying
2012-02-01
This article proposes a nonparametric method for estimating the period and values of a periodic sequence when the data are evenly spaced in time. The period is estimated by a "leave-out-one-cycle" version of cross-validation (CV) and complements the periodogram, a widely used tool for period estimation. The CV method is computationally simple and implicitly penalizes multiples of the smallest period, leading to a "virtually" consistent estimator of integer periods. This estimator is investigated both theoretically and by simulation.We also propose a nonparametric test of the null hypothesis that the data have constantmean against the alternative that the sequence of means is periodic. Finally, our methodology is demonstrated on three well-known time series: the sunspots and lynx trapping data, and the El Niño series of sea surface temperatures. © 2012 American Statistical Association and the American Society for Quality.
Decompounding random sums: A nonparametric approach
DEFF Research Database (Denmark)
Hansen, Martin Bøgsted; Pitts, Susan M.
Observations from sums of random variables with a random number of summands, known as random, compound or stopped sums arise within many areas of engineering and science. Quite often it is desirable to infer properties of the distribution of the terms in the random sum. In the present paper we...... review a number of applications and consider the nonlinear inverse problem of inferring the cumulative distribution function of the components in the random sum. We review the existing literature on non-parametric approaches to the problem. The models amenable to the analysis are generalized considerably...
Spectral analysis methods for vehicle interior vibro-acoustics identification
Hosseini Fouladi, Mohammad; Nor, Mohd. Jailani Mohd.; Ariffin, Ahmad Kamal
2009-02-01
Noise has various effects on comfort, performance and health of human. Sound are analysed by human brain based on the frequencies and amplitudes. In a dynamic system, transmission of sound and vibrations depend on frequency and direction of the input motion and characteristics of the output. It is imperative that automotive manufacturers invest a lot of effort and money to improve and enhance the vibro-acoustics performance of their products. The enhancement effort may be very difficult and time-consuming if one relies only on 'trial and error' method without prior knowledge about the sources itself. Complex noise inside a vehicle cabin originated from various sources and travel through many pathways. First stage of sound quality refinement is to find the source. It is vital for automotive engineers to identify the dominant noise sources such as engine noise, exhaust noise and noise due to vibration transmission inside of vehicle. The purpose of this paper is to find the vibro-acoustical sources of noise in a passenger vehicle compartment. The implementation of spectral analysis method is much faster than the 'trial and error' methods in which, parts should be separated to measure the transfer functions. Also by using spectral analysis method, signals can be recorded in real operational conditions which conduce to more consistent results. A multi-channel analyser is utilised to measure and record the vibro-acoustical signals. Computational algorithms are also employed to identify contribution of various sources towards the measured interior signal. These achievements can be utilised to detect, control and optimise interior noise performance of road transport vehicles.
Nonparametric predictive inference in reliability
International Nuclear Information System (INIS)
Coolen, F.P.A.; Coolen-Schrijner, P.; Yan, K.J.
2002-01-01
We introduce a recently developed statistical approach, called nonparametric predictive inference (NPI), to reliability. Bounds for the survival function for a future observation are presented. We illustrate how NPI can deal with right-censored data, and discuss aspects of competing risks. We present possible applications of NPI for Bernoulli data, and we briefly outline applications of NPI for replacement decisions. The emphasis is on introduction and illustration of NPI in reliability contexts, detailed mathematical justifications are presented elsewhere
Czech Academy of Sciences Publication Activity Database
Barseghyan, Diana; Exner, Pavel; Khrabustovskyi, A.; Tater, Miloš
2016-01-01
Roč. 49, č. 16 (2016), s. 165302 ISSN 1751-8113 R&D Projects: GA ČR(CZ) GA14-06818S Institutional support: RVO:61389005 Keywords : Schrodinger operator * eigenvalue estimates * spectral transition Subject RIV: BE - Theoretical Physics Impact factor: 1.857, year: 2016
Hayden, W. L.; Robinson, L. H.
1972-01-01
Spectral analyses of angle-modulated communication systems is studied by: (1) performing a literature survey of candidate power spectrum computational techniques, determining the computational requirements, and formulating a mathematical model satisfying these requirements; (2) implementing the model on UNIVAC 1230 digital computer as the Spectral Analysis Program (SAP); and (3) developing the hardware specifications for a data acquisition system which will acquire an input modulating signal for SAP. The SAP computational technique uses extended fast Fourier transform and represents a generalized approach for simple and complex modulating signals.
Analysis of cirrus cloud spectral signatures in the far infrared
International Nuclear Information System (INIS)
Maestri, T.; Rizzi, R.; Tosi, E.; Veglio, P.; Palchetti, L.; Bianchini, G.; Di Girolamo, P.; Masiello, G.; Serio, C.; Summa, D.
2014-01-01
This paper analyses high spectral resolution downwelling radiance measurements in the far infrared in the presence of cirrus clouds taken by the REFIR-PAD interferometer, deployed at 3500 m above the sea level at the Testa Grigia station (Italy), during the Earth COoling by WAter vapouR emission (ECOWAR) campaign. Atmospheric state and cloud geometry are characterised by the co-located millimeter-wave spectrometer GBMS and by radiosonde profile data, an interferometer (I-BEST) and a Raman lidar system deployed at a nearby location (Cervinia). Cloud optical depth and effective diameter are retrieved from REFIR-PAD data using a limited number of channels in the 820–960 cm −1 interval. The retrieved cloud parameters are the input data for simulations covering the 250–1100 cm −1 band in order to test our ability to reproduce the REFIR-PAD spectra in the presence of ice clouds. Inverse and forward simulations are based on the same radiative transfer code. A priori information concerning cloud ice vertical distribution is used to better constrain the simulation scheme and an analysis of the degree of approximation of the phase function within the radiative transfer codes is performed to define the accuracy of computations. Simulation-data residuals over the REFIR-PAD spectral interval show an excellent agreement in the window region, but values are larger than total measurement uncertainties in the far infrared. Possible causes are investigated. It is shown that the uncertainties related to the water vapour and temperature profiles are of the same order as the sensitivity to the a priori assumption on particle habits for an up-looking configuration. In case of a down-looking configuration, errors due to possible incorrect description of the water vapour profile would be drastically reduced. - Highlights: • We analyze down-welling spectral radiances in the far infrared (FIR) spectrum. • Discuss the scattering in the fir and the ice crystals phase function
Comprehensive spectral analysis of Cyg X-1 using RXTE data
International Nuclear Information System (INIS)
Shahid, Rizwan; Jaaffrey, S. N. A.; Misra, Ranjeev
2012-01-01
We analyze a large number (> 500) of pointed Rossi X-Ray Timing Explorer (RXTE) observations of Cyg X-1 and model the spectrum of each one. A subset of the observations for which there is a simultaneous reliable measure of the hardness ratio by the All Sky Monitor shows that the sample covers nearly all the spectral shapes of Cyg X-1. Each observation is fitted with a generic empirical model consisting of a disk black body spectrum, a Comptonized component whose input photon shape is the same as the disk emission, a Gaussian to represent the iron line and a reflection feature. The relative strength, width of the iron line and the reflection parameter are in general correlated with the high energy photon spectral index Γ. This is broadly consistent with a geometry where for the hard state (low Γ ∼ 1.7) there is a hot inner Comptonizing region surrounded by a truncated cold disk. The inner edge of the disk moves inwards as the source becomes softer till finally in the soft state (high Γ > 2.2) the disk fills the inner region and active regions above the disk produce the Comptonized component. However, the reflection parameter shows non-monotonic behavior near the transition region (Γ ∼ 2), which suggests a more complex geometry or physical state of the reflector. In addition, the inner disk temperature, during the hard state, is on average higher than in the soft one, albeit with large scatter. These inconsistencies could be due to limitations in the data and the empirical model used to fit them. The flux of each spectral component is well correlated with Γ, which shows that unlike some other black hole systems, Cyg X-1 does not show any hysteresis behavior. In the soft state, the flux of the Comptonized component is always similar to the disk one, which confirms that the ultra-soft state (seen in other brighter black hole systems) is not exhibited by Cyg X-1. The rapid variation of the Compton amplification factor with Γ naturally explains the absence of
Chebyshev super spectral viscosity method for water hammer analysis
Directory of Open Access Journals (Sweden)
Hongyu Chen
2013-09-01
Full Text Available In this paper, a new fast and efficient algorithm, Chebyshev super spectral viscosity (SSV method, is introduced to solve the water hammer equations. Compared with standard spectral method, the method's advantage essentially consists in adding a super spectral viscosity to the equations for the high wave numbers of the numerical solution. It can stabilize the numerical oscillation (Gibbs phenomenon and improve the computational efficiency while discontinuities appear in the solution. Results obtained from the Chebyshev super spectral viscosity method exhibit greater consistency with conventional water hammer calculations. It shows that this new numerical method offers an alternative way to investigate the behavior of the water hammer in propellant pipelines.
Spectral analysis for evaluation of myocardial tracers for medical imaging
International Nuclear Information System (INIS)
Huesman, Ronald H.; Reutter, Bryan W.; Marshall, Robert C.
2000-01-01
Kinetic analysis of dynamic tracer data is performed with the goal of evaluating myocardial radiotracers for cardiac nuclear medicine imaging. Data from experiments utilizing the isolated rabbit heart model are acquired by sampling the venous blood after introduction of a tracer of interest and a reference tracer. We have taken the approach that the kinetics are properly characterized by an impulse response function which describes the difference between the reference molecule (which does not leave the vasculature) and the molecule of interest which is transported across the capillary boundary and is made available to the cell. Using this formalism we can model the appearance of the tracer of interest in the venous output of the heart as a convolution of the appearance of the reference tracer with the impulse response. In this work we parameterize the impulse response function as the sum of a large number of exponential functions whose predetermined decay constants form a spectrum, and each is required only to have a nonnegative coefficient. This approach, called spectral analysis, has the advantage that it allows conventional compartmental analysis without prior knowledge of the number of compartments which the physiology may require or which the data will support
Spectral Unmixing Analysis of Time Series Landsat 8 Images
Zhuo, R.; Xu, L.; Peng, J.; Chen, Y.
2018-05-01
Temporal analysis of Landsat 8 images opens up new opportunities in the unmixing procedure. Although spectral analysis of time series Landsat imagery has its own advantage, it has rarely been studied. Nevertheless, using the temporal information can provide improved unmixing performance when compared to independent image analyses. Moreover, different land cover types may demonstrate different temporal patterns, which can aid the discrimination of different natures. Therefore, this letter presents time series K-P-Means, a new solution to the problem of unmixing time series Landsat imagery. The proposed approach is to obtain the "purified" pixels in order to achieve optimal unmixing performance. The vertex component analysis (VCA) is used to extract endmembers for endmember initialization. First, nonnegative least square (NNLS) is used to estimate abundance maps by using the endmember. Then, the estimated endmember is the mean value of "purified" pixels, which is the residual of the mixed pixel after excluding the contribution of all nondominant endmembers. Assembling two main steps (abundance estimation and endmember update) into the iterative optimization framework generates the complete algorithm. Experiments using both simulated and real Landsat 8 images show that the proposed "joint unmixing" approach provides more accurate endmember and abundance estimation results compared with "separate unmixing" approach.
Spectral analysis, death and coronary anatomy following cardiac catheterisation.
Moore, Roger K G; Newall, Nick; Groves, David G; Barlow, Pauline E; Stables, Rodney H; Jackson, Mark; Ramsdale, David R
2007-05-16
To establish the associations and prognostic utility of angiographic, clinical and HRV parameters in a large cohort of patients undergoing diagnostic cardiac catheterisation (CC). Patients undergoing CC as elective day cases were enrolled at a single tertiary center from September 2001 to January 2003. Patient data, serum biochemistry, current drug therapy, catheter reports and five minute high resolution electrocardiograph (ECG) recordings were prospectively recorded and validated in an electronic archive. ECG recordings were used to generate time domain (SDNN (standard deviation of NN intervals)) and spectral HRV parameters (low frequency (LF) and high frequency (HF) power). Significant associations between dichotomized HRV variables and covariates were investigated using binary logistic regression. The independent prognostic ability of clinical markers was evaluated using the Cox proportional hazard model. 841 consecutive consenting patients of mean age 61+/-10 years were recruited into the study with a mean follow-up period of 690+/-436 days. In multivariate analysis decreasing LF spectral power was independently associated with proximal right coronary stenosis OR (odds ratio)=1.65 (95% CI=1.16-2.36), P=0.006 and to all cause mortality OR=5.01 (95% CI=1.47-17.01), P=0.010. Increasing LF power was also independently associated with normal coronary angiograms in patients investigated suspected coronary disease without a confirmed prior history of a coronary ischaemic event OR=2.16 (95% CI=1.26-3.73), P=0.002. Reduced LF power independently predicts all cause mortality in a large cohort of patients receiving medical therapy after elective CC. LF power was also independently associated with >75% proximal RCA stenosis.
Directory of Open Access Journals (Sweden)
Steven M Carr
-stepping-stone biogeographic models, but not a simple 1-step trans-Atlantic model. Plots of the cumulative pairwise sequence difference curves among seals in each of the four populations provide continuous proxies for phylogenetic diversification within each. Non-parametric Kolmogorov-Smirnov (K-S tests of maximum pairwise differences between these curves indicates that the Greenland Sea population has a markedly younger phylogenetic structure than either the White Sea population or the two Northwest Atlantic populations, which are of intermediate age and homogeneous structure. The Monte Carlo and K-S assessments provide sensitive quantitative tests of within-species mitogenomic phylogeography. This is the first study to indicate that the White Sea and Greenland Sea populations have different population genetic histories. The analysis supports the hypothesis that Harp Seals comprises three genetically distinguishable breeding populations, in the White Sea, Greenland Sea, and Northwest Atlantic. Implications for an ice-dependent species during ongoing climate change are discussed.
Non-parametric smoothing of experimental data
International Nuclear Information System (INIS)
Kuketayev, A.T.; Pen'kov, F.M.
2007-01-01
Full text: Rapid processing of experimental data samples in nuclear physics often requires differentiation in order to find extrema. Therefore, even at the preliminary stage of data analysis, a range of noise reduction methods are used to smooth experimental data. There are many non-parametric smoothing techniques: interval averages, moving averages, exponential smoothing, etc. Nevertheless, it is more common to use a priori information about the behavior of the experimental curve in order to construct smoothing schemes based on the least squares techniques. The latter methodology's advantage is that the area under the curve can be preserved, which is equivalent to conservation of total speed of counting. The disadvantages of this approach include the lack of a priori information. For example, very often the sums of undifferentiated (by a detector) peaks are replaced with one peak during the processing of data, introducing uncontrolled errors in the determination of the physical quantities. The problem is solvable only by having experienced personnel, whose skills are much greater than the challenge. We propose a set of non-parametric techniques, which allows the use of any additional information on the nature of experimental dependence. The method is based on a construction of a functional, which includes both experimental data and a priori information. Minimum of this functional is reached on a non-parametric smoothed curve. Euler (Lagrange) differential equations are constructed for these curves; then their solutions are obtained analytically or numerically. The proposed approach allows for automated processing of nuclear physics data, eliminating the need for highly skilled laboratory personnel. Pursuant to the proposed approach is the possibility to obtain smoothing curves in a given confidence interval, e.g. according to the χ 2 distribution. This approach is applicable when constructing smooth solutions of ill-posed problems, in particular when solving
Spectral analysis of linear relations and degenerate operator semigroups
International Nuclear Information System (INIS)
Baskakov, A G; Chernyshov, K I
2002-01-01
Several problems of the spectral theory of linear relations in Banach spaces are considered. Linear differential inclusions in a Banach space are studied. The construction of the phase space and solutions is carried out with the help of the spectral theory of linear relations, ergodic theorems, and degenerate operator semigroups
Spectral Efficiency Analysis for Multicarrier Based 4G Systems
DEFF Research Database (Denmark)
Silva, Nuno; Rahman, Muhammad Imadur; Frederiksen, Flemming Bjerge
2006-01-01
In this paper, a spectral efficiency definition is proposed. Spectral efficiency for multicarrier based multiaccess techniques, such as OFDMA, MC-CDMA and OFDMA-CDM, is analyzed. Simulations for different indoor and outdoor scenarios are carried out. Based on the simulations, we have discussed ho...
Evaluation of abrasive waterjet produced titan surfaces topography by spectral analysis techniques
Directory of Open Access Journals (Sweden)
D. Kozak
2012-01-01
Full Text Available Experimental study of a titan grade 2 surface topography prepared by abrasive waterjet cutting is performed using methods of the spectral analysis. Topographic data are acquired by means of the optical profilometr MicroProf®FRT. Estimation of the areal power spectral density of the studied surface is carried out using the periodogram method combined with the Welch´s method. Attention is paid to a structure of the areal power spectral density, which is characterized by means of the angular power spectral density. This structure of the areal spectral density is linked to the fine texture of the surface studied.
Nonparametric identification of copula structures
Li, Bo
2013-06-01
We propose a unified framework for testing a variety of assumptions commonly made about the structure of copulas, including symmetry, radial symmetry, joint symmetry, associativity and Archimedeanity, and max-stability. Our test is nonparametric and based on the asymptotic distribution of the empirical copula process.We perform simulation experiments to evaluate our test and conclude that our method is reliable and powerful for assessing common assumptions on the structure of copulas, particularly when the sample size is moderately large. We illustrate our testing approach on two datasets. © 2013 American Statistical Association.
Application of nonparametric statistic method for DNBR limit calculation
International Nuclear Information System (INIS)
Dong Bo; Kuang Bo; Zhu Xuenong
2013-01-01
Background: Nonparametric statistical method is a kind of statistical inference method not depending on a certain distribution; it calculates the tolerance limits under certain probability level and confidence through sampling methods. The DNBR margin is one important parameter of NPP design, which presents the safety level of NPP. Purpose and Methods: This paper uses nonparametric statistical method basing on Wilks formula and VIPER-01 subchannel analysis code to calculate the DNBR design limits (DL) of 300 MW NPP (Nuclear Power Plant) during the complete loss of flow accident, simultaneously compared with the DL of DNBR through means of ITDP to get certain DNBR margin. Results: The results indicate that this method can gain 2.96% DNBR margin more than that obtained by ITDP methodology. Conclusions: Because of the reduction of the conservation during analysis process, the nonparametric statistical method can provide greater DNBR margin and the increase of DNBR margin is benefited for the upgrading of core refuel scheme. (authors)
Comparing parametric and nonparametric regression methods for panel data
DEFF Research Database (Denmark)
Czekaj, Tomasz Gerard; Henningsen, Arne
We investigate and compare the suitability of parametric and non-parametric stochastic regression methods for analysing production technologies and the optimal firm size. Our theoretical analysis shows that the most commonly used functional forms in empirical production analysis, Cobb......-Douglas and Translog, are unsuitable for analysing the optimal firm size. We show that the Translog functional form implies an implausible linear relationship between the (logarithmic) firm size and the elasticity of scale, where the slope is artificially related to the substitutability between the inputs....... The practical applicability of the parametric and non-parametric regression methods is scrutinised and compared by an empirical example: we analyse the production technology and investigate the optimal size of Polish crop farms based on a firm-level balanced panel data set. A nonparametric specification test...
Spectral analysis of the gravity and topography of Mars
Bills, Bruce G.; Frey, Herbert V.; Kiefer, Walter S.; Nerem, R. Steven; Zuber, Maria T.
1993-01-01
New spherical harmonic models of the gravity and topography of Mars place important constraints on the structure and dynamics of the interior. The gravity and topography models are significantly phase coherent for harmonic degrees n less than 30 (wavelengths greater than 700 km). Loss of coherence below that wavelength is presumably due to inadequacies of the models, rather than a change in behavior of the planet. The gravity/topography admittance reveals two very different spectral domains: for n greater than 4, a simple Airy compensation model, with mean depth of 100 km, faithfully represents the observed pattern; for degrees 2 and 3, the effective compensation depths are 1400 and 550 km, respectively, strongly arguing for dynamic compensation at those wavelengths. The gravity model has been derived from a reanalysis of the tracking data for Mariner 9 and the Viking Orbiters, The topography model was derived by harmonic analysis of the USGS digital elevation model of Mars. Before comparing gravity and topography for internal structure inferences, we must ensure that both are consistently referenced to a hydrostatic datum. For the gravity, this involves removal of hydrostatic components of the even degree zonal coefficients. For the topography, it involves adding the degree 4 equipotential reference surface, to get spherically referenced values, and then subtracting the full degree 50 equipotential. Variance spectra and phase coherence of orthometric heights and gravity anomalies are addressed.
Spectral analysis of HIV seropositivity among migrant workers entering Kuwait
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Mohammad Hameed GHH
2008-03-01
Full Text Available Abstract Background There is paucity of published data on human immunodeficiency virus (HIV seroprevalence among migrant workers entering Middle-East particularly Kuwait. We took advantage of the routine screening of migrants for HIV infection, upon arrival in Kuwait from the areas with high HIV prevalence, to 1 estimate the HIV seroprevalence among migrant workers entering Kuwait and to 2 ascertain if any significant time trend or changes had occurred in HIV seroprevalence among these migrants over the study period. Methods The monthly aggregates of daily number of migrant workers tested and number of HIV seropositive were used to generate the monthly series of proportions of HIV seropositive (per 100,000 migrants over a period of 120 months from January 1, 1997 to December 31, 2006. We carried out spectral analysis of these time series data on monthly proportions (per 100,000 of HIV seropositive migrants. Results Overall HIV seroprevalence (per 100,000 among the migrants was 21 (494/2328582 (95% CI: 19 -23, ranging from 11 (95% CI: 8 – 16 in 2003 to 31 (95% CI: 24 -41 in 1998. There was no discernable pattern in the year-specific proportions of HIV seropositive migrants up to 2003; in subsequent years there was a slight but consistent increase in the proportions of HIV seropositive migrants. However, the Mann-Kendall test showed non-significant (P = 0.741 trend in de-seasonalized data series of proportions of HIV seropositive migrants. The spectral density had a statistically significant (P = 0.03 peak located at a frequency (radians 2.4, which corresponds to a regular cycle of three-month duration in this study. Auto-correlation function did not show any significant seasonality (correlation coefficient at lag 12 = – 0.025, P = 0.575. Conclusion During the study period, overall a low HIV seroprevalence (0.021% was recorded. Towards the end of the study, a slight but non-significant upward trend in the proportions of HIV seropositive
Studying soil properties using visible and near infrared spectral analysis
Moretti, S.; Garfagnoli, F.; Innocenti, L.; Chiarantini, L.
2009-04-01
This research is carried out inside the DIGISOIL Project, whose purposes are the integration and improvement of in situ and proximal measurement technologies, for the assessment of soil properties and soil degradation indicators, going form the sensing technologies to their integration and their application in digital soil mapping. The study area is located in the Virginio river basin, about 30 km south of Firenze, in the Chianti area, where soils with agricultural suitability have a high economic value connected to the production of internationally famous wines and olive oils. The most common soil threats, such as erosion and landslide, may determine huge economic losses, which must be considered in farming management practices. This basin has a length of about 23 km for a basin area of around 60,3 Km2. Geological formations outcropping in the area are Pliocene to Pleistocene marine and lacustrine sediments in beds with almost horizontal bedding. Vineyards, olive groves and annual crops are the main types of land use. A typical Mediterranean climate prevails with a dry summer followed by intense and sometimes prolonged rainfall in autumn, decreasing in winter. In this study, three types of VNIR and SWIR techniques, operating at different scales and in different environments (laboratory spectroscopy, portable field spectroscopy) are integrated to rapidly quantify various soil characteristics, in order to acquire data for assessing the risk of occurrence for typically agricultural practice-related soil threats (swelling, compaction, erosion, landslides, organic matter decline, ect.) and to collect ground data in order to build up a spectral library to be used in image analysis from air-borne and satellite sensors. Difficulties encountered in imaging spectroscopy, such as influence of measurements conditions, atmospheric attenuation, scene dependency and sampling representation are investigated and mathematical pre-treatments, using proper algorithms, are applied and
Bistable flow spectral analysis. Repercussions on jet pumps
International Nuclear Information System (INIS)
Gavilan Moreno, C.J.
2011-01-01
Highlights: → The most important thing in this paper, is the spectral characterization of the bistable flow in a Nuclear Power Plant. → This paper goes deeper in the effect of the bistable flow over the jet pump and the induced vibrations. → The jet pump frequencies are very close to natural jet pump frequencies, in the 3rd and 6th mode. - Abstract: There have been many attempts at characterizing and predicting bistable flow in boiling water reactors (BWRs). Nevertheless, in most cases the results have only managed to develop models that analytically reproduce the phenomenon (). Modeling has been forensic in all cases, while the capacity of the model focus on determining the exclusion areas on the recirculation flow map. The bistability process is known by its effects given there is no clear definition of its causal process. In the 1980s, Hitachi technicians () managed to reproduce bistable flow in the laboratory by means of pipe geometry, similar to that which is found in recirculation loops. The result was that the low flow pattern is formed by the appearance of a quasi stationary, helicoidal vortex in the recirculation collector's branches. This vortex creates greater frictional losses than regions without vortices, at the same discharge pressure. Neither the behavior nor the dynamics of these vortices were characterized in this paper. The aim of this paper is to characterize these vortices in such a way as to enable them to provide their own frequencies and their later effect on the jet pumps. The methodology used in this study is similar to the one used previously when analyzing the bistable flow in tube arrays with cross flow (). The method employed makes use of the power spectral density function. What differs is the field of application. We will analyze a Loop B with a bistable flow and compare the high and low flow situations. The same analysis will also be carried out on the loop that has not developed the bistable flow (Loop A) at the same moments
Spectral Analysis and Dirichlet Forms on Barlow-Evans Fractals
Steinhurst, Benjamin; Teplyaev, Alexander
2012-01-01
We show that if a Barlow-Evans Markov process on a vermiculated space is symmetric, then one can study the spectral properties of the corresponding Laplacian using projective limits. For some examples, such as the Laakso spaces and a Spierpinski P\\^ate \\`a Choux, one can develop a complete spectral theory, including the eigenfunction expansions that are analogous to Fourier series. Also, one can construct connected fractal spaces isospectral to the fractal strings of Lapidus and van Frankenhu...
Use of new spectral analysis methods in gamma spectra deconvolution
International Nuclear Information System (INIS)
Pinault, J.L.
1991-01-01
A general deconvolution method applicable to X and gamma ray spectrometry is proposed. Using new spectral analysis methods, it is applied to an actual case: the accurate on-line analysis of three elements (Ca, Si, Fe) in a cement plant using neutron capture gamma rays. Neutrons are provided by a low activity (5 μg) 252 Cf source; the detector is a BGO 3 in.x8 in. scintillator. The principle of the methods rests on the Fourier transform of the spectrum. The search for peaks and determination of peak areas are worked out in the Fourier representation, which enables separation of background and peaks and very efficiently discriminates peaks, or elements represented by several peaks. First the spectrum is transformed so that in the new representation the full width at half maximum (FWHM) is independent of energy. Thus, the spectrum is arranged symmetrically and transformed into the Fourier representation. The latter is multiplied by a function in order to transform original Gaussian into Lorentzian peaks. An autoregressive filter is calculated, leading to a characteristic polynomial whose complex roots represent both the location and the width of each peak, provided that the absolute value is lower than unit. The amplitude of each component (the area of each peak or the sum of areas of peaks characterizing an element) is fitted by the weighted least squares method, taking into account that errors in spectra are independent and follow a Poisson law. Very accurate results are obtained, which would be hard to achieve by other methods. The DECO FORTRAN code has been developed for compatible PC microcomputers. Some features of the code are given. (orig.)
PIXEL ANALYSIS OF PHOTOSPHERIC SPECTRAL DATA. I. PLASMA DYNAMICS
Energy Technology Data Exchange (ETDEWEB)
Rasca, Anthony P.; Chen, James [Plasma Physics Division, U.S. Naval Research Laboratory, Washington, DC 20375 (United States); Pevtsov, Alexei A., E-mail: anthony.rasca.ctr@nrl.navy.mil [National Solar Observatory, Sunspot, NM 88349 (United States)
2016-11-20
Recent observations of the photosphere using high spatial and temporal resolution show small dynamic features at or below the current resolving limits. A new pixel dynamics method has been developed to analyze spectral profiles and quantify changes in line displacement, width, asymmetry, and peakedness of photospheric absorption lines. The algorithm evaluates variations of line profile properties in each pixel and determines the statistics of such fluctuations averaged over all pixels in a given region. The method has been used to derive statistical characteristics of pixel fluctuations in observed quiet-Sun regions, an active region with no eruption, and an active region with an ongoing eruption. Using Stokes I images from the Vector Spectromagnetograph (VSM) of the Synoptic Optical Long-term Investigations of the Sun (SOLIS) telescope on 2012 March 13, variations in line width and peakedness of Fe i 6301.5 Å are shown to have a distinct spatial and temporal relationship with an M7.9 X-ray flare in NOAA 11429. This relationship is observed as stationary and contiguous patches of pixels adjacent to a sunspot exhibiting intense flattening in the line profile and line-center displacement as the X-ray flare approaches peak intensity, which is not present in area scans of the non-eruptive active region. The analysis of pixel dynamics allows one to extract quantitative information on differences in plasma dynamics on sub-pixel scales in these photospheric regions. The analysis can be extended to include the Stokes parameters and study signatures of vector components of magnetic fields and coupled plasma properties.
A contingency table approach to nonparametric testing
Rayner, JCW
2000-01-01
Most texts on nonparametric techniques concentrate on location and linear-linear (correlation) tests, with less emphasis on dispersion effects and linear-quadratic tests. Tests for higher moment effects are virtually ignored. Using a fresh approach, A Contingency Table Approach to Nonparametric Testing unifies and extends the popular, standard tests by linking them to tests based on models for data that can be presented in contingency tables.This approach unifies popular nonparametric statistical inference and makes the traditional, most commonly performed nonparametric analyses much more comp
Hurricane coastal flood analysis using multispectral spectral images
Ogashawara, I.; Ferreira, C.; Curtarelli, M. P.
2013-12-01
Flooding is one of the main hazards caused by extreme events such as hurricanes and tropical storms. Therefore, flood maps are a crucial tool to support policy makers, environmental managers and other government agencies for emergency management, disaster recovery and risk reduction planning. However traditional flood mapping methods rely heavily on the interpolation of hydrodynamic models results, and most recently, the extensive collection of field data. These methods are time-consuming, labor intensive, and costly. Efficient and fast response alternative methods should be developed in order to improve flood mapping, and remote sensing has been proved as a valuable tool for this application. Our goal in this paper is to introduce a novel technique based on spectral analysis in order to aggregate knowledge and information to map coastal flood areas. For this purpose we used the Normalized Diference Water Index (NDWI) which was derived from two the medium resolution LANDSAT/TM 5 surface reflectance product from the LANDSAT climate data record (CDR). This product is generated from specialized software called Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS). We used the surface reflectance products acquired before and after the passage of Hurricane Ike for East Texas in September of 2008. We used as end member a classification of estimated flooded area based on the United States Geological Survey (USGS) mobile storm surge network that was deployed for Hurricane Ike. We used a dataset which consisted of 59 water levels recording stations. The estimated flooded area was delineated interpolating the maximum surge in each location using a spline with barriers method with high tension and a 30 meter Digital Elevation Model (DEM) from the National Elevation Dataset (NED). Our results showed that, in the flooded area, the NDWI values decreased after the hurricane landfall on average from 0.38 to 0.18 and the median value decreased from 0.36 to 0.2. However
Dichotomous classification of black-colored metal using spectral analysis
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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.
Analysis of wheezes using wavelet higher order spectral features.
Taplidou, Styliani A; Hadjileontiadis, Leontios J
2010-07-01
Wheezes are musical breath sounds, which usually imply an existing pulmonary obstruction, such as asthma and chronic obstructive pulmonary disease (COPD). Although many studies have addressed the problem of wheeze detection, a limited number of scientific works has focused in the analysis of wheeze characteristics, and in particular, their time-varying nonlinear characteristics. In this study, an effort is made to reveal and statistically analyze the nonlinear characteristics of wheezes and their evolution over time, as they are reflected in the quadratic phase coupling of their harmonics. To this end, the continuous wavelet transform (CWT) is used in combination with third-order spectra to define the analysis domain, where the nonlinear interactions of the harmonics of wheezes and their time variations are revealed by incorporating instantaneous wavelet bispectrum and bicoherence, which provide with the instantaneous biamplitude and biphase curves. Based on this nonlinear information pool, a set of 23 features is proposed for the nonlinear analysis of wheezes. Two complementary perspectives, i.e., general and detailed, related to average performance and to localities, respectively, were used in the construction of the feature set, in order to embed trends and local behaviors, respectively, seen in the nonlinear interaction of the harmonic elements of wheezes over time. The proposed feature set was evaluated on a dataset of wheezes, acquired from adult patients with diagnosed asthma and COPD from a lung sound database. The statistical evaluation of the feature set revealed discrimination ability between the two pathologies for all data subgroupings. In particular, when the total breathing cycle was examined, all 23 features, but one, showed statistically significant difference between the COPD and asthma pathologies, whereas for the subgroupings of inspiratory and expiratory phases, 18 out of 23 and 22 out of 23 features exhibited discrimination power, respectively
Cui, Qian; Shi, Jiancheng; Xu, Yuanliu
2011-12-01
Water is the basic needs for human society, and the determining factor of stability of ecosystem as well. There are lots of lakes on Tibet Plateau, which will lead to flood and mudslide when the water expands sharply. At present, water area is extracted from TM or SPOT data for their high spatial resolution; however, their temporal resolution is insufficient. MODIS data have high temporal resolution and broad coverage. So it is valuable resource for detecting the change of water area. Because of its low spatial resolution, mixed-pixels are common. In this paper, four spectral libraries are built using MOD09A1 product, based on that, water body is extracted in sub-pixels utilizing Multiple Endmembers Spectral Mixture Analysis (MESMA) using MODIS daily reflectance data MOD09GA. The unmixed result is comparing with contemporaneous TM data and it is proved that this method has high accuracy.
Rotating shadowband radiometer development and analysis of spectral shortwave data
Energy Technology Data Exchange (ETDEWEB)
Michalsky, J.; Harrison, L.; Min, Q. [State Univ. of New York, Albany, NY (United States)] [and others
1996-04-01
Our goals in the Atmospheric Radiation Measurement (ARM) Program are improved measurements of spectral shortwave radiation and improved techniques for the retrieval of climatologically sensitive parameters. The multifilter rotating shadowband radiometer (MFRSR) that was developed during the first years of the ARM program has become a workhorse at the Southern Great Plains (SGP) Cloud and Radiation Testbed (CART) site, and it is widely deployed in other climate programs. We have spent most of our effort this year developing techniques to retrieve column aerosol, water vapor, and ozone from direct beam spectral measurements of the MFRSR. Additionally, we have had some success in calculating shortwave surface diffuse spectral irradiance. Using the surface albedo and the global irradiance, we have calculated cloud optical depths. From cloud optical depth and liquid water measured with the microwave radiometer, we have calculated effective liquid cloud particle radii. The rest of the text will provide some detail regarding each of these efforts.
Spectral analysis of the turbulent mixing of two fluids
Energy Technology Data Exchange (ETDEWEB)
Steinkamp, M.J.
1996-02-01
The authors describe a spectral approach to the investigation of fluid instability, generalized turbulence, and the interpenetration of fluids across an interface. The technique also applies to a single fluid with large variations in density. Departures of fluctuating velocity components from the local mean are far subsonic, but the mean Mach number can be large. Validity of the description is demonstrated by comparisons with experiments on turbulent mixing due to the late stages of Rayleigh-Taylor instability, when the dynamics become approximately self-similar in response to a constant body force. Generic forms for anisotropic spectral structure are described and used as a basis for deriving spectrally integrated moment equations that can be incorporated into computer codes for scientific and engineering analyses.
Two-body threshold spectral analysis, the critical case
DEFF Research Database (Denmark)
Skibsted, Erik; Wang, Xue Ping
We study in dimension $d\\geq2$ low-energy spectral and scattering asymptotics for two-body $d$-dimensional Schrödinger operators with a radially symmetric potential falling off like $-\\gamma r^{-2},\\;\\gamma>0$. We consider angular momentum sectors, labelled by $l=0,1,\\dots$, for which $\\gamma......>(l+d/2 -1)^2$. In each such sector the reduced Schrödinger operator has infinitely many negative eigenvalues accumulating at zero. We show that the resolvent has a non-trivial oscillatory behaviour as the spectral parameter approaches zero in cones bounded away from the negative half-axis, and we derive...
Parametric vs. Nonparametric Regression Modelling within Clinical Decision Support
Czech Academy of Sciences Publication Activity Database
Kalina, Jan; Zvárová, Jana
2017-01-01
Roč. 5, č. 1 (2017), s. 21-27 ISSN 1805-8698 R&D Projects: GA ČR GA17-01251S Institutional support: RVO:67985807 Keywords : decision support systems * decision rules * statistical analysis * nonparametric regression Subject RIV: IN - Informatics, Computer Science OBOR OECD: Statistics and probability
Non-parametric tests of productive efficiency with errors-in-variables
Kuosmanen, T.K.; Post, T.; Scholtes, S.
2007-01-01
We develop a non-parametric test of productive efficiency that accounts for errors-in-variables, following the approach of Varian. [1985. Nonparametric analysis of optimizing behavior with measurement error. Journal of Econometrics 30(1/2), 445-458]. The test is based on the general Pareto-Koopmans
Methodology for diagnosing of skin cancer on images of dermatologic spots by spectral analysis.
Guerra-Rosas, Esperanza; Álvarez-Borrego, Josué
2015-10-01
In this paper a new methodology for the diagnosing of skin cancer on images of dermatologic spots using image processing is presented. Currently skin cancer is one of the most frequent diseases in humans. This methodology is based on Fourier spectral analysis by using filters such as the classic, inverse and k-law nonlinear. The sample images were obtained by a medical specialist and a new spectral technique is developed to obtain a quantitative measurement of the complex pattern found in cancerous skin spots. Finally a spectral index is calculated to obtain a range of spectral indices defined for skin cancer. Our results show a confidence level of 95.4%.
Statistical Analysis of Spectral Properties and Prosodic Parameters of Emotional Speech
Přibil, J.; Přibilová, A.
2009-01-01
The paper addresses reflection of microintonation and spectral properties in male and female acted emotional speech. Microintonation component of speech melody is analyzed regarding its spectral and statistical parameters. According to psychological research of emotional speech, different emotions are accompanied by different spectral noise. We control its amount by spectral flatness according to which the high frequency noise is mixed in voiced frames during cepstral speech synthesis. Our experiments are aimed at statistical analysis of cepstral coefficient values and ranges of spectral flatness in three emotions (joy, sadness, anger), and a neutral state for comparison. Calculated histograms of spectral flatness distribution are visually compared and modelled by Gamma probability distribution. Histograms of cepstral coefficient distribution are evaluated and compared using skewness and kurtosis. Achieved statistical results show good correlation comparing male and female voices for all emotional states portrayed by several Czech and Slovak professional actors.
Convergence analysis of spectral element method for electromechanical devices
Curti, M.; Jansen, J.W.; Lomonova, E.A.
2017-01-01
This paper concerns the comparison of the performance of the Spectral Element Method (SEM) and the Finite Element Method (FEM) for a magnetostatic problem. The convergence of the vector magnetic potential, the magnetic flux density, and the total stored energy in the system is compared with the
Ultra-wideband spectral analysis using S2 technology
International Nuclear Information System (INIS)
Krishna Mohan, R.; Chang, T.; Tian, M.; Bekker, S.; Olson, A.; Ostrander, C.; Khallaayoun, A.; Dollinger, C.; Babbitt, W.R.; Cole, Z.; Reibel, R.R.; Merkel, K.D.; Sun, Y.; Cone, R.; Schlottau, F.; Wagner, K.H.
2007-01-01
This paper outlines the efforts to develop an ultra-wideband spectrum analyzer that takes advantage of the broad spectral response and fine spectral resolution (∼25 kHz) of spatial-spectral (S2) materials. The S2 material can process the full spectrum of broadband microwave transmissions, with adjustable time apertures (down to 100 μs) and fast update rates (up to 1 kHz). A cryogenically cooled Tm:YAG crystal that operates on microwave signals modulated onto a stabilized optical carrier at 793 nm is used as the core for the spectrum analyzer. Efforts to develop novel component technologies that enhance the performance of the system and meet the application requirements are discussed, including an end-to-end device model for parameter optimization. We discuss the characterization of new ultra-wide bandwidth S2 materials. Detection and post-processing module development including the implementation of a novel spectral recovery algorithm using field programmable gate array technology (FPGA) is also discussed
Detecting gallbladders in chicken livers using spectral analysis
DEFF Research Database (Denmark)
Jørgensen, Anders; Mølvig Jensen, Eigil; Moeslund, Thomas B.
2015-01-01
This paper presents a method for detecting gallbladders attached to chicken livers using spectral imaging. Gallbladders can contaminate good livers, making them unfit for human consumption. A data set consisting of chicken livers with and without gallbladders, has been captured using 33 wavelengths...
Ultra-wideband spectral analysis using S2 technology
Energy Technology Data Exchange (ETDEWEB)
Krishna Mohan, R. [Spectrum Lab, Montana State University, Bozeman, MT 59717 (United States)]. E-mail: krishna@spectrum.montana.edu; Chang, T. [Spectrum Lab, Montana State University, Bozeman, MT 59717 (United States); Tian, M. [Spectrum Lab, Montana State University, Bozeman, MT 59717 (United States); Department of Physics, Montana State University, Bozeman, MT 59717 (United States); Bekker, S. [Spectrum Lab, Montana State University, Bozeman, MT 59717 (United States); Olson, A. [Spectrum Lab, Montana State University, Bozeman, MT 59717 (United States); Ostrander, C. [Spectrum Lab, Montana State University, Bozeman, MT 59717 (United States); Khallaayoun, A. [Spectrum Lab, Montana State University, Bozeman, MT 59717 (United States); Dollinger, C. [Spectrum Lab, Montana State University, Bozeman, MT 59717 (United States); Babbitt, W.R. [Spectrum Lab, Montana State University, Bozeman, MT 59717 (United States); Department of Physics, Montana State University, Bozeman, MT 59717 (United States); Cole, Z. [Spectrum Lab, Montana State University, Bozeman, MT 59717 (United States); S2 Corporation, Bozeman, MT 59718 (United States); Reibel, R.R. [Spectrum Lab, Montana State University, Bozeman, MT 59717 (United States); S2 Corporation, Bozeman, MT 59718 (United States); Merkel, K.D. [Spectrum Lab, Montana State University, Bozeman, MT 59717 (United States); S2 Corporation, Bozeman, MT 59718 (United States); Sun, Y. [Department of Physics, Montana State University, Bozeman, MT 59717 (United States); Cone, R. [Department of Physics, Montana State University, Bozeman, MT 59717 (United States); Schlottau, F. [University of Colorado, Boulder, CO 80309 (United States); Wagner, K.H. [University of Colorado, Boulder, CO 80309 (United States)
2007-11-15
This paper outlines the efforts to develop an ultra-wideband spectrum analyzer that takes advantage of the broad spectral response and fine spectral resolution ({approx}25 kHz) of spatial-spectral (S2) materials. The S2 material can process the full spectrum of broadband microwave transmissions, with adjustable time apertures (down to 100 {mu}s) and fast update rates (up to 1 kHz). A cryogenically cooled Tm:YAG crystal that operates on microwave signals modulated onto a stabilized optical carrier at 793 nm is used as the core for the spectrum analyzer. Efforts to develop novel component technologies that enhance the performance of the system and meet the application requirements are discussed, including an end-to-end device model for parameter optimization. We discuss the characterization of new ultra-wide bandwidth S2 materials. Detection and post-processing module development including the implementation of a novel spectral recovery algorithm using field programmable gate array technology (FPGA) is also discussed.
Analysis of visible spectral lines in LHD helium discharge
International Nuclear Information System (INIS)
Wan, B.N.; Goto, M.; Morita, S.
1999-06-01
In this study, visible spectral lines in LHD helium discharges are analyzed and it was found that they could be well fitted with gaussian profile. The results reveal a simple mechanism of helium atom recycling. Ion temperatures were also derived from the fitting. A typical value of the ion temperature obtained was about 6 eV. (author)
Convergence analysis of spectral element method for magnetic devices
Curti, M.; Jansen, J.W.; Lomonova, E.A.
2018-01-01
This paper concerns the comparison of the performance of the Spectral Element Method (SEM) and the Finite Element Method (FEM) for modeling a magnetostatic problem. The convergence of the vector magnetic potential, the magnetic flux density, and the total stored energy in the system is compared with
Bedload transport from spectral analysis of seismic noise near rivers
Hsu, L.; Finnegan, N. J.; Brodsky, E. E.
2010-12-01
Channel change in rivers is driven by bedload sediment transport. However, the nonlinear nature of sediment transport combined with the difficulty of making direct observations in rivers at flood hinder prediction of the timing and magnitude of bedload movement. Recent studies have shown that spectral analysis of seismic noise from seismometers near rivers illustrate a correlation between the relative amplitude of high frequency (>1 Hz) seismic noise and conditions for bedload transport, presumably from the energy transferred from clast collisions with the channel. However, a previous study in the Himalayas did not contain extensive bedload transport or discharge measurements, and the correspondence of seismic noise with proxy variables such as regional hydrologic and meteorologic data was not exact. A more complete understanding of the relationship between bedload transport and seismic noise would be valuable for extending the spatial and temporal extent of bedload data. To explore the direct relationship between bedload transport and seismic noise, we examine data from several seismic stations near the Trinity River in California, where the fluvial morphodynamics and bedload rating curves have been studied extensively. We compare the relative amplitude of the ambient seismic noise with records of water discharge and sediment transport. We also examine the noise at hourly, daily, and seasonal timescales to determine other possible sources of noise. We report the influence of variables such as local river slope, adjacent geology, anthropogenic noise, and distance from the river. The results illustrate the feasibility of using existing seismic arrays to sense radiated energy from processes of bedload transport. In addition, the results can be used to design future seismic array campaigns to optimize information about bedload transport. This technique provides great spatial and temporal coverage, and can be performed where direct bedload measurements are difficult or
Automated computation of autonomous spectral submanifolds for nonlinear modal analysis
Ponsioen, Sten; Pedergnana, Tiemo; Haller, George
2018-04-01
We discuss an automated computational methodology for computing two-dimensional spectral submanifolds (SSMs) in autonomous nonlinear mechanical systems of arbitrary degrees of freedom. In our algorithm, SSMs, the smoothest nonlinear continuations of modal subspaces of the linearized system, are constructed up to arbitrary orders of accuracy, using the parameterization method. An advantage of this approach is that the construction of the SSMs does not break down when the SSM folds over its underlying spectral subspace. A further advantage is an automated a posteriori error estimation feature that enables a systematic increase in the orders of the SSM computation until the required accuracy is reached. We find that the present algorithm provides a major speed-up, relative to numerical continuation methods, in the computation of backbone curves, especially in higher-dimensional problems. We illustrate the accuracy and speed of the automated SSM algorithm on lower- and higher-dimensional mechanical systems.
Semiconductor detectors in current energy dispersive X-ray spectral analysis
Energy Technology Data Exchange (ETDEWEB)
Betin, J; Zhabin, E; Krampit, I; Smirnov, V
1980-04-01
A review is presented of the properties of semiconductor detectors and of the possibilities stemming therefrom of using the detectors in X-ray spectral analysis in industries, in logging, in ecology and environmental control, in medicine, etc.
Spectral Analysis of the Background in Ground-based, Long-slit ...
Indian Academy of Sciences (India)
1996-12-08
Dec 8, 1996 ... Spectral Analysis of the Background in Ground-based,. Long-slit .... Figure 1 plots spectra from the 2-D array, after instrumental calibration and before correction for ..... which would merit attention and a better understanding.
High-speed Vibrational Imaging and Spectral Analysis of Lipid Bodies by Compound Raman Microscopy
Slipchenko, Mikhail N.; Le, Thuc T.; Chen, Hongtao; Cheng, Ji-Xin
2009-01-01
Cells store excess energy in the form of cytoplasmic lipid droplets. At present, it is unclear how different types of fatty acids contribute to the formation of lipid-droplets. We describe a compound Raman microscope capable of both high-speed chemical imaging and quantitative spectral analysis on the same platform. We use a picosecond laser source to perform coherent Raman scattering imaging of a biological sample and confocal Raman spectral analysis at points of interest. The potential of t...
Nonparametric Bayesian Modeling of Complex Networks
DEFF Research Database (Denmark)
Schmidt, Mikkel Nørgaard; Mørup, Morten
2013-01-01
an infinite mixture model as running example, we go through the steps of deriving the model as an infinite limit of a finite parametric model, inferring the model parameters by Markov chain Monte Carlo, and checking the model?s fit and predictive performance. We explain how advanced nonparametric models......Modeling structure in complex networks using Bayesian nonparametrics makes it possible to specify flexible model structures and infer the adequate model complexity from the observed data. This article provides a gentle introduction to nonparametric Bayesian modeling of complex networks: Using...
Spectral Analysis of Certain Schrödinger Operators
Directory of Open Access Journals (Sweden)
Mourad E.H. Ismail
2012-09-01
Full Text Available The J-matrix method is extended to difference and q-difference operators and is applied to several explicit differential, difference, q-difference and second order Askey-Wilson type operators. The spectrum and the spectral measures are discussed in each case and the corresponding eigenfunction expansion is written down explicitly in most cases. In some cases we encounter new orthogonal polynomials with explicit three term recurrence relations where nothing is known about their explicit representations or orthogonality measures. Each model we analyze is a discrete quantum mechanical model in the sense of Odake and Sasaki [J. Phys. A: Math. Theor. 44 (2011, 353001, 47 pages].
Assessment of modern spectral analysis methods to improve wavenumber resolution of F-K spectra
International Nuclear Information System (INIS)
Shirley, T.E.; Laster, S.J.; Meek, R.A.
1987-01-01
The improvement in wavenumber spectra obtained by using high resolution spectral estimators is examined. Three modern spectral estimators were tested, namely the Autoregressive/Maximum Entropy (AR/ME) method, the Extended Prony method, and an eigenstructure method. They were combined with the conventional Fourier method by first transforming each trace with a Fast Fourier Transform (FFT). A high resolution spectral estimator was applied to the resulting complex spatial sequence for each frequency. The collection of wavenumber spectra thus computed comprises a hybrid f-k spectrum with high wavenumber resolution and less spectral ringing. Synthetic and real data records containing 25 traces were analyzed by using the hybrid f-k method. The results show an FFT-AR/ME f-k spectrum has noticeably better wavenumber resolution and more spectral dynamic range than conventional spectra when the number of channels is small. The observed improvement suggests the hybrid technique is potentially valuable in seismic data analysis
An Improved Spectral Analysis Method for Fatigue Damage Assessment of Details in Liquid Cargo Tanks
Zhao, Peng-yuan; Huang, Xiao-ping
2018-03-01
Errors will be caused in calculating the fatigue damages of details in liquid cargo tanks by using the traditional spectral analysis method which is based on linear system, for the nonlinear relationship between the dynamic stress and the ship acceleration. An improved spectral analysis method for the assessment of the fatigue damage in detail of a liquid cargo tank is proposed in this paper. Based on assumptions that the wave process can be simulated by summing the sinusoidal waves in different frequencies and the stress process can be simulated by summing the stress processes induced by these sinusoidal waves, the stress power spectral density (PSD) is calculated by expanding the stress processes induced by the sinusoidal waves into Fourier series and adding the amplitudes of each harmonic component with the same frequency. This analysis method can take the nonlinear relationship into consideration and the fatigue damage is then calculated based on the PSD of stress. Take an independent tank in an LNG carrier for example, the accuracy of the improved spectral analysis method is proved much better than that of the traditional spectral analysis method by comparing the calculated damage results with the results calculated by the time domain method. The proposed spectral analysis method is more accurate in calculating the fatigue damages in detail of ship liquid cargo tanks.
Nonparametric methods in actigraphy: An update
Directory of Open Access Journals (Sweden)
Bruno S.B. Gonçalves
2014-09-01
Full Text Available Circadian rhythmicity in humans has been well studied using actigraphy, a method of measuring gross motor movement. As actigraphic technology continues to evolve, it is important for data analysis to keep pace with new variables and features. Our objective is to study the behavior of two variables, interdaily stability and intradaily variability, to describe rest activity rhythm. Simulated data and actigraphy data of humans, rats, and marmosets were used in this study. We modified the method of calculation for IV and IS by modifying the time intervals of analysis. For each variable, we calculated the average value (IVm and ISm results for each time interval. Simulated data showed that (1 synchronization analysis depends on sample size, and (2 fragmentation is independent of the amplitude of the generated noise. We were able to obtain a significant difference in the fragmentation patterns of stroke patients using an IVm variable, while the variable IV60 was not identified. Rhythmic synchronization of activity and rest was significantly higher in young than adults with Parkinson׳s when using the ISM variable; however, this difference was not seen using IS60. We propose an updated format to calculate rhythmic fragmentation, including two additional optional variables. These alternative methods of nonparametric analysis aim to more precisely detect sleep–wake cycle fragmentation and synchronization.
Stellar and wind parameters of massive stars from spectral analysis
Araya, Ignacio; Curé, Michel
2017-11-01
The only way to deduce information from stars is to decode the radiation it emits in an appropriate way. Spectroscopy can solve this and derive many properties of stars. In this work we seek to derive simultaneously the stellar and wind characteristics of a wide range of massive stars. Our stellar properties encompass the effective temperature, the surface gravity, the stellar radius, the micro-turbulence velocity, the rotational velocity and the Si abundance. For wind properties we consider the mass-loss rate, the terminal velocity and the line-force parameters α, k and δ (from the line-driven wind theory). To model the data we use the radiative transport code Fastwind considering the newest hydrodynamical solutions derived with Hydwind code, which needs stellar and line-force parameters to obtain a wind solution. A grid of spectral models of massive stars is created and together with the observed spectra their physical properties are determined through spectral line fittings. These fittings provide an estimation about the line-force parameters, whose theoretical calculations are extremely complex. Furthermore, we expect to confirm that the hydrodynamical solutions obtained with a value of δ slightly larger than ~ 0.25, called δ-slow solutions, describe quite reliable the radiation line-driven winds of A and late B supergiant stars and at the same time explain disagreements between observational data and theoretical models for the Wind-Momentum Luminosity Relationship (WLR).
Embedded gamma spectrometry: new algorithms for spectral analysis
International Nuclear Information System (INIS)
Martin-Burtart, Nicolas
2012-01-01
Airborne gamma spectrometry was first used for mining prospecting. Three main families were looked for: K-40, U-238 and Th-232. The Chernobyl accident acted as a trigger and for the last fifteen years, a lot of new systems have been developed for intervention in case of nuclear accident or environmental purposes. Depending on their uses, new algorithms were developed, mainly for medium or high energy signal extraction. These spectral regions are characteristics of natural emissions (K-40, U-238 and Th-232 decay chains) and fissions products (mainly Cs-137 and Co-60). Below 400 keV, where special nuclear materials emit, these methods can still be used but are greatly imprecise. A new algorithm called 2-windows (extended to 3), was developed. It allows an accurate extraction, taking the flight altitude into account to minimize false detection. Watching radioactive materials traffic appeared with homeland security policy a few years ago. This particular use of dedicated sensors require a new type of algorithms. Before, one algorithm was very efficient for a particular nuclide or spectral region. Now, we need algorithm able to detect an anomaly wherever it is and whatever it is: industrial, medical or SNM. This work identified two families of methods working under these circumstances. Finally, anomalies have to be identified. IAEA recommend to watch around 30 radionuclides. A brand new identification algorithm was developed, using several rays per element and avoiding identifications conflicts. (author) [fr
Spectral Analysis of Chinese Medicinal Herbs Based on Delayed Luminescence
Directory of Open Access Journals (Sweden)
Jingxiang Pang
2016-01-01
Full Text Available Traditional Chinese medicine (TCM plays a critical role in healthcare; however, it lacks scientific evidence to support the multidimensional therapeutic effects. These effects are based on experience, and, to date, there is no advanced tool to evaluate these experience based effects. In the current study, Chinese herbal materials classified with different cold and heat therapeutic properties, based on Chinese medicine principles, were investigated using spectral distribution, as well as the decay probability distribution based on delayed luminescence (DL. A detection system based on ultraweak biophoton emission was developed to determine the DL decay kinetics of the cold and heat properties of Chinese herbal materials. We constructed a mathematical model to fit the experimental data and characterize the properties of Chinese medicinal herbs with different parameters. The results demonstrated that this method has good reproducibility. Moreover, there is a significant difference (p<0.05 in the spectral distribution and the decay probability distribution of Chinese herbal materials with cold and heat properties. This approach takes advantage of the comprehensive nature of DL compared with more reductionist approaches and is more consistent with TCM principles, in which the core comprises holistic views.
The spectral analysis of cyclo-non-stationary signals
Abboud, D.; Baudin, S.; Antoni, J.; Rémond, D.; Eltabach, M.; Sauvage, O.
2016-06-01
Condition monitoring of rotating machines in speed-varying conditions remains a challenging task and an active field of research. Specifically, the produced vibrations belong to a particular class of non-stationary signals called cyclo-non-stationary: although highly non-stationary, they contain hidden periodicities related to the shaft angle; the phenomenon of long term modulations is what makes them different from cyclostationary signals which are encountered under constant speed regimes. In this paper, it is shown that the optimal way of describing cyclo-non-stationary signals is jointly in the time and the angular domains. While the first domain describes the waveform characteristics related to the system dynamics, the second one reveals existing periodicities linked to the system kinematics. Therefore, a specific class of signals - coined angle-time cyclostationary is considered, expressing the angle-time interaction. Accordingly, the related spectral representations, the order-frequency spectral correlation and coherence functions are proposed and their efficiency is demonstrated on two industrial cases.
Global spectral graph wavelet signature for surface analysis of carpal bones
Masoumi, Majid; Rezaei, Mahsa; Ben Hamza, A.
2018-02-01
Quantitative shape comparison is a fundamental problem in computer vision, geometry processing and medical imaging. In this paper, we present a spectral graph wavelet approach for shape analysis of carpal bones of the human wrist. We employ spectral graph wavelets to represent the cortical surface of a carpal bone via the spectral geometric analysis of the Laplace-Beltrami operator in the discrete domain. We propose global spectral graph wavelet (GSGW) descriptor that is isometric invariant, efficient to compute, and combines the advantages of both low-pass and band-pass filters. We perform experiments on shapes of the carpal bones of ten women and ten men from a publicly-available database of wrist bones. Using one-way multivariate analysis of variance (MANOVA) and permutation testing, we show through extensive experiments that the proposed GSGW framework gives a much better performance compared to the global point signature embedding approach for comparing shapes of the carpal bones across populations.
Comparison of modal spectral and non-linear time history analysis of a piping system
International Nuclear Information System (INIS)
Gerard, R.; Aelbrecht, D.; Lafaille, J.P.
1987-01-01
A typical piping system of the discharge line of the chemical and volumetric control system, outside the containment, between the penetration and the heat exchanger, an operating power plant was analyzed using four different methods: Modal spectral analysis with 2% constant damping, modal spectral analysis using ASME Code Case N411 (PVRC damping), linear time history analysis, non-linear time history analysis. This paper presents an estimation of the conservatism of the linear methods compared to the non-linear analysis. (orig./HP)
Nonparametric functional mapping of quantitative trait loci.
Yang, Jie; Wu, Rongling; Casella, George
2009-03-01
Functional mapping is a useful tool for mapping quantitative trait loci (QTL) that control dynamic traits. It incorporates mathematical aspects of biological processes into the mixture model-based likelihood setting for QTL mapping, thus increasing the power of QTL detection and the precision of parameter estimation. However, in many situations there is no obvious functional form and, in such cases, this strategy will not be optimal. Here we propose to use nonparametric function estimation, typically implemented with B-splines, to estimate the underlying functional form of phenotypic trajectories, and then construct a nonparametric test to find evidence of existing QTL. Using the representation of a nonparametric regression as a mixed model, the final test statistic is a likelihood ratio test. We consider two types of genetic maps: dense maps and general maps, and the power of nonparametric functional mapping is investigated through simulation studies and demonstrated by examples.
Essays on nonparametric econometrics of stochastic volatility
Zu, Y.
2012-01-01
Volatility is a concept that describes the variation of financial returns. Measuring and modelling volatility dynamics is an important aspect of financial econometrics. This thesis is concerned with nonparametric approaches to volatility measurement and volatility model validation.
Nonparametric methods for volatility density estimation
Es, van Bert; Spreij, P.J.C.; Zanten, van J.H.
2009-01-01
Stochastic volatility modelling of financial processes has become increasingly popular. The proposed models usually contain a stationary volatility process. We will motivate and review several nonparametric methods for estimation of the density of the volatility process. Both models based on
Spectral Karyotyping. An new method for chromosome analysis
International Nuclear Information System (INIS)
Zhou Liying; Qian Jianxin; Guo Xiaokui; Dai Hong; Liu Yulong; Zhou Jianying
2006-01-01
Spectral Karyotyping (SKY) can reveal fine changes in Chromosome structure which could not be detected by G, R, Q banding before, has become an accurate, sensitive and reliable method for karyotyping, promoted the development of cell genetics to molecular level and has been used in medicine and radiological injury research. It also has the ability of analyzing 24 chromosomes on its once test run and, find implicated structure of chromosome changes, such as metathesis, depletion, amplification, rearrangement, dikinetochore, equiarm and maker-body, detect the abnormal change of stable Chromosome and calculate the bio-dose curve; The abnormal Chromosome detected by SKY can be adopted as early diagnosis, effective indexes of minor remaining changes for use of monitor of treatment and in the duration of follow up. This technique provides us a more advanced and effective method for relative gene cloning and the study of pathological mechanism of cancer. (authors)
[Estimation of Hunan forest carbon density based on spectral mixture analysis of MODIS data].
Yan, En-ping; Lin, Hui; Wang, Guang-xing; Chen, Zhen-xiong
2015-11-01
With the fast development of remote sensing technology, combining forest inventory sample plot data and remotely sensed images has become a widely used method to map forest carbon density. However, the existence of mixed pixels often impedes the improvement of forest carbon density mapping, especially when low spatial resolution images such as MODIS are used. In this study, MODIS images and national forest inventory sample plot data were used to conduct the study of estimation for forest carbon density. Linear spectral mixture analysis with and without constraint, and nonlinear spectral mixture analysis were compared to derive the fractions of different land use and land cover (LULC) types. Then sequential Gaussian co-simulation algorithm with and without the fraction images from spectral mixture analyses were employed to estimate forest carbon density of Hunan Province. Results showed that 1) Linear spectral mixture analysis with constraint, leading to a mean RMSE of 0.002, more accurately estimated the fractions of LULC types than linear spectral and nonlinear spectral mixture analyses; 2) Integrating spectral mixture analysis model and sequential Gaussian co-simulation algorithm increased the estimation accuracy of forest carbon density to 81.5% from 74.1%, and decreased the RMSE to 5.18 from 7.26; and 3) The mean value of forest carbon density for the province was 30.06 t · hm(-2), ranging from 0.00 to 67.35 t · hm(-2). This implied that the spectral mixture analysis provided a great potential to increase the estimation accuracy of forest carbon density on regional and global level.
Spectral analysis of growing graphs a quantum probability point of view
Obata, Nobuaki
2017-01-01
This book is designed as a concise introduction to the recent achievements on spectral analysis of graphs or networks from the point of view of quantum (or non-commutative) probability theory. The main topics are spectral distributions of the adjacency matrices of finite or infinite graphs and their limit distributions for growing graphs. The main vehicle is quantum probability, an algebraic extension of the traditional probability theory, which provides a new framework for the analysis of adjacency matrices revealing their non-commutative nature. For example, the method of quantum decomposition makes it possible to study spectral distributions by means of interacting Fock spaces or equivalently by orthogonal polynomials. Various concepts of independence in quantum probability and corresponding central limit theorems are used for the asymptotic study of spectral distributions for product graphs. This book is written for researchers, teachers, and students interested in graph spectra, their (asymptotic) spectr...
ANALYSIS OF SPECTRAL CHARACTERISTICS AMONG DIFFERENT SENSORS BY USE OF SIMULATED RS IMAGES
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
This research, by use of RS image-simulating method, simulated apparent reflectance images at sensor level and ground-reflectance images of SPOT-HRV,CBERS-CCD,Landsat-TM and NOAA14-AVHRR' s corresponding bands. These images were used to analyze sensor's differences caused by spectral sensitivity and atmospheric impacts. The differences were analyzed on Normalized Difference Vegetation Index(NDVI). The results showed that the differences of sensors' spectral characteristics cause changes of their NDVI and reflectance. When multiple sensors' data are applied to digital analysis, the error should be taken into account. Atmospheric effect makes NDVI smaller, and atn~pheric correction has the tendency of increasing NDVI values. The reflectance and their NDVIs of different sensors can be used to analyze the differences among sensor' s features. The spectral analysis method based on RS simulated images can provide a new way to design the spectral characteristics of new sensors.
Spatio-spectral analysis of ionization times in high-harmonic generation
Energy Technology Data Exchange (ETDEWEB)
Soifer, Hadas, E-mail: hadas.soifer@weizmann.ac.il [Department of Physics of Complex Systems, Weizmann Institute of Science, Rehovot 76100 (Israel); Dagan, Michal; Shafir, Dror; Bruner, Barry D. [Department of Physics of Complex Systems, Weizmann Institute of Science, Rehovot 76100 (Israel); Ivanov, Misha Yu. [Department of Physics, Imperial College London, South Kensington Campus, SW7 2AZ London (United Kingdom); Max-Born Institute for Nonlinear Optics and Short Pulse Spectroscopy, Max-Born-Strasse 2A, D-12489 Berlin (Germany); Serbinenko, Valeria; Barth, Ingo; Smirnova, Olga [Max-Born Institute for Nonlinear Optics and Short Pulse Spectroscopy, Max-Born-Strasse 2A, D-12489 Berlin (Germany); Dudovich, Nirit [Department of Physics of Complex Systems, Weizmann Institute of Science, Rehovot 76100 (Israel)
2013-03-12
Graphical abstract: A spatio-spectral analysis of the two-color oscillation phase allows us to accurately separate short and long trajectories and reconstruct their ionization times. Highlights: ► We perform a complete spatio-spectral analysis of the high harmonic generation process. ► We analyze the ionization times across the entire spatio-spectral plane of the harmonics. ► We apply this analysis to reconstruct the ionization times of both short and long trajectories. - Abstract: Recollision experiments have been very successful in resolving attosecond scale dynamics. However, such schemes rely on the single atom response, neglecting the macroscopic properties of the interaction and the effects of using multi-cycle laser fields. In this paper we perform a complete spatio-spectral analysis of the high harmonic generation process and resolve the distribution of the subcycle dynamics of the recolliding electron. Specifically, we focus on the measurement of ionization times. Recently, we have demonstrated that the addition of a weak, crossed polarized second harmonic field allows us to resolve the moment of ionization (Shafir, 2012) [1]. In this paper we extend this measurement and perform a complete spatio-spectral analysis. We apply this analysis to reconstruct the ionization times of both short and long trajectories showing good agreement with the quantum path analysis.
Standard gamma-ray spectra for the comparison of spectral analysis software
International Nuclear Information System (INIS)
Woods, S.; Hemingway, J.; Bowles, N.
1997-01-01
Three sets of standard γ-ray spectra have been produced for use in assessing the performance of spectral analysis software. The origin of and rationale behind the spectra are described. Nine representative analysis systems have been tested both in terms of component performance and in terms of overall performance and the problems encountered in the analysis are discussed. (author)
Standard gamma-ray spectra for the comparison of spectral analysis software
Energy Technology Data Exchange (ETDEWEB)
Woods, S.; Hemingway, J.; Bowles, N. [and others
1997-08-01
Three sets of standard {gamma}-ray spectra have been produced for use in assessing the performance of spectral analysis software. The origin of and rationale behind the spectra are described. Nine representative analysis systems have been tested both in terms of component performance and in terms of overall performance and the problems encountered in the analysis are discussed. (author)
Methodology for diagnosing of skin cancer on images of dermatologic spots by spectral analysis
Guerra-Rosas, Esperanza; Álvarez-Borrego, Josué
2015-01-01
In this paper a new methodology for the diagnosing of skin cancer on images of dermatologic spots using image processing is presented. Currently skin cancer is one of the most frequent diseases in humans. This methodology is based on Fourier spectral analysis by using filters such as the classic, inverse and k-law nonlinear. The sample images were obtained by a medical specialist and a new spectral technique is developed to obtain a quantitative measurement of the complex pattern found in can...
Technical Training on High-Order Spectral Analysis and Thermal Anemometry Applications
Maslov, A. A.; Shiplyuk, A. N.; Sidirenko, A. A.; Bountin, D. A.
2003-01-01
The topics of thermal anemometry and high-order spectral analyses were the subject of the technical training. Specifically, the objective of the technical training was to study: (i) the recently introduced constant voltage anemometer (CVA) for high-speed boundary layer; and (ii) newly developed high-order spectral analysis techniques (HOSA). Both CVA and HOSA are relevant tools for studies of boundary layer transition and stability.
Investigating cardiorespiratory interaction by cross-spectral analysis of event series
Schäfer, Carsten; Rosenblum, Michael G.; Pikovsky, Arkady S.; Kurths, Jürgen
2000-02-01
The human cardiovascular and respiratory systems interact with each other and show effects of modulation and synchronization. Here we present a cross-spectral technique that specifically considers the event-like character of the heartbeat and avoids typical restrictions of other spectral methods. Using models as well as experimental data, we demonstrate how modulation and synchronization can be distinguished. Finally, we compare the method to traditional techniques and to the analysis of instantaneous phases.
Abramovych, Anton; Poddubny, Volodymyr
2017-01-01
The authors theoretically and experimentally substantiated the use of the spectral method for processing a signal of the vortex-current metal detector for dichotomous differentiation between metals. Results of experimental research that prove the possibility of using spectral analysis for differentiation between metals were presented. The vortex-current method for detection of hidden metal objects was analyzed. It was indicated that amplitude of output VCD signal is determined by electric con...
Archives of Astronomical Spectral Observations and Atomic/Molecular Databases for their Analysis
Directory of Open Access Journals (Sweden)
Ryabchikova T.
2015-12-01
Full Text Available We present a review of open-source data for stellar spectroscopy investigations. It includes lists of the main archives of medium-to-high resolution spectroscopic observations, with brief characteristics of the archive data (spectral range, resolving power, flux units. We also review atomic and molecular databases that contain parameters of spectral lines, cross-sections and reaction rates needed for a detailed analysis of high resolution, high signal-to-noise ratio stellar spectra.
Robust and transferable quantification of NMR spectral quality using IROC analysis
Zambrello, Matthew A.; Maciejewski, Mark W.; Schuyler, Adam D.; Weatherby, Gerard; Hoch, Jeffrey C.
2017-12-01
Non-Fourier methods are increasingly utilized in NMR spectroscopy because of their ability to handle nonuniformly-sampled data. However, non-Fourier methods present unique challenges due to their nonlinearity, which can produce nonrandom noise and render conventional metrics for spectral quality such as signal-to-noise ratio unreliable. The lack of robust and transferable metrics (i.e. applicable to methods exhibiting different nonlinearities) has hampered comparison of non-Fourier methods and nonuniform sampling schemes, preventing the identification of best practices. We describe a novel method, in situ receiver operating characteristic analysis (IROC), for characterizing spectral quality based on the Receiver Operating Characteristic curve. IROC utilizes synthetic signals added to empirical data as "ground truth", and provides several robust scalar-valued metrics for spectral quality. This approach avoids problems posed by nonlinear spectral estimates, and provides a versatile quantitative means of characterizing many aspects of spectral quality. We demonstrate applications to parameter optimization in Fourier and non-Fourier spectral estimation, critical comparison of different methods for spectrum analysis, and optimization of nonuniform sampling schemes. The approach will accelerate the discovery of optimal approaches to nonuniform sampling experiment design and non-Fourier spectrum analysis for multidimensional NMR.
International Nuclear Information System (INIS)
Peebles, D.E.; Ohlhausen, J.A.; Kotula, P.G.; Hutton, S.; Blomfield, C.
2004-01-01
The acquisition of spectral images for x-ray photoelectron spectroscopy (XPS) is a relatively new approach, although it has been used with other analytical spectroscopy tools for some time. This technique provides full spectral information at every pixel of an image, in order to provide a complete chemical mapping of the imaged surface area. Multivariate statistical analysis techniques applied to the spectral image data allow the determination of chemical component species, and their distribution and concentrations, with minimal data acquisition and processing times. Some of these statistical techniques have proven to be very robust and efficient methods for deriving physically realistic chemical components without input by the user other than the spectral matrix itself. The benefits of multivariate analysis of the spectral image data include significantly improved signal to noise, improved image contrast and intensity uniformity, and improved spatial resolution - which are achieved due to the effective statistical aggregation of the large number of often noisy data points in the image. This work demonstrates the improvements in chemical component determination and contrast, signal-to-noise level, and spatial resolution that can be obtained by the application of multivariate statistical analysis to XPS spectral images
Single versus mixture Weibull distributions for nonparametric satellite reliability
International Nuclear Information System (INIS)
Castet, Jean-Francois; Saleh, Joseph H.
2010-01-01
Long recognized as a critical design attribute for space systems, satellite reliability has not yet received the proper attention as limited on-orbit failure data and statistical analyses can be found in the technical literature. To fill this gap, we recently conducted a nonparametric analysis of satellite reliability for 1584 Earth-orbiting satellites launched between January 1990 and October 2008. In this paper, we provide an advanced parametric fit, based on mixture of Weibull distributions, and compare it with the single Weibull distribution model obtained with the Maximum Likelihood Estimation (MLE) method. We demonstrate that both parametric fits are good approximations of the nonparametric satellite reliability, but that the mixture Weibull distribution provides significant accuracy in capturing all the failure trends in the failure data, as evidenced by the analysis of the residuals and their quasi-normal dispersion.
Energy Technology Data Exchange (ETDEWEB)
Comsa, D.C. E-mail: comsadc@mcmaster.ca; Prestwich, W.V.; McNeill, F.E.; Byun, S.H
2004-12-01
The toxic effects of aluminum are cumulative and result in painful forms of renal osteodystrophy, most notably adynamic bone disease and osteomalacia, but also other forms of disease. The Trace Element Group at McMaster University has developed an accelerator-based in vivo procedure for detecting aluminum body burden by neutron activation analysis (NAA). Further refining of the method was necessary for increasing its sensitivity. In this context, the present study proposes an improved algorithm for data analysis, based on spectral decomposition. A new minimum detectable limit (MDL) of (0.7{+-}0.1) mg Al was reached for a local dose of (20{+-}1) mSv. The study also addresses the feasibility of a new data acquisition technique, the electronic rejection of the coincident events detected by a NaI(Tl) system. It is expected that the application of this technique, together with spectral decomposition analysis, would provide an acceptable MDL for the method to be valuable in a clinical setting.
New development of neutron spectral modulation data analysis
International Nuclear Information System (INIS)
Ito, Y.
1988-01-01
A study is made on procedures for obtaining desired scattering function information. The neutron spectral modulation technique incorporates both the low (including DC) and high frequency Fourier components in its incident spectrum. Lake's procedure increases the Fourier components of the doconvoluted scattering function by using the existing Fourier components as nucleus, thereby bridges the Fourier gap and extends the Fourier region. Since the Lake's procedure takes care of the missing Fourier components, a single measurement using an appropriate NSM modulation suffices to recover the S(W) line shape. Deep modulation depth is not essential to reproduce the scattering function. This should be contrasted to the previous NSM treatment as well as to the neutron spin echo method, both of which require the several repeat of measurements with the varying modulation frequency under the high degree of beam polarization condition. Although the computer simulation of the present paper does not include the statistical fluctuation encountered in the experimental data, these analyses show a great promise of the NSM method, which can now be used with much flexibility in the field of both cold and ultracold neutron scattering experiment. (N.K.)
Power Spectral Density Specification and Analysis of Large Optical Surfaces
Sidick, Erkin
2009-01-01
The 2-dimensional Power Spectral Density (PSD) can be used to characterize the mid- and the high-spatial frequency components of the surface height errors of an optical surface. We found it necessary to have a complete, easy-to-use approach for specifying and evaluating the PSD characteristics of large optical surfaces, an approach that allows one to specify the surface quality of a large optical surface based on simulated results using a PSD function and to evaluate the measured surface profile data of the same optic in comparison with those predicted by the simulations during the specification-derivation process. This paper provides a complete mathematical description of PSD error, and proposes a new approach in which a 2-dimentional (2D) PSD is converted into a 1-dimentional (1D) one by azimuthally averaging the 2D-PSD. The 1D-PSD calculated this way has the same unit and the same profile as the original PSD function, thus allows one to compare the two with each other directly.
Spectral analysis and markov switching model of Indonesia business cycle
Fajar, Muhammad; Darwis, Sutawanir; Darmawan, Gumgum
2017-03-01
This study aims to investigate the Indonesia business cycle encompassing the determination of smoothing parameter (λ) on Hodrick-Prescott filter. Subsequently, the components of the filter output cycles were analyzed using a spectral method useful to know its characteristics, and Markov switching regime modeling is made to forecast the probability recession and expansion regimes. The data used in the study is real GDP (1983Q1 - 2016Q2). The results of the study are: a) Hodrick-Prescott filter on real GDP of Indonesia to be optimal when the value of the smoothing parameter is 988.474, b) Indonesia business cycle has amplitude varies between±0.0071 to±0.01024, and the duration is between 4 to 22 quarters, c) the business cycle can be modelled by MSIV-AR (2) but regime periodization is generated this model not perfect exactly with real regime periodzation, and d) Based on the model MSIV-AR (2) obtained long-term probabilities in the expansion regime: 0.4858 and in the recession regime: 0.5142.
LDA measurements and turbulence spectral analysis in an agitated vessel
Directory of Open Access Journals (Sweden)
Chára Zdeněk
2013-04-01
Full Text Available During the last years considerable improvement of the derivation of turbulence power spectrum from Laser Doppler Anemometry (LDA has been achieved. The irregularly sampled LDA data is proposed to approximate by several methods e.g. Lomb-Scargle method, which estimates amplitude and phase of spectral lines from missing data, methods based on the reconstruction of the auto-correlation function (referred to as correlation slotting technique, methods based on the reconstruction of the time series using interpolation between the uneven sampling and subsequent resampling etc. These different methods were used on the LDA data measured in an agitated vessel and the results of the power spectrum calculations were compared. The measurements were performed in the mixing vessel with flat bottom. The vessel was equipped with four baffles and agitated with a six-blade pitched blade impeller. Three values of the impeller speed (Reynolds number were tested. Long time series of the axial velocity component were measured in selected points. In each point the time series were analyzed and evaluated in a form of power spectrum.
LDA measurements and turbulence spectral analysis in an agitated vessel
Kysela, Bohuš; Konfršt, Jiří; Chára, Zdeněk
2013-04-01
During the last years considerable improvement of the derivation of turbulence power spectrum from Laser Doppler Anemometry (LDA) has been achieved. The irregularly sampled LDA data is proposed to approximate by several methods e.g. Lomb-Scargle method, which estimates amplitude and phase of spectral lines from missing data, methods based on the reconstruction of the auto-correlation function (referred to as correlation slotting technique), methods based on the reconstruction of the time series using interpolation between the uneven sampling and subsequent resampling etc. These different methods were used on the LDA data measured in an agitated vessel and the results of the power spectrum calculations were compared. The measurements were performed in the mixing vessel with flat bottom. The vessel was equipped with four baffles and agitated with a six-blade pitched blade impeller. Three values of the impeller speed (Reynolds number) were tested. Long time series of the axial velocity component were measured in selected points. In each point the time series were analyzed and evaluated in a form of power spectrum.
Isolation and Spectral Analysis of Naturally Occurring Thiarubrine A
Reyes, Juan; Morton, Melita; Downum, Kelsey; O'Shea, Kevin E.
2001-06-01
We have designed an experiment in which students isolate and characterize thiarubrine A, a pseudo-antiaromatic 1,2-dithia-3,5-cyclohexadiene derivative. Thiarubrines are an important class of compounds which have recently received attention because of their unusual reactivity, unique biological activity, and potential medicinal applications. They possess a distinctive red color and structure features that are particularly useful for demonstrating UV-vis, NMR, and IR spectral analyses. A crude mixture containing thiarubrine A is obtained by methanol (liquid-solid) extraction of the roots of short ragweed, Ambrosia artemisiifolia. Alternatively, these compounds can be isolated from numerous taxa within the family Asteraceae. Thiarubrine A possesses alkyl, alkenyl, and alkynyl functionality, which is useful in illustrating the utility of IR and NMR in the characterization of natural products. The long wavelength UV-vis absorption band of thiarubrine is indication of the nonplanarity of dithiin ring and provides an excellent opportunity to discuss the concepts of aromaticity, conjugation, and molecular orbital theory.
The Observatory as Laboratory: Spectral Analysis at Mount Wilson Observatory
Brashear, Ronald
2018-01-01
This paper will discuss the seminal changes in astronomical research practices made at the Mount Wilson Observatory in the early twentieth century by George Ellery Hale and his staff. Hale’s desire to set the agenda for solar and stellar astronomical research is often described in terms of his new telescopes, primarily the solar tower observatories and the 60- and 100-inch telescopes on Mount Wilson. This paper will focus more on the ancillary but no less critical parts of Hale’s research mission: the establishment of associated “physical” laboratories as part of the observatory complex where observational spectral data could be quickly compared with spectra obtained using specialized laboratory equipment. Hale built a spectroscopic laboratory on the mountain and a more elaborate physical laboratory in Pasadena and staffed it with highly trained physicists, not classically trained astronomers. The success of Hale’s vision for an astronomical observatory quickly made the Carnegie Institution’s Mount Wilson Observatory one of the most important astrophysical research centers in the world.
Systematic wavelength selection for improved multivariate spectral analysis
Thomas, Edward V.; Robinson, Mark R.; Haaland, David M.
1995-01-01
Methods and apparatus for determining in a biological material one or more unknown values of at least one known characteristic (e.g. the concentration of an analyte such as glucose in blood or the concentration of one or more blood gas parameters) with a model based on a set of samples with known values of the known characteristics and a multivariate algorithm using several wavelength subsets. The method includes selecting multiple wavelength subsets, from the electromagnetic spectral region appropriate for determining the known characteristic, for use by an algorithm wherein the selection of wavelength subsets improves the model's fitness of the determination for the unknown values of the known characteristic. The selection process utilizes multivariate search methods that select both predictive and synergistic wavelengths within the range of wavelengths utilized. The fitness of the wavelength subsets is determined by the fitness function F=.function.(cost, performance). The method includes the steps of: (1) using one or more applications of a genetic algorithm to produce one or more count spectra, with multiple count spectra then combined to produce a combined count spectrum; (2) smoothing the count spectrum; (3) selecting a threshold count from a count spectrum to select these wavelength subsets which optimize the fitness function; and (4) eliminating a portion of the selected wavelength subsets. The determination of the unknown values can be made: (1) noninvasively and in vivo; (2) invasively and in vivo; or (3) in vitro.
International Nuclear Information System (INIS)
Sivia, D.S.; Hamilton, W.A.; Smith, G.S.
1991-01-01
The analysis of neutron reflectivity data to obtain nuclear scattering length density profiles is akin to the notorious phaseless Fourier problem, well known in many fields such as crystallography. Current methods of analysis culminate in the refinement of a few parameters of a functional model, and are often preceded by a long and laborious process of trial and error. We start by discussing the use of maximum entropy for obtained 'free-form' solutions of the density profile, as an alternative to the trial and error phase when a functional model is not available. Next we consider a Bayesian spectral analysis approach, which is appropriate for optimising the parameters of a simple (but adequate) type of model when the number of parameters is not known. Finally, we suggest a novel experimental procedure, the analogue of astronomical speckle holography, designed to alleviate the ambiguity problems inherent in traditional reflectivity measurements. (orig.)
Spectral analysis of an algebraic collapsing acceleration for the characteristics method
International Nuclear Information System (INIS)
Le Tellier, R.; Hebert, A.
2005-01-01
A spectral analysis of a diffusion synthetic acceleration called Algebraic Collapsing Acceleration (ACA) was carried out in the context of the characteristics method to solve the neutron transport equation. Two analysis were performed in order to assess the ACA performances. Both a standard Fourier analysis in a periodic and infinite slab-geometry and a direct spectral analysis for a finite slab-geometry were investigated. In order to evaluate its performance, ACA was compared with two competing techniques used to accelerate the convergence of the characteristics method, the Self-Collision Re-balancing technique and the Asymptotic Synthetic Acceleration. In the restricted framework of 1-dimensional slab-geometries, we conclude that ACA offers a good compromise between the reduction of the spectral radius of the iterative matrix and the resources to construct, store and solve the corrective system. A comparison on a monoenergetic 2-dimensional benchmark was performed and tends to confirm these conclusions. (authors)
VIBRATIONS DETECTION IN INDUSTRIAL PUMPS BASED ON SPECTRAL ANALYSIS TO INCREASE THEIR EFFICIENCY
Directory of Open Access Journals (Sweden)
Belhadef RACHID
2016-01-01
Full Text Available Spectral analysis is the key tool for the study of vibration signals in rotating machinery. In this work, the vibration analy-sis applied for conditional preventive maintenance of such machines is proposed, as part of resolved problems related to vibration detection on the organs of these machines. The vibration signal of a centrifugal pump was treated to mount the benefits of the approach proposed. The obtained results present the signal estimation of a pump vibration using Fourier transform technique compared by the spectral analysis methods based on Prony approach.
Spectral characterization as a tool for parchment analysis
Radis, Michela; Iacomussi, Paola; Rossi, Giuseppe
2015-06-01
The paper presents an investigation on the correlation between spectral characteristics and conservation conditions of parchment to define a NON invasive methodology able to detect and monitor deterioration process in historical parchment without the need of taking small samples. To verify the feasibility and define the most appropriate measurement method, several samples of contemporary parchments, produced following ancient recipes and coming from different animal species, with different degrees of artificially induced damage, were analyzed. The SRF and STF of each sample were measured in the same point, before and after each step of the artificial ageing treatment. Having at disposal a parchment coming from a whole lamb leather, allowed also the study of the correlations between the variations of SRF - STF and the intrinsic factors of a parchment like the variability of animal skin anatomy and of manufacturing. Analyzing different samples allowed also the definition of the measuring method sensitivity and of reference spectrum for the different animal species parchments with accuracy limits. The definition of a reference spectrum of not damaged parchment with acceptability limits is a necessary step for understanding, through SRF - STF measurements, historical parchments conservation conditions: indeed it is necessary to know if deviations from the reference spectrum are ascribable to damage or only to parchment anatomic/production variability. As a case study, the method has been applied to two historical parchment scrolls stored at the Archivio di Stato di Torino (Italy). The SRF - STF of both scrolls was acquired in several points of the scroll, the average spectrum of each scroll was compared with the reference spectra with the relative tolerance limits, recognizing the animal species and damage alterations and demonstrating the feasibility of the method.
DEFF Research Database (Denmark)
Vincent, Claire Louise; Giebel, Gregor; Pinson, Pierre
2010-01-01
a 4-yr time series of 10-min wind speed observations. An adaptive spectral analysis method called the Hilbert–Huang transform is chosen for the analysis, because the nonstationarity of time series of wind speed observations means that they are not well described by a global spectral analysis method...... such as the Fourier transform. The Hilbert–Huang transform is a local method based on a nonparametric and empirical decomposition of the data followed by calculation of instantaneous amplitudes and frequencies using the Hilbert transform. The Hilbert–Huang transformed 4-yr time series is averaged and summarized...
Automics: an integrated platform for NMR-based metabonomics spectral processing and data analysis
Directory of Open Access Journals (Sweden)
Qu Lijia
2009-03-01
Full Text Available Abstract Background Spectral processing and post-experimental data analysis are the major tasks in NMR-based metabonomics studies. While there are commercial and free licensed software tools available to assist these tasks, researchers usually have to use multiple software packages for their studies because software packages generally focus on specific tasks. It would be beneficial to have a highly integrated platform, in which these tasks can be completed within one package. Moreover, with open source architecture, newly proposed algorithms or methods for spectral processing and data analysis can be implemented much more easily and accessed freely by the public. Results In this paper, we report an open source software tool, Automics, which is specifically designed for NMR-based metabonomics studies. Automics is a highly integrated platform that provides functions covering almost all the stages of NMR-based metabonomics studies. Automics provides high throughput automatic modules with most recently proposed algorithms and powerful manual modules for 1D NMR spectral processing. In addition to spectral processing functions, powerful features for data organization, data pre-processing, and data analysis have been implemented. Nine statistical methods can be applied to analyses including: feature selection (Fisher's criterion, data reduction (PCA, LDA, ULDA, unsupervised clustering (K-Mean and supervised regression and classification (PLS/PLS-DA, KNN, SIMCA, SVM. Moreover, Automics has a user-friendly graphical interface for visualizing NMR spectra and data analysis results. The functional ability of Automics is demonstrated with an analysis of a type 2 diabetes metabolic profile. Conclusion Automics facilitates high throughput 1D NMR spectral processing and high dimensional data analysis for NMR-based metabonomics applications. Using Automics, users can complete spectral processing and data analysis within one software package in most cases
Automics: an integrated platform for NMR-based metabonomics spectral processing and data analysis.
Wang, Tao; Shao, Kang; Chu, Qinying; Ren, Yanfei; Mu, Yiming; Qu, Lijia; He, Jie; Jin, Changwen; Xia, Bin
2009-03-16
Spectral processing and post-experimental data analysis are the major tasks in NMR-based metabonomics studies. While there are commercial and free licensed software tools available to assist these tasks, researchers usually have to use multiple software packages for their studies because software packages generally focus on specific tasks. It would be beneficial to have a highly integrated platform, in which these tasks can be completed within one package. Moreover, with open source architecture, newly proposed algorithms or methods for spectral processing and data analysis can be implemented much more easily and accessed freely by the public. In this paper, we report an open source software tool, Automics, which is specifically designed for NMR-based metabonomics studies. Automics is a highly integrated platform that provides functions covering almost all the stages of NMR-based metabonomics studies. Automics provides high throughput automatic modules with most recently proposed algorithms and powerful manual modules for 1D NMR spectral processing. In addition to spectral processing functions, powerful features for data organization, data pre-processing, and data analysis have been implemented. Nine statistical methods can be applied to analyses including: feature selection (Fisher's criterion), data reduction (PCA, LDA, ULDA), unsupervised clustering (K-Mean) and supervised regression and classification (PLS/PLS-DA, KNN, SIMCA, SVM). Moreover, Automics has a user-friendly graphical interface for visualizing NMR spectra and data analysis results. The functional ability of Automics is demonstrated with an analysis of a type 2 diabetes metabolic profile. Automics facilitates high throughput 1D NMR spectral processing and high dimensional data analysis for NMR-based metabonomics applications. Using Automics, users can complete spectral processing and data analysis within one software package in most cases. Moreover, with its open source architecture, interested
Spectral analysis of the fifth spectrum of indium: In V
International Nuclear Information System (INIS)
Swapnil; Tauheed, A.
2016-01-01
The fifth spectrum of indium (In V) has been investigated in the grazing and normal incidence wavelength regions. In"4"+ is a Rh-like ion with the ground configuration 4p"64d"9 and first excited configurations of the type 4p"64d"8nℓ (n≥4). The theoretical predications for this ion were made by Cowan's quasi-relativistic Hartree–Fock code with superposition of configurations involving 4p"64d"8(5p+6p+7p+4f+5f+6f), 4p"54d"1"0, 4p"64d"75s(5p+4f) for the odd parity matrix and 4p"64d"8 (5s+6s+7s+5d+6d), 4p"64d"7(5s"2+5p"2) for the even parity system. The spectra used for this work were recorded on 10.7 m grazing and normal incidence spectrographs at the National Institute of Standards and Technology, Gaithersburg, Maryland (USA) and also on a 3-m normal incidence vacuum spectrograph at Antigonish (Canada). The sources used were a sliding spark and a triggered spark respectively. Two hundred and thirty two energy levels based on the identification of 873 spectral lines have been established, forty six being new. Least squares fitted parametric calculations were used to interpret the observed level structure. The energy levels were optimized using a level optimization computer program (LOPT). Our wavelength accuracy for sharp and unblended lines is estimated to be within ±0.005 Å for λ below 400 Å and ±0.006 Å up to 1200 Å. - Highlights: • Indium spectra were recorded on both grazing and normal incidence spectrographs. • Calculations were made with Cowan's quasi-relativistic Hartree–Fock code. • New atomic transitions of In V were identified with newly found energy levels. • Uncertainties and Ritz wavelengths of all observed transitions were calculated. • Weighted transition probabilities (gA) were calculated.
IR spectral analysis for the diagnostics of crust earthquake precursors
Umarkhodgaev, R. M.; Liperovsky, V. A.; Mikhailin, V. V.; Meister, C.-V.; Naumov, D. Ju
2012-04-01
In regions of future earthquakes, a few days before the seismic shock, the emanation of radon and hydrogen is being observed, which causes clouds of increased ionisation in the atmosphere. In the present work the possible diagnostics of these clouds using infrared (IR) spectroscopy is considered, which may be important and useful for the general geophysical system of earthquake prediction and the observation of industrial emissions of radioactive materials into the atmosphere. Some possible physical processes are analysed, which cause, under the condition of additional ionisation in a pre-breakdown electrical field, emissions in the IR interval. In doing so, the transparency region of the IR spectrum at wavelengths of 7-15 μm is taken into account. This transparency region corresponds to spectral lines of small atmospheric constituents like CH4, CO2, N2O, NO2, NO, and O3. The possible intensities of the IR emissions observable in laboratories and in nature are estimated. The acceleration process of the electrons in the pre-breakdown electrical field before its adhesion to the molecules is analysed. The laboratory equipment for the investigation of the IR absorption spectrum is constructed for the cases of normal and decreased atmospheric pressures. The syntheses of ozone and nitrous oxides are performed in the barrier discharge. It is studied if the products of the syntheses may be used to model atmospheric processes where these components take part. Spectra of products of the syntheses in the wavelength region of 2-10 μm are observed and analysed. A device is created for the syntheses and accumulation of nitrous oxides. Experiments to observe the IR-spectra of ozone and nitrous oxides during the syntheses and during the further evolution of these molecules are performed. For the earthquake prediction, practically, the investigation of emission spectra is most important, but during the laboratory experiments, the radiation of the excited molecules is shifted by a
Cloud Masking for Remotely Sensed Data Using Spectral and Principal Components Analysis
Directory of Open Access Journals (Sweden)
A. Ahmad
2012-06-01
Full Text Available Two methods of cloud masking tuned to tropical conditions have been developed, based on spectral analysis and Principal Components Analysis (PCA of Moderate Resolution Imaging Spectroradiometer (MODIS data. In the spectral approach, thresholds were applied to four reflective bands (1, 2, 3, and 4, three thermal bands (29, 31 and 32, the band 2/band 1 ratio, and the difference between band 29 and 31 in order to detect clouds. The PCA approach applied a threshold to the first principal component derived from the seven quantities used for spectral analysis. Cloud detections were compared with the standard MODIS cloud mask, and their accuracy was assessed using reference images and geographical information on the study area.
Spectral Analysis of Traffic Functions in Urban Areas
Directory of Open Access Journals (Sweden)
Florin Nemtanu
2015-12-01
Full Text Available The paper is focused on the Fourier transform application in urban traffic analysis and the use of said transform in traffic decomposition. The traffic function is defined as traffic flow generated by different categories of traffic participants. A Fourier analysis was elaborated in terms of identifying the main traffic function components, called traffic sub-functions. This paper presents the results of the method being applied in a real case situation, that is, an intersection in the city of Bucharest where the effect of a bus line was analysed. The analysis was done using different time scales, while three different traffic functions were defined to demonstrate the theoretical effect of the proposed method of analysis. An extension of the method is proposed to be applied in urban areas, especially in the areas covered by predictive traffic control.
Multi spectral imaging analysis for meat spoilage discrimination
DEFF Research Database (Denmark)
Christiansen, Asger Nyman; Carstensen, Jens Michael; Papadopoulou, Olga
classification methods: Naive Bayes Classifier as a reference model, Canonical Discriminant Analysis (CDA) and Support Vector Classification (SVC). As the final step, generalization of the models was performed using k-fold validation (k=10). Results showed that image analysis provided good discrimination of meat......In the present study, fresh beef fillets were purchased from a local butcher shop and stored aerobically and in modified atmosphere packaging (MAP, CO2 40%/O2 30%/N2 30%) at six different temperatures (0, 4, 8, 12, 16 and 20°C). Microbiological analysis in terms of total viable counts (TVC......) was performed in parallel with videometer image snapshots and sensory analysis. Odour and colour characteristics of meat were determined by a test panel and attributed into three pre-characterized quality classes, namely Fresh; Semi Fresh and Spoiled during the days of its shelf life. So far, different...
An experiment with spectral analysis of emotional speech affected by orthodontic appliances
Přibil, Jiří; Přibilová, Anna; Ďuračková, Daniela
2012-11-01
The contribution describes the effect of the fixed and removable orthodontic appliances on spectral properties of emotional speech. Spectral changes were analyzed and evaluated by spectrograms and mean Welch’s periodograms. This alternative approach to the standard listening test enables to obtain objective comparison based on statistical analysis by ANOVA and hypothesis tests. Obtained results of analysis performed on short sentences of a female speaker in four emotional states (joyous, sad, angry, and neutral) show that, first of all, the removable orthodontic appliance affects the spectrograms of produced speech.
A Molecular Iodine Spectral Data Set for Rovibronic Analysis
Williamson, J. Charles; Kuntzleman, Thomas S.; Kafader, Rachael A.
2013-01-01
A data set of 7,381 molecular iodine vapor rovibronic transitions between the X and B electronic states has been prepared for an advanced undergraduate spectroscopic analysis project. Students apply standard theoretical techniques to these data and determine the values of three X-state constants (image omitted) and four B-state constants (image…
Recent Advances and Trends in Nonparametric Statistics
Akritas, MG
2003-01-01
The advent of high-speed, affordable computers in the last two decades has given a new boost to the nonparametric way of thinking. Classical nonparametric procedures, such as function smoothing, suddenly lost their abstract flavour as they became practically implementable. In addition, many previously unthinkable possibilities became mainstream; prime examples include the bootstrap and resampling methods, wavelets and nonlinear smoothers, graphical methods, data mining, bioinformatics, as well as the more recent algorithmic approaches such as bagging and boosting. This volume is a collection o
Nonparametric Identification and Estimation of Finite Mixture Models of Dynamic Discrete Choices
Hiroyuki Kasahara; Katsumi Shimotsu
2006-01-01
In dynamic discrete choice analysis, controlling for unobserved heterogeneity is an important issue, and finite mixture models provide flexible ways to account for unobserved heterogeneity. This paper studies nonparametric identifiability of type probabilities and type-specific component distributions in finite mixture models of dynamic discrete choices. We derive sufficient conditions for nonparametric identification for various finite mixture models of dynamic discrete choices used in appli...
International Nuclear Information System (INIS)
Foltz Biegalski, K.M.; Biegalski, S.R.; Haas, D.A.
2008-01-01
The Spectral Deconvolution Analysis Tool (SDAT) software was developed to improve counting statistics and detection limits for nuclear explosion radionuclide measurements. SDAT utilizes spectral deconvolution spectroscopy techniques and can analyze both β-γ coincidence spectra for radioxenon isotopes and high-resolution HPGe spectra from aerosol monitors. Spectral deconvolution spectroscopy is an analysis method that utilizes the entire signal deposited in a gamma-ray detector rather than the small portion of the signal that is present in one gamma-ray peak. This method shows promise to improve detection limits over classical gamma-ray spectroscopy analytical techniques; however, this hypothesis has not been tested. To address this issue, we performed three tests to compare the detection ability and variance of SDAT results to those of commercial off- the-shelf (COTS) software which utilizes a standard peak search algorithm. (author)
Real-time spectral analysis of HRV signals: an interactive and user-friendly PC system.
Basano, L; Canepa, F; Ottonello, P
1998-01-01
We present a real-time system, built around a PC and a low-cost data acquisition board, for the spectral analysis of the heart rate variability signal. The Windows-like operating environment on which it is based makes the computer program very user-friendly even for non-specialized personnel. The Power Spectral Density is computed through the use of a hybrid method, in which a classical FFT analysis follows an autoregressive finite-extension of data; the stationarity of the sequence is continuously checked. The use of this algorithm gives a high degree of robustness of the spectral estimation. Moreover, always in real time, the FFT of every data block is computed and displayed in order to corroborate the results as well as to allow the user to interactively choose a proper AR model order.
Directory of Open Access Journals (Sweden)
Fubiao Feng
2017-03-01
Full Text Available Recently, graph embedding has drawn great attention for dimensionality reduction in hyperspectral imagery. For example, locality preserving projection (LPP utilizes typical Euclidean distance in a heat kernel to create an affinity matrix and projects the high-dimensional data into a lower-dimensional space. However, the Euclidean distance is not sufficiently correlated with intrinsic spectral variation of a material, which may result in inappropriate graph representation. In this work, a graph-based discriminant analysis with spectral similarity (denoted as GDA-SS measurement is proposed, which fully considers curves changing description among spectral bands. Experimental results based on real hyperspectral images demonstrate that the proposed method is superior to traditional methods, such as supervised LPP, and the state-of-the-art sparse graph-based discriminant analysis (SGDA.
Processing of spectral X-ray data with principal components analysis
Butler, A P H; Cook, N J; Butzer, J; Schleich, N; Tlustos, L; Scott, N; Grasset, R; de Ruiter, N; Anderson, N G
2011-01-01
The goal of the work was to develop a general method for processing spectral x-ray image data. Principle component analysis (PCA) is a well understood technique for multivariate data analysis and so was investigated. To assess this method, spectral (multi-energy) computed tomography (CT) data was obtained using a Medipix2 detector in a MARS-CT (Medipix All Resolution System). PCA was able to separate bone (calcium) from two elements with k-edges in the X-ray spectrum used (iodine and barium) within a mouse. This has potential clinical application in dual-energy CT systems and future Medipix3 based spectral imaging where up to eight energies can be recorded simultaneously with excellent energy resolution. (c) 2010 Elsevier B.V. All rights reserved.
Analysis of spectral data with rare events statistics
International Nuclear Information System (INIS)
Ilyushchenko, V.I.; Chernov, N.I.
1990-01-01
The case is considered of analyzing experimental data, when the results of individual experimental runs cannot be summed due to large systematic errors. A statistical analysis of the hypothesis about the persistent peaks in the spectra has been performed by means of the Neyman-Pearson test. The computations demonstrate the confidence level for the hypothesis about the presence of a persistent peak in the spectrum is proportional to the square root of the number of independent experimental runs, K. 5 refs
Spectral analysis of optical emission of microplasma in sea water
Gamaleev, Vladislav; Morita, Hayato; Oh, Jun-Seok; Furuta, Hiroshi; Hatta, Akimitsu
2016-09-01
This work presents an analysis of optical emission spectra from microplasma in three types of liquid, namely artificial sea water composed of 10 typical agents (10ASW), reference solutions each containing a single agent (NaCl, MgCl2 + H2O, Na2SO4, CaCl2, KCl, NaHCO3, KBr, NaHCO3, H3BO3, SrCl2 + H2O, NaF) and naturally sampled deep sea water (DSW). Microplasma was operated using a needle(Pd)-to-plate(Pt) electrode system sunk into each liquid in a quartz cuvette. The radius of the tip of the needle was 50 μm and the gap between the electrodes was set at 20 μm. An inpulse generator circuit, consisting of a MOSFET switch, a capacitor, an inductor and the resistance of the liquid between the electrodes, was used as a pulse current source for operation of discharges. In the spectra, the emission peaks for the main components of sea water and contaminants from the electrodes were detected. Spectra for reference solutions were examined to enable the identification of unassigned peaks in the spectra for sea water. Analysis of the Stark broadening of H α peak was carried out to estimate the electron density of the plasma under various conditions. The characteristics of microplasma discharge in sea water and the analysis of the optical emission spectra will be presented. This work was supported by JSPS KAKENHI Grant Number 26600129.
Tapia-Herrera, R.; Huerta-Lopez, C. I.; Martinez-Cruzado, J. A.
2009-05-01
Results of site characterization for an experimental site in the metropolitan area of Tijuana, B. C., Mexico are presented as part of the on-going research in which time series of earthquakes, ambient noise, and induced vibrations were processed with three different methods: H/V spectral ratios, Spectral Analysis of Surface Waves (SASW), and the Random Decrement Method, (RDM). Forward modeling using the wave propagation stiffness matrix method (Roësset and Kausel, 1981) was used to compute the theoretical SH/P, SV/P spectral ratios, and the experimental H/V spectral ratios were computed following the conventional concepts of Fourier analysis. The modeling/comparison between the theoretical and experimental H/V spectral ratios was carried out. For the SASW method the theoretical dispersion curves were also computed and compared with the experimental one, and finally the theoretical free vibration decay curve was compared with the experimental one obtained with the RDM. All three methods were tested with ambient noise, induced vibrations, and earthquake signals. Both experimental spectral ratios obtained with ambient noise as well as earthquake signals agree quite well with the theoretical spectral ratios, particularly at the fundamental vibration frequency of the recording site. Differences between the fundamental vibration frequencies are evident for sites located at alluvial fill (~0.6 Hz) and at sites located at conglomerate/sandstones fill (0.75 Hz). Shear wave velocities for the soft soil layers of the 4-layer discrete soil model ranges as low as 100 m/s and up to 280 m/s. The results with the SASW provided information that allows to identify low velocity layers, not seen before with the traditional seismic methods. The damping estimations obtained with the RDM are within the expected values, and the dominant frequency of the system also obtained with the RDM correlates within the range of plus-minus 20 % with the one obtained by means of the H/V spectral
Press, Craig A; Morgan, Lindsey; Mills, Michele; Stack, Cynthia V; Goldstein, Joshua L; Alonso, Estella M; Wainwright, Mark S
2017-01-01
Spectral electroencephalogram analysis is a method for automated analysis of electroencephalogram patterns, which can be performed at the bedside. We sought to determine the utility of spectral electroencephalogram for grading hepatic encephalopathy in children with acute liver failure. Retrospective cohort study. Tertiary care pediatric hospital. Patients between 0 and 18 years old who presented with acute liver failure and were admitted to the PICU. None. Electroencephalograms were analyzed by spectral analysis including total power, relative δ, relative θ, relative α, relative β, θ-to-Δ ratio, and α-to-Δ ratio. Normal values and ranges were first derived using normal electroencephalograms from 70 children of 0-18 years old. Age had a significant effect on each variable measured (p liver failure were available for spectral analysis. The median age was 4.3 years, 14 of 33 were male, and the majority had an indeterminate etiology of acute liver failure. Neuroimaging was performed in 26 cases and was normal in 20 cases (77%). The majority (64%) survived, and 82% had a good outcome with a score of 1-3 on the Pediatric Glasgow Outcome Scale-Extended at the time of discharge. Hepatic encephalopathy grade correlated with the qualitative visual electroencephalogram scores assigned by blinded neurophysiologists (rs = 0.493; p encephalopathy was correlated with a total power of less than or equal to 50% of normal for children 0-3 years old, and with a relative θ of less than or equal to 50% normal for children more than 3 years old (p > 0.05). Spectral electroencephalogram classification correlated with outcome (p encephalopathy and correlates with outcome. Spectral electroencephalogram may allow improved quantitative and reproducible assessment of hepatic encephalopathy grade in children with acute liver failure.
Correlative Spectral Analysis of Gamma-Ray Bursts using Swift-BAT and GLAST-GBM
International Nuclear Information System (INIS)
Stamatikos, Michael; Sakamoto, Taka; Band, David L.
2008-01-01
We discuss the preliminary results of spectral analysis simulations involving anticipated correlated multi-wavelength observations of gamma-ray bursts (GRBs) using Swift's Burst Alert Telescope (BAT) and the Gamma-Ray Large Area Space Telescope's (GLAST) Burst Monitor (GLAST-GBM), resulting in joint spectral fits, including characteristic photon energy (E peak ) values, for a conservative annual estimate of ∼30 GRBs. The addition of BAT's spectral response will (i) complement in-orbit calibration efforts of GBM's detector response matrices, (ii) augment GLAST's low energy sensitivity by increasing the ∼20-100 keV effective area, (iii) facilitate ground-based follow-up efforts of GLAST GRBs by increasing GBM's source localization precision, and (iv) help identify a subset of non-triggered GRBs discovered via off-line GBM data analysis. Such multi-wavelength correlative analyses, which have been demonstrated by successful joint-spectral fits of Swift-BAT GRBs with other higher energy detectors such as Konus-WIND and Suzaku-WAM, would enable the study of broad-band spectral and temporal evolution of prompt GRB emission over three energy decades, thus potentially increasing science return without placing additional demands upon mission resources throughout their contemporaneous orbital tenure over the next decade.
Correlative Spectral Analysis of Gamma-Ray Bursts using Swift-BAT and GLAST-GBM
International Nuclear Information System (INIS)
Stamatikos, Michael; Sakamoto, Takanori; Band, David L.
2008-01-01
We discuss the preliminary results of spectral analysis simulations involving anticipated correlated multi-wavelength observations of gamma-ray bursts (GRBs) using Swift's Burst Alert Telescope (BAT) and the Gamma-Ray Large Area Space Telescope's (GLAST) Burst Monitor (GLAST-GBM), resulting in joint spectral fits, including characteristic photon energy (E peak ) values, for a conservative annual estimate of ∼30 GRBs. The addition of BAT/s spectral response will (i) complement in-orbit calibration efforts of GBM's detector response matrices, (ii) augment GLAST's low energy sensitivity by increasing the ∼20-100 keV effective area, (iii) facilitate ground-based follow-up efforts of GLAST GRBs by increasing GBM's source localization precision, and (iv) help identify a subset of non-triggered GRBs discovered via off-line GBM data analysis. Such multi-wavelength correlative analyses, which have been demonstrated by successful joint-spectral fits of Swift-BAT GRBs with other higher energy detectors such as Konus-WIND and Suzaku-WAM, would enable the study of broad-band spectral and temporal evolution of prompt GRB emission over three energy decades, thus potentially increasing science return without placing additional demands upon mission resources throughout their contemporaneous orbital tenure over the next decade
Non destructive defect detection by spectral density analysis.
Krejcar, Ondrej; Frischer, Robert
2011-01-01
The potential nondestructive diagnostics of solid objects is discussed in this article. The whole process is accomplished by consecutive steps involving software analysis of the vibration power spectrum (eventually acoustic emissions) created during the normal operation of the diagnosed device or under unexpected situations. Another option is to create an artificial pulse, which can help us to determine the actual state of the diagnosed device. The main idea of this method is based on the analysis of the current power spectrum density of the received signal and its postprocessing in the Matlab environment with a following sample comparison in the Statistica software environment. The last step, which is comparison of samples, is the most important, because it is possible to determine the status of the examined object at a given time. Nowadays samples are compared only visually, but this method can't produce good results. Further the presented filter can choose relevant data from a huge group of data, which originate from applying FFT (Fast Fourier Transform). On the other hand, using this approach they can be subjected to analysis with the assistance of a neural network. If correct and high-quality starting data are provided to the initial network, we are able to analyze other samples and state in which condition a certain object is. The success rate of this approximation, based on our testing of the solution, is now 85.7%. With further improvement of the filter, it could be even greater. Finally it is possible to detect defective conditions or upcoming limiting states of examined objects/materials by using only one device which contains HW and SW parts. This kind of detection can provide significant financial savings in certain cases (such as continuous casting of iron where it could save hundreds of thousands of USD).
Application of OLAM network in X-ray spectral analysis
International Nuclear Information System (INIS)
Liu Yinbing; Zhou Rongsheng
2001-01-01
The author describes a new approach to the automatic radioisotope identification problem based on the use of OLAM network. Different from the traditional methods, the OLAM network takes the spectrum as a whole comparing its shape with the patterns learned during the training period of the network. It is found that the OLAM network, once adequately trained, is quite suitable to identify a given isotope present in a mixture of elements as well as the relative proportions of each identified substance. Preliminary results are good enough to consider OLAM network as powerful and simple tools in the automatic spectrum analysis
Aristovnik, Aleksander
2012-01-01
The purpose of the paper is to review some previous researches examining ICT efficiency and the impact of ICT on educational output/outcome as well as different conceptual and methodological issues related to performance measurement. Moreover, a definition, measurements and the empirical application of a model measuring the efficiency of ICT use and its impact at national levels will be considered. For this purpose, the Data Envelopment Analysis (DEA) technique is presented and then applied t...
Micro-Raman Imaging for Biology with Multivariate Spectral Analysis
Malvaso, Federica
2015-05-05
Raman spectroscopy is a noninvasive technique that can provide complex information on the vibrational state of the molecules. It defines the unique fingerprint that allow the identification of the various chemical components within a given sample. The aim of the following thesis work is to analyze Raman maps related to three pairs of different cells, highlighting differences and similarities through multivariate algorithms. The first pair of analyzed cells are human embryonic stem cells (hESCs), while the other two pairs are induced pluripotent stem cells (iPSCs) derived from T lymphocytes and keratinocytes, respectively. Although two different multivariate techniques were employed, ie Principal Component Analysis and Cluster Analysis, the same results were achieved: the iPSCs derived from T-lymphocytes show a higher content of genetic material both compared with the iPSCs derived from keratinocytes and the hESCs . On the other side, equally evident, was that iPS cells derived from keratinocytes assume a molecular distribution very similar to hESCs.
International Nuclear Information System (INIS)
Venancio Filho, F.; DeCarvalho Santos, S.H.; Joia, L.A.
1987-01-01
A numerical methodology to obtain Power Spectral Density Functions (PSDF) of ground accelerations, compatible with a given design response spectrum is presented. The PSDF's are derived from the statistical analysis of the amplitudes of the frequency components in a set of artificially generated time-histories matching the given spectrum. A so obtained PSDF is then used in the stochastic analysis of a NPP Reactor Building. The main results of this analysis are compared with the ones obtained by deterministic methods
International Nuclear Information System (INIS)
Venancio Filho, F.; Joia, L.A.
1987-01-01
A numerical methodology to obtain Power Spectral Density Functions (PSDF) of ground accelerations, compatible with a given design response spectrum is presented. The PSDF's are derived from the statistical analysis of the amplitudes of the frequency components in a set of artificially generated time-histories matching the given spectrum. A so obtained PSDF is then used in the stochastic analysis of a reactor building. The main results of this analysis are compared with the ones obtained by deterministic methods. (orig./HP)
Spectral analysis of viscous static compressible fluid equilibria
Energy Technology Data Exchange (ETDEWEB)
Nunez, Manuel [Departamento de Analisis Matematico, Universidad de Valladolid, Valladolid (Spain)
2001-05-25
It is generally assumed that the study of the spectrum of the linearized Navier-Stokes equations around a static state will provide information about the stability of the equilibrium. This is obvious for inviscid barotropic compressible fluids by the self-adjoint character of the relevant operator, and rather easy for viscous incompressible fluids by the compact character of the resolvent. The viscous compressible linearized system, both for periodic and homogeneous Dirichlet boundary problems, satisfies neither condition, but it does turn out to be the generator of an immediately continuous, almost stable semigroup, which justifies the analysis of the spectrum as predictive of the initial behaviour of the flow. As for the spectrum itself, except for a unique negative finite accumulation point, it is formed by eigenvalues with negative real part, and nonreal eigenvalues are confined to a certain bounded subset of complex numbers. (author)
Selective laser ionization for mass-spectral isotopic analysis
International Nuclear Information System (INIS)
Miller, C.M.; Nogar, N.S.; Downey, S.W.
1983-01-01
Resonant enhancement of the ionization process can provide a high degree of elemental selectivity, thus eliminating or drastically reducing the interference problem. In addition, extension of this method to isotopically selective ionization has the potential for greatly increasing the range of isotope ratios that can be determined experimentally. This gain can be realized by reducing or eliminating the tailing of the signal from the high-abundance isotope into that of the low-abundance isotope, augmenting the dispersion of the mass spectrometer. We briefly discuss the hardware and techniques used in both our pulsed and cw RIMS experiments. Results are presented for both cw ionization experiments on Lu/Yb mixtures, and spectroscopic studies of multicolor RIMS of Tc. Lastly, we discuss practical limits of cw RIMS analysis in terms of detection limits and measurable isotope ratios
Spectral analysis of musical sounds with emphasis on the piano
Koenig, David M
2014-01-01
There are three parts to this book which addresses the analysis of musical sounds from the viewpoint of someone at the intersection between physicists, engineers, piano technicians, and musicians. The reader is introduced to a variety of waves and a variety of ways of presenting, visualizing, and analyzing them in the first part. A tutorial on the tools used throughout the book accompanies this introduction. The mathematics behind the tools is left to the appendices. Part 2 is a graphical survey of the classical areas of acoustics that pertain to musical instruments: vibrating strings, bars, membranes, and plates. Part 3 is devoted almost exclusively to the piano. Several two- and three-dimensional graphical tools are introduced to study the following characteristics of pianos: individual notes and interactions among them, the missing fundamental, inharmonicity, tuning visualization, the different distribution of harmonic power for the various zones of the piano keyboard, and potential uses for quality contro...
Hyperspectral image segmentation using a cooperative nonparametric approach
Taher, Akar; Chehdi, Kacem; Cariou, Claude
2013-10-01
In this paper a new unsupervised nonparametric cooperative and adaptive hyperspectral image segmentation approach is presented. The hyperspectral images are partitioned band by band in parallel and intermediate classification results are evaluated and fused, to get the final segmentation result. Two unsupervised nonparametric segmentation methods are used in parallel cooperation, namely the Fuzzy C-means (FCM) method, and the Linde-Buzo-Gray (LBG) algorithm, to segment each band of the image. The originality of the approach relies firstly on its local adaptation to the type of regions in an image (textured, non-textured), and secondly on the introduction of several levels of evaluation and validation of intermediate segmentation results before obtaining the final partitioning of the image. For the management of similar or conflicting results issued from the two classification methods, we gradually introduced various assessment steps that exploit the information of each spectral band and its adjacent bands, and finally the information of all the spectral bands. In our approach, the detected textured and non-textured regions are treated separately from feature extraction step, up to the final classification results. This approach was first evaluated on a large number of monocomponent images constructed from the Brodatz album. Then it was evaluated on two real applications using a respectively multispectral image for Cedar trees detection in the region of Baabdat (Lebanon) and a hyperspectral image for identification of invasive and non invasive vegetation in the region of Cieza (Spain). A correct classification rate (CCR) for the first application is over 97% and for the second application the average correct classification rate (ACCR) is over 99%.
Spectral Analysis of a Quantum System with a Double Line Singular Interaction
Czech Academy of Sciences Publication Activity Database
Kondej, S.; Krejčiřík, David
2013-01-01
Roč. 49, č. 4 (2013), s. 831-859 ISSN 0034-5318 R&D Projects: GA ČR GAP203/11/0701 Institutional support: RVO:61389005 Keywords : Schrödinger operator * singular perturbation * spectral analysis * Hardy inequality * resonance Subject RIV: BE - Theoretical Physics Impact factor: 0.614, year: 2013
Semiconductor detectors in current energy dispersive X-ray spectral analysis
International Nuclear Information System (INIS)
Betin, J.; Zhabin, E.; Krampit, I.; Smirnov, V.
1980-01-01
A review is presented of the properties of semiconductor detectors and of the possibilities stemming therefrom of using the detectors in X-ray spectral analysis in industries, in logging, in ecology and environmental control, in medicine, etc. (M.S.)
Evaluation of skin melanoma in spectral range 450-950 nm using principal component analysis
Jakovels, D.; Lihacova, I.; Kuzmina, I.; Spigulis, J.
2013-06-01
Diagnostic potential of principal component analysis (PCA) of multi-spectral imaging data in the wavelength range 450- 950 nm for distant skin melanoma recognition is discussed. Processing of the measured clinical data by means of PCA resulted in clear separation between malignant melanomas and pigmented nevi.
Spectral analysis of K-shell X-ray emission of magnesium plasma
Indian Academy of Sciences (India)
2014-02-06
Feb 6, 2014 ... Spectral analysis of K-shell X-ray emission of magnesium plasma, produced by laser pulses of 45 fs duration, focussed up to an intensity of ∼1018 W cm-2, is carried out. The plasma conditions prevalent during the emission of X-ray spectrum were identified by comparing the experimental spectra with the ...
WINDOWS: a program for the analysis of spectral data foil activation measurements
International Nuclear Information System (INIS)
Stallmann, F.W.; Eastham, J.F.; Kam, F.B.K.
1978-12-01
The computer program WINDOWS together with its subroutines is described for the analysis of neutron spectral data foil activation measurements. In particular, the unfolding of the neutron differential spectrum, estimated windows and detector contributions, upper and lower bounds for an integral response, and group fluxes obtained from neutron transport calculations. 116 references
WINDOWS: a program for the analysis of spectral data foil activation measurements
Energy Technology Data Exchange (ETDEWEB)
Stallmann, F.W.; Eastham, J.F.; Kam, F.B.K.
1978-12-01
The computer program WINDOWS together with its subroutines is described for the analysis of neutron spectral data foil activation measurements. In particular, the unfolding of the neutron differential spectrum, estimated windows and detector contributions, upper and lower bounds for an integral response, and group fluxes obtained from neutron transport calculations. 116 references. (JFP)
Polder, G.; Heijden, van der G.W.A.M.
2003-01-01
Independent Component Analysis (ICA) is one of the most widely used methods for blind source separation. In this paper we use this technique to estimate the important compounds which play a role in the ripening of tomatoes. Spectral images of tomatoes were analyzed. Two main independent components
Directory of Open Access Journals (Sweden)
Yuanyuan Ma
2016-01-01
Full Text Available To overcome the problem that the horizontal resolution of global climate models may be too low to resolve features which are important at the regional or local scales, dynamical downscaling has been extensively used. However, dynamical downscaling results generally drift away from large-scale driving fields. The nudging technique can be used to balance the performance of dynamical downscaling at large and small scales, but the performances of the two nudging techniques (analysis nudging and spectral nudging are debated. Moreover, dynamical downscaling is now performed at the convection-permitting scale to reduce the parameterization uncertainty and obtain the finer resolution. To compare the performances of the two nudging techniques in this study, three sensitivity experiments (with no nudging, analysis nudging, and spectral nudging covering a period of two months with a grid spacing of 6 km over continental China are conducted to downscale the 1-degree National Centers for Environmental Prediction (NCEP dataset with the Weather Research and Forecasting (WRF model. Compared with observations, the results show that both of the nudging experiments decrease the bias of conventional meteorological elements near the surface and at different heights during the process of dynamical downscaling. However, spectral nudging outperforms analysis nudging for predicting precipitation, and analysis nudging outperforms spectral nudging for the simulation of air humidity and wind speed.
Sex Differences in the Sleep EEG of Young Adults : Visual Scoring and Spectral Analysis
Dijk, Derk Jan; Beersma, Domien G.M.; Bloem, Gerda M.
1989-01-01
Baseline sleep of 13 men (mean age of 23.5 years) and 15 women (21.9 years) was analyzed. Visual scoring of the electroencephalograms (EEGs) revealed no significant differences between the sexes in the amounts of slow-wave sleep and rapid-eye-movement (REM) sleep. Spectral analysis, however,
Teaching Nonparametric Statistics Using Student Instrumental Values.
Anderson, Jonathan W.; Diddams, Margaret
Nonparametric statistics are often difficult to teach in introduction to statistics courses because of the lack of real-world examples. This study demonstrated how teachers can use differences in the rankings and ratings of undergraduate and graduate values to discuss: (1) ipsative and normative scaling; (2) uses of the Mann-Whitney U-test; and…
Nonparametric conditional predictive regions for time series
de Gooijer, J.G.; Zerom Godefay, D.
2000-01-01
Several nonparametric predictors based on the Nadaraya-Watson kernel regression estimator have been proposed in the literature. They include the conditional mean, the conditional median, and the conditional mode. In this paper, we consider three types of predictive regions for these predictors — the
Nonparametric predictive inference in statistical process control
Arts, G.R.J.; Coolen, F.P.A.; Laan, van der P.
2000-01-01
New methods for statistical process control are presented, where the inferences have a nonparametric predictive nature. We consider several problems in process control in terms of uncertainties about future observable random quantities, and we develop inferences for these random quantities hased on
Nonparametric predictive inference in statistical process control
Arts, G.R.J.; Coolen, F.P.A.; Laan, van der P.
2004-01-01
Statistical process control (SPC) is used to decide when to stop a process as confidence in the quality of the next item(s) is low. Information to specify a parametric model is not always available, and as SPC is of a predictive nature, we present a control chart developed using nonparametric
Non-Parametric Estimation of Correlation Functions
DEFF Research Database (Denmark)
Brincker, Rune; Rytter, Anders; Krenk, Steen
In this paper three methods of non-parametric correlation function estimation are reviewed and evaluated: the direct method, estimation by the Fast Fourier Transform and finally estimation by the Random Decrement technique. The basic ideas of the techniques are reviewed, sources of bias are point...
Nonparametric estimation in models for unobservable heterogeneity
Hohmann, Daniel
2014-01-01
Nonparametric models which allow for data with unobservable heterogeneity are studied. The first publication introduces new estimators and their asymptotic properties for conditional mixture models. The second publication considers estimation of a function from noisy observations of its Radon transform in a Gaussian white noise model.
Nonparametric estimation of location and scale parameters
Potgieter, C.J.; Lombard, F.
2012-01-01
Two random variables X and Y belong to the same location-scale family if there are constants μ and σ such that Y and μ+σX have the same distribution. In this paper we consider non-parametric estimation of the parameters μ and σ under minimal
Panel data specifications in nonparametric kernel regression
DEFF Research Database (Denmark)
Czekaj, Tomasz Gerard; Henningsen, Arne
parametric panel data estimators to analyse the production technology of Polish crop farms. The results of our nonparametric kernel regressions generally differ from the estimates of the parametric models but they only slightly depend on the choice of the kernel functions. Based on economic reasoning, we...
Advances in spectral analysis using artificial neural networks
International Nuclear Information System (INIS)
Martinez, M.; Vigneron, V.
1995-01-01
Artificial Neural networks (ANNs) have a powerful representational capacity and ability to handle with any multi-input multi-output mapping problem, e.g. in clustering, pattern recognition and identification areas, particularly when combined with some a priori knowledge and statistical point of view. They can be useful in spectrometry for the uranium enrichment methods by examples, where numerous approaches like models fitting or experts analysis are limited. These depends on the radiation measured: the methods most widely used developed over the past 20 years were based on the counting of the 185.7-keV peak with a sodium iodide scintillation detector or the 163.4-keV peak of 235 U. But these methods depend critically of the source-detector geometry. A means of improving the above conventional methods is to reduce the region of interest: it is possible by focusing at the region called KαX where the three elementary components are present. The measurement of these components in mixtures leads to the isotope ratio 235 U / ( 235 U + 236 U + 238 U). In this paper we explore statistical orientations and their consequences on 'neural' parameters. We show this decisions are induced by a log-linear model, a special case of a GLIM (Generalized LInear Model) and correspond to a Maximum Likelihood Estimation problem. (authors). 15 refs., 7 figs., 2 tabs
Energy Technology Data Exchange (ETDEWEB)
Wang, Qi, E-mail: wq20@hotmail.com; Shi, Gaofeng, E-mail: gaofengs62@sina.com; Qi, Xiaohui, E-mail: qixiaohui1984@163.com; Fan, Xueli, E-mail: 407849960@qq.com; Wang, Lijia, E-mail: 893197597@qq.com
2014-10-15
Highlights: • We establish a feasible method using the virtual spectral curves (VSC) to differentiate focal liver lesions using DECT. • Our study shows the slope of the VSC can be used to differentiate between hemangioma, HCC, metastasis and cyst. • Importantly, the diagnostic specificities associated with using the slope to diagnose both hemangioma and cysts were 100%. - Abstract: Objective: To assess the usefulness of the spectral curve slope of dual-energy CT (DECT) for differentiating between hepatocellular carcinoma (HCC), hepatic metastasis, hemangioma (HH) and cysts. Methods: In total, 121 patients were imaged in the portal venous phase using dual-energy mode. Of these patients, 23 patients had HH, 28 patients had HCC, 40 patients had metastases and 30 patients had simple cysts. The spectral curves of the hepatic lesions were derived from the 40–190 keV levels of virtual monochromatic spectral imaging. The spectral curve slopes were calculated from 40 to 110 keV. The slopes were compared using the Kruskal–Wallis test. Receiver operating characteristic curves (ROC) were used to determine the optimal cut-off value of the slope of the spectral curve to differentiate between the lesions. Results: The spectral curves of the four lesion types had different baseline levels. The HH baseline level was the highest followed by HCC, metastases and cysts. The slopes of the spectral curves of HH, HCC, metastases and cysts were 3.81 ± 1.19, 1.49 ± 0.57, 1.06 ± 0.76 and 0.13 ± 0.17, respectively. These values were significantly different (P < 0.008). Based on ROC analysis, the respective diagnostic sensitivity and specificity were 87% and 100% for hemangioma (cut-off value ≥ 2.988), 82.1% and 65.9% for HCC (cut-off value 1.167–2.998), 65.9% and 59% for metastasis (cut-off value 0.133–1.167) and 44.4% and 100% for cysts (cut-off value ≤ 0.133). Conclusion: Quantitative analysis of the DECT spectral curve in the portal venous phase can be used to
Li, Qi-Gang; He, Yong-Han; Wu, Huan; Yang, Cui-Ping; Pu, Shao-Yan; Fan, Song-Qing; Jiang, Li-Ping; Shen, Qiu-Shuo; Wang, Xiao-Xiong; Chen, Xiao-Qiong; Yu, Qin; Li, Ying; Sun, Chang; Wang, Xiangting; Zhou, Jumin; Li, Hai-Peng; Chen, Yong-Bin; Kong, Qing-Peng
2017-01-01
Heterogeneity in transcriptional data hampers the identification of differentially expressed genes (DEGs) and understanding of cancer, essentially because current methods rely on cross-sample normalization and/or distribution assumption-both sensitive to heterogeneous values. Here, we developed a new method, Cross-Value Association Analysis (CVAA), which overcomes the limitation and is more robust to heterogeneous data than the other methods. Applying CVAA to a more complex pan-cancer dataset containing 5,540 transcriptomes discovered numerous new DEGs and many previously rarely explored pathways/processes; some of them were validated, both in vitro and in vivo , to be crucial in tumorigenesis, e.g., alcohol metabolism ( ADH1B ), chromosome remodeling ( NCAPH ) and complement system ( Adipsin ). Together, we present a sharper tool to navigate large-scale expression data and gain new mechanistic insights into tumorigenesis.
International Nuclear Information System (INIS)
Borgermans, P.
2002-01-01
The document is an abstract of a PhD thesis. The PhD work concerns the detailed investigation of the behaviour of optical fibres in radiation fields such as is the case for various nuclear and space application,s. The core of the work concerns the spectral and kinetic analysis of the radiation induced optical attenuation. Models describing underlying physical phenomena, both for the spectral and the time dimensions, have been developed. The potential of silica optical fibre waveguides for intrinsic dosimetry has been assessed by employing specific properties of radiation induced defects in the silica waveguide material
International Nuclear Information System (INIS)
Castro, E.B.; Vilche, J.R.; Milocco, R.H.
1984-01-01
An impedance measurement system based on the spectral analysis of excitation and response signals was implemented using a pseudo-random binary sequence in the generation of the electrical perturbation signal. The spectral density functions were estimated through finite Fourier transforms of the original time history records by fast computation of Fourier series. Experimental results obtained using the FFT algorithm in the developed impedance measurement system which covers a wide frequency range, 10 KHz >= f >= 1 mHz, are given both for dummy cells representing conventional electric circuits in electrochemistry and corrosion systems and for the Fe/acidic chloride solution interfaces under different polarization conditions. (C.L.B.) [pt
The analysis of toxic connections content in water by spectral methods
Plotnikova, I. V.; Chaikovskaya, O. N.; Sokolova, I. V.; Artyushin, V. R.
2017-08-01
The current state of ecology means the strict observance of measures for the utilization of household and industrial wastes that is connected with very essential expenses of means and time. Thanks to spectroscopic devices usage the spectral methods allow to carry out the express quantitative and qualitative analysis in a workplace and field conditions. In a work the application of spectral methods by studying the degradation of toxic organic compounds after preliminary radiation of various sources is shown. Experimental data of optical density of water at various influences are given.
Spectral Analysis within the Virtual Observatory: The GAVO Service TheoSSA
Ringat, E.
2012-03-01
In the last decade, numerous Virtual Observatory organizations were established. One of these is the German Astrophysical Virtual Observatory (GAVO) that e.g. provides access to spectral energy distributions via the service TheoSSA. In a pilot phase, these are based on the Tübingen NLTE Model-Atmosphere Package (TMAP) and suitable for hot, compact stars. We demonstrate the power of TheoSSA in an application to the sdOB primary of AA Doradus by comparison with a “classical” spectral analysis.
Monitoring PSR B1509–58 with RXTE: Spectral analysis 1996–2010
Directory of Open Access Journals (Sweden)
E. Litzinger
2011-01-01
Full Text Available We present an analysis of the X-ray spectra of the young, Crab-like pulsar PSR B1509–58 (pulse period P ~ 151ms observed by RXTE over 14 years since the beginning of the mission in 1996. The uniform dataset is especially well suited for studying the stability of the spectral parameters over time as well as for determining pulse phase resolved spectral parameters with high significance. The phase averaged spectra as well as the resolved spectra can be well described by an absorbed power law.
Ivanova, B. B.
2005-11-01
A stereo structural characterization of 2,5,6-thrimethylbenzimidazole (MBIZ) and 2-amino-benzimidaziole (2-NH 2-BI) and their N 1 protonation salts was carried out using a polarized solid state linear dichroic infrared spectral (IR-LD) analysis in nematic liquid crystal suspension. All experimental predicted structures were compared with the theoretical ones, obtained by ab initio calculations. The Cs to C2v* symmetry transformation as a result of protonation processes, with a view of its reflection on the infrared spectral characteristics was described.
Spectral analysis of the geomagnetic activity index Ap during different IMF conditions (1947-1978)
International Nuclear Information System (INIS)
Francia, P.; Villante, U.
1986-01-01
The spectral analysis of the geomagnetic activity index Ap (1947-1978) has been conducted for intervals associated respectively with two and four sectors of the interplanetary magnetic fields per solar rotation. A recurrent 2-sector structure is typically associated with an emerging spectral peak close to T s (T s being the period of solar rotation as seen from Earth), while the T 2 /2 modulation becomes more important during intervals corresponding to four sectors per solar rotation. The recurrence tendency of two high-velocity streams per solar rotation seems to reinforce the relative importance of the T 2 /2 modulation
Spectral Analysis of Geomagnetic Activity Indices and Solar Wind Parameters
Directory of Open Access Journals (Sweden)
Jung-Hee Kim
2014-06-01
Full Text Available Solar variability is widely known to affect the interplanetary space and in turn the Earth’s electromagnetical environment on the basis of common periodicities in the solar and geomagnetic activity indices. The goal of this study is twofold. Firstly, we attempt to associate modes by comparing a temporal behavior of the power of geomagnetic activity parameters since it is barely sufficient searching for common peaks with a similar periodicity in order to causally correlate geomagnetic activity parameters. As a result of the wavelet transform analysis we are able to obtain information on the temporal behavior of the power in the velocity of the solar wind, the number density of protons in the solar wind, the AE index, the Dst index, the interplanetary magnetic field, B and its three components of the GSM coordinate system, BX, BY, BZ. Secondly, we also attempt to search for any signatures of influence on the space environment near the Earth by inner planets orbiting around the Sun. Our main findings are as follows: (1 Parameters we have investigated show periodicities of ~ 27 days, ~ 13.5 days, ~ 9 days. (2 The peaks in the power spectrum of BZ appear to be split due to an unknown agent. (3 For some modes powers are not present all the time and intervals showing high powers do not always coincide. (4 Noticeable peaks do not emerge at those frequencies corresponding to the synodic and/or sidereal periods of Mercury and Venus, which leads us to conclude that the Earth’s space environment is not subject to the shadow of the inner planets as suggested earlier.
Spectral analysis of highly aliased sea-level signals
Ray, Richard D.
1998-10-01
Observing high-wavenumber ocean phenomena with a satellite altimeter generally calls for "along-track" analyses of the data: measurements along a repeating satellite ground track are analyzed in a point-by-point fashion, as opposed to spatially averaging data over multiple tracks. The sea-level aliasing problems encountered in such analyses can be especially challenging. For TOPEX/POSEIDON, all signals with frequency greater than 18 cycles per year (cpy), including both tidal and subdiurnal signals, are folded into the 0-18 cpy band. Because the tidal bands are wider than 18 cpy, residual tidal cusp energy, plus any subdiurnal energy, is capable of corrupting any low-frequency signal of interest. The practical consequences of this are explored here by using real sea-level measurements from conventional tide gauges, for which the true oceanographic spectrum is known and to which a simulated "satellite-measured" spectrum, based on coarsely subsampled data, may be compared. At many locations the spectrum is sufficently red that interannual frequencies remain unaffected. Intra-annual frequencies, however, must be interpreted with greater caution, and even interannual frequencies can be corrupted if the spectrum is flat. The results also suggest that whenever tides must be estimated directly from the altimetry, response methods of analysis are preferable to harmonic methods, even in nonlinear regimes; this will remain so for the foreseeable future. We concentrate on three example tide gauges: two coastal stations on the Malay Peninsula where the closely aliased K1 and Ssa tides are strong and at Canton Island where trapped equatorial waves are aliased.
Directory of Open Access Journals (Sweden)
Corrado lo Storto
2013-12-01
Full Text Available This article reports the outcome of a performance study of the water service provision industry in Italy. The study evaluates the efficiency of 21 “private or public-private” equity and 32 “public” equity water service operators and investigates controlling factors. In particular, the influence that the operator typology and service management nature - private vs. public - has on efficiency is assessed. The study employed a two-stage Data Envelopment Analysis methodology. In the first stage, the operational efficiency of water supply operators is calculated by implementing a conventional BCC DEA model, that uses both physical infrastructure and financial input and output variables to explore economies of scale. In the second stage, bootstrapped DEA and Tobit regression are performed to estimate the influence that a number of environmental factors have on water supplier efficiency. The results show that the integrated water provision industry in Italy is characterized by operational inefficiencies of service operators, and scale and agglomeration economies may have a not negligible effect on efficiency. In addition, the operator typology and its geographical location affect efficiency.
Nonparametric Bayesian models for a spatial covariance.
Reich, Brian J; Fuentes, Montserrat
2012-01-01
A crucial step in the analysis of spatial data is to estimate the spatial correlation function that determines the relationship between a spatial process at two locations. The standard approach to selecting the appropriate correlation function is to use prior knowledge or exploratory analysis, such as a variogram analysis, to select the correct parametric correlation function. Rather that selecting a particular parametric correlation function, we treat the covariance function as an unknown function to be estimated from the data. We propose a flexible prior for the correlation function to provide robustness to the choice of correlation function. We specify the prior for the correlation function using spectral methods and the Dirichlet process prior, which is a common prior for an unknown distribution function. Our model does not require Gaussian data or spatial locations on a regular grid. The approach is demonstrated using a simulation study as well as an analysis of California air pollution data.
Spectral analysis of turbulence propagation mechanisms in solar wind and tokamaks plasmas
International Nuclear Information System (INIS)
Dong, Yue
2014-01-01
This thesis takes part in the study of spectral transfers in the turbulence of magnetized plasmas. We will be interested in turbulence in solar wind and tokamaks. Spacecraft measures, first principle simulations and simple dynamical systems will be used to understand the mechanisms behind spectral anisotropy and spectral transfers in these plasmas. The first part of this manuscript will introduce the common context of solar wind and tokamaks, what is specific to each of them and present some notions needed to understand the work presented here. The second part deals with turbulence in the solar wind. We will present first an observational study on the spectral variability of solar wind turbulence. Starting from the study of Grappin et al. (1990, 1991) on Helios mission data, we bring a new analysis taking into account a correct evaluation of large scale spectral break, provided by the higher frequency data of the Wind mission. This considerably modifies the result on the spectral index distribution of the magnetic and kinetic energy. A second observational study is presented on solar wind turbulence anisotropy using autocorrelation functions. Following the work of Matthaeus et al. (1990); Dasso et al. (2005), we bring a new insight on this statistical, in particular the question of normalisation choices used to build the autocorrelation function, and its consequence on the measured anisotropy. This allows us to bring a new element in the debate on the measured anisotropy depending on the choice of the referential either based on local or global mean magnetic field. Finally, we study for the first time in 3D the effects of the transverse expansion of solar wind on its turbulence. This work is based on a theoretical and numerical scheme developed by Grappin et al. (1993); Grappin and Velli (1996), but never used in 3D. Our main results deal with the evolution of spectral and polarization anisotropy due to the competition between non-linear and linear (Alfven coupling
Modal spectral analysis of piping: Determination of the significant frequency range
International Nuclear Information System (INIS)
Geraets, L.H.
1981-01-01
This paper investigates the influence of the number of modes on the response of a piping system in a dynamic modal spectral analysis. It shows how the analysis can be limited to a specific frequency range of the pipe (independent of the frequency range of the response spectrum), allowing cost reduction without loss in accuracy. The 'missing mass' is taken into account through an original technique. (orig./HP)
Nonparametric Change Point Diagnosis Method of Concrete Dam Crack Behavior Abnormality
Directory of Open Access Journals (Sweden)
Zhanchao Li
2013-01-01
Full Text Available The study on diagnosis method of concrete crack behavior abnormality has always been a hot spot and difficulty in the safety monitoring field of hydraulic structure. Based on the performance of concrete dam crack behavior abnormality in parametric statistical model and nonparametric statistical model, the internal relation between concrete dam crack behavior abnormality and statistical change point theory is deeply analyzed from the model structure instability of parametric statistical model and change of sequence distribution law of nonparametric statistical model. On this basis, through the reduction of change point problem, the establishment of basic nonparametric change point model, and asymptotic analysis on test method of basic change point problem, the nonparametric change point diagnosis method of concrete dam crack behavior abnormality is created in consideration of the situation that in practice concrete dam crack behavior may have more abnormality points. And the nonparametric change point diagnosis method of concrete dam crack behavior abnormality is used in the actual project, demonstrating the effectiveness and scientific reasonableness of the method established. Meanwhile, the nonparametric change point diagnosis method of concrete dam crack behavior abnormality has a complete theoretical basis and strong practicality with a broad application prospect in actual project.
Spectral analysis of time series of events: effect of respiration on heart rate in neonates
International Nuclear Information System (INIS)
Van Drongelen, Wim; Williams, Amber L; Lasky, Robert E
2009-01-01
Certain types of biomedical processes such as the heart rate generator can be considered as signals that are sampled by the occurring events, i.e. QRS complexes. This sampling property generates problems for the evaluation of spectral parameters of such signals. First, the irregular occurrence of heart beats creates an unevenly sampled data set which must either be pre-processed (e.g. by using trace binning or interpolation) prior to spectral analysis, or analyzed with specialized methods (e.g. Lomb's algorithm). Second, the average occurrence of events determines the Nyquist limit for the sampled time series. Here we evaluate different types of spectral analysis of recordings of neonatal heart rate. Coupling between respiration and heart rate and the detection of heart rate itself are emphasized. We examine both standard and data adaptive frequency bands of heart rate signals generated by models of coupled oscillators and recorded data sets from neonates. We find that an important spectral artifact occurs due to a mirror effect around the Nyquist limit of half the average heart rate. Further we conclude that the presence of respiratory coupling can only be detected under low noise conditions and if a data-adaptive respiratory band is used
International Nuclear Information System (INIS)
Speetjens, M F M; Meleshko, V V; Van Heijst, G J F
2014-01-01
The present study addresses the classical problem of the dynamics and stability of a cluster of N-point vortices of equal strength arranged in a polygonal configuration (‘N-vortex polygons’). In unbounded domains, such N-vortex polygons are unconditionally stable for N⩽7. Confinement in a circular domain tightens the stability conditions to N⩽6 and a maximum polygon size relative to the domain radius. This work expands on existing studies on stability and integrability by a first giving an exploratory spectral analysis of the dynamics of N vortex polygons in circular domains. Key to this is that the spectral signature of the time evolution of vortex positions reflects their qualitative behaviour. Expressing vortex motion by a generic evolution operator (the so-called Koopman operator) provides a rigorous framework for such spectral analyses. This paves the way to further differentiation and classification of point-vortex behaviour beyond stability and integrability. The concept of Koopman-based spectral analysis is demonstrated for N-vortex polygons. This reveals that conditional stability can be seen as a local form of integrability and confirms an important generic link between spectrum and dynamics: discrete spectra imply regular (quasi-periodic) motion; continuous (sub-)spectra imply chaotic motion. Moreover, this exposes rich nonlinear dynamics as intermittency between regular and chaotic motion and quasi-coherent structures formed by chaotic vortices. (ss 1)
On the spectral analysis of iterative solutions of the discretized one-group transport equation
International Nuclear Information System (INIS)
Sanchez, Richard
2004-01-01
We analyze the Fourier-mode technique used for the spectral analysis of iterative solutions of the one-group discretized transport equation. We introduce a direct spectral analysis for the iterative solution of finite difference approximations for finite slabs composed of identical layers, providing thus a complementary analysis that is more appropriate for reactor applications. Numerical calculations for the method of characteristics and with the diamond difference approximation show the appearance of antisymmetric modes generated by the iteration on boundary data. We have also utilized the discrete Fourier transform to compute the spectrum for a periodic slab containing N identical layers and shown that at the limit N → ∞ one obtains the familiar Fourier-mode solution
The spectral analysis of motion: An "open field" activity test example
Directory of Open Access Journals (Sweden)
Obradović Z.
2013-01-01
Full Text Available In this work we have described the new mathematical approach, with spectral analysis of the data to evaluate position and motion in the „„open field““ experiments. The aim of this work is to introduce several new parameters mathematically derived from experimental data by means of spectral analysis, and to quantitatively estimate the quality of the motion. Two original software packages (TRACKER and POSTPROC were used for transforming a video data to a log file, suitable for further computational analysis, and to perform analysis from the log file. As an example, results obtained from the experiments with Wistar rats in the „open field“ test are included. The test group of animals was treated with diazepam. Our results demonstrate that all the calculated parameters, such as movement variability, acceleration and deceleration, were significantly lower in the test group compared to the control group. We believe that the application of parameters obtained by spectral analysis could be of great significance in assessing the locomotion impairment in any kind of motion. [Projekat Ministarstva nauke Republike Srbije, br. III41007 i br. ON174028
Pan, C.; Rogers, D.
2012-12-01
Characterizing the thermal infrared (TIR) spectral mixing behavior of compacted fine-grained mineral assemblages is necessary for facilitating quantitative mineralogy of sedimentary surfaces from spectral measurements. Previous researchers have demonstrated that TIR spectra from igneous and metamorphic rocks as well as coarse-grained (>63 micron) sand mixtures combine in proportion to their volume abundance. However, the spectral mixing behavior of compacted, fine-grained mineral mixtures that would be characteristic of sedimentary depositional environments has received little attention. Here we characterize the spectral properties of pressed pellet samples of pestle and centrifuged to obtain less than 10 micron size. Pure phases and mixtures of two, three and four components were made in varying proportions by volume. All of the samples were pressed into pellets at 15000PSI to minimize volume scattering. Thermal infrared spectra of pellets were measured in the Vibrational Spectroscopy Laboratory at Stony Brook University with a Thermo Fisher Nicolet 6700 Fourier transform infrared Michelson interferometer from ~225 to 2000 cm-1. Our preliminary results indicate that some pelletized samples have contributions from volume scattering, which leads to non-linear spectral combinations. It is not clear if the transparency features (which arise from multiple surface reflections of incident photons) are due to minor clinging fines on an otherwise specular pellet surface or to partially transmitted energy through optically thin grains in the compacted mixture. Inclusion of loose powder (analysis of TES and Mini-TES data of lithified sedimentary deposits.
Parametric and Non-Parametric System Modelling
DEFF Research Database (Denmark)
Nielsen, Henrik Aalborg
1999-01-01
the focus is on combinations of parametric and non-parametric methods of regression. This combination can be in terms of additive models where e.g. one or more non-parametric term is added to a linear regression model. It can also be in terms of conditional parametric models where the coefficients...... considered. It is shown that adaptive estimation in conditional parametric models can be performed by combining the well known methods of local polynomial regression and recursive least squares with exponential forgetting. The approach used for estimation in conditional parametric models also highlights how...... networks is included. In this paper, neural networks are used for predicting the electricity production of a wind farm. The results are compared with results obtained using an adaptively estimated ARX-model. Finally, two papers on stochastic differential equations are included. In the first paper, among...
Nonparametric Bayes Modeling of Multivariate Categorical Data.
Dunson, David B; Xing, Chuanhua
2012-01-01
Modeling of multivariate unordered categorical (nominal) data is a challenging problem, particularly in high dimensions and cases in which one wishes to avoid strong assumptions about the dependence structure. Commonly used approaches rely on the incorporation of latent Gaussian random variables or parametric latent class models. The goal of this article is to develop a nonparametric Bayes approach, which defines a prior with full support on the space of distributions for multiple unordered categorical variables. This support condition ensures that we are not restricting the dependence structure a priori. We show this can be accomplished through a Dirichlet process mixture of product multinomial distributions, which is also a convenient form for posterior computation. Methods for nonparametric testing of violations of independence are proposed, and the methods are applied to model positional dependence within transcription factor binding motifs.
Hu, Zhi-yu; Zhang, Lei; Ma, Wei-guang; Yan, Xiao-juan; Li, Zhi-xin; Zhang, Yong-zhi; Wang, Le; Dong, Lei; Yin, Wang-bao; Jia, Suo-tang
2012-03-01
Self-designed identifying software for LIBS spectral line was introduced. Being integrated with LabVIEW, the soft ware can smooth spectral lines and pick peaks. The second difference and threshold methods were employed. Characteristic spectrum of several elements matches the NIST database, and realizes automatic spectral line identification and qualitative analysis of the basic composition of sample. This software can analyze spectrum handily and rapidly. It will be a useful tool for LIBS.
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.
High-speed vibrational imaging and spectral analysis of lipid bodies by compound Raman microscopy.
Slipchenko, Mikhail N; Le, Thuc T; Chen, Hongtao; Cheng, Ji-Xin
2009-05-28
Cells store excess energy in the form of cytoplasmic lipid droplets. At present, it is unclear how different types of fatty acids contribute to the formation of lipid droplets. We describe a compound Raman microscope capable of both high-speed chemical imaging and quantitative spectral analysis on the same platform. We used a picosecond laser source to perform coherent Raman scattering imaging of a biological sample and confocal Raman spectral analysis at points of interest. The potential of the compound Raman microscope was evaluated on lipid bodies of cultured cells and live animals. Our data indicate that the in vivo fat contains much more unsaturated fatty acids (FAs) than the fat formed via de novo synthesis in 3T3-L1 cells. Furthermore, in vivo analysis of subcutaneous adipocytes and glands revealed a dramatic difference not only in the unsaturation level but also in the thermodynamic state of FAs inside their lipid bodies. Additionally, the compound Raman microscope allows tracking of the cellular uptake of a specific fatty acid and its abundance in nascent cytoplasmic lipid droplets. The high-speed vibrational imaging and spectral analysis capability renders compound Raman microscopy an indispensible analytical tool for the study of lipid-droplet biology.
Spectral analysis of bacanora (agave-derived liquor) by using FT-Raman spectroscopy
Ortega Clavero, Valentin; Weber, Andreas; Schröder, Werner; Curticapean, Dan
2016-04-01
The industry of the agave-derived bacanora, in the northern Mexican state of Sonora, has been growing substantially in recent years. However, this higher demand still lies under the influences of a variety of social, legal, cultural, ecological and economic elements. The governmental institutions of the state have tried to encourage a sustainable development and certain levels of standardization in the production of bacanora by applying different economical and legal strategies. However, a large portion of this alcoholic beverage is still produced in a traditional and rudimentary fashion. Beyond the quality of the beverage, the lack of proper control, by using adequate instrumental methods, might represent a health risk, as in several cases traditional-distilled beverages can contain elevated levels of harmful materials. The present article describes the qualitative spectral analysis of samples of the traditional-produced distilled beverage bacanora in the range from 0 cm-1 to 3500 cm-1 by using a Fourier Transform Raman spectrometer. This particular technique has not been previously explored for the analysis of bacanora, as in the case of other beverages, including tequila. The proposed instrumental arrangement for the spectral analysis has been built by combining conventional hardware parts (Michelson interferometer, photo-diodes, visible laser, etc.) and a set of self-developed evaluation algorithms. The resulting spectral information has been compared to those of pure samples of ethanol and to the spectra from different samples of the alcoholic beverage tequila. The proposed instrumental arrangement can be used the analysis of bacanora.
Network structure exploration via Bayesian nonparametric models
International Nuclear Information System (INIS)
Chen, Y; Wang, X L; Xiang, X; Tang, B Z; Bu, J Z
2015-01-01
Complex networks provide a powerful mathematical representation of complex systems in nature and society. To understand complex networks, it is crucial to explore their internal structures, also called structural regularities. The task of network structure exploration is to determine how many groups there are in a complex network and how to group the nodes of the network. Most existing structure exploration methods need to specify either a group number or a certain type of structure when they are applied to a network. In the real world, however, the group number and also the certain type of structure that a network has are usually unknown in advance. To explore structural regularities in complex networks automatically, without any prior knowledge of the group number or the certain type of structure, we extend a probabilistic mixture model that can handle networks with any type of structure but needs to specify a group number using Bayesian nonparametric theory. We also propose a novel Bayesian nonparametric model, called the Bayesian nonparametric mixture (BNPM) model. Experiments conducted on a large number of networks with different structures show that the BNPM model is able to explore structural regularities in networks automatically with a stable, state-of-the-art performance. (paper)
portfolio optimization based on nonparametric estimation methods
Directory of Open Access Journals (Sweden)
mahsa ghandehari
2017-03-01
Full Text Available One of the major issues investors are facing with in capital markets is decision making about select an appropriate stock exchange for investing and selecting an optimal portfolio. This process is done through the risk and expected return assessment. On the other hand in portfolio selection problem if the assets expected returns are normally distributed, variance and standard deviation are used as a risk measure. But, the expected returns on assets are not necessarily normal and sometimes have dramatic differences from normal distribution. This paper with the introduction of conditional value at risk ( CVaR, as a measure of risk in a nonparametric framework, for a given expected return, offers the optimal portfolio and this method is compared with the linear programming method. The data used in this study consists of monthly returns of 15 companies selected from the top 50 companies in Tehran Stock Exchange during the winter of 1392 which is considered from April of 1388 to June of 1393. The results of this study show the superiority of nonparametric method over the linear programming method and the nonparametric method is much faster than the linear programming method.
Nonparametric Mixture Models for Supervised Image Parcellation.
Sabuncu, Mert R; Yeo, B T Thomas; Van Leemput, Koen; Fischl, Bruce; Golland, Polina
2009-09-01
We present a nonparametric, probabilistic mixture model for the supervised parcellation of images. The proposed model yields segmentation algorithms conceptually similar to the recently developed label fusion methods, which register a new image with each training image separately. Segmentation is achieved via the fusion of transferred manual labels. We show that in our framework various settings of a model parameter yield algorithms that use image intensity information differently in determining the weight of a training subject during fusion. One particular setting computes a single, global weight per training subject, whereas another setting uses locally varying weights when fusing the training data. The proposed nonparametric parcellation approach capitalizes on recently developed fast and robust pairwise image alignment tools. The use of multiple registrations allows the algorithm to be robust to occasional registration failures. We report experiments on 39 volumetric brain MRI scans with expert manual labels for the white matter, cerebral cortex, ventricles and subcortical structures. The results demonstrate that the proposed nonparametric segmentation framework yields significantly better segmentation than state-of-the-art algorithms.
Robustifying Bayesian nonparametric mixtures for count data.
Canale, Antonio; Prünster, Igor
2017-03-01
Our motivating application stems from surveys of natural populations and is characterized by large spatial heterogeneity in the counts, which makes parametric approaches to modeling local animal abundance too restrictive. We adopt a Bayesian nonparametric approach based on mixture models and innovate with respect to popular Dirichlet process mixture of Poisson kernels by increasing the model flexibility at the level both of the kernel and the nonparametric mixing measure. This allows to derive accurate and robust estimates of the distribution of local animal abundance and of the corresponding clusters. The application and a simulation study for different scenarios yield also some general methodological implications. Adding flexibility solely at the level of the mixing measure does not improve inferences, since its impact is severely limited by the rigidity of the Poisson kernel with considerable consequences in terms of bias. However, once a kernel more flexible than the Poisson is chosen, inferences can be robustified by choosing a prior more general than the Dirichlet process. Therefore, to improve the performance of Bayesian nonparametric mixtures for count data one has to enrich the model simultaneously at both levels, the kernel and the mixing measure. © 2016, The International Biometric Society.
Somers, B.; Asner, G. P.
2014-09-01
The use of imaging spectroscopy for florisic mapping of forests is complicated by the spectral similarity among co-existing species. Here we evaluated an alternative spectral unmixing strategy combining a time series of EO-1 Hyperion images and an automated feature selection in Multiple Endmember Spectral Mixture Analysis (MESMA). The temporal analysis provided a way to incorporate species phenology while feature selection indicated the best phenological time and best spectral feature set to optimize the separability between tree species. Instead of using the same set of spectral bands throughout the image which is the standard approach in MESMA, our modified Wavelength Adaptive Spectral Mixture Analysis (WASMA) approach allowed the spectral subsets to vary on a per pixel basis. As such we were able to optimize the spectral separability between the tree species present in each pixel. The potential of the new approach for floristic mapping of tree species in Hawaiian rainforests was quantitatively assessed using both simulated and actual hyperspectral image time-series. With a Cohen's Kappa coefficient of 0.65, WASMA provided a more accurate tree species map compared to conventional MESMA (Kappa = 0.54; p-value < 0.05. The flexible or adaptive use of band sets in WASMA provides an interesting avenue to address spectral similarities in complex vegetation canopies.
Hyperspectral imaging of polymer banknotes for building and analysis of spectral library
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.
Assessing and monitoring of urban vegetation using multiple endmember spectral mixture analysis
Zoran, M. A.; Savastru, R. S.; Savastru, D. M.
2013-08-01
During last years urban vegetation with significant health, biological and economical values had experienced dramatic changes due to urbanization and human activities in the metropolitan area of Bucharest in Romania. We investigated the utility of remote sensing approaches of multiple endmember spectral mixture analysis (MESMA) applied to IKONOS and Landsat TM/ETM satellite data for estimating fractional cover of urban/periurban forest, parks, agricultural vegetation areas. Because of the spectral heterogeneity of same physical features of urban vegetation increases with the increase of image resolution, the traditional spectral information-based statistical method may not be useful to classify land cover dynamics from high resolution imageries like IKONOS. So we used hierarchy tree classification method in classification and MESMA for vegetation land cover dynamics assessment based on available IKONOS high-resolution imagery of Bucharest town. This study employs thirty two endmembers and six hundred and sixty spectral models to identify all Earth's features (vegetation, water, soil, impervious) and shade in the Bucharest area. The mean RMS error for the selected vegetation land cover classes range from 0.0027 to 0.018. The Pearson correlation between the fraction outputs from MESMA and reference data from all IKONOS images 1m panchromatic resolution data for urban/periurban vegetation were ranging in the domain 0.7048 - 0.8287. The framework in this study can be applied to other urban vegetation areas in Romania.
Spectral decomposition in advection-diffusion analysis by finite element methods
International Nuclear Information System (INIS)
Nickell, R.E.; Gartling, D.K.; Strang, G.
1978-01-01
In a recent study of the convergence properties of finite element methods in nonlinear fluid mechanics, an indirect approach was taken. A two-dimensional example with a known exact solution was chosen as the vehicle for the study, and various mesh refinements were tested in an attempt to extract information on the effect of the local Reynolds number. However, more direct approaches are usually preferred. In this study one such direct approach is followed, based upon the spectral decomposition of the solution operator. Spectral decomposition is widely employed as a solution technique for linear structural dynamics problems and can be applied readily to linear, transient heat transfer analysis; in this case, the extension to nonlinear problems is of interest. It was shown previously that spectral techniques were applicable to stiff systems of rate equations, while recent studies of geometrically and materially nonlinear structural dynamics have demonstrated the increased information content of the numerical results. The use of spectral decomposition in nonlinear problems of heat and mass transfer would be expected to yield equally increased flow of information to the analyst, and this information could include a quantitative comparison of various solution strategies, meshes, and element hierarchies
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.)
Vo, T D; Dwyer, G; Szeto, H H
1986-04-01
A relatively powerful and inexpensive microcomputer-based system for the spectral analysis of the EEG is presented. High resolution and speed is achieved with the use of recently available large-scale integrated circuit technology with enhanced functionality (INTEL Math co-processors 8087) which can perform transcendental functions rapidly. The versatility of the system is achieved with a hardware organization that has distributed data acquisition capability performed by the use of a microprocessor-based analog to digital converter with large resident memory (Cyborg ISAAC-2000). Compiled BASIC programs and assembly language subroutines perform on-line or off-line the fast Fourier transform and spectral analysis of the EEG which is stored as soft as well as hard copy. Some results obtained from test application of the entire system in animal studies are presented.
High-Selectivity Filter Banks for Spectral Analysis of Music Signals
Directory of Open Access Journals (Sweden)
Luiz W. P. Biscainho
2007-01-01
Full Text Available This paper approaches, under a unified framework, several algorithms for the spectral analysis of musical signals. Such algorithms include the fast Fourier transform (FFT, the fast filter bank (FFB, the constant-Q transform (CQT, and the bounded-Q transform (BQT, previously known from the associated literature. Two new methods are then introduced, namely, the constant-Q fast filter bank (CQFFB and the bounded-Q fast filter bank (BQFFB, combining the positive characteristics of the previously mentioned algorithms. The provided analyses indicate that the proposed BQFFB achieves an excellent compromise between the reduced computational effort of the FFT, the high selectivity of each output channel of the FFB, and the efficient distribution of frequency channels associated to the CQT and BQT methods. Examples are included to illustrate the performances of these methods in the spectral analysis of music signals.
Spectral analysis of the He-enriched sdO-star HD 127493
Dorsch, Matti; Latour, Marilyn; Heber, Ulrich
2018-02-01
The bright sdO star HD127493 is known to be of mixed H/He composition and excellent archival spectra covering both optical and ultraviolet ranges are available. UV spectra play a key role as they give access to many chemical species that do not show spectral lines in the optical, such as iron and nickel. This encouraged the quantitative spectral analysis of this prototypical mixed H/He composition sdO star. We determined atmospheric parameters for HD127493 in addition to the abundance of C, N, O, Si, S, Fe, and Ni in the atmosphere using non-LTE model atmospheres calculated with TLUSTY/SYNSPEC. A comparison between the parallax distance measured by Hipparcos and the derived spectroscopic distance indicate that the derived atmospheric parameters are realistic. From our metal abundance analysis, we find a strong CNO signature and enrichment in iron and nickel.
Localized Spectral Analysis of Fluctuating Power Generation from Solar Energy Systems
Directory of Open Access Journals (Sweden)
Johan Nijs
2007-01-01
Full Text Available Fluctuations in solar irradiance are a serious obstacle for the future large-scale application of photovoltaics. Occurring regularly with the passage of clouds, they can cause unexpected power variations and introduce voltage dips to the power distribution system. This paper proposes the treatment of such fluctuating time series as realizations of a stochastic, locally stationary, wavelet process. Its local spectral density can be estimated from empirical data by means of wavelet periodograms. The wavelet approach allows the analysis of the amplitude of fluctuations per characteristic scale, hence, persistence of the fluctuation. Furthermore, conclusions can be drawn on the frequency of occurrence of fluctuations of different scale. This localized spectral analysis was applied to empirical data of two successive years. The approach is especially useful for network planning and load management of power distribution systems containing a high density of photovoltaic generation units.
Energy Technology Data Exchange (ETDEWEB)
Michalsky, J.; Harrison, L. [State Univ. of New York, Albany, NY (United States)
1996-04-01
Our goal in the Atmospheric Radiation Measurement (ARM) Program is the improvement of radiation models used in general circulation models (GCMs), especially in the shortwave, (1) by providing improved shortwave radiometric measurements for the testing of models and (2) by developing methods for retrieving climatologically sensitive parameters that serve as input to shortwave and longwave models. At the Atmospheric Sciences Research Center (ASRC) in Albany, New York, we are acquiring downwelling direct and diffuse spectral irradiance, at six wavelengths, plus downwelling broadband longwave, and upwelling and downwelling broadband shortwave irradiances that we combine with National Weather Service surface and upper air data from the Albany airport as a test data set for ARM modelers. We have also developed algorithms to improve shortwave measurements made at the Southern Great Plains (SGP) ARM site by standard thermopile instruments and by the multifilter rotating shadowband radiometer (MFRSR) based on these Albany data sets. Much time has been spent developing techniques to retrieve column aerosol, water vapor, and ozone from the direct beam spectral measurements of the MFRSR. Additionally, we have had success in calculating shortwave surface albedo and aerosol optical depth from the ratio of direct to diffuse spectral reflectance.
Spectral analysis of Jupiter kilometric radio emissions during the Ulysses flyby
Echer, M. P. D. S.; Echer, E.; Gonzalez, W.; Magalães, F. P.
2016-12-01
In this work we analyze Ulysses URAP kilometric radio data during Ulysses Jupiter flyby. The interval selected for analysis was from October 1991 to February 1992. URAP 10-min averages of auroral (bkom) and torus (nkom) radio data are used. The wavelet and iterative regression spectral analyses techniques are employed on both data set. The results obtained will enable us to determine the major frequencies present in the auroral and torus data and study their similar and different periodicities.
Spectral analysis of surface waves method to assess shear wave velocity within centrifuge models
MURILLO, Carol Andrea; THOREL, Luc; CAICEDO, Bernardo
2009-01-01
The method of the spectral analysis of surface waves (SASW) is tested out on reduced scale centrifuge models, with a specific device, called the mini Falling Weight, developed for this purpose. Tests are performed on layered materials made of a mixture of sand and clay. The shear wave velocity VS determined within the models using the SASW is compared with the laboratory measurements carried out using the bender element test. The results show that the SASW technique applied to centrifuge test...
Spectral Analysis Related to Bare-Metal and Drug-Eluting Coronary Stent Implantation
Energy Technology Data Exchange (ETDEWEB)
Silva, Rose Mary Ferreira Lisboa da, E-mail: roselisboa@cardiol.br [Faculdade de Medicina da UFMG, Divinópolis, MG (Brazil); Silva, Carlos Augusto Bueno [Faculdade de Medicina da UFMG, Divinópolis, MG (Brazil); Belo Horizonte, Hospital São João de Deus, Divinópolis, MG (Brazil); Greco, Otaviano José [Belo Horizonte, Hospital São João de Deus, Divinópolis, MG (Brazil); Moreira, Maria da Consolação Vieira [Faculdade de Medicina da UFMG, Divinópolis, MG (Brazil)
2014-08-15
The autonomic nervous system plays a central role in cardiovascular regulation; sympathetic activation occurs during myocardial ischemia. To assess the spectral analysis of heart rate variability during stent implantation, comparing the types of stent. This study assessed 61 patients (mean age, 64.0 years; 35 men) with ischemic heart disease and indication for stenting. Stent implantation was performed under Holter monitoring to record the spectral analysis of heart rate variability (Fourier transform), measuring the low-frequency (LF) and high-frequency (HF) components, and the LF/HF ratio before and during the procedure. Bare-metal stent was implanted in 34 patients, while the others received drug-eluting stents. The right coronary artery was approached in 21 patients, the left anterior descending, in 28, and the circumflex, in 9. As compared with the pre-stenting period, all patients showed an increase in LF and HF during stent implantation (658 versus 185 ms2, p = 0.00; 322 versus 121, p = 0.00, respectively), with no change in LF/HF. During stent implantation, LF was 864 ms2 in patients with bare-metal stents, and 398 ms2 in those with drug-eluting stents (p = 0.00). The spectral analysis of heart rate variability showed no association with diabetes mellitus, family history, clinical presentation, beta-blockers, age, and vessel or its segment. Stent implantation resulted in concomitant sympathetic and vagal activations. Diabetes mellitus, use of beta-blockers, and the vessel approached showed no influence on the spectral analysis of heart rate variability. Sympathetic activation was lower during the implantation of drug-eluting stents.
Perturbation method utilization in the analysis of the Convertible Spectral Shift Reactor (RCVS)
International Nuclear Information System (INIS)
Bruna, G.B; Legendre, J.F.; Porta, J.; Doriath, J.Y.
1988-01-01
In the framework of the preliminary faisability studies on a new core concept, techniques derived from perturbation theory show-up very useful in the calculation and physical analysis of project parameters. We show, in the present work, some applications of these methods to the RCVS (Reacteur Convertible a Variation de Spectre - Convertible Spectral Shift Reactor) Concept studies. Actually, we present here the search of a few group project type energy structure and the splitting of reactivity effects into individual components [fr
Czech Academy of Sciences Publication Activity Database
Hovorka, Ondřej; Šubr, Vladimír; Větvička, David; Kovář, Lubomír; Strohalm, Jiří; Strohalm, Martin; Benda, Aleš; Hof, Martin; Ulbrich, Karel; Říhová, Blanka
2010-01-01
Roč. 76, č. 3 (2010), s. 514-524 ISSN 0939-6411 R&D Projects: GA AV ČR IAA400200702; GA AV ČR IAAX00500803; GA MŠk(CZ) LC06063 Institutional research plan: CEZ:AV0Z50200510; CEZ:AV0Z40400503; CEZ:AV0Z40500505 Keywords : doxorubicin * spectral analysis * fluorescence Subject RIV: EC - Immunology Impact factor: 4.304, year: 2010
Directory of Open Access Journals (Sweden)
Z. Pashazadeh Atabakan
2013-01-01
Full Text Available Spectral homotopy analysis method (SHAM as a modification of homotopy analysis method (HAM is applied to obtain solution of high-order nonlinear Fredholm integro-differential problems. The existence and uniqueness of the solution and convergence of the proposed method are proved. Some examples are given to approve the efficiency and the accuracy of the proposed method. The SHAM results show that the proposed approach is quite reasonable when compared to homotopy analysis method, Lagrange interpolation solutions, and exact solutions.
Tibau, Elisenda; Valencia, Miguel; Soriano, Jordi
2013-01-01
Neuronal networks in vitro are prominent systems to study the development of connections in living neuronal networks and the interplay between connectivity, activity and function. These cultured networks show a rich spontaneous activity that evolves concurrently with the connectivity of the underlying network. In this work we monitor the development of neuronal cultures, and record their activity using calcium fluorescence imaging. We use spectral analysis to characterize global dynamical and structural traits of the neuronal cultures. We first observe that the power spectrum can be used as a signature of the state of the network, for instance when inhibition is active or silent, as well as a measure of the network's connectivity strength. Second, the power spectrum identifies prominent developmental changes in the network such as GABAA switch. And third, the analysis of the spatial distribution of the spectral density, in experiments with a controlled disintegration of the network through CNQX, an AMPA-glutamate receptor antagonist in excitatory neurons, reveals the existence of communities of strongly connected, highly active neurons that display synchronous oscillations. Our work illustrates the interest of spectral analysis for the study of in vitro networks, and its potential use as a network-state indicator, for instance to compare healthy and diseased neuronal networks.
Directory of Open Access Journals (Sweden)
Qian Wang
2016-01-01
Full Text Available Spectroscopy is an efficient and widely used quantitative analysis method. In this paper, a spectral quantitative analysis model with combining wavelength selection and topology structure optimization is proposed. For the proposed method, backpropagation neural network is adopted for building the component prediction model, and the simultaneousness optimization of the wavelength selection and the topology structure of neural network is realized by nonlinear adaptive evolutionary programming (NAEP. The hybrid chromosome in binary scheme of NAEP has three parts. The first part represents the topology structure of neural network, the second part represents the selection of wavelengths in the spectral data, and the third part represents the parameters of mutation of NAEP. Two real flue gas datasets are used in the experiments. In order to present the effectiveness of the methods, the partial least squares with full spectrum, the partial least squares combined with genetic algorithm, the uninformative variable elimination method, the backpropagation neural network with full spectrum, the backpropagation neural network combined with genetic algorithm, and the proposed method are performed for building the component prediction model. Experimental results verify that the proposed method has the ability to predict more accurately and robustly as a practical spectral analysis tool.
Moghaderi, Hamid; Dehghan, Mehdi; Donatelli, Marco; Mazza, Mariarosa
2017-12-01
Fractional diffusion equations (FDEs) are a mathematical tool used for describing some special diffusion phenomena arising in many different applications like porous media and computational finance. In this paper, we focus on a two-dimensional space-FDE problem discretized by means of a second order finite difference scheme obtained as combination of the Crank-Nicolson scheme and the so-called weighted and shifted Grünwald formula. By fully exploiting the Toeplitz-like structure of the resulting linear system, we provide a detailed spectral analysis of the coefficient matrix at each time step, both in the case of constant and variable diffusion coefficients. Such a spectral analysis has a very crucial role, since it can be used for designing fast and robust iterative solvers. In particular, we employ the obtained spectral information to define a Galerkin multigrid method based on the classical linear interpolation as grid transfer operator and damped-Jacobi as smoother, and to prove the linear convergence rate of the corresponding two-grid method. The theoretical analysis suggests that the proposed grid transfer operator is strong enough for working also with the V-cycle method and the geometric multigrid. On this basis, we introduce two computationally favourable variants of the proposed multigrid method and we use them as preconditioners for Krylov methods. Several numerical results confirm that the resulting preconditioning strategies still keep a linear convergence rate.
Using spectral imaging for the analysis of abnormalities for colorectal cancer: When is it helpful?
Awan, Ruqayya; Al-Maadeed, Somaya; Al-Saady, Rafif
2018-01-01
The spectral imaging technique has been shown to provide more discriminative information than the RGB images and has been proposed for a range of problems. There are many studies demonstrating its potential for the analysis of histopathology images for abnormality detection but there have been discrepancies among previous studies as well. Many multispectral based methods have been proposed for histopathology images but the significance of the use of whole multispectral cube versus a subset of bands or a single band is still arguable. We performed comprehensive analysis using individual bands and different subsets of bands to determine the effectiveness of spectral information for determining the anomaly in colorectal images. Our multispectral colorectal dataset consists of four classes, each represented by infra-red spectrum bands in addition to the visual spectrum bands. We performed our analysis of spectral imaging by stratifying the abnormalities using both spatial and spectral information. For our experiments, we used a combination of texture descriptors with an ensemble classification approach that performed best on our dataset. We applied our method to another dataset and got comparable results with those obtained using the state-of-the-art method and convolutional neural network based method. Moreover, we explored the relationship of the number of bands with the problem complexity and found that higher number of bands is required for a complex task to achieve improved performance. Our results demonstrate a synergy between infra-red and visual spectrum by improving the classification accuracy (by 6%) on incorporating the infra-red representation. We also highlight the importance of how the dataset should be divided into training and testing set for evaluating the histopathology image-based approaches, which has not been considered in previous studies on multispectral histopathology images.
An Excel‐based implementation of the spectral method of action potential alternans analysis
Pearman, Charles M.
2014-01-01
Abstract Action potential (AP) alternans has been well established as a mechanism of arrhythmogenesis and sudden cardiac death. Proper interpretation of AP alternans requires a robust method of alternans quantification. Traditional methods of alternans analysis neglect higher order periodicities that may have greater pro‐arrhythmic potential than classical 2:1 alternans. The spectral method of alternans analysis, already widely used in the related study of microvolt T‐wave alternans, has also been used to study AP alternans. Software to meet the specific needs of AP alternans analysis is not currently available in the public domain. An AP analysis tool is implemented here, written in Visual Basic for Applications and using Microsoft Excel as a shell. This performs a sophisticated analysis of alternans behavior allowing reliable distinction of alternans from random fluctuations, quantification of alternans magnitude, and identification of which phases of the AP are most affected. In addition, the spectral method has been adapted to allow detection and quantification of higher order regular oscillations. Analysis of action potential morphology is also performed. A simple user interface enables easy import, analysis, and export of collated results. PMID:25501439
An Excel-based implementation of the spectral method of action potential alternans analysis.
Pearman, Charles M
2014-12-01
Action potential (AP) alternans has been well established as a mechanism of arrhythmogenesis and sudden cardiac death. Proper interpretation of AP alternans requires a robust method of alternans quantification. Traditional methods of alternans analysis neglect higher order periodicities that may have greater pro-arrhythmic potential than classical 2:1 alternans. The spectral method of alternans analysis, already widely used in the related study of microvolt T-wave alternans, has also been used to study AP alternans. Software to meet the specific needs of AP alternans analysis is not currently available in the public domain. An AP analysis tool is implemented here, written in Visual Basic for Applications and using Microsoft Excel as a shell. This performs a sophisticated analysis of alternans behavior allowing reliable distinction of alternans from random fluctuations, quantification of alternans magnitude, and identification of which phases of the AP are most affected. In addition, the spectral method has been adapted to allow detection and quantification of higher order regular oscillations. Analysis of action potential morphology is also performed. A simple user interface enables easy import, analysis, and export of collated results. © 2014 The Author. Physiological Reports published by Wiley Periodicals, Inc. on behalf of the American Physiological Society and The Physiological Society.
Monte-Carlo error analysis in x-ray spectral deconvolution
International Nuclear Information System (INIS)
Shirk, D.G.; Hoffman, N.M.
1985-01-01
The deconvolution of spectral information from sparse x-ray data is a widely encountered problem in data analysis. An often-neglected aspect of this problem is the propagation of random error in the deconvolution process. We have developed a Monte-Carlo approach that enables us to attach error bars to unfolded x-ray spectra. Our Monte-Carlo error analysis has been incorporated into two specific deconvolution techniques: the first is an iterative convergent weight method; the second is a singular-value-decomposition (SVD) method. These two methods were applied to an x-ray spectral deconvolution problem having m channels of observations with n points in energy space. When m is less than n, this problem has no unique solution. We discuss the systematics of nonunique solutions and energy-dependent error bars for both methods. The Monte-Carlo approach has a particular benefit in relation to the SVD method: It allows us to apply the constraint of spectral nonnegativity after the SVD deconvolution rather than before. Consequently, we can identify inconsistencies between different detector channels
Spectral methods for the detection of network community structure: a comparative analysis
International Nuclear Information System (INIS)
Shen, Hua-Wei; Cheng, Xue-Qi
2010-01-01
Spectral analysis has been successfully applied to the detection of community structure of networks, respectively being based on the adjacency matrix, the standard Laplacian matrix, the normalized Laplacian matrix, the modularity matrix, the correlation matrix and several other variants of these matrices. However, the comparison between these spectral methods is less reported. More importantly, it is still unclear which matrix is more appropriate for the detection of community structure. This paper answers the question by evaluating the effectiveness of these five matrices against benchmark networks with heterogeneous distributions of node degree and community size. Test results demonstrate that the normalized Laplacian matrix and the correlation matrix significantly outperform the other three matrices at identifying the community structure of networks. This indicates that it is crucial to take into account the heterogeneous distribution of node degree when using spectral analysis for the detection of community structure. In addition, to our surprise, the modularity matrix exhibits very similar performance to the adjacency matrix, which indicates that the modularity matrix does not gain benefits from using the configuration model as a reference network with the consideration of the node degree heterogeneity
Identification of mineral compositions in some renal calculi by FT Raman and IR spectral analysis
Tonannavar, J.; Deshpande, Gouri; Yenagi, Jayashree; Patil, Siddanagouda B.; Patil, Nikhil A.; Mulimani, B. G.
2016-02-01
We present in this paper accurate and reliable Raman and IR spectral identification of mineral constituents in nine samples of renal calculi (kidney stones) removed from patients suffering from nephrolithiasis. The identified mineral components include Calcium Oxalate Monohydrate (COM, whewellite), Calcium Oxalate Dihydrate (COD, weddellite), Magnesium Ammonium Phosphate Hexahydrate (MAPH, struvite), Calcium Hydrogen Phosphate Dihydrate (CHPD, brushite), Pentacalcium Hydroxy Triphosphate (PCHT, hydroxyapatite) and Uric Acid (UA). The identification is based on a satisfactory assignment of all the observed IR and Raman bands (3500-400 cm- 1) to chemical functional groups of mineral components in the samples, aided by spectral analysis of pure materials of COM, MAPH, CHPD and UA. It is found that the eight samples are composed of COM as the common component, the other mineral species as common components are: MAPH in five samples, PCHT in three samples, COD in three samples, UA in three samples and CHPD in two samples. One sample is wholly composed of UA as a single component; this inference is supported by the good agreement between ab initio density functional theoretical spectra and experimental spectral measurements of both sample and pure material. A combined application of Raman and IR techniques has shown that, where the IR is ambiguous, the Raman analysis can differentiate COD from COM and PCHT from MAPH.
Arbitrary-order Hilbert Spectral Analysis and Intermittency in Solar Wind Density Fluctuations
Carbone, Francesco; Sorriso-Valvo, Luca; Alberti, Tommaso; Lepreti, Fabio; Chen, Christopher H. K.; Němeček, Zdenek; Šafránková, Jana
2018-05-01
The properties of inertial- and kinetic-range solar wind turbulence have been investigated with the arbitrary-order Hilbert spectral analysis method, applied to high-resolution density measurements. Due to the small sample size and to the presence of strong nonstationary behavior and large-scale structures, the classical analysis in terms of structure functions may prove to be unsuccessful in detecting the power-law behavior in the inertial range, and may underestimate the scaling exponents. However, the Hilbert spectral method provides an optimal estimation of the scaling exponents, which have been found to be close to those for velocity fluctuations in fully developed hydrodynamic turbulence. At smaller scales, below the proton gyroscale, the system loses its intermittent multiscaling properties and converges to a monofractal process. The resulting scaling exponents, obtained at small scales, are in good agreement with those of classical fractional Brownian motion, indicating a long-term memory in the process, and the absence of correlations around the spectral-break scale. These results provide important constraints on models of kinetic-range turbulence in the solar wind.
Identification of mineral compositions in some renal calculi by FT Raman and IR spectral analysis.
Tonannavar, J; Deshpande, Gouri; Yenagi, Jayashree; Patil, Siddanagouda B; Patil, Nikhil A; Mulimani, B G
2016-02-05
We present in this paper accurate and reliable Raman and IR spectral identification of mineral constituents in nine samples of renal calculi (kidney stones) removed from patients suffering from nephrolithiasis. The identified mineral components include Calcium Oxalate Monohydrate (COM, whewellite), Calcium Oxalate Dihydrate (COD, weddellite), Magnesium Ammonium Phosphate Hexahydrate (MAPH, struvite), Calcium Hydrogen Phosphate Dihydrate (CHPD, brushite), Pentacalcium Hydroxy Triphosphate (PCHT, hydroxyapatite) and Uric Acid (UA). The identification is based on a satisfactory assignment of all the observed IR and Raman bands (3500-400c m(-1)) to chemical functional groups of mineral components in the samples, aided by spectral analysis of pure materials of COM, MAPH, CHPD and UA. It is found that the eight samples are composed of COM as the common component, the other mineral species as common components are: MAPH in five samples, PCHT in three samples, COD in three samples, UA in three samples and CHPD in two samples. One sample is wholly composed of UA as a single component; this inference is supported by the good agreement between ab initio density functional theoretical spectra and experimental spectral measurements of both sample and pure material. A combined application of Raman and IR techniques has shown that, where the IR is ambiguous, the Raman analysis can differentiate COD from COM and PCHT from MAPH. Copyright © 2015 Elsevier B.V. All rights reserved.
Use of fast Fourier transform in gamma-ray spectral analysis
International Nuclear Information System (INIS)
Tominaga, Shoji; Nayatani, Yoshinobu; Nagata, Shojiro; Sasaki, Takashi; Ueda, Isamu.
1978-01-01
In order to simplify the mass data processing in a response matrix method for γ-ray spectral analysis, a method using a Fast Fourier Transform has been devised. The validity of the method has been confirmed by computer simulation for spectra of a NaI detector. First, it is shown that spectral data can be represented by Fourier series with a reduced number of terms. Then the estimation of intensities of γ-ray components is performed by a matrix operation using the compressed data of an observation spectrum and standard spectra in Fourier coefficients. The identification of γ-ray energies is also easy. Several features of the method and a general problem to be solved in relation to a response matrix method are described. (author)
The quantum spectral analysis of the two-dimensional annular billiard system
International Nuclear Information System (INIS)
Yan-Hui, Zhang; Ji-Quan, Zhang; Xue-You, Xu; Sheng-Lu, Lin
2009-01-01
Based on the extended closed-orbit theory together with spectral analysis, this paper studies the correspondence between quantum mechanics and the classical counterpart in a two-dimensional annular billiard. The results demonstrate that the Fourier-transformed quantum spectra are in very good accordance with the lengths of the classical ballistic trajectories, whereas spectral strength is intimately associated with the shapes of possible open orbits connecting arbitrary two points in the annular cavity. This approach facilitates an intuitive understanding of basic quantum features such as quantum interference, locations of the wavefunctions, and allows quantitative calculations in the range of high energies, where full quantum calculations may become impractical in general. This treatment provides a thread to explore the properties of microjunction transport and even quantum chaos under the much more general system. (general)
A spectral analysis of the domain decomposed Monte Carlo method for linear systems
Energy Technology Data Exchange (ETDEWEB)
Slattery, S. R.; Wilson, P. P. H. [Engineering Physics Department, University of Wisconsin - Madison, 1500 Engineering Dr., Madison, WI 53706 (United States); Evans, T. M. [Oak Ridge National Laboratory, 1 Bethel Valley Road, Oak Ridge, TN 37830 (United States)
2013-07-01
The domain decomposed behavior of the adjoint Neumann-Ulam Monte Carlo method for solving linear systems is analyzed using the spectral properties of the linear operator. Relationships for the average length of the adjoint random walks, a measure of convergence speed and serial performance, are made with respect to the eigenvalues of the linear operator. In addition, relationships for the effective optical thickness of a domain in the decomposition are presented based on the spectral analysis and diffusion theory. Using the effective optical thickness, the Wigner rational approximation and the mean chord approximation are applied to estimate the leakage fraction of stochastic histories from a domain in the decomposition as a measure of parallel performance and potential communication costs. The one-speed, two-dimensional neutron diffusion equation is used as a model problem to test the models for symmetric operators. In general, the derived approximations show good agreement with measured computational results. (authors)
Use of the spectral analysis for estimating the intensity of a weak periodic source
International Nuclear Information System (INIS)
Marseguerra, M.
1989-01-01
This paper deals with the possibility of exploiting spectral methods for the analysis of counting experiments in which one has to estimate the intensity of a weak periodic source of particles buried in a high background. The general theoretical expressions here obtained for the auto- and cross-spectra are applied to three kinds of simulated experiments. In all cases it turns out that the source intensity can acutally be estimated with a standard deviation comparable with that obtained in classical experiments in which the source can be moved out. Thus the spectral methods represent an interesting technique nowadays easy to implement on low-cost computers which could also be used in many research fields by suitably redesigning classical experiments. The convenience of using these methods in the field of nuclear safeguards is presently investigated in our Institute. (orig.)
A spectral analysis of the domain decomposed Monte Carlo method for linear systems
International Nuclear Information System (INIS)
Slattery, S. R.; Wilson, P. P. H.; Evans, T. M.
2013-01-01
The domain decomposed behavior of the adjoint Neumann-Ulam Monte Carlo method for solving linear systems is analyzed using the spectral properties of the linear operator. Relationships for the average length of the adjoint random walks, a measure of convergence speed and serial performance, are made with respect to the eigenvalues of the linear operator. In addition, relationships for the effective optical thickness of a domain in the decomposition are presented based on the spectral analysis and diffusion theory. Using the effective optical thickness, the Wigner rational approximation and the mean chord approximation are applied to estimate the leakage fraction of stochastic histories from a domain in the decomposition as a measure of parallel performance and potential communication costs. The one-speed, two-dimensional neutron diffusion equation is used as a model problem to test the models for symmetric operators. In general, the derived approximations show good agreement with measured computational results. (authors)
Wavelet-based spectral finite element dynamic analysis for an axially moving Timoshenko beam
Mokhtari, Ali; Mirdamadi, Hamid Reza; Ghayour, Mostafa
2017-08-01
In this article, wavelet-based spectral finite element (WSFE) model is formulated for time domain and wave domain dynamic analysis of an axially moving Timoshenko beam subjected to axial pretension. The formulation is similar to conventional FFT-based spectral finite element (SFE) model except that Daubechies wavelet basis functions are used for temporal discretization of the governing partial differential equations into a set of ordinary differential equations. The localized nature of Daubechies wavelet basis functions helps to rule out problems of SFE model due to periodicity assumption, especially during inverse Fourier transformation and back to time domain. The high accuracy of WSFE model is then evaluated by comparing its results with those of conventional finite element and SFE results. The effects of moving beam speed and axial tensile force on vibration and wave characteristics, and static and dynamic stabilities of moving beam are investigated.
Energy Technology Data Exchange (ETDEWEB)
Martinez-Torres, C.; Streppa, L. [CNRS, UMR5672, Laboratoire de Physique, Ecole Normale Supérieure de Lyon, 46 Allée d' Italie, Université de Lyon, 69007 Lyon (France); Arneodo, A.; Argoul, F. [CNRS, UMR5672, Laboratoire de Physique, Ecole Normale Supérieure de Lyon, 46 Allée d' Italie, Université de Lyon, 69007 Lyon (France); CNRS, UMR5798, Laboratoire Ondes et Matière d' Aquitaine, Université de Bordeaux, 351 Cours de la Libération, 33405 Talence (France); Argoul, P. [Université Paris-Est, Ecole des Ponts ParisTech, SDOA, MAST, IFSTTAR, 14-20 Bd Newton, Cité Descartes, 77420 Champs sur Marne (France)
2016-01-18
Compared to active microrheology where a known force or modulation is periodically imposed to a soft material, passive microrheology relies on the spectral analysis of the spontaneous motion of tracers inherent or external to the material. Passive microrheology studies of soft or living materials with atomic force microscopy (AFM) cantilever tips are rather rare because, in the spectral densities, the rheological response of the materials is hardly distinguishable from other sources of random or periodic perturbations. To circumvent this difficulty, we propose here a wavelet-based decomposition of AFM cantilever tip fluctuations and we show that when applying this multi-scale method to soft polymer layers and to living myoblasts, the structural damping exponents of these soft materials can be retrieved.
Spectral Analysis of the sdO Standard Star Feige 34
Latour, M.; Chayer, P.; Green, E. M.; Fontaine, G.
2017-03-01
We present our current work on the spectral analysis of the hot sdO star Feige 34. We combine high S/N optical spectra and fully-blanketed non-LTE model atmospheres to derive its fundamental parameters (Teff, log g) and helium abundance. Our best fits indicate Teff = 63 000 K, log g = 6.0 and log N(He)/N(H) = -1.8. We also use available ultraviolet spectra (IUE and FUSE) to measure metal abundances. We find the star to be enriched in iron and nickel by a factor of ten with respect to the solar values, while lighter elements have subsolar abundances. The FUSE spectrum suggests that the spectral lines could be broadened by rotation.
International Nuclear Information System (INIS)
Haaland, D.M.; Easterling, R.G.; Vopicka, D.A.
1985-01-01
In an extension of earlier work, weighted multivariate least-squares methods of quantitative FT-IR analysis have been developed. A linear least-squares approximation to nonlinearities in the Beer-Lambert law is made by allowing the reference spectra to be a set of known mixtures, The incorporation of nonzero intercepts in the relation between absorbance and concentration further improves the approximation of nonlinearities while simultaneously accounting for nonzero spectra baselines. Pathlength variations are also accommodated in the analysis, and under certain conditions, unknown sample pathlengths can be determined. All spectral data are used to improve the precision and accuracy of the estimated concentrations. During the calibration phase of the analysis, pure component spectra are estimated from the standard mixture spectra. These can be compared with the measured pure component spectra to determine which vibrations experience nonlinear behavior. In the predictive phase of the analysis, the calculated spectra are used in our previous least-squares analysis to estimate sample component concentrations. These methods were applied to the analysis of the IR spectra of binary mixtures of esters. Even with severely overlapping spectral bands and nonlinearities in the Beer-Lambert law, the average relative error in the estimated concentration was <1%
TOF plotter - a program to perform routine analysis time-of-flight mass spectral data
International Nuclear Information System (INIS)
Knippel, Brad C.; Padgett, Clifford W.; Marcus, R. Kenneth
2004-01-01
The main article discusses the operation and application of the program to mass spectral data files. This laboratory has recently reported the construction and characterization of a linear time-of-flight mass spectrometer (ToF-MS) utilizing a radio frequency glow discharge ionization source. Data acquisition and analysis was performed using a digital oscilloscope and Microsoft Excel, respectively. Presently, no software package is available that is specifically designed for time-of-flight mass spectral analysis that is not instrument dependent. While spreadsheet applications such as Excel offer tremendous utility, they can be cumbersome when repeatedly performing tasks which are too complex or too user intensive for macros to be viable. To address this situation and make data analysis a faster, simpler task, our laboratory has developed a Microsoft Windows-based software program coded in Microsoft Visual Basic. This program enables the user to rapidly perform routine data analysis tasks such as mass calibration, plotting and smoothing on x-y data sets. In addition to a suite of tools for data analysis, a number of calculators are built into the software to simplify routine calculations pertaining to linear ToF-MS. These include mass resolution, ion kinetic energy and single peak identification calculators. A detailed description of the software and its associated functions is presented followed by a characterization of its performance in the analysis of several representative ToF-MS spectra obtained from different GD-ToF-MS systems
Nonparametric Analyses of Log-Periodic Precursors to Financial Crashes
Zhou, Wei-Xing; Sornette, Didier
We apply two nonparametric methods to further test the hypothesis that log-periodicity characterizes the detrended price trajectory of large financial indices prior to financial crashes or strong corrections. The term "parametric" refers here to the use of the log-periodic power law formula to fit the data; in contrast, "nonparametric" refers to the use of general tools such as Fourier transform, and in the present case the Hilbert transform and the so-called (H, q)-analysis. The analysis using the (H, q)-derivative is applied to seven time series ending with the October 1987 crash, the October 1997 correction and the April 2000 crash of the Dow Jones Industrial Average (DJIA), the Standard & Poor 500 and Nasdaq indices. The Hilbert transform is applied to two detrended price time series in terms of the ln(tc-t) variable, where tc is the time of the crash. Taking all results together, we find strong evidence for a universal fundamental log-frequency f=1.02±0.05 corresponding to the scaling ratio λ=2.67±0.12. These values are in very good agreement with those obtained in earlier works with different parametric techniques. This note is extracted from a long unpublished report with 58 figures available at , which extensively describes the evidence we have accumulated on these seven time series, in particular by presenting all relevant details so that the reader can judge for himself or herself the validity and robustness of the results.
Communication system and spectral analysis for Ge-Li and GeHp detectors
International Nuclear Information System (INIS)
Fernandez, J.; Castano, P.; Bonino, A.D.; Righetti, M.A.
1990-01-01
An integral communication and spectral analysis system (SICADE) was developed and implemented to satisfy the need to optimize and automate the measurement system used in Atucha I nuclear power plant for the activity in the primary loop's water extracted by the TV system. The importance of these measurements is based on the fact that from the spectrometric analysis of the samples extracted, the Iodines-GN and Iodines-Iodines relations, which allow to detect the presence of deficient fuel elements, are calculated. The system developed is based on two modules integrated in a unique set commanded by the operators through the screen dialogue. (Author) [es
A Nonparametric Test for Seasonal Unit Roots
Kunst, Robert M.
2009-01-01
Abstract: We consider a nonparametric test for the null of seasonal unit roots in quarterly time series that builds on the RUR (records unit root) test by Aparicio, Escribano, and Sipols. We find that the test concept is more promising than a formalization of visual aids such as plots by quarter. In order to cope with the sensitivity of the original RUR test to autocorrelation under its null of a unit root, we suggest an augmentation step by autoregression. We present some evidence on the siz...
Elnasir, Selma; Shamsuddin, Siti Mariyam; Farokhi, Sajad
2015-01-01
Palm vein recognition (PVR) is a promising new biometric that has been applied successfully as a method of access control by many organizations, which has even further potential in the field of forensics. The palm vein pattern has highly discriminative features that are difficult to forge because of its subcutaneous position in the palm. Despite considerable progress and a few practical issues, providing accurate palm vein readings has remained an unsolved issue in biometrics. We propose a robust and more accurate PVR method based on the combination of wavelet scattering (WS) with spectral regression kernel discriminant analysis (SRKDA). As the dimension of WS generated features is quite large, SRKDA is required to reduce the extracted features to enhance the discrimination. The results based on two public databases-PolyU Hyper Spectral Palmprint public database and PolyU Multi Spectral Palmprint-show the high performance of the proposed scheme in comparison with state-of-the-art methods. The proposed approach scored a 99.44% identification rate and a 99.90% verification rate [equal error rate (EER)=0.1%] for the hyperspectral database and a 99.97% identification rate and a 99.98% verification rate (EER=0.019%) for the multispectral database.
TULEN, JHM; MULDER, G; PEPPLINKHUIZEN, L; INTVELD, AJM; VANSTEENIS, HG; MOLEMAN, P
Dose-dependent effects of intravenously administered lorazepam on haemodynamic fluctuations were studied by means of spectral analysis, in order to elucidate sympathetic and parasympathetic components in cardiovascular control during situations of rest and mental stress after benzodiazepine
J.H.M. Tulen (Joke); G. Mulder (G.); L. Pepplinkhuizen (Lolke); A.J. Man in't Veld (A.); H.G. van Steenis (H.); P. Moleman (Peter)
1994-01-01
textabstractDose-dependent effects of intravenously administered lorazepam on haemodynamic fluctuations were studied by means of spectral analysis, in order to elucidate sympathetic and parasympathetic components in cardiovascular control during situations of rest and mental stress after
A Bayesian nonparametric estimation of distributions and quantiles
International Nuclear Information System (INIS)
Poern, K.
1988-11-01
The report describes a Bayesian, nonparametric method for the estimation of a distribution function and its quantiles. The method, presupposing random sampling, is nonparametric, so the user has to specify a prior distribution on a space of distributions (and not on a parameter space). In the current application, where the method is used to estimate the uncertainty of a parametric calculational model, the Dirichlet prior distribution is to a large extent determined by the first batch of Monte Carlo-realizations. In this case the results of the estimation technique is very similar to the conventional empirical distribution function. The resulting posterior distribution is also Dirichlet, and thus facilitates the determination of probability (confidence) intervals at any given point in the space of interest. Another advantage is that also the posterior distribution of a specified quantitle can be derived and utilized to determine a probability interval for that quantile. The method was devised for use in the PROPER code package for uncertainty and sensitivity analysis. (orig.)
Generative Temporal Modelling of Neuroimaging - Decomposition and Nonparametric Testing
DEFF Research Database (Denmark)
Hald, Ditte Høvenhoff
The goal of this thesis is to explore two improvements for functional magnetic resonance imaging (fMRI) analysis; namely our proposed decomposition method and an extension to the non-parametric testing framework. Analysis of fMRI allows researchers to investigate the functional processes...... of the brain, and provides insight into neuronal coupling during mental processes or tasks. The decomposition method is a Gaussian process-based independent components analysis (GPICA), which incorporates a temporal dependency in the sources. A hierarchical model specification is used, featuring both...... instantaneous and convolutive mixing, and the inferred temporal patterns. Spatial maps are seen to capture smooth and localized stimuli-related components, and often identifiable noise components. The implementation is freely available as a GUI/SPM plugin, and we recommend using GPICA as an additional tool when...
Bayesian Nonparametric Clustering for Positive Definite Matrices.
Cherian, Anoop; Morellas, Vassilios; Papanikolopoulos, Nikolaos
2016-05-01
Symmetric Positive Definite (SPD) matrices emerge as data descriptors in several applications of computer vision such as object tracking, texture recognition, and diffusion tensor imaging. Clustering these data matrices forms an integral part of these applications, for which soft-clustering algorithms (K-Means, expectation maximization, etc.) are generally used. As is well-known, these algorithms need the number of clusters to be specified, which is difficult when the dataset scales. To address this issue, we resort to the classical nonparametric Bayesian framework by modeling the data as a mixture model using the Dirichlet process (DP) prior. Since these matrices do not conform to the Euclidean geometry, rather belongs to a curved Riemannian manifold,existing DP models cannot be directly applied. Thus, in this paper, we propose a novel DP mixture model framework for SPD matrices. Using the log-determinant divergence as the underlying dissimilarity measure to compare these matrices, and further using the connection between this measure and the Wishart distribution, we derive a novel DPM model based on the Wishart-Inverse-Wishart conjugate pair. We apply this model to several applications in computer vision. Our experiments demonstrate that our model is scalable to the dataset size and at the same time achieves superior accuracy compared to several state-of-the-art parametric and nonparametric clustering algorithms.
Spectral and morphological analysis of the remnant of supernova 1987A with ALMA and ATCA
Energy Technology Data Exchange (ETDEWEB)
Zanardo, Giovanna; Staveley-Smith, Lister [International Centre for Radio Astronomy Research (ICRAR), M468, University of Western Australia, Crawley, WA 6009 (Australia); Indebetouw, Remy; Chevalier, Roger A. [Department of Astronomy, University of Virginia, P.O. Box 400325, Charlottesville, VA 22904 (United States); Matsuura, Mikako; Barlow, Michael J. [Department of Physics and Astronomy, University College London, Gower Street, London WC1E 6BT (United Kingdom); Gaensler, Bryan M. [Australian Research Council, Centre of Excellence for All-sky Astrophysics (CAASTRO) (Australia); Fransson, Claes; Lundqvist, Peter [Department of Astronomy, Oskar Klein Center, Stockholm University, AlbaNova, SE-106 91 Stockholm (Sweden); Manchester, Richard N. [CSIRO Astronomy and Space Science, Australia Telescope National Facility, P.O. Box 76, Epping, NSW 1710 (Australia); Baes, Maarten [Sterrenkundig Observatorium, Universiteit Gent, Krijgslaan 281 S9, B-9000 Gent (Belgium); Kamenetzky, Julia R. [Steward Observatory, University of Arizona, 933 North Cherry Avenue, Tucson, AZ 85721-0065 (United States); Lakićević, Maša [Institute for the Environment, Physical Sciences and Applied Mathematics, Lennard-Jones Laboratories, Keele University, Staffordshire ST5 5BG (United Kingdom); Marcaide, Jon M. [Departamento de Astronomía, Universidad de Valencia, C/Dr. Moliner 50, E-46100 Burjassot (Spain); Martí-Vidal, Ivan [Department of Earth and Space Sciences, Chalmers University of Technology, Onsala Space Observatory, SE-439 92 Onsala (Sweden); Meixner, Margaret [Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD 21218 (United States); Ng, C.-Y. [Department of Physics, University of Hong Kong, Pokfulam Road, Hong Kong (China); Park, Sangwook, E-mail: giovanna.zanardo@gmail.com [Department of Physics, University of Texas at Arlington, 108 Science Hall, Box 19059, Arlington, TX 76019 (United States); and others
2014-12-01
We present a comprehensive spectral and morphological analysis of the remnant of supernova (SN) 1987A with the Australia Telescope Compact Array (ATCA) and the Atacama Large Millimeter/submillimeter Array (ALMA). The non-thermal and thermal components of the radio emission are investigated in images from 94 to 672 GHz (λ 3.2 mm to 450 μm), with the assistance of a high-resolution 44 GHz synchrotron template from the ATCA, and a dust template from ALMA observations at 672 GHz. An analysis of the emission distribution over the equatorial ring in images from 44 to 345 GHz highlights a gradual decrease of the east-to-west asymmetry ratio with frequency. We attribute this to the shorter synchrotron lifetime at high frequencies. Across the transition from radio to far infrared, both the synchrotron/dust-subtracted images and the spectral energy distribution (SED) suggest additional emission beside the main synchrotron component (S {sub ν}∝ν{sup –0.73}) and the thermal component originating from dust grains at T ∼ 22 K. This excess could be due to free-free flux or emission from grains of colder dust. However, a second flat-spectrum synchrotron component appears to better fit the SED, implying that the emission could be attributed to a pulsar wind nebula (PWN). The residual emission is mainly localized west of the SN site, as the spectral analysis yields –0.4 ≲ α ≲ –0.1 across the western regions, with α ∼ 0 around the central region. If there is a PWN in the remnant interior, these data suggest that the pulsar may be offset westward from the SN position.
EZ and GOSSIP, two new VO compliant tools for spectral analysis
Franzetti, P.; Garill, B.; Fumana, M.; Paioro, L.; Scodeggio, M.; Paltani, S.; Scaramella, R.
2008-10-01
We present EZ and GOSSIP, two new VO compliant tools dedicated to spectral analysis. EZ is a tool to perform automatic redshift measurement; GOSSIP is a tool created to perform the SED fitting procedure in a simple, user friendly and efficient way. These two tools have been developed by the PANDORA Group at INAF-IASF (Milano); EZ has been developed in collaboration with Osservatorio Monte Porzio (Roma) and Integral Science Data Center (Geneve). EZ is released to the astronomical community; GOSSIP is currently in beta-testing.
Spectral analysis of surface waves method to assess shear wave velocity within centrifuge models
Murillo, Carol Andrea; Thorel, Luc; Caicedo, Bernardo
2009-06-01
The method of the spectral analysis of surface waves (SASW) is tested out on reduced scale centrifuge models, with a specific device, called the mini Falling Weight, developed for this purpose. Tests are performed on layered materials made of a mixture of sand and clay. The shear wave velocity VS determined within the models using the SASW is compared with the laboratory measurements carried out using the bender element test. The results show that the SASW technique applied to centrifuge testing is a relevant method to characterize VS near the surface.
International Nuclear Information System (INIS)
Eilek, J.A.
1989-01-01
Recent theories of magnetohydrodynamic turbulence are used to construct microphysical turbulence models, with emphasis on models of anisotropic turbulence. These models have been applied to the determination of the emergent polarization from a resolved uniform source. It is found that depolarization alone is not a unique measure of the turbulence, and that the turblence will also affect the total-intensity distributions. Fluctuations in the intensity image can thus be employed to measure turbulence strength. In the second part, it is demonstrated that a power-spectral analysis of the total and polarized intensity images can be used to obtain the power spectra of the synchrotron emission. 81 refs
Energy Technology Data Exchange (ETDEWEB)
Alchimov, A B; Drobot, S I; Drokov, V G; Zarubin, V P; Kazmirov, A D; Skodaev, Y D; Podrezov, A M [Applied Physics Institute of Irkutsk State University, Irkutsk (Russian Federation)
1998-12-31
The comparison of different spectral methods of analysis for wear diagnostics of aircraft engines has been carried out. It is shown that known techniques of determination of metals content in aviation oils with the use the spectrometers MFS (Russia) and MOA (USA) give a low accuracy of measurements. As an alternative the method of wear diagnostics on the base of a scintillation spectrometer is suggested. This method possess far better metrological properties in comparison with those on the base of the spectrometer MFS and MOA. (orig.) 6 refs.
Cragin, B. L.; Hanson, W. B.; Mcclure, J. P.; Valladares, C. E.
1985-01-01
Equatorial bottomside sinusoidal (BSS) irregularities have been studied by applying techniques of cross-correlation and spectral analysis to the Atmosphere Explorer data set. The phase of the cross-correlations of the plasma number density is discussed and the two drift velocity components observed using the retarding potential analyzer and ion drift meter on the satellite are discussed. Morphology is addressed, presenting the geographical distributions of the occurrence of BSS events for the equinoxes and solstices. Physical processes including the ion Larmor flux, interhemispheric plasma flows, and variations in the lower F region Pedersen conductivity are invoked to explain the findings.
Energy Technology Data Exchange (ETDEWEB)
Alchimov, A.B.; Drobot, S.I.; Drokov, V.G.; Zarubin, V.P.; Kazmirov, A.D.; Skodaev, Y.D.; Podrezov, A.M. [Applied Physics Institute of Irkutsk State University, Irkutsk (Russian Federation)
1997-12-31
The comparison of different spectral methods of analysis for wear diagnostics of aircraft engines has been carried out. It is shown that known techniques of determination of metals content in aviation oils with the use the spectrometers MFS (Russia) and MOA (USA) give a low accuracy of measurements. As an alternative the method of wear diagnostics on the base of a scintillation spectrometer is suggested. This method possess far better metrological properties in comparison with those on the base of the spectrometer MFS and MOA. (orig.) 6 refs.
A Spectral Analysis of Discrete-Time Quantum Walks Related to the Birth and Death Chains
Ho, Choon-Lin; Ide, Yusuke; Konno, Norio; Segawa, Etsuo; Takumi, Kentaro
2018-04-01
In this paper, we consider a spectral analysis of discrete time quantum walks on the path. For isospectral coin cases, we show that the time averaged distribution and stationary distributions of the quantum walks are described by the pair of eigenvalues of the coins as well as the eigenvalues and eigenvectors of the corresponding random walks which are usually referred as the birth and death chains. As an example of the results, we derive the time averaged distribution of so-called Szegedy's walk which is related to the Ehrenfest model. It is represented by Krawtchouk polynomials which is the eigenvectors of the model and includes the arcsine law.
On the 485-day Mode in the Atmospheric Angular Momentum: Spectral Analysis of IERS Data
Tsurkis, I. Ya.; Kuchai, M. S.
2018-05-01
The modification of spectral analysis especially intended for studying the disturbing functions of the atmosphere and ocean, as well as the observed polar motion (Wiener-Liouville spectrum), is used. The time series of the atmospheric disturbing functions obtained by the U.S. National Centers for Environmental Prediction (NCEP) of the International Earth Rotation and Reference Systems Service (IERS) for the period from January 1, 1980 to June 20, 2014 (http://www.iers.org/.cs1?pid=43-1100116) are analyzed. It is shown that the baric disturbing function contains a regular mode with a period of 16 months; the contribution of this mode in the polar motion is estimated.
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.
Application of Arbitrary-Order Hilbert Spectral Analysis to Passive Scalar Turbulence
International Nuclear Information System (INIS)
Huang, Y X; Lu, Z M; Liu, Y L; Schmitt, F G; Gagne, Y
2011-01-01
In previous work [Huang et al., PRE 82, 26319, 2010], we found that the passive scalar turbulence field maybe less intermittent than what we believed before. Here we apply the same method, namely arbitrary-order Hilbert spectral analysis, to a passive scalar (temperature) time series with a Taylor's microscale Reynolds number Re λ ≅ 3000. We find that with increasing Reynolds number, the discrepancy of scaling exponents between Hilbert ξ θ (q) and Kolmogorov-Obukhov-Corrsin (KOC) theory is increasing, and consequently the discrepancy between Hilbert and structure function could disappear at infinite Reynolds number.
Gauss-Vanicek Spectral Analysis of the Sepkoski Compendium: No New Life Cycles
Omerbashich, M.
2006-01-01
New periods can emerge from data as a byproduct of incorrect processing or even the method applied. In one such recent instance, a new life cycle with a 62+-3 Myr period was reportedly found (about trend) in genus variations from the Sepkoski compendium, the world most complete fossil record. The approach that led to reporting this period was based on Fourier method of spectral analysis. I show here that no such period is found when the original data set is considered rigorously and processed...
On the detection of corrosion pit interactions using two-dimensional spectral analysis
International Nuclear Information System (INIS)
Jarrah, Adil; Nianga, Jean-Marie; Iost, Alain; Guillemot, Gildas; Najjar, Denis
2010-01-01
A statistical methodology for detecting pits interactions based on a two-dimensional spectral analysis is presented. This method can be used as a tool for the exploratory analysis of spatial point patterns and can be advanced as an alternative of classical methods based on distance. One of the major advantages of the spectral analysis approach over the use of classical methods is its ability to reveal more details about the spatial structure like the scale for which pits corrosion can be considered as independent. Furthermore, directional components of pattern can be investigated. The method is validated in a first time using numerical simulations on random, regular and aggregated structures. The density of pits, used in the numerical simulations, corresponds to that assessed from a corroded aluminium sheet. In a second time, this method is applied to verify the independence of the corrosion pits observed on the aforementioned aluminium sheet before applying the Gumbel theory to determine the maximum pit depth. Indeed, the property of independence is a prerequisite of the Gumbel theory which is one of the most frequently used in the field of safety and reliability.
Spectral analysis of coolant activity from a commercial nuclear generating station
International Nuclear Information System (INIS)
Swann, J.D.; Lewis, B.J.; Ip, M.
2008-01-01
In support of the development of a real-time on-line fuel failure monitoring system for the CANDU reactor, actual gamma spectroscopy data files from the gaseous fission product (GFP) monitoring system were acquired from almost four years of operation at a commercial Nuclear Generating Station (NGS). Several spectral analysis techniques were used to process the data files. Radioisotopic activity from the plant information (PI) system was compared to an in-house C++ code that was used to determine the photopeak area and to a separate analysis with commercial software from Canberra-Aptec. These various techniques provided for a calculation of the coolant activity concentration of the noble gas and iodine species in the primary heat transport system. These data were then used to benchmark the Visual DETECT code, a user friendly software tool which can be used to characterize the defective fuel state based on a coolant activity analysis. Acceptable agreement was found with the spectral techniques when compared to the known defective bundle history at the commercial reactor. A more generalized method of assessing the fission product release data was also considered with the development of a pre-processor to evaluate the radioisotopic release rate from mass balance considerations. The release rate provided a more efficient means to characterize the occurrence of a defect and was consistent with the actual defect situation at the power plant as determined from in-bay examination of discharged fuel bundles. (author)
Spectral analysis to detection of short circuit fault of solar photovoltaic modules in strings
International Nuclear Information System (INIS)
Sevilla-Camacho, P.Y.; Robles-Ocampo, J.B.; Zuñiga-Reyes, Marco A.
2017-01-01
This research work presents a method to detect the number of short circuit faulted solar photovoltaic modules in strings of a photovoltaic system by taking into account speed, safety, and non-use of sensors and specialized and expensive equipment. The method consists on apply the spectral analysis and statistical techniques to the alternating current output voltage of a string and detect the number of failed modules through the changes in the amplitude of the component frequency of 12 kHz. For that, the analyzed string is disconnected of the array; and a small pulsed voltage signal of frequency of 12 kHz introduces him under dark condition and controlled temperature. Previous to the analysis, the signal is analogic filtered in order to reduce the direct current signal component. The spectral analysis technique used is the Fast Fourier Transform. The obtained experimental results were validated through simulation of the alternating current equivalent circuit of a solar cell. In all experimental and simulated test, the method allowed to identify correctly the number of photovoltaic modules with short circuit in the analyzed string. (author)
Nonparametric Bayesian density estimation on manifolds with applications to planar shapes.
Bhattacharya, Abhishek; Dunson, David B
2010-12-01
Statistical analysis on landmark-based shape spaces has diverse applications in morphometrics, medical diagnostics, machine vision and other areas. These shape spaces are non-Euclidean quotient manifolds. To conduct nonparametric inferences, one may define notions of centre and spread on this manifold and work with their estimates. However, it is useful to consider full likelihood-based methods, which allow nonparametric estimation of the probability density. This article proposes a broad class of mixture models constructed using suitable kernels on a general compact metric space and then on the planar shape space in particular. Following a Bayesian approach with a nonparametric prior on the mixing distribution, conditions are obtained under which the Kullback-Leibler property holds, implying large support and weak posterior consistency. Gibbs sampling methods are developed for posterior computation, and the methods are applied to problems in density estimation and classification with shape-based predictors. Simulation studies show improved estimation performance relative to existing approaches.
Directory of Open Access Journals (Sweden)
Rabia Ece OMAY
2013-06-01
Full Text Available In this study, relationship between gross domestic product (GDP per capita and sulfur dioxide (SO2 and particulate matter (PM10 per capita is modeled for Turkey. Nonparametric fixed effect panel data analysis is used for the modeling. The panel data covers 12 territories, in first level of Nomenclature of Territorial Units for Statistics (NUTS, for period of 1990-2001. Modeling of the relationship between GDP and SO2 and PM10 for Turkey, the non-parametric models have given good results.
Spectral analysis of the stick-slip phenomenon in "oral" tribological texture evaluation.
Sanahuja, Solange; Upadhyay, Rutuja; Briesen, Heiko; Chen, Jianshe
2017-08-01
"Oral" tribology has become a new paradigm in food texture studies to understand complex texture attributes, such as creaminess, oiliness, and astringency, which could not be successfully characterized by traditional texture analysis nor by rheology. Stick-slip effects resulting from intermittent sliding motion during kinetic friction of oral mucosa could constitute an additional determining factor of sensory perception where traditional friction coefficient values and their Stribeck regimes fail in predicting different lubricant (food bolus and saliva) behaviors. It was hypothesized that the observed jagged behavior of most sliding force curves are due to stick-slip effects and depend on test velocity, normal load, surface roughness as well as lubricant type. Therefore, different measurement set-ups were investigated: sliding velocities from 0.01 to 40 mm/s, loads of 0.5 and 2.5 N as well as a smooth and a textured silicone contact surface. Moreover, dry contact measurements were compared to model food systems, such as water, oil, and oil-in-water emulsions. Spectral analysis permitted to extract the distribution of stick-slip magnitudes for specific wave numbers, characterizing the occurrence of jagged force peaks per unit sliding distance, similar to frequencies per unit time. The spectral features were affected by all the above mentioned tested factors. Stick-slip created vibration frequencies in the range of those detected by oral mechanoreceptors (0.3-400 Hz). The study thus provides a new insight into the use of tribology in food psychophysics. Dynamic spectral analysis has been applied for the first time to the force-displacement curves in "oral" tribology. Analyzing the stick-slip phenomenon in the dynamic friction provides new information that is generally overlooked or confused with machine noise and which may help to understand friction-related sensory attributes. This approach allows us to differentiate samples that have similar friction coefficient
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.
Spectral Mixture Analysis to map burned areas in Brazil's deforestation arc from 1992 to 2011
Antunes Daldegan, G.; Ribeiro, F.; Roberts, D. A.
2017-12-01
The two most extensive biomes in South America, the Amazon and the Cerrado, are subject to several fire events every dry season. Both are known for their ecological and environmental importance. However, due to the intensive human occupation over the last four decades, they have been facing high deforestation rates. The Cerrado biome is adapted to fire and is considered a fire-dependent landscape. In contrast, the Amazon as a tropical moist broadleaf forest does not display similar characteristics and is classified as a fire-sensitive landscape. Nonetheless, studies have shown that forest areas that have already been burned become more prone to experience recurrent burns. Remote sensing has been extensively used by a large number of researchers studying fire occurrence at a global scale, as well as in both landscapes aforementioned. Digital image processing aiming to map fire activity has been applied to a number of imagery from sensors of various spatial, temporal, and spectral resolutions. More specifically, several studies have used Landsat data to map fire scars in the Amazon forest and in the Cerrado. An advantage of using Landsat data is the potential to map fire scars at a finer spatial resolution, when compared to products derived from imagery of sensors featuring better temporal resolution but coarser spatial resolution, such as MODIS (Moderate Resolution Imaging Spectrometer) and GOES (Geostationary Operational Environmental Satellite). This study aimed to map burned areas present in the Amazon-Cerrado transition zone by applying Spectral Mixture Analysis on Landsat imagery for a period of 20 years (1992-2011). The study area is a subset of this ecotone, centered at the State of Mato Grosso. By taking advantage of the Landsat 5TM and Landsat 7ETM+ imagery collections available in Google Earth Engine platform and applying Spectral Mixture Analysis (SMA) techniques over them permitted to model fire scar fractions and delimitate burned areas. Overlaying
Spectral analysis of IGR J01572-7259 during its 2016 outburst
La Palombara, N.; Esposito, P.; Mereghetti, S.; Pintore, F.; Sidoli, L.; Tiengo, A.
2018-03-01
We report on the results of the XMM-Newton observation of IGR J01572-7259 during its most recent outburst in 2016 May, the first since 2008. The source reached a flux f ˜ 10-10 erg cm-2 s-1, which allowed us to perform a detailed analysis of its timing and spectral properties. We obtained a pulse period Pspin = 11.58208(2) s. The pulse profile is double peaked and strongly energy dependent, as the second peak is prominent only at low energies and the pulsed fraction increases with energy. The main spectral component is a power-law model, but at low energies, we also detected a soft thermal component, which can be described with either a blackbody or a hot plasma model. Both the EPIC and RGS spectra show several emission lines, which can be identified with the transition lines of ionized N, O, Ne, and Fe and cannot be described with a thermal emission model. The phase-resolved spectral analysis showed that the flux of both the soft excess and the emission lines vary with the pulse phase: the soft excess disappears in the first pulse and becomes significant only in the second, where also the Fe line is stronger. This variability is difficult to explain with emission from a hot plasma, while the reprocessing of the primary X-ray emission at the inner edge of the accretion disc provides a reliable scenario. On the other hand, the narrow emission lines can be due to the presence of photoionized matter around the accreting source.
Emission spectral analysis of nickel-base superalloys with fixed time intergration technique
International Nuclear Information System (INIS)
Okochi, Haruno; Takahashi, Katsuyuki; Suzuki, Shunichi; Sudo, Emiko
1980-01-01
Simultaneous determination of multielements (C, B, Mo, Ta, Co, Fe, Mn, Cr, Nb, Cu, Ti, Zr, and Al) in nickel-base superalloys (Ni: 68 -- 76%) was performed by emission spectral analysis. At first, samples which had various nickel contents (ni: 68 -- 76%) were prepared by using JAERI R9, nickel and other metals (Fe, Co, or Cr). It was confirmed that in the internal standard method (Ni II 227.73 nm), analytical values of all the elements examined decreased with a decrease of the integration time (ca. 3.9 -- 4.6 s), that is, an increase of the nickel content. On the other hand, according to the fixed time integration method, elements except for C, Mo, and Cr were not interfered within the range of nickel contents examined. A series of nickel-base binary alloys (Al, Si, Ti, Cr, Mn, Fe, Co, Nb, Mo, and W series) were prepared by high frequency induction melting and the centrifugal casting method and formulae for correcting interferences with near spectral lines were obtained. Various synthetic samples were prepared and analysed by this method. The equations of calibration curves were derived from the data for standard samples (JAERI R1 -- R6, NBS 1189, 1203 -- 1205, and B.S. 600B) by curve fitting with orthogonal polynomials using a computer. For the assessment of this method studied, the F-test was performed by comparison of variances of both analytical values of standard and synthetic samples. The surfaces of specimens were polished with a belt grinder using No. 80 of alumina or silicon carbide endless-paper. The preburn period and integration one were decided at 5 and 6 s respectively. A few standard samples which gave worse reproducibility in emission spectral analysis was investigated with an optical microscope and an electron probe X-ray microanalyser. (author)
Validation of spectral methods for the seismic analysis of multi-supported structures
International Nuclear Information System (INIS)
Viola, B.
1999-01-01
There are many methodologies for the seismic analysis of buildings. When a seism occurs, structures such piping systems in nuclear power plants are subjected to motions that may be different at each support point. Therefore it is necessary to develop methods that take into account the multi-supported effect. In a first time, a bibliography analysis on the different methods that exist has been carried out. The aim was to find a particular method applicable to the study of piping systems. The second step of this work consisted in developing a program that may be used to test and make comparisons on different selected methods. So spectral methods have the advantage to give an estimation of the maximum values for strain in the structure, in reduced calculation time. The time history analysis is used as the reference for the tests. (author)
Two Step Procedure Using a 1-D Slab Spectral Geometry in a Pebble Bed Reactor Core Analysis
International Nuclear Information System (INIS)
Lee, Hyun Chul; Kim, Kang Seog; Noh, Jae Man; Joo, Hyung Kook
2005-01-01
A strong spectral interaction between the core and the reflector has been one of the main concerns in the analysis of pebble bed reactor cores. To resolve this problem, VSOP adopted iteration between the spectrum calculation in a spectral zone and the global core calculation. In VSOP, the whole problem domain is divided into many spectral zones in which the fine group spectrum is calculated using bucklings for fast groups and albedos for thermal groups from the global core calculation. The resulting spectrum in each spectral zone is used to generate broad group cross sections of the spectral zone for the global core calculation. In this paper, we demonstrate a two step procedure in a pebble bed reactor core analysis. In the first step, we generate equivalent cross sections from a 1-D slab spectral geometry model with the help of the equivalence theory. The equivalent cross sections generated in this way include the effect of the spectral interaction between the core and the reflector. In the second step, we perform a diffusion calculation using the equivalent cross sections generated in the first step. A simple benchmark problem derived from the PMBR-400 Reactor was introduced to verify this approach. We compared the two step solutions with the Monte Carlo (MC) solutions for the problem
Zainudin, M. N. Shah; Sulaiman, Md Nasir; Mustapha, Norwati; Perumal, Thinagaran
2017-10-01
Prior knowledge in pervasive computing recently garnered a lot of attention due to its high demand in various application domains. Human activity recognition (HAR) considered as the applications that are widely explored by the expertise that provides valuable information to the human. Accelerometer sensor-based approach is utilized as devices to undergo the research in HAR since their small in size and this sensor already build-in in the various type of smartphones. However, the existence of high inter-class similarities among the class tends to degrade the recognition performance. Hence, this work presents the method for activity recognition using our proposed features from combinational of spectral analysis with statistical descriptors that able to tackle the issue of differentiating stationary and locomotion activities. The noise signal is filtered using Fourier Transform before it will be extracted using two different groups of features, spectral frequency analysis, and statistical descriptors. Extracted signal later will be classified using random forest ensemble classifier models. The recognition results show the good accuracy performance for stationary and locomotion activities based on USC HAD datasets.
Directory of Open Access Journals (Sweden)
M. Ern
2009-01-01
Full Text Available Space-time spectral analysis of satellite data is an important method to derive a synoptic picture of the atmosphere from measurements sampled asynoptically by satellite instruments. In addition, it serves as a powerful tool to identify and separate different wave modes in the atmospheric data. In our work we present space-time spectral analyses of chemical heating rates derived from Scanning Imaging Absorption SpectroMeter for Atmospheric CHartographY (SCIAMACHY hydroxyl nightglow emission measurements onboard Envisat for the years 2002–2006 at mesopause heights. Since SCIAMACHY nightglow hydroxyl emission measurements are restricted to the ascending (nighttime part of the satellite orbit, our analysis also includes temperature spectra derived from 15 μm CO2 emissions measured by the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER instrument. SABER offers better temporal and spatial coverage (daytime and night-time values of temperature and a more regular sampling grid. Therefore SABER spectra also contain information about higher frequency waves. Comparison of SCIAMACHY and SABER results shows that SCIAMACHY, in spite of its observational restrictions, provides valuable information on most of the wave modes present in the mesopause region. The main differences between wave spectra obtained from these sensors can be attributed to the differences in their sampling patterns.
Directory of Open Access Journals (Sweden)
M. Ern
2009-01-01
Full Text Available Space-time spectral analysis of satellite data is an important method to derive a synoptic picture of the atmosphere from measurements sampled asynoptically by satellite instruments. In addition, it serves as a powerful tool to identify and separate different wave modes in the atmospheric data. In our work we present space-time spectral analyses of chemical heating rates derived from Scanning Imaging Absorption SpectroMeter for Atmospheric CHartographY (SCIAMACHY hydroxyl nightglow emission measurements onboard Envisat for the years 2002–2006 at mesopause heights.
Since SCIAMACHY nightglow hydroxyl emission measurements are restricted to the ascending (nighttime part of the satellite orbit, our analysis also includes temperature spectra derived from 15 μm CO_{2} emissions measured by the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER instrument. SABER offers better temporal and spatial coverage (daytime and night-time values of temperature and a more regular sampling grid. Therefore SABER spectra also contain information about higher frequency waves.
Comparison of SCIAMACHY and SABER results shows that SCIAMACHY, in spite of its observational restrictions, provides valuable information on most of the wave modes present in the mesopause region. The main differences between wave spectra obtained from these sensors can be attributed to the differences in their sampling patterns.
SVM-Based Spectral Analysis for Heart Rate from Multi-Channel WPPG Sensor Signals.
Xiong, Jiping; Cai, Lisang; Wang, Fei; He, Xiaowei
2017-03-03
Although wrist-type photoplethysmographic (hereafter referred to as WPPG) sensor signals can measure heart rate quite conveniently, the subjects' hand movements can cause strong motion artifacts, and then the motion artifacts will heavily contaminate WPPG signals. Hence, it is challenging for us to accurately estimate heart rate from WPPG signals during intense physical activities. The WWPG method has attracted more attention thanks to the popularity of wrist-worn wearable devices. In this paper, a mixed approach called Mix-SVM is proposed, it can use multi-channel WPPG sensor signals and simultaneous acceleration signals to measurement heart rate. Firstly, we combine the principle component analysis and adaptive filter to remove a part of the motion artifacts. Due to the strong relativity between motion artifacts and acceleration signals, the further denoising problem is regarded as a sparse signals reconstruction problem. Then, we use a spectrum subtraction method to eliminate motion artifacts effectively. Finally, the spectral peak corresponding to heart rate is sought by an SVM-based spectral analysis method. Through the public PPG database in the 2015 IEEE Signal Processing Cup, we acquire the experimental results, i.e., the average absolute error was 1.01 beat per minute, and the Pearson correlation was 0.9972. These results also confirm that the proposed Mix-SVM approach has potential for multi-channel WPPG-based heart rate estimation in the presence of intense physical exercise.
Morphological, spectral and chromatography analysis and forensic comparison of PET fibers.
Farah, Shady; Tsach, Tsadok; Bentolila, Alfonso; Domb, Abraham J
2014-06-01
Poly(ethylene terephthalate) (PET) fiber analysis and comparison by spectral and polymer molecular weight determination was investigated. Plain fibers of PET, a common textile fiber and plastic material was chosen for this study. The fibers were analyzed for morphological (SEM and AFM), spectral (IR and NMR), thermal (DSC) and molecular weight (MS and GPC) differences. Molecular analysis of PET fibers by Gel Permeation Chromatography (GPC) allowed the comparison of fibers that could not be otherwise distinguished with high confidence. Plain PET fibers were dissolved in hexafluoroisopropanol (HFIP) and analyzed by GPC using hexafluoroisopropanol:chloroform 2:98 v/v as eluent. 14 PET fiber samples, collected from various commercial producers, were analyzed for polymer molecular weight by GPC. Distinct differences in the molecular weight of the different fiber samples were found which may have potential use in forensic fiber comparison. PET fibers with average molecular weights between about 20,000 and 70,000 g mol(-1) were determined using fiber concentrations in HFIP as low as 1 μg mL(-1). This GPC analytical method can be applied for exclusively distinguish between PET fibers using 1 μg of fiber. This method can be extended to forensic comparison of other synthetic fibers such as polyamides and acrylics. Copyright © 2014 Elsevier B.V. All rights reserved.
[Vegetation index estimation by chlorophyll content of grassland based on spectral analysis].
Xiao, Han; Chen, Xiu-Wan; Yang, Zhen-Yu; Li, Huai-Yu; Zhu, Han
2014-11-01
Comparing the methods of existing remote sensing research on the estimation of chlorophyll content, the present paper confirms that the vegetation index is one of the most practical and popular research methods. In recent years, the increasingly serious problem of grassland degradation. This paper, firstly, analyzes the measured reflectance spectral curve and its first derivative curve in the grasslands of Songpan, Sichuan and Gongger, Inner Mongolia, conducts correlation analysis between these two spectral curves and chlorophyll content, and finds out the regulation between REP (red edge position) and grassland chlorophyll content, that is, the higher the chlorophyll content is, the higher the REIP (red-edge inflection point) value would be. Then, this paper constructs GCI (grassland chlorophyll index) and selects the most suitable band for retrieval. Finally, this paper calculates the GCI by the use of satellite hyperspectral image, conducts the verification and accuracy analysis of the calculation results compared with chlorophyll content data collected from field of twice experiments. The result shows that for grassland chlorophyll content, GCI has stronger sensitivity than other indices of chlorophyll, and has higher estimation accuracy. GCI is the first proposed to estimate the grassland chlorophyll content, and has wide application potential for the remote sensing retrieval of grassland chlorophyll content. In addition, the grassland chlorophyll content estimation method based on remote sensing retrieval in this paper provides new research ideas for other vegetation biochemical parameters' estimation, vegetation growth status' evaluation and grassland ecological environment change's monitoring.
COMBINED ANALYSIS OF IMAGES AND SPECTRAL ENERGY DISTRIBUTIONS OF TAURUS PROTOSTARS
International Nuclear Information System (INIS)
Gramajo, Luciana V.; Gomez, Mercedes; Whitney, Barbara A.; Robitaille, Thomas P.
2010-01-01
We present an analysis of spectral energy distributions (SEDs), near- and mid-infrared images, and Spitzer spectra of eight embedded Class I/II objects in the Taurus-Auriga molecular cloud. The initial model for each source was chosen using the grid of young stellar objects (YSOs) and SED fitting tool of Robitaille et al. Then the models were refined using the radiative transfer code of Whitney et al. to fit both the spectra and the infrared images of these objects. In general, our models agree with previous published analyses. However, our combined models should provide more reliable determinations of the physical and geometrical parameters since they are derived from SEDs, including the Spitzer spectra, covering the complete spectral range; and high-resolution near-infrared and Spitzer IRAC images. The combination of SED and image modeling better constrains the different components (central source, disk, envelope) of the YSOs. Our derived luminosities are higher, on average, than previous estimates because we account for the viewing angles (usually nearly edge-on) of most of the sources. Our analysis suggests that the standard rotating collapsing protostar model with disks and bipolar cavities works well for the analyzed sample of objects in the Taurus molecular cloud.
Research on the strong optical feedback effects based on spectral analysis method
Zeng, Zhaoli; Qu, XueMin; Li, Weina; Zhang, Min; Wang, Hao; Li, Tuo
2018-01-01
The strong optical feedback has the advantage of generating high resolution fringes. However, these feedback fringes usually seem like the noise signal when the feedback level is high. This defect severely limits its practical application. In this paper, the generation mechanism of noise fringes with strong optical feedback is studied by using spectral analysis method. The spectral analysis results show that, in most cases, the noise-like fringes are observed owing to the strong multiple high-order feedback. However, at certain feedback cavity condition, there may be only one high-order feedback beam goes back to the laser cavity, the noise-like fringes can change to the cosine-like fringes. And the resolution of this fringe is dozens times than that of the weak optical feedback. This research provides a method to obtain high resolution cosine-like fringes rather than noise signal in the strong optical feedback, which makes it possible to be used in nanoscale displacement measurements.
Spectral analysis of epicardial 60-lead electrograms in dogs with 4-week-old myocardial infarction.
Hosoya, Y; Ikeda, K; Komatsu, T; Yamaki, M; Kubota, I
2001-01-01
There were few studies on the spectral analysis of multiple-lead epicardial electrograms in chronic myocardial infarction. Spectral analysis of multi-lead epicardial electrograms was performed in 6 sham-operated dogs (N group) and 8 dogs with 4-week-old myocardial infarction (MI group). Four weeks after the ligation of left anterior descending coronary artery, fast Fourier transform was performed on 60-lead epicardial electrograms, and then inverse transform was performed on 5 frequency ranges from 0 to 250 Hz. From the QRS onset to QRS offset, the time integration of unsigned value of reconstructed waveform was calculated and displayed as AQRS maps. On 0-25 Hz AQRS map, there was no significant difference between the 2 groups. In the frequency ranges of 25-250 Hz, MI group had significantly smaller AQRS values than N group solely in the infarct zone. It was shown that high frequency potentials (25-250 Hz) within QRS complex were reduced in the infarct zone.
SVM-Based Spectral Analysis for Heart Rate from Multi-Channel WPPG Sensor Signals
Directory of Open Access Journals (Sweden)
Jiping Xiong
2017-03-01
Full Text Available Although wrist-type photoplethysmographic (hereafter referred to as WPPG sensor signals can measure heart rate quite conveniently, the subjects’ hand movements can cause strong motion artifacts, and then the motion artifacts will heavily contaminate WPPG signals. Hence, it is challenging for us to accurately estimate heart rate from WPPG signals during intense physical activities. The WWPG method has attracted more attention thanks to the popularity of wrist-worn wearable devices. In this paper, a mixed approach called Mix-SVM is proposed, it can use multi-channel WPPG sensor signals and simultaneous acceleration signals to measurement heart rate. Firstly, we combine the principle component analysis and adaptive filter to remove a part of the motion artifacts. Due to the strong relativity between motion artifacts and acceleration signals, the further denoising problem is regarded as a sparse signals reconstruction problem. Then, we use a spectrum subtraction method to eliminate motion artifacts effectively. Finally, the spectral peak corresponding to heart rate is sought by an SVM-based spectral analysis method. Through the public PPG database in the 2015 IEEE Signal Processing Cup, we acquire the experimental results, i.e., the average absolute error was 1.01 beat per minute, and the Pearson correlation was 0.9972. These results also confirm that the proposed Mix-SVM approach has potential for multi-channel WPPG-based heart rate estimation in the presence of intense physical exercise.
On Parametric (and Non-Parametric Variation
Directory of Open Access Journals (Sweden)
Neil Smith
2009-11-01
Full Text Available This article raises the issue of the correct characterization of ‘Parametric Variation’ in syntax and phonology. After specifying their theoretical commitments, the authors outline the relevant parts of the Principles–and–Parameters framework, and draw a three-way distinction among Universal Principles, Parameters, and Accidents. The core of the contribution then consists of an attempt to provide identity criteria for parametric, as opposed to non-parametric, variation. Parametric choices must be antecedently known, and it is suggested that they must also satisfy seven individually necessary and jointly sufficient criteria. These are that they be cognitively represented, systematic, dependent on the input, deterministic, discrete, mutually exclusive, and irreversible.
Nonparametric predictive pairwise comparison with competing risks
International Nuclear Information System (INIS)
Coolen-Maturi, Tahani
2014-01-01
In reliability, failure data often correspond to competing risks, where several failure modes can cause a unit to fail. This paper presents nonparametric predictive inference (NPI) for pairwise comparison with competing risks data, assuming that the failure modes are independent. These failure modes could be the same or different among the two groups, and these can be both observed and unobserved failure modes. NPI is a statistical approach based on few assumptions, with inferences strongly based on data and with uncertainty quantified via lower and upper probabilities. The focus is on the lower and upper probabilities for the event that the lifetime of a future unit from one group, say Y, is greater than the lifetime of a future unit from the second group, say X. The paper also shows how the two groups can be compared based on particular failure mode(s), and the comparison of the two groups when some of the competing risks are combined is discussed
Nonparametric estimation of location and scale parameters
Potgieter, C.J.
2012-12-01
Two random variables X and Y belong to the same location-scale family if there are constants μ and σ such that Y and μ+σX have the same distribution. In this paper we consider non-parametric estimation of the parameters μ and σ under minimal assumptions regarding the form of the distribution functions of X and Y. We discuss an approach to the estimation problem that is based on asymptotic likelihood considerations. Our results enable us to provide a methodology that can be implemented easily and which yields estimators that are often near optimal when compared to fully parametric methods. We evaluate the performance of the estimators in a series of Monte Carlo simulations. © 2012 Elsevier B.V. All rights reserved.
Nonparametric inference of network structure and dynamics
Peixoto, Tiago P.
The network structure of complex systems determine their function and serve as evidence for the evolutionary mechanisms that lie behind them. Despite considerable effort in recent years, it remains an open challenge to formulate general descriptions of the large-scale structure of network systems, and how to reliably extract such information from data. Although many approaches have been proposed, few methods attempt to gauge the statistical significance of the uncovered structures, and hence the majority cannot reliably separate actual structure from stochastic fluctuations. Due to the sheer size and high-dimensionality of many networks, this represents a major limitation that prevents meaningful interpretations of the results obtained with such nonstatistical methods. In this talk, I will show how these issues can be tackled in a principled and efficient fashion by formulating appropriate generative models of network structure that can have their parameters inferred from data. By employing a Bayesian description of such models, the inference can be performed in a nonparametric fashion, that does not require any a priori knowledge or ad hoc assumptions about the data. I will show how this approach can be used to perform model comparison, and how hierarchical models yield the most appropriate trade-off between model complexity and quality of fit based on the statistical evidence present in the data. I will also show how this general approach can be elegantly extended to networks with edge attributes, that are embedded in latent spaces, and that change in time. The latter is obtained via a fully dynamic generative network model, based on arbitrary-order Markov chains, that can also be inferred in a nonparametric fashion. Throughout the talk I will illustrate the application of the methods with many empirical networks such as the internet at the autonomous systems level, the global airport network, the network of actors and films, social networks, citations among
Wang, Hong-Fei; Gan, Wei; Lu, Rong; Rao, Yi; Wu, Bao-Hua
Sum frequency generation vibrational spectroscopy (SFG-VS) has been proven to be a uniquely effective spectroscopic technique in the investigation of molecular structure and conformations, as well as the dynamics of molecular interfaces. However, the ability to apply SFG-VS to complex molecular interfaces has been limited by the ability to abstract quantitative information from SFG-VS experiments. In this review, we try to make assessments of the limitations, issues and techniques as well as methodologies in quantitative orientational and spectral analysis with SFG-VS. Based on these assessments, we also try to summarize recent developments in methodologies on quantitative orientational and spectral analysis in SFG-VS, and their applications to detailed analysis of SFG-VS data of various vapour/neat liquid interfaces. A rigorous formulation of the polarization null angle (PNA) method is given for accurate determination of the orientational parameter D = /, and comparison between the PNA method with the commonly used polarization intensity ratio (PIR) method is discussed. The polarization and incident angle dependencies of the SFG-VS intensity are also reviewed, in the light of how experimental arrangements can be optimized to effectively abstract crucial information from the SFG-VS experiments. The values and models of the local field factors in the molecular layers are discussed. In order to examine the validity and limitations of the bond polarizability derivative model, the general expressions for molecular hyperpolarizability tensors and their expression with the bond polarizability derivative model for C3v, C2v and C∞v molecular groups are given in the two appendixes. We show that the bond polarizability derivative model can quantitatively describe many aspects of the intensities observed in the SFG-VS spectrum of the vapour/neat liquid interfaces in different polarizations. Using the polarization analysis in SFG-VS, polarization selection rules or
West, A G; Goldsmith, G R; Matimati, I; Dawson, T E
2011-08-30
Previous studies have demonstrated the potential for large errors to occur when analyzing waters containing organic contaminants using isotope ratio infrared spectroscopy (IRIS). In an attempt to address this problem, IRIS manufacturers now provide post-processing spectral analysis software capable of identifying samples with the types of spectral interference that compromises their stable isotope analysis. Here we report two independent tests of this post-processing spectral analysis software on two IRIS systems, OA-ICOS (Los Gatos Research Inc.) and WS-CRDS (Picarro Inc.). Following a similar methodology to a previous study, we cryogenically extracted plant leaf water and soil water and measured the δ(2)H and δ(18)O values of identical samples by isotope ratio mass spectrometry (IRMS) and IRIS. As an additional test, we analyzed plant stem waters and tap waters by IRMS and IRIS in an independent laboratory. For all tests we assumed that the IRMS value represented the "true" value against which we could compare the stable isotope results from the IRIS methods. Samples showing significant deviations from the IRMS value (>2σ) were considered to be contaminated and representative of spectral interference in the IRIS measurement. Over the two studies, 83% of plant species were considered contaminated on OA-ICOS and 58% on WS-CRDS. Post-analysis, spectra were analyzed using the manufacturer's spectral analysis software, in order to see if the software correctly identified contaminated samples. In our tests the software performed well, identifying all the samples with major errors. However, some false negatives indicate that user evaluation and testing of the software are necessary. Repeat sampling of plants showed considerable variation in the discrepancies between IRIS and IRMS. As such, we recommend that spectral analysis of IRIS data must be incorporated into standard post-processing routines. Furthermore, we suggest that the results from spectral analysis be
Directory of Open Access Journals (Sweden)
Daniel Sousa
2018-02-01
Full Text Available Planned hyperspectral satellite missions and the decreased revisit time of multispectral imaging offer the potential for data fusion to leverage both the spectral resolution of hyperspectral sensors and the temporal resolution of multispectral constellations. Hyperspectral imagery can also be used to better understand fundamental properties of multispectral data. In this analysis, we use five flight lines from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS archive with coincident Landsat 8 acquisitions over a spectrally diverse region of California to address the following questions: (1 How much of the spectral dimensionality of hyperspectral data is captured in multispectral data?; (2 Is the characteristic pyramidal structure of the multispectral feature space also present in the low order dimensions of the hyperspectral feature space at comparable spatial scales?; (3 How much variability in rock and soil substrate endmembers (EMs present in hyperspectral data is captured by multispectral sensors? We find nearly identical partitions of variance, low-order feature space topologies, and EM spectra for hyperspectral and multispectral image composites. The resulting feature spaces and EMs are also very similar to those from previous global multispectral analyses, implying that the fundamental structure of the global feature space is present in our relatively small spatial subset of California. Finally, we find that the multispectral dataset well represents the substrate EM variability present in the study area – despite its inability to resolve narrow band absorptions. We observe a tentative but consistent physical relationship between the gradation of substrate reflectance in the feature space and the gradation of sand versus clay content in the soil classification system.
Directory of Open Access Journals (Sweden)
D. R. Bowdalo
2016-07-01
Full Text Available Models of atmospheric composition play an essential role in our scientific understanding of atmospheric processes and in providing policy strategies to deal with societally relevant problems such as climate change, air quality, and ecosystem degradation. The fidelity of these models needs to be assessed against observations to ensure that errors in model formulations are found and that model limitations are understood. A range of approaches are necessary for these comparisons. Here, we apply a spectral analysis methodology for this comparison. We use the Lomb–Scargle periodogram, a method similar to a Fourier transform, but better suited to deal with the gapped data sets typical of observational data. We apply this methodology to long-term hourly ozone observations and the equivalent model (GEOS-Chem output. We show that the spectrally transformed observational data show a distinct power spectrum with regimes indicative of meteorological processes (weather, macroweather and specific peaks observed at the daily and annual timescales together with corresponding harmonic peaks at one-half, one-third, etc., of these frequencies. Model output shows corresponding features. A comparison between the amplitude and phase of these peaks introduces a new comparison methodology between model and measurements. We focus on the amplitude and phase of diurnal and seasonal cycles and present observational/model comparisons and discuss model performance. We find large biases notably for the seasonal cycle in the mid-latitude Northern Hemisphere where the amplitudes are generally overestimated by up to 16 ppbv, and phases are too late on the order of 1–5 months. This spectral methodology can be applied to a range of model–measurement applications and is highly suitable for Multimodel Intercomparison Projects (MIPs.
Synthetic spectral analysis of a kinetic model for slow-magnetosonic waves in solar corona
Energy Technology Data Exchange (ETDEWEB)
Ruan, Wenzhi; He, Jiansen; Tu, Chuanyi; Wang, Linghua [School of Earth and Space Sciences, Peking University, Beijing, 100871, China, E-mail: jshept@gmail.com (China); Zhang, Lei [State Key Laboratory of Space Weather, Chinese Academy of Sciences, Beijing 100190 (China); Vocks, Christian [Leibniz-Institut für Astrophysik Potsdam, 14482, Potsdam (Germany); Marsch, Eckart [Institute for Experimental and Applied Physics, Christian-Albrechts-Universität zu Kiel, 24118 Kiel (Germany); Peter, Hardi [Max Plank Institut für Sonnensystemforschung, Justus-von-Liebig-Weg 3, 37077 Göttingen (Germany)
2016-03-25
We propose a kinetic model of slow-magnetosonic waves to explain various observational features associated with the propagating intensity disturbances (PIDs) occurring in the solar corona. The characteristics of slow mode waves, e.g, inphase oscillations of density, velocity, and thermal speed, are reproduced in this kinetic model. Moreover, the red-blue (R-B) asymmetry of the velocity distribution as self-consistently generated in the model is found to be contributed from the beam component, as a result of the competition between Landau resonance and Coulomb collisions. Furthermore, we synthesize the spectral lines and make the spectral analysis, based on the kinetic simulation data of the flux tube plasmas and the hypothesis of the surrounding background plasmas. It is found that the fluctuations of parameters of the synthetic spectral lines are basically consistent with the observations: (1) the line intensity, Doppler shift, and line width are fluctuating in phase; (2) the R-B asymmetry usually oscillate out of phase with the former three parameters; (3) the blueward asymmetry is more evident than the redward asymmetry in the R-B fluctuations. The oscillations of line parameters become weakened for the case with denser surrounding background plasmas. Similar to the observations, there is no doubled-frequency oscillation of the line width for the case with flux-tube plasmas flowing bulkly upward among the static background plasmas. Therefore, we suggest that the “wave + beam flow” kinetic model may be a viable interpretation for the PIDs observed in the solar corona.
Digital signal processing and spectral analysis for scientists concepts and applications
Alessio, Silvia Maria
2016-01-01
This book covers the basics of processing and spectral analysis of monovariate discrete-time signals. The approach is practical, the aim being to acquaint the reader with the indications for and drawbacks of the various methods and to highlight possible misuses. The book is rich in original ideas, visualized in new and illuminating ways, and is structured so that parts can be skipped without loss of continuity. Many examples are included, based on synthetic data and real measurements from the fields of physics, biology, medicine, macroeconomics etc., and a complete set of MATLAB exercises requiring no previous experience of programming is provided. Prior advanced mathematical skills are not needed in order to understand the contents: a good command of basic mathematical analysis is sufficient. Where more advanced mathematical tools are necessary, they are included in an Appendix and presented in an easy-to-follow way. With this book, digital signal processing leaves the domain of engineering to address the ne...
Flaw location and characterization in anisotropic materials by ultrasonic spectral analysis
International Nuclear Information System (INIS)
Adler, L.; Cook, K.V.; Simpson, W.A.; Lewis, D.K.
1978-01-01
A method of quantitatively determining size and location of flaws in anisotropic materials such as stainless steel welds is described. In previous work, it was shown that spectral analysis of a broad band ultrasonic pulse scattered from a defect can be used to determine size and orientation in isotropic materials if the velocity of sound in the material is known. In an anisotropic structural material (stainless steel weld, centrifugal cast pipe), the velocity (both shear and longitudinal) is direction-dependent. When anisotropy is not taken into account, defect location and defect size estimation is misjudged. It will be shown that the effect of this structural variation in materials must be considered to obtain the correct size and location of defects by frequency analysis. A theoretical calculation, including anisotropy, of the scattered field from defects will also be presented
Zejkan, A; Bejcek, Z; Horejs, J; Vrbová, H; Bakosová, M; Macholda, F; Rykl, D
1989-10-01
The authors present results of serial quality and quantity microanalyses of bone patterns and dental tissue patterns in patient with desmoid fibromatosis. Methods of absorption spectroscopy, emission spectral analysis and X-ray diffraction analysis with follow-up to x-ray examination are tested. The above mentioned methods function in a on-line system by means of specially adjusted monitor unit which is controlled centrally by the computer processor system. The whole process of measurement is fully automated and the data obtained are recorded processed in the unit data structure classified into index sequence blocks of data. Serial microanalyses offer exact data for the study of structural changes of dental and bone tissues which manifest themselves in order of crystal grid shifts. They prove the fact that microanalyses give new possibilities in detection and interpretation of chemical and structural changes of apatite cell.
Statistical learning method in regression analysis of simulated positron spectral data
International Nuclear Information System (INIS)
Avdic, S. Dz.
2005-01-01
Positron lifetime spectroscopy is a non-destructive tool for detection of radiation induced defects in nuclear reactor materials. This work concerns the applicability of the support vector machines method for the input data compression in the neural network analysis of positron lifetime spectra. It has been demonstrated that the SVM technique can be successfully applied to regression analysis of positron spectra. A substantial data compression of about 50 % and 8 % of the whole training set with two and three spectral components respectively has been achieved including a high accuracy of the spectra approximation. However, some parameters in the SVM approach such as the insensitivity zone e and the penalty parameter C have to be chosen carefully to obtain a good performance. (author)
Spectral analysis of stellar light curves by means of neural networks
Tagliaferri, R.; Ciaramella, A.; Milano, L.; Barone, F.; Longo, G.
1999-06-01
Periodicity analysis of unevenly collected data is a relevant issue in several scientific fields. In astrophysics, for example, we have to find the fundamental period of light or radial velocity curves which are unevenly sampled observations of stars. Classical spectral analysis methods are unsatisfactory to solve the problem. In this paper we present a neural network based estimator system which performs well the frequency extraction in unevenly sampled signals. It uses an unsupervised Hebbian nonlinear neural algorithm to extract, from the interpolated signal, the principal components which, in turn, are used by the MUSIC frequency estimator algorithm to extract the frequencies. The neural network is tolerant to noise and works well also with few points in the sequence. We benchmark the system on synthetic and real signals with the Periodogram and with the Cramer-Rao lower bound. This work was been partially supported by IIASS, by MURST 40\\% and by the Italian Space Agency.
Ferrero, A; Campos, J; Rabal, A M; Pons, A; Hernanz, M L; Corróns, A
2011-09-26
The Bidirectional Reflectance Distribution Function (BRDF) is essential to characterize an object's reflectance properties. This function depends both on the various illumination-observation geometries as well as on the wavelength. As a result, the comprehensive interpretation of the data becomes rather complex. In this work we assess the use of the multivariable analysis technique of Principal Components Analysis (PCA) applied to the experimental BRDF data of a ceramic colour standard. It will be shown that the result may be linked to the various reflection processes occurring on the surface, assuming that the incoming spectral distribution is affected by each one of these processes in a specific manner. Moreover, this procedure facilitates the task of interpolating a series of BRDF measurements obtained for a particular sample. © 2011 Optical Society of America
Wang, Yuan; Bao, Shan; Du, Wenjun; Ye, Zhirui; Sayer, James R
2017-11-17
This article investigated and compared frequency domain and time domain characteristics of drivers' behaviors before and after the start of distracted driving. Data from an existing naturalistic driving study were used. Fast Fourier transform (FFT) was applied for the frequency domain analysis to explore drivers' behavior pattern changes between nondistracted (prestarting of visual-manual task) and distracted (poststarting of visual-manual task) driving periods. Average relative spectral power in a low frequency range (0-0.5 Hz) and the standard deviation in a 10-s time window of vehicle control variables (i.e., lane offset, yaw rate, and acceleration) were calculated and further compared. Sensitivity analyses were also applied to examine the reliability of the time and frequency domain analyses. Results of the mixed model analyses from the time and frequency domain analyses all showed significant degradation in lateral control performance after engaging in visual-manual tasks while driving. Results of the sensitivity analyses suggested that the frequency domain analysis was less sensitive to the frequency bandwidth, whereas the time domain analysis was more sensitive to the time intervals selected for variation calculations. Different time interval selections can result in significantly different standard deviation values, whereas average spectral power analysis on yaw rate in both low and high frequency bandwidths showed consistent results, that higher variation values were observed during distracted driving when compared to nondistracted driving. This study suggests that driver state detection needs to consider the behavior changes during the prestarting periods, instead of only focusing on periods with physical presence of distraction, such as cell phone use. Lateral control measures can be a better indicator of distraction detection than longitudinal controls. In addition, frequency domain analyses proved to be a more robust and consistent method in assessing
Analysis of errors in spectral reconstruction with a Laplace transform pair model
International Nuclear Information System (INIS)
Archer, B.R.; Bushong, S.C.
1985-01-01
The sensitivity of a Laplace transform pair model for spectral reconstruction to random errors in attenuation measurements of diagnostic x-ray units has been investigated. No spectral deformation or significant alteration resulted from the simulated attenuation errors. It is concluded that the range of spectral uncertainties to be expected from the application of this model is acceptable for most scientific applications. (author)
Fereidouni, F.; Bader, A.N.; Colonna, A.; Gerritsen, H.C.
2014-01-01
Skin contains many autofluorescent components that can be studied using spectral imaging. We employed a spectral phasor method to analyse two photon excited auto-fluorescence and second harmonic generation images of in vivo human skin. This method allows segmentation of images based on spectral
Nonparametric Estimation of Distributions in Random Effects Models
Hart, Jeffrey D.
2011-01-01
We propose using minimum distance to obtain nonparametric estimates of the distributions of components in random effects models. A main setting considered is equivalent to having a large number of small datasets whose locations, and perhaps scales, vary randomly, but which otherwise have a common distribution. Interest focuses on estimating the distribution that is common to all datasets, knowledge of which is crucial in multiple testing problems where a location/scale invariant test is applied to every small dataset. A detailed algorithm for computing minimum distance estimates is proposed, and the usefulness of our methodology is illustrated by a simulation study and an analysis of microarray data. Supplemental materials for the article, including R-code and a dataset, are available online. © 2011 American Statistical Association.
Spurious Seasonality Detection: A Non-Parametric Test Proposal
Directory of Open Access Journals (Sweden)
Aurelio F. Bariviera
2018-01-01
Full Text Available This paper offers a general and comprehensive definition of the day-of-the-week effect. Using symbolic dynamics, we develop a unique test based on ordinal patterns in order to detect it. This test uncovers the fact that the so-called “day-of-the-week” effect is partly an artifact of the hidden correlation structure of the data. We present simulations based on artificial time series as well. While time series generated with long memory are prone to exhibit daily seasonality, pure white noise signals exhibit no pattern preference. Since ours is a non-parametric test, it requires no assumptions about the distribution of returns, so that it could be a practical alternative to conventional econometric tests. We also made an exhaustive application of the here-proposed technique to 83 stock indexes around the world. Finally, the paper highlights the relevance of symbolic analysis in economic time series studies.
Nonparametric estimation of stochastic differential equations with sparse Gaussian processes.
García, Constantino A; Otero, Abraham; Félix, Paulo; Presedo, Jesús; Márquez, David G
2017-08-01
The application of stochastic differential equations (SDEs) to the analysis of temporal data has attracted increasing attention, due to their ability to describe complex dynamics with physically interpretable equations. In this paper, we introduce a nonparametric method for estimating the drift and diffusion terms of SDEs from a densely observed discrete time series. The use of Gaussian processes as priors permits working directly in a function-space view and thus the inference takes place directly in this space. To cope with the computational complexity that requires the use of Gaussian processes, a sparse Gaussian process approximation is provided. This approximation permits the efficient computation of predictions for the drift and diffusion terms by using a distribution over a small subset of pseudosamples. The proposed method has been validated using both simulated data and real data from economy and paleoclimatology. The application of the method to real data demonstrates its ability to capture the behavior of complex systems.
Nonparametric estimation of benchmark doses in environmental risk assessment
Piegorsch, Walter W.; Xiong, Hui; Bhattacharya, Rabi N.; Lin, Lizhen
2013-01-01
Summary An important statistical objective in environmental risk analysis is estimation of minimum exposure levels, called benchmark doses (BMDs), that induce a pre-specified benchmark response in a dose-response experiment. In such settings, representations of the risk are traditionally based on a parametric dose-response model. It is a well-known concern, however, that if the chosen parametric form is misspecified, inaccurate and possibly unsafe low-dose inferences can result. We apply a nonparametric approach for calculating benchmark doses, based on an isotonic regression method for dose-response estimation with quantal-response data (Bhattacharya and Kong, 2007). We determine the large-sample properties of the estimator, develop bootstrap-based confidence limits on the BMDs, and explore the confidence limits’ small-sample properties via a short simulation study. An example from cancer risk assessment illustrates the calculations. PMID:23914133
Spectral negentropy based sidebands and demodulation analysis for planet bearing fault diagnosis
Feng, Zhipeng; Ma, Haoqun; Zuo, Ming J.
2017-12-01
Planet bearing vibration signals are highly complex due to intricate kinematics (involving both revolution and spinning) and strong multiple modulations (including not only the fault induced amplitude modulation and frequency modulation, but also additional amplitude modulations due to load zone passing, time-varying vibration transfer path, and time-varying angle between the gear pair mesh lines of action and fault impact force vector), leading to difficulty in fault feature extraction. Rolling element bearing fault diagnosis essentially relies on detection of fault induced repetitive impulses carried by resonance vibration, but they are usually contaminated by noise and therefor are hard to be detected. This further adds complexity to planet bearing diagnostics. Spectral negentropy is able to reveal the frequency distribution of repetitive transients, thus providing an approach to identify the optimal frequency band of a filter for separating repetitive impulses. In this paper, we find the informative frequency band (including the center frequency and bandwidth) of bearing fault induced repetitive impulses using the spectral negentropy based infogram. In Fourier spectrum, we identify planet bearing faults according to sideband characteristics around the center frequency. For demodulation analysis, we filter out the sensitive component based on the informative frequency band revealed by the infogram. In amplitude demodulated spectrum (squared envelope spectrum) of the sensitive component, we diagnose planet bearing faults by matching the present peaks with the theoretical fault characteristic frequencies. We further decompose the sensitive component into mono-component intrinsic mode functions (IMFs) to estimate their instantaneous frequencies, and select a sensitive IMF with an instantaneous frequency fluctuating around the center frequency for frequency demodulation analysis. In the frequency demodulated spectrum (Fourier spectrum of instantaneous frequency) of
Kramer, G.Y.; Besse, S.; Dhingra, D.; Nettles, J.; Klima, R.; Garrick-Bethell, I.; Clark, Roger N.; Combe, J.-P.; Head, J. W.; Taylor, L.A.; Pieters, C.M.; Boardman, J.; McCord, T.B.
2011-01-01
We examined the lunar swirls using data from the Moon Mineralogy Mapper (M3). The improved spectral and spatial resolution of M3 over previous spectral imaging data facilitates distinction of subtle spectral differences, and provides new information about the nature of these enigmatic features. We characterized spectral features of the swirls, interswirl regions (dark lanes), and surrounding terrain for each of three focus regions: Reiner Gamma, Gerasimovich, and Mare Ingenii. We used Principle Component Analysis to identify spectrally distinct surfaces at each focus region, and characterize the spectral features that distinguish them. We compared spectra from small, recent impact craters with the mature soils into which they penetrated to examine differences in maturation trends on- and off-swirl. Fresh, on-swirl crater spectra are higher albedo, exhibit a wider range in albedos and have well-preserved mafic absorption features compared with fresh off-swirl craters. Albedoand mafic absorptions are still evident in undisturbed, on-swirl surface soils, suggesting the maturation process is retarded. The spectral continuum is more concave compared with off-swirl spectra; a result of the limited spectral reddening being mostly constrained to wavelengths less than ∼1500 nm. Off-swirl spectra show very little reddening or change in continuum shape across the entire M3 spectral range. Off-swirl spectra are dark, have attenuated absorption features, and the narrow range in off-swirl albedos suggests off-swirl regions mature rapidly. Spectral parameter maps depicting the relative OH surface abundance for each of our three swirl focus regions were created using the depth of the hydroxyl absorption feature at 2.82 μm. For each of the studied regions, the 2.82 μm absorption feature is significantly weaker on-swirl than off-swirl, indicating the swirls are depleted in OH relative to their surroundings. The spectral characteristics of the swirls and adjacent terrains
A NONPARAMETRIC HYPOTHESIS TEST VIA THE BOOTSTRAP RESAMPLING
Temel, Tugrul T.
2001-01-01
This paper adapts an already existing nonparametric hypothesis test to the bootstrap framework. The test utilizes the nonparametric kernel regression method to estimate a measure of distance between the models stated under the null hypothesis. The bootstraped version of the test allows to approximate errors involved in the asymptotic hypothesis test. The paper also develops a Mathematica Code for the test algorithm.
Simple nonparametric checks for model data fit in CAT
Meijer, R.R.
2005-01-01
In this paper, the usefulness of several nonparametric checks is discussed in a computerized adaptive testing (CAT) context. Although there is no tradition of nonparametric scalability in CAT, it can be argued that scalability checks can be useful to investigate, for example, the quality of item
Nonparametric Bayesian inference for multidimensional compound Poisson processes
Gugushvili, S.; van der Meulen, F.; Spreij, P.
2015-01-01
Given a sample from a discretely observed multidimensional compound Poisson process, we study the problem of nonparametric estimation of its jump size density r0 and intensity λ0. We take a nonparametric Bayesian approach to the problem and determine posterior contraction rates in this context,
Chakraborty, Somsubhra; Das, Bhabani S; Ali, Md Nasim; Li, Bin; Sarathjith, M C; Majumdar, K; Ray, D P
2014-03-01
The aim of this study was to investigate the feasibility of using visible near-infrared (VisNIR) diffuse reflectance spectroscopy (DRS) as an easy, inexpensive, and rapid method to predict compost enzymatic activity, which traditionally measured by fluorescein diacetate hydrolysis (FDA-HR) assay. Compost samples representative of five different compost facilities were scanned by DRS, and the raw reflectance spectra were preprocessed using seven spectral transformations for predicting compost FDA-HR with six multivariate algorithms. Although principal component analysis for all spectral pretreatments satisfactorily identified the clusters by compost types, it could not separate different FDA contents. Furthermore, the artificial neural network multilayer perceptron (residual prediction deviation=3.2, validation r(2)=0.91 and RMSE=13.38 μg g(-1) h(-1)) outperformed other multivariate models to capture the highly non-linear relationships between compost enzymatic activity and VisNIR reflectance spectra after Savitzky-Golay first derivative pretreatment. This work demonstrates the efficiency of VisNIR DRS for predicting compost enzymatic as well as microbial activity. Copyright © 2013 Elsevier Ltd. All rights reserved.
International Nuclear Information System (INIS)
Osman, Abdalla; El-Sheimy, Naser; Nourledin, Aboelamgd; Theriault, Jim; Campbell, Scott
2009-01-01
The problem of target detection and tracking in the ocean environment has attracted considerable attention due to its importance in military and civilian applications. Sonobuoys are one of the capable passive sonar systems used in underwater target detection. Target detection and bearing estimation are mainly obtained through spectral analysis of received signals. The frequency resolution introduced by current techniques is limited which affects the accuracy of target detection and bearing estimation at a relatively low signal-to-noise ratio (SNR). This research investigates the development of a bearing estimation method using fast orthogonal search (FOS) for enhanced spectral estimation. FOS is employed in this research in order to improve both target detection and bearing estimation in the case of low SNR inputs. The proposed methods were tested using simulated data developed for two different scenarios under different underwater environmental conditions. The results show that the proposed method is capable of enhancing the accuracy for target detection as well as bearing estimation especially in cases of a very low SNR
Directory of Open Access Journals (Sweden)
Peeyush Sahay
2009-10-01
Full Text Available Breath analysis, a promising new field of medicine and medical instrumentation, potentially offers noninvasive, real-time, and point-of-care (POC disease diagnostics and metabolic status monitoring. Numerous breath biomarkers have been detected and quantified so far by using the GC-MS technique. Recent advances in laser spectroscopic techniques and laser sources have driven breath analysis to new heights, moving from laboratory research to commercial reality. Laser spectroscopic detection techniques not only have high-sensitivity and high-selectivity, as equivalently offered by the MS-based techniques, but also have the advantageous features of near real-time response, low instrument costs, and POC function. Of the approximately 35 established breath biomarkers, such as acetone, ammonia, carbon dioxide, ethane, methane, and nitric oxide, 14 species in exhaled human breath have been analyzed by high-sensitivity laser spectroscopic techniques, namely, tunable diode laser absorption spectroscopy (TDLAS, cavity ringdown spectroscopy (CRDS, integrated cavity output spectroscopy (ICOS, cavity enhanced absorption spectroscopy (CEAS, cavity leak-out spectroscopy (CALOS, photoacoustic spectroscopy (PAS, quartz-enhanced photoacoustic spectroscopy (QEPAS, and optical frequency comb cavity-enhanced absorption spectroscopy (OFC-CEAS. Spectral fingerprints of the measured biomarkers span from the UV to the mid-IR spectral regions and the detection limits achieved by the laser techniques range from parts per million to parts per billion levels. Sensors using the laser spectroscopic techniques for a few breath biomarkers, e.g., carbon dioxide, nitric oxide, etc. are commercially available. This review presents an update on the latest developments in laser-based breath analysis.
International Nuclear Information System (INIS)
Becker, J.K.; Marschall, P.; Brunner, P.; Cholet, C.; Renard, P.; Buckley, S.; Kurz, T.
2012-01-01
, and are readily available as spectral libraries for use in software processing packages. Since rocks are composites of minerals, their spectra represent a mixture of spectra of the constituent minerals concerning the reflectance. In general, imaging spectrometry allows a semi-quantitative analysis of mineral abundances from rock spectra, for example by analysing the intensity of absorption bands. In many cases a mineral with a unique absorption signature can be correlated to a specific lithological unit, which can be used to trace and map the lithology. Additionally, abundance and spatial variation can be determined from the rock spectra. Common reflection features in sedimentary rocks are typically related to carbonate and clay minerals, hydroxyl, water or iron-bearing material and weathering products. A number of physical properties can influence the intensity of features in the spectral curves of minerals and rocks, such as particle size, angle of incidence, porosity and surface roughness, though the wavelength positions of the absorption features are not changed. Next to the obvious ability to use the hyper-spectral images to 'visually' correlate layers within a rock over a certain distance they can also be used for a more rigorous approach of geostatistical correlation. We have developed a work flow for this approach using the hyper-spectral image classifications: 1. In a first step, image reconstruction must be performed. During the scanning and possibly also later during classification, some areas of the hyper-spectral images may not be completely usable or some pixels may not have been classified. In this case, the 'holes' should be filled using multiple-point geostatistical techniques. 2. In the present example, images at three different resolutions have been taken. It is envisaged to use the high resolution images and simulate the high resolution over the entire rock face in a way that the high resolution simulations are guided by the low resolution images
Directory of Open Access Journals (Sweden)
Quan Liu
2018-01-01
Full Text Available Important information about the state dynamics of the brain during anesthesia is unraveled by Electroencephalogram (EEG approaches. Patterns that are observed through EEG related to neural circuit mechanism under different molecular targets dependent anesthetics have recently attracted much attention. Propofol, a Gamma-amino butyric acid, is known with evidently increasing alpha oscillation. Desflurane shares the same receptor action and should be similar to propofol. To explore their dynamics, EEG under routine surgery level anesthetic depth is analyzed using multitaper spectral method from two groups: propofol (n = 28 and desflurane (n = 23. The time-varying spectrum comparison was undertaken to characterize their properties. Results show that both of the agents are dominated by slow and alpha waves. Especially, for increased alpha band feature, propofol unconsciousness shows maximum power at about 10 Hz (mean ± SD; frequency: 10.2 ± 1.4 Hz; peak power, −14.0 ± 1.6 dB, while it is approximate about 8 Hz (mean ± SD; frequency: 8.3 ± 1.3 Hz; peak power, −13.8 ± 1.6 dB for desflurane with significantly lower frequency-resolved spectra for this band. In addition, the mean power of propofol is much higher from alpha to gamma band, including slow oscillation than that of desflurane. The patterns might give us an EEG biomarker for specific anesthetic. This study suggests that both of the anesthetics exhibit similar spectral dynamics, which could provide insight into some common neural circuit mechanism. However, differences between them also indicate their uniqueness where relevant.
Spectral data de-noising using semi-classical signal analysis: application to localized MRS
Laleg-Kirati, Taous-Meriem
2016-09-05
In this paper, we propose a new post-processing technique called semi-classical signal analysis (SCSA) for MRS data de-noising. Similar to Fourier transformation, SCSA decomposes the input real positive MR spectrum into a set of linear combinations of squared eigenfunctions equivalently represented by localized functions with shape derived from the potential function of the Schrodinger operator. In this manner, the MRS spectral peaks represented as a sum of these \\'shaped like\\' functions are efficiently separated from noise and accurately analyzed. The performance of the method is tested by analyzing simulated and real MRS data. The results obtained demonstrate that the SCSA method is highly efficient in localized MRS data de-noising and allows for an accurate data quantification.
Account of spectral dependence of instrumental factor in quantitative X-ray fluorescence analysis
International Nuclear Information System (INIS)
Pershin, N.V.; Mosichev, V.I.
1990-01-01
A new method for calibration of X-ray fluorescence spectrometers using scanning spectrometric channel is proposed. The method is based on a separate account of matrix and instrumental effects and needs no calibration standards for the element analysed. For calibration in the whole spectral range of XRS (0.03-1.0 nm) it is sufficient to have from 10 to 15 pure element emitters made of most wide spread elements. The method provides rapid development of quantitative analysis for the elements which are not provided with standard samples and preparation of pure element emitters for which is impossible or problematic. The practical verification of the method was made by analysing a set of 146 standard samples covering a wide group of alloys. The mean relative error of the method was 3-5 % in an analytical range of 0.1-3.0 wt %
Spectral data de-noising using semi-classical signal analysis: application to localized MRS
Laleg-Kirati, Taous-Meriem; Zhang, Jiayu; Achten, Eric; Serrai, Hacene
2016-01-01
In this paper, we propose a new post-processing technique called semi-classical signal analysis (SCSA) for MRS data de-noising. Similar to Fourier transformation, SCSA decomposes the input real positive MR spectrum into a set of linear combinations of squared eigenfunctions equivalently represented by localized functions with shape derived from the potential function of the Schrodinger operator. In this manner, the MRS spectral peaks represented as a sum of these 'shaped like' functions are efficiently separated from noise and accurately analyzed. The performance of the method is tested by analyzing simulated and real MRS data. The results obtained demonstrate that the SCSA method is highly efficient in localized MRS data de-noising and allows for an accurate data quantification.
Spectral analysis of the SN approximations in a slab with quadratically anisotropic scattering
International Nuclear Information System (INIS)
Ourique, L.E.; Pazos, R.P.; Vilhena, M.T.; Barros, R.C.
2003-01-01
The spectral analysis of the S N approximations to the one-dimensional transport equation began with 3 and 4, following the studies of 1 and 2 about the discrete eigenvalues of the transport equation. In previous work about the influence of a parameter in the solutions of S N approximations, it was considered the total macroscopic cross section as a control parameter and was analyzed how its variation changes the nature of the eigenvalues of the S N transport matrix, in problems with linearly anisotropic scattering. It was showed the existence of bifurcations points, i.e., there exist some values of control parameters for which the S N transport matrix has only real eigenvalues while for other values the S N relation between the eigenvalues of S N transport matrix and control parameter, supposing quadratically anisotropic scattering. Numerical results are reported. (author)
Self-adjoint extensions and spectral analysis in the Calogero problem
International Nuclear Information System (INIS)
Gitman, D M; Tyutin, I V; Voronov, B L
2010-01-01
In this paper, we present a mathematically rigorous quantum-mechanical treatment of a one-dimensional motion of a particle in the Calogero potential αx -2 . Although the problem is quite old and well studied, we believe that our consideration based on a uniform approach to constructing a correct quantum-mechanical description for systems with singular potentials and/or boundaries, proposed in our previous works, adds some new points to its solution. To demonstrate that a consideration of the Calogero problem requires mathematical accuracy, we discuss some 'paradoxes' inherent in the 'naive' quantum-mechanical treatment. Using a self-adjoint extension method, we construct and study all possible self-adjoint operators (self-adjoint Hamiltonians) associated with a formal differential expression for the Calogero Hamiltonian. In particular, we discuss a spontaneous scale-symmetry breaking associated with self-adjoint extensions. A complete spectral analysis of all self-adjoint Hamiltonians is presented.
Spectral analysis of the S{sub N} approximations in a slab with quadratically anisotropic scattering
Energy Technology Data Exchange (ETDEWEB)
Ourique, L.E.; Pazos, R.P. [Pontificia Univ. Catolica do Rio Grande do Sul, Porto Alegre, RS (Brazil)]. E-mail: ourique@pucrs.br; rpp@pucrs.br; Vilhena, M.T. [Rio Grande do Sul Univ., Porto Alegre, RS (Brazil). Escola de Engenharia); vilhena@cesup.ufrgs.br; Barros, R.C. [Universidade do Estado, Nova Friburgo, RJ (Brazil). Instituto Politecnico]. E-mail: dickbarros@uol.com.br
2003-07-01
The spectral analysis of the S{sub N} approximations to the one-dimensional transport equation began with 3 and 4, following the studies of 1 and 2 about the discrete eigenvalues of the transport equation. In previous work about the influence of a parameter in the solutions of S{sub N} approximations, it was considered the total macroscopic cross section as a control parameter and was analyzed how its variation changes the nature of the eigenvalues of the S{sub N} transport matrix, in problems with linearly anisotropic scattering. It was showed the existence of bifurcations points, i.e., there exist some values of control parameters for which the S{sub N} transport matrix has only real eigenvalues while for other values the S{sub N} relation between the eigenvalues of S{sub N} transport matrix and control parameter, supposing quadratically anisotropic scattering. Numerical results are reported. (author)
Energy Technology Data Exchange (ETDEWEB)
T Haraszti; C Trantow; A Hedberg-Buenz; M Grunze; M Anderson
2011-12-31
GPNMB is a unique melanosomal protein. Unlike many melanosomal proteins, GPNMB has not been associated with any forms of albinism, and it is unclear whether GPNMB has any direct influence on melanosomes. Here, melanosomes from congenic strains of C57BL/6J mice mutant for Gpnmb are compared to strain-matched controls using standard transmission electron microscopy and synchrotron-based X-ray absorption near-edge structure analysis (XANES). Whereas electron microscopy did not detect any ultrastructural changes in melanosomes lacking functional GPNMB, XANES uncovered multiple spectral phenotypes. These results directly demonstrate that GPNMB influences the chemical composition of melanosomes and more broadly illustrate the potential for using genetic approaches in combination with nano-imaging technologies to study organelle biology.
Energy Technology Data Exchange (ETDEWEB)
Pan, Meiyan, E-mail: yphantomohive@gmail.com; Zeng, Yingzhi; Huang, Zuohua, E-mail: zuohuah@163.com [Laboratory of Quantum Engineering and Quantum Materials, School of Physics and Telecommunication Engineering, South China Normal University, Guangzhou, Guangdong 510006 (China)
2014-09-15
A new method based on diffraction spectral analysis is proposed for the quantitative measurement of the phase variation amplitude of an ultrasonic diffraction grating. For a traveling wave, the phase variation amplitude of the grating depends on the intensity of the zeroth- and first-order diffraction waves. By contrast, for a standing wave, this amplitude depends on the intensity of the zeroth-, first-, and second-order diffraction waves. The proposed method is verified experimentally. The measured phase variation amplitude ranges from 0 to 2π, with a relative error of approximately 5%. A nearly linear relation exists between the phase variation amplitude and driving voltage. Our proposed method can also be applied to ordinary sinusoidal phase grating.
Frequency-dependant homogenized properties of composite using spectral analysis method
International Nuclear Information System (INIS)
Ben Amor, M; Ben Ghozlen, M H; Lanceleur, P
2010-01-01
An inverse procedure is proposed to determine the material constants of multilayered composites using a spectral analysis homogenization method. Recursive process gives interfacial displacement perpendicular to layers in term of deepness. A fast-Fourier transform (FFT) procedure has been used in order to extract the wave numbers propagating in the multilayer. The upper frequency bound of this homogenization domain is estimated. Inside the homogenization domain, we discover a maximum of three planes waves susceptible to propagate in the medium. A consistent algorithm is adopted to develop an inverse procedure for the determination of the materials constants of multidirectional composite. The extracted wave numbers are used as the inputs for the procedure. The outputs are the elastic constants of multidirectional composite. Using this method, the frequency dependent effective elastic constants are obtained and example for [0/90] composites is given.
International Nuclear Information System (INIS)
Bhade, Sonali P.D.; Reddy, P.J.; Kolekar, R.V.; Singh, Rajvir; Pradeepkumar, K.S.
2014-01-01
The potential use of alpha LSC technique is nowadays recognized widely. However the energy resolution of α particle is poor with liquid scintillators. Moreover, α peak positions are influenced by the level of quenching in the samples. To overcome this problem, a thorough study of all concerned parameters that affect spectral information was carried out. The parameters such as peak's centroid, quenching, % resolution, energy of α particle were investigated and the correlation between them was evaluated. In the present work, the qualitative analysis of α spectrum was carried out. Correlations between the energy of α particle and various parameters affecting the peaks of the collected spectra with respect to quenching were established. These correlations will be useful for the deconvolution studies of composite samples containing different alpha radionuclides
Wavelet and Spectral Analysis of Some Selected Problems in Reactor Diagnostics
Energy Technology Data Exchange (ETDEWEB)
Sunde, Carl
2004-12-01
Both spectral and wavelet analysis were successfully used in various diagnostic problems involving non-stationary core processes in nuclear power reactors. Three different problems were treated: two-phase flow identification, detector tube impacting and core-barrel vibrations. The first two problems are of non-stationary nature, whereas the last one is not. In the first problem, neutron radiographic and visible light images of four different vertical two-phase flow regimes, bubbly, slug, chum and annular flow, were analysed and classified with a neuro-wavelet algorithm. The algorithm consists of a wavelet part, using the 2-D discrete wavelet transform and of an artificial neural network. It classifies the different flow regimes with up to 99% efficiency. Detector tubes in a Boiling Water Reactor may execute vibrations and may also impact on nearby fuel-assemblies. Signals from in-core neutron detectors in Ringhals-1 were analysed, for detection of impacting, with both a classical spectral method and wavelet-based methods. The wavelet methods include both the discrete and the continuous 1-D wavelet transform. It was found that there is agreement between the different methods as well as with visual inspections made during the outage at the plant. However, the wavelet technique has the advantage that it does not require expert judgement for the interpretation of the analysis. In the last part two analytical calculations of the neutron noise, induced by shell-mode core-barrel vibrations, were carried out. The results are in good agreement with calculations from a numerical simulator. An out-of-phase behaviour between in-core and ex-core positions was found, which is in agreement with earlier measurements from the Pressurised Water Reactor Ringhals-3. The results from these calculations are planned to be used when diagnosing the shell-mode core-barrel vibrations in an operating plant.