990 resultados para Complexity measurement


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We report the first observation of two Cabibbo-suppressed ecay modes, Xi(+)(c) -> Sigma(+)pi(-)pi(+) and Xi c+ -> Sigma(-)pi(+)pi(+). We observe 59 +/- 14 over a background of 87, and 22 +/- 8 over a background of 13 events, respectively, for the signals. The data were accumulated using the SELEX spectrometer during the 1996-1997 fixed target run at Fermilab, chiefly from a 600 Gev/c Sigma(-) beam. The branching ratios of the decays relative to the Cabibbo-favored Xi c+ -> Xi(-)pi(+)pi(+) are measured to be B(Xi(+)(c) -> Sigma(+)pi(-)pi(+))/B(Xi(+)(c) -> Xi(-)pi(+)pi(+)) = 0.48 +/- 0.20, and B(Xi(+)(c) -> Sigma(-)pi(+)pi(+))/B(Xi(+)(c) -> Sigma(-)pi(+)pi(+)) = 0.18 +/- 0.09, respectively. We also report branching ratios for the same decay modes of the Delta(+)(c) relative to Delta(+)(c) -> pK(-)pi(+.) (C) 2008 Elsevier B.V. All rights reserved.

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The (16)O+(27)Al elastic and inelastic angular distributions have been measured in a broad angular range (13 degrees < theta(lab) < 52 degrees) at about 100 MeV incident energy. The use of the MAGNEX large acceptance magnetic spectrometer and of the ray-reconstruction analysis technique has been crucial in order to provide, in the same experiment, high-resolution energy spectra and cross-section measurements distributed over more than seven orders of magnitude down to hundreds of nb/sr. (C) 2011 Elsevier B.V. All rights reserved.

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We describe how the method of detection of delayed K x-rays produced by the electron capture decay of the residual nuclei can be a powerful tool in the investigation of the effect of the breakup process on the complete fusion (CF) cross-section of weakly bound nuclei at energies close to the Coulomb barrier. This is presently one of the most interesting subjects under investigation in the field of low-energy nuclear reactions, and the difficult experimental task of separating CF from the incomplete fusion (ICF) of one of the breakup fragments can be achieved by the x-ray spectrometry method. We present results for the fusion of the (9)Be + (144)Sm system. Copyright (c) 2008 John Wiley & Sons, Ltd.

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Electron transport parameters are important in several areas ranging from particle detectors to plasma-assisted processing reactors. Nevertheless, especially at high fields strengths and for complex gases, relatively few data are published. A dedicated setup has been developed to measure the electron drift velocity and the first Townsend coefficient in parallel plate geometry. An RPC-like cell has been adopted to reach high field strengths without the risk of destructive sparks. The validation data obtained with pure Nitrogen will be presented and compared to a selection of the available literature and to calculations performed with Magboltz 2 version 8.6. The new data collected in pure Isobutane will then be discussed. This is the first time the electron drift velocity in pure Isobutane is measured well into the saturation region. Good agreement is found with expectations from Magboltz. (C) 2009 Elsevier B.V. All rights reserved.

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We report the J/psi -> e(+)e(-) and the psi` -> e(+)e(-) production cross sections in the PHENIX experiment at RHIC. The first measurements of the production cross sections of the psi` and the psi` over the J/psi, will contribute to the clarification of the theoretical understanding of the J/psi meson production. The inclusive J/psi polarization through the same decay channel is also presented, showing a trend of slightly longitudinal polarization for p(T) <5 GeV/c.

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Texture is one of the most important visual attributes used in image analysis. It is used in many content-based image retrieval systems, where it allows the identification of a larger number of images from distinct origins. This paper presents a novel approach for image analysis and retrieval based on complexity analysis. The approach consists of a texture segmentation step, performed by complexity analysis through BoxCounting fractal dimension, followed by the estimation of complexity of each computed region by multiscale fractal dimension. Experiments have been performed with MRI database in both pattern recognition and image retrieval contexts. Results show the accuracy of the method and also indicate how the performance changes as the texture segmentation process is altered.

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The aim of this study was to evaluate the shrinkage of a microhybrid dental composite resin photo-activated by one LED with different power densities by means of speckle technique. The dental composite resin Filtek (TM) Z-250 (3M/ESPE) at color A(2) was used for the samples preparation. Uncured composite was packed in a metallic mold and irradiated during 20 s from 100 to 1000 mW cm(-2). For the photo-activation of the samples, it was used a LED prototype (Light Emission Diode) with wavelength centered at 470 nm and adjustable power density until 1 W cm(-2). The speckle patterns obtained from the bottom composite surfaces were monitored using a CCD camera without lens. The speckle field is recorded in a digital picture and stored by CCD camera as the carrier of information on the displacement of the tested surface. The calculated values were obtained for each pair of adjacent patterns and the changes in speckle contrast as a function of time were obtained from six repeated measurements. The speckle contrasts obtained from the bottom surface with 100 mW cm(-1) were smaller than those than the other power densities. The higher power densities provided the higher shrinkage.

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In this paper, I review some recent high-precision Rydberg state lifetime measurements using a cold-trapped sample of neutral atoms held in a magneto-optical trap. The measurements were performed in rubidium for the S, P and D states varying the principal quantum number from n = 26 to 45 using the field ionization technique. The experimental results were compared with quantum mechanical calculations and good agreement was observed. This is an important demonstration of how cold atomic samples can be used to perform high-precision spectroscopy in the time domain.

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One of the challenges in epidemiology is to account for the complex morphological structure of hosts such as plant roots, crop fields, farms, cells, animal habitats and social networks, when the transmission of infection occurs between contiguous hosts. Morphological complexity brings an inherent heterogeneity in populations and affects the dynamics of pathogen spread in such systems. We have analysed the influence of realistically complex host morphology on the threshold for invasion and epidemic outbreak in an SIR (susceptible-infected-recovered) epidemiological model. We show that disorder expressed in the host morphology and anisotropy reduces the probability of epidemic outbreak and thus makes the system more resistant to epidemic outbreaks. We obtain general analytical estimates for minimally safe bounds for an invasion threshold and then illustrate their validity by considering an example of host data for branching hosts (salamander retinal ganglion cells). Several spatial arrangements of hosts with different degrees of heterogeneity have been considered in order to separately analyse the role of shape complexity and anisotropy in the host population. The estimates for invasion threshold are linked to morphological characteristics of the hosts that can be used for determining the threshold for invasion in practical applications.

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We report a measurement of the flux of cosmic rays with unprecedented precision and Statistics using the Pierre Auger Observatory Based on fluorescence observations in coincidence with at least one Surface detector we derive a spectrum for energies above 10(18) eV We also update the previously published energy spectrum obtained with the surface detector array The two spectra are combined addressing the systematic uncertainties and, in particular. the influence of the energy resolution on the spectral shape The spectrum can be described by a broken power law E(-gamma) with index gamma = 3 3 below the ankle which is measured at log(10)(E(ankle)/eV) = 18 6 Above the ankle the spectrum is described by a power law with index 2 6 followed by a flux suppression, above about log(10)(E/eV) = 19 5, detected with high statistical significance (C) 2010 Elsevier B V All rights reserved

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In this article, we discuss inferential aspects of the measurement error regression models with null intercepts when the unknown quantity x (latent variable) follows a skew normal distribution. We examine first the maximum-likelihood approach to estimation via the EM algorithm by exploring statistical properties of the model considered. Then, the marginal likelihood, the score function and the observed information matrix of the observed quantities are presented allowing direct inference implementation. In order to discuss some diagnostics techniques in this type of models, we derive the appropriate matrices to assessing the local influence on the parameter estimates under different perturbation schemes. The results and methods developed in this paper are illustrated considering part of a real data set used by Hadgu and Koch [1999, Application of generalized estimating equations to a dental randomized clinical trial. Journal of Biopharmaceutical Statistics, 9, 161-178].

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The main object of this paper is to discuss the Bayes estimation of the regression coefficients in the elliptically distributed simple regression model with measurement errors. The posterior distribution for the line parameters is obtained in a closed form, considering the following: the ratio of the error variances is known, informative prior distribution for the error variance, and non-informative prior distributions for the regression coefficients and for the incidental parameters. We proved that the posterior distribution of the regression coefficients has at most two real modes. Situations with a single mode are more likely than those with two modes, especially in large samples. The precision of the modal estimators is studied by deriving the Hessian matrix, which although complicated can be computed numerically. The posterior mean is estimated by using the Gibbs sampling algorithm and approximations by normal distributions. The results are applied to a real data set and connections with results in the literature are reported. (C) 2011 Elsevier B.V. All rights reserved.

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This work presents a Bayesian semiparametric approach for dealing with regression models where the covariate is measured with error. Given that (1) the error normality assumption is very restrictive, and (2) assuming a specific elliptical distribution for errors (Student-t for example), may be somewhat presumptuous; there is need for more flexible methods, in terms of assuming only symmetry of errors (admitting unknown kurtosis). In this sense, the main advantage of this extended Bayesian approach is the possibility of considering generalizations of the elliptical family of models by using Dirichlet process priors in dependent and independent situations. Conditional posterior distributions are implemented, allowing the use of Markov Chain Monte Carlo (MCMC), to generate the posterior distributions. An interesting result shown is that the Dirichlet process prior is not updated in the case of the dependent elliptical model. Furthermore, an analysis of a real data set is reported to illustrate the usefulness of our approach, in dealing with outliers. Finally, semiparametric proposed models and parametric normal model are compared, graphically with the posterior distribution density of the coefficients. (C) 2009 Elsevier Inc. All rights reserved.

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Scale mixtures of the skew-normal (SMSN) distribution is a class of asymmetric thick-tailed distributions that includes the skew-normal (SN) distribution as a special case. The main advantage of these classes of distributions is that they are easy to simulate and have a nice hierarchical representation facilitating easy implementation of the expectation-maximization algorithm for the maximum-likelihood estimation. In this paper, we assume an SMSN distribution for the unobserved value of the covariates and a symmetric scale mixtures of the normal distribution for the error term of the model. This provides a robust alternative to parameter estimation in multivariate measurement error models. Specific distributions examined include univariate and multivariate versions of the SN, skew-t, skew-slash and skew-contaminated normal distributions. The results and methods are applied to a real data set.

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In general, the normal distribution is assumed for the surrogate of the true covariates in the classical error model. This paper considers a class of distributions, which includes the normal one, for the variables subject to error. An estimation approach yielding consistent estimators is developed and simulation studies reported.