272 resultados para Relax NG


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Multiple flame-flame interactions in premixed combustion are investigated using direct numerical simulations of twin turbulent V-flames for a range of turbulence intensities and length scales. Interactions are identified using a novel automatic feature extraction (AFE) technique, based on data registration using the dual-tree complex wavelet transform. Information on the time, position, and type of interactions, and their influence on the flame area is extracted using AFE. Characteristic length and time scales for the interactions are identified. The effect of interactions on the flame brush is quantified through a global stretch rate, defined as the sum of flamelet stretch and interaction stretch contributions. The effects of each interaction type are discussed. It is found that the magnitude of the fluctuations in flamelet and interaction stretch are comparable, and a qualitative sensitivity to turbulence length scale is found for one interaction type. Implications for modeling are discussed. © 2013 Copyright Taylor and Francis Group, LLC.

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Copulas allow to learn marginal distributions separately from the multivariate dependence structure (copula) that links them together into a density function. Vine factorizations ease the learning of high-dimensional copulas by constructing a hierarchy of conditional bivariate copulas. However, to simplify inference, it is common to assume that each of these conditional bivariate copulas is independent from its conditioning variables. In this paper, we relax this assumption by discovering the latent functions that specify the shape of a conditional copula given its conditioning variables We learn these functions by following a Bayesian approach based on sparse Gaussian processes with expectation propagation for scalable, approximate inference. Experiments on real-world datasets show that, when modeling all conditional dependencies, we obtain better estimates of the underlying copula of the data.

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Restoring a scene distorted by atmospheric turbulence is a challenging problem in video surveillance. The effect, caused by random, spatially varying, perturbations, makes a model-based solution difficult and in most cases, impractical. In this paper, we propose a novel method for mitigating the effects of atmospheric distortion on observed images, particularly airborne turbulence which can severely degrade a region of interest (ROI). In order to extract accurate detail about objects behind the distorting layer, a simple and efficient frame selection method is proposed to select informative ROIs only from good-quality frames. The ROIs in each frame are then registered to further reduce offsets and distortions. We solve the space-varying distortion problem using region-level fusion based on the dual tree complex wavelet transform. Finally, contrast enhancement is applied. We further propose a learning-based metric specifically for image quality assessment in the presence of atmospheric distortion. This is capable of estimating quality in both full-and no-reference scenarios. The proposed method is shown to significantly outperform existing methods, providing enhanced situational awareness in a range of surveillance scenarios. © 1992-2012 IEEE.

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The influence of Lewis number on turbulent premixed flame interactions is investigated using automatic feature extraction (AFE) applied to high-resolution flame simulation data. Premixed turbulent twin V-flames under identical turbulence conditions are simulated at global Lewis numbers of 0.4, 0.8, 1.0, and 1.2. Information on the position, frequency, and magnitude of the interactions is compared, and the sensitivity of the results to sample interval is discussed. It is found that both the frequency and magnitude of normal type interactions increases with decreasing Lewis number. Counternormal type interactions become more likely as the Lewis number increases. The variation in both the frequency and the magnitude of the interactions is found to be caused by large-scale changes in flame wrinkling resulting from differences in the thermo-diffusive stability of the flames. During flame interactions, thermo-diffusive effects are found to be insignificant due to the separation of time scales. © 2013 Copyright Taylor and Francis Group, LLC.

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We perform polarization-resolved Raman spectroscopy on graphene in magnetic fields up to 45 T. This reveals a filling-factor-dependent, multicomponent anticrossing structure of the Raman G peak, resulting from magnetophonon resonances between magnetoexcitons and E2g phonons. This is explained with a model of Raman scattering taking into account the effects of spatially inhomogeneous carrier densities and strain. Random fluctuations of strain-induced pseudomagnetic fields lead to increased scattering intensity inside the anticrossing gap, consistent with the experiments. © 2013 American Physical Society.

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Label-free detection of cancer biomarkers using low cost biosensors has promising applications in clinical diagnostics. In this work, ZnO-based thin film bulk acoustic wave resonators (FBARs) with resonant frequency of ∼1.5 GHz and mass sensitivity of 0.015 mg/m2 (1.5 ng/cm2) have been fabricated for their deployment as biosensors. Mouse monoclonal antibody, anti-human prostate-specific antigen (Anti-hPSA) has been used to bind human prostate-specific antigen (hPSA), a model cancer used in this study. Ellipsometry was used to characterize and optimise the antibody adsorption and antigen binding on gold surface. It was found that the best amount of antibody at the gold surface for effective antigen binding is around 1 mg/m2, above or below which resulted in the reduced antigen binding due to either the limited binding sites (below 1 mg/m2) or increased steric effect (above 1 mg/m2). The FBAR data were in good agreement with the data obtained from ellipsometry. Antigen binding experiments using FBAR sensors demonstrated that FBARs have the capability to precisely detect antigen binding, thereby making FBARs an attractive low cost alternative to existing cancer diagnostic sensors. © 2013 Elsevier B.V.

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This letter demonstrates for the first time the effect of the incomplete ionization (I.I.) of the transparent p-anode layer on the static and dynamic characteristics of the field-stop insulated gate bipolar transistors (FS IGBTs). This effect needs to be considered in FS IGBTs TCAD modeling to match accurately the device characteristics across a wide range of temperatures. The acceptor ionization energy (EA) governing the I.I. mechanism for the p-anode is extracted via matching the experimental turn-off waveforms and the static performance with Medici simulator. © 1980-2012 IEEE.

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Picosecond pulsed laser (10.4 ps, 1064 nm, 5 and 50 kHz) patterning studies were performed, of PEDOT:PSS thin films of varying thickness deposited by spin coating on glass substrates, by ablating the films or by changing locally by laser irradiation the optical and electrical properties of the polymer. From a detailed observation of the morphology of single pulse ablated holes on the surfaces of the films, in combination with simple calculations, it is concluded that photomechanical ablation is the likely ablation mechanism of the films. The single pulse ablation thresholds were measured equal to 0.13-0.18 J/cm 2 for films with thicknesses in the region of ∼100-600 nm. The implications on ablation line patterning of the films using different fluences, scanning speeds and pulse repetition rates, were investigated systematically. Laser irradiation of the films before ablation induces a metal-insulator transition of the polymer because of the formation of charge localization due to a possible creation of molecular disorder in the polymer and shortening of its conjugation length. © 2010 Elsevier B.V. All rights reserved.

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The importance of properly exploiting a classifier's inherent geometric characteristics when developing a classification methodology is emphasized as a prerequisite to achieving near optimal performance when carrying out thematic mapping. When used properly, it is argued that the long-standing maximum likelihood approach and the more recent support vector machine can perform comparably. Both contain the flexibility to segment the spectral domain in such a manner as to match inherent class separations in the data, as do most reasonable classifiers. The choice of which classifier to use in practice is determined largely by preference and related considerations, such as ease of training, multiclass capabilities, and classification cost. © 1980-2012 IEEE.