961 resultados para azeotropic mixture


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Traditional subspace based speech enhancement (SSE)methods use linear minimum mean square error (LMMSE) estimation that is optimal if the Karhunen Loeve transform (KLT) coefficients of speech and noise are Gaussian distributed. In this paper, we investigate the use of Gaussian mixture (GM) density for modeling the non-Gaussian statistics of the clean speech KLT coefficients. Using Gaussian mixture model (GMM), the optimum minimum mean square error (MMSE) estimator is found to be nonlinear and the traditional LMMSE estimator is shown to be a special case. Experimental results show that the proposed method provides better enhancement performance than the traditional subspace based methods.Index Terms: Subspace based speech enhancement, Gaussian mixture density, MMSE estimation.

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Sub-pixel classification is essential for the successful description of many land cover (LC) features with spatial resolution less than the size of the image pixels. A commonly used approach for sub-pixel classification is linear mixture models (LMM). Even though, LMM have shown acceptable results, pragmatically, linear mixtures do not exist. A non-linear mixture model, therefore, may better describe the resultant mixture spectra for endmember (pure pixel) distribution. In this paper, we propose a new methodology for inferring LC fractions by a process called automatic linear-nonlinear mixture model (AL-NLMM). AL-NLMM is a three step process where the endmembers are first derived from an automated algorithm. These endmembers are used by the LMM in the second step that provides abundance estimation in a linear fashion. Finally, the abundance values along with the training samples representing the actual proportions are fed to multi-layer perceptron (MLP) architecture as input to train the neurons which further refines the abundance estimates to account for the non-linear nature of the mixing classes of interest. AL-NLMM is validated on computer simulated hyperspectral data of 200 bands. Validation of the output showed overall RMSE of 0.0089±0.0022 with LMM and 0.0030±0.0001 with the MLP based AL-NLMM, when compared to actual class proportions indicating that individual class abundances obtained from AL-NLMM are very close to the real observations.

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Binary mixtures have strong influence on activities of polymers and biopolymers even at low cosolvent concentration. Among the several aqueous binary mixtures studied, water-DMSO especially stands out for its unusual behavior at certain specific concentrations of DMSO. In the present work, we study the effect of water-DMSO binary mixture on polymers and biopolymers by taking a simple linear hydrocarbon chain of intermediate length (n = 30) and the protein lysozyme, respectively. We find that at a mole fraction of 0.05 of DMSO (x(DMSO) = 0.05) in aqueous solution, the hydrocarbon chain adopts the collapsed conformation as the most stable and rigid state. In this case of 0.05 mole fraction of DMSO in bulk, the DMSO concentration in the first hydration layer around the polymer is found to be as large as 17%. Formation of such hydrophobic environment around the polymer is the reason for the collapsed state gaining so much stability. Interestingly, similar quench of conformational fluctuation is also observed for the protein investigated. It is observed that in the case of alkane polymer chains, long wavelength fluctuation gets easily quenched, the polymer being purely hydrophobic. However, in case of the protein, quench of fluctuation is prominent only at the hydrophobic surface, and quench of long wavelength fluctuation becomes insignificant for the full protein. As protein contains both hydrophobic and hydrophilic moieties, the extent of quench of conformational fluctuation with respect to that in pure water is almost half for the biopolymer complex (16.83%) than the same for pure hydrophobic polymer chain (32.43%).

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The mechanical properties of clays are highly dependent not only on the stress/strain ratio to which the material is subjected but also on the chemistry of the pore fluids which in turn affects the intergranular or the effective stresses. Atterberg limits and vane shear tests were performed with different pore fluids in order to observe how the fine-grained material mechanically responded. The diffuse double layer theory has been used to interpret the data of vane shear tests in order to explain the variation of geotechnical responses with the different clays. Van der Waals forces and double layer forces were obtained and capillary forces calculated. The results show that while for kaolinite and illite the chemistry of the pore fluids has no influence on the water content and hence on the mechanical behaviour of the material, Na-smectite shows a strong correlation between the dielectric constant of the pore fluids and an increase in undrained shear strength. The data obtained extends an understanding of the influence of the dielectric constant (epsilon) of the pore fluids on the geotechnical properties of fine-grained materials.

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In this Letter the results of an experimental investigation of 1 keV electron irradiation of a 1:1 ice mixture of NH3:CO2 at 30 K was made under ultrahigh vacuum (10(-9) mbar) conditions. Molecular products formed within the ice were detected and monitored using FTIR spectroscopy. The formation of ammonium ions (NH4+), cyanate ions (OCN-), CO was observed leading to the synthesis of ammonium carbamate (NH4NH2CO2). The consequences of these results for prebiotic chemistry in the interstellar medium and star forming regions are discussed. Crown Copyright (C) 2012 Published by Elsevier B.V. All rights reserved.

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The ternary solubilities of solid isomers of nitrobenzoic acid (NBA) were experimentally determined at 308, 318 and 328K over a pressure range of 12-18 MPa in supercritical carbon dioxide (SCCO2). Compared to its binary solubility, the ternary solubilities of m-NBA increased at 308 K while it decreased at 328 K. However, the ternary solubilities of p-NBA increased at all temperatures and pressures except at 13 MPa and 328K. A new model was developed by applying solution model and activity coefficient model for the ternary solubilities of pharmaceutical and non-pharmaceutical solid mixtures in terms of temperature, density and cosolute composition. The model equation involves four temperature independent constraint-free parameters. The model equation correlates the ternary solubilities of seven pharmaceutical solid mixtures along with current data with an average AARD around 9.5% and sixteen non-pharmaceutical solid mixtures with 9% AARD. (C) 2012 Elsevier B.V. All rights reserved.

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We address the problem of robust formant tracking in continuous speech in the presence of additive noise. We propose a new approach based on mixture modeling of the formant contours. Our approach consists of two main steps: (i) Computation of a pyknogram based on multiband amplitude-modulation/frequency-modulation (AM/FM) decomposition of the input speech; and (ii) Statistical modeling of the pyknogram using mixture models. We experiment with both Gaussian mixture model (GMM) and Student's-t mixture model (tMM) and show that the latter is robust with respect to handling outliers in the pyknogram data, parameter selection, accuracy, and smoothness of the estimated formant contours. Experimental results on simulated data as well as noisy speech data show that the proposed tMM-based approach is also robust to additive noise. We present performance comparisons with a recently developed adaptive filterbank technique proposed in the literature and the classical Burg's spectral estimator technique, which show that the proposed technique is more robust to noise.

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The results of an experimental investigation of 1 keV electron irradiation of ices (deposited at 30 K) of (i) pure methanol and (ii) of a 1:1 mixture of NH3:CH3OH are reported. Molecular products formed within the ice were detected and monitored using FTIR spectroscopy. The products observed were methyl formate (H3COHCO), methane (CH4), hydroxymethyl (CH2OH), formamide (HCONH2), formic acid (HCOOH), formaldehyde (H2CO), formyl radical (HCO), cyanate ion (OCN-), isocyanic acid (HNCO), carbon monoxide (CO) and carbon dioxide (CO2). The consequences of these results for prebiotic chemistry in the interstellar medium and star forming regions are discussed. Crown Copyright (C) 2012 Published by Elsevier B. V. All rights reserved.

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Adaptive Gaussian Mixture Models (GMM) have been one of the most popular and successful approaches to perform foreground segmentation on multimodal background scenes. However, the good accuracy of the GMM algorithm comes at a high computational cost. An improved GMM technique was proposed by Zivkovic to reduce computational cost by minimizing the number of modes adaptively. In this paper, we propose a modification to his adaptive GMM algorithm that further reduces execution time by replacing expensive floating point computations with low cost integer operations. To maintain accuracy, we derive a heuristic that computes periodic floating point updates for the GMM weight parameter using the value of an integer counter. Experiments show speedups in the range of 1.33 - 1.44 on standard video datasets where a large fraction of pixels are multimodal.

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Raman spectroscopic study on Oxyfluoro Vanadate glasses containing various proportions of lithium fluoride and rubidium fluoride was carried out to see an effect of mixture of alkali on vanadium-oxygen (V-O) bond length. Glasses with a general formula 40V(2)O(5) - 30BaF(2) - (30 - x) LiF - xRbF (x = 0-30) were prepared. Room temperature Raman spectra of these glass samples were recorded in back scattering geometry. The data presented is in ``reduced Raman intensity'' form with maximum peak scaled to 100. We have used v = Aexp(BR), where A and B are fitting parameters, to correlate the bond length R with Raman scattering frequency v. We observed that variation in bond length and its distribution about a most probable value can be correlated to the alkali environment present in these glasses. We also observed that all rubidium environment around the network forming unit is more homogenous than all lithium environment.

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The solid phase formed by a binary mixture of oppositely charged colloidal particles can be either substitutionally ordered or substitutionally disordered depending on the nature and strength of interactions among the particles. In this work, we use Monte Carlo molecular simulations along with the Gibbs-Duhem integration technique to map out the favorable inter-particle interactions for the formation of substitutionally ordered crystalline phases from a fluid phase. The inter-particle interactions are modeled using the hard core Yukawa potential but the method can be easily extended to other systems of interest. The study obtains a map of interactions depicting regions indicating the type of the crystalline aggregate that forms upon phase transition.

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Experimental and simulation studies have uncovered at least two anomalous concentration regimes in water-dimethyl sulfoxide (DMSO) binary mixture whose precise origin has remained a subject of debate. In order to facilitate time domain experimental investigation of the dynamics of such binary mixtures, we explore strength or extent of influence of these anomalies in dipolar solvation dynamics by carrying out long molecular dynamics simulations over a wide range of DMSO concentration. The solvation time correlation function so calculated indeed displays strong composition dependent anomalies, reflected in pronounced non-exponential kinetics and non-monotonous composition dependence of the average solvation time constant. In particular, we find remarkable slow-down in the solvation dynamics around 10%-20% and 35%-50% mole percentage. We investigate microscopic origin of these two anomalies. The population distribution analyses of different structural morphology elucidate that these two slowing down are reflections of intriguing structural transformations in water-DMSO mixture. The structural transformations themselves can be explained in terms of a change in the relative coordination number of DMSO and water molecules, from 1DMSO:2H(2)O to 1H(2)O:1DMSO and 1H(2)O:2DMSO complex formation. Thus, while the emergence of first slow down (at 15% DMSO mole percentage) is due to the percolation among DMSO molecules supported by the water molecules (whose percolating network remains largely unaffected), the 2nd anomaly (centered on 40%-50%) is due to the formation of the network structure where the unit of 1DMSO:1H(2)O and 2DMSO:1H(2)O dominates to give rise to rich dynamical features. Through an analysis of partial solvation dynamics an interesting negative cross-correlation between water and DMSO is observed that makes an important contribution to relaxation at intermediate to longer times.

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The experimental solubilities of the mixture of nitrophenol (m- and p-) isomers were determined at 308, 318 and 328 K over a pressure range of 10-17.55 MPa. Compared to the binary solubilities, the ternary solubilities of m-nitrophenol increased at 308, 318 and 328 K. The ternary solubilities of p-nitrophenol increased at 308 K, while the ternary solubilities decreased at lower pressures and increased at higher pressure at 318 and 328 K. The solubilities of the solid mixtures in supercritical carbon dioxide (SCCO2) were correlated with solution models by incorporating the non-idealities using activity coefficient based models. The Wilson and NRTL activity coefficient models were applied to determine the nature of the interactions between the molecules. The equation developed by using the NRTL model has three parameters and correlates mixture solubilities of solid solutes in terms of temperature and cosolute composition. The equation derived from the Wilson model contains five parameters and correlates solubilities in terms of temperature, density and cosolute composition. These two new equations developed in this work were used to correlate the solubilities of 25 binary solid mixtures including the current data. The average AARDs of the model equations derived using the NRTL and Wilson models for the solid mixtures were found to be 7% and 4%, respectively. (C) 2012 Elsevier B.V. All rights reserved.

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A binary mixture of oppositely charged colloidal particles can self-assemble into either a substitutionally ordered or substitutionally disordered crystalline phase depending on the nature and strength of interactions among the particles. An earlier study had mapped out favorable inter-particle interactions for the formation of substitutionally ordered crystalline phases from a fluid phase using Monte Carlo molecular simulations along with the Gibbs-Duhem integration technique. In this paper, those studies are extended to determine the effect of fluid phase composition on formation of substitutionally ordered solid phases.