969 resultados para Metabolization coefficients


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Interdiffusion study is conducted in the V-Si system to determine integrated diffusion coefficients of the phases. Activation energy values are calculated from the experiments conducted at different temperatures. The average values are found to be 208, 240 and 141 kJ/mol, respectively, for the V(3)Si, V(5)Si(3) and VSi(2) phases. The low activation energy for the VSi(2) phase indicates very high concentration of defects or the significant contribution from the grain boundary diffusion. The error in calculation of diffusion parameters from a very thin phase layer in a multiphase diffusion couple is discussed. Further the data available in the literature in this system is compared and the problems in the indirect methodology followed previously to calculate the diffusion parameters are discussed.

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Polynomial chaos expansion (PCE) with Latin hypercube sampling (LHS) is employed for calculating the vibrational frequencies of an inviscid incompressible fluid partially filled in a rectangular tank with and without a baffle. Vibration frequencies of the coupled system are described through their projections on the PCE which uses orthogonal basis functions. PCE coefficients are evaluated using LHS. Convergence on the coefficient of variation is used to find the orthogonal polynomial basis function order which is employed in PCE. It is observed that the dispersion in the eigenvalues is more in the case of a rectangular tank with a baffle. The accuracy of the PCE method is verified with standard MCS results and is found to be more efficient.

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We propose a method to encode a 3D magnetic resonance image data and a decoder in such way that fast access to any 2D image is possible by decoding only the corresponding information from each subband image and thus provides minimum decoding time. This will be of immense use for medical community, because most of the PET and MRI data are volumetric data. Preprocessing is carried out at every level before wavelet transformation, to enable easier identification of coefficients from each subband image. Inclusion of special characters in the bit stream facilitates access to corresponding information from the encoded data. Results are taken by performing Daub4 along x (row), y (column) direction and Haar along z (slice) direction. Comparable results are achieved with the existing technique. In addition to that decoding time is reduced by 1.98 times. Arithmetic coding is used to encode corresponding information independently

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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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We formulate a two-stage Iterative Wiener filtering (IWF) approach to speech enhancement, bettering the performance of constrained IWF, reported in literature. The codebook constrained IWF (CCIWF) has been shown to be effective in achieving convergence of IWF in the presence of both stationary and non-stationary noise. To this, we include a second stage of unconstrained IWF and show that the speech enhancement performance can be improved in terms of average segmental SNR (SSNR), Itakura-Saito (IS) distance and Linear Prediction Coefficients (LPC) parameter coincidence. We also explore the tradeoff between the number of CCIWF iterations and the second stage IWF iterations.

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In this paper, we present a new speech enhancement approach, that is based on exploiting the intra-frame dependency of discrete cosine transform (DCT) domain coefficients. It can be noted that the existing enhancement techniques treat the transformdomain coefficients independently. Instead of this traditional approach of independently processing the scalars, we split the DCT domain noisy speech vector into sub-vectors and each sub-vector is enhanced independently. Through this sub-vector based approach, the higher dimensional enhancement advantage, viz. non-linear dependency, is exploited. In the developed method, each clean speech sub-vector is modeled using a Gaussian mixture (GM) density. We show that the proposed Gaussian mixture model (GMM) based DCT domain method, using sub-vector processing approach, provides better performance than the conventional approach of enhancing the transform domain scalar components independently. Performance improvement over the recently proposed GMM based time domain approach is also shown.

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We address the problem of local-polynomial modeling of smooth time-varying signals with unknown functional form, in the presence of additive noise. The problem formulation is in the time domain and the polynomial coefficients are estimated in the pointwise minimum mean square error (PMMSE) sense. The choice of the window length for local modeling introduces a bias-variance tradeoff, which we solve optimally by using the intersection-of-confidence-intervals (ICI) technique. The combination of the local polynomial model and the ICI technique gives rise to an adaptive signal model equipped with a time-varying PMMSE-optimal window length whose performance is superior to that obtained by using a fixed window length. We also evaluate the sensitivity of the ICI technique with respect to the confidence interval width. Simulation results on electrocardiogram (ECG) signals show that at 0dB signal-to-noise ratio (SNR), one can achieve about 12dB improvement in SNR. Monte-Carlo performance analysis shows that the performance is comparable to the basic wavelet techniques. For 0 dB SNR, the adaptive window technique yields about 2-3dB higher SNR than wavelet regression techniques and for SNRs greater than 12dB, the wavelet techniques yield about 2dB higher SNR.

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Conventional hardware implementation techniques for FIR filters require the computation of filter coefficients in software and have them stored in memory. This approach is static in the sense that any further fine tuning of the filter requires computation of new coefficients in software. In this paper, we propose an alternate technique for implementing FIR filters in hardware. We store a considerably large number of impulse response coefficients of the ideal filter (having box type frequency response) in memory. We then do the windowing process, on these coefficients, in hardware using integer sequences as window functions. The integer sequences are also generated in hardware. This approach offers the flexibility in fine tuning the filter, like varying the transition bandwidth around a particular cutoff frequency.

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Abstract—A method of testing for parametric faults of analog circuits based on a polynomial representaion of fault-free function of the circuit is presented. The response of the circuit under test (CUT) is estimated as a polynomial in the applied input voltage at relevant frequencies apart from DC. Classification of CUT is based on a comparison of the estimated polynomial coefficients with those of the fault free circuit. The method needs very little augmentation of circuit to make it testable as only output parameters are used for classification. This procedure is shown to uncover several parametric faults causing smaller than 5 % deviations the nominal values. Fault diagnosis based upon sensitivity of polynomial coefficients at relevant frequencies is also proposed.

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Transfer function coefficients (TFC) are widely used to test linear analog circuits for parametric and catastrophic faults. This paper presents closed form expressions for an upper bound on the defect level (DL) and a lower bound on fault coverage (FC) achievable in TFC based test method. The computed bounds have been tested and validated on several benchmark circuits. Further, application of these bounds to scalable RC ladder networks reveal a number of interesting characteristics. The approach adopted here is general and can be extended to find bounds of DL and FC of other parametric test methods for linear and non-linear circuits.

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Abstract—DC testing of parametric faults in non-linear analog circuits based on a new transformation, entitled, V-Transform acting on polynomial coefficient expansion of the circuit function is presented. V-Transform serves the dual purpose of monotonizing polynomial coefficients of circuit function expansion and increasing the sensitivity of these coefficients to circuit parameters. The sensitivity of V-Transform Coefficients (VTC) to circuit parameters is up to 3x-5x more than sensitivity of polynomial coefficients. As a case study, we consider a benchmark elliptic filter to validate our method. The technique is shown to uncover hitherto untestable parametric faults whose sizes are smaller than 10 % of the nominal values. I.

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In this paper we propose a concept and report experimental results based on a circular array of Piezoelectric Wafer Active Sensors (PWASs) for rapid localization and parametric identification of corrosion type damage in metallic plates. Implementation of this circular array of PWASs combines the use of ultrasonic Lamb wave propagation technique and an algorithm based on symmetry breaking in the signal pattern to locate and monitor the growth of a corrosion pit on a metallic plate. Wavelet time-frequency maps of the sensor signals are employed to obtain an insight regarding the effect of corrosion growth on the Lamb wave transmission in time-frequency scale. We present here a method to eliminate the time scale, which helps in identifying easily the signature of damage in the measured signals. The proposed method becomes useful in determining the approximate location of the damage with respect to the location of three neighboring sensors in the circular array. A cumulative damage index is computed from the wavelet coefficients for varying damage sizes and the results appear promising. Damage index is plotted against the damage parameters for frequency sweep of the excitation signal (a windowed sine signal). Results of corrosion damage are compared with circular holes of various sizes to demonstrate the applicability of present method to different types of damage. (C) 2011 Elsevier Ltd. All rights reserved.

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Laboratory advection-diffusion tests are performed on two regional soils-Brown Earth and Red Earth-in order to assess their capacity to control contaminant migration with synthetic contaminant solution of sodium sulphate with sodium concentration of 1000 mg/L. The test was designed to study the transport/attenuation behaviour of sodium in the presence of sulphate. Effective diffusion coefficient (De) that takes into consideration of attenuation processes is used. Cation exchange capacity is an important factor for the attenuation of cationic species. Monovalent sodium ion cannot usually replace other cations and the retention of sodium ion is very less. This is particularly true when chloride is anion is solution. However, sulphate is likely to play a role in the attenuation of sodium. Cation exchange capacity and type of exchangeable ions of soils are likely to play an important role. The effect of sulphate ions on the effective diffusion coefficient of sodium, in two different types of soils, of different cation exchange capacity has been studied. The effective diffusion coefficients of sodium ion for both the soils were calculated using Ogata Bank’s equation. It was shown that effective diffusion coefficient of sodium in the presence of sulphate is lower for Brown Earth than for Red Earth due to exchange of sodium with calcium ions from the exchangeable complex of clay. The soil with the higher cation exchange retained more sodium. Consequently, the breakthrough times and the number of pore volumes of sodium ion increase with the cation exchange capacity of soil.

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In this paper the use of probability theory in reliability based optimum design of reinforced gravity retaining wall is described. The formulation for computing system reliability index is presented. A parametric study is conducted using advanced first order second moment method (AFOSM) developed by Hasofer-Lind and Rackwitz-Fiessler (HL-RF) to asses the effect of uncertainties in design parameters on the probability of failure of reinforced gravity retaining wall. Totally 8 modes of failure are considered, viz overturning, sliding, eccentricity, bearing capacity failure, shear and moment failure in the toe slab and heel slab. The analysis is performed by treating back fill soil properties, foundation soil properties, geometric properties of wall, reinforcement properties and concrete properties as random variables. These results are used to investigate optimum wall proportions for different coefficients of variation of φ (5% and 10%) and targeting system reliability index (βt) in the range of 3 – 3.2.

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Poly(acrylic acid-co-sodium acrylate-co-acrylamide) superabsorbent polymers (SAPs) cross-linked with ethylene glycol dimethacrylate (EGDMA) were synthesized by inverse suspension polymerization. The SAPs were swollen in DI water, and it was found that the equilibrium swelling capacities varied with the acrylamide content. The SAPs were subjected to reversible swelling/deswelling cycles in DI water and aqueous NaCl solution, respectively. The effect of the addition of an electrolyte on the swelling of the SAP was explored. The equilibrium swelling capacity of the SAPs was found to decrease with increasing concentration of added electrolyte in the swelling medium. The effect of the particle size of the dry SAPs on the swelling properties was also investigated. A first order model was used to describe the kinetics of swelling/deswelling, and the equilibrium swelling capacity, limiting swelling capacity, and swelling/deswelling rate coefficients were determined.