940 resultados para Binary mask


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The self-diffusion properties of pure CH4 and its binary mixture with CO2 within MY zeolite have been investigated by combining an experimental quasi-elastic neutron scattering (QENS) technique and classical Molecular dynamics simulations. The QENS measurements carried out at 200 K led to an unexpected self-diffusivity profile for Pure CH4 with the presence of a maximum for a loading of 32 CH4/unit cell, which was never observed before for the diffusion of apolar species in azeolite system With large windows. Molecular dynamics simulations were performed using two distinct microscopic models for representing the CH4/NaY interactions. Depending on the model, we are able to fairly reproduce either the magnitude or the profile of the self-diffusivity.Further analysis allowed LIS to provide some molecular insight into the diffusion mechanism in play. The QENS measurements report only a slight decrease of the self-diffusivity of CH4 in the presence of CO2 when the CO2 loading increases. Molecular dynamics simulations successfully capture this experimental trend and suggest a plausible microscopic diffusion mechanism in the case of this binary mixture.

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This paper reports on a study of 25 nonprofit human service organisations offering four types of human services. The purpose of the study was first to explore the manner in which consumer rights are both conceptualized and operationalized in the nonprofit human service context. Secondly the study explored whether differences occur between organisations whose primary funding body emphasized the importance of a rights framework in its program delivery and those where this is not the case.

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This thesis studies binary time series models and their applications in empirical macroeconomics and finance. In addition to previously suggested models, new dynamic extensions are proposed to the static probit model commonly used in the previous literature. In particular, we are interested in probit models with an autoregressive model structure. In Chapter 2, the main objective is to compare the predictive performance of the static and dynamic probit models in forecasting the U.S. and German business cycle recession periods. Financial variables, such as interest rates and stock market returns, are used as predictive variables. The empirical results suggest that the recession periods are predictable and dynamic probit models, especially models with the autoregressive structure, outperform the static model. Chapter 3 proposes a Lagrange Multiplier (LM) test for the usefulness of the autoregressive structure of the probit model. The finite sample properties of the LM test are considered with simulation experiments. Results indicate that the two alternative LM test statistics have reasonable size and power in large samples. In small samples, a parametric bootstrap method is suggested to obtain approximately correct size. In Chapter 4, the predictive power of dynamic probit models in predicting the direction of stock market returns are examined. The novel idea is to use recession forecast (see Chapter 2) as a predictor of the stock return sign. The evidence suggests that the signs of the U.S. excess stock returns over the risk-free return are predictable both in and out of sample. The new "error correction" probit model yields the best forecasts and it also outperforms other predictive models, such as ARMAX models, in terms of statistical and economic goodness-of-fit measures. Chapter 5 generalizes the analysis of univariate models considered in Chapters 2 4 to the case of a bivariate model. A new bivariate autoregressive probit model is applied to predict the current state of the U.S. business cycle and growth rate cycle periods. Evidence of predictability of both cycle indicators is obtained and the bivariate model is found to outperform the univariate models in terms of predictive power.

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The coexistence curve of the carbondisulphide-acetic anhydride system has been measured. The shape of the curve in the critical region (Xc ≈ 70.89 mole % mole % CS2 and Tc ≈ 30.56° C) is determined by the equation |X′ - X″| = Bx (1 - T/Tc)β with the critical indices β = 0.34 ± 0.01 and Bx = 1.7 ± 0.1 over a range 10-6 < (Tc - T)/Tc < 10-2. The values of β and Bx agree with those of other systems and the theoretical predictions of the Ising model.

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Ultrasonic absorption has been studied by the pulse technique in the binary mixtures of acetic acid in water, methyl and ethyl alcohols and covers a range of 2 to 26 Mc/s. The mixtures are studied from 0 to 100% by weight of the acid. In all the three mixtures, two relaxation processes are observed, the first occurring below the frequency range of the study. The second one occurs near 20 Mc/s in the acid-water mixtures and at much higher frequencies in the other cases. It is qualitatively explained that the monomer-dimer reaction of the acetic acid giving a relaxation near 1 Mc/s has shifted to a higher frequency when mixed in a solvent thus giving rise to a second relaxation in the mixtures.

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This paper describes a hardware implementation of a two-way converter logic by which conversion between numbers from positive to negative binary representation is possible. Index terms: (i) Negative radix, (ii) Positive radix, (iii) Two-way conversion.

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Binary room temperature molten electrolytes based on acetamide and zinc perchlorate have been prepared and characterized. The electrolytes are found to be highly zinc ion-conducting with very favorable physicochemical and electrochemical characteristics. Raman and infrared spectroscopic studies reveal the presence of large free-ion concentration in the molten liquid. This is corroborated by the high conductivity observed under ambient conditions. Rechargeable zinc batteries assembled using gamma-MnO2 as the cathode and Zn as the anode with the molten electrolyte show high discharge capacities over several cycles, indicating excellent reversibility. This unique class of acetamide-based, room temperature molten liquids may become viable and green alternative electrolytes for rechargeable zinc-based secondary batteries. (C) 2009 Elsevier Inc. All rights reserved.

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Template matching is concerned with measuring the similarity between patterns of two objects. This paper proposes a memory-based reasoning approach for pattern recognition of binary images with a large template set. It seems that memory-based reasoning intrinsically requires a large database. Moreover, some binary image recognition problems inherently need large template sets, such as the recognition of Chinese characters which needs thousands of templates. The proposed algorithm is based on the Connection Machine, which is the most massively parallel machine to date, using a multiresolution method to search for the matching template. The approach uses the pyramid data structure for the multiresolution representation of templates and the input image pattern. For a given binary image it scans the template pyramid searching the match. A binary image of N × N pixels can be matched in O(log N) time complexity by our algorithm and is independent of the number of templates. Implementation of the proposed scheme is described in detail.

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The phase equilibrium studies of organic system, involving resorcinol (R) and p-dimethylaminobenzaldehyde (DMAB), reveal the formation of a 1:1 molecular complex with two eutectics. The heat of mixing, entropy of fusion, roughness parameter, interfacial energy, and the excess thermodynamic functions were calculated based on enthalpy of fusion data determined via differential scanning calorimetric (DSC) method. X-ray powder diffraction studies confirm that the eutectics are not simple mechanical mixture of the components under investigation. The spectroscopic investigations (IR and NMR) suggest the occurrence of hydrogen bonding between the components forming the molecular complex. The dielectric measurements, carried out on hot-pressed addition compound (molecular complex), show higher dielectric constant at 320 K than that of individual components. The microstructural investigations of eutectic and addition compound indicate dendritic and faceted morphological features. (C) 2000 Elsevier Science B.V. All rights reserved.

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A molecular theory of collective orientational relaxation of dipolar molecules in a dense liquid is presented. Our work is based on a generalized, nonlinear, Smoluchowski equation (GSE) that includes the effects of intermolecular interactions through a mean‐field force term. The effects of translational motion of the liquid molecules on the orientational relaxation is also included self‐consistently in the GSE. Analytic expressions for the wave‐vector‐dependent orientational correlation functions are obtained for one component, pure liquid and also for binary mixtures. We find that for a dipolar liquid of spherical molecules, the correlation function ϕ(k,t) for l=1, where l is the rank of the spherical harmonics, is biexponential. At zero wave‐vector, one time constant becomes identical with the dielectric relaxation time of the polar liquid. The second time constant is the longitudinal relaxation time, but the contribution of this second component is small. We find that polar forces do not affect the higher order correlation functions (l>1) of spherical dipolar molecules in a linearized theory. The expression of ϕ(k,t) for a binary liquid is a sum of four exponential terms. We also find that the wave‐vector‐dependent relaxation times depend strongly on the microscopic structure of the dense liquid. At intermediate wave vectors, the translational diffusion greatly accelerates the rate of orientational relaxation. The present study indicates that one must pay proper attention to the microscopic structure of the liquid while treating the translational effects. An analysis of the nonlinear terms of the GSE is also presented. An interesting coupling between the number density fluctuation and the orientational fluctuation is uncovered.