11 resultados para Spectrum decomposition

em Cochin University of Science


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Preparation of simple and mixed ferrospinels of nickel, cobalt and copper and their sulphated analogues by the room temperature coprecipitation method yielded fine particles with high surface areas. Study of the vapour phase decomposition of cyclohexanol at 300 °C over all the ferrospinel systems showed very good conversions yielding cyclohexene by dehydration and/or cyclohexanone by dehydrogenation, as the major products. Sulphation very much enhanced the dehydration activity over all the samples. A good correlation was obtained between the dehydration activities of the simple ferrites and their weak plus medium strength acidities (usually of the Brφnsted type) determined independently by the n-butylamine adsorption and ammonia-TPD methods. Mixed ferrites containing copper showed a general decrease in acidities and a drastic decrease in dehydration activities. There was no general correlation between the basicity parameters obtained by electron donor studies and the ratio of dehydrogenation to dehydration activities. There was a leap in the dehydrogenation activities in the case of all the ferrospinel samples containing copper. Along with the basic properties, the redox properties of copper ion have been invoked to account for this added activity.

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Cyclohexanol decomposition activity of supported vanadia catalysts is ascribed to the high surface area, total acidity and interaction between supported vanadia and the amorphous support. Among the supported catalysts, the effect of vanadia over various wt% V2O5 (2–10) loading indicates that the catalyst comprising of 6 wt% V2O5 exhibits higher acidity and decomposition activity. Structural characterization of the catalysts has been done by techniques like energy dispersive X-ray analysis, X-ray diffraction and BET surface area. Acidity of the catalysts has been measured by temperature programmed desorption using ammonia as a probe molecule and the results have been correlated with the activity of catalysts.

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Department of Applied Chemistry, Cochin University of Science and Technology

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The wavelength dependence of thermal lens signal from organic dyes are studied using dual beam thermal lens technique. It is found that the profile of thermal lens spectrum widely differ from the conventional absorption spectrum in the case of rhodamine B unlike in the case of crystal violet. This is explained on the basis of varying contribution of nonradiative relaxations from the excited vibronic levels.

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High resolution optogalvanic spectrum of the (11, 7) band in the first positive system of nitrogen molecule has been recorded from 17179 to 17376 cm- 1. Assignment of 432 rotational lines belonging to the 27 branches of this band has been carried out.

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The wavelength dependence of thermal lens signal from organic dyes are studied using dual beam thermal lens technique. It is found that the profile of thermal lens spectrum widely differ from the conventional absorption spectrum in the case of rhodamine B unlike in the case of crystal violet. This is explained on the basis of varying contribution of nonradiative relaxations from the excited vibronic levels.

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Photoacoustic spectrum of samarium phthalocyanine powder is recorded and compared with previously reported UV–vis absorption spectra of the same dissolved in different liquid and solid host media. The Davidov splitting of Q band is observed in the PA spectrum but the two bands are overlapped considerably and the shorter wavelength band is more intense and dominating one in the powder spectrum.

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A phantom that exhibits complex dielectric properties similar to low-water-content biological tissues over the electromagnetic spectrum of 2000–3000 MHz has been synthesized from carbon black, graphite powder, and poly vinyl acetate (PVA)-based adhesive. The material overcomes various problems that are inherent in conventional phantoms such as decomposition and deterioration due to the invasion of bacteria or mold. The absorption coefficients of the material for various concentrations of carbon and graphite are studied. A combination of 50% poly-vinyl-acetate-based adhesive, 20% carbon, and 30% graphite exhibits a high absorption coefficient, which suggests another application of the material as a good microwave absorber for the interior lining of tomographic chamber in microwave imaging. The cavity-perturbation technique is adopted to study the dielectric properties of the material.

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Phantoms that exhibit complex dielectric properties similar to low water content biological tissues over the electromagnetic spectrum of 2–3 GHz have been synthesized from carbon black powder, graphite powder and polyvinyl-acetate-based adhesive. The materials overcome various problems that are inherent in conventional phantoms such as decomposition and deterioration due to the invasion of bacteria or mold. The absorption coefficients of the materials for various compositions of carbon black and graphite powder are studied. A combination of 50% polyvinylacetate- based adhesive, 20% carbon black powder and 30% graphite powder exhibits high absorption coefficient, which suggests another application of the material as good microwave absorber for interior lining of tomographic chamber in microwave imaging. Cavity perturbation technique is adopted to study the dielectric properties of the material.

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The thesis has covered various aspects of modeling and analysis of finite mean time series with symmetric stable distributed innovations. Time series analysis based on Box and Jenkins methods are the most popular approaches where the models are linear and errors are Gaussian. We highlighted the limitations of classical time series analysis tools and explored some generalized tools and organized the approach parallel to the classical set up. In the present thesis we mainly studied the estimation and prediction of signal plus noise model. Here we assumed the signal and noise follow some models with symmetric stable innovations.We start the thesis with some motivating examples and application areas of alpha stable time series models. Classical time series analysis and corresponding theories based on finite variance models are extensively discussed in second chapter. We also surveyed the existing theories and methods correspond to infinite variance models in the same chapter. We present a linear filtering method for computing the filter weights assigned to the observation for estimating unobserved signal under general noisy environment in third chapter. Here we consider both the signal and the noise as stationary processes with infinite variance innovations. We derived semi infinite, double infinite and asymmetric signal extraction filters based on minimum dispersion criteria. Finite length filters based on Kalman-Levy filters are developed and identified the pattern of the filter weights. Simulation studies show that the proposed methods are competent enough in signal extraction for processes with infinite variance.Parameter estimation of autoregressive signals observed in a symmetric stable noise environment is discussed in fourth chapter. Here we used higher order Yule-Walker type estimation using auto-covariation function and exemplify the methods by simulation and application to Sea surface temperature data. We increased the number of Yule-Walker equations and proposed a ordinary least square estimate to the autoregressive parameters. Singularity problem of the auto-covariation matrix is addressed and derived a modified version of the Generalized Yule-Walker method using singular value decomposition.In fifth chapter of the thesis we introduced partial covariation function as a tool for stable time series analysis where covariance or partial covariance is ill defined. Asymptotic results of the partial auto-covariation is studied and its application in model identification of stable auto-regressive models are discussed. We generalize the Durbin-Levinson algorithm to include infinite variance models in terms of partial auto-covariation function and introduce a new information criteria for consistent order estimation of stable autoregressive model.In chapter six we explore the application of the techniques discussed in the previous chapter in signal processing. Frequency estimation of sinusoidal signal observed in symmetric stable noisy environment is discussed in this context. Here we introduced a parametric spectrum analysis and frequency estimate using power transfer function. Estimate of the power transfer function is obtained using the modified generalized Yule-Walker approach. Another important problem in statistical signal processing is to identify the number of sinusoidal components in an observed signal. We used a modified version of the proposed information criteria for this purpose.

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Department of Mathematics, Cochin University of Science and Technology