971 resultados para Non linear optical phenomina,


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In this paper we examine the equilibrium states of periodic finite amplitude flow in a horizontal channel with differential heating between the two rigid boundaries. The solutions to the Navier-Stokes equations are obtained by means of a perturbation method for evaluating the Landau coefficients and through a Newton-Raphson iterative method that results from the Fourier expansion of the solutions that bifurcate above the linear stability threshold of infini- tesimal disturbances. The results obtained from these two different methods of evaluating the convective flow are compared in the neighbourhood of the critical Rayleigh number. We find that for small Prandtl numbers the discrepancy of the two methods is noticeable.

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Exploratory analysis of data seeks to find common patterns to gain insights into the structure and distribution of the data. In geochemistry it is a valuable means to gain insights into the complicated processes making up a petroleum system. Typically linear visualisation methods like principal components analysis, linked plots, or brushing are used. These methods can not directly be employed when dealing with missing data and they struggle to capture global non-linear structures in the data, however they can do so locally. This thesis discusses a complementary approach based on a non-linear probabilistic model. The generative topographic mapping (GTM) enables the visualisation of the effects of very many variables on a single plot, which is able to incorporate more structure than a two dimensional principal components plot. The model can deal with uncertainty, missing data and allows for the exploration of the non-linear structure in the data. In this thesis a novel approach to initialise the GTM with arbitrary projections is developed. This makes it possible to combine GTM with algorithms like Isomap and fit complex non-linear structure like the Swiss-roll. Another novel extension is the incorporation of prior knowledge about the structure of the covariance matrix. This extension greatly enhances the modelling capabilities of the algorithm resulting in better fit to the data and better imputation capabilities for missing data. Additionally an extensive benchmark study of the missing data imputation capabilities of GTM is performed. Further a novel approach, based on missing data, will be introduced to benchmark the fit of probabilistic visualisation algorithms on unlabelled data. Finally the work is complemented by evaluating the algorithms on real-life datasets from geochemical projects.

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Exploratory analysis of petroleum geochemical data seeks to find common patterns to help distinguish between different source rocks, oils and gases, and to explain their source, maturity and any intra-reservoir alteration. However, at the outset, one is typically faced with (a) a large matrix of samples, each with a range of molecular and isotopic properties, (b) a spatially and temporally unrepresentative sampling pattern, (c) noisy data and (d) often, a large number of missing values. This inhibits analysis using conventional statistical methods. Typically, visualisation methods like principal components analysis are used, but these methods are not easily able to deal with missing data nor can they capture non-linear structure in the data. One approach to discovering complex, non-linear structure in the data is through the use of linked plots, or brushing, while ignoring the missing data. In this paper we introduce a complementary approach based on a non-linear probabilistic model. Generative topographic mapping enables the visualisation of the effects of very many variables on a single plot, while also dealing with missing data. We show how using generative topographic mapping also provides an optimal method with which to replace missing values in two geochemical datasets, particularly where a large proportion of the data is missing.

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For a Switched Reluctance Motor (SRM), the flux linkage characteristic is the most basic magnetic characteristic, and many other quantities, including the incremental inductance, back emf, and electromagnetic torque can be determined indirectly from it. In this paper, two methods of measuring the flux linkage profile of an SRM from the phase winding voltage and current measurements, with and without rotor locking devices, are presented. Torque, incremental inductance and back emf characteristics of the SRM are then obtained from the flux linkage measurements. The torque of the SRM is also measured directly as a comparison, and the closeness of the calculated and directly measured torque curves suggests the validity of the method to obtain the SRM torque, incremental inductance and back emf profiles from the flux linkage measurements. © 2013 IEEE.

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DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT

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DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT

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Background: A new commercially available device (IOLMaster, Zeiss Instruments) provides high resolution non-contact measurements of axial length (using partial coherent interferometry), anterior chamber depth, and corneal radius (using image analysis). The study evaluates the validity and repeatability of these measurements and compares the findings with those obtained from instrumentation currently used in clinical practice. Method: Measurements were taken on 52 subjects (104 eyes) aged 18-40 years with a range of mean spherical refractive error from +7.0 D to -9.50 D. IOLMaster measurements of anterior chamber depth and axial length were compared with A-scan applanation ultrasonography (Storz Omega) and those for corneal radius with a Javal-Schiötz keratometer (Topcon) and an EyeSys corneal videokeratoscope. Results: Axial length: the difference between IOLMaster and ultrasound measures was insignificant (0.02 (SD 0.32) mm, p = 0.47) with no bias across the range sampled (22.40-27.99 mm). Anterior chamber depth: significantly shorter depths than ultrasound were found with the IOLMaster (-0.06 (0.25) mm, p <0.02) with no bias across the range sampled (2.85-4.40 mm). Corneal radius: IOLMaster measurements matched more closely those of the keratometer than those of the videokeratoscope (mean difference -0.03 v -0.06 mm respectively), but were more variable (95% confidence 0.13 v 0.07 mm). The repeatability of all the above IOLMaster biometric measures was found to be of a high order with no significant bias across the measurement ranges sampled. Conclusions: The validity and repeatability of measurements provided by the IOLMaster will augment future studies in ocular biometry.

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We present some results on the formation of singularities for C^1 - solutions of the quasi-linear N × N strictly hyperbolic system Ut + A(U )Ux = 0 in [0, +∞) × Rx . Under certain weak non-linearity conditions (weaker than genuine non-linearity), we prove that the first order derivative of the solution blows-up in finite time.

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The paper presents a new network-flow interpretation of Łukasiewicz’s logic based on models with an increased effectiveness. The obtained results show that the presented network-flow models principally may work for multivalue logics with more than three states of the variables i.e. with a finite set of states in the interval from 0 to 1. The described models give the opportunity to formulate various logical functions. If the results from a given model that are contained in the obtained values of the arc flow functions are used as input data for other models then it is possible in Łukasiewicz’s logic to interpret successfully other sophisticated logical structures. The obtained models allow a research of Łukasiewicz’s logic with specific effective methods of the network-flow programming. It is possible successfully to use the specific peculiarities and the results pertaining to the function ‘traffic capacity of the network arcs’. Based on the introduced network-flow approach it is possible to interpret other multivalue logics – of E.Post, of L.Brauer, of Kolmogorov, etc.

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Mathematics Subject Classification: 26A33, 74B20, 74D10, 74L15