Adaptive Bayesian sampling with application to 'bubbles'

The project consists in applying the Markov Random Fields (MRF) theory in order to make inference in spatial graphical models. We are interested in solving the problem of the use of information in certain categorization problems where facial image information is revealed by a certain number of trials and the observer facing an image tries to classify the sampled information. MRFs have the purpose to render information sampling less exhaustive: they allow to identify significantly informative image regions which are used for further sampling and to exclude from sampling those image regions which contribute at least to solving our categorization problem. Denoting the observed lattice of data values y and the underlying latent/hidden field x, the problem ofinterest can be formulated in the following way: conditioned on y, we aim to make inference about all unknown parameters, that is, we aim to evaluate the posterior distribution pi(x|y) which is proportional to the product of the likelihood L(y|x) and the prior distribution pi(x). Generating samples from the posterior by running the Markov Chain Monte Carlo (MCMC), we compute the posterior expectation/posterior probability map of lattice x given the observed data y. Calculated posterior probability map values comprise the information on importance of certain sampling regions. Based on this information, we can adopt the sampling strategy sequentially, thereby minimizing the number of sampling trials. The project contains certain simulated experiments to compare the exhaustive and the adaptive sampling approaches. Thereby, images with incorporated spatial dependence are used. We conclude that the adaptive sampling algorithm which uses MRFs performs better than the exhaustive sampling algorithm. This results in a lower number of trials and a smaller classification error

Inhomogeneous Dependency Modelling with Time Varying Copulae

Measuring dependence in a multivariate time series is tantamount to modelling its dynamic structure in space and time. In the context of a multivariate normally distributed time series, the evolution of the covariance (or correlation) matrix over time describes this dynamic. A wide variety of applications, though, requires a modelling framework different from the multivariate normal. In risk management the non-normal behaviour of most financial time series calls for nonlinear (i.e. non-gaussian) dependency. The correct modelling of non-gaussian dependencies is therefore a key issue in the analysis of multivariate time series. In this paper we use copulae functions with adaptively estimated time varying parameters for modelling the distribution of returns, free from the usual normality assumptions. Further, we apply copulae to estimation of Value-at-Risk (VaR) of a portfolio and show its better performance over the RiskMetrics approach, a widely used methodology for VaR estimation.Value-at-Risk, time varying copula, adaptive estimation, nonparametric estimation.

SFB 649 Discussion Paper 2006-075 Inhomogeneous Dependency Modelling with Time Varying

Measuring dependence in a multivariate time series is tantamount to modelling its dynamic structure in space and time. In the context of a multivariate normally distributed time series, the evolution of the covariance (or correlation) matrix over time describes this dynamic. A wide variety of applications, though, requires a modelling framework different from the multivariate normal. In risk management the non-normal behaviour of most financial time series calls for nonlinear (i.e. non-gaussian) dependency. The correct modelling of non-gaussian dependencies is therefore a key issue in the analysis of multivariate time series. In this paper we use copulae functions with adaptively estimated time varying parameters for modelling the distribution of returns, free from the usual normality assumptions. Further, we apply copulae to estimation of Value-at-Risk (VaR) of a portfolio and show its better performance over the RiskMetrics approach, a widely used methodology for VaR estimation. JEL classification: C 1

Phase Equilibria in Ternary System Na₂MoO₄-KF-KI

Методом дифференциального термического анализа исследована трехкомпонентная система, определены температуры плавления и составы тройных нонвариантных точек, описаны фазовые равновесия для разлиных элементов треугольника.The three-component system has been examined by the differential thermal analysis. As a result we have defined melting point temperature, the compositions and the enthalpy of melting ternary eutectic mixtures. We also have described the non and invariant equilibria

Prediction and Studied of the Phase Complex of NaF-NaI-Na2WO4 System

Проведено прогнозирование фазового комплекса системы NaF-NaI-Na2WO4 на основе анализа характера ликвидусов в трехкомпонентных системах NaF-NaГ-Na2WO4 (Г - cl, Br, I). Предложена методика прогнозирования характеристик тройной эвтектики на основании изучения рядов однотипных двух- и трехкомпонентных систем, сравнительного анализа их характера ликвидуса, а также построения ряда зависимостей. Методом дифференциального термического анализа исследована трехкомпонентная система NaF-NaI-Na2WO4, определены температура плавления, состав тройной эвтектической смеси, описаны фазовые равновесия.Prediction of the phase complex of system NaF-NaI-Na2WO4 has been holded on the basis of phase equilibrium in the row of ternary systems NaF-NaHa -Na2WO4 (Hal - Cl, Br, I). We have methods for prediction characteristic of a ternary eutectic on basis of series exploration the single-type twocomponent and ternary system, comparative research its liquidus character, as well as building a series of dependencies. The three-component system NaF-NaI-Na2WO4 has been studied by the differential thermal analysis. As a result we have defined melting point temperature, and the compositions ternary eutectic mixture. We also have described the non and invariant equilibria

Prediction and Studied of the Phase Complex of NaF-NaI-Na2WO4 System

Проведено прогнозирование фазового комплекса системы NaF-NaI-Na2WO4 на основе анализа характера ликвидусов в трехкомпонентных системах NaF-NaГ-Na2WO4 (Г - cl, Br, I). Предложена методика прогнозирования характеристик тройной эвтектики на основании изучения рядов однотипных двух- и трехкомпонентных систем, сравнительного анализа их характера ликвидуса, а также построения ряда зависимостей. Методом дифференциального термического анализа исследована трехкомпонентная система NaF-NaI-Na2WO4, определены температура плавления, состав тройной эвтектической смеси, описаны фазовые равновесия.Prediction of the phase complex of system NaF-NaI-Na2WO4 has been holded on the basis of phase equilibrium in the row of ternary systems NaF-NaHa -Na2WO4 (Hal - Cl, Br, I). We have methods for prediction characteristic of a ternary eutectic on basis of series exploration the single-type twocomponent and ternary system, comparative research its liquidus character, as well as building a series of dependencies. The three-component system NaF-NaI-Na2WO4 has been studied by the differential thermal analysis. As a result we have defined melting point temperature, and the compositions ternary eutectic mixture. We also have described the non and invariant equilibria

Phase Equilibria in Ternary System Na₂MoO₄-KF-KI

Методом дифференциального термического анализа исследована трехкомпонентная система, определены температуры плавления и составы тройных нонвариантных точек, описаны фазовые равновесия для разлиных элементов треугольника.The three-component system has been examined by the differential thermal analysis. As a result we have defined melting point temperature, the compositions and the enthalpy of melting ternary eutectic mixtures. We also have described the non and invariant equilibria

Nanocomposite Co₃O₄-ZnO Thin Films for Photoconductivity Sensors

Thin nanocomposite films based on zinc oxide (ZnO) added with cobalt oxide (Co3O4) were synthesized by solid-phase pyrolysis. According to XRD, the films consist of a ZnO wurtzite phase and a cubic structure of Co3O4 spinel. The crystallite sizes in the films increased from 18 nm to 24 nm with growing annealing temperature and Co3O4 concentration. Optical and X-ray photoelectron spectroscopy data revealed that enhancing the Co3O4 concentration leads to a change in the optical absorption spectrum and the appearance of allowed transitions in the material. Electrophysical measurements showed that Co3O4-ZnO films have a resistivity up to 3 × 104 Ohm∙cm and a semiconductor conductivity close to intrinsic. With advancing the Co3O4 concentration, the mobility of the charge carriers was found to increase by almost four times. The photosensors based on the 10Co-90Zn film exhibited a maximum normalized photoresponse when exposed to radiation with wavelengths of 400 nm and 660 nm. It was found that the same film has a minimum response time of ca. 26.2 ms upon exposure to radiation of 660 nm wavelength. The photosensors based on the 3Co-97Zn film have a minimum response time of ca. 58.3 ms versus the radiation of 400 nm wavelength. Thus, the Co3O4 content was found to be an effective impurity to tune the photosensitivity of radiation sensors based on Co3O4-ZnO films in the wavelength range of 400–660 nm