This master's thesis deals with the development of the application for automatic price comparison of goods. The application works on the principle that the user enters inputs as a list of products and output is a list of offers from monitored dealers for all entered products. There is possibility for the user to create his individual settings for each website or use searching on existing comparison shopping website. Target group of users are dealers, distributors and manufacturers who use the data for monitoring competitors and changes in market prices.

PhD thesis deals with the application of simulation, forecasting and optimization methods in the waste management. An introduction describes current state and outlook in the waste management in the Czech Republic. The following chapter analyzes the available data base in the field of the waste management in the Czech Republic, focusing on the specifics and problems such as variable availability of spatially and hierarchically structured, heterogeneous input data. The core work is the computational tool named Justine, which represents the balance system, ensuring consistency of values for the standalone and aggregated data, in terms of their composition and distribution in intended area and time. Development of the tool was motivated by the need to predict the production and composition of various types of waste. The application of the concept is shown in three case studies, focusing on the prognosis of hazardous waste, the forecast of production and composition of municipal solid waste and components of separated waste collection, and estimation of the waste with waste-to-energy potential, all in the Czech Republic. The outputs of the tool represent valuable inputs for the related optimization supply chain models, which are used e.g. for the design of new waste-to-energy facilities.

The aim of this diploma thesis is to get acquainted with the properties of image data and the principle of their capture. Literary research on methods of image segmentation in the area of cardiac tissue imaging and, last but not least, efforts to find methods for classification of dead cardiomyocytes and analysis of their viability. Dead cardiomyocytes were analyzed for their shape and similarity to the template created as a mean of dead cells. Another approach was the application of the method based on local binary characters and the computation of symptoms from a simple and associated histogram.

Microorganisms are all around us. Some of them even live in our body and are essential for our healthy being. Study of microbial communities based on their genetic content has become very popular with the development of new technologies, which enable easy reading of DNA or RNA. The key role of these studies is usually to characterize significant microbial patterns of an environment. However, currently used visualization tools have many drawbacks for such analyses. The subject of this thesis is to design a R/Bioconductor package for simple creation of bipartite graphs from microbial data. This type of visualization brings many advantages for microbiome analysis. Benefits of bipartite graphs are further demonstrated by analysis of main parameters affecting computer processing of microbial data.

Title: Ensemble Kalman filter on high and infinite dimensional spaces Author: Mgr. Ivan Kasanický Department: Department of Probability and Mathematical Statistics Supervisor: doc. RNDr. Daniel Hlubinka, Ph.D., Department of Probability and Mathematical Statistics Consultant: prof. RNDr. Jan Mandel, CSc., Department of Mathematical and Statistical Sciences, University of Colorado Denver Abstract: The ensemble Kalman filter (EnKF) is a recursive filter, which is used in a data assimilation to produce sequential estimates of states of a hidden dynamical system. The evolution of the system is usually governed by a set of di↵erential equations, so one concrete state of the system is, in fact, an element of an infinite dimensional space. In the presented thesis we show that the EnKF is well defined on a infinite dimensional separable Hilbert space if a data noise is a weak random variable with a covariance bounded from below. We also show that this condition is su cient for the 3DVAR and the Bayesian filtering to be well posed. Additionally, we extend the already known fact that the EnKF converges to the Kalman filter in a finite dimension, and prove that a similar statement holds even in a infinite dimension. The EnKF su↵ers from a low rank approximation of a state covariance, so a covariance localization is required in...

This text deals with the issue of identification of stakeholders in the evaluation. The concept of stakeholders is defined first, and the characteristics of the evaluation approaches are presented. Later is presented the position of the world evaluation societies on the stakeholders. There are four methods of stakeholder identification: 1) Brainstorming, 2) General list, 3) Questions and 4) The snowball method. Own research focuses on methods of identification of stakeholders in evaluations in the Czech Republic. Data sources are evaluations of OP and ROP programs. Secondary and content data analysis was used to analyse the data. The result of the research is that specific methods of stakeholder identification have not been applied in OP and ROP evaluations. Based on the results of the research, a new procedure for identification of stakeholders in the evaluation was formulated.

Satellite instruments currently provide the largest source of infor- mation to today's data assimilation (DA) systems for numerical weather predic- tion (NWP). With the development of high-resolution models, the efficient use of observations at high density is essential to improve small-scale information in the weather forecast. However, a large amount of satellite radiances has to be removed from DA by horizontal data thinning due to uncorrelated observation error assumptions. Moreover, satellite radiances include systematic errors (biases) that may be even larger than the observation signal itself, and must be properly removed prior to DA. Although the Variational Bias Correction (VarBC) scheme is widely used by global NWP centers, there are still open questions regarding its use in Limited-Area Models (LAMs). This thesis aims to tackle the obser- vation error difficulties in assimilating polar satellite radiances in the meso-scale ALADIN system. Firstly, we evaluate spatial- and inter-channel error correla- tions to enhance the positive effect of data thinning. Secondly, we study satellite radiance bias characteristics with the key aspects of the VarBC in LAMs, and we compare the different VarBC configurations with regards to forecast performance. This work is a step towards improving the...

This diploma thesis deals with the identification of factors that affect income inequality in the world. The literary overview describes the issue of income inequality, possible methods of measurement, projected factors of influence and the possibility of addressing income inequality. Statistical methods, in particular cluster, regression and panel analysis, are used to quantify and define the significance of the selected factors. The economic and technological level of the country, the education and the state of health of the population are key economic and demographic indicators. Each of these indicators, according to the results of the regression analysis, has a weak negative effect on income inequality, reducing it. The results of the panel analysis demonstrate that an indicator of the level of technology, education and the state of health of the population can be included among the major factors affecting income inequality in the world. The indicator of the economic level measured using per capita gross domestic product has proved insignificant, which means that while GDP has an impact on Gini’s coefficient, the other variables describe the relationship better.

The diploma thesis deals with the impact of euro adoption on export. Two basic channels of an impact of the adoption of the common currency are identified, namely the reduction of the exchange rate risk and the loss of an autonomous monetary policy. The main contribution of the thesis is the application of the exchange rate stability index and the index of monetary independence as variables representing the mentioned channels and the assessment of their impact on exports in the empirical analysis. The regression analysis of the panel data with fixed effects is used because of the heterogeneity of EU states. In addition to the aforementioned indices, a foreign demand and the nominal effective exchange rate are included in the models. The results indicate that the exchange rate stability index and a foreign demand have a positive and statistically significant impact on export. The empirical analysis uses monthly data for 25 countries of the European Union during the period from January 1994 to May 2017.

This master thesis is focused on design and implementation of a web application for a company to show users of this application relevant data in prearranged dashboards using visual elements, such as charts, information cards or tables, depending on the role of the logged in user in the application. The data that will be used by the application are obtained from the QI system in which they are transformed into multidimensional cubes that are automatically uploaded to Microsoft SQL Analysis Services Server.