The thesis analyzes the accuracy of the multi-step inflation forecast using se-lected methods of machine learning through inflationary factors in the Visegrad group countries. The methods that were applied in the work analysis are the re-gression of tree methods and the algorithm method to the k-nearest neighbors. Based on the regression tree method, we are able to identify factors that are most prominent in price level development. The output of the analysis consists of 8 models, the suitability and accuracy of which are discussed. The results of the em-pirical analysis are compared with the assumptions that were presented before the analysis has begun. This suggests that methods are not suitable for multi-step inflation prediction.

This thesis formulates and solves an economic decision problem of the acquisi- tion of costly information in data-driven decision making. The thesis assumes an agent predicting a random variable utilizing several costly explanatory vari- ables. Prior to the decision making, the agent learns about the relationship between the random variables utilizing its past realizations. During the deci- sion making, the agent decides what costly variables to acquire and predicts using the acquired variables. The agent's utility consists of the correctness of the prediction and the costs of the acquired variables. To solve the decision problem, the thesis divides the decision process into two parts: acquisition of variables and prediction using the acquired variables. For the prediction, the thesis presents a novel approach for training a single predictive model accepting any combination of acquired variables. For the acquisition, the thesis presents two novel methods using supervised machine learning models: a backward es- timation of the expected utility of each variable and a greedy acquisition of variables based on a myopic increase in the expected utility of variables. Next, the thesis formulates the decision problem as a Markov decision process which allows approximating the optimal acquisition via deep...

The diploma thesis deals with the evaluation of hydrological drought in the Bouřlivec and Loučenský stream basins, located in the northwest of the Czech Republic in the Ore Mountains. Available hydrological and climatological data series from two limnographic and four climatological stations were used to characterize the hydrological drought. The intensity of the occurrence of hydrological drought in the stream basins of interest was assessed using the method of threshold values and the method of insufficient volumes. According to the results of the work, the hydrological year 2020 was marked as extremely low in water on both monitored profiles, which points to the accumulating causes of drought from previous years. In terms of hydrological drought, the year 2018 was also significant. The diploma thesis also aims to detect trends in data series of precipitation, air temperature and inflow into the Všechlapy reservoir using the Mann-Kendall test. The results of statistical testing of the trend point to an increasing trend of air temperature and a decreasing trend of the inflow into the Všechlapy reservoir. A significant trend in the precipitation data series was not confirmed. Trend testing was preceded by an assessment of the homogeneity of the available data sets. Last but not least, emphasis is...

This thesis investigates different aspects of children's computer game world. In the opening chapters are described available computer games for kids, which are split into groups. After that follows theoretical introduction to the problems of sociological research and advantages of using computer and Internet for it. On the basis of observation are introduced three types of applications for investigation of children's interest and abilities in computer games and parents opinions. Two of them were already used for investigation within this thesis. Thesis also presents results of realized survey.

This project was originated by K2 atmitec Brno s.r.o. company. The result is data mining module in K2 information system environment. Engineered data module implements association analysis over the data of K2 information system data warehouse. Analyzed data contains information about sales filed in K2 information system. Module is implementing consumer basket analysis.

Title: IT Security in Biomedicine Author: Ing. Anna Schlenker Supervisor: Ing. Milan Šárek, CSc. Abstract: The aim of this work is to propose a solution to the biomedical data security strategy. The work provides an overview of the most commonly used biometric methods designed to identify or authenticate users. From these methods, the keystroke dynamics was chosen and used in the application solution. The reliability of this method has been tested by classical and modern classification methods. The greatest benefit of the work is the use of the created application in combination with the measurement using integrated electromyography to objectify the evaluation of the work related to keyboard typing in terms of local muscle load. Keywords: Biometrics, Data Security, Keystroke Dynamics, Local Muscle Load

The diploma thesis deals with synthetic data, selected approaches to their generation together with a practical task of data generation. The goal of the thesis is to describe the selected approaches to data generation, capture their key advantages and disadvantages and compare the individual approaches to each other. The practical part of the thesis describes generation of synthetic data for teaching knowledge discovery using databases. The thesis includes a basic description of synthetic data and thoroughly explains the process of their generation. The approaches selected for further examination are random data generation, the statistical approach, data generation languages and the ReverseMiner tool. The thesis also describes the practical usage of synthetic data and the suitability of each approach for certain purposes. Within this thesis, educational data Hotel SD were created using the ReverseMiner tool. The data contain relations discoverable with SD (set-difference) GUHA-procedures.

The work deals with the measurement and management in power. Provides an introduction to the problems of remote meter reading, management, and describes the current situation in the field of modern technologies Smart metering and Smart grids. It also analyzed the issue of collection of networks and data collection from a large number of meters over a wide area. For the purpose of data transmission are described GPRS, PLC, DSL, ... Further, there are given options to streamline communication. This area is used hierarchical aggregation. Using k-means algorithm is a program designed to calculate the number of concentrators and their location in the group of meters. The finished program is written in Java. It has a graphical interface and shows how the calculation is conducted. To verify the results of the optimization program is given simulation model in OPNET Modeler tool. Audited results are described in the conclusion and can deduce that using the optimization program is to streamline communications.

The work deals with automatic summarization of documents in HTML format. As a language of web documents, Czech language has been chosen. The project is focused on algorithms of text summarization. The work also includes document preprocessing for summarization and conversion of text into representation suitable for summarization algorithms. General text mining is also briefly discussed but the project is mainly focused on the automatic document summarization. Two simple summarization algorithms are introduced. Then, the main attention is paid to an advanced algorithm that uses latent semantic analysis. Result of the work is a design and implementation of summarization module for Python language. Final part of the work contains evaluation of summaries generated by implemented summarization methods and their subjective comparison of the author.

This thesis summarizes the information retrieval theory, the relational model basic and focuses on the data indexing in relational database systems. The thesis focuses on multimedia data searching. It includes description of automatic multimedia data content extraction and multimedia data indexing. Practical part discusses design and solution implementation for improving query effectivity for multidimensional vector similarity which describes multimedia data. Thesis final part discusses experiments with this solution.