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The Phenomenon of Architecture in One's Own Art and Pedagogical Work (Pedagogical Implications)
Gajdošíková, Pavla ; Fulková, Marie (advisor) ; Géringová, Jitka (referee) ; Zahoranský, Dušan (referee)
Pavla Gajdošíková: The Phenomenon of Architecture in One's Own Art and Pedagogical Work (Pedagogical Implications) Abstract: The dissertation looks at the perception of architecture and space in art and explores the possible uses of artistic and reflective processes in learning situations involving students of art education. It is based on ongoing public discussions regarding architecture's influence on the perception of the environment and the associated quality of life of each and every one of us. Thematically, it follows on the author's cycle of artworks titled Subjective Urbanism, which explored the subject using various artistic media. The dissertation makes use of a/r/tography, a methodology that offers a way of understanding a subject of research from three different perspectives (artist, teacher, researchers), thus enabling complementarily structured learning in "interspace." Metaphorically speaking, the subject of architecture and space is approached as an intertwining of these three identities. This also the paper's triadic structure. In the first part, the author introduces the subject at hand through her own works of art, a reflection of which formed the starting point for her subsequent inquiries. In the second part, she uses several case studies to describe three pedagogical projects aimed at...
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Software using random forest for risk prediction of heart valve surgery patients
HERMANUTZ, Georg
CASPeR - Cardiac surgery prediction tool for risk stratification of heart valve surgeries is presented. The base builds a machine learning pipeline for training a random forest classifier which predicts the mortality after a certain amount of days after the surgery was performed. The classifier also offers a list of potential risk factors through its in build feature selection. With a survival analysis the groups "high-risk" and "low-risk" are compared with each other to check for statistical difference. The tool uses "Shiny" a R package which offers a web frame work to develop data analysis visualizations for the User Interface. CASpeR is delivered as a Microsoft Windows standalone desktop application, that comes with a .exe installer and a detailed manual.
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Data Mining with Python
Šenovský, Jakub ; Bartík, Vladimír (referee) ; Zendulka, Jaroslav (advisor)
The main goal of this thesis was to get acquainted with the phases of data mining, with the support of the programming languages Python and R in the field of data mining and demonstration of their use in two case studies. The comparison of these languages in the field of data mining is also included. The data preprocessing phase and the mining algorithms for classification, prediction and clustering are described here. There are illustrated the most significant libraries for Python and R. In the first case study, work with time series was demonstrated using the ARIMA model and Neural Networks with precision verification using a Mean Square Error. In the second case study, the results of football matches are classificated using the K - Nearest Neighbors, Bayes Classifier, Random Forest and Logical Regression. The precision of the classification is displayed using Accuracy Score and Confusion Matrix. The work is concluded with the evaluation of the achived results and suggestions for the future improvement of the individual models.
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Reporting of socioeconomic data using R Markdown
Sládek, David ; Sobíšek, Lukáš (advisor) ; Procházka, Jiří (referee)
This bachelor thesis does theoretical as well as practical research in R Markdown tool. The practical part should serve as a guide for new users of this system. The description of features of this tool is shown directly at this thesis, because it is completely written in R Markdown. The second part investigates the possibility of quantification of religious belief's strength in several European countries and comparison of this belief among them. For this purpose has been used basic tools of contingency analysis. The results show different tendencies of strength of belief among some countries.
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Descriptive statistics in R with application on real data
Pirohová, Eva ; Bašta, Milan (advisor) ; Šulc, Zdeněk (referee)
The aim of this thesis is to introduce the statistical software R, its use in descriptive statistics and to explain the principle of entering commands and functions in R. In the theoretical part of the thesis the user will be given the basic information about descriptive statistics and the key principles of R software. An important part of the thesis is an illustration of functions and codes which are to be entered into a script or a command window. The practical part represents the way of applying descriptive statistics on real data by using functions and codes in R, including the corresponding types of graphs. There is always an explanation following the example. This thesis contains all the important information which those who start with basic statistical analysis and R software should know. Despite the fact that working with R may be rather complicated at the beginning, this thesis is written in such a way so that it can be read by a beginner in R and statistical analysis.
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Data Visualisation Methods in the Statistical Computational Programme R
Hanková, Monika ; Procházka, Jiří (advisor) ; Malá, Ivana (referee)
Visualisation is a key element for analysis in statistics. This thesis describes data visualisation methods in the statistical computational programme R which, thanks to add-on packages, contains several tools for plotting. Data visualisation may be much more complicated than it seems to be, the focus is aimed at the general connection between packages as well as the particular visualisation of base graphics, ggplot2 and lattice package. These packages are built based on the traditional graphical model in R, grammar of graphics and trellis plotting. The interactive shiny app provides an overall view about how the data are visualised by each package.
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Statistical methods in stylometry
Dupal, Pavel ; Kaspříková, Nikola (advisor) ; Šulc, Zdeněk (referee)
The aim of this thesis is to provide an overview of some of the commonly used methods in the area of authorship attribution (stylometry). The text begins with a recap of history from the end of the 19th century to present time and the required terminology from the field of text mining is presented and explained. What follows is a list of selected methods from the field of multidimensional statistics (principal components analysis, cluster analysis) and machine learning (Support Vector Machines, Naive Bayes) and their application as pertains to stylometrical problems, including several methods created specifically for use in this field (bootstrap consensus tree, contrast analysis). Finally these same methods are applied to a practical problem of authorship verification based on a corpus bulit from the works of four internet writers.
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Limited and censored explained variables
Kostka, Rudolf ; Bejda, Přemysl (advisor) ; Komárek, Arnošt (referee)
In this thesis at first we focus on theory of dealing with limited and censored explained variables. We begin with discrete variables and show the theory of binary and categorical variables. Later we explain utility of models logit and probit and demonstrate it at a practical example. We also provide a comparison of these two models. Third chapter deals with limited explained variables, specifically censored, truncated and variables representing some time to event. In the last chapter we describe some functions, which might be used to plot a graph of a survival function using softwares R or Mathematica. Some options in Excel are also mentioned, but they are very limited. Described functions are then demonstrated in use at a practical example with our gained data. Powered by TCPDF (www.tcpdf.org)
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Limited and censored explained variables
Kostka, Rudolf ; Bejda, Přemysl (advisor) ; Komárek, Arnošt (referee)
In this thesis at first we focus on theory of dealing with limited and censored explained variables. We begin with discrete variables and show the theory of binary variables. Later we explain utility of models logit and probit and demonstrate it at a practical example. Third chapter deals with limited explained variables, specifically censored and variables representing some time to event. We show how to work with the most used parametric models and Kaplan-Meier estimator. In the last chapter we describe some functions, which might be used to plot a graph of a survival function using softwares R or Mathematica. Some options in Excel are also mentioned, but they are very limited. Described functions are then demonstrated in use at a practical example with our gained data. Powered by TCPDF (www.tcpdf.org)
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