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Geographical aspects of electoral support for the populist radical right in Czechia
Cihlář, Pavel ; Lepič, Martin (advisor) ; Suchánek, Jonáš (referee)
The populist radical right parties, along with their political successes in the 21st century, have also gained considerable academic interest. Given the significant geographic variation in support of these parties, the attention is also turning to the geographical aspects of this phenomenon. These aspects are the focus of this thesis. It aims to map the intensity and shape of the clustering of electoral support for the Freedom and Direct Democracy (SPD) movement in the 2017 and 2021 parliamentary elections and to further examine geographical differences in the explanatory factors of this electoral support. The thesis uses the method of spatial autocorrelation and multiscale geographically weighted regression to achieve these objectives. The statistical units are the municipalities of the Czech Republic, and the explanatory variables are socio-demographic indicators, conceptualized according to three categories of explanatory support for the populist radical right: economic grievances, cultural grievances, and anomie. Particular attention is paid to the theory of anomie, based on theories of mass society and social capital. Earlier analyses of this theory have led to ambivalent results and this thesis tests a potential explanation for this in terms of the geographical non-stationarity of the...
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Market segmentation using statistical methods
Bystřická, Michaela ; Marciánová, Pavla (referee) ; Schüller, David (advisor)
The thesis is focused on the segmentation of customers of selected summer swimming pool. The first part of the thesis is devoted to the theoretical concept of the chosen issue. In the analytical part, a summer swimming pool is presented and selected analyses are carried out. The analytical part also includes a questionnaire survey. In the last part of the thesis, measures are proposed that would lead to an increase in the level of services for the selected customer segment.
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Application of Mathematical and Statistical Methods in Company Management
Zezula, Lukáš ; Šustrová, Tereza (referee) ; Novotná, Veronika (advisor)
This thesis discusses the analysis of logistics costs for a company operating a network of vending machines and the subsequent minimization of the established costs by changing the locations and number of supply depots. A function reflecting the dependence of transport, warehousing, and inventory holding costs on the number and locations of depots is derived. The coefficients of this objective function are identified based on data provided by the analyzed company. Optimization of the locations and number of supply depots is performed using the Nelder and Mead iterative algorithm in combination with agglomerative clustering. The proposed approach to optimizing the logistics network is described from a mathematical-statistical and implementation perspective. Special attention is paid to finding optimal routes between supply depots and vending machines using geographic software, which also allows for measuring the route length and the time required to cover the obtained distance. The thesis then presents six proposals for reorganizing the logistics network, reflecting the optimal distribution of supply depots at their different numbers. Various shapes of the inventory holding costs are also considered, and their impact on the optimal number and locations of supply depots is discussed.
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Comparing of Clustering Algorithms
Jakšík, Aleš ; Rozman, Jaroslav (referee) ; Zbořil, František (advisor)
This bachelor thesis deals with the comparison of K-means, K-medoids and Fuzzy C-means algorithms. In the first part, it discusses the types of distance measurements, clustering evaluation options and categorization of clustering methods. In the second part, it presents a web application for comparing the selected methods and in the third part it discusses the comparison and evaluation of the results and statistics from running the clustering algorithms in the demonstration application.
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Comparison of road tax regulations in the Czech Republic and neighboring countries
PRÁŠKOVÁ, Vendula
The work focuses on comparing the adjustment of road and similar taxes in the Czech Republic and neighbouring states respectively. It describes the road tax treatment in the Czech Republic, the reasons for its introduction and the development of this tax since 1992, through relevant tax laws and regulations. Furthermore, adjustments to similar taxes on Germany, Poland, Austria and Slovakia are described in detail here. In the next part of the thesis, the criteria for cluster analysis are discussed, namely the share of road tax in the tax mix, the share of road tax in GDP and the tax burden of road tax per capita, for lower risk, all these data are taken from EUROSTAT and OECD In US dollars (USD), data on the number of motor vehicles in the region is added to expand the issue. A clustered analysis was carried out on the basis of the values of these indicators for 2012, 2021 and 2022. The result of this analysis is three dendrograms, each representing one of the years studied. Dendrograms provide a visual representation of the cluster structure and allow for the interpretation of relationships.
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ECG Cluster Analysis
Pospíšil, David ; Kozumplík, Jiří (referee) ; Klimek, Martin (advisor)
This diploma thesis deals with the use of some methods of cluster analysis on the ECG signal in order to sort QRS complexes according to their morphology to normal and abnormal. It is used agglomerative hierarchical clustering and non-hierarchical method K – Means for which an application in Mathworks MATLAB programming equipment was developed. The first part deals with the theory of the ECG signal and cluster analysis, and then the second is the design, implementation and evaluation of the results of the usage of developed software on the ECG signal for the automatic division of QRS complexes into clusters.
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Analysis of AVG signals
Musil, Václav ; Sekora, Jiří (referee) ; Rozman, Jiří (advisor)
The presented thesis discusses the basic analysis methods of arteriovelocitograms. The core of this work rests in classification of signals and contribution to possibilities of noninvasive diagnostic methods for evaluation patients with peripheral ischemic occlusive arterial disease. The classification employs multivariate statistical methods and principles of neural networks. The data processing works with an angiographic verified set of arteriovelocitogram dates. The digital subtraction angiography classified them into 3 separable classes in dependence on degree of vascular stenosis. Classification AVG signals are represented in the program by the 6 parameters that are measured on 3 different places on each patient’s leg. Evaluation of disease appeared to be a comprehensive approach at signals acquired from whole patient’s leg. The sensitivity of clustering method compared with angiography is between 82.75 % and 90.90 %, specificity between 80.66 % and 88.88 %. Using neural networks sensitivity is in range of 79.06 % and 96.87 %, specificity is in range of 73.07 % and 91.30 %.
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Analysis of AVG signal
Matušek, Adam ; Kozumplík, Jiří (referee) ; Rozman, Jiří (advisor)
Bachelor´s thesis deals with analysis of AVG signal (arteriovelocitogram). Measured data predicate about speed and caracteristic of blood flow in human arteria. Signal is taken by ultrasound mesure. We use reflection of mechanic wave from moving objets followed by a chase of frequence. This fenomen is called Doppler effect. When we know analysis results we can diagnostic the existence and phase of ischemic desease. The clasification of the dates was made by methods of cluster analysis. Statistic algorithm was realised in programing world MATLAB.
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Methods for Clustering Data
Pohlídal, Antonín ; Burgetová, Ivana (referee) ; Bartík, Vladimír (advisor)
This bachelor's thesis deals with hierarchical clustering methods with a focus on implementation of agglomerative hierarchical clustering method and its comparison with the DENCLUE method. First of all, various methods are described with emphasis on hierarchical clustering methods. Further, there is an implementation of the selected method, using the Java programming language and MySQL database. The last part contains a comparison with the implementation of DENCLUE method, implemented by Mr. Bc. Radim Kapavík.
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Data Mining on Oracle Database Server and MS SQL Server
Opršal, Martin ; Chmelař, Petr (referee) ; Stryka, Lukáš (advisor)
This bachelor's thesis deals with issue of knowledge discovery in databases. This document is focused in getting rules from relation databases based on Microsoft SQL server or Oracle Data mining server. The practical part of this document is about design applications that run on both servers. These applications are programmed in asp.NET, C# for Microsoft SQL server and Java for Oracle server.
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