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Exploratory Analysis of Big Data in "jmenomesto"
Trampeška, Václav ; Plchot, Oldřich (referee) ; Landini, Federico Nicolás (advisor)
Tato práce se zabývá analýzou databáze online hry Jméno, město. V této hře mají hráči za úkol adekvátně odpovídat na zadané kategorie odpovědmi začínající na zadané písmeno. Práce analyzuje evoluci chování hráčů během existence hry a chování hráčů v různých zemích a kulturách v rámci stejného i jiného jazyka na základě popularity různých odpovědí. Pro zjednodušení vykonávání těchto analýz byla vyvinuta webová aplikace umožňující snadnou kolekci a vizualizaci dat v grafech bez nutnosti znalosti databázové struktury a dotazovacího jazyka. Výsledky navržených analyzačních metod jsou porovnávány s daty služby Google Trends za účelem zjištění podobností mezi daty sledovanými ve hře a internetovým vyhledáváním. Z toho porovnání vyplývá, že navržené metody mohou dávat smysluplné výsledky a databáze tedy může být vhodnou pro vykonávání dalších konkrétně zaměřených analýz. Práce dále, i na základě výsledků analýz, navrhuje změny pro zlepšení hry v rámci hráčského prožitku a výdělečnosti.
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Adekvátnost informací Česká národní banky při zajišťování finanční stability
Le Viet, Cuong
The bachelor thesis deals with the adequacy of the information of the Czech National Bank in fulfilling its basic functions with a focus on ensuring financial stability. The work is based on information that individual central banks publish on their official websites. In order to meet the main goal of this thesis, we have defined the term "financial stability" and have formulated important information to ensure financial stability. In the last step, we chose the method of comparing the methodology of data collection and data range with central banks of the Czech Republic, Eurozone, USA, Great Britain and Japan. The benefit of this work is the evaluation of the current data collection and data type at the Czech National Bank. At the same time, it provides insight into new opportunities in data collection and data type and use in the direction of ensuring financial stability.
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Big Data Processing in Industry 4.0
Trubka, Jakub ; Fajčík, Martin (referee) ; Smrž, Pavel (advisor)
This thesis deals with collecting, processing, and storing big data obtained from monitoring industry machines. The designed and implemented system focuses on extensibility and scalability attributes of the realised solution. The survey part of the text briefly describes existing solutions and discusses collecting and processing big industrial data. A special attention is also paid to the big data storage technology. The crucial part of the thesis then refers to the design and realisation of the system and its individual components, as well as its testing and final evaluation.
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Information and Communication Technology and Brexit Referendum
Šindelka, Dan ; Sedláček, Pavel (referee) ; Froehling, Kenneth (advisor)
Cílem této práce je popsat informační a komunikační technologie, které byly použity během Referenda o členství Spojeného království v Evropské unii 2016. Tato práce také poskytuje popis referend ve Spojeném království, následně jsou popsány informační a komunikační technologie. Účel firmy AggregateIQ v Referendu členství Spojeného království v Evropské unii 2016 je vysvětlen. Je popsána kombinace velkých dat a psychografik, dále je popsána role této kombinace na Referendum o členství Spojeného království v Evropské unii 2016. Kromě toho je ještě diskutován možný následek informačních a komunikačních technologií na pozdější demokratické volby.
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Web Interface for a Database of Events
Hanzlík, Tomáš ; Křivka, Zbyněk (referee) ; Burget, Radek (advisor)
This work includes the design and implementation of a web application that serves as an interface between users and data aggregated from social networks. In the web interface, an emphasis is placed on displaying large amounts of data and browsing through filters. It consists of the JavaScript client part written in Vue.js and Nuxt.js and the server part of the Django REST framework that serves as a data source.
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Big data visualization
Lehončák, Michal ; Pelikán, Josef (advisor) ; Horáček, Jan (referee)
Nowadays, data are an integral part of our lives. Their volume is growing every day, and it often prevents us from understanding what these data means. The object of this thesis is to develop an application for large dataset analysis and visualization. Thesis also explores statistical methods used to reduce volume and dimensionality of data and implements selected algorithms from this field. Another goal is to explore the possibilities of modern graphics cards, as their performance increases every year. The visualization should use a graphics processor with data are shown as points in point- cloud in 3D space and user should be able to browse this data interactively.
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Analytical methods for measurement error estimation in survey data
Chylíková, Johana ; Vinopal, Jiří (advisor) ; Kreidl, Martin (referee) ; Buriánek, Jiří (referee)
Analytical methods for measurement error estimation in survey data This dissertation aims at the domain of measurement error in social science survey data. To conceptualize and estimate measurement errors it employs the analytical and theoretical framework that stems from the analytical method of structural equation modeling (SEM) and Classical Test Theory (CTT), extended with the component of the systematic measurement error. This thesis has two goals that may contribute to development and extension of Czech social science methodology. The first goal is to illustrate methods of measurement error estimation, which has not been used for analysis of Czech data yet, and to point out to some problematical aspects of these methods. The second goal is to employ presented methods to obtain new findings regarding the quality of data from Czech surveys. The dissertation presents three empirical studies, each of which uses one of the methods defined within the presented theoretical and analytical framework. First study presents an analysis of reliability of measurement with the Quasi Simplex Model (QSM). It illustrates how to use the model and brings optimistic results regarding the reliability of the Czech EU SILC panel data. In the second study the confirmatory factor analysis model, operationally called...
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Transformation of journalistic practices relating to advent of data journalism
Ďuríčková, Monika ; Dvořák, Tomáš (advisor) ; Nečas, Vlastimil (referee)
The diploma thesis titled Transformation of Journalistic Practices Relating to Advent of Data Journalism concerns the current situation in Czech data journalism and its devel- opment. It examines how the newsroom, the journalists and the readers cope with new technology, big data and the related advent of data journalism. The theoretical part of the text explains the relationship between classical journalism and data-driven journal- ism and compares the so-called "narrative" and "interactive" approaches as forms of data-driven journalism. Further it gives a deeper understanding of the relation between data journalism and the new concept of objectivity and it deals with the cultural, social and technical preconditions of data journalism. The thesis also describes the historical aspects of the topic comparing computer-assisted reporting to current practice. Sub- sequent chapters deal with the visualizations, infographics, amateur data journalism and open data which all play a key role in data-driven journalism. The practical part intro- duces the Czech data team. It was originally established within the publishing house Economia and then moved to the office of Czech Radio (Český rozhlas). The final parts discuss the cooperation model of the Czech data team, the use of visualization in their projects,...
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Mathematical analysis of equations describing the flow of compressible heat conducting fluids
Axmann, Šimon ; Pokorný, Milan (advisor) ; Feireisl, Eduard (referee) ; Novotný, Antonín (referee)
Title: Mathematical analysis of equations describing the flow of compressible heat conducting fluids Author: Šimon Axmann Department: Mathematical Institute of Charles University Supervisor: doc. Mgr. Milan Pokorný, Ph.D., Mathematical Institute of Charles University Abstract: The present thesis is devoted to the mathematical analysis of equa- tions describing the flow of viscous compressible newtonian fluid in various time regimes. In particular, we present existence results for three problems arising as special cases of a general model derived in the introductory part. The first chap- ter deals with time-periodic solutions to the full Navier-Stokes-Fourier system for heat-conducting fluid. The second chapter contains the proof of existence of steady solutions to a system arising from phase field model for two-phase com- pressible fluid. Finally, in the last section we study steady strong solutions to the Navier-Stokes equations under the additional assumption that the fluid is suffi- ciently dense. For each problem a different concept of the solution is considered, on the other hand in all cases an essential role is played by the crucial quantity effective viscous flux. Keywords: compressible Navier-Stokes system; weak solution; entropy variational solution; large data
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High-Performance Analytics (HPA)
Soukup, Petr ; Pour, Jan (advisor) ; Novotný, Ota (referee)
The aim of the thesis on the topic of High-Performance Analytics is to gain a structured overview of solutions of high performance methods for data analysis. The thesis introduction concerns with definitions of primary and secondary data analysis, and with the primary systems which are not appropriate for analytical data analysis. The usage of mobile devices, modern information technologies and other factors caused a rapid change of the character of data. The major part of this thesis is devoted particularly to the historical turn in the new approaches towards analytical data analysis, which was caused by Big Data, a very frequent term these days. Towards the end of the thesis there are discussed the system sources which greatly participate in the new approaches to the analytical data analysis as well as in the technological solutions of High Performance Analytics themselves. The second, practical part of the thesis is aimed at a comparison of the performance in conventional methods for data analysis and in one of the high performance methods of High Performance Analytics (more precisely, with In-Memory Analytics). Comparison of individual solutions is performed in identical environment of High Performance Analytics server. The methods are applied to a certain sample whose volume is increased after every round of executed measurement. The conclusion evaluates the tests results and discusses the possibility of usage of the individual High Performance Analytics methods.
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