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Design of inter-operational transport in a manufacturing company according to the Industry 4.0 concept
Mravec, Roman ; Vyroubal, Petr (oponent) ; Bayer, Robert (vedoucí práce)
Based on the description and definition of technology and processes falling within the vision of the fourth industrial revolution with the aim of creating intelligent factories, this diploma thesis deals with the principles of the Industry 4.0 concept in Hilti's production plant with a focus on transport and supply of production equipment. The aim of the work is to create a comprehensive proposal that takes into account all the necessary aspects associated with upgrading the existing state of inter-operational transport in a particular production line to fully automated, flexible and autonomous transport of materials and products in the context of Industry 4.0. A prerequisite for creating a design is the connection of automatically guided vehicles (AGVs) serving individual transport orders. The selection of the vehicle was made taking into account the safety of movement, the method of charging, the system and network integrity of existing and proposed technologies and components. The intention is not only to automate the inter-operational service, but also on the basis of the created automation concept, the ability to autonomously procure the flow of material and products. The mathematical calculation of capacity planning in the production line helped to determine the total load and the number of vehicles needed for continuous procurement of transport requirements. The result of the design part is also the design of specific transport routes and transport conditions that AGV vehicles must comply with in order to maintain a high level of safety. Transparency and a constant overview of transported products is provided by the presented scheme for identification of production batches, Auto-ID system. The financial efficiency of the whole project elaborated in the diploma thesis is evaluated as payable after 4 years from the implementation of the proposal. The financial efficiency of the whole project elaborated in the diploma thesis is evaluated as payable after 4 years from the implementation of the proposal due to high labor costs.
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Processing of big data from measurements and simulations of dynamic systems
Ďuriš, Anton ; Musil, Filip (oponent) ; Kšica, Filip (vedoucí práce)
This thesis is focused on Big data processing from modern technical devices. Big data processing is a time-consuming and complex process requiring powerful hardware, however, there are some methods which enable Big data processing even on a personal computer. In the theoretical part of this thesis, available methods and functions for Big data processing, which are integrated within software and programming languages, are summarized. We focus on TDMS file format, its features and opening options in software and programming languages and their comparison. Then, data preprocessing methods accelerating processing and analysis are listed. In the practical part of this thesis, a graphical user interface in Matlab environment for TDMS file format processing with implemented data preprocessing methods is created. The aim of this thesis is to make processing with this file format more efficient by using a personal computer.
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Information and Communication Technology and Brexit Referendum
Šindelka, Dan ; Sedláček, Pavel (oponent) ; Froehling, Kenneth (vedoucí práce)
The aim of this work to describe Information and Communication Technologies used in the 2016 United Kingdom European Union membership referendum. This thesis provides a description of referendums in the UK. Following is the general description of Information and Communication Technologies. The role of AggregateIQ in the 2016 United Kingdom European Union membership referendum is explained. The description of the combination of Big Data and Psychographics is provided, additionally, their role in the 2016 United Kingdom European Union membership referendum.is explained. Furthermore, the possible effect of the Information and Communication Technologies on later democratic elections is discussed.
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Model Driven Development of Spark Tasks by Means of Eclipse Acceleo
Šalgovič, Marek ; Bartík, Vladimír (oponent) ; Rychlý, Marek (vedoucí práce)
This thesis deals with the Model-Driven Development of Big Data tasks in the Apache Spark environment. In the beginning, the reader is introduced to the Apache Spark framework and necessary details. Afterward, a closer look at the Model-Driven Development methodology is provided, and its advantages and disadvantages are described. The second part describes the designed meta-model for modeling Spark tasks. The designed Profile diagram features that extend the Class diagram are described in detail. Afterward, the code generator is implemented. The input of the generator are models that satisfy the designed meta-model. The thesis also contains example models and their evaluation.
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Big Data a ochrana osobních údajů v době kapitalismu dohledu
Jirásková, Kristýna ; Slavíček, Daniel (vedoucí práce) ; Gvoždiak, Vít (oponent)
Diplomová práce se věnuje tématu ochrany osobních údajů v době kapitalismu dohledu, přičemž se opírá o Obecné nařízení o ochraně osobních údajů neboli GDPR. Představuje v prvé řadě, co si lze představit pod pojmem Big Data, neboť ochrana osobních údajů spočívá v ustavičném shromažďování veškerých dat, mezi nimiž se nacházejí i ony osobní údaje. V souvislosti s danou problematikou budou rozebrána jednotlivá rizika sběru a zpracování dat. Poté je zde pozornost věnována kapitalismu dohledu, tj. nejen definici, ale rovněž tomu, v čem spočívá a jaká úskalí spolu s ním přichází. A především se tato práce snaží zodpovědět na otázku, jakou roli v současné době ve vztahu k ochraně osobních údajů sehrává GDPR, tedy, zdali je úspěšné či nikoli, což se ovšem neobejde bez podrobnější analýzy tohoto právního dokumentu. Za tímto účelem se práce zaměří na vybrané ukázky z praxe, které by měly napomoci k zodpovězení položené otázky. Klíčová slova Surveillance Studies, dohled, Big Data, dohledový kapitalismus, GDPR, ochrana osobních údajů, sociální sítě
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Some Robust Approaches to Reducing the Complexity of Economic Data
Kalina, Jan
The recent advent of complex (and potentially big) data in economics requires modern and effective tools for their analysis including tools for reducing the dimensionality (complexity) of the given data. This paper starts with recalling the importance of Big Data in economics and with characterizing the main categories of dimension reduction techniques. While there have already been numerous techniques for dimensionality reduction available, this work is interested in methods that are robust to the presence of outlying measurements (outliers) in the economic data. Particularly, methods based on implicit weighting assigned to individual observations are developed in this paper. As the main contribution, this paper proposes three novel robust methods of dimension reduction. One method is a dimension reduction within a robust regularized linear regression, namely a sparse version of the least weighted squares estimator. The other two methods are robust versions of feature extraction methods popular in econometrics: robust principal component analysis and robust factor analysis.
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Some Robust Approaches to Reducing the Complexity of Economic Data
Kalina, Jan
The recent advent of complex (and potentially big) data in economics requires modern and effective tools for their analysis including tools for reducing the dimensionality (complexity) of the given data. This paper starts with recalling the importance of Big Data in economics and with characterizing the main categories of dimension reduction techniques. While there have already been numerous techniques for dimensionality reduction available, this work is interested in methods that are robust to the presence of outlying measurements (outliers) in the economic data. Particularly, methods based on implicit weighting assigned to individual observations are developed in this paper. As the main contribution, this paper proposes three novel robust methods of dimension reduction. One method is a dimension reduction within a robust regularized linear regression, namely a sparse version of the least weighted squares estimator. The other two methods are robust versions of feature extraction methods popular in econometrics: robust principal component analysis and robust factor analysis.
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Cloud computing and its introduction in small and medium sized enterprises
Šimonfy, Adam
Simonfy, A. Cloud computing and its introduction in small and medium enterpris-es. Bakalárska práca. Brno: Mendlova Univerzita v Brne, 2015. Táto práca sa zameriava na tému Cloud computing a jeho úvod do malých a stredných podnikov a následné zhodnotenie jeho spojitosti s nadchádzajúcimi modernými technológiami a vybranými faktormi operačného menežmentu s dôrazom na náklady. Cloud computing vykazuje značné benefity pre biznis, Skúmaním zvolenej modelovej spoločnosti ukázalo, že je adekvátne pre firmy zvažovať túto technológiu, hoci to nemusí byť prínosom pre všetky typy firiem.
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Big Social Data and the Study of Celebrity Fandom
Sedláček, Jakub ; Numerato, Dino (vedoucí práce) ; Špaček, Ondřej (oponent) ; Mikuláš, Peter (oponent)
Tato práce přináší nový pohled na celebrity a jejich fanoušky optikou big social data, přičemž zkoumá možnosti využití digitální stopy ze sociálních sítí pro sociologický výzkum. První kapitola přináší sociologické zarámování celebrity, její krátkou historii v kontextu rozvoje médií a diskusi o revoluční roli, kterou pro celebritní kulturu sehrály platformy sociálních médií. Nakonec se snaží o propojení teorií role celebrity ve společnosti s výzkumem životního stylu, polarizace, subkultur vkusu a "enkláv životního stylu". Druhá kapitola slouží jako úvod do problematiky digitální stopy a big social data obecně. Nejprve jako sociálně- technologických fenoménů, poté jako výzkumných nástrojů. Zabývá se jejich historickou i současnou dostupností, epistemologickými implikacemi pro výzkum, limity i nebezpečími. Nakonec představuje seznamy oblíbených stránek na Facebooku jako cenný zdroj informací o životním stylu. Třetí kapitola empiricky zkoumá digitální stopu 90 tisíc fanoušků českých celebrit na Facebooku. Klade si otázku, zda preference celebrit souvisejí s rozdíly v různých aspektech života, včetně politiky, volného času nebo kulturní spotřeby. Z metodologického hlediska se zabývá kombinací dat z API s web scrapingem a praktickými výzvami při práci s "řídkými" daty ze sociálních médií. Testuje rovněž využití...
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