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Design of inter-operational transport in a manufacturing company according to the Industry 4.0 concept
Mravec, Roman ; Vyroubal, Petr (referee) ; Bayer, Robert (advisor)
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 (referee) ; Kšica, Filip (advisor)
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 (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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Model Driven Development of Spark Tasks by Means of Eclipse Acceleo
Šalgovič, Marek ; Bartík, Vladimír (referee) ; Rychlý, Marek (advisor)
Táto diplomová práca sa zaoberá modelom riadeným vývojom Big Data úloh v prostredí Apache Spark. Na začiatok je čitateľovi predstavený framework Apache Spark a potrebné detaily. Ďalej sa priblíži problematika modelom riadeného vývoja a popíšu sa jeho výhody a nevýhody. V druhej časti je popísaný navrhnutý meta-model pre modelovanie úloh Sparku. Detailne sú popísané vlastnosti navrhnutého profilového diagramu, ktorý rozširuje diagram tried. Následne je implementovaný generátor kódu, ktorého vstup sú modely vyhovujúce navrhnutému meta-modelu. Práca taktiež obsahuje príklady modelov a ich vyhodnotenie.
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Big Data and Personal Data Protection in the Age of Surveillance Capitalism
Jirásková, Kristýna ; Slavíček, Daniel (advisor) ; Gvoždiak, Vít (referee)
The diploma thesis deals with the topic of personal data protection in the age of surveillance capitalism, relying on the General Data Protection Regulation or GDPR. It presents, first of all, what can be imagined by the term Big Data, since the protection of personal data consists in the constant collection of all data, among which there are personal data. In the context of this issue, the various risks of data collection and processing will be discussed. Then, attention is given to surveillance capitalism, i.e. not only the definition, but also what it consists of and what pitfalls come with it. Above all, this paper seeks to answer the question of what role the GDPR currently plays in relation to data protection, i.e. whether it is successful or not, which of course cannot be done without a more detailed analysis of this legal document. To this end, the thesis will focus on selected examples from practice that should help to answer the question posed. Key words Surveillance Studies, surveillance, Big Data, surveillance capitalism, GDPR, protection of personal data, social media
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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. Bachelor thesis. Brno: Mendel University in Brno, 2015. This thesis is compiled on the Cloud computing and its introduction in the small and medium enterprises and evaluation of its connection to the up-coming tech-nologies and chosen factors connected to the operations management with the stress on costs. Cloud computing shows strong benefits for the business. The study of selected model company showed that it is justified for a company to con-sider the technology, however, it might not be applicable for all kinds of small and medium enterprises.
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Big Social Data and the Study of Celebrity Fandom
Sedláček, Jakub ; Numerato, Dino (advisor) ; Špaček, Ondřej (referee) ; Mikuláš, Peter (referee)
This thesis provides a novel view of celebrity fandom through the lens of big social data, while at the same time exploring the opportunities and challenges of using digital traces from social media for sociological research. The first chapter provides a sociological framing of celebrity, a short, joint history of celebrity and the media, and a discussion of the revolutionary role that social media and its platforms played in celebrity culture. Finally, it attempts to bridge theories related to celebrity's role in society with research on "lifestyle politics", "polarization", "taste cultures" and "lifestyle enclaves". The second chapter serves as an introduction into big social data and digital trace data. First as a socio-technological phenomenon, then as a research tool. It covers its historical and current availability and discusses its epistemological and practical opportunities, limits and dangers. Finally, it introduces Facebook pagelikes as a valuable source of information on lifestyle politics. Chapter three is an exploration of Facebook digital traces of 90k celebrity followers. It asks whether celebrity preferences are related to differences in various aspects of life, including politics, leisure or cultural consumption. Methodologically, it covers combining data from APIs with web scraping and...
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