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Family house,Brno-Líšeň
Kubík, Jan ; ing.arch.Klvaňa Jiří (referee) ; Eliáš, Luboš (advisor)
This bachelor´s thesis deals with the design of family house with an establishment - shop and repair tool. The building is located on sloping land, it is brick house and it has two floors and a basement. The roofs are flat. The house is designed for family of four. The entrance is oriented to the northwest and living rooms to the south. The work includes documentation part and drawing part and it is created as an implementing project.
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Perspective bus powertrains
Kubík, Jan ; Maršálek, Ondřej (referee) ; Píštěk, Václav (advisor)
The aim of this thesis is to consider possible future development of alternative powertrains with regard to their use in buses. First described are the most promising alternative fuel vehicles, which use an internal combustion engine. The next part is evaluated ways to store energy using electric drives. At the end of the work is mentioned hybrid technology as a combination of previous drives.
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Marketing Plan for Fitness ProGym
Kubík, Ján ; Láník, Klára (referee) ; Novák, Petr (advisor)
The aim of the bachelor thesis is to elaborate a marketing plan for Fitness ProGym, belonging to the Sokol Brno 1. The focus of the thesis is on analysis of the current situation, services and competition, research of customer satisfaction and opportunities in these areas. On the basis of the analyses and information gathered, a proposal to promote a gym, support sales in the form of loyalty shares and increase customer satisfaction is made so that Fitness ProGym is a dignified competitor in the sports market in Brno.
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Neural Network for Autocomplete in the Browser
Kubík, Ján Jakub ; Zemčík, Pavel (referee) ; Kolář, Martin (advisor)
The goal of this thesis is to create and train a neural network and use it in a web browser for English text sequence prediction during writing of text by the user. The intention is to simplify the writing of frequent phrases. The problem is solved by employing a recurrent neural network that is able to predict output text based on the text input. Trained neural network is then used in a Google Chrome extension. By normalized ouput of the neural network, text choosing by sampling decoding algorithm and connecting, the extension is able to generate English word sequences, which are shown to the user as suggested text. The neural network is optimized by selecting the right loss function, and a suitable number of recurrent layers, neurons in the layers, and training epochs. The thesis contributes to enhancing the everyday user experience of writing on the Internet by using a neural network for English word sequence autocomplete in the browser.
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Penzion SKI - Orlické hory
Kubík, Jan ; Klvaňa, Jiří (referee) ; Eliáš, Luboš (advisor)
The content of the master thesis is processing of project documentation for he mountain boarding house in Zdobnice in Orlické hory, first done as a pilot project and then as a building construction project. It concerns a three floor building. Vertical load-bearing structures are made of ceramic blocks. Horizontal load-bearing structures are made of prestressed hollow core slabs. Roofing is solved with mono-pitched roof and flat roof. The access to building is from the west for the public and from the east for the staff. There is the ski and bike rental in this building.
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Investments of Automotive Industry in Metals as Strategic Materials
Kubík, Ján ; Ptáček, Roman (referee) ; Rejnuš, Oldřich (advisor)
This diploma thesis deals with the fundamental analysis of selected metals as commodities, for use in the production of batteries for electric vehicles, to hedge against changes in the price of physical raw materials. Selected metals are analyzed based on the fundamental parameters, historical price development and the current situation on the commodity market. Based on these fundamental data, a recommendation is formulated for the method of hedging the prices of selected commodities.
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An Empirical Evaluation of Selfish Mining Strategies on Various Blockchains
Kubík, Ján Jakub ; Košťál,, Kristián (referee) ; Homoliak, Ivan (advisor)
Táto práca si kladie za cieľ posilniť bezpečnosť blockchainu tým, že prehĺbi pochopenie útokov typu sobecké ťaženie v rámci rôznych konsenzuálnych protokolov. Predchádzajúce výskumy sa sústredili na jednotlivé protokoly s jedným útočníkom. Štúdie s viacerými útočníkmi boli len pre konsenzuálny protokol Nakamoto. Na preklenutie tejto medzery bol vytvorený diskrétny, statický, stochastický simulačný framework na analýzu sobecnkého ťaženia s viacerými útočníkmi naprieč rôznymi protokolmi vrátane Nakamoto, Subchain a Strongchain. S použitím tohoto frameworku boli zreprodukované hranice pre úspešný útok na Nakamoto a Strongchain. Ďalej bola zistená hranica pre úspešný útok na Strongchain pre dvoch útočníkov. Pre Subchain bolo nezávisle skúmané sobecké ťaženie na slabých a silných blokoch. Bolo zistené, že len pre silné bloky je sobecké ťaženie ziskové s mierne vyššími hraniciami ako v Nakamoto. Hlavným prínosom tejto práce je vytvorený framework s overenými hranicami a vývojom sobeckého ťaženia pre podporované protokoly. Taktiež tento framework je ľahko rozšíriteľný o nové konsenzuálne protokoly, čo umožňuje hodnotiť odolnosť rôznych Proof of Work protokolov voči útokom typu sobecké ťaženie.
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Investments of Automotive Industry in Metals as Strategic Materials
Kubík, Ján ; Ptáček, Roman (referee) ; Rejnuš, Oldřich (advisor)
This diploma thesis deals with the fundamental analysis of selected metals as commodities, for use in the production of batteries for electric vehicles, to hedge against changes in the price of physical raw materials. Selected metals are analyzed based on the fundamental parameters, historical price development and the current situation on the commodity market. Based on these fundamental data, a recommendation is formulated for the method of hedging the prices of selected commodities.
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Neural Network for Autocomplete in the Browser
Kubík, Ján Jakub ; Zemčík, Pavel (referee) ; Kolář, Martin (advisor)
The goal of this thesis is to create and train a neural network and use it in a web browser for English text sequence prediction during writing of text by the user. The intention is to simplify the writing of frequent phrases. The problem is solved by employing a recurrent neural network that is able to predict output text based on the text input. Trained neural network is then used in a Google Chrome extension. By normalized ouput of the neural network, text choosing by sampling decoding algorithm and connecting, the extension is able to generate English word sequences, which are shown to the user as suggested text. The neural network is optimized by selecting the right loss function, and a suitable number of recurrent layers, neurons in the layers, and training epochs. The thesis contributes to enhancing the everyday user experience of writing on the Internet by using a neural network for English word sequence autocomplete in the browser.
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