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Multi-filament yarns testing for textile-reinforced concrete
Kaděrová, Jana ; Seitl,, Stanislav (referee) ; Vořechovský, Miroslav (advisor)
The scope of the presented master thesis was the experimental study of multi-filament yarns made of AR-glass and used for textile-reinforced concrete. The behavior under the tensile loading was investigated by laboratory tests. A high number of yarn specimens (over 300) of six different lengths (from 1 cm to 74 cm) was tested to obtain statistically significant data which were subsequently corrected and statistically processed. The numerical model of the multi-filament bundle was studied and applied for prediction of the yarn performance and for later results interpretation. The model of n parallel filaments describes the behavior of a bundle with varying parameters representing different sources of disorder of the response and provides the qualitative information about the influence of their randomization on the overall bundle response. The aim of the carried experiment was to validate the model presumptions and to identify the model parameters to fit the real load-displacement curves. Unfortunately, due to unsuccessful correction of measured displacements devalued by additional non-linear contribution of the unstiff experiment device the load-displacement diagrams were not applicable to model parameters identification. The statistical evaluation was carried only for the maximal load values and the effect of the specimen size (length) on its strength was demonstrated. The size effect curve did not exclude the existence of spatial correlation of material mechanical properties modifying the classical statistical Weibull theory.
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Bayesian Networks Applications
Chaloupka, David ; Rozman, Jaroslav (referee) ; Zbořil, František (advisor)
This master's thesis deals with possible applications of Bayesian networks. The theoretical part is mainly of mathematical nature. At first, we focus on general probability theory and later we move on to the theory of Bayesian networks and discuss approaches to inference and to model learning while providing explanations of pros and cons of these techniques. The practical part focuses on applications that demand learning a Bayesian network, both in terms of network parameters as well as structure. These applications include general benchmarks, usage of Bayesian networks for knowledge discovery regarding the causes of criminality and exploration of the possibility of using a Bayesian network as a spam filter.
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Analysis of Economic Risk of Investment Project
Malý, Lukáš ; Holá, Michaela (referee) ; Hromádka, Vít (advisor)
This thesis focuses on considering of the investor economic risk during the preparation of the investment project including the financial plan, its evaluation and suggestions of proposals for risk reduction. Correct decisions on implementation or rejection of the project are based on the realistic financial plan. However, expenses and revenues are only implied and are burdened with some variability that leads to the risk of failure to achieve the planned values. To assess the acceptability of certain risks for the investor, an analysis of risk factors was conducted. The factors are first identified for their significance and potential negative impact, then the most risk factors are evaluated and determined whether it is necessary to further tracking or the risk to the investor is acceptable.
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Risk analysis of the Hradek water supply system
Hofmannová, Lenka ; Svoboda,, Miroslav (referee) ; Ručka, Jan (advisor)
The diploma thesis is focused on risk analysis of water supply system in a small community. The WaterRisk project was solved by using tools of risk management including risk identification and quantification in the field of public water supply systems. Methodology and software for the risk management of water supply were evolved by using this project. In this thesis there is applied the methodology to the water supply system of Hradek village. The hydraulic analysis was performed for a thorough knowledge of water supply and its characteristic behavior. Risk analysis could be performed thanks to the knowledge of the entire system, its working and the most common faults. Analysis results are evaluated and compared for the water supply system which is consider like a system simple and complex. The corrective actions eliminate number of risks. These actions were proposed like a part of complex methodology. Further, there were determined optimal costs which corresponds with these corrective actions.
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The Use of Means of Artificial Intelligence for the Decision Making Support on Stock Market
Hrach, Vlastimil ; Budík, Jan (referee) ; Dostál, Petr (advisor)
The diploma thesis deals with artificial intelligence utilization for predictions on stock markets.The prediction is unconventionally based on Bayes' probabilistic model theorem and on its based Naive Bayes classifier. I the practical part algorithm is designed. The algorithm uses recognized relations between identifiers of technical analyze. Concretely exponential running averages at 20 and 50 days had been used. The program output is a graphic forecast of future stock development which is designed on ground of relations classification between the identifiers
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Probability-based model for network traffic
Bednár, Peter ; Jelínek, Mojmír (referee) ; Molnár, Karol (advisor)
This work identifies several basic types of traffic in IP networks and describes main features. The basic network services such as HTTP, VoIP and electronic mail are discussed focusing mainly on HTTP and VoIP probability-based models for network traffic which are applied to the software simulation of real network.
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Risk Analysis of Self-Driven Vehicles
Weigel, Filip ; Šimek, Václav (referee) ; Strnadel, Josef (advisor)
The goal of this thesis was to design and implement system for risk analysis in self-driving cars. This thesis focused on design and implementation of system for risk analysis in models. One of the requirements for the system was to be flexible and robust. Design of the risk analysis was presented at theoretical level and then implemented in models of ABS and ESP systems in UPPAAL environment. The system was then tested via multiple experiments. The experiments were beneficial and the system for risk analysis correctly evaluated failure scenarios with adequate response to the rising level of risk. Experiment outputs were then presented at graphs with comment to each failure scenario.
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Software Projects Risk Management Support Tool
Gabriš, Ondrej ; Chudý, Peter (referee) ; Kreslíková, Jitka (advisor)
Management projektů a jejich rizik je v současnosti rozvíjející se disciplína, která si získává stále větší pozornost a uplatnění v praxi. Tato práce popisuje úvod do problematiky řízení rizik, zkoumání metod jejich identifikace, vyhodnocení a managementu, předcházení jejich následkům a jejich zvládání. V další části práce byla provedena analýza vzorků rizik z reálných projektů, byly popsány metody pro identifikaci a vyhodnocení následků rizik v úvodních fázích softwarového projektu, taktéž byly popsány atributy rizik a navržen způsob jejich dokumentace. V závěrečné části zadání byl navržen a implementován prototyp modelové aplikace pro podporu managementu rizik softwarových projektů.
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Risk assessment design margin of process and power equipment
Horsák, Jan ; Pačíska, Tomáš (referee) ; Jegla, Zdeněk (advisor)
This work is devoted to description of methodology of determining process and power equipment design margins, which is based on assessment of a relative process importance of the equipment in question. The methodology is theoretically analysed, brought into context of common design practice and demonstrated on actual cases. Substantial part of this work analyses heat transfer in general as a base of heat exchanger design process.
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Enhancement of Probabilistic Methods for Password Cracking
Lištiak, Filip ; Polčák, Libor (referee) ; Hranický, Radek (advisor)
This thesis describes passwords cracking using probabilistic context-free grammars, specifically PCFG Cracker tool. The aim of the thesis is to design and implement enhancements to this tool, which reduce the size of output dictionaries while maintaining acceptable success rate. This work also solves critical parts in the tool that slow down the overall duration of the program. Another goal of the thesis is to analyze and implement targeted attack dictionaries that increase the scope and success rate of generated passwords.
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