National Repository of Grey Literature 255 records found  1 - 10nextend  jump to record: Search took 0.00 seconds. 
Prediction of Selected Parameters of Rotational Kinematics Pairs of Machine Tools
Marek, Tomáš ; Šooš, Ĺubomír (referee) ; Kolář, Petr (referee) ; Blecha, Petr (advisor)
The dissertation thesis is used as a methodology for prediction of selected parameters of rotational kinematic pairs of machine tools. The motivation for its writing has been continually increasing requirements for parameters (performance, accuracy, static and dynamic stiffness) of machine tools. The methodology takes into account the availability of suitable measuring devices and description of the design of rotary kinematic pairs. It will be useable for predicting the behavior of rotational kinematic pairs, even at the design stage by applying results to the machine design. The work is processed so that first is used a system approach to suggest methodology for prediction of the behavior of rotary kinematic pair in CNC machine tools, planning measurement strategy and verifying the results, including applications for specific kinematic chain of the selected machine. Based on this system approach and the resulting methodology, the measurement of the rotary kinematic pair was performed. The results of the system approach and measurement are generalized in the form of recommendations for designers of machining centers, allowing to increase the accuracy of the rotational kinematic pair.
Analysis of circulating markers in patients with solid tumors
Buranovská, Katarína ; Souček, Pavel (advisor) ; Němcová, Vlasta (referee)
Circulating cell-free DNA (cfDNA) and its tumour-derived circulating tumour DNA (ctDNA) fraction are considered an innovative prognostic and predictive biomarker in oncological diagnostics. Many studies have demonstrated higher levels of cfDNA concentration and integrity, as an indicator of the amount of ctDNA in cfDNA, in body fluids from patients with cancer diseases in comparison with healthy individuals, which suggest its potential as an effective biomarker for monitoring of the tumour dynamics. This study focused on optimisation and validation of measurement methods later used for analysis of cfDNA concentration and integrity in blood samples from patients with four different solid cancers. Two different commercial isolation kits have been tested in plasma and serum samples. Quantitative real-time polymerase reaction (qPCR) and PicoGreen dsDNA assay were optimized to effectively quantify low concentrations of cfDNA, subsequently compared to each other and to droplet digital PCR assay tested on selected samples. The concentration and integrity of cfDNA from plasma samples of breast, ovarian, colorectal and pancreatic cancer patients were evaluated. Higher amounts of cfDNA were obtained by the QIAamp Circulating Nucleic Acid isolation kit (Qiagen) in comparison to Plasma/Serum Cell-Free...
Comparison of alternative league formats in european football
Pešková, Tereza ; Šíma, Jan (advisor) ; Kolmistr, Martin (referee)
Title: Comparison of alternative league formats in european football Objectives: The aim of this work is to analyse play - offs of chosen european league formats. The other aim is to make a prediction about czech league. Methods: A method of comparison was used in this thesis. A placement of each team before play - offs was compared to a placement of the same teams after play - offs. After that, there was a comparison if play - offs have more impact on championship round or on relegation round. Based on conclusions from these comparisons we have made an estimate of development in Czech league. Results: We discovered that play - offs have more impact on teams which played relegation round. In most of analysed seasons play - offs did not change the winner of the league and neither helped a lot of teams to enter European championships. We estimate that play - offs of Czech league will help more second league teams to promote to first league. Keywords: football, tournament systems, league, prediction
Predictive Modelling with Python
Duda, Jan ; Burgetová, Ivana (referee) ; Zendulka, Jaroslav (advisor)
The main goal of this bachelor thesis is get to know with the data mining and its domain, also with the Knowledge discovery in databases process. It shows the most importnant approaches, which are implemented in Python language afterwards. The case study contains the prediction of index S&P 500 describing stock market developments on the US stock exchange. Both classification and regression models are used for the forecasting. Model evaluation is reached by the Monte Carlo experimental method.
Web Simulator of Football Leagues and Championships
Urbanczyk, Martin ; Holkovič, Martin (referee) ; Hynek, Jiří (advisor)
This thesis is about the creation of a simulator of football leagues and championships. I studied the problematics of football competitions and their systems and also about the base of machine learning. There was also an analysis of similar and existing solutions and I took inspiration for my proposal from them. After that, I made the design of the whole simulator structure and of all of its key parts. Then the simulator was implemented and tested. The application allows simulating top five competitions in UEFA club coefficients rating.
Lossless Light Field Compression
Navrátil, Robert ; Šolony, Marek (referee) ; Bařina, David (advisor)
This thesis is focused on lossless light-field images compression, where it could be viable to extend common predictors into more dimensions. First chapter is regarding to essential theory about light-field images and 4D light-field, which is followed by description of every predictor and coder. With this is connected description of used compression pipeline. Last chapters contains description of solution and differences between every predictor result and theirs dimensional variant. At the end the results are compared with PNG. The result is that some 4D variants of implemented predictors have better compression rate than PNG.
Assessing Economic Situation of a Company and Proposals for Its Improvement
Matys, Jan ; Veselovský, Pavel (referee) ; Doubravský, Karel (advisor)
The diploma thesis evaluates the economic situation of BPS Bicycle Industrial s. r. o. time series analysis. The theoretical part describes financial indicators, time series analyzes and regression and correlation analysis. Based on the analyzes, suggestions were made to improve the current situation of the company. BPS has proven to be financially sound. Shortcomings to improvement were identified from the analyzes. For example, share of equity and debt, use of surplus funds and turnover of receivables and payables. This ratio needs to be addressed through greater use of debt. The system of sanctions is solution for problem the turnover of receivables and the use of surplus funds by investing in shares.
Application of Mathematical and Statistical Methods in Company Management
Ondrašíková, Kristýna ; Doubravský, Karel (referee) ; Novotná, Veronika (advisor)
Ondrašíková, K. Application of Mathematical and Statistical Methods in Business Management. Thesis. Brno: Brno University of Technology, 2019. This thesis deals with the analysis of the mortgage market and the identification of factors that influence its growth. The thesis proposes using the available mathematical and statistical methods of measures for the bank at the level of mortgage sales based on the market analysis.
The Use of Artificial Intelligence for Decision Making in the Firm
Seryj, Michal ; Budík, Jan (referee) ; Dostál, Petr (advisor)
Diploma thesis deals with design of a model for currency rate prediction by using artificial intelligence as a tool for decision making process in business and public administration. Concrete usage of this prediction is applied in company TechPlasty s.r.o. The thesis focuses on analysis of input data, optimization of a prediction model and evaluation of the results and their profit for the selected company.
Tool for Classification of Lifestyle Traits Based on Metagenomic Data from the Large Intestine
Kubica, Jan ; Hon, Jiří (referee) ; Smatana, Stanislav (advisor)
This thesis deals with analysis of human microbiome using metagenomic data from large intestine. The main focus is placed on bacteria composition in a sample on different taxonomic levels regarding the lifestyle traits of an individual. For this purpose, a tool for classification of several attributes was created. It considers attributes like diet type and eating habits (vegetarian, vegan, omnivore), gluten and lactose intolerance, body mass index, age or sex. From range of machine learning perspectives considering K Nearest Neighbours (kNN), Random Forest (RF) and Support Vector Machines (SVM) were used. Datasets for training and final evaluation of the classifier were taken from American Gut project. The thesis also focuses on particular problems with metagenomic datasets like its multidimensionality, sparsity, compositional character and class imbalance.

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