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Estimation of the parameters of quartz oscillators
Čermák, Jan
The main parameters of quartz oscillators are frequency accuracy, frequency drift, and frequency (phase) stability. Methods used to estimate these parameters depend on the oscillator quality and measurements capability of the calibration laboratory. The issue is demonstrated on the measurements performed within the National Time and Frequency Standard.
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Reasoning for decisions on mobile application testing
Balák, Martin ; Gála, Libor (advisor) ; Beránek, Marek (referee)
Thesis analyses the problematics of determining both qualitative and quantitative parameters for testing on projects involving development of mobile applications. First, content and scope of testing is fixed, followed by the specification of influence model. Methodology is proposed to ascertain the financial and temporal extent of the testing based on obtained influence model.
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Clustering and regression analysis of micro panel data
Sobíšek, Lukáš ; Pecáková, Iva (advisor) ; Komárek, Arnošt (referee) ; Brabec, Marek (referee)
The main purpose of panel studies is to analyze changes in values of studied variables over time. In micro panel research, a large number of elements are periodically observed within the relatively short time period of just a few years. Moreover, the number of repeated measurements is small. This dissertation deals with contemporary approaches to the regression and the clustering analysis of micro panel data. One of the approaches to the micro panel analysis is to use multivariate statistical models originally designed for crosssectional data and modify them in order to take into account the within-subject correlation. The thesis summarizes available tools for the regression analysis of micro panel data. The known and currently used linear mixed effects models for a normally distributed dependent variable are recapitulated. Besides that, new approaches for analysis of a response variable with other than normal distribution are presented. These approaches include the generalized marginal linear model, the generalized linear mixed effects model and the Bayesian modelling approach. In addition to describing the aforementioned models, the paper also includes a brief overview of their implementation in the R software. The difficulty with the regression models adjusted for micro panel data is the ambiguity of their parameters estimation. This thesis proposes a way to improve the estimations through the cluster analysis. For this reason, the thesis also contains a description of methods of the cluster analysis of micro panel data. Because supply of the methods is limited, the main goal of this paper is to devise its own two-step approach for clustering micro panel data. In the first step, the panel data are transformed into a static form using a set of proposed characteristics of dynamics. These characteristics represent different features of time course of the observed variables. In the second step, the elements are clustered by conventional spatial clustering techniques (agglomerative clustering and the C-means partitioning). The clustering is based on a dissimilarity matrix of the values of clustering variables calculated in the first step. Another goal of this paper is to find out whether the suggested procedure leads to an improvement in quality of the regression models for this type of data. By means of a simulation study, the procedure drafted herein is compared to the procedure applied in the kml package of the R software, as well as to the clustering characteristics proposed by Urso (2004). The simulation study demonstrated better results of the proposed combination of clustering variables as compared to the other combinations currently used. A corresponding script written in the R-language represents another benefit of this paper. It is available on the attached CD and it can be used for analyses of readers own micro panel data.
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Comparison of Business Intelligence implementation using open source solutions for middle size companies
Schmidt, Róbert ; Maryška, Miloš (advisor) ; Sládek, Pavel (referee)
The main goal of master thesis is to analyze and propose possible low cost Business Intelligence solution with open source technologies and comparison of available tools for implementation in middle size company. We compare Pentaho and Jaspersoft tools implemented on local hardware and cloud environment with Microsoft Azure services. The theoretical part focuses mainly on understanding the business intelligence and its architecture, because architecture is an important part of the work. Actual tools are designed as stand alone modules for specific activities in the business intelligence lifecycle. Low cost tools are often connected with open source technologies and cloud computing. This part of the work contains explanation of these terms and their advantages and disadvantages for our chosen target group of companies. The analytical part includes defined parameters by which it is conducted analysis of tools and their comparison. Business Intelligence solutions are divided according to arcitectural layers. The evaluation criteria are divided into financial, technical and user category. In conclusion, chosen tools are compared and evaluated. The main contribution of this thesis is comparison of open source business intelligence tools for implementation in middle size company. According to the EU directive, middle size company does not exceed 250 employees or profit is less than 50 million euros. The reader can compare the different solutions and their pitfalls or shortcomings that could be critical for the implementation.
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INFLUENCE OF LASER CUTTING AND PUNCHING ON MAGNETIC PROPERTIES\nOF ELECTRICAL STEEL M470-50A
Bulín, Tomáš ; Švábenská, Eva ; Hapla, Miroslav ; Ondrůšek, Č. ; Schneeweiss, Oldřich
Electrical steel M470-50A belongs to the most often used materials in electrical machines. Due to this fact, it is desirable to know the magnetic parameters after processing raw sheets into the required shape. Basic parameters of mechanical, electrical, and magnetic properties of the sheets are usually obtained from the producer but the magnetic properties are changing in dependence on additional machining processes. The aim of this study is to describe changes in parameters of magnetic behavior after punching, laser and spark cutting of the original sheets. The basic information of structure was obtained by optical and scanning electron microscopy. The magnetic parameters were acquired from the measuring of magnetic hysteresis loops in dependence on saturation fields and frequencies. The results are discussed from the point of view of applied\ncutting technology with the aim to obtain the best magnetic parameters and consequently a higher efficiency of the final product. Results can be used as input parameters in simulation of the electrical machine.
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HYDROGEN ABSORPTION IN A-Co30Fe55B15
Čermák, Jiří ; Král, Lubomír ; Roupcová, Pavla
Hydrogen solved in amorphous alloys (AAs) influences their magnetic characteristics. AAs are also perspective\nas additives that can improve hydrogen storage kinetic in certain types of ball-milled hydrogen storage\nmaterials (HSMs). Therefore, knowledge of hydrogen solubility and hydrogen sorption kinetics in AAs are of a\ngreat importance for aimed design both AAs with optimal magnetic parameters and HSMs with desired sorption\ncharacteristics. In the present paper, amorphous alloy Co30Fe55B15 (an example of the type a-TM1xTM2y Bz ;\nTM - transition metal) was investigated. Hydrogen concentration c H was measured by Sieverts method in\ntemperature interval from T = 150 °C to T = 350 °C under hydrogen pressure p up to 6 MPa. It was found that\nc H was an increasing function of p and its maximum value was typically 0.5 wt.% H2 at 350 °C and 6 MPa.\nHowever, when the alloy was preliminary hydrogen charged (PHC), the pressure dependence of total c Htot in\nthe first absorption cycle(s) is non-monotonous in dependence on PHC conditions. For the sake of comparison,\nthe same absorption characteristics were measured also in Mg2Ni intermetallic that is a common constituent\nin Mg-based HSMs. Comparing Co30Fe55B15 and Mg2Ni, it was concluded that Co30Fe55B15 shows lower\nhydrogen solubility, but much better absorption kinetics.
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ELECTRON BEAM REMELTING OF PLASMA SPRAYED ALUMINA COATINGS
Matějíček, Jiří ; Veverka, J. ; Čížek, J. ; Kouřil, J.
Plasma sprayed alumina coatings find numerous applications in various fields, where they enhance the properties of the base material. Examples include thermal barriers, wear resistance, electrical insulation, and diffusion and corrosion barriers. A typical structure of plasma sprayed coatings, containing a multitude of voids and imperfectly bonded interfaces, gives them unique properties - particularly low thermal conductivity, high strain tolerance, etc. However, for certain applications such as permeation barriers or wear resistance, these voids may be detrimental.\nThis paper reports on the first experiments with remelting of plasma sprayed alumina coatings by electron beam technology, with the purpose of densifying the coatings and thereby eliminating the voids. Throughout the study, several parameters of the e-beam device were varied - beam current, traverse velocity and number of passes. The treated coatings were observed by light and electron microscopy and the thickness, structure and surface morphology of the remelted layer were determined and correlated with the process parameters. Based on the first series of experiments, the e-beam settings leading to dense and smooth remelted layer of sufficient thickness were obtained. In this layer, a change of phase composition and a marked increase in hardness were observed.\n
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Diagnostics for Robust Regression: Linear Versus Nonlinear Model
Kalina, Jan
Robust statistical methods represent important tools for estimating parameters in linear as well as nonlinear econometric models. In contrary to the least squares, they do not suffer from vulnerability to the presence of outlying measurements in the data. Nevertheless, they need to be accompanied by diagnostic tools for verifying their assumptions. In this paper, we propose the asymptotic Goldfeld-Quandt test for the regression median. It allows to formulate a natural procedure for models with heteroscedastic disturbances, which is again based on the regression median. Further, we pay attention to nonlinear regression model. We focus on the nonlinear least weighted squares estimator, which is one of recently proposed robust estimators of parameters in a nonlinear regression. We study residuals of the estimator and use a numerical simulation to reveal that they can be severely heteroscedastic also for data generated from a model with homoscedastic disturbances. Thus, we give a warning that standard residuals of the robust nonlinear estimator may produce misleading results if used for the standard diagnostic tools
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Plasma spraying from liquids: plasma liquid interaction and coating build up
Tesař, Tomáš ; Mušálek, Radek ; Medřický, Jan ; Lukáč, František
Plasma spraying from liquid feedstocks is a rapidly developing field of thermal spraying since the coatings prepared from liquids exhibit some unique features, such as high hardness, thermal shock resistance or low thermal and electric conductivity. The key factor influencing the final coating character and properties is the input material which may be in the form of a suspension or a solution. Parameters of the selected suspension (solids concentration, viscosity, surface tension, chemical composition, etc.) or solution (concentration, etc.) determine its interaction with the plasma jet which strongly influences the coating buildup. This proceeding introduces the problematics of the interaction between the liquid feedstock material with the plasma jet and presents the way of evaluation of the coating buildup.
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Neural Networks Between Integer and Rational Weights
Šíma, Jiří
The analysis of the computational power of neural networks with the weight parameters between integer and rational numbers is refined. We study an intermediate model of binary-state neural networks with integer weights, corresponding to finite automata, which is extended with an extra analog unit with rational weights, as already two additional analog units allow for Turing universality. We characterize the languages that are accepted by this model in terms of so-called cut languages which are combined in a certain way by usual string operations. We employ this characterization for proving that the languages accepted by neural networks with an analog unit are context-sensitive and we present an explicit example of such non-context-free languages. In addition, we formulate a sufficient condition when these networks accept only regular languages in terms of quasi-periodicity of parameters derived from their weights.
Fulltext: content.csg -  PDF
Plný tet: v1237-16 - PDF
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