The diploma thesis deals with an assessment of the topical financial situation of BARVY A LAKY TELURIA, s. r. o. using the time series analysis. The theoretical part focuses on the description of the financial indicators, analysis of the time series, and subsequently the regressive and correlative analysis. In the practical part, selected financial indicators are statistically analyzed. The future two-year development of indicators is predicted on the basis of the selected models; subsequently dependencies among the particular indicators are determined. In the conclusion, proposals to ameliorate the current financial situation of the company are recommended, which was carried out on the basis of the identified shortcomings.

The diploma thesis is focused on the creation of a program enabling calculation of selected economic indicators of Arbela s.r.o. The thesis is divided into a theoretical and practical part. The content of the theoretical part is a description of individual methods and procedures of financial analysis, description of principles of time series, and regression analysis. In the practical part, the program created to calculate the selected economic indicators of the company Arbela s.r.o. is presented. These indicators are subsequently evaluated and foreseeable development of the company is determined for the future. At the end of the thesis, solutions for possible improvement of the economic situation of the company can be found.

Environmental risk assessment in industrial enterprise is important part of safety documentation required by legislation of the Czech Republic and of the EU. Despite that, there is given less attention to this part of risk analysis in the Czech Republic, than in the other countries of EU. Importance of this part is evident for a number of significant industrial accidents with impact to the environment. This Master’s thesis deals with the methods used in safety engineering for the environmental risk assessment, according to Act No. 59/2006 Coll., on the prevention of major accidents, as amended by later regulations. The thesis is divided into theoretical and practical part. Theoretical part includes the legislative summary of Act No. 59/2006 Coll. on the prevention of major accidents, as amended by later regulations and requirements for owners, which result from this law. Further, the frameworks for environmental risk assessment in the EU and USA were evaluated and compared. Main part deals with the characteristics of selected (most commonly used in practice) methods for environmental risk assessment, evaluation of its usability and creation of compact process for environmental risk assessment in industrial enterprise in accordance to legislative requirements. In the final part, there is performed application of suggested process for environmental risk assessment in the concrete industrial enterprise.

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Целью работы является развитие методических основ анализа и оценки инновационной активности промышленного предприятия. В качестве механизма оценки предложен усовершенствованный метод, состоящий из семи этапов. Разработанный метод оценки инновационной активности промышленного предприятия позволяет отслеживать его инновационное развитие и, используя полученные выводы и рекомендации, корректировать мероприятия, нацеленные на внедрение передовых инновационных стратегий развития с учетом текущего состоянии компании и ее финансового положения и деятельности в рамках рынка. / The aim of the work is to develop the methodological foundations for the analysis and evaluation of the innovative activity of an industrial enterprise. An improved method consisting of seven stages is proposed as an evaluation mechanism. The developed method for assessing the innovative activity of an industrial enterprise makes it possible to monitor its innovative development and, using the findings and recommendations obtained, adjust measures aimed at introducing advanced innovative development strategies, taking into account the current state of the company and its financial position and activities within the market.

Theories of how galaxies form and evolve depend greatly on constraints provided by observations. However, when those observations come from different datasets, systematic offsets may occur. This causes difficulties measuring variations in parameters between filters. In this thesis I present the variation in total luminosity density with wavelength in the nearby Universe (z<0.1), produced from a consistent reanalysis of NIR and optical observations, taken from the MGC, UKIDSS and SDSS surveys. I derive luminosity distributions, best-fitting Schechter function parameterisations and total luminosity densities in ugrizYJHK, and compare the variation in luminosity density with cosmic star formation history (CSFH) and initial mass function (IMF) models. I examine the r band luminosity distribution produced using different aperture definitions, the joint luminosity- surface brightness (bivariate brightness) distribution in ugrizYJHK, comparing them to previously derived distributions, and how the total luminosity density varies with wavelength when surface brightness incompleteness is accounted for. I find the following results. (1) The total luminosity density calculated using a non-Sersic (e.g. Kron or Petrosian) aperture is underestimated by at least 15%, (2) Changing the detection threshold has a minor effect on the best-fitting Schecter parameters, but the choice of Kron or Petrosian apertures causes an offset between datasets, regardless of the filter used to define the source list, (3) The decision to use circular or elliptical apertures causes an offset in M* of 0.20 mag, and best-fitting Schechter parameters from total magnitude photometric systems have a flatter faint-end slope than Kron or Petrosian photometry, (4) There is no surface brightness distribution evolution with luminosity for luminous galaxies, but at fainter magnitudes the distribution broadens and the peak surface brightness dims. A Choloniewski function that is modified to account for this surface brightness evolution fits the bivariate-brightness distribution better than an unmodified Choloniewski function, (5) The energy density per unit interval, vf(v) derived using MGC and GAMA samples agrees within 90% confidence intervals, but does not agree with predictions using standard CSFH and IMF models. Possible improvements to the data and alterations to the theory are suggested.

<p>Doktorska disertacija ukazuje na model dijagnostike stanja koji zbog svog istraživačkog karaktera može dovesti do novih naučnih saznanja i metoda praćenja uticaja najvažnijih parametara na pouzdanost vozila, izučavanja ključnih performansi iz oblasti održavanja motornih vozila. Njen cilj je da teorijski i empirijski, kritički, sistematski i kontrolisano defini&scaron;e model dijagnostike stanja kao i da izvr&scaron;i izbor optimalnih parametara, radne temperature i pohabanosti ležajeva, a sve u cilju određivanja sigurnosti funkcionisanja sastavnih komponenti motornih vozila. Proces istraživanja modela predstavlja vezu između periodičnosti provere parametara stanja u radu i otkaza sastavnih komponenata motornih vozila. Simulacijom se može prognozirati vremenski trenutak zamene komponenata pre nego &scaron;to dođe do njihovog otkaza. Dati model je univerzalnog tipa iz razloga &scaron;to se može primeniti i na složene sisteme, bez obzira na dimenzije komponenti sklopova motornih vozila.</p> / <p>PhD dissertation indicates a model of state diagnostics, which due to its research nature, could lead to new scientific knowledge and methods of monitoring the impact of the most important parameters on vehicle reliability, the study of key performance in the field of maintenance of motor vehicles. Its aim is to theoretically and empirically, critically, systematically and in a controlled way define the model of conditions diagnostic and to make the selection of optimal parameters, operating temperature and wear of bearings, all for the purpose of determining the security of functioning of the parts and components of motor vehicles. The research process of a model represents the relationship between the periodicity of testing parameters of the operating mode and cancellation of integral components of motor vehicles. The simulation can predict time for replacement of components before they cancel. The present model is of a universal type because it can be applied to complex systems, regardless of the dimensions of the components of motor vehicles.</p>

The master's thesis deals with the fundamental and technical analysis of stock Philip Morris ČR. The aim of the thesis is a specification of investment recommendation. The fundamental analysis specifies an intrinsic value of the stock Philip Morris ČR, compares it with a real stock price and recommends sale or purchase of this stock. Technical analysis uses graphical methods and technical indicators to determine an appropriate time to sale or purchase this stock.

[Truncated abstract] The hydrodynamics of wave impact on offshore structures is not well understood. Wave impacts often involve large deformations of water free-surface. Therefore, a wave impact problem is usually combined with a free-surface problem. The complexity is expanded when the body exposed to a wave impact is allowed to move. The nonlinear interactions between a moving body and fluid is a complicated process that has been a dilemma in the engineering design of offshore and coastal structures for a long time. This thesis used experimental and numerical means to develop further understanding of the wave impact problems as well as to create a numerical tool suitable for simulation of such problems. The study included the consideration of moving boundaries in order to include the coupled interactions of the body and fluid. The thesis is organized into two experimental and numerical parts. There is a lack of benchmarking experimental data for studying fluid-structure interactions with moving boundaries. In the experimental part of this research, novel experiments were, therefore, designed and performed that were useful for validation of the numerical developments. By considering a dynamical system with only one degree of freedom, the complexity of the experiments performed was minimal. The setup included a plate that was attached to the bottom of a flume via a hinge and tethered by two springs from the top one at each side. The experiments modelled fluid-structure interactions in three subsets. The first subset studied a highly nonlinear decay test, which resembled a harsh wave impact (or slam) incident. The second subset included waves overtopping on the vertically restrained plate. In the third subset, the plate was free to oscillate and was excited by the same waves. The wave overtopping the plate resembled the physics of the green water on fixed and moving structures. An analytical solution based on linear potential theory was provided for comparison with experimental results. ... In simulation of the nonlinear decay test, the SPH results captured the frequency variation in plate oscillations, which indicated that the radiation forces (added mass and damping forces) were calculated satisfactorily. In simulation of the nonlinear waves, the waves progressed in the flume similar to the physical experiments and the total energy of the system was conserved with an error of 0.025% of the total initial energy. The wave-plate interactions were successfully modelled by SPH. The simulations included wave run-up and shipping of water for fixed and oscillating plate cases. The effects of the plate oscillations on the flow regime are also discussed in detail. The combination of experimental and numerical investigation provided further understanding of wave impact problems. The novel design of the experiments extended the study to moving boundaries in small scale. The use of SPH eliminated the difficulties of dealing with free-surface problems so that the focus of study could be placed on the impact forces on fixed and moving bodies.

This dissertation deals with customised image analysis tools in cancer research. In the field of biomedical sciences, mathematical imaging has become crucial in order to account for advancements in technical equipment and data storage by sound mathematical methods that can process and analyse imaging data in an automated way. This thesis contributes to the development of such mathematically sound imaging models in four ways: (i) automated cell segmentation and tracking. In cancer drug development, time-lapse light microscopy experiments are conducted for performance validation. The aim is to monitor behaviour of cells in cultures that have previously been treated with chemotherapy drugs, since atypical duration and outcome of mitosis, the process of cell division, can be an indicator of successfully working drugs. As an imaging modality we focus on phase contrast microscopy, hence avoiding phototoxicity and influence on cell behaviour. As a drawback, the common halo- and shade-off effect impede image analysis. We present a novel workflow uniting both automated mitotic cell detection with the Hough transform and subsequent cell tracking by a tailor-made level-set method in order to obtain statistics on length of mitosis and cell fates. The proposed image analysis pipeline is deployed in a MATLAB software package called MitosisAnalyser. For the detection of mitotic cells we use the circular Hough transform. This concept is investigated further in the framework of image regularisation in the general context of imaging inverse problems, in which circular objects should be enhanced, (ii) exploiting sparsity of first-order derivatives in combination with the linear circular Hough transform operation. Furthermore, (iii) we present a new unified higher-order derivative-type regularisation functional enforcing sparsity of a vector field related to an image to be reconstructed using curl, divergence and shear operators. The model is able to interpolate between well-known regularisers such as total generalised variation and infimal convolution total variation. Finally, (iv) we demonstrate how we can learn sparsity promoting parametrised regularisers via quotient minimisation, which can be motivated by generalised Eigenproblems. Learning approaches have recently become very popular in the field of inverse problems. However, the majority aims at fitting models to favourable training data, whereas we incorporate knowledge about both fit and misfit data. We present results resembling behaviour of well-established derivative-based sparse regularisers, introduce novel families of non-derivative-based regularisers and extend this framework to classification problems.