This masters thesis optimises production of the step plates (which are parts of the sliding steps systems used in tramways, subways, hi-speed trains etc.) to increase the production rate to meet customers demand. The purpose of the work was reached by detailed analysis of the production process followed by evaluation of the results which led to the list of the possible solutions. The solution with the greatest time improvement was chosen and explained in detail.

The main goal of this work is to design an efficient and cheap car-alarm with an electricity consumption not exceeding 1mA in the stand-by mode. The first part focuses on the conception of the car-alarm. As the best option - GPS/GSM car-alarm conception is chosen. Then the design of the switching power supply, communication via RS232 with the GSM module, and GPS module, I2C communication with accelerometer and timer IC, and design of the display module are described. Furthermore, the process of how to code/decode sms into the PDU format is also discussed in this part. The second part provides some basic empirical characteristics of the switching power supply (efficiency, switching frequency etc.). Then the owchart of the main loop is explained, followed by an example of the sms which the car-alarm sends in case a car theft. Explanation of how to set up timer, acceleration threshold and the time between the check of the sms commads is the subject of the next section. Fifth part deals with the installation the car-alarm into a car which is illustrated on the Skoda Favorit example. Total costs and also different cost items are listed just before concluding and suggesting some potential improvements of the device.

Master´s thesis describes current economic state of the OHL ŽS, a.s., analyzes the makronomics and mikronomics surrounding. On the basis of this analysis I suggest arrangements that will lead to achieve the required marketing´s targets.

La contamination des milieux côtiers par des contaminants émergents est une préoccupation sociétale récente ce qui explique le peu de données disponibles, à ce jour dans ce milieu. Pourtant, certains de ces contaminants sont susceptibles de générer des effets écotoxiques sur les organismes aquatiques du milieu marin. Trois voies d’introduction de contaminants dans l’environnement marin sont communément identifiées : l’apport indirect depuis les bassins versants à travers les fleuves côtiers et les apports directs soit lors d’activités récréatives, soit par le rejet d’effluents d’eaux usées. Ce travail de thèse s’est focalisé sur les apports directs. L’objectif principal de cette thèse a été d’établir un état des lieux de la contamination du milieu marin par les pharmaceutiques et les produits de soin (PPCP) et d’évaluer leur apport par les activités récréatives et les eaux usées. Pour évaluer l’impact des activités de baignade sur la contamination marine, des analyses d’occurrence de filtres UV, substances principalement contenues dans les crèmes solaires ont été réalisées en zones côtières dans l’eau de mer et dans des organismes aquatiques, les moules. Les résultats de ces mesures ont montré des variations saisonnières et intra journalières de la concentration de filtres UV dans le milieu côtier, confirmant l’apport de ces substances par les activités récréatives. Le traitement par les stations d’épuration (STEP) ne permet pas une élimination complète de certains PPCP persistants. Pour évaluer l’impact des effluents de STEP sur les milieux récepteurs, des molécules pharmaceutiques et leurs formes conjuguées ont été recherchées dans des effluents domestiques et d’hôpitaux et en entrée et sortie de STEP. Les concentrations faibles de molécules conjuguées retrouvées en sortie de STEP ont démontré que les molécules conjuguées ne représentaient pas des marqueurs pertinents de la contamination marine par les eaux usées. Cependant les eaux usées traitées de manière partielle sont parfois rejetées directement dans le milieu marin via des émissaires en mer d’où l’importance de l’évaluation de cet apport. Les données acquises sur l’occurrence d’une molécule pharmaceutique, la venlafaxine et ses produits de transformation en sortie d’émissaire en mer a permis de confirmer la présence de ses molécules dans le milieu marin et l’importance d’inclure les métabolites dans les programmes de surveillance de la contamination marine. / Contamination of coastal environments by emerging contaminants is a recent societal concern, explaining the lack of data available today in this environment. However, some of these contaminants are likely to cause ecotoxic effects on aquatic organisms in the marine environment. Three ways of contaminants introduction into the marine environment are commonly identified: indirect inputs with catchments through coastal rivers and direct inputs through recreational activities and through the wastewater effluents. This work focused on direct contributions. The main objective of this thesis was to assess the current state of the contamination of the marine environment by pharmaceuticals and care products (PPCP) and to evaluate their contribution by the recreational activities and the wastewater releases. In order to assess the impact of bathing activities on marine contamination, occurrence studies of UV filters, substances mainly contained in sunscreens, have been carried out in coastal areas in seawater and in aquatic organisms and more precisely in mussels. The results showed seasonal and intra-day variations in the concentration of UV filters in the coastal environment, confirming that recreational activities contribute to introduce these substances in marine environment. Wastewater treatment plants (WWTP) does not allow the complete elimination of some persistent PPCPs. To evaluate the impact of WWTP effluents on the receiving environment, pharmaceuticals and their conjugated forms were analyzed in domestic and hospital effluents and in WWTP influents and effluents. The low concentrations of conjugated found in WWTP effluents demonstrated that the conjugated were not represented relevant markers of marine contamination by wastewater. However, partially treated wastewater is sometimes discharged directly into the marine environment via marine outfalls, hence the importance of assessing this input. The data on the occurrence of a pharmaceutical molecule, venlafaxine and its transformation products at marine outfall, confirmed the presence of its molecules in the marine environment and the importance of including metabolites in monitoring programs of marine contamination.

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The importance of multiplicity adjustment has gained wide recognition in modern scientific research. Without it, there will be too many spurious results and reproducibility becomes an issue; with it, if overtly conservative, discoveries will be made more difficult. In the current literature on repeated testing of multiple hypotheses, Bonferroni-based methods are still the main vehicle carrying the bulk of multiplicity adjustment. There is room for power improvement by suitably utilizing both hypothesis-wise and analysis- wise dependencies. This research will contribute to the development of a natural group-sequential extension of the classical stepwise multiple testing procedures, such as Dunnett’s stepdown and Hochberg’s step-up procedures. It is shown that the proposed group-sequential procedures strongly control the familywise error rate while being more powerful than the recently developed class of group-sequential Bonferroni-Holm’s procedures. Particularly in this research, a convexity property is discovered for the distribution of the maxima of pairwise null P-values with the underlying test statistics having distributions such as bivariate normal, t, Gamma, F, or Archimedean copulas. Such property renders itself for an immediate use in improving Holm’s procedure by incorporating pairwise dependencies of P-values. The improved Holm’s procedure, as all stepdown multiple testing procedures, can also be naturally extended to group-sequential setting. / Statistics

Modeling of engineering objects with complex heterogeneous material structure at nanoscale level has emerged as an important research problem. In this research, we are interested in multiscale modeling and analysis of mechanical properties of the polymer structures created in the Step and Flash Imprint Lithography (SFIL) process. SFIL is a novel imprint lithography process designed to transfer circuit patterns for fabricating microchips in low-pressure and room-temperature environments. Since the smallest features in SFIL are only a few molecules across, approximating them as a continuum is not completely accurate. Previous research in this subject has dealt with coupling discrete models with continuum hyperelasticity models. The modeling of the post-polymerization step in SFIL involves computing solutions of large nonlinear energy minimization problems with fast spatial variation in material properties. An equilibrium configuration is found by minimizing the energy of this heterogeneous polymeric lattice. Numerical solution of such a molecular statics base model, which is assumed to describe the microstructure completely, is computationally very expensive. This is due to the problem size – on the order of millions of degrees of freedom (DOFs). Rapid variation in material properties, ill-conditioning, nonlinearity, and non-convexity make this problem even more challenging to solve. We devise a method for efficient approximation of the solution. Combining numerical homogenization, adaptive finite element meshes, and goaloriented error estimation, we develop a black-box method for efficient solution of problems with multiple spatial scales. The purpose of this homogenization method is to reduce the number of DOFs, find locally optimal effective material properties, and do goal-oriented mesh refinement. In addition, it smoothes the energy landscape. Traditionally, a finite element mesh is designed after obtaining material properties in different regions. The mesh has to resolve material discontinuities and rapid variations. In our approach, however, we generate a sequence of coarse meshes (possibly 1-irregular), and homogenize material properties on each coarse mesh element using a locally posed constrained convex quadratic optimization problem. This upscaling is done using Moore-Penrose pseudoinverse of the linearized fine-scale element stiffness matrices, and a material independent interpolation operator. This requires solution of a continuous-time Lyapunov equation on each element. Using the adjoint solution, we compute local error estimates in the quantity of interest. The error estimates also drive the automatic mesh adaptivity algorithm. The results show that this method uses orders of magnitude fewer degrees of freedom to give fast and approximate solutions of the original fine-scale problem. Critical to the computational speed of local homogenization is computing Moore-Penrose pseudoinverse of rank-deficient matrices without using Singular Value Decomposition. To this end, we use four algorithms, each having different desirable features. The algorithms are based on Tikhonov regularization, sparse QR factorization, a priori knowledge of the null-space of the matrix, and iterative methods based on proper splittings of matrices. These algorithms can exploit sparsity and thus are fast. Although the homogenization method is designed with a specific molecular statics problem in mind, it is a general method applicable for problems with a given fine mesh that sufficiently resolves the fine-scale material properties. We verify the method using a conductivity problem in 2-D, with chessboard like thermal conductivity pattern, which has a known homogenized conductivity. We analyze other aspects of the homogenization method, for example the choice of norm in which we measure local error, optimum coarse mesh element size for homogenizing SFIL lattices, and the effect of the method chosen for computing the pseudoinverse. / text

This report describes how a new and modern monitoring system is crea- ted for a wind turbine. Elvira Vind AB is a company that has an old operating surveillance system manufactured in 1992. A need has arisen with the owner of the company and are looking for a simple and smooth system that monitors the situation in a wind turbine. Therefore, a system is created that can transmit data wireless- ly through a GSM-module. The system must be able to sense temperature, vibration and sound levels. Also a camera has to take a picture when it de- tects vibration and display the values of the sensors in a web site. The system must also be powered during a power failure, therefore a voltage regulator and a charging circuit was made in the circuit board. The goal of this project is to create a sensor-based monitoring system for a wind turbine and to see the sensor readings wirelessly and displayed in a web site. The report describes how the electronic circuit board has been created and which methods have been used for each sensor in this project. There is also a description of how to use the system for both software and hardware. / Övervakningssystem för vindkraftverk

In this thesis, we address two major problems in Generative Adversarial Networks (GAN), an important sub-field in deep learning. The first problem that we address is the instability in the training process that happens in many real-world problems and the second problem that we address is the lack of a good evaluation metric for the performance of GAN algorithms. To understand and address the first problem, three approaches are developed. Namely, we introduce randomness to the training process; we investigate various normalization methods; most importantly we develop a better parameter initialization strategy to help stabilize training. In the randomness techniques part of the thesis, we developed two randomness approaches, namely the addition of gradient noise and the batch random flipping of the results from the discrimination section of a GAN. In the normalization part of the thesis, we compared the performances of the z-score transform, the min-max normalization, affine transformations and batch normalization. In the most novel and important part of this thesis, we developed techniques to initialize the GAN generator section with parameters that can produce a uniform distribution on the range of the training data. As far as we are aware, this seemingly simple idea has not yet appeared in the extant literature, and the empirical results we obtain on 2-dimensional synthetic data show marked improvement. As to better evaluation metrics, we demonstrate a simple yet effective way to evaluate the effectiveness of the generator using a novel "overlap loss".