Die Produktvisualisierung in AR/VR-Anwendungen erfordert einen weitgehend manuellen Prozess der Datenaufbereitung. Bisherige Veröffentlichungen konzentrieren sich auf die fehlerfreie Triangulation oder Transformation von Produktstrukturdaten und Anzeigeattributen für AR/VR-Anwendungen. Diese Arbeit konzentriert sich auf die Aufbereitung der benötigten Geometriedaten. In diesem Zusammenhang kann durch Automatisierung eine deutliche Aufwandsreduzierung erreicht werden. Die Schritte der Geometrieaufbereitung werden identifiziert und auf ihr Automatisierungspotenzial hin untersucht. Darüber hinaus werden mögliche Kopplungen von Teilschritten diskutiert. Es wird eine Struktur für den Geometrieaufbereitungsprozess vorgeschlagen. Mit diesem strukturierten Prozess wird es möglich, die verfügbare Rechenleistung der Zielplattform bei der Geometrieaufbereitung zu berücksichtigen. Die Anzahl der zu rendernden Objekte, die Qualität der Tesselierung und der Detailgrad können durch die automatisierte Wahl der Transformationsparameter gesteuert werden. Es wird ein Software-Tool vorgestellt, in dem Teile der automatischen Aufbereitung bereits implementiert sind. Nach einer Analyse der Produktstruktur einer CAD-Datei wird die Transformation für jede Komponente (Bauteil oder Baugruppe) durchgeführt. Bisher implementierte Funktionen erlauben z.B. die Auswahl von Komponenten anhand von Filteroptionen, die Transformation im Batch-Modus, das Entfernen bestimmter Details und die Erstellung von UV-Maps. Flexibilität, Transformationsqualität und Zeitersparnis werden beschrieben und diskutiert.

The theme of the work is sentiment analysis, especially in terms of informatics (marginally from a linguistic point of view). The linguistic part discusses the term sentiment and language methods for its analysis, e.g. lemmatization, POS tagging, using the list of stopwords etc. More attention is paid to the structure of the sentiment analyzer which is based on some of the machine learning methods (support vector machines, Naive Bayes and maximum entropy classification). On the basis of the theoretical background, a functional analyzer is projected and implemented. The experiments are focused mainly on comparing the classification methods and on the benefits of using the individual preprocessing methods. The success rate of the constructed classifier reaches up to 84 % in the cross-validation.

This thesis deals with grayscale e-beam lithography and diffractive optical elements fabrication. Three topics are addressed. The first topic is combined grayscale e-beam lithography. The goal of this task is combining exposures performed by two systems with various beam energies. This combined technique leads to a better usage of both systems because various structures can be more easily prepared by one electron beam energy than by the other. The next topic is the optimization of shape borders of exposing structures that are defined by image input. The influence of such optimization on exposure data preparation is evaluated, as well as the exposure time and the change of optical properties of testing structures. The possibility of deep multilevel diffractive optical element fabrication in plexiglass blocks is researched as the third topic. Plexiglass can replace the system of a resist and a substrate. A new approach to writing down the structures by electron beam is presented, minimizing thermal stress on the plexiglass block during the exposure. The writing method also improves the homogeneity of exposed motifs. A method for computing the exposure dose for specific multilevel structures was designed. This method is based on the existing model of proximity effect computation and it minimizes the computing time necessary to obtain the exposure doses.

This master’s thesis describes the design and implementation of the application that created the basis set pieces "puzzle" according to the shape of the folded edges of the original image. This application is developed using Matlab. The work also describes how to create a database of actual pieces of the puzzle composite photo image. Closer was also focused on finding the characteristic section points, their segmentation and appropriate description. There is dismantled procedure for selecting the types of symptoms and their extraction. On the basis of suitably described pieces of segmented parts is designed and implemented the algorithm of comparing and grouping into clusters. Using the proposed method of visualization is then displayed in the resulting composite picture puzzle.

This master’s thesis describes the design and implementation of the application that created the basis set pieces "puzzle" according to the shape of the folded edges of the original image. This application is developed using Matlab. The work also describes how to create a database of actual pieces of the puzzle composite photo image. Closer was also focused on finding the characteristic section points, their segmentation and appropriate description. There is dismantled procedure for selecting the types of symptoms and their extraction. On the basis of suitably described pieces of segmented parts is designed and implemented the algorithm of comparing and grouping into clusters. Using the proposed method of visualization is then displayed in the resulting composite picture puzzle.

This work deals with the prediction of numerical series whose application is suitable for prediction of stock prices. They explain the procedures for analysis and works with price charts. Also explains the methods of machine learning. Knowledge is used to build a program that finds patterns in numerical series for estimation.

The dissertation thesis is focused on research and development in the field of microfabrication by the technology of electron beam lithography. In the first part of this work, the extensive study is conducted in the field of technology of electron beam lithography in terms of physical principles, writing strategies and resist materials. This is followed with description of physical principles of etching for the transfer of relief structures into substrates. The thesis describes innovative techniques in modelling, simulation, data preparation and optimization of manufacturing technology. It brings new possibilities to record deep binary or multilevel microstructures using electron beam lithography, plasma and reactive ion etching technology. Experience and knowledge in the large area of microlithography, plasma and anisotropic wet-etching of silicon have been capitalized to the design process of manufacturing of nano-patterned membranes. It was followed with practical verification and optimization of the microfabrication process.