Open Access

Neben dem Verbessern einzelner Methoden der Datenauswertung können Methoden miteinander kombiniert werden, um so umfangreichere und tiefgehendere Analysen durchzuführen. In der vorliegenden Arbeit wird untersucht, welche Mehrwerte sich aus der kombinierten Anwendung von Methode des Process Minings und der Trendanalyse ergeben. Beginnend mit den Methoden des Process Minings, werden die theoretischen Grundlagen beleuchtet. Daran schließt die Vorstellung der Methoden der Trendanalyse und der Korrelationsanalyse an. Nach einer Betrachtung des aktuellen Standes der Technik werden einerseits die Mehrwerte des Einsatzes von Methoden des Process Minings in der Trendanalyse und andererseits die Mehrwerte der Verwendung von Trendanalysemethoden im Process Mining aufgezeigt.

Das Volkswagen Bildungsinstitut ist ein Bildungsdienstleister aus Zwickau und beschäftigt sich mit Maßnahmen der Aus- und Weiterbildung auf den Gebieten der beruflichen Qualifizierung, Personalentwicklung, sowie Organisationsberatung. Durch neue Anwendungsfälle im Unternehmen wurde sich entschieden, die bestehende betriebsinterne Entwicklung um das Themengebiet der Webentwicklung zu erweitern. Die Arbeit beschäftigt sich dabei mit der Auswahl von Webentwicklungsframeworks. Unter diesem Gesichtspunkt werden Kriterien aufgestellt, nach denen die Frameworks Angular und Blazor verglichen und auf Eignung im Volkswagen Bildungsinstitut geprüft werden.

Die Strahlentherapie zählt neben der Chemotherapie und der Chirurgie zu den drei Säulen der Tumortherapie. Bei der Bestrahlungsplanung entstehen mehrere Planvarianten, die auf den Patienten angewendet werden könnten. Das Ziel dieser Arbeit ist es, neben den üblichen Kriterien wie dem Dosis-Volumen-Histogramm, den organspezifischen Dosiswerten und der räumlichen Dosisverteilung, zusätzliche Bewertungskriterien auf der Basis von strahlenbiologischen Konzepten zu untersuchen. Diese Modelle sind in Bestrahlungsplanungssytemen implementiert. Die vorliegende Arbeit befasst sich mit der Theorie der strahlenbiologischen Modelle und mit deren Anwendung in der Therapieplanung anhand ausgewählter Fallbeispiele. Dabei wird gezeigt, dass die strahlenbiologischen Konzepte in mehreren Fällen eine Hilfestellung für die Auswahl des Bestrahlungsplanes sind. In einigen Fällen konnten auch die Grenzen der strahlenbiologischen Modelle aufgezeigt werden. Die implementierten Modelle stellen unter Berücksichtigung der Einschränkungen ein weiteres wertvolles Hilfsmittel zur Bewertung von Bestrahlungsplänen dar.

Natural Language Processing (NLP) is a wide area in computer science and software engineering that finds its application not only in such fields as machine learning or artificial intelligence, but also has very quickly become a very popular solution to various questions and issues raised in the academic field. Those issues include information classification, text analysis, performing a so-called “smart search”, information grouping, providing feedback to academic papers, and many more. The application designed and implemented for this thesis targets solving a similar problem, which is described in details below. The faculty of Physical Engineering and Informatics at the Westsächsische Hochschule Zwickau uses a software tool called “Quest”. The “Quest” serves as an online platform that enables students to ask questions regarding the module material introduced by the teaching professors. The professors can use these questions in order to keep track of the topics rising the most amount of uncertainty, as well as to clarify those questions during the lectures. Since the modules repeat over time, similar or identical questions are frequently asked by students. The current functionality of the “Quest” tool, however, does not provide grouping or clustering questions with a similar content into one category. The reason why this is important is because in the future phases of the improvement of the functionality of the “Quest”, professors want to be able to link similar questions with a learning material or online resources that the students can benefit from. This, however, is only possible when each incoming question is labeled with a certain category, and all previously inputted questions associated with this category become visible through the UI of the tool. That would allow students to review the questions referring to the same category that were previously asked by others, as well as to get access to the study materials or resources associated with that category. The functionality described above would significantly improve the study process and therefore a solution to this problem is needed. One way to solve this issue would be to perform a manual classification of existing questions into associated categories, which given the large size of the question database would be quite time- and effort-consuming. Another option would be to build an application that would be able to analyze the existing dataset of questions and, with the help of the NLP techniques, classify new questions asked by students and identify the similar ones from an existing database. The tool implemented for the above-mentioned purposes aims to serve as text analytics and classification application that would be able to find and categorize similar text and questions provided by students and/or professors at the Westsächsische Hochschule Zwickau. This bachelor thesis demonstrates the process of building a software tool using certain NLP techniques, such as tokenization, model training, categorization, NER (Named Entity Recognition), and POS (Parts of Speech tagging), which are defined and described in Chapter 2: “Literature Overview”. The relevance of these techniques in terms of the classification tool built in the context of this thesis is discussed in the section “Selection of NLP tools and techniques” of the “Methodology” chapter. The aim of this thesis is to describe the methods and software tools used to develop a restful API for text classification, as well as to compare and analyze the effectiveness of two common NLP classifiers – the Naïve Bayes and Logistic Regression (Entropy Model) algorithms.

This work aimed to apply the Floating Film Transfer Method (FTM), developed by Kaneto et.al., as a new way of coating planar and nonplanar substrates with photoresist. Focus laid on the creation of a workflow to coat the substrate and process it by UV-Lithography and Nanoimprint lithography. Conventional coating methods like spin-, spray- or dip coating are well established in today’s industry but are limited in their capabilities to coat curved and structured surfaces. FTM offers the possibility to overcome these limitations. Therefore, two negative resists AR N 4400 and AR N 4600 10 as well as two positive resists AR P 3110 and AZ MIR 701 were drop cast on deionized water. The resist spreads into a thin film that can be transferred to a planar or curved substrate. Profilometric and ellipsometric measurements were conducted to evaluate the topography of the resist. A non-uniform thickness distribution was found depending on the resist and parameters like solid content, water temperature, and the amount of surfactant. UV-Lithography and Nanoimprintl ithography were successfully performed with these films. Resolutions as low as 2,3±0,4 µm were achieved by UV-Lithography of AR P 3110. A periodic pattern with a pitch of 1,51 µm was transferred by thermal nanoimprint lithography to AR N 4400 10. As proof of concept Laser Direct Writing was performed to structure AZ MIR 701coated on a glass vial.