Molecular dynamics (MD) as a field of molecular modelling has great potential to revolutionize our knowledge and understanding of complex macromolecular structures. Its field of application is huge, reaching from computational chemistry and biology over material sciences to computer-aided drug design. This thesis on one hand provides insights into the underlying physical concepts of molecular dynamics simulations and how they are applied in the MD algorithm, and also briefly illustrates different approaches, as for instance the molecular mechanics and molecular quantum mechanics approaches. On the other hand an own all-atom MD algorithm is implemented utilizing and simplifying a version of the molecular mechanics based AMBER force field published by \big[\cite{cornell1995second}\big]. This simulation algorithm is then used to show by the example of oxytocin how individual energy terms of a force field function. As a result it has been observed, that applying the bond stretch forces alone caused the molecule to be compacted first in certain regions and then as a whole, and that with adding more energy terms the molecule got to move with increasing flexibility.

Regarding the rising amount of legal regulations, businesses should get the opportunity to use software to fulfill their Compliance Management with the usage of compliance pattern. These patterns are used to represent substantive and structural parts of the processes. This means companies can increase their efficiency and react to new regulations quickly to avoid possible violation which can lead to monetary losses or legal consequences. In the literature are many approaches that deal with compliance pattern but currently there does not exist any list with necessary compliance pattern that companies should face at (Delfmann and Hübers, 2015). The following bachelor thesis classifies 80 research contributions regarding their different approaches of compliance pattern. For that a systematic literature review was executed. As a result, the author developed a graphical classification context that provides an overview of connections between different compliance approaches. Furthermore, an appendix with 32 compliance patterns of the analyzed papers was developed that contains real-world patterns with the classification of the previous sections.

Social media platforms such as Twitter or Reddit allow users almost unrestricted access to publish their opinions on recent events or discuss trending topics. While the majority of users approach these platforms innocently, some groups have set their mind on spreading misinformation and influencing or manipulating public opinion. These groups disguise as native users from various countries to spread frequently manufactured articles, strong polarizing opinions in the political spectrum and possibly become providers of hate-speech or extremely political positions. This thesis aims to implement an AutoML pipeline for identifying second language speakers from English social media texts. We investigate style differences of text in different topics and across the platforms Reddit and Twitter, and analyse linguistic features. We employ feature-based models with datasets from Reddit, which include mostly English conversation from European users, and Twitter, which was newly created by collecting English tweets from selected trending topics in different countries. The pipeline classifies language family, native language and origin (Native or non-Native English speakers) of a given textual input. We evaluate the resulting classifications by comparing prediction accuracy, precision and F1 scores of our classification pipeline to traditional machine learning processes. Lastly, we compare the results from each dataset and find differences in language use for topics and platforms. We obtained high prediction accuracy for all categories on the Twitter dataset and observed high variance in features such as average text length especially for Balto-Slavic countries.

Analyse der führenden Interessenverbände in der Eisenbahnbranche in Europa – Struktur, Ziele und Einflussnahme auf verkehrspolitische Maßnahmen

Social Network of Business Objects (SoNBO) is a concept for aggregating information distributed in he-terogeneous system landscapes and making it available via a single user interface. The central idea is to understand company information as a network (graph). There is already a SoNBO-Explorer which integrates the information of a customer relationship management system (CRM system). The challenge in configuring such an application is to identify the corporate network and thus find out how the stored data is linked within the company. A tool that can visualize the corporate network is helpful for this. In this thesis a selfdeveloped tool (SoNBO-Graph-App) is presented as a prototype, which realizes this visualization. With this application the configuration of the network in the SoNBO Explorer consisting of the merged data can be supported by carrying out that configuration on a graphical level. The prototype is connected to two different databases of a Customer Relationship Management (CRM) system and allows the aggregation of these data so that it is displayed as a graph in an overview. This gives the user a better insight and understanding of the relationship between the different data. This work is part of the longterm research project SoNBO, whose goal is a concept for the integration of information from different business application systems.

Abstract This bachelor thesis delivers a comprehensive overview of the topic Internet of Things (IoT). With the help of a first literature review, important characteristics, architectures, and properties have been identified. The main aim of this bachelor thesis is to determine whether the use of IoT in the transport of food, considering the compliance with the cold chain, can provide advantages for companies to reduce food waste. For this purpose, a second literature review has been carried out with food transport systems without the use, as well as with the use of IoT. Based on the literature review, it is possible at the end to determine a theoretical ‘ideal’ system for food transport in refrigerated trucks. The respective used technologies are also mentioned. The findings of several authors have shown that often significant improvements can be achieved in surveillance, transport in general, or traceability of food, and ultimately food waste can be reduced. However, benefits can also be gained using new non-IoT-based technologies. Thus, the main knowledge of this bachelor thesis is that a theoretical ‘ideal’ transport system contains a sensible combination of technologies with and without IoT. This system includes the use of a Wireless Sensor Network (WSN) for real-time food monitoring, as well as an alarm function when the temperature exceeds a maximum. Real-time monitoring with GPS coupled with a monitoring center to prevent traffic jams is another task. Smart and energy-efficient packaging, and finally the use of the new supercooling-technology, make the system significantly more efficient in reducing food waste. These highlights, that when choosing a transport system, which is as efficient and profitable as possible for food with refrigerated transport, companies need not just rely on the use of IoT. On this basis, it is advisable to combine the systems and technologies used so far with IoT in order to avoid as much food waste as possible.

In this thesis, the theory of video seethrough is fundamentally presented on the basis of a panoramic view from several camera frames of different perspectives. Based on this, a system was designed and implemented in which video streams are put together into a panoramic image by perspective distortion. This is then projected onto the inside of a cylinder with the virtual position of the viewer in the middle. Finally, the resulting video panoramas will be displayed in VR glasses. Within the implementation some optimizations are also presented, among others those that make the system real-time capable beyond the task. Furthermore, the developed system will be evaluated and compared with two other methods.

This Bachelor thesis describes the conception, implementation and evaluation of a playful augmented reality application for mobile devices. Building on the ARCore SDK, the game pARcours was developed, where the player can place virtual objects in the real environment to build their own parcours. This must be flown through with a likewise virtual aircraft. The main focus in the implementation of the game was on the interaction with the virtual objects and the collision detection of these with real surfaces. Furthermore, various input methods for building the parcours and controlling the aircrafts were examined. In a final evaluation both the game and the various input methods could be evaluated, as well as ARCore with regard to the development of augmented reality applications.

The goal of this work is the induction, conception, implementation and evaluation of an interactive game application among Android. The game genre of the app is a 2D-Jump ‘n’ Run Side-Scroller, whose graphical implementation is based on the four elements earth, fire, water and wind. The application should have classic functions of a Jump ‘n’ Run game and allow the player to overcome the four game worlds to find the finish. The implementation is based on Unity Engine and Adobe Photoshop. A user test asks basic questions about the application and specific questions about the research question, which are then evaluated. The research question examines the connection between fun factor and color perception while playing the app. Represented by the natural color combinations of the four elements. At the end possibilities for expansion and future prospects will be discussed.

The development of a game engine is considered a non-trivial problem. [3] The architecture of such simulation software must be able to manage large amounts of simulation objects in real-time while dealing with “crosscutting concerns” [3,p. 36] between subsystems. The use of object oriented paradigms to model simulation objects in class hierarchies has been reported as incompatible with constantly changing demands during game development [2, p. 9], resulting in anti-patterns and eventual, messy refactoring.[13] Alternative architectures using data oriented paradigms revolving around object composition and aggregation have been proposed as a result. [13, 9, 1, 11] This thesis describes the development of such an architecture with the explicit goals to be simple, inherently compatible with data oriented design, and to make reasoning about performance characteristics possible. Concepts are formally defined to help analyze the problem and evaluate results. A functional implementation of the architecture is presented together with use cases common to simulation software.