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Algorithmische Komposition
(2018)
Algorithmic composition is an interdisciplinary topic that unites music and science. The computer is able to generate algorithmic music with the aid of a specific algorithm. In this bachelor thesis, algorithmic composition is realized with the biology-inspired algorithms called Lindenmayer-system and cellular automaton. In order to realize the compositions, several techniques are presented as well as implemented and evaluated. Those techniques map the generated data from the algorithms on a meaningful musical result.
The present thesis describes the development of an OpenGL-based tool visualizing cavities of proteins, which can be observed during a static docking simulation. The goal is to achieve knowledge about interactions between proteins and ligands based on information about distances between them. At first chemical basics, which motivate the topic and are important for understanding the topic and the used algorithms, are presented. Furthermore existing software, which deals with similar issues, is described. Next the prerequisites for the development of the program are presented and the tool is described in detail. Concluding the tool is evaluated concerning performance and usage and a summarizing conclusion is given. The program turns out as a helpful tool for current research and a good base for further and deeper research projects.
Companies try to utilise Knowledge Management (KM) to gain more efficiency and effectiveness in business. The major problem is that most of these KM projects are not or rarely based on sustainable analyses or established theories about KM. Often there is a big gap between the expectations and the real outcome of such KM initiatives. So the research question to be answered is: What challenges arise in KM projects, which KM requirements can be derived from them and which recommendations support the goal of meeting the requirements for KM? As theoretical foundation a set of KM frameworks is examined. Subsequently KM challenges from literature are analysed and best practices from case studies are used to provide recommendations for action on this challenges. The main outcome of this thesis is a best practice guideline,which allows Chief Knowledge Officers (CKOs) and KM project managers to examine the challenges mentioned in this thesis closely, and to find a suitable method to master these challenge in an optimal way. This guideline shows that KM can be positively and negatively influenced in a variety of ways. Mastering Knowledge Management (KM) in a company is a big and far-reaching venture and that technology respectively Information Technology (IT) is only a part of the big picture.
In dieser Arbeit werden auf der Basis des aktuellen Forschungsstandes der Politolinguistik die Relevanz und Erklärungsmöglichkeiten politolinguistischer Analysen für das Verständnis der Sprachverwendung und Sprachprägung in der Politik am Beispiel der rechtspopulistischen Rhetorik der Alternative für Deutschland thematisiert. Die Arbeit folgt im Allgemeinen der Fragestellung, inwiefern die Politolinguistik die Sprachverwendung in der Politik und die dort entstehenden, sprachlichen Prägungen lexikalisch analysieren und mithilfe der politolinguistischen Lexikanalyse die durch politische Akteure vermittelten, politischen Intentionen offenlegen kann. Im Besonderen wird sich daran die Frage anschließen, auf welche Weise sich mit den Analysewerkzeugen der politolinguistischen Lexikanalyse das Kurzwahlprogramm der Alternative für Deutschland zur Bundestagswahl 2017 im Hinblick auf ihre rechtspopulistische Rhetorik untersuchen lässt und dortige, lexikalische Prägungsversuche der AfD identifiziert werden können.
Am Schluss der Arbeit steht Erkenntnisfortschritt, der eine deskriptive Erörterung der Relevanz und Möglichkeiten politolinguistischer Lexikanalysen sowie ihrer Werkzeuge für die Untersuchung politischer Sprachverwendung und durch Wortprägungen offenbarter Intentionen beinhaltet, dabei explizit sowohl etablierte als auch neuere Erkenntnisse des Forschungsfeldes miteinbezieht und diese im Hinblick auf die Anwendbarkeit zur Erforschung rechtspopulistischer Rhetorik reflektiert.
Wikipedia is the biggest, free online encyclopaedia that can be expanded by any-one. For the users, who create content on a specific Wikipedia language edition, a social network exists. In this social network users are categorised into different roles. These are normal users, administrators and functional bots. Within the networks, a user can post reviews, suggestions or send simple messages to the "talk page" of another user. Each language in the Wikipedia domain has this type of social network.
In this thesis characteristics of the three different roles are analysed in order to learn how they function in one language network of Wikipedia and apply them to another Wikipedia network to identify bots. Timestamps from created posts are analysed to reveal noticeable characteristics referring to continuous messages, message rates and irregular behaviour of a user are discovered. Through this process we show that there exist differences between the roles for the mentioned characteristics.
Entwicklung eines Social Collaboration Analytics Dashboard-Prototyps für Beiträge von UniConnect
(2018)
Seit der vergangenen Dekade steigt die Nutzung von sogenannten Enterprise Collaboration Systems (ECS) in Unternehmen. Diese versprechen sich mit der Einführung eines solchen zur Gattung der Social Software gehörenden Kollaborationssystems, die menschliche Kommunikation und Kooperation der eigenen Mitarbeiter zu verbessern. Durch die Integration von Funktionen, wie sie aus Social Media bekannt sind, entstehen große Mengen an Daten. Darunter befinden sich zu einem erheblichen Teil textuelle Daten, die beispielsweise mit Funktionen wie Blogs, Foren, Statusaktualisierungen oder Wikis erstellt wurden. Diese in unstrukturierter Form vorliegenden Daten bieten ein großes Potenzial zur Analyse und Auswertung mittels Methoden des Text Mining. Die Forschung belegt dazu jedoch, dass Umsetzungen dieser Art momentan nicht gebräuchlich sind. Aus diesem Grund widmet sich die vorliegende Arbeit diesem Mangel. Ziel ist die Erstellung eines Dashboard-Prototyps, der sich im Rahmen von Social Collaboration Analytics (SCA) mit der Auswertung von textuellen Daten befasst. Analyseziel ist die Identifikation von populären Themen, die innerhalb von Communities oder communityübergreifend von den Plattformnutzern in den von ihnen erstellten Beiträgen aufgegriffen werden. Als Datenquelle wurde das auf IBM Connections aufbauende ECS UniConnect ausgewählt. Dieses wird vom University Competence Center for Collaboration Technologies (UCT) an der Universität Koblenz-Landau betrieben. Grundlegend für die korrekte Funktionsweise des Dashboards sind mehrere Java-Klassen, deren Umsetzungen auf verschiedenen Methoden des Text Mining basieren. Vermittelt werden die Analyseergebnisse im Dashboard durch verschiedene Diagrammarten, Wordclouds und Tabellen.
Photo realistic rendering of fur is a common problem in computer graphics and is often needed in animation films. This work presents two illumination models, originally presented for human hair rendering. The first model is from Marschner et al. presented in 2003, which is the basis of many other models. The second model is from d’Eon et al., which was presented in 2011. Both models are implemented into a path tracer, which simulates global illumination. The special features of fur fibers in contrast to human hair fibers will be shown and an explanation, to why both models can also be used for fur rendering, will be given. The main point of interest is a realistic visualization of fur. In addition to that the performance of both models will be compared and a suggestion to improve the performance will be given and evaluated in form of the use of a cylindrical intersection object for path tracing.
This Bachelor thesis illustrates the connection between the technologies Augmented and Virtual Reality and creates an expedient interdependency of the two forms of presentation. For this purpose, an application in the area of interior design has been implemented, where designing a room can be made more intuitive by using Augmented Reality, as it provides a realistic impression of the planned apartment with a Virtual Reality simulation. Based on the relevant knowledge, a project-concept has been drafted and realized by using several development systems. During a series of tests this implementation has been evaluated and subsequently optimized. The result confirms the assumption, that Augmented and Virtual Reality with their strengths can be combined to an evident solution. This thesis is relevant for computer science students as well as for people interested in innovative solutions.
During the last couple of years the extension of the internet into the real world, also referred to as the Internet of Things (IoT), was positively affected by an ongoing digitalization (Mattern and Floerkemeier, 2010; Evans, 2013). Furthermore, one of the most active IoT domains is the personal health ecosystem (Steele and Clarke, 2013). However, this thesis proposes a gamification framework which is supported and enabled by IoT to bring personal health and IoT together in the context of health-insurances. By examining gamification approaches and identifying the role of IoT in such, a conceptual model of a gamification approach was created which indicates where and how IoT is ap-plicable to it. Hence, IoT acts as enabler and furthermore as enhancer of gamified activities. Especial-ly the necessity of wearable devices was highlighted. A stakeholder analysis shed light on respective benefits which concluded in the outcome, that IoT enabled two paradigm shifts for both, the insur-ance and their customer. While taking the results of the examination and the stakeholder analysis as input, the previously made insights were used to develop an IoT supported gamification framework. The framework includes a multi-level structure which is meant to guide through the process of creat-ing an approach but also to analyze already existing approaches. Additionally, the developed frame-work was instantiated based on the application Pokémon Go to identify occurring issues and explain why it failed to retain their customer in the long term. The thesis provides a foundation on which fur-ther context related research can be orientated.
In dieser Forschungsarbeit wird eine Methode zur anwendungsbasierten Verknüpfung von Anforde-rungen und Enterprise Collaboration Softwarekompenten vorgestellt. Basierend auf dem etablierten IRESS Modell wird dabei ein praxistaugliches Mappingschema entwickelt, welches Use Cases über Kol-laborationsszenarien, Collaborative Features und Softwarekomponenten mit ECS verbindet. Somit las-sen sich Anforderungen von Unterhemen in Form von Use Cases und Kollaborationsszenarien model-lieren und anschließend über das Mappingschema mit konkreten ECS verbinden. Zusätzlich wird eine Methodik zur Identifikation von in Softwarekomponenten enthaltenen Collaborative Features vorge-stellt und exemplarisch angewandt.
Anschließend wird ein Konzept für eine Webapplikation entworfen, welches das vorgestellte Mapping automatisiert durchführt, und somit nach Eingabe der Anforderungen in Form vom Use Cases oder Kol-laborationsszenarien, die ECS ausgibt, die eben diese Anforderungen unterstützen.