Topic models are a popular tool to extract concepts of large text corpora. These text corpora tend to contain hidden meta groups. The size relation of these groups is frequently imbalanced. Their presence is often ignored when applying a topic model. Therefore, this thesis explores the influence of such imbalanced corpora on topic models. The influence is tested by training LDA on samples with varying size relations. The samples are generated from data sets containing a large group differences i.e language difference and small group differences i.e. political orientation. The predictive performance on those imbalanced corpora is judged using perplexity. The experiments show that the presence of groups in training corpora can influence the prediction performance of LDA. The impact varies due to various factors, including language-specific perplexity scores. The group-related prediction performance changes for groups when varying the relative group sizes. The actual change varies between data sets. LDA is able to distinguish between different latent groups in document corpora if differences between groups are large enough, e.g. for groups with different languages. The proportion of group-specific topics is under-proportional to the share of the group in the corpus and relatively smaller for minorities.

Schrift ist in ihrer Besonderheit verkannt, versteht man sie allein als Mittel zur Stillstellung gesprochener Sprache. Phänomene wie Schriftbildlichkeit, Operativität und die Physiognomie des Schriftbildes machen Schrift zu einem Medium. In der Entwicklung und in der Verwendung von Schriftgebrauchsformen in unterschiedlichen Kontexten werden sowohl die Eigenschaften, die Schriftzeichen mit verbalen Zeichen gemeinsam haben, als auch die Potentiale, die sie mit pikturalen Zeichen gemeinsam haben, genutzt. Daher werden in der vorliegenden Arbeit die Funktionalisierungsmöglichkeiten von Schriftgebrauchsformen vor dem Hintergrund der Symboltheorie Nelson Goodmans vorgestellt. Eine an die ästhetische Theorie angelehnte Herangehensweise ermöglicht es, gerade die bildlichen Aspekte von Schriftformen – die bislang in schrifttheoretischen Arbeiten meist als irrelevant ausgeblendet werden – zu berücksichtigen. Es wird ein dynamischer Kompetenzbegriff in Anlehnung an J.G. Schneider entwickelt, der alle Fähigkeiten umfasst, die benötigt werden, um Schriftgebrauchsformen erfolgversprechend verwenden zu können. Zu diesen Fähigkeiten gehören nicht nur grammatische und orthographische Kompetenz, sondern ebenso Geschmack und die Fähigkeit zur Analogiebildung. An Beispielen verschiedener Schriftverwendungen wird gezeigt, wie unterschiedlich Schriftgebrauchsformen eingesetzt werden können. So wird Schrift als Kulturtechnik darstellbar und mithin verdeutlicht, dass die Art und Weise, wie Menschen ihre Kultur, ihre Welt, aber auch ihre spezifische Umgebung und eigene Identität modellieren, von Schriftverwendungen geprägt und verändert wird.

Modern software projects are composed of several software languages, software technologies and different kind of artifacts. Therefore, the understanding of the software project at hand, including the semantic links between the different parts, becomes a difficult challenge for a developer. One approach to attack this issue is to document the software project with the help of a linguistic architecture. This kind of architecture can be described with the help of the MegaL ontology. A remaining challenge is the creation of it since it requires different kind of skills. Therefore, this paper proposes an approach for the automatic extraction of a linguistic architecture. The open source framework Apache Jena, which is focusing on semantic web technologies like RDF and OWL, is used to define custom rules that are capable to infer new knowledge based on the defined or already extracted RDF triples. The complete approach is tested in a case study on ten different open source projects. The aim of the case study is to extract a linguistic architecture that is describing the use of Hibernate in the selected projects. In the end, the result is evaluated with the help of different metrics. The evaluation is performed with the help of an internal and external approach.

Within aquatic environments sediment water interfaces (SWIs) are the most important areas concerning exchange processes between the water body and the sediment. These spatially restricted regions are characterized by steep biogeochemical gradients that determine the speciation and fate of natural or artificial substances. Apart from biological mediated processes (e.g., burrowing organisms, photosynthesis) the determining exchange processes are diffusion or a colloid-mediated transport. Hence, methods are required enabling to capture the fine scale structures at the boundary layer and to distinguish between the different transport pathways. Regarding emerging substances that will probably reach the aquatic environment engineered nanomaterials (ENMs) are of great concern due to their increased use in many products and applications. Since they are determined based on their size (<100 nm) they include a variety of different materials behaving differently in the environment. Once released, they will inevitable mix with naturally present colloids (< 1 μm) including natural nanomaterials. With regard to existing methodological gaps concerning the characterization of ENMs (as emerging substances) and the investigation of SWIs (as receiving environmental compartments), the aim of this thesis was to develop, validate and apply suitable analytical tools. The challenges were to i) develop methods that enable a high resolution and low-invasive sampling of sediment pore water. To ii) develop routine-suitable methods for the characterization of metal-based engineered nanoparticles and iii) to adopt and optimize size-fractionation approaches for pore water samples of sediment depth profiles to obtain size-related information on element distributions at SWIs. Within the first part, an available microprofiling system was combined with a novel micro sampling system equipped with newly developed sample filtration-probes. The system was thoroughly validated and applied to a freshwater sediment proving the applicability for an automatic sampling of sediment pore waters in parallel to microsensor measurements. Thereby, for the first time multi-element information for sediment depth profiles were obtained at a millimeter scale that could directly be related to simultaneously measured sediment parameters. Due to the expected release of ENMs to the environment the aim was to develop methods that enable the investigation of fate and transport of ENMs at sediment water interfaces. Since standardized approaches are still lacking, methods were developed for the determination of the total mass concentration and the determination of the dissolved fraction of (nano)particle suspensions. Thereby, validated, routine suitable methods were provided enabling for the first time a routine-suitable determination of these two, among the most important properties regarding the analyses of colloidal systems, also urgently needed as a basis for the development of appropriate (future) risk assessments and regulatory frameworks. Based on this methodological basis, approaches were developed enabling to distinguish between dissolved and colloidal fractions of sediment pore waters. This made it possible for the first time to obtain fraction related element information for sediment depth profiles at a millimeter scale, capturing the fine scale structures and distinguishing between diffusion and colloid-mediated transport. In addition to the research oriented parts of this thesis, questions concerning the regulation of ENPs in the case of a release into aquatic systems were addressed in a separate publication (included in the Appendix) discussing the topic against the background of the currently valid German water legislation and the actual state of the research.

Mit der Microsoft Kinect waren die ersten Aufnahmen von synchronisierten Farb- und Tiefendaten (RGB-D) möglich, ohne hohe finanzielle Mittel aufwenden zu müssen und neue Möglichkeiten der Forschung eröffneten sich. Mit fortschreitender Technik sind auch mobile Endgeräte in der Lage, immer mehr zu leisten. Lenovo und Asus bieten die ersten kommerziell erwerblichen Geräte mit RGB D-Wahrnehmung an. Mit integrierten Funktionen der Lokalisierung, Umgebungserkennung und Tiefenwahrnehmung durch die Plattform Tango von Google gibt es bereits die ersten Tests in verschiedenen Bereichen des Rechnersehens z.B. Mapping. In dieser Arbeit wird betrachtet, inwiefern sich ein Tango Gerät für die Objekterkennung eignet. Aus den Ausgangsdaten des Tango Geräts werden RGB D-Daten extrahiert und für die Objekterkennung verarbeitet. Es wird ein Überblick über den aktuellen Stand der Forschung und gewisse Grundlagen bezüglich der Tango Plattform gegeben. Dabei werden existierende Ansätze und Methoden für eine Objekterkennung auf mobilen Endgeräten untersucht. Die Implementation der Erkennung wird anhand einer selbst erstellten Datenbank von RGB-D Bildern gelernt und getestet. Neben der Vorstellung der Ergebnisse werden Verbesserungen und Erweiterungen für die Erkennung vorgeschlagen.